02971nas a2200373 4500008004100000022001400041245011900055210006900174260001300243300001000256490000800266520185400274653003202128653000902160653004402169653004502213653001902258653001702277653003002294653001102324653001802335653001102353653000902364653002602373653001502399100002302414700002102437700001902458700002202477700002402499700001902523700002002542856003502562 2004 eng d a1097-674400aTime trends in the use of beta-blockers and other pharmacotherapies in older adults with congestive heart failure.0 aTime trends in the use of betablockers and other pharmacotherapi c2004 Oct a710-70 v1483 a
BACKGROUND: Evidence supporting pharmacotherapy of congestive heart failure (CHF) has grown substantially over the past decade and includes large, placebo-controlled trials with mortality end points. We describe beta-blocker and other medication temporal treatment trends of CHF in the Cardiovascular Health Study, a community-based cohort study of 5888 adults > or =65 years of age.
METHODS: Prescription medication data were collected from hospital discharge summaries for incident CHF events and at in-study annual clinic visits for prevalent CHF cases from 1989 to 2000. Change in use of agents over time was estimated by using generalized estimating equations while adjusting for potential confounding factors of age, sex, race, and cardiovascular and pulmonary comorbidities.
RESULTS: Among 1033 incident CHF events, beta-blocker use after diagnosis increased an average of 2.4 percentage points annually (95% CI, 1.5 to 3.4 points) from 1989 to 2000. The increasing trend was consistent throughout follow-up. Among participants with coronary disease and/or hypertension and among those with low ejection fractions (<45%), beta-blocker use remained flat from 1989 to 1994 and increased 4.7 points annually (2.5 to 6.9) and 10.0 points annually (6.1 to 13.8), respectively, from 1995 to 2000. Among participants without coronary disease or hypertension, there was no overall increase in use. Use of renin-angiotensin system inhibitors increased 2.3 points annually (1.0 to 3.5), digoxin use decreased 2.4 points annually (-3.6 to -1.1), and loop diuretic use remained flat between 1989 and 2000. In general, treatment trends were similar for prevalent CHF.
CONCLUSIONS: Treatment of CHF has changed gradually in the 1990s and may in part reflect the influence of CHF clinical trial evidence.
10aAdrenergic beta-Antagonists10aAged10aAngiotensin II Type 1 Receptor Blockers10aAngiotensin-Converting Enzyme Inhibitors10aCohort Studies10aDrug Therapy10aDrug Therapy, Combination10aFemale10aHeart Failure10aHumans10aMale10aMultivariate Analysis10aPrevalence1 aSmith, Nicholas, L1 aChan, Jeannie, D1 aRea, Thomas, D1 aWiggins, Kerri, L1 aGottdiener, John, S1 aLumley, Thomas1 aPsaty, Bruce, M uhttps://chs-nhlbi.org/node/80705209nas a2201129 4500008004100000022001400041245009100055210006900146260001600215300001300231490000600244520200900250653001502259653001002274653000902284653002202293653002802315653001002343653002102353653003202374653003202406653003102438653003102469653001902500653004002519653001102559653001702570653003402587653001102621653000902632653002702641653002102668653001602689653003602705653002002741653001602761100001802777700001702795700001702812700002302829700002502852700002002877700002002897700001902917700001802936700002402954700002702978700001703005700001703022700001903039700002803058700002603086700001903112700002703131700002303158700001503181700002003196700002603216700002203242700001903264700002203283700002003305700002303325700002403348700001903372700002203391700002203413700002003435700001603455700002203471700001803493700002603511700002103537700002203558700002403580700002003604700001703624700002203641700002303663700002803686700001703714700001903731700001603750700002703766700002103793700002303814700002203837700002203859700002103881700001903902700002403921700002403945700002803969700001803997710002804015856003604043 2010 eng d a1553-740400aFour novel Loci (19q13, 6q24, 12q24, and 5q14) influence the microcirculation in vivo.0 aFour novel Loci 19q13 6q24 12q24 and 5q14 influence the microcir c2010 Oct 28 ae10011840 v63 aThere is increasing evidence that the microcirculation plays an important role in the pathogenesis of cardiovascular diseases. Changes in retinal vascular caliber reflect early microvascular disease and predict incident cardiovascular events. We performed a genome-wide association study to identify genetic variants associated with retinal vascular caliber. We analyzed data from four population-based discovery cohorts with 15,358 unrelated Caucasian individuals, who are members of the Cohort for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and replicated findings in four independent Caucasian cohorts (n = 6,652). All participants had retinal photography and retinal arteriolar and venular caliber measured from computer software. In the discovery cohorts, 179 single nucleotide polymorphisms (SNP) spread across five loci were significantly associated (p<5.0×10(-8)) with retinal venular caliber, but none showed association with arteriolar caliber. Collectively, these five loci explain 1.0%-3.2% of the variation in retinal venular caliber. Four out of these five loci were confirmed in independent replication samples. In the combined analyses, the top SNPs at each locus were: rs2287921 (19q13; p = 1.61×10(-25), within the RASIP1 locus), rs225717 (6q24; p = 1.25×10(-16), adjacent to the VTA1 and NMBR loci), rs10774625 (12q24; p = 2.15×10(-13), in the region of ATXN2,SH2B3 and PTPN11 loci), and rs17421627 (5q14; p = 7.32×10(-16), adjacent to the MEF2C locus). In two independent samples, locus 12q24 was also associated with coronary heart disease and hypertension. Our population-based genome-wide association study demonstrates four novel loci associated with retinal venular caliber, an endophenotype of the microcirculation associated with clinical cardiovascular disease. These data provide further insights into the contribution and biological mechanisms of microcirculatory changes that underlie cardiovascular disease.
10aAdolescent10aAdult10aAged10aAged, 80 and over10aCardiovascular Diseases10aChild10aChild, Preschool10aChromosomes, Human, Pair 1210aChromosomes, Human, Pair 1910aChromosomes, Human, Pair 510aChromosomes, Human, Pair 610aCohort Studies10aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenome-Wide Association Study10aHumans10aMale10aMeta-Analysis as Topic10aMicrocirculation10aMiddle Aged10aPolymorphism, Single Nucleotide10aRetinal Vessels10aYoung Adult1 aIkram, Kamran1 aSim, Xueling1 aXueling, Sim1 aJensen, Richard, A1 aCotch, Mary, Frances1 aHewitt, Alex, W1 aIkram, Arfan, M1 aWang, Jie, Jin1 aKlein, Ronald1 aKlein, Barbara, E K1 aBreteler, Monique, M B1 aCheung, Ning1 aLiew, Gerald1 aMitchell, Paul1 aUitterlinden, André, G1 aRivadeneira, Fernando1 aHofman, Albert1 ade Jong, Paulus, T V M1 aDuijn, Cornelia, M1 aKao, Linda1 aCheng, Ching-Yu1 aSmith, Albert, Vernon1 aGlazer, Nicole, L1 aLumley, Thomas1 aMcKnight, Barbara1 aPsaty, Bruce, M1 aJonasson, Fridbert1 aEiriksdottir, Gudny1 aAspelund, Thor1 aHarris, Tamara, B1 aLauner, Lenore, J1 aTaylor, Kent, D1 aLi, Xiaohui1 aIyengar, Sudha, K1 aXi, Quansheng1 aSivakumaran, Theru, A1 aMackey, David, A1 aMacgregor, Stuart1 aMartin, Nicholas, G1 aYoung, Terri, L1 aBis, Josh, C1 aWiggins, Kerri, L1 aHeckbert, Susan, R1 aHammond, Christopher, J1 aAndrew, Toby1 aFahy, Samantha1 aAttia, John1 aHolliday, Elizabeth, G1 aScott, Rodney, J1 aIslam, F, M Amirul1 aRotter, Jerome, I1 aMcAuley, Annie, K1 aBoerwinkle, Eric1 aTai, Shyong, E1 aGudnason, Vilmundur1 aSiscovick, David, S1 aVingerling, Johannes, R1 aWong, Tien, Y1 aGlobal BPgen Consortium uhttps://chs-nhlbi.org/node/124304638nas a2200901 4500008004100000022001400041245020700055210006900262260001600331300001200347490000800359520199800367653001002365653001502375653001602390653001102406653003402417653001502451653001102466653000902477653001602486653001402502653003602516653001502552653002602567100002302593700002002616700001902636700002302655700001702678700002002695700002202715700001602737700002502753700001902778700002502797700001602822700001902838700001602857700002702873700002202900700002002922700002302942700002202965700002302987700002203010700002103032700002303053700002103076700002203097700002803119700001803147700002003165700002003185700002103205700001803226700002203244700002203266700002103288700001903309700002103328700002403349700001903373700002003392700001903412700002103431700002203452700002403474700002003498700002103518700002003539700001903559700003003578700001803608700003003626710004403656856003603700 2010 eng d a1524-453900aNovel associations of multiple genetic loci with plasma levels of factor VII, factor VIII, and von Willebrand factor: The CHARGE (Cohorts for Heart and Aging Research in Genome Epidemiology) Consortium.0 aNovel associations of multiple genetic loci with plasma levels o c2010 Mar 30 a1382-920 v1213 aBACKGROUND: Plasma levels of coagulation factors VII (FVII), VIII (FVIII), and von Willebrand factor (vWF) influence risk of hemorrhage and thrombosis. We conducted genome-wide association studies to identify new loci associated with plasma levels.
METHODS AND RESULTS: The setting of the study included 5 community-based studies for discovery comprising 23 608 European-ancestry participants: Atherosclerosis Risk In Communities Study, Cardiovascular Health Study, British 1958 Birth Cohort, Framingham Heart Study, and Rotterdam Study. All subjects had genome-wide single-nucleotide polymorphism (SNP) scans and at least 1 phenotype measured: FVII activity/antigen, FVIII activity, and vWF antigen. Each study used its genotype data to impute to HapMap SNPs and independently conducted association analyses of hemostasis measures using an additive genetic model. Study findings were combined by meta-analysis. Replication was conducted in 7604 participants not in the discovery cohort. For FVII, 305 SNPs exceeded the genome-wide significance threshold of 5.0x10(-8) and comprised 5 loci on 5 chromosomes: 2p23 (smallest P value 6.2x10(-24)), 4q25 (3.6x10(-12)), 11q12 (2.0x10(-10)), 13q34 (9.0x10(-259)), and 20q11.2 (5.7x10(-37)). Loci were within or near genes, including 4 new candidate genes and F7 (13q34). For vWF, 400 SNPs exceeded the threshold and marked 8 loci on 6 chromosomes: 6q24 (1.2x10(-22)), 8p21 (1.3x10(-16)), 9q34 (<5.0x10(-324)), 12p13 (1.7x10(-32)), 12q23 (7.3x10(-10)), 12q24.3 (3.8x10(-11)), 14q32 (2.3x10(-10)), and 19p13.2 (1.3x10(-9)). All loci were within genes, including 6 new candidate genes, as well as ABO (9q34) and VWF (12p13). For FVIII, 5 loci were identified and overlapped vWF findings. Nine of the 10 new findings were replicated.
CONCLUSIONS: New genetic associations were discovered outside previously known biological pathways and may point to novel prevention and treatment targets of hemostasis disorders.
10aAdult10aFactor VII10aFactor VIII10aFemale10aGenome-Wide Association Study10aHemostasis10aHumans10aMale10aMiddle Aged10aPhenotype10aPolymorphism, Single Nucleotide10aThrombosis10avon Willebrand Factor1 aSmith, Nicholas, L1 aChen, Ming-Huei1 aDehghan, Abbas1 aStrachan, David, P1 aBasu, Saonli1 aSoranzo, Nicole1 aHayward, Caroline1 aRudan, Igor1 aSabater-Lleal, Maria1 aBis, Joshua, C1 ade Maat, Moniek, P M1 aRumley, Ann1 aKong, Xiaoxiao1 aYang, Qiong1 aWilliams, Frances, M K1 aVitart, Veronique1 aCampbell, Harry1 aMälarstig, Anders1 aWiggins, Kerri, L1 aDuijn, Cornelia, M1 aMcArdle, Wendy, L1 aPankow, James, S1 aJohnson, Andrew, D1 aSilveira, Angela1 aMcKnight, Barbara1 aUitterlinden, André, G1 aAleksic, Nena1 aMeigs, James, B1 aPeters, Annette1 aKoenig, Wolfgang1 aCushman, Mary1 aKathiresan, Sekar1 aRotter, Jerome, I1 aBovill, Edwin, G1 aHofman, Albert1 aBoerwinkle, Eric1 aTofler, Geoffrey, H1 aPeden, John, F1 aPsaty, Bruce, M1 aLeebeek, Frank1 aFolsom, Aaron, R1 aLarson, Martin, G1 aSpector, Timothy, D1 aWright, Alan, F1 aWilson, James, F1 aHamsten, Anders1 aLumley, Thomas1 aWitteman, Jacqueline, C M1 aTang, Weihong1 aO'Donnell, Christopher, J1 aWellcome Trust Case Control Consortium; 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Over one billion people worldwide have hypertension (≥140 mm Hg systolic blood pressure or ≥90 mm Hg diastolic blood pressure). Even small increments in blood pressure are associated with an increased risk of cardiovascular events. This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention.
10aAfrica10aAsia10aBlood Pressure10aCardiovascular Diseases10aCoronary Artery Disease10aEurope10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aHypertension10aKidney Diseases10aPolymorphism, Single Nucleotide10aStroke1 aInternational Consortium for Blood Pressure Genome-Wide Association Studies1 aEhret, Georg, B1 aMunroe, Patricia, B1 aRice, Kenneth, M1 aBochud, Murielle1 aJohnson, Andrew, D1 aChasman, Daniel, I1 aSmith, Albert, V1 aTobin, Martin, D1 aVerwoert, Germaine, C1 aHwang, Shih-Jen1 aPihur, Vasyl1 aVollenweider, Peter1 aO'Reilly, Paul, F1 aAmin, Najaf1 aBragg-Gresham, Jennifer, L1 aTeumer, Alexander1 aGlazer, Nicole, L1 aLauner, Lenore1 aZhao, Jing Hua1 aAulchenko, Yurii1 aHeath, Simon1 aSõber, Siim1 aParsa, Afshin1 aLuan, Jian'an1 aArora, Pankaj1 aDehghan, Abbas1 aZhang, Feng1 aLucas, Gavin1 aHicks, Andrew, A1 aJackson, Anne, U1 aPeden, John, F1 aTanaka, Toshiko1 aWild, Sarah, H1 aRudan, Igor1 aIgl, Wilmar1 aMilaneschi, Yuri1 aParker, Alex, N1 aFava, Cristiano1 aChambers, John, C1 aFox, Ervin, R1 aKumari, Meena1 aGo, Min Jin1 aHarst, Pim1 aKao, Wen Hong Linda1 aSjögren, Marketa1 aVinay, D G1 aAlexander, Myriam1 aTabara, Yasuharu1 aShaw-Hawkins, Sue1 aWhincup, Peter, H1 aLiu, Yongmei1 aShi, Gang1 aKuusisto, Johanna1 aTayo, Bamidele1 aSeielstad, Mark1 aSim, Xueling1 aNguyen, Khanh-Dung Hoang1 aLehtimäki, Terho1 aMatullo, Giuseppe1 aWu, Ying1 aGaunt, Tom, R1 aOnland-Moret, Charlotte, N1 aCooper, Matthew, N1 aPlatou, Carl, G P1 aOrg, Elin1 aHardy, Rebecca1 aDahgam, Santosh1 aPalmen, Jutta1 aVitart, Veronique1 aBraund, Peter, S1 aKuznetsova, Tatiana1 aUiterwaal, Cuno, S P M1 aAdeyemo, Adebowale1 aPalmas, Walter1 aCampbell, Harry1 aLudwig, Barbara1 aTomaszewski, Maciej1 aTzoulaki, Ioanna1 aPalmer, Nicholette, D1 aAspelund, Thor1 aGarcia, Melissa1 aChang, Yen-Pei, C1 aO'Connell, Jeffrey, R1 aSteinle, Nanette, I1 aGrobbee, Diederick, E1 aArking, Dan, E1 aKardia, Sharon, L1 aMorrison, Alanna, C1 aHernandez, Dena1 aNajjar, Samer1 aMcArdle, Wendy, L1 aHadley, David1 aBrown, Morris, J1 aConnell, John, M1 aHingorani, Aroon, D1 aDay, Ian, N M1 aLawlor, Debbie, A1 aBeilby, John, P1 aLawrence, Robert, W1 aClarke, Robert1 aHopewell, Jemma, C1 aOngen, Halit1 aDreisbach, Albert, W1 aLi, Yali1 aYoung, Hunter, J1 aBis, Joshua, C1 aKähönen, Mika1 aViikari, Jorma1 aAdair, Linda, S1 aLee, Nanette, R1 aChen, Ming-Huei1 aOlden, Matthias1 aPattaro, Cristian1 aBolton, Judith Hoffman, A1 aKöttgen, Anna1 aBergmann, Sven1 aMooser, Vincent1 aChaturvedi, Nish1 aFrayling, Timothy, M1 aIslam, Muhammad1 aJafar, Tazeen, H1 aErdmann, Jeanette1 aKulkarni, Smita, R1 aBornstein, Stefan, R1 aGrässler, Jürgen1 aGroop, Leif1 aVoight, Benjamin, F1 aKettunen, Johannes1 aHoward, Philip1 aTaylor, Andrew1 aGuarrera, Simonetta1 aRicceri, Fulvio1 aEmilsson, Valur1 aPlump, Andrew1 aBarroso, Inês1 aKhaw, Kay-Tee1 aWeder, Alan, B1 aHunt, Steven, C1 aSun, Yan, V1 aBergman, Richard, N1 aCollins, Francis, S1 aBonnycastle, Lori, L1 aScott, Laura, J1 aStringham, Heather, M1 aPeltonen, Leena1 aPerola, Markus1 aVartiainen, Erkki1 aBrand, Stefan-Martin1 aStaessen, Jan, A1 aWang, Thomas, J1 aBurton, Paul, R1 aArtigas, Maria, Soler1 aDong, Yanbin1 aSnieder, Harold1 aWang, Xiaoling1 aZhu, Haidong1 aLohman, Kurt, K1 aRudock, Megan, E1 aHeckbert, Susan, R1 aSmith, Nicholas, L1 aWiggins, Kerri, L1 aDoumatey, Ayo1 aShriner, Daniel1 aVeldre, Gudrun1 aViigimaa, Margus1 aKinra, Sanjay1 aPrabhakaran, Dorairaj1 aTripathy, Vikal1 aLangefeld, Carl, D1 aRosengren, Annika1 aThelle, Dag, S1 aCorsi, Anna Maria1 aSingleton, Andrew1 aForrester, Terrence1 aHilton, Gina1 aMcKenzie, Colin, A1 aSalako, Tunde1 aIwai, Naoharu1 aKita, Yoshikuni1 aOgihara, Toshio1 aOhkubo, Takayoshi1 aOkamura, Tomonori1 aUeshima, Hirotsugu1 aUmemura, Satoshi1 aEyheramendy, Susana1 aMeitinger, Thomas1 aWichmann, H-Erich1 aCho, Yoon Shin1 aKim, Hyung-Lae1 aLee, Jong-Young1 aScott, James1 aSehmi, Joban, S1 aZhang, Weihua1 aHedblad, Bo1 aNilsson, Peter1 aSmith, George Davey1 aWong, Andrew1 aNarisu, Narisu1 aStančáková, Alena1 aRaffel, Leslie, J1 aYao, Jie1 aKathiresan, Sekar1 aO'Donnell, Christopher, J1 aSchwartz, Stephen, M1 aIkram, Arfan, M1 aLongstreth, W T1 aMosley, Thomas, H1 aSeshadri, Sudha1 aShrine, Nick, R G1 aWain, Louise, V1 aMorken, Mario, A1 aSwift, Amy, J1 aLaitinen, Jaana1 aProkopenko, Inga1 aZitting, Paavo1 aCooper, Jackie, A1 aHumphries, Steve, E1 aDanesh, John1 aRasheed, Asif1 aGoel, Anuj1 aHamsten, Anders1 aWatkins, Hugh1 aBakker, Stephan, J L1 aGilst, Wiek, H1 aJanipalli, Charles, S1 aMani, Radha, K1 aYajnik, Chittaranjan, S1 aHofman, Albert1 aMattace-Raso, Francesco, U S1 aOostra, Ben, A1 aDemirkan, Ayse1 aIsaacs, Aaron1 aRivadeneira, Fernando1 aLakatta, Edward, G1 aOrrù, Marco1 aScuteri, Angelo1 aAla-Korpela, Mika1 aKangas, Antti, J1 aLyytikäinen, Leo-Pekka1 aSoininen, Pasi1 aTukiainen, Taru1 aWürtz, Peter1 aOng, Rick Twee-Hee1 aDörr, Marcus1 aKroemer, Heyo, K1 aVölker, Uwe1 aVölzke, Henry1 aGalan, Pilar1 aHercberg, Serge1 aLathrop, Mark1 aZelenika, Diana1 aDeloukas, Panos1 aMangino, Massimo1 aSpector, Tim, D1 aZhai, Guangju1 aMeschia, James, F1 aNalls, Michael, A1 aSharma, Pankaj1 aTerzic, Janos1 aKumar, Kranthi, M V1 aDenniff, Matthew1 aZukowska-Szczechowska, Ewa1 aWagenknecht, Lynne, E1 aFowkes, Gerald, F R1 aCharchar, Fadi, J1 aSchwarz, Peter, E H1 aHayward, Caroline1 aGuo, Xiuqing1 aRotimi, Charles1 aBots, Michiel, L1 aBrand, Eva1 aSamani, Nilesh, J1 aPolasek, Ozren1 aTalmud, Philippa, J1 aNyberg, Fredrik1 aKuh, Diana1 aLaan, Maris1 aHveem, Kristian1 aPalmer, Lyle, J1 aSchouw, Yvonne, T1 aCasas, Juan, P1 aMohlke, Karen, L1 aVineis, Paolo1 aRaitakari, Olli1 aGanesh, Santhi, K1 aWong, Tien, Y1 aTai, Shyong, E1 aCooper, Richard, S1 aLaakso, Markku1 aRao, Dabeeru, C1 aHarris, Tamara, B1 aMorris, Richard, W1 aDominiczak, Anna, F1 aKivimaki, Mika1 aMarmot, Michael, G1 aMiki, Tetsuro1 aSaleheen, Danish1 aChandak, Giriraj, R1 aCoresh, Josef1 aNavis, Gerjan1 aSalomaa, Veikko1 aHan, Bok-Ghee1 aZhu, Xiaofeng1 aKooner, Jaspal, S1 aMelander, Olle1 aRidker, Paul, M1 aBandinelli, Stefania1 aGyllensten, Ulf, B1 aWright, Alan, F1 aWilson, James, F1 aFerrucci, Luigi1 aFarrall, Martin1 aTuomilehto, Jaakko1 aPramstaller, Peter, P1 aElosua, Roberto1 aSoranzo, Nicole1 aSijbrands, Eric, J G1 aAltshuler, David1 aLoos, Ruth, J F1 aShuldiner, Alan, R1 aGieger, Christian1 aMeneton, Pierre1 aUitterlinden, André, G1 aWareham, Nicholas, J1 aGudnason, Vilmundur1 aRotter, Jerome, I1 aRettig, Rainer1 aUda, Manuela1 aStrachan, David, P1 aWitteman, Jacqueline, C M1 aHartikainen, Anna-Liisa1 aBeckmann, Jacques, S1 aBoerwinkle, Eric1 aVasan, Ramachandran, S1 aBoehnke, Michael1 aLarson, Martin, G1 aJarvelin, Marjo-Riitta1 aPsaty, Bruce, M1 aAbecasis, Goncalo, R1 aChakravarti, Aravinda1 aElliott, Paul1 aDuijn, Cornelia, M1 aNewton-Cheh, Christopher1 aLevy, Daniel1 aCaulfield, Mark, J1 aJohnson, Toby1 aCARDIoGRAM consortium1 aCKDGen Consortium1 aKidneyGen Consortium1 aEchoGen consortium1 aCHARGE-HF consortium uhttps://chs-nhlbi.org/node/132507496nas a2202305 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2011 eng d a1476-468700aNew gene functions in megakaryopoiesis and platelet formation.0 aNew gene functions in megakaryopoiesis and platelet formation c2011 Nov 30 a201-80 v4803 aPlatelets are the second most abundant cell type in blood and are essential for maintaining haemostasis. Their count and volume are tightly controlled within narrow physiological ranges, but there is only limited understanding of the molecular processes controlling both traits. Here we carried out a high-powered meta-analysis of genome-wide association studies (GWAS) in up to 66,867 individuals of European ancestry, followed by extensive biological and functional assessment. We identified 68 genomic loci reliably associated with platelet count and volume mapping to established and putative novel regulators of megakaryopoiesis and platelet formation. These genes show megakaryocyte-specific gene expression patterns and extensive network connectivity. Using gene silencing in Danio rerio and Drosophila melanogaster, we identified 11 of the genes as novel regulators of blood cell formation. Taken together, our findings advance understanding of novel gene functions controlling fate-determining events during megakaryopoiesis and platelet formation, providing a new example of successful translation of GWAS to function.
10aAnimals10aBlood Platelets10aCell Size10aDrosophila melanogaster10aDrosophila Proteins10aEurope10aGene Expression Profiling10aGene Silencing10aGenome, Human10aGenome-Wide Association Study10aHematopoiesis10aHumans10aMegakaryocytes10aPlatelet Count10aProtein Interaction Maps10aTranscription, Genetic10aZebrafish10aZebrafish Proteins1 aGieger, Christian1 aRadhakrishnan, Aparna1 aCvejic, Ana1 aTang, Weihong1 aPorcu, Eleonora1 aPistis, Giorgio1 aSerbanovic-Canic, Jovana1 aElling, Ulrich1 aGoodall, Alison, H1 aLabrune, Yann1 aLopez, Lorna, M1 aMägi, Reedik1 aMeacham, Stuart1 aOkada, Yukinori1 aPirastu, Nicola1 aSorice, Rossella1 aTeumer, Alexander1 aVoss, Katrin1 aZhang, Weihua1 aRamirez-Solis, Ramiro1 aBis, Joshua, C1 aEllinghaus, David1 aGögele, Martin1 aHottenga, Jouke-Jan1 aLangenberg, Claudia1 aKovacs, Peter1 aO'Reilly, Paul, F1 aShin, So-Youn1 aEsko, Tõnu1 aHartiala, Jaana1 aKanoni, Stavroula1 aMurgia, Federico1 aParsa, Afshin1 aStephens, Jonathan1 aHarst, Pim1 avan der Schoot, Ellen1 aAllayee, Hooman1 aAttwood, Antony1 aBalkau, Beverley1 aBastardot, François1 aBasu, Saonli1 aBaumeister, Sebastian, E1 aBiino, Ginevra1 aBomba, Lorenzo1 aBonnefond, Amélie1 aCambien, Francois1 aChambers, John, C1 aCucca, Francesco1 aD'Adamo, Pio1 aDavies, Gail1 ade Boer, Rudolf, A1 aGeus, Eco, J C1 aDöring, Angela1 aElliott, Paul1 aErdmann, Jeanette1 aEvans, David, M1 aFalchi, Mario1 aFeng, Wei1 aFolsom, Aaron, R1 aFrazer, Ian, H1 aGibson, Quince, D1 aGlazer, Nicole, L1 aHammond, Chris1 aHartikainen, Anna-Liisa1 aHeckbert, Susan, R1 aHengstenberg, Christian1 aHersch, Micha1 aIllig, Thomas1 aLoos, Ruth, J F1 aJolley, Jennifer1 aKhaw, Kay, Tee1 aKuhnel, Brigitte1 aKyrtsonis, Marie-Christine1 aLagou, Vasiliki1 aLloyd-Jones, Heather1 aLumley, Thomas1 aMangino, Massimo1 aMaschio, Andrea1 aLeach, Irene, Mateo1 aMcKnight, Barbara1 aMemari, Yasin1 aMitchell, Braxton, D1 aMontgomery, Grant, W1 aNakamura, Yusuke1 aNauck, Matthias1 aNavis, Gerjan1 aNöthlings, Ute1 aNolte, Ilja, M1 aPorteous, David, J1 aPouta, Anneli1 aPramstaller, Peter, P1 aPullat, Janne1 aRing, Susan, M1 aRotter, Jerome, I1 aRuggiero, Daniela1 aRuokonen, Aimo1 aSala, Cinzia1 aSamani, Nilesh, J1 aSambrook, Jennifer1 aSchlessinger, David1 aSchreiber, Stefan1 aSchunkert, Heribert1 aScott, James1 aSmith, Nicholas, L1 aSnieder, Harold1 aStarr, John, M1 aStumvoll, Michael1 aTakahashi, Atsushi1 aTang, W, H Wilson1 aTaylor, Kent1 aTenesa, Albert1 aThein, Swee, Lay1 aTönjes, Anke1 aUda, Manuela1 aUlivi, Sheila1 avan Veldhuisen, Dirk, J1 aVisscher, Peter, M1 aVölker, Uwe1 aWichmann, H-Erich1 aWiggins, Kerri, L1 aWillemsen, Gonneke1 aYang, Tsun-Po1 aZhao, Jing, Hua1 aZitting, Paavo1 aBradley, John, R1 aDedoussis, George, V1 aGasparini, Paolo1 aHazen, Stanley, L1 aMetspalu, Andres1 aPirastu, Mario1 aShuldiner, Alan, R1 avan Pelt, Joost1 aZwaginga, Jaap-Jan1 aBoomsma, Dorret, I1 aDeary, Ian, J1 aFranke, Andre1 aFroguel, Philippe1 aGanesh, Santhi, K1 aJarvelin, Marjo-Riitta1 aMartin, Nicholas, G1 aMeisinger, Christa1 aPsaty, Bruce, M1 aSpector, Timothy, D1 aWareham, Nicholas, J1 aAkkerman, Jan-Willem, N1 aCiullo, Marina1 aDeloukas, Panos1 aGreinacher, Andreas1 aJupe, Steve1 aKamatani, Naoyuki1 aKhadake, Jyoti1 aKooner, Jaspal, S1 aPenninger, Josef1 aProkopenko, Inga1 aStemple, Derek1 aToniolo, Daniela1 aWernisch, Lorenz1 aSanna, Serena1 aHicks, Andrew, A1 aRendon, Augusto1 aFerreira, Manuel, A1 aOuwehand, Willem, H1 aSoranzo, Nicole uhttps://chs-nhlbi.org/node/135506059nas a2201225 4500008004100000022001400041245014700055210006900202260001300271300001100284490000700295520244300302653001902745653002302764653003802787653003402825653001102859653001702870653001102887100002102898700002002919700002702939700001902966700002302985700002003008700002003028700002003048700001803068700001703086700002803103700001903131700001903150700002203169700001903191700002303210700002403233700002503257700002303282700002703305700002003332700002203352700002403374700003003398700002003428700002203448700002103470700001803491700002303509700002203532700001903554700001703573700001903590700001703609700001903626700001903645700001803664700002603682700002603708700002303734700002303757700001503780700001703795700002303812700002303835700001503858700002003873700002203893700001903915700001603934700002503950700002703975700001904002700002704021700002404048700002804072700001904100700001904119700002204138700002104160700002104181700001804202700002504220700001904245700002204264700002504286700001704311700001904328700002204347700002004369700002604389700002804415700001904443700001904462700002704481700002004508700002304528700002104551700002204572700002104594700002104615700002004636710009604656710004504752856003604797 2012 eng d a1474-446500aGenetic risk factors for ischaemic stroke and its subtypes (the METASTROKE collaboration): a meta-analysis of genome-wide association studies.0 aGenetic risk factors for ischaemic stroke and its subtypes the M c2012 Nov a951-620 v113 aBACKGROUND: Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.
METHODS: We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.
FINDINGS: We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10(-16)) and ZFHX3 (p=2·28×10(-8)), and for large-vessel stroke at a 9p21 locus (p=3·32×10(-5)) and HDAC9 (p=2·03×10(-12)). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p<5×10(-6). However, we were unable to replicate any of these novel associations in the replication cohort.
INTERPRETATION: Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.
FUNDING: Wellcome Trust, UK Medical Research Council (MRC), Australian National and Medical Health Research Council, National Institutes of Health (NIH) including National Heart, Lung and Blood Institute (NHLBI), the National Institute on Aging (NIA), the National Human Genome Research Institute (NHGRI), and the National Institute of Neurological Disorders and Stroke (NINDS).
10aBrain Ischemia10aDatabases, Genetic10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aRisk Factors10aStroke1 aTraylor, Matthew1 aFarrall, Martin1 aHolliday, Elizabeth, G1 aSudlow, Cathie1 aHopewell, Jemma, C1 aCheng, Yu-Ching1 aFornage, Myriam1 aIkram, Arfan, M1 aMalik, Rainer1 aBevan, Steve1 aThorsteinsdottir, Unnur1 aNalls, Mike, A1 aLongstreth, Wt1 aWiggins, Kerri, L1 aYadav, Sunaina1 aParati, Eugenio, A1 aDeStefano, Anita, L1 aWorrall, Bradford, B1 aKittner, Steven, J1 aKhan, Muhammad, Saleem1 aReiner, Alex, P1 aHelgadottir, Anna1 aAchterberg, Sefanja1 aFernandez-Cadenas, Israel1 aAbboud, Sherine1 aSchmidt, Reinhold1 aWalters, Matthew1 aChen, Wei-Min1 aRingelstein, Bernd1 aO'Donnell, Martin1 aHo, Weang, Kee1 aPera, Joanna1 aLemmens, Robin1 aNorrving, Bo1 aHiggins, Peter1 aBenn, Marianne1 aSale, Michele1 aKuhlenbäumer, Gregor1 aDoney, Alexander, S F1 aVicente, Astrid, M1 aDelavaran, Hossein1 aAlgra, Ale1 aDavies, Gail1 aOliveira, Sofia, A1 aPalmer, Colin, N A1 aDeary, Ian1 aSchmidt, Helena1 aPandolfo, Massimo1 aMontaner, Joan1 aCarty, Cara1 ade Bakker, Paul, I W1 aKostulas, Konstantinos1 aFerro, Jose, M1 avan Zuydam, Natalie, R1 aValdimarsson, Einar1 aNordestgaard, Børge, G1 aLindgren, Arne1 aThijs, Vincent1 aSlowik, Agnieszka1 aSaleheen, Danish1 aParé, Guillaume1 aBerger, Klaus1 aThorleifsson, Gudmar1 aHofman, Albert1 aMosley, Thomas, H1 aMitchell, Braxton, D1 aFurie, Karen1 aClarke, Robert1 aLevi, Christopher1 aSeshadri, Sudha1 aGschwendtner, Andreas1 aBoncoraglio, Giorgio, B1 aSharma, Pankaj1 aBis, Joshua, C1 aGretarsdottir, Solveig1 aPsaty, Bruce, M1 aRothwell, Peter, M1 aRosand, Jonathan1 aMeschia, James, F1 aStefansson, Kari1 aDichgans, Martin1 aMarkus, Hugh, S1 aAustralian Stroke Genetics Collaborative, Wellcome Trust Case Control Consortium 2 (WTCCC2)1 aInternational Stroke Genetics Consortium uhttps://chs-nhlbi.org/node/586304387nas a2201021 4500008004100000022001400041245005800055210005700113260000900170300001100179490000600190520154700196653000901743653002201752653001501774653003101789653004001820653001101860653001701871653003401888653001301922653001101935653000901946653003101955653002101986653001602007653002002023653002002043100001702063700002302080700001802103700002502121700001602146700002202162700001402184700002602198700002102224700001902245700001802264700002402282700002202306700001902328700002202347700002002369700002702389700001902416700002602435700002802461700002302489700001902512700002402531700002202555700002302577700002202600700001602622700001902638700002002657700002702677700002002704700002202724700002102746700002402767700001202791700002302803700002202826700001702848700002002865700002002885700002402905700002502929700001402954700002002968700002102988700002703009700002103036700002303057700002203080700002203102700001903124700002403143700002803167700002403195700001903219700001803238710004503256710002803301856003603329 2013 eng d a1932-620300aGenetic loci for retinal arteriolar microcirculation.0 aGenetic loci for retinal arteriolar microcirculation c2013 ae658040 v83 aNarrow arterioles in the retina have been shown to predict hypertension as well as other vascular diseases, likely through an increase in the peripheral resistance of the microcirculatory flow. In this study, we performed a genome-wide association study in 18,722 unrelated individuals of European ancestry from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium and the Blue Mountain Eye Study, to identify genetic determinants associated with variations in retinal arteriolar caliber. Retinal vascular calibers were measured on digitized retinal photographs using a standardized protocol. One variant (rs2194025 on chromosome 5q14 near the myocyte enhancer factor 2C MEF2C gene) was associated with retinal arteriolar caliber in the meta-analysis of the discovery cohorts at genome-wide significance of P-value <5×10(-8). This variant was replicated in an additional 3,939 individuals of European ancestry from the Australian Twins Study and Multi-Ethnic Study of Atherosclerosis (rs2194025, P-value = 2.11×10(-12) in combined meta-analysis of discovery and replication cohorts). In independent studies of modest sample sizes, no significant association was found between this variant and clinical outcomes including coronary artery disease, stroke, myocardial infarction or hypertension. In conclusion, we found one novel loci which underlie genetic variation in microvasculature which may be relevant to vascular disease. The relevance of these findings to clinical outcomes remains to be determined.
10aAged10aAged, 80 and over10aArterioles10aChromosomes, Human, Pair 510aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenome-Wide Association Study10aGenotype10aHumans10aMale10aMEF2 Transcription Factors10aMicrocirculation10aMiddle Aged10aModels, Genetic10aRetinal Vessels1 aSim, Xueling1 aJensen, Richard, A1 aIkram, Kamran1 aCotch, Mary, Frances1 aLi, Xiaohui1 aMacgregor, Stuart1 aXie, Jing1 aSmith, Albert, Vernon1 aBoerwinkle, Eric1 aMitchell, Paul1 aKlein, Ronald1 aKlein, Barbara, E K1 aGlazer, Nicole, L1 aLumley, Thomas1 aMcKnight, Barbara1 aPsaty, Bruce, M1 ade Jong, Paulus, T V M1 aHofman, Albert1 aRivadeneira, Fernando1 aUitterlinden, André, G1 aDuijn, Cornelia, M1 aAspelund, Thor1 aEiriksdottir, Gudny1 aHarris, Tamara, B1 aJonasson, Fridbert1 aLauner, Lenore, J1 aAttia, John1 aBaird, Paul, N1 aHarrap, Stephen1 aHolliday, Elizabeth, G1 aInouye, Michael1 aRochtchina, Elena1 aScott, Rodney, J1 aViswanathan, Ananth1 aLi, Guo1 aSmith, Nicholas, L1 aWiggins, Kerri, L1 aKuo, Jane, Z1 aTaylor, Kent, D1 aHewitt, Alex, W1 aMartin, Nicholas, G1 aMontgomery, Grant, W1 aSun, Cong1 aYoung, Terri, L1 aMackey, David, A1 avan Zuydam, Natalie, R1 aDoney, Alex, S F1 aPalmer, Colin, N A1 aMorris, Andrew, D1 aRotter, Jerome, I1 aTai, Shyong, E1 aGudnason, Vilmundur1 aVingerling, Johannes, R1 aSiscovick, David, S1 aWang, Jie, Jin1 aWong, Tien, Y1 aWellcome Trust Case Control Consortium 21 aGlobal BPgen Consortium uhttps://chs-nhlbi.org/node/602704413nas a2200889 4500008004100000022001400041245008200055210006900137260000900206300001100215490000600226520194300232653000902175653002202184653001102206653003402217653001302251653002502264653001102289653001702300653000902317653003602326653002302362653002102385100002302406700001702429700001602446700002502462700001802487700002702505700002402532700002202556700002302578700002402601700002202625700002602647700002102673700001702694700002002711700001702731700001902748700001902767700001602786700001802802700002202820700001902842700002202861700002002883700001702903700001902920700002702939700002602966700002802992700001803020700001903038700002003057700001703077700002003094700001903114700001403133700002203147700003003169700001903199700002203218700001703240700002303257700002403280700001803304700002403322700002203346700001503368700002503383700001803408710003903426710002203465856003603487 2013 eng d a1932-620300aGenome-wide association study of retinopathy in individuals without diabetes.0 aGenomewide association study of retinopathy in individuals witho c2013 ae542320 v83 aBACKGROUND: Mild retinopathy (microaneurysms or dot-blot hemorrhages) is observed in persons without diabetes or hypertension and may reflect microvascular disease in other organs. We conducted a genome-wide association study (GWAS) of mild retinopathy in persons without diabetes.
METHODS: A working group agreed on phenotype harmonization, covariate selection and analytic plans for within-cohort GWAS. An inverse-variance weighted fixed effects meta-analysis was performed with GWAS results from six cohorts of 19,411 Caucasians. The primary analysis included individuals without diabetes and secondary analyses were stratified by hypertension status. We also singled out the results from single nucleotide polymorphisms (SNPs) previously shown to be associated with diabetes and hypertension, the two most common causes of retinopathy.
RESULTS: No SNPs reached genome-wide significance in the primary analysis or the secondary analysis of participants with hypertension. SNP, rs12155400, in the histone deacetylase 9 gene (HDAC9) on chromosome 7, was associated with retinopathy in analysis of participants without hypertension, -1.3±0.23 (beta ± standard error), p = 6.6×10(-9). Evidence suggests this was a false positive finding. The minor allele frequency was low (∼2%), the quality of the imputation was moderate (r(2) ∼0.7), and no other common variants in the HDAC9 gene were associated with the outcome. SNPs found to be associated with diabetes and hypertension in other GWAS were not associated with retinopathy in persons without diabetes or in subgroups with or without hypertension.
CONCLUSIONS: This GWAS of retinopathy in individuals without diabetes showed little evidence of genetic associations. Further studies are needed to identify genes associated with these signs in order to help unravel novel pathways and determinants of microvascular diseases.
10aAged10aAged, 80 and over10aFemale10aGenome-Wide Association Study10aGenotype10aHistone Deacetylases10aHumans10aHypertension10aMale10aPolymorphism, Single Nucleotide10aRepressor Proteins10aRetinal Diseases1 aJensen, Richard, A1 aSim, Xueling1 aLi, Xiaohui1 aCotch, Mary, Frances1 aIkram, Kamran1 aHolliday, Elizabeth, G1 aEiriksdottir, Gudny1 aHarris, Tamara, B1 aJonasson, Fridbert1 aKlein, Barbara, E K1 aLauner, Lenore, J1 aSmith, Albert, Vernon1 aBoerwinkle, Eric1 aCheung, Ning1 aHewitt, Alex, W1 aLiew, Gerald1 aMitchell, Paul1 aWang, Jie, Jin1 aAttia, John1 aScott, Rodney1 aGlazer, Nicole, L1 aLumley, Thomas1 aMcKnight, Barbara1 aPsaty, Bruce, M1 aTaylor, Kent1 aHofman, Albert1 ade Jong, Paulus, T V M1 aRivadeneira, Fernando1 aUitterlinden, André, G1 aTay, Wan-Ting1 aTeo, Yik, Ying1 aSeielstad, Mark1 aLiu, Jianjun1 aCheng, Ching-Yu1 aSaw, Seang-Mei1 aAung, Tin1 aGanesh, Santhi, K1 aO'Donnell, Christopher, J1 aNalls, Mike, A1 aWiggins, Kerri, L1 aKuo, Jane, Z1 aDuijn, Cornelia, M1 aGudnason, Vilmundur1 aKlein, Ronald1 aSiscovick, David, S1 aRotter, Jerome, I1 aTai, Shong1 aVingerling, Johannes1 aWong, Tien, Y1 aBlue Mountains Eye Study GWAS Team1 aCKDGen Consortium uhttps://chs-nhlbi.org/node/607204635nas a2200913 4500008004100000022001400041245013400055210006900189260001300258300001100271490000600282520207800288653001002366653000902376653002002385653001302405653001802418653001902436653001102455653001702466653003402483653001302517653001702530653001102547653000902558653002102567653001602588653003602604653003202640653001702672653001102689653002602700653001802726100002202744700001902766700001802785700002002803700001602823700002202839700002302861700002202884700002302906700002002929700002702949700002702976700002003003700002003023700002103043700002403064700002003088700002003108700002103128700001703149700001803166700002403184700002203208700002003230700002203250700002103272700002203293700001803315700002303333700002203356700002103378700002403399700002003423700002203443700002303465700002003488700001803508700002403526700002403550700002203574700002003596700002003616700002703636700002203663856003603685 2014 eng d a1942-326800aGenome-wide association study of L-arginine and dimethylarginines reveals novel metabolic pathway for symmetric dimethylarginine.0 aGenomewide association study of Larginine and dimethylarginines c2014 Dec a864-720 v73 aBACKGROUND: Dimethylarginines (DMA) interfere with nitric oxide formation by inhibiting nitric oxide synthase (asymmetrical DMA [ADMA]) and l-arginine uptake into the cell (ADMA and symmetrical DMA [SDMA]). In prospective clinical studies, ADMA has been characterized as a cardiovascular risk marker, whereas SDMA is a novel marker for renal function and associated with all-cause mortality after ischemic stroke. The aim of the current study was to characterize the environmental and genetic contributions to interindividual variability of these biomarkers.
METHODS AND RESULTS: This study comprised a genome-wide association analysis of 3 well-characterized population-based cohorts (Framingham Heart Study [FHS; n=2992], Gutenberg Health Study [GHS; n=4354], and Multinational Monitoring of Trends and Determinants in Cardiovascular Disease Study [MONICA]/Cooperative Health Research in the Augsburg Area, Augsburg, Bavaria, Germany [KORA] F3 [n=581]) and identified replicated loci (DDAH1, MED23, Arg1, and AGXT2) associated with the interindividual variability in ADMA, l-arginine, and SDMA. Experimental in silico and in vitro studies confirmed functional significance of the identified AGXT2 variants. Clinical outcome analysis in 384 patients of the Leeds stroke study demonstrated an association between increased plasma levels of SDMA, AGXT2 variants, and various cardiometabolic risk factors. AGXT2 variants were not associated with poststroke survival in the Leeds study or were they associated with incident stroke in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.
CONCLUSIONS: These genome-wide association study support the importance of DDAH1 and MED23/Arg1 in regulating ADMA and l-arginine metabolism, respectively, and identify a novel regulatory renal pathway for SDMA by AGXT2. AGXT2 variants might explain part of the pathogenic link between SDMA, renal function, and outcome. An association between AGXT2 variants and stroke is unclear and warrants further investigation.
10aAdult10aAged10aAmidohydrolases10aArginine10aBinding Sites10aCohort Studies10aFemale10aGenetic Loci10aGenome-Wide Association Study10aGenotype10aHEK293 Cells10aHumans10aMale10aMediator Complex10aMiddle Aged10aPolymorphism, Single Nucleotide10aProtein Structure, Tertiary10aRisk Factors10aStroke10aSubstrate Specificity10aTransaminases1 aLüneburg, Nicole1 aLieb, Wolfgang1 aZeller, Tanja1 aChen, Ming-Huei1 aMaas, Renke1 aCarter, Angela, M1 aXanthakis, Vanessa1 aGlazer, Nicole, L1 aSchwedhelm, Edzard1 aSeshadri, Sudha1 aIkram, Mohammad, Arfan1 aLongstreth, William, T1 aFornage, Myriam1 aKönig, Inke, R1 aLoley, Christina1 aOjeda, Francisco, M1 aSchillert, Arne1 aWang, Thomas, J1 aSticht, Heinrich1 aKittel, Anja1 aKönig, Jörg1 aBenjamin, Emelia, J1 aSullivan, Lisa, M1 aBernges, Isabel1 aAnderssohn, Maike1 aZiegler, Andreas1 aGieger, Christian1 aIllig, Thomas1 aMeisinger, Christa1 aWichmann, H-Erich1 aWild, Philipp, S1 aSchunkert, Heribert1 aPsaty, Bruce, M1 aWiggins, Kerri, L1 aHeckbert, Susan, R1 aSmith, Nicholas1 aLackner, Karl1 aLunetta, Kathryn, L1 aBlankenberg, Stefan1 aErdmann, Jeanette1 aMünzel, Thomas1 aGrant, Peter, J1 aVasan, Ramachandran, S1 aBöger, Rainer, H uhttps://chs-nhlbi.org/node/681904872nas a2201453 4500008004100000022001400041245010900055210006900164260001600233300000900249490000600258520072200264653002100986653003401007653001101041653005101052653002101103653003601124100001801160700002001178700002501198700002301223700001601246700002101262700002301283700001701306700002501323700002401348700002201372700002201394700001901416700001701435700002001452700001201472700002101484700002101505700002801526700002301554700002501577700002001602700002401622700001401646700002601660700002001686700001901706700002401725700001701749700001801766700001901784700002201803700001801825700002201843700001901865700002601884700002101910700002501931700002401956700001801980700002501998700002202023700002102045700001702066700002402083700001602107700001602123700001902139700002202158700001602180700001902196700001902215700001802234700002302252700001902275700002102294700001802315700002102333700002002354700003002374700002702404700001602431700002202447700001802469700001602487700001702503700002302520700001602543700002202559700002102581700002602602700002002628700002502648700002802673700002402701700002302725700002202748700001902770700002302789700002302812700002202835700002002857700002302877700002802900700001902928700002602947700002002973700002102993700002003014700002403034700001703058700002103075700002803096700002203124700002203146700002003168700002303188700002403211700002203235700001903257700002203276700001903298700002303317710004203340856003603382 2014 eng d a2041-172300aPharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins.0 aPharmacogenetic metaanalysis of genomewide association studies o c2014 Oct 28 a50680 v53 aStatins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.
10aCholesterol, LDL10aGenome-Wide Association Study10aHumans10aHydroxymethylglutaryl-CoA Reductase Inhibitors10aPharmacogenetics10aPolymorphism, Single Nucleotide1 aPostmus, Iris1 aTrompet, Stella1 aDeshmukh, Harshal, A1 aBarnes, Michael, R1 aLi, Xiaohui1 aWarren, Helen, R1 aChasman, Daniel, I1 aZhou, Kaixin1 aArsenault, Benoit, J1 aDonnelly, Louise, A1 aWiggins, Kerri, L1 aAvery, Christy, L1 aGriffin, Paula1 aFeng, QiPing1 aTaylor, Kent, D1 aLi, Guo1 aEvans, Daniel, S1 aSmith, Albert, V1 ade Keyser, Catherine, E1 aJohnson, Andrew, D1 ade Craen, Anton, J M1 aStott, David, J1 aBuckley, Brendan, M1 aFord, Ian1 aWestendorp, Rudi, G J1 aSlagboom, Eline1 aSattar, Naveed1 aMunroe, Patricia, B1 aSever, Peter1 aPoulter, Neil1 aStanton, Alice1 aShields, Denis, C1 aO'Brien, Eoin1 aShaw-Hawkins, Sue1 aChen, Y-D, Ida1 aNickerson, Deborah, A1 aSmith, Joshua, D1 aDubé, Marie, Pierre1 aBoekholdt, Matthijs1 aHovingh, Kees1 aKastelein, John, J P1 aMcKeigue, Paul, M1 aBetteridge, John1 aNeil, Andrew1 aDurrington, Paul, N1 aDoney, Alex1 aCarr, Fiona1 aMorris, Andrew1 aMcCarthy, Mark, I1 aGroop, Leif1 aAhlqvist, Emma1 aBis, Joshua, C1 aRice, Kenneth1 aSmith, Nicholas, L1 aLumley, Thomas1 aWhitsel, Eric, A1 aStürmer, Til1 aBoerwinkle, Eric1 aNgwa, Julius, S1 aO'Donnell, Christopher, J1 aVasan, Ramachandran, S1 aWei, Wei-Qi1 aWilke, Russell, A1 aLiu, Ching-Ti1 aSun, Fangui1 aGuo, Xiuqing1 aHeckbert, Susan, R1 aPost, Wendy1 aSotoodehnia, Nona1 aArnold, Alice, M1 aStafford, Jeanette, M1 aDing, Jingzhong1 aHerrington, David, M1 aKritchevsky, Stephen, B1 aEiriksdottir, Gudny1 aLauner, Leonore, J1 aHarris, Tamara, B1 aChu, Audrey, Y1 aGiulianini, Franco1 aMacFadyen, Jean, G1 aBarratt, Bryan, J1 aNyberg, Fredrik1 aStricker, Bruno, H1 aUitterlinden, André, G1 aHofman, Albert1 aRivadeneira, Fernando1 aEmilsson, Valur1 aFranco, Oscar, H1 aRidker, Paul, M1 aGudnason, Vilmundur1 aLiu, Yongmei1 aDenny, Joshua, C1 aBallantyne, Christie, M1 aRotter, Jerome, I1 aCupples, Adrienne1 aPsaty, Bruce, M1 aPalmer, Colin, N A1 aTardif, Jean-Claude1 aColhoun, Helen, M1 aHitman, Graham1 aKrauss, Ronald, M1 aJukema, Wouter1 aCaulfield, Mark, J1 aWelcome Trust Case Control Consortium uhttps://chs-nhlbi.org/node/659105255nas a2200949 4500008004100000022001400041245015700055210006900212260000900281300001300290490000700303520251800310653002202828653000902850653002802859653002802887653004002915653001102955653003402966653001103000653001703011653001403028653000903042653001603051653003603067653002203103100001903125700002103144700001603165700002203181700002603203700001603229700002103245700002303266700001603289700002003305700002203325700002203347700002103369700002303390700002303413700002003436700002203456700002303478700002103501700002203522700002003544700002103564700002203585700001803607700002003625700002503645700002203670700002303692700001703715700002103732700002303753700002403776700002003800700002103820700002203841700002503863700002803888700002203916700001403938700001903952700001903971700002003990700002604010700002404036700002704060700001904087700002404106700002204130700001604152700001904168700002304187700002104210700002004231700001804251856003604269 2015 eng d a1932-620300aDrug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium.0 aDrugGene Interactions of Antihypertensive Medications and Risk o c2015 ae01404960 v103 aBACKGROUND: Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals.
METHODS: Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases).
RESULTS: Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD.
10aAfrican Americans10aAged10aAntihypertensive Agents10aCardiovascular Diseases10aEuropean Continental Ancestry Group10aFemale10aGenome-Wide Association Study10aHumans10aHypertension10aIncidence10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aTreatment Outcome1 aBis, Joshua, C1 aSitlani, Colleen1 aIrvin, Ryan1 aAvery, Christy, L1 aSmith, Albert, Vernon1 aSun, Fangui1 aEvans, Daniel, S1 aMusani, Solomon, K1 aLi, Xiaohui1 aTrompet, Stella1 aKrijthe, Bouwe, P1 aHarris, Tamara, B1 aQuibrera, Miguel1 aBrody, Jennifer, A1 aDemissie, Serkalem1 aDavis, Barry, R1 aWiggins, Kerri, L1 aTranah, Gregory, J1 aLange, Leslie, A1 aSotoodehnia, Nona1 aStott, David, J1 aFranco, Oscar, H1 aLauner, Lenore, J1 aStürmer, Til1 aTaylor, Kent, D1 aCupples, Adrienne, L1 aEckfeldt, John, H1 aSmith, Nicholas, L1 aLiu, Yongmei1 aWilson, James, G1 aHeckbert, Susan, R1 aBuckley, Brendan, M1 aIkram, Arfan, M1 aBoerwinkle, Eric1 aChen, Yii-Der Ida1 ade Craen, Anton, J M1 aUitterlinden, André, G1 aRotter, Jerome, I1 aFord, Ian1 aHofman, Albert1 aSattar, Naveed1 aSlagboom, Eline1 aWestendorp, Rudi, G J1 aGudnason, Vilmundur1 aVasan, Ramachandran, S1 aLumley, Thomas1 aCummings, Steven, R1 aTaylor, Herman, A1 aPost, Wendy1 aJukema, Wouter1 aStricker, Bruno, H1 aWhitsel, Eric, A1 aPsaty, Bruce, M1 aArnett, Donna uhttps://chs-nhlbi.org/node/687504154nas a2200829 4500008004100000022001400041245006800055210006700123260001300190300001000203490000700213520178300220653001202003653002002015653003502035653001902070653003702089653001302126653003402139653001302173653001102186653001302197653001802210653002702228653001402255653003602269653001102305100002702316700002102343700001802364700001702382700001902399700002302418700002002441700002202461700001902483700002102502700002802523700001902551700001802570700002002588700002002608700002002628700001602648700002302664700001902687700002102706700002202727700002202749700001902771700002702790700002302817700002002840700002302860700002002883700002102903700001902924700001902943700002202962700002502984700002103009700002503030700002103055700002003076700002203096700001603118700001903134710004503153710004503198710004503243856003603288 2015 eng d a1524-462800aGenetic overlap between diagnostic subtypes of ischemic stroke.0 aGenetic overlap between diagnostic subtypes of ischemic stroke c2015 Mar a615-90 v463 aBACKGROUND AND PURPOSE: Despite moderate heritability, the phenotypic heterogeneity of ischemic stroke has hampered gene discovery, motivating analyses of diagnostic subtypes with reduced sample sizes. We assessed evidence for a shared genetic basis among the 3 major subtypes: large artery atherosclerosis (LAA), cardioembolism, and small vessel disease (SVD), to inform potential cross-subtype analyses.
METHODS: Analyses used genome-wide summary data for 12 389 ischemic stroke cases (including 2167 LAA, 2405 cardioembolism, and 1854 SVD) and 62 004 controls from the Metastroke consortium. For 4561 cases and 7094 controls, individual-level genotype data were also available. Genetic correlations between subtypes were estimated using linear mixed models and polygenic profile scores. Meta-analysis of a combined LAA-SVD phenotype (4021 cases and 51 976 controls) was performed to identify shared risk alleles.
RESULTS: High genetic correlation was identified between LAA and SVD using linear mixed models (rg=0.96, SE=0.47, P=9×10(-4)) and profile scores (rg=0.72; 95% confidence interval, 0.52-0.93). Between LAA and cardioembolism and SVD and cardioembolism, correlation was moderate using linear mixed models but not significantly different from zero for profile scoring. Joint meta-analysis of LAA and SVD identified strong association (P=1×10(-7)) for single nucleotide polymorphisms near the opioid receptor μ1 (OPRM1) gene.
CONCLUSIONS: Our results suggest that LAA and SVD, which have been hitherto treated as genetically distinct, may share a substantial genetic component. Combined analyses of LAA and SVD may increase power to identify small-effect alleles influencing shared pathophysiological processes.
10aAlleles10aAtherosclerosis10aCerebral Small Vessel Diseases10aCohort Studies10aData Interpretation, Statistical10aEmbolism10aGenome-Wide Association Study10aGenotype10aHumans10aIschemia10aLinear Models10aMeta-Analysis as Topic10aPhenotype10aPolymorphism, Single Nucleotide10aStroke1 aHolliday, Elizabeth, G1 aTraylor, Matthew1 aMalik, Rainer1 aBevan, Steve1 aFalcone, Guido1 aHopewell, Jemma, C1 aCheng, Yu-Ching1 aCotlarciuc, Ioana1 aBis, Joshua, C1 aBoerwinkle, Eric1 aBoncoraglio, Giorgio, B1 aClarke, Robert1 aCole, John, W1 aFornage, Myriam1 aFurie, Karen, L1 aIkram, Arfan, M1 aJannes, Jim1 aKittner, Steven, J1 aLincz, Lisa, F1 aMaguire, Jane, M1 aMeschia, James, F1 aMosley, Thomas, H1 aNalls, Mike, A1 aOldmeadow, Christopher1 aParati, Eugenio, A1 aPsaty, Bruce, M1 aRothwell, Peter, M1 aSeshadri, Sudha1 aScott, Rodney, J1 aSharma, Pankaj1 aSudlow, Cathie1 aWiggins, Kerri, L1 aWorrall, Bradford, B1 aRosand, Jonathan1 aMitchell, Braxton, D1 aDichgans, Martin1 aMarkus, Hugh, S1 aLevi, Christopher1 aAttia, John1 aWray, Naomi, R1 aAustralian Stroke Genetics Collaborative1 aWellcome Trust Case Control Consortium 21 aInternational Stroke Genetics Consortium uhttps://chs-nhlbi.org/node/668804273nas a2200853 4500008004100000022001400041245012600055210006900181260001500250300001100265490000700276520176600283653003802049653003402087653001302121653001102134653002702145653003202172653001502204653001702219653002702236100002002263700002302283700002202306700001802328700002102346700001802367700002302385700002802408700002202436700001902458700001802477700002102495700002202516700003002538700002202568700001202590700002702602700002302629700002102652700002002673700001902693700002302712700002002735700001802755700001902773700002702792700002002819700002402839700003002863700001902893700002002912700001802932700001802950700002002968700003202988700002303020700002203043700001703065700002203082700002203104700001703126700002003143700002403163700002503187700002103212700001503233700002303248700003203271700002303303700002903326710002803355856003603383 2015 eng d a1537-660500aMeta-analysis of 65,734 individuals identifies TSPAN15 and SLC44A2 as two susceptibility loci for venous thromboembolism.0 aMetaanalysis of 65734 individuals identifies TSPAN15 and SLC44A2 c2015 Apr 2 a532-420 v963 aVenous thromboembolism (VTE), the third leading cause of cardiovascular mortality, is a complex thrombotic disorder with environmental and genetic determinants. Although several genetic variants have been found associated with VTE, they explain a minor proportion of VTE risk in cases. We undertook a meta-analysis of genome-wide association studies (GWASs) to identify additional VTE susceptibility genes. Twelve GWASs totaling 7,507 VTE case subjects and 52,632 control subjects formed our discovery stage where 6,751,884 SNPs were tested for association with VTE. Nine loci reached the genome-wide significance level of 5 × 10(-8) including six already known to associate with VTE (ABO, F2, F5, F11, FGG, and PROCR) and three unsuspected loci. SNPs mapping to these latter were selected for replication in three independent case-control studies totaling 3,009 VTE-affected individuals and 2,586 control subjects. This strategy led to the identification and replication of two VTE-associated loci, TSPAN15 and SLC44A2, with lead risk alleles associated with odds ratio for disease of 1.31 (p = 1.67 × 10(-16)) and 1.21 (p = 2.75 × 10(-15)), respectively. The lead SNP at the TSPAN15 locus is the intronic rs78707713 and the lead SLC44A2 SNP is the non-synonymous rs2288904 previously shown to associate with transfusion-related acute lung injury. We further showed that these two variants did not associate with known hemostatic plasma markers. TSPAN15 and SLC44A2 do not belong to conventional pathways for thrombosis and have not been associated to other cardiovascular diseases nor related quantitative biomarkers. Our findings uncovered unexpected actors of VTE etiology and pave the way for novel mechanistic concepts of VTE pathophysiology.
10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aHumans10aMembrane Glycoproteins10aMembrane Transport Proteins10aOdds Ratio10aTetraspanins10aVenous Thromboembolism1 aGermain, Marine1 aChasman, Daniel, I1 ade Haan, Hugoline1 aTang, Weihong1 aLindström, Sara1 aWeng, Lu-Chen1 ade Andrade, Mariza1 ade Visser, Marieke, C H1 aWiggins, Kerri, L1 aSuchon, Pierre1 aSaut, Noémie1 aSmadja, David, M1 aLe Gal, Grégoire1 aVlieg, Astrid, van Hylcka1 aDi Narzo, Antonio1 aHao, Ke1 aNelson, Christopher, P1 aRocanin-Arjo, Ares1 aFolkersen, Lasse1 aMonajemi, Ramin1 aRose, Lynda, M1 aBrody, Jennifer, A1 aSlagboom, Eline1 aAïssi, Dylan1 aGagnon, France1 aDeleuze, Jean-Francois1 aDeloukas, Panos1 aTzourio, Christophe1 aDartigues, Jean-François1 aBerr, Claudine1 aTaylor, Kent, D1 aCivelek, Mete1 aEriksson, Per1 aPsaty, Bruce, M1 aHouwing-Duitermaat, Jeanine1 aGoodall, Alison, H1 aCambien, Francois1 aKraft, Peter1 aAmouyel, Philippe1 aSamani, Nilesh, J1 aBasu, Saonli1 aRidker, Paul, M1 aRosendaal, Frits, R1 aKabrhel, Christopher1 aFolsom, Aaron, R1 aHeit, John1 aReitsma, Pieter, H1 aTrégouët, David-Alexandre1 aSmith, Nicholas, L1 aMorange, Pierre-Emmanuel1 aCardiogenics consortium uhttps://chs-nhlbi.org/node/668104476nas a2201081 4500008004100000022001400041245011400055210006900169260001600238300001100254490000800265520141200273653001901685653001501704653001601719653001501735653001901750653003201769653002201801653001101823653002601834653003601860653002301896653002601919100002501945700002201970700002401992700002502016700002002041700001802061700002302079700002302102700002002125700001702145700001502162700002502177700003002202700001902232700002102251700002002272700002502292700001802317700002202335700001502357700002002372700002102392700001902413700001802432700002602450700001902476700001502495700002002510700002202530700002802552700002202580700001302602700001802615700001702633700002602650700002102676700002102697700002302718700002402741700001902765700002402784700002402808700002102832700001902853700002402872700002502896700002002921700002202941700002102963700001602984700002303000700002003023700002003043700002403063700001703087700001803104700002003122700002003142700001803162700002103180700002103201700002203222700002203244700001903266700002003285700003003305700002303335856003603358 2015 eng d a1528-002000aRare and low-frequency variants and their association with plasma levels of fibrinogen, FVII, FVIII, and vWF.0 aRare and lowfrequency variants and their association with plasma c2015 Sep 10 ae19-290 v1263 aFibrinogen, coagulation factor VII (FVII), and factor VIII (FVIII) and its carrier von Willebrand factor (vWF) play key roles in hemostasis. Previously identified common variants explain only a small fraction of the trait heritabilities, and additional variations may be explained by associations with rarer variants with larger effects. The aim of this study was to identify low-frequency (minor allele frequency [MAF] ≥0.01 and <0.05) and rare (MAF <0.01) variants that influence plasma concentrations of these 4 hemostatic factors by meta-analyzing exome chip data from up to 76,000 participants of 4 ancestries. We identified 12 novel associations of low-frequency (n = 2) and rare (n = 10) variants across the fibrinogen, FVII, FVIII, and vWF traits that were independent of previously identified associations. Novel loci were found within previously reported genes and had effect sizes much larger than and independent of previously identified common variants. In addition, associations at KCNT1, HID1, and KATNB1 identified new candidate genes related to hemostasis for follow-up replication and functional genomic analysis. Newly identified low-frequency and rare-variant associations accounted for modest amounts of trait variance and therefore are unlikely to increase predicted trait heritability but provide new information for understanding individual variation in hemostasis pathways.
10aCohort Studies10aFactor VII10aFactor VIII10aFibrinogen10aGene Frequency10aGenetic Association Studies10aGenetic Variation10aHumans10aNerve Tissue Proteins10aPolymorphism, Single Nucleotide10aPotassium Channels10avon Willebrand Factor1 aHuffman, Jennifer, E1 ade Vries, Paul, S1 aMorrison, Alanna, C1 aSabater-Lleal, Maria1 aKacprowski, Tim1 aAuer, Paul, L1 aBrody, Jennifer, A1 aChasman, Daniel, I1 aChen, Ming-Huei1 aGuo, Xiuqing1 aLin, Li-An1 aMarioni, Riccardo, E1 aMüller-Nurasyid, Martina1 aYanek, Lisa, R1 aPankratz, Nathan1 aGrove, Megan, L1 ade Maat, Moniek, P M1 aCushman, Mary1 aWiggins, Kerri, L1 aQi, Lihong1 aSennblad, Bengt1 aHarris, Sarah, E1 aPolasek, Ozren1 aRiess, Helene1 aRivadeneira, Fernando1 aRose, Lynda, M1 aGoel, Anuj1 aTaylor, Kent, D1 aTeumer, Alexander1 aUitterlinden, André, G1 aVaidya, Dhananjay1 aYao, Jie1 aTang, Weihong1 aLevy, Daniel1 aWaldenberger, Melanie1 aBecker, Diane, M1 aFolsom, Aaron, R1 aGiulianini, Franco1 aGreinacher, Andreas1 aHofman, Albert1 aHuang, Chiang-Ching1 aKooperberg, Charles1 aSilveira, Angela1 aStarr, John, M1 aStrauch, Konstantin1 aStrawbridge, Rona, J1 aWright, Alan, F1 aMcKnight, Barbara1 aFranco, Oscar, H1 aZakai, Neil1 aMathias, Rasika, A1 aPsaty, Bruce, M1 aRidker, Paul, M1 aTofler, Geoffrey, H1 aVölker, Uwe1 aWatkins, Hugh1 aFornage, Myriam1 aHamsten, Anders1 aDeary, Ian, J1 aBoerwinkle, Eric1 aKoenig, Wolfgang1 aRotter, Jerome, I1 aHayward, Caroline1 aDehghan, Abbas1 aReiner, Alex, P1 aO'Donnell, Christopher, J1 aSmith, Nicholas, L uhttps://chs-nhlbi.org/node/678803153nas a2200529 4500008004100000022001400041245012000055210006900175260001300244300001000257490000800267520166400275653000901939653002201948653001901970653002401989653001102013653002202024653001502046653001102061653001402072653001802086653000902104653002602113653003702139653001402176653003202190653002402222653000902246653001702255653000902272653001502281100002002296700002402316700002202340700001802362700002402380700002402404700002702428700002402455700002202479700002302501700002202524700002102546700002002567856003602587 2015 eng d a1468-201X00aVariation in resting heart rate over 4 years and the risks of myocardial infarction and death among older adults.0 aVariation in resting heart rate over 4 years and the risks of my c2015 Jan a132-80 v1013 aOBJECTIVE: Resting heart rate (RHR) is an established predictor of myocardial infarction (MI) and mortality, but the relationship between variation in RHR over a period of several years and health outcomes is unclear. We evaluated the relationship between long-term variation in RHR and the risks of incident MI and mortality among older adults.
METHODS: 1991 subjects without cardiovascular disease from the Cardiovascular Health Study were included. RHR was taken from resting ECGs at the first five annual study visits. RHR mean, trend and variation were estimated with linear regression. Subjects were followed for incident MI and death until December 2010. HRs for RHR mean, trend and variation are reported for differences of 10 bpm, 2 bpm/year and 2 bpm, respectively.
RESULTS: 262 subjects had an incident MI event (13%) and 1326 died (67%) during 12 years of median follow-up. In primary analyses adjusted for cardiovascular risk factors, RHR mean (HR 1.12; 95% CI 1.05 to 1.20) and variation (HR 1.08; 95% CI 1.03 to 1.13) were associated with the risk of death while trend was not. None of the RHR variables were significantly associated with the risk of incident MI events; however, CIs were wide and the MI associations with RHR variables were not significantly different from the mortality associations. Adjusting for additional variables did not affect estimates, and there were no significant interactions with sex.
CONCLUSIONS: Variation in RHR over a period of several years represents a potential predictor of long-term mortality among older persons free of cardiovascular disease.
10aAged10aAged, 80 and over10aCause of Death10aElectrocardiography10aFemale10aFollow-Up Studies10aHeart Rate10aHumans10aIncidence10aLinear Models10aMale10aMyocardial Infarction10aOutcome Assessment (Health Care)10aPrognosis10aProportional Hazards Models10aProspective Studies10aRest10aRisk Factors10aTime10aWashington1 aFloyd, James, S1 aSitlani, Colleen, M1 aWiggins, Kerri, L1 aWallace, Erin1 aSuchy-Dicey, Astrid1 aAbbasi, Siddique, A1 aCarnethon, Mercedes, R1 aSiscovick, David, S1 aSotoodehnia, Nona1 aHeckbert, Susan, R1 aMcKnight, Barbara1 aRice, Kenneth, M1 aPsaty, Bruce, M uhttps://chs-nhlbi.org/node/656105220nas a2201201 4500008004100000022001400041245010300055210006900158260001600227300000800243490000700251520181700258100002002075700001802095700002302113700002602136700002302162700002002185700002002205700002202225700001902247700001702266700002302283700001602306700002202322700001702344700001802361700001802379700002802397700001902425700001902444700002002463700002202483700002202505700001702527700002302544700001302567700002302580700001902603700002302622700002202645700002102667700002102688700001802709700001602727700001402743700002402757700002902781700002102810700002502831700001802856700002002874700002002894700002102914700001902935700001902954700002202973700002102995700001403016700001603030700002003046700001903066700001903085700002003104700001903124700002503143700002203168700002403190700001903214700002303233700002403256700002403280700002103304700002503325700002503350700002503375700002003400700002603420700002203446700002203468700002303490700002803513700002603541700002103567700002203588700001703610700002303627700001803650700002203668700001903690700002003709700001603729700002903745700002103774700002103795700002103816700002603837700002403863700001903887710002703906710004903933856003603982 2016 eng d a1474-760X00aDNA methylation signatures of chronic low-grade inflammation are associated with complex diseases.0 aDNA methylation signatures of chronic lowgrade inflammation are c2016 Dec 12 a2550 v173 aBACKGROUND: Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation.
RESULTS: We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10(-7)) in the discovery panel of European ancestry and replicated (P < 2.29 × 10(-4)) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10(-5)), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10(-3)), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10(-5)). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants.
CONCLUSION: We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.
1 aLigthart, Symen1 aMarzi, Carola1 aAslibekyan, Stella1 aMendelson, Michael, M1 aConneely, Karen, N1 aTanaka, Toshiko1 aColicino, Elena1 aWaite, Lindsay, L1 aJoehanes, Roby1 aGuan, Weihua1 aBrody, Jennifer, A1 aElks, Cathy1 aMarioni, Riccardo1 aJhun, Min, A1 aAgha, Golareh1 aBressler, Jan1 aWard-Caviness, Cavin, K1 aChen, Brian, H1 aHuan, Tianxiao1 aBakulski, Kelly1 aSalfati, Elias, L1 aFiorito, Giovanni1 aWahl, Simone1 aSchramm, Katharina1 aSha, Jin1 aHernandez, Dena, G1 aJust, Allan, C1 aSmith, Jennifer, A1 aSotoodehnia, Nona1 aPilling, Luke, C1 aPankow, James, S1 aTsao, Phil, S1 aLiu, Chunyu1 aZhao, Wei1 aGuarrera, Simonetta1 aMichopoulos, Vasiliki, J1 aSmith, Alicia, K1 aPeters, Marjolein, J1 aMelzer, David1 aVokonas, Pantel1 aFornage, Myriam1 aProkisch, Holger1 aBis, Joshua, C1 aChu, Audrey, Y1 aHerder, Christian1 aGrallert, Harald1 aYao, Chen1 aShah, Sonia1 aMcRae, Allan, F1 aLin, Honghuang1 aHorvath, Steve1 aFallin, Daniele1 aHofman, Albert1 aWareham, Nicholas, J1 aWiggins, Kerri, L1 aFeinberg, Andrew, P1 aStarr, John, M1 aVisscher, Peter, M1 aMurabito, Joanne, M1 aKardia, Sharon, L R1 aAbsher, Devin, M1 aBinder, Elisabeth, B1 aSingleton, Andrew, B1 aBandinelli, Stefania1 aPeters, Annette1 aWaldenberger, Melanie1 aMatullo, Giuseppe1 aSchwartz, Joel, D1 aDemerath, Ellen, W1 aUitterlinden, André, G1 avan Meurs, Joyce, B J1 aFranco, Oscar, H1 aChen, Yii-Der Ida1 aLevy, Daniel1 aTurner, Stephen, T1 aDeary, Ian, J1 aRessler, Kerry, J1 aDupuis, Josée1 aFerrucci, Luigi1 aOng, Ken, K1 aAssimes, Themistocles, L1 aBoerwinkle, Eric1 aKoenig, Wolfgang1 aArnett, Donna, K1 aBaccarelli, Andrea, A1 aBenjamin, Emelia, J1 aDehghan, Abbas1 aWHI-EMPC Investigators1 aCHARGE epigenetics of Coronary Heart Disease uhttps://chs-nhlbi.org/node/734904724nas a2201189 4500008004100000022001400041245009300055210006900148260001300217300001200230490000700242520135800249100001801607700002101625700002001646700002501666700002201691700001901713700002301732700002801755700002501783700002101808700001701829700001601846700002201862700002101884700001601905700002001921700002101941700002301962700002201985700002102007700002402028700002102052700002402073700001902097700002502116700002402141700002102165700002502186700002402211700002402235700001402259700001702273700002202290700002302312700001902335700001802354700002502372700002302397700001802420700001702438700001902455700002202474700002402496700001702520700002602537700002002563700001802583700003002601700001602631700001802647700002702665700001802692700002102710700002602731700001902757700001702776700002202793700002202815700002002837700002302857700002102880700002202901700001902923700002002942700002302962700001802985700002803003700001603031700002603047700002103073700002203094700002203116700002803138700002203166700002503188700002103213700002403234700001903258700002303277700002003300700002003320700002603340700002203366700002403388700002303412700001903435700002203454700002203476856003603498 2016 eng d a1468-624400aMeta-analysis of genome-wide association studies of HDL cholesterol response to statins.0 aMetaanalysis of genomewide association studies of HDL cholestero c2016 Dec a835-8450 v533 aBACKGROUND: In addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation.
METHODS AND RESULTS: We performed a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p<1×10(-4) from the 16 769 statin-treated participants in the first analysis stage were followed up in an independent group of 10 951 statin-treated individuals, providing a total sample size of 27 720 individuals. The only associations of genome-wide significance (p<5×10(-8)) were between minor alleles at the CETP locus and greater HDL-C response to statin treatment.
CONCLUSIONS: Based on results from this study that included a relatively large sample size, we suggest that CETP may be the only detectable locus with common genetic variants that influence HDL-C response to statins substantially in individuals of European descent. Although CETP is known to be associated with HDL-C, we provide evidence that this pharmacogenetic effect is independent of its association with baseline HDL-C levels.
1 aPostmus, Iris1 aWarren, Helen, R1 aTrompet, Stella1 aArsenault, Benoit, J1 aAvery, Christy, L1 aBis, Joshua, C1 aChasman, Daniel, I1 ade Keyser, Catherine, E1 aDeshmukh, Harshal, A1 aEvans, Daniel, S1 aFeng, QiPing1 aLi, Xiaohui1 aSmit, Roelof, A J1 aSmith, Albert, V1 aSun, Fangui1 aTaylor, Kent, D1 aArnold, Alice, M1 aBarnes, Michael, R1 aBarratt, Bryan, J1 aBetteridge, John1 aBoekholdt, Matthijs1 aBoerwinkle, Eric1 aBuckley, Brendan, M1 aChen, Y-D, Ida1 ade Craen, Anton, J M1 aCummings, Steven, R1 aDenny, Joshua, C1 aDubé, Marie, Pierre1 aDurrington, Paul, N1 aEiriksdottir, Gudny1 aFord, Ian1 aGuo, Xiuqing1 aHarris, Tamara, B1 aHeckbert, Susan, R1 aHofman, Albert1 aHovingh, Kees1 aKastelein, John, J P1 aLauner, Leonore, J1 aLiu, Ching-Ti1 aLiu, Yongmei1 aLumley, Thomas1 aMcKeigue, Paul, M1 aMunroe, Patricia, B1 aNeil, Andrew1 aNickerson, Deborah, A1 aNyberg, Fredrik1 aO'Brien, Eoin1 aO'Donnell, Christopher, J1 aPost, Wendy1 aPoulter, Neil1 aVasan, Ramachandran, S1 aRice, Kenneth1 aRich, Stephen, S1 aRivadeneira, Fernando1 aSattar, Naveed1 aSever, Peter1 aShaw-Hawkins, Sue1 aShields, Denis, C1 aSlagboom, Eline1 aSmith, Nicholas, L1 aSmith, Joshua, D1 aSotoodehnia, Nona1 aStanton, Alice1 aStott, David, J1 aStricker, Bruno, H1 aStürmer, Til1 aUitterlinden, André, G1 aWei, Wei-Qi1 aWestendorp, Rudi, G J1 aWhitsel, Eric, A1 aWiggins, Kerri, L1 aWilke, Russell, A1 aBallantyne, Christie, M1 aColhoun, Helen, M1 aCupples, Adrienne, L1 aFranco, Oscar, H1 aGudnason, Vilmundur1 aHitman, Graham1 aPalmer, Colin, N A1 aPsaty, Bruce, M1 aRidker, Paul, M1 aStafford, Jeanette, M1 aStein, Charles, M1 aTardif, Jean-Claude1 aCaulfield, Mark, J1 aJukema, Wouter1 aRotter, Jerome, I1 aKrauss, Ronald, M uhttps://chs-nhlbi.org/node/735804580nas a2200937 4500008004100000022001400041245022100055210006900276260001300345300001200358490000700370520179400377100002102171700002402192700002202216700002202238700002702260700002202287700002002309700002102329700001602350700002102366700001602387700001202403700002102415700001902436700002302455700001902478700002302497700002102520700002402541700002502565700001502590700002102605700002902626700002202655700002302677700002202700700001902722700002002741700001702761700002202778700001202800700002002812700002102832700001802853700002302871700002302894700002902917700001802946700002502964700002102989700001903010700002503029700002403054700001903078700001703097700002303114700002003137700002403157700002203181700002003203700001803223700002003241700002503261700002803286700002403314700002103338700002403359700001903383700002103402700001703423700002903440700002403469700002203493700002703515700002003542700002303562700002103585856003603606 2017 eng d a1468-624400aA genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.0 agenomewide interaction analysis of tricyclictetracyclic antidepr c2017 May a313-3230 v543 aBACKGROUND: Increased heart rate and a prolonged QT interval are important risk factors for cardiovascular morbidity and mortality, and can be influenced by the use of various medications, including tricyclic/tetracyclic antidepressants (TCAs). We aim to identify genetic loci that modify the association between TCA use and RR and QT intervals.
METHODS AND RESULTS: We conducted race/ethnic-specific genome-wide interaction analyses (with HapMap phase II imputed reference panel imputation) of TCAs and resting RR and QT intervals in cohorts of European (n=45 706; n=1417 TCA users), African (n=10 235; n=296 TCA users) and Hispanic/Latino (n=13 808; n=147 TCA users) ancestry, adjusted for clinical covariates. Among the populations of European ancestry, two genome-wide significant loci were identified for RR interval: rs6737205 in BRE (β=56.3, pinteraction=3.9e(-9)) and rs9830388 in UBE2E2 (β=25.2, pinteraction=1.7e(-8)). In Hispanic/Latino cohorts, rs2291477 in TGFBR3 significantly modified the association between TCAs and QT intervals (β=9.3, pinteraction=2.55e(-8)). In the meta-analyses of the other ethnicities, these loci either were excluded from the meta-analyses (as part of quality control), or their effects did not reach the level of nominal statistical significance (pinteraction>0.05). No new variants were identified in these ethnicities. No additional loci were identified after inverse-variance-weighted meta-analysis of the three ancestries.
CONCLUSIONS: Among Europeans, TCA interactions with variants in BRE and UBE2E2 were identified in relation to RR intervals. Among Hispanic/Latinos, variants in TGFBR3 modified the relation between TCAs and QT intervals. Future studies are required to confirm our results.
1 aNoordam, Raymond1 aSitlani, Colleen, M1 aAvery, Christy, L1 aStewart, James, D1 aGogarten, Stephanie, M1 aWiggins, Kerri, L1 aTrompet, Stella1 aWarren, Helen, R1 aSun, Fangui1 aEvans, Daniel, S1 aLi, Xiaohui1 aLi, Jin1 aSmith, Albert, V1 aBis, Joshua, C1 aBrody, Jennifer, A1 aBusch, Evan, L1 aCaulfield, Mark, J1 aChen, Yii-der, I1 aCummings, Steven, R1 aCupples, Adrienne, L1 aDuan, Qing1 aFranco, Oscar, H1 aMéndez-Giráldez, Rául1 aHarris, Tamara, B1 aHeckbert, Susan, R1 avan Heemst, Diana1 aHofman, Albert1 aFloyd, James, S1 aKors, Jan, A1 aLauner, Lenore, J1 aLi, Yun1 aLi-Gao, Ruifang1 aLange, Leslie, A1 aLin, Henry, J1 ade Mutsert, Renée1 aNapier, Melanie, D1 aNewton-Cheh, Christopher1 aPoulter, Neil1 aReiner, Alexander, P1 aRice, Kenneth, M1 aRoach, Jeffrey1 aRodriguez, Carlos, J1 aRosendaal, Frits, R1 aSattar, Naveed1 aSever, Peter1 aSeyerle, Amanda, A1 aSlagboom, Eline1 aSoliman, Elsayed, Z1 aSotoodehnia, Nona1 aStott, David, J1 aStürmer, Til1 aTaylor, Kent, D1 aThornton, Timothy, A1 aUitterlinden, André, G1 aWilhelmsen, Kirk, C1 aWilson, James, G1 aGudnason, Vilmundur1 aJukema, Wouter1 aLaurie, Cathy, C1 aLiu, Yongmei1 aMook-Kanamori, Dennis, O1 aMunroe, Patricia, B1 aRotter, Jerome, I1 aVasan, Ramachandran, S1 aPsaty, Bruce, M1 aStricker, Bruno, H1 aWhitsel, Eric, A uhttps://chs-nhlbi.org/node/735303304nas a2200553 4500008004100000022001400041245016300055210006900218260001300287300001200300490000700312520166500319100001801984700002402002700002202026700002102048700001902069700002402088700002502112700001802137700002102155700002402176700002202200700001902222700002502241700002102266700001902287700001802306700002202324700001602346700001702362700001902379700001802398700002002416700002202436700002302458700002402481700002102505700002202526700002002548700001602568700002702584700002102611700002102632700002202653700002102675700001802696856003602714 2017 eng d a1942-326800aPCSK9 Loss-of-Function Variants, Low-Density Lipoprotein Cholesterol, and Risk of Coronary Heart Disease and Stroke: Data From 9 Studies of Blacks and Whites.0 aPCSK9 LossofFunction Variants LowDensity Lipoprotein Cholesterol c2017 Aug ae0016320 v103 aBACKGROUND: PCSK9 loss-of-function (LOF) variants allow for the examination of the effects of lifetime reduced low-density lipoprotein cholesterol (LDL-C) on cardiovascular events. We examined the association of PCSK9 LOF variants with LDL-C and incident coronary heart disease and stroke through a meta-analysis of data from 8 observational cohorts and 1 randomized trial of statin therapy.
METHODS AND RESULTS: These 9 studies together included 17 459 blacks with 403 (2.3%) having at least 1 Y142X or C679X variant and 31 306 whites with 955 (3.1%) having at least 1 R46L variant. Unadjusted odds ratios for associations between PCSK9 LOF variants and incident coronary heart disease (851 events in blacks and 2662 events in whites) and stroke (523 events in blacks and 1660 events in whites) were calculated using pooled Mantel-Haenszel estimates with continuity correction factors. Pooling results across studies using fixed-effects inverse-variance-weighted models, PCSK9 LOF variants were associated with 35 mg/dL (95% confidence interval [CI], 32-39) lower LDL-C in blacks and 13 mg/dL (95% CI, 11-16) lower LDL-C in whites. PCSK9 LOF variants were associated with a pooled odds ratio for coronary heart disease of 0.51 (95% CI, 0.28-0.92) in blacks and 0.82 (95% CI, 0.63-1.06) in whites. PCSK9 LOF variants were not associated with incident stroke (odds ratio, 0.84; 95% CI, 0.48-1.47 in blacks and odds ratio, 1.06; 95% CI, 0.80-1.41 in whites).
CONCLUSIONS: PCSK9 LOF variants were associated with lower LDL-C and coronary heart disease incidence. PCSK9 LOF variants were not associated with stroke risk.
1 aKent, Shia, T1 aRosenson, Robert, S1 aAvery, Christy, L1 aChen, Yii-der, I1 aCorrea, Adolfo1 aCummings, Steven, R1 aCupples, Adrienne, L1 aCushman, Mary1 aEvans, Daniel, S1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aHoward, George1 aIrvin, Marguerite, R1 aJudd, Suzanne, E1 aJukema, Wouter1 aLange, Leslie1 aLevitan, Emily, B1 aLi, Xiaohui1 aLiu, Yongmei1 aPost, Wendy, S1 aPostmus, Iris1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aSafford, Monika, M1 aSitlani, Colleen, M1 aSmith, Albert, V1 aStewart, James, D1 aTrompet, Stella1 aSun, Fangui1 aVasan, Ramachandran, S1 aWoolley, Michael1 aWhitsel, Eric, A1 aWiggins, Kerri, L1 aWilson, James, G1 aMuntner, Paul uhttps://chs-nhlbi.org/node/744805167nas a2201273 4500008004100000022001400041245013800055210006900193260001300262300001300275490000700288520164300295653002201938653001201960653004901972653001902021653001402040653002502054653001102079653001702090653003402107653001102141653001702152653000902169653002202178653000902200653003102209653003602240100002002276700001502296700002802311700002202339700002102361700002302382700001802405700002302423700001802446700001902464700002102483700002402504700001702528700001502545700001802560700002302578700001502601700002202616700002102638700001602659700002402675700002002699700001402719700001402733700002002747700002302767700001702790700001702807700002302824700002502847700002402872700001702896700001802913700002202931700002402953700002002977700002202997700001303019700001403032700002403046700001803070700002103088700002003109700001803129700002103147700002203168700001903190700001703209700002803226700002003254700002103274700001803295700001903313700002103332700002403353700001503377700001603392700002003408700002403428700002303452700002103475700002103496700001703517700002003534700002003554700001903574700002403593700002103617700001603638700002103654700001903675700002303694700001403717700002203731700002003753700001703773700002603790700001803816700002303834856003603857 2017 eng d a1553-740400aSingle-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.0 aSingletrait and multitrait genomewide association analyses ident c2017 May ae10067280 v133 aHypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.
10aAfrican Americans10aAnimals10aBasic Helix-Loop-Helix Transcription Factors10aBlood Pressure10aCadherins10aCase-Control Studies10aFemale10aGenetic Loci10aGenome-Wide Association Study10aHumans10aHypertension10aMale10aMembrane Proteins10aMice10aMultifactorial Inheritance10aPolymorphism, Single Nucleotide1 aLiang, Jingjing1 aLe, Thu, H1 aEdwards, Digna, R Velez1 aTayo, Bamidele, O1 aGaulton, Kyle, J1 aSmith, Jennifer, A1 aLu, Yingchang1 aJensen, Richard, A1 aChen, Guanjie1 aYanek, Lisa, R1 aSchwander, Karen1 aTajuddin, Salman, M1 aSofer, Tamar1 aKim, Wonji1 aKayima, James1 aMcKenzie, Colin, A1 aFox, Ervin1 aNalls, Michael, A1 aYoung, Hunter, J1 aSun, Yan, V1 aLane, Jacqueline, M1 aCechova, Sylvia1 aZhou, Jie1 aTang, Hua1 aFornage, Myriam1 aMusani, Solomon, K1 aWang, Heming1 aLee, Juyoung1 aAdeyemo, Adebowale1 aDreisbach, Albert, W1 aForrester, Terrence1 aChu, Pei-Lun1 aCappola, Anne1 aEvans, Michele, K1 aMorrison, Alanna, C1 aMartin, Lisa, W1 aWiggins, Kerri, L1 aHui, Qin1 aZhao, Wei1 aJackson, Rebecca, D1 aWare, Erin, B1 aFaul, Jessica, D1 aReiner, Alex, P1 aBray, Michael1 aDenny, Joshua, C1 aMosley, Thomas, H1 aPalmas, Walter1 aGuo, Xiuqing1 aPapanicolaou, George, J1 aPenman, Alan, D1 aPolak, Joseph, F1 aRice, Kenneth1 aTaylor, Ken, D1 aBoerwinkle, Eric1 aBottinger, Erwin, P1 aLiu, Kiang1 aRisch, Neil1 aHunt, Steven, C1 aKooperberg, Charles1 aZonderman, Alan, B1 aLaurie, Cathy, C1 aBecker, Diane, M1 aCai, Jianwen1 aLoos, Ruth, J F1 aPsaty, Bruce, M1 aWeir, David, R1 aKardia, Sharon, L R1 aArnett, Donna, K1 aWon, Sungho1 aEdwards, Todd, L1 aRedline, Susan1 aCooper, Richard, S1 aRao, D, C1 aRotter, Jerome, I1 aRotimi, Charles1 aLevy, Daniel1 aChakravarti, Aravinda1 aZhu, Xiaofeng1 aFranceschini, Nora uhttps://chs-nhlbi.org/node/757202535nas a2200217 4500008004100000022001400041245008000055210006900135260001600204520187300220100002202093700002202115700002102137700001302158700002402171700002202195700002202217700001902239700002302258856003602281 2018 eng d a1932-873700aAtrial fibrillation in an African-American cohort: The Jackson Heart Study.0 aAtrial fibrillation in an AfricanAmerican cohort The Jackson Hea c2018 Jul 023 aBACKGROUND: Atrial fibrillation (AF) is an important public health problem across race/ethnic groups. Data from US cohort studies initiated in the 1980s suggest a higher prevalence of AF risk factors among African-Americans (AAs) than whites, but lower AF incidence. The Jackson Heart Study (JHS) is a community-based study of 5306 AAs recruited starting in 2000.
HYPOTHESIS: Demographic, anthropometric, cardiovascular, and/or electrocardiographic factors are associated with AF incidence in JHS.
METHODS: Using baseline participant characteristics and incident AF identified through hospital surveillance, study electrocardiogram, and Medicare claims, we estimated age- and sex-specific AF incidence rates, compared them with rates in AA participants in the Multi-Ethnic Study of Atherosclerosis (MESA) and Cardiovascular Health Study (CHS), and examined associations of cardiovascular risk factors with AF.
RESULTS: A total of 66 participants had prevalent AF at baseline. Over an average follow-up of 8.5 years, 242 cases of incident AF were identified. Age- and sex-specific AF incidence rates in JHS were similar to those among AAs in MESA and appeared slightly lower than those among AAs in CHS. In an age- and sex-adjusted model, associations with incident AF were observed for modifiable risk factors: high body weight (HR = 1.23 per 15 kg, 95%CI 1.13-1.35), systolic blood pressure (HR = 1.29 per 20 mmHg, 95%CI 1.13-1.47), and current smoking (HR = 1.80, 95%CI 1.27-2.55). Risk estimates associated with these risk factors were only slightly attenuated after multivariable adjustments.
CONCLUSIONS: These findings underscore the potential additional benefits of interventions for weight management, control of hypertension, and smoking cessation for the prevention of AF among AAs.
1 aAustin, Thomas, R1 aWiggins, Kerri, L1 aBlackshear, Chad1 aYang, Yi1 aBenjamin, Emelia, J1 aCurtis, Lesley, H1 aSotoodehnia, Nona1 aCorrea, Adolfo1 aHeckbert, Susan, R uhttps://chs-nhlbi.org/node/777903942nas a2200757 4500008004100000022001400041245010600055210006900161260001600230520175200246100002801998700002502026700001702051700002002068700002202088700001602110700001702126700002302143700002102166700001202187700002502199700002202224700002602246700002202272700001602294700002102310700002102331700003002352700001702382700001602399700001702415700002102432700003202453700001802485700002402503700002102527700002202548700002202570700001702592700002002609700002102629700002202650700002302672700002102695700001802716700001402734700001802748700002402766700002602790700002802816700002102844700001802865700002802883700002102911700002302932700001902955700002902974700001903003700001903022700002303041700001903064700002203083700002303105700002003128856003603148 2018 eng d a1528-002000aDNA methylation age is associated with an altered hemostatic profile in a multi-ethnic meta-analysis.0 aDNA methylation age is associated with an altered hemostatic pro c2018 Jul 243 aMany hemostatic factors are associated with age and age-related diseases, however much remains unknown about the biological mechanisms linking aging and hemostatic factors. DNA methylation is a novel means by which to assess epigenetic aging, which is a measure of age and the aging processes as determined by altered epigenetic states. We used a meta-analysis approach to examine the association between measures of epigenetic aging and hemostatic factors, as well as a clotting time measure. For fibrinogen, we used European and African-ancestry participants who were meta-analyzed separately and combined via a random effects meta-analysis. All other measures only included participants of European-ancestry. We found that 1-year higher extrinsic epigenetic age as compared to chronological age was associated with higher fibrinogen (0.004 g/L per year; 95% CI: 0.001, 0.007; P = 0.01) and plasminogen activator inhibitor 1 (PAI-1; 0.13 U/mL per year; 95% CI: 0.07, 0.20; P = 6.6x10-5) concentrations as well as lower activated partial thromboplastin time, a measure of clotting time. We replicated PAI-1 associations using an independent cohort. To further elucidate potential functional mechanisms we associated epigenetic aging with expression levels of the PAI-1 protein encoding gene (SERPINE1) and the three fibrinogen subunit-encoding genes (FGA, FGG, and FGB), in both peripheral blood and aorta intima-media samples. We observed associations between accelerated epigenetic aging and transcription of FGG in both tissues. Collectively, our results indicate that accelerated epigenetic aging is associated with a pro-coagulation hemostatic profile, and that epigenetic aging may regulate hemostasis in part via gene transcription.
1 aWard-Caviness, Cavin, K1 aHuffman, Jennifer, E1 aEvertt, Karl1 aGermain, Marine1 avan Dongen, Jenny1 aHill, David1 aJhun, Min, A1 aBrody, Jennifer, A1 aGhanbari, Mohsen1 aDu, Lei1 aRoetker, Nicholas, S1 ade Vries, Paul, S1 aWaldenberger, Melanie1 aGieger, Christian1 aWolf, Petra1 aProkisch, Holger1 aKoenig, Wolfgang1 aO'Donnell, Christopher, J1 aLevy, Daniel1 aLiu, Chunyu1 aTruong, Vinh1 aWells, Philip, S1 aTrégouët, David-Alexandre1 aTang, Weihong1 aMorrison, Alanna, C1 aBoerwinkle, Eric1 aWiggins, Kerri, L1 aMcKnight, Barbara1 aGuo, Xiuqing1 aPsaty, Bruce, M1 aSotoodenia, Nona1 aBoomsa, Dorret, I1 aWillemsen, Gonneke1 aLigthart, Lannie1 aDeary, Ian, J1 aZhao, Wei1 aWare, Erin, B1 aKardia, Sharon, L R1 avan Meurs, Joyce, B J1 aUitterlinden, André, G1 aFranco, Oscar, H1 aEriksson, Per1 aFranco-Cereceda, Anders1 aPankow, James, S1 aJohnson, Andrew, D1 aGagnon, France1 aMorange, Pierre-Emmanuel1 aGeus, Eco, J C1 aStarr, John, M1 aSmith, Jennifer, A1 aDehghan, Abbas1 aBjörck, Hanna, M1 aSmith, Nicholas, L1 aPeters, Annette uhttps://chs-nhlbi.org/node/781602630nas a2200421 4500008004100000022001400041245015400055210006900209260001600278520131200294100002501606700002401631700002101655700002301676700001901699700002001718700001201738700001901750700003301769700001901802700002301821700002901844700002201873700002501895700001801920700002001938700002101958700002801979700002202007700002102029700001502050700002302065700002202088700002102110700002002131700002102151856003602172 2018 eng d a1473-115000aGenome-wide meta-analysis of SNP-by9-ACEI/ARB and SNP-by-thiazide diuretic and effect on serum potassium in cohorts of European and African ancestry.0 aGenomewide metaanalysis of SNPby9ACEIARB and SNPbythiazide diure c2018 Jun 013 aWe evaluated interactions of SNP-by-ACE-I/ARB and SNP-by-TD on serum potassium (K+) among users of antihypertensive treatments (anti-HTN). Our study included seven European-ancestry (EA) (N = 4835) and four African-ancestry (AA) cohorts (N = 2016). We performed race-stratified, fixed-effect, inverse-variance-weighted meta-analyses of 2.5 million SNP-by-drug interaction estimates; race-combined meta-analysis; and trans-ethnic fine-mapping. Among EAs, we identified 11 significant SNPs (P < 5 × 10) for SNP-ACE-I/ARB interactions on serum K+ that were located between NR2F1-AS1 and ARRDC3-AS1 on chromosome 5 (top SNP rs6878413 P = 1.7 × 10; ratio of serum K+ in ACE-I/ARB exposed compared to unexposed is 1.0476, 1.0280, 1.0088 for the TT, AT, and AA genotypes, respectively). Trans-ethnic fine mapping identified the same group of SNPs on chromosome 5 as genome-wide significant for the ACE-I/ARB analysis. In conclusion, SNP-by-ACE-I /ARB interaction analyses uncovered loci that, if replicated, could have future implications for the prevention of arrhythmias due to anti-HTN treatment-related hyperkalemia. Before these loci can be identified as clinically relevant, future validation studies of equal or greater size in comparison to our discovery effort are needed.
1 aIrvin, Marguerite, R1 aSitlani, Colleen, M1 aNoordam, Raymond1 aAvery, Christie, L1 aBis, Joshua, C1 aFloyd, James, S1 aLi, Jin1 aLimdi, Nita, A1 aSrinivasasainagendra, Vinodh1 aStewart, James1 ade Mutsert, Renée1 aMook-Kanamori, Dennis, O1 aLipovich, Leonard1 aKleinbrink, Erica, L1 aSmith, Albert1 aBartz, Traci, M1 aWhitsel, Eric, A1 aUitterlinden, André, G1 aWiggins, Kerri, L1 aWilson, James, G1 aZhi, Degui1 aStricker, Bruno, H1 aRotter, Jerome, I1 aArnett, Donna, K1 aPsaty, Bruce, M1 aLange, Leslie, A uhttps://chs-nhlbi.org/node/779416401nas a2205425 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2018 eng d a1546-171800aMultiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.0 aMultiancestry genomewide association study of 520000 subjects id c2018 Apr a524-5370 v503 aStroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.
1 aMalik, Rainer1 aChauhan, Ganesh1 aTraylor, Matthew1 aSargurupremraj, Muralidharan1 aOkada, Yukinori1 aMishra, Aniket1 aRutten-Jacobs, Loes1 aGiese, Anne-Katrin1 avan der Laan, Sander, W1 aGretarsdottir, Solveig1 aAnderson, Christopher, D1 aChong, Michael1 aAdams, Hieab, H H1 aAgo, Tetsuro1 aAlmgren, Peter1 aAmouyel, Philippe1 aAy, Hakan1 aBartz, Traci, M1 aBenavente, Oscar, R1 aBevan, Steve1 aBoncoraglio, Giorgio, B1 aBrown, Robert, D1 aButterworth, Adam, S1 aCarrera, Caty1 aCarty, Cara, L1 aChasman, Daniel, I1 aChen, Wei-Min1 aCole, John, W1 aCorrea, Adolfo1 aCotlarciuc, Ioana1 aCruchaga, Carlos1 aDanesh, John1 ade Bakker, Paul, I W1 aDeStefano, Anita, L1 aHoed, Marcel, den1 aDuan, Qing1 aEngelter, Stefan, T1 aFalcone, Guido, J1 aGottesman, Rebecca, F1 aGrewal, Raji, P1 aGudnason, Vilmundur1 aGustafsson, Stefan1 aHaessler, Jeffrey1 aHarris, Tamara, B1 aHassan, Ahamad1 aHavulinna, Aki, S1 aHeckbert, Susan, R1 aHolliday, Elizabeth, G1 aHoward, George1 aHsu, Fang-Chi1 aHyacinth, Hyacinth, I1 aIkram, Arfan, M1 aIngelsson, Erik1 aIrvin, Marguerite, R1 aJian, Xueqiu1 aJimenez-Conde, Jordi1 aJohnson, Julie, A1 aJukema, Wouter1 aKanai, Masahiro1 aKeene, Keith, L1 aKissela, Brett, M1 aKleindorfer, Dawn, O1 aKooperberg, Charles1 aKubo, Michiaki1 aLange, Leslie, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLee, Jin-Moo1 aLemmens, Robin1 aLeys, Didier1 aLewis, Cathryn, M1 aLin, Wei-Yu1 aLindgren, Arne, G1 aLorentzen, Erik1 aMagnusson, Patrik, K1 aMaguire, Jane1 aManichaikul, Ani1 aMcArdle, Patrick, F1 aMeschia, James, F1 aMitchell, Braxton, D1 aMosley, Thomas, H1 aNalls, Michael, A1 aNinomiya, Toshiharu1 aO'Donnell, Martin, J1 aPsaty, Bruce, M1 aPulit, Sara, L1 aRannikmae, Kristiina1 aReiner, Alexander, P1 aRexrode, Kathryn, M1 aRice, Kenneth1 aRich, Stephen, S1 aRidker, Paul, M1 aRost, Natalia, S1 aRothwell, Peter, M1 aRotter, Jerome, I1 aRundek, Tatjana1 aSacco, Ralph, L1 aSakaue, Saori1 aSale, Michèle, M1 aSalomaa, Veikko1 aSapkota, Bishwa, R1 aSchmidt, Reinhold1 aSchmidt, Carsten, O1 aSchminke, Ulf1 aSharma, Pankaj1 aSlowik, Agnieszka1 aSudlow, Cathie, L M1 aTanislav, Christian1 aTatlisumak, Turgut1 aTaylor, Kent, D1 aThijs, Vincent, N S1 aThorleifsson, Gudmar1 aThorsteinsdottir, Unnur1 aTiedt, Steffen1 aTrompet, Stella1 aTzourio, Christophe1 aDuijn, Cornelia, M1 aWalters, Matthew1 aWareham, Nicholas, J1 aWassertheil-Smoller, Sylvia1 aWilson, James, G1 aWiggins, Kerri, L1 aYang, Qiong1 aYusuf, Salim1 aBis, Joshua, C1 aPastinen, Tomi1 aRuusalepp, Arno1 aSchadt, Eric, E1 aKoplev, Simon1 aBjörkegren, Johan, L M1 aCodoni, Veronica1 aCivelek, Mete1 aSmith, Nicholas, L1 aTrégouët, David, A1 aChristophersen, Ingrid, E1 aRoselli, Carolina1 aLubitz, Steven, A1 aEllinor, Patrick, T1 aTai, Shyong, E1 aKooner, Jaspal, S1 aKato, Norihiro1 aHe, Jiang1 aHarst, Pim1 aElliott, Paul1 aChambers, John, C1 aTakeuchi, Fumihiko1 aJohnson, Andrew, D1 aSanghera, Dharambir, K1 aMelander, Olle1 aJern, Christina1 aStrbian, Daniel1 aFernandez-Cadenas, Israel1 aLongstreth, W T1 aRolfs, Arndt1 aHata, Jun1 aWoo, Daniel1 aRosand, Jonathan1 aParé, Guillaume1 aHopewell, Jemma, C1 aSaleheen, Danish1 aStefansson, Kari1 aWorrall, Bradford, B1 aKittner, Steven, J1 aSeshadri, Sudha1 aFornage, Myriam1 aMarkus, Hugh, S1 aHowson, Joanna, M M1 aKamatani, Yoichiro1 aDebette, Stephanie1 aDichgans, Martin1 aMalik, Rainer1 aChauhan, Ganesh1 aTraylor, Matthew1 aSargurupremraj, Muralidharan1 aOkada, Yukinori1 aMishra, Aniket1 aRutten-Jacobs, Loes1 aGiese, Anne-Katrin1 avan der Laan, Sander, W1 aGretarsdottir, Solveig1 aAnderson, Christopher, D1 aChong, Michael1 aAdams, Hieab, H H1 aAgo, Tetsuro1 aAlmgren, Peter1 aAmouyel, Philippe1 aAy, Hakan1 aBartz, Traci, M1 aBenavente, Oscar, R1 aBevan, Steve1 aBoncoraglio, Giorgio, B1 aBrown, Robert, D1 aButterworth, Adam, S1 aCarrera, Caty1 aCarty, Cara, L1 aChasman, Daniel, I1 aChen, Wei-Min1 aCole, John, W1 aCorrea, Adolfo1 aCotlarciuc, Ioana1 aCruchaga, Carlos1 aDanesh, John1 ade Bakker, Paul, I W1 aDeStefano, Anita, L1 aHoed, Marcel, den1 aDuan, Qing1 aEngelter, Stefan, T1 aFalcone, Guido, J1 aGottesman, Rebecca, F1 aGrewal, Raji, P1 aGudnason, Vilmundur1 aGustafsson, Stefan1 aHaessler, Jeffrey1 aHarris, Tamara, B1 aHassan, Ahamad1 aHavulinna, Aki, S1 aHeckbert, Susan, R1 aHolliday, Elizabeth, G1 aHoward, George1 aHsu, Fang-Chi1 aHyacinth, Hyacinth, I1 aIkram, Arfan, M1 aIngelsson, Erik1 aIrvin, Marguerite, R1 aJian, Xueqiu1 aJimenez-Conde, Jordi1 aJohnson, Julie, A1 aJukema, Wouter1 aKanai, Masahiro1 aKeene, Keith, L1 aKissela, Brett, M1 aKleindorfer, Dawn, O1 aKooperberg, Charles1 aKubo, Michiaki1 aLange, Leslie, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLee, Jin-Moo1 aLemmens, Robin1 aLeys, Didier1 aLewis, Cathryn, M1 aLin, Wei-Yu1 aLindgren, Arne, G1 aLorentzen, Erik1 aMagnusson, Patrik, K1 aMaguire, Jane1 aManichaikul, Ani1 aMcArdle, Patrick, F1 aMeschia, James, F1 aMitchell, Braxton, D1 aMosley, Thomas, H1 aNalls, Michael, A1 aNinomiya, Toshiharu1 aO'Donnell, Martin, J1 aPsaty, Bruce, M1 aPulit, Sara, L1 aRannikmae, Kristiina1 aReiner, Alexander, P1 aRexrode, Kathryn, M1 aRice, Kenneth1 aRich, Stephen, S1 aRidker, Paul, M1 aRost, Natalia, S1 aRothwell, Peter, M1 aRotter, Jerome, I1 aRundek, Tatjana1 aSacco, Ralph, L1 aSakaue, Saori1 aSale, Michèle, M1 aSalomaa, Veikko1 aSapkota, Bishwa, R1 aSchmidt, Reinhold1 aSchmidt, Carsten, O1 aSchminke, Ulf1 aSharma, Pankaj1 aSlowik, Agnieszka1 aSudlow, Cathie, L M1 aTanislav, Christian1 aTatlisumak, Turgut1 aTaylor, Kent, D1 aThijs, Vincent, N S1 aThorleifsson, Gudmar1 aThorsteinsdottir, Unnur1 aTiedt, Steffen1 aTrompet, Stella1 aTzourio, Christophe1 aDuijn, Cornelia, M1 aWalters, Matthew1 aWareham, Nicholas, J1 aWassertheil-Smoller, Sylvia1 aWilson, James, G1 aWiggins, Kerri, L1 aYang, Qiong1 aYusuf, Salim1 aAmin, Najaf1 aAparicio, Hugo, S1 aArnett, Donna, K1 aAttia, John1 aBeiser, Alexa, S1 aBerr, Claudine1 aBuring, Julie, E1 aBustamante, Mariana1 aCaso, Valeria1 aCheng, Yu-Ching1 aChoi, Seung, Hoan1 aChowhan, Ayesha1 aCullell, Natalia1 aDartigues, Jean-François1 aDelavaran, Hossein1 aDelgado, Pilar1 aDörr, Marcus1 aEngström, Gunnar1 aFord, Ian1 aGurpreet, Wander, S1 aHamsten, Anders1 aHeitsch, Laura1 aHozawa, Atsushi1 aIbanez, Laura1 aIlinca, Andreea1 aIngelsson, Martin1 aIwasaki, Motoki1 aJackson, Rebecca, D1 aJood, Katarina1 aJousilahti, Pekka1 aKaffashian, Sara1 aKalra, Lalit1 aKamouchi, Masahiro1 aKitazono, Takanari1 aKjartansson, Olafur1 aKloss, Manja1 aKoudstaal, Peter, J1 aKrupinski, Jerzy1 aLabovitz, Daniel, L1 aLaurie, Cathy, C1 aLevi, Christopher, R1 aLi, Linxin1 aLind, Lars1 aLindgren, Cecilia, M1 aLioutas, Vasileios1 aLiu, Yong, Mei1 aLopez, Oscar, L1 aMakoto, Hirata1 aMartinez-Majander, Nicolas1 aMatsuda, Koichi1 aMinegishi, Naoko1 aMontaner, Joan1 aMorris, Andrew, P1 aMuiño, Elena1 aMüller-Nurasyid, Martina1 aNorrving, Bo1 aOgishima, Soichi1 aParati, Eugenio, A1 aPeddareddygari, Leema, Reddy1 aPedersen, Nancy, L1 aPera, Joanna1 aPerola, Markus1 aPezzini, Alessandro1 aPileggi, Silvana1 aRabionet, Raquel1 aRiba-Llena, Iolanda1 aRibasés, Marta1 aRomero, Jose, R1 aRoquer, Jaume1 aRudd, Anthony, G1 aSarin, Antti-Pekka1 aSarju, Ralhan1 aSarnowski, Chloe1 aSasaki, Makoto1 aSatizabal, Claudia, L1 aSatoh, Mamoru1 aSattar, Naveed1 aSawada, Norie1 aSibolt, Gerli1 aSigurdsson, Ásgeir1 aSmith, Albert1 aSobue, Kenji1 aSoriano-Tárraga, Carolina1 aStanne, Tara1 aStine, Colin1 aStott, David, J1 aStrauch, Konstantin1 aTakai, Takako1 aTanaka, Hideo1 aTanno, Kozo1 aTeumer, Alexander1 aTomppo, Liisa1 aTorres-Aguila, Nuria, P1 aTouze, Emmanuel1 aTsugane, Shoichiro1 aUitterlinden, André, G1 aValdimarsson, Einar, M1 avan der Lee, Sven, J1 aVölzke, Henry1 aWakai, Kenji1 aWeir, David1 aWilliams, Stephen, R1 aWolfe, Charles, D A1 aWong, Quenna1 aXu, Huichun1 aYamaji, Taiki1 aSanghera, Dharambir, K1 aMelander, Olle1 aJern, Christina1 aStrbian, Daniel1 aFernandez-Cadenas, Israel1 aLongstreth, W T1 aRolfs, Arndt1 aHata, Jun1 aWoo, Daniel1 aRosand, Jonathan1 aParé, Guillaume1 aHopewell, Jemma, C1 aSaleheen, Danish1 aStefansson, Kari1 aWorrall, Bradford, B1 aKittner, Steven, J1 aSeshadri, Sudha1 aFornage, Myriam1 aMarkus, Hugh, S1 aHowson, Joanna, M M1 aKamatani, Yoichiro1 aDebette, Stephanie1 aDichgans, Martin1 aAFGen Consortium1 aCohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium1 aInternational Genomics of Blood Pressure (iGEN-BP) Consortium1 aINVENT Consortium1 aSTARNET1 aBioBank Japan Cooperative Hospital Group1 aCOMPASS Consortium1 aEPIC-CVD Consortium1 aEPIC-InterAct Consortium1 aInternational Stroke Genetics Consortium (ISGC)1 aMETASTROKE Consortium1 aNeurology Working Group of the CHARGE Consortium1 aNINDS Stroke Genetics Network (SiGN)1 aUK Young Lacunar DNA Study1 aMEGASTROKE Consortium1 aMEGASTROKE Consortium: uhttps://chs-nhlbi.org/node/768308664nas a2202749 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2018 eng d a1546-171800aMulti-ethnic genome-wide association study for atrial fibrillation.0 aMultiethnic genomewide association study for atrial fibrillation c2018 Sep a1225-12330 v503 aAtrial fibrillation (AF) affects more than 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.
1 aRoselli, Carolina1 aChaffin, Mark, D1 aWeng, Lu-Chen1 aAeschbacher, Stefanie1 aAhlberg, Gustav1 aAlbert, Christine, M1 aAlmgren, Peter1 aAlonso, Alvaro1 aAnderson, Christopher, D1 aAragam, Krishna, G1 aArking, Dan, E1 aBarnard, John1 aBartz, Traci, M1 aBenjamin, Emelia, J1 aBihlmeyer, Nathan, A1 aBis, Joshua, C1 aBloom, Heather, L1 aBoerwinkle, Eric1 aBottinger, Erwin, B1 aBrody, Jennifer, A1 aCalkins, Hugh1 aCampbell, Archie1 aCappola, Thomas, P1 aCarlquist, John1 aChasman, Daniel, I1 aChen, Lin, Y1 aChen, Yii-Der Ida1 aChoi, Eue-Keun1 aChoi, Seung, Hoan1 aChristophersen, Ingrid, E1 aChung, Mina, K1 aCole, John, W1 aConen, David1 aCook, James1 aCrijns, Harry, J1 aCutler, Michael, J1 aDamrauer, Scott, M1 aDaniels, Brian, R1 aDarbar, Dawood1 aDelgado, Graciela1 aDenny, Joshua, C1 aDichgans, Martin1 aDörr, Marcus1 aDudink, Elton, A1 aDudley, Samuel, C1 aEsa, Nada1 aEsko, Tõnu1 aEskola, Markku1 aFatkin, Diane1 aFelix, Stephan, B1 aFord, Ian1 aFranco, Oscar, H1 aGeelhoed, Bastiaan1 aGrewal, Raji, P1 aGudnason, Vilmundur1 aGuo, Xiuqing1 aGupta, Namrata1 aGustafsson, Stefan1 aGutmann, Rebecca1 aHamsten, Anders1 aHarris, Tamara, B1 aHayward, Caroline1 aHeckbert, Susan, R1 aHernesniemi, Jussi1 aHocking, Lynne, J1 aHofman, Albert1 aHorimoto, Andrea, R V R1 aHuang, Jie1 aHuang, Paul, L1 aHuffman, Jennifer1 aIngelsson, Erik1 aIpek, Esra, Gucuk1 aIto, Kaoru1 aJimenez-Conde, Jordi1 aJohnson, Renee1 aJukema, Wouter1 aKääb, Stefan1 aKähönen, Mika1 aKamatani, Yoichiro1 aKane, John, P1 aKastrati, Adnan1 aKathiresan, Sekar1 aKatschnig-Winter, Petra1 aKavousi, Maryam1 aKessler, Thorsten1 aKietselaer, Bas, L1 aKirchhof, Paulus1 aKleber, Marcus, E1 aKnight, Stacey1 aKrieger, Jose, E1 aKubo, Michiaki1 aLauner, Lenore, J1 aLaurikka, Jari1 aLehtimäki, Terho1 aLeineweber, Kirsten1 aLemaitre, Rozenn, N1 aLi, Man1 aLim, Hong, Euy1 aLin, Henry, J1 aLin, Honghuang1 aLind, Lars1 aLindgren, Cecilia, M1 aLokki, Marja-Liisa1 aLondon, Barry1 aLoos, Ruth, J F1 aLow, Siew-Kee1 aLu, Yingchang1 aLyytikäinen, Leo-Pekka1 aMacfarlane, Peter, W1 aMagnusson, Patrik, K1 aMahajan, Anubha1 aMalik, Rainer1 aMansur, Alfredo, J1 aMarcus, Gregory, M1 aMargolin, Lauren1 aMargulies, Kenneth, B1 aMärz, Winfried1 aMcManus, David, D1 aMelander, Olle1 aMohanty, Sanghamitra1 aMontgomery, Jay, A1 aMorley, Michael, P1 aMorris, Andrew, P1 aMüller-Nurasyid, Martina1 aNatale, Andrea1 aNazarian, Saman1 aNeumann, Benjamin1 aNewton-Cheh, Christopher1 aNiemeijer, Maartje, N1 aNikus, Kjell1 aNilsson, Peter1 aNoordam, Raymond1 aOellers, Heidi1 aOlesen, Morten, S1 aOrho-Melander, Marju1 aPadmanabhan, Sandosh1 aPak, Hui-Nam1 aParé, Guillaume1 aPedersen, Nancy, L1 aPera, Joanna1 aPereira, Alexandre1 aPorteous, David1 aPsaty, Bruce, M1 aPulit, Sara, L1 aPullinger, Clive, R1 aRader, Daniel, J1 aRefsgaard, Lena1 aRibasés, Marta1 aRidker, Paul, M1 aRienstra, Michiel1 aRisch, Lorenz1 aRoden, Dan, M1 aRosand, Jonathan1 aRosenberg, Michael, A1 aRost, Natalia1 aRotter, Jerome, I1 aSaba, Samir1 aSandhu, Roopinder, K1 aSchnabel, Renate, B1 aSchramm, Katharina1 aSchunkert, Heribert1 aSchurman, Claudia1 aScott, Stuart, A1 aSeppälä, Ilkka1 aShaffer, Christian1 aShah, Svati1 aShalaby, Alaa, A1 aShim, Jaemin1 aShoemaker, Benjamin1 aSiland, Joylene, E1 aSinisalo, Juha1 aSinner, Moritz, F1 aSlowik, Agnieszka1 aSmith, Albert, V1 aSmith, Blair, H1 aSmith, Gustav1 aSmith, Jonathan, D1 aSmith, Nicholas, L1 aSoliman, Elsayed, Z1 aSotoodehnia, Nona1 aStricker, Bruno, H1 aSun, Albert1 aSun, Han1 aSvendsen, Jesper, H1 aTanaka, Toshihiro1 aTanriverdi, Kahraman1 aTaylor, Kent, D1 aTeder-Laving, Maris1 aTeumer, Alexander1 aThériault, Sébastien1 aTrompet, Stella1 aTucker, Nathan, R1 aTveit, Arnljot1 aUitterlinden, André, G1 aHarst, Pim1 aVan Gelder, Isabelle, C1 aVan Wagoner, David, R1 aVerweij, Niek1 aVlachopoulou, Efthymia1 aVölker, Uwe1 aWang, Biqi1 aWeeke, Peter, E1 aWeijs, Bob1 aWeiss, Raul1 aWeiss, Stefan1 aWells, Quinn, S1 aWiggins, Kerri, L1 aWong, Jorge, A1 aWoo, Daniel1 aWorrall, Bradford, B1 aYang, Pil-Sung1 aYao, Jie1 aYoneda, Zachary, T1 aZeller, Tanja1 aZeng, Lingyao1 aLubitz, Steven, A1 aLunetta, Kathryn, L1 aEllinor, Patrick, T uhttps://chs-nhlbi.org/node/781104760nas a2201057 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2019 eng d a1524-453900aBlood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease.0 aBlood Leukocyte DNA Methylation Predicts Risk of Future Myocardi c2019 08 20 a645-6570 v1403 aBACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts.
METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts.
RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts.
CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.
10aAdult10aAged10aCohort Studies10aCoronary Disease10aCpG Islands10aDNA Methylation10aEurope10aFemale10aGenome-Wide Association Study10aHumans10aIncidence10aLeukocytes10aMale10aMiddle Aged10aMyocardial Infarction10aPopulation Groups10aPrognosis10aProspective Studies10aRisk10aUnited States1 aAgha, Golareh1 aMendelson, Michael, M1 aWard-Caviness, Cavin, K1 aJoehanes, Roby1 aHuan, Tianxiao1 aGondalia, Rahul1 aSalfati, Elias1 aBrody, Jennifer, A1 aFiorito, Giovanni1 aBressler, Jan1 aChen, Brian, H1 aLigthart, Symen1 aGuarrera, Simonetta1 aColicino, Elena1 aJust, Allan, C1 aWahl, Simone1 aGieger, Christian1 aVandiver, Amy, R1 aTanaka, Toshiko1 aHernandez, Dena, G1 aPilling, Luke, C1 aSingleton, Andrew, B1 aSacerdote, Carlotta1 aKrogh, Vittorio1 aPanico, Salvatore1 aTumino, Rosario1 aLi, Yun1 aZhang, Guosheng1 aStewart, James, D1 aFloyd, James, S1 aWiggins, Kerri, L1 aRotter, Jerome, I1 aMulthaup, Michael1 aBakulski, Kelly1 aHorvath, Steven1 aTsao, Philip, S1 aAbsher, Devin, M1 aVokonas, Pantel1 aHirschhorn, Joel1 aFallin, Daniele1 aLiu, Chunyu1 aBandinelli, Stefania1 aBoerwinkle, Eric1 aDehghan, Abbas1 aSchwartz, Joel, D1 aPsaty, Bruce, M1 aFeinberg, Andrew, P1 aHou, Lifang1 aFerrucci, Luigi1 aSotoodehnia, Nona1 aMatullo, Giuseppe1 aPeters, Annette1 aFornage, Myriam1 aAssimes, Themistocles, L1 aWhitsel, Eric, A1 aLevy, Daniel1 aBaccarelli, Andrea, A uhttps://chs-nhlbi.org/node/850704831nas a2201009 4500008004100000022001400041245014800055210006900203260001600272300001400288490000700302520194700309653000902256653002802265653003002293653001902323653002502342653004102367653002902408653002502437653002002462653003502482653001102517653001102528653001702539653003402556653001102590653001702601653000902618653001602627653002402643653001802667653001802685653002102703653002902724653003602753653002002789653001702809653002602826653001802852653001702870100002502887700002402912700002002936700002002956700001902976700002202995700002103017700001803038700001903056700002003075700001603095700001803111700001503129700002503144700002103169700001903190700001803209700002103227700002203248700002103270700002203291700001303313700001603326700001703342700001603359700002603375700001803401700001903419700002003438700001403458700001903472700002403491700002903515700002003544700001903564700002103583700002503604700001603629700002703645700002103672700002103693700002803714700002103742700002203763856003603785 2019 eng d a1941-722500aGenome-Wide Association Study of Apparent Treatment-Resistant Hypertension in the CHARGE Consortium: The CHARGE Pharmacogenetics Working Group.0 aGenomeWide Association Study of Apparent TreatmentResistant Hype c2019 Nov 15 a1146-11530 v323 aBACKGROUND: Only a handful of genetic discovery efforts in apparent treatment-resistant hypertension (aTRH) have been described.
METHODS: We conducted a case-control genome-wide association study of aTRH among persons treated for hypertension, using data from 10 cohorts of European ancestry (EA) and 5 cohorts of African ancestry (AA). Cases were treated with 3 different antihypertensive medication classes and had blood pressure (BP) above goal (systolic BP ≥ 140 mm Hg and/or diastolic BP ≥ 90 mm Hg) or 4 or more medication classes regardless of BP control (nEA = 931, nAA = 228). Both a normotensive control group and a treatment-responsive control group were considered in separate analyses. Normotensive controls were untreated (nEA = 14,210, nAA = 2,480) and had systolic BP/diastolic BP < 140/90 mm Hg. Treatment-responsive controls (nEA = 5,266, nAA = 1,817) had BP at goal (<140/90 mm Hg), while treated with one antihypertensive medication class. Individual cohorts used logistic regression with adjustment for age, sex, study site, and principal components for ancestry to examine the association of single-nucleotide polymorphisms with case-control status. Inverse variance-weighted fixed-effects meta-analyses were carried out using METAL.
RESULTS: The known hypertension locus, CASZ1, was a top finding among EAs (P = 1.1 × 10-8) and in the race-combined analysis (P = 1.5 × 10-9) using the normotensive control group (rs12046278, odds ratio = 0.71 (95% confidence interval: 0.6-0.8)). Single-nucleotide polymorphisms in this locus were robustly replicated in the Million Veterans Program (MVP) study in consideration of a treatment-responsive control group. There were no statistically significant findings for the discovery analyses including treatment-responsive controls.
CONCLUSION: This genomic discovery effort for aTRH identified CASZ1 as an aTRH risk locus.
10aAged10aAntihypertensive Agents10aBlack or African American10aBlood Pressure10aCase-Control Studies10aDNA (Cytosine-5-)-Methyltransferases10aDNA Methyltransferase 3A10aDNA-Binding Proteins10aDrug Resistance10aDystrophin-Associated Proteins10aEurope10aFemale10aGenetic Loci10aGenome-Wide Association Study10aHumans10aHypertension10aMale10aMiddle Aged10aMyosin Heavy Chains10aMyosin Type V10aNeuropeptides10aPharmacogenetics10aPharmacogenomic Variants10aPolymorphism, Single Nucleotide10aRisk Assessment10aRisk Factors10aTranscription Factors10aUnited States10aWhite People1 aIrvin, Marguerite, R1 aSitlani, Colleen, M1 aFloyd, James, S1 aPsaty, Bruce, M1 aBis, Joshua, C1 aWiggins, Kerri, L1 aWhitsel, Eric, A1 aStürmer, Til1 aStewart, James1 aRaffield, Laura1 aSun, Fangui1 aLiu, Ching-Ti1 aXu, Hanfei1 aCupples, Adrienne, L1 aTanner, Rikki, M1 aRossing, Peter1 aSmith, Albert1 aZilhão, Nuno, R1 aLauner, Lenore, J1 aNoordam, Raymond1 aRotter, Jerome, I1 aYao, Jie1 aLi, Xiaohui1 aGuo, Xiuqing1 aLimdi, Nita1 aSundaresan, Aishwarya1 aLange, Leslie1 aCorrea, Adolfo1 aStott, David, J1 aFord, Ian1 aJukema, Wouter1 aGudnason, Vilmundur1 aMook-Kanamori, Dennis, O1 aTrompet, Stella1 aPalmas, Walter1 aWarren, Helen, R1 aHellwege, Jacklyn, N1 aGiri, Ayush1 aO'donnell, Christopher1 aHung, Adriana, M1 aEdwards, Todd, L1 aAhluwalia, Tarunveer, S1 aArnett, Donna, K1 aAvery, Christy, L uhttps://chs-nhlbi.org/node/937203604nas a2200553 4500008004100000022001400041245013100055210006900186260001200255300001100267490000600278520187600284653002202160653004502182653002802227653002902255653001102284653003502295653002902330653003602359653004102395653003402436100001502470700001402485700002602499700002302525700002202548700002002570700002302590700002202613700001602635700001502651700002402666700002002690700002002710700002202730700002302752700003102775700002402806700002102830700002102851700002302872700002402895700002202919700002702941700002102968700002502989856003603014 2019 eng d a2324-926900aGenome-wide meta-analysis of SNP and antihypertensive medication interactions on left ventricular traits in African Americans.0 aGenomewide metaanalysis of SNP and antihypertensive medication i c2019 10 ae007880 v73 aBACKGROUND: Left ventricular (LV) hypertrophy affects up to 43% of African Americans (AAs). Antihypertensive treatment reduces LV mass (LVM). However, interindividual variation in LV traits in response to antihypertensive treatments exists. We hypothesized that genetic variants may modify the association of antihypertensive treatment class with LV traits measured by echocardiography.
METHODS: We evaluated the main effects of the three most common antihypertensive treatments for AAs as well as the single nucleotide polymorphism (SNP)-by-drug interaction on LVM and relative wall thickness (RWT) in 2,068 participants across five community-based cohorts. Treatments included thiazide diuretics (TDs), angiotensin converting enzyme inhibitors (ACE-Is), and dihydropyridine calcium channel blockers (dCCBs) and were compared in a pairwise manner. We performed fixed effects inverse variance weighted meta-analyses of main effects of drugs and 2.5 million SNP-by-drug interaction estimates.
RESULTS: We observed that dCCBs versus TDs were associated with higher LVM after adjusting for covariates (p = 0.001). We report three SNPs at a single locus on chromosome 20 that modified the association between RWT and treatment when comparing dCCBs to ACE-Is with consistent effects across cohorts (smallest p = 4.7 × 10 , minor allele frequency range 0.09-0.12). This locus has been linked to LV hypertrophy in a previous study. A marginally significant locus in BICD1 (rs326641) was validated in an external population.
CONCLUSIONS: Our study identified one locus having genome-wide significant SNP-by-drug interaction effect on RWT among dCCB users in comparison to ACE-I users. Upon additional validation in future studies, our findings can enhance the precision of medical approaches in hypertension treatment.
10aAfrican Americans10aAngiotensin-Converting Enzyme Inhibitors10aAntihypertensive Agents10aCalcium Channel Blockers10aHumans10aObservational Studies as Topic10aPharmacogenomic Variants10aPolymorphism, Single Nucleotide10aSodium Chloride Symporter Inhibitors10aVentricular Dysfunction, Left1 aDo, Anh, N1 aZhao, Wei1 aBaldridge, Abigail, S1 aRaffield, Laura, M1 aWiggins, Kerri, L1 aShah, Sanjiv, J1 aAslibekyan, Stella1 aTiwari, Hemant, K1 aLimdi, Nita1 aZhi, Degui1 aSitlani, Colleen, M1 aTaylor, Kent, D1 aPsaty, Bruce, M1 aSotoodehnia, Nona1 aBrody, Jennifer, A1 aRasmussen-Torvik, Laura, J1 aLloyd-Jones, Donald1 aLange, Leslie, A1 aWilson, James, G1 aSmith, Jennifer, A1 aKardia, Sharon, L R1 aMosley, Thomas, H1 aVasan, Ramachandran, S1 aArnett, Donna, K1 aIrvin, Marguerite, R uhttps://chs-nhlbi.org/node/851104216nas a2200841 4500008004100000022001400041245011700055210006900172260001600241300001400257490000800271520173700279100002102016700001302037700001902050700002002069700003002089700002302119700002302142700002002165700002202185700002102207700002302228700001902251700002002270700002202290700002002312700002202332700002102354700002402375700002502399700002102424700002402445700002202469700002302491700002302514700001902537700002302556700002302579700002302602700001802625700002202643700002502665700002502690700002102715700002102736700002302757700001702780700002102797700002502818700002602843700002702869700002402896700001502920700002202935700001702957700002402974700002402998700001803022700002003040700001803060700002403078700002003102700002003122700002903142700002303171700002503194700003203219700002303251710002803274710003603302856003603338 2019 eng d a1528-002000aGenomic and transcriptomic association studies identify 16 novel susceptibility loci for venous thromboembolism.0 aGenomic and transcriptomic association studies identify 16 novel c2019 Nov 07 a1645-16570 v1343 aVenous thromboembolism (VTE) is a significant contributor to morbidity and mortality. To advance our understanding of the biology contributing to VTE, we conducted a genome-wide association study (GWAS) of VTE and a transcriptome-wide association study (TWAS) based on imputed gene expression from whole blood and liver. We meta-analyzed GWAS data from 18 studies for 30 234 VTE cases and 172 122 controls and assessed the association between 12 923 718 genetic variants and VTE. We generated variant prediction scores of gene expression from whole blood and liver tissue and assessed them for association with VTE. Mendelian randomization analyses were conducted for traits genetically associated with novel VTE loci. We identified 34 independent genetic signals for VTE risk from GWAS meta-analysis, of which 14 are newly reported associations. This included 11 newly associated genetic loci (C1orf198, PLEK, OSMR-AS1, NUGGC/SCARA5, GRK5, MPHOSPH9, ARID4A, PLCG2, SMG6, EIF5A, and STX10) of which 6 replicated, and 3 new independent signals in 3 known genes. Further, TWAS identified 5 additional genetic loci with imputed gene expression levels differing between cases and controls in whole blood (SH2B3, SPSB1, RP11-747H7.3, RP4-737E23.2) and in liver (ERAP1). At some GWAS loci, we found suggestive evidence that the VTE association signal for novel and previously known regions colocalized with expression quantitative trait locus signals. Mendelian randomization analyses suggested that blood traits may contribute to the underlying risk of VTE. To conclude, we identified 16 novel susceptibility loci for VTE; for some loci, the association signals are likely mediated through gene expression of nearby genes.
1 aLindström, Sara1 aWang, Lu1 aSmith, Erin, N1 aGordon, William1 aVlieg, Astrid, van Hylcka1 ade Andrade, Mariza1 aBrody, Jennifer, A1 aPattee, Jack, W1 aHaessler, Jeffrey1 aBrumpton, Ben, M1 aChasman, Daniel, I1 aSuchon, Pierre1 aChen, Ming-Huei1 aTurman, Constance1 aGermain, Marine1 aWiggins, Kerri, L1 aMacDonald, James1 aBraekkan, Sigrid, K1 aArmasu, Sebastian, M1 aPankratz, Nathan1 aJackson, Rebecca, D1 aNielsen, Jonas, B1 aGiulianini, Franco1 aPuurunen, Marja, K1 aIbrahim, Manal1 aHeckbert, Susan, R1 aDamrauer, Scott, M1 aNatarajan, Pradeep1 aKlarin, Derek1 ade Vries, Paul, S1 aSabater-Lleal, Maria1 aHuffman, Jennifer, E1 aBammler, Theo, K1 aFrazer, Kelly, A1 aMcCauley, Bryan, M1 aTaylor, Kent1 aPankow, James, S1 aReiner, Alexander, P1 aGabrielsen, Maiken, E1 aDeleuze, Jean-Francois1 aO'Donnell, Chris, J1 aKim, Jihye1 aMcKnight, Barbara1 aKraft, Peter1 aHansen, John-Bjarne1 aRosendaal, Frits, R1 aHeit, John, A1 aPsaty, Bruce, M1 aTang, Weihong1 aKooperberg, Charles1 aHveem, Kristian1 aRidker, Paul, M1 aMorange, Pierre-Emmanuel1 aJohnson, Andrew, D1 aKabrhel, Christopher1 aTrégouët, David-Alexandre1 aSmith, Nicholas, L1 aMillion Veteran Program1 aCHARGE Hemostasis Working Group uhttps://chs-nhlbi.org/node/820002918nas a2200589 4500008004100000022001400041245006600055210006200121260001600183520123400199100002101433700002301454700002201477700002001499700002001519700001901539700002001558700002001578700002001598700002101618700002101639700001701660700001701677700001801694700001901712700002601731700001801757700002101775700002401796700002201820700002701842700002901869700001901898700002101917700002001938700002201958700001701980700002501997700002302022700002402045700001702069700002402086700001802110700002302128700002902151700002502180700001702205700002302222700002502245710002202270856003602292 2019 eng d a1098-227200aA large-scale exome array analysis of venous thromboembolism.0 alargescale exome array analysis of venous thromboembolism c2019 Jan 193 aAlthough recent Genome-Wide Association Studies have identified novel associations for common variants, there has been no comprehensive exome-wide search for low-frequency variants that affect the risk of venous thromboembolism (VTE). We conducted a meta-analysis of 11 studies comprising 8,332 cases and 16,087 controls of European ancestry and 382 cases and 1,476 controls of African American ancestry genotyped with the Illumina HumanExome BeadChip. We used the seqMeta package in R to conduct single variant and gene-based rare variant tests. In the single variant analysis, we limited our analysis to the 64,794 variants with at least 40 minor alleles across studies (minor allele frequency [MAF] ~0.08%). We confirmed associations with previously identified VTE loci, including ABO, F5, F11, and FGA. After adjusting for multiple testing, we observed no novel significant findings in single variant or gene-based analysis. Given our sample size, we had greater than 80% power to detect minimum odds ratios greater than 1.5 and 1.8 for a single variant with MAF of 0.01 and 0.005, respectively. Larger studies and sequence data may be needed to identify novel low-frequency and rare variants associated with VTE risk.
1 aLindström, Sara1 aBrody, Jennifer, A1 aTurman, Constance1 aGermain, Marine1 aBartz, Traci, M1 aSmith, Erin, N1 aChen, Ming-Huei1 aPuurunen, Marja1 aChasman, Daniel1 aHassler, Jeffrey1 aPankratz, Nathan1 aBasu, Saonli1 aGuan, Weihua1 aGyorgy, Beata1 aIbrahim, Manal1 aEmpana, Jean-Philippe1 aOlaso, Robert1 aJackson, Rebecca1 aBraekkan, Sigrid, K1 aMcKnight, Barbara1 aDeleuze, Jean-Francois1 aO'Donnell, Cristopher, J1 aJouven, Xavier1 aFrazer, Kelly, A1 aPsaty, Bruce, M1 aWiggins, Kerri, L1 aTaylor, Kent1 aReiner, Alexander, P1 aHeckbert, Susan, R1 aKooperberg, Charles1 aRidker, Paul1 aHansen, John-Bjarne1 aTang, Weihong1 aJohnson, Andrew, D1 aMorange, Pierre-Emmanuel1 aTrégouët, David, A1 aKraft, Peter1 aSmith, Nicholas, L1 aKabrhel, Christopher1 aINVENT Consortium uhttps://chs-nhlbi.org/node/797904639nas a2200829 4500008004100000022001400041245010700055210006900162260000900231300001300240490000700253520225600260100002802516700002202544700002202566700002502588700001902613700002402632700002302656700001702679700002202696700002002718700001802738700002202756700002502778700002502803700001702828700001902845700003002864700002402894700002102918700002602939700002202965700002102987700002103008700001803029700001603047700002303063700001303086700002503099700002803124700002103152700002303173700002203196700002203218700002003240700002303260700002103283700002403304700002303328700002603351700002003377700002003397700001303417700001903430700002203449700002003471700001903491700001903510700002103529700002403550700002203574700002003596700001803616700002303634700001903657700003003676700002303706700002003729700002403749856003603773 2019 eng d a1932-620300aMendelian randomization evaluation of causal effects of fibrinogen on incident coronary heart disease.0 aMendelian randomization evaluation of causal effects of fibrinog c2019 ae02162220 v143 aBACKGROUND: Fibrinogen is an essential hemostatic factor and cardiovascular disease risk factor. Early attempts at evaluating the causal effect of fibrinogen on coronary heart disease (CHD) and myocardial infraction (MI) using Mendelian randomization (MR) used single variant approaches, and did not take advantage of recent genome-wide association studies (GWAS) or multi-variant, pleiotropy robust MR methodologies.
METHODS AND FINDINGS: We evaluated evidence for a causal effect of fibrinogen on both CHD and MI using MR. We used both an allele score approach and pleiotropy robust MR models. The allele score was composed of 38 fibrinogen-associated variants from recent GWAS. Initial analyses using the allele score used a meta-analysis of 11 European-ancestry prospective cohorts, free of CHD and MI at baseline, to examine incidence CHD and MI. We also applied 2 sample MR methods with data from a prevalent CHD and MI GWAS. Results are given in terms of the hazard ratio (HR) or odds ratio (OR), depending on the study design, and associated 95% confidence interval (CI). In single variant analyses no causal effect of fibrinogen on CHD or MI was observed. In multi-variant analyses using incidence CHD cases and the allele score approach, the estimated causal effect (HR) of a 1 g/L higher fibrinogen concentration was 1.62 (CI = 1.12, 2.36) when using incident cases and the allele score approach. In 2 sample MR analyses that accounted for pleiotropy, the causal estimate (OR) was reduced to 1.18 (CI = 0.98, 1.42) and 1.09 (CI = 0.89, 1.33) in the 2 most precise (smallest CI) models, out of 4 models evaluated. In the 2 sample MR analyses for MI, there was only very weak evidence of a causal effect in only 1 out of 4 models.
CONCLUSIONS: A small causal effect of fibrinogen on CHD is observed using multi-variant MR approaches which account for pleiotropy, but not single variant MR approaches. Taken together, results indicate that even with large sample sizes and multi-variant approaches MR analyses still cannot exclude the null when estimating the causal effect of fibrinogen on CHD, but that any potential causal effect is likely to be much smaller than observed in epidemiological studies.
1 aWard-Caviness, Cavin, K1 ade Vries, Paul, S1 aWiggins, Kerri, L1 aHuffman, Jennifer, E1 aYanek, Lisa, R1 aBielak, Lawrence, F1 aGiulianini, Franco1 aGuo, Xiuqing1 aKleber, Marcus, E1 aKacprowski, Tim1 aGroß, Stefan1 aPetersman, Astrid1 aSmith, George, Davey1 aHartwig, Fernando, P1 aBowden, Jack1 aHemani, Gibran1 aMüller-Nuraysid, Martina1 aStrauch, Konstantin1 aKoenig, Wolfgang1 aWaldenberger, Melanie1 aMeitinger, Thomas1 aPankratz, Nathan1 aBoerwinkle, Eric1 aTang, Weihong1 aFu, Yi-Ping1 aJohnson, Andrew, D1 aSong, Ci1 ade Maat, Moniek, P M1 aUitterlinden, André, G1 aFranco, Oscar, H1 aBrody, Jennifer, A1 aMcKnight, Barbara1 aChen, Yii-Der Ida1 aPsaty, Bruce, M1 aMathias, Rasika, A1 aBecker, Diane, M1 aPeyser, Patricia, A1 aSmith, Jennifer, A1 aBielinski, Suzette, J1 aRidker, Paul, M1 aTaylor, Kent, D1 aYao, Jie1 aTracy, Russell1 aDelgado, Graciela1 aTrompet, Stella1 aSattar, Naveed1 aJukema, Wouter1 aBecker, Lewis, C1 aKardia, Sharon, L R1 aRotter, Jerome, I1 aMärz, Winfried1 aDörr, Marcus1 aChasman, Daniel, I1 aDehghan, Abbas1 aO'Donnell, Christopher, J1 aSmith, Nicholas, L1 aPeters, Annette1 aMorrison, Alanna, C uhttps://chs-nhlbi.org/node/805003488nas a2200637 4500008004100000022001400041245010900055210006900164260000900233300001300242490000700255520161700262100002001879700002401899700002301923700002301946700002501969700002101994700002002015700002102035700001802056700001902074700001702093700001402110700001902124700001802143700002702161700001902188700002202207700002402229700002002253700001902273700002302292700002702315700002302342700002502365700001902390700002202409700003102431700001902462700002102481700001902502700002002521700002102541700002402562700002102586700003902607700001802646700002202664700002202686700002302708700002002731700001902751710004402770856003602814 2019 eng d a1932-620300aPharmacogenomics of statin-related myopathy: Meta-analysis of rare variants from whole-exome sequencing.0 aPharmacogenomics of statinrelated myopathy Metaanalysis of rare c2019 ae02181150 v143 aAIMS: Statin-related myopathy (SRM), which includes rhabdomyolysis, is an uncommon but important adverse drug reaction because the number of people prescribed statins world-wide is large. Previous association studies of common genetic variants have had limited success in identifying a genetic basis for this adverse drug reaction. We conducted a multi-site whole-exome sequencing study to investigate whether rare coding variants confer an increased risk of SRM.
METHODS AND RESULTS: SRM 3-5 cases (N = 505) and statin treatment-tolerant controls (N = 2047) were recruited from multiple sites in North America and Europe. SRM 3-5 was defined as symptoms consistent with muscle injury and an elevated creatine phosphokinase level >4 times upper limit of normal without another likely cause of muscle injury. Whole-exome sequencing and variant calling was coordinated from two analysis centres, and results of single-variant and gene-based burden tests were meta-analysed. No genome-wide significant associations were identified. Given the large number of cases, we had 80% power to identify a variant with minor allele frequency of 0.01 that increases the risk of SRM 6-fold at genome-wide significance.
CONCLUSIONS: In this large whole-exome sequencing study of severe statin-related muscle injury conducted to date, we did not find evidence that rare coding variants are responsible for this adverse drug reaction. Larger sample sizes would be required to identify rare variants with small effects, but it is unclear whether such findings would be clinically actionable.
1 aFloyd, James, S1 aBloch, Katarzyna, M1 aBrody, Jennifer, A1 aMaroteau, Cyrielle1 aSiddiqui, Moneeza, K1 aGregory, Richard1 aCarr, Daniel, F1 aMolokhia, Mariam1 aLiu, Xiaoming1 aBis, Joshua, C1 aAhmed, Ammar1 aLiu, Xuan1 aHallberg, Pär1 aYue, Qun-Ying1 aMagnusson, Patrik, K E1 aBrisson, Diane1 aWiggins, Kerri, L1 aMorrison, Alanna, C1 aKhoury, Etienne1 aMcKeigue, Paul1 aStricker, Bruno, H1 aLapeyre-Mestre, Maryse1 aHeckbert, Susan, R1 aGallagher, Arlene, M1 aChinoy, Hector1 aGibbs, Richard, A1 aBondon-Guitton, Emmanuelle1 aTracy, Russell1 aBoerwinkle, Eric1 aGaudet, Daniel1 aConforti, Anita1 avan Staa, Tjeerd1 aSitlani, Colleen, M1 aRice, Kenneth, M1 avan der Zee, Anke-Hilse, Maitland-1 aWadelius, Mia1 aMorris, Andrew, P1 aPirmohamed, Munir1 aPalmer, Colin, A N1 aPsaty, Bruce, M1 aAlfirevic, Ana1 aPREDICTION-ADR Consortium and EUDRAGENE uhttps://chs-nhlbi.org/node/810202650nas a2200589 4500008004100000022001400041245008000055210006900135260001600204490000600220520090300226100001301129700002401142700002201166700002301188700002401211700001401235700002701249700002501276700001301301700001701314700002501331700002401356700002101380700002101401700002001422700002401442700002301466700002001489700002501509700002101534700002001555700002401575700002301599700002701622700001701649700002801666700002001694700001401714700001901728700002201747700002001769700002101789700001701810700002201827700001901849700002601868700001901894700001601913710009501929856003602024 2021 eng d a2666-979X00aAssociation of mitochondrial DNA copy number with cardiometabolic diseases.0 aAssociation of mitochondrial DNA copy number with cardiometaboli c2021 Oct 130 v13 aMitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN ( = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN ( = 1.82 × 10) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity ( = 5.6 × 10), hypertension ( = 2.8 × 10), diabetes ( = 3.6 × 10), and hyperlipidemia ( = 6.3 × 10). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.
1 aLiu, Xue1 aLongchamps, Ryan, J1 aWiggins, Kerri, L1 aRaffield, Laura, M1 aBielak, Lawrence, F1 aZhao, Wei1 aPitsillides, Achilleas1 aBlackwell, Thomas, W1 aYao, Jie1 aGuo, Xiuqing1 aKurniansyah, Nuzulul1 aThyagarajan, Bharat1 aPankratz, Nathan1 aRich, Stephen, S1 aTaylor, Kent, D1 aPeyser, Patricia, A1 aHeckbert, Susan, R1 aSeshadri, Sudha1 aCupples, Adrienne, L1 aBoerwinkle, Eric1 aGrove, Megan, L1 aLarson, Nicholas, B1 aSmith, Jennifer, A1 aVasan, Ramachandran, S1 aSofer, Tamar1 aFitzpatrick, Annette, L1 aFornage, Myriam1 aDing, Jun1 aCorrea, Adolfo1 aAbecasis, Goncalo1 aPsaty, Bruce, M1 aWilson, James, G1 aLevy, Daniel1 aRotter, Jerome, I1 aBis, Joshua, C1 aSatizabal, Claudia, L1 aArking, Dan, E1 aLiu, Chunyu1 aTOPMed mtDNA Working Group in NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/899704296nas a2200973 4500008004100000022001400041245010700055210006900162260001600231520147300247100002301720700002101743700001901764700001801783700001901801700002301820700001901843700001701862700001901879700003001898700002601928700002801954700002801982700002102010700001702031700002202048700002302070700002202093700002202115700002102137700002402158700002302182700002002205700002402225700002002249700002102269700002302290700002402313700002402337700001902361700001902380700002002399700001902419700002502438700002302463700002402486700002002510700002302530700001602553700002202569700002002591700002002611700001702631700002202648700001802670700002402688700002402712700002302736700002402759700001902783700001502802700002302817700002502840700002502865700002202890700002402912700001902936700002602955700002602981700002103007700002103028700002203049700002303071700002003094700002703114700002103141700002003162700002103182700001903203700002003222700002303242700002103265856003603286 2021 eng d a1476-625600aA System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program.0 aSystem for Phenotype Harmonization in the NHLBI TransOmics for P c2021 Apr 163 aGenotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institute's Trans-Omics for Precision Medicine program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 studies per phenotype (participants recruited 1948-2012). We discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.
1 aStilp, Adrienne, M1 aEmery, Leslie, S1 aBroome, Jai, G1 aButh, Erin, J1 aKhan, Alyna, T1 aLaurie, Cecelia, A1 aWang, Fei, Fei1 aWong, Quenna1 aChen, Dongquan1 aD'Augustine, Catherine, M1 aHeard-Costa, Nancy, L1 aHohensee, Chancellor, R1 aJohnson, William, Craig1 aJuarez, Lucia, D1 aLiu, Jingmin1 aMutalik, Karen, M1 aRaffield, Laura, M1 aWiggins, Kerri, L1 ade Vries, Paul, S1 aKelly, Tanika, N1 aKooperberg, Charles1 aNatarajan, Pradeep1 aPeloso, Gina, M1 aPeyser, Patricia, A1 aReiner, Alex, P1 aArnett, Donna, K1 aAslibekyan, Stella1 aBarnes, Kathleen, C1 aBielak, Lawrence, F1 aBis, Joshua, C1 aCade, Brian, E1 aChen, Ming-Huei1 aCorrea, Adolfo1 aCupples, Adrienne, L1 ade Andrade, Mariza1 aEllinor, Patrick, T1 aFornage, Myriam1 aFranceschini, Nora1 aGan, Weiniu1 aGanesh, Santhi, K1 aGraffelman, Jan1 aGrove, Megan, L1 aGuo, Xiuqing1 aHawley, Nicola, L1 aHsu, Wan-Ling1 aJackson, Rebecca, D1 aJaquish, Cashell, E1 aJohnson, Andrew, D1 aKardia, Sharon, L R1 aKelly, Shannon1 aLee, Jiwon1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aNorth, Kari, E1 aNouraie, Seyed, Mehdi1 aOelsner, Elizabeth, C1 aPankratz, Nathan1 aRich, Stephen, S1 aRotter, Jerome, I1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aVasan, Ramachandran, S1 aWeeks, Daniel, E1 aWeiss, Scott, T1 aWilson, Carla, G1 aYanek, Lisa, R1 aPsaty, Bruce, M1 aHeckbert, Susan, R1 aLaurie, Cathy, C uhttps://chs-nhlbi.org/node/871303642nas a2200589 4500008004100000022001400041245009900055210006900154260001600223520192000239100002002159700001702179700002602196700002402222700002202246700001702268700002002285700002402305700001802329700002402347700001602371700002002387700002202407700002402429700002602453700002002479700002202499700002202521700002502543700002002568700002002588700002702608700002102635700002602656700002202682700002502704700001802729700002002747700002702767700002302794700001902817700002202836700001302858700002102871700002402892700001902916700002002935700002202955700001902977700002002996856003603016 2022 eng d a1875-890800aAssociations of Pulmonary Function with MRI Brain Volumes: A Coordinated Multi-Study Analysis.0 aAssociations of Pulmonary Function with MRI Brain Volumes A Coor c2022 Oct 033 aBACKGROUND: Previous studies suggest poor pulmonary function is associated with increased burden of cerebral white matter hyperintensities and brain atrophy among elderly individuals, but the results are inconsistent.
OBJECTIVE: To study the cross-sectional associations of pulmonary function with structural brain variables.
METHODS: Data from six large community-based samples (N = 11,091) were analyzed. Spirometric measurements were standardized with respect to age, sex, height, and ethnicity using reference equations of the Global Lung Function Initiative. Associations of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and their ratio FEV1/FVC with brain volume, gray matter volume, hippocampal volume, and volume of white matter hyperintensities were investigated using multivariable linear regressions for each study separately and then combined using random-effect meta-analyses.
RESULTS: FEV1 and FVC were positively associated with brain volume, gray matter volume, and hippocampal volume, and negatively associated with white matter hyperintensities volume after multiple testing correction, with little heterogeneity present between the studies. For instance, an increase of FVC by one unit was associated with 3.5 ml higher brain volume (95% CI: [2.2, 4.9]). In contrast, results for FEV1/FVC were more heterogeneous across studies, with significant positive associations with brain volume, gray matter volume, and hippocampal volume, but not white matter hyperintensities volume. Associations of brain variables with both FEV1 and FVC were consistently stronger than with FEV1/FVC, specifically with brain volume and white matter hyperintensities volume.
CONCLUSION: In cross-sectional analyses, worse pulmonary function is associated with smaller brain volumes and higher white matter hyperintensities burden.
1 aFrenzel, Stefan1 aBis, Josh, C1 aGudmundsson, Elias, F1 aO'Donnell, Adrienne1 aSimino, Jeannette1 aYaqub, Amber1 aBartz, Traci, M1 aBrusselle, Guy, G O1 aBülow, Robin1 aDeCarli, Charles, S1 aEwert, Ralf1 aGharib, Sina, A1 aGhosh, Saptaparni1 aGireud-Goss, Monica1 aGottesman, Rebecca, F1 aIkram, Arfan, M1 aKnopman, David, S1 aLauner, Lenore, J1 aLondon, Stephanie, J1 aLongstreth, W T1 aLopez, Oscar, L1 avan Lent, Debora, Melo1 aO'Connor, George1 aSatizabal, Claudia, L1 aShrestha, Srishti1 aSigurdsson, Sigurdur1 aStubbe, Beate1 aTalluri, Rajesh1 aVasan, Ramachandran, S1 aVernooij, Meike, W1 aVölzke, Henry1 aWiggins, Kerri, L1 aYu, Bing1 aBeiser, Alexa, S1 aGudnason, Vilmundur1 aMosley, Thomas1 aPsaty, Bruce, M1 aWolters, Frank, J1 aGrabe, Hans, J1 aSeshadri, Sudha uhttps://chs-nhlbi.org/node/916306322nas a2201285 4500008004100000022001400041245007900055210006900134260001600203300001400219490000800233520251800241653003802759653003402797653001302831653001102844653003602855653002802891653001502919653002702934100002102961700001802982700002303000700002003023700002203043700002303065700002003088700002003108700002403128700002603152700001803178700002503196700001503221700002303236700002203259700002403281700002203305700002903327700002303356700002003379700002403399700002403423700002003447700001803467700001903485700002003504700001903524700002203543700001403565700003003579700002003609700002303629700002303652700002203675700001703697700002603714700002003740700002203760700001203782700002503794700001403819700001403833700002403847700002403871700002103895700002203916700002303938700002403961700002203985700001804007700002204025700002004047700002004067700002304087700002504110700001804135700002104153700001904174700001804193700002604211700002004237700002304257700002504280700002104305700002504326700002204351700002004373700003004393700002704423700001704450700002104467700002004488700002004508700002604528700002104554700001904575700002104594700001704615700001804632700002404650700002404674700002904698700002504727700003204752700002304784700002304807700002304830710014704853856003605000 2022 eng d a1524-453900aCross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors.0 aCrossAncestry Investigation of Venous Thromboembolism Genomic Pr c2022 Oct 18 a1225-12420 v1463 aBACKGROUND: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources.
METHODS: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations.
RESULTS: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis.
CONCLUSIONS: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.
10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenomics10aHumans10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aThrombosis10aVenous Thromboembolism1 aThibord, Florian1 aKlarin, Derek1 aBrody, Jennifer, A1 aChen, Ming-Huei1 aLevin, Michael, G1 aChasman, Daniel, I1 aGoode, Ellen, L1 aHveem, Kristian1 aTeder-Laving, Maris1 aMartinez-Perez, Angel1 aAïssi, Dylan1 aDaian-Bacq, Delphine1 aIto, Kaoru1 aNatarajan, Pradeep1 aLutsey, Pamela, L1 aNadkarni, Girish, N1 ade Vries, Paul, S1 aCuellar-Partida, Gabriel1 aWolford, Brooke, N1 aPattee, Jack, W1 aKooperberg, Charles1 aBraekkan, Sigrid, K1 aLi-Gao, Ruifang1 aSaut, Noémie1 aSept, Corriene1 aGermain, Marine1 aJudy, Renae, L1 aWiggins, Kerri, L1 aKo, Darae1 aO'Donnell, Christopher, J1 aTaylor, Kent, D1 aGiulianini, Franco1 ade Andrade, Mariza1 aNøst, Therese, H1 aBoland, Anne1 aEmpana, Jean-Philippe1 aKoyama, Satoshi1 aGilliland, Thomas1 aDo, Ron1 aHuffman, Jennifer, E1 aWang, Xin1 aZhou, Wei1 aSoria, Jose, Manuel1 aSouto, Juan, Carlos1 aPankratz, Nathan1 aHaessler, Jeffery1 aHindberg, Kristian1 aRosendaal, Frits, R1 aTurman, Constance1 aOlaso, Robert1 aKember, Rachel, L1 aBartz, Traci, M1 aLynch, Julie, A1 aHeckbert, Susan, R1 aArmasu, Sebastian, M1 aBrumpton, Ben1 aSmadja, David, M1 aJouven, Xavier1 aKomuro, Issei1 aClapham, Katharine, R1 aLoos, Ruth, J F1 aWiller, Cristen, J1 aSabater-Lleal, Maria1 aPankow, James, S1 aReiner, Alexander, P1 aMorelli, Vania, M1 aRidker, Paul, M1 aVlieg, Astrid, van Hylcka1 aDeleuze, Jean-Francois1 aKraft, Peter1 aRader, Daniel, J1 aLee, Kyung, Min1 aPsaty, Bruce, M1 aSkogholt, Anne, Heidi1 aEmmerich, Joseph1 aSuchon, Pierre1 aRich, Stephen, S1 aVy, Ha, My T1 aTang, Weihong1 aJackson, Rebecca, D1 aHansen, John-Bjarne1 aMorange, Pierre-Emmanuel1 aKabrhel, Christopher1 aTrégouët, David-Alexandre1 aDamrauer, Scott, M1 aJohnson, Andrew, D1 aSmith, Nicholas, L1 aGlobal Biobank Meta-Analysis Initiative; Estonian Biobank Research Team; 23andMe Research Team; Biobank Japan; CHARGE Hemostasis Working Group uhttps://chs-nhlbi.org/node/919403010nas a2200697 4500008004100000022001400041245012100055210006900176260001600245300000900261490000700270520097500277653001001252653003001262653003801292653003401330653001101364653001701375653003101392653001501423653001701438100002501455700002401480700002101504700001801525700002201543700001901565700001701584700001901601700002001620700001801640700002201658700001301680700001901693700002301712700001301735700002401748700002201772700001401794700002001808700001501828700003201843700002101875700002701896700002101923700002001944700001901964700001901983700002402002700002002026700002202046700002002068700002202088700002102110700002402131700002302155700001702178700001702195710006402212856003602276 2022 eng d a2041-172300aA multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood.0 amultiethnic polygenic risk score is associated with hypertension c2022 Jun 21 a35490 v133 aIn a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.
10aAdult10aDiabetes Mellitus, Type 210aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aHypertension10aMultifactorial Inheritance10aPrevalence10aRisk Factors1 aKurniansyah, Nuzulul1 aGoodman, Matthew, O1 aKelly, Tanika, N1 aElfassy, Tali1 aWiggins, Kerri, L1 aBis, Joshua, C1 aGuo, Xiuqing1 aPalmas, Walter1 aTaylor, Kent, D1 aLin, Henry, J1 aHaessler, Jeffrey1 aGao, Yan1 aShimbo, Daichi1 aSmith, Jennifer, A1 aYu, Bing1 aFeofanova, Elena, V1 aSmit, Roelof, A J1 aWang, Zhe1 aHwang, Shih-Jen1 aLiu, Simin1 aWassertheil-Smoller, Sylvia1 aManson, JoAnn, E1 aLloyd-Jones, Donald, M1 aRich, Stephen, S1 aLoos, Ruth, J F1 aRedline, Susan1 aCorrea, Adolfo1 aKooperberg, Charles1 aFornage, Myriam1 aKaplan, Robert, C1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aArnett, Donna, K1 aMorrison, Alanna, C1 aFranceschini, Nora1 aLevy, Daniel1 aSofer, Tamar1 aNHLBI Trans-Omics in Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/910003392nas a2200565 4500008004100000022001400041245014400055210006900199260001600268520170200284100002201986700002302008700002302031700001902054700002402073700002002097700001902117700001802136700002102154700002002175700003002195700002602225700002002251700002002271700002202291700002402313700002302337700002002360700002002380700002402400700002002424700002202444700001302466700002402479700002002503700001502523700002302538700002702561700001702588700001602605700002402621700002002645700002402665700002202689700002202711700002202733700001502755700002002770856003602790 2022 eng d a1573-728400aProteomics and Population Biology in the Cardiovascular Health Study (CHS): design of a study with mentored access and active data sharing.0 aProteomics and Population Biology in the Cardiovascular Health S c2022 Jul 053 aBACKGROUND: In the last decade, genomic studies have identified and replicated thousands of genetic associations with measures of health and disease and contributed to the understanding of the etiology of a variety of health conditions. Proteins are key biomarkers in clinical medicine and often drug-therapy targets. Like genomics, proteomics can advance our understanding of biology.
METHODS AND RESULTS: In the setting of the Cardiovascular Health Study (CHS), a cohort study of older adults, an aptamer-based method that has high sensitivity for low-abundance proteins was used to assay 4979 proteins in frozen, stored plasma from 3188 participants (61% women, mean age 74 years). CHS provides active support, including central analysis, for seven phenotype-specific working groups (WGs). Each CHS WG is led by one or two senior investigators and includes 10 to 20 early or mid-career scientists. In this setting of mentored access, the proteomic data and analytic methods are widely shared with the WGs and investigators so that they may evaluate associations between baseline levels of circulating proteins and the incidence of a variety of health outcomes in prospective cohort analyses. We describe the design of CHS, the CHS Proteomics Study, characteristics of participants, quality control measures, and structural characteristics of the data provided to CHS WGs. We additionally highlight plans for validation and replication of novel proteomic associations.
CONCLUSION: The CHS Proteomics Study offers an opportunity for collaborative data sharing to improve our understanding of the etiology of a variety of health conditions in older adults.
1 aAustin, Thomas, R1 aMcHugh, Caitlin, P1 aBrody, Jennifer, A1 aBis, Joshua, C1 aSitlani, Colleen, M1 aBartz, Traci, M1 aBiggs, Mary, L1 aBansal, Nisha1 aBůzková, Petra1 aCarr, Steven, A1 adeFilippi, Christopher, R1 aElkind, Mitchell, S V1 aFink, Howard, A1 aFloyd, James, S1 aFohner, Alison, E1 aGerszten, Robert, E1 aHeckbert, Susan, R1 aKatz, Daniel, H1 aKizer, Jorge, R1 aLemaitre, Rozenn, N1 aLongstreth, W T1 aMcKnight, Barbara1 aMei, Hao1 aMukamal, Kenneth, J1 aNewman, Anne, B1 aNgo, Debby1 aOdden, Michelle, C1 aVasan, Ramachandran, S1 aShojaie, Ali1 aSimon, Noah1 aSmith, George Davey1 aDavies, Neil, M1 aSiscovick, David, S1 aSotoodehnia, Nona1 aTracy, Russell, P1 aWiggins, Kerri, L1 aZheng, Jie1 aPsaty, Bruce, M uhttps://chs-nhlbi.org/node/908604507nas a2201189 4500008004100000022001400041245006700055210006600122260001600188520113600204100002201340700001601362700002401378700002101402700002801423700002401451700002101475700001901496700001901515700002401534700002901558700002201587700002301609700001901632700003201651700002101683700001901704700002501723700001801748700002301766700001901789700002301808700002201831700002401853700002001877700002301897700002401920700002001944700002001964700002201984700002302006700002202029700001602051700002002067700002202087700001602109700002102125700002202146700002402168700001902192700001502211700002402226700001702250700002702267700002002294700002402314700002102338700002802359700001902387700001902406700002302425700002802448700001902476700002602495700002602521700002202547700002002569700002402589700002002613700002002633700001602653700002102669700002202690700001902712700002002731700002502751700002102776700002202797700002302819700002402842700002402866700002302890700001802913700002102931700002302952700001802975700002002993700002203013700002703035700002303062700001403085700002203099700001903121700001903140700002103159700002203180700001803202700002003220700002303240700001803263856003603281 2022 eng d a2397-337400aRare genetic variants explain missing heritability in smoking.0 aRare genetic variants explain missing heritability in smoking c2022 Aug 043 aCommon genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.
1 aJang, Seon-Kyeong1 aEvans, Luke1 aFialkowski, Allison1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBecker, Diane, M1 aBis, Joshua, C1 aBlangero, John1 aBleecker, Eugene, R1 aBoorgula, Meher, Preethi1 aBowden, Donald, W1 aBrody, Jennifer, A1 aCade, Brian, E1 aJenkins, Brenda, W Campbell1 aCarson, April, P1 aChavan, Sameer1 aCupples, Adrienne, L1 aCuster, Brian1 aDamrauer, Scott, M1 aDavid, Sean, P1 ade Andrade, Mariza1 aDinardo, Carla, L1 aFingerlin, Tasha, E1 aFornage, Myriam1 aFreedman, Barry, I1 aGarrett, Melanie, E1 aGharib, Sina, A1 aGlahn, David, C1 aHaessler, Jeffrey1 aHeckbert, Susan, R1 aHokanson, John, E1 aHou, Lifang1 aHwang, Shih-Jen1 aHyman, Matthew, C1 aJudy, Renae1 aJustice, Anne, E1 aKaplan, Robert, C1 aKardia, Sharon, L R1 aKelly, Shannon1 aKim, Wonji1 aKooperberg, Charles1 aLevy, Daniel1 aLloyd-Jones, Donald, M1 aLoos, Ruth, J F1 aManichaikul, Ani, W1 aGladwin, Mark, T1 aMartin, Lisa, Warsinger1 aNouraie, Mehdi1 aMelander, Olle1 aMeyers, Deborah, A1 aMontgomery, Courtney, G1 aNorth, Kari, E1 aOelsner, Elizabeth, C1 aPalmer, Nicholette, D1 aPayton, Marinelle1 aPeljto, Anna, L1 aPeyser, Patricia, A1 aPreuss, Michael1 aPsaty, Bruce, M1 aQiao, Dandi1 aRader, Daniel, J1 aRafaels, Nicholas1 aRedline, Susan1 aReed, Robert, M1 aReiner, Alexander, P1 aRich, Stephen, S1 aRotter, Jerome, I1 aSchwartz, David, A1 aShadyab, Aladdin, H1 aSilverman, Edwin, K1 aSmith, Nicholas, L1 aSmith, Gustav1 aSmith, Albert, V1 aSmith, Jennifer, A1 aTang, Weihong1 aTaylor, Kent, D1 aTelen, Marilyn, J1 aVasan, Ramachandran, S1 aGordeuk, Victor, R1 aWang, Zhe1 aWiggins, Kerri, L1 aYanek, Lisa, R1 aYang, Ivana, V1 aYoung, Kendra, A1 aYoung, Kristin, L1 aZhang, Yingze1 aLiu, Dajiang, J1 aKeller, Matthew, C1 aVrieze, Scott uhttps://chs-nhlbi.org/node/916809141nas a2202533 4500008004100000022001400041245008200055210006900137260001600206520188300222100001902105700001802124700002202142700002202164700002002186700002202206700002502228700001802253700002202271700001802293700001402311700002502325700001602350700001802366700001902384700002002403700001502423700003202438700003302470700001802503700001802521700002002539700002202559700001802581700002002599700002802619700001702647700001702664700002902681700001602710700002702726700002202753700002402775700001802799700002802817700001902845700001902864700001902883700001702902700002202919700002502941700002002966700002002986700002203006700001903028700002203047700001903069700001603088700002003104700001503124700002003139700002103159700001803180700002203198700001903220700002103239700002403260700002503284700002203309700002403331700001403355700001303369700002103382700001603403700002203419700002303441700002603464700002003490700001903510700002303529700002003552700002303572700002003595700002303615700002303638700002103661700001603682700001703698700002203715700001803737700001703755700001403772700001503786700002103801700002003822700002503842700002203867700002503889700002603914700002303940700002203963700001903985700002804004700002504032700002004057700003104077700002104108700002004129700002004149700002104169700002104190700002204211700002004233700002104253700002904274700002004303700003304323700001904356700002604375700002404401700002104425700002304446700002104469700001804490700001604508700001604524700001904540700002304559700002804582700002204610700003204632700002004664700002404684700002604708700002104734700001604755700002204771700002204793700002104815700001604836700002304852700001604875700001604891700002004907700002204927700002204949700002404971700001904995700001905014700002105033700002005054700002005074700001905094700002205113700002405135700002505159700001705184700003205201700002305233700002305256700002005279700002505299700002105324700001605345700002605361700001805387700002405405700001605429700002205445700002505467700002505492700001805517700002605535700002105561700003005582700002005612700001905632700002105651700002105672700002305693700002305716700002205739700002905761700002205790700002305812700002005835700001805855700002005873700003005893700002205923700002305945700002305968700002505991700001706016700002306033700002106056700002306077710002306100710002206123710007406145710002106219710002406240710002306264710004106287710002606328710002106354710004706375710003106422710005206453710001806505710002206523710002606545856003606571 2022 eng d a1476-468700aStroke genetics informs drug discovery and risk prediction across ancestries.0 aStroke genetics informs drug discovery and risk prediction acros c2022 Sep 303 aPrevious genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
1 aMishra, Aniket1 aMalik, Rainer1 aHachiya, Tsuyoshi1 aJürgenson, Tuuli1 aNamba, Shinichi1 aPosner, Daniel, C1 aKamanu, Frederick, K1 aKoido, Masaru1 aLe Grand, Quentin1 aShi, Mingyang1 aHe, Yunye1 aGeorgakis, Marios, K1 aCaro, Ilana1 aKrebs, Kristi1 aLiaw, Yi-Ching1 aVaura, Felix, C1 aLin, Kuang1 aWinsvold, Bendik, Slagsvold1 aSrinivasasainagendra, Vinodh1 aParodi, Livia1 aBae, Hee-Joon1 aChauhan, Ganesh1 aChong, Michael, R1 aTomppo, Liisa1 aAkinyemi, Rufus1 aRoshchupkin, Gennady, V1 aHabib, Naomi1 aJee, Yon, Ho1 aThomassen, Jesper, Qvist1 aAbedi, Vida1 aCárcel-Márquez, Jara1 aNygaard, Marianne1 aLeonard, Hampton, L1 aYang, Chaojie1 aYonova-Doing, Ekaterina1 aKnol, Maria, J1 aLewis, Adam, J1 aJudy, Renae, L1 aAgo, Tetsuro1 aAmouyel, Philippe1 aArmstrong, Nicole, D1 aBakker, Mark, K1 aBartz, Traci, M1 aBennett, David, A1 aBis, Joshua, C1 aBordes, Constance1 aBørte, Sigrid1 aCain, Anael1 aRidker, Paul, M1 aCho, Kelly1 aChen, Zhengming1 aCruchaga, Carlos1 aCole, John, W1 aDe Jager, Phil, L1 ade Cid, Rafael1 aEndres, Matthias1 aFerreira, Leslie, E1 aGeerlings, Mirjam, I1 aGasca, Natalie, C1 aGudnason, Vilmundur1 aHata, Jun1 aHe, Jing1 aHeath, Alicia, K1 aHo, Yuk-Lam1 aHavulinna, Aki, S1 aHopewell, Jemma, C1 aHyacinth, Hyacinth, I1 aInouye, Michael1 aJacob, Mina, A1 aJeon, Christina, E1 aJern, Christina1 aKamouchi, Masahiro1 aKeene, Keith, L1 aKitazono, Takanari1 aKittner, Steven, J1 aKonuma, Takahiro1 aKumar, Amit1 aLacaze, Paul1 aLauner, Lenore, J1 aLee, Keon-Joo1 aLepik, Kaido1 aLi, Jiang1 aLi, Liming1 aManichaikul, Ani1 aMarkus, Hugh, S1 aMarston, Nicholas, A1 aMeitinger, Thomas1 aMitchell, Braxton, D1 aMontellano, Felipe, A1 aMorisaki, Takayuki1 aMosley, Thomas, H1 aNalls, Mike, A1 aNordestgaard, Børge, G1 aO'Donnell, Martin, J1 aOkada, Yukinori1 aOnland-Moret, Charlotte, N1 aOvbiagele, Bruce1 aPeters, Annette1 aPsaty, Bruce, M1 aRich, Stephen, S1 aRosand, Jonathan1 aSabatine, Marc, S1 aSacco, Ralph, L1 aSaleheen, Danish1 aSandset, Else, Charlotte1 aSalomaa, Veikko1 aSargurupremraj, Muralidharan1 aSasaki, Makoto1 aSatizabal, Claudia, L1 aSchmidt, Carsten, O1 aShimizu, Atsushi1 aSmith, Nicholas, L1 aSloane, Kelly, L1 aSutoh, Yoichi1 aSun, Yan, V1 aTanno, Kozo1 aTiedt, Steffen1 aTatlisumak, Turgut1 aTorres-Aguila, Nuria, P1 aTiwari, Hemant, K1 aTrégouët, David-Alexandre1 aTrompet, Stella1 aTuladhar, Anil, Man1 aTybjærg-Hansen, Anne1 avan Vugt, Marion1 aVibo, Riina1 aVerma, Shefali, S1 aWiggins, Kerri, L1 aWennberg, Patrik1 aWoo, Daniel1 aWilson, Peter, W F1 aXu, Huichun1 aYang, Qiong1 aYoon, Kyungheon1 aMillwood, Iona, Y1 aGieger, Christian1 aNinomiya, Toshiharu1 aGrabe, Hans, J1 aJukema, Wouter1 aRissanen, Ina, L1 aStrbian, Daniel1 aKim, Young, Jin1 aChen, Pei-Hsin1 aMayerhofer, Ernst1 aHowson, Joanna, M M1 aIrvin, Marguerite, R1 aAdams, Hieab1 aWassertheil-Smoller, Sylvia1 aChristensen, Kaare1 aIkram, Mohammad, A1 aRundek, Tatjana1 aWorrall, Bradford, B1 aLathrop, Mark, G1 aRiaz, Moeen1 aSimonsick, Eleanor, M1 aKõrv, Janika1 aFrança, Paulo, H C1 aZand, Ramin1 aPrasad, Kameshwar1 aFrikke-Schmidt, Ruth1 ade Leeuw, Frank-Erik1 aLiman, Thomas1 aHaeusler, Karl, Georg1 aRuigrok, Ynte, M1 aHeuschmann, Peter, Ulrich1 aLongstreth, W T1 aJung, Keum, Ji1 aBastarache, Lisa1 aParé, Guillaume1 aDamrauer, Scott, M1 aChasman, Daniel, I1 aRotter, Jerome, I1 aAnderson, Christopher, D1 aZwart, John-Anker1 aNiiranen, Teemu, J1 aFornage, Myriam1 aLiaw, Yung-Po1 aSeshadri, Sudha1 aFernandez-Cadenas, Israel1 aWalters, Robin, G1 aRuff, Christian, T1 aOwolabi, Mayowa, O1 aHuffman, Jennifer, E1 aMilani, Lili1 aKamatani, Yoichiro1 aDichgans, Martin1 aDebette, Stephanie1 aCOMPASS Consortium1 aINVENT Consortium1 aDutch Parelsnoer Initiative (PSI) Cerebrovascular Disease Study Group1 aEstonian Biobank1 aPRECISEQ Consortium1 aFinnGen Consortium1 aNINDS Stroke Genetics Network (SiGN)1 aMEGASTROKE Consortium1 aSIREN Consortium1 aChina Kadoorie Biobank Collaborative Group1 aVA Million Veteran Program1 aInternational Stroke Genetics Consortium (ISGC)1 aBiobank Japan1 aCHARGE Consortium1 aGIGASTROKE Consortium uhttps://chs-nhlbi.org/node/917206073nas a2201597 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2023 eng d a1476-468700aAberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis.0 aAberrant activation of TCL1A promotes stem cell expansion in clo c2023 Apr a755-7630 v6163 aMutations in a diverse set of driver genes increase the fitness of haematopoietic stem cells (HSCs), leading to clonal haematopoiesis. These lesions are precursors for blood cancers, but the basis of their fitness advantage remains largely unknown, partly owing to a paucity of large cohorts in which the clonal expansion rate has been assessed by longitudinal sampling. Here, to circumvent this limitation, we developed a method to infer the expansion rate from data from a single time point. We applied this method to 5,071 people with clonal haematopoiesis. A genome-wide association study revealed that a common inherited polymorphism in the TCL1A promoter was associated with a slower expansion rate in clonal haematopoiesis overall, but the effect varied by driver gene. Those carrying this protective allele exhibited markedly reduced growth rates or prevalence of clones with driver mutations in TET2, ASXL1, SF3B1 and SRSF2, but this effect was not seen in clones with driver mutations in DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 led to the expression of TCL1A protein and the expansion of HSCs in vitro. The protective allele restricted TCL1A expression and expansion of mutant HSCs, as did experimental knockdown of TCL1A expression. Forced expression of TCL1A promoted the expansion of human HSCs in vitro and mouse HSCs in vivo. Our results indicate that the fitness advantage of several commonly mutated driver genes in clonal haematopoiesis may be mediated by TCL1A activation.
10aAlleles10aAnimals10aClonal Hematopoiesis10aGenome-Wide Association Study10aHematopoiesis10aHematopoietic Stem Cells10aHumans10aMice10aMutation10aPromoter Regions, Genetic1 aWeinstock, Joshua, S1 aGopakumar, Jayakrishnan1 aBurugula, Bala, Bharathi1 aUddin, Md, Mesbah1 aJahn, Nikolaus1 aBelk, Julia, A1 aBouzid, Hind1 aDaniel, Bence1 aMiao, Zhuang1 aLy, Nghi1 aMack, Taralynn, M1 aLuna, Sofia, E1 aProthro, Katherine, P1 aMitchell, Shaneice, R1 aLaurie, Cecelia, A1 aBroome, Jai, G1 aTaylor, Kent, D1 aGuo, Xiuqing1 aSinner, Moritz, F1 avon Falkenhausen, Aenne, S1 aKääb, Stefan1 aShuldiner, Alan, R1 aO'Connell, Jeffrey, R1 aLewis, Joshua, P1 aBoerwinkle, Eric1 aBarnes, Kathleen, C1 aChami, Nathalie1 aKenny, Eimear, E1 aLoos, Ruth, J F1 aFornage, Myriam1 aHou, Lifang1 aLloyd-Jones, Donald, M1 aRedline, Susan1 aCade, Brian, E1 aPsaty, Bruce, M1 aBis, Joshua, C1 aBrody, Jennifer, A1 aSilverman, Edwin, K1 aYun, Jeong, H1 aQiao, Dandi1 aPalmer, Nicholette, D1 aFreedman, Barry, I1 aBowden, Donald, W1 aCho, Michael, H1 aDeMeo, Dawn, L1 aVasan, Ramachandran, S1 aYanek, Lisa, R1 aBecker, Lewis, C1 aKardia, Sharon, L R1 aPeyser, Patricia, A1 aHe, Jiang1 aRienstra, Michiel1 aHarst, Pim1 aKaplan, Robert1 aHeckbert, Susan, R1 aSmith, Nicholas, L1 aWiggins, Kerri, L1 aArnett, Donna, K1 aIrvin, Marguerite, R1 aTiwari, Hemant1 aCutler, Michael, J1 aKnight, Stacey1 aMuhlestein, Brent1 aCorrea, Adolfo1 aRaffield, Laura, M1 aGao, Yan1 ade Andrade, Mariza1 aRotter, Jerome, I1 aRich, Stephen, S1 aTracy, Russell, P1 aKonkle, Barbara, A1 aJohnsen, Jill, M1 aWheeler, Marsha, M1 aSmith, Gustav1 aMelander, Olle1 aNilsson, Peter, M1 aCuster, Brian, S1 aDuggirala, Ravindranath1 aCurran, Joanne, E1 aBlangero, John1 aMcGarvey, Stephen1 aWilliams, Keoki1 aXiao, Shujie1 aYang, Mao1 aGu, Charles1 aChen, Yii-Der Ida1 aLee, Wen-Jane1 aMarcus, Gregory, M1 aKane, John, P1 aPullinger, Clive, R1 aShoemaker, Benjamin1 aDarbar, Dawood1 aRoden, Dan, M1 aAlbert, Christine1 aKooperberg, Charles1 aZhou, Ying1 aManson, JoAnn, E1 aDesai, Pinkal1 aJohnson, Andrew, D1 aMathias, Rasika, A1 aBlackwell, Thomas, W1 aAbecasis, Goncalo, R1 aSmith, Albert, V1 aKang, Hyun, M1 aSatpathy, Ansuman, T1 aNatarajan, Pradeep1 aKitzman, Jacob, O1 aWhitsel, Eric, A1 aReiner, Alexander, P1 aBick, Alexander, G1 aJaiswal, Siddhartha1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/938703922nas a2200673 4500008004100000022001400041245014500055210006900200260001600269300001200285520190200297100001302199700001802212700001902230700001902249700001402268700002202282700002302304700002402327700001402351700002702365700002202392700001702414700002502431700001302456700001702469700001502486700002402501700002102525700002102546700002002567700002402587700002302611700002002634700002102654700002002675700002402695700002302719700002702742700002802769700002002797700001402817700002102831700002202852700001902874700002202893700002402915700001602939700002002955700002102975700001702996700002203013700001903035700002603054700001903080700001603099710009703115856003603212 2023 eng d a2047-998000aAssociation Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk.0 aAssociation Between Whole BloodDerived Mitochondrial DNA Copy Nu c2023 Oct 07 ae0290903 aBackground The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04-1.12; <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; =0.11) or in the reverse direction (β=-0.012; =0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (β=-0.084; <0.001), but the reverse direction was not significant (=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=-0.092; <0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.
1 aLiu, Xue1 aSun, Xianbang1 aZhang, Yuankai1 aJiang, Wenqing1 aLai, Meng1 aWiggins, Kerri, L1 aRaffield, Laura, M1 aBielak, Lawrence, F1 aZhao, Wei1 aPitsillides, Achilleas1 aHaessler, Jeffrey1 aZheng, Yinan1 aBlackwell, Thomas, W1 aYao, Jie1 aGuo, Xiuqing1 aQian, Yong1 aThyagarajan, Bharat1 aPankratz, Nathan1 aRich, Stephen, S1 aTaylor, Kent, D1 aPeyser, Patricia, A1 aHeckbert, Susan, R1 aSeshadri, Sudha1 aBoerwinkle, Eric1 aGrove, Megan, L1 aLarson, Nicholas, B1 aSmith, Jennifer, A1 aVasan, Ramachandran, S1 aFitzpatrick, Annette, L1 aFornage, Myriam1 aDing, Jun1 aCarson, April, P1 aAbecasis, Goncalo1 aDupuis, Josée1 aReiner, Alexander1 aKooperberg, Charles1 aHou, Lifang1 aPsaty, Bruce, M1 aWilson, James, G1 aLevy, Daniel1 aRotter, Jerome, I1 aBis, Joshua, C1 aSatizabal, Claudia, L1 aArking, Dan, E1 aLiu, Chunyu1 aTOPMed mtDNA Working Group in NHLBI Trans‐Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/950204492nas a2200649 4500008004100000022001400041245014000055210006900195260001600264520258200280100001902862700001302881700002202894700002502916700001702941700002402958700001402982700001902996700002203015700002703037700002903064700001703093700001903110700002203129700002103151700001903172700002103191700001803212700002203230700001603252700002303268700002203291700001903313700001703332700001903349700002303368700002103391700002203412700002003434700001903454700002403473700002403497700002003521700002103541700002003562700002403582700002303606700002003629700002503649700001903674700002003693700002303713700002803736700001603764700002603780856003603806 2023 eng d a1526-632X00aAssociation of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-analysis of Community-Based Cohorts.0 aAssociation of Mitochondrial DNA Copy Number With Brain MRI Mark c2023 Mar 163 aBACKGROUND AND OBJECTIVES: Previous studies suggest lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer's disease (AD) and AD related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults.
METHODS: We included dementia-free participants from nine diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within ±5 years (i.e., cross-sectional analyses) or 5 to 20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (<60 vs. ≥60 years). Fixed-effects or sample size-weighted meta-analyses were performed to combine results. Finally, we performed Mendelian randomization (MR) analyses to assess causality.
RESULTS: We included up to 19,152 participants (mean age 59 years, 57% women). Higher mtDNA CN was cross-sectionally associated with better general cognitive function (Beta=0.04; 95% CI 0.02, 0.06) independent of age, sex, batch effects, race/ethnicity, time between blood draw and cognitive evaluation, cohort-specific variables, and education. Additional adjustment for blood cell counts or cardiometabolic traits led to slightly attenuated results. We observed similar significant associations with cognition in prospective analyses, although of reduced magnitude. We found no significant associations between mtDNA CN and brain MRI measures in meta-analyses. MR analyses did not reveal a causal relation between mtDNA CN in blood and cognition.
DISCUSSION: Higher mtDNA CN in blood is associated with better current and future general cognitive function in large and diverse communities across the US. Although MR analyses did not support a causal role, additional research is needed to assess causality. Circulating mtDNA CN could serve nevertheless as a biomarker of current and future cognitive function in the community.
1 aZhang, Yuankai1 aLiu, Xue1 aWiggins, Kerri, L1 aKurniansyah, Nuzulul1 aGuo, Xiuqing1 aRodrigue, Amanda, L1 aZhao, Wei1 aYanek, Lisa, R1 aRatliff, Scott, M1 aPitsillides, Achilleas1 aPatiño, Juan, Sebastian1 aSofer, Tamar1 aArking, Dan, E1 aAustin, Thomas, R1 aBeiser, Alexa, S1 aBlangero, John1 aBoerwinkle, Eric1 aBressler, Jan1 aCurran, Joanne, E1 aHou, Lifang1 aHughes, Timothy, M1 aKardia, Sharon, L1 aLauner, Lenore1 aLevy, Daniel1 aMosley, Tom, H1 aNasrallah, Ilya, M1 aRich, Stephen, S1 aRotter, Jerome, I1 aSeshadri, Sudha1 aTarraf, Wassim1 aGonzález, Kevin, A1 aRamachandran, Vasan1 aYaffe, Kristine1 aNyquist, Paul, A1 aPsaty, Bruce, M1 aDeCarli, Charles, S1 aSmith, Jennifer, A1 aGlahn, David, C1 aGonzález, Hector, M1 aBis, Joshua, C1 aFornage, Myriam1 aHeckbert, Susan, R1 aFitzpatrick, Annette, L1 aLiu, Chunyu1 aSatizabal, Claudia, L uhttps://chs-nhlbi.org/node/932303124nas a2200769 4500008004100000022001400041245010100055210006900156260001600225300000900241490000700250520097600257653001901233653001401252653001101266653003801277653003401315653001101349653000901360653003101369653002201400653001701422100002501439700002401464700001901488700002001507700002101527700001901548700002201567700002501589700001801614700001801632700001701650700001901667700001801686700002001704700001301724700001801737700002301755700002301778700001301801700001501814700003201829700002101861700001801882700002201900700001401922700001601936700002701952700002401979700002002003700002402023700001902047700002002066700002102086700002102107700002102128700002202149700001902171700002502190700002302215700001702238700002202255700002402277700001702301856003602318 2023 eng d a2041-172300aEvaluating the use of blood pressure polygenic risk scores across race/ethnic background groups.0 aEvaluating the use of blood pressure polygenic risk scores acros c2023 Jun 02 a32020 v143 aWe assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.
10aBlood Pressure10aEthnicity10aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aMale10aMultifactorial Inheritance10aPopulation Health10aRisk Factors1 aKurniansyah, Nuzulul1 aGoodman, Matthew, O1 aKhan, Alyna, T1 aWang, Jiongming1 aFeofanova, Elena1 aBis, Joshua, C1 aWiggins, Kerri, L1 aHuffman, Jennifer, E1 aKelly, Tanika1 aElfassy, Tali1 aGuo, Xiuqing1 aPalmas, Walter1 aLin, Henry, J1 aHwang, Shih-Jen1 aGao, Yan1 aYoung, Kendra1 aKinney, Gregory, L1 aSmith, Jennifer, A1 aYu, Bing1 aLiu, Simin1 aWassertheil-Smoller, Sylvia1 aManson, JoAnn, E1 aZhu, Xiaofeng1 aChen, Yii-Der Ida1 aLee, I-Te1 aGu, Charles1 aLloyd-Jones, Donald, M1 aZöllner, Sebastian1 aFornage, Myriam1 aKooperberg, Charles1 aCorrea, Adolfo1 aPsaty, Bruce, M1 aArnett, Donna, K1 aIsasi, Carmen, R1 aRich, Stephen, S1 aKaplan, Robert, C1 aRedline, Susan1 aMitchell, Braxton, D1 aFranceschini, Nora1 aLevy, Daniel1 aRotter, Jerome, I1 aMorrison, Alanna, C1 aSofer, Tamar uhttps://chs-nhlbi.org/node/937905138nas a2201357 4500008004100000022001400041245012700055210006900182260001600251300000900267490000700276520124600283653002501529653002701554653001501581653002801596653002401624653003401648653001101682653001701693100002201710700002201732700002601754700001901780700001301799700001801812700002201830700001901852700002001871700002901891700002701920700002401947700001801971700001601989700002202005700001302027700002102040700002002061700001902081700002602100700002402126700001902150700002702169700002002196700002602216700002202242700001902264700002302283700002102306700001902327700001902346700002102365700002702386700002402413700002702437700001502464700002302479700001702502700001902519700002302538700002402561700001702585700003202602700002102634700002502655700002402680700001702704700002302721700002602744700002502770700001802795700002102813700001402834700002402848700002402872700001802896700002902914700001902943700002502962700001802987700002103005700002103026700002203047700001903069700002203088700001703110700002103127700001803148700002203166700001903188700002903207700002803236700002503264700002003289700002203309700002903331700002203360700002303382700001503405700002303420700001803443700002103461700001903482700002203501700001803523700002403541700001803565700002103583700002403604700002203628700002003650700002203670700002803692700002403720856003603744 2023 eng d a2041-172300aGenetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.0 aGenetic architecture of spatial electrical biomarkers for cardia c2023 Mar 14 a14110 v143 aThe 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.
10aArrhythmias, Cardiac10aAtrioventricular Block10aBiomarkers10aCardiovascular Diseases10aElectrocardiography10aGenome-Wide Association Study10aHumans10aRisk Factors1 aYoung, William, J1 aHaessler, Jeffrey1 aBenjamins, Jan-Walter1 aRepetto, Linda1 aYao, Jie1 aIsaacs, Aaron1 aHarper, Andrew, R1 aRamirez, Julia1 aGarnier, Sophie1 aVan Duijvenboden, Stefan1 aBaldassari, Antoine, R1 aConcas, Maria, Pina1 aDuong, ThuyVy1 aFoco, Luisa1 aIsaksen, Jonas, L1 aMei, Hao1 aNoordam, Raymond1 aNursyifa, Casia1 aRichmond, Anne1 aSantolalla, Meddly, L1 aSitlani, Colleen, M1 aSoroush, Negin1 aThériault, Sébastien1 aTrompet, Stella1 aAeschbacher, Stefanie1 aAhmadizar, Fariba1 aAlonso, Alvaro1 aBrody, Jennifer, A1 aCampbell, Archie1 aCorrea, Adolfo1 aDarbar, Dawood1 aDe Luca, Antonio1 aDeleuze, Jean-Francois1 aEllervik, Christina1 aFuchsberger, Christian1 aGoel, Anuj1 aGrace, Christopher1 aGuo, Xiuqing1 aHansen, Torben1 aHeckbert, Susan, R1 aJackson, Rebecca, D1 aKors, Jan, A1 aLima-Costa, Maria, Fernanda1 aLinneberg, Allan1 aMacfarlane, Peter, W1 aMorrison, Alanna, C1 aNavarro, Pau1 aPorteous, David, J1 aPramstaller, Peter, P1 aReiner, Alexander, P1 aRisch, Lorenz1 aSchotten, Ulrich1 aShen, Xia1 aSinagra, Gianfranco1 aSoliman, Elsayed, Z1 aStoll, Monika1 aTarazona-Santos, Eduardo1 aTinker, Andrew1 aTrajanoska, Katerina1 aVillard, Eric1 aWarren, Helen, R1 aWhitsel, Eric, A1 aWiggins, Kerri, L1 aArking, Dan, E1 aAvery, Christy, L1 aConen, David1 aGirotto, Giorgia1 aGrarup, Niels1 aHayward, Caroline1 aJukema, Wouter1 aMook-Kanamori, Dennis, O1 aOlesen, Morten, Salling1 aPadmanabhan, Sandosh1 aPsaty, Bruce, M1 aPattaro, Cristian1 aRibeiro, Antonio, Luiz P1 aRotter, Jerome, I1 aStricker, Bruno, H1 aHarst, Pim1 aDuijn, Cornelia, M1 aVerweij, Niek1 aWilson, James, G1 aOrini, Michele1 aCharron, Philippe1 aWatkins, Hugh1 aKooperberg, Charles1 aLin, Henry, J1 aWilson, James, F1 aKanters, Jørgen, K1 aSotoodehnia, Nona1 aMifsud, Borbala1 aLambiase, Pier, D1 aTereshchenko, Larisa, G1 aMunroe, Patricia, B uhttps://chs-nhlbi.org/node/932204639nas a2201273 4500008004100000022001400041245008500055210006900140260001600209300001300225490000600238520107000244653002301314653001801337653001101355653001601366653001301382653002301395653001401418100002501432700002301457700001901480700002001499700001701519700002301536700002601559700002101585700002101606700002401627700002001651700002101671700002001692700002001712700001901732700001901751700002401770700001901794700002101813700001801834700002001852700002501872700002001897700001901917700002301936700002401959700001801983700001602001700002002017700002202037700001902059700002602078700002302104700002202127700002002149700002702169700002302196700001902219700002102238700001902259700001402278700001902292700002302311700002302334700002202357700002102379700002502400700001902425700001902444700002302463700001302486700002302499700002202522700002102544700002402565700002302589700002102612700002302633700002102656700002802677700002202705700001902727700001902746700001702765700002002782700002302802700001602825700001902841700002202860700001602882700002202898700001802920700002402938700001902962700001502981700002202996700002403018700001803042700002503060700002503085700002103110700001803131700002003149700002303169700002403192700002503216700002303241710006503264856003603329 2023 eng d a2375-254800aThe genetic determinants of recurrent somatic mutations in 43,693 blood genomes.0 agenetic determinants of recurrent somatic mutations in 43693 blo c2023 Apr 28 aeabm49450 v93 aNononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.
10aGerm-Line Mutation10aHematopoiesis10aHumans10aMiddle Aged10aMutation10aMutation, Missense10aPhenotype1 aWeinstock, Joshua, S1 aLaurie, Cecelia, A1 aBroome, Jai, G1 aTaylor, Kent, D1 aGuo, Xiuqing1 aShuldiner, Alan, R1 aO'Connell, Jeffrey, R1 aLewis, Joshua, P1 aBoerwinkle, Eric1 aBarnes, Kathleen, C1 aChami, Nathalie1 aKenny, Eimear, E1 aLoos, Ruth, J F1 aFornage, Myriam1 aRedline, Susan1 aCade, Brian, E1 aGilliland, Frank, D1 aChen, Zhanghua1 aGauderman, James1 aKumar, Rajesh1 aGrammer, Leslie1 aSchleimer, Robert, P1 aPsaty, Bruce, M1 aBis, Joshua, C1 aBrody, Jennifer, A1 aSilverman, Edwin, K1 aYun, Jeong, H1 aQiao, Dandi1 aWeiss, Scott, T1 aLasky-Su, Jessica1 aDeMeo, Dawn, L1 aPalmer, Nicholette, D1 aFreedman, Barry, I1 aBowden, Donald, W1 aCho, Michael, H1 aVasan, Ramachandran, S1 aJohnson, Andrew, D1 aYanek, Lisa, R1 aBecker, Lewis, C1 aKardia, Sharon1 aHe, Jiang1 aKaplan, Robert1 aHeckbert, Susan, R1 aSmith, Nicholas, L1 aWiggins, Kerri, L1 aArnett, Donna, K1 aIrvin, Marguerite, R1 aTiwari, Hemant1 aCorrea, Adolfo1 aRaffield, Laura, M1 aGao, Yan1 ade Andrade, Mariza1 aRotter, Jerome, I1 aRich, Stephen, S1 aManichaikul, Ani, W1 aKonkle, Barbara, A1 aJohnsen, Jill, M1 aWheeler, Marsha, M1 aCuster, Brian, S1 aDuggirala, Ravindranath1 aCurran, Joanne, E1 aBlangero, John1 aGui, Hongsheng1 aXiao, Shujie1 aWilliams, Keoki1 aMeyers, Deborah, A1 aLi, Xingnan1 aOrtega, Victor1 aMcGarvey, Stephen1 aGu, Charles1 aChen, Yii-Der Ida1 aLee, Wen-Jane1 aShoemaker, Benjamin1 aDarbar, Dawood1 aRoden, Dan1 aAlbert, Christine1 aKooperberg, Charles1 aDesai, Pinkal1 aBlackwell, Thomas, W1 aAbecasis, Goncalo, R1 aSmith, Albert, V1 aKang, Hyun, M1 aMathias, Rasika1 aNatarajan, Pradeep1 aJaiswal, Siddhartha1 aReiner, Alexander, P1 aBick, Alexander, G1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/941905739nas a2200901 4500008004100000245012500041210006900166260001600235520316300251100002003414700003103434700002303465700002103488700001803509700001503527700002303542700001303565700001703578700002203595700001803617700001803635700002303653700001503676700002203691700001703713700001803730700002503748700001703773700001803790700002103808700001903829700002203848700002003870700001503890700002003905700001603925700002503941700002403966700001903990700002404009700002404033700002504057700002104082700002404103700002404127700002204151700002004173700002104193700002104214700003004235700002004265700002104285700001204306700002104318700001904339700002004358700001904378700002104397700002304418700002104441700001604462700002504478700002104503700002404524700001904548700002204567700002004589700002304609700002304632700002404655700001904679700002104698700002204719700001804741700002204759700002004781856003604801 2023 eng d00aTime-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus.0 aTimetoEvent GenomeWide Association Study for Incident Cardiovasc c2023 Jul 283 aBACKGROUND: Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD.
METHODS: From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D.
RESULTS: A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance ( <5.0×10 ): rs147138607 (intergenic variant between and ) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 - 1.32, =3.6×10 , rs11444867 (intergenic variant near ) with HR 1.89, 95% CI 1.52 - 2.35, =9.9×10 , and rs335407 (intergenic variant between and ) HR 1.25, 95% CI 1.16 - 1.35, =1.5×10 . Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with <0.05, and 5 were significant after Bonferroni correction ( <0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 - 1.16) per 1 standard deviation increase ( =1.0×10 ).
CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.
CLINICAL PERSPECTIVE: We conducted a large-scale multi-ancestry time-to-event GWAS to identify genetic variants associated with CVD among people with T2D. Three variants were significantly associated with incident CVD in people with T2D: rs147138607 (intergenic variant between and ), rs11444867 (intergenic variant near ), and rs335407 (intergenic variant between and ). A polygenic score composed of known CAD variants identified in the general population was significantly associated with the risk of CVD in people with T2D. There are genetic risk factors specific to T2D that could at least partially explain the excess risk of CVD in people with T2D.In addition, we show that people with T2D have enrichment of known CAD association signals which could also explain the excess risk of CVD.
1 aKwak, Soo, Heon1 aHernandez-Cancela, Ryan, B1 aDiCorpo, Daniel, A1 aCondon, David, E1 aMerino, Jordi1 aWu, Peitao1 aBrody, Jennifer, A1 aYao, Jie1 aGuo, Xiuqing1 aAhmadizar, Fariba1 aMeyer, Mariah1 aSincan, Murat1 aMercader, Josep, M1 aLee, Sujin1 aHaessler, Jeffrey1 aVy, Ha, My T1 aLin, Zhaotong1 aArmstrong, Nicole, D1 aGu, Shaopeng1 aTsao, Noah, L1 aLange, Leslie, A1 aWang, Ningyuan1 aWiggins, Kerri, L1 aTrompet, Stella1 aLiu, Simin1 aLoos, Ruth, J F1 aJudy, Renae1 aSchroeder, Philip, H1 aHasbani, Natalie, R1 aBos, Maxime, M1 aMorrison, Alanna, C1 aJackson, Rebecca, D1 aReiner, Alexander, P1 aManson, JoAnn, E1 aChaudhary, Ninad, S1 aCarmichael, Lynn, K1 aChen, Yii-Der Ida1 aTaylor, Kent, D1 aGhanbari, Mohsen1 avan Meurs, Joyce1 aPitsillides, Achilleas, N1 aPsaty, Bruce, M1 aNoordam, Raymond1 aDo, Ron1 aPark, Kyong, Soo1 aJukema, Wouter1 aKavousi, Maryam1 aCorrea, Adolfo1 aRich, Stephen, S1 aDamrauer, Scott, M1 aHajek, Catherine1 aCho, Nam, H1 aIrvin, Marguerite, R1 aPankow, James, S1 aNadkarni, Girish, N1 aSladek, Robert1 aGoodarzi, Mark, O1 aFlorez, Jose, C1 aChasman, Daniel, I1 aHeckbert, Susan, R1 aKooperberg, Charles1 aDupuis, Josée1 aMalhotra, Rajeev1 ade Vries, Paul, S1 aLiu, Ching-Ti1 aRotter, Jerome, I1 aMeigs, James, B uhttps://chs-nhlbi.org/node/945003549nas a2200541 4500008004100000022001400041245010100055210006900156260001600225300001200241520193400253100002302187700002302210700002402233700001702257700002402274700002002298700002002318700002702338700002402365700001902389700002302408700002402431700002302455700001402478700002102492700002202513700002302535700002402558700002502582700001702607700001802624700002202642700002102664700002302685700002302708700002202731700002102753700002002774700002702794700001402821700002402835700002102859700002302880700002102903710004702924856003602971 2023 eng d a2574-830000aWhole Genome Analysis of Venous Thromboembolism: the Trans-Omics for Precision Medicine Program.0 aWhole Genome Analysis of Venous Thromboembolism the TransOmics f c2023 Mar 24 ae0035323 aBackground Risk for venous thromboembolism has a strong genetic component. Whole genome sequencingfrom the Trans-Omics for Precision Medicine program allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies. Methods The 3793 cases and 7834 controls (11.6% of cases were Black, Hispanic/Latino, or Asian American) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants). Results Single variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only (odds ratio, 6.2 for carriers of rare variants; =7.4×10) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at (odds ratio, 3.8; =1.6×10), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: became significant (minimum =1.8×10 with the secondary filter), while did not (minimum =4.4×10 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, , became significant (=4.4×10 using all missense variants with minor allele frequency <0.0005). Conclusions Here, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel locus and to identify additional rare variation associated with venous thromboembolism.
1 aSeyerle, Amanda, A1 aLaurie, Cecelia, A1 aCoombes, Brandon, J1 aJain, Deepti1 aConomos, Matthew, P1 aBrody, Jennifer1 aChen, Ming-Huei1 aGogarten, Stephanie, M1 aBeutel, Kathleen, M1 aGupta, Namrata1 aHeckbert, Susan, R1 aJackson, Rebecca, D1 aJohnson, Andrew, D1 aKo, Darae1 aManson, JoAnn, E1 aMcKnight, Barbara1 aMetcalf, Ginger, A1 aMorrison, Alanna, C1 aReiner, Alexander, P1 aSofer, Tamar1 aTang, Weihong1 aWiggins, Kerri, L1 aBoerwinkle, Eric1 ade Andrade, Mariza1 aGabriel, Stacey, B1 aGibbs, Richard, A1 aLaurie, Cathy, C1 aPsaty, Bruce, M1 aVasan, Ramachandran, S1 aRice, Ken1 aKooperberg, Charles1 aPankow, James, S1 aSmith, Nicholas, L1 aPankratz, Nathan1 aTrans-Omics for Precision Medicine Program uhttps://chs-nhlbi.org/node/932105493nas a2201573 4500008004100000245011200041210006900153260001600222520100600238100001801244700002301262700002201285700002501307700002001332700001501352700001401367700002001381700002101401700002201422700001401444700001401458700002401472700002101496700002401517700001901541700002901560700002201589700001901611700001801630700002801648700002001676700001901696700001901715700002101734700002401755700001901779700001701798700002801815700001701843700002201860700002301882700002401905700001701929700001801946700002501964700002001989700002102009700001602030700002002046700001602066700001302082700001802095700002402113700001702137700002102154700002402175700002102199700002002220700002002240700001702260700002202277700002802299700002302327700002402350700001702374700002302391700003002414700002602444700002102470700002002491700001902511700002302530700001402553700002402567700002402591700001802615700002802633700002402661700002302685700002202708700002702730700001702757700002102774700002102795700002202816700002202838700002302860700001902883700002302902700001402925700002402939700002102963700002802984700002403012700001903036700002103055700002503076700002103101700002303122700002203145700002203167700002003189700002303209700001403232700002303246700001603269700002503285700002403310700002103334700002503355700001903380700002003399700002303419700002503442700002103467700002203488700002403510700002303534700002003557700002203577700002003599700001803619700002503637700001603662700001603678700002503694700002103719700001803740700002003758700001903778700002103797710006503818856003603883 2023 eng d00aWHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE.0 aWHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES N c2023 Aug 223 aObesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals ( < 5 × 10 ). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the and loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.
1 aZhang, Xinruo1 aBrody, Jennifer, A1 aGraff, Mariaelisa1 aHighland, Heather, M1 aChami, Nathalie1 aXu, Hanfei1 aWang, Zhe1 aFerrier, Kendra1 aChittoor, Geetha1 aJosyula, Navya, S1 aLi, Xihao1 aLi, Zilin1 aAllison, Matthew, A1 aBecker, Diane, M1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBoorgula, Meher, Preethi1 aBowden, Donald, W1 aBroome, Jai, G1 aButh, Erin, J1 aCarlson, Christopher, S1 aChang, Kyong-Mi1 aChavan, Sameer1 aChiu, Yen-Feng1 aChuang, Lee-Ming1 aConomos, Matthew, P1 aDeMeo, Dawn, L1 aDu, Margaret1 aDuggirala, Ravindranath1 aEng, Celeste1 aFohner, Alison, E1 aFreedman, Barry, I1 aGarrett, Melanie, E1 aGuo, Xiuqing1 aHaiman, Chris1 aHeavner, Benjamin, D1 aHidalgo, Bertha1 aHixson, James, E1 aHo, Yuk-Lam1 aHobbs, Brian, D1 aHu, Donglei1 aHui, Qin1 aHwu, Chii-Min1 aJackson, Rebecca, D1 aJain, Deepti1 aKalyani, Rita, R1 aKardia, Sharon, L R1 aKelly, Tanika, N1 aLange, Ethan, M1 aLeNoir, Michael1 aLi, Changwei1 aLe Marchand, Loic1 aMcDonald, Merry-Lynn, N1 aMcHugh, Caitlin, P1 aMorrison, Alanna, C1 aNaseri, Take1 aO'Connell, Jeffrey1 aO'Donnell, Christopher, J1 aPalmer, Nicholette, D1 aPankow, James, S1 aPerry, James, A1 aPeters, Ulrike1 aPreuss, Michael, H1 aRao, D, C1 aRegan, Elizabeth, A1 aReupena, Sefuiva, M1 aRoden, Dan, M1 aRodriguez-Santana, Jose1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aTiwari, Hemant, K1 aVasan, Ramachandran, S1 aWang, Zeyuan1 aWeeks, Daniel, E1 aWessel, Jennifer1 aWiggins, Kerri, L1 aWilkens, Lynne, R1 aWilson, Peter, W F1 aYanek, Lisa, R1 aYoneda, Zachary, T1 aZhao, Wei1 aZöllner, Sebastian1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBlangero, John1 aBoerwinkle, Eric1 aBurchard, Esteban, G1 aCarson, April, P1 aChasman, Daniel, I1 aChen, Yii-Der Ida1 aCurran, Joanne, E1 aFornage, Myriam1 aGordeuk, Victor, R1 aHe, Jiang1 aHeckbert, Susan, R1 aHou, Lifang1 aIrvin, Marguerite, R1 aKooperberg, Charles1 aMinster, Ryan, L1 aMitchell, Braxton, D1 aNouraie, Mehdi1 aPsaty, Bruce, M1 aRaffield, Laura, M1 aReiner, Alexander, P1 aRich, Stephen, S1 aRotter, Jerome, I1 aShoemaker, Benjamin1 aSmith, Nicholas, L1 aTaylor, Kent, D1 aTelen, Marilyn, J1 aWeiss, Scott, T1 aZhang, Yingze1 aCosta, Nancy, Heard-1 aSun, Yan, V1 aLin, Xihong1 aCupples, Adrienne, L1 aLange, Leslie, A1 aLiu, Ching-Ti1 aLoos, Ruth, J F1 aNorth, Kari, E1 aJustice, Anne, E1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/9484