05324nas a2201021 4500008004100000022001400041245012300055210006900178260001300247300001100260490000800271520242700279653001002706653002002716653001902736653001902755653002802774653000902802653002102811653001802832653004002850653002902890653001102919653003302930653003802963653001103001653000903012653001603021653001203037653003603049653001003085653001603095100002203111700002003133700002003153700002003173700001903193700002403212700001703236700002103253700002503274700002103299700001803320700002503338700001903363700002003382700002403402700001803426700002803444700003103472700001903503700001903522700002403541700001603565700002303581700001503604700001903619700002203638700002303660700001903683700002003702700002003722700001803742700002503760700002403785700002003809700002203829700002403851700002303875700002303898700002203921700002003943700002403963700002503987700002104012700002104033700001904054700002004073700002004093700002304113700002504136700001904161700002104180700002204201700002204223700002104245856003604266 2015 eng d a1938-320700aHabitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants.0 aHabitual sleep duration is associated with BMI and macronutrient c2015 Jan a135-430 v1013 a
BACKGROUND: Short sleep duration has been associated with greater risks of obesity, hypertension, diabetes, and cardiovascular disease. Also, common genetic variants in the human Circadian Locomotor Output Cycles Kaput (CLOCK) show associations with ghrelin and total energy intake.
OBJECTIVES: We examined associations between habitual sleep duration, body mass index (BMI), and macronutrient intake and assessed whether CLOCK variants modify these associations.
DESIGN: We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations of sleep duration and BMI and macronutrient intake as percentages of total energy as well as interactions with CLOCK variants from 9 cohort studies including up to 14,906 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.
RESULTS: We observed a significant association between sleep duration and lower BMI (β ± SE = 0.16 ± 0.04, P < 0.0001) in the overall sample; however, associations between sleep duration and relative macronutrient intake were evident in age- and sex-stratified analyses only. We observed a significant association between sleep duration and lower saturated fatty acid intake in younger (aged 20-64 y) adults (men: 0.11 ± 0.06%, P = 0.03; women: 0.10 ± 0.05%, P = 0.04) and with lower carbohydrate (-0.31 ± 0.12%, P < 0.01), higher total fat (0.18 ± 0.09%, P = 0.05), and higher PUFA (0.05 ± 0.02%, P = 0.02) intakes in older (aged 65-80 y) women. In addition, the following 2 nominally significant interactions were observed: between sleep duration and rs12649507 on PUFA intake and between sleep duration and rs6858749 on protein intake.
CONCLUSIONS: Our results indicate that longer habitual sleep duration is associated with lower BMI and age- and sex-specific favorable dietary behaviors. Differences in the relative intake of specific macronutrients associated with short sleep duration could, at least in part, explain previously reported associations between short sleep duration and chronic metabolic abnormalities. In addition, the influence of obesity-associated CLOCK variants on the association between sleep duration and macronutrient intake suggests that longer habitual sleep duration could ameliorate the genetic predisposition to obesity via a favorable dietary profile.
10aAdult10aBody Mass Index10aCLOCK Proteins10aCohort Studies10aCross-Sectional Studies10aDiet10aDietary Proteins10aEnergy Intake10aEuropean Continental Ancestry Group10aFatty Acids, Unsaturated10aFemale10aGene-Environment Interaction10aGenetic Predisposition to Disease10aHumans10aMale10aMiddle Aged10aObesity10aPolymorphism, Single Nucleotide10aSleep10aYoung Adult1 aDashti, Hassan, S1 aFollis, Jack, L1 aSmith, Caren, E1 aTanaka, Toshiko1 aCade, Brian, E1 aGottlieb, Daniel, J1 aHruby, Adela1 aJacques, Paul, F1 aLamon-Fava, Stefania1 aRichardson, Kris1 aSaxena, Richa1 aScheer, Frank, A J L1 aKovanen, Leena1 aBartz, Traci, M1 aPerälä, Mia-Maria1 aJonsson, Anna1 aFrazier-Wood, Alexis, C1 aKalafati, Ioanna-Panagiota1 aMikkilä, Vera1 aPartonen, Timo1 aLemaitre, Rozenn, N1 aLahti, Jari1 aHernandez, Dena, G1 aToft, Ulla1 aJohnson, Craig1 aKanoni, Stavroula1 aRaitakari, Olli, T1 aPerola, Markus1 aPsaty, Bruce, M1 aFerrucci, Luigi1 aGrarup, Niels1 aHighland, Heather, M1 aRallidis, Loukianos1 aKähönen, Mika1 aHavulinna, Aki, S1 aSiscovick, David, S1 aRäikkönen, Katri1 aJørgensen, Torben1 aRotter, Jerome, I1 aDeloukas, Panos1 aViikari, Jorma, S A1 aMozaffarian, Dariush1 aLinneberg, Allan1 aSeppälä, Ilkka1 aHansen, Torben1 aSalomaa, Veikko1 aGharib, Sina, A1 aEriksson, Johan, G1 aBandinelli, Stefania1 aPedersen, Oluf1 aRich, Stephen, S1 aDedoussis, George1 aLehtimäki, Terho1 aOrdovas, Jose, M uhttps://chs-nhlbi.org/node/661406025nas a2201489 4500008004100000022001400041245009200055210006900147260001500216300000900231490000700240520184700247100002002094700002002114700002202134700002002156700002502176700002402201700002602225700002002251700002202271700002002293700001602313700002002329700002302349700002302372700002102395700001902416700002102435700001702456700002102473700001602494700002302510700001602533700002002549700002102569700002102590700002102611700002302632700002402655700002802679700002302707700002002730700002402750700001802774700002202792700002202814700002002836700002002856700001202876700002402888700002402912700001902936700002202955700002202977700002302999700002503022700002403047700001903071700002503090700002003115700001703135700002203152700002203174700001203196700002403208700002103232700001703253700001803270700002803288700001803316700002303334700001903357700002103376700001803397700001903415700002603434700001703460700002403477700002503501700001903526700002303545700001803568700002003586700002303606700002103629700002103650700002103671700002603692700002203718700001903740700002603759700001903785700002003804700002203824700002303846700002403869700002203893700002103915700001903936700002703955700002303982700002604005700001804031700001804049700002804067700002604095700002004121700002404141700002104165700002104186700002304207700002204230700001804252700001604270700002004286700002104306700002004327700002104347700002104368700002204389700001804411700002304429700002504452700002204477856003604499 2016 eng d a1537-660500aExome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits.0 aExome Genotyping Identifies Pleiotropic Variants Associated with c2016 Jul 7 a8-210 v993 aRed blood cell (RBC) traits are important heritable clinical biomarkers and modifiers of disease severity. To identify coding genetic variants associated with these traits, we conducted meta-analyses of seven RBC phenotypes in 130,273 multi-ethnic individuals from studies genotyped on an exome array. After conditional analyses and replication in 27,480 independent individuals, we identified 16 new RBC variants. We found low-frequency missense variants in MAP1A (rs55707100, minor allele frequency [MAF] = 3.3%, p = 2 × 10(-10) for hemoglobin [HGB]) and HNF4A (rs1800961, MAF = 2.4%, p < 3 × 10(-8) for hematocrit [HCT] and HGB). In African Americans, we identified a nonsense variant in CD36 associated with higher RBC distribution width (rs3211938, MAF = 8.7%, p = 7 × 10(-11)) and showed that it is associated with lower CD36 expression and strong allelic imbalance in ex vivo differentiated human erythroblasts. We also identified a rare missense variant in ALAS2 (rs201062903, MAF = 0.2%) associated with lower mean corpuscular volume and mean corpuscular hemoglobin (p < 8 × 10(-9)). Mendelian mutations in ALAS2 are a cause of sideroblastic anemia and erythropoietic protoporphyria. Gene-based testing highlighted three rare missense variants in PKLR, a gene mutated in Mendelian non-spherocytic hemolytic anemia, associated with HGB and HCT (SKAT p < 8 × 10(-7)). These rare, low-frequency, and common RBC variants showed pleiotropy, being also associated with platelet, white blood cell, and lipid traits. Our association results and functional annotation suggest the involvement of new genes in human erythropoiesis. We also confirm that rare and low-frequency variants play a role in the architecture of complex human traits, although their phenotypic effect is generally smaller than originally anticipated.
1 aChami, Nathalie1 aChen, Ming-Huei1 aSlater, Andrew, J1 aEicher, John, D1 aEvangelou, Evangelos1 aTajuddin, Salman, M1 aLove-Gregory, Latisha1 aKacprowski, Tim1 aSchick, Ursula, M1 aNomura, Akihiro1 aGiri, Ayush1 aLessard, Samuel1 aBrody, Jennifer, A1 aSchurmann, Claudia1 aPankratz, Nathan1 aYanek, Lisa, R1 aManichaikul, Ani1 aPazoki, Raha1 aMihailov, Evelin1 aHill, David1 aRaffield, Laura, M1 aBurt, Amber1 aBartz, Traci, M1 aBecker, Diane, M1 aBecker, Lewis, C1 aBoerwinkle, Eric1 aBork-Jensen, Jette1 aBottinger, Erwin, P1 aO'Donoghue, Michelle, L1 aCrosslin, David, R1 ade Denus, Simon1 aDubé, Marie-Pierre1 aElliott, Paul1 aEngström, Gunnar1 aEvans, Michele, K1 aFloyd, James, S1 aFornage, Myriam1 aGao, He1 aGreinacher, Andreas1 aGudnason, Vilmundur1 aHansen, Torben1 aHarris, Tamara, B1 aHayward, Caroline1 aHernesniemi, Jussi1 aHighland, Heather, M1 aHirschhorn, Joel, N1 aHofman, Albert1 aIrvin, Marguerite, R1 aKähönen, Mika1 aLange, Ethan1 aLauner, Lenore, J1 aLehtimäki, Terho1 aLi, Jin1 aLiewald, David, C M1 aLinneberg, Allan1 aLiu, Yongmei1 aLu, Yingchang1 aLyytikäinen, Leo-Pekka1 aMägi, Reedik1 aMathias, Rasika, A1 aMelander, Olle1 aMetspalu, Andres1 aMononen, Nina1 aNalls, Mike, A1 aNickerson, Deborah, A1 aNikus, Kjell1 aO'Donnell, Chris, J1 aOrho-Melander, Marju1 aPedersen, Oluf1 aPetersmann, Astrid1 aPolfus, Linda1 aPsaty, Bruce, M1 aRaitakari, Olli, T1 aRaitoharju, Emma1 aRichard, Melissa1 aRice, Kenneth, M1 aRivadeneira, Fernando1 aRotter, Jerome, I1 aSchmidt, Frank1 aSmith, Albert, Vernon1 aStarr, John, M1 aTaylor, Kent, D1 aTeumer, Alexander1 aThuesen, Betina, H1 aTorstenson, Eric, S1 aTracy, Russell, P1 aTzoulaki, Ioanna1 aZakai, Neil, A1 aVacchi-Suzzi, Caterina1 aDuijn, Cornelia, M1 avan Rooij, Frank, J A1 aCushman, Mary1 aDeary, Ian, J1 aEdwards, Digna, R Velez1 aVergnaud, Anne-Claire1 aWallentin, Lars1 aWaterworth, Dawn, M1 aWhite, Harvey, D1 aWilson, James, G1 aZonderman, Alan, B1 aKathiresan, Sekar1 aGrarup, Niels1 aEsko, Tõnu1 aLoos, Ruth, J F1 aLange, Leslie, A1 aFaraday, Nauder1 aAbumrad, Nada, A1 aEdwards, Todd, L1 aGanesh, Santhi, K1 aAuer, Paul, L1 aJohnson, Andrew, D1 aReiner, Alexander, P1 aLettre, Guillaume uhttps://chs-nhlbi.org/node/713805559nas a2201297 4500008004100000022001400041245013800055210006900193260001500262300001000277490000700287520188700294100002402181700002202205700002002227700002002247700001602267700002302283700001602306700002002322700001202342700002802354700002102382700002102403700002802424700002102452700001702473700002102490700002602511700002302537700002702560700002402587700002502611700001902636700001602655700002002671700002602691700002002717700002402737700002202761700002502783700002102808700001702829700001802846700001902864700002302883700002602906700001702932700001902949700002402968700002102992700002803013700002003041700002003061700002103081700002103102700002303123700001903146700002003165700002003185700001203205700002403217700002403241700002103265700002403286700002103310700002103331700002103352700002003373700002403393700002203417700001903439700001803458700001703476700002203493700002203515700001803537700002103555700002403576700002403600700002103624700002403645700002003669700002603689700002303715700002303738700001803761700001803779700001803797700002203815700002403837700002003861700002003881700002203901700002203923700001903945700002103964700002203985700002004007700001604027700002004043700002104063700001804084700002304102700002104125700001904146700002204165700002004187700001804207856003604225 2016 eng d a1537-660500aLarge-Scale Exome-wide Association Analysis Identifies Loci for White Blood Cell Traits and Pleiotropy with Immune-Mediated Diseases.0 aLargeScale Exomewide Association Analysis Identifies Loci for Wh c2016 Jul 7 a22-390 v993 aWhite blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise healthy individuals can provide insights into genes and biologic pathways involved in production, differentiation, or clearance of particular WBC lineages (myeloid, lymphoid) and also potentially inform the genetic basis of autoimmune, allergic, and blood diseases. We performed an exome array-based meta-analysis of total WBC and subtype counts (neutrophils, monocytes, lymphocytes, basophils, and eosinophils) in a multi-ancestry discovery and replication sample of ∼157,622 individuals from 25 studies. We identified 16 common variants (8 of which were coding variants) associated with one or more WBC traits, the majority of which are pleiotropically associated with autoimmune diseases. Based on functional annotation, these loci included genes encoding surface markers of myeloid, lymphoid, or hematopoietic stem cell differentiation (CD69, CD33, CD87), transcription factors regulating lineage specification during hematopoiesis (ASXL1, IRF8, IKZF1, JMJD1C, ETS2-PSMG1), and molecules involved in neutrophil clearance/apoptosis (C10orf54, LTA), adhesion (TNXB), or centrosome and microtubule structure/function (KIF9, TUBD1). Together with recent reports of somatic ASXL1 mutations among individuals with idiopathic cytopenias or clonal hematopoiesis of undetermined significance, the identification of a common regulatory 3' UTR variant of ASXL1 suggests that both germline and somatic ASXL1 mutations contribute to lower blood counts in otherwise asymptomatic individuals. These association results shed light on genetic mechanisms that regulate circulating WBC counts and suggest a prominent shared genetic architecture with inflammatory and autoimmune diseases.
1 aTajuddin, Salman, M1 aSchick, Ursula, M1 aEicher, John, D1 aChami, Nathalie1 aGiri, Ayush1 aBrody, Jennifer, A1 aHill, David1 aKacprowski, Tim1 aLi, Jin1 aLyytikäinen, Leo-Pekka1 aManichaikul, Ani1 aMihailov, Evelin1 aO'Donoghue, Michelle, L1 aPankratz, Nathan1 aPazoki, Raha1 aPolfus, Linda, M1 aSmith, Albert, Vernon1 aSchurmann, Claudia1 aVacchi-Suzzi, Caterina1 aWaterworth, Dawn, M1 aEvangelou, Evangelos1 aYanek, Lisa, R1 aBurt, Amber1 aChen, Ming-Huei1 avan Rooij, Frank, J A1 aFloyd, James, S1 aGreinacher, Andreas1 aHarris, Tamara, B1 aHighland, Heather, M1 aLange, Leslie, A1 aLiu, Yongmei1 aMägi, Reedik1 aNalls, Mike, A1 aMathias, Rasika, A1 aNickerson, Deborah, A1 aNikus, Kjell1 aStarr, John, M1 aTardif, Jean-Claude1 aTzoulaki, Ioanna1 aEdwards, Digna, R Velez1 aWallentin, Lars1 aBartz, Traci, M1 aBecker, Lewis, C1 aDenny, Joshua, C1 aRaffield, Laura, M1 aRioux, John, D1 aFriedrich, Nele1 aFornage, Myriam1 aGao, He1 aHirschhorn, Joel, N1 aLiewald, David, C M1 aRich, Stephen, S1 aUitterlinden, Andre1 aBastarache, Lisa1 aBecker, Diane, M1 aBoerwinkle, Eric1 ade Denus, Simon1 aBottinger, Erwin, P1 aHayward, Caroline1 aHofman, Albert1 aHomuth, Georg1 aLange, Ethan1 aLauner, Lenore, J1 aLehtimäki, Terho1 aLu, Yingchang1 aMetspalu, Andres1 aO'Donnell, Chris, J1 aQuarells, Rakale, C1 aRichard, Melissa1 aTorstenson, Eric, S1 aTaylor, Kent, D1 aVergnaud, Anne-Claire1 aZonderman, Alan, B1 aCrosslin, David, R1 aDeary, Ian, J1 aDörr, Marcus1 aElliott, Paul1 aEvans, Michele, K1 aGudnason, Vilmundur1 aKähönen, Mika1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aSlater, Andrew, J1 aDehghan, Abbas1 aWhite, Harvey, D1 aGanesh, Santhi, K1 aLoos, Ruth, J F1 aEsko, Tõnu1 aFaraday, Nauder1 aWilson, James, G1 aCushman, Mary1 aJohnson, Andrew, D1 aEdwards, Todd, L1 aZakai, Neil, A1 aLettre, Guillaume1 aReiner, Alex, P1 aAuer, Paul, L uhttps://chs-nhlbi.org/node/714606109nas a2201525 4500008004100000022001400041245009200055210006900147260001500216300001000231490000700241520179700248100002002045700002002065700002002085700002002105700002002125700001902145700002402164700002202188700002202210700002102232700001802253700002302271700001602294700002302310700002102333700002102354700001602375700001702391700001702408700002502425700002102450700001202471700002602483700002302509700002102532700002102553700001602574700002302590700002802613700001702641700002302658700002002681700002102701700001802722700002302740700002202763700001802785700001902803700002602822700002302848700002102871700002302892700002002915700002502935700002002960700002002980700002203000700002403022700002203046700002003068700002103088700002403109700001903133700002403152700002003176700001803196700002403214700002003238700002603258700002203284700002203306700002403328700002803352700002403380700001703404700002203421700002203443700002103465700002503486700002103511700001203532700001703544700002103561700002103582700001803603700002103621700002103642700001603663700002703679700001903706700002303725700002203748700002203770700002503792700001903817700002803836700002403864700002003888700002103908700002003929700002003949700002103969700002003990700001604010700002404026700002204050700001804072700002404090700001704114700001904131700001904150700002604169700002804195700002104223700001904244700002104263700002204284700002204306700002004328700001804348700002004366700002204386700002304408710003804431710003204469710004604501856003604547 2016 eng d a1537-660500aPlatelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals.0 aPlateletRelated Variants Identified by Exomechip Metaanalysis in c2016 Jul 7 a40-550 v993 aPlatelet production, maintenance, and clearance are tightly controlled processes indicative of platelets' important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.
1 aEicher, John, D1 aChami, Nathalie1 aKacprowski, Tim1 aNomura, Akihiro1 aChen, Ming-Huei1 aYanek, Lisa, R1 aTajuddin, Salman, M1 aSchick, Ursula, M1 aSlater, Andrew, J1 aPankratz, Nathan1 aPolfus, Linda1 aSchurmann, Claudia1 aGiri, Ayush1 aBrody, Jennifer, A1 aLange, Leslie, A1 aManichaikul, Ani1 aHill, David1 aPazoki, Raha1 aElliot, Paul1 aEvangelou, Evangelos1 aTzoulaki, Ioanna1 aGao, He1 aVergnaud, Anne-Claire1 aMathias, Rasika, A1 aBecker, Diane, M1 aBecker, Lewis, C1 aBurt, Amber1 aCrosslin, David, R1 aLyytikäinen, Leo-Pekka1 aNikus, Kjell1 aHernesniemi, Jussi1 aKähönen, Mika1 aRaitoharju, Emma1 aMononen, Nina1 aRaitakari, Olli, T1 aLehtimäki, Terho1 aCushman, Mary1 aZakai, Neil, A1 aNickerson, Deborah, A1 aRaffield, Laura, M1 aQuarells, Rakale1 aWiller, Cristen, J1 aPeloso, Gina, M1 aAbecasis, Goncalo, R1 aLiu, Dajiang, J1 aDeloukas, Panos1 aSamani, Nilesh, J1 aSchunkert, Heribert1 aErdmann, Jeanette1 aFornage, Myriam1 aRichard, Melissa1 aTardif, Jean-Claude1 aRioux, John, D1 aDubé, Marie-Pierre1 ade Denus, Simon1 aLu, Yingchang1 aBottinger, Erwin, P1 aLoos, Ruth, J F1 aSmith, Albert, Vernon1 aHarris, Tamara, B1 aLauner, Lenore, J1 aGudnason, Vilmundur1 aEdwards, Digna, R Velez1 aTorstenson, Eric, S1 aLiu, Yongmei1 aTracy, Russell, P1 aRotter, Jerome, I1 aRich, Stephen, S1 aHighland, Heather, M1 aBoerwinkle, Eric1 aLi, Jin1 aLange, Ethan1 aWilson, James, G1 aMihailov, Evelin1 aMägi, Reedik1 aHirschhorn, Joel1 aMetspalu, Andres1 aEsko, Tõnu1 aVacchi-Suzzi, Caterina1 aNalls, Mike, A1 aZonderman, Alan, B1 aEvans, Michele, K1 aEngström, Gunnar1 aOrho-Melander, Marju1 aMelander, Olle1 aO'Donoghue, Michelle, L1 aWaterworth, Dawn, M1 aWallentin, Lars1 aWhite, Harvey, D1 aFloyd, James, S1 aBartz, Traci, M1 aRice, Kenneth, M1 aPsaty, Bruce, M1 aStarr, J, M1 aLiewald, David, C M1 aHayward, Caroline1 aDeary, Ian, J1 aGreinacher, Andreas1 aVölker, Uwe1 aThiele, Thomas1 aVölzke, Henry1 avan Rooij, Frank, J A1 aUitterlinden, André, G1 aFranco, Oscar, H1 aDehghan, Abbas1 aEdwards, Todd, L1 aGanesh, Santhi, K1 aKathiresan, Sekar1 aFaraday, Nauder1 aAuer, Paul, L1 aReiner, Alex, P1 aLettre, Guillaume1 aJohnson, Andrew, D1 aGlobal Lipids Genetics Consortium1 aCARDIoGRAM Exome Consortium1 aMyocardial Infarction Genetics Consortium uhttps://chs-nhlbi.org/node/713903442nas a2200469 4500008004100000022001400041245018400055210006900239260001300308300001200321490000700333520199400340100002202334700002502356700002402381700002502405700002002430700001702450700002402467700002002491700002602511700001302537700002302550700002002573700002702593700001902620700002202639700001902661700002102680700002302701700002002724700002102744700002202765700001702787700002102804700001902825700002702844700002202871700002402893700001902917856003602936 2017 eng d a1556-387100aFine mapping of QT interval regions in global populations refines previously identified QT interval loci and identifies signals unique to African and Hispanic descent populations.0 aFine mapping of QT interval regions in global populations refine c2017 Apr a572-5800 v143 aBACKGROUND: The electrocardiographically measured QT interval (QT) is heritable and its prolongation is an established risk factor for several cardiovascular diseases. Yet, most QT genetic studies have been performed in European ancestral populations, possibly reducing their global relevance.
OBJECTIVE: To leverage diversity and improve biological insight, we fine mapped 16 of the 35 previously identified QT loci (46%) in populations of African American (n = 12,410) and Hispanic/Latino (n = 14,837) ancestry.
METHODS: Racial/ethnic-specific multiple linear regression analyses adjusted for heart rate and clinical covariates were examined separately and in combination after inverse-variance weighted trans-ethnic meta-analysis.
RESULTS: The 16 fine-mapped QT loci included on the Illumina Metabochip represented 21 independent signals, of which 16 (76%) were significantly (P-value≤9.1×10(-5)) associated with QT. Through sequential conditional analysis we also identified three trans-ethnic novel SNPs at ATP1B1, SCN5A-SCN10A, and KCNQ1 and three Hispanic/Latino-specific novel SNPs at NOS1AP and SCN5A-SCN10A (two novel SNPs) with evidence of associations with QT independent of previous identified GWAS lead SNPs. Linkage disequilibrium patterns helped to narrow the region likely to contain the functional variants at several loci, including NOS1AP, USP50-TRPM7, and PRKCA, although intervals surrounding SLC35F1-PLN and CNOT1 remained broad in size (>100 kb). Finally, bioinformatics-based functional characterization suggested a regulatory function in cardiac tissues for the majority of independent signals that generalized and the novel SNPs.
CONCLUSION: Our findings suggest that a majority of identified SNPs implicate gene regulatory dysfunction in QT prolongation, that the same loci influence variation in QT across global populations, and that additional, novel, population-specific QT signals exist.
1 aAvery, Christy, L1 aWassel, Christina, L1 aRichard, Melissa, A1 aHighland, Heather, M1 aBien, Stephanie1 aZubair, Niha1 aSoliman, Elsayed, Z1 aFornage, Myriam1 aBielinski, Suzette, J1 aTao, Ran1 aSeyerle, Amanda, A1 aShah, Sanjiv, J1 aLloyd-Jones, Donald, M1 aBuyske, Steven1 aRotter, Jerome, I1 aPost, Wendy, S1 aRich, Stephen, S1 aHindorff, Lucia, A1 aJeff, Janina, M1 aShohet, Ralph, V1 aSotoodehnia, Nona1 aLin, Dan, Yu1 aWhitsel, Eric, A1 aPeters, Ulrike1 aHaiman, Christopher, A1 aCrawford, Dana, C1 aKooperberg, Charles1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/746304643nas a2200985 4500008004100000022001400041245023800055210006900293260001300362300001200375490000800387520178500395653002002180653001802200653002502218653001102243653001202254100003002266700001502296700002202311700002302333700002202356700002802378700001602406700002502422700002202447700002102469700002002490700002402510700001902534700001702553700002002570700002102590700001302611700001802624700002702642700002102669700002202690700002002712700001602732700001702748700002602765700001902791700001802810700002502828700001502853700002702868700002302895700002502918700001902943700001802962700002402980700002003004700002103024700001703045700001803062700001403080700001703094700001803111700001603129700002003145700001403165700001603179700002003195700002403215700002303239700002203262700002603284700002003310700002203330700001903352700002103371700002103392700002403413700002003437700002503457700002503482700001703507700002003524700001903544700002003563700001903583700001903602856003603621 2017 eng d a1432-120300aTrans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci.0 aTransethnic finemapping of genetic loci for body mass index in t c2017 Jun a771-8000 v1363 aMost body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70 kg/m(2)) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants.
10aBody Mass Index10aEthnic Groups10aGenetics, Population10aHumans10aObesity1 aFernandez-Rhodes, Lindsay1 aGong, Jian1 aHaessler, Jeffrey1 aFranceschini, Nora1 aGraff, Mariaelisa1 aNishimura, Katherine, K1 aWang, Yujie1 aHighland, Heather, M1 aYoneyama, Sachiko1 aBush, William, S1 aGoodloe, Robert1 aRitchie, Marylyn, D1 aCrawford, Dana1 aGross, Myron1 aFornage, Myriam1 aBůzková, Petra1 aTao, Ran1 aIsasi, Carmen1 aAvilés-Santa, Larissa1 aDaviglus, Martha1 aMackey, Rachel, H1 aHouston, Denise1 aGu, Charles1 aEhret, Georg1 aNguyen, Khanh-Dung, H1 aLewis, Cora, E1 aLeppert, Mark1 aIrvin, Marguerite, R1 aLim, Unhee1 aHaiman, Christopher, A1 aLe Marchand, Loïc1 aSchumacher, Fredrick1 aWilkens, Lynne1 aLu, Yingchang1 aBottinger, Erwin, P1 aLoos, Ruth, J L1 aSheu, Wayne, H-H1 aGuo, Xiuqing1 aLee, Wen-Jane1 aHai, Yang1 aHung, Yi-Jen1 aAbsher, Devin1 aWu, I-Chien1 aTaylor, Kent, D1 aLee, I-Te1 aLiu, Yeheng1 aWang, Tzung-Dau1 aQuertermous, Thomas1 aJuang, Jyh-Ming, J1 aRotter, Jerome, I1 aAssimes, Themistocles1 aHsiung, Chao, A1 aChen, Yii-Der Ida1 aPrentice, Ross1 aKuller, Lewis, H1 aManson, JoAnn, E1 aKooperberg, Charles1 aSmokowski, Paul1 aRobinson, Whitney, R1 aGordon-Larsen, Penny1 aLi, Rongling1 aHindorff, Lucia1 aBuyske, Steven1 aMatise, Tara, C1 aPeters, Ulrike1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/746503238nas a2200529 4500008004100000022001400041245012300055210006900178260001600247300000900263490000600272520170300278100002301981700002302004700002002027700002202047700002902069700002402098700002302122700002502145700001202170700002402182700001402206700001502220700001902235700001302254700001702267700002002284700002302304700002202327700001902349700002502368700002002393700002202413700001902435700002102454700002702475700001802502700002302520700002002543700002002563700002202583700002402605700002202629700002102651856003602672 2018 eng d a2045-232200aGenome-wide association study and meta-analysis identify loci associated with ventricular and supraventricular ectopy.0 aGenomewide association study and metaanalysis identify loci asso c2018 Apr 04 a56750 v83 aThe genetic basis of supraventricular and ventricular ectopy (SVE, VE) remains largely uncharacterized, despite established genetic mechanisms of arrhythmogenesis. To identify novel genetic variants associated with SVE/VE in ancestrally diverse human populations, we conducted a genome-wide association study of electrocardiographically identified SVE and VE in five cohorts including approximately 43,000 participants of African, European and Hispanic/Latino ancestry. In thirteen ancestry-stratified subgroups, we tested multivariable-adjusted associations of SVE and VE with single nucleotide polymorphism (SNP) dosage. We combined subgroup-specific association estimates in inverse variance-weighted, fixed-effects and Bayesian meta-analyses. We also combined fixed-effects meta-analytic t-test statistics for SVE and VE in multi-trait SNP association analyses. No loci reached genome-wide significance in trans-ethnic meta-analyses. However, we found genome-wide significant SNPs intronic to an apoptosis-enhancing gene previously associated with QRS interval duration (FAF1; lead SNP rs7545860; effect allele frequency = 0.02; P = 2.0 × 10) in multi-trait analysis among European ancestry participants and near a locus encoding calcium-dependent glycoproteins (DSC3; lead SNP rs8086068; effect allele frequency = 0.17) in meta-analysis of SVE (P = 4.0 × 10) and multi-trait analysis (P = 2.9 × 10) among African ancestry participants. The novel findings suggest several mechanisms by which genetic variation may predispose to ectopy in humans and highlight the potential value of leveraging pleiotropy in future studies of ectopy-related phenotypes.
1 aNapier, Melanie, D1 aFranceschini, Nora1 aGondalia, Rahul1 aStewart, James, D1 aMéndez-Giráldez, Rául1 aSitlani, Colleen, M1 aSeyerle, Amanda, A1 aHighland, Heather, M1 aLi, Yun1 aWilhelmsen, Kirk, C1 aYan, Song1 aDuan, Qing1 aRoach, Jeffrey1 aYao, Jie1 aGuo, Xiuqing1 aTaylor, Kent, D1 aHeckbert, Susan, R1 aRotter, Jerome, I1 aNorth, Kari, E1 aReiner, Alexander, P1 aZhang, Zhu-Ming1 aTinker, Lesley, F1 aLiao, Duanping1 aLaurie, Cathy, C1 aGogarten, Stephanie, M1 aLin, Henry, J1 aBrody, Jennifer, A1 aBartz, Traci, M1 aPsaty, Bruce, M1 aSotoodehnia, Nona1 aSoliman, Elsayed, Z1 aAvery, Christy, L1 aWhitsel, Eric, A uhttps://chs-nhlbi.org/node/766909584nas a2203049 4500008004100000022001400041245011700055210006900172260001300241300001200254490000700266520112500273100002001398700002101418700002101439700001401460700002301474700001901497700001301516700002401529700001901553700002001572700001701592700001801609700001201627700002301639700001201662700001801674700002001692700001801712700001901730700002301749700002001772700001801792700003601810700002001846700002001866700002001886700002301906700003001929700002101959700002001980700002002000700002102020700001202041700002602053700001302079700002002092700002302112700002202135700001902157700002702176700003202203700002102235700002102256700002002277700002402297700002102321700002502342700002102367700002002388700002002408700002402428700002102452700001602473700001802489700001902507700001902526700001602545700001702561700002202578700002302600700002302623700002102646700002302667700001902690700002202709700002202731700001902753700002402772700002402796700002102820700002002841700002202861700002602883700002002909700002502929700002202954700001402976700001502990700002603005700002503031700001503056700002003071700002503091700002303116700002903139700001703168700001903185700002503204700001803229700002203247700002403269700001803293700002103311700001803332700002003350700001703370700001903387700002103406700001803427700001303445700001503458700001803473700002203491700002703513700002103540700001803561700002103579700001903600700002403619700002303643700001803666700002103684700001503705700002103720700002603741700002203767700002103789700002503810700002303835700002003858700002403878700002103902700002503923700001803948700001803966700001803984700002104002700002004023700001904043700001304062700001604075700001704091700002204108700001904130700002104149700002404170700001904194700002404213700002204237700001904259700002004278700002304298700002004321700002004341700002304361700002404384700002204408700002304430700002404453700002204477700002204499700001504521700002204536700002404558700002204582700002504604700002104629700002204650700001904672700002104691700001804712700002204730700002204752700002304774700002504797700002304822700001904845700002004864700002504884700001804909700002004927700002604947700002404973700002504997700002005022700002105042700001605063700002005079700002405099700002805123700001705151700002305168700002205191700002505213700002905238700002305267700001705290700002005307700001905327700002105346700002005367700002205387700002105409700001605430700001805446700001905464700002605483700002205509700002005531700002405551700001905575700002605594700001905620700002005639700001905659700001205678700001505690700001705705700002005722700002305742700002105765700002605786700002805812700002305840700002105863700001905884700002005903700002105923700001905944700002505963700002005988700002406008700002106032700002206053700002806075700002206103700002306125700002506148700002106173700002406194700002106218700001906239700002506258700002206283700002006305700002106325700002106346700002206367700002206389700002206411710002306433710002106456710002106477856003606498 2018 eng d a1546-171800aRefining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.0 aRefining the accuracy of validated target identification through c2018 Apr a559-5710 v503 aWe aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
1 aMahajan, Anubha1 aWessel, Jennifer1 aWillems, Sara, M1 aZhao, Wei1 aRobertson, Neil, R1 aChu, Audrey, Y1 aGan, Wei1 aKitajima, Hidetoshi1 aTaliun, Daniel1 aRayner, William1 aGuo, Xiuqing1 aLu, Yingchang1 aLi, Man1 aJensen, Richard, A1 aHu, Yao1 aHuo, Shaofeng1 aLohman, Kurt, K1 aZhang, Weihua1 aCook, James, P1 aPrins, Bram, Peter1 aFlannick, Jason1 aGrarup, Niels1 aTrubetskoy, Vassily, Vladimirov1 aKravic, Jasmina1 aKim, Young, Jin1 aRybin, Denis, V1 aYaghootkar, Hanieh1 aMüller-Nurasyid, Martina1 aMeidtner, Karina1 aLi-Gao, Ruifang1 aVarga, Tibor, V1 aMarten, Jonathan1 aLi, Jin1 aSmith, Albert, Vernon1 aAn, Ping1 aLigthart, Symen1 aGustafsson, Stefan1 aMalerba, Giovanni1 aDemirkan, Ayse1 aTajes, Juan, Fernandez1 aSteinthorsdottir, Valgerdur1 aWuttke, Matthias1 aLecoeur, Cécile1 aPreuss, Michael1 aBielak, Lawrence, F1 aGraff, Marielisa1 aHighland, Heather, M1 aJustice, Anne, E1 aLiu, Dajiang, J1 aMarouli, Eirini1 aPeloso, Gina, Marie1 aWarren, Helen, R1 aAfaq, Saima1 aAfzal, Shoaib1 aAhlqvist, Emma1 aAlmgren, Peter1 aAmin, Najaf1 aBang, Lia, B1 aBertoni, Alain, G1 aBombieri, Cristina1 aBork-Jensen, Jette1 aBrandslund, Ivan1 aBrody, Jennifer, A1 aBurtt, Noel, P1 aCanouil, Mickaël1 aChen, Yii-Der Ida1 aCho, Yoon Shin1 aChristensen, Cramer1 aEastwood, Sophie, V1 aEckardt, Kai-Uwe1 aFischer, Krista1 aGambaro, Giovanni1 aGiedraitis, Vilmantas1 aGrove, Megan, L1 ade Haan, Hugoline, G1 aHackinger, Sophie1 aHai, Yang1 aHan, Sohee1 aTybjærg-Hansen, Anne1 aHivert, Marie-France1 aIsomaa, Bo1 aJäger, Susanne1 aJørgensen, Marit, E1 aJørgensen, Torben1 aKäräjämäki, AnneMari1 aKim, Bong-Jo1 aKim, Sung, Soo1 aKoistinen, Heikki, A1 aKovacs, Peter1 aKriebel, Jennifer1 aKronenberg, Florian1 aLäll, Kristi1 aLange, Leslie, A1 aLee, Jung-Jin1 aLehne, Benjamin1 aLi, Huaixing1 aLin, Keng-Hung1 aLinneberg, Allan1 aLiu, Ching-Ti1 aLiu, Jun1 aLoh, Marie1 aMägi, Reedik1 aMamakou, Vasiliki1 aMcKean-Cowdin, Roberta1 aNadkarni, Girish1 aNeville, Matt1 aNielsen, Sune, F1 aNtalla, Ioanna1 aPeyser, Patricia, A1 aRathmann, Wolfgang1 aRice, Kenneth1 aRich, Stephen, S1 aRode, Line1 aRolandsson, Olov1 aSchönherr, Sebastian1 aSelvin, Elizabeth1 aSmall, Kerrin, S1 aStančáková, Alena1 aSurendran, Praveen1 aTaylor, Kent, D1 aTeslovich, Tanya, M1 aThorand, Barbara1 aThorleifsson, Gudmar1 aTin, Adrienne1 aTönjes, Anke1 aVarbo, Anette1 aWitte, Daniel, R1 aWood, Andrew, R1 aYajnik, Pranav1 aYao, Jie1 aYengo, Loic1 aYoung, Robin1 aAmouyel, Philippe1 aBoeing, Heiner1 aBoerwinkle, Eric1 aBottinger, Erwin, P1 aChowdhury, Raj1 aCollins, Francis, S1 aDedoussis, George1 aDehghan, Abbas1 aDeloukas, Panos1 aFerrario, Marco, M1 aFerrieres, Jean1 aFlorez, Jose, C1 aFrossard, Philippe1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aHeckbert, Susan, R1 aHowson, Joanna, M M1 aIngelsson, Martin1 aKathiresan, Sekar1 aKee, Frank1 aKuusisto, Johanna1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLindgren, Cecilia, M1 aMännistö, Satu1 aMeitinger, Thomas1 aMelander, Olle1 aMohlke, Karen, L1 aMoitry, Marie1 aMorris, Andrew, D1 aMurray, Alison, D1 ade Mutsert, Renée1 aOrho-Melander, Marju1 aOwen, Katharine, R1 aPerola, Markus1 aPeters, Annette1 aProvince, Michael, A1 aRasheed, Asif1 aRidker, Paul, M1 aRivadineira, Fernando1 aRosendaal, Frits, R1 aRosengren, Anders, H1 aSalomaa, Veikko1 aSheu, Wayne, H-H1 aSladek, Rob1 aSmith, Blair, H1 aStrauch, Konstantin1 aUitterlinden, André, G1 aVarma, Rohit1 aWiller, Cristen, J1 aBlüher, Matthias1 aButterworth, Adam, S1 aChambers, John, Campbell1 aChasman, Daniel, I1 aDanesh, John1 aDuijn, Cornelia1 aDupuis, Josée1 aFranco, Oscar, H1 aFranks, Paul, W1 aFroguel, Philippe1 aGrallert, Harald1 aGroop, Leif1 aHan, Bok-Ghee1 aHansen, Torben1 aHattersley, Andrew, T1 aHayward, Caroline1 aIngelsson, Erik1 aKardia, Sharon, L R1 aKarpe, Fredrik1 aKooner, Jaspal, Singh1 aKöttgen, Anna1 aKuulasmaa, Kari1 aLaakso, Markku1 aLin, Xu1 aLind, Lars1 aLiu, Yongmei1 aLoos, Ruth, J F1 aMarchini, Jonathan1 aMetspalu, Andres1 aMook-Kanamori, Dennis1 aNordestgaard, Børge, G1 aPalmer, Colin, N A1 aPankow, James, S1 aPedersen, Oluf1 aPsaty, Bruce, M1 aRauramaa, Rainer1 aSattar, Naveed1 aSchulze, Matthias, B1 aSoranzo, Nicole1 aSpector, Timothy, D1 aStefansson, Kari1 aStumvoll, Michael1 aThorsteinsdottir, Unnur1 aTuomi, Tiinamaija1 aTuomilehto, Jaakko1 aWareham, Nicholas, J1 aWilson, James, G1 aZeggini, Eleftheria1 aScott, Robert, A1 aBarroso, Inês1 aFrayling, Timothy, M1 aGoodarzi, Mark, O1 aMeigs, James, B1 aBoehnke, Michael1 aSaleheen, Danish1 aMorris, Andrew, P1 aRotter, Jerome, I1 aMcCarthy, Mark, I1 aExomeBP Consortium1 aMAGIC Consortium1 aGIANT Consortium uhttps://chs-nhlbi.org/node/766804013nas a2200685 4500008004100000022001400041245016200055210006900217260001600286300001200302490000800314520192200322100002102244700001702265700002302282700001502305700002202320700002002342700001702362700001602379700001702395700001802412700001202430700002302442700002202465700002302487700002502510700001702535700001802552700001902570700002602589700002002615700002402635700002202659700002102681700002002702700002202722700002102744700001902765700002402784700002002808700002302828700002502851700002502876700002502901700002702926700001902953700002402972700002102996700002203017700002103039700002203060700001903082700002003101710003403121710003603155710003603191710006403227856003603291 2019 eng d a1537-660500aImpact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program.0 aImpact of Rare and Common Genetic Variants on Diabetes Diagnosis c2019 Oct 03 a706-7180 v1053 aHemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.
1 aSarnowski, Chloe1 aLeong, Aaron1 aRaffield, Laura, M1 aWu, Peitao1 ade Vries, Paul, S1 aDiCorpo, Daniel1 aGuo, Xiuqing1 aXu, Huichun1 aLiu, Yongmei1 aZheng, Xiuwen1 aHu, Yao1 aBrody, Jennifer, A1 aGoodarzi, Mark, O1 aHidalgo, Bertha, A1 aHighland, Heather, M1 aJain, Deepti1 aLiu, Ching-Ti1 aNaik, Rakhi, P1 aO'Connell, Jeffrey, R1 aPerry, James, A1 aPorneala, Bianca, C1 aSelvin, Elizabeth1 aWessel, Jennifer1 aPsaty, Bruce, M1 aCurran, Joanne, E1 aPeralta, Juan, M1 aBlangero, John1 aKooperberg, Charles1 aMathias, Rasika1 aJohnson, Andrew, D1 aReiner, Alexander, P1 aMitchell, Braxton, D1 aCupples, Adrienne, L1 aVasan, Ramachandran, S1 aCorrea, Adolfo1 aMorrison, Alanna, C1 aBoerwinkle, Eric1 aRotter, Jerome, I1 aRich, Stephen, S1 aManning, Alisa, K1 aDupuis, Josée1 aMeigs, James, B1 aTOPMed Diabetes Working Group1 aTOPMed Hematology Working Group1 aTOPMed Hemostasis Working Group1 aNational Heart, Lung, and Blood Institute TOPMed Consortium uhttps://chs-nhlbi.org/node/820505763nas a2201477 4500008004100000022001400041245012500055210006900180260001500249300001400264490000800278520153200286653001101818653001501829653002301844653003801867653001801905653003401923653001101957653001501968653005301983653001402036653003602050653001402086653001302100653004302113653002802156653001902184653001802203653002802221100002402249700002302273700002102296700002302317700002902340700002502369700002302394700001602417700002002433700002002453700002402473700001502497700002202512700001902534700002002553700002002573700002302593700002502616700002002641700001802661700001702679700002102696700002802717700001502745700002002760700002302780700002002803700001902823700002102842700001402863700002302877700002202900700002002922700001402942700002002956700001902976700001502995700002503010700001803035700002403053700002003077700002103097700001903118700002103137700002503158700001903183700002003202700002003222700001903242700001503261700001903276700002003295700002003315700002403335700001603359700002303375700002003398700001903418700002403437700001803461700002303479700002203502700002103524700001703545700001203562700002703574700002003601700002103621700002303642700002503665700002403690700001503714700002603729700002303755700001903778700002603797700002203823700002103845700002003866700002003886700002103906700002003927700002203947700002403969700002303993700001404016700002204030700002504052700002704077700001404104700002304118700002504141700001804166710006504184856003604249 2021 eng d a1537-660500aWhole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program.0 aWholegenome sequencing in diverse subjects identifies genetic co c2021 10 07 a1836-18510 v1083 aMany common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.
10aAsthma10aBiomarkers10aDermatitis, Atopic10aGenetic Predisposition to Disease10aGenome, Human10aGenome-Wide Association Study10aHumans10aLeukocytes10aNational Heart, Lung, and Blood Institute (U.S.)10aPhenotype10aPolymorphism, Single Nucleotide10aPrognosis10aProteome10aPulmonary Disease, Chronic Obstructive10aQuantitative Trait Loci10aUnited Kingdom10aUnited States10aWhole Genome Sequencing1 aMikhaylova, Anna, V1 aMcHugh, Caitlin, P1 aPolfus, Linda, M1 aRaffield, Laura, M1 aBoorgula, Meher, Preethi1 aBlackwell, Thomas, W1 aBrody, Jennifer, A1 aBroome, Jai1 aChami, Nathalie1 aChen, Ming-Huei1 aConomos, Matthew, P1 aCox, Corey1 aCurran, Joanne, E1 aDaya, Michelle1 aEkunwe, Lynette1 aGlahn, David, C1 aHeard-Costa, Nancy1 aHighland, Heather, M1 aHobbs, Brian, D1 aIlboudo, Yann1 aJain, Deepti1 aLange, Leslie, A1 aMiller-Fleming, Tyne, W1 aMin, Nancy1 aMoon, Jee-Young1 aPreuss, Michael, H1 aRosen, Jonathon1 aRyan, Kathleen1 aSmith, Albert, V1 aSun, Quan1 aSurendran, Praveen1 ade Vries, Paul, S1 aWalter, Klaudia1 aWang, Zhe1 aWheeler, Marsha1 aYanek, Lisa, R1 aZhong, Xue1 aAbecasis, Goncalo, R1 aAlmasy, Laura1 aBarnes, Kathleen, C1 aBeaty, Terri, H1 aBecker, Lewis, C1 aBlangero, John1 aBoerwinkle, Eric1 aButterworth, Adam, S1 aChavan, Sameer1 aCho, Michael, H1 aChoquet, Helene1 aCorrea, Adolfo1 aCox, Nancy1 aDeMeo, Dawn, L1 aFaraday, Nauder1 aFornage, Myriam1 aGerszten, Robert, E1 aHou, Lifang1 aJohnson, Andrew, D1 aJorgenson, Eric1 aKaplan, Robert1 aKooperberg, Charles1 aKundu, Kousik1 aLaurie, Cecelia, A1 aLettre, Guillaume1 aLewis, Joshua, P1 aLi, Bingshan1 aLi, Yun1 aLloyd-Jones, Donald, M1 aLoos, Ruth, J F1 aManichaikul, Ani1 aMeyers, Deborah, A1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aNgo, Debby1 aNickerson, Deborah, A1 aNongmaithem, Suraj1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aOrtega, Victor, E1 aPankratz, Nathan1 aPerry, James, A1 aPsaty, Bruce, M1 aRich, Stephen, S1 aSoranzo, Nicole1 aRotter, Jerome, I1 aSilverman, Edwin, K1 aSmith, Nicholas, L1 aTang, Hua1 aTracy, Russell, P1 aThornton, Timothy, A1 aVasan, Ramachandran, S1 aZein, Joe1 aMathias, Rasika, A1 aReiner, Alexander, P1 aAuer, Paul, L1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/891401045nas a2200325 4500008004100000022001400041245014300055210006900198260001600267300001200283490000800295653002100303653002100324653001400345653003400359653004100393653001400434653001800448100002400466700002500490700001600515700002300531700002000554700002100574700002000595700002400615700002200639700002200661856003600683 2022 eng d a1524-457100aGenome Wide Association Studies of Variant-by-Thiazide Interaction on Lipids Identifies a Novel Low-Density Lipoprotein Cholesterol Locus.0 aGenome Wide Association Studies of VariantbyThiazide Interaction c2022 Jul 22 a277-2790 v13110aCholesterol, HDL10aCholesterol, LDL10aDiuretics10aGenome-Wide Association Study10aSodium Chloride Symporter Inhibitors10aThiazides10aTriglycerides1 aDownie, Carolina, G1 aHighland, Heather, M1 aLee, Moa, P1 aRaffield, Laura, M1 aPreuss, Michael1 aWhitsel, Eric, A1 aPsaty, Bruce, M1 aSitlani, Colleen, M1 aGraff, Mariaelisa1 aAvery, Christy, L uhttps://chs-nhlbi.org/node/945205141nas a2201381 4500008004100000022001400041245014300055210006900198260001500267300000800282490000600290520117000296653003001466653001201496653001201508653001101520653001201531653005301543653002601596653003601622653002301658653002701681653001801708100002001726700002201746700002201768700002601790700002301816700002501839700001501864700002101879700002501900700001801925700002401943700002201967700002301989700002002012700001702032700002002049700002602069700001902095700002202114700001902136700001702155700001702172700003302189700002102222700001902243700001802262700002602280700002002306700002102326700002302347700002602370700002202396700002402418700002302442700002202465700002002487700002202507700002002529700002502549700002102574700002102595700001802616700001802634700002002652700002102672700002102693700001702714700002102731700003102752700002502783700003402808700002202842700002302864700002102887700001602908700001302924700001402937700002002951700001902971700002102990700001903011700002103030700001903051700002503070700002203095700002803117700001403145700002303159700002403182700001703206700002403223700001503247700002303262700002503285700002503310700002403335700002403359700002003383700001903403700002303422700002003445700002703465700003003492700002003522700002103542700001903563700002103582700002203603700001603625700001903641700002003660700002103680700002203701856003603723 2022 eng d a2399-364200aWhole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program.0 aWhole genome sequence association analysis of fasting glucose an c2022 07 28 a7560 v53 aThe genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.
10aDiabetes Mellitus, Type 210aFasting10aGlucose10aHumans10aInsulin10aNational Heart, Lung, and Blood Institute (U.S.)10aNerve Tissue Proteins10aPolymorphism, Single Nucleotide10aPrecision Medicine10aReceptors, Immunologic10aUnited States1 aDiCorpo, Daniel1 aGaynor, Sheila, M1 aRussell, Emily, M1 aWesterman, Kenneth, E1 aRaffield, Laura, M1 aMajarian, Timothy, D1 aWu, Peitao1 aSarnowski, Chloe1 aHighland, Heather, M1 aJackson, Anne1 aHasbani, Natalie, R1 ade Vries, Paul, S1 aBrody, Jennifer, A1 aHidalgo, Bertha1 aGuo, Xiuqing1 aPerry, James, A1 aO'Connell, Jeffrey, R1 aLent, Samantha1 aMontasser, May, E1 aCade, Brian, E1 aJain, Deepti1 aWang, Heming1 aAlbanus, Ricardo, D'Oliveira1 aVarshney, Arushi1 aYanek, Lisa, R1 aLange, Leslie1 aPalmer, Nicholette, D1 aAlmeida, Marcio1 aPeralta, Juan, M1 aAslibekyan, Stella1 aBaldridge, Abigail, S1 aBertoni, Alain, G1 aBielak, Lawrence, F1 aChen, Chung-Shiuan1 aChen, Yii-Der Ida1 aChoi, Won, Jung1 aGoodarzi, Mark, O1 aFloyd, James, S1 aIrvin, Marguerite, R1 aKalyani, Rita, R1 aKelly, Tanika, N1 aLee, Seonwook1 aLiu, Ching-Ti1 aLoesch, Douglas1 aManson, JoAnn, E1 aMinster, Ryan, L1 aNaseri, Take1 aPankow, James, S1 aRasmussen-Torvik, Laura, J1 aReiner, Alexander, P1 aReupena, Muagututi'a, Sefuiva1 aSelvin, Elizabeth1 aSmith, Jennifer, A1 aWeeks, Daniel, E1 aXu, Huichun1 aYao, Jie1 aZhao, Wei1 aParker, Stephen1 aAlonso, Alvaro1 aArnett, Donna, K1 aBlangero, John1 aBoerwinkle, Eric1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 aDuggirala, Ravindranath1 aHe, Jiang1 aHeckbert, Susan, R1 aKardia, Sharon, L R1 aKim, Ryan, W1 aKooperberg, Charles1 aLiu, Simin1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRedline, Susan1 aShuldiner, Alan, R1 aTaylor, Kent, D1 aVasan, Ramachandran, S1 aViaud-Martinez, Karine, A1 aFlorez, Jose, C1 aWilson, James, G1 aSladek, Robert1 aRich, Stephen, S1 aRotter, Jerome, I1 aLin, Xihong1 aDupuis, Josée1 aMeigs, James, B1 aWessel, Jennifer1 aManning, Alisa, K uhttps://chs-nhlbi.org/node/915805493nas 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