03487nas a2200505 4500008004100000022001400041245012900055210006900184260001300253300001100266490000700277520205800284653000902342653002202351653001502373653002302388653001902411653001102430653001102441653001702452653004602469653001902515653001802534653001402552653000902566653004502575653001702620100001902637700001802656700001802674700002102692700001702713700001702730700002102747700002202768700001702790700001702807700002002824700001702844700002502861700001902886700002002905700002002925856003602945 2014 eng d a1758-535X00aSimple biologically informed inflammatory index of two serum cytokines predicts 10 year all-cause mortality in older adults.0 aSimple biologically informed inflammatory index of two serum cyt c2014 Feb a165-730 v693 a
BACKGROUND: Individual measurements of inflammation have been utilized to assess adverse outcomes risk in older adults with varying degrees of success. This study was designed to identify biologically informed, aggregate measures of inflammation for optimal risk assessment and to inform further biological study of inflammatory pathways.
METHODS: In total, 15 nuclear factor-kappa B-mediated pathway markers of inflammation were first measured in baseline serum samples of 1,155 older participants in the InCHIANTI population. Of these, C-reactive protein, interleukin-1-receptor antagonist, interleukin-6, interleukin-18, and soluble tumor necrosis factor-α receptor-1 were independent predictors of 5-year mortality. These five inflammatory markers were measured in baseline serum samples of 5,600 Cardiovascular Health Study participants. A weighted summary score, the first principal component summary score, and an inflammation index score were developed from these five log-transformed inflammatory markers, and their prediction of 10-year all-cause mortality was evaluated in Cardiovascular Health Study and then validated in InCHIANTI.
RESULTS: The inflammation index score that included interleukin-6 and soluble tumor necrosis factor-α receptor-1 was the best predictor of 10-year all-cause mortality in Cardiovascular Health Study, after adjusting for age, sex, education, race, smoking, and body mass index (hazards ratio = 1.62; 95% CI: 1.54, 1.70) compared with all other single and combined measures. The inflammation index score was also the best predictor of mortality in the InCHIANTI validation study (hazards ratio 1.33; 95% CI: 1.17-1.52). Stratification by sex and CVD status further strengthened the association of inflammation index score with mortality.
CONCLUSION: A simple additive index of serum interleukin-6 and soluble tumor necrosis factor-α receptor-1 best captures the effect of chronic inflammation on mortality in older adults among the 15 biomarkers measured.
10aAged10aAged, 80 and over10aBiomarkers10aC-Reactive Protein10aCohort Studies10aFemale10aHumans10aInflammation10aInterleukin 1 Receptor Antagonist Protein10aInterleukin-1810aInterleukin-610aLongevity10aMale10aReceptors, Tumor Necrosis Factor, Type I10aRisk Factors1 aVaradhan, Ravi1 aYao, Wenliang1 aMatteini, Amy1 aBeamer, Brock, A1 aXue, Qian-Li1 aYang, Huanle1 aManwani, Bhavish1 aReiner, Alexander1 aJenny, Nancy1 aParekh, Neel1 aFallin, Daniele1 aNewman, Anne1 aBandeen-Roche, Karen1 aTracy, Russell1 aFerrucci, Luigi1 aWalston, Jeremy uhttps://chs-nhlbi.org/node/660803753nas a2200601 4500008004100000022001400041245011800055210006900173260001300242300001100255490000700266520199300273653002202266653002502288653001902313653003802332653003402370653001102404653003602415653001702451653001102468100001902479700002002498700002002518700002202538700001802560700001602578700001902594700002302613700002102636700002102657700002302678700002202701700002302723700002302746700002202769700001702791700001602808700002002824700001702844700002202861700002102883700001802904700002002922700002502942700002002967700002402987700002203011700002503033700002003058710003703078856003603115 2015 eng d a1524-462800aMeta-Analysis of Genome-Wide Association Studies Identifies Genetic Risk Factors for Stroke in African Americans.0 aMetaAnalysis of GenomeWide Association Studies Identifies Geneti c2015 Aug a2063-80 v463 aBACKGROUND AND PURPOSE: The majority of genome-wide association studies (GWAS) of stroke have focused on European-ancestry populations; however, none has been conducted in African Americans, despite the disproportionately high burden of stroke in this population. The Consortium of Minority Population Genome-Wide Association Studies of Stroke (COMPASS) was established to identify stroke susceptibility loci in minority populations.
METHODS: Using METAL, we conducted meta-analyses of GWAS in 14 746 African Americans (1365 ischemic and 1592 total stroke cases) from COMPASS, and tested genetic variants with P<10(-6) for validation in METASTROKE, a consortium of ischemic stroke genetic studies in European-ancestry populations. We also evaluated stroke loci previously identified in European-ancestry populations.
RESULTS: The 15q21.3 locus linked with lipid levels and hypertension was associated with total stroke (rs4471613; P=3.9×10(-8)) in African Americans. Nominal associations (P<10(-6)) for total or ischemic stroke were observed for 18 variants in or near genes implicated in cell cycle/mRNA presplicing (PTPRG, CDC5L), platelet function (HPS4), blood-brain barrier permeability (CLDN17), immune response (ELTD1, WDFY4, and IL1F10-IL1RN), and histone modification (HDAC9). Two of these loci achieved nominal significance in METASTROKE: 5q35.2 (P=0.03), and 1p31.1 (P=0.018). Four of 7 previously reported ischemic stroke loci (PITX2, HDAC9, CDKN2A/CDKN2B, and ZFHX3) were nominally associated (P<0.05) with stroke in COMPASS.
CONCLUSIONS: We identified a novel genetic variant associated with total stroke in African Americans and found that ischemic stroke loci identified in European-ancestry populations may also be relevant for African Americans. Our findings support investigation of diverse populations to identify and characterize genetic risk factors, and the importance of shared genetic risk across populations.
10aAfrican Americans10aCase-Control Studies10aCohort Studies10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aPolymorphism, Single Nucleotide10aRisk Factors10aStroke1 aCarty, Cara, L1 aKeene, Keith, L1 aCheng, Yu-Ching1 aMeschia, James, F1 aChen, Wei-Min1 aNalls, Mike1 aBis, Joshua, C1 aKittner, Steven, J1 aRich, Stephen, S1 aTajuddin, Salman1 aZonderman, Alan, B1 aEvans, Michele, K1 aLangefeld, Carl, D1 aGottesman, Rebecca1 aMosley, Thomas, H1 aShahar, Eyal1 aWoo, Daniel1 aYaffe, Kristine1 aLiu, Yongmei1 aSale, Michèle, M1 aDichgans, Martin1 aMalik, Rainer1 aLongstreth, W T1 aMitchell, Braxton, D1 aPsaty, Bruce, M1 aKooperberg, Charles1 aReiner, Alexander1 aWorrall, Bradford, B1 aFornage, Myriam1 aCOMPASS and METASTROKE Consortia uhttps://chs-nhlbi.org/node/681202728nas a2200241 4500008004100000022001400041245010300055210006900158260001600227520198200243100002202225700002002247700001902267700002102286700002202307700001802329700001702347700001802364700002402382700002402406700002002430856003602450 2016 ENG d a1468-201X00aAssociation of inflammatory, lipid and mineral markers with cardiac calcification in older adults.0 aAssociation of inflammatory lipid and mineral markers with cardi c2016 Jul 133 aOBJECTIVE: Calcification of the aortic valve and adjacent structures involves inflammatory, lipid and mineral metabolism pathways. We hypothesised that circulating biomarkers reflecting these pathways are associated with cardiac calcification in older adults.
METHODS: We investigated the associations of various biomarkers with valvular and annular calcification in the Cardiovascular Health Study. Of the 5888 participants, up to 3585 were eligible after exclusions for missing biomarker, covariate or echocardiographic data. We evaluated analytes reflecting lipid (lipoprotein (Lp) (a), Lp-associated phospholipase A2 (LpPLA2) mass and activity), inflammatory (interleukin-6, soluble (s) CD14) and mineral metabolism (fetuin-A, fibroblast growth factor (FGF)-23) pathways that were measured within 5 years of echocardiography. The relationships of plasma biomarkers with aortic valve calcification (AVC), aortic annular calcification (AAC) and mitral annular calcification (MAC) were assessed with relative risk (RR) regression.
RESULTS: Calcification was prevalent: AVC 59%, AAC 45% and MAC 41%. After adjustment, Lp(a), LpPLA2 mass and activity and sCD14 were positively associated with AVC. RRs for AVC per SD (95% CI) were as follows: Lp(a), 1.051 (1.022 to 1.081); LpPLA2 mass, 1.036 (1.006 to 1.066) and LpPLA2 activity, 1.037 (1.004 to 1.071); sCD14, 1.039 (1.005 to 1.073). FGF-23 was positively associated with MAC, 1.040 (1.004 to 1.078) and fetuin-A was negatively associated, 0.949 (0.911 to 0.989). No biomarkers were significantly associated with AAC.
CONCLUSION: This study shows novel associations of circulating FGF-23 and fetuin-A with MAC, and LpPLA2 and sCD14 with AVC, confirming that previously reported for Lp(a). Further investigation of Lp and inflammatory pathways may provide added insight into the aetiology of AVC, while study of phosphate regulation may illuminate the pathogenesis of MAC.
1 aBortnick, Anna, E1 aBartz, Traci, M1 aIx, Joachim, H1 aChonchol, Michel1 aReiner, Alexander1 aCushman, Mary1 aOwens, David1 aBarasch, Eddy1 aSiscovick, David, S1 aGottdiener, John, S1 aKizer, Jorge, R uhttps://chs-nhlbi.org/node/712002329nas a2200301 4500008004100000022001400041245010500055210006900160260001500229490000700244520139300251653001101644653003401655653001301689653003901702653002801741100001701769700001401786700001401800700001901814700001901833700002201852700002301874700001701897700001201914710006501926856003601991 2022 eng d a1477-405400aeSCAN: scan regulatory regions for aggregate association testing using whole-genome sequencing data.0 aeSCAN scan regulatory regions for aggregate association testing c2022 01 170 v233 aMultiple statistical methods for aggregate association testing have been developed for whole-genome sequencing (WGS) data. Many aggregate variants in a given genomic window and ignore existing knowledge to define test regions, resulting in many identified regions not clearly linked to genes, and thus, limiting biological understanding. Functional information from new technologies (such as Hi-C and its derivatives), which can help link enhancers to their effector genes, can be leveraged to predefine variant sets for aggregate testing in WGS data. Here, we propose the eSCAN (scan the enhancers) method for genome-wide assessment of enhancer regions in sequencing studies, combining the advantages of dynamic window selection in SCANG (SCAN the Genome), a previously developed method, with the advantages of incorporating putative regulatory regions from annotation. eSCAN, by searching in putative enhancers, increases statistical power and aids mechanistic interpretation, as demonstrated by extensive simulation studies. We also apply eSCAN for blood cell traits using NHLBI Trans-Omics for Precision Medicine WGS data. Results from real data analysis show that eSCAN is able to capture more significant signals, and these signals are of shorter length (indicating higher resolution fine-mapping capability) and drive association of larger regions detected by other methods.
10aGenome10aGenome-Wide Association Study10aGenomics10aRegulatory Sequences, Nucleic Acid10aWhole Genome Sequencing1 aYang, Yingxi1 aSun, Quan1 aHuang, Le1 aBroome, Jai, G1 aCorrea, Adolfo1 aReiner, Alexander1 aRaffield, Laura, M1 aYang, Yuchen1 aLi, Yun1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/911303922nas 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/950207212nas a2201753 4500008004100000245012700041210006900168260001600237520220800253100002502461700001902486700001602505700001902521700002302540700001902563700002302582700002102605700001802626700002002644700002402664700002302688700002902711700002302740700002002763700002102783700002102804700002102825700002402846700002202870700001902892700001502911700002102926700002002947700001802967700001902985700002103004700002503025700002603050700002103076700001903097700001903116700002803135700002203163700002203185700001903207700002003226700001803246700001703264700001503281700002003296700002803316700001703344700001703361700002703378700002503405700002003430700002003450700002003470700002403490700001203514700001603526700002003542700002803562700001603590700002103606700001903627700002103646700002703667700002103694700002403715700001603739700002203755700002403777700002503801700001703826700001403843700002103857700002003878700002203898700001903920700002003939700001503959700002003974700002203994700002404016700002004040700001804060700002004078700002704098700001804125700001704143700002104160700001604181700001804197700002404215700002004239700002004259700002604279700001904305700002004324700002304344700002304367700002504390700002004415700003004435700001804465700002304483700001804506700002104524700001904545700002004564700001804584700001904602700002304621700002204644700002004666700001904686700002204705700002004727700001904747700002304766700002104789700002004810700002304830700002504853700002904878700002904907700001904936700002604955700001904981700002205000700002005022700002405042700002005066700001705086700001805103700002105121700001305142700003205155700002305187700002205210700002205232700002505254700002405279700002305303710003105326710006505357856003605422 2023 eng d00aWhole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles.0 aWhole genome analysis of plasma fibrinogen reveals populationdif c2023 Jun 123 aUNLABELLED: Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three ( , and signals contain predicted deleterious missense variants. Two loci, and , each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits ( ), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation.
KEY POINTS: Largest and most diverse genetic study of plasma fibrinogen identifies 54 regions (18 novel), housing 69 conditionally distinct variants (20 novel).Sufficient power achieved to identify signal driven by African population variant.Links to (1) liver enzyme, blood cell and lipid genetic signals, (2) liver regulatory elements, and (3) thrombotic and inflammatory disease.
1 aHuffman, Jennifer, E1 aNicolas, Jayna1 aHahn, Julie1 aHeath, Adam, S1 aRaffield, Laura, M1 aYanek, Lisa, R1 aBrody, Jennifer, A1 aThibord, Florian1 aAlmasy, Laura1 aBartz, Traci, M1 aBielak, Lawrence, F1 aBowler, Russell, P1 aCarrasquilla, Germán, D1 aChasman, Daniel, I1 aChen, Ming-Huei1 aEmmert, David, B1 aGhanbari, Mohsen1 aHaessle, Jeffery1 aHottenga, Jouke-Jan1 aKleber, Marcus, E1 aLe, Ngoc-Quynh1 aLee, Jiwon1 aLewis, Joshua, P1 aLi-Gao, Ruifang1 aLuan, Jian'an1 aMalmberg, Anni1 aMangino, Massimo1 aMarioni, Riccardo, E1 aMartinez-Perez, Angel1 aPankratz, Nathan1 aPolasek, Ozren1 aRichmond, Anne1 aRodriguez, Benjamin, At1 aRotter, Jerome, I1 aSteri, Maristella1 aSuchon, Pierre1 aTrompet, Stella1 aWeiss, Stefan1 aZare, Marjan1 aAuer, Paul1 aCho, Michael, H1 aChristofidou, Paraskevi1 aDavies, Gail1 ade Geus, Eco1 aDeleuze, Jean-Francois1 aDelgado, Graciela, E1 aEkunwe, Lynette1 aFaraday, Nauder1 aGögele, Martin1 aGreinacher, Andreas1 aHe, Gao1 aHoward, Tom1 aJoshi, Peter, K1 aKilpeläinen, Tuomas, O1 aLahti, Jari1 aLinneberg, Allan1 aNaitza, Silvia1 aNoordam, Raymond1 aPaüls-Vergés, Ferran1 aRich, Stephen, S1 aRosendaal, Frits, R1 aRudan, Igor1 aRyan, Kathleen, A1 aSouto, Juan, Carlos1 avan Rooij, Frank, Ja1 aWang, Heming1 aZhao, Wei1 aBecker, Lewis, C1 aBeswick, Andrew1 aBrown, Michael, R1 aCade, Brian, E1 aCampbell, Harry1 aCho, Kelly1 aCrapo, James, D1 aCurran, Joanne, E1 ade Maat, Moniek, Pm1 aDoyle, Margaret1 aElliott, Paul1 aFloyd, James, S1 aFuchsberger, Christian1 aGrarup, Niels1 aGuo, Xiuqing1 aHarris, Sarah, E1 aHou, Lifang1 aKolcic, Ivana1 aKooperberg, Charles1 aMenni, Cristina1 aNauck, Matthias1 aO'Connell, Jeffrey, R1 aOrrù, Valeria1 aPsaty, Bruce, M1 aRäikkönen, Katri1 aSmith, Jennifer, A1 aSoria, José, Manuel1 aStott, David, J1 aVlieg, Astrid, van Hylcka1 aWatkins, Hugh1 aWillemsen, Gonneke1 aWilson, Peter1 aBen-Shlomo, Yoav1 aBlangero, John1 aBoomsma, Dorret1 aCox, Simon, R1 aDehghan, Abbas1 aEriksson, Johan, G1 aFiorillo, Edoardo1 aFornage, Myriam1 aHansen, Torben1 aHayward, Caroline1 aIkram, Arfan, M1 aJukema, Wouter1 aKardia, Sharon, Lr1 aLange, Leslie, A1 aMärz, Winfried1 aMathias, Rasika, A1 aMitchell, Braxton, D1 aMook-Kanamori, Dennis, O1 aMorange, Pierre-Emmanuel1 aPedersen, Oluf1 aPramstaller, Peter, P1 aRedline, Susan1 aReiner, Alexander1 aRidker, Paul, M1 aSilverman, Edwin, K1 aSpector, Tim, D1 aVölker, Uwe1 aWareham, Nick1 aWilson, James, F1 aYao, Jie1 aTrégouët, David-Alexandre1 aJohnson, Andrew, D1 aWolberg, Alisa, S1 ade Vries, Paul, S1 aSabater-Lleal, Maria1 aMorrison, Alanna, C1 aSmith, Nicholas, L1 aVA Million Veteran Program1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/9449