@article {1371, title = {Associations between incident ischemic stroke events and stroke and cardiovascular disease-related genome-wide association studies single nucleotide polymorphisms in the Population Architecture Using Genomics and Epidemiology study.}, journal = {Circ Cardiovasc Genet}, volume = {5}, year = {2012}, month = {2012 Apr 01}, pages = {210-6}, abstract = {

BACKGROUND: Genome-wide association studies (GWAS) have identified loci associated with ischemic stroke (IS) and cardiovascular disease (CVD) in European-descent individuals, but their replication in different populations has been largely unexplored.

METHODS AND RESULTS: Nine single nucleotide polymorphisms (SNPs) selected from GWAS and meta-analyses of stroke, and 86 SNPs previously associated with myocardial infarction and CVD risk factors, including blood lipids (high density lipoprotein [HDL], low density lipoprotein [LDL], and triglycerides), type 2 diabetes, and body mass index (BMI), were investigated for associations with incident IS in European Americans (EA) N=26 276, African-Americans (AA) N=8970, and American Indians (AI) N=3570 from the Population Architecture using Genomics and Epidemiology Study. Ancestry-specific fixed effects meta-analysis with inverse variance weighting was used to combine study-specific log hazard ratios from Cox proportional hazards models. Two of 9 stroke SNPs (rs783396 and rs1804689) were significantly associated with [corrected] IS hazard in AA; none were significant in this large EA cohort. Of 73 CVD risk factor SNPs tested in EA, 2 (HDL and triglycerides SNPs) were associated with IS. In AA, SNPs associated with LDL, HDL, and BMI were significantly associated with IS (3 of 86 SNPs tested). Out of 58 SNPs tested in AI, 1 LDL SNP was significantly associated with IS.

CONCLUSIONS: Our analyses showing lack of replication in spite of reasonable power for many stroke SNPs and differing results by ancestry highlight the need to follow up on GWAS findings and conduct genetic association studies in diverse populations. We found modest IS associations with BMI and lipids SNPs, though these findings require confirmation.

}, keywords = {Aged, Aged, 80 and over, Cardiovascular Diseases, Cholesterol, HDL, Cholesterol, LDL, European Continental Ancestry Group, Female, Genetics, Population, Genome-Wide Association Study, Genomics, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, Stroke, Triglycerides}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.111.962191}, author = {Carty, Cara L and B{\r u}zkov{\'a}, Petra and Fornage, Myriam and Franceschini, Nora and Cole, Shelley and Heiss, Gerardo and Hindorff, Lucia A and Howard, Barbara V and Mann, Sue and Martin, Lisa W and Zhang, Ying and Matise, Tara C and Prentice, Ross and Reiner, Alexander P and Kooperberg, Charles} } @article {6067, title = {Best practices and joint calling of the HumanExome BeadChip: the CHARGE Consortium.}, journal = {PLoS One}, volume = {8}, year = {2013}, month = {2013}, pages = {e68095}, abstract = {

Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77\% were concordant, 0.14\% had missing data, and 0.09\% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip.

}, keywords = {Aging, Alleles, Cluster Analysis, Cohort Studies, Continental Population Groups, Exome, Female, Gene Frequency, Genomics, Genotype, Heart, Humans, Male, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Sample Size, Self Report, Sequence Analysis, DNA}, issn = {1932-6203}, doi = {10.1371/journal.pone.0068095}, author = {Grove, Megan L and Yu, Bing and Cochran, Barbara J and Haritunians, Talin and Bis, Joshua C and Taylor, Kent D and Hansen, Mark and Borecki, Ingrid B and Cupples, L Adrienne and Fornage, Myriam and Gudnason, Vilmundur and Harris, Tamara B and Kathiresan, Sekar and Kraaij, Robert and Launer, Lenore J and Levy, Daniel and Liu, Yongmei and Mosley, Thomas and Peloso, Gina M and Psaty, Bruce M and Rich, Stephen S and Rivadeneira, Fernando and Siscovick, David S and Smith, Albert V and Uitterlinden, Andre and van Duijn, Cornelia M and Wilson, James G and O{\textquoteright}Donnell, Christopher J and Rotter, Jerome I and Boerwinkle, Eric} } @article {6290, title = {Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {BMC Med Genet}, volume = {14}, year = {2013}, month = {2013 Sep 25}, pages = {98}, abstract = {

BACKGROUND: Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S.

METHODS: As part of the {\textquoteright}Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites.

RESULTS: Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 {\texttimes} 10-15), versus 3/9 in AA (p= 0.03 to 6 {\texttimes} 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only.

CONCLUSIONS: Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.

}, keywords = {Adaptor Proteins, Signal Transducing, Adult, African Americans, Aged, Alleles, Asian Continental Ancestry Group, Blood Glucose, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Genomics, Hispanic Americans, Humans, Indians, North American, Insulin, Male, Middle Aged, Polymorphism, Single Nucleotide, Transcription Factor 7-Like 2 Protein}, issn = {1471-2350}, doi = {10.1186/1471-2350-14-98}, author = {Fesinmeyer, Megan D and Meigs, James B and North, Kari E and Schumacher, Fredrick R and B{\r u}zkov{\'a}, Petra and Franceschini, Nora and Haessler, Jeffrey and Goodloe, Robert and Spencer, Kylee L and Voruganti, Venkata Saroja and Howard, Barbara V and Jackson, Rebecca and Kolonel, Laurence N and Liu, Simin and Manson, JoAnn E and Monroe, Kristine R and Mukamal, Kenneth and Dilks, Holli H and Pendergrass, Sarah A and Nato, Andrew and Wan, Peggy and Wilkens, Lynne R and Le Marchand, Lo{\"\i}c and Ambite, Jose Luis and Buyske, Steven and Florez, Jose C and Crawford, Dana C and Hindorff, Lucia A and Haiman, Christopher A and Peters, Ulrike and Pankow, James S} } @article {6283, title = {Whole-genome sequence-based analysis of high-density lipoprotein cholesterol.}, journal = {Nat Genet}, volume = {45}, year = {2013}, month = {2013 Aug}, pages = {899-901}, abstract = {

We describe initial steps for interrogating whole-genome sequence data to characterize the genetic architecture of a complex trait, levels of high-density lipoprotein cholesterol (HDL-C). We report whole-genome sequencing and analysis of 962 individuals from the Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) studies. From this analysis, we estimate that common variation contributes more to heritability of HDL-C levels than rare variation, and screening for mendelian variants for dyslipidemia identified individuals with extreme HDL-C levels. Whole-genome sequencing analyses highlight the value of regulatory and non-protein-coding regions of the genome in addition to protein-coding regions.

}, keywords = {Cholesterol, HDL, Computational Biology, Databases, Genetic, Genetic Variation, Genome, Human, Genome-Wide Association Study, Genomics, Heterozygote, Humans, Open Reading Frames}, issn = {1546-1718}, doi = {10.1038/ng.2671}, author = {Morrison, Alanna C and Voorman, Arend and Johnson, Andrew D and Liu, Xiaoming and Yu, Jin and Li, Alexander and Muzny, Donna and Yu, Fuli and Rice, Kenneth and Zhu, Chengsong and Bis, Joshua and Heiss, Gerardo and O{\textquoteright}Donnell, Christopher J and Psaty, Bruce M and Cupples, L Adrienne and Gibbs, Richard and Boerwinkle, Eric} } @article {6580, title = {ADAM19 and HTR4 variants and pulmonary function: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {350-8}, abstract = {

BACKGROUND: The pulmonary function measures of forced expiratory volume in 1 second (FEV1) and its ratio to forced vital capacity (FVC) are used in the diagnosis and monitoring of lung diseases and predict cardiovascular mortality in the general population. Genome-wide association studies (GWASs) have identified numerous loci associated with FEV1 and FEV1/FVC, but the causal variants remain uncertain. We hypothesized that novel or rare variants poorly tagged by GWASs may explain the significant associations between FEV1/FVC and 2 genes: ADAM19 and HTR4.

METHODS AND RESULTS: We sequenced ADAM19 and its promoter region along with the ≈21-kb portion of HTR4 harboring GWAS single-nucleotide polymorphisms for pulmonary function and analyzed associations with FEV1/FVC among 3983 participants of European ancestry from Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Meta-analysis of common variants in each region identified statistically significant associations (316 tests; P<1.58{\texttimes}10(-4)) with FEV1/FVC for 14 ADAM19 single-nucleotide polymorphisms and 24 HTR4 single-nucleotide polymorphisms. After conditioning on the sentinel GWASs hit in each gene (ADAM19 rs1422795, minor allele frequency=0.33 and HTR4 rs11168048, minor allele frequency=0.40], 1 single-nucleotide polymorphism remained statistically significant (ADAM19 rs13155908, minor allele frequency=0.12; P=1.56{\texttimes}10(-4)). Analysis of rare variants (minor allele frequency <1\%) using sequence kernel association test did not identify associations with either region.

CONCLUSIONS: Sequencing identified 1 common variant associated with FEV1/FVC independent of the sentinel ADAM19 GWAS hit and supports the original HTR4 GWAS findings. Rare variants do not seem to underlie GWAS associations with pulmonary function for common variants in ADAM19 and HTR4.

}, keywords = {ADAM Proteins, Aged, Aged, 80 and over, Aging, Cohort Studies, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Lung, Male, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000066}, author = {London, Stephanie J and Gao, Wei and Gharib, Sina A and Hancock, Dana B and Wilk, Jemma B and House, John S and Gibbs, Richard A and Muzny, Donna M and Lumley, Thomas and Franceschini, Nora and North, Kari E and Psaty, Bruce M and Kovar, Christie L and Coresh, Josef and Zhou, Yanhua and Heckbert, Susan R and Brody, Jennifer A and Morrison, Alanna C and Dupuis, Jos{\'e}e} } @article {6555, title = {Association of levels of fasting glucose and insulin with rare variants at the chromosome 11p11.2-MADD locus: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {374-382}, abstract = {

BACKGROUND: Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3, and SPI1, has been associated in genome-wide association studies with fasting glucose and insulin (FI). In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study, we sequenced 5 gene regions at 11p11.2 to identify rare, potentially functional variants influencing fasting glucose or FI levels.

METHODS AND RESULTS: Sequencing (mean depth, 38{\texttimes}) across 16.1 kb in 3566 individuals without diabetes mellitus identified 653 variants, 79.9\% of which were rare (minor allele frequency <1\%) and novel. We analyzed rare variants in 5 gene regions with FI or fasting glucose using the sequence kernel association test. At NR1H3, 53 rare variants were jointly associated with FI (P=2.73{\texttimes}10(-3)); of these, 7 were predicted to have regulatory function and showed association with FI (P=1.28{\texttimes}10(-3)). Conditioning on 2 previously associated variants at MADD (rs7944584, rs10838687) did not attenuate this association, suggesting that there are >2 independent signals at 11p11.2. One predicted regulatory variant, chr11:47227430 (hg18; minor allele frequency=0.00068), contributed 20.6\% to the overall sequence kernel association test score at NR1H3, lies in intron 2 of NR1H3, and is a predicted binding site for forkhead box A1 (FOXA1), a transcription factor associated with insulin regulation. In human HepG2 hepatoma cells, the rare chr11:47227430 A allele disrupted FOXA1 binding and reduced FOXA1-dependent transcriptional activity.

CONCLUSIONS: Sequencing at 11p11.2-NR1H3 identified rare variation associated with FI. One variant, chr11:47227430, seems to be functional, with the rare A allele reducing transcription factor FOXA1 binding and FOXA1-dependent transcriptional activity.

}, keywords = {Aged, Aged, 80 and over, Aging, Blood Glucose, Chromosomes, Human, Pair 11, Cohort Studies, Death Domain Receptor Signaling Adaptor Proteins, Diabetes Mellitus, Type 2, Fasting, Female, Gene Frequency, Genetic Variation, Genome-Wide Association Study, Genomics, Guanine Nucleotide Exchange Factors, Heart Diseases, Humans, Insulin, Male, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000169}, author = {Cornes, Belinda K and Brody, Jennifer A and Nikpoor, Naghmeh and Morrison, Alanna C and Chu, Huan and Ahn, Byung Soo and Wang, Shuai and Dauriz, Marco and Barzilay, Joshua I and Dupuis, Jos{\'e}e and Florez, Jose C and Coresh, Josef and Gibbs, Richard A and Kao, W H Linda and Liu, Ching-Ti and McKnight, Barbara and Muzny, Donna and Pankow, James S and Reid, Jeffrey G and White, Charles C and Johnson, Andrew D and Wong, Tien Y and Psaty, Bruce M and Boerwinkle, Eric and Rotter, Jerome I and Siscovick, David S and Sladek, Robert and Meigs, James B} } @article {6567, title = {Genome-wide association study of plasma N6 polyunsaturated fatty acids within the cohorts for heart and aging research in genomic epidemiology consortium.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {321-331}, abstract = {

BACKGROUND: Omega6 (n6) polyunsaturated fatty acids (PUFAs) and their metabolites are involved in cell signaling, inflammation, clot formation, and other crucial biological processes. Genetic components, such as variants of fatty acid desaturase (FADS) genes, determine the composition of n6 PUFAs.

METHODS AND RESULTS: To elucidate undiscovered biological pathways that may influence n6 PUFA composition, we conducted genome-wide association studies and meta-analyses of associations of common genetic variants with 6 plasma n6 PUFAs in 8631 white adults (55\% women) across 5 prospective studies. Plasma phospholipid or total plasma fatty acids were analyzed by similar gas chromatography techniques. The n6 fatty acids linoleic acid (LA), γ-linolenic acid (GLA), dihomo-GLA, arachidonic acid, and adrenic acid were expressed as percentage of total fatty acids. We performed linear regression with robust SEs to test for single-nucleotide polymorphism-fatty acid associations, with pooling using inverse-variance-weighted meta-analysis. Novel regions were identified on chromosome 10 associated with LA (rs10740118; P=8.1{\texttimes}10(-9); near NRBF2), on chromosome 16 with LA, GLA, dihomo-GLA, and arachidonic acid (rs16966952; P=1.2{\texttimes}10(-15), 5.0{\texttimes}10(-11), 7.6{\texttimes}10(-65), and 2.4{\texttimes}10(-10), respectively; NTAN1), and on chromosome 6 with adrenic acid after adjustment for arachidonic acid (rs3134950; P=2.1{\texttimes}10(-10); AGPAT1). We confirmed previous findings of the FADS cluster on chromosome 11 with LA and arachidonic acid, and further observed novel genome-wide significant association of this cluster with GLA, dihomo-GLA, and adrenic acid (P=2.3{\texttimes}10(-72), 2.6{\texttimes}10(-151), and 6.3{\texttimes}10(-140), respectively).

CONCLUSIONS: Our findings suggest that along with the FADS gene cluster, additional genes may influence n6 PUFA composition.

}, keywords = {Adult, Aged, Aged, 80 and over, Aging, Chromosomes, Human, Pair 10, Chromosomes, Human, Pair 16, Chromosomes, Human, Pair 6, Fatty Acid Desaturases, Fatty Acids, Omega-6, Female, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Prospective Studies, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000208}, author = {Guan, Weihua and Steffen, Brian T and Lemaitre, Rozenn N and Wu, Jason H Y and Tanaka, Toshiko and Manichaikul, Ani and Foy, Millennia and Rich, Stephen S and Wang, Lu and Nettleton, Jennifer A and Tang, Weihong and Gu, Xiangjun and Bandinelli, Stafania and King, Irena B and McKnight, Barbara and Psaty, Bruce M and Siscovick, David and Djouss{\'e}, Luc and Chen, Yii-Der Ida and Ferrucci, Luigi and Fornage, Myriam and Mozafarrian, Dariush and Tsai, Michael Y and Steffen, Lyn M} } @article {6667, title = {No evidence for genome-wide interactions on plasma fibrinogen by smoking, alcohol consumption and body mass index: results from meta-analyses of 80,607 subjects.}, journal = {PLoS One}, volume = {9}, year = {2014}, month = {2014}, pages = {e111156}, abstract = {

Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI). Genome-wide association studies (GWAS) have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2 {\texttimes} 10(-8). This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.

}, keywords = {Alcohol Drinking, Body Mass Index, Fibrinogen, Gene-Environment Interaction, Genomics, Humans, Smoking}, issn = {1932-6203}, doi = {10.1371/journal.pone.0111156}, author = {Baumert, Jens and Huang, Jie and McKnight, Barbara and Sabater-Lleal, Maria and Steri, Maristella and Chu, Audrey Y and Trompet, Stella and Lopez, Lorna M and Fornage, Myriam and Teumer, Alexander and Tang, Weihong and Rudnicka, Alicja R and M{\"a}larstig, Anders and Hottenga, Jouke-Jan and Kavousi, Maryam and Lahti, Jari and Tanaka, Toshiko and Hayward, Caroline and Huffman, Jennifer E and Morange, Pierre-Emmanuel and Rose, Lynda M and Basu, Saonli and Rumley, Ann and Stott, David J and Buckley, Brendan M and de Craen, Anton J M and Sanna, Serena and Masala, Marco and Biffar, Reiner and Homuth, Georg and Silveira, Angela and Sennblad, Bengt and Goel, Anuj and Watkins, Hugh and M{\"u}ller-Nurasyid, Martina and R{\"u}ckerl, Regina and Taylor, Kent and Chen, Ming-Huei and de Geus, Eco J C and Hofman, Albert and Witteman, Jacqueline C M and de Maat, Moniek P M and Palotie, Aarno and Davies, Gail and Siscovick, David S and Kolcic, Ivana and Wild, Sarah H and Song, Jaejoon and McArdle, Wendy L and Ford, Ian and Sattar, Naveed and Schlessinger, David and Grotevendt, Anne and Franzosi, Maria Grazia and Illig, Thomas and Waldenberger, Melanie and Lumley, Thomas and Tofler, Geoffrey H and Willemsen, Gonneke and Uitterlinden, Andr{\'e} G and Rivadeneira, Fernando and R{\"a}ikk{\"o}nen, Katri and Chasman, Daniel I and Folsom, Aaron R and Lowe, Gordon D and Westendorp, Rudi G J and Slagboom, P Eline and Cucca, Francesco and Wallaschofski, Henri and Strawbridge, Rona J and Seedorf, Udo and Koenig, Wolfgang and Bis, Joshua C and Mukamal, Kenneth J and van Dongen, Jenny and Widen, Elisabeth and Franco, Oscar H and Starr, John M and Liu, Kiang and Ferrucci, Luigi and Polasek, Ozren and Wilson, James F and Oudot-Mellakh, Tiphaine and Campbell, Harry and Navarro, Pau and Bandinelli, Stefania and Eriksson, Johan and Boomsma, Dorret I and Dehghan, Abbas and Clarke, Robert and Hamsten, Anders and Boerwinkle, Eric and Jukema, J Wouter and Naitza, Silvia and Ridker, Paul M and V{\"o}lzke, Henry and Deary, Ian J and Reiner, Alexander P and Tr{\'e}gou{\"e}t, David-Alexandre and O{\textquoteright}Donnell, Christopher J and Strachan, David P and Peters, Annette and Smith, Nicholas L} } @article {6579, title = {Sequence variation in TMEM18 in association with body mass index: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {344-9}, abstract = {

BACKGROUND: Genome-wide association studies for body mass index (BMI) previously identified a locus near TMEM18. We conducted targeted sequencing of this region to investigate the role of common, low-frequency, and rare variants influencing BMI.

METHODS AND RESULTS: We sequenced TMEM18 and regions downstream of TMEM18 on chromosome 2 in 3976 individuals of European ancestry from 3 community-based cohorts (Atherosclerosis Risk in Communities, Cardiovascular Health Study, and Framingham Heart Study), including 200 adults selected for high BMI. We examined the association between BMI and variants identified in the region from nucleotide position 586 432 to 677 539 (hg18). Rare variants (minor allele frequency, <1\%) were analyzed using a burden test and the sequence kernel association test. Results from the 3 cohort studies were meta-analyzed. We estimate that mean BMI is 0.43 kg/m(2) higher for each copy of the G allele of single-nucleotide polymorphism rs7596758 (minor allele frequency, 29\%; P=3.46{\texttimes}10(-4)) using a Bonferroni threshold of P<4.6{\texttimes}10(-4). Analyses conditional on previous genome-wide association study single-nucleotide polymorphisms associated with BMI in the region led to attenuation of this signal and uncovered another independent (r(2)<0.2), statistically significant association, rs186019316 (P=2.11{\texttimes}10(-4)). Both rs186019316 and rs7596758 or proxies are located in transcription factor binding regions. No significant association with rare variants was found in either the exons of TMEM18 or the 3{\textquoteright} genome-wide association study region.

CONCLUSIONS: Targeted sequencing around TMEM18 identified 2 novel BMI variants with possible regulatory function.

}, keywords = {Adult, Aged, Aging, Body Mass Index, Cohort Studies, Female, Genetic Association Studies, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Male, Membrane Proteins, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Young Adult}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.13.000067}, author = {Liu, Ching-Ti and Young, Kristin L and Brody, Jennifer A and Olden, Matthias and Wojczynski, Mary K and Heard-Costa, Nancy and Li, Guo and Morrison, Alanna C and Muzny, Donna and Gibbs, Richard A and Reid, Jeffrey G and Shao, Yaming and Zhou, Yanhua and Boerwinkle, Eric and Heiss, Gerardo and Wagenknecht, Lynne and McKnight, Barbara and Borecki, Ingrid B and Fox, Caroline S and North, Kari E and Cupples, L Adrienne} } @article {6547, title = {Sequencing of 2 subclinical atherosclerosis candidate regions in 3669 individuals: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {359-64}, abstract = {

BACKGROUND: Atherosclerosis, the precursor to coronary heart disease and stroke, is characterized by an accumulation of fatty cells in the arterial intimal-medial layers. Common carotid intima media thickness (cIMT) and plaque are subclinical atherosclerosis measures that predict cardiovascular disease events. Previously, genome-wide association studies demonstrated evidence for association with cIMT (SLC17A4) and plaque (PIK3CG).

METHODS AND RESULTS: We sequenced 120 kb around SLC17A4 (6p22.2) and 251 kb around PIK3CG (7q22.3) among 3669 European ancestry participants from the Atherosclerosis Risk in Communities (ARIC) study, Cardiovascular Health Study (CHS), and Framingham Heart Study (FHS) in Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Primary analyses focused on 438 common variants (minor allele frequency >=1\%), which were independently meta-analyzed. A 3{\textquoteright} untranslated region CCDC71L variant (rs2286149), upstream from PIK3CG, was the most significant finding in cIMT (P=0.00033) and plaque (P=0.0004) analyses. A SLC17A4 intronic variant was also associated with cIMT (P=0.008). Both were in low linkage disequilibrium with the genome-wide association study single nucleotide polymorphisms. Gene-based tests including T1 count and sequence kernel association test for rare variants (minor allele frequency <1\%) did not yield statistically significant associations. However, we observed nominal associations for rare variants in CCDC71L and SLC17A3 with cIMT and of the entire 7q22 region with plaque (P=0.05).

CONCLUSIONS: Common and rare variants in PIK3CG and SLC17A4 regions demonstrated modest association with subclinical atherosclerosis traits. Although not conclusive, these findings may help to understand the genetic architecture of regions previously implicated by genome-wide association studies and identify variants within these regions for further investigation in larger samples.

}, keywords = {Aged, Aged, 80 and over, Aging, Atherosclerosis, Class Ib Phosphatidylinositol 3-Kinase, Cohort Studies, European Continental Ancestry Group, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Sodium-Phosphate Cotransporter Proteins, Type I}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000116}, author = {Bis, Joshua C and White, Charles C and Franceschini, Nora and Brody, Jennifer and Zhang, Xiaoling and Muzny, Donna and Santibanez, Jireh and Gibbs, Richard and Liu, Xiaoming and Lin, Honghuang and Boerwinkle, Eric and Psaty, Bruce M and North, Kari E and Cupples, L Adrienne and O{\textquoteright}Donnell, Christopher J} } @article {6583, title = {Sequencing of SCN5A identifies rare and common variants associated with cardiac conduction: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {365-73}, abstract = {

BACKGROUND: The cardiac sodium channel SCN5A regulates atrioventricular and ventricular conduction. Genetic variants in this gene are associated with PR and QRS intervals. We sought to characterize further the contribution of rare and common coding variation in SCN5A to cardiac conduction.

METHODS AND RESULTS: In Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study, we performed targeted exonic sequencing of SCN5A (n=3699, European ancestry individuals) and identified 4 common (minor allele frequency >1\%) and 157 rare variants. Common and rare SCN5A coding variants were examined for association with PR and QRS intervals through meta-analysis of European ancestry participants from CHARGE, National Heart, Lung, and Blood Institute{\textquoteright}s Exome Sequencing Project (n=607), and the UK10K (n=1275) and by examining Exome Sequencing Project African ancestry participants (n=972). Rare coding SCN5A variants in aggregate were associated with PR interval in European and African ancestry participants (P=1.3{\texttimes}10(-3)). Three common variants were associated with PR and QRS interval duration among European ancestry participants and one among African ancestry participants. These included 2 well-known missense variants: rs1805124 (H558R) was associated with PR and QRS shortening in European ancestry participants (P=6.25{\texttimes}10(-4) and P=5.2{\texttimes}10(-3), respectively) and rs7626962 (S1102Y) was associated with PR shortening in those of African ancestry (P=2.82{\texttimes}10(-3)). Among European ancestry participants, 2 novel synonymous variants, rs1805126 and rs6599230, were associated with cardiac conduction. Our top signal, rs1805126 was associated with PR and QRS lengthening (P=3.35{\texttimes}10(-7) and P=2.69{\texttimes}10(-4), respectively) and rs6599230 was associated with PR shortening (P=2.67{\texttimes}10(-5)).

CONCLUSIONS: By sequencing SCN5A, we identified novel common and rare coding variants associated with cardiac conduction.

}, keywords = {Adult, Aged, Aged, 80 and over, Aging, Cohort Studies, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Conduction System, Heart Diseases, Humans, Male, Middle Aged, NAV1.5 Voltage-Gated Sodium Channel, Polymorphism, Single Nucleotide, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000098}, author = {Magnani, Jared W and Brody, Jennifer A and Prins, Bram P and Arking, Dan E and Lin, Honghuang and Yin, Xiaoyan and Liu, Ching-Ti and Morrison, Alanna C and Zhang, Feng and Spector, Tim D and Alonso, Alvaro and Bis, Joshua C and Heckbert, Susan R and Lumley, Thomas and Sitlani, Colleen M and Cupples, L Adrienne and Lubitz, Steven A and Soliman, Elsayed Z and Pulit, Sara L and Newton-Cheh, Christopher and O{\textquoteright}Donnell, Christopher J and Ellinor, Patrick T and Benjamin, Emelia J and Muzny, Donna M and Gibbs, Richard A and Santibanez, Jireh and Taylor, Herman A and Rotter, Jerome I and Lange, Leslie A and Psaty, Bruce M and Jackson, Rebecca and Rich, Stephen S and Boerwinkle, Eric and Jamshidi, Yalda and Sotoodehnia, Nona} } @article {6578, title = {Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {335-43}, abstract = {

BACKGROUND: Genome-wide association studies have identified thousands of genetic variants that influence a variety of diseases and health-related quantitative traits. However, the causal variants underlying the majority of genetic associations remain unknown. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study aims to follow up genome-wide association study signals and identify novel associations of the allelic spectrum of identified variants with cardiovascular-related traits.

METHODS AND RESULTS: The study included 4231 participants from 3 CHARGE cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, and the Framingham Heart Study. We used a case-cohort design in which we selected both a random sample of participants and participants with extreme phenotypes for each of 14 traits. We sequenced and analyzed 77 genomic loci, which had previously been associated with >=1 of 14 phenotypes. A total of 52 736 variants were characterized by sequencing and passed our stringent quality control criteria. For common variants (minor allele frequency >=1\%), we performed unweighted regression analyses to obtain P values for associations and weighted regression analyses to obtain effect estimates that accounted for the sampling design. For rare variants, we applied 2 approaches: collapsed aggregate statistics and joint analysis of variants using the sequence kernel association test.

CONCLUSIONS: We sequenced 77 genomic loci in participants from 3 cohorts. We established a set of filters to identify high-quality variants and implemented statistical and bioinformatics strategies to analyze the sequence data and identify potentially functional variants within genome-wide association study loci.

}, keywords = {Adult, Aged, Aged, 80 and over, Aging, Cohort Studies, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Research Design, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000350}, author = {Lin, Honghuang and Wang, Min and Brody, Jennifer A and Bis, Joshua C and Dupuis, Jos{\'e}e and Lumley, Thomas and McKnight, Barbara and Rice, Kenneth M and Sitlani, Colleen M and Reid, Jeffrey G and Bressler, Jan and Liu, Xiaoming and Davis, Brian C and Johnson, Andrew D and O{\textquoteright}Donnell, Christopher J and Kovar, Christie L and Dinh, Huyen and Wu, Yuanqing and Newsham, Irene and Chen, Han and Broka, Andi and DeStefano, Anita L and Gupta, Mayetri and Lunetta, Kathryn L and Liu, Ching-Ti and White, Charles C and Xing, Chuanhua and Zhou, Yanhua and Benjamin, Emelia J and Schnabel, Renate B and Heckbert, Susan R and Psaty, Bruce M and Muzny, Donna M and Cupples, L Adrienne and Morrison, Alanna C and Boerwinkle, Eric} } @article {6860, title = {Integrative pathway genomics of lung function and airflow obstruction.}, journal = {Hum Mol Genet}, volume = {24}, year = {2015}, month = {2015 Dec 1}, pages = {6836-48}, abstract = {

Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signaling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analyzed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10{\textquoteright}s role in influencing lung{\textquoteright}s susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unraveled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung disease.

}, keywords = {Airway Obstruction, Animals, Cell Proliferation, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Immune System, Lung, Male, Metabolic Networks and Pathways, Mice, Phenotype, Polymorphism, Single Nucleotide, Signal Transduction}, issn = {1460-2083}, doi = {10.1093/hmg/ddv378}, author = {Gharib, Sina A and Loth, Daan W and Soler Artigas, Maria and Birkland, Timothy P and Wilk, Jemma B and Wain, Louise V and Brody, Jennifer A and Obeidat, Ma{\textquoteright}en and Hancock, Dana B and Tang, Wenbo and Rawal, Rajesh and Boezen, H Marike and Imboden, Medea and Huffman, Jennifer E and Lahousse, Lies and Alves, Alexessander C and Manichaikul, Ani and Hui, Jennie and Morrison, Alanna C and Ramasamy, Adaikalavan and Smith, Albert Vernon and Gudnason, Vilmundur and Surakka, Ida and Vitart, Veronique and Evans, David M and Strachan, David P and Deary, Ian J and Hofman, Albert and Gl{\"a}ser, Sven and Wilson, James F and North, Kari E and Zhao, Jing Hua and Heckbert, Susan R and Jarvis, Deborah L and Probst-Hensch, Nicole and Schulz, Holger and Barr, R Graham and Jarvelin, Marjo-Riitta and O{\textquoteright}Connor, George T and K{\"a}h{\"o}nen, Mika and Cassano, Patricia A and Hysi, Pirro G and Dupuis, Jos{\'e}e and Hayward, Caroline and Psaty, Bruce M and Hall, Ian P and Parks, William C and Tobin, Martin D and London, Stephanie J} } @article {8564, title = {A hybrid computational strategy to address WGS variant analysis in >5000 samples.}, journal = {BMC Bioinformatics}, volume = {17}, year = {2016}, month = {2016 Sep 10}, pages = {361}, abstract = {

BACKGROUND: The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS environment and supercomputers also have limitations due to which large scale joint variant calling becomes infeasible, and infrastructure specific variant calling strategies either fail to scale up to large datasets or abandon joint calling strategies.

RESULTS: We present a high throughput framework including multiple variant callers for single nucleotide variant (SNV) calling, which leverages hybrid computing infrastructure consisting of cloud AWS, supercomputers and local high performance computing infrastructures. We present a novel binning approach for large scale joint variant calling and imputation which can scale up to over 10,000 samples while producing SNV callsets with high sensitivity and specificity. As a proof of principle, we present results of analysis on Cohorts for Heart And Aging Research in Genomic Epidemiology (CHARGE) WGS freeze 3 dataset in which joint calling, imputation and phasing of over 5300 whole genome samples was produced in under 6 weeks using four state-of-the-art callers. The callers used were SNPTools, GATK-HaplotypeCaller, GATK-UnifiedGenotyper and GotCloud. We used Amazon AWS, a 4000-core in-house cluster at Baylor College of Medicine, IBM power PC Blue BioU at Rice and Rhea at Oak Ridge National Laboratory (ORNL) for the computation. AWS was used for joint calling of 180~TB of BAM files, and ORNL and Rice supercomputers were used for the imputation and phasing step. All other steps were carried out on the local compute cluster. The entire operation used 5.2 million core hours and only transferred a total of 6~TB of data across the platforms.

CONCLUSIONS: Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low coverage data can be accomplished in a scalable, cost effective and fast manner by using heterogeneous computing platforms without compromising on the quality of variants.

}, keywords = {Databases, Genetic, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans}, issn = {1471-2105}, doi = {10.1186/s12859-016-1211-6}, author = {Huang, Zhuoyi and Rustagi, Navin and Veeraraghavan, Narayanan and Carroll, Andrew and Gibbs, Richard and Boerwinkle, Eric and Venkata, Manjunath Gorentla and Yu, Fuli} } @article {9194, title = {Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors.}, journal = {Circulation}, volume = {146}, year = {2022}, month = {2022 Oct 18}, pages = {1225-1242}, abstract = {

BACKGROUND: 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.

}, keywords = {Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Thrombosis, Venous Thromboembolism}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.122.059675}, author = {Thibord, Florian and Klarin, Derek and Brody, Jennifer A and Chen, Ming-Huei and Levin, Michael G and Chasman, Daniel I and Goode, Ellen L and Hveem, Kristian and Teder-Laving, Maris and Martinez-Perez, Angel and A{\"\i}ssi, Dylan and Daian-Bacq, Delphine and Ito, Kaoru and Natarajan, Pradeep and Lutsey, Pamela L and Nadkarni, Girish N and de Vries, Paul S and Cuellar-Partida, Gabriel and Wolford, Brooke N and Pattee, Jack W and Kooperberg, Charles and Braekkan, Sigrid K and Li-Gao, Ruifang and Saut, No{\'e}mie and Sept, Corriene and Germain, Marine and Judy, Renae L and Wiggins, Kerri L and Ko, Darae and O{\textquoteright}Donnell, Christopher J and Taylor, Kent D and Giulianini, Franco and de Andrade, Mariza and N{\o}st, Therese H and Boland, Anne and Empana, Jean-Philippe and Koyama, Satoshi and Gilliland, Thomas and Do, Ron and Huffman, Jennifer E and Wang, Xin and Zhou, Wei and Manuel Soria, Jose and Carlos Souto, Juan and Pankratz, Nathan and Haessler, Jeffery and Hindberg, Kristian and Rosendaal, Frits R and Turman, Constance and Olaso, Robert and Kember, Rachel L and Bartz, Traci M and Lynch, Julie A and Heckbert, Susan R and Armasu, Sebastian M and Brumpton, Ben and Smadja, David M and Jouven, Xavier and Komuro, Issei and Clapham, Katharine R and Loos, Ruth J F and Willer, Cristen J and Sabater-Lleal, Maria and Pankow, James S and Reiner, Alexander P and Morelli, Vania M and Ridker, Paul M and Vlieg, Astrid van Hylckama and Deleuze, Jean-Francois and Kraft, Peter and Rader, Daniel J and Min Lee, Kyung and Psaty, Bruce M and Heidi Skogholt, Anne and Emmerich, Joseph and Suchon, Pierre and Rich, Stephen S and Vy, Ha My T and Tang, Weihong and Jackson, Rebecca D and Hansen, John-Bjarne and Morange, Pierre-Emmanuel and Kabrhel, Christopher and Tr{\'e}gou{\"e}t, David-Alexandre and Damrauer, Scott M and Johnson, Andrew D and Smith, Nicholas L} } @article {9113, title = {eSCAN: scan regulatory regions for aggregate association testing using whole-genome sequencing data.}, journal = {Brief Bioinform}, volume = {23}, year = {2022}, month = {2022 01 17}, abstract = {

Multiple 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.

}, keywords = {Genome, Genome-Wide Association Study, Genomics, Regulatory Sequences, Nucleic Acid, Whole Genome Sequencing}, issn = {1477-4054}, doi = {10.1093/bib/bbab497}, author = {Yang, Yingxi and Sun, Quan and Huang, Le and Broome, Jai G and Correa, Adolfo and Reiner, Alexander and Raffield, Laura M and Yang, Yuchen and Li, Yun} }