@article {7261, title = {Epigenetic Signatures of Cigarette Smoking.}, journal = {Circ Cardiovasc Genet}, volume = {9}, year = {2016}, month = {2016 Oct}, pages = {436-447}, abstract = {

BACKGROUND: DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, and cardiovascular disorders.

METHODS AND RESULTS: To comprehensively determine the association between cigarette smoking and DNA methylation, we conducted a meta-analysis of genome-wide DNA methylation assessed using the Illumina BeadChip 450K array on 15 907 blood-derived DNA samples from participants in 16 cohorts (including 2433 current, 6518 former, and 6956 never smokers). Comparing current versus never smokers, 2623 cytosine-phosphate-guanine sites (CpGs), annotated to 1405 genes, were statistically significantly differentially methylated at Bonferroni threshold of P<1{\texttimes}10(-7) (18 760 CpGs at false discovery rate <0.05). Genes annotated to these CpGs were enriched for associations with several smoking-related traits in genome-wide studies including pulmonary function, cancers, inflammatory diseases, and heart disease. Comparing former versus never smokers, 185 of the CpGs that differed between current and never smokers were significant P<1{\texttimes}10(-7) (2623 CpGs at false discovery rate <0.05), indicating a pattern of persistent altered methylation, with attenuation, after smoking cessation. Transcriptomic integration identified effects on gene expression at many differentially methylated CpGs.

CONCLUSIONS: Cigarette smoking has a broad impact on genome-wide methylation that, at many loci, persists many years after smoking cessation. Many of the differentially methylated genes were novel genes with respect to biological effects of smoking and might represent therapeutic targets for prevention or treatment of tobacco-related diseases. Methylation at these sites could also serve as sensitive and stable biomarkers of lifetime exposure to tobacco smoke.

}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.116.001506}, author = {Joehanes, Roby and Just, Allan C and Marioni, Riccardo E and Pilling, Luke C and Reynolds, Lindsay M and Mandaviya, Pooja R and Guan, Weihua and Xu, Tao and Elks, Cathy E and Aslibekyan, Stella and Moreno-Macias, Hortensia and Smith, Jennifer A and Brody, Jennifer A and Dhingra, Radhika and Yousefi, Paul and Pankow, James S and Kunze, Sonja and Shah, Sonia H and McRae, Allan F and Lohman, Kurt and Sha, Jin and Absher, Devin M and Ferrucci, Luigi and Zhao, Wei and Demerath, Ellen W and Bressler, Jan and Grove, Megan L and Huan, Tianxiao and Liu, Chunyu and Mendelson, Michael M and Yao, Chen and Kiel, Douglas P and Peters, Annette and Wang-Sattler, Rui and Visscher, Peter M and Wray, Naomi R and Starr, John M and Ding, Jingzhong and Rodriguez, Carlos J and Wareham, Nicholas J and Irvin, Marguerite R and Zhi, Degui and Barrdahl, Myrto and Vineis, Paolo and Ambatipudi, Srikant and Uitterlinden, Andr{\'e} G and Hofman, Albert and Schwartz, Joel and Colicino, Elena and Hou, Lifang and Vokonas, Pantel S and Hernandez, Dena G and Singleton, Andrew B and Bandinelli, Stefania and Turner, Stephen T and Ware, Erin B and Smith, Alicia K and Klengel, Torsten and Binder, Elisabeth B and Psaty, Bruce M and Taylor, Kent D and Gharib, Sina A and Swenson, Brenton R and Liang, Liming and DeMeo, Dawn L and O{\textquoteright}Connor, George T and Herceg, Zdenko and Ressler, Kerry J and Conneely, Karen N and Sotoodehnia, Nona and Kardia, Sharon L R and Melzer, David and Baccarelli, Andrea A and van Meurs, Joyce B J and Romieu, Isabelle and Arnett, Donna K and Ong, Ken K and Liu, Yongmei and Waldenberger, Melanie and Deary, Ian J and Fornage, Myriam and Levy, Daniel and London, Stephanie J} } @article {7583, title = {DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation.}, journal = {Am J Hum Genet}, volume = {101}, year = {2017}, month = {2017 Dec 07}, pages = {888-902}, abstract = {

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0~{\texttimes} 10-7; replication: N = 7,182, p~<~1.6~{\texttimes} 10-3). The replicated methylation sites are heritable (h2 > 30\%) and independent of known BP genetic variants, explaining an additional 1.4\% and 2.0\% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

}, keywords = {Aged, Blood Pressure, CpG Islands, Cross-Sectional Studies, DNA Methylation, Epigenesis, Genetic, Genetic Variation, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Middle Aged, Nerve Tissue Proteins, Quantitative Trait Loci, Tetraspanins}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2017.09.028}, author = {Richard, Melissa A and Huan, Tianxiao and Ligthart, Symen and Gondalia, Rahul and Jhun, Min A and Brody, Jennifer A and Irvin, Marguerite R and Marioni, Riccardo and Shen, Jincheng and Tsai, Pei-Chien and Montasser, May E and Jia, Yucheng and Syme, Catriona and Salfati, Elias L and Boerwinkle, Eric and Guan, Weihua and Mosley, Thomas H and Bressler, Jan and Morrison, Alanna C and Liu, Chunyu and Mendelson, Michael M and Uitterlinden, Andr{\'e} G and van Meurs, Joyce B and Franco, Oscar H and Zhang, Guosheng and Li, Yun and Stewart, James D and Bis, Joshua C and Psaty, Bruce M and Chen, Yii-Der Ida and Kardia, Sharon L R and Zhao, Wei and Turner, Stephen T and Absher, Devin and Aslibekyan, Stella and Starr, John M and McRae, Allan F and Hou, Lifang and Just, Allan C and Schwartz, Joel D and Vokonas, Pantel S and Menni, Cristina and Spector, Tim D and Shuldiner, Alan and Damcott, Coleen M and Rotter, Jerome I and Palmas, Walter and Liu, Yongmei and Paus, Tom{\'a}{\v s} and Horvath, Steve and O{\textquoteright}Connell, Jeffrey R and Guo, Xiuqing and Pausova, Zdenka and Assimes, Themistocles L and Sotoodehnia, Nona and Smith, Jennifer A and Arnett, Donna K and Deary, Ian J and Baccarelli, Andrea A and Bell, Jordana T and Whitsel, Eric and Dehghan, Abbas and Levy, Daniel and Fornage, Myriam} } @article {7586, title = {Leisure-time physical activity and leukocyte telomere length among older women.}, journal = {Exp Gerontol}, volume = {95}, year = {2017}, month = {2017 Sep}, pages = {141-147}, abstract = {

BACKGROUND: Shortened leukocyte telomere length (LTL), a purported marker of cellular aging, is associated with morbidity and mortality. However, the association of physical activity, a modifiable lifestyle behavior, with LTL has not been adequately studied among older adults.

METHODS: In this cross-sectional study, we examined associations of various intensity levels of leisure-time physical activity with LTL among 1476 older white and African American women from the Women{\textquoteright}s Health Initiative Objective Physical Activity and Cardiovascular Health study. Self-reported physical activity was assessed by questionnaire, and LTL was measured by Southern blot. The association between physical activity and LTL was evaluated using multiple linear regression models adjusted for demographic characteristics, lifestyle behaviors, and health-related variables.

RESULTS: Women were on average aged 79.2 (standard deviation 6.7) years old. In the final model adjusted for age, race/ethnicity, education, marital status, smoking, alcohol, body mass index, a history of chronic diseases, and hormone therapy use, LTL was on average 110 (95\% confidence interval, 20-190) base pairs longer among women in the highest (>=17.00MET-hours/week) compared with the lowest (<1.25MET-hours/week) level of total leisure-time physical activity (P for trend=0.02). Higher levels of moderate-to-vigorous physical activity (P for trend=0.04) and faster walking speed (P for trend=0.03) were also associated with longer LTL in the fully-adjusted models.

CONCLUSION: Older women participating in greater amounts of total leisure-time physical activity and moderate-to-vigorous physical activity had longer LTL.

}, issn = {1873-6815}, doi = {10.1016/j.exger.2017.05.019}, author = {Shadyab, Aladdin H and Lamonte, Michael J and Kooperberg, Charles and Reiner, Alexander P and Carty, Cara L and Manini, Todd M and Hou, Lifang and Di, Chongzhi and Macera, Caroline A and Gallo, Linda C and Shaffer, Richard A and Jain, Sonia and LaCroix, Andrea Z} } @article {8507, title = {Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease.}, journal = {Circulation}, volume = {140}, year = {2019}, month = {2019 08 20}, pages = {645-657}, abstract = {

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts.

METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts.

RESULTS: Among 11 461 individuals (mean age 64 years, 67\% women, 35\% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts.

CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

}, keywords = {Adult, Aged, Cohort Studies, Coronary Disease, CpG Islands, DNA Methylation, Europe, Female, Genome-Wide Association Study, Humans, Incidence, Leukocytes, Male, Middle Aged, Myocardial Infarction, Population Groups, Prognosis, Prospective Studies, Risk, United States}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.118.039357}, author = {Agha, Golareh and Mendelson, Michael M and Ward-Caviness, Cavin K and Joehanes, Roby and Huan, Tianxiao and Gondalia, Rahul and Salfati, Elias and Brody, Jennifer A and Fiorito, Giovanni and Bressler, Jan and Chen, Brian H and Ligthart, Symen and Guarrera, Simonetta and Colicino, Elena and Just, Allan C and Wahl, Simone and Gieger, Christian and Vandiver, Amy R and Tanaka, Toshiko and Hernandez, Dena G and Pilling, Luke C and Singleton, Andrew B and Sacerdote, Carlotta and Krogh, Vittorio and Panico, Salvatore and Tumino, Rosario and Li, Yun and Zhang, Guosheng and Stewart, James D and Floyd, James S and Wiggins, Kerri L and Rotter, Jerome I and Multhaup, Michael and Bakulski, Kelly and Horvath, Steven and Tsao, Philip S and Absher, Devin M and Vokonas, Pantel and Hirschhorn, Joel and Fallin, M Daniele and Liu, Chunyu and Bandinelli, Stefania and Boerwinkle, Eric and Dehghan, Abbas and Schwartz, Joel D and Psaty, Bruce M and Feinberg, Andrew P and Hou, Lifang and Ferrucci, Luigi and Sotoodehnia, Nona and Matullo, Giuseppe and Peters, Annette and Fornage, Myriam and Assimes, Themistocles L and Whitsel, Eric A and Levy, Daniel and Baccarelli, Andrea A} } @article {8621, title = {Inherited causes of clonal haematopoiesis in 97,691 whole genomes.}, journal = {Nature}, volume = {586}, year = {2020}, month = {2020 10}, pages = {763-768}, abstract = {

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is~termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP~driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

}, issn = {1476-4687}, doi = {10.1038/s41586-020-2819-2}, author = {Bick, Alexander G and Weinstock, Joshua S and Nandakumar, Satish K and Fulco, Charles P and Bao, Erik L and Zekavat, Seyedeh M and Szeto, Mindy D and Liao, Xiaotian and Leventhal, Matthew J and Nasser, Joseph and Chang, Kyle and Laurie, Cecelia and Burugula, Bala Bharathi and Gibson, Christopher J and Lin, Amy E and Taub, Margaret A and Aguet, Francois and Ardlie, Kristin and Mitchell, Braxton D and Barnes, Kathleen C and Moscati, Arden and Fornage, Myriam and Redline, Susan and Psaty, Bruce M and Silverman, Edwin K and Weiss, Scott T and Palmer, Nicholette D and Vasan, Ramachandran S and Burchard, Esteban G and Kardia, Sharon L R and He, Jiang and Kaplan, Robert C and Smith, Nicholas L and Arnett, Donna K and Schwartz, David A and Correa, Adolfo and de Andrade, Mariza and Guo, Xiuqing and Konkle, Barbara A and Custer, Brian and Peralta, Juan M and Gui, Hongsheng and Meyers, Deborah A and McGarvey, Stephen T and Chen, Ida Yii-Der and Shoemaker, M Benjamin and Peyser, Patricia A and Broome, Jai G and Gogarten, Stephanie M and Wang, Fei Fei and Wong, Quenna and Montasser, May E and Daya, Michelle and Kenny, Eimear E and North, Kari E and Launer, Lenore J and Cade, Brian E and Bis, Joshua C and Cho, Michael H and Lasky-Su, Jessica and Bowden, Donald W and Cupples, L Adrienne and Mak, Angel C Y and Becker, Lewis C and Smith, Jennifer A and Kelly, Tanika N and Aslibekyan, Stella and Heckbert, Susan R and Tiwari, Hemant K and Yang, Ivana V and Heit, John A and Lubitz, Steven A and Johnsen, Jill M and Curran, Joanne E and Wenzel, Sally E and Weeks, Daniel E and Rao, Dabeeru C and Darbar, Dawood and Moon, Jee-Young and Tracy, Russell P and Buth, Erin J and Rafaels, Nicholas and Loos, Ruth J F and Durda, Peter and Liu, Yongmei and Hou, Lifang and Lee, Jiwon and Kachroo, Priyadarshini and Freedman, Barry I and Levy, Daniel and Bielak, Lawrence F and Hixson, James E and Floyd, James S and Whitsel, Eric A and Ellinor, Patrick T and Irvin, Marguerite R and Fingerlin, Tasha E and Raffield, Laura M and Armasu, Sebastian M and Wheeler, Marsha M and Sabino, Ester C and Blangero, John and Williams, L Keoki and Levy, Bruce D and Sheu, Wayne Huey-Herng and Roden, Dan M and Boerwinkle, Eric and Manson, JoAnn E and Mathias, Rasika A and Desai, Pinkal and Taylor, Kent D and Johnson, Andrew D and Auer, Paul L and Kooperberg, Charles and Laurie, Cathy C and Blackwell, Thomas W and Smith, Albert V and Zhao, Hongyu and Lange, Ethan and Lange, Leslie and Rich, Stephen S and Rotter, Jerome I and Wilson, James G and Scheet, Paul and Kitzman, Jacob O and Lander, Eric S and Engreitz, Jesse M and Ebert, Benjamin L and Reiner, Alexander P and Jaiswal, Siddhartha and Abecasis, Goncalo and Sankaran, Vijay G and Kathiresan, Sekar and Natarajan, Pradeep} } @article {8446, title = {Whole Blood DNA Methylation Signatures of Diet Are Associated With Cardiovascular Disease Risk Factors and All-Cause Mortality.}, journal = {Circ Genom Precis Med}, volume = {13}, year = {2020}, month = {2020 Aug}, pages = {e002766}, abstract = {

BACKGROUND: DNA methylation patterns associated with habitual diet have not been well studied.

METHODS: Diet quality was characterized using a Mediterranean-style diet score and the Alternative Healthy Eating Index score. We conducted ethnicity-specific and trans-ethnic epigenome-wide association analyses for diet quality and leukocyte-derived DNA methylation at over 400 000 CpGs (cytosine-guanine dinucleotides) in 5 population-based cohorts including 6662 European ancestry, 2702 African ancestry, and 360 Hispanic ancestry participants. For diet-associated CpGs identified in epigenome-wide analyses, we conducted Mendelian randomization (MR) analysis to examine their relations to cardiovascular disease risk factors and examined their longitudinal associations with all-cause mortality.

RESULTS: We identified 30 CpGs associated with either Mediterranean-style diet score or Alternative Healthy Eating Index, or both, in European ancestry participants. Among these CpGs, 12 CpGs were significantly associated with all-cause mortality (Bonferroni corrected <1.6{\texttimes}10). Hypermethylation of cg18181703 () was associated with higher scores of both Mediterranean-style diet score and Alternative Healthy Eating Index and lower risk for all-cause mortality (=5.7{\texttimes}10). Ten additional diet-associated CpGs were nominally associated with all-cause mortality (<0.05). MR analysis revealed 8 putatively causal associations for 6 CpGs with 4 cardiovascular disease risk factors (body mass index, triglycerides, high-density lipoprotein cholesterol concentrations, and type 2 diabetes mellitus; Bonferroni corrected MR <4.5{\texttimes}10). For example, hypermethylation of cg11250194 () was associated with lower triglyceride concentrations (MR, =1.5{\texttimes}10).and hypermethylation of cg02079413 (; ) was associated with body mass index (corrected MR, =1{\texttimes}10).

CONCLUSIONS: Habitual diet quality was associated with differential peripheral leukocyte DNA methylation levels of 30 CpGs, most of which were also associated with multiple health outcomes, in European ancestry individuals. These findings demonstrate that integrative genomic analysis of dietary information may reveal molecular targets for disease prevention and treatment.

}, issn = {2574-8300}, doi = {10.1161/CIRCGEN.119.002766}, author = {Ma, Jiantao and Rebholz, Casey M and Braun, Kim V E and Reynolds, Lindsay M and Aslibekyan, Stella and Xia, Rui and Biligowda, Niranjan G and Huan, Tianxiao and Liu, Chunyu and Mendelson, Michael M and Joehanes, Roby and Hu, Emily A and Vitolins, Mara Z and Wood, Alexis C and Lohman, Kurt and Ochoa-Rosales, Carolina and van Meurs, Joyce and Uitterlinden, Andre and Liu, Yongmei and Elhadad, Mohamed A and Heier, Margit and Waldenberger, Melanie and Peters, Annette and Colicino, Elena and Whitsel, Eric A and Baldassari, Antoine and Gharib, Sina A and Sotoodehnia, Nona and Brody, Jennifer A and Sitlani, Colleen M and Tanaka, Toshiko and Hill, W David and Corley, Janie and Deary, Ian J and Zhang, Yan and Sch{\"o}ttker, Ben and Brenner, Hermann and Walker, Maura E and Ye, Shumao and Nguyen, Steve and Pankow, Jim and Demerath, Ellen W and Zheng, Yinan and Hou, Lifang and Liang, Liming and Lichtenstein, Alice H and Hu, Frank B and Fornage, Myriam and Voortman, Trudy and Levy, Daniel} } @article {9006, title = {Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus.}, journal = {Nat Commun}, volume = {12}, year = {2021}, month = {2021 12 09}, pages = {7173}, abstract = {

Elevated serum urate levels, a complex trait and major risk factor for incident gout, are~correlated with cardiometabolic traits via incompletely understood mechanisms. DNA methylation in whole blood captures genetic and environmental influences and is assessed in transethnic meta-analysis of epigenome-wide association studies (EWAS) of serum urate (discovery, n = 12,474, replication, n = 5522). The 100 replicated, epigenome-wide significant (p < 1.1E-7) CpGs explain 11.6\% of the serum urate variance. At SLC2A9, the serum urate locus with the largest effect in genome-wide association studies (GWAS), five CpGs are associated with SLC2A9 gene expression. Four CpGs at SLC2A9 have significant causal effects on serum urate levels and/or gout, and two of these partly mediate the effects of urate-associated GWAS variants. In other genes, including SLC7A11 and PHGDH, 17 urate-associated CpGs are associated with conditions defining metabolic syndrome, suggesting that these CpGs may represent a blood DNA methylation signature of cardiometabolic risk factors. This study demonstrates that EWAS can provide new insights into GWAS loci and the correlation of serum urate with other complex traits.

}, keywords = {Amino Acid Transport System y+, Cohort Studies, CpG Islands, DNA Methylation, Epigenome, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Glucose Transport Proteins, Facilitative, Gout, Humans, Male, Uric Acid}, issn = {2041-1723}, doi = {10.1038/s41467-021-27198-4}, author = {Tin, Adrienne and Schlosser, Pascal and Matias-Garcia, Pamela R and Thio, Chris H L and Joehanes, Roby and Liu, Hongbo and Yu, Zhi and Weihs, Antoine and Hoppmann, Anselm and Grundner-Culemann, Franziska and Min, Josine L and Kuhns, Victoria L Halperin and Adeyemo, Adebowale A and Agyemang, Charles and Arnl{\"o}v, Johan and Aziz, Nasir A and Baccarelli, Andrea and Bochud, Murielle and Brenner, Hermann and Bressler, Jan and Breteler, Monique M B and Carmeli, Cristian and Chaker, Layal and Coresh, Josef and Corre, Tanguy and Correa, Adolfo and Cox, Simon R and Delgado, Graciela E and Eckardt, Kai-Uwe and Ekici, Arif B and Endlich, Karlhans and Floyd, James S and Fraszczyk, Eliza and Gao, Xu and G{\`a}o, Xin and Gelber, Allan C and Ghanbari, Mohsen and Ghasemi, Sahar and Gieger, Christian and Greenland, Philip and Grove, Megan L and Harris, Sarah E and Hemani, Gibran and Henneman, Peter and Herder, Christian and Horvath, Steve and Hou, Lifang and Hurme, Mikko A and Hwang, Shih-Jen and Kardia, Sharon L R and Kasela, Silva and Kleber, Marcus E and Koenig, Wolfgang and Kooner, Jaspal S and Kronenberg, Florian and Kuhnel, Brigitte and Ladd-Acosta, Christine and Lehtim{\"a}ki, Terho and Lind, Lars and Liu, Dan and Lloyd-Jones, Donald M and Lorkowski, Stefan and Lu, Ake T and Marioni, Riccardo E and M{\"a}rz, Winfried and McCartney, Daniel L and Meeks, Karlijn A C and Milani, Lili and Mishra, Pashupati P and Nauck, Matthias and Nowak, Christoph and Peters, Annette and Prokisch, Holger and Psaty, Bruce M and Raitakari, Olli T and Ratliff, Scott M and Reiner, Alex P and Sch{\"o}ttker, Ben and Schwartz, Joel and Sedaghat, Sanaz and Smith, Jennifer A and Sotoodehnia, Nona and Stocker, Hannah R and Stringhini, Silvia and Sundstr{\"o}m, Johan and Swenson, Brenton R and van Meurs, Joyce B J and van Vliet-Ostaptchouk, Jana V and Venema, Andrea and V{\"o}lker, Uwe and Winkelmann, Juliane and Wolffenbuttel, Bruce H R and Zhao, Wei and Zheng, Yinan and Loh, Marie and Snieder, Harold and Waldenberger, Melanie and Levy, Daniel and Akilesh, Shreeram and Woodward, Owen M and Susztak, Katalin and Teumer, Alexander and K{\"o}ttgen, Anna} } @article {9002, title = {Meta-analyses identify DNA methylation associated with kidney function and damage.}, journal = {Nat Commun}, volume = {12}, year = {2021}, month = {2021 12 09}, pages = {7174}, abstract = {

Chronic kidney disease is a major public health burden. Elevated urinary albumin-to-creatinine ratio is a measure of kidney damage, and used to diagnose and stage chronic kidney disease. To extend the knowledge on regulatory mechanisms related to kidney function and disease, we conducted a blood-based epigenome-wide association study for estimated glomerular filtration rate (n = 33,605) and urinary albumin-to-creatinine ratio (n = 15,068) and detected 69 and seven CpG sites where DNA methylation was associated with the respective trait. The majority of these findings showed directionally consistent associations with the respective clinical outcomes chronic kidney disease and moderately increased albuminuria. Associations of DNA methylation with kidney function, such as CpGs at JAZF1, PELI1 and CHD2 were validated in kidney tissue. Methylation at PHRF1, LDB2, CSRNP1 and IRF5 indicated causal effects on kidney function. Enrichment analyses revealed pathways related to hemostasis and blood cell migration for estimated glomerular filtration rate, and immune cell activation and response for urinary albumin-to-creatinineratio-associated CpGs.

}, keywords = {Adult, Aged, CpG Islands, DNA Methylation, Female, Glomerular Filtration Rate, Humans, Interferon Regulatory Factors, Kidney, Kidney Function Tests, LIM Domain Proteins, Male, Membrane Proteins, Middle Aged, Renal Insufficiency, Chronic, Transcription Factors}, issn = {2041-1723}, doi = {10.1038/s41467-021-27234-3}, author = {Schlosser, Pascal and Tin, Adrienne and Matias-Garcia, Pamela R and Thio, Chris H L and Joehanes, Roby and Liu, Hongbo and Weihs, Antoine and Yu, Zhi and Hoppmann, Anselm and Grundner-Culemann, Franziska and Min, Josine L and Adeyemo, Adebowale A and Agyemang, Charles and Arnl{\"o}v, Johan and Aziz, Nasir A and Baccarelli, Andrea and Bochud, Murielle and Brenner, Hermann and Breteler, Monique M B and Carmeli, Cristian and Chaker, Layal and Chambers, John C and Cole, Shelley A and Coresh, Josef and Corre, Tanguy and Correa, Adolfo and Cox, Simon R and de Klein, Niek and Delgado, Graciela E and Domingo-Relloso, Arce and Eckardt, Kai-Uwe and Ekici, Arif B and Endlich, Karlhans and Evans, Kathryn L and Floyd, James S and Fornage, Myriam and Franke, Lude and Fraszczyk, Eliza and Gao, Xu and G{\`a}o, Xin and Ghanbari, Mohsen and Ghasemi, Sahar and Gieger, Christian and Greenland, Philip and Grove, Megan L and Harris, Sarah E and Hemani, Gibran and Henneman, Peter and Herder, Christian and Horvath, Steve and Hou, Lifang and Hurme, Mikko A and Hwang, Shih-Jen and Jarvelin, Marjo-Riitta and Kardia, Sharon L R and Kasela, Silva and Kleber, Marcus E and Koenig, Wolfgang and Kooner, Jaspal S and Kramer, Holly and Kronenberg, Florian and Kuhnel, Brigitte and Lehtim{\"a}ki, Terho and Lind, Lars and Liu, Dan and Liu, Yongmei and Lloyd-Jones, Donald M and Lohman, Kurt and Lorkowski, Stefan and Lu, Ake T and Marioni, Riccardo E and M{\"a}rz, Winfried and McCartney, Daniel L and Meeks, Karlijn A C and Milani, Lili and Mishra, Pashupati P and Nauck, Matthias and Navas-Acien, Ana and Nowak, Christoph and Peters, Annette and Prokisch, Holger and Psaty, Bruce M and Raitakari, Olli T and Ratliff, Scott M and Reiner, Alex P and Rosas, Sylvia E and Sch{\"o}ttker, Ben and Schwartz, Joel and Sedaghat, Sanaz and Smith, Jennifer A and Sotoodehnia, Nona and Stocker, Hannah R and Stringhini, Silvia and Sundstr{\"o}m, Johan and Swenson, Brenton R and Tellez-Plaza, Maria and van Meurs, Joyce B J and van Vliet-Ostaptchouk, Jana V and Venema, Andrea and Verweij, Niek and Walker, Rosie M and Wielscher, Matthias and Winkelmann, Juliane and Wolffenbuttel, Bruce H R and Zhao, Wei and Zheng, Yinan and Loh, Marie and Snieder, Harold and Levy, Daniel and Waldenberger, Melanie and Susztak, Katalin and K{\"o}ttgen, Anna and Teumer, Alexander} } @article {8913, title = {Whole genome sequence analysis of platelet traits in the NHLBI trans-omics for precision medicine initiative.}, journal = {Hum Mol Genet}, year = {2021}, month = {2021 Sep 06}, abstract = {

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing from NHLBI{\textquoteright}s Trans-Omics for Precision Medicine Initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several GWAS identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of whole genome sequencing in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

}, issn = {1460-2083}, doi = {10.1093/hmg/ddab252}, author = {Little, Amarise and Hu, Yao and Sun, Quan and Jain, Deepti and Broome, Jai and Chen, Ming-Huei and Thibord, Florian and McHugh, Caitlin and Surendran, Praveen and Blackwell, Thomas W and Brody, Jennifer A and Bhan, Arunoday and Chami, Nathalie and Vries, Paul S and Ekunwe, Lynette and Heard-Costa, Nancy and Hobbs, Brian D and Manichaikul, Ani and Moon, Jee-Young and Preuss, Michael H and Ryan, Kathleen and Wang, Zhe and Wheeler, Marsha and Yanek, Lisa R and Abecasis, Goncalo R and Almasy, Laura and Beaty, Terri H and Becker, Lewis C and Blangero, John and Boerwinkle, Eric and Butterworth, Adam S and Choquet, Helene and Correa, Adolfo and Curran, Joanne E and Faraday, Nauder and Fornage, Myriam and Glahn, David C and Hou, Lifang and Jorgenson, Eric and Kooperberg, Charles and Lewis, Joshua P and Lloyd-Jones, Donald M and Loos, Ruth J F and Min, Nancy and Mitchell, Braxton D and Morrison, Alanna C and Nickerson, Debbie and North, Kari E and O{\textquoteright}Connell, Jeffrey R and Pankratz, Nathan and Psaty, Bruce M and Vasan, Ramachandran S and Rich, Stephen S and Rotter, Jerome I and Smith, Albert V and Smith, Nicholas L and Tang, Hua and Tracy, Russell P and Conomos, Matthew P and Laurie, Cecelia A and Mathias, Rasika A and Li, Yun and Auer, Paul L and Thornton, Timothy and Reiner, Alexander P and Johnson, Andrew D and Raffield, Laura M} } @article {8779, title = {Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program.}, journal = {Am J Hum Genet}, volume = {108}, year = {2021}, month = {2021 05 06}, pages = {874-893}, abstract = {

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3~bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

}, keywords = {Adult, Aged, Chromosomes, Human, Pair 16, Datasets as Topic, Erythrocytes, Female, Gene Editing, Genetic Variation, Genome-Wide Association Study, HEK293 Cells, Humans, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Quality Control, Reproducibility of Results, United States}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.04.003}, author = {Hu, Yao and Stilp, Adrienne M and McHugh, Caitlin P and Rao, Shuquan and Jain, Deepti and Zheng, Xiuwen and Lane, John and M{\'e}ric de Bellefon, S{\'e}bastian and Raffield, Laura M and Chen, Ming-Huei and Yanek, Lisa R and Wheeler, Marsha and Yao, Yao and Ren, Chunyan and Broome, Jai and Moon, Jee-Young and de Vries, Paul S and Hobbs, Brian D and Sun, Quan and Surendran, Praveen and Brody, Jennifer A and Blackwell, Thomas W and Choquet, Helene and Ryan, Kathleen and Duggirala, Ravindranath and Heard-Costa, Nancy and Wang, Zhe and Chami, Nathalie and Preuss, Michael H and Min, Nancy and Ekunwe, Lynette and Lange, Leslie A and Cushman, Mary and Faraday, Nauder and Curran, Joanne E and Almasy, Laura and Kundu, Kousik and Smith, Albert V and Gabriel, Stacey and Rotter, Jerome I and Fornage, Myriam and Lloyd-Jones, Donald M and Vasan, Ramachandran S and Smith, Nicholas L and North, Kari E and Boerwinkle, Eric and Becker, Lewis C and Lewis, Joshua P and Abecasis, Goncalo R and Hou, Lifang and O{\textquoteright}Connell, Jeffrey R and Morrison, Alanna C and Beaty, Terri H and Kaplan, Robert and Correa, Adolfo and Blangero, John and Jorgenson, Eric and Psaty, Bruce M and Kooperberg, Charles and Walton, Russell T and Kleinstiver, Benjamin P and Tang, Hua and Loos, Ruth J F and Soranzo, Nicole and Butterworth, Adam S and Nickerson, Debbie and Rich, Stephen S and Mitchell, Braxton D and Johnson, Andrew D and Auer, Paul L and Li, Yun and Mathias, Rasika A and Lettre, Guillaume and Pankratz, Nathan and Laurie, Cathy C and Laurie, Cecelia A and Bauer, Daniel E and Conomos, Matthew P and Reiner, Alexander P} } @article {8914, title = {Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program.}, journal = {Am J Hum Genet}, volume = {108}, year = {2021}, month = {2021 10 07}, pages = {1836-1851}, abstract = {

Many 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.

}, keywords = {Asthma, Biomarkers, Dermatitis, Atopic, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Leukocytes, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Prognosis, Proteome, Pulmonary Disease, Chronic Obstructive, Quantitative Trait Loci, United Kingdom, United States, Whole Genome Sequencing}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.08.007}, author = {Mikhaylova, Anna V and McHugh, Caitlin P and Polfus, Linda M and Raffield, Laura M and Boorgula, Meher Preethi and Blackwell, Thomas W and Brody, Jennifer A and Broome, Jai and Chami, Nathalie and Chen, Ming-Huei and Conomos, Matthew P and Cox, Corey and Curran, Joanne E and Daya, Michelle and Ekunwe, Lynette and Glahn, David C and Heard-Costa, Nancy and Highland, Heather M and Hobbs, Brian D and Ilboudo, Yann and Jain, Deepti and Lange, Leslie A and Miller-Fleming, Tyne W and Min, Nancy and Moon, Jee-Young and Preuss, Michael H and Rosen, Jonathon and Ryan, Kathleen and Smith, Albert V and Sun, Quan and Surendran, Praveen and de Vries, Paul S and Walter, Klaudia and Wang, Zhe and Wheeler, Marsha and Yanek, Lisa R and Zhong, Xue and Abecasis, Goncalo R and Almasy, Laura and Barnes, Kathleen C and Beaty, Terri H and Becker, Lewis C and Blangero, John and Boerwinkle, Eric and Butterworth, Adam S and Chavan, Sameer and Cho, Michael H and Choquet, Helene and Correa, Adolfo and Cox, Nancy and DeMeo, Dawn L and Faraday, Nauder and Fornage, Myriam and Gerszten, Robert E and Hou, Lifang and Johnson, Andrew D and Jorgenson, Eric and Kaplan, Robert and Kooperberg, Charles and Kundu, Kousik and Laurie, Cecelia A and Lettre, Guillaume and Lewis, Joshua P and Li, Bingshan and Li, Yun and Lloyd-Jones, Donald M and Loos, Ruth J F and Manichaikul, Ani and Meyers, Deborah A and Mitchell, Braxton D and Morrison, Alanna C and Ngo, Debby and Nickerson, Deborah A and Nongmaithem, Suraj and North, Kari E and O{\textquoteright}Connell, Jeffrey R and Ortega, Victor E and Pankratz, Nathan and Perry, James A and Psaty, Bruce M and Rich, Stephen S and Soranzo, Nicole and Rotter, Jerome I and Silverman, Edwin K and Smith, Nicholas L and Tang, Hua and Tracy, Russell P and Thornton, Timothy A and Vasan, Ramachandran S and Zein, Joe and Mathias, Rasika A and Reiner, Alexander P and Auer, Paul L} } @article {9184, title = {Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI.}, journal = {Brain}, year = {2022}, month = {2022 Aug 09}, abstract = {

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at approximately 450,000 CpG sites in 9,732 middle-aged to older adults from 14 community-based studies. Single-CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single-CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 {\texttimes} 10-8), was associated with F2 expression in blood (P = 6.4 {\texttimes} 10-5), and colocalized with FOLH1 expression in brain (posterior probability =0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single-CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis, and multi-omics colocalization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug repositioning analysis indicated antihyperlipidemic agents, more specifically peroxisome proliferator-activated receptor alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood brain barrier disruption.

}, issn = {1460-2156}, doi = {10.1093/brain/awac290}, author = {Yang, Yunju and Knol, Maria J and Wang, Ruiqi and Mishra, Aniket and Liu, Dan and Luciano, Michelle and Teumer, Alexander and Armstrong, Nicola and Bis, Joshua C and Jhun, Min A and Li, Shuo and Adams, Hieab H H and Aziz, Nasir Ahmad and Bastin, Mark E and Bourgey, Mathieu and Brody, Jennifer A and Frenzel, Stefan and Gottesman, Rebecca F and Hosten, Norbert and Hou, Lifang and Kardia, Sharon L R and Lohner, Valerie and Marquis, Pascale and Maniega, Susana Mu{\~n}oz and Satizabal, Claudia L and Sorond, Farzaneh A and Vald{\'e}s Hern{\'a}ndez, Maria C and van Duijn, Cornelia M and Vernooij, Meike W and Wittfeld, Katharina and Yang, Qiong and Zhao, Wei and Boerwinkle, Eric and Levy, Daniel and Deary, Ian J and Jiang, Jiyang and Mather, Karen A and Mosley, Thomas H and Psaty, Bruce M and Sachdev, Perminder S and Smith, Jennifer A and Sotoodehnia, Nona and DeCarli, Charles S and Breteler, Monique M B and Arfan Ikram, M and Grabe, Hans J and Wardlaw, Joanna and Longstreth, W T and Launer, Lenore J and Seshadri, Sudha and Debette, Stephanie and Fornage, Myriam} } @article {9094, title = {Integrative analysis of clinical and epigenetic biomarkers of mortality.}, journal = {Aging Cell}, volume = {21}, year = {2022}, month = {2022 Jun}, pages = {e13608}, abstract = {

DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome-wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n~=~15,013). During a mean follow-up of 10~years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry-stratified meta-analysis of all-cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p~<~1~{\texttimes}~10 , of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm-based prediction models for all-cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5\% increase in the C-index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta~=~1.2, P ~=~4.1~{\texttimes}~10 ) and negatively associated with longevity (Beta~=~-1.9, P ~=~0.02). Pathway analysis revealed that genes associated with mortality-related CpGs are enriched for immune- and cancer-related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk.

}, keywords = {Biomarkers, Cardiovascular Diseases, DNA Methylation, Epigenesis, Genetic, Epigenomics, Humans, Male, Neoplasms}, issn = {1474-9726}, doi = {10.1111/acel.13608}, author = {Huan, Tianxiao and Nguyen, Steve and Colicino, Elena and Ochoa-Rosales, Carolina and Hill, W David and Brody, Jennifer A and Soerensen, Mette and Zhang, Yan and Baldassari, Antoine and Elhadad, Mohamed Ahmed and Toshiko, Tanaka and Zheng, Yinan and Domingo-Relloso, Arce and Lee, Dong Heon and Ma, Jiantao and Yao, Chen and Liu, Chunyu and Hwang, Shih-Jen and Joehanes, Roby and Fornage, Myriam and Bressler, Jan and van Meurs, Joyce B J and Debrabant, Birgit and Mengel-From, Jonas and Hjelmborg, Jacob and Christensen, Kaare and Vokonas, Pantel and Schwartz, Joel and Gahrib, Sina A and Sotoodehnia, Nona and Sitlani, Colleen M and Kunze, Sonja and Gieger, Christian and Peters, Annette and Waldenberger, Melanie and Deary, Ian J and Ferrucci, Luigi and Qu, Yishu and Greenland, Philip and Lloyd-Jones, Donald M and Hou, Lifang and Bandinelli, Stefania and Voortman, Trudy and Hermann, Brenner and Baccarelli, Andrea and Whitsel, Eric and Pankow, James S and Levy, Daniel} } @article {9168, title = {Rare genetic variants explain missing heritability in smoking.}, journal = {Nat Hum Behav}, year = {2022}, month = {2022 Aug 04}, abstract = {

Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this {\textquoteright}missing heritability{\textquoteright}. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74\% of it attributable to rare variants with minor allele frequencies between 0.01\% and 1\%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60\% to 100\% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.

}, issn = {2397-3374}, doi = {10.1038/s41562-022-01408-5}, author = {Jang, Seon-Kyeong and Evans, Luke and Fialkowski, Allison and Arnett, Donna K and Ashley-Koch, Allison E and Barnes, Kathleen C and Becker, Diane M and Bis, Joshua C and Blangero, John and Bleecker, Eugene R and Boorgula, Meher Preethi and Bowden, Donald W and Brody, Jennifer A and Cade, Brian E and Jenkins, Brenda W Campbell and Carson, April P and Chavan, Sameer and Cupples, L Adrienne and Custer, Brian and Damrauer, Scott M and David, Sean P and de Andrade, Mariza and Dinardo, Carla L and Fingerlin, Tasha E and Fornage, Myriam and Freedman, Barry I and Garrett, Melanie E and Gharib, Sina A and Glahn, David C and Haessler, Jeffrey and Heckbert, Susan R and Hokanson, John E and Hou, Lifang and Hwang, Shih-Jen and Hyman, Matthew C and Judy, Renae and Justice, Anne E and Kaplan, Robert C and Kardia, Sharon L R and Kelly, Shannon and Kim, Wonji and Kooperberg, Charles and Levy, Daniel and Lloyd-Jones, Donald M and Loos, Ruth J F and Manichaikul, Ani W and Gladwin, Mark T and Martin, Lisa Warsinger and Nouraie, Mehdi and Melander, Olle and Meyers, Deborah A and Montgomery, Courtney G and North, Kari E and Oelsner, Elizabeth C and Palmer, Nicholette D and Payton, Marinelle and Peljto, Anna L and Peyser, Patricia A and Preuss, Michael and Psaty, Bruce M and Qiao, Dandi and Rader, Daniel J and Rafaels, Nicholas and Redline, Susan and Reed, Robert M and Reiner, Alexander P and Rich, Stephen S and Rotter, Jerome I and Schwartz, David A and Shadyab, Aladdin H and Silverman, Edwin K and Smith, Nicholas L and Smith, J Gustav and Smith, Albert V and Smith, Jennifer A and Tang, Weihong and Taylor, Kent D and Telen, Marilyn J and Vasan, Ramachandran S and Gordeuk, Victor R and Wang, Zhe and Wiggins, Kerri L and Yanek, Lisa R and Yang, Ivana V and Young, Kendra A and Young, Kristin L and Zhang, Yingze and Liu, Dajiang J and Keller, Matthew C and Vrieze, Scott} } @article {9258, title = {Whole-Exome Sequencing Study Identifies Four Novel Gene Loci Associated with Diabetic Kidney Disease.}, journal = {Hum Mol Genet}, year = {2022}, month = {2022 Nov 29}, abstract = {

Diabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease (CKD) and diabetes. Our two-stage whole-exome sequencing study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort (CRIC) and Atherosclerosis Risk in Communities (ARIC) studies (stage-1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine (TOPMed) participants (stage-2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex, and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test (SKAT-O) implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds (95\% confidence interval: 33.6, 1105) of DKD compared with non-carriers (P = 3.59 {\texttimes} 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95\% confidence interval: 3.06, 9.21) of DKD (P = 2.72 {\texttimes} 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 {\texttimes} 10-8) and NPEPPS (P = 1.51 {\texttimes} 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD.

}, issn = {1460-2083}, doi = {10.1093/hmg/ddac290}, author = {Pan, Yang and Sun, Xiao and Mi, Xuenan and Huang, Zhijie and Hsu, Yenchih and Hixson, James E and Munzy, Donna and Metcalf, Ginger and Franceschini, Nora and Tin, Adrienne and K{\"o}ttgen, Anna and Francis, Michael and Brody, Jennifer A and Kestenbaum, Bryan and Sitlani, Colleen M and Mychaleckyj, Josyf C and Kramer, Holly and Lange, Leslie A and Guo, Xiuqing and Hwang, Shih-Jen and Irvin, Marguerite R and Smith, Jennifer A and Yanek, Lisa R and Vaidya, Dhananjay and Chen, Yii-Der Ida and Fornage, Myriam and Lloyd-Jones, Donald M and Hou, Lifang and Mathias, Rasika A and Mitchell, Braxton D and Peyser, Patricia A and Kardia, Sharon L R and Arnett, Donna K and Correa, Adolfo and Raffield, Laura M and Vasan, Ramachandran S and Cupple, L Adrienne and Levy, Daniel and Kaplan, Robert C and North, Kari E and Rotter, Jerome I and Kooperberg, Charles and Reiner, Alexander P and Psaty, Bruce M and Tracy, Russell P and Gibbs, Richard A and Morrison, Alanna C and Feldman, Harold and Boerwinkle, Eric and He, Jiang and Kelly, Tanika N} } @article {9387, title = {Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis.}, journal = {Nature}, volume = {616}, year = {2023}, month = {2023 Apr}, pages = {755-763}, abstract = {

Mutations in a diverse set of driver genes increase the fitness of haematopoietic stem cells (HSCs), leading to clonal haematopoiesis. These lesions are precursors for blood cancers, but the basis of their fitness advantage remains largely unknown, partly owing to a paucity of large cohorts in which the clonal expansion rate has been assessed by longitudinal sampling. Here, to circumvent this limitation, we developed a method to infer the expansion rate from data from a single time point. We applied this method to 5,071 people with clonal haematopoiesis. A genome-wide association study revealed that a common inherited polymorphism in the TCL1A promoter was associated with a slower expansion rate in clonal haematopoiesis overall, but the effect varied by driver gene. Those carrying this protective allele exhibited markedly reduced growth rates or prevalence of clones with driver mutations in TET2, ASXL1, SF3B1 and SRSF2, but~this effect was not seen in~clones with~driver mutations in DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 led to the expression of TCL1A protein and the expansion of HSCs in vitro. The protective allele restricted TCL1A expression and expansion of mutant HSCs, as did experimental~knockdown of TCL1A expression. Forced expression of TCL1A promoted the expansion of human HSCs in vitro and mouse HSCs in vivo. Our results indicate that the fitness advantage of several commonly mutated driver genes in clonal haematopoiesis may be mediated by TCL1A activation.

}, keywords = {Alleles, Animals, Clonal Hematopoiesis, Genome-Wide Association Study, Hematopoiesis, Hematopoietic Stem Cells, Humans, Mice, Mutation, Promoter Regions, Genetic}, issn = {1476-4687}, doi = {10.1038/s41586-023-05806-1}, author = {Weinstock, Joshua S and Gopakumar, Jayakrishnan and Burugula, Bala Bharathi and Uddin, Md Mesbah and Jahn, Nikolaus and Belk, Julia A and Bouzid, Hind and Daniel, Bence and Miao, Zhuang and Ly, Nghi and Mack, Taralynn M and Luna, Sofia E and Prothro, Katherine P and Mitchell, Shaneice R and Laurie, Cecelia A and Broome, Jai G and Taylor, Kent D and Guo, Xiuqing and Sinner, Moritz F and von Falkenhausen, Aenne S and K{\"a}{\"a}b, Stefan and Shuldiner, Alan R and O{\textquoteright}Connell, Jeffrey R and Lewis, Joshua P and Boerwinkle, Eric and Barnes, Kathleen C and Chami, Nathalie and Kenny, Eimear E and Loos, Ruth J F and Fornage, Myriam and Hou, Lifang and Lloyd-Jones, Donald M and Redline, Susan and Cade, Brian E and Psaty, Bruce M and Bis, Joshua C and Brody, Jennifer A and Silverman, Edwin K and Yun, Jeong H and Qiao, Dandi and Palmer, Nicholette D and Freedman, Barry I and Bowden, Donald W and Cho, Michael H and DeMeo, Dawn L and Vasan, Ramachandran S and Yanek, Lisa R and Becker, Lewis C and Kardia, Sharon L R and Peyser, Patricia A and He, Jiang and Rienstra, Michiel and van der Harst, Pim and Kaplan, Robert and Heckbert, Susan R and Smith, Nicholas L and Wiggins, Kerri L and Arnett, Donna K and Irvin, Marguerite R and Tiwari, Hemant and Cutler, Michael J and Knight, Stacey and Muhlestein, J Brent and Correa, Adolfo and Raffield, Laura M and Gao, Yan and de Andrade, Mariza and Rotter, Jerome I and Rich, Stephen S and Tracy, Russell P and Konkle, Barbara A and Johnsen, Jill M and Wheeler, Marsha M and Smith, J Gustav and Melander, Olle and Nilsson, Peter M and Custer, Brian S and Duggirala, Ravindranath and Curran, Joanne E and Blangero, John and McGarvey, Stephen and Williams, L Keoki and Xiao, Shujie and Yang, Mao and Gu, C Charles and Chen, Yii-Der Ida and Lee, Wen-Jane and Marcus, Gregory M and Kane, John P and Pullinger, Clive R and Shoemaker, M Benjamin and Darbar, Dawood and Roden, Dan M and Albert, Christine and Kooperberg, Charles and Zhou, Ying and Manson, JoAnn E and Desai, Pinkal and Johnson, Andrew D and Mathias, Rasika A and Blackwell, Thomas W and Abecasis, Goncalo R and Smith, Albert V and Kang, Hyun M and Satpathy, Ansuman T and Natarajan, Pradeep and Kitzman, Jacob O and Whitsel, Eric A and Reiner, Alexander P and Bick, Alexander G and Jaiswal, Siddhartha} } @article {9502, title = {Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk.}, journal = {J Am Heart Assoc}, year = {2023}, month = {2023 Oct 07}, pages = {e029090}, abstract = {

Background 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.

}, issn = {2047-9980}, doi = {10.1161/JAHA.122.029090}, author = {Liu, Xue and Sun, Xianbang and Zhang, Yuankai and Jiang, Wenqing and Lai, Meng and Wiggins, Kerri L and Raffield, Laura M and Bielak, Lawrence F and Zhao, Wei and Pitsillides, Achilleas and Haessler, Jeffrey and Zheng, Yinan and Blackwell, Thomas W and Yao, Jie and Guo, Xiuqing and Qian, Yong and Thyagarajan, Bharat and Pankratz, Nathan and Rich, Stephen S and Taylor, Kent D and Peyser, Patricia A and Heckbert, Susan R and Seshadri, Sudha and Boerwinkle, Eric and Grove, Megan L and Larson, Nicholas B and Smith, Jennifer A and Vasan, Ramachandran S and Fitzpatrick, Annette L and Fornage, Myriam and Ding, Jun and Carson, April P and Abecasis, Goncalo and Dupuis, Jos{\'e}e and Reiner, Alexander and Kooperberg, Charles and Hou, Lifang and Psaty, Bruce M and Wilson, James G and Levy, Daniel and Rotter, Jerome I and Bis, Joshua C and Satizabal, Claudia L and Arking, Dan E and Liu, Chunyu} } @article {9323, title = {Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-analysis of Community-Based Cohorts.}, journal = {Neurology}, year = {2023}, month = {2023 Mar 16}, abstract = {

BACKGROUND AND OBJECTIVES: Previous studies suggest lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer{\textquoteright}s disease (AD) and AD related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults.

METHODS: We included dementia-free participants from nine diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within {\textpm}5 years (i.e., cross-sectional analyses) or 5 to 20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (<60 vs. >=60 years). Fixed-effects or sample size-weighted meta-analyses were performed to combine results. Finally, we performed Mendelian randomization (MR) analyses to assess causality.

RESULTS: We included up to 19,152 participants (mean age 59 years, 57\% women). Higher mtDNA CN was cross-sectionally associated with better general cognitive function (Beta=0.04; 95\% CI 0.02, 0.06) independent of age, sex, batch effects, race/ethnicity, time between blood draw and cognitive evaluation, cohort-specific variables, and education. Additional adjustment for blood cell counts or cardiometabolic traits led to slightly attenuated results. We observed similar significant associations with cognition in prospective analyses, although of reduced magnitude. We found no significant associations between mtDNA CN and brain MRI measures in meta-analyses. MR analyses did not reveal a causal relation between mtDNA CN in blood and cognition.

DISCUSSION: Higher mtDNA CN in blood is associated with better current and future general cognitive function in large and diverse communities across the US. Although MR analyses did not support a causal role, additional research is needed to assess causality. Circulating mtDNA CN could serve nevertheless as a biomarker of current and future cognitive function in the community.

}, issn = {1526-632X}, doi = {10.1212/WNL.0000000000207157}, author = {Zhang, Yuankai and Liu, Xue and Wiggins, Kerri L and Kurniansyah, Nuzulul and Guo, Xiuqing and Rodrigue, Amanda L and Zhao, Wei and Yanek, Lisa R and Ratliff, Scott M and Pitsillides, Achilleas and Aguirre Pati{\~n}o, Juan Sebastian and Sofer, Tamar and Arking, Dan E and Austin, Thomas R and Beiser, Alexa S and Blangero, John and Boerwinkle, Eric and Bressler, Jan and Curran, Joanne E and Hou, Lifang and Hughes, Timothy M and Kardia, Sharon L and Launer, Lenore and Levy, Daniel and Mosley, Tom H and Nasrallah, Ilya M and Rich, Stephen S and Rotter, Jerome I and Seshadri, Sudha and Tarraf, Wassim and Gonz{\'a}lez, Kevin A and Ramachandran, Vasan and Yaffe, Kristine and Nyquist, Paul A and Psaty, Bruce M and DeCarli, Charles S and Smith, Jennifer A and Glahn, David C and Gonz{\'a}lez, Hector M and Bis, Joshua C and Fornage, Myriam and Heckbert, Susan R and Fitzpatrick, Annette L and Liu, Chunyu and Satizabal, Claudia L} } @article {9285, title = {Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease.}, journal = {JAMA Cardiol}, year = {2023}, month = {2023 Feb 01}, abstract = {

IMPORTANCE: Protein-truncating variants (PTVs) in apolipoprotein B (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are associated with significantly lower low-density lipoprotein (LDL) cholesterol concentrations. The association of these PTVs with coronary heart disease (CHD) warrants further characterization in large, multiracial prospective cohort studies.

OBJECTIVE: To evaluate the association of PTVs in APOB and PCSK9 with LDL cholesterol concentrations and CHD risk.

DESIGN, SETTING, AND PARTICIPANTS: This studied included participants from 5 National Heart, Lung, and Blood Institute (NHLBI) studies and the UK Biobank. NHLBI study participants aged 5 to 84 years were recruited between 1971 and 2002 across the US and underwent whole-genome sequencing. UK Biobank participants aged 40 to 69 years were recruited between 2006 and 2010 in the UK and underwent whole-exome sequencing. Data were analyzed from June 2021 to October 2022.

EXPOSURES: PTVs in APOB and PCSK9.

MAIN OUTCOMES AND MEASURES: Estimated untreated LDL cholesterol levels and CHD.

RESULTS: Among 19 073 NHLBI participants (10 598 [55.6\%] female; mean [SD] age, 52 [17] years), 139 (0.7\%) carried an APOB or PCSK9 PTV, which was associated with 49 mg/dL (95\% CI, 43-56) lower estimated untreated LDL cholesterol level. Over a median (IQR) follow-up of 21.5 (13.9-29.4) years, incident CHD was observed in 12 of 139 carriers (8.6\%) vs 3029 of 18 934 noncarriers (16.0\%), corresponding to an adjusted hazard ratio of 0.51 (95\% CI, 0.28-0.89; P = .02). Among 190 464 UK Biobank participants (104 831 [55.0\%] female; mean [SD] age, 57 [8] years), 662 (0.4\%) carried a PTV, which was associated with 45 mg/dL (95\% CI, 42-47) lower estimated untreated LDL cholesterol level. Estimated CHD risk by age 75 years was 3.7\% (95\% CI, 2.0-5.3) in carriers vs 7.0\% (95\% CI, 6.9-7.2) in noncarriers, corresponding to an adjusted hazard ratio of 0.51 (95\% CI, 0.32-0.81; P = .004).

CONCLUSIONS AND RELEVANCE: Among 209 537 individuals in this study, 0.4\% carried an APOB or PCSK9 PTV that was associated with less exposure to LDL cholesterol and a 49\% lower risk of CHD.

}, issn = {2380-6591}, doi = {10.1001/jamacardio.2022.5271}, author = {Dron, Jacqueline S and Patel, Aniruddh P and Zhang, Yiyi and Jurgens, Sean J and Maamari, Dimitri J and Wang, Minxian and Boerwinkle, Eric and Morrison, Alanna C and de Vries, Paul S and Fornage, Myriam and Hou, Lifang and Lloyd-Jones, Donald M and Psaty, Bruce M and Tracy, Russell P and Bis, Joshua C and Vasan, Ramachandran S and Levy, Daniel and Heard-Costa, Nancy and Rich, Stephen S and Guo, Xiuqing and Taylor, Kent D and Gibbs, Richard A and Rotter, Jerome I and Willer, Cristen J and Oelsner, Elizabeth C and Moran, Andrew E and Peloso, Gina M and Natarajan, Pradeep and Khera, Amit V} } @article {9388, title = {Association of Severe Hypercholesterolemia and Familial Hypercholesterolemia Genotype With Risk of Coronary Heart Disease.}, journal = {Circulation}, volume = {147}, year = {2023}, month = {2023 May 16}, pages = {1556-1559}, keywords = {Coronary Disease, Genotype, Humans, Hypercholesterolemia, Hyperlipoproteinemia Type II}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.123.064168}, author = {Zhang, Yiyi and Dron, Jacqueline S and Bellows, Brandon K and Khera, Amit V and Liu, Junxiu and Balte, Pallavi P and Oelsner, Elizabeth C and Amr, Sami Samir and Lebo, Matthew S and Nagy, Anna and Peloso, Gina M and Natarajan, Pradeep and Rotter, Jerome I and Willer, Cristen and Boerwinkle, Eric and Ballantyne, Christie M and Lutsey, Pamela L and Fornage, Myriam and Lloyd-Jones, Donald M and Hou, Lifang and Psaty, Bruce M and Bis, Joshua C and Floyd, James S and Vasan, Ramachandran S and Heard-Costa, Nancy L and Carson, April P and Hall, Michael E and Rich, Stephen S and Guo, Xiuqing and Kazi, Dhruv S and de Ferranti, Sarah D and Moran, Andrew E} } @article {9418, title = {Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study.}, journal = {medRxiv}, year = {2023}, month = {2023 Jun 29}, abstract = {

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a {\textpm}500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73\%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56\%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.

}, doi = {10.1101/2023.06.28.23291966}, author = {Wang, Yuxuan and Selvaraj, Margaret Sunitha and Li, Xihao and Li, Zilin and Holdcraft, Jacob A and Arnett, Donna K and Bis, Joshua C and Blangero, John and Boerwinkle, Eric and Bowden, Donald W and Cade, Brian E and Carlson, Jenna C and Carson, April P and Chen, Yii-Der Ida and Curran, Joanne E and de Vries, Paul S and Dutcher, Susan K and Ellinor, Patrick T and Floyd, James S and Fornage, Myriam and Freedman, Barry I and Gabriel, Stacey and Germer, Soren and Gibbs, Richard A and Guo, Xiuqing and He, Jiang and Heard-Costa, Nancy and Hildalgo, Bertha and Hou, Lifang and Irvin, Marguerite R and Joehanes, Roby and Kaplan, Robert C and Kardia, Sharon Lr and Kelly, Tanika N and Kim, Ryan and Kooperberg, Charles and Kral, Brian G and Levy, Daniel and Li, Changwei and Liu, Chunyu and Lloyd-Jone, Don and Loos, Ruth Jf and Mahaney, Michael C and Martin, Lisa W and Mathias, Rasika A and Minster, Ryan L and Mitchell, Braxton D and Montasser, May E and Morrison, Alanna C and Murabito, Joanne M and Naseri, Take and O{\textquoteright}Connell, Jeffrey R and Palmer, Nicholette D and Preuss, Michael H and Psaty, Bruce M and Raffield, Laura M and Rao, Dabeeru C and Redline, Susan and Reiner, Alexander P and Rich, Stephen S and Ruepena, Muagututi{\textquoteright}a Sefuiva and Sheu, Wayne H-H and Smith, Jennifer A and Smith, Albert and Tiwari, Hemant K and Tsai, Michael Y and Viaud-Martinez, Karine A and Wang, Zhe and Yanek, Lisa R and Zhao, Wei and Rotter, Jerome I and Lin, Xihong and Natarajan, Pradeep and Peloso, Gina M} } @article {9543, title = {A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies.}, journal = {bioRxiv}, year = {2023}, month = {2023 Nov 02}, abstract = {

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of and an intergenic region on chromosome 1.

}, doi = {10.1101/2023.10.30.564764}, author = {Li, Xihao and Chen, Han and Selvaraj, Margaret Sunitha and Van Buren, Eric and Zhou, Hufeng and Wang, Yuxuan and Sun, Ryan and McCaw, Zachary R and Yu, Zhi and Arnett, Donna K and Bis, Joshua C and Blangero, John and Boerwinkle, Eric and Bowden, Donald W and Brody, Jennifer A and Cade, Brian E and Carson, April P and Carlson, Jenna C and Chami, Nathalie and Chen, Yii-Der Ida and Curran, Joanne E and de Vries, Paul S and Fornage, Myriam and Franceschini, Nora and Freedman, Barry I and Gu, Charles and Heard-Costa, Nancy L and He, Jiang and Hou, Lifang and Hung, Yi-Jen and Irvin, Marguerite R and Kaplan, Robert C and Kardia, Sharon L R and Kelly, Tanika and Konigsberg, Iain and Kooperberg, Charles and Kral, Brian G and Li, Changwei and Loos, Ruth J F and Mahaney, Michael C and Martin, Lisa W and Mathias, Rasika A and Minster, Ryan L and Mitchell, Braxton D and Montasser, May E and Morrison, Alanna C and Palmer, Nicholette D and Peyser, Patricia A and Psaty, Bruce M and Raffield, Laura M and Redline, Susan and Reiner, Alexander P and Rich, Stephen S and Sitlani, Colleen M and Smith, Jennifer A and Taylor, Kent D and Tiwari, Hemant and Vasan, Ramachandran S and Wang, Zhe and Yanek, Lisa R and Yu, Bing and Rice, Kenneth M and Rotter, Jerome I and Peloso, Gina M and Natarajan, Pradeep and Li, Zilin and Liu, Zhonghua and Lin, Xihong} } @article {9449, title = {Whole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles.}, journal = {medRxiv}, year = {2023}, month = {2023 Jun 12}, abstract = {

UNLABELLED: 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{\textquoteright}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.

}, doi = {10.1101/2023.06.07.23291095}, author = {Huffman, Jennifer E and Nicolas, Jayna and Hahn, Julie and Heath, Adam S and Raffield, Laura M and Yanek, Lisa R and Brody, Jennifer A and Thibord, Florian and Almasy, Laura and Bartz, Traci M and Bielak, Lawrence F and Bowler, Russell P and Carrasquilla, Germ{\'a}n D and Chasman, Daniel I and Chen, Ming-Huei and Emmert, David B and Ghanbari, Mohsen and Haessle, Jeffery and Hottenga, Jouke-Jan and Kleber, Marcus E and Le, Ngoc-Quynh and Lee, Jiwon and Lewis, Joshua P and Li-Gao, Ruifang and Luan, Jian{\textquoteright}an and Malmberg, Anni and Mangino, Massimo and Marioni, Riccardo E and Martinez-Perez, Angel and Pankratz, Nathan and Polasek, Ozren and Richmond, Anne and Rodriguez, Benjamin At and Rotter, Jerome I and Steri, Maristella and Suchon, Pierre and Trompet, Stella and Weiss, Stefan and Zare, Marjan and Auer, Paul and Cho, Michael H and Christofidou, Paraskevi and Davies, Gail and de Geus, Eco and Deleuze, Jean-Francois and Delgado, Graciela E and Ekunwe, Lynette and Faraday, Nauder and G{\"o}gele, Martin and Greinacher, Andreas and He, Gao and Howard, Tom and Joshi, Peter K and Kilpel{\"a}inen, Tuomas O and Lahti, Jari and Linneberg, Allan and Naitza, Silvia and Noordam, Raymond and Pa{\"u}ls-Verg{\'e}s, Ferran and Rich, Stephen S and Rosendaal, Frits R and Rudan, Igor and Ryan, Kathleen A and Souto, Juan Carlos and van Rooij, Frank Ja and Wang, Heming and Zhao, Wei and Becker, Lewis C and Beswick, Andrew and Brown, Michael R and Cade, Brian E and Campbell, Harry and Cho, Kelly and Crapo, James D and Curran, Joanne E and de Maat, Moniek Pm and Doyle, Margaret and Elliott, Paul and Floyd, James S and Fuchsberger, Christian and Grarup, Niels and Guo, Xiuqing and Harris, Sarah E and Hou, Lifang and Kolcic, Ivana and Kooperberg, Charles and Menni, Cristina and Nauck, Matthias and O{\textquoteright}Connell, Jeffrey R and Orr{\`u}, Valeria and Psaty, Bruce M and R{\"a}ikk{\"o}nen, Katri and Smith, Jennifer A and Soria, Jos{\'e} Manuel and Stott, David J and van Hylckama Vlieg, Astrid and Watkins, Hugh and Willemsen, Gonneke and Wilson, Peter and Ben-Shlomo, Yoav and Blangero, John and Boomsma, Dorret and Cox, Simon R and Dehghan, Abbas and Eriksson, Johan G and Fiorillo, Edoardo and Fornage, Myriam and Hansen, Torben and Hayward, Caroline and Ikram, M Arfan and Jukema, J Wouter and Kardia, Sharon Lr and Lange, Leslie A and M{\"a}rz, Winfried and Mathias, Rasika A and Mitchell, Braxton D and Mook-Kanamori, Dennis O and Morange, Pierre-Emmanuel and Pedersen, Oluf and Pramstaller, Peter P and Redline, Susan and Reiner, Alexander and Ridker, Paul M and Silverman, Edwin K and Spector, Tim D and V{\"o}lker, Uwe and Wareham, Nick and Wilson, James F and Yao, Jie and Tr{\'e}gou{\"e}t, David-Alexandre and Johnson, Andrew D and Wolberg, Alisa S and de Vries, Paul S and Sabater-Lleal, Maria and Morrison, Alanna C and Smith, Nicholas L} } @article {9484, title = {WHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE.}, journal = {medRxiv}, year = {2023}, month = {2023 Aug 22}, abstract = {

Obesity 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 {\texttimes} 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.

}, doi = {10.1101/2023.08.21.23293271}, author = {Zhang, Xinruo and Brody, Jennifer A and Graff, Mariaelisa and Highland, Heather M and Chami, Nathalie and Xu, Hanfei and Wang, Zhe and Ferrier, Kendra and Chittoor, Geetha and Josyula, Navya S and Li, Xihao and Li, Zilin and Allison, Matthew A and Becker, Diane M and Bielak, Lawrence F and Bis, Joshua C and Boorgula, Meher Preethi and Bowden, Donald W and Broome, Jai G and Buth, Erin J and Carlson, Christopher S and Chang, Kyong-Mi and Chavan, Sameer and Chiu, Yen-Feng and Chuang, Lee-Ming and Conomos, Matthew P and DeMeo, Dawn L and Du, Margaret and Duggirala, Ravindranath and Eng, Celeste and Fohner, Alison E and Freedman, Barry I and Garrett, Melanie E and Guo, Xiuqing and Haiman, Chris and Heavner, Benjamin D and Hidalgo, Bertha and Hixson, James E and Ho, Yuk-Lam and Hobbs, Brian D and Hu, Donglei and Hui, Qin and Hwu, Chii-Min and Jackson, Rebecca D and Jain, Deepti and Kalyani, Rita R and Kardia, Sharon L R and Kelly, Tanika N and Lange, Ethan M and LeNoir, Michael and Li, Changwei and Marchand, Loic Le and McDonald, Merry-Lynn N and McHugh, Caitlin P and Morrison, Alanna C and Naseri, Take and O{\textquoteright}Connell, Jeffrey and O{\textquoteright}Donnell, Christopher J and Palmer, Nicholette D and Pankow, James S and Perry, James A and Peters, Ulrike and Preuss, Michael H and Rao, D C and Regan, Elizabeth A and Reupena, Sefuiva M and Roden, Dan M and Rodriguez-Santana, Jose and Sitlani, Colleen M and Smith, Jennifer A and Tiwari, Hemant K and Vasan, Ramachandran S and Wang, Zeyuan and Weeks, Daniel E and Wessel, Jennifer and Wiggins, Kerri L and Wilkens, Lynne R and Wilson, Peter W F and Yanek, Lisa R and Yoneda, Zachary T and Zhao, Wei and Z{\"o}llner, Sebastian and Arnett, Donna K and Ashley-Koch, Allison E and Barnes, Kathleen C and Blangero, John and Boerwinkle, Eric and Burchard, Esteban G and Carson, April P and Chasman, Daniel I and Chen, Yii-Der Ida and Curran, Joanne E and Fornage, Myriam and Gordeuk, Victor R and He, Jiang and Heckbert, Susan R and Hou, Lifang and Irvin, Marguerite R and Kooperberg, Charles and Minster, Ryan L and Mitchell, Braxton D and Nouraie, Mehdi and Psaty, Bruce M and Raffield, Laura M and Reiner, Alexander P and Rich, Stephen S and Rotter, Jerome I and Shoemaker, M Benjamin and Smith, Nicholas L and Taylor, Kent D and Telen, Marilyn J and Weiss, Scott T and Zhang, Yingze and Costa, Nancy Heard- and Sun, Yan V and Lin, Xihong and Cupples, L Adrienne and Lange, Leslie A and Liu, Ching-Ti and Loos, Ruth J F and North, Kari E and Justice, Anne E} } @article {9500, title = {Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium.}, journal = {bioRxiv}, year = {2023}, month = {2023 Sep 12}, abstract = {

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

}, doi = {10.1101/2023.09.10.555215}, author = {Jiang, Min-Zhi and Gaynor, Sheila M and Li, Xihao and Van Buren, Eric and Stilp, Adrienne and Buth, Erin and Wang, Fei Fei and Manansala, Regina and Gogarten, Stephanie M and Li, Zilin and Polfus, Linda M and Salimi, Shabnam and Bis, Joshua C and Pankratz, Nathan and Yanek, Lisa R and Durda, Peter and Tracy, Russell P and Rich, Stephen S and Rotter, Jerome I and Mitchell, Braxton D and Lewis, Joshua P and Psaty, Bruce M and Pratte, Katherine A and Silverman, Edwin K and Kaplan, Robert C and Avery, Christy and North, Kari and Mathias, Rasika A and Faraday, Nauder and Lin, Honghuang and Wang, Biqi and Carson, April P and Norwood, Arnita F and Gibbs, Richard A and Kooperberg, Charles and Lundin, Jessica and Peters, Ulrike and Dupuis, Jos{\'e}e and Hou, Lifang and Fornage, Myriam and Benjamin, Emelia J and Reiner, Alexander P and Bowler, Russell P and Lin, Xihong and Auer, Paul L and Raffield, Laura M} } @article {9620, title = {Familial Hypercholesterolemia Variant and Cardiovascular Risk in Individuals With Elevated Cholesterol.}, journal = {JAMA Cardiol}, year = {2024}, month = {2024 Jan 31}, abstract = {

IMPORTANCE: Familial hypercholesterolemia (FH) is a genetic disorder that often results in severely high low-density lipoprotein cholesterol (LDL-C) and high risk of premature coronary heart disease (CHD). However, the impact of FH variants on CHD risk among individuals with moderately elevated LDL-C is not well quantified.

OBJECTIVE: To assess CHD risk associated with FH variants among individuals with moderately (130-189 mg/dL) and severely (>=190 mg/dL) elevated LDL-C and to quantify excess CHD deaths attributable to FH variants in US adults.

DESIGN, SETTING, AND PARTICIPANTS: A total of 21 426 individuals without preexisting CHD from 6 US cohort studies (Atherosclerosis Risk in Communities study, Coronary Artery Risk Development in Young Adults study, Cardiovascular Health Study, Framingham Heart Study Offspring cohort, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis) were included, 63 of whom had an FH variant. Data were collected from 1971 to 2018, and the median (IQR) follow-up was 18 (13-28) years. Data were analyzed from March to May 2023.

EXPOSURES: LDL-C, cumulative past LDL-C, FH variant status.

MAIN OUTCOMES AND MEASURES: Cox proportional hazards models estimated associations between FH variants and incident CHD. The Cardiovascular Disease Policy Model projected excess CHD deaths associated with FH variants in US adults.

RESULTS: Of the 21 426 individuals without preexisting CHD (mean [SD] age 52.1 [15.5] years; 12 041 [56.2\%] female), an FH variant was found in 22 individuals with moderately elevated LDL-C (0.3\%) and in 33 individuals with severely elevated LDL-C (2.5\%). The adjusted hazard ratios for incident CHD comparing those with and without FH variants were 2.9 (95\% CI, 1.4-6.0) and 2.6 (95\% CI, 1.4-4.9) among individuals with moderately and severely elevated LDL-C, respectively. The association between FH variants and CHD was slightly attenuated when further adjusting for baseline LDL-C level, whereas the association was no longer statistically significant after adjusting for cumulative past LDL-C exposure. Among US adults 20 years and older with no history of CHD and LDL-C 130 mg/dL or higher, more than 417 000 carry an FH variant and were projected to experience more than 12 000 excess CHD deaths in those with moderately elevated LDL-C and 15 000 in those with severely elevated LDL-C compared with individuals without an FH variant.

CONCLUSIONS AND RELEVANCE: In this pooled cohort study, the presence of FH variants was associated with a 2-fold higher CHD risk, even when LDL-C was only moderately elevated. The increased CHD risk appeared to be largely explained by the higher cumulative LDL-C exposure in individuals with an FH variant compared to those without. Further research is needed to assess the value of adding genetic testing to traditional phenotypic FH screening.

}, issn = {2380-6591}, doi = {10.1001/jamacardio.2023.5366}, author = {Zhang, Yiyi and Dron, Jacqueline S and Bellows, Brandon K and Khera, Amit V and Liu, Junxiu and Balte, Pallavi P and Oelsner, Elizabeth C and Amr, Sami Samir and Lebo, Matthew S and Nagy, Anna and Peloso, Gina M and Natarajan, Pradeep and Rotter, Jerome I and Willer, Cristen and Boerwinkle, Eric and Ballantyne, Christie M and Lutsey, Pamela L and Fornage, Myriam and Lloyd-Jones, Donald M and Hou, Lifang and Psaty, Bruce M and Bis, Joshua C and Floyd, James S and Vasan, Ramachandran S and Heard-Costa, Nancy L and Carson, April P and Hall, Michael E and Rich, Stephen S and Guo, Xiuqing and Kazi, Dhruv S and de Ferranti, Sarah D and Moran, Andrew E} } @article {9787, title = {Rare variant contribution to the heritability of coronary artery disease.}, journal = {Nat Commun}, volume = {15}, year = {2024}, month = {2024 Oct 09}, pages = {8741}, abstract = {

Whole genome sequences (WGS) enable discovery of rare variants which may contribute to missing heritability of coronary artery disease (CAD). To measure their contribution, we apply the GREML-LDMS-I approach to WGS of 4949 cases and 17,494 controls of European ancestry from the NHLBI TOPMed program. We estimate CAD heritability at 34.3\% assuming a prevalence of 8.2\%. Ultra-rare (minor allele frequency <= 0.1\%) variants with low linkage disequilibrium (LD) score contribute ~50\% of the heritability. We also investigate CAD heritability enrichment using a diverse set of functional annotations: i) constraint; ii) predicted protein-altering impact; iii) cis-regulatory elements from a cell-specific chromatin atlas of the human coronary; and iv) annotation principal components representing a wide range of functional processes. We observe marked enrichment of CAD heritability for most functional annotations. These results reveal the predominant role of ultra-rare variants in low LD on the heritability of CAD. Moreover, they highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

}, keywords = {Case-Control Studies, Coronary Artery Disease, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Middle Aged, Polymorphism, Single Nucleotide, White People, Whole Genome Sequencing}, issn = {2041-1723}, doi = {10.1038/s41467-024-52939-6}, author = {Rocheleau, Ghislain and Clarke, Shoa L and Auguste, Ga{\"e}lle and Hasbani, Natalie R and Morrison, Alanna C and Heath, Adam S and Bielak, Lawrence F and Iyer, Kruthika R and Young, Erica P and Stitziel, Nathan O and Jun, Goo and Laurie, Cecelia and Broome, Jai G and Khan, Alyna T and Arnett, Donna K and Becker, Lewis C and Bis, Joshua C and Boerwinkle, Eric and Bowden, Donald W and Carson, April P and Ellinor, Patrick T and Fornage, Myriam and Franceschini, Nora and Freedman, Barry I and Heard-Costa, Nancy L and Hou, Lifang and Chen, Yii-Der Ida and Kenny, Eimear E and Kooperberg, Charles and Kral, Brian G and Loos, Ruth J F and Lutz, Sharon M and Manson, JoAnn E and Martin, Lisa W and Mitchell, Braxton D and Nassir, Rami and Palmer, Nicholette D and Post, Wendy S and Preuss, Michael H and Psaty, Bruce M and Raffield, Laura M and Regan, Elizabeth A and Rich, Stephen S and Smith, Jennifer A and Taylor, Kent D and Yanek, Lisa R and Young, Kendra A and Hilliard, Austin T and Tcheandjieu, Catherine and Peyser, Patricia A and Vasan, Ramachandran S and Rotter, Jerome I and Miller, Clint L and Assimes, Themistocles L and de Vries, Paul S and Do, Ron} } @article {9869, title = {Cardiovascular Risk Factors and Genetic Risk in Transthyretin V142I Carriers.}, journal = {JACC Heart Fail}, volume = {13}, year = {2025}, month = {2025 Jan}, pages = {91-101}, abstract = {

BACKGROUND: Nearly 3\% to 4\% of Black individuals in the United States carry the transthyretin V142I variant, which increases their risk of heart failure. However, the role of cardiovascular (CV) risk factors (RFs) in influencing the risk of clinical outcomes among V142I variant carriers is unknown.

OBJECTIVES: This study aimed to assess the impact of CV RFs on the risk of heart failure in V142I carriers.

METHODS: This study included self-identified Black individuals without prevalent heart failure from 6 TOPMed (Trans-Omics for Precision Medicine) cohorts, the REGARDS (Reasons for Geographic And Racial Differences in Stroke) study, and the All of Us Research Program. The cohort was stratified based on the V142I genotype and the number of CV RFs (hypertension, diabetes, obesity, and hypercholesterolemia). Adjusted Cox models were used to assess the association of heart failure with the V142I genotype and CV RF profile, taking noncarriers with a favorable CV RF profile as reference.

RESULTS: The cross-sectional analysis, including 1,625 V142I carriers among 48,365 Black individuals, found that the prevalence of CV RFs did not vary by V142I carrier status. In the longitudinal analysis, there were 587 (3.2\%) V142I carriers among 18,407 Black individuals (median age: 60 years [Q1-Q3: 52-68 years], 63.0\% female). Among carriers, the heart failure risk was attenuated with a favorable (0 or 1 RF) CV RF profile (adjusted HR: 2.26; 95\%~CI: 1.58-3.23) compared with an unfavorable (3 or 4 RFs) CV RF profile (adjusted HR: 4.14; 95\%~CI: 2.79-6.14).

CONCLUSIONS: A favorable CV RF profile lowers but does not abrogate V142I variant-associated heart failure risk. This study highlights the importance of having a favorable CV RF profile among V142I carriers for risk reduction of heart failure.

}, keywords = {Aged, Black or African American, Cardiovascular Diseases, Cross-Sectional Studies, Diabetes Mellitus, Female, Genotype, Heart Disease Risk Factors, Heart Failure, Heterozygote, Humans, Hypercholesterolemia, Hypertension, Male, Middle Aged, Obesity, Prealbumin, Risk Factors, United States}, issn = {2213-1787}, doi = {10.1016/j.jchf.2024.08.019}, author = {Shetty, Naman S and Gaonkar, Mokshad and Pampana, Akhil and Patel, Nirav and Morrison, Alanna C and Reiner, Alexander P and Carson, April P and Yu, Bing and Psaty, Bruce M and Kooperberg, Charles and Fatkin, Diane and Boerwinkle, Eric and Rotter, Jerome I and Taylor, Kent D and Hou, Lifang and Irvin, Marguerite R and Hall, Michael E and Maurer, Mathew and Fornage, Myriam and Armstrong, Nicole D and Bart, Nicole and Goyal, Parag and Rich, Stephen S and Vasan, Ramachandran S and Li, Peng and Arora, Garima and Arora, Pankaj} } @article {9899, title = {A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies.}, journal = {Nat Comput Sci}, volume = {5}, year = {2025}, month = {2025 Feb}, pages = {125-143}, abstract = {

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally scalable analytical pipeline for functionally informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits in 61,838 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered and replicated new associations with lipid traits missed by single-trait analysis.

}, keywords = {Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Lipids, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Whole Genome Sequencing}, issn = {2662-8457}, doi = {10.1038/s43588-024-00764-8}, author = {Li, Xihao and Chen, Han and Selvaraj, Margaret Sunitha and Van Buren, Eric and Zhou, Hufeng and Wang, Yuxuan and Sun, Ryan and McCaw, Zachary R and Yu, Zhi and Jiang, Min-Zhi and DiCorpo, Daniel and Gaynor, Sheila M and Dey, Rounak and Arnett, Donna K and Benjamin, Emelia J and Bis, Joshua C and Blangero, John and Boerwinkle, Eric and Bowden, Donald W and Brody, Jennifer A and Cade, Brian E and Carson, April P and Carlson, Jenna C and Chami, Nathalie and Chen, Yii-Der Ida and Curran, Joanne E and de Vries, Paul S and Fornage, Myriam and Franceschini, Nora and Freedman, Barry I and Gu, Charles and Heard-Costa, Nancy L and He, Jiang and Hou, Lifang and Hung, Yi-Jen and Irvin, Marguerite R and Kaplan, Robert C and Kardia, Sharon L R and Kelly, Tanika N and Konigsberg, Iain and Kooperberg, Charles and Kral, Brian G and Li, Changwei and Li, Yun and Lin, Honghuang and Liu, Ching-Ti and Loos, Ruth J F and Mahaney, Michael C and Martin, Lisa W and Mathias, Rasika A and Mitchell, Braxton D and Montasser, May E and Morrison, Alanna C and Naseri, Take and North, Kari E and Palmer, Nicholette D and Peyser, Patricia A and Psaty, Bruce M and Redline, Susan and Reiner, Alexander P and Rich, Stephen S and Sitlani, Colleen M and Smith, Jennifer A and Taylor, Kent D and Tiwari, Hemant K and Vasan, Ramachandran S and Viali, Satupa{\textquoteright}itea and Wang, Zhe and Wessel, Jennifer and Yanek, Lisa R and Yu, Bing and Dupuis, Jos{\'e}e and Meigs, James B and Auer, Paul L and Raffield, Laura M and Manning, Alisa K and Rice, Kenneth M and Rotter, Jerome I and Peloso, Gina M and Natarajan, Pradeep and Li, Zilin and Liu, Zhonghua and Lin, Xihong} } @article {9942, title = {Whole genome sequencing analysis of body mass index identifies novel African ancestry-specific risk allele.}, journal = {Nat Commun}, volume = {16}, year = {2025}, month = {2025 Apr 11}, pages = {3470}, abstract = {

Obesity 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 (P < 5 {\texttimes} 10), including two secondary signals. Notably, we identified and replicated a novel low-frequency single nucleotide polymorphism (SNP) in MTMR3 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 POC5 and DMD 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.

}, keywords = {Adult, African People, Alleles, Body Mass Index, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Population Groups, Whole Genome Sequencing}, issn = {2041-1723}, doi = {10.1038/s41467-025-58420-2}, author = {Zhang, Xinruo and Brody, Jennifer A and Graff, Mariaelisa and Highland, Heather M and Chami, Nathalie and Xu, Hanfei and Wang, Zhe and Ferrier, Kendra R and Chittoor, Geetha and Josyula, Navya Shilpa and Meyer, Mariah and Gupta, Shreyash and Li, Xihao and Li, Zilin and Allison, Matthew A and Becker, Diane M and Bielak, Lawrence F and Bis, Joshua C and Boorgula, Meher Preethi and Bowden, Donald W and Broome, Jai G and Buth, Erin J and Carlson, Christopher S and Chang, Kyong-Mi and Chavan, Sameer and Chiu, Yen-Feng and Chuang, Lee-Ming and Conomos, Matthew P and DeMeo, Dawn L and Du, Mengmeng and Duggirala, Ravindranath and Eng, Celeste and Fohner, Alison E and Freedman, Barry I and Garrett, Melanie E and Guo, Xiuqing and Haiman, Chris and Heavner, Benjamin D and Hidalgo, Bertha and Hixson, James E and Ho, Yuk-Lam and Hobbs, Brian D and Hu, Donglei and Hui, Qin and Hwu, Chii-Min and Jackson, Rebecca D and Jain, Deepti and Kalyani, Rita R and Kardia, Sharon L R and Kelly, Tanika N and Lange, Ethan M and LeNoir, Michael and Li, Changwei and Le Marchand, Lo{\"\i}c and McDonald, Merry-Lynn N and McHugh, Caitlin P and Morrison, Alanna C and Naseri, Take and O{\textquoteright}Connell, Jeffrey and O{\textquoteright}Donnell, Christopher J and Palmer, Nicholette D and Pankow, James S and Perry, James A and Peters, Ulrike and Preuss, Michael H and Rao, D C and Regan, Elizabeth A and Reupena, Sefuiva M and Roden, Dan M and Rodriguez-Santana, Jose and Sitlani, Colleen M and Smith, Jennifer A and Tiwari, Hemant K and Vasan, Ramachandran S and Wang, Zeyuan and Weeks, Daniel E and Wessel, Jennifer and Wiggins, Kerri L and Wilkens, Lynne R and Wilson, Peter W F and Yanek, Lisa R and Yoneda, Zachary T and Zhao, Wei and Z{\"o}llner, Sebastian and Arnett, Donna K and Ashley-Koch, Allison E and Barnes, Kathleen C and Blangero, John and Boerwinkle, Eric and Burchard, Esteban G and Carson, April P and Chasman, Daniel I and Ida Chen, Yii-Der and Curran, Joanne E and Fornage, Myriam and Gordeuk, Victor R and He, Jiang and Heckbert, Susan R and Hou, Lifang and Irvin, Marguerite R and Kooperberg, Charles and Minster, Ryan L and Mitchell, Braxton D and Nouraie, Mehdi and Psaty, Bruce M and Raffield, Laura M and Reiner, Alexander P and Rich, Stephen S and Rotter, Jerome I and Benjamin Shoemaker, M and Smith, Nicholas L and Taylor, Kent D and Telen, Marilyn J and Weiss, Scott T and Zhang, Yingze and Heard-Costa, Nancy and Sun, Yan V and Lin, Xihong and Cupples, L Adrienne and Lange, Leslie A and Liu, Ching-Ti and Loos, Ruth J F and North, Kari E and Justice, Anne E} }