@article {1248, title = {European ancestry as a risk factor for atrial fibrillation in African Americans.}, journal = {Circulation}, volume = {122}, year = {2010}, month = {2010 Nov 16}, pages = {2009-15}, abstract = {

BACKGROUND: Despite a higher burden of standard atrial fibrillation (AF) risk factors, African Americans have a lower risk of AF than whites. It is unknown whether the higher risk is due to genetic or environmental factors. Because African Americans have varying degrees of European ancestry, we sought to test the hypothesis that European ancestry is an independent risk factor for AF.

METHODS AND RESULTS: We studied whites (n=4543) and African Americans (n=822) in the Cardiovascular Health Study (CHS) and whites (n=10 902) and African Americans (n=3517) in the Atherosclerosis Risk in Communities (ARIC) Study (n=3517). Percent European ancestry in African Americans was estimated with 1747 ancestry informative markers from the Illumina custom ITMAT-Broad-CARe array. Among African Americans without baseline AF, 120 of 804 CHS participants and 181 of 3517 ARIC participants developed incident AF. A meta-analysis from the 2 studies revealed that every 10\% increase in European ancestry increased the risk of AF by 13\% (hazard ratio, 1.13; 95\% confidence interval, 1.03 to 1.23; P=0.007). After adjustment for potential confounders, European ancestry remained a predictor of incident AF in each cohort alone, with a combined estimated hazard ratio for each 10\% increase in European ancestry of 1.17 (95\% confidence interval, 1.07 to 1.29; P=0.001). A second analysis using 3192 ancestry informative markers from a genome-wide Affymetrix 6.0 array in ARIC African Americans yielded similar results.

CONCLUSIONS: European ancestry predicted risk of incident AF. Our study suggests that investigating genetic variants contributing to differential AF risk in individuals of African versus European ancestry will be informative.

}, keywords = {African Americans, Aged, Atrial Fibrillation, European Continental Ancestry Group, Female, Genome-Wide Association Study, Humans, Male, Middle Aged, Risk Factors}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.110.958306}, author = {Marcus, Gregory M and Alonso, Alvaro and Peralta, Carmen A and Lettre, Guillaume and Vittinghoff, Eric and Lubitz, Steven A and Fox, Ervin R and Levitzky, Yamini S and Mehra, Reena and Kerr, Kathleen F and Deo, Rajat and Sotoodehnia, Nona and Akylbekova, Meggie and Ellinor, Patrick T and Paltoo, Dina N and Soliman, Elsayed Z and Benjamin, Emelia J and Heckbert, Susan R} } @article {1306, title = {Electrocardiographic and clinical predictors separating atherosclerotic sudden cardiac death from incident coronary heart disease.}, journal = {Heart}, volume = {97}, year = {2011}, month = {2011 Oct}, pages = {1597-601}, abstract = {

OBJECTIVE: To identify specific ECG and clinical predictors that separate atherosclerotic sudden cardiac death (SCD) from incident coronary heart disease (CHD) (non-fatal events and non-sudden death) in the combined cohorts of the Atherosclerosis Risk in Communities study and the Cardiovascular Health Study.

METHODS: This analysis included 18,497 participants (58\% females, 24\% black individuals, mean age 58 years) who were initially free of clinical CHD. A competing risk analysis was conducted to examine the prognostic significance of baseline clinical characteristics and an extensive electronic database of ECG measurements for prediction of 229 cases of SCD as a first event versus 2297 incident CHD cases (2122 non-fatal events and 175 non-sudden death) that occurred during a median follow-up time of 13 years in the Cardiovascular Health Study and 14 years in the Atherosclerosis Risk in Communities study.

RESULTS: After adjusting for common CHD risk factors, a number of clinical characteristics and ECG measurements were independently predictive of SCD and CHD. However, the risk of SCD versus incident CHD was significantly different for race/ethnicity, hypertension, body mass index (BMI), heart rate, QTc, abnormally inverted T wave in any ECG lead group and level of ST elevation in V2. Black race/ethnicity (compared to non-black) was predictive of high SCD risk but less risk of incident CHD (p value for differences in the risk (HR) for SCD versus CHD <0.0001). Hypertension, increased heart rate, prolongation of QTc and abnormally inverted T wave were stronger predictors of high SCD risk compared to CHD (p value=0.0460, 0.0398, 0.0158 and 0.0265, respectively). BMI was not predictive of incident CHD but was predictive of high SCD risk in a quadratic fashion (p value=0.0220). On the other hand, elevated ST height as measured at the J point and that measured at 60 ms after the J point in V2 were not predictive of SCD but were predictive of high incident CHD risk (p value=0.0251 and 0.0155, respectively).

CONCLUSIONS: SCD and CHD have many risk factors in common. Hypertension, race/ethnicity, BMI, heart rate, QTc, abnormally inverted T wave in any ECG lead group and level of ST elevation in V2 have the potential to separate between the risks of SCD and CHD. These results need to be validated in another cohort.

}, keywords = {Adult, Aged, Aged, 80 and over, Body Mass Index, Continental Population Groups, Coronary Disease, Death, Sudden, Cardiac, Electrocardiography, Ethnic Groups, Female, Heart Rate, Humans, Hypertension, Male, Middle Aged, Predictive Value of Tests, Prognosis, Proportional Hazards Models, Risk Adjustment, Risk Factors, Time Factors, United States}, issn = {1468-201X}, doi = {10.1136/hrt.2010.215871}, author = {Soliman, Elsayed Z and Prineas, Ronald J and Case, L Douglas and Russell, Gregory and Rosamond, Wayne and Rea, Thomas and Sotoodehnia, Nona and Post, Wendy S and Siscovick, David and Psaty, Bruce M and Burke, Gregory L} } @article {7125, title = {Echocardiographic Predictors of Sudden Cardiac Death: The Atherosclerosis Risk in Communities Study and Cardiovascular Health Study.}, journal = {Circ Cardiovasc Imaging}, volume = {9}, year = {2016}, month = {2016 Aug}, abstract = {

BACKGROUND: This study assessed the echocardiographic predictors of sudden cardiac death (SCD) within 2 population-based cohorts.

METHODS AND RESULTS: Echocardiograms were obtained on 2383 participants (1993-1995) from the ARIC study (Atherosclerosis Risk in Communities; 100\% black) and 5366 participants (1987-1989 and 1994-1995) from the CHS (Cardiovascular Health Study). The main outcome was physician-adjudicated SCD. We used Cox proportional-hazards models with incident coronary heart disease and heart failure as time-dependent covariates to assess the association between echocardiographic variables and SCD, adjusting for Framingham risk score variables, coronary heart disease, and renal function. Cohort-specific results were meta-analyzed. During a median follow-up of 7.3 and 13.1 years, 44 ARIC study participants and 275 CHS participants had SCD, respectively. In the meta-analyzed results, the adjusted hazard ratios (95\% confidence intervals) for predictors of SCD were 3.07 (2.29-4.11) for reduced left ventricular ejection fraction; 1.85 (1.36-2.52) for mitral annular calcification; 1.64 (1.07-2.51) for mitral E/A >1.5, and 1.52 (1.14-2.02) for mitral E/A <0.7 (versus mitral E/A 0.7-1.5); 1.30 (1.15-1.48) per 1 SD increase in left ventricular mass; and 1.15 (1.02-1.30) per 1 SD increase in left atrial diameter. A receiver-operating characteristic model for prediction of SCD using Framingham risk score variables had a C statistic of 0.61 for ARIC study and 0.67 for CHS; the full multivariable model including all echocardiographic variables had a C statistic of 0.76 for ARIC study and 0.74 for CHS.

CONCLUSIONS: In addition to reduced left ventricular ejection fraction, we identified other echocardiographic-derived variables predictive for SCD that provided incremental value compared with clinical risk factors.

}, issn = {1942-0080}, doi = {10.1161/CIRCIMAGING.115.004431}, author = {Konety, Suma H and Koene, Ryan J and Norby, Faye L and Wilsdon, Tony and Alonso, Alvaro and Siscovick, David and Sotoodehnia, Nona and Gottdiener, John and Fox, Ervin R and Chen, Lin Y and Adabag, Selcuk and Folsom, Aaron R} } @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 {7464, title = {eGFR and Albuminuria in Relation to Risk of Incident Atrial Fibrillation: A Meta-Analysis of the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Cardiovascular Health Study.}, journal = {Clin J Am Soc Nephrol}, volume = {12}, year = {2017}, month = {2017 Sep 07}, pages = {1386-1398}, abstract = {

BACKGROUND AND OBJECTIVES: The incidence of atrial fibrillation is high in ESRD, but limited data are available on the incidence of atrial fibrillation across a broad range of kidney function. Thus, we examined the association of eGFR and urine albumin-to-creatinine ratio with risk of incident atrial fibrillation.

DESIGN, SETTING, PARTICIPANTS, \& MEASUREMENTS: We meta-analyzed three prospective cohorts: the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Cardiovascular Health Study. Cox regression models were performed examining the association of eGFR and urine albumin-to-creatinine ratio with incident atrial fibrillation adjusting for demographics and comorbidity. In additional analyses, we adjusted for measures of subclinical cardiovascular disease (by electrocardiogram and cardiac imaging) and interim heart failure and myocardial infarction events.

RESULTS: In the meta-analyzed study population of 16,769 participants without prevalent atrial fibrillation, across categories of decreasing eGFR (eGFR>90 [reference], 60-89, 45-59, 30-44, and <30 ml/min per 1.73 m(2)), there was a stepwise increase in the adjusted risk of incident atrial fibrillation: hazard ratios (95\% confidence intervals) were 1.00, 1.09 (0.97 to 1.24), 1.17 (1.00 to 1.38), 1.59 (1.28 to 1.98), and 2.03 (1.40 to 2.96), respectively. There was a stepwise increase in the adjusted risk of incident atrial fibrillation across categories of increasing urine albumin-to-creatinine ratio (urine albumin-to-creatinine ratio <15 [reference], 15-29, 30-299, and >=300 mg/g): hazard ratios (95\% confidence intervals) were 1.00, 1.04 (0.83 to 1.30), 1.47 (1.20 to 1.79), and 1.76 (1.18 to 2.62), respectively. The associations were consistent after adjustment for subclinical cardiovascular disease measures and interim heart failure and myocardial infarction events.

CONCLUSIONS: In this meta-analysis of three cohorts, reduced eGFR and elevated urine albumin-to-creatinine ratio were significantly associated with greater risk of incident atrial fibrillation, highlighting the need for further studies to understand mechanisms linking kidney disease with atrial fibrillation.

}, issn = {1555-905X}, doi = {10.2215/CJN.01860217}, author = {Bansal, Nisha and Zelnick, Leila R and Alonso, Alvaro and Benjamin, Emelia J and de Boer, Ian H and Deo, Rajat and Katz, Ronit and Kestenbaum, Bryan and Mathew, Jehu and Robinson-Cohen, Cassianne and Sarnak, Mark J and Shlipak, Michael G and Sotoodehnia, Nona and Young, Bessie and Heckbert, Susan R} } @article {7809, title = {Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6.}, journal = {Genome Biol}, volume = {19}, year = {2018}, month = {2018 07 17}, pages = {87}, abstract = {

BACKGROUND: Genome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear.

RESULTS: Here, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874~individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction.

CONCLUSIONS: Our approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes.

}, issn = {1474-760X}, doi = {10.1186/s13059-018-1457-6}, author = {Prins, Bram P and Mead, Timothy J and Brody, Jennifer A and Sveinbjornsson, Gardar and Ntalla, Ioanna and Bihlmeyer, Nathan A and van den Berg, Marten and Bork-Jensen, Jette and Cappellani, Stefania and Van Duijvenboden, Stefan and Klena, Nikolai T and Gabriel, George C and Liu, Xiaoqin and Gulec, Cagri and Grarup, Niels and Haessler, Jeffrey and Hall, Leanne M and Iorio, Annamaria and Isaacs, Aaron and Li-Gao, Ruifang and Lin, Honghuang and Liu, Ching-Ti and Lyytik{\"a}inen, Leo-Pekka and Marten, Jonathan and Mei, Hao and M{\"u}ller-Nurasyid, Martina and Orini, Michele and Padmanabhan, Sandosh and Radmanesh, Farid and Ramirez, Julia and Robino, Antonietta and Schwartz, Molly and van Setten, Jessica and Smith, Albert V and Verweij, Niek and Warren, Helen R and Weiss, Stefan and Alonso, Alvaro and Arnar, David O and Bots, Michiel L and de Boer, Rudolf A and Dominiczak, Anna F and Eijgelsheim, Mark and Ellinor, Patrick T and Guo, Xiuqing and Felix, Stephan B and Harris, Tamara B and Hayward, Caroline and Heckbert, Susan R and Huang, Paul L and Jukema, J W and K{\"a}h{\"o}nen, Mika and Kors, Jan A and Lambiase, Pier D and Launer, Lenore J and Li, Man and Linneberg, Allan and Nelson, Christopher P and Pedersen, Oluf and Perez, Marco and Peters, Annette and Polasek, Ozren and Psaty, Bruce M and Raitakari, Olli T and Rice, Kenneth M and Rotter, Jerome I and Sinner, Moritz F and Soliman, Elsayed Z and Spector, Tim D and Strauch, Konstantin and Thorsteinsdottir, Unnur and Tinker, Andrew and Trompet, Stella and Uitterlinden, Andre and Vaartjes, Ilonca and van der Meer, Peter and V{\"o}lker, Uwe and V{\"o}lzke, Henry and Waldenberger, Melanie and Wilson, James G and Xie, Zhijun and Asselbergs, Folkert W and D{\"o}rr, Marcus and van Duijn, Cornelia M and Gasparini, Paolo and Gudbjartsson, Daniel F and Gudnason, Vilmundur and Hansen, Torben and K{\"a}{\"a}b, Stefan and Kanters, J{\o}rgen K and Kooperberg, Charles and Lehtim{\"a}ki, Terho and Lin, Henry J and Lubitz, Steven A and Mook-Kanamori, Dennis O and Conti, Francesco J and Newton-Cheh, Christopher H and Rosand, Jonathan and Rudan, Igor and Samani, Nilesh J and Sinagra, Gianfranco and Smith, Blair H and Holm, Hilma and Stricker, Bruno H and Ulivi, Sheila and Sotoodehnia, Nona and Apte, Suneel S and van der Harst, Pim and Stefansson, Kari and Munroe, Patricia B and Arking, Dan E and Lo, Cecilia W and Jamshidi, Yalda} } @article {7784, title = {ExomeChip-Wide Analysis of 95 626 Individuals Identifies 10 Novel Loci Associated With QT and JT Intervals.}, journal = {Circ Genom Precis Med}, volume = {11}, year = {2018}, month = {2018 Jan}, pages = {e001758}, abstract = {

BACKGROUND: QT interval, measured through a standard ECG, captures the time it takes for the cardiac ventricles to depolarize and repolarize. JT interval is the component of the QT interval that reflects ventricular repolarization alone. Prolonged QT interval has been linked to higher risk of sudden cardiac arrest.

METHODS AND RESULTS: We performed an ExomeChip-wide analysis for both QT and JT intervals, including 209 449 variants, both common and rare, in 17 341 genes from the Illumina Infinium HumanExome BeadChip. We identified 10 loci that modulate QT and JT interval duration that have not been previously reported in the literature using single-variant statistical models in a meta-analysis of 95 626 individuals from 23 cohorts (comprised 83 884 European ancestry individuals, 9610 blacks, 1382 Hispanics, and 750 Asians). This brings the total number of ventricular repolarization associated loci to 45. In addition, our approach of using coding variants has highlighted the role of 17 specific genes for involvement in ventricular repolarization, 7 of which are in novel loci.

CONCLUSIONS: Our analyses show a role for myocyte internal structure and interconnections in modulating QT interval duration, adding to previous known roles of potassium, sodium, and calcium ion regulation, as well as autonomic control. We anticipate that these discoveries will open new paths to the goal of making novel remedies for the prevention of lethal ventricular arrhythmias and sudden cardiac arrest.

}, issn = {2574-8300}, doi = {10.1161/CIRCGEN.117.001758}, author = {Bihlmeyer, Nathan A and Brody, Jennifer A and Smith, Albert Vernon and Warren, Helen R and Lin, Honghuang and Isaacs, Aaron and Liu, Ching-Ti and Marten, Jonathan and Radmanesh, Farid and Hall, Leanne M and Grarup, Niels and Mei, Hao and M{\"u}ller-Nurasyid, Martina and Huffman, Jennifer E and Verweij, Niek and Guo, Xiuqing and Yao, Jie and Li-Gao, Ruifang and van den Berg, Marten and Weiss, Stefan and Prins, Bram P and van Setten, Jessica and Haessler, Jeffrey and Lyytik{\"a}inen, Leo-Pekka and Li, Man and Alonso, Alvaro and Soliman, Elsayed Z and Bis, Joshua C and Austin, Tom and Chen, Yii-Der Ida and Psaty, Bruce M and Harrris, Tamara B and Launer, Lenore J and Padmanabhan, Sandosh and Dominiczak, Anna and Huang, Paul L and Xie, Zhijun and Ellinor, Patrick T and Kors, Jan A and Campbell, Archie and Murray, Alison D and Nelson, Christopher P and Tobin, Martin D and Bork-Jensen, Jette and Hansen, Torben and Pedersen, Oluf and Linneberg, Allan and Sinner, Moritz F and Peters, Annette and Waldenberger, Melanie and Meitinger, Thomas and Perz, Siegfried and Kolcic, Ivana and Rudan, Igor and de Boer, Rudolf A and van der Meer, Peter and Lin, Henry J and Taylor, Kent D and de Mutsert, Ren{\'e}e and Trompet, Stella and Jukema, J Wouter and Maan, Arie C and Stricker, Bruno H C and Rivadeneira, Fernando and Uitterlinden, Andre and V{\"o}lker, Uwe and Homuth, Georg and V{\"o}lzke, Henry and Felix, Stephan B and Mangino, Massimo and Spector, Timothy D and Bots, Michiel L and Perez, Marco and Raitakari, Olli T and K{\"a}h{\"o}nen, Mika and Mononen, Nina and Gudnason, Vilmundur and Munroe, Patricia B and Lubitz, Steven A and van Duijn, Cornelia M and Newton-Cheh, Christopher H and Hayward, Caroline and Rosand, Jonathan and Samani, Nilesh J and Kanters, J{\o}rgen K and Wilson, James G and K{\"a}{\"a}b, Stefan and Polasek, Ozren and van der Harst, Pim and Heckbert, Susan R and Rotter, Jerome I and Mook-Kanamori, Dennis O and Eijgelsheim, Mark and D{\"o}rr, Marcus and Jamshidi, Yalda and Asselbergs, Folkert W and Kooperberg, Charles and Lehtim{\"a}ki, Terho and Arking, Dan E and Sotoodehnia, Nona} } @article {8096, title = {Epigenome-wide association analysis of daytime sleepiness in the Multi-Ethnic Study of Atherosclerosis reveals African-American-specific associations.}, journal = {Sleep}, year = {2019}, month = {2019 May 29}, abstract = {

STUDY OBJECTIVES: Daytime sleepiness is a consequence of inadequate sleep, sleep-wake control disorder, or other medical conditions. Population variability in prevalence of daytime sleepiness is likely due to genetic and biological factors as well as social and environmental influences. DNA methylation (DNAm) potentially influences multiple health outcomes. Here, we explored the association between DNAm and daytime sleepiness quantified by the Epworth Sleepiness Scale (ESS).

METHODS: We performed multi-ethnic and ethnic-specific epigenome-wide association studies for DNAm and ESS in the Multi-Ethnic Study of Atherosclerosis (MESA; n = 619) and the Cardiovascular Health Study (n = 483), with cross-study replication and meta-analysis. Genetic variants near ESS-associated DNAm were analyzed for methylation quantitative trait loci and followed with replication of genotype-sleepiness associations in the UK Biobank.

RESULTS: In MESA only, we detected four DNAm-ESS associations: one across all race/ethnic groups; three in African-Americans (AA) only. Two of the MESA AA associations, in genes KCTD5 and RXRA, nominally replicated in CHS (p-value < 0.05). In the AA meta-analysis, we detected 14 DNAm-ESS associations (FDR q-value < 0.05, top association p-value = 4.26 {\texttimes} 10-8). Three DNAm sites mapped to genes (CPLX3, GFAP, and C7orf50) with biological relevance. We also found evidence for associations with DNAm sites in RAI1, a gene associated with sleep and circadian phenotypes. UK Biobank follow-up analyses detected SNPs in RAI1, RXRA, and CPLX3 with nominal sleepiness associations.

CONCLUSIONS: We identified methylation sites in multiple genes possibly implicated in daytime sleepiness. Most significant DNAm-ESS associations were specific to AA. Future work is needed to identify mechanisms driving ancestry-specific methylation effects.

}, issn = {1550-9109}, doi = {10.1093/sleep/zsz101}, author = {Barfield, Richard and Wang, Heming and Liu, Yongmei and Brody, Jennifer A and Swenson, Brenton and Li, Ruitong and Bartz, Traci M and Sotoodehnia, Nona and Chen, Yii-der I and Cade, Brian E and Chen, Han and Patel, Sanjay R and Zhu, Xiaofeng and Gharib, Sina A and Johnson, W Craig and Rotter, Jerome I and Saxena, Richa and Purcell, Shaun and Lin, Xihong and Redline, Susan and Sofer, Tamar} } @article {9001, title = {Epigenetic Age and the Risk of Incident Atrial Fibrillation.}, journal = {Circulation}, volume = {144}, year = {2021}, month = {2021 12 14}, pages = {1899-1911}, abstract = {

BACKGROUND: The most prominent risk factor for atrial fibrillation (AF) is chronological age; however, underlying mechanisms are unexplained. Algorithms using epigenetic modifications to the human genome effectively predict chronological age. Chronological and epigenetic predicted ages may diverge in a phenomenon referred to as epigenetic age acceleration (EAA), which may reflect accelerated biological aging. We sought to evaluate for associations between epigenetic age measures and incident AF.

METHODS: Measures for 4 epigenetic clocks (Horvath, Hannum, DNA methylation [DNAm] PhenoAge, and DNAm GrimAge) and an epigenetic predictor of PAI-1 (plasminogen activator inhibitor-1) levels (ie, DNAm PAI-1) were determined for study participants from 3 population-based cohort studies. Cox models evaluated for associations with incident AF and results were combined via random-effects meta-analyses. Two-sample summary-level Mendelian randomization analyses evaluated for associations between genetic instruments of the EAA measures and AF.

RESULTS: Among 5600 participants (mean age, 65.5 years; female, 60.1\%; Black, 50.7\%), there were 905 incident AF cases during a mean follow-up of 12.9 years. Unadjusted analyses revealed all 4 epigenetic clocks and the DNAm PAI-1 predictor were associated with statistically significant higher hazards of incident AF, though the magnitudes of their point estimates were smaller relative to the associations observed for chronological age. The pooled EAA estimates for each epigenetic measure, with the exception of Horvath EAA, were associated with incident AF in models adjusted for chronological age, race, sex, and smoking variables. After multivariable adjustment for additional known AF risk factors that could also potentially function as mediators, pooled EAA measures for 2 clocks remained statistically significant. Five-year increases in EAA measures for DNAm GrimAge and DNAm PhenoAge were associated with 19\% (adjusted hazard ratio [HR], 1.19 [95\% CI, 1.09-1.31]; <0.01) and 15\% (adjusted HR, 1.15 [95\% CI, 1.05-1.25]; <0.01) higher hazards of incident AF, respectively. Mendelian randomization analyses for the 5 EAA measures did not reveal statistically significant associations with AF.

CONCLUSIONS: Our study identified adjusted associations between EAA measures and incident AF, suggesting that biological aging plays an important role independent of chronological age, though a potential underlying causal relationship remains unclear. These aging processes may be modifiable and not constrained by the immutable factor of time.

}, keywords = {Aged, Aging, Atrial Fibrillation, DNA Methylation, Epigenesis, Genetic, Epigenomics, Female, Follow-Up Studies, Humans, Incidence, Male, Mendelian Randomization Analysis, Middle Aged, Models, Cardiovascular, Models, Genetic}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.121.056456}, author = {Roberts, Jason D and Vittinghoff, Eric and Lu, Ake T and Alonso, Alvaro and Wang, Biqi and Sitlani, Colleen M and Mohammadi-Shemirani, Pedrum and Fornage, Myriam and Kornej, Jelena and Brody, Jennifer A and Arking, Dan E and Lin, Honghuang and Heckbert, Susan R and Prokic, Ivana and Ghanbari, Mohsen and Skanes, Allan C and Bartz, Traci M and Perez, Marco V and Taylor, Kent D and Lubitz, Steven A and Ellinor, Patrick T and Lunetta, Kathryn L and Pankow, James S and Par{\'e}, Guillaume and Sotoodehnia, Nona and Benjamin, Emelia J and Horvath, Steve and Marcus, Gregory M} } @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 {9167, title = {Endophenotype effect sizes support variant pathogenicity in monogenic disease susceptibility genes.}, journal = {Nat Commun}, volume = {13}, year = {2022}, month = {2022 08 30}, pages = {5106}, abstract = {

Accurate and efficient classification of variant pathogenicity is critical for research and clinical care. Using data from three large studies, we demonstrate that population-based associations between rare variants and quantitative endophenotypes for three monogenic diseases (low-density-lipoprotein cholesterol for familial hypercholesterolemia, electrocardiographic QTc interval for long QT syndrome, and glycosylated hemoglobin for maturity-onset diabetes of the young) provide evidence for variant pathogenicity. Effect sizes are associated with pathogenic ClinVar assertions (P < 0.001 for each trait) and discriminate pathogenic from non-pathogenic variants (area under the curve 0.82-0.84 across endophenotypes). An effect size threshold of >= 0.5 times the endophenotype standard deviation nominates up to 35\% of rare variants of uncertain significance or not in ClinVar in disease susceptibility genes with pathogenic potential. We propose that variant associations with quantitative endophenotypes for monogenic diseases can provide evidence supporting pathogenicity.

}, keywords = {Disease Susceptibility, Endophenotypes, Humans, Long QT Syndrome, Virulence}, issn = {2041-1723}, doi = {10.1038/s41467-022-32009-5}, author = {Halford, Jennifer L and Morrill, Valerie N and Choi, Seung Hoan and Jurgens, Sean J and Melloni, Giorgio and Marston, Nicholas A and Weng, Lu-Chen and Nauffal, Victor and Hall, Amelia W and Gunn, Sophia and Austin-Tse, Christina A and Pirruccello, James P and Khurshid, Shaan and Rehm, Heidi L and Benjamin, Emelia J and Boerwinkle, Eric and Brody, Jennifer A and Correa, Adolfo and Fornwalt, Brandon K and Gupta, Namrata and Haggerty, Christopher M and Harris, Stephanie and Heckbert, Susan R and Hong, Charles C and Kooperberg, Charles and Lin, Henry J and Loos, Ruth J F and Mitchell, Braxton D and Morrison, Alanna C and Post, Wendy and Psaty, Bruce M and Redline, Susan and Rice, Kenneth M and Rich, Stephen S and Rotter, Jerome I and Schnatz, Peter F and Soliman, Elsayed Z and Sotoodehnia, Nona and Wong, Eugene K and Sabatine, Marc S and Ruff, Christian T and Lunetta, Kathryn L and Ellinor, Patrick T and Lubitz, Steven A} } @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 {9742, title = {Epigenome-wide DNA Methylation Association Study of CHIP Provides Insight into Perturbed Gene Regulation.}, journal = {Res Sq}, year = {2024}, month = {2024 Jul 16}, abstract = {

With age, hematopoietic stem cells can acquire somatic mutations in leukemogenic genes that confer a proliferative advantage in a phenomenon termed "clonal hematopoiesis of indeterminate potential" (CHIP). How these mutations confer a proliferative advantage and result in increased risk for numerous age-related diseases remains poorly understood. We conducted a multiracial meta-analysis of epigenome-wide association studies (EWAS) of CHIP and its subtypes in four cohorts (N=8196) to elucidate the molecular mechanisms underlying CHIP and illuminate how these changes influence cardiovascular disease risk. The EWAS findings were functionally validated using human hematopoietic stem cell (HSC) models of CHIP. A total of 9615 CpGs were associated with any CHIP, 5990 with DNMT3A CHIP, 5633 with TET2 CHIP, and 6078 with ASXL1 CHIP (P <1{\texttimes}10). CpGs associated with CHIP subtypes overlapped moderately, and the genome-wide DNA methylation directions of effect were opposite for TET2 and DNMT3A CHIP, consistent with their opposing effects on global DNA methylation. There was high directional concordance between the CpGs shared from the meta-EWAS and human edited CHIP HSCs. Expression quantitative trait methylation analysis further identified transcriptomic changes associated with CHIP-associated CpGs. Causal inference analyses revealed 261 CHIP-associated CpGs associated with cardiovascular traits and all-cause mortality (FDR adjusted p-value <0.05). Taken together, our study sheds light on the epigenetic changes impacted by CHIP and their associations with age-related disease outcomes. The novel genes and pathways linked to the epigenetic features of CHIP may serve as therapeutic targets for preventing or treating CHIP-mediated diseases.

}, issn = {2693-5015}, doi = {10.21203/rs.3.rs-4656898/v1}, author = {Levy, Daniel and Kirmani, Sara and Huan, Tianxiao and Van Amburg, Joseph and Joehanes, Roby and Uddin, Md Mesbah and Nguyen, Ngoc Quynh and Yu, Bing and Brody, Jennifer and Fornage, Myriam and Bressler, Jan and Sotoodehnia, Nona and Ong, David and Puddu, Fabio and Floyd, James and Ballantyne, Christie and Psaty, Bruce and Raffield, Laura and Natarajan, Pradeep and Conneely, Karen and Carson, April and Lange, Leslie and Ferrier, Kendra and Heard-Costa, Nancy and Murabito, Joanne and Bick, Alexander} }