@article {7349, title = {DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases.}, journal = {Genome Biol}, volume = {17}, year = {2016}, month = {2016 Dec 12}, pages = {255}, abstract = {

BACKGROUND: Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation.

RESULTS: We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 {\texttimes} 10(-7)) in the discovery panel of European ancestry and replicated (P < 2.29 {\texttimes} 10(-4)) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16\%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 {\texttimes} 10(-5)), ten (17\%) CpG sites were associated with a nearby genetic variant (P < 2.50 {\texttimes} 10(-3)), and 51 (88\%) were also associated with at least one related cardiometabolic entity (P < 9.58 {\texttimes} 10(-5)). An additive weighted score of replicated CpG sites accounted for up to 6\% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants.

CONCLUSION: We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.

}, issn = {1474-760X}, doi = {10.1186/s13059-016-1119-5}, author = {Ligthart, Symen and Marzi, Carola and Aslibekyan, Stella and Mendelson, Michael M and Conneely, Karen N and Tanaka, Toshiko and Colicino, Elena and Waite, Lindsay L and Joehanes, Roby and Guan, Weihua and Brody, Jennifer A and Elks, Cathy and Marioni, Riccardo and Jhun, Min A and Agha, Golareh and Bressler, Jan and Ward-Caviness, Cavin K and Chen, Brian H and Huan, Tianxiao and Bakulski, Kelly and Salfati, Elias L and Fiorito, Giovanni and Wahl, Simone and Schramm, Katharina and Sha, Jin and Hernandez, Dena G and Just, Allan C and Smith, Jennifer A and Sotoodehnia, Nona and Pilling, Luke C and Pankow, James S and Tsao, Phil S and Liu, Chunyu and Zhao, Wei and Guarrera, Simonetta and Michopoulos, Vasiliki J and Smith, Alicia K and Peters, Marjolein J and Melzer, David and Vokonas, Pantel and Fornage, Myriam and Prokisch, Holger and Bis, Joshua C and Chu, Audrey Y and Herder, Christian and Grallert, Harald and Yao, Chen and Shah, Sonia and McRae, Allan F and Lin, Honghuang and Horvath, Steve and Fallin, Daniele and Hofman, Albert and Wareham, Nicholas J and Wiggins, Kerri L and Feinberg, Andrew P and Starr, John M and Visscher, Peter M and Murabito, Joanne M and Kardia, Sharon L R and Absher, Devin M and Binder, Elisabeth B and Singleton, Andrew B and Bandinelli, Stefania and Peters, Annette and Waldenberger, Melanie and Matullo, Giuseppe and Schwartz, Joel D and Demerath, Ellen W and Uitterlinden, Andr{\'e} G and van Meurs, Joyce B J and Franco, Oscar H and Chen, Yii-Der Ida and Levy, Daniel and Turner, Stephen T and Deary, Ian J and Ressler, Kerry J and Dupuis, Jos{\'e}e and Ferrucci, Luigi and Ong, Ken K and Assimes, Themistocles L and Boerwinkle, Eric and Koenig, Wolfgang and Arnett, Donna K and Baccarelli, Andrea A and Benjamin, Emelia J and Dehghan, Abbas} } @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 {7264, title = {Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci.}, journal = {Nat Genet}, volume = {48}, year = {2016}, month = {2016 Oct}, pages = {1162-70}, abstract = {

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure-associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein-protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure-associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

}, issn = {1546-1718}, doi = {10.1038/ng.3660}, author = {Liu, Chunyu and Kraja, Aldi T and Smith, Jennifer A and Brody, Jennifer A and Franceschini, Nora and Bis, Joshua C and Rice, Kenneth and Morrison, Alanna C and Lu, Yingchang and Weiss, Stefan and Guo, Xiuqing and Palmas, Walter and Martin, Lisa W and Chen, Yii-Der Ida and Surendran, Praveen and Drenos, Fotios and Cook, James P and Auer, Paul L and Chu, Audrey Y and Giri, Ayush and Zhao, Wei and Jakobsdottir, Johanna and Lin, Li-An and Stafford, Jeanette M and Amin, Najaf and Mei, Hao and Yao, Jie and Voorman, Arend and Larson, Martin G and Grove, Megan L and Smith, Albert V and Hwang, Shih-Jen and Chen, Han and Huan, Tianxiao and Kosova, Gulum and Stitziel, Nathan O and Kathiresan, Sekar and Samani, Nilesh and Schunkert, Heribert and Deloukas, Panos and Li, Man and Fuchsberger, Christian and Pattaro, Cristian and Gorski, Mathias and Kooperberg, Charles and Papanicolaou, George J and Rossouw, Jacques E and Faul, Jessica D and Kardia, Sharon L R and Bouchard, Claude and Raffel, Leslie J and Uitterlinden, Andr{\'e} G and Franco, Oscar H and Vasan, Ramachandran S and O{\textquoteright}Donnell, Christopher J and Taylor, Kent D and Liu, Kiang and Bottinger, Erwin P and Gottesman, Omri and Daw, E Warwick and Giulianini, Franco and Ganesh, Santhi and Salfati, Elias and Harris, Tamara B and Launer, Lenore J and D{\"o}rr, Marcus and Felix, Stephan B and Rettig, Rainer and V{\"o}lzke, Henry and Kim, Eric and Lee, Wen-Jane and Lee, I-Te and Sheu, Wayne H-H and Tsosie, Krystal S and Edwards, Digna R Velez and Liu, Yongmei and Correa, Adolfo and Weir, David R and V{\"o}lker, Uwe and Ridker, Paul M and Boerwinkle, Eric and Gudnason, Vilmundur and Reiner, Alexander P and van Duijn, Cornelia M and Borecki, Ingrid B and Edwards, Todd L and Chakravarti, Aravinda and Rotter, Jerome I and Psaty, Bruce M and Loos, Ruth J F and Fornage, Myriam and Ehret, Georg B and Newton-Cheh, Christopher and Levy, Daniel and Chasman, Daniel I} } @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 {7819, title = {Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function.}, journal = {Nat Commun}, volume = {9}, year = {2018}, month = {2018 Jul 30}, pages = {2976}, abstract = {

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of lung function and clinical relevance of implicated loci.

}, issn = {2041-1723}, doi = {10.1038/s41467-018-05369-0}, author = {Wyss, Annah B and Sofer, Tamar and Lee, Mi Kyeong and Terzikhan, Natalie and Nguyen, Jennifer N and Lahousse, Lies and Latourelle, Jeanne C and Smith, Albert Vernon and Bartz, Traci M and Feitosa, Mary F and Gao, Wei and Ahluwalia, Tarunveer S and Tang, Wenbo and Oldmeadow, Christopher and Duan, Qing and de Jong, Kim and Wojczynski, Mary K and Wang, Xin-Qun and Noordam, Raymond and Hartwig, Fernando Pires and Jackson, Victoria E and Wang, Tianyuan and Obeidat, Ma{\textquoteright}en and Hobbs, Brian D and Huan, Tianxiao and Gui, Hongsheng and Parker, Margaret M and Hu, Donglei and Mogil, Lauren S and Kichaev, Gleb and Jin, Jianping and Graff, Mariaelisa and Harris, Tamara B and Kalhan, Ravi and Heckbert, Susan R and Paternoster, Lavinia and Burkart, Kristin M and Liu, Yongmei and Holliday, Elizabeth G and Wilson, James G and Vonk, Judith M and Sanders, Jason L and Barr, R Graham and de Mutsert, Ren{\'e}e and Menezes, Ana Maria Baptista and Adams, Hieab H H and van den Berge, Maarten and Joehanes, Roby and Levin, Albert M and Liberto, Jennifer and Launer, Lenore J and Morrison, Alanna C and Sitlani, Colleen M and Celed{\'o}n, Juan C and Kritchevsky, Stephen B and Scott, Rodney J and Christensen, Kaare and Rotter, Jerome I and Bonten, Tobias N and Wehrmeister, Fernando C{\'e}sar and Boss{\'e}, Yohan and Xiao, Shujie and Oh, Sam and Franceschini, Nora and Brody, Jennifer A and Kaplan, Robert C and Lohman, Kurt and McEvoy, Mark and Province, Michael A and Rosendaal, Frits R and Taylor, Kent D and Nickle, David C and Williams, L Keoki and Burchard, Esteban G and Wheeler, Heather E and Sin, Don D and Gudnason, Vilmundur and North, Kari E and Fornage, Myriam and Psaty, Bruce M and Myers, Richard H and O{\textquoteright}Connor, George and Hansen, Torben and Laurie, Cathy C and Cassano, Patricia A and Sung, Joohon and Kim, Woo Jin and Attia, John R and Lange, Leslie and Boezen, H Marike and Thyagarajan, Bharat and Rich, Stephen S and Mook-Kanamori, Dennis O and Horta, Bernardo Lessa and Uitterlinden, Andr{\'e} G and Im, Hae Kyung and Cho, Michael H and Brusselle, Guy G and Gharib, Sina A and Dupuis, Jos{\'e}e and Manichaikul, Ani and London, Stephanie J} } @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 {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 {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 {9583, title = {Genome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure.}, journal = {medRxiv}, year = {2023}, month = {2023 Nov 11}, abstract = {

OBJECTIVE: We examined interactions between genotype and a Dietary Approaches to Stop Hypertension (DASH) diet score in relation to systolic blood pressure (SBP).

METHODS: We analyzed up to 9,420,585 biallelic imputed single nucleotide polymorphisms (SNPs) in up to 127,282 individuals of six population groups (91\% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (CHARGE; n=35,660) and UK Biobank (n=91,622) and performed European population-specific and cross-population meta-analyses.

RESULTS: We identified three loci in European-specific analyses and an additional four loci in cross-population analyses at P for interaction < 5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency = 0.03) and the DASH diet score (P for interaction = 4e-8; P for heterogeneity = 0.35) in European population, where the interaction effect size was 0.42{\textpm}0.09 mm Hg (P for interaction = 9.4e-7) and 0.20{\textpm}0.06 mm Hg (P for interaction = 0.001) in CHARGE and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with -expression quantitative trait loci (eQTL) variants (P = 4e-273) and -DNA methylation quantitative trait loci (mQTL) variants (P = 1e-300). While the closest gene for rs117878928 is , the highest narrow sense heritability accounted by SNPs potentially interacting with the DASH diet score in this locus was for gene at 15q25.1.

CONCLUSION: We demonstrated gene-DASH diet score interaction effects on SBP in several loci. Studies with larger diverse populations are needed to validate our findings.

}, doi = {10.1101/2023.11.10.23298402}, author = {Guirette, Melanie and Lan, Jessie and McKeown, Nicola and Brown, Michael R and Chen, Han and de Vries, Paul S and Kim, Hyunju and Rebholz, Casey M and Morrison, Alanna C and Bartz, Traci M and Fretts, Amanda M and Guo, Xiuqing and Lemaitre, Rozenn N and Liu, Ching-Ti and Noordam, Raymond and de Mutsert, Ren{\'e}e and Rosendaal, Frits R and Wang, Carol A and Beilin, Lawrence and Mori, Trevor A and Oddy, Wendy H and Pennell, Craig E and Chai, Jin Fang and Whitton, Clare and van Dam, Rob M and Liu, Jianjun and Tai, E Shyong and Sim, Xueling and Neuhouser, Marian L and Kooperberg, Charles and Tinker, Lesley and Franceschini, Nora and Huan, Tianxiao and Winkler, Thomas W and Bentley, Amy R and Gauderman, W James and Heerkens, Luc and Tanaka, Toshiko and van Rooij, Jeroen and Munroe, Patricia B and Warren, Helen R and Voortman, Trudy and Chen, Honglei and Rao, D C and Levy, Daniel and Ma, Jiantao} } @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} }