%0 Journal Article %J Nature %D 2020 %T Inherited causes of clonal haematopoiesis in 97,691 whole genomes. %A Bick, Alexander G %A Weinstock, Joshua S %A Nandakumar, Satish K %A Fulco, Charles P %A Bao, Erik L %A Zekavat, Seyedeh M %A Szeto, Mindy D %A Liao, Xiaotian %A Leventhal, Matthew J %A Nasser, Joseph %A Chang, Kyle %A Laurie, Cecelia %A Burugula, Bala Bharathi %A Gibson, Christopher J %A Lin, Amy E %A Taub, Margaret A %A Aguet, François %A Ardlie, Kristin %A Mitchell, Braxton D %A Barnes, Kathleen C %A Moscati, Arden %A Fornage, Myriam %A Redline, Susan %A Psaty, Bruce M %A Silverman, Edwin K %A Weiss, Scott T %A Palmer, Nicholette D %A Vasan, Ramachandran S %A Burchard, Esteban G %A Kardia, Sharon L R %A He, Jiang %A Kaplan, Robert C %A Smith, Nicholas L %A Arnett, Donna K %A Schwartz, David A %A Correa, Adolfo %A de Andrade, Mariza %A Guo, Xiuqing %A Konkle, Barbara A %A Custer, Brian %A Peralta, Juan M %A Gui, Hongsheng %A Meyers, Deborah A %A McGarvey, Stephen T %A Chen, Ida Yii-Der %A Shoemaker, M Benjamin %A Peyser, Patricia A %A Broome, Jai G %A Gogarten, Stephanie M %A Wang, Fei Fei %A Wong, Quenna %A Montasser, May E %A Daya, Michelle %A Kenny, Eimear E %A North, Kari E %A Launer, Lenore J %A Cade, Brian E %A Bis, Joshua C %A Cho, Michael H %A Lasky-Su, Jessica %A Bowden, Donald W %A Cupples, L Adrienne %A Mak, Angel C Y %A Becker, Lewis C %A Smith, Jennifer A %A Kelly, Tanika N %A Aslibekyan, Stella %A Heckbert, Susan R %A Tiwari, Hemant K %A Yang, Ivana V %A Heit, John A %A Lubitz, Steven A %A Johnsen, Jill M %A Curran, Joanne E %A Wenzel, Sally E %A Weeks, Daniel E %A Rao, Dabeeru C %A Darbar, Dawood %A Moon, Jee-Young %A Tracy, Russell P %A Buth, Erin J %A Rafaels, Nicholas %A Loos, Ruth J F %A Durda, Peter %A Liu, Yongmei %A Hou, Lifang %A Lee, Jiwon %A Kachroo, Priyadarshini %A Freedman, Barry I %A Levy, Daniel %A Bielak, Lawrence F %A Hixson, James E %A Floyd, James S %A Whitsel, Eric A %A Ellinor, Patrick T %A Irvin, Marguerite R %A Fingerlin, Tasha E %A Raffield, Laura M %A Armasu, Sebastian M %A Wheeler, Marsha M %A Sabino, Ester C %A Blangero, John %A Williams, L Keoki %A Levy, Bruce D %A Sheu, Wayne Huey-Herng %A Roden, Dan M %A Boerwinkle, Eric %A Manson, JoAnn E %A Mathias, Rasika A %A Desai, Pinkal %A Taylor, Kent D %A Johnson, Andrew D %A Auer, Paul L %A Kooperberg, Charles %A Laurie, Cathy C %A Blackwell, Thomas W %A Smith, Albert V %A Zhao, Hongyu %A Lange, Ethan %A Lange, Leslie %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Scheet, Paul %A Kitzman, Jacob O %A Lander, Eric S %A Engreitz, Jesse M %A Ebert, Benjamin L %A Reiner, Alexander P %A Jaiswal, Siddhartha %A Abecasis, Gonçalo %A Sankaran, Vijay G %A Kathiresan, Sekar %A Natarajan, Pradeep %K Adult %K Africa %K African Continental Ancestry Group %K Aged %K Aged, 80 and over %K alpha Karyopherins %K Cell Self Renewal %K Clonal Hematopoiesis %K DNA-Binding Proteins %K Female %K Genetic Predisposition to Disease %K Genome, Human %K Germ-Line Mutation %K Hematopoietic Stem Cells %K Humans %K Intracellular Signaling Peptides and Proteins %K Male %K Middle Aged %K National Heart, Lung, and Blood Institute (U.S.) %K Phenotype %K Precision Medicine %K Proto-Oncogene Proteins %K Tripartite Motif Proteins %K United States %K Whole Genome Sequencing %X

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.

%B Nature %V 586 %P 763-768 %8 2020 10 %G eng %N 7831 %1 https://www.ncbi.nlm.nih.gov/pubmed/33057201?dopt=Abstract %R 10.1038/s41586-020-2819-2 %0 Journal Article %J Nat Commun %D 2020 %T Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions. %A Fahed, Akl C %A Wang, Minxian %A Homburger, Julian R %A Patel, Aniruddh P %A Bick, Alexander G %A Neben, Cynthia L %A Lai, Carmen %A Brockman, Deanna %A Philippakis, Anthony %A Ellinor, Patrick T %A Cassa, Christopher A %A Lebo, Matthew %A Ng, Kenney %A Lander, Eric S %A Zhou, Alicia Y %A Kathiresan, Sekar %A Khera, Amit V %K Aged %K Breast Neoplasms %K Case-Control Studies %K Colorectal Neoplasms %K Coronary Artery Disease %K Female %K Genetic Predisposition to Disease %K Genome, Human %K Humans %K Male %K Middle Aged %K Multifactorial Inheritance %K Odds Ratio %K Penetrance %K Risk Factors %X

Genetic variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions - familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background - the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant.

%B Nat Commun %V 11 %P 3635 %8 2020 08 20 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/32820175?dopt=Abstract %R 10.1038/s41467-020-17374-3 %0 Journal Article %J N Engl J Med %D 2016 %T Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease. %A Khera, Amit V %A Emdin, Connor A %A Drake, Isabel %A Natarajan, Pradeep %A Bick, Alexander G %A Cook, Nancy R %A Chasman, Daniel I %A Baber, Usman %A Mehran, Roxana %A Rader, Daniel J %A Fuster, Valentin %A Boerwinkle, Eric %A Melander, Olle %A Orho-Melander, Marju %A Ridker, Paul M %A Kathiresan, Sekar %K Aged %K Cohort Studies %K Coronary Disease %K Cross-Sectional Studies %K Female %K Genetic Predisposition to Disease %K Healthy Lifestyle %K Humans %K Incidence %K Male %K Middle Aged %K Multifactorial Inheritance %K Patient Compliance %K Polymorphism, Genetic %K Risk %X

BACKGROUND: Both genetic and lifestyle factors contribute to individual-level risk of coronary artery disease. The extent to which increased genetic risk can be offset by a healthy lifestyle is unknown.

METHODS: Using a polygenic score of DNA sequence polymorphisms, we quantified genetic risk for coronary artery disease in three prospective cohorts - 7814 participants in the Atherosclerosis Risk in Communities (ARIC) study, 21,222 in the Women's Genome Health Study (WGHS), and 22,389 in the Malmö Diet and Cancer Study (MDCS) - and in 4260 participants in the cross-sectional BioImage Study for whom genotype and covariate data were available. We also determined adherence to a healthy lifestyle among the participants using a scoring system consisting of four factors: no current smoking, no obesity, regular physical activity, and a healthy diet.

RESULTS: The relative risk of incident coronary events was 91% higher among participants at high genetic risk (top quintile of polygenic scores) than among those at low genetic risk (bottom quintile of polygenic scores) (hazard ratio, 1.91; 95% confidence interval [CI], 1.75 to 2.09). A favorable lifestyle (defined as at least three of the four healthy lifestyle factors) was associated with a substantially lower risk of coronary events than an unfavorable lifestyle (defined as no or only one healthy lifestyle factor), regardless of the genetic risk category. Among participants at high genetic risk, a favorable lifestyle was associated with a 46% lower relative risk of coronary events than an unfavorable lifestyle (hazard ratio, 0.54; 95% CI, 0.47 to 0.63). This finding corresponded to a reduction in the standardized 10-year incidence of coronary events from 10.7% for an unfavorable lifestyle to 5.1% for a favorable lifestyle in ARIC, from 4.6% to 2.0% in WGHS, and from 8.2% to 5.3% in MDCS. In the BioImage Study, a favorable lifestyle was associated with significantly less coronary-artery calcification within each genetic risk category.

CONCLUSIONS: Across four studies involving 55,685 participants, genetic and lifestyle factors were independently associated with susceptibility to coronary artery disease. Among participants at high genetic risk, a favorable lifestyle was associated with a nearly 50% lower relative risk of coronary artery disease than was an unfavorable lifestyle. (Funded by the National Institutes of Health and others.).

%B N Engl J Med %V 375 %P 2349-2358 %8 2016 Dec 15 %G eng %N 24 %1 https://www.ncbi.nlm.nih.gov/pubmed/27959714?dopt=Abstract %R 10.1056/NEJMoa1605086