@article {155, title = {Whole-genome sequencing of African Americans implicates differential genetic architecture in inflammatory bowel disease.}, journal = {Am J Hum Genet}, volume = {108}, year = {2021}, month = {2021 03 04}, pages = {431-445}, abstract = {

Whether or not populations diverge with respect to the genetic contribution to risk of specific complex diseases is relevant to understanding the evolution of susceptibility and origins of health disparities. Here, we describe a large-scale whole-genome sequencing study of inflammatory bowel disease encompassing 1,774 affected individuals and 1,644 healthy control Americans with African ancestry (African Americans). Although no new loci for inflammatory bowel disease are discovered at genome-wide significance levels, we identify numerous instances of differential effect sizes in combination with divergent allele frequencies. For example, the major effect at PTGER4 fine maps to a single credible interval of 22 SNPs corresponding to one of four independent associations at the locus in European ancestry individuals but with an elevated odds ratio for Crohn disease in African Americans. A rare variant aggregate analysis implicates Ca-binding neuro-immunomodulator CALB2 in ulcerative colitis. Highly significant overall overlap of common variant risk for inflammatory bowel disease susceptibility between individuals with African and European ancestries was observed, with 41 of 241 previously known lead variants replicated and overall correlations in effect sizes of 0.68 for combined inflammatory bowel disease. Nevertheless, subtle differences influence the performance of polygenic risk scores, and we show that ancestry-appropriate weights significantly improve polygenic prediction in the highest percentiles of risk. The median amount of variance explained per locus remains the same in African and European cohorts, providing evidence for compensation of effect sizes as allele frequencies diverge, as expected under a highly polygenic model of disease.

}, keywords = {African Americans, Aged, Aged, 80 and over, Calbindin 2, Colitis, Ulcerative, Crohn Disease, European Continental Ancestry Group, Female, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Inflammatory Bowel Diseases, Male, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Receptors, Prostaglandin E, EP4 Subtype, Whole Genome Sequencing}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.02.001}, author = {Somineni, Hari K and Nagpal, Sini and Venkateswaran, Suresh and Cutler, David J and Okou, David T and Haritunians, Talin and Simpson, Claire L and Begum, Ferdouse and Datta, Lisa W and Quiros, Antonio J and Seminerio, Jenifer and Mengesha, Emebet and Alexander, Jonathan S and Baldassano, Robert N and Dudley-Brown, Sharon and Cross, Raymond K and Dassopoulos, Themistocles and Denson, Lee A and Dhere, Tanvi A and Iskandar, Heba and Dryden, Gerald W and Hou, Jason K and Hussain, Sunny Z and Hyams, Jeffrey S and Isaacs, Kim L and Kader, Howard and Kappelman, Michael D and Katz, Jeffry and Kellermayer, Richard and Kuemmerle, John F and Lazarev, Mark and Li, Ellen and Mannon, Peter and Moulton, Dedrick E and Newberry, Rodney D and Patel, Ashish S and Pekow, Joel and Saeed, Shehzad A and Valentine, John F and Wang, Ming-Hsi and McCauley, Jacob L and Abreu, Maria T and Jester, Traci and Molle-Rios, Zarela and Palle, Sirish and Scherl, Ellen J and Kwon, John and Rioux, John D and Duerr, Richard H and Silverberg, Mark S and Zwick, Michael E and Stevens, Christine and Daly, Mark J and Cho, Judy H and Gibson, Greg and McGovern, Dermot P B and Brant, Steven R and Kugathasan, Subra} } @article {129, title = {Genome-Wide Polygenic Score, Clinical Risk Factors, and Long-Term Trajectories of Coronary Artery Disease.}, journal = {Arterioscler Thromb Vasc Biol}, volume = {40}, year = {2020}, month = {2020 11}, pages = {2738-2746}, abstract = {

OBJECTIVE: To determine the relationship of a genome-wide polygenic score for coronary artery disease (GPS) with lifetime trajectories of CAD risk, directly compare its predictive capacity to traditional risk factors, and assess its interplay with the Pooled Cohort Equations (PCE) clinical risk estimator. Approach and Results: We studied GPS in 28 556 middle-aged participants of the Malm{\"o} Diet and Cancer Study, of whom 4122 (14.4\%) developed CAD over a median follow-up of 21.3 years. A pronounced gradient in lifetime risk of CAD was observed-16\% for those in the lowest GPS decile to 48\% in the highest. We evaluated the discriminative capacity of the GPS-as assessed by change in the C-statistic from a baseline model including age and sex-among 5685 individuals with PCE risk estimates available. The increment for the GPS (+0.045, <0.001) was higher than for any of 11 traditional risk factors (range +0.007 to +0.032). Minimal correlation was observed between GPS and 10-year risk defined by the PCE (=0.03), and addition of GPS improved the C-statistic of the PCE model by 0.026. A significant gradient in lifetime risk was observed for the GPS, even among individuals within a given PCE clinical risk stratum. We replicated key findings-noting strikingly consistent results-in 325 003 participants of the UK Biobank.

CONCLUSIONS: GPS-a risk estimator available from birth-stratifies individuals into varying trajectories of clinical risk for CAD. Implementation of GPS may enable identification of high-risk individuals early in life, decades in advance of manifest risk factors or disease.

}, keywords = {Adult, Aged, Coronary Artery Disease, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Heart Disease Risk Factors, Heredity, Humans, Incidence, Male, Middle Aged, Multifactorial Inheritance, Phenotype, Prognosis, Risk Assessment, Sweden, Time Factors, United Kingdom}, issn = {1524-4636}, doi = {10.1161/ATVBAHA.120.314856}, author = {Hindy, George and Aragam, Krishna G and Ng, Kenney and Chaffin, Mark and Lotta, Luca A and Baras, Aris and Drake, Isabel and Orho-Melander, Marju and Melander, Olle and Kathiresan, Sekar and Khera, Amit V} } @article {141, title = {Non-parametric Polygenic Risk Prediction via Partitioned GWAS Summary Statistics.}, journal = {Am J Hum Genet}, volume = {107}, year = {2020}, month = {2020 07 02}, pages = {46-59}, abstract = {

In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait{\textquoteright}s heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments.

}, keywords = {Aged, Cohort Studies, Diabetes Mellitus, Type 2, Female, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Middle Aged, Models, Genetic, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2020.05.004}, author = {Chun, Sung and Imakaev, Maxim and Hui, Daniel and Patsopoulos, Nikolaos A and Neale, Benjamin M and Kathiresan, Sekar and Stitziel, Nathan O and Sunyaev, Shamil R} } @article {105, title = {Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions.}, journal = {Nat Commun}, volume = {11}, year = {2020}, month = {2020 08 20}, pages = {3635}, abstract = {

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.

}, keywords = {Aged, Breast Neoplasms, Case-Control Studies, Colorectal Neoplasms, Coronary Artery Disease, Female, Genetic Predisposition to Disease, Genome, Human, Humans, Male, Middle Aged, Multifactorial Inheritance, Odds Ratio, Penetrance, Risk Factors}, issn = {2041-1723}, doi = {10.1038/s41467-020-17374-3}, author = {Fahed, Akl C and Wang, Minxian and Homburger, Julian R and Patel, Aniruddh P and Bick, Alexander G and Neben, Cynthia L and Lai, Carmen and Brockman, Deanna and Philippakis, Anthony and Ellinor, Patrick T and Cassa, Christopher A and Lebo, Matthew and Ng, Kenney and Lander, Eric S and Zhou, Alicia Y and Kathiresan, Sekar and Khera, Amit V} } @article {101, title = {Transcriptomic signatures across human tissues identify functional rare genetic variation.}, journal = {Science}, volume = {369}, year = {2020}, month = {2020 09 11}, abstract = {

Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.

}, keywords = {Genetic Variation, Genome, Human, Humans, Multifactorial Inheritance, Organ Specificity, Transcriptome}, issn = {1095-9203}, doi = {10.1126/science.aaz5900}, author = {Ferraro, Nicole M and Strober, Benjamin J and Einson, Jonah and Abell, Nathan S and Aguet, Fran{\c c}ois and Barbeira, Alvaro N and Brandt, Margot and Bucan, Maja and Castel, Stephane E and Davis, Joe R and Greenwald, Emily and Hess, Gaelen T and Hilliard, Austin T and Kember, Rachel L and Kotis, Bence and Park, YoSon and Peloso, Gina and Ramdas, Shweta and Scott, Alexandra J and Smail, Craig and Tsang, Emily K and Zekavat, Seyedeh M and Ziosi, Marcello and Ardlie, Kristin G and Assimes, Themistocles L and Bassik, Michael C and Brown, Christopher D and Correa, Adolfo and Hall, Ira and Im, Hae Kyung and Li, Xin and Natarajan, Pradeep and Lappalainen, Tuuli and Mohammadi, Pejman and Montgomery, Stephen B and Battle, Alexis} } @article {127, title = {Validation of a Genome-Wide Polygenic~Score for Coronary Artery~Disease in~South Asians.}, journal = {J Am Coll Cardiol}, volume = {76}, year = {2020}, month = {2020 08 11}, pages = {703-714}, abstract = {

BACKGROUND: Genome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery disease (CAD) are substantially higher among South Asians, a GPS to identify high-risk individuals may be particularly useful in this population.

OBJECTIVES: This analysis used summary statistics from a prior genome-wide association study to derive a new GPS for South Asians.

METHODS: This GPS was validated in 7,244 South Asian UK Biobank participants and tested in 491 individuals from a case-control study in Bangladesh. Next, a static ancestry and GPS reference distribution was built using whole-genome sequencing from 1,522 Indian individuals, and a framework was tested for projecting individuals onto this static ancestry and GPS reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India.

RESULTS: The GPS, containing 6,630,150 common DNA variants, had an odds ratio (OR) per SD of 1.58 in South Asian UK Biobank participants and 1.60 in the Bangladeshi study (p~<~0.001 for each). Next, individuals of the Indian case-control study were projected onto static reference distributions, observing an OR/SD of 1.66 (p~<~0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5\% of the GPS distribution-ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p~<~0.05 for each).

CONCLUSIONS: The new GPS has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment.

}, keywords = {Adult, Aged, Bangladesh, Case-Control Studies, Coronary Artery Disease, Female, Genome-Wide Association Study, Humans, India, Male, Middle Aged, Multifactorial Inheritance}, issn = {1558-3597}, doi = {10.1016/j.jacc.2020.06.024}, author = {Wang, Minxian and Menon, Ramesh and Mishra, Sanghamitra and Patel, Aniruddh P and Chaffin, Mark and Tanneeru, Deepak and Deshmukh, Manjari and Mathew, Oshin and Apte, Sanika and Devanboo, Christina S and Sundaram, Sumathi and Lakshmipathy, Praveena and Murugan, Sakthivel and Sharma, Krishna Kumar and Rajendran, Karthikeyan and Santhosh, Sam and Thachathodiyl, Rajesh and Ahamed, Hisham and Balegadde, Aniketh Vijay and Alexander, Thomas and Swaminathan, Krishnan and Gupta, Rajeev and Mullasari, Ajit S and Sigamani, Alben and Kanchi, Muralidhar and Peterson, Andrew S and Butterworth, Adam S and Danesh, John and Di Angelantonio, Emanuele and Naheed, Aliya and Inouye, Michael and Chowdhury, Rajiv and Vedam, Ramprasad L and Kathiresan, Sekar and Gupta, Ravi and Khera, Amit V} } @article {21, title = {Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting.}, journal = {Circulation}, volume = {135}, year = {2017}, month = {2017 May 30}, pages = {2091-2101}, abstract = {

BACKGROUND: Relative risk reduction with statin therapy has been consistent across nearly all subgroups studied to date. However, in analyses of 2 randomized controlled primary prevention trials (ASCOT [Anglo-Scandinavian Cardiac Outcomes Trial-Lipid-Lowering Arm] and JUPITER [Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin]), statin therapy led to a greater relative risk reduction among a subgroup at high genetic risk. Here, we aimed to confirm this observation in a third primary prevention randomized controlled trial. In addition, we assessed whether those at high genetic risk had a greater burden of subclinical coronary atherosclerosis.

METHODS: We studied participants from a randomized controlled trial of primary prevention with statin therapy (WOSCOPS [West of Scotland Coronary Prevention Study]; n=4910) and 2 observational cohort studies (CARDIA [Coronary Artery Risk Development in Young Adults] and BioImage; n=1154 and 4392, respectively). For each participant, we calculated a polygenic risk score derived from up to 57 common DNA sequence variants previously associated with coronary heart disease. We compared the relative efficacy of statin therapy in those at high genetic risk (top quintile of polygenic risk score) versus all others (WOSCOPS), as well as the association between the polygenic risk score and coronary artery calcification (CARDIA) and carotid artery plaque burden (BioImage).

RESULTS: Among WOSCOPS trial participants at high genetic risk, statin therapy was associated with a relative risk reduction of 44\% (95\% confidence interval [CI], 22-60; <0.001), whereas in all others, the relative risk reduction was 24\% (95\% CI, 8-37; =0.004) despite similar low-density lipoprotein cholesterol lowering. In a study-level meta-analysis across the WOSCOPS, ASCOT, and JUPITER primary prevention, relative risk reduction in those at high genetic risk was 46\% versus 26\% in all others ( for heterogeneity=0.05). Across all 3 studies, the absolute risk reduction with statin therapy was 3.6\% (95\% CI, 2.0-5.1) among those in the high genetic risk group and 1.3\% (95\% CI, 0.6-1.9) in all others. Each 1-SD increase in the polygenic risk score was associated with 1.32-fold (95\% CI, 1.04-1.68) greater likelihood of having coronary artery calcification and 9.7\% higher (95\% CI, 2.2-17.8) burden of carotid plaque.

CONCLUSIONS: Those at high genetic risk have a greater burden of subclinical atherosclerosis and derive greater relative and absolute benefit from statin therapy to prevent a first coronary heart disease event.

CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00738725 (BioImage) and NCT00005130 (CARDIA). WOSCOPS was carried out and completed before the requirement for clinical trial registration.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Atherosclerosis, Cohort Studies, Cost of Illness, Female, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Male, Middle Aged, Multifactorial Inheritance, Primary Prevention, Risk Factors, Young Adult}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.116.024436}, author = {Natarajan, Pradeep and Young, Robin and Stitziel, Nathan O and Padmanabhan, Sandosh and Baber, Usman and Mehran, Roxana and Sartori, Samantha and Fuster, Valentin and Reilly, Dermot F and Butterworth, Adam and Rader, Daniel J and Ford, Ian and Sattar, Naveed and Kathiresan, Sekar} } @article {8, title = {Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease.}, journal = {N Engl J Med}, volume = {375}, year = {2016}, month = {2016 Dec 15}, pages = {2349-2358}, abstract = {

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{\textquoteright}s Genome Health Study (WGHS), and 22,389 in the Malm{\"o} 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.).

}, keywords = {Aged, Cohort Studies, Coronary Disease, Cross-Sectional Studies, Female, Genetic Predisposition to Disease, Healthy Lifestyle, Humans, Incidence, Male, Middle Aged, Multifactorial Inheritance, Patient Compliance, Polymorphism, Genetic, Risk}, issn = {1533-4406}, doi = {10.1056/NEJMoa1605086}, author = {Khera, Amit V and Emdin, Connor A and Drake, Isabel and Natarajan, Pradeep and Bick, Alexander G and Cook, Nancy R and Chasman, Daniel I and Baber, Usman and Mehran, Roxana and Rader, Daniel J and Fuster, Valentin and Boerwinkle, Eric and Melander, Olle and Orho-Melander, Marju and Ridker, Paul M and Kathiresan, Sekar} }