@article {151, title = {Association of structural variation with cardiometabolic traits in Finns.}, journal = {Am J Hum Genet}, volume = {108}, year = {2021}, month = {2021 04 01}, pages = {583-596}, abstract = {

The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47~{\texttimes} 10) and is also associated with increased levels of total cholesterol (p = 1.22~{\texttimes} 10) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81~{\texttimes} 10) and alanine (p = 6.14~{\texttimes} 10) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24~{\texttimes} 10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53~{\texttimes} 10). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.

}, keywords = {Alleles, Cardiovascular Diseases, Cholesterol, DNA Copy Number Variations, Female, Finland, Genome, Human, Genomic Structural Variation, Genotype, High-Throughput Nucleotide Sequencing, Humans, Male, Mitochondrial Proteins, Promoter Regions, Genetic, Pyruvate Dehydrogenase (Lipoamide)-Phosphatase, Pyruvic Acid, Serum Albumin, Human}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.03.008}, author = {Chen, Lei and Abel, Haley J and Das, Indraniel and Larson, David E and Ganel, Liron and Kanchi, Krishna L and Regier, Allison A and Young, Erica P and Kang, Chul Joo and Scott, Alexandra J and Chiang, Colby and Wang, Xinxin and Lu, Shuangjia and Christ, Ryan and Service, Susan K and Chiang, Charleston W K and Havulinna, Aki S and Kuusisto, Johanna and Boehnke, Michael and Laakso, Markku and Palotie, Aarno and Ripatti, Samuli and Freimer, Nelson B and Locke, Adam E and Stitziel, Nathan O and Hall, Ira M} } @article {122, title = {Mapping and characterization of structural variation in 17,795 human genomes.}, journal = {Nature}, volume = {583}, year = {2020}, month = {2020 07}, pages = {83-89}, abstract = {

A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0-11.2\% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2\% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90\% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2\% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing.

}, keywords = {Alleles, Case-Control Studies, Continental Population Groups, Epigenesis, Genetic, Female, Gene Dosage, Genetic Variation, Genetics, Population, Genome, Human, High-Throughput Nucleotide Sequencing, Humans, Male, Molecular Sequence Annotation, Quantitative Trait Loci, Software, Whole Genome Sequencing}, issn = {1476-4687}, doi = {10.1038/s41586-020-2371-0}, author = {Abel, Haley J and Larson, David E and Regier, Allison A and Chiang, Colby and Das, Indraniel and Kanchi, Krishna L and Layer, Ryan M and Neale, Benjamin M and Salerno, William J and Reeves, Catherine and Buyske, Steven and Matise, Tara C and Muzny, Donna M and Zody, Michael C and Lander, Eric S and Dutcher, Susan K and Stitziel, Nathan O and Hall, Ira M} } @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 {12, title = {ANGPTL3 Deficiency and Protection Against Coronary Artery Disease.}, journal = {J Am Coll Cardiol}, volume = {69}, year = {2017}, month = {2017 Apr 25}, pages = {2054-2063}, abstract = {

BACKGROUND: Familial combined hypolipidemia, a Mendelian condition characterized by substantial reductions in all 3~major lipid fractions, is caused by mutations that inactivate the gene angiopoietin-like 3 (ANGPTL3). Whether ANGPTL3 deficiency reduces risk of coronary artery disease (CAD) is unknown.

OBJECTIVES: The study goal was to leverage 3 distinct lines of evidence-a family that included individuals with complete (compound heterozygote) ANGPTL3 deficiency, a population based-study of humans with partial (heterozygote) ANGPTL3 deficiency, and biomarker levels in patients with myocardial infarction (MI)-to test whether ANGPTL3 deficiency is associated with lower risk for CAD.

METHODS: We assessed coronary atherosclerotic burden in 3 individuals with complete ANGPTL3 deficiency and 3~wild-type first-degree relatives using computed tomography angiography. In the population, ANGPTL3 loss-of-function (LOF) mutations were ascertained in up to 21,980 people with CAD and 158,200 control subjects. LOF mutations were~defined as nonsense, frameshift, and splice-site variants, along with missense variants resulting in~<25\% of wild-type ANGPTL3 activity in a mouse model. In a biomarker study, circulating ANGPTL3 concentration was measured in 1,493 people who presented with MI and 3,232 control subjects.

RESULTS: The 3 individuals with complete ANGPTL3 deficiency showed no evidence of coronary atherosclerotic plaque. ANGPTL3 gene sequencing demonstrated that approximately 1 in 309 people was a heterozygous carrier for an LOF mutation. Compared with those without mutation, heterozygous carriers of ANGPTL3 LOF mutations demonstrated a 17\% reduction in circulating triglycerides and a 12\% reduction in low-density lipoprotein cholesterol. Carrier status was associated with a 34\% reduction in odds of CAD (odds ratio: 0.66; 95\% confidence interval: 0.44 to 0.98; p~= 0.04). Individuals in the lowest tertile of circulating ANGPTL3 concentrations, compared with the highest, had reduced odds of MI (adjusted odds ratio: 0.65; 95\% confidence interval: 0.55 to 0.77; p~< 0.001).

CONCLUSIONS: ANGPTL3 deficiency is associated with protection from CAD.

}, keywords = {Adult, Angiopoietin-Like Protein 3, Angiopoietin-like Proteins, Angiopoietins, Animals, Atherosclerosis, Case-Control Studies, Coronary Artery Disease, Female, Humans, Lipids, Male, Mice, Inbred C57BL, Mice, Knockout, Middle Aged, Mutation, Missense, Myocardial Infarction, Risk Factors}, issn = {1558-3597}, doi = {10.1016/j.jacc.2017.02.030}, author = {Stitziel, Nathan O and Khera, Amit V and Wang, Xiao and Bierhals, Andrew J and Vourakis, A Christina and Sperry, Alexandra E and Natarajan, Pradeep and Klarin, Derek and Emdin, Connor A and Zekavat, Seyedeh M and Nomura, Akihiro and Erdmann, Jeanette and Schunkert, Heribert and Samani, Nilesh J and Kraus, William E and Shah, Svati H and Yu, Bing and Boerwinkle, Eric and Rader, Daniel J and Gupta, Namrata and Frossard, Philippe M and Rasheed, Asif and Danesh, John and Lander, Eric S and Gabriel, Stacey and Saleheen, Danish and Musunuru, Kiran and Kathiresan, Sekar} } @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} }