@article {897, 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 {812, title = {A genome-wide case-only test for the detection of digenic inheritance in human exomes.}, journal = {Proc Natl Acad Sci U S A}, volume = {117}, year = {2020}, month = {2020 08 11}, pages = {19367-19375}, abstract = {

Whole-exome sequencing (WES) has facilitated the discovery of genetic lesions underlying monogenic disorders. Incomplete penetrance and variable expressivity suggest a contribution of additional genetic lesions to clinical manifestations and outcome. Some monogenic disorders may therefore actually be digenic. However, only a few digenic disorders have been reported, all discovered by candidate gene approaches applied to at least one locus. We propose here a two-locus genome-wide test for detecting digenic inheritance in WES data. This approach uses the gene as the unit of analysis and tests all pairs of genes to detect pairwise gene {\texttimes} gene interactions underlying disease. It is a case-only method, which has several advantages over classic case-control tests, in particular by avoiding recruitment of controls. Our simulation studies based on real WES data identified two major sources of type I error inflation in this case-only test: linkage disequilibrium and population stratification. Both were corrected by specific procedures. Moreover, our case-only approach is more powerful than the corresponding case-control test for detecting digenic interactions in various population stratification scenarios. Finally, we confirmed the potential of our unbiased, genome-wide approach by successfully identifying a previously reported digenic lesion in patients with craniosynostosis. Our case-only test is a powerful and timely tool for detecting digenic inheritance in WES data from patients.

}, keywords = {Craniosynostoses, Epistasis, Genetic, Exome, Genetic Linkage, Genetic Variation, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, Humans, Models, Genetic, Multifactorial Inheritance, Whole Exome Sequencing}, issn = {1091-6490}, doi = {10.1073/pnas.1920650117}, author = {Kerner, Gaspard and Bouaziz, Matthieu and Cobat, Aurelie and Bigio, Benedetta and Timberlake, Andrew T and Bustamante, Jacinta and Lifton, Richard P and Casanova, Jean-Laurent and Abel, Laurent} } @article {855, 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 {875, 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 {848, 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 {845, 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, Francois 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 {853, 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 {484, title = {Novel digenic inheritance of PCDH15 and USH1G underlies profound non-syndromic hearing impairment.}, journal = {BMC Med Genet}, volume = {19}, year = {2018}, month = {2018 07 20}, pages = {122}, abstract = {

BACKGROUND: Digenic inheritance is the simplest model of oligenic disease. It can be observed when there is a strong epistatic interaction between two loci. For both syndromic and non-syndromic hearing impairment, several forms of digenic inheritance have been reported.

METHODS: We performed exome sequencing in a Pakistani family with profound non-syndromic hereditary hearing impairment to identify the genetic cause of disease.

RESULTS: We found that this family displays digenic inheritance for two trans heterozygous missense mutations, one in PCDH15 [p.(Arg1034His)] and another in USH1G [p.(Asp365Asn)]. Both of these genes are known to cause autosomal recessive non-syndromic hearing impairment and Usher syndrome. The protein products of PCDH15 and USH1G function together at the stereocilia tips in the hair cells and are necessary for proper mechanotransduction. Epistasis between Pcdh15 and Ush1G has been previously reported in digenic heterozygous mice. The digenic mice displayed a significant decrease in hearing compared to age-matched heterozygous animals. Until now no human examples have been reported.

CONCLUSIONS: The discovery of novel digenic inheritance mechanisms in hereditary hearing impairment will aid in understanding the interaction between defective proteins and further define inner ear function and its interactome.

}, keywords = {Adult, Animals, Cadherins, Hearing Loss, Heterozygote, Humans, Male, Mechanotransduction, Cellular, Multifactorial Inheritance, Mutation, Nerve Tissue Proteins, Pakistan, Pedigree, Usher Syndromes, Young Adult}, issn = {1471-2350}, doi = {10.1186/s12881-018-0618-5}, author = {Schrauwen, Isabelle and Chakchouk, Imen and Acharya, Anushree and Liaqat, Khurram and Nickerson, Deborah A and Bamshad, Michael J and Shah, Khadim and Ahmad, Wasim and Leal, Suzanne M} } @article {249, title = {Variant association tools for quality control and analysis of large-scale sequence and genotyping array data.}, journal = {Am J Hum Genet}, volume = {94}, year = {2014}, month = {2014 May 01}, pages = {770-83}, abstract = {

Currently there is great interest in detecting associations between complex traits and rare variants. In this report, we describe Variant Association Tools (VAT) and the VAT pipeline, which implements best practices for rare-variant association studies. Highlights of VAT include variant-site and call-level quality control (QC), summary statistics, phenotype- and genotype-based sample selection, variant annotation, selection of variants for association analysis, and a collection of rare-variant association methods for analyzing qualitative and quantitative traits. The association testing framework for VAT is regression based, which readily allows for flexible construction of association models with multiple covariates and weighting themes based on allele frequencies or predicted functionality. Additionally, pathway analyses, conditional analyses, and analyses of gene-gene and gene-environment interactions can be performed. VAT is capable of rapidly scanning through data by using multi-process computation, adaptive permutation, and simultaneously conducting association analysis via multiple methods. Results are available in text or graphic file formats and additionally can be output to relational databases for further annotation and filtering. An interface to R language also facilitates user implementation of novel association methods. The VAT{\textquoteright}s data QC and association-analysis pipeline can be applied to sequence, imputed, and genotyping array, e.g., "exome chip," data, providing a reliable and reproducible computational environment in which to analyze small- to large-scale studies with data from the latest genotyping and sequencing technologies. Application of the VAT pipeline is demonstrated through analysis of data from the 1000 Genomes project.

}, keywords = {Genetic Association Studies, Genetic Variation, Genotyping Techniques, High-Throughput Nucleotide Sequencing, Humans, Multifactorial Inheritance, Quality Control, Software}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2014.04.004}, author = {Wang, Gao T and Peng, Bo and Leal, Suzanne M} }