@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 {93, title = {Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism.}, journal = {Cell}, volume = {180}, year = {2020}, month = {2020 02 06}, pages = {568-584.e23}, abstract = {

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n~= 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

}, keywords = {Autistic Disorder, Case-Control Studies, Cell Lineage, Cerebral Cortex, Cohort Studies, Exome, Female, Gene Expression Regulation, Developmental, Gene Frequency, Genetic Predisposition to Disease, Humans, Male, Mutation, Missense, Neurobiology, Neurons, Phenotype, Sex Factors, Single-Cell Analysis, Whole Exome Sequencing}, issn = {1097-4172}, doi = {10.1016/j.cell.2019.12.036}, author = {Satterstrom, F Kyle and Kosmicki, Jack A and Wang, Jiebiao and Breen, Michael S and De Rubeis, Silvia and An, Joon-Yong and Peng, Minshi and Collins, Ryan and Grove, Jakob and Klei, Lambertus and Stevens, Christine and Reichert, Jennifer and Mulhern, Maureen S and Artomov, Mykyta and Gerges, Sherif and Sheppard, Brooke and Xu, Xinyi and Bhaduri, Aparna and Norman, Utku and Brand, Harrison and Schwartz, Grace and Nguyen, Rachel and Guerrero, Elizabeth E and Dias, Caroline and Betancur, Catalina and Cook, Edwin H and Gallagher, Louise and Gill, Michael and Sutcliffe, James S and Thurm, Audrey and Zwick, Michael E and B{\o}rglum, Anders D and State, Matthew W and Cicek, A Ercument and Talkowski, Michael E and Cutler, David J and Devlin, Bernie and Sanders, Stephan J and Roeder, Kathryn and Daly, Mark J and Buxbaum, Joseph D} } @article {139, title = {A variant-centric perspective on geographic patterns of human allele frequency variation.}, journal = {Elife}, volume = {9}, year = {2020}, month = {2020 12 22}, abstract = {

A key challenge in human genetics is to understand the geographic distribution of human genetic variation. Often genetic variation is described by showing relationships among populations or individuals, drawing inferences over many variants. Here, we introduce an alternative representation of genetic variation that reveals the relative abundance of different allele frequency patterns. This approach allows viewers to easily see several features of human genetic structure: (1) most variants are rare and geographically localized, (2) variants that are common in a single geographic region are more likely to be shared across the globe than to be private to that region, and (3) where two individuals differ, it is most often due to variants that are found globally, regardless of whether the individuals are from the same region or different regions. Our variant-centric visualization clarifies the geographic patterns of human variation and can help address misconceptions about genetic differentiation among populations.

}, keywords = {Gene Frequency, Genetic Variation, Genetics, Population, Geography, Humans}, issn = {2050-084X}, doi = {10.7554/eLife.60107}, author = {Biddanda, Arjun and Rice, Daniel P and Novembre, John} } @article {38, title = {Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease.}, journal = {Nat Commun}, volume = {9}, year = {2018}, month = {2018 04 24}, pages = {1613}, abstract = {

Less than 3\% of protein-coding genetic variants are predicted to result in loss of protein function through the introduction of a stop codon, frameshift, or the disruption of an essential splice site; however, such predicted loss-of-function (pLOF) variants provide insight into effector transcript and direction of biological effect. In >400,000 UK Biobank participants, we conduct association analyses of 3759 pLOF variants with six metabolic traits, six cardiometabolic diseases, and twelve additional diseases. We identified 18 new low-frequency or rare (allele frequency < 5\%) pLOF variant-phenotype associations. pLOF variants in the gene GPR151 protect against obesity and type 2 diabetes, in the gene IL33 against asthma and allergic disease, and in the gene IFIH1 against hypothyroidism. In the gene PDE3B, pLOF variants associate with elevated height, improved body fat distribution and protection from coronary artery disease. Our findings prioritize genes for which pharmacologic mimics of pLOF variants may lower risk for disease.

}, keywords = {Databases, Genetic, Diabetes Mellitus, Type 2, Disease, Gene Frequency, Genetic Testing, Genetic Variation, Humans, Obesity, Phenotype, Proteins, Respiratory Hypersensitivity, United Kingdom}, issn = {2041-1723}, doi = {10.1038/s41467-018-03911-8}, author = {Emdin, Connor A and Khera, Amit V and Chaffin, Mark and Klarin, Derek and Natarajan, Pradeep and Aragam, Krishna and Haas, Mary and Bick, Alexander and Zekavat, Seyedeh M and Nomura, Akihiro and Ardissino, Diego and Wilson, James G and Schunkert, Heribert and McPherson, Ruth and Watkins, Hugh and Elosua, Roberto and Bown, Matthew J and Samani, Nilesh J and Baber, Usman and Erdmann, Jeanette and Gupta, Namrata and Danesh, John and Chasman, Daniel and Ridker, Paul and Denny, Joshua and Bastarache, Lisa and Lichtman, Judith H and D{\textquoteright}Onofrio, Gail and Mattera, Jennifer and Spertus, John A and Sheu, Wayne H-H and Taylor, Kent D and Psaty, Bruce M and Rich, Stephen S and Post, Wendy and Rotter, Jerome I and Chen, Yii-Der Ida and Krumholz, Harlan and Saleheen, Danish and Gabriel, Stacey and Kathiresan, Sekar} } @article {7, title = {Practical Approaches for Whole-Genome Sequence Analysis of Heart- and Blood-Related Traits.}, journal = {Am J Hum Genet}, volume = {100}, year = {2017}, month = {2017 Feb 02}, pages = {205-215}, abstract = {

Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.

}, keywords = {Black or African American, C-Reactive Protein, Cholesterol, HDL, Cholesterol, LDL, Chromosomes, Human, Pair 9, Gene Frequency, Genome, Human, Genome-Wide Association Study, Genomics, Hemoglobins, Humans, Introns, Leukocyte Count, Lipoprotein(a), Magnesium, Natriuretic Peptide, Brain, Neutrophils, Peptide Fragments, Phosphorus, Platelet Count, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Troponin T, White People}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2016.12.009}, author = {Morrison, Alanna C and Huang, Zhuoyi and Yu, Bing and Metcalf, Ginger and Liu, Xiaoming and Ballantyne, Christie and Coresh, Josef and Yu, Fuli and Muzny, Donna and Feofanova, Elena and Rustagi, Navin and Gibbs, Richard and Boerwinkle, Eric} } @article {20, title = {SVScore: an impact prediction tool for structural variation.}, journal = {Bioinformatics}, volume = {33}, year = {2017}, month = {2017 04 01}, pages = {1083-1085}, abstract = {

Summary: Here we present SVScore, a tool for in silico structural variation (SV) impact prediction. SVScore aggregates per-base single nucleotide polymorphism (SNP) pathogenicity scores across relevant genomic intervals for each SV in a manner that considers variant type, gene features and positional uncertainty. We show that the allele frequency spectrum of high-scoring SVs is strongly skewed toward lower frequencies, suggesting that they are under purifying selection, and that SVScore identifies deleterious variants more effectively than alternative methods. Notably, our results also suggest that duplications are under surprisingly strong selection relative to deletions, and that there are a similar number of strongly pathogenic SVs and SNPs in the human population.

Availability and Implementation: SVScore is implemented in Perl and available freely at {{ http://www.github.com/lganel/SVScore }} for use under the MIT license.

Contact: ihall@wustl.edu.

Supplementary information: Supplementary data are available at Bioinformatics online.

}, keywords = {Gene Frequency, Genomic Structural Variation, Genomics, Humans, Polymorphism, Single Nucleotide, Sequence Deletion, Software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btw789}, author = {Ganel, Liron and Abel, Haley J and Hall, Ira M} }