@article {119, title = {Identification of Required Host Factors for SARS-CoV-2 Infection in Human Cells.}, journal = {Cell}, volume = {184}, year = {2021}, month = {2021 01 07}, pages = {92-105.e16}, abstract = {

To better understand host-virus genetic dependencies and find potential therapeutic targets for COVID-19, we performed a genome-scale CRISPR loss-of-function screen to identify host factors required for SARS-CoV-2 viral infection of human alveolar epithelial cells. Top-ranked genes cluster into distinct pathways, including the vacuolar ATPase proton pump, Retromer, and Commander complexes. We validate these gene targets using several orthogonal methods such as CRISPR knockout, RNA interference knockdown, and small-molecule inhibitors. Using single-cell RNA-sequencing, we identify shared transcriptional changes in cholesterol biosynthesis upon loss of top-ranked genes. In addition, given the key role of the ACE2 receptor in the early stages of viral entry, we show that loss of RAB7A reduces viral entry by sequestering the ACE2 receptor inside cells. Overall, this work provides a genome-scale, quantitative resource of the impact of the loss of each host gene on fitness/response to viral infection.

}, keywords = {A549 Cells, Alveolar Epithelial Cells, Angiotensin-Converting Enzyme 2, Biosynthetic Pathways, Cholesterol, Clustered Regularly Interspaced Short Palindromic Repeats, COVID-19, Endosomes, Gene Expression Profiling, Gene Knockdown Techniques, Gene Knockout Techniques, Genome-Wide Association Study, Host-Pathogen Interactions, Humans, rab GTP-Binding Proteins, rab7 GTP-Binding Proteins, RNA Interference, SARS-CoV-2, Single-Cell Analysis, Viral Load}, issn = {1097-4172}, doi = {10.1016/j.cell.2020.10.030}, author = {Daniloski, Zharko and Jordan, Tristan X and Wessels, Hans-Hermann and Hoagland, Daisy A and Kasela, Silva and Legut, Mateusz and Maniatis, Silas and Mimitou, Eleni P and Lu, Lu and Geller, Evan and Danziger, Oded and Rosenberg, Brad R and Phatnani, Hemali and Smibert, Peter and Lappalainen, Tuuli and tenOever, Benjamin R and Sanjana, Neville E} } @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 {117, title = {Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy.}, journal = {Nat Commun}, volume = {11}, year = {2020}, month = {2020 05 07}, pages = {2254}, abstract = {

Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we report a genome-wide association study of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 36,041 UK Biobank participants, with replication in 2184 participants from the Multi-Ethnic Study of Atherosclerosis. We identify 45 previously unreported loci associated with cardiac structure and function, many near well-established genes for Mendelian cardiomyopathies. A polygenic score of MRI-derived left ventricular end systolic volume strongly associates with incident DCM in the general population. Even among carriers of TTN truncating mutations, this polygenic score influences the size and function of the human heart. These results further implicate common genetic polymorphisms in the pathogenesis of DCM.

}, keywords = {Cardiomyopathy, Dilated, Genome-Wide Association Study, Heart, Humans, Magnetic Resonance Imaging, Myocardium, Polymorphism, Single Nucleotide}, issn = {2041-1723}, doi = {10.1038/s41467-020-15823-7}, author = {Pirruccello, James P and Bick, Alexander and Wang, Minxian and Chaffin, Mark and Friedman, Samuel and Yao, Jie and Guo, Xiuqing and Venkatesh, Bharath Ambale and Taylor, Kent D and Post, Wendy S and Rich, Stephen and Lima, Joao A C and Rotter, Jerome I and Philippakis, Anthony and Lubitz, Steven A and Ellinor, Patrick T and Khera, Amit V and Kathiresan, Sekar and Aragam, Krishna G} } @article {126, title = {Epilepsy subtype-specific copy number burden observed in a genome-wide study of 17 458 subjects.}, journal = {Brain}, volume = {143}, year = {2020}, month = {2020 07 01}, pages = {2106-2118}, abstract = {

Cytogenic testing is routinely applied in most neurological centres for severe paediatric epilepsies. However, which characteristics of copy number variants (CNVs) confer most epilepsy risk and which epilepsy subtypes carry the most CNV burden, have not been explored on a genome-wide scale. Here, we present the largest CNV investigation in epilepsy to date with 10 712 European epilepsy cases and 6746 ancestry-matched controls. Patients with genetic generalized epilepsy, lesional focal epilepsy, non-acquired focal epilepsy, and developmental and epileptic encephalopathy were included. All samples were processed with the same technology and analysis pipeline. All investigated epilepsy types, including lesional focal epilepsy patients, showed an increase in CNV burden in at least one tested category compared to controls. However, we observed striking differences in CNV burden across epilepsy types and investigated CNV categories. Genetic generalized epilepsy patients have the highest CNV burden in all categories tested, followed by developmental and epileptic encephalopathy patients. Both epilepsy types also show association for deletions covering genes intolerant for truncating variants. Genome-wide CNV breakpoint association showed not only significant loci for genetic generalized and developmental and epileptic encephalopathy patients but also for lesional focal epilepsy patients. With a 34-fold risk for developing genetic generalized epilepsy, we show for the first time that the established epilepsy-associated 15q13.3 deletion represents the strongest risk CNV for genetic generalized epilepsy across the whole genome. Using the human interactome, we examined the largest connected component of the genes overlapped by CNVs in the four epilepsy types. We observed that genetic generalized epilepsy and non-acquired focal epilepsy formed disease modules. In summary, we show that in all common epilepsy types, 1.5-3\% of patients carry epilepsy-associated CNVs. The characteristics of risk CNVs vary tremendously across and within epilepsy types. Thus, we advocate genome-wide genomic testing to identify all disease-associated types of CNVs.

}, keywords = {DNA Copy Number Variations, Epilepsy, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male}, issn = {1460-2156}, doi = {10.1093/brain/awaa171}, author = {Niestroj, Lisa-Marie and Perez-Palma, Eduardo and Howrigan, Daniel P and Zhou, Yadi and Cheng, Feixiong and Saarentaus, Elmo and N{\"u}rnberg, Peter and Stevelink, Remi and Daly, Mark J and Palotie, Aarno and Lal, Dennis} } @article {104, title = {Genome-wide association meta-analysis for early age-related macular degeneration highlights novel loci and insights for advanced disease.}, journal = {BMC Med Genomics}, volume = {13}, year = {2020}, month = {2020 08 26}, pages = {120}, abstract = {

BACKGROUND: Advanced age-related macular degeneration (AMD) is a leading cause of blindness. While around half of the genetic contribution to advanced AMD has been uncovered, little is known about the genetic architecture of early AMD.

METHODS: To identify genetic factors for early AMD, we conducted a genome-wide association study (GWAS) meta-analysis (14,034 cases, 91,214 controls, 11 sources of data including the International AMD Genomics Consortium, IAMDGC, and UK Biobank, UKBB). We ascertained early AMD via color fundus photographs by manual grading for 10 sources and via an automated machine learning approach for > 170,000 photographs from UKBB. We searched for early AMD loci via GWAS and via a candidate approach based on 14 previously suggested early AMD variants.

RESULTS: Altogether, we identified 10 independent loci with statistical significance for early AMD: (i) 8 from our GWAS with genome-wide significance (P~< 5 {\texttimes} 10), (ii) one previously suggested locus with experiment-wise significance (P~< 0.05/14) in our non-overlapping data and with genome-wide significance when combining the reported and our non-overlapping data (together 17,539 cases, 105,395 controls), and (iii) one further previously suggested locus with experiment-wise significance in our non-overlapping data. Of these 10 identified loci, 8 were novel and 2 known for early AMD. Most of the 10 loci overlapped with known advanced AMD loci (near ARMS2/HTRA1, CFH, C2, C3, CETP, TNFRSF10A, VEGFA, APOE), except two that have not yet been identified with statistical significance for any AMD. Among the 17 genes within these two loci, in-silico functional annotation suggested CD46 and TYR as the most likely responsible genes. Presence or absence of an early AMD effect distinguished the known pathways of advanced AMD genetics (complement/lipid pathways versus extracellular matrix metabolism).

CONCLUSIONS: Our GWAS on early AMD identified novel loci, highlighted shared and distinct genetics between early and advanced AMD and provides insights into AMD etiology. Our data provide a resource comparable in size to the existing IAMDGC data on advanced AMD genetics enabling a joint view. The biological relevance of this joint view is underscored by the ability of early AMD effects to differentiate the major pathways for advanced AMD.

}, keywords = {Case-Control Studies, Genetic Loci, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Macular Degeneration, Polymorphism, Single Nucleotide}, issn = {1755-8794}, doi = {10.1186/s12920-020-00760-7}, author = {Winkler, Thomas W and Grassmann, Felix and Brandl, Caroline and Kiel, Christina and G{\"u}nther, Felix and Strunz, Tobias and Weidner, Lorraine and Zimmermann, Martina E and Korb, Christina A and Poplawski, Alicia and Schuster, Alexander K and M{\"u}ller-Nurasyid, Martina and Peters, Annette and Rauscher, Franziska G and Elze, Tobias and Horn, Katrin and Scholz, Markus and Ca{\~n}adas-Garre, Marisa and McKnight, Amy Jayne and Quinn, Nicola and Hogg, Ruth E and K{\"u}chenhoff, Helmut and Heid, Iris M and Stark, Klaus J and Weber, Bernhard H F} } @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 {97, title = {The GTEx Consortium atlas of genetic regulatory effects across human tissues.}, journal = {Science}, volume = {369}, year = {2020}, month = {2020 09 11}, pages = {1318-1330}, abstract = {

The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

}, keywords = {Datasets as Topic, Disease, Female, Gene Expression Regulation, Genome-Wide Association Study, Humans, Male, Organ Specificity, Quantitative Trait Loci, Sequence Analysis, RNA}, issn = {1095-9203}, doi = {10.1126/science.aaz1776} } @article {102, title = {The impact of sex on gene expression across human tissues.}, journal = {Science}, volume = {369}, year = {2020}, month = {2020 09 11}, abstract = {

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37\% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.

}, keywords = {Chromosomes, Human, X, Disease, Epigenesis, Genetic, Female, Gene Expression, Gene Expression Regulation, Genetic Variation, Genome-Wide Association Study, Humans, Male, Organ Specificity, Promoter Regions, Genetic, Quantitative Trait Loci, Sex Characteristics, Sex Factors}, issn = {1095-9203}, doi = {10.1126/science.aba3066}, author = {Oliva, Meritxell and Mu{\~n}oz-Aguirre, Manuel and Kim-Hellmuth, Sarah and Wucher, Valentin and Gewirtz, Ariel D H and Cotter, Daniel J and Parsana, Princy and Kasela, Silva and Balliu, Brunilda and Vi{\~n}uela, Ana and Castel, Stephane E and Mohammadi, Pejman and Aguet, Fran{\c c}ois and Zou, Yuxin and Khramtsova, Ekaterina A and Skol, Andrew D and Garrido-Mart{\'\i}n, Diego and Reverter, Ferran and Brown, Andrew and Evans, Patrick and Gamazon, Eric R and Payne, Anthony and Bonazzola, Rodrigo and Barbeira, Alvaro N and Hamel, Andrew R and Martinez-Perez, Angel and Soria, Jos{\'e} Manuel and Pierce, Brandon L and Stephens, Matthew and Eskin, Eleazar and Dermitzakis, Emmanouil T and Segr{\`e}, Ayellet V and Im, Hae Kyung and Engelhardt, Barbara E and Ardlie, Kristin G and Montgomery, Stephen B and Battle, Alexis J and Lappalainen, Tuuli and Guigo, Roderic and Stranger, Barbara E} } @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 {125, title = {The Parkinson{\textquoteright}s Disease Genome-Wide Association Study Locus Browser.}, journal = {Mov Disord}, volume = {35}, year = {2020}, month = {2020 11}, pages = {2056-2067}, abstract = {

BACKGROUND: Parkinson{\textquoteright}s disease (PD) is a neurodegenerative disease with an often complex component identifiable by genome-wide association studies. The most recent large-scale PD genome-wide association studies have identified more than 90 independent risk variants for PD risk and progression across more than 80 genomic regions. One major challenge in current genomics is the identification of the causal gene(s) and variant(s) at each genome-wide association study locus. The objective of the current study was to create a tool that would display data for relevant PD risk loci and provide guidance with the prioritization of causal genes and potential mechanisms at each locus.

METHODS: We included all significant genome-wide signals from multiple recent PD genome-wide association studies including themost recent PD risk genome-wide association study, age-at-onset genome-wide association study, progression genome-wide association study, and Asian population PD risk genome-wide association study. We gathered data for all genes 1 Mb up and downstream of each variant to allow users to assess which gene(s) are most associated with the variant of interest based on a set of self-ranked criteria. Multiple databases were queried for each gene to collect additional causal data.

RESULTS: We created a PD genome-wide association study browser tool (https://pdgenetics.shinyapps.io/GWASBrowser/) to assist the PD research community with the prioritization of genes for follow-up functional studies to identify potential therapeutic targets.

CONCLUSIONS: Our PD genome-wide association study browser tool provides users with a useful method of identifying potential causal genes at all known PD risk loci from large-scale PD genome-wide association studies. We plan to update this tool with new relevant data as sample sizes increase and new PD risk loci are discovered. {\textcopyright} 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

}, keywords = {Age of Onset, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Neurodegenerative Diseases, Parkinson Disease, Risk Factors}, issn = {1531-8257}, doi = {10.1002/mds.28197}, author = {Grenn, Francis P and Kim, Jonggeol J and Makarious, Mary B and Iwaki, Hirotaka and Illarionova, Anastasia and Brolin, Kajsa and Kluss, Jillian H and Schumacher-Schuh, Artur F and Leonard, Hampton and Faghri, Faraz and Billingsley, Kimberley and Krohn, Lynne and Hall, Ashley and Diez-Fairen, Monica and Peri{\~n}{\'a}n, Maria Teresa and Foo, Jia Nee and Sandor, Cynthia and Webber, Caleb and Fiske, Brian K and Gibbs, J Raphael and Nalls, Mike A and Singleton, Andrew B and Bandres-Ciga, Sara and Reed, Xylena and Blauwendraat, Cornelis} } @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 {52, title = {A multi-task convolutional deep neural network for variant calling in single molecule sequencing.}, journal = {Nat Commun}, volume = {10}, year = {2019}, month = {2019 03 01}, pages = {998}, abstract = {

The accurate identification of DNA sequence variants is an important, but challenging task in genomics. It is particularly difficult for single molecule sequencing, which has a per-nucleotide error rate of ~5-15\%. Meeting this demand, we developed Clairvoyante, a multi-task five-layer convolutional neural network model for predicting variant type (SNP or indel), zygosity, alternative allele and indel length from aligned reads. For the well-characterized NA12878 human sample, Clairvoyante achieves 99.67, 95.78, 90.53\% F1-score on 1KP common variants, and 98.65, 92.57, 87.26\% F1-score for whole-genome analysis, using Illumina, PacBio, and Oxford Nanopore data, respectively. Training on a second human sample shows Clairvoyante is sample agnostic and finds variants in less than 2 h on a standard server. Furthermore, we present 3,135 variants that are missed using Illumina but supported independently by both PacBio and Oxford Nanopore reads. Clairvoyante is available open-source ( https://github.com/aquaskyline/Clairvoyante ), with modules to train, utilize and visualize the model.

}, keywords = {Base Sequence, Computational Biology, DNA Mutational Analysis, Genome, Human, Genome-Wide Association Study, Genomics, Genotype, Genotyping Techniques, Humans, INDEL Mutation, Nanopores, Neural Networks (Computer), Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Software}, issn = {2041-1723}, doi = {10.1038/s41467-019-09025-z}, author = {Luo, Ruibang and Sedlazeck, Fritz J and Lam, Tak-Wah and Schatz, Michael C} } @article {28, title = {Exome sequencing reveals novel genetic loci influencing obesity-related traits in Hispanic children.}, journal = {Obesity (Silver Spring)}, volume = {25}, year = {2017}, month = {2017 Jul}, pages = {1270-1276}, abstract = {

OBJECTIVE: To perform whole exome sequencing in 928 Hispanic children and identify variants and genes associated with childhood obesity.

METHODS: Single-nucleotide variants (SNVs) were identified from Illumina whole exome sequencing data using integrated read mapping, variant calling, and an annotation pipeline (Mercury). Association analyses of 74 obesity-related traits and exonic variants were performed using SeqMeta software. Rare autosomal variants were analyzed using gene-based association analyses, and common autosomal variants were analyzed at the SNV level.

RESULTS: (1) Rare exonic variants in 10 genes and 16 common SNVs in 11 genes that were associated with obesity traits in a cohort of Hispanic children were identified, (2) novel rare variants in peroxisome biogenesis factor 1 (PEX1) associated with several obesity traits (weight, weight z score, BMI, BMI z score, waist circumference, fat mass, trunk fat mass) were discovered, and (3) previously reported SNVs associated with childhood obesity were replicated.

CONCLUSIONS: Convergence of whole exome sequencing, a family-based design, and extensive phenotyping discovered novel rare and common variants associated with childhood obesity. Linking PEX1 to obesity phenotypes poses a novel mechanism of peroxisomal biogenesis and metabolism underlying the development of childhood obesity.

}, keywords = {Adolescent, ATPases Associated with Diverse Cellular Activities, Body Mass Index, Body Weight, Child, Child, Preschool, Cohort Studies, Exome, Genetic Loci, Genome-Wide Association Study, Hispanic or Latino, Humans, Membrane Proteins, Pediatric Obesity, Polymorphism, Single Nucleotide, Risk Factors, Sequence Analysis, DNA, Software, Waist Circumference, Young Adult}, issn = {1930-739X}, doi = {10.1002/oby.21869}, author = {Sabo, Aniko and Mishra, Pamela and Dugan-Perez, Shannon and Voruganti, V Saroja and Kent, Jack W and Kalra, Divya and Cole, Shelley A and Comuzzie, Anthony G and Muzny, Donna M and Gibbs, Richard A and Butte, Nancy F} } @article {23, title = {Genomic Patterns of De Novo Mutation in Simplex Autism.}, journal = {Cell}, volume = {171}, year = {2017}, month = {2017 Oct 19}, pages = {710-722.e12}, abstract = {

To further our understanding of the genetic etiology of autism, we generated and analyzed genome sequence data from 516 idiopathic autism families (2,064 individuals). This resource includes >59 million single-nucleotide variants (SNVs) and 9,212 private copy number variants (CNVs), of which 133,992 and 88 are de novo mutations (DNMs), respectively. We estimate a mutation rate of \~{}1.5~{\texttimes} 10 SNVs per site per generation with a significantly higher mutation rate in repetitive DNA. Comparing probands and unaffected siblings, we observe several DNM trends. Probands carry more gene-disruptive CNVs and SNVs, resulting in severe~missense mutations and mapping to predicted fetal brain promoters and embryonic stem cell enhancers. These differences become more pronounced for autism genes (p~= 1.8~{\texttimes} 10, OR~= 2.2). Patients are more likely to carry multiple coding and noncoding DNMs in different genes, which are enriched for expression in striatal neurons (p~= 3~{\texttimes} 10), suggesting a path forward for genetically characterizing more complex cases of autism.

}, keywords = {Animals, Autistic Disorder, DNA Copy Number Variations, DNA Mutational Analysis, Female, Genome-Wide Association Study, Humans, INDEL Mutation, Male, Mice, Polymorphism, Single Nucleotide}, issn = {1097-4172}, doi = {10.1016/j.cell.2017.08.047}, author = {Turner, Tychele N and Coe, Bradley P and Dickel, Diane E and Hoekzema, Kendra and Nelson, Bradley J and Zody, Michael C and Kronenberg, Zev N and Hormozdiari, Fereydoun and Raja, Archana and Pennacchio, Len A and Darnell, Robert B and Eichler, Evan E} } @article {16, title = {The impact of structural variation on human gene expression.}, journal = {Nat Genet}, volume = {49}, year = {2017}, month = {2017 May}, pages = {692-699}, abstract = {

Structural variants (SVs) are an important source of human genetic diversity, but their contribution to traits, disease and gene regulation remains unclear. We mapped cis expression quantitative trait loci (eQTLs) in 13 tissues via joint analysis of SVs, single-nucleotide variants (SNVs) and short insertion/deletion (indel) variants from deep whole-genome sequencing (WGS). We estimated that SVs are causal at 3.5-6.8\% of eQTLs-a substantially higher fraction than prior estimates-and that expression-altering SVs have larger effect sizes than do SNVs and indels. We identified 789 putative causal SVs predicted to directly alter gene expression: most (88.3\%) were noncoding variants enriched at enhancers and other regulatory elements, and 52 were linked to genome-wide association study loci. We observed a notable abundance of rare high-impact SVs associated with aberrant expression of nearby genes. These results suggest that comprehensive WGS-based SV analyses will increase the power of common- and rare-variant association studies.

}, keywords = {Algorithms, Chromosome Mapping, Gene Expression Regulation, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, INDEL Mutation, Linear Models, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sequence Analysis, DNA}, issn = {1546-1718}, doi = {10.1038/ng.3834}, author = {Chiang, Colby and Scott, Alexandra J and Davis, Joe R and Tsang, Emily K and Li, Xin and Kim, Yungil and Hadzic, Tarik and Damani, Farhan N and Ganel, Liron and Montgomery, Stephen B and Battle, Alexis and Conrad, Donald F and Hall, Ira M} } @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 {15, title = {Concerted Genetic Function in Blood Traits.}, journal = {Cell}, volume = {167}, year = {2016}, month = {2016 Nov 17}, pages = {1167-1169}, abstract = {

The hematopoietic system plays a major role in human health. Two studies by Astle et~al. and Chen~et~al. published in this issue of Cell use genome-wide association and functional genomics approaches to provide deep insights into the role of genetic variants in hematological traits. We~discuss these discoveries and future strategies toward completing our understanding of the genetic basis for variation in human traits.

}, keywords = {Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Phenotype, Polymorphism, Single Nucleotide}, issn = {1097-4172}, doi = {10.1016/j.cell.2016.10.055}, author = {Kim-Hellmuth, Sarah and Lappalainen, Tuuli} }