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Background: Rare variants play an essential role in the etiology of cancer. In this study, we aim to characterize rare germline variants that impact the risk of cancer. Methods: We performed a genome-wide rare variant analysis using germline whole exome sequencing (WES) data derived from the Geisinger MyCode initiative to discover cancer predisposition variants. The case–control association analysis was conducted by binning variants in 5,538 patients with cancer and 7,286 matched controls in a discovery set and 1,991 patients with cancer and 2,504 matched controls in a validation set across nine cancer types. Further, The Cancer Genome Atlas (TCGA) germline data were used to replicate the findings. Results: We identified 133 significant pathway–cancer pairs (85 replicated) and 90 significant gene–cancer pairs (12 replicated). In addition, we identified 18 genes and 3 pathways that were associated with survival outcome across cancers (Bonferroni P < 0.05). Conclusions: In this study, we identified potential predisposition genes and pathways based on rare variants in nine cancers. Impact: This work adds to the knowledge base and progress being made in precision medicine.

Exome sequencing in hundreds of thousands of persons may enable the identification of rare protein-coding genetic variants associated with protection from human diseases like liver cirrhosis, providing a strategy for the discovery of new therapeutic targets.We performed a multistage exome sequencing and genetic association analysis to identify genes in which rare protein-coding variants were associated with liver phenotypes. We conducted in vitro experiments to further characterize associations.The multistage analysis involved 542,904 persons with available data on liver aminotransferase levels, 24,944 patients with various types of liver disease, and 490,636 controls without liver disease. We found that rare coding variants inRare germline mutations in

ImportanceVEXAS (vacuoles, E1-ubiquitin-activating enzyme, X-linked, autoinflammatory, somatic) syndrome is a disease with rheumatologic and hematologic features caused by somatic variants in UBA1. Pathogenic variants are associated with a broad spectrum of clinical manifestations. Knowledge of prevalence, penetrance, and clinical characteristics of this disease have been limited by ascertainment biases based on known phenotypes. This study used a genomic ascertainment approach to overcome these limitations and better define UBA1-related disease.ObjectiveDetermine the prevalence of pathogenic variants in UBA1 and associated clinical manifestations in an unselected population using a genomic ascertainment approach.Design, Setting and ParticipantsThis cohort study evaluated UBA1 variants in exome data from 163,096 participants within the Geisinger MyCode Community Health Initiative. Clinical phenotypes were determined from Geisinger electronic health record (EHR) data up to January 1st, 2022.Main outcomes and measuresPrevalence of somatic UBA1 variation; presence of rheumatologic, hematologic, pulmonary, dermatologic, and other symptoms in individuals with somatic UBA1 variation; structured and manual review of EHR; review of bone marrow biopsies; survival in carriers of somatic UBA1 variation.ResultsIn a retrospective study of 163,096 participants (mean age 52.8 years; 94% of European ancestry, 61% female), 11 individuals harbored somatic, known pathogenic UBA1 variants, with 100% having clinical manifestations consistent with VEXAS syndrome. We found a previously unreported UBA1 variant (c.1861A>T; p.Ser621Cys) in a symptomatic patient. Disease-causing UBA1 variants were found in ∼1 in 14,000 unrelated individuals, and ∼1 in 4,000 men >50 years old. A disease-causing UBA1 variant confers a ∼ 6.6 higher probability of mortality vs. age-, sex-, and BMI-matched non-carriers. The majority (7, 58%) of individuals did not meet criteria for rheumatologic and hematologic diagnoses previously associated with VEXAS syndrome, however all individuals had anemia (mean 7.8 g/dL, median 7.5g/dL), mostly macrocytic (91%) with concomitant thrombocytopenia (91%). Finally, we identified a pathogenic variant in one male prior to onset of VEXAS-related signs or symptoms and two females had disease with heterozygous variants.Conclusions and relevanceThis cohort study showed that the prevalence, penetrance, and expressivity of pathogenic UBA1 variants were higher than expected. More expansive UBA1 testing will lead to molecular diagnoses and improved treatment for patients.

Objective: To implement, disseminate and evaluate a sustainable method for identifying, diagnosing, and promoting individualized therapy for monogenic diabetes. Research Design and Methods: Patients were recruited into the implementation study through a screening questionnaire completed in the waiting room or through the patient portal, physician recognition, or self-referral. Patients suspected of monogenic diabetes based on the processing of their questionnaire and other data through an algorithm underwent next-generation sequencing for 40 genes implicated in monogenic diabetes and related conditions. Results: Three hundred thirteen probands with suspected monogenic diabetes (but most diagnosed with type 2 diabetes) were enrolled from October 2014 to January 2019. Sequencing identified 38 individuals with monogenic diabetes, with most variants found in GCK or HNF1A. Positivity rates for ascertainment methods were 3.1% in clinic screening, 5.3% in EHR portal screening, 16.5% for physician recognition, and 32.4% for self-referral. The algorithm criterion of non-type 1 diabetes before age 30 years had an overall positivity rate of 15.0%. Conclusions: We successfully modeled the efficient incorporation of monogenic diabetes diagnosis into the diabetes care setting, using multiple strategies to screen and identify a subpopulation with a 12.1% prevalence of monogenic diabetes by molecular testing. Self-referral was particularly efficient (32% prevalence), suggesting that educating the lay public in addition to clinicians may be the most effective way to increase the diagnosis rate of monogenic diabetes. Scaling up this model will assure access to diagnosis and customized treatment for monogenic diabetes and more broadly access to personalized medicine across disease areas.

The true prevalence and penetrance of monogenic disease variants are often not known because of clinical-referral ascertainment bias. We comprehensively assess the penetrance and prevalence of pathogenic variants in HNF1A, HNF4A, and GCK that account for80% of monogenic diabetes. We analyzed clinical and genetic data from 1,742 clinically referred probands, 2,194 family members, clinically unselected individuals from a US health system-based cohort (n = 132,194), and a UK population-based cohort (n = 198,748). We show that one in 1,500 individuals harbor a pathogenic variant in one of these genes. The penetrance of diabetes for HNF1A and HNF4A pathogenic variants was substantially lower in the clinically unselected individuals compared to clinically referred probands and was dependent on the setting (32% in the population, 49% in the health system cohort, 86% in a family member, and 98% in probands for HNF1A). The relative risk of diabetes was similar across the clinically unselected cohorts highlighting the role of environment/other genetic factors. Surprisingly, the penetrance of pathogenic GCK variants was similar across all cohorts (89%-97%). We highlight that pathogenic variants in HNF1A, HNF4A, and GCK are not ultra-rare in the population. For HNF1A and HNF4A, we need to tailor genetic interpretation and counseling based on the setting in which a pathogenic monogenic variant was identified. GCK is an exception with near-complete penetrance in all settings. This along with the clinical implication of diagnosis makes it an excellent candidate for the American College of Medical Genetics secondary gene list.

Patients with germline pathogenic variants (GPV) in cancer predisposition genes are at increased risk of pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer. The genes most frequently found to harbor GPV in unselected PDAC cases are ATM, BRCA1, BRCA2, CDKN2A, CHEK2, and PALB2. However, GPV prevalence and gene-specific associations have not been extensively studied in the general population. To further explore these associations, we analyzed genomic and phenotypic data obtained from the UK Biobank (UKB) and Geisinger MyCode Community Health Initiative (GHS) cohorts comprising 200,600 and 175,449 participants, respectively. We estimated the frequency and calculated relative risks (RRs) of heterozygotes in both cohorts and a subset of individuals with PDAC. The combined frequency of heterozygous carriers of GPV in the general population ranged from 1.22% for CHEK2 to 0.05% for CDKN2A. The frequency of GPV in PDAC cases varied from 2.38% (ATM) to 0.19% (BRCA1 and CDKN2A). The RRs of PDAC were elevated for all genes except for BRCA1 and varied widely by gene from high (ATM) to low (CHEK2, BRCA2). This work expands our understanding of the frequencies of GPV heterozygous carriers and associations between PDAC and GPV in several important PDAC susceptibility genes.

Opioid abuse during pregnancy can result in Neonatal Opioid Withdrawal Syndrome (NOWS). We investigated genome-wide methylation analyses of 96 placental tissue samples, including 32 prenatally opioid-exposed infants with NOWS who needed therapy (+Opioids/+NOWS), 32 prenatally opioid-exposed infants with NOWS who did not require treatment (+Opioids/-NOWS), and 32 prenatally unexposed controls (-Opioids/-NOWS, control). Statistics, bioinformatics , Artificial Intelligence (AI), including Deep Learning (DL), and Ingenuity Pathway Analyses (IPA) were performed. We identified 17 dysregulated pathways thought to be important in the pathophysiology of NOWS and reported accurate AI prediction of NOWS diagnoses. The DL had an AUC (95% CI) =0.98 (0.95–1.0) with a sensitivity and specificity of 100% for distinguishing NOWS from the +Opioids/-NOWS group and AUCs (95% CI) =1.00 (1.0–1.0) with a sensitivity and specificity of 100% for distinguishing NOWS versus control and + Opioids/-NOWS group versus controls. This study provides strong evidence of methylation dysregulation of placental tissue in NOWS development.

Monogenic causes in over 300 kidney-associated genes account for roughly 12% of end stage kidney disease (ESKD) cases. Advances in next generation sequencing, and large customized panels enable the diagnosis of monogenic kidney disease noninvasively at relatively low cost, allowing for more precise management for patients and their families. A major challenge is interpreting rare variants, many of which are classified as variants of unknown significance (VUS). We present a framework in which we thoroughly evaluated and provided evidence of pathogenicity for HNF1B-p.Arg303His, a VUS returned from clinical genetic testing for a kidney transplant candidate. This blueprint, designed by a multi-disciplinary team of clinicians, molecular biologists, and diagnostic geneticists, includes using a health system-based cohort with genetic and clinical information to perform deep phenotyping of VUS carriers, examination of existing genetic databases, as well as functional testing. With our approach, we demonstrate evidence for pathogenicity for HNF1B-p.Arg303His by showing similar burden of kidney manifestations in this variant to known HNF1B pathogenic variants, and greater burden compared to non-carriers. Determination of a molecular diagnosis for the example family allows for proper surveillance and management of HNF1B-related manifestations such as kidney disease, diabetes, and hypomagnesemia with important implications for safe living-related kidney donation. The candidate gene-variant pair also allows for clinical biomarker testing for aberrations of linked pathways. This working model may be applicable other diseases of genetic etiology.

Introduction Obesity accounts for a substantial and growing burden of disease globally. Body adiposity is highly heritable, and human genetic studies can lead to biological and therapeutic insights. Rationale Whole-exome sequencing of hundreds of thousands of individuals is complementary to approaches used to date in obesity genetics and has the potential to identify rare protein-coding variants with large phenotypic impact. We sequenced the exomes of 645,626 individuals from the UK, the US, and Mexico and estimated associations of rare coding variants with body mass index (BMI), a measure of overall adiposity used to define obesity in clinical practice. We complemented exome sequencing with fine-mapping of common alleles, polygenic score analysis, and in vitro and in vivo modeling work. Results We identified 16 genes for which the burden of rare nonsynonymous variants was associated with BMI at exome-wide statistical significance (inverse-variance weighted meta-analysis P < 3.6 × 10−7), including associations at five brain-expressed G protein–coupled receptors (CALCR, MC4R, GIPR, GPR151, and GPR75). We observed an overrepresentation of genes highly expressed in the hypothalamus, a key center for the neuroendocrine regulation of energy balance. Protein-truncating variants in GPR75 were found in ~4/10,000 sequenced people and were associated with 1.8 kg/m2 lower BMI, 5.3 kg lower bodyweight, and 54% lower odds of obesity in heterozygous carriers. Knock out of Gpr75 in mice resulted in resistance to weight gain in a high-fat diet model, which was allele-dose dependent (25% and 44% lower weight gain, respectively, for heterozygous Gpr75−/+ mice and knockout Gpr75−/− mice compared with wild type) and accompanied by improved glycemic control and insulin sensitivity. Protein-truncating variants in CALCR were associated with higher BMI and obesity risk, whereas protein-truncating variants in GIPR and two missense alleles [Arg190→Gln (Arg190Gln), Glu288Gly], which we show result in loss of function in vitro, were associated with lower adiposity. Among monogenic obesity genes in the leptin-melanocortin pathway, heterozygous predicted loss-of-function variants in LEP, POMC, PCSK1, and MC4R (but not LEPR) were associated with higher BMI. Rare protein-truncating variants in UBR2, ANO4, and PCSK1 were associated with more than twofold higher odds of obesity in heterozygous carriers, similar to predicted-deleterious nonsynonymous variants in MC4R, which are considered the most common cause of monogenic obesity. Polygenic predisposition due to >2 million common genetic variants influenced the penetrance of obesity in rare variant carriers in an additive fashion. Conclusion These results suggest that inhibition of GPR75 may be a therapeutic strategy for obesity and illustrate the power of massive-scale exome sequencing for the identification of large-effect coding variant associations and drug targets for complex traits.

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community., Exome sequences from the first 49,960 participants in the UK Biobank highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

Background/Objectives Melanocortin-4 receptor (MC4R) plays an essential role in food intake and energy homeostasis. More than 170 MC4R variants have been described over the past two decades, with conflicting reports regarding the prevalence and phenotypic effects of these variants in diverse cohorts. To determine the frequency of MC4R variants in large cohort of different ancestries, we evaluated the MC4R coding region for 20,537 eMERGE participants with sequencing data plus additional 77,454 independent individuals with genome-wide genotyping data at this locus. Subjects/Methods The sequencing data were obtained from the eMERGE phase III study, in which multisample variant call format calls have been generated, curated, and annotated. In addition to penetrance estimation using body mass index (BMI) as a binary outcome, GWAS and PheWAS were performed using median BMI in linear regression analyses. All results were adjusted for principal components, age, sex, and sites of genotyping. Results Targeted sequencing data of MC4R revealed 125 coding variants in 1839 eMERGE participants including 30 unreported coding variants that were predicted to be functionally damaging. Highly penetrant unreported variants included (L325I, E308K, D298N, S270F, F261L, T248A, D111V, and Y80F) in which seven participants had obesity class III defined as BMI ≥ 40 kg/m2. In GWAS analysis, in addition to known risk haplotype upstream of MC4R (best variant rs6567160 (P = 5.36 × 10−25, Beta = 0.37), a novel rare haplotype was detected which was protective against obesity and encompassed the V103I variant with known gain-of-function properties (P = 6.23 × 10−08, Beta = −0.62). PheWAS analyses extended this protective effect of V103I to type 2 diabetes, diabetic nephropathy, and chronic renal failure independent of BMI. Conclusions MC4R screening in a large eMERGE cohort confirmed many previous findings, extend the MC4R pleotropic effects, and discovered additional MC4R rare alleles that probably contribute to obesity.

Monogenic causes in over 300 kidney-associated genes account for approximately 12% of end stage kidney disease (ESKD) cases. Advances in sequencing and large customized panels enable the noninvasive diagnosis of monogenic kidney disease at relatively low cost, thereby allowing for more precise management for patients and their families. A major challenge is interpreting rare variants, many of which are classified as variants of unknown significance (VUS). We present a framework in which we thoroughly evaluated and provided evidence of pathogenicity forA blueprint was designed by a multidisciplinary team of clinicians, molecular biologists, and diagnostic geneticists. The blueprint included using a health system-based cohort with genetic and clinical information to perform deep phenotyping of VUS heterozygotes to identify the candidate VUS and rule out other VUS, examination of existing genetic databases, as well as functional testing.Our approach demonstrated evidence for pathogenicity forDetermination of a molecular diagnosis for the example family allows for proper surveillance and management of

ImportanceVEXAS (vacuoles, E1-ubiquitin-activating enzyme, X-linked, autoinflammatory, somatic) syndrome is a disease with rheumatologic and hematologic features caused by somatic variants in UBA1. Pathogenic variants are associated with a broad spectrum of clinical manifestations. Knowledge of prevalence, penetrance, and clinical characteristics of this disease have been limited by ascertainment biases based on known phenotypes.ObjectiveTo determine the prevalence of pathogenic variants in UBA1 and associated clinical manifestations in an unselected population using a genomic ascertainment approach.Design, Setting, and ParticipantsThis retrospective observational study evaluated UBA1 variants in exome data from 163 096 participants within the Geisinger MyCode Community Health Initiative. Clinical phenotypes were determined from Geisinger electronic health record data from January 1, 1996, to January 1, 2022.ExposuresExome sequencing was performed.Main Outcomes and MeasuresOutcome measures included prevalence of somatic UBA1 variation; presence of rheumatologic, hematologic, pulmonary, dermatologic, and other findings in individuals with somatic UBA1 variation on review of the electronic health record; review of laboratory data; bone marrow biopsy pathology analysis; and in vitro enzymatic assays.ResultsIn 163 096 participants (mean age, 52.8 years; 94% White; 61% women), 11 individuals harbored likely somatic variants at known pathogenic UBA1 positions, with 11 of 11 (100%) having clinical manifestations consistent with VEXAS syndrome (9 male, 2 female). A total of 5 of 11 individuals (45%) did not meet criteria for rheumatologic and/or hematologic diagnoses previously associated with VEXAS syndrome; however, all individuals had anemia (hemoglobin: mean, 7.8 g/dL; median, 7.5 g/dL), which was mostly macrocytic (10/11 [91%]) with concomitant thrombocytopenia (10/11 [91%]). Among the 11 patients identified, there was a pathogenic variant in 1 male participant prior to onset of VEXAS-related signs or symptoms and 2 female participants had disease with heterozygous variants. A previously unreported UBA1 variant (c.1861A>T; p.Ser621Cys) was found in a symptomatic patient, with in vitro data supporting a catalytic defect and pathogenicity. Together, disease-causing UBA1 variants were found in 1 in 13 591 unrelated individuals (95% CI, 1:7775-1:23 758), 1 in 4269 men older than 50 years (95% CI, 1:2319-1:7859), and 1 in 26 238 women older than 50 years (95% CI, 1:7196-1:147 669).Conclusions and RelevanceThis study provides an estimate of the prevalence and a description of the clinical manifestations of UBA1 variants associated with VEXAS syndrome within a single regional health system in the US. Additional studies are needed in unselected and genetically diverse populations to better define general population prevalence and phenotypic spectrum.

ImportanceMost studies of autosomal dominant polycystic kidney disease (ADPKD) genetics have used kidney specialty cohorts, focusing on PKD1 and PKD2. These can lead to biased estimates of population prevalence of ADPKD-associated gene variants and their phenotypic expression.ObjectiveTo determine the prevalence of ADPKD and contributions of PKD1, PKD2, and other genes related to cystic kidney disease in a large, unselected cohort.Design, Setting, and ParticipantsThis retrospective observational study used an unselected health system–based cohort in central and northeast Pennsylvania with exome sequencing (enrolled from 2004 to 2020) and electronic health record data (up to October 2021). The genotype-first approach included the entire cohort and the phenotype-first approach focused on patients with ADPKD diagnosis codes, confirmed by chart and imaging review.ExposuresLoss-of-function (LOF) variants in PKD1, PKD2, and other genes associated with cystic kidney disease (ie, ALG8, ALG9, DNAJB11, GANAB, HNF1B, IFT140, SEC61B, PKHD1, PRKCSH, SEC63); likely pathogenic missense variants in PKD1 and PKD2.Main Outcomes and MeasuresGenotype-first analysis: ADPKD diagnosis code (Q61.2, Q61.3, 753.13, 753.12); phenotype-first analysis: presence of a rare variant in PKD1, PKD2, or other genes associated with cystic kidney disease.ResultsOf 174 172 patients (median age, 60 years; 60.6% female; 93% of European ancestry), 303 patients had ADPKD diagnosis codes, including 235 with sufficient chart review data for confirmation. In addition to PKD1 and PKD2, LOF variants in IFT140, GANAB, and HNF1B were associated with ADPKD diagnosis after correction for multiple comparisons. Among patients with LOF variants in PKD1, 66 of 68 (97%) had ADPKD; 43 of 43 patients (100%) with LOF variants in PKD2 had ADPKD. In contrast, only 24 of 77 patients (31.2%) with a PKD1 missense variant previously classified as “likely pathogenic” had ADPKD, suggesting misclassification or variable penetrance. Among patients with ADPKD diagnosis confirmed by chart review, 180 of 235 (76.6%) had a potential genetic cause, with the majority being rare variants in PKD1 (127 patients) or PKD2 (34 patients); 19 of 235 (8.1%) had variants in other genes associated with cystic kidney disease. Of these 235 patients with confirmed ADPKD, 150 (63.8%) had a family history of ADPKD. The yield for a genetic determinant of ADPKD was higher for those with a family history of ADPKD compared with those without family history (91.3% [137/150] vs 50.6% [43/85]; difference, 40.7% [95% CI, 29.2%-52.3%]; P PKD1, PKD2, and GANAB variants were identified with pedigree data suggesting pathogenicity, and several PKD1 missense variants previously reported as likely pathogenic appeared to be benign.Conclusions and RelevanceThis study demonstrates substantial genetic and phenotypic variability in ADPKD among patients within a regional health system in the US.

OBJECTIVE To implement, disseminate, and evaluate a sustainable method for identifying, diagnosing, and promoting individualized therapy for monogenic diabetes. RESEARCH DESIGN AND METHODS Patients were recruited into the implementation study through a screening questionnaire completed in the waiting room or through the patient portal, physician recognition, or self-referral. Patients suspected of having monogenic diabetes based on the processing of their questionnaire and other data through an algorithm underwent next-generation sequencing for 40 genes implicated in monogenic diabetes and related conditions. RESULTS Three hundred thirteen probands with suspected monogenic diabetes (but most diagnosed with type 2 diabetes) were enrolled from October 2014 to January 2019. Sequencing identified 38 individuals with monogenic diabetes, with most variants found in GCK or HNF1A. Positivity rates for ascertainment methods were 3.1% for clinic screening, 5.3% for electronic health record portal screening, 16.5% for physician recognition, and 32.4% for self-referral. The algorithmic criterion of non–type 1 diabetes before age 30 years had an overall positivity rate of 15.0%. CONCLUSIONS We successfully modeled the efficient incorporation of monogenic diabetes diagnosis into the diabetes care setting, using multiple strategies to screen and identify a subpopulation with a 12.1% prevalence of monogenic diabetes by molecular testing. Self-referral was particularly efficient (32% prevalence), suggesting that educating the lay public in addition to clinicians may be the most effective way to increase the diagnosis rate in monogenic diabetes. Scaling up this model will assure access to diagnosis and customized treatment among those with monogenic diabetes and, more broadly, access to personalized medicine across disease areas.

Aims The HERMES (HEart failure Molecular Epidemiology for Therapeutic targets) consortium aims to identify the genomic and molecular basis of heart failure.Methods and results The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of >1.10 for common variants (allele frequency > 0.05) and >1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 x 10(-8) under an additive genetic model.Conclusions HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

BACKGROUNDAccurate penetrance of monogenic disorders is often unknown due to a phenotype-first approach to genetic testing. Here, we use a genotype-first approach in four large cohorts with different ascertainment contexts to accurately estimate penetrance of the three commonest causes of monogenic diabetes, Maturity Onset Diabetes of the Young (MODY). We contrast HNF1A-MODY / HNF4A-MODY which causes an age-related progressive diabetes and GCK-MODY, which causes life-long mild hyperglycaemia.METHODSWe analysed clinical and genetic sequencing data from four different cohorts: 1742 probands referred for clinical MODY testing; 2194 family members of the MODY probands; 132,194 individuals from an American hospital-based cohort; and 198,748 individuals from a UK population-based cohort.RESULTSAge-related penetrance of diabetes for pathogenic variants in HNF1A and HNF4A was substantially lower in the clinically unselected cohorts compared to clinically referred probands (ranging from 32% to 98% at age 40yrs for HNF1A, and 21% to 99% for HNF4A). The background rate of diabetes, but not clinical features or variant type, explained the reduced penetrance in the unselected cohorts. In contrast, penetrance of mild hyperglycaemia for pathogenic GCK variants was similarly high across cohorts (ranging from 89 to 97%) despite substantial variation in the background rates of diabetes.CONCLUSIONSAscertainment context is crucial when interpreting the consequences of monogenic variants for age-related variably penetrant disorders. This finding has important implications for opportunistic screening during genomic testing.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

Background Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver illness with a genetically heterogeneous background that can be accompanied by considerable morbidity and attendant health care costs. The pathogenesis and progression of NAFLD is complex with many unanswered questions. We conducted genome-wide association studies (GWASs) using both adult and pediatric participants from the Electronic Medical Records and Genomics (eMERGE) Network to identify novel genetic contributors to this condition. Methods First, a natural language processing (NLP) algorithm was developed, tested, and deployed at each site to identify 1106 NAFLD cases and 8571 controls and histological data from liver tissue in 235 available participants. These include 1242 pediatric participants (396 cases, 846 controls). The algorithm included billing codes, text queries, laboratory values, and medication records. Next, GWASs were performed on NAFLD cases and controls and case-only analyses using histologic scores and liver function tests adjusting for age, sex, site, ancestry, PC, and body mass index (BMI). Results Consistent with previous results, a robust association was detected for the PNPLA3 gene cluster in participants with European ancestry. At the PNPLA3-SAMM50 region, three SNPs, rs738409, rs738408, and rs3747207, showed strongest association (best SNP rs738409 p = 1.70 × 10− 20). This effect was consistent in both pediatric (p = 9.92 × 10− 6) and adult (p = 9.73 × 10− 15) cohorts. Additionally, this variant was also associated with disease severity and NAFLD Activity Score (NAS) (p = 3.94 × 10− 8, beta = 0.85). PheWAS analysis link this locus to a spectrum of liver diseases beyond NAFLD with a novel negative correlation with gout (p = 1.09 × 10− 4). We also identified novel loci for NAFLD disease severity, including one novel locus for NAS score near IL17RA (rs5748926, p = 3.80 × 10− 8), and another near ZFP90-CDH1 for fibrosis (rs698718, p = 2.74 × 10− 11). Post-GWAS and gene-based analyses identified more than 300 genes that were used for functional and pathway enrichment analyses. Conclusions In summary, this study demonstrates clear confirmation of a previously described NAFLD risk locus and several novel associations. Further collaborative studies including an ethnically diverse population with well-characterized liver histologic features of NAFLD are needed to further validate the novel findings. Electronic supplementary material The online version of this article (10.1186/s12916-019-1364-z) contains supplementary material, which is available to authorized users.

Phenome-wide association studies (PheWASs) have been a useful tool for testing associations between genetic variations and multiple complex traits or diagnoses. Linking PheWAS-based associations between phenotypes and a variant or a genomic region into a network provides a new way to investigate cross-phenotype associations, and it might broaden the understanding of genetic architecture that exists between diagnoses, genes, and pleiotropy. We created a network of associations from one of the largest PheWASs on electronic health record (EHR)-derived phenotypes across 38,682 unrelated samples from the Geisinger's biobank; the samples were genotyped through the DiscovEHR project. We computed associations between 632,574 common variants and 541 diagnosis codes. Using these associations, we constructed a "disease-disease" network (DDN) wherein pairs of diseases were connected on the basis of shared associations with a given genetic variant. The DDN provides a landscape of intra-connections within the same disease classes, as well as inter-connections across disease classes. We identified clusters of diseases with known biological connections, such as autoimmune disorders (type 1 diabetes, rheumatoid arthritis, and multiple sclerosis) and cardiovascular disorders. Previously unreported relationships between multiple diseases were identified on the basis of genetic associations as well. The network approach applied in this study can be used to uncover interactions between diseases as a result of their shared, potentially pleiotropic SNPs. Additionally, this approach might advance clinical research and even clinical practice by accelerating our understanding of disease mechanisms on the basis of similar underlying genetic associations.

Objective: To determine whether Polygenic Risk Scores (PRS) derived from MEGASTROKE is associated with ischemic stroke (IS) and its subtypes in an independent tertiary healthcare system and to identify PRS derived from gene-sets of known biological pathways associated with IS and its outcomes (mortality and recurrent stroke). Methods: Controls(n=19806/7484, age≥69/79) and cases(n=1184/951 for discovery/replication) of acute IS with European ancestry and clinical risk factors identified by leveraging the Geisinger Electronic Health Record (EHR) and chart review confirmation. All Geisinger MyCode patients with age ≥69/79, without any stroke-related diagnostic codes as low-risk control. Genetic heritability and genetic correlation between Geisinger and MEGASTROKE(EUR) using the summary statistics of GWAS by LDSC. All PRS for any stroke — AS, any ischemic stroke — AIS, large artery stroke — LAS, cardioembolic stroke — CES, and small vessel stroke — SVS constructed by PRSice-2. PRS (top or bottom quantiles) derived from 7350 gene-sets of GO Biological Process was used to stratify the IS. Results: A moderate heritability (10-20%) for Geisinger sample as well as the genetic correlation between MEGASTROKE and the Geisinger cohort was identified. Gene sets analyses highlighted the association of PRS with Gene Ontology terms (vascular endothelial growth factor, amyloid precursor protein, and atherosclerosis). The PRS LAS , PRS CES , and PRS SVS explained the most variance of the corresponding subtypes of Geisinger IS suggesting shared etiologies and corroborated Geisinger TOAST subtyping. We further evaluate PRS derived from the gene-sets of which GO terms may best differentiate the survival in IS cases with the corresponding high or low genetic burden. The result from the Cox regression analysis showed simultaneously the effect of several risk factors including PRS on mortality and recurrent stroke probabilities. Conclusions: We provide the first evidence that PRSs derived from MEGASTROKE have value in identifying shared etiologies and determining stroke subtypes.

SARS-CoV-2 enters host cells by binding angiotensin-converting enzyme 2 (ACE2). Through a genome-wide association study, we show that a rare variant (MAF = 0.3%, odds ratio 0.60, P=4.5x10-13) that down-regulates ACE2 expression reduces risk of COVID-19 disease, providing human genetics support for the hypothesis that ACE2 levels influence COVID-19 risk. Further, we show that common genetic variants define a risk score that predicts severe disease among COVID-19 cases.

The present study sought to determine whether protein-truncating variants (PTVs) in PIEZO1 and CASZ1 genes, previously shown to be associated with varicose veins, were associated with an altered risk of varicose veins.An exome sequence database of 131,918 participants from the Geisinger MyCode Community Health Initiative was used to identify individuals with genetic variants in the PIEZO1 or CASZ1 gene. Clinical phenotypes, including varicose vein diagnoses, were determined by analysis of the electronic health record data.We identified 12,531 individuals (9.5%) with a diagnosis of varicose veins. Exome sequence data identified 92 PIEZO1 PTVs in 305 heterozygous carriers. PIEZO1 PTVs were significantly enriched in those with varicose vein (0.37% of cases vs 0.22% of controls; odds ratio [OR], 1.7; P = .0010). Nearly all varicose vein cases were associated with frameshift or stop-gain PTVs (OR, 3.0 for stop-gain [P = .0001]; OR, 2.9 for frameshift variants [P .0001]). In the varicose vein cases, the PTV carriers were more likely to have an encounter with a vascular surgeon (62.5% for PTV carriers; 36.9% for noncarriers; P = .0003) and more likely to have received vein ablation therapy (OR, 6.9; P .0001). No association was found between PIEZO1 PTVs and lymphedema, and no association was found for rare missense variants in PIEZO1 with varicose veins. PTVs in CASZ1 were extremely rare (16 total carriers), with none identified in those with varicose vein.Rare PTVs in PIEZO1 but not CASZ1 were associated with varicose veins and the need for vein ablation therapy. These results have demonstrated that PTVs in the PIEZO1 gene are rare but represent strong genetic risk factors for varicose veins and the need for vein ablation therapy. These results have also identified a potential biologic mechanism and target for the development of novel therapies.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable athttps://rgc-covid19.regeneron.com.

SUMMARYAging is characterized by degeneration in cellular and organismal functions leading to increased disease susceptibility and death. Although our understanding of aging biology in model systems has increased dramatically, large-scale sequencing studies to understand human aging are now just beginning. We applied exome sequencing and association analyses (ExWAS) to identify age-related variants on 58,470 participants of the DiscovEHR cohort. Linear Mixed Model regression analyses of age at last encounter revealed variants in genes known to be linked with clonal hematopoiesis of indeterminate potential, which are associated with myelodysplastic syndromes, as top signals in our analysis, suggestive of age-related somatic mutation accumulation in hematopoietic cells despite patients lacking clinical diagnoses. In addition to APOE, we identified rare DISP2 rs183775254 (p = 7.40×10−10) and ZYG11A rs74227999 (p = 2.50×10−08) variants that were negatively associated with age in either both sexes combined and females, respectively, which were replicated with directional consistency in two independent cohorts. Epigenetic mapping showed these variants are located within cell-type-specific enhancers, suggestive of important transcriptional regulatory functions. To discover variants associated with extreme age, we performed exome-sequencing on persons of Ashkenazi Jewish descent ascertained for extensive lifespans. Case-Control analyses in 525 Ashkenazi Jews cases (Males ≥ 92 years, Females ≥ 95years) were compared to 482 controls. Our results showed variants in APOE (rs429358, rs6857), and TMTC2 (rs7976168) passed Bonferroni-adjusted p-value, as well as several nominally-associated population-specific variants. Collectively, our Age-ExWAS, the largest performed to date, confirmed and identified previously unreported candidate variants associated with human age.

Investigation of genetic susceptibility to cerebrovascular disease has been of growing interest. A systematic review of human studies assessing neurogenomic aspects of cerebrovascular disease was performed according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. Any association study exploring genetic variants located in the exome associated with one of the major cerebrovascular diseases with at least 500 subjects was eligible for inclusion. Of 6874 manuscripts identified, 35 studies met the inclusion criteria. Most studies of interest focused on ischemic stroke and cerebrovascular occlusive disease. Large cohort genetic association studies on hemorrhagic cerebrovascular disease were less common. In addition to rare, well-established monogenic conditions with significant risk for cerebrovascular disease, a number of genetic variants are also relevant to cerebrovascular pathogenesis as part of a multifactorial process. The 45 polymorphisms identified were located in genes involved in processes related to endothelial and vascular health (15 (33.4%) variants), plasma lipid metabolism (10 (22.2%) variants), inflammation (9 (20%) variants), coagulation (3 (6.7%) variants), and blood pressure modulation (2 (4.4%) variants), and other (6 (13.3%) variants). This work represents a comprehensive overview of genetic variants in the exome relevant to ischemic and hemorrhagic stroke pathophysiology.

Rare variants play an essential role in the etiology of cancer and characterizing rare germline variants that impact the risk of cancer is an ongoing challenge. We performed a genome-wide rare variant analysis using germline whole exome sequencing (WES) data derived from the Geisinger MyCode initiative to discover cancer predisposition variants. The analysis was conducted using 5,538 cancer patients and 7,286 matched controls in a discovery set and 1,991 cancer patients and 2,504 matched controls in a validation set across nine cancer types. The variants in the WES data were annotated and filtered for pathogenic and likely pathogenic variants using ClinVar and Variant Effect Predictor (VEP). After filtering, case-control association tests were conducted on each cancer type separately by binning the pathogenic and likely pathogenic rare variants into genes and pathways using SKAT-O. We discovered 87 genes and 106 pathways significantly associated with cancer (Bonferroni-corrected P < 0.05) out of which seven genes and 26 pathways replicated from the validation set (suggestive threshold P < 0.05). Further, four genes and 21 pathways were discovered to be associated with multiple cancers (Bonferroni-corrected P < 0.05). Additionally, we identified 13 genes and two pathways associated with survival outcome across seven cancers (Bonferroni-corrected P < 0.05), where two genes, PCDHB8 and DCHS2, were also associated with survival outcome in TCGA data. In summary, we conducted one of the largest pan-cancer association studies using germline data derived from a single hospital system to find novel predisposition genes and pathways associated with nine cancers. Our results can inform future guidelines for germline genetic testing in cancer, which will be helpful in screening for cancer high-risk patients. This work adds to the knowledge base and progress being made in precision medicine.

Angiopoietin-like 4 (ANGPTL4) is an endogenous inhibitor of lipoprotein lipase that modulates lipid levels, coronary atherosclerosis risk, and nutrient partitioning. We hypothesize that loss of ANGPTL4 function might improve glucose homeostasis and decrease risk of type 2 diabetes (T2D). We investigate protein-altering variants in ANGPTL4 among 58,124 participants in the DiscovEHR human genetics study, with follow-up studies in 82,766 T2D cases and 498,761 controls. Carriers of p.E40K, a variant that abolishes ANGPTL4 ability to inhibit lipoprotein lipase, have lower odds of T2D (odds ratio 0.89, 95% confidence interval 0.85–0.92, p = 6.3 × 10−10), lower fasting glucose, and greater insulin sensitivity. Predicted loss-of-function variants are associated with lower odds of T2D among 32,015 cases and 84,006 controls (odds ratio 0.71, 95% confidence interval 0.49–0.99, p = 0.041). Functional studies in Angptl4-deficient mice confirm improved insulin sensitivity and glucose homeostasis. In conclusion, genetic inactivation of ANGPTL4 is associated with improved glucose homeostasis and reduced risk of T2D., Genetic variation in ANGPTL4 is associated with lipid traits. Here, the authors find that predicted loss-of-function variants in ANGPTL4 are associated with glucose homeostasis and reduced risk of type 2 diabetes and that Angptl4−/− mice on a high-fat diet show improved insulin sensitivity.

Purpose The clinical utility of screening unselected individuals for pathogenic BRCA1/2 variants has not been established. Data on cancer risk management behaviors and diagnoses of BRCA1/2-associated cancers can help inform assessments of clinical utility. Methods Whole-exome sequences of participants in the MyCode Community Health Initiative were reviewed for pathogenic/likely pathogenic BRCA1/2 variants. Clinically confirmed variants were disclosed to patient–participants and their clinicians. We queried patient–participants’ electronic health records for BRCA1/2-associated cancer diagnoses and risk management that occurred within 12 months after results disclosure, and calculated the percentage of patient–participants of eligible age who had begun risk management. Results Thirty-seven MyCode patient–participants were unaware of their pathogenic/likely pathogenic BRCA1/2 variant, had not had a BRCA1/2-associated cancer, and had 12 months of follow-up. Of the 33 who were of an age to begin BRCA1/2-associated risk management, 26 (79%) had performed at least one such procedure. Three were diagnosed with an early-stage, BRCA1/2-associated cancer—including a stage 1C fallopian tube cancer—via these procedures. Conclusion Screening for pathogenic BRCA1/2 variants among unselected individuals can lead to occult cancer detection shortly after disclosure. Comprehensive outcomes data generated within our learning healthcare system will aid in determining whether population-wide BRCA1/2 genomic screening programs offer clinical utility.

Large-scale human genetics studies are ascertaining increasing proportions of populations as they continue growing in both number and scale. As a result, the amount of cryptic relatedness within these study cohorts is growing rapidly and has significant implications on downstream analyses. We demonstrate this growth empirically among the first 92,455 exomes from the DiscovEHR cohort and, via a custom simulation framework we developed called SimProgeny, show that these measures are in-line with expectations given the underlying population and ascertainment approach. For example, we identified ∼66,000 close (first- and second-degree) relationships within DiscovEHR involving 55.6% of study participants. Our simulation results project that >70% of the cohort will be involved in these close relationships as DiscovEHR scales to 250,000 recruited individuals. We reconstructed 12,574 pedigrees using these relationships (including 2,192 nuclear families) and leveraged them for multiple applications. The pedigrees substantially improved the phasing accuracy of 20,947 rare, deleterious compound heterozygous mutations. Reconstructed nuclear families were critical for identifying 3,415 de novo mutations in ∼1,783 genes. Finally, we demonstrate the segregation of known and suspected disease-causing mutations through reconstructed pedigrees, including a tandem duplication in LDLR causing familial hypercholesterolemia. In summary, this work highlights the prevalence of cryptic relatedness expected among large healthcare population genomic studies and demonstrates several analyses that are uniquely enabled by large amounts of cryptic relatedness.