Electronic health records (EHR) provide a comprehensive resource for discovery, allowing unprecedented exploration of the impact of genetic architecture on health and disease. The data of EHRs also ...allow for exploration of the complex interactions between health measures across health and disease. The discoveries arising from EHR based research provide important information for the identification of genetic variation for clinical decision-making. Due to the breadth of information collected within the EHR, a challenge for discovery using EHR based data is the development of high-throughput tools that expose important areas of further research, from genetic variants to phenotypes. Phenome-Wide Association studies (PheWAS) provide a way to explore the association between genetic variants and comprehensive phenotypic measurements, generating new hypotheses and also exposing the complex relationships between genetic architecture and outcomes, including pleiotropy. EHR based PheWAS have mainly evaluated associations with case/control status from International Classification of Disease, Ninth Edition (ICD-9) codes. While these studies have highlighted discovery through PheWAS, the rich resource of clinical lab measures collected within the EHR can be better utilized for high-throughput PheWAS analyses and discovery. To better use these resources and enrich PheWAS association results we have developed a sound methodology for extracting a wide range of clinical lab measures from EHR data. We have extracted a first set of 21 clinical lab measures from the de-identified EHR of participants of the Geisinger MyCodeTM biorepository, and calculated the median of these lab measures for 12,039 subjects. Next we evaluated the association between these 21 clinical lab median values and 635,525 genetic variants, performing a genome-wide association study (GWAS) for each of 21 clinical lab measures. We then calculated the association between SNPs from these GWAS passing our Bonferroni defined p-value cutoff and 165 ICD-9 codes. Through the GWAS we found a series of results replicating known associations, and also some potentially novel associations with less studied clinical lab measures. We found the majority of the PheWAS ICD-9 diagnoses highly related to the clinical lab measures associated with same SNPs. Moving forward, we will be evaluating further phenotypes and expanding the methodology for successful extraction of clinical lab measurements for research and PheWAS use. These developments are important for expanding the PheWAS approach for improved EHR based discovery.
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.
Abstract
The Minimal Information about MHC Multimers (MIAMM, miamm.lji.org) is a recently established data standard to be applied to publications utilizing these reagents. Available at miamm.lji.org, ...we explain how to easily represent multimer reagents in a standardized format using ontology terminology. Additionally, we provide a free, publicly available Multimer Validation Tool. This tool helps users adopt this new data standard and was proven to be generally applicable to real life use cases by its validation of the data present in the NIH Tetramer Core Facility and the nearly 18,500 multimer assays in the Immune Epitope Database (IEDB). As the scientific public adopts MIAMM, the quality, reproducibility, and annotatability of MHC multimer reagent data in the scientific literature will be improved.
Funding: JDA, RAW, and DLL acknowledge support from the contract for the NIH Tetramer Facility (75N93020D00005) from the Yerkes National Primate Research Center (P51OD011132), and the Emory Center for AIDS Research (P30AI050409). RV, JAO, AM, and BP acknowledge support from National Institutes of Health grant R24 HG010032. RV, JAO, AM, BP, and AS acknowledge support from National Institutes of Health contract 75N93019C00001
Objective: To present a case of adult-onset familial diabetes mellitus in which a genetic etiology typical for neonatal diabetes was identified.Methods: We conducted whole-exome and Sanger ...sequencing, assessed clinical presentation and family history, and performed a literature review.Results: A 40-year-old, thin woman presented with a 10-year history of mildly elevated fasting glucose and A1C levels. Her mother had diabetes mellitus since her 40s and is on insulin, and her daughter presented with diabetes mellitus at age 21. The patient and her daughter underwent whole-exome sequencing and were found to have a mutation in the KCNJ11 gene, c.G685A, p.E229K. This mutation is known to be associated with neonatal presentation of diabetes mellitus, which neither of these family members had a history of. Given her known mutation and postprandial hyperglycemia, a trial of low-dose sulfonylurea was initiated in the daughter but failed due to hypoglycemia. She was found to have a CYP2C9 genotype associated with poor oral drug clearance.Conclusion:KCNJ11 mutation should be screened for in patients and families meeting criteria for maturity-onset diabetes of the young, even without evidence of neonatal onset in the family. Furthermore, even though sulfonylurea therapy is successful in the majority of patients with KCNJ11 mutations, there may be a role for other interacting environmental or genetic modifiers, such as CYP2C9 geno-type, that affect sulfonylurea metabolism. Those patients who have delayed onset of disease and milder courses may be less ideal candidates for this treatment.Abbreviations: BMI = body mass index;KATP = ATP-sensitive potassium channel;MODY = maturity-onset diabetes of the young;NDM = neonatal diabetes mellitus
Prediction of disease risk is a key component of precision medicine. Common traits such as psychiatric disorders have a complex polygenic architecture, making the identification of a single risk ...predictor difficult. Polygenic risk scores (PRSs) denoting the sum of an individual’s genetic liability for a disorder are a promising biomarker for psychiatric disorders, but they require evaluation in a clinical setting.
We developed PRSs for 6 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, and anorexia nervosa) and 17 nonpsychiatric traits in more than 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We performed phenome-wide association analyses to test their association across disease categories.
Four of the 6 psychiatric PRSs were associated with their primary phenotypes (odds ratios from 1.2 to 1.6). Cross-trait associations were identified both within the psychiatric domain and across trait domains. PRSs for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder.
We demonstrated that the genetic architecture of electronic health record–derived psychiatric diagnoses is similar to ascertained research cohorts from large consortia. Psychiatric PRSs are moderately associated with psychiatric diagnoses but are not yet clinically predictive in naïve patients. Cross-trait associations for these PRSs suggest a broader effect of genetic liability beyond traditional diagnostic boundaries. As identification of genetic markers increases, including PRSs alongside other clinical risk factors may enhance prediction of psychiatric disorders and associated conditions in clinical registries.
Enlargement of the aorta is an important risk factor for aortic aneurysm and dissection, a leading cause of morbidity in the developed world. Here we performed automated extraction of ascending ...aortic diameter from cardiac magnetic resonance images of 36,021 individuals from the UK Biobank, followed by genome-wide association. We identified lead variants across 41 loci, including genes related to cardiovascular development (HAND2, TBX20) and Mendelian forms of thoracic aortic disease (ELN, FBN1). A polygenic score significantly predicted prevalent risk of thoracic aortic aneurysm and the need for surgical intervention for patients with thoracic aneurysm across multiple ancestries within the UK Biobank, FinnGen, the Penn Medicine Biobank and the Million Veterans Program (MVP). Additionally, we highlight the primary causal role of blood pressure in reducing aortic dilation using Mendelian randomization. Overall, our findings provide a roadmap for using genetic determinants of human anatomy to understand cardiovascular development while improving prediction of diseases of the thoracic aorta.
Body fat distribution is a major, heritable risk factor for cardiometabolic disease, independent of overall adiposity. Using exome-sequencing in 618,375 individuals (including 160,058 non-Europeans) ...from the UK, Sweden and Mexico, we identify 16 genes associated with fat distribution at exome-wide significance. We show 6-fold larger effect for fat-distribution associated rare coding variants compared with fine-mapped common alleles, enrichment for genes expressed in adipose tissue and causal genes for partial lipodystrophies, and evidence of sex-dimorphism. We describe an association with favorable fat distribution (p = 1.8 × 10
), favorable metabolic profile and protection from type 2 diabetes (~28% lower odds; p = 0.004) for heterozygous protein-truncating mutations in INHBE, which encodes a circulating growth factor of the activin family, highly and specifically expressed in hepatocytes. Our results suggest that inhibin βE is a liver-expressed negative regulator of adipose storage whose blockade may be beneficial in fat distribution-associated metabolic disease.
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