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Carey, D. J.

Publications and source records attributed to Carey, D. J..

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Rare GPR37L1 variants reveal potential roles in anxiety and migraine disorders

GPR37L1 is an orphan receptor that couples through heterotrimeric G-proteins to regulate physiological functions. Since its role in humans is not fully defined, we used an unbiased computational approach to assess the clinical significance of rare GPR37L1 genetic variants found among 51,289 whole exome sequences from the DiscovEHR cohort. Briefly, rare GPR37L1 coding variants were binned according to predicted pathogenicity, and analyzed by Sequence Kernel Association testing to reveal significant associations with disease diagnostic codes for epilepsy and migraine, among others. Since associations do not prove causality, rare GPR37L1 variants were then functionally analyzed in SK-N-MC cells to evaluate potential signaling differences and pathogenicity. Notably, receptor variants exhibited varying abilities to reduce cAMP levels, activate MAPK signaling, and/or upregulate receptor expression in response to the agonist prosaptide (TX14(A)), as compared to the wild-type receptor. In addition to signaling changes, knockout of GPR37L1 or expression of certain rare variants altered cellular cholesterol levels, which were also acutely regulated by administration of the agonist TX14(A) via activation of the MAPK pathway. Finally, to simulate the impact of rare nonsense variants found in the large patient cohort, a knockout (KO) mouse line lacking Gpr37L1 was generated, revealing loss of this receptor produced sex-specific changes implicated in migraine-related disorders. Collectively, these observations define the existence of rare GPR37L1 variants in the human population that are associated with neuropsychiatric conditions and identify the underlying signaling changes that are implicated in the in vivo actions of this receptor in pathological processes leading to anxiety and migraine. SIGNIFICANCE STATEMENTG-protein coupled receptors (GPCRs) represent a diverse group of membrane receptors that contribute to a wide range of diseases and serve as effective drug targets. However, a number of these receptors have no identified ligands or functions, i.e., orphan receptors. Over the past decade, advances have been made, but there is a need for identifying new strategies to reveal their roles in health and disease. Our results highlight the utility of rare variant analyses of orphan receptors for identifying human disease associations, coupled with functional analyses in relevant cellular and animal systems, to ultimately reveal their roles as novel drug targets for treatment of neurological disorders that lack wide-spread efficacy.

neuroscience↗

Exome-wide association studies in general and long-lived populations identify genetic variants related to human age

Aging 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 = 7.40x10-10) and ZYG11A rs74227999 (p = 2.50x10-08) 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.

genetics↗

Genome-wide association study provides new insights into the genetic architecture and pathogenesis of heart failure

Heart failure (HF) is a leading cause of morbidity and mortality worldwide1. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained2-4. We report the largest GWAS meta-analysis of HF to-date, comprising 47,309 cases and 930,014 controls. We identify 12 independent variant associations with HF at 11 genomic loci, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function suggesting shared genetic aetiology. Expression quantitative trait analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homeostasis (BAG3), and cellular senescence (CDKN1A). Using Mendelian randomisation analysis we provide new evidence supporting previously equivocal causal roles for several HF risk factors identified in observational studies, and demonstrate CAD-independent effects for atrial fibrillation, body mass index, hypertension and triglycerides. These findings extend our knowledge of the genes and pathways underlying HF and may inform the development of new therapeutic approaches.

genetics↗

Calcium Sensing Receptor Common Variants Influence the Effects of Serum Calcium on Coronary Artery Disease Risks

RationaleThe calcium-sensing receptor (CaSR) regulates serum calcium concentrations and common single nucleotide polymorphisms (SNPs) in a carboxyl terminal tri-locus haplotype block contribute to serum calcium variance in the general population. Altered serum calcium concentrations are associated with coronary artery disease (CAD), but direct role for CaSR in CAD remains to be determined.\n\nMethodsWe evaluated the associations of serum calcium and common CASR SNPs or the tri-locus haplotype block with major diseases including CAD in 51,289 patients from the DiscovEHR cohort derived from a single US health care system.\n\nResultsSerum calcium concentrations were positively associated with the risk of CAD, and this risk was modified by common CASR SNPs. The Ala986Ser SNP was positively associated with hypercalcemia. Carriers of Ala986Ser had a significantly increased CAD risk whereas Arg990Gly carriers had a reduced risk relative to the reference SNP, for those with albumin-corrected serum calcium from 8.5-9.5 mg/dL. In the context of the tri-locus haplotype, the reduced CAD risk conferred by Arg990Gly remained significant. Analysis of the association of common CASR SNPs with CAD risk factors showed Arg990Gly was negatively associated with the CAD risk factor of chronic kidney disease, but independent of alterations in lipids, hemoglobin A1c, or blood pressure.\n\nConclusionsThis study compares the common approach of single SNP analysis with the impact of a common variant haplotype block and refocuses attention on the CaSR Arg990Gly SNP which reduces the risk of CAD over a specific range of median albumin-corrected calcium concentrations.\n\nPrecisClinical data and whole exome sequences from a cohort of 51,289 individuals (DiscovEHR) were used to assess the independent contributions of serum Ca2+ and CASR common variants to cardiovascular diseases including CAD.

genetics↗

Whole exome sequencing and characterization of coding variation in 49,960 individuals in the UK Biobank

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world. Here we describe the first tranche of large-scale exome sequence data for 49,960 study participants, revealing approximately 4 million coding variants (of which ~98.4% have frequency < 1%). The data includes 231,631 predicted loss of function variants, a >10-fold increase compared to imputed sequence for the same participants. Nearly all genes (>97%) had [&ge;]1 predicted loss of function carrier, and most genes (>69%) had [&ge;]10 loss of function carriers. We illustrate the power of characterizing loss of function variation in this large population through association analyses across 1,741 phenotypes. In addition to replicating a range of established associations, we discover novel loss of function 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 significance in this population, finding that 2% of the population has a medically actionable variant. Additionally, we leverage the phenotypic data to characterize the relationship between rare BRCA1 and BRCA2 pathogenic variants and cancer risk. Exomes from the first 49,960 participants are now made accessible to the scientific community and highlight the promise offered by genomic sequencing in large-scale population-based studies.

genomics↗

Rare Variant Pathogenicity Triage and Inclusion of Synonymous Variants Improves Analysis of Disease Associations

Many G protein-coupled receptors (GPCRs) lack common variants that lead to reproducible genome-wide disease associations. Here we used rare variant approaches to assess the disease associations of 85 orphan or understudied GPCRs in an unselected cohort of 51,289 individuals. Rare loss-of-function variants, missense variants predicted to be pathogenic or likely pathogenic, and a subset of rare synonymous variants were used as independent data sets for sequence kernel association testing (SKAT). Strong, phenome-wide disease associations shared by two or more variant categories were found for 39% of the GPCRs. Validating the bioinformatics and SKAT analyses, functional characterization of rare missense and synonymous variants of GPR39, a Family A GPCR, showed altered expression and/or Zn2+-mediated signaling for members of both variant classes. Results support the utility of rare variant analyses for identifying disease associations for genes that lack common variants, while also highlighting the functional importance of rare synonymous variants.\n\nAuthor summaryRare variant approaches have emerged as a viable way to identify disease associations for genes without clinically important common variants. Rare synonymous variants are generally considered benign. We demonstrate that rare synonymous variants represent a potentially important dataset for deriving disease associations, here applied to analysis of a set of orphan or understudied GPCRs. Synonymous variants yielded disease associations in common with loss-of-function or missense variants in the same gene. We rationalize their associations with disease by confirming their impact on expression and agonist activation of a representative example, GPR39. This study highlights the importance of rare synonymous variants in human physiology, and argues for their routine inclusion in any comprehensive analysis of genomic variants as potential causes of disease.

genetics↗

Profiling and leveraging relatedness in a precision medicine cohort of 92,455 exomes

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.

genomics↗

A Model for Genome-First Care: Returning Secondary Genomic Findings to Participants and Their Healthcare Providers in a Large Research Cohort

BackgroundResearch cohorts with linked genomic data exist, or are being developed, at many research centers. Within any such \"sequenced cohort\" of more than 100 participants, it is likely that there are participants with previously undisclosed risk for life-threatening monogenic diseases that could be identified with targeted analysis of their existing data. Identification of such disease-associated findings are not usually primary to the enrollment research goals. At Geisinger Health System, MyCode(R) Community Health Initiative (MyCode) participants represent one such large sequenced cohort. Since 2013, MyCode participants in discovery research have been consented for secondary analysis of their existing research genomic sequences to allow delivery of medically actionable findings to them and their healthcare providers. This return of genomic results program was developed to manage an anticipated 3.5% of MyCode participants who will receive clinically confirmed genomic variants from an approved gene list out of more than 150,000 total participants. Risk-associated DNA sequences alone without any clinical parameter, prompt \"genome-first\" follow-up encounters.\n\nMethodsThis article describes our process for generating clinical grade results from research-based genomic sequencing data, delivering results to patients and their providers, facilitating targeted clinical evaluations of patients and promoting cascade testing of at-risk relatives. We also summarize our early data about the results generated during this process and our ability to contact patients and their providers to disclose the information.\n\nResultsThis process has been used to generate 343 results on 339 patients. 93% of patients with a result have been successfully contacted about their results as evidenced by direct interaction about their result with the research team or a healthcare provider. 222 healthcare providers have been notified of a result on one or more patient through this result delivery process.\n\nConclusionsHere we describe the existing GHS model to deliver genomic data into the electronic medical record and the clinical interactions that are prompted and supported. Elements of this genome-first care model can be applied in other healthcare settings and in national efforts, such as \"All of Us\", that wish to establish programs for returning genomic results to research participants.

genomics↗

Profiling copy number variation and disease associations from 50,726 DiscovEHR Study exomes

Copy number variants (CNVs) are a substantial source of genomic variation and contribute to a wide range of human disorders. Gene-disrupting exonic CNVs have important clinical implications as they can underlie variability in disease presentation and susceptibility. The relationship between exonic CNVs and clinical traits has not been broadly explored at the population level, primarily due to technical challenges. We surveyed common and rare CNVs in the exome sequences of 50,726 adult DiscovEHR study participants with linked electronic health records (EHRs). We evaluated the diagnostic yield and clinical expressivity of known pathogenic CNVs, and performed tests of association with EHR-derived serum lipids, thereby evaluating the relationship between CNVs and complex traits and phenotypes in an unbiased, real-world clinical context. We identified CNVs from megabase to exon-level resolution, demonstrating reliable, high-throughput detection of clinically relevant exonic CNVs. In doing so, we created a catalog of high-confidence common and rare CNVs and refined population frequency estimates of known and novel gene-disrupting CNVs. Our survey among an unselected clinical population provides further evidence that neuropathy-associated duplications and deletions in 17p12 have similar population prevalence but are clinically under-diagnosed. Similarly, adults who harbor 22q11.2 deletions frequently had EHR documentation of neurodevelopmental/neuropsychiatric disorders and congenital anomalies, but not a formal genetic diagnosis (i.e., deletion). In an exome-wide association study of lipid levels, we identified a novel five-exon duplication within LDLR segregating in a large kindred with features of familial hypercholesterolemia. Exonic CNVs provide new opportunities to understand and diagnose human disease.

genomics↗