Faculty Bibliography
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64
Neptune: an environment for the delivery of genomic medicine
PURPOSE:Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. METHODS:We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. RESULTS:Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. CONCLUSION:Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .
PMCID:8487966
PMID: 34257418
ISSN: 1530-0366
CID: 5479332
A semi-supervised model to predict regulatory effects of genetic variants at single nucleotide resolution using massively parallel reporter assays
MOTIVATION:Predicting regulatory effects of genetic variants is a challenging but important problem in functional genomics. Given the relatively low sensitivity of functional assays, and the pervasiveness of class imbalance in functional genomic data, popular statistical prediction models can sharply underestimate the probability of a regulatory effect. We describe here the presence-only model (PO-EN), a type of semi-supervised model, to predict regulatory effects of genetic variants at sequence-level resolution in a context of interest by integrating a large number of epigenetic features and massively parallel reporter assays (MPRAs). RESULTS:Using experimental data from a variety of MPRAs we show that the presence-only model produces better calibrated predicted probabilities and has increased accuracy relative to state-of-the-art prediction models. Furthermore, we show that the predictions based on pre-trained PO-EN models are useful for prioritizing functional variants among candidate eQTLs and significant SNPs at GWAS loci. In particular, for the costimulatory locus, associated with multiple autoimmune diseases, we show evidence of a regulatory variant residing in an enhancer 24.4 kb downstream of CTLA4, with evidence from capture Hi-C of interaction with CTLA4. Furthermore, the risk allele of the regulatory variant is on the same risk increasing haplotype as a functional coding variant in exon 1 of CTLA4, suggesting that the regulatory variant acts jointly with the coding variant leading to increased risk to disease. AVAILABILITY:The presence-only model is implemented in the R package 'PO.EN', freely available on CRAN. A vignette describing a detailed demonstration of using the proposed PO-EN model can be found on github at https://github.com/Iuliana-Ionita-Laza/PO.EN/. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
PMCID:8337004
PMID: 33515242
ISSN: 1367-4811
CID: 5710552
Medical Records-Based Genetic Studies of the Complement System
BACKGROUND:Genetic variants in complement genes have been associated with a wide range of human disease states, but well-powered genetic association studies of complement activation have not been performed in large multiethnic cohorts. METHODS:We performed medical records-based genome-wide and phenome-wide association studies for plasma C3 and C4 levels among participants of the Electronic Medical Records and Genomics (eMERGE) network. RESULTS:). Overall, C4 levels were strongly correlated with copy numbers of C4A and C4B genes. In comprehensive phenome-wide association studies involving 102,138 eMERGE participants, we cataloged a full spectrum of autoimmune, cardiometabolic, and kidney diseases genetically related to systemic complement activation. CONCLUSIONS:We discovered genetic determinants of plasma C3 and C4 levels using eMERGE genomic data linked to electronic medical records. Genetic variants regulating C3 and C4 levels have large effects and multiple clinical correlations across the spectrum of complement-related diseases in humans.
PMID: 33941608
ISSN: 1533-3450
CID: 5710572
171 Hidradenitis suppurativa genome-wide association study [Meeting Abstract]
Hidradenitis suppurativa (HS) is a prevalent inflammatory skin disease. HS causes deep, painful, recurrent abscesses. African Americans and females are at an increased risk. A lack of effective therapies and limited knowledge about HS pathogenesis contribute to unmet needs. Unlike other common inflammatory skin diseases, there has never been a genome-wide association study (GWAS) conducted for HS. Here, we performed a first GWAS for HS using data from the eMERGE network of electronic health record linked biorepositories (project NT227). We used HS diagnosis codes to identify cases and controls. We estimated ancestry with principal component analysis using a set of 40,156 SNPs. Our final cohort consisted of 600 HS cases and 82,611 controls with comparable multi-ethnic ancestry (lambda=1.005). Our cohort recapitulated HS race and gender predilections with genetically African female participants accounting for 35% of cases, but only 10% of controls. Genotype data for 6 million variants was tested for association, adjusting for five principal components. No locus exceeded our threshold for statistical significance. Importantly, there was no evidence for HLA association supporting classification of HS as inflammatory rather than autoimmune. Several loci approached the significance threshold, suggesting that an expansion in cohort size is needed to provide adequate power to detect associations. Interestingly, the lead SNP at one of the most significant loci (rs11075745; p=8x10-7) is an eQTL for NFAT5, a mediator of NOTCH signaling whose expression is downregulated in HS lesional skin relative to patient-matched nonlesional skin. The risk allele influences expression in tissue specific manner. Our group is constructing multi-ethnic replication cohorts that will allow us to expand this study in the near future.
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EMBASE:2011607800
ISSN: 1523-1747
CID: 4857662
Blockade of IL-7 signaling suppresses inflammatory responses and reverses alopecia areata in C3H/HeJ mice
The interleukin-7 (IL-7) signaling pathway plays an important role in regulation of T cell function and survival. We detected overexpression of IL-7 in lesional skin from both humans and C3H/HeJ mice with alopecia areata (AA), a T cell-mediated autoimmune disease of the hair follicle. We found that exogenous IL-7 accelerated the onset of AA by augmenting the expansion of alopecic T cells. Conversely, blockade of IL-7 stopped the progression of AA and reversed early AA in C3H/HeJ mice. Mechanistically, we observed that IL-7Rα blockade substantially reduced the total number of most T cell subsets, but relative sparing of regulatory T cells (Tregs). We postulated that short-term anti-IL-7Rα treatment in combination with a low dose of Treg-tropic cytokines might improve therapeutic efficacy in AA. We demonstrated that short-term IL-7Rα blockade in combination with low doses of Treg-tropic cytokines enhanced therapeutic effects in the treatment of AA, and invite further clinical investigation.
PMCID:11060042
PMID: 33811067
ISSN: 2375-2548
CID: 5710562
Journal of investigative dermatology symposium proceedings. 2020:20(1):S22-S27.DOI: 10.1016/j.jisp.2020.04.003
An Imperative Need for Further Genetic Studies of Alopecia Areata
Human genetic studies of diseases that are multifactorial and prevalent have generated a wealth of knowledge about the genetic architecture of chronic diseases. Generalizable attributes are shaping the development of models to explain how the human genome influences our health and can be leveraged to improve it. Importantly, both rare and common genetic variants contribute to disease risk and provide complementary information. Although initial genetic studies of alopecia areata have yielded insight with high clinical impact, there remains a number of important unanswered questions pertaining to disease biology and patient care that could be addressed by further genetic investigations.
PMCID:7594098
PMID: 33099379
ISSN: 1529-1774
CID: 5710542
Integrative analysis of rare copy number variants and gene expression data in alopecia areata implicates an aetiological role for autophagy
Alopecia areata (AA) is a highly prevalent autoimmune disease that attacks the hair follicle and leads to hair loss that can range from small patches to complete loss of scalp and body hair. Our previous linkage and genome-wide association studies (GWAS) generated strong evidence for aetiological contributions from inherited genetic variants at different population frequencies, including both rare mutations and common polymorphisms. Additionally, we conducted gene expression (GE) studies on scalp biopsies of 96 patients and controls to establish signatures of active disease. In this study, we performed an integrative analysis on these two datasets to test the hypothesis that rare CNVs in patients with AA could be leveraged to identify drivers of disease in our AA GE signatures. We analysed copy number variants (CNVs) in a case-control cohort of 673 patients with AA and 16 311 controls independent of the case-control cohort of 96 research participants used in our GE study. Using an integrative computational analysis, we identified 14 genes whose expression levels were altered by CNVs in a consistent direction of effect, corresponding to gene expression changes in lesional skin of patients. Four of these genes were affected by CNVs in three or more unrelated patients with AA, including ATG4B and SMARCA2, which are involved in autophagy and chromatin remodelling, respectively. Our findings identified new classes of genes with potential contributions to AA pathogenesis.
PMCID:7213039
PMID: 31169925
ISSN: 1600-0625
CID: 5710522
Association of Genetic Risk of Obesity with Postoperative Complications Using Mendelian Randomization
BACKGROUND:The extent to which obesity and genetics determine postoperative complications is incompletely understood. METHODS:We performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990 and 2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome-wide genotyping data to the Electronic Medical Records and Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease-9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score was constructed from 97 obesity-risk single-nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk of obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components. RESULTS:). Association findings were similar after limitation of the cohorts to those who underwent abdominal procedures. CONCLUSIONS:Clinical and Mendelian randomization studies suggest that obesity, as measured by BMI, is associated with the development of postoperative incisional hernia and infection.
PMID: 31605180
ISSN: 1432-2323
CID: 5710532
Genome-wide association study of hidradenitis suppurativa in a multi-ethnic cohort [Meeting Abstract]
ISI:000550287000063
ISSN: 0906-6705
CID: 5713782
Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network
The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.
PMCID:6731372
PMID: 31447099
ISSN: 1537-6605
CID: 5479312
