Genotyping Array Design and Data Quality Control in the Million Veteran Program.
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ABSTRACT:
SUBMITTER: Hunter-Zinck H
PROVIDER: S-EPMC7118558 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Biomedical studies have become larger in size and yielded large quantities of data, yet efficient data processing remains a challenge. Here we present Trellis, a cloud-based data and task management framework that completely automates the process from data ingestion to result presentation, while tracking data lineage, facilitating information query, and supporting fault-tolerance and scalability. Using a graph database to coordinate the state of the data processing workflows and a scalable microservice architecture to perform bioinformatics tasks, Trellis has enabled efficient variant calling on 100,000 human genomes collected in the VA Million Veteran Program.
| S-EPMC8636485 | biostudies-literature
Project description:PurposePrimary open-angle glaucoma (POAG) is a degenerative eye disease for which early treatment is critical to mitigate visual impairment and irreversible blindness. POAG-associated loci individually confer incremental risk. Genetic risk score(s) (GRS) could enable POAG risk stratification. Despite significantly higher POAG burden among individuals of African ancestry (AFR), GRS are limited in this population. A recent large-scale, multi-ancestry meta-analysis identified 127 POAG-associated loci and calculated cross-ancestry and ancestry-specific effect estimates, including in European ancestry (EUR) and AFR individuals. We assessed the utility of the 127-variant GRS for POAG risk stratification in EUR and AFR Veterans in the Million Veteran Program (MVP). We also explored the association between GRS and documented invasive glaucoma surgery (IGS).DesignCross-sectional study.ParticipantsMVP Veterans with imputed genetic data, including 5830 POAG cases (445 with IGS documented in the electronic health record) and 64 476 controls.MethodsWe tested unweighted and weighted GRS of 127 published risk variants in EUR (3382 cases and 58 811 controls) and AFR (2448 cases and 5665 controls) Veterans in the MVP. Weighted GRS were calculated using effect estimates from the most recently published report of cross-ancestry and ancestry-specific meta-analyses. We also evaluated GRS in POAG cases with documented IGS.Main outcome measuresPerformance of 127-variant GRS in EUR and AFR Veterans for POAG risk stratification and association with documented IGS.ResultsGRS were significantly associated with POAG (P < 5 × 10-5) in both groups; a higher proportion of EUR compared with AFR were consistently categorized in the top GRS decile (21.9%-23.6% and 12.9%-14.5%, respectively). Only GRS weighted by ancestry-specific effect estimates were associated with IGS documentation in AFR cases; all GRS types were associated with IGS in EUR cases.ConclusionsVaried performance of the GRS for POAG risk stratification and documented IGS association in EUR and AFR Veterans highlights (1) the complex risk architecture of POAG, (2) the importance of diverse representation in genomics studies that inform GRS construction and evaluation, and (3) the necessity of expanding diverse POAG-related genomic data so that GRS can equitably aid in screening individuals at high risk of POAG and who may require more aggressive treatment.
| S-EPMC9997524 | biostudies-literature
Project description:With the rise of high-throughput sequencing technology, traditional genotyping arrays are gradually being replaced by sequencing technology. Against this trend, Illumina has introduced an exome genotyping array that provides an alternative approach to sequencing, especially suited to large-scale genome-wide association studies (GWASs). The exome genotyping array targets the exome plus rare single-nucleotide polymorphisms (SNPs), a feature that makes it substantially more challenging to process than previous genotyping arrays that targeted common SNPs. Researchers have struggled to generate a reliable protocol for processing exome genotyping array data. The Vanderbilt Epidemiology Center, in cooperation with Vanderbilt Technologies for Advanced Genomics Analysis and Research Design (VANGARD), has developed a thorough exome chip-processing protocol. The protocol was developed during the processing of several large exome genotyping array-based studies, which included over 60,000 participants combined. The protocol described herein contains detailed clustering techniques and robust quality control procedures, and it can benefit future exome genotyping array-based GWASs.
| S-EPMC4441213 | biostudies-literature
Project description:BackgroundTo describe an automated method for assessment of the plausibility of continuous variables collected in the electronic health record (EHR) data for real world evidence research use.MethodsThe most widely used approach in quality assessment (QA) for continuous variables is to detect the implausible numbers using prespecified thresholds. In augmentation to the thresholding method, we developed a score-based method that leverages the longitudinal characteristics of EHR data for detection of the observations inconsistent with the history of a patient. The method was applied to the height and weight data in the EHR from the Million Veteran Program Data from the Veteran's Healthcare Administration (VHA). A validation study was also conducted.ResultsThe receiver operating characteristic (ROC) metrics of the developed method outperforms the widely used thresholding method. It is also demonstrated that different quality assessment methods have a non-ignorable impact on the body mass index (BMI) classification calculated from height and weight data in the VHA's database.ConclusionsThe score-based method enables automated and scaled detection of the problematic data points in health care big data while allowing the investigators to select the high-quality data based on their need. Leveraging the longitudinal characteristics in EHR will significantly improve the QA performance.
| S-EPMC8529838 | biostudies-literature
Project description:Currently there is great interest in detecting associations between complex traits and rare variants. In this report, we describe Variant Association Tools (VAT) and the VAT pipeline, which implements best practices for rare-variant association studies. Highlights of VAT include variant-site and call-level quality control (QC), summary statistics, phenotype- and genotype-based sample selection, variant annotation, selection of variants for association analysis, and a collection of rare-variant association methods for analyzing qualitative and quantitative traits. The association testing framework for VAT is regression based, which readily allows for flexible construction of association models with multiple covariates and weighting themes based on allele frequencies or predicted functionality. Additionally, pathway analyses, conditional analyses, and analyses of gene-gene and gene-environment interactions can be performed. VAT is capable of rapidly scanning through data by using multi-process computation, adaptive permutation, and simultaneously conducting association analysis via multiple methods. Results are available in text or graphic file formats and additionally can be output to relational databases for further annotation and filtering. An interface to R language also facilitates user implementation of novel association methods. The VAT's data QC and association-analysis pipeline can be applied to sequence, imputed, and genotyping array, e.g., "exome chip," data, providing a reliable and reproducible computational environment in which to analyze small- to large-scale studies with data from the latest genotyping and sequencing technologies. Application of the VAT pipeline is demonstrated through analysis of data from the 1000 Genomes project.
| S-EPMC4067555 | biostudies-literature
Project description:No data exist on the prevalence of ideal cardiovascular health metrics in a national sample of U.S. veterans. We assessed the prevalence of ideal Life's Simple Seven (LSS) metrics in a cross-sectional study of 554,855 U.S. veterans enrolled in the Million Veteran Program (MVP) from 2011 to 2017. We used the American Heart Association's established criteria to categorize each LSS metric as either poor, intermediate, or ideal for a veteran at time of MVP enrollment. Information on adiposity/body mass index, smoking status, diet, and physical activity was obtained from self-reported survey data, and clinical measurements for total cholesterol, blood pressure, and plasma glucose were obtained from electronic health records. Complete data on all LSS health factors were available for 201,745 veterans. The prevalence of having 0, 1, 2, 3, 4, 5, 6, and 7 ideal cardiovascular health metrics was 29.2%, 34.6%, 22.6%, 10.0%, 3.0%, 0.6%, <0.1%, and 0%, respectively. The frequency of ideal body mass index, physical activity, smoking status, total cholesterol, blood pressure, and plasma glucose was 19.4%, 3.8%, 27.0%, 21.8%, 17.8%, and 34.5%, respectively, in our study population. Among the 7 metrics, MVP participants were least likely to achieve ideal diet (0.4%), particularly the recommendation for fruit and vegetable (at least 4.5 cups/day) intake. Our data show an extremely low prevalence of ideal cardiovascular health factors among veterans in the MVP, especially for diet and physical activity. These findings underscore the need to improve adherence to modifiable lifestyle factors that could result in subsequent reduction in cardiovascular disease burden among veterans.
| S-EPMC7020617 | biostudies-literature
Project description:BackgroundAbdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability.MethodsWe performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease.ResultsThrough a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24-1.66]; P=1.6×10-6), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97-1.15]; P=0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratioPRS, 1.26 [95% CI, 1.18-1.36]; PPRS=2.7×10-11 per SD increase in PRS), independent of family history and smoking risk factors (odds ratioPRS+family history+smoking, 1.24 [95% CI, 1.14-1.35]; PPRS=1.27×10-6). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines.ConclusionsWe identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.
| S-EPMC7580856 | biostudies-literature
Project description:BackgroundAlthough previous studies have suggested cocoa products may promote cardiovascular health in the general population, no public data are available from patients receiving care in a national integrated health care system.ObjectivesWe tested the hypothesis that regular chocolate consumption is associated with a lower risk of coronary artery disease (CAD) events among participants of the Million Veteran Program (MVP). Secondary analysis examined if the main hypothesis was observed among participants with type 2 diabetes.MethodsWe analyzed data from MVP participants who completed the food frequency section of the MVP Lifestyle Survey and were free of CAD at the time of survey completion. CAD events during follow-up (International Statistical Classification of Diseases Ninth Revision codes 410-411 and 413-414, and Tenth Revision codes I20-I25 except I25.2) were assessed using electronic health records. We fitted a Cox proportional hazard model to estimate the RR of CAD.ResultsOf 188,447 MVP enrollees with survey data, mean ± SD age was 64 ± 12.0 y and 90% were men. For regular chocolate (28.3 g/serving) consumption of <1 serving/mo, 1-3 servings/mo, 1 serving/wk, 2-4 servings/wk, and ≥5 servings/wk, crude incidence rates (per 1000 person-years) for fatal and nonfatal CAD events or coronary procedures were 20.2, 17.5, 16.7, 17.1, and 16.9, respectively, during a mean follow-up of 3.2 y. After adjusting for age, sex, race, and lifestyle factors, the corresponding HRs (95% CIs) were 1.00 (ref), 0.92 (0.87, 0.96), 0.88 (0.83, 0.93), 0.89 (0.84, 0.95), and 0.89 (0.84, 0.96), respectively (P for linear trend < 0.0001). In a secondary analysis of 47,265 diabetics, we did not observe a decreasing trend in CAD mortality among those who consumed ≥1 serving of chocolate a month compared with those who consumed <1 serving/mo.ConclusionsRegular chocolate consumption was associated with a lower risk of CAD among veterans, but was not associated with cardiovascular disease risk in veterans with type 2 diabetes.
| S-EPMC8412179 | biostudies-literature
Project description:IntroductionDiabetes and dementia are diseases of high healthcare burden worldwide. Individuals with diabetes have 1.4 to 2.2 times higher risk of dementia. Our objective was to evaluate evidence of causality between these two common diseases.MethodsWe conducted a one-sample Mendelian randomization (MR) analysis in the U.S. Department of Veterans Affairs Million Veteran program. The study included 334,672 participants ≥65 years of age with type 2 diabetes and dementia case-control status and genotype data.ResultsFor each standard deviation increase in genetically-predicted diabetes, we found increased odds of three dementia diagnoses in non-Hispanic White participants (all-cause: OR=1.07[1.05-1.08], P =3.40E-18; vascular: OR=1.11[1.07-1.15], P =3.63E-09, Alzheimer's: OR=1.06[1.02-1.09], P =6.84E-04) and non-Hispanic Black participants (all-cause: OR=1.06[1.02-1.10], P =3.66E-03, vascular: OR=1.11[1.04-1.19], P =2.20E-03, Alzheimer's: OR=1.12 [1.02-1.23], P =1.60E-02) but not in Hispanic participants (all P >.05).DiscussionWe found evidence of causality between diabetes and dementia using a one-sample MR study, with access to individual level data, overcoming limitations of prior studies utilizing two-sample MR techniques.
| S-EPMC10029030 | biostudies-literature
Project description:BackgroundThe US government considers veterans to have been exposed to Agent Orange if they served in Vietnam while the carcinogen was in use, and these veterans are often deemed at high risk of prostate cancer (PCa). Here, we assess whether presumed Agent Orange exposure is independently associated with increased risk of any metastatic or fatal PCa in a diverse Veteran cohort still alive in the modern era (at least 2011), when accounting for race/ethnicity, family history, and genetic risk.Patients and methodsParticipants in the Million Veteran Program (MVP; enrollment began in 2011) who were on active duty during the Vietnam War era (August 1964-April 1975) were included (n = 301,470). Agent Orange exposure was determined using the US government definition. Genetic risk was assessed via a validated polygenic hazard score. Associations with age at diagnosis of any PCa, metastatic PCa, and death from PCa were assessed via Cox proportional hazards models.Results and interpretationOn univariable analysis, exposure to Agent Orange was not associated with increased PCa (hazard ratio [HR]: 1.02, 95% confidence interval [CI]: 1.00-1.04, p = 0.06), metastatic PCa (HR: 0.98, 95% CI: 0.91-1.05, p = 0.55), or fatal PCa (HR: 0.94, 95% CI: 0.79-1.09, p = 0.41). When accounting for race/ethnicity and family history, Agent Orange exposure was independently associated with slightly increased risk of PCa (HR: 1.06, 95% CI: 1.04-1.09, <10-6) but not with metastatic PCa (HR: 1.07, 95% CI: 0.98-1.15, p = 0.10) or PCa death (HR: 1.02, 95% CI: 0.83-1.23, p = 0.09). Similar results were found when accounting for genetic risk. Agent Orange exposure history may not improve modern PCa risk stratification.
| S-EPMC11332552 | biostudies-literature