The Biobank Portal for Partners Personalized Medicine: A Query Tool for Working with Consented Biobank Samples, Genotypes, and Phenotypes Using i2b2

Gainer, Vivian S.; Cagan, Andrew; Castro, Víctor M.; Duey, Stacey; Ghosh, B. N.; Goodson, Alyssa P.; Goryachev, Sergey; Metta, Reeta; Wang, Taowei David; Wattanasin, Nich; Murphy, Shawn N.

doi:10.3390/jpm6010011

Cited by 57 publications

(38 citation statements)

References 20 publications

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“…We conduct simulation studies using the UK Biobank genetic data 13,14 , and demonstrate that PRS-CS dramatically improves the predictive performance of PRS over existing methods across a wide range of genetic architectures, especially when the training sample size is large. We apply PRS-CS to predict six curated common complex diseases (breast cancer, coronary artery disease, depression, inflammatory bowel disease, rheumatoid arthritis, and type 2 diabetes mellitus) and six quantitative traits (height, body mass index, high-density lipoproteins, low-density lipoproteins, cholesterol, and triglycerides) in the Partners HealthCare Biobank 15 , and further demonstrate the potential of PRS-CS for the clinical translation of polygenic prediction.…”

Section: Introductionmentioning

confidence: 92%

Polygenic Prediction via Bayesian Regression and Continuous Shrinkage Priors

Chen

et al. 2018

Preprint

280

489

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Polygenic prediction has shown promise in identifying individuals at high risk for complex diseases, and may become clinically useful as the predictive performance of polygenic risk scores (PRS) improves. Here, we present PRS-CS, a novel polygenic prediction method that infers posterior SNP effect sizes using GWAS summary statistics and an external linkage disequilibrium (LD) reference panel. PRS-CS utilizes a highdimensional Bayesian regression framework, and is distinct from previous work by placing a continuous shrinkage (CS) prior on SNP effect sizes, which is robust to varying genetic architectures, provides substantial computational advantages, and enables multivariate modeling of local LD patterns. Simulation studies using data from the UK Biobank show that PRS-CS outperforms existing methods across a wide range of effect size distributions, especially when the training sample size is large. We apply PRS-CS to predict six complex diseases and six quantitative traits in the Partners HealthCare Biobank, and further demonstrate the improvement of PRS-CS in prediction accuracy over alternative methods.

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Section: Introductionmentioning

confidence: 92%

Polygenic Prediction via Bayesian Regression and Continuous Shrinkage Priors

Chen

et al. 2018

Preprint

280

489

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“…We drew on three cohorts of patients seen in the Brigham and Women's Hospital network and the Massachusetts General Hospital network, representing the first 15,064 individuals genotyped as part of the Partners HealthCare Biobank initiative (10). These individuals provided informed consent for their electronic health records (EHRs) to be examined in investigations approved by the Partners Institutional Review Board, and provided blood samples for DNA extraction.…”

Section: Cohort Derivation and Genotypingmentioning

confidence: 99%

Efficient Genome-wide Association in Biobanks Using Topic Modeling Identifies Multiple Novel Disease Loci

McCoy

Castro

Snapper

et al. 2017

Mol Med

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“…We drew on three waves of participants in the Partners Biobank from the Brigham and Women's Hospital network as well as the Massachusetts General Hospital network, representing the first ∼15,000 individuals genotyped as part of the Partners HealthCare Biobank initiative . Structured data, including sociodemographic data as well as inpatient and outpatient diagnostic codes (International Classification of Diseases, Ninth Revision [ICD9]), were extracted from the longitudinal electronic health record (EHR) of these two academic medical centers . We included individuals age 18 years or older with biobank data, and at least one of the following ICD9 codes representing nonunion (733.81 or 733.82) (identifying cases), or fracture of upper (810–819) or lower limb (820–829) in the absence of nonunion (identifying controls).…”

Section: Methodsmentioning

confidence: 99%

Genomewide Association Study of Fracture Nonunion Using Electronic Health Records

et al. 2018

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Nonunion is a clinically significant complication of fracture associated with worse outcomes, including increased pain, disability, and higher healthcare costs. The risk for nonunion is likely to be complex and multifactorial, and as such, the biology underlying such risk remains poorly understood. Genetic studies represent one approach to identify implicated biology for further investigation, but to date the lack of large cohorts for study has limited such efforts. We utilized the electronic health records of two large academic medical centers in Boston to identify individuals with fracture nonunion and control individuals with fracture but no evidence of nonunion. We conducted a genomewide association study among 1760 individuals of Northern European ancestry with upper or lower extremity fracture, including 131 with nonunion, to examine whether common variants were associated with nonunion in this cohort. In all, one locus in the Calcyon (CALY) gene exceeded a genomewide threshold for statistical significance (p = 1.95e–8), with eight additional loci associated with p < 5e–7. Previously reported candidate genes were not supported by this analysis. Electronic health records should facilitate identification of common genetic variations associated with adverse orthopedic outcomes. The loci we identified in this small cohort require replication and further study to characterize mechanism of action, but represent a starting point for the investigation of genetic liability for this costly outcome. © 2018 American Society for Bone and Mineral Research.

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The Biobank Portal for Partners Personalized Medicine: A Query Tool for Working with Consented Biobank Samples, Genotypes, and Phenotypes Using i2b2

Cited by 57 publications

References 20 publications

Polygenic Prediction via Bayesian Regression and Continuous Shrinkage Priors

Polygenic Prediction via Bayesian Regression and Continuous Shrinkage Priors

Efficient Genome-wide Association in Biobanks Using Topic Modeling Identifies Multiple Novel Disease Loci

Genomewide Association Study of Fracture Nonunion Using Electronic Health Records

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