Identifying Family Structures from Obituaries and Matching them to Patients in an Electronic Heath Record.

Motivation: Family data is a valuable data source in bioinformatic research. This is because family members often share common genetic and environmental exposures. Collecting this family data is traditionally very labor intensive but advances in electronic health record (EHR) data mining has proven useful when identifying pedigrees linked to longitudinal health histories.

Long-telomeropathy is associated with tumor predisposition syndrome.

Telomeres protect chromosomal integrity, and telomere length (TL) is influenced by environmental and genetic factors. While short-telomeres are linked to rare telomeropathies, this study explored the hypothesis that a "long-telomeropathy" is associated with a cancer-predisposing syndrome. Using genomic and health data from 113,861 individuals, a trans-ancestry polygenic risk score for TL (PRS ) was developed.

Familial Renal Glucosuria and Potential Pharmacogenetic Impact on SGLT2 Inhibitors.

Background: Renal glucosuria is a rare inheritable trait caused by loss-of-function variants in the gene that encodes SGLT2 (i.e., SLC5A2).

Exploring prognostic implications of miRNA signatures and telomere maintenance genes in kidney cancer.

Kidney cancer, particularly clear cell renal cell carcinoma (KIRC), presents significant challenges in disease-specific survival. This study investigates the prognostic potential of microRNAs (miRNAs) in kidney cancers, including KIRC and kidney papillary cell carcinoma (KIRP), focusing on their interplay with telomere maintenance genes. Utilizing data from The Cancer Genome Atlas, miRNA expression profiles of 166 KIRC and 168 KIRP patients were analyzed.

Automated Family Histories Significantly Improve Risk Prediction in an EHR.

We recently demonstrated that electronically constructed family pedigrees (e-pedigrees) have great value in epidemiologic research using electronic health record (EHR) data. Prior to this work, it has been well accepted that family health history is a major predictor for a wide spectrum of diseases, reflecting shared effects of genetics, environment, and lifestyle. With the widespread digitalization of patient data via EHRs, there is an unprecedented opportunity to use machine learning algorithms to better predict disease risk.

Assessment of the current status of real-world pharmacogenomic testing: informed consent, patient education, and related practices.

The practice of informed consent (IC) for pharmacogenomic testing in clinical settings varies, and there is currently no consensus on which elements of IC to provide to patients. This study aims to assess current IC practices for pharmacogenomic testing. An online survey was developed and sent to health providers at institutions that offer clinical germline pharmacogenomic testing to assess current IC practices.

An evolutionary learning-based method for identifying a circulating miRNA signature for breast cancer diagnosis prediction.

Breast cancer (BC) is one of the most commonly diagnosed cancers worldwide. As key regulatory molecules in several biological processes, microRNAs (miRNAs) are potential biomarkers for cancer. Understanding the miRNA markers that can detect BC may improve survival rates and develop new targeted therapeutic strategies.

Estimating the efficacy of pharmacogenomics over a lifetime.

It is well known that common variants in specific genes influence drug metabolism and response, but it is currently unknown what fraction of patients are given prescriptions over a lifetime that could be contraindicated by their pharmacogenomic profiles. To determine the clinical utility of pharmacogenomics over a lifetime in a general patient population, we sequenced the genomes of 300 deceased Marshfield Clinic patients linked to lifelong medical records. Genetic variants in 33 pharmacogenes were evaluated for their lifetime impact on drug prescribing using extensive electronic health records.

Genetic and clinical determinants of telomere length.

Many epidemiologic studies have identified important relationships between leukocyte telomere length (LTL) with genetics and health. Most of these studies have been significantly limited in scope by focusing predominantly on individual diseases or restricted to GWAS analysis. Using two large patient populations derived from Vanderbilt University and Marshfield Clinic biobanks linked to genomic and phenomic data from medical records, we investigated the inter-relationship between LTL, genomics, and human health.

Familial Hypercholesterolemia in the Electronic Medical Records and Genomics Network: Prevalence, Penetrance, Cardiovascular Risk, and Outcomes After Return of Results.

Background: The implications of secondary findings detected in large-scale sequencing projects remain uncertain. We assessed prevalence and penetrance of pathogenic familial hypercholesterolemia (FH) variants, their association with coronary heart disease (CHD), and 1-year outcomes following return of results in phase III of the electronic medical records and genomics network.

Methods: Adult participants (n=18 544) at 7 sites were enrolled in a prospective cohort study to assess the clinical impact of returning results from targeted sequencing of 68 actionable genes, including , , and .

Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics.

Objective: High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach.

Methods: This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults.

The Research Program: Data quality, utility, and diversity.

The Research Program seeks to engage at least one million diverse participants to advance precision medicine and improve human health. We describe here the cloud-based Researcher Workbench that uses a data passport model to democratize access to analytical tools and participant information including survey, physical measurement, and electronic health record (EHR) data. We also present validation study findings for several common complex diseases to demonstrate use of this novel platform in 315,000 participants, 78% of whom are from groups historically underrepresented in biomedical research, including 49% self-reporting non-White races.

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations.

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD.

Large-scale genomic analyses reveal insights into pleiotropy across circulatory system diseases and nervous system disorders.

Clinical and epidemiological studies have shown that circulatory system diseases and nervous system disorders often co-occur in patients. However, genetic susceptibility factors shared between these disease categories remain largely unknown. Here, we characterized pleiotropy across 107 circulatory system and 40 nervous system traits using an ensemble of methods in the eMERGE Network and UK Biobank.

Kidney failure in Bardet-Biedl syndrome.

The aim of this study was to explore kidney failure (KF) in Bardet-Biedl syndrome (BBS), focusing on high-risk gene variants, demographics, and morbidity. We employed the Clinical Registry Investigating BBS (CRIBBS) to identify 44 (7.2%) individuals with KF out of 607 subjects.

An independently validated, portable algorithm for the rapid identification of COPD patients using electronic health records.

Electronic health records (EHR) provide an unprecedented opportunity to conduct large, cost-efficient, population-based studies. However, the studies of heterogeneous diseases, such as chronic obstructive pulmonary disease (COPD), often require labor-intensive clinical review and testing, limiting widespread use of these important resources. To develop a generalizable and efficient method for accurate identification of large COPD cohorts in EHRs, a COPD datamart was developed from 3420 participants meeting inclusion criteria in the Mass General Brigham Biobank.

Genetic association of primary nonresponse to anti-TNFα therapy in patients with inflammatory bowel disease.

Objectives: Primary nonresponse (PNR) to antitumor necrosis factor-α (TNFα) biologics is a serious concern in patients with inflammatory bowel disease (IBD). We aimed to identify the genetic variants associated with PNR.

Patients And Methods: Patients were recruited from outpatient GI clinics and PNR was determined using both clinical and endoscopic findings.

Penetrance of Breast Cancer Susceptibility Genes From the eMERGE III Network.

Background: Unbiased estimates of penetrance are challenging but critically important to make informed choices about strategies for risk management through increased surveillance and risk-reducing interventions.

Methods: We studied the penetrance and clinical outcomes of 7 breast cancer susceptibility genes (, , , , , , and ) in almost 13 458 participants unselected for personal or family history of breast cancer. We identified 242 female participants with pathogenic or likely pathogenic variants in 1 of the 7 genes for penetrance analyses, and 147 women did not previously know their genetic results.

The genetic architecture of plasma kynurenine includes cardiometabolic disease mechanisms associated with the SH2B3 gene.

Inflammation increases the risk of cardiometabolic disease. Delineating specific inflammatory pathways and biomarkers of their activity could identify the mechanistic underpinnings of the increased risk. Plasma levels of kynurenine, a metabolite involved in inflammation, associates with cardiometabolic disease risk.

Associations of Genetically Predicted Lp(a) (Lipoprotein [a]) Levels With Cardiovascular Traits in Individuals of European and African Ancestry.

Background: Lp(a) (lipoprotein [a]) levels are higher in individuals of African ancestry (AA) than in individuals of European ancestry (EA). We examined associations of genetically predicted Lp(a) levels with (1) atherosclerotic cardiovascular disease subtypes: coronary heart disease, cerebrovascular disease, peripheral artery disease, and abdominal aortic aneurysm and (2) nonatherosclerotic cardiovascular disease phenotypes, stratified by ancestry.

Methods: We performed (1) Mendelian randomization analyses for previously reported cardiovascular associations and (2) Mendelian randomization-phenome-wide association analyses for novel associations.

E-Pedigrees: a large-scale automatic family pedigree prediction application.

Motivation: The use and functionality of Electronic Health Records (EHR) have increased rapidly in the past few decades. EHRs are becoming an important depository of patient health information and can capture family data. Pedigree analysis is a longstanding and powerful approach that can gain insight into the underlying genetic and environmental factors in human health, but traditional approaches to identifying and recruiting families are low-throughput and labor-intensive.