Electronic health record signatures identify undiagnosed patients with common variable immunodeficiency disease.

Human inborn errors of immunity include rare disorders entailing functional and quantitative antibody deficiencies due to impaired B cells called the common variable immunodeficiency (CVID) phenotype. Patients with CVID face delayed diagnoses and treatments for 5 to 15 years after symptom onset because the disorders are rare (prevalence of ~1/25,000), and there is extensive heterogeneity in CVID phenotypes, ranging from infections to autoimmunity to inflammatory conditions, overlapping with other more common disorders. The prolonged diagnostic odyssey drives excessive system-wide costs before diagnosis.

Bronchopulmonary dysplasia is associated with polyhydramnios in a scan for novel perinatal risk factors.

Background: The pathogenesis of bronchopulmonary dysplasia (BPD) is multifactorial, and there are limited data about prenatal exposures and risk of BPD.

Study Design: Our study performed parallel analyses using a logistic regression model in a cohort of 4527 infants with data from a curated registry and using a phenome wide association study (PheWAS) based on ICD9/10-based phecodes. We examined 20 prenatal exposures from a neonatal intensive care unit (NICU) curated registry database related to pregnancy and maternal health as well as 94 maternal diagnosis phecodes with a PheWAS analysis.

LabWAS: Novel findings and study design recommendations from a meta-analysis of clinical labs in two independent biobanks.

Phenotypes extracted from Electronic Health Records (EHRs) are increasingly prevalent in genetic studies. EHRs contain hundreds of distinct clinical laboratory test results, providing a trove of health data beyond diagnoses. Such lab data is complex and lacks a ubiquitous coding scheme, making it more challenging than diagnosis data.

Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies.

In genome-wide association studies (GWAS) for thousands of phenotypes in large biobanks, most binary traits have substantially fewer cases than controls. Both of the widely used approaches, the linear mixed model and the recently proposed logistic mixed model, perform poorly; they produce large type I error rates when used to analyze unbalanced case-control phenotypes. Here we propose a scalable and accurate generalized mixed model association test that uses the saddlepoint approximation to calibrate the distribution of score test statistics.

PregOMICS-Leveraging systems biology and bioinformatics for drug repurposing in maternal-child health.

Obstetric diseases remain underserved and understudied. Drug repurposing-utilization of a drug whose use is accepted in one condition for a different condition-could represent a rapid and low-cost way to identify new therapies that are known to be safe. In diseases of pregnancy, the known safety profile is a strong additional incentive.

Calcium channel blockers as drug repurposing candidates for gestational diabetes: Mining large scale genomic and electronic health records data to repurpose medications.

New therapeutic approaches are needed for gestational diabetes mellitus (GDM), but must show safety and efficacy in a historically understudied population. We studied associations between electronic medical record (EMR) phenotypes and genetic variants to uncover drugs currently considered safe in pregnancy that could treat or prevent GDM. We identified 129 systemically active drugs considered safe in pregnancy targeting the proteins produced from 196 genes.

Using Human 'Experiments of Nature' to Predict Drug Safety Issues: An Example with PCSK9 Inhibitors.

Introduction: When a new drug enters the market, its full array of side effects remains to be defined. Current surveillance approaches targeting these effects remain largely reactive. There is a need for development of methods to predict specific safety events that should be sought for a given new drug during development and postmarketing activities.

Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record.

Objective: To compare three groupings of Electronic Health Record (EHR) billing codes for their ability to represent clinically meaningful phenotypes and to replicate known genetic associations. The three tested coding systems were the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, the Agency for Healthcare Research and Quality Clinical Classification Software for ICD-9-CM (CCS), and manually curated "phecodes" designed to facilitate phenome-wide association studies (PheWAS) in EHRs.

Methods And Materials: We selected 100 disease phenotypes and compared the ability of each coding system to accurately represent them without performing additional groupings.

A common deletion in the haptoglobin gene associated with blood cholesterol levels among Chinese women.

Haptoglobin (HP) protein plays a critical role in binding and removing free hemoglobin from blood. A deletion in the HP gene affects the protein structure and function. A recent study developed a novel method to impute this variant and discovered significant association of this variant with low-density lipoprotein (LDL) and total cholesterol levels among European descendants.

Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals.

Objective: Phenotyping algorithms applied to electronic health record (EHR) data enable investigators to identify large cohorts for clinical and genomic research. Algorithm development is often iterative, depends on fallible investigator intuition, and is time- and labor-intensive. We developed and evaluated 4 types of phenotyping algorithms and categories of EHR information to identify hypertensive individuals and controls and provide a portable module for implementation at other sites.

Inactivating mutations in NPC1L1 and protection from coronary heart disease.

Background: Ezetimibe lowers plasma levels of low-density lipoprotein (LDL) cholesterol by inhibiting the activity of the Niemann-Pick C1-like 1 (NPC1L1) protein. However, whether such inhibition reduces the risk of coronary heart disease is not known. Human mutations that inactivate a gene encoding a drug target can mimic the action of an inhibitory drug and thus can be used to infer potential effects of that drug.