A gene-based association method for mapping traits using reference transcriptome data.

Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype.

Intelligent use and clinical benefits of electronic health records in rheumatoid arthritis.

In the past 10 years, electronic health records (EHRs) have had growing impact in clinical care. EHRs efficiently capture and reuse clinical information, which can directly benefit patient care by guiding treatments and providing effective reminders for best practices. The increased adoption has also lead to more complex implementations, including robust, disease-specific tools, such as for rheumatoid arthritis (RA).

Magnetic resonance imaging of the cardiac manifestations of Churg-Strauss.

Through the detection of acute inflammation, edema, and fibrosis, cardiac magnetic resonance imaging provides a complete and safe evaluation of the myocardium in Churg-Strauss disease and is a useful tool for following the disease course.

Integration of sequence data from a Consanguineous family with genetic data from an outbred population identifies PLB1 as a candidate rheumatoid arthritis risk gene.

Integrating genetic data from families with highly penetrant forms of disease together with genetic data from outbred populations represents a promising strategy to uncover the complete frequency spectrum of risk alleles for complex traits such as rheumatoid arthritis (RA). Here, we demonstrate that rare, low-frequency and common alleles at one gene locus, phospholipase B1 (PLB1), might contribute to risk of RA in a 4-generation consanguineous pedigree (Middle Eastern ancestry) and also in unrelated individuals from the general population (European ancestry). Through identity-by-descent (IBD) mapping and whole-exome sequencing, we identified a non-synonymous c.

Genetics of rheumatoid arthritis contributes to biology and drug discovery.

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4).

Applying active learning to high-throughput phenotyping algorithms for electronic health records data.

Objectives: Generalizable, high-throughput phenotyping methods based on supervised machine learning (ML) algorithms could significantly accelerate the use of electronic health records data for clinical and translational research. However, they often require large numbers of annotated samples, which are costly and time-consuming to review. We investigated the use of active learning (AL) in ML-based phenotyping algorithms.

Portability of an algorithm to identify rheumatoid arthritis in electronic health records.

Objectives: Electronic health records (EHR) can allow for the generation of large cohorts of individuals with given diseases for clinical and genomic research. A rate-limiting step is the development of electronic phenotype selection algorithms to find such cohorts. This study evaluated the portability of a published phenotype algorithm to identify rheumatoid arthritis (RA) patients from EHR records at three institutions with different EHR systems.

Naïve Electronic Health Record phenotype identification for Rheumatoid arthritis.

Electronic Health Records (EHRs) provide a real-world patient cohort for clinical and genomic research. Phenotype identification using informatics algorithms has been shown to replicate known genetic associations found in clinical trials and observational cohorts. However, development of accurate phenotype identification methods can be challenging, requiring significant time and effort.

Milnacipran for the management of fibromyalgia syndrome.

Fibromyalgia syndrome (FMS) is a widespread pain condition associated with fatigue, cognitive dysfunction, sleep disturbance, depression, anxiety, and stiffness. Milnacipran is one of three medications currently approved by the Food and Drug Administration in the United States for the management of adult FMS patients. This review is the second in a three-part series reviewing each of the approved FMS drugs and serves as a primer on the use of milnacipran in FMS treatment including information on pharmacology, pharmacokinetics, safety and tolerability.