We have explored the polygenic contributions of substance use disorders (alcohol, cannabis) across multiple medical phenotypes.
Our primary site has been BioVU, but it would be fantastic to replicate some of these findings across any other site that may be interested.
Studies have indicated that Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders(ASD) are associated with a range of behavioral and physical problems. The aim of our study is to examine comorbidity patterns of ADHD and ASD across the medical phenome.
Functional seizures (FS) are severely understudied paroxysmal episodes clinically similar to epileptic seizures but without aberrant brain electrical patterns. FS is thought to be primarily related to psychiatric distress. FS patients have high rates of psychiatric comorbidities, and around 75% are female.
Polygenic risk scores (PRS) are already being used in the clinical context (e.g., cancer genetics) and they may eventually be implemented in routine clinical practice as clinical biomarkers. It is both important and urgent to develop a better understanding of how non-genetic factors biology may affect the value of the PRS, before applying them in clinical settings.
Posttraumatic stress disorder (PTSD) is the sentinel psychiatric disorder following traumatic events and is highly debilitating. The large-scale nature of electronic health records offers a new opportunity to characterize the real-world prevalence of trauma, PTSD, and other post-traumatic stress outcomes in health systems and identify their epidemiological and genetic correlates.
Developmental language disorder (DLD) is a common pediatric language impairment that affects up to 7% of the population, that remains under-diagnosed in the population. Further, the underlying biology, etiology and risk factors especially at the population level are not well understood.
The goal is to impute genomic features (e.g. gene/isoform expression, histone modifications, chromatin accessibility etc.) at the level of each individual for different tissues, cell types and developmental stages and associate them with phenotypic traits.
The availability of large-scale biobanks linking electronic health records (EHRs) to biospecimens has created a powerful opportunity for increasing diversity in psychiatric research. Defining and assigning case status is an important step in conducting research using EHR. Case status is often defined using phenotypic algorithms which have been developed from majority white individuals.
The Opioid Use Disorder workgroup aims to study the genetics of opioid use disorders (OUD) using electronic health record data across multiple sites from the psycheMERGE network (Vanderbilt, Geisenger, Michigan, Partners, Penn Medicine, Million Veterans Program).
The goal of the LabWAS workgroup is to leverage clinical lab tests stored in EHRs to understand the relationship between genetic risk for psychiatric disorders and quantitative physiological measurements. At Vanderbilt, we developed a pipeline to clean and analyze thousands of lab traits stored in EHRs, QualityLab and LabWAS. We conducted proof-of-principle analyses at Vanderbilt and MGB demonstrating cardiovascular disease polygenic scores associated with known risk factors using the cleaned lab values.
