Researchers in the Psychiatric Genomics and Pharmacogenomics Program study genetics related to complex mental health conditions, especially bipolar disorder and alcohol use disorder. The ultimate goal is to advance better individualized treatment options through improved precision medicine.
Our work on bipolar disorder includes investigating rigorously and narrowly defined clinical subphenotypes in genetic association studies. Our objective is to improve the ability to detect genetic factors that contribute to complex traits by reducing the phenotypic heterogeneity through more precise clinical subtyping. This approach is critical to the advancement of precision psychiatry.
Our work is done in collaboration with the Individualized Medicine Biobank for Bipolar Disorder, which offers a rich research resource of biospecimen samples and clinical data from thousands of participants. Read more about the Bipolar Disorder Biobank.
Our program also participates in international collaborative efforts, including the Psychiatric Genomics Consortium and the International Consortium on Lithium Genetics. Our group also leads the Mood Stabilizer Genomics (MoStGen) Consortium to create a larger database and biorepository to examine pharmacogenomics for bipolar disorder.
We're investigating differences in how people respond to the medication acamprosate to treat alcohol use disorder. This work includes understanding a variety of risk factors, including genetics and sex, related to patterns of alcohol use in people in alcohol use treatment programs. This research is done alongside the Samuel C. Johnson Genomics of Addiction Program at Mayo Clinic.
Pharmacogenomic research aims to identify genetic predictors of a person's response to medicine. This is a critical component of advancing precision medicine.
Dr. Biernacka's team has led pharmacogenomic analyses of:
- Antidepressant treatment of a major depressive disorder.
- Mood stabilizer treatment of bipolar disorder.
- Acamprosate and naltrexone treatment of alcohol use disorders.
Our team uses analytical approaches and incorporates biomarker data, such as metabolomics, to guide the identification of pharmacogenomic targets.
Psychiatric genomics research using electronic health records
With support from the National Institute of Mental Health, our program leads cutting-edge research that uses data from electronic health records (EHRs) to gain insights into the risk and prognosis of mental health conditions. By linking EHR data to genomic data from research biobanks, we can leverage detailed clinical information from the EHR for a broad range of projects in psychiatric genomics, including:
- Depression and anxiety.
- Substance use disorders.
- Clinical outcomes, including treatment resistance.
This line of research is critical for understanding the usefulness of genomic medicine in psychiatry and its potential for advancing precision psychiatry.
Statistical genetics methods
Our research team develops new statistical genetics methods to analyze complex genetic data. These methods are used to investigate the genetic factors that contribute to complex psychiatric traits.
Our team develops methodologies related to:
- Gene-set analysis.
- Detecting interactions among risk factors contributing to complex psychiatric traits.
- Data-mining methods for genetic data analysis.
- Polygenic risk score methods.