Skip to Main Content


Ganesh Receives ECIP Travel Award for 2021 Virtual World Congress of Psychiatric Genetics

August 10, 2021
by Jordan Sisson

Suhas Ganesh, MD, Postdoctoral Associate in the Schizophrenia Neuropharmacology Research Group at Yale (SNRGY), has received an Early Career Investigator Program (ECIP) travel award for the International Society of Psychiatric Genetics’ 2021 Virtual World Congress of Psychiatric Genetics (WCPG).

The 2021 WCPG will be held virtually from Oct. 11-15. As an awardee, Ganesh will receive registration reimbursement to the 2021 WCPG, as well as a travel stipend for the 2022 WCPG in Florence, Italy. Ganesh will also be assigned a senior researcher to serve as a mentor.

Additionally, Ganesh will present a poster titled, “Polygenic Risk Score for Cannabis Use Disorder predicts acute intoxicating effects and cognitive deficits induced by delta-9-Tetrahydrocannabinol – A pilot study.”

Suhas completed clinical training in psychiatry and addiction medicine, and research training in psychiatry genetics at National Institute of Mental Health and Neurosciences, Bengaluru, India before joining SNRGY, directed by Deepak Cyril D’Souza, MD, Professor of Psychiatry, to study how cannabis exposure interacts with individual genetic vulnerability to determine mental health outcomes.

The WCPG is the premier international scientific meeting for research in psychiatric genetics and related areas. Leading experts from all over the world in the area of genetics, neuroscience, and psychiatry will participate. The theme of the 2021 congress is, “Genomics: The Journey to Improve Mental Health,” which will highlight how genetics improves diagnostics and treatment of neurodevelopmental disease, provide an update on pharmacogenetics in psychiatry, and how results from large scale genome-wide association studies can be translated for clinical application. Furthermore, the congress will explore the best way forward to integrate genetic findings with molecular and cellular function and combine information on the environment with the genome for refined risk prediction.

Submitted by Jordan Sisson on August 09, 2021