Psychiatric & Neurodevelopmental Genetics Unit

About the Unit

Psychiatric and neurodevelopmental disorders are common, costly and often disabling conditions that affect individuals throughout their lives. Disability associated with neuropsychiatric disorders exceeds that of other medical illnesses, and psychiatric disorders are also associated with premature mortality. Familial and genetic factors are the most-substantiated risk factors for a broad range of neuropsychiatric disorders.

The Psychiatric & Neurodevelopmental Genetics Unit (PNGU) at Massachusetts General Hospital is working to identify and characterize the genetic basis of these disorders and offer hope for improving treatment and prevention strategies.

Current Research

The Psychiatric & Neurodevelopmental Genetics Unit is currently running a number of different studies. Contact us to learn about our research.

• Understanding the Connections Among Genes, Environment, Family Processes and Mental Health (The Nepal Study)
  This study, conducted in collaboration with the University of Michigan, aims to identify key predictors of psychiatric disorders in a large population-based sample of South Asian families and communities. This collaboration is part of an existing 20-year study comprised of 10,000 individuals from 2,700 households in various sub-population groups in Nepal. Through genome-wide genotyping and analyses, the role of polygenic risk scores (PRS) and genetic modifiers of environmental risk and resilience factors will be examined.
• Longitudinal Histories as Predictors of Future Suicide Attempts (FUSS)
  Through generous funding by The Fuss Family, in support of The Tommy Fuss Fund, this study aims to determine whether longitudinal data in electronic medical records can be used to predict future risk for suicide. A primary goal of this study has been to develop a medical informatics algorithm to be used as a decision support tool for clinicians. In order to adapt and validate this prediction tool, it is being tested using six diverse, independent, de-identified datasets within the Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS) network.
• Neural and Genetic Basis of Negative Valence Traits (rDOC)
  This study aims to characterize the neural and genetic basis of anxiety, focusing on a phenotype previously implicated in anxiety proneness involving the amygdala and medial pre-frontal cortex. This study builds on the Mass General Brain Genomic Superstruct Project, studying the effects of genes and genetic variation in brain structure and function.
• International Cohort Collection for Bipolar Disorder (ICCBD)
  The major goals of this project are to collect a large cohort of bipolar disorder cases and unaffected controls and construct a harmonized data source for genome-wide studies. The cohort will combine phenotypic data from the U.S. case-control sample with a parallel, separately funded European case-control sample.
• The Development and Neural Bases of Emotion Processing (NBE)
  This study, conducted in collaboration with Boston Children’s Hospital, aims to examine the brain systems that underlie recognizing emotion from facial expressions and other types of social cues among infants between 5 to 36 months old. The study hypothesizes that the functional maturation of amygdalocortical connections within the brain might account for the change in behavioral responses to fearful facial expressions.
• Brain Genomics: The Neural and Genetic Architecture of Mental Illness (Morphometricity)
  This study aims to develop a novel tool for prediction and prevention of psychiatric illness by estimating the proportion of observable variations in a trait that can be explained by brain morphology. Data collected as part of this study will be combined with existing data from the Mass General Scholars protocol to estimate the similarity between brain structure signatures, known as "cross disorder morphometricity."
• Gene Regulation and Linkage Analysis in Bipolar Disorder and Schizophrenia
  This study, conducted in collaboration with researchers at McLean Hospital, aims to identify genes associated with mood, anxiety and psychotic disorders through genetic association analyses

Software

MEGHA: Massively Expedited Genome-wide Heritability Analysis

MEGHA is a MATLAB toolbox for fast and flexible high-dimensional heritability analysis using genome-wide single nucleotide polymorphism (SNP) data from unrelated individuals, developed by Mass General's Psychiatric & Neurodevelopmental Genetics Unit. Learn more about it in the article "Massively Expedited Genome-wide Heritability Analysis (MEGHA),” published in the Proceedings of the National Academy of Sciences of the Unite States of America.

Download the program

For more information or help with the program, please contact Tian Ge (TGE1@partners.org).