Division of Human Genetics

US Department of Veterans Affairs Career Development Award 2 (PI: Levey DF)
09/1/2021 – 08/30/2026
Investigating the Genomic Architecture of Anxiety and Overlap with Mental Health Disorders in the Million Veteran Program
The aims of this study are to identify risk loci in the autosomes, sex chromosomes and mitochondria for anxiety disorders in the context of the Million Veteran Program; and to conduct extensive post-GWAS analyses.

NIH/NIAAA P50AA012870 (PI: Gelernter J)
06/01/2021 – 05/31/2026
Translational Technologies Core - Center for the Translational Neuroscience of Alcoholism
The Translational Technologies Core will support and provide expertise related to genetics and neuroimaging throughout the Center.

MSCA-IF-GF 101028810 (PI: Koller D)
05/01/2021 – 04/30/2024
Distinguishing genetic overlap and causal relationship among attention deficit-hyperactivity disorder and substance use disorders
Using large-scale genome-wide association studies, we will test whether the epidemiological correlation between attention deficit-hyperactivity disorder and substance use disorders is due to shared risk alleles acting independently on both disorders or to causal effects between the disorders.

NIH/NIDA R01 DA054869 (MPIs: Agrawal A, Edenberg H, Gelernter J)
04/01/2021 – 01/31/2026
Psychiatric Genomics Consortium: Advancing Discovery and Impact
The aim is to expand the work of the Substance Use Disorder Workgroup of the Psychiatric Genomics Consortium so we can learn key lessons about the fundamental basis of substance use, abuse, and dependence and their comorbidities psychiatric disorders.

NIH/NIDA R33 DA047527 (PI: Polimanti R)
03/15/2021 – 01/31/2024
Investigating the Systems Genetics of the Patterns of Polysubstance Abuse and Addiction
The aim of this project is to investigate polysubstance use patterns using genome-wide polygenic risk scores of psychiatric disorders and behavioral traits.

NIH/NIDA R21 DA050160 (PI: Montalvo-Ortiz JL)
09/30/2020 – 08/31/2022
Integrative Epigenomic Mapping of Co-Morbid OUD and PTSD
The goal of this project is to gain a deeper understanding of the biological mechanisms involved in comorbid opioid use disorder (OUD) and post-traumatic stress disorder (PTSD) by investigating the neuronal epigenomic landscape in postmortem human brain.

NIH/NIMH F32MH122058 (PI: Wendt FR)
05/01/2020 – 04/30/2022
Decoding the Sex-Specific Biological Mechanisms of Psychiatric Disorders Using Genome-Wide Analyses
This proposal seeks to decipher the biological mechanisms that differ, or are similar, between males and females affected by psychiatric disorders using genome-wide data.

US Department of Veterans Affairs Career Development Award 2 (PI: Montalvo-Ortiz, JL)
01/01/2020 - 12/31/2024
Identifying Biomarkers of Post-traumatic Stress Disorder in U.S. Veterans Using An Integrative Multi-Omics Approach
This is a career development award to investigate the underlying biology of post-traumatic stress disorder (PTSD) trajectories of in U.S. Veterans. Multi-omics datasets will be integrated to identify biomarkers and gene networks associated with PTSD in this population.

NIH/NIDCD R21 DC018098 (PI: Polimanti R)
09/01/2019 – 08/31/2022
Genome-wide Investigation of the Interplay Between Age-Related Hearing Loss and Smoking Behaviors
The aim of this project is to conduct a large-scale genome-wide analysis of hearing loss and the interplay with smoking behaviors.

US Department of Veterans Affairs Merit Award (co-PI: Gelernter J and Stein M)
10/1/2018 – 9/30/2022
Genomics of PTSD and Related Traits
The aims of this study are to identify risk loci for PTSD and related traits in the context of the Million Veteran Program; and to conduct extensive post-GWAS analyses.

NIH/NIAAA R01AA026364 (PI: Gelernter J)
9/1/2018 – 8 /31/2023
Genetics of Alcohol Dependence in African Americans: Recruitment
Alcohol dependence (AD) in the United States is highly destructive and costly to individuals and to society. We previously conducted an AD research project focused on the understudied African-American (AA) population. Compared to most studies of European-ancestry subjects, studies to date of AAs have often been underpowered due to both inadequate sample size and insufficient genomewide coverage. Additional recruitment of AA AD subjects with a state-of-the-art assessment is necessary, and that is the goal of the present project. Deep phenotyping will make available other relevant related phenotypes.

NIH/NIDA R01DA037974 (PI: Gelernter J)
06/15/2015 – 03/31/2022
Identifying Methamphetamine Risk Variants by Extreme Phenotype Exome Sequencing
The identification of genes underlying the risk for methamphetamine addiction will shed light on the underlying causes of the disorder, and in turn, lead to improvements in our understanding and treatment, and ultimately prevention, of this devastating problem.

The members of the division meet every Tuesday at 2.30 pm to critically discuss a recent article including novel findings related to human genetics. Yale or VA affiliates interested but not currently members of the division are invited to join the Journal Club. Please contact one of the faculty to be included in the Journal club mailing list.

We are always looking forward to highly motivated individuals to join our division as postdoc and postgrad associates. The successful candidates will have the opportunity to be involved in research projects focused on the genetics of psychiatric disorders, behavioral phenotypes, and other complex traits, also including collaborative studies based on datasets from the Psychiatric Genomics Consortium, the Army Study to Assess Risk and Resilience in Servicemembers, the Million Veteran Project, and the UK Biobank. Interested individuals should contact one of the affiliated faculty to learn more about what opportunities we currently have to support potential trainees.

The participants recruited in the Yale-Penn cohort are assessed using Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA; PMID: 15896927, 17590536, 19371499, 20888699, 26048641). This is poly-diagnostic assessment with detailed ascertainment of all major DSM diagnoses, with the exception of eating disorders. The structured nature of the SSADDA permits its use by well-trained lay interviewers. Computer algorithms are used to make all DSM-IV or DSM-5 diagnoses based on the edited SSADDA interviews. The SSADDA is currently available in English, Thai, and Chinese. Scientists interested to use the SSADDA in their studies should contact Dr. Gelernter and Ms. Nunez.