Major depressive disorder (MDD) is common, with first onset.often in adolescence, recurrent into adulthood, a leading cause of disability woridwide, with a heritability pf 31-50%. It is widely accepted that MDD may involve a vulnerability to natural or experimental alterations in serotonin in certain individuals. Our overall contribution will be to understand how variation in genes and neurocircuitry related to serotonergic tone can modify the risk for MDD by taking advantage of a unique cohort of 3 generations of families at high/low risk for MDD. The cohort has been followed prospectively up to five times over 25 years. All assessments have been conducted blind to previous clinical history, diagnoses of other family members, and include extensive clinical data and biological markers. The design has allowed us to study high-risk populations prior to onset of illness, and thereby disentangle causal effects from compensatory mechanisms. We have clinical data on over 900 subjects, DNA on 307 subjects, structural/functional images on 216 subjects, and EEG on 234 subjects, resulting in the largest available sample of families with MDD who have biological markers. We have strong published clinical and MRI findings. We propose to further study this cohort. We will collect DNA on 150 additional subjects, first targeting subjects who already have MRI and/or EEG data, but not DNA, so that we can more comprehensively address how iserotonin-related genetic variation may lead to changes in brain morphology or function, and whether these changes might mediate the relationship between serotonin genes and MDD. We will expand the number of polymorphisms to test new candidates, and will test for gene by gene (epistatic) and gene by environment interactions. We will conduct focused gene-based genotyping in order to facilitate family-based tests of genetic association to the diagnostic, EEG, and MRI phenotypes collected in this sample. Additionally, we have over 3000 samples of subjects with MDD and about 3000 controls who have been genotyped and characterized whom we will use to follow up genetic findings. There are 4 aims: (1) To collect 150 new 3-generation samples and isolate genomic DNA, (2) to genotype 69 DNA variants in the 3-generation samples, (3) to examine the DNA variants with MDD and other related clinical phenotypes, with MRI, and with EEG phenotypes, and (4) to replicate the top 10% findings in available large genetic samples of MDD and controls. Our findings will be used to guide and generate hypotheses from the other Projects and will also test findings from the other Projects. We will contribute to the translational linking of population, clinical, and basic science and training of investigators in these links.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Specialized Center (P50)
Project #
Application #
Study Section
Special Emphasis Panel (ZMH1-ERB-M)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
New York State Psychiatric Institute
New York
United States
Zip Code
Spann, Marisa N; Serino, Dana; Bansal, Ravi et al. (2015) Morphological features of the neonatal brain following exposure to regional anesthesia during labor and delivery. Magn Reson Imaging 33:213-21
Horga, Guillermo; Kaur, Tejal; Peterson, Bradley S (2014) Annual research review: Current limitations and future directions in MRI studies of child- and adult-onset developmental psychopathologies. J Child Psychol Psychiatry 55:659-80
Polo-Kantola, Paivi; Lampi, Katja M; Hinkka-Yli-Salomaki, Susanna et al. (2014) Obstetric risk factors and autism spectrum disorders in Finland. J Pediatr 164:358-65
Goodman, Jarid; Marsh, Rachel; Peterson, Bradley S et al. (2014) Annual research review: The neurobehavioral development of multiple memory systems--implications for childhood and adolescent psychiatric disorders. J Child Psychol Psychiatry 55:582-610
Spann, Marisa N; Bansal, Ravi; Rosen, Tove S et al. (2014) Morphological features of the neonatal brain support development of subsequent cognitive, language, and motor abilities. Hum Brain Mapp 35:4459-74
Yan, Xu; Zhou, Minxiong; Ying, Lingfang et al. (2014) A fast schema for parameter estimation in diffusion kurtosis imaging. Comput Med Imaging Graph 38:469-80
Gyllenberg, David; Gissler, Mika; Malm, Heli et al. (2014) Specialized service use for psychiatric and neurodevelopmental disorders by age 14 in Finland. Psychiatr Serv 65:367-73
He, Xiaofu; Liu, Wei; Li, Xuzhou et al. (2014) Automated assessment of the quality of diffusion tensor imaging data using color cast of color-encoded fractional anisotropy images. Magn Reson Imaging 32:446-56
Yan, Xu; Zhou, Minxiong; Ying, Lingfang et al. (2013) Evaluation of optimized b-value sampling schemas for diffusion kurtosis imaging with an application to stroke patient data. Comput Med Imaging Graph 37:272-80
Talati, Ardesheer; Weissman, Myrna M; Hamilton, Steven P (2013) Using the high-risk family design to identify biomarkers for major depression. Philos Trans R Soc Lond B Biol Sci 368:20120129

Showing the most recent 10 out of 19 publications