Presented By: Department of Psychology
Clinical Science Brown Bag: Polygenic Risk and Social Support in Predicting Depression Under Stress
Jennifer (Jenny) Cleary, MS, Clinical Science Doctoral Student
Abstract:
Depression is one of the leading causes of disability in US adults. Potential contributors to depressive symptoms have been identified at the genomic and environmental levels, though the mechanisms by which these factors independently and jointly influence depression risk remain unclear. Although the recent development of genomic technology has fueled substantial progress in identifying the genomic variation associated with major depression, genes alone do not fully predict who will develop depression. As responsivity to social support varies between individuals, sensitivity to the social environment may be one mechanism linking identified genomic variation and depressive symptoms. This talk will present the results of two studies assessing whether changes in social support affect the likelihood of depression development differently across the spectrum of genomic risk, and discuss implications for understanding depressive symptom etiology and clinical practice.
Depression is one of the leading causes of disability in US adults. Potential contributors to depressive symptoms have been identified at the genomic and environmental levels, though the mechanisms by which these factors independently and jointly influence depression risk remain unclear. Although the recent development of genomic technology has fueled substantial progress in identifying the genomic variation associated with major depression, genes alone do not fully predict who will develop depression. As responsivity to social support varies between individuals, sensitivity to the social environment may be one mechanism linking identified genomic variation and depressive symptoms. This talk will present the results of two studies assessing whether changes in social support affect the likelihood of depression development differently across the spectrum of genomic risk, and discuss implications for understanding depressive symptom etiology and clinical practice.
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