Applying Novel Methods for Assessing Individual- and Neighborhood-Level Social and Psychosocial Environment Interactions with Genetic Factors in the Prediction of Depressive Symptoms in the Multi-Ethnic Study of Atherosclerosis

Erin B Ware; Jennifer A Smith; Bhramar Mukherjee; Seunggeun Lee; Sharon L R Kardia; Ana V Diez-Roux

doi:10.1007/s10519-015-9734-6

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Applying Novel Methods for Assessing Individual- and Neighborhood-Level Social and Psychosocial Environment Interactions with Genetic Factors in the Prediction of Depressive Symptoms in the Multi-Ethnic Study of Atherosclerosis

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Applying Novel Methods for Assessing Individual- and Neighborhood-Level Social and Psychosocial Environment Interactions with Genetic Factors in the Prediction of Depressive Symptoms in the Multi-Ethnic Study of Atherosclerosis

Erin B Ware, Jennifer A Smith, Bhramar Mukherjee, Seunggeun Lee, Sharon L R Kardia and Ana V Diez-Roux

Behavior genetics, v 46(1), pp 89-99

Jan 2016

DOI: https://doi.org/10.1007/s10519-015-9734-6

PMID: 26254610

Featured in Collection : UN Sustainable Development Goals @ Drexel

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Abstract

Aged

Atherosclerosis - etiology

Atherosclerosis - genetics

Atherosclerosis - psychology

Data Interpretation, Statistical

Depression - etiology

Depression - genetics

Depression - psychology

Depressive Disorder - etiology

Depressive Disorder - genetics

Ethnic Groups

Female

Gene-Environment Interaction

Genetic Association Studies - methods

Genetic Predisposition to Disease

Humans

Male

Middle Aged

Polymorphism, Single Nucleotide

Residence Characteristics

Complex illnesses, like depression, are thought to arise from the interplay between psychosocial stressors and genetic predispositions. Approaches that take into account both personal and neighborhood factors and that consider gene regions as well as individual SNPs may be necessary to capture these interactions across race and ethnic groups. We used novel gene-region based analysis methods [Sequence Kernel Association Test (SKAT) and meta-analysis (MetaSKAT), gene-environment set association test (GESAT)], as well as traditional linear models to identify gene region and SNP × psychosocial factor interactions at the individual- and neighborhood-level, across multiple race/ethnicities. Multiple regions identified in SKAT analyses showed evidence of a significant gene-region association with averaged depressive symptom scores across race/ethnicity (MetaSKAT p values <0.001). One region × neighborhood-environment interaction was significantly associated with averaged depressive symptom score across race/ethnicity after multiple testing correction (chr 18:21454070-21494070, Fisher's combined p value = 0.001). The examination of gene regions jointly with environmental factors measured at multiple levels (individuals and their contexts) may shed light on the etiology of depressive illness across race/ethnicities.

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7 citations in Web of Science

9 citations in Scopus

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Title: Applying Novel Methods for Assessing Individual- and Neighborhood-Level Social and Psychosocial Environment Interactions with Genetic Factors in the Prediction of Depressive Symptoms in the Multi-Ethnic Study of Atherosclerosis
Creators: Erin B Ware - University of Michigan–Ann Arbor
Jennifer A Smith - University of Michigan–Ann Arbor
Bhramar Mukherjee - University of Michigan–Ann Arbor
Seunggeun Lee - University of Michigan–Ann Arbor
Sharon L R Kardia - University of Michigan–Ann Arbor
Ana V Diez-Roux - Drexel University
Publication Details: Behavior genetics, v 46(1), pp 89-99
Publisher: Springer Nature
Grant note: N01HC95169 / NHLBI NIH HHS UL1-TR-000040 / NCATS NIH HHS N01HC95161 / NHLBI NIH HHS R01-HL-101161 / NHLBI NIH HHS N01HC95164 / NHLBI NIH HHS N01-HC-95169 / NHLBI NIH HHS N01HC95167 / NHLBI NIH HHS N02HL64278 / NHLBI NIH HHS N01HC95159 / NHLBI NIH HHS P60MD002249 / NIMHD NIH HHS N01-HC-95166 / NHLBI NIH HHS R00-HL-113164 / NHLBI NIH HHS N01HC95163 / NHLBI NIH HHS R00 HL113164 / NHLBI NIH HHS N01HC95166 / NHLBI NIH HHS N01-HC-95163 / NHLBI NIH HHS UL1 TR001079 / NCATS NIH HHS R01 HL071759 / NHLBI NIH HHS N01-HC-95168 / NHLBI NIH HHS N01-HC-95165 / NHLBI NIH HHS HL071759 / NHLBI NIH HHS N01HC95160 / NHLBI NIH HHS N01-HC-95162 / NHLBI NIH HHS UL1-TR-001079 / NCATS NIH HHS N01-HC-95159 / NHLBI NIH HHS P60 MD002249 / NIMHD NIH HHS N01HC95168 / NHLBI NIH HHS UL1 TR000040 / NCATS NIH HHS N01-HC-95161 / NHLBI NIH HHS N01-HC-95167 / NHLBI NIH HHS R01 HL101161 / NHLBI NIH HHS N01-HC-95164 / NHLBI NIH HHS N01HC95165 / NHLBI NIH HHS N01HC95162 / NHLBI NIH HHS
Resource Type: Journal article
Language: English
Academic Unit: Urban Health Collaborative
Web of Science ID: WOS:000368722300008
Scopus ID: 2-s2.0-84958150525
Other Identifier: 991019168713304721

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Collaboration types: Domestic collaboration
Web of Science research areas: Behavioral Sciences; Genetics & Heredity; Psychology, Multidisciplinary

Applying Novel Methods for Assessing Individual- and Neighborhood-Level Social and Psychosocial Environment Interactions with Genetic Factors in the Prediction of Depressive Symptoms in the Multi-Ethnic Study of Atherosclerosis

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Abstract

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UN Sustainable Development Goals (SDGs)

InCites Highlights

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