@article {8057, title = {A polygenic risk score associated with measures of depressive symptoms among older adults.}, journal = {Biodemography Soc Biol}, volume = {60}, year = {2014}, note = {Times Cited: 0 SI 0}, month = {2014}, pages = {199-211}, publisher = {60}, abstract = {
It has been suggested that depression is a polygenic trait, arising from the influences of multiple loci with small individual effects. The aim of this study is to generate a polygenic risk score (PRS) to examine the association between genetic variation and depressive symptoms. Our analytic sample included N = 10,091 participants aged 50 and older from the Health and Retirement Study (HRS). Depressive symptoms were measured by Center for Epidemiological Studies-Depression scale (CESD) scores assessed on up to nine occasions across 18 years. We conducted a genome-wide association analysis for a discovery set (n = 7,000) and used the top 11 single-nucleotide polymorphisms, all with p < 10(-5) to generate a weighted PRS for our replication sample (n = 3,091). Results showed that the PRS was significantly associated with mean CESD score in the replication sample (β = .08, p = .002). The R(2) change for the inclusion of the PRS was .003. Using a multinomial logistic regression model, we also examined the association between genetic risk and chronicity of high (4+) CESD scores. We found that a one-standard-deviation increase in PRS was associated with a 36 percent increase in the odds of having chronically high CESD scores relative to never having had high CESD scores. Our findings are consistent with depression being a polygenic trait and suggest that the cumulative influence of multiple variants increases an individual{\textquoteright}s susceptibility for chronically experiencing high levels of depressive symptoms.
}, keywords = {Aged, Aged, 80 and over, Depressive Disorder, Major, Female, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Male, Middle Aged, Multifactorial Inheritance, Odds Ratio, Risk Factors}, issn = {1948-5573}, doi = {10.1080/19485565.2014.952705}, author = {Morgan E. Levine and Eileen M. Crimmins and Carol A Prescott and Drystan F. Phillips and Thalida E. Arpawong and Jinkook Lee} }