A Genome-Wide Association Study of Depressive Symptoms

作者:Hek Karin; Demirkan Ayse; Lahti Jari; Terracciano Antonio; Teumer Alexander; Cornelis Marilyn C; Amin Najaf; Bakshis Erin; Baumert Jens; Ding Jingzhong; Liu Yongmei; Marciante Kristin; Meirelles Osorio; Nalls Michael A; Sun Yan V; Vogelzangs Nicole; Yu Lei; Bandinelli Stefania; Benjamin Emelia J; Bennett David A; Boomsma Dorret; Cannas Alessandra; Coker Laura H; de Geus Eco; De Jager Philip L; Diez Roux Ana V; Purcell Shaun; Hu Frank B; Rimm Eric B
来源:Biological Psychiatry, 2013, 73(7): 667-678.
DOI:10.1016/j.biopsych.2012.09.033

摘要

Background: Depression is a heritable trait that exists on a continuum of varying severity and duration. Yet, the search for genetic variants associated with depression has had few successes. We exploit the entire continuum of depression to find common variants for depressive symptoms. %26lt;br%26gt;Methods: In this genome-wide association study, we combined the results of 17 population-based studies assessing depressive symptoms with the Center for Epidemiological Studies Depression Scale. Replication of the independent top hits (p %26lt; 1 x 10(-5)) was performed in five studies assessing depressive symptoms with other instruments. In addition, we performed a combined meta-analysis of all 22 discovery and replication studies. %26lt;br%26gt;Results: The discovery sample comprised 34,549 individuals (mean age of 66.5) and no loci reached genome-wide significance (lowest p = 1.05 x 10(-7)). Seven independent single nucleotide polymorphisms were considered for replication. In the replication set (n = 16,709), we found suggestive association of one single nucleotide polymorphism with depressive symptoms (rs161645, 5q21, p = 9.19 x 10(-3)). This 5q21 region reached genome-wide significance (p = 4.78 x 10(-8)) in the overall meta-analysis combining discovery and replication studies (n = 51,258). %26lt;br%26gt;Conclusions: The results suggest that only a large sample comprising more than 50,000 subjects may be sufficiently powered to detect genes for depressive symptoms.