Major depression (MD) accounts for substantial worldwide morbidity and mortality. Risk for MD is strongly influenced by genetic risk factors. This project seeks to elucidate the molecular basis of the genetic risk for MD by combining the rich phenotypic measures and sequence data from the CONVERGE (China, Oxford and VCU Experimental Research on Genetic Epidemiology) project. CONVERGE obtained detailed structured interviews on 6,000 Han Chinese women with recurrent MD and 6,000 ethically matched screened controls. Furthermore, in order to interrogate the genome more broadly and more deeply than is possible with genotyping arrays, genotypes will be obtained from low pass (LP) whole genome sequencing. In a sample of the size of CONVERGE, the design provides comprehensive measurement of common variation together with variants at minor allele frequencies below 1-2%, which are poorly imputed from microarray data. LP whole genome sequencing and variant calling will be completed in 2012 using external funding. An ancestry matched sample of 5,000 cases of MD and 5,000 controls is available for replication. We request 4 years of support to conduct i) clinical-phenotypic, ii) molecular-statistical analyses, including gene X environmental interaction analyses with verified environmental risk factors, and iii) replication analyses. In addition to our large sample size, the CONVERGE project has six design features which maximize the probability that we will be able to clarify the nature of the genetic risk factors for MD. We have recruited i) only women who are of ii) Han Chinese ancestry and who have had iii) recurrent illness. For these women, we have carefully assessed iv) four key environmental risk factors and v) a very rich phenotypic profile including important co-morbidities. Finally, our controls are relatively elderly and have been carefully screened to ensure a low liability to depressive illness. The identification of genetic variants which impact o risk for MD would open up the possibility of understanding the pathophysiology of this disorder and developing new methods of treatment and prevention.
Major depression (MD) accounts for substantial worldwide morbidity and mortality and is influence by genetic risk factors. We will elucidate the molecular basis of the genetic risk for MD by studying whole genome DNA sequence in a large sample of Chinese women with and without depression.
|Peterson, Roseann E; Cai, Na; Dahl, Andy W et al. (2018) Molecular Genetic Analysis Subdivided by Adversity Exposure Suggests Etiologic Heterogeneity in Major Depression. Am J Psychiatry 175:545-554|
|van Loo, H M; Van Borkulo, C D; Peterson, R E et al. (2018) Robust symptom networks in recurrent major depression across different levels of genetic and environmental risk. J Affect Disord 227:313-322|
|Kendler, Kenneth S; Aggen, Steven H; Flint, Jonathan et al. (2018) The centrality of DSM and non-DSM depressive symptoms in Han Chinese women with major depression. J Affect Disord 227:739-744|
|Edwards, A C; Docherty, A R; Moscati, A et al. (2018) Polygenic risk for severe psychopathology among Europeans is associated with major depressive disorder in Han Chinese women. Psychol Med 48:777-789|
|Cai, Na; Bigdeli, Tim B; Kretzschmar, Warren W et al. (2017) 11,670 whole-genome sequences representative of the Han Chinese population from the CONVERGE project. Sci Data 4:170011|
|Rappaport, L M; Flint, J; Kendler, K S (2017) Clarifying the role of neuroticism in suicidal ideation and suicide attempt among women with major depressive disorder. Psychol Med 47:2334-2344|
|Bigdeli, T B; Ripke, S; Peterson, R E et al. (2017) Genetic effects influencing risk for major depressive disorder in China and Europe. Transl Psychiatry 7:e1074|
|Docherty, Anna R; Edwards, Alexis C; Yang, Fuzhong et al. (2017) Age of onset and family history as indicators of polygenic risk for major depression. Depress Anxiety 34:446-452|
|Peterson, Roseann E; Cai, Na; Bigdeli, Tim B et al. (2017) The Genetic Architecture of Major Depressive Disorder in Han Chinese Women. JAMA Psychiatry 74:162-168|
|Bigdeli, T Bernard; Lee, Donghyung; Webb, Bradley Todd et al. (2016) A simple yet accurate correction for winner's curse can predict signals discovered in much larger genome scans. Bioinformatics 32:2598-603|
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