TY - JOUR
T1 - Identifying the Common Genetic Basis of Antidepressant Response
AU - GSRD Consortium
AU - Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium
AU - Pain, Oliver
AU - Hodgson, Karen
AU - Trubetskoy, Vassily
AU - Ripke, Stephan
AU - Marshe, Victoria S.
AU - Adams, Mark J.
AU - Byrne, Enda M.
AU - Campos, Adrian I.
AU - Carrillo-Roa, Tania
AU - Cattaneo, Annamaria
AU - Als, Thomas D.
AU - Souery, Daniel
AU - Dernovsek, Mojca Z.
AU - Fabbri, Chiara
AU - Hayward, Caroline
AU - Henigsberg, Neven
AU - Hauser, Joanna
AU - Kennedy, James L.
AU - Lenze, Eric J.
AU - Lewis, Glyn
AU - Müller, Daniel J.
AU - Martin, Nicholas G.
AU - Mulsant, Benoit H.
AU - Mors, Ole
AU - Perroud, Nader
AU - Porteous, David J.
AU - Rentería, Miguel E.
AU - Reynolds, Charles F.
AU - Rietschel, Marcella
AU - Uher, Rudolf
AU - Wigmore, Eleanor M.
AU - Maier, Wolfgang
AU - Wray, Naomi R.
AU - Aitchison, Katherine J.
AU - Arolt, Volker
AU - Baune, Bernhard T.
AU - Biernacka, Joanna M.
AU - Bondolfi, Guido
AU - Domschke, Katharina
AU - Kato, Masaki
AU - Li, Qingqin S.
AU - Liu, Yu-Li
AU - Serretti, Alessandro
AU - Tsai, Shih-Jen
AU - Turecki, Gustavo
AU - Weinshilboum, Richard
AU - Kasper, Siegfried
AU - Abdellaoui, Abdel
AU - Derks, Eske M.
AU - Middeldorp, Christel M.
AU - Beekman, Aartjan T. F.
AU - Jansen, Rick
AU - Milaneschi, Yuri
AU - Peyrot, Wouter J.
AU - Posthuma, Danielle
AU - Schoevers, Robert
AU - Smit, Johannes H.
AU - de Geus, E. J. C.
AU - Penninx, Brenda W. J. H.
PY - 2022/4/1
Y1 - 2022/4/1
N2 - Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.
AB - Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85148554722&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/35712048
U2 - https://doi.org/10.1016/j.bpsgos.2021.07.008
DO - https://doi.org/10.1016/j.bpsgos.2021.07.008
M3 - Article
C2 - 35712048
SN - 2667-1743
VL - 2
SP - 115
EP - 126
JO - Biological Psychiatry Global Open Science
JF - Biological Psychiatry Global Open Science
IS - 2
ER -