Pain Oliver, Hodgson Karen, Trubetskoy Vassily, Ripke Stephan, Marshe Victoria S, Adams Mark J, Byrne Enda M, Campos Adrian I, Carrillo-Roa Tania, Cattaneo Annamaria, Als Thomas D, Souery Daniel, Dernovsek Mojca Z, Fabbri Chiara, Hayward Caroline, Henigsberg Neven, Hauser Joanna, Kennedy James L, Lenze Eric J, Lewis Glyn, Müller Daniel J, Martin Nicholas G, Mulsant Benoit H, Mors Ole, Perroud Nader, Porteous David J, Rentería Miguel E, Reynolds Charles F, Rietschel Marcella, Uher Rudolf, Wigmore Eleanor M, Maier Wolfgang, Wray Naomi R, Aitchison Katherine J, Arolt Volker, Baune Bernhard T, Biernacka Joanna M, Bondolfi Guido, Domschke Katharina, Kato Masaki, Li Qingqin S, Liu Yu-Li, Serretti Alessandro, Tsai Shih-Jen, Turecki Gustavo, Weinshilboum Richard, McIntosh Andrew M, Lewis Cathryn M
Social, Genetic and Developmental Psychiatry Centre, King's College London, London, United Kingdom.
Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Medical Psychology, Berlin, Germany.
Biol Psychiatry Glob Open Sci. 2022 Apr;2(2):115-126. doi: 10.1016/j.bpsgos.2021.07.008.
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.
Genome-wide analysis of remission ( = 1852, = 3299) and percentage improvement ( = 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.
Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism-based heritability was significantly different from zero for remission ( = 0.132, SE = 0.056) but not for percentage improvement ( = -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 and as significantly associated with antidepressant response.
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.
抗抑郁药是抑郁症的一线治疗方法。然而,只有三分之一的患者在首次治疗后实现缓解。常见的基因变异可能在一定程度上调节抗抑郁反应,但先前全基因组关联研究的成功受到样本量的限制。本研究对重度抑郁症患者经前瞻性评估的抗抑郁反应进行了最大规模的基因分析,以深入了解其潜在生物学机制并实现样本外预测。
对缓解情况(n = 1852,m = 3299)和改善百分比(n = 5218)进行全基因组分析。使用全基因组复杂性状分析估计基于单核苷酸多态性的遗传力。使用多基因评分/AVENGEME估计与八种心理健康表型的遗传协方差。评估抗抑郁反应多基因评分的样本外预测。使用MAGMA和转录组范围关联研究进行基因水平关联分析。使用MAGMA估计组织、通路和药物结合富集情况。
两项全基因组关联研究均未发现全基因组显著关联。基于单核苷酸多态性的遗传力在缓解方面显著非零(h² = 0.132,SE = 0.056),但在改善百分比方面并非如此(h² = -0.018,SE = 0.032)。更好的抗抑郁反应与精神分裂症的遗传风险呈负相关,与受教育程度的遗传倾向呈正相关。抗抑郁反应多基因评分的留一法验证显示了样本外预测的显著证据,尽管外部队列的结果有所不同。基于基因的分析确定ANK3和CACNA1C与抗抑郁反应显著相关。
本研究表明,抗抑郁反应受常见基因变异影响,与精神分裂症和受教育程度存在遗传重叠,并为未来研究提供了有用资源。需要更大的样本量来发挥遗传学在理解和预测抗抑郁反应方面的潜力。