Xu Bohan, Forthman Katherine L, Kuplicki Rayus, Ahern Jonathan, Loughnan Robert, Naber Firas, Thompson Wesley K, Nemeroff Charles B, Paulus Martin P, Fan Chun Chieh
Population Neuroscience and Genetics Center, Laureate Institute for Brain Research, Tulsa, Oklahoma, USA.
Laureate Institute for Brain Research, Tulsa, Oklahoma, USA.
medRxiv. 2024 Jul 5:2024.07.03.24309914. doi: 10.1101/2024.07.03.24309914.
Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable economic and social burdens. The etiological factors contributing to TRD are complex and not fully understood.
To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits, and to explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us Research Program (AoU).
Data from 292,663 participants in the AoU were analyzed using a case-cohort design. Treatment resistant depression (TRD), treatment responsive Major Depressive Disorder (trMDD), and all others who have no formal diagnosis of Major Depressive Disorder (non-MDD) were identified through diagnostic codes and prescription patterns. Polygenic scores (PGS) for 61 unique traits from seven domains were used and logistic regressions were conducted to assess associations between PGS and TRD. Finally, Cox proportional hazard models were used to explore the predictive value of PGS for progression rate from the diagnostic event of Major Depressive Disorder (MDD) to TRD.
In the discovery set (104128 non-MDD, 16640 trMDD, and 4177 TRD), 44 of 61 selected PGS were found to be significantly associated with MDD, regardless of treatment responsiveness. Eleven of them were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia and specific neuroticism traits were associated with increased TRD risk (OR range from 1.05 to 1.15), while higher education and intelligence scores were protective (ORs 0.88 and 0.91, respectively). These associations are consistent across two other independent sets within AoU (n = 104,388 and 63,330). Among 28,964 individuals tracked over time, 3,854 developed TRD within an average of 944 days (95% CI: 883 ~ 992 days) after MDD diagnosis. All eleven previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD. Thus, those having higher education PGS would experiencing slower conversion rates than those who have lower education PGS with hazard ratios in 0.79 (80 versus 20 percentile, 95% CI: 0.74 ~ 0.85). Those who had higher insomnia PGS experience faster conversion rates than those who had lower insomnia PGS, with hazard ratios in 1.21 (80 versus 20 percentile, 95% CI: 1.13 ~ 1.30).
Our results indicate that genetic predisposition related to neuroticism, cognitive function, and sleep patterns play a significant role in the development of TRD. These findings underscore the importance of considering genetic and psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance our understanding of pathways leading to treatment resistance.
难治性抑郁症(TRD)是心理健康领域的一项重大挑战,影响着大量患者,并导致相当大的经济和社会负担。导致TRD的病因复杂,尚未完全明确。
利用多基因评分(PGS)研究与TRD相关的遗传因素,并使用来自“我们所有人”研究计划(AoU)的大规模基因组数据探讨其在TRD病因学中的潜在作用。
采用病例队列设计对AoU中292,663名参与者的数据进行分析。通过诊断编码和处方模式识别出难治性抑郁症(TRD)、治疗反应性重度抑郁症(trMDD)以及所有未被正式诊断为重度抑郁症的其他人(非MDD)。使用来自七个领域的61个独特性状的多基因评分(PGS),并进行逻辑回归以评估PGS与TRD之间的关联。最后,使用Cox比例风险模型探讨PGS对从重度抑郁症(MDD)诊断事件到TRD进展率的预测价值。
在发现集(104128名非MDD、16640名trMDD和4177名TRD)中,发现61个选定的PGS中有44个与MDD显著相关,无论治疗反应如何。其中11个与TRD的关联比与trMDD的关联更强,包括来自教育、认知、人格、睡眠和气质领域的PGS。失眠和特定神经质性状的遗传易感性与TRD风险增加相关(OR范围为1.05至1.15),而高等教育和智力得分具有保护作用(OR分别为0.88和0.91)。这些关联在AoU内的另外两个独立数据集(n = 104,388和63,330)中是一致的。在随时间追踪的28,964名个体中,3,854人在MDD诊断后的平均944天内(95% CI:883 ~ 992天)发展为TRD。所有先前确定并重复的11个PGS都被发现调节从MDD到TRD的转化率。因此,高等教育PGS的个体比低等教育PGS的个体转化率更低,风险比为0.79(第80百分位数与第20百分位数相比,95% CI:0.74 ~ 0.85)。高失眠PGS的个体比低失眠PGS的个体转化率更高,风险比为1.21(第80百分位数与第20百分位数相比,95% CI:1.13 ~ 1.30)。
我们的结果表明,与神经质、认知功能和睡眠模式相关的遗传易感性在TRD的发展中起重要作用。这些发现强调了在管理和治疗TRD时考虑遗传和社会心理因素的重要性。未来的研究应专注于将遗传数据与临床结果相结合,以加深我们对导致治疗抵抗的途径的理解。