Yin Liangying, Liu Menghui, Shi Yujia, Zhang Ruoyu, Lui Simom, So Hon-Cheong
School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
Eric and Wendy Schmidt Center, The Broad Institute of MIT and Harvard, USA.
Psychol Med. 2025 Sep 12;55:e270. doi: 10.1017/S0033291725101396.
Psychiatric disorders are highly heterogeneous. It is clinically valuable to distinguish psychiatric disorders by the presence or absence of a specific comorbid condition.
We employed a novel algorithm (CombGWAS) to decipher the genetic basis of psychiatric disorder combinations using genome-wide association studies summary statistics. We focused on comorbidities and combinations of diseases, such as schizophrenia (SCZ) with and without depression, which can be considered as two 'subtypes' of SCZ. We also studied psychiatric disorders comorbid with obesity as disease subtypes.
We compared the genetic architectures of psychiatric disorders with and without specific comorbidities, identifying both shared and unique susceptibility genes/variants across 8 subtype pairs (16 entities). Despite high genetic correlations between subtypes, most subtype pairs exhibited distinct genetic correlations with the same cardiovascular disease (CVD). Some pairs even displayed opposite genetic correlations, especially those involving obesity. For instance, the genetic correlation (rg) between SCZ with obesity and type 2 diabetes (T2DM) was 0.248 ( = 4.42E-28), while the rg between SCZ without obesity and T2DM was -0.154 ( = 6.79E-12). Mendelian randomization analyses revealed that comorbid psychiatric disorders often have stronger causal effects on cardiovascular risks compared to single disorders, but the effects vary across psychiatric subtypes. Notably, obese and nonobese major depressive disorder/SCZ showed opposite causal effects on the risks of T2DM.
Our study provides novel insights into the genetic basis of psychiatric disorder heterogeneity, revealing unique genetic signatures across various disorder combinations. Notably, comorbid psychiatric disorders often showed different causal relationships with CVD compared to single disorders.
精神疾病具有高度异质性。通过特定共病情况的存在与否来区分精神疾病具有临床价值。
我们采用了一种新算法（CombGWAS），利用全基因组关联研究汇总统计数据来解读精神疾病组合的遗传基础。我们关注疾病的共病情况和组合，例如伴有和不伴有抑郁症的精神分裂症（SCZ），可将其视为SCZ的两种“亚型”。我们还研究了与肥胖共病的精神疾病作为疾病亚型。
我们比较了伴有和不伴有特定共病的精神疾病的遗传结构，在8对亚型（16个实体）中识别出了共享和独特的易感基因/变异。尽管各亚型之间存在高度遗传相关性，但大多数亚型对与同一种心血管疾病（CVD）表现出不同的遗传相关性。有些对子甚至呈现相反的遗传相关性，尤其是那些涉及肥胖的对子。例如，伴有肥胖的SCZ与2型糖尿病（T2DM）之间的遗传相关性（rg）为0.248（P = 4.42E - 28），而不伴有肥胖的SCZ与T2DM之间的rg为 - 0.154（P = 6.79E - 12）。孟德尔随机化分析表明，与单一疾病相比，共病的精神疾病对心血管风险往往具有更强的因果效应，但效应在不同精神亚型中有所不同。值得注意的是，肥胖和非肥胖的重度抑郁症/精神分裂症对T2DM风险呈现相反的因果效应。
我们的研究为精神疾病异质性的遗传基础提供了新见解，揭示了不同疾病组合的独特遗传特征。值得注意的是，与单一疾病相比，共病的精神疾病与心血管疾病往往表现出不同的因果关系。
