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脱咖啡因咖啡消费与神经精神疾病之间的共同遗传学及因果关系:一项大规模全基因组跨性状分析和孟德尔随机化分析

Shared Genetics and Causality Between Decaffeinated Coffee Consumption and Neuropsychiatric Diseases: A Large-Scale Genome-Wide Cross-Trait Analysis and Mendelian Randomization Analysis.

作者信息

Yin Bian, Wang Xinpei, Huang Tao, Jia Jinzhu

机构信息

Department of Biostatistics, School of Public Health, Peking University, Beijing, China.

Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China.

出版信息

Front Psychiatry. 2022 Jul 11;13:910432. doi: 10.3389/fpsyt.2022.910432. eCollection 2022.

Abstract

Coffee or caffeine consumption has been associated with neuropsychiatric disorders, implying a shared etiology. However, whether these associations reflect causality remains largely unknown. To understand the genetic structure of the association between decaffeinated coffee consumption (DCC) and neuropsychiatric traits, we examined the genetic correlation, causality, and shared genetic structure between DCC and neuropsychiatric traits using linkage disequilibrium score regression, bidirectional Mendelian randomization (MR), and genome-wide cross-trait meta-analysis in large GWAS Consortia for coffee consumption ( = 329,671) and 13 neuropsychiatric traits (sample size ranges from 36,052 to 500,199). We found strong positive genetic correlations between DCC and lifetime cannabis use (LCU; Rg = 0.48, = 8.40 × 10), alcohol use disorder identification test (AUDIT) total score (AUDIT_T; Rg = 0.40, = 4.63 × 10), AUDIT_C score (alcohol consumption component of the AUDIT; Rg = 0.40, = 5.26 × 10), AUDIT_P score (dependence and hazardous-use component of the AUDIT; Rg = 0.28, = 1.36 × 10), and strong negative genetic correlations between DCC and neuroticism (Rg = -0.15, = 7.27 × 10), major depressed diseases (MDD; Rg = -0.15, = 0.0010), and insomnia (Rg= -0.15, = 0.0007). In the cross-trait meta-analysis, we identified 6, 5, 1, 1, 2, 31, and 27 shared loci between DCC and Insomnia, LCU, AUDIT_T, AUDIT_C, AUDIT_P, neuroticism, and MDD, respectively, which were mainly enriched in bone marrow, lymph node, cervix, uterine, lung, and thyroid gland tissues, T cell receptor signaling pathway, antigen receptor-mediated signaling pathway, and epigenetic pathways. A large of TWAS-significant associations were identified in tissues that are part of the nervous system, digestive system, and exo-/endocrine system. Our findings further indicated a causal influence of liability to DCC on LCU and low risk of MDD (odds ratio: 0.90, = 9.06 × 10 and 1.27, = 7.63 × 10 respectively). We also observed that AUDIT_T and AUDIT_C were causally related to DCC (odds ratio: 1.83 per 1-SD increase in AUDIT_T, = 1.67 × 10, 1.80 per 1-SD increase in AUDIT_C, = 5.09 × 10). Meanwhile, insomnia and MDD had a causal negative influence on DCC (OR: 0.91, 95% CI: 0.86-0.95, = 1.51 × 10 for Insomnia; OR: 0.93, 95% CI: 0.89-0.99, = 6.02 × 10 for MDD). These findings provided evidence for the shared genetic basis and causality between DCC and neuropsychiatric diseases, and advance our understanding of the shared genetic mechanisms underlying their associations, as well as assisting with making recommendations for clinical works or health education.

摘要

饮用咖啡或摄入咖啡因与神经精神疾病有关,这意味着它们有共同的病因。然而,这些关联是否反映因果关系在很大程度上仍不清楚。为了了解脱咖啡因咖啡消费(DCC)与神经精神特质之间关联的遗传结构,我们使用连锁不平衡评分回归、双向孟德尔随机化(MR)以及在大型全基因组关联研究联盟中对咖啡消费(n = 329,671)和13种神经精神特质(样本量范围从36,052到500,199)进行全基因组跨性状荟萃分析,来研究DCC与神经精神特质之间的遗传相关性、因果关系和共享遗传结构。我们发现DCC与终生大麻使用(LCU;遗传相关系数Rg = 0.48,p = 8.40×10⁻⁸)、酒精使用障碍识别测试(AUDIT)总分(AUDIT_T;Rg = 0.40,p = 4.63×10⁻⁶)、AUDIT_C评分(AUDIT中的酒精消费成分;Rg = 0.40,p = 5.26×10⁻⁶)、AUDIT_P评分(AUDIT中的依赖和危险使用成分;Rg = 0.28,p = 1.36×10⁻⁴)之间存在强正遗传相关性,与神经质(Rg = -0.15,p = 7.27×10⁻²)、重度抑郁症(MDD;Rg = -0.15,p = 0.0010)和失眠(Rg = -0.15,p = 0.0007)之间存在强负遗传相关性。在跨性状荟萃分析中,我们分别在DCC与失眠、LCU、AUDIT_T、AUDIT_C、AUDIT_P、神经质和MDD之间鉴定出6、5、1、1、2、31和27个共享位点,这些位点主要富集于骨髓、淋巴结、子宫颈、子宫、肺和甲状腺组织、T细胞受体信号通路、抗原受体介导的信号通路以及表观遗传通路。在神经系统、消化系统和外分泌/内分泌系统的组织中鉴定出大量全转录组关联研究(TWAS)显著关联。我们的研究结果进一步表明DCC易感性对LCU有因果影响,对MDD风险较低(优势比分别为:0.90,p = 9.06×10⁻⁴和1.27,p = 7.63×10⁻³)。我们还观察到AUDIT_T和AUDIT_C与DCC存在因果关系(优势比:AUDIT_T每增加1个标准差为1.83,p = 1.67×10⁻⁴,AUDIT_C每增加1个标准差为1.80,p = 5.09×10⁻⁵)。同时,失眠和MDD对DCC有因果负影响(失眠的OR:0.91,95%置信区间:0.86 - 0.95,p = 1.51×10⁻⁴;MDD的OR:0.93,95%置信区间:0.89 - 0.99,p = 6.02×10⁻³)。这些发现为DCC与神经精神疾病之间的共享遗传基础和因果关系提供了证据,推进了我们对它们关联背后共享遗传机制的理解,并有助于为临床工作或健康教育提供建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f22e/9309364/051623a300fc/fpsyt-13-910432-g0001.jpg

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