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孟德尔随机化研究表明,东亚人群的身体成分与抑郁之间存在潜在的特定环境因果关系。

Mendelian randomisation study of body composition and depression in people of East Asian ancestry highlights potential setting-specific causality.

机构信息

Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.

Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.

出版信息

BMC Med. 2023 Feb 1;21(1):37. doi: 10.1186/s12916-023-02735-8.

Abstract

BACKGROUND

Extensive evidence links higher body mass index (BMI) to higher odds of depression in people of European ancestry. However, our understanding of the relationship across different settings and ancestries is limited. Here, we test the relationship between body composition and depression in people of East Asian ancestry.

METHODS

Multiple Mendelian randomisation (MR) methods were used to test the relationship between (a) BMI and (b) waist-hip ratio (WHR) with depression. Firstly, we performed two-sample MR using genetic summary statistics from a recent genome-wide association study (GWAS) of depression (with 15,771 cases and 178,777 controls) in people of East Asian ancestry. We selected 838 single nucleotide polymorphisms (SNPs) correlated with BMI and 263 SNPs correlated with WHR as genetic instrumental variables to estimate the causal effect of BMI and WHR on depression using the inverse-variance weighted (IVW) method. We repeated these analyses stratifying by home location status: China versus UK or USA. Secondly, we performed one-sample MR in the China Kadoorie Biobank (CKB) in 100,377 participants. This allowed us to test the relationship separately in (a) males and females and (b) urban and rural dwellers. We also examined (c) the linearity of the BMI-depression relationship.

RESULTS

Both MR analyses provided evidence that higher BMI was associated with lower odds of depression. For example, a genetically-instrumented 1-SD higher BMI in the CKB was associated with lower odds of depressive symptoms [OR: 0.77, 95% CI: 0.63, 0.95]. There was evidence of differences according to place of residence. Using the IVW method, higher BMI was associated with lower odds of depression in people of East Asian ancestry living in China but there was no evidence for an association in people of East Asian ancestry living in the USA or UK. Furthermore, higher genetic BMI was associated with differential effects in urban and rural dwellers within China.

CONCLUSIONS

This study provides the first MR evidence for an inverse relationship between BMI and depression in people of East Asian ancestry. This contrasts with previous findings in European populations and therefore the public health response to obesity and depression is likely to need to differ based on sociocultural factors for example, ancestry and place of residence. This highlights the importance of setting-specific causality when using genetic causal inference approaches and data from diverse populations to test hypotheses. This is especially important when the relationship tested is not purely biological and may involve sociocultural factors.

摘要

背景

大量证据表明,较高的体重指数(BMI)与欧洲血统人群患抑郁症的几率较高有关。然而,我们对不同环境和血统之间的关系的理解是有限的。在这里,我们测试了东亚血统人群的身体成分与抑郁症之间的关系。

方法

使用多种孟德尔随机化(MR)方法来测试(a)BMI 和(b)腰围-臀围比(WHR)与抑郁症之间的关系。首先,我们使用最近一项关于东亚人群抑郁症的全基因组关联研究(GWAS)的两样本 MR 方法(15771 例病例和 178777 例对照)。我们选择了 838 个与 BMI 相关的单核苷酸多态性(SNP)和 263 个与 WHR 相关的 SNP 作为遗传工具变量,使用逆方差加权(IVW)方法估计 BMI 和 WHR 对抑郁症的因果效应。我们按家庭所在地进行分层,对这些分析进行了重复:中国与英国或美国。其次,我们在中国科大卫生物银行(CKB)的 100377 名参与者中进行了单样本 MR 分析。这使我们能够分别在(a)男性和女性以及(b)城市和农村居民中测试这种关系。我们还检查了(c)BMI 与抑郁之间关系的线性。

结果

两项 MR 分析都提供了证据表明,较高的 BMI 与较低的抑郁几率有关。例如,CKB 中遗传上增加 1 个标准差的 BMI 与较低的抑郁症状几率相关[OR:0.77,95%CI:0.63,0.95]。根据居住地的不同,存在差异的证据。使用 IVW 方法,居住在中国的东亚血统人群中较高的 BMI 与较低的抑郁几率相关,但居住在美国或英国的东亚血统人群中没有这种关联的证据。此外,较高的遗传 BMI 与中国城乡居民的差异效应相关。

结论

本研究首次提供了东亚血统人群中 BMI 与抑郁之间存在反比关系的 MR 证据。这与欧洲人群的先前发现形成对比,因此,肥胖和抑郁的公共卫生应对措施可能需要根据社会文化因素(例如,血统和居住地)而有所不同。这凸显了在使用遗传因果推断方法和来自不同人群的数据来测试假设时,特定于环境的因果关系的重要性。当测试的关系不仅仅是生物学上的关系,并且可能涉及社会文化因素时,这一点尤其重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1ca/9893684/3f0b5297573d/12916_2023_2735_Fig1_HTML.jpg

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