Associations of Adiposity, Circulating Protein Biomarkers, and Risk of Major Vascular Diseases.
Associations of Adiposity, Circulating Protein Biomarkers, and Risk of Major Vascular Diseases.
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肥胖、循环蛋白生物标志物与主要血管疾病风险的关系
DOI：
10.1001/jamacardio.2020.6041
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发表时间：
2021-03-01
期刊：
影响因子：
24
通讯作者：
Chen Z
中科院分区：
文献类型：
--
作者：
Pang Y;Kartsonaki C;Lv J;Fairhurst-Hunter Z;Millwood IY;Yu C;Guo Y;Chen Y;Bian Z;Yang L;Chen J;Clarke R;Walters RG;Holmes MV;Li L;Chen Z
肥胖是否与循环蛋白质浓度的差异有关，这些蛋白质是否可能解释肥胖与心血管疾病风险的关系？在一项中国628例受试者的队列研究中，有证据表明体重指数与蛋白质生物标志物的遗传相关性与观察相关性一致，特别是白细胞介素-6、白细胞介素-18、单核细胞趋化蛋白-1、单核细胞趋化蛋白-3、TNF-相关凋亡诱导配体和肝细胞生长因子。这些蛋白质中有几种在观察上与心血管疾病的风险有关。在这项针对中国成年人的研究中，肥胖在横断面和遗传分析中与一系列蛋白质生物标志物相关，这可能部分解释了肥胖与心血管疾病之间的关联。这项针对中国成年人的亚队列研究考察了肥胖与蛋白质组学的观察和遗传关联，以及肥胖与心血管疾病的观察关联。肥胖与心血管疾病（CVD）的高风险相关，但对循环蛋白质生物标志物在这种关联中的作用知之甚少。研究肥胖与循环蛋白质生物标志物的观察和遗传相关性，以及蛋白质与CVD事件的观察相关性。该亚队列研究包括来自前瞻性中国嘉道理生物样本库的628名参与者，他们在基线时没有癌症病史。Olink平台测量了基线血浆样本中的92种蛋白质标志物。数据收集时间为2004年6月至2016年1月，分析时间为2019年1月至2020年6月。在基线调查期间获得的测量的体重指数（BMI）和使用571个外部加权单核苷酸变体推导的遗传仪器BMI。使用线性回归检查肥胖与生物标志物的横截面关联。使用考克斯回归分析评估基线时无癌症或CVD的患者中生物标志物与CVD风险的相关性。进行孟德尔随机化以推导BMI与生物标志物的遗传估计关联。在对628名个体的观察分析中，（平均[SD]年龄，52.2 [10.5]岁; 385例女性[61.3%]），BMI（平均值[SD]，23.9 [3.6]）与27种蛋白质呈正相关（BMI每升高1-SD;例如，白细胞介素-6：0.21 [95% CI，0.12-0.29] SD;白细胞介素-18：0.13 [95% CI，0.05-0.21] SD;单核细胞趋化蛋白-1：0.12 [95% CI，0.04-0.20] SD;肝细胞生长因子：0.31 [95% CI，0.24-0.39] SD），与3种蛋白质呈负相关（Fas配体：−0.11 [95%CI，−0.19至−0.03] SD; TNF相关弱凋亡诱导剂：−0.14 [95%CI，−0.23至−0.06] SD;碳酸酐酶9：（-0.14 [95%CI，-0.22 to-0.05] SD），与其他肥胖特征（例如腰围[r = 0.96]）的相关性相似。在孟德尔随机化中，遗传性BMI升高与特定蛋白质的相关性与观察相关性在方向上一致。在对遗传性BMI升高与8种蛋白质的荟萃分析中，结合目前的估计和以前的研究，显示了白细胞介素-6的最强关联（每1-SD较高的BMI; 0.21 [95% CI，0.13-0.29] SD），白细胞介素-18（0.16 [95% CI，0.06-0.26] SD），单核细胞趋化蛋白-1（0.21 [95% CI，0.11-0.30] SD），单核细胞趋化蛋白-3（0.12 [95% CI，0.03-0.21] SD），TNF相关凋亡诱导配体（0.23 [95% CI，0.13-0.32] SD）和肝细胞生长因子（0.14 [95% CI，0.06-0.22] SD）。在30种BMI相关生物标志物中，10种（包括白细胞介素-6、白细胞介素-18和肝细胞生长因子）与CVD事件名义上相关。孟德尔随机化显示肥胖与一系列蛋白质生物标志物相关，一些生物标志物也显示与CVD风险相关。未来的研究有必要验证这些发现，并评估蛋白质是否可能是肥胖和CVD之间的介质。
Is adiposity associated with differences in circulating protein concentrations, and might these proteins potentially explain the associations of adiposity with risk of cardiovascular disease? In a cohort study of 628 individuals in China, there was evidence of genetic associations of body mass index with protein biomarkers consistent with observational associations, particularly for interleukin-6, interleukin-18, monocyte chemoattractant protein–1, monocyte chemotactic protein–3, TNF-related apoptosis-inducing ligand, and hepatocyte growth factor. Several of these proteins were observationally associated with risk of incident cardiovascular disease. In this study of Chinese adults, adiposity was associated both cross-sectionally and through genetic analyses with a range of protein biomarkers, which might partly explain the association between adiposity and cardiovascular disease. This subcohort study of Chinese adults examines the observational and genetic associations of adiposity with proteomics and the observational associations of adiposity with cardiovascular disease. Obesity is associated with a higher risk of cardiovascular disease (CVD), but little is known about the role that circulating protein biomarkers play in this association. To examine the observational and genetic associations of adiposity with circulating protein biomarkers and the observational associations of proteins with incident CVD. This subcohort study included 628 participants from the prospective China Kadoorie Biobank who did not have a history of cancer at baseline. The Olink platform measured 92 protein markers in baseline plasma samples. Data were collected from June 2004 to January 2016 and analyzed from January 2019 to June 2020. Measured body mass index (BMI) obtained during the baseline survey and genetically instrumented BMI derived using 571 externally weighted single-nucleotide variants. Cross-sectional associations of adiposity with biomarkers were examined using linear regression. Associations of biomarkers with CVD risk were assessed using Cox regression among those without prior cancer or CVD at baseline. Mendelian randomization was conducted to derive genetically estimated associations of BMI with biomarkers. In observational analyses of 628 individuals (mean [SD] age, 52.2 [10.5] years; 385 women [61.3%]), BMI (mean [SD], 23.9 [3.6]) was positively associated with 27 proteins (per 1-SD higher BMI; eg, interleukin-6: 0.21 [95% CI, 0.12-0.29] SD; interleukin-18: 0.13 [95% CI, 0.05-0.21] SD; monocyte chemoattractant protein–1: 0.12 [95% CI, 0.04-0.20] SD; hepatocyte growth factor: 0.31 [95% CI, 0.24-0.39] SD), and inversely with 3 proteins (Fas ligand: −0.11 [95% CI, −0.19 to −0.03] SD; TNF-related weak inducer of apoptosis, −0.14 [95% CI, −0.23 to −0.06] SD; and carbonic anhydrase 9: (−0.14 [95% CI, −0.22 to −0.05] SD), with similar associations identified for other adiposity traits (eg, waist circumference [r = 0.96]). In mendelian randomization, the associations of genetically elevated BMI with specific proteins were directionally consistent with the observational associations. In meta-analyses of genetically elevated BMI with 8 proteins, combining present estimates with previous studies, the most robust associations were shown for interleukin-6 (per 1-SD higher BMI; 0.21 [95% CI, 0.13-0.29] SD), interleukin-18 (0.16 [95% CI, 0.06-0.26] SD), monocyte chemoattractant protein–1 (0.21 [95% CI, 0.11-0.30] SD), monocyte chemotactic protein–3 (0.12 [95% CI, 0.03-0.21] SD), TNF-related apoptosis-inducing ligand (0.23 [95% CI, 0.13-0.32] SD), and hepatocyte growth factor (0.14 [95% CI, 0.06-0.22] SD). Of the 30 BMI-associated biomarkers, 10 (including interleukin-6, interleukin-18, and hepatocyte growth factor) were nominally associated with incident CVD. Mendelian randomization shows adiposity to be associated with a range of protein biomarkers, with some biomarkers also showing association with CVD risk. Future studies are warranted to validate these findings and assess whether proteins may be mediators between adiposity and CVD.
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影响因子：
15.8
作者：
Danesh, John;Kaptoge, Stephen;Mann, Andrea G.;Sarwar, Nadeem;Wood, Angela;Angleman, Sara B.;Wensley, Frances;Higgins, Julian P. T.;Lennon, Lucy;Eiriksdottir, Gudny;Rumley, Ann;Whincup, Peter H.;Lowe, Gordon D. O.;Gudnason, Vilmundur
通讯作者：
Gudnason, Vilmundur
影响因子：
5.7
作者：
Bielinski, Suzette J.;Berardi, Cecilia;Tsai, Michael Y.
通讯作者：
Tsai, Michael Y.
影响因子：
9.8
作者：
Ahola-Olli, Ari V.;Wurtz, Peter;Raitakari, Olli T.
通讯作者：
Raitakari, Olli T.
DOI：
10.1136/bmj.k601
发表时间：
2018-07-12
期刊：
BMJ (Clinical research ed.)
影响因子：
--
作者：
Davies NM;Holmes MV;Davey Smith G
通讯作者：
Davey Smith G
影响因子：
11.2
作者：
Imayama I;Ulrich CM;Alfano CM;Wang C;Xiao L;Wener MH;Campbell KL;Duggan C;Foster-Schubert KE;Kong A;Mason CE;Wang CY;Blackburn GL;Bain CE;Thompson HJ;McTiernan A
通讯作者：
McTiernan A