Metabolome-Genome-Wide Association Study (mGWAS) Reveals Novel Metabolites Associated with Future Type 2 Diabetes Risk and Susceptibility Loci in a Case-Control Study in a Chinese Prospective Cohort.
Metabolome-Genome-Wide Association Study (mGWAS) Reveals Novel Metabolites Associated with Future Type 2 Diabetes Risk and Susceptibility Loci in a Case-Control Study in a Chinese Prospective Cohort.
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全基因组代谢组关联研究 (mGWAS) 在中国前瞻性队列的病例对照研究中揭示了与未来 2 型糖尿病风险和易感性位点相关的新代谢物
DOI：
10.1002/gch2.202000088
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发表时间：
2021-04
期刊：
影响因子：
--
通讯作者：
Xu G
中科院分区：
文献类型：
--
作者：
Ouyang Y;Qiu G;Zhao X;Su B;Feng D;Lv W;Xuan Q;Wang L;Yu D;Wang Q;Lin X;Wu T;Xu G
在一项中国前瞻性队列中，选择 500 名 4.61 年内新发 2 型糖尿病（T2D）患者和 500 名匹配的健康参与者作为病例组和对照组，并随机分为发现组和验证组，以发现 T2D 发病前的代谢变化以及相关的糖尿病基因位点。血清代谢组学分析显示，81 种代谢物在 T2D 发病前发生显着变化。基于二元逻辑回归，八种代谢物被定义为 T2D 预测的生物标志物组。哌啶酸、肉碱 C14:0、肾上腺素和磷脂酰乙醇胺 34:2 首次被发现与未来的 T2D 相关。将生物标志物组添加到临床标志物（BMI、甘油三酯和空腹血糖）中，分别显着提高了发现集和验证集的预测能力。通过将代谢组学与基因组学相关联，观察到二十碳四烯酸和 FADS1 (rs174559) 基因之间存在显着相关性 (p < 5.0 × 10−8)，哌可林酸和 CHRM3 (rs535514) 以及亮氨酸/异亮氨酸和 WWOX 之间也存在提示相关性 (p < 5.0 × 10−6) （rs72487966）被发现。亮氨酸/异亮氨酸水平升高会增加患 T2D 的风险。总之，在 T2D 发病前观察到多种代谢失调发生，新的生物标志物组可以帮助预测 T2D 风险。在一项中国前瞻性队列中，选择了 500 名 4.61 年内新发 2 型糖尿病 (T2D) 患者和 500 名匹配的健康参与者。进行血清代谢组学分析，发现 81 种代谢物在 T2D 发病前发生显着变化。新的生物标志物组合有助于预测 T2D。发现基因 FADS1、CHRM3 和 WWOX 与 T2D 相关代谢物相关。
In a Chinese prospective cohort, 500 patients with new‐onset type 2 diabetes (T2D) within 4.61 years and 500 matched healthy participants are selected as case and control groups, and randomized into discovery and validation sets to discover the metabolite changes before T2D onset and the related diabetogenic loci. A serum metabolomics analysis reveals that 81 metabolites changed significantly before T2D onset. Based on binary logistic regression, eight metabolites are defined as a biomarker panel for T2D prediction. Pipecolinic acid, carnitine C14:0, epinephrine and phosphatidylethanolamine 34:2 are first found associated with future T2D. The addition of the biomarker panel to the clinical markers (BMI, triglycerides, and fasting glucose) significantly improves the predictive ability in the discovery and validation sets, respectively. By associating metabolomics with genomics, a significant correlation (p < 5.0 × 10−8) between eicosatetraenoic acid and the FADS1 (rs174559) gene is observed, and suggestive correlations (p < 5.0 × 10−6) between pipecolinic acid and CHRM3 (rs535514), and leucine/isoleucine and WWOX (rs72487966) are discovered. Elevated leucine/isoleucine levels increased the risk of T2D. In conclusion, multiple metabolic dysregulations are observed to occur before T2D onset, and the new biomarker panel can help to predict T2D risk. In a Chinese prospective cohort, 500 patients with new‐onset type 2 diabetes (T2D) within 4.61 years and 500 matched healthy participants are selected. A serum metabolomics analysis is performed and 81 metabolites are found to significantly change before T2D onset. The new biomarker panel helps to predict T2D. Gene FADS1, CHRM3, and WWOX are found to be associated with T2D‐related metabolites.
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DOI：
10.1002/hep.29561
发表时间：
2018-03
期刊：
Hepatology (Baltimore, Md.)
影响因子：
--
作者：
Luo P;Yin P;Hua R;Tan Y;Li Z;Qiu G;Yin Z;Xie X;Wang X;Chen W;Zhou L;Wang X;Li Y;Chen H;Gao L;Lu X;Wu T;Wang H;Niu J;Xu G
通讯作者：
Xu G
全基因组关联研究的荟萃分析确定了东亚人 2 型糖尿病的 8 个新位点
影响因子：
30.8
作者：
Cho, Yoon Shin;Chen, Chien-Hsiun;Hu, Cheng;Long, Jirong;Ong, Rick Twee Hee;Sim, Xueling;Takeuchi, Fumihiko;Wu, Ying;Go, Min Jin;Yamauchi, Toshimasa;Chang, Yi-Cheng;Kwak, Soo Heon;Ma, Ronald C. W.;Yamamoto, Ken;Adair, Linda S.;Aung, Tin;Cai, Qiuyin;Chang, Li-Ching;Chen, Yuan-Tsong;Gao, Yutang;Hu, Frank B.;Kim, Hyung-Lae;Kim, Sangsoo;Kim, Young Jin;Lee, Jeannette Jen-Mai;Lee, Nanette R.;Li, Yun;Liu, Jian Jun;Lu, Wei;Nakamura, Jiro;Nakashima, Eitaro;Ng, Daniel Peng-Keat;Tay, Wan Ting;Tsai, Fuu-Jen;Wong, Tien Yin;Yokota, Mitsuhiro;Zheng, Wei;Zhang, Rong;Wang, Congrong;So, Wing Yee;Ohnaka, Keizo;Ikegami, Hiroshi;Hara, Kazuo;Cho, Young Min;Cho, Nam H.;Chang, Tien-Jyun;Bao, Yuqian;Hedman, Asa K.;Morris, Andrew P.;McCarthy, Mark I.;Takayanagi, Ryoichi;Park, Kyong Soo;Jia, Weiping;Chuang, Lee-Ming;Chan, Juliana C. N.;Maeda, Shiro;Kadowaki, Takashi;Lee, Jong-Young;Wu, Jer-Yuarn;Teo, Yik Ying;Tai, E. Shyong;Shu, Xiao Ou;Mohlke, Karen L.;Kato, Norihiro;Han, Bok-Ghee;Seielstad, Mark
通讯作者：
Seielstad, Mark
影响因子：
3.6
作者：
Dow, Courtney;Mangin, Marie;Fagherazzi, Guy
通讯作者：
Fagherazzi, Guy
影响因子：
6.9
作者：
Mihalik, Stephanie J.;Goodpaster, Bret H.;Kelley, David E.;Chace, Donald H.;Vockley, Jerry;Toledo, Frederico G. S.;DeLany, James P.
通讯作者：
DeLany, James P.
影响因子：
16.2
作者：
Lu, Jieli;Lam, Sin Man;Wang, Weiqing
通讯作者：
Wang, Weiqing