The pharmacogenetics of type 2 diabetes: a systematic review.
The pharmacogenetics of type 2 diabetes: a systematic review.
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2型糖尿病的药物遗传学：系统评价。
DOI：
10.2337/dc13-1276
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发表时间：
2014
期刊：
影响因子：
16.2
通讯作者：
Clark JM
中科院分区：
文献类型：
--
作者：
Maruthur NM;Gribble MO;Bennett WL;Bolen S;Wilson LM;Balakrishnan P;Sahu A;Bass E;Kao WH;Clark JM
我们进行了一项系统回顾，以确定哪些遗传变异预测糖尿病药物的反应。我们对电子数据库（PubMed、EMBASE和科克伦数据库）进行了检索，并通过人工检索，以确定糖尿病药物对糖尿病前期或2型糖尿病的发病率、HbA 1c、空腹血糖和餐后血糖影响的原始纵向研究。两名研究者独立审查标题、摘要和文章。两名研究者按顺序提取数据并独立评估研究质量。质量评价是根据加强遗传关联研究报告准则和人类基因组流行病学网络指南进行的。在7,279篇引文中，我们纳入了34篇（N = 10,407）评价二甲双胍（n = 14）、磺脲类药物（n = 4）、瑞格列奈（n = 8）、吡格列酮（n = 3）、罗格列酮（n = 4）和阿卡波糖（n = 4）的文章。研究不是独立的随机对照试验，大多数评估糖尿病患者。血糖结局的显著药物-基因相互作用包括：1）二甲双胍与SLC 22 A1、SLC 22 A2、SLC 47 A1、PRKAB 2、PRKAA 2、PRKAA 1和STK 11基因座; 2）磺酰脲类药物与CYP 2C 9和TCF 7 L2基因座; 3）瑞格列奈与KCNJ 11、SLC 30 A8、NEUROD 1/BETA 2、UCP 2和PAX 4基因座; 4）吡格列酮与PPARG 2和PTPRD基因座; 5）罗格列酮和KCNQ 1和RBP 4基因座;和5）阿卡波糖和PPARA、HNF 4A、LIPC和PPARGC 1A基因座。数据不足以进行荟萃分析。我们发现二甲双胍、磺脲类、瑞格列奈、噻唑烷二酮类和阿卡波糖的药物遗传学相互作用的证据与其药代动力学和药效学一致。虽然仍然缺乏预先指定分析的高质量对照研究，但我们的结果使糖尿病个性化药物的承诺更接近实现。
We performed a systematic review to identify which genetic variants predict response to diabetes medications. We performed a search of electronic databases (PubMed, EMBASE, and Cochrane Database) and a manual search to identify original, longitudinal studies of the effect of diabetes medications on incident diabetes, HbA1c, fasting glucose, and postprandial glucose in prediabetes or type 2 diabetes by genetic variation. Two investigators reviewed titles, abstracts, and articles independently. Two investigators abstracted data sequentially and evaluated study quality independently. Quality evaluations were based on the Strengthening the Reporting of Genetic Association Studies guidelines and Human Genome Epidemiology Network guidance. Of 7,279 citations, we included 34 articles (N = 10,407) evaluating metformin (n = 14), sulfonylureas (n = 4), repaglinide (n = 8), pioglitazone (n = 3), rosiglitazone (n = 4), and acarbose (n = 4). Studies were not standalone randomized controlled trials, and most evaluated patients with diabetes. Significant medication–gene interactions for glycemic outcomes included 1) metformin and the SLC22A1, SLC22A2, SLC47A1, PRKAB2, PRKAA2, PRKAA1, and STK11 loci; 2) sulfonylureas and the CYP2C9 and TCF7L2 loci; 3) repaglinide and the KCNJ11, SLC30A8, NEUROD1/BETA2, UCP2, and PAX4 loci; 4) pioglitazone and the PPARG2 and PTPRD loci; 5) rosiglitazone and the KCNQ1 and RBP4 loci; and 5) acarbose and the PPARA, HNF4A, LIPC, and PPARGC1A loci. Data were insufficient for meta-analysis. We found evidence of pharmacogenetic interactions for metformin, sulfonylureas, repaglinide, thiazolidinediones, and acarbose consistent with their pharmacokinetics and pharmacodynamics. While high-quality controlled studies with prespecified analyses are still lacking, our results bring the promise of personalized medicine in diabetes one step closer to fruition.
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影响因子：
6.7
作者：
Kang, ES;Park, SY;Lee, HC
通讯作者：
Lee, HC
影响因子：
2.6
作者：
Gong L;Goswami S;Giacomini KM;Altman RB;Klein TE
通讯作者：
Klein TE
影响因子：
16.2
作者：
Feng Y;Mao G;Ren X;Xing H;Tang G;Li Q;Li X;Sun L;Yang J;Ma W;Wang X;Xu X
通讯作者：
Xu X
影响因子：
158.5
作者：
Florez, Jose C.;Jablonski, Kathleen A.;Altshuler, David
通讯作者：
Altshuler, David
影响因子：
16.2
作者：
Blüher, M;Lübben, GR;Paschke, R
通讯作者：
Paschke, R