Analysis of overlapping genetic association in type 1 and type 2 diabetes.
Analysis of overlapping genetic association in type 1 and type 2 diabetes.
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1型和2型糖尿病重叠遗传关联分析。
DOI：
10.1007/s00125-021-05428-0
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发表时间：
2021-06
期刊：
影响因子：
8.2
通讯作者：
Todd JA
中科院分区：
文献类型：
--
作者：
Inshaw JRJ;Sidore C;Cucca F;Stefana MI;Crouch DJM;McCarthy MI;Mahajan A;Todd JA
考虑到1型糖尿病和2型糖尿病之间潜在的共同病因，我们的目标是确定与这两种疾病相关的任何遗传区域。对于存在共同信号且增加一种疾病风险的等位基因也会增加另一种疾病风险的关联，可以对共同的病因做出推断，有可能开发出同时治疗或预防这两种疾病的治疗策略。或者，如果一个遗传信号与不同的影响方向共同定位，它可能为这种联系如何以不同的方式影响这两种疾病提供有价值的生物学见解。使用对欧洲血统个体(74,124例和824,006名对照)进行的全基因组关联研究(GWAS)汇总分析中的公开可用的2型糖尿病汇总统计数据，以及对来自英国和撒丁岛的个人进行的荟萃分析(7467例和10,218对照)中的1型糖尿病汇总统计数据，我们确定了0.5Mb的所有区域包含与这两种疾病相关的变异(错误发现率和0.01)。在每个区域，我们进行前向逐步Logistic回归以识别独立的关联信号，然后使用COLC检查每个1型糖尿病信号与每个2型糖尿病信号的协同定位。任何与≥0.9后机率共定位的关联都被认为是与这两种疾病的真正共有关联。在来自42个遗传区域的81个与1型和2型糖尿病相关的关联信号中，有4个关联信号共同定位在两种疾病之间(后验概率≥为0.9%)：(1)16q23.1号染色体，靠近CTRB1/BCAR1型，先前已被识别；(2)染色体11p15.5，靠近INS基因；(3)染色体4p16.3，靠近TMEM129和(4)染色体1p31.3，靠近PGM1。在这些区域中的每个区域，基因变异对1型糖尿病的影响与对2型糖尿病的影响相反。使用额外的数据集也支持先前发现的在染色体9p24.2上靠近GLIS3基因的共定位，在这种情况下符合一致的效应方向。共同定位于1型糖尿病和2型糖尿病之间的五个关联信号中有四个方向相反，这表明这两种疾病之间存在复杂的遗传关系。网上版载有经同行审查但未经编辑的补充材料，可在10.1007/s00125-021-05428-0查阅。
Given the potential shared aetiology between type 1 and type 2 diabetes, we aimed to identify any genetic regions associated with both diseases. For associations where there is a shared signal and the allele that increases risk to one disease also increases risk to the other, inference about shared aetiology could be made, with the potential to develop therapeutic strategies to treat or prevent both diseases simultaneously. Alternatively, if a genetic signal co-localises with divergent effect directions, it could provide valuable biological insight into how the association affects the two diseases differently. Using publicly available type 2 diabetes summary statistics from a genome-wide association study (GWAS) meta-analysis of European ancestry individuals (74,124 cases and 824,006 controls) and type 1 diabetes GWAS summary statistics from a meta-analysis of studies on individuals from the UK and Sardinia (7467 cases and 10,218 controls), we identified all regions of 0.5 Mb that contained variants associated with both diseases (false discovery rate <0.01). In each region, we performed forward stepwise logistic regression to identify independent association signals, then examined co-localisation of each type 1 diabetes signal with each type 2 diabetes signal using coloc. Any association with a co-localisation posterior probability of ≥0.9 was considered a genuine shared association with both diseases. Of the 81 association signals from 42 genetic regions that showed association with both type 1 and type 2 diabetes, four association signals co-localised between both diseases (posterior probability ≥0.9): (1) chromosome 16q23.1, near CTRB1/BCAR1, which has been previously identified; (2) chromosome 11p15.5, near the INS gene; (3) chromosome 4p16.3, near TMEM129 and (4) chromosome 1p31.3, near PGM1. In each of these regions, the effect of genetic variants on type 1 diabetes was in the opposite direction to the effect on type 2 diabetes. Use of additional datasets also supported the previously identified co-localisation on chromosome 9p24.2, near the GLIS3 gene, in this case with a concordant direction of effect. Four of five association signals that co-localise between type 1 diabetes and type 2 diabetes are in opposite directions, suggesting a complex genetic relationship between the two diseases. The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-021-05428-0.
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影响因子：
30.8
作者：
Onengut-Gumuscu, Suna;Chen, Wei-Min;Burren, Oliver;Cooper, Nick J.;Quinlan, Aaron R.;Mychaleckyj, Josyf C.;Farber, Emily;Bonnie, Jessica K.;Szpak, Michal;Schofield, Ellen;Achuthan, Premanand;Guo, Hui;Fortune, Mary D.;Stevens, Helen;Walker, Neil M.;Ward, Lucas D.;Kundaje, Anshul;Kellis, Manolis;Daly, Mark J.;Barrett, Jeffrey C.;Cooper, Jason D.;Deloukas, Panos;Todd, John A.;Wallace, Chris;Concannon, Patrick;Rich, Stephen S.
通讯作者：
Rich, Stephen S.
影响因子：
30.8
作者：
Dooley J;Tian L;Schonefeldt S;Delghingaro-Augusto V;Garcia-Perez JE;Pasciuto E;Di Marino D;Carr EJ;Oskolkov N;Lyssenko V;Franckaert D;Lagou V;Overbergh L;Vandenbussche J;Allemeersch J;Chabot-Roy G;Dahlstrom JE;Laybutt DR;Petrovsky N;Socha L;Gevaert K;Jetten AM;Lambrechts D;Linterman MA;Goodnow CC;Nolan CJ;Lesage S;Schlenner SM;Liston A
通讯作者：
Liston A
影响因子：
30.8
作者：
Mahajan A;Taliun D;Thurner M;Robertson NR;Torres JM;Rayner NW;Payne AJ;Steinthorsdottir V;Scott RA;Grarup N;Cook JP;Schmidt EM;Wuttke M;Sarnowski C;Mägi R;Nano J;Gieger C;Trompet S;Lecoeur C;Preuss MH;Prins BP;Guo X;Bielak LF;Below JE;Bowden DW;Chambers JC;Kim YJ;Ng MCY;Petty LE;Sim X;Zhang W;Bennett AJ;Bork-Jensen J;Brummett CM;Canouil M;Ec Kardt KU;Fischer K;Kardia SLR;Kronenberg F;Läll K;Liu CT;Locke AE;Luan J;Ntalla I;Nylander V;Schönherr S;Schurmann C;Yengo L;Bottinger EP;Brandslund I;Christensen C;Dedoussis G;Florez JC;Ford I;Franco OH;Frayling TM;Giedraitis V;Hackinger S;Hattersley AT;Herder C;Ikram MA;Ingelsson M;Jørgensen ME;Jørgensen T;Kriebel J;Kuusisto J;Ligthart S;Lindgren CM;Linneberg A;Lyssenko V;Mamakou V;Meitinger T;Mohlke KL;Morris AD;Nadkarni G;Pankow JS;Peters A;Sattar N;Stančáková A;Strauch K;Taylor KD;Thorand B;Thorleifsson G;Thorsteinsdottir U;Tuomilehto J;Witte DR;Dupuis J;Peyser PA;Zeggini E;Loos RJF;Froguel P;Ingelsson E;Lind L;Groop L;Laakso M;Collins FS;Jukema JW;Palmer CNA;Grallert H;Metspalu A;Dehghan A;Köttgen A;Abecasis GR;Meigs JB;Rotter JI;Marchini J;Pedersen O;Hansen T;Langenberg C;Wareham NJ;Stefansson K;Gloyn AL;Morris AP;Boehnke M;McCarthy MI
通讯作者：
McCarthy MI
影响因子：
4.5
作者：
Wallace, Chris
通讯作者：
Wallace, Chris
影响因子：
9.8
作者：
Hormozdiari, Farhad;van de Bunt, Martijn;Eskin, Eleazar
通讯作者：
Eskin, Eleazar