Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.
Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.
复制标题
四组2型糖尿病导致新诊断个体的病因学和临床异质性：IMI DIRECT研究
DOI：
10.1016/j.xcrm.2021.100477
复制
发表时间：
2022-01-18
期刊：
影响因子：
--
通讯作者：
IMI DIRECT Consortium
中科院分区：
文献类型：
--
作者：
Wesolowska-Andersen A;Brorsson CA;Bizzotto R;Mari A;Tura A;Koivula R;Mahajan A;Vinuela A;Tajes JF;Sharma S;Haid M;Prehn C;Artati A;Hong MG;Musholt PB;Kurbasic A;De Masi F;Tsirigos K;Pedersen HK;Gudmundsdottir V;Thomas CE;Banasik K;Jennison C;Jones A;Kennedy G;Bell J;Thomas L;Frost G;Thomsen H;Allin K;Hansen TH;Vestergaard H;Hansen T;Rutters F;Elders P;t'Hart L;Bonnefond A;Canouil M;Brage S;Kokkola T;Heggie A;McEvoy D;Hattersley A;McDonald T;Teare H;Ridderstrale M;Walker M;Forgie I;Giordano GN;Froguel P;Pavo I;Ruetten H;Pedersen O;Dermitzakis E;Franks PW;Schwenk JM;Adamski J;Pearson E;McCarthy MI;Brunak S;IMI DIRECT Consortium
2型糖尿病（T2D）的表现和基础病理生理学是复杂和异质的。最近的研究试图使用数据驱动的方法将T2D分层为不同的亚组，但如果复杂表型的分类表示是次优的，则其临床效用可能有限。我们应用软聚类（原型）方法来表征基于32个临床变量的新诊断的T2D。我们为个体分配定量聚类评分，并调查36个月内与血糖恶化、遗传风险评分、循环组学生物标志物和表型稳定性的相关性。四种原型谱代表了T2D病因学过程组合中的功能障碍模式，并与多种循环生物标志物相关。与肥胖、胰岛素抵抗、血脂异常和β细胞葡萄糖敏感性受损相关的一种原型对应于最快的疾病进展和最高的抗糖尿病治疗需求。我们证明了T2D的临床异质性可以映射到个体病因过程的异质性，为个性化治疗提供了一条潜在的途径。基于32种表型的软聚类识别出4种定量原型，这些反映了T2D病因学过程中功能障碍的不同模式。这四种原型在疾病进展、GRS和组学信号方面不同。将新诊断的T2D的临床异质性表示为反映疾病病因学过程中功能障碍模式的四种定量原型谱，而不是如其他人所尝试的将个体聚类为分类亚组。原型谱在遗传风险评分、疾病进展和循环组学生物标志物方面不同。
The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments. Soft clustering based on 32 phenotypes identified 4 quantitative archetypes These reflect different patterns of dysfunction across T2D etiological processes The four archetypes are different in disease progression, GRSs, and omics signals Some patients are dominated by one archetype, but many have etiological combinations Wesolowska-Andersen et al. represent the clinical heterogeneity of newly diagnosed T2D as four quantitative archetype profiles reflecting patterns of dysfunction in disease etiological processes, rather than clustering individuals into categorical subgroups as attempted by others. The archetype profiles differ in genetic risk scores, disease progression, and circulating omics biomarkers.
登录
查看更多内容
影响因子：
7.7
作者：
Floegel A;Stefan N;Yu Z;Mühlenbruch K;Drogan D;Joost HG;Fritsche A;Häring HU;Hrabě de Angelis M;Peters A;Roden M;Prehn C;Wang-Sattler R;Illig T;Schulze MB;Adamski J;Boeing H;Pischon T
通讯作者：
Pischon T
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：
7
作者：
Harrow J;Frankish A;Gonzalez JM;Tapanari E;Diekhans M;Kokocinski F;Aken BL;Barrell D;Zadissa A;Searle S;Barnes I;Bignell A;Boychenko V;Hunt T;Kay M;Mukherjee G;Rajan J;Despacio-Reyes G;Saunders G;Steward C;Harte R;Lin M;Howald C;Tanzer A;Derrien T;Chrast J;Walters N;Balasubramanian S;Pei B;Tress M;Rodriguez JM;Ezkurdia I;van Baren J;Brent M;Haussler D;Kellis M;Valencia A;Reymond A;Gerstein M;Guigó R;Hubbard TJ
通讯作者：
Hubbard TJ
影响因子：
8.2
作者：
Koivula, Robert W.;Forgie, Ian M.;Franks, Paul W.
通讯作者：
Franks, Paul W.
影响因子：
4.4
作者：
Hong, Mun-Gwan;Lee, Woojoo;Schwenk, Jochen M.
通讯作者：
Schwenk, Jochen M.