慕尼黑大學(xué)Karsten Suhre等科學(xué)家發(fā)現(xiàn)了能導(dǎo)致脂質(zhì)代謝紊亂的多個(gè)基因變異,。這類基因基因變異常導(dǎo)致糖尿病的發(fā)生,。這項(xiàng)新的研究發(fā)現(xiàn)或許有助于科學(xué)家更好的了解糖尿病的發(fā)病機(jī)制以及臨床表現(xiàn)，從而達(dá)到更好的診斷和治療糖尿病的目的,。這篇研究報(bào)告發(fā)表在最近的Nature Genetics雜志上。
Karsten Suhre從九個(gè)不同基因中發(fā)現(xiàn)了與脂質(zhì)代謝紊亂相關(guān)的基因變異，并首次發(fā)現(xiàn)糖尿病風(fēng)險(xiǎn)基因MTNR1B和GCKR基因與脂質(zhì)代謝之間的聯(lián)系,。
該課題組首先確定1,800名實(shí)驗(yàn)參與者的血液樣本中163種代謝產(chǎn)物的濃度，然后對這些代謝產(chǎn)物進(jìn)行全基因組相關(guān)性研究,，尋找與某些常見的基因變異(如SNPs)之間可能的聯(lián)系,，再通過多次獨(dú)立重復(fù)試驗(yàn)驗(yàn)證。（生物谷Bioon.com）
生物谷推薦原始出處：
Nature Genetics 27 December 2009 | doi:10.1038/ng.507
A genome-wide perspective of genetic variation in human metabolism
Thomas Illig1,13, Christian Gieger1,13, Guangju Zhai2, Werner R?misch-Margl3, Rui Wang-Sattler1, Cornelia Prehn4, Elisabeth Altmaier3,5, Gabi Kastenmüller3, Bernet S Kato2, Hans-Werner Mewes3,6, Thomas Meitinger7,8, Martin Hrabé de Angelis4,9, Florian Kronenberg10, Nicole Soranzo2,11, H-Erich Wichmann1,12, Tim D Spector2, Jerzy Adamski4,9 & Karsten Suhre3,5
Serum metabolite concentrations provide a direct readout of biological processes in the human body, and they are associated with disorders such as cardiovascular and metabolic diseases. We present a genome-wide association study (GWAS) of 163 metabolic traits measured in human blood from 1,809 participants from the KORA population, with replication in 422 participants of the TwinsUK cohort. For eight out of nine replicated loci (FADS1, ELOVL2, ACADS, ACADM, ACADL, SPTLC3, ETFDH and SLC16A9), the genetic variant is located in or near genes encoding enzymes or solute carriers whose functions match the associating metabolic traits. In our study, the use of metabolite concentration ratios as proxies for enzymatic reaction rates reduced the variance and yielded robust statistical associations with P values ranging from 3 × 10?24 to 6.5 × 10?179. These loci explained 5.6%–36.3% of the observed variance in metabolite concentrations. For several loci, associations with clinically relevant parameters have been reported previously.
1 Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
2 Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
3 Institute of Bioinformatics and Systems Biology, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
4 Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
5 Faculty of Biology, Ludwig-Maximilians-Universit?t, Planegg-Martinsried, Germany.
6 Department of Genome Oriented Bioinformatics, Life and Food Science Center Weihenstephan, Technische Universit?t München, Freising-Weihenstephan, Germany.
7 Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
8 Institute of Human Genetics, Klinikum rechts der Isar, Technische Universit?t München, Munich, Germany.
9 Institute of Experimental Genetics, Life and Food Science Center Weihenstephan, Technische Universit?t München, Freising-Weihenstephan, Germany.
10 Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria.
11 The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK.
12 Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universit?t and Klinikum Grosshadern, Munich, Germany.
These authors contributed equally to this work.
