Quick Links

Publications:

Gene expression in thiazide diuretic or statin users in relation to incident type 2 diabetes.

Authors: Astrid Suchy-Dicey|||Susan R Heckbert|||Nicholas L Smith|||Barbara McKnight|||Jerome I Rotter|||Yd Ida Chen|||Bruce M Psaty|||Daniel A Enquobahrie

Journal: International journal of molecular epidemiology and genetics

Publication Type: Journal Article

Date: 2014

DOI: PMC3939004

ID: 24596594

Affiliations:

Affiliations

    Department of Epidemiology, University of Washington Seattle, WA, USA.|||Department of Epidemiology, University of Washington Seattle, WA, USA ; Department of Pharmacy, University of Washington Seattle, WA, USA ; Group Health Research Institute, Group Health Cooperative Seattle, WA, USA.|||Department of Epidemiology, University of Washington Seattle, WA, USA ; Group Health Research Institute, Group Health Cooperative Seattle, WA, USA ; Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development Seattle, WA, USA.|||Department of Biostatistics, University of Washington Seattle, WA, USA.|||Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center Torrance, CA, USA.|||Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center Torrance, CA, USA.|||Department of Epidemiology, University of Washington Seattle, WA, USA ; Department of Health Services, University of Washington Seattle, WA, USA ; Department of Medicine, University of Washington Seattle, WA, USA ; Group Health Research Institute, Group Health Cooperative Seattle, WA, USA.|||Department of Epidemiology, University of Washington Seattle, WA, USA.

Abstract

Thiazide diuretics and statins are used to improve cardiovascular outcomes, but may also cause type 2 diabetes (T2DM), although mechanisms are unknown. Gene expression studies may facilitate understanding of these associations. Participants from ongoing population-based studies were sampled for these longitudinal studies of peripheral blood microarray gene expression, and followed to incident diabetes. All sampled subjects were statin or thiazide users. Those who developed diabetes during follow-up comprised cases (44 thiazide users; 19 statin users), and were matched to drug-using controls who did not develop diabetes on several factors. Supervised normalization, surrogate variable analyses removed technical bias and confounding. Differentially-expressed genes were those with a false discovery rate Q-value<0.05. Among thiazide users, diabetes cases had significantly different expression of CCL14 (down-regulated 6%, Q-value=0.0257), compared with controls. Among statin users, diabetes cases had marginal but insignificantly different expression of ZNF532 (up-regulated 15%, Q-value=0.0584), CXORF21 (up-regulated 11%, Q-value=0.0584), and ZNHIT3 (up-regulated 19%, Q-value=0.0959), compared with controls. These genes comprise potential targets for future expression or mechanistic research on medication-related diabetes development.


Reference List

    Barzilay JI, Davis BR, Cutler JA, Pressel SL, Whelton PK, Basile J, Margolis KL, Ong ST, Sadler LS, Summerson J ALLHAT Collaborative Research Group. Fasting glucose levels and incident diabetes mellitus in older nondiabetic adults randomized to receive 3 different classes of antihypertensive treatment: a report from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) Arch Intern Med. 2006;166:2191–201.|||Sattar N, Preiss D, Murray HM, Welsh P, Buckley BM, de Craen AJ, Seshasai SR, McMurray JJ, Freeman DJ, Jukema JW, Macfarlane PW, Packard CJ, Stott DJ, Westendorp RG, Shepherd J, Davis BR, Pressel SL, Marchioli R, Marfisi RM, Maggioni AP, Tavazzi L, Tognoni G, Kjekshus J, Pedersen TR, Cook TJ, Gotto AM, Clearfield MB, Downs JR, Nakamura H, Ohashi Y, Mizuno K, Ray KK, Ford I. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet. 2010;375:735–42.|||Padwal R, Laupacis A. Antihypertensive therapy and incidence of type 2 diabetes: a systematic review. Diabetes Care. 2004;27:247–55.|||Ghosh S, Dent R, Harper ME, Gorman SA, Stuart JS, McPherson R. Gene expression profiling in whole blood identifies distinct biological pathways associated with obesity. BMC Med Genomics. 2010;3:56.|||Diboun I, Wernisch L, Orengo CA, Koltzenburg M. Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma. BMC Genomics. 2006;7:252.|||Du P, Kibbe WA, Lin SM. lumi: a pipeline for processing Illumina microarray. Bioinformatics. 2008;24:1547–8.|||Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004;5:R80.|||Gentleman RHK. R 1.5 and the Bioconductor 1.0 releases. Comput Stat Data An. 2002;39:558–9.|||Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. 2012;28:882–3.|||Leek JT, Storey JD. Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genetics. 2007;3:1724–35.|||Mecham BH, Nelson PS, Storey JD. Supervised normalization of microarrays. Bioinformatics. 2010;26:1308–15.|||Lunceford JK, Chen G, Hu PH, Mehrotra DV. Evaluating surrogate variables for improving microarray multiple testing inference. Pharm Stat. 2011;10:302–10.|||Chatterjee R, Yeh HC, Shafi T, Selvin E, Anderson C, Pankow JS, Miller E, Brancati F. Serum and dietary potassium and risk of incident type 2 diabetes mellitus: The Atherosclerosis Risk in Communities (ARIC) study. Arch Intern Med. 2010;170:1745–51.|||Cooper-DeHoff RM, Wen S, Beitelshees AL, Zineh I, Gums JG, Turner ST, Gong Y, Hall K, Parekh V, Chapman AB, Boerwinkle E, Johnson JA. Impact of abdominal obesity on incidence of adverse metabolic effects associated with antihypertensive medications. Hypertension. 2010;55:61–8.|||Elliott WJ, Meyer PM. Incident diabetes in clinical trials of antihypertensive drugs: a network meta-analysis. Lancet. 2007;369:201–7.|||Feero WG, Guttmacher AE, Collins FS. Genomic medicine--an updated primer. N Engl J Med. 2010;362:2001–11.|||Lam SK, Owen A. Incident diabetes in clinical trials of antihypertensive drugs. Lancet. 2007;369:1513–4. author reply 4-5.|||Zillich AJ, Garg J, Basu S, Bakris GL, Carter BL. Thiazide diuretics, potassium, and the development of diabetes: a quantitative review. Hypertension. 2006;48:219–24.|||Stump CS, Hamilton MT, Sowers JR. Effect of antihypertensive agents on the development of type 2 diabetes mellitus. Mayo Clin Proc. 2006;81:796–806.|||Manrique C, Johnson M, Sowers JR. Thiazide diuretics alone or with beta-blockers impair glucose metabolism in hypertensive patients with abdominal obesity. Hypertension. 2010;55:15–7.|||Bozkurt O, de Boer A, Grobbee DE, de Leeuw PW, Kroon AA, Schiffers P, Klungel OH. Variation in Renin-Angiotensin system and salt-sensitivity genes and the risk of diabetes mellitus associated with the use of thiazide diuretics. Am J Hypertens. 2009;22:545–51.|||Moelants EA, Mortier A, Van Damme J, Proost P. In vivo regulation of chemokine activity by post-translational modification. Immunol Cell Biol. 2013;91:402–7.|||Siezen CL, Bont L, Hodemaekers HM, Ermers MJ, Doornbos G, Van’t Slot R, Wijmenga C, Houwelingen HC, Kimpen JL, Kimman TG, Hoebee B, Janssen R. Genetic susceptibility to respiratory syncytial virus bronchiolitis in preterm children is associated with airway remodeling genes and innate immune genes. Pediatr Infect Dis J. 2009;28:333–5.|||Vyshkina T, Sylvester A, Sadiq S, Bonilla E, Perl A, Kalman B. CCL genes in multiple sclerosis and systemic lupus erythematosus. J Neuroimmunol. 2008;200:145–52.|||Saku K, Harada R, Yamamoto K, Ying H, Ozaki I, Arakawa K. Apolipoprotein AI mRNA levels in WHHL rabbits. Atherosclerosis. 1990;84:73–4.|||Mann D, Reynolds K, Smith D, Muntner P. Trends in statin use and low-density lipoprotein cholesterol levels among US adults: impact of the 2001 National Cholesterol Education Program guidelines. Ann Pharmacother. 2008;42:1208–15.|||Mascitelli L, Pezzetta F, Goldstein MR. Statins and risk of incident diabetes. Lancet. 2010;375:2140–1. author reply 1-2.|||Ishikawa M, Okajima F, Inoue N, Motomura K, Kato T, Takahashi A, Oikawa S, Yamada N, Shimano H. Distinct effects of pravastatin, atorvastatin, and simvastatin on insulin secretion from a beta-cell line, MIN6 cells. J Atheroscler Thromb. 2006;13:329–35.|||Miraglia E, Hogberg J, Stenius U. Statins exhibit anticancer effects through modifications of the pAkt signaling pathway. Int J Oncol. 2012;40:867–75.|||Kimura K, Wakamatsu A, Suzuki Y, Ota T, Nishikawa T, Yamashita R, Yamamoto J, Sekine M, Tsuritani K, Wakaguri H, Ishii S, Sugiyama T, Saito K, Isono Y, Irie R, Kushida N, Yoneyama T, Otsuka R, Kanda K, Yokoi T, Kondo H, Wagatsuma M, Murakawa K, Ishida S, Ishibashi T, Takahashi-Fujii A, Tanase T, Nagai K, Kikuchi H, Nakai K, Isogai T, Sugano S. Diversification of transcriptional modulation: large-scale identification and characterization of putative alternative promoters of human genes. Genome Res. 2006;16:55–65.|||Shi Y, Chan DW, Jung SY, Malovannaya A, Wang Y, Qin J. A data set of human endogenous protein ubiquitination sites. Mol Cell Proteomics. 2011 May;10:M110.002089.|||Iwahashi H, Yamagata K, Yoshiuchi I, Terasaki J, Yang Q, Fukui K, Ihara A, Zhu Q, Asakura T, Cao Y, Imagawa A, Namba M, Hanafusa T, Miyagawa J, Matsuzawa Y. Thyroid hormone receptor interacting protein 3 (trip3) is a novel coactivator of hepatocyte nuclear factor-4alpha. Diabetes. 2002;51:910–4.|||Koppen A, Houtman R, Pijnenburg D, Jeninga EH, Ruijtenbeek R, Kalkhoven E. Nuclear receptor coregulator interaction profiling identifies TRIP3 as a novel peroxisome proliferator-activated receptor gamma cofactor. Mol Cell Proteomics. 2009 Oct;8:2212–26.|||Lee JW, Choi HS, Gyuris J, Brent R, Moore DD. Two classes of proteins dependent on either the presence or absence of thyroid hormone for interaction with the thyroid hormone receptor. Mol Endocrinol. 1995;9:243–54.|||Baker WL, Talati R, White CM, Coleman CI. Differing effect of statins on insulin sensitivity in non-diabetics: a systematic review and meta-analysis. Diabetes Res Clin Pract. 2010;87:98–107.|||Culver AL, Ockene IS, Balasubramanian R, Olendzki BC, Sepavich DM, Wactawski-Wende J, Manson JE, Qiao Y, Liu S, Merriam PA, Rahilly-Tierny C, Thomas F, Berger JS, Ockene JK, Curb JD, Ma Y. Statin use and risk of diabetes mellitus in postmenopausal women in the Women’s Health Initiative. Arch Intern Med. 2012;172:144–52.|||Moutzouri E, Liberopoulos E, Mikhailidis DP, Kostapanos MS, Kei AA, Milionis H, Elisaf M. Comparison of the effects of simvastatin vs. rosuvastatin vs. simvastatin/ezetimibe on parameters of insulin resistance. Int J Clin Pract. 2011;65:1141–8.