Associations of circulating plasma microRNAs with age, body mass index and sex in a population-based study

BMC Medical Genomics

Uwe Völker²  Elke Hammer²  Georg Homuth¹  Nele Friedrich²  Maik Pietzner³  Karsten Suhre⁵  Volkmar Liebscher⁴  Carolin Malsch¹  Ravi Kumar Chilukoti¹  Tim Kacprowski¹  Sabine Ameling² 

[1] Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, , Friedrich-Ludwig-Jahn-Str. 15A, Greifswald, D-17475, Germany;DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany;Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany;Institute of Mathematics and Informatics, Ernst-Moritz-Arndt-University, Greifswald, Germany;Helmholtz Zentrum München, Germany, Research Centre for Environmental Health, Neuherberg, Germany

关键词: Blood;    Plasma;    Association studies;    miRNA;    Circulating microRNA;    Sex;    Age;    BMI;   

Others  :  1233862
DOI  :  10.1186/s12920-015-0136-7

 received in 2015-06-05, accepted in 2015-09-20,  发布年份 2015

【 摘 要 】

Background

Non-cellular blood circulating microRNAs (plasma miRNAs) represent a promising source for the development of prognostic and diagnostic tools owing to their minimally invasive sampling, high stability, and simple quantification by standard techniques such as RT-qPCR. So far, the majority of association studies involving plasma miRNAs were disease-specific case-control analyses. In contrast, in the present study, plasma miRNAs were analysed in a sample of 372 individuals from a population-based cohort study, the Study of Health in Pomerania (SHIP).

Methods

Quantification of miRNA levels was performed by RT-qPCR using the Exiqon Serum/Plasma Focus microRNA PCR Panel V3.M covering 179 different miRNAs. Of these, 155 were included in our analyses after quality-control. Associations between plasma miRNAs and the phenotypes age, body mass index (BMI), and sex were assessed via a two-step linear regression approach per miRNA. The first step regressed out the technical parameters and the second step determined the remaining associations between the respective plasma miRNA and the phenotypes of interest.

Results

After regressing out technical parameters and adjusting for the respective other two phenotypes, 7, 15, and 35 plasma miRNAs were significantly (q < 0.05) associated with age, BMI, and sex, respectively. Additional adjustment for the blood cell parameters identified 12 and 19 miRNAs to be significantly associated with age and BMI, respectively. Most of the BMI-associated miRNAs likely originate from liver. Sex-associated differences in miRNA levels were largely determined by differences in blood cell parameters. Thus, only 7 as compared to originally 35 sex-associated miRNAs displayed sex-specific differences after adjustment for blood cell parameters.

Conclusions

These findings emphasize that circulating miRNAs are strongly impacted by age, BMI, and sex. Hence, these parameters should be considered as covariates in association studies based on plasma miRNA levels. The established experimental and computational workflow can now be used in future screening studies to determine associations of plasma miRNAs with defined disease phenotypes.

【 授权许可】

   
2015 Ameling et al.

【 图 表 】

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

【 参考文献 】

• [1]Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004, 116(2):281-97.
• [2]Urbich C, Kuehbacher A, Dimmeler S: Role of microRNAs in vascular diseases, inflammation, and angiogenesis. Cardiovasc Res. 2008, 79(4):581-8.
• [3]Vickers KC, Palmisano BT, Shoucri BM, Shamburek RD, Remaley AT: MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat Cell Biol. 2011, 13(4):423-33.
• [4]Chen X, Liang H, Zhang J, Zen K, Zhang CY: Secreted microRNAs: a new form of intercellular communication. Trends Cell Biol. 2012, 22(3):125-32.
• [5]De Guire V, Robitaille R, Tetreault N, Guerin R, Menard C, Bambace N, et al.: Circulating miRNAs as sensitive and specific biomarkers for the diagnosis and monitoring of human diseases: promises and challenges. Clin Biochem. 2013, 46(10-11):846-60.
• [6]Keller A, Leidinger P, Bauer A, Elsharawy A, Haas J, Backes C, et al.: Toward the blood-borne miRNome of human diseases. Nat Methods 2011, 8(10):841-3.
• [7]Pescador N, Perez-Barba M, Ibarra JM, Corbaton A, Martinez-Larrad MT, Serrano-Rios M: Serum circulating microRNA profiling for identification of potential type 2 diabetes and obesity biomarkers. PLoS One 2013, 8(10):e77251.
• [8]Zampetaki A, Willeit P, Tilling L, Drozdov I, Prokopi M, Renard JM, et al.: Prospective study on circulating MicroRNAs and risk of myocardial infarction. J Am Coll Cardiol. 2012, 60(4):290-9.
• [9]Keller A, Leidinger P, Vogel B, Backes C, ElSharawy A, Galata V, et al.: miRNAs can be generally associated with human pathologies as exemplified for miR-144. BMC Med 2014, 12(1):224. BioMed Central Full Text
• [10]Beyer C, Zampetaki A, Lin NY, Kleyer A, Perricone C, Iagnocco A, et al.: Signature of circulating microRNAs in osteoarthritis. Ann Rheum Dis. 2015, 74(3):e18.
• [11]Nair VS, Pritchard CC, Tewari M, Ioannidis JP: Design and Analysis for Studying microRNAs in Human Disease: A Primer on -Omic Technologies. Am J Epidemiol. 2014, 180(2):140-52.
• [12]Hooten NN, Fitzpatrick M, Wood WH, De S, Ejiogu N, Zhang YQ, et al.: Age-related changes in microRNA levels in serum. Aging-Us 2013, 5(10):725-40.
• [13]Olivieri F, Spazzafumo L, Santini G, Lazzarini R, Albertini MC, Rippo MR, et al.: Age-related differences in the expression of circulating microRNAs: miR-21 as a new circulating marker of inflammaging. Mech Ageing Dev. 2012, 133(11-12):675-85.
• [14]Meder B, Backes C, Haas J, Leidinger P, Stahler C, Grossmann T, et al.: Influence of the confounding factors age and sex on microRNA profiles from peripheral blood. Clin Chem. 2014, 60(9):1200-8.
• [15]Mestdagh P, Hartmann N, Baeriswyl L, Andreasen D, Bernard N, Chen C, et al.: Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study. Nat Methods 2014, 11(8):809-15.
• [16]Volzke H, Alte D, Schmidt CO, Radke D, Lorbeer R, Friedrich N, et al.: Cohort profile: the study of health in Pomerania. Int J Epidemiol. 2011, 40(2):294-307.
• [17]Lefever S, Hellemans J, Pattyn F, Przybylski DR, Taylor C, Geurts R, et al.: RDML: structured language and reporting guidelines for real-time quantitative PCR data. Nucleic Acids Res. 2009, 37(7):2065-9.
• [18]R-Core-Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2014.. http://www.R-project.org/ webcite
• [19]Zhou X, Zhu W, Li H, Wen W, Cheng W, Wang F, et al.: Diagnostic value of a plasma microRNA signature in gastric cancer: a microRNA expression analysis. Sci Rep. 2015, 5:11251.
• [20]Starikova I, Jamaly S, Sorrentino A, Blondal T, Latysheva N, Sovershaev M, et al.: Differential expression of plasma miRNAs in patients with unprovoked venous thromboembolism and healthy control individuals. Thromb Res. 2015, 136(3):566-72.
• [21]Zou H, Hastie T: Regularization and variable selection via the elastic net. J R Statist Soc B 2005, 67(2):301-20.
• [22]Friedman J, Hastie T, Tibshirani R: Regularization Paths for Generalized Linear Models via Coordinate Descent. J Stat Softw. 2010, 33(1):1-22.
• [23]Cheng HH, Yi HS, Kim Y, Kroh EM, Chien JW, Eaton KD, et al.: Plasma processing conditions substantially influence circulating microRNA biomarker levels. PLoS One 2013, 8(6):e64795.
• [24]Pritchard CC, Kroh E, Wood B, Arroyo JD, Dougherty KJ, Miyaji MM, et al.: Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies. Cancer Prev Res (Phila) 2012, 5(3):492-7.
• [25]Olivieri F, Bonafe M, Spazzafumo L, Gobbi M, Prattichizzo F, Recchioni R, et al.: Age- and glycemia-related miR-126-3p levels in plasma and endothelial cells. Aging 2014, 6(9):771-87.
• [26]Hatse S, Brouwers B, Dalmasso B, Laenen A, Kenis C, Schoffski P, et al.: Circulating MicroRNAs as easy-to-measure aging biomarkers in older breast cancer patients: correlation with chronological age but not with fitness/frailty status. PLoS One 2014, 9(10):e110644.
• [27]Park S, Kang S, Min KH, Woo Hwang K, Min H: Age-associated changes in microRNA expression in bone marrow derived dendritic cells. Immunol Investig. 2013, 42(3):179-90.
• [28]Hackl M, Brunner S, Fortschegger K, Schreiner C, Micutkova L, Muck C, et al.: miR-17, miR-19b, miR-20a, and miR-106a are down-regulated in human aging. Aging Cell 2010, 9(2):291-6.
• [29]Bandiera S, Pfeffer S, Baumert TF, Zeisel MB: miR-122--a key factor and therapeutic target in liver disease. J Hepatol. 2015, 62(2):448-57.
• [30]Peng Y, Yu S, Li H, Xiang H, Peng J, Jiang S: MicroRNAs: emerging roles in adipogenesis and obesity. Cell Signal. 2014, 26(9):1888-96.
• [31]Starkey Lewis PJ, Dear J, Platt V, Simpson KJ, Craig DG, Antoine DJ, et al.: Circulating microRNAs as potential markers of human drug-induced liver injury. Hepatology 2011, 54(5):1767-76.
• [32]Waidmann O, Bihrer V, Pleli T, Farnik H, Berger A, Zeuzem S, et al.: Serum microRNA-122 levels in different groups of patients with chronic hepatitis B virus infection. J Viral Hepat. 2012, 19(2):e58-65.
• [33]van der Meer AJ, Farid WR, Sonneveld MJ, de Ruiter PE, Boonstra A, van Vuuren AJ, et al.: Sensitive detection of hepatocellular injury in chronic hepatitis C patients with circulating hepatocyte-derived microRNA-122. J Viral Hepat. 2013, 20(3):158-66.
• [34]Tan Y, Ge G, Pan T, Wen D, Gan J: A pilot study of serum microRNAs panel as potential biomarkers for diagnosis of nonalcoholic fatty liver disease. PLoS One 2014, 9(8):e105192.
• [35]Girard M, Jacquemin E, Munnich A, Lyonnet S, Henrion-Caude A: miR-122, a paradigm for the role of microRNAs in the liver. J Hepatol. 2008, 48(4):648-56.
• [36]Teruel-Montoya R, Kong X, Abraham S, Ma L, Kunapuli SP, Holinstat M, et al.: MicroRNA expression differences in human hematopoietic cell lineages enable regulated transgene expression. PLoS One 2014, 9(7):e102259.
• [37]Ambayya A, Su AT, Osman NH, Nik-Samsudin NR, Khalid K, Chang KM, et al.: Haematological reference intervals in a multiethnic population. PLoS One 2014, 9(3):e91968.
• [38]Murphy WG: The sex difference in haemoglobin levels in adults - mechanisms, causes, and consequences. Blood Rev. 2014, 28(2):41-7.
• [39]Zimmerman AL, Wu S: MicroRNAs, cancer and cancer stem cells. Cancer Lett. 2011, 300(1):10-9.
• [40]Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A, et al.: A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 2007, 129(7):1401-14.
• [41]Dai R, Ahmed SA: Sexual dimorphism of miRNA expression: a new perspective in understanding the sex bias of autoimmune diseases. Ther Clin Risk Manag. 2014, 10:151-63.