Influence of the Confounding Factors Age and Sex on MicroRNA Profiles from Peripheral Blood

Author:

Meder Benjamin123,Backes Christina4,Haas Jan12,Leidinger Petra4,Stähler Cord5,Großmann Thomas6,Vogel Britta1,Frese Karen1,Giannitsis Evangelos1,Katus Hugo A123,Meese Eckart4,Keller Andreas6

Affiliation:

1. Department of Internal Medicine III, University of Heidelberg, Heidelberg, Germany

2. DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany

3. Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg, Germany

4. Department of Human Genetics, Saarland University, Homburg, Germany

5. Siemens Healthcare, Erlangen, Germany

6. Clinical Bioinformatics, Saarland University, Saarbrucken, Germany

Abstract

Abstract BACKGROUND MicroRNAs (miRNAs) measured from blood samples are promising minimally invasive biomarker candidates that have been extensively studied in several case-control studies. However, the influence of age and sex as confounding variables remains largely unknown. METHODS We systematically explored the impact of age and sex on miRNAs in a cohort of 109 physiologically unaffected individuals whose blood was characterized by microarray technology (stage 1). We also investigated an independent cohort from a different institution consisting of 58 physiologically unaffected individuals having a similar mean age but with a smaller age distribution. These samples were measured by use of high-throughput sequencing (stage 2). RESULTS We detected 318 miRNAs that were significantly correlated with age in stage 1 and, after adjustment for multiple testing of 35 miRNAs, remained statistically significant. Regarding sex, 144 miRNAs showed significant dysregulation. Here, no miRNA remained significant after adjustment for multiple testing. In the high-throughput datasets of stage 2, we generally observed a smaller number of significant associations, mainly as an effect of the smaller cohort size and age distribution. Nevertheless, we found 7 miRNAs that were correlated with age, of which 5 were concordant with stage 1. CONCLUSIONS The age distribution of individuals recruited for case-control studies needs to be carefully considered, whereas sex may be less confounding. To support the translation of miRNAs into clinical application, we offer a web-based application (http://www.ccb.uni-saarland.de/mirnacon) to test individual miRNAs or miRNA signatures for their likelihood of being influenced.

Publisher

Oxford University Press (OUP)

Subject

Biochemistry (medical),Clinical Biochemistry

Reference18 articles.

1. Toward the blood-borne miRNome of human diseases;Keller;Nat Methods,2011

2. Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls;Keller;PLoS One,2009

3. Comprehensive analysis of microRNA profiles in multiple sclerosis including next-generation sequencing;Keller;Mult Scler,2013

4. A blood based 12-miRNA signature of Alzheimer disease patients;Leidinger;Genome Biol,2013

5. Specific peripheral miRNA profiles for distinguishing lung cancer from COPD;Leidinger;Lung Cancer,2011

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