Abstract 524: Impact of age, sex, smoking, body mass and physical activity on circulating small non-coding RNA expression profiles
Authors: Trine Ballestad Rounge, Sinan Ugur Umu, Andreas Keller, Eckart Meese, Giske Ursin, Steinar Tretli, Robert Lyle, Hilde Langseth
Journal: Cancer Research (2018)

Abstract Non-coding RNAs (ncRNA) are regulators of cell functions and circulating ncRNAs from the majority of the RNA classes, such as miRNA, tRNA, piRNAs, lncRNA, snoRNA, snRNA and miscRNAs, are potential non-invasive cancer biomarkers. Understanding how non-disease traits influence ncRNA expression is essential for assessing their biomarker potential. The aim of the study was to investigate associations between sex, age, smoking, body mass, physical activity, technical factors such as sample storage and processing, and serum ncRNA expression profiles. Serum samples from 526 healthy individuals in the Janus Serum Bank Cohort were included in the study. The samples were collected in the time-period 1972-2004 with varying collection procedures, and stored at - 25º C. Information on smoking habits, body mass and physical activity was linked from health examination survey data. RNA was extracted from 400 µl serum using phenol-chloroform separation and the miRNA Neasy Serum/Plasma kit (Qiagen). Small RNAseq was performed using NEBNext Small RNA Library Prep Set for Illumina with an average sequencing depth of 18 million reads per sample. The RNAseq reads were initially trimmed for adapters using Adapter Removal (v2.1.7). We then mapped the collapsed reads (generated by FASTX v0.14) to the human genome (hg38) using Bowtie2 (10 alignments per read were allowed). We compiled a comprehensive annotation set from miRBase (v21) for miRNAs, pirBAse (v1.0) for piRNAs, GENCODE (v26) for other RNAs and tRNAs. We used SeqBuster (v3.1) to get isomiR and miRNA profiles. To count the mapped reads, HTSeq (v0.7.2) was used. Differential gene expression analyses based on the negative binomial distribution and Wald significance tests were performed for each trait using the R package DESeq2 version 1.14.1. We identified associations between all RNA classes and traits. Ageing showed the strongest association with ncRNA expression, both in terms of statistical significance and number of RNAs, regardless of RNA class. Serum processing modifications and storage times significantly altered expression levels of a number of ncRNAs. Smoking cessation generally restored RNA expression to non-smoking levels, although for some isomiRs, mRNA fragments and tRNAs smoking-related expression levels persisted. sncRNA expression levels in serum are considerably age-dependent and age should be adjusted for in studies of circulating sncRNA expression. Certain biomarkers are also influenced by body mass, smoking, physical activity, serum processing and storage conditions. Citation Format: Trine Ballestad Rounge, Sinan Ugur Umu, Andreas Keller, Eckart Meese, Giske Ursin, Steinar Tretli, Robert Lyle, Hilde Langseth. Impact of age, sex, smoking, body mass and physical activity on circulating small non-coding RNA expression profiles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 524.