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Dagostino, C.* ; De Gregori, M.* ; Gieger, C. ; Manz, J. ; Gudelj, I.* ; Lauc, G.* ; Divizia, L.* ; Wang, W.* ; Sim, M.* ; Pemberton, I.K.* ; MacDougall, J.* ; Williams, F.* ; Van Zundert, J.* ; Primorac, D.* ; Aulchenko, Y.* ; Kapural, L.* ; Allegri, M.*

Validation of standard operating procedures in a multicenter retrospective study to identify -omics biomarkers for chronic low back pain.

PLoS ONE 12:e0176372 (2017)

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Chronic low back pain (CLBP) is one of the most common medical conditions, ranking as the greatest contributor to global disability and accounting for huge societal costs based on the Global Burden of Disease 2010 study. Large genetic and -omics studies provide a promising avenue for the screening, development and validation of biomarkers useful for personalized diagnosis and treatment (precision medicine). Multicentre studies are needed for such an effort, and a standardized and homogeneous approach is vital for recruitment of large numbers of participants among different centres (clinical and laboratories) to obtain robust and reproducible results. To date, no validated standard operating procedures (SOPs) for genetic/-omics studies in chronic pain have been developed. In this study, we validated an SOP model that will be used in the multicentre (5 centres) retrospective "PainOmics" study, funded by the European Community in the 7th Framework Programme, which aims to develop new biomarkers for CLBP through three different -omics approaches: genomics, glycomics and activomics. The SOPs describe the specific procedures for (1) blood collection, (2) sample processing and storage, (3) shipping details and (4) cross-check testing and validation before assays that all the centres involved in the study have to follow. Multivariate analysis revealed the absolute specificity and homogeneity of the samples collected by the five centres for all genetics, glycomics and activomics analyses. The SOPs used in our multicenter study have been validated. Hence, they could represent an innovative tool for the correct management and collection of reliable samples in other large-omics-based multicenter studies.

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