Chronic widespread musculoskeletal pain (CWP) and frailty are prevalent conditions in older people. We have shown previously that interindividual variation in frailty and CWP is genetically determined. We also reported an association of frailty and CWP caused by shared genetic and common environmental factors. The aim of this study was to use omic approaches to identify molecular genetic factors underlying the heritability of frailty and its genetic correlation with CWP. Frailty was quantified through the Rockwood Frailty Index (FI) as a proportion of deficits from 33 binary health deficit questions in 3626 female twins. Common widespread pain was assessed using a screening questionnaire. OMICS analysis included 305 metabolites and whole-genome (.2.5 3 106 SNPs) and epigenome (;1 3 106 MeDIP-seq regions) assessments performed on fasting blood samples. Using family-based statistical analyses, including path analysis, we examined how FI scores were related to molecular genetic factors and to CWP, taking into account known risk factors such as fat mass and smoking. Frailty Index was significantly correlated with 51 metabolites after correction for multiple testing, with 20 metabolites having P-values between 2.1 3 1026 and 4.0 3 10216. Three metabolites (uridine, C-glycosyl tryptophan, and N-acetyl glycine) were statistically independent and thought to exert a direct effect on FI. Epiandrosterone sulphate, previously shown to be highly inversely associated with CWP, was found to exert an indirect influence on FI. Bioinformatics analysis of genome-wide association study and EWAS showed that FI and its covariation with CWP was through genomic regions involved in neurological pathways. Neurological pathway involvement accounts for the associated conditions of aging CWP and FI.

Multi-OMICS analyses of frailty and chronic widespread musculoskeletal pain suggest involvement of shared neurological pathways / G. Livshits, I. Malkin, R. Bowyer, S. Verdi, J. Bell, C. Menni, F. Williams, C. Steves. - In: PAIN. - ISSN 0304-3959. - 159:12(2018), pp. 2565-2572. [10.1097/j.pain.0000000000001364]

Multi-OMICS analyses of frailty and chronic widespread musculoskeletal pain suggest involvement of shared neurological pathways

C. Menni;
2018

Abstract

Chronic widespread musculoskeletal pain (CWP) and frailty are prevalent conditions in older people. We have shown previously that interindividual variation in frailty and CWP is genetically determined. We also reported an association of frailty and CWP caused by shared genetic and common environmental factors. The aim of this study was to use omic approaches to identify molecular genetic factors underlying the heritability of frailty and its genetic correlation with CWP. Frailty was quantified through the Rockwood Frailty Index (FI) as a proportion of deficits from 33 binary health deficit questions in 3626 female twins. Common widespread pain was assessed using a screening questionnaire. OMICS analysis included 305 metabolites and whole-genome (.2.5 3 106 SNPs) and epigenome (;1 3 106 MeDIP-seq regions) assessments performed on fasting blood samples. Using family-based statistical analyses, including path analysis, we examined how FI scores were related to molecular genetic factors and to CWP, taking into account known risk factors such as fat mass and smoking. Frailty Index was significantly correlated with 51 metabolites after correction for multiple testing, with 20 metabolites having P-values between 2.1 3 1026 and 4.0 3 10216. Three metabolites (uridine, C-glycosyl tryptophan, and N-acetyl glycine) were statistically independent and thought to exert a direct effect on FI. Epiandrosterone sulphate, previously shown to be highly inversely associated with CWP, was found to exert an indirect influence on FI. Bioinformatics analysis of genome-wide association study and EWAS showed that FI and its covariation with CWP was through genomic regions involved in neurological pathways. Neurological pathway involvement accounts for the associated conditions of aging CWP and FI.
Chronic pain; EWAS; Frailty; GWAS; Metabolite; Path analysis
Settore MEDS-24/A - Statistica medica
2018
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1099748
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