We conducted metabolic pathway analysis focusing on pathway enrichment analysis (http://www.metaboanalyst.ca/faces/home.xhtml). This analysis was conducted twice: first, the top 20 metabolites (Table 2) were tested. Next, 51 metabolites with P-value ≤0.0002 (corrected for multiple testing) were examined. In the first analysis, galactose, pyrimidine, arginine and proline, and D-glutamine and D-glutamate metabolism pathways were suggested, with P-values 0.014 to 0.046. In the second analysis, metabolic pathways of gluconeogenesis, galactose, taurine and hypotaurine, alanine, and some others were suggested, with P-values 0.002 to 0.033. After FDR correction, however, no significant metabolic pathways were identified.
A multiple linear regression model with additive genetic effect was applied to test for FI score–genotype association using ∼2.5 million genotyped and/or imputed autosomal SNPs. Other covariates adjusted in the model included age and relative fat mass. In addition, we similarly tested each of the metabolites associated with frailty phenotype. The results are presented as series of Manhattan plots (Figure S1 and Table S1, supplementary material 1, available at http://links.lww.com/PAIN/A639). Frailty Index showed no genome-wide significant associations, with top P-values ranging between the 10−3 and 10−4. Genome-wide association study of the 4 significantly associated metabolites showed a different pattern. Three of them, specifically uridine, N-AG, and EAS, displayed strong association with the single genomic region, with the top P-values correspondingly: <10−12 (Chr#22, mapped to 49304328-49318618bp, rs131794), <10−74 (Chr#2 mapped to 27596107-27584444bp, rs1260326) and <10−76 (Chr#7 mapped to 98994442-99024762bp, rs1581492). For variation of C-GT, we found no genome-wide significant associations.
Testing 723,029 lsBINs in 50 FI discordant MZ twin pairs (Gr1) implementing paired t tests revealed overall ND = 27,485 bins that showed nominally significant associations (P < 0.05), and of these, the top 20 association signals were ranged P = 7.01−5 to 2.17−6. Correlation analysis of lsBINs with FI scores in our main sample (Gr2) identified NM = 31,430 nominally significant correlations, with top 20 associations in a range between P = 3.76−5 and 4.02−6. The results of both analyses were combined by the Fisher test, which detected 27,781 nominally significant results showing the same direction of association in both study subsamples. The 20 top combined results are shown in Table S2 (supplementary material 1, available at http://links.lww.com/PAIN/A639). These data, as well as the GWAS data, were subjected to GO analysis (Tables S3–S5, in supplementary material, available at http://links.lww.com/PAIN/A639).
Because CWP and FI are highly associated with common shared genetic factors, we were interested whether and to what extent they shared multi-omic characteristics. We have reported the results of the OMICS analyses of the CWP elsewhere.12,14 They were compared with the present results. Of 4 metabolites significantly associated with FI score (Table 3), EAS and uridine were also significantly (P = 1.05−9 and P = 5.8−03, respectively, after adjustment for covariates) associated with CWP. Comparing the nominal significant results identified in a similar analysis design, we observed 2 potential common pathways: D-glutamine and D-glutamate metabolism and galactose metabolism pathways. However, they were not significant after FDR correction.
We examined a model including the direct and indirect effect of covariates on FI scores through CWP. In other words, we hypothesized that CWP manifestation could be an independent risk factor for worsening FI status of an individual and several studies suggest this sequence of relations between CWP and FI.29,30 First, using modified variance decomposition analysis testing the liability-threshold model of dichotomous variables,16 we examined the contribution of potential covariates (age, smoking, relative fat mass, EAS levels, and leading SNPs), on CWP. Next, implementing variance decomposition analysis, we estimated all possible direct and indirect effects of CWP manifestation and other covariates on FI scores variation. At this stage, the epigenome signals were not included in the analysis. Figure 2 summarizes the main results of path analysis showing that all tested covariates affect the CWP liability scores significantly. Although age, fat mass, and smoking increase the risk of CWP, EAS circulating levels decrease with raising of the CWP scores.
Evaluating all possible direct and indirect effects on FI scores, we observed that again almost all tested covariates (CWP, age, smoking, and relative fat mass but not EAS levels) exerted a significant effect on FI scores, with clear dominance of the CWP manifestation. Remarkably, when we added C-glycosyl tryptophan, N-acetyl glycine, and uridine to the analysis (identified as independently associated with FI scores (Table 3)), they contributed their independent association to FI (Fig. 2) while not altering other parameter estimates, and their own regression coefficients were virtually the same as reported in Table 3.
OMICS analyses identified 20 top metabolites associated with FI after correction for multiple testing (P < 0.0002, Table 2). However, the metabolites themselves are highly correlated and final multiple regression analysis revealed only 4 independently associated metabolites: EAS, C-glycosyl tryptophan, N-acetyl glycine, and uridine (Table 3). Although they represent different facets of human physiology, they seem to be relevant in view of the results obtained in present GWAS and EWAS of this sample, which also suggest involvement of genomic regions associated with the nervous system. Path analysis showed that the latter 3 metabolites were independently associated with frailty, whereas the effect of EAS seemed to be mediated through CWP. Epiandrosterone sulphate circulating levels showed no direct path correlation with FI (Fig. 2), but was highly significantly associated with CWP, which in turn was strongly related to FI.
Epiandrosterone sulphate is a major precursor of testosterone and estradiol and a potential neurosteroid (https://pubchem.ncbi.nlm.nih.gov/compound/epiandrosterone). In addition, EAS is involved in blood pressure regulation (through inhibition of the pentose phosphate pathway) and several other components of blood biochemistry, thus affecting blood circulation in the microvasculature. In our data set, unpublished analysis has also identified this metabolite to be associated with depression and anxiety. A causal role of CWP for FI has been suggested repeatedly in the literature in samples of diverse ethnicity;29,30 however, no clear potential mechanism of association was proposed. Our previous studies suggested involvement of neurological pathways in aetiology of CWP,14 and showed that its appearance significantly correlates with neuropathic pain features,20 and with fatigue and depression.3,9 This study further suggests that steroid pathways are involved in the mechanism of interaction between frailty and pain.
Overall, our data consistently point to the association of neurological pathway markers with progression of FI scores. The association between chronic pain and frailty may be mediated by alterations in sex hormone metabolism.
The authors have no conflict of interest to declare.
This work was supported by Arthritis Research UK Grant number 20682 to F.M.K. Williams, by the MRC AimHY (MR/M016560/1) project grant to C. Menni, by the HATS grant code WT081878MA to C.J. Steves, and by the Israel Science Foundation Grant number 1018/13 to G. Livshits. TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy's, and St Thomas' NHS Foundation Trust in partnership with King's College London. This study received ethics approval from the St. Thomas' Hospital Research Ethics Committee.
Supplemental digital content
Supplemental digital content associated with this article can be found online at http://links.lww.com/PAIN/A639.
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