For nonadecanoate (19:0), we found no genome-wide significant association signals. The results of GWAS of 3-(4-hydroxyphenyl)lactate revealed a single genome-wide significant peak (P ≥ 10−9), which mapped to chromosome 17 between 77.67 and 77.77 Mbp. Of 9 SNPs genotyped in this region, 8 were in almost perfect LD (D′ ∼ 1, r2 > 0.99). Although the nearest gene is CCDC57, the SLC16A3 locus also lies in that region and is more likely to harbour the causal variant, as this gene is known to encode a protein that transports lactate and derivatives thereof.
Finally, all covariates significantly associated with CWP were included in a single multiple logistic regression model simultaneously to test their relative contribution to CWP risk (Table 3). In particular, we tested the independent association of genotyped SNP, rs10235235, which was virtually in perfect LD with our top but imputed SNP rs1581492. The analysis revealed that besides age and FMI, EAS, SNP rs10235235, and co-twin affection status (residual genetic effect) made major contributions to overall model significance (χ2(10) = 340.8, P << 0.001) and the prediction of CWP. When all 6 metabolites were tested simultaneously, only 3 remained significantly and independently associated with CWP. Of these, EAS was highly associated with CWP (P = 5.9 × 10−10) in a combined model including age, co-twin status, FMI, and SNPs (Table 3).
Taken together, the results suggested that EAS levels influence the development of CWP. To test this hypothesis, we performed a Mendelian randomization study of the lead genotyped SNP. If circulating levels of EAS genetically determined by rs10235235 are causally related to CWP, individuals carrying the rs10235235 C allele would be expected to have reduced EAS levels and a higher prevalence of CWP. In fact, our results showed that CWP prevalence among C allele carriers was lower compared with noncarriers (0.17 vs 0.21, P = 0.046). Conducting the 2 stage instrumental variable analysis using genotype-predicted EAS levels showed that predicted levels do not significantly influence the risk of CWP (β = 0.458 ± 0.239, P = 0.055), whereas EAS residuals, after adjustment for genotype effect and other covariates, were significantly associated with CWP (β = −0.512 ± 0.066, P = 2.01 × 10−14). These finding are consistent with EAS levels falling as a consequence of pain, rather than predisposing to it, determined by the genotype at 7q22.1. However, the presence of an unobserved confounding variable influencing the outcome of this analysis cannot be excluded.
Fibromyalgia is a highly prevalent health problem in the EU and USA comprising CWP, fatigue, and sleep disturbance.6 Chronic widespread musculoskeletal pain is recognised to coexist with other common pain states, and they are thought to share a genetic underlying predisposition.30 We used novel omics technologies to dissect the biological mechanisms underlying the CWP–BMI relationship. Our analysis, replicated in an independent sample, has shown that adiposity or FMI is the major mediating body composition factor. The associations we observed were consistently significant in the 2 data sets, despite differences in their phenotyping of both CWP and body composition. Metabolomic data analysis revealed joint independent associations between steroid hormones, FMI, and CWP in both TwinsUK and KORA cohorts with an inverse association of CWP risk with EAS—that is, the risk of CWP increasing with falling levels of EAS.
The use of metabolites as an intermediate phenotype in GWAS is providing a tractable approach to understanding better the genetic variants, and hence the pathways, involved in common complex traits.29 GWAS of EAS levels revealed multiple highly associated SNPs on chromosome 7q22.1 in TwinsUK, a finding that was replicated in KORA, providing robust evidence of a true association. The lead genotyped SNP rs10235235 explained 8% of the total variance of EAS, and it was our expectation that this represented a novel genomic locus predisposing to CWP. Note, however, that the inclusion of the top imputed SNP rs1581492, instead rs10235235, gives virtually the same result. Chromosome 7q22.1 is a gene-rich region and includes both the zinc finger gene ZNF789 and cytochrome p450 gene CYP3A5, which lies 0.3 Mbp upstream of the SNP (Fig. 2). The latter is known to be involved in intracellular drug metabolism11 and synthesis and breakdown of a variety of lipids including cholesterol and steroid hormones and so very likely has an influence on the androgen steroid metabolism pathway containing both dehydroepiandrosterone and its breakdown product, EAS. Mendelian randomization analysis, however, did not confirm that EAS lies in the causal pathway for CWP. Explanations for this include lack of power to detect a real effect: power for this analysis was estimated at 56%. Alternatively, there may be pleiotropic effects of SNP rs10235235 on CWP and EAS or else reverse causation: that CWP leads to reduced EAS levels. Finally, it is possible that other factors (genetic loci or epigenetic influences) could be responsible for this consistently observed correlation. Either way, falling EAS levels may represent a sensitive marker of chronic pain manifestation and has the potential greatly to assist in the clinical management of CWP.
There are a number of limitations of the study. Questions used to define the pain phenotype in the TwinsUK and KORA collections differed, as did the precise definition of CWP that was applied. This is a field of study where standardisation of phenotype is greatly needed; however, both samples have contributed to the successful GWAS meta-analysis of CWP,22 which was limited by similarly varied diagnostic criteria from among the many contributors. The advantage of using population cohorts is the availability of large sample sizes—which are essential in omic studies. With less well-defined conditions, the trade-off with phenotype consistency would serve to bias findings towards the null—and lessen the chance of positive findings or successful replication. TwinsUK has CWP prevalence high enough to provide informative case/control numbers, and the questions used were taken from a validated questionnaire (LFESSQ),32 whereas the CWP data for KORA consistently replicated the findings regardless of how the phenotype was defined (semiquantitative or dichotomous). Our findings are pertinent to chronic pain in the community as both TwinsUK and KORA are population samples. TwinsUK has been shown to be similar for common traits and outcomes to age-matched singleton women.2 These results might also extend to other chronic pain syndromes such as irritable bowel syndrome and chronic pelvic pain, and this needs to be investigated. Other limitations include the predominance of females in the TwinsUK sample, something that might be regarded as an advantage here as CWP is more prevalent in women. It is noteworthy that in KORA, a similar relationship between body composition and metabolites in men and women was observed—despite the use of a different method to determine body fat. These results suggest that our findings are robust and pertinent to both sexes.
To date, genetic studies of pain phenotypes have explored an array of candidate genes taken from putative and diverse biochemical pathways.9 By narrowing our focus to the association between CWP and BMI/body composition, we have shed light on possible neuroendocrine and central hormonal mechanisms that are shared between the 2 traits. The findings show that CWP influences EAS in a highly genotype-dependent manner, the specific nature of which remains to be established. It is possible that this effect is mediated by the cytochrome P450 enzyme 3A5, the gene, which is mapped to the genomic region highly associated with EAS variation. Further exploration of the chromosomal region is under way, and the use of EAS as a clinical biomarker in CWP and other chronic pain states will need to be assessed in independent samples.
The authors have no conflicts of interest to declare.
F. M.K. Williams is supported by funding from the Pain Relief Foundation and EU FP7 Pain_OMICS project.
The TwinsUK study was funded by the Wellcome Trust; European Community's Seventh Framework Programme (FP7/2007-2013). The study also receives support from 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. SNP Genotyping was performed by The Wellcome Trust Sanger Institute and National Eye Institute via NIH/CIDR. The study was also supported by Israel Science Foundation, Grant Nos. 994/10 and 1018/13. The KORA (Kooperative Gesundheitsforschung in der Region Augsburg) research platform and the MONICA Augsburg studies were initiated and financed by the Helmholtz Zentrum München National Research Center for Environmental Health, which is funded by the German Federal Ministry of Education, Science, Research and Technology and by the state of Bavaria. This study was supported by a grant from the German Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research (DZD). The German National Genome Research Network financed part of this work (NGFNPlus 01GS0823).
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