Objective Low back pain (LBP) is a common musculoskeletal disorder, but it is still unclear which individuals develop it. The authors examined the contribution of genetic factors, lumbar disc degeneration (LDD) and other risk factors in a female sample of the general population. Material and Methods A cross-sectional study was conducted among 2256 women (371 and 698 monozygotic and dizygotic twin pairs and 29 sibling pairs and 60 singletons) with a mean age of 50 years (18–84). A self-reported validated questionnaire was used to collect back pain data. Risk factors including body weight, smoking, occupation, physical exercise and MRI assessed LDD were measured. Data analysis included logistic regression and variance decomposition. Results The major factors associated with LBP included genetic background, with OR approximately 6 if the monozygotic co-twin had LBP, or 2.2 if she was a dizygotic co-twin. In addition, LDD and overweight were highly significantly (p<0.001) associated with non-specific LBP. The single most important risk factor was the amount of LDD. After adjustment for other risk factors, the individuals who exhibited advanced LDD (90% vs 10%) had 3.2 higher odds of manifesting LBP. The data also showed a significant (p<0.001) genetic correlation between the LBP and LDD measurements, suggesting that approximately 11–13% of the genetic effects are shared by LDD and LBP. Conclusions The main risk factors for reported episodes of severe and disabling LBP in UK women include the degree of LDD as assessed by MRI, being overweight and genetic heritability.

Objective: There is a great need for identification of biomarkers that could improve the prediction of early osteoarthritis (OA). We undertook this study to determine whether circulating levels of interleukin‐6 (IL‐6), tumor necrosis factor α (TNFα), and C‐reactive protein (CRP) can serve as useful markers of radiographic knee OA (RKOA) in a normal human population.Methods: RKOA data were obtained from the cohort of the Chingford Study, a prospective population‐based study of healthy, middle‐aged British women. The RKOA‐affected status of the subjects was assessed using the Kellgren/Lawrence (K/L) grade as determined on radiographs obtained at baseline (n = 908) and at 10 years and 15 years thereafter. Serum levels of CRP, IL‐6, and TNFα were assayed at 5, 8, and 15 years, using high‐sensitivity commercial assays. A K/L grade of ≥2 in either knee was used as the outcome measure. Statistical analyses included analysis of variance for repeated measurements and logistic regression models, together with longitudinal modeling of dichotomous responses.Results: During 15 years of followup, the prevalence of RKOA (K/L grade ≥2) increased from 14.7% to 48.7% (P < 0.00001 versus baseline). The body mass index (BMI) and circulating levels of CRP and IL‐6 were consistently and significantly higher in subjects diagnosed as having RKOA. When multiple logistic regression was applied to the data, the variables of older age (P = 3.93 × 10⁻⁵), higher BMI at baseline (P = 0.0003), and increased levels of IL‐6 at year 5 (P = 0.0129) were determined to be independent predictors of the appearance of RKOA at year 10. The results were fully confirmed using longitudinal modeling of repeated measurements of the data obtained at 3 visits. The odds ratio for RKOA in subjects whose IL‐6 levels were in the fourth quartile of increasing levels (versus the first quartile) was 2.74 (95% confidence interval 1.94–3.87).Conclusion: This followup study showed that individuals were more likely to be diagnosed as having RKOA if they had a higher BMI and increased circulating levels of IL‐6. These results should stimulate more work on IL‐6 as a potential therapeutic target.

Recent genome-wide (GW) scans have identified several independent loci affecting human stature, but their contribution through the different skeletal components of height is still poorly understood. We carried out a genome-wide scan in 12,611 participants, followed by replication in an additional 7,187 individuals, and identified 17 genomic regions with GW-significant association with height. Of these, two are entirely novel (rs11809207 in CATSPER4, combined P-value = 6.1×10⁻⁸ and rs910316 in TMED10, P-value = 1.4×10⁻⁷) and two had previously been described with weak statistical support (rs10472828 in NPR3, P-value = 3×10⁻⁷ and rs849141 in JAZF1, P-value = 3.2×10⁻¹¹). One locus (rs1182188 at GNA12) identifies the first height eQTL. We also assessed the contribution of height loci to the upper- (trunk) and lower-body (hip axis and femur) skeletal components of height. We find evidence for several loci associated with trunk length (including rs6570507 in GPR126, P-value = 4×10⁻⁵ and rs6817306 in LCORL, P-value = 4×10⁻⁴), hip axis length (including rs6830062 at LCORL, P-value = 4.8×10⁻⁴ and rs4911494 at UQCC, P-value = 1.9×10⁻⁴), and femur length (including rs710841 at PRKG2, P-value = 2.4×10⁻⁵ and rs10946808 at HIST1H1D, P-value = 6.4×10⁻⁶). Finally, we used conditional analyses to explore a possible differential contribution of the height loci to these different skeletal size measurements. In addition to validating four novel loci controlling adult stature, our study represents the first effort to assess the contribution of genetic loci to three skeletal components of height. Further statistical tests in larger numbers of individuals will be required to verify if the height loci affect height preferentially through these subcomponents of height. The first genetic association studies of adult height have confirmed a role of many common variants in influencing human height, but to date, the genetic basis of differences between different skeletal components of height have not been addressed. Here, we take advantage of recent technical and methodological advances to examine the role of common genetic variants on both height and skeletal components of height. By examining nearly 20,000 individuals from the UK and the Netherlands, we provide statistically significant evidence that 17 genomic regions are associated with height, including four novel regions. We also examine, for the first time, the association of these 17 regions with skeletal size measurements of spine, femur, and hip axis length, a measurement of hip geometry known to influence the risk of osteoporotic fractures. We find that some height loci are also associated with these skeletal components, although further statistical tests will be required to verify if these genetic variants act differentially on the individual skeletal measurements. The knowledge generated by this and other studies will not only inform the genetics of human quantitative variation, but will also lead to the potential discovery of many medically important polymorphisms.