Back pain is a common and debilitating disorder with largely unknown underlying biology. Here we report a genome-wide association study of back pain using diagnoses assigned in clinical practice; dorsalgia (119,100 cases, 909,847 controls) and intervertebral disc disorder (IDD) (58,854 cases, 922,958 controls). We identify 41 variants at 33 loci. The most significant association (ORIDD = 0.92, P = 1.6 × 10−39; ORdorsalgia = 0.92, P = 7.2 × 10−15) is with a 3’UTR variant (rs1871452-T) in CHST3, encoding a sulfotransferase enzyme expressed in intervertebral discs. The largest effects on IDD are conferred by rare (MAF = 0.07 − 0.32%) loss-of-function (LoF) variants in SLC13A1, encoding a sodium-sulfate co-transporter (LoF burden OR = 1.44, P = 3.1 × 10−11); variants that also associate with reduced serum sulfate. Genes implicated by this study are involved in cartilage and bone biology, as well as neurological and inflammatory processes.

Genetic studies of disease progression can be used to identify factors that may influence survival or prognosis, which may differ from factors that influence on disease susceptibility. Studies of disease progression feed directly into therapeutics for disease, whereas studies of incidence inform prevention strategies. However, studies of disease progression are known to be affected by collider (also known as “index event”) bias since the disease progression phenotype can only be observed for individuals who have the disease. This applies equally to observational and genetic studies, including genome-wide association studies and Mendelian randomisation (MR) analyses. In this paper, our aim is to review several statistical methods that can be used to detect and adjust for index event bias in studies of disease progression, and how they apply to genetic and MR studies using both individual- and summary-level data. Methods to detect the presence of index event bias include the use of negative controls, a comparison of associations between risk factors for incidence in individuals with and without the disease, and an inspection of Miami plots. Methods to adjust for the bias include inverse probability weighting (with individual-level data), or Slope-Hunter and Dudbridge et al.’s index event bias adjustment (when only summary-level data are available). We also outline two approaches for sensitivity analysis. We then illustrate how three methods to minimise bias can be used in practice with two applied examples. Our first example investigates the effects of blood lipid traits on mortality from coronary heart disease, while our second example investigates genetic associations with breast cancer mortality.

Bone accrual impacts lifelong skeletal health, but genetic discovery has been hampered by cross-sectional study designs and uncertainty about target effector genes. Here, we captured this dynamic phenotype by modeling longitudinal bone accrual across 11,000 bone scans followed by genome-wide association studies (GWAS). We revealed 40 loci (35 novel), half residing in topological associated domains harboring known bone genes. Several of these loci also associated with fracture risk later in life. Variant-to-gene mapping identified contacts between GWAS loci and nearby gene promoters, and siRNA knockdown of gene expression clarified the putative effector gene at three specific loci in two osteoblast cell models. The resulting target genes highlight the cell fate decision between osteogenic and adipogenic lineages as important in normal bone accrual.

Musculoskeletal conditions, including fractures, can have severe and long-lasting consequences. Higher body mass index in adulthood is widely acknowledged to be protective for most fracture sites, indicated through previous clinical and epidemiological observational research. However, the association between weight and bone health is complex and sources of bias, induced by confounding factors, may have distorted earlier findings. Employing a lifecourse Mendelian randomization (MR) approach by using genetic instruments to separate effects at different life stages, this investigation aims to explore how prepubertal and adult body size independently influence fracture risk in later life. Using data from a large UK-based prospective cohort, univariable and multivariable MR with inverse variance weighted meta-analysis were conducted to simultaneously estimate the effects of age-specific genetic proxies for body size (n=453,169) on the odds of fracture in later life (n=416,795). A two-step MR framework was additionally applied to elucidate potential mediators. Univariable and multivariable MR indicated strong evidence that higher body size in childhood reduced fracture risk in later life (OR, 95% CI: 0.89, 0.82 to 0.96, P=0.005 and OR, 95% CI: 0.76, 0.69 to 0.85, P=1x10-6, respectively). Conversely, higher body size in adulthood increased fracture risk (OR, 95% CI: 1.08, 1.01 to 1.16, P=0.023 and OR, 95% CI: 1.26, 1.14 to 1.38, P=2x10-6, respectively). Two-step MR analyses suggested that the effect of higher body size in childhood on reduced fracture risk was mediated by its influence on higher estimated bone mineral density (eBMD) in adulthood. This investigation provides novel evidence that higher body size in childhood has a direct effect on reduced fracture risk in later life through its influence on increased eBMD. Results indicate that higher body size in adulthood is a risk factor for fractures, opposing findings from earlier research. Protective effect estimates previously observed are likely attributed to childhood effects.

BackgroundPerinatally-acquired HIV infection commonly causes stunting in children, but how this affects bone and muscle development is unclear. We investigated differences in bone and muscle mass and muscle function between children with HIV (CWH) and uninfected children.SettingCross-sectional study of CWH (6–16 years) receiving antiretroviral therapy (ART) for >6 months and children in the same age-group testing HIV-negative at primary health clinics in Zimbabwe.MethodsFrom Dual-energy X-ray Absorptiometry (DXA) we calculated total-body less-head (TBLH) Bone Mineral Content (BMC) for lean mass adjusted-for-height (TBLH-BMCLBM) Z-scores, and lumbar spine (LS) Bone Mineral Apparent Density (BMAD) Z-scores.ResultsThe 97 CWH were older (mean age 12.7 vs. 10.0 years) and therefore taller (mean height 142cm vs. 134cm) than those 77 uninfected. However, stunting (height-for-age Z-score≤-2) was more prevalent in CWH (35% vs. 5%, p<0.001). Amongst CWH, 15% had low LS-BMAD (Z-score ≤-2) and 13% had low TBLH-BMCLBM, vs. 1% and 3% respectively in those uninfected (both p≤0.02). After age, sex, height and puberty adjustment, LS-BMAD was 0.33 SDs (95%CI −0.01, 0.67; p=0.06) lower in CWH, with no differences in TBLH-BMCLBM, lean mass or grip strength by HIV status. However, there was a strong relationship between age at ART initiation and both LS-BMAD Z-score (r=-0.33, p=0.001) and TBLH-BMCLBM Z-score (r=-0.23, p=0.027); for each year ART initiation was delayed a 0.13 SD reduction in LS-BMAD was seen.ConclusionSize-adjusted low bone density is common in CWH. Delay in initiating ART adversely affects bone density. Findings support immediate ART initiation at HIV diagnosis.

Sclerostin inhibition is a new therapeutic approach for increasing bone mineral density (BMD) but its cardiovascular safety is unclear. We conducted a genome-wide association study (GWAS) meta-analysis of circulating sclerostin in 33,961 Europeans followed by Mendelian randomization (MR) to estimate the causal effects of sclerostin on 15 atherosclerosis-related diseases and risk factors. GWAS meta-analysis identified 18 variants independently associated with sclerostin, which including a novel cis signal in the SOST region and three trans signals in B4GALNT3, RIN3 and SERPINA1 regions that were associated with opposite effects on circulating sclerostin and eBMD. MR combining these four SNPs suggested lower sclerostin increased hypertension risk (odds ratio [OR]=1.09, 95%CI=1.04 to 1.15), whereas bi-directional analyses revealed little evidence for an effect of genetic liability to hypertension on sclerostin levels. MR restricted to cis (SOST) SNPs additionally suggested sclerostin inhibition increased risk of type 2 diabetes (T2DM) (OR=1.26; 95%CI=1.08 to 1.48) and myocardial infarction (MI) (OR=1.31, 95% CI=1.183 to 1.45). Furthermore, these analyses suggested sclerostin inhibition increased coronary artery calcification (CAC) (beta=0.74, 95%CI=0.33 to 1.15), levels of apoB (beta=0.07; 95%CI=0.04 to 0.10; this result was driven by rs4793023) and triglycerides (beta=0.18; 95%CI=0.13 to 0.24), and reduced HDL-C (beta=-0.14; 95%CI=-0.17 to -0.10). This study provides genetic evidence to support a causal effect of sclerostin inhibition on increased hypertension risk. Cis-only analyses suggested that sclerostin inhibition additionally increases the risk of T2DM, MI, CAC, and an atherogenic lipid profile. Together, our findings reinforce the requirement for strategies to mitigate against adverse effects of sclerostin inhibitors like romosozumab on atherosclerosis and its related risk factors.

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OBJECTIVES: Observational analyses suggest that high Bone Mineral Density (BMD) is a risk factor for osteoarthritis (OA); it is unclear whether this represents a causal effect or shared aetiology and whether these relationships are body mass index (BMI)-independent. We performed bidirectional Mendelian randomization (MR) to uncover the causal pathways between BMD, BMI and OA. METHODS: One-sample (1S)MR estimates were generated by two-stage least-squares regression. Unweighted allele scores instrumented each exposure. Two-sample (2S)MR estimates were generated using inverse-variance weighted fixed-effects meta-analysis. Multivariable MR (MVMR), including BMD and BMI instruments in the same model, determined the BMI-independent causal pathway from BMD to OA. Latent causal variable (LCV) analysis, using weight-adjusted FN-BMD and hip/knee OA summary statistics, determined if genetic correlation explained the causal effect of BMD on OA. RESULTS: 1SMR provided strong evidence for a causal effect of eBMD on hip and knee OA (ORhip=1.28[1.05,1.57],p=0.02, ORknee=1.40[1.20,1.63],p=3x10-5, OR per SD increase). 2SMR effect sizes were consistent in direction. Results suggested that the causal pathways between eBMD and OA were bidirectional (βhip=1.10[0.36,1.84],p=0.003, βknee=4.16[2.74,5.57],p=8x10-9, β=SD increase per doubling in risk). MVMR identified a BMI-independent causal pathway between eBMD and hip/knee OA. LCV suggested that genetic correlation (i.e. shared genetic aetiology) did not fully explain causal effects of BMD on hip/knee OA. CONCLUSIONS: These results provide evidence for a BMI-independent causal effect of eBMD on OA. Despite evidence of bidirectional effects, the effect of BMD on OA did not appear to be fully explained by shared genetic aetiology, suggesting a direct action of bone on joint deterioration.