Multi-Trait Exome-Wide Association Study of Back Pain-Related Phenotypes.

Back pain (BP) is a major contributor to disability worldwide, with heritability estimated at 40-60%. However, less than half of the heritability is explained by common genetic variants identified by genome-wide association studies. More powerful methods and rare and ultra-rare variant analysis may offer additional insight. This study utilized exome sequencing data from the UK Biobank to perform a multi-trait gene-based association analysis of three BP-related phenotypes: chronic back pain, dorsalgia, and intervertebral disc disorder. We identified the SLC13A1 gene as a contributor to chronic back pain via loss-of-function (LoF) and missense variants. This gene has been previously detected in two studies. A multi-trait approach uncovered the novel FSCN3 gene and its impact on back pain through LoF variants. This gene deserves attention because it is only the second gene shown to have an effect on back pain due to LoF variants and represents a promising drug target for back pain therapy.

Repurposing Antihypertensive and Statin Medications for Spinal Pain: A Mendelian Randomization Study.

STUDY DESIGN: Mendelian randomization (MR) study. OBJECTIVE: To examine whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal pain (back or neck pain). SUMMARY OF BACKGROUND DATA: Observational studies and a recent MR study have found associations between elevated blood pressure and a greater risk of back pain. Observational studies have found associations between hyperlipidemia and statin use and greater risk of back pain. No prior MR studies have examined the effects of antihypertensives or statins on spinal pain. MATERIALS AND METHODS: This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies (GWAS). Sample sizes in exposure GWASs were n=757,601 (systolic blood pressure) and n=173,082 (low-density lipoprotein cholesterol), and n=1,028,947 for the outcome GWAS of spinal pain defined as health care seeking for any spinal pain-related diagnosis. Genes and cis-acting variants were identified as proxies for the drug targets of interest. MR analyses used inverse-variance weighted meta-analysis. The threshold for statistical significance after correction for multiple testing was P <0.0125. RESULTS: No statistically significant associations of these medications with spinal pain were found. However, findings were suggestive of a protective effect of beta-blockers on spinal pain risk (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72-0.98; P =0.03), and calcium channel blockers on greater spinal pain risk (OR 1.12, 95% CI 1.02-1.24; P =0.02). CONCLUSIONS: A protective effect of beta-blockers on spinal pain was suggested in the current study, consistent with findings from observational studies of various other pain phenotypes. The detrimental effect of calcium channel blockers on spinal pain suggested in the current study must be interpreted in the context of conflicting directions of effect on nonspinal pain phenotypes in other observational studies.This Mendelian randomization study examined whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal.This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies ranging size from 173,082 to 1,028,947 adults.While no statistically significant associations were found, a protective effect of beta-blockers on spinal pain was suggested (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72 to 0.98; p= 0.03), as was a detrimental effect of calcium channel blockers on spinal pain (OR 1.12, 95% CI 1.02 to 1.24; p= 0.02).

Bidirectional Mendelian Randomization Study of Personality Traits Reveals a Positive Feedback Loop Between Neuroticism and Back Pain.

We conducted a bidirectional Mendelian randomization study to examine the causal effects of six personality traits (anxiety, neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) on back pain associated with health care use and the causal effect of back pain on the same risk factors. Genetic instruments for the personality traits and back pain were obtained from the largest published genome-wide association studies conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis and Causal Analysis Using Summary Effect for primary analyses and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results of at least one primary analysis were statistically significant after accounting for multiple statistical testing (P-value < .0042), and the direction and magnitude of effect estimates were concordant between primary and sensitivity analyses. We found evidence for statistically significant bidirectional causal associations between neuroticism and back pain, with odds ratio 1.51 (95% confidence interval 1.37; 1.67) of back pain per neuroticism sum score standard deviation, P-value = 7.80e-16; and beta = .12, se = .04 of neuroticism sum score standard deviation per log odds of back pain, P-value = 2.48e-03. Other relationships did not meet our predefined criteria for causal association. PERSPECTIVE: The significant positive feedback loop between neuroticism and back pain highlights the importance of considering neuroticism in the management of patients with back pain.

Development and Replication of a Genome-Wide Polygenic Risk Score for Chronic Back Pain.

Chronic back pain (CBP) is a complex heritable trait and a major cause of disability worldwide. We developed and validated a genome-wide polygenic risk score (PRS) for CBP using a large-scale GWAS based on UK Biobank participants of European ancestry (N = 265,000). The PRS showed poor overall predictive ability (AUC = 0.56 and OR = 1.24 per SD, 95% CI: 1.22-1.26), but individuals from the 99th percentile of PRS distribution had a nearly two-fold increased risk of CBP (OR = 1.82, 95% CI: 1.60-2.06). We validated the PRS on an independent TwinsUK sample, obtaining a similar magnitude of effect. The PRS was significantly associated with various ICD-10 and OPCS-4 diagnostic codes, including chronic ischemic heart disease (OR = 1.1, p-value = 4.8 × 10-15), obesity, metabolism-related traits, spine disorders, disc degeneration, and arthritis-related disorders. PRS and environment interaction analysis with twelve known CBP risk factors revealed no significant results, suggesting that the magnitude of G × E interactions with studied factors is small. The limited predictive ability of the PRS that we developed is likely explained by the complexity, heterogeneity, and polygenicity of CBP, for which sample sizes of a few hundred thousand are insufficient to estimate small genetic effects robustly.

Evidence of causal effects of blood pressure on back pain and back pain on type II diabetes provided by a bidirectional Mendelian randomization study.

BACKGROUND CONTEXT: Cardiovascular risk factors (hypertension, dyslipidemia, and type II diabetes) have been proposed as risk factors for back pain. However, few longitudinal studies have found significant associations between cardiovascular risk factors and back pain, and these may be explained by confounding or reverse causation. PURPOSE: To examine potential causal effects of cardiovascular risk factors on back pain, and vice versa. STUDY DESIGN: Bidirectional Mendelian randomization (MR) study. PATIENT SAMPLES: Genome-wide association studies (GWAS) with sample sizes between 173,082 and 1,028,947 participants. OUTCOME MEASURES: Outcomes included (1) back pain associated with health care use (BP-HC) in the forward MR; and (2) seven cardiovascular phenotypes in the reverse MR, including 2 measurements used for the evaluation of hypertension (diastolic blood pressure and systolic blood pressure), 4 phenotypes related to dyslipidemia (LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides), and type II diabetes. METHODS: We used summary statistics from large, publicly available GWAS for BP-HC and the 7 cardiovascular phenotypes to obtain genetic instrumental variables. We examined MR evidence for causal associations using inverse-variance weighted (IVW) analysis, Causal Analysis Using Summary Effect (CAUSE), and sensitivity analyses. RESULTS: In forward MR analyses of seven cardiovascular phenotypes, diastolic blood pressure was associated with BP-HC across all analyses (IVW estimate: OR = 1.10 per 10.5 mm Hg increase [1.04-1.17], p-value = .001), and significant associations of systolic blood pressure with BP-HC were also found (IVW estimate: OR = 1.09 per 19.3 mm Hg increase [1.04-1.15], p-value = .0006). In reverse MR analyses, only type II diabetes was associated with BP-HC across all analyses (IVW estimate: OR = 1.40 [1.13-1.73], p-value = .002). CONCLUSIONS: These findings from analyses of large, population-based samples indicate that higher blood pressure increases the risk of BP-HC, and BP-HC itself increases the risk of type II diabetes.

A Novel Framework for Analysis of the Shared Genetic Background of Correlated Traits.

We propose a novel effective framework for the analysis of the shared genetic background for a set of genetically correlated traits using SNP-level GWAS summary statistics. This framework called SHAHER is based on the construction of a linear combination of traits by maximizing the proportion of its genetic variance explained by the shared genetic factors. SHAHER requires only full GWAS summary statistics and matrices of genetic and phenotypic correlations between traits as inputs. Our framework allows both shared and unshared genetic factors to be effectively analyzed. We tested our framework using simulation studies, compared it with previous developments, and assessed its performance using three real datasets: anthropometric traits, psychiatric conditions and lipid concentrations. SHAHER is versatile and applicable to summary statistics from GWASs with arbitrary sample sizes and sample overlaps, allows for the incorporation of different GWAS models (Cox, linear and logistic), and is computationally fast.

Causal effects of psychosocial factors on chronic back pain: a bidirectional Mendelian randomisation study.

PURPOSE: Risk factors for chronic back pain (CBP) may share underlying genetic factors, making them difficult to study using conventional methods. We conducted a bi-directional Mendelian randomisation (MR) study to examine the causal effects of risk factors (education, smoking, alcohol consumption, physical activity, sleep and depression) on CBP and the causal effect of CBP on the same risk factors. METHODS: Genetic instruments for risk factors and CBP were obtained from the largest published genome-wide association studies (GWAS) of risk factor traits conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis (IVW), Causal Analysis Using Summary Effect (CAUSE) and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results with IVW or CAUSE were statistically significant after accounting for multiple statistical testing (p < 0.003), and the direction and magnitude of effect estimates were concordant between IVW, CAUSE, and sensitivity analyses. RESULTS: We found evidence for statistically significant causal associations between greater education (OR per 4.2 years of schooling = 0.54), ever smoking (OR = 1.27), greater alcohol consumption (OR = 1.29 per consumption category increase) and major depressive disorder (OR = 1.41) and risk of CBP. Conversely, we found evidence for significant causal associations between CBP and greater alcohol consumption (OR = 1.19) and between CBP and smoking (OR = 1.21). Other relationships did not meet our pre-defined criteria for causal association. CONCLUSION: Fewer years of schooling, smoking, greater alcohol consumption, and major depressive disorder increase the risk of CBP. CBP increases the risk of greater alcohol consumption and smoking.

A protocol for recruiting and analyzing the disease-oriented Russian disc degeneration study (RuDDS) biobank for functional omics studies of lumbar disc degeneration.

Lumbar intervertebral disc degeneration (DD) disease is one of the main risk factors for low back pain and a leading cause of population absenteeism and disability worldwide. Despite a variety of biological studies, lumbar DD is not yet fully understood, partially because there are only few studies that use systematic and integrative approaches. This urges the need for studies that integrate different omics (including genomics and transcriptomics) measured on samples within a single cohort. This protocol describes a disease-oriented Russian disc degeneration study (RuDDS) biobank recruitment and analyses aimed to facilitate further omics studies of lumbar DD integrating genomic, transcriptomic and glycomic data. A total of 1,100 participants aged over 18 with available lumbar MRI scans, medical histories and biological material (whole blood, plasma and intervertebral disc tissue samples from surgically treated patients) will be enrolled during the three-year period from two Russian clinical centers. Whole blood, plasma and disc tissue specimens will be used for genotyping with genome-wide SNP-arrays, glycome profiling and RNA sequencing, respectively. Omics data will be further used for a genome-wide association study of lumbar DD with in silico functional annotation, analysis of plasma glycome and lumbar DD disease interactions and transcriptomic data analysis including an investigation of differential expression patterns associated with lumbar DD disease. Statistical tests applied in each of the analyses will meet the standard criteria specific to the attributed study field. In a long term, the results of the study will expand fundamental knowledge about lumbar DD development and contribute to the elaboration of novel personalized approaches for disease prediction and therapy. Additionally to the lumbar disc degeneration study, a RuDDS cohort could be used for other genetic studies, as it will have unique omics data. Trial registration number NCT04600544.

Mendelian randomization analysis of plasma levels of CD209 and MICB proteins and the risk of varicose veins of lower extremities.

Varicose veins of lower extremities (VVs) are a highly prevalent condition, the pathogenesis of which is still not fully elucidated. Mendelian randomization (MR) can provide useful preliminary information on the traits that are potentially causally related to the disease. The aim of the present study is to replicate the effects of the plasma levels of MHC class I polypeptide-related sequence B (MICB) and cluster of differentiation 209 (CD209) proteins reported in a previous hypothesis-free MR study. We conducted MR analysis using a fixed effects inverse-variance weighted meta-analysis of Wald ratios method. For MICB and CD209, we used data from a large-scale genome-wide association study (GWAS) for plasma protein levels (N = 3,301). For VVs, we used GWAS data obtained in the FinnGen project (N = 128,698), the eMERGE network (phase 3, N = 48,429), and the UK Biobank data available in the Gene ATLAS (N = 452,264). The data used in the study were obtained in individuals of European descent. The results for MICB did not pass criteria for statistical significance and replication. The results for CD209 passed all statistical significance thresholds, indicating that the genetically predicted increase in CD209 level is associated with increased risk of VVs (ßMR (SE) = 0.07 (0.01), OR (95% CI) = 1.08 (1.05-1.10), P-value = 5.9 ×10-11 in the meta-analysis of three cohorts). Our findings provide further support that CD209 can potentially be involved in VVs. In future studies, independent validation of our results using data from more powerful GWASs for CD209 measured by different methods would be beneficial.

Replication of 15 loci involved in human plasma protein N-glycosylation in 4802 samples from four cohorts.

Human protein glycosylation is a complex process, and its in vivo regulation is poorly understood. Changes in glycosylation patterns are associated with many human diseases and conditions. Understanding the biological determinants of protein glycome provides a basis for future diagnostic and therapeutic applications. Genome-wide association studies (GWAS) allow to study biology via a hypothesis-free search of loci and genetic variants associated with a trait of interest. Sixteen loci were identified by three previous GWAS of human plasma proteome N-glycosylation. However, the possibility that some of these loci are false positives needs to be eliminated by replication studies, which have been limited so far. Here, we use the largest set of samples so far (4802 individuals) to replicate the previously identified loci. For all but one locus, the expected replication power exceeded 95%. Of the 16 loci reported previously, 15 were replicated in our study. For the remaining locus (near the KREMEN1 gene), the replication power was low, and hence, replication results were inconclusive. The very high replication rate highlights the general robustness of the GWAS findings as well as the high standards adopted by the community that studies genetic regulation of protein glycosylation. The 15 replicated loci present a good target for further functional studies. Among these, eight loci contain genes encoding glycosyltransferases: MGAT5, B3GAT1, FUT8, FUT6, ST6GAL1, B4GALT1, ST3GAL4 and MGAT3. The remaining seven loci offer starting points for further functional follow-up investigation into molecules and mechanisms that regulate human protein N-glycosylation in vivo.

Candidate genes for age at menarche are associated with endometriosis.

RESEARCH QUESTION: Are the candidate genes for age at menarche associated with a risk of endometriosis? DESIGN: Fifty-two candidate single nucleotide polymorphisms (SNP) for age at menarche, their gene-gene and gene-environment interactions were analysed for possible association with endometriosis in a sample of 395 patients and 981 controls. Association of the polymorphisms was analysed using logistic regression according to three main genetic models (additive, recessive and dominant). The gene-gene and gene-environment interactions were analysed for the second-, third- and fourth-order models with adjustment for covariates and multiple comparisons with subsequent cross-validation. RESULTS: Sixteen SNP for age at menarche out of the 52 studied were associated with endometriosis. Polymorphism rs6589964 BSX was associated with endometriosis according to the additive and recessive models (OR 1.27-1.47, Pperm ≤ 0.006). Fourteen SNP were associated with the disease within 12 most significant models of gene-gene interactions (Pperm ≤ 0.008). Twelve SNP involved in 10 most significant models of SNP-induced abortion interactions are associated with endometriosis. Fourteen of the 16 polymorphisms associated with endometriosis demonstrated pleiotropic effects: they were also associated with either age at menarche (7 SNP) or height and/or body mass index (10 SNP) in the studied sample. The 16 SNP associated with endometriosis and 316 SNP linked to them have regulatory and expression quantitative trait locus significance for 28 genes contributing to the G alpha signal pathway (fold enrichment 31.09, PFDR = 0.001) and responses to endogenous stimuli (fold enrichment 16.01, PFDR = 0.027). CONCLUSIONS: Sixteen SNP for age at menarche out of the 52 studied were associated with endometriosis.

Analysis of genetically independent phenotypes identifies shared genetic factors associated with chronic musculoskeletal pain conditions.

Chronic musculoskeletal pain affects all aspects of human life. However, mechanisms of its genetic control remain poorly understood. Genetic studies of pain are complicated by the high complexity and heterogeneity of pain phenotypes. Here, we apply principal component analysis to reduce phenotype heterogeneity of chronic musculoskeletal pain at four locations: the back, neck/shoulder, hip, and knee. Using matrices of genetic covariances, we constructed four genetically independent phenotypes (GIPs) with the leading GIP (GIP1) explaining 78.4% of the genetic variance of the analyzed conditions, and GIP2-4 explain progressively less. We identified and replicated five GIP1-associated loci and one GIP2-associated locus and prioritized the most likely causal genes. For GIP1, we showed enrichment with multiple nervous system-related terms and genetic correlations with anthropometric, sociodemographic, psychiatric/personality traits and osteoarthritis. We suggest that GIP1 represents a biopsychological component of chronic musculoskeletal pain, related to physiological and psychological aspects and reflecting pain perception and processing.

ISSLS Prize in Clinical Science 2020. Examining causal effects of body mass index on back pain: a Mendelian randomization study.

PURPOSE: Measures of body fat accumulation are associated with back pain, but a causal association is unclear. We hypothesized that BMI would have causal effects on back pain. We conducted a two-sample Mendelian randomization (MR) study to assess the causal effect of body mass index (BMI) on the outcomes of (1) back pain and (2) chronic back pain (duration > 3 months). METHODS: We identified genetic instrumental variables for BMI (n = 60 variants) from a meta-analysis of genome-wide association studies (GWAS) conducted by the Genetic Investigation of ANthropometric Traits consortium in individuals of European ancestry (n = 322,154). We conducted GWAS of back pain and chronic back pain (n = 453,860) in a non-overlapping sample of individuals of European ancestry. We used inverse-variance weighted (IVW) meta-analysis as the primary method to estimate causal effects. RESULTS: The IVW analysis showed evidence supporting a causal association of BMI on back pain, with a 1-standard deviation (4.65 kg/m2) increase in BMI conferring 1.15 times the odds of back pain (95% confidence interval [CI]: 1.06-1.25, p = 0.001]; effects were directionally consistent in secondary analysis and sensitivity analyses. The IVW analysis supported a causal association of BMI on chronic back pain (OR 1.20 per 1 SD deviation increase in BMI [95% CI 1.09-1.32; p = 0.0002]), and effects were directionally consistent in secondary analysis and sensitivity analyses. CONCLUSION: In this first MR study of BMI and back pain, we found a significant causal effect of BMI on both back pain and chronic back pain. These slides can be retrieved under Electronic Supplementary Material.