Accurate phenotypic classification and exome sequencing allow identification of novel genes and variants associated with adult-onset hearing loss.

Adult-onset progressive hearing loss is a common, complex disease with a strong genetic component. Although to date over 150 genes have been identified as contributing to human hearing loss, many more remain to be discovered, as does most of the underlying genetic diversity. Many different variants have been found to underlie adult-onset hearing loss, but they tend to be rare variants with a high impact upon the gene product. It is likely that combinations of more common, lower impact variants also play a role in the prevalence of the disease. Here we present our exome study of hearing loss in a cohort of 532 older adult volunteers with extensive phenotypic data, including 99 older adults with normal hearing, an important control set. Firstly, we carried out an outlier analysis to identify genes with a high variant load in older adults with hearing loss compared to those with normal hearing. Secondly, we used audiometric threshold data to identify individual variants which appear to contribute to different threshold values. We followed up these analyses in a second cohort. Using these approaches, we identified genes and variants linked to better hearing as well as those linked to worse hearing. These analyses identified some known deafness genes, demonstrating proof of principle of our approach. However, most of the candidate genes are novel associations with hearing loss. While the results support the suggestion that genes responsible for severe deafness may also be involved in milder hearing loss, they also suggest that there are many more genes involved in hearing which remain to be identified. Our candidate gene lists may provide useful starting points for improved diagnosis and drug development.

Understanding the complex genetic architecture connecting rheumatoid arthritis, osteoporosis and inflammation: discovering causal pathways.

Rheumatoid arthritis (RA) and osteoporosis (OP) are two comorbid complex inflammatory conditions with evidence of shared genetic background and causal relationships. We aimed to clarify the genetic architecture underlying RA and various OP phenotypes while additionally considering an inflammatory component, C-reactive protein (CRP). Genome-wide association study summary statistics were acquired from the GEnetic Factors for OSteoporosis Consortium, Cohorts for Heart and Aging Research Consortium and UK Biobank. Mendelian randomization (MR) was used to detect the presence of causal relationships. Colocalization analysis was performed to determine shared genetic variants between CRP and OP phenotypes. Analysis of pleiotropy between traits owing to shared causal single nucleotide polymorphisms (SNPs) was performed using PL eiotropic A nalysis under CO mposite null hypothesis (PLACO). MR analysis was suggestive of horizontal pleiotropy between RA and OP traits. RA was a significant causal risk factor for CRP (ß = 0.027, 95% confidence interval = 0.016-0.038). There was no evidence of CRP→OP causal relationship, but horizontal pleiotropy was apparent. Colocalization established shared genomic regions between CRP and OP, including GCKR and SERPINA1 genes. Pleiotropy arising from shared causal SNPs revealed through the colocalization analysis was all confirmed by PLACO. These genes were found to be involved in the same molecular function 'protein binding' (GO:0005515) associated with RA, OP and CRP. We identified three major components explaining the epidemiological relationship among RA, OP and inflammation: (1) Pleiotropy explains a portion of the shared genetic relationship between RA and OP, albeit polygenically; (2) RA contributes to CRP elevation and (3) CRP, which is influenced by RA, demonstrated pleiotropy with OP.

Treatment response in rheumatoid arthritis is predicted by the microbiome: a large observational study in UK DMARD-naïve patients.

OBJECTIVES: Disease-modifying antirheumatic drugs (DMARDs) are first line treatment in rheumatoid arthritis (RA). Treatment response to DMARDs is patient-specific, dose efficacy is difficult to predict and long-term results variable. The gut microbiota are known to play a pivotal role in prodromal and early-disease RA, manifested by Prevotella spp. enrichment. The clinical response to therapy may be mediated by microbiota, and large-scale studies assessing the microbiome are few. This study assessed whether microbiome signals were associated with, and predictive of, patient response to DMARD-treatment. Accurate early identification of those who will respond poorly to DMARD therapy would allow selection of alternative treatment (e.g. biologic therapy), and potentially improve patient outcome. METHODS: A multicentre, longitudinal, observational study of stool- and saliva microbiome was performed in DMARD-naïve, newly diagnosed RA patients during introduction of DMARD treatment. Clinical data and samples were collected at baseline (n = 144) in DMARD-naïve patients and at six weeks (n = 117) and 12 weeks (n = 95) into DMARD-therapy. Samples collected (n = 365 stool, n = 365 saliva) underwent shotgun sequencing. Disease activity measures were collected at each timepoint and minimal clinically important improvement determined. RESULTS: In total, 26 stool microbes were found to decrease in those manifesting a minimal clinically important improvement. Prevotella spp. and Streptococcus spp. were the predominant taxa to decline following six weeks and 12 weeks of DMARDs, respectively. Furthermore, baseline microbiota of DMARD-naïve patients were indicative of future response. CONCLUSION: DMARDs appear to restore a perturbed microbiome to a eubiotic state. Moreover, microbiome status can be used to predict likelihood of patient response to DMARD.

Discovery of circulating blood biomarkers in patients with and without Modic changes of the lumbar spine: a preliminary analysis.

PURPOSE: The following study aimed to determine the existence of blood biomarkers in symptomatic patients with or without lumbar Modic changes (MC). METHODS: A cross-sectional sub-analyses of a prospective cohort was performed. Fasting blood samples were collected from patients with and without lumbar MC who had undergone spinal fusion or microdiscectomy. An 80-plex panel and CCL5/RANTES were used to assess preoperative plasma cytokine concentrations. Patient demographics and imaging phenotypes were also assessed. RESULTS: Thirty-one subjects were analysed (n = 18 no MC; n = 13 MC). No significant differences were found in age, sex, body mass index, smoking and alcohol history, and surgical procedure (i.e. fusion, decompression) between the two groups (p > 0.05). Several statistically significant blood biomarkers in MC patients were identified, including elevated levels of C-C Motif Chemokine Ligand 5 (CCL5, p = 0.0006), while Macrophage Migration Inhibitory Factor (MIF) was significantly lower (p = 0.009). Additionally, C-X-C Motif Chemokine Ligand 5 (CXCL5, p = 0.052), Pentraxin 3 (PTX3, p = 0.06) and Galectin-3 (Gal-3, p = 0.07) showed potential relevance. Moreover, MC patients exhibited significantly higher levels of disc degeneration (p = 0.0001) and displacement severity (p = 0.020). Based on multivariate analyses and controlling for disc degeneration/displacement, CCL5 (OR 1.02; 95% CI 1.002-1.033; p = 0.028) and MIF (OR 0.60; 95% CI 0.382-0.951; p = 0.030) were independently associated with MC patients. CONCLUSION: This "proof-of-concept" study is the first to identify specific and significantly circulating blood biomarkers associated with symptomatic patients with lumbar MC, independent of disc alterations of degeneration and/or bulges/herniations. Specifically, differences in CCL5 and MIF protein levels were significantly noted in MC patients compared to those without MC.

Glycoprotein Acetyls Is a Novel Biomarker Predicting Cardiovascular Complications in Rheumatoid Arthritis.

The relationship between rheumatoid arthritis (RA) and early onset atherosclerosis is well depicted, each with an important inflammatory component. Glycoprotein acetyls (GlycA), a novel biomarker of inflammation, may play a role in the manifestation of these two inflammatory conditions. The present study examined a potential mediating role of GlycA within the RA-atherosclerosis relationship to determine whether it accounts for the excess risk of cardiovascular disease over that posed by lipid risk factors. The UK Biobank dataset was acquired to establish associations among RA, atherosclerosis, GlycA, and major lipid factors: total cholesterol (TC), high- and low-density lipoprotein (HDL, LDL) cholesterol, and triglycerides (TGs). Genome-wide association study summary statistics were collected from various resources to perform genetic analyses. Causality among variables was tested using Mendelian Randomization (MR) analysis. Genes of interest were identified using colocalization analysis and gene enrichment analysis. MR results appeared to indicate that the genetic relationship between GlycA and RA and also between RA and atherosclerosis was explained by horizontal pleiotropy (p-value = 0.001 and <0.001, respectively), while GlycA may causally predict atherosclerosis (p-value = 0.017). Colocalization analysis revealed several functionally relevant genes shared between GlycA and all the variables assessed. Two loci were apparent in all relationships tested and included the HLA region as well as SLC22A1. GlycA appears to mediate the RA-atherosclerosis relationship through several possible pathways. GlycA, although pleiotropically related to RA, appears to causally predict atherosclerosis. Thus, GlycA is suggested as a significant factor in the etiology of atherosclerosis development in RA.

Long-COVID fatigue is not predicted by pre-pandemic plasma IL-6 levels in mild COVID-19.

OBJECTIVE AND DESIGN: Fatigue is a prominent symptom in the general population and may follow viral infection, including SARS-CoV2 infection which causes COVID-19. Chronic fatigue lasting more than three months is the major symptom of the post-COVID syndrome (known colloquially as long-COVID). The mechanisms underlying long-COVID fatigue are unknown. We hypothesized that the development of long-COVID chronic fatigue is driven by the pro-inflammatory immune status of an individual prior to COVID-19. SUBJECTS AND METHODS: We analyzed pre-pandemic plasma levels of IL-6, which plays a key role in persistent fatigue, in N = 1274 community dwelling adults from TwinsUK. Subsequent COVID-19-positive and -negative participants were categorized based on SARS-CoV-2 antigen and antibody testing. Chronic fatigue was assessed using the Chalder Fatigue Scale. RESULTS: COVID-19-positive participants exhibited mild disease. Chronic fatigue was a prevalent symptom among this population and significantly higher in positive vs. negative participants (17% vs 11%, respectively; p = 0.001). The qualitative nature of chronic fatigue as determined by individual questionnaire responses was similar in positive and negative participants. Pre-pandemic plasma IL-6 levels were positively associated with chronic fatigue in negative, but not positive individuals. Raised BMI was associated with chronic fatigue in positive participants. CONCLUSIONS: Pre-existing increased IL-6 levels may contribute to chronic fatigue symptoms, but there was no increased risk in individuals with mild COVID-19 compared with uninfected individuals. Elevated BMI also increased the risk of chronic fatigue in mild COVID-19, consistent with previous reports.

Modic change is associated with increased BMI but not autoimmune diseases in TwinsUK.

PURPOSE: Low back pain (LBP) is one of the largest causes of morbidity worldwide. The aetiology of LBP is complex, and many factors contribute to the onset. Bone marrow lesions within the vertebra adjacent to an intervertebral degenerate disc named Modic change (MC) have been suggested as a diagnostic subgroup of LBP. Autoimmune response has been proposed to be one of the causes that promote the development of MC. The aim of the current investigation is to assess prevalence and severity of MC and LBP in participants with an autoimmune disease diagnosis in a well-documented cohort of adult twin volunteers. METHODS: Multivariate generalized mixed linear models (GLMM) were implemented in order to calculate the association between having an autoimmune disorder and MC prevalence, width and severe and disabling LBP. The model was corrected for family structure as well as for covariates such as age, BMI and smoking. RESULTS: No association was found between diagnosis of autoimmune disorder and MC. Interestingly, BMI was independently associated with MC width but not to MC prevalence. These results help to shed light on the relationship between MC and autoimmunity as well as the role of BMI in the development of the lesions. CONCLUSION: This study is the first to examine autoimmune disorders and MC prevalence in a large, population-based female cohort. The study was well powered to detect a small effect. No association was found between having a diagnosis of one or more autoimmune conditions and MC prevalence, width or LBP.

Are current machine learning applications comparable to radiologist classification of degenerate and herniated discs and Modic change? A systematic review and meta-analysis.

INTRODUCTION: Low back pain is the leading contributor to disability burden globally. It is commonly due to degeneration of the lumbar intervertebral discs (LDD). Magnetic resonance imaging (MRI) is the current best tool to visualize and diagnose LDD, but places high time demands on clinical radiologists. Automated reading of spine MRIs could improve speed, accuracy, reliability and cost effectiveness in radiology departments. The aim of this review and meta-analysis was to determine if current machine learning algorithms perform well identifying disc degeneration, herniation, bulge and Modic change compared to radiologists. METHODS: A PRISMA systematic review protocol was developed and four electronic databases and reference lists were searched. Strict inclusion and exclusion criteria were defined. A PROBAST risk of bias and applicability analysis was performed. RESULTS: 1350 articles were extracted. Duplicates were removed and title and abstract searching identified original research articles that used machine learning (ML) algorithms to identify disc degeneration, herniation, bulge and Modic change from MRIs. 27 studies were included in the review; 25 and 14 studies were included multi-variate and bivariate meta-analysis, respectively. Studies used machine learning algorithms to assess LDD, disc herniation, bulge and Modic change. Models using deep learning, support vector machine, k-nearest neighbors, random forest and naïve Bayes algorithms were included. Meta-analyses found no differences in algorithm or classification performance. When algorithms were tested in replication or external validation studies, they did not perform as well as when assessed in developmental studies. Data augmentation improved algorithm performance when compared to models used with smaller datasets, there were no performance differences between augmented data and large datasets. DISCUSSION: This review highlights several shortcomings of current approaches, including few validation attempts or use of large sample sizes. To the best of the authors' knowledge, this is the first systematic review to explore this topic. We suggest the utilization of deep learning coupled with semi- or unsupervised learning approaches. Use of all information contained in MRI data will improve accuracy. Clear and complete reporting of study design, statistics and results will improve the reliability and quality of published literature.

A genome-wide association study finds genetic variants associated with neck or shoulder pain in UK Biobank.

BACKGROUND: Common types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203 309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK. METHODS: A genome-wide association study was performed adjusting for age, sex, BMI and nine population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication. RESULTS: We identified three genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 × 10-11. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 × 10-10 for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 × 10-8 for rs62053992. In the replication stage, among four significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively). CONCLUSIONS: We have identified three loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain.

Genetic and environmental correlational structure among metabolic syndrome endophenotypes.

Metabolic syndrome (MetS) is diagnosed by the presence of high scores on three or more metabolic traits, including systolic and diastolic blood pressure (SBP, DBP), glucose and insulin levels, cholesterol and triglyceride (TG) levels, and central obesity. A diagnosis of MetS is associated with increased risk of cardiovascular disease and type 2 diabetes. The components of MetS have long been demonstrated to have substantial genetic components, but their genetic overlap is less well understood. The present paper takes a multi-prong approach to examining the extent of this genetic overlap. This includes the quantitative genetic and additive Bayesian network modeling of the large TwinsUK project and examination of the results of genome-wide association study (GWAS) of UK Biobank data through use of LD score regression and examination of the number of genes and pathways identified in the GWASes which overlap across MetS traits. Results demonstrate a modest genetic overlap, and the genetic correlations obtained from TwinsUK and UK Biobank are nearly identical. However, these correlations imply more genetic dissimilarity than similarity. Furthermore, examination of the extent of overlap in significant GWAS hits, both at the gene and pathway level, again demonstrates only modest but significant genetic overlap. This lends support to the idea that in clinical treatment of MetS, treating each of the components individually may be an important way to address MetS.

GWAS Identifies 44 Independent Associated Genomic Loci for Self-Reported Adult Hearing Difficulty in UK Biobank.

Age-related hearing impairment (ARHI) is the most common sensory impairment in the aging population; a third of individuals are affected by disabling hearing loss by the age of 65. It causes social isolation and depression and has recently been identified as a risk factor for dementia. The genetic risk factors and underlying pathology of ARHI are largely unknown, meaning that targets for new therapies remain elusive, yet heritability estimates range between 35% and 55%. We performed genome-wide association studies (GWASs) for two self-reported hearing phenotypes, using more than 250,000 UK Biobank (UKBB) volunteers aged between 40 and 69 years. Forty-four independent genome-wide significant loci (p < 5E-08) were identified, considerably increasing the number of established trait loci. Thirty-four loci are novel associations with hearing loss of any form, and only one of the ten known hearing loci has a previously reported association with an ARHI-related trait. Gene sets from these loci are enriched in auditory processes such as synaptic activities, nervous system processes, inner ear morphology, and cognition, while genetic correlation analysis revealed strong positive correlations with multiple personality and psychological traits for the first time. Immunohistochemistry for protein localization in adult mouse cochlea implicate metabolic, sensory, and neuronal functions for NID2, CLRN2, and ARHGEF28. These results provide insight into the genetic landscape underlying ARHI, opening up novel therapeutic targets for further investigation. In a wider context, our study also highlights the viability of using self-report phenotypes for genetic discovery in very large samples when deep phenotyping is unavailable.

Whole-exome sequencing identifies rare variants in STAB2 associated with venous thromboembolic disease.

Deep vein thrombosis and pulmonary embolism, collectively defined as venous thromboembolism (VTE), are the third leading cause of cardiovascular death in the United States. Common genetic variants conferring increased varying degrees of VTE risk have been identified by genome-wide association studies (GWAS). Rare mutations in the anticoagulant genes PROC, PROS1 and SERPINC1 result in perinatal lethal thrombosis in homozygotes and markedly increased VTE risk in heterozygotes. However, currently described VTE variants account for an insufficient portion of risk to be routinely used for clinical decision making. To identify new rare VTE risk variants, we performed a whole-exome study of 393 individuals with unprovoked VTE and 6114 controls. This study identified 4 genes harboring an excess number of rare damaging variants in patients with VTE: PROS1, STAB2, PROC, and SERPINC1. At STAB2, 7.8% of VTE cases and 2.4% of controls had a qualifying rare variant. In cell culture, VTE-associated variants of STAB2 had a reduced surface expression compared with reference STAB2. Common variants in STAB2 have been previously associated with plasma von Willebrand factor and coagulation factor VIII levels in GWAS, suggesting that haploinsufficiency of stabilin-2 may increase VTE risk through elevated levels of these procoagulants. In an independent cohort, we found higher von Willebrand factor levels and equivalent propeptide levels in individuals with rare STAB2 variants compared with controls. Taken together, this study demonstrates the utility of gene-based collapsing analyses to identify loci harboring an excess of rare variants with functional connections to a complex thrombotic disease.

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.

Evidence for infection in intervertebral disc degeneration: a systematic review.

PURPOSE: Back pain is a major problem worldwide and is linked to intervertebral disc degeneration and Modic change. Several studies report growth of bacteria following extraction of degenerate discs at spine surgery. A pathophysiological role for infection in back pain has been proposed. METHOD: We conducted a PRISMA systematic review. MEDLINE, PubMed, Scopus and Web of Science were searched with the terms Modic change, intervertebral dis*, bacteria, microb*, and infect*. Date limits of 2001-2021 were set. Human studies investigating the role of bacteria in disc degeneration or Modic change in vertebrae were included. RESULTS: Thirty-six articles from 34 research investigations relating to bacteria in human degenerate discs were found. Cutibacterium acnes was identified in pathological disc material. A 'candidate bacterium' approach has been repeatedly adopted which may have biased results to find species a priori, with disc microbial evidence heavily weighted to find C. acnes. CONCLUSION: Evidence to date implicates C. acnes identified through culture, microscopy and sequencing, with some suggestion of diverse bacterial colonisation in the disc. This review found studies which used culture methods and conventional PCR for bacterial detection. Further agnostic investigation using newer methods should be undertaken.

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.

Defining the genetic control of human blood plasma N-glycome using genome-wide association study.

Glycosylation is a common post-translational modification of proteins. Glycosylation is associated with a number of human diseases. Defining genetic factors altering glycosylation may provide a basis for novel approaches to diagnostic and pharmaceutical applications. Here we report a genome-wide association study of the human blood plasma N-glycome composition in up to 3811 people measured by Ultra Performance Liquid Chromatography (UPLC) technology. Starting with the 36 original traits measured by UPLC, we computed an additional 77 derived traits leading to a total of 113 glycan traits. We studied associations between these traits and genetic polymorphisms located on human autosomes. We discovered and replicated 12 loci. This allowed us to demonstrate an overlap in genetic control between total plasma protein and IgG glycosylation. The majority of revealed loci contained genes that encode enzymes directly involved in glycosylation (FUT3/FUT6, FUT8, B3GAT1, ST6GAL1, B4GALT1, ST3GAL4, MGAT3 and MGAT5) and a known regulator of plasma protein fucosylation (HNF1A). However, we also found loci that could possibly reflect other more complex aspects of glycosylation process. Functional genomic annotation suggested the role of several genes including DERL3, CHCHD10, TMEM121, IGH and IKZF1. The hypotheses we generated may serve as a starting point for further functional studies in this research area.

Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects.

Bone mineral density (BMD) assessed by DXA is used to evaluate bone health. In children, total body (TB) measurements are commonly used; in older individuals, BMD at the lumbar spine (LS) and femoral neck (FN) is used to diagnose osteoporosis. To date, genetic variants in more than 60 loci have been identified as associated with BMD. To investigate the genetic determinants of TB-BMD variation along the life course and test for age-specific effects, we performed a meta-analysis of 30 genome-wide association studies (GWASs) of TB-BMD including 66,628 individuals overall and divided across five age strata, each spanning 15 years. We identified variants associated with TB-BMD at 80 loci, of which 36 have not been previously identified; overall, they explain approximately 10% of the TB-BMD variance when combining all age groups and influence the risk of fracture. Pathway and enrichment analysis of the association signals showed clustering within gene sets implicated in the regulation of cell growth and SMAD proteins, overexpressed in the musculoskeletal system, and enriched in enhancer and promoter regions. These findings reveal TB-BMD as a relevant trait for genetic studies of osteoporosis, enabling the identification of variants and pathways influencing different bone compartments. Only variants in ESR1 and close proximity to RANKL showed a clear effect dependency on age. This most likely indicates that the majority of genetic variants identified influence BMD early in life and that their effect can be captured throughout the life course.

Genome-wide association study identifies RNF123 locus as associated with chronic widespread musculoskeletal pain.

BACKGROUND AND OBJECTIVES: Chronic widespread musculoskeletal pain (CWP) is a symptom of fibromyalgia and a complex trait with poorly understood pathogenesis. CWP is heritable (48%-54%), but its genetic architecture is unknown and candidate gene studies have produced inconsistent results. We conducted a genome-wide association study to get insight into the genetic background of CWP. METHODS: Northern Europeans from UK Biobank comprising 6914 cases reporting pain all over the body lasting >3 months and 242 929 controls were studied. Replication of three independent genome-wide significant single nucleotide polymorphisms was attempted in six independent European cohorts (n=43 080; cases=14 177). Genetic correlations with risk factors, tissue specificity and colocalisation were examined. RESULTS: Three genome-wide significant loci were identified (rs1491985, rs10490825, rs165599) residing within the genes Ring Finger Protein 123 (RNF123), ATPase secretory pathway Ca2+transporting 1 (ATP2C1) and catechol-O-methyltransferase (COMT). The RNF123 locus was replicated (meta-analysis p=0.0002), the ATP2C1 locus showed suggestive association (p=0.0227) and the COMT locus was not replicated. Partial genetic correlation between CWP and depressive symptoms, body mass index, age of first birth and years of schooling were identified. Tissue specificity and colocalisation analysis highlight the relevance of skeletal muscle in CWP. CONCLUSIONS: We report a novel association of RNF123 locus and a suggestive association of ATP2C1 locus with CWP. Both loci are consistent with a role of calcium regulation in CWP. The association with COMT, one of the most studied genes in chronic pain field, was not confirmed in the replication analysis.

An association between chronic widespread pain and the gut microbiome.

OBJECTIVES: Chronic widespread musculoskeletal pain (CWP) is a characteristic symptom of fibromyalgia, which has been shown to be associated with an altered gut microbiome. Microbiome studies to date have not examined the milder CWP phenotype specifically nor have they explored the role of raised BMI. The aim of this study was to investigate whether the microbiome is abnormal in CWP. METHODS: CWP was assessed using a standardized screening questionnaire in female volunteers from the TwinsUK cohort including 113 CWP cases and 1623 controls. The stool microbiome was characterized using 16S rRNA amplicon sequencing and amplicon sequence variants, and associations with CWP examined using linear mixed-effects models adjusting for BMI, age, diet, family relatedness and technical factors. RESULTS: Alpha diversity was significantly lower in CWP cases than controls (Mann-Whitney test, P-values 2.3e-04 and 1.2e-02, for Shannon and Simpson indices respectively). The species Coprococcus comes was significantly depleted in CWP cases (Padj = 3.04e-03). A genome-wide association study (GWAS) performed for C. comes in TwinsUK followed by meta-analysis with three Dutch cohorts (total n = 3521) resulted in nine suggestive regions, with the most convincing on chromosome 4 near the TRAM1L1 gene (rs76957229, P = 7.4e-8). A Mendelian randomization study based on the results of the GWAS did not support a causal role for C. comes on the development of CWP. CONCLUSIONS: We have demonstrated reduced diversity in the microbiome in CWP, indicating an involvement of the gut microbiota in CWP; prospectively the microbiome may offer therapeutic opportunities for this condition.

Alcohol-involved motor vehicle crashes and the size and duration of random breath testing checkpoints.

OBJECTIVE: Sobriety checkpoints have strong empirical and theoretical support as an intervention to reduce alcohol-involved motor vehicle crashes. The purpose of this study was to examine whether checkpoint size (the number of police officers) and checkpoint duration (the amount of time in operation) affect associations between individual checkpoints and subsequent alcohol-related crash incidence. METHOD: Queensland Police Service provided latitude-longitude coordinates and date and time data for all breath tests that occurred in Brisbane, Australia, from January 2012 to June 2018. We applied hierarchical cluster analysis to the latitude-longitude coordinates for breath tests, identifying checkpoints as clusters of ≥25 breath tests conducted by ≥3 breath testing devices over a duration of 3 to 8 hours. Generalized linear autoregressive moving average (GLARMA) models related counts of alcohol-involved motor vehicle crashes to the number of checkpoints conducted per week, as well as 1 week prior and 2 weeks prior. RESULTS: A total of 3420 alcohol-related crashes occurred and 2069 checkpoints were conducted in Brisbane over the 6.5-year (339-week) study period. On average, checkpoints included a mean of 266.0 breath tests (SD = 216.3), 16.4 devices (SD = 13.7), and were 286.3 minutes in duration (SD = 104.2). Each 10 additional checkpoints were associated with a 12% decrease in crash incidence at a lag of 1 week (IRR = 0.88; 95%CI: 0.80, 0.97). We detected no differential associations according to checkpoint size or duration. CONCLUSIONS: Sobriety checkpoints are associated with fewer alcohol-related motor vehicle crashes for around 1 week. Checkpoint size and duration do not appear to affect this relationship.