Effector functions of immunoglobulin G (IgG) are regulated by the composition of a glycan moiety, thus affecting activity of the immune system. Aberrant glycosylation of IgG has been observed in many diseases, but little is understood about the underlying mechanisms. We performed a genome-wide association study of IgG N-glycosylation (N = 8090) and, using a data-driven network approach, suggested how associated loci form a functional network. We confirmed in vitro that knockdown of IKZF1 decreases the expression of fucosyltransferase FUT8, resulting in increased levels of fucosylated glycans, and suggest that RUNX1 and RUNX3, together with SMARCB1, regulate expression of glycosyltransferase MGAT3. We also show that variants affecting the expression of genes involved in the regulation of glycoenzymes colocalize with variants affecting risk for inflammatory diseases. This study provides new evidence that variation in key transcription factors coupled with regulatory variation in glycogenes modifies IgG glycosylation and has influence on inflammatory diseases.

Back pain (BP) is a common condition of major social importance and poorly understood pathogenesis. Combining data from the UK Biobank and CHARGE consortium cohorts allowed us to perform a very large GWAS (total N = 509,070) and examine the genetic correlation and pleiotropy between BP and its clinical and psychosocial risk factors. We identified and replicated three BP associated loci, including one novel region implicating SPOCK2/CHST3 genes. We provide evidence for pleiotropic effects of genetic factors underlying BP, height, and intervertebral disc problems. We also identified independent genetic correlations between BP and depression symptoms, neuroticism, sleep disturbance, overweight, and smoking. A significant enrichment for genes involved in central nervous system and skeletal tissue development was observed. The study of pleiotropy and genetic correlations, supported by the pathway analysis, suggests at least two strong molecular axes of BP genesis, one related to structural/anatomic factors such as intervertebral disk problems and anthropometrics; and another related to the psychological # Corresponding author. * These authors contributed equally to this work. AUTHOR CONTRIBUTIONS MF and YT contributed to the design of the study, carried out statistical analysis, produced the figures, and first draft of the manuscript; LC provided statistical and computational support; MP and PS analysed CHARGE dataset and contributed to interpretation of the results; YA and FW conceived and oversaw the study, contributed to the design and interpretation of the results; all co-authors contributed to the final manuscript revision. COMPETING FINANCIAL INTERESTS YSA and LCK are owners of Maatschap PolyOmica, a private organization, providing services, research and development in the field of computational and statistical (gen)omics. Other authors declare no conflicts of interest.

Aging populations face diminishing quality of life due to increased disease and morbidity. These challenges call for longevity research to focus on understanding the pathways controlling healthspan. We use the data from the UK Biobank (UKB) cohort and observe that the risks of major chronic diseases increased exponentially and double every eight years, i.e., at a rate compatible with the Gompertz mortality law. Assuming that aging drives the acceleration in morbidity rates, we build a risk model to predict the age at the end of healthspan depending on age, gender, and genetic background. Using the sub-population of 300,447 British individuals as a discovery cohort, we identify 12 loci associated with healthspan at the whole-genome significance level. We find strong genetic correlations between healthspan and all-cause mortality, life-history, and lifestyle traits. We thereby conclude that the healthspan offers a promising new way to interrogate the genetics of human longevity.

Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry were included from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and from the UK Biobank interim data release. CBP cases were defined as those reporting back pain present for ≥3–6 months; non-cases were included as comparisons (“controls”). Each cohort conducted genotyping using commercially available arrays followed by imputation. GWAS used logistic regression models with additive genetic effects, adjusting for age, sex, study-specific covariates, and population substructure. The threshold for genome-wide significance in the fixed-effect inverse-variance weighted meta-analysis was p<5×10−8. Suggestive (p<5×10−7) and genome-wide significant (p<5×10−8) variants were carried forward for replication or further investigation in the remaining UK Biobank participants not included in the discovery sample. The discovery sample comprised 158,025 individuals, including 29,531 CBP cases. A genome-wide significant association was found for the intronic variant rs12310519 in SOX5 (OR 1.08, p = 7.2×10−10). This was subsequently replicated in 283,752 UK Biobank participants not included in the discovery sample, including 50,915 cases (OR 1.06, p = 5.3×10−11), and exceeded genome-wide significance in joint meta-analysis (OR 1.07, p = 4.5×10−19). We found suggestive associations at three other loci in the discovery sample, two of which exceeded genome-wide significance in joint meta-analysis: an intergenic variant, rs7833174, located between CCDC26 and GSDMC (OR 1.05, p = 4.4×10−13), and an intronic variant, rs4384683, in DCC (OR 0.97, p = 2.4×10−10). In this first reported meta-analysis of GWAS for CBP, we identified and replicated a genetic locus associated with CBP (SOX5). We also identified 2 other loci that reached genome-wide significance in a 2-stage joint meta-analysis (CCDC26/GSDMC and DCC).

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 GIP2associated 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.

Varicose veins of lower extremities (VVs) are a common multifactorial vascular disease. Genetic factors underlying VVs development remain largely unknown. Here we report the first large-scale study of VVs performed on a freely available genetic data of 408,455 European-ancestry individuals. We identified the 12 reliably associated loci that explain 13% of the SNP-based heritability, and prioritized the most likely causal genes CASZ1 , PIEZO1 , PPP3R1 , EBF1 , STIM2 , HFE , GATA2 , NFATC2 , and SOX9 . VVs-associated variants within these loci exhibited pleiotropic effects on several phenotypes including blood pressure/hypertension and blood cell traits. Gene set enrichment analysis revealed gene categories related to abnormal vasculogenesis. Genetic correlation analysis confirmed known epidemiological associations between VVs and deep venous thrombosis, weight, rough labor, and standing job, and found a genetic overlap with multiple traits that have not been previously suspected to share common genetic background with VVs. These traits included educational attainment, fluid intelligence and prospective memory scores, walking pace (negative correlation with VVs), smoking, height, number of operations, pain, and gonarthrosis (positive correlation with VVs). Finally, Mendelian randomization analysis provided evidence for causal effects of plasma levels of MICB and CD209 proteins, and anthropometric traits such as waist and hip circumference, height, weight, and both fat and fat-free mass. Our results provide novel insight into both VVs genetics and etiology. The revealed genes and proteins can be considered as good candidates for follow-up functional studies and might be of interest as potential drug targets.

OBJECTIVES To conduct a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). METHODS Adults of European ancestry were included from 16 cohorts in Europe and North America. CBP cases were defined as those reporting back pain present for >3-6 months; non-cases were included as comparisons (“controls”). Each cohort conducted genotyping using commercially available arrays followed by imputation. GWAS used logistic regression models with additive genetic effects, adjusting for age, sex, study-specific covariates, and population substructure. The threshold for genome-wide significance in the fixed-effect inverse-variance weighted meta-analysis was p<5×10−8. Suggestive (p<5×10−7) and genome-wide significant (p<5×10−8) variants were carried forward for replication or further investigation in an independent sample. RESULTS The discovery sample was comprised of 158,025 individuals, including 29,531 CBP cases. A genome-wide significant association was found for the intronic variant rs12310519 in SOX5 (OR 1.08, p=7.2×10−10). This was subsequently replicated in an independent sample of 283,752 subjects, including 50,915 cases (OR 1.06, p=5.3×10−11), and exceeded genome-wide significance in joint meta-analysis (OR=1.07, p=4.5×10−19). We found suggestive associations at three other loci in the discovery sample, two of which exceeded genome-wide significance in joint meta-analysis: an intergenic variant, rs7833174, located between CCDC26 and GSDMC (OR 1.05, p=4.4×10−13), and an intronic variant, rs4384683, in DCC (OR 0.97, p=2.4×10−10). DISCUSSION In this first reported meta-analysis of GWAS for CBP, we identified and replicated a genetic locus associated with CBP (SOX5). We also identified 2 other loci that reached genome-wide significance in a 2-stage joint meta-analysis (CCDC26/GSDMC and DCC).

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/m 2 ) 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.