Rare SLC13A1 variants associate with intervertebral disc disorder highlighting role of sulfate in disc pathology

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. © 2022, The Author(s)

Author Correction: Rare SLC13A1 variants associate with intervertebral disc disorder highlighting role of sulfate in disc pathology (Nature Communications, (2022), 13, 1, (634), 10.1038/s41467-022-28167-1)

The original version of this Article contained an error in Fig. 3, in which the blue and red trend lines on the left plot were incorrect. In addition, the text “Dorsalgia variants” in the table should have been italicized and underlined. The correct version of Fig. 3 is: (Figure presented.) which replaces the previous incorrect version: (Figure presented.). This has been corrected in both the PDF and HTML versions of the Article. © The Author(s) 2022

Rare SLC13A1 variants associate with intervertebral disc disorder highlighting role of sulfate in disc pathology

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. © 2022, The Author(s)

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation. © 2021 The Author

Investigation of nomophobia and smartphone addiction predictors among adolescents in Turkey: Demographic variables and academic performance

Most individuals spend a great amount of time on their smartphones. The intense usage of smartphones leads to some physical symptoms, good and bad feelings, pathological addiction, depression, symptoms such as fear-anxiety, productivity and low academic achievement. For this reason, prevention activities must be prioritized when dealing with the intense and uncontrolled usage of smartphones. The aim of this study is to determine nomophobia levels and smartphone addiction among 12-18 age group secondary and high school students and to investigate the demographic and academic variables predicting these levels. Designed with a relational model, the population of this research consists of 612 students studying at all levels of secondary school and high school. Personal information form and two different scales were used in the research. Descriptive analyses and hierarchical linear multiple regression analysis were used in the analysis of the data obtained by means of data collection in the research. As a result of the research, there is a significant relationship between smartphone addiction and nomophobia. In this study, Model 4 has been identified to be the most important predictor of smartphone addiction and nomophobia. In Model 4, variables related to smartphone usage are included in the analysis. Recommendations have been made according to the results of the study. (C) 2018 Western Social Science Association. Published by Elsevier Inc. All rights reserved