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Xu L, Li H, Liu B, Han X, Sun H. Systemic Inflammatory Regulators Associated with Osteoporosis: A Bidirectional Mendelian Randomization Study. Calcif Tissue Int 2024; 114:490-501. [PMID: 38528199 DOI: 10.1007/s00223-024-01200-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 02/20/2024] [Indexed: 03/27/2024]
Abstract
To elucidate the precise upstream and downstream regulatory mechanisms of inflammatory factors in osteoporosis (OP) progression and to establish a causal relationship between inflammatory factors and OP. We conducted bidirectional Mendelian randomization (MR) analyses using data for 41 cytokines obtained from three independent cohorts comprising 8293 Finnish individuals. Estimated bone mineral density (eBMD) data were derived from 426,824 UK Biobank White British individuals (55% female) and fracture data from 416,795 UK Biobank participants of European ancestry. The inverse variance-weighted method was the primary MR analysis approach. We employed other methods as complementary approaches for mutual corroboration. To test for pleiotropy and heterogeneity, we used the MR-Egger regression, MR-pleiotropy residual sum and outlier global test, and the Cochrane Q test. Macrophage inflammatory protein (MIP)-1α and interleukin (IL)-12p70 expression associated negatively and causally with eBMD (β = -0.017 [MIP-1α], β = -0.011 [IL-12p70]). Conversely, tumor necrosis factor-related apoptosis-inducing ligand was associated with a decreased risk of fractures (Odds Ratio: 0.980). Additionally, OP influenced the expression of multiple inflammatory factors, including growth-regulated oncogene-α, interferon-gamma, IL-6, beta nerve growth factor, and IL-2. Finally, we discovered complex bidirectional causal relationships between IL-8, IL-10, and OP. Specific inflammatory factors may contribute to OP development or may be causally affected by OP. We identified a bidirectional causal relationship between certain inflammatory factors and OP. These findings provide new perspectives for early prediction and targeted treatment of OP. Larger cohort studies are necessary in the future to further validate these findings.
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Affiliation(s)
- Lei Xu
- Department of Orthopedics, The First Hospital of Shanxi Medical University, Taiyuan, 030000, China
- The First Clinical Medical College, Shanxi Medical University, Taiyuan, 030000, China
| | - Hui Li
- Department of Orthopedics, The First Hospital of Shanxi Medical University, Taiyuan, 030000, China
- The First Clinical Medical College, Shanxi Medical University, Taiyuan, 030000, China
| | - Bin Liu
- Department of Orthopedics, The First Hospital of Shanxi Medical University, Taiyuan, 030000, China
- The First Clinical Medical College, Shanxi Medical University, Taiyuan, 030000, China
| | - Xiaoqiang Han
- Department of Orthopedics, The First Hospital of Shanxi Medical University, Taiyuan, 030000, China
| | - Haibiao Sun
- Department of Orthopedics, The First Hospital of Shanxi Medical University, Taiyuan, 030000, China.
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102
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Liaw YC, Matsuda K, Liaw YP. Identification of an novel genetic variant associated with osteoporosis: insights from the Taiwan Biobank Study. JBMR Plus 2024; 8:ziae028. [PMID: 38655459 PMCID: PMC11037432 DOI: 10.1093/jbmrpl/ziae028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 02/18/2024] [Accepted: 03/01/2024] [Indexed: 04/26/2024] Open
Abstract
Purpose The purpose of this study was to identify new independent significant SNPs associated with osteoporosis using data from the Taiwan Biobank (TWBB). Material and Methods The dataset was divided into discovery (60%) and replication (40%) subsets. Following data quality control, genome-wide association study (GWAS) analysis was performed, adjusting for sex, age, and the top 5 principal components, employing the Scalable and Accurate Implementation of the Generalized mixed model approach. This was followed by a meta-analysis of TWBB1 and TWBB2. The Functional Mapping and Annotation (FUMA) platform was used to identify osteoporosis-associated loci. Manhattan and quantile-quantile plots were generated using the FUMA platform to visualize the results. Independent significant SNPs were selected based on genome-wide significance (P < 5 × 10-8) and independence from each other (r2 < 0.6) within a 1 Mb window. Positional, eQTL(expression quantitative trait locus), and Chromatin interaction mapping were used to map SNPs to genes. Results A total of 29 084 individuals (3154 osteoporosis cases and 25 930 controls) were used for GWAS analysis (TWBB1 data), and 18 918 individuals (1917 cases and 17 001 controls) were utilized for replication studies (TWBB2 data). We identified a new independent significant SNP for osteoporosis in TWBB1, with the lead SNP rs76140829 (minor allele frequency = 0.055, P-value = 1.15 × 10-08). Replication of the association was performed in TWBB2, yielding a P-value of 6.56 × 10-3. The meta-analysis of TWBB1 and TWBB2 data demonstrated a highly significant association for SNP rs76140829 (P-value = 7.52 × 10-10). In the positional mapping of rs76140829, 6 genes (HABP2, RP11-481H12.1, RNU7-165P, RP11-139 K1.2, RP11-57H14.3, and RP11-214 N15.5) were identified through chromatin interaction mapping in mesenchymal stem cells. Conclusions Our GWAS analysis using the Taiwan Biobank dataset unveils rs76140829 in the VTI1A gene as a key risk variant associated with osteoporosis. This finding expands our understanding of the genetic basis of osteoporosis and highlights the potential regulatory role of this SNP in mesenchymal stem cells.
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Affiliation(s)
- Yi-Ching Liaw
- Department of Computational Biology and Medical Sciences, Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung 40201, Taiwan
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
- Institute of Medical Science, The University of Tokyo, Laboratory of Genome Technology, Human Genome Center, Tokyo 108-8639, Japan
| | - Yung-Po Liaw
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung 40201, Taiwan
- Institute of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung 40201, Taiwan
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103
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Prijatelj V, Grgic O, Uitterlinden AG, Wolvius EB, Rivadeneira F, Medina-Gomez C. Bone health index in the assessment of bone health: The Generation R Study. Bone 2024; 182:117070. [PMID: 38460828 DOI: 10.1016/j.bone.2024.117070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 02/25/2024] [Accepted: 03/06/2024] [Indexed: 03/11/2024]
Abstract
Bone Health Index (BHI) has been proposed as a useful instrument for assessing bone health in children. However, its relationship with fracture risk remains unknown. We aimed to investigate whether BHI is associated with bone mineral density (BMD) and prevalent fracture odds in children from the Generation R Study. We also implemented genome-wide association study (GWAS) and polygenic score (PGS) approaches to improve our understanding of BHI and its potential. In total, 4150 children (49.4 % boys; aged 9.8 years) with genotyped data and bone assessments were included in this study. BMD was measured across the total body (less head following ISCD guidelines) using a GE-Lunar iDXA densitometer; and BHI was determined from the hand DXA scans using BoneXpert®. Fractures were self-reported collected with home questionnaires. The association of BHI with BMD and fractures was evaluated using linear models corrected for age, sex, ethnicity, height, and weight. We observed a positive correlation between BHI and BMD (ρ = 0.32, p-value<0.0001). Further, every SD decrease in BHI was associated with an 11 % increased risk of prevalent fractures (OR:1.11, 95 % CI 1.00-1.24, p-value = 0.05). Our BHI GWAS identified variants (lead SNP rs1404264-A, p-value = 2.61 × 10-14) mapping to the ING3/CPED1/WNT16 locus. Children in the extreme tails of the BMD PGS presented a difference in BHI values of -0.10 standard deviations (95% CI -0.14 to -0.07; p-value<0.0001). On top of the demonstrated epidemiological association of BHI with both BMD and fracture risk, our results reveal a partially shared biological background between BHI and BMD. These findings highlight the potential value of using BHI to screen children at risk of fracture.
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Affiliation(s)
- Vid Prijatelj
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands; Department of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands; The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, the Netherlands
| | - Olja Grgic
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands; Department of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands; The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, the Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands; The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, the Netherlands; Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands
| | - Eppo B Wolvius
- Department of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands; The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, the Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands; Department of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands; The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, the Netherlands; Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands; The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, the Netherlands; Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, the Netherlands.
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104
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Jung J, Wu Q. Identification of bone mineral density associated genes with shared genetic architectures across multiple tissues: Functional insights for EPDR1, PKDCC, and SPTBN1. PLoS One 2024; 19:e0300535. [PMID: 38683846 PMCID: PMC11057974 DOI: 10.1371/journal.pone.0300535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 02/28/2024] [Indexed: 05/02/2024] Open
Abstract
Recent studies suggest a shared genetic architecture between muscle and bone, yet the underlying molecular mechanisms remain elusive. This study aims to identify the functionally annotated genes with shared genetic architecture between muscle and bone using the most up-to-date genome-wide association study (GWAS) summary statistics from bone mineral density (BMD) and fracture-related genetic variants. We employed an advanced statistical functional mapping method to investigate shared genetic architecture between muscle and bone, focusing on genes highly expressed in muscle tissue. Our analysis identified three genes, EPDR1, PKDCC, and SPTBN1, which are highly expressed in muscle tissue and previously unlinked to bone metabolism. About 90% and 85% of filtered Single-Nucleotide Polymorphisms were in the intronic and intergenic regions for the threshold at P≤5×10-8 and P≤5×10-100, respectively. EPDR1 was highly expressed in multiple tissues, including muscles, adrenal glands, blood vessels, and the thyroid. SPTBN1 was highly expressed in all 30 tissue types except blood, while PKDCC was highly expressed in all 30 tissue types except the brain, pancreas, and skin. Our study provides a framework for using GWAS findings to highlight functional evidence of crosstalk between multiple tissues based on shared genetic architecture between muscle and bone. Further research should focus on functional validation, multi-omics data integration, gene-environment interactions, and clinical relevance in musculoskeletal disorders.
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Affiliation(s)
- Jongyun Jung
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America
| | - Qing Wu
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America
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105
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Qu YD, Zhu ZH, Li JX, Zhang W, Chen Q, Xia CL, Ma JN, Ou SJ, Yang Y, Qi Y, Xu CP. Diabetes and osteoporosis: a two-sample mendelian randomization study. BMC Musculoskelet Disord 2024; 25:317. [PMID: 38654244 PMCID: PMC11036742 DOI: 10.1186/s12891-024-07430-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 04/09/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND The effects on bone mineral density (BMD)/fracture between type 1 (T1D) and type 2 (T2D) diabetes are unknown. Therefore, we aimed to investigate the causal relationship between the two types of diabetes and BMD/fracture using a Mendelian randomization (MR) design. METHODS A two-sample MR study was conducted to examine the causal relationship between diabetes and BMD/fracture, with three phenotypes (T1D, T2D, and glycosylated hemoglobin [HbA1c]) of diabetes as exposures and five phenotypes (femoral neck BMD [FN-BMD], lumbar spine BMD [LS-BMD], heel-BMD, total body BMD [TB-BMD], and fracture) as outcomes, combining MR-Egger, weighted median, simple mode, and inverse variance weighted (IVW) sensitivity assessments. Additionally, horizontal pleiotropy was evaluated and corrected using the residual sum and outlier approaches. RESULTS The IVW method showed that genetically predicted T1D was negatively associated with TB-BMD (β = -0.018, 95% CI: -0.030, -0.006), while T2D was positively associated with FN-BMD (β = 0.033, 95% CI: 0.003, 0.062), heel-BMD (β = 0.018, 95% CI: 0.006, 0.031), and TB-BMD (β = 0.050, 95% CI: 0.022, 0.079). Further, HbA1c was not associated with the five outcomes (β ranged from - 0.012 to 0.075). CONCLUSIONS Our results showed that T1D and T2D have different effects on BMD at the genetic level. BMD decreased in patients with T1D and increased in those with T2D. These findings highlight the complex interplay between diabetes and bone health, suggesting potential age-specific effects and genetic influences. To better understand the mechanisms of bone metabolism in patients with diabetes, further longitudinal studies are required to explain BMD changes in different types of diabetes.
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Grants
- 202201020303, 202102080052, 202102010057, 201804010226 Science and Technology Planning Project of Guangzhou
- 202201020303, 202102080052, 202102010057, 201804010226 Science and Technology Planning Project of Guangzhou
- 3D-A2020004, 3D-A2020002, YQ2019-009, C2020019 Foundation of Guangdong Second Provincial General Hospital
- 3D-A2020004, 3D-A2020002, YQ2019-009, C2020019 Foundation of Guangdong Second Provincial General Hospital
- 81972083 National Natural Science Foundation of China
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Affiliation(s)
- Yu-Dun Qu
- The Second School of Clinical Medicine, Guangdong Second Provincial General Hospital, Southern Medical University, Guangzhou, Guangdong, P.R. China
| | - Zhao-Hua Zhu
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Jia-Xuan Li
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, P.R. China
| | - Wei Zhang
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, No. 466 Xingang Road, Haizhu District, Guangzhou, 510317, Guangdong, People's Republic of China
| | - Qi Chen
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, No. 466 Xingang Road, Haizhu District, Guangzhou, 510317, Guangdong, People's Republic of China
| | - Chang-Liang Xia
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, No. 466 Xingang Road, Haizhu District, Guangzhou, 510317, Guangdong, People's Republic of China
| | - Jun-Nan Ma
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, No. 466 Xingang Road, Haizhu District, Guangzhou, 510317, Guangdong, People's Republic of China
| | - Shuan-Ji Ou
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, No. 466 Xingang Road, Haizhu District, Guangzhou, 510317, Guangdong, People's Republic of China
| | - Yang Yang
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, No. 466 Xingang Road, Haizhu District, Guangzhou, 510317, Guangdong, People's Republic of China
| | - Yong Qi
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, No. 466 Xingang Road, Haizhu District, Guangzhou, 510317, Guangdong, People's Republic of China.
| | - Chang-Peng Xu
- Department of Orthopaedics, Guangdong Second Provincial General Hospital, The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, P.R. China.
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106
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Li GHY, Tang CM, Wu SM, Cheung CL. Causal association of genetically determined caffeine intake from tea or coffee with bone health: a two-sample Mendelian randomization study. Postgrad Med J 2024:qgae051. [PMID: 38651568 DOI: 10.1093/postmj/qgae051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 02/24/2024] [Accepted: 03/22/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND Relationship of caffeine intake and consumption of caffeinated beverages, such as tea and coffee, with bone health remains controversial. This study aimed to evaluate whether genetically determined caffeine intake from tea or coffee has causal effects on overall total body bone mineral density (TB-BMD) and fracture. We also assessed the association with TB-BMD in five age strata. METHODS Using two-sample Mendelian randomization approach, summary statistics were retrieved from genome-wide association studies (GWAS)/GWAS meta-analyses of caffeine intake from tea (n = 395 866)/coffee (n = 373 522), TB-BMD (n = 66 628), and fracture (n = 426 795). Inverse variance weighted method was adopted as the main univariable analysis. Multivariable analysis was conducted to evaluate whether the causal effect is independent. RESULTS In univariable analysis, genetically determined caffeine intake from tea had positive association with overall TB-BMD (per SD increase in genetically determined caffeine intake, beta of TB-BMD [in SD]: 0.166; 95% confidence interval (CI): 0.006-0.326) and inverse association with fracture (OR = 0.79; 95% CI: 0.654-0.954). Genetically determined caffeine intake from coffee was also positively associated with overall TB-BMD (beta = 0.231; 95% CI: 0.093-0.369). The association remained significant after adjustment for smoking in multivariable analysis. Genetically determined caffeine intake from tea or coffee was both positively associated with TB-BMD in the age strata of 45-60 years, but we lacked evidence of association in other strata. CONCLUSIONS Genetically, caffeine intake from tea or coffee may be beneficial to bone health. Due to the ascertainment method of caffeine intake from tea, our study also implied genetically higher tea consumption may improve TB-BMD and lower fracture risk.
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Affiliation(s)
- Gloria Hoi-Yee Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Lee Shau Kee Building, 11 Yuk Choi Road, Hung Hom, Hong Kong
| | - Ching-Man Tang
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Lee Shau Kee Building, 11 Yuk Choi Road, Hung Hom, Hong Kong
| | - Suet-Man Wu
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Lee Shau Kee Building, 11 Yuk Choi Road, Hung Hom, Hong Kong
| | - Ching-Lung Cheung
- Department of Pharmacology and Pharmacy, The University of Hong Kong, Laboratory Block, 21 Sassoon Road, Pokfulam, Hong Kong
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107
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Tobias JH, Nethander M, Faber BG, Heppenstall SV, Ebsim R, Cootes T, Lindner C, Saunders FR, Gregory JS, Aspden RM, Harvey NC, Kemp JP, Frysz M, Ohlsson C. Femoral neck width genetic risk score is a novel independent risk factor for hip fractures. J Bone Miner Res 2024; 39:241-251. [PMID: 38477772 PMCID: PMC11240160 DOI: 10.1093/jbmr/zjae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 11/02/2023] [Accepted: 11/09/2023] [Indexed: 03/14/2024]
Abstract
Femoral neck width (FNW) derived from DXA scans may provide a useful adjunct to hip fracture prediction. Therefore, we investigated whether FNW is related to hip fracture risk independently of femoral neck bone mineral density (FN-BMD), using a genetic approach. FNW was derived from points automatically placed on the proximal femur using hip DXA scans from 38 150 individuals (mean age 63.8 yr, 48.0% males) in UK Biobank (UKB). Genome-wide association study (GWAS) identified 71 independent genome-wide significant FNW SNPs, comprising genes involved in cartilage differentiation, hedgehog, skeletal development, in contrast to SNPs identified by FN-BMD GWAS which primarily comprised runx1/Wnt signaling genes (MAGMA gene set analyses). FNW and FN-BMD SNPs were used to generate genetic instruments for multivariable Mendelian randomization. Greater genetically determined FNW increased risk of all hip fractures (odds ratio [OR] 1.53; 95% CI, 1.29-1.82 per SD increase) and femoral neck fractures (OR 1.58;1.30-1.92), but not trochanteric or forearm fractures. In contrast, greater genetically determined FN-BMD decreased fracture risk at all 4 sites. FNW and FN-BMD SNPs were also used to generate genetic risk scores (GRSs), which were examined in relation to incident hip fracture in UKB (excluding the FNW GWAS population; n = 338 742, 3222 cases) using a Cox proportional hazards model. FNW GRS was associated with increased risk of all incident hip fractures (HR 1.08;1.05-1.12) and femoral neck fractures (hazard ratio [HR] 1.10;1.06-1.15), but not trochanteric fractures, whereas FN-BMD GRS was associated with reduced risk of all hip fracture types. We conclude that the underlying biology regulating FNW and FN-BMD differs, and that DXA-derived FNW is causally related to hip fractures independently of FN-BMD, adding information beyond FN-BMD for hip fracture prediction. Hence, FNW derived from DXA analyses or a FNW GRS may contribute clinically useful information beyond FN-BMD for hip fracture prediction.
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Affiliation(s)
- Jonathan H Tobias
- Musculoskeletal Research Unit, Translational Health Sciences, Southmead Hospital, University of Bristol, Bristol BS10 5NB, United Kingdom
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol BS8 2BN, United Kingdom
| | - Maria Nethander
- Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, 41345 Gothenburg, Sweden
- Bioinformatics and Data Center, Sahlgrenska Academy at University of Gothenburg, 40530 Gothenburg, Sweden
| | - Benjamin G Faber
- Musculoskeletal Research Unit, Translational Health Sciences, Southmead Hospital, University of Bristol, Bristol BS10 5NB, United Kingdom
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol BS8 2BN, United Kingdom
| | - Sophie V Heppenstall
- Musculoskeletal Research Unit, Translational Health Sciences, Southmead Hospital, University of Bristol, Bristol BS10 5NB, United Kingdom
| | - Raja Ebsim
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, The University of Manchester, Manchester M13 9PT, United Kingdom
| | - Tim Cootes
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, The University of Manchester, Manchester M13 9PT, United Kingdom
| | - Claudia Lindner
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, The University of Manchester, Manchester M13 9PT, United Kingdom
| | - Fiona R Saunders
- Centre for Arthritis and Musculoskeletal Health, University of Aberdeen, Aberdeen AB24 3FX, United Kingdom
| | - Jenny S Gregory
- Centre for Arthritis and Musculoskeletal Health, University of Aberdeen, Aberdeen AB24 3FX, United Kingdom
| | - Richard M Aspden
- Centre for Arthritis and Musculoskeletal Health, University of Aberdeen, Aberdeen AB24 3FX, United Kingdom
| | - Nicholas C Harvey
- Medical Research Council Lifecourse Epidemiology Centre, University of Southampton, Southampton SO16 6YD, United Kingdom
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, United Kingdom
| | - John P Kemp
- Mater Research Institute, University of Queensland, Brisbane QLD, Australia 4102
| | - Monika Frysz
- Musculoskeletal Research Unit, Translational Health Sciences, Southmead Hospital, University of Bristol, Bristol BS10 5NB, United Kingdom
| | - Claes Ohlsson
- Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, 41345 Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, 41345 Gothenburg, Sweden
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108
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Ozgurel SU, Reyes Fernandez PC, Chanpaisaeng K, Fleet JC. Male Lrp5A214V mice maintain high bone mass during dietary calcium restriction by altering the vitamin D endocrine system. J Bone Miner Res 2024; 39:315-325. [PMID: 38477773 PMCID: PMC11240165 DOI: 10.1093/jbmr/zjae011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 12/20/2023] [Accepted: 01/10/2024] [Indexed: 03/14/2024]
Abstract
Environmental factors and genetic variation individually impact bone. However, it is not clear how these factors interact to influence peak bone mass accrual. Here we tested whether genetically programmed high bone formation driven by missense mutations in the Lrp5 gene (Lrp5A214V) altered the sensitivity of mice to an environment of inadequate dietary calcium (Ca) intake. Weanling male Lrp5A214V mice and wildtype littermates (control) were fed AIN-93G diets with 0.125%, 0.25%, 0.5% (reference, basal), or 1% Ca from weaning until 12 weeks of age (ie, during bone growth). Urinary Ca, serum Ca, Ca regulatory hormones (PTH, 1,25 dihydroxyvitamin D3 (1,25(OH)2D3)), bone parameters (μCT, ash), and renal/intestinal gene expression were analyzed. As expected, low dietary Ca intake negatively impacted bones and Lrp5A214V mice had higher bone mass and ash content. Although bones of Lrp5A214V mice have more matrix to mineralize, their bones were not more susceptible to low dietary Ca intake. In control mice, low dietary Ca intake exerted expected effects on serum Ca (decreased), PTH (increased), and 1,25(OH)2D3 (increased) as well as their downstream actions (ie, reducing urinary Ca, increasing markers of intestinal Ca absorption). In contrast, Lrp5A214V mice had elevated serum Ca with a normal PTH response but a blunted 1,25(OH)2D3 response to low dietary Ca that was reflected in the renal 1,25(OH)2D3 producing/degrading enzymes, Cyp27b1 and Cyp24a1. Despite elevated serum Ca in Lrp5A214V mice, urinary Ca was not elevated. Despite an abnormal serum 1,25(OH)2D3 response to low dietary Ca, intestinal markers of Ca absorption (Trpv6, S100g mRNA) were elevated in Lrp5A214V mice and responded to low Ca intake. Collectively, our data indicate that the Lrp5A214V mutation induces changes in Ca homeostasis that permit mice to retain more Ca and support their high bone mass phenotype.
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Affiliation(s)
- Serra Ucer Ozgurel
- Department of Nutritional Sciences, University of Texas, Austin, TX 78723, United States
| | - Perla C Reyes Fernandez
- Department of Physical Therapy, Indiana University –Purdue University, Indianapolis, IN 46202, United States
| | - Krittikan Chanpaisaeng
- National Center for Genetic Engineering and Biotechnology, Pathum Thani 12120, Thailand
- Department of Pharmacology and Physiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok 10330, Thailand
| | - James C Fleet
- Department of Nutritional Sciences, University of Texas, Austin, TX 78723, United States
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Gai S, Qian Y, Zhang Z, Zheng HF. Integrating both common and rare variants to predict bone mineral density and fracture. J Bone Miner Res 2024; 39:193-194. [PMID: 38477769 DOI: 10.1093/jbmr/zjad022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 12/19/2023] [Accepted: 12/22/2023] [Indexed: 03/14/2024]
Affiliation(s)
- Sirui Gai
- The Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
| | - Yu Qian
- The Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
| | - Zhenlin Zhang
- Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hou-Feng Zheng
- The Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
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Musolf AM, Justice CM, Erdogan-Yildirim Z, Goovaerts S, Cuellar A, Shaffer JR, Marazita ML, Claes P, Weinberg SM, Li J, Senders C, Zwienenberg M, Simeonov E, Kaneva R, Roscioli T, Di Pietro L, Barba M, Lattanzi W, Cunningham ML, Romitti PA, Boyadjiev SA. Whole genome sequencing identifies associations for nonsyndromic sagittal craniosynostosis with the intergenic region of BMP2 and noncoding RNA gene LINC01428. Sci Rep 2024; 14:8533. [PMID: 38609424 PMCID: PMC11014861 DOI: 10.1038/s41598-024-58343-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 03/27/2024] [Indexed: 04/14/2024] Open
Abstract
Craniosynostosis (CS) is a major birth defect resulting from premature fusion of cranial sutures. Nonsyndromic CS occurs more frequently than syndromic CS, with sagittal nonsyndromic craniosynostosis (sNCS) presenting as the most common CS phenotype. Previous genome-wide association and targeted sequencing analyses of sNCS have identified multiple associated loci, with the strongest association on chromosome 20. Herein, we report the first whole-genome sequencing study of sNCS using 63 proband-parent trios. Sequencing data for these trios were analyzed using the transmission disequilibrium test (TDT) and rare variant TDT (rvTDT) to identify high-risk rare gene variants. Sequencing data were also examined for copy number variants (CNVs) and de novo variants. TDT analysis identified a highly significant locus at 20p12.3, localized to the intergenic region between BMP2 and the noncoding RNA gene LINC01428. Three variants (rs6054763, rs6054764, rs932517) were identified as potential causal variants due to their probability of being transcription factor binding sites, deleterious combined annotation dependent depletion scores, and high minor allele enrichment in probands. Morphometric analysis of cranial vault shape in an unaffected cohort validated the effect of these three single nucleotide variants (SNVs) on dolichocephaly. No genome-wide significant rare variants, de novo loci, or CNVs were identified. Future efforts to identify risk variants for sNCS should include sequencing of larger and more diverse population samples and increased omics analyses, such as RNA-seq and ATAC-seq.
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Affiliation(s)
- Anthony M Musolf
- Statistical Genetics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Baltimore, MD, 21224, USA
| | - Cristina M Justice
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Bethesda, MD, 20892, USA
| | - Zeynep Erdogan-Yildirim
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, 15219, USA
| | - Seppe Goovaerts
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT-PSI, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Araceli Cuellar
- Department of Pediatrics, University of California Davis, Sacramento, CA, 95817, USA
| | - John R Shaffer
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, 15219, USA
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Mary L Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, 15219, USA
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT-PSI, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Seth M Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, 15219, USA
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Jae Li
- Bioinformatics Core, Genome Center, University of California Davis, Davis, CA, 95618, USA
| | - Craig Senders
- Department of Otolaryngology, Head and Neck Surgery, University of California Davis, Sacramento, CA, 95817, USA
| | - Marike Zwienenberg
- Department of Neurosurgery, University of California Davis, Sacramento, CA, 95817, USA
| | - Emil Simeonov
- Pediatric Clinic, Alexandrovska University Hospital, Medical University of Sofia, 1431, Sofia, Bulgaria
| | - Radka Kaneva
- Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical Faculty, Medical University of Sofia, 1431, Sofia, Bulgaria
| | - Tony Roscioli
- Neuroscience Research Australia, University of New South Wales, Sydney, Australia
| | - Lorena Di Pietro
- Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
- Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168, Rome, Italy
| | - Marta Barba
- Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
- Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168, Rome, Italy
| | - Wanda Lattanzi
- Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
- Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168, Rome, Italy
| | - Michael L Cunningham
- Seattle Children's Craniofacial Center, Center of Developmental Biology and Regenerative Medicine and Division of Craniofacial Medicine, Department of Pediatrics, University of Washington, Seattle, WA, 98105, USA
| | - Paul A Romitti
- Department of Epidemiology, College of Public Health, The University of Iowa, Iowa City, IA, 52242, USA.
| | - Simeon A Boyadjiev
- Department of Pediatrics, University of California Davis, Sacramento, CA, 95817, USA
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Zhao P, Sheng Z, Xu L, Li P, Xiao W, Yuan C, Xu Z, Yang M, Qian Y, Zhong J, Gu J, Karasik D, Zheng HF. Deciphering the complex relationship between type 2 diabetes and fracture risk with both genetic and observational evidence. eLife 2024; 12:RP89281. [PMID: 38591545 PMCID: PMC11003741 DOI: 10.7554/elife.89281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/10/2024] Open
Abstract
The 'diabetic bone paradox' suggested that type 2 diabetes (T2D) patients would have higher areal bone mineral density (BMD) but higher fracture risk than individuals without T2D. In this study, we found that the genetically predicted T2D was associated with higher BMD and lower risk of fracture in both weighted genetic risk score (wGRS) and two-sample Mendelian randomization (MR) analyses. We also identified ten genomic loci shared between T2D and fracture, with the top signal at SNP rs4580892 in the intron of gene RSPO3. And the higher expression in adipose subcutaneous and higher protein level in plasma of RSPO3 were associated with increased risk of T2D, but decreased risk of fracture. In the prospective study, T2D was observed to be associated with higher risk of fracture, but BMI mediated 30.2% of the protective effect. However, when stratified by the T2D-related risk factors for fracture, we observed that the effect of T2D on the risk of fracture decreased when the number of T2D-related risk factors decreased, and the association became non-significant if the T2D patients carried none of the risk factors. In conclusion, the genetically determined T2D might not be associated with higher risk of fracture. And the shared genetic architecture between T2D and fracture suggested a top signal around RSPO3 gene. The observed effect size of T2D on fracture risk decreased if the T2D-related risk factors could be eliminated. Therefore, it is important to manage the complications of T2D to prevent the risk of fracture.
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Affiliation(s)
- Pianpian Zhao
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, ChinaHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - Zhifeng Sheng
- Health Management Center, The Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Lin Xu
- Department of Orthopedics, Yantai Affiliated Hospital of Binzhou Medical UniversityYantaiChina
| | - Peng Li
- Department of Geratology, The Third People's Hospital of HangzhouHangzhouChina
| | - Wenjin Xiao
- Department of Endocrinology, Second Affiliated Hospital of Soochow UniversitySuzhouChina
| | - Chengda Yuan
- Department of Dermatology, Hangzhou Hospital of Traditional Chinese MedicineHangzhouChina
| | - Zhanwei Xu
- Central Health Center of Mashenqiao TownTianjinChina
| | - Mengyuan Yang
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - Yu Qian
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - Jiadong Zhong
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - Jiaxuan Gu
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - David Karasik
- Azrieli Faculty of Medicine, Bar-Ilan UniversitySafedIsrael
| | - Hou-Feng Zheng
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, ChinaHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
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112
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Moksnes MR, Hansen AF, Wolford BN, Thomas LF, Rasheed H, Simić A, Bhatta L, Brantsæter AL, Surakka I, Zhou W, Magnus P, Njølstad PR, Andreassen OA, Syversen T, Zheng J, Fritsche LG, Evans DM, Warrington NM, Nøst TH, Åsvold BO, Flaten TP, Willer CJ, Hveem K, Brumpton BM. A genome-wide association study provides insights into the genetic etiology of 57 essential and non-essential trace elements in humans. Commun Biol 2024; 7:432. [PMID: 38594418 PMCID: PMC11004147 DOI: 10.1038/s42003-024-06101-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 03/22/2024] [Indexed: 04/11/2024] Open
Abstract
Trace elements are important for human health but may exert toxic or adverse effects. Mechanisms of uptake, distribution, metabolism, and excretion are partly under genetic control but have not yet been extensively mapped. Here we report a comprehensive multi-element genome-wide association study of 57 essential and non-essential trace elements. We perform genome-wide association meta-analyses of 14 trace elements in up to 6564 Scandinavian whole blood samples, and genome-wide association studies of 43 trace elements in up to 2819 samples measured only in the Trøndelag Health Study (HUNT). We identify 11 novel genetic loci associated with blood concentrations of arsenic, cadmium, manganese, selenium, and zinc in genome-wide association meta-analyses. In HUNT, several genome-wide significant loci are also indicated for other trace elements. Using two-sample Mendelian randomization, we find several indications of weak to moderate effects on health outcomes, the most precise being a weak harmful effect of increased zinc on prostate cancer. However, independent validation is needed. Our current understanding of trace element-associated genetic variants may help establish consequences of trace elements on human health.
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Affiliation(s)
- Marta R Moksnes
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.
| | - Ailin F Hansen
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Brooke N Wolford
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Laurent F Thomas
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- BioCore-Bioinformatics Core Facility, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Laboratory Medicine, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Humaira Rasheed
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Division of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
| | - Anica Simić
- Department of Chemistry, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Laxmi Bhatta
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Anne Lise Brantsæter
- Department of Food Safety, Division of Climate and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Pål R Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Tore Syversen
- Department of Neuroscience, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
| | - Lars G Fritsche
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - David M Evans
- Institute for Molecular Biosciences, The University of Queensland, Brisbane, QLD, Australia
- Frazer Institute, The University of Queensland, Woolloongabba, QLD, Australia
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
| | - Nicole M Warrington
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- Institute for Molecular Biosciences, The University of Queensland, Brisbane, QLD, Australia
- Frazer Institute, The University of Queensland, Woolloongabba, QLD, Australia
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
| | - Therese H Nøst
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Bjørn Olav Åsvold
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Levanger, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Trond Peder Flaten
- Department of Chemistry, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Cristen J Willer
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kristian Hveem
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Levanger, Norway
| | - Ben M Brumpton
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.
- HUNT Research Centre, Department of Public Health and Nursing, NTNU-Norwegian University of Science and Technology, Levanger, Norway.
- Clinic of Medicine, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway.
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Zeng L, Li Y, Hong C, Wang J, Zhu H, Li Q, Cui H, Ma P, Li R, He J, Zhu H, Liu L, Xiao L. Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies. Osteoporos Int 2024; 35:679-689. [PMID: 38221591 DOI: 10.1007/s00198-023-06996-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 12/04/2023] [Indexed: 01/16/2024]
Abstract
Previously observational studies did not draw a clear conclusion on the association between fatty liver diseases and bone mineral density (BMD). Our large-scale studies revealed that MAFLD and hepatic steatosis had no causal effect on BMD, while some metabolic factors were correlated with BMD. The findings have important implications for the relationship between fatty liver diseases and BMD, and may help direct the clinical management of MAFLD patients who experience osteoporosis and osteopenia. PURPOSE Liver and bone are active endocrine organs with several metabolic functions. However, the link between metabolic dysfunction-associated fatty liver disease (MAFLD) and bone mineral density (BMD) is contradictory. METHODS Using the UK Biobank and National Health and Nutrition Examination Survey (NHANES) dataset, we investigated the association between MAFLD, steatosis, and BMD in the observational analysis. We performed genome-wide association analysis to identify single-nucleotide polymorphisms associated with MAFLD. Large-scale two-sample Mendelian randomization (TSMR) analyses examined the potential causal relationship between MAFLD, hepatic steatosis, or major comorbid metabolic factors, and BMD. RESULTS After adjusting for demographic factors and body mass index, logistic regression analysis demonstrated a significant association between MAFLD and reduced heel BMD. However, this association disappeared after adjusting for additional metabolic factors. MAFLD was not associated with total body, femur neck, and lumbar BMD in the NHANES dataset. Magnetic resonance imaging-measured steatosis did not show significant associations with reduced total body, femur neck, and lumbar BMD in multivariate analysis. TSMR analyses indicated that MAFLD and hepatic steatosis were not associated with BMD. Among all MAFLD-related comorbid factors, overweight and type 2 diabetes showed a causal relationship with increased BMD, while waist circumference and hyperlipidemia had the opposite effect. CONCLUSION No causal effect of MAFLD and hepatic steatosis on BMD was observed in this study, while some metabolic factors were correlated with BMD. This has important implications for understanding the relationship between fatty liver disease and BMD, which may help direct the clinical management of MAFLD patients with osteoporosis.
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Affiliation(s)
- Lin Zeng
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Yan Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Chang Hong
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Jiaren Wang
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Hongbo Zhu
- Department of Medical Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan Province, China
| | - Qimei Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Hao Cui
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Pengcheng Ma
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Ruining Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Jingzhe He
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Hong Zhu
- Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Li Liu
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Lushan Xiao
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
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114
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Dashti P, Lewallen EA, Gordon JAR, Montecino MA, Davie JR, Stein GS, van Leeuwen JPTM, van der Eerden BCJ, van Wijnen AJ. Epigenetic regulators controlling osteogenic lineage commitment and bone formation. Bone 2024; 181:117043. [PMID: 38341164 DOI: 10.1016/j.bone.2024.117043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/08/2024] [Accepted: 02/04/2024] [Indexed: 02/12/2024]
Abstract
Bone formation and homeostasis are controlled by environmental factors and endocrine regulatory cues that initiate intracellular signaling pathways capable of modulating gene expression in the nucleus. Bone-related gene expression is controlled by nucleosome-based chromatin architecture that limits the accessibility of lineage-specific gene regulatory DNA sequences and sequence-specific transcription factors. From a developmental perspective, bone-specific gene expression must be suppressed during the early stages of embryogenesis to prevent the premature mineralization of skeletal elements during fetal growth in utero. Hence, bone formation is initially inhibited by gene suppressive epigenetic regulators, while other epigenetic regulators actively support osteoblast differentiation. Prominent epigenetic regulators that stimulate or attenuate osteogenesis include lysine methyl transferases (e.g., EZH2, SMYD2, SUV420H2), lysine deacetylases (e.g., HDAC1, HDAC3, HDAC4, HDAC7, SIRT1, SIRT3), arginine methyl transferases (e.g., PRMT1, PRMT4/CARM1, PRMT5), dioxygenases (e.g., TET2), bromodomain proteins (e.g., BRD2, BRD4) and chromodomain proteins (e.g., CBX1, CBX2, CBX5). This narrative review provides a broad overview of the covalent modifications of DNA and histone proteins that involve hundreds of enzymes that add, read, or delete these epigenetic modifications that are relevant for self-renewal and differentiation of mesenchymal stem cells, skeletal stem cells and osteoblasts during osteogenesis.
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Affiliation(s)
- Parisa Dashti
- Department of Internal Medicine, Erasmus MC, Erasmus University Medical Center, Rotterdam, Netherlands; Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Eric A Lewallen
- Department of Biological Sciences, Hampton University, Hampton, VA, USA
| | | | - Martin A Montecino
- Institute of Biomedical Sciences, Faculty of Medicine, Universidad Andres Bello, Santiago, Chile; Millennium Institute Center for Genome Regulation (CRG), Santiago, Chile
| | - James R Davie
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada; CancerCare Manitoba Research Institute, CancerCare Manitoba, Winnipeg, Manitoba R3E 0V9, Canada.
| | - Gary S Stein
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
| | | | - Bram C J van der Eerden
- Department of Internal Medicine, Erasmus MC, Erasmus University Medical Center, Rotterdam, Netherlands.
| | - Andre J van Wijnen
- Department of Internal Medicine, Erasmus MC, Erasmus University Medical Center, Rotterdam, Netherlands; Department of Biochemistry, University of Vermont, Burlington, VT, USA.
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115
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Chen Y, Yu J, Li W, Wang L, Zhou X, Zhuang C, Guo W, Tian K, Zhuang R. Potential causal association between leisure sedentary behaviors and osteoporosis: A two-sample Mendelian randomization analysis. Medicine (Baltimore) 2024; 103:e37467. [PMID: 38518020 PMCID: PMC10956994 DOI: 10.1097/md.0000000000037467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 02/12/2024] [Indexed: 03/24/2024] Open
Abstract
Previous observational studies have observed a correlation between sedentary behavior and osteoporosis. However, conclusions from these studies have been contradictory. To explore the potential causal relationship between sedentary behavior and osteoporosis, we conducted a Mendelian randomization analysis. A two-sample Mendelian randomization was adopted to explore the causal relationship of leisure sedentary behavior with osteoporosis. We employed 5 methods to estimate the causal associations between leisure sedentary behavior and osteoporosis. Univariable Mendelian randomization results provided evidence for the causal relationship of the time spent on computer-use with the bone mineral density estimated by heel quantitative ultrasound (eBMD) (inverse variance weighted [IVW]: β (95% confidence interval [CI]) - 0.150 (-0.270 to -0.031), P = .013; weighted median: β (95%CI) - 0.195 (-0.336 to -0.055), P = .006). Similar associations were observed in the driving forearm bone mineral density (FABMD) (IVW: β (95%CI) - 0.933 (-1.860 to -0.007), P = .048) and driving lumbar spine bone mineral density (IVW: β (95%CI) - 0.649 (-1.175 to -0.124), P = .015). However, we did not find a significant causal relationship between the time spent on watching TV and bone mineral density. Research showed that there was a causal relationship between the time spent on computer use and driving time and eBMD, FABMD, and lumbar spine bone mineral density.
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Affiliation(s)
- Yixuan Chen
- Zhejiang Chinese Medical University, Hangzhou, China
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Jinsheng Yu
- Zhejiang Chinese Medical University, Hangzhou, China
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Wenkai Li
- Zhejiang Chinese Medical University, Hangzhou, China
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Likang Wang
- Zhejiang Chinese Medical University, Hangzhou, China
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Xing Zhou
- Zhejiang Chinese Medical University, Hangzhou, China
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | | | - Wenxuan Guo
- Zhejiang Chinese Medical University, Hangzhou, China
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Kun Tian
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Rujie Zhuang
- Zhejiang Chinese Medical University, Hangzhou, China
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
- Quzhou Traditional Chinese Medicine (TCM) Hospital at the Junction of Four Provinces, Affiliated to Zhejiang Chinese Medical University, Quzhou, China
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116
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Xu F, Zhang X, Zhang Y, Chen W, Liao Z. Causal Relationship of Obstructive Sleep Apnea with Bone Mineral Density and the Role of BMI. Nat Sci Sleep 2024; 16:325-333. [PMID: 38533250 PMCID: PMC10964782 DOI: 10.2147/nss.s443557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Accepted: 03/03/2024] [Indexed: 03/28/2024] Open
Abstract
Background Observational studies have yielded conflicting evidence concerning the relationships between obstructive sleep apnea (OSA) and bone mineral density (BMD). As the exact causal inferences remain inconclusive, we conducted a two-sample Mendelian randomization (MR) to identify the causal associations between OSA and BMD. Methods Single-nucleotide polymorphisms associated with OSA were extracted from the FinnGen study. Summary statistics for 10 BMD measured at different age or skeletal sites were obtained from the publicly available IEU GWAS database. Inverse-variance weighted (IVW) method was chosen as the primary analysis, combined with several sensitivity analyses to evaluate the robustness of results. The study design included two-sample MR and network MR. Results Our primary MR analysis revealed that genetically predicted OSA was positively linked to increased forearm BMD (β = 0.24, 95% confidence interval [CI]: 0.06-0.41, p = 0.009) and heel BMD (β=0.10, 95% CI = 0.02-0.18, p = 0.018), while no significant causal relationships were observed between OSA and total body BMD, lumbar spine BMD, or femoral neck BMD (all p > 0.05). Network MR suggests that OSA might act as a mediating factor in the effect of BMI on forearm BMD and heel BMD, with a mediated portion estimated at 73% and 84%, respectively. Conclusion Our findings provide support for a causal relationship between genetically predicted OSA and increased forearm BMD and heel BMD. Furthermore, our results suggest that OSA may play a role in mediating the influence of BMI on BMD.
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Affiliation(s)
- Fei Xu
- General Surgery Department, Zhongshan Boai Hospital, Zhongshan, Guangdong, 528400, People’s Republic of China
| | - XiuRong Zhang
- Breast Surgery Department, Zhongshan Boai Hospital, Zhongshan, Guangdong, 528400, People’s Republic of China
| | - YinRong Zhang
- General Surgery Department, Zhongshan Boai Hospital, Zhongshan, Guangdong, 528400, People’s Republic of China
| | - WenHui Chen
- Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510630, People’s Republic of China
| | - ZiCong Liao
- General Surgery Department, Zhongshan Boai Hospital, Zhongshan, Guangdong, 528400, People’s Republic of China
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Austin TR, Fink HA, Jalal DI, Törnqvist AE, Buzkova P, Barzilay JI, Lu T, Carbone L, Gabrielsen ME, Grahnemo L, Hveem K, Jonasson C, Kizer JR, Langhammer A, Mukamal KJ, Gerszten RE, Nethander M, Psaty BM, Robbins JA, Sun YV, Skogholt AH, Åsvold BO, Valderrabano RJ, Zheng J, Richards JB, Coward E, Ohlsson C. Large-scale circulating proteome association study (CPAS) meta-analysis identifies circulating proteins and pathways predicting incident hip fractures. J Bone Miner Res 2024; 39:139-149. [PMID: 38477735 PMCID: PMC11070286 DOI: 10.1093/jbmr/zjad011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 11/09/2023] [Accepted: 11/23/2023] [Indexed: 03/14/2024]
Abstract
Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. In an exploratory search of the underlying biology as reflected through the circulating proteome, we performed a comprehensive Circulating Proteome Association Study (CPAS) meta-analysis for incident hip fractures. Analyses included 6430 subjects from two prospective cohort studies (Cardiovascular Health Study and Trøndelag Health Study) with circulating proteomics data (aptamer-based 5 K SomaScan version 4.0 assay; 4979 aptamers). Associations between circulating protein levels and incident hip fractures were estimated for each cohort using age and sex-adjusted Cox regression models. Participants experienced 643 incident hip fractures. Compared with the individual studies, inverse-variance weighted meta-analyses yielded more statistically significant associations, identifying 23 aptamers associated with incident hip fractures (conservative Bonferroni correction 0.05/4979, P < 1.0 × 10-5). The aptamers most strongly associated with hip fracture risk corresponded to two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR. High levels of several inflammation-related proteins (CD14, CXCL12, MMP12, ITIH3) were also associated with increased hip fracture risk. Ingenuity pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. These analyses identified several circulating proteins and pathways consistently associated with incident hip fractures. These findings underscore the usefulness of the meta-analytic approach for comprehensive CPAS in a similar manner as has previously been observed for large-scale human genetic studies. Future studies should investigate the underlying biology of these potential novel drug targets.
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Affiliation(s)
- Thomas R Austin
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98195, United States
| | - Howard A Fink
- Geriatric Research Education and Clinical Center, VA Health Care System, Minneapolis, MN, 56401, United States
| | - Diana I Jalal
- Division of Nephrology, Department of Internal Medicine, Carver College of Medicine, Iowa City, IA, 52242, United States
- Iowa City VA Medical Center, Iowa City, IA, 52246, United States
| | - Anna E Törnqvist
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
| | - Petra Buzkova
- Department of Biostatistics, University of Washington, Seattle, WA, 98115, United States
| | - Joshua I Barzilay
- Division of Endocrinology, Kaiser Permanente of Georgia, Atlanta, GA, 30339, United States
| | - Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, H3T 1E2, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec, H3G 0B1, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, H3Y 2W4, Canada
| | - Laura Carbone
- Charlie Norwood VAMC, Augusta, GA, 30901, United States
- Department of Medicine, Medical College of Georgia, Augusta University, Augusta, GA, 30912, United States
| | - Maiken E Gabrielsen
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Louise Grahnemo
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
| | - Kristian Hveem
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
- HUNT Research Centre, NTNU, 7600, Levanger, Norway
| | - Christian Jonasson
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Jorge R Kizer
- Cardiology Section, San Francisco VA Health Care System, San Francisco, CA, 94121, United States
- Department of Medicine, Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, 94158, United States
| | - Arnulf Langhammer
- HUNT Research Centre, NTNU, 7600, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, 7600, Levanger, Norway
| | - Kenneth J Mukamal
- Department of Medicine, Beth Israel Deaconess Medical Center, Brookline, MA, 2446, United States
| | - Robert E Gerszten
- Department of Medicine, Beth Israel Deaconess Medical Center, Brookline, MA, 2446, United States
| | - Maria Nethander
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
- Bioinformatics and Data Center, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98195, United States
- Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, 98195, United States
| | - John A Robbins
- Department of Medicine, University of California, Davis, CA, 95817, United States
| | - Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, United States
| | - Anne Heidi Skogholt
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Bjørn Olav Åsvold
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, 7491, Trondheim, Norway
| | - Rodrigo J Valderrabano
- Research Program in Men’s Health, Aging and Metabolism, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, 2130, United States
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai Jiao Tong University School of Medicine, Ruijin Hospital, Shanghai, 200025, China
- Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai National Clinical Research Center for Metabolic Diseases, Shanghai Digital Medicine Innovation Center, Shanghai Jiao Tong University School of Medicine, Ruijin Hospital, Shanghai, 200025, China
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Bristol, BS8 2BN, United Kingdom
| | - J Brent Richards
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, H3T 1E2, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, H3Y 2W4, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
- Department of Medicine, McGill University, Montreal, Quebec, H4A 3J1, Canada
- Department of Twin Research, King’s College London, London, SE1 7EH, United Kingdom
| | - Eivind Coward
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
- Department of Drug Treatment, Region Västra Götaland, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden
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118
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Ye Y, Zhong R, Xiong XM, Wang CE. Association of coffee intake with bone mineral density: a Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1328748. [PMID: 38572474 PMCID: PMC10987693 DOI: 10.3389/fendo.2024.1328748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 03/04/2024] [Indexed: 04/05/2024] Open
Abstract
Background In observational studies, the relationship between coffee intake and bone mineral density (BMD) is contradictory. However, residual confounding tends to bias the results of these studies. Therefore, we used a two-sample Mendelian randomization (MR) approach to further investigate the potential causal relationship between the two. Methods Genetic instrumental variables (IVs) associated with coffee intake were derived from genome-wide association studies (GWAS) of the Food Frequency Questionnaire (FFQ) in 428,860 British individuals and matched using phenotypes in PhenoScanner. Summarized data on BMD were obtained from 537,750 participants, including total body BMD (TB-BMD), TB-BMD in five age brackets ≥60, 45-60, 30-45, 15-30, and 0-15 years, and BMD in four body sites: the lumbar spine, the femoral neck, the heel, and the ultradistal forearm. We used inverse variance weighting (IVW) methods as the primary analytical method for causal inference. In addition, several sensitivity analyses (MR-Egger, Weighted median, MR-PRESSO, Cochran's Q test, and Leave-one-out test) were used to test the robustness of the results. Results After Bonferroni correction, Coffee intake has a potential positive correlation with total body BMD (effect estimate [Beta]: 0.198, 95% confidence interval [Cl]: 0.05-0.35, P=0.008). In subgroup analyses, coffee intake was potentially positively associated with TB-BMD (45-60, 30-45 years) (Beta: 0.408, 95% Cl: 0.12-0.69, P=0.005; Beta: 0.486, 95% Cl: 0.12-0.85, P=0.010). In addition, a significant positive correlation with heel BMD was also observed (Beta: 0.173, 95% Cl: 0.08-0.27, P=0.002). The results of the sensitivity analysis were generally consistent. Conclusion The results of the present study provide genetic evidence for the idea that coffee intake is beneficial for bone density. Further studies are needed to reveal the biological mechanisms and offer solid support for clinical guidelines on osteoporosis prevention.
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Affiliation(s)
- Yang Ye
- Department of Spinal Surgery, Affiliated Sports Hospital of Chengdu Sport University, Chengdu, China
| | - Rui Zhong
- Department of Spinal Surgery, Affiliated Sports Hospital of Chengdu Sport University, Chengdu, China
- School of Sports Medicine and Health, Chengdu Sports University, Chengdu, China
| | - Xiao-ming Xiong
- Department of Spinal Surgery, Affiliated Sports Hospital of Chengdu Sport University, Chengdu, China
- School of Sports Medicine and Health, Chengdu Sports University, Chengdu, China
| | - Chuan-en Wang
- Department of Spinal Surgery, Affiliated Sports Hospital of Chengdu Sport University, Chengdu, China
- School of Sports Medicine and Health, Chengdu Sports University, Chengdu, China
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Zhao Y, Ning J, Teng H, Deng Y, Sheldon M, Shi L, Martinez C, Zhang J, Tian A, Sun Y, Nakagawa S, Yao F, Wang H, Ma L. Long noncoding RNA Malat1 protects against osteoporosis and bone metastasis. Nat Commun 2024; 15:2384. [PMID: 38493144 PMCID: PMC10944492 DOI: 10.1038/s41467-024-46602-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 03/04/2024] [Indexed: 03/18/2024] Open
Abstract
MALAT1, one of the few highly conserved nuclear long noncoding RNAs (lncRNAs), is abundantly expressed in normal tissues. Previously, targeted inactivation and genetic rescue experiments identified MALAT1 as a suppressor of breast cancer lung metastasis. On the other hand, Malat1-knockout mice are viable and develop normally. On a quest to discover the fundamental roles of MALAT1 in physiological and pathological processes, we find that this lncRNA is downregulated during osteoclastogenesis in humans and mice. Remarkably, Malat1 deficiency in mice promotes osteoporosis and bone metastasis of melanoma and mammary tumor cells, which can be rescued by genetic add-back of Malat1. Mechanistically, Malat1 binds to Tead3 protein, a macrophage-osteoclast-specific Tead family member, blocking Tead3 from binding and activating Nfatc1, a master regulator of osteoclastogenesis, which results in the inhibition of Nfatc1-mediated gene transcription and osteoclast differentiation. Notably, single-cell transcriptome analysis of clinical bone samples reveals that reduced MALAT1 expression in pre-osteoclasts and osteoclasts is associated with osteoporosis and metastatic bone lesions. Altogether, these findings identify Malat1 as a lncRNA that protects against osteoporosis and bone metastasis.
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Affiliation(s)
- Yang Zhao
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jingyuan Ning
- Institute of Basic Medical Sciences, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100010, China
| | - Hongqi Teng
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Yalan Deng
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Marisela Sheldon
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Lei Shi
- Department of Endocrine Neoplasia and Hormonal Disorders, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Consuelo Martinez
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jie Zhang
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Annie Tian
- Department of Kinesiology, Rice University, Houston, TX, 77005, USA
| | - Yutong Sun
- Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Shinichi Nakagawa
- RNA Biology Laboratory, Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, 060-0812, Japan
| | - Fan Yao
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Hai Wang
- Department of Molecular and Cellular Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, 14263, USA
| | - Li Ma
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
- The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, TX, 77030, USA.
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120
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Mou X, Sun M, Chen X. Causal effect of education on bone mineral density: A Mendelian randomization study. Medicine (Baltimore) 2024; 103:e37435. [PMID: 38489681 PMCID: PMC10939692 DOI: 10.1097/md.0000000000037435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 02/02/2024] [Accepted: 02/08/2024] [Indexed: 03/17/2024] Open
Abstract
Education level may have some association with the incidence of osteoporosis, but it is elusive if this association is causal. This two-sample Mendelian randomization analysis focused on the causal effect of education level on femoral neck bone mineral density (FN-BMD), forearm BMD, lumbar spine BMD, and heel BMD. Twelve single nucleotide polymorphisms were used as instrumental variables. The results suggested that high education level was associated with improved FN-BMD (beta-estimate: 0.406, 95% confidence interval: 0.061 to 0.751, standard error: 0.176, P-value = .021). There were null association between education and other sites of bone mineral density. Our results found the causal effect of high education level on improved FN-BMD, and improved educational attainment may be beneficial to prevent osteoporosis.
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Affiliation(s)
- Xiaoqing Mou
- Department of Radiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, China
| | - Mingqi Sun
- Department of Orthopaedic Trauma, The Second Affiliated Hospital of Inner Mongolia Medical University, Huhhot, Inner Mongolia, China
| | - Xiaojun Chen
- Department of Orthopedics, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, Sichuan, China
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Chen XF, Duan YY, Jia YY, Dong QH, Shi W, Zhang Y, Dong SS, Li M, Liu Z, Chen F, Huang XT, Hao RH, Zhu DL, Jing RH, Guo Y, Yang TL. Integrative high-throughput enhancer surveying and functional verification divulges a YY2-condensed regulatory axis conferring risk for osteoporosis. CELL GENOMICS 2024; 4:100501. [PMID: 38335956 PMCID: PMC10943593 DOI: 10.1016/j.xgen.2024.100501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/23/2023] [Accepted: 01/10/2024] [Indexed: 02/12/2024]
Abstract
The precise roles of chromatin organization at osteoporosis risk loci remain largely elusive. Here, we combined chromatin interaction conformation (Hi-C) profiling and self-transcribing active regulatory region sequencing (STARR-seq) to qualify enhancer activities of prioritized osteoporosis-associated single-nucleotide polymorphisms (SNPs). We identified 319 SNPs with biased allelic enhancer activity effect (baaSNPs) that linked to hundreds of candidate target genes through chromatin interactions across 146 loci. Functional characterizations revealed active epigenetic enrichment for baaSNPs and prevailing osteoporosis-relevant regulatory roles for their chromatin interaction genes. Further motif enrichment and network mapping prioritized several putative, key transcription factors (TFs) controlling osteoporosis binding to baaSNPs. Specifically, we selected one top-ranked TF and deciphered that an intronic baaSNP (rs11202530) could allele-preferentially bind to YY2 to augment PAPSS2 expression through chromatin interactions and promote osteoblast differentiation. Our results underline the roles of TF-mediated enhancer-promoter contacts for osteoporosis, which may help to better understand the intricate molecular regulatory mechanisms underlying osteoporosis risk loci.
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Affiliation(s)
- Xiao-Feng Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Yuan-Yuan Duan
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Ying-Ying Jia
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Qian-Hua Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Wei Shi
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Yan Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Meng Li
- Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi, China
| | - Zhongbo Liu
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Fei Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Xiao-Ting Huang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Ruo-Han Hao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Dong-Li Zhu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Rui-Hua Jing
- Department of Ophthalmology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710000, Shaanxi, China
| | - Yan Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China.
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China; Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi, China.
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122
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Chen M, Lin S, Chen W, Chen X. Antidiabetic drug administration prevents bone mineral density loss: Evidence from a two-sample Mendelian randomization study. PLoS One 2024; 19:e0300009. [PMID: 38451994 PMCID: PMC10919632 DOI: 10.1371/journal.pone.0300009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 02/19/2024] [Indexed: 03/09/2024] Open
Abstract
The aim of this study was to investigate the effect of common antidiabetic drugs on BMD by two-sample Mendelian randomization (MR). The single nucleotide polymorphisms that were strongly associated with insulin, metformin, rosiglitazone and gliclazide were extracted as instrumental variables (IVs) for MR analysis. The inverse variance weighted (IVW) method was used as the primary MR method to assess the causal effect of antidiabetic drugs on BMD, and other MR methods, including Weighted median, MR Egger and Weighted mode, were used for complementary analysis. Reliability and stability were assessed by the leave-one-out test. In the present work, IVW estimation of the causal effect of insulin on heel BMD demonstrated that there was a null effect of insulin on heel BMD (β = 0.765; se = 0.971; P = 0.430), while metformin treatment had a positive effect on heel BMD (β = 1.414; se = 0.460; P = 2.118*10-3). The causal relationship between rosiglitazone and heel BMD analysed by IVW suggested that there was a null effect of rosiglitazone on heel BMD (β = -0.526; se = 1.744; P = 0.763), but the causal effect of gliclazide on heel BMD evaluated by IVW demonstrated that there was a positive effect of gliclazide on heel BMD (β = 2.671; se = 1.340; P = 0.046). In summary, the present work showed that metformin and gliclazide have a role in reducing BMD loss in patients with diabetes and are recommended for BMD loss prevention in diabetes.
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Affiliation(s)
- Mingzhu Chen
- School of Pharmacy, Quanzhou Medical College, Quanzhou, China
| | - Shuisen Lin
- School of Pharmacy, Quanzhou Medical College, Quanzhou, China
| | - Wanqiong Chen
- School of Pharmacy, Quanzhou Medical College, Quanzhou, China
| | - Xiaoqiang Chen
- Department of Orthopaedic Surgery, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China
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123
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Tang AS, Rankin KP, Cerono G, Miramontes S, Mills H, Roger J, Zeng B, Nelson C, Soman K, Woldemariam S, Li Y, Lee A, Bove R, Glymour M, Aghaeepour N, Oskotsky TT, Miller Z, Allen IE, Sanders SJ, Baranzini S, Sirota M. Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights. NATURE AGING 2024; 4:379-395. [PMID: 38383858 PMCID: PMC10950787 DOI: 10.1038/s43587-024-00573-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 01/19/2024] [Indexed: 02/23/2024]
Abstract
Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.
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Affiliation(s)
- Alice S Tang
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
- Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, San Francisco and Berkeley, CA, USA.
| | - Katherine P Rankin
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Gabriel Cerono
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Silvia Miramontes
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Hunter Mills
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Jacquelyn Roger
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Billy Zeng
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Charlotte Nelson
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Karthik Soman
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Sarah Woldemariam
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Yaqiao Li
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Albert Lee
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Riley Bove
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Maria Glymour
- Department of Anesthesiology, Pain, and Perioperative Medicine, Stanford University, Palo Alto, CA, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Pain, and Perioperative Medicine, Stanford University, Palo Alto, CA, USA
- Department of Pediatrics, Stanford University, Palo Alto, CA, USA
- Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA
| | - Tomiko T Oskotsky
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Zachary Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Isabel E Allen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Stephan J Sanders
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, UK
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Sergio Baranzini
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
- Department of Pediatrics, University of California, San Francisco, CA, USA.
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124
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Liu J, Bao X, Huang J, Chen R, Tan Y, Zhang Z, Xiao B, Kong F, Gu C, Du J, Wang H, Qi J, Tan J, Ma D, Shi C, Xu G. TMEM135 maintains the equilibrium of osteogenesis and adipogenesis by regulating mitochondrial dynamics. Metabolism 2024; 152:155767. [PMID: 38154611 DOI: 10.1016/j.metabol.2023.155767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/10/2023] [Accepted: 12/20/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND Disturbance in the differentiation process of bone marrow mesenchymal stem cells (BMSCs) leads to osteoporosis. Mitochondrial dynamics plays a pivotal role in the metabolism and differentiation of BMSCs. However, the mechanisms underlying mitochondrial dynamics and their impact on the differentiation equilibrium of BMSCs remain unclear. METHODS We investigated the mitochondrial morphology and markers related to mitochondrial dynamics during BMSCs osteogenic and adipogenic differentiation. Bioinformatics was used to screen potential genes regulating BMSCs differentiation through mitochondrial dynamics. Subsequently, we evaluated the impact of Transmembrane protein 135 (TMEM135) deficiency on bone homeostasis by comparing Tmem135 knockout mice with their littermates. The mechanism of TMEM135 in mitochondrial dynamics and BMSCs differentiation was also investigated in vivo and in vitro. RESULTS Distinct changes in mitochondrial morphology were observed between osteogenic and adipogenic differentiation of BMSCs, manifesting as fission in the late stage of osteogenesis and fusion in adipogenesis. Additionally, we revealed that TMEM135, a modulator of mitochondrial dynamics, played a functional role in regulating the equilibrium between adipogenesis and osteogenesis. The TMEM135 deficiency impaired mitochondrial fission and disrupted crucial mitochondrial energy metabolism during osteogenesis. Tmem135 knockout mice showed osteoporotic phenotype, characterized by reduced osteogenesis and increased adipogenesis. Mechanistically, TMEM135 maintained intracellular calcium ion homeostasis and facilitated the dephosphorylation of dynamic-related protein 1 at Serine 637 in BMSCs. CONCLUSIONS Our findings underscore the significant role of TMEM135 as a modulator in orchestrating the differentiation trajectory of BMSCs and promoting a shift in mitochondrial dynamics toward fission. This ultimately contributes to the osteogenesis process. This work has provided promising biological targets for the treatment of osteoporosis.
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Affiliation(s)
- Jia Liu
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Xiaogang Bao
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Jian Huang
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Rukun Chen
- Faculty of Medicine, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Yixuan Tan
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Zheng Zhang
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Bing Xiao
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Fanqi Kong
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Changjiang Gu
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Jianhang Du
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Haotian Wang
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Junqiang Qi
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China
| | - Junming Tan
- Department of Orthopedics, The 72nd Army Hospital of the People's Liberation Army, Huzhou 313099, PR China
| | - Duan Ma
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, PR China.
| | - Changgui Shi
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China.
| | - Guohua Xu
- Department of Orthopedic Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200003, PR China.
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125
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Zhao J, Wang J, Xu H, Hu W, Shi F, Fan Z, Zhou C, Mu H. Intervertebral Disk Degeneration and Bone Mineral Density: A Bidirectional Mendelian Randomization Study. Calcif Tissue Int 2024; 114:228-236. [PMID: 37978069 PMCID: PMC10902056 DOI: 10.1007/s00223-023-01165-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 11/10/2023] [Indexed: 11/19/2023]
Abstract
This study aimed to investigate the causal relationship between bone mineral density (BMD) and intervertebral disk degeneration (IVDD) using a two-sample bidirectional Mendelian randomization analysis. Summary-level data from the Genome-Wide Association Study (GWAS) were used. Instrumental variables (IVs) for IVDD were selected from the large-scale Genome-Wide Association Study (GWAS) (20,001 cases and 164,682 controls). Bone mineral density (BMD) at five different sites (heel (n = 426,824), total body (TB) (n = 56,284), forearm (FA) (n = 8143), femoral neck (FN) (n = 32,735), and lumbar spine (LS) (n = 28,498)) was used as a phenotype for OP. Bidirectional causality between IVDD and BMD was assessed using inverse variance weighting (IVW) and other methods. Related sensitivity analyses were performed. Myopia was also analyzed as a negative control result to ensure the validity of IVs. Heel bone mineral density (heel BMD), total body bone mineral density (TB-BMD), femoral neck bone mineral density (FN-BMD), and lumbar spine bone mineral density (LS-BMD) have a direct causal relationship on intervertebral disk degeneration (IVDD) [heel BMD-related analysis: beta = 0.06, p = 0.03; TB-BMD-related analysis: beta = 0.18, p = 8.72E-08; FN-BMD-related analysis: beta = 0.15, p = 4.89E-03; LS-BMD-related analysis: beta = 0.16, p = 1.43E-04]. There was no evidence of a significant causal effect of IVDD on BMD. In conclusion, our study found a significant positive causal effect of lower BMD on IVDD, and we identified significant causal effects of heel, TB-, FN-, and LS-BMD on IVDD, but there was no evidence of a significant causal effect of IVDD on BMD.
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Affiliation(s)
- Jie Zhao
- Department of Clinical Lab, Tianjin First Central Hospital, 300192, Tianjin, China
| | - Jingyu Wang
- Department of Clinical Lab, Tianjin First Central Hospital, 300192, Tianjin, China
| | - Haixu Xu
- Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, 300070, Tianjin, China
| | - Wei Hu
- Department of Spine Surgery, Tianjin People's Hospital, 300122, Tianjin, China
| | - Fangyuan Shi
- School of Information Engineering, Ningxia University, Yinchuan, China
| | - Zhengrui Fan
- Department of Orthopedics, Tianjin University Tianjin Hospital, 300211, Tianjin, China.
| | - Chunlei Zhou
- Department of Clinical Lab, Tianjin First Central Hospital, 300192, Tianjin, China.
| | - Hong Mu
- Department of Clinical Lab, Tianjin First Central Hospital, 300192, Tianjin, China.
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126
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Adams DJ, Barlas B, McIntyre RE, Salguero I, van der Weyden L, Barros A, Vicente JR, Karimpour N, Haider A, Ranzani M, Turner G, Thompson NA, Harle V, Olvera-León R, Robles-Espinoza CD, Speak AO, Geisler N, Weninger WJ, Geyer SH, Hewinson J, Karp NA, Fu B, Yang F, Kozik Z, Choudhary J, Yu L, van Ruiten MS, Rowland BD, Lelliott CJ, Del Castillo Velasco-Herrera M, Verstraten R, Bruckner L, Henssen AG, Rooimans MA, de Lange J, Mohun TJ, Arends MJ, Kentistou KA, Coelho PA, Zhao Y, Zecchini H, Perry JRB, Jackson SP, Balmus G. Genetic determinants of micronucleus formation in vivo. Nature 2024; 627:130-136. [PMID: 38355793 PMCID: PMC10917660 DOI: 10.1038/s41586-023-07009-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 12/21/2023] [Indexed: 02/16/2024]
Abstract
Genomic instability arising from defective responses to DNA damage1 or mitotic chromosomal imbalances2 can lead to the sequestration of DNA in aberrant extranuclear structures called micronuclei (MN). Although MN are a hallmark of ageing and diseases associated with genomic instability, the catalogue of genetic players that regulate the generation of MN remains to be determined. Here we analyse 997 mouse mutant lines, revealing 145 genes whose loss significantly increases (n = 71) or decreases (n = 74) MN formation, including many genes whose orthologues are linked to human disease. We found that mice null for Dscc1, which showed the most significant increase in MN, also displayed a range of phenotypes characteristic of patients with cohesinopathy disorders. After validating the DSCC1-associated MN instability phenotype in human cells, we used genome-wide CRISPR-Cas9 screening to define synthetic lethal and synthetic rescue interactors. We found that the loss of SIRT1 can rescue phenotypes associated with DSCC1 loss in a manner paralleling restoration of protein acetylation of SMC3. Our study reveals factors involved in maintaining genomic stability and shows how this information can be used to identify mechanisms that are relevant to human disease biology1.
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Affiliation(s)
- D J Adams
- Wellcome Sanger Institute, Cambridge, UK.
| | - B Barlas
- UK Dementia Research Institute at the University of Cambridge, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | - I Salguero
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK
| | | | - A Barros
- Wellcome Sanger Institute, Cambridge, UK
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - J R Vicente
- UK Dementia Research Institute at the University of Cambridge, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - N Karimpour
- UK Dementia Research Institute at the University of Cambridge, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - A Haider
- UK Dementia Research Institute at the University of Cambridge, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - M Ranzani
- Wellcome Sanger Institute, Cambridge, UK
| | - G Turner
- Wellcome Sanger Institute, Cambridge, UK
| | | | - V Harle
- Wellcome Sanger Institute, Cambridge, UK
| | | | - C D Robles-Espinoza
- Wellcome Sanger Institute, Cambridge, UK
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, México
| | - A O Speak
- Wellcome Sanger Institute, Cambridge, UK
| | - N Geisler
- Wellcome Sanger Institute, Cambridge, UK
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - W J Weninger
- Division of Anatomy, MIC, Medical University of Vienna, Wien, Austria
| | - S H Geyer
- Division of Anatomy, MIC, Medical University of Vienna, Wien, Austria
| | - J Hewinson
- Wellcome Sanger Institute, Cambridge, UK
| | - N A Karp
- Wellcome Sanger Institute, Cambridge, UK
| | - B Fu
- Wellcome Sanger Institute, Cambridge, UK
| | - F Yang
- Wellcome Sanger Institute, Cambridge, UK
| | - Z Kozik
- Functional Proteomics Group, Chester Beatty Laboratories, The Institute of Cancer Research, London, UK
| | - J Choudhary
- Functional Proteomics Group, Chester Beatty Laboratories, The Institute of Cancer Research, London, UK
| | - L Yu
- Functional Proteomics Group, Chester Beatty Laboratories, The Institute of Cancer Research, London, UK
| | - M S van Ruiten
- Division of Cell Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - B D Rowland
- Division of Cell Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | | | | | - L Bruckner
- Experimental and Clinical Research Center (ECRC) of the MDC and Charité Berlin, Berlin, Germany
- Max-Delbrück-Centrum für Molekulare Medizin, Berlin, Germany
| | - A G Henssen
- Experimental and Clinical Research Center (ECRC) of the MDC and Charité Berlin, Berlin, Germany
- Max-Delbrück-Centrum für Molekulare Medizin, Berlin, Germany
- Department of Pediatric Oncology and Hematology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - M A Rooimans
- Department of Human Genetics, Section of Oncogenetics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Cancer Biology and Immunology, Amsterdam, The Netherlands
| | - J de Lange
- Department of Human Genetics, Section of Oncogenetics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Cancer Biology and Immunology, Amsterdam, The Netherlands
| | - T J Mohun
- Division of Developmental Biology, MRC, National Institute for Medical Research, London, UK
| | - M J Arends
- Division of Pathology, Cancer Research UK Scotland Centre, Institute of Genetics & Cancer The University of Edinburgh, Edinburgh, UK
| | - K A Kentistou
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - P A Coelho
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Y Zhao
- UK Dementia Research Institute at the University of Cambridge, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - H Zecchini
- Metabolic Research Laboratory, Wellcome-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - J R B Perry
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Metabolic Research Laboratory, Wellcome-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - S P Jackson
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, Cambridge, UK
| | - G Balmus
- Wellcome Sanger Institute, Cambridge, UK.
- UK Dementia Research Institute at the University of Cambridge, University of Cambridge, Cambridge, UK.
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK.
- Department of Molecular Neuroscience, Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania.
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127
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Smit A, Meijer O, Winter E. The multi-faceted nature of age-associated osteoporosis. Bone Rep 2024; 20:101750. [PMID: 38566930 PMCID: PMC10985042 DOI: 10.1016/j.bonr.2024.101750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 03/03/2024] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Age-associated osteoporosis (AAOP) poses a significant health burden, characterized by increased fracture risk due to declining bone mass and strength. Effective prevention and early treatment strategies are crucial to mitigate the disease burden and the associated healthcare costs. Current therapeutic approaches effectively target the individual contributing factors to AAOP. Nonetheless, the management of AAOP is complicated by the multitude of variables that affect its development. Main intrinsic and extrinsic factors contributing to AAOP risk are reviewed here, including mechanical unloading, nutrient deficiency, hormonal disbalance, disrupted metabolism, cognitive decline, inflammation and circadian disruption. Furthermore, it is discussed how these can be targeted for prevention and treatment. Although valuable as individual targets for intervention, the interconnectedness of these risk factors result in a unique etiology for every patient. Acknowledgement of the multifaceted nature of AAOP will enable the development of more effective and sustainable management strategies, based on a holistic, patient-centered approach.
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Affiliation(s)
- A.E. Smit
- Department of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden, the Netherlands
| | - O.C. Meijer
- Department of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden, the Netherlands
| | - E.M. Winter
- Department of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden, the Netherlands
- Department of Medicine, Center for Bone Quality, Leiden University Medical Center, Leiden, the Netherlands
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128
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Lu Z, Li X, Qi Y, Li B, Chen L. Genetic evidence of the causal relationship between chronic liver diseases and musculoskeletal disorders. J Transl Med 2024; 22:138. [PMID: 38321551 PMCID: PMC10845502 DOI: 10.1186/s12967-024-04941-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/30/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND Chronic liver diseases constitute a major global public health burden, posing a substantial threat to patients' daily lives and even survival due to the potential development of musculoskeletal disorders. Although the relationship between chronic liver diseases and musculoskeletal disorders has received extensive attention, their causal relationship has not been comprehensively and systematically investigated. METHODS This study aimed to assess the causal relationships between viral hepatitis, primary biliary cholangitis, primary sclerosing cholangitis (PSC), liver cirrhosis, and hepatocellular carcinoma (HCC) with osteoporosis, osteoarthritis, and sarcopenia through bidirectional Mendelian randomization (MR) research. The traits related to osteoporosis and osteoarthritis included both overall and site-specific phenotypes, and the traits linked to sarcopenia involved indicators of muscle mass and function. Random-effect inverse-variance weighted (IVW), weighted median, MR-Egger, and Causal Analysis Using the Summary Effect Estimates were used to evaluate causal effects, with IVW being the main analysis method. To enhance robustness, sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept, MR-PRESSO global test, funnel plots, leave-one-out analyses, and latent causal variable model. RESULTS The forward MR analysis indicated that PSC can reduce forearm bone mineral density (beta = - 0.0454, 95% CI - 0.0798 to - 0.0110; P = 0.0098) and increase the risk of overall osteoarthritis (OR = 1.012, 95% CI 1.002-1.022; P = 0.0247), while HCC can decrease grip strength (beta = - 0.0053, 95% CI - 0.008 to - 0.0025; P = 0.0002). The reverse MR analysis did not find significant causal effects of musculoskeletal disorders on chronic liver diseases. Additionally, no heterogeneity or pleiotropy was detected. CONCLUSIONS These findings corroborate the causal effects of PSC on osteoporosis and osteoarthritis, as well as the causal impact of HCC on sarcopenia. Thus, the implementation of comprehensive preventive measures is imperative for PSC and HCC patients to mitigate the risk of musculoskeletal disorders, ultimately improving their quality of life.
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Affiliation(s)
- Zhengjie Lu
- Division of Joint Surgery and Sports Medicine, Department of Orthopedic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430000, China
| | - Xuefei Li
- Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Yongjian Qi
- Department of Spine Surgery and Musculoskeletal Tumor, Department of Orthopedic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Bin Li
- Division of Joint Surgery and Sports Medicine, Department of Orthopedic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430000, China.
| | - Liaobin Chen
- Division of Joint Surgery and Sports Medicine, Department of Orthopedic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430000, China.
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129
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Emanuelsson F, Afzal S, Jørgensen NR, Nordestgaard BG, Benn M. Hyperglycaemia, diabetes and risk of fragility fractures: observational and Mendelian randomisation studies. Diabetologia 2024; 67:301-311. [PMID: 38095658 PMCID: PMC10789835 DOI: 10.1007/s00125-023-06054-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/12/2023] [Indexed: 01/16/2024]
Abstract
AIMS/HYPOTHESIS Fragility fractures may be a complication of diabetes, partly caused by chronic hyperglycaemia. We hypothesised that: (1) individuals with hyperglycaemia and diabetes have increased risk of fragility fracture; (2) hyperglycaemia is causally associated with increased risk of fragility fracture; and (3) diabetes and fragility fracture jointly associate with the highest risk of all-cause mortality. METHODS In total, 117,054 individuals from the Copenhagen City Heart Study and the Copenhagen General Population Study (the Copenhagen studies) and 390,374 individuals from UK Biobank were included for observational and one-sample Mendelian randomisation (MR) analyses. Fragility fractures were defined as fractures at the hip, spine and arm (humerus/wrist), collected from national health registries. Summary data for fasting glucose and HbA1c concentrations from 196,743 individuals in the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) were combined with data on fragility fractures from the Copenhagen studies in two-sample MR analyses. RESULTS Higher fasting and non-fasting glucose and HbA1c concentrations were associated with higher risk of any fragility fracture (p<0.001). Individuals with vs without diabetes had HRs for fragility fracture of 1.50 (95% CI 1.19, 1.88) in type 1 diabetes and 1.22 (1.13, 1.32) in type 2 diabetes. One-sample MR supported a causal association between high non-fasting glucose concentrations and increased risk of arm fracture in the Copenhagen studies and UK Biobank combined (RR 1.41 [1.11, 1.79], p=0.004), with similar results for fasting glucose and HbA1c in two-sample MR analyses (ORs 1.50 [1.03, 2.18], p=0.03; and 2.79 [1.12, 6.93], p=0.03, respectively). The corresponding MR estimates for any fragility fracture were 1.18 (1.00, 1.41), p=0.06; 1.36 (0.89, 2.09), p=0.15; and 2.47 (0.95, 6.43), p=0.06, respectively. At age 80 years, cumulative death was 27% in individuals with fragility fracture only, 54% in those with diabetes only, 67% in individuals with both conditions and 17% in those with neither. CONCLUSIONS/INTERPRETATION Hyperglycaemia and diabetes are risk factors for fragility fracture and one- and two-sample MR analyses supported a causal effect of hyperglycaemia on arm fractures. Diabetes and previous fragility fracture jointly conferred the highest risk of death in the general population.
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Affiliation(s)
- Frida Emanuelsson
- Department of Clinical Biochemistry, Copenhagen University Hospital Rigshospitalet, Centre of Diagnostic Investigation, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Shoaib Afzal
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Copenhagen University Hospital Herlev and Gentofte, Herlev, Denmark
- The Copenhagen General Population Study, Copenhagen University Hospital Herlev and Gentofte, Herlev, Denmark
| | - Niklas R Jørgensen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Copenhagen University Hospital Rigshospitalet, Centre of Diagnostic Investigation, Glostrup, Denmark
| | - Børge G Nordestgaard
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Copenhagen University Hospital Herlev and Gentofte, Herlev, Denmark
- The Copenhagen General Population Study, Copenhagen University Hospital Herlev and Gentofte, Herlev, Denmark
| | - Marianne Benn
- Department of Clinical Biochemistry, Copenhagen University Hospital Rigshospitalet, Centre of Diagnostic Investigation, Copenhagen, Denmark.
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
- The Copenhagen General Population Study, Copenhagen University Hospital Herlev and Gentofte, Herlev, Denmark.
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130
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Wang Y, Huang X, Zhang Q, Cheng C, Qin Z, Lu L, Huang Q. The osteoporosis susceptibility SNP rs188303909 at 2q14.2 regulates EN1 expression by modulating DNA methylation and E2F6 binding. J Mol Med (Berl) 2024; 102:273-284. [PMID: 38153509 DOI: 10.1007/s00109-023-02412-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 12/11/2023] [Accepted: 12/19/2023] [Indexed: 12/29/2023]
Abstract
EN1 encodes a homeodomain-containing transcription factor and is a determinant of bone density and fracture. Previous powerful genome-wide association studies (GWASs) have identified multiple single-nucleotide polymorphisms (SNPs) near EN1 at 2q14.2 locus for osteoporosis, but the causal SNPs and functional mechanisms underlying these associations are poorly understood. The target genes regulated by the transcription factor EN1 are also unclear. In this study, we identified rs188303909, a functional CpG-SNP, as a causal SNP for osteoporosis at 2q14.2 through the integration of functional and epigenomic analyses. Functional experiments demonstrated that unmethylated rs188303909 acted as a strong allele-specific distal enhancer to regulate EN1 expression by modifying the binding of transcription factor E2F6, but rs188303909 methylation attenuated the active effect of E2F6 on EN1 expression. Importantly, transcription factor EN1 could differentially bind osteoporosis GWAS lead SNPs rs4869739-T and rs4355801-G to upregulate CCDC170 and COLEC10 expression, thus promoting bone formation. Our study provided a mechanistic insight into expression regulation of the osteoporosis susceptibility gene EN1, which could be a potential therapeutic target for osteoporosis precision medicine. KEY MESSAGES: CpG-SNP rs188303909 is a causal SNP at the osteoporosis susceptibility locus 2q14.2. Rs188303909 distally regulates EN1 expression by modulating DNA methylation and E2F6 binding. EN1 upregulates CCDC170 and COLEC10 expression through osteoporosis GWAS lead SNPs rs4869739 and rs4355801.
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Affiliation(s)
- Ya Wang
- Hubei Key Laboratory of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, Hubei, 430079, China
- Key Laboratory of Laboratory Medicine, Ministry of Education, Zhejiang Provincial Key Laboratory of Medical Genetics, School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, 325035, China
| | - Xinyao Huang
- Hubei Key Laboratory of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, Hubei, 430079, China
| | - Qiongdan Zhang
- Hubei Key Laboratory of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, Hubei, 430079, China
| | - Chen Cheng
- Hubei Key Laboratory of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, Hubei, 430079, China
| | - Zixuan Qin
- Hubei Key Laboratory of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, Hubei, 430079, China
| | - Li Lu
- Hubei Key Laboratory of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, Hubei, 430079, China
| | - Qingyang Huang
- Hubei Key Laboratory of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, Wuhan, Hubei, 430079, China.
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131
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Sterenborg RBTM, Steinbrenner I, Li Y, Bujnis MN, Naito T, Marouli E, Galesloot TE, Babajide O, Andreasen L, Astrup A, Åsvold BO, Bandinelli S, Beekman M, Beilby JP, Bork-Jensen J, Boutin T, Brody JA, Brown SJ, Brumpton B, Campbell PJ, Cappola AR, Ceresini G, Chaker L, Chasman DI, Concas MP, Coutinho de Almeida R, Cross SM, Cucca F, Deary IJ, Kjaergaard AD, Echouffo Tcheugui JB, Ellervik C, Eriksson JG, Ferrucci L, Freudenberg J, Fuchsberger C, Gieger C, Giulianini F, Gögele M, Graham SE, Grarup N, Gunjača I, Hansen T, Harding BN, Harris SE, Haunsø S, Hayward C, Hui J, Ittermann T, Jukema JW, Kajantie E, Kanters JK, Kårhus LL, Kiemeney LALM, Kloppenburg M, Kühnel B, Lahti J, Langenberg C, Lapauw B, Leese G, Li S, Liewald DCM, Linneberg A, Lominchar JVT, Luan J, Martin NG, Matana A, Meima ME, Meitinger T, Meulenbelt I, Mitchell BD, Møllehave LT, Mora S, Naitza S, Nauck M, Netea-Maier RT, Noordam R, Nursyifa C, Okada Y, Onano S, Papadopoulou A, Palmer CNA, Pattaro C, Pedersen O, Peters A, Pietzner M, Polašek O, Pramstaller PP, Psaty BM, Punda A, Ray D, Redmond P, Richards JB, Ridker PM, Russ TC, Ryan KA, Olesen MS, Schultheiss UT, Selvin E, Siddiqui MK, et alSterenborg RBTM, Steinbrenner I, Li Y, Bujnis MN, Naito T, Marouli E, Galesloot TE, Babajide O, Andreasen L, Astrup A, Åsvold BO, Bandinelli S, Beekman M, Beilby JP, Bork-Jensen J, Boutin T, Brody JA, Brown SJ, Brumpton B, Campbell PJ, Cappola AR, Ceresini G, Chaker L, Chasman DI, Concas MP, Coutinho de Almeida R, Cross SM, Cucca F, Deary IJ, Kjaergaard AD, Echouffo Tcheugui JB, Ellervik C, Eriksson JG, Ferrucci L, Freudenberg J, Fuchsberger C, Gieger C, Giulianini F, Gögele M, Graham SE, Grarup N, Gunjača I, Hansen T, Harding BN, Harris SE, Haunsø S, Hayward C, Hui J, Ittermann T, Jukema JW, Kajantie E, Kanters JK, Kårhus LL, Kiemeney LALM, Kloppenburg M, Kühnel B, Lahti J, Langenberg C, Lapauw B, Leese G, Li S, Liewald DCM, Linneberg A, Lominchar JVT, Luan J, Martin NG, Matana A, Meima ME, Meitinger T, Meulenbelt I, Mitchell BD, Møllehave LT, Mora S, Naitza S, Nauck M, Netea-Maier RT, Noordam R, Nursyifa C, Okada Y, Onano S, Papadopoulou A, Palmer CNA, Pattaro C, Pedersen O, Peters A, Pietzner M, Polašek O, Pramstaller PP, Psaty BM, Punda A, Ray D, Redmond P, Richards JB, Ridker PM, Russ TC, Ryan KA, Olesen MS, Schultheiss UT, Selvin E, Siddiqui MK, Sidore C, Slagboom PE, Sørensen TIA, Soto-Pedre E, Spector TD, Spedicati B, Srinivasan S, Starr JM, Stott DJ, Tanaka T, Torlak V, Trompet S, Tuhkanen J, Uitterlinden AG, van den Akker EB, van den Eynde T, van der Klauw MM, van Heemst D, Verroken C, Visser WE, Vojinovic D, Völzke H, Waldenberger M, Walsh JP, Wareham NJ, Weiss S, Willer CJ, Wilson SG, Wolffenbuttel BHR, Wouters HJCM, Wright MJ, Yang Q, Zemunik T, Zhou W, Zhu G, Zöllner S, Smit JWA, Peeters RP, Köttgen A, Teumer A, Medici M. Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications. Nat Commun 2024; 15:888. [PMID: 38291025 PMCID: PMC10828500 DOI: 10.1038/s41467-024-44701-9] [Show More Authors] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 12/29/2023] [Indexed: 02/01/2024] Open
Abstract
To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.
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Affiliation(s)
- Rosalie B T M Sterenborg
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | | | - Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- Digital Environment Research Institute, Queen Mary University of London, London, UK
| | - Tessel E Galesloot
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Oladapo Babajide
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Laura Andreasen
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Arne Astrup
- Department of Obesity and Nutritional Sciences, The Novo Nordisk Foundation, Hellerup, Denmark
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | | | - Marian Beekman
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - John P Beilby
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, 6009, Australia
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thibaud Boutin
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Suzanne J Brown
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
| | - Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, 7600, Norway
| | - Purdey J Campbell
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
| | - Anne R Cappola
- Division of Endocrinology, Diabetes, and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
| | - Graziano Ceresini
- Oncological Endocrinology, University of Parma, Parma, Italy
- Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Layal Chaker
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
| | - Rodrigo Coutinho de Almeida
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Simone M Cross
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
- Università di Sassari, Dipartimento di Scienze Biomediche, V.le San Pietro, 07100, Sassari (SS), Italy
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Alisa Devedzic Kjaergaard
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Palle Juul-Jensens Blvd. 11, Entrance A, 8200, Aarhus, Denmark
| | - Justin B Echouffo Tcheugui
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Christina Ellervik
- Harvard Medical School, Boston, USA
- Faculty of Medical Science, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Laboratory Medicine, Boston Children's Hospital, Boston, MA, USA
- Department of Clinical Biochemistry, Zealand University Hospital, Køge, Denmark
| | - Johan G Eriksson
- Department of General Practice and Primary health Care, University of Helsinki, Helsinki, Finland
- National University Singapore, Yong Loo Lin School of Medicine, Department of Obstetrics and Gynecology, Singapore, Singapore
| | - Luigi Ferrucci
- Longitudinal Study Section, National Institute on Aging, Baltimore, MD, USA
| | | | - Christian Fuchsberger
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
| | - Martin Gögele
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Sarah E Graham
- Department of Internal Medicine, Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivana Gunjača
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Barbara N Harding
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Barcelona Institute for Global Health, Barcelona, Spain
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Stig Haunsø
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jennie Hui
- Pathwest Laboratory Medicine WA, Nedlands, WA, 6009, Australia
- School of Population and Global Health, The University of Western Australia, Crawley, WA, 6009, Australia
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Eero Kajantie
- Finnish Institute for Health and Welfare, Population Health Unit, Helsinki and Oulu, Oulu, Finland
- Clinical Medicine Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jørgen K Kanters
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center of Physiological Research, University of California San Francisco, San Francisco, USA
| | - Line L Kårhus
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Lambertus A L M Kiemeney
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Margreet Kloppenburg
- Departments of Rheumatology and Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Brigitte Kühnel
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Bruno Lapauw
- Department of Endocrinology, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium
| | | | - Shuo Li
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - David C M Liewald
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Allan Linneberg
- Center of Physiological Research, University of California San Francisco, San Francisco, USA
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jesus V T Lominchar
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | | | - Antonela Matana
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
| | - Marcel E Meima
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Thomas Meitinger
- Institute for Human Genetics, Technical University of Munich, Munich, Germany
| | - Ingrid Meulenbelt
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Braxton D Mitchell
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition, Baltimore, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, 21201, USA
| | - Line T Møllehave
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Samia Mora
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Silvia Naitza
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Romana T Netea-Maier
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Casia Nursyifa
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Japan
| | - Stefano Onano
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - Areti Papadopoulou
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Colin N A Palmer
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - Cristian Pattaro
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Metabolic Research, Herlev-Gentofte University Hospital, Copenhagen, Denmark
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Maik Pietzner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Ozren Polašek
- Department of Public Health, University of Split, School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Peter P Pramstaller
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ante Punda
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Debashree Ray
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - J Brent Richards
- Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, H3T 1E2, Canada
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Tom C Russ
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathleen A Ryan
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition, Baltimore, USA
| | - Morten Salling Olesen
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Moneeza K Siddiqui
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Carlo Sidore
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - P Eline Slagboom
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Enrique Soto-Pedre
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - Tim D Spector
- The Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Campus, Lambeth Palace Road, London, SE1 7EH, UK
| | - Beatrice Spedicati
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Sundararajan Srinivasan
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - John M Starr
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Toshiko Tanaka
- Longitudinal Study Section, National Institute on Aging, Baltimore, MD, USA
| | - Vesela Torlak
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Johanna Tuhkanen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Erik B van den Akker
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, The Netherlands
- Department of Pattern Recognition and Bioinformatics, Delft University of Technology, Delft, The Netherlands
| | - Tibbert van den Eynde
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Melanie M van der Klauw
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Charlotte Verroken
- Department of Endocrinology, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium
| | - W Edward Visser
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Dina Vojinovic
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - John P Walsh
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
- Medical School, The University of Western Australia, Crawley, WA, 6009, Australia
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Stefan Weiss
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Cristen J Willer
- Department of Internal Medicine, Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Scott G Wilson
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, 6009, Australia
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
- The Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Campus, Lambeth Palace Road, London, SE1 7EH, UK
| | - Bruce H R Wolffenbuttel
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hanneke J C M Wouters
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Qiong Yang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Tatijana Zemunik
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Johannes W A Smit
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Robin P Peeters
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
- CIBSS - Centre for Integrative Biological Signalling Studies, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany.
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland.
| | - Marco Medici
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands.
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
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Hansen MS, Madsen K, Price M, Søe K, Omata Y, Zaiss MM, Gorvin CM, Frost M, Rauch A. Transcriptional reprogramming during human osteoclast differentiation identifies regulators of osteoclast activity. Bone Res 2024; 12:5. [PMID: 38263167 PMCID: PMC10806178 DOI: 10.1038/s41413-023-00312-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 11/08/2023] [Accepted: 12/15/2023] [Indexed: 01/25/2024] Open
Abstract
Enhanced osteoclastogenesis and osteoclast activity contribute to the development of osteoporosis, which is characterized by increased bone resorption and inadequate bone formation. As novel antiosteoporotic therapeutics are needed, understanding the genetic regulation of human osteoclastogenesis could help identify potential treatment targets. This study aimed to provide an overview of transcriptional reprogramming during human osteoclast differentiation. Osteoclasts were differentiated from CD14+ monocytes from eight female donors. RNA sequencing during differentiation revealed 8 980 differentially expressed genes grouped into eight temporal patterns conserved across donors. These patterns revealed distinct molecular functions associated with postmenopausal osteoporosis susceptibility genes based on RNA from iliac crest biopsies and bone mineral density SNPs. Network analyses revealed mutual dependencies between temporal expression patterns and provided insight into subtype-specific transcriptional networks. The donor-specific expression patterns revealed genes at the monocyte stage, such as filamin B (FLNB) and oxidized low-density lipoprotein receptor 1 (OLR1, encoding LOX-1), that are predictive of the resorptive activity of mature osteoclasts. The expression of differentially expressed G-protein coupled receptors was strong during osteoclast differentiation, and these receptors are associated with bone mineral density SNPs, suggesting that they play a pivotal role in osteoclast differentiation and activity. The regulatory effects of three differentially expressed G-protein coupled receptors were exemplified by in vitro pharmacological modulation of complement 5 A receptor 1 (C5AR1), somatostatin receptor 2 (SSTR2), and free fatty acid receptor 4 (FFAR4/GPR120). Activating C5AR1 enhanced osteoclast formation, while activating SSTR2 decreased the resorptive activity of mature osteoclasts, and activating FFAR4 decreased both the number and resorptive activity of mature osteoclasts. In conclusion, we report the occurrence of transcriptional reprogramming during human osteoclast differentiation and identified SSTR2 and FFAR4 as antiresorptive G-protein coupled receptors and FLNB and LOX-1 as potential molecular markers of osteoclast activity. These data can help future investigations identify molecular regulators of osteoclast differentiation and activity and provide the basis for novel antiosteoporotic targets.
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Affiliation(s)
- Morten S Hansen
- Molecular Endocrinology Laboratory (KMEB), Department of Endocrinology, Odense University Hospital, DK-5000, Odense C, Denmark
- Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, DK-5000, Odense C, Denmark
- Clinical Cell Biology, Pathology Research Unit, Department of Clinical Research, University of Southern Denmark, DK-5000, Odense C, Denmark
| | - Kaja Madsen
- Molecular Endocrinology Laboratory (KMEB), Department of Endocrinology, Odense University Hospital, DK-5000, Odense C, Denmark
- Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, DK-5000, Odense C, Denmark
| | - Maria Price
- Institute of Metabolism and Systems Research (IMSR) and Centre for Diabetes, Endocrinology and Metabolism (CEDAM), University of Birmingham, Birmingham, B15 2TT, UK
- Centre for Membrane Proteins and Receptors (COMPARE), Universities of Birmingham and Nottingham, Birmingham, B15 2TT, UK
| | - Kent Søe
- Clinical Cell Biology, Pathology Research Unit, Department of Clinical Research, University of Southern Denmark, DK-5000, Odense C, Denmark
- Department of Molecular Medicine, University of Southern Denmark, DK-5000, Odense C, Denmark
| | - Yasunori Omata
- Department of Orthopedic Surgery, Faculty of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan
- Department of Internal Medicine 3, Rheumatology and Immunology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, D-91054, Erlangen, Germany
| | - Mario M Zaiss
- Department of Internal Medicine 3, Rheumatology and Immunology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, D-91054, Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, D-91054, Erlangen, Germany
| | - Caroline M Gorvin
- Institute of Metabolism and Systems Research (IMSR) and Centre for Diabetes, Endocrinology and Metabolism (CEDAM), University of Birmingham, Birmingham, B15 2TT, UK
- Centre for Membrane Proteins and Receptors (COMPARE), Universities of Birmingham and Nottingham, Birmingham, B15 2TT, UK
| | - Morten Frost
- Molecular Endocrinology Laboratory (KMEB), Department of Endocrinology, Odense University Hospital, DK-5000, Odense C, Denmark.
- Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, DK-5000, Odense C, Denmark.
- Steno Diabetes Center Odense, Odense University Hospital, DK-5000, Odense C, Denmark.
| | - Alexander Rauch
- Molecular Endocrinology Laboratory (KMEB), Department of Endocrinology, Odense University Hospital, DK-5000, Odense C, Denmark.
- Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, DK-5000, Odense C, Denmark.
- Steno Diabetes Center Odense, Odense University Hospital, DK-5000, Odense C, Denmark.
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Yang G(K, Chen H, Cheng KL, Tang MF, Wang Y, Hung LH(A, Cheng CY(J, Mak KL(K, Lee YW(W. Potential Interaction between WNT16 and Vitamin D on Bone Qualities in Adolescent Idiopathic Scoliosis Patients and Healthy Controls. Biomedicines 2024; 12:250. [PMID: 38275421 PMCID: PMC10813331 DOI: 10.3390/biomedicines12010250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 01/01/2024] [Accepted: 01/16/2024] [Indexed: 01/27/2024] Open
Abstract
Adolescent idiopathic scoliosis (AIS) is a three-dimensional spinal deformity that is associated with low bone mineral density (BMD). Vitamin D (Vit-D) supplementation has been suggested to improve BMD in AIS, and its outcomes may be related to genetic factors. The present study aimed to (a) investigate the synergistic effect between a low BMD-related gene (wingless-related integration site 16, WNT16) and two important Vit-D pathway genes (Vit-D receptor, VDR, and Vit-D binding protein, VDBP) on serum Vit-D and bone qualities in Chinese AIS patients and healthy adolescents, and (b) to further investigate the effect of ablating Wnt16 on the cortical bone quality and whether diets with different dosages of Vit-D would further influence bone quality during the rapid growth phase in mice in the absence of Wnt16. A total of 519 girls (318 AIS vs. 201 controls) were recruited, and three selected single-nucleotide polymorphisms (SNPs) (WNT16 rs3801387, VDBP rs2282679, and VDR rs2228570) were genotyped. The serum 25(OH)Vit-D level was significantly associated with VDBP rs2282679 alleles (OR = -4.844; 95% CI, -7.521 to -2.167, p < 0.001). Significant multi-locus models were identified by generalized multifactor dimensionality reduction (GMDR) analyses on the serum 25(OH)Vit-D level (p = 0.006) and trabecular area (p = 0.044). In the gene-edited animal study, Wnt16 global knockout (KO) and wildtype (WT) male mice were provided with different Vit-D diets (control chow (1000 IU/Kg) vs. Vit-D-deficient chow (Nil in Vit-D) vs. high-dose Vit-D chow (20,000 IU/Kg)) from 4 weeks to 10 weeks old. Wnt16 global KO mice had significantly lower serum 25(OH)Vit-D levels and higher liver Vdbp mRNA expression levels than WT mice. In addition, Wnt16 global KO mice showed a decrease in bone density, cortical thickness and cortical area compared with WT mice. Interestingly, high-dose Vit-D chow led to lower bone density, cortical thickness, and cortical area in WT mice, which were less obvious in Wnt16 global KO mice. In conclusion, WNT16 may regulate the serum 25(OH)Vit-D level and bone qualities, which might be associated with VDBP expression. Further investigations with a larger sample size and wider spectrum of scoliosis severity are required to validate our findings regarding the interaction between WNT16 and Vit-D status in patients with AIS.
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Affiliation(s)
- Guangpu (Kenneth) Yang
- SH Ho Scoliosis Research Laboratory, Joint Scoliosis Research Centre of the Chinese University of Hong Kong and Nanjing University, The Chinese University of Hong Kong, Hong Kong, China
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China
| | - Huanxiong Chen
- SH Ho Scoliosis Research Laboratory, Joint Scoliosis Research Centre of the Chinese University of Hong Kong and Nanjing University, The Chinese University of Hong Kong, Hong Kong, China
- Department of Spine Surgery, The First Affiliated Hospital of Hainan Medical University, Haikou 571199, China
| | - Ka-Lo Cheng
- SH Ho Scoliosis Research Laboratory, Joint Scoliosis Research Centre of the Chinese University of Hong Kong and Nanjing University, The Chinese University of Hong Kong, Hong Kong, China
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China
| | - Man-Fung Tang
- Department of Paediatrics, The Chinese University of Hong Kong, Hong Kong, China
| | - Yujia Wang
- SH Ho Scoliosis Research Laboratory, Joint Scoliosis Research Centre of the Chinese University of Hong Kong and Nanjing University, The Chinese University of Hong Kong, Hong Kong, China
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China
| | - Lik-Hang (Alec) Hung
- SH Ho Scoliosis Research Laboratory, Joint Scoliosis Research Centre of the Chinese University of Hong Kong and Nanjing University, The Chinese University of Hong Kong, Hong Kong, China
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China
- Department of Orthopaedics and Traumatology, Prince of Wales Hospital, Hong Kong, China
| | - Chun-Yiu (Jack) Cheng
- SH Ho Scoliosis Research Laboratory, Joint Scoliosis Research Centre of the Chinese University of Hong Kong and Nanjing University, The Chinese University of Hong Kong, Hong Kong, China
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China
| | | | - Yuk-Wai (Wayne) Lee
- SH Ho Scoliosis Research Laboratory, Joint Scoliosis Research Centre of the Chinese University of Hong Kong and Nanjing University, The Chinese University of Hong Kong, Hong Kong, China
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
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134
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Mbarek H, Gordon SD, Duffy DL, Hubers N, Mortlock S, Beck JJ, Hottenga JJ, Pool R, Dolan CV, Actkins KV, Gerring ZF, Van Dongen J, Ehli EA, Iacono WG, Mcgue M, Chasman DI, Gallagher CS, Schilit SLP, Morton CC, Paré G, Willemsen G, Whiteman DC, Olsen CM, Derom C, Vlietinck R, Gudbjartsson D, Cannon-Albright L, Krapohl E, Plomin R, Magnusson PKE, Pedersen NL, Hysi P, Mangino M, Spector TD, Palviainen T, Milaneschi Y, Penninnx BW, Campos AI, Ong KK, Perry JRB, Lambalk CB, Kaprio J, Ólafsson Í, Duroure K, Revenu C, Rentería ME, Yengo L, Davis L, Derks EM, Medland SE, Stefansson H, Stefansson K, Del Bene F, Reversade B, Montgomery GW, Boomsma DI, Martin NG. Genome-wide association study meta-analysis of dizygotic twinning illuminates genetic regulation of female fecundity. Hum Reprod 2024; 39:240-257. [PMID: 38052102 PMCID: PMC10767824 DOI: 10.1093/humrep/dead247] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 09/14/2023] [Indexed: 12/07/2023] Open
Abstract
STUDY QUESTION Which genetic factors regulate female propensity for giving birth to spontaneous dizygotic (DZ) twins? SUMMARY ANSWER We identified four new loci, GNRH1, FSHR, ZFPM1, and IPO8, in addition to previously identified loci, FSHB and SMAD3. WHAT IS KNOWN ALREADY The propensity to give birth to DZ twins runs in families. Earlier, we reported that FSHB and SMAD3 as associated with DZ twinning and female fertility measures. STUDY DESIGN, SIZE, DURATION We conducted a genome-wide association meta-analysis (GWAMA) of mothers of spontaneous dizygotic (DZ) twins (8265 cases, 264 567 controls) and of independent DZ twin offspring (26 252 cases, 417 433 controls). PARTICIPANTS/MATERIALS, SETTING, METHODS Over 700 000 mothers of DZ twins, twin individuals and singletons from large cohorts in Australia/New Zealand, Europe, and the USA were carefully screened to exclude twins born after use of ARTs. Genetic association analyses by cohort were followed by meta-analysis, phenome wide association studies (PheWAS), in silico and in vivo annotations, and Zebrafish functional validation. MAIN RESULTS AND THE ROLE OF CHANCE This study enlarges the sample size considerably from previous efforts, finding four genome-wide significant loci, including two novel signals and a further two novel genes that are implicated by gene level enrichment analyses. The novel loci, GNRH1 and FSHR, have well-established roles in female reproduction whereas ZFPM1 and IPO8 have not previously been implicated in female fertility. We found significant genetic correlations with multiple aspects of female reproduction and body size as well as evidence for significant selection against DZ twinning during human evolution. The 26 top single nucleotide polymorphisms (SNPs) from our GWAMA in European-origin participants weakly predicted the crude twinning rates in 47 non-European populations (r = 0.23 between risk score and population prevalence, s.e. 0.11, 1-tail P = 0.058) indicating that genome-wide association studies (GWAS) are needed in African and Asian populations to explore the causes of their respectively high and low DZ twinning rates. In vivo functional tests in zebrafish for IPO8 validated its essential role in female, but not male, fertility. In most regions, risk SNPs linked to known expression quantitative trait loci (eQTLs). Top SNPs were associated with in vivo reproductive hormone levels with the top pathways including hormone ligand binding receptors and the ovulation cycle. LARGE SCALE DATA The full DZT GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/). LIMITATIONS, REASONS FOR CAUTION Our study only included European ancestry cohorts. Inclusion of data from Africa (with the highest twining rate) and Asia (with the lowest rate) would illuminate further the biology of twinning and female fertility. WIDER IMPLICATIONS OF THE FINDINGS About one in 40 babies born in the world is a twin and there is much speculation on why twinning runs in families. We hope our results will inform investigations of ovarian response in new and existing ARTs and the causes of female infertility. STUDY FUNDING/COMPETING INTEREST(S) Support for the Netherlands Twin Register came from the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organization for Health Research and Development (ZonMW) grants, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, 911-09-032, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI.NL, 184.021.007), Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB, European Research Council (ERC-230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1) and the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health and Grand Opportunity grants 1RC2 MH089951. The QIMR Berghofer Medical Research Institute (QIMR) study was supported by grants from the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485, 552498, 1050208, 1075175). L.Y. is funded by Australian Research Council (Grant number DE200100425). The Minnesota Center for Twin and Family Research (MCTFR) was supported in part by USPHS Grants from the National Institute on Alcohol Abuse and Alcoholism (AA09367 and AA11886) and the National Institute on Drug Abuse (DA05147, DA13240, and DA024417). The Women's Genome Health Study (WGHS) was funded by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with support for genotyping provided by Amgen. Data collection in the Finnish Twin Registry has been supported by the Wellcome Trust Sanger Institute, the Broad Institute, ENGAGE-European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement number 201413, National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, AA-09203, AA15416, and K02AA018755) and the Academy of Finland (grants 100499, 205585, 118555, 141054, 264146, 308248, 312073 and 336823 to J. Kaprio). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. For NESDA, funding was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10000-1002), the Center for Medical Systems Biology (CSMB, NVVO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University's Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, ROI D0042157-01A, MH081802, Grand Opportunity grants 1 RC2 Ml-1089951 and IRC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. Work in the Del Bene lab was supported by the Programme Investissements d'Avenir IHU FOReSIGHT (ANR-18-IAHU-01). C.R. was supported by an EU Horizon 2020 Marie Skłodowska-Curie Action fellowship (H2020-MSCA-IF-2014 #661527). H.S. and K.S. are employees of deCODE Genetics/Amgen. The other authors declare no competing financial interests. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Hamdi Mbarek
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Qatar Genome Program, Qatar Foundation, Doha, Qatar
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - David L Duffy
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nikki Hubers
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Sally Mortlock
- Institute of Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Jeffrey J Beck
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD, USA
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | - René Pool
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | - Ky’Era V Actkins
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | | | - Jenny Van Dongen
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Erik A Ehli
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt Mcgue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Daniel I Chasman
- Harvard Medical School, Harvard University, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | | | - Samantha L P Schilit
- Harvard Medical School, Harvard University, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Cynthia C Morton
- Harvard Medical School, Harvard University, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Guillaume Paré
- Population Health Research Institute, McMaster University, Hamilton, ON, Canada
| | - Gonneke Willemsen
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | | | | | | | | | | | | | - Eva Krapohl
- Medical Research Council Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Statistical Sciences & Innovation, UCB Biosciences GmbH, Monheim, Germany
| | - Robert Plomin
- Medical Research Council Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Pirro Hysi
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK
| | - Massimo Mangino
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London, UK
| | - Timothy D Spector
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Yuri Milaneschi
- Department of Psychiatry, EMGO Institute for Health and Care Research, Vrije Universiteit, Amsterdam, The Netherlands
| | - Brenda W Penninnx
- Department of Psychiatry, EMGO Institute for Health and Care Research, Vrije Universiteit, Amsterdam, The Netherlands
| | - Adrian I Campos
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Institute of Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Ken K Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Cornelis B Lambalk
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
- Amsterdam University Medical Centers Location VU Medical Center, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Ísleifur Ólafsson
- Department of Clinical Biochemistry, National University Hospital of Iceland, Reykjavik, Iceland
| | - Karine Duroure
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Céline Revenu
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | | | - Loic Yengo
- Institute of Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Lea Davis
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Eske M Derks
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | | | - Filippo Del Bene
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Bruno Reversade
- Genome Institute of Singapore, Laboratory of Human Genetics & Therapeutics, A*STAR, Singapore, Singapore
- Smart-Health Initiative, BESE, KAUST, Thuwal, Saudi Arabia
| | - Grant W Montgomery
- Institute of Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
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Brazill JM, Shen IR, Craft CS, Magee KL, Park JS, Lorenz M, Strickland A, Wee NK, Zhang X, Beeve AT, Meyer GA, Milbrandt J, DiAntonio A, Scheller EL. Sarm1 knockout prevents type 1 diabetic bone disease in females independent of neuropathy. JCI Insight 2024; 9:e175159. [PMID: 38175722 PMCID: PMC11143934 DOI: 10.1172/jci.insight.175159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 01/03/2024] [Indexed: 01/05/2024] Open
Abstract
Patients with diabetes have a high risk of developing skeletal diseases accompanied by diabetic peripheral neuropathy (DPN). In this study, we isolated the role of DPN in skeletal disease with global and conditional knockout models of sterile-α and TIR-motif-containing protein-1 (Sarm1). SARM1, an NADase highly expressed in the nervous system, regulates axon degeneration upon a range of insults, including DPN. Global knockout of Sarm1 prevented DPN, but not skeletal disease, in male mice with type 1 diabetes (T1D). Female wild-type mice also developed diabetic bone disease but without DPN. Unexpectedly, global Sarm1 knockout completely protected female mice from T1D-associated bone suppression and skeletal fragility despite comparable muscle atrophy and hyperglycemia. Global Sarm1 knockout rescued bone health through sustained osteoblast function with abrogation of local oxidative stress responses. This was independent of the neural actions of SARM1, as beneficial effects on bone were lost with neural conditional Sarm1 knockout. This study demonstrates that the onset of skeletal disease occurs rapidly in both male and female mice with T1D completely independently of DPN. In addition, this reveals that clinical SARM1 inhibitors, currently being developed for treatment of neuropathy, may also have benefits for diabetic bone through actions outside of the nervous system.
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Affiliation(s)
| | - Ivana R. Shen
- Division of Bone and Mineral Diseases, Department of Medicine, and
| | | | | | - Jay S. Park
- Division of Bone and Mineral Diseases, Department of Medicine, and
| | - Madelyn Lorenz
- Division of Bone and Mineral Diseases, Department of Medicine, and
| | - Amy Strickland
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Natalie K. Wee
- Division of Bone and Mineral Diseases, Department of Medicine, and
| | - Xiao Zhang
- Division of Bone and Mineral Diseases, Department of Medicine, and
- Department of Biomedical Engineering, McKelvey School of Engineering, Washington University, St. Louis, Missouri, USA
| | - Alec T. Beeve
- Division of Bone and Mineral Diseases, Department of Medicine, and
- Department of Biomedical Engineering, McKelvey School of Engineering, Washington University, St. Louis, Missouri, USA
| | | | - Jeffrey Milbrandt
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
| | | | - Erica L. Scheller
- Division of Bone and Mineral Diseases, Department of Medicine, and
- Department of Biomedical Engineering, McKelvey School of Engineering, Washington University, St. Louis, Missouri, USA
- Department of Developmental Biology, and
- Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, Missouri, USA
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136
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Riesmeijer SA, Kamali Z, Ng M, Drichel D, Piersma B, Becker K, Layton TB, Nanchahal J, Nothnagel M, Vaez A, Hennies HC, Werker PMN, Furniss D, Nolte IM. A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren's disease. Nat Commun 2024; 15:199. [PMID: 38172110 PMCID: PMC10764787 DOI: 10.1038/s41467-023-44451-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 12/13/2023] [Indexed: 01/05/2024] Open
Abstract
Dupuytren's disease (DD) is a highly heritable fibrotic disorder of the hand with incompletely understood etiology. A number of genetic loci, including Wnt signaling members, have been previously identified. Our overall aim was to identify novel genetic loci, to prioritize genes within the loci for functional studies, and to assess genetic correlation with associated disorders. We performed a meta-analysis of six DD genome-wide association studies from three European countries and extensive bioinformatic follow-up analyses. Leveraging 11,320 cases and 47,023 controls, we identified 85 genome-wide significant single nucleotide polymorphisms in 56 loci, of which 11 were novel, explaining 13.3-38.1% of disease variance. Gene prioritization implicated the Hedgehog and Notch signaling pathways. We also identified a significant genetic correlation with frozen shoulder. The pathways identified highlight the potential for new therapeutic targets and provide a basis for additional mechanistic studies for a common disorder that can severely impact hand function.
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Affiliation(s)
- Sophie A Riesmeijer
- University of Groningen, University Medical Center Groningen, Department of Plastic Surgery, Groningen, The Netherlands.
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands.
| | - Zoha Kamali
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
- Department of bioinformatics, School of Advanced Medical Technologies, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Michael Ng
- Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Science, Botnar Research Centre, University of Oxford, Oxford, UK
| | - Dmitriy Drichel
- Cologne Center for Genomics, University of Cologne, Cologne, Germany
- Faculty of Medicine and the Cologne University Hospital, Cologne, Germany
| | - Bram Piersma
- University of Groningen, Groningen, The Netherlands
| | - Kerstin Becker
- Cologne Center for Genomics, University of Cologne, Cologne, Germany
| | | | | | - Michael Nothnagel
- Cologne Center for Genomics, University of Cologne, Cologne, Germany
- Faculty of Medicine and the Cologne University Hospital, Cologne, Germany
| | - Ahmad Vaez
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
- Department of bioinformatics, School of Advanced Medical Technologies, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Hans Christian Hennies
- Faculty of Medicine and the Cologne University Hospital, Cologne, Germany
- Department of Biological Sciences, University of Huddersfield, Huddersfield, UK
| | - Paul M N Werker
- University of Groningen, University Medical Center Groningen, Department of Plastic Surgery, Groningen, The Netherlands
| | - Dominic Furniss
- Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Science, Botnar Research Centre, University of Oxford, Oxford, UK
| | - Ilja M Nolte
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
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137
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Irving-Pease EK, Refoyo-Martínez A, Barrie W, Ingason A, Pearson A, Fischer A, Sjögren KG, Halgren AS, Macleod R, Demeter F, Henriksen RA, Vimala T, McColl H, Vaughn AH, Speidel L, Stern AJ, Scorrano G, Ramsøe A, Schork AJ, Rosengren A, Zhao L, Kristiansen K, Iversen AKN, Fugger L, Sudmant PH, Lawson DJ, Durbin R, Korneliussen T, Werge T, Allentoft ME, Sikora M, Nielsen R, Racimo F, Willerslev E. The selection landscape and genetic legacy of ancient Eurasians. Nature 2024; 625:312-320. [PMID: 38200293 PMCID: PMC10781624 DOI: 10.1038/s41586-023-06705-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 10/03/2023] [Indexed: 01/12/2024]
Abstract
The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.
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Affiliation(s)
- Evan K Irving-Pease
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
| | - Alba Refoyo-Martínez
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - William Barrie
- GeoGenetics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Andrés Ingason
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Roskilde, Denmark
| | - Alice Pearson
- Department of Genetics, University of Cambridge, Cambridge, UK
- Department of Zoology, University of Cambridge, Cambridge, UK
| | - Anders Fischer
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
- Sealand Archaeology, Kalundborg, Denmark
| | - Karl-Göran Sjögren
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
| | - Alma S Halgren
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
| | - Ruairidh Macleod
- GeoGenetics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- UCL Genetics Institute, University College London, London, UK
| | - Fabrice Demeter
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Eco-anthropologie, Muséum national d'Histoire naturelle, CNRS, Université Paris Cité, Musée de l'Homme, Paris, France
| | - Rasmus A Henriksen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Tharsika Vimala
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Hugh McColl
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Andrew H Vaughn
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Leo Speidel
- UCL Genetics Institute, University College London, London, UK
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK
| | - Aaron J Stern
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Gabriele Scorrano
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Abigail Ramsøe
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Roskilde, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
| | - Anders Rosengren
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Roskilde, Denmark
| | - Lei Zhao
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Kristian Kristiansen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
| | - Astrid K N Iversen
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Lars Fugger
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
- MRC Human Immunology Unit, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Peter H Sudmant
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Daniel J Lawson
- Institute of Statistical Sciences, School of Mathematics, University of Bristol, Bristol, UK
| | - Richard Durbin
- Department of Genetics, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Cambridge, UK
| | - Thorfinn Korneliussen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Werge
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
| | - Morten E Allentoft
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Trace and Environmental DNA (TrEnD) Laboratory, School of Molecular and Life Science, Curtin University, Perth, Western Australia, Australia
| | - Martin Sikora
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Rasmus Nielsen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
- Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA, USA.
| | - Fernando Racimo
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
| | - Eske Willerslev
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
- GeoGenetics Group, Department of Zoology, University of Cambridge, Cambridge, UK.
- MARUM Center for Marine Environmental Sciences and Faculty of Geosciences, University of Bremen, Bremen, Germany.
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138
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Friedman MA, Buettmann EG, Zeineddine Y, Abraham LB, Hoppock GA, Meas SJ, Zhang Y, Farber CR, Donahue HJ. Genetic variation influences the skeletal response to hindlimb unloading in the eight founder strains of the diversity outbred mouse population. J Orthop Res 2024; 42:134-140. [PMID: 37321985 PMCID: PMC10721729 DOI: 10.1002/jor.25646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 06/11/2023] [Accepted: 06/11/2023] [Indexed: 06/17/2023]
Abstract
During disuse, mechanical unloading causes extensive bone loss, decreasing bone volume and strength. Variations in bone mass and risk of osteoporosis are influenced by genetics; however, it remains unclear how genetic variation affects the skeletal response to unloading. We previously found that genetic variation affects the musculoskeletal response to 3 weeks of immobilization in the 8 Jackson Laboratory J:DO founder strains: C57Bl/6J, A/J, 129S1/SvImJ, NOD/ShiLtJ, NZO/HlLtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ. Hindlimb unloading (HLU) is the best model for simulating local and systemic contributors of disuse and therefore may have a greater impact on bones than immobilization. We hypothesized that genetic variation would affect the response to HLU across the eight founder strains. Mice of each founder strain were placed in HLU for 3 weeks, and the femurs and tibias were analyzed. There were significant HLU and mouse strain interactions on body weight, femur trabecular BV/TV, and femur ultimate force. This indicates that unloading only caused significant catabolic effects in some mouse strains. C57BL/6 J mice were most affected by unloading while other strains were more protected. There were significant HLU and mouse strain interactions on gene expression of genes encoding bone metabolism genes in the tibia. This indicates that unloading only caused significant effects on bone metabolism genes in some mouse strains. Different mouse strains respond to HLU differently, and this can be explained by genetic differences. These results suggest the outbred J:DO mice will be a powerful model for examining the effects of genetics on the skeletal response to HLU.
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Affiliation(s)
| | | | | | | | | | | | - Yue Zhang
- Virginia Commonwealth University, Richmond VA
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139
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Wang J, Yang M, Tian Y, Feng R, Xu K, Teng M, Wang J, Wang Q, Xu P. Causal associations between common musculoskeletal disorders and dementia: a Mendelian randomization study. Front Aging Neurosci 2023; 15:1253791. [PMID: 38125810 PMCID: PMC10731015 DOI: 10.3389/fnagi.2023.1253791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 11/23/2023] [Indexed: 12/23/2023] Open
Abstract
Introduction Dementia and musculoskeletal disorders (MSDs) are major public health problems. We aimed to investigate the genetic causality of common MSDs and dementia. Methods Two-sample Mendelian randomization (MR) was used in this study. MR analysis based on gene-wide association study (GWAS) data on osteoarthritis (OA), dementia with Lewy bodies, and other MSDs and dementia types were obtained from the Genetics of Osteoarthritis consortium, IEU-open GWAS project, GWAS catalog, and FinnGen consortium. Rigorously selected single-nucleotide polymorphisms were regarded as instrumental variables for further MR analysis. Inverse-variance weighted, MR-Egger regression, weight median, simple mode, and weight mode methods were used to obtain the MR estimates. Cochran's Q test, MR-Egger and MR-Pleiotropy Residual Sum and Outlier analysis, and the leave-one-out test were applied for sensitivity testing. Results The inverse-variance weighted method showed that hip OA was genetically associated with a lower risk of dementia, unspecified dementia, dementia in Alzheimer's disease, and vascular dementia. Kneehip OA was inversely associated with unspecified dementia and vascular dementia. Rheumatoid arthritis, juvenile idiopathic arthritis and seronegative rheumatoid arthritis were inversely associated with frontotemporal dementia, and rheumatoid arthritis was inversely associated with unspecified dementia. Simultaneously, ankylosing spondylitis was an independent risk factor for dementia, dementia with Lewy bodies, and dementia in Alzheimer's disease. Sensitivity tests showed that heterogeneity and horizontal pleiotropy did not exist in these associations. The leave-one-out test showed that these associations were stable. Conclusion We found that some MSDs were associated with the risk of dementia and provide evidence for the early detection of dementia in patients with MSDs and for the impact of inflammation on the central nervous system.
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Affiliation(s)
- Jiachen Wang
- Department of Joint Surgery, HongHui Hospital, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Mingyi Yang
- Department of Joint Surgery, HongHui Hospital, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Ye Tian
- Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ruoyang Feng
- Department of Joint Surgery, HongHui Hospital, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Ke Xu
- Department of Joint Surgery, HongHui Hospital, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Menghao Teng
- Department of Orthopedics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Junxiang Wang
- Department of Joint Surgery, HongHui Hospital, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Qi Wang
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Peng Xu
- Department of Joint Surgery, HongHui Hospital, Xi’an Jiaotong University, Xi’an, Shaanxi, China
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140
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Lovegrove CE, Bešević J, Wiberg A, Lacey B, Littlejohns TJ, Allen NE, Goldsworthy M, Kim J, Hannan FM, Curhan GC, Turney BW, McCarthy MI, Mahajan A, Thakker RV, Holmes MV, Furniss D, Howles SA. Central Adiposity Increases Risk of Kidney Stone Disease through Effects on Serum Calcium Concentrations. J Am Soc Nephrol 2023; 34:1991-2011. [PMID: 37787550 PMCID: PMC10703081 DOI: 10.1681/asn.0000000000000238] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 08/25/2023] [Accepted: 09/14/2023] [Indexed: 10/04/2023] Open
Abstract
SIGNIFICANCE STATEMENT Kidney stone disease is a common disorder with poorly understood pathophysiology. Observational and genetic studies indicate that adiposity is associated with an increased risk of kidney stone disease. However, the relative contribution of general and central adipose depots and the mechanisms by which effects of adiposity on kidney stone disease are mediated have not been defined. Using conventional and genetic epidemiological techniques, we demonstrate that general and central adiposity are independently associated with kidney stone disease. In addition, one mechanism by which central adiposity increases risk of kidney stone disease is by increasing serum calcium concentration. Therapies targeting adipose depots may affect calcium homeostasis and help to prevent kidney stone disease. BACKGROUND Kidney stone disease affects approximately 10% of individuals in their lifetime and is frequently recurrent. The disease is linked to obesity, but the mechanisms mediating this association are uncertain. METHODS Associations of adiposity and incident kidney stone disease were assessed in the UK Biobank over a mean of 11.6 years/person. Genome-wide association studies and Mendelian randomization (MR) analyses were undertaken in the UK Biobank, FinnGen, and in meta-analyzed cohorts to identify factors that affect kidney stone disease risk. RESULTS Observational analyses on UK Biobank data demonstrated that increasing central and general adiposity is independently associated with incident kidney stone formation. Multivariable MR, using meta-analyzed UK Biobank and FinnGen data, established that risk of kidney stone disease increases by approximately 21% per one standard deviation increase in body mass index (BMI, a marker of general adiposity) independent of waist-to-hip ratio (WHR, a marker of central adiposity) and approximately 24% per one standard deviation increase of WHR independent of BMI. Genetic analyses indicate that higher WHR, but not higher BMI, increases risk of kidney stone disease by elevating adjusted serum calcium concentrations (β=0.12 mmol/L); WHR mediates 12%-15% of its effect on kidney stone risk in this way. CONCLUSIONS Our study indicates that visceral adipose depots elevate serum calcium concentrations, resulting in increased risk of kidney stone disease. These findings highlight the importance of weight loss in individuals with recurrent kidney stones and suggest that therapies targeting adipose depots may affect calcium homeostasis and contribute to prevention of kidney stone disease.
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Affiliation(s)
| | - Jelena Bešević
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Akira Wiberg
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
| | - Ben Lacey
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Thomas J. Littlejohns
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Naomi E. Allen
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Michelle Goldsworthy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Jihye Kim
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Fadil M. Hannan
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, United Kingdom
| | - Gary C. Curhan
- Channing Division of Network Medicine and Renal Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Ben W. Turney
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Mark I. McCarthy
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Genentech, South San Francisco, Califirnia
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Genentech, South San Francisco, Califirnia
| | - Rajesh V. Thakker
- Academic Endocrine Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Michael V. Holmes
- Medical Research Council, Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Dominic Furniss
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
| | - Sarah A. Howles
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
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141
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Lu T, Forgetta V, Zhou S, Richards JB, Greenwood CM. Identifying Rare Genetic Determinants for Improved Polygenic Risk Prediction of Bone Mineral Density and Fracture Risk. J Bone Miner Res 2023; 38:1771-1781. [PMID: 37830501 DOI: 10.1002/jbmr.4920] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 09/13/2023] [Accepted: 10/06/2023] [Indexed: 10/14/2023]
Abstract
Osteoporosis and fractures severely impact the elderly population. Polygenic risk scores for bone mineral density have demonstrated potential clinical utility. However, the value of rare genetic determinants in risk prediction has not been assessed. With whole-exome sequencing data from 436,824 UK Biobank participants, we assigned White British ancestry individuals into a training data set (n = 317,434) and a test data set (n = 74,825). In the training data set, we developed a common variant-based polygenic risk score for heel ultrasound speed of sound (SOS). Next, we performed burden testing to identify genes harboring rare determinants of bone mineral density, targeting influential rare variants with predicted high deleteriousness. We constructed a genetic risk score, called ggSOS, to incorporate influential rare variants in significant gene burden masks into the common variant-based polygenic risk score. We assessed the predictive performance of ggSOS in the White British test data set, as well as in populations of non-White British European (n = 18,885), African (n = 7165), East Asian (n = 2236), South Asian (n = 9829), and other admixed (n = 1481) ancestries. Twelve genes in pivotal regulatory pathways of bone homeostasis harbored influential rare variants associated with SOS (p < 5.5 × 10-7 ), including AHNAK, BMP5, CYP19A1, FAM20A, FBXW5, KDM5B, KREMEN1, LGR4, LRP5, SMAD6, SOST, and WNT1. Among 4013 (5.4%) individuals in the test data set carrying these variants, a one standard deviation decrease in ggSOS was associated with 1.35-fold (95% confidence interval [CI] 1.16-1.57) increased hazard of major osteoporotic fracture. However, compared with a common variant-based polygenic risk score (C-index = 0.641), ggSOS had only marginally improved prediction accuracy in identifying at-risk individuals (C-index = 0.644), with overlapping confidence intervals. Similarly, ggSOS did not demonstrate substantially improved predictive performance in non-European ancestry populations. In summary, modeling the effects of rare genetic determinants may assist polygenic prediction of fracture risk among carriers of influential rare variants. Nonetheless, improved clinical utility is not guaranteed for population-level risk screening. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
| | | | - Sirui Zhou
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - J Brent Richards
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
- 5 Prime Sciences Inc., Montreal, QC, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Celia Mt Greenwood
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada
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Ghanbari F, Otomo N, Gamache I, Iwami T, Koike Y, Khanshour AM, Ikegawa S, Wise CA, Terao C, Manousaki D. Interrogating Causal Effects of Body Composition and Puberty-Related Risk Factors on Adolescent Idiopathic Scoliosis: A Two-Sample Mendelian Randomization Study. JBMR Plus 2023; 7:e10830. [PMID: 38130750 PMCID: PMC10731118 DOI: 10.1002/jbm4.10830] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 09/18/2023] [Accepted: 09/20/2023] [Indexed: 12/23/2023] Open
Abstract
Adolescent idiopathic scoliosis (AIS) is the most common form of pediatric musculoskeletal disorder. Observational studies have pointed to several risk factors for AIS, but almost no evidence exists to support their causal association with AIS. Here, we applied Mendelian randomization (MR), known to limit bias from confounding and reverse causation, to investigate causal associations between body composition and puberty-related exposures and AIS risk in Europeans and Asians. For our two-sample MR studies, we used single nucleotide polymorphisms (SNPs) associated with body mass index (BMI), waist-hip ratio, lean mass, childhood obesity, bone mineral density (BMD), 25-hydroxyvitamin D (25OHD), age at menarche, and pubertal growth in large European genome-wide association studies (GWAS), and with adult osteoporosis risk and age of menarche in Biobank Japan. We extracted estimates of the aforementioned SNPs on AIS risk from the European or Asian subsets of the largest multiancestry AIS GWAS (N = 7956 cases/88,459 controls). The results of our inverse variance-weighted (IVW) MR estimates suggest no causal association between the aforementioned risk factors and risk of AIS. Pleiotropy-sensitive MR methods yielded similar results. However, restricting our analysis to European females with AIS, we observed a causal association between estimated BMD and the risk of AIS (IVW odds ratio for AIS = 0.1, 95% confidence interval 0.01 to 0.7, p = 0.02 per SD increase in estimated BMD), but this association was no longer significant after adjusting for BMI, body fat mass, and 25OHD and remained significant after adjusting for age at menarche in multivariable MR. In conclusion, we demonstrated a protective causal effect of BMD on AIS risk in females of European ancestry, but this effect was modified by BMI, body fat mass, and 25OHD levels. Future MR studies using larger AIS GWAS are needed to investigate small effects of the aforementioned exposures on AIS. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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Affiliation(s)
- Faegheh Ghanbari
- Research Center of the Sainte‐Justine University HospitalUniversity of MontrealMontrealQuebecCanada
| | - Nao Otomo
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
- Department of Orthopedic SurgeryKeio University School of MedicineTokyoJapan
| | - Isabel Gamache
- Research Center of the Sainte‐Justine University HospitalUniversity of MontrealMontrealQuebecCanada
| | - Takuro Iwami
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
- Department of Orthopedic SurgeryKeio University School of MedicineTokyoJapan
| | - Yoshinao Koike
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
- Department of Orthopedic SurgeryHokkaido University Graduate School of MedicineSapporoJapan
| | - Anas M. Khanshour
- Scottish Rite for Children Center for Pediatric Bone Biology and Translational ResearchDallasTexasUSA
| | - Shiro Ikegawa
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
| | - Carol A. Wise
- Scottish Rite for Children Center for Pediatric Bone Biology and Translational ResearchDallasTexasUSA
- McDermott Center for Human Growth & DevelopmentUniversity of Texas Southwestern Medical CenterDallasTexasUSA
| | - Chikashi Terao
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
| | - Despoina Manousaki
- Research Center of the Sainte‐Justine University HospitalUniversity of MontrealMontrealQuebecCanada
- Department of PediatricsUniversity of MontrealMontrealCanada
- Department of Biochemistry and Molecular MedicineUniversity of MontrealMontrealQuebecCanada
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Zhang X, Krishnamoorthy S, Tang CTL, Hsu WWQ, Li GHY, Sing CW, Tan KCB, Cheung BMY, Wong ICK, Kung AWC, Cheung CL. Association of Bone Mineral Density and Bone Turnover Markers with the Risk of Diabetes: Hong Kong Osteoporosis Study and Mendelian Randomization. J Bone Miner Res 2023; 38:1782-1790. [PMID: 37850799 DOI: 10.1002/jbmr.4924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 10/08/2023] [Accepted: 10/13/2023] [Indexed: 10/19/2023]
Abstract
Preclinical studies demonstrated that bone plays a central role in energy metabolism. However, how bone metabolism is related to the risk of diabetes in humans is unknown. We investigated the association of bone health (bone mineral density [BMD] and bone turnover markers) with incident type-2 diabetes mellitus (T2DM) based on the Hong Kong Osteoporosis Study (HKOS). A total of 993 and 7160 participants from the HKOS were studied for the cross-sectional and prospective analyses, respectively. The cross-sectional study evaluated the association of BMD and bone biomarkers with fasting glucose and glycated hemoglobin (HbA1c ) levels, whereas the prospective study examined the associations between BMD at study sites and the risk of T2DM by following subjects a median of 16.8 years. Body mass index (BMI) was adjusted in all full models. Mendelian randomization (MR) was conducted for causal inference. In the cross-sectional analysis, lower levels of circulating bone turnover markers and higher BMD were significantly associated with increased fasting glucose and HbA1c levels. In the prospective analysis, higher BMD (0.1 g/cm2 ) at the femoral neck and total hip was associated with increased risk of T2DM with hazard ratios (HRs) of 1.10 (95% confidence interval [CI], 1.03 to 1.18) and 1.14 (95% CI, 1.08 to 1.21), respectively. The presence of osteoporosis was associated with a 30% reduction in risk of T2DM compared to those with normal BMD (HR = 0.70; 95% CI, 0.55 to 0.90). The MR results indicate a robust genetic causal association of estimated BMD (eBMD) with 2-h glucose level after an oral glucose challenge test (estimate = 0.043; 95% CI, 0.007 to 0.079) and T2DM (odds ratio = 1.064; 95% CI, 1.036 to 1.093). Higher BMD and lower levels of circulating bone biomarkers were cross-sectionally associated with poor glycemic control. Moreover, higher BMD was associated with a higher risk of incident T2DM and the association is probably causal. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Xiaowen Zhang
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Suhas Krishnamoorthy
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Casey Tze-Lam Tang
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Warrington Wen-Qiang Hsu
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Gloria Hoi-Yee Li
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Chor-Wing Sing
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Kathryn Choon-Beng Tan
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Bernard Man-Yung Cheung
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Ian Chi-Kei Wong
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Pak Shek Kok, Hong Kong, China
| | - Annie Wai-Chee Kung
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Ching-Lung Cheung
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Pak Shek Kok, Hong Kong, China
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Gagnon E, Paulin A, Mitchell PL, Arsenault BJ. Disentangling the impact of gluteofemoral versus visceral fat accumulation on cardiometabolic health using sex-stratified Mendelian randomization. Atherosclerosis 2023; 386:117371. [PMID: 38029505 DOI: 10.1016/j.atherosclerosis.2023.117371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 10/24/2023] [Accepted: 10/31/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND AND AIMS Individuals with a higher abdominal adipose tissue accumulation are at higher risk of developing cardiometabolic diseases. For a given body mass index (BMI), women typically present lower abdominal adipose tissue accumulation compared to men. Whether abdominal adiposity is a causal driver of cardiometabolic risk, or a mere marker of ectopic fat deposition is debated. METHODS We investigated the sex-specific and sex-combined impact of height and BMI-adjusted gluteofemoral adipose tissue (GFATadj) adjusted abdominal subcutaneous adipose tissue (ASATadj) and adjusted visceral adipose tissue (VATadj) on cardiometabolic traits and diseases using Mendelian randomization. RESULTS Leveraging genome-wide summary statistics on GFATadj, ASATadj and VATadj from 39,076 UK Biobank participants with full-body magnetic resonance imaging available, we found that GFATadj is associated with a more favourable cardiometabolic risk profile including lower low density lipoprotein (LDL) cholesterol, triglycerides, fasting glucose, fasting insulin, liver enzyme levels and blood pressure as well as higher high density lipoprotein (HDL) cholesterol levels. GFATadj also is negatively associated with ischemic stroke, coronary artery disease, type 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). ASATadj is not associated with cardiometabolic traits and diseases, whereas VATadj is associated with liver fat accumulation but not with NAFLD or other cardiometabolic traits or diseases. Although the absolute effect sizes of GFATadj on LDL cholesterol were more pronounced in women compared to men, most associations did not differ by sex. CONCLUSIONS The inability of subcutaneous fat depots to efficiently store energy substrates could be the causal factor underlying the association of visceral lipid deposition with cardiometabolic health.
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Affiliation(s)
- Eloi Gagnon
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
| | - Audrey Paulin
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
| | - Patricia L Mitchell
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
| | - Benoit J Arsenault
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada; Department of Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada.
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145
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Chen JJ, Chen IC, Wei CY, Lin SY, Chen YM. Utilize polygenic risk score to enhance fracture risk estimation and improve the performance of FRAX in patients with osteoporosis. Arch Osteoporos 2023; 18:147. [PMID: 38036866 DOI: 10.1007/s11657-023-01357-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 11/20/2023] [Indexed: 12/02/2023]
Abstract
This study examined the use of polygenic risk scores (PGS) in combination with the Fracture Risk Assessment Tool (FRAX) to enhance fragility fractures risk estimation in osteoporosis patients. Analyzing data from over 57,000 participants, PGS improved fracture risk estimation, especially for individuals with intermediate to low risks, allowing personalized preventive strategies. INTRODUCTION Osteoporosis and fragility fractures are multifactorial, with contributions from both clinical and genetic determinants. However, whether using polygenic risk scores (PGS) may enhance the risk estimation of osteoporotic fracture in addition to Fracture Risk Assessment Tool (FRAX) remains unknown. This study investigated the collective association of PGS and FRAX with fragility fracture. METHODS We conducted a cohort study from the Taiwan Precision Medicine Initiative (TPMI) at Taichung Veterans General Hospital, Taiwan. Genotyping was performed to compute PGS associated with bone mineral density (BMD). Phenome-wide association studies were executed to pinpoint phenotypes correlated with the PGS. Logistic regression analysis was conducted to ascertain factors associated with osteoporotic fractures. RESULTS Among all 57,257 TPMI participants, 3744 (904 men and 2840 women, with a mean age of 66.7) individuals had BMD testing, with 540 (14.42%) presenting with fractures. The 3744 individuals who underwent BMD testing were categorized into four quartiles (Q1-Q4) based on PGS; 540 (14.42%) presented with fractures. Individuals with PGS-Q1 exhibited lower BMD, a higher prevalence of major fractures, and elevated FRAX-major and FRAX-hip than those with PGS-Q4. PGS was associated with major fractures after adjusting age, sex, and FRAX scores. Notably, the risk of major fractures (PGS-Q1 vs. Q4) was significantly higher in the subgroups of FRAX-major scores < 10% and 10-20%, but not in participants with a FRAX-major score ≧ 20%. CONCLUSIONS Our study highlights the potential of PGS to augment fracture risk estimation in conjunction with FRAX, particularly in individuals with middle to low risks. Incorporating genetic testing could empower physicians to tailor personalized preventive strategies for osteoporosis.
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Affiliation(s)
- Jian-Jiun Chen
- Department of Orthopedics, Taipei Veterans General Hospital, Taipei, Taiwan
| | - I-Chieh Chen
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Chia-Yi Wei
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Shih-Yi Lin
- Center for Geriatrics and Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan.
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung-Hsing University, Taichung, Taiwan.
- School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan.
| | - Yi-Ming Chen
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan.
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung-Hsing University, Taichung, Taiwan.
- School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan.
- Division of Allergy, Immunology and Rheumatology, Taichung Veterans General Hospital, Taichung, Taiwan.
- Institute of Biomedical Science and Rong-Hsing Research Center for Translational Medicine, Chung-Hsing University, Taichung, Taiwan.
- Precision Medicine Research Center, College of Medicine, National Chung Hsing University, Taichung, Taiwan.
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146
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Kaya S, Alliston T, Evans DS. Genetic and Gene Expression Resources for Osteoporosis and Bone Biology Research. Curr Osteoporos Rep 2023; 21:637-649. [PMID: 37831357 PMCID: PMC11098148 DOI: 10.1007/s11914-023-00821-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/11/2023] [Indexed: 10/14/2023]
Abstract
PURPOSE OF REVIEW The integration of data from multiple genomic assays from humans and non-human model organisms is an effective approach to identify genes involved in skeletal fragility and fracture risk due to osteoporosis and other conditions. This review summarizes genome-wide genetic variation and gene expression data resources relevant to the discovery of genes contributing to skeletal fragility and fracture risk. RECENT FINDINGS Genome-wide association studies (GWAS) of osteoporosis-related traits are summarized, in addition to gene expression in bone tissues in humans and non-human organisms, with a focus on rodent models related to skeletal fragility and fracture risk. Gene discovery approaches using these genomic data resources are described. We also describe the Musculoskeletal Knowledge Portal (MSKKP) that integrates much of the available genomic data relevant to fracture risk. The available genomic resources provide a wealth of knowledge and can be analyzed to identify genes related to fracture risk. Genomic resources that would fill particular scientific gaps are discussed.
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Affiliation(s)
- Serra Kaya
- Department of Orthopedic Surgery, University of California, San Francisco, CA, USA
| | - Tamara Alliston
- Department of Orthopedic Surgery, University of California, San Francisco, CA, USA
| | - Daniel S Evans
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
- California Pacific Medical Center Research Institute, San Francisco, CA, USA.
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147
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Zhao C, Keyak JH, Cao X, Sha Q, Wu L, Luo Z, Zhao LJ, Tian Q, Serou M, Qiu C, Su KJ, Shen H, Deng HW, Zhou W. Multi-view information fusion using multi-view variational autoencoder to predict proximal femoral fracture load. Front Endocrinol (Lausanne) 2023; 14:1261088. [PMID: 38075049 PMCID: PMC10710145 DOI: 10.3389/fendo.2023.1261088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 10/30/2023] [Indexed: 12/18/2023] Open
Abstract
Background Hip fracture occurs when an applied force exceeds the force that the proximal femur can support (the fracture load or "strength") and can have devastating consequences with poor functional outcomes. Proximal femoral strengths for specific loading conditions can be computed by subject-specific finite element analysis (FEA) using quantitative computerized tomography (QCT) images. However, the radiation and availability of QCT limit its clinical usability. Alternative low-dose and widely available measurements, such as dual energy X-ray absorptiometry (DXA) and genetic factors, would be preferable for bone strength assessment. The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion. Results We developed new models using multi-view variational autoencoder (MVAE) for feature representation learning and a product of expert (PoE) model for multi-view information fusion. We applied the proposed models to an in-house Louisiana Osteoporosis Study (LOS) cohort with 931 male subjects, including 345 African Americans and 586 Caucasians. We performed genome-wide association studies (GWAS) to select 256 genetic variants with the lowest p-values for each proximal femoral strength and integrated whole genome sequence (WGS) features and DXA-derived imaging features to predict proximal femoral strength. The best prediction model for fall fracture load was acquired by integrating WGS features and DXA-derived imaging features. The designed models achieved the mean absolute percentage error of 18.04%, 6.84% and 7.95% for predicting proximal femoral fracture loads using linear models of fall loading, nonlinear models of fall loading, and nonlinear models of stance loading, respectively. Conclusion The proposed models are capable of predicting proximal femoral strength using WGS features and DXA-derived imaging features. Though this tool is not a substitute for predicting FEA using QCT images, it would make improved assessment of hip fracture risk more widely available while avoiding the increased radiation exposure from QCT.
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Affiliation(s)
- Chen Zhao
- Department of Applied Computing, Michigan Technological University, Houghton, MI, United States
| | - Joyce H. Keyak
- Department of Radiological Sciences, Department of Biomedical Engineering, Department of Mechanical and Aerospace Engineering, and Chao Family Comprehensive Cancer Center, University of California, Irvine, Irvine, CA, United States
| | - Xuewei Cao
- Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, United States
| | - Qiuying Sha
- Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, United States
| | - Li Wu
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, United States
| | - Zhe Luo
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, United States
| | - Lan-Juan Zhao
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, United States
| | - Qing Tian
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, United States
| | - Michael Serou
- Department of Radiology, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States
| | - Chuan Qiu
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, United States
| | - Kuan-Jui Su
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, United States
| | - Hui Shen
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, United States
| | - Hong-Wen Deng
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, United States
| | - Weihua Zhou
- Department of Applied Computing, Michigan Technological University, Houghton, MI, United States
- Center for Biocomputing and Digital Health, Institute of Computing and Cybersystems, and Health Research Institute, Michigan Technological University, Houghton, MI, United States
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148
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Mou X, He B, Zhang M, Zhu Y, Ou Y, Chen X. Causal influence of muscle weakness on cardiometabolic diseases and osteoporosis. Sci Rep 2023; 13:19974. [PMID: 37968290 PMCID: PMC10651997 DOI: 10.1038/s41598-023-46837-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 11/06/2023] [Indexed: 11/17/2023] Open
Abstract
The causal roles of muscle weakness in cardiometabolic diseases and osteoporosis remain elusive. This two-sample Mendelian randomization (MR) study aims to explore the causal roles of muscle weakness in the risk of cardiometabolic diseases and osteoporosis. 15 single nucleotide polymorphisms (SNPs, P < 5 × 10-8) associated with muscle weakness were used as instrumental variables. Genetic predisposition to muscle weakness led to increased risk of coronary artery disease (inverse variance weighted [IVW] analysis, beta-estimate: 0.095, 95% confidence interval [CI]: 0.023 to 0.166, standard error [SE]:0.036, P-value = 0.009) and reduced risk of heart failure (weight median analysis, beta-estimate: - 0.137, 95% CI - 0.264 to - 0.009, SE:0.065, P-value = 0.036). In addition, muscle weakness may reduce the estimated bone mineral density (eBMD, weight median analysis, beta-estimate: - 0.059, 95% CI - 0.110 to - 0.008, SE:0.026, P-value = 0.023). We found no MR associations between muscle weakness and atrial fibrillation, type 2 diabetes or fracture. This study provides robust evidence that muscle weakness is causally associated with the incidence of coronary artery disease and heart failure, which may provide new insight to prevent and treat these two cardiometabolic diseases.
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Affiliation(s)
- Xiaoqing Mou
- Department of Radiology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Bin He
- Department of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
| | - Muzi Zhang
- Department of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yong Zhu
- Department of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yunsheng Ou
- Department of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaojun Chen
- Department of Orthopedics, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, China.
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149
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Yu J, Zhuang C, Guo W, Zhou X, Chen Y, Wang L, Li W, Zhu Y, Zhuang R, Tian K. Causal relationship between breakfast skipping and bone mineral density: a two-sample Mendelian randomized study. Front Endocrinol (Lausanne) 2023; 14:1200892. [PMID: 38027166 PMCID: PMC10660815 DOI: 10.3389/fendo.2023.1200892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 10/11/2023] [Indexed: 12/01/2023] Open
Abstract
Objective To explore the causal association between breakfast skipping and bone mineral density (BMD) through two-sample Mendelian randomisation (MR) analysis. Methods A two-sample MR approach was adopted to explore the causal relationship of breakfast skipping with BMDs (across three skeletal sites and five age groups). Publicly available genome-wide association study summary data were used for MR analysis. We used five methods to estimate the causal associations between breakfast skipping and BMDs: inverse-variance weighting (IVW), MR-Egger, weighted median, simple mode, and weighted mode. IVW was used for the main analysis and the remaining four methods were used as supplementary analyses. The heterogeneity of the MR results was determined using IVW and MR-Egger methods. The pleiotropy of the MR results was determined using MR-Egger intercept. Furthermore, a leave-one-out test was performed to determine whether the MR results were affected by a single nucleotide polymorphism. Results With the IVW method, we did not find any causal relationship between breakfast skipping and forearm, femoral neck, and lumbar spine BMD. Subsequently, when we included BMD data stratified by five different age groups in the analysis, the results showed that there was no apparent causal effect between breakfast skipping and age-stratified BMD. This finding was supported by all four supplementary methods (P > 0.05 for all methods). No heterogeneity or horizontal pleiotropy was detected in any of the analyses (P > 0.05). The leave-one-out tests conducted in the analyses did not identify any single nucleotide polymorphism that could have influenced the MR results, indicating the reliability of our findings. Conclusion No causal effect was found between breakfast skipping and BMD (across three skeletal sites and five age groups).
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Affiliation(s)
- Jinsheng Yu
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Chen Zhuang
- Alberta Institute, Wenzhou Medical University, Wenzhou, China
| | - Wenxuan Guo
- Orthopedic Department, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Xing Zhou
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Yixuan Chen
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Likang Wang
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Wenkai Li
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Yiwen Zhu
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Rujie Zhuang
- Orthopedic Department, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Kun Tian
- Orthopedic Department, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
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150
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Nethander M, Movérare-Skrtic S, Kämpe A, Coward E, Reimann E, Grahnemo L, Borbély É, Helyes Z, Funck-Brentano T, Cohen-Solal M, Tuukkanen J, Koskela A, Wu J, Li L, Lu T, Gabrielsen ME, Mägi R, Hoff M, Lerner UH, Henning P, Ullum H, Erikstrup C, Brunak S, Langhammer A, Tuomi T, Oddsson A, Stefansson K, Pettersson-Kymmer U, Ostrowski SR, Pedersen OBV, Styrkarsdottir U, Mäkitie O, Hveem K, Richards JB, Ohlsson C. An atlas of genetic determinants of forearm fracture. Nat Genet 2023; 55:1820-1830. [PMID: 37919453 PMCID: PMC10632131 DOI: 10.1038/s41588-023-01527-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 09/13/2023] [Indexed: 11/04/2023]
Abstract
Osteoporotic fracture is among the most common and costly of diseases. While reasonably heritable, its genetic determinants have remained elusive. Forearm fractures are the most common clinically recognized osteoporotic fractures with a relatively high heritability. To establish an atlas of the genetic determinants of forearm fractures, we performed genome-wide association analyses including 100,026 forearm fracture cases. We identified 43 loci, including 26 new fracture loci. Although most fracture loci associated with bone mineral density, we also identified loci that primarily regulate bone quality parameters. Functional studies of one such locus, at TAC4, revealed that Tac4-/- mice have reduced mechanical bone strength. The strongest forearm fracture signal, at WNT16, displayed remarkable bone-site-specificity with no association with hip fractures. Tall stature and low body mass index were identified as new causal risk factors for fractures. The insights from this atlas may improve fracture prediction and enable therapeutic development to prevent fractures.
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Grants
- Wellcome Trust
- IngaBritt och Arne Lundbergs Forskningsstiftelse (Ingabritt and Arne Lundberg Research Foundation)
- Novo Nordisk Fonden (Novo Nordisk Foundation)
- Knut och Alice Wallenbergs Stiftelse (Knut and Alice Wallenberg Foundation)
- the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALFGBG-720331 and ALFGBG-965235)
- the Hungarian Brain research Program 3.0, Hungarian National Research, Development and Innovation Office (OTKA K- 138046, OTKA FK-137951, TKP2021-EGA-16), New National Excellence Program of the Ministry for Innovation and Technology (ÚNKP-22-5-PTE-1447), János Bolyai János Scholarship (BO/00496/21/5) of the Hungarian Academy of Sciences, Eotvos Lorad Research Network, National Laboratory for Drug Research and Development.
- Vetenskapsrådet (Swedish Research Council)
- Svenska Läkaresällskapet (Swedish Society of Medicine)
- Kempestiftelserna (Kempe Foundations)
- the Swedish Sports Research Council (87/06) the Medical Faculty of Umeå University (ALFVLL:968:22-2005, ALFVLL: 937-2006, ALFVLL:223:11-2007, ALFVLL:78151-2009) the county council of Västerbotten (Spjutspetsanslag VLL:159:33-2007)
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Affiliation(s)
- Maria Nethander
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sofia Movérare-Skrtic
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anders Kämpe
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Eivind Coward
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ene Reimann
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Louise Grahnemo
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Éva Borbély
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Pécs, Hungary
- National Laboratory for Drug Research and Development, Budapest, Hungary
| | - Zsuzsanna Helyes
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Pécs, Hungary
- National Laboratory for Drug Research and Development, Budapest, Hungary
- Eotvos Lorand Research Network, Chronic Pain Research Group, University of Pécs, Pécs, Hungary
| | - Thomas Funck-Brentano
- BIOSCAR UMRS 1132, Université Paris Diderot, Sorbonne Paris Cité, INSERM, Paris, France
| | - Martine Cohen-Solal
- BIOSCAR UMRS 1132, Université Paris Diderot, Sorbonne Paris Cité, INSERM, Paris, France
| | - Juha Tuukkanen
- Department of Anatomy and Cell Biology, Faculty of Medicine, Institute of Cancer Research and Translational Medicine, University of Oulu, Oulu, Finland
| | - Antti Koskela
- Department of Anatomy and Cell Biology, Faculty of Medicine, Institute of Cancer Research and Translational Medicine, University of Oulu, Oulu, Finland
| | - Jianyao Wu
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Lei Li
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
| | - Maiken E Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Mari Hoff
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Rheumatology, St Olavs Hospital, Trondheim, Norway
| | - Ulf H Lerner
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Petra Henning
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Endocrinology, Abdominal Center, Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | - Kari Stefansson
- deCODE genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Sisse Rye Ostrowski
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Copenhagen Hospital Biobank Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Ole Birger Vesterager Pedersen
- Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Koege, Denmark
| | | | - Outi Mäkitie
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Folkhälsan Institute of Genetics, Helsinki, Finland
- Children's Hospital and Pediatric Research Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, and Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - J Brent Richards
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Drug Treatment, Gothenburg, Sweden.
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