1
|
Choi J, Xu Z, Sun R. Variance-components tests for genetic association with multiple interval-censored outcomes. Stat Med 2024; 43:2560-2574. [PMID: 38636557 PMCID: PMC11116038 DOI: 10.1002/sim.10081] [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: 10/19/2022] [Revised: 02/18/2024] [Accepted: 04/02/2024] [Indexed: 04/20/2024]
Abstract
Massive genetic compendiums such as the UK Biobank have become an invaluable resource for identifying genetic variants that are associated with complex diseases. Due to the difficulties of massive data collection, a common practice of these compendiums is to collect interval-censored data. One challenge in analyzing such data is the lack of methodology available for genetic association studies with interval-censored data. Genetic effects are difficult to detect because of their rare and weak nature, and often the time-to-event outcomes are transformed to binary phenotypes for access to more powerful signal detection approaches. However transforming the data to binary outcomes can result in loss of valuable information. To alleviate such challenges, this work develops methodology to associate genetic variant sets with multiple interval-censored outcomes. Testing sets of variants such as genes or pathways is a common approach in genetic association settings to lower the multiple testing burden, aggregate small effects, and improve interpretations of results. Instead of performing inference with only a single outcome, utilizing multiple outcomes can increase statistical power by aggregating information across multiple correlated phenotypes. Simulations show that the proposed strategy can offer significant power gains over a single outcome approach. We apply the proposed test to the investigation that motivated this study, a search for the genes that perturb risks of bone fractures and falls in the UK Biobank.
Collapse
Affiliation(s)
- Jaihee Choi
- Department of Statistics, Rice University, Texas, USA
| | - Zhichao Xu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Texas, USA
| | - Ryan Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Texas, USA
| |
Collapse
|
2
|
Sobczyk MK, Faber BG, Southam L, Frysz M, Hartley A, Zeggini E, Tang H, Gaunt TR. Causal relationships between anthropometric traits, bone mineral density, osteoarthritis and spinal stenosis: A Mendelian randomisation investigation. Osteoarthritis Cartilage 2024; 32:719-729. [PMID: 38160745 DOI: 10.1016/j.joca.2023.12.003] [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: 10/31/2023] [Revised: 12/12/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVE Spinal stenosis is a common condition among older individuals, with significant morbidity attached. Little is known about its risk factors but degenerative conditions, such as osteoarthritis (OA) have been identified for their mechanistic role. This study aims to explore causal relationships between anthropometric risk factors, OA, and spinal stenosis using Mendelian randomisation (MR) techniques. DESIGN We applied two-sample MR to investigate the causal relationships between genetic liability for select risk factors and spinal stenosis. Next, we examined the genetic relationship between OA and spinal stenosis with linkage disequilibrium score regression and Causal Analysis Using Summary Effect estimates MR method. Finally, we used multivariable MR (MVMR) to explore whether OA and body mass index (BMI) mediate the causal pathways identified. RESULTS Our analysis revealed strong evidence for the effect of higher BMI (odds ratio [OR] = 1.54, 95%CI: 1.41-1.69, p-value = 2.7 × 10-21), waist (OR = 1.43, 95%CI: 1.15-1.79, p-value = 1.5 × 10-3) and hip (OR = 1.50, 95%CI: 1.27-1.78, p-value = 3.3 × 10-6) circumference on spinal stenosis. Strong evidence of causality was also observed for higher bone mineral density (BMD): total body (OR = 1.21, 95%CI: 1.12-1.29, p-value = 1.6 × 10-7), femoral neck (OR = 1.35, 95%CI: 1.09-1.37, p-value = 7.5×10-7), and lumbar spine (OR = 1.38, 95%CI: 1.25-1.52, p-value = 4.4 × 10-11). We detected high genetic correlations between spinal stenosis and OA (rg range: 0.47-0.66), with Causal Analysis Using Summary Effect estimates results supporting a causal effect of OA on spinal stenosis (ORallOA = 1.6, 95%CI: 1.41-1.79). Direct effects of BMI, BMD on spinal stenosis remained after adjusting for OA in the MVMR. CONCLUSIONS Genetic susceptibility to anthropometric risk factors, particularly higher BMI and BMD can increase the risk of spinal stenosis, independent of OA status. These results may inform preventative strategies and treatments.
Collapse
Affiliation(s)
- Maria K Sobczyk
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom.
| | - Benjamin G Faber
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom; Musculoskeletal Research Unit, University of Bristol, Bristol, UK.
| | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany.
| | - Monika Frysz
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom; Musculoskeletal Research Unit, University of Bristol, Bristol, UK.
| | - April Hartley
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom.
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany; Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, 81675 Munich, Germany.
| | - Haotian Tang
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom.
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom.
| |
Collapse
|
3
|
Roca-Ayats N, Maceda I, Bruque CD, Martínez-Gil N, Garcia-Giralt N, Cozar M, Mellibovsky L, Van Hul W, Lao O, Grinberg D, Balcells S. Evolutionary and functional analyses of LRP5 in archaic and extant modern humans. Hum Genomics 2024; 18:53. [PMID: 38802968 DOI: 10.1186/s40246-024-00616-6] [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: 02/02/2024] [Accepted: 05/07/2024] [Indexed: 05/29/2024] Open
Abstract
BACKGROUND The human lineage has undergone a postcranial skeleton gracilization (i.e. lower bone mass and strength relative to body size) compared to other primates and archaic populations such as the Neanderthals. This gracilization has been traditionally explained by differences in the mechanical load that our ancestors exercised. However, there is growing evidence that gracilization could also be genetically influenced. RESULTS We have analyzed the LRP5 gene, which is known to be associated with high bone mineral density conditions, from an evolutionary and functional point of view. Taking advantage of the published genomes of archaic Homo populations, our results suggest that this gene has a complex evolutionary history both between archaic and living humans and within living human populations. In particular, we identified the presence of different selective pressures in archaics and extant modern humans, as well as evidence of positive selection in the African and South East Asian populations from the 1000 Genomes Project. Furthermore, we observed a very limited evidence of archaic introgression in this gene (only at three haplotypes of East Asian ancestry out of the 1000 Genomes), compatible with a general erasing of the fingerprint of archaic introgression due to functional differences in archaics compared to extant modern humans. In agreement with this hypothesis, we observed private mutations in the archaic genomes that we experimentally validated as putatively increasing bone mineral density. In particular, four of five archaic missense mutations affecting the first β-propeller of LRP5 displayed enhanced Wnt pathway activation, of which two also displayed reduced negative regulation. CONCLUSIONS In summary, these data suggest a genetic component contributing to the understanding of skeletal differences between extant modern humans and archaic Homo populations.
Collapse
Affiliation(s)
- Neus Roca-Ayats
- Departament de Genètica, Microbiologia i Estadística and IBUB, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) ISCIII, Barcelona, Spain
- Institut de Recerca Sant Joan de Déu (IRSJD), Barcelona, Spain
| | - Iago Maceda
- CNAG, Centre Nacional d'Analisi Genòmic, C/ Baldiri I Reixach 4, 08028, Barcelona, Spain
- Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Carlos David Bruque
- Unidad de Conocimiento Traslacional Hospitalaria Patagónica, Hospital de Alta Complejidad El Calafate - S.A.M.I.C., Santa Cruz, Argentina
| | - Núria Martínez-Gil
- Departament de Genètica, Microbiologia i Estadística and IBUB, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) ISCIII, Barcelona, Spain
- Institut de Recerca Sant Joan de Déu (IRSJD), Barcelona, Spain
| | - Natàlia Garcia-Giralt
- Musculoskeletal Research Group, IMIM (Hospital del Mar Medical Research Institute), Centro de Investigación Biomédica en Red en Fragilidad y Envejecimiento Saludable (CIBERFES), ISCIII, Departament de Genètica, Microbiologia i Estadística, UB, Barcelona, Spain
| | - Mónica Cozar
- Departament de Genètica, Microbiologia i Estadística and IBUB, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) ISCIII, Barcelona, Spain
- Institut de Recerca Sant Joan de Déu (IRSJD), Barcelona, Spain
| | - Leonardo Mellibovsky
- Musculoskeletal Research Group, IMIM (Hospital del Mar Medical Research Institute), Centro de Investigación Biomédica en Red en Fragilidad y Envejecimiento Saludable (CIBERFES), ISCIII, Barcelona, Spain
| | - Wim Van Hul
- Center of Medical Genetics, University of Antwerp, 2650, Antwerp, Belgium
| | - Oscar Lao
- Institute of Evolutionary Biology, CSIC-Universitat Pompeu Fabra, 08003, Barcelona, Spain.
| | - Daniel Grinberg
- Departament de Genètica, Microbiologia i Estadística and IBUB, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) ISCIII, Barcelona, Spain
- Institut de Recerca Sant Joan de Déu (IRSJD), Barcelona, Spain
| | - Susanna Balcells
- Departament de Genètica, Microbiologia i Estadística and IBUB, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) ISCIII, Barcelona, Spain
- Institut de Recerca Sant Joan de Déu (IRSJD), Barcelona, Spain
| |
Collapse
|
4
|
Yue YS, Liu Y, Lu K, Shi Q, Zhou KX, Li C. Outdoor walking, genetic predisposition, and the risk of incident osteoporosis among older adults: A prospective large population-based cohort study. Osteoporos Int 2024:10.1007/s00198-024-07122-4. [PMID: 38771526 DOI: 10.1007/s00198-024-07122-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 05/06/2024] [Indexed: 05/22/2024]
Abstract
This large-scale prospective study showed that a significant association between longer duration of daily outdoor walking and reduced osteoporosis risk was found among older adults, particularly among those with a low genetic predisposition to osteoporosis, which highlighted the importance of outdoor walking as a simple, cost-effective adjunct for preventing osteoporosis. PURPOSE The available cross-sectional data and small-scale studies indicate that outdoor walking benefits bone metabolism. Nevertheless, there is a scarcity of comprehensive prospective research investigating the enduring correlation between outdoor walking and osteoporosis. This study aims to conduct a prospective analysis of the correlation between outdoor walking and osteoporosis while also examining potential variations influenced by genetic susceptibility to osteoporosis. METHODS 24,700 older adults without osteoporosis at baseline were enrolled. These individuals were followed up until December 31, 2021, during which data on outdoor walking was gathered. The genetic risk score for osteoporosis was comprised of 14 single-nucleotide polymorphisms. RESULTS 4,586 cases of osteoporosis were identified throughout a median follow-up period of 37.3 months. Those who walked outside for > 30 but ≤ 60 min per day had a hazard ratio (HR) of 0.83 (95% confidence interval (CI): 0.72-0.95) for incident osteoporosis, whereas those who walked outside for > 60 min per day had an HR of 0.60 (95% CI: 0.39-0.92). We found that osteoporosis risk exhibited a declining trend in individuals with low genetic risk. Individuals walking outside for > 60 min per day tended to have the lowest overall osteoporosis risk among those with high genetic risk. CONCLUSIONS A significant negative correlation exists between an extended period of daily outdoor walking and osteoporosis incidence risk. This correlation is particularly pronounced among individuals with low genetic risk. The results above underscore the significance of outdoor walking as a simple and economical adjunct to public health programs to prevent osteoporosis.
Collapse
Affiliation(s)
- Yu-Shan Yue
- Department of Rehabilitation, Affiliated Kunshan Hospital of Jiangsu University, Suzhou, Jiangsu, China
| | - Yang Liu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Ke Lu
- Department of Orthopedics, Affiliated Kunshan Hospital of Jiangsu University, Suzhou, Jiangsu, China
| | - Qin Shi
- Department of Orthopedics, the First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Kai-Xin Zhou
- Guangzhou Laboratory, Guangzhou, Guangdong, China.
| | - Chong Li
- Department of Orthopedics, Affiliated Kunshan Hospital of Jiangsu University, Suzhou, Jiangsu, China.
| |
Collapse
|
5
|
Reppe S, Gundersen S, Sandve GK, Wang Y, Andreassen OA, Medina-Gomez C, Rivadeneira F, Utheim TP, Hovig E, Gautvik KM. Identification of Transcripts with Shared Roles in the Pathogenesis of Postmenopausal Osteoporosis and Cardiovascular Disease. Int J Mol Sci 2024; 25:5554. [PMID: 38791593 PMCID: PMC11121938 DOI: 10.3390/ijms25105554] [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: 04/11/2024] [Revised: 05/11/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
Epidemiological evidence suggests existing comorbidity between postmenopausal osteoporosis (OP) and cardiovascular disease (CVD), but identification of possible shared genes is lacking. The skeletal global transcriptomes were analyzed in trans-iliac bone biopsies (n = 84) from clinically well-characterized postmenopausal women (50 to 86 years) without clinical CVD using microchips and RNA sequencing. One thousand transcripts highly correlated with areal bone mineral density (aBMD) were further analyzed using bioinformatics, and common genes overlapping with CVD and associated biological mechanisms, pathways and functions were identified. Fifty genes (45 mRNAs, 5 miRNAs) were discovered with established roles in oxidative stress, inflammatory response, endothelial function, fibrosis, dyslipidemia and osteoblastogenesis/calcification. These pleiotropic genes with possible CVD comorbidity functions were also present in transcriptomes of microvascular endothelial cells and cardiomyocytes and were differentially expressed between healthy and osteoporotic women with fragility fractures. The results were supported by a genetic pleiotropy-informed conditional False Discovery Rate approach identifying any overlap in single nucleotide polymorphisms (SNPs) within several genes encoding aBMD- and CVD-associated transcripts. The study provides transcriptional and genomic evidence for genes of importance for both BMD regulation and CVD risk in a large collection of postmenopausal bone biopsies. Most of the transcripts identified in the CVD risk categories have no previously recognized roles in OP pathogenesis and provide novel avenues for exploring the mechanistic basis for the biological association between CVD and OP.
Collapse
Affiliation(s)
- Sjur Reppe
- Department of Medical Biochemistry, Oslo University Hospital, 0450 Oslo, Norway
- Unger-Vetlesen Institute, Lovisenberg Diaconal Hospital, 0440 Oslo, Norway
- Department of Plastic and Reconstructive Surgery, Oslo University Hospital, 0424 Oslo, Norway
| | - Sveinung Gundersen
- Center for Bioinformatics, Department of Informatics, University of Oslo, 0313 Oslo, Norway
| | - Geir K. Sandve
- Department of Informatics, University of Oslo, 0373 Oslo, Norway; (G.K.S.)
| | - Yunpeng Wang
- NORMENT, Institute of Clinical Medicine, University of Oslo, 0450 Oslo, Norway; (Y.W.); (O.A.A.)
- Division of Mental Health and Addiction, Oslo University Hospital, 0424 Oslo, Norway
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Ole A. Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, 0450 Oslo, Norway; (Y.W.); (O.A.A.)
- Division of Mental Health and Addiction, Oslo University Hospital, 0424 Oslo, Norway
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands; (C.M.-G.); (F.R.)
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands; (C.M.-G.); (F.R.)
| | - Tor P. Utheim
- Department of Medical Biochemistry, Oslo University Hospital, 0450 Oslo, Norway
- Department of Plastic and Reconstructive Surgery, Oslo University Hospital, 0424 Oslo, Norway
| | - Eivind Hovig
- Department of Informatics, University of Oslo, 0373 Oslo, Norway; (G.K.S.)
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, 0424 Oslo, Norway
| | - Kaare M. Gautvik
- Unger-Vetlesen Institute, Lovisenberg Diaconal Hospital, 0440 Oslo, Norway
| |
Collapse
|
6
|
Zhao P, Ying Z, Yuan C, Zhang H, Dong A, Tao J, Yi X, Yang M, Jin W, Tian W, Karasik D, Tian G, Zheng H. Shared genetic architecture highlights the bidirectional association between major depressive disorder and fracture risk. Gen Psychiatr 2024; 37:e101418. [PMID: 38737893 PMCID: PMC11086190 DOI: 10.1136/gpsych-2023-101418] [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: 10/31/2023] [Accepted: 03/28/2024] [Indexed: 05/14/2024] Open
Abstract
Background There is limited evidence suggesting that osteoporosis might exacerbate depressive symptoms, while more studies demonstrate that depression negatively affects bone density and increases fracture risk. Aims To explore the relationship between major depressive disorder (MDD) and fracture risk. Methods We conducted a nested case-control analysis (32 670 patients with fracture and 397 017 individuals without fracture) and a matched cohort analysis (16 496 patients with MDD and 435 492 individuals without MDD) in the same prospective UK Biobank data set. Further, we investigated the shared genetic architecture between MDD and fracture with linkage disequilibrium score regression and the MiXeR statistical tools. We used the conditional/conjunctional false discovery rate approach to identify the specific shared loci. We calculated the weighted genetic risk score for individuals in the UK Biobank and logistic regression was used to confirm the association observed in the prospective study. Results We found that MDD was associated with a 14% increase in fracture risk (hazard ratio (HR) 1.14, 95% CI 1.14 to 1.15, p<0.001) in the nested case-control analysis, while fracture was associated with a 72% increase in MDD risk (HR 1.72, 95% CI 1.64 to 1.79, p<0.001) in the matched cohort analysis, suggesting a longitudinal and bidirectional relationship. Further, genetic summary data suggested a genetic overlap between MDD and fracture. Specifically, we identified four shared genomic loci, with the top signal (rs7554101) near SGIP1. The protein encoded by SGIP1 is involved in cannabinoid receptor type 1 signalling. We found that genetically predicted MDD was associated with a higher risk of fracture and vice versa. In addition, we found that the higher expression level of SGIP1 in the spinal cord and muscle was associated with an increased risk of fracture and MDD. Conclusions The genetic pleiotropy between MDD and fracture highlights the bidirectional association observed in the epidemiological analysis. The shared genetic components (such as SGIP1) between the diseases suggest that modulating the endocannabinoid system could be a potential therapeutic strategy for both MDD and bone loss.
Collapse
Affiliation(s)
- Pianpian Zhao
- The Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou,Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Zhimin Ying
- Department of Orthopedic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Chengda Yuan
- Department of Dermatology, Hangzhou Hospital of Traditional Chinese Medicine, Hangzhou, Zhejiang, China
| | - Haisheng Zhang
- The Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou,Zhejiang, China
| | - Ao Dong
- The Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou,Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
| | - Jianguo Tao
- The Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou,Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
| | - Xiangjiao Yi
- The Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou,Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
| | - Mengyuan Yang
- The Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou,Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
| | - Wen Jin
- The Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou,Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
| | - Weiliang Tian
- Department of Global Statistics, Eli Lilly and Company, Branchburg, New Jersey, USA
| | - David Karasik
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Geng Tian
- Binzhou Medical University, Yantai, Shandong, China
| | - Houfeng Zheng
- The Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou,Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| |
Collapse
|
7
|
Wu Q, Dai J. Enhanced osteoporotic fracture prediction in postmenopausal women using Bayesian optimization of machine learning models with genetic risk score. J Bone Miner Res 2024; 39:462-472. [PMID: 38477741 DOI: 10.1093/jbmr/zjae025] [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: 05/31/2023] [Revised: 01/10/2024] [Accepted: 01/12/2024] [Indexed: 03/14/2024]
Abstract
This study aimed to enhance the fracture risk prediction accuracy in major osteoporotic fractures (MOFs) and hip fractures (HFs) by integrating genetic profiles, machine learning (ML) techniques, and Bayesian optimization. The genetic risk score (GRS), derived from 1,103 risk single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS), was formulated for 25,772 postmenopausal women from the Women's Health Initiative dataset. We developed four ML models: Support Vector Machine (SVM), Random Forest, XGBoost, and Artificial Neural Network (ANN) for binary fracture outcome and 10-year fracture risk prediction. GRS and FRAX clinical risk factors (CRFs) were used as predictors. Death as a competing risk was accounted for in ML models for time-to-fracture data. ML models were subsequently fine-tuned through Bayesian optimization, which displayed marked superiority over traditional grid search. Evaluation of the models' performance considered an array of metrics such as accuracy, weighted F1 Score, the area under the precision-recall curve (PRAUC), and the area under the receiver operating characteristic curve (AUC) for binary fracture predictions, and the C-index, Brier score, and dynamic mean AUC over a 10-year follow-up period for fracture risk predictions. We found that GRS-integrated XGBoost with Bayesian optimization is the most effective model, with an accuracy of 91.2% (95% CI: 90.4-92.0%) and an AUC of 0.739 (95% CI: 0.731-0.746) in MOF binary predictions. For 10-year fracture risk modeling, the XGBoost model attained a C-index of 0.795 (95% CI: 0.783-0.806) and a mean dynamic AUC of 0.799 (95% CI: 0.788-0.809). Compared to FRAX, the XGBoost model exhibited a categorical net reclassification improvement (NRI) of 22.6% (P = .004). A sensitivity analysis, which included BMD but lacked GRS, reaffirmed these findings. Furthermore, portability tests in diverse non-European groups, including Asians and African Americans, underscored the model's robustness and adaptability. This study accentuates the potential of combining genetic insights and optimized ML in strengthening fracture predictions, heralding new preventive strategies for postmenopausal women.
Collapse
Affiliation(s)
- Qing Wu
- Department of Biomedical Informatics (Dr. Qing Wu, Jingyuan Dai), College of Medicine, The Ohio State University, Columbus, OH 43210, United States
| | - Jingyuan Dai
- Department of Biomedical Informatics (Dr. Qing Wu, Jingyuan Dai), College of Medicine, The Ohio State University, Columbus, OH 43210, United States
| |
Collapse
|
8
|
Zhang W, Lu T, Sladek R, Li Y, Najafabadi H, Dupuis J. SharePro: an accurate and efficient genetic colocalization method accounting for multiple causal signals. Bioinformatics 2024; 40:btae295. [PMID: 38688586 PMCID: PMC11105950 DOI: 10.1093/bioinformatics/btae295] [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: 07/24/2023] [Revised: 04/11/2024] [Accepted: 04/29/2024] [Indexed: 05/02/2024] Open
Abstract
MOTIVATION Colocalization analysis is commonly used to assess whether two or more traits share the same genetic signals identified in genome-wide association studies (GWAS), and is important for prioritizing targets for functional follow-up of GWAS results. Existing colocalization methods can have suboptimal performance when there are multiple causal variants in one genomic locus. RESULTS We propose SharePro to extend the COLOC framework for colocalization analysis. SharePro integrates linkage disequilibrium (LD) modeling and colocalization assessment by grouping correlated variants into effect groups. With an efficient variational inference algorithm, posterior colocalization probabilities can be accurately estimated. In simulation studies, SharePro demonstrated increased power with a well-controlled false positive rate at a low computational cost. Compared to existing methods, SharePro provided stronger and more consistent colocalization evidence for known lipid-lowering drug target proteins and their corresponding lipid traits. Through an additional challenging case of the colocalization analysis of the circulating abundance of R-spondin 3 GWAS and estimated bone mineral density GWAS, we demonstrated the utility of SharePro in identifying biologically plausible colocalized signals. AVAILABILITY AND IMPLEMENTATION SharePro for colocalization analysis is written in Python and openly available at https://github.com/zhwm/SharePro_coloc.
Collapse
Affiliation(s)
- Wenmin Zhang
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec H3A 1E3, Canada
- Montreal Heart Institute, Université de Montréal, Montreal, Quebec H1T 1C8, Canada
| | - Tianyuan Lu
- Department of Statistical Sciences, University of Toronto, Toronto, Ontario M5S 1A1, Canada
| | - Robert Sladek
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec H3A 1E3, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec H3A 0C7, Canada
- Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, Quebec H3A 0G1, Canada
| | - Yue Li
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec H3A 1E3, Canada
- School of Computer Science, McGill University, Montreal, Quebec H3A 2A7, Canada
| | - Hamed Najafabadi
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec H3A 1E3, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec H3A 0C7, Canada
- Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, Quebec H3A 0G1, Canada
| | - Josée Dupuis
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec H3A 1E3, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, McGill College, QC H3A 1Y7, Canada
| |
Collapse
|
9
|
Lu H, Lary CW, Hodonsky CJ, Peyser PA, Bos D, van der Laan SW, Miller CL, Rivadeneira F, Kiel DP, Kavousi M, Medina-Gomez C. Association between BMD and coronary artery calcification: an observational and Mendelian randomization study. J Bone Miner Res 2024; 39:443-452. [PMID: 38477752 DOI: 10.1093/jbmr/zjae022] [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: 08/07/2023] [Revised: 01/10/2024] [Accepted: 01/22/2024] [Indexed: 03/14/2024]
Abstract
Observational studies have reported inconsistent associations between bone mineral density (BMD) and coronary artery calcification (CAC). We examined the observational association of BMD with CAC in 2 large population-based studies and evaluated the evidence for a potential causal relation between BMD and CAC using polygenic risk scores (PRS), 1- and 2-sample Mendelian randomization (MR) approaches. Our study populations comprised 1414 individuals (mean age 69.9 yr, 52.0% women) from the Rotterdam Study and 2233 individuals (mean age 56.5 yr, 50.9% women) from the Framingham Heart Study with complete information on CAC and BMD measurements at the total body (TB-), lumbar spine (LS-), and femoral neck (FN-). We used linear regression models to evaluate the observational association between BMD and CAC. Subsequently, we compared the mean CAC across PRSBMD quintile groups at different skeletal sites. In addition, we used the 2-stage least squares regression and the inverse variance weighted (IVW) model as primary methods for 1- and 2-sample MR to test evidence for a potentially causal association. We did not observe robust associations between measured BMD levels and CAC. These results were consistent with a uniform random distribution of mean CAC across PRSBMD quintile groups (P-value > .05). Moreover, neither 1- nor 2-sample MR supported the possible causal association between BMD and CAC. Our results do not support the contention that lower BMD is (causally) associated with an increased CAC risk. These findings suggest that previously reported epidemiological associations of BMD with CAC are likely explained by unmeasured confounders or shared etiology, rather than by causal pathways underlying both osteoporosis and vascular calcification processes.
Collapse
Affiliation(s)
- Haojie Lu
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, CA 3000, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, CA 3000, The Netherlands
| | - Christine W Lary
- Roux Institute at Northeastern University, Portland, ME 04101, United States
| | - Chani J Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, United States
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, United States
| | - Daniel Bos
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, CA 3000, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, CA 3000, The Netherlands
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, CX 3584, The Netherlands
| | - Clint L Miller
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, United States
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22903, United States
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22903, United States
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, CA 3000, The Netherlands
| | - Douglas P Kiel
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA 02131, United States
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, United States
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, CA 3000, The Netherlands
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, CA 3000, The Netherlands
| |
Collapse
|
10
|
Qin Y, Yang X, Ning Z. Causal roles of educational duration in bone mineral density and risk factors for osteoporosis: a Mendelian randomization study. BMC Musculoskelet Disord 2024; 25:345. [PMID: 38693494 PMCID: PMC11064366 DOI: 10.1186/s12891-024-07428-8] [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: 12/26/2023] [Accepted: 04/09/2024] [Indexed: 05/03/2024] Open
Abstract
BACKGROUND Educational duration might play a vital role in preventing the occurrence and development of osteoporosis(OP). PURPOSE To assess the causal effect of educational duration on bone mineral density(BMD) and risk factors for OP by Mendelian randomization(MR) study. METHODS The causal relationship was analyzed using data from genome-wide association study(GWAS). Inverse variance weighting (IVW) was used as the main analysis method. Horizontal pleiotropy was identified by MR-Egger intercept test, MR pleiotropy residual sum and outlier (MR-PRESSO) test. The leave-one-out method was used as a sensitivity analysis. RESULTS The IVW results indicated that there was a positive causal relationship between educational duration and BMD (OR = 1.012, 95%CI:1.003-1.022), physical activity(PA) (OR = 1.156, 95%CI:1.032-1.295), calcium consumption (OR = 1.004, 95%CI:1.002-1.005), and coffee intake (OR = 1.019, 95%CI:1.014-1.024). There was a negative association between whole body fat mass (OR = 0.950, 95%CI:0.939-0.961), time for vigorous PA (OR = 0.955, 95%CI:0.939-0.972), sunbath (OR = 0.987, 95%CI:0.986-0.989), salt consumption (OR = 0.965, 95%CI:0.959-0.971), fizzy drink intake (OR = 0.985, 95%CI:0.978-0.992), smoking (OR = 0.969, 95%CI:0.964-0.975), and falling risk (OR = 0.976, 95%CI:0.965-0.987). There was no significant association between educational duration and lean mass, time for light-to-moderate PA, milk intake, and alcohol intake. Horizontal pleiotropy was absent in this study. The results were robust under sensitivity analyses. CONCLUSION A longer educational duration was causally linked with increased BMD. No causal relationship had been found between educational duration and lean mass, time for light-to-moderate PA, milk intake, and alcohol consumption as risk factors for osteoporosis.
Collapse
Affiliation(s)
- Yujun Qin
- Department of General Practice, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Nanning, P.R. China.
- The People's Hospital of Hechi, Guangxi Zhuang Autonomous Region, Hechi, P.R. China.
| | - Xia Yang
- Department of General Practice, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Nanning, P.R. China
| | - Zong Ning
- Department of General Practice, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Nanning, P.R. China.
| |
Collapse
|
11
|
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.
Collapse
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.
| |
Collapse
|
12
|
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.
Collapse
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.
| |
Collapse
|
13
|
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.
Collapse
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
| |
Collapse
|
14
|
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.
Collapse
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
| |
Collapse
|
15
|
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.
Collapse
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
Collapse
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.
| |
Collapse
|
16
|
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.
Collapse
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
| |
Collapse
|
17
|
Mabilleau G, Bouvard B. Gut hormone analogues and skeletal health in diabetes and obesity: evidence from preclinical models. Peptides 2024; 177:171228. [PMID: 38657908 DOI: 10.1016/j.peptides.2024.171228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 04/17/2024] [Accepted: 04/22/2024] [Indexed: 04/26/2024]
Abstract
Diabetes mellitus and obesity are rapidly growing worldwide. Aside from metabolic disturbances, these two disorders also affect bone with a higher prevalence of bone fractures. In the last decade, a growingbody of evidence suggested that several gut hormones, including ghrelin, gastrin, glucose-dependent insulinotropic polypeptide (GIP), glucagon, and glucagon-like peptide-1 and 2 (GLP-1 and GLP-2, respectively) may affect bone physiology. Several gut hormone analogues have been developed for the treatment of type 2 diabetes and obesity, and could represent a new alternative in the therapeutic arsenal against bone fragility. In the present review, a summary of the physiological roles of these gut hormones and their analogues is presented at the cellular level but also in several preclinical models of bone fragility disorders including type 2 diabetes mellitus, especially on bone mineral density, microarchitecture and bone material properties. The present review also summarizes the impact of GLP-1 receptor agonists approved for the treatment of type 2 diabetes mellitus and the more recent dual or triple analogue on bone physiology and strength.
Collapse
Affiliation(s)
- Guillaume Mabilleau
- Univ Angers, Nantes Université, ONIRIS, Inserm, RMeS, UMR 1229, SFR ICAT, F-49000, Angers, France; CHU Angers, Département de Pathologie Cellulaire et Tissulaire, UF de Pathologie osseuse, 49933 Angers, France.
| | - Béatrice Bouvard
- Univ Angers, Nantes Université, ONIRIS, Inserm, RMeS, UMR 1229, SFR ICAT, F-49000, Angers, France; CHU Angers, Service de Rhumatologie, F-49933 Angers, France
| |
Collapse
|
18
|
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 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.
Collapse
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
| |
Collapse
|
19
|
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
| |
Collapse
|
20
|
Grigoryan S, Clines GA. Hormonal Control of Bone Architecture Throughout the Lifespan: Implications for Fracture Prediction and Prevention. Endocr Pract 2024:S1530-891X(24)00496-8. [PMID: 38631489 DOI: 10.1016/j.eprac.2024.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 03/31/2024] [Accepted: 04/09/2024] [Indexed: 04/19/2024]
Abstract
BACKGROUND Skeletal modeling in childhood and adolescence and continuous remodeling throughout the lifespan are designed to adapt to a changing environment and resist external forces and fractures. The flux of sex steroids in men and women, beginning from fetal development and evolving through infancy, childhood, puberty, young adulthood, peri/menopause transition, and postmenopause, is critical for bone size, peak bone mass, and fracture resistance. OBJECTIVE This review will highlight how changes in sex steroids throughout the lifespan affect bone cells and the consequence of these changes on bone architecture and strength. METHODS Literature review and discussion. RESULTS The contributions of estrogen and testosterone on skeletal development have been difficult to study due to the reciprocal and intertwining contributions of one on the other. Although orchiectomy in men renders circulating testosterone absent, circulating estrogen also declines due to testosterone being the substrate for estradiol. The discovery of men with absent estradiol or resistance to estrogen and the study of mouse models led to the understanding that estrogen has a larger direct role in skeletal development and maintenance in men and women. The mechanistic reason for larger bone size in men is incompletely understood but related to indirect effects of testosterone on the skeleton, such as higher muscle mass leading to larger mechanical loading. Declines in sex steroids during menopause in women and androgen deprivation therapies in men have profound and negative effects on the skeleton. Therapies to prevent such bone loss are available, but how such therapies can be tailored based on bone size and architecture remains an area of investigation. CONCLUSION In this review, the elegant interplay and contribution of sex steroids on bone architecture in men and women throughout the lifespan is described.
Collapse
Affiliation(s)
- Seda Grigoryan
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Gregory A Clines
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan School of Medicine, Ann Arbor, Michigan; Endocrinology Section, Veterans Affairs Medical Center, Ann Arbor, Michigan.
| |
Collapse
|
21
|
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.
Collapse
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
| |
Collapse
|
22
|
Busse E, Lee B, Nagamani SCS. Genetic Evaluation for Monogenic Disorders of Low Bone Mass and Increased Bone Fragility: What Clinicians Need to Know. Curr Osteoporos Rep 2024:10.1007/s11914-024-00870-6. [PMID: 38600318 DOI: 10.1007/s11914-024-00870-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/23/2024] [Indexed: 04/12/2024]
Abstract
PURPOSE OF REVIEW The purpose of this review is to outline the principles of clinical genetic testing and to provide practical guidance to clinicians in navigating genetic testing for patients with suspected monogenic forms of osteoporosis. RECENT FINDINGS Heritability assessments and genome-wide association studies have clearly shown the significant contributions of genetic variations to the pathogenesis of osteoporosis. Currently, over 50 monogenic disorders that present primarily with low bone mass and increased risk of fractures have been described. The widespread availability of clinical genetic testing offers a valuable opportunity to correctly diagnose individuals with monogenic forms of osteoporosis, thus instituting appropriate surveillance and treatment. Clinical genetic testing may identify the appropriate diagnosis in a subset of patients with low bone mass, multiple or unusual fractures, and severe or early-onset osteoporosis, and thus clinicians should be aware of how to incorporate such testing into their clinical practices.
Collapse
Affiliation(s)
- Emily Busse
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, USA
| | - Brendan Lee
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
- Texas Children's Hospital, Houston, TX, USA.
| | - Sandesh C S Nagamani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Texas Children's Hospital, Houston, TX, USA
| |
Collapse
|
23
|
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.
Collapse
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
| |
Collapse
|
24
|
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.
Collapse
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.
| |
Collapse
|
25
|
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] [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.
Collapse
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.
| |
Collapse
|
26
|
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.
Collapse
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.
| |
Collapse
|
27
|
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.
Collapse
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
| |
Collapse
|
28
|
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.
Collapse
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
| |
Collapse
|
29
|
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, Heidi Skogholt A, Åsvold BO, Valderrabano RJ, Zheng J, Brent Richards J, 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.
Collapse
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
| |
Collapse
|
30
|
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.
Collapse
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
| |
Collapse
|
31
|
Conery M, Pippin JA, Wagley Y, Trang K, Pahl MC, Villani DA, Favazzo LJ, Ackert-Bicknell CL, Zuscik MJ, Katsevich E, Wells AD, Zemel BS, Voight BF, Hankenson KD, Chesi A, Grant SF. GWAS-informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.19.585778. [PMID: 38562830 PMCID: PMC10983984 DOI: 10.1101/2024.03.19.585778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Over 1,100 independent signals have been identified with genome-wide association studies (GWAS) for bone mineral density (BMD), a key risk factor for mortality-increasing fragility fractures; however, the effector gene(s) for most remain unknown. Informed by a variant-to-gene mapping strategy implicating 89 non-coding elements predicted to regulate osteoblast gene expression at BMD GWAS loci, we executed a single-cell CRISPRi screen in human fetal osteoblast 1.19 cells (hFOBs). The BMD relevance of hFOBs was supported by heritability enrichment from cross-cell type stratified LD-score regression involving 98 cell types grouped into 15 tissues. 24 genes showed perturbation in the screen, with four (ARID5B, CC2D1B, EIF4G2, and NCOA3) exhibiting consistent effects upon siRNA knockdown on three measures of osteoblast maturation and mineralization. Lastly, additional heritability enrichments, genetic correlations, and multi-trait fine-mapping revealed that many BMD GWAS signals are pleiotropic and likely mediate their effects via non-bone tissues that warrant attention in future screens.
Collapse
Affiliation(s)
- Mitchell Conery
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - James A. Pippin
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Yadav Wagley
- Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, MI 48109
| | - Khanh Trang
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Matthew C. Pahl
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - David A. Villani
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Cell Biology, Stems Cells and Development Ph.D. Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Lacey J. Favazzo
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- University of Colorado Interdisciplinary Joint Biology Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Cheryl L. Ackert-Bicknell
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- University of Colorado Interdisciplinary Joint Biology Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Michael J. Zuscik
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- University of Colorado Interdisciplinary Joint Biology Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Eugene Katsevich
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Babette S. Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kurt D. Hankenson
- Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, MI 48109
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Endocrinology and Diabetes, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| |
Collapse
|
32
|
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.
Collapse
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.
| |
Collapse
|
33
|
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.
Collapse
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
| |
Collapse
|
34
|
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.
Collapse
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.
| |
Collapse
|
35
|
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.
Collapse
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
| |
Collapse
|
36
|
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.
Collapse
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.
| |
Collapse
|
37
|
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.
Collapse
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.
| |
Collapse
|
38
|
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.
Collapse
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.
| |
Collapse
|
39
|
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.
Collapse
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.
| |
Collapse
|
40
|
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.
Collapse
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
| |
Collapse
|
41
|
Di D, Zhou H, Cui Z, Zhang J, Liu Q, Yuan T, Zhou T, Luo X, Ling D, Wang Q. Early-life tobacco smoke elevating later-life osteoporosis risk: Mediated by telomere length and interplayed with genetic predisposition. J Adv Res 2024:S2090-1232(24)00083-3. [PMID: 38431123 DOI: 10.1016/j.jare.2024.02.021] [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: 12/14/2023] [Revised: 02/11/2024] [Accepted: 02/28/2024] [Indexed: 03/05/2024] Open
Abstract
INTRODUCTION The growing prevalence of osteoporosis (OP) in an aging global population presents a significant public health concern. Tobacco smoke negatively affects bone turnover, leading to reduced bone mass and heightened OP and fracture risk. However, the impact of early-life tobacco smoke exposure on later-life OP risk remains unclear. OBJECTIVES This study was to explore the effects of early-life tobacco smoke exposure on incident OP risk in later life. The mediating role of telomere length (TL) and the interaction with genetic predisposition were also studied. METHODS Data on in utero tobacco smoke exposure (IUTSE) status and age of tobacco use initiation from the UK Biobank were used to estimate early-life tobacco smoke exposure. Incident OP cases were identified according to health-related records. Linear, Cox, and Laplace regression models were mainly used for data analysis. RESULTS Individuals with IUTSE showed a higher OP risk [hazard ratio (HR): 1.06, 95 % confidence interval (CI): 1.01, 1.11] and experienced earlier OP onset by 0.30 years [50th percentile difference = -0.30, 95 % CI: -0.51, -0.09] compared to those without. Participants initiating tobacco smoke in childhood, adolescence, and adulthood had 1.41 times (95 % CI: 1.23, 1.61), 1.17 times (95 % CI:1.10, 1.24), and 1.14 times (95 % CI: 1.07, 1.20) the risk of OP, respectively, compared to never smokers. They also experienced earlier OP onset by 2.16, 0.95, and 0.71 years, sequentially. The TL significantly mediated the early-life tobacco exposure and OP association. Significant joint and interactive effects were detected between early-life tobacco smoke exposure and genetic elements. CONCLUSIONS Our findings implicate that early-life tobacco smoke exposure elevates the later-life OP risk, mediated by telomere length and interplayed with genetic predisposition. These findings highlight the importance of early-life intervention against tobacco smoke exposure and ageing status for precise OP prevention, especially in individuals with a high genetic risk.
Collapse
Affiliation(s)
- Dongsheng Di
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Haolong Zhou
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Zhangbo Cui
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Jianli Zhang
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Qian Liu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Tingting Yuan
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Tingting Zhou
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Xiao Luo
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Danyang Ling
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Qi Wang
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| |
Collapse
|
42
|
Ru Y, Ma M, Zhou X, Kriti D, Cohen N, D’Souza S, Schaniel C, Motch Perrine SM, Kuo S, Pinto D, Housman G, Wu M, Holmes G, Schadt E, van Bakel H, Zhang B, Jabs EW. Transcriptomic landscape of human induced pluripotent stem cell-derived osteogenic differentiation identifies a regulatory role of KLF16. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.11.579844. [PMID: 38405902 PMCID: PMC10888757 DOI: 10.1101/2024.02.11.579844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Osteogenic differentiation is essential for bone development and metabolism, but the underlying gene regulatory networks have not been well investigated. We differentiated mesenchymal stem cells, derived from 20 human induced pluripotent stem cell lines, into preosteoblasts and osteoblasts, and performed systematic RNA-seq analyses of 60 samples for differential gene expression. We noted a highly significant correlation in expression patterns and genomic proximity among transcription factor (TF) and long noncoding RNA (lncRNA) genes. We identified TF-TF regulatory networks, regulatory roles of lncRNAs on their neighboring coding genes for TFs and splicing factors, and differential splicing of TF, lncRNA, and splicing factor genes. TF-TF regulatory and gene co-expression network analyses suggested an inhibitory role of TF KLF16 in osteogenic differentiation. We demonstrate that in vitro overexpression of human KLF16 inhibits osteogenic differentiation and mineralization, and in vivo Klf16+/- mice exhibit increased bone mineral density, trabecular number, and cortical bone area. Thus, our model system highlights the regulatory complexity of osteogenic differentiation and identifies novel osteogenic genes.
Collapse
Affiliation(s)
- Ying Ru
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Meng Ma
- Mount Sinai Genomics, Sema4, Stamford, CT, 06902, USA
| | - Xianxiao Zhou
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Divya Kriti
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ninette Cohen
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Present address: Division of Cytogenetics and Molecular Pathology, Zucker School of Medicine at Hofstra/Northwell, Northwell Health Laboratories, Lake Success, NY, 11030, USA
| | - Sunita D’Souza
- Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Present address: St Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - Christoph Schaniel
- Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Medicine, Division of Hematology and Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mount Sinai Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Susan M. Motch Perrine
- Department of Anthropology, Pennsylvania State University, University Park, PA, 16802, USA
| | - Sharon Kuo
- Department of Anthropology, Pennsylvania State University, University Park, PA, 16802, USA
- Department of Biomedical Sciences, University of Minnesota, Duluth, MN, 55812, USA
| | - Dalila Pinto
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Genevieve Housman
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, 60637, USA
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, 04103, Germany
| | - Meng Wu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN, 55905
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, 55905
| | - Greg Holmes
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Eric Schadt
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Harm van Bakel
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ethylin Wang Jabs
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN, 55905
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, 55905
| |
Collapse
|
43
|
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.
Collapse
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.
| |
Collapse
|
44
|
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.
Collapse
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.
| |
Collapse
|
45
|
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.
Collapse
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.
| |
Collapse
|
46
|
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, 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] [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: 03/07/2023] [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.
Collapse
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.
| |
Collapse
|
47
|
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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [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.
Collapse
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.
| |
Collapse
|
48
|
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.
Collapse
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
| |
Collapse
|
49
|
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: 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: 06/22/2022] [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.
Collapse
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
| | | |
Collapse
|
50
|
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 DOI: 10.1172/jci.insight.175159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [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.
Collapse
Affiliation(s)
| | - Ivana R Shen
- Division of Bone and Mineral Diseases, Department of Medicine, and
| | - Clarissa S Craft
- Division of Bone and Mineral Diseases, Department of Medicine, and
| | - Kristann L Magee
- 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
| |
Collapse
|