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1,198 results on '"Kocher, T"'

10. 853 HMCN1 variants aggravate epidermolysis bullosa phenotype

Author

Bergson, S., primary, Sarig, O., additional, Nitzan, A., additional, Hainzl, S., additional, Kocher, T., additional, Giladi, M., additional, Illmer, J., additional, Mohamad, J., additional, Geller, E., additional, Malovitski, K., additional, Feller, Y., additional, Kdosha, N. Eretz, additional, Zauner, R., additional, Hofbauer, J. Pinon, additional, Shalom-Feuerstein, R., additional, Wally, V., additional, Koller, U., additional, Zaidel-Bar, R., additional, Samuelov, L., additional, and Sprecher, E., additional

Published
2023
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17. Increased Sphingosine-1-Phosphate Serum Concentrations in Subjects with Periodontitis: A Matter of Inflammation

Author

Moritz E, Jedlitschky G, Negnal J, Tzvetkov MV, Daum G, Dörr M, Felix SB, Völzke H, Nauck M, Schwedhelm E, Meisel P, Kocher T, Rauch BH, and Holtfreter B

Subjects
Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950, sphingosine-1-phosphate – lipid mediator – periodontitis – inflammation
Abstract

Eileen Moritz,1,2,* Gabriele Jedlitschky,1,* Josefine Negnal,1 Mladen V Tzvetkov,1 Günter Daum,3,4 Marcus Dörr,2,5 Stephan B Felix,2,5 Henry Völzke,2,6 Matthias Nauck,2,7 Edzard Schwedhelm,4,8 Peter Meisel,9 Thomas Kocher,9 Bernhard H Rauch,1,2,10,* Birte Holtfreter9,* 1Institute of Pharmacology, Department of General Pharmacology, University Medicine Greifswald, Greifswald, Germany; 2German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany; 3Clinic and Polyclinic for Vascular Medicine, University Heart Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 4German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck, Hamburg, Germany; 5Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany; 6Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; 7Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany; 8Institute of Clinical Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Humburg, Germany; 9Dental Clinics, Department of Periodontology, University Medicine Greifswald, Greifswald, Germany; 10Carl von Ossietzky Universität Oldenburg, Department of Human Medicine, Section of Pharmacology and Toxicology, Oldenburg, Germany*These authors contributed equally to this workCorrespondence: Bernhard H RauchCarl von Ossietzky Universität Oldenburg, Department of Human Medicine, Section of Pharmacology and Toxicology, Carl-von-Ossietzky-Str. 9-11, Oldenburg, 26129, GermanyTel +49 (0) 441 798 4930Fax +49 (0) 441 798 3088Email Bernhard.Rauch@uni-oldenburg.dePurpose: Periodontitis is an inflammatory disease of the oral cavity with an alarmingly high prevalence within the adult population. The signaling lipid sphingosine-1-phosphate (S1P) plays a crucial role in inflammatory and immunomodulatory responses. In addition to cardiovascular disease, sepsis and tumor entities, S1P has been recently identified as both mediator and biomarker in osteoporosis. We hypothesized that S1P may play a role in periodontitis as an inflammation-prone bone destructive disorder. The goal of our study was to evaluate associations between periodontitis and S1P serum concentrations in the Study of Health in Pomerania (SHIP)-Trend cohort. In addition, we investigated the expression of S1P metabolizing enzymes in inflamed gingival tissue.Patients and Methods: We analyzed data from 3371 participants (51.6% women) of the SHIP-Trend cohort. Periodontal parameters and baseline characteristics were assessed. Serum S1P was measured by liquid chromatography tandem mass spectrometry. The expression of S1P metabolizing enzymes was determined by immunofluorescence staining of human gingival tissue.Results: S1P serum concentrations were significantly increased in subjects with both moderate and severe periodontitis, assessed as probing depth and clinical attachment loss. In contrast, no significant association of S1P was seen with caries variables (number and percentage of decayed or filled surfaces). S1P concentrations significantly increased with increasing high-sensitivity C-reactive protein (hs-CRP) levels. Interestingly, inflamed compared to normal human gingival tissue exhibited elevated expression levels of the S1P-generating enzyme sphingosine kinase 1 (SphK1).Conclusion: We report an intriguingly significant association of various periodontal parameters with serum levels of the inflammatory lipid mediator S1P. Our data point towards a key role of S1P during periodontitis pathology. Modulation of local S1P levels or its signaling properties may represent a potential future therapeutic strategy to prevent or to retard periodontitis progression and possibly reduce periodontitis-related tooth loss.Keywords: sphingosine-1-phosphate, lipid mediator, periodontitis, inflammation

Published
2021

19. Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium

Author

Divaris, K., primary, Haworth, S., additional, Shaffer, J.R., additional, Anttonen, V., additional, Beck, J.D., additional, Furuichi, Y., additional, Holtfreter, B., additional, Jönsson, D., additional, Kocher, T., additional, Levy, S.M., additional, Magnusson, P.K.E., additional, McNeil, D.W., additional, Michaëlsson, K., additional, North, K.E., additional, Palotie, U., additional, Papapanou, P.N., additional, Pussinen, P.J., additional, Porteous, D., additional, Reis, K., additional, Salminen, A., additional, Schaefer, A.S., additional, Sudo, T., additional, Sun, Y.Q., additional, Suominen, A.L., additional, Tamahara, T., additional, Weinberg, S.M., additional, Lundberg, P., additional, Marazita, M.L., additional, and Johansson, I., additional

Published
2022
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22. Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium.

Author

Divaris, K, Haworth, S, Shaffer, J R, Anttonen, V, Beck, J D, Furuichi, Y, Holtfreter, B, Jönsson, Daniel, Kocher, T, Levy, S M, Magnusson, P K E, McNeil, D W, Michaëlsson, K, North, K E, Palotie, U, Papapanou, P N, Pussinen, P J, Porteous, D, Reis, K, Salminen, A, Schaefer, A S, Sudo, T, Sun, Y Q, Suominen, A L, Tamahara, T, Weinberg, S M, Lundberg, P, Marazita, M L, Johansson, I, Divaris, K, Haworth, S, Shaffer, J R, Anttonen, V, Beck, J D, Furuichi, Y, Holtfreter, B, Jönsson, Daniel, Kocher, T, Levy, S M, Magnusson, P K E, McNeil, D W, Michaëlsson, K, North, K E, Palotie, U, Papapanou, P N, Pussinen, P J, Porteous, D, Reis, K, Salminen, A, Schaefer, A S, Sudo, T, Sun, Y Q, Suominen, A L, Tamahara, T, Weinberg, S M, Lundberg, P, Marazita, M L, and Johansson, I

Abstract

Genetic risk factors play important roles in the etiology of oral, dental, and craniofacial diseases. Identifying the relevant risk loci and understanding their molecular biology could highlight new prevention and management avenues. Our current understanding of oral health genomics suggests that dental caries and periodontitis are polygenic diseases, and very large sample sizes and informative phenotypic measures are required to discover signals and adequately map associations across the human genome. In this article, we introduce the second wave of the Gene-Lifestyle Interactions and Dental Endpoints consortium (GLIDE2) and discuss relevant data analytics challenges, opportunities, and applications. In this phase, the consortium comprises a diverse, multiethnic sample of over 700,000 participants from 21 studies contributing clinical data on dental caries experience and periodontitis. We outline the methodological challenges of combining data from heterogeneous populations, as well as the data reduction problem in resolving detailed clinical examination records into tractable phenotypes, and describe a strategy that addresses this. Specifically, we propose a 3-tiered phenotyping approach aimed at leveraging both the large sample size in the consortium and the detailed clinical information available in some studies, wherein binary, severity-encompassing, and "precision," data-driven clinical traits are employed. As an illustration of the use of data-driven traits across multiple cohorts, we present an application of dental caries experience data harmonization in 8 participating studies (N = 55,143) using previously developed permanent dentition tooth surface-level dental caries pattern traits. We demonstrate that these clinical patterns are transferable across multiple cohorts, have similar relative contributions within each study, and thus are prime targets for genetic interrogation in the expanded and diverse multiethnic sample of GLIDE2. We anticipate that resul

Published
2022
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23. Phenotype harmonization in the GLIDE2 oral health genomics consortium

Author

Divaris, K. (K.), Haworth, S. (S.), Shaffer, J. (J.R.), Anttonen, V. (V.), Beck, J. (J.D.), Furuichi, Y. (Y.), Holtfreter, B. (B.), Jönsson, D. (D.), Kocher, T. (T.), Levy, S. (S.M.), Magnusson, P. (P.K.E.), McNeil, D. (D.W.), Michaëlsson, K. (K.), North, K. (K.E.), Palotie, U. (U.), Papapanou, P. (P.N.), Pussinen, P. (P.J.), Porteous, D. (D.), Reis, K. (K.), Salminen, A. (A.), Schaefer, A. (A.S.), Sudo, T. (T.), Sun, Y. (Y.Q.), Suominen, A. (A.L.), Tamahara, T. (T.), Weinberg, S. (S.M.), Lundberg, P. (P.), Marazita, M. (M.L.), Johansson, I. (I.), Divaris, K. (K.), Haworth, S. (S.), Shaffer, J. (J.R.), Anttonen, V. (V.), Beck, J. (J.D.), Furuichi, Y. (Y.), Holtfreter, B. (B.), Jönsson, D. (D.), Kocher, T. (T.), Levy, S. (S.M.), Magnusson, P. (P.K.E.), McNeil, D. (D.W.), Michaëlsson, K. (K.), North, K. (K.E.), Palotie, U. (U.), Papapanou, P. (P.N.), Pussinen, P. (P.J.), Porteous, D. (D.), Reis, K. (K.), Salminen, A. (A.), Schaefer, A. (A.S.), Sudo, T. (T.), Sun, Y. (Y.Q.), Suominen, A. (A.L.), Tamahara, T. (T.), Weinberg, S. (S.M.), Lundberg, P. (P.), Marazita, M. (M.L.), and Johansson, I. (I.)

Abstract

Genetic risk factors play important roles in the etiology of oral, dental, and craniofacial diseases. Identifying the relevant risk loci and understanding their molecular biology could highlight new prevention and management avenues. Our current understanding of oral health genomics suggests that dental caries and periodontitis are polygenic diseases, and very large sample sizes and informative phenotypic measures are required to discover signals and adequately map associations across the human genome. In this article, we introduce the second wave of the Gene-Lifestyle Interactions and Dental Endpoints consortium (GLIDE2) and discuss relevant data analytics challenges, opportunities, and applications. In this phase, the consortium comprises a diverse, multiethnic sample of over 700,000 participants from 21 studies contributing clinical data on dental caries experience and periodontitis. We outline the methodological challenges of combining data from heterogeneous populations, as well as the data reduction problem in resolving detailed clinical examination records into tractable phenotypes, and describe a strategy that addresses this. Specifically, we propose a 3-tiered phenotyping approach aimed at leveraging both the large sample size in the consortium and the detailed clinical information available in some studies, wherein binary, severity-encompassing, and “precision,” data-driven clinical traits are employed. As an illustration of the use of data-driven traits across multiple cohorts, we present an application of dental caries experience data harmonization in 8 participating studies (N = 55,143) using previously developed permanent dentition tooth surface–level dental caries pattern traits. We demonstrate that these clinical patterns are transferable across multiple cohorts, have similar relative contributions within each study, and thus are prime targets for genetic interrogation in the expanded and diverse multiethnic sample of GLIDE2. We anticipate t

Published
2022

24. sj-docx-1-jdr-10.1177_00220345221129807 – Supplemental material for Development and External Validation of a Multivariable Prediction Model to Identify Nondiabetic Hyperglycemia and Undiagnosed Type 2 Diabetes: Diabetes Risk Assessment in Dentistry Score (DDS)

Author

Yonel, Z., Kocher, T., Chapple, I.L.C., Dietrich, T., Völzke, H., Nauck, M., Collins, G., Gray, L.J., and Holtfreter, B.

Subjects
110599 Dentistry not elsewhere classified, FOS: Materials engineering, FOS: Clinical medicine, 91299 Materials Engineering not elsewhere classified
Abstract

Supplemental material, sj-docx-1-jdr-10.1177_00220345221129807 for Development and External Validation of a Multivariable Prediction Model to Identify Nondiabetic Hyperglycemia and Undiagnosed Type 2 Diabetes: Diabetes Risk Assessment in Dentistry Score (DDS) by Z. Yonel, T. Kocher, I.L.C. Chapple, T. Dietrich, H. Völzke, M. Nauck, G. Collins, L.J. Gray and B. Holtfreter in Journal of Dental Research

Published
2022
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25. sj-docx-1-jdr-10.1177_00220345221109775 – Supplemental material for Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium

Author

Divaris, K., Haworth, S., Shaffer, J.R., Anttonen, V., Beck, J.D., Furuichi, Y., Holtfreter, B., Jönsson, D., Kocher, T., Levy, S.M., Magnusson, P.K.E., McNeil, D.W., Michaëlsson, K., North, K.E., Palotie, U., Papapanou, P.N., Pussinen, P.J., Porteous, D., Reis, K., Salminen, A., Schaefer, A.S., Sudo, T., Sun, Y.Q., Suominen, A.L., Tamahara, T., Weinberg, S.M., Lundberg, P., Marazita, M.L., and Johansson, I.

Subjects
110599 Dentistry not elsewhere classified, FOS: Materials engineering, FOS: Clinical medicine, 91299 Materials Engineering not elsewhere classified
Abstract

Supplemental material, sj-docx-1-jdr-10.1177_00220345221109775 for Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium by K. Divaris, S. Haworth, J.R. Shaffer, V. Anttonen, J.D. Beck, Y. Furuichi, B. Holtfreter, D. Jönsson, T. Kocher, S.M. Levy, P.K.E. Magnusson, D.W. McNeil, K. Michaëlsson, K.E. North, U. Palotie, P.N. Papapanou, P.J. Pussinen, D. Porteous, K. Reis, A. Salminen, A.S. Schaefer, T. Sudo, Y.Q. Sun, A.L. Suominen, T. Tamahara, S.M. Weinberg, P. Lundberg, M.L. Marazita and I. Johansson in Journal of Dental Research

Published
2022
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27. Development and External Validation of a Multivariable Prediction Model to Identify Nondiabetic Hyperglycemia and Undiagnosed Type 2 Diabetes: Diabetes Risk Assessment in Dentistry Score (DDS).

Author

Yonel, Z., Kocher, T., Chapple, I.L.C., Dietrich, T., Völzke, H., Nauck, M., Collins, G., Gray, L.J., and Holtfreter, B.

Subjects
PERIODONTITIS, PREDIABETIC state, HYPERGLYCEMIA, TYPE 2 diabetes
Abstract

The aim of this study was to develop and externally validate a score for use in dental settings to identify those at risk of undiagnosed nondiabetic hyperglycemia (NDH) or type 2 diabetes (T2D). The Studies of Health in Pomerania (SHIP) project comprises 2 representative population-based cohort studies conducted in northeast Germany. SHIP-TREND-0, 2008 to 2012 (the development data set) had 3,339 eligible participants, with 329 having undiagnosed NDH or T2D. Missing data were replaced using multiple imputation. Potential covariates were selected for inclusion in the model using backward elimination. Heuristic shrinkage was used to reduce overfitting, and the final model was adjusted for optimism. We report the full model and a simplified paper-based point-score system. External validation of the model and score employed an independent data set comprising 2,359 participants with 357 events. Predictive performance, discrimination, calibration, and clinical utility were assessed. The final model included age, sex, body mass index, smoking status, first-degree relative with diabetes, presence of a dental prosthesis, presence of mobile teeth, history of periodontal treatment, and probing pocket depths ≥5 mm as well as prespecified interaction terms. In SHIP-TREND-0, the model area under the curve (AUC) was 0.72 (95% confidence interval [CI] 0.69, 0.75), calibration in the large was −0.025. The point score AUC was 0.69 (95% CI 0.65, 0.72), with sensitivity of 77.0 (95% CI 76.8, 77.2), specificity of 51.5 (95% CI 51.4, 51.7), negative predictive value of 94.5 (95% CI 94.5, 94.6), and positive predictive value of 17.0 (95% CI 17.0, 17.1). External validation of the point score gave an AUC of 0.69 (95% CI 0.66, 0.71), sensitivity of 79.2 (95% CI 79.0, 79.4), specificity of 49.9 (95% CI 49.8, 50.00), negative predictive value 91.5 (95% CI 91.5, 91.6), and positive predictive value of 25.9 (95% CI 25.8, 26.0). A validated prediction model involving dental variables can identify NDH or undiagnosed T2DM. Further studies are required to validate the model for different European populations. [ABSTRACT FROM AUTHOR]

Published
2023
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30. Association of heat shock proteins with all-cause mortality

Author

Broer, L., Demerath, E. W., Garcia, M. E., Homuth, G., Kaplan, R. C., Lunetta, K. L., Tanaka, T., Tranah, G. J., Walter, S., Arnold, A. M., Atzmon, G., Harris, T. B., Hoffmann, W., Karasik, D., Kiel, D. P., Kocher, T., Launer, L. J., Lohman, K. K., Rotter, J. I., Tiemeier, H., Uitterlinden, A. G., Wallaschofski, H., Bandinelli, S., Dörr, M., Ferrucci, L., Franceschini, N., Gudnason, V., Hofman, A., Liu, Y., Murabito, J. M., Newman, A. B., Oostra, B. A., Psaty, B. M., Smith, A. V., and van Duijn, C. M.

Published
2013
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36. Design und Qualitätskontrolle der zahnmedizinischen Untersuchung in der NAKO Gesundheitsstudie [Design and quality control of the oral health status examination in the German National Cohort (GNC)]

Author

Holtfreter, B., Samietz, S., Hertrampf, K., Aarabi, G., Hagenfeld, D., Kim, T.S., Kocher, T., Koos, B., Schmitter, M., Ahrens, W., Alwers, E., Becher, H., Berger, K., Brenner, H., Damms-Machado, A., Ebert, N., Fischer, B., Franzke, C.W., Frölich, S., Greiser, H., Gies, A., Günther, K., Hassan, L., Hoffmann, W., Jaeschke, L., Keil, T., Kemmling, Y., Krause, G., Krist, L., Legath, N., Lieb, W., Leitzmann, M., Linseisen, J., Loeffler, M., Meinke-Franze, C., Michels, K.B., Mikolajczyk, R., Obi, N., Peters, A., Pischon, T., Schipf, S., Schmidt, B., Völzke, H., Waniek, S., Wigmann, C., Wirkner, K., Schmidt, C.O., Kühnisch, J., and Rupf, S.

Subjects
stomatognathic diseases, Cardiovascular and Metabolic Diseases
Abstract

BACKGROUND: Caries and periodontitis are highly prevalent worldwide. Because detailed data on these oral diseases were collected within the framework of the German National Cohort (GNC), associations between oral and systemic diseases and conditions can be investigated. OBJECTIVES: The study protocol for the oral examination was designed to ensure a comprehensive collection of dental findings by trained non-dental staff within a limited examination time. At the mid-term of the GNC baseline examination, a first quality evaluation was performed to check the plausibility of results and to propose measures to improve the data quality. MATERIALS AND METHODS: A dental interview, saliva sampling and oral diagnostics were conducted. As part of the level‑1 examination, the number of teeth and prostheses were recorded. As part of the level‑2 examination, detailed periodontal, cariological and functional aspects were examined. All examinations were conducted by trained non-dental personnel. Parameters were checked for plausibility and variable distributions were descriptively analysed. RESULTS: Analyses included data of 57,967 interview participants, 56,913 level‑1 participants and 6295 level‑2 participants. Percentages of missing values for individual clinical parameters assessed in level 1 and level 2 ranged between 0.02 and 3.9%. Results showed a plausible distribution of the data; rarely, implausible values were observed, e.g. for measurements of horizontal and vertical overbite (overjet and overbite). Intra-class correlation coefficients indicated differences in individual parameters between regional clusters, study centres and across different examiners. CONCLUSIONS: he results confirm the feasibility of the study protocol by non-dental personnel and its successful integration into the GNC's overall assessment program. However, rigorous dental support of the study centres is required for quality management.

Published
2020

37. Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women

Author

Jones, G. (Garan), Trajanoska, K. (Katerina), Santanasto, A.J. (Adam J.), Stringa, N. (Najada), Kuo, C.-L. (Chia-Ling), Atkins, J.L. (Janice L.), Lewis, J.R. (Joshua), Duong, T.V. (ThuyVy), Hong, S. (Shengjun), Biggs, M.L. (M.), Luan, J. (Jian’an), Sarnowski, C., Lunetta, K.L. (Kathryn), Tanaka, T. (Toshiko), Wojczynski, M.K. (Mary ), Cvejkus, R. (Ryan), Nethander, M. (Maria), Ghasemi, S. (Sahar), Yang, J. (Jingyun), Zillikens, M.C. (Carola), Walter, S. (Stefan), Sicinski, K. (Kamil), Kague, E. (Erika), Ackert-Bicknell, C.L. (Cheryl L.), Arking, D.E. (Dan E.), Windham, B.G. (Gwen), Boerwinkle, E.A. (Eric), Grove, M.L. (Megan L.), Graff, M. (Misa), Spira, D. (Dominik), Demuth, I. (Ilja), Velde, N. (Nathalie) van der, de Groot, L.C.P.G.M. (Lisette C. P. G. M.), Psaty, B.M. (Bruce M.), Odden, M.C. (Michelle C.), Fohner, A.E. (Alison E.), Langenberg, C. (Claudia), Wareham, N.J. (Nick), Bandinelli, S. (Stefania), Schoor, N.M. (Natasja) van, Huisman, M. (Martijn), Tan, Q. (Qihua), Zmuda, J. (Joseph), Mellström, D. (Dan), Karlsson, M. (Magnus), Bennett, D.A. (David), Buchman, A.S. (Aron S.), De Jager, P., Uitterlinden, A.G. (Andre G.), Völker, U. (Uwe), Kocher, T. (Thomas), Teumer, A. (Alexander), Rodríguez-Mañas, L. (Leocadio), García, F.J. (Francisco J.), Carnicero, J.A. (José A.), Herd, P. (Pamela), Bertram, L. (Lars), Ohlsson, C. (Claes), Murabito, J. (Joanne), Melzer, D. (David), Kuchel, G.A. (George A.), Ferrucci, L. (Luigi), Karasik, D. (David), Rivadeneira Ramirez, F. (Fernando), Kiel, D.P. (Douglas P.), Pilling, L.C. (Luke C.), Jones, G. (Garan), Trajanoska, K. (Katerina), Santanasto, A.J. (Adam J.), Stringa, N. (Najada), Kuo, C.-L. (Chia-Ling), Atkins, J.L. (Janice L.), Lewis, J.R. (Joshua), Duong, T.V. (ThuyVy), Hong, S. (Shengjun), Biggs, M.L. (M.), Luan, J. (Jian’an), Sarnowski, C., Lunetta, K.L. (Kathryn), Tanaka, T. (Toshiko), Wojczynski, M.K. (Mary ), Cvejkus, R. (Ryan), Nethander, M. (Maria), Ghasemi, S. (Sahar), Yang, J. (Jingyun), Zillikens, M.C. (Carola), Walter, S. (Stefan), Sicinski, K. (Kamil), Kague, E. (Erika), Ackert-Bicknell, C.L. (Cheryl L.), Arking, D.E. (Dan E.), Windham, B.G. (Gwen), Boerwinkle, E.A. (Eric), Grove, M.L. (Megan L.), Graff, M. (Misa), Spira, D. (Dominik), Demuth, I. (Ilja), Velde, N. (Nathalie) van der, de Groot, L.C.P.G.M. (Lisette C. P. G. M.), Psaty, B.M. (Bruce M.), Odden, M.C. (Michelle C.), Fohner, A.E. (Alison E.), Langenberg, C. (Claudia), Wareham, N.J. (Nick), Bandinelli, S. (Stefania), Schoor, N.M. (Natasja) van, Huisman, M. (Martijn), Tan, Q. (Qihua), Zmuda, J. (Joseph), Mellström, D. (Dan), Karlsson, M. (Magnus), Bennett, D.A. (David), Buchman, A.S. (Aron S.), De Jager, P., Uitterlinden, A.G. (Andre G.), Völker, U. (Uwe), Kocher, T. (Thomas), Teumer, A. (Alexander), Rodríguez-Mañas, L. (Leocadio), García, F.J. (Francisco J.), Carnicero, J.A. (José A.), Herd, P. (Pamela), Bertram, L. (Lars), Ohlsson, C. (Claes), Murabito, J. (Joanne), Melzer, D. (David), Kuchel, G.A. (George A.), Ferrucci, L. (Luigi), Karasik, D. (David), Rivadeneira Ramirez, F. (Fernando), Kiel, D.P. (Douglas P.), and Pilling, L.C. (Luke C.)

Abstract

Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1p = 4 × 10−17), arthritis (GDF5p = 4 × 10−13), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing.

Published
2021
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38. Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women

Author

Jones, G, Trajanoska, Katerina, Santanasto, AJ, Stringa, Najada, Kuo, CL, Atkins, JL, Lewis, JR, Duong, TV, Hong, S, Biggs, ML, Luan, J, Sarnowski, C, Lunetta, KL, Tanaka, T, Wojczynski, MK, Cvejkus, R, Nethander, M, Ghasemi, S, Yang, J, Zillikens, M.C., Walter, S, Sicinski, K, Kague, E, Ackert-Bicknell, CL, Arking, DE, Windham, BG, Boerwinkle, E, Grove, ML, Graff, M, Spira, D, Demuth, I, Velde, N, de Groot, LCPCM, Psaty, BM, Odden, MC, Fohner, AE, Langenberg, C, Wareham, NJ, Bandinelli, S, Schoor, NM, Huisman, M, Tan, Q, Zmuda, J, Mellström, D, Karlsson, M, Bennett, DA, Buchman, AS, De Jager, PL, Uitterlinden, André, Völker, U, Kocher, T, Teumer, A, Rodriguéz-Mañas, L, García, FJ, Carnicero, JA, Herd, P, Bertram, L, Ohlsson, C, Murabito, JM, Melzer, D, Kuchel, GA, Ferrucci, L, Karasik, D, Rivadeneira, Fernando, Kiel, DP, Pilling, LC, Jones, G, Trajanoska, Katerina, Santanasto, AJ, Stringa, Najada, Kuo, CL, Atkins, JL, Lewis, JR, Duong, TV, Hong, S, Biggs, ML, Luan, J, Sarnowski, C, Lunetta, KL, Tanaka, T, Wojczynski, MK, Cvejkus, R, Nethander, M, Ghasemi, S, Yang, J, Zillikens, M.C., Walter, S, Sicinski, K, Kague, E, Ackert-Bicknell, CL, Arking, DE, Windham, BG, Boerwinkle, E, Grove, ML, Graff, M, Spira, D, Demuth, I, Velde, N, de Groot, LCPCM, Psaty, BM, Odden, MC, Fohner, AE, Langenberg, C, Wareham, NJ, Bandinelli, S, Schoor, NM, Huisman, M, Tan, Q, Zmuda, J, Mellström, D, Karlsson, M, Bennett, DA, Buchman, AS, De Jager, PL, Uitterlinden, André, Völker, U, Kocher, T, Teumer, A, Rodriguéz-Mañas, L, García, FJ, Carnicero, JA, Herd, P, Bertram, L, Ohlsson, C, Murabito, JM, Melzer, D, Kuchel, GA, Ferrucci, L, Karasik, D, Rivadeneira, Fernando, Kiel, DP, and Pilling, LC

Abstract

Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1p = 4 × 10−17), arthritis (GDF5p = 4 × 10−13), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing.

Published
2021

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