Article (Scientific journals)
High-throughput quantification of the mechanical competence of murine femora - A highly automated approach for large-scale genetic studies
Ruffoni, Davide; Kohler, T.; Voide, R. et al.
2013In BONE, 55 (1), p. 216-221
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Keywords :
High-throughput analysis; Micro-finite element; Inbred mouse strains; Mouse femora; Genetics
Abstract :
[en] Animal models are widely used to gain insight into the role of genetics on bone structure and function. One of the main strategies to map the genes regulating specific traits is called quantitative trait loci (QTL) analysis, which generally requires a very large number of animals (often more than 1000) to reach statistical significance. QTL analysis for mechanical traits has been mainly based on experimental mechanical testing, which, in view of the large number of animals, is time consuming. Hence, the goal of the present work was to introduce an automated method for large-scale high-throughput quantification of the mechanical properties of murine femora. Specifically, our aims were, first, to develop and validate an automated method to quantify murine femoral bone stiffness. Second, to test its high-throughput capabilities on murine femora from a large genetic study, more specifically, femora from two growth hormone (GH) deficient inbred strains of mice (B6-lit/lit and C3.B6-lit/lit) and their first (F1) and second (F2) filial offsprings. Automated routines were developed to convert micro-computed tomography (micro-CT) images of femora into micro-finite element (micro-FE) models. The method was experimentally validated on femora from C57BL/6J and C3H/HeJ mice: for both inbred strains the micro-FE models closely matched the experimentally measured bone stiffness when using a single tissue modulus of 13.06 GPa. The mechanical analysis of the entire dataset (n = 1990) took approximately 44 CPU hours on a supercomputer. In conclusion, our approach, in combination with QTL analysis could help to locate genes directly involved in controlling bone mechanical competence. (C) 2013 Elsevier Inc. All rights reserved.
Disciplines :
Endocrinology, metabolism & nutrition
Author, co-author :
Ruffoni, Davide  ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > Mécanique des matériaux biologiques et bioinspirés
Kohler, T.;  Swiss Fed Inst Technol, Inst Biomech, CH-8093 Zurich, Switzerland.
Voide, R.;  Swiss Fed Inst Technol, Inst Biomech, CH-8093 Zurich, Switzerland.
Wirth, A. J.;  Swiss Fed Inst Technol, Inst Biomech, CH-8093 Zurich, Switzerland.
Donahue, L. R.;  Jackson Labs, Bar Harbor, ME USA.
Mueller, R.;  Swiss Fed Inst Technol, Inst Biomech, CH-8093 Zurich, Switzerland.
van Lenthe, G. H.;  Swiss Fed Inst Technol, Inst Biomech, CH-8093 Zurich, Switzerland.
Language :
English
Title :
High-throughput quantification of the mechanical competence of murine femora - A highly automated approach for large-scale genetic studies
Publication date :
2013
Journal title :
BONE
ISSN :
8756-3282
eISSN :
1873-2763
Publisher :
Elsevier Science Inc, New York, United States - New York
Volume :
55
Issue :
1
Pages :
216-221
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
Roche Research Foundation [76-2004]
Swiss National Supercomputing Centre (CSCS, Lugano, Switzerland)
Commentary :
The authors acknowledge the support of the Roche Research Foundation (grant 76-2004) and the Swiss National Supercomputing Centre (CSCS, Lugano, Switzerland).
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