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Physiol. Genomics 22: 390-397, 2005. First published May 24, 2005; doi:10.1152/physiolgenomics.00010.2005
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Received 12 January 2005; accepted in final form 17 May 2005.
Physiological Genomics 22:390-397 (2005)
1094-8341/05 $8.00 © 2005 American Physiological Society

Quantitative trait loci for human muscle strength: linkage analysis of myostatin pathway genes

W. Huygens1, M. A. I. Thomis1, M. W. Peeters1, J. Aerssens3,4, R. Vlietinck2,4 and G. P. Beunen1

1 Research Center for Exercise and Health, Faculty of Kinesiology and Rehabilitation Sciences
2 Department of Human Genetics, Faculty of Medicine, Katholieke Universiteit Leuven, Belgium
3 Drug Discovery, Johnson and Johnson Pharmaceutical Research and Development, Beerse, Belgium
4 Department of Population Genetics, Genomics and Bioinformatics, Universiteit Maastricht, Maastricht, The Netherlands


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 GRANTS
 REFERENCES
 
This study reports the results of a multipoint linkage study that aims to unravel the genetic basis of muscle strength and muscle mass in humans. Myostatin (GDF8) is known to be a strong inhibitor of muscle growth in animals. However, studies examining human myostatin polymorphisms are rare and are limited to the GDF8 gene itself. Here, the contribution to isometric and concentric knee strength of nine key proteins involved in the myostatin pathway is studied in a nonparametric multipoint linkage analysis by means of a variance components and regression method. A sample of 367 healthy young male siblings was phenotyped on an isokinetic dynamometer and genotyped for markers of the myostatin pathway genes. Three of the loci were found significantly linked with a quantitative trait locus (QTL) for knee muscle strength. First, D13S1303 showed replication of an explorative single-point linkage study with a maximum LOD score of 2.7 (P = 0.0002). Second, maximum LOD scores of 3.4 (P = 0.00004) and 3.3 (P = 0.00005) were observed for markers D12S1042 and D12S85, respectively, at 12q12–14. Finally, marker D12S78 showed an LOD score of 2.7 at 12q22–23. We conclude that several genes involved in the myostatin pathway, but not the myostatin gene itself, are important QTLs for human muscle strength. An additional set of valuable candidate genes that were not part of the myostatin pathway was found in the chromosome 12 and 13 genomic regions.

complex trait; candidate genes; retinoblastoma; CDK2; multipoint linkage


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 GRANTS
 REFERENCES
 
IT HAS BEEN WELL ESTABLISHED that myostatin, or growth and differentiation factor-8 (GDF8), a member of the transforming growth factor-ß superfamily, is a negative regulator of muscle mass in animals. Mice lacking functional myostatin show a two- to threefold increase in muscle mass (29), and Belgian Blue and Piedmontese breeds of cattle with GDF8 mutations are characterized by the "double-muscling" phenotype (15, 25, 28). Recently, a few studies blocking myostatin with antibodies in adult mice showed an increase in muscle growth and strength and a reduced muscle wasting in dystrophic muscles (6, 42, 43), which makes the myostatin pathway an interesting pharmacological target. However, studies showing the same function in humans are sparse. People suffering from chronic disuse muscle atrophy (32) and human immunodeficiency virus (HIV)-infected patients (14) all show increased levels of myostatin expression in muscle tissue. In addition, three studies investigated the possible association between myostatin polymorphisms and human muscle strength (11, 24, 37), and they suggest a potential role for myostatin in humans despite the lack of significant associations. Recently, Roth et al. (34) reported decreased myostatin gene expression in humans after a 9-wk strength training program, albeit not significant. Probably, statistical significance was not reached due to the lack of power (7 men, 8 women). The most convincing evidence, however, for a functional role of myostatin in humans was recently reported by Schuelke et al. (36). They identified a homozygous mutation in the myostatin gene (g.IVS1+5 g->a) that dramatically affects muscle mass and strength in a child.

A search for genes coding for muscle strength is justified, because in twin and family studies the genetic determination (h2) of strength, often determined by field tests, varied between 30 and 90% (27, 31, 40). Isokinetic knee-strength parameters show upper-limit h2 between 63 and 86% (23). However, muscle strength is a complex multifactorial trait, and high heritabilities do not guarantee the presence of a quantitative trait locus (QTL) with large effect size, although it increases the probability of finding one.

To clarify the inconclusive role of myostatin and other key proteins of the myostatin pathway in humans, an explorative single-point linkage analysis was performed in an earlier study (21). The investigated pathway and its role in proliferation and differentiation of muscle fibers are given in detail elsewhere (21, 26, 39). Results from this single-point linkage exploration with a single microsatellite marker per candidate gene revealed that the chromosomal regions harboring GDF8, CDKN1A, MYOD1, and RB1 are potentially interesting regions for further genetic studies (P values varying between 0.05 and 0.0002). Strengthened by these preliminary single-point linkage results and the physiological evidence for the entire pathway, we performed a multipoint linkage analysis on another larger sample for the following genetic regions: myostatin (GDF8); the muscle regulatory factors MyoD (MYOD1), Myf5 (MYF5), and Myf6 (MYF6); p21 (CDKN1A); retinoblastoma (RB1); insulin-like growth factor-1 (IGF1); cyclin-dependent kinase-2 (CDK2); and titin (TTN).


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 APPENDIX
 GRANTS
 REFERENCES
 
Subjects
The sample comprises 367 male siblings of 145 Caucasian families and was composed of 82 pairs, 49 trios, and 14 quads resulting in a maximal number of 313 pairwise comparisons. These young male adults (17–36 yr) were recruited via advertisements in local and national media in the region of Flanders, Belgium, and participated on a voluntary basis after reading and signing a written informed consent. For this study, the subjects were not randomly chosen from the larger Leuven Genes for Muscular Strength project (LGfMS; n = 748) as in the single-point analysis (21), but they were selected based on family size (all trios and quads for in total 203 subjects). The remaining 82 pairs were chosen based on the highest ranked expected contribution to an LOD score of a QTL of 20% (ELOD20 score). This is a theoretical score based on phenotypic values that provides an estimate of the linkage informativeness of each family (2). This selection scheme resulted in the most informative sample possible for this sample size, with an overlap of 36% of the subjects with the single-point study (21). Although no selection was made on physical activity or physical fitness level, it cannot be ruled out that the subjects were more active than average, since they volunteered in a strength test study. To control for this possible environmental confounding factor, the Baecke physical activity questionnaire (4) was filled out by all sibling pairs. This study was approved by the medical and ethical committee of the Katholieke Universiteit Leuven.

Measurements
Muscle mass.
Fat-free mass (FFM) was estimated by the Durnin and Womersley equation (9), for which body weight and skin folds of triceps, biceps, suprailiac, and subscapula were measured. Cross-sectional area of thigh was calculated by means of midthigh circumference corrected for subcutaneous fat at this location, resulting in an estimate of muscle and bone cross-sectional area (MBA). Measurements were taken by experienced anthropometrists and are described in more detail elsewhere (20). The body mass index (BMI) is the ratio of total body weight over stature (kg/m2) and is widely used as an indication of overweight and obesity.

Strength measurements.
In epidemiological studies, muscle strength is often determined by simple field tests like handgrip or jump tests. However, accuracy and validity of these measurements might be suboptimal, and the preferable measurement would be strength tests on isokinetic dynamometers. Consequently, a test must be chosen that 1) involves activation of a large muscle group, 2) requires no specific motor skills so that it is applicable even for sedentary people, and 3) can be highly standardized. Knee flexion and extension strength tests on a Cybex NORM dynamometer (Lumex, Ronkomkoma, NY) meet these criteria.

After a 5- to 10-min warm-up on an ergometer cycle and light stretching exercises, subjects were positioned onto the dynamometer according to the instructions of the manufacturer. Anatomical zero was set at full extension of the knee, and the rotation axis of the joint was aligned with the mechanical axis of the dynamometer. Two isometric and four concentric trials preceded the actual tests, for familiarization with the testing procedure (angle, range of motion, or velocity). Maximal isometric knee strength was measured at two angles (30° and 60°). At each angle, highest torque values (Nm) during a 6-s isometric contraction of three maximal flexion and extension contractions were retained for further analysis. Thirty seconds of rest between each contraction were given. Peak torque over the complete range of motion (0–90°) of concentric knee extension and flexion was measured at 60°/s (3 repetitions), at 120°/s (25 repetitions), and at 240°/s (5 repetitions). During these contractions, torque at specific angles was also recorded: following the force-length relationship of a muscle, optimal strength is generated at longer muscle length, i.e., at an angle of 60° for knee extension (quadriceps) and 30° for knee flexion (hamstring). Furthermore, total work (J) was measured at each velocity. Subjects were verbally encouraged to perform at their maximum effort, and visual feedback of their performance was presented after each test.

Microsatellite genotyping.
Genotyping was performed on DNA extracted from EDTA whole blood by a salting out procedure. Twenty-nine microsatellite markers were chosen in regions of the genes GDF8, CDKN1A, MYOD1, MYF5, MYF6, IGF1, RB1, CDK2, and TTN. Compared with the initial single-point linkage study (21), these latter two genes (CDK2 and TTN) were added, as they were positioned in relative proximity to some initial myostatin pathway genes and because they have an important role in muscle mass regulation. In contrast, TCAP, MYOG, and MADH3 did not show any evidence for linkage with any strength phenotype in the earlier single-point study and were therefore withdrawn from these follow-up multipoint linkage analyses. Linkage analysis on these 29 markers showed increases in LOD scores for markers on both ends of the candidate region on chromosome 12, but a peak LOD could not be delineated because of insufficient markers on these sides. Therefore, an additional set of 10 markers covering a region that was not myostatin pathway related was genotyped to extend the linkage region to delineate the linkage peak. The position of the 39 markers and the genes is given in Table 1, and the additional markers are highlighted in bold. Genetic marker positions (in Kosambi cM) were obtained from Marshfield Center for Medical Genetics (7), and physical location of the genes was obtained from the human University of California-Santa Cruz (UCSC) Genome Browser (UCSC version hg16, July 2003), which is based on National Center for Biotechnology Information build no. 34. Average marker spacing in the candidate regions was 4.65 cM (range 1.64–12.12 cM). Heterozygosity of the markers varied between 47.9 and 92% (Table 1).


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  		Table 1. Marker specifications

 
Fluorescently labeled primers were purchased from Applied Biosystems, and PCR amplification was done by a Dyad thermal cycler at standardized conditions [58°C annealing temperature, 30 cycles (1 min/segment), 5 pmol/primer, and 10 ng of DNA]. The labeled PCR products were size separated by the ABI-3730 genetic analyzer (Applied Biosystems), and allele calling was performed using Genemapper v.3.0 software.

Linkage analyses.
Merlin v.0.10.2 software (2) was used for analyzing sibling pair data with two statistical multipoint nonparametric linkage methods: first, by applying the variance components method (VC option in Merlin), which is based on maximum-likelihood estimations (3), and second, by the revised Haseman-Elston regression method outlined by Sham et al. (38) (REG; Merlin-regress option). This latter method requires specification of trait heritability, population means, and variance, which were derived using the QTDT program (1). Despite the fact that only 39 markers were tested for physiological candidate genes rather than ±400 markers near anonymous genes in a total genome scan, we applied stringent criteria for the LOD scores, similar to those for a genome-wide linkage scan: an LOD score ≥3 was considered as evidence for linkage, and LOD scores between 1.5 and 3 were considered as suggestive for linkage.

Before statistical analyses, all genotypes were checked for Mendelian inheritance, using the error detection protocol in Merlin. Unlikely genotypes were verified with the lab data, corrected when possible, or else removed.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 APPENDIX
 GRANTS
 REFERENCES
 
Table 2 gives the main somatic characteristics (mean ± SD) and muscle strength statistics of the 367 siblings with corresponding upper-limit heritabilities estimated on the total LGfMS sample (n = 748). Subjects were rather lean, with a mean BMI of 23.1 ± 3.0 kg/m2, a mean FFM of 63.5 ± 7.3 kg, and a mean total body weight of 74.6 ± 11 kg. Strength measures were highly heritable (48–91%) and showed the expected force-velocity relationship [torques at 240° are not shown; the decrease in peak torque from isometric strength (0°/s) to 240°/s was 45 and 55% for knee flexion and extension, respectively].


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  		Table 2. Somatic characteristics and strength statistics (n = 367)

 
Four candidate genes (CDK2, MYF5, MYF6, and IGF1) from the myostatin pathway were located on chromosome 12 in a region of ~50 cM, and an initial linkage analysis was performed with eight markers. Unfortunately, the LOD curve increased toward the two ends of the region (near CDK2 and IGF1) and showed no linkage in the middle (MYF5/6). These increases were modest to high (maximum LOD was 2.2 for CDK2 and 3.1 for IGF1) but consistent over different-strength phenotypes. Therefore, an additional set of 10 microsatellite markers was genotyped for delineation of the LOD peak. Figure 1 shows an example of the LOD curves with indication of all markers, marker distances, and location of the candidate genes on chromosome 12. Figure 2 shows the linkage results for other strength phenotypes, but for reasons of clarity of the figures, indication of markers and genes is omitted. Highest LOD scores were found at the centromeric end of the region (CDK2), with total work at 120°/s flexion, total work at 60°/s extension, torque at 60° at 120°/s flexion, and peak torque at 120°/s flexion (LODs 3.4, 3.3, 2.9, and 2.7, respectively). At the telomeric end of the candidate region (IGF1) on chromosome 12, a maximum LOD peak of 2.6 was observed for the isometric strength at 30° flexion. Although this peak was present in some other phenotypes (Fig. 2), it did not exceed the suggestive linkage level. In general, the linkage findings were higher for flexion than for extension and for the lower contraction velocities (60°/s and 120°/s).



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  		Fig. 1. Detailed multipoint LOD score pattern on chromosome 12. Multipoint linkage results for chromosome 12q12-q23 based on 18 microsatellite markers. The bottom x-axis depicts the marker positions in cM, and the top x-axis depicts the location of the markers with the additional markers highlighted in bold. Schematic position of candidate genes for muscle strength is indicated by arrows. The y-axis depicts the LOD score. Thick line represents results from the regression analysis (REG; Ref. 38), and thin line represents results from the variance components analysis (VC; Ref. 2).

 


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  		Fig. 2. Multipoint LOD score pattern on chromosome 12. Multipoint linkage results for chromosome 12q12-q23 based on 18 microsatellite markers for different knee strength phenotypes. The x-axis depicts the marker positions in cM, and the y-axis depicts the LOD scores. Thick line is REG analysis, and thin line is VC analysis. For position of specific markers and candidate genes, see Fig. 1.

 
Multipoint LOD scores of variance components and regression linkage analyses for the 13q14.2 region are displayed in Fig. 3. The region around RB1 revealed a pattern of significant LOD scores, both for knee flexion and extension. A peak over ~10 cM was observed at slow and intermediate velocities (60°/s and 120°/s). Highest LOD score was found for torque measured at 60° during knee extension at 60°/s (LOD = 2.74, P = 0.0002) with D13S1303 at 47 cM (Fig. 3). At 120°/s this peak was somewhat lower (1.48, P = 0.004) and shifted toward D13S153 (46 cM). For the intermediate velocity of knee flexion (120°/s), evidence for suggestive linkage with 13q14.2 was found. Despite the fact that the maximum LOD scores remain suggestive, the recurrent patterns for peak torque, total work, and torque at 60° at 120°/s confirmed the possible presence of a QTL for muscle strength at the 13q14.2 region.



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  		Fig. 3. Multipoint LOD score pattern on chromosome 13. Multipoint linkage results for chromosome 13q14 based on 5 microsatellite markers. The bottom x-axis depicts the marker positions in cM, and the top x-axis depicts the location of the markers. Schematic position of interesting candidate genes for muscle strength is indicated by arrows. The y-axis depicts the LOD score. Thick line is REG analysis, and thin line is VC analysis.

 
In addition, Figs. 1–3 clearly show that variance components linkage analysis and the regression method from Sham et al. (38) revealed virtually identical LOD score estimates for the lower LOD scores, but the difference between the two methods increased with increasing LOD estimates (with the regression method resulting in higher LOD scores).

Although myostatin was the candidate gene on which this pathway and linkage study was built, we did not find convincing evidence for linkage with knee flexion/extension or muscle mass and the myostatin gene region. Isometric knee flexion at 30° reached the highest P value of 0.009 (LOD = 1.195), and most strength phenotypes showed a trend of a modest peak. Also, none of the muscle mass phenotypes, which have the strongest physiological link with myostatin, showed any evidence for linkage (P > 0.02).

Similar to the linkage findings on chromosome 12, torques measured at the highest velocity (240°/s) did not show any indication of linkage with any of the candidate genes. Furthermore, 12q and 13q were the only two of the selected regions that showed a consistent linkage pattern with muscle strength. None of the strength or mass phenotypes showed linkage with markers on chromosome 6 (CDKN1A) or 11 (MYOD1). Muscle mass, as determined by circumference of the midthigh, the total thigh muscle and bone cross-sectional area, and the cross-sectional area of the quadriceps all showed identical modest LOD scores with D12S1632 (LOD 1.15, 1.24, and 1.17, respectively), which is the marker 3 Mb from CDK2.

Variation in physical activity and other environmental factors might also contribute to the observed variability in muscle strength and mass. Therefore, a physical activity questionnaire, taking into account work, leisure, and sport activities (4), was taken from all subjects. However, no significant correlation was found for the sports index score with muscle strength or mass (23). Stepwise regression and multiple R2 analyses were performed, and the physical activity index as determined by the Baecke questionnaire did not contribute to the variability in muscle strength. Consequently, physical activity as determined by the Baecke questionnaire was not used as a covariable in this linkage study.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
APPENDIX
 GRANTS
 REFERENCES
 
The Leuven Genes for Muscular Strength Study is the first to search for QTLs for muscle strength in humans in a linkage framework and the first that used genes from the myostatin pathway as candidate genes. Dissecting the genetic basis of muscle mass and function contributes not only to the general knowledge of the trait but can also help in understanding pathological conditions. The underlying mechanisms of skeletal muscle function and development are not yet fully understood, and nonpathological variation in muscle strength has an important link with public health care, more specifically with aging, disuse atrophy, and sarcopenia (33, 35). The mode of inheritance is, however, complex, and the interaction with the environment, such as physical activity and nutrition, is obvious but not easily quantifiable.

In this study, nine candidate genes selected from the myostatin pathway were analyzed, resulting in three interesting regions showing significant or suggestive linkage with knee muscle strength, accurately measured with several tests on an isokinetic dynamometer. The initial candidate genes from the myostatin pathway in 12q13 and 13q14.2 are CDK2 (maximum LOD 3.4, P = 0.00004) and RB1 (maximum LOD 2.74, P = 0.0002), respectively. These genes code for two crucial signaling proteins in the myostatin pathway: CDK2 is responsible for phosphorylation of retinoblastoma and consequently for the proliferation of muscle cells and thus growth (18). Recent studies have shown that Cdk2–/– mice were unexpectedly viable but smaller (5, 30), indicating that functional variations can occur and result in decreased growth. Retinoblastoma plays a pivotal role in the GDF8 pathway, as it is the regulator of the myogenic cell cycle (17, 39). Linkage results from the present study support the previous, preliminary findings of our group (22): in another male sample, a maximal single-point LOD score of 2.78 (P = 0.0002) was found for trunk strength at D13S153. Thus variations in the CDK2 gene may disrupt phosphorylation of retinoblastoma, or variations in RB1 itself can cause improper myoblast proliferation. The third candidate gene that showed suggestive linkage with muscle strength was IGF1 on 12q23, with markers located 1.3 Mb (D12S78) and 7.2 Mb (D12S1645) from IGF1. This is in line with literature reports, evidencing an important role of IGF as a general growth factor (12). Consideration of IGF1 as a potentially important QTL for muscle strength stems from its physiological role in muscle growth, repair, and hypertrophy; however, the limited replication in correlated strength phenotypes in this study hinders us in making a final conclusion regarding the validity of the LOD peak.

It should be noted that the genetic distances used for these linkage analyses were the average of the male and female map of Marshfield. However, because our sample comprised only males, it was of interest to reanalyze our data with the male map distances. The curves were, as expected, similar although some LOD scores were increased. For example, maximum LOD for total work at 60°/s extension increased from 3.3 to 3.6 (P = 0.00002, D12S85) for the revised regression method, reaching even genome-wide linkage significance. These additional results are shown as Supplemental Material (available at the Physiological Genomics web site).1

Despite the fact that two powerful statistical linkage methods were used for this particular study (10), no evidence for linkage was found for markers in the vicinity of the myostatin gene (GDF8). Probably, the limited variation in the human GDF8 gene cannot account for the variability in muscle strength or mass in the same way as in animals. Ferrell et al. (11) reported five variants in the coding region of the human GDF8 gene, but only K153R and A55T appeared polymorphic in a Caucasian and African American population. However, they did not find a significant association with training effects in muscle mass. Similarly, in a case control study, we genotyped 57 male strength athletes and 57 control subjects for the myostatin variants described in Ferrell et al., for which only one individual in each group was found heterozygous for the K153R polymorphism (41). Although it appears unlikely that rare variants with a large phenotypic effect might account for the overall variation of muscle strength in the human population, a recent case report has demonstrated the important role of myostatin in muscle mass regulation in humans: a rare homozygous myostatin mutation (g.IVS1+5 g->a) was found in an extremely muscular and strong child. The heterozygote carrier mother was a former professional athlete (36).

This study is the second to investigate genes from the myostatin pathway as candidate genes for human muscularity. This, however, does not mean that these candidate genes are the only valuable candidate genes in their region. Significant linkage findings can also be caused by neighboring genes. Therefore, these regions should be screened for other potential candidate genes. Several interesting muscle-associated genes are located within a region of 8 Mb around CDK2 on 12q12–14: GDF11 (which belongs to the same family as GDF8), myosin light chain-1 slow-twitch muscle A isoform (MCL1SA), myosin light chain polypeptide-6 (MYL6), integrin-{alpha}7 [ITGA7, which is associated with congenital myopathy (19) and muscular dystrophy (8)], vitamin D receptor [VDR, which is associated with muscle strength (13)], and IGF binding protein-6 (IGFBP6).

Interestingly, VDR interaction protein (VDRIP) is located more to the centromeric side of RB1 (~210 kb from RB1) on 13q14.2. Because polymorphisms in the VDR gene (located within the chromosome 12 LOD peak region) have shown significant association with muscle strength in case control designs (13, 16), its interaction protein also seems a valuable candidate gene. Finally, at 12q22–12q23.2 in the region of IGF1, the slow type of myosin binding protein C (MYBPC1) is located 1.5 Mb apart from IGF1 and is highly expressed in skeletal muscle, as it is involved in muscle contraction. The LOD peak at chromosome 12q22–23 was found with isometric strength, which makes MYBPC1 also a good candidate gene.

Because, to the best of our knowledge, no other linkage studies for muscle strength have been undertaken, comparison can only be made with results of our explorative single-point linkage results (21). That study had a smaller (n = 204 pairs) and less informative sample (randomly selected sibling pairs), the analysis was performed on only one microsatellite marker per candidate gene, and the strength phenotypes under study were corrected for muscle mass by taking the ratio over cross-sectional area of the limb. The present study used the absolute strength values, because it has been shown that the cross-sectional area was not the appropriate measurement to correct for muscularity (23). Nevertheless, retinoblastoma was the only candidate gene that showed significant LOD scores (>2.4) in both studies, and a clear pattern was observed in the multipoint analysis with a peak above RB1 or slightly more telomeric than RB1. The single-point linkage study also indicated GDF8, CDKN1A, and MYOD1 as promising candidate genes, although the current multipoint linkage analysis failed to replicate these findings. Yet, several isometric and slow velocity torques revealed modest LOD scores between 0.5 and 1 with markers near GDF8 and TTN (data not shown). In both samples, MYF5 and MYF6 did not show any significant linkage with muscle strength or muscle mass. On the other hand, in the present study, linkage results for IGF1 increased modestly compared with the single-point linkage analysis, only in a limited set of phenotypes, however. Finally, CDK2 was not tested in the single-point study, so no comparison can be made for this candidate gene.

LOD scores decreased for contractions from 60°/s to 120°/s and became nonsignificant at 240°/s. This trend was observed for all traits and all markers, even for nonsignificant LOD scores. A possible explanation is the nature of slow and fast muscle contractions. It is suggested that fast muscle contraction is optimized by increased sarcomeres in series (length of a muscle), each contracting at high speed, whereas maximized slow and isometric force require highly hypertrophied muscle fibers that have more sarcomeres in parallel (cross-sectional area of a muscle). Because myostatin in animals is associated with muscle mass, the focus of the pathway addressed herein is on muscle mass and thus on the cross-sectional area of a muscle rather than on contraction velocity. Therefore, more significant linkage findings might be expected with slow muscle contractions rather than with fast contractions.

In conclusion, muscle strength and muscle mass are multifactorial quantitative traits that are under strong genetic control. In contrast with studies that aim to localize QTLs underlying a complex disease, the phenotype in this study is less easy to define. Therefore, a set of accurate muscle strength and mass measurements was taken, and consistent patterns of significant multipoint LOD scores were observed for related phenotypes, which might strengthen the interpretation of our findings. We observed significant or suggestive linkage at chromosomal regions 12q12–14, 13q14.2–21, and 12q22–23, suggesting a role for CDK2, RB1, and possibly IGF1 as potent QTLs for muscle strength. However, screening of the detected regions revealed other valuable candidate genes for muscle strength that are not related to the myostatin pathway; this warrants further investigation of these genes. These results support the hypothesis that at least some of the myostatin pathway-related genes play a role in explaining phenotypic variation of muscle strength in humans, although the contribution of the myostatin gene itself seems marginal.


   APPENDIX
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
GRANTS
 REFERENCES
 
Electronic Database Information
http://www.sph.umich.edu/csg/abecasis/Merlin/

http://genome.ucsc.edu/

http://research.marshfieldclinic.org/genetics/


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 GRANTS
REFERENCES
 
The Research Fund of the Katholieke Universiteit Leuven supported this study (grant no. OT/98/39). This Research Fund also supported W. Huygens with pre- and postdoctoral positions (nos. OT/98/39 and OT/04/260).


   ACKNOWLEDGMENTS
 
We thank all siblings of the Leuven Genes for Muscular Strength study for maximum efforts and cooperation.


   FOOTNOTES
 
Address for reprint requests and other correspondence: M. A. I. Thomis, Research Center for Exercise and Health, Faculty of Kinesiology and Rehabilitation Sciences, Katholieke Universiteit Leuven, Tervuursevest 101, B-3001 Leuven, Belgium (e-mail: martine.thomis{at}faber.kuleuven.be)

10.1152/physiolgenomics.00010.2005

1 The Supplemental Material for this article (Supplemental Figs. S1 and S2 and Supplemental Table S1) is available online at http://physiolgenomics.physiology.org/cgi/content/full/00010.2005/DC1. Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 GRANTS
 REFERENCES
 

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