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Genome-wide linkage scan for contraction velocity

characteristics of knee musculature in the Leuven Genes for

Muscular Strength Study

Gunther De Mars1, An Windelinckx1, Wim Huygens1, Maarten W Peeters1, Gaston P

Beunen1, Jeroen Aerssens², Robert Vlietinck³, Martine AI Thomis1§

1Department of Biomedical Kinesiology, Research Center for Exercise and Health, Faculty of

Kinesiology and Rehabilitation Sciences, Katholieke Universiteit Leuven, 3001 Leuven,

Belgium

²Department of Translational Medical Research, TIBOTEC BVBA, 2800 Mechelen, Belgium

³Department of Human Genetics, Faculty of Medicine, Katholieke Universiteit Leuven, 3000

Leuven, Belgium

§Corresponding author: Martine Thomis, Department of Biomedical Kinesiology, Research

Center for Exercise and Health, FABER, Tervuursevest 101, 3001 Leuven

Mail: martine.thomis@faber.kuleuven.be

Tel./Fax : +32 (0) 16 32 90 80 / +32 (0) 16 32 91 97

Running head: Genome-wide linkage scan for torque-velocity relation

Articles in PresS. Physiol Genomics (August 5, 2008). doi:10.1152/physiolgenomics.90252.2008

Copyright © 2008 by the American Physiological Society.

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Abstract

The torque-velocity relationship is known to be affected by ageing, decreasing its protective

role in the prevention of falls. Interindividual variability in this torque-velocity relationship is

partly determined by genetic factors (h²: 44-67%) As a first attempt, this genome-wide

linkage study aimed to identify chromosomal regions linked to the torque-velocity

relationship of the knee flexors and extensors. A selection of 283 informative male siblings

(17-36 years), belonging to 105 families, was used to conduct a genome-wide SNP-based

(Illumina Linkage IVb panel) multipoint linkage analysis for the torque-velocity relationship

of the knee flexors and extensors. The strongest evidence for linkage was found at 15q23 for

the torque-velocity slope of the knee extensors (TVSE). Other interesting linkage regions

with LOD scores > 2 were found at 7p12.3 (LOD = 2.03; P = 0.0011) for the torque-velocity

ratio of the knee flexors (TVRF), at 2q14.3 (LOD = 2.25; P = 0.0006) for TVSE, and at 4p14

and 18q23 for the torque-velocity ratio of the knee extensors TVRE, (LOD = 2.23 and 2.08; P

= 0.0007 and 0.001, respectively). We conclude that many small contributing genes are

involved in causing variation in the torque-velocity relationship of the knee flexor and

extensor muscles. Several earlier reported candidate genes for muscle strength and muscle

mass and new candidates are harboured within or in close vicinity of the linkage regions

reported in the present study.

Keywords

Human muscle strength, torque-velocity relationship, linkage, whole genome

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Introduction

The force generated by a muscle not only depends on the length of the muscle, and thus the

sarcomere length or contractile filaments overlap, but it also varies with the velocity at which

it shortens. With increasing shortening velocity, the force sustained by the muscle rapidly

decreases, finally leading to a velocity at which force can no longer be sustained; this is the

maximum velocity of shortening (Vmax). Force at zero velocity of shortening is the isometric

force (F0). It is possible to compare muscles of different sizes by expressing the force at a

particular velocity as a fraction of F0. The speed of shortening of a contracting muscle is

dependent on the number of sarcomeres in series.

The torque-velocity relationship is known to be affected by ageing (6, 34, 44) and

concentric torques have been found to be depressed in older individuals (15, 24). The deficit

in concentric peak torque between young and elderly individuals has also been found to

increase with contraction velocity (6). Explosive muscle power (the product of force and the

speed at which force is produced during the first seconds of a movement) is important in

correcting a displacement or movement error. To prevent a fall, an individual must have

sufficient lower limb muscle power in the stabilizing leg to counteract the kinetic energy of

the imbalance (31). The discovery of genomic factors (e.g., DNA sequence variants) causing

individual variation in the torque-velocity relationship can elucidate the physiological

pathways involved in this trait. Furthermore, final discovery of velocity-dependent gene

variants might ultimately be used for screening individuals at risk for low muscle power and

be used in individualized exercise prescription.

Several studies suggest that isometric (Fisom) and concentric (Fconc) muscle strength

are under moderate to high genetic control with heritabilities ranging between 44% - 78% for

Fisom and 31% - 61% for Fconc (23, 35-37, 39, 41, 42). However, muscle strength is a complex

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multifactorial trait, and high heritabilities do not guarantee the presence of quantitative trait

loci (QTL) with large effect size. Heritability estimates for variation in eccentric and

concentric arm flexion torques at different velocities, indicative for torque-velocity

specificity, have been reported by Thomis et al. (39). The contribution of genetic factors was

larger in eccentric torques at different velocities (66-78% at 110° and 62-82% at 140°) than

in concentric torques at different velocities (29-51% at 110° and 52-65% at 140°). The

importance of genetic factors gradually decreased with increasing velocity contraction in

concentric torques (from 65% at 30°/sec to 53% at 120°/sec in an elbow angle of 140°).

The ‘Human gene map for performance and health-related fitness phenotypes’ (26)

indicates that only a few studies have reported significant association of allelic variants in

putative QTLs with muscle strength characteristics, and even fewer associations have

consistently been replicated. To our knowledge, only a limited number of studies has been

performed to investigate association of candidate genes with the torque-velocity relationship.

Vincent et al. (45) demonstrated a genotype by velocity interaction with a greater decrease of

torque at higher velocities for the ACTN3 XX compared to the RR genotype group.

The linkage studies of Huygens et al. (16, 17) were the first to explore the role of

candidate genes in the myostatin pathway as QTLs for knee or trunk muscle strength and

estimated muscle cross-sectional area in 329 young male Caucasian siblings from the Leuven

Genes for Muscular Strength study (LGfMS). Results from these single-point linkage

explorations with a single microsatellite marker per candidate gene revealed that the

chromosomal regions harbouring myostatin (GDF8; 2q32.2), p21 (CDKN1A; 6p21.2), MyoD

(MYOD1; 11p15.1) and retinoblastoma (RB1; 13q14.2) are potentially interesting regions for

further genetic studies (LOD scores between 1.50 and 2.78, P values between 0.05 and

0.0002). Strengthened by these preliminary single-point linkage results and the physiological

evidence for the entire myostatin pathway, a multipoint linkage analysis was performed on a

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larger and partially independent sample (18) for these genetic regions, in addition to the

regions harbouring the muscle regulatory factors Myf5 (MYF5; 12q21.31) and Myf6 (MYF6;

12q21.31); insulin-like growth factor-1 (IGF1; 12q22q23); cyclin-dependent kinase-2

(CDK2; 12q13); and titin (TTN; 2q31.2) (18). Significant or suggestive linkage with knee

muscle strength was found for the regions comprising CDK2 (LOD 3.4, P = 0.0004), RB1

(LOD 2.74, P = 0.0002) and IGF1 (LOD 2.6, P = 0.0002).

The first genome-wide multipoint linkage analysis on different muscle strength

characteristics revealed one region on chromosome 14 with significant evidence for linkage

with torque-length relationship of the knee flexors (14q24.3) and several other regions with

suggestive evidence for linkage (muscle and bone cross-sectional area: 14q32.2; isometric

knee peak torque at 30° flexion: 2p24.2; torque-length relationship of the knee extensors:

1q21.3, 2p23.3 and 18q11.2; muscle-cross sectional area adjusted knee extension torque:

18p11.31) (12).

In this paper we report the results of a genome-wide linkage scan using 6008 SNP

markers, aimed at identifying genomic regions harbouring candidate genes that cause

variation in the torque-velocity relationship of the knee flexor and extensor muscles.

Methods

Subjects

A selection of 283 male siblings aged 17-36 years in 105 families from the total sample of the

Leuven Genes for Muscular Strength study (LGfMS) was made and was composed of 13

quads, 47 trios and 45 pairs of brothers, resulting in 309 pairwise comparisons. As the

absence of parental genotypes reduces the accuracy of IBD estimation within families and

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thus the power to detect linkage, emphasis was placed on the inclusion of trios and quads, as

well as the selection of the most informative sibpairs based on their level of discordance for

different strength phenotypes as Risch and Zhang (29) showed that extreme discordant

sibpairs provide substantial power to detect linkage for a QTL. The recruitment procedures

and subject characteristics have been described in detail previously (16, 18). Prior to

participation, the purpose and procedures of the study were explained in detail and the

subjects gave their written informed consent. The procedures used in this study were

approved by the medical and ethical committee of the Katholieke Universiteit Leuven.

Measurements

A detailed overview of the anthropometrical and muscle strength measurements in the

LGfMS project can be found in Huygens et al. (16, 18).

Muscle strength. The Cybex NORM isokinetic dynamometer (Lumex, Ronkonkoma, NY)

was used to assess the maximal isometric and concentric knee strength characteristics. After a

5 – 10 minutes warm-up period on an ergometer cycle and light stretching exercises, subjects

were positioned on the dynamometer, following 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

submaximal 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 6s 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

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60°/sec (3 repetitions), at 120°/sec (25 repetitions) and at 240°/sec (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 (hamstrings). Subjects

were verbally encouraged to perform at their maximum effort, and visual feedback of their

performance was presented after each test.

Torque-velocity calculations. Dynamic torques at different velocities (0°/sec, 60°/sec,

120°/sec and 240°/sec) for the optimal angles were first expressed as a percentage of

maximal isometric torque (relative torque per velocity). A natural logarithmic transformation

(Ln) of velocity was performed to linearize the torque-velocity curve with the equation y = a

+ bx (whereby a = intercept, b = slope, x = Ln(velocity); R² between .96 and .99). The

torque-velocity slope of each subjects linear torque-velocity curve for knee flexors (TVSF)

and extensors (TVSE) was calculated and retained for further analyses. A second measure of

torque-velocity was the ratio of torque at 240°/sec and torque at 60°/sec, multiplied by 100.

This torque-velocity ratio was calculated for knee flexors (TVRF) and extensors (TVRE).

Baecke Sport Index. The Baecke physical activity questionnaire (5) was used to assess the

level of daily physical activity and more specifically the subjects’ sports participation in the

Sport Index.

DNA collection

DNA was extracted using the Chemagic DNA Blood Kit on an automated Chemagic

Magnetic Separation Module I (Chemagen®, Baesweiler, Germany) and a Multiprobe I

(PerkinElmer®, Waltham, Massachusetts, USA) robotic station. An OrageneTM saliva kit

(Genotek, Ottawa, Ontario, Canada) was provided to siblings who were not able to deliver a

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blood sample. DNA from these saliva kits was extracted following the guidelines of the

manufacturer.

Genotyping

The Illumina SNP-based Linkage Panel IVb was selected for genotyping. The panel includes

6008 bi-allelic SNP markers distributed evenly across the genome. The average and median

intervals between markers are 482kb (0.64 cM) and 298kb (0.35 cM), respectively. The

largest interval between successfully genotyped markers is 5.02 cM on chromosome 8 and

linkage disequilibrium between markers is minimal. The panel is designed to reach an

average minor allele frequency and heterozygosity of SNP markers of 37% and 44%,

respectively (Illumina technical report). The Illumina markers were typed with the Illumina

Beadstation 500GX, in accordance with the manufacturer’s standard recommendations. The

genotype success rate was 99.6% (33 SNPs were excluded from analysis due to low signal or

cluster overlap). Only autosomal SNPs were included for further analyses.

Statistical analysis

Descriptive statistics. Descriptive statistics and phenotypic correlations between the different

strength characteristics and covariates were calculated using SAS version 9.1.(SAS Institute

Inc., Cary, NC, USA). To explore the contribution of velocity-dependent torque declines on

the measure of the torque-velocity slope, linear stepwise regression analyses were performed.

The declines in torque from 0°/sec to 60°/sec and 60°/sec to 240°/sec were expressed as

ratios, and the proportion of variance explained by each of these torque-velocity curve ratios

was then estimated through regression analyses.

Heritability estimations. Upper-limit heritability of the traits (h²) were estimated using the

variance-components analysis procedure (VC) in QTDT (2). This estimate includes common

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environmental variation in addition to the additive genetic component, because these factors

can not be separated using sib pairs only. Hence, it is called the upper-limit heritability.

Linkage analysis. Nonparametric multipoint linkage analyses were performed on 22

autosomes using the revised Haseman-Elston regression algorithm (MERLIN Regress)

outlined by Sham et al. (30) - implemented in MERLIN software v.1.1.1 (3). The revised H-E

algorithm combines the simplicity and robustness of regression-based methods and the

generality and power of variance components methods (30). This method requires

specification of trait heritability, population means and variances, which were calculated

using the Pedstats (46) and QTDT program (2). Average minor allele frequencies and

heterozygosities of markers in the present linkage panel within our sample were calculated

using MERLIN (3). Before statistical analyses, all genotypes were checked for Mendelian

inheritance, using the error detection protocol in MERLIN (3). Deviations from Hardy-

Weinberg equilibrium were assessed using the PEDSTATS program (46). Polymorphisms

with Hardy-Weinberg P values < 0.001 were removed from further analyses.

Under the assumption of no susceptibility loci, simulated data for 100 genome scans

were generated using MERLIN (3), in order to estimate the significant and suggestive

threshold for linkage (10, 21, 43). In each simulation, we retained the original pedigree

structure and generated a new data set with the same allele frequencies, marker spacing,

phenotypes and any missing genotypes or data pattern. Any evidence for linkage in these

simulated data is due to chance. The cut-off for suggestive linkage (LOD = 2.37) was

calculated as the mean of the genome-wide maximum LOD score from each genome scan,

which determines the maximum peak size expected once per genome scan by chance alone.

The significant linkage threshold (LOD = 3.64) was defined as the maximum LOD score

occurring with probability 0.05 in a genome scan (i.e., 5 peaks of equal or greater size

observed in the 100 simulations).

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It is nowadays a widely accepted practice to obtain empirical P values for reported

LOD scores (1, 4, 32). We calculated empirical P values through the use of 1,000, 10,000 or

100,000 gene-dropping simulations (related to the original P values of SNPs with LOD > 1.5,

see Table 3 under P value) using MERLIN (3), under the assumption of no susceptibility loci.

The empirical significance level of a LOD peak was then determined by counting the

proportion of simulated (unlinked) LOD scores higher or equal to the original LOD score.

Combined linkage and association analysis. Tests for joint linkage and association in regions

with suggestive and significant evidence for linkage were carried out using QTDT

(Quantitative Transmission Disequilibrium Test) software (2). SNPs in a minus 1 LOD

support region around SNPs showing suggestive or significant evidence for linkage in the

MERLIN-regress linkage analysis were investigated. Fulker et al. (14) developed a method

for simultaneous modelling of association and linkage for quantitative traits using sib pair

data that also controls for population stratification. Combined linkage and association

analysis is a powerful tool for pinpointing functional associated loci responsible for a linkage

signal. Assuming there is suggestive/significant linkage before modelling association, the

extent to which evidence for linkage diminishes in the joint test of linkage and association

reflects the proximity of the marker to the functional quantitative trait locus (QTL) (9, 14). If

the linkage signal of a certain locus is entirely explained by modelling association (i.e., the

linkage signal is no longer significant), that particular locus is either the functional locus or in

tight LD with the functional locus.

Association analysis. SNPs in a minus 1 LOD support region around the SNP showing

significant evidence for linkage were tested for association with the MERLIN likelihood-ratio

test for the different strength phenotypes (3).

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Results

Descriptive statistics

Average minor allele frequencies and heterozygosities for the autosomes within this

sample were 50% and 45%, respectively. The percentage of SNPs with MAF < 5% was

0.65%.

Table 1 shows the main somatic and muscle strength statistics of 283 siblings, with

corresponding upper-limit heritabilities (h²) estimated for both the total LGfMS sample (n =

748) and the subsample (n = 283). Subjects had normal weight and height; the body mass

index (BMI: 22.9 ± 2.9 kg/m²) indicates that they were, on average, rather lean.

As expected, the upper-limit heritability estimate of stature was high (99%), and

genetic determination of body mass and BMI were somewhat lower (89% and 87%,

respectively). Fat-free mass and muscle and bone cross-sectional area (MBA) of the mid-

thigh showed h² estimates of 94% and 89%, respectively. In this sample, moderate to high

upper-limit heritabilities were found for the torque-velocity slopes and ratios of the knee

flexors and extensors (44-67%). Variability in the Sport Index could be accounted for by

genetic factors for at most 63%.

Correlations between the different torque-velocity phenotypes ranged from .20 to .73

(Table 2). Moderate to high correlations were found between TVSF and TVRF (.73), and

between TVSE and TVRE (.62). Low to moderate cross-trait/-estimate correlations were

found (r between .20 and .46), indicating the specificity of both torque-velocity estimates and

the torque-velocity characteristics of knee extensor muscles and flexor muscles. Correlations

between Sport Index and torque-velocity phenotypes were not significant.

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Regression analyses demonstrated that the ratios for 0°/sec to 60°/sec and 60°/sec to

240°/sec for the knee flexors and extensors account for 41% and 55%, and 48% and 44%,

respectively, of the total variance in the torque velocity slope from 0°/sec to 240°/sec.

Linkage analyses

Figure 1 shows LOD score curves over the autosomal genome for each of the phenotypes.

Empirical P values and LOD scores for regions with LOD of 1.5 and higher are shown in

Table 3. The highest multipoint LOD score (2.91) was found on chromosome 15q23 for

TVSE, with an empirical P value < 10-5. Other interesting linkage regions with LOD scores >

2 were found for TVRF (LOD = 2.03 on 7p12.3), TVSE (LOD = 2.25 on 2q14.3) and TVRE

(LOD = 2.23 and 2.08 on 4p14 and 18q23, respectively).

Combined linkage and association analyses

Figure 2 shows two examples of LOD score curves for the effects of combined linkage and

association analysis for SNPs in a LOD -1 support region around SNP rs1403970 (2q36.3)

for TVRF, and around SNP rs477449 (2q14.3) for TVSE. No significant drop in LOD scores

was observed after modelling a joint test for linkage and association, indicative for rather

limited effects of allelic association between the investigated SNPs and the studied traits.

Similar results were found for all other SNPs in regions with evidence for linkage. However,

when applying the MERLIN likelihood-ratio association test, significant associations (P <

0.01) were found (Table 4) between SNPs within these LOD-1 support regions and several

phenotypes. Association tests for the SNPs with peak LOD scores are included in table 3,

however, these were not significant. Classical AN(C)OVA-type association analysis

confirmed the above MERLIN likelihood-ratio association findings, except for SNPs

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rs1479371 at chr3 (TVRF) and SNP rs1321834 at chr6 (TVSF) (Table 4). Peak LOD scores

for the associated SNPs in table 4 are also included.

Discussion

We performed a genome-wide multipoint linkage analysis to identify quantitative trait loci

for the torque-velocity relationship of the knee flexors and extensors, including two

measures: 1) the slope of the linearized torque-velocity relationship and 2) the ratio of torque

at 240°/sec and torque at 60°/sec. The most promising evidence for linkage was observed for

the torque-velocity slope of the knee extensors with SNP rs1348318 on chromosome 15q23.

It is possible that the identified susceptibility locus is muscle specific (flexors vs. extensors)

and does not account for variability in knee flexion. As muscle strength and its derived

phenotypes are regarded as a complex genetic trait, identification of a large number of

markers with LOD scores that meet the criteria of suggestive linkage should not be expected.

Another interesting chromosomal region is region 7p12.3 that harbours a candidate gene

(IGFBP-1) for TVRF, although this region was not reported in earlier linkage studies

investigating strength-related phenotypes.

Our group previously performed a multipoint linkage analysis for muscle strength

and muscle mass in a similar cohort of young, male siblings, using microsatellite markers in

chromosomal regions harbouring myostatin pathway genes (18). Region 12q24.32 was

identified in the present study and is in the vicinity of the earlier reported region 12q22-23

(18). Compared with our previous analyses (18) with microsatellites markers (average marker

distance 4.81 cM for chromosome 12), the current study used the Illumina pre-designed SNP

based Linkage IVb panel with an average marker distance of 0.56 cM for chromosome 12.

Although this SNP panel induces higher genetic informativeness than microsatellite markers

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(13, 47), differences between present (n = 283; Illumina SNP panel) and previous findings (n

= 367; microsatellite markers; Applied Biosystems) (18) are probably related to sample size

differences, or region-specific informativeness of closely chosen microsatellite markers

versus SNP markers (mean heterozygosity of SNP markers was 44.2% on chr12). Of note,

also several other overlapping/neighbouring linkage regions could be detected between the

present study and our genome-wide scan for maximum and length-dependent knee muscle

strength (12): region 2p25.3 (TVRE) with 2p24.2 for isometric torque at 30° flexion; region

10q25.3 (TVSE) with 10q26.13 for torque-length flexion; region 2q14.3 (TVSE) with 2q14.2

for muscle-bone area of the mid-thigh; region 12q24.32 (TVSE) with 12q24.32 and 12q24.31

for torque-length flexion and extension, respectively; and 15q23 (TVSE) with 15q23 for

isometric torque at 30° flexion. These regions might harbour candidate genes for underlying

shared characteristics like muscle fiber type distribution that cause variability in both torque-

length and torque-velocity characteristics.

Several multivariate genetic studies examined genetic and environmental

contributions to individual differences in various muscle strength characteristics (11, 36, 37,

39, 41, 42). These studies suggest a shared pleiotropic gene action for the different

phenotypic characteristics (the same genes causing variability in different types of

contractions, speeds, angles), referring to a common underlying genetic cause of strength

generality. This would imply that different examined phenotypes share the same

chromosomal region with suggestive or significant evidence for linkage. However, no clear

overlap for chromosomal regions between the different phenotypes was found within this

study. This is somewhat surprising, given the correlations up to 0.73, which strongly suggest

a shared genetic source of variance in muscle strength, although additional shared

environmental sources of covariance might induce this correlation. Common linkage signals

were also absent between highly intercorrelated VO2max and maximal power output (r = 0.94)

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in the HERITAGE Family study (27). An explanation might be the different information

provided by each measure: the slope measure encompasses the torque-velocity curve in a

range of 0°sec to 240°/sec, whereas the ratio measure focuses on the faster part of the curve

(60°/sec to 240°/sec). Therefore, the torque-velocity ratio does not pick up linkage signals for

slower contraction velocities (0°/sec to 60/°sec), whereas the torque-velocity slope does.

The examined phenotypes related to the torque-velocity relationship are regulated

by numerous genes. In addition, gene-gene and gene-environment interactions and

contributions of environmental factors for muscle strength can be assumed to affect the

power of linkage studies. The identification of susceptibility loci using a small sample

size is therefore difficult. We calculated the successful estimation of IBD status for each

pairwise comparison over all 133 SNP markers at chromosome 22 by counting a >0.95

probability level as a successful classification of IBD status (IBD0, IBD1 or IBD2). The

information content for duo, trio and quad families was 60%, 78% and 88%, respectively,

which is even higher than reported in (33). The power to detect regions harbouring

susceptibility loci was estimated using the Genetic Power Calculator (25) based on the

heritabilities estimated in QTDT (assumptions: θ = 0; additive QTL variance = 30%;

common residual shared variance = 40% (= genetic variance not attributable to the QTL

and/or common environmental variance); no dominance; residual nonshared variance =

30%; α level = 0.05). A weighted non-centrality parameter was derived based on the

proportion of quads, trios and sib pairs. With the current sample, it is estimated that a

power of 70% can be reached for the detection of a QTL accounting for 30% of the

phenotypic variance, 30% residual shared variance, no dominance, and residual non-

shared variance of 40%. Much higher sample sizes are needed when small QTL effect

sizes are aimed to be detected.

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Heritability of slope flexion in the subsample (n = 283) is low, which might in

part explain the single LOD peak > 1.5 for this trait. 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.

Different mechanisms underly the variability in the torque-velocity relationship. First,

Rijkelijkhuizen et al. (28) showed in rats that the mean curvature of the torque-velocity

relationship for fast oxidative fibers was higher than for fast glycolytic fibers. They

concluded that the degree of curvature is fiber-type dependent. This is in line with the single-

fiber study of Bottinelli et al. (8) who demonstrated in humans that curvature was higher for

slow fibers than for fast fibers; among fast fibers, curvature was higher for fast oxidative (IIa)

than for fast glycolytic (IIb) fibers although the difference was not statistically significant.

Furthermore, a shortened velocity of knee extensor muscles was found to be significantly

correlated with the percentage of fast-twitch fibers in the vastus lateralis muscles (40).

Second, previous studies have also suggested the presence of unique genetic causes of

variance (genes causing non-shared variability in one specific muscle characteristic) (11, 36,

37, 39, 41, 42). For example, the ACTN3 (11q13.1) gene, which is expressed in Z-lines of

fast but not of slow muscle fibers, is believed to be one of the contributing genes in the

heritability of fiber type distribution (45) and might be (in)directly involved in the presence

of different curvatures of the torque-velocity relationships. ACTN3 R577X genotype

associations were reported for relative torques at 300°/sec (45), which is at much higher

speeds than measured in the present study. We did not find an important linkage signal in the

vicinity of ACTN3, which might be attributed to the absence of a causal SNP or lack of LD

with the causal SNP in the current Illumina SNP panel. An exploratory association analysis

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of ACTN3 R577X genotypes at 60°/sec, 120°/sec and 240°/sec in a subsample of the LGfMS

study (n = 362) demonstrated stronger associations for relative dynamic knee extension

torques with increasing velocities (38). The lower relative dynamic torques at higher

contraction speeds for XX carriers might indicate a downward shift of the force-velocity

curve in subjects lacking the ACTN3 protein. Second, the torque-velocity relationship can

also be determined by fascicle length (muscle fibers packed in bundles which extend from the

proximal to distal tendons) and pennation angle of muscle fibers (angle between the muscle

fiber and the axis of the muscle). In a group of 37 male 100-m sprinters (fast and slow

group), Kumagai et al. (20) found significant, negative correlations between 100-m personal

best performance and fascicle length (absolute and relative to limb length) of the vastus

lateralis, and gastrocnemius medius and lateralis muscles. They argued that longer fascicle

length might lead to greater maximal velocity of shortening and allows for a greater force

output at an identical shortening velocity, which results in greater power production.

Furthermore, sprinters in the fast group had a significantly lower pennation angle than did the

slow group for the selected muscles. Both muscle architectural characteristics might be the

result of genes and/or gene-environment (i.e. training) interactions.

A candidate gene for the torque-velocity relationship is the insulin-like growth factor-

binding protein 1 gene (IGFBP-1) which is located on chromosome 7p12p13, within the

LOD peak of 2.03 at 7p12.3 (for TVRF). It binds to the insulin-like growth factor 1 protein

(IGF-1) which has previously been associated with quadriceps-muscle strength gains in

response to strength training (19). Lang et al. (22) demonstrated that an acute in vivo

elevation in circulating levels of IGFBP-1 is capable of selectively decreasing protein

synthesis in fast-twitch skeletal muscle and concluded that elevations in circulating and tissue

levels of IGFBP-1 may be an important mediator for the muscle catabolism observed in

various stress conditions. Several candidate genes have been associated with muscle strength

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phenotypes (7, 26). However, these genes are not located within linkage regions reported in

the present study. Growth and differentiation factor 8 (GDF8; 190.6 Mb) is located in relative

vicinity to region 2q36.3 (221.8 Mb), myosin light chain kinase (MYLK; 124.9 Mb) to region

3q21 (141.8 Mb), both linked to TVRF, and insulin like growth factor 1 (IGF1; 101.3 Mb) to

region 12q24.32 (122.2 Mb). Further fine mapping analysis will be required to assess the

potential contribution of each of these candidate genes to explain velocity-dependent muscle

strength variation.

The results of the joint test for linkage and association showed no evidence for

association with any of the SNPs in regions with suggestive or significant evidence for

linkage. However, the association analysis using Merlin software (3) revealed significant

association in six different chromosomal regions (Table 4). These SNPs are located in the

vicinity of the SNPs with highest LOD scores within their respective chromosomal region.

Finding “true” association between a trait and a SNP requires complete LD between the

marker and the functional SNP, or the SNP being the actually functional SNP itself. Marker

spacing in the Linkage IVb Panel of Illumina, designed to perform linkage analyses rather

than association analyses, is relatively large (average marker spacing = 482Kb or 0.64 cM),

with low between-marker LD. Furthermore, the panel is not specifically enriched for

functional SNPs (eg non-synonymous variants), as minor allele frequency and heterozygosity

are the main criteria for markers to be included. This might explain the observation that the

SNPs which identified the highest linkage LOD score did not show up as most significant in

the association analysis. A much denser marker panel (eg microarray chips) or a functional

fine mapping panel of SNPs located in relevant ranked candidate genes (48) will be needed to

assess association in regions with suggestive or significant evidence for linkage.

19

Conclusions

This genome-wide multipoint linkage analysis of different torque-velocity characteristics

revealed several promising regions with evidence for linkage with the torque-velocity

relationship of the knee flexors and extensors. Several candidate genes that might be relevant

from a physiological point of view are located within the identified regions, and warrant

further fine mapping analyses by additional linkage and/or association studies. Despite only

the largest families from the LGfMS project were selected for this study, the relatively small

sample size limits the possibility to detect chromosomal regions where genes with small

effect sizes are harboured. Therefore, fine mapping and replication studies should focus on

highly informative samples (e.g. large families) of sufficiently large size, and preferably

extend to females and other age groups.

Acknowledgements

We thank the siblings for the participation in the study and their enthusiasm in performing at

their maximum during the strength testing protocol. The authors wish to thank I Salden for

his support during the preparation of DNA samples, and Ruben van ‘t Slot for careful

assistance with the genome scan.

Grants

GDM is funded by grant G.0496.05 of the Research Foundation Flanders (FWO). AW is

supported by the Research Fund of the Katholieke Universiteit Leuven (OT/04/44). WH was

funded by grant OT/98/39. Maarten Peeters is a Postdoctoral Fellow (FWO). The project is

20

funded by OT/98/39 for the phenotyping phase, and OT/04/44, G.0496.05 and mainly FWO

G.0567.07 for the genome scan.

Disclosures

The authors confirm that there is no conflict of interest for this research article.

Table legends

TABLE 1. Somatic characteristics and muscle strength statistics

* h² estimated on the total Leuven Genes for Muscular Strength sample (n = 748); ratios were calculated by

dividing peak torque at 240°/sec by peak torque at 60°/sec, multiplied by 100; slopes were estimated using

peak torque at 0°/sec, 60°/sec, 120°/sec and 240°/sec (see Materials and methods); flexion and extension

torques were measured at a knee angle of 30° and 60°, respectively; MBA = muscle and bone area.

TABLE 2. Pearson correlations (P value) between torque-velocity characteristics

and scores on the Baecke Sport Index

Correlations are calculated on the total GfMS sample (n = 748)

TABLE 3. LOD scores > 1.5 and P values of multipoint linkage analysis for torque-

velocity relationship of the knee flexors and extensors

TABLE 4. Association results for SNPs with P <0.01

Values are means±SE. 1G carriers vs. CC; 2G carriers vs. AA; 3C carriers vs. AA; 4A carriers vs. CC. 5A

carriers vs. GG. Genotype frequencies are in Hardy-Weinberg equilibrium (P > 0.01)

21

Figure legends

FIGURE 1. LOD scores for autosomal linkage analysis for ratio and slope

characteristics of torque-velocity for the knee flexors and extensors

Cut-off LOD scores for suggestive and significant linkage are 2.37 and 3.64, respectively.

FIGURE 2. Representation of combined linkage and association analysis for ratio

flexion and slope extension at LOD -1 support region around SNPs rs1403970 and

rs477449, respectively

LOD scores for variance components analyses in QTDT: Linkage (VC_L) and combined linkage and

association (VC_LA); LOD scores for Merlin-regress analyses (REG)

22

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TABLE 1. Somatic characteristics and muscle strength statistics

Trait Mean ± SD h², %* h², % †

Age 25.1 ± 4.5

Weight, kg 74.5 ± 10.4 85 89

Stature, cm 180.2 ± 6.5 92 99

Fat-free mass, kg 63.4 ± 6.5 90 94

Body mass index, kg/m² 22.9 ± 2.9 81 87

MBA mid-thigh, cm² 171.8 ± 22.7 85 89

Slope flexion, % -23.1 ± 5.0 71 44

Slope extension, % -27.9 ± 3.6 44 55

Ratio flexion, % 62.0 ± 11.1 68 67

Ratio extension, % 54.8 ± 8.3 59 52

Sport Index 3.0 ± 0.7 50 63

* h² estimated on the total Leuven Genes for Muscular Strength sample (n = 748); † h² estimated on the

subsample (n = 283)ratios were calculated by dividing peak torque at 240°/sec by peak torque at 60°/sec,

multiplied by 100; slopes were estimated using peak torque at 0°/sec, 60°/sec, 120°/sec and 240°/sec (see

Materials and methods); flexion and extension torques were measured at a knee angle of 30° and 60°,

respectively; MBA = muscle and bone area.

32

TABLE 2. Pearson correlations (P value) between torque-velocity characteristics

and scores on the Baecke Sport Index

Sport Index Slope flexion Slope extension Ratio flexion

Slope flexion 0.07 (0.24)

Slope extension -0.05 (0.40) 0.32 (<0.0001)

Ratio flexion 0.07 (0.25) 0.73 (<0.0001) 0.20 (0.0013)

Ratio extension -0.05 (0.40) 0.40 (<0.0001) 0.62 (<0.0001) 0.46 (<0.0001)

Correlations are calculated on the total GfMS sample (n = 748)

33

TABLE 3. LOD scores > 1.5 and P values of multipoint linkage analysis for torque-

velocity relationship of the knee flexors and extensors

Trait SNP Chromosomal region

cM LOD

P value Empirical P value

P value Likelihood-ratio test

Slope flexion rs717651 13q12.3 26.87 1.70 0.003 0.002 0.95 Ratio flexion rs1403970 2q36.3 231.87 1.55 0.004 0.004 0.36 rs1384542 3q25.32 164.47 1.53 0.004 0.002 0.92 rs2998367 6q14.1 88.25 1.93 0.0014 0.0007 0.18 rs921630 7p12.3 70.13 2.03 0.0011 0.0006 0.32 Slope extension rs477449 2q14.3 139.88 2.25 0.0006 <0.0001 0.96 rs4751909 10q25.3 133.38 1.85 0.002 <0.001 0.095 rs918044 12q24.32 149.17 1.85 0.002 0.001 0.149 rs768826 13q21.33 64.23 1.82 0.002 <0.001 0.73 rs1348318 15q23 76.79 2.91 0.00013 <0.00001 0.62 Ratio extension rs938326 2p25.3 3.58 1.85 0.002 0.001 0.033 rs1039559 4p14 58.04 2.23 0.0007 0.0001 0.70 rs1866338 18q23 118.79 2.08 0.001 <0.001 0.73

34

TABLE 4. Association results for SNPs with P <0.01

Values are means±SE. 1G carriers vs. CC; 2G carriers vs. AA; 3C carriers vs. AA; 4A carriers vs. CC. 5A

carriers vs. GG. Genotype frequencies are in Hardy-Weinberg equilibrium (P > 0.01)

Likelihood-ratio test Analysis of variance

SNP Chromosomal

region

Genetic

Location

cM

Torque-velocity

phenotype

LOD Allele Allele

Effect

size

P value Carriers (n) Non-carriers (n) P value

rs1479371 3q12.3 113.38 Ratio flexion 0.692 G -4.896 0.00031 61.7±0.9 (271) 64.2±6.1 (10) 0.701

rs765695 3q24 151.04 Ratio extension 0.127 G -2.339 0.0041 54.4±0.8 (234) 58.2±1.6 (47) 0.042

rs1321834 6q13 86.07 Slope flexion 0.379 G -1.712 0.0041 -23.2±0.5 (270) -21.2±1.4 (11) 0.182

rs1321834 6q13 86.07 Ratio extension 1.011 G -3.380 0.00071 54.8±0.7 (270) 63.5±2.4 (11) 0.012

rs1545963 13q21.31 59.33 Slope flexion 0.008 G +1.337 0.0038 -22.8±0.5 (241) -25.6±0.7 (40) 0.00022

Ratio flexion (TVRF)

0

1

2

3

4

Chromosome

LOD

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Slope flexion (TVSF)

0

1

2

3

4

Chromosome

LOD

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Ratio extension (TVRE)

0

1

2

3

4

Chromosome

LOD

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Slope extension (TVSE)

0

1

2

3

4

Chromosome

LOD

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Ratio flexion (TVRF)

0

0.5

1

1.5

2

223.8 226.2 228.0 229.1 234.0 238.2 239.6 243.9

Position (cM)

LOD

VC_L

VC_LA

REG

rs1403970

Slope extension (TVSE)

0

0.5

1

1.5

2

2.5

130.7 134.6 135.2 138.6 141.4 142.4

Position (cM)

LO

D

rs477449