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Biomedical subjects

G P Beunen

Publications and source records attributed to G P Beunen.

17 recordsLinked to original sources
PubMed2005

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

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.

Adolescent↗
PubMed2000

Predictive power of individual genetic and environmental factor scores.

This study explores the use of an individual's genetic (IGFS) and environmental factor score (IEFS), constructed using genetic model fitting of a multivariate strength phenotype. Maximal isometric and dynamic strength measures, one maximal repetition load (1RM) and muscle cross-sectional area (MCSA) were measured in 25 monozygotic and 16 dizygotic twin pairs. The use of IGFS and IEFS in predicting the sensitivity to environmental stress was evaluated by the association of the scores with strength training gains after a 10-week high resistance strength training programme. Results show a high contribution of genetic factors to the covariation between maximal strength and muscle cross-sectional area (84-97%) at pre-training evaluation. Individual factor scores explained the largest part of the variation in IRM and other strength measures at pre-training and post-training evaluation respectively. Genes that are switched on due to training stress (gene-environment interaction) could explain the decrease in explained variation over time. A negative correlation was found between IGFS and strength training gains (-0.24 to -0.51, P < 0.05); individuals with a high IGFS tend to gain less strength than individuals with low IGFS. Individual environmental factor scores have lower differential power. The predictive value of the IGFS has potential utility in identifying an individual's susceptibility to environmental stress in a variety of multifactorial characteristics, eg diseases and impairments, and for selection of sib pairs for QTL analyses.

Adolescent↗
PubMed1998

Inheritance of static and dynamic arm strength and some of its determinants.

Maximal static, eccentric and concentric torques and arm components estimated by anthropometry and measured by computed tomography were evaluated in 25 male monozygotic twins and 16 dizygotic twins (22.4 +/- 3.7 years). The importance of genetic and environmental factors in the observed variation in these measurements was estimated by genetic model-fitting techniques. In this sample of young adult male twins, genetic factors were significant in most of the strength measurements, arm muscle components and muscle activation variables. The contribution of genetic factors in strength measures depended on the angle, contraction type and to some extent on contraction velocity. For isometric strength, angle-specificity in genetic and environmental variation could be attributed to the degree of variability in muscle activation and performance discomfort at each specific angle, with the highest unique environmental impact at extreme angles. The high genetic contribution at 170 degrees, but not at 50 degrees, possibly expressed different contributions of genetic factors in the muscle-length factor and moment arm in torques at both angles. The importance of genetic factors in eccentric arm flexor strength (62-82%) was larger than for concentric flexion (29-65%), as the pattern of genetic determination followed the torque-velocity curve. Genetic variations in contractile and elastic components, contributing differently to eccentric and concentric torques, together with velocity-dependent actin-myosin binding factors, could account for the observed differences. The broad heritability was very high for all anthropometric and arm cross-sectional area measurements (> 85%) and common environmental factors were only significant for anthropometrically estimated mid-arm muscle tissue are (48%). Heritability estimates of different arm muscularity measurements were comparable.

Adolescent↗
PubMed1998

Strength training: importance of genetic factors.

PURPOSE: This study focuses on the quantification of genetic and environmental factors in arm strength after high-resistance strength training. METHODS: Male monozygotic (MZ, N = 25) and dizygotic (DZ, N = 16) twins (22.4 +/- 3.7 yr) participated in a 10-wk resistance training program for the elbow flexors. The evidence for genotype*training interaction, or association of interindividual differences in training effects with the genotype, was tested by a two-way ANOVA in the MZ twins and using a bivariate model-fitting approach on pre- and post-training phenotypes in MZ and DZ twins. One repetition maximum (1RM), isometric strength, and concentric and eccentric moments in 110 degree arm flexion at velocities of 30 degrees x s(-1), 60 degrees x s(-1), and 12 degrees x s(-1) were evaluated as well as arm muscle cross-sectional area (MCSA). RESULTS: Results indicated significant positive training effects for all measures except for maximal eccentric moments. Evidence for genotype*training interaction was found for 1RM and isometric strength, with MZ intra-pair correlations of 0.46 and 0.30, respectively. Bivariate model-fitting indicated that about 20% of the variation in post-training 1RM, isometric strength, and concentric moment at 120 degrees x s(-1) was explained by training-specific genetic factors that were independent from genetic factors that explained variation in the pretraining phenotype (30-77%). CONCLUSIONS: Genetic correlations between measures of pre- and post-training strength were indicative for high pleiotropic gene action and minor activation of training-specific genes during training.

Adult↗
PubMed1997

Skeletal maturation, somatic growth and physical fitness in girls 6-16 years of age.

The importance of chronological age (CA) and skeletal age (SA) in explaining variation in somatic dimensions, and the independent contributions of CA, SA, stature (ST) and weight (WT) to variability in physical fitness were investigated in a sample of 6593 girls 6-16 years of age. Body dimensions included lengths, breadths, circumferences, skinfolds, and Heath-Carter somatotype, while fitness tests included measures of health- and performance-related fitness, and cardiovascular and lung functions. Age-specific correlations were calculated between SA and anthropometric dimensions, fitness tests and cardiovascular and lung functions, while age-specific stepwise multiple regressions were used to investigate the relative importance of SA, CA, ST and WT in explaining fitness and cardiovascular and lung functions. SA is most highly correlated with lengths and then with breadths, circumferences and skinfolds in this order. SA per se or in interaction with CA is the only significant predictor of somatic characteristics. Among fitness items, physical working capacity and static strength correlate highest with SA. Bent arm hang, leg lifts and sit-ups correlate negatively with SA but values are low, while all other components correlate at non-significant or low levels. Results of the multiple regression analysis indicate that, with few exceptions, CA, SA, ST and WT and their interactions explain less than 10% of the variance in most physical fitness items. However, for PWC, arm pull strength, and bent arm hang, the interaction terms explain between 12% and 67% of the variance.

Adolescent↗
PubMed1997

Prediction of adult stature and noninvasive assessment of biological maturation.

The Tanner-Whitehouse method to predict adult stature uses current stature, current skeletal age (SA), and chronological age (CA), and, if available, change (gain) in stature and SA over the previous year. Since assessment of SA requires invasive techniques, a method is proposed to predict adult stature noninvasively and to use percentage of adult stature as a maturity indicator. Age-specific multiple regression equations were calculated in a sample of 102 Flemish boys 13 through 16 yr who were followed during adolescence and remeasured at 30 yr of age. The proposed procedure, the Beunen-Malina method for prediction of adult stature, includes four somatic dimensions (current stature, sitting height, subscapular skinfold, triceps skinfold) and CA. In this age range multiple correlations (Rs between 0.70 and 0.87) and SEEs (between 3.0 and 4.2 cm) compare favorably with the original Tanner-Whitehouse method. Furthermore, when maturity groups based on percentage of adult stature calculated from the Beunen-Malina predictions are contrasted for somatic dimensions and performance characteristics, differences are similar to those observed when maturity grouping is based on skeletal maturity.

Adolescent↗
PubMed1997

Multivariate genetic analysis of maximal isometric muscle force at different elbow angles.

The maximal isometric moment at five different elbow joint angles was measured in 25 monozygotic and 16 dizygotic male adult twin pairs (22.4 +/- 3.7 yr). Genetic model fitting was used to quantify the genetic and environmental contributions to individual differences in isometric strength. Additive genetic factors explained 66-78% of the variance in maximal torque at 170-140-110 and 80 degrees flexion (extension = 180 degrees). At 50 degrees flexion, common and subject-specific environmental factors contributed equally to the variation. The contribution of unique environmental factors concurs with the level of variability in muscle activation and (dis)-comfort of torque production in the specific angle. The relative contribution of lever arm and force-length relationship in torque varies according to the angle. Because these factors might be genetic, this variability is reflected in the genetic contribution at the extreme angles of 170 and 50 degrees. Multivariate analyses suggested a general set of genes that control muscle area and isometric strength, together with a more specific strength factor. Genetic correlations were high (0.82-0.99). Genes responsible for arm-segment lengths did not contribute to muscle area nor to isometric strength.

Adolescent↗
PubMed1996

Inheritance of physical fitness in 10-yr-old twins and their parents.

This study focuses on the quantification of genetic and environmental sources of variation in physical fitness components in 105 10-yr-old twin pairs and their parents. Nine motor tests and six skinfold measures were administered. Motor tests can be divided into those that are performance-related: static strength, explosive strength, running speed, speed of limb movement, and balance; and those that are health-related: trunk strength, functional strength, maximum oxygen uptake, and flexibility. The significance and contribution of genetic and environmental factors to variation in physical fitness were tested with model fitting. Performance-related fitness characteristics were moderately to highly heritable. The heritability estimates were slightly higher for health-related fitness characteristics. For most variables a simple model including genetic and specific environmental factors fitted the observed phenotypic variance well. Common environmental factors explained a significant part of the variation in speed components and flexibility. Assortative mating was significant and positive for speed components, balance, trunk strength, and cardiorespiratory fitness, but negative for adiposity. Static strength, explosive strength, functional strength, and cardiorespiratory fitness showed evidence for reduced genetic transmission or dominance. The hypothesis that performance-related fitness characteristics are more determined by genetic factors than health-related fitness was not supported. At this prepubertal age, genetic factors have the predominant effect on fitness.

Adult↗
PubMed1995

Fatness and physical fitness of girls 7 to 17 years.

A two-fold approach was used to investigate the association between fatness and fitness of girls 7 to 17 years of age: first, age-specific correlations between fatness and measures of health-related and motor fitness, and second, comparisons of fitness levels of girls classified as fat and lean. A representative sample of 6700 between 7 to 17 years was surveyed. Adiposity (fatness) was estimated as the sum of five skinfolds (biceps, triceps, subscapular, suprailiac, medial calf). Physical fitness included health-related items (step test, PWC170, the sit and reach, sit-ups and leg lifts, flexed arm hang) and motor performance items (standing long jump, vertical jump, arm pull strength, flamingo stand, shuttle run, plate tapping). Age-specific partial correlations between fatness and each fitness item, controlling for stature and weight, were calculated. In addition, in each age group the fattest 5% (presumably the obese) and the leanest 5% were compared on each fitness test. After controlling for stature and weight, subcutaneous fatness accounts for variable percentages of the variance in each fitness item. Estimates for health-related fitness items are: cardiorespiratory endurance-step test (3% to 5%) and PWC170 (0% to 16%), flexibility-sit and reach (3% to 8%), functional strength-flexed arm hand (6% to 17%) and abdominal strength-sit-ups/leg lifts (1% to 8%). Corresponding estimates for motor fitness items are more variable: speed of limb movement-plate tapping (0% to 3%), balance-flamingo stand (0% to 5%), speed and agility-shuttle run (2% to 12%), static strength-arm pull (4% to 12%), explosive strength-standing long jump/vertical jump (11% to 18%). At the extremes, the fattest girls have generally poorer levels of health-related and motor fitness.

Adolescent↗
PubMed1994

Adiposity and biological maturity in girls 6-16 years of age.

The aim of this study was to investigate the relationships between adiposity and skeletal maturity, relative skeletal maturity and percentage of predicted adult stature. A representative sample of 6,029 Flemish girls aged 6-16 years of age was investigated. Age specific correlations between adiposity and biological maturity indicators were calculated and in each age group the fattest 5% were compared with the leanest 5%. Adiposity was estimated from the sum of five skinfolds (biceps, triceps, subscapular, suprailiac and medial calf). Skeletal age was assessed according to the Tanner-Whitehouse technique. Relative skeletal age was calculated as the difference between skeletal age and chronological age and percentage of predicted adult stature was calculated according to the Tanner-Whitehouse Mark II regression technique. Correlations between adiposity and maturity indicators are positive, but vary between r = 0.00 and r = 0.39. When stature is statistically controlled, correlations are reduced slightly. The 5% fattest girls are equally advanced (0.2 to 1.2 years) as the 5% leanest girls are delayed (0.0 to 0.9 years) in skeletal maturation. Attained statures are consistent with the maturity data and indicate that size differences between fat and lean girls are primarily due to maturity differences. It was concluded that during childhood and adolescence, fatness is associated with advanced and leanness with delayed biological maturity status. This association seems to have long term effects that merit further study.

Adipose Tissue↗
PubMed1993

Fractures, physical activity, and growth velocity in adolescent Belgian boys.

The relationship of fractures to physical activity and growth velocity in stature and metacarpal II bone dimensions was investigated in adolescent Belgian boys. Peak fracture incidence occurred between 12 and 14 yr of age and preceded the age at peak height velocity. The peak fracture rate occurred during mid adolescence (+/- 2 SD of the age at peak height velocity) and was twice as high as the rates before and after this period. The majority of fractures occurred during active participation in sports and general physical activities. The age at peak growth velocity for metacarpal cortical thickness, an indirect measure of bone mineral content, was about 6 months later than the ages at peak height velocity and peak growth velocity for metacarpal length. Peak fracture incidence occurred during a period when the amount of time spent in sports physical activity was low compared with later years. A lag in cortical bone thickness and mineralization, relative to linear skeletal growth, and unknown factors associated with active participation in sports, rather than an increase in the amount of physical activity, appear to be the predominant factors associated with the increased fracture incidence in Belgian boys during the growth spurt.

Adolescent↗
PubMed1992

Physical activity and growth, maturation and performance: a longitudinal study.

The effects of increased physical activity upon physical growth, maturation and performance were investigated in samples of 32 active and 32 nonactive Belgian boys followed longitudinally from 13 to 18 yr of age. Active boys participated in sports activities for more than 5 h.wk-1.yr-1 during each of the first 3 yr of the study, in addition to compulsory physical education. Nonactive boys participated in less than 1.5 h.wk-1.yr-1 during the first 3 yr of the study, but did participate in required school physical education. Anthropometric dimensions included lengths, breadths, circumferences, and skinfolds. A physical fitness test battery was administered at each observation including nine health- and performance-related tests. Skeletal maturation was assessed; sociocultural determinants and sports participation were obtained through written questionnaires verified by a control interview. No significant effects of increased physical activity were observed on growth in somatic dimensions, including skinfolds, age at peak height velocity, skeletal maturation, and most of the physical fitness components. More active boys obtained better results from 14 yr onward only for pulse recuperation and for bent arm hang. These results can be generalized to the average population but do not necessarily apply for highly trained and selected elite athletes.

Adolescent↗
PubMedDate not supplied

Adolescent physical performance and adult physical activity in Flemish males.

Limited information is available about the associations between adolescent fitness levels and adult physical activity. In the present study, these associations are investigated using different indicators of physical activity. It is hypothesized that both health- and performance-related fitness characteristics, observed during the adolescent period, contribute equally to the explained variance in adult physical activity levels. Subjects were 109 Flemish males followed over a period of 27 years from 13 to 40 years of age in the Leuven Longitudinal Study on Lifestyle Fitness and Health. Performance and health-related fitness characteristics were observed during the growth period and at 40 years of age. The Work Index, Leisure Time Index, and Sport Index of the Baecke questionnaire were used as indicators of physical activity together with triaxial accelerometry. Multiple regression and discriminant analyses contrasting extreme quintiles of activity groupings were used to analyse the associations. Only the Baecke Sport Index showed consistent significant associations (R2 = 0.03 to R2 = 0.23) with adolescent fitness levels observed at 13, 15, and 18 years. When upper and lower quintiles were contrasted, fitness characteristics observed at the three age levels during adolescence were significantly different for each of the three indices of the Baecke questionnaire at 40 years of age. Lowest associations (R2 = 0.09 to R2 = 0.17) were found for the Work Index, followed by the Leisure Time Index (R2 = 0.12 to R2 = 0.28) and Sport Index (R2 = 0.25 to R2 = 0.43). Highest associations were evident for the 18- to 40-year interval. Performance- and health-related fitness characteristics explain equally well the variance in physical activity indicators.

Adolescent↗
PubMedDate not supplied

Allometric relationship between body size and peak VO2 relative to age at menarche.

The present study examined allometric coefficients relating peak VO2 and body size relative to the time of menarche. Peak oxygen uptake (peak VO2) during exercise on a bicycle ergometer, stature and body mass were measured at annual intervals in a mixed-longitudinal sample of 40 active girls from 11 to 14 years of age. The girls were interviewed about their menarcheal status at each examination. The data were treated relative to the time before and after menarche: 2 years before (n = 18), 1 year before (n = 26), during the year of menarche (+/- 6 months, n = 32), 1 year after (n = 35) and 2 years after menarche (n = 22). Allometric coefficients were calculated for each of the five menarcheal groups based on logarithmic transformations of peak VO2 and body mass and peak VO2 and stature. The major axis of VO2 and body mass or stature (log transformed) was also calculated. This is the most appropriate slope for comparison with theoretical allometry coefficients. Mean peak VO2 increases from 2.1 +/- 0.19 L 2 years before menarche to 2.3 +/- 0.26 L 2 years after menarche. The slope of the major axis for body mass is always higher (0.508-0.926) than that for the allometric coefficient (0.323-0.591) in each of the menarcheal groups. The major axis slope and allometric coefficient are lowest between body mass and peak VO2 during the year of menarche. The slope of the major axis is below the theoretical allometric coefficients assuming geometric or elastic similarity, 2/3 or 3/4, before and at menarche and increases after menarche. Although the differences are not statistically significant, the results suggest that the relationship between body mass and peak VO2 at menarche is lower compared with relationships before and after this maturational landmark. Allometric coefficients for stature relative to peak VO2 show a similar pattern.

Adolescent↗
PubMedDate not supplied

Longitudinal study of ontogenetic allometry of oxygen uptake in boys and girls grouped by maturity status.

The utility of removing the confounding effect of body mass on oxygen uptake by simply dividing the measured values by mass has been questioned: Allometric transformation or calculation of covariance analysis have been proposed as more appropriate alternatives. This study hypothesized that scaling factors for individual youths differ with maturity status. Peak oxygen uptake (peak VO2) during exercise on a bicycle ergometer, stature and body mass were measured at annual intervals in 47 active boys and 31 active girls from 11 to 14 years of age. All subjects attended sport schools during the study. The children were classified into two maturity categories, early and average (for the sake of sample size and consistency between sexes), and late on the basis of individual stature velocities in boys and age at menarche in girls. Individual data for peak VO2 were normalized for differences in body mass by double logarithmic transformation and regression analysis (ontogenetic allometry). Individual allometric coefficients (mean +/- SD) for boys showing a good fit were, respectively, 0.799 +/- 0.239 and 0.536 +/- 0.141 in early and average maturing boys combined and in late maturing boys. Logarithmic transforms of VO2 and mass were highly related (r > 0.90) in 10 of 16 early and average maturers, and in 18 of 31 late maturers. Corresponding individual allometric coefficients in girls were more variable, and the logarithmic transforms of VO2 and mass were not highly related (r < 0.70). Similar results were obtained for the relationships between the logarithmic transforms of VO2 and stature. The evidence thus suggests that in boys scaling VO2 for body mass varies with maturity status of the individual, and that there is considerable inter-individual variation in scaling coefficients during early and mid-adolescence. The increase in peak VO2 in active girls 11-14 years is not related to the increase in body mass or stature in the majority.

Adolescent↗
PubMedDate not supplied

The contribution of biological maturation to the strength and motor fitness of children.

The interrelationships among skeletal maturity, body size, strength and motor fitness were examined in American children 7-12 years of chronological age (CA). A total of 391 Black (184 boys, 207 girls) and 349 White (193 boys, 156 girls) children participated in the study. Biological maturity was assessed by the Tanner-Whitehouse II method, 20 bone skeletal ages (SA). Strength items included right and left grip strength, and pushing and pulling strength of the shoulders. Motor fitness items included a 35-yard dash, the standing long jump, and softball throw for distance. The standardized residuals of SA on CA (AG) were used to represent the effects of SA, independent of CA. Interaction terms were also computed by multiplying standardized values of stature (ST), body mass (MA), and AG together in all combinations. Regression analyses showed that the strongest predictor of strength was MA, while AG was the best predictor of motor performance. The interaction terms were also significant predictors of performance, explaining between 2% and 9% of the variance in 19 of the 41 significant regressions. The results highlight the complexity of the interrelationships among body size, biological maturation, strength and motor fitness. The effects of SA in children 7-12 years of age are expressed mainly through body size, but SA apparently influences motor fitness more so than muscular strength.

Body Height↗