Louis Pérusse

The Human Gene Map for Performance and Health-Related Fitness Phenotypes: The 2005 Update

The current review presents the 2005 update of the human gene map for physical performance and health-related fitness phenotypes. It is based on peer-reviewed papers published by the end of 2005. The genes and markers with evidence of association or linkage with a performance or fitness phenotype in sedentary or active people, in adaptation to acute exercise, or for training-induced changes are positioned on the genetic map of all autosomes and the X chromosome. Negative studies are reviewed, but a gene or locus must be supported by at least one positive study before being inserted on the map. By the end of 2000, in the early version of the gene map, 29 loci were depicted. In contrast, the 2005 human gene map for physical performance and health-related phenotypes includes 165 autosomal gene entries and QTL, plus five others on the X chromosome. Moreover, there are 17 mitochondrial genes in which sequence variants have been shown to influence relevant fitness and performance phenotypes. Thus, the map is growing in complexity. Unfortunately, progress is slow in the field of genetics of fitness and performance, primarily because the number of laboratories and scientists focused on the role of genes and sequence variations in exercise-related traits continues to be quite limited.

The prediction of abdominal visceral fat level from body composition and anthropometry: ROC analysis.

OBJECTIVE: To evaluate the merit of body mass index (BMI), % body fat, waist circumference and waist-to-hip ratio as predictors of abdominal visceral fat (AVF) level.DESIGN: Cross-sectional measurements obtained from 458 female and 331 male subjects of French Canadian descent with an age range from 18–72 y.MEASUREMENTS: AVF level was assessed by computed tomography. BMI was calculated as weight (in kg) divided by stature2 (in m), body density was derived from underwater weighing and % body fat was computed from the estimate of body density with the Siri equation. Waist-to-hip ratio was calculated as waist circumference divided by hip circumference. Receiver operating characteristic (ROC) curves were used to identify the optimal cut-off points.RESULTS: In younger women (<40 y, n=258), waist-to-hip ratio was the poorest predictor of AVF level with areas under the ROC curves (Az) ranging from 0.684–0.716, sensitivity (Sen) from 63.3–68.8% and specificity (Spe) from 64.0–67.5%, whereas the Az, Sen and Spe for other predictors ranged from 0.924–0.983, 87.0–96.8, and 83.4–92.7, respectively. The same trend was observed in older (≥40 y, n=200) women, although differences between waist-to-hip ratio and other predictors were less pronounced. In older men, waist circumference was the best overall predictor (Az from 0.88–0.92), whereas BMI showed the lowest Az values (0.831–0.875, P≤0.001 vs waist circumference). In younger men, BMI had the smallest Az (P<0.007 vs others) with the lowest AVF cut-off point (100 cm2). However, with higher AVF cut-offs the differences were not significant.CONCLUSION: Waist circumference is the best overall predictor of abdominal visceral obesity, whereas in women waist-to-hip ratio is a poor indicator of AVF and its use as a surrogate measure of visceral fat should be avoided.

Aerobic performance in brothers, dizygotic and monozygotic twins.

Forty-two brothers, 66 dizygotic twins of both sexes and 106 monozygotic twins of both sexes, 16 to 34 yr of age, took part in this study that was designed to investigate the effect of heredity in aerobic performance. Maximal oxygen uptake (VO2 max), maximal heart rate (HR max), maximal ventilation, and maximal oxygen pulse were obtained from a progressive ergocycle test to exhaustion. Total work output in a 90-min maximal ergocycle test was also determined in the twins. Fat-free weight was estimated from body density measurements obtained through underwater weighing. Aerobic performance scores were adjusted for age (brothers), and age and sex (dizygotic and monozygotic twins) by regression procedures. Dizygotic twins and brothers of same sibship exhibited about the same level of resemblance for all variables or were only slightly different, with the exception of HR max. Monozygotic pairs were generally more alike than the other sibs, as suggested by the intra-class coefficients. Twin data were used to compute the genetic effects. The within-pair estimate of genetic variance revealed that it was significant (P less than or equal to 0.05) for all variables except VO2 max X kg-1 fat-free weight X min-1. In the case of HR max, the among-pairs component estimate had to be used, and it also proved significant (P less than or equal to 0.01). The size of the genetic effect was computed from three different methods, and it reached about 40% for VO2 max X kg-1 X min-1, 50% for HR max, 60% for maximal oxygen pulse and maximal ventilation, and 70% for 90-min work output X kg-1.(ABSTRACT TRUNCATED AT 250 WORDS)

Genome-Wide Linkage Analysis of Systolic and Diastolic Blood Pressure The Québec Family Study

BackgroundBlood pressure (BP), an important risk factor for coronary heart disease, is a complex trait with multiple genetic etiologies. While some loci affecting BP variation are known (eg, angiotensinogen), there are likely to be novel signals that can be detected with a genome scan approach. Methods and ResultsA genome-wide scan was performed in 125 random and 81 obese families participating in the Québec Family Study. A multipoint variance-components linkage analysis of 420 markers (353 microsatellites and 67 restriction fragment length polymorphisms) revealed several signals (P <0.0023) for systolic BP on 1p (D1S551, ATP1A1), 2p (D2S1790, D2S2972), 5p (D5S1986), 7q (D7S530), 8q (CRH), and 19p (D19S247). Suggestive evidence (0.0023<P <0.01) was found on 3q, 10p, 12p, 14q, and 22q. The results were encouraging for HSD3B1 (P <0.03), AGT (P <0.03), ACE (P <0.02), and adipsin (P <0.005) but null with regard to other candidates (eg, renin, and glucocorticoid and adrenergic receptors). ConclusionsMultiple linkage regions support the notion that risk for hypertension is due to multiple (ie, oligogenic) susceptibility loci. Comparisons across the complete, random, and obese samples suggest that some regions are specific to BP and others may involve obesity (eg, pleiotropy, epistasis, or gene-environment interaction). Some of these areas harbor known candidates. Others involve novel regions, some of which replicate previous reports and provide a focus for future studies to identify novel genes that influence interindividual variation in BP.

Identification of an obesity quantitative trait locus on mouse chromosome 2 and evidence of linkage to body fat and insulin on the human homologous region 20q.

Chromosomal synteny between the mouse model and humans was used to map a gene for the complex trait of obesity. Analysis of NZB/BINJ x SM/J intercross mice located a quantitative trait locus (QTL) for obesity on distal mouse chromosome 2, in a region syntenic with a large region of human chromosome 20, showing linkage to percent body fat (likelihood of the odds [LOD] score 3.6) and fat mass (LOD score 4.3). The QTL was confirmed in a congenic mouse strain. To test whether the QTL contributes to human obesity, we studied linkage between markers located within a 52-cM region extending from 20p12 to 20q13.3 and measures of obesity in 650 French Canadian subjects from 152 pedigrees participating in the Quebec Family Study. Sib-pair analysis based on a maximum of 258 sib pairs revealed suggestive linkages between the percentage of body fat (P < 0.004), body mass index (P < 0.008), and fasting insulin (P < 0.0005) and a locus extending approximately from ADA (the adenosine deaminase gene) to MC3R (the melanocortin 3 receptor gene). These data provide evidence that a locus on human chromosome 20q contributes to body fat and insulin in a human population, and demonstrate the utility of using interspecies syntenic relationships to find relevant disease loci in humans.

Stability of indicators of the metabolic syndrome from childhood and adolescence to young adulthood: the Québec Family Study

The stability of indicators of the metabolic syndrome from childhood and adolescence to young adulthood was examined. The sample included 76 males and 71 females measured between the ages of 8 and 18 years and again as young adults (12 year follow-up). Indicators included the sum of three trunk skinfolds (SF3), mean blood pressure (MBP), and fasting blood glucose (GLY), high-density lipoprotein cholesterol (HDL-C), ratio of total cholesterol to HDL-C (CHOL/HDL), and triglycerides (TG). The indicators were subjected to principal components analysis to obtain a composite risk factor index (RFI). Partial interage correlations, controlling for initial age and length of follow-up, were 0.70 and 0.50 for SF3, 0.40 and 0.54 for MBP, 0.58 and 0.56 for HDL-C, 0.51 and 0.57 for CHOL/HDL, 0.37 and 0.20 (NS) for TG, 0.30 and 0.14 (NS) for GLY, and 0.51 and 0.46 for the RFI, in males and females, respectively. The results indicate that indicators of the metabolic syndrome are moderately stable from childhood and adolescence into young adulthood.

Genetic Variants of FTO Influence Adiposity, Insulin Sensitivity, Leptin Levels, and Resting Metabolic Rate in the Quebec Family Study

OBJECTIVE—A genome-wide association study conducted by the Wellcome Trust Case Control Consortium recently associated single nucleotide polymorphisms (SNPs) in the FTO (fatso/fat mass and obesity associated) gene with type 2 diabetes. These associations were shown to be mediated by obesity. Other research groups found similar results in Europeans and Hispanics but not African Americans. The mechanism by which FTO influences obesity and type 2 diabetes is currently unknown. The present study investigated the role of two FTO SNPs (rs17817449 and rs1421085) in adiposity, insulin sensitivity, and body weight regulation, including energy intake and expenditure. RESEARCH DESIGN AND METHODS—We genotyped 908 individuals from the Quebec City metropolitan area that participated in the Quebec Family Study, a long-term study of extensively phenotyped individuals designed to investigate factors involved in adiposity. RESULTS—We found significant associations for both SNPs with several obesity-related phenotypes. In particular, rs17817449 was associated with BMI (P = 0.0014), weight (P = 0.0059), and waist circumference (P = 0.0021) under an additive model. In addition, this FTO SNP influenced fasting insulin (P = 0.011), homeostasis model assessment of insulin resistance (P = 0.038), and an insulin sensitivity index derived from an oral glucose tolerance test (P = 0.0091). Associations were also found with resting metabolic rate (RMR) (P = 0.042) and plasma leptin levels (P = 0.036). Adjustment for BMI abolished the associations with insulin sensitivity, RMR, and plasma leptin levels. CONCLUSIONS—These results confirm that genetic variation at the FTO locus contributes to the etiology of obesity, insulin resistance, and increased plasma leptin levels.

The PPAR-gamma P12A polymorphism modulates the relationship between dietary fat intake and components of the metabolic syndrome: results from the Québec Family Study

The metabolic syndrome is a complex disorder characterized by an atherogenic dyslipidemia resulting from the interaction between genetic and nutritional factors. The objective of this study was to examine in a cohort of 720 adults participating in the Québec Family Study (QFS) whether dietary fat interacts with the P12A polymorphism in the gene encoding the peroxisome proliferator‐activated receptor‐gamma (PPAR‐γ), a nuclear factor that regulates lipid and glucose homeostasis. Carriers of the A12 allele had a higher body mass index (BMI), waist circumference, fat mass as well as subcutaneous adipose tissue and visceral adipose tissue (VAT) areas both assessed by computed tomography than P12/P12 homozygotes. Total fat and saturated fat intakes estimated from a 3‐day food record were significantly correlated with several components of the metabolic syndrome in P12/P12 homozygotes. None of these expected associations were observed among carriers of the A12 allele. Furthermore, in a model including the PPAR‐γ P12A polymorphism, fat intake, age and gender, PPAR‐γ P12A and its interaction with fat intake were associated with BMI and waist circumference. Similar results were obtained when saturated fat intake replaced total fat intake into the model. When the two genotype groups were further classified into quartiles of total fat or saturated fat intake and their characteristics compared, an increase in fat intake was associated with an increase in waist circumference in P12/P12 homozygotes but not in A12 carriers. There was no difference in the waist circumference in carriers of the A12 allele whether the fat or the saturated fat intake was high or low. These results suggest that the PPAR‐γ P12A polymorphism can modulate the association between dietary fat intake and components of the metabolic syndrome.

Set points, settling points and some alternative models: Theoretical options to understand how genes and environments combine to regulate body adiposity

The close correspondence between energy intake and expenditure over prolonged time periods, coupled with an apparent protection of the level of body adiposity in the face of perturbations of energy balance, has led to the idea that body fatness is regulated via mechanisms that control intake and energy expenditure. Two models have dominated the discussion of how this regulation might take place. The set point model is rooted in physiology, genetics and molecular biology, and suggests that there is an active feedback mechanism linking adipose tissue (stored energy) to intake and expenditure via a set point, presumably encoded in the brain. This model is consistent with many of the biological aspects of energy balance, but struggles to explain the many significant environmental and social influences on obesity, food intake and physical activity. More importantly, the set point model does not effectively explain the ‘obesity epidemic’ – the large increase in body weight and adiposity of a large proportion of individuals in many countries since the 1980s. An alternative model, called the settling point model, is based on the idea that there is passive feedback between the size of the body stores and aspects of expenditure. This model accommodates many of the social and environmental characteristics of energy balance, but struggles to explain some of the biological and genetic aspects. The shortcomings of these two models reflect their failure to address the gene-by-environment interactions that dominate the regulation of body weight. We discuss two additional models – the general intake model and the dual intervention point model – that address this issue and might offer better ways to understand how body fatness is controlled.

Differential epigenomic and transcriptomic responses in subcutaneous adipose tissue between low and high responders to caloric restriction.

BACKGROUND Caloric restriction is recommended for the treatment of obesity, but it is generally characterized by large interindividual variability in responses. The factors affecting the magnitude of weight loss remain poorly understood. Epigenetic factors (ie, heritable but reversible changes to genomic function that regulate gene expression independently of DNA sequence) may explain some of the interindividual variability seen in weight-loss responses. OBJECTIVE The objective was to determine whether epigenetics and gene expression changes may play a role in weight-loss responsiveness. DESIGN Overweight/obese postmenopausal women were recruited for a standard 6-mo caloric restriction intervention. Abdominal subcutaneous adipose tissue biopsy samples were collected before (n = 14) and after (n = 14) intervention, and the epigenomic and transcriptomic profiles of the high and low responders to dieting, on the basis of changes in percentage body fat, were compared by using microarray analysis. RESULTS Significant DNA methylation differences at 35 loci were found between the high and low responders before dieting, with 3 regions showing differential methylation after intervention. Some of these regions contained genes known to be involved in weight control and insulin secretion, whereas others were localized in known imprinted genomic regions. Differences in gene expression profiles were observed only after dieting, with 644 genes being differentially expressed between the 2 groups. These included genes likely to be involved in metabolic pathways related to angiogenesis and cerebellar long-term depression. CONCLUSIONS These data show that both DNA methylation and gene expression are responsive to caloric restriction and provide new insights about the molecular pathways involved in body weight loss as well as methylation regulation during adulthood.