Publications

We hypothesized that greater cardiorespiratory fitness is associated with lower odds of having unfavorable brain MRI findings.We studied 565 healthy, middle-aged, black and white men and women in the CARDIA (Coronary Artery Risk Development in Young Adults) Study. The fitness measure was symptom-limited maximal treadmill test duration (Maxdur); brain MRI was measured 5 years later. Brain MRI measures were analyzed as means and as proportions below the 15th percentile (above the 85th percentile for white matter abnormal tissue volume).Per 1-minute-higher Maxdur, the odds ratio for having less whole brain volume was 0.85 (p = 0.04) and for having low white matter integrity was 0.80 (p = 0.02), adjusted for age, race, sex, clinic, body mass index, smoking, alcohol, diet, physical activity, education, blood pressure, diabetes, total cholesterol, and lung function (plus intracranial volume for white matter integrity). No significant associations were observed between Maxdur and abnormal tissue volume or blood flow in white matter. Findings were similar for associations with continuous brain MRI measures.Greater physical fitness was associated with more brain volume and greater white matter integrity measured 5 years later in middle-aged adults.

A Reply to Rebuttal: The Rsal Polymorphism in the α-Fibrinogen Gene and Response of Plasma Fibrinogen to Physical Training -

Objectives We investigated whether high responsiveness or low responsiveness to exercise training aggregates in the same individuals across seven cardiometabolic traits. Methods A total of 564 adults (29.2% black, 53.7% female) from the HERITAGE family study completed a 20-week endurance training programme (at 55%–75% of participants’ maximal oxygen uptake (VO 2 max)) with VO 2 max, per cent body fat, visceral adipose tissue, fasting levels of insulin, high-density lipoprotein cholesterol, small low-density lipoprotein particles and inflammatory marker GlycA measured before and after training. For each exercise response trait, we created ethnicity-specific, sex-specific and generation-specific quintiles. High responses were defined as those within the 20th percentile representing the favourable end of the response trait distribution, low responses were defined as the 20th percentile from the least favourable end, and the remaining were labelled as average responses. Results Only one individual had universally high or low responses for all seven cardiometabolic traits. Almost half (49%) of the cohort had at least one high response and one low response across the seven traits. About 24% had at least one high response but no low responses, 24% had one or more low responses but no high responses, and 2.5% had average responses across all traits. Conclusions Interindividual variation in exercise responses was evident in all the traits we investigated, and responsiveness did not aggregate consistently in the same individuals. While adherence to an exercise prescription is known to produce health benefits, targeted risk factors may not improve.

No abstract is provided for this article.

WILMORE, J. H., P. R. STANFORTH, J. GAGNON, T. RICE, S. MANDEL, A. S. LEON, D. C. RAO, J. S. SKINNER, and C. BOUCHARD. Heart rate and blood pressure changes with endurance training: The HERITAGE Family Study. Med. Sci. Sports Exerc., Vol. 33, No. 1, 2001, pp. 107–116. Purpose: The purpose of this study was to determine the magnitude of change in resting and exercise heart rate (HR) and blood pressure (BP), by race, sex, and age, after a 20-wk endurance training program in 507 healthy and previously sedentary subjects from the HERITAGE Family Study. Methods: After baseline measurements, subjects exercised on cycle ergometers 3 d·wk-1 for a total of 60 exercise sessions starting at 55% of O2max for 30 min·session−1 and building to 75% of O2max for 50 min·session−1 for the last 6 wk. HR and BP at rest and during exercise (50 W, 60% of O2max, maximal exercise) were each determined in duplicate on two different days both before and after training (resting values at 24-h and 72-h posttraining). Results: After the period of training, there was a small decrease in resting HR (−2.7 to −4.6 beats·min-1 across groups at 72-h posttraining), and small changes (i.e., < 3 mm Hg) in resting systolic (SBP), diastolic (DBP), and calculated mean BP (MBP), which varied by race, sex, and age. During exercise at the same absolute work rate (50 W), HR, SBP, DBP, and MBP were all significantly reduced, with greater reductions in HR in women compared with men, and greater reductions in BP in blacks and older subjects compared with whites and younger subjects, respectively. At the same relative work rate (60% O2max), HR, DBP, and MBP were reduced, but SBP remained unchanged. Blacks had a greater reduction in DBP, but whites had a greater reduction in HR. Finally, at maximal exercise, there was a small decrease in HR, with men and whites decreasing more than women and blacks; an 8 mm Hg increase in SBP, with men increasing more than women; a 4 mm Hg decrease in DBP, with blacks decreasing more than whites; and no change in MBP. Conclusion: In conclusion, the reductions in resting HR and BP with training were generally small, but the reductions during exercise were substantial and clinically important, with the older and the black populations experiencing greater reductions.

The relationship between physique and metabolic fitness was examined in a sample of 413 boys and 343 girls 9-18 years of age from Phase 1 of the Québec Family Study. Physique was assessed using Heath-Carter anthropometric somatotype. Indicators of metabolic fitness used were plasma triglyceride levels (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) estimated using the procedures of Friedewald et al. (Clin. Chem. 18:499-502, 1972), and blood glucose levels (GLY). The sample was divided into three age groups, 9-12, 13-15, and 16-18 years of age. A partial canonical correlation analysis was used to quantify the relationship between the standardized somatotype and metabolic fitness variables (z-transformed), with age as the covariate. In both boys and girls the first canonical correlation is significant(p<.001), which indicates that there is a significant relationship between the physique and metabolic fitness variables. By age group, the 16-18 year old boys, and the 9-12, 13-15 and 16-18 year old girls demonstrate significant canonical correlations (p<.03). The makeup of the canonical variates is similar for all age groups. Generally, the physique domain is characterized by a positive loading for ectomorphy and negative loadings for endomorphy and mesomorphy. The metabolic fitness domain has a positive loading for HDL-C and negative loadings for TG, LDL-C, and GLY. The results suggest that in youth 9-18 years, a physique characterized by high endomorphy and mesomorphy is associated with higher levels of TG. LDL-C, and GLY, and lower levels of HDL-C.

Dans le contexte pénitentiaire actuel de la lutte contre la désocialisation, des associations offrent un soutien psychologique et social aux familles des prisonniers. La recherche-action « Regards d’enfants sur l’incarcération » dont rend compte cet article, menée en collaboration avec deux de ces associations, consiste à créer des groupes de soutien pour les enfants qui ont un parent ou un proche en prison. L’objectif de cette recherche-action est d’évaluer les conditions, moyens et outils qui permettraient d’offrir une possibilité d’échange aux enfants pour leur rendre possible de partager leurs expériences et d’exprimer ce qui ne peut être dit à des parents, des proches et à leur environnement social (amis, école, voisins...). Les résultats confirment le besoin manifeste de renforcer les pratiques professionnelles autour des familles, et notamment des enfants, grands absents dans nos dispositifs d’accompagnement français.

Background A poor diet is a risk factor for chronic diseases such as obesity, cardiovascular disease, hypertension, and some cancers. Twin and family studies suggest that genetic factors potentially influence energy and nutrient intakes. Objective We sought to identify genomic regions harboring genes affecting total energy, carbohydrate, protein, and fat intakes. Design We performed a genomic scan in 347 white sibling pairs and 99 black sibling pairs. Dietary energy and nutrient intakes were assessed by using Willett's food-frequency questionnaire. Single-point and multipoint Haseman-Elston regression techniques were used to test for linkage. These subjects were part of the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study, a multicenter project undertaken by 5 laboratories. Results In the whites, the strongest evidence of linkage appeared for dietary energy and nutrient intakes on chromosomes 1p21.2 (P = 0.0002) and 20q13.13 (P = 0.00007), and that for fat intake appeared on chromosome 12q14.1 (P = 0.0013). The linkage evidence on chromosomes 1 and 20 related to total energy intake rather than to the intake of specific macronutrients. In the blacks, promising linkages for macronutrient intakes occurred on chromosomes 12q23-q24.21, 1q32.1, and 7q11.1. Several potential candidate genes are encoded in and around the linkage regions on chromosomes 1p21.2, 12q14.1, and 20q13.13. Conclusions These are the first reported human quantitative trait loci for dietary energy and macronutrient intakes. Further study may refine these quantitative trait loci to identify potential candidate genes for energy and specific macronutrient intakes that would be amenable to more detailed molecular studies.

Summary The genetics of human fatness has been the subject of many recent studies, motivated by the increased morbidity and mortality associated with obesity, as well as the increasing prevalence of overweight and obesity. The body-mass index (BMI) and fat mass (FM), measured by underwater weighing, were assessed for 1,630 individuals from ∼300 families from phase 1 of the Quebec Family Study. The two phenotypes are highly correlated (∼.8) in adults, and previous segregation analysis revealed evidence for a recessive major gene for each trait. In our study, we utilized bivariate segregation analysis to determine the source(s) of phenotypic correlation—namely, a pleiotropic major gene, shared familial factors/polygenes, or shared nontransmitted environmental factors. Analysis was performed by use of the Pedigree Analysis Package, with extensions to the bivariate case. Tests of hypotheses provided evidence for two pleiotropic recessive loci, together accounting for 64% and 47% of the variance in BMI and FM, respectively. Under the model, all sources of phenotypic correlation were significant: 73% of the covariance was attributed to the pleiotropic major loci, 8% to residual familial effects, and 19% to nontransmitted environmental factors. The high degree of genetic identity between the two traits is not surprising, since the BMI often is used as a surrogate for FM; however, simultaneous analysis of both phenotypes enabled the detection of a second major locus, which apparently does not affect extreme overweight (as does the primary major locus) but which affects variation in the “normal” range.

Introduction: A recent study utilized plasma proteins to identify organ-specific aging signatures that were related to health and disease. However, it is unknown whether exercise interventions can change predicted organ aging. Methods: We measured 4979 plasma proteins using the SomaScan assay before and after 20 weeks of endurance exercise training in 673 Black and White adults from the HERITAGE Family Study. Organ age was estimated for 11 major organs using different panels of proteins and age gap was calculated as the difference between predicted age and the LOWESS regression estimate of the population mean. Accelerated aging was defined as an age gap value ±2SD from the mean. Paired t-tests examines changes in predicted organ age with exercise training. Results: We found low-to-modest correlations between predicted organ age and chronological age for 9 of 11 traits ( Table 1 ). These correlations were almost exclusively observed in the oldest (age quartile 4: ages 47.6-65.9) and not younger participants (age quartiles 1-3: age&lt;47.6 yrs) ( Table 1 ). A total of 37% of participants had accelerated aging in at least one organ at baseline, with 15% having 2 or more accelerated organ ages, which was balanced across chronological age quartiles. Exercise training did not significantly alter any of the predicted organ ages in the total sample or by age quartile, with wide interindividual variability in the training responsiveness of predicted organ ages. Moreover, although some participants reduced their number of accelerated organ age traits after training, the prevalence of accelerated organ aging remained 37% at post-training. Conclusions: We found that existing proteomic organ aging signatures only replicated in the oldest (middle aged) HERITAGE participants, which likely reflects the fact the signatures were derived in older populations. Importantly, organ aging signatures were not sensitive to exercise training, which likely limits their potential clinical utility.

No abstract is provided for this article.

Adiponectin, an insulin-sensitizing and anti-atherosclerotic adipocytokine, exists in different isoforms. The high-molecular weight (HMW) isoform may be more biologically active. PURPOSE: To examine the effect of a vigorous-intensity endurance exercise training program on serum HMW adiponectin concentration in a sample of black and white men and women aged 17 to 65 years (n=515). METHODS: Serum HMW adiponectin concentrations from before and after a 20-week exercise program were analyzed via ELISA. RESULTS: When controlling for age, HMW adiponectin concentration before training was not related to VO2max in men or women (r=−0.028 and −0.031, respectively, p>0.05). As we have previously found with total serum adiponectin, the HMW isoform decreased slightly as a result of exercise training (before vs. after: 3.01±0.10 vs. 2.53±0.09, mean±SE, p<0.001). This decrease was significant within each of the four race/sex groups (p=0.04). Baseline HMW adiponectin was related to intra-abdominal and subcutaneous abdominal fat areas and overall body fat mass (r=−0.287, −0.185, and −0.154, respectively, p=0.001). Training-related change in HMW adiponectin was not related to changes in these fat variables (r=−0.058, −0.089, and −0.014, p>0.05). However, significant change relationships were present in black women (r=−0.253, −0.338, and −0.367, p=0.02). HMW adiponectin and insulin sensitivity (derived from minimal modeling after intravenous glucose tolerance testing) were related at baseline (r=0.224, p<0.001), but training−induced changes were not related (r=0.006, p>0.05). At baseline, HMW adiponectin was related to HDL-cholesterol and triglyceride concentrations (r=0.405 and −0.210, p<0.001). A modest change relationship was present for HDL-cholesterol (r=0.162, p<0.001), but not triglyceride (r=0.027, p>0.05). CONCLUSIONS: Serum HMW adiponectin concentration did not increase in response to 20 weeks of vigorous-intensity exercise training. Overall, exercise-induced change in HMW adiponectin was not strongly related with changes in other factors associated with cardiometabolic risk. These results largely mirror those of total serum adiponectin previously found in the HERITAGE sample. Funded by the American Heart Association (Mid-Atlantic Affiliate) and multiple grants from NIH-NHLBI.