PPARα L162V underlies variation in serum triglycerides and subcutaneous fat volume in young males

<p>Abstract</p> <p>Background</p> <p>Of the five sub-phenotypes defining metabolic syndrome, all are known to have strong genetic components (typically 50–80% of population variation). Studies defining genetic predispositions have typically focused on older populations with metabolic syndrome and/or type 2 diabetes. We hypothesized that the study of younger populations would mitigate many confounding variables, and allow us to better define genetic predisposition loci for metabolic syndrome.</p> <p>Methods</p> <p>We studied 610 young adult volunteers (average age 24 yrs) for metabolic syndrome markers, and volumetric MRI of upper arm muscle, bone, and fat pre- and post-unilateral resistance training.</p> <p>Results</p> <p>We found the PPARα L162V polymorphism to be a strong determinant of serum triglyceride levels in young White males, where carriers of the V allele showed 78% increase in triglycerides relative to L homozygotes (LL = 116 ± 11 mg/dL, LV = 208 ± 30 mg/dL; p = 0.004). Men with the V allele showed lower HDL (LL = 42 ± 1 mg/dL, LV = 34 ± 2 mg/dL; p = 0.001), but women did not. Subcutaneous fat volume was higher in males carrying the V allele, however, exercise training increased fat volume of the untrained arm in V carriers, while LL genotypes significantly decreased in fat volume (LL = -1,707 ± 21 mm³, LV = 17,617 ± 58 mm³; p = 0.002), indicating a systemic effect of the V allele on adiposity after unilateral training. Our study suggests that the primary effect of PPARα L162V is on serum triglycerides, with downstream effects on adiposity and response to training.</p> <p>Conclusion</p> <p>Our results on association of PPARα and triglycerides in males showed a much larger effect of the V allele than previously reported in older and less healthy populations. Specifically, we showed the V allele to increase triglycerides by 78% (p = 0.004), and this single polymorphism accounted for 3.8% of all variation in serum triglycerides in males (p = 0.0037).</p

Genetic variation and exercise-induced muscle damage: implications for athletic performance, injury and ageing.

Prolonged unaccustomed exercise involving muscle lengthening (eccentric) actions can result in ultrastructural muscle disruption, impaired excitation-contraction coupling, inflammation and muscle protein degradation. This process is associated with delayed onset muscle soreness and is referred to as exercise-induced muscle damage. Although a certain amount of muscle damage may be necessary for adaptation to occur, excessive damage or inadequate recovery from exercise-induced muscle damage can increase injury risk, particularly in older individuals, who experience more damage and require longer to recover from muscle damaging exercise than younger adults. Furthermore, it is apparent that inter-individual variation exists in the response to exercise-induced muscle damage, and there is evidence that genetic variability may play a key role. Although this area of research is in its infancy, certain gene variations, or polymorphisms have been associated with exercise-induced muscle damage (i.e. individuals with certain genotypes experience greater muscle damage, and require longer recovery, following strenuous exercise). These polymorphisms include ACTN3 (R577X, rs1815739), TNF (-308 G>A, rs1800629), IL6 (-174 G>C, rs1800795), and IGF2 (ApaI, 17200 G>A, rs680). Knowing how someone is likely to respond to a particular type of exercise could help coaches/practitioners individualise the exercise training of their athletes/patients, thus maximising recovery and adaptation, while reducing overload-associated injury risk. The purpose of this review is to provide a critical analysis of the literature concerning gene polymorphisms associated with exercise-induced muscle damage, both in young and older individuals, and to highlight the potential mechanisms underpinning these associations, thus providing a better understanding of exercise-induced muscle damage

Adaptations in antagonist co-activation: Role in the repeated-bout effect

Eccentric exercise results in an adaptation which attenuates muscle damage from subsequent exercise—termed the “repeated-bout effect (RBE).” Purpose: Study examined antagonist co-activation and motor-unit recruitment strategy, assessed via dEMG, concomitant to the RBE. Methods: Nine participants performed 5 sub-maximal isometric trapezoid (ramp-up, hold, ramp-down) contractions at force levels corresponding to 50% and 80% of maximal isometric strength (MVC). Surface EMG signals of the biceps brachii were decomposed into individual motor-unit action potential trains. The relationship between mean firing rate (MFR) of each motor-unit and its recruitment threshold (RT) was examined using linear regression. Eccentric exercise was then performed until biceps brachii MVC had decreased by ~40%. Surface EMG of the biceps and triceps were collected during eccentric exercise. MVC, range-of-motion (ROM), and delayed onset muscle soreness (DOMS) were measured 24-hours, 72-hours, and 1-week following eccentric exercise. Three weeks later all procedures were repeated. Results: Changes in MVC (-32±14% vs -25±10%; p = 0.034), ROM (-11% vs 6%; p = 0.01), and DOMS (31.0±19mm vs 19±12mm; p = 0.015) were attenuated following the second bout of exercise. Triceps EMG was reduced (16.8±9.5% vs. 12.6±7.2%; p = 0.03) during the second bout of eccentric exercise. The slope (-0.60±0.13 vs -0.70±0.18; p = 0.029) and y-intercept (46.5±8.3 vs 53.3±8.8; p = 0.020) of the MFR vs. RT relationship was altered during contractions at 80% of MVC prior to the second bout of eccentric exercise. No changes were observed at 50% of MVC. Conclusion: A reduction in antagonist co-activation during the second bout of eccentric exercise suggests less total force was required to move an identical external load. This finding is supported by the increased negative slope coefficient and an increased y-intercept of the linear relationship between RT and MFR.Funded by University of Oklahoma Graduate College Robberson Grant.Ye

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 x 10(-8)) or suggestively genome wide (p < 2.3 x 10(-6)). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/ near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/ near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass

Lessons Learned in Modeling Schizophrenic and Depressed Responsive Virtual Humans for Training

This paper describes lessons learned in developing the linguistic, cognitive, emotional, and gestural models underlying virtual human behavior in a training application designed to train civilian police officers how to recognize gestures and verbal cues indicating different forms of mental illness and how to verbally interact with the mentally ill. Schizophrenia, paranoia, and depression were all modeled for the application. For linguistics, the application has quite complex language grammars that captured a range of syntacric structures and semantic categories. For cognition, there is a great deal of augmentation to a plan-based transition network needed to model the virtual human&apos;s knowledge. For emotions and gestures, virtual human behavior is based on expert-validated mapping tables specific to each mental illness. The paper presents five areas demanding continued research to improve virtual human behavior for use in training applications