Common synaptic inputs and persistent inward currents of vastus lateralis motor units are reduced in older male adults

Although muscle atrophy may partially account for age-related strength decline, it is further influenced by alterations of neural input to muscle. Persistent inward currents (PIC) and the level of common synaptic inputs to motoneurons influence neuromuscular function. However, these have not yet been described in the aged human quadriceps. High-density surface electromyography (HDsEMG) signals were collected from the vastus lateralis of 15 young (mean ± SD, 23 ± 5 y) and 15 older (67 ± 9 y) men during submaximal sustained and 20-s ramped contractions. HDsEMG signals were decomposed to identify individual motor unit discharges, from which PIC amplitude and intramuscular coherence were estimated. Older participants produced significantly lower knee extensor torque (p < 0.001) and poorer force tracking ability (p < 0.001) than young. Older participants also had lower PIC amplitude (p = 0.001) and coherence estimates in the alpha frequency band (p < 0.001) during ramp contractions when compared to young. Persistent inward currents and common synaptic inputs are lower in the vastus lateralis of older males when compared to young. These data highlight altered neural input to the clinically and functionally important quadriceps, further underpinning age-related loss of function which may occur independently of the loss of muscle mass.</p

Muscle volume, muscle mass, and strength changes following resistance training.

<p>The absolute increase in A) Quadriceps muscle volume determined by MRI, B) Fat free bone free mass determined by DXA, C) Leg press 1RM and D) Chest press 1RM. Each dot represents a single subject, the lines show the group mean change and the standard deviation of the mean. All increases were significantly different from zero (i.e., an increase from pre training P<0.05).</p

Relationship between muscle hypertrophy and potential correlates.

<p>A) The relationship between changes in muscle volume as measured by MRI and the Myofibrillar fractional synthetic rate (FSR) measured from 1 to 6 hours after an acute bout of resistance exercise and nutrition before the start of the resistance training period (r = 0.10, P = 0.67). B) The relationship between changes in muscle volume as measured by MRI and 4E-BP1 phosphorylation at Thr37/46 measured 1 hour after an acute bout of resistance exercise and nutrition before the start of the resistance training period (r = 0.42, P = 0.05).</p

Myofibrillar Protein synthesis.

<p>FSR is calculated at rest and after an acute bout of resistance exercise and protein ingestion prior to the start of the resistance training period. The other rates were calculated from 1 to 3–6 hours after the resistance exercises. Each circle, square, and triangle represents a single subject at rest, 1–3 and 3–6 hours post exercises respectively * Significantly different than rest P<0.05.</p

Phosphorylation of anabolic signalizing proteins.

<p>The results are expressed as fold changes from rest at 1, 3 and 6) mTOR phosphorylation at Ser2448, B) Akt phosphorylation at Ser473, C) 4E-BP1 phosphorylation at Thr37/46 and D) rpS6 phosphorylation at Ser240/244. * Significantly different from rest P<0.05. † Signficantly different from 1 and 3 hour time points P<0.05.</p

Quantitative SAM analysis using a continuum of age versus gene expression produces network hubs that are activated with human muscle age.

<p>Using a total of 97 U133+2 Affymetrix gene-chips newly produced from two independent studies, the DRET study and the HERITAGE family study we produced a novel analysis that relied on the full age-range present in these data sets. A) We first found a set of genes that co-varied with age in the DRET study and then confirmed that 580 of these were also related to age in the HERITAGE study. Mitochondrial genes were not a feature of this linear age vs gene analysis. We then mapped the Affymetrix probe-sets to the IPA database and examined the up-stream analysis output. We found in IPA that the age-related dataset was consistent with the activation of the PGR (z-score = 2.6 and p-value = 0.001) and RXR (z-score = 2.0 and p-value = 0.0001) proteins and 5-fluorouracil agonism (Z-score = 2.2 and p-value = 0.0005). B) We noted that some members of these age-related networks were also associated with lean mass gains in humans. However about 50% of the common genes were positively associated with lean mass gain and age; and 50% were regulated in a discordant manner. Clearly some responses can be causal, some may be purely correlative and some may represent compensatory events.</p

Baseline biochemical and physiological characteristics of the DRET cohort.

<p>Baseline biochemical and physiological characteristics of the DRET cohort.</p

Inhibition of the mTOR-related expression network is correlated with gains in lean mass following RET.

<p>A) Quantitative SAM analysis was used to relate the change in RNA expression in response to 10 wk RET in 44 subjects. The change in gene expression was related to the change in lean mass (%) and a false discovery rate calculated based on permutation of the subject labels. Data were imported into IPA and 384 genes (FDR<5%) could be mapped to the data-base for up-stream analysis. An active rapamycin signature, equating to <i>inhibition</i> of mTOR signaling was discovered (Z-score = 2.8 for directional consistency; <i>P</i>-value for transcript overlap p = 1.4×10⁻³⁰). B) Given the strength of the negative statistical association between the rapamycin signature, we then plotted the data to establish the precise nature of the relationship. We presented the mean gains in lean mass by quartiles establishing that 25% of the subject demonstrated negligible changes in lean mass. C) We selected a representative subset of the genes from <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003389#pgen-1003389-g002" target="_blank">Figure 2A</a> and plotted the mean changes with respect to lean mass changes. This established that those with the greatest lean mass actually had a <i>reduction</i> in mTOR related genes with RET and not simple a lesser increase as one might have expected from first inspection of <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003389#pgen-1003389-g002" target="_blank">Figure 2A</a>.</p

Differential gene expression analysis, contrasting young and old subjects, does not produce a reliable biomarker signature of age.

<p>Several attempts have been to define a set of genes that differ in skeletal muscle between young and old human subjects. We re-analysed three of the most robust and largest human studies with common methods, including our new study, and contrasted the genes identified to be differentially regulated using SAM analysis and Gene Ontology analysis. No common pattern of differential gene expression could be found using this analysis method indicating that no prior gene signature for muscle ageing can be considered a reliable marker of muscle age in humans. Gene ontology analysis found that both the Trappe and Melov data sets had modest enrichment in mitochondrial genes, which were down-regulated with age however this was not true for the DRET study and both Melov and Trappe data-sets had elderly with much lower physical fitness levels making it impossible to attribute these changes to age <i>per se</i> with differential expression analysis.</p

Using principal component analysis to evaluate the relationship between physiological and acute protein signaling events to RET induced gains in lean mass.

<p>A) Change in lean mass following 20 wk RET and a number of physiological parameters which demonstrated the most variance were scaled to a common value and plotted using principal component analysis in R. Principal component (PC) 1 captured the major variance in lean mass gains across subjects however none of the commonly postulated physiological parameters varied with lean mass (linear regression analysis demonstrated no significant association also). PC2, the second largest proportion of independent variance also demonstrated no association between factors such as fiber type or age and gains in lean mass. B) Phospho-protein signaling 2 hr after a combined exercise and nutrition acute intervention (to promote anabolic signaling) were scaled and plotted with change in lean mass following 20 wk RET. Again these acute signaling events shared little common variance in either PC1 or PC2 with changes in lean mass with 20 wk RET.</p