Maximal oxygen uptake (V̇o2max) and the amount of type 1 fibers are interrelated, but the underlying unifying molecular mechanisms are poorly understood. To explore these mechanisms, we related gene expression profiles in skeletal muscle biopsies of 43 age-matched men from published datasets with V̇o2max and the amount of type 1 fibers and replicated some of the findings in muscle biopsies from 154 young and elderly individuals using real-time PCR. We identified 66 probe sets (genes or expressed sequence tags) positively and 83 probe sets inversely correlated with V̇o2max and 171 probe sets positively and 217 probe sets inversely correlated with percentage of type 1 fibers in human skeletal muscle. Genes involved in oxidative phosphorylation (OXPHOS) showed high expression in individuals with high V̇o2max, whereas the opposite was not the case in individuals with low V̇o2max. Instead, genes such as AHNAK and BCL6 were associated with low V̇o2max. Also, expression of the OXPHOS genes NDUFB5 and ATP5C1 increased with exercise training and decreased with aging. In contrast, expression of AHNAK in skeletal muscle decreased with exercise training and increased with aging. Eleven genes (NDUFB4, COX5A, UQCRB, ATP5C1, ATP5G3, ETHE1, FABP3, ISCA1, MYST4, C9orf3, and PKIA) were positively correlated with both V̇o2max and the percentage of type 1 fibers. V̇o2max closely reflects expression of OXPHOS genes, particularly that of NDUFB5 and ATP5C1, in skeletal muscle, suggesting good muscle fitness. In contrast, a high expression of AHNAK was associated with a low V̇o2max and poor muscle fitness.
- oxidative phosphorylation
maximal oxygen uptake (V̇o2max) is defined as the highest oxygen uptake achievable by an individual for a given exercise profile and is commonly used as a measure of not only physical fitness but also mitochondrial function, since mitochondrial ATP production is associated with V̇o2max (38). Several studies have shown that untrained individuals with type 2 diabetes mellitus (T2DM) have reduced V̇o2max compared with healthy control individuals. Also, a low V̇o2max predicts future T2DM (7, 37).
There are several potential mechanisms by which a low V̇o2max could increase risk for T2DM, e.g., mitochondrial dysfunction (11), a change in muscle fiber type (15), and as insulin resistance (29). In addition, there is a relatively strong positive correlation between insulin sensitivity and V̇o2max (5a), and exercise training can increase both V̇o2max and insulin sensitivity (5). Intriguingly, after exercise, V̇o2max correlated with insulin sensitivity only in individuals without, not in individuals with, a family history of T2DM, suggesting that in people predisposed to T2DM, an increase in V̇o2max is not translated into an improvement in insulin sensitivity (23). Also, insulin-resistant offspring of T2DM patients showed a 30% decrease in muscle mitochondrial substrate oxidation as measured by 13C magnetic resonance spectroscopy (2) and a reduction in mitochondrial density as assessed by electron microscopy, which was found to correlate with the decrease in mitochondrial function (22). Furthermore, modest weight loss in insulin-resistant offspring of T2DM patients improved muscle insulin sensitivity and reduced muscle lipid content independently of changes in mitochondrial function (22).
A high proportion of type 1 fibers (slow-twitch muscle fibers) is associated with a high V̇o2max (18), whereas a low proportion of type 1 fibers and high proportion of type 2B fibers are associated with decreased mitochondrial function in the insulin-resistant offspring of T2DM patients (26) as well as predicting T2DM (15).
Although exercise and age are the most important nongenetic determinants of V̇o2max, there is also ample evidence that V̇o2max is under genetic control. Several studies have reported heritability of V̇o2max ranging from 40 to 70% (3, 4, 9, 17, 35).
There is still limited information on the molecular mechanisms contributing to V̇o2max. Expression of genes regulating oxidative phosphorylation (OXPHOS), including their master regulator, PPARGC1A, was downregulated in skeletal muscle of patients with T2DM (21) and their nondiabetic first-degree relatives (25), and this downregulation correlated with a decrease in V̇o2max (21). It is, however, not known whether downregulation of PPARGC1A and OXPHOS genes is primary or secondary to insulin resistance or hyperglycemia.
The aim of this study was to investigate molecular mechanisms associated with V̇o2max and type 1 fibers in skeletal muscle. We confirmed observed findings by measuring expression of individual genes using real time-PCR. Finally, we examined whether expression of these genes in skeletal muscle was influenced by aging or exercise training, determining the latter using published data.
Human Participants and Clinical Measurements
To replicate the findings from study A and to study the influence of aging on gene expression, we studied an additional 76 young (ages 25–32 yr) and 78 elderly (ages 58–66 yr) nondiabetic twins. Details of this study have been described previously (16, 27).
All subjects underwent an oral glucose tolerance test (OGTT), and glucose tolerance was classified in accordance with World Health Organization criteria (1). The muscle biopsies were obtained from the vastus lateralis muscle under local anesthesia from participants in both studies by using a modified Bergström needle (8).
In both studies, V̇o2max was measured using an incremental work-conducted upright exercise test with a bicycle ergometer (Monark Varberg) combined with continuous analysis of expiratory gases and minute ventilation. Exercise was started at a workload varying from 30 to 100 W depending on the previous history of endurance training or exercise habits and was then increased by 20–50 W every 3 min until a perceived exhaustion or a respiratory quotient of 1.0 was reached. V̇o2max was defined as the oxygen uptake measured during the last 30 s of exercise and was expressed per kilogram of total body weight. Fiber-type composition was determined as previously described (31). We quantified and calculated the fibers using the COMFAS image analysis system (Scan Beam).
Clinical and biochemical characteristics of participants in study A are shown in Supplemental Tables 1 and 2. (Supplemental data for this article is available online at the American Journal of Physiology-Endocrinology and Metabolism website.) To identify gene expression characteristic of low and high V̇o2max and type 1 fibers, we subdivided the participants into two groups based on their mean value of V̇o2max (Supplemental Table 1) and amount of type 1 fibers (Supplemental Table 2). Clinical and biochemical characteristics of participants in study B are shown in Supplemental Table 3 after the subjects were subdivided two groups based on their age.
All studies were approved by local ethics committees, and all individuals gave their informed consent for participation. All studies were conducted according to the principles of the Helsinki Declaration.
Real-time PCR was used to measure expression of individual genes in skeletal muscle biopsies of participants in study B. Extraction of total RNA from the muscle biopsies was performed with the Tri reagent (Sigma-Aldrich; http://www.sigmaaldrich.com). cDNA was synthesized using SuperScript II RNase H-reverse transcriptase (Life Technologies; http://www.invitrogen.com). Real-time PCR was performed in 10 μl using the ABI PRISM 7900 sequence detection system (Applied Biosystems; http://www.appliedbiosystems.com) according to the manufacturer's instructions. Primers and probes for NDUFB5, ATP5C1, and AHNAK mRNA were ordered as a ready-to-use mix of primers and FAM-labeled probes (Applied Biosystems). Peptidylprolyl isomerase A (cyclophilin A) was used as an endogenous control to standardize the amount of cDNA added to the reactions using a ready-to-use mix of primers and a VIC-labeled probe (Applied Biosystems). All samples were run in duplicate, and data were calculated using the standard curve method and are expressed as a ratio to the cyclophilin A reference.
Expression of individual genes.
For study A, targets from human biopsies were hybridized to the Affymetrix HG-U133A GeneChip as previously described (21). We used normalized gene expression data from human skeletal muscle (21) (http://www-genome.wi.mit.edu/pmg/oxphos). For individual gene analysis, we included only those probe sets for which percentage present calls were >50% of all arrays (19); 3,980 of 22,283 probe sets passed this filtering criterion. Spearman partial correlation analysis was performed to determine the independent effects of gene expression on V̇o2max and percentage of type 1 fibers after correction for body mass index (BMI) and T2DM status. We considered only those probe sets that were significantly correlated with V̇o2max and percentage of type 1 fibers with a P value <0.05. We used Spearman correlation to evaluate the relationship between different clinical phenotypes. For interclass, unpaired comparisons, we used the Mann-Whitney U-test to identify differences between two groups. The Kyoto Encyclopedia of Genes and Genomes pathway analysis of genes was performed using a web-based gene set analysis toolkit (WebGestalt) that implements the hypergeometric test (40).
We performed gene set enrichment analysis (GSEA) using 522 gene sets (21, 34) and assessed significance of the enrichment score by permuting participant's class labels from study A after they were divided into two groups based on mean values of V̇o2max and percentage of type 1 fibers. We considered gene sets that were significantly enriched with familywise error rate of <5%.
Published exercise training microarray datasets.
We evaluated the effect of exercise training on expression of genes of interest from previously published microarray data (28). We downloaded the normalized gene expression data from The National Center for Biotechnology Information's Gene Expression Omnibus (GEO) database (accession no. GSE1786; http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE1786). We used Wilcoxon signed rank tests to identify differences in expression of individual genes. We included only those genes whose expression was positively or inversely correlated with V̇o2max and increased or decreased significantly after endurance training, respectively, with a significance level set to 0.05.
Generalized estimating equations.
To replicate findings from study A, we performed real-time PCR of selected genes in muscle biopsies obtained from monozygotic and dizygotic twins (Supplemental Table 3). To relate expression data with age and V̇o2max, we used a generalized estimating equation (GEE) model to correct for dependence within twin pairs (16, 39). In this model the correlation is assumed to be different for monozygotic and dizygotic twins. The variables included in the model were selected using a backward selection regression with a significance level set to 0.05.
There was a modest positive correlation between V̇o2max and percentage of type 1 fibers (r = 0.37, P = 0.03) in the 43 individuals from study A. Clinical characteristics are shown in Supplemental Tables 1 and 2.
Genes Whose Expression in Skeletal Muscle Correlated With V̇o2max: Study A
To identify genes whose expression was consistently correlated with V̇o2max, we reanalyzed our previously published gene expression data from human skeletal muscle (21). We performed Spearman partial correlation analyses to determine the independent effect of gene expression on V̇o2max after correction for BMI and T2DM status. We identified 66 probe sets (genes or expressed sequence tags) positively correlated (Table 1) and 83 probe sets inversely correlated with V̇o2max (Table 2). Among positively correlated genes, we found 13 genes involved in OXPHOS using WebGestalt (P < 1 × 10−19), i.e., NDUFS3, NDUFS8, NDUFB4, NDUFB5, and NDUFB11 from complex I, UQCRB and UQCRC2 from complex III, COX5A, COX5B, and COX6A1 from complex IV, and ATP5C1, ATP5G3, and ATP6V0C from complex V (Fig. 1). There were no OXPHOS genes among genes inversely correlated with V̇o2max. Instead, this list comprised genes with varying function, including AHNAK, NACA, and BCL6 (Table 2).
Assuming that significant changes in gene expression would influence not only single genes but the whole metabolic pathway, we performed a GSEA (21, 34) by comparing groups with V̇o2max below or above the mean of V̇o2max in all individuals (Supplemental Table 1). We hereby identified three gene sets (OXPHOS-CR, electron transport chain, and oxidative phosphorylation) significantly enriched in the high-V̇o2max group but none in the low-V̇o2max group (Table 3).
To examine whether any of these genes were influenced by aerobic training, we examined their expression in skeletal muscle biopsies obtained before and after 3 mo of endurance training using published data sets (28). From the list of genes positively correlated with V̇o2max, the expression of 6 genes (ATP5C1, NDUFB5, PTP4A1, MTCH2, TSG101, and GOLGA7) was consistently increased (Supplemental Table 4), whereas the expression of 10 genes (PSMB1, AHNAK, CIRBP, ABCA8, ZBTB20, FOXO1, HNRPA3P1, TTC3, CYLD, and ZNF611) was decreased after training (Supplemental Table 5).
Genes Whose Expression in Skeletal Muscle Correlated With the Amount of Type 1 Fibers: Study A
We also performed similar analyses to determine the independent effects of gene expression on the amount of type 1 fibers in skeletal muscle biopsies obtained from the vastus lateralis muscle after correction for BMI and T2DM status in individuals from study A. We identified 171 probe sets positively correlated (Supplemental Table 6) and 217 probe sets inversely correlated with percentage of type 1 fibers (Supplemental Table 7). There were 15 OXPHOS genes whose expression positively correlated with type 1 fibers (%) using WebGestalt (P < 1 × 10−16), i.e., NDUFB4, NDUFC2, UQCRB, UQCRC2, UQCRQ, COX5A, COX7A2, COX7B, ATP5C1, ATP5J2, ATP5G3, ATP5L, ATP5O, ATP6V1D, and ATP5F1 (Fig. 1). In keeping with the findings for V̇o2max, no OXPHOS gene was inversely correlated with the amount of type 1 fibers in muscle. Instead, this list included among others RAB21, PPP3CB, and RAF1 (Supplemental Table 7). In contrast to the situation with V̇o2max, we could not find any gene set significantly enriched when comparing groups with a percentage of type 1 fibers below or above the mean of all individuals using GSEA. Notably, 11 genes (NDUFB4, C9orf3, ETHE1, FABP3, ISCA1, MYST4, UQCRB, COX5A, ATP5C1, ATP5G3, and PKIA) were positively correlated with both percentage of type 1 fibers and V̇o2max, whereas 12 genes (BZW1, CCT8, DDAH1, EIF3EIP, FOXO1, HRAS, POLR3E, PSMB1, RAB21, TAF15, WBSCR22, and ZBED1) were inversely correlated with both percentage of type 1 fibers and V̇o2max.
Real-Time PCR Confirmation of Specific Genes: Study B
For replication of some of the above findings by applying real-time PCR to archived RNA samples from skeletal muscle of 154 nondiabetic individuals in study B (see methods), we selected four genes, i.e., NDUFB5, ATP5C1, AHNAK, and BCL6, for the following reasons: 1) NDUFB5 because its expression was positively correlated with V̇o2max (Fig. 2A) and increased after training (Supplemental Table 4), and also because a recent study showed that the expression of NDUFB5 decreased after a high-fat diet (32); 2) ATP5C1 because its expression was positively correlated with V̇o2max (Fig. 2B) and type 1 fibers and increased after training (Supplemental Table 4); 3) AHNAK because its expression was strongly and inversely correlated with V̇o2max (Fig. 2C) and decreased after training (Supplemental Table 5); and 4) BCL6 expression because we had previously shown that its expression is influenced by insulin (24).
We used a GEE to model expression of these genes individually as a function of age, sex, BMI, and zygosity. Interestingly, the expression of NDUFB5 (6.33 ± 0.25 vs. 7.70 ± 0.26, P < 0.01) and ATP5C1 (1.13 ± 0.06 vs. 1.59 ± 0.08, P < 0.01) was reduced, whereas expression of AHNAK (2.01 ± 0.12 vs. 1.36 ± 0.09, P < 0.01) was increased in elderly compared with young individuals. BCL6 expression (0.27 ± 0.02 vs. 0.26 ± 0.01, P = 0.34) did not change in elderly compared with young individuals.
We also modeled V̇o2max as a function of age, sex, BMI, zygosity, and expression of individual genes (NDUFB5, ATP5C1, AHNAK, and BCL6). Expression of NDUFB5 (P = 0.03; Table 4) and ATP5C1 (P = 0.02; Table 4) but not of AHNAK [regression coefficient β = −0.10, 95% confidence interval (CI) = −1.34–1.14, P = 0.87] or BCL6 (β = 3.13, 95% CI = −2.65–8.91, P = 0.29) was significantly correlated with V̇o2max.
We have presently extended our knowledge from previous studies (21, 28) to identify genes that are correlated with V̇o2max and type 1 fibers and influenced by exercise training and aging in skeletal muscle. V̇o2max and, to some extent, type 1 fibers were positively correlated with expression of OXPHOS genes in skeletal muscle, particularly that of NDUFB5 and ATP5C1. Also, expression of NDUFB5 and ATP5C1 increased after exercise training and decreased with aging. In addition, expression of NDUFB5 was previously shown to decrease in skeletal muscle after high-fat feeding of C57BL/6J mice and humans (32). However, the opposite was not the case, because a low V̇o2max was not associated with a low expression of OXPHOS genes. Instead, this list included genes such as AHNAK and BCL6. Interestingly, expression of AHNAK decreased with exercise training and increased with aging.
The NDUFB5 gene encodes for a protein (NADH dehydrogenase 1β, subcomplex 5) from complex I, located on the inner mitochondrial membrane. It transfers electrons from NADH to the respiratory chain. Intriguingly, expression of this gene was decreased in human skeletal muscle after a 3-day isoenergetic high-fat diet as well as in mouse muscle after 21 days of high-fat feeding (32). No mutations in the gene on chromosome 3 have been linked with human pathology. However, expression of this gene in skeletal muscle seems to reflect fitness of muscle, since it increased with endurance training and decreased with aging.
The ATP5C1 gene on chromosome 10p encodes for a subunit of the soluble catalytic portion of mitochondrial ATP synthase, which catalyzes ATP synthesis during oxidative phosphorylation, thereby utilizing an electrochemical gradient of protons across the inner membrane. ATP5C1 was also correlated positively with both V̇o2max and type 1 fibers. No obvious pathology has been associated with ATP5C1, and we could not observe any association between common variants in this gene and T2DM or related metabolic traits in the Diabetes Genetics Initiative scan (30).
In contrast, AHNAK seems to reflect poor muscle fitness, since it was associated with low V̇o2max and increased with aging but decreased with exercise training. AHNAK encodes for a very large protein, desmoyokin (700 kDa), the carboxyl-terminal domain of which has been ascribed a stabilizing effect on muscle contractility via interaction with actin (10). AHNAK also seems to mediate activation of phospholipase C and release of arachidonic acid through protein kinase C (14). This opens up the interesting possibility that AHNAK could represent a link to inflammation. In fact, AHNAK was recently suggested to mediate the repressing effect of arachidonic acid on glucose transporter GLUT4 expression in muscle and interfere with phosphatidylinositol 3-kinase-Akt signaling (Karnieli E, unpublished observations). AHNAK has been suggested to link actin with L-type Ca2+ channels in cardiomyocytes (12).
However, expression of these genes did not significantly differ in muscle between individuals with and without T2DM (Supplemental Table 8) (21), suggesting that they merely reflect muscle fitness rather than being involved in the pathogenesis of T2DM.
Among other genes inversely correlated with V̇o2max was BCL6. It is downregulated by insulin (24) and is a negative regulator of peroxisome proliferator-activated receptor-δ (PPARδ) (13). This could be a potential explanation for the inverse correlation between BCL6 expression and V̇o2max, since PPARδ is a positive regulator of fat oxidation in skeletal muscle (36).
As expected, there was a positive correlation between V̇o2max and percentage of type 1 fibers, and 11 genes (NDUFB4, C9orf3, ETHE1, FABP3, ISCA1, MYST4, UQCRB, COX5A, ATP5C1, ATP5G3, and PKIA) were correlated positively with both type 1 fibers and V̇o2max, whereas 12 genes (BZW1, CCT8, DDAH1, EIF3EIP, FOXO1, HRAS, POLR3E, PSMB1, RAB21, TAF15, WBSCR22, and ZBED1) were inversely correlated with both type 1 fibers and V̇o2max. PSMB1 is involved in proteosomal cleavage of peptides in an ATP/ubiquitin-dependent process, whereas BZW1 is a cell cycle regulator (20).
In conclusion, V̇o2max closely reflects expression of OXPHOS genes, particularly that of NDUFB5 and ATP5C1, in skeletal muscle, the expression of which decreases with aging and increases with exercise training. These genes thereby seem to reflect good muscle fitness. In contrast, expression of AHNAK was associated with low V̇o2max, increased with aging, and decreased with exercise training. AHNAK thus seems to reflect poor muscle fitness. It remains to be shown whether these changes are the cause or consequence of the age-related decline in V̇o2max (33).
This work was supported by grants from the Swedish Knowledge Foundation through the Industrial PhD program in Medical Bioinformatics at the Center for Medical Innovations at the Karolinska Institute (to H. Parikh), The Diabetes Programme at Lund University (to H. Parikh), Diabetesföreningen in Malmö (to H. Parikh), the Swedish Research Council (Linné) (to L. Groop), and EXGENESIS Novo Nordisk Foundation (to L. Groop).
We are grateful to Vamsi Mootha for valuable comments.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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