Age‐related changes in human skeletal muscle transcriptome and proteome are more affected by chronic inflammation and physical inactivity than primary aging

Abstract Evaluation of the influence of primary and secondary aging on the manifestation of molecular and cellular hallmarks of aging is a challenging and currently unresolved issue. Our study represents the first demonstration of the distinct role of primary aging and chronic inflammation/physical inactivity – the most important drivers of secondary aging, in the regulation of transcriptomic and proteomic profiles in human skeletal muscle. To achieve this purpose, young healthy people (n = 15), young (n = 8) and older (n = 37) patients with knee/hip osteoarthritis, a model to study the effect of long‐term inactivity and chronic inflammation on the vastus lateralis muscle, were included in the study. It was revealed that widespread and substantial age‐related changes in gene expression in older patients relative to young healthy people (~4000 genes regulating mitochondrial function, proteostasis, cell membrane, secretory and immune response) were related to the long‐term physical inactivity and chronic inflammation rather than primary aging. Primary aging contributed mainly to the regulation of genes (~200) encoding nuclear proteins (regulators of DNA repair, RNA processing, and transcription), mitochondrial proteins (genes encoding respiratory enzymes, mitochondrial complex assembly factors, regulators of cristae formation and mitochondrial reactive oxygen species production), as well as regulators of proteostasis. It was found that proteins associated with aging were regulated mainly at the post‐transcriptional level. The set of putative primary aging genes and their potential transcriptional regulators can be used as a resource for further targeted studies investigating the role of individual genes and related transcription factors in the emergence of a senescent cell phenotype.


| INTRODUC TI ON
Aging causes complex changes in the organism associated with a progressive decrease in functionality at the systemic, organ, tissue, and cellular levels along with the development of various age-related pathologies and an increase in the likelihood of death.
Age-related decline in the functionality and mass of skeletal muscles-one of the key integral hallmarks of aging, known as sarcopenia-is related to a decrease in physical performance (endurance) and muscle strength, the ability of muscle tissue to oxidize fats and carbohydrates, and reduction in insulin sensitivity (Campisi et al., 2019;Furrer & Handschin, 2023;Lopez-Otin et al., 2023).
The decline of skeletal muscle functions affects other systems and organs, leading to the development of various pathologies (metabolic disorders, cardiovascular and nervous system diseases, etc.) and is one of the crucial factors that reduce the quality of life in advanced age.About a dozen molecular and cellular hallmarks of aging are described in the literature, such as loss of proteostasis, genomic instability, telomere attrition, epigenetic alterations, disabled macroautophagy, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, chronic inflammation, and dysbiosis (Campisi et al., 2019;Lopez-Otin et al., 2023).The appearance of these hallmarks is associated with primary aging, an innate maturational process that occurs with the passage of time from fertilization to death, and secondary aging, which includes the effects of the environment, pathological processes, and/or diseases (Busse, 1969).
Evaluation of the influence of primary and secondary aging on the manifestation of molecular and cellular hallmarks of aging is a challenging and currently unresolved issue.
Since age-related changes, especially in humans, are very complex, exploratory studies using high-throughput methods are of the greatest interest.Several studies attempted to identify molecular changes associated with "healthy" aging in human skeletal muscle, considering primary aging with minimal contribution of physical impairment and chronic diseases.For this, different muscle molecular parameters were compared between physically active and sedentary elderly people (Hinkley et al., 2023;Lanza et al., 2008) or between young (sedentary) and older people with a comparable level of physical activity/performance (physically active) (Lagerwaard et al., 2021;Lanza et al., 2008;Murgia et al., 2017;Ubaida-Mohien et al., 2019).
The last approach compared people of different ages who appeared to have different levels of physical activity throughout their lives; that is, the influence of two factors was simultaneously examined: age and increased levels of physical activity throughout life.The lack of reliable information on the differences between the level of physical activity and performance (and other marks, such as inflammation) in older physically active people compared to the relevant same people at a younger age seems to be a critical limitation of the approach.
The present study aimed to evaluate the role of primary aging and pathological processes/environmental factors including chronic inflammation and physical inactivity in age-related changes of the transcriptomic and proteomic profiles in human skeletal muscle.To achieve this purpose, three groups of volunteers were included in the study: young healthy people (YH) and young and older patients with knee/hip osteoarthritis (YP and OP, respectively).Advancedstage, symptomatic knee/hip osteoarthritis has been used as a model to study the effect of long-term inactivity/disuse and chronic inflammation on human skeletal muscle (Callahan et al., 2014(Callahan et al., , 2015;;Miller et al., 2017;Suetta et al., 2007).A comparison of YP vs. YH focused on the influence of both chronic inflammation and physical inactivity, while a comparison of OP vs. YH (age-related changes in older patients relative to young, healthy people) made it possible to evaluate the overall effect of primary and secondary aging on gene and protein expression patterns in skeletal muscle.The comparison of OP and YP (age-related changes in patients occurring against the background of chronic inflammation and physical inactivity) was more relevant to the contribution of primary aging to the observed changes.However, this effect may be markedly modulated by long-lasting (years) chronic inflammation and inactivity; therefore, to identify genes associated with primary aging, the mRNAs and proteins that unidirectionally changed expression were determined when comparing OP vs. YP and OP vs. YH.Finally, using the transcription factor binding site enrichment analysis, transcriptional factors associated with primary aging genes in human skeletal muscle were predicted.

| Advanced age-and disease-related physiological changes in subjects
To evaluate the contribution of primary and secondary aging to the molecular changes of human skeletal muscle, three groups of muscle biopsy samples as mentioned earlier were compared (Figure 1a).In older patients (OP) compared to healthy volunteers (YH), there was a pronounced decrease in physical status and an increase in the level of blood leukocytes-a marker of chronic inflammation-as the acute inflammatory response was excluded in all subjects before the biopsy (Figure 1b, Figure S1).
Osteoarthritis-related chronic inflammation and inactivity, as well as age-related sarcopenia, resulted in a two-fold decrease in thigh muscle size, violation in the muscle fiber structure, and a decrease in the total RNA content (Figure 1c,d).In addition, some hallmarks disuse, inflammation, primary aging, proteome, skeletal muscle, transcriptome of age-related metabolic disorders were observed in OP: an increase in baseline blood insulin, body mass index, and subcutaneous thigh fat volume (Figure 1d, Figure S1).
It is important that young patients (YP) relative to the healthy young control (YP vs. YH) showed an increase in the level of blood leukocytes, a decrease in physical status, and the content of total RNA in the muscle samples, as well as violation in the muscle fiber structure.However, no significant changes were found in the thigh muscle size, and markers of metabolic disorders in YP, which, apparently, is associated with a shorter duration of the disease and small sample size (Figure 1b-d and Figure S1).

| Physical inactivity and chronic inflammation are key drivers of age-related changes in the skeletal muscle transcriptome in older patients relative to young healthy people
After removing low-expressed genes, >10,000 mRNAs were identified (Table S1).Principal component analysis showed that the transcriptomic profiles of both patient groups (YP and OP) differed markedly from YH, while the patient profiles were quite similar (Figure 2a).In older patients, widespread changes in the transcriptome profile were revealed relative to young healthy volunteers (OP F I G U R E 1 Pathology-and age-related physiological changes in young (YP) and older (OP) patients with advanced-stage, symptomatic knee osteoarthritis compared to young healthy (YH) individuals.(a) Design of the study.(b) Both patient groups demonstrate a substantial decrease in physical status and an increase in the blood leukocyte level, a marker of inflammation.(c, d) In patients, chronic physical inactivity and inflammation led to a comparable violation in the muscle fiber structure (c), a progressive decrease in the specific crosssectional area of thigh muscles (CSA), an increase in the baseline insulin level and body mass index [BMI] (markers of metabolic disorders), as well as to a comparable decrease in the total RNA content in M. vastus lateralis (see also Figure S1).vs. YH): ~2000 and ~ 2300 mRNAs were up-and down-regulated, respectively (Figure 2b, Table S1).The functional enrichment analysis showed that the changes were strongly associated with a decrease in the expression of genes encoding mitochondrial proteins (>500 mRNAs out of ~1000 mRNAs of mitochondrial proteins) and especially respiratory complex proteins, as well as regulators of proteostasis, carbohydrate and fat metabolism, transport, and membrane proteins (Figure 2c).Up-regulated mRNAs were associated mainly with secreted extracellular matrix proteins and membrane proteins, as well as with immune and inflammatory responses.These findings are in good agreement with previous studies comparing muscle transcriptome in young people with that in older people F I G U R E 2 Chronic inflammation and physical inactivity are key drivers of age-related changes in the skeletal muscle transcriptome in older patients relative to young healthy people.(a) Principal component analysis showed that the transcriptomic and proteomic profiles in young healthy people (YH) were markedly different compared to young patients (YP), while the proteomic profiles in young (YP) and older patients (OP) were much more similar.(b) Number of differentially expressed mRNAs and proteins for each comparison.(c) Function enrichment analysis revealed that chronic inflammation and physical inactivity were key drivers of age-related changes in the skeletal muscle transcriptome.BP and CC, biological processes and cellular components, respectively; the heat map shows the significance level (NS, nonsignificant; see also Table S2).YH: n = 15, YP: n = 8, OP: n = 37. (Borsch et al., 2021;Su et al., 2015) and in older physically active people, with the level of physical activity comparable to the young control (a model of "healthy" aging; Lagerwaard et al., 2021).
The number of differentially expressed genes in YP relative to YH was 1.5 times less than in OP vs. YH (~1400 and ~ 1400 up-and down-regulated mRNAs; Figure 2b, Table S1); however, the direction of the transcriptome profile changes was similar (Figure S2 and Figure 2c).In particular, there was a decrease in the expression of many genes encoding mitochondrial and membrane proteins, as well as sarcoplasmic reticulum proteins, and an increase in gene expression of secreted, membrane, and extracellular matrix proteins and regulators of inflammatory and immune response (Figure 2c).
Curiously, in OP, the number (Figure 2c) and expression (Figure S3) of up-regulated mRNAs-enriched functional categories "inflammatory response" and "immunity" were lower than in YP, which may indicate age-related suppression of the pro-inflammatory response in the patient's muscle.
Transcriptomic changes in older patients relative to younger patients (OP vs. YP) were more likely associated with primary aging than those between other groups; however, it is important to note that these changes occurred against the background of long-lasting (years) inflammation, which could significantly modulate the transcriptome profile (Figure S3).Surprisingly, these transcriptomic changes (OP vs. YP) were modest (~110 and ~ 360 up-and downregulated mRNAs, respectively; Figure 2b and Table S1) and fundamentally different from the previous comparisons: the up-regulated mRNAs enriched the functional categories "nucleus" and "chromosome", while down-regulated mRNAs enriched the terms "cell membrane" and "secreted" (Figure 2c, Figure S2, and Table S2).Altogether, the obtained transcriptomic data, as well as a pronounced decrease in the total RNA content in YP relative to YH, indicate the key role of chronic inflammation and inactivity in the development of agerelated changes in the skeletal muscle transcriptome in OP relative to YH.

| Proteins with distinguished functions are differently regulated at the mRNA level, while aging-related protein changes in patients are regulated mainly at the post-transcriptional level
Sarcomeric proteins make up about half of muscle proteins, which limits the depth of shotgun proteomic analysis in this tissue.Proteins highly abundant within skeletal muscle were mainly detected (n = 1899; sarcomeric and mitochondrial proteins, energy metabolism enzymes, chaperones, etc.), of which 1387 proteins were detected in all samples (n = 60; Table S3).Principal component analysis showed that the YH proteomic profiles, like the transcriptomic profiles, markedly differed compared to YP, while the YP and OP proteomic profiles were substantially more similar (Figure 2a).As expected, the greatest proteomic change (413 proteins) was found in older patients relative to young, healthy individuals (OP vs. YH; Figure 2b).In contrast to the transcriptomic data, the number of differentially expressed proteins in OP vs. YP (196 proteins) was comparable to YP vs. YH (178 proteins; Figure 2b), which may be due to the fact that only a fraction (n = 1899, less than a third) of proteins expressed in human tissues (~10,000; Wang et al., 2019) was detected.
It was determined that only a third of age-and pathology-related changes in protein content (OP vs. YH and YP vs. YH, respectively) correlated with changes in their mRNA level (sets "protein UP-mRNA UP" and "protein DOWN-mRNA DOWN" in Figure 3a).Moreover, when comparing older patients to young patients (OP vs. YP), changes in the content of almost all proteins occurred without changes in the expression of the corresponding mRNAs (sets "protein UP-mRNA NS" and "protein DOWN-mRNA NS" in Figure 3a), meaning that agerelated protein changes in patients were regulated mainly at the post-transcriptional level.
A comparison of proteomic and transcriptomic data (Figures 2c   and 3b,c, Table S4) showed that age-related changes in the content of proteins with various functions were differently regulated at the level of their mRNA expression, namely, intergroup expression trajectory (YH-YP-OP) of proteins and mRNAs were significantly different.In particular, the expression of cytoskeletal proteins correlated with the expression of their mRNAs in all comparisons.On the contrary, a decrease in the expression of genes encoding oxidative phosphorylation enzymes-the most pronounced change in the transcriptomic profile-did not cause a decrease in the content of corresponding proteins in young patients (YP vs. YH), but correlated with a decrease in these proteins in older patients (OP vs. YP and OP vs. YH).Other proteins (proteins of the cell membrane, endoplasmic reticulum, regulators of protein transport, splicing, and transcription) showed a pathology-and age-related increase in their content, which occurred against the background of multidirectional regulation of their mRNAs (Figure 3c).

| Genes associated with primary aging in human skeletal muscle
It was found that in older patients, relative to young patients (OP vs. YP), the direction of changes in the expression of many genes did not coincide with those observed in older patients relative to the healthy control (OP vs. YH; Figure 3c and Figure S3).This may partly be explained by the fact that in younger patients, up-regulated genes are more enriched immune/inflammatory functional categories than in older patients (at the mRNA and protein levels; Figures 2c and 3b, respectively), which indicates muscle inflammation.Therefore, genes associated with primary aging were defined as genes whose proteins (or mRNAs, since it was possible to determine the expression of less than a third of all muscle proteins) unidirectionally changed expression in OP vs. YP and OP vs. YH (mRNAs whose protein products did not change expression were excluded; Figure 4a and Figure S2), and then their functions and potential protein-protein interactions were described (Figure 4b and Table S5).The largest clusters of interacting proteins were formed by mitochondrial and nuclear proteins.S4).(c) Analysis of the intergroup expression trajectory (YH-YP-OP) of differentially expressed proteins belonging to some enriched functional categories and their mRNAs showed that pathology-and age-related changes in the abundance of protein with various functions were differently regulated at the mRNA expression level.Normalized expression (z-score) for each protein/mRNA, as well as the name and ID of functional categories, are indicated.* -difference from YH, # -difference from YP: one and three symbols -p < 0.05 and <0.001, respectively.YH: n = 15, YP: n = 8, OP: n = 37.

| Putative transcription factors regulating primary aging gene expression in human skeletal muscle
A change in gene expression profile can be caused by changes in cell signaling, proteostasis, epigenetic regulation, etc. Identifying the mechanisms (in particular, transcription factors) that control the expression of primary aging genes is of great importance.To predict transcription factors involved in the regulation of primary aging genes, the individual promoter regions (see Methods) of primary aging genes (43 and 71 up-and down-regulated mRNAs in Figure 4a) were examined using the transcription factor binding site enrichment analysis.Significant enrichment was found only for the promoters of down-regulated mRNAs, which indicated a decrease in the activity of the putative transcription factors.On the other hand, down-regulation of these mRNAs may be due to the fact that half of the predicted factors (NR3C1, ETS1, NR2F6, ZNF436, BCL6, GATAD2A, and ZNF461) can act as repressors (Figure 5 and Table S6).The highest enrichment was found for transcription factor motifs: ZFP64, NR3C1, ETS1, NR2F6, ZNF436, ZNF528, and a dimer RELB:NFKB1.

| DISCUSS ION
The present work examined, for the first time, the role of pathological processes (chronic inflammation and physical inactivity) and primary aging in age-related changes of the transcriptomic and proteomic profiles in human skeletal muscle.As expected, widespread changes were found in gene and protein expression profiles in older patients relative to young healthy individuals (associated mainly with the suppression of mitochondrial protein gene expression and increased expression of extracellular matrix, secreted, immune, and nuclear protein genes; Figures 2 and 3, Tables S2 and S4), which was in good agreement with studies comparing older people (Borsch et al., 2021;Cutler et al., 2017;Lanza et al., 2008;Su et al., 2015), as well as older physically active people (a model of "healthy" aging) (Lagerwaard et al., 2021;Lanza et al., 2008;Murgia et al., 2017;Ubaida-Mohien et al., 2019), with young subjects.Next, it was revealed that young patients showed significant and similar to the previous comparison changes in the phenotype (an increase in markers of inflammation and a violation in the muscle fiber structure) as well as in transcriptome relative to the young healthy control (Figures 1 and 2), which clearly indicated that physical inactivity and chronic inflammation could be considered key drivers of age-related changes in skeletal muscle of older patients (relative to young healthy people).
To identify genes associated with primary aging, genes that unidirectionally changed the expression of proteins (or mRNAs) in OP vs. YP and in OP vs. YH (Figure S2, Figure 4) were determined.
Unexpectedly, only a few of such genes were revealed compared to pathology-associated genes (YP vs. YH).The lack of overlapping of primary aging genes and pathology-associated genes (Figure S2) clearly indicates the distinct functions of these gene sets.It is possible that a small number of primary aging-related genes are specific for skeletal muscle only (Figure S4В).A number of studies showed that the age-related acquisition of senescence markers varied significantly in cells of different mammalian tissues, while in skeletal muscle this increase [such as DNA damage foci-associated protein H2AX (Wang et al., 2009), senescence-associated heterochromatin fociassociated core histone macro-H2A.1 (H2AY) (Kreiling et al., 2011), telomere dysfunction-induced foci-associated TP53-binding protein 1 (TP53B) (Jeyapalan et al., 2007), and tumorigenesis (Seely, 1980)] is lower and/or absent compared to cells of other tissues (hepatocytes/liver, dermis and fibroblasts/skin, alveoli/lung, lymphocytes/ spleen, crypt/small intestine).A small number of primary aging genes (as well as a slight age-related increase in senescence markers) might be a specific characteristic of muscle fibers-fully differentiated postmitotic (non-replicated) cells with a very high plasticity potential.The main function of skeletal muscles is contractile activity; maintaining/increasing the level of physical activity in the elderly was shown to have a pronounced positive effect on the content and function of skeletal muscle mitochondria, fat and carbohydrate metabolism, insulin sensitivity, and endurance performance (Distefano et al., 2018;Lanza et al., 2008) and can induce an increase in muscle mass and strength (Papa et al., 2017;Peterson et al., 2010), thereby contributing to the exercise-induced increase in lifespan (Campisi et al., 2019;Goh et al., 2023).This suggests that senescent skeletal muscle cells (unlike many other somatic cells) retain an exceptionally high potential to restore their functions under the action of a specific physiological stimulus-regular contractile activity.This reasoning is supported by the fact that some of the molecular "anti-aging" effects of long-term physical training (transcription and methylation reprogramming) coincide with those of partial in vivo reprogramming by short-term induction of the Yamanaka transcription factors (Jones 3rd et al., 2023), facilitating cellular plasticity and regeneration that are characteristics of a more youthful cell state (Gill et al., 2022;Ocampo et al., 2016).Together, these data indicate the need to identify primary aging genes in cells of various tissues and compare them with skeletal muscle.This approach may reveal mechanisms of sensitivity/resistance to the emergence of a senescent cell phenotype and also indicate the possibility of using skeletal muscle as a model to study restoring the functions of senescent cells.
It was revealed that only a third of age-related changes in the content of muscle proteins (predominantly highly abundant proteins) correlated with changes in their mRNA level (OP vs. YH in Figure 3a), which is consistent with the work that investigated age-related changes in proteomic and transcriptomic profiles in mouse skeletal muscle (Hunt et al., 2021).A similar pattern was observed for pathology-related changes (YP vs. YH in Figure 3a), meaning that changes in the abundance of the majority (more than half) of the detected proteins are regulated by changes in the rate of transcript-specific translation and/or protein-specific degradation.This conclusion complements studies showing that the age-related decrease in the fractional protein synthesis rate in human skeletal muscle (Breen et al., 2011) occurs together with transcript-specific deregulation in translation efficiency (ribosome occupancy), which decreases for genes encoding mitochondrial proteins in human skeletal muscle (Tharakan et al., 2021), mitochondrial membrane proteins, and translation regulators in mouse liver and kidney, but increases for genes encoding inflammatory proteins (Anisimova et al., 2020).Curiously, the change in the content of almost all proteins in patients (OP vs. YP in Figure 3a), as well as proteins associated with primary aging (for example, mitochondrial proteins, Figure 4b, Table S5), occurs without changing the expression of their mRNAs, indicating that (primary) aging-related changes in expression of highly abundant proteins are exclusively regulated at the post-transcriptional level (translation and protein degradation).In addition, it was demonstrated that proteins with different functions were differently regulated at the mRNA level, and the pattern of this regulation was modulated by aging and the presence of pathological conditions F I G U R E 4 Genes associated with primary aging.(a) Genes associated with primary aging were identified as proteins (as well mRNAs) that unidirectionally change expression in both OP vs. YP and OP vs. YH (YH: n = 15, YP: n = 8, OP: n = 37).(b) Functions of primary aging associated genes.Analysis of protein-protein interactions and search of the GO and KEGG BRITE databases revealed the major functional groups of proteins, including proteins interacting with each other.Proteins and mRNAs are shown in italics and bold, respectively: underlining indicates changes in both mRNA and protein level.Up-and down-regulated proteins or mRNAs are shown in red and blue, respectively (see also Table S5).Thicker edges indicate higher protein-protein interaction scores.

F I G U R E 5
Transcriptional factors associated with down-regulated primary aging genes (mRNAs).The heat map shows adjacent fold enrichment (FE adj , statistically corrected odds ratios with a confidence interval of 99%) for transcription factor binding site frequency in individual promoters of primary aging genes relative to that of random genes showing no differential expression (see also Table S6).Thicker edges indicate higher protein-protein interaction scores.
(inactivity/inflammation; Figure 3).The specificity in the regulation of proteins with different functions was shown previously by high-throughput approaches in mouse fibroblasts (Schwanhausser et al., 2011), human hematopoietic stem cells differentiating into erythroid progenitors (Liu et al., 2017), and human skeletal muscle after a period of physical training (Makhnovskii et al., 2020).
Overall, these results clearly demonstrate the presence of conserved function-specific mechanisms that regulate protein abundance under the influence of various stimuli, including chronic inflammation/inactivity and aging.
Analysis of the functions of putative primary aging genes identified in this study (Figure 4b, Table S6) showed that ~40% of them were previously attributed to aging and/or senescence in muscle and other tissues (Figure S4).For example, PPARGC1A, an important regulator of mitochondrial biogenesis and antioxidant defense (Ji & Kang, 2015;Wenz et al., 2009), genes encoding mitochondrial proteins (subunits of the pyruvate dehydrogenase complex and all respiratory complexes) (Murgia et al., 2017;Ubaida-Mohien et al., 2019;all down-regulated), regulators of splicing (Lee et al., 2016;Ubaida-Mohien et al., 2019), and DNA repair (Schumacher et al., 2021;predominantly up-regulated).It is important to note that many genes in these groups were not previously associated with aging and are therefore of interest for future research.Interestingly, down-regulated genes encoding assembly factors and regulators of cristae formation, as well as chaperones and associated proteins, were identified as primary aging genes, which is in line with data on age-related disturbances in the cristae structure (Beregi et al., 1988) and proteostasis (Goh et al., 2023) in old muscles.Other interesting examples: the downregulation of IGF1, a growth factor regulating muscle protein expression/synthesis, is consistent with its decreased level in plasma in people with sarcopenia (Bian et al., 2020) and expression in various tissues of long-lived species (Tyshkovskiy et al., 2023), as well as the down-regulation of mitochondrial creatine kinase (CKMT2) and ADP/ATP translocase 1 (SLC25A4), those recently identified (along with mitochondrial-bound hexokinase I or II) as key regulators of mitochondrial reactive oxygen species production in skeletal muscle and other tissues (Vyssokikh et al., 2020).
Identifying the mechanisms regulating the expression of primary aging genes is of fundamental importance.Transcription factors associated with down-regulated (at the mRNA level) primary aging genes were predicted (Figure 5).The validity of the prediction of some transcriptional regulators (such as NFKB1, BCL6, NR4A1, and NR2F6) is confirmed by previous mechanistic studies.Namely, knockout of Nfkb1 leads to early mice aging, which is associated with reduced apoptosis and increased cellular senescence (Bernal et al., 2014;Jurk et al., 2014).Knockdown of Bcl6, a terminal differentiation factor for C2C12 myoblasts, induces apoptosis (Kumagai et al., 1999).Additionally, orphan nuclear receptors of the NR4A family are considered age-dependent regulators of fat and carbohydrate metabolism and DNA repair (Paillasse & de Medina, 2015).
On the contrary, overexpression of the repressor Nr2f6 suppresses the expression of Ppargc1a, genes related to energetic metabolism and muscle contraction, induces muscle atrophy, and impairs muscle force production (Guimarães et al., 2023).

| LI M ITATI O N S
The lack of a "healthy" older group (physically active older persons with minimal contribution of physical impairment and chronic diseases) limits the interpretation of our data.Comparison of this group with older patients would be useful to identify genes associated with inflammation and decreased physical activity in older patients.It can be assumed that this set of genes differs from that identified for YP vs. YH.Another limitation of the study is the small number of people in the young patient group.Further studies with an increase the number of compared groups and sample size seem to be an interesting and promising direction.
Recent studies found some sex-related differences in human skeletal muscle transcriptome during aging (de Jong et al., 2023;Huang et al., 2023).We analyzed sex-related differences in the older patient group (32 old females vs. 5 old males) and found small number (43) of differentially expressed genes and little overlap of these genes with other comparisons (OP vs. YH and OP vs. YP).Moreover, no differentially expressed proteins were found for this comparison (Figure S5).Together, this suggests little influence of sex-related differences in gene expression on the main results of our study.

| CON CLUS IONS
To the best of the authors' knowledge, this study represents the first demonstration of the distinct role of primary and secondary aging in the regulation of transcriptomic and proteomic profiles in human skeletal muscle.Using the specific approach to the selection of experimental groups, it was revealed that widespread and substantial age-related changes in gene and protein expression (genes regulating mitochondrial function, proteostasis, cell membrane, secretory, and immune response) in older patients relative to young healthy people were related to the long-term physical inactivity and chronic inflammation rather than primary aging.The impact of primary aging was also separated, and it was demonstrated that it contributed mainly to the regulation of genes encoding nuclear proteins (including genes related to DNA repair, RNA processing, and transcription regulation), mitochondrial proteins (genes encoding oxidative metabolism enzymes, mitochondrial complex assembly factors, regulators of cristae formation, and mitochondrial reactive oxygen species production), as well as regulators of proteostasis.
Comparing the changes in the expression of proteins and the corresponding mRNAs, it was found that proteins associated with aging were regulated mainly at the post-transcriptional level.The study of this regulatory mechanism seems to be a promising avenue for future investigations.The set of putative primary aging genes and their potential transcriptional regulators identified in this study can Sequencing quality was assessed using the FastQC tool (v.0.11.5).Low-quality reads and adapter sequences were deleted (Timmomatic tool, v0.36), and then the reads were aligned to the GRCh38.p13primary genome assembly.Uniquely aligned reads were counted for known exons of each gene using the Rsubread package (R environment) and Ensembl annotation (GRCh38.101).
Differential expression analysis was performed by the DESeq2 method (analysis of unpaired samples with the Benjamini-Hochberg correction).Differentially expressed genes (DEGs) were defined as protein-coding genes (also polymorphic pseudogene or translated pseudogene) with p adj < 0.01, |Fold Change| ≥ 1.25, and the expression level TPM >1 (Transcripts Per Million) was calculated using Kallisto v0.46.2.

| Transcription factor binding site enrichment analysis (positional weight matrix [PWM] approach)
To predict transcription factors associated with primary aging genes, the individual promoter regions identified for human skeletal muscle by gene-specific positions of the transcription start site and open chromatin (Makhnovskii et al., 2022) were investigated.Enrichment of the transcription factor binding sites (and corresponding transcription factors) in individual promoter regions of genes associated with primary aging was performed by the GeneXplain platform (the "Search for enriched TFBSs (tracks)" function http:// wiki.biouml.org/ index.php/ Search_ for_ enric hed_ TFBSs_ (tracks)_(analysis)) using the PWM database TRANSFAC v2022.2, as described elsewhere (Makhnovskii et al., 2022).Briefly, the maximum fold enrichment (FE adj , statistically corrected odds ratios with a confidence interval of 99%) was determined for each PWM (site frequency ≤1 per 2000 bp) relative to that in 5000 random individual promoters showing no differential expression in any of the experimental groups (DESeq2 method, p adj > 0.4).Adjusted fold enrichment (FE adj ) >1 for both transcription factor binding site frequency and promoter's sequence number (the binomial test and exact Fisher's test, respectively), as well as FDR <0.05, were set as significance thresholds.The FE adj evaluated by these tests demonstrated a strong correlation (Table S6).If a transcription factor has several PWM, the most enriched PWM was used.Only expressed transcription factors (TPM in OP >1) were included in further analysis.
The mixture of labeled peptides was subjected to reverse-phase LC fractionation using an Agilent 1200 Series HPLC (Agilent, USA) to obtain 24 fractions, then fractions were combined (1 and 13, etc.) to obtain 12 fractions.Briefly, the peptides were concentrated on an Accalaim μ-Precolumn (0.5 mm × 3 mm, particle size 5 μm; Thermo Scientific) in the isocratic mode at a 10 μL/min flow for 5 min in the mobile phase C (2% acetonitrile, 0.1% formic acid).The peptides were then separated on a Peaky C18 column (100 μm × 300 mm, particle size 1.9 μm; Molecta, Russia) in a gradient mode of elution.
Each fraction was analyzed and tripled by an HPLC Ultimate 3000 RSLC nanosystem (Thermo Scientific) and a Q Exactive HF-X Hybrid Quadrupole-Orbitrap mass spectrometer (Thermo Scientific) using the nanoelectrospray ion source in the positive mode of ionization (Thermo Scientific).The gradient (90 min) was formed by the mobile phase A (0.1% formic acid) and B (80% acetonitrile, 0.1% formic acid) at a 0.4 μL/min flow.The ionizing voltage was 2.1 kV.MS spectra were acquired at a resolution of 60,000 in the 390-1300 m/z range; fragment ions were mass scanned at a resolution of 60,000 at the range from m/z 120 to the upper m/z value as assigned by the mass to charge state of the precursor ion.All tandem MS scans were performed on ions with a charge state from z = 2+ to z = 4+.
Synchronous precursor selection facilitated the simultaneous isolation of up to 40 MS2 fragment ions.The maximum ion accumulation times were set to 50 ms for precursor ions and 25 ms for fragment ions.AGC targets were set to 10 6 and 10 5 for precursor ions and fragment ions, respectively.
The search and identification of peptides and proteins were carried out using the MaxQuant platform (2.1.4.0;Max Planck Institute of Biochemistry) at default settings (the FDR for peptides 1%, Nterminal acetylation and methionine oxidation as variable modifications and cysteine carbamidomethylation as fixed modification).
Further analysis was performed using the Perseus platform (1.6.5;Max Planck Institute of Biochemistry).To avoid the batch effect related to labeling by the TMT 10-plex and 16-plex kits, the mean intensity of the reporter ions of all samples labeled by 10-plex isobaric tags was normalized to that of all samples labeled by 16-plex tags (Figure S8).After filtration (removing potential contaminants, reverse peptides, and peptides identified only by site), proteins identified by >1 unique+razor peptide and present in >70% of samples were taken for further analysis.To examine differentially expressed proteins, the one-way analysis of variance with q-value (Benjamini-Hochberg corrected p-value) <0.05 and post-hoc analysis (Tukey's test; p < 0.05) were applied.

F
I G U R E 3 Proteins with different functions are differently regulated at the mRNA level, while aging-related protein changes in patients are regulated mainly at the post-transcriptional level.(a) Changes in the content of highly abundant proteins are weakly regulated at the mRNA level, especially in the patient groups (OP vs. YP).Different colors represent the protein regulation pattern at the mRNA level.NSnonsignificant.(b) Function enrichment analysis revealed specific proteomic changes for each comparison.BP and CC, biological processes and cellular components, respectively; the heat map shows the significance level (NS -nonsignificant; see also Table