Introduction
Sarcopenia is a syndrome of aging skeletal muscle mass reduction with decreased skeletal muscle strength and function [
1], which can be classified as primary and secondary depending on the cause. Primary sarcopenia is mainly associated with age, secondary sarcopenia has obvious causes other than age, including poor exercise patterns, chronic wasting diseases, and impaired nutrient absorption [
2]. In 2010, the European Working Group on Sarcopenia in the Elderly (EWGSOP) published a consensus on the definition and diagnosis of Sarcopenia, which has been recognized worldwide [
3]. Sarcopenia is a relatively common disease in the elderly, and its prevalence increases with age. The survey found that the prevalence of over 65 years old is 5–13% and over 80 years old is 50% in the population of European countries [
4]. In Asia, the prevalence rate in Japan was 7% for women aged 60–69 years 24% for men aged 70–80 years, 33% for men aged 60–69 years, and 47% for men aged 70–85 years [
5]. A serious consequence of Sarcopenia is that it leads to a decrease in skeletal muscle strength, slowness, and balance in the elderly, making them prone to falls and fractures, greatly reducing the quality of life and increasing the burden on families and society. In 2015, China’s population aged 60 and above had reached 222 million, accounting for 16.1% of the total population. With the global trends in population aging, the number of people over 60 years old in China will increase and is expected to reach 400 million by 2050, accounting for about 25% of the total population. The quality of life of the elderly is related to the economic stability and development of our country and has attracted wide attention from the whole society.
Sarcopenia, first proposed by Evans WJ and Rosenberg IR in 1991, is a condition characterized by a reduction in bone-invasive muscle, but also involves mitochondrial dysfunction, impaired protein synthesis and degradation, autophagy and satellite cell activation, and other factors considered to be the underlying pathophysiological basis for sarcopenia. The hazards of sarcopenia mainly include increasing the risk of falls, fractures, and disabilities, making the elderly lose the ability to live independently, increasing the incidence of hypertension, diabetes, and other chronic diseases in the elderly, and increasing the all-cause mortality and disability rate of the elderly. Muscles and bones interact and correlate with each other. Some researchers have confirmed through systematic review that sarcopenia is significantly associated with the incidence of fracture, and male patients with sarcopenia and low bone mineral density have a significantly increased risk of fracture [
6]. Decreased muscle function and reduced mass are risk factors for the development of falls [
7,
8]. Therefore, the pathogenesis of sarcopenia needs to be studied, which provides a new target and theoretical reference for the future treatment of myopathy or skeletal sarcopenia associated with delaying aging.
Sarcopenia-osteoporosis has been used to describe the co-existence of sarcopenia and osteoporosis, both of which have a diminished motor system and loss of mass with age, focusing on the skeleton and muscle, respectively, and it has been claimed that "they are manifestations of one disease in different physiological systems [
9]. There are no uniform criteria for the diagnosis of Sarcopenia in China and abroad. The European Working Group on Sarcopenia in the Elderly (EWGSOP), the Asian Working Group on Sarcopenia (AWGS), the International Working Group on Sarcopenia (IWGS), and the National Foundation for Sarcopenia Programs (FNIH) mainly diagnose Sarcopenia based on muscle mass, muscle strength, and muscle function. such as Table
1. The lack of characteristic genes and molecular markers and the unclear molecular mechanism make the treatment and prognosis of Sarcopenia difficult.
Table 1
The lack of characteristic genes and molecular markers and the unclear molecular mechanism makes the treatment and prognosis of Sarcopenia difficult
EWGSOP | Less than healthy muscle mass Adult #2 standard deviations | Muscle strength is lower than healthy Adult #2 standard deviations | Pace lower than healthy Adult #2 standard deviations |
AWGS | Limb muscle mass/height 2: Male < 7.0 kg/m2 Female < 5.4 kg/m2 | Muscle strength: Male < 26 kg Female < 18 kg | Step speed < 0.8 m/s |
IWGS | Extremity muscle mass/height2: Male ≤ 7.23 kg/m2 Female ≤ 5.67 kg/m2 | – | Step speed < 1 m/s |
FNIH | Extremity muscle mass/height2/BMI*: Male < 0.789 Female < 0.512 | Muscle strength: Male < 26 kg Female < 16 kg | Step speed ≤ 0.8 m/s |
The concept of epigenetics was first proposed by Waddinglon in 1942, who referred to epigenetics as the study of biological developmental mechanisms [
10]. By the mid-1970s, R. Holliday considered epigenetics as the study of heritable changes in gene expression due to non-DNA sequence changes [
11], which is now a more widely accepted concept. Epigenetic modifications play an important role in the development and progression of cancer and subsequent cachexia. Epigenetic modifications describe changes in the state of chromatin condensation and ultimately determine the accessibility of DNA to proteins that control transcription. Three major epigenetic mechanisms are said to play a key role in cancer development.
Bioinformatics is a new science that uses computer science and information technology to collect, process, analyze, and interpret a large number of bioinformatics data. Bioinformatics analysis technology is accompanied by the rapid development of life sciences and computer science, providing an efficient analysis tool for revealing the potential significance of large and complex biological data [
12,
13]. Microarray microarray assay data from public data repositories such as GEO can then be screened for potentially relevant genes and related signaling pathways for disease prevention, diagnosis, and treatment using bioinformatics analysis methods. Many candidate genes for osteoporosis and sarcopenia have been identified and confirmed, but these studies still suffer from low reproducibility of the identified genes and lack of functional validation of the candidate genes. Therefore, we aimed to screen characteristic genes related to sarcopenia by bioinformatics and machine learning and to verify the accuracy of characteristic genes in the diagnosis of sarcopenia.
Discussion
The global population is aging at an accelerating rate, and with age comes changes in the composition of the body, including fatty tissue and muscle. Skeletal muscle decreases gradually after age 50 and muscle mass and strength also decreases gradually. Sarcopenia is a syndrome of progressive, widespread loss of skeletal muscle mass and strength, and the resulting adverse consequences of decreased physical performance, decreased quality of life, and death [
3]. As more research emerges, the most widely cited definition currently comes from the EWGSOP2 consensus proposed by the 2018 EWGSOP, which identified decreased muscle strength as the primary parameter for the assessment of sarcopenia, arguing that sarcopenia may be present when it is found sarcopenia is diagnosed when low muscle quantity or quality is found, and severe sarcopenia is when low muscle strength, low muscle quantity or quality, and physical function are all present [
23]. Sarcopenia is a common disease among the elderly, and its incidence is increasing with age. However, at present, its diagnosis can only be made by combining the indicators of muscle volume, muscle strength, and muscle function, lacking specific molecular markers, and its molecular mechanism is also complicated. Various pathological factors, including oxidative stress, inflammatory response, and insulin resistance, are known to be involved in the formation of Sarcopenia, which ultimately leads to decreased protein synthesis and increased catabolism in skeletal muscle cells and the conversion of muscle fibers from type II fibers (fast muscle fibers) to type I fibers (slow muscle fibers) [
24].
In this study, we found that
TPPP3,
C1QA,
LGR5,
MYH8,
CDKN1A gene expression was upregulated, while
SLC38A1, SERPINA5,
HOXB2 gene expression was downregulated and the AUC value was greater than 0.7 in elderly muscles compared to young people, suggesting that these genes and their encoded proteins have the potential to be diagnostic markers for sarcopenia. Among them,
MYH8, HOXB2,
C1QA,
CDKN1A, and
SLC38A1 are associated with sarcopenia [
25], and in this study,
LGR5,
SERPINA5, and
TPPP3 genes were found to be associated with Sarcopenia for the first time. the protein encoded by
LGR5 is a newly discovered G protein-coupled receptor in recent years and is involved in the classical Wnt signaling pathway [
26], Interestingly, the Wnt signaling pathway is involved in skeletal muscle production and development [
27].
SERPINA5 encodes a protein that is a glycoprotein that inhibits a variety of serine proteases, including protein C, various fibrinogen activators, and kinin-release enzymes [
28].
TPPP3 encodes a pro-microtubule polymerization protein that specifically binds to microtubules in vitro and in vivo and may play a role in pro-microtubule aggregation into bundles, cell proliferation, and mitosis [
29]. All of these genes encode proteins that are associated with muscle composition and function and are likely to play a role in the development of Sarcopenia.
The present study also has some limitations, such as a small sample size to better set up biological replicates, and it is only a theoretical study under bioinformatics analysis; the next step should be to perform some molecular biology experiments for validation, to further elucidate the specific mechanisms and effects of sarcopenia activation in vitro.
This study analyzed the possibility of differential genes as a diagnostic molecule for Sarcopenia and explored its possible molecular mechanisms, providing new ideas for the diagnosis of Sarcopenia and the exploration of molecular mechanisms.
Conclusions
In conclusion, our results suggest that the expression of TPP3, C1QA, LGR5, MYH8, and CDKN1A genes are upregulated in sarcopenic patients, while the expression of SLC38A1, SERPINA5, and HOXB2 genes are downregulated and can be used as biomarkers for the diagnosis of sarcopenic patients.
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