Abstract
In recent years, studies have found that Sarcopenia alters inflammatory biomarkers. However, the behavior of inflammatory biomarkers at different stages of Sarcopenia is not well understood. This study aimed to compare a broad panel of inflammatory biomarkers in older women at different stages of Sarcopenia. The study included 71 Brazilian community-dwelling older women. Muscle Strength was assessed by using handgrip strength (Jamar dynamometer). The Short Physical Performance Battery (SPPB) was performed to assess the physical performance, and body composition was assessed by DEXA. Sarcopenia was diagnosed and classified according to the EWGSOP2 criteria. Blood was drawn, and inflammatory biomarkers associated with Sarcopenia (IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, TNF, adiponectin, leptin, resistin, BDNF, sTNFr-1 and sTNFr-2) was analysed. After diagnosis and classification of sarcopenia, 45% of women did not present Sarcopenia (NS, N = 32), 23.9% were diagnosed with Sarcopenia Probable (SP, N = 17), 19,7% with Sarcopenia Confirmed (SC, N = 14), and 11.3% with Severe Sarcopenia (SS, N = 8). The analysis of inflammatory biomarkers revealed that the more advanced the stage of Sarcopenia, the higher the levels of BDNF, IL-8, sTNFr-1, and sTNFr-2. The assessment of BDNF, IL-8, sTNFr-1, and sTNFr-2 levels may be an adjuvant tool in diagnosis and severity classification of Sarcopenia in older Brazilian women.
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Introduction
According to the International Classification of Diseases (ICD-10-MC-M62.84), Sarcopenia is a syndrome characterized by progressive loss of muscular mass, muscle strength, and physical function that increases risk of falls, hospitalization and mortality1,2,3.
Sarcopenia affects older people globally to a range of 10–27%4, while in Brazil it ranges from 1.8%5 to 49.2%6. This variation is caused by the use of different instruments for assessing muscle mass and strength, distinct cut-off points for each global population, and different classification algorithms4. Evidence indicates the feminization of aging in Brazil7, increasing the rates of Sarcopenia in older women. Advanced age, cognitive impairment, lower income, smoking, and malnutrition are potential risk factors for the incidence and severity of Sarcopenia8. In 2010, the European Study Group on Sarcopenia (EWGSOP1) presented classification criteria for the three stages of Sarcopenia: pre-sarcopenia, Sarcopenia, and severe Sarcopenia9. However, in 2018 the EWGSOP revised the guidelines. The diagnostic process consisted of three steps: (1) screening for low muscle strength to identify individuals with probable Sarcopenia; (2) identifying low muscle mass to confirm the presence of Sarcopenia; and (3) identifying low physical performance to assess the severity of Sarcopenia1. Thus, the classification was stratified into non Sarcopenia, probable Sarcopenia, confirmed Sarcopenia, and severe Sarcopenia.
Sarcopenia is also characterized by endocrine, inflammatory, and metabolic disorders, and the balance of pro- and anti-inflammatory biomarkers regulates muscle regeneration mechanisms playing a critical role in determining the disease severity10,11,12. A pro-inflammatory profile is frequently associated with a reduction in muscle mass, strength, mobility, and physical performance in sarcopenic individuals3,11,12.
The measurement of clinical biomarkers is faster and less expensive than the direct measurement of the final clinical outcome for sarcopenia diagnosis13. Biomarkers are generally used to screen, diagnose, characterize, and monitor diseases13. However, the potential biomarkers involved in the pathogenesis of Sarcopenia have been the topic of of intense debate3,10,11,12. Thus, the development of a panel of inflammatory biomarkers to assist in the diagnosis and severity classification of Sarcopenia has been a major area of interest3. Adiponectin, Leptin, Resistin, Interleukin (IL)-6, IL-8, IL-10, tumoral necrosis factor (TNF), soluble receptor of TNF (sTNFr)-1 and sTNFr-2 have been reported as potential inflammatory biomarkers associated with the diagnosis of Sarcopenia, and an imbalance between pro- and anti-inflammatory cytocines was associated with loss of mass and muscle function and locomotor disabilities10,11,12,13. Brain-derived neurotrophic factor (BDNF) has also been identified as a possible biomarker related to sacopenia14,15. The presence of high concentrations of pro-inflammatory markers are related to greater systemic and skeletal muscle inflammation, indicative of the presence and severity of sarcopenia10,11,12,13,14,15.
However, a panel of biomarkers that characterize the diagnosis and severity of sarcopenia has yet to be studied10,11. The identification of biomarkers that describe Sarcopenia is challenging due to the disease's complexity and multifactorial pathogenesis10,16. In this context, the purpose of this study was to compare a panel of inflammatory biomarkers among older women with different stagies of Sarcopenia.
Methods
Study design
This is an exploratory, observational, and cross-sectional study. The study was approved by the Research Ethics Committee of the Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM) (protocol 1.461.306). All participants signed a written Informed consent. All evaluations were carried out between June 2016 and June 2017 at the Laboratório de Fisiologia do Exerccio (LAFIEX) and Laboratório de Inflamaço e Metabolismo (LIM) from the UFVJM.
Participants
Older women from the community were considered for the present study. A survey was carried out of the total number of older women (> 65 years) registered in all primary care units in the city of Diamantina, Minas Gerais, Brazil. All addresses were visited to invite participants. All participants who accepted the invitation answered a clinical questionaire. The inclusion criteria were women over the age of 65 who were functionally independent in the community and capable of completing the study evaluations. The exclusion criteria was subjects who had comproved cognitive disfunction in the Mini Mental State Examination (MMSE)14; those with neurological sequelae; those who were hospitalized less than 3 months ago; who had fractures in the lower or upper limbs for less than 6 months; who had acute musculoskeletal disorders that interfered with the proposed physical assessments; who had acute respiratory or cardiovascular diseases; that they could not perform the respiratory measures maneuvers; who had an inflammatory disease in the acute phase; neoplasm in activity in the last 5 years; in palliative care; who were using anti-inflammatory medications or drugs that act on the immune system; and those with significant visual or auditory deficits that would make it impossible to carry out the proposed procedures.
Procedures
The evaluations were carried out during three laboratory visits on three different days. On the first visit, participants who met the eligibility criteria signed the written informed consent, and answered the clinical health interviews. On the second visit, participants underwent body composition measurements in the morning while fasting from food, beverages, and medications. After a 15-min pause for rest, all participants performed the handgrip strength and physical performance tests. On the third visit (24 h after physical tests), participants’blood samples were drawn for analysis of blood inflammatory biomarkers.
Assessment of muscle strength
Handgrip strength (HGS) was evaluated using a Jamar dynamometer. The participant was instructed to maintain a seated position with a neutral hand, flexed elbow, and neutral shoulder. The HGS measurement, i.e., an isometric contraction the dominant hand applied on the handles of the dynamometer, was expressed in kilogram-force (kgf). The average of three measurements was used for the analysis15. The cutoff point adopted was < 20 kgf for women established by physical function for diagnosis of Sarcopenia in a longitudinal study on aging1,16.
Assessment of body composition
Body composition was measured using Dual X-ray Absorptiometry (DXA Lunar Type DPX—encore software 2005), one of the gold standard method for assessing muscle mass in Sarcopenia17,18. Body composition measurements were conducted in the morning by the same researcher (08:00 a.m.). Skeletal muscle mass index (SMI) was calculated by the ALM/height squared ratio (ALM/h2), the cutoff point used for low SMI was < 5.5 kg/m21,9.
Assessment of physical performance
The Short Physical Performance Battery (SPPB) test was used to evaluate the physical capacity of participants with respect to their balance, gait speed, and lower limb muscular strength19. The SPPB is composed of tests of static balance while standing, walking speed at the usual pace, and muscle strength of the lower limbs estimated by the sit-to-stand test from an armless chair. A final score of 12 points is calculated for each test based on the performance indicated by scores ranging from 0 to 4 (respectively, the worse and better performance). Participants who obtained scores from 0 to 3—had a poor performance or had inability; from 4 to 6—had low performance; from 7 to 9—had moderate performance; from 10 to 12—had good performance19. The cutoff point for low physical performance was ≤ 8 points1,9.
Sarcopenia stages classifications
Sarcopenia was diagnosed by performing the evaluations according to the EWGSOP2 guidelines, beginning with muscle strength, to identify older women with probable Sarcopenia1. To confirm Sarcopenia and determine severe Sarcopenia, we utilized the classification criteria proposed by the EWGSOP19, which proposes the diagnosis based on the documentation of criterion 1, plus criterion 2 or criterion 3 to confirm Sarcopenia, and the presence of all three criteria to confirm severe Sarcopenia. Therefore, the participants were classified into four groups: (1) non-sarcopenia (NS)—Those who did not have loss in muscle strength, in muscle mass and physical performance; (2) sarcopenia probable (SP)—Those who had only loss of muscle strength; (3) Sarcopenia Confirmed (SC)—Those who had loss of muscle strength together with loss of muscle mass or low physical performance; and (4) Severe Sarcopenia (SS)—Those who had loss of muscle strength, muscle mass and low physical performance concomitantly.
Analysis of blood inflammatory biomarker
Blood was drawn at 8 a.m. (10 mL from the antecubital fossa of the upper limb with disposable material) after participants fasted from food and drink and without using medication for 10 h. The samples were drawn in vacutainer bottles with heparin in a sterile environment. Immediately after this procedure, the samples were centrifuged at 3000 rpm in a centrifuge for 10 min. Plasma samples were extracted and kept at − 80 °C for 6 months before being analyzed. The IL-2, IL-4, IL-5, IL-10, TNF, adiponectin, leptin, resistin, BDNF, sTNFr-1 and sTNFr-2 levels were analyzed by Enzyme-linked Immunosorbent technique (ELISA) (Duo-Set, R&D Systems, Minneapolis, USA). The plasma levels of IL-6, IL-8, and IFN were measured using the cytometric bead arrays kit (BD Bioscience, San Jose, CA) according to the manufacturer’s protocol. Samples were acquired in a FACSCanto flow cytometer (BD Bioscience) and analyzed using the FCAP array v1.0.1 software (Soft Flow)20.
Statistical analyses
Openepi Software (www.openepi.com) was used to determine the sample size, taking into account a population of 2522 older women (> 65 years old) in the municipality of Diamantina, Minas Gerais, as registered by the Brazilian Institute of Geography and Statistics (IBGE—ibge.gov.br). Thus, considering a sarcopenia prevalence of 16%7, an effect size of 0.80, a significance level of 5%, and a confidence interval of 80%, a sample size of 71 older women were met. The Statistical Package for the Social Sciences (SPSS Statistics, version 22.0, IBM, Armonk, NY, USA) and the Med-Calc Statistical (Med-Calc Software, version 13.1, Ostend, Belgium) softwares were used for statistical analyses. Data normality was verified by the Kolmogorov–Smirnov test. Continuous variables were expressed as the minimum and maximum values and median. The one-way ANOVA test was used for comparison between groups when the variables were parametric, and the Kruskal Wallis test for independent samples was used for comparison between groups when the variables were non-parametric.
Institutional review board statement
The study will be conducted according to the guidelines of the Declaration of Helsinki and was approved by the Institutional Ethics and Research Committee of Federal University of Jequitinhonha and Mucuri Valleys (protocol code 1.461.306 on 22 March of 2016).
Informed consent
Informed consent will be collected from all subjects involved in the study.
Results
A total of 411 older women were identified based on their BHU registration. One hundred and ten addresses were not found, and thirty-one were excluded since they did not meet the study's age criteria inclusion.Two hundred seventy women were interviewed, and a total of 114 were excluded based on the exclusion criteria. One hundred fifty-six women living in the community were eligible for the study. Eighty-five older women did not complete all evaluations; thus, the sample size was composed of 71 women. After the evaluations, we found 32 women without Sarcopenia, 17 with probable Sarcopenia, 14 with verified Sarcopenia, and 8 with severe Sarcopenia after the evaluations (Fig. 1).
The diagnosis of probable sarcopenia (SP) confirmed Sarcopenia (SC) and severe Sarcopenia (SS) was found in 23.9%, 19.7% and 11.3% respectively. Participants had a mean age of 75 years old (± 7), a mean height of 1.50 m (± 0.05), a mean muscle mass index (SMI) of 6.39 kg/m2 (± 1.05), a mean handgrip strength (HGS) of 19.9 kgf (± 6.38), and a mean of 8.62 points (± 2.01) in the SPPB test. Blood inflammatory biomarker data revealed an increase in the ratio of pro inflammatory biomarkers as the severity of Sarcopenia increased (Table 1).
Analysis of the distribution of biomarkers showed significant differences in the plasmatic concentrations of BDNF, IL-8, sTNFr-1 and sTNFr-2 between all groups (Fig. 2).
Distribution of biomarkers between groups. Plasma concentrations of biomarkers are higher in groups with more severity of sarcopenia. Comparisons were made using the ANOVA test and kruskal wallis depending on the distribution of the variable. In (a) plasma concentrations of BDNF (pg/ml). (b) IL-8 (pg/ml). (c) sTNFr-1 (pg/ml). (d) sTNFr-2 (pg/ml). Blood inflammatory biomarkers of the participants according to the sarcopenia severity (n = 71). BDNF brain derived neurothophic factor, TNF tumor necrosis factor, sTNFr soluble receptor of TNF, IL-8 interleukin 8; *difference statistically significant using Kruskal Wallis test for independent samples (*p < 0.05 and **p < 0.01).
Discussion
To our knowledge, this is the first study to investigate a broad panel of inflammatory biomarkers according to the severity of Sarcopenia in older women. The major finding of this study is that when the severity of Sarcopenia increases in older Brazilian women, an imbalance in inflammatory biomarkers occurs that favors a pro-inflammatory state. Specifically, we found higher levels of BDNF, IL-8, sTNFr-1 and sTNFr-2 as the sarcopenia severity increased.
As expected, body composition results revealed lower levels of muscle mass and strength, as well as physical performance, as the severity of Sarcopenia increased1,2,4,9,21,22. Interestingly, there was no difference in age between the groups, indicating that the severity of sarcopenia can occur regardless of more advanced age. In addition, no differences were found in the height among SS and NS groups, indicating that height is not a determinant factor for the diagnosis of severe sarcopenia.
The increased levels of IL-8 in the SP and SS groups compared to the NS group indicate that Sarcopenia induces a pro-inflammatory state. Interleukin-8 (IL-8) is a chemotactic factor that promotes inflammation12, and high plasma levels of this biomarker were associated with less strength gain during resistance training, less lean body mass, and a greater risk of Sarcopenia11,12. In line with these results, IL-8 levels increased as the severity of Sarcopenia increased among the participants of this study. The differences were observed in two situations: among NS and SP groups, and among NS and SC groups. Within sarcopenia subgroups there was no significate difference in the concentration of this marker i.e., no significant differences were found in IL-8 among the SP and SC or SS groups. In addition, there was no significant difference in IL-8 levels between NS and SS groups. These results might indicate that IL-8 increases in the early stages of Sarcopenia.
The levels of IL-8, sTNFr-1, and sTNFr-2 differed among the groups with confirmed Sarcopenia, and these differences probably contribute to the impaired muscular strength in these groups. In a previous study, we demonstrated that sTNFr-1 and sTNFr-2 are predictors of the functional performance of individuals with chronic diseases, with high levels of these biomarkers correlated to poor performance23. Other studies have reported that sTNFr-1 initiates the inflammatory response and stimulates realease IL-624 and others pro- and anti-inflammatory cytokines6,24,25.
Schaap et al. found a negative correlation between sTNFr-1 and a 5-year change in thigh muscle area in the older25. Similarly, Gonzalo-Calvo et al. found that high levels of sTNFr-1 are associated with functional dependency in the older population26. However, opposite results were found by Lustosa et al., who investigated the association between muscular strength and blood sTNFr-1 levels in 63 community-dwelling older women divided into non-sarcopenic (n = 32) and sarcopenic (n = 31) groups6. Using the same EWGSOP1 algorithm, tools, and procedures as in the present investigation, they found that sarcopenic older women had lower muscle strength and blood sTNFr-1 levels than non-sarcopenic older women (p = 0.01). However, as Lustosa et al. categorized the sample into only two groups, they were unable to examine sTNFr-1 levels at different stages of Sarcopenia. According to our findings, the levels of sTNFr-1 increased as the severity of Sarcopenia increased; nevertheless, we identified statistically significant differences only between the non-sarcopenic and sarcopenic groups.
Recently, sTNFr-2 levels were positively correlated with serum progranulin levels, a key marker of frailty; however, sTNFr-2 levels were not associated with Sarcopenia (assessed by SARC-F)27. Other studies found that reduction in the sTNFr-2 levels and were associated with improvements in health conditions28 and physical performance in individuals with chronic diseases23. In the current investigation, as Sarcopenia is more severe, sTNFr-2 levels were higher, and statistically significant differences were identified between the NS and SC and SS groups. These results indicate a pivotal role of sTNFr-2 in the inflammatory responses of Sarcopenia, especially when muscle strength and mass, as well as physical performance, reduce.
Brain-derived neurotrophic factor (BDNF) is a neurotrophin involved with neuronal growth, differentiation, and plasticity29. In skeletal muscle BDNF is involved with the development and differentiation of myoblasts into muscle fibers, motoneuron survival and transmission synaptic30. BDNF is produced in skeletal muscle cells especially during muscle contractions or in response to injury31, acting in an autocrine or paracrine manner, and playing an important role in muscle repair30. Increased levels of BDNF have also been reported in severe illnesses characterized by high levels of systemic inflammation31. Similarly, our findings also revealed a possible association between BDNF levels and the severity of Sarcopenia. Interestingly, the most significant differences were observed between sarcopenic groups, suggesting the involvement of BDNF in the severity of Sarcopenia.
BDNF has been found to play a critical role in regulating neuromuscular function during aging in a mouse model32. On the other hand, other studies found that frailty older Korean and Japanese presented low levels of BDNF and was negatively associated with physical performance and severity of Sarcopenia29. Serum BDNF levels were positively correlated with quadriceps femoris thickness (= 0.096, p = 0.006), however there was no association between BDNF and handgrip strength (= 0.046, p = 0.197) or walking frequency. Interestingly, participants who required assistance to stand from their chairs had significantly (p = 0.028) lower serum BDNF levels than those who stood without assistance34. Importantly, the measuring instruments were imprecise, and questionnaires were used to evaluate crucial physical and functional characteristics of the study participants34. In this investigation, we employed the methodologies, tools, and algorithm closest to the recognized gold standard for the evaluation of Sarcopenia.
It should be emphasized that BDNF levels differed across all stages of Sarcopenia, demonstrating a correlation between the progression of Sarcopenia and BDNF production in community-dwelling older women. There is evidence that BDNF expression increases in response to muscle injury, and inflammation can stimulate the generation of high levels of BDNF30,31,35. This enables us to hypothesize that BDNF is implicated in the physiopathology of Sarcopenia and that its rise is related to muscle injury and impaired neuromuscular synaptic transmission caused by Sarcopenia and its progression. Further study along these lines is required to elucidate the pathophysiological mechanism underlying the association between BDNF and sarcopenia severity.
Using the same population, studies comparing EWGSOP1 with EWGSOP2 guidelines found substantial differences in prevalence, clinical outcomes, and risk factors36,37. Thus the order of screening and assessment can result in different outcomes found. Recently, Sayer and Cruz–Jentoft published a commentary suggesting that muscle mass levels are a common element for the diagnosis of various health conditions, including sarcopenia2.
Inflammatory biomarkers that indicate muscle catabolism are highly correlated with frailty in multimorbid patients38, and previous studies have associated adiponectin levels with reduced appendicular muscle mass independent of body fat in older women39. It is crucial to consider the algorithm employed in our sample for evaluating screening procedures based on handgrip strength, being muscle mass or physical performance is a secondary component in determining Sarcopenia. Thus, there may exist distinct and specific biomarkers that indicate low muscle strength, muscle mass, and physical function, as well as when these losses occur concomitantly. Further studies are needed to determine whether or not there is a biomarker capable of distinguishing the loss of strength, muscle mass, and physical performance in sarcopenic older individuals.
We highlight that the sample analyzed in this study was homogeneous, thereby reducing the influence of clinical, sociodemographic, cultural, functional, or lifestyle characteristics. The present study should be interpreted with caution due to the short duration of observation (cross-sectional design), the limited number of older women evaluated in each group, and the absence of correlation or association analyses. Nevertheless, even with a small sample size, statistically significant differences were observed, and we used the methodologies, instruments, and algorithm closest to the gold standard methods for sarcopenia evaluation. In addition, other strengths of the present study were the investigation of a large panel of biomarkers previously associated with Sarcopenia, the blinding of the researchers in the evaluations, the methodological rigor, and the tight inclusion and exclusion criteria of the study.
Our study provides information on the behavior of several inflammatory biomarkers according to the severity of Sarcopenia in older women and indicates a worsen in phisical performance and a pro-inflamatory state as sarcopenia increases in severity.
In clinical terms, our study describes the behavior of several inflammatory biomarkers accordinf to the severity of Sarcopenia and reveals a decline in physical performance and a pro-inflammatory state as the severity of sarcopenia increases in older women. This study's findings may also be valuable for clinicians and researchers seeking a more comprehensive understanding of the diagnosis and severity of sarcopenia.
Conclusion
Taken together, the results of this study reveal for the first time that the greater the severity of Sarcopenia in older women, the higher the blood levels of BDNF, sTNFr1, sTNFr2, and IL-8. These findings may improve the comprehension of the diagnosis and severity of Sarcopenia in older women.
Data availability
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the privacy guarantee of the data collected individually.
References
Cruz-Jentoft, A. J. et al. Sarcopenia: Revised European consensus on definition and diagnosis European working group on sarcopenia in older people 2 (EWGSOP2), and the extended group for EWGSOP2. Age Ageing 48, 16–31. https://doi.org/10.1093/ageing/afy169 (2019).
Sayer, A. A. & Cruz-Jentoft, A. Sarcopenia definition, diagnosis and treatment: consensus is growing. Age Ageing 51, 10. https://doi.org/10.1093/ageing/afac220 (2022).
Wiedmer, P. et al. Sarcopenia—Molecular mechanisms and open questions. Ageing Res. Rev. 65, 1. https://doi.org/10.1016/j.arr.2020.101200 (2021).
Petermann-Rocha, F. et al. Global prevalence of sarcopenia and severe sarcopenia: a systematic review and meta-analysis. J. Cachexia Sarcopenia Mus. 13(1), 1. https://doi.org/10.1002/jcsm.12783 (2022).
Szlejf, C., Suemoto, C. K., Lotufo, P. A. & Benseñor, I. M. Association of sarcopenia with performance on multiple cognitive domains: Results from the ELSA-Brasil Study. J. Gerontol. Ser. Biol. Sci. Med. Sci. 74(11), 1. https://doi.org/10.1093/gerona/glz118 (2019).
Lustosa, L. P. et al. Comparison between parameters of muscle performance and inflammatory biomarkers of non-sarcopenic and sarcopenic elderly women. Clin. Interv. Aging 12, 1. https://doi.org/10.2147/CIA.S139579 (2017).
Diz, J. B. M. et al. Prevalence of sarcopenia in older Brazilians: A systematic review and meta-analysis. Geriatr. Gerontol. Int. 17, 1. https://doi.org/10.1111/ggi.12720 (2017).
Alexandre, T. D. S., Duarte, Y. A., Santos, J. L. F. & Lebrão, M. L. Prevalência e fatores associados à sarcopenia, dinapenia e sarcodinapenia em idosos residentes no Município de São Paulo—Estudo SABE. Rev. Bras. Epidemiol. 21(suppl 2), 1. https://doi.org/10.1590/1980-549720180009.supl.2 (2018).
Cruz-Jentoft, A. J. et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 39(4), 1. https://doi.org/10.1093/ageing/afq034 (2010).
Curcio, F. et al. Biomarkers in sarcopenia: A multifactorial approach. Exp. Gerontol. 85, 1. https://doi.org/10.1016/j.exger.2016.09.007 (2016).
Pan, L. et al. Inflammation and sarcopenia: A focus on circulating inflammatory cytokines. Exp. Gerontol. 154, 1. https://doi.org/10.1016/j.exger.2021.111544 (2021).
Wang, T. Searching for the link between inflammaging and sarcopenia. Ageing Res. Rev. 77, 1. https://doi.org/10.1016/j.arr.2022.101611 (2022).
Aronson, J. K., & Ferner, R. E. Biomarkers—a general review. Curr. Prot. Pharmacol. https://doi.org/10.1002/cpph.19 (2017).
Bertolucci, P. H. F., Brucki, S. M. D., Campacci, S. R. & Juliano, Y. O Mini-Exame do Estado Mental em uma população geral: impacto da escolaridade. Arq Neuropsiquiatr 52(1), 1. https://doi.org/10.1590/s0004-282x1994000100001 (1994).
Dias, J. A., Ovando, A. C., Külkamp, W. & Junior, N. G. B. Hand grip strength: Evaluation methods and factors influencing this measure. Revista Brasileira de Cineantropometria e Desempenho Humano 12(3), 1 (2010).
Tessier, A. J., Wing, S. S., Rahme, E., Morais, J. A. & Chevalier, S. Physical function-derived cut-points for the diagnosis of sarcopenia and dynapenia from the Canadian longitudinal study on aging. J. Cachexia Sarcopenia Musc. 10(5), 1. https://doi.org/10.1002/jcsm.12462 (2019).
Scafoglieri, A. & Clarys, J. P. Dual energy X-ray absorptiometry: gold standard for muscle mass?. J. Cachexia Sarcopenia Musc. 9(4), 1. https://doi.org/10.1002/jcsm.12308 (2018).
Buckinx, F. et al. Pitfalls in the measurement of muscle mass: A need for a reference standard. J. Cachexia Sarcopenia Muscle 9(2), 1. https://doi.org/10.1002/jcsm.12268 (2018).
Guralnik, J. M. et al. A short physical performance battery assessing lower extremity function: Association with self-reported disability and prediction of mortality and nursing home admission. J. Gerontol. 49(2), 1. https://doi.org/10.1093/geronj/49.2.M85 (1994).
Neves, C. D. C. et al. Inflammatory and oxidative biomarkers as determinants of functional capacity in patients with COPD assessed by 6-min walk test-derived outcomes. Exp. Gerontol. 152, 1. https://doi.org/10.1016/j.exger.2021.111456 (2021).
Studenski, S. A. et al. The FNIH sarcopenia project: Rationale, study description, conference recommendations, and final estimates. J. Gerontol. Ser. A Biol. Sci. Med. Sci. 69A(5), 1. https://doi.org/10.1093/gerona/glu010 (2014).
Kim, H. et al. Sarcopenia: Prevalence and associated factors based on different suggested definitions in community-dwelling older adults. Geriatr. Gerontol. Int. 16, 1. https://doi.org/10.1111/ggi.12723 (2016).
Arrieiro, A. N. et al. Inflammation biomarkers are independent contributors to functional performance in chronic conditions: An exploratory study. Int. J. Med. Sci. Health Res. 5(4), 1. https://doi.org/10.51505/ijmshr.2021.5404 (2021).
Singh, T. & Newman, A. B. Inflammatory markers in population studies of aging. Ageing Res. Rev. 10(3), 1. https://doi.org/10.1016/j.arr.2010.11.002 (2011).
Schaap, L. A. et al. Higher inflammatory marker levels in older persons: Associations with 5-year change in muscle mass and muscle strength. J. Gerontol. Ser. A Biol. Sci. Med. Sci. 64(11), 1. https://doi.org/10.1093/gerona/glp097 (2009).
de Gonzalo-Calvo, D. et al. Interleukin 6, soluble tumor necrosis factor receptor I and red blood cell distribution width as biological markers of functional dependence in an elderly population: A translational approach. Cytokine 58(2), 1. https://doi.org/10.1016/j.cyto.2012.01.005 (2012).
Nguyen, A. D. et al. Serum progranulin levels are associated with frailty in middle-aged individuals. PLoS ONE 15(9), 1. https://doi.org/10.1371/journal.pone.0238877 (2020).
Figueiredo, P. H. S. et al. Effects of the inspiratory muscle training and aerobic training on respiratory and functional parameters, inflammatory biomarkers, redox status and quality of life in hemodialysis patients: A randomized clinical trial. PLoS ONE 13(7), 1. https://doi.org/10.1371/journal.pone.0200727 (2018).
Miyazaki, S., Iino, N., Koda, R., Narita, I. & Kaneko, Y. Brain-derived neurotrophic factor is associated with sarcopenia and frailty in Japanese hemodialysis patients. Geriatr Gerontol Int. 21(1), 1. https://doi.org/10.1111/ggi.14089 (2021).
Kalinkovich, A. & Livshits, G. Sarcopenia—The search for emerging biomarkers. Ageing Res. Rev. 22, 1. https://doi.org/10.1016/j.arr.2015.05.001 (2015).
Papathanassoglou, E. D. E., Miltiadous, P. & Karanikola, M. N. May BDNF be implicated in the exercise-mediated regulation of inflammation?. Crit. Rev. Synth. Evid. Biol. Res. Nurs. 17(5), 1. https://doi.org/10.1177/1099800414555411 (2015).
Greising, S. M., Ermilov, L. G., Sieck, G. C. & Mantilla, C. B. Ageing and neurotrophic signalling effects on diaphragm neuromuscular function. J. Physiol. 593(2), 1. https://doi.org/10.1113/jphysiol.2014.282244 (2015).
Roh, E. et al. Association of plasma brain-derived neurotrophic factor levels and frailty in community-dwelling older adults. Sci. Rep. 12(1), 18605. https://doi.org/10.1038/s41598-022-19706-3 (2022).
Hachisu, M. et al. Relationships between serum brain-derived neurotrophic factor concentration and parameters for health scores in community-dwelling older adults. Geriatr. Gerontol. Int. 18(3), 1. https://doi.org/10.1111/ggi.13210 (2018).
Casati, M. et al. The biological foundations of sarcopenia: Established and promising markers. Front. Med. 6, 1. https://doi.org/10.3389/fmed.2019.00184 (2019).
Fernandes, L. V. et al. Prevalence of sarcopenia according to EWGSOP1 and EWGSOP2 in older adults and their associations with unfavorable health outcomes: A systematic review. Aging Clin. Exp. Res. 34(3), 1. https://doi.org/10.1007/s40520-021-01951-7 (2022).
Shafiee, G. et al. Comparison of EWGSOP-1and EWGSOP-2 diagnostic criteria on prevalence of and risk factors for sarcopenia among Iranian older people: the Bushehr Elderly Health (BEH) program. J. Diabetes Metab. Disord. 19(2), 1. https://doi.org/10.1007/s40200-020-00553-w (2020).
Kochlik, B. et al. Frailty is characterized by biomarker patterns reflecting inflammation or muscle catabolism in multi-morbid patients. J. Cachexia Sarcopenia Muscle. https://doi.org/10.1002/jcsm.13118 (2022).
Teixeira, L. et al. Clinical medicine adiponectin is a contributing factor of low appendicular lean mass in older community-dwelling women: A cross-sectional study. J. Clin. Med 2022, 7175. https://doi.org/10.3390/jcm11237175 (2022).
Acknowledgements
The authors are grateful to the old woman participants as study volunteers, and the professionals from the Health Department and the Basic Health Units of the municipality of Diamantina, Minas Gerais, for assisting in the conduct of recruitment and facilitating contact with the older population of the sample.
Funding
This study was supported by the Fundação de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG), Conselho Nacional de Desenvolvimento Científico e Tecnológico (Universal CNPq-402574/2021-4), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).
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Report with the name and contribution of each of the authors in the present work: 1. Leonardo A. C. Teixeira: conception, design, execution, interpretation and preparation of table 1 and figure 1 of the study. 2. Núbia C P Avelar: conception, design and interpretation of the study. 3. Marco F D Peixoto: conception, design, interpretation and of the study. 4. Adriana N Parentoni: conception, design, execution and interpretation of the study. 5. Jousielle M Santos: design and interpretation of the study. 6. Fabiana S M Pereira: design and interpretation of the study. 7. Ana L Danielewicz: design and interpretation of the study. 8. Amanda A O Leopoldino: conception, design and interpretation of the study. 9. Sabrina P Costa: design and interpretation of the study. 10. Arthur N Arrieiro: design and interpretation of the study. 11. Luana A Soares: design and interpretation of the study. 12. Vanessa K S Lage: design and interpretation of the study 13. Ana C N Prates: design and interpretation of the study 14. Redha Taiar: design and interpretation of the study 15. Alessandra C Bastone: conception, design and interpretation of the study. 16. Vinicius C Oliveira: design and interpretation of the study. 17. Murilo X Oliveira: design and interpretation of the study. 18. Henrique S Costa: design and interpretation of the study. 19. Juliana N P Nobre: conception, design and interpretation of the study. 20. Franciane P Brant: conception, design, execution and interpretation of the study. 21. Tamiris C Duarte: conception, design and execution of the study. 22. Pedro H S Figueiredo: design and interpretation of the study. 23. Vanessa A Mendonça: conception, design, execution and interpretation of the study. 24. Ana C R Lacerda (corresponding author*): conception, design, execution and interpretation of the study. All authors reviewed the manuscript and we declare that there is no conflict of interest.
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da Costa Teixeira, L.A., Avelar, N.C.P., Peixoto, M.F.D. et al. Inflammatory biomarkers at different stages of Sarcopenia in older women. Sci Rep 13, 10367 (2023). https://doi.org/10.1038/s41598-023-37229-3
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DOI: https://doi.org/10.1038/s41598-023-37229-3
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