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F U L L T I T L E : Immunosenescence profiles are not associated with muscle strength, physical performance and sarcopenia risk in very old adults: The Newcastle 85+ Study.
O P E N A C C E S S S O U R C E : Mechanisms of Ageing and Development
Highlights
• Immunosenescence has been implicated in several age-related disorders.
• Little is known about the link between immunosenescence and muscle ageing in very old adults.
• Immunosenescence profiles were derived by clustering of T-cell senescence biomarkers.
• T-cell senescence was not associated with 5-year decline in muscle function or risk of sarcopenia.
Abstract
Decline in immune system function (immunosenescence) has been implicated in several age-related disorders. However, little is known about whether alteration in T-cell senescence, a process underlying immunological ageing, is related to muscle health in very old adults (aged ≥85 years). Utilising data from the Newcastle 85+ Study, we aimed to (a) derive and characterise immunosenescence profiles by clustering 13 baseline immunosenescence-related biomarkers of lymphocyte compartments in 657 participants; (b) explore the association between the profiles and 5-year change in muscle strength (grip strength) and physical performance (Timed Up-and-Go test), and © determine whether immunosenescence profiles predict 3-year incident sarcopenia. Two distinct clusters were identified; Cluster 1 (‘Senescent-like phenotype’, n = 421), and Cluster 2 (‘Less senescent-like phenotype’, n = 236) in individuals with complete biomarker data. Although Cluster 1 was characterised by T-cell senescence (e.g., higher frequency of CD4 and CD8 senescence-like effector memory cells), and elements of the immune risk profile (lower CD4/CD8 ratio, CMV+), it was not associated with change in muscle function over time, or with prevalent or incident sarcopenia. Future studies will determine whether more in-depth characterisation or change in T-cell phenotypes predict the decline in muscle health in late adulthood.
1. Introduction
A progressive loss of skeletal muscle strength and mass (sarcopenia) leads to impaired function, and increased risk of disability, frailty, and death in older adults (Cruz-Jentoft et al., 2019; Cruz-Jentoft and Sayer, 2019). Alterations in metabolic, hormonal and immune factors have been implicated in the pathogenesis of sarcopenia and age-related loss of muscle function (Cruz-Jentoft and Sayer, 2019; Wilson et al., 2017). Specifically, ageing of the immune system (immunosenescence) is an integral part of the intrinsic biology of ageing, characterised by accumulation of molecular and cellular damage, which results in the appearance of a diverse array of pathobiological hallmarks (López-Otín et al., 2013; Kirkwood, 2005). In this scenario, overlap among causal pathways might be revealed by links between sarcopenia and immunosenescence.
Although research about the role of immunosenescence in sarcopenia, independently or through inflammation, lags behind other mechanistic studies, the evidence linking immune system and skeletal muscle is growing (Nelke et al., 2016; Saini et al., 2017; Schiaffino et al., 2017; Wilson et al., 2017). With regard to immune factors, older adults experience profound change in immune system function due to systemic decline in both adaptive and innate immunity (Licastro et al., 2005; Le Page et al., 2018; Moro-García et al., 2013; Pawelec et al., 2010; Ventura et al., 2017), resulting in reduced ability to fight infections and tumours, and increased chronic low-grade inflammation (inflammageing) (Moro-García et al., 2013; Ventura et al., 2017). The main features of immunosenescence in adaptive immunity include reduced numbers of naïve T-cell lymphocytes due to thymic atrophy, and expansion of highly differentiated, antigen-specific T-cells, such as cytotoxic CD8+ and CD28- CD4+ T-cells (Le Page et al., 2018; Moro-García et al., 2013). These lymphocyte compartments, characterised by replicative senescence, accumulate with advancing age in healthy older adults, in those with autoimmune disorders, and in patients exposed to chronic viral infections, such as cytomegalovirus (CMV) (Pawelec et al., 2010). Seropositivity for CMV (CMV+), an element of the ‘immune risk profile’ (Pawelec et al., 2010), has been recognised as one of the main drivers of highly differentiated (senescent) CD8 + T lymphocytes (Jergović et al., 2019). An inverted CD4:CD8 ratio of <1, another element of the immune risk profile (Jergović et al., 2019), has been linked to a depleted naïve T cell pool and compromised immune response to new pathogens and vaccinations in older adults (Ventura et al., 2017). Although less profound, another key feature of the ageing immune system is defects in the function of innate immune cells such as natural killer (NK) cells, neutrophils, macrophages, and dendritic cells (Ventura et al., 2017; Wilson et al., 2017).
The immunosenescence phenotype includes inflammageing, which is characterised by increased production of pro-inflammatory cytokines (e.g. interleukin 1β (IL-1β), IL-6, tumour necrosis factor α (TNF-α)) and other inflammatory markers by senescent cells and adipose tissue (Ventura et al., 2017; Wilson et al., 2017). This chronic low-grade inflammation is induced, in part, by constant antigen exposure (infections) and oxidative stress, and has been implicated in pathophysiology of several age-related diseases, including sarcopenia (Michaud et al., 2013; Ventura et al., 2017; Wilson et al., 2017). Recently, immunosenescence has been shown to play a role in age-related muscle atrophy, myofibre denervation and reduced regeneration upon injury (Saini et al., 2016; Schiaffino et al., 2017) in animal models. Also, skeletal muscle has been proposed as a regulator of the immune system, partly by secretion of myokines affecting the maintenance and regulation of immune cells and having pro-inflammatory and catabolic effects (reviewed in Nelke et al., 2019).
Studies that have investigated the link between markers of immunosenescence and physical functioning, sarcopenia and frailty in older adults are sparse, and yielded mixed results based on cross-sectional analyses of a few biomarkers. Lower lymphocyte count was independently associated with a higher risk of combined sarcopenia and frailty in Spanish older patients (aged 77.3 ± 8.4 years) recruited from hospitals and outpatient clinics with at least two chronic conditions at admission (Bernabeu-Wittel et al., 2019). A negative correlation between the lymphocyte count and frailty, but a positive association between the lymphocyte count and hand grip strength was observed in Spanish older women (aged 84.2 ± 6.5 years) living in the community (Fernández-Garrido et al., 2014). In the Berlin Aging Study (BASE-II study) of older adults (aged 60-85 years), several immunosenescence-related biomarkers (CMV+, leukocyte telomere length, IL-6 levels) were not associated with grip strength (Goldeck et al., 2016). In the Lothian Birth Cohort 1936 of older adults aged ≥70 years, CMV + was associated with smaller neck muscle cross-sectional area even after adjustment for IL-6 in men but not in women (Kilgour et al., 2013). A strong male-specific correlation was observed between the increased proportion of the CD27- IgD- B late memory cells and the physical capacity decline and frailty in a subcohort of The Vitality 90+ study of Finish nonagenarians (Nevalainen et al., 2019). In the BELFRAIL Study of community-dwelling older adults aged ≥80 years (the very old) from Belgium, a CD4:CD8 ratio >5 was counterintuitively associated with impaired physical performance (Short Physical Performance Battery) in CMV + participants (Adriaensen et al., 2017).
Utilising longitudinal data from the Newcastle 85+ Study, we have described previously the trajectories of muscle strength and physical performance in very old adults (Granic et al., 2016), and investigated their relationship to potential determinants such as other biological markers, including inflammation and serum vitamin D (Granic et al., 2017a; Granic et al., 2017b). However to our knowledge, no prospective studies have investigated the association between immunosenescence profiles defined from a set of immunosenescence-related biomarkers and trajectories of muscle strength and physical performance, or risk of sarcopenia in very old adults. Therefore, employing data from the Newcastle 85+ Study, we aimed to: (a) derive immunosenescence profiles by clustering immunosenescence-related biomarkers of lymphocyte compartments and to characterise them in relation to socio-demographic, health, and lifestyle factors; (b) explore the association between the profiles, muscle strength (grip strength) and physical performance (Timed Up-and-Go test, TUG) decline over 5 years, and © determine whether immunosenescence profiles were associated with the risk of prevalent and 3-year incident sarcopenia in very old adults.
2. Materials and Methods
2.1. Study population
The Newcastle 85+ Study is a prospective, population-based study of very old adults living in Newcastle and Tyneside area, United Kingdom. The study aimed to investigate biological, psychological and social influences of ageing of individuals born in 1921 at baseline (2006/07) and their health trajectories over 5 years (1.5- (wave 2), 3- (wave 3), and 5-year (wave 4) follow-up). The study details have been described previously (Collerton et al., 2007; Collerton et al., 2009) and are available at http://research.ncl.ac.uk/85plus/. A complete multidimensional health assessment at baseline (wave 1), including the review of general practice records, was available for 845 participants. Of those, 657 (77.8%) had complete values for 13 immunosenescence-related biomarkers of lymphocyte compartments to establish immunosenescence profiles comprising the analytic sample for the present study at baseline.
The study was approved by the Newcastle and North Tyneside 1 Research Ethics Committee, and conducted in accordance with the Declaration of Helsinki. A written informed consent was obtained from all participants; for those who lacked the capacity to consent, the consent was obtained from a relative or carer.
2.2. Blood-based biomarkers
Blood-based biomarkers from 749 participants were analysed in peripheral blood samples drawn between 7-10:30 am after an overnight fast (no drinks including coffee and tea, and food), and delivered to the laboratory (the Royal Victoria Infirmary, Newcastle upon Tyne, UK) for initial processing within 1 hour as described previously (Martin-Ruiz et al., 2011; Spyridopoulos et al., 2016). All blood samples were collected within 6 months post-baseline assessments, except for CMV serostatus (within 18 months) (Martin-Ruiz et al., 2011).
2.2.1. Lymphocyte compartments
Lymphocyte immunophenotyping and gating strategy has been described in detail previously (Martin-Ruiz et al., 2011; Spyridopoulos et al., 2016). Briefly, we used 4-colour flow-cytometry (Becton Dickson FACScan Flow Cytometer) and fluorescence-labelled antibodies (BD Bioscience, Oxford UK) to analyse blood samples. The marker combination to define lymphocyte compartments are described in Table A.1 (Appendix A). The senescence-like phenotype in T-cells was defined as the lack of CD27 and CD28 receptor expression in the CD4 subset (marker combination: CD4+CD45RO+CD27-CD28-) and the lack of CD45RO and CD27 expression in the CD8 T effector memory cells (TEMRA; marker combination: CD3+CD8+CD45RO-CD27-), as previously described by us (Spyridopoulos et al., 2016). These marker combinations were regarded as appropriate markers of a senescence-like T-cells phenotype because of the presence of telomere dysfunction and reduced proliferation in the cells (discussed in Spyridopoulos et al., 2016). Lymphocyte compartments frequencies that were considered to establish immunosenescence profiles and the frequency of CD4 and CD8 and B cells ratios are reported in Table A.2.
2.2.2. Other biomarkers
For CMV seropositivity, CMV IgG concentration was determined using bioMerieux VIDAS (bioMerieux SA, France) fluorescent assay (sensitivity: 99.2%; specificity: 100%) and expressed in arbitrary units (AU < 4 for CMV-, and AU ≥ 6 for CMV+) (Spyridopoulos et al., 2016). C-reactive protein (CRP) was measured using Dade Behring CardioPhase high sensitivity CRP assay (Martin-Ruiz et al., 2011). Production of interleukin-6 (IL-6) was measured in supernatant of lipopolysaccharide-stimulated peripheral blood mononuclear cells (PBMC) by electrochemiluminescence as described (Martin-Ruiz et al., 2011). CMV seropositivity and a low CD4/CD8 ratio of <1 have been regarded as elements of the immune risk profile, a simplified parameter of an ageing immune system.
2.3. Muscle strength and physical performance
2.3.1. Grip strength
Grip strength was measured using a hand-held dynamometer (Takei A5401 digital 0-100 kg x 0.1kgLCD) (Martin-Ruiz et al., 2011). In a standing position and with the elbows at approximately 180° angle, participants were instructed to squeeze the dynamometer as hard as possible alternating between the hands. Two measurements (in kg) for each hand were obtained and the maximum of four measurements for each participant (mean (M), standard deviation (SD)) was calculated (Roberts et al., 2011), and used in the analysis. In the analytic sample (n = 657), data to calculate the maximum grip strength was available for 646 (98.3%) participants at baseline (wave 1), 499 (76%) at wave 2, 380 (57.8%) at wave 3, and 254 (38.7%) at wave 4.
2.3.2. Timed Up-and-Go (TUG) test
Physical performance was assessed by the TUG test (Podsiadlo and Richardson1991). The time needed to get up from a chair (seat height 46 cm from the floor), walk in straight line for 3 m to and back from a marker placed on the floor, and sit back on the chair was recorded in seconds (s) with a stopwatch. Each participant performed the test only once and the use of walking aids (e.g. cane, walking frame, and wheeled walker) was documented at each wave. In the analytic sample, TUG data was available for 613 (93.3%) participants at baseline, 454 (69.1%) at wave 2, 339 (51.6%) at wave 3, and 231 (35.2%) at wave 4.
2.4. Sarcopenia
To establish the prevalence (wave 1 and wave 3) and incidence of sarcopenia (wave 3) in 657 participants, we used the revised European Working Group for Sarcopenia in Older People (EWGSOP 2) algorithm (Cruz-Jentoft et al., 2019; Cruz-Jentoft and Sayer, 2019). Sarcopenia was defined as the presence of both weak grip strength (<27 kg in men, and <16 kg in women) and low skeletal muscle index (SMI; skeletal muscle mass divided by height square, kg/m2) of <8.87 kg/m2 in men, and <6.67 kg/m2 in women (as described previously in Dodds et al., 2017 in this cohort). Complete data for prevalent sarcopenia in the analytic sample was available for 598 (91%) at baseline, and 332 (50.5%) at wave 3. The severity of sarcopenia was confirmed by the presence of low TUG (≥20 s). Complete data (grip strength, SMI, and TUG) to establish severe sarcopenia was available for 587 (89.3%) participants at baseline, and 320 (48.7%) at follow-up (wave 3). Body composition, including muscle mass was estimated with the Tanita-305 bioimpedance inbuilt algorithm (Tanita Corp., Tokyo, Japan).
2.5. Other measures and covariates
We used several socio-demographic, anthropometric, and health variables assessed at baseline to describe the immunosenescence profiles or to include them in multivariable analyses. The levels for all categorical variables are described in Table 1. Socio-demographic variable included sex, education, and social class coded to the National Statistics Socio-economic Classification (NS-SEC) system (Chandola and Jenkinson, 2000). Anthropometry included fat-free mass assessed by bioimpedance, height, and BMI. Other health-related variables were self-rated health compared with others of the same age, number of diseases reported from general practice records, cognitive impairment (Standardised Mini-mental State Examination, SMMSE), self-reported physical activity (Granic et al., 2019), and arthritis in hands (of any kind, including osteoarthritis, rheumatoid arthritis, other arthritis and non-specified arthritis in one or both hands). Overall attrition over 5-year follow-up (wave 2 to 4) was categorised as completing the study or not (due to mortality or withdrawal).
