Highlights
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Higher serum follistatin levels are linked to a decline in pulmonary function, especially shown by reduced peak expiratory flow (PEF).
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The simultaneous presence of elevated follistatin levels and reduced PEF was independently linked to the risk of all-cause mortality.
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Exploring the potential of follistatin-related treatments to counteract pulmonary function decline in the older population is worthwhile.
Keywords: Pulmonary function, Aging, Follistatin, Biomarkers, Mortality
Abstract
Objectives
The link between aging and pulmonary function decline is well-established, but the underlying mechanisms have yet to be fully revealed. Serum follistatin, a myokine implicated in muscle degeneration, may play a role in age-related pulmonary changes. This study aims to investigate the relationship between serum follistatin levels and pulmonary function decline in community-dwelling older adults, and evaluate their combined association with all-cause mortality.
Research design and methods
This longitudinal cohort study utilized data from 751 participants aged ≥50 years in the I-Lan Longitudinal Aging Study between 2018−2019. Serum follistatin levels, spirometry results, demographic and clinical data were retrieved. Participants were stratified based on their follistatin levels. Survival curves and group comparisons based on follistatin levels and decline in peak expiratory flow (PEF) using Kaplan-Meier analysis and log-rank tests. Multivariate Cox proportional hazards models were further used to identify independent predictors of all-cause mortality during the 52-month follow-up.
Results
Elevated follistatin levels significantly correlated with worse pulmonary function, particularly decreased PEF (p = 0.030). Kaplan–Meier analysis revealed the combination of elevated follistatin levels and decreased PEF was associated with increased risk of all-cause mortality (Log-rank p = 0.023). Cox proportional hazards models further identified that concurrent presence of higher follistatin levels and decreased PEF predicted higher risk of all-cause mortality (adjusted HR 3.58, 95% CI: 1.22–10.53, p = 0.020).
Conclusion
Higher serum follistatin levels correlate with decreased pulmonary function, specifically PEF decline, in community-dwelling older adults. Furthermore, the coexistence of elevated follistatin levels and decreased PEF was associated with risk of all-cause mortality. Follistatin may serve as a biomarker for pulmonary aging and related adverse outcomes.
1. Indroduction
Aging is a process marked by disrupted homeostasis, reduced physiological reserve, diminished organ functionality, heightened occurrence of multiple health conditions, and increased social vulnerability [1,2], ultimately resulting in frailty, disability, and cognitive decline, often exacerbated by psychosocial or environmental stressors [3,4]. The age-related functional abilities decline across cognitive, mobility, and sensory domains, encompassing memory, reasoning, physical strength, balance, and sensory perception such as vision and hearing [5,6]. A critical aspect affected by aging is pulmonary function, where changes in the respiratory system, including reduced lung elasticity, decreased respiratory muscle strength, and diminished gas exchange efficiency, occur with advancing age [7,8]. These alterations may contribute to a decrement in pulmonary function, rendering older adults more susceptible to respiratory ailments such as chronic obstructive pulmonary disease (COPD) and pneumonia [9].
Among all age-related alterations in pulmonary functions, the link between muscle strength and pulmonary function has gain extensive attentions. As individuals age, there is a natural decline in respiratory muscle strength due to factors such as sarcopenia, decreased neural drive, and changes in muscle composition [[10], [11], [12]]. The decline in respiratory muscle function is associated with reduced pulmonary function parameters, including a decrease in forced vital capacity (FVC) and forced expiratory volume in one second (FEV1). Additionally, it affects handgrip strength and dynamic balance [[13], [14], [15], [16]]. Peak Expiratory Flow (PEF), a parameter of spirometry, is also considered an indicator of the respiratory muscles strength and has been recognized as one of the variables for diagnosing sarcopenia by the 2010 European Working Group on Sarcopenia in Older People [17].
Further investigating the molecular underpinnings of sarcopenia, recent studies have identified several circulating factors and biomarkers that serve as indicators of muscle health. Among these, adipomyokines, secreted by skeletal myocytes or adipocytes, encompass interleukin-6, myostatin, and follistatin [[18], [19], [20], [21]]. Serum follistatin, a glycosylated plasma protein of the transforming growth factor-β superfamily [22,23], is emerging as an important biomarker with various physiological functions [[19], [20], [21],24]. As a myostatin antagonist, follistatin sequesters myostatin, preventing its inhibitory effect on muscle growth in the circulation [25,26]. A study also found serum myostatin and follistatin are negatively associated with muscle function, particularly in older women [20]. Despite links between muscle atrophy, declining pulmonary function, and follistatin's potential as a muscle atrophy marker, the interplay between serum follistatin, diminishing pulmonary function, and clinical outcomes in older adults remains unexplored [27,28]. Notably, recent studies have identified follistatin levels as a potential predictor of mortality risk [29,30], warranting further investigation into this association.
Recognizing the established link between declining pulmonary function and adverse clinical outcomes, including mortality, in older adults, this current study aims to bridge the knowledge gap by investigating the association between serum follistatin levels and pulmonary function decline, while also examining their relationships with all-cause mortality in community-dwelling older adults.
2. Material and methods
2.1. Study design and population
The data used in this study were derived from the I-Lan Longitudinal Aging Study (ILAS). ILAS was a prospective cohort study that began in 2011 and aimed to investigate the longitudinal changes of conditions associated with aging, such as sarcopenia, frailty, and cognitive function among community-dwelling middle-aged and older adults. The study's design, recruitment process, and data collection methods for ILAS have been previously documented in other reports [4,[31], [32], [33], [34]]. Adults residing in the community and aged 50 years or older were randomly selected from I-Lan County, Taiwan. Upon selection, these individuals received either written or telephonic invitations from the research team. Participation was contingent upon their comprehensive understanding of the study’s parameters and their provision of explicit written consent.
Eligibility for participation was determined by the following criteria: (i) individuals who had an established residence in I-Lan County and had no impending relocation plans; and (ii) those who were 50 years of age or older. Conversely, exclusion criteria encompassed: (i) those incapable of establishing effective communication with research nurse or providing an interview; (ii) those hindered by severe functional impediments, preventing the completion of evaluative assessments; (iii) individuals with a projected life expectancy of less than 6 months due to critical health conditions; and (iv) individuals presently domiciled in long-term care facilities. During the third wave of the ILAS, data of participants who underwent spirometry between 2018 and 2019 were selected for analysis to examine the roles of serum follistatin and pulmonary function on clinical outcomes. The study protocol received approval from the institutional review board of the Taipei Veterans General Hospital (2018-05-003B). The study’s design and execution followed the principles outlined in the Declaration of Helsinki.
2.2. Pulmonary function by spirometry
Participants were instructed to abstain from using inhaled bronchodilators for a duration of 12 h preceding the spirometry. For the analytical phase, two flow-sensing spirometers (MS-IOS Jaeger, Würzburg, Germany, and Vmax 22 Sensor Medics, Yorba Linda, California, USA) interfaced with a computer were employed. Data derived from the forced expiratory flow-volume curve included the PEF, FVC, and FEV1. The percentage of predicted indices was obtained. Airflow limitation was defined as FEV1/FVC < 70% [35].
2.3. Follistatin and other laboratory data
Following a minimum 10-h overnight fast, blood specimens were procured from each participant during the subsequent morning. Biochemical evaluations encompassed measurements of serum aspartate aminotransferase (AST), serum alanine aminotransferase (ALT), serum albumin, serum creatinine, blood urea nitrogen (BUN), high-sensitivity C-reactive protein (hs-CRP). Complete blood count was also measured. The serum levels of follistatin were measured by sandwich enzyme immunoassay kits (R&D systems, Inc., Minneapolis, USA).
2.4. All-cause mortality
In the ILAS cohort, research nurses conducted regular phone check-ins with each participant every three months. These calls were aimed at collecting survival information. Survival data was precisely determined from the date of the initial interview until the last phone contact prior to May 19, 2023.
2.5. Other variables
Demographic characteristics, anthropometric measurements, and functional assessments were gathered by research nurses during in-person interviews. This encompassed data on health behaviors (such as smoking and alcohol consumption within the past six months), body mass index, and self-reported physician-diagnosed chronic conditions. Disease burden was evaluated using the Charlson’s comorbidity index (CCI) [36].
A Lunar Prodigy whole-body dual-energy X-ray absorptiometry scans (GE Healthcare, Madison, WI, USA) were employed to determine total fat mass, fat-free lean body mass, and bone mineral density (BMD). Appendicular skeletal mass was characterized as the cumulative fat-free lean body mass of all four limbs. The relative appendicular skeletal muscle mass index (RASM) was derived by dividing the appendicular skeletal mass by the square of height (expressed in kg/m2). The percentage of total body fat was ascertained by dividing the total fat mass by the overall body mass, subsequently multiplied by 100.
2.6. Statistical analysis
Categorical variables were presented by numbers (percentage) and continuous variables were presented by median with interquartile. Descriptive statistics were compared using appropriate statistical tests. The Mann–Whitney U test facilitated comparisons of continuous variables between paired groups (i.e. lower vs. higher follistatin), while the Kruskal–Wallis H test enabled such analyses across four distinct groups (i.e. lower follistatin (non-decreased vs. decreased PEF) vs. higher follistatin (non-decreased vs. decreased PEF)). Categorical variables were examined through Pearson’s chi-square test.
Survival curves and group comparisons based on follistatin levels and PEF were assessed using Kaplan–Meier analysis and log-rank tests. Multivariate Cox proportional hazards models were used to identify independent predictors of all-cause mortality, applying a force in or stepwise backward elimination method. A p-value < 0.05 was set as threshold for statistical significance. All the analyses were performed using IBM SPSS Statistics for Windows/Macintosh, version 25.0 (IBM Corp., Armonk, NY, USA); and MedCalc, version 20.215.
3. Results
3.1. Study participants and demographics
This analysis included a cohort of 910 participants from the ILAS study who underwent spirometry during wave 3. Following a review by two independent pulmonologists (HCS and CYS), based on criteria of acceptability, usability, and repeatability [37], data of 22 subjects were excluded. An additional 137 participants were excluded due to missing follistatin data. The final analysis included 751 participants, who were then divided into lower and higher follistatin groups, based on the median follistatin level of 1.612 pg/μL of all study participants (Fig. 1).
Fig. 1.
Study flow chart. ILAS study: I-Lan Longitudinal Aging Study. *Two independent reviewers evaluated the spirometry data including graphs to decide if interpretable. #Higher and lower follistatin is divided by median (1.612 pg/μL).
Table 1 summarizes the demographic characteristics of the study participants stratified by follistatin levels. Participants exhibiting higher follistatin levels (n = 375) were characterized by older age (higher follistatin group vs. lower follistatin group, median (IQR) 66 (61–72) vs. 63 (59–68) years old, p < 0.001), a predominance of male (49.3% vs. 39.6%, p = 0.007), less educational years (educational years=0 (illiterate), 12.8% vs. 10.1%, educational years = 1−6, 40.8% vs. 25.5%, p < 0.001), and higher comorbidity burden (CCI=1, 22.4% vs. 11.7%; CCI ≥ 2, 2.9% vs. 2.1%, p < 0.001). In addition, participants in the higher follistatin group were more likely to have higher WBC counts (median 5.8 vs. 5.2 × 109/L, p < 0.001), platelet counts (253 vs. 243 × 1000/μL, p = 0.026) as well as higher levels of serum hs-CRP (median 0.10 vs. 0.04 mg/dL, p < 0.001), creatinine (median 0.81 vs. 0.74 mg/dL, p < 0.001) and BUN (median 17.0 vs. 15.6 mg/dL, p < 0.001).
Table 1.
Demographics of study participants, lower follistatin vs. higher follistatin.
| Total (N = 751) |
Lower follistatin (N = 376) |
Higher follistatin (N = 375) |
p-Value | |||||
|---|---|---|---|---|---|---|---|---|
| n | (%) | n | (%) | n | (%) | |||
| Demographics | ||||||||
| Age, years | Median (IQR) | 65 | (60–70) | 63 | (59–68) | 66 | (61–72) | <0.001 |
| 50−64 | 373 | (49.7) | 232 | (61.7) | 141 | (37.6) | <0.001 | |
| 65−74 | 264 | (35.2) | 105 | (27.9) | 159 | (42.4) | ||
| 75+ | 114 | (15.2) | 39 | (10.4) | 75 | (20.0) | ||
| Sex | Male | 334 | (44.5) | 149 | (39.6) | 185 | (49.3) | 0.007 |
| Female | 417 | (55.5) | 227 | (60.3) | 190 | (50.7) | ||
| Educational years | 0 | 86 | (11.5) | 38 | (10.1) | 48 | (12.8) | <0.001 |
| 1−6 | 249 | (33.2) | 96 | (25.5) | 153 | (40.8) | ||
| 7−9 | 137 | (18.2) | 70 | (18.6) | 67 | (17.9) | ||
| 10−12 | 139 | (18.5) | 85 | (22.6) | 54 | (14.4) | ||
| 13+ | 140 | (18.6) | 87 | (23.1) | 53 | (14.1) | ||
| Current smoker | 72 | (9.6) | 29 | (7.7) | 43 | (11.5) | 0.081 | |
| Current drinking | 28 | (3.7) | 13 | (3.5) | 15 | (4.0) | 0.695 | |
| Body mass index (BMI), kg/m2 | Median (IQR) | 24.3 | (22.2–26.7) | 24.3 | (22.1–26.5) | 24.3 | (22.2–26.8) | 0.549 |
| Charlson comorbidity index (CCI) | Median (IQR) | 0 | (0−0) | 0 | (0–0) | 0 | (0–1) | <0.001 |
| 0 | 604 | (80.4) | 324 | (86.2) | 280 | (74.7) | <0.001 | |
| 1 | 128 | (17.1) | 44 | (11.7) | 84 | (22.4) | ||
| 2+ | 19 | (2.5) | 8 | (2.1) | 11 | (2.9) | ||
| X-ray absorptiometry, median (IQR) | ||||||||
| BMD of L spine, g/cm2 | 1.03 | (0.92–1.14) | 1.03 | (0.91–1.14) | 1.04 | (0.92–1.15) | 0.374 | |
| BMD of hip, g/cm2 | 0.82 | (0.74–0.91) | 0.82 | (0.74–0.91) | 0.82 | (0.74–0.91) | 0.682 | |
| Fat percentage, % | 33.8 | (27.3–40.0) | 34.2 | (28.0–40.1) | 33.3 | (26.3–40.0) | 0.431 | |
| RASM, kg/body height2 | 6.5 | (5.7–7.5) | 6.5 | (5.7–7.6) | 6.5 | (5.7–7.5) | 0.895 | |
| Laboratory tests (biomarkers), median (IQR) | ||||||||
| Immune | ||||||||
| Albumin, g/dL | Median (IQR) | 4.4 | (4.3–4.6) | 4.4 | (4.3–4.6) | 4.4 | (4.3–4.6) | 0.271 |
| White blood cell count (WBC) ×109/L | Median (IQR) | 5.5 | (4.7–6.5) | 5.2 | (4.4–6.1) | 5.8 | (4.9–7.1) | <0.001 |
| Hemoglobin (Hb), g/dL | Median (IQR) | 13.9 | (13.0–14.8) | 13.8 | (13.0–14.7) | 14.0 | (12.9–14.9) | 0.890 |
| PLT (×1000/μL) | Median (IQR) | 247 | (210–287) | 243 | (206–279) | 253 | (214–295) | 0.026 |
| Hs-CRP, mg/dL | Median (IQR) | 0.06 | (0.02–0.19) | 0.04 | (0.01–0.10) | 0.10 | (0.03–0.31) | <0.001 |
| Liver function | ||||||||
| AST, U/L | Median (IQR) | 25 | (21–29) | 25 | (21–28) | 25 | (22–29) | 0.245 |
| ALT, U/L | Median (IQR) | 22 | (17–29) | 22 | (17–29) | 22 | (18–30) | 0.896 |
| Renal function | ||||||||
| Creatinine (mg/dL) | Median (IQR) | 0.77 | (0.65–0.91) | 0.74 | (0.63–0.87) | 0.81 | (0.68–0.96) | <0.001 |
| BUN (mg/dL) | Median (IQR) | 16.3 | (13.7–19.1) | 15.6 | (13.1–17.8) | 17.0 | (14.5–20.4) | <0.001 |
Data are presented as the median (IQR) and number (%) unless otherwise indicated. Follistatin is divided by median (1.612 pg/μL).
IQR: interquartile range; BMD: bone mineral density; RASM: relative appendicular skeletal muscle mass index; PLT: platelet; Hs-CRP: high sensitivity C- reactive protein; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase; BUN: Blood urea nitrogen.
3.1.1. Pulmonary function and clinical outcomes stratified by follistatin levels
Table 2 revealed results of pulmonary function and clinical outcomes, stratified by follistatin levels. FEV1 (higher follistatin group vs. lower follistatin group, 1.78 vs. 1.92 L, p = 0.001), FVC (1.19 vs. 2.31 L, p = 0.012), PEF (4.31 vs. 4.54 L/s, p = 0.045), and PEF % predicted (75% vs. 79%, p = 0.015) were all significantly worse in the higher follistatin level group. Additionally, participants with higher follistatin levels were more likely to present reduced PEF (defined as PEF% predicted below 80%) compared to those with lower follistatin (60.3% vs. 52.4%, p = 0.030). The incidence of all-cause mortality was comparable between the high and low follistatin groups.
Table 2.
Pulmonary function and clinical outcomes of study participants, lower follistatin vs. higher follistatin.
| Total (N = 751) |
Lower follistatin (N = 376) |
Higher follistatin (N = 375) |
p-Value | |||||
|---|---|---|---|---|---|---|---|---|
| n | (%) | n | (%) | n | (%) | |||
| Pulmonary function | ||||||||
| FEV1, best (L) | Median (IQR) | 1.85 | (1.53–2.20) | 1.92 | (1.61–2.29) | 1.78 | (1.47–2.14) | 0.001 |
| FEV1, predicted (%) | Median (IQR) | 85 | (75–95) | 87 | (75–96) | 84 | (74–95) | 0.126 |
| <80% | 273 | (36.4) | 128 | (34.0) | 147 | (38.7) | 0.188 | |
| FVC, best (L) | Median (IQR) | 2.24 | (1.88–2.72) | 2.31 | (1.94–2.77) | 1.19 | (1.83–2.68) | 0.012 |
| FVC, predicted (%) | Median (IQR) | 86 | (77–96) | 87 | (77–96) | 85 | (76–96) | 0.597 |
| <80% | 233 | (31.0) | 117 | (31.1) | 116 | (30.9) | 0.957 | |
| FEV1/FVC | Median (IQR) | 82 | (78–85) | 82 | (79–86) | 82 | (78–85) | 0.084 |
| <70% | 40 | (5.3) | 17 | (4.5) | 23 | (6.1) | 0.325 | |
| PEF, best (L/s) | Median (IQR) | 4.43 | (3.56–5.47) | 4.54 | (3.65–5.57) | 4.31 | (3.48–5.42) | 0.045 |
| PEF, predicted (%) | Median (IQR) | 77 | (63–90) | 79 | (65–91) | 75 | (60–88) | 0.015 |
| <80% | 423 | (56.3) | 197 | (52.4) | 226 | (60.3) | 0.030 | |
| Clinical outcomes | ||||||||
| All-cause mortality | 49 | (6.5) | 19 | (5.1) | 30 | (8.0) | 0.102 | |
Data are presented as the median (IQR) and number (%) unless otherwise indicated. Decreased PEF defined as PEF % predicted < 80%. Follistatin is divided by median (1.612 pg/μL). IQR: interquartile range; FEV1: forced expiratory volume in one second; FVC: forced vital capacity; PEF: peak expiratory flow.
In Table 3, we further divided participants into four groups based on their follistatin levels and PEF status (lower follistatin and non-decreased PEF, lower follistatin and decreased PEF, higher follistatin and non-decreased PEF, and higher follistatin and decreased PEF) for further analysis. Compared to other groups, participants with both higher follistatin levels and decreased PEF exhibited the oldest age (median 68 years old, p < 0.001), with the highest proportion of male (54.0%, p = 0.003), highest proportion of being illiterate (16.4%, p < 0.001), highest proportion of higher burden of comorbidity (CCI ≥ 2, 3.1%, p = 0.001), highest WBC counts (median 5.9 × 109/L, p < 0.001), and highest serum levels of hs-CRP (median 0.11 mg/dL, p < 0.001), creatinine (0.85 mg/dL, p < 0.001) and BUN (17.5 mg/dL, p < 0.001). Notably, participants exhibiting higher follistatin levels and reduced PEF had highest mortality rate (9.7%, p = 0.019).
Table 3.
Demographics and clinical outcomes of study participants, stratified by PEF and follistatin.
| Lower follistatin | Higher follistatin | p-Value | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total | Non-decreased PEF | Decreased PEF | Non-decreased PEF | Decreased PEF | ||||||||
| n | (%) | n | (%) | n | (%) | n | (%) | n | (%) | |||
| Patient number | 751 | (100) | 179 | (23.8) | 197 | (26.2) | 149 | (19.8) | 226 | (30.1) | ||
| Demographics | ||||||||||||
| Age, years | Median (IQR) | 65 | (60–70) | 61 | (58–66) | 64 | (60–72) | 63 | (60–68) | 68 | (64–75) | <0.001 |
| 50−64 | 373 | (49.7) | 124 | (69.3) | 108 | (54.8) | 78 | (52.3) | 63 | (27.9) | <0.001 | |
| 65−74 | 264 | (35.2) | 47 | (26.3) | 58 | (29.4) | 53 | (35.6) | 106 | (46.9) | ||
| 75+ | 114 | (15.2) | 8 | (4.5) | 31 | (15.7) | 18 | (12.1) | 57 | (25.2) | ||
| Sex | Male | 334 | (44.5) | 65 | (36.3) | 84 | (42.6) | 63 | (42.3) | 122 | (54.0) | 0.003 |
| Female | 417 | (55.5) | 114 | (63.7) | 113 | (57.4) | 86 | (57.7) | 104 | (46.0) | ||
| Educational years | 0 | 86 | (11.5) | 7 | (3.9) | 31 | (15.7) | 11 | (7.4) | 37 | (16.4) | <0.001 |
| 1−6 | 249 | (33.2) | 40 | (22.3) | 56 | (28.4) | 51 | (34.2) | 102 | (45.1) | ||
| 7−9 | 137 | (18.2) | 36 | (20.1) | 34 | (17.3) | 34 | (22.8) | 33 | (14.6) | ||
| 10−12 | 139 | (18.5) | 43 | (24.0) | 42 | (21.3) | 23 | (15.4) | 31 | (13.7) | ||
| 13+ | 140 | (18.6) | 53 | (29.6) | 34 | (17.3) | 30 | (20.1) | 23 | (10.2) | ||
| Current smoker | 72 | (9.6) | 14 | (7.8) | 15 | (7.6) | 17 | (11.4) | 26 | (11.5) | 0.383 | |
| Current drinking | 28 | (3.7) | 7 | (3.9) | 6 | (3.0) | 4 | (2.7) | 11 | (4.9) | 0.673 | |
| Body mass index | Median (IQR) | 24.3 | (22.2–26.7) | 24.2 | (22.0–26.4) | 24.3 | (22.3–26.7) | 24.3 | (24.6–27.0) | 24.3 | (21.9–26.8) | 0.573 |
| Charlson comorbidity index (CCI) | Median (IQR) | 0 | (0–0) | 0 | (0–0) | 0 | (0–0) | 0 | (0–0) | 0 | (0–1) | <0.001 |
| 0 | 604 | (80.4) | 163 | (91.1) | 161 | (81.7) | 114 | (76.5) | 166 | (73.5) | 0.001 | |
| 1 | 128 | (17.1) | 14 | (7.8) | 30 | (15.2) | 31 | (20.8) | 53 | (23.5) | ||
| 2+ | 19 | (2.5) | 2 | (1.1) | 6 | (3.0) | 4 | (2.7) | 7 | (3.1) | ||
| X-ray absorptiometry, median (IQR) | ||||||||||||
| BMD of L spine, g/cm2 | Median (IQR) | 1.03 | (0.92–1.14) | 1.01 | (0.91–1.13) | 1.03 | (0.91–1.14) | 1.03 | (0.93–1.13) | 1.04 | (0.92–1.15) | 0.782 |
| BMD of hip, g/cm2 | Median (IQR) | 0.82 | (0.74–0.91) | 0.81 | (0.73–0.91) | 0.82 | (0.75–0.91) | 0.81 | (0.75–0.91) | 0.82 | (0.73–0.91) | 0.936 |
| Fat percentage, % | Median (IQR) | 33.8 | (27.3–40.0) | 34.6 | (28.8–39.7) | 34.2 | (27.1–40.4) | 33.8 | (26.9–41.3) | 32.8 | (25.7–39.6) | 0.250 |
| RASM, kg/body height2 | Median (IQR) | 6.5 | (5.7–7.5) | 6.3 | (5.6–7.4) | 6.6 | (5.8–7.7) | 6.3 | (5.6–7.4) | 6.6 | (5.8–7.5) | 0.371 |
| Laboratory tests (biomarkers), median (IQR) | ||||||||||||
| Immune | ||||||||||||
| Albumin, g/dL | Median (IQR) | 4.4 | (4.3–4.6) | 4.4 | (4.3–4.6) | 4.4 | (4.3–4.6) | 4.4 | (4.3–4.6) | 4.4 | (4.3–4.5) | 0.344 |
| White blood cell count (WBC) ×109/L | Median (IQR) | 5.5 | (4.7–6.5) | 4.9 | (4.3–5.8) | 5.5 | (4.6–6.3) | 5.8 | (5.0–6.9) | 5.9 | (4.9–7.2) | <0.001 |
| Hemoglobin (Hb), g/dL | Median (IQR) | 13.9 | (13.0–14.8) | 13.8 | (13.1–14.7) | 14.0 | (13.0–14.9) | 13.9 | (13.2–15.1) | 14.0 | (12.8–14.8) | 0.808 |
| PLT (×1000/μL) | Median (IQR) | 247 | (210–287) | 240 | (210–280) | 246 | (210–278) | 254 | (215–297) | 251 | (214–295) | 0.061 |
| Hs-CRP, mg/dL | Median (IQR) | 0.06 | (0.02–0.19) | 0.03 | (0.01–0.08) | 0.05 | (0.02–0.12) | 0.10 | (0.03–0.28) | 0.11 | (0.04–0.33) | <0.001 |
| Liver function | ||||||||||||
| AST, U/L | Median (IQR) | 25 | (21–29) | 25 | (21–28) | 24 | (21–29) | 24 | (21–29) | 25 | (22–32) | 0.644 |
| ALT, U/L | Median (IQR) | 22 | (17–29) | 22 | (17–29) | 22 | (18–28) | 22 | (17–30) | 23 | (18–30) | 0.964 |
| Renal function | ||||||||||||
| Creatinine (mg/dL) | Median (IQR) | 0.77 | (0.65–0.91) | 0.73 | (0.63–0.85) | 0.74 | (0.64–0.89) | 0.75 | (0.65–0.90) | 0.85 | (0.70–0.99) | <0.001 |
| BUN (mg/dL) | Median (IQR) | 16.3 | (13.7–19.1) | 15.7 | (13.1–17.5) | 15.5 | (13.0–18.0) | 16.5 | (13.9–19.3) | 17.5 | (14.9–21.4) | <0.001 |
| Clinical outcomes | ||||||||||||
| All-cause mortality | 49 | (6.5) | 4 | (2.2) | 15 | (7.6) | 8 | (5.4) | 22 | (9.7) | 0.019 | |
Data are presented as the median (IQR) and number (%) unless otherwise indicated. Decreased PEF defined as PEF % predicted < 80%. Follistatin is divided by median (1.612 pg/μL). IQR: interquartile range; BMD: bone mineral density; RASM: relative appendicular skeletal muscle mass index; PLT: platelet; Hs-CRP: high sensitivity C- reactive protein; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase; BUN: Blood urea nitrogen.
3.2. Follistatin, PEF and risk of all-cause mortality
Kaplan–Meier survival analysis revealed the association between follistatin and PEF groups and risk of all-cause mortality (log-rank p = 0.023) (Fig. 2). Multivariate Cox proportional hazards model (Table 4) revealed that having co-existing elevated follistatin levels and reduced PEF was an independent predictor of higher risk of all-cause mortality (cHR 4.34, 95% CI: 1.50–12.60, p = 0.007). This association remained consistent across three adjusted models: model 1: adjusting for age and sex (aHR 3.28, 95% CI: 1.10–9.79, p = 0.034), model 2: adjusting for age, sex, and comorbidity (aHR 3.10, 95% CI: 1.03–9.35, p = 0.044), and model 3: adjusting for age, sex, comorbidity and other variables linked to all-cause mortality as outlined in Supplemental Table 1 (aHR 3.58, 95% CI: 1.22–10.53, p = 0.020).
Fig. 2.
Kaplan–Meier curves for survival estimates by cumulative risks of higher follistatin and decreased PEF. Group 1: Lower follistatin & Normal PEF; Group 2: Lower follistatin & Decreased PEF; Group 3: Higher follistatin & Normal PEF; Group 4: Higher follistatin & Decreased PEF. Decreased PEF defined as PEF % predicted < 80%. Follistatin is divided by median (1.612 pg/μL). Patients with higher follistatin, alongside decreased PEF had a significant higher mortality (log-rank test: p = 0.023). PEF: peak expiratory flow.
Table 4.
The association between follistatin, PEF and all-cause mortality.
| Unadjusted models |
Adjusted models |
|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| cHR | (95%CI) | p-Value | aHRb | (95%CI) | p-Value | aHRc | (95%CI) | p-Value | aHRd | (95%CI) | p-Value | |
| Follistatin and PEF statusa | 0.039 | 0.149 | 0.179 | 0.113 | ||||||||
| Group 1 | ref | ref | ref | ref | ||||||||
| Group 2 | 3.33 | (1.10–10.02) | 0.033 | 2.93 | (0.97–8.88) | 0.058 | 2.85 | (0.94–8.67) | 0.064 | 3.05 | (1.00–9.26) | 0.050 |
| Group 3 | 2.28 | (0.69–7.58) | 0.178 | 2.00 | (0.60–6.68) | 0.263 | 1.92 | (0.57–6.45) | 0.292 | 2.21 | (0.67–7.34) | 0.196 |
| Group 4 | 4.34 | (1.50–12.60) | 0.007 | 3.28 | (1.10–9.79) | 0.034 | 3.10 | (1.03–9.35) | 0.044 | 3.58 | (1.22–10.53) | 0.020 |
| Age, years | 0.009 | 0.105 | 0.116 | 0.0984 | ||||||||
| 50–64 | ref | Ref | ref | ref | ||||||||
| 65–74 | 1.25 | (0.64–2.46) | 1.05 | (0.53–2.10) | 1.03 | (0.51–2.07) | ||||||
| 75+ | 2.83 | (1.43–5.63) | 1.01 | (0.98–4.10) | 1.01 | (0.96–4.05) | ||||||
| Sex | 0.006 | 0.030 | 0.030 | 0.4264 | ||||||||
| Female | ref | ref | Ref | ref | ||||||||
| Male | 2.27 | (1.26–4.09) | 1.94 | (1.07–3.52) | 1.94 | (1.07–3.52) | ||||||
| CCI | 0.312 | 0.635 | ||||||||||
| 0 | ref | ref | ref | ref | ||||||||
| 1 | 1.66 | (0.87–3.20) | 1.38 | (0.71–2.68) | ||||||||
| 2+ | 1.07 | (0.15–7.80) | 1.16 | (0.16–8.69) | ||||||||
| Education years | 0.234 | 0.8374 | ||||||||||
| 0 | ref | ref | ref | ref | ||||||||
| 1–6 | 0.79 | (0.36–1.74) | ||||||||||
| 7–9 | 0.68 | (0.28–1.67) | ||||||||||
| 10–12 | 0.78 | (0.23–2.58) | ||||||||||
| 13+ | 0.23 | (0.06–0.85) | ||||||||||
| Fat percentage, % | 0.96 | (0.93–0.99) | 0.005 | 0.96 | (0.92–0.99) | 0.006 | ||||||
| Hs-CRP, mg/dL | 1.21 | (1.10–1.32) | <0.001 | 1.20 | (1.08–1.32) | 0.006 | ||||||
| Creatinine (mg/dL) | 2.03 | (1.15–3.57) | 0.014 | |||||||||
Group 1: Lower follistatin & Normal PEF; Group 2: Lower follistatin & Decreased PEF; Group 3: Higher follistatin & Normal PEF; Group 4: Higher follistatin & Decreased PEF. Decreased PEF defined as PEF % predicted < 80%80%. Follistatin is divided by median (1.612 pg/μL). cHR: crude hazard ratio; aHR: adjusted hazard ratio.
Force in age, sex.
Force in age, sex, CCI.
Model with backward selection of variables, including age, sex, CCI, education years, fat percentage, Hs-CRP and Creatinine. PEF: peak expiratory flow; CCI: Charlson comorbidity index. Hs-CRP: high sensitivity C- reactive protein.
4. Discussion
The current study found that elevated levels of follistatin were associated with the decline of pulmonary function, particularly in PEF, which suggested that follistatin may be a potential biomarker for pulmonary function declines. Moreover, combining PEF measurements with serum follistatin levels provides prognostic insight into all-cause mortality.
Follistatin is a multi-tasking protein that promotes muscle growth and fights inflammation, influencing processes like bone health and muscle repair. This study demonstrates a positive correlation between elevated serum follistatin levels and both impaired pulmonary function and a pro-inflammatory profile. This observation may be indicative of a compensatory upregulation of follistatin in response to the underlying pathological processes. In this cohort study, elevated serum follistatin levels may not be interpreted as favorable signs, but rather as biomarkers for a negative physiological presentation. The co-occurrence of high serum follistatin and reduced pulmonary function, as observed in this study, may provide a more comprehensive assessment of health risk and all-cause mortality in individuals with poorer pulmonary function.
Our study revealed a significant association between higher follistatin levels and older age within the study cohort. This observation suggests a potential link between follistatin upregulation and either the aging process itself or the development of age-related muscular weakness. [38,39]. However, the interaction between age and follistatin level may not be so straightforward. While we did find that participants exhibiting higher follistatin levels were characterized by older age, our attempt to investigate the interaction effects between follistatin levels and age on the risk of decreased PEF did not support such hypothesis. To be specific, despite follistatin, age, and the interaction term (follistatin*age) individually increased the risk of decreased PEF, the multivariate model (backward selection) indicates that there is no interaction effect between follistatin and age on decreased PEF after adjusting for other covariates. Other factors, such as age and male gender, may contribute more on the risk of decreased PEF (Supplementary Table 2). Our study also found that higher follistatin group exhibited greater male predominance, potentially reflecting the established link between follistatin and larger muscle mass in males [20]. In addition, elevated serum follistatin in this study correlated with increased disease burden, pro-inflammatory markers, and renal dysfunction, potentially reflecting a compensatory response to these pathological conditions. This aligns with prior studies suggesting that follistatin could be a biomarker related to both morbidity and inflammation, including polycystic ovary syndrome [40], cardiometabolic disorders [29], type 2 diabetes [41], chronic kidney disease [42,43], and septicemia [44,45].
This study's observation of a positive correlation between elevated follistatin and poorer pulmonary function aligns with prior research suggesting a mechanistic link between impaired pulmonary function and follistatin upregulation, potentially driven by physiological compensation for reduced physical performance associated with impaired lung function [20,39,42]. This is evident by our additional analyses that higher levels of follistatin was associated with weakened physical performance, including grip strength, walking speed, frailty (particularly weakness, slowness and low physical activity) (Supplementary Table 3). While the precise mechanisms underlying this association remain elusive, it compels further investigation. On the other hand, previous literature has established follistatin’s involvement in inflammatory processes across various pathologies. Roles of follistatin upregulation in response to pulmonary dysfunction serves as a compensatory mechanism to mitigate inflammation and associated tissue damage should be further investigated [29,[40], [41], [42], [43], [44], [45]]. Concomitant with our findings, a growing body of research suggests that systemic inflammation precipitates a decline in pulmonary function [[46], [47], [48], [49]]. Furthermore, the inflammatory process is intricately linked to age-related deterioration in lung function [50,51]. The current study strengthens the established link between pulmonary function decline and mortality [[52], [53], [54]], demonstrating that incorporating follistatin levels into risk assessment models may further enhance prediction of all-cause mortality. In the context of aging, elevated serum follistatin, linked to inflammation and cardiometabolic health, emerges as a potential biomarker of vulnerability predicting both pulmonary function decline and adverse clinical outcomes. However, the specific biological mechanisms underpinning this association remain to be elucidated.
On the other hand, the link between serum follistatin and pulmonary fibrosis may partially explain our findings. Pulmonary fibrosis encompasses a variety of conditions marked by interstitial remodeling, destruction of tissue architecture, and irreversible scarring [55]. It is associated with aging and primarily involves the alveolar regions, but it also affects the airways [55,56]. Impaired lung function is observed in pulmonary fibrosis, affecting not only parameters associated with restrictive ventilatory defects [57] but also those related to reduced resistance in the conducting airways [58].
For pulmonary fibrosis, TGF-β is thought to be the most important cytokine, stimulating the production of extracellular matrix, fibroblast proliferation, and induction of myofibroblast differentiation [59,60]. In animal models, follistatin play a role of TGF-β signaling pathway activation and is associated with pulmonary fibrosis [61,62] In human studies, follistatin mRNA levels were elevated in the lungs of patients with idiopathic pulmonary fibrosis (IPF) [63], and serum concentrations of follistatin were also higher in IPF patients. [64]. These findings suggest that follistatin could be a valuable biomarker of pulmonary fibrosis and a potential treatment target. However, the precise mechanisms and biomarker significance of follistatin in pulmonary aging and fibrosis still need further exploration.
Despite all efforts went into this study, several limitations inherent to the study design warrant consideration when interpreting the findings. First, the absence of longitudinal data on pulmonary function and follistatin precludes definitive establishment of a causal relationship between these factors. Second, the limited sample size of impaired pulmonary function, with only 44 individuals (representing a mere 5% of the total cohort) exhibiting an FEV1/FVC ratio below 70%, restricts our ability to comprehensively assess the influence of follistatin levels on specific airway diseases like COPD. Last but not the least, the absence of a bronchodilator test during pulmonary function evaluation hinders our capacity to differentiate between reversible and irreversible airflow obstruction.
However, our study offers several noteworthy strengths. First, it represents, to the best of our knowledge, the most extensive community-based investigation to date exploring the association between serum follistatin levels and pulmonary function. Second, the inclusion of a substantial follow-up period (approximately 52 months) with mortality data analysis provides a valuable temporal dimension to the study. Furthermore, by stratifying participants based on elevated follistatin levels and reduced PEF, we were able to conduct a more nuanced exploration of the potential interplay between these factors and all-cause mortality. Building upon the existing body of research that has meticulously explored follistatin’s therapeutic mechanisms in various disease contexts [65,66], future studies are warranted to specifically investigate its potential in mitigating pulmonary function decline within the older population.
5. Conclusions
In conclusion, the current study suggests that serum follistatin may serve as a biomarker in a combined vulnerability index, potentially predicting both age-related pulmonary decline and negative clinical outcomes. Further investigations are warranted to elucidate the biological mechanisms underlying this association and explore the therapeutic potential of follistatin in mitigating pulmonary dysfunction.
Ethics approval and consent to participate
This study was performed in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the Taipei Veterans General Hospital (2018-05-003B). All participants provided written informed consent prior to inclusion. The study followed the STROBE guidelines for observational studies in its design and reporting format.
Consent for publication
Not applicable.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Competing interest
The authors declare that they have no competing interest.
Funding
This research was funded by the Taiwan Ministry of Science and Technology (MOST110-2634-F-010-001, L.-K.C.), the Taiwan National Science and Technology Council (NSTC 111-2622-8-A49-019-IE, L.-K.C., NSTC 112-2923-B-A49-002-MY2, L.-K.C., NSTC 112-2314-B-A49-040, K.-Y.Y., NSTC 112-2622-8-A49-016-IE, L.-K.C., NSCT 112-2923-B-A49-002-MY2, L.-K.C., MOST NSTC 112-2314-B-075-050, W.-C.C.), the Taipei Veterans General Hospital (V112C-068, K.-Y.Y., V112D65-003-MY2-1, K.-Y.Y., V112D65-003-MY2-2, K.-Y.Y., 112VACS-001, L.-K.C., and V113C-007, K.-Y.Y., V111B-024, W.-C.C., V112B-031, W.-C.C., V113B-015, W.-C.C.), Cancer Progression Research Center (111W31101, K.-Y.Y.) and Cancer and Immunology Research Center (112W31101, K.-Y.Y. and 113W31101, K.-Y.Y.) of National Yang Ming Chiao Tung University and the Interdisciplinary Research Center for Healthy Longevity of National Yang Ming Chiao Tung University from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan, L.-K.C. The funding source had no role in conducting this study, including study design, data collection and analysis, manuscript preparation and review, and the decision to submit the manuscript for publication.
CRediT authorship contribution statement
Hsiao-Chin Shen: Conceptualization, Data curation, Formal analysis, Methodology, Writing - original draft, Writing - review & editing. Wei-Ju Lee: Conceptualization, Formal analysis, Methodology, Project administration, Supervision, Writing - review & editing. Chuan-Yen Sun: Conceptualization, Data curation. Wen-Kuang Yu: Conceptualization. Wei-Chih Chen: Conceptualization. Fei-Yuan Hsiao: Formal analysis, Methodology, Writing - review & editing. Kuang-Yao Yang: Conceptualization, Project administration, Supervision, Writing - review & editing. Liang-Kung Chen: Conceptualization, Project administration, Supervision, Writing - review & editing.
Acknowledgments
We express our gratitude to the support staff from the Center for Geriatrics and Gerontology of Taipei Veterans General Hospital and the Department of Family Medicine of Taipei Veterans General Hospital Yuanshan Branch.
Footnotes
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.jnha.2024.100285.
Appendix A. Supplementary data
The following is Supplementary data to this article:
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.