Abstract
Background:
This study examines the association between cystatin C (cysC) levels and risks of progression of frailty status or death in older men.
Methods:
Prospective study of 2,613 men without overt frailty aged 67 years and older enrolled in the MrOS ancillary sleep study. Baseline measurements included serum cysC, serum creatinine, and frailty status. Repeat frailty status, performed an average of 3.4 years later, was assessed as an ordinal outcome of robust, intermediate stage (prefrail), frail or dead.
Results:
Mean age was 75.7 years. Men with higher cysC were older and had a higher comorbidity burden. After adjusting for age, clinical site, and race, higher cysC was associated with nearly twofold greater odds of being classified as intermediate stage versus robust (OR quartile 4 vs 1; 1.82, 95% confidence interval [CI] 1.35–2.45), a threefold greater odds of frailty versus robust (OR quartile 4 vs 1; 3.13, 95% CI 2.03–4.82), and a more than fivefold greater odds of death versus robust (OR quartile 4 vs 1; 5.48, 95% CI 2.98–10.08). Results were similar for cysC-based estimated glomerular filtration rate (eGFR). This relationship was attenuated but persisted after adjusting for additional potential confounders including baseline frailty status, body mass index, smoking status, comorbidity burden, self-reported disability, and serum albumin. In contrast, neither serum creatinine nor creatinine-based eGFR was associated in a graded manner with higher risks of development of frailty or death.
Conclusions:
In this cohort of older men without overt frailty, higher cysC and cysC-based eGFR, but not creatinine or creatinine-based estimates of GFR, were associated with increased risks of frailty or death. These findings suggest that higher cysC level may be a promising biomarker for unsuccessful aging as manifested by increased risks of frailty and death.
Keywords: Cystatin C, Creatinine, Frailty, Mortality, Men
Chronic kidney disease (CKD), typically defined as an estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m2, is common among older adults (1,2) and has been associated with higher rates of prevalent and incident physical impairment, cognitive impairment, and frailty (3,4). Frailty, characterized by decreased physiologic reserve and increased vulnerability to physical decline and death, is frequently defined using the Cardiovascular Health Study (CHS) index proposed by Fried and colleagues in which three or more of the following criteria are present: shrinking (eg, unintentional weight loss), self-reported exhaustion or poor energy, weakness manifested by low grip strength, slow walking speed, and low physical activity. Participants with none of the criteria are considered to be robust, whereas those with one or two criteria are considered to be in an intermediate stage (5). In an analysis of CHS data, frailty defined by the CHS index was predictive of an increased risk of falling, hospitalization, disability, and mortality (6). Although multiple instruments have been developed to operationalize the construct of frailty, the CHS index has been extensively studied and the predictive value has been validated in multiple cohorts (7–10).
Serum creatinine-based eGFR (eGFRCr) presents challenges in elderly individuals with mild-to-moderate reductions in kidney function due to its dependence on muscle mass and lower accuracy at higher eGFR levels (11). These concerns have generated interest in the use of cystatin C (cysC), an alternative measure of kidney function that is less dependent on muscle mass (12) and has better accuracy than eGFRCr alone (13). CysC has been found to have a stronger association than eGFRCr with risks of mortality, end-stage kidney disease, cardiovascular events (14,15), and hip fracture (16,17). However, the association between higher cysC and incident frailty among older adults without overt frailty has not been fully evaluated. A previous longitudinal study (18) reported that eGFR using cysC (eGFRCysC), but not eGFRCr, was associated with greater risk of incident frailty in a cohort of older adults, but this analysis did not evaluate frailty status as a continuum ranging from robust, intermediate stage, frail to dead.
To test the hypothesis whether older men with higher cysC (and lower eGFRCysC) at baseline are at risk of progression of frailty status and death at follow-up, we measured cysC in a cohort of 2,429 men aged 67 years and older without overt frailty at baseline enrolled in the Outcomes of Sleep Disorders of Older Men (MrOS Sleep) study and reassessed frailty status and vital status an average of 3.4 years later. In secondary analyses, we examined whether serum creatinine and eGFRCr were associated with these outcomes.
Methods
Participants
The Osteoporotic Fractures in Men (MrOS) Study is a prospective multicenter observational study of a cohort of 5,994 community-dwelling men aged 65 years and older recruited between 2000 and 2002 from six clinical sites in the United States. Detailed descriptions of the study design and recruitment have been previously published (19,20). In order to participate, men needed to be able to walk without assistance, must not have had a bilateral hip replacement, and must not have had a medical condition that (in the judgment of the investigator) would result in imminent death. These inclusion criteria were designed to yield a cohort of men that was reasonably representative of a broad population of older men. No inclusion or exclusion criteria were based on risk of osteoporotic fracture. 3,135 men enrolled in an ancillary sleep study examination (56% of active surviving participants, >100% of recruitment goal) between 2003 and 2005 (baseline for this analysis). Of these, 2,613 were both not overtly frail at baseline and had adequate sera for cysC and creatinine measurement. After excluding 184 men who did not have frailty data at the follow-up visit an average (SD) of 3.42 (0.46) years later, 2,429 men comprised the analytical cohort (Supplementary Figure 1). The institutional review board at each center approved the protocol, and written informed consent was obtained from all participants.
Biochemical Data
Measures of renal function were performed on previously frozen (−70°C) stored serum samples collected at baseline; serum creatinine and cysC were measured from the same sample. Serum creatinine was analyzed using the Roche Modular P chemistry analyzer (Enzymatic/Roche Diagnostics, Indianapolis, IN) in 2013; inter-assay coefficient of variation (CV) for serum creatinine is 3.7% at 0.82 mg/dL and 2.3% at 3.62 mg/dL. This assay is calibrated to be isotope dilution mass spectrometry traceable. CysC was measured using the Roche Modular P chemistry analyzer (Turbidimetric/Gentian AS, Moss, Norway) in 2013; inter-assay CV is 4.1% at 0.94 mg/L and 2.8% at 3.29 mg/L. This assay is calibrated to the international cysC reference material ERM-DA471/IFCC. Both assays were performed at the Fairview University Medical Center Clinical Laboratory (Minneapolis, MN).
Using the Chronic Kidney Disease Epidemiology (CKD-EPI) Collaboration equation based on age, gender, and cysC alone, eGFRcysC was calculated (13). Using the CKD-EPI equation that includes variables for standardized creatinine, age, gender, and race, eGFRCr was calculated (21). CysC + creatinine-based eGFR (eGFRCr-CysC) was calculated using the CKD-EPI equation including variables for cysC, creatinine, age, gender, and race (13).
C-reactive protein was measured using the ELISA assay kit from ALPCO (C-reactive protein sensitive ELISA), interleukin-6 and tumor necrosis factor-α were assayed using the Human ProInflammatory I 4-Plex Ultra-Sensitive Kit by MSD (catalog K15009C-4). Serum albumin was measured using serum collected between 2000 and 2002 using a Roche COBAS Integra 800 automated analyzer (Roche Diagnostics) with inter-assay CV of 1.98%.
Other Measurements
At baseline, demographic information, health status, social support, and smoking status were ascertained through self-administered questionnaires. Men were asked whether they had received a physician diagnosis of the nine selected medical conditions (see footnote of Table 1). In addition, dementia was defined as a score less than 80 on the Modified Mini-Mental State Examination (22–24). A summary comorbidity score was calculated as the sum of these conditions (range 0–10). Physical activity was assessed using the Physical Activity Scale for the Elderly (PASE) score (25). Height was measured with Harpenden stadiometers and weight was measured on balance beam or digital scales. Body mass index was calculated as kilograms per square meter. Walking speed was measured on a 6-m walking course and expressed as meters per second averaged over two trials. Grip strength (kg) was measured using a Jamar hand dynamometer (Lafayette Instrument, Lafayette, IN). Men were asked about their ability to perform five instrumental activities of daily living (IADLs) (26–28).
Table 1.
Baseline Characteristics of 2,429 Men Overall and by Serum Cystatin C Quartile
| Overall | Q1 | Q2 | Q3 | Q4 | p Value | |
|---|---|---|---|---|---|---|
| Characteristic | (N = 2,429) | (n = 605) | (n = 573) | (n = 624) | (n = 627) | |
| Age (y), mean (SD) | 75.7 (5.2) | 73.7 (4.4) | 75.1 (4.8) | 76.1 (5.0) | 78.0 (5.6) | <.001 |
| Caucasian race, n (%) | 2201 (90.6) | 516 (85.3) | 523 (91.3) | 578 (92.6) | 584 (93.1) | <.001 |
| Self-reported health status, n (%) | <.001 | |||||
| Poor, very poor, or fair | 255 (10.5) | 43 (7.1) | 47 (8.2) | 67 (10.8) | 98 (15.6) | |
| Good or excellent | 2172 (89.5) | 561 (92.9) | 526 (91.8) | 556 (89.3) | 529 (84.4) | |
| Current or past smoker, n (%) | 1449 (59.7) | 356 (58.8) | 344 (60.0) | 360 (57.8) | 389 (62.0) | .46 |
| Number of select medical conditions, n (%)a | <.001 | |||||
| 0–1 | 1370 (56.6) | 399 (66.1) | 358 (62.8) | 347 (55.9) | 266 (42.6) | |
| 2–3 | 946 (39.1) | 195 (32.3) | 192 (33.7) | 253 (40.7) | 306 (49.0) | |
| ≥4 | 103 (4.3) | 10 (1.7) | 20 (3.5) | 21 (3.4) | 52 (8.3) | |
| PASE physical activity score, mean (SD) | 157.4 (68.8) | 168.3 (70.2) | 158.4 (65.0) | 157.0 (70.9) | 146.5 (67.0) | <.001 |
| Body mass index (kg/m2), mean (SD) | 27.2 (3.7) | 26.4 (3.3) | 26.6 (3.5) | 27.5 (3.5) | 28.0 (4.2) | <.001 |
| Number of IADL impairments (0–5), mean (SD) | 0.2 (0.6) | 0.1 (0.5) | 0.2 (0.5) | 0.2 (0.6) | 0.4 (0.8) | <.001 |
| Baseline serum albumin (g/dL), mean (SD) | 4.3 (0.2) | 4.3 (0.2) | 4.3 (0.2) | 4.3 (0.2) | 4.2 (0.2) | <.001 |
| Frailty status at baseline, n (%) | <.001 | |||||
| Robust | 917 (37.8) | 294 (48.6) | 235 (41.0) | 230 (36.9) | 158 (25.2) | |
| Intermediate stage | 1512 (62.3) | 311 (51.4) | 338 (59.0) | 394 (63.1) | 469 (74.8) | |
| eGFRCr (mL/min/1.73 m2), mean (SD) | 71.5 (14.3) | 82.8 (8.6) | 76.5 (9.8) | 70.7 (10.0) | 56.9 (13.1) | <.001 |
| Inflammatory markers | ||||||
| CRP (µg/mL), mean (SD) | 2.7 (5.6) | 2.0 (2.8) | 2.2 (4.0) | 2.9 (7.1) | 3.7 (6.8) | <.001 |
| IL-6 (pg/mL), mean (SD) | 1.7 (3.8) | 1.3 (3.8) | 1.4 (3.9) | 1.7 (2.3) | 2.3 (4.6) | <.001 |
| TNF-α, mean (SD) | 5.4 (2.2) | 4.5 (1.6) | 5.0 (1.3) | 5.4 (2.6) | 6.6 (2.4) | <.001 |
Note: Quartile ranges (mg/L): <0.91, 0.91 to <1.04, 1.04 to <1.22, ≥1.22.
CRP = C-reactive protein; eGFRcr = creatinine-based estimated glomerular filtration rate; IADL = instrumental activities of daily living; IL-6 = interleukin-6; TNF-α = tumor necrosis factor α; PASE = Physical Activity Scale for the Elderly.
aSelected medical conditions include fracture after age 50, dementia (Modified Mini-Mental State Examination score < 80), transient ischemic attack or stroke, diabetes mellitus, hypertension, coronary heart disease (including myocardial infarction, bypass surgery, coronary angioplasty, or angina), congestive heart failure, chronic obstructive pulmonary disease, Parkinsonism, or cancer (except non-melanoma skin cancer).
Frailty Status Assessment
Frailty status at baseline was defined using criteria similar to those proposed by Fried and colleagues using data collected in the CHS study (5). Cutpoints where applicable are provided in Supplementary Table 1:
(1) Shrinking as identified by an unintentional weight loss of 5% or more over an average of 3.36 (SD 0.48) years prior to baseline;
(2) Weakness as identified by a grip strength at baseline in the lowest quintile stratified by body mass index (quartiles);
(3) Poor energy as identified by an answer of “no” to the question “Do you feel full of energy?” from the Geriatric Depression Scale (29) administered at baseline;
(4) Slowness as identified by a walk speed at baseline in the lowest quintile stratified by standing height (median); and
(5) Low physical activity level at baseline as identified by a PASE score in the lowest quintile.
At baseline, men with none of the above components were categorized as robust, those with one or two components were categorized as intermediate stage, and those with three or more components were categorized as frail. Because we are evaluating the outcome of incident frailty, men who were categorized as frail at baseline were excluded from the analytical cohort. Frailty status at the follow-up exam an average of 3.4 years later was defined using the same criteria cutpoints from the baseline examination (Supplementary Table 1). Because frailty and mortality are competing events, frailty status at follow-up and mortality between the baseline and follow-up exams was analyzed by considering four outcome levels at follow-up: robust, intermediate stage, frail, or dead.
Statistical Analysis
All analyses were prespecified. The primary predictor variables were serum cysC and eGFRcysC expressed as quartiles. The referent group was the lowest quartile (Q1) for analyses examining cysC and the highest quartile (Q4) for analyses examining eGFRcysC. Secondary predictors included quartiles of serum creatinine (referent group Q1) as well as quartiles of eGFRCr (referent group Q4) and quartiles of eGFRcysC-Cr (referent group Q4).
Differences in baseline characteristics by quartile of cysC were compared using chi-square (for categorical data) and analysis of variance (for normally distributed continuous data) and Kruskal–Wallis (for skewed continuous data) tests. Given the ordinal nature of the frailty status outcome variable (robust, intermediate stage, frail, or dead), multinomial logistic regression was used to simultaneously calculate the odds at follow-up of being dead versus robust, frail versus robust, or intermediate stage versus robust.
Base models were adjusted for age, race, and clinical site; then additionally adjusted for baseline frailty status (intermediate stage vs robust). In forming the multivariate model, prespecified characteristics that may be related to cysC level or frailty status (ie, body mass index, comorbidity burden, smoking status, IADL impairment, and serum albumin) were added to the base + baseline frailty status model. A test for linear trend was performed for predictor variables categorized in quartiles by expressing each predictor quartile as an ordinal variable. To explore the effect of mediation by inflammation, inflammatory markers (C-reactive protein, interleukin-6, and tumor necrosis factor-alpha) were added one at a time to the multivariate model for cysC to examine whether the results were similar in effect size or statistical significance.
In sensitivity analyses, we expressed cysC, eGFRcysC, creatinine, eGFRCr, and eGFRCysC-Cr as continuous variables. In addition, we evaluated eGFRcysC, eGFRCr, and eGFRCysC-Cr as binary variables of <60 mL/min/1.73 m2 versus ≥60 mL/min/1.73 m2 to examine the association of CKD with risks of progression of frailty status and death at follow-up. All significance levels reported were two sided and all analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC).
Results
The characteristics of the analytical cohort (n = 2,429) overall and by quartile (Q) of cysC (Q1: <0.91, Q2: 0.91 to <1.04, Q3: 1.04 to <1.22, Q4: ≥1.22 mg/L) are shown in Table 1. The mean age of the cohort was 75.7 years. 2,201 (90.6%) were Caucasian and 2,172 (89.5%) reported their health status as “good” or “excellent.” Among our cohort of men without overt frailty at baseline, the frailty status of 917 (37.8%) men was classified as robust, whereas that of 1,512 (62.5%) men was classified as intermediate stage. Mean (SD) was 1.09 (0.27) mg/L for serum cysC, 69.8 (19.3) mL/min/1.73 m2 for eGFRcysC, 1.05 (0.23) mL/dL for serum creatinine, and 71.5 (14.3) mL/min/1.73 m2 for eGFRCr. Using a definition of CKD as an eGFR less than 60 mL/min/1.73 m2, 787 (32.4%) men had CKD when eGFR was calculated using cysC, whereas 508 (20.9%) had CKD when eGFR was calculated using creatinine. Only 159 (6.6%) had moderate CKD with an eGFRcysC-Cr less than 45 mL/min/1.73 m2 and only 16 (0.66%) had advanced CKD with an eGFRcysC-Cr less than 30 mL/min/1.73 m2.
The mean time to follow-up was 3.4 (0.5) years. After adjusting for age, clinical site, and race, higher cysC was associated with greater odds of being classified as intermediate stage (vs robust), frail (vs robust), or dead (vs robust). Compared with men in the Q1 of cysC (referent), men in Q4 had a twofold greater odds of intermediate stage (OR 1.82, 95% confidence interval [CI] 1.35–2.45), a threefold greater odds of frailty (OR 3.13, 95% CI 2.03–4.82), and a more than fivefold greater odds of death (OR 5.48, 95% CI 2.98–10.08) (Table 2). The associations appeared graded in nature (p for linear trend across cysC quartiles ≤ .001).
Table 2.
Association Between Cystatin C and Frailty Status and Death at Follow-Up
| Odds Ratio (95 % Confidence Interval) | |||
|---|---|---|---|
| Intermediate Stage vs Robust | Frail vs Robust | Dead vs Robust | |
| Base modela | |||
| Quartile 1 | 1.00 (referent) | 1.00 (referent) | 1.00 (referent) |
| Quartile 2 | 1.06 (0.82, 1.38) | 1.10 (0.71, 1.71) | 2.05 (1.10, 3.85) |
| Quartile 3 | 0.97 (0.75, 1.27) | 1.48 (0.98, 2.25) | 2.43 (1.33, 4.47) |
| Quartile 4 | 1.82 (1.35, 2.45) | 3.13 (2.03, 4.82) | 5.48 (2.98, 10.08) |
| p Trend | .001 | <.001 | <.001 |
| Continuous, per 1 SD increase (0.27) | 1.30 (1.15, 1.46) | 1.69 (1.45, 1.97) | 1.94 (1.64, 2.30) |
| Base model + Baseline frailty status | |||
| Quartile 1 | 1.00 (referent) | 1.00 (referent) | 1.00 (referent) |
| Quartile 2 | 0.99 (0.75, 1.30) | 0.99 (0.63, 1.57) | 1.88 (1.00, 3.55) |
| Quartile 3 | 0.88 (0.67, 1.16) | 1.29 (0.84, 2.00) | 2.17 (1.17, 4.02) |
| Quartile 4 | 1.50 (1.10, 2.06) | 2.40 (1.53, 3.77) | 4.39 (2.37, 8.16) |
| p Trend | .07 | <.001 | <.001 |
| Continuous, per 1 SD increase (0.27) | 1.19 (1.05, 1.35) | 1.52 (1.30, 1.78) | 1.77 (1.48, 2.10) |
| Multivariable modelb | |||
| Quartile 1 | 1.00 (referent) | 1.00 (referent) | 1.00 (referent) |
| Quartile 2 | 0.95 (0.71, 1.27) | 0.89 (0.55, 1.45) | 1.80 (0.92, 3.52) |
| Quartile 3 | 0.84 (0.63, 1.13) | 1.12 (0.71, 1.78) | 1.89 (0.98, 3.65) |
| Quartile 4 | 1.20 (0.86, 1.69) | 1.60 (0.98, 2.60) | 2.94 (1.50, 5.76) |
| p Trend | .62 | .045 | .005 |
| Continuous, per 1 SD increase (0.27) | 1.09 (0.95, 1.25) | 1.29 (1.08, 1.53) | 1.54 (1.27, 1.87) |
Note: Quartile ranges (mg/L): <0.91, 0.91 to <1.04, 1.04 to <1.22, ≥1.22.
IADL = instrumental activities of daily living.
aAdjusted for age, race, and clinic. bAdjusted for age, race, clinic, baseline frailty status (intermediate stage vs robust), body mass index, smoking (ever vs never), number of comorbidities, number of IADL impairments, and serum albumin.
After further adjustment for baseline frailty status, body mass index, smoking status, comorbidity burden, IADL impairments, and serum albumin, associations of cysC with frailty and death were attenuated but persisted. Compared with men in Q1 of cysC, men in Q4 had 60% higher odds of frailty (OR 1.60, 95% CI 0.98–2.60; p trend .045) and a nearly threefold greater odds of death (OR 2.94, 95% CI 1.50–5.76; p trend .005). However, the association between higher cysC and intermediate stage was no longer significant (Q4 vs Q1 OR 1.20, 95% CI 0.86–1.69; p trend .62). Further adjustment for inflammatory markers to the multivariate model did not substantially alter the association between cysC and frailty or death (data not shown). Results were similar when cysC was expressed as a continuous variable; each 1 SD increase in cysC was associated with a 1.3-fold odds of being frail (vs robust) and a 1.5-fold odds of being dead (vs robust) at follow-up (Table 2). The strength of the associations between higher cysC and greater odds of frailty and death at follow-up was nearly identical to that between lower eGFRcysC and these outcomes at follow-up (Supplementary Table 2).
Conversely, neither lower eGFRCr (Supplementary Table 3) nor higher serum creatinine (data not shown) was associated with greater odds of intermediate stage, frailty, or death at follow-up in base or multivariable models (p value for linear trend across quartiles ranged from .19 to 0.67). When eGFR was calculated using a formula based on both serum cysC and serum creatinine, the inclusion of serum creatinine with cysC in the calculation appeared to slightly attenuate the association of eGFR with frailty status and death at follow-up, as the strength of the association between eGFRcysC-Cr and these outcomes was somewhat smaller in magnitude to that for eGFRcysC alone (Supplementary Table 4).
Discussion
In this cohort of community-dwelling older men who were not overtly frail at baseline, higher serum cysC and lower eGFRcysC were associated in a graded manner with greater odds of incident frailty or death at follow-up. However, we found no evidence of an association between higher serum creatinine (or lower eGFRCr) and risks of frailty or death at follow-up.
Our findings contribute to a growing body of literature suggesting that cysC is a more sensitive predictor for adverse age-related outcomes than creatinine or creatinine-based eGFR (4,15,17,18,30,31). These results may in part be explained by the improved sensitivity of cysC in identifying reduced kidney function in older adults with less muscle mass, especially among those with mild-to-moderate reductions in function. Studies have also noted a J-shaped association between creatinine and poor outcomes (4,15–17), suggesting that low serum creatinine is often more indicative of low muscle mass (and presumably decreased biological reserve) than excellent kidney function and that population-based equations for eGFR fail to account for this phenomenon. Indeed, 11.5% of the cohort would be reclassified as having CKD as defined by eGFRcysC less than 60 mL/min/1.73 m2 compared with CKD defined by eGFRCr.
A previous study reported that the accuracy of equations used to estimate true (directly measured) GFR is better when both cysC and creatinine are included compared with those based on either creatinine or cysC alone (13) and that analysis included almost 1,000 individuals older than 65 years. The benefit of combining cysC and creatinine to estimate GFR was again noted in a study of 610 adults aged 70 years and older (32). In our analysis, the association between eGFRcysC-Cr and risks of frailty or death actually appeared to be somewhat attenuated compared with that between eGFRcysC or cysC and these outcomes. These results suggest that the association of cysC with incident frailty and death is not entirely due to cysC being a marker of kidney function. In addition, the association of cysC with frailty or death was observed despite the cohort being predominantly comprised of men with at most mild reductions in kidney function; indeed, the lowest quartile of eGFRcysC included men with eGFR less than 55 mL/min/1.73 m2. The concept that cysC may be a predictor of frailty beyond its use to define GFR was supported by an analysis of the CHS cohort by Dalrymple and colleagues (18). In that analysis, although the risks of frailty differed somewhat in magnitude between two different eGFRcysC prediction equations when eGFR was expressed as a categorical variable, the hazard ratio of risk of frailty per 10 mL/min/1.73 m2 decrease in eGFR was nearly identical regardless of which eGFRcysC prediction equation was used.
Other potential mechanisms may drive the association of cysC with risks of frailty or death, including the role of inflammation (33). We have previously examined the effect of potential biological mediators, including calciotropic hormones and inflammatory markers, on the associations between cysC and between prevalent frailty status (4) in a cross-sectional analysis of the MrOS study cohort. Adjustment for these potential biological mediators had little, if any, impact on the association between cysC and prevalent frailty status. Similarly, in this longitudinal analysis, the association between cysC and frailty or death remained largely unchanged after further adjustment for inflammatory markers. It is possible that higher cysC is indicative of alterations in biochemical pathways that, in combination with mild decrements in kidney function, synergistically increase risk of frailty or death.
This study includes several strengths, including its large sample size and the inclusion of a comprehensively characterized cohort of community-dwelling older men who were not selected for CKD. We were able to prospectively evaluate a validated measure of frailty status as well as death and included an evaluation of frailty status as a continuum from robust to intermediate stage to frail to death. Failing to include death as a level of frailty could erroneously underestimate the association between cysC and poor outcomes, as men who died would not be classified as frail. However, this study has several limitations. We relied on surrogate markers of kidney function rather than direct measurements. Recent investigations indicate that equations using creatinine + cysC-based estimates of GFR are more accurate than those based on either marker alone, but error remains a concern particularly at the higher levels of GFR of ≥60 mL/min/1.73 m2. The use of single measurements of cysC and creatinine may increase variability; however, this variability would likely bias our findings toward the null hypothesis of no association. Our cohort was comprised of community-dwelling, predominantly Caucasian men, and findings may not be generalizable to other population groups; our results should be confirmed in other cohort studies of older adults. Very few men in the MrOS cohort had advanced CKD, limiting our ability to assess the association between cysC and frailty or death among those with markedly impaired kidney function. Measures used to identify frailty status included some frailty components that were similar but not identical to the original CHS frailty index definition. However, previous studies have reported that the associations between this frailty index (8,9) and risk of adverse health outcomes are similar in magnitude to those between the CHS frailty index and risk of adverse outcomes. Finally, as with any observational study, the possibility for residual confounding persists.
In conclusion, higher serum cysC (and lower eGFRcysC) among older men without overt frailty was associated with increased risks of progression of frailty status and death at follow-up. These relationships were not observed for serum creatinine or eGFRCr. These results suggest that cysC itself may be a promising biomarker for unsuccessful aging as manifested by increased risks of frailty and death.
Supplementary Material
Supplementary data is available at The Journals of Gerontology, Series A: Biomedical Sciences and Medical Sciences online.
Funding
The Osteoporotic Fractures in Men (MrOS) Study is supported by the National Institutes of Health funding. The following institutes provide support: the National Institute on Aging (NIA), the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), the National Center for Advancing Translational Sciences (NCATS), and NIH Roadmap for Medical Research under the following grant numbers: U01 AG027810, U01 AG042124, U01 AG042139, U01 AG042140, U01 AG042143, U01 AG042145, U01 AG042168, U01 AR066160, and UL1 TR000128.
The National Heart, Lung, and Blood Institute (NHLBI) provides funding for the MrOS Sleep ancillary study “Outcomes of Sleep Disorders in Older Men” under the following grant numbers: R01 HL071194, R01 HL070848, R01 HL070847, R01 HL070842, R01 HL070841, R01 HL070837, R01 HL070838, and R01 HL070839.
A.H. was also supported by the National Center for Advancing Translational Sciences in the National Institutes of Health Award Number UL1TR000114.
The funding agencies had no direct role in the conduct of the study, the collection, management, analyses, and interpretation of the data, or preparation or approval of the manuscript. This manuscript is the result of work supported with resources and use of facilities of the Minneapolis VA Health Care System.
Declaration of Interest
The authors report no declarations of interest.
Supplementary Material
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