Serum α-Klotho and SIRT1 - Relationship with graft function, inflammation and hospitalization rates in kidney transplant recipients

Abstract

Emerging evidence indicates kidney transplant recipients (KTRs) suffer from accelerated cellular aging, low-grade inflammation and variable degrees of allograft dysfunction. These pathobiological processes shape chronic kidney disease in the graft, for which α-Klotho is being explored as a candidate peptide marker for risk stratification. In this observational cohort study, we recruited 127 KTRs in outpatient care at the University Hospital in Kraków, Poland between September 2016 and June 2019. Serum α-Klotho, sirtuin-1 (SIRT1), and high-sensitivity interleukin-6 (hsIL-6) were assayed using ELISA kits in KTRs and 32 healthy controls (HCs). Thereafter, we utilized crude, age-adjusted, and fully adjusted Firth Poisson regression models with robust standard errors to evaluate predictors of all-cause hospitalization. We observed that circulating α-Klotho was reduced in KTRs, as compared with HCs (median 616 vs. 1,042 pg/mL, P < 0.001). Further, α-Klotho was moderately associated with eGFR at baseline (rho = 0.30) and final follow-up (rho = 0.29). In contrast, α-Klotho was inversely correlated with hsIL-6 (rho = −0.39, 95% CI −0.60–0.15, P = 0.002). In multivariable linear regression models, ln (α-Klotho) changes were tied to higher final eGFR (14.8 95% CI 6.2–25.6 mL/min/1.73 m²). During follow-up of 274 person-years, we recorded 153 hospitalizations. In multivariable models, higher ln (α-Klotho) was independently associated with lower hospitalization rate (IRR 0.31, 95% CI 0.15–0.65, P = 0.002). This association persisted after adjustment for baseline eGFR (IRR 0.37, 95% CI 0.20–0.69, P = 0.002). Overall, given further validation and standardization of assay technology, serum α-Klotho may be a strong candidate for supplemental, outpatient risk stratification in KTRs.

Graphical Abstract

Introduction

Patients with chronic kidney disease (CKD) and kidney transplant recipients (KTRs) experience enhanced biological aging, variable renal dysfunction and low-grade inflammation, which are drivers of cardiovascular (CV), infectious and neoplastic morbidity [1, 2]. Candidate prognostic markers, such as α-Klotho and sirtuin-1 (SIRT1), are increasingly studied as signature molecules of cytoprotective, anti-inflammatory and renoprotective pathways [2, 3]. The need for improved post kidney transplant (KTx) management, both from a perspective of graft dysfunction and comorbid disorder risk, has prompted research into risk stratification tools [4–7]. The post-KTx setting is unique in that chronic immunosuppression carries the risk of cardiometabolic side-effects that must be balanced against the risk of allograft dysfunction [8].

α-Klotho has been identified both as a transmembrane co-receptor for fibroblast growth factor-23 (FGF-23) and as a soluble circulating form [9, 10]. FGF-23 is known to regulate phosphate and vitamin D metabolism [11, 12], though Klotho also exerts anti-inflammatory and anti-fibrotic effects [13]. The kidney is considered a major source of α-Klotho [14–16], which strengthens its potential utility as a circulating marker. In murine models, lower α-Klotho is tied to premature aging, vascular disease, skin atrophy, and mineral-bone dysregulation [14]. In turn, its overexpression is tied to enhanced longevity, which may be mediated through effects on insulin and insulin-like growth factor-1 signalling pathways [17].

In humans, lower α-Klotho is tied to CV disease and mortality [18]. Population studies report inverse associations with body-mass measures and non-linear relationships with lipid abnormalities [18, 19]. Lower α-Klotho is also linked to metabolic syndrome, with apparent sex-specific patterns [20, 21]. Systemic inflammation is also reported to affect Klotho signalling [22, 23], while in kidney disease α-Klotho may exert vaso- and renoprotective effects [16, 24].

SIRT1 is an NAD + -dependent histone deacetylase that acts as an intracellular energy regulator; through deacetylation of key mediators (e.g., FOXO, NF-κB, p53) it can modulate pathways tied to oxidative stress, inflammation, DNA repair, apoptosis, autophagy and mitochondrial function [25, 26].

Metabolic and inflammatory processes are implicated in development of post-KTx complications, while underlying pathobiological processes are also affected by maintenance immunosuppressive treatment in KTRs [2, 27, 28]. The accelerated aging and chronic inflammation described in the setting of CKD implicate potential roles for both α-Klotho and SIRT1 in disease progression [29, 30]. However, the relationships between α-Klotho, SIRT1, and inflammatory markers in KTRs are not well understood. This study investigated serum concentrations of α-Klotho, SIRT1, and high-sensitivity interleukin-6 (hsIL-6) in KTRs and their associations with hospitalization outcomes and clinical characteristics.

Materials and methods

Study design

This was an observational cohort study that enrolled 127 KTRs under routine ambulatory care at the Nephrology and Transplantology Department of the University Hospital in Kraków, Poland, between 1 September 2016 and 30 June 2019. The median (IQR) follow-up duration was 29 [25–32] months. All patients provided written informed consent prior to study participation. This study was conducted in accordance with Declaration of Helsinki and ICH/GCP guidelines and represents an extension of our prior work and institutional research into circulating biomarkers in KTRs. Approval from the local Bioethics Committee was granted in extension of the original biomarker assessment study and updated for patient follow-up (Bioethics Committee Decision No. 1072.6120.202.2022).

Data collection

Demographic and clinical data were collected at the time of patient enrolment and over follow-up based on manual chart review. Longitudinal assessments were obtained through screening of electronic and paper-based medical records from consecutive ambulatory clinic visits by physicians, at pre-defined 3-to-6-month intervals. The main outcomes assessed over follow-up included: (i) hospitalization at the University Hospital departments for any cause; (ii) all-cause mortality; and (iii) death-censored graft loss, defined as graft dysfunction requiring permanent return to dialysis or re-transplantation listing. Study outcome data was gathered based on direct patient, family or dialysis centre contact, when available. Individual record censoring occurred at the date of death, dialysis transfer or last ambulatory care visit assessment.

Definitions

Hypertension was defined as outpatient visit blood pressure measurement ≥140/90 mmHg or recorded use of antihypertensive medications. Dyslipidaemia was defined based on existing medical record or use of lipid-lowering agents. Similarly, diabetes was identified based on pre-existing records or use of glucose-lowering therapy and/or biochemical data according to Polish Diabetes Society guidelines. Coronary artery disease (CAD) was defined broadly as a composite outcome of either history of myocardial infarction, stroke/transient ischemic attack, percutaneous coronary intervention or coronary artery bypass grafting, or existing record of chronic coronary syndrome. We did not include heart failure within this definition. Body mass index (BMI) and waist-to-hip ratio (WHR) were calculated based on standard formula. Estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2021 race-free equation via nephro package [31]. CKD was classified according to KDIGO guidelines [32].

Biochemical assessment

We collected peripheral venous blood samples from patients presenting for first study visit following overnight fast. Serum was obtained and stored in serum separator tubes, allowed to clot at room temperature, and then centrifuged. Aliquots were frozen at −70 °C and stored. Assays were conducted later, in batch and under standardized conditions. Procedures were performed by experienced laboratory staff blinded to patient outcomes.

Concentrations of study markers were measured using commercially available enzyme-linked immunosorbent assay (ELISA) kits, in accordance with manufacturer instructions. For α-Klotho (Immuno-Biological Laboratories Co., Ltd., Fujioka, Japan; Catalog No. 27998) sensitivity was 6.15 pg/mL; measurement range 93.75–6,000 pg/mL; intra-assay coefficient of variation (CV) < 3.5% and inter-assay CV was <11.4%. For sirtuin-1 (Wuhan EIAab Science Co., Ltd., Wuhan, China; Catalog No. E3949h) sensitivity <32 pg/mL; detection range 78–5,000 pg/mL; intra-assay CV was <4.3% and inter-assay CV was <7.2%. For high-sensitivity Interleukin-6 (hsIL-6; Quantikine HS ELISA Human IL-6 Immunoassay; R&D Systems, Inc., Minneapolis, MN, USA; Catalog No. HS600B) the mean minimum detectable dose was 0.039 pg/mL; reference range: 0.447–9.96 pg/mL; intra-assay CV was <7.8% and inter-assay CV was <9.6%.

Routine biochemical tests, including serum creatinine, were measured using standardized methods on automated analysers, as per standard laboratory protocol (Hitachi 917, Hitachi, Tokyo, Japan; Modular P, Roche Diagnostics, Mannheim, Germany).

Statistical analysis

Analyses were performed in R 4.5.3 (R Core Team, 2026; R Foundation for Statistical Computing, Vienna, Austria). Continuous and categorical variables were summarized as median with interquartile range (IQR) and counts with proportion (N, %), respectively. Variable distributions were assessed with visual inspection of density plots and Shapiro-Wilk test. For between-group comparisons we utilized exact Wilcoxon rank-sum tests for continuous variables, whereas Fisher’s test was employed for categorical variable comparison. To assess relationships from a robust perspective, we utilized Spearman’s rank correlation coefficient (rho), with 95% confidence intervals (CI) derived using percentile bootstrap over 2000 replicates.

The relationship between ln (α-Klotho) and final eGFR was modelled using hierarchical linear regression approach. CIs for coefficients were derived using bootstrap methods. We performed influence diagnostics and Cohen’s f² was utilized to quantify effect size. For additional sensitivity, we confirmed linearity of relationships based on alternative restricted cubic spline (3 knot; P = 0.07 for non-linearity).

Due to overdispersion of hospitalization counts, we considered different modelling approaches. Overall, we utilized quasi-Poisson regression, with log-transformed follow-up time as offset variable. To assess whether ln (α-Klotho) was independently associated with outcome after adjustment for all candidate predictors, we fitted a fully-adjusted bias-reduced Poisson model via brglm2 package. Additionally, non-parametric bootstrap and a negative binomial sensitivity model were considered. The Firth model was refitted with baseline CKD-EPI eGFR added as a covariate to further test if serum α-Klotho provides additional information over eGFR. Multicollinearity was assessed with variance inflation factors. Statistical tests were two-tailed and we treated P < 0.05 as statistically significant.

Results

Baseline characteristics of the study cohort

This study included 127 KTRs who were followed for a median (IQR) time of 29 [25–32] months. Most patients were of male gender (N = 86, 67.7%) and middle-aged, with median (IQR) age of 54 [33–52] years. We compared serum α-Klotho concentrations between KTRs and 32 healthy controls (16 male [50.0%]; mean age 50 years, age range 29–74 years). We observed lower circulating α-Klotho levels in serum of KTRs, with median (IQR) values of 616 (514–788) pg/mL versus 1,042 (922–1,472) pg/mL (P < 0.001), which correspond to an estimated difference of 463 (95% CI 346–605) pg/mL (see Figure 1).

FIGURE 1

For descriptive comparison of clinical characteristics, we stratified patients using a 75th-percentile cut-off (788 pg/mL) into “low” (n = 95) and “high” (n = 32) α-Klotho groups (see Table 1). However, for inferential analyses, serum α-Klotho was modelled as a continuous variable with natural log transformation due to distributional considerations. Both “low” and “high” α-Klotho groups were comparable in age, sex, body mass indices, metabolic parameters, smoking status, and baseline eGFR. Interestingly, hypertension was more frequently recorded in the low α-Klotho group (P = 0.016). The high α-Klotho group also showed lower log-transformed hsIL-6 levels, with median (IQR) values of 0.81 (0.37–1.20) versus 1.31 (0.94–1.73) (P < 0.001). Respectively, higher SIRT1 levels, with median (IQR) values of 11.46 (9.78–14.48) versus 9.82 (8.11–11.52) ng/mL were recorded in the “high” α-Klotho groyp, as compared to “low” α-Klotho group (P = 0.010). Of note, this difference in SIRT1 concentrations was not robust to the cut-off, as detailed in Section Relationships between clinical characteristics and α-Klotho and SIRT1 concentrations in serum of KTRs.

Relationships between clinical characteristics and α-Klotho and SIRT1 concentrations in serum of KTRs

For monotonic relationship analyses, we followed Cohen’s approach to interpretation of Spearman’s correlation strength (rho = 0.10, weak; rho = 0.30, moderate; rho = 0.50, strong). We observed that serum α-Klotho was consistently associated with allograft function across all timepoints: baseline eGFR (rho = 0.304), follow-up T1 (rho = 0.315), and follow-up T2 (rho = 0.29). Circulating α-Klotho in serum was inversely correlated with hsIL-6 levels (rho = −0.39, 95% CI -0.60–0.15, P = 0.002). Importantly, this association was also consistent in alternative analysis with α-Klotho categorization approaches (P = 0.001 for the 75th-percentile cut-off, P = 0.026 for the median cut-off).

By contrast, the α-Klotho-SIRT1 relationship was weaker and cut-off dependent. In continuous analysis, Spearman rho was estimated at 0.21 (95% CI -0.04–0.44, P = 0.098). Group differences are reported descriptively in Table 1 (P = 0.010 for the 75th-percentile cut-off), though were not preserved using a median split (P = 0.31). The SIRT1 finding should be interpreted with caution and requires validation. Other monotonic relationships between α-Klotho and clinical features were weak: HbA1c (rho = −0.140), BMI (rho = −0.087), mean arterial pressure (rho = 0.099), waist-to-hip ratio (rho = 0.020), and age (rho = 0.006).

Relationship between changes in kidney allograft function over follow-up

At baseline, median (IQR) eGFR was 57.4 (41.7–72.9) mL/min/1.73 m², with a median change of 0 (−10.4–7.1) mL/min/1.73 m² over follow-up. Most KTRs (N = 103, 80%) were characterized with stable graft function, which we defined as absolute change within 15 mL/min/1.73 m². At the last available follow-up visit, KDIGO stage distribution was as follows: G1 (11.8%), G2 (35.4%), G3a (20.5%), G3b (12.6%), G4 (11.8%), and G5 (7.9%).

We observed that when patients were stratified by serum concentrations of α-Klotho categorized into tertiles, they differed by eGFR (P = 0.010; Figure 2A). Specifically, patients in the lowest tertile had a median (IQR) final eGFR of 44.2 (25.6–65.9) mL/min/1.73 m², which is markedly lower than the second tertile (63.9 (52.7–76.5); P = 0.048) and the third tertile (61.4 (49.6–89.0); P = 0.024). Patients with eGFR decline also showed numerically lower median ln (α-Klotho) (P = 0.14; Figure 2B). Further, the continuous monotonic relationship between ln (α-Klotho) and final eGFR was formally significant (rho = 0.28, P = 0.002; Figure 2C), and the distribution of α-Klotho tertiles across KDIGO stages also supported a significant trend association (P = 0.003; Figure 2D).

FIGURE 2

We then constructed iterative linear regression models with progressive covariate adjustment (see Table 2). In the unadjusted model, each unit increase in ln (α-Klotho) was associated with 15.4 mL/min/1.73 m² higher final eGFR (95% CI 6.7–25.4). The association was preserved after demographic adjustment (Beta 15.3, 95% CI 7.3–25.8) and after additional adjustment for BMI and diabetes status (Beta 14.8, 95% CI 6.2–25.6). However, the effect size was modest (f² = 0.083). In additional sensitivity analysis after excluding high-influence observations, the relationship was consistently observed (Beta 15.4, 95% CI 3.1–27.7, P = 0.015). We also confirmed the plausible linearity of the ln (α-Klotho) effect using comparison with a three-knot restricted cubic spline model (P = 0.07 for non-linearity).

Relationship between α-Klotho, SIRT1 and all-cause hospitalization

Over 274 person-years of follow-up, we recorded 153 inpatient admissions that occurred among 54 KTRs (42.5%); 73 (57.5%) were not hospitalized during follow-up. Of note, we recorded hospitalizations that occurred within the setting of the University Hospital. Recurrent admissions ranged from 1 to 12 per patient, with a median (IQR) of 1 [1, 2] admissions. In age-adjusted quasi-Poisson regression (see Table 3), higher ln (α-Klotho) was significantly associated with lower hospitalization rate (IRR 0.38, 95% CI 0.19–0.74, P = 0.006). Coronary artery disease was also associated with higher rate (IRR 2.51, 95% CI 0.98–6.14, P = 0.049), while sex, diabetes, hypertension, dyslipidaemia, mean arterial pressure, BMI, ln (hsIL-6), and SIRT1 were not significant predictors.

To evaluate whether ln (α-Klotho) was independently associated with readmission after adjustment for all candidate predictors, we fitted a fully-adjusted Firth-corrected Poisson model containing age, sex, BMI, mean arterial pressure, diabetes mellitus, hypertension, dyslipidaemia, coronary artery disease, ln (hsIL-6), SIRT1, and ln (α-Klotho), with robust standard errors and log (follow-up time) as offset (Supplementary Table S1; Figure 3A). Although exploratory, ln (α-Klotho) was observed with a maintained, strong inverse relationship with hospitalization rate (IRR 0.31, 95% CI 0.15–0.65, P = 0.002). Similar observations were noted for coronary artery disease (IRR 3.02, 95% CI 1.25–7.30, P = 0.014). These findings were consistent across different, alternative model constructs, both using a non-parametric bootstrap of the same model (R = 1,000) with a 95% CI of 0.10–0.66, as well as a negative binomial regression model (similarly, the estimated IRR was 0.32 95% CI 0.14–0.73, P = 0.005). In model diagnostics, all variance inflation factors were <2, which suggesting limited confounding by collinearity.

FIGURE 3

To further investigate whether α-Klotho may provide additional information over eGFR monitoring, we refitted the fully adjusted Firth model with baseline eGFR added as a covariate. Consistently, ln (α-Klotho) consistently demonstrated an independent inverse association with hospitalization rate (IRR 0.37, 95% CI 0.20–0.69, P = 0.002), even after adjustment for baseline eGFR. At the same time, baseline eGFR was a strong predictor of hospitalization (IRR 0.97 per mL/min/1.73 m²; P < 0.001).

Discussion

The salient findings of this observational study are that (i) serum α-Klotho concentrations are significantly reduced in KTRs and (ii) are independently associated with future graft function, (iii) inversely correlated with circulating inflammatory burden, and (iv) inversely associated with all-cause hospitalization, even after adjustment for baseline kidney function. Our results extend evidence from prior work and recent meta-analyses that have reported reduced serum α-Klotho levels after kidney donation, while an increase of α-Klotho was observed in individuals post-KTx [53]. Our findings place α-Klotho as a candidate supplemental marker that may add information to standard eGFR-based risk stratification in the post-KTx setting.

In this exploratory study we observed that higher serum α-Klotho concentrations were associated with preserved graft function over follow-up, an observation consistent across multivariable specifications for last available eGFR. This aligns with reports from other KTR cohorts, in which higher circulating α-Klotho was tied to improvement in renal function over time [54–57].

Importantly, the lower hospitalization rate associated with higher α-Klotho remains a novel and clinically relevant finding, strengthened by consistent risk attribution in different models, even when baseline eGFR was added as a covariate to the fully adjusted model. Preliminary reports suggest α-Klotho deficiency may be detectable at very early stages of CKD [58, 59], though few studies have investigated circulating α-Klotho levels in KTRs, with mixed results [60]. Other research groups have reported associations between α-Klotho levels and glomerular function [56, 57], though variability of α-Klotho concentrations at different post-transplant timepoints has been observed, with decremental trends over time [60, 61]. While baseline eGFR and age remain important confounders and determinants of graft function [33], our analyses suggest serum α-Klotho is an independent predictor of future eGFR and may provide supplemental risk stratification value.

While Klotho functions as a co-receptor for FGF-23 signalling, its full biological roles and protective mechanisms remain unelucidated [13, 34]. High Klotho expression has been demonstrated in the kidney [35], with this organ identified as a major source of circulating α-Klotho [36]. In experimental models of transgenic mice, Klotho overexpression was tied to improved renal function, reduced calcification and higher phosphaturia [14, 17, 24]. In patients with autosomal dominant polycystic kidney disease, serum α-Klotho was associated with cyst size and renal growth [37]. On a cellular level, Klotho is likely to exert anti-apoptotic [38] and anti-fibrotic [39] effects.

We observed higher prevalence of hypertension in patients with lower α-Klotho levels, alongside an inverse correlation with circulating hsIL-6 levels that was robust to both alternative dichotomizations and continuous analysis. On a theoretical level, cytokines such as TNF-α and IL-6 may suppress α-Klotho expression in the kidney [40–42], and evidence from murine studies suggests Klotho acts as a negative regulator of NF-κB-related inflammation [43]. Oxidative stress, cellular damage and fibrosis due to events such as ischemia-reperfusion are likely to occur post-KTx, with experimental data supportive of a protective role of Klotho [44]. In peritoneal dialysis patients, lower circulating Klotho levels have been associated with higher markers of oxidative stress and inflammation (8-isoprostane and IL-6), although this relationship was not retained in multivariable models [45]. Previous studies in haemodialysis patients have shown that lower Klotho is associated with CV events, in a manner independent of common risk factors and other covariates [46]. Since Klotho levels are closely tied to age and renal function, understanding inter-relationships between these factors appears crucial for clinical interpretation. Taken together, α-Klotho deficiency is likely to be an important player in the development of kidney disease and may also promote vascular calcification [34, 47, 48, 58].

Theoretical justification for anti-inflammatory (e.g., via inhibition of NF-κB signalling and M2 polarization [49]) effects of SIRT1 is increasing. A schematic representation of the potential, cytoprotective pathways involving α-Klotho and SIRT1 is shown in Figure 4 [14, 50]. Acute rejection studies have also reported SIRT1 decline [51]. However, the descriptive group difference in serum SIRT1 between high and low α-Klotho strata observed at present was not retained in models with continuous predictor form, as well as in categorization approaches. Our continuous analysis did not provide sufficient evidence to speculate regarding an α-Klotho-SIRT1 relationship. This null finding may reflect threshold effects, statistical noise, or a combination of both.

FIGURE 4

The systemic bioactivity of Klotho may be dependent on both membrane-bound and soluble isoform activity. Vasoprotective effects of soluble α-Klotho have been reported, alongside its capacity to inhibit growth factor pathways driving towards pro-fibrotic transition [24, 52]. However, cross-population differences in serum α-Klotho concentrations may affect inter-assay variance and comparability [36, 70]. While our findings align with some adult and paediatric studies [71, 72], research in dialysis and CKD populations shows inconsistent results [73, 74]. These discrepancies may reflect methodological differences, sample heterogeneity, or the complex inflammatory environment in kidney disorders.

The limitations of our study need to be emphasized. First, we measured the level of circulating candidate markers in serum at a single post-KTx timepoint. Caution in interpretation is required due to the declining levels of α-Klotho over time post-KTx, as well as methodological considerations that relate to freeze-thaw cycle and assay standardization [60, 70]). Moreover, the observational design precludes any causal inference at present. At the same time, reverse causation remains a relevant concern, in that impaired graft function may attenuate α-Klotho levels; therefore, greater mechanistic understanding of potential interactions from experimental models is crucial to build the theoretical framework for Klotho interpretation. Third, it should be stated that serum α-Klotho shows substantial inter-individual variation, while no standardized ELISA is widely accepted. We cannot, therefore, recommend the use of a pragmatic clinical cut-off, although research is encouraged and the use of percentile-based cut-offs seems preferable. Additionally, there are multiple potential confounding factors and exposures, such as diet [75], alcohol consumption [76], exercise [77] or stress [78]. Lastly, the modest sample size, event rate and exploratory nature of this study merit additional caution when interpreting our results on a causal level.

To summarize, in this observational cohort of KTRs, we observed that higher circulating α-Klotho levels were independently associated with reduced all-cause hospitalization rates, even after adjustment for baseline eGFR, and were inversely tied to hsIL-6. Higher KDIGO stage was also associated with lower serum α-Klotho concentrations. Our findings extend the current work in the field that supports circulating α-Klotho as a candidate supplemental marker for the KTx setting. Our findings also indirectly support the ongoing interest into mechanistic aspects of therapies that are hypothesized to modulate α-Klotho expression, which includes renin-angiotensin-aldosterone system inhibitors [79], active vitamin D analogues such as calcitriol and paricalcitol [80], and mTOR inhibitors such as sirolimus and everolimus [81, 82]. Direct strategies, such as recombinant soluble α-Klotho administration, remain highly experimental. Importantly, mechanistic speculation on clinical utility requires high caution. Future prospective, large studies with standardized assays and serial α-Klotho measurements remain of importance to replicate and validate the associations investigated at present. At the same time, experimental studies that will clarify mechanistic relationship underlying α-Klotho relationship with inflammation, renal disease and metabolic dysfunction are warranted.

References

• 1.

  BetjesMGHMeijersRWJLitjensNHR. Loss of renal function causes premature aging of the immune system. Blood Purif (2013) 36:173–8. 10.1159/000356084

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 2.

  HeldalTFUelandTJenssenTHartmannAReisæterAVAukrustPet alInflammatory and related biomarkers are associated with post-transplant diabetes mellitus in kidney recipients: a retrospective study. Transpl Int (2018) 31:510–9. 10.1111/tri.13116

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 3.

  JallahBPKuypersDRJ. Impact of immunosenescence in older kidney transplant recipients: associated clinical outcomes and possible risk stratification for immunosuppression reduction. Drugs Aging (2024) 41:219–38. 10.1007/s40266-024-01100-5

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 4.

  CréonAMorinLGarciaVAouniLRabantMTerziFet alEarly post-transplant urinary EGF as a potential predictor of long-term allograft loss in kidney transplant recipients. Transpl Int (2025) 38:15061. 10.3389/ti.2025.15061

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 5.

  de RooijENMvan DuijlTTHoogeveenEKRomijnFPHTMDekkerFWvan KootenCet alUrinary NGAL outperforms 99mTc-MAG3 renography in predicting DCD kidney graft function. Transpl Int (2025) 38:13818. 10.3389/ti.2025.13818

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 6.

  BudhirajaPSmithBHKuklaAKlineTLKorfiatisPStegallMDet alClinical and radiological fusion: a new frontier in predicting post-transplant diabetes mellitus. Transpl Int (2025) 38:14377. 10.3389/ti.2025.14377

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 7.

  AkifovaABuddeKOellerichMBeckJBornemann-KolatzkiKSchützEet alPerspective for donor-derived cell-free DNA in antibody-mediated rejection after kidney transplantation: defining context of use and clinical implications. Transpl Int (2024) 37:13239. 10.3389/ti.2024.13239

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 8.

  ParkSSellaresJTinelCAnglicheauDBestardOFriedewaldJJ. European society of organ transplantation consensus statement on testing for non-invasive diagnosis of kidney allograft rejection. Transpl Int (2024) 36:12115. 10.3389/ti.2023.12115

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 9.

  ImuraAIwanoATohyamaOTsujiYNozakiKHashimotoNet alSecreted klotho protein in sera and CSF: implication for post-translational cleavage in release of klotho protein from cell membrane. FEBS Lett (2004) 565:143–7. 10.1016/j.febslet.2004.03.090

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 10.

  MatsumuraYAizawaHShiraki-IidaTNagaiRKuro-oMNabeshimaY. Identification of the human klotho gene and its two transcripts encoding membrane and secreted klotho protein. Biochem Biophys Res Commun (1998) 242:626–30. 10.1006/bbrc.1997.8019

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 11.

  KaludjerovicJKomabaHSatoTErbenRGBaronROlausonHet alKlotho expression in long bones regulates FGF23 production during renal failure. FASEB J (2017) 31:2050–64. 10.1096/fj.201601036R

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 12.

  OlausonHLindbergKAminRJiaTWernersonAAnderssonGet alTargeted deletion of klotho in kidney distal tubule disrupts mineral metabolism. J Am Soc Nephrol (2012) 23:1641–51. 10.1681/ASN.2012010048

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 13.

  Prud’hommeGJKurtMWangQ. Pathobiology of the klotho antiaging protein and therapeutic considerations. Front Aging (2022) 3:3. 10.3389/fragi.2022.931331

  • CrossRef
  • Google Scholar

• 14.

  MatsumuraYAizawaHKawaguchiHSugaTUtsugiTOhyamaYet alMutation of the mouse klotho gene leads to a syndrome resembling ageing. Nature (1997) 390:45–51. 10.1038/36285

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 15.

  LindbergKAminRMoeOWHuM-CErbenRGÖstman WernersonAet alThe kidney is the principal organ mediating klotho effects. J Am Soc Nephrol (2014) 25:2169–75. 10.1681/ASN.2013111209

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 16.

  LiS-AWatanabeMYamadaHNagaiAKinutaMTakeiK. Immunohistochemical localization of klotho protein in brain, kidney, and reproductive organs of mice. Cell Struct Funct (2004) 29:91–9. 10.1247/csf.29.91

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 17.

  KurosuHYamamotoMClarkJDPastorJVNandiAGurnaniPet alSuppression of aging in mice by the hormone klotho. Science (2005) 309:1829–33. 10.1126/science.1112766

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 18.

  LeeJKimDLeeH-JChoiJ-YMinJ-YMinK-B. Association between serum klotho levels and cardiovascular disease risk factors in older adults. BMC Cardiovasc Disord (2022) 22:442. 10.1186/s12872-022-02885-2

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 19.

  ChenZTaoTHuangGTongXLiQSuG. Analysis of the association between serum antiaging humoral factor klotho and cardiovascular disease potential risk factor apolipoprotein B in general population. Medicine (Baltimore) (2023) 102:e34056. 10.1097/MD.0000000000034056

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 20.

  WangZZhangHZhengGWangZShiL. Gender-specific association between circulating serum klotho and metabolic components in adults. BMC Endocr Disord (2024) 24:198. 10.1186/s12902-024-01737-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 21.

  ChO. The association between metabolic syndrome and the anti-aging humoral factor klotho in middle-aged and older adults. Diabetes & Metabolic Syndrome (2022) 16 (6), 102522. 10.1016/j.dsx.2022.102522

  • CrossRef
  • Google Scholar

• 22.

  LiangYLiuYTanQZhouKWuYYuL. Systemic immune-inflammation mediates the association between klotho protein and metabolic syndrome: findings from a large-scale population-based study. Lipids Health Dis (2024) 23:360. 10.1186/s12944-024-02339-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 23.

  ChenCTangPZhuW. Systemic immune-inflammation index mediates the association between abdominal obesity and serum klotho levels. Sci Rep (2025) 15:4205. 10.1038/s41598-025-88015-2

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 24.

  HuMCShiMZhangJQuiñonesHGriffithCKuro-oMet alKlotho deficiency causes vascular calcification in chronic kidney disease. J Am Soc Nephrol (2011) 22:124–36. 10.1681/ASN.2009121311

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 25.

  YangYLiuYWangYChaoYZhangJJiaYet alRegulation of SIRT1 and its roles in inflammation. Front Immunol (2022) 13:13. 10.3389/fimmu.2022.831168

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 26.

  KongLWuHZhouWLuoMTanYMiaoLet alSirtuin 1: a target for kidney diseases. Mol Med (2015) 21:87–97. 10.2119/molmed.2014.00211

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 27.

  LundKPvon StemannJHErikssonFHansenMBPedersenBKSørensenSSet alIL-10-specific autoantibodies predict major adverse cardiovascular events in kidney transplanted patients - a retrospective cohort study. Transpl Int (2019) 32:933–48. 10.1111/tri.13425

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 28.

  BoluferMSolerJMolinaMTacoOVilaAMacíaM. Immunotherapy for cancer in kidney transplant patients: a difficult balance between risks and benefits. Transpl Int (2024) 37:13204. 10.3389/ti.2024.13204

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 29.

  StenvinkelPLarssonTE. Chronic kidney disease: a clinical model of premature aging. Am J Kidney Dis (2013) 62:339–51. 10.1053/j.ajkd.2012.11.051

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 30.

  YanZShaoT. Chronic inflammation in chronic kidney disease. Nephron (2023) 148:143–51. 10.1159/000534447

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 31.

  InkerLAEneanyaNDCoreshJTighiouartHWangDSangYet alNew Creatinine- and cystatin C–Based equations to estimate GFR without race. N Engl J Med (2021) 385:1737–49. 10.1056/NEJMoa2102953

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 32.

  Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int (2024) 105:S117–S314. 10.1016/j.kint.2023.10.018

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 33.

  BatkoKSączekABanaszkiewiczMMałyszkoJKoc-ŻórawskaEŻórawskiMet alRisk prediction of kidney function in long-term kidney transplant recipients. Front Med (2025) 12:1469363. 10.3389/fmed.2025.1469363

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 34.

  LimKLuT-SMolostvovGLeeCLamFTZehnderDet alVascular klotho deficiency potentiates the development of human artery calcification and mediates resistance to fibroblast growth factor 23. Circulation (2012) 125:2243–55. 10.1161/CIRCULATIONAHA.111.053405

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 35.

  OlausonHMenckeRHillebrandsJ-LLarssonTE. Tissue expression and source of circulating αKlotho. Bone (2017) 100:19–35. 10.1016/j.bone.2017.03.043

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 36.

  HuMCShiMZhangJAddoTChoHJBarkerSLet alRenal production, uptake, and handling of circulating αKlotho. J Am Soc Nephrol (2016) 27:79–90. 10.1681/ASN.2014101030

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 37.

  PavikIJaegerPEbnerLPosterDKrauerFKistlerADet alSoluble klotho and autosomal dominant polycystic kidney disease. Clin J Am Soc Nephrol (2012) 7:248–57. 10.2215/CJN.09020911

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 38.

  PanessoMCShiMChoHJPaekJYeJMoeOWet alKlotho has dual protective effects on cisplatin-induced acute kidney injury. Kidney Int (2014) 85:855–70. 10.1038/ki.2013.489

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 39.

  GuanXNieLHeTYangKXiaoTWangSet alKlotho suppresses renal tubulo-interstitial fibrosis by controlling basic fibroblast growth factor-2 signalling. J Pathol (2014) 234:560–72. 10.1002/path.4420

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 40.

  MorenoJAIzquierdoMCSanchez-NiñoMDSuárez-AlvarezBLopez-LarreaCJakubowskiAet alThe inflammatory cytokines TWEAK and TNFα reduce renal klotho expression through NFκB. J Am Soc Nephrol (2011) 22:1315–25. 10.1681/ASN.2010101073

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 41.

  ZengYWangP-HZhangMDuJ-R. Aging-related renal injury and inflammation are associated with downregulation of klotho and induction of RIG-I/NF-κB signaling pathway in senescence-accelerated mice. Aging Clin Exp Res (2016) 28:69–76. 10.1007/s40520-015-0371-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 42.

  ThurstonRDLarmonierCBMajewskiPMRamalingamRMidura-KielaMLaubitzDet alTumor necrosis factor and interferon-gamma down-regulate klotho in mice with colitis. Gastroenterology (2010) 138:1384–94. 10.1053/j.gastro.2009.12.002

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 43.

  ZhaoYBanerjeeSDeyNLeJeuneWSSarkarPSBrobeyRet alKlotho depletion contributes to increased inflammation in kidney of the db/db mouse model of diabetes via RelA (serine)536 phosphorylation. Diabetes (2011) 60:1907–16. 10.2337/db10-1262

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 44.

  HuM-CMoeOW. Klotho as a potential biomarker and therapy for acute kidney injury. Nat Rev Nephrol (2012) 8:423–9. 10.1038/nrneph.2012.92

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 45.

  OhHJNamBYLeeMJKimCHKooHMDohFMet alDecreased circulating klotho levels in patients undergoing dialysis and relationship to oxidative stress and inflammation. Perit Dial Int (2015) 35:43–51. 10.3747/pdi.2013.00150

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 46.

  MemmosESarafidisPPateinakisPTsiantoulasAFaitatzidouDGiamalisPet alSoluble klotho is associated with mortality and cardiovascular events in hemodialysis. BMC Nephrol (2019) 20:217. 10.1186/s12882-019-1391-1

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 47.

  PatidarASinghDKThakurSFarringtonKBaydounAR. Uremic serum-induced calcification of human aortic smooth muscle cells is a regulated process involving klotho and RUNX2. Biosci Rep (2019) 39:BSR20190599. 10.1042/BSR20190599

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 48.

  KimHRNamBYKimDWKangMWHanJ-HLeeMJet alCirculating α-klotho levels in CKD and relationship to progression. Am J Kidney Dis (2013) 61:899–909. 10.1053/j.ajkd.2013.01.024

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 49.

  ZhaoXLiMLuYWangMXiaoJXieQet alSirt1 inhibits macrophage polarization and inflammation in gouty arthritis by inhibiting the MAPK/NF-κB/AP-1 pathway and activating the Nrf2/HO-1 pathway. Inflamm Res (2024) 73:1173–84. 10.1007/s00011-024-01890-9

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 50.

  GaoDZuoZTianJAliQLinYLeiHet alActivation of SIRT1 attenuates klotho deficiency–induced arterial stiffness and hypertension by enhancing AMP-activated protein kinase activity. Hypertension (2016) 68:1191–9. 10.1161/HYPERTENSIONAHA.116.07709

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 51.

  AksungurNKizilkayaMAltundaşNBalkanEKaraSDemirciEet alMolecular crosstalk between SIRT1, Wnt/β-Catenin signaling, and inflammatory pathways in renal transplant rejection: role of miRNAs, lncRNAs, IL-1, IL-6, and tubulointerstitial inflammation. Medicina (Kaunas) (2025) 61:1073. 10.3390/medicina61061073

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 52.

  DoiSZouYTogaoOPastorJVJohnGBWangLet alKlotho inhibits transforming growth Factor-β1 (TGF-β1) signaling and suppresses renal fibrosis and cancer metastasis in mice. J Biol Chem (2011) 286:8655–65. 10.1074/jbc.M110.174037

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 53.

  ThongprayoonCNeyraJAHansrivijitPMedauraJLeeaphornNDavisPWet alSerum klotho in living kidney donors and kidney transplant recipients: a meta-analysis. J Clin Med (2020) 9:1834. 10.3390/jcm9061834

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 54.

  KimSMKimSJAhnSMinS-IMinS-KHaJ. The potential role of klotho as a prognostic biomarker in deceased donor kidney transplantation. Transplantation (2018) 102:S539. 10.1097/01.tp.0000543389.60945.78

  • CrossRef
  • Google Scholar

• 55.

  DengGYangAWuJZhouJMengSZhuCet alThe value of older Donors’ Klotho Level in Predicting Recipients’ short-term renal function. Med Sci Monit (2018) 24:7936–43. 10.12659/MSM.913274

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 56.

  TsujitaMKosugiTMasudaTOkadaMFutamuraKHiramitsuTet alSerum αKlotho as a predictor of graft dysfunction after kidney transplantation. Transpl Proc (2018) 50:3440–4. 10.1016/j.transproceed.2018.09.008

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 57.

  ShikidaYMizobuchiMYoshitakeOKatoTOgataHKoiwaFet alLower soluble klotho levels in the pretransplant period are associated with an increased risk of renal function decline in renal transplant patients. Ther Apher Dial (2021) 25:331–40. 10.1111/1744-9987.13578

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 58.

  BarkerSLPastorJCarranzaDQuiñonesHGriffithCGoetzRet alThe demonstration of αKlotho deficiency in human chronic kidney disease with a novel synthetic antibody. Nephrol Dial Transpl (2015) 30:223–33. 10.1093/ndt/gfu291

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 59.

  ShimamuraYHamadaKInoueKOgataKIshiharaMKagawaTet alSerum levels of soluble secreted α-Klotho are decreased in the early stages of chronic kidney disease, making it a probable novel biomarker for early diagnosis. Clin Exp Nephrol (2012) 16:722–9. 10.1007/s10157-012-0621-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 60.

  Donate-CorreaJMatos-PerdomoEGonzález-LuisAMartín-OliveraAOrtizAMora-FernándezCet alThe value of klotho in kidney transplantation. Transplantation (2023) 107:616–27. 10.1097/TP.0000000000004331

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 61.

  BleskestadIHThorsenISJonssonGSkadbergØBergremHGøranssonLG. Soluble klotho and intact fibroblast growth factor 23 in long-term kidney transplant patients. Eur J Endocrinol (2015) 172:343–50. 10.1530/EJE-14-0457

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 62.

  LimSWJinLLuoKJinJShinYJHongSYet alKlotho enhances FoxO3-mediated manganese superoxide dismutase expression by negatively regulating PI3K/AKT pathway during tacrolimus-induced oxidative stress. Cell Death Dis (2017) 8:e2972. 10.1038/cddis.2017.365

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 63.

  de BorstMHVervloetMGter WeePMNavisG. Cross talk between the renin-angiotensin-aldosterone system and vitamin D-FGF-23-klotho in chronic kidney disease. J Am Soc Nephrol (2011) 22:1603–9. 10.1681/ASN.2010121251

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 64.

  García-VizcaínoEMLiarteSAlonso-RomeroJLNicolásFJ. Sirt1 interaction with active Smad2 modulates transforming growth factor-β regulated transcription. Cell Commun Signal (2017) 15:50. 10.1186/s12964-017-0205-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 65.

  ZhuHGaoYZhuSCuiQDuJ. Klotho improves cardiac function by suppressing reactive oxygen species (ROS) mediated apoptosis by modulating Mapks/Nrf2 signaling in doxorubicin-induced cardiotoxicity. Med Sci Monit (2017) 23:5283–93. 10.12659/MSM.907449

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 66.

  BiFLiuWWuZJiCChangC. Antiaging factor klotho retards the progress of intervertebral disc degeneration through the toll-like receptor 4-NF-κB pathway. Int J Cell Biol (2020) 2020:8319516. 10.1155/2020/8319516

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 67.

  WangYWangKBaoYZhangTAiniwaerDXiongXet alThe serum soluble klotho alleviates cardiac aging and regulates M2a/M2c macrophage polarization via inhibiting TLR4/Myd88/NF-κB pathway. Tissue Cell (2022) 76:101812. 10.1016/j.tice.2022.101812

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 68.

  YiJLuoJ. SIRT1 and p53, effect on cancer, senescence and beyond. Biochim Biophys Acta (2010) 1804:1684–9. 10.1016/j.bbapap.2010.05.002

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 69.

  JeongSMHaigisMC. Sirtuins in cancer: a balancing act between genome stability and metabolism. Mol Cells (2015) 38:750–8. 10.14348/molcells.2015.0167

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 70.

  AdemaAYVervloetMGBlankensteinMAHeijboerAC. α-Klotho is unstable in human urine. Kidney Int (2015) 88:1442–4. 10.1038/ki.2015.238

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 71.

  GamrotZAdamczykPŚwiętochowskaERoszkowska-BjanidDGamrotJSzczepanskaM. Tumour necrosis factor alpha (TNFα) and alpha-Klotho (αKL) in children and adolescents with chronic kidney disease (CKD). Endokrynol Pol (2021) 72:625–33. 10.5603/EP.a2021.0082

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 72.

  WangQSuWShenZWangR. Correlation between soluble α-Klotho and renal function in patients with chronic kidney disease: a review and meta-analysis. Biomed Res Int (2018) 2018:9481475. 10.1155/2018/9481475

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 73.

  LisowskaKAStoroniakHSoroczyńska-CybulaMMaziewskiMDębska-ŚlizieńA. Serum levels of α-Klotho, inflammation-related cytokines, and mortality in hemodialysis patients. J Clin Med (2022) 11:6518. 10.3390/jcm11216518

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 74.

  SeilerSWenMRothHJFehrenzMFlüggeFHerathEet alPlasma klotho is not related to kidney function and does not predict adverse outcome in patients with chronic kidney disease. Kidney Int (2013) 83:121–8. 10.1038/ki.2012.288

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 75.

  Jurado-FasoliLAmaro-GaheteFJMartinez-TellezBRuizJRGutiérrezÁCastilloMJet alAdherence to the mediterranean diet, dietary factors, and S-Klotho plasma levels in sedentary middle-aged adults. Exp Gerontol (2019) 119:25–32. 10.1016/j.exger.2019.01.019

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 76.

  Jurado-FasoliLAmaro-GaheteFJGutiérrezÁCastilloMJ. Alcohol consumption and S-Klotho plasma levels in sedentary healthy middle-aged adults: a cross sectional study. Drug Alcohol Depend (2019) 194:107–11. 10.1016/j.drugalcdep.2018.09.024

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 77.

  Amaro-GaheteFJGutiérrezÁJurado-FasoliLRuizJRCastilloMJGutiérrezÁ. Role of exercise on S-Klotho protein regulation: a systematic review. Curr Aging Sci (2018) 11:100–7. 10.2174/1874609811666180702101338

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 78.

  PratherAAEpelESArenanderJBroestlLGarayBIWangDet alLongevity factor klotho and chronic psychological stress. Transl Psychiatry (2015) 5:e585. 10.1038/tp.2015.81

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 79.

  LimSCLiuJ-JSubramaniamTSumCF. Elevated circulating alpha-klotho by angiotensin II receptor blocker losartan is associated with reduction of albuminuria in type 2 diabetic patients. J Renin Angiotensin Aldosterone Syst (2014) 15:487–90. 10.1177/1470320313475905

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 80.

  LauWLLeafEMHuMCTakenoMMKuro-oMMoeOWet alVitamin D receptor agonists increase klotho and osteopontin while decreasing aortic calcification in mice with chronic kidney disease fed a high phosphate diet. Kidney Int (2012) 82:1261–70. 10.1038/ki.2012.322

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 81.

  MizusakiKHasuikeYKimuraTNagasawaYKuraganoTYamadaYet alInhibition of the mammalian target of rapamycin may augment the increase in soluble klotho levels in renal transplantation recipients. Blood Purif (2019) 47(Suppl. 2):12–8. 10.1159/000496630

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 82.

  WuQ-JZhangT-NChenH-HYuX-FLvJ-LLiuY-Yet alThe sirtuin family in health and disease. Sig Transduct Target Ther (2022) 7:402. 10.1038/s41392-022-01257-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar