Time‐Restricted Feeding With High‐Fat Diet Slows Weight Gain and Reduces Renal Calcium Oxalate Crystal Formation Without Reducing Energy Intake

ABSTRACT

Renal calcium oxalate stones are closely linked to lipid metabolism disorders. A long‐term high‐fat diet (HFD) can lead to obesity and other metabolic disorders, which significantly contribute to stone formation. Recent studies indicate that time‐restricted feeding (TRF) plays a crucial role in improving metabolic homeostasis and preventing metabolic diseases. However, its impact on kidney stone formation has yet to be investigated. We examined differences in calcium oxalate crystal formation in mouse kidneys using glyoxylic acid (Gly) modeling in HFD mouse models subjected to either ad libitum (Ad) feeding or TRF. TRF mitigated weight gain, improved blood lipid metabolism disorders, and reduced lipid deposition in the liver and kidneys, alleviating pathological damage. Compared with the Ad group, the TRF group exhibited lower urinary concentrations of oxalate and calcium ions, which corresponded with reduced expression of OPN and CD44, leading to decreased oxalate crystal formation. Gly intervention in the Ad group increased the expression of TNF‐α and IL‐6 in the kidneys, leading to an imbalance between oxidative stress and antioxidant responses. In contrast, TRF showed significant improvement, potentially linked to activation of the PI3K‐AKT pathway. Nighttime TRF, which more closely aligns with the natural work and rest rhythms of mice, produced more pronounced effects than daytime TRF. NR1D1 expression in the kidneys was closely associated with stone formation. TRF can improve lipid metabolism and inhibit the formation of renal calcium oxalate stones, and dietary preventive strategies that align with biological rhythms demonstrate particularly significant effects.

This graphical abstract compares ad libitum feeding with time‐restricted feeding (TRF) in mice on a high‐fat diet. TRF (10‐h access during either daytime or nighttime) does not reduce total energy intake but slows weight gain, improves serum lipid profiles, reduces lipid deposition in liver and kidney, lowers urinary oxalate and calcium levels, decreases renal calcium oxalate crystal formation, down‐regulates CD44/OPN expression, alleviates oxidative stress and PI3K‐AKT‐mediated inflammation, and partially restores circadian rhythm disruption. Night‐time TRF shows more pronounced benefits than daytime TRF.

1. Introduction

Kidney stones have become a prominent global health concern over the past three decades and largely affect the well‐being of patients [1]. Studies show a consistent rise in the prevalence of kidney stones in various countries. Kidney stones are primarily addressed through surgical interventions. However, due to their high incidence and recurrence rates, many patients undergo multiple surgical treatments, and some are left with residual stones post‐surgery, which necessitates further surgical intervention. This situation not only prolongs the treatment cycle for kidney stones and deteriorates patients' quality of life but also significantly increases the socioeconomic burden on public health. For instance, the United States spends more than 2 billion US dollars each year on kidney stone healthcare [2]. Therefore, prevention and early intervention must be prioritized over treatment. Metabolic disorders, including hyperlipidemia, obesity, and insulin resistance, are recognized as independent risk factors for kidney stone formation. Among these, dietary habits, particularly a high‐fat diet (HFD), play a crucial role in the progression of both metabolic disorders and kidney stone formation. HFD‐induced dyslipidemia and systemic inflammation have been demonstrated to exacerbate oxidative stress and impair renal function, thereby increasing the risk of kidney stone development [3, 4]. Nevertheless, the mechanisms underlying this association remain only partially understood.

In recent years, there has been increasing attention to dietary interventions that focus not only on dietary composition but also on meal timing. Time‐restricted feeding (TRF), a dietary approach that limits food intake to specific daily time windows (typically less than 12 h) without altering total caloric intake, has emerged as a promising intervention for mitigating metabolic disorders such as obesity, hyperlipidemia, and insulin resistance [5]. Studies suggest that TRF exerts its beneficial effects by aligning with circadian rhythms, which may reduce inflammation, oxidative stress, and metabolic disruption [6, 7, 8]. Furthermore, these effects may confer renal protective benefits, as evidenced by TRF's potential to mitigate acute kidney injury [9].

Given the strong association between HFD‐induced metabolic disturbances and the risk of kidney stones, investigating the role of TRF in this context is particularly pertinent. While previous studies emphasize the protective effects of high‐quality diets against kidney stone formation, the influence of meal timing on the development of kidney stones remains relatively underexplored [10, 11]. Building upon existing evidence and our prior research, we hypothesize that TRF will improve lipid metabolism and reduce kidney stone formation by mitigating inflammation and oxidative stress, especially when aligned with circadian rhythms. This study aims to clarify the role of TRF in the prevention of kidney stones and its interaction with lipid metabolism, offering new insights into dietary interventions for kidney stone management.

2. Methods

2.1. Animals

Eight‐week‐old male C57BL/6JGpt mice weighing 23.60 ± 1.20 g were procured from GemPharmatech (Nanjing, China). The mice were housed at the Animal Experiment Center under specific conditions, including a constant room temperature of 25°C, humidity 40%–60%, and a 12‐h light: dark cycle. In this cycle, Zeitgeber time 0 (ZT) signifies the start of the light phase, whereas ZT12 indicates the shift to the dark phase. All animal procedures were ethically approved by the Laboratory Animal Ethics Committee, and the work has been reported in accordance with the ARRIVE guidelines (Animals in Research: Reporting In Vivo Experiments) [12].

2.2. TRF and Glyoxylic Acid (Gly) Injection

Thirty‐two mice were adaptively raised for one week and then randomly divided according to body weight into four groups (n = 8 per group) and housed four per cage. The feeding regimen lasted for 5 weeks, during which fresh high‐fat feed (HFD) (Research Diets, D12492 60 kcal% fat) was provided daily. Distilled water was freely available for drinking, and dressings were changed regularly. Daily water and food intake were measured per cage, and each mouse was weighed individually every other day. A researcher blinded to the experimental design recorded all relevant data as well as qualitative observations of general behaviors and health status to avoid subjective bias.

The grouping details are shown in Figure 1a (1) An HFD group and (2) an HFD + Gly modeling group (HFD + Gly) both received ad libitum (Ad) (ZT0‐ZT24) HFD for 5 weeks. (3) A (Daytime TRF)HFD + Gly group ((dTRF)HFD + Gly) received HFD from 10:00 to 20:00 (ZT2‐ZT12) during the day. (4) A (Nighttime TRF) HFD + Gly group ((nTRF)HFD + Gly) was given HFD from 20:00 to 8:00 the next day (ZT14‐ZT24) for 5 weeks. All the groups received drug intervention for 7 days starting from the fifth week, with intraperitoneal injection of 80 mg/kg/d 2% Gly in the HFD + Gly, (dTRF)HFD + Gly, and (nTRF)HFD + Gly groups and 0.9% sodium chloride solution instead of Gly in the HFD group [13, 14]. For detailed experimental procedures, please refer to the [Link], [Link], [Link].

FIGURE 1.

Time‐restricted feeding does not affect calorie and water intake. (a) The experimental scheme. HFD (n = 8), HFD + Gly (n = 8), (dTRF)HFD + Gly (n = 8), (nTRF)HFD + Gly (n = 8). (b, d, f, g) Changes in high‐fat feed intake per cage (n = 4) during weeks 1–5. (c, e) Changes in water intake per cage (n = 4) in mice during weeks 1–5. Data are presented as mean ± standard deviation. Comparisons between multiple groups were performed using one‐way ANOVA followed by Bonferroni post hoc test in b, c, d, e ***p < 0.001.

2.3. Urine and Serum Isolation

At the end of the fifth week, the mice were moved to a clean metabolic cage for urine collection. After 24 h of adjustment, urine was collected from the base of the cage the following day. The collected urine was centrifuged at 3000 rpm and 4°C for 20 min. The resulting supernatant was transferred to a 1.5 mL EP tube and promptly frozen at −80°C for analysis. Then venous blood was obtained from anesthetized mice after the removal of eyeballs. The blood samples were kept on ice for 30 min and centrifuged at 3000 rpm and 4°C for 10 min. The serum was then aliquoted into 1.5 mL EP tubes and stored at −80°C until further analysis.

2.4. Less' Index and Tissue Isolation (Kidney and Liver)

The length of the mice in each group was measured under isoflurane anesthesia. The length referred to the distance from the nose tip to the anus while the tested mouse was in a supine position. Lee's index was calculated to evaluate obesity level:

$${\mathrm{Lee}}^{\text{'}}\mathrm{s}\text{index}=\sqrt[3]{\text{weight}\left(\mathrm{g}\right)}\times \frac{1000}{\text{length}\left(\mathrm{cm}\right)}$$

The mice were euthanized through cervical dislocation. A 5‐cm longitudinal incision was made along the midline of the lower abdomen, and 2‐cm transverse openings were made on both sides to fully expose the intra‐abdominal tissues. The perirenal tissue was carefully separated layer by layer, and both kidneys were removed and weighed. One kidney was quickly frozen in liquid nitrogen, while the other was fixed in a 4% paraformaldehyde solution. The liver was fully exposed, while the surrounding blood vessels and tissues removed and weighed. A portion of the liver tissue was fixed in a 4% paraformaldehyde solution, while another portion was urgently frozen in liquid nitrogen. Then kidney organ index was calculated as an indicator of renal hypertrophy and edema, which often accompany inflammatory and pathological changes.

$$\text{Organ index}=\frac{\mathrm{wet}\text{weight of organ}\left(\mathrm{g}\right)}{\text{weight}\left(\mathrm{g}\right)}\times 100\%$$

2.5. Urine and Serum Measurement

The frozen urine and serum samples were analyzed using a fully automated analyzer (Mindary BS‐360E) following the manufacturer's protocol. The analyzer measured urine pH, electrolyte levels (calcium, phosphorus, magnesium), renal function (serum creatinine, serum urea nitrogen), and serum lipids (total cholesterol, TG, triglycerides, TC, high‐density lipoprotein, HDL, low‐density lipoprotein, LDL). In addition, the oxalate content in urine samples was detected using high‐performance liquid chromatography (Agilent Technologies 1200).

2.6. Enzyme‐Linked Immunosorbent Assay (ELISA) for Leptin and Adiponectin

Leptin and adiponectin levels were measured using ELISA kits (02902M2 and 02830M2, Jiangsu Jingmei Biotechnology, China) in accordance with the manufacturer's instructions.

2.7. Nuclear Fast Red Staining for Calcium Oxalate

Paraffin‐embedded tissues (livers and kidneys) were processed following standard procedures. The tissue sections were baked and deparaffinized using environmentally‐friendly solutions and graded ethanol, and then rinsed with deionized water. Next, the sections were stained with 1% nuclear fast red and observed under a microscope until the optimal staining was achieved. After staining, the sections were dehydrated in graded ethanol, cleared in xylene, air‐dried, and mounted with neutral resin. The stained sections were then examined under a polarized light microscope to observe calcium oxalate crystal deposition, with three random fields photographed per section, and quantitative analysis of the calcium oxalate crystal area was conducted using ImageJ.

2.8. Hematoxylin–Eosin (HE) Staining

The kidney and liver samples were stained with HE following standard procedures. The sections were deparaffinized using graded ethanol, then stained with hematoxylin for 4 min, immersed in an acidic alcohol differentiation solution, and rinsed with deionized water. After that, the sections were stained with eosin for 20 s, dehydrated with 95% ethanol, and finally sealed with xylene transparent and neutral resin before observation under a microscope post‐solidification.

2.9. Oil Red O Staining

Mouse liver and kidney tissues were fixed in a 4% paraformaldehyde solution, trimmed, dehydrated in a 20% sucrose solution followed by a 30% sucrose solution, and then embedded in an OCT embedding medium for curing. The samples were rapidly frozen, sectioned at a thickness of 8 μm, and cryopreserved at −20°C. Frozen sections were washed in 60% isopropanol before Oil red O staining. Excessive stain was removed with isopropanol and deionized water. Next, the sections were lightly stained with Mayer's hematoxylin, differentiated in a 1% hydrochloric acid alcohol solution, and rinsed with deionized water. Finally, the sections were cleared, mounted with neutral resin, and examined in terms of lipid deposition indicated by oil red O staining in the tissue sections.

2.10. Western Blot

Proteins were extracted from the frozen kidney tissues. The tissues were initially rinsed with ice‐cold physiological saline, then lysed using a radio‐immunoprecipitation assay (RIPA) buffer, homogenized, and sonicated. After centrifugation, the supernatant was obtained and stored at −80°C. Protein concentration was detected using the bicinchoninic acid (BCA) method, and the samples were appropriately diluted based on the results. They were then combined with a protein‐loading buffer and denatured under boiling. The optimal concentration of a precast gel was selected for electrophoresis, and both protein samples and markers were loaded into the wells. Electrophoresis was conducted at the correct voltage, and the proteins were transferred to a polyvinylidene difluoride (PVDF) membrane using the “sandwich” method. The membrane was blocked with 5% skim milk and incubated with primary (1:1000 for rabbit CD44, rabbit anti‐OPN, rabbit anti‐NR1D1, rabbit anti‐PI3K, rabbit anti‐p PI3K, rabbit anti‐AKT, rabbit anti‐p AKT, rabbit anti‐TNF‐α, and rabbit anti‐IL6, 1:5000 for rabbit anti‐GAPDH) and secondary antibodies (goat anti‐rabbit IgG, 1:1000), with Tris–buffered saline and 0.05% Tween‐20 (TBST) washes after each incubation. Finally, chemiluminescent detection was carried out, and the bands were imaged and analyzed for protein expression levels using software to compare grayscale values.

2.11. Immunohistochemistry (IHC)

Tissue sections were baked and dewaxed, followed by antigen retrieval using pH 6.0 citrate buffer in a microwave oven. Slides were then washed in phosphate buffer solution (PBS, pH 7.4) and incubated in 3% H₂O₂ to block endogenous peroxidase activity. After blocking with 3% bovine serum albumin (BSA), the slides were incubated overnight at 4°C with primary antibodies in the dark (rabbit anti‐OPN 1:500, rabbit anti‐CD44 1:200, rabbit anti‐NR1D1 1:100, rabbit anti‐PI3K 1:2000, rabbit anti‐AKT 1:100, rabbit anti‐TNF‐α 1:400, rabbit anti‐IL‐6 1:800). On the next day, the slides were washed with PBS, incubated with secondary antibodies (goat anti‐rabbit IgG, 1:200) raised in rabbits for 50 min at room temperature, and then stained with diaminobenzidine (DAB) as the chromogenic substrate. After counterstaining with hematoxylin, the slides were dehydrated in an ethanol gradient, immersed in xylene and butanol, and observed under a bright‐field microscope. Positive staining showed brownish‐yellow after neutral resin embedding.

2.12. Fluorescent Staining of Reactive Oxygen Species (ROS)

ROS fluorescence staining was conducted by outlining tissue sections with a hydrophobic barrier pen, followed by incubation with dihydroethidium (DHE, Biyuntian S0063, China) in PBS at 37°C for 30 min in the dark. The sections were then washed, air‐dried, and stained with 4′,6‐diamidino‐2‐phenylindole (DAPI) for 10 min without light protection to label cell nuclei. After additional washes, the sections were mounted with an anti‐fade mounting medium and examined using a fluorescence microscope.

2.13. Redox Levels (MDA, SOD, GSH)

Frozen mouse kidney tissues (20 mg) were homogenized with physiological saline at a 1:9 ratio and centrifuged at 3500 rpm for 10 min to obtain the supernatant for analysis. The levels of superoxide dismutase (SOD, A001‐3), malondialdehyde (MDA, A003‐1), and glutathione (GSH, A006‐2‐1) in the supernatant were quantified using specific assay kits from Nanjing Jiancheng Biotechnology.

2.14. Transcriptome Sequencing

The frozen mouse kidney tissues were sent to high‐throughput sequencing and bioinformatics analysis at Jiangxi Haipulos Medical Laboratory Co. Ltd. Differential expressions were analyzed on the R package DESeq 1.18.1 with Benjamini and Hochberg correction for false discovery rate control. The criteria of differentially expressed genes (DEGs) were |log2(FoldChange)| > 1 and adjusted p < 0.05. Volcano plots were drawn using ggplot2, and subsequent functional enrichment analysis was performed with the R package clusterProfiler for GO and KEGG pathways.

2.15. Statistic Analysis

To minimize potential bias, the histological evaluation and data analysis were conducted in a blinded manner. The data were analyzed and graphed using SPSS 25.0, R 4.2.2, Graph Pad Prism 10, ImageJ 1.46r, and Figdraw. Various statistical analysis methods were chosen depending on the type of data. Measured data were reported as mean ± standard deviation, and compared between groups using t‐test or analysis of variance. Counting data were presented as percentage (%) and analyzed using Chi‐square test or Fisher's exact test. ANOVA test was performed when comparing more than two groups, applying Bonferroni correction for multiple statistical hypotheses testing. A significant difference was determined as p < 0.05.

3. Results

3.1. TRF Improves Overall Condition and Slows Weight Gain in Gly‐Treated Mice

During the initial 4‐week experimental period, qualitative observations by the blinded researcher showed that mice in the TRF groups exhibited more frequent cage exploration and grooming behaviors, while mice in the two ad libitum (Ad) groups spent more time resting and showed weaker responses to routine cage operations. These observations were not quantitatively measured. No significant differences in food intake or water consumption were observed among the four groups (Figure 1b–e). The TRF did not significantly impact the food intake or water consumption of the mice (Figure 1f). After Gly treatment in the fifth week, the mice in the HFD + Gly (n = 8), (dTRF)HFD + Gly (n = 8), and (nTRF)HFD + Gly groups (n = 8) exhibited reduced appetite and food intake, while food intake in the HFD group (n = 8) initially increased and eventually stabilized (Figure 1g).

During the first four weeks, the mice under TRF showed slower weight gain compared to the Ad mice (Figure 2a–c). After Gly treatment in the fifth week, the mice in the HFD group showed a steady increase in weight, while those in the HFD + Gly group lost notable weight. The weight loss in the TRF‐treated mice was less pronounced, as the (nTRF)HFD + Gly group exhibited less weight loss than the (dTRF)HFD + Gly group. Analysis with Lee's index suggests TRF intervention can potentially improve the obesity status of the mice (Figure 2d).

FIGURE 2.

Time‐restricted feeding slows rapid weight gain and reduces organ damage. (a) Eating effect on weight changes during weeks 1–5. (b) A comparison of macrophotographs of four groups of mice at the time of execution on day 35. (c) Comparison of body weight between groups at different time points: 1 day (prior to the initiation of HFD), 27 days (before the intraperitoneal injection of Gly or saline), and 35 days (prior to execution). (d) Quantification of Less's index (e) and Leptin, adiponectin in serum. (f) H&E staining of liver tissue (100×). (g) Liver issue stained with Oil Red O (40×, 100×), (h) and Oil Red O staining of kidney issue. (i) H&E staining of kidney issue. (j) Kidney organ index. Scale bars indicate 100 and 250 μm. Data are presented as mean ± standard deviation. Comparisons between multiple groups were performed using one‐way ANOVA followed by Bonferroni post hoc test in a, c, d, e, j (*p < 0.05, **p < 0.01, ***p < 0.001).

3.2. TRF Improves Blood Lipid Metabolism Disorders in Gly‐Treated Mice

Both TRF groups showed a trend of reduced serum LDL and elevated HDL levels compared with the HFD + Gly group, with statistical significance reached only in the (nTRF)HFD + Gly group (Table 1). The (nTRF)HFD + Gly group exhibited greater lipid metabolism improvement than the (dTRF)HFD + Gly group. The serum adiponectin and leptin levels in the (nTRF)HFD + Gly group decreased compared to other groups, but not significantly (Figure 2e).

TABLE 1.

Differences in the levels of serum lipid metabolism and kidney function.

Serum	Groups				p
	HFD	HFD + Gly	(dTRF)HFD + Gly	(nTRF)HFD + Gly
TG (mmol/L)	0.48 ± 0.04	0.45 ± 0.03	0.41 ± 0.05	0.44 ± 0.05	0.098
TC (mmol/L)	4.99 ± 0.86	5.66 ± 0.62	5.69 ± 0.62	5.77 ± 0.43	0.247
HDL (mmol/L)	3.41 ± 0.55 ^	3.84 ± 0.37 ^	3.96 ± 0.52 ^	4.71 ± 0.28 #	0.002
LDL (mmol/L)	0.73 ± 0.25 ^	0.72 ± 0.12 ^	0.70 ± 0.11 ^	0.38 ± 0.12 #	0.009
Creatinine (μmol/L)	3.74 ± 2.49 #	11.92 ± 4.51 ^	7.84 ± 3.91	4.52 ± 2.44 #	0.012
Urea nitrogen (mmol/L)	9.40 ± 0.99 #	20.94 ± 7.51 ^	19.87 ± 6.99 ^	12.28 ± 2.18 #	0.984

Note: Data are presented as the mean ± SEM. One‐way ANOVA analysis followed by Tukey post hoc multi‐comparison test was used.

^# p < 0.05, compared with HFD + Gly.

^{^} p < 0.05, compared with (nTRF)HFD + Gly.

3.3. TRF Attenuates Hepatic Lipid Accumulation and Structural Damage in Gly‐Treated Mice

HE staining of liver tissue sections revealed that mice with HFD displayed liver cell changes resembling non‐alcoholic fatty liver disease (Figure 2f). The HFD group exhibited liver cell swelling, fatty degeneration, lipid droplets, and fat vacuoles in the cytoplasm as well as disordered cell arrangement and nuclei displacement. These pathological changes were alleviated in the TRF intervention group, and the most significant improvement was observed in the (nTRF)HFD + Gly group. These observations were supported by Oil red O staining, which showed red‐stained substances and large lipid droplets in liver and renal cells of the HFD group (Figure 2g,h). Conversely, the other three groups demonstrated reduced hepatocyte steatosis and lipid droplet numbers as well as lighter and smaller droplets. The (nTRF)HFD + Gly group exhibited the most notable improvement.

3.4. TRF Attenuates Renal Structural Damage and Dysfunction in Gly‐Treated Mice

HE staining of kidneys in each group revealed pathological changes to varying degrees (Figure 2i). In the HFD + Gly group, glomeruli were damaged and deformed along with inflammatory cell infiltration. Some glomeruli exhibited mesangial and endothelial cell proliferation, unclear capillary loops, and surrounding renal interstitial congestion. Additionally, renal tubular epithelial cells were edematous and degenerated, with instances of cell necrosis and detachment. The cytoplasmic staining was lighter, nuclei were loosely arranged, and casts and exudates were visible in the lumen, predominantly in the proximal tubules. These pathological changes in the (dTRF)HFD + Gly and (nTRF)HFD + Gly groups demonstrated significant improvement, with a decreasing trend in the severity of renal tubular epithelial cell injury. Compared with the HFD + Gly group, both TRF intervention groups showed a notable reduction in kidney organ index, suggesting that TRF attenuated Gly‐induced renal hypertrophic changes. Although the (nTRF)HFD + Gly group had a numerically lower mean organ index than the (dTRF)HFD + Gly group, no statistically significant difference was found between the two TRF regimens. Analysis of mouse serum urea nitrogen and creatinine levels corroborated with the above histological findings (Table 1).

3.5. TRF Reduces Urinary Oxalate and Calcium Ion Concentrations, and Decreases Renal Calcium Oxalate Crystal Deposition

Compared to the HFD, the 24‐h urine concentrations of oxalate, Ca, Mg, and P increased in the other three groups following Gly treatment (Table 2). No significant differences in urinary pH were observed among groups. Statistical analysis revealed significant differences in urinary Ca and oxalate salt contents between groups. The TRF intervention group exhibited lower oxalate and Ca levels compared to the HFD + Gly group. Notably, the (nTRF)HFD + Gly group demonstrated a more pronounced reduction in urinary oxalate content than the (dTRF)HFD + Gly group.

TABLE 2.

Differences in the levels of electrolytes and oxalate in urine.

Urine	Groups				p
	HFD	HFD + Gly	(dTRF)HFD + Gly	(nTRF)HFD + Gly
Oxalate (μg/mL)	51.56 ± 10.72 #	149.09 ± 8.42 ^	102.3 ± 9.55 # , ^	68.15 ± 3.12 #	< 0.001
Ca (mmol/L)	0.64 ± 0.02 # , ^	1.72 ± 0.10 ^	1.15 ± 0.08 # , ^	1.17 ± 0.15 #	< 0.001
Mg (mmol/L)	2.72 ± 0.15 ^	2.84 ± 0.02	2.80 ± 0.06	2.88 ± 0.03	0.179
P (mmol/L)	17.43 ± 5.60 ^	20.90 ± 4.40	24.03 ± 0.19	24.33 ± 0.95	0.141
pH	6.1 ± 0.10	6.03 ± 0.06	6.00 ± 0.00	6.00 ± 0.00	0.193

Note: Data are presented as the mean ± SEM. One‐way ANOVA analysis followed by Tukey post hoc multi‐comparison test was used.

^# p < 0.05, compared with HFD + Gly.

^{^} p < 0.05, compared with (nTRF)HFD + Gly.

Nuclear fast red staining revealed a high number of large renal calcium oxalate crystals in the HFD + Gly model group (Figure 3a,b). Conversely, the (dTRF)HFD + Gly and the (nTRF)HFD + Gly groups both exhibited significantly lower crystal formation; no significant difference was detected between the two TRF regimens. Interestingly, no calcium oxalate crystal deposition was detected in the kidneys of the HFD group.

FIGURE 3.

Time‐restricted feeding reduces calcium oxalate crystal deposition in the kidneys. (a) Nuclear Fast Red staining of kidney tissues and deposition of calcium oxalate crystals (white). Scale bars indicate 100 and 200 μm. (b) Stone area in the whole kidney section. (c) Western blot detection of CD44 and OPN protein expression. (d and e) Quantification of crystal adhesion protein CD44 and OPN expression in the kidney (^# p < 0.05, compared with HFD + Gly, ^p < 0.05, compared with (nTRF)HFD + Gly). Data are presented as mean ± standard deviation. Comparisons between multiple groups were performed using one‐way ANOVA followed by Bonferroni post hoc test in b, d. ***p < 0.001. ^# p < 0.05, compared with HFD + Gly. ^p < 0.05, compared with (nTRF)HFD + Gly.

3.6. TRF Reduces Expressions of Crystal Adhesion‐Related Genes OPN and CD44

Western blot revealed a significant increase in osteopontin (OPN) and CD44 expressions after Gly administration in the HFD group (Figure 3c). TRF pretreatment resulted in a notable decrease in renal OPN and CD44 levels, showing significant differences from the HFD + Gly group (Figure 3d,e). IHC experiments supported these results and demonstrated intense staining in the renal tubules of the HFD + Gly group, while positive staining was significantly reduced after TRF intervention (Figure 4). Notably, the (nTRF)HFD + Gly group exhibited the least amount of staining in the renal tubules.

FIGURE 4.

Time‐restricted eating partial reversal of NR1D1 and reduces inflammatory response expression in the kidney. Scale bars indicate 50 μm. (Immunohistochemistry, 100×).

3.7. TRF Improves Redox Imbalance in Kidneys After Gly Intervention

A DHE fluorescent probe was employed to quantify ROS levels in mouse kidneys. The red‐stained areas covered the entire kidneys in the HFD + Gly group but decreased in a sequential manner in the (dTRF)HFD + Gly and the (nTRF)HFD + Gly groups (Figure 5a,b). The HFD group without Gly intervention showed the lowest ROS levels among all groups, which is consistent with the absence of an acute oxidative insult.

FIGURE 5.

Time‐restricted feeding ameliorates the imbalance of the redox system in the kidney and renal inflammatory response. (a, b) Detection of renal reactive oxygen species (ROS) content by DHE fluorescent staining. Scale bars indicate 1000 μm. (c–e) Quantification of lipid peroxidation metabolites, including malondialdehyde (MDA), as well as the antioxidants superoxide dismutase (SOD) and glutathione (GSH). (f) The volcano map of High‐throughput sequencing of kidney tissue (Blue dots represent down‐regulated genes, red dots represent up‐regulated genes, and gray dots represent undifferentiated genes) (HFD vs. HFD + Gly). (g) Bubble chart for KEGG enrichment analysis. (h) Western blot detection of key protein expression in the PI3K‐AKT pathway. (i–m) Quantification of NR1D1 and key protein expression and inflammatory factor expression in the PI3K‐AKT pathway in the kidney by immunohistoblotting. Data are presented as mean ± standard deviation. Comparisons between multiple groups were performed using one‐way ANOVA followed by Bonferroni post hoc test in b, c, g. (*p < 0.05, **p < 0.01, ***p < 0.001). ^# p < 0.05, compared with HFD + Gly. ^p < 0.05, compared with (nTRF)HFD + Gly.

To assess renal oxidative stress, we measured MDA (malondialdehyde, the end product of lipid peroxidation that reflects the severity of oxidative injury), SOD (superoxide dismutase, a vital endogenous antioxidant enzyme), and GSH (glutathione, a predominant non‐enzymatic antioxidant maintaining intracellular redox homeostasis). Compared with the HFD + Gly group, TRF‐pretreated mice exhibited significantly lower renal MDA levels and higher GSH content (Figure 5c–e). No significant differences in these oxidative stress markers were observed between the dTRF and nTRF groups. Renal SOD expression showed a similar trend across groups, but the differences did not reach statistical significance.

3.8. TRF Partially Rescues Expression of Circadian Gene NR1D1

NR1D1 (nuclear receptor subfamily 1 group D member 1) is a core circadian clock gene that regulates metabolic and inflammatory pathways; increased NR1D1 expression is generally associated with restoration of circadian rhythm and anti‐inflammatory effects. Western blot and IHC analysis on mouse kidney tissues revealed high renal expression of NR1D1 in the HFD group, with renal tubules stained dark brown (Figures 4 and 5f,g). Conversely, the HFD + Gly group showed the lowest NR1D1 protein expression, with sections stained light yellow. TRF pretreatment increased NR1D1 expression compared with the HFD + Gly group, and notably, the (nTRF)HFD + Gly group exhibited significantly higher NR1D1 levels than the (dTRF)HFD + Gly group.

3.9. TRF Reduces Expression of PI3K‐AKT Pathway

Transcriptome sequencing of mouse kidneys identified a multitude of differentially expressed genes (DEGs), predominantly up‐regulated, in the Gly‐treated mice compared to the HFD group (Figure 5h). KEGG enrichment analysis revealed that DEGs were significantly enriched in biological processes including inflammatory response, autophagy, and growth factor/hormone signaling. Among these, the phosphatidylinositol 3‐kinase (PI3K)/protein kinase B (AKT) and mitogen‐activated protein kinase (MAPK) pathways were the most significantly enriched (Figure 5i). Western blot indicated significantly elevated renal levels of inflammatory TNF‐α and IL‐6 in the HFD + Gly group in comparison to the HFD group (Figure 5j,k). Notably, TRF intervention resulted in a marked reduction in renal TNF‐α and IL‐6 expressions. Furthermore, key proteins in the PI3K‐AKT pathway were analyzed. The expression patterns of p‐PI3K/PI3K and p‐AKT/AKT proteins were correlated with the trends observed in the inflammatory factors mentioned earlier (Figure 5l,m). IHC of kidney tissue sections visually confirmed the distinctions among the experimental groups (Figure 4).

4. Discussion

TRF in mice resulted in slower weight gain compared to the mice treated with Ad. The (nTFR)HFD + Gly group exhibited even slower weight gain than in the (dTFR)HFD + Gly group. Furthermore, TRF improved blood lipid metabolism disorders (HDL, LDL), reduced lipid deposition and pathological damage in the liver and kidneys, and protected renal function by lowering serum creatinine and urea nitrogen levels. TRF also led to a decrease in oxalate and calcium ion concentrations in urine, and a significant reduction in the expressions of renal crystal adhesion proteins (OPN, CD44) and calcium oxalate crystal deposition. These effects were more pronounced in the (nTFR)HFD + Gly group. Additionally, TRF intervention partially reset the renal biological clock through the modulation of NR1D1 expression and reduced the overexpression of key proteins in the inflammatory response pathway PI3K‐AKT, potentially contributing to the reduction in stone formation.

Although there is no study on the impact of TRF on kidney stones, TRF shows promise in preventing and improving various metabolic diseases, such as diabetes, hypertension, hyperlipidemia, and cardiovascular diseases [9, 15]. Previous research has established a link between these diseases and renal health. TRF is gaining attention from clinicians and researchers as a potentially effective preventive intervention against kidney stone formation. Clinical studies on TRF in patients with metabolic syndrome lasting 12 weeks or more demonstrate that TRF decreases not only body weight, waist circumference, body fat and visceral fat, but also blood pressure, blood lipid and sugar levels. Additionally, TRF reduces insulin resistance and uric acid levels, and enhances cardiometabolic health, leading to a decreased need for medications such as statins, insulin, and antihypertensive drugs [16, 17, 18]. TRF demonstrates sustained advantages, particularly in the context of improving metabolic disorders, while exhibiting minimal adverse effects, which may include minor issues such as fatigue, dizziness, and gastrointestinal reactions [19]. However, it should be noted that most of these clinical studies combined TRF with caloric restriction, either intentionally or unintentionally. Therefore, the observed metabolic benefits cannot be solely attributed to TRF alone. This design heterogeneity complicates the precise attribution of clinical outcomes to TRF‐specific mechanisms. Notably, we found that TRF influences metabolic efficiency and substrate utilization without relying on caloric reduction. The extended fasting periods characteristic of TRF promote the utilization of stored fats as energy sources and enhance lipid oxidation, thereby reducing fat accumulation despite equivalent caloric intake. Additionally, TRF aligns feeding times with the body's natural circadian rhythms, optimizing energy metabolism by mitigating mitochondrial damage and reducing metabolic inefficiencies. Overall, TRF effectively addresses multiple risk factors for kidney stones and may influence the mechanisms of kidney stone formation through various pathways, rather than through caloric intake limitation. TRF is considered a safe intervention with promising clinical outcomes.

Our study demonstrates that TRF can enhance lipid metabolism disorders in mice and potentially plays a crucial role in kidney stone prevention. Studies have demonstrated that free fatty acids (FFAs) can induce renal tubular lipotoxicity under high‐fat dietary conditions. A HFD elevates circulating FFAs, such as palmitic acid, which activates the TLR4/NF‐κB signaling pathway in renal tubular cells, thereby upregulating the expression of oxalate transporters, including SLC26A6. This process results in an increased urinary excretion of oxalate [20]. Additionally, elevated LDL levels facilitate the deposition of cholesterol crystals in the renal interstitium, leading to local inflammation and oxidative stress, which compromise the urothelial barrier and promote the accumulation of calcium oxalate crystals [21]. Conversely, TRF intervention has been shown to reduce lipolysis and lower serum LDL levels, thereby mitigating the risk of kidney damage and stone formation. Numerous studies have indicated that TRF enhances the activity and mitochondrial density of hepatic cells, increases the expression of hepatic lipase (LIPC), and elevates lipase products in the liver of mice, while simultaneously decreasing body weight, hepatic fat deposition, and degeneration. Moreover, TRF resulted in increased levels of β‐hydroxybutyrate, and down‐regulated the expression of liver lipid‐related synthesis genes [22]. Additionally, TRF activated brown adipose tissues in mice, boosted lipid metabolism activity and reduced white fat accumulation [23]. Overall, TRF decreased lipogenesis by extending fasting periods and enhanced lipid metabolism activity, utilized fatty acids as energy sources and promoted fat storage consumption. Consequently, TRF effectively addressed high‐fat conditions in the body and mitigated the adverse effects of elevated blood lipids, thus reducing the risk of kidney stone formation.

In this study, despite significant weight differences between TRF‐pretreated and ad libitum‐fed mice, serum leptin and adiponectin levels did not change significantly. This finding is consistent with meta‐analytic evidence showing that fasting regimens significantly reduce leptin but have only marginal or non‐significant effects on adiponectin, with substantial heterogeneity across studies [24, 25]. Several factors explain this observation. First, the 5‐week TRF duration primarily slowed fat accumulation rather than inducing substantial fat mass loss, and significant adipokine changes typically require longer interventions. Second, TRF's main benefit lies in restoring circadian rhythmicity of adipokine secretion rather than altering average 24‐h levels [26]. Third, leptin is secreted in a pulsatile pattern, and TRF entrains leptin oscillations [27]. Our single‐time‐point sampling cannot capture these dynamics. Moreover, adiponectin is inherently less responsive to short‐term dietary interventions. Thus, the absence of significant adipokine changes does not negate the metabolic benefits of TRF, but rather reflects the complexity and timing‐dependence of adipokine regulation.

As reported, dietary exposure is a crucial factor in preventing kidney stones and influences kidney stone formation from various aspects, including urine osmotic pressure, composition, and pH [28, 29]. The 24‐h water intake of animals was not affected by TRF compared to the Ad, which aligns with other studies. However, in a 7‐week animal study, the TRF HFD group (8 h) took in more water compared to the HFD group. This difference can be attributed to increased physical activity and respiratory exchange rate in the TRF group. It is indicated higher metabolic efficiency necessitates more water intake to meet body demands and reduce urine saturation [30]. Despite some debate regarding the influence of TRF on water intake, no study suggests that TRF significantly reduces water consumption to raise the risk of kidney stone formation. In the Gly model group, TRF significantly reduced urinary oxalate and Ca excretion compared to the Ad A study involving 15 health examination cases revealed that even with an 18‐h fasting intervention, TRF led to slower renal urinary flow rate and significant reductions in urinary Na⁺ and Ca²⁺ excretion rates and concentrations. Phosphate, citrate, and magnesium concentrations were not significantly impacted. The risk of CaHPO₄ precipitation did not increase, which is possibly due to the increased ion reabsorption from RAAS system activation [31]. Furthermore, our study showed TRF notably enhanced renal pathological damage and function (serum creatinine, urea nitrogen), potentially affecting urine electrolyte excretion. These findings suggest TRF does not decrease water intake, electrolyte excretion, or main urine stone components in mice, and may even offer some benefits in kidney stone prevention. However, more direct research is needed to confirm the impact of TRF on kidney stone formation via urine components.

Previous studies have demonstrated that oxidative stress and inflammatory responses play a significant role in the formation of kidney stones, with these two factors interacting to jointly promote their occurrence [32, 33, 34]. In our study, following Gly intervention, we observed an imbalance between oxidative and antioxidant activities, evidenced by increased ROS content, elevated MDA concentrations, and decreased GSH levels, alongside heightened expression of inflammatory factors (TNF‐α, IL‐6) and key proteins in the PI3K/AKT and MAPK pathways. Mechanistically, our transcriptome sequencing data identified the PI3K/AKT and MAPK pathways as the most significantly enriched signaling hubs in Gly‐induced renal injury. These pathways are well‐established central regulators of renal inflammation, oxidative stress, and apoptosis—all core pathological processes driving calcium oxalate crystal‐induced tubular damage and stone formation [1, 14]. In mice subjected to TRF intervention, this heightened state of oxidative stress and inflammation was partially rectified, as evidenced by reduced ROS accumulation, restored antioxidant capacity, and downregulated phosphorylation of PI3K and AKT. Supporting our findings, prior research has indicated that dietary modifications, regardless of whether high‐fat or normal diets are administered, can reduce extensive macrophage infiltration and the expression of pro‐inflammatory genes (NF‐κB, TNF‐α, IL‐6, and CXCL2) in white adipose tissue, with similar trends noted in the liver and jejunum [6, 17]. Additionally, studies involving diabetic rat models have demonstrated that a 7‐day TRF regimen (12 h) significantly down‐regulates the elevation of renal inflammatory factors (TNF‐α, NLRP‐3, TGF‐β1, and VCAM‐1) and renal apoptosis induced by a high‐glucose environment, while also reducing apoptosis levels (CASP‐9 and CASP‐3) and enhancing kidney function (serum creatinine and urea nitrogen) [30]. Furthermore, TRF inhibits the positive feedback loop between lens retention and inflammation. HFDs induce mitochondrial fission (via DRP1 activation) and damage to the electron transport chain, leading to tubular ROS accumulation [9]. TRF improves mitochondrial function by activating autophagy‐mitochondrial quality control mechanisms (such as the Parkin/PINK1 pathway) through prolonged fasting. Additionally, calcium oxalate crystal retention further upregulates OPN/CD44 expression by activating the NLRP3 inflammasome, which induces macrophages to polarize toward the pro‐inflammatory M1 type, resulting in the release of IL‐1β and TNF‐α [35]. In this study, TRF decreased the levels of TNF‐α and IL‐6, which may disrupt this cycle by inhibiting the PI3K/AKT‐mediated NLRP3 pathway activation. Consequently, managing oxidative stress and inflammatory responses may represent a promising strategy for the prevention and treatment of kidney stones.

Abnormal circadian rhythms not only affect kidney structure and function by disrupting metabolic balance and inflammatory responses, but also are linked with several risk factors for kidney stones, including diabetes, cardiovascular diseases, inflammation, and sleep disorders [21]. Individuals with chronic kidney damage often exhibit abnormal renal expressions of circadian clock genes (e.g., Bmal1, Per1, and NR1D1), leading to increased local and systemic inflammatory responses and infiltration of inflammatory cells, exacerbating kidney damage [36, 37]. The circadian rhythm, regulated by the expressions of circadian clock genes, impacts nearly all daily physiological processes in the body. Circadian oscillations occur in more than 13% of the gene transcriptome in the kidneys, as well as renal plasma flow, renal function, and urinary electrolyte excretion [38, 39]. Therefore, maintaining a stable biological rhythm is crucial for kidney health and kidney stone prevention. We found renal NR1D1 expression in mice significantly decreased after Gly intervention. Furthermore, Gly intervention increased NR1D1 expression when subjected to TRF, and a more pronounced effect was seen in the (nTFR)HFD + Gly group. This result indicates a association between kidney stone formation and disruptions in biological rhythms. TRF can partially restore biological rhythms, especially when synchronized with the natural work and rest cycle of mice. The study also showed the positive effects of TRF intervention on various experimental outcomes, such as body weight, lipid metabolism, urinary excretion, inflammatory oxidative stress, and kidney stone formation [35, 40, 41]. Unhealthy diet or eating patterns can disrupt the circadian expressions of metabolic factors and lead to metabolic disorders. HFD disrupted the rhythmic expression of metabolic genes and subsequent obesity in mice [42]. However, TRF can restore the expressions of circadian clock genes (e.g., Clock, cry1, Per1, Per2, Per3, Cry2, Bmal1, Rorα, and Rev‐erbα), resulting in reshaped circadian oscillations [26, 43]. An 8‐week TRF (12 h) intervention study showed that dietary changes partially reversed abnormal oscillations of renal clock genes with chronic kidney disease. This intervention also improved immune‐inflammatory response and fatty acid oxidation, reduced renal fibrosis, and repaired damaged kidneys, ultimately enhancing renal function (decreased eGFR and increased urea nitrogen level). Transcriptome data showed TRF may protect the kidneys by inhibiting renal cell cycle arrest [36]. Aligning eating‐fasting time windows with the natural physical rhythms is crucial (e.g., sleep and activity), as disrupting these inherent rhythms may not yield the same benefits as aligning with them over a short period. While dTRF improved body weight and metabolic activity compared to Ad, the benefits were even greater with nTRF [44, 45]. Additionally, the disruption of circadian rhythm can lead to abnormal circulating lipids, which indirectly contributes to renal tubular lipotoxicity. TRF may synergistically enhance renal metabolism by restoring hepatic NR1D1 rhythm [36]. The study indicates that SLC26A6, an oxalate transporter, is directly regulated by BMAL1/Clock, with its expression peaking during the active phase (night in mice), thereby synchronizing with the rhythm of urinary oxalate excretion. TRF appears to inhibit the overexpression of SLC26A6, potentially by strengthening the BMAL1‐NR1D1 axis [38]. However, the long‐term effects of TRF on full adaptation to environmental changes, and whether the benefits of the intervention outweigh the impact of the specific TRF time window are still unclear. Some existing evidence suggests aligning the TRF time window with the biological rhythms of a species may have greater benefits in reshaping biological rhythms, reducing inflammatory reactions, improving glucose and lipid metabolism, and preventing kidney stones.

This study presents novel findings on the impact of TRF on lipid metabolism and the formation of renal calcium oxalate stones in HFD mice, and initially explores the underlying mechanisms. However, several limitations should be acknowledged. First, regarding experimental design, this study did not include a TRF‐only control group (HFD + TRF without Gly), preventing precise quantification of TRF's relative contributions to improving metabolic dysfunction versus directly protecting against renal injury. Second, the TRF intervention duration was relatively short. Long‐term systemic metabolic changes and the persistence of TRF's beneficial effects after discontinuation were not evaluated. Third, this study only confirmed the preventive effect of TRF against kidney stone formation. Its therapeutic potential for established stones remains to be investigated to fully assess clinical translational value. Finally, the relatively small sample size (inherent to the exploratory nature of this study) and the absence of quantitative behavioral assays should be noted. Future studies addressing these limitations will further validate and extend our findings.

5. Conclusions

TRF, as a preventive dietary intervention, improves lipid metabolism and prevents renal calcium oxalate stone formation in HFD‐fed mice independent of caloric restriction, with nighttime TRF showing greater preventive benefits. These effects are associated with reduced urinary stone‐forming ions, attenuated oxidative stress and inflammation, and restored circadian gene expression. Our findings establish TRF as a promising non‐pharmacological preventive strategy for metabolic kidney stones, offering a simple, safe, and easily implementable approach for high‐risk populations such as those with obesity and metabolic syndrome, and potentially reducing the global healthcare burden of this disease. Future research should explore its long‐term preventive effects, therapeutic potential for existing stones, and underlying molecular mechanisms.

Author Contributions

Yunfei Xiao: conceptualization, methodology, software, formal analysis, investigation, data curation, writing – original draft, writing – review and editing, visualization. Jiahao Wang: investigation, data curation, writing – review and editing, visualization. Jianwei Cui: investigation, data curation, writing – review and editing, visualization. Shan Yin: methodology, data curation, visualization, writing – review and editing. Yaqing Yang: methodology, data curation, visualization, writing – review and editing. Yunjin Bai: conceptualization, methodology, supervision, project administration, writing – review and editing. Jia Wang: funding acquisition, supervision, investigation, methodology, resources, writing – review and editing, visualization.

Funding

This work was supported by the Key Research and Development Projects of Sichuan Science and Technology Department (grant number: 2022YFS0306).

Ethics Statement

All animal procedures were ethically approved by Laboratory Animal Ethics Committee of West China Hospital, Sichuan University (20230731005), and adhered to the Guide for Care and Use of Laboratory Animals.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Figure S1: Approval certificate for animal experiments from the ethics committee.

Figure S2: Full unmodified Western blot images showing all target protein bands.

Dataset S1: Complete raw dataset with all experimental measurement results.

Data Availability Statement

The original contributions presented in the study are included in the article/[Link], [Link], [Link], and further inquiries can be directed to the corresponding author.