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. 2025 Feb 28;16(4):731–748. doi: 10.1007/s13300-025-01708-9

Evaluation of the Regulatory Effect of the Pan-PPAR Agonist Chiglitazar on the Dawn Phenomenon

Wenxuan Li 1,✉, Yangang Wang 1, Chuanfeng Liu 1, Yongzhuo Yu 1, Lili Xu 1, Bingzi Dong 1
PMCID: PMC11926308  PMID: 40016574

Abstract

Introduction

The dawn phenomenon (DP), characterized by early morning hyperglycemia, poses a significant challenge in diabetes management and is associated with increased glycemic variability and long-term complications. Despite its clinical impact, effective therapeutic strategies remain limited. Chiglitazar, a novel pan-PPAR agonist, has demonstrated benefits in improving lipid metabolism and insulin sensitivity, but its potential role in mitigating DP remains unexplored. This study evaluates the regulatory effect of chiglitazar on DP and investigates its possible mechanisms beyond lipid modulation.

Methods

This retrospective observational study included 22 hospitalized diabetic patients who received chiglitazar (20 mg). Blood glucose levels at 3:00 a.m. and fasting glucose levels over three consecutive days were measured pre- and post-treatment, and the dawn phenomenon intensity was calculated. Lipid profiles were assessed to explore potential correlations with glucose changes.

Results

Following chiglitazar administration, significant reductions were observed in LDL-C (43.82 ± 18.27 vs. 36.97 ± 16.90, p < 0.05), FFA (6.00 ± 2.38 vs. 5.06 ± 1.77, p < 0.05), mean 3:00 a.m. blood glucose (Z = – 2.03, p < 0.05), and fasting blood glucose (Z = – 2.96, p < 0.05). DP intensity also significantly improved (Z = – 3.48, p < 0.01). However, no significant correlation was found between glucose improvements and lipid profile changes (p > 0.05), suggesting an alternative mechanism of action.

Conclusions

Chiglitazar effectively reduces DP intensity and improves glycemic control, independent of its effects on lipid metabolism. These findings suggest a potential link between chiglitazar’s mechanism and circadian rhythm regulation, possibly through the modulation of REV-ERB nuclear receptors. Further research is needed to confirm this hypothesis and evaluate the long-term clinical benefits of chiglitazar in diabetes management.

Keywords: Diabetes, Dawn phenomenon, PPARs, SCN, REV-ERBs

Key Summary Points

Why carry out this study?
The dawn phenomenon, characterized by early morning hyperglycemia, poses significant challenges in diabetes management and increases the risk of complications. There is an unmet need for effective therapeutic strategies to address this issue.
Chiglitazar, a novel pan-PPAR agonist, has demonstrated potential benefits in improving lipid metabolism and glucose control, but its role in mitigating the dawn phenomenon intensity remains underexplored.
This study hypothesized that chiglitazar could alleviate the dawn phenomenon intensity in diabetic patients by improving glucose metabolism, potentially through mechanisms independent of lipid profile modulation.
What was learned from the study?
Chiglitazar significantly improved the dawn phenomenon intensity, reducing fasting blood glucose levels, 3:00 a.m. glucose levels, and dawn phenomenon intensity. Lipid profile indicators, such as LDL-C and FFA, also showed significant improvement post-treatment.
No significant correlation was found between the improvements in dawn phenomenon intensity and changes in lipid profiles, suggesting that the glucose-regulating effects may involve alternative mechanisms, possibly related to the regulation of circadian rhythm genes.
The findings indicate that chiglitazar offers a promising therapeutic option for addressing the dawn phenomenon intensity in diabetes, particularly for patients with unstable morning glucose control.
While the exact mechanism remains unclear, the study highlights a potential link between chiglitazar’s effects and circadian rhythm regulation, offering new avenues for research and therapeutic development in diabetes care.
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Introduction

Diabetes mellitus (DM) is a highly prevalent and complex chronic disease worldwide. With the rise of unhealthy dietary habits, sedentary lifestyles, and reduced physical activity, the incidence of diabetes has rapidly increased. According to a survey by the International Diabetes Federation, the incidence rate among young individuals in the United States has been growing at an annual rate of 7.1% [1]. DM and its associated complications are significant contributors to human mortality. Therefore, maintaining stable and normalized blood glucose levels and preventing or reducing complications are key therapeutic goals in DM management. However, recent clinical observations have noted a marked increase in the frequency of the dawn phenomenon (DP) among diabetic patients, adding to patients’ psychological burden and posing challenges for clinical blood glucose management.

The term “dawn phenomenon (DP)” was introduced over 30 years ago to describe a rise in blood glucose from the nocturnal nadir to early morning in patients with type 1 diabetes (T1DM) [2, 3]. Later, this phenomenon was also observed in type 2 diabetes (T2DM) [4]. The presence of DP not only influences choices, dosages, and timing of oral hypoglycemic agents or insulin during the night but also complicates clinical blood glucose management, intensifying blood glucose fluctuations and raising the risk of diabetic complications. Although the exact mechanism of DP remains unclear, existing research suggests it is associated with biological clock disruption and an increase in counter-regulatory hormones [3, 5–9].

Peroxisome proliferator-activated receptors (PPARs) are a group of ligand-activated nuclear hormone receptor proteins that belong to the nuclear receptor superfamily. Currently, three PPAR subtypes have been identified: PPAR-α, PPAR-δ, and PPAR-γ [10–12]. Extensive research has shown that PPARs can regulate gene transcription and expression, thereby improving glucose and lipid metabolism, insulin resistance, and inflammatory responses [13]. Currently, single-receptor agonists targeting PPARs, such as pioglitazone, are widely used in clinical practice to improve blood glucose and insulin sensitivity. However, side effects such as sodium and water retention and congestive heart failure limit their long-term and extensive use in diabetes treatment [14, 15]. The pan-PPAR agonist chiglitazar activates all three PPAR subtypes simultaneously, leveraging their overlapping or distinct biological activities [16, 17]. This approach aims to enhance insulin sensitivity and blood glucose control while minimizing adverse effects [18–20]. Its efficacy and safety have been validated in phase I, II, and III clinical trials, demonstrating blood glucose control and improved insulin sensitivity comparable to other drugs but with fewer adverse events [21–24]. As a result, since 2021, chiglitazar has been approved in China for clinical use in blood glucose control.

In our clinical practice, we observed that certain diabetic patients experience significant clinical benefits from using chiglitazar, showing more stable blood glucose control and a noticeable improvement in the occurrence of the dawn phenomenon. To further investigate whether chiglitazar helps mitigate the dawn phenomenon in diabetic patients, we conducted this study. To quantify the dawn phenomenon intensity, we defined it as the difference between fasting blood glucose upon waking and the nocturnal nadir (between 0:00 and 6:00 a.m., often measured at 3:00 a.m.). An increase in fasting blood glucose exceeding 10 mg/dl upon waking was considered indicative of the dawn phenomenon [25]. In this study, patients served as their own controls, with data collected both pre- and post-treatment. Measurements included blood glucose at 3:00 a.m. and fasting blood glucose over three consecutive days, as well as changes in lipid profile indicators before and after treatment. This approach allowed us to assess changes in the dawn phenomenon intensity before and after chiglitazar administration and to explore possible mechanisms underlying these changes.

Methods

Study Design and Participants

This observational clinical study was conducted at the Affiliated Hospital of Qingdao University and received ethical approval from the hospital’s ethics committee (No: QYFYWZLL29393). The study adhered to the principles of Good Clinical Practice, the Declaration of Helsinki, and relevant Chinese regulations. All patients selected for this observational study signed written informed consent forms. Data were collected by specialized medical staff and maintained in strict confidentiality, with no disclosure or misuse beyond the scope of this study.

Inclusion criteria: (1) Age between 18 and 70 years; (2) body mass index (BMI) between 18.5 and 35.0 kg/m2; (3) poor blood glucose control, with glycated hemoglobin (HbA1c) levels between 7.5 and 10% despite strict dietary and exercise therapy.

Exclusion criteria: (1) History of acute or chronic diabetic complications such as diabetic ketoacidosis, hyperosmolar hyperglycemic syndrome, retinopathy, or diabetic nephropathy; (2) presence of resistant hypertension requiring four or more medications for control; (3) triglyceride (TG) levels > 500 mg/dl; (4) use of fibrates or other glucose-modifying medications (including corticosteroids, steroids, and receptor blockers); (5) history of transient ischemic attack, cerebrovascular accident, or unstable angina within 6 months prior to screening; (6) presence of pancreatic or hepatic diseases, such as cirrhosis, active hepatitis, or impaired renal function (eGFR < 60 ml/min/1.73 m2); (7) diagnosis of malignant tumors or other severe diseases within the past 5 years at the time of screening.

This study was conducted in a hospital setting, with all participants hospitalized throughout the observation period. To minimize dietary influence on metabolic parameters, all patients received standardized meals designed according to diabetes-specific dietary guidelines. The type and quantity of food provided were identical for each participant, ensuring consistency in macronutrient intake. This controlled dietary regimen helped to reduce the potential confounding effects of diet on lipid metabolism and glucose variability. A total of 22 patients met the inclusion criteria after screening. All participants had suboptimal blood glucose control, with glycated hemoglobin levels ranging from 7.4 to 11.2%, and none had previously used chiglitazar. Each participant (N = 22) served as their own control in a before-and-after study design. After initial inclusion, individualized glucose-lowering regimens were developed based on each participant’s blood glucose levels and prior medication, incorporating oral hypoglycemic agents and insulin as needed. Prior to chiglitazar administration, a single fasting serum sample was collected in the early morning. Over the next 3 days, daily blood samples and clinical variables were collected. On day 4, chiglitazar (20 mg) was added to the regimen, with daily blood samples and clinical variables collected for three additional days. On the morning following the final dose, another fasting serum sample was collected. The study lasted for 7 days, with all 22 participants completing the study.

In this study, all interventions were tailored based on patients’ prior glycemic levels, medication history, and individual clinical needs. The addition of chiglitazar (20 mg) was part of routine clinical treatment, aimed primarily at optimizing glycemic management rather than being established solely for research purposes. Patients not participating in this study but meeting the relevant clinical indications could also receive similar treatment. This study solely observed and recorded the effects of this medication in a specific patient population, without altering its standard clinical application.

Serum Profile Measurement

Before the start of chiglitazar administration, all patients underwent comprehensive measurement of triglycerides (TG), cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), free fatty acids (FFA), and HbA1c. HbA1c was measured using high-performance liquid chromatography (HPLC) (Bio-Rad Laboratories, Inc.). Following the final dose of chiglitazar, TG, TC, LDL, HDL, and FFA were measured again on the morning of the next day. All samples were transported to the central laboratory under a cold chain system and processed within 2–4 h. HbA1c was analyzed using HPLC (Bio-Rad Variant II HbA1c Analyzer; Bio-Rad), and lipid profiles were measured using the Beckman Coulter AU 680 analyzer (Krefeld).

Overview of Dawn Phenomenon Intensity Changes

As described earlier, we defined the dawn phenomenon intensity as the difference between fasting blood glucose (FBG) upon waking and the nocturnal nadir (typically the 3:00 a.m. blood glucose level, measured between 0:00 and 6:00 a.m.) [25]. After patients were enrolled and began the study medication, their 3:00 a.m. blood glucose and FBG were measured using a fingertip glucose meter for three consecutive days before chiglitazar administration. On the fourth day, chiglitazar was added, and the same method was used to measure 3:00 a.m. blood glucose and FBG for three additional days post-treatment. To minimize analytical error, hypoglycemic values (blood glucose < 70 mg/dl) were excluded, and each participant’s average 3:00 a.m. blood glucose, FBG, and dawn phenomenon intensity were used for analysis.

Throughout the trial, each patient received dietary and exercise counseling in accordance with local guidelines. Participants were asked to eat three meals at consistent times and to record any hypoglycemic events (blood glucose < 70 mg/dl) or other abnormalities.

Statistical Analysis

Data were analyzed using the SPSS statistical software package, version 29 (IBM SPSS version 29.0; International Business Machines Corporation, Armonk, NY, USA). The Shapiro–Wilk test was used to assess the distribution of the data. For normally distributed continuous variables, results were expressed as mean ± SEM, while non-normally distributed variables were presented as median (interquartile range). Paired t tests and Wilcoxon signed-rank tests were used for comparing continuous variables, and the chi-square (χ2) test was applied for categorical variables. Pearson and Spearman correlation analyses were conducted to examine the relationships between changes in dawn phenomenon intensity, the presence of the dawn phenomenon, and serum profile changes. All p values were two-tailed, with a significance level set at 5%.

Results

Baseline Characteristics

A total of 22 patients participated in this study, with baseline results presented in Table 1. The gender ratio of participants was 1:1, with an average age of 63 years. The median diabetes duration was 9.5 years (5.0–15.0 years), and 63.64% of patients had hypertension, 54.55% had dyslipidemia, and 22.73% had cardiovascular disease. These baseline characteristics were considered when interpreting the study results. The average HbA1c level was 8.84%. The pre-treatment average 3:00 a.m. blood glucose level was 164.63 mg/dl, and the average fasting blood glucose (FBG) level was 186.14 mg/dl.

Table 1.

Baseline characteristics of study patients

Numbers of patients (N) 22
Female N (%) 11 (50.00)
Age (years) 63.00(60.00–71.00)
Height (cm) 167.64 ± 7.93
Weight (kg) 77.11 ± 13.41
Diabetes course (years) 9.5 (5–15)
HbA1c (%) 8.84 ± 1.07
BMI (kg m2) 26.25 (23.50–30.43)
Hypertension N (%) 14 (63.64%)
Dyslipidemia N (%) 12 (54.55%)
Cardiovascular disease N (%) 5 (22.73%)
TG (mg/dl) 24.39 (15.39–38.3)
TC (mg/dl) 79.68 ± 27.21
LDL-C (mg/dl) 43.82 ± 18.27
HDL-C (mg/dl) 21.69 (34.88–26.46)
FFA (mg/dl) 6.00 ± 2.38
Average of 3:00 a.m. blood glucose (mg/dl) 164.63 ± 27.81
Average of fasting blood glucose (mg/dl) 186.14 ± 35.51
Average of dawn phenomenon intensity (mg/dl) 9.00 (0.00–25.05)
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BMI body mass index, HbA1c glycated hemoglobin, TG triglycerides, TC total cholesterol, LDL-C low-density lipoprotein cholesterol, HDL-C high-density lipoprotein cholesterol, FFA free fatty acids

Changes in Serum Indicators and Dawn Phenomenon Intensity Post-Treatment

The pre- and post-treatment values for TG, TC, LDL-C, HDL-C, FFA, average 3:00 a.m. blood glucose, average fasting blood glucose, and dawn phenomenon intensity are shown in Table 2. Following chiglitazar treatment, significant reductions were observed in LDL-C (43.82 ± 18.27 vs. 36.97 ± 16.90, p < 0.05), FFA (6.00 ± 2.38 vs. 5.06 ± 1.77, p < 0.05), average 3:00 a.m. blood glucose (Z = − 2.03, p < 0.05), and average fasting blood glucose (Z = − 2.96, p < 0.05) compared to pre-treatment values. Additionally, dawn phenomenon intensity showed significant improvement post-treatment compared to pre-treatment levels (9.00 [0.00–25.05] vs. − 4.80 [− 12.75–2.85], p < 0.01).

Table 2.

Changes in indicators before and after chiglitazar treatment

Variables Pre-treatment (N = 22) Post-treatment (N = 22) Degrees of freedom Clinical relevance p
TG (mg/dl) 24.39 (15.39–38.3) 22.32 (16.61–32.54) Z = − 0.26 rs = 0.06 p = 0.80
TC (mg/dl) 79.68 ± 27.21 69.21 (56.21–87.35) Z = − 1.38 rs = 0.29 p = 0.17
LDL-C (mg/dl) 43.82 ± 18.27 36.97 ± 16.90 t = 9.31 Cohen’s d = 1.41 p < 0.05
HDL-C (mg/dl) 21.69 (34.88–26.46) 30.33 ± 11.20 Z = − 2.84 rs = 0.61 p < 0.05
FFA (mg/dl) 6.00 ± 2.38 5.06 ± 1.77 t = 2.84 Cohen’s d = 1.41 p < 0.05
Average of 3:00 a.m. blood glucose (mg/dl) 164.63 ± 27.81 134.10 (117.75–160.20) Z = − 2.03 rs = 0.43 p < 0.05
Average of fasting blood glucose (mg/dl) 186.14 ± 35.51 128.10 (113.70–152.85) Z =− 2.96 rs = 0.63 p < 0.05
Average of dawn phenomenon intensity (mg/dl) 9.00 (0.00–25.05) − 4.80 (− 12.75–2.85) Z = − 3.48 rs = 0.74 p < 0.01
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p < 0.05 indicates a significant difference; otherwise, no significant difference is present

rs, rank-biserial correlation

The changes in dawn phenomenon intensity pre- and post-treatment are detailed in Table 3. The chi-square (χ2) test indicated a significant difference in the presence of the dawn phenomenon intensity before and after treatment (proportion of dawn phenomenon intensity presence, pre-treatment: post-treatment = 0.455: 0.182, p = 0.015 < 0.05).

Table 3.

Presence of dawn phenomenon before and after chiglitazar treatment

Frequency Percentage (%) Chi-square value (χ2) OR p
Presence of dawn phenomenon before treatment Presence 10.00 45.50 5.87 3.75 p < 0.05
Absence 12.00 54.50
Presence of dawn phenomenon after treatment Presence 4.00 18.20
Absence 18.00 81.80
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p < 0.05 indicates a significant difference; otherwise, no significant difference is present

Relationship Between Blood Glucose and Lipid Profiles

Both blood glucose and lipid metabolism indicators before and after treatment were quantitative variables. Pearson correlation analysis revealed that there was no statistically significant correlation between 3:00 a.m. blood glucose or fasting blood glucose and any of the lipid indicators (TG, TC, LDL-C, HDL-C, FFA) at any time point—whether pre-treatment, post-treatment, or in the differences between pre- and post-treatment values (p > 0.05).

Correlation Between Dawn Phenomenon Intensity and Lipid Profiles

Although some lipid indicators showed significant improvement after chiglitazar treatment (see Table 2), there was no statistically significant correlation between dawn phenomenon intensity and lipid indicators—TG, TC, LDL-C, HDL-C, and FFA (p > 0.05). Additionally, the changes in dawn phenomenon intensity pre- and post-treatment showed no statistically significant correlation with changes in lipid indicators (p > 0.05). However, a significant correlation was observed between changes in dawn phenomenon intensity and changes in 3:00 a.m. blood glucose levels pre- and post-treatment (p = 0.004 < 0.05) (Table 6).

Safety and Tolerability

During the study, only one patient experienced a hypoglycemic episode (3:00 a.m. blood glucose of 50.4 mg/dl) prior to the addition of chiglitazar. After appropriate management, no further hypoglycemic episodes occurred. All other patients demonstrated good tolerance to the treatment both before and after chiglitazar administration.

Discussion

This study demonstrated that the pan-PPAR agonist chiglitazar provides significant clinical benefits in alleviating the dawn phenomenon intensity in diabetic patients (see Table 4a, b). Chiglitazar effectively reduced LDL-C and FFA levels, increased HDL-C, improved lipid metabolism, and significantly enhanced blood glucose control (see Table 2). In this study, we excluded hypoglycemic values (blood glucose < 70 mg/dl) from the analysis to prevent potential confounding effects on assessing the dawn phenomenon intensity. Nocturnal hypoglycemia can induce counter-regulatory hormone responses, leading to reactive hyperglycemia (commonly referred to as the Somogyi effect), which may artificially elevate fasting blood glucose levels. If these events were included in the analysis, it would be challenging to distinguish whether the observed improvements in the dawn phenomenon intensity were attributable to chiglitazar or were secondary to counter-regulatory mechanisms compensating for hypoglycemia. By excluding these episodes, we aimed to ensure that the reductions in fasting blood glucose and dawn phenomenon intensity observed in this study were truly reflective of chiglitazar’s effects rather than confounding influences. Nevertheless, we acknowledge that this exclusion criterion may have led to a slight underestimation of the overall variability in glucose responses. Future studies incorporating continuous glucose monitoring (CGM) could provide a more comprehensive assessment of nocturnal glucose fluctuations and further validate these findings. Additionally, chiglitazar was associated with a lower incidence of adverse events, indicating superior efficacy and safety, consistent with findings from previous studies [24, 26–28]. However, further analysis showed no correlation between changes in blood glucose indicators (3:00 a.m. blood glucose, fasting blood glucose) and lipid indicators, nor between the dawn phenomenon intensity and lipid profile changes (p > 0.05) (see Tables 2, 3, 5). This suggests that the improvement in the dawn phenomenon intensity with chiglitazar is not mediated through lipid metabolism modulation. Instead, the data indicate that chiglitazar may alleviate the abnormal dawn phenomenon intensity in diabetic patients through a more complex mechanism—potentially involving the biological clock.

Table 4.

Correlation between dawn phenomenon and lipid profiles before and after treatment

Variables Pre-treatment Post-treatment
Dawn phenomenon intensity Presence of dawn phenomenon before treatment Dawn phenomenon intensity Presence of dawn phenomenon before treatment
p p
Age (years) 0.80 0.12 0.79 0.41
Height (cm) 0.03 0.15 0.06 0.06
Weight (kg) 0.34 0.46 0.12 0.59
HbA1c 0.91 0.98 0.52 0.38
BMI (kg/m2) 0.60 0.82 0.67 0.46
TG (mg/dl) 0.59 0.52 0.55 0.68
TC (mg/dl) 0.86 0.22 0.91 0.94
LDL-C (mg/dl) 0.81 0.30 0.78 0.56
HDL-C (mg/dl) 0.79 0.46 0.77 0.41
FFA (mg/dl) 0.65 0.46 0.72 0.93
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p < 0.05 indicates a significant difference; otherwise, no significant difference is present

Table 5.

Correlation between changes in dawn phenomenon intensity and changes in various indicators before and after treatment

Variables p (two-tailed)
TG comparison pre- vs. post-treatment comparison 0.52
TC comparison pre- vs. post-treatment comparison 0.17
LDL-C comparison pre- vs. post-treatment comparison 0.48
HDL-C comparison pre- vs. post-treatment comparison 0.61
FFA comparison pre- vs. post-treatment comparison 0.22
3:00 a.m. blood glucose comparison pre- vs. post-treatment comparison < 0.05
Fasting blood glucose comparison pre- vs. post-treatment comparison 0.69
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p < 0.05 indicates a significant difference; otherwise, no significant difference is present

As lipid sensors that regulate systemic energy metabolism, PPARs belong to the nuclear receptor superfamily and have three subtypes (PPAR-α, PPAR-δ, and PPAR-γ), each with distinct primary distribution sites—for instance, PPAR-α is primarily found in the liver, while PPAR-γ is mainly located in white adipose tissue (WAT) [13]. PPARs form heterodimers by interacting with retinoid X receptors and other co-regulatory factors, such as nuclear receptor co-repressor 1, PPAR-γ coactivator 1-α (PGC1-α), or receptor-interacting protein 140 (REFS). These heterodimers then bind to PPAR response elements (PPREs) on DNA, thereby regulating the transcription and expression of target genes [29, 30]. PPAR agonists have been shown to modulate lipid synthesis, glucose metabolism, and insulin sensitivity throughout the body by controlling the transcription and expression of genes related to fatty acid transport and fatty acid oxidation (FAO) [31].

The central biological clock is located in the suprachiasmatic nucleus (SCN), with a molecular core based on a transcription-translation feedback loop (TTFL) [32]. The primary loop consists of the BMAL1 (Arntl) and CLOCK transcription factors [33, 34], which form heterodimers in the nucleus and drive the transcription of Period (PER1,2) and Cryptochrome (CRY1,2) genes [35, 36]. PERs and CRYs accumulate in the cytoplasm and, upon entering the nucleus, inhibit the BMAL1-CLOCK complex, creating rhythmic oscillations in gene expression that establish circadian rhythms [37–39]. Beyond the SCN’s core loop, studies have shown that REV-ERB-α and REV-ERB-β within the SCN mediate transcriptional repression of clock genes, inhibiting BMAL1 expression within a negative feedback loop [40, 41]. Ding et al. demonstrated in animal studies that REV-ERB-α and REV-ERB-β control circadian rhythms by modulating gene expression rhythms and oscillatory firing in the SCN, influencing glucose metabolism through these rhythmic oscillations [9]. This research, along with prior studies, suggests that the dawn phenomenon is linked to disruptions in the biological clock [42, 43]. The findings indicate significant differences in mRNA levels of REV-ERB-α and REV-ERB-β (NR1D1 and NR1D2) and BMAL1 between groups with and without the dawn phenomenon, with overexpression of these genes in the dawn phenomenon group. Therefore, we hypothesize that individuals with the dawn phenomenon may counteract metabolic disturbances caused by circadian disruptions by overexpressing NR1D1, NR1D2, and BMAL1, stabilizing glucose levels, correcting the dawn phenomenon, and maintaining homeostasis.

Considerable research has established a close link between PPARs and the SCN, indicating that PPARs can regulate circadian rhythm and systemic metabolism by modulating gene expression in the SCN. In an in vitro study, Liu et al. [44] suggested that activation of PPAR-α may activate REV-ERB-α and promote its transcription and expression through the following mechanisms:

  1. PPAR-α recruits H3K27ac and H3K4me1 to the Nr1d1 enhancer region, along with H3K27ac and H3K4me3 to its transcriptional region, and increases the occupancy of RNA polymerase II (Pol-II) in the Nr1d1 transcriptional region, thereby activating and promoting Nr1d1 gene transcription and enhancing REV-ERB-α expression.

  2. As REV-ERB-α levels increase, the expression of core loop genes in the SCN is suppressed, generating rhythmic oscillations in gene expression.

In addition to PPAR-α, some clinical and in vitro studies [26, 45, 46] have also shown that PPAR-γ participates in SCN regulation. Possible mechanisms include:

  1. Clinical research by Wang et al. [26] demonstrated that PPAR-γ activation significantly reduces inflammatory factors like interleukin-6 (IL-6). Vieira E et al. [45] found in an in vitro study that disruption of circadian genes, especially REV-ERB-β and the genes it regulates (BMAL1-CLOCK), in the SCN leads to metabolic disturbances and abnormal inflammatory responses, with elevated levels of inflammatory factors such as IL-6. These findings suggest a regulatory role of PPAR-γ on REV-ERB-β expression.

  2. Further studies by Wang et al. [46] indicated that PPAR-γ dysfunction results in downregulation of SLC1A5, a transporter for glutamine and methionine uptake, which reduces fat cells’ ability to absorb these amino acids. This leads to decreased H3K27ac and H3K4me3 at the BMAL1 promoter and reduced REV-ERB-β expression, ultimately impairing BMAL1 gene expression and promoting circadian disruption.

As a pan-PPAR agonist, chiglitazar demonstrated an ability to improve the dawn phenomenon in diabetic patients in this study. We hypothesize that its mechanisms in correcting circadian metabolic disturbances and mitigating or resolving the dawn phenomenon may involve the following pathways:

  1. PPAR-α pathway:
    • i.
      Chiglitazar activates PPAR-α, which promotes Nr1d1 gene transcription and increases REV-ERB-α expression, thereby inhibiting CLOCK-BMAL1 gene expression.
    • ii.
      Chiglitazar may inhibit CLOCK-BMAL1 expression by repressing the REV-ERB-α transcription complex. After REV-ERB-α is recruited to the transcriptional region of CLOCK-BMAL1, activated PPAR-α forms heterodimers with REV-ERB-α. This complex recruits histone deacetylase 3 (HDAC3) and nuclear receptor co-repressor 1 (NCOR1), which reduce H3K27ac, H3K4me2, and RNA polymerase II (Pol-II) binding at target genes, while also lowering levels of coactivator p300, Pol II, and associated local histone modifications, ultimately suppressing CLOCK-BMAL1 gene expression [44].
    • iii.
      As a receptor subtype primarily found in the liver, PPAR-α may enhance glycogen synthesis, reduce glucose utilization, modulate inflammation, and regulate other hormones—particularly growth hormone [9, 25]. This likely aids in restoring the normal circadian function of hepatocytes, correcting diurnal metabolic rhythms, and effectively controlling the dawn phenomenon in diabetic patients.
  2. PPAR-γ pathway:
    • i.
      Through activation of PPAR-γ, chiglitazar upregulates SLC1A5, a transporter for glutamine and methionine uptake, which increases glutamine and methionine absorption in adipocytes, leading to enhanced REV-ERBβ expression and increased H3K27ac and H3K4me3 at the BMAL1 promoter.
    • ii.
      As a receptor subtype primarily located in white adipose tissue (WAT), PPAR-γ may help alleviate obesity and reduce abnormal inflammatory responses, ultimately restoring the clock function of adipocytes and reducing the occurrence of the dawn phenomenon.

The results of this study indicate that the novel pan-PPAR agonist chiglitazar not only improves lipid abnormalities in diabetic patients but also significantly ameliorates the dawn phenomenon. Compared with other oral hypoglycemic agents, chiglitazar demonstrates more stable and pronounced efficacy in blood glucose control, along with better safety and a lower incidence of adverse reactions [16–21]. The dawn phenomenon is a common challenge in diabetes management; its presence not only imposes a psychological burden on patients but also complicates the selection, dosing, and timing of hypoglycemic agents, creating barriers in patient–provider communication and clinical management. This study’s findings highlight the clear clinical benefits of chiglitazar in mitigating the dawn phenomenon, offering a new therapeutic approach and insights for future clinical practice. While our study demonstrated a statistically significant reduction in dawn phenomenon intensity following chiglitazar treatment (from 9.00 to 4.80 mg/dl, p < 0.01), the clinical significance of this reduction requires further consideration. The dawn phenomenon contributes to early morning hyperglycemia, which complicates glycemic control and often necessitates additional pharmacologic interventions, such as increased insulin doses or adjunctive glucose-lowering therapies. Even modest improvements in dawn phenomenon intensity can be beneficial, particularly in patients with unstable morning glucose levels, as they may reduce glycemic variability and potentially lower the risk of long-term diabetes-related complications. However, we acknowledge that the absolute magnitude of reduction observed in this study may not be sufficient as a standalone intervention for all patients. Future studies with larger sample sizes and extended follow-up periods are needed to determine whether this level of improvement translates into sustained clinical benefits, such as reduced insulin requirements, improved HbA1c levels, or a lower incidence of hypoglycemia. Additionally, exploring whether specific patient subgroups derive greater benefit from chiglitazar’s effects on the dawn phenomenon could help refine its clinical application. While this study identified significant improvements in both lipid parameters and blood glucose levels following chiglitazar treatment, no significant correlation was observed between lipid changes and the reduction in dawn phenomenon intensity. This finding suggests that the glucose-lowering effects of chiglitazar may not be directly mediated through lipid metabolism but rather through alternative mechanisms. Chiglitazar’s known effects on improving glucose and lipid metabolism have been well established in previous clinical and mechanistic studies. Given this, a detailed re-examination of these pathways in the current study would not contribute additional novelty. Instead, our findings indicate that circadian rhythm regulation and nuclear receptor interactions, particularly via REV-ERB pathways, may play a critical role in chiglitazar’s ability to mitigate the dawn phenomenon. Emerging evidence suggests that PPAR activation can influence core clock genes, modulating diurnal metabolic rhythms and systemic glucose homeostasis. PPAR-α and PPAR-γ have been implicated in circadian regulation via their interactions with REV-ERB nuclear receptors, which are known to suppress BMAL1-CLOCK gene transcription and regulate hepatic glucose metabolism. These mechanisms may provide a plausible explanation for the observed improvements in dawn phenomenon intensity that were independent of lipid profile changes. Future studies with targeted molecular analyses and continuous glucose monitoring (CGM) could further clarify the extent to which chiglitazar influences glucose homeostasis through circadian modulation rather than lipid regulation. Expanding this area of research may provide valuable insights into novel therapeutic strategies for addressing dawn phenomenon beyond traditional metabolic approaches.

This study has several limitations:

  1. Retrospective observational design and sample size: This is a retrospective observational study with a small sample size and short observation period. The effects and duration of chiglitazar’s improvement on the dawn phenomenon, as well as the potential for other adverse events, require further validation with a larger patient population and extended study duration. Current therapeutic approaches for managing the dawn phenomenon (DP) primarily focus on insulin therapy adjustments, oral glucose-lowering agents, and lifestyle modifications. Basal insulin titration and long-acting insulin analogs, such as glargine and degludec, are commonly used to suppress early morning hyperglycemia; however, they require careful dose adjustments to minimize nocturnal hypoglycemia risk. Additionally, some patients may require split-dose basal insulin regimens to better control nocturnal glucose fluctuations. Among oral antidiabetic agents, sodium-glucose cotransporter-2 (SGLT-2) inhibitors have been reported to reduce fasting blood glucose levels and may attenuate DP by promoting urinary glucose excretion overnight. Similarly, dipeptidyl peptidase-4 (DPP-4) inhibitors improve postprandial glucose metabolism but show inconsistent effects on DP. Metformin, due to its hepatic glucose production suppression, is sometimes used as an adjunct to mitigate DP, though its effect on nocturnal glucose regulation remains limited. Comparing chiglitazar to other PPAR agonists, pioglitazone (a PPAR-γ agonist) has demonstrated glucose-lowering effects and some impact on DP. However, pioglitazone’s use is often restricted due to side effects such as weight gain and fluid retention. In contrast, chiglitazar, as a pan-PPAR agonist, activates PPAR-α, PPAR-δ, and PPAR-γ, potentially offering a broader metabolic benefit with improved insulin sensitivity and lipid regulation while reducing the dawn phenomenon intensity. Beyond pharmacologic approaches, lifestyle interventions, including meal timing adjustments, late-night carbohydrate intake modification, and structured exercise routines, have been explored as non-pharmacologic strategies to manage DP. While these methods can be beneficial, their effectiveness varies among individuals and often depends on long-term adherence. Our findings suggest that chiglitazar represents a novel therapeutic strategy for mitigating DP, potentially through a mechanism that extends beyond conventional glucose-lowering pathways. Its effects may be linked to circadian rhythm regulation, particularly through modulation of REV-ERB nuclear receptors, offering an alternative approach for patients who experience persistent morning hyperglycemia despite existing treatments. Further research is warranted to confirm its long-term efficacy and compare its effects directly with other established interventions.

  2. Limited blood glucose measurement points: The blood glucose values of the subjects were measured at two specific time points. Although these time points are supported by some literature, the inherent variability may introduce substantial error into the study results.

  3. Potential influence of nocturnal hypoglycemia: The potential influence of nocturnal hypoglycemia cannot be fully excluded. Although we omitted data from days with nocturnal blood glucose < 70 mg/dl, we cannot entirely rule out residual errors from this factor.

  4. Predominantly type 2 diabetes population: The study population consisted mainly of typical type 2 diabetes patients, so extrapolating these findings to other diabetic populations may be limited by the inclusion and exclusion criteria of this study.

  5. Hypothesized mechanisms of chiglitazar in improving the dawn phenomenon: The proposed mechanisms by which chiglitazar improves the dawn phenomenon are partly based on animal studies; further large-scale clinical trials are needed to elucidate the precise mechanisms in humans.

    In summary, while this study offers new clinical insights into the potential of chiglitazar in ameliorating the dawn phenomenon in diabetic patients, it has notable limitations. For patients with various diabetes types, poor blood glucose control, or even diabetic complications, a single medication may not suffice to address the dawn phenomenon. More clinical experience and individualized treatment plans are needed to develop more detailed glucose-lowering strategies.

  6. Although our study demonstrated significant improvements in dawn phenomenon intensity, fasting blood glucose, and lipid metabolism after chiglitazar treatment, we acknowledge that the lack of a parallel placebo or control group limits the ability to definitively attribute these effects solely to chiglitazar. As a retrospective clinical study, our design does not fully exclude the possibility that other factors, such as lifestyle changes, hospitalization conditions, or natural disease progression, may have influenced the observed metabolic improvements. However, we attempted to minimize confounding variables through the following measures: (1) hospitalized treatment setting: all patients remained in the hospital throughout the study period, ensuring consistent dietary intake and treatment regimens, which reduces lifestyle-related variability. (2) Short-term observation period: the relatively short duration of the study minimizes the potential impact of natural disease progression on glucose and lipid metabolism. (3) self-controlled design: each patient effectively served as their own control, allowing for a direct comparison of pre- and post-treatment metabolic parameters. Despite these efforts, we recognize that a randomized controlled trial (RCT) design would provide stronger evidence by controlling for confounding factors and allowing direct comparisons with a placebo or standard-of-care treatment. Future studies should incorporate RCT methodologies to validate these findings and further elucidate chiglitazar’s specific role in dawn phenomenon modulation.

  7. Although our study suggests that chiglitazar may modulate the dawn phenomenon via circadian rhythm regulation, we acknowledge that no direct biomarker evidence (e.g., melatonin or cortisol levels) was included to confirm this hypothesis. The regulatory role of PPARs in circadian rhythm and glucose metabolism has been explored in previous studies, but currently, no research has specifically examined chiglitazar’s impact on circadian biomarkers in diabetic patients. To better validate this hypothesis, future studies should incorporate biomarker assessments such as: 1. Melatonin and cortisol rhythms: Evaluating these key circadian hormones could provide insight into chiglitazar’s effects on hypothalamic–pituitary–adrenal (HPA) axis regulation and its potential role in mitigating the dawn phenomenon. 2. Core circadian gene expression: Measuring genes such as BMAL1, CLOCK, REV-ERBα, and PER genes in peripheral blood mononuclear cells (PBMCs) or adipose tissue may help establish whether chiglitazar exerts its effects through circadian transcriptional control. 3. Continuous glucose monitoring (CGM): Integrating CGM data with circadian biomarker measurements could provide a comprehensive understanding of chiglitazar’s effects on nocturnal glucose fluctuations and dawn phenomenon modulation. Given the current lack of direct experimental validation, we emphasize that our proposed mechanism remains hypothetical, based on existing studies linking PPAR activation to circadian control. Further well-designed clinical and mechanistic studies are needed to confirm these findings and determine whether chiglitazar’s glucose-lowering effects are partially or primarily mediated by circadian regulation.

  8. Although this study provides valuable insights into the effects of chiglitazar on the dawn phenomenon, we acknowledge that subgroup analysis based on patient characteristics (e.g., age, sex, diabetes duration, and comorbidities) was not performed due to the limited sample size. Given that metabolic responses to treatment may vary among different patient populations, future studies with larger cohorts and stratified analyses are warranted to explore potential differential efficacy of chiglitazar. Previous studies have suggested that longer diabetes duration and underlying comorbid conditions such as hypertension and dyslipidemia may influence glucose regulation and response to insulin-sensitizing therapies. Therefore, an in-depth analysis of how these factors affect chiglitazar’s efficacy could provide personalized therapeutic insights. Future research should aim to incorporate subgroup analyses and assess treatment response across different patient demographics to optimize clinical decision-making.

  9. While our study demonstrated significant improvements in fasting glucose levels and HbA1c, the precise impact of chiglitazar on insulin sensitivity and β-cell function remains unclear due to the lack of post-treatment insulin and C-peptide measurements. The HOMA-IR (Homeostatic Model Assessment for Insulin Resistance) and HOMA-β (β-cell function index) are widely used to assess insulin resistance and pancreatic β-cell function, but these indices require both fasting glucose and fasting insulin (or C-peptide) values for accurate calculation. Due to data limitations in our study design, post-treatment insulin and C-peptide levels were not available, making it impossible to retrospectively compute HOMA-IR or HOMA-β. Nevertheless, previous studies have suggested that PPAR agonists improve insulin sensitivity through multiple mechanisms, including enhanced lipid metabolism, adipocyte differentiation, reduced inflammation, and mitochondrial function modulation. To further elucidate chiglitazar’s role in glucose homeostasis, future studies should incorporate direct insulin sensitivity assessments, such as: 1. HOMA-IR and HOMA-β calculations, with fasting insulin and C-peptide measurements at multiple time points. 2. Hyperinsulinemic-euglycemic clamp studies, which represent the gold standard for assessing insulin sensitivity. 3. Oral glucose tolerance tests (OGTT) with insulin response curves, to provide additional insights into β-cell function dynamics. Given these limitations, we acknowledge that our study primarily focuses on glycemic control outcomes rather than the detailed mechanistic impact on insulin resistance or β-cell function. Future well-designed studies with comprehensive metabolic assessments will be necessary to further validate chiglitazar’s effects on insulin sensitivity and pancreatic β-cell function.

Conclusions

Our study provides clinical evidence that chiglitazar significantly improves dawn phenomenon intensity, fasting blood glucose levels, and lipid metabolism in diabetic patients. These findings suggest that chiglitazar may offer a novel therapeutic approach for mitigating early morning hyperglycemia, an aspect of glycemic control that remains challenging in diabetes management. Although the precise mechanisms underlying these improvements remain to be fully elucidated, our results indicate that the glucose-lowering effects of chiglitazar are not directly correlated with lipid profile changes, suggesting alternative pathways beyond lipid metabolism. Given the growing interest in circadian rhythm regulation in metabolic disorders, we propose that chiglitazar’s effects may involve circadian gene modulation, though this hypothesis requires further experimental validation. Despite these promising findings, our study has several limitations, including the small sample size, short observation period, and the absence of a control group. As a retrospective study, the findings should be interpreted with caution, and randomized controlled trials (RCTs) with larger cohorts and longer follow-up periods are needed to confirm the long-term efficacy and safety of chiglitazar. Additionally, future research should incorporate biomarker assessments (e.g., melatonin, cortisol, core circadian genes) and insulin sensitivity indices (e.g., HOMA-IR, HOMA-β, clamp studies) to provide a comprehensive mechanistic understanding of chiglitazar’s metabolic effects. In conclusion, our study suggests that chiglitazar represents a potential therapeutic option for improving dawn phenomenon intensity and glycemic control in diabetes, with mechanisms that may extend beyond traditional lipid modulation. Further well-designed trials and mechanistic studies are warranted to validate these findings and explore the full therapeutic potential of chiglitazar in metabolic disorders.

Author Contribution

Wx. Li collected samples, analyzed data, and drafted the manuscript. Cf. Liu, Yz. Yu, and Ll. Xu collected samples and organized data. Yg. Wang and Bz. Dong conceived and supervised the study.

Funding

No funding was received to undertake the study and for the publication of this article. The Rapid Service Fee was funded by the authors.

Data Availability

The data generated and analyzed in this study are not publicly available due to patient confidentiality, ethical considerations, and institutional policies. However, the datasets used in this study may be made available upon reasonable request from the corresponding author.

Declarations

Conflict of Interest

Wenxuan Li, Yangang Wang, Chuanfeng Liu, Yongzhuo Yu, Lili Xu, Bingzi Dong declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ethical Approval

This study was approved by the Ethics Committee of the Affiliated Hospital of Qingdao University, and informed consent was obtained from all participants. No misuse or disclosure of patients’ personal information occurred, and all data generated during the study were strictly confidential and used solely for research purposes. We extend our gratitude to the Department of Endocrinology at the Affiliated Hospital of Qingdao University for their support of this research.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data generated and analyzed in this study are not publicly available due to patient confidentiality, ethical considerations, and institutional policies. However, the datasets used in this study may be made available upon reasonable request from the corresponding author.

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