Introduction

Diabetes, particularly type 2 diabetes mellitus (T2DM), has emerged as a significant global health challenge. The International Diabetes Federation (IDF) reports that there are around 422 million individuals living with diabetes worldwide1. The challenge of long-term management of this chronic disease lies in its multitude of complications, which affect the vasculature, nerves, and multiple organs, particularly the kidney. Microalbuminuria (MAU), identified by urinary albumin to creatinine ratio (UACR) ranging from 30 to 300 mg/g, was initially recognized for its predictive value in diabetic kidney disease (DKD)2. Research indicates that MAU not only serves as an indicator for DKD but is also intricately linked to elevated risks of cardiovascular diseases and associated mortality rates3,4,5. An earlier finding suggests a significant correlation between elevated urinary albumin levels and heightened cardiovascular disease risk among individuals with T2DM6. Therefore, analyzing risk factors for MAU can offer new insights for the prevention and treatment of progressing to significant proteinuria or various cardiovascular diseases, ultimately enhancing the prognosis of patients with T2DM7.

The thyroid gland plays a vital role as an essential endocrine gland in the human body. Its function is primarily governed by levels of thyroid hormones (TH), which are crucial for cellular metabolism, blood sugar regulation, and other essential processes8. TH directly impact renal tubular function, glomerular filtration rate, and renal hemodynamics9. Previous research demonstrates that, even within populations with normal thyroid function, levels of TH are closely linked to the risk of developing conditions such as DKD and cardiovascular diseases10,11. Furthermore, studies suggest that TH levels also influence endothelial cell function. TH regulate vascular dilation, angiotensin II receptor activity, and its signaling pathway, thus modulating endothelial function and vascular homeostasis12. The primary TH include free triiodothyronine (FT3), free thyroxine (FT4), and thyroid-stimulating hormone (TSH). The FT3/FT4 ratio can be understood as the conversion rate of thyroxine (T4) to triiodothyronine (T3), indicating the responsiveness to TH in peripheral tissues13. Additionally, research indicates that the correlation between the FT3/FT4 ratio and cardiovascular diseases, as well as DKD, is stronger than the correlation between either FT3 or FT4 alone14,15.

In recent years, researches have highlighted the significant association between thyroid dysfunction and both MAU and DKD16,17,18. However, in euthyroid patients with T2DM, studies on TH, particularly the ratio of FT4 to FT3, in relation to MAU are still limited. Therefore, this study aims to explore the potential link between the FT4/FT3 ratio and MAU in euthyroid patients with T2DM.

Methods

Study design: This study employed a cross-sectional design aimed at evaluating the relationship between the FT4/FT3 ratio and MAU in patients with T2DM, who were receiving care at the Endocrinology Department of Linyi People’s Hospital, Shandong Province, China, from January 2020 to March 2023. These individuals were diagnosed according to the criteria established by the World Health Organization (WHO) in 1999. The selection process incorporated specific exclusion criteria, including: (1) patients manifesting any form of thyroid dysfunction; (2) patients with UACR ≥ 300 mg/g; (3) individuals < 18 years; (4) patients suffering from significant liver or kidney impairments; (5) patients with urinary tract infections; and (6) cases with incomplete medical records. After a rigorous screening process, a cohort of 1734 patients who satisfied all eligibility requirements was assembled. This cohort was further stratified into two distinct groups for analysis: participants were divided into MAU group (30 ≤ UACR < 300 mg/g) and NAU group (UACR < 30 mg/g).

Laboratory biochemical indices: Following a period of overnight fasting, venous blood is collected in the early morning for comprehensive analysis. The assay panel includes alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum creatinine (Scr), uric acid (UA), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), hemoglobin (Hb), fasting blood glucose (FBG), and glycated hemoglobin (HbA1c, assessed through high-performance liquid chromatography), utilizing an automated biochemical analyzer (Cobas c 702, Roche, Germany). The analysis of urinary creatinine, using the Jaffe method, and urinary microalbumin (UMA), determined by transmission turbidimetry, along with the calculation of the urinary albumin-to-creatinine ratio (UACR), is performed using an automated analyzer (Beckman Coulter AU5821). Visceral fat area (VFA) and subcutaneous fat area (SFA) measurements were conducted using the Omron DUALSCAN BIA machine (Omron HDS-2000, Kyoto, Japan). Thyroid function tests, covering FT3, FT4, thyroid-stimulating hormone (TSH), and anti-thyroid peroxidase antibody (TPOAb), are conducted via chemiluminescence immunoassay (Siemens, USA), with the normal ranges for thyroid function specified as follows: TSH from 0.55 to 4.78 uIU/mL, FT3 from 3.5 to 6.5 pmol/L, and FT4 from 11.5 to 22.7 pmol/L.

Medical data and anthropometric measurement: In this study, comprehensive medical data were extracted from patients’ records, including demographic information (age, gender), lifestyle factors (smoking and drinking status), and clinical parameters (diabetes duration). Laboratory results, such as blood glucose, lipid profiles, and thyroid function tests, were also collected to analyze their potential associations with the FT4/FT3 ratio and MAU. Anthropometric measurements, including height, weight and blood pressure, were obtained following standardized protocols, with BMI calculated as BMI (kg/m²) = weight (kg) / height² (m²)19. These data were analyzed to examine the relationship between the FT4/FT3 ratio and the occurrence of MAU in T2DM patients. The estimated glomerular filtration rate (eGFR) was calculated following the Modification of Diet in Renal Disease equation: 194 × serum Cr −1.094 × age −0.287(×0.739 if women)20.

Diagnosis of diabetic retinopathy (DR)

According to the corresponding criteria, diagnose DR21.

Statistical analysis: The Statistical Package for the Social Sciences (SPSS), version 20.0 (Chicago, IL, USA) was utilized for data analysis. The software can be accessed at https://www.ibm.com/products/spss-statistics. Normal distribution variables were presented as mean ± SD, while non-normal variables were described with medians and interquartile ranges. The comparisons of normally and non-normally distributed continuous variables were performed using the independent-samples T test and Mann-Whitney U test, respectively. Categorical variables were compared using the chi-square test. Pearson and Spearman coefficients assessed correlations between UACR, MAU, and other factors. Multiple linear regression and binary logistic stepwise regression analyses identified independent predictors for UACR and MAU. A two-tailed P value < 0.05 was considered statistically significant.

Results

Baseline characteristics of the study subjects

The baseline clinical characteristics of the study participants are shown in Table 1. The MAU group (n = 367) demonstrated marked increases in several parameters including age, diabetes duration, systolic blood pressure (SBP), TC, TG, FBG, HbA1c, FT4, FT4/FT3 ratio, UA, and Scr, compared to the NAU group (all P < 0.05). Conversely, significant reductions in FT3, eGFR, and Hb levels were observed (both P < 0.05). Notably, the incidence of diabetic retinopathy (DR) was significantly higher within the MAU group than in the NAU group (P < 0.05). Yet, no significant distinctions were found between two groups regarding the proportions of male participants, smokers, and drinkers, as well as BMI, VFA, SFA, diastolic blood pressure (DBP), LDL-c, HDL-c, AST, ALT, TSH, and TPOAb levels (all P > 0.05).

Table 1 Comparison of clinical and biochemical characteristics between NAU and MAU groups.
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Univariate analysis

As shown in Table 2, Pearson’s correlation analysis indicated that UACR positively correlated with age, duration of diabetes, SBP, TC, TG, FBG, HbA1c, FT4, the FT4/FT3 ratio, and Scr, while it negatively correlated with FT3, eGFR and Hb (all P < 0.05). There was no significant relationship between UACR and BMI, VFA, SFA, DBP, LDL-c, HDL-c, AST, ALT, TSH, TPOAb, UA (all P > 0.05). Similarly, Spearman correlation analysis showed that MAU was positively related to age, duration of diabetes, SBP, TG, FBG, HbA1c, FT4, the FT4/FT3 ratio, UA, and Scr, and negatively related to FT3, eGFR and Hb (all P < 0.05). No significant correlations were found between MAU and BMI, VFA, SFA, DBP, TC, LDL-c, HDL-c, AST, ALT, TSH, TPOAb (all P > 0.05).

Table 2 The correlation between UACR or MAU by univariate analysis.
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Multivariate analysis

In our analytical framework, UACR was designated as the dependent variable, while various aforementioned metrics served as independent variables. Consequently, a multivariate linear stepwise regression analysis was undertaken. Following the adjustment for additional variables, the derived model from the multivariate linear regression equation is presented in Table 3. Our findings indicate that the FT4/FT3 ratio, SBP, Scr, Hb, HbA1c, duration of diabetes, and TG were significant contributors to the model (with standardized coefficients of 0.148, 0.164, 0.150, −0.209, 0.184, 0.119, and 0.088 respectively, all P < 0.001).

Table 3 The independent variables of UACR.
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In this investigation, MAU was classified as having a UACR between 30 and 300 mg/g. The binary logistic regression analysis, adjusted for confounding factors and illustrated in Table 4, revealed odds ratios (OR) and 95% confidence intervals (CI) for the FT4/FT3 ratio, SBP, Scr, Hb, HbA1c, duration of diabetes, UA, and DR as follows: 1.947 (1.522–2.491), 1.021 (1.014–1.029), 1.018 (1.009–1.027), 0.980 (0.972–0.989), 1.196 (1.117–1.280), 1.045 (1.025–1.066), 1.003 (1.002–1.005), and 1.385 (1.037–1.851), respectively.

Table 4 The relative risk for MUA by logistic regression analysis.
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Discussion

In our research, we have introduced FT4/FT3 ratio to more effectively delineate the independent risk factors for the onset of MAU. This study found that in patients with T2DM and normal TH levels, the level of FT4/FT3 is positively correlated with the risk of developing MAU. After adjusting for confounding factors, high FT4/FT3 levels remain an independent risk factor for MAU.

The progression of DKD encompasses several stages, beginning with MAU and culminating in end-stage renal disease (ESRD). In patients with diabetes, MAU has a heightened propensity to evolve into overt proteinuria, ultimately culminating in renal failure22,23. This is a critical factor leading to mortality and the incidence of cardiovascular events in patients with T2DM. A global study indicates that the overall prevalence of MAU among patients with T2DM is approximately 39%24. In this study, the prevalence of MAU in patients with T2DM is approximately 21.2%. This variance may be attributed to factors such as ethnicity, sample size, among others. Another meta-analysis concerning the prevalence of MAU in diabetic patients in Africa revealed that the overall prevalence of MAU among African diabetic patients is approximately 37%25. Generally, the prevalence of MAU among diabetic patients is high25,26.

Prior studies have assessed the relationship between TH levels and DKD progression, demonstrating a negative correlation between FT3 and the advancement of DKD10,27,28. Further research has discovered that, within the middle-aged and elderly demographic in China, low FT3 levels within the normal range are linked to the development of MAU29. In our study, the results differ from those of the aforementioned study. Although in univariate analysis, FT3 levels were negatively associated with UACR and MAU respectively (p< 0.05), FT3 did not ultimately enter into the multiple linear regression and logistic regression equations. Moreover, reports on the correlation between FT4, TSH, and UACR have been inconsistent10,30. In our study, FT4 exhibited a positive correlation with both UACR and MAU in both Pearson and Spearman correlation analyses (p < 0.05), while TSH demonstrated no correlation in either analysis (p> 0.05). The variation could be attributed to the differences in the populations screened, confounding factors adjusted, ethnicities, and study designs. It is noteworthy that the FT4/FT3 ratio is the only TH-related parameter that entered the final regression equation, suggesting a closer association with MAU in euthyroid patients with T2DM. Currently, there is no reported analysis of the relationship between these two factors, which is consistent with prior research findings, with the distinction that they did not differentiate between significant albuminuria and MAU15. The underlying mechanism for the positive correlation between the FT4/ FT3 ratio and MAU remains incompletely understood. In addition, it is crucial to consider the broader implications of TH imbalances on kidney function. Endothelial dysfunction, a key factor in the progression of DKD, contributes to kidney damage through mechanisms such as inflammation, fibrosis, and microvascular injury31. Research suggests that TH play a significant role in regulating various biological processes, including cardiovascular and renal function, and influence endothelial function9. When TH levels are dysregulated, particularly when elevated or reduced, endothelial dysfunction may be exacerbated, accelerating the progression of DKD32. This dysregulation adds complexity to the relationship between TH levels and the progression of MAU in T2DM.

From a biological perspective, TH play a crucial role in the human body, impacting the cardiovascular system, metabolism, and growth and development, among other aspects. They can influence kidney function through multiple mechanisms, including the activation of the renin-angiotensin-aldosterone system (RAAS), and affect the function of the renal tubules and glomeruli9. TH receptors are expressed in both cardiac myocytes and vascular tissues. Therefore, in addition to their direct effects on the kidneys, TH can also impact renal function through the cardiovascular system, potentially leading to renal damage and MAU33.

In addition, we also found that SBP, HbA1c, duration of diabetes, DR, and MAU were independently associated. This is consistent with previous research findings29,34,35.

Limitations

This study has certain limitations. Firstly, due to its cross-sectional design, we cannot establish a causal relationship between the FT4/FT3 ratio and MAU. Future prospective or interventional studies would be beneficial in further exploring this relationship. Secondly, the study results may be influenced by the limited sample size. In the future, we need to expand the sample size, conduct multicenter studies, and refine the findings of this study.

Conclusion

In conclusion, this study demonstrates that the FT4/FT3 ratio is positively correlated with MAU in patients with normal thyroid function and T2DM, suggesting that this ratio may be an independent risk factor for the development of MAU in these patients. Future studies should further explore the potential application value of this ratio in the monitoring and management of MAU in patients with normal thyroid function and T2DM.