Semaglutide Therapy and Cardiorenal Risk Management in Type 2 Diabetes: hsCRP as a Biomarker of Risk

Abstract

Background: Inflammation plays a key role in the pathogenesis of type 2 diabetes (T2D) and the associated cardiovascular complications. High-sensitivity C-reactive protein (hsCRP) is a widely used marker of systemic inflammation as well as a predictor of cardiovascular risk. Objective: There is increasing evidence that glucagon-like peptide-1 receptor agonists (GLP-1RAs), including semaglutide, may have effects on hsCRP levels, independent of their effects on glycemic control and body weight loss. This purpose of our study is to explore the effect of semaglutide on hsCRP levels in patients with type 2 diabetes. Additionally, we aimed to determine whether the observed effect of semaglutide on hsCRP is fully mediated by changes in HbA1c and body weight, or whether there is a direct effect suggesting the presence of an independent anti-inflammatory mechanism. Methods: The study included 70 outpatients with diagnosed type 2 diabetes undergoing therapy with metformin and/or a sulfonylurea. Semaglutide was added to the existing therapeutic regimen. All participants were followed up after a 6-month a period. At the beginning and at the end of the study, the hsCRP values, some selected indicators of glycemic control, and the anthropometric measurements were recorded. Results: The mean hsCRP value at baseline was 4.90 ± 1.21 mg/L, while after six-month therapy, it dropped to 2.23 ± 2.21 mg/L. Conclusions: The results of the analysis have a good potential to contribute to a better understanding of the pleiotropic effects of GLP-1 RAs and support the hypothesis of a direct anti-inflammatory role of semaglutide, which could have clinical significance in the context of cardiometabolic risk management in patients with type 2 diabetes.

1. Introduction

High-sensitivity C-reactive protein (hsCRP) is a form of C-reactive protein used to detect low-grade inflammation. Historically, CRP was discovered in the 1930s in the serum of patients with pneumococcal pneumonia; in these patients, it reacted with C-polysaccharide from the cell wall of Streptococcus pneumoniae to form a precipitate—hence its name: “C-reactive protein” [1]. Sustained high levels of hsCRP over time, rather than instantaneous peaks, have been used as a prognostic biomarker for cardiovascular risk and development of atherosclerosis in otherwise apparently healthy individuals or individuals with or without risk factors [2,3,4]. The normal range for hsCRP is up to 1.0 mg/L. Higher levels are associated with a greater risk of cardiovascular disease (CVD). Levels above 2.0 mg/L are associated with poor prognosis, higher rates of complications, and mortality [5,6].

Type 2 diabetes is one of the most common chronic metabolic diseases, which is characterized by the development of insulin resistance and elevated blood sugar, relative insulin deficiency, and, often, concomitant hyperglycemia. Patients with type 2 diabetes tend to develop micro- and macrovascular complications, mainly due to accelerated atherosclerosis, which is exacerbated by vascular inflammation and free radical damage caused by elevated blood glucose levels [7,8]. hsCRP has been shown to be a strong and independent marker of risk for cardiovascular and nephrological complications [9].

In parallel with the progress in understanding the inflammatory component of type 2 diabetes, incretin-based drugs, including GLP-1 receptor agonists, have been widely introduced into therapeutic practice. These not only demonstrate a glucose-lowering effect but also the potential to modulate the inflammatory processes [10,11]. It has been suggested that this pleiotropic effect may contribute to lower residual cardiovascular risk in specific patient groups. The results of clinical studies support the observation that semaglutide has a potential anti-inflammatory effect, resulting in an hsCRP decrease in patients with type 2 diabetes, which is partly due to the reduction in HbA1c and body weight loss. In addition, the hypothesis of a possible direct effect of semaglutide on hsCRP levels remains to be fully elucidated by further analyses [12,13].

Objective: To study the semaglutide effect on hsCRP levels, carbohydrate metabolism parameters, and renal function in patients with type 2 diabetes. In addition, the aim is to determine whether the observed effect of semaglutide on hsCRP is fully mediated by changes in HbA1c and body weight, or whether there is a direct effect, suggesting the presence of an independent anti-inflammatory mechanism.

2. Material and Applied Methodology

Based on existing published studies on the GLP-1 Ras anti-inflammatory activity, we conducted an observational single-center study to evaluate the effect of semaglutide on high-sensitivity C-reactive protein levels in patients with type 2 diabetes mellitus. The study included 70 outpatients with proven type 2 diabetes, undergoing therapy with metformin and/or a sulfonylurea-class medication. In these patients, semaglutide was added to the existing therapeutic regimen at an initial dose of 0.25 mg per week with gradual titration to 1.0 mg per week in accordance with the available recommendations. All participants were followed for 6 months. hsCRP levels, some selected glycemic control parameters, and the anthropometric measurements were recorded at baseline as well as at the end of the study period. After the collection of all data, a cross-correlation analysis was performed between the different groups of markers in order to assess changes at baseline and after 6 months of GLP-1 RA treatment. hsCRP was investigated using the ELISA method.

3. Tracking Design

At the beginning of the study, all patients underwent a detailed medical interview recording information on their age, type 2 diabetes duration, currently administered therapy, presence of concomitant diseases, and diabetic complications. A review and analysis of the available medical documentation was performed. The study design is a prospective, observational study with a 6-month follow-up.

The following clinical and laboratory parameters were recorded at the beginning and the end of the 6-month period:

• Glycated hemoglobin (HbA1c);
• Serum creatinine and estimated glomerular filtration rate (eGFR) through the CKD-EPI formula;
• High-sensitivity C-reactive protein (hsCRP);
• Microalbuminuria (MALB);
• Anthropometric measurements: height, body weight, body mass index (BMI), and waist circumference.

3.1. Data Collection Procedure

Empirical data were collected through standardized methods of applied medical sociology and clinical assessment, including

• Structured individual survey;
• Semi-standardized clinical interview;
• Direct clinical observation.

The information was collected in real clinical practice conditions in outpatient medical care facilities, including

• Medical Center “Doctors for Us”—Burgas;
• Individual Practice of Specialized Medical Care “Dr. Nikolay Kostadinov”—city of Burgas.

3.2. Patient Characteristics

The patients included in the study were randomly selected based on predefined inclusion and exclusion criteria.

Inclusion criteria:

• Age over 18 years;
• Confirmed diagnosis of type 2 diabetes mellitus for at least 6 months;
• Undergone prior treatment with metformin and/or a sulfonylurea;
• Signed informed consent for study participation.

Exclusion criteria:

• Type 1 diabetes mellitus;
• Gestational diabetes;
• Age under 18 years;
• Presence of cognitive deficits and/or mental illnesses limiting the validity of informed consent and/or access to objective information.

All participants signed an informed-consent form prior to their inclusion in the study.

In Bulgaria, semaglutide is reimbursed by the health fund in a dose of 1.0 mg weekly. Given this low dose, only two patients could not tolerate the 1.0 mg dose and were excluded. Given their small number, they were not described in the study.

Patients who had concomitant diseases such as dyslipidemia and arterial hypertension were included in the study on the background of stable therapy for them, which was not changed during the course of 6 months of treatment with semaglutide. Thus, we report the effect of semaglutide on the levels of hsCRP added to a statin or RAAS blocker.

The patients were not current smokers and had not received SGLT 2 inhibitor treatment. Patients were free of clinical evidence of infection during clinical examinations prior to inclusion in the study and after 6 months of semaglutide treatment.

The therapeutic intervention included the addition of semaglutide to the treatment with sulfonylurea-class medication and/or metformin. Semaglutide was administered subcutaneously, once a week, in a gradually titrated dose of 0.25 mg for weeks 1–4, 0.5 mg for weeks 5–8, and then 1.0 mg weekly for the next four months of the study. Only patients who reached a weekly dose of 1.0 mg semaglutide remained in the study. All participants who, due to side effects of the drug, did not reach a weekly dose of 1 mg semaglutide, were excluded from the follow-up.

4. Results

4.1. Demographic and Anthropometric Profile of the Studied Population

The profile of the participants in the study was constructed based on demographic and social characteristics, including gender, age, educational level, professional status, and work schedule, as well as basic anthropometric measurements characterizing physical development—height, body weight, waist circumference, and body mass index (BMI).

Regarding the gender distribution, out of 70 participating patients, 41.4% (n = 29) were male and 58.6% (n = 41) were female.

The age of the participants ranged from 33 to 75 years, with a mean value of 54.54 ± 10.05 years. The most frequently observed age (mode) is 43 years, while the median age, representing 50% of the patient group, is 53 years.

The distribution of patients according to educational level showed that 36 (51.4%) had secondary education, 31 (44.3%) had higher education, and 3 (4.3%) had primary education.

As far as nature of employment is concerned, the participants have been divided into three main groups: 48.8% of the patients have a daytime job, 15.3% have a mixed work schedule (including night shifts), and 35.9% are not actively employed, with the majority of them being of retirement age. The distribution by professional employment has the following structure: 18.8% of the participants’ jobs involve physical labor, 16.5% have employment with no physical strain, 15.9% are employed in the field of public services, 5.3% hold managerial positions, 4.1% work in healthcare, and 3.5% responded that they are engaged in intellectual work. The remaining 35.9% were not employed at the time of the survey.

4.2. Clinical and Anthropometric Profile

The analysis of the anthropometric measurements of the studied group showed a mean body weight of 110.76 ± 19.12 kg and a mean waist circumference of 114.71 ± 10.95 cm, which corresponds to a high degree of central obesity. The mean value of the body mass index (BMI) was 38.56 ± 5.46 kg/m², which places the group in the category II obesity according to the WHO criteria.

In terms of health status, the duration of type 2 diabetes mellitus in the participants ranged from 1 to 25 years, with a mean value of 6.83 ± 5.79 years. The distribution analysis revealed that in 25% of the patients, the duration of the disease was up to 1 year; in 50%, up to 5 years; and in 25%, 10 years or more.

The above data reflect the heterogeneity of the group both in terms of metabolic risk as well as in terms of personal experience with diabetes and chronic complications.

4.3. Monitored Laboratory Parameters and Their Dynamics During the Course of Administered Treatment

The dynamics of the following laboratory parameters were monitored at the beginning and at the end of the 6-month observational period for each participant: high-sensitivity C-reactive protein (hsCRP), glycated hemoglobin (HbA1c), microalbuminuria (MALB), serum creatinine, as well as estimated glomerular filtration rate (eGFR), calculated using the CKD-EPI formula (

Table 1. Dynamics of laboratory parameters in patients with type 2 diabetes before and after 6 months of semaglutide treatment.

	MALB (mg/L)	Creat (mkmol/L)	eGFR (mL/min)	HbA1c (%)	HsCRP (mg/L)
Baseline value	43.54	77.00	88.35	8.18	4.90
Value after 6 months	44.55	71.08	94.13	6.50	1.21

).

4.4. Inflammatory Marker hsCRP in Patients Treated with GLP-1 RA

C-reactive protein (CRP) belongs to the pentraxin family and exists in at least two conformationally distinct forms, the native pentameric form (pCRP) and the monomeric form (mCRP) [14,15]. Studies have consistently demonstrated that pCRP can exhibit both pro- as well as anti-inflammatory properties depending on the context. In contrast, mCRP exhibits a strong pro-inflammatory effect on endothelial cells, endothelial precursor cells, leukocytes, and platelets, potentiating the inflammatory response. The dissociation of pCRP to the pro-inflammatory form mCRP is considered a mechanism directly linking CRP to inflammatory processes. Patients with elevated basal levels of C-reactive protein are at increased risk of developing cardiovascular disease, type 2 diabetes mellitus, and systemic hypertension [16,17].

During the 6-month period of treatment with semaglutide, a significant reduction in high-sensitivity C-reactive protein levels was observed, indicating a decreased inflammatory response. The reduction in hsCRP may suggest a potential association with improved health status in patients receiving semaglutide therapy. The mean hsCRP value at the beginning of the study was 4.90 ± 1.21 mg/L, while after 6 months of therapy, it was down to 2.23 ± 2.21 mg/L. The difference between the mean values was statistically significant, supported by a t-statistic t = 3.92, with a significance level p < 0.05 (Figure 1).

The results are a compelling support for the hypothesis that GLP-1 RAs not only affect metabolic control, but also play a key role in modulating systemic inflammation in patients with metabolic disorders [18,19].

A number of studies have highlighted the existing relationship between glycated hemoglobin (HbA1c) levels and high-sensitivity C-reactive protein while simultaneously pointing out the importance of optimal glycemic control for reduction in systemic inflammation and limiting diabetes-associated complications [20,21,22].

All patients at the current visits received advice on physical and movement regimes.

In this analysis, the mean HbA1c at baseline was 8.18 ± 1.98%, and after 6 months of treatment with GLP-1 RA (semaglutide), it decreased to 6.50 ± 1.19%. The difference of 1.68% is statistically significant (p < 0.05). The calculated t-statistic was t = 8.983 (Figure 2).

The results reaffirm the effectiveness of GLP-1 RA in achieving significant improvement in glycemic control in patients with type 2 diabetes.

4.5. Dynamics of Changes in the Blood Glucose Profile

An analysis of the blood glucose profile (BGP) of patients taking a GLP-1 receptor agonist shows that the differences between the mean values at the beginning of the study and after 6 months were statistically significant (p < 0.05) for all seven BGP follow-up stages. Based on these data, the conclusion is that the administration of GLP-1 RA (semaglutide) has significantly lowered blood sugar levels at each stage of patients’ follow-up (Figure 3).

Administration of semaglutide

By monitoring glycemic control throughout the study, we found that improvement in glycemic parameters was directly related to a reduction in hsCRP levels, which is the key factor for reducing the inflammatory response in patients. The data confirm that elevated hsCRP levels are associated with a higher risk of developing type 2 diabetes, especially in individuals with metabolic syndrome [23].

Based on all that, hsCRP can be considered a valuable potential tool for early diagnosis and targeting individuals for adopting early preventive measures against cardiovascular events, as well as to reduce morbidity and mortality among patients with type 2 diabetes. As a sensitive and accessible inflammatory marker, hsCRP has the potential to be used to detect prediabetes and to serve as a prognostic indicator for identifying cardiovascular complications, including in individuals without overt disease but with elevated blood glucose levels [24,25].

4.6. Descriptive and Comparative Analysis of the Therapeutic Effect of the Therapy with GLP-1 RA

The correlations between key clinical and laboratory parameters were analyzed: hsCRP, eGFR, serum creatinine, microalbuminuria, HbA1c, and BMI.

Table 2. Descriptive statistics of the studied parameters at baseline and after 6 months of GLP-1 RA therapy (semaglutide).

Beginning of Therapy
		hsCRP (mg/L)	eGFR (mL/min 1.73 m2)	Creatinine (µmol/L)	MALB (mg/L)	HbA1c (%)	BMI
N	Valid	70	70	70	70	70	70
	Missing	0	0	0	0	0	0
Mean value		4.9025	4.9025	88.57	77.0033	43.5409	8.1897
Std. Deviation		5.2119	5.2119	17.077	14.56903	73.62230	0.97865
Range		34.39	34.39	68	56.00	399.00	4.00
Minimum		0.44	0.44	50	55.00	1.00	7.50
Maximum		34.83	34.83	118	111.00	400.00	11.50
Results After 6 Months
		hsCRP (mg/L)	eGFR (mL/min 1.73 m2)	Creatinine (µmol/L)	MALB (mg/L)	HbA1c (%)	BMI
N	Valid	70	70	70	70	70	70
	Missing	0	0	0	0	0	0
Mean		2.2304	94.13	71.0876	44.5559	6.5036	35.5551
Std. Deviation		2.2172	16.154	14.14804	87.54986	1.19244	5.72462
Range		12.35	77	69.00	452.17	4.90	28.40
Minimum		0.45	57	37.00	1.00	4.90	26.97
Maximum		12.80	134	106.00	453.17	9.80	55.37

summarizes descriptive characteristics of the main parameters studied at baseline and after six months of treatment with semaglutide. The application of the comparative/paired t-test (Paired Samples T-Test) showed that the differences between the mean values of most indicators were statistically significant at a confidence level of p = 95% (α = 0.05), with the exception of microalbuminuria, where no significant change was found.

Six-month therapy with a GLP-1 receptor agonist (semaglutide) in patients with type 2 diabetes and comorbid obesity led to significant improvements in a number of metabolic and inflammatory markers. The reported statistically significant reduction in hsCRP confirms a pronounced anti-inflammatory effect, probably mediated by the body weight loss, improved glycemic control, and possible direct immunomodulatory mechanisms of semaglutide. Regarding renal function, a significant increase in eGFR and a reduction in serum creatinine were witnessed, which supports a potential nephroprotective effect of the therapy. These effects are explained as a complex effect of the therapy on glucotoxicity, renal hemodynamics, and systemic inflammation. Despite the lack of statistically significant change in microalbumin (MALB) levels, the results indicate the need for longer-term follow-up to assess the impact on early glomerular injury. Glycemic control also improved significantly, with HbA1c decreasing by an average of almost 2%, which is clinically significant and correlates with a reduced risk of vascular complications. In addition, a marked reduction in BMI of over 3 points was observed, which further contributes to the improvement in metabolic profile, inflammatory parameters, and cardiovascular risk.

In summary, the study results demonstrate the multimodal therapeutic potential of semaglutide, with simultaneous effects on glycemia, body weight, inflammation, and renal function, which positions it as a key component in the comprehensive approach to the treatment of type 2 diabetes, especially in patients at increased cardiovascular and nephropathic risk.

4.7. Correlation Analysis

In order to dig deeper into the relations between inflammatory, nephrological, and metabolic biomarkers, a Pearson’s correlation analysis was performed using the statistical software SPSS v.26. Two correlation matrices were constructed—for baseline values and after a 6-month therapeutic course with semaglutide.

This study aims to apply the correlation analysis in a Bulgarian outpatient practice among patients with type 2 diabetes, examining, for the first time, the associations between the following parameters: patient age, diabetes duration, body mass index (BMI), high-sensitivity C-reactive protein (hsCRP), glycated hemoglobin (HbA1c), estimated glomerular filtration rate (eGFR), serum creatinine, and microalbuminuria.

4.8. Correlation Analysis of the Data at the Beginning of GLP-1 RA Therapy

At the initial stage of semaglutide therapy, five statistically significant associations, marked with yellow color, were identified with a confidence level of p ≥ 99% (α = 0.01), as presented in

Table 3. Correlation matrix between biomarkers and clinical parameters at the baseline of semaglutide therapy.

Correlations
		Age	Duration of Diabetes	BMI	hsCRP (mg/L)	eGFR (mL/min 1.73 m2)	Creatinine (µmol/L)	MALB (mg/B)	HbA1c (%)
Age	Pearson’s Correlation	1	0.411 **	−0.222	−0.020	−0.421 **	0.072	−0.043	−0.187
	Sig. (2-tailed)		0.000	0.065	0.872	0.000	0.554	0.725	0.122
Duration of diabetes	Pearson’s Correlation	0.411 **	1	−0.157	−0.118	−0.058	−0.041	−0.023	0.172
	Sig. (2-tailed)	0.000		0.194	0.335	0.635	0.736	0.852	0.154
BMI	Pearson’s Correlation	−0.222	−0.157	1	0.045	−0.058	0.170	−0.011	−0.021
	Sig. (2-tailed)	0.065	0.194		0.711	0.636	0.159	0.927	0.866
hsCRP (mg/L)	Pearson’s Correlation	−0.020	−0.118	0.045	1	−0.294 *	0.354 **	0.035	0.091
	Sig. (2-tailed)	0.872	0.335	0.711		0.014	0.003	0.774	0.456
eGFR (mL/min 1.73 m2)	Pearson’s Correlation	−0.421 **	−0.058	−0.058	−0.294 *	1	−0.776 **	0.193	0.088
	Sig. (2-tailed)	0.000	0.635	0.636	0.014		0.000	0.109	0.467
Creatinine (µmol/L)	Pearson’s Correlation	0.072	−0.041	0.170	0.354 **	−0.776 **	1	−0.078	0.136
	Sig. (2-tailed)	0.554	0.736	0.159	0.003	0.000		0.520	0.263
MALB (mg/L)	Pearson’s Correlation	−0.043	−0.023	−0.011	0.035	0.193	−0.078	1	0.000
	Sig. (2-tailed)	0.725	0.852	0.927	0.774	0.109	0.520		0.998
HbA1c (%)	Pearson’s Correlation	−0.187	0.172	−0.021	0.091	0.088	0.136	0.000	1
	Sig. (2-tailed)	0.122	0.154	0.866	0.456	0.467	0.263	0.998
	N	70	70	70	69	70	70	70	70

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

.

The associations observed during semaglutide therapy were further analyzed using linear correlation analysis based on the following parameters:

R—correlation coefficient, reflecting the strength and direction of the linear relationship between the variables studied (values range from −1 to +1).

R² (R Square)—coefficient of determination, indicating the proportion of variation in the dependent variable explained by the independent variable.

Std. Error of the Estimate—standard error of the estimate; a measure of the accuracy of predictions made by the regression model.

F—F-test value from one-way ANOVA, assessing the overall significance of the regression model.

Sig. (p-value)—level of statistical significance; values below 0.05 are considered statistically significant at α = 0.05.

The results obtained are presented in

Table 4. Associations between clinical parameters and the initiation of semaglutide therapy—correlation analysis.

Parameters	Linear Correlation Dependence	R	R2	Std. Error of the Estimate	F	Sig. (p-Value)
X—Age Y—Duration of diabetes	Y = −6.521 + 0.217 × X	0.411	0.169	4.876	13.842	0.000
X—Age Y—eGFR	Y = 127.618 − 0.716 marked with yellow color × X	−0.421	0.178	15.600	14.681	0.000
X—hsCRP Y—eGFR	Y = 92.236 − 0.803 × X	−0.246	0.061	16.632	3.994	0.050
X—hsCRP Y—Creatinine	Y = 72.099 + 0.971 × X	0.354	0.125	14.224	9.596	0.003
X—eGFR Y—Creatinine	Y = 137.453 − 0.681 × X	−0.776	0.602	9.528	102.796	0.000

.

A moderate positive correlation was observed between age and duration of diabetes (R = 0.411, p = 0.000) (Figure 4a).

A moderate negative correlation was observed between age and eGFR (R = −0.421, p = 0.000) (Figure 4b).

A weak but statistically significant negative correlation was found between hsCRP and eGFR (R = −0.246, p = 0.04), linking systemic inflammation and early renal dysfunction. This is consistent with known pathophysiological mechanisms in which inflammation affects the endothelial function and renal perfusion (Figure 4c).

There was also a moderate positive correlation between hsCRP and serum creatinine (R = 0.354, p = 0.003), supporting the role of inflammation in renal injury. Higher hsCRP values correspond to elevated creatinine, which may reflect both impaired renal function and inflammatory processes (Figure 4d).

A strong negative correlation was observed between eGFR and creatinine (R = −0.776, p = 0.000) (Figure 4e).

Conclusion: Correlation analysis at the initiation of therapy indicates a significant relationship between inflammation and renal function in patients with type 2 diabetes. Higher hsCRP levels are associated with reduced glomerular filtration and increased serum creatinine, supporting an inflammation-mediated mechanism of renal impairment.

4.9. Correlation Analysis of the Data at the End of GLP-1 RA Therapy

During the follow-up after six months of semaglutide therapy, six statistically significant associations among the examined parameters, marked with yellow color, were identified with a confidence level of p ≥ 99% (α = 0.01). The results are presented in

Table 5. Correlation matrix of variables after six months of semaglutide treatment.

Correlations
		Age	Duration of Diabetes	BMI	hsCRP (mg/L)	eGFR (mL/min 1.73 m2)	Creatinine (µmol/L)	MALB (mg/L)	HbA1c (%)
Age	Pearson’s Correlation	1	0.411 **	−0.045	0.058	−0.384 **	0.030	−0.027	0.044
	Sig. (2-tailed)		0.000	0.713	0.632	0.001	0.805	0.821	0.717
Duration of diabetes	Pearson’s Correlation	0.411 **	1	−0.044	0.084	−0.144	0.017	0.031	0.394 **
	Sig. (2-tailed)	0.000		0.720	0.490	0.233	0.889	0.798	0.001
BMI	Pearson’s Correlation	−0.045	−0.044	1	0.179	−0.044	0.108	0.082	0.329 **
	Sig. (2-tailed)	0.713	0.720		0.139	0.716	0.373	0.499	0.005
hsCRP (mg/L)	Pearson’s Correlation	0.058	0.084	0.179	1	−0.137	0.082	0.211	0.233
	Sig. (2-tailed)	0.632	0.490	0.139		0.259	0.499	0.080	0.052
eGFR (mL/min 1.73 m2)	Pearson’s Correlation	−0.384 **	−0.144	−0.044	−0.137	1	−0.759 **	0.247 *	0.060
	Sig. (2-tailed)	0.001	0.233	0.716	0.259		0.000	0.039	0.619
Creatinine (µmol/L)	Pearson’s Correlation	0.030	0.017	0.108	0.082	−0.759 **	1	−0.174	−0.146
	Sig. (2-tailed)	0.805	0.889	0.373	0.499	0.000		0.150	0.227
MALB (mg/L)	Pearson’s Correlation	−0.027	0.031	0.082	0.211	0.247 *	−0.174	1	0.205
	Sig. (2-tailed)	0.821	0.798	0.499	0.080	0.039	0.150		0.088
HbA1c (%)	Pearson’s Correlation	0.044	0.394 **	0.329 **	0.233	0.060	−0.146	0.205	1
	Sig. (2-tailed)	0.717	0.001	0.005	0.052	0.619	0.227	0.088
	N	70	70	70	70	70	70	70	70

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

.

The associations observed during semaglutide therapy were further analyzed using linear correlation analysis. The results obtained are presented in

Table 6. Associations between clinical parameters and the end of semaglutide therapy—correlation analysis.

Parameters	Linear Correlation Dependence	R	R2	Std. Error of the Estimate	F	Sig. (p-Value)
X—Age Y—Duration of diabetes	Y = −6.521 + 0.217 × X	0.411	0.169	4.876	13.842	0.000
X—Age Y—eGFR	Y = 127.809 − 0.618 × X	−0.384	0.148	15.023	11.778	0.001
X—Duration of diabetes Y—HbA1c	Y = 6.032 + 0.089 × X	0.394	0.155	1.104	12.503	0.001
X—BMI Y—HbA1c	Y = 4.067 + 0.069 × X	0.329	0.108	1.134	8.257	0.005
X—Creatinine Y—eGFR	Y = 155.763 − 0.867 × X	−0.759	0.557	10.588	92.614	0.000
X—MALB Y—eGFR	Y = 92.099 + 0.046 × X	0.247	0.061	15.769	4.411	0.039

.

A similar moderate positive correlation was observed between age and duration of diabetes (Figure 5a) (R = 0.411, p = 0.000).

A moderate negative correlation was observed between age and eGFR (Figure 5b) (R = −0.384, Sig. p = 0.001).

A moderate positive correlation was observed between diabetes duration and HbA1c (Figure 5c) (R = 0.394, p = 0.001).

Additionally, a moderate positive correlation was found between BMI after six months of treatment and HbA1c (Figure 5d) (R = 0.329, p = 0.005).

A strong negative correlation was observed between creatinine and eGFR (Figure 5e) (R = −0.759, p = 0.000).

A weak positive correlation was observed between eGFR and microalbuminuria (MALB) (Figure 5f) (R = 0.247, p = 0.039).

Conclusion: In addition to renal improvements, the overall results demonstrate the beneficial effects of semaglutide on cardiovascular status through the reduction in systemic inflammation, improved metabolic control, and a favorable impact on cardiac function. These findings highlight the multifactorial therapeutic potential of semaglutide in patients with type 2 diabetes, contributing both to renal protection and to the reduction in cardiovascular risk.

Results of the Multiple Correlation of hsCRP obtained using the stepwise method.

The multiple correlation shows that BMI and eGFR, marked with yellow color, are the most significant factors for the change in hsCRP at the end of therapy (

Table 7. Multiple regression coefficients.

Coefficients a
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	−0.125	0.873		−0.143	0.887
	BMI	0.068	0.026	0.198	2.607	0.010
2	(Constant)	1.359	1.041		1.305	0.194
	BMI	0.075	0.026	0.217	2.896	0.004
	eGFR	−0.020	0.008	−0.189	−2.524	0.013

^a. Dependent variable: CRP6.

).

hsCRP = 0.075 × BMI − 0.020 × eGFR

The correlation coefficient of the multiple correlation is R = 0.273 (

Table 8. Model summary.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	0.198 a	0.039	0.033	1.99348
2	0.273 b	0.075	0.063	1.96219

^a. Predictors: (Constant), BMI. ^b. Predictors: (Constant), BMI, eGFR.

).

5. Discussion

The present prospective study on the Bulgarian population selection group provides a pivotal contribution to the scientific literature by applying a cross-correlation analysis between inflammatory and renal biomarkers in patients with type 2 diabetes, treated with GLP-1 receptor agonists (semaglutide). Conducted on a Bulgarian population, it is the first of its kind to explore the interaction between inflammation and early markers of kidney damage in a real clinical setting, tracking the dynamics of these relations before and after six months of therapy and supporting the possible role of GLP-1 RA not only as an antidiabetic therapy, but also as a strategic tool in cardiorenal risk management.

5.1. GLP-1 RA in the Context of the Cardiorenal Continuum

Type 2 diabetes mellitus is a disease that impacts multiple organs and systems, with renal and cardiovascular complications being the leading causes of morbidity and mortality. The concept of a close physiopathological link between renal damage and cardiovascular risk—the so-called cardiorenal continuum—in which chronic low-grade inflammation plays a central role, is increasingly gaining traction in scientific circles. In this background, the results of the present study are particularly valuable.

The significant correlations between hsCRP and renal markers (eGFR and creatinine) established at baseline evidence the presence of an inflammatory component, even before the appearance of clinical renal failure. This is supported by an array of medical texts, which refer to hsCRP as a predictor not only of cardiovascular risk, but also of the progression of diabetic nephropathy [26,27]. The moderate positive relationship between hsCRP and serum creatinine (R = 0.341; p = 0.042) in this study proves the early role of systemic inflammation in the impairment of glomerular function. The strongest relation, the negative correlation between eGFR and microalbuminuria (R = −0.768; p < 0.001), confirms the classical pathophysiology of diabetic nephropathy while offering readily available and inexpensive biomarkers for renal risk stratification in outpatient settings.

5.2. Renoprotection and Cardiovascular Risk—The Two Faces of the Therapy with GLP-1 RA

After 6 months of GLP-1 RA therapy, renal function was preserved and even slightly improved, in the absence of progression of microalbuminuria or elevation of the inflammatory marker hsCRP. This points to the potential role of GLP-1 RA in limiting renal inflammation and delaying diabetic nephropathy. The renoprotective effect is of particular importance in the light of cardiovascular risk management, as microalbuminuria and reduced eGFR. The improvement or stabilization of these parameters under the influence of GLP-1 RA can be interpreted as an indirect cardiovascular benefit, which is in line with the results from some large-scale studies (LEADER, REWIND, SUSTAIN 6) [28,29].

The initial values of hsCRP before and the results after 6 months of treatment with semaglutide are similar to those of large clinical studies, such as SUSTAIN 3, PIONEER 1, PIONEER 2, and PIONEER 5. Our study is of a confirmatory nature to these previous ones, which did not require the inclusion of a control group [30].

Therefore, renoprotection in patients with type 2 diabetes should not be considered in isolation, but as part of a comprehensive strategy to reduce cardiovascular events. Our study has provided local, validated data that confirm the applicability of this holistic approach in the Bulgarian population.

5.3. Author Contribution and Clinical Significance

The analysis offers not only theoretical but also practical guidelines for monitoring the effect of GLP-1 RA on cardiovascular risk and progression of chronic kidney disease, through accessible and routinely used parameters.

The study definitively underpins that early identification and control of inflammation, combined with targeted GLP-1 RA therapy, could become a powerful tool for secondary prevention in high-risk patients with type 2 diabetes.

6. Conclusions

The observed simultaneous optimization of glycemic control and reduction in hsCRP, combined with improvement in eGFR and reduction in MALB, suggests a possible direct anti-inflammatory effect of GLP-1 RA. The decrease in hsCRP level—a validated cardiovascular risk marker—in the background of stabilized renal function points to a pronounced cardioprotective effect of the therapy. The data demonstrate that GLP-1 RA has an impact on metabolic, inflammatory, and nephrological parameters, which have the potential to optimize cardiovascular risk management in patients with type 2 diabetes in real-world clinical practice, with the aim of improving their long-term prognosis.

We cannot claim that the stated results could be applied to populations with different genetic or cultural backgrounds.

As the first Bulgarian study of its kind with a cross-correlation analysis of GLP-1 RA therapy, this work makes a significant local contribution to the current knowledge base on cardiorenal protection in type 2 diabetes. The obtained results support the integrated approach to monitoring and therapy, based on multimodal impact—glycemic, anti-inflammatory, and organoprotective.

* Cross-correlation analysis is a statistical method used to measure the relationship between two (or more) variables, taking into account their course over time or under different conditions. Usually, this type of analysis is applied when the researcher wants to make sure whether a change in one variable is associated with a lagged or synchronous change in another, i.e., whether there is a temporal or functional parallel between them.