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Association of triglyceride glucose–body mass index and left ventricular hypertrophy in patients with IgA nephropathy: a retrospective study

European Journal of Medical Research volume 29, Article number: 627 (2024) Cite this article

Abstract

Introduction

IgA nephropathy (IgAN) is one of the most prevalent forms of glomerulonephritis worldwide, particularly affecting 40–50% of the East Asian population. Cardiovascular mortality represents a leading cause of death in patients with IgAN. Left ventricular hypertrophy (LVH) serves as a predictor of heart failure and cardiovascular mortality. Previous studies have indicated that Triglyceride glucose–body mass index (TyG–BMI), a surrogate marker for insulin resistance surrogates, correlated with the development of LVH. However, there is a lack of information available regarding the association between TyG–BMI and LVH in patients with IgAN. This study aims to explore the relationship between TyG–BMI and LVH in this population.

Methods

This retrospective study was conducted in the Fifth Affiliated Hospital of Sun Yat-sen University recruiting inpatients with renal biopsy-confirmed IgAN who were over the age of 18 years. Left ventricular dimensions were assessed through echocardiography. Linear regression and multivariate logistic regression analyses were performed using R language software and SPSS to investigate the association between TyG–BMI levels and LVH risk. Statistical significance was set at p < 0.05.

Results

A total of 327 patients with IgAN were enrolled in this study. Left ventricular mass index (LVMI) was positively correlated with TyG–BMI index (corr. coefficient: 0.453, p < 0.001) and inversely correlated with eGFR (corr. coefficient: -0.392, p < 0.001). After adjusting for age, gender, smoking, alcohol use, hemoglobin, low-density lipoprotein cholesterol, Scr, and urine output, advanced age and higher levels of hemoglobin and Scr were independently associated with increased TyG–BMI (p < 0.05). The odds ratios of the highest quartile of TyG–BMI compared with the lowest quartile were 8.39 (95%CI 1.66–42.39; p = 0.010).

Conclusions

Our findings indicated that the TyG–BMI level was positively correlated with LVMI. A high TyG–BMI level was independently associated with an increased risk of LVH in patients with IgAN. TyG–BMII demonstrated predictive ability for LVH in IgAN patients.

Introduction

IgA nephropathy (IgAN) is one of the most prevalent forms of primary glomerulonephritis worldwide and a major cause of end-stage renal disease among the East Asian population[[1,2]]. Cardiovascular mortality constitutes a leading cause of death in chronic kidney disease (CKD) including IgAN [3].

Left ventricular hypertrophy (LVH), characterized by an increase in left ventricular mass (LVM), is an important predictor of heart failure and cardiovascular mortality, potentially contributing to the high incidence of cardiovascular events in CKD patients [4]. Epidemiological and basic science studies have shown that insulin resistance (IR) had a significant correlation with LVH, progression of CKD, and renal dysfunction [5]. Furthermore, both IR and LVH have been reported to exist in patients with early stage CKD, even when the estimated glomerular filtration rate (eGFR) remains within the normal range [5,6].

Triglyceride glucose–body mass index (TyG–BMI) is calculated as Ln[(1/2 fasting glucose(mg/dL)) × triglycerides (mg/dL)] × weight(kg)/height(m)2. [7] It has been identified as a surrogate marker for IR [8], a central factor of cardiovascular diseases (CVD) including LVH [9]. Several studies have reported an association between TyG–BMI and cerebrovascular [10] and cardiovascular diseases [11,12]. A study focused on hypertensive population indicated that, as a surrogate for IR, TyG–BMI level correlate with the development of LVH [13]. Compelling evidence suggests that a notable elevation in TyG–BMI presents a heightened likelihood of LVH manifestation [13]. Recent studies have explored the application of TyG–BMI in CKD patients [14,15]. One retrospective cohort study [15] investigated the relationship between TyG–BMI and cardiovascular mortality in CKD patients undergoing peritoneal dialysis. Their findings suggest that a higher TyG–BMI level was significantly associated with elevated odds of CVD and all-cause mortality in patients undergoing peritoneal dialysis. As a surrogate marker for IR, TyG–BMI is easy to collect and has a strong connection with LVH. Thus, TyG–BMI is an important and convenient index for the early prevention of LVH in clinical practice. However, the relationship between TyG–BMI and LVH in the CKD population remains unclear. Thus, the present study aimed to explore the underlying association of TyG–BMI and LVH in patients with IgAN.

Materials and methods

Study design and subjects

This retrospective study was conducted in the Fifth Affiliated hospital of Sun Yat-sen University aimed to explore the association between TyG–BMI and LVH in IgAN patients. Inpatients over 18 years with renal biopsy-confirmed IgAN were recruited from January 2019 to December 2023. The exclusion criteria included: 1) endocrine diseases such as diabetes, hyperthyroidism, hypothyroidism, etc.; 2) treatment with corticosteroids or renal replacement therapy prior to admission; 3) treatment with lipid-lowering agents before admission; 4) a history of cardiovascular diseases or heart failure; 5) any form of malignancy; 6) a history of kidney transplantation; 7) severe systemic infections; 8) female were pregnant. Ultimately, 327 patients with IgAN were included in this study.

Clinical data collection

Demographic and baseline characteristics including age, gender, height, weight, blood pressure, past medical history, and smoking/drinking status were collected from the medical records. Participants wore light clothing when measuring their height and weight. Blood pressure was measured in a quiet environment using a standard mercury sphygmomanometer. Fasting venous blood of all individuals was collected for the laboratory examination. 24-h urine specimens were also collected synchronously to analyze the excretion of urinary sodium, potassium, and protein.

Echocardiography measurements

Left ventricular (LV) dimensions were assessed using echocardiography performed by a trained radiologist, following the recommendations of the American Society of Echocardiography. [16]. Two-dimensional guided M-mode echocardiography with 2.25- and 3.5-MHz transducers was performed with a commercially available instrument. LV interior diameter (LVID), interventricular septum (IVS), and posterior wall thickness (PWT) were measured during three cardiac cycles, end-diastolic and systolic as previously reported [17]. According to the American Society of Echocardiography and the European Association of Cardiovascular Imaging Guidelines [18], LVM was calculated by the cube formula: LVM = 0.8 × 1.04 × [(IVS + LVID + PWT)3 − LVID3] + 0.6. LVM was divided by height2.7 to obtain LVM index (LVMI) to reduce the confounding effects of body size [17]. LVH was diagnosed with the criteria of LVMI ≥ 49.2 g/m2.7 in males and 46.7 g/m2.7 in females [19].

Statistical analysis

Of all the subjects, the TyG–BMI levels ranged from 101.8 to 548.7. According to quartiles (Q) of TyG–BMI levels, patients were divided into four groups. For continuous variables, the results are presented as means ± standard deviation (SD) or median (interquartile range). For categorical variables, the results are presented as frequencies and percentages. Non-normally distributed data were logarithmically transformed before statistical analysis. The baseline characteristics between different groups were compared by applying general linear models (GLM) for continuous variables and Pearson’s χ2-test for categorical variables, respectively. The relationship between the two variables was examined using Pearson correlation analysis. Univariate regression analysis was applied to screen the parameters with statistically significant differences. Then, these parameters were included in the multivariate regression for further analysis. The relevant parameters of TyG–BMI were analyzed using a multivariate linear regression model. A multivariate logistic regression model was used to evaluate the association between TyG–BMI levels and LVH risk. The area under the curve (AUC) was calculated by receiver operating characteristic (ROC) curve analysis to evaluate the predictive abilities of the TyG–BMI. Stratification analysis was performed to explore the association between LVH and TyG–BMI levels across different subgroups. R software version 4.3.2 and SPSS version 26 were utilized for the statistical analyses, while figures were generated by GraphPad Prism version 8.0. Statistical significance was set at p < 0.05.

Results

Anthropometric and clinical characteristics of patients with IgAN in different groups

A total of 327 patients with IgAN were enrolled in this study. These anthropometric and clinical characteristics of patients stratified based on the quartiles of the TyG–BMI index are presented in Table 1. The mean age of enrolled patients was 39.37 ± 10.92 years; with 173 (52.91%) were male. It is obviously shown in Table 1 that a higher TyG–BMI index correlates with an increased proportion of males. The levels of TyG index, hemoglobin, serum creatinine, uric acid, urea nitrogen, eGFR, LVM, and LVMI were significantly different among the four groups. Patients in the highest quartile of the TyG–BMI index exhibited higher levels of TyG index, hemoglobin, serum creatinine, uric acid, urea nitrogen, serum potassium, LVM, and LVMI compared to those in the lowest quartile. Conversely, eGFR was statistically higher in the lowest quartile of TyG–BMI index. Furthermore, the proportion of patients with LVH significantly increased in the highest quartile of the TyG–BMI index compared with the lowest quartile.

Table 1 Anthropometric and clinical characteristics of IgAN patients categorized by quartile of TyG–BMI
Full size table

The details of the anthropometric and clinical characteristics for patients, stratified by gender and quartile of TyG–BMI index are shown in Table 2. For both males and females, there is a statistical significance of triglyceride, TyG index, age, LVM, LVMI, and LVH among groups. With increasing TyG–BMI index, the levels of LVM, LVMI and the proportion of LVH exhibited a significantly gradual increase.

Table 2 Anthropometric and clinical characteristics of IgAN patients categorized by quartile of TyG–BMI and gender
Full size table

Relationship analyses

The relationship between the two variables was examined using a bivariate correlation method (Pearson’s correlation). LVMI was positively correlated with the TyG–BMI index (corr. coefficient: 0.453, p < 0.001) (Fig. 1A) and inversely correlated with eGFR (corr. coefficient: − 0.392, p < 0.001) (Fig. 1B). There is no correlation between LVMI and urinary sodium excretion (corr. coefficient: 0.004, p = 0.943) (Fig. 1C). Furthermore, the TyG–BMI index exhibited a weak inverse correlation with eGFR (corr. coefficient: − 0.297, p < 0.001) (Fig. 1D).

Fig. 1
figure 1

Relationship analyses. The correlation of LVMI and TyG–BMI (A), LVMI and eGFR (B), LVMI and urinary sodium (C), TyG–BMI and eGFR (D), respectively

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Factors associated with higher TyG–BMI

The results of multivariate linear regression analysis are shown in Table 3. The results demonstrated that advanced age, higher levels of hemoglobin and Scr were independently associated with higher TyG–BMI after adjusting for age, gender, smoking, alcohol use, hemoglobin, LDL-C, Scr, and urine output (p < 0.05).

Table 3 Clinical association of TyG–BMI and reference parameters
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Predictive value of TyG–BMI

The ROC curve analysis was performed to evaluate the predictive ability of TyG–BMI for LVH in IgAN. For the prediction of LVH, the AUC of TyG–BMI was 0.729 with confidential interval range from 0.654 to 0.805 (see Fig. 2).

Fig. 2
figure 2

Receiver operating characteristic (ROC) curve analyses. ROC curve was applied to predict left ventricular hypertrophy (LVH). AUC, area under the curve

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Odds ratios (ORs) of LVH according to TyG–BMI levels.

The odds ratios (ORs) with a 95% confidence interval (CI) for LVH according to changes in TyG–BMI levels are summarized in Table 4. In the unadjusted model, compared with patients in Q1, the risk of LVH was significantly increased in Q2 [OR (95% CI), 4.93 (1.03–23.58); p = 0.046], Q3 [OR (95% CI), 4.93 (1.03–23.58); p = 0.046] and Q4 [OR (95% CI), 16.84 (3.83–74.13); p < 0.001], respectively. The TyG–BMI in Q4 was markedly associated with an increased risk of LVH after adjusted for age, sex, RAS blocking agents using, smoking and alcohol consumption, diastolic blood pressure, systolic blood pressure, hemoglobin, urine output and eGFR[OR (95% CI), 8.39 (1.66–42.39); p = 0.010].

Table 4 Odds ratios (ORs) of LVH according to TyG–BMI levels
Full size table

Stratification analysis

As the results of the stratification analysis show, there were no significant differences in the association between TyG–BMI levels and LVH among age, gender, and RAS medicine subgroups (All p for interaction > 0.05). However, certain specific groups exhibited a significantly higher risk of developing LVH. For patients aged under 50 years, the risk of LVH was significantly increased in Q4 [OR (95% CI), 5.00 (0.23–109.38); p = 0.030] compared with patients in Q1. Female patients in Q4 demonstrated a significantly increased risk of LVH compared to those in Q1 [OR (95% CI), 17.19 (1.64–180.24); p = 0.018]. In addition, the individuals in Q4 without treatment involving RAS blocking agents also showed a significantly increased risk of LVH compared to those in Q1 [OR (95% CI), 6.32 (1.19–33.54); p = 0.030] (Table 5).

Table 5 Odds ratios of LVH according to TyG–BMI levels in different subgroups
Full size table

Discussion

It has been established that kidneys play a crucial role not only in excreting the end products of metabolism but also in metabolism and endocrine regulation. A multitude of physiological and metabolic disturbances caused by CKD are associated with LVH. As one of the IR surrogates, TyG–BMI has been confirmed to be correlated with CVD including LVH in CKD patients. IgAN has a high prevalence in Asian populations and cardiovascular mortality is the main cause of death in individuals with IgAN. Consequently, preventing the occurrence of cardiovascular disease is of great significance to improving the prognosis of IgAN. Early detection of populations at heightened risk for developing LVH is crucial to mitigate the associated fatalities of IgAN. Our study preliminarily explored the correlation between TyG–BMI and LVH to provide clinical evidence for preventing the occurrence of LVH and reducing the risk of cardiovascular death in patients with IgAN.

Since the TyG–BMI index is calculated as Ln[(1/2 fasting glucose(mg/dL)) × triglycerides (mg/dL)] × weight(kg)/height(m)2, metabolic diseases such as diabetes and hyperthyroidism will have impact on this index. Meanwhile, patients with cardiovascular diseases are more likely to develop LVH. To ensure the accuracy of the research results, we have excluded these patients. In this retrospective study, we scrutinized the links between TyG–BMI and LVH in IgAN patients. Our results show that the age, TyG index, LVM, LVMI, and the proportion of LVH are significantly different according to TyG–BMI levels in IgAN patients. LVM, LVMI levels, and the proportion of LVH gradually increased with rising TyG–BMI levels. Multivariate regression analysis showed that the risk of LVH in patients with the highest TyG–BMI (patients in Q4 group) is significantly increased compared with that in Q1 (p = 0.01). This demonstrated that TyG–BMI is closely associated with LVH in IgAN patients. Meanwhile, an elevated TyG–BMI indicates a higher risk for LVH which aligns with the previous study [13]. In our study, both LVMI and TyG–BMI were found to be increased as the eGFR decreased. It has been previously reported that decline in eGFR is significantly associated with the development of LVH in CKD patients, and LVH was more severe with the progression of CKD [5]. The incidence of LVH is higher in male patients than in females. The previous studies [13,20,21] have indicated that gender differences exist in the LVH incidence. In concordance with our findings, male individuals have been found to be more likely to develop LVH than females in the age range of 20–79.9 years in previous studies [22]. Not in line with the aforementioned results, growing evidence supports an increased likelihood of LVH risk in women especially the female with hypertension [23,24]. The increased risk of LV concentric remodeling in women may be related to the synergistic effect of lipid metabolism and hypertension [13,25]. Thus, further research is needed to understand gender differences in the risk of LVH for IgAN patients. In addition, the stratified analysis showed that for IgAN patients aged over 50, the risk of LVH was significantly increased with significantly elevated TyG–BMI levels. In patients not receiving treatment with RAS blocking agents, those in the highest TyG–BMI group had a significantly higher risk of LVH than other patients.

The factors associated with higher TyG–BMI levels including advanced age, elevated hemoglobin and serum creatinine levels in IgAN patients were identified by applying multivariate linear regression analysis(all p < 0.05) after adjusting for demographics and lifestyle risk factors. This result is consistent with the recent clinical study [15]. Notably, it has been proposed that increased sodium intake is directly correlated with the risk of LVH as reported in the previous studies [26,27,28]. Urinary sodium excretion was found to be significantly associated with greater LVM in healthy young adults and individuals with hypertension [29,30]. Research involving 1556 individuals with type 2 diabetes mellitus revealed that high urinary sodium excretion was independently associated with an increased risk of LVH and CVD [31]. Our study also explored the correlation between urinary sodium excretion and LVH. On the contrary to the previous reports, the results demonstrated that positive correlation between LVMI and TyG–BMI index (corr. coefficient: 0.453, p < 0.001), while LVMI did not correlate with urinary sodium excretion (corr. coefficient: 0.004, p = 0.943). Extensive studies [32,33] have pointed out that obesity and hypertension are the most important determinants of LVH in the general population. Through chronic hemodynamic overload and increased central pressure, elevated blood pressure contributes to the development of LVH [34]. Abnormal lipid metabolism is usually accompanied by insulin resistance which may activate the CD40/CD40L pathway through disruption, inducing the production of multiple potent pro-inflammatory cytokines, which in turn triggers genes related to cardiac inflammation and hypertrophy [35]. Activation of the CD40L pathway also promotes cellular lipid uptake, alters the function and expression of sensitive KATP channels in the myocardium to promote the occurrence of LVH. Moreover, dyslipidemia can inducing the activation of the ERK/MAPK pathway, increasing mRNA expression of AT2 receptors, and activating the sympathetic nervous system, and ultimately leads to cardiac hypertrophy [13,36]. In this study, our data demonstrated that TyG–BMI is positively correlated with LVMI and TyG–BMI is highly relevant to the development of LVH in IgAN patients. There was no significant difference in the occurrence of LVH between patients with and without RAS blocking agents treatment. The reason that caused these results may be the participants included in this study were diagnosed with IGAN at onset which had not yet developed severe hypertensive complications. However, the TyG–BMI may offer a more comprehensive representation of lipids metabolism and IR status of the human body. The patients may suffer from long-term lipid metabolism abnormalities. Therefore, the present study shows that TyG–BMI is independently associated with the development of LVH in patients with IgAN. Importantly, these findings also suggest the applicability of the TyG–BMI index in the early identification of LVH risk in IgAN patients. Moreover, the results emphasized the importance of lipids metabolism and obesity management in developing LVH to reduce the risk of cardiovascular death in IgAN patients. This study revealed that the TyG–BMI is associated with LVH in IgAN patients. However, the relationship between TyG–BMI and LVH in other CKD remains unclear. This is also an important direction in our further research.

Conclusion

In summary, our findings reveal the association between TyG–BMI level and LVH in IgAN patients. TyG–BMI level is positively correlated with LVMI and is independently associated with the increased risk of LVH. This study provided clinical evidence to enhance the value of TyG–BMI in the evaluation of LVH in IgAN. It can be used as an indicator to predict the occurrence of LVH in IgAN patients. It has the potential to serve as a complementary measure of LVH risk in clinical practice and prospective epidemiological studies involving patients with IgAN. A multicenter study is necessary to externally validate the results. Long-term follow-up can be performed to study the correlation between TyG–BMI and cardiovascular death in IgAN patients.

Limitations

There are some limitations in our study that must be expressed. This study is a single-center retrospective study. Although we conducted subgroup analysis and applied multivariable adjustment and subgroup analysis to reduce the impact of confounding factors, the small sample size of the subgroup analysis had an influence on the results. We plan to increase the sample size to optimize the stratified analysis results in further studies. A multicenter study is also planned to enhance the external validity of this study. Meanwhile, we just analyzed the association of TyG–BMI level and LVH and did not explore the underlying association of TyG–BMI level and cardiovascular mortality in patients with IgAN because of the lack of follow-up data. We designed to conduct studies including long-term follow-up data of the IgAN patients to investigate the relationship between TyG–BMI and the risk of cardiovascular mortality.

Data Availability

No datasets were generated or analysed during the current study.

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Funding

This research was supported by the Zhuhai Science and Technology Plan Project (Project No. 2220004000323).

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Author notes

  1. Menglei Jv, Jun Zhang and Yuzhang Han have contributed equally to this work.

Authors and Affiliations

  1. Department of Nephrology, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China

    Menglei Jv, Yuzhang Han & Ye Zhu

  2. Department of Otolaryngology Head and Neck Surgery, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China

    Jun Zhang & Anni Yang

Authors
  1. Menglei Jv
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  4. Anni Yang
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Contributions

AN.Y. and Y.Z. have proposed the study and design study methods. ML.J., J.Z., and AN.Y. collected the data. ML.J. and J.Z. have done the statistical analysis. ML.J., J.Z., and YZ.H. have written the manuscript. Y.Z. have supervised and supported.All authors reviewed the manuscript.

Corresponding authors

Correspondence to Anni Yang or Ye Zhu.

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Ethics approval and consent to participate

Our study was approved by the Ethics Committee of the Fifth Affiliated Hospital of Sun Yat-sen University which is followed the guidelines outlined in the Declaration of Helsinki. An exemption for informed consent was applied and approved by the Ethics Committee, because this retrospective study only involved the clinical data and completed test results without any intervention in the diagnosis and treatment of the patients.

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The authors declare no competing interests.

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Jv, M., Zhang, J., Han, Y. et al. Association of triglyceride glucose–body mass index and left ventricular hypertrophy in patients with IgA nephropathy: a retrospective study. Eur J Med Res 29, 627 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40001-024-02234-3

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European Journal of Medical Research

ISSN: 2047-783X

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