Lipidomics reveals association of circulating lipids with body mass index and outcomes in IgA nephropathy patients

Abstract

IgA nephropathy (IgAN) is a leading cause of chronic kidney disease (CKD), which are commonly accompanied by dyslipidemia. Obesity is also associated with dyslipidemia and risk of CKD, but the relation of the dyslipidemia patterns with obesity and disease progression in IgAN patients remains unknown. Traditional Chinese medicine (TCM) and the combined treatment with corticosteroids and TCM have been shown to be of benefit for IgAN patients, but predictive markers for guiding these treatments are lacking. Here, we quantified 545 lipid species in the plasma from 196 participants, including 140 IgAN patients and 56 healthy volunteers, and revealed an altered plasma lipidome in IgAN patients as compared to healthy participants. Association analysis showed that a sub-group of glycerides, particularly triacylglycerols (TGs) containing docosahexaenoic acid, were positively associated with high body mass index (BMI) in under- or normal weight IgAN patients, while several free fatty acids and sphingomyelins were positively associated with high BMI in overweight or obese IgAN patients. Further, our study suggested that elevated levels of eight lipids, mainly TG species containing linolenic acid, were independent risk factors for IgAN progression and also reported the prospective association of circulating lipids with treatment outcomes in IgAN. Taken together, our findings may not only help to achieve precision medicine but also provide a knowledge base for dietary intervention in the treatment of IgAN.

Keywords: IgA nephropathy; body mass index; circulating lipids; dyslipidemia; lipidomics; traditional Chinese medicine.

Figure 1

Density plots illustrating the distributions of changes in renal function (12-month follow-up vs. baseline) in patients with IgAN undergoing TCM (n = 50) or CT treatment (n = 54). Kernel density plots of the log₂ transformed ratios of serum albumin (A), eGFR (B), and 24-h urine protein (C) at 12-month follow-up against those at baseline in IgAN patients undergoing TCM (green lines) or CT (red lines) treatment. Dashed lines represent the mean of each group. Blue arrows indicate the direction of improvement.

Figure 2

PCA of lipidomic data. The score plot for the first two principal components (PC1 and PC2) shows the clustering of 56 HCs and 140 IgAN patients. Ellipsoids represent a 95% confidence interval (CI) surrounding each group. Nonparametric two-sided Mann–Whitney U-test was used to analyze significant differences between HC and IgAN groups for PC1 and PC2. Box plots display first and third quartiles, and whiskers extend from each quartile to the minimum or maximum values.

Figure 3

An overview over changes of various lipid classes in the plasma between IgAN patients (n = 140) and HCs (n = 56). (A) Relative abundance of the sum of lipid classes in IgAN samples compared to HC samples. Data represent means ± SEM. P-values were determined by two-tailed Student's t-test. (B and C) IgAN: HC mean ratio of lipid abundance by the carbon number (B) and number of bonds (C) in different lipid classes. Only the lipid classes with the Spearman's rank correlation statistically significant (P < 0.05) are shown.

Figure 4

Associations of circulating lipids with BMI in HCs and IgAN patients. Forest plot of the estimated regression coefficients (95% CI) on the association between top 10 significant lipids and BMI in under- or normal-weight healthy participants (BMI < 24, n = 28) (A), under- or normal-weight IgAN patients (BMI < 24, n = 51) (B), and overweight or obese IgAN patients (BMI ≥ 24, n = 49) (C). Linear regression models were adjusted for gender and baseline age. Association magnitudes are in standardized units of 1-SD BMI per 1-SD lipid concentration. Error bars indicate 95% CIs. *P < 0.05, **P < 0.01, ***P < 0.001.

Figure 5

Association of lipid correlation network modules with demographics and clinical traits. WGCNA groups the lipid species in the plasma of IgAN patients (n = 104) into eight modules. The networks are thresholded at an adjacency of 0.02 (akin weighted correlation of 0.8). The module‒trait associations are shown where the colors correspond to the correlation coefficients (red for positive correlations and blue for negative correlations). Upper values in each cell are correlation coefficients between module eigenlipids (the first principal component) and clinical traits, and lower values are the corresponding P-value (Spearman's rank correlation test). The pink, brown, yellow, and blue modules are significantly (P < 0.05) correlated with clinical traits.

Figure 6

Odds ratios for IgAN progression at 12-month follow-up per 1-SD increase in baseline demographics and clinical characteristics and lipid concentrations (n = 140). (A) Odds ratios of the univariate logistic regression with demographics and clinical characteristics of patients as predictors. (B) Adjusted odds ratios of the multivariable logistic regression with lipid concentrations of patients as predictors. The multivariable logistic model was adjuested for gender, age at baseline, BMI, eGFR at baseline, and treatment. Error bars indicate 95% CIs. *P < 0.05.

Figure 7

Associations of FA composition in different lipid classes with renal outcomes of IgAN patients receiving TCM (A, n = 50) or CT (B, n = 54) treatment. Individual lipid species are depicted as filled circles and arranged by lipid classes in panels. Within each panel, their position is determined by the total number of carbon atoms (x axes) and of double bonds (y axes) in the acyl chain. Circle size indicates the significance level, and circle color indicates the effect size per SD that was calculated using multivariable linear regression.