Imaging mass spectrometry analysis reveals an altered lipid distribution pattern in the tubular areas of hyper-IgA murine kidneys

Clinicopathological Characteristics and Outcomes of Immunoglobulin A Nephropathy with Different Types of Dyslipidemia: A Retrospective Single-Center Study

INTRODUCTION

Immunoglobulin A nephropathy (IgAN) is one of the most common glomerulonephritic diseases in the world. Several lines of evidence have suggested that dyslipidemia is related to the disease progression and prognosis of IgAN. However, the study is scarce on the clinicopathological characteristics and outcomes of IgAN with dyslipidemia.

METHODS

This study retrospectively analyzed 234 patients with biopsy-proven idiopathic IgAN at the Department of Nephrology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, between January 2015 and June 2021. The participants were divided into dyslipidemia (n = 119) and non-dyslipidemia (n = 115), and the dyslipidemia group was also divided into the following 4 groups: hypertriglyceridemia group, hypercholesterolemia group, mixed hyperlipidemia group, and low high-density lipoprotein cholesterol group. The estimated glomerular filtration rate (eGFR) was estimated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.

RESULTS

The prevalence of dyslipidemia in IgAN patients in our center was 50.9% (119/234). The patients with dyslipidemia presented with higher systolic blood pressure (BP), diastolic BP, serum creatinine, uric acid, hemoglobin, proteinuria, and eGFR (p < 0.05). Proportions of males, hypertension, and chronic kidney disease stage 2∼5 were also higher in the dyslipidemia group (p < 0.05). Similarly, the pathological characteristics performed were worse in the dyslipidemia group. Most dyslipidemia patients had a higher percentage of mesangial hypercellularity (M1) and tubular atrophy/interstitial fibrosis (T1∼2) in the Oxford Classification's scoring system (p < 0.05). Multivariate logistic regression analysis revealed that male gender (odds ratio [OR] = 2.397, 95% confidence interval [CI]: 1.051-5.469, p = 0.038) and proteinuria (OR = 1.000, 95% CI: 1.000-1.001, p = 0.035) were possible risk factors for dyslipidemia. A total of 13 patients (13.8%) in the dyslipidemia group had an endpoint event, of which 6 patients (6.4%) had a ≥50% decrease in eGFR from baseline and 7 patients (7.4%) reached the end-stage renal disease stage. Kaplan-Meier survival curve analysis showed that patients in the dyslipidemia group had a worse outcome than those in the non-dyslipidemia group (log-rank test, p = 0.048).

CONCLUSIONS

IgAN patients with dyslipidemia presented more severe clinicopathological characteristics. Male gender and proteinuria are significantly associated with the occurrence of dyslipidemia in IgAN patients. Patients in the dyslipidemia group had a worse prognosis than those in the non-dyslipidemia group, which may be essential for the disease management of IgAN and help identify the high-risk patients.

Early detection of unilateral ureteral obstruction by desorption electrospray ionization mass spectrometry

Desorption electrospray ionization mass spectrometry (DESI-MS) is an emerging analytical tool for rapid in situ assessment of metabolomic profiles on tissue sections without tissue pretreatment or labeling. We applied DESI-MS to identify candidate metabolic biomarkers associated with kidney injury at the early stage. DESI-MS was performed on sections of kidneys from 80 mice over a time course following unilateral ureteral obstruction (UUO) and compared to sham controls. A predictive model of renal damage was constructed using the LASSO (least absolute shrinkage and selection operator) method. Levels of lipid and small metabolites were significantly altered and glycerophospholipids comprised a significant fraction of altered species. These changes correlate with altered expression of lipid metabolic genes, with most genes showing decreased expression. However, rapid upregulation of PG(22:6/22:6) level appeared to be a hitherto unknown feature of the metabolic shift observed in UUO. Using LASSO and SAM (significance analysis of microarrays), we identified a set of well-measured metabolites that accurately predicted UUO-induced renal damage that was detectable by 12 h after UUO, prior to apparent histological changes. Thus, DESI-MS could serve as a useful adjunct to histology in identifying renal damage and demonstrates early and broad changes in membrane associated lipids.

Two Specific Sulfatide Species Are Dysregulated during Renal Development in a Mouse Model of Alport Syndrome

Alport syndrome is caused by mutations in collagen IV that alter the morphology of renal glomerular basement membrane. Mutations result in proteinuria, tubulointerstitial fibrosis, and renal failure but the pathogenic mechanisms are not fully understood. Using imaging mass spectrometry, we aimed to determine whether the spatial and/or temporal patterns of renal lipids are perturbed during the development of Alport syndrome in the mouse model. Our results show that most sulfatides are present at similar levels in both the wild-type (WT) and the Alport kidneys, with the exception of two specific sulfatide species, SulfoHex-Cer(d18:2/24:0) and SulfoHex-Cer(d18:2/16:0). In the Alport but not in WT kidneys, the levels of these species mirror the previously described abnormal laminin expression in Alport syndrome. The presence of these sulfatides in renal tubules but not in glomeruli suggests that this specific aberrant lipid pattern may be related to the development of tubulointerstitial fibrosis in Alport disease.

Kidney Lipidomics by Mass Spectrometry Imaging: A Focus on the Glomerulus

Lipid disorders have been associated with glomerulopathies, a distinct type of renal pathologies, such as nephrotic syndrome. Global analyses targeting kidney lipids in this pathophysiologic context have been extensively performed, but most often regardless of the architectural and functional complexity of the kidney. The new developments in mass spectrometry imaging technologies have opened a promising field in localized lipidomic studies focused on this organ. In this article, we revisit the main works having employed the Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF) technology, and the few reports on the use of TOF-Secondary Ion Mass Spectrometry (TOF-SIMS). We also present a first analysis of mouse kidney cortex sections by cluster TOF-SIMS. The latter represents a good option for high resolution lipid imaging when frozen unfixed histological samples are available. The advantages and drawbacks of this developing field are discussed.

Lipid imaging for visualizing cilastatin amelioration of cisplatin-induced nephrotoxicity

Nephrotoxicity is a major limitation to cisplatin antitumor therapies. Cilastatin, an inhibitor of renal dehydropeptidase-I, was recently proposed as a promising nephroprotector against cisplatin toxicity, preventing apoptotic cell death. In this work, cilastatin nephroprotection was further investigated in a rat model, with a focus on its effect on 76 renal lipids altered by cisplatin, including 13 new cisplatin-altered mitochondrial cardiolipin species. Lipid imaging was performed with MALDI mass spectrometry imaging (MALDI-MSI) in kidney sections from treated rats. Cilastatin was proved to significantly diminish the lipid distribution alterations caused by cisplatin, lipid levels being almost completely recovered to those of control samples. The extent of recovery of cisplatin-altered lipids by cilastatin turned out to be relevant for discriminating direct or secondary lipid alterations driven by cisplatin. Lipid peroxidation induced by cisplatin was also shown to be reduced when cilastatin was administered. Importantly, significant groups separation was achieved during multivariate analysis of cortex and outer-medullary lipids, indicating that damaged kidney can be discerned from the nephroprotected and healthy groups and classified according to lipid distribution. Therefore, we propose MALDI-MSI as a powerful potential tool offering multimolecule detection possibilities to visualize and evaluate nephrotoxicity and nephroprotection based on lipid analysis.

Label-free molecular imaging of the kidney

In this review, we will highlight technologies that enable scientists to study the molecular characteristics of tissues and/or cells without the need for antibodies or other labeling techniques. Specifically, we will focus on matrix-assisted laser desorption/ionization imaging mass spectrometry, infrared spectroscopy, and Raman spectroscopy.

Coronary triglyceride deposition in contemporary advanced diabetics

It is of importance to clarify pathophysiology of diabetic heart diseases such as heart failure and coronary artery disease. We reported a novel clinical phenotype called triglyceride deposit cardiomyovasculopathy (TGCV), showing aberrant TG accumulation in both coronary arteries and myocardium, in a cardiac transplant recipient. Here, we examined autopsied diabetics for TG deposition in cardiovasculature. Consecutive series of hearts from advanced diabetes mellitus (DM) subjects (DM group: DMG, n = 20) and those from age- and sex-matched non-diabetic controls (non DM group: NDMG, n = 20) were examined. The diagnostic criteria of 'advanced DM' was made based on 2014 Clinical Practice Recommendations proposed by the American Diabetes Association. The mean duration of DM was 15.8 years. All DMG suffered from heart diseases including coronary artery diseases and 14 subjects had multi-vessel disease. Tissue TG contents were measured biochemically. Coronary arterial TG contents was significantly higher in DMG compared with NDMG. Spatial distribution of TG in transverse sections of coronary arteries showed TG deposition mainly in smooth muscle cells by Imaging Mass Spectrometry. Abundant TG deposition in coronary artery might be associated with advanced DM.

Lipid imaging within the normal rat kidney using silver nanoparticles by matrix-assisted laser desorption/ionization mass spectrometry

The well-characterized cellular and structural components of the kidney show distinct regional compositions and distribution of lipids. In order to more fully analyze the renal lipidome we developed a matrix-assisted laser desorption/ionization mass spectrometry approach for imaging that may be used to pinpoint sites of changes from normal in pathological conditions. This was accomplished by implanting sagittal cryostat rat kidney sections with a stable, quantifiable and reproducible uniform layer of silver using a magnetron sputtering source to form silver nanoparticles. Thirty-eight lipid species including seven ceramides, eight diacylglycerols, 22 triacylglycerols, and cholesterol were detected and imaged in positive ion mode. Thirty-six lipid species consisting of seven sphingomyelins, 10 phosphatidylethanolamines, one phosphatidylglycerol, seven phosphatidylinositols, and 11 sulfatides were imaged in negative ion mode for a total of seventy-four high-resolution lipidome maps of the normal kidney. Thus, our approach is a powerful tool not only for studying structural changes in animal models of disease, but also for diagnosing and tracking stages of disease in human kidney tissue biopsies.

Lipidomics: new insight into kidney disease

Due to the incidence of type-2 diabetes and hypertension, chronic kidney disease (CKD) has emerged as a major public health problem worldwide. CKD results in premature death from accelerated cardiovascular disease and various other complications. Early detection, careful monitoring of renal function, and response to therapeutic intervention are critical for prevention of CKD progression and its complications. Unfortunately, traditional biomarkers of renal function are insufficiently sensitive or specific to detect early stages of disease when therapeutic intervention is most effective. Therefore, more sensitive biomarkers of kidney disease are needed for early diagnosis, monitoring, and effective treatment. CKD results in profound changes in lipid and lipoprotein metabolism that, in turn, contribute to progression of CKD and its cardiovascular complications. Lipids and lipid-derived metabolites play diverse and critically important roles in the structure and function of cells, tissues, and biofluids. Lipidomics is a branch of metabolomics, which encompasses the global study of lipids and their biologic function in health and disease including identification of biomarkers for diagnosis, prognosis, prevention, and therapeutic response for various diseases. This review summarizes recent developments in lipidomics and its application to various kidney diseases including chronic glomerulonephritis, IgA nephropathy, chronic renal failure, renal cell carcinoma, diabetic nephropathy, and acute renal failure in clinical and experimental research. Analytical technologies, data analysis, as well as currently known metabolic biomarkers of kidney diseases are addressed. Future perspectives and potential limitations of lipidomics are discussed.

Diabetic nephropathy induces alterations in the glomerular and tubule lipid profiles

Diabetic nephropathy (DN) is a major life-threatening complication of diabetes. Renal lesions affect glomeruli and tubules, but the pathogenesis is not completely understood. Phospholipids and glycolipids are molecules that carry out multiple cell functions in health and disease, and their role in DN pathogenesis is unknown. We employed high spatial resolution MALDI imaging MS to determine lipid changes in kidneys of eNOS(-/-) db/db mice, a robust model of DN. Phospholipid and glycolipid structures, localization patterns, and relative tissue levels were determined in individual renal glomeruli and tubules without disturbing tissue morphology. A significant increase in the levels of specific glomerular and tubular lipid species from four different classes, i.e., gangliosides, sulfoglycosphingolipids, lysophospholipids, and phosphatidylethanolamines, was detected in diabetic kidneys compared with nondiabetic controls. Inhibition of nonenzymatic oxidative and glycoxidative pathways attenuated the increase in lipid levels and ameliorated renal pathology, even though blood glucose levels remained unchanged. Our data demonstrate that the levels of specific phospho- and glycolipids in glomeruli and/or tubules are associated with diabetic renal pathology. We suggest that hyperglycemia-induced DN pathogenic mechanisms require intermediate oxidative steps that involve specific phospholipid and glycolipid species.

Renopathological Microstructure Visualization from Formalin Fixed Kidney Tissue by Matrix-Assisted Laser/Desorption Ionization-Time-of-Flight Mass Spectrometry Imaging

Understanding early stage renal malfunctions with regard to the glomerular filtration processes is essential for nephropathological prescreening strategies and intervention at an early stage. Mass spectrometry imaging (MSI) in combination with histopathology can provide an universal analytical approach. Proteomic and lipidomic aspects of glomerular biocompositions were applied for micro-structural differentiation in healthy rat kidney samples. Usability of commonly used tissue embedding media and the compatibility of histological staining and fixation methods were of interest. It was demonstrated that ultra-thin tissue samples (500 nm, 1 and 10 μm) can be used for lipid and peptide-based differentiation at the glomerular resolution level in formalin-fixed tissue samples in combination with preceding histological staining for correlating optical and molecular mass images.

Systematization of the protein sequence diversity in enzymes related to secondary metabolic pathways in plants, in the context of big data biology inspired by the KNApSAcK motorcycle database

Biology is increasingly becoming a data-intensive science with the recent progress of the omics fields, e.g. genomics, transcriptomics, proteomics and metabolomics. The species-metabolite relationship database, KNApSAcK Core, has been widely utilized and cited in metabolomics research, and chronological analysis of that research work has helped to reveal recent trends in metabolomics research. To meet the needs of these trends, the KNApSAcK database has been extended by incorporating a secondary metabolic pathway database called Motorcycle DB. We examined the enzyme sequence diversity related to secondary metabolism by means of batch-learning self-organizing maps (BL-SOMs). Initially, we constructed a map by using a big data matrix consisting of the frequencies of all possible dipeptides in the protein sequence segments of plants and bacteria. The enzyme sequence diversity of the secondary metabolic pathways was examined by identifying clusters of segments associated with certain enzyme groups in the resulting map. The extent of diversity of 15 secondary metabolic enzyme groups is discussed. Data-intensive approaches such as BL-SOM applied to big data matrices are needed for systematizing protein sequences. Handling big data has become an inevitable part of biology.

Imaging mass spectrometry: a new tool for kidney disease investigations

Matrix-assisted laser desorption ionization (MALDI)-profiling and imaging mass spectrometry are promising technologies for measuring hundreds of different molecules directly on tissues. For instance, small molecules, drugs and their metabolites, endogenous lipids, carbohydrates and complex peptides/proteins can be measured at the same time without significant disruption of sample integrity. In this review, the potential of MALDI-profiling/imaging technologies in disease proteomics, drug action and studies of cellular processes in the context of kidney tissue is described. Spatial and sequence information obtained in tissue MALDI-profiling/imaging studies can be correlated with other mass spectrometry-based techniques, auxiliary imaging technologies and routine (immuno) histochemical staining.

Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology

Molecular biological data has rapidly increased with the recent progress of the Omics fields, e.g., genomics, transcriptomics, proteomics and metabolomics that necessitates the development of databases and methods for efficient storage, retrieval, integration and analysis of massive data. The present study reviews the usage of KNApSAcK Family DB in metabolomics and related area, discusses several statistical methods for handling multivariate data and shows their application on Indonesian blended herbal medicines (Jamu) as a case study. Exploration using Biplot reveals many plants are rarely utilized while some plants are highly utilized toward specific efficacy. Furthermore, the ingredients of Jamu formulas are modeled using Partial Least Squares Discriminant Analysis (PLS-DA) in order to predict their efficacy. The plants used in each Jamu medicine served as the predictors, whereas the efficacy of each Jamu provided the responses. This model produces 71.6% correct classification in predicting efficacy. Permutation test then is used to determine plants that serve as main ingredients in Jamu formula by evaluating the significance of the PLS-DA coefficients. Next, in order to explain the role of plants that serve as main ingredients in Jamu medicines, information of pharmacological activity of the plants is added to the predictor block. Then N-PLS-DA model, multiway version of PLS-DA, is utilized to handle the three-dimensional array of the predictor block. The resulting N-PLS-DA model reveals that the effects of some pharmacological activities are specific for certain efficacy and the other activities are diverse toward many efficacies. Mathematical modeling introduced in the present study can be utilized in global analysis of big data targeting to reveal the underlying biology.

Mapping of phospholipids by MALDI imaging (MALDI-MSI): realities and expectations

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has emerged as a novel powerful MS methodology that has the ability to generate both molecular and spatial information within a tissue section. Application of this technology as a new type of biochemical lipid microscopy may lead to new discoveries of the lipid metabolism and biomarkers associated with area-specific alterations or damage under stress/disease conditions such as traumatic brain injury or acute lung injury, among others. However there are limitations in the range of what it can detect as compared with liquid chromatography-MS (LC-MS) of a lipid extract from a tissue section. The goal of the current work was to critically consider remarkable new opportunities along with the limitations and approaches for further improvements of MALDI-MSI. Based on our experimental data and assessments, improvements of the spectral and spatial resolution, sensitivity and specificity towards low abundance species of lipids are proposed. This is followed by a review of the current literature, including methodologies that other laboratories have used to overcome these challenges.

[Imaging mass spectrometry]

Matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry (IMS) enables the visualization of the distribution of a range of biomolecules that have varied structures in the cells and tissue sections. This emerging imaging technique was initially developed as a tool for protein imaging, but recently it is increasingly being used for the imaging of small organic molecules. IMS is an effective technique for the imaging of small metabolites, including endogenous metabolites such as lipids and exogenous drugs because of the following advantages: First, IMS does not require any specific labels or probes. Second, IMS is a non-targeted imaging method. Finally, the simultaneous imaging of many types of metabolite molecules is possible, and all these features are necessary for the assessment of metabolite localization. In this review, we discuss the capability of current IMS techniques for imaging small molecules, and introduce representative studies on imaging of endogenous and exogenous metabolites. In addition, the limitations and problems of the technique are also discussed, and reports of progress toward solving the problems with this technique are also introduced.