Proteomic and metabolomic approaches in the search for biomarkers in chronic kidney disease

A comparative urinary proteomic and metabolomic analysis between renal aa amyloidosis and membranous nephropathy with clinicopathologic correlations

Urinary omics has become a powerful tool for elucidating pathophysiology of glomerular diseases. However, no urinary omics analysis has been performed yet on renal AA amyloidosis. Here, we performed a comparative urine proteomic and metabolomic analysis between recently diagnosed renal AA amyloidosis (AA) and membranous nephropathy (MN) patients. Urine samples of 22 (8 AA, 8 MN and 6 healthy control) patients were analyzed with nLC-MS/MS and GC/MS for proteomic and metabolomic studies, respectively. Pathological specimens were scored for glomerulosclerosis and tubulointerstitial fibrosis grades. Functional enrichment analysis between AA and control groups showed enrichment in cell adhesion related sub-domains. Uromodulin (UMOD) was lower, whereas ribonuclease 1 (RNase1) and α-1-microglobulin/bikunin precursor (AMBP) were higher in AA compared to MN group. Correlations were demonstrated between UMOD-proteinuria (r = -0.48, p = 0.03) and AMBP-eGFR (r = -0.69, p = 0.003) variables. Metabolomic analysis showed myo-inositol and urate were higher in AA compared to MN group. A positive correlation was detected between RNase1 and urate independent of eGFR values (r = 0.63, p = 0.01). Enrichment in cell adhesion related domains suggested a possible increased urinary shear stress due to amyloid fibrils. UMOD, AMBP and myo-inositol were related with tubulointerstitial damage, whereas RNase1 and urate were believed to be related with systemic inflammation in AA amyloidosis. SIGNIFICANCE: Urinary omics studies have become a standard tool for biomarker studies. However, no urinary omics analysis has been performed yet on renal AA amyloidosis. Here, we performed a comparative urinary omics analysis between recently diagnosed renal AA amyloidosis (AA), membranous nephropathy (MN) patients and healthy controls. Pathological specimens were scored with glomerulosclerosis (G) and tubulointerstitial fibrosis (IF) grades to consolidate the results of the omics studies and correlation analyzes. Functional enrichment analysis showed enrichment in cell adhesion related sub-domains due to downregulation of cadherins; which could be related with increased urinary shear stress due to amyloid deposition and disruption of tissue micro-architecture. In comparative proteomic analyzes UMOD was lower, whereas RNase1 and AMBP were higher in AA compared to MN group. Whereas in metabolomic analyzes; myo-inositol, urate and maltose were higher in AA compared to MN group. Correlations were demonstrated between UMOD-proteinuria (r = -0.48, p = 0.03), AMBP-eGFR (r = -0.69, p = 0.003) and between RNase1-Urate independent of eGFR values (r = 0.63, p = 0.01). This study is the first comprehensive urinary omics analysis focusing on renal AA Amyloidosis to the best of our knowledge. Based on physiologic roles and clinicopathologic correlations of the molecules; UMOD, AMBP and myo-inositol were related with tubulointerstitial damage, whereas RNase1 and urate were believed to be increased with systemic inflammation and endothelial damage in AA amyloidosis.

Development of a Two-Dimensional Liquid Chromatographic Method for Analysis of Urea Cycle Amino Acids

The urea cycle has been found to be closely associated with certain types of cancers and other diseases such as cardiovascular disease and chronic kidney disease. An analytical method for the precise quantification of urea cycle amino acids (arginine, ornithine, citrulline, and argininosuccinate) by off-line two-dimensional liquid chromatography (2D-LC) combined with fluorescence-based detection was developed. Before analysis, the amino acids were derivatised with 4-fluoro-7-nitro-2,1,3-benzoxadiazole (NBD-F) to obtain NBD-amino acids. The first dimension involved the reversed-phase separation, in which NBD derivatives of urea cycle amino acids were completely separated from each other and mostly separated from the 18 NBD-proteinogenic amino acids. The samples were eluted with stepwise gradient using 0.02% trifluoroacetic acid in water-acetonitrile as the mobile phase. In the second dimension, an amino column was used for the separation of NBD-ornithine, -citrulline, and -argininosuccinate, while a sulfonic acid column was used to separate NBD-arginine. The developed 2D-LC system was used to analyse human plasma samples. The fractions of NBD-urea cycle amino acids obtained in the first dimension were collected manually and introduced into the second dimension. By choosing appropriate mobile phases for the second dimension, each NBD-urea cycle amino acid eluted in the first dimension was well separated from the other proteinogenic amino acids and interference from endogenous substance. This could not be achieved in the first dimension. The urea cycle amino acids in human plasma sample were quantified, and the method was well validated. The calibration curves for each NBD-urea cycle amino acid showed good linearity from 3 (ASA) or 15 (Orn, Cit, and Arg) to 600 nM, with correlation coefficients higher than 0.9969. The intraday and interday precisions were less than 7.9% and 15%, respectively. The 2D-LC system is expected to be useful for understanding the involvement of the urea cycle in disease progression.

Gut-Kidney-Heart: A Novel Trilogy

The microbiota represents a key factor in determining health and disease. Its role in inflammation and immunological disorders is well known, but it is also involved in several complex conditions, ranging from neurological to psychiatric, from gastrointestinal to cardiovascular diseases. It has recently been hypothesized that the gut microbiota may act as an intermediary in the close interaction between kidneys and the cardiovascular system, leading to the conceptualization of the "gut-kidney-heart" axis. In this narrative review, we will discuss the impact of the gut microbiota on each system while also reviewing the available data regarding the axis itself. We will also describe the role of gut metabolites in this complex interplay, as well as potential therapeutical perspectives.

Plasma thrombin-activatable fibrinolysis inhibitor and the 1040C/T polymorphism are risk factors for diabetic kidney disease in Chinese patients with type 2 diabetes

Background

Inflammatory and hemostatic disorders in diabetic microangiopathy (DMA) can be linked to thrombin-activatable fibrinolysis inhibitor (TAFI) and its own gene polymorphisms. Thus, the study aimed to investigate the associations of plasma TAFI and gene polymorphisms with DMA in Chinese patients with type 2 diabetes (T2D).

Methods

Plasma TAFI of 223 patients with T2D was measured, and the genotypes and alleles of the 1040C/T, 438G/A, and 505G/A polymorphisms of the TAFI gene were analyzed. A ROC curve was constructed to evaluate the identifying power of TAFI between patients with T2D and DMA, and logistic regression analysis was used to observe the correlation of plasma TAFI and gene polymorphisms with the risk for DMA.

Results

Plasma TAFI was higher in patients with DMA than in patients with only T2D (p < 0.05). TAFI exhibited the largest area under ROC in identifying diabetic kidney disease (DKD) from only T2D (0.763, 95% CI [0.674-0.853], p < 0.01), and adjusted multivariate analysis showed a high odds ratio (OR: 15.72, 95% CI [4.573-53.987], p < 0.001) for DKD. Higher frequencies of the CT genotype and T allele of the 1040C/T polymorphism were found in DKD compared with only T2D (respectively p < 0.05), and the CT genotype exhibited a high OR (1.623, 95% CI [1.173-2.710], p < 0.05) for DKD. DKD patients with the CT genotype had higher plasma TAFI levels, while T2D and DKD patients with CC/TT genotypes had lower plasma TAFI levels.

Conclusion

Plasma TAFI and the CT genotype and T allele of the 1040C/T polymorphism are independent risk factors for DKD in Chinese T2D patients.

Insulin and the kidneys: a contemporary view on the molecular basis

Insulin is a hormone that is composed of 51 amino acids and structurally organized as a hexamer comprising three heterodimers. Insulin is the central hormone involved in the control of glucose and lipid metabolism, aiding in processes such as body homeostasis and cell growth. Insulin is synthesized as a large preprohormone and has a leader sequence or signal peptide that appears to be responsible for transport to the endoplasmic reticulum membranes. The interaction of insulin with the kidneys is a dynamic and multicenter process, as it acts in multiple sites throughout the nephron. Insulin acts on a range of tissues, from the glomerulus to the renal tubule, by modulating different functions such as glomerular filtration, gluconeogenesis, natriuresis, glucose uptake, regulation of ion transport, and the prevention of apoptosis. On the other hand, there is sufficient evidence showing the insulin receptor's involvement in renal functions and its responsibility for the regulation of glucose homeostasis, which enables us to understand its contribution to the insulin resistance phenomenon and its association with the progression of diabetic kidney disease.

Integrated proteomic and metabolomic profiling of urine of renal anemia patients uncovers the molecular mechanisms of roxadustat

Roxadustat (FG-4592) is a hypoxia-inducible factor prolyl hydroxylase inhibitor (HIF-PHI) prescribed to patients with low hemoglobin associated with chronic kidney disease. Due to the various HIF-mediated adaptive responses, FG-4592 has attracted significant interest for therapeutic use against various diseases. However, the clinical application of Roxadustat remains limited due to a lack of understanding of its underlying mechanisms. Herein, we performed label-free quantitative liquid chromatography with tandem mass spectrometry (LC-MS-MS) proteomics and un-targeted metabolomics to study the protein and metabolite alterations in the urine of renal anemia patients before and after Roxadustat therapy. The results were validated by parallel reaction monitoring (PRM). A total of 46 proteins (including 15 upregulated and 31 downregulated proteins) and 207 metabolites were significantly altered after Roxadustat treatment in urine samples obtained from renal anemia patients. Then, the altered proteins were further validated by PRM. Finally, proteomics combined with metabolomics analysis revealed that the Ras signalling pathway, cysteine and methionine metabolism, arginine and proline metabolism, and cholesterol metabolism were the main pathways altered by Roxadustat treatment. The multi-omics analysis revealed that Roxadustat could alter the protein expression and reverse the potential metabolic changes to exert hypotensive, lipid metabolic regulation, and renoprotective effects in clinical practice.

Albuminuria-Related Genetic Biomarkers: Replication and Predictive Evaluation in Individuals with and without Diabetes from the UK Biobank

Increased albuminuria indicates underlying glomerular pathology and is associated with worse renal disease outcomes, especially in diabetic kidney disease. Many single nucleotide polymorphisms (SNPs), associated with albuminuria, could be potentially useful to construct polygenic risk scores (PRSs) for kidney disease. We investigated the diagnostic accuracy of SNPs, previously associated with albuminuria-related traits, on albuminuria and renal injury in the UK Biobank population, with a particular interest in diabetes. Multivariable logistic regression was used to evaluate the influence of 91 SNPs on urine albumin-to-creatinine ratio (UACR)-related traits and kidney damage (any pathology indicating renal injury), stratifying by diabetes. Weighted PRSs for microalbuminuria and UACR from previous studies were used to calculate the area under the receiver operating characteristic curve (AUROC). CUBN-rs1801239 and DDR1-rs116772905 were associated with all the UACR-derived phenotypes, in both the overall and non-diabetic cohorts, but not with kidney damage. Several SNPs demonstrated different effects in individuals with diabetes compared to those without. SNPs did not improve the AUROC over currently used clinical variables. Many SNPs are associated with UACR or renal injury, suggesting a role in kidney dysfunction, dependent on the presence of diabetes in some cases. However, individual SNPs or PRSs did not improve the diagnostic accuracy for albuminuria or renal injury compared to standard clinical variables.

Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance

BACKGROUND

As a leading cause of chronic kidney disease, clinical demand for noninvasive biomarkers of diabetic kidney disease (DKD) beyond proteinuria is increasing. Metabolomics is a popular method to identify mechanisms and biomarkers. We investigated urinary targeted metabolomics in DKD patients.

METHODS

We conducted a targeted metabolomics study of 26 urinary metabolites in consecutive patients with DKD stage 1 to 5 (n = 208) and healthy controls (n = 26). The relationships between estimated glomerular filtration rate (eGFR) or urine protein-creatinine ratio (UPCR) and metabolites were evaluated. Multivariate Cox analysis was used to estimate relationships between urinary metabolites and the target outcome, end-stage renal disease (ESRD). C statistics and time-dependent receiver operating characteristics (ROC) were used to assess diagnostic validity.

RESULTS

During a median 4.5 years of follow-up, 103 patients (44.0%) progressed to ESRD and 65 (27.8%) died. The median fold changes of nine metabolites belonged to monosaccharide and tricarboxylic acid (TCA) cycle metabolites tended to increase with DKD stage. Myo-inositol, choline, and citrates were correlated with eGFR and choline, while mannose and myo-inositol were correlated with UPCR. Elevated urinary monosaccharide and TCA cycle metabolites showed associations with increased morality and ESRD progression. The predictive power of ESRD progression was high, in the order of choline, myo-inositol, and citrate. Although urinary metabolites alone were less predictive than serum creatinine or UPCR, myo-inositol had additive effect with serum creatinine and UPCR. In time-dependent ROC, myo-inositol was more predictive than UPCR of 1-year ESRD progression prediction.

CONCLUSION

Myo-inositol can be used as an additive biomarker of ESRD progression in DKD.

Unlocking the secrets of the microbiome: exploring the dynamic microbial interplay with humans through metabolomics and their manipulation for synthetic biology applications

Metabolomics is a powerful research discovery tool with the potential to measure hundreds to low thousands of metabolites. In this review, we discuss the application of GC-MS and LC-MS in discovery-based metabolomics research, we define metabolomics workflows and we highlight considerations that need to be addressed in order to generate robust and reproducible data. We stress that metabolomics is now routinely applied across the biological sciences to study microbiomes from relatively simple microbial systems to their complex interactions within consortia in the host and the environment and highlight this in a range of biological species and mammalian systems including humans. However, challenges do still exist that need to be overcome to maximise the potential for metabolomics to help us understanding biological systems. To demonstrate the potential of the approach we discuss the application of metabolomics in two broad research areas: (1) synthetic biology to increase the production of high-value fine chemicals and reduction in secondary by-products and (2) gut microbial interaction with the human host. While burgeoning in importance, the latter is still in its infancy and will benefit from the development of tools to detangle host-gut-microbial interactions and their impact on human health and diseases.

Proteomics profiling of kidney brush border membrane from rats using LC-MS/MS analysis

PURPOSE

Chronic kidney disease (CKD) is defined by a reduced renal function, that is, glomerular filtration rate, and the extent of kidney damage is assessed by determining serum creatinine levels and proteins in urine, diagnosed as proteinuria/albuminuria. Albuminuria increases with age and can result from glomerular and/or proximal tubule (PT) alterations. Brush border membranes (BBMs) on PT cells are important in maintaining the stability of PT functions.

EXPERIMENTAL DESIGN

An LC-MS/MS bottom-up proteomics analysis of BBMs from four groups of rat models was applied to investigate protein abundance alterations associated with CKD progression. Moreover, systems biology analyses were used to identify key proteins that can provide insight into the different regulated molecular pathways and processes associated with CKD.

RESULTS

Our results indicated that 303 proteins showed significantly altered expressions from the severe CKD BBM group when compared to the control. Focusing on renal diseases, several proteins including Ctnnb1, Fah, and Icam1 were annotated to kidney damage and urination disorder. The up-regulation of Ctnnb1 (β-catenin) could contribute to CKD through the regulation of the WNT signaling pathway.

CONCLUSION AND CLINICAL RELEVANCE

Overall, the study of protein abundance changes in BBMs from rat models helps to reveal protein corrections with important pathways and regulator effects involved in CKD. Although this study is focused on rat models, the results provided more information for a deeper insight into possible CKD mechanisms in humans.

Exploration of the anti-hyperuricemia effect of TongFengTangSan (TFTS) by UPLC-Q-TOF/MS-based non-targeted metabonomics

BACKGROUND

TongFengTangSan (TFTS) is a commonly used Tibetan prescription for gout treatment. Previously, TFTS (CF) was confirmed to have a significant uric acid-lowering effect. However, the anti-hyperuricemia mechanisms and the main active fractions remain unclear. The current study aimed to investigate the anti-hyperuricemia mechanism using metabolomics and confirm the active CF fraction.

METHODS

The hyperuricemia model was established through intraperitoneal injection containing 100 mg/kg potassium oxonate and 150 mg/kg hypoxanthine by gavage. We used serum uric acid (sUA), creatinine (CRE), blood urea nitrogen (BUN), xanthine oxidase (XOD) activity, interleukin-6 (IL-6) and interleukin-1β (IL-1β) as indicators to evaluate the efficacy of CF and the four fractions (SX, CF30, CF60, and CF90). The anti-hyperuricemia mechanism of CF was considered through non-targeted metabolomics depending on the UPLC-Q-TOF-MS technology. Principle component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) helped explore the potential biomarkers in hyperuricemia. Moreover, the differential metabolites and metabolic pathways regulated by CF and four fractions were also assessed.

RESULTS

CF revealed a significant anti-hyperuricemia effect by down-regulating the level of sUA, sCRE, sIL-1β, and XOD. SX, CF30, CF60, and CF90 differed in the anti-hyperuricemia effect. Only CF60 significantly lowered the sUA level among the four fractions, and it could be the main efficacy fraction of TFTS. Forty-three differential metabolites were identified in hyperuricemia rats from plasma and kidney. Pathway analysis demonstrated that seven pathways were disrupted among hyperuricemia rats. CF reversed 19 metabolites in hyperuricemia rats and exerted an anti-hyperuricemia effect by regulating purine metabolism. CF60 was the main active fraction of TFTS and exerted a similar effect of CF by regulating purine metabolism.

CONCLUSIONS

CF and CF60 could exert an anti-hyperuricemia effect by regulating the abnormal purine metabolism because of hyperuricemia while improving intestinal and renal function. CF60 could be the main active fraction of TFTS.

Associations of serum amino acids related to urea cycle with risk of chronic kidney disease in Chinese with type 2 diabetes

OBJECTIVE

Serum levels of amino acids related to urea cycle are associated with risk of type 2 diabetes mellitus (T2DM). Our study aimed to explore whether serum levels of amino acids related to urea cycle, i.e., arginine, citrulline, and ornithine, are also associated with increased risk of chronic kidney disease (CKD) in T2DM.

METHODS

We extracted medical records of 1032 consecutive patients with T2DM from the Electronic Administrative System of Liaoning Medical University First Affiliated Hospital (LMUFAH) system from May 2015 to August 2016. Of them, 855 patients with completed data available were used in the analysis. CKD was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m². Serum amino acids were measured by mass spectrometry (MS) technology. Binary logistic regression was performed to obtain odds ratios (ORs) and their 95% confidence intervals (CIs).

RESULTS

52.3% of the 855 T2DM patients were male, and 143 had CKD. In univariable analysis, high serum citrulline, high ratio of arginine to ornithine, and low ratio of ornithine to citrulline were associated with markedly increased risk of CKD (OR of top vs. bottom tertile: 2.87, 95%CI, 1.79-4.62 & 1.98, 95%CI,1.25-3.14 & 2.56, 95%CI, 1.61-4.07, respectively). In multivariable analysis, the ORs of citrulline and ornithine/citrulline ratio for CKD remained significant (OR of top vs. bottom tertile: 2.22, 95%CI, 1.29-3.82 & 2.24, 1.29-3.87, respectively).

CONCLUSIONS

In Chinese patients with T2DM, high citrulline and low ornithine/citrulline ratio were associated with increased risk of CKD.

Molecular Pathways of Diabetic Kidney Disease Inferred from Proteomics

Diabetic kidney disease (DKD) affects an estimated 20-40% of type 2 diabetes patients and is among the most prevalent microvascular complications in this patient population, contributing to high morbidity and mortality rates. Currently, changes in albuminuria status are thought to be a primary indicator of the onset or progression of DKD, yet progressive nephropathy and renal impairment can occur in certain diabetic individuals who exhibit normal urinary albumin levels, emphasizing the lack of sensitivity and specificity associated with the use of albuminuria as a biomarker for detecting diabetic kidney disease and predicting DKD risk. According to the study, a non-invasive method for early detection or prediction of DKD may involve combining proteomic analytical techniques such second generation sequencing, mass spectrometry, two-dimensional gel electrophoresis, and other advanced system biology algorithms. Another category of proteins of relevance may now be provided by renal tissue biomarkers. The establishment of reliable proteomic biomarkers of DKD represents a novel approach to improving the diagnosis, prognostic evaluation, and treatment of affected patients. In the present review, a series of protein biomarkers that have been characterized to date are discussed, offering a theoretical foundation for future efforts to aid patients suffering from this debilitating microvascular complication.

Nuclear Magnetic Resonance Metabolomic Profiling and Urine Chemistries in Incident Kidney Stone Formers Compared with Controls

BACKGROUND

The urine metabolites and chemistries that contribute to kidney stone formation are not fully understood. This study examined differences between the urine metabolic and chemistries profiles of first-time stone formers and controls.

METHODS

High-resolution 1H-nuclear magnetic resonance (NMR) spectroscopy-based metabolomic analysis was performed in 24-hour urine samples from a prospective cohort of 418 first-time symptomatic kidney stone formers and 440 controls. In total, 48 NMR-quantified metabolites in addition to 12 standard urine chemistries were assayed. Analysis of covariance was used to determine the association of stone former status with urine metabolites or chemistries after adjusting for age and sex and correcting for the false discovery rate. Gradient-boosted machine methods with nested cross-validation were applied to predict stone former status.

RESULTS

Among the standard urine chemistries, stone formers had lower urine oxalate and potassium and higher urine calcium, phosphate, and creatinine. Among NMR urine metabolites, stone formers had lower hippuric acid, trigonelline, 2-furoylglycine, imidazole, and citrate and higher creatine and alanine. A cross-validated model using urine chemistries, age, and sex yielded a mean AUC of 0.76 (95% CI, 0.73 to 0.79). A cross-validated model using urine chemistries, NMR-quantified metabolites, age, and sex did not meaningfully improve the discrimination (mean AUC, 0.78; 95% CI, 0.75 to 0.81). In this combined model, among the top ten discriminating features, four were urine chemistries and six NMR-quantified metabolites.

CONCLUSIONS

Although NMR-quantified metabolites did not improve discrimination, several urine metabolic profiles were identified that may improve understanding of kidney stone pathogenesis.

TMAO as a potential biomarker and therapeutic target for chronic kidney disease: A review

The gut microbiota and its metabolites have become a hotspot of recent research. Trimethylamine N-oxide (TMAO) metabolized by the gut microbiota is closely related to many diseases such as cardiovascular disease, chronic kidney disease, type 2 diabetes, etc. Chronic kidney disease (CKD) is an important contributor to morbidity and mortality from non-communicable diseases. Recently, increasing focus has been put on the role of TMAO in the development and progress of chronic kidney disease. The level of TMAO in patients with chronic kidney disease is significantly increased, and a high level of TMAO deteriorates chronic kidney disease. This article describes the relationship between TMAO and chronic kidney disease and the research progress of drugs targeted TMAO, providing a reference for the development of anti-chronic kidney disease drugs targeted TMAO.

Analysis of chronic kidney disease patients by targeted next-generation sequencing identifies novel variants in kidney-related genes

Despite the enormous economic and societal burden of chronic kidney disease (CKD), its pathogenesis remains elusive, impeding specific diagnosis and targeted therapy. Herein, we sought to elucidate the genetic causes of end-stage renal disease (ESRD) and identify genetic variants associated with CKD and related traits in Saudi kidney disease patients. We applied a genetic testing approach using a targeted next-generation sequencing gene panel including 102 genes causative or associated with CKD. A total of 1,098 Saudi participants were recruited for the study, including 534 patients with ESRD and 564 healthy controls. The pre-validated NGS panel was utilized to screen for genetic variants, and then, statistical analysis was conducted to test for associations. The NGS panel revealed 7,225 variants in 102 sequenced genes. Cases had a significantly higher number of confirmed pathogenic variants as classified by the ClinVar database than controls (i.e., individuals with at least one allele of a confirmed pathogenic variant that is associated with CKD; 279 (0.52) vs. 258 (0.45); p-value = 0.03). A total of 13 genetic variants were found to be significantly associated with ESRD in PLCE1, CLCN5, ATP6V1B1, LAMB2, INVS, FRAS1, C5orf42, SLC12A3, COL4A6, SLC3A1, RET, WNK1, and BICC1, including four novel variants that were not previously reported in any other population. Furthermore, studies are necessary to validate these associations in a larger sample size and among individuals of different ethnic groups.

Harnessing the Full Potential of Multi-Omic Analyses to Advance the Study and Treatment of Chronic Kidney Disease

Chronic kidney disease (CKD) was the 12th leading cause of death globally in 2017 with the prevalence of CKD estimated at ~9%. Early detection and intervention for CKD may improve patient outcomes, but standard testing approaches even in developed countries do not facilitate identification of patients at high risk of developing CKD, nor those progressing to end-stage kidney disease (ESKD). Recent advances in CKD research are moving towards a more personalised approach for CKD. Heritability for CKD ranges from 30% to 75%, yet identified genetic risk factors account for only a small proportion of the inherited contribution to CKD. More in depth analysis of genomic sequencing data in large cohorts is revealing new genetic risk factors for common diagnoses of CKD and providing novel diagnoses for rare forms of CKD. Multi-omic approaches are now being harnessed to improve our understanding of CKD and explain some of the so-called 'missing heritability'. The most common omic analyses employed for CKD are genomics, epigenomics, transcriptomics, metabolomics, proteomics and phenomics. While each of these omics have been reviewed individually, considering integrated multi-omic analysis offers considerable scope to improve our understanding and treatment of CKD. This narrative review summarises current understanding of multi-omic research alongside recent experimental and analytical approaches, discusses current challenges and future perspectives, and offers new insights for CKD.

Advances in the Progression and Prognosis Biomarkers of Chronic Kidney Disease

Chronic kidney disease (CKD) is one of the increasingly serious public health concerns worldwide; the global burden of CKD is increasingly due to high morbidity and mortality. At present, there are three key problems in the clinical treatment and management of CKD. First, the current diagnostic indicators, such as proteinuria and serum creatinine, are greatly interfered by the physiological conditions of patients, and the changes in the indicator level are not synchronized with renal damage. Second, the established diagnosis of suspected CKD still depends on biopsy, which is not suitable for contraindication patients, is also traumatic, and is not sensitive to early progression. Finally, the prognosis of CKD is affected by many factors; hence, it is ineviatble to develop effective biomarkers to predict CKD prognosis and improve the prognosis through early intervention. Accurate progression monitoring and prognosis improvement of CKD are extremely significant for improving the clinical treatment and management of CKD and reducing the social burden. Therefore, biomarkers reported in recent years, which could play important roles in accurate progression monitoring and prognosis improvement of CKD, were concluded and highlighted in this review article that aims to provide a reference for both the construction of CKD precision therapy system and the pharmaceutical research and development.

Kynurenine pathway in kidney diseases

Kidney diseases have become one of the most common health care problems. Due to a growing number of advanced aged patients with concomitant disorders the prevalence of these diseases will increase over the coming decades. Despite available laboratory tests, accurate and rapid diagnosis of renal dysfunction has yet to be realized, and prognosis is uncertain. Moreover, data on diagnostic and prognostic markers in kidney diseases are lacking. The kynurenine (KYN) pathway is one of the routes of tryptophan (Trp) degradation, with biologically active substances presenting ambiguous properties. The KYN pathway is known to be highly dependent on immunological system activity. As the kidneys are one of the main organs involved in the formation, degradation and excretion of Trp end products, pathologies involving the kidneys result in KYN pathway activity disturbances. This review aims to summarize changes in the KYN pathway observed in the most common kidney disease, chronic kidney disease (CKD), with a special focus on diabetic kidney disease, acute kidney injury (AKI), glomerulonephritis and kidney graft function monitoring. Additionally, the importance of KYN pathway activity in kidney cancer pathogenesis is discussed, as are available pharmacological agents affecting KYN pathway activity in the kidney. Despite limited clinical data, the KYN pathway appears to be a promising target in the diagnosis and prognosis of kidney diseases. Modulation of KYN pathway activity by pharmacological agents should be considered in the treatment of kidney diseases.

Role of Transcription Factor 7 like 2 and Silent Information Regulator 1 Genes in the Development of Cardiovascular Complications in a Group of Egyptian Patients with Chronic Kidney Disease

BACKGROUND: Sirtuins silent information regulator 1 (SIRT) is histone deacetylases that act as antioxidants and involved in the pathogenesis of cardiovascular diseases (CVD) which are the major complications of chronic kidney disease (CKD). Transcription factor 7-like 2 (TCF7L2) genetic polymorphisms could contribute to the risk of CVD as TCF7L2 proteins regulate vascular remodeling. AIM: We tried to demonstrate the role of genetic polymorphisms: rs7069102 and rs10823108 in SIRT1 gene and rs7903146 in TCF7L2 gene in the development of CVD in CKD Egyptian patients. METHODS: This study included 120 CKD patients (60 with CVD and 60 without CVD) and 60 age and sex-matched healthy subjects as a control group. Routine laboratory investigations were performed and genotyping for candidate single nucleotide polymorphisms was done by Taqman-real-time polymerase chain reaction. RESULTS: The frequency of the C allele of rs7069102 was significantly higher in CKD patients with CVD as compared to the normal control group (p < 0.001) and as compared to CKD patients without CVD (p < 0.001). Percentages of AG and GG genotypes of rs10823108 were significantly higher in CKD patients with CVD as compared to the normal control group (p = 0.002, 0.035, respectively). The frequency of the T allele of rs7903146 was significantly higher in CKD patients with CVD as compared to the normal control group (p < 0.001). CONCLUSION: We found that C allele of rs7069102, GG and AG genotypes of rs10823108 in the SIRT1 gene and T allele of rs7903146 in TCF7L2 gene have a potential role in the pathogenesis and the risk of CVD development in CKD Egyptian patients.

Role of uromodulin and complement activation in the progression of kidney disease

Uromodulin (UMOD) is a glycoprotein that is selectively expressed on the epithelial cells of the thick ascending limb of Henle's loop and the early distal renal tubule. The present study aimed to investigate whether UMOD was associated with complement activation in patients with renal diseases. In addition, its biological function was examined in vitro. The expression levels of UMOD and complement components, including C1q, C3, C4 and C3a, and membrane attack complex (MAC) in the plasma of patients with IgA nephropathy (IgAN; n=58) and lupus nephritis (LN; n=36) were detected using ELISA, which was used to determine the association between UMOD expression and complement components. In addition, a simulated hypoxia-reoxygenation (H/R) model was used to stimulate UMOD expression in mouse inner medullary collecting duct cells. Additionally, the association between UMOD expression and complement components C1q and C3d at the cellular level was identified using western blotting and immunofluorescence, respectively. It was revealed that the plasma UMOD concentration was significantly decreased in patients with IgAN and LN compared with in healthy controls, and the levels of C3a and MAC were significantly increased in the plasma of patients with IgAN and LN. Furthermore, the plasma levels of C1q, C3 and C4 in patients with LN, but not in patients with IgAN, were significantly decreased compared with in healthy controls. The plasma levels of UMOD were negatively correlated with the plasma C3a and MAC concentrations. However, the plasma levels of UMOD were significantly and positively correlated with the plasma C1q concentration, but not with that of C3 and C4. It was identified that UMOD expression started to increase after 1 h of simulated H/R, and continued to increase at 6 and 12 h. In addition, cells with lower UMOD expression had higher C3d expression in vitro. Collectively, the present results suggested that UMOD was associated with severe complement activation and may be involved in complement-mediated immune protection by inhibiting complement activation in renal disease.

Altered O-glycomes of Renal Brush-Border Membrane in Model Rats with Chronic Kidney Diseases

Chronic kidney disease (CKD) is defined as a decrease in renal function or glomerular filtration rate (GFR), and proteinuria is often present. Proteinuria increases with age and can be caused by glomerular and/or proximal tubule (PT) alterations. PT cells have an apical brush border membrane (BBM), which is a highly dynamic, organized, and specialized membrane region containing multiple glycoproteins required for its functions including regulating uptake, secretion, and signaling dependent upon the physiologic state. PT disorders contribute to the dysfunction observed in CKD. Many glycoprotein functions have been attributed to their N- and O-glycans, which are highly regulated and complex. In this study, the O-glycans present in rat BBMs from animals with different levels of kidney disease and proteinuria were characterized and analyzed using liquid chromatography tandem mass spectrometry (LC–MS/MS). A principal component analysis (PCA) documented that each group has distinct O-glycan distributions. Higher fucosylation levels were observed in the CKD and diabetic groups, which may contribute to PT dysfunction by altering physiologic glycoprotein interactions. Fucosylated O-glycans such as 1-1-1-0 exhibited higher abundance in the severe proteinuric groups. These glycomic results revealed that differential O-glycan expressions in CKD progressions has the potential to define the mechanism of proteinuria in kidney disease and to identify potential therapeutic interventions.

Novel biomarkers of inflammation, kidney function and chronic kidney disease in the general population

BACKGROUND

Inflammatory processes have been implicated in the development of chronic kidney disease (CKD). We investigated the association of a large panel of inflammatory biomarkers reflecting aspects of immunity with kidney function and CKD incidence.

METHODS

We used data from two independent population-based studies, KORA F4 (discovery, n = 1,110, mean age 70.3 years, 48.7% male) and ESTHER (replication, n = 1,672, mean age 61.9 years, 43.6% male). Serum levels of biomarkers were measured using proximity extension assay technology. The association of biomarkers with estimated glomerular filtration rate (eGFR) at baseline and with incident CKD was investigated using linear and logistic regression models adjusted for cardiorenal risk factors. Independent results from prospective analyses of both studies were pooled. The significance level was corrected for multiple testing by false-discovery rate (PFDR < 0.05.).

RESULTS

In the KORA F4 discovery study, 52 out of 71 inflammatory biomarkers were inversely associated with eGFR estimated based on serum creatinine. Top biomarkers included CD40, TNFRSF9 and IL10RB. Forty-two of these 52 biomarkers were replicated in the ESTHER study. Nine of the 42 biomarkers were associated with incident CKD independently of cardiorenal risk factors in the meta-analysis of the KORA (n = 142, mean follow-up of 6.5 years) and ESTHER (n = 103, mean follow-up of 8 years) studies. Pathway analysis revealed the involvement of inflammatory and immunomodulatory processes reflecting cross-communication of innate and adaptive immune cells.

CONCLUSIONS

Novel and known biomarkers of inflammation were reproducibly associated with kidney function. Future studies should investigate their clinical utility and underlying molecular mechanisms in independent cohorts.

Classification of Chronic Kidney Disease in Sonography Using the GLCM and Artificial Neural Network

Chronic kidney disease (CKD) can be treated if it is detected early, but as the disease progresses, recovery becomes impossible. Eventually, renal replacement therapy such as transplantation or dialysis is necessary. Ultrasound is a test method with which to diagnose kidney cancer, inflammatory disease, nodular disease, chronic kidney disease, etc. It is used to determine the degree of inflammation using information such as the kidney size and internal echo characteristics. The degree of the progression of chronic kidney disease in the current clinical trial is based on the value of the glomerular filtration rate. However, changes in the degree of inflammation and disease can even be observed with ultrasound. In this study, from a total of 741 images, 251 normal kidney images, 328 mild and moderate CKD images, and 162 severe CKD images were tested. In order to diagnose CKD in clinical practice, three ROIs were set: the cortex of the kidney, the boundary between the cortex and medulla, and the medulla, which are areas examined to obtain information from ultrasound images. Parameters were extracted from each ROI using the GLCM algorithm, which is widely used in ultrasound image analysis. When each parameter was extracted from the three areas, a total of 57 GLCM parameters were extracted. Finally, a total of 58 parameters were used by adding information on the size of the kidney, which is important for the diagnosis of chronic kidney disease. The artificial neural network (ANN) was composed of 58 input parameters, 10 hidden layers, and 3 output layers (normal, mild and moderate CKD, and severe CKD). Using the ANN model, the final classification rate was 95.4%, the epoch needed for training was 38 times, and the misclassification rate was 4.6%.

Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease

Urinary proteomics studies have primarily focused on identifying markers of chronic kidney disease (CKD) progression. Here, we aimed to determine urinary markers of CKD renal parenchymal injury through proteomics analysis in animal kidney tissues and cells and in the urine of patients with CKD. Label-free quantitative proteomics analysis based on liquid chromatography-tandem mass spectrometry was performed on urine samples obtained from 6 normal controls and 9, 11, and 10 patients with CKD stages 1, 3, and 5, respectively, and on kidney tissue samples from a rat CKD model by 5/6 nephrectomy. Tandem mass tag-based quantitative proteomics analysis was performed for glomerular endothelial cells (GECs) and proximal tubular epithelial cells (PTECs) before and after inducing 24-h hypoxia injury. Upon hierarchical clustering, out of 858 differentially expressed proteins (DEPs) in the urine of CKD patients, the levels of 416 decreased and 403 increased sequentially according to the disease stage, respectively. Among 2965 DEPs across 5/6 nephrectomized and sham-operated rat kidney tissues, 86 DEPs showed same expression patterns in the urine and kidney tissue. After cross-validation with two external animal proteome data sets, 38 DEPs were organized; only ten DEPs, including serotransferrin, gelsolin, poly ADP-ribose polymerase 1, neuroblast differentiation-associated protein AHNAK, microtubule-associated protein 4, galectin-1, protein S, thymosin beta-4, myristoylated alanine-rich C-kinase substrate, and vimentin, were finalized by screening human GECs and PTECs data. Among these ten potential candidates for universal CKD marker, validation analyses for protein S and galectin-1 were conducted. Galectin-1 was observed to have a significant inverse correlation with renal function as well as higher expression in glomerulus with chronic injury than protein S. This constitutes the first multisample proteomics study for identifying key renal-expressed proteins associated with CKD progression. The discovered proteins represent potential markers of chronic renal cell and tissue damage and candidate contributors to CKD pathophysiology.

Plasma metabolites associated with chronic kidney disease and renal function in adults from the Baltimore Longitudinal Study of Aging

INTRODUCTION

Chronic kidney disease (CKD) is an important cause of disability and death, but its pathogenesis is poorly understood. Plasma metabolites can provide insights into underlying processes associated with CKD.

OBJECTIVES

To clarify the relationship of plasma metabolites with CKD and renal function in human.

METHODS

We used a targeted metabolomics approach to characterize the relationship of 450 plasma metabolites with CKD and estimated glomerular filtration rate (eGFR) in 616 adults, aged 38-94 years, who participated in the Baltimore Longitudinal Study of Aging.

RESULTS

There were 74 (12.0%) adults with CKD. Carnitine, acetylcarnitine, propionylcarnitine, butyrylcarnitine, trigonelline, trimethylamine N-oxide (TMAO), 1-methylhistidine, citrulline, homoarginine, homocysteine, sarcosine, symmetric dimethylarginine, aspartate, phenylalanine, taurodeoxycholic acid, 3-indolepropionic acid, phosphatidylcholines (PC).aa.C40:2, PC.aa.C40:3, PC.ae.C40:6, triglycerides (TG) 20:4/36:3, TG 20:4/36:4, and choline were associated with higher odds of CKD in multivariable analyses adjusting for potential confounders and using a false discovery rate (FDR) to address multiple testing. Six acylcarnitines, trigonelline, TMAO, 18 amino acids and biogenic amines, taurodeoxycholic acid, hexoses, cholesteryl esters 22:6, dehydroepiandrosterone sulfate, 3-indolepropionic acid, 2 PCs, 17 TGs, and choline were negatively associated with eGFR, and hippuric acid was positively associated with eGFR in multivariable analyses adjusting for potential confounders and using a FDR approach.

CONCLUSION

The metabolites associated with CKD and reduced eGFR suggest that several pathways, such as the urea cycle, the arginine-nitric oxide pathway, the polyamine pathway, and short chain acylcarnitine metabolism are altered in adults with CKD and impaired renal function.

New Potential Biomarkers for Chronic Kidney Disease Management-A Review of the Literature

The prevalence of chronic kidney disease (CKD) is increasing worldwide, and the mortality rate continues to be unacceptably high. The biomarkers currently used in clinical practice are considered relevant when there is already significant renal impairment compromising the early use of potentially successful therapeutic interventions. More sensitive and specific biomarkers to detect CKD earlier on and improve patients' prognoses are an important unmet medical need. The aim of this review is to summarize the recent literature on new promising early CKD biomarkers of renal function, tubular lesions, endothelial dysfunction and inflammation, and on the auspicious findings from metabolomic studies in this field. Most of the studied biomarkers require further validation in large studies and in a broad range of populations in order to be implemented into routine CKD management. A panel of biomarkers, including earlier biomarkers of renal damage, seems to be a reasonable approach to be applied in clinical practice to allow earlier diagnosis and better disease characterization based on the underlying etiologic process.

A Targeted Multiomics Approach to Identify Biomarkers Associated with Rapid eGFR Decline in Type 1 Diabetes

BACKGROUND

Individuals with type 1 diabetes (T1D) demonstrate varied trajectories of estimated glomerular filtration rate (eGFR) decline. The molecular pathways underlying rapid eGFR decline in T1D are poorly understood, and individual-level risk of rapid eGFR decline is difficult to predict.

METHODS

We designed a case-control study with multiple exposure measurements nested within 4 well-characterized T1D cohorts (FinnDiane, Steno, EDC, and CACTI) to identify biomarkers associated with rapid eGFR decline. Here, we report the rationale for and design of these studies as well as results of models testing associations of clinical characteristics with rapid eGFR decline in the study population, upon which "omics" studies will be built. Cases (n = 535) and controls (n = 895) were defined as having an annual eGFR decline of ≥3 and <1 mL/min/1.73 m2, respectively. Associations of demographic and clinical variables with rapid eGFR decline were tested using logistic regression, and prediction was evaluated using area under the curve (AUC) statistics. Targeted metabolomics, lipidomics, and proteomics are being performed using high-resolution mass-spectrometry techniques.

RESULTS

At baseline, the mean age was 43 years, diabetes duration was 27 years, eGFR was 94 mL/min/1.73 m2, and 62% of participants were normoalbuminuric. Over 7.6-year median follow-up, the mean annual change in eGFR in cases and controls was -5.7 and 0.6 mL/min/1.73 m2, respectively. Younger age, longer diabetes duration, and higher baseline HbA1c, urine albumin-creatinine ratio, and eGFR were significantly associated with rapid eGFR decline. The cross-validated AUC for the predictive model incorporating these variables plus sex and mean arterial blood pressure was 0.74 (95% CI: 0.68-0.79; p < 0.001).

CONCLUSION

Known risk factors provide moderate discrimination of rapid eGFR decline. Identification of blood and urine biomarkers associated with rapid eGFR decline in T1D using targeted omics strategies may provide insight into disease mechanisms and improve upon clinical predictive models using traditional risk factors.

Exploring Metabolic Signature of Protein Energy Wasting in Hemodialysis Patients

End-stage renal disease patients undergoing maintenance hemodialysis (HD) are vulnerable to the protein energy wasting (PEW) syndrome. Identification and diagnosis of PEW relies on clinical processes of judgment dependent on fulfilling multiple criteria drawn from serum biochemistry, weight status, predictive muscle mass, dietary energy and protein intakes. Therefore, we sought to explore the biomarkers’ signature with plasma metabolites of PEW by using ¹H-nuclear magnetic resonance for an untargeted metabolomics approach in the HD population, to understand metabolic alteration of PEW. In this case-controlled study, a total of 53 patients undergoing chronic HD were identified having PEW based on established diagnostic criteria and were age- and sex-matched with non-PEW (n = 53) HD patients. Fasting predialysis plasma samples were analyzed. Partial least square discriminant analysis demonstrated a significant separation between groups for specific metabolic pattern alterations. Further quantitative analysis showed that the level of 3-hydroxybutyrate, acetate, arabinose, maltose, ribose, sucrose and tartrate were significantly increased whilst creatinine was significantly decreased (all p < 0.05) in PEW subjects. Pathway analysis indicated that PEW-related metabolites reflected perturbations in fatty acid mechanism and induction of glyoxylate and dicarboxylate pathway attributed to gluconeogenesis. These results provide preliminary data in understanding metabolic alteration of PEW and corresponding abnormal metabolites that could potentially serve as biomarkers of PEW.

RAS inhibition modulates kynurenine levels in a CKD population with and without type 2 diabetes mellitus

Kynurenine pathway of tryptophan metabolism is involved in the pathophysiology of chronic kidney disease (CKD) and diabetes mellitus, mainly through the inflammation-induced activity of indoleamine 2,3-dioxygenase (IDO), and few studies have investigated its potential link with proteinuria. Renin-angiotensin system inhibitors (RASis) are recommended in these patients to decrease proteinuria, slow CKD progression and reduce cardiovascular risk, but whether these drugs influence kynurenine levels in humans is unknown. We evaluated serum tryptophan and kynurenine in patients suffering from CKD with or without type 2 diabetes mellitus, their correlations with markers of reduced kidney function, and their relationship with RAS-inhibiting therapy. Of 72 adult patients enrolled, 55 were receiving RASis, whereas 17 were not. Tryptophan was assessed by HPLC (high-performance liquid chromatography); kynurenine was measured using an enzyme-linked immunosorbent assay kit; IDO activity (%) was calculated with the formula (kynurenine/tryptophan) × 100. Kynurenine levels were significantly lower in the group under RASis compared to the untreated group (1.56 ± 0.79 vs 2.16 ± 1.51 µmol/l; P = 0.0378). In patients not receiving RASis, kynurenine was inversely related to estimated glomerular filtration rate (eGFR) (r = - 0.4862; P = 0.0478) and directly related to both proteinuria (ρ = 0.493; P = 0.0444) and albuminuria (ρ = 0.542; P = 0.0247). IDO activity was higher in patients with history of cardiovascular disease compared to patients with no such history, and it negatively correlated with eGFR (ρ = - 0.554; P = 0.0210) in the same group. These findings may contribute to explain the well-known beneficial effects of RAS inhibition in CKD population, especially considering that kynurenine is emerging as a potential new biomarker of CKD.

Dataset on the mass spectrometry-based proteomic profiling of the kidney from wild type and the dystrophic mdx-4cv mouse model of X-linked muscular dystrophy

The proteomic data presented in this article provide supporting information to the related research article “Proteomic and cell biological profiling of the renal phenotype of the mdx-4cv mouse model of Duchenne muscular dystrophy” (Dowling et al., 2019) [1]. This article supplies additional datasets on protein species with increased versus decreased concentration in the kidney from the dystrophic mdx-4cv mouse, as well as tables with mass spectrometrically identified kidney marker proteins that exhibit characteristic tissue distributions, subcellular localizations and physiological functions. Information is provided on the underlying multi-consensus protein listings from the proteomic screening of both wild type and mdx-4cv mouse kidneys. The data article provides comprehensive information on the systematic and mass spectrometric identification of the mouse kidney proteome.

Proteomic and cell biological profiling of the renal phenotype of the mdx-4cv mouse model of Duchenne muscular dystrophy

The X-linked inherited muscle wasting disease Duchenne muscular dystrophy, which is caused by primary abnormalities in the membrane cytoskeletal protein dystrophin, is a multi-system disorder. Highly progressive forms of dystrophinopathy are associated with a complex secondary pathophysiology, including renal dysfunction. It was therefore of interest to carry out a systematic survey of potential proteome-wide changes in the kidney of the established mdx-4cv mouse model of dystrophinopathy. Of 5878 mass spectrometrically identified kidney proteins, 82 versus 142 proteins were shown to be decreased or increased, respectively, in association with muscular dystrophy. The most decreased versus increased protein species are the ACSM3 isoform of mitochondrial acyl-coenzyme A synthetase and the FABP1 isoform of fatty acid binding protein, respectively. Both proteomic findings were verified by immunofluorescence microscopy and immunoblot analysis. Interestingly, haematoxylin/eosin staining indicated diffuse whitish deposits in the mdx-4cv kidney, and an increased intensity of Sudan Black labelling of kidney cells revealed ectopic fat deposition. Although the proteomic results and cell biological findings do not demonstrate a direct functional link between increased FABP1 and fat accumulation, the results suggest that the up-regulation of FABP1 may be related to abnormal fat metabolism. This makes FABP1 potentially a novel pathobiochemical indicator for studying kidney abnormalities in the mdx-4cv model of dystrophinopathy.

The Challenges of Chromosome Y Analysis and the Implications for Chronic Kidney Disease

The role of chromosome Y in chronic kidney disease (CKD) remains unknown, as chromosome Y is typically excluded from genetic analysis in CKD. The complex, sex-specific presentation of CKD could be influenced by chromosome Y genetic variation, but there is limited published research available to confirm or reject this hypothesis. Although traditionally thought to be associated with male-specific disease, evidence linking chromosome Y genetic variation to common complex disorders highlights a potential gap in CKD research. Chromosome Y variation has been associated with cardiovascular disease, a condition closely linked to CKD and one with a very similar sexual dimorphism. Relatively few sources of genetic variation in chromosome Y have been examined in CKD. The association between chromosome Y aneuploidy and CKD has never been explored comprehensively, while analyses of microdeletions, copy number variation, and single-nucleotide polymorphisms in CKD have been largely limited to the autosomes or chromosome X. In many studies, it is unclear whether the analyses excluded chromosome Y or simply did not report negative results. Lack of imputation, poor cross-study comparability, and requirement for separate or additional analyses in comparison with autosomal chromosomes means that chromosome Y is under-investigated in the context of CKD. Limitations in genotyping arrays could be overcome through use of whole-chromosome sequencing of chromosome Y that may allow analysis of many different types of genetic variation across the chromosome to determine if chromosome Y genetic variation is associated with CKD.

Genetic Susceptibility to Chronic Kidney Disease - Some More Pieces for the Heritability Puzzle

Chronic kidney disease (CKD) is a major global health problem with an increasing prevalence partly driven by aging population structure. Both genomic and environmental factors contribute to this complex heterogeneous disease. CKD heritability is estimated to be high (30-75%). Genome-wide association studies (GWAS) and GWAS meta-analyses have identified several genetic loci associated with CKD, including variants in UMOD, SHROOM3, solute carriers, and E3 ubiquitin ligases. However, these genetic markers do not account for all the susceptibility to CKD, and the causal pathways remain incompletely understood; other factors must be contributing to the missing heritability. Less investigated biological factors such as telomere length; mitochondrial proteins, encoded by nuclear genes or specific mitochondrial DNA (mtDNA) encoded genes; structural variants, such as copy number variants (CNVs), insertions, deletions, inversions and translocations are poorly covered and may explain some of the missing heritability. The sex chromosomes, often excluded from GWAS studies, may also help explain gender imbalances in CKD. In this review, we outline recent findings on molecular biomarkers for CKD (telomeres, CNVs, mtDNA variants, sex chromosomes) that typically have received less attention than gene polymorphisms. Shorter telomere length has been associated with renal dysfunction and CKD progression, however, most publications report small numbers of subjects with conflicting findings. CNVs have been linked to congenital anomalies of the kidney and urinary tract, posterior urethral valves, nephronophthisis and immunoglobulin A nephropathy. Information on mtDNA biomarkers for CKD comes primarily from case reports, therefore the data are scarce and diverse. The most consistent finding is the A3243G mutation in the MT-TL1 gene, mainly associated with focal segmental glomerulosclerosis. Only one GWAS has found associations between X-chromosome and renal function (rs12845465 and rs5987107). No loci in the Y-chromosome have reached genome-wide significance. In conclusion, despite the efforts to find the genetic basis of CKD, it remains challenging to explain all of the heritability with currently available methods and datasets. Although additional biomarkers have been investigated in less common suspects such as telomeres, CNVs, mtDNA and sex chromosomes, hidden heritability in CKD remains elusive, and more comprehensive approaches, particularly through the integration of multiple -"omics" data, are needed.