Metabolome Panels As Potential Noninvasive Biomarkers for Primary Glomerulonephritis Sub-types: Meta-analysis of Profiling Metabolomics Studies

Overview

Journal Sci Rep

Specialty Science

Date 2023 Nov 22

PMID 37990116

Authors

Amir Roointan

Maryam Ghaeidamini

Saba Shafieizadegan

Kelly L Hudkins

Alieh Gholaminejad

Affiliations

Soon will be listed here.

Abstract

Primary glomerulonephritis diseases (PGDs) are known as the top causes of chronic kidney disease worldwide. Renal biopsy, an invasive method, is the main approach to diagnose PGDs. Studying the metabolome profiles of kidney diseases is an inclusive approach to identify the disease's underlying pathways and discover novel non-invasive biomarkers. So far, different experiments have explored the metabolome profiles in different PGDs, but the inconsistencies might hinder their clinical translations. The main goal of this meta-analysis study was to achieve consensus panels of dysregulated metabolites in PGD sub-types. The PGDs-related metabolome profiles from urine samples in humans were selected in a comprehensive search. Amanida package in R software was utilized for performing the meta-analysis. Through sub-type analyses, the consensus list of metabolites in each category was obtained. To identify the most affected pathways, functional enrichment analysis was performed. Also, a gene-metabolite network was constructed to identify the key metabolites and their connected proteins. After a vigorous search, among the 11 selected studies (15 metabolite profiles), 270 dysregulated metabolites were recognized in urine of 1154 PGDs and control samples. Through sub-type analyses by Amanida package, the consensus list of metabolites in each category was obtained. Top dysregulated metabolites (vote score of ≥ 4 or ≤ - 4) in PGDs urines were selected as main panel of meta-metabolites including glucose, leucine, choline, betaine, dimethylamine, fumaric acid, citric acid, 3-hydroxyisovaleric acid, pyruvic acid, isobutyric acid, and hippuric acid. The enrichment analyses results revealed the involvement of different biological pathways such as the TCA cycle and amino acid metabolisms in the pathogenesis of PGDs. The constructed metabolite-gene interaction network revealed the high centralities of several metabolites, including pyruvic acid, leucine, and choline. The identified metabolite panels could shed a light on the underlying pathological pathways and be considered as non-invasive biomarkers for the diagnosis of PGD sub-types.

Citing Articles

Emerging biomarkers for non-invasive diagnosis and treatment of cancer: a systematic review.

Zakari S, Niels N, Olagunju G, Nnaji P, Ogunniyi O, Tebamifor M Front Oncol. 2024; 14:1405267.

PMID: 39132504 PMC: 11313249. DOI: 10.3389/fonc.2024.1405267.

References

Guo F, Dai Q, Zeng X, Liu Y, Tan Z, Zhang H . Renal function is associated with plasma trimethylamine-N-oxide, choline, L-carnitine and betaine: a pilot study. Int Urol Nephrol. 2020; 53(3):539-551. DOI: 10.1007/s11255-020-02632-6. View

Foxall P, Mellotte G, Bending M, Lindon J, Nicholson J . NMR spectroscopy as a novel approach to the monitoring of renal transplant function. Kidney Int. 1993; 43(1):234-45. DOI: 10.1038/ki.1993.37. View

Duranton F, Lundin U, Gayrard N, Mischak H, Aparicio M, Mourad G . Plasma and urinary amino acid metabolomic profiling in patients with different levels of kidney function. Clin J Am Soc Nephrol. 2013; 9(1):37-45. PMC: 3878706. DOI: 10.2215/CJN.06000613. View

Llambrich M, Correig E, Guma J, Brezmes J, Cumeras R . Amanida: an R package for meta-analysis of metabolomics non-integral data. Bioinformatics. 2021; 38(2):583-585. PMC: 8722753. DOI: 10.1093/bioinformatics/btab591. View

Jiang S, Kennard A, Walters G . Recurrent glomerulonephritis following renal transplantation and impact on graft survival. BMC Nephrol. 2018; 19(1):344. PMC: 6278033. DOI: 10.1186/s12882-018-1135-7. View

Pecoits-Filho R, Abensur H, Betonico C, Machado A, Parente E, Queiroz M . Interactions between kidney disease and diabetes: dangerous liaisons. Diabetol Metab Syndr. 2016; 8:50. PMC: 4964290. DOI: 10.1186/s13098-016-0159-z. View

Summers S, Quimby J, Phillips R, Stockman J, Isaiah A, Lidbury J . Preliminary evaluation of fecal fatty acid concentrations in cats with chronic kidney disease and correlation with indoxyl sulfate and p-cresol sulfate. J Vet Intern Med. 2019; 34(1):206-215. PMC: 6979089. DOI: 10.1111/jvim.15634. View

Tseng G, Ghosh D, Feingold E . Comprehensive literature review and statistical considerations for microarray meta-analysis. Nucleic Acids Res. 2012; 40(9):3785-99. PMC: 3351145. DOI: 10.1093/nar/gkr1265. View

Andrulli S, Rossini M, Gigliotti G, La Manna G, Feriozzi S, Aucella F . The risks associated with percutaneous native kidney biopsies: a prospective study. Nephrol Dial Transplant. 2022; 38(3):655-663. PMC: 9976765. DOI: 10.1093/ndt/gfac177. View

10.

De Angelis M, Montemurno E, Piccolo M, Vannini L, Lauriero G, Maranzano V . Microbiota and metabolome associated with immunoglobulin A nephropathy (IgAN). PLoS One. 2014; 9(6):e99006. PMC: 4055632. DOI: 10.1371/journal.pone.0099006. View

11.

BRYAN A . CLINICAL AND EXPERIMENTAL STUDIES ON SODIUM BENZOATE: The Value of the Sodium Benzoate Test of Renal Function, and the Effect of Injury of the Liver on Hippuric Acid Synthesis. J Clin Invest. 1925; 2(1):1-33. PMC: 434574. DOI: 10.1172/JCI100032. View

12.

Trajceska L, Severova-Andreevska G, Dzekova-Vidimliski P, Nikolov I, Selim G, Spasovski G . Complications and Risks of Percutaneous Renal Biopsy. Open Access Maced J Med Sci. 2019; 7(6):992-995. PMC: 6454172. DOI: 10.3889/oamjms.2019.226. View

13.

Gholaminejad A, Moein S, Roointan A, Mortazavi M, Nouri R, Mansourian M . Circulating β2 and α1 microglobulins predict progression of nephropathy in diabetic patients: a meta-analysis of prospective cohort studies. Acta Diabetol. 2022; 59(11):1417-1427. DOI: 10.1007/s00592-022-01940-w. View

14.

Gao Y, Zhang J, Chen H, Wang Z, Hou J, Wang L . Dimethylamine enhances platelet hyperactivity in chronic kidney disease model. J Bioenerg Biomembr. 2021; 53(5):585-595. DOI: 10.1007/s10863-021-09913-4. View

15.

Zhou Q, Yang X, Wang M, Wang H, Zhao J, Bi Y . Changes in the diagnosis of glomerular diseases in east China: a 15-year renal biopsy study. Ren Fail. 2018; 40(1):657-664. PMC: 6282433. DOI: 10.1080/0886022X.2018.1537930. View

16.

Taherkhani A, Farrokhi Yekta R, Mohseni M, Saidijam M, Arefi Oskouie A . Chronic kidney disease: a review of proteomic and metabolomic approaches to membranous glomerulonephritis, focal segmental glomerulosclerosis, and IgA nephropathy biomarkers. Proteome Sci. 2020; 17:7. PMC: 6925425. DOI: 10.1186/s12953-019-0155-y. View

17.

Taherkhani A, Kalantari S, Arefi Oskouie A, Nafar M, Taghizadeh M, Tabar K . Network analysis of membranous glomerulonephritis based on metabolomics data. Mol Med Rep. 2018; 18(5):4197-4212. PMC: 6172390. DOI: 10.3892/mmr.2018.9477. View

18.

Jacob M, Nimer R, Alabdaljabar M, Sabi E, Al-Ansari M, Housien M . Metabolomics Profiling of Nephrotic Syndrome towards Biomarker Discovery. Int J Mol Sci. 2022; 23(20). PMC: 9603939. DOI: 10.3390/ijms232012614. View

19.

Suliman M, Qureshi A, Stenvinkel P, Pecoits-Filho R, Barany P, Heimburger O . Inflammation contributes to low plasma amino acid concentrations in patients with chronic kidney disease. Am J Clin Nutr. 2005; 82(2):342-9. DOI: 10.1093/ajcn.82.2.342. View

20.

Woo K, Chan C, Chin Y, Choong H, Tan H, Foo M . Global evolutionary trend of the prevalence of primary glomerulonephritis over the past three decades. Nephron Clin Pract. 2010; 116(4):c337-46. DOI: 10.1159/000319594. View