Unbiased Human Kidney Tissue Proteomics Identifies Matrix Metalloproteinase 7 as a Kidney Disease Biomarker.
Journal
Journal of the American Society of Nephrology : JASN
ISSN: 1533-3450
Titre abrégé: J Am Soc Nephrol
Pays: United States
ID NLM: 9013836
Informations de publication
Date de publication:
01 07 2023
01 07 2023
Historique:
received:
18
12
2022
accepted:
10
03
2023
pmc-release:
01
07
2024
medline:
5
7
2023
pubmed:
7
4
2023
entrez:
6
4
2023
Statut:
ppublish
Résumé
Although gene expression changes have been characterized in human diabetic kidney disease (DKD), unbiased tissue proteomics information for this condition is lacking. The authors conducted an unbiased aptamer-based proteomic analysis of samples from patients with DKD and healthy controls, identifying proteins with levels that associate with kidney function (eGFR) or fibrosis, after adjusting for key covariates. Overall, tissue gene expression only modestly correlated with tissue protein levels. Kidney protein and RNA levels of matrix metalloproteinase 7 (MMP7) strongly correlated with fibrosis and with eGFR. Single-cell RNA sequencing indicated that kidney tubule cells are an important source of MMP7. Furthermore, plasma MMP7 levels predicted future kidney function decline. These findings identify kidney tissue MMP7 as a biomarker of fibrosis and blood MMP7 as a biomarker for future kidney function decline. Diabetic kidney disease (DKD) is responsible for close to half of all ESKD cases. Although unbiased gene expression changes have been extensively characterized in human kidney tissue samples, unbiased protein-level information is not available. We collected human kidney samples from 23 individuals with DKD and ten healthy controls, gathered associated clinical and demographics information, and implemented histologic analysis. We performed unbiased proteomics using the SomaScan platform and quantified the level of 1305 proteins and analyzed gene expression levels by bulk RNA and single-cell RNA sequencing (scRNA-seq). We validated protein levels in a separate cohort of kidney tissue samples as well as in 11,030 blood samples. Globally, human kidney transcript and protein levels showed only modest correlation. Our analysis identified 14 proteins with kidney tissue levels that correlated with eGFR and found that the levels of 152 proteins correlated with interstitial fibrosis. Of the identified proteins, matrix metalloprotease 7 (MMP7) showed the strongest association with both fibrosis and eGFR. The correlation between tissue MMP7 protein expression and kidney function was validated in external datasets. The levels of MMP7 RNA correlated with fibrosis in the primary and validation datasets. Findings from scRNA-seq pointed to proximal tubules, connecting tubules, and principal cells as likely cellular sources of increased tissue MMP7 expression. Furthermore, plasma MMP7 levels correlated not only with kidney function but also associated with prospective kidney function decline. Our findings, which underscore the value of human kidney tissue proteomics analysis, identify kidney tissue MMP7 as a diagnostic marker of kidney fibrosis and blood MMP7 as a biomarker for future kidney function decline.
Sections du résumé
SIGNIFICANCE STATEMENT
Although gene expression changes have been characterized in human diabetic kidney disease (DKD), unbiased tissue proteomics information for this condition is lacking. The authors conducted an unbiased aptamer-based proteomic analysis of samples from patients with DKD and healthy controls, identifying proteins with levels that associate with kidney function (eGFR) or fibrosis, after adjusting for key covariates. Overall, tissue gene expression only modestly correlated with tissue protein levels. Kidney protein and RNA levels of matrix metalloproteinase 7 (MMP7) strongly correlated with fibrosis and with eGFR. Single-cell RNA sequencing indicated that kidney tubule cells are an important source of MMP7. Furthermore, plasma MMP7 levels predicted future kidney function decline. These findings identify kidney tissue MMP7 as a biomarker of fibrosis and blood MMP7 as a biomarker for future kidney function decline.
BACKGROUND
Diabetic kidney disease (DKD) is responsible for close to half of all ESKD cases. Although unbiased gene expression changes have been extensively characterized in human kidney tissue samples, unbiased protein-level information is not available.
METHODS
We collected human kidney samples from 23 individuals with DKD and ten healthy controls, gathered associated clinical and demographics information, and implemented histologic analysis. We performed unbiased proteomics using the SomaScan platform and quantified the level of 1305 proteins and analyzed gene expression levels by bulk RNA and single-cell RNA sequencing (scRNA-seq). We validated protein levels in a separate cohort of kidney tissue samples as well as in 11,030 blood samples.
RESULTS
Globally, human kidney transcript and protein levels showed only modest correlation. Our analysis identified 14 proteins with kidney tissue levels that correlated with eGFR and found that the levels of 152 proteins correlated with interstitial fibrosis. Of the identified proteins, matrix metalloprotease 7 (MMP7) showed the strongest association with both fibrosis and eGFR. The correlation between tissue MMP7 protein expression and kidney function was validated in external datasets. The levels of MMP7 RNA correlated with fibrosis in the primary and validation datasets. Findings from scRNA-seq pointed to proximal tubules, connecting tubules, and principal cells as likely cellular sources of increased tissue MMP7 expression. Furthermore, plasma MMP7 levels correlated not only with kidney function but also associated with prospective kidney function decline.
CONCLUSIONS
Our findings, which underscore the value of human kidney tissue proteomics analysis, identify kidney tissue MMP7 as a diagnostic marker of kidney fibrosis and blood MMP7 as a biomarker for future kidney function decline.
Identifiants
pubmed: 37022120
doi: 10.1681/ASN.0000000000000141
pii: 00001751-202307000-00017
pmc: PMC10356165
doi:
Substances chimiques
Matrix Metalloproteinase 7
EC 3.4.24.23
Biomarkers
0
RNA
63231-63-0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1279-1291Subventions
Organisme : NIDDK NIH HHS
ID : R01 DK076077
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK087635
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK105821
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK132630
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK123459
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK124399
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK036836
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201700001I
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201700002I
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201700003I
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201700005I
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201700004I
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201100005C
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201100006C
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201100007C
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201100008C
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201100009C
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201100010C
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201100011C
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268201100012C
Pays : United States
Informations de copyright
Copyright © 2023 by the American Society of Nephrology.
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