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. 2024 Aug 27;15(1):7368.
doi: 10.1038/s41467-024-51304-x.

Plasma proteomics of acute tubular injury

Insa M Schmidt  1   2   3   4 , Aditya L Surapaneni  5 , Runqi Zhao  6   7 , Dhairya Upadhyay  5 , Wan-Jin Yeo  5 , Pascal Schlosser  8   9   10 , Courtney Huynh  6   7 , Anand Srivastava  11 , Ragnar Palsson  12 , Taesoo Kim  12 , Isaac E Stillman  13 , Daria Barwinska  14 , Jonathan Barasch  15 , Michael T Eadon  14 , Tarek M El-Achkar  14 , Joel Henderson  16 , Dennis G Moledina  17 , Sylvia E Rosas  18 , Sophie E Claudel  6   7 , Ashish Verma  6   7 , Yumeng Wen  19 , Maja Lindenmayer  20   21 , Tobias B Huber  20   21 , Samir V Parikh  22 , John P Shapiro  22 , Brad H Rovin  22 , Ian B Stanaway  23 , Neha A Sathe  24 , Pavan K Bhatraju  23   24 , Josef Coresh  5 ; Kidney Precision Medicine Project; Eugene P Rhee  12 , Morgan E Grams  5 , Sushrut S Waikar  6   7
Affiliations

Plasma proteomics of acute tubular injury

Insa M Schmidt et al. Nat Commun. .

Abstract

The kidney tubules constitute two-thirds of the cells of the kidney and account for the majority of the organ's metabolic energy expenditure. Acute tubular injury (ATI) is observed across various types of kidney diseases and may significantly contribute to progression to kidney failure. Non-invasive biomarkers of ATI may allow for early detection and drug development. Using the SomaScan proteomics platform on 434 patients with biopsy-confirmed kidney disease, we here identify plasma biomarkers associated with ATI severity. We employ regional transcriptomics and proteomics, single-cell RNA sequencing, and pathway analysis to explore biomarker protein and gene expression and enriched biological pathways. Additionally, we examine ATI biomarker associations with acute kidney injury (AKI) in the Kidney Precision Medicine Project (KPMP) (n = 44), the Atherosclerosis Risk in Communities (ARIC) study (n = 4610), and the COVID-19 Host Response and Clinical Outcomes (CHROME) study (n = 268). Our findings indicate 156 plasma proteins significantly linked to ATI with osteopontin, macrophage mannose receptor 1, and tenascin C showing the strongest associations. Pathway analysis highlight immune regulation and organelle stress responses in ATI pathogenesis.

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Conflict of interest statement

S.S.W. reports personal fees from Public Health Advocacy Institute, CVS, Roth Capital Partners, Kantum Pharma, Mallinckrodt, Wolters Kluewer, GE Health Care, GSK, Allena Pharmaceuticals, Mass Medical International, Barron and Budd (vs Fresenius), JNJ, Venbio, Strataca, Takeda, Cerus, Pfizer, Bunch and James, Harvard Clinical Research Institute (aka Baim), Oxidien, Sironax, Metro Biotechnology, Biomarin, and Bain. S.E.R reports grant support to Joslin from Bayer and AstraZeneca. In addition, she has participated as advisory member for Bayer and AstraZeneca. D.G.M. is named co-inventor on a pending patent, “Methods and Systems for Diagnosis of Acute Interstitial Nephritis” and is a co-founder of the diagnostics company Predict AIN, LLC. Y.W. reports being an employee of Genentech and having stock and stock options in Roche at the time of final manuscript revision. The remaining authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1. Outline of studies, study participants, and primary outcomes.
ATI: acute tubular injury, AKI: acute kidney injury. This figure was created with BioRender.com and released under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International license.
Fig. 2
Fig. 2. Acute tubular injury (ATI) scores and identification of ATI biomarkers.
a Distribution of semiquantitative severity scores for ATI by clinicopathologic diagnostic category in the Boston Kidney Biopsy Cohort (BKBC), Study 1. b Circulating plasma proteins associated with ATI severity in native kidney biopsy specimens. Beta coefficients are derived from multivariable linear regression models, adjusted for age, sex, race, and eGFR. The horizontal dotted line shows the Bonferroni-adjusted significance threshold. P-values are two-sided. ATI: acute tubular injury, BKBC: Boston Kidney Biopsy Cohort, eGFR: estimated glomerular filtration rate, GN: glomerulonephritis, GP: glomerulopathy.
Fig. 3
Fig. 3. Expression of acute tubular injury (ATI) biomarkers in regional proteomics and transcriptomics data and pathway analysis.
a ATI biomarkers with elevated protein expression comparing tubulointerstitial to glomerular levels in KPMP regional proteomics data (AKI, CKD, HRT combined). b Protein expression of ATI biomarkers in the tubulointerstitium of individuals with AKI compared to healthy controls using Wilcoxon Rank Sum Test and Benjamini–Hochberg FDR to account for multiple comparisons. Shown are all proteins with a two-sided p < 0.05. c Gene expression of ATI biomarkers in KPMP regional transcriptomics data (AKI, CKD, HRT combined) using ANOVA. Two-sided p-values are adjusted for multiple comparisons using Benjamini–Hochberg FDR. d Pathway analysis of biomarkers associated with ATI severity. The top-ranked pathways are listed in black (one-sided p < 0.05) and gray (one-sided p < 0.25) following Benjamini–Hochberg correction. ATI: acute tubular injury, AKI: acute kidney injury, CKD: chronic kidney disease, HRT: healthy reference tissue, NES: normalized enrichment score, R-HSA: Reactome-Homo sapiens, GO: Gene Ontology, COPII: Coat Protein II.
Fig. 4
Fig. 4. ATI biomarkers and acute kidney injury (AKI).
a Comparison of ATI biomarker levels between healthy participants and those with AKI in the KPMP study using Student’s t-test. b Plasma ATI biomarkers associated with incident AKI in ARIC. Hazard ratios are derived from Cox proportional hazards models, adjusted for age, sex, Black race, hypertension, diabetes, systolic blood pressure, current smoking, eGFR, and log(UACR). p-values were calculated using the Wald test. c Plasma ATI biomarkers associated with severe AKI 7 days after ICU admission in a cohort of critically ill patients (CHROME). Odds ratios are derived from multivariable logistic regression models, adjusted for age, sex, and COVID-19 status. p-values were calculated using the Wald test. The horizontal dotted lines (a–c) show the Bonferroni-adjusted significance thresholds. p-values (a–c) are two-sided. d The heatmap illustrates the associations of 156 ATI biomarkers with specific outcomes across studies. Each biomarker is represented by a color: red signifies a statistically significant positive association, blue denotes a statistically significant negative association, and gray indicates that the biomarker was not available in the respective cohort. The biomarkers are organized based on their frequency of associations across studies and are further ordered according to the magnitude of their association with ATI severity in Study 1 (BKBC). ARIC: Atherosclerosis Risk in Communities study, ATI: acute tubular injury, BKBC: Boston Kidney Biopsy Cohort, CHROME: COVID-19 Host Response and Clinical Outcomes study, eGFR: estimated glomerular filtration rate, KPMP: Kidney Precision Medicine Project, UACR: urine albumin to creatinine ratio.
See this image and copyright information in PMC

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