ArticleCommunications medicine2023
Proteomic characterization of acute kidney injury in patients hospitalized with SARS-CoV2 infection.
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Article in Communications medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15citing papers in PubMed
3.8field-weighted citation impact, top 6% of its field
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Who cites it
15 citing papers in PubMed, 20 citations in OpenAlex.
- The significance of matrix remodeling associated 7 (MXRA7) in pathogenesis or management of renal diseases deserves more investigations.Renal failure · 2025Article
- Liquid Biopsy-Multiomics Link Adhesion Pathway Dysregulation to Kidney Injury Severity.Kidney international reports · 2025Article
- The peptidoglycan ofScience translational medicine · 2025Article
- Peripheral Transcriptomics in Acute and Long-Term Kidney Dysfunction in SARS-CoV-2 Infection.Kidney360 · 2025Article
- New approaches to acute kidney injury.Clinical kidney journal · 2024Article
- Proteomics and Incident Kidney Failure in Individuals With CKD: The African American Study of Kidney Disease and Hypertension and the Boston Kidney Biopsy Cohort.Kidney medicine · 2024Article
- Brain-wide alterations revealed by spatial transcriptomics and proteomics in COVID-19 infection.Nature aging · 2024Article
- Risk of acute kidney injury in critically-ill patients with COVID-19 compared with seasonal influenza: a retrospective cohort study.EClinicalMedicine · 2024Article
- Proteomic profiling of peripheral blood mononuclear cells reveals immune dysregulation and metabolic alterations in kidney transplant recipients with COVID-19.Frontiers in immunology · 2024Article
- Kidney Disease and Proteomics: A Recent Overview of a Useful Tool for Improving Early Diagnosis.Advances in experimental medicine and biology · 2024Article
- Multi-omics Approach in Kidney Transplant: Lessons Learned from COVID-19 Pandemic.Current transplantation reports · 2023Article
- Acyl coenzyme A binding protein (ACBP): An aging- and disease-relevant "autophagy checkpoint".Aging cell · 2023Review
- Kidney Injury in Critically Ill Patients with COVID-19 - From Pathophysiological Mechanisms to a Personalized Therapeutic Model.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2023Review
- Circulating proteins to predict COVID-19 severity.Scientific reports · 2023Article
- Multi-omics identify falling LRRC15 as a COVID-19 severity marker and persistent pro-thrombotic signals in convalescence.Nature communications · 2022Article
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Authors and funding
43 authors at 8 institutions in 4 countries.
Ishan Paranjpe *Department of Medicine, Stanford University, Stanford, CA, USA.
Pushkala Jayaraman *The Charles Bronfman Institute for Personalized Medicine (CBIPM), Division of Data Driven and Digital Medicine (D3M), Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0003-1159-8354
Chen-Yang SuLady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada.ORCID http://orcid.org/0000-0001-6071-4660
Sirui ZhouLady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada.ORCID http://orcid.org/0000-0003-4963-0815
Steven ChenThe Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Ryan ThompsonThe Charles Bronfman Institute for Personalized Medicine (CBIPM), Division of Data Driven and Digital Medicine (D3M), Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-0450-8181
Diane Marie Del ValleThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Ephraim KenigsbergThe Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-4107-3295
Shan ZhaoDepartment of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-6618-8793
Suraj JaladankiThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0003-0406-2973
Kumardeep ChaudharyClinical Informatics, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi, India.
Steven AscolilloThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-9894-7838
Akhil VaidThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-3343-744X
Edgar Gonzalez-KozlovaThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-6948-0626
Justin KauffmanThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Arvind KumarThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-2865-1732
Manish ParanjpeDivision of Health Sciences and Technology, Harvard Medical School, Boston, MA, USA.
Ross O HaganThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Samir KamatThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Faris F GulamaliThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Hui XieHuman Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Joceyln HarrisHuman Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Manishkumar PatelHuman Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-7949-5610
Kimberly ArguetaHuman Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Craig BatchelorHuman Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Kai NieHuman Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Sergio DellepianeDepartment of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Leisha ScottHuman Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Matthew A LevinThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-6013-2684
John Cijiang HeDepartment of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-1502-2849
Mayte Suarez-FarinasDepartment of Biostatistics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0001-8712-3553
Steven G CocaDepartment of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Lili ChanDepartment of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Evren U AzelogluDepartment of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0001-6137-109X
Eric SchadtDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-7892-8808
Noam BeckmannThe Mount Sinai Clinical Intelligence Center (MSCIC), The Charles Bronfman Institute for Personalized Medicine (CBIPM), Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-4258-1574
Sacha GnjaticDepartment of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0001-5643-9520
Miram MeradThe Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-4481-7827
Seunghee Kim-SchulzeThe Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Brent RichardsLady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada.ORCID http://orcid.org/0000-0002-3746-9086
Benjamin S GlicksbergData Science and Machine Learning, Character Biosciences, New York, NY, USA.ORCID http://orcid.org/0000-0003-4515-8090
Alexander W CharneyLady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada.ORCID http://orcid.org/0000-0001-8135-6858
Girish N NadkarniThe Charles Bronfman Institute for Personalized Medicine (CBIPM), Division of Data Driven and Digital Medicine (D3M), Icahn School of Medicine at Mount Sinai, New York, NY, USA. girish.nadkarni@mountsinai.org.ORCID http://orcid.org/0000-0001-6319-4314
Icahn School of Medicine at Mount Sinai · USJewish General Hospital · CABoston University · USCharacter · USInstitute of Genomics and Integrative Biology · INKing's College London · GBMount Sinai Health System · USStanford University · US
Funding
High-Dimensional Immune Monitoring of NCI-Supported Immunotherapy TrialsU24CA224319 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Sacha Gnjatic, Seunghee Kim-Schulze · 2017 to 2026
$21.5MPrediction of Major Adverse Kidney Events and Recovery (Pred-MAKER) in COVID-19 PatientsR01DK118222 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Evren U. AZELOGLU · 2018 to 2026
$4.3MElucidating Genetic and Environmental Second Hits in Racial and Ethnic Minorities with APOL1 High-Risk GenotypesR01DK127139 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI NADKARNI, GIRISH NITIN · 2021 to 2025
$4.0MElucidating hereditary transthyretin-mediated heart failure risk using machine learning, polygenic risk and recall by genotype approaches in African ancestry individualsR01HL155915 · NHLBI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI DO, RON, NADKARNI, GIRISH NITIN · 2021 to 2024
$3.4MArtificial Intelligence to Predict Outcomes in Patients with Acute Kidney Injury on Continuous Renal Replacement TherapyR01DK133539 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Girish Nitin Nadkarni, Javier A. Neyra · 2023 to 2026
$2.6MBig Omics Data Engine 2 SupercomputerS10OD026880 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2019 to 2019
$2.0MImproving risk prediction of adverse outcomes in hemodialysis patients by incorporating non-traditional risk factorsK23DK124645 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI CHAN, LILI · 2021 to 2025
$952kArtificial Intelligence to Predict Outcomes in Patients with Acute Kidney Injury on Continuous Renal Replacement TherapyR56DK126930 · NIDDK · UNIVERSITY OF KENTUCKY · PI NADKARNI, GIRISH NITIN, NEYRA, JAVIER A. · 2020 to 2020
$100kNCI NIH HHS U24 CA224319NHLBI NIH HHS R01 HL155915NIDDK NIH HHS K23 DK124645NIDDK NIH HHS R01 DK118222NIDDK NIH HHS R01 DK127139NIDDK NIH HHS R01 DK133539NIDDK NIH HHS R56 DK126930NIH HHS S10 OD026880
Abstract
backgroundAcute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms.
methodsUsing measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N = 437), we identified 413 higher plasma abundances of protein targets and 30 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p < 0.05). Of these, 62 proteins were validated in an external cohort (p < 0.05, N = 261).
resultsWe demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p < 0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury.
conclusionsUsing clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.
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