| Autor: |
Gerald B. Appel, Fernando C. Fervenza, Sharon G. Adler, Vincent Boima, Michelle Hladunewich, Richard A. Lafayette, Katherine R. Tuttle, Jennifer L. Harder, Suzanne Vento, Kimberly J. Reidy, Marie C. Hogan, Virginia Vega-Warner, Daniel C. Cattran, Akinlolu Ojo, Elizabeth J. Brown, Laura Barisoni, Dwomoa Adu, Larry A. Greenbaum, Noel L. Wys, Vimal K. Derebail, Lawrence B. Holzman, Sean Eddy, Katherine MacRae Dell, Sangeeta Hingorani, Fadhl M. Al-Akwaa, Felix Eichinger, Crystal A. Gadegbeku, Adebowale D. Ademola, Rajarasee Menon, Alessia Fornoni, Keisha L. Gibson, Jeffrey B. Hodgin, Debbie S. Gipson, Chia-shi Wang, John C. Lieske, Pamela Singer, Alicia M. Neu, Christine B. Sethna, Cheryl L. Tran, Meredith A. Atkinson, Kevin V. Lemley, Phillip J. McCown, Jeffrey B. Kopp, Ambarish M. Athavale, John R. Sedor, Jonathan J. Hogan, Jen-Jar Lin, Sebastian Martini, Patrick H. Nachman, Matthias Kretzler, Kamalanathan K. Sambandam, Jamal El Saghir, Serena M. Bagnasco, Cynthia C. Nast, Laura H. Mariani, Bradley Godfrey, Viji Nair, Tarak Srivastava, Kevin E.C. Meyers, Wenjun Ju, Heather N. Reich, J. Ashley Jefferson, Edgar A. Otto, Michelle M. O’Shaughnessy, Emily Tanner, Frederick J. Kaskel, Howard Trachtman |
| Rok vydání: |
2021 |
| Předmět: |
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| DOI: |
10.1101/2021.09.09.21262925 |
| Popis: |
BackgroundClassification of nephrotic syndrome relies on clinical presentation and descriptive patterns of injury on kidney biopsies. This approach does not reflect underlying disease biology, limiting the ability to predict progression or treatment response.MethodsSystems biology approaches were used to categorize patients with minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) based on kidney biopsy tissue transcriptomics across three cohorts and assessed association with clinical outcomes. Patient-level tissue pathway activation scores were generated using differential gene expression. Then, functional enrichment and non-invasive urine biomarker candidates were identified. Biomarkers were validated in kidney organoid models and single nucleus RNA-seq (snRNAseq) from kidney biopsies.ResultsTranscriptome-based categorization identified three subgroups of patients with shared molecular signatures across independent North American, European and African cohorts. One subgroup demonstrated worse longterm outcomes (HR 5.2, p = 0.001) which persisted after adjusting for diagnosis and clinical measures (HR 3.8, p = 0.035) at time of biopsy. This subgroup’s molecular profile was largely (48%) driven by tissue necrosis factor (TNF) activation and could be predicted based on levels of TNF pathway urinary biomarkers TIMP-1 and MCP-1 and clinical features (correlation 0.63, p ConclusionsMolecular profiling identified a patient subgroup within nephrotic syndrome with poor outcome and kidney TNF pathway activation. Clinical trials using non-invasive biomarkers of pathway activation to target therapies are currently being evaluated.Significance StatementMechanistic, targeted therapies are urgently needed for patients with nephrotic syndrome. The inability to target an individual’s specific disease mechanism using currently used diagnostic parameters leads to potential treatment failure and toxicity risk. Patients with focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) were grouped by kidney tissue transcriptional profiles and a subgroup associated with poor outcomes defined. The segregation of the poor outcome group was driven by tumor necrosis factor (TNF) pathway activation and could be identified by urine biomarkers, MCP1 and TIMP1. Based on these findings, clinical trials utilizing non-invasive biomarkers of pathway activation to target therapies, improve response rates and facilitate personalized treatment in nephrotic syndrome have been initiated. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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