TY - JOUR
T1 - Molecular Characterization of Membranous Nephropathy
AU - Sealfon, Rachel
AU - Mariani, Laura
AU - Avila-Casado, Carmen
AU - Nair, Viji
AU - Menon, Rajasree
AU - Funk, Julien
AU - Wong, Aaron
AU - Lerner, Gabriel
AU - Hayashi, Norifumi
AU - Troyanskaya, Olga
AU - Kretzler, Matthias
AU - Beck, Laurence H.
N1 - Funding Information:
Funders: National Institute of Diabetes and Digestive and Kidney Diseases, (Grant / Award Number: '2P30-DK-081943','3T32DK007053-45S1','K08 DK115891 ','R01 097053','U24DK100845','U2CDK114886','U2CTR002818','UH3DK114907')
Funding Information:
This work was supported by the following grants from the National Institute of Diabetes, Digestive, and Kidney Diseases: R01 097053 (to L. Beck and M. Kretzler); U24DK100845, UH3DK114907, U2CDK114886 (to O. Troyanskaya and M. Kretzler); K08 DK115891 (to L. Mariani); and 3T32DK007053-45S1 (G. Lerner). This study was supported, in part, by the George M. O’Brien Michigan Kidney Translational Core Center, funded by NIH/NIDDK grant 2P30-DK-081943 The Nephrotic Syndrome Rare Disease Clinical Research Network III (NEPTUNE) is part of the Rare Diseases Clinical Research Network (RDCRN), which is funded by the National Institutes of Health (NIH) and led by the National Center for Advancing Translational Sciences (NCATS) through its Office of Rare Diseases Research (ORDR). NEPTUNE is funded under grant number U54DK083912 as a collaboration between NCATS and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Additional funding and/or programmatic support for this project has also been provided by the University of Michigan, NephCure Kidney International and the Halpin Foundation. All RDCRN consortia are supported by the network’s Data Management and Coordinating Center (DMCC) (U2CTR002818). Funding support for the DMCC is provided by NCATS and the National Institute of Neurological Disorders and Stroke (NINDS).
Funding Information:
This work was supported by the following grants from the National Institute of Diabetes, Digestive, and Kidney Diseases: R01 097053 (to L. Beck and M. Kretzler); U24DK100845, UH3DK114907, U2CDK114886 (to O. Troyanskaya and M. Kretzler); K08 DK115891 (to L. Mariani); and 3T32DK007053-45S1 (G. Lerner). This study was supported, in part, by the George M. O’Brien Michigan Kidney Translational Core Center, funded by NIH/NIDDK grant 2P30-DK-081943 The Nephrotic Syndrome Rare Disease Clinical Research Network III (NEPTUNE) is part of the Rare Diseases Clinical Research Network (RDCRN), which is funded by the National Institutes of Health (NIH) and led by the National Center for Advancing Translational Sciences (NCATS) through its Office of Rare Diseases Research (ORDR). NEPTUNE is funded under grant number U54DK083912 as a collaboration between NCATS and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Additional funding and/or programmatic support for this project has also been provided by the University of Michigan, NephCure Kidney International and the Halpin Foundation. All RDCRN consortia are supported by the network’s Data Management and Coordinating Center (DMCC) (U2CTR002818). Funding support for the DMCC is provided by NCATS and the National Institute of Neurological Disorders and Stroke (NINDS). The authors would like to thank Sean Eddy for assistance with submitting the expression data to GEO.
Funding Information:
National Center for Advancing Translational Sciences, (Grant / Award Number: 'U54DK083912')
Publisher Copyright:
© 2022 American Society of Nephrology. All rights reserved.
PY - 2022/6
Y1 - 2022/6
N2 - Background Molecular characterization of nephropathies may facilitate pathophysiologic insight, development of targeted therapeutics, and transcriptome-based disease classification. Although membranous nephropathy (MN) is a common cause of adult-onset nephrotic syndrome, the molecular pathways of kidney damage in MN require further definition. Methods We applied a machine learning framework to predict diagnosis based on gene expression from microdissected kidney tissue of participants in the Nephrotic Syndrome Study Network (NEPTUNE) cohort. We sought to identify differentially expressed genes between participants with MN versus those of other glomerulonephropathies across the NEPTUNE and European Renal cDNA Bank (ERCB) cohorts, to find MN-specific gene modules in a kidney-specific functional network, and to identify cell-type specificity of MN-specific genes using single-cell sequencing data from reference nephrectomy tissue. Results Glomerular gene expression alone accurately separated participants with MN from those with other nephrotic syndrome etiologies. The top predictive classifier genes from NEPTUNE participants were also differentially expressed in the ERCB participants with MN. We identified a signature of 158 genes that are significantly differentially expressed in MN across both cohorts, finding 120 of these in a validation cohort. This signature is enriched in targets of transcription factor NF-кB. Clustering these MN-specific genes in a kidney-specific functional network uncovered modules with functional enrichments, including in ion transport, cell projection morphogenesis, regulation of adhesion, and wounding response. Expression data from reference nephrectomy tissue indicated that 43% of these genes are most highly expressed by podocytes. Conclusions These results suggest that relative to other glomerulonephropathies, MN has a distinctive molecular signature that includes upregulation of many podocyte-expressed genes, provide a molecular snapshot of MN, and facilitate insight into MN’s underlying pathophysiology.
AB - Background Molecular characterization of nephropathies may facilitate pathophysiologic insight, development of targeted therapeutics, and transcriptome-based disease classification. Although membranous nephropathy (MN) is a common cause of adult-onset nephrotic syndrome, the molecular pathways of kidney damage in MN require further definition. Methods We applied a machine learning framework to predict diagnosis based on gene expression from microdissected kidney tissue of participants in the Nephrotic Syndrome Study Network (NEPTUNE) cohort. We sought to identify differentially expressed genes between participants with MN versus those of other glomerulonephropathies across the NEPTUNE and European Renal cDNA Bank (ERCB) cohorts, to find MN-specific gene modules in a kidney-specific functional network, and to identify cell-type specificity of MN-specific genes using single-cell sequencing data from reference nephrectomy tissue. Results Glomerular gene expression alone accurately separated participants with MN from those with other nephrotic syndrome etiologies. The top predictive classifier genes from NEPTUNE participants were also differentially expressed in the ERCB participants with MN. We identified a signature of 158 genes that are significantly differentially expressed in MN across both cohorts, finding 120 of these in a validation cohort. This signature is enriched in targets of transcription factor NF-кB. Clustering these MN-specific genes in a kidney-specific functional network uncovered modules with functional enrichments, including in ion transport, cell projection morphogenesis, regulation of adhesion, and wounding response. Expression data from reference nephrectomy tissue indicated that 43% of these genes are most highly expressed by podocytes. Conclusions These results suggest that relative to other glomerulonephropathies, MN has a distinctive molecular signature that includes upregulation of many podocyte-expressed genes, provide a molecular snapshot of MN, and facilitate insight into MN’s underlying pathophysiology.
KW - Glomerulonephritis
KW - Membranous
KW - machine learning
KW - membranous nephropathy
KW - podocyte
KW - scRNA-seq
KW - single-cell sequencing
KW - transcriptional profiling
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U2 - 10.1681/ASN.2021060784
DO - 10.1681/ASN.2021060784
M3 - Article
C2 - 35477557
AN - SCOPUS:85131215524
SN - 1046-6673
VL - 33
SP - 1208
EP - 1221
JO - Journal of the American Society of Nephrology : JASN
JF - Journal of the American Society of Nephrology : JASN
IS - 6
ER -