Dataset Information

Generation of Monogenic Candidate Genes for Human Nephrotic Syndrome Using 3 Independent Approaches.

ABSTRACT:

Introduction

Steroid-resistant nephrotic syndrome (SRNS) is the second most common cause of chronic kidney disease during childhood. Identification of 63 monogenic human genes has delineated 12 distinct pathogenic pathways.

Methods

Here, we generated 2 independent sets of nephrotic syndrome (NS) candidate genes to augment the discovery of additional monogenic causes based on whole-exome sequencing (WES) data from 1382 families with NS.

Results

We first identified 63 known monogenic causes of NS in mice from public databases and scientific publications, and 12 of these genes overlapped with the 63 known human monogenic SRNS genes. Second, we used a set of 64 genes that are regulated by the transcription factor Wilms tumor 1 (WT1), which causes SRNS if mutated. Thirteen of these WT1-regulated genes overlapped with human or murine NS genes. Finally, we overlapped these lists of murine and WT1 candidate genes with our list of 120 candidate genes generated from WES in 1382 NS families, to identify novel candidate genes for monogenic human SRNS. Using this approach, we identified 7 overlapping genes, of which 3 genes were shared by all datasets, including SYNPO. We show that loss-of-function of SYNPO leads to decreased CDC42 activity and reduced podocyte migration rate, both of which are rescued by overexpression of wild-type complementary DNA (cDNA), but not by cDNA representing the patient mutation.

Conclusion

Thus, we identified 3 novel candidate genes for human SRNS using 3 independent, nonoverlapping hypotheses, and generated functional evidence for SYNPO as a novel potential monogenic cause of NS.

SUBMITTER: Klambt V

PROVIDER: S-EPMC7879125 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Generation of Monogenic Candidate Genes for Human Nephrotic Syndrome Using 3 Independent Approaches.

Klämbt Verena V Mao Youying Y Schneider Ronen R Buerger Florian F Shamseldin Hanan H Onuchic-Whitford Ana C AC Deutsch Konstantin K Kitzler Thomas M TM Nakayama Makiko M Majmundar Amar J AJ Mann Nina N Hugo Hannah H Widmeier Eugen E Tan Weizhen W Rehm Heidi L HL Mane Shrikant S Lifton Richard P RP Alkuraya Fowzan S FS Shril Shirlee S Hildebrandt Friedhelm F

Kidney international reports 20201203 2

<h4>Introduction</h4>Steroid-resistant nephrotic syndrome (SRNS) is the second most common cause of chronic kidney disease during childhood. Identification of 63 monogenic human genes has delineated 12 distinct pathogenic pathways.<h4>Methods</h4>Here, we generated 2 independent sets of nephrotic syndrome (NS) candidate genes to augment the discovery of additional monogenic causes based on whole-exome sequencing (WES) data from 1382 families with NS.<h4>Results</h4>We first identified 63 known m ...[more]

PMID: 33615071

Similar Datasets

Project description:Nephrotic syndrome (NS) gene discovery efforts are now occurring in small kindreds and cohorts of sporadic cases. Power to identify causal variants in these groups beyond a statistical significance threshold is challenging due to small sample size and/or lack of family information. There is a need to develop novel methods to identify NS-associated variants. One way to determine putative functional relevance of a gene is to measure its strength of negative selection, as variants in genes under strong negative selection are more likely to be deleterious. We created a gene-level, integrated metric of negative selection (GIMS) score for 20,079 genes by combining multiple comparative genomics and population genetics measures. To understand the utility of GIMS for NS gene discovery, we examined this score in a diverse set of NS-relevant gene sets. These included genes known to cause monogenic forms of NS in humans as well as genes expressed in the cells of the glomerulus and, particularly, the podocyte. We found strong negative selection in the following NS-relevant gene sets: (1) autosomal-dominant Mendelian focal segmental glomerulosclerosis (FSGS) genes (p = 0.03 compared to reference), (2) glomerular expressed genes (p = 4×10(-23)), and (3) predicted podocyte genes (p = 3×10(-9)). Eight genes causing autosomal dominant forms of FSGS had a stronger combined score of negative selection and podocyte enrichment as compared to all other genes (p = 1 x 10(-3)). As a whole, recessive FSGS genes were not enriched for negative selection. Thus, we also created a transcript-level, integrated metric of negative selection (TIMS) to quantify negative selection on an isoform level. These revealed transcripts of known autosomal recessive disease-causing genes that were nonetheless under strong selection. We suggest that a filtering strategy that includes measuring negative selection on a gene or isoform level could aid in identifying NS-related genes. Our GIMS and TIMS scores are available at http://glom.sph.umich.edu/GIMS/.

Dataset Information

Generation of Monogenic Candidate Genes for Human Nephrotic Syndrome Using 3 Independent Approaches.

Introduction

Methods

Results

Conclusion

Publications

Generation of Monogenic Candidate Genes for Human Nephrotic Syndrome Using 3 Independent Approaches.

Similar Datasets

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