Prioritization of Monogenic Congenital Anomalies of the Kidney and Urinary Tract Candidate Genes with Existing Single-Cell Transcriptomics Data of the Human Fetal Kidney
Bibliographic record
Abstract
INTRODUCTION: Congenital anomalies of the kidney and urinary tract (CAKUT) are the most common cause of chronic kidney disease in the first 3 decades of life. Over 40 genes have been identified as causative for isolated human CAKUT. However, many genes remain unknown, and the prioritization of potential CAKUT candidate genes is challenging. To develop an independent approach to prioritize CAKUT candidate genes, we hypothesized that monogenic CAKUT genes are most likely co-expressed along a temporal axis during kidney development and that genes with coinciding high expression may represent strong novel CAKUT candidate genes. METHODS: We analyzed single-cell mRNA (sc-mRNA) transcriptomics data of human fetal kidney for temporal sc-mRNA co-expression of 40 known CAKUT genes. A maximum of high expression in consecutive timepoints of kidney development was found for four of the 40 genes (EYA1, SIX1, SIX2, and ITGA8) in nephron progenitor cells a, b, c, d (NPCa-d). We concluded that NPCa-d are relevant for CAKUT pathogenesis and intersected two lists of CAKUT candidate genes resulting from unbiased whole-exome sequencing (WES) with the 100 highest expressed genes in NPCa-d. RESULTS: Intersection of the 100 highest expressed genes in NPCa-d with WES-derived CAKUT candidate genes identified an overlap with the candidate genes KIF19, TRIM36, USP35, CHTF18, in each of which a biallelic variant was detected in different families with CAKUT. CONCLUSION: Sc-mRNA expression data of human fetal kidney can be utilized to prioritize WES-derived CAKUT candidate genes. KIF19, TRIM36, USP35, and CHTF18 may represent strong novel candidate genes for CAKUT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".