Transcriptome-wide association analysis identifies DACH1 as a kidney disease risk gene that contributes to fibrosis
Bibliographic record
Abstract
Genome-wide association studies (GWAS) for kidney function identified hundreds of risk regions; however, the causal variants, target genes, cell types, and disease mechanisms remain poorly understood. Here, we performed transcriptome-wide association studies (TWAS), summary Mendelian randomization, and MetaXcan to identify genes whose expression mediates the genotype effect on the phenotype. Our analyses identified Dachshund homolog 1 (DACH1), a cell-fate determination factor. GWAS risk variant was associated with lower DACH1 expression in human kidney tubules. Human and mouse kidney single-cell open chromatin data (snATAC-Seq) prioritized estimated glomerular filtration rate (eGFR) GWAS variants located on an intronic regulatory region in distal convoluted tubule cells. CRISPR-Cas9-mediated gene editing confirmed the role of risk variants in regulating DACH1 expression. Mice with tubule-specific Dach1 deletion developed more severe renal fibrosis both in folic acid and diabetic kidney injury models. Mice with tubule-specific Dach1 overexpression were protected from folic acid nephropathy. Single-cell RNA sequencing, chromatin immunoprecipitation, and functional analysis indicated that DACH1 controls the expression of cell cycle and myeloid chemotactic factors, contributing to macrophage infiltration and fibrosis development. In summary, integration of GWAS, TWAS, single-cell epigenome, expression analyses, gene editing, and functional validation in different mouse kidney disease models identified DACH1 as a kidney disease risk gene.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".