Copy Number Variation Analysis Facilitates Identification of Genetic Causation in Patients with Congenital Anomalies of the Kidney and Urinary Tract
Bibliographic record
Abstract
Background: Congenital anomalies of the kidneys and urinary tract (CAKUT) are the most common cause of chronic kidney disease among children and adults younger than 30 yr. In our previous study, whole-exome sequencing (WES) identified a known monogenic cause of isolated or syndromic CAKUT in 13% of families with CAKUT. However, WES has limitations and detection of copy number variations (CNV) is technically challenging, and CNVs causative of CAKUT have previously been detected in up to 16% of cases. Objective: To detect CNVs causing CAKUT in this WES cohort and increase the diagnostic yield. Design setting and participants: We performed a genome-wide single nucleotide polymorphism (SNP)-based CNV analysis on the same CAKUT cohort for whom WES was previously conducted. Outcome measurements and statistical analysis: We evaluated and classified the CNVs using previously published predefined criteria. Results and limitations: In a cohort of 170 CAKUT families, we detected a pathogenic CNV known to cause CAKUT in nine families (5.29%, 9/170). There were no competing variants on genome-wide CNV analysis or WES analysis. In addition, we identified novel likely pathogenic CNVs that may cause a CAKUT phenotype in three of the 170 families (1.76%). Conclusions: CNV analysis in this cohort of 170 CAKUT families previously examined via WES increased the rate of diagnosis of genetic causes of CAKUT from 13% on WES to 18% on WES + CNV analysis combined. We also identified three candidate loci that may potentially cause CAKUT. Patient summary: We conducted a genetics study on families with congenital anomalies of the kidney and urinary tract (CAKUT). We identified gene mutations that can explain CAKUT symptoms in 5.29% of the families, which increased the percentage of genetic causes of CAKUT to 18% from a previous study, so roughly one in five of our patients with CAKUT had a genetic cause. These analyses can help patients with CAKUT and their families in identifying a possible genetic cause.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".