Fabry disease with atypical phenotype identified by massively parallel sequencing in early-onset kidney failure
Bibliographic record
Abstract
Background: The cause of chronic kidney disease (CKD) remains unknown in ∼20% of patients with kidney failure. Massively parallel sequencing (MPS) can be a valuable diagnostic tool in patients with unexplained CKD, with a diagnostic yield of 12%-56%. Here, we report the use of MPS to establish a genetic diagnosis in a 24-year-old index patient who presented with hypertension, nephrotic-range proteinuria and kidney failure of unknown origin. Additionally, we describe a second family with the same mutation presenting with early-onset CKD. Results: (p.Ile319Thr), and plasma globotriaosylsphingosine and α-galactosidase A activity were compatible with the diagnosis of Fabry disease (FD). Segregation analysis identified three other family members carrying the same pathogenic variant who had mild or absent kidney phenotypes. One family member was offered enzyme therapy. While FD could not be established with certainty as the cause of kidney failure in the index patient, no alternative explanation was found. In Family 2, the index patient had severe glomerulosclerosis and a kidney biopsy compatible with FD at the age of 30 years, along with cardiac involvement and a history of acroparesthesia since childhood, in keeping with a more classical Fabry phenotype. Conclusion: mutations in FD and underline several important implications of MPS in the work-up of patients with unexplained kidney failure.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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 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".