Reduced guanidinoacetate in plasma of patients with autosomal dominant Fanconi syndrome due to heterozygous <scp>P341L <i>GATM</i></scp> variant and study of organoids towards treatment
Bibliographic record
Abstract
Abstract Autosomal dominant Fanconi syndrome due to a GATM variant (GATM‐FS), causes accumulation of misfolded arginine‐glycine amidinotransferase (AGAT) in proximal renal tubules leading to cellular injury. GATM‐FS presents during childhood and progresses to end‐stage kidney disease (ESKD) in adults. We study creatine metabolism in two individuals of unrelated families with a known GATM variant and the effect of creatine supplementation in kidney organoids. Plasma and urine metabolites were measured by mass spectrometry. Brain creatine was assessed by magnetic resonance spectroscopy (MRS). Guanidinoacetate (GAA) synthesis by the AGAT mutant was measured in patient‐derived immortalized lymphocytes using stable isotopes of arginine and glycine. The effect of creatine on GATM expression was assessed in human kidney cells and organoids. Several family members from two unrelated families were diagnosed with Fanconi syndrome and had the c.1022C>T (p. P341L) variant in GATM . Two affected individuals in both families had moderately reduced plasma GAA levels. In comparison to wild‐type cells, GAA synthesis by patient‐derived GATM P341L+/− lymphoblastoid cell lines (LCL) was reduced, but not absent as in GATM cells from a patient with creatine deficiency syndrome. In vitro studies on human kidney organoids revealed reduced AGAT expression after treatment with creatine. Finally, we showed in one patient that creatine supplementation (5 g daily) substantially increased plasma creatine levels. We report low plasma and urine GAA in patients with autosomal dominant GATM‐FS and show that creatine downregulates AGAT in human kidney cells.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".