French Canadian Leigh Syndrome Due To Novel LRPPRC Variants C.1921?7A>G/C.2056A>G is Clinically Similar to Classical Leigh Syndrome
Bibliographic record
Abstract
With interest we read the article by Piro et al. about a preterm born male with Leigh syndrome French Canadian type (LSFC) due to the novel compound heterozygote variants c.1921–7A>G and c.2056A>G in LRPPRC [1]. The patient manifested phenotypically with developmental delay, dysmorphism, generalised hypotonia, poor sucking, dysphagia, cortical atrophy, vermal atrophy, callosal atrophy, hippocampal unfolding, hearing impairment, and visual impairment [1]. We have the following comments and conerns. The authors claim that LSFC has a distinct phenotype at variance from that of Leigh syndrome due to mutations in other genes. However, the phenotype of their index patient typically matched with that of classical Leigh syndrome. The patient presented with facial dysmorphism [2], neonatal hypotonia [3], non-epileptic paroxysmal motor phenomena [4], absent sucking-swallowing-breathing coordination [5], diffuse cortical atrophy [6], hypoplasia of the cerebellar vermis, and unfolded hippocampus [7]. The authors observed motor paroxysms involving the limbs, without concomitant EEG discharges but no classification of the phenomenon or causal relation was provided [1]. Do the authors interpret the motor phenomenon as myocloni, as subcortical seizure, or as dystonia? We should know if there was involvement of the spinal cord as has been previously reported in Leigh syndrome [4]. Patients with Leigh syndrome frequently present with lactic acidosis [8]. Lactate may not only be elevated in the serum but also in the brain. Thus, normal serum lactate levels, as reported in the index patient, do not exclude elevated lactate in the brain and we should know if lactate was elevated in the central nervous system (CNS). CNS lactate can be determined by measuring lactate levels in the cerebro-spinal fluid (CSF) or measuring brain tissue lactate by MR spectroscopy (MRS). A shortcoming of the study is that the patient was not prospectively investigated for multisystem disease. Leigh syndrome frequently goes along with affection of organs other than the CNS, including the eyes, ears, endocrine system, heart, gastro-intestinal tract, muscle, or kidneys [9]. Since cardiac involvement is of prognostic relvance and can strongly determine the outcome of these patients, we should know the results of echocardiography and long-term ECG monitoring, particularly if there was cardiomoypathy or ventricular arrhythmias. A further shortcoming is that no biochemical investigations of any affected tissue for measuring the function of respiratory chain complexes had been carried out. Knowing the degree of respiratory chain dysfunction is crucial as it may strongly determine the course and outcome of patients with Leigh syndrome and additionally may influence therapeutic decisions. Leigh syndrome may manifest with optic atrophy [10]. We should know if increaed P100 latencies on visually-evoked potentials were attributed to optic atrophy or retro-chiasmatic demyelination of the optic tract. A therapeutic option not mentioned in the report is the application of the ketogenic diet to treat epilepsy or other manifestations. Missing are axial T2/FLAIR sequences to see if the patient had bilaterally symmetric lesions of the basal ganglia, midbrain, pons, medulla, or cerebellum, as typically reported in patients with Leigh syndrome. Overall, the interesting study has a number of shortcomings which should be addressed before drawing final conclusions. Further investigations are warrented to assess the severity of affection, course, therapeutic options, prognosis, and eventual outcome of the index patient.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".