Generation and Evaluation of Isogenic iPSC as a Source of Cell Replacement Therapies in Patients with Kearns Sayre Syndrome
Bibliographic record
Abstract
Kearns Sayre syndrome (KSS) is mitochondrial multisystem disorder with no proven effective treatment. The underlying cause for multisystem involvement is the energy deficit resulting from the load of mutant mitochondrial DNA (mtDNA), which manifests as loss of cells and tissue dysfunction. Therefore, functional organ or cellular replacement provides a promising avenue as a therapeutic option. Patient-specific induced pluripotent stem cells (iPSC) have become a handy tool to create personalized cell -based therapies. iPSC are capable of self-renewal, differentiation into all types of body cells including cardiomyocytes (CM) and neural progenitor cells (NPC). In KSS patients, mutations in mtDNA are largely found in the muscle tissue and are predominantly absent in the blood cells. Therefore, we conceptualized that peripheral blood mononuclear cells (PBMNC) from KSS patients can be reprogrammed to generate mutation free, patient specific iPSC lines that can be used as isogenic source of cell replacement therapies to treat affected organs. In the current study we generated iPSC lines from two female patients with clinical diagnosis of classic KSS. Our data demonstrate that iPSC from these KSS patients showed normal differentiation potential toward CM, NPC and fibroblasts without any mtDNA deletions over passages. Next, we also found that functional studies including ATP production, reactive oxygen species generation, lactate accumulation and mitochondrial membrane potential in iPSC, CM, NPC and fibroblasts of these KSS patients were not different from respective cells from healthy controls. PBMNCs from these KSS patients in the current study did not reproduce mtDNA mutations which were present in muscle biopsies. Furthermore, we demonstrate for the first time that this phenomenon provides opportunities to create isogenic mutation free iPSC with absent or very low level of expression of mtDNA deletion which can be banked for future cell replacement therapies in these patients as the disease progresses.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".