Systems biology identifies preserved integrity but impaired metabolism of mitochondria due to a glycolytic defect in Alzheimer's disease neurons
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Bibliographic record
Abstract
Mitochondrial dysfunction is implicated in most neurodegenerative diseases, including Alzheimer's disease (AD). We here combined experimental and computational approaches to investigate mitochondrial health and bioenergetic function in neurons from a double transgenic animal model of AD (PS2APP/B6.152H). Experiments in primary cortical neurons demonstrated that AD neurons had reduced mitochondrial respiratory capacity. Interestingly, the computational model predicted that this mitochondrial bioenergetic phenotype could not be explained by any defect in the mitochondrial respiratory chain (RC), but could be closely resembled by a simulated impairment in the mitochondrial NADH flux. Further computational analysis predicted that such an impairment would reduce levels of mitochondrial NADH, both in the resting state and following pharmacological manipulation of the RC. To validate these predictions, we utilized fluorescence lifetime imaging microscopy (FLIM) and autofluorescence imaging and confirmed that transgenic AD neurons had reduced mitochondrial NAD(P)H levels at rest, and impaired power of mitochondrial NAD(P)H production. Of note, FLIM measurements also highlighted reduced cytosolic NAD(P)H in these cells, and extracellular acidification experiments showed an impaired glycolytic flux. The impaired glycolytic flux was identified to be responsible for the observed mitochondrial hypometabolism, since bypassing glycolysis with pyruvate restored mitochondrial health. This study highlights the benefits of a systems biology approach when investigating complex, nonintuitive molecular processes such as mitochondrial bioenergetics, and indicates that primary cortical neurons from a transgenic AD model have reduced glycolytic flux, leading to reduced cytosolic and mitochondrial NAD(P)H and reduced mitochondrial respiratory capacity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it