Amyloid beta 42 alters cardiac metabolism and impairs cardiac function in obesity
Bibliographic record
Abstract
ABSTRACT There are epidemiological associations between obesity and type 2 diabetes, cardiovascular disease and Alzheimer’s disease. While some common aetiological mechanisms are known, the role of amyloid beta 42 (Aβ 42 ) in these diverse chronic diseases is obscure. Here we show that adipose tissue releases Aβ 42 , which is increased from adipose tissue of obese mice and is associated with higher plasma Aβ 42 . Increasing circulating Aβ 42 levels in non-obese mice had no effect on systemic glucose homeostasis but had obesity-like effects on the heart, including reduced cardiac glucose clearance and impaired cardiac function. These effects on cardiac function were not observed when circulating levels of the closely related Aβ 40 isoform were increased. Administration of an Aβ neutralising antibody prevented obesity-induced cardiac dysfunction and hypertrophy. Furthermore, Aβ neutralising antibody administration in established obesity prevented further deterioration of cardiac function. Multi-contrast transcriptomic analyses revealed that Aβ 42 impacted pathways of mitochondrial metabolism and exposure of cardiomyocytes to Aβ 42 inhibited mitochondrial function. These data reveal a role for systemic Aβ 42 in the development of cardiac disease in obesity and suggest that therapeutics designed for Alzheimer’s disease could be effective in combating obesity-induced heart failure.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".