Angiotensin II receptor blocker losartan exacerbates muscle damage and exhibits weak blood pressure-lowering activity in a dysferlin-null model of Limb-Girdle muscular dystrophy type 2B
Bibliographic record
Abstract
There is no cure or beneficial management option for Limb-Girdle muscular dystrophy (MD) type 2B (LGMD2B). Losartan, a blood pressure (BP) lowering angiotensin II (AngII) receptor type 1 (ATR1) blocker (ARB) with unique anti-transforming growth factor-β (TGF-β) properties, can protect muscles in various types of MD such as Duchenne MD, suggesting a potential benefit for LGMD2B patients. Herein, we show in a mild, dysferlin-null mouse model of LGMD2B that losartan increased quadriceps muscle fibrosis (142%; P<0.0001). In a severe, atherogenic diet-fed model of LGMD2B recently described by our group, losartan further exacerbated dysferlin-null mouse muscle wasting in quadriceps and triceps brachii, two muscles typically affected by LGMD2B, by 40% and 51%, respectively (P<0.05). Lower TGF-β signalling was not observed with losartan, therefore plasma levels of atherogenic lipids known to aggravate LGMD2B severity were investigated. We report that losartan increased both plasma triglycerides and cholesterol concentrations in dysferlin-null mice. Other protective properties of losartan, such as increased nitric oxide release and BP lowering, were also reduced in the absence of dysferlin expression. Our data suggest that LGMD2B patients may show some resistance to the primary BP-lowering effects of losartan along with accelerated muscle wasting and dyslipidemia. Hence, we urge caution on the use of ARBs in this population as their ATR1 pathway may be dysfunctional.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".