Amyloid-Journal of Protein Folding Disorders最新文献

Background: Hereditary transthyretin amyloidosis with polyneuropathy (ATTRv-PN) is often associated with neuropathic pain (NP), involving developing mechanisms across different nerve fibres. This study aimed to explore the relationship between NP intensity and clinical/neurophysiological measures in symptomatic ATTR V30M (p.V50M)-PN patients.

Methods: We included 106 symptomatic patients (46 males; mean age 47.5 ± 13.2 years). NP severity was classified using three pain-related items from the Norfolk QOL-DN, generating three groups: no pain, mild pain, and moderate-to-severe pain. Clinical and neurophysiological assessments included the Neuropathy Impairment Score (NIS), nerve conduction studies (sural SNAP, peroneal CMAP), electrochemical skin conductance (ESC), sympathetic skin response (SSR), and Quantitative Sensory Testing (QST). Statistical analyses included non-parametric tests and ordinal logistic regression.

Results: Patients with NP had significantly higher NIS scores and reduced sural/peroneal amplitudes and ESC values. However, only NIS was significantly associated with NP intensity (OR = 1.062, 95% CI: 1.008-1.119, p = .024). Subscore analysis showed the sensory component as the main driver (OR = 1.205, p = .015). QST variables differed by pain presence but not intensity.

Conclusion: NIS, especially its sensory subscore, is a robust predictor of NP severity in ATTRv-PN. These findings support its utility in monitoring disease burden and guiding management.

Objectives: Tafamidis has demonstrated survival benefits in transthyretin amyloid cardiomyopathy (ATTR-CM), yet variability in therapeutic response underscores the need for reliable tools to predict outcomes. This study evaluates the prognostic utility of cardiopulmonary exercise testing (CPET) in this population.

Methods: This retrospective study included tafamidis treated wild-type (ATTRwt) CM patients who completed CPET. Univariable and multivariable Cox regression models were used to evaluate predictors of mortality and composite secondary endpoint (mortality and heart failure admissions).

Results: Total of 105 ATTRwt-CM patients were enrolled with median age of 80 years. During median follow-up of 2.1 years, 33 (31%) died and 67 (63.8%) had composite outcome of mortality and heart failure hospitalisations. Multivariable analysis showed VE/VCO₂ slope (HR 1.61 per SD, 95% CI: 1.13-2.30, p = 0.01), peak circulatory power [CP] (HR 0.43 per SD, 95% CI 0.21-0.89, p = 0.02), Mayo stage 3 (HR 5.34, 95% CI: 1.07-26.7, p = 0.04) were independent predictors of mortality. The VE/VCO₂ slope (HR 1.57 per SD, 95% CI 1.2, 2.05, p= <0.01), creatinine (HR 1.37 per SD, 95% CI 1.07, 1.76, p = 0.01) and Mayo stage 3 (HR 2.49, 95% CI 1.10, 5.66, p = 0.03) were independent predictors of composite outcome.

Conclusions: CPET provides prognostic insights for ATTRwt-CM patients in addition to known prognostic laboratory factors.

Background: Amyloid typing, particularly in monoclonal gammopathies of renal significance, can be technically challenging. Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry Imaging (MALDI-MSI) has been proposed as a non-destructive method to detect and type amyloid deposits on a single tissue slide. This study aims to confirm this capability of MALDI-MSI in renal light chain amyloidosis (AL amyloidosis), irrespective of the fixative utilised, confronting results with other traditional and upcoming methods for amyloid detection.

Methodology: MALDI-MSI was applied to 15 renal biopsies diagnosed with AL amyloidosis. Results were compared with the routinely utilised methods of amyloid detection and typing, respectively, the pathologist's evaluation and immunofluorescence (IF) and additionally with a computational technique for amyloid detection, SPADA (Streamlined Pipeline for Amyloid Detection through Congo red fluorescence digital Analysis).

Results: MALDI-MSI demonstrated an agreement of 85.0% and 86.4% with SPADA and the pathologist in detecting glomerular deposits. It also showed complementary potential with SPADA, suggesting the possibility of combining all methodologies on a single tissue slide. Furthermore, MALDI-MSI showed a complete agreement with IF in amyloid typing.

Conclusion: This study confirmed the capability of MALDI-MSI to detect and type AL amyloidosis, assessing the possibility to integrate an additional computational method for amyloid detection on a single tissue slide.