Amyloid-Journal of Protein Folding Disorders最新文献

Background: Congo red (CR) staining of surrogate tissues, such as the abdominal fat pad (FP) or bone marrow (BM), provides a minimally invasive approach to diagnosing systemic amyloidosis. This study evaluated the diagnostic yield of surrogate tissue biopsies across amyloidosis classes.

Methods: We retrospectively analyzed 4,027 patients with systemic amyloidosis (1968-2023) who underwent CR staining of FP aspirates (n = 3,873) and/or BM core biopsies (n = 2,598). Detection rates were compared by amyloidosis class and biopsy site.

Results: AL amyloidosis had the highest CR positivity rates (FP: 73%; BM: 53%), whereas ATTRwt amyloidosis had the lowest (FP: 22%; BM: 26%). CR positivity in BM was not exclusive to AL amyloidosis; 74 CR-positive BM biopsies were in non-AL cases. Among 2,213 patients with AL amyloidosis who underwent both FP and BM sampling, combined testing increased detection to 85% (40% positive in both; 32% FP-only; 13% BM-only). Higher CR positivity grades in FP aspirates correlated with shorter survival in AL amyloidosis but not in other amyloidosis classes.

Conclusions: The diagnostic yield of CR-stained surrogate tissue biopsies varies by amyloidosis class and biopsy site. In AL amyloidosis, combining FP and BM sampling enhances detection, and FP CR positivity grade offers prognostic insight.

Background: Predicting amyloidogenic risk of immunoglobulin light chains in amyloid light-chain (AL) amyloidosis is a major challenge, and existing computational models fail to generalize to new patient data.

Methods: We developed ALyzer3D.AI, a multi-modal deep learning architecture that integrates evolutionary features from the ESM-2 Protein Language Model, structural metrics from ColabFold and engineered biophysical features. Generalizability was evaluated on published and independent datasets, and model interpretability was assessed using IMGT-aligned SHapley Additive exPlanations (SHAP).

Results: While existing models dropped in performance on new data (accuracy 0.42-0.56), ALyzer3D.AI maintained an accuracy of 0.65 when trained and tested on the same datasets. A final model built on the full combined cohort of 5261 sequences achieved stable performance across repeated splits, with independent test AUC of 0.86 and accuracy of 0.84 at an optimized decision threshold. Performance arose from synergistic integration of PLM, structural and scalar features. PLM attributions were broadly distributed and slightly enriched in framework regions, whereas structural SHAP values were concentrated in CDRs and FR4. The most informative positions had intermediate sequence entropy.

Conclusions: ALyzer3D.AI provides a robust, interpretable tool for predicting light-chain amyloidogenicity that generalizes better to independent datasets than existing methods. It is publicly available via https://colab.research.google.com/github/pcmay/ALyzer3D.AI/blob/main/ALyzer3DAI.ipynb.

Background: Hereditary transthyretin amyloidosis (ATTRv) is a rare, progressive disorder caused by TTR gene variants, leading to amyloid fibril deposition and clinical manifestations like cardiomyopathy and polyneuropathy. National data for Spain are scarce, despite known high-prevalence areas such as Majorca.

Methods: This multicentric, retrospective study analysed 4,526 individuals from 48/52 Spanish regions between 2015 and 2024, including 3,960 index cases and 566 at-risk relatives. Genetic testing was performed to identify pathogenic TTR variants.

Results: Among 393 carriers of pathogenic variants, the most prevalent were p.Val50Met (64.1%) and p.Val142Ile (29.5%). Regional prevalence varied, with new high-prevalence areas identified, including Cádiz, Castellón, Ciudad Real, Huelva, Valencia and Zamora. A novel variant of unknown clinical significance, p.Ser137Thr, was found in two unrelated cases. Genotype-phenotype correlations showed p.Val50Met is linked to neurological phenotypes, while p.Val142Ile is associated with cardiac manifestations. A male predominance was observed in index cases, while the sex ratio in carrier relatives was similar to the general population.

Conclusions: This is the largest nationwide study of ATTRv in Spain, providing key insights into its genetic landscape. The findings suggest migratory factors may influence variant distribution, emphasising the importance of genetic screening for early diagnosis and management.