Breakthrough advances enhancing care in ATTR amyloid cardiomyopathy

Mechanisms of damage and therapies for cardiac amyloidosis: a role for inflammation?

The term cardiac amyloidosis (CA) refers to the accumulation of extracellular amyloid deposits in the heart because of different conditions often affecting multiple organs including brain, kidney and liver. Notably, cardiac involvement significantly impacts prognosis of amyloidosis, with cardiac biomarkers playing a pivotal role in prognostic stratification. Therapeutic management poses a challenge due to limited response to conventional heart failure therapies, necessitating targeted approaches aimed at preventing, halting or reversing amyloid deposition. Mechanisms underlying organ damage in CA are multifactorial, involving proteotoxicity, oxidative stress, and mechanical interference. While the role of inflammation in CA remains incompletely understood, emerging evidence suggests its potential contribution to disease progression as well as its utility as a therapeutic target. This review reports on the cardiac involvement in systemic amyloidosis, its prognostic role and how to assess it. Current and emerging therapies will be critically discussed underscoring the need for further efforts aiming at elucidating CA pathophysiology. The emerging evidence suggesting the contribution of inflammation to disease progression and its prognostic role will also be reviewed possibly offering insights into novel therapeutic avenues for CA.

Molecular basis for non-invasive diagnostics of cardiac amyloids using bone tracers

Amyloid diseases including Alzheimer's, Parkinson's and over 30 others are incurable life-threatening disorders caused by abnormal protein deposition as fibrils in various organs. Cardiac amyloidosis is particularly challenging to diagnose and treat. Identification of the fibril-forming protein, which in the heart is usually amyloid transthyretin (ATTR) or amyloid immunoglobulin light chain (AL), is paramount to treatment. A transformative non-invasive diagnostic modality is imaging using technetium-labeled pyrophosphate or diphosphonate bone tracers, 99mTc-PYP/DPD/HMDP. For unknown reasons, these tracers show preferential uptake by ATTR deposits. The tracer-binding moiety is unknown and potentially involves amyloid fibrils and/or amyloid-associated calcific deposits. We propose that, like in the bone, the tracers chelate to surface-bound Ca2+ in amyloid. In high-affinity protein sites, Ca2+ is coordinated by pairs of acidic residues. To identify such residues on amyloids, we harnessed atomic structures of patient-derived cardiac amyloids determined using cryogenic electron microscopy since 2019. These structures help explain why most but not all ATTR deposits uptake 99mTc-PYP/DPD/HMDP radiotracers, while in AL the opposite is true. Moreover, fibril structures help explain greater microcalcification observed in ATTR vs. AL deposits. These findings may aid the diagnostics and therapeutic targeting of cardiac amyloidosis and are relevant to other amyloids.

Cardiac Amyloidosis: A Comprehensive Review of Pathophysiology, Diagnostic Approach, Applications of Artificial Intelligence, and Management Strategies

Cardiac amyloidosis (CA) is a serious and often fatal condition caused by the accumulation of amyloid fibrils in the heart, leading to progressive heart failure. It involves the misfolding of normally soluble proteins into insoluble amyloid fibrils, with transthyretin and light-chain amyloidosis being the most common forms affecting the heart. Advances in diagnostics, especially cardiac magnetic resonance imaging and non-invasive techniques, have improved early detection and disease management. Artificial intelligence has emerged as a diagnostic tool for cardiac amyloidosis, improving accuracy and enabling earlier intervention through advanced imaging analysis and pattern recognition. Management strategies include volume control, specific pharmacotherapies like tafamidis, and addressing arrhythmias and advanced heart failure. However, further research is needed for novel therapeutic approaches, the long-term effectiveness of emerging treatments, and the optimization of artificial intelligence applications in clinical practice for better patient outcomes. The article aims to provide an overview of CA, outlining its pathophysiology, diagnostic advancements, the role of artificial intelligence, management strategies, and the need for further research.