Cardiac Amyloidosis

MRI-Extracellular Volume Fraction Versus Histological Amyloid Load in Cardiac Amyloidosis: The Importance of T2 Mapping

BACKGROUND

MRI-derived myocardial extracellular volume fraction (ECV) is elevated in the presence of fibrosis, amyloid deposition, inflammation and edema. In patients with cardiac amyloidosis and prolonged T2 due to concomitant inflammation or edema, MRI-ECV may not correctly reflect histological amyloid load. The authors sought to determine whether MRI-ECV can accurately reflect histological amyloid load in 2 groups of patients with wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM), with and without T2 prolongation.

METHODS

This retrospective study included consecutive patients with ATTRwt-CM who underwent endomyocardial biopsy and cardiac MRI from March 2017 to October 2021 for initial evaluation of ATTRwt-CM. We measured MRI-ECV and T2, and evaluated correlation between MRI-ECV and amyloid load from endomyocardial biopsy by means of Pearson correlation analysis.

RESULTS

Of 44 patients (mean age, 75±6 years [SD]; 40 men), 24 showed T2 prolongation (T2≥50 milliseconds). All specimens obtained by endomyocardial biopsy were suitable for analysis. The interval between endomyocardial biopsy and cardiac MRI examination was a median of 3 days (interquartile range, 2-4). In the absence of T2 prolongation due to increased water content, MRI-ECV and amyloid load showed a moderately significant correlation (Spearman ρ=0.50, P=0.03). However, in the presence of T2 prolongation, there was no significant correlation between MRI-ECV and amyloid load (Spearman ρ=-0.05, P=0.83).

CONCLUSIONS

In patients with ATTRwt-CM and prolonged T2, MRI-ECV did not accurately reflect histological amyloid load. Our findings underscore the need for a multiparametric imaging approach, combining both ECV and T2 mapping, to better characterize myocardial tissue in patients with ATTRwt-CM, and further prospective research in larger and more diverse cohorts is needed to validate our results.

Potential Hematopoietic Effects of SGLT2 Inhibitors in Patients with Cardiac Amyloidosis

Background

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have been found to have potential hematopoietic effects in patients with heart failure (HF). However, these benefits have not been studied in patients with cardiac amyloidosis (CA). CA patients present with HF symptoms and often suffer from iron deficiency, which has a negative impact on erythropoiesis and leads to lower hemoglobin and hematocrit levels. We sought to determine the potential effects of SGLT2i on hematological parameters and functional capacity (FC) in CA patients.

Methods

A prospective analysis was conducted to compare the effects of SGLT2i in patients who received the best medical therapy (BMT) along with SGLT2i (n = 20), versus patients receiving only BMT without SGLT2i (n = 20) (historical control group). All patients underwent blood testing and cardiopulmonary exercise testing (CPET) at baseline (BL) and after 6 months [interquartile range (IQR): 4.0 to 8.0].

Results

The SGLT2i-based therapy resulted in a significant improvement and difference in hematological parameters at 6 months follow-up compared to the control group. In the SGLT2i group, the mean hemoglobin level increased (+1.2 mg/dL), whereas in the control group, it decreased (-0.8 g/dL) (p < 0.001 for overall group comparison). The hematocrit showed a significant increase in the SGLT2i group (+4.4%) compared to a decrease in the control group (-1.8%) (p < 0.001). Additionally, the serum iron level improved in the SGLT2i-treated group (+ 5.5 [-5.0 to 17.5] μg/dL vs. -6.0 [-15.0 to 4.0] μg/dL, p = 0.121). Although there was no significant change in the peak oxygen consumption (peak VO2, (mL/min)/kg) (p = 0.206), as well as in pulmonary ventilation (VE)/carbon dioxide production (VCO2) slope in both groups (p = 0.964), the SGLT2i group maintained a peak VO2 and VE/VCO2 slope throughout the study.

Conclusions

SGLT2i therapy improved hematological parameters and stabilized the FC of CA patients.

Prevalence and functional impact of chronotropic incompetence in amyloid cardiomyopathy: a multicentre analysis

BACKGROUND

Little evidence is available about heart rate (HR) response to exercise as well as its relationship with functional capacity in amyloid cardiomyopathy. Then, in a multicentre cohort of patients with amyloid cardiomyopathy, we investigated the prevalence of chronotropic incompetence (CI) and its relationships with cardiopulmonary exercise testing (CPET) variables.

METHODS

Data from 172 outpatients with amyloid cardiomyopathy who performed a maximal CPET and who had no significant rhythm disorders were analysed.

RESULTS

The prevalence of CI differed depending on the age-predicted peak HR (pHR%) cut-off value adopted, ranging from 16% to 59%. pHR% correlated non-linearly with peak oxygen uptake (pVO2), either as expressed as a percentage of the maximum predicted or as mL/kg/min (p<0.001). Although to a lesser extent, pHR% correlated inversely with ventilatory efficiency (p<0.001). A pHR%≤75% resulted in the most accurate cut-off value in identifying a moderate-to-severe exercise impairment (sensitivity 72%; specificity 73%; area under the curve 77.2%).

CONCLUSIONS

CI is prevalent in patients with amyloid cardiomyopathy in sinus rhythm, its percentage varying according to the pHR% cut-off value. A blunted exercise-induced HR response correlated with a poor exercise capacity even in this setting of patients, a pHR%≤75% cut-off value being possibly useful in centres without CPET availability to identify a significant exercise impairment.

Prevalence and outcomes of concomitant cardiac amyloidosis and coronary artery disease

BACKGROUND

Cardiac amyloidosis (CA) and coronary artery disease (CAD) can have similar presentations in the acute care setting which can potentially delay the diagnosis of CA.

METHODS

We conducted a retrospective analysis of patients referred to our institution for evaluation of cardiac amyloidosis. We obtained demographic and clinical characteristics, laboratory data, and echocardiographic measurements of those patients with confirmed cardiac amyloidosis. The population was divided into two groups based on the presence of CAD. Frequency of heart failure hospitalizations, and one-year overall mortality were compared between both groups.

RESULTS

Between 2018 to 2021, 327 patients with suspected cardiac amyloidosis were referred to our institution. Out of 114 confirmed CA patients, 28 patients (25%) had concomitant CAD and CA. The overall mean age of CA diagnosis was 74.7 (±8.4) years for the CAD group and 69.7 (±9.8) for the non-CAD group (P value 0.002). Notably, a higher percentage of males were observed in the CAD group (92/.9% vs. 60%, p-value 0.002), and a higher prevalence of hypertension (92.9% vs 70%, p-value 0.018) and dyslipidemia (89.3% vs 59%, p-value 0.004) were also found in the CAD group. Overall, there were no significant differences in outcomes.

CONCLUSION

Larger studies are needed to identify characteristics that will result in a prompt diagnosis of CA in patients with concomitant CAD. Although our study did not appreciate a significant difference between these two groups, outcomes of our study were likely impacted by a small sample size in the CA with CAD cohort.

Endovascular thrombectomy for acute ischemic stroke complicated with systemic light chain amyloidosis: Two case reports

Systemic light chain amyloidosis (AL) is a non-proliferative plasma cell disease characterized by the deposition of fragments of immunoglobulin light or heavy chain in tissues. There has been no relevant report on the treatment of vascularization during the acute stage of acute ischemic stroke (AIS) complicated with AL. This paper presented two cases of AIS complicated with AL that were treated with intravenous thrombolysis (IVT) and mechanical thrombectomy (MT). The combination of aspiration thrombectomy and IVT might be feasible for patients with AIS complicated with AL.

Evolving Strategies in Cardiac Amyloidosis: From Mechanistic Discoveries to Diagnostic and Therapeutic Advances

Diagnosis and treatment of cardiac amyloidosis have rapidly evolved over the past decade by harnessing mechanisms of disease pathogenesis. Cardiac amyloidosis is caused by myocardial deposition of fibrils formed by misfolded proteins, namely transthyretin (ATTR) and immunoglobulin light chains (AL). Advances in noninvasive imaging have revolutionized diagnosis of ATTR cardiomyopathy (CM). Novel treatments for ATTR-CM utilize a range of therapeutic techniques, including protein stabilizers, interfering RNA, gene editing, and monoclonal antibodies. AL-CM, primarily driven by plasma cell dyscrasias, requires treatment with chemotherapy and consideration for autologous stem cell transplant. These incredible advances aim to improve patient outcomes in cardiac amyloidosis.

Cardiovascular magnetic resonance-derived left atrioventricular coupling index as a novel prognostic marker for light-chain amyloidosis

BACKGROUND

Left atrioventricular coupling index (LACI) is a novel biomarker, and the prognostic value of LACI to predict cardiovascular events has been validated. The present study aimed to explore the prognostic value of LACI in patients with light-chain (AL) amyloidosis.

METHODS

We prospectively enrolled 179 patients with AL amyloidosis who underwent cardiovascular magnetic resonance imaging between December 2011 and January 2020. LACI was defined as the ratio between the left atrial volume and the left ventricular volume at end-diastole. The primary endpoint was all-cause mortality. Receiver operating characteristic curve was used to identify the optimal cut-off of LACI in predicting all-cause mortality. Univariable and multivariable Cox proportional hazard models were used to assess the association of LACI and primary endpoint.

RESULTS

During a median follow-up of 30 months, 118 (65.9 %) patients with all-cause mortality were documented. LACI was significantly higher in patients with primary endpoint compared to those without primary endpoint (55.4 %, interquartile range: 31.6 %-71.5 % vs. 39.4 %, interquartile range: 24.1 %-54.7 %, p = 0.001). The optimal cut-off for LACI to predict mortality was 49.3 %. In multivariate Cox regression analysis, LACI≥49.3 % (HR 1.907, 95 % CI 1.273-2.857, p = 0.002) was an independent predictor of all-cause mortality. On Kaplan-Meier analysis, patients at advanced Mayo stage (IIIa and IIIb) can be further risk stratified using LACI≥49.3 % (log-rank p = 0.035, p = 0.025).

CONCLUSION

The LACI provides powerful independent prognostic value in AL amyloidosis. The LACI has incremental prognostic value to predict all-cause mortality over the Mayo stage in patients at the advanced Mayo stage.

Advancements in Cardiac Amyloidosis Treatment

Cardiac amyloidosis (CA) is a progressive condition resulting from the deposition of amyloid fibrils in the heart, which leads to severe diastolic dysfunction and restrictive cardiomyopathy. The disease has two main subtypes: light-chain and transthyretin (TTR) CA, with the latter subdivided into wild-type and hereditary forms. Despite advances in diagnostic imaging, early detection remains a challenge due to non-specific symptoms that mimic other cardiac conditions. Treatment has evolved significantly with targeted therapies like TTR stabilizers, gene silencers, and RNA interference, showing promise in altering disease progression. However, barriers such as high costs, limited availability of genetic testing, and inadequate multidisciplinary care continue to impede comprehensive management. Future strategies should focus on integrating novel gene-editing therapies, expanding access to diagnostics, and enhancing multidisciplinary care models to improve outcomes. Overall, early diagnosis, equitable access to therapies, and personalized management plans are crucial to advancing care for CA patients.

Strain echocardiography predictors in patients with concomitant cardiac amyloidosis and aortic stenosis: a cross-sectional study

BACKGROUND

Concomitant cardiac amyloidosis (CA) and aortic stenosis (AS) may be mistaken for isolated AS, potentially impacting the treatment strategy and patient's prognosis. Therefore, it is crucial to distinguish between these conditions, as failure to promptly diagnose CA may lead to considerable complications. The aim of this study is to investigate the diagnostic value of strain predictors in patients with concomitant CA and AS compared to isolated AS.

METHODS

Forty-two patients with severe AS suspected of concomitant CA based on a comprehensive clinical evaluation were selected to undergo 99mTc-DPD scintigraphy. Those showing Perugini grade 2 or 3 tracer uptakes without evidence of monoclonal gammopathy were diagnosed with CA and underwent speckle-tracking echocardiography. Furthermore, strain analysis was performed to evaluate myocardial deformation, with a focus on detecting apical sparing and reduction in bull's eye mapping, resulting in the characteristic "cherry on top" sign.

RESULTS

Eight patients were diagnosed with CA, representing 19.0% of those suspected of concomitant CA and 7.8% of the overall cohort with severe AS. AF arrhythmia was significantly more frequent in these patients compared to those with isolated AS. Echocardiography findings revealed that E/E' ratio and RALS were significantly higher in patients with concomitant CA, while GLS and mean basal LS were significantly lower in this group. The "cherry on top" sign was detected in 19 patients (45.2%), present in 100% of those with concomitant CA and AS, versus 32.4% in isolated AS cases (P = 0.04). This sign demonstrated a sensitivity of 100% and a specificity of 67.6% for predicting concomitant CA and AS.

CONCLUSIONS

In conclusion, the "cherry on top" sign was significantly more prevalent in patients with concomitant CA and AS, compared to those with isolated AS, demonstrating a sensitivity of 100% and a specificity of 67.6% for predicting concomitant CA. Moreover, RALS and E/E' ratios were significantly higher in patients with concomitant CA, whereas GLS and mean basal LS were significantly lower in this group.

Exogenous Amyloid Fibrils Can Cause Significant Upregulation of Neurodegenerative Disease Proteins

Neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease, are associated with the formation of amyloid fibrils. In familial cases, the mutant causative genes accentuate disease progression through overexpression or misfolding of amyloidogenic proteins. Besides, considerable amyloidosis cases arise from external factors, but their origin and mechanisms are not yet fully understood. Herein, we found that amyloid fibrils generated from egg and milk proteins, in addition to their nutritional effects to intestinal cells, can selectively reduce the viability of nervous cells as well as pancreatic islet cells. In contrast, soy protein amyloid fibrils lacked cytotoxicity to the aforementioned cells. This protein source and cell type-dependent cytotoxicity are demonstrated to be associated with the significant upregulation of amyloidogenic proteins. The finding was also confirmed by the vein injection of beta-lactoglobulin fibrils to mice, exhibiting the pronounced upregulations of amyloid beta1-42 (Aβ1-42) and islet amyloid polypeptide in vivo. The study therefore provides insight into the health implications of exogenous amyloid fibrils.

A machine learning prediction model for Cardiac Amyloidosis using routine blood tests in patients with left ventricular hypertrophy

Current approaches for cardiac amyloidosis (CA) identification are time-consuming, labor-intensive, and present challenges in sensitivity and accuracy, leading to limited treatment efficacy and poor prognosis for patients. In this retrospective study, we aimed to leverage machine learning (ML) to create a diagnostic model for CA using data from routine blood tests. Our dataset included 6,563 patients with left ventricular hypertrophy, 261 of whom had been diagnosed with CA. We divided the dataset into training and testing cohorts, applying ML algorithms such as logistic regression, random forest, and XGBoost for automated learning and prediction. Our model's diagnostic accuracy was then evaluated against CA biomarkers, specifically serum-free light chains (FLCs). The model's interpretability was elucidated by visualizing the feature importance through the gain map. XGBoost outperformed both random forest and logistic regression in internal validation on the testing cohort, achieving an area under the curve (AUC) of 0.95 (95%CI: 0.92-0.97), sensitivity of 0.92 (95%CI: 0.86-0.98), specificity of 0.95 (95%CI: 0.94-0.97), and an F1 score of 0.89 (95%CI: 0.85-0.92). Its performance was also superior to the serum FLC-kappa and FLC-lambda combination (AUC of 0.88). Furthermore, XGBoost identified unique biomarker signatures indicative of multisystem dysfunction in CA patients, with significant changes in eGFR, FT3, cTnI, ANC, and NT-proBNP. This study develops a highly sensitive and accurate ML model for CA detection using routine clinical laboratory data, effectively streamlining diagnostic procedures, and providing valuable clinical insights and guiding future research into disease mechanisms.

Cardiac Amyloidosis: State-of-the-Art Review in Molecular Pathology

Amyloidosis refers to a group of diseases caused by extracellular deposits of misfolded proteins, which alter tissue function and structure, potentially affecting any organ. The term "amyloid" was introduced in the 19th century and later associated with pathological protein deposits. Amyloid fibrils, which are insoluble and resistant to degradation, originate from soluble proteins that undergo misfolding. This process can be triggered by several factors, such as aging, elevated protein concentrations, or pathogenic variants. Amyloid deposits damage organs both by disrupting tissue architecture and through direct cytotoxic effects, leading to conditions such as heart failure. Amyloidosis can be classified into acquired or inherited forms and can be systemic or localized. Diagnosing cardiac amyloidosis is complex and often requires tissue biopsies, which are supported by Congo Red dye staining. In some cases, bisphosphonate bone scans may provide a less invasive diagnostic option. In this state-of-the-art review, we focus on the most common forms of cardiac amyloidosis, from epidemiology to therapy, emphasizing the differences in molecular mechanisms and the importance of pathological diagnosis for appropriate treatment using a multidisciplinary approach.

Impact of Case and Control Selection on Training Artificial Intelligence Screening of Cardiac Amyloidosis

Background

Recent studies suggest that cardiac amyloidosis (CA) is significantly underdiagnosed. For rare diseases like CA, the optimal selection of cases and controls for artificial intelligence model training is unknown and can significantly impact model performance.

Objectives

This study evaluates the performance of electrocardiogram (ECG) waveform-based artificial intelligence models for CA screening and assesses impact of different criteria for defining cases and controls.

Methods

Using a primary cohort of ∼1.3 million ECGs from 341,989 patients, models were trained using different case and control definitions. Case definitions included ECGs from patients with an amyloidosis diagnosis by International Classification of Diseases-9/10 code, patients with CA, and patients seen in CA clinic. Models were then tested on test cohorts with identical selection criteria as well as a Cedars-Sinai general patient population cohort.

Results

In matched held-out test data sets, different model AUCs ranged from 0.660 (95% CI: 0.642-0.736) to 0.898 (95% CI: 0.868-0.924). However, algorithms exhibited variable generalizability when tested on a Cedars-Sinai general patient population cohort, with AUCs dropping to 0.467 (95% CI: 0.443-0.491) to 0.898 (95% CI: 0.870-0.923). Models trained on more well-curated patient cases resulted in higher AUCs on similarly constructed test cohorts. However, all models performed similarly in the overall Cedars-Sinai general patient population cohort. A model trained with International Classification of Diseases 9/10 cases and population controls matched for age and sex resulted in the best screening performance.

Conclusions

Models performed similarly in population screening, regardless of stringency of cases used during training, showing that institutions without dedicated amyloid clinics can train meaningful models on less curated CA cases. Additionally, AUC or other metrics alone are insufficient in evaluating deep learning algorithm performance. Instead, evaluation in the most clinically meaningful population is key.

Advances in the Diagnosis and Management of Cardiac Amyloidosis: A Literature Review

Cardiac amyloidosis, increasingly recognized for its significant impact on global heart health and patient survival, demands a thorough review to understand its complexity and the urgency of improved management strategies. As a cause of cardiomyopathy and heart failure, particularly in patients with aortic stenosis and atrial fibrillation, this condition also relates to higher incidences of dementia in the affected populations. The objective of this review was to integrate and discuss the latest advancements in diagnostics and therapeutics for cardiac amyloidosis, emphasizing the implications for patient prognosis. We evaluated the latest literature from major medical databases such as PubMed and Scopus, focusing on research from 2020 to 2024, to gather comprehensive insights into the current landscape of this condition. Insights from our review highlight the complex pathophysiology of cardiac amyloidosis and the diagnostic challenges it presents. We detail the effectiveness of emerging treatments, notably gene silencing therapies like patisiran and vutrisiran, which offer transformative potential by targeting the production of amyloidogenic proteins. Additionally, the stabilization therapy acoramidis shows promise in modifying disease progression and improving clinical outcomes. This review underscores the critical need for updated clinical guidelines and further research to expand access to groundbreaking therapies and enhance disease management. Advocating for continued research and policy support, we emphasize the importance of advancing diagnostic precision and treatment effectiveness, which are vital for improving patient outcomes and addressing this debilitating disease globally.

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.

Transthyretin Cardiac Amyloidosis in an Elderly Male With Heart Failure Intolerant to Guideline-Directed Medical Therapy

Cardiac amyloidosis arises when there is a deposition of abnormal proteins, called amyloids, in the myocardium. It can manifest as overt heart failure, conduction abnormalities, atrial and ventricular arrhythmia, cardiomyopathy, and aortic stenosis. Two main types of proteins identified in cardiac amyloidosis are light-chain amyloid and transthyretin amyloid. Cardiac amyloidosis, although common, is an underdiagnosed cause of heart failure in many cases. A high index of suspicion is needed to make a diagnosis, given that symptoms are not specific. Early diagnosis and treatment of cardiac amyloidosis are associated with reduced morbidity and improved survival. We present a case of a 73-year-old African American male with decompensated heart failure with reduced ejection fraction intolerant to guideline-directed medical therapy who was later found to have cardiac amyloidosis.

Early diagnosis and management of cardiac amyloidosis: A clinical perspective

Cardiac amyloidosis multidisciplinary team (MDT). We propose the creation of a multidisciplinary team (MDT) for cardiac amyloidosis in which internal medicine physicians could take a lead role in coordinating other specialists involved in patient care. Created with BioRender.com.

Chest Tightness With QR and ST-Segment Elevation in Lead V1

This case report describes a patient in their 50s with a 2-month history of worsening chest tightness and dyspnea after COVID-19 infection.

Emerging therapeutic avenues in cardiac amyloidosis

Cardiac Amyloidosis (CA) is a toxic infiltrative cardiomyopathy occurred by the deposition of the amyloid fibres in the extracellular matrix of the myocardium. This results in severe clinical complications such as increased left ventricular wall thickness and interventricular stiffness, a decrease in left ventricular stroke volume and cardiac output, diastolic dysfunction, arrhythmia, etc. In a prolonged period, this condition progresses into heart failure. The amyloid fibres affecting the heart include immunoglobulin light chain (AL - amyloidosis) and transthyretin protein (ATTR - amyloidosis) misfolded amyloid fibres. ATTRwt has the highest prevalence of 155 to 191 cases per million while ATTRv has an estimated prevalence of 5.2 cases per million. The pathological findings and therapeutic approaches developed recently have aided in the treatment regimen of cardiac amyloidosis patients. In recent years, understanding the pathophysiology of amyloid fibres formation and mechanistic pathways triggered in both types of cardiac amyloidosis has led to the development of new therapeutic approaches and agents. This review focuses on the current status of emerging therapeutic agents in clinical trials. Earlier, melphalan and bortezomib in combination with alkylating agents and immunomodulatory drugs were used as a standard therapy for AL amyloidosis. Tafamidis, approved recently by FDA is used as a standard for ATTR amyloidosis. However, the emerging therapeutic agents under development for the treatment of AL and ATTR cardiac amyloidosis have shown a potent and rapid effect with a safety profile.

Identification of a novel splicing-altering LAMP2 variant in a Chinese family with Danon disease

AIMS

This study aimed to identify a novel splicing-altering LAMP2 variant associated with Danon disease.

METHODS AND RESULTS

To identify the potential genetic mutation in a Chinese pedigree, whole-exome sequencing was conducted in the proband, and Sanger sequencing was performed on the proband's parents. To verify the impact of the splice-site variant, a minigene splicing assay was applied. The AlphaFold2 analysis was used to analyse the mutant protein structure. A splice-site variant (NM_013995.2:c.864+5G>A) located at intron 6 of the LAMP2 gene was identified as a potential pathogenic variant. The minigene splicing revealed that this variant causes exon 6 to be skipped, resulting in a truncated protein. The AlphaFold2 analysis showed that the mutation caused a protein twist direction change, leading to conformational abnormality.

CONCLUSIONS

A novel splice-site variant (NM_013995.2:c.864+5G>A) located at intron 6 of the LAMP2 gene was identified. This discovery may enlarge the LAMP2 variant spectrum, promote accurate genetic counselling, and contribute to the diagnosis of Danon disease.

Role of the mechanisms for antibody repertoire diversification in monoclonal light chain deposition disorders: when a friend becomes foe

The adaptive immune system of jawed vertebrates generates a highly diverse repertoire of antibodies to meet the antigenic challenges of a constantly evolving biological ecosystem. Most of the diversity is generated by two mechanisms: V(D)J gene recombination and somatic hypermutation (SHM). SHM introduces changes in the variable domain of antibodies, mostly in the regions that form the paratope, yielding antibodies with higher antigen binding affinity. However, antigen recognition is only possible if the antibody folds into a stable functional conformation. Therefore, a key force determining the survival of B cell clones undergoing somatic hypermutation is the ability of the mutated heavy and light chains to efficiently fold and assemble into a functional antibody. The antibody is the structural context where the selection of the somatic mutations occurs, and where both the heavy and light chains benefit from protective mechanisms that counteract the potentially deleterious impact of the changes. However, in patients with monoclonal gammopathies, the proliferating plasma cell clone may overproduce the light chain, which is then secreted into the bloodstream. This places the light chain out of the protective context provided by the quaternary structure of the antibody, increasing the risk of misfolding and aggregation due to destabilizing somatic mutations. Light chain-derived (AL) amyloidosis, light chain deposition disease (LCDD), Fanconi syndrome, and myeloma (cast) nephropathy are a diverse group of diseases derived from the pathologic aggregation of light chains, in which somatic mutations are recognized to play a role. In this review, we address the mechanisms by which somatic mutations promote the misfolding and pathological aggregation of the light chains, with an emphasis on AL amyloidosis. We also analyze the contribution of the variable domain (V_L) gene segments and somatic mutations on light chain cytotoxicity, organ tropism, and structure of the AL fibrils. Finally, we analyze the most recent advances in the development of computational algorithms to predict the role of somatic mutations in the cardiotoxicity of amyloidogenic light chains and discuss the challenges and perspectives that this approach faces.

Machine Learning Approaches in Diagnosis, Prognosis and Treatment Selection of Cardiac Amyloidosis

Cardiac amyloidosis is an uncommon restrictive cardiomyopathy featuring an unregulated amyloid protein deposition that impairs organic function. Early cardiac amyloidosis diagnosis is generally delayed by indistinguishable clinical findings of more frequent hypertrophic diseases. Furthermore, amyloidosis is divided into various groups, according to a generally accepted taxonomy, based on the proteins that make up the amyloid deposits; a careful differentiation between the various forms of amyloidosis is necessary to undertake an adequate therapeutic treatment. Thus, cardiac amyloidosis is thought to be underdiagnosed, which delays necessary therapeutic procedures, diminishing quality of life and impairing clinical prognosis. The diagnostic work-up for cardiac amyloidosis begins with the identification of clinical features, electrocardiographic and imaging findings suggestive or compatible with cardiac amyloidosis, and often requires the histological demonstration of amyloid deposition. One approach to overcome the difficulty of an early diagnosis is the use of automated diagnostic algorithms. Machine learning enables the automatic extraction of salient information from “raw data” without the need for pre-processing methods based on the a priori knowledge of the human operator. This review attempts to assess the various diagnostic approaches and artificial intelligence computational techniques in the detection of cardiac amyloidosis.

The importance of pathways to facilitate early diagnosis and treatment of patients with cardiac amyloidosis

Cardiac amyloidosis (CA) is a condition caused by extracellular deposition of amyloid fibrils in the heart. It is an underdiagnosed disease entity which can present with a variety of cardiac and non-cardiac manifestations. Diagnosis usually follows an initial suspicion based on clinical evaluation or imaging findings before confirmation with subsequent imaging (echocardiography, cardiac magnetic resonance imaging, 3,3-diphosphono-1,2-propanodicarboxylic acid scintigraphy) in combination with biochemical screening for monoclonal dyscrasia (serum free light chains and serum and urine electrophoresis) and/or histology (bone marrow trephine, fat or endomyocardial biopsy). More than 95% of CA can be classified as either amyloid light-chain (AL) CA or amyloid transthyretin (ATTR) CA; these two conditions have very different management strategies. AL-CA, which may be associated with multiple myeloma, can be managed with chemotherapy agents, autologous stem cell transplantation, cardiac transplant and supportive therapies. For ATTR-CA, there is increasing importance in making an early diagnosis because of novel treatments in development, which have transformed this once incurable disease to a potentially treatable disease. Timely diagnosis is crucial as there may only be a small window of opportunity where patients can benefit from treatment beyond which therapies may be less effective. Reviewing the existing patient pathway provides a basis to better understand the complexities of real-world activities which may be important to help reduce missed opportunities related to diagnosis and treatment for patients with CA. With healthcare provider interest in improving the care of patients with CA, the development of an optimal care pathway for the condition may help reduce delays in diagnosis and treatment and thus enhance patient outcomes.