Active clinical trials for "Amyloidosis"

Patients with left ventricular hypertrophy are further examined according to an algorithm to check if they have a cardiac amyloidosis

The study aims to test the diagnostic accuracy of native T1 mapping for the diagnosis of cardiac amyloidosis prospectively. The hypothesis is that native T1 mapping with a cut-off value of 1341ms (3 tesla CMR) in older patients with symptomatic heart failure, increased LV wall thickness and elevated cardiac biomarkers is non-inferior to the reference method to diagnose cardiac amyloidosis (CA). As secondary measure, a web-based ATTR probability estimator for the diagnosis of CA will be evaluated.

Approximately 1.5 million of the 44 million Blacks in the United States are carriers of the valine-to-isoleucine substitution at position 122 (V122I) in the transthyretin (TTR) protein. Virtually exclusive to Blacks, this is the most common cause of hereditary cardiac amyloidosis (hATTR-CA) worldwide. hATTR-CA leads to worsening heart failure (HF) and premature death. Fortunately, new therapies that stabilize TTR improve morbidity and mortality in hATTR-CA, especially when prescribed early in the disease. However, hATTR-CA is often diagnosed at an advanced stage and conventional diagnostic tools lack diagnostic specificity to detect early disease. The overall objectives of this study are to determine the presence of subclinical hATTR-CA and to identify biomarkers that indicate amyloid progression in V122I TTR carriers. The central hypothesis of this proposal is that hATTR-CA has a long latency period that will be detected through subclinical amyloidosis imaging and biomarker phenotyping. The central hypothesis will be tested by pursuing 2 specific aims: Aim 1) determine the association of V122I TTR carrier status with CMRI evidence of amyloid infiltration; Sub-aim 1) determine the association of V122I TTR carrier status with cardiac reserve; Aim 2) determine the association between amyloid-specific biomarkers and V122I TTR carrier status; and Sub-aim 2) determine the association of amyloid-specific biomarkers with imaging-based parameters and evaluate their diagnostic utility for identifying subclinical hATTR-CA. In Aim 1, CMRI will be used to compare metrics associated with cardiac amyloid infiltration between a cohort of V122I TTR carriers without HF formed by cascade genetic testing and age-, sex-, and race-matched non-carrier controls. For Sub-Aim 1, a sub-sample of carriers and non-carrier controls enrolled in Aim 1 will undergo novel exercise CMRI to measure and compare cardiac systolic and diastolic reserve. Aim 2 involves measuring and comparing amyloid-specific biomarkers in V122I TTR carriers without HF with samples matched non-carriers (both from Aim 1) and individuals with symptomatic V122I hATTR-CA from our clinical sites. These biomarkers detect and quantify different processes of TTR amyloidogenesis and include circulating TTR, retinol binding protein 4, TTR kinetic stability, and misfolded TTR oligomers. Sub-aim 2 will establish the role of these biomarkers to detect imaging evidence of subclinical hATTR-CA disease.

To collect, preserve, and/or distribute annotated biospecimens and associated medical data to institutionally approved, investigator-directed biomedical research to discover and develop new treatments, diagnostics, and preventative methods for specific and complex conditions.

Despite rapidly advancing developments in targeted therapeutics and genetic sequencing, persistent limits in the accuracy and throughput of clinical phenotyping has led to a widening gap between the potential and the actual benefits realized by precision medicine. Recent advances in machine learning and image processing techniques have shown that machine learning models can identify features unrecognized by human experts and more precisely/accurately assess common measurements made in clinical practice. The investigators have developed an algorithm, termed EchoNet-LVH, to identify cardiac hypertrophy and identify patients who would benefit from additional screening for cardiac amyloidosis and will prospectively evaluate its accuracy in identifying patients whom would benefit from additional screening for cardiac amyloidosis.

Early diagnosis of cardiac amyloidosis (CA) is crucial because of the poor overall survival, high mortality and the need for early therapy including new treatment possibilities for transthyretin amyloidosis. Previously considered a rare condition, CA is being demonstrated to account for up to 17 % of heart failure with preserved ejection fraction cases as well as up to 16 % of Patients with severe aortic stenosis, undergoing surgical of transcatheter aortic valve replacement. It seems that CA is being underdiagnosed as the data of post-mortem studies demonstrate that at least 25% of elderly individuals have histologic evidence of amyloid deposits. Other common conditions with increased afterload such as hypertensive or hypertrophic heart disease that mimic echocardiographic features or clinical symptoms may be the reason of postponed recognition of CA. Furthermore, the lack of definitive biomarkers makes the diagnosis even more challenging. However, it has been shown that some clinical, laboratory and echocardiographic findings, so called "red flags", may indicate occult CA. A deeper and constructive analysis of the findings and establishment of prediction criteria could possibly lead to improvement of early CA recognition and survival in subjects at risk. We aim to prospectively perform a systematic screening for CA in individuals at risk based on predefined selection criteria. Our aim is to evaluate if specific criteria would lead to increased detection of CA and in this case, to define major and minor diagnostic criteria.

Use samples procured from patients to improve understanding of molecular, cellular, and tissue-level processes produced by cardiac amyloidosis and therapeutic interventions.

Background: In stroke patients treated with intravenous thrombolysis (IVT), presence and high number of strictly lobar cerebral microbleeds (compatible with cerebral amyloid angiopathy, CAA) seems to be associated with increased risk of hemorrhagic transformation, symptomatic hemorrhagic transformation, remote hemorrhage, and poor functional outcome. Some of these reported CAA patients with cerebral microbleeds also had chronic lobar intracerebral haemorrhage. Few data is available on IVT-treated CAA patients showing cortical superficial siderosis. There are no reports studying factors associated with brain hemorrhagic complication or functional outcome inside a group of IVT-treated CAA patients. Our aim was to evaluate brain hemorrhagic complications on 24h-CT and functional outcome after IVT in stroke patients with CAA features on pre-IVT MRI. Methods: In our stroke center, IVT decision in patients with CAA MRI features is left at the discretion of the treating physician. We retrospectively screened pre-IVT imaging of 959 consecutive IVT-treated stroke patients (between January 2015 and July 2022) without ongoing anticoagulation therapy for probable CAA MRI features defined by modified Boston criteria. After exclusion of 119 patients with lacking MRI (n=47), with MRI showing motion artefacts (n=49) or with alternative chronic brain hemorrhage cause on MRI (n=23), 15 IVT-treated patients with probable CAA on pre-IVT MRI were identified. In these 15 patients, clinical, biological and MRI characteristics were compared between patients with vs. without post-IVT hemorrhage and between patients with poor (MRS 3-6) vs. good (MRS 0-2) functional outcome at discharge.

The purpose of this protocol is to generate a registry of Chinese patients with AL amyloidosis treated with subcutaneous/intravenous daratumumab alone or subcutaneous/intravenous daratumumab combined with chemotherapy.

National, multicenter, epidemiological, longitudinal protocol to investigate the hATTR prevalence in an at-risk population for Hereditary Transthyretin Amyloidosis (hATTR) and subjects diagnosed with hATTR, to monitor the clinical status in TTR positive subjects and to establish hATTR biomarker/s