Hereditary Transthyretin-Related Amyloidosis Ongoing Observational Study: A Baseline Report of the First 3167 Participants

<b>Background</b>: Hereditary transthyretin-related amyloidosis is a clinically heterogeneous autosomal dominant disease caused by pathogenic variants in the <i>TTR</i> gene (hATTR amyloidosis). <b>Objective:</b> The current study describes the demographic, clinical, and genetic characteristics of patients with suspected hATTR amyloidosis. <b>Methods</b>: This study is part of the "Hereditary transthyretin-related amyloidosis and longitudinal monitoring of <i>TTR</i>-positive patients" (TRAMmoni<i>TTR</i>) study. This study included 3167 participants, along with their clinical details. Principal component (PC) analysis was used to analyze their clinical symptomatology. Next-generation sequencing of the <i>TTR</i> gene was performed and genotype-phenotype relationships were investigated. We compared the demographic and clinical characteristics using the principal components (PCs) and also compared participants with and without the <i>TTR</i> pathogenic variants. <b>Results:</b> We identified five main clinical phenotypes out of 22 single symptoms that explained 49% of the variation. The first two PCs referred to polyneuropathy and cardiomyopathy. We found significant differences between gender and PC-polyneuropathy and PC-cardiomyopathy, with male over-representation in the higher quantiles of PC-polyneuropathy and male under-representation in the lowest quantiles of PC-cardiomyopathy. We identified 92 participants with hATTR (3%), exhibiting 17 unique heterozygous <i>TTR</i> variants. The p.Val50Met variant was the most frequent. Furthermore, 503 participants (20%) were identified with ATTR and no relevant <i>TTR</i> variants (ATTRwt). We detected significant differences between the ATTRwt and hATTR groups, with male gender predominance in only the ATTRwt group and a positive family history of polyneuropathy and/or cardiomyopathy among the hATTR participants. <b>Conclusions</b>: The current clinical and genetic characterization of this cohort serves as a foundation for further longitudinal monitoring and assessment.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Medicine
Published
2024-10-17
DOI
https://doi.org/10.3390/jcm13206197
Citations
2
Primary Topic
Amyloidosis: Diagnosis, Treatment, Outcomes
Type
article
Field-Weighted Citation Impact
0.47

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hereditary Transthyretin-Related Amyloidosis Ongoing Observational Study: A Baseline Report of the First 3167 Participants

Thomas Skripuletz, Jörg Rennecke, Luba M. Pardo, Snezana Skobalj et al.
2 citations
Journal of Clinical Medicine
Amyloidosis: Diagnosis, Treatment, Outcomes
0.47
article

Hereditary Transthyretin-Related Amyloidosis Ongoing Observational Study: A Baseline Report of the First 3167 Participants

Thomas Skripuletz, Jörg Rennecke, Luba M. Pardo, Snezana Skobalj, Volha Skrahina, Susanne Zielke, Sabine Rösner, Birgit Aßmus, Xenia Bogdanovic, Sabine Schröder, Jonas H. Kreth, Katrin Hahn, Pierre Engel, Monica Patten, Aida M. Bertoli‐Avella, Peter Bauer, Arndt Rolfs, Felix Reder, Susan Zielske, Gina Westphal, Paula Grieger, Valerie Bonke
article en
2 citations

Abstract

<b>Background</b>: Hereditary transthyretin-related amyloidosis is a clinically heterogeneous autosomal dominant disease caused by pathogenic variants in the <i>TTR</i> gene (hATTR amyloidosis). <b>Objective:</b> The current study describes the demographic, clinical, and genetic characteristics of patients with suspected hATTR amyloidosis. <b>Methods</b>: This study is part of the "Hereditary transthyretin-related amyloidosis and longitudinal monitoring of <i>TTR</i>-positive patients" (TRAMmoni<i>TTR</i>) study. This study included 3167 participants, along with their clinical details. Principal component (PC) analysis was used to analyze their clinical symptomatology. Next-generation sequencing of the <i>TTR</i> gene was performed and genotype-phenotype relationships were investigated. We compared the demographic and clinical characteristics using the principal components (PCs) and also compared participants with and without the <i>TTR</i> pathogenic variants. <b>Results:</b> We identified five main clinical phenotypes out of 22 single symptoms that explained 49% of the variation. The first two PCs referred to polyneuropathy and cardiomyopathy. We found significant differences between gender and PC-polyneuropathy and PC-cardiomyopathy, with male over-representation in the higher quantiles of PC-polyneuropathy and male under-representation in the lowest quantiles of PC-cardiomyopathy. We identified 92 participants with hATTR (3%), exhibiting 17 unique heterozygous <i>TTR</i> variants. The p.Val50Met variant was the most frequent. Furthermore, 503 participants (20%) were identified with ATTR and no relevant <i>TTR</i> variants (ATTRwt). We detected significant differences between the ATTRwt and hATTR groups, with male gender predominance in only the ATTRwt group and a positive family history of polyneuropathy and/or cardiomyopathy among the hATTR participants. <b>Conclusions</b>: The current clinical and genetic characterization of this cohort serves as a foundation for further longitudinal monitoring and assessment.

Journal of Clinical MedicineVol. 13(20)
Universitätsklinikum Gießen und Marburg (DE), Medizinische Hochschule Hannover (DE), Centogene (Germany) (DE), CS Diagnostics (DE), University of Rostock (DE), Charité - Universitätsmedizin Berlin (DE)
Alnylam Pharmaceuticals
Openalex Percentile: Top 35%
Amyloidosis: Diagnosis, Treatment, Outcomes
0.47
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.