Hereditary ATTR Amyloidosis in Austria: Prevalence and Epidemiological Hot Spots
Bibliographic record
Abstract
Background: Hereditary transthyretin amyloidosis (hATTR) is an autosomal dominantly inherited disorder caused by an accumulation of amyloid fibrils in tissues due to mutations in the transthyretin (TTR) gene. The prevalence of hATTR is still unclear and likely underestimated in many countries. In order to apply new therapies in a targeted manner, early diagnosis and knowledge of phenotype-genotype correlations are mandatory. This study aimed to assess the prevalence and phenotypic spectrum of hATTR in Austria. Methods: Within the period of 2014–2019, patients with ATTR-associated cardiomyopathy and/or unexplained progressive polyneuropathies were screened for mutations in the TTR gene. Results: We identified 43 cases from 22 families carrying 10 different TTR missense mutations and confirmed two mutational hot spots at c.323A>G (p.His108Arg) and c.337G>C (p.Val113Leu). Two further patients with late onset ATTR carried TTR variants of unknown significance. The majority of patients initially presented with heart failure symptoms that were subsequently accompanied by progressive polyneuropathy in most cases. A total of 55% had a history of carpal tunnel syndrome before the onset of other organ manifestations. Conclusions: Our study underlined the relevance of hATTR in the pathogenesis of amyloid-driven cardiomyopathy and axonal polyneuropathy and indicated considerable genetic heterogeneity of this disease in the Austrian population. The estimated prevalence of hATTR in Austria based on this study is 1:200,000 but a potentially higher number of unknown cases must be taken into account. With respect to new therapeutic approaches, we strongly propose genetic testing of the TTR gene in an extended cohort of patients with unexplained heart failure and progressive polyneuropathy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".