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Updated: Nov 18, 2025

Genetic Analysis of Hereditary Transthyretin Ala97Ser Related Amyloidosis
Published on: June 9, 2018
Clinical presentations of four patients with rare Alpha 1 Antitrypsin variants identified in a single US center
1Lewis Katz School of Medicine at Temple University, Department of Thoracic Surgery and Medicine, Medicine Education and Research Building (MERB), 3500 N. Broad Street, Philadelphia, PA, 19140, USA.
Abstract:
Alpha 1 Antitrypsin Deficiency (AATD) is a rare condition primarily associated with lung complications and liver disease. As disease symptoms are similar to those in other respiratory conditions, patients generally experience long delays before receiving an accurate diagnosis and treatment. AATD results from mutations in the SERPINA1 gene that encodes Alpha 1 Antitrypsin (AAT). Over 500 single-nucleotide variants have been reported in mutation databases; however, there is increasing interest in the clinical significance of rare and novel SERPINA1 variants. In this case series of four patients from a single US center, next-generation sequencing (NGS) was used to guide AATD diagnosis. Four distinct rare variants of SERPINA1 (P289S; I50N; E204K; H262Y) were identified, three of which were found in patients with advanced chronic obstructive pulmonary disease (COPD)/emphysema. Computational modeling predicted these mutations to have potentially deleterious effects, a finding supported by AAT levels that were comparable with those seen in individuals heterozygous for the most common deficiency allele (PI*MZ). The remaining mutation (E204K) was found in a patient with a cerebral aneurysm; potential links between SERPINA1 variants and neurological conditions, such as cerebral aneurysm and arterial dissections, have been previously reported in individuals with heterozygous AATD phenotypes (PI*MS and PI*MZ). Novel and rare variants, often not detected by basic AATD diagnostic tests, have the potential to contribute to the development of COPD and emphysema. Detection of these variants can be enhanced by NGS, and modeling techniques can help determine if variants are pathogenic, thereby enabling a quicker, more accurate AATD diagnosis.
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