Literature DB >> 33659933

Alpha-1 antitrypsin deficiency: an update on clinical aspects of diagnosis and management.

Gabriela Santos1, Alice M Turner2.   

Abstract

Clinical heterogeneity has been demonstrated in alpha-1 antitrypsin deficiency (AATD), such that clinical suspicion plays an important role in its diagnosis. The PiZZ genotype is the most common severe deficiency genotype and so tends to result in the worst clinical presentation, hence it has been the major focus of research. However, milder genotypes, especially PiSZ and PiMZ, are also linked to the development of lung and liver disease, mainly when unhealthy behaviors are present, such as smoking and alcohol use. Monitoring and managing AATD patients remains an area of active research. Lung function tests or computed tomography (CT) densitometry may allow physicians to identify progressive disease during follow up of patients, with a view to decision making about AATD-specific therapy, like augmentation therapy, or eventually surgical procedures such as lung volume reduction or transplant. Different types of biological markers have been suggested for disease monitoring and therapy selection, although most need further investigation. Intravenous augmentation therapy reduces the progression of emphysema in PiZZ patients and is available in many European countries, but its effect in milder deficiency is less certain. AATD has also been suggested to represent a risk factor and trigger for pulmonary infections, like those induced by mycobacteria. We summarize the last 5-10 years' key findings in AATD diagnosis, assessment, and management, with a focus on milder deficiency variants. Copyright:
© 2020 Turner AM et al.

Entities:  

Keywords:  alpha-1 antitrypsin deficiency; chronic obstructive pulmonary disease; cirrhosis; emphysema; treatment

Year:  2020        PMID: 33659933      PMCID: PMC7886062          DOI: 10.12703/b/9-1

Source DB:  PubMed          Journal:  Fac Rev        ISSN: 2732-432X


  2 in total

Review 1.  A Review of Alpha-1 Antitrypsin Binding Partners for Immune Regulation and Potential Therapeutic Application.

Authors:  Michael E O'Brien; Grace Murray; Debananda Gogoi; Azeez Yusuf; Cormac McCarthy; Mark R Wormald; Michelle Casey; Claudie Gabillard-Lefort; Noel G McElvaney; Emer P Reeves
Journal:  Int J Mol Sci       Date:  2022-02-23       Impact factor: 5.923

2.  A stacking ensemble machine learning model to predict alpha-1 antitrypsin deficiency-associated liver disease clinical outcomes based on UK Biobank data.

Authors:  Linxi Meng; Will Treem; Graham A Heap; Jingjing Chen
Journal:  Sci Rep       Date:  2022-10-11       Impact factor: 4.996

  2 in total

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