| Title: | Development of a simple clinical score to prioritize detection of severe alpha-1 antitrypsin deficiency with PiZZ genotype |
| Journal: | Genetics in Medicine |
| Published: | 20 Aug 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42626852/ |
| DOI: | https://doi.org/10.1016/j.gim.2026.102690 |
Publication 20984
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Abstract
PURPOSE: Alpha-1 antitrypsin deficiency (AATD) is caused primarily by the PiZZ genotype in SERPINA1 and remains underdiagnosed despite its association with severe lung and liver diseases. We aimed to develop and validate a clinical score using electronic health record (EHR) data to identify individuals more likely to carry the PiZZ genotype.</p>
MATERIALS AND METHODS: In the UK Biobank (UKB; N = 277,082), we developed the clinical score using logistic regression with variable selection based on medical conditions and anthropometric measurements. We evaluated its performance against random screening and targeted screening based on individual medical conditions in an independent UKB test dataset (N = 69,272) and the NIH All of Us Research Program (AoU; N = 162,198).</p>
RESULTS: The optimized clinical score included chronic obstructive pulmonary disease, bronchiectasis, cirrhosis, and height. In the UKB test dataset and AoU, the score outperformed any single phenotype in identifying PiZZ genotype. Targeting individuals in the top 0.5% of the score increased screening efficiency by >95% compared with random screening and outperformed all medical condition-based screening strategies.</p>
CONCLUSION: Using readily available EHR data, the clinical score represents a starting point that may improve targeted case-finding and optimize allocation of diagnostic resources for AATD.</p>
4 Authors
- Yanzhen Cheng
- Guillaume Butler-Laporte
- Tomoko Nakanishi
- Tianyuan Lu
1 Application
| Application ID | Title |
|---|---|
| 440468 | Novel statistical genetics methods for complex disease risk prediction and biomarker identification |
Enabling scientific discoveries that improve human health