Related Experiment Video
Updated: Aug 8, 2025
05:53
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
10.2K
Identifying COPD subtypes using multi-trait genetics
Andrey Ziyatdinov1,2, Brian D Hobbs2,3, Samir Kanaan-Izquierdo4,5,6
1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Medrxiv : the Preprint Server for Health Sciences
|March 3, 2023
Summary
Genetic variants influence Chronic Obstructive Pulmonary Disease (COPD) phenotypes. Our study identified distinct genetic clusters associated with varied health traits, revealing genetically driven patterns in COPD.
Area of Science:
- Pulmonary Medicine
- Genetics
- Bioinformatics
Background:
- Chronic Obstructive Pulmonary Disease (COPD) exhibits significant clinical heterogeneity despite a clear physiological diagnosis.
- The genetic underpinnings of COPD phenotypic variability remain largely unexplored.
Approach:
- Genome-wide association study (GWAS) data from UK Biobank was analyzed to link lung function, COPD, and asthma genetic variants with diverse phenotypes.
- Clustering analysis identified three distinct groups of genetic variants impacting traits like white blood cell count, height, and body mass index (BMI).
- Cluster-specific genetic risk scores were evaluated in the COPDGene cohort to assess clinical and molecular associations.
Key Points:
- Three clusters of genetic variants showed differential associations with non-respiratory phenotypes, including BMI and blood cell counts.
- Genetic risk scores derived from these clusters correlated with variations in steroid use, BMI, lymphocyte counts, and chronic bronchitis.
- Significant differences in gene and protein expression were observed across the genetic risk score groups.
Conclusions:
- Genetic variants associated with obstructive lung diseases contribute to phenotypic diversity in COPD.
- Multi-phenotype analysis of genetic risk variants can uncover genetically driven patterns within COPD.
- This approach offers insights into the biological mechanisms underlying COPD heterogeneity.
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