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Integrating Genomics and Proteomics to Identify Causal Proteins and Biologic Pathways for Incident Atrial
Adrian M Petzl1, Yue Ren2, Faye L Norby3
1Division of Cardiovascular Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
Insights
This study identified causal proteins linking chronic kidney disease (CKD) to atrial fibrillation. A new proteomic risk score for atrial fibrillation in CKD patients showed similar performance to existing clinical scores.
Area of Science:
- Biomarkers and proteomics
- Cardiovascular disease research
- Chronic kidney disease (CKD) research
Background:
- Chronic kidney disease (CKD) is strongly linked to atrial fibrillation (AF).
- Understanding the biological pathways and developing predictive models for AF in CKD patients remains challenging.
- The overlap between biomarkers for AF and left atrial enlargement in CKD is not well understood.
Purpose of the Study:
- To identify causal proteins and biological mechanisms linking CKD to incident atrial fibrillation (AF).
- To explore the overlap in pathways between AF and left atrial enlargement in CKD.
- To develop and validate a multi-protein risk score for predicting incident AF in CKD.
Main Methods:
- SomaScan proteomic analysis of 4,590 plasma proteins in two CKD cohorts (CRIC and ARIC).
- Mendelian randomization to identify proteins in the causal pathway to AF.
- Identification of proteins and pathways associated with left atrial size.
- Development and validation of a multi-protein risk score for incident AF.
Main Results:
- Three proteins (NELL1, CILP2, MMP12) were identified as causally linked to incident AF.
- Significant overlap (8 of top 10 pathways) was found between pathways for AF and left atrial enlargement.
- The multi-protein risk score demonstrated predictive performance (AUC 0.65-0.76) comparable to the CHARGE AF clinical risk score.
Conclusions:
- Causal proteins and biological mechanisms underlying incident AF in CKD have been identified.
- A proteomic risk score for incident AF in CKD performs similarly to established clinical risk scores.
- These findings advance the understanding and prediction of AF in CKD populations.
Key Points:
Using proteomics and Mendelian randomization, we identified causal proteins for the development of atrial fibrillation in patients with CKD. Immunologic function, cell growth, and neural development were common biologic pathways underlying atrial fibrillation and left atrial enlargement. Machine learning led to a nine-protein risk model that had a similar predictive performance for incident atrial fibrillation as clinical risk scores.
Background:
CKD is strongly associated with atrial fibrillation. Understanding the biologic pathways for this association and creating predictive models have been challenging. Left atrial enlargement is a substrate for atrial fibrillation, but any overlap between biomarkers of atrial fibrillation and left atrial enlargement in patients with CKD is unknown.
Methods:
We evaluated 4590 plasma proteins with SomaScan in two cohorts of adult patients with CKD: the Chronic Renal Insufficiency Cohort (CRIC; n =2654) and the Atherosclerosis Risk in Communities cohort (ARIC; n =1326). Using Mendelian randomization, we identified proteins along the causal pathway to atrial fibrillation. We also identified proteins and corresponding pathways associated with larger echocardiographic left atrial size, a recognized substrate for atrial fibrillation. Finally, we developed and validated a multiprotein risk score for incident atrial fibrillation in the CKD population.
Results:
Over 5 years, incident atrial fibrillation occurred among 150 patients in the CRIC and 140 in the ARIC cohort. We identified three proteins causally linked to incident atrial fibrillation: neural EGF like‑like protein 1, cartilage intermediate layer protein 2, and matrix metallopeptidase 12. Pathway analysis revealed an overlap in eight of the top ten canonical pathways for incident atrial fibrillation and left atrial enlargement. A risk model for incident atrial fibrillation composed of proteins had annualized areas under the receiver-operating characteristic curve over 5 years ranging from 0.65 to 0.76, a performance similar to the Cohorts for Heart and Aging Research in Genomic Epidemiology Atrial Fibrillation (CHARGE-AF) clinical risk score.
Conclusions:
This study identified causal proteins and biologic mechanisms underlying incident atrial fibrillation in CKD. A proteomic risk score for incident atrial fibrillation in CKD performed similarly to the CHARGE-AF clinical risk score.
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