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Biostatistics Seminar Series: Novel Genetic Association Test and Cardiomyopathy Risk Prediction in Cancer Survivors

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The Division of Biostatistics at the Department of Preventive Medicine invites you to attend the following seminar.

Time: Monday, January 24, 2:00 PM-3:00 PM CDT

ZOOM Virtual Room Connection: Register in advance for this meeting

Speaker: Dr. Xuexia Wang, University of North Texas

Title: Novel Genetic Association Test and Cardiomyopathy Risk Prediction in Cancer Survivors

Abstract: This talk includes two projects. Project 1: Gene-based association tests are widely used in GWAS. The power of a test is often limited by the sample size, the effect size, and the number of causal variants or their directions in a gene. In addition, access to individual-level data is often limited. To resolve the existing limitations, we proposed an optimally weighted combination (OWC) test based on summary statistics from GWAS. We analytically proved that aggregating the variants in one gene is the same as using the weighted combination of Z-scores for each variant based on the proposed score test. Several existing methods are special cases. We also numerically illustrated that our proposed test outperforms several existing methods via simulation studies. Furthermore, we utilized schizophrenia GWAS data and fasting glucose GWAS meta-analysis data to demonstrate that our method outperforms the existing methods in real data analyses. Project 2: We used a carefully curated list of 87 previously published genetic variants to determine whether the incorporation of genetic variants with non-genetic variables could improve the identification of cancer survivors at risk for anthracycline-related cardiomyopathy. We used anthracycline-exposed childhood cancer survivors from a Children’s Oncology Group study (COG-ALTE03N1: 146 cases; 195 matched controls) as the discovery set. Replication was performed in two anthracycline-exposed survivor populations: i) childhood cancer survivors from the Childhood Cancer Survivor Study (CCSS: 126 cases; 250 controls); ii) autologous blood or marrow transplantation (BMT) survivors from the BMT Survivor Study (BMTSS: 80 cases; 78 controls). The Clinical+Genetic model performed better than the Clinical Model in COG-ALTE03N1 (AUC of Clinical+Genetic Model = 0.88 vs. AUC of Clinical Model = 0.81) and BMTSS (AUC of Clinical+Genetic Model = 0.72 vs. AUC of Clinical Model = 0.64), but not in CCSS (AUC of Clinical+Genetic Model = 0.88 vs. AUC of Clinical Model = 0.89). However, the Clinical+Genetic model performed marginally better in CCSS patients without CVRFs where cardiomyopathy developed within 30 years of anthracycline exposure (AUC of Clinical+Genetic Model = 0.90 vs. AUC of Clinical Model = 0.85). Conclusions: Adding a comprehensively assembled genetic profile to clinical characteristics improves the identification of cancer survivors at risk for anthracycline-related cardiomyopathy.

Bio: https://math.unt.edu/people/xuexia-wang

Publication: https://pubmed.ncbi.nlm.nih.gov/32413235/

We look forward to seeing you all among us.