Novel/Alternative statistical approaches for genetic association studies

Introduction: Single SNP analyses using logistic regression have traditionally been applied in genetic association studies to assess main effects. However, many complex diseases, such as bladder cancer (BC), are likely to be associated with the combined effects of multiple loci. Problems derived from genetic data are that most single SNP analyses are underpowered to detect small effects and so methods such as least absolute shrinkage and selection operator (LASSO) have emerged as promising alternatives since they can deal both with high-throughput genotyping data and with the correlations between them. We applied the classical and the LASSO approaches to conduct a comprehensive association analysis between common germline variation in genes from the P53 pathway and BC risk.