Efficient genome-wide association studies and post- GWAS integrative analyses for human cancer and neurodegenerative diseases

It is evident that in etiologies of human complex diseases, genetic factors play some important roles. Genome-wide association study (GWAS) is a standard technique to identify heritable genetic basis of complex diseases. In relation with GWAS, there exist some challenges in selecting input samples completely randomly, to biologically describe GWAS results, to translate them into clinical benefits and to compare germ line variants achieved from GWAS with somatic mutations in creating, development and treatment of human complex diseases. Likelihood-based statistical methods are robust in estimating linkage disequilibrium when factors like non-randomness and population structures exist. Then the results of GWAS can be used for post-GWAS analyses to predict multiple biological components like genes, non-coding RNAs and transcription factor binding sites in association with complex diseases. An integrative analysis seeks to pool information from multiple GWAS results, somatic mutations and genetic drug targets of human complex disorders and the results of such analysis can provide new insight into the genetic and treatments of complex diseases.

Author(s): Zahra Mortezaei

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