Quality Control Measures and Validation in Gene Association Studies: Lessons for Acute Illness. Issue 3 (March 2020) - Cohen, Maria; Lamparello, Ashley J.; Schimunek, Lukas; El-Dehaibi, Fayten; Namas, Rami A.; Xu, Yan; Kaynar, A Murat; Billiar, Timothy R.; Vodovotz, Yoram
Abstract : ABSTRACT: Acute illness is a complex constellation of responses involving dysregulated inflammatory and immune responses, which are ultimately associated with multiple organ dysfunction. Gene association studies have associated single-nucleotide polymorphisms (SNPs) with clinical and pharmacological outcomes in a variety of disease states, including acute illness. With approximately 4 to 5 million SNPs in the human genome and recent studies suggesting that a large portion of SNP studies are not reproducible, we suggest that the ultimate clinical utility of SNPs in acute illness depends on validation and quality control measures. To investigate this issue, in December 2018 and January 2019 we searched the literature for peer-reviewed studies reporting data on associations between SNPs and clinical outcomes and between SNPs and pharmaceuticals (i.e., pharmacogenomics) published between January 2011 to February 2019. We review key methodologies and results from a variety of clinical and pharmacological gene association studies, including trauma and sepsis studies, as illustrative examples on current SNP association studies. In this review article, we have found three key points which strengthen the potential accuracy of SNP association studies in acute illness and other diseases: providing evidence of following a protocol quality control method such as the one in Nature Protocols or the OncoArray QC Guidelines; enrolling enough patients to have large cohort groups; and validating the SNPs using an independent technique such as a second study using the same SNPs with new patient cohorts. Our survey suggests the need to standardize validation methods and SNP quality control measures in medicine in general, and specifically in the context of complex disease states such as acute illness.