Drugs that reverse disease transcriptomic signatures are more effective in a mouse model of dyslipidemia. Issue 3 (3rd March 2015) - Wagner, Allon; Cohen, Noa; Kelder, Thomas; Amit, Uri; Liebman, Elad; Steinberg, David M; Radonjic, Marijana; Ruppin, Eytan
Abstract: High‐throughput omics have proven invaluable in studying human disease, and yet day‐to‐day clinical practice still relies on physiological, non‐omic markers. The metabolic syndrome, for example, is diagnosed and monitored by blood and urine indices such as blood cholesterol levels. Nevertheless, the association between the molecular and the physiological manifestations of the disease, especially in response to treatment, has not been investigated in a systematic manner. To this end, we studied a mouse model of diet‐induced dyslipidemia and atherosclerosis that was subject to various drug treatments relevant to the disease in question. Both physiological data and gene expression data (from the liver and white adipose) were analyzed and compared. We find that treatments that restore gene expression patterns to their norm are associated with the successful restoration of physiological markers to their baselines. This holds in a tissue‐specific manner—treatments that reverse the transcriptomic signatures of the disease in a particular tissue are associated with positive physiological effects in that tissue. Further, treatments that introduce large non‐restorative gene expression alterations are associated with unfavorable physiological outcomes. These results provide a sound basis to in silico methods that rely on omic metrics for drug repurposing and drug discovery by searching for compounds that reverse a disease's omic signatures. Moreover, they highlight the need to develop drugs that restore the global cellular state to its healthy norm rather than rectify particular disease phenotypes. Synopsis: Drugs that reverse the omic signatures associated with dyslipidemia are shown to also restore physiological markers to their normal baselines. This provides a sound basis to computational methods that identify compounds which reverse a disease's omic signatures as potential therapeutic agents. We study a mouse model of dyslipidemia in which liver and adipose gene expression, as well as physiological data such as blood and urine indices, were collected. We find that drugs that successfully reverse the disease signatures in gene expression also restore the physiological markers to their normal baselines. Treatments that reverse the transcriptomic signatures of the disease in a particular tissue are associated with favorable physiological outcomes in that tissue. These results provide a sound rationale for predicting a drug's potential therapeutic effect based on its ability to reverse a disease's global molecular signature. They also suggest a need to develop drugs that restore the global cellular state back to its healthy norm rather than rectify only a particular subset of disease phenotypes. Abstract : Drugs that reverse the omic signatures associated with dyslipidemia are shown to also restore physiological markers to their normal baselines. This provides a sound basis to computational methods that identify compounds which reverse a disease's omic signatures as potential therapeutic agents.