Differential expression analyses provide powerful tools for the identification of genes playing a role in disease pathogenesis. Yet, such approaches are usually restricted by the high variation in expression profiles when primary specimens are analyzed. It is conceivable that with the assessment of the degree of coordination in gene expression as opposed to the magnitude of differential expression, we may obtain hints underscoring different biological and pathological states. Here we have analyzed a publicly available dataset related to frailty, a syndrome characterized by reduced responsiveness to stressors and exhibiting increased prevalence in the elderly. We evaluated the transcriptome that loses its coordination between the frailty and control groups and assessed the biological functions that are acquired in the former group. Among the top genes exhibiting the lowest correlation, at the whole transcriptome level, between the control and frailty groups were TSIX, BEST1 and ADAMTSL4. Processes related to immune response and regulation of cellular metabolism and the metabolism of macromolecules emerged in the frailty group. The proposed strategy confirms and extends earlier findings regarding the pathogenesis of frailty and provides a paradigm on how the diversity in expression profiles of primary specimens could be leveraged for target discovery.