Gene expression changes in disease and after drug treatment are sizeable in breadth and magnitude – but surprisingly consistent between patients or samples. The current paradigm of altered transcription factor activity that is co-ordinated across every individual gene promoter to explain this outcome seems far-fetched in its complexity and inefficient in implementation. A systemic mechanism of gene expression control which could also be tied to intended biological outcome would be a more rational evolutionary design – and we believe that we have discovered such a mechanism hidden in the base composition and length of each mRNA transcript.

We've shown that gene expression changes are strongly correlated with the scale of these mRNA parameters in autism spectrum disorder, Alzheimer’s disease/mild cognitive impairment, amyotrophic lateral sclerosis/frontotemporal dementia, Pick disease, diffuse Lewy-body dementia, Parkinson’s disease, major depression, schizophrenia, Huntington’s disease, multiple sclerosis, dilated heart myopathy, chronic kidney disease, Crohn’s disease, polyendocrine metabolic ovarian syndrome, chronic obstructive pulmonary disease, psoriasis, and COVID infection.

Additionally, normal development and ageing appear to engage this form of regulation. Furthermore, mRNA parameters can produce the expression consequences seen for a proportion of drug treatments and may provide new insights into their adverse effects. Importantly, these parameters are disproportionately enriched in specific functional groups of genes, providing a direct link between expression change and biological consequence.

We've embarked a program of work to catalogue the influences of mRNA parameters on expression and explore the underlying genetic and biological mechanism of their action. Much of this work involves the analysis of existing large RNAseq datasets but we are also exploring assays of nucleotide abundance in cells as a means to explain our mechanism. Future research projects which may be suitable for PhD students would include the testing of candidate drug molecules in cellular models of disease, the dissection of the molecular mechanisms of the process, and an assessment of the implications for pharmacoepidemiology that these findings raise.