Transition from Reactionary to Preventative Medicine with Epigenetic Disease Associations
To revolutionize the next generation medicine with a transition from reactionary medicine to preventative medicine using genome-wide epigenetic disease associations and diagnostics.
Large worldwide epidemiology studies have suggested over 85% of the human population has chronic disease which increase in number as we age. The current clinical medicine focus uses Reactionary Medicine that treats disease after it has developed. The frequency of many major diseases have increased over ten-fold in the last 25 years. We need a major paradigm shift in how we approach and do medicine. What if you could earlier in life (20-30 years) have a diagnostic that would indicate your susceptibility to develop a specific disease later in life, and then use a preventative therapeutic or lifestyle change to delay or prevent the disease from developing? This is Preventative Medicine and will develop when we can use non-genetic molecular diagnostics (epigenetics) to allow this preventative medicine approach. The program will further develop and apply epigenetic diagnostics for most major diseases to facilitate the prevention of later life onset disease.
The Problem –
At the risk of oversimplification, most government and philanthropic funding that is aimed at clinical interventions are essentially reactionary, focused on detecting and treating disease that occur in the late stages of development. This idea is contrarian and catalytic, as the Michael Skinner lab seeks to establish a revolutionary paradigm shift in medicine toward preventative medicine, through developing non-genetic molecular biomarkers or diagnostics for the individual disease or pathologies. After 20 years of genome wide genetic association studies (i.e. GWAS) the percentage of a specific disease population with correlated genetic mutations is less than 1% of the population with the disease. Even with a very large study, 350 thousand patients worldwide with obesity, multiple genetic mutations found constitute only a 2-3% correlation with the obesity population. Therefore, while genetics has a role in disease, the low correlation of specific genetic mutations has not allowed efficient biomarkers or diagnostics to be developed for the general population for any disease. The problem is that the current focus on reactionary medicine and genetics alone has not had a significant reduction on worldwide human sickness and suffering.
Demand to Address the Problem:
Several worldwide epidemiology studies have indicated over 85% of the human population has chronic disease. Even at the age of 0-9 years over 70% of the population has at least one chronic disease, that then increases to 3-6 different chronic diseases in individuals over 50 years. Many major diseases have increased over 10-fold in the past 25 years. The predictions are a significant increase in disease frequency in the future since there has been no major advances in the preventative medicine treatments of disease. The cost of health care for nearly all nations worldwide has now become one of the primary financial burdens for society and governments. The current approach of reactionary medicine has not been able to reduce worldwide sickness and suffering, which instead is increasing. A change in our current paradigm for medicine is needed to prevent or delay the onset of chronic disease.
Your Solution –
An alternate molecular mechanism that controls genome activity and is associated with disease is epigenetics, molecular factors around the DNA that regulate genome activity independent of DNA sequence. Studies in animals and humans suggest much higher associations with epigenetic alterations (i.e. epimutations) and disease, and it is also now clear that such epimutations can be inherited for generations (suggesting generational toxicology and disease load is a reality). Often over 90% of the disease population has the correlated epimutations, and we propose to use epigenetic mutations as more effective biomarkers or diagnostics for disease susceptibility than the traditional genetic mutation approach. Effective epigenetic biomarkers for disease susceptibility would allow early life assessment opportunities for preventative therapeutics and lifestyle changes that may prevent or delay disease development. An example is the use of tamoxifen, which if taken in your 30s (well before patients are symptomatic), has been shown to delay or prevent the onset of breast cancer later in life. Thus, if successful, our approach would result in minimizing future suffering and disease, by first developing disease susceptibility diagnostics; second allowing early treatment options; third facilitating preventative pharmaceutical and therapy options; and fourth identifying epigenetic modifications that may be transgenerationally inherited (biasing the susceptibility of disease for generations to come). The development and use of epigenetic diagnostics early in life will allow preventative medicine to later in life prevent or delay disease onset.
Technical Process Description:
How would we accomplish this? Our conceptual idea involves analyzing large numbers of samples with various subpopulations of a wide variety of diseases in the general population. We would conduct Epigenetic Genome Wide Association Studies (EWAS) to identify biomarkers for early life disease susceptibility, and also perform GWAS analysis to identify genetic mutations in the same samples (to compare the differences in efficiency of the two approaches to obtain efficient disease biomarkers that are present in the majority of individuals with the disease). Epigenetic biomarkers will be developed for all major chronic diseases. To allow generational toxicological considerations, buccal cells (cheek swab) from mother, father and child trios will be obtained to assess the molecular changes associated with the pathologies of the mother, father and child populations. Large population-based sample collections, as well as disease focused, will allow subpopulations and epidemiology to obtain disease epigenetic diagnostics for most major diseases. Critically, epigenetic biomarker development will be facilitated using a novel artificial intelligence computational approach to translate these findings into relevant data for clinicians. Our work will demonstrate that a preventative approach with diagnostics and treatment is possible, allowing a paradigm shift away from reactionary medicine.