Gene-Environment Interaction in the Era of Precision Medicine

Gene–Environment Interaction in the Era of Precision Medicine – Filling the Potholes Rather Than Starting to Build a New Road

“…In the aforementioned paper, Li et al (2019) echo the message that techniques using conventional genetic models do not often provide insightful enough results and that, in particular, they have so far provided no clear-cut evidence on whether disease etiologies are due to rare alleles with strong effects or to common alleles with weak effects. More to the point, Li et al (2019) have carried out a simulation by means of which certain genetic models are shown not to be able to capture the complexity of realistic underlying factors of a disease—particularly, involving epistatic effects (gene interactions, i.e., departures from the sum of the marginal contributions of the effects of the genes involved).…”

“…Further on, Li et al (2019) provide a probabilistic approach based on a Bayesian framework to hierarchically model gene–environment interaction, leading to a population-dependent index, C, called the genetic coefficient of the disease (at a population)—“a large C indicates large distinguishability of case genomes from control genomes.” Then they illustrate the performance of the proposed methodology using a built-up example in which the disease susceptibility is by default very low (0.01) and it significantly increases due to either environmental (exposure) or genetic (risk allele) factors or both, to 0.4, 0.5, and 0.9, respectively. That case is hereafter referred to as the risk and exposure (RAE) case (see Table 1 ).…”

“…The aforementioned advances in genetics methodologies have enabled increasingly accurate medical predictions, particularly in regards to treatment efficiencies and prevention strategies for different (groups of) individuals, an approach that has been coined as precision medicine. In this context, the first half of the title above, “Gene–environment interaction in the era of precision medicine,” has been stolen from a recent paper in which bottlenecks of classical models of genetic effects and their use in genetic mapping are discussed ( Li et al, 2019 ). This is so because the present paper takes the baton of the aforementioned one by reviewing whether it is realistic and worth it to try and further amend classical models of genetic effects or whether it proves more sensible (or even necessary) to undertake alternative theoretical strategies instead.…”

Mitochondrial diseases in adults

“…Basic preclinical research has new powerful tools to speed the process of understanding the pathogenic mechanisms, from modelling the diseases in animals, which still represents a major challenge for mtDNA [149], to reprogramming patient‐derived cells to pluripotent stem cells (iPSCs) [150,151] and generating mini‐organs [152]. On the clinical ground, innovative precision medicine approaches to follow up patients and understand the frequently unpredictable evolution of mitochondrial disorders, such as the occurrence of stroke‐like, status epilepticus or the sudden intestinal pseudo‐obstruction episodes, will need to conjugate clinical with multi‐omics investigations, taking advantage of wearable devices, as recently proposed [153]. This will capture at the highest level the complexities of how genetics and environmental factors contribute to determine the clinical outcomes, ultimately providing the basis to prevent or effectively modify the disease occurrence or its evolution [153].…”

“…On the clinical ground, innovative precision medicine approaches to follow up patients and understand the frequently unpredictable evolution of mitochondrial disorders, such as the occurrence of stroke‐like, status epilepticus or the sudden intestinal pseudo‐obstruction episodes, will need to conjugate clinical with multi‐omics investigations, taking advantage of wearable devices, as recently proposed [153]. This will capture at the highest level the complexities of how genetics and environmental factors contribute to determine the clinical outcomes, ultimately providing the basis to prevent or effectively modify the disease occurrence or its evolution [153].…”