Molecular pathological epidemiologyMolecular pathological epidemiology (MPE, also molecular pathologic epidemiology) is a discipline combining epidemiology and pathology. It is defined as "epidemiology of molecular pathology and heterogeneity of disease". Pathology and epidemiology share the same goal of elucidating etiology of disease, and MPE aims to achieve this goal at molecular, individual and population levels. Typically, MPE utilizes tissue pathology resources and data within existing epidemiology studies.
Molecular pathologyMolecular pathology is an emerging discipline within pathology which is focused in the study and diagnosis of disease through the examination of molecules within organs, tissues or bodily fluids. Molecular pathology shares some aspects of practice with both anatomic pathology and clinical pathology, molecular biology, biochemistry, proteomics and genetics, and is sometimes considered a "crossover" discipline. It is multi-disciplinary in nature and focuses mainly on the sub-microscopic aspects of disease.
Gene–environment interactionGene–environment interaction (or genotype–environment interaction or G×E) is when two different genotypes respond to environmental variation in different ways. A norm of reaction is a graph that shows the relationship between genes and environmental factors when phenotypic differences are continuous. They can help illustrate GxE interactions. When the norm of reaction is not parallel, as shown in the figure below, there is a gene by environment interaction. This indicates that each genotype responds to environmental variation in a different way.
Genome-wide association studyIn genomics, a genome-wide association study (GWA study, or GWAS), is an observational study of a genome-wide set of genetic variants in different individuals to see if any variant is associated with a trait. GWA studies typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits like major human diseases, but can equally be applied to any other genetic variants and any other organisms. When applied to human data, GWA studies compare the DNA of participants having varying phenotypes for a particular trait or disease.
