Monthly Archives: October 2019

These GEITP pages continue to discuss genome-wide association studies (GWAS) which, since ~2006, are designed to detect genes or genetic loci correlated with whatever trait (phenotype) the researchers have chosen to study. Rather than Mendelian traits (usually reflecting defects in … Continue reading →

This topic might seem a bit unusual for the theme of gene-environment interactions — but responses of genes (genetic susceptibility) to any drug (an environmental signal) seems clear. And any screening-model system that attempts to predict clinical drug response would … Continue reading →

Our theme of gene-environment interactions — includes environmental signals that elicit alterations in gene expression to respond to that signal; this article [see attached] qualifies for that theme. Helicobacter pylori is a bacterial pathogen that is able to colonize the … Continue reading →

As these GEITP pages continue to emphasize, any multifactorial trait reflects the contributions of genetics, epigenetic factors, environmental effects, endogenous influences, and each individual’s microbiome. It is now well appreciated that the intestinal microbiome has profound effects on the physiology … Continue reading →

Because these GEITP pages believe that multiple sclerosis (MS) represents a combination of genetic susceptibility and external signals, this falls within the theme of gene-environment interactions. Over the past decade, elements of the genetic architecture (i.e. the underlying genetic basis … Continue reading →

As these GEITP pages continue to emphasize, multifactorial traits (phenotypes) reflect the contributions of [a] genetics, [b] epigenetic factors, [c] environmental effects, [d] endogenous influences, and [e] each person’s microbiome. The topic of this email [see attached article and editorial] … Continue reading →

In keeping with our gene-environment interactions theme, these GEITP pages are interested in genes (from any organism) that might “receive information” from any “environmental signal.” In today’s article [see attached], the worm genome (Caenorhabditis elegans, nematode; a roundworm) is the … Continue reading →

These GEITP pages have continued to examine genome-wide association studies (GWAS) because they are central to our theme of gene-environment interactions. Common (complex) diseases (e.g. obesity, schizophrenia) and other multifactorial traits (e.g. height, body mass index, response to drugs or … Continue reading →

From time to time, these GEITP pages have discussed animal (and plant) evolution — which was of course heavily influenced by gene-environment interactions. Given the climate and conditions on various regions of Earth some 2 billion years ago, living cells … Continue reading →

The topic for these GEITP pages today — is mind-boggling; I had no idea something like this was remotely yet possible. Recall that any trait (e.g. type-2 diabetes, coronary heart disease, height, body mass index, response to a drug or … Continue reading →