Part of the Advances and Challenges in Computational Biology, hosted by PLoS Computational Biology
Should be from Bench to Bytes to Bedside (and Back), not from Bench to Bedside. There have been many successes in TM, but it’s not always clear that the loop is being closed between new discoveries and the clinical practices. Common complaint is lack of funding, and time it takes to get new drugs to market. What might be helpful in closing the loop: strongly-interdisciplinary collaborations, availability of clinical data, and standards to ensure that data are shared in useful ways.
Translational Development Genomics: while there has been progress in screening, is there anything more that we can get out of genomics data and help with diagnoses? Collaboration with Diana Bianchi. In addition to DNA screening, real-time fetal RNA from amniotic fluid could get lots of information. Also, you can find fetal RNA in maternal blood. They identified 157 genes upregulated in pregnant moms and their babies, compared to postpartum moms. In the UniGene db, 6 of their proteins were unique to the fetus and 76 have predominately fetal or neonatal expression. Over-represented functions include neural development, muscle development, lung development, cell division, visual perception, digestion, perception of smell, response to pathogens. This hinted that these were fetal. So, they looked for SNPs in the transcript to verify the fetal source of RNA. They were seeing fetal transcripts, as SNPs suggested antepartum e.g. A/A + A/T, fetal was A/T and postpartum was A/A.
So they did a pilot study for Down’s Syndrome (caused by trisomy 21). They profiled amniotic fluid from trisomy 21 and control sample pairs matched by sex – looking for 1.5-fold expression in chromosome 21 to account for the extra genes. There is quite a range of expression – very little is significant. BUT there’s huge disregulation of the genome. Everything (414 individual genes, 82 leading edge genes in Chr21q22, connectivity map) pointed to the same functional results. Categories significant in both gene sets (chr21 and rest of genome): response to oxidative stress ,G-protein signaling, ion transport, cell structure proteins, circulatory system function, developmental pathways, sensory perception. The connectivity map further implicates oxidative stress: this map correlates observed expression patterns with gene expression changes caused by various drugs. The top compounds (positive correlation) relate to oxidation and ion transport. Trying to find any drugs that affect these are also approved for use in pregnant women (will take a while).
Their work relies on shared public data and tools. An additional obstacle to progress is that functional annotation is not designed for this developmental stage, and there is need for a shared annotation effort.
Please note that this post is merely my notes on the presentation. They are not guaranteed to be correct, and unless explicitly stated are not my opinions. They do not reflect the opinions of my employers. Any errors you can happily assume to be mine and no-one else’s. I’m happy to correct any errors you may spot – just let me know!