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Pasta Analyzes Aging The authors from the Karolinska Institute published an article on Pasta, an open set of programs for analyzing transcriptomes, on July 27. It estimates the age shift by gene activity and suggests which chemical or genetic effects to test in cells. In the article, Jerome Sailon and colleagues trained Pasta on 17,212 samples of healthy people from 21 studies. The transcriptome is a set of genes that a cell is using at the moment. The model compares which ones are more and less active within one sample and calculates the relative age score based on this order. One model works with different ways to measure gene activity: regular RNA sequencing, single cells, and old microchips. Usually, aging clocks give only a number: the sample looks younger or older. But the number depends on the model: eight epigenetic clocks gave the same blood samples estimates with a spread of 17 years on average. The authors of Pasta found another application for the age score. They passed the model through the Connectivity Map, an archive of cell reactions to substances and gene changes. It contains more than three million transcriptomes of 248 cell lines after more than 30,000 chemical and 14,000 genetic effects. 🔗 Read original →