Multi-study reanalysis of 2,213 acute myeloid leukemia patients reveals age- and sex-dependent gene expression signatures.

In 2019 it is estimated that more than 21,000 new acute myeloid leukemia (AML) patients will be diagnosed in the United States, and nearly 11,000 are expected to die from the disease. AML is primarily diagnosed among the elderly (median 68 years old at diagnosis). Prognoses have significantly improved for younger patients, but as much as 70% of patients over 60 years old will die within a year of diagnosis. In this study, we conducted a reanalysis of 2,213 acute myeloid leukemia patients compared to 548 healthy individuals, using curated publicly available microarray gene expression data. We carried out an analysis of normalized batch corrected data, using a linear model that included considerations for disease, age, sex, and tissue. We identified 974 differentially expressed probe sets and 4 significant pathways associated with AML. Additionally, we identified 375 age- and 70 sex-related probe set expression signatures relevant to AML. Finally, we trained a k nearest neighbors model to classify AML and healthy subjects with 90.9% accuracy. Our findings provide a new reanalysis of public datasets, that enabled the identification of new gene sets relevant to AML that can potentially be used in future experiments and possible stratified disease diagnostics.

The TFAP2A-IRF6-GRHL3 genetic pathway is conserved in neurulation.

Mutations in IRF6, TFAP2A and GRHL3 cause orofacial clefting syndromes in humans. However, Tfap2a and Grhl3 are also required for neurulation in mice. Here, we found that homeostasis of Irf6 is also required for development of the neural tube and associated structures. Over-expression of Irf6 caused exencephaly, a rostral neural tube defect, through suppression of Tfap2a and Grhl3 expression. Conversely, loss of Irf6 function caused a curly tail and coincided with a reduction of Tfap2a and Grhl3 expression in tail tissues. To test whether Irf6 function in neurulation was conserved, we sequenced samples obtained from human cases of spina bifida and anencephaly. We found two likely disease-causing variants in two samples from patients with spina bifida. Overall, these data suggest that the Tfap2a-Irf6-Grhl3 genetic pathway is shared by two embryologically distinct morphogenetic events that previously were considered independent during mammalian development. In addition, these data suggest new candidates to delineate the genetic architecture of neural tube defects and new therapeutic targets to prevent this common birth defect.

MathIOmica: An Integrative Platform for Dynamic Omics.

Multiple omics data are rapidly becoming available, necessitating the use of new methods to integrate different technologies and interpret the results arising from multimodal assaying. The MathIOmica package for Mathematica provides one of the first extensive introductions to the use of the Wolfram Language to tackle such problems in bioinformatics. The package particularly addresses the necessity to integrate multiple omics information arising from dynamic profiling in a personalized medicine approach. It provides multiple tools to facilitate bioinformatics analysis, including importing data, annotating datasets, tracking missing values, normalizing data, clustering and visualizing the classification of data, carrying out annotation and enumeration of ontology memberships and pathway analysis. We anticipate MathIOmica to not only help in the creation of new bioinformatics tools, but also in promoting interdisciplinary investigations, particularly from researchers in mathematical, physical science and engineering fields transitioning into genomics, bioinformatics and omics data integration.