Connections for Matters of the Heart: Network Medicine in Cardiovascular Diseases.

Cardiovascular diseases (CVD) are diverse disorders affecting the heart and vasculature in millions of people worldwide. Like other fields, CVD research has benefitted from the deluge of multiomics biomedical data. Current CVD research focuses on disease etiologies and mechanisms, identifying disease biomarkers, developing appropriate therapies and drugs, and stratifying patients into correct disease endotypes.

Constructing gene regulatory networks using epigenetic data.

The biological processes that drive cellular function can be represented by a complex network of interactions between regulators (transcription factors) and their targets (genes). A cell's epigenetic state plays an important role in mediating these interactions, primarily by influencing chromatin accessibility. However, how to effectively use epigenetic data when constructing a gene regulatory network remains an open question.

GRAND: a database of gene regulatory network models across human conditions.

Gene regulation plays a fundamental role in shaping tissue identity, function, and response to perturbation. Regulatory processes are controlled by complex networks of interacting elements, including transcription factors, miRNAs and their target genes. The structure of these networks helps to determine phenotypes and can ultimately influence the development of disease or response to therapy.

Using network science tools to identify novel diet patterns in prodromal dementia.

Objective: To use network science to model complex diet relationships a decade before onset of dementia in a large French cohort, the 3-City Bordeaux study.

Methods: We identified cases of dementia incident to the baseline food frequency questionnaire over 12 years of follow-up. For each case, we randomly selected 2 controls among individuals at risk at the age at case diagnosis and matched for age at diet assessment, sex, education, and season of the survey.

Understanding Tissue-Specific Gene Regulation.

Although all human tissues carry out common processes, tissues are distinguished by gene expression patterns, implying that distinct regulatory programs control tissue specificity. In this study, we investigate gene expression and regulation across 38 tissues profiled in the Genotype-Tissue Expression project. We find that network edges (transcription factor to target gene connections) have higher tissue specificity than network nodes (genes) and that regulating nodes (transcription factors) are less likely to be expressed in a tissue-specific manner as compared to their targets (genes).