Using mechanistic models for the clinical interpretation of complex genomic variation

Abstract

The sustained generation of genomic data in the last decade has increased the knowledge on the causal mutations of a large number of diseases, especially for highly penetrant Mendelian diseases, typically caused by a unique or a few genes. However, the discovery of causal genes in complex diseases has been far less successful. Many complex diseases are actually a consequence of the failure of complex biological modules, composed by interrelated proteins, which can happen in many different ways, which conferring a multigenic nature to the condition that can hardly be attributed to one or a few genes. We present a mechanistic model, Hipathia, implemented in a web server that allows estimating the effect that mutations, or changes in the expression of genes, have over the whole system of human signaling and the corresponding functional consequences. We show several use cases where we demonstrate how different the ultimate impact of mutations with similar loss-of-function potential can be and how the potential pathological role of a damaged gene can be inferred within the context of a signaling network. The use of systems biology-based approaches, such as mechanistic models, allows estimating the potential impact of loss-of-function mutations occurring in proteins that are part of complex biological interaction networks, such as signaling pathways. This holistic approach provides an elegant alternative to gene-centric approaches that can open new avenues in the interpretation of the genomic variability in complex diseases.

Mechanistic Models of Signaling Pathways Reveal the Drug Action Mechanisms behind Gender-Specific Gene Expression for Cancer Treatments

“…Nevertheless, the functional consequences at the level of cell behavior or fate of gender bias in gene expression have remained mainly unknown. To our knowledge, this is the first time that such gender specific differences in gene expression are evaluated in the context of perturbation response, taking into consideration cell mechanisms as a whole, an approach that has successfully been used to explain different cancer molecular mechanisms [14,15,17,20,53].…”

“…Therefore, a proper interpretation of the effect that differences in gene expression have over phenotypes, such as drug response or disease progression, involves understanding the mechanisms of the disease or the mode of action of drugs, which can be interpreted through mechanistic models of cell signaling [ 12 ] or cell metabolism [ 13 ]. Mechanistic models have helped to understand the disease mechanisms behind different cancers [ 14 , 15 ], including neuroblastoma [ 16 , 17 ], breast cancer [ 18 ], rare diseases [ 19 ], complex diseases [ 20 ], the mechanisms of action of drugs [ 21 , 22 ], and other biologically interesting scenarios such as the molecular mechanisms that explain how stress-induced activation of brown adipose tissue prevents obesity [ 23 ] or the molecular mechanisms of death and the post-mortem ischemia of a tissue [ 24 ]. Among the few available proposals of mechanistic modeling algorithms that model different aspects of signaling pathway activity, Hipathia has demonstrated having superior sensitivity and specificity [ 12 ].…”

Genetic Modifiers and Rare Mendelian Disease

“…Over the years, researchers have developed such knowledge bases and ontologies, which have facilitated the development of computational models and automation systems for bioinformatics analysis. A range of scoring and variant interpretation techniques have been developed to better understand each variant and its pathway [145]. Resources like BioGrid [118], GeneMania [146], model organism-specific knowledgebases [29,147], Gene Ontology [148,149], Phenotype Ontology [150], and pathway analysis [151] are currently helping researchers in modifier identification studies and may help to develop computational models for modifier identification in the future [2].…”

Mechanistic modeling of the SARS-CoV-2 disease map

“…The knowledge of these links allows a better understanding of the molecular mechanisms of the viral infection and the responses to drugs. Actually, mechanistic models of human signaling (7) or metabolic pathways (8) have been successfully used to uncover speci c molecular mechanisms behind different cancers (7,(9)(10)(11), rare (12) and common (13) diseases, to reveal mechanisms of action of drugs (14), and dissecting them at single cell level (15), to suggest personalized treatments (16,17) and in other biologically interesting scenarios (18,19). Basically, mechanistic models analyze experimental values in the context of the disease map information, which is used to point out the relevant aspects of the molecular mechanisms behind the experiment.…”