Phenologue

How can researchers find biological determinants of brain-related disorders given the challenges of systematically characterizing those conditions? Despite advancements in genotyping technologies and analytic methodologies, much remains unknown about how genetic variants relate to complex traits found in psychiatric disorders, such as schizophrenia, major depression, bipolar disorder and autism.

One oft-cited reason for this lack of progress is the under use of intermediate phenotypes, or endophenotypes, which arguably provide higher genetic signal-to-noise ratios than the use of disease categories themselves. When researchers have incorporated endophenotypes into genetic analyses, the categories have not been based on a shared, well-defined and standardized set of definitions, making comparisons across studies and replication of prior findings problematic. Furthermore, it is unclear how categories of endophenotype measurements can be coherently integrated into multi-scale models of neuropathology. Phenomics—the systematic cataloging of phenotypes on a genome-wide scale—has emerged as a scientific endeavor within psychiatric genetics to address this challenge. A critical limitation to its advancement is the lack of available methods and tools for modeling, managing, and reasoning about endophenotypes.

Through support from the NSF-NIH Collaborative Research in Computational Neuroscience (CRCNS) initiative, we are overcoming this major impediment through the development of the Phenologue, a knowledge-based technology that can support collaborative efforts to reason about experimental data and published findings about endophenotypes. The project’s research objectives are to (1) develop an ontology of autism endophenotypes that maps brain connectivity, neural deficits, and genetic markers into a subject domain theory; (2) develop logic-based methods to encode and classify endophenotypes based on multi-scale measurements; (3) create tools to acquire new endophenotypes and annotate phenotype-genotype findings in online resources such as published literature; and (4) develop query-elicitation methods that can evaluate hypotheses about the subject domain theory of endophenotypes using deductive inference. These efforts are being undertaken through a collaboration of researchers in psychiatric genetics and deductive reasoning.