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Related Experiment Video

Updated: Feb 4, 2026

Generation of Human Brain Organoids for Mitochondrial Disease Modeling

Generation of Human Brain Organoids for Mitochondrial Disease Modeling

Published on: June 21, 2021

Pathway networks generated from human disease phenome.

Ann G Cirincione¹, Kaylyn L Clark¹, Maricel G Kann²

¹Department of Biological Sciences, University of Maryland, Baltimore County (UMBC), Baltimore, MD, 21250, USA.

BMC Medical Genomics

|September 27, 2018

Summary

This summary is machine-generated.

This study reveals new molecular links between genetic variations and diseases using a pathway-based approach. It identifies novel disease connections and common pathways, aiding personalized medicine and drug discovery.

Keywords:

Disease mutations Networks Phenome

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Area of Science:

Genomics and Bioinformatics
Systems Biology
Medical Genetics

Background:

Human genetic variations influence disease susceptibility and phenotype-genotype relationships.
Understanding these links is crucial for advancing personalized medicine.
Current knowledge of disease-associated genetic markers is incomplete.

Purpose of the Study:

To develop and apply a pathway-based approach to uncover novel disease-variant associations.
To identify new molecular connections between genetic mutations and diseases.
To extend the understanding of the genetic basis of complex diseases.

Main Methods:

Utilized a comprehensive dataset of over 80,000 human genetic variants with known disease associations.
Employed the Unified Medical Language System (UMLS) for normalizing variant phenotype terminologies.
Grouped variants by UMLS Medical Subject Heading (MeSH) identifiers to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis.

Main Results:

Elucidated connections between the human genetic variant-based disease phenome and metabolic pathways.
Identified novel disease connections not apparent through gene-level analysis.
Found that complex diseases like cancers share common pathways; Cardiovascular and Skin/Connective Tissue Diseases showed the most common pathways.

Conclusions:

This study extends disease-variant connections and reveals new molecular links between diseases.
Novel disease connections were established through disease-pathway associations, bypassing single-gene analysis limitations.
The findings support the development of disease-drug networks for improved diagnostics and therapeutics.