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Related Experiment Video

Updated: Feb 10, 2026

Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins

Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins

Published on: June 11, 2015

Clinical phenome scanning.

Nader Ghebranious^1,2, Catherine A McCarty², Russell A Wilke^2,3

¹Marshfield Clinic, Molecular Diagnostics Genotyping Laboratory, Marshfield, WI, USA. ghebranious.nader@marshfieldclinic.org.

Personalized Medicine

|May 24, 2018

Summary

This summary is machine-generated.

This study introduces a clinical phenome scanning approach for genetic research. It links comprehensive patient health data to genetic variations to uncover gene-disease associations.

Keywords:

DNA biobank clinical phenome scan common diseases phenomic markers pleiotropy

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CMAP Scan MUNE MScan - A Novel Motor Unit Number Estimation MUNE Method

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Published on: June 7, 2018

Area of Science:

Genetics and Genomics
Bioinformatics
Clinical Research

Background:

Large population cohorts are crucial for studying complex diseases and gene interactions.
Common diseases exhibit heterogeneity, necessitating advanced analytical approaches.
Population-based DNA biobanks offer rich phenotypic data for genetic studies.

Purpose of the Study:

To propose a novel clinical phenome scanning approach for genotype-phenotype association studies.
To leverage extensive electronic medical record data for disease-gene discovery.
To shift the research question from "Which gene for which disease?" to "Which disease for which gene?"

Main Methods:

Implementing a clinical phenome scan by analyzing all available clinical information from electronic medical records.
Conducting a subject-by-subject scan to construct individual phenomes.
Interrogating phenomes for associations with specific gene alleles.

Main Results:

The clinical phenome scanning approach enables the identification of diseases associated with specific genes.
This method accounts for the heterogeneous nature of common complex disorders.
It facilitates a phenotype-first strategy in genetic association studies.

Conclusions:

The clinical phenome scanning approach offers a powerful new paradigm for genotype-phenotype association studies.
This method enhances the utility of population-based DNA biobanks and electronic health records.
It provides a framework for discovering novel gene-disease relationships by prioritizing phenotypes.