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Updated: Jun 20, 2026

Phenotypic Profiling of Human Stem Cell-Derived Midbrain Dopaminergic Neurons

Phenotypic Profiling of Human Stem Cell-Derived Midbrain Dopaminergic Neurons

Published on: July 7, 2023

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

Jeban Ganesalingam¹, Daniel Stahl, Lokesh Wijesekera

¹Department of Clinical Neuroscience, MRC Centre for Neurodegeneration Research, King's College London, Institute of Psychiatry, London, United Kingdom.

|September 23, 2009

Summary

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Latent cluster analysis identified five distinct amyotrophic lateral sclerosis (ALS) phenotypes that predict survival. This approach can improve patient stratification in clinical trials and research for ALS.

Area of Science:

Neurology
Biostatistics

Background:

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder with diverse clinical presentations.
The underlying disease processes for different ALS phenotypes remain unclear.
Objective phenotyping is crucial for advancing ALS research and clinical management.

Purpose of the Study:

To objectively identify distinct phenotypic groupings in amyotrophic lateral sclerosis (ALS) using latent cluster analysis.
To improve the phenotyping of ALS for enhanced clinical trials and research.
To determine if distinct ALS phenotypes correlate with different disease processes.

Main Methods:

Latent class cluster analysis was performed on a database of 1467 individuals with ALS.
Discrete clinical variables, readily available at initial appointments, were utilized.

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Last Updated: Jun 20, 2026

Phenotypic Profiling of Human Stem Cell-Derived Midbrain Dopaminergic Neurons

Phenotypic Profiling of Human Stem Cell-Derived Midbrain Dopaminergic Neurons

Published on: July 7, 2023

The clinical relevance of identified phenotypic groups was assessed using Kaplan-Meier survival analysis.

Main Results:

The analysis yielded five distinct phenotypic classes of ALS.
These five classes demonstrated a strong predictive capability for patient survival (p<0.0001).
Accurate classification was achievable using only two variables: symptom onset site and time from onset to diagnosis.

Conclusions:

The identified five phenotypic classes of ALS are prognostic.
These objective phenotypic groupings can be utilized for stratifying patients in clinical trials.
The classification facilitates the creation of more homogeneous groups for genetic, proteomic, and risk factor research in ALS.