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Generalized Anxiety Disorder

Generalized Anxiety Disorder

Generalized Anxiety Disorder (GAD) is a chronic condition characterized by excessive and uncontrollable worry that persists for at least six months, significantly interfering with daily functioning. Unlike situational anxiety, which arises in response to specific stressors, GAD often occurs without a clear cause. Individuals may experience disproportionate worry about work, health, or relationships. For instance, a person might continuously fear poor health despite normal medical evaluations or...

Anxiety: Overview

Anxiety: Overview

Anxiety is a common mental disorder featuring excessive worry, fear, and apprehension, significantly affecting daily life. People with anxiety disorders experience persistent and intense anxiety, interrupting their everyday functioning.
Individuals with anxiety often experience a range of physical and emotional symptoms, including sweating, trembling, tachycardia, and disturbances in sleep patterns. These symptoms vary in intensity and frequency but are generally disruptive and distressing.

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Brain Age Prediction in Generalized Anxiety Disorder using a Convolutional Neural Network.

Corey Richier^1,2, André Zugman², Anita Harrewijn^2,3

¹Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

Research Square

|July 9, 2025

Summary

This summary is machine-generated.

This study found no accelerated brain aging in individuals with generalized anxiety disorder (GAD). However, individuals with GAD showed greater variability in predicted brain age difference, suggesting increased heterogeneity in brain aging patterns.

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Published on: February 14, 2014

Area of Science:

Neuroimaging
Psychiatry
Aging Research

Background:

Accelerated brain aging is linked to psychiatric disorders.
Generalized anxiety disorder (GAD) may present markers of accelerated aging.

Purpose of the Study:

To determine brain predicted age difference (PAD) in individuals with GAD compared to healthy controls (HC).
To investigate group differences in PAD variability using structural MRI.

Main Methods:

Utilized a large dataset (3,511 controls, 1,595 GAD, 4,552 HC) from the ENIGMA-Anxiety GAD Working Group.
Employed a convolutional neural network model with four input modalities for brain age prediction.
Calculated PAD by subtracting chronological age from predicted brain age.

Main Results:

Model performance showed consistent accuracy (MAE ≈ 2.95 years) in training and HC testing sets.
No evidence of accelerated brain aging was found in individuals with GAD.
Individuals with GAD exhibited significantly greater variability in PAD (Levene's test: W = 442.98, p < .001), particularly those over 25 years old.

Conclusions:

The study did not find a significant association between GAD and accelerated brain aging (PAD).
GAD is associated with increased heterogeneity in brain-predicted age, indicating diverse aging trajectories within the GAD group.
No correlations were observed between PAD and clinical or demographic factors in individuals with GAD.