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. 2025 Jan;66(1):170-183.
doi: 10.1111/epi.18170. Epub 2024 Nov 2.

Distinct comorbidity phenotypes among post-9/11 Veterans with epilepsy are linked to diverging outcomes and mortality risks

Mary Jo Pugh  1   2 , Heidi Munger Clary  3   4 , Madeleine Myers  1   2 , Eamonn Kennedy  1   2 , Megan Amuan  1 , Alicia A Swan  5 , Sidney Hinds  6   7   8   9 , W Curt LaFrance  10   11   12 , Hamada Altalib  13   14 , Alan Towne  14   15   16 , Amy Henion  1   2 , Abigail White  1   2 , Christine Baca  15 , Chen-Pin Wang  5
Affiliations

Distinct comorbidity phenotypes among post-9/11 Veterans with epilepsy are linked to diverging outcomes and mortality risks

Mary Jo Pugh et al. Epilepsia. 2025 Jan.

Abstract

Objective: To investigate phenotypes of comorbidity before and after an epilepsy diagnosis in a national cohort of post-9/11 Service Members and Veterans and explore phenotypic associations with mortality.

Methods: Among a longitudinal cohort of Service Members and Veterans receiving care in the Veterans Health Administration (VHA) from 2002 to 2018, annual diagnoses for 26 conditions associated with epilepsy were collected over 5 years, ranging from 2 years prior to 2 years after the year of first epilepsy diagnosis. Latent class analysis (LCA) was used to identify probabilistic comorbidity phenotypes with distinct health trajectories. Descriptive statistics were used to describe the characteristics of each phenotype. Fine and Gray cause-specific survival models were used to measure mortality outcomes for each phenotype up to 2021.

Results: Six distinct phenotypes were identified: (1) relatively healthy, (2) post-traumatic stress disorder, (3) anxiety and depression, (4) chronic disease, (5) bipolar/substance use disorder, and (6) polytrauma. Accidents were the most common cause of death overall, followed by suicide/mental health and cancer, respectively. Each phenotype exhibited unique associations with mortality and cause of death, highlighting the differential impact of comorbidity patterns on patient outcomes.

Significance: By delineating clinically meaningful epilepsy comorbidity phenotypes, this study offers a framework for clinicians to tailor interventions. Moreover, these data support systems of care that facilitate treatment of epilepsy and comorbidities within an interdisciplinary health team that allows continuity of care. Targeting treatment toward patients with epilepsy who present with specific heightened risks could help mitigate adverse outcomes and enhance overall patient care.

Keywords: epilepsy; mental health; phenotype; somatic comorbidity; traumatic brain injury.

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Conflict of interest statement

We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines. M.J. Pugh's institutions receive and has received (in the past 5 years) research grant funding from the National Institutes of Health, Department of Defense, and the Department of Veterans Affairs, and is employed by the Department of Veterans Affairs and the University of Utah. Dr. Pugh also received funding from Sanofi unrelated to epilepsy research. H. Munger Clary reports research funding from the National Institutes of Health, Department of Defense, National Science Foundation, Duke Endowment, Susanne Marcus Collins Foundation, and Eysz, Inc. E. Kennedy reports research funded by the Department of Defense.

S. Hinds reports consultant for SCS Consulting, LLC. Dr. Hinds has also received funding from the Department of Defense and National Institutes of Health and was previously employed by the Department of Defense. W. LaFrance reports research funded by the Department of Defense. H. Altalib reports that his institution has received research support from UCB, Eisai, and Sunovian. The institution of Dr. Altalib has received research support from the Department Of Defense—Congressionally Directed Medical Research Programs. A. Towne reports research grants from CURE and AbbVie (unrelated to epilepsy research) and participation on speakers' bureaus for AbbVie. Dr. Towne has also received funding from the Department of Defense and Department of Veterans Affairs, and is employed by the Department of Veterans Affairs and Virginia Commonwealth University. The remaining authors have no conflicts of interest to disclose.

Figures

FIGURE 1
FIGURE 1
Cohort flow diagram.
FIGURE 2
FIGURE 2
Comorbidity Trajectories of each Phenotype Class: 2 years prior to Epilepsy Index Date—2 Years after Epilepsy Index Date.Six phenotypes of epilepsy were identified using LCA. Phenotypes include (A) Relatively Healthy, (B) Post‐Traumatic Stress Disorder (PTSD), (C) Anxiety and Depression, (D) Chronic Disease, (E) Bipolar Disorder/Substance Use Disorder (Bipolar/SUD), and (F) Polytrauma.
FIGURE 3
FIGURE 3
Kaplan–Meier curves of mortality from the epilepsy index date, according to phenotype. Mortality rates and causes of death across phenotypes in a follow‐up period, with the highest observed in Chronic Disease and Bipolar Disorder/SUD (substance use disorder) groups, followed by Polytrauma, PTSD (Post‐Traumatic Stress Disorder), Anxiety and Depression, and Relatively Healthy.
FIGURE 4
FIGURE 4
Common causes of death by epilepsy comorbidity phenotype.
See this image and copyright information in PMC

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