Introduction
Veterans diagnosed with post-traumatic stress disorder (PTSD) perform more poorly on neuropsychological measures (Vasterling et al., Reference Vasterling, Brailey, Constans and Sutker1998) and are more than twice as likely to develop dementia than those without PTSD (Yaffe et al, Reference Yaffe, Vittinghoff, Lindquist, Barnes, Covinsky, Neylan, Kluse and Marmar2010). The presence of vascular risk factors, such as hypertension, has been also associated with worse cognitive functioning and increased dementia risk (DeCarli et al., Reference DeCarli, Villeneuve, Maillard, Harvey, Singh, Carmichael, Fletcher, Olichney, Farias, Jagust, Reed and Mungas2019). Both PTSD and hypertension are common among Veterans (National Center for PTSD, 2024; DeBlois et al., Reference DeBlois, London and Heffernan2024) and Veterans with PTSD are at increased risk of developing hypertension (Kang et al., Reference Kang, Bullman and Taylor2006). While PTSD and hypertension often co-occur, little research has examined their combined effects on cognitive functioning, which may be more detrimental than the effect of either alone.
There are various mechanisms through which PTSD may affect cognitive functioning. The hypothalamic-pituitary-adrenal axis activates the stress response and, when dysregulated, may contribute to cardiovascular disease (Kang et al., Reference Kang, Bullman and Taylor2006) and Alzheimer’s disease (Elgh et al., Reference Elgh, Lindqvist Åstot, Fagerlund, Eriksson, Olsson and Näsman2006). Indeed, animal studies have revealed that chronic stress increases secretion of glucocorticoids and abnormal hyperphosphorylation of tau (Sotiropoulos et al., Reference Sotiropoulos, Catania, Pinto, Silva, Pollerberg, Takashima, Sousa and Almeida2011). Furthermore, human studies have shown that PTSD is associated with inflammatory markers (Lohr et al., Reference Lohr, Palmer, Eidt, Aailaboyina, Mausbach, Wolkowitz and Jeste2015) as well as perfusion alterations and white matter disruption (Schuff et al., Reference Schuff, Zhang, Zhan, Lenoci, Ching, Boreta, Mueller, Wang, Marmar, Weiner and Neylan2011), which may in turn affect cognition.
Similar to PTSD, there are multiple mechanisms by which hypertension may influence cognition. Hypertension is a major risk factor for stroke and has been associated with brain changes short of stroke including atherosclerosis (Eglit et al., Reference Eglit, Weigand, Nation, Bondi and Bangen2020), impaired perfusion and disruption of the blood-brain barrier, which may promote neuroinflammation and accumulation of AD neuropathology (Eglit et al., Reference Eglit, Weigand, Nation, Bondi and Bangen2020). The combined effects of PTSD and hypertension may exacerbate pathologic alterations such that there is a compounding effect on cognitive functioning. Although many previous studies have found additive or synergistic effects of other dementia risk factors (e.g., age, genetic risk, aggregate vascular risk) on cognitive and brain outcomes (Bangen et al., Reference Bangen, Nation, Clark, Harmell, Wierenga, Dev, Delano-Wood, Zlatar, Salmon, Liu and Bondi2014), to our knowledge, combined effects of hypertension and PTSD symptom severity on cognition have not been studied.
There is a critical need to identify early cognitive changes in individuals at risk for cognitive impairment and dementia before the development of significant cognitive and functional decline. Cognitive dispersion measures the within-person variability in performance across multiple neuropsychological tests at one single time point. Unlike the summary scores conventionally used in neuropsychological assessments, which assess mean-level performance within a cognitive domain or across multiple cognitive domains, cognitive dispersion can be conceptualized as a representation of the intraindividual variability in performance across cognitive measures. Studies have demonstrated that cognitive dispersion may provide a more sensitive marker of early cognitive difficulties than mean cognitive performance (Bangen et al., Reference Bangen, Weigand, Thomas, Delano-Wood, Clark, Eppig, Werhane, Edmonds and Bondi2019). As such, there is growing interest in applying cognitive dispersion indices as predictors of outcomes in various neurological disorders including Alzheimer’s disease (Bangen et al., Reference Bangen, Weigand, Thomas, Delano-Wood, Clark, Eppig, Werhane, Edmonds and Bondi2019), human immunodeficiency virus (Vance et al., Reference Vance, Del Bene, Frank, Billings, Triebel, Buchholz, Rubin, Woods, Li and Fazeli2022), and traumatic brain injury (Sorg et al., Reference Sorg, Merritt, Clark, Werhane, Holiday, Schiehser, Bondi and Delano-Wood2021).
In the present study we aimed to address gaps in the literature by examining the interactive effects of PTSD symptom severity and hypertension on cognitive dispersion, a potentially sensitive marker of subtle cognitive changes. This study included Veterans with PTSD only for two primary reasons. First, Veterans diagnosed with PTSD have poorer neuropsychological functioning relative to those not diagnosed with PTSD (Vasterling et al., Reference Vasterling, Brailey, Constans and Sutker1998). Second, we aimed to examine effects of PTSD symptom severity on cognitive dispersion among this group who is at increased risk of cognitive difficulties by virtue of having multiple dementia risk factors. We hypothesized that, among our sample of older Veterans with PTSD, greater PTSD symptom severity and the presence of hypertension would act synergistically to negatively impact cognitive dispersion (i.e., reflecting higher intraindividual variability).
Methods
Participants
Data were obtained using the Department of Defense Alzheimer’s Disease Neuroimaging Initiative (DoD-ADNI) database publicly available at adni.loni.usc.edu. DoD-ADNI recruitment procedures include identifying Vietnam Veterans who are service connected for PTSD and/or TBI from Veterans Affairs compensation and pension records and Veterans Affairs health records (Weiner et al., Reference Weiner, Harvey, Hayes, Landau, Aisen, Petersen, Tosun, Veitch, Jack, Decarli, Saykin, Grafman and Neylan2017). A minimum CAPS score of 40 points are required for inclusion in the PTSD group (Weiner et al., Reference Weiner, Harvey, Hayes, Landau, Aisen, Petersen, Tosun, Veitch, Jack, Decarli, Saykin, Grafman and Neylan2017). The present study included 128 Vietnam-era Veterans with PTSD with available demographic, neuropsychological, health, and psychiatric data. Participants were all between 61 and 82 years of age and with no prior diagnosis of dementia. Individuals with a history of psychosis, bipolar disorder, substance use disorder in the past 5 years, MRI ineligibility, seizure disorder, stroke, or unstable medical comorbidities were excluded from the overall DoD-ADNI study during screening. We additionally excluded individuals who were enrolled in DoD-ADNI and reported a history of stroke during their study participation (n = 3). This study was approved by the Institutional Review Board at DoD-ADNI study sites. Treatment of human participants was in full accordance with ethical standards set forth by the Helsinki Declaration. Informed written consent was obtained from all participants.
Clinical and cognitive measures
PTSD
Severity of PTSD symptoms was based on lifetime scores on the Clinician-Administered PTSD Scale (CAPS-IV), a structured interview performed by a trained interviewer. The overall structure of the CAPS-IV is congruent with the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria for PTSD diagnosis. Current symptoms are based on the one-month period before the CAPS interview and lifetime symptoms are based on the most symptomatic one-month period after the traumatic event(s). The structured interview provides severity ratings of current and lifetime/chronic PTSD symptoms based upon the summing of frequency and intensity scores. Consistent with DoD-ADNI study procedures (Weiner et al., Reference Weiner, Harvey, Hayes, Landau, Aisen, Petersen, Tosun, Veitch, Jack, Decarli, Saykin, Grafman and Neylan2017) and previous research studies (Weathers et al., Reference Weathers, Keane and Davidson2001), a minimum CAPS-IV score of 40 was required to be characterized with PTSD.
Hypertension status
Hypertension status was based on participant’s self-reported history of hypertension, systolic blood pressure > 140, and/or diastolic blood pressure > 90. If participants had any one or more of these indications, they were labeled as having hypertension and, if not, they were categorized as not having hypertension.
Cognitive dispersion
Cognitive dispersion was calculated as the within-person standard deviation across various neuropsychological measures at one time point. Eight measures were included in the dispersion index: (1) Boston Naming Test, (2) Animal Fluency, (3) Auditory Verbal Learning Test (AVLT) immediate recall, (4) AVLT delayed recall, (5) Logical Memory immediate recall, (6) Logical Memory delayed recall, (7) Trail Making Test, Part A, and (8) Trail Making Test, Part B. Prior to creating the dispersion index, all scores were standardized as z-scores based on the sample mean and standard deviation. Dispersion scores were log transformed to reduce skewness and one participant was excluded from analyses due to being an extreme outlier on the dispersion variable. The intraindividual mean of the 8 cognitive scores was also calculated. Given results may vary depending on which measures are included in a dispersion metric, an alternative dispersion index including the 4 episodic memory measures only was calculated to be used in secondary analyses.
Covariates
Depression symptoms were measured using the Geriatric Depression Scale. History of traumatic brain injury (TBI) was operationally defined as experiencing a loss of consciousness for more than 5 minutes, amnesia, and/or being dazed and confused for more than 24 hours (Weiner et al., Reference Weiner, Harvey, Hayes, Landau, Aisen, Petersen, Tosun, Veitch, Jack, Decarli, Saykin, Grafman and Neylan2017). Given comorbid vascular risk factors associated with hypertension may also affect cognition, we included comorbid vascular risk factors of type 2 diabetes and body mass index (BMI) as covariates.
Statistical analyses
Hierarchical linear regression models examined associations between PTSD symptom severity (mean centered CAPS-IV score), hypertension (present versus absent), and cognitive dispersion. Covariates were entered on step 1 and included age, education, depression symptoms, history of TBI (yes/no), type 2 diabetes (yes/no), and BMI; main effects of our predictor variables including PTSD symptom severity and hypertension were entered on step 2; and the interaction between PTSD symptom severity and hypertension was entered on step 3.
Secondary analyses were also performed. First, we re-ran primary analyses described above additionally adjusting for mean neuropsychological performance by including it as a covariate on step 1 of the model. Second, we re-ran primary analyses substituting mean neuropsychological performance as the dependent variable rather than cognitive dispersion. Finally, we re-ran our primary analyses using the memory dispersion variable as the dependent variable.
Relevant assumptions of ordinary least squares regression were tested to ensure that they were not violated. Potential multicollinearity of the independent variables was examined for our primary models. All variance inflation factor values were <1.25. Visual inspection of the probability plot revealed a normal distribution of the residuals and scatterplots showed that assumptions of homoscedasticity were met. Statistical analyses were performed using IBM SPSS Statistics for Macintosh, Version 28.0.1.1.
Results
Participant characteristics
The sample of 128 older Veterans with PSTD was majority male (98.4%) and White (85.9%). Across the entire sample, the mean age was 68.80 and the mean educational attainment was 14.61 years. The majority of the sample had hypertension (78.9%).
There were no significant differences between individuals with and without hypertension in age, education, sex, race/ethnicity, PTSD symptom severity, depression symptoms, TBI status, mean neuropsychological performance, or cognitive dispersion scores (p-values > 0.05). There were no group differences on cognitive screening measures (mean Mini-Mental State Examination score across the sample was 28 and all participants had a Clinical Dementia Rating global score of 0 or 0.5). However, the hypertensive group had higher mean BMI than the non-hypertensive group (F = 7.78, p = .006).
Main effects and interaction of PTSD symptom severity and hypertension on dispersion
Adjusting for age, education, depression symptoms, TBI status, type 2 diabetes, and BMI, there was a significant main effect of PTSD symptom severity on cognitive dispersion (β = .212, p = .028) but no significant main effect of hypertension on cognitive dispersion (β = −.061, p = .513). There was a significant interaction between PTSD symptom severity and hypertension on cognitive dispersion (β = .482, p = .026). See Table 1. Analyses stratified by hypertensive status showed greater PTSD symptom severity was associated with higher cognitive dispersion (β = .348, p = .002) among those with hypertension, but not those without hypertension (β = −.147, p = .531). See Table 2.
Table 1. Hierarchical linear regression model for effects of PTSD symptom severity, hypertension, and their interaction on cognitive dispersion as the outcome variable across the entire sample (n = 128)
TBI = Traumatic Brain Injury; PTSD = Post-Traumatic Stress Disorder; BMI = Body Mass Index. Significant associations (p < .05) appear in bold font.
Table 2. Hierarchical linear regression models for effects of PTSD symptom severity on cognitive dispersion as the outcome variable stratified by hypertension status
TBI = Traumatic brain injury; PTSD = Post-Traumatic Stress Disorder; BMI = Body Mass Index. Significant associations (p < .05) appear in bold font.
Secondary analyses
After re-running the primary analyses described above but including mean cognitive performance as an additional covariate, there were no significant main effects of PTSD symptom severity or hypertension on cognitive dispersion (p-values > .05). The interaction of PTSD symptom severity and hypertension on cognitive dispersion remained significant (β = .441, p = .033). Analyses stratified by hypertensive status showed that, after additionally adjusting for mean cognitive performance, greater PTSD symptom severity was associated with higher cognitive dispersion among those with hypertension (β = .275, p = .012) but not among those without hypertension (β = −.199, p = .382). When re-running our primary analyses replacing cognitive dispersion with mean cognitive performance as our dependent variable, there was no significant interactive effect of PTSD symptom severity and hypertension (β = −.131, p = .543). Finally, when re-running our primary models using the episodic memory dispersion measure as the dependent variable, there was no significant interactive effect of PTSD and hypertension (β = .215, p = .339).
Discussion
We identified an interaction whereby, for older Veterans with hypertension and PTSD, greater PTSD symptom severity was associated with greater cognitive dispersion (i.e., greater intraindividual variability). For those older Veterans without hypertension, there was no association between PTSD symptom severity and cognitive dispersion. This pattern of findings suggests that older Veterans with both more severe PTSD symptoms and hypertension may be particularly at risk for cognitive difficulties. These results may have implications for clinical practice, emphasizing the importance of considering risk factor comorbidity when determining risk of cognitive decline and dementia.
Our results indicated PTSD symptom severity and hypertension had synergistic effects on cognitive dispersion, but not on mean cognitive performance. This might suggest that cognitive dispersion provides a more sensitive marker of subtle cognitive deficits than traditional mean performance among participants with comorbid psychiatric and vascular risk factors. It could have been that cognitive dispersion provided a sensitive enough measure to detect the more subtle cognitive deficits that have previously been associated with PTSD in the absence of dementia (Leskin & White, Reference Leskin and White2007). The present findings are consistent with previous studies also showing the effects of variables of interest on dispersion remain after adjusting for mean performance, further highlighting the utility of dispersion (Bangen et al., Reference Bangen, Weigand, Thomas, Delano-Wood, Clark, Eppig, Werhane, Edmonds and Bondi2019).
Cognitive dispersion has often been proposed to index cognitive control processes subserved by frontal regions (MacDonald et al., Reference MacDonald, Li and Bäckman2009) and may be relevant for many different disorders and conditions that affect frontal lobe integrity and/or connectivity. Interestingly, depending on the model, some of the covariates including age, history of TBI, and depression were associated with cognitive dispersion. These results are in line with previous research showing that advancing age and history of TBI are associated with increased dispersion (Hilborn et al., Reference Hilborn, Strauss, Hultsch and Hunter2009; Sorg et al., Reference Sorg, Merritt, Clark, Werhane, Holiday, Schiehser, Bondi and Delano-Wood2021). There has been growing interest in using cognitive dispersion to predict outcomes in several different neurological disorders including, but not limited, to Alzheimer’s disease risk (Bangen et al., Reference Bangen, Weigand, Thomas, Delano-Wood, Clark, Eppig, Werhane, Edmonds and Bondi2019), human immunodeficiency virus (Vance et al., Reference Vance, Del Bene, Frank, Billings, Triebel, Buchholz, Rubin, Woods, Li and Fazeli2022), and TBI (Sorg et al., Reference Sorg, Merritt, Clark, Werhane, Holiday, Schiehser, Bondi and Delano-Wood2021). To our knowledge, the present study is the first to examine associations of cognitive dispersion with PTSD symptom severity and hypertension. Future research is needed to assess specificity and sensitivity of dispersion indices across different conditions.
Our findings suggest that results may vary depending on how many and which measures are included in the dispersion index. Results from secondary analyses using an alternative dispersion metric that included episodic memory measures only were attenuated and the interaction term was no longer significant. However, we were unable to comprehensively assess how findings might differ by test/domains sampled given the relatively limited neuropsychological battery used in the DoD-ADNI study. Nonetheless, our findings suggest that including measures across multiple cognitive domains may be more sensitive than a metric including scores from a single domain. Future research is needed to determine which measures and how many measures form the optimal dispersion metric as well as to establish consensus methods for calculating dispersion, which will increase the utility of cognitive dispersion in both clinical practice and research.
We focused on hypertension given it is prevalent among older adults (Mills et al., Reference Mills, Bundy, Kelly, Reed, Kearney, Reynolds, Chen and He2016), can have widespread damaging effects on multiple organs, and significantly increases the risk of conditions including cardiovascular disease and stroke (Libby et al., Reference Libby, Buring, Badimon, Hansson, Deanfield, Bittencourt, Tokgözoğlu and Lewis2019). Our finding of an interactive effect between hypertension and PTSD symptom severity after adjusting for potentially confounding comorbid vascular risk factors and excluding individuals with history of stroke, suggests that hypertension itself may have synergistic effects with PTSD symptom severity. However, it is difficult to completely isolate effects of a single vascular risk factor and it is possible that other comorbid health conditions, including those unmeasured in the present study, may contribute to cognitive dispersion. Notably, we did not have access to some health-related data including cholesterol levels, inflammatory markers, and liver and kidney function, which should be incorporated in future research.
Study limitations include the cross-sectional design; overrepresentation of non-Latino whites and underrepresentation of women; and the small size of the non-hypertensive group which may have reduced statistical power. Future longitudinal studies will be useful to compare lifetime and current PTSD as well as the effects of duration and chronicity of PTSD on cognitive dispersion. Such studies may help disentangle whether subtle cognitive difficulties such as those captured by dispersion are reversible if PTSD symptoms are treated.
Acknowledgements
The analyses reported in the manuscript were funded by NIH/NIA grant R01 AG063782 to K.J.B. and NIH/NIA grant to the San Diego State University Advancing Diversity in Aging Research program (5R25 AG043364-12). Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This research was also supported by NIH grants P30 AG010129 and K01 AG030514.
Competing Interests
The authors have no conflicts of interest to report.
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