Examining Frontal Lobe Asymmetry and Its Potential Role in Aggressive Behaviors in Early Alzheimer’s Disease

Abstract

Background:

Neuropsychiatric symptoms (NPS) in patients with dementia lead to caregiver burdens and worsen the patient’s prognosis. Although many neuroimaging studies have been conducted, the etiology of NPS remains complex. We hypothesize that brain structural asymmetry could play a role in the appearance of NPS.

Objective:

This study explores the relationship between NPS and brain asymmetry in patients with Alzheimer’s disease (AD).

Methods:

Demographic and MRI data for 121 mild AD cases were extracted from a multicenter Japanese database. Brain asymmetry was assessed by comparing the volumes of gray matter in the left and right brain regions. NPS was evaluated using the Neuropsychiatric Inventory (NPI). Subsequently, a comprehensive assessment of the correlation between brain asymmetry and NPS was conducted.

Results:

Among each NPS, aggressive NPS showed a significant correlation with asymmetry in the frontal lobe, indicative of right-side atrophy (r = 0.235, p = 0.009). This correlation remained statistically significant even after adjustments for multiple comparisons (p < 0.01). Post-hoc analysis further confirmed this association (p < 0.05). In contrast, no significant correlations were found for other NPS subtypes, including affective and apathetic symptoms.

Conclusions:

The study suggests frontal lobe asymmetry, particularly relative atrophy in the right hemisphere, may be linked to aggressive behaviors in early AD. These findings shed light on the neurobiological underpinnings of NPS, contributing to the development of potential interventions.

Keywords

Alzheimer’s disease asymmetry behavioral and psychological symptoms of dementia neuroimaging

INTRODUCTION

Approximately 47 million people worldwide are affected by dementia, projected to increase to 131 million by 2050 [1]. During the course of dementia, patients present with neuropsychiatric symptoms (NPS), including aggression, delusions and apathy, which significantly increases the caregiver burdens and worsens the patient’s prognosis [2, 3]. NPS manifests from the early to late stages of dementia [4], and early intervention is expected to alleviate these symptoms[5]. However, there is no established treatment for NPS, and its pathogenesis remains unclear [6].

In addition to psychological and social factors, the etiology of NPS is considered to involve structural and functional changes in the brain associated with neurodegeneration [7]. Although numerous neuroimaging studies have explored neural correlates of NPS, their findings have been inconsistent. In particular, nonspecific symptoms such as agitation and apathy involve multiple brain regions, including the frontal, temporal, and limbic regions [8 –10], and it is difficult to localize these symptoms into a single region [11, 12]. In recent years, the focus has shifted to examining these symptoms in the context of brain circuits or large-scale brain networks [13 –15]; however, a consensus has yet to be reached [16]. Consequently, there is an urgent need for neuroimaging studies that can elucidate the neural correlates of nonspecific symptoms such as agitation.

Recently, asymmetric changes in brain structure in dementia have been shown to detect cognitive dysfunction [17, 18], and could even be associated with NPS [19 –21]. These asymmetric changes are not only thought to result in functional imbalances between the left and right cerebral hemispheres. Hence, they could cause an imbalance between the opposing functions of each hemisphere, leading to NPS [22, 23]. Asymmetric changes in brain structure have been suggested as diagnostic biomarkers for Alzheimer’s disease (AD) [24], but their association with NPS has not yet been fully explored. In this study, based on neuroimaging analysis using MRI examinations, we investigate the relationship between NPS, predominantly nonspecific symptoms such as agitation, and asymmetric changes in brain structure in AD patients.

METHODS

Study design

We conducted the present study as part of a multicenter research study in Japan: The Behavioral and Psychological Symptoms Integrated Research in Dementia-Retrospective Neuroimaging (J-BIRD-RN). Firstly, we performed a comprehensive review of clinical records for patients diagnosed with AD, dementia with Lewy Bodies, and mild cognitive impairment across three medical facilities, from which we collected data on 530 demographic and imaging data. Cases with comorbid cerebrovascular disorders, traumatic brain injuries, or those with MRI scans compromised by motion artifacts were excluded. For the current study, we further focused on 121 cases of mild AD (Clinical Dementia Rating Scale = 1) diagnosed using National Institute on Aging and Alzheimer’s Association guidelines [25]. We aimed to minimize the impact of disease heterogeneity on brain morphology and to capture alterations that occur in the early stages of the disease. This study was conducted at Tokyo Jikei University Hospital, Kochi Medical School Hospital, and Osaka University Hospital. The ethics committees at each facility approved the investigation by the ethical standards outlined in the Helsinki Declaration.

Assessment of cognitive functions and NPS classification

Cognitive functions were assessed using the Mini-Mental State Examination (MMSE), Wechsler Memory Scale-Revised (WMS-R), and Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-cog). NPS were comprehensively evaluated with the Neuropsychiatric Inventory (NPI), which assesses 12 subtypes of NPS based on caregiver interviews. In order to find out whether non-specific broad NPS can be explained in the context of imbalance, we reclassified the categories of NPS into four types: aggressive, psychotic, affective, and apathetic according to our previous study [26]. The frequency and severity of each subtype were aggregated to form a composite score for each of these four types of NPS.

Evaluation of brain volume and asymmetry

MRI three dimensional-T1 weighted images were collected using 1.5 or 3 Tesla MRI machines across all three facilities. Each brain image underwent preprocessing using the Computational Anatomy Toolbox 12 (CAT12) implemented in the Statistical Parametric Mapping software (SPM12, Wellcome Department of Cognitive Neurology). The volume of gray matter in each brain region was calculated using labeling provided by Neuromorphometrics, Inc, brain atlas at the lobe level: frontal, temporal, parietal, occipital, and limbic. Each volume was also corrected for total intracranial volume individually. In addition, brain asymmetry was assessed using two metrics: the Asymmetry (ratio) and the Asymmetry (index) [27]. $Asymmetry (ratio) = Left volume / Right volume$ $Asymmetry (index) = Left volume : Right volume$

The Asymmetry (ratio) is a measure that indicates relative atrophy in the right hemisphere or preservation in the left by dividing the volume of the left brain by that of the right. A larger ratio suggests right-hemisphere atrophy or left-hemisphere preservation; a smaller ratio indicates the opposite result. The Asymmetry (index) reflects the degree of asymmetry in a non-directional manner. It is a comparative metric that juxtaposes the volume of the left hemisphere against that of the right, without indicating which side may be atrophied or preserved.

Statistical analysis

Statistical analyses were performed using SPSS 28.0 (IBM) and GraphPad Prism 7.0 (GraphPad Software). First, a comprehensive correlation analysis was performed to uncover the correlation between brain parameters (asymmetry and volume) and each NPS composite score. The threshold p-value was set at 0.05, and multiple comparisons were corrected for using Bonferroni correction based on the number of lobes (p < 0.01 indicates p < 0.05 Bonferroni-corrected). Following the significant correlations identified between NPS and brain parameters, multivariate analyses and group comparisons were conducted as a post-hoc analysis. In the multiple linear regression analysis, the NPS was the dependent variable for the identified significant NPS-brain parameter correlation. The corresponding brain parameter was treated as the explanatory variable. Additionally, background factors that demonstrated a correlation with NPS, along with gender, dominant hand, and MRI scanner type (either 1.5T or 3T), were incorporated as covariates. The brain parameters were also compared between groups, distinguished by whether an NPI subscale was included in the NPS composite score. Spearman tests were employed for correlation analyses, and the Mann-Whitney U test was utilized for between-group comparisons.

RESULTS

Demographics and NPS characteristics

Table 1 presents the demographic data, revealing that most participants were right-hand dominant. Regarding the onset of AD, there were 16 cases of early-onset AD (<65 years) and 105 cases of late-onset AD (≥65 years). Figure 1 illustrates the NPI subscale and composite scores for each category of NPS in the AD cohort. Apathy had the highest NPI subscale score (mean±standard deviation: 3.45±3.19), followed by sleep disturbance (2.13±3.48) and delusion (1.69±3.06). Among the composite NPS scores, aggressive symptoms led the list with a score of 6.14±8.61, followed by apathetic symptoms (5.37±4.96), affective symptoms (3.09±4.79), and psychotic symptoms (2.26±4.07). Only the composite score for affective symptoms was significantly correlated with cognitive function tests (as measured by the WMS-R logical memory IIA: r = 0.198, p = 0.031). No other significant correlations were observed with cognitive function tests or background variables such as age or educational history (p > 0.05).

Fig. 1

Distribution of scores for individual NPI subscales and the NPS composite score. Each bar or data point represents the specific score within the studied population. NPI subscales are on the left, and NPS composite scores are on the right. The NPS composite score is the sum of each category of NPI subscales. The aggressive NPS composite score comprises agitation, disinhibition, aberrant motor behavior, and sleep disturbances (red). Psychotic NPS includes delusions and hallucinations (green). Affective NPS encompasses depression, anxiety, and euphoria (blue). Apathic NPS consists of apathy and eating behaviors (brown).

Table 1

Demographic data of 121 mild AD subjects

	Mean [±standard
	deviation or N (%)]
Age (y)	78.4±9.7
Gender (Female)	82 (67.8%)
Right hand dominant	112 (92.6%)
Education (y)	12.2±2.6
Early-onset AD (onset < 65 y)	16 (13.2%)
Duration (y)	1.9±2.6
MMSE	19.6±3.8
ADAS-cog	17.1±5.8
WMS-R logical memory IA	2.0±2.0
WMS-R logical memory IIA	0.23±0.7

MMSE, Mini-Mental State Examination; ADAS-cog, Alzheimer’s Disease Assessment Scale –Cognitive Subscale; WMS-R, Wechsler Memory Scale-Revised; IA, Immediate Recall; IIA, Delayed Recall.

Association of NPS with brain volume and asymmetry

Figures 2 and 3 display heat maps illustrating the correlations between brain volume and asymmetry at the lobe level with the composite NPS scores. Psychotic NPS was positively correlated with the volume of the left parietal lobe (r = 0.180, p = 0.049). They were also significantly correlated with frontal lobe Asymmetry (index) values (r = 0.185, p = 0.042) and Asymmetry (ratio) values (r = 0.199, p = 0.029). However, these correlations were not significant after adjusting for multiple comparisons. Meanwhile, Aggressive NPS showed a significant correlation with Asymmetry (ratio) in both the frontal lobe (r = 0.235, p = 0.009) and the parietal lobe (r = 0.195, p = 0.032). Notably, the correlation of Asymmetry (ratio) in the frontal lobe remained statistically significant even after adjusting for multiple comparisons (p < 0.01). No significant correlations were observed for affective or apathetic symptoms.

Fig. 2

Heatmap showing the correlation between NPS scores and the volume of each brain region. Color intensity indicates the strength of the correlation, with warmer colors representing positive correlations and cooler colors showing negative correlations. L, left; R, right.

Fig. 3

Heat map showing the correlation between composite NPS scores and brain asymmetry. Color intensity indicates the strength of the correlation, with warmer colors representing positive correlations and cooler colors showing negative correlations. Asymmetry Ratio: Calculated as the volume of the left hemisphere divided by the volume of the right hemisphere (Left/Right volume). Asymmetry Index: Represented as a direct comparison between the volumes of the left and right hemispheres (Left volume: Right volume).

Post-hoc analyses on aggressive NPS

A post-hoc analysis was conducted on aggressive NPS, the only subtype that remained significant after adjustments for multiple comparisons. Analyses of background factors indicated that aggressive NPS was not associated with age, education or cognitive impairment as mentioned above; therefore, gender, dominant hand, and MRI scanner type were included as covariates along with frontal lobe Asymmetry (ratio). The forced entry regression analysis revealed that frontal lobe Asymmetry (ratio) significantly predicted aggressive NPS (Coefficient = 61.6598, p = 0.010), accounting for approximately 9.4% of the variance (R-squared=0.094). However, gender, dominant hand, and MRI scanner type did not show statistically significant associations. Furthermore, a comparison between groups based on the presence of aggressive NPS showed that the asymmetry (ratio) in the frontal lobe was significantly higher in the aggressive NPS (+) group compared to the aggressive NPS (-) group, as shown in Table 2. However, no significant differences were observed in the volumes of individual brain regions (data not shown). These findings were consistent with the results from the correlation analysis.

Table 2

Comparison of brain asymmetry ratios in AD patients with and without aggressive NPS

Asymmetry	Aggressive	Aggressive	p
(ratio)	NPS (+)	NPS (-)
Frontal lobe	1.03±0.032	1.01±0.032	0.029^*
Temporal lobe	0.984±0.080	0.973±0.093	0.482
Parietal lobe	1.027±0.058	1.016±0.075	0.409
Occipital lobe	1.01±0.082	1.01±0.076	0.954
Limbic lobe	1.06±0.067	1.07±0.092	0.532

^*p<0.05.

DISCUSSION

The present study comprehensively evaluated the association between NPS and brain volume and asymmetry in early-stage AD. Consequently, Aggressive NPS demonstrated a significant correlation with Asymmetry (ratio) in the frontal lobes, suggesting relative atrophy in the right hemisphere. Post-hoc analysis further corroborated this association, indicating that asymmetrical atrophy in the frontal lobes may be linked to aggressive behaviors in early-stage AD patients.

Based on our findings, it is worth noting that several studies have previously identified a connection between frontal lobe damage and increased aggression [28]. While some research has pinpointed specific regions such as the dorsolateral prefrontal cortex [29], orbitofrontal cortex [30], and inferior frontal gyrus [31] as neurobiological bases for aggression, a comprehensive morphological explanation remains elusive. In the context of AD, reduced blood flow in the frontal lobe has been associated with aggression [32], and increased phosphorylated tau in frontal cortical areas has been linked with agitation [33]. Further supporting our observation of a significant correlation between aggressive NPS and right hemisphere atrophy, research has indicated that the right hemisphere is particularly implicated in neuropsychiatric manifestations, including aggression [34]. The lack of a significant correlation in the Asymmetry (index) also suggests that the asymmetry favoring the right hemisphere could be associated with aggression. This is consistent with multiple studies that have linked organic changes in the right cerebral hemisphere to increased aggression, notably in conditions such as frontotemporal dementia and stroke [35 –37].

Distinctively, our study found no direct correlation between frontal lobe volume and aggression; instead, it highlighted the significance of the left-to-right ratio in the frontal lobes. This aligns with research emphasizing the importance of interhemispheric interactions for emotional control [38] and indicating that interhemispheric imbalance might be linked to aggression [39]. Given that neurodegenerative diseases like AD are characterized by asymmetric atrophic changes [40, 41], our study sensitizes us to the idea that right-dominant pathological changes in the frontal lobes of AD patients may contribute to increased aggression. Supporting our results, the asymmetrical distribution of tau pathology, closely associated with brain atrophy, has been reported [42, 43]. Furthermore, a tau PET study has also reported that an increase in right-dominant accumulation is linked to worsening behavioral disturbance [44]. The present result is not just a result of volume loss but likely stems from an imbalance in left-to-right morphological changes, including functional alterations. The most unique aspect of the present study is that nonspecific symptoms such as aggressive NPS can be explained by neuroimaging studies in terms of left-to-right asymmetry.

The present study did not establish a significant link between non-aggressive NPS such as apathy and brain asymmetry despite existing literature suggesting that other NPSs may be linked to various structural changes [12]. This could be due to the NPS clustering method employed in the study. However, this method aligns with more extensive cohort studies and offers potential utility as a psychiatric screening tool [26]. Therefore, our findings may suggest that frontal lobe asymmetry is relevant for understanding aggressive BPSD and could serve as a valuable biomarker for treatment decisions. Furthermore, there were also correlations between psychotic symptoms and frontal asymmetry, although the results lacked robustness due to the absence of significance after adjusting for multiple comparisons. The link between brain asymmetry and psychosis has been reported not only in AD but also in schizophrenia [23, 45]; further studies with larger sample sizes are warranted in the future.

Our study has several limitations. First, we did not conduct a functional assessment of the brain. Particularly, it has been frequently reported that AD pathology appears in the locus coeruleus from the early stages of the disease, potentially leading to various symptoms such as agitation [46]; therefore, concurrent evaluations regarding physiology and neurotransmitters are necessary [47]. Further validation with biomarkers such as cerebral blood flow SPECT and FDG-PET, which may offer higher contrast in detecting brain function, could be beneficial. This is particularly pertinent considering the potential challenges in visually assessing asymmetrical changes associated with NPS, as illustrated in Supplementary Figure 1. Additionally, we did not also conduct assessments based on AD core biomarkers such as amyloid or tau PET imaging [48]. The absence of an evaluation of AD core biomarkers might also cause contamination of non-AD conditions in the dataset. For example, argyrophilic grain disease, characterized by left-to-right morphological differences [49] and symptoms such as agitation and irritability [50], is also challenging to distinguish from AD dementia [51, 52]. Moreover, the composition of the dataset, featuring an unequal mix of early-onset and late-onset AD, should also be considered. This is because early-onset AD is more prone to an atypical clinical course and NPS compared to late-onset AD [53, 54]. Meanwhile, the association between aggressive NPS and brain asymmetry was significant even in the analysis stratified by age of onset (Supplementary Figure 2). Finally, the absence of asymmetry data in the healthy control group leaves the pathological significance of the observed asymmetry needing clarification.

Despite these limitations, this is the first study to focus on the left-to-right ratio in the brain to investigate the neural basis of NPS in AD using multi-center data. A more thorough understanding of the neural basis of NPS can be expected by paying attention to localized changes in the brain asymmetry. Future studies should ideally employ more extensive datasets, incorporating functional imaging and AD core biomarkers.

AUTHOR CONTRIBUTIONS

Hiroshi Kameyama (Data curation; Formal analysis; Writing – original draft); Kenji Tagai, MD, PhD (Conceptualization; Data curation; Formal analysis; Methodology; Writing – original draft; Writing – review & editing); Emi Takasaki (Data curation; Investigation); Tetsuo Kashibayashi (Data curation); Ryuichi Takahashi (Data curation); Hideki Kanemoto (Data curation); Kazunari Ishii (Data curation); Manabu Ikeda (Supervision); Masatoshi Shigeta (Supervision); Shunichiro Shinagawa (Supervision; Writing – review & editing); Hiroaki Kazui (Funding acquisition; Supervision).

Footnotes

ACKNOWLEDGMENTS

The authors thank all patients and their caregivers for participation in this study, as well as researchers; Eiji Mizuta at Hyogo Prefectural Rehabilitation Hospital; Kenji Yoshiyama, Takashi Suehiro, Yuto Satake and Daiki Taomoto at Osaka University Graduate School of Medicine. ChatGPT, version 4, a language model developed by OpenAI (), was used for language refinement of this manuscript.

FUNDING

This research was supported by AMED under Grant Number JP15km0908001 and JP21dk0207056 to Hiroaki Kazui.

CONFLICT OF INTEREST

The authors have no conflicts of interest to report.

DATA AVAILABILITY

The data supporting this study’s findings are available from the corresponding author on reasonable request.

The supplementary material is available in the electronic version of this article: .

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