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. 2021 Feb 18;16(2):e0247184. doi: 10.1371/journal.pone.0247184

Clinical features of behavioral symptoms in patients with semantic dementia: Does semantic dementia cause autistic traits?

Shizuka Sakuta 1,¤, Mamoru Hashimoto 2,3,*, Manabu Ikeda 3, Asuka Koyama 2, Akihiro Takasaki 1,4, Maki Hotta 1,5, Ryuji Fukuhara 4, Tomohisa Ishikawa 4, Seiji Yuki 4, Yusuke Miyagawa 4, Yosuke Hidaka 1, Keiichiro Kaneda 6, Minoru Takebayashi 2,7
Editor: Kenji Hashimoto8
PMCID: PMC7891790  PMID: 33600474

Abstract

Objective

To investigate the behavioral characteristics of semantic dementia (SD) using an instrument originally developed for patients with autism spectrum disorder.

Methods

The behavioral symptoms of 20 patients with SD and 20 patients with Alzheimer’s disease (AD) in both the preclinical state and the dementia state were evaluated using the Pervasive Developmental Disorders Autism Society Japan Rating Scale (PARS).

Results

The SD group showed high prevalence in four behaviors related to stereotypy and social impairment: eating very few food items, selfishness, difficulty in recognizing others’ feeling and thoughts, and interpreting language literally. Scores on the PARS short version, which is sensitive for diagnosis of autism spectrum disorder, were significantly higher in the dementia state than in the preclinical state in both the SD (11.5 ± 6.0 and 1.7 ± 2.5, respectively; t (19) = 6.7, p < 0.001) and AD (6.9 ± 4.6 and 1.7 ± 2.0, respectively; t (19) = 5.1, p < 0.001) groups. PARS short version scores after dementia onset increased in both the SD and AD groups, although the increase was significantly larger in the SD group (F = 5.6, p = 0.023). Additionally, a significantly higher rate of patients exceeded the cutoff score for autism diagnosis in the dementia state in the SD group (75%) than in the AD group (40%; χ2 = 5.0, p = 0.025). PARS scores in the dementia state were significantly correlated with illness duration (r = 0.46, p = 0.04) and Mini-Mental State Examination scores (r = −0.75, p < 0.001) in the SD group only.

Conclusions

Although SD and autism spectrum disorder are etiologically distinct diseases, patients with semantic dementia behave like those with autism spectrum disorder. Our findings suggest the symptomatic similarity of the two disorders.

Introduction

Semantic dementia (SD) is a subtype of frontotemporal dementia (FTD) characterized by progressive aphasia caused by semantic memory loss and severe focal atrophy in the temporal lobe [1]. Although attention has been focused on verbal disabilities in SD, behavioral symptoms, which are included in the SD consensus criteria as supportive features, are also clinically important [1]. Rosen et al. compared behavioral symptoms of SD, progressive nonfluent aphasia, logopenic progressive aphasia, behavioral variant FTD (bvFTD), and Alzheimer’s disease (AD) using the Neuropsychiatric Inventory (NPI) [2]. Compared with the other two progressive aphasias and AD, SD was associated with substantially more socioemotional behavioral dysfunction; specifically, more disinhibition, aberrant motor behavior, and eating disorders [2]. However, Rosen et al. found no significant differences in neuropsychiatric symptoms between SD and bvFTD, except that apathy and eating behavior were more prevalent in bvFTD than in SD patients [2]. Their findings may not fully represent the behavioral characteristics of SD because NPI is a comprehensive measure of neuropsychiatric symptoms for dementia due to Alzheimer’s disease [3]. Only two studies have evaluated in detail the behavioral symptoms of SD. Snowden et al. compared clinical features of behavioral symptoms in SD and bvFTD using caregiver interviews originally designed to examine behavioral changes in FTD [4]. They found that some behavioral symptoms, including selfishness, more selective/food fads, repetitive themes, and adherence to daily routines, were more frequent in SD than in bvFTD [4]. Bozeat et al. compared behavioral symptoms among SD, bvFTD, and AD using an originally designed questionnaire to confirm the neuropsychiatric symptoms commonly reported in FTD and/or AD [5]. They showed that some behavioral symptoms, such as mental rigidity, loss of sympathy/empathy, and clockwatching, were more frequent in SD than in bvFTD and AD [5]. These studies suggest that SD may exhibit behavioral disorders distinct from those of bvFTD and AD. A recent study demonstrated that the severity of abnormal behaviors was substantially associated with caregiver burden for SD patients [6]. Therefore, it is important to clarify the clinical features of abnormal behaviors in SD.

In the present study, we investigated the behavioral characteristics of patients with SD using the Pervasive Developmental Disorders Autism Society Japan Rating Scale (PARS), which is a standardized, reliable, and valid assessment instrument for autistic traits in autism spectrum disorder (ASD). ASD is a neurodevelopmental disorder characterized by deficits in social communication accompanied by excessively repetitive behaviors, restricted interests, and insistence on sameness [7]. We used an ASD instrument for SD patients for the following reasons. First, there is a symptomatic similarity between SD and ASD. Specifically, social impairments such as selfishness and loss of empathy reported in SD correspond to a core feature of ASD, described as impairment of reciprocal social communication and social interaction [4,5,7]. Additionally, other SD behavioral symptoms, such as high frequency of complex routines, adherence to daily routine, selective food fads, and exaggerated reaction to sensory irritation [4,5,8,9], seem to overlap with other core features and diagnostic criteria of ASD, such as repetitive behaviors, restricted interests, insistence on sameness, and hyperreactivity to sensory input [7]. Second, there is an association between neurodegeneration and myelination. Neural degeneration in FTD starts in the regions of later myelination in neural development and expands, as if to retrace the neural developmental process [10]. Thus, symptoms caused by abnormalities in neural development may present with the neural degeneration of older age. Third, temporal pole abnormalities have been reported in both SD and ASD [1113]. Although SD and ASD are etiologically distinct diseases, assessment instruments originally developed for patients with ASD could be used to increase the understanding of behavioral symptoms in patients with SD.

We aimed to compare the clinical features of behavioral symptoms of patients with SD and those with AD using an autism rating scale. First, we evaluated behavioral symptoms of SD using the PARS to determine whether behavioral symptoms of SD comparable to those of ASD. We then investigated whether a different dementia type (i.e., AD) was also associated with autistic traits. Next, we examined whether patients with SD had exhibited autistic traits before the onset of symptoms and whether autistic trait scores increased with dementia progression.

Materials and methods

Participants

This study was approved by the human ethics review committee of Kumamoto University and Osaka University. Informed written consent was obtained from patients and their primary caregivers in compliance with the institution’s human research standards and in accordance with the Helsinki Declaration.

Participants were selected from outpatients who attended either the dementia clinic of the Department of Neuropsychiatry at Kumamoto University Hospital or the outpatient Department of Neuropsychiatry at Osaka University Hospital between January 2018 and December 2018. Patients with SD were consecutive outpatients who fulfilled the consensus clinical diagnostic criteria developed in an international workshop for SD [1]. Patients with AD were selected from the same cohort according to the consensus criteria for the clinical diagnosis of probable AD and formed the control group [14]. Control patients were matched with SD patients for sex and illness duration. We defined illness duration as the period from the moment which the nearest caregiver was aware of the patient’s cognitive or behavioral abnormality to the first assessment.

All patients received routine laboratory tests, neurological examination, and standard neuropsychological examinations, including the Mini-Mental State Examination (MMSE) [15]. Brain magnetic resonance imaging and single photon emission computed tomography of the brain were performed for all patients. All results were used for diagnoses, which were made by a team of neuropsychiatrists, neuropsychologists, and neuroradiologists. The following patients were excluded from the study: 1) those with serious psychiatric diseases such as schizophrenia, major depression, or substance abuse, and 2) those without a reliable informant.

Assessment of neuropsychiatric symptoms

We conducted a comprehensive assessment of patients’ neuropsychiatric symptoms using the Japanese version of the 12-item NPI [3]. The NPI assesses the following 12 symptoms: delusions, hallucinations, agitation/aggression, depression/dysphoria, anxiety, elation/euphoria, apathy/indifference, disinhibition, irritability/lability, aberrant motor behavior, nighttime behavioral disturbances, and appetite/eating changes. As part of the NPI, caregivers are first asked a screening question to determine whether the symptom is present. If present, symptom frequency is rated from 1 (<once per week) to 4 (at least once per day), and severity from 1 (mild, present but not causing distress) to 3 (severe, very disruptive); each domain has a maximum total score (frequency × severity) of 12.

Assessment of behavioral symptoms

To assess participant behavioral symptoms, we used the PARS, which is a semi-structured, caregiver-based interview. The PARS is a standardized tool used to assess autistic traits and obtain a diagnosis for ASD, and is widely used in Japan [1618]. The PARS is easier to administer than current “gold standard” instruments such as the Autism Diagnostic Interview-Revised (ADI-R) [19] and the Autism Diagnostic Observation Schedule [20]. The validity of the PARS has been demonstrated by its correlation with the ADI-R [16]. There are three versions of the PARS, which target different age groups (preschoolers, primary schoolers, and adolescents/adults). Some items are common to all versions and others are specific to particular age groups. We used the adolescent/adult version in this study. The full adolescent/adult PARS comprises 33 items in 5 domains: reciprocal social interaction skills, communication skills, restricted interest, difficulty, and sensitivity [17]. The evaluator rates each item on a three-point scale (0 = none; 1 = somewhat apparent; 2 = apparent); a higher score indicates stronger ASD traits [1618]. The PARS full version emphasizes the evaluation of difficulty and the need for administrative and medical support for ASD. In this study, we used the 33 items to qualitatively assess participants’ behavioral characteristics. The short adolescent/adult version requires the selection of 12 of the 33 items that are sensitive for diagnosis of ASD and assesses three domains: reciprocal social interaction skills, communication skills, and restricted interest [18]. The PARS short version emphasizes ASD diagnosis, with ASD diagnosis cutoff scores of 7/8 [18]. We used the short version of the PARS to evaluate whether participants demonstrated autistic traits equivalent to adult ASD.

In the current study, we evaluated each participant’s behavioral symptoms in both present state and preclinical state. We defined “preclinical” as the time before the onset of the symptoms. When administering the PARS, caregivers were first asked, “Does this content apply to him/her now?” for each question. To evaluate the preclinical state, caregivers were then asked, “Now, please think back to his/her state well before he/she developed some disability in language (SD patients) or memory (AD patients). Did this content apply to him/her in those days?” In principal, the PARS is administered by a physician or clinical psychologist who specializes in child and adolescent psychiatry. One psychiatrist (SS) experienced in child and adolescent psychiatry interviewed all caregivers.

Statistical analyses

The sociodemographic and clinical characteristics of the SD and AD groups were compared using the two-tailed t-test for continuous data and the χ2 test and Fisher’s exact test for categorical data. We compared the SD and AD groups on NPI total score and the number of patients with each neuropsychiatric symptom. Next, we compared the number of patients showing an increase in PARS score after the onset of the symptoms between the SD and AD groups using the χ2 test and Fisher’s exact test for each PARS item. Additionally, we compared the PARS short version scores between the preclinical state and the present state for the SD and AD groups using the two-tailed t-test, paired two-tailed t-test, and two-way repeated measures analysis of variance. Finally, we calculated Pearson’s correlation coefficients (r) for illness duration, MMSE score, and PARS short version score to examine whether autistic traits increased with disease progression. Statistical analyses were performed using SPSS software (SPSS v.25.0; IBM Japan, Tokyo, Japan). The statistical threshold was set at p < 0.05 for each analysis.

Results

Table 1 shows the participant characteristics. We found no significant differences between the SD and AD groups in terms of age, education, dominant hand, MMSE score, caregivers’ relationship with patients, and caregiver sex.

Table 1. Patient demographic and clinical characteristics.

SD (n = 20) AD (n = 20) t2 p value
Patients
Age, years 68.7 ± 5.6a 70.4 ± 9.6 0.68 0.50
Sex, male/female 10/10 10/10 - -
Education, years 12.9 ± 2.7 12.4 ± 2.2 0.58 0.56
Duration of illness, years 5.9 ± 3.0 5.8 ± 3.3 0.15 0.88
Dominant hand, right/left/bilateral 19/0/1 19/0/1 - -
MMSE score 14.2 ± 10.1 16.4 ± 7.2 0.79 0.43
Dominant atrophy, right/left 6/14 - - -
Caregivers
Relationship to patient, spouse/adult-child/other 15/3/2 15/4/1 0.48 0.79
Sex, male/female 5/15 6/14 0.13 0.72

aValues are expressed as number or mean ± standard deviation.

SD, semantic dementia; AD, Alzheimer’s disease; MMSE, Mini-Mental State Examination.

There was no significant difference in NPI total score between the SD (11.9 ± 13.4) and AD (11.0 ± 10.5) groups (t (38) = 0.24, p = 0.81). We found no significant differences in the prevalence of individual NPI symptoms between the SD and AD groups (Table 2).

Table 2. Prevalence of neuropsychiatric symptoms: Comparison of SD and AD groups.

Each item of NPI SD (n = 20) AD (n = 20) χ2/t p values
Delusions 1 4 2.1 0.34
Hallucinations 0 2 2.1 0.49
Agitation/aggression 3 5 0.6 0.70
Depression/dysphoria 6 3 1.3 0.45
Anxiety 1 6 4.3 0.091
Elation/euphoria 0 0 - -
Apathy/indifference 11 15 1.8 0.19
Disinhibition 7 3 2.1 0.27
Irritability/lability 6 4 0.5 0.72
Aberrant motor behavior 5 3 0.6 0.70
Nighttime behavioral disturbances 3 3 0.0 1.0
Appetite/eating changes 10 4 4.0 0.096

NPI, Neuropsychiatric Inventory; SD, semantic dementia; AD, Alzheimer’s disease.

Table 3 shows the number of patients whose PARS score increased after the onset of the symptoms for each PARS item. The most frequent behavioral symptoms in the SD group were “Only interprets language in a literal sense; cannot understand jokes or irony,” observed in 16 patients (80%), followed by “Has difficulty understanding what is said according to each situation” (75%) and “Cannot recognize/understand others’ feelings and thoughts” (75%). Compared with the AD group, the SD group showed a significantly greater score increase after the onset of the symptoms for the following four PARS items: “Extremely unbalanced diet: eats very few food items,” “Does not care about others and behaves selfishly,” “Cannot recognize/understand others’ feelings and thoughts,” and “Only interprets language in a literal sense; cannot understand jokes or irony,” which could be considered SD-specific behavioral symptoms.

Table 3. Comparison of SD and AD patients with increased PARS scores after dementia onset.

Each item of PARSa SD (n = 20) AD (n = 20) χ2 p values
1. Persistently asks the same questiona (RI) 9 11 0.40 0.75
2. Becomes confused when everyday situations or routines change (RI) 6 3 1.29 0.45
3. Cannot maintain personal independence due to disrupted lifestyle (R) 3 9 4.29 0.082
4. Becomes unstable when recalling unpleasant memories (R) 0 3 3.24 0.23
5. Extremely unbalanced diet; eats very few food items (H) 7 1 5.62 0.044
6. Disturbed by particular sounds (H) 3 3 0 1.0
7. Is either insensitive or oversensitive to pain, heat, etc. (H) 13 8 2.51 0.21
8. Is very scared over nothing (R) 0 0 - -
9. Suddenly cries or becomes upset (R) 0 1 1.03 1.0
10. Shows self-injurious action such as banging head on wall or chewing hands (R) 2 0 2.11 0.49
11. Does not have appropriate friendship for his/her age (I) 13 13 0.00 1.0
12. Does not care about others and behaves selfishly (I) 10 3 5.58 0.04
13. Cannot respond appropriately to others (I) 5 1 3.14 0.18
14. Only speaks to others when making a request (I) 9 4 2.85 0.17
15. Has difficulty understanding what is said according to each situation (C) 15 11 1.76 0.32
16. Tends to use difficult words without understanding their meanings (C) 0 0 - -
17. Cannot figure out who is the talker and who is the listener in conversation with many people (C) 11 8 0.90 0.53
18. Cannot explain/answer with causality (C) 14 15 0.13 1.0
19. Talks in monotonous and unnatural tone (C) 2 0 2.11 0.48
20. Cannot recognize/understand others’ feelings and thoughts (C) 15 7 6.47 0.025
21. Only interprets language in a literal sense; cannot understand jokes or irony (C) 16 5 12.13 0.001
22. Immerses her/himself in specific knowledge acquisition such as name of places or train stations (RI) 3 0 3.24 0.07
23. Does an impression of familiar TV scene alone (RI) 1 0 1.02 1.0
24. Repeats inappropriate behavior tenaciously in spite of others’ disapproval (RI) 4 0 4.44 0.11
25. Cannot settle down without taking first place in any situation (RI) 1 0 1.03 1.0
26. Has tic disorder (R) 1 2 0.36 1.0
27. Is restless and cannot adjust behavior to the occasion (R) 8 3 3.14 0.16
28. Is inattentive and cannot adjust behavior to the occasion (R) 5 1 3.14 0.18
29. His/her actions are often interrupted and he/she cannot transfer to the new action (R) 5 5 0 1.0
30. Behaves as if s/he never feels shame (I) 7 4 1.13 0.48
31. Is easily tricked (I) 7 9 0.42 0.75
32. Interprets others’ statements as persecutory or offensive; paranoid (R) 2 4 0.78 0.66
33. Shows mood swings and recurring depression and agitation (R) 2 5 1.56 0.41

aThe 12 items of the PARS short version are underlined.

PARS, Pervasive Developmental Disorders Autism Society Japan Rating Scale; SD, semantic dementia; AD, Alzheimer’s disease, RI; restricted interests, R; resistance, H; hypersensitivity, I; interpersonal relationship, C; communication.

The PARS short version scores for the two groups in the preclinical and the present states are shown in Fig 1. The PARS short version score was significantly higher for individuals in the present state than in the preclinical state in both the SD (11.5 ± 6.0 and 1.7 ± 2.5, respectively; t (19) = 6.7, p < 0.001) and AD (6.9 ± 4.6 and 1.7 ± 2.0, respectively; t (19) = 5.1, p < 0.001) groups. There were no significant differences in PARS short version scores between the SD and AD groups in the preclinical state. Although the PARS short version score increased after the onset of the symptoms in both the SD and AD groups, the increase was significantly larger in the SD group than in the AD group (F = 5.6, p = 0.023). The rate of patients who exceeded the PARS cutoff score in the present state in the SD group (75%) was significantly higher than that in the AD group (40%; χ2 = 5.0, p = 0.025). Only one patient in each group (5%) exceeded the PARS cutoff score in the preclinical state.

Fig 1. PARS Scores of SD and AD patients in preclinical and present states.

Fig 1

Two-tailed t-test. PARS, Pervasive Developmental Disorders Autism Society Japan Rating Scale; SD, semantic dementia; AD, Alzheimer’s disease.

A scatterplot showing the association of illness duration and MMSE score with PARS short version score in individuals in the present state is shown in Fig 2. PARS score was significantly positively correlated with illness duration (r = 0.46, p = 0.04) [a] and significantly negatively correlated with MMSE score (r = −0.75, p < 0.001) in the SD group [b]. In the AD group, we found no significant correlations between PARS score and either illness duration [c] or MMSE score [d].

Fig 2. Correlation of PARS Scores with illness duration and MMSE score in the present state.

Fig 2

[a]Correlation (Pearson’s r) between PARS score and illness duration in SD group. [b] Correlation between PARS score and MMSE score in SD group. [c]Correlation between PARS score and illness duration in AD group. [d]Correlation between PARS score and MMSE score in AD group. PARS, Pervasive Developmental Disorders Autism Society Japan Rating Scale; MMSE, Mini-Mental State Examination; SD, semantic dementia; AD, Alzheimer’s disease. **p < 0.01, *p < 0.05.

Discussion

In this study, we found no significant difference between the SD and AD group in either NPI total score or the prevalence of each neuropsychiatric symptom in NPI. This negative result may partly be attributable to the small sample size. However, the increase in PARS short version score was significantly larger in the SD group than in the AD group. Furthermore, SD patients showed significant score changes for four PARS items compared with AD patients. These results demonstrate both the usefulness of the PARS and the limitation of the NPI for evaluating SD behavioral symptoms.

The primary aim of this study was to improve understanding of the behavioral disorders of SD patients by using the PARS. In this respect, it was noteworthy that three-quarters of SD patients in the present state exceeded the PARS short version cutoff score; that is, they had autistic trait levels indicative of an ASD diagnosis. Significantly more SD patients than AD patients exceeded the cutoff score, and the PARS score increase in the SD group was larger than that in the AD group. Additionally, autistic traits (as represented by the PARS score) were associated with illness duration and cognitive decline only in the SD group. These results suggest that SD onset leads to ASD-like behaviors.

According to previous studies, the prevalence of ASD in UK adults older than 16 years is 9.8 per 1000 [21], and the prevalence of ASD in US individuals aged 3–17 years is 2.24% [22]. However, the prevalence of ASD in 5-year-old children in Japan is 4.48% [23], which is comparable to our finding that only one (5%) patient exceeded the cutoff score for ASD diagnosis in a preclinical state across both the SD and AD groups. Therefore, it is likely that autistic traits in SD patients do not reflect those of individuals in a preclinical state. To our knowledge, this is the first study to mention the symptomatic similarity between SD and ASD.

We conducted a detailed evaluation of SD behavioral symptoms using the 33 PARS items. Four SD-specific behavioral symptoms were identified (“Extremely unbalanced diet; eats very few food items,” “Does not care about others and behaves selfishly,” “Cannot recognize/understand others’ feelings and thoughts,” and “Only interprets language in a literal sense; cannot understand jokes or irony”). Regarding the eating of very few food items, Snowden et al. reported a prevalence of selective/food fads of 55% in SD patients, which was more than twice that for bvFTD patients [4]. Ikeda et al. reported that the prevalence of wanting to cook or eat exactly the same foods each day was 40% in SD patients, higher than the 26% in bvFTD patients [8]. Additionally, Ikeda et al. showed the prevalence of altered food preference toward sweet foods in SD patients was equivalent to or higher than that in bvFTD patients [8]. These previous reports suggest that stereotyped behavior or changes in food preferences may cause this type of behavior in individuals with SD. Patients with ASD often eat the same food every day because of their insistence on sameness, and eat very few food items because of a hypersensitivity to food taste, smell, texture, or appearance [7]. Although the background factors for this type of eating behavior are not identical, the common feature of stereotyped behavior may generate similar behavior in both SD and ASD patients.

Social impairment (i.e., impairment of reciprocal social communication and social interaction) is a core feature of ASD and attributable to impairments in theory of mind (ToM) in ASD. In this study, SD patients presented social impairments such as selfishness and difficulty in recognizing others’ feelings and thoughts. Regarding selfish behavior, Snowden et al. reported a prevalence of selfishness of 91% in SD patients, which was equivalent to or higher than that in bvFTD patients [4]. Difficulty in recognizing others’ feelings and thoughts presents as a loss of empathy for others in SD. In a study examining the prevalence of changes in personality and behavior in FTD, the prevalence of lack of empathy was slightly higher in SD than in bvFTD patients [5]. Several studies show that SD patients as well as ASD patients experience problems with ToM [24,25]. Some socioemotional behavioral dysfunctions in SD that overlap with those of ASD may be related to common deficits in psychological processes such as ToM. Specific assessment instruments such as the Interpersonal Reactivity Index [26] may provide a better understanding of empathy in patients with SD in future studies.

Regarding literal interpretation of language, Rankin et al. reported that SD patients showed more impairments in simple sarcasm than bvFTD, AD, and progressive supranuclear palsy patients [27]. It is interesting that both ASD and SD patients cannot understand jokes or irony, which requires integration of a wide range of information and an understanding of the whole situation and its implications. Thus, difficulty in understanding jokes and irony is likely a result of weak central coherence, which is generally described as a limited ability in ASD patients to understand context or to see the bigger picture [28]. Like ASD patients, SD patients show under-generalization in cognitive behaviors such as semantic narrowing and an inability to see the whole picture [29]. Lambon et al. hypothesized that SD is characterized by impaired semantic generalization, in which the anterior temporal lobe plays a critical role [29]. Problems with cognitive processes such as seeing the whole picture may underlie the similarities in social behavior between SD and ASD.

Given that SD and ASD are etiologically distinct diseases, it is unsurprising that some symptomatic features were different between patients with SD and those with ASD. For example, no patients with SD showed a score change between the preclinical state and dementia state in the following PARS items: “Becomes unstable when recalling unpleasant memories”, “Is very scared for no obvious reason”, and “Suddenly cries or becomes upset”. These PARS items evaluate the characteristic emotional instability seen in those with ASD. That said, Snowden et al. argued that a loss of basic emotion is a characteristic feature of SD [4], which indicates that people with SD and those with ASD have marked differences in their emotional expression. A recent study reported that older patients with ASD were difficult to distinguish from patients with FTD owing to symptomatic similarity [30]. The different profiles between patients with SD and ASD shown in this study may help to guide the development of strategies to improve FTD diagnosis accuracy.

The neural mechanisms underlying the behavioral symptoms of SD are still unknown. Social and behavioral disturbances observed in bvFTD are mainly explained by frontal lobe atrophy. However, numerous studies have reported that the cortical atrophy in SD is relatively localized to one side of the temporal lobes in the early stage of the disease, and that there is progressive grey and white matter involvement of the frontal and contralateral temporal lobe with disease progression [31,32]. Recently, Collins et al. examined the most prominent and consistent region of atrophy in SD patients using cortical thickness analysis [33] and found that the maximal cortical atrophy was consistently localized in the left temporal pole, whereas the progressive neurodegeneration of SD follows pathways in a large-scale neural network connected to the temporal pole [33]. No studies have directly demonstrated an association between temporal lobe atrophy and SD behavioral symptoms. However, the present finding that PARS short version scores were correlated with MMSE scores and illness duration only in the SD group suggests that neural network failure centered on the anterior temporal lobes may play a critical role in development of ASD-like behavioral disorders in SD.

Several studies have also documented structural and functional abnormalities in the temporal lobe in ASD. For example, compared with patients with typical development, ASD patients show morphological and functional changes in the temporal lobe [1113]. Pereira et al. also reported functional changes in the default mode network between the left temporal pole and various regions in ASD [13], and the presence of thicker cortices in the right temporal pole is associated with greater communication impairment, as measured by the ADI-R [13]. The temporal pole is a key region for various social and emotional functions in typical development, such as identification and facial recognition, expression, mentalizing, and ToM [34]. Regarding the neuroanatomical implications of our study, the symptomatic similarities between SD and ASD likely reflect involvement of a common neural network centered on the anterior temporal lobes. Further study is needed to confirm the association between autistic traits and atrophy or functional decline in the temporal lobe. From the perspective of pathology, SD has been reported to be predominantly associated with DNA-binding protein 43 (TDP-43) [35]. While the background pathology of ASD has not yet been elucidated, Cetin et al. reported that the mean serum TDP-43 levels in children with ASD were lower than those of healthy control children [36]. These findings highlight the possibility that functional abnormalities of TDP-43 may be involved in the development of behavioral symptoms that are common to both SD and ASD. However, we found no difference in autistic traits or ASD prevalence in the preclinical state between the SD and AD groups, which suggests that ASD is not a risk factor for SD. Further studies to elucidate the role of TDP-43 in both neurodegenerative and neurodevelopmental disorders would further our understanding of the neural mechanisms underlying the symptomatic similarities between SD and ASD.

There are some methodological limitations of using an assessment instrument originally developed for ASD patients to assess behavioral symptoms in dementia. First, the cognitive impairments associated with dementia may have increased PARS scores in both the SD and AD groups. For example, in the SD group, the increased scoring on the PARS item, “Has difficulty understanding what is said according to each situation,” may be a result of verbal disability owing to semantic memory loss. In the AD group, more than half the patients scored higher in the present state than in the preclinical state on the PARS item, “Persistently asks the same question.” However, the increased score on this item can mostly be attributed to memory impairment in the AD group. Thus, the presence of cognitive impairments may lead to an overestimation of ASD traits in patients with dementia. Second, we assessed autistic traits in the preclinical state based on the primary caregiver’s memory. Prospective collection of premorbid data is extremely difficult in rare diseases such as SD. Thus, our findings in the preclinical state may have been affected by the reliability of caregiver memory. Third, the sample size was relatively small, which may have caused a type II error.

Conclusions

The behavioral characteristics of SD were examined in detail using an instrument originally developed for ASD. We demonstrated that onset of SD produces similar behaviors to those of ASD. Our findings suggest the symptomatic similarity of SD and ASD.

Acknowledgments

The authors thank all the patients and their families. We also thank the staff of Kumamoto University Hospital and Osaka University Hospital for their assistance. We thank Diane Williams, PhD, from Edanz Group (https://en-author-services.edanz.com/ac), for editing a draft of this manuscript.

Data Availability

All relevant data are within the manuscript.

Funding Statement

This work was supported by JSPS KAKENHI Grant number JP17K10310 for MH. https://www.jsps.go.jp/j-grantsinaid/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Kenji Hashimoto

11 Dec 2020

PONE-D-20-33509

Clinical features of behavioral symptoms in patients with semantic dementia: Does semantic dementia cause autistic traits?

PLOS ONE

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Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: 1. There is a definite difference between SD and AD from a point of neuroimaging such as MRI and SPECT. Additionally, it can be methematicaly scored using VSRAD for hippocampus atrophy. The absence of these data made the manuscript confusing.

2. The rationale for the use of PARS is obscure. I do not think that the answers to the questions #12, 20 and 21 by caregivers were so important to differentiate the two dementia-related symptoms.

3. Although the authors discussed about empathy, there were no data about empathy by the IRI, QCAE, and soon. Also we did not see data about AQ.

4. The data about the correlations between PARS and MMSE is striking. But the data constitute of two groups.

5. How did authors check illness of duration?

6. There are no data about memory.

Reviewer #2: In the present study, the author compared the twenty patients with SD with the twenty patients with AD, and they found that the SD groups showed significantly higher score of autistic traits (measured by PARS) compared to the AD groups. This difference in autistic traits was enhanced when the patients in the SD group started to suffer from dementia, since the two groups were similar in terms of autistic traits prior to the onset of dementia and dementia scale (measured by NPI) at the assessment of PARS. According to the authors, this study was the first assessing SD patients using with the scale for ASD, in spite of that patients with SD have psychopathologies such as perseveration, stereotypy, impairment of ToM or other kind of characteristics, all of which were core pathology in patients with ASD.

This study was unique and the authors successfully applied the methodology of clinical research to a clinical question of certain similarities between SD and ASD in clinical practice. This topic is likely to develop as an important research area and this study may be a pioneering data in this issue. However, the following points need to be discussed and be addressed by the authors.

Point 1: The authors should consider (or hypothesize) the relationship between SD and ASD, and it would be needed to explain them in more elaborated manner particularly in the Introduction and Discussion sections. This is because one cannot come to a conclusion that both disorders have similar etiology only from similar score(s) in an assessment scale. Do the authors consider a common pathology shared by the two disorders (that is, a dimensional perspective among different diagnosis categories), or a continuous pathology between them (e.g., patient with subclinical autistic traits can develop SD)? The authors discuss more these points from the viewpoint of phenomenology and symptomatology.

Point 2: I feel that the authors emphasized too much the commonalities between SD and ASD, although SD is a type of dementia whereas ASD is a neurodevelopmental disorder. It would be better for the authors to discuss equally different profiles between them.

Point 3: Is there any reason that the authors did not describe the ethic committee of Osaka University? (although it seemed that the authors recruited patients from Osaka University)

Point 4: Is the possible score range of PARS 33 items 0-66? What is the cutoff point for this scale?

Point 5: I feel that Table 3 should generally compare patients with the mean and standard deviation of each item of PARS. Why did the authors compare this with numbers of patients exceeding some points?

Point 6: In the Discussion section, the sentence describing MRI (Page 22, Line 321) is necessary to cite the relevant reports.

Point 7: implications (Page 24, Line 345)⇒limitations?

Point 8: In the Discussion, the small number of patients in the study should be included as a limitation of study.

**********

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Reviewer #2: No

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PLoS One. 2021 Feb 18;16(2):e0247184. doi: 10.1371/journal.pone.0247184.r002

Author response to Decision Letter 0


28 Jan 2021

Editor and Reviewers’ Comments

-Editor

- There are no comments.

For Reviewer #1:

Thank you for your attentive and detailed comments. The manuscript has benefited from these insightful suggestions.

1. There is a definite difference between SD and AD from a point of neuroimaging such as MRI and SPECT. Additionally, it can be methematicaly scored using VSRAD for hippocampus atrophy. The absence of these data made the manuscript confusing.

Response: Thank you for this comment. While we agree that analyzing neuroimaging data, such as MRI and SPECT data, could indeed be useful for a differential diagnosis between SD and AD, the main aim of the present study was to clarify the behavioral features of SD rather than to distinguish between the two diseases. Thus, we did not statistically analyze neuroimaging data, and instead used visual inspection in light of our findings of a differential diagnosis. As you have pointed out, it is important to clarify the relationship between behavioral symptoms of SD and cerebral atrophy, so we have mentioned this as a potential topic of future research (page 24, lines 361-362).

2. The rationale for the use of PARS is obscure. I do not think that the answers to the questions #12, 20 and 21 by caregivers were so important to differentiate the two dementia-related symptoms.

Response: Thank you for highlighting this; we agree that the reason for using the PARS in this study might have been unclear. The primary aim of this study was to further our understanding of the behavioral disorders in patients with SD using the PARS. One limitation of using conventional assessment scales to assess neuropsychiatric symptoms of dementia, such as the NPI, is that they do not always adequately evaluate abnormal behavioral problems that are characteristic to SD. We reviewed the symptomatic similarities between SD and ASD reported in the existing literature, and determined that behavioral differences between SD and AD could be assessed using the PARS. Our results demonstrate that the PARS can be used to evaluate SD behavioral symptoms. In addition, the present results could help to better understand the neural mechanisms underlying behavioral symptoms of not only SD, but also ASD.

3. Although the authors discussed about empathy, there were no data about empathy by the IRI, QCAE, and soon. Also we did not see data about AQ.

Response: Thank you for this valuable comment. In this study, we used the PARS as a screening assessment scale, because our aim was to clarify the overall picture of behavioral symptoms in SD. We found that 80% of patients with SD showed a higher score for item number 20, “Cannot recognize/understand others’ feelings and thoughts”, which was indicative of a lack of empathy. However, this item only assesses one aspect of empathy; the IRI and QCAE might be needed to evaluate empathy in patients with SD in more detail in future work. Therefore, we have added the following sentence to the discussion section (page 22, line 309-311):

“Specific assessment instruments such as the Interpersonal Reactivity Index [26] may provide a better understanding of empathy in patients with SD in future studies.”

As you have pointed out, AQ is one of the major assessment instruments with which to measure autistic traits, and we did indeed use the AQ to evaluate patients’ autistic traits. However, as the AQ is self-reported assessment scale, it is considered less reliable when completed by caregivers. Moreover, it was difficult to conduct self-reported AQ for patients with dementia. In fact, 7 patients with SD had an MMSE score that was less than 10. For these reasons, we did not include the AQ results in this study.

4. The data about the correlations between PARS and MMSE is striking. But the data constitute of two groups.

Response: Thank you for this comment. As you have pointed out, we analyzed the correlation between the PARS and MMSE scores separately for the SD and AD groups. In this study, both the SD and AD groups showed a significant increase in the PARS score after the onset of dementia, although this increase was significantly larger in the SD group. This could be explained in two ways. First, the onset of any dementia could increase ASD traits, and second, SD onset could lead to ASD-like behaviors. If the increase in ASD traits results from neurodegeneration, this would be expected to result in a longer illness and a more severe dementia, and a greater increase in the PARS score. Thus, we analyzed the SD and AD groups separately to test the above two hypotheses. We found that the PARS short version scores were correlated with MMSE scores and disease duration in the SD group only. Therefore, we speculated that the ASD traits in patients with SD were a result of neurodegeneration.

5. How did authors check illness of duration?

Response: In this study, we defined disease duration based on the interviews with caregivers. We have added the following text to the methods section to clarify this (page 8, line 123-125):

“We defined illness duration as the period from the moment which the nearest caregiver was aware of the patient’s cognitive or behavioral abnormality to the first assessment.”

6. There are no data about memory.

Response: As you have pointed out, memory is an important background characteristic. However, patients with SD present with a marked language impairment from an early stage of the illness, and so it is difficult to evaluate memory function in patients with SD using common memory tests. Therefore, we did not perform a detailed memory test. However, given that the results of some PARS items could have been affected by patients’ memory impairments, we have mentioned this as a limitation of the present study (page 25-26, lines 378-382).

For Reviewer#2.

Thank you for your kind and detailed comments. The manuscript has improved with your valuable suggestions.

Point 1: The authors should consider (or hypothesize) the relationship between SD and ASD, and it would be needed to explain them in more elaborated manner particularly in the Introduction and Discussion sections. This is because one cannot come to a conclusion that both disorders have similar etiology only from similar score(s) in an assessment scale. Do the authors consider a common pathology shared by the two disorders (that is, a dimensional perspective among different diagnosis categories), or a continuous pathology between them (e.g., patient with subclinical autistic traits can develop SD)? The authors discuss more these points from the viewpoint of phenomenology and symptomatology.

Response: Thank you for this important suggestion. We completely agree that a more detailed discussion about common pathologies shared by the two disorders was needed. In accordance with this suggestion, we have added the following sentence to the Discussion (page 24-25, lines 362-372):

“From the perspective of pathology, SD has been reported to be predominantly associated with DNA-binding protein 43 (TDP-43) [35]. While the background pathology of ASD has not yet been elucidated, Cetin et al. reported that the mean serum TDP-43 levels in children with ASD were lower than those of healthy control children [36]. These findings highlight the possibility that functional abnormalities of TDP-43 may be involved in the development of behavioral symptoms that are common to both SD and ASD. However, we found no difference in autistic traits or ASD prevalence in the preclinical state between the SD and AD groups, which suggests that ASD is not a risk factor for SD. Further studies to elucidate the role of TDP-43 in both neurodegenerative and neurodevelopmental disorders would further our understanding of the neural mechanisms underlying the symptomatic similarities between SD and ASD.”

Point 2: I feel that the authors emphasized too much the commonalities between SD and ASD, although SD is a type of dementia whereas ASD is a neurodevelopmental disorder. It would be better for the authors to discuss equally different profiles between them.

Response: Thank you for this valuable comment. We completely agree that it is also important to consider the different profiles between patients with SD and those with ASD. Therefore, we have added the following paragraph to the Discussion section (page 22-23, lines 324-335):

“Given that SD and ASD are etiologically distinct diseases, it is unsurprising that some symptomatic features were different between patients with SD and those with ASD. For example, no patients with SD showed a score change between the preclinical state and dementia state in the following PARS items: “Becomes unstable when recalling unpleasant memories”, “Is very scared for no obvious reason”, and “Suddenly cries or becomes upset”. These PARS items evaluate the characteristic emotional instability seen in those with ASD. That said, Snowden et al. argued that a loss of basic emotion is a characteristic feature of SD [4], which indicates that people with SD and those with ASD have marked differences in their emotional expression. A recent study reported that older patients with ASD were difficult to distinguish from patients with FTD owing to symptomatic similarity [30]. The different profiles between patients with SD and ASD shown in this study may help to guide the development of strategies to improve FTD diagnosis accuracy.”

Point 3: Is there any reason that the authors did not describe the ethic committee of Osaka University? (although it seemed that the authors recruited patients from Osaka University)

Response: Thank you for this important point. This was a simple mistake, and the study was approved by the human ethics review committees of both Kumamoto University and Osaka University. We have corrected this, as suggested (page 8, line 113).

Point 4: Is the possible score range of PARS 33 items 0-66? What is the cutoff point for this scale?

Response: Thank you for this valuable comment. As you have pointed out, the PARS full version, which was developed for adolescent and adults, has 33 items and a score range of 0 to 66. The cut-off scores of the PARS full version for a probable ASD diagnosis, as well as an imminent need for administrative and medical support, is 19 out of 20. Considering that the PARS full version includes items that evaluate symptoms that increase caregivers’ burden and which reflect the necessity of medical or administrative intervention, we used the PARS short version, which is more targeted to making an ASD diagnosis.

Point 5: I feel that Table 3 should generally compare patients with the mean and standard deviation of each item of PARS. Why did the authors compare this with numbers of patients exceeding some points?

Response: Thank you for this comment. In this study, we compared the number of patients that showed a score increase between the SD and AD groups, and for two reasons. First, we asked the clinical question of how many patients with SD had ASD-like behaviors. Second, given that each item of the PARS is rated on a 3-point scale (0 = none; 1 = somewhat apparent; 2 = apparent), it was difficult to quantify the change of each item. As you have pointed out, future work could more effectively compare these changes using other assessment scales.

Point 6: In the Discussion section, the sentence describing MRI (Page 22, Line 321) is necessary to cite the relevant reports.

Response: Thank you for this thoughtful comment. In accordance with your suggestion, we have added the two following references to the Discussion section, and have added these to the reference list:

31. Whitwell JL, Josephs KA. Recent advances in the imaging of frontotemporal dementia. Curr Neurol Neurosci Rep. 2012;12: 715-723.

32. Diehl-Schmid J, Onur OA, Kuhn J, Gruppe T, Drzezga A. Imaging frontotemporal lobar degeneration. Curr Neurol Neurosci Rep. 2014;14: 489.

Point 7: implications (Page 24, Line 345)⇒limitations?

Response: In accordance with your suggestion, we have corrected this (page 25, line 373).

Point 8: In the Discussion, the small number of patients in the study should be included as a limitation of study.

Response: In accordance with your suggestion, we have added the following sentence to the limitations section (page 26, lines 386):

“Third, the sample size was relatively small, which may have caused a type II error.”

Decision Letter 1

Kenji Hashimoto

3 Feb 2021

Clinical features of behavioral symptoms in patients with semantic dementia: Does semantic dementia cause autistic traits?

PONE-D-20-33509R1

Dear Dr. Hashimoto,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Kenji Hashimoto, PhD

Section Editor

PLOS ONE

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Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #2: Yes: Nobuhisa Kanahara

Acceptance letter

Kenji Hashimoto

8 Feb 2021

PONE-D-20-33509R1

Clinical features of behavioral symptoms in patients with semantic dementia:Does semantic dementia cause autistic traits?

Dear Dr. Hashimoto:

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on behalf of

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    Data Availability Statement

    All relevant data are within the manuscript.


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