The Gesture Imitation in Alzheimer’s Disease Dementia and Amnestic Mild Cognitive Impairment

Abstract

Background: Alzheimer’s disease dementia (ADD) has become an important health problem in the world. Visuospatial deficits are considered to be an early symptom besides memory disorder.

Objectives: The gesture imitation test was devised to detect ADD and amnestic mild cognitive impairment (aMCI).

Methods: A total of 117 patients with ADD, 118 with aMCI, and 95 normal controls were included in this study. All participants were administered our gesture imitation test, the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Clock Drawing Test (CDT), and the Clinical Dementia Rating Scale (CDR).

Results: Patients with ADD performed worse than normal controls on global scores and had a lower success rate on every item (p < 0.001). The area under the curve (AUC) for the global scores when comparing the ADD and control groups was 0.869 (p < 0.001). Item 4 was a better discriminator with a sensitivity of 84.62% and a specificity of 67.37%. The AUC for the global scores decreased to 0.621 when applied to the aMCI and control groups (p = 0.002). After controlling for age and education, the gesture imitation test scores were positively correlated with the MMSE (r = 0.637, p < 0.001), the MoCA (r = 0.572, p < 0.001), and the CDT (r = 0.514, p < 0.001) and were negatively correlated with the CDR scores (r = –0.558, p < 0.001).

Conclusions: The gesture imitation test is an easy, rapid tool for detecting ADD, and is suitable for the patients suspected of mild ADD and aMCI in outpatient clinics.

Keywords

Alzheimer’s disease gesture imitation mild cognitive impairment neuropsychological test

INTRODUCTION

Over the past three decades, aging has accelerated in China in conjunction with an exponential growth in the economy. Alzheimer’s disease dementia (ADD) has become an important health problem with a prevalence of 3.21% among individuals aged 65 years and older [1]. Early diagnosis of ADD is based on a combination of the history obtained from the patient and a knowledgeable informant and an objective cognitive assessment that includes a “bedside” mental status examination or neuropsychological testing [2]. Although memory disorder is the most prominent feature associated with ADD, visuospatial deficits are also considered to be an early symptom [3]. Because the standard neuropsychological tests are complex and time-consuming, we devised a simple and rapid gesture imitation test to assess visuospatial function. The parietal lobe contains visuokinesthetic motor processes that program motor acts. Bilateral parietal hypoperfusion on single photon emission computed tomography (SPECT) is a characteristic feature of ADD [4, 5] and is considered the pathophysiological basis for visuospatial impairment. In addition, decreased ¹⁸ fluorodeoxyglucose (FDG) uptake on positron emission computed tomography (PET) in the temporoparietal cortex has been shown to be a biomarker of downstream neuronal degeneration or injury [2, 6].

Gesture comprehension is based on visual analysis, access to an action input lexicon, and access to action semantics. Gesture production requires access to and activation of action semantics, action output lexicon and motor systems [7, 8]. Gestures can convey transitive (involving the use of objects) or intransitive (communicative) meanings, symbolic or nonsymbolic meanings, or can be meaningless or meaningful. Imitation of symbolic, meaningful gestures can be performed with access to action semantics, whereas imitation of nonsymbolic, meaningless gestures requires more intense visual–spatial analysis [9, 10]. We selected intransitive, nonsymbolic, and meaningless gestures to exclude the involvement of semantics. The transitive tests were also felt to be unsuitable for use in clinics. Both hands were used to avoid the effect of hand dominance. The purpose of the present study was to develop an easy and rapid gesture imitation test to detect ADD and amnestic mild cognitive impairment (aMCI) in memory clinics and to investigate the diagnostic role on ADD and aMCI and the relationship between the test and cognitive dysfunctions.

METHODS

Subjects

Three hundred and thirty subjects were recruited from our memory clinics between 2011 and 2014. All participants underwent routine assessments, including standardized history taking, physical and neurological examinations, necessary laboratory tests, and a CT or MRI scan. Of these patients, 117 (57 men and 60 women, mean age 75.77±8.43 years, range 52 to 88 years) met the consensus criteria of NINCDS-ADRDA (National Institute of Neurological and Communicative Disorders and Stroke - Alzheimer’s Disease and Related Disorders Association) for probable ADD [11]. One hundred and eighteen patients (47 men and 71 women, mean age 73.55±8.25 years, range 51 to 89 years) were diagnosed with aMCI and fulfilled the following criteria: (1) cognitive complaint, preferably corroborated by an informant; (2) objective cognitive impairment, quantified as a performance of more than 1.5 SD below the appropriate mean on an episodic memory test (Auditory Verbal Learning Test); (3) largely normal general cognitive functioning; (4) essentially intact activities of daily living (ADL) and (5) not demented [12]. Ninety-five subjects were considered as healthy controls including 34 men and 61 women with a mean age of 69.32±9.06 years. The inclusion criteria for controls were as follows: (1) almost normal cognitive functions verified by informants; (2) scores of the Mini-Mental State Examination (MMSE) [13] equal to or above 26; (3) intact ADL; (4) a Clinical Dementia Rating Scale (CDR) [14] of 0. Exclusion criteria for the controls were: severe medical illness, neurological disorder, psychiatric disease, hearing or eyesight loss, and obvious abnormalities on cranial CT or MRI. Participants who were prescribed psychiatric drugs were also excluded.

The objectives of the research were explained to participants and their families, and written informed consent was obtained. The research was approved by the Ethics Committee of the China-Japan Friendship Hospital.

Clinical evaluations

The MMSE and Montreal Cognitive Assessment (MoCA) [15] were used for global cognitive screening. The MMSE includes an evaluation of orientation, memory, attention/calculation, language and visuospatial ability. The MoCA assesses visuospatial and executive function, naming, attention, language, abstraction, memory, and orientation. The Clock Drawing Test (CDT) was used for visuospatial function and was scored by the Rouleau system [16]. ADL was also collected and analyzed. CDR assessed the severity of dementia. ADD patients were rated as mild (CDR = 1), moderate (CDR = 2), and severe (CDR = 3) according to the CDR. The CDR of MCI was 0.5. The scores of the sum of the boxes in the CDR (CDR-SOB) were obtained by summing each of the domain box scores, with scores ranging from 0 to 18. Neuropsychological tests were administered and scored according to standard procedures.

The gesture imitation test

The gesture imitation test was administered as described below to all participants. The scorers rated the test during a neurological examination and were blinded to the cognitive test scores. The time required for test administration was approximately 1-2 minutes.

The test included four meaningless gesture imitations. The examiner sat face-to-face with the subject and instructed him/her to watch the examiners hand gesture carefully and then imitate it. The instruction was repeated if necessary. The examiner opened both hands, spread his/her fingers with palms facing the subject, and then used both hands to complete the four gestures. The first gesture (Item 1) was performed with fingers III touching the thumb on flexion of the metacarpophalangeal joints with fingers II, IV and V extended upward (Fig. 1a). The second gesture (Item 2) involved intertwining of the left and right thumb-index circle (Fig. 1b). The third gesture (Item 3) intersected the left thumb and right little finger (Fig. 1c). The fourth gesture (Item 4) was performed with palms facing the body, then crossing both hands with fingers II–V extended upward and the two thumbs crossing each other (Fig. 1d). The examiner maintained the gesture for 10 s. The subject imitated the gesture concurrently with the examiner. If the subject produced the gestures imperfectly, the examiner reminded the subject to make the gesture the same as that of the examiner after 10 s. If the subject erred with any direction, finger or intersection in 10 s, the score was 0; otherwise, 1 point was given. The maximum score for gesture imitation was 4.

Statistical analysis

Statistical analyses were performed using SPSS, version 17.0 (SPSS Inc., USA). Data were expressed as the mean±SD unless otherwise specified. One-way ANOVA was applied for quantitative variables among the controls, aMCI, and ADD groups or mild, moderate, and severe ADD groups, as well as the demographic data, the results of the MMSE or MoCA and the global scores of the gesture imitation test. The Chi-square test was used to compare the differences between the qualitative variables among three groups, including sex ratio, handiness, and the percentage of four gestures imitated perfectly. Receiver operating characteristic (ROC) analysis was calculated to compare the diagnostic performance between the ADD and control groups, or the aMCI and control groups. The sensitivity and specificity of every imitation subset was also assessed. Pearson correlation coefficient (r) was used to evaluate the correlations between gesture imitation and age, education, and neuropsychological test scores. The role of the gesture imitation test was also evaluated with other variables on discriminating between ADD and controls, aMCI and controls, or mild ADD and aMCI by binary logistic regression. All statistical tests were 2 tailed, and p < 0.05 was considered to achieve statistical significance.

The inter-rater reliability of the gesture imitation test was determined by rating 20 randomly selected participants. One examiner tested and scored the participant, and the other examiner scored simultaneously. The Spearman correlation coefficient was calculated to analyze the reliability of the total scores.

RESULTS

The demographic and clinical data of the patients with ADD, aMCI, and the normal controls are summarized in Table 1. The normal controls were younger and better educated than patients with aMCI and ADD (p < 0.001). Patients with aMCI were also younger and had a higher educational level than patients with ADD (p < 0.001). The sex ratio and the percentage of patients who were right-handed were similar among the three groups. All three groups had similar percentages of patients with hypertension, diabetes mellitus, smoking, drinking, and a family history of dementia.

Patients with ADD (15.10±6.37, 10.10±6.02, 4.62±3.56) performed worse than patients with aMCI (25.50±2.76, 19.72±3.36, 8.28±2.10) and normal controls (28.62±1.22, 26.03±1.65, 9.40±1.21) on the MMSE, MoCA, and CDT, whereas patients with aMCI had lower scores on these tests than normal controls (p < 0.001).

The coefficient for the total scores of the gesture imitation test was 0.961 (p < 0.001), which revealed good inter-rater reliability.

The global scores of the gesture imitation test in normal controls (3.58±0.54) were higher than those of patients with ADD (2.04±1.17) and aMCI (3.16±0.82), and patients with aMCI performed better than those with ADD (p < 0.001). The distribution of the scores in different groups was shown in Fig. 2. Patients with ADD (the error rate of Item 1–4:26.5%, 27.4%, 57.3%, 84.6%) performed worse on every gesture imitation test compared with patients with aMCI (7.6%, 1.7%, 16.2%, 56.9%) and normal controls (3.2%, 0%, 6.3%, 32.6%) (p < 0.001), but the differences between patients with aMCI and normal controls were only evident for Item 3 (p = 0.026) and 4 (p < 0.001). The success rate of all imitation tests of patients with severe ADD (37.5%, 31.3%, 6.3%, 0%) was lower than that of patients in the moderate (65.7%, 62.9%, 28.6%, 5.7%) and mild (86.4%, 87.9%, 59.1%, 24.2%) ADD groups (p < 0.001, p < 0.001, p < 0.001, p = 0.009). Patients in the moderate group performed worse than those in the mild group. The global scores of the gesture imitation test in patients with mild ADD were also lower than those of patient with aMCI and normal controls (p < 0.001) after excluding patients with moderate and severe ADD because of their low success rate. The error rate of all imitation tests (13.6%, 12.1%, 40.9%, 75.8%) in patients with mild ADD was higher than that of normal controls (p = 0.013, p < 0.001, p < 0.001, p < 0.001), whereas the difference between patients with mild ADD and aMCI was only found in Item 2, 3, and 4 (p = 0.003, p < 0.001, p = 0.011) (Table 2).

The area under the curve (AUC) for the global scores of the gesture imitation test when comparing the ADD and control groups was 0.869 (CI = 0.821–0.917) (p < 0.001). If two or more items were failed, the sensitivity was 63.25% to diagnose ADD and the specificity was 97.89%. When one item or more was failed, the sensitivity increased to 89.74%, but the specificity decreased to 60%. Among the four gestures of the imitation test, Items 1, 2, and 3 had a high specificity (96.84%, 100%, 93.68%) and low sensitivity (26.50%, 27.35%, 57.26%), respectively. Item 4 was a better discriminator with a sensitivity of 84.62% and a specificity of 67.37%. The AUC for the global scores of the gesture imitation test was 0.803 (CI = 0.731–0.875) (p < 0.001) when comparing the mild ADD and control groups. Item 4 was also a better discriminator with a sensitivity of 75.76% and a specificity of 67.37%.

The AUC for the global scores of the gesture imitation test decreased to 0.621 (CI = 0.545–0.697) when comparing the aMCI and control groups (p = 0.002). The sensitivity for Item 4 decreased (56.90%), and the specificity was unchanged (67.37%). The AUC for the global scores of the gesture imitation test was 0.682 (CI = 0.600–0.764) when comparing the mild ADD and aMCI groups (p < 0.001). The sensitivity for Item 3 and 4 was 40.91% and 75.76%, and the specificity was 83.76% and 43.10% respectively. Binary logistic regression also demonstrated that the gesture imitation test could discriminate effectively ADD from controls (Odd ratio (OR) = 7.629) (p < 0.001), aMCI from controls (OR = 2.510) (p < 0.001), and mild ADD from aMCI (OR = 2.120) (p < 0.001) after other variables were excluded.

The gesture imitation test did not correlate with the cognitive test scores of the MMSE, MoCA, or CDT in normal controls (p > 0.05). In the aMCI group, the gesture imitation test was positively correlated with the MMSE scores (r = 0.188, p = 0.041), the orientation part of the MMSE (r = 0.224, p = 0.015), and the MoCA (r = 0.182, p = 0.049) and was negatively correlated with CDR-SOB (r = –0.235, p = 0.010). After controlling for age and education, the positive correlation disappeared, but the negative correlation between the gesture imitation test and the CDR-SOB remained (r = –0.194, p = 0.042). In patients with ADD, the gesture imitation test scores clearly correlated with the cognitive test scores, namely, they positively correlated with the MMSE (r = 0.637, p < 0.001), MoCA (r = 0.572, p < 0.001), and CDT (r = 0.514, p < 0.001), and negatively correlated with the CDR (r = –0.558, p < 0.001) and the CDR-SOB scores (r = –0.578, p < 0.001). These correlations remained significant after controlling for age and education. Further correlation analyses revealed positive relationships between gesture imitation and orientation (r = 0.455, p < 0.001), memory (r = 0.512, p < 0.001), attention/calculation (r = 0.550, p < 0.001), language (r = 0.511, p < 0.001), and visuospatial parts (r = 0.465, p < 0.001).

DISCUSSION

The present study investigated the capacity of a gesture imitation test to detect ADD or aMCI in our memory clinics. Our findings suggest that this test is potentially a useful tool for discriminating between patients with ADD and healthy controls because the AUC was 0.869. While the specificity was very good, the sensitivity was poor if the cut-off value of the global scores was 2. However, sensitivity significantly increased if a cut-off value of 3 was selected. The test was still effective even if only patients with mild ADD were included because the AUC was 0.803. The gesture imitation test scores were clearly correlated with the CDT and the pentagon part of the MMSE, which reflect impairment in visuospatial function. The gesture imitation test scores also correlated with those of the general neuropsychological tests and the CDR and CDR-SOB, reflecting the severity of dementia in patients with ADD.

Item 4 was the best discriminator among all of the gestures and, as such, served a function similar to the pigeon part of the Yamaguchi Imitation Test [17, 18]. We added the movement of both hands, changing from the palm facing the subject to facing the examiner to make the test more complex. A sensitivity of 86.42% was still achieved, although some normal controls could not successfully perform the gesture. Perspective taking is the cognitive process that occurs when perceiving a visual scene from one’s own perspective and is different from viewing the same scene from another person’s viewpoint. This process requires more intense recruitment of the bilateral parietal area. Body midline crossing refers to gestures in which the hands invade the contralateral space and is more complex than gestures that are limited to the ipsilateral side [17]. Both perspective taking and body midline crossing are thought to form the basis of the discriminating capacity of the Yamaguchi Imitation Test. In our test, both Items 2 and 3 involved body midline crossing. However, the discriminating effects were worse than for Item 4, suggesting that body midline crossing was not a main contributing factor. We added the reversal of hand movements to Item 4, which made the gesture sequential. In the Crutch’s study [19], only a third of patients with mild ADD were impaired using the dominant hand in the meaningful sequential movement task. By contrast, in the meaningless task, three quarters of patients with mild ADD were affected. Indeed, a significantly higher proportion of patients with ADD failed the meaningless sequential movement task than the traditional gesture production tasks. Perhaps Item 4 represents a type of sequential meaningless movement, which may in part contribute to its impact on the improved sensitivity for detecting ADD.

Three other items were also included in our imitation test, although they did not discriminate as well as Item 4. The success rate of those items differed among the various ADD groups. The success rate of item 4 was very low in cases of moderate and severe dementia. The correlation analyses also demonstrated that the global imitation scores were clearly correlated with the general neuropsychological tests and the CDR and CDR-SOB, reflecting the severity of dementia. Therefore, while other items distinguished different degrees of dementia, notably between moderate and severe cases, Item 4 detected early dementia.

The efficacy of the gesture imitation test decreased when applied to patients with aMCI. The sensitivity of Item 4 also decreased (56.90%), similar to the reduction observed with the pigeon movement (57.9%) [17]. MCI, especially amnestic MCI, is believed to represent a transitional state between normal aging and ADD. In aMCI, there is a predominance of memory impairment, while ADD is associated with impairment in many cognitive domains, which may explain the lower efficacy of the gesture imitation test.

It is difficult in differentiating between mild ADD and aMCI during the clinical practice. The gesture imitation test was an effective method because the AUC was 0.682. Item 4 combined with Item 3 could have a better sensitivity and specificity.

Our imitation test is easy, rapid (requiring only 1 min), and suitable for administration in clinics. Unlike the CDT, pencil and paper are not required. While the ideomotor apraxia test developed by Dobigny-Roman et al. [20] is excellent for diagnosing ADD and correlates with MMSE, the test includes 10 gestures and requires 10 minutes to complete. Furthermore, the scoring technique is complex, making it less suitable for use in outpatient clinics. The Yamaguchi Fox-Pigeon Imitation Test [17] or Reverse Fox test [5] are very easy, rapid, useful supporting tools for detecting mild ADD. However, it does not easily distinguish between degrees of dementia and has not been shown to correlate with cognitive tests.

The deficits in praxis function in ADD have been well documented in previous studies [21 –24]. Our gesture imitation test is a test for imitation of meaningless gesture, which is considered a form of praxis and also evaluates visuospatial and visuomotor ability based on copying hand positions [17]. The model of limb praxis suggested by Rothi et al. [25] included both an indirect (lexical) and a direct (non-lexical) route to action production. The revised version of Rothi et al.’s model [26] further described five types of apraxia: (1) deficit of action input lexicon labeled “pantomime agnosia” or difficulty in discriminating and comprehending observed gestures; (2) impairment within the action semantic system called “conceptual apraxia”, manifesting as impaired execution on command coupled with problems in attributing meaning to gestures; (3) deficit of the action output lexicon; (4) deficit of the visuomotor conversion mechanism, referring to isolated impairment of imitation for meaningless gestures; (5) deficit of gestural buffer which produces impairment in all execution tasks. The imitation of meaningful and meaningless gestures is processed in different ways. The meaningful actions access conceptual knowledge (action semantic system) and stored movement representations (engrams), whereas the meaningless gestures function through another route and bypass both action semantics and engrams [27]. The results of early gesture imitation studies in ADD remain controversial. Crutch et al. [19, 28] and Rousseaux et al. [7] recently reported greater impairment in meaningless as opposed to meaningful gestures. The imitation tasks were overall quite dependent on visuospatial processing and were thus best predicted either by the Judgment of Line Orientation or the Visual Reproduction task [29]. Our results also demonstrated the capacity of meaningless imitation to detect ADD, and the correlation with visuospatial tests. Individuals with early ADD who failed the Reverse Fox test had lower rCBF in the bilateral temporoparietal and medial parietal regions (including the precuneus and posterior cingulate cortex) than those who passed it, which supports the relationship between parietal hypoperfusion and meaningless imitation [17].

The present study has some limitations. First, the participants were selected from our memory clinics, not from the community, which may lead to bias. Second, the selected normal controls had cognitive preservation with a CDR of 0, which may not necessarily be representative of health.

In conclusion, the cognitive abnormalities detected by the gesture imitation test correlated closely with general cognitive dysfunctions in ADD, most notably the visuospatial function. Thus, the gesture imitation test is an easy, rapid tool for detecting ADD, and is suitable for the patients suspected of mild ADD and aMCI in outpatient clinics. The test should be performed in a larger population to further determine its usefulness.

Footnotes

ACKNOWLEDGMENTS

The study was supported by the China-Japan Friendship Hospital (2014-4-QN-32).

Authors’ disclosures available online ().

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