Dement Geriatr Cogn Disord 2014;38:1–9 DOI: 10.1159/000355558 Accepted: September 10, 2013 Published online: February 19, 2014
© 2014 S. Karger AG, Basel 1420–8008/14/0382–0001$39.50/0 www.karger.com/dem
Original Research Article
Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease Eric Rinehardt a, b Katie Eichstaedt c John A. Schinka d David A. Loewenstein e, g Michelle Mattingly a Jean Fils a Mike R. Schoenberg a
Ranjan Duara f, g
a
Department of Psychiatry and Behavioral Neurosciences, University of South Florida, Tampa, Fla., b Carolinas Rehabilitation, Carolinas Healthcare System, Charlotte, N.C., c Florida School of Professional Psychology, Argosy University, and d James A. Haley VA Medical Center, Tampa, Fla., e Departments of Psychiatry and Behavioral Sciences and Center on Aging, University of Miami Miller School of Medicine, Miami, Fla., f Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, Fla., and g Department of Neurology, Florida International University, Miami, Fla., USA
Key Words Neuropsychological assessment · Cognitive impairment · Semantic fluency · Phonetic fluency · Mild cognitive impairment · Dementia · Alzheimer’s disease Abstract Background/Aims: Verbal fluency patterns can assist in differential diagnosis during neuropsychological assessment and identify individuals at risk for developing Alzheimer’s disease (AD). While evidence suggests that subjects with AD perform worse on category fluency than letter fluency tasks, the pattern in mild cognitive impairment (MCI) is less well known. Methods: Performance on the Controlled Oral Word Association Test (COWAT) and Animal fluency was compared in control, amnestic MCI, non-amnestic MCI, and AD groups. The sample included 136 participants matched for age, education, and gender. Results: Both MCI groups performed similarly with a category > letter fluency pattern rather than a category < letter fluency pattern typically observed in AD. The pattern in MCI, albeit relatively more impaired than in controls, was more similar to healthy controls who exhibited a category > letter fluency pattern. Conclusion: MCI using a category < letter fluency pattern may not represent AD; however, future research requires longitudinal studies of pattern analysis. © 2014 S. Karger AG, Basel
Eric Rinehardt, PhD Carolinas Rehabilitation 1100 Blythe Blvd Charlotte, NC 28203 (USA) E-Mail eric.rinehardt @ carolinashealthcare.org
2
Dement Geriatr Cogn Disord 2014;38:1–9 DOI: 10.1159/000355558
© 2014 S. Karger AG, Basel www.karger.com/dem
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
Introduction
Patterns of verbal fluency are frequently used during neuropsychological assessments to differentiate frontal lobe from temporal lobe dysfunction. In support of this distinction, imaging studies have shown that category or semantic fluency is largely mediated by the temporal cortex, while letter or phonemic fluency is mediated by the frontal cortex [1, 2]. This paradigm can be clinically useful in neuropsychological assessment when evaluating whether patients have pathology focused in the anterior or frontal regions compared to posterior or temporal regions. There is substantial evidence, for example, that individuals with Alzheimer’s disease (AD) perform worse on category than letter fluency tasks, presumably due to medial temporal pathology, which is a hallmark characteristic of AD [see 3 for a review]. Mild cognitive impairment (MCI) is considered a transitional phase between normal aging and dementia [4, 5–7]. Cross-sectional research suggests that subjects diagnosed with the amnestic subtype of MCI (aMCI), who are at the greatest risk of developing AD, exhibit a similar pattern on verbal fluency measures as subjects with AD [8–11]. In contrast, some studies have found that individuals with aMCI did not follow the traditional letter > category fluency performance associated with AD. Nutter-Upham et al. [12], for example, evaluated verbal fluency performances of individuals with aMCI and compared their results with individuals with cognitive complaints (no impairment) and healthy controls. The aMCI group performed poorest, yet letter and category fluency performances were equally impaired. Brandt and Manning [13] compared verbal fluency performances for words starting with F, A, and S and Animals, Fruits and Vegetables across groups with different subtypes of MCI and healthy controls. Patients with single domain aMCI were the least likely to exhibit a letter > category fluency pattern when comparing word production of F words and Animals. In fact, the aMCI group performed worse on F letter fluency than category fluency. Since word generation for S words and Vegetables resulted in the conventional letter > category fluency pattern for most groups, they concluded that verbal fluency performance is dependent on the specific letter or category comparison. Similarly, Clark et al. [14] indicated that the preclinical AD subjects exhibited an overall letter > category pattern, but their results also varied depending on the stimuli. While individuals in the preclinical AD group had significantly lower Animal fluency than letter fluency (FAS total score), no differences were found between Supermarket fluency and letter fluency. The objectives of this study are to: (1) further evaluate whether differences exist between specific verbal fluency tasks among individuals with MCI and AD, (2) reevaluate Brandt and Manning’s [13] hypothesis that performances on verbal fluency measures are task dependent, and (3) help clarify the conflicting verbal fluency patterns of individuals with aMCI reported in previous works [10–13]. We hypothesized that individuals with MCI will perform more poorly on semantic fluency than letter fluency, which is similar to the pattern conventionally observed in AD. Methods Participants Participants were patients referred to a memory disorders clinic (MDC) and subjects recruited to participate in an Alzheimer’s Disease Research Center (ADRC) located in the southeastern United States. Referrals for clinical evaluation through the MDC were made by community physicians, self-referrals, and through community outreach efforts. Individuals seeking services through the MDC were invited to participate in the research. All participants underwent a comprehensive evaluation that included clinical interviews, laboratory studies, neuroimaging, and neuropsychological evaluation. The ADRC study was a prospective study
3
Dement Geriatr Cogn Disord 2014;38:1–9 DOI: 10.1159/000355558
© 2014 S. Karger AG, Basel www.karger.com/dem
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
of aging and dementia that recruited individuals from the Tampa and Miami metropolitan areas during the period 2005–2008. Individuals participating in the ADRC study completed a comprehensive evaluation similar to that provided by the MDC. These studies were approved by their respective Institutional Review Boards. All participants provided written informed consent. Inclusion criteria were an age of 60 or older, fluency in English, and 9 or more years of education. Exclusion criteria included prior history of or current comorbid neurological disease, psychiatric disorder (e.g., schizophrenia, bipolar disorder, mood disorders such as moderate to severe depression, and/or active psychosis) or other medical conditions that may affect cognitive function (e.g., cerebrovascular disease). Procedures Data was collected via retrospective chart review, utilizing data from a prospective longitudinal study of normal elderly, elderly with MCI or cognitive impairment without dementia, and cases of early-stage AD (Florida Alzheimer’s Disease Research Center; FADRC) as well as clinical data from the University of South Florida Memory Disorder Clinic (USF MDC). Subject recruitment in the FADRC required an MMSE score >19, stable medical status, fluency in English or Spanish, and at least 6 years of formal education. Recruitment of subjects into the USF MDC was based on clinical referral. All individuals must have been older than 18 years of age, had a stable medical status, and been fluent in English or Spanish. Recruitment requirements for education and MMSE scores were not required to receive services from the USF MDC, but all participants enrolled in the current analyses must have met inclusion and exclusion criteria described above which were the same for the FADRC and USF MDC. All participants were evaluated by board certified geriatric psychiatrists, neurologists, neuroradiologists, and neuropsychologists who contributed to the determination of the clinical diagnosis. Participants completed a comprehensive interview with an informant or caregiver by a physician, review of medical and psychiatric history, neuropsychological testing, structural brain imaging (i.e., MRI), laboratory testing, and questionnaire measures of mood and functional ability. Patients in both studies underwent blood draws to rule out encephalopathy/delirium, and participants enrolled in the FADRC underwent blood draws for genotyping. A diagnosis of AD was given to participants who met NINCDS-ADRDA criteria [15]. In addition, all subjects with a diagnosis of AD must have demonstrated a memory score and at least one other score in another cognitive domain (e.g., attention, language, visuospatial construction, or executive functions) at or below 2 SD of age and education based norms. A diagnosis of aMCI required impairment on a subtest of delayed recall at or below 1.5 SD of age and education based norms, which is consistent with commonly accepted criteria for a diagnosis of MCI [6]. Non-amnestic MCI (naMCI) required impairment on a measure in a non-memory cognitive domain as defined by a –1.5 SD cutoff. Participants with no cognitive impairment (i.e., controls) required all neuropsychological measures to be above the –1.5 SD mark of age and education adjusted norms and normal brain imaging. Neuropsychological Measures Each participant was administered a comprehensive neuropsychological evaluation that included measures of attention, processing speed, language, memory, visuospatial construction/visuoperception, and executive functions. Self-report measures of depression, such as the Geriatric Depression Scale (GDS) [16] and Beck Depression Inventory – Second Edition (BDI-II) [17], were also completed to evaluate severity of affective symptoms. Although neuropsychological test batteries differed between the ADRC and MDC datasets, the common measures of interest (i.e., verbal fluency measures) were the same. All participants were evaluated in English. Measures of language of particular interest in these analyses were the Controlled Oral Word Association Test (COWAT) and a semantic verbal fluency test (Animals) according to standardized instructions with a 60-s time limit [see 18 for a description]. Since normative data varied between datasets, raw scores were converted to Z-scores for the letter total (F, A, and S) and Animals using the same normative dataset [19]. Data Analysis Data analyses were calculated using SPSS version 20. Age and education were analyzed with analysis of variance (ANOVA) tests and gender was assessed with a χ2 test. There were no significant difference in verbal fluency scores between study datasets (i.e., MDC and FADRC), and data were pooled for further analyses. Given the potential influence of age, education, and gender [20, 21] on verbal fluency performance, diagnostic groups were matched on these demographic variables. Since our dataset had many more healthy controls than individuals diagnosed with MCI or AD, we first matched AD and MCI cases on age and education and
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Dement Geriatr Cogn Disord 2014;38:1–9 © 2014 S. Karger AG, Basel www.karger.com/dem
DOI: 10.1159/000355558
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
Table 1. Demographics and clinical characteristics of the study groups
Variable
Controls (n = 34)
aMCI (n = 34)
naMCI (n = 34)
AD (n = 34)
MMSE BDI-II/GDS Age Education Gender, m/f
28.88 ± 1.2 N/A/1.68 ± 1.8 75.21 ± 5.3 13.74 ± 1.8 19/15
27.00 ± 2.0 9.33 ± 4.7/2.84 ±2.2 74.65 ± 6.0 13.79 ± 2.2 20/14
27.31± 2.3 6.86 ± 2.8/3.56 ± 2.9 74.24 ± 6.7 13.91 ± 3.2 19/15
22.93 ± 2.8 4.00 ± 3.8/2.42 ± 1.6 74.59 ± 5.9 13.88 ± 2.6 19/15
Data are means ± SD, except where indicated otherwise.
then selected appropriate controls. Following the statistical model of previous studies evaluating verbal fluency patterns [10, 13], we utilized two-factor mixed design repeated measures ANOVAs. In these models, diagnostic category (i.e., controls, aMCI, naMCI, and AD) was the between-subjects factor and fluency (i.e., letter vs. category) was identified as the repeated within-subjects factor. Post hoc analyses were corrected with Bonferroni adjustments with a p value of 0.05). However, there was a significant diagnostic group by fluency task interaction F(3, 132) = 4.10, p < 0.01, ηp2 = 0.09. Post hoc inspection revealed that controls performed better than all other diagnostic groups (p < 0.001). In addition, the naMCI group performed significantly better than the AD group (p < 0.05); however, performances were neither significantly different between MCI groups nor between the aMCI and AD groups (fig. 2). Differences between Z-scores for the letter total (F, A, and S) and Animals were also calculated separately by diagnostic group. In the AD group, letter total Z-scores were significantly higher than Animal Z-scores, F(1, 66) = 7.60, p < 0.01. However, no significant differences were observed between Z-scores for letter total and Animals in the control, aMCI, or naMCI group.
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Dement Geriatr Cogn Disord 2014;38:1–9 © 2014 S. Karger AG, Basel www.karger.com/dem
DOI: 10.1159/000355558
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
25
F
A
S
Animals
Mean verbal fluency score
20
15
10
5
Fig. 1. Data are means of the total words generated. Error bars represent 95% confidence interval.
0
naMCI aMCI Diagnostic category
Controls
AD
50
Mean Z-score
0
–0.50
–1.00
–1.50 FAS total
Fig. 2. Data are Z-scores of the total letters and animals generated. Error bars represent 95% confidence interval.
Animals
–2.00 Controls
aMCI naMCI Diagnostic category
AD
Discussion
Verbal fluency patterns can assist in differential diagnosis during neuropsychological assessment and have the potential to identify subjects at risk for developing a neurodegenerative disorder such as AD. While there is a large body of empirical evidence which suggests that individuals with AD perform significantly worse on category fluency tasks than letter fluency tasks presumably due to the semantic breakdown of temporal and/or mesial temporal
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Dement Geriatr Cogn Disord 2014;38:1–9 DOI: 10.1159/000355558
© 2014 S. Karger AG, Basel www.karger.com/dem
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
structures [3], there are conflicting reports on whether this pattern is also found in subjects with MCI [9, 10, 12, 13]. Some evidence also suggests that verbal fluency patterns are task dependent, in which performances vary with letter or category provided to the participant. For example, Brandt and Manning [13] found that generation of F words was more difficult than Animals, but noted an opposite pattern for S words and Vegetables. Due to the apparent variability in performance, these authors also warned about the limitations of basing verbal fluency patterns solely on one trial. From a clinical perspective, however, it is often assumed that different letter fluency stimuli (F, A, S among other letters) and semantic categories stimuli (e.g., Animals, Fruits, and Vegetables) are similar and can be interchanged [22]. This study aimed to reinvestigate the verbal fluency patterns in controls as well as those with MCI and AD. In our sample of older individuals, we found that generation of F, A, and S words was more difficult than the production of Animal words. Results also indicated that both aMCI and naMCI groups performed very similarly with a category > letter fluency pattern rather than a category < letter fluency pattern which is typically observed in AD. The pattern in MCI, albeit more impaired than controls, was more similar to that of healthy controls who also performed in a category > letter fluency pattern. This indicates that early identification of AD in both aMCI and naMCI groups may not resemble the letter > category pattern observed in AD, which is consistent with recent studies addressing this issue [12, 13]. In contrast to the hypothesis that verbal fluency patterns are task dependent, data from our sample indicated that F, A, and S and Animal comparisons were stable across various conditions. This finding is limited to comparison of letter fluency to one semantic category due to the fact that our study only incorporated Animals as the categorical variable. Limitations of this study include the ability to generalize results based on the operational definition of MCI. This study procedure followed the Petersen MCI criteria [6], in which objective evidence of cognitive impairment within a domain was established when at least one test score in a domain was 1.5 SDs or below the age and education adjusted mean. However, other methods to establish the presence of MCI have been proposed for objective neuropsychological data, with some experts suggesting that using two subtests below 1 SD in a particular cognitive domain may improve the diagnostic accuracy of MCI and affect study outcomes [23, 24]. Further investigations may evaluate verbal fluency patterns in these populations using various psychometric properties to assess potential differences. Ethnicity [see 25 for a comprehensive summit regarding this issue] and bilingualism [26] were not considered as separate variables in these analyses, but certainly have the potential to modulate results. The use of neuropsychological tests to contribute, at least in part, to group assignment is an additional limitation of this study that should be acknowledged. While this can increase the risk of circular reasoning, objective neuropsychological measures can be essential in the diagnosis of MCI and decrease the risk of error such as false-positives or false-negatives in-group assignment. The cross-sectional nature of this study also limits the ability to predict conversion to AD based on MCI verbal fluency patterns. While longitudinal analyses are relatively scarce, they indicate that category fluency and not letter fluency during preclinical AD can predict progression to AD [14, 27, 28–30] or that verbal fluency performance is not predictive of progression to dementia [31]. Given the results of Brandt and Manning [13] and Nutter-Upham et al. [12], one might conclude that this association is not as predictive of AD as previously thought. Future prospective longitudinal studies on the predictive value of verbal fluency patterns are necessary to fully understand the diagnostic contributions of verbal fluency performances.
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Dement Geriatr Cogn Disord 2014;38:1–9 DOI: 10.1159/000355558
© 2014 S. Karger AG, Basel www.karger.com/dem
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
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Lonie JA, Herrmann LL, Tierney KM, Donaghey C, O’Carroll R, Lee A, Ebmeier KP: Lexical and semantic fluency discrepancy scores in aMCI and early Alzheimer’s disease. J Neuropsychol 2009;3:79–92. Murphy KJ, Rich JB, Troyer AK: Verbal fluency patterns in amnestic mild cognitive impairment are characteristic of Alzheimer’s type dementia. J Int Neuropsychol Soc 2006;12:570–574. Adlam AL, Bozeat S, Arnold R, Watson P, Hodges JR: Semantic knowledge in mild cognitive impairment and mild Alzheimer’s disease. Cortex 2006;42:675–684. Nutter-Upham KE, Saykin AJ, Rabin LA, Roth RM, Wishart HA, Pare N, Flashman LA: Verbal fluency performance in amnestic MCI and older adults with cognitive complaints. Arch Clin Neuropsychol 2008;23: 229– 241. Brandt J, Manning KJ: Patterns of word-list generation in mild cognitive impairment and Alzheimer’s disease. Clin Neuropsychol 2009;23:870–879. Clark LJ, Gatz M, Zheng L, Chen YL, McCleary C, Mack WJ: Longitudinal verbal fluency in normal aging, preclinical, and prevalent Alzheimer’s disease. Am J Alzheimers Dis Other Demen 2009;24:461–468. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM: Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34:939–944. Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, Leirer VO: Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res 1982;17:37–49. Beck AT, Steer RA, Brown GK: Beck Depression Inventory. San Antonio, The Psychological Corporation, 1996. Strauss E, Sherman EMS, Spreen O: A Compendium of Neuropsychological Tests: Administration, Norms, and Commentary, ed 3. New York, Oxford University Press, 2006. 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Schinka JA, Loewenstein DA, Raj A, Schoenberg MR, Banko JL, Potter H, Duara R: Defining mild cognitive impairment: impact of varying decision criteria on neuropsychological diagnostic frequencies and correlates. Am J Geriatr Psychiatry 2010;18:684–691. Romero HR, Lageman SK, Kamath VV, Irani F, Sim A, Suarez P, Manly JJ, Attix DK: Challenges in the neuropsychological assessment of ethnic minorities: summit proceedings. Clin Neuropsychol 2009;23:761–779. Luo L, Luk G, Bialystok E: Effect of language proficiency and executive control on verbal fluency performance in bilinguals. Cognition 2010;114:29–41. Saxton J, Lopez OL, Ratcliff G, Dulberg C, Fried LP, Carlson MC, Newman AB, Kuller L: Preclinical Alzheimer disease: neuropsychological test performance 1.5 to 8 years prior to onset. Neurology 2004; 63: 2341– 2347. Tierney MC, Yao C, Kiss A, McDowell I: Neuropsychological tests accurately predict incident Alzheimer disease after 5 and 10 years. Neurology 2005;64:1853–1859.
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Amieva H, Jacqmin-Gadda H, Orgogozo JM, Le Carret N, Helmer C, Letenneur L, Barberger-Gateau P, Fabrigoule C, Dartigues JF: The 9 year cognitive decline before dementia of the Alzheimer type: a prospective populationbased study. Brain 2005;128:1093–1101. Auriacombe S, Lechevallier N, Amieva H, Harston S, Raoux N, Dartigues JF: A longitudinal study of quantitative and qualitative features of category verbal fluency in incident Alzheimer’s disease subjects: results from the PAQUID study. Dement Geriatr Cogn Disord 2006;21:260–266. Loewenstein DA, Acevedo A, Agron J, Duara R: Vulnerability to proactive semantic interference and progression to dementia among older adults with mild cognitive impairment. Dement Geriatr Cogn Disord 2007;24:363– 368.
Copyright: S. Karger AG, Basel 2014. Reproduced with the permission of S. Karger AG, Basel. Further reproduction or distribution (electronic or otherwise) is prohibited without permission from the copyright holder.
© 2014 S. Karger AG, Basel 1420–8008/14/0382–0001$39.50/0 www.karger.com/dem
Original Research Article
Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease Eric Rinehardt a, b Katie Eichstaedt c John A. Schinka d David A. Loewenstein e, g Michelle Mattingly a Jean Fils a Mike R. Schoenberg a
Ranjan Duara f, g
a
Department of Psychiatry and Behavioral Neurosciences, University of South Florida, Tampa, Fla., b Carolinas Rehabilitation, Carolinas Healthcare System, Charlotte, N.C., c Florida School of Professional Psychology, Argosy University, and d James A. Haley VA Medical Center, Tampa, Fla., e Departments of Psychiatry and Behavioral Sciences and Center on Aging, University of Miami Miller School of Medicine, Miami, Fla., f Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, Fla., and g Department of Neurology, Florida International University, Miami, Fla., USA
Key Words Neuropsychological assessment · Cognitive impairment · Semantic fluency · Phonetic fluency · Mild cognitive impairment · Dementia · Alzheimer’s disease Abstract Background/Aims: Verbal fluency patterns can assist in differential diagnosis during neuropsychological assessment and identify individuals at risk for developing Alzheimer’s disease (AD). While evidence suggests that subjects with AD perform worse on category fluency than letter fluency tasks, the pattern in mild cognitive impairment (MCI) is less well known. Methods: Performance on the Controlled Oral Word Association Test (COWAT) and Animal fluency was compared in control, amnestic MCI, non-amnestic MCI, and AD groups. The sample included 136 participants matched for age, education, and gender. Results: Both MCI groups performed similarly with a category > letter fluency pattern rather than a category < letter fluency pattern typically observed in AD. The pattern in MCI, albeit relatively more impaired than in controls, was more similar to healthy controls who exhibited a category > letter fluency pattern. Conclusion: MCI using a category < letter fluency pattern may not represent AD; however, future research requires longitudinal studies of pattern analysis. © 2014 S. Karger AG, Basel
Eric Rinehardt, PhD Carolinas Rehabilitation 1100 Blythe Blvd Charlotte, NC 28203 (USA) E-Mail eric.rinehardt @ carolinashealthcare.org
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Dement Geriatr Cogn Disord 2014;38:1–9 DOI: 10.1159/000355558
© 2014 S. Karger AG, Basel www.karger.com/dem
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
Introduction
Patterns of verbal fluency are frequently used during neuropsychological assessments to differentiate frontal lobe from temporal lobe dysfunction. In support of this distinction, imaging studies have shown that category or semantic fluency is largely mediated by the temporal cortex, while letter or phonemic fluency is mediated by the frontal cortex [1, 2]. This paradigm can be clinically useful in neuropsychological assessment when evaluating whether patients have pathology focused in the anterior or frontal regions compared to posterior or temporal regions. There is substantial evidence, for example, that individuals with Alzheimer’s disease (AD) perform worse on category than letter fluency tasks, presumably due to medial temporal pathology, which is a hallmark characteristic of AD [see 3 for a review]. Mild cognitive impairment (MCI) is considered a transitional phase between normal aging and dementia [4, 5–7]. Cross-sectional research suggests that subjects diagnosed with the amnestic subtype of MCI (aMCI), who are at the greatest risk of developing AD, exhibit a similar pattern on verbal fluency measures as subjects with AD [8–11]. In contrast, some studies have found that individuals with aMCI did not follow the traditional letter > category fluency performance associated with AD. Nutter-Upham et al. [12], for example, evaluated verbal fluency performances of individuals with aMCI and compared their results with individuals with cognitive complaints (no impairment) and healthy controls. The aMCI group performed poorest, yet letter and category fluency performances were equally impaired. Brandt and Manning [13] compared verbal fluency performances for words starting with F, A, and S and Animals, Fruits and Vegetables across groups with different subtypes of MCI and healthy controls. Patients with single domain aMCI were the least likely to exhibit a letter > category fluency pattern when comparing word production of F words and Animals. In fact, the aMCI group performed worse on F letter fluency than category fluency. Since word generation for S words and Vegetables resulted in the conventional letter > category fluency pattern for most groups, they concluded that verbal fluency performance is dependent on the specific letter or category comparison. Similarly, Clark et al. [14] indicated that the preclinical AD subjects exhibited an overall letter > category pattern, but their results also varied depending on the stimuli. While individuals in the preclinical AD group had significantly lower Animal fluency than letter fluency (FAS total score), no differences were found between Supermarket fluency and letter fluency. The objectives of this study are to: (1) further evaluate whether differences exist between specific verbal fluency tasks among individuals with MCI and AD, (2) reevaluate Brandt and Manning’s [13] hypothesis that performances on verbal fluency measures are task dependent, and (3) help clarify the conflicting verbal fluency patterns of individuals with aMCI reported in previous works [10–13]. We hypothesized that individuals with MCI will perform more poorly on semantic fluency than letter fluency, which is similar to the pattern conventionally observed in AD. Methods Participants Participants were patients referred to a memory disorders clinic (MDC) and subjects recruited to participate in an Alzheimer’s Disease Research Center (ADRC) located in the southeastern United States. Referrals for clinical evaluation through the MDC were made by community physicians, self-referrals, and through community outreach efforts. Individuals seeking services through the MDC were invited to participate in the research. All participants underwent a comprehensive evaluation that included clinical interviews, laboratory studies, neuroimaging, and neuropsychological evaluation. The ADRC study was a prospective study
3
Dement Geriatr Cogn Disord 2014;38:1–9 DOI: 10.1159/000355558
© 2014 S. Karger AG, Basel www.karger.com/dem
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
of aging and dementia that recruited individuals from the Tampa and Miami metropolitan areas during the period 2005–2008. Individuals participating in the ADRC study completed a comprehensive evaluation similar to that provided by the MDC. These studies were approved by their respective Institutional Review Boards. All participants provided written informed consent. Inclusion criteria were an age of 60 or older, fluency in English, and 9 or more years of education. Exclusion criteria included prior history of or current comorbid neurological disease, psychiatric disorder (e.g., schizophrenia, bipolar disorder, mood disorders such as moderate to severe depression, and/or active psychosis) or other medical conditions that may affect cognitive function (e.g., cerebrovascular disease). Procedures Data was collected via retrospective chart review, utilizing data from a prospective longitudinal study of normal elderly, elderly with MCI or cognitive impairment without dementia, and cases of early-stage AD (Florida Alzheimer’s Disease Research Center; FADRC) as well as clinical data from the University of South Florida Memory Disorder Clinic (USF MDC). Subject recruitment in the FADRC required an MMSE score >19, stable medical status, fluency in English or Spanish, and at least 6 years of formal education. Recruitment of subjects into the USF MDC was based on clinical referral. All individuals must have been older than 18 years of age, had a stable medical status, and been fluent in English or Spanish. Recruitment requirements for education and MMSE scores were not required to receive services from the USF MDC, but all participants enrolled in the current analyses must have met inclusion and exclusion criteria described above which were the same for the FADRC and USF MDC. All participants were evaluated by board certified geriatric psychiatrists, neurologists, neuroradiologists, and neuropsychologists who contributed to the determination of the clinical diagnosis. Participants completed a comprehensive interview with an informant or caregiver by a physician, review of medical and psychiatric history, neuropsychological testing, structural brain imaging (i.e., MRI), laboratory testing, and questionnaire measures of mood and functional ability. Patients in both studies underwent blood draws to rule out encephalopathy/delirium, and participants enrolled in the FADRC underwent blood draws for genotyping. A diagnosis of AD was given to participants who met NINCDS-ADRDA criteria [15]. In addition, all subjects with a diagnosis of AD must have demonstrated a memory score and at least one other score in another cognitive domain (e.g., attention, language, visuospatial construction, or executive functions) at or below 2 SD of age and education based norms. A diagnosis of aMCI required impairment on a subtest of delayed recall at or below 1.5 SD of age and education based norms, which is consistent with commonly accepted criteria for a diagnosis of MCI [6]. Non-amnestic MCI (naMCI) required impairment on a measure in a non-memory cognitive domain as defined by a –1.5 SD cutoff. Participants with no cognitive impairment (i.e., controls) required all neuropsychological measures to be above the –1.5 SD mark of age and education adjusted norms and normal brain imaging. Neuropsychological Measures Each participant was administered a comprehensive neuropsychological evaluation that included measures of attention, processing speed, language, memory, visuospatial construction/visuoperception, and executive functions. Self-report measures of depression, such as the Geriatric Depression Scale (GDS) [16] and Beck Depression Inventory – Second Edition (BDI-II) [17], were also completed to evaluate severity of affective symptoms. Although neuropsychological test batteries differed between the ADRC and MDC datasets, the common measures of interest (i.e., verbal fluency measures) were the same. All participants were evaluated in English. Measures of language of particular interest in these analyses were the Controlled Oral Word Association Test (COWAT) and a semantic verbal fluency test (Animals) according to standardized instructions with a 60-s time limit [see 18 for a description]. Since normative data varied between datasets, raw scores were converted to Z-scores for the letter total (F, A, and S) and Animals using the same normative dataset [19]. Data Analysis Data analyses were calculated using SPSS version 20. Age and education were analyzed with analysis of variance (ANOVA) tests and gender was assessed with a χ2 test. There were no significant difference in verbal fluency scores between study datasets (i.e., MDC and FADRC), and data were pooled for further analyses. Given the potential influence of age, education, and gender [20, 21] on verbal fluency performance, diagnostic groups were matched on these demographic variables. Since our dataset had many more healthy controls than individuals diagnosed with MCI or AD, we first matched AD and MCI cases on age and education and
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Dement Geriatr Cogn Disord 2014;38:1–9 © 2014 S. Karger AG, Basel www.karger.com/dem
DOI: 10.1159/000355558
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
Table 1. Demographics and clinical characteristics of the study groups
Variable
Controls (n = 34)
aMCI (n = 34)
naMCI (n = 34)
AD (n = 34)
MMSE BDI-II/GDS Age Education Gender, m/f
28.88 ± 1.2 N/A/1.68 ± 1.8 75.21 ± 5.3 13.74 ± 1.8 19/15
27.00 ± 2.0 9.33 ± 4.7/2.84 ±2.2 74.65 ± 6.0 13.79 ± 2.2 20/14
27.31± 2.3 6.86 ± 2.8/3.56 ± 2.9 74.24 ± 6.7 13.91 ± 3.2 19/15
22.93 ± 2.8 4.00 ± 3.8/2.42 ± 1.6 74.59 ± 5.9 13.88 ± 2.6 19/15
Data are means ± SD, except where indicated otherwise.
then selected appropriate controls. Following the statistical model of previous studies evaluating verbal fluency patterns [10, 13], we utilized two-factor mixed design repeated measures ANOVAs. In these models, diagnostic category (i.e., controls, aMCI, naMCI, and AD) was the between-subjects factor and fluency (i.e., letter vs. category) was identified as the repeated within-subjects factor. Post hoc analyses were corrected with Bonferroni adjustments with a p value of 0.05). However, there was a significant diagnostic group by fluency task interaction F(3, 132) = 4.10, p < 0.01, ηp2 = 0.09. Post hoc inspection revealed that controls performed better than all other diagnostic groups (p < 0.001). In addition, the naMCI group performed significantly better than the AD group (p < 0.05); however, performances were neither significantly different between MCI groups nor between the aMCI and AD groups (fig. 2). Differences between Z-scores for the letter total (F, A, and S) and Animals were also calculated separately by diagnostic group. In the AD group, letter total Z-scores were significantly higher than Animal Z-scores, F(1, 66) = 7.60, p < 0.01. However, no significant differences were observed between Z-scores for letter total and Animals in the control, aMCI, or naMCI group.
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Dement Geriatr Cogn Disord 2014;38:1–9 © 2014 S. Karger AG, Basel www.karger.com/dem
DOI: 10.1159/000355558
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
25
F
A
S
Animals
Mean verbal fluency score
20
15
10
5
Fig. 1. Data are means of the total words generated. Error bars represent 95% confidence interval.
0
naMCI aMCI Diagnostic category
Controls
AD
50
Mean Z-score
0
–0.50
–1.00
–1.50 FAS total
Fig. 2. Data are Z-scores of the total letters and animals generated. Error bars represent 95% confidence interval.
Animals
–2.00 Controls
aMCI naMCI Diagnostic category
AD
Discussion
Verbal fluency patterns can assist in differential diagnosis during neuropsychological assessment and have the potential to identify subjects at risk for developing a neurodegenerative disorder such as AD. While there is a large body of empirical evidence which suggests that individuals with AD perform significantly worse on category fluency tasks than letter fluency tasks presumably due to the semantic breakdown of temporal and/or mesial temporal
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Dement Geriatr Cogn Disord 2014;38:1–9 DOI: 10.1159/000355558
© 2014 S. Karger AG, Basel www.karger.com/dem
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
structures [3], there are conflicting reports on whether this pattern is also found in subjects with MCI [9, 10, 12, 13]. Some evidence also suggests that verbal fluency patterns are task dependent, in which performances vary with letter or category provided to the participant. For example, Brandt and Manning [13] found that generation of F words was more difficult than Animals, but noted an opposite pattern for S words and Vegetables. Due to the apparent variability in performance, these authors also warned about the limitations of basing verbal fluency patterns solely on one trial. From a clinical perspective, however, it is often assumed that different letter fluency stimuli (F, A, S among other letters) and semantic categories stimuli (e.g., Animals, Fruits, and Vegetables) are similar and can be interchanged [22]. This study aimed to reinvestigate the verbal fluency patterns in controls as well as those with MCI and AD. In our sample of older individuals, we found that generation of F, A, and S words was more difficult than the production of Animal words. Results also indicated that both aMCI and naMCI groups performed very similarly with a category > letter fluency pattern rather than a category < letter fluency pattern which is typically observed in AD. The pattern in MCI, albeit more impaired than controls, was more similar to that of healthy controls who also performed in a category > letter fluency pattern. This indicates that early identification of AD in both aMCI and naMCI groups may not resemble the letter > category pattern observed in AD, which is consistent with recent studies addressing this issue [12, 13]. In contrast to the hypothesis that verbal fluency patterns are task dependent, data from our sample indicated that F, A, and S and Animal comparisons were stable across various conditions. This finding is limited to comparison of letter fluency to one semantic category due to the fact that our study only incorporated Animals as the categorical variable. Limitations of this study include the ability to generalize results based on the operational definition of MCI. This study procedure followed the Petersen MCI criteria [6], in which objective evidence of cognitive impairment within a domain was established when at least one test score in a domain was 1.5 SDs or below the age and education adjusted mean. However, other methods to establish the presence of MCI have been proposed for objective neuropsychological data, with some experts suggesting that using two subtests below 1 SD in a particular cognitive domain may improve the diagnostic accuracy of MCI and affect study outcomes [23, 24]. Further investigations may evaluate verbal fluency patterns in these populations using various psychometric properties to assess potential differences. Ethnicity [see 25 for a comprehensive summit regarding this issue] and bilingualism [26] were not considered as separate variables in these analyses, but certainly have the potential to modulate results. The use of neuropsychological tests to contribute, at least in part, to group assignment is an additional limitation of this study that should be acknowledged. While this can increase the risk of circular reasoning, objective neuropsychological measures can be essential in the diagnosis of MCI and decrease the risk of error such as false-positives or false-negatives in-group assignment. The cross-sectional nature of this study also limits the ability to predict conversion to AD based on MCI verbal fluency patterns. While longitudinal analyses are relatively scarce, they indicate that category fluency and not letter fluency during preclinical AD can predict progression to AD [14, 27, 28–30] or that verbal fluency performance is not predictive of progression to dementia [31]. Given the results of Brandt and Manning [13] and Nutter-Upham et al. [12], one might conclude that this association is not as predictive of AD as previously thought. Future prospective longitudinal studies on the predictive value of verbal fluency patterns are necessary to fully understand the diagnostic contributions of verbal fluency performances.
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Dement Geriatr Cogn Disord 2014;38:1–9 DOI: 10.1159/000355558
© 2014 S. Karger AG, Basel www.karger.com/dem
Rinehardt et al.: Verbal Fluency Patterns in Mild Cognitive Impairment and Alzheimer’s Disease
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