Hostname: page-component-89b8bd64d-j4x9h Total loading time: 0 Render date: 2026-05-09T19:53:57.989Z Has data issue: false hasContentIssue false

Language performance as a prognostic factor for developing Alzheimer’s clinical syndrome and mild cognitive impairment: Results from the population-based HELIAD cohort

Published online by Cambridge University Press:  21 October 2022

Vasiliki Folia*
Affiliation:
Lab of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, University Campus, Thessaloniki, Greece
Ioannis Liampas
Affiliation:
Department of Neurology, School of Medicine, University Hospital of Larissa, University of Thessaly, Mezourlo Hill, Larissa, Greece
Vasileios Siokas
Affiliation:
Department of Neurology, School of Medicine, University Hospital of Larissa, University of Thessaly, Mezourlo Hill, Larissa, Greece
Susana Silva
Affiliation:
Center for Psychology, University of Porto, Porto, Portugal
Eva Ntanasi
Affiliation:
Department of Nutrition and Dietetics, Harokopio University, Athens, Greece 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
Mary Yannakoulia
Affiliation:
Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
Paraskevi Sakka
Affiliation:
Athens Alzheimer’s Association, Athens, Greece
Georgios Hadjigeorgiou
Affiliation:
Department of Neurology, School of Medicine, University Hospital of Larissa, University of Thessaly, Mezourlo Hill, Larissa, Greece School of Medicine, University of Cyprus, Engomi, Nicosia, Cyprus
Nikolaos Scarmeas
Affiliation:
1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, The Gertrude H. Sergievsky Center, Department of Neurology, Columbia University, New York, USA
Efthimios Dardiotis
Affiliation:
Department of Neurology, School of Medicine, University Hospital of Larissa, University of Thessaly, Mezourlo Hill, Larissa, Greece
Mary H. Kosmidis
Affiliation:
Lab of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, University Campus, Thessaloniki, Greece
*
Corresponding author: Vasiliki Folia, email: vfolia@psy.auth.gr
Rights & Permissions [Opens in a new window]

Abstract

Objectives:

There is limited research on the prognostic value of language tasks regarding mild cognitive impairment (MCI) and Alzheimer’s clinical syndrome (ACS) development in the cognitively normal (CN) elderly, as well as MCI to ACS conversion.

Methods:

Participants were drawn from the population-based Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) cohort. Language performance was evaluated via verbal fluency [semantic (SVF) and phonemic (PVF)], confrontation naming [Boston Naming Test short form (BNTsf)], verbal comprehension, and repetition tasks. An additional language index was estimated using both verbal fluency tasks: SVF-PVF discrepancy. Cox proportional hazards analyses adjusted for important sociodemographic parameters (age, sex, education, main occupation, and socioeconomic status) and global cognitive status [Mini Mental State Examination score (MMSE)] were performed.

Results:

A total of 959 CN and 118 MCI older (>64 years) individuals had follow-up investigations after a mean of ∼3 years. Regarding the CN group, each standard deviation increase in the composite language score reduced the risk of ACS and MCI by 49% (8–72%) and 32% (8–50%), respectively; better SVF and BNTsf performance were also independently associated with reduced risk of ACS and MCI. On the other hand, using the smaller MCI participant set, no language measurement was related to the risk of MCI to ACS conversion.

Conclusions:

Impaired language performance is associated with elevated risk of ACS and MCI development. Better SVF and BNTsf performance are associated with reduced risk of ACS and MCI in CN individuals, independent of age, sex, education, main occupation, socioeconomic status, and MMSE scores at baseline.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © INS. Published by Cambridge University Press, 2022
Figure 0

Table 1. Baseline characteristics of cognitively normal participants (CN) according to the follow-up diagnosis of Alzheimer’s clinical syndrome (ACS) or not. Those with any other dementia diagnosis at follow-up were excluded. The number of participants with available data per parameter is provided

Figure 1

Table 2. Baseline characteristics of cognitively normal participants (CN) based on the follow-up diagnosis of mild cognitive impairment (MCI) of any type (amnestic or nonamnestic) or not. Those with dementia diagnosis at follow-up were excluded. The number of participants with available data per parameter is provided

Figure 2

Table 3. Baseline characteristics of participants with mild cognitive impairment (MCI) of any type (amnestic or nonamnestic) based on the follow-up diagnosis of Alzheimer’s clinical syndrome (ACS) or not. Those with any other dementia diagnosis at follow-up were excluded. The number of participants with available data per parameter is provided

Figure 3

Table 4. Adjusted cox proportional hazards regressions with follow-up diagnosis of Alzheimer’s clinical syndrome (ACS) and mild cognitive impairment (MCI) of any type (amnestic or nonamnestic) as the dichotomous outcomes. Individuals with normal cognition (CN) at baseline were analyzed

Figure 4

Table 5. Adjusted cox proportional hazards regressions with follow-up diagnosis of Alzheimer’s clinical syndrome (ACS) as the dichotomous outcome. Individuals with mild cognitive impairment (MCI) of any type (amnestic or non-amnestic) at baseline were analyzed

Figure 5

Figure 1. Survival curves for incident Alzheimer’s clinical syndrome (ACS) according to the baseline composite language performance of the participants. Individuals were clustered using mean composite language values and standard deviation (SD) units to form four baseline strata: ≤−1SD unit, >−1SD unit and ≤ mean, > mean and ≤ +1SD unit, >+1SD unit.

Figure 6

Figure 2. Survival curves for incident mild cognitive impairment (MCI) according to the baseline composite language performance of the participants. Individuals were clustered using mean composite language values and standard deviation (SD) units to form four baseline strata: ≤ −1SD unit, >−1SD unit and ≤ mean, > mean and ≤ +1SD unit, >+1SD unit.