ARTICLE
Auteur(s) : Caroline
Hommet1,2,3, Karl Mondon2,3, Anne
Petit1, Dominique Chavanne1, Pierre
Lecomte4, Vincent Camus2,3, Thierry
Constans1,2
1Médecine Interne Gériatrique et Université F.
Rabelais, Tours
2CMRR région Centre, CHU de Tours
3Inserm U930, Tours
4Médecine Interne et Université F. Rabelais,
Tours
Diabetes mellitus (DM) is a frequent and complex disease. Its
prevalence in elderly subjects older than 65 years is
estimated at 8.5% in the Paquid study [1]. The type 2 DM
represents more than 90% of DM cases.
While DM consequences on various organs are well known, many of
its cerebral effects are still unrecognized, in term of cognitive
impairment profile and physiopathological mechanisms.
DM is associated with a 1.5-fold increased risk of dementia
[2-10]. Many studies featured the role of DM as a risk factor for
vascular dementia. However, this is not the only complication of
type 2 DM. In fact, elderly subjects with DM are at
higher risk to develop cognitive impairment than those without DM,
but this impairment doesn’t fulfilling criteria for dementia [2,
5]. Nevertheless, the many associated comorbidities (hypertension,
coronary artery diseases, past history of stroke…) are as well
confusion factors. The aim of this study is to review current
knowledge about cognitive consequences of type 2 DM,
especially data concerning cognitive function assessment and
cerebral imaging.
Diabetes and dementia
Aging is associated with the incidence of many diseases such as
Alzheimer’s disease (AD) and related syndromes [11]. In Europe, the
prevalence of “any dementia” over 65 years of age is 6.4%.
Therefore, both DM and dementia are frequent diseases [2].
DM is a well-known vascular risk factor. It can increase not
only the risk of vascular dementia through cerebral vascular
lesions [6, 7, 10, 12-18], but also the risk of AD [4, 5, 7, 8, 15,
18-20].
The relation between DM and AD has been reported in studies
assessing the frequency of DM in patients with AD, but results are
controversial. Some studies did not find an increased frequency of
DM [13, 21, 22], type 2 DM or glucose intolerance [23]
among AD patients. In a recent meta-analysis, Biessels et al.
[5] reviewed population-based studies published since
40 years. After excluding individuals that presented, at study
entry, a cognitive decline without dementia and those with
established dementia diagnosis, they demonstrated an increased risk
of “any dementia” in people with type 2 DM.
Cognitive impairment and cognitive decline, without dementia,
in elderly subjects with type 2 DM
Epidemiological studies
Several epidemiological studies have reported a cognitive
impairment in elderly subjects with DM, which led to the
presumption that DM is a risk factor for long-term cognitive
decline [17, 24-30]. Nevertheless, the analysis of the literature
regarding cognitive impairment in subjects with type 2 DM
reveals methodological difficulties:
- – the first difficulty concerns the definition of the
cognitive impairment and that of the cognitive decline. There are
two types of studies on DM and cognition: transversal and
longitudinal studies. Only longitudinal ones are capable to bring
us helpful data on cognitive decline, with a definition varying
from one study to another;
- – the second difficulty is about the description of the
neuropsychological profile of elderly subjects with
type 2 DM. The analysis of published works features a
variety of neuropsychological tests that are used in the assessment
of global efficiency, memory, attention, speed processing and
mental flexibility (table 1).
Several transversal studies had assessed the relation between DM
and cognitive function, but results are sometimes controversial
(table 2). Elderly subjects with
type 2 DM always have a decline in their performances
when compared with control subjects. Nevertheless, the used tests
are variable from one study to another. The most frequent assessed
domains, beside the global efficiency, are:
- – verbal episodic memory;
- – working memory;
- – attention;
- – mental flexibility;
- – cognitive speed of information processing.
Global efficiency is weaker in subjects with type 2 DM
than in control subjects [31, 32]. Cognitive decline in elderly
subjects with DM is often expressed by a negative composite score
per domain [32-34] and persists even after adjustment for vascular
risk factors [31, 33-36]. In general, the mostly described
neuropsychological profile is a sub-cortico-frontal syndrome
characterized by cognitive slowing down, impaired mental
flexibility and planning disorders [31, 33, 34].
The longitudinal cohort studies report more interesting data
(table 3). They assess, over long
periods of time, the relation between DM and cognitive decline [17,
24-30, 37] or the occurrence of mild cognitive impairment (MCI)
[28, 38] or incident dementia [6, 8, 9, 14-17, 39].
Table 1 Main assessed domains.
|
Cognitive domain
|
Test
|
|
Global efficiency
|
|
TICS: Telephonic interview for cognitive status
|
|
MMS
|
|
3MS
|
|
Raven’s progressive matrices
|
|
Memory
|
• Word list learning • Free and delayed recall
|
• Rey 15-item memory test • Word list learning
|
|
Logic memory
|
WMS
|
|
Work memory
|
Memory digit span in order and reverse order
|
|
Rivermead behavioral memory test
|
–
|
|
Speed of information processing
|
Psychomotor efficiency
|
• WAIS: Wechsler adult intelligence scale • Pegboard • TMT A
|
|
Motor velocity
|
• Simple reaction time • Digital finger tapping
|
|
Attention
|
Visual attention
|
Stroop test; parts 1 et 2
|
|
Divided attention
|
Pasat
|
|
Selective attention
|
Stroop test; part 3
|
|
Face recognition test
|
Sustained attention
|
|
Cognitive flexibility
|
|
TMT B
|
|
Verbal fluency
|
|
Cowat
|
|
Language
|
Naming
|
Boston naming test
|
|
Vocabulary level
|
Mill-Hill
|
Table 2 Transversal studies.
|
References
|
Age
|
Definition of diabetes
|
Number of subjects
|
Tests
|
Results in diabetic subjects/controls
|
|
Total
|
With diabetes
|
|
Kumari, 2005
|
44-88 years (mean age 56 years)
|
• Questionnaire • Glycemia measurement: – diabetes – glucose
intolerance
|
Cohort Whitehall II: – men, n = 4020 – women,
n = 1627
|
• Men: 5% • Women: 6% • Glucose intolerance: – 10% of men – 12% of
women
|
• Verbal memory • Inductive reasoning • Mill-Hill test • Formal and
semantic fluency
|
• Women: Mill-Hill • Men: reasoning • Control of other vascular
factors
|
|
Qiu, 2006
|
• ≥ 60 years (mean age 74.5 y) • Exclusion of subjects
with MMS < 10
|
Use of oral antidiabetic drugs or glycemia > 1.26 g/L
|
n = 291
|
40%
|
• MMS • Cubes • Executive functions: TMT, fluency • Memory:
learning, recall • Logic memory • Span • ADL
|
• Memory impairment • Executive functions • Visuospatial functions•
Correction of vascular risk factors
|
|
Manshot, 2007
|
55-80 years
|
General practitioners for at least one year
|
Utrecht
|
n = 122
|
• Attention • Speed processing • Executive functions • Memory •
Reasoning • Visuoconstruction
|
• Setting-up of a composite Z-score • Impairment of all domains
|
|
Van Harten, 2007
|
≥ 60 years
|
• Glycemia • Glycosylated hemoglobin • For at least one year
|
• Communal • Controls: n = 44
|
n = 92
|
• MMS • Fluency • TMT • Stroop • Cowat • Rey 15-item • Rivermead •
Reaction time • Pegboard • Setting-up Z-score per domain
|
• Reduction: – mental speed – executive functions – motor speed •
Memory: unimpaired
|
Table 3 Longitudinal studies.
|
References
|
Age
|
Definition of diabetes
|
Number of subjects
|
Follow-up duration
|
Neuropsychological test
|
Results in subjects with diabetes/controls
|
|
Total number
|
With diabetes
|
|
Hann, 1999
|
> 65 years
|
• History taking • Biology
|
Cardiovascular Health Study USA n = 5888
|
–
|
7 years
|
• 3 MMS • Digit symbol
|
• Greater decline in subjects with diabetes • Digit symbol: decline
> 1,8 points
|
|
Gregg, 2000
|
65-99 years
|
History taking or drug intake
|
Women (n = 9679) Communal study USA
|
n = 682
|
6 years
|
• MMS • TMT B • Digit symbol
|
• 2-fold increased decline risk • Control of other vascular risk
factors
|
|
Knopman, 2001
|
47-70 years
|
History taking or drug intake or glycemia
|
Communal study USA n = 10963
|
n = 1329
|
6 years
|
• Memory • Digit symbol • Verbal fluency
|
• Decline in delayed recall and digit symbol control:
hyperlipidemia, hypertension, stroke, cardiovascular disease,
smoking, intimal thickness
|
|
Fontbonne, 2001
|
59-71 years
|
Glycemic measurement 3 groups: – without diabetes – glucose
intolerance – diabetes
|
France n = 926
|
n = 55 Glucose intolerance: 103
|
4 years
|
• MMS • TMT B • Auditory and verbal learning • Face recognizing
test • Digit symbol • Tapping • Benton retention visual test •
Raven’s progressive matrices test • Pasat
|
• Cognitive decline > 15% (significant) 4/8 in subjects with
diabetes or glucose intolerance • Adjusting factors: sex,
socio-educational level, age
|
|
Arvanitakis, 2004
|
> 55 years
|
History taking or drug intake
|
Communal study n = 824
|
n = 127
|
5.5 years
|
• MMS • Memory learning and recall, recognition • Immediate and
delayed histories recall verbal fluency • Naming • Compound
measures of cognition
|
• 40% exclusive decline of perceptual speed
|
|
Logroscino, 2004
|
70-81 years
|
By the physician
|
Women North Health Study n = 18999
|
n=1394 (7.3%) 67%: oral hypoglycemic drugs
|
• 2 years • 12-years diabetes • Control of vascular
variables
|
• TICS • Memory: immediate and delayed recall • Verbal fluency •
Span in reverse order • Delayed recall and word list learning •
Z-scores
|
Decline in TICS 1.26 [1.03-1.54]
|
|
Luchsinger, 2007
|
≥ 65 years (mean age 75.9)
|
Antidiabetic treatment
|
n = 1772 USA Excluded: dementia and early stage MCI
n = 918
|
n = 918
|
(6.1 ± 3.2)
|
• Language • Episodic, verbal and non verbal memory •
Visuoconstruction
|
• MCI incidence: 334 • 160 (7.9%): amnesic MCI • 174 (52%): non
amnesic MCI • Adjusting variables: age, sex, education, APO E4,
hypertension, dyslipidemia, smoking, cardiovascular disease
|
|
Okereke, 2008
|
• Mean age men: 74.1 • Mean age women: 71.9
|
Questionnaire
|
Men: n = 5907 Women: n = 6326 Women Health
Study
|
Women: n = 553 Men: n = 405
|
• Men: 2 years • Women: until 4 years
|
• TICS • Global score of 5 memory tests • Verbal fluency
|
• TICS • Verbal memory
|
Discussion
The analysis of works assessing the relation between
type 2 DM and cognitive function reveals some
methodological remarks. The definition of populations with DM is
not the same for all studies. The diagnosis DM relies often on the
medical history taking or the intake of antidiabetic medications,
more rarely on glycemia measurement. In cohort studies, the
inclusion of subjects on the only basis of a medical history taking
is certainly a limiting factor especially that DM is underestimated
in elderly population [40]. As well, studies do not specify the
survival rate, whereas in longitudinal studies patients with DM may
have a reduced survival rate. As a result, the effects of DM on
cognition can be underestimated. Furthermore, DM is often
associated with other vascular risk factors, in particular
hypertension, which can also have an impact on cognition [41]. The
control of these risk factors has to be integrated in the studies’
methodology in order to better assess the effect of DM on
cognition.
In longitudinal studies, the cognitive decline is measured by
either assessing the incidence of dementia syndrome or featuring a
decline in cognitive performances without necessarily fulfilling
the criteria of dementia. In fact, the diagnosis of dementia is
sometimes complex especially when cerebral imaging is not always
realized. Vascular dementia includes a variety of disorders
therefore its diagnosis is particularly difficult. Vascular
cognitive impairment (VCI) [42] has generally replaced the term of
vascular dementia, and comprises the whole of cognitive disorders
in relation with a vascular disease such as dysexecutive syndrome
and vascular dementia according to NINCDS-ADRDA criteria [43,
44].
Similarly, the cognitive decline definition varies according to
studies and relies on neuropsychiatric tests that change from one
study to another (table 1). The
choice of these tests is not always based on a well-defined
reasoning. The global efficiency tests assess a few numbers of
cognitive domains, so they are not well appropriated to define a
neuropsychological profile. They are useful only in the detection
of disorders. The memory, cognitive speed and flexibility are the
most often impaired domains and the most frequently assessed ones.
Some authors have defined a composite cognitive score in order to
limit the number of analyzed variables, but this score is limited
by a lack of specificity.
The episodic memory has been assessed by means of several tests
(table 1). However, it could be
interesting to identify episodic memory impairments by means of new
developed tests such as the RL/RI-16 [45], the test derived from
the Grober and Buschke test [46] or the DMS-48 [47], which are
precociously altered in case of temporal lobe pathological process.
A test such as RL/RI-16 will enable the differentiation of
episodic memory impairment related to difficulties in retrieving
information due to a sub-cortico-frontal lesion, from the
hippocampal amnesic syndrome secondary to medial temporal lesion.
Among cognitive functions, language and visuoconstructive functions
have been insufficiently assessed in studies.
The signification of cognitive disorders remains uncertain in
term of daily impact, possible link with anatomical data (cortical
atrophy, white matter hyperintensites) and subsequent risk to
develop dementia syndrome. Some authors searched for a relation
between these disorders and the contestable concept of mild
cognitive impairment [28]. In fact, some cognitive disorders
encountered in patients with type 2 DM may have similar
MCI pattern [28, 38, 48].
Beside the associated vascular risk factors that can affect
cognition, humor disorders were not always considered [31, 41] as
well as the role of DM-related factors (duration, glycemic control
and treatments) was not clearly analyzed.
Disorders of memory, attention and mental flexibility are not
specific enough but they can be supported by the presence of white
matter signal hyperintensity due to sub-cortical vascular lesions.
Nevertheless, the relation between cognitive performances and white
matter hyperintensites is not yet clearly established [32]. While
some authors showed a relation between cognitive performances
(slowing speed processing and memory disorders), and white matter
hyperintensites or cortical atrophy [49], others did not [36].
Therefore, the absence of homogeneity in between studies makes
their comparison complex and hazardous.
Value of cerebral imaging
Cerebral MRI provided indications of pathogenesis of cognitive
decline in DM [50]. Studies, mainly transversal, compared
morphological differences between subjects with type 2 DM
and controls, according to certain markers:
- – cortical atrophy [50-52];
- – white matter hyperintensites [33, 34, 50, 51, 53,
54];
- – more recently hippocampal volumetry [51, 55].
MRI allows the visualization of asymptomatic infarcts and the
quantification of cortical atrophy, which are more pronounced in
subjects with DM [51, 52] as well as white matter hyperintensites,
which is more observed in elderly subjects with DM than in elderly
controls [34, 35, 53, 54]. The quantification of white matter
lesions on MRI is not easy and there is no validated relevant
technique. Moreover, visible lesions of leukoaraiosis on MRI denote
already occurred important alterations. More discrete lesions that
can be visualized by more specific imaging techniques might precede
these ones. Therefore, some recent techniques such as diffusion
tensor imaging (DTI) seem to be promising [56]. DTI is a type of
MRI that measures motion of water molecules that results from the
thermal energy carried by these molecules and gives information
about biological tissues microarchitecture. In cerebrospinal fluid,
the diffusion is random (isotropic diffusion), while in white
matter the diffusion is preferentially in the direction of white
matter fibers (high anisotropy). Reduced white matter fractional
anisotropy (FA) indicates damage in white matter fibers that
connect between them different cortex regions [57]. DTI could be
more sensitive in studying leukoaraiosis clinical manifestations
than do current visual scales. As well, voxel-based morphometry
(VBM) analysis appeared as a powerful instrument to investigate
local tissue volumes, mean diffusibility and fractional anisotropy
of the whole brain. Therefore, for examining relations between
white matter damages density and cognitive disorders, VBM analysis
and DTI seem to be more interesting than signal intensity
visualization in T2-weighted MRI.
Measurement of the hippocampal volume is an alternative approach
to morphological imaging, which is supported by the potential
association between DM and AD. The increasing interest for
hippocampal region has many reasons:
- – crucial role in declarative memory [55];
- – increased density in insulin receptors [58];
- – sensitivity to metabolic modifications.
Hippocampal volume reduction has been reported in elderly
subjects with type 2 DM [51, 54]. This reduction accounts
for the use of specific instruments able to better assess the
amygdala-hippocampal complex functioning (RL/RI-16, DMS-48), which
is the original site of occurrence of AD histological lesions
[59].
The analysis of data collected from different imaging techniques
is complex, in part due to methodological problems that are not yet
completely resolved:
- – accurate atrophy quantification;
- – topography and quantification of white matter signal
hyperintensity;
- – hippocampal volumetry.
Moreover, imaging is absent from the different studies and flair
sequences that are more sensitive to vascular lesions are missing
from the rare works on imaging.
Management modalities
Basing on current literature data, cognitive function assessment
should be included in the follow-up of patients with DM. The first
approach is measuring the global efficacy that can be realized my
means of the MMSE [60]. This test enables the assessment of verbal
memory and the conception of the memory profile, but it is
insufficient to detect a sub-cortico-frontal syndrome [61]. Other
“rapid tests” such as the Frontal assessment battery (FAB) [62],
can detect frontal lobe dysfunction. When screening tests detect an
anomaly in an elderly patient with DM, more detailed
neuropsychological tests will be required in order to assess
memory, executive functions, and attention. The assessment of humor
disorders that are frequent in DM should be realized beforehand.
Cerebral imaging is also important for diagnosis of cognitive
dysfunction in DM.
Cognitive profile follow-up aims to identify subjects at risk of
cognitive decline and/or to detect the occurrence of dementia
syndrome. Screening of cognitive impairments and the follow-up of a
progressive decline are essential approaches in the management,
however their application timing during the course of disease
remains to be determined. No specific preventive measure to prevent
or improve cognitive function of elderly subjects with DM has been
really validated. Nevertheless, glycemic control seems to be a
determinant factor [63]. Only relatively fey studies [64, 65] have
shown that antidiabetic treatment may have a beneficial effect on
cognitive function. Early management of other vascular risk factors
is also determining. However, rigorous glycemic control in elderly
subjects with DM is equivocal, since fall risk increases with rigid
glycemic targets [65].
The early screening of cognitive decline enables the
implementation of orthophonic rehabilitation, and even the using of
more specific future molecules.
Conclusion
Diabetes and cognition are apparently linked together. Elderly
subjects with type 2 DM have a 1.5-to 2-fold increased
risk to develop dementia [4]. Dementia is not the only complication
since cognitive impairment has been reported in patients with
type 2 DM, without necessarily fulfilling the criteria of
dementia. Cognitive domains that are particularly impaired are
memory, attention, speed of processing, and executive functions.
In type 2 DM, the natural history and clinical
significance of cognitive disorders remain hypothetical. Many
factors are probably implicated in the relation between DM and
cognition involving metabolic and vascular modifications related to
hyperglycemia and probable defect in insulin action in cerebral
tissue. Moreover, the interaction with the age evokes particular
brain vulnerability in elderly subjects with type 2 DM.
So, aging like the developing period in childhood, may represent a
crucial period in the life of subjects with DM, during which the
brain is more vulnerable to hyperglycemia effects [3]. Although DM
is associated to the incidence of AD, we wonder whether subtle
changes reported in some cognitive domains are the precursors to
dementia occurrence or the resultant of another process. In another
words, if DM-related cognitive disorders would reveal an
accelerated cognitive decline, or they could indicate a progression
to dementia. Therefore, DM could decrease the detection threshold
of a clinically detectable AD.
The relation between DM and AD raises the question of whether
this correlation is directly related to DM-associated metabolic
disorders favoring histological lesions of AD, or indirectly by
means of vascular lesions or metabolic disorders reducing the
detection threshold of AD. Imaging and hippocampal volumetry recent
data are certainly interesting, but automated measurements of the
hippocampus should be validated before being routinely applied.
Searching for early signs of AD by more recent techniques like
imaging amyloid plaques could be beneficial [66].
The impact of type 2 DM on cognitive function is now
well identified. Beside vascular factors, many other factors can
contribute to cognitive decline as socio-educational level, oral
antidiabetic drugs and genetic factors. However, the effect of
cognitive decline on independency has to be more precisely
assessed.
In elderly subjects with type 2 DM, it is necessary to
integrate a regular assessment of cognitive functions in the
systematic follow-up of the different DM complications. Challenges
are great in this chronic and frequent disease. In fact, cognitive
disturbances could be the result of bad observance to treatment,
insufficient control of vascular risk factors, increased
dependency, and inadequate hospitalizations in elderly subjects
[67].
Further studies, in particular longitudinal studies including
neuropsychological instruments, biological markers [68] and
cerebral imaging [66], are needed for better understanding the
relation between diabetes and cognitive function.
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