Random change point model for joint modeling of cognitive decline and dementia

We propose a joint model for cognitive decline and risk of dementia to describe the pre-diagnosis phase of dementia. We aim to estimate the time when the cognitive evolution of subjects in the pre-dementia phase becomes distinguishable from normal evolution and to study whether the shape of cognitive decline depends on educational level. The model combines a piecewise polynomial mixed model with a random change point for the evolution of the cognitive test and a log-normal model depending on the random change point for the time to dementia. Parameters are estimated by maximum likelihood using a Newton-Raphson-like algorithm. The expected cognitive evolution given age to dementia is then derived and the marginal distribution of dementia is estimated to check the log-normal assumption.     

A prospective study of cognitive health in the elderly (Oregon Brain Aging Study): effects of family history and apolipoprotein E genotype.

The oldest old are the fastest-growing segment of our population and have the highest prevalence of dementia. Little is known about the genetics of cognitive health in the very old. The aim of this study was to determine whether the genetic risk factors for Alzheimer disease (AD)--namely, apolipoprotein E (APOE) epsilon4 allele and a family history of dementia-continue to be important factors in the cognitive health of the very old. Case-control studies suggest that the effect of genetic factors diminishes at age >75 years. The present prospective study provided evidence to the contrary. We studied 114 Caucasian subjects who were physically healthy and cognitively intact at age 75 years and who were followed, for an average of 4 years, with neurological, psychometric, and neuroimaging examinations. Excellent health at entry did not protect against cognitive decline. Incidence of cognitive decline rose sharply with age. epsilon4 and a family history of dementia (independent of epsilon4) were associated with an earlier age at onset of dementia. Subjects who had epsilon4 or a family history of dementia had a ninefold-higher age-specific risk for dementia than did those who had neither epsilon4 nor a family history of dementia. These observations suggest that the rate of cognitive decline increases with age and that APOE and other familial/genetic factors influence the onset age throughout life.     

Cut-off Scores of a Brief Neuropsychological Battery (NBACE) for Spanish Individual Adults Older than 44 Years Old

The neuropsychological battery used in Fundació ACE (NBACE) is a relatively brief, and easy to administer, test battery that was designed to detect cognitive impairment in the adulthood. The NBACE includes measures of cognitive information processing speed, orientation, attention, verbal learning and memory, language, visuoperception, praxis and executive functions. The aim of the present study was to establish the cut-off scores for impairment for different levels of age and education that could be useful in the cognitive assessment of Spanish subjects who are at risk for cognitive impairment, especially dementia. Data from 1018 patients with a mild dementia syndrome, and 512 cognitively healthy subjects, older than 44 years, from the Memory Clinic of Fundació ACE (Barcelona, Spain) were analyzed. In the whole sample, cut-off scores and sensitivity/specificity values were calculated for six conditions after combining 3 age ranges (44 to 64; 65 to 74; and older than 74 years old) by 2 educational levels (until Elementary school; and more than Elementary school). Moreover, general cut-offs are reported for Catalan and Spanish speakers. The results showed that most of NBACE tests reached good sensitivity and specificity values, except for Ideomotor praxis, Repetition and Verbal Comprehension tests, which had a ceiling effect. Word List Learning from the Wechsler Memory Scale-III and Semantic Verbal Fluency were the most useful tests to discriminate between cognitively healthy and demented subjects. The NBACE has been shown to be a useful tool able to detect cognitive impairment, especially dementia, in older than 44 years Spanish persons.     

Feelings of Hopelessness in Midlife and Cognitive Health in Later Life: A Prospective Population-Based Cohort Study

BackgroundSeveral studies have found depression and depressive feelings to be associated with subsequent dementia. As dementias typically have a long preclinical development phase, it has been difficult to determine whether depression and depressive feelings reflect a concurrent underlying dementia disease, rather than playing a causative role. Our aim was to investigate hopelessness, one dimension of depressive feelings, and evaluate the likelihood of a prodromal versus a causative role of hopelessness feelings in dementia development.MethodsWe invited a random sample of 2000 survivors from a representative population in Eastern Finland, originally investigated in midlife between 1972 and 1987, for re-examination an average of 21 years later. The age of the 1449 persons who accepted the invitation was between 39 and 64 years (mean 50.4 years) in midlife and between 65 and 80 (mean 71.3) at follow-up. To measure feelings of hopelessness in midlife and at follow-up, the participants indicated their level of agreement to two statements about their own possible future. We used logistic regression to investigate the association between the combined scores from these two items and cognitive health at follow-up, while adjusting for several health and life-style variables from midlife and for apolipoprotein E4 (ApoE4) status, depression and hopelessness feelings at follow-up. We compared the associations with late-life cognitive health when feelings of hopelessness were either measured in midlife or at the follow-up. In addition we analyzed the changes in hopelessness scores from midlife to follow-up in participants who were either cognitively healthy or impaired at follow-up.ResultsWe found higher levels of hopelessness in midlife, but not at follow-up, to be associated with cognitive impairment at follow-up; the adjusted odds ratio for each step of the five-level hopelessness scale was 1.30 (95% confidence interval 1.11–1.51) for any cognitive impairment and 1.37 (1.05–1.78) for Alzheimer’s disease. These associations remained significant also after the final adjustments for depressive feelings and for hopelessness at follow-up. The individual changes in hopelessness scores between midlife and follow-up were not systematically related to cognitive health at the follow-up.ConclusionOur results suggest that feelings of hopelessness already in midlife may have long-term implications for cognitive health and increase the risk of Alzheimer’s disease in later life.     

General session: III. Heredity counseling

ABSTRACT

Aging is a major risk factor for both normal and pathological cognitive decline. However, individuals vary in their rate of age-related decline. We developed an easily interpretable composite measure of cognitive age, and related both the level of cognitive age and cognitive slope to sociodemographic, genetic, and disease indicators and examined its prediction of dementia transition. Using a sample of 19,594 participants from the Health and Retirement Study, cognitive age was derived from a set of performance tests administered at each wave. Our findings reveal different conclusions as they relate to levels versus slopes of cognitive age, with more pronounced differences by sex and race/ethnicity for absolute levels of cognitive decline rather than for rates of declines. We also find that both level and slope of cognitive age are inversely related to education, as well as increased for persons with APOE ?4 and/or diabetes. Finally, results show that the slope in cognitive age predicts subsequent dementia among non-demented older adults. Overall, our study suggests that this measure is applicable to cross-sectional and longitudinal studies on cognitive aging, decline, and dementia with the goal of better understanding individual differences in cognitive decline.     

Scintigraphie cérébrale de perfusion et exploration des syndromes démentiels : illustration à l’aide de cinq cas cliniques

The epidemiological evidence suggests that individuals with higher education level have a reduced risk of developing dementia. Because cognitive reserve and its compensation mechanisms may modulate the clinical expression in neurodegenerative pathology, it is important to study subjects who present mild cognitive disturbance with functional imaging. The cerebral SPECT has been used to determine regional uptake of radiotracer into the brain of patients with cognitive impairment. These abnormalities of blood flow were correlated with cognitive impairment. The cerebral SPECT is also useful to investigate preclinical dementia and to predict the evolution of cognitive disturbance. This article, reports some technical and semiological notions and illustrate with five clinical cases the scintigraphic aspect of some dementia syndrome.     

Multi-stage transitional models with random effects and their application to the Einstein aging study

Longitudinal studies of aging often gather repeated observations of cognitive status to describe the development of dementia and to assess the influence of risk factors. Clinical progression to dementia is often conceptualized by a multi-stage model of several transitions that synthesizes time-varying effects. In this study, we assess the influence of risk factors on the transitions among three cognitive status: cognitive stability (normal cognition for age), memory impairment, and clinical dementia. We have developed a shared random effects model that not only links the propensity of transitions and to the probability of informative missingness due to death, but also incorporates heterogeneous transition between subjects. We evaluate four approaches using generalized logit and four using proportional odds models to the first-order Markov transition probabilities as a function of covariates. Random effects were incorporated into these models to account for within-subject correlations. Data from the Einstein Aging Study are used to evaluate the goodness-of-fit of these models using the Akaike information criterion. The best fitting model for each type (generalized logit and proportional odds) is recommended and their results are discussed in more details.     

Age-Correction of Test Scores Reduces the Validity of Mild Cognitive Impairment in Predicting Progression to Dementia

Objectives

A phase of mild cognitive impairment (MCI) precedes most forms of neurodegenerative dementia. Many definitions of MCI recommend the use of test norms to diagnose cognitive impairment. It is, however, unclear whether the use of norms actually improves the detection of individuals at risk of dementia. Therefore, the effects of age- and education-norms on the validity of test scores in predicting progression to dementia were investigated.

Methods

Baseline cognitive test scores (Syndrome Short Test) of dementia-free participants aged ≥65 were used to predict progression to dementia within three years. Participants were comprehensively examined one, two, and three years after baseline. Test scores were calculated with correction for (1) age and education, (2) education only, (3) age only and (4) without correction. Predictive validity was estimated with Cox proportional hazard regressions. Areas under the curve (AUCs) were calculated for the one-, two-, and three-year intervals.

Results

82 (15.3%) of initially 537 participants, developed dementia. Model coefficients, hazard ratios, and AUCs of all scores were significant (p<0.001). Predictive validity was the lowest with age-corrected scores (−2 log likelihood  = 840.90, model fit χ² (1)  = 144.27, HR  = 1.33, AUCs between 0.73 and 0.87) and the highest with education-corrected scores (−2 log likelihood  = 815.80, model fit χ² (1)  = 171.16, HR  = 1.34, AUCs between 0.85 and 0.88).

Conclusion

The predictive validity of test scores is markedly reduced by age-correction. Therefore, definitions of MCI should not recommend the use of age-norms in order to improve the detection of individuals at risk of dementia.     

A Clinical Index to Predict Progression from Mild Cognitive Impairment to Dementia Due to Alzheimer's Disease

Background

Mild cognitive impairment is often a precursor to dementia due to Alzheimer''s disease, but many patients with mild cognitive impairment never develop dementia. New diagnostic criteria may lead to more patients receiving a diagnosis of mild cognitive impairment.

Objective

To develop a prediction index for the 3-year risk of progression from mild cognitive impairment to dementia relying only on information that can be readily obtained in most clinical settings.

Design and Participants

382 participants diagnosed with amnestic mild cognitive impairment enrolled in the Alzheimer''s Disease Neuroimaging Initiative (ADNI), a multi-site, longitudinal, observational study.

Main Predictors Measures

Demographics, comorbid conditions, caregiver report of participant symptoms and function, and participant performance on individual items from basic neuropsychological scales.

Main Outcome Measure

Progression to probable Alzheimer''s disease.

Key Results

Subjects had a mean (SD) age of 75 (7) years and 43% progressed to probable Alzheimer''s disease within 3 years. Important independent predictors of progression included being female, resisting help, becoming upset when separated from caregiver, difficulty shopping alone, forgetting appointments, number of words recalled from a 10-word list, orientation and difficulty drawing a clock. The final point score could range from 0 to 16 (mean [SD]: 4.2 [2.9]). The optimism-corrected Harrell''s c-statistic was 0.71(95% CI: 0.68–0.75). Fourteen percent of subjects with low risk scores (0–2 points, n = 124) converted to probable Alzheimer''s disease over 3 years, compared to 51% of those with moderate risk scores (3–8 points, n = 223) and 91% of those with high risk scores (9–16 points, n = 35).

Conclusions

An index using factors that can be obtained in most clinical settings can predict progression from amnestic mild cognitive impairment to probable Alzheimer''s disease and may help clinicians differentiate between mild cognitive impairment patients at low vs. high risk of progression.     

Multi factorial interactions in the pathogenesis pathway of Alzheimer’s disease: a new risk charts for prevention of dementia

Background

The population longitudinal study named “The Conselice Study” has been the focus of the present investigation. 65 years old or older participants of this population study on brain aging were followed up for 5 years: 937 subjects completed the follow-up. Relationships of 46 genetic, phenotypic, clinical and nutritional factors on incident cognitive decline and incident dementia cases were investigated.

Results

A new statistical approach, called the Auto Contractive Map (AutoCM) was applied to find relationship between variables and a possible hierarchy in the relevance of each variable with incident dementia. This method, based on an artificial adaptive system, was able to define the association strength of each variable with all the others. Moreover, few variables resulted to be aggregation points in the variable connectivity map related to cognitive decline and dementia. Gene variants and cognate phenotypic variables showed differential degrees of relevance to brain aging and dementia. A risk map for age associated cognitive decline and dementia has been constructed and will be presented and discussed.

Conclusion

This map of variables may be use to identify subjects with increased risk of developing cognitive decline end/or dementia and provide pivotal information for early intervention protocols for prevention of dementia.

     

Effect of APOE and a polygenic risk score on incident dementia and cognitive decline in a healthy older population

Few studies have measured the effect of genetic factors on dementia and cognitive decline in healthy older individuals followed prospectively. We studied cumulative incidence of dementia and cognitive decline, stratified by APOE genotypes and polygenic risk score (PRS) tertiles, in 12,978 participants of the ASPirin in Reducing Events in the Elderly (ASPREE) trial. At enrolment, participants had no history of diagnosed dementia, cardiovascular disease, physical disability or cognitive impairment. Dementia (adjudicated trial endpoint) and cognitive decline, defined as a >1.5 standard deviation decline in test score for either global cognition, episodic memory, language/executive function or psychomotor speed, versus baseline scores. Cumulative incidence for all‐cause dementia and cognitive decline was calculated with mortality as a competing event, stratified by APOE genotypes and tertiles of a PRS based on 23 common non‐APOE variants. During a median 4.5 years of follow‐up, 324 participants developed dementia, 503 died. Cumulative incidence of dementia to age 85 years was 7.4% in all participants, 12.6% in APOE ε3/ε4 and 26.6% in ε4/ε4. APOE ε4 heterozygosity/homozygosity was associated with a 2.5/6.3‐fold increased dementia risk and 1.4/1.8‐fold cognitive decline risk, versus ε3/ε3 (p < 0.001 for both). High PRS tertile was associated with a 1.4‐fold dementia risk versus low (CI 1.04–1.76, p = 0.02), but was not associated with cognitive decline (CI 0.96–1.22, p = 0.18). Incidence of dementia among healthy older individuals is low across all genotypes; however, APOE ε4 and high PRS increase relative risk. APOE ε4 is associated with cognitive decline, but PRS is not.     

Type 2 Diabetes with Comorbid Depression in Relation to Cognitive Impairment: an Opportunity for Prevention?

Studies show poor glycemic control is associated with increased risk of dementia among patients with Type 2 diabetes, indicating potential for prevention of dementia with improved glycemia. Emerging evidence suggests that a relationship between short-term glycemic control and cognitive function exists in Type 2 diabetes. However, detailed mechanisms relating diabetic dementia are lacking, as other concurrent conditions, such as depression, may also increase the risk of dementia in Type 2 diabetes. We examined the effects of glycemic control and depression on cognitive function in 88 patients (mean age, 67 ± 4 years) whose A1c (glycosylated hemoglobin) levels, comorbid depression, mini-mental state examination (MMSE) scores were recorded at baseline. Seventeen patients had depression; 14 agreed on anti-depressants. In 6 months, 69 patients reached A1c goal of < 7% (A1c from 9.7 ± 0.8 to 6.4 ± 0.3) while cognition improved significantly (MMSE scored from 20.2 ± 3.5 to 26.2 ± 2.1, p < 0.05). Cognitive increment in controlled diabetes was more consistently observed if their underlying depression was effectively treated (n ? 14). Nineteen patients did not reach A1c goal of < 7% (A1c from 9.6 ± 0.9 to 8.9 ± 0.9) while cognitive increment was minimal (MMSE scored from 20.6 ± 4.9 to 21.3 ± 5.1, p > 0.05). Cognitive decrements were observed among depressed diabetics who refused anti-depressants. Multivariate analysis adjusted for age, education, alcohol use, and other variables yielded similar results. We found controlled glycemia and depression prevent cognitive decline. Further research into mechanisms of cognitive impairment in diabetes may allow us to challenge the concept of dementia in those patients as an irremediable disease.     

Cardiovascular Disease Risk Models and Longitudinal Changes in Cognition: A Systematic Review

Background

Cardiovascular disease and its risk factors have consistently been associated with poor cognitive function and incident dementia. Whether cardiovascular disease prediction models, developed to predict an individual''s risk of future cardiovascular disease or stroke, are also informative for predicting risk of cognitive decline and dementia is not known.

Objective

The objective of this systematic review was to compare cohort studies examining the association between cardiovascular disease risk models and longitudinal changes in cognitive function or risk of incident cognitive impairment or dementia.

Materials and Methods

Medline, PsychINFO, and Embase were searched from inception to March 28, 2014. From 3,413 records initially screened, 21 were included.

Results

The association between numerous different cardiovascular disease risk models and cognitive outcomes has been tested, including Framingham and non-Framingham risk models. Five studies examined dementia as an outcome; fourteen studies examined cognitive decline or incident cognitive impairment as an outcome; and two studies examined both dementia and cognitive changes as outcomes. In all studies, higher cardiovascular disease risk scores were associated with cognitive changes or risk of dementia. Only four studies reported model prognostic performance indices, such as Area Under the Curve (AUC), for predicting incident dementia or cognitive impairment and these studies all examined non-Framingham Risk models (AUC range: 0.74 to 0.78).

Conclusions

Cardiovascular risk prediction models are associated with cognitive changes over time and risk of dementia. Such models are easily obtainable in clinical and research settings and may be useful for identifying individuals at high risk of future cognitive decline and dementia.     

Peripheral inflammatory biomarkers are associated with cognitive function and dementia: Framingham Heart Study Offspring cohort

Inflammatory protein biomarkers induced by immune responses have been associated with cognitive decline and the pathogenesis of Alzheimer's disease (AD). Here, we investigate associations between a panel of inflammatory biomarkers and cognitive function and incident dementia outcomes in the well-characterized Framingham Heart Study Offspring cohort. Participants aged ≥40 years and dementia-free at Exam 7 who had a stored plasma sample were selected for profiling using the OLINK proteomics inflammation panel. Cross-sectional associations of the biomarkers with cognitive domain scores (N = 708, 53% female, 22% apolipoprotein E (APOE) ε4 carriers, 15% APOE ε2 carriers, mean age 61) and incident all-cause and AD dementia during up to 20 years of follow-up were tested. APOE genotype-stratified analyses were performed to explore effect modification. Higher levels of 12 and 3 proteins were associated with worse executive function and language domain factor scores, respectively. Several proteins were associated with more than one cognitive domain, including IL10, LIF-R, TWEAK, CCL19, IL-17C, MCP-4, and TGF-alpha. Stratified analyses suggested differential effects between APOE ε2 and ε4 carriers: most ε4 carrier associations were with executive function and memory domains, whereas most ε2 associations were with the visuospatial domain. Higher levels of TNFB and CDCP1 were associated with higher risks of incident all-cause and AD dementia. Our study found that TWEAK concentration was associated both with cognitive function and risks for AD dementia. The association of these inflammatory biomarkers with cognitive function and incident dementia may contribute to the discovery of therapeutic interventions for the prevention and treatment of cognitive decline.     

Executive function and falls in older adults: new findings from a five-year prospective study link fall risk to cognition

BACKGROUND: Recent findings suggest that executive function (EF) plays a critical role in the regulation of gait in older adults, especially under complex and challenging conditions, and that EF deficits may, therefore, contribute to fall risk. The objective of this study was to evaluate if reduced EF is a risk factor for future falls over the course of 5 years of follow-up. Secondary objectives were to assess whether single and dual task walking abilities, an alternative window into EF, were associated with fall risk. METHODOLOGY/MAIN RESULTS: We longitudinally followed 256 community-living older adults (age: 76.4±4.5 yrs; 61% women) who were dementia free and had good mobility upon entrance into the study. At baseline, a computerized cognitive battery generated an index of EF, attention, a closely related construct, and other cognitive domains. Gait was assessed during single and dual task conditions. Falls data were collected prospectively using monthly calendars. Negative binomial regression quantified risk ratios (RR). After adjusting for age, gender and the number of falls in the year prior to the study, only the EF index (RR: .85; CI: .74-.98, p?=?.021), the attention index (RR: .84; CI: .75-.94, p?=?.002) and dual tasking gait variability (RR: 1.11; CI: 1.01-1.23; p?=?.027) were associated with future fall risk. Other cognitive function measures were not related to falls. Survival analyses indicated that subjects with the lowest EF scores were more likely to fall sooner and more likely to experience multiple falls during the 66 months of follow-up (p<0.02). CONCLUSIONS/SIGNIFICANCE: These findings demonstrate that among community-living older adults, the risk of future falls was predicted by performance on EF and attention tests conducted 5 years earlier. The present results link falls among older adults to cognition, indicating that screening EF will likely enhance fall risk assessment, and that treatment of EF may reduce fall risk.     

BrainAGE in Mild Cognitive Impaired Patients: Predicting the Conversion to Alzheimer’s Disease

Alzheimer’s disease (AD), the most common form of dementia, shares many aspects of abnormal brain aging. We present a novel magnetic resonance imaging (MRI)-based biomarker that predicts the individual progression of mild cognitive impairment (MCI) to AD on the basis of pathological brain aging patterns. By employing kernel regression methods, the expression of normal brain-aging patterns forms the basis to estimate the brain age of a given new subject. If the estimated age is higher than the chronological age, a positive brain age gap estimation (BrainAGE) score indicates accelerated atrophy and is considered a risk factor for conversion to AD. Here, the BrainAGE framework was applied to predict the individual brain ages of 195 subjects with MCI at baseline, of which a total of 133 developed AD during 36 months of follow-up (corresponding to a pre-test probability of 68%). The ability of the BrainAGE framework to correctly identify MCI-converters was compared with the performance of commonly used cognitive scales, hippocampus volume, and state-of-the-art biomarkers derived from cerebrospinal fluid (CSF). With accuracy rates of up to 81%, BrainAGE outperformed all cognitive scales and CSF biomarkers in predicting conversion of MCI to AD within 3 years of follow-up. Each additional year in the BrainAGE score was associated with a 10% greater risk of developing AD (hazard rate: 1.10 [CI: 1.07–1.13]). Furthermore, the post-test probability was increased to 90% when using baseline BrainAGE scores to predict conversion to AD. The presented framework allows an accurate prediction even with multicenter data. Its fast and fully automated nature facilitates the integration into the clinical workflow. It can be exploited as a tool for screening as well as for monitoring treatment options.     

Associations between Skeletal Growth in Childhood and Cognitive Function in Mid-Life in a 53-Year Prospective Birth Cohort Study

Background

Several studies have found that shorter stature (height and limb length) in late life is associated with dementia and cognitive impairment. The extent to which childhood environment and early life cognitive function accounts for these associations is not clear.

Methods

We investigated associations of adult trunk height and leg length with cognitive function in middle age, analysing data from the MRC National Survey of Health and Development: a cohort followed from birth to age 53, 1677 of whom had data on all covariates. The four cognitive tests measured verbal ability, word list memory, verbal fluency and speed/concentration. Early life environmental measures included parental education, poverty, parental divorce, physical health, cognitive ability at age 15, own education and own adult social class.

Results

After adjusting for gender, shorter trunk length was associated with lower cognitive function on all four tests and shorter leg length with lower verbal intelligence and word list memory. These associations were only partially attenuated following adjustment for childhood adversity/health but were substantially accounted for by cognitive ability at age 15.

Conclusions

Shorter stature was associated with lower cognitive function at age 53, the majority of this association being accounted for by cognitive function at age 15. Reduced cognitive reserve may well account for later associations between anthropometric measures and dementia.     

Identification and comparative analysis of novel alternatively spliced transcripts of RhoGEF domain encoding gene in C. elegans and C. briggsae

This study was aimed at identifying, in 203 patients with Alzheimer's disease followed during long-term treatment with Acetylcholinesterase inhibitors (ChEIs), the predictive factors of the clinical response among cognition (MMSE), functioning (BADL and IADL) measures and age and gender at the baseline (T0). The ANCOVA test showed a significant association between MMSE scores at time T0 and T3, and the variation T9 to T0, T15 to T0 and T21 to T0 of the MMSE scores, using also gender, age and drug as covariates. The significance was higher for the patients affected by mild dementia. Regarding functional activities, a significant relationship was detected, by the ANCOVA test, only between the scores at T3 and the variation T15 to T0 for BADL, and the variation T9 to T0, T15 to T0 for IADL, respectively. Our results confirm, in a real world setting, that ChEIs provide long-term cognitive benefit, which is correlated to, and predictable by, the short-term response (within the third month) as well as the cognitive status (evaluated by means of the MMSE) at the beginning of the treatment. These factors should be the basis of any cost/effectiveness algorithm in health economic decision models.     

Association of Structural Global Brain Network Properties with Intelligence in Normal Aging

Higher general intelligence attenuates age-associated cognitive decline and the risk of dementia. Thus, intelligence has been associated with cognitive reserve or resilience in normal aging. Neurophysiologically, intelligence is considered as a complex capacity that is dependent on a global cognitive network rather than isolated brain areas. An association of structural as well as functional brain network characteristics with intelligence has already been reported in young adults. We investigated the relationship between global structural brain network properties, general intelligence and age in a group of 43 cognitively healthy elderly, age 60–85 years. Individuals were assessed cross-sectionally using Wechsler Adult Intelligence Scale-Revised (WAIS-R) and diffusion-tensor imaging. Structural brain networks were reconstructed individually using deterministic tractography, global network properties (global efficiency, mean shortest path length, and clustering coefficient) were determined by graph theory and correlated to intelligence scores within both age groups. Network properties were significantly correlated to age, whereas no significant correlation to WAIS-R was observed. However, in a subgroup of 15 individuals aged 75 and above, the network properties were significantly correlated to WAIS-R. Our findings suggest that general intelligence and global properties of structural brain networks may not be generally associated in cognitively healthy elderly. However, we provide first evidence of an association between global structural brain network properties and general intelligence in advanced elderly. Intelligence might be affected by age-associated network deterioration only if a certain threshold of structural degeneration is exceeded. Thus, age-associated brain structural changes seem to be partially compensated by the network and the range of this compensation might be a surrogate of cognitive reserve or brain resilience.     

Associations between White Matter Microstructure and Cognitive Performance in Old and Very Old Age

Increasing age is associated with deficits in a wide range of cognitive domains as well as with structural brain changes. Recent studies using diffusion tensor imaging (DTI) have shown that microstructural integrity of white matter is associated with cognitive performance in elderly persons, especially on tests that rely on perceptual speed. We used structural equation modeling to investigate associations between white matter microstructure and cognitive functions in a population-based sample of elderly persons (age ≥ 60 years), free of dementia, stroke, and neurological disorders (n = 253). Participants underwent a magnetic resonance imaging scan, from which mean fractional anisotropy (FA) and mean diffusivity (MD) of seven white matter tracts were quantified. Cognitive functioning was analyzed according to performance in five task domains (perceptual speed, episodic memory, semantic memory, letter fluency, and category fluency). After controlling for age, FA and MD were exclusively related to perceptual speed. When further stratifying the sample into two age groups, the associations were reliable in the old-old (≥78 years) only. This relationship between white matter microstructure and perceptual speed remained significant after excluding persons in a preclinical dementia phase. The observed pattern of results suggests that microstructural white matter integrity may be especially important to perceptual speed among very old adults.