Rate of cognitive decline in preclinical Alzheimer's disease: the role of comorbidity

Homocysteine - A predictor for five year-mortality in patients with subjective cognitive decline, mild cognitive impairment and Alzheimer's dementia

BACKGROUND

Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI) are preclinical stages of Alzheimer's Disease (AD), which is the most common entity of dementia. Homocysteine is an amino acid in the methionine cycle, and many studies revealed a significant association between elevated homocysteine serum levels and the progression of dementia. The primary objective of this retrospective study was to investigate whether elevated homocysteine serum levels could be associated with mortality and neuropsychological test results in individuals suffering from SCD, MCI or AD.

METHODS

This study is a single-center explorative retrospective data analysis with 976 data protocols from the Memory Outpatient's Clinic of the Medical University of Vienna included. All patients underwent a neurological examination, a laboratory blood test, and neuropsychological testing to establish a diagnosis of either SCD, MCI, or AD. Data was evaluated by Kaplan-Meier functions, factor analysis, and binary logistic regression models.

RESULTS

Patients with AD showed significantly higher mean homocysteine levels (SCD 12.15 ± 4.71, MCI 12.80 ± 4.81, AD 15.0 ± 6.44 μmol/L) compared to those with SCD and MCI (p ≤ .001). The mean age of patients with AD (75.2 ± 7.8) was significantly older at the time of testing than of patients with MCI (69.1 ± 9.6) or SCD (66.8 ± 9.3). Since homocysteine levels increase with age, this could be a possible explanation for the higher levels of AD patients. The age at death did not differ significantly between all diagnostic subgroups, resulting in the shortest survival times for AD patients. Homocysteine levels were negatively associated with in Mini-Mental State Examination (MMSE) and Neuropsyhcological Test Battery Vienna (NTBV) factors F1-F4 (F1 = attention, F2 = memory, F3 = executive functions, F4 = naming/verbal comprehension). Moreover, higher homocysteine levels significantly predicted shorter five-year survival in the logistic regression models, even after adjusting for age, diagnostic subgroups, sex, years of education and results of neuropsychological testing.

CONCLUSION

The results of this study suggest that homocysteine levels are independently associated with impaired cognitive function and increased five-year mortality.

Genetic effects on longitudinal cognitive decline during the early stages of Alzheimer's disease

Cognitive decline in early-stage Alzheimer's disease (AD) may depend on genetic variability. In the Swedish BioFINDER study, we used polygenic scores (PGS) (for AD, intelligence, and educational attainment) to predict longitudinal cognitive change (measured by mini-mental state examination (MMSE) [primary outcome] and other cognitive tests) over a mean of 4.2 years. We included 260 β-amyloid (Aβ) negative cognitively unimpaired (CU) individuals, 121 Aβ-positive CU (preclinical AD), 50 Aβ-negative mild cognitive impairment (MCI) patients, and 127 Aβ-positive MCI patients (prodromal AD). Statistical significance was determined at Bonferroni corrected p value < 0.05. The PGS for intelligence (beta = 0.1, p = 2.9e-02) was protective against decline in MMSE in CU and MCI participants regardless of Aβ status. The polygenic risk score for AD (beta =  - 0.12, p = 9.4e-03) was correlated with the rate of change in MMSE and was partially mediated by Aβ-pathology (mediation effect 20%). There was no effect of education PGS on cognitive measures. Genetic variants associated with intelligence mitigate cognitive decline independent of Aβ-pathology, while effects of genetic variants associated with AD are partly mediated by Aβ-pathology.

Assessing visuo-constructive functions in patients with subjective cognitive decline, mild cognitive impairment and Alzheimer’s disease with the Vienna Visuo-Constructional Test 3.0 (VVT 3.0)

Background

Visuo-Constructive functions have considerable potential for the early diagnosis and monitoring of disease progression in Alzheimer’s disease.

Objectives

Using the Vienna Visuo-Constructional Test 3.0 (VVT 3.0), we measured visuo-constructive functions in subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD), and healthy controls to determine whether VVT performance can be used to distinguish these groups.

Materials and methods

Data of 671 participants was analyzed comparing scores across diagnostic groups and exploring associations with relevant clinical variables. Predictive validity was assessed using Receiver Operator Characteristic curves and multinomial logistic regression analysis.

Results

We found significant differences between AD and the other groups. Identification of cases suffering from visuo-constructive impairment was possible using VVT scores, but these did not permit classification into diagnostic subgroups.

Conclusions

In summary, VVT scores are useful indicators for visuo-constructive impairment but face challenges when attempting to discriminate between several diagnostic groups.

Generalizability of findings from a clinical sample to a community-based sample: A comparison of ADNI and ARIC

INTRODUCTION

Clinic-based study samples, including the Alzheimer's Disease Neuroimaging Initiative (ADNI), offer rich data, but findings may not generalize to community-based settings. We compared associations in ADNI to those in the Atherosclerosis Risk in Communities (ARIC) study to assess generalizability across the two settings.

METHODS

We estimated cohort-specific associations among risk factors, cognitive test scores, and neuroimaging outcomes to identify and quantify the extent of significant and substantively meaningful differences in associations between cohorts. We explored whether using more homogenous samples improved comparability in effect estimates.

RESULTS

The proportion of associations that differed significantly between cohorts ranged from 27% to 34% across sample subsets. Many differences were substantively meaningful (e.g., odds ratios [OR] for apolipoprotein E ε4 on amyloid positivity in ARIC: OR = 2.8, in ADNI: OR = 8.6).

DISCUSSION

A higher proportion of associations differed significantly and substantively than would be expected by chance. Findings in clinical samples should be confirmed in more representative samples.

Empirically Defining Trajectories of Late-Life Cognitive and Functional Decline

BACKGROUND

Alzheimer's disease (AD) is associated with variable cognitive and functional decline, and it is difficult to predict who will develop the disease and how they will progress.

OBJECTIVE

This exploratory study aimed to define latent classes from participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database who had similar growth patterns of both cognitive and functional change using Growth Mixture Modeling (GMM), identify characteristics associated with those trajectories, and develop a decision tree using clinical predictors to determine which trajectory, as determined by GMM, individuals will most likely follow.

METHODS

We used ADNI early mild cognitive impairment (EMCI), late MCI (LMCI), AD dementia, and healthy control (HC) participants with known amyloid-β status and follow-up assessments on the Alzheimer's Disease Assessment Scale - Cognitive Subscale or the Functional Activities Questionnaire (FAQ) up to 24 months postbaseline. GMM defined trajectories. Classification and Regression Tree (CART) used certain baseline variables to predict likely trajectory path.

RESULTS

GMM identified three trajectory classes (C): C1 (n = 162, 13.6%) highest baseline impairment and steepest pattern of cognitive/functional decline; C3 (n = 819, 68.7%) lowest baseline impairment and minimal change on both; C2 (n = 211, 17.7%) intermediate pattern, worsening on both, but less steep than C1. C3 had fewer amyloid- or apolipoprotein-E ɛ4 (APOE4) positive and more healthy controls (HC) or EMCI cases. CART analysis identified two decision nodes using the FAQ to predict likely class with 82.3% estimated accuracy.

CONCLUSIONS

Cognitive/functional change followed three trajectories with greater baseline impairment and amyloid and APOE4 positivity associated with greater progression. FAQ may predict trajectory class.

Association Between Accelerated Multimorbidity and Age-Related Cognitive Decline in Older Baltimore Longitudinal Study of Aging Participants without Dementia

OBJECTIVES

To explore the association between rate of physical health deterioration, operationalized as rising multimorbidity overtime, and longitudinal decline in cognitive function in older adults without dementia.

DESIGN

Longitudinal (Baltimore Longitudinal Study of Aging (BLSA)).

SETTING

Community.

PARTICIPANTS

BLSA participants aged 65 and older followed for an average of 3 years and free of dementia or mild cognitive impairment (MCI) at baseline and follow-up (N = 756).

MEASUREMENTS

Standardized neurocognitive tests evaluating mental status, memory, executive function, processing speed, and verbal fluency were administered. Multimorbidity was assessed at each visit as number of diagnosed chronic diseases from a predefined list. Faster accumulation of chronic diseases was defined as upper quartile of rate of change in number of diseases over time (≥0.25 diseases/year).

RESULTS

Faster accumulation of chronic diseases was significantly associated with greater rate of decline on the Category (P = .01) and Letter (P = .01) Fluency Tests. Similar trends were also found for the Trail-Making Test Parts A (P = .08) and B (P = .07); no association was found with rate of change in visual and verbal memory.

CONCLUSION

Although further investigations are required to validate the results and fully understand the underlying mechanisms, these findings suggest that accelerated deterioration of physical health is associated with accelerated decline with aging in specific cognitive domains in older adults without dementia.

Neuroinflammation in Alzheimer's disease; A source of heterogeneity and target for personalized therapy

Neuroinflammation has long been known as an accompanying pathology of Alzheimer's disease. Microglia surrounding amyloid plaques in the brain of Auguste D were described in the original publication of Alois Alzheimer. It is only quite recently, however, that we have a more complete appreciation for the diverse roles of neuroinflammation in neurodegenerative disorders such as Alzheimer's. While gaps in our knowledge remain, and conflicting data are abound in the field, our understanding of the complexities and heterogeneous functions of the inflammatory response in Alzheimer's is vastly improved. This review article will discuss some of the roles of neuroinflammation in Alzheimer's disease, in particular, how understanding heterogeneity in the individual inflammatory response can be used in therapeutic development and as a mechanism of personalizing our treatment of the disease.

The influence of multimorbidity on clinical progression of dementia in a population-based cohort

Introduction

Co-occurrence with other chronic diseases may influence the progression of dementia, especially in case of multiple chronic diseases. We aimed to verify whether multimorbidity influenced cognitive and daily functioning during nine years after dementia diagnosis compared with the influence in persons without dementia.

Methods

In the Kungsholmen Project, a population-based cohort study, we followed 310 persons with incident dementia longitudinally. We compared their trajectories with those of 679 persons without dementia. Progression was studied for cognition and activities of daily life (ADLs), measured by MMSE and Katz Index respectively. The effect of multimorbidity and its interaction with dementia status was studied using individual growth models.

Results

The mean (SD) follow-up time was 4.7 (2.3) years. As expected, dementia related to both the decline in cognitive and daily functioning. Irrespective of dementia status, persons with more diseases had significantly worse baseline daily functioning. In dementia patients having more diseases also related to a significantly faster decline in daily functioning. Due to the combination of lower functioning in ADLs at baseline and faster decline, dementia patients with multimorbidity were about one to two years ahead of the decline of dementia patients without any co-morbidity. In persons without dementia, no significant decline in ADLs over time was present, nor was multimorbidity related to the decline rate. Cognitive decline measured with MMSE remained unrelated to the number of diseases present at baseline.

Conclusion

Multimorbidity was related to baseline daily function in both persons with and without dementia, and with accelerated decline in people with dementia but not in non-demented individuals. No relationship of multimorbidity with cognitive functioning was established. These findings imply a strong interconnection between physical and mental health, where the greatest disablement occurs when both somatic and mental disorders are present.

Rapid cognitive decline in Alzheimer's disease: a literature review

BACKGROUND

The rate of cognitive decline in Alzheimer's disease (AD) varies considerably between individuals. Predicting rapid cognitive decline might help clinicians provide prognostic information, select subjects for trial intervention and/or reduce costs.

METHODS

PubMed and PsycINFO were searched for all the English written studies published until the end of 2010 on rapid cognitive decline in AD and factors associated with it.

RESULTS

More than 300 individual articles were retrieved. We selected 82 relevant studies. The main findings of these papers are that younger, more educated and more impaired patients are more likely to show rapid cognitive decline. ApoE alleles seem not to modify the velocity of clinical progression of dementia, or at most could have a very small effect. No inference can be made for all the other variables analysed.

CONCLUSIONS

There are many studies on rapid cognitive decline. Results are heterogeneous and often contradictory. No reliable conclusions about factors that may be associated with rapid cognitive decline can yet be drawn.

Are inflammatory profiles the key to personalized Alzheimer's treatment?

There is currently no disease-modifying treatment for Alzheimer's disease (AD) and the need is great as the number of people diagnosed with AD is predicted to steadily increase. Inflammation is associated with AD, and is predictive of more advanced disease pathology and cognitive impairment. Moreover, preventing inflammation reduces the risk of developing AD. However, clinical trials with anti-inflammatory treatment have not been successful. One reason may be that there is diversity in the immune response and reducing immune activity with anti-inflammatories is not appropriate in all conditions. Recently, we have begun to apply categorizations, used to characterize the peripheral immune response, to the immune processes of the brain. When we do this, we are able to describe an individual's inflammatory profile within this spectrum. We have observed that patients with early AD are distributed across two broad categories of immune activation. If we recognize the diversity within this cohort of individuals with early AD and use information about immune phenotypes to guide the choice of treatment, then we may expect better clinical outcomes.

The association of age with rate of cognitive decline in elderly individuals residing in supporting care facilities

OBJECTIVES

This study examines the effect of age on rate of cognitive decline in different stages of dementia, of nursing home and assisted-living residents.

METHODS

In this longitudinal study, the Mini Mental State Examination (MMSE) was used to measure rate of cognitive decline in subjects who were nondemented [Clinical Dementia Rating (CDR)=0; n=353], questionably demented (CDR=0.5; n=121), or frankly demented (CDR≥1; n=213) at baseline.

RESULTS

A generalized estimating equation was used to model the MMSE scores over time (mean follow-up 2.9±2.0 y). The generalized estimating equation model had the MMSE scores at successive follow-up time points as dependent variables and had linear and quadratic age, follow-up time from baseline, CDR at baseline, and all the interactions among them as independent variables, controlling for MMSE at baseline, sex, race, and education. The mean age of the entire sample was 85.2±7.4 years at baseline. There were no significant interactions of linear age effects with rate of cognitive decline. The analysis of interaction of quadratic age with rate of cognitive decline showed complex relationships: in the nondemented group, there was no substantial quadratic association of age with the rate of cognitive decline (P=0.13); in the questionable demented group, the oldest subjects declined relatively faster (P=0.02); and in the demented group, the youngest and oldest subjects tended to decline relatively less than subjects in the intermediate ages (P=0.07).

CONCLUSIONS

This study adds an additional aspect to the complexity of the association between age and rate of cognitive decline, showing that the direction and amplitude of this effect differs according to the stage along the course of cognitive decline.

Dynamic links between memory and functional limitations in old age: longitudinal evidence for age-based structural dynamics from the AHEAD study

This study examined competing substantive hypotheses about dynamic (i.e., time-ordered) links between memory and functional limitations in old age. We applied the Bivariate Dual Change Score Model to 13-year longitudinal data from the Asset and Health Dynamics Among the Oldest Old Study (AHEAD; N = 6,990; ages 70 - 95). Results revealed that better memory predicted shallower increases in functional limitations. Little evidence was found for the opposite direction that functional limitations predict ensuing changes in memory. Spline models indicated that dynamic associations between memory and functional limitations were substantively similar between participants aged 70-79 and those aged 80-95. Potential covariates (gender, education, health conditions, and depressive symptoms) did not account for these differential lead-lag associations. Applying a multivariate approach, our results suggest that late-life developments in two key components of successful aging are intrinsically interrelated. Our discussion focuses on possible mechanisms why cognitive functioning may serve as a source of age-related changes in health both among the young-old and the old-old.

Trajectories of cognitive decline following dementia onset: what accounts for variation in progression?

BACKGROUND

Delineating the natural history of dementia progression has important clinical implications, including reducing caregiver burden and targeting effective drug trials. We examined whether trajectories of cognitive change differed reliably after diagnosis, and whether diverse predictors of such differences (demographic, psychological, biological, genetic, social) could be identified.

METHODS

Cognitive change was examined for incident dementia cases (mild: n = 156; moderate: n = 77; severe: n = 73) and controls (n = 249) from the Kungsholmen Project, a community-based study of adults 75 years and older.

RESULTS

For those with dementia, total variance attributed to between-person differences in cognitive decline was modest and linked to but a single predictor (history of cardiovascular disease). Although less variance in cognitive decline was observed for the similarly aged controls, numerous significant predictors of these differences were identified.

CONCLUSION

The neurodegenerative process underlying dementia overshadows formerly significant predictors of cognitive change.

Clinical features and multidisciplinary approaches to dementia care

Dementia is a clinical syndrome of widespread progressive deterioration of cognitive abilities and normal daily functioning. These cognitive and behavioral impairments pose considerable challenges to individuals with dementia, along with their family members and caregivers. Four primary dementia classifications have been defined according to clinical and research criteria: 1) Alzheimer's disease; 2) vascular dementias; 3) frontotemporal dementias; and 4) dementia with Lewy bodies/Parkinson's disease dementia. The cumulative efforts of multidisciplinary healthcare teams have advanced our understanding of dementia beyond basic descriptions, towards a more complete elucidation of risk factors, clinical symptoms, and neuropathological correlates. The characterization of disease subtypes has facilitated targeted management strategies, advanced treatments, and symptomatic care for individuals affected by dementia. This review briefly summarizes the current state of knowledge and directions of dementia research and clinical practice. We provide a description of the risk factors, clinical presentation, and differential diagnosis of dementia. A summary of multidisciplinary team approaches to dementia care is outlined, including management strategies for the treatment of cognitive impairments, functional deficits, and behavioral and psychological symptoms of dementia. The needs of individuals with dementia are extensive, often requiring care beyond traditional bounds of medical practice, including pharmacologic and non-pharmacologic management interventions. Finally, advanced research on the early prodromal phase of dementia is reviewed, with a focus on change-point models, trajectories of cognitive change, and threshold models of pathological burden. Future research goals are outlined, with a call to action for social policy initiatives that promote preventive lifestyle behaviors, and healthcare programs that will support the growing number of individuals affected by dementia.

Top cited papers in International Psychogeriatrics: 6c. Tracking cognitive decline in Alzheimer's disease using the Mini-mental State Examination: a meta-analysis ("mini" is not necessarily trivial!)

It was well beyond my expectations when I heard from Professor Ames that our meta-analysis paper (Han et al., 2000) was among the top-cited papers in International Psychogeriatrics. As an expression of my gratitude to the editor for the invitation and to the audience of this paper, I would like to offer this informal discussion on the background of the paper and extend a few ideas that were not conveyed fully at the time, due either to insufficient knowledge or unavailability of relevant data or methodologies.

High medical co-morbidity and family history of dementia is associated with lower cognitive function in older patients

BACKGROUND

Risk factors for cognitive decline in ageing are multifactorial, including medical co-morbidities and familial genetic risk.

OBJECTIVES

To assess the effect of medical co-morbidity and family history of dementia on cognitive performance in older outpatients of family practitioners.

METHODS

Analysis of 535 outpatients from 11 practices aged 65 and older, without a diagnosis of dementia. Information on medical co-morbidities, family history of dementia and cognitive test data were obtained.

RESULTS

Patients were classified into high or low medical co-morbidities (<7 versus >8) and positive or negative family history of dementia. After controlling for age, education, gender and depression, global cognitive test scores, as well as memory, executive function, spatial ability and attention were significantly lower for persons having a high number of medical co-morbidities. Cognitive test scores were not significantly different for persons with or without a family history of dementia. A significant interaction between medical co-morbidities and family history of dementia was observed for the global cognitive score, executive function and spatial ability. Those persons with a high number of medical co-morbidities and positive family history of dementia had the lowest performance. Separate regression analysis assessing individual disease risk factors (e.g. hypertension and diabetes) did not find any relationship between specific medical variables and cognitive test scores for any of the subgroups.

CONCLUSIONS

A high number of medical co-morbidities in addition to a reported family history of dementia are particularly detrimental to cognitive performance in elderly non-demented family practice patients.

Alcohol consumption as a risk factor for dementia and cognitive decline: meta-analysis of prospective studies

The relationships between alcohol consumption and dementia and cognitive decline were investigated in a systematic review including meta-analyses of 15 prospective studies. Follow-ups ranged from 2 to 8 years. Meta-analyses were conducted on samples including 14,646 participants evaluated for Alzheimer disease (AD), 10,225 participants evaluated for vascular dementia (VaD), and 11,875 followed for any type of dementia (Any dementia). The pooled relative risks (RRs) of AD, VaD, and Any dementia for light to moderate drinkers compared with nondrinkers were 0.72 (95% CI = 0.61-0.86), 0.75 (95% CI = 0.57-0.98), and 0.74 (95% CI = 0.61-0.91), respectively. When the more generally classified "drinkers," were compared with "nondrinkers," they had a reduced risk of AD (RR = 0.66, 95% CI = 0.47-0.94) and Any dementia (RR = 0.53, 95% CI = 0.53-0.82) but not cognitive decline. There were not enough data to examine VaD risk among "drinkers." Those classified as heavy drinkers did not have an increased risk of Any dementia compared with nondrinkers, but this may reflect sampling bias. Our results suggest that alcohol drinkers in late life have reduced risk of dementia. It is unclear whether this reflects selection effects in cohort studies commencing in late life, a protective effect of alcohol consumption throughout adulthood, or a specific benefit of alcohol in late life.

Activity loss is associated with cognitive decline in age-related macular degeneration

BACKGROUND/METHODS

The objective of this study was to determine whether relinquishing cognitive, physical, and social activities is associated with an increased risk of cognitive decline in patients with age-related macular degeneration (AMD). We conducted a 3-year longitudinal study of 206 nondemented patients with AMD.

RESULTS

Twenty-three subjects (14.4%) declined cognitively. Age, sex, education, decline in visual acuity, and number of dropped activities were associated with cognitive decline; each additional dropped activity increased the risk by 58%. Subjects who relinquished three activities were 3.87 times (95% confidence interval, 1.95-7.76) more likely to become demented than subjects who relinquished no activities; those who relinquished five activities were 9.54 times (95% confidence interval, 3.05-30.43) more likely. A multivariate model demonstrated that number of dropped activities was a powerful predictor of cognitive decline after controlling for relevant risk factors, particularly for subjects younger than 80 years of age.

CONCLUSIONS

Relinquishing valued activities is associated with an increased risk of cognitive decline in older patients with vision loss caused by AMD. These data suggest the importance of promoting optimal cognitive and physical health in patients with AMD and perhaps other chronic diseases.

Age-related decline in brain resources modulates genetic effects on cognitive functioning

Individual differences in cognitive performance increase from early to late adulthood, likely reflecting influences of a multitude of factors. We hypothesize that losses in neurochemical and anatomical brain resources in normal aging modulate the effects of common genetic variations on cognitive functioning. Our hypothesis is based on the assumption that the function relating brain resources to cognition is nonlinear, so that genetic differences exert increasingly large effects on cognition as resources recede from high to medium levels in the course of aging. Direct empirical support for this hypothesis comes from a study by Nagel et al. (2008), who reported that the effects of the Catechol-O-Methyltransferase (COMT) gene on cognitive performance are magnified in old age and interacted with the Brain-Derived Neurotrophic Factor (BDNF) gene. We conclude that common genetic polymorphisms contribute to the increasing heterogeneity of cognitive functioning in old age. Extensions of the hypothesis to other polymorphisms are discussed. (150 of 150 words)

Memory and cognition in preclinical dementia: what we know and what we do not know

This overview focuses on the cognitive transition between normal aging and dementia. Numerous studies indicate that individuals who will go on to develop dementia show cognitive deficits many years before the time at which a clinical diagnosis could be rendered. The degree of preclinical impairment is remarkably similar for tasks assessing episodic memory, executive functioning, and perceptual speed, consistent with the view that multiple brain alterations occur prior to clinical disease onset. Although most research in this area has dealt with Alzheimer disease (AD), several recent reports indicate that the pattern of preclinical impairment is very similar in the second largest dementia disorder, vascular dementia (VaD). This is important because currently the possibility for interventions to postpone disease onset is greater in VaD than in AD. Despite pronounced preclinical cognitive deficits in dementia, the performance distributions between cases and controls are largely overlapping, hampering the ability to identify high-risk individuals. To alleviate this problem, future research should evaluate hybrid models for the prediction of dementia. In such models, multiple indicators of cognitive functioning should be included along with markers from other domains that have been linked to subsequent dementia (such as brain imaging, genetics, and lifestyle variables). To the extent that these categories of variables add unique variance, classification accuracy will increase and the overlap in performance scores between incident cases and controls will decrease, thereby enhancing clinical usefulness. This approach would also facilitate the examination of interactive effects among classes of preclinical markers.

A comparison of parametric models for the investigation of the shape of cognitive change in the older population

BACKGROUND

Cognitive decline is a major threat to well being in later life. Change scores and regression based models have often been used for its investigation. Most methods used to describe cognitive decline assume individuals lose their cognitive abilities at a constant rate with time. The investigation of the parametric curve that best describes the process has been prevented by restrictions imposed by study design limitations and methodological considerations. We propose a comparison of parametric shapes that could be considered to describe the process of cognitive decline in late life. Attrition plays a key role in the generation of missing observations in longitudinal studies of older persons. As ignoring missing observations will produce biased results and previous studies point to the important effect of the last observed cognitive score on the probability of dropout, we propose modelling both mechanisms jointly to account for these two considerations in the model likelihood.

METHODS

Data from four interview waves of a population based longitudinal study of the older population, the Cambridge City over 75 Cohort Study were used. Within a selection model process, latent growth models combined with a logistic regression model for the missing data mechanism were fitted. To illustrate advantages of the model proposed, a sensitivity analysis of the missing data assumptions was conducted.

RESULTS

Results showed that a quadratic curve describes cognitive decline best. Significant heterogeneity between individuals about mean curve parameters was identified. At all interviews, MMSE scores before dropout were significantly lower than those who remained in the study. Individuals with good functional ability were found to be less likely to dropout, as were women and younger persons in later stages of the study.

CONCLUSION

The combination of a latent growth model with a model for the missing data has permitted to make use of all available data and quantify the effect of significant predictors of dropout on the dropout and observational processes. Cognitive decline over time in older persons is often modelled as a linear process, though we have presented other parametric curves that may be considered.

Cognitive deficits in preclinical Alzheimer's disease and vascular dementia: Patterns of findings from the Kungsholmen Project

Using data from the Kungsholmen Project (KP), we describe a program of research that focuses on preclinical cognitive markers of dementia. A large number of KP studies convincingly demonstrate that there is a preclinical period that spans several years in both Alzheimer's disease (AD) and vascular dementia (VaD), during which cognitive deficits are possible to detect. In AD, the preclinical impairment generalizes across a variety of cognitive domains, including episodic memory, executive functioning, perceptual speed, attention, verbal ability, and visuospatial skill. Although less research has been directed at cognition in preclinical VaD, the emerging evidence suggests a rather broad prodromal impairment in this disease as well. Thus, the nature of the cognitive impairment appears to be largely similar in preclinical AD and VaD. Despite the fact that average group differences in cognitive performance between incident dementia cases and controls are large several years before diagnosis, the distribution of scores in these groups overlap greatly. In order to improve group classification, future research should consider combining cognitive markers with preclinical indicators from other domains (e.g., biological, clinical, social, genetic) into multivariate prediction models.

Cognitive impairment in preclinical Alzheimer's disease: a meta-analysis

To determine the size of the impairment across different cognitive domains in preclinical Alzheimer's disease (AD), a meta-analysis based on 47 studies involving 9,097 controls and 1,207 preclinical AD cases was conducted. There were marked preclinical deficits in global cognitive ability, episodic memory, perceptual speed, and executive functioning; somewhat smaller deficits in verbal ability, visuospatial skill, and attention; and no preclinical impairment in primary memory. Younger age (< 75 years) and shorter follow-up intervals (< 3 years) were associated with larger effect sizes for both global cognitive ability and episodic memory. For global cognitive ability, studies that used population-based sampling yielded larger effect sizes; for episodic memory, larger differences were seen in studies that preidentified groups in terms of baseline cognitive impairment. Within episodic memory, delayed testing and recall-based assessment resulted in the largest effect sizes. The authors conclude that deficits in multiple cognitive domains are characteristic of AD several years before clinical diagnosis. The generalized nature of the deficit is consistent with recent observations that multiple brain structures and functions are affected long before the AD diagnosis.

Multiple cognitive deficits during the transition to Alzheimer's disease

The literature on cognitive markers in preclinical AD is reviewed. The findings demonstrate that impairment in multiple cognitive domains is typically observed several years before clinical diagnosis. Measures of executive functioning, episodic memory and perceptual speed appear to be most effective at identifying at-risk individuals. The fact that these cognitive domains are most implicated in normal cognitive aging suggests that the cognitive deficit observed preclinically is not qualitatively different from that observed in normal aging. The degree of cognitive impairment prior to the diagnosis of Alzheimer's disease (AD) appears to generalize relatively well across major study characteristics, including sample ascertainment procedures, age and cognitive status of participants, as well as time to diagnosis of dementia. In episodic memory, there is evidence that the size of the preclinical deficit increases with increasing cognitive demands. The global cognitive impairment observed is highly consistent with observations that multiple brain structures and functions are affected long before the diagnosis of AD. However, there is substantial overlap in the distribution of cognitive scores between those who will and those who will not be diagnosed with AD, hence limiting the clinical utility of cognitive markers for early identification of cases. Future research should consider combining cognitive indicators with other types of markers (i.e. social, somatic, genetic, brain-based) in order to increase prediction accuracy.