Up to 60% of the patients with Alzheimer’s disease (AD) can have cortical or brainstem Lewy bodies (LB), and extrapyramidal signs (EPS) have been found to be associated with LB in AD patients. However, the relationship between EPS and brain volumes has not been studied in the LB variant of AD using structural magnetic resonance imaging (MRI). The purpose of this study was to determine the relationship between patterns of brain atrophy and clinical EPS in patients with pathologically confirmed AD. We compared gray matter structure using voxel-based morphometry in 29 Definite AD cases, 16 (55%) of whom also had LBs identified with α-synuclein immunohistochemistry. Multivariate models analyzed brain volume at a voxel level accounting for subject group, Mini-Mental State Examination (MMSE), EPS, total brain volume, and the time from MRI scan to death. There was no significant difference in gray matter volume in the Definite AD patients as a function of LB. There was a significant association between gray matter volumes and the MMSE in AD patients, both with and without LBs. There was a significant correlation between gray matter volume and EPS only in the group of AD patients with LBs, and not in those with pure AD. These findings suggest that that the etiology of EPS in patients with the LB variant of AD is associated with neuronal loss in the nigrostriatal tracts. By contrast, the source of the EPS in AD alone appears to be less well localized.

Cholesterol metabolism is believed to play a role in the development of Alzheimer’s disease (AD). Oxysterol metabolites of cholesterol, 24S-hydroxycholesterol (24-OHC, a brain-derived oxysterol) and 27-hydroxycholesterol (27-OHC, a peripherally derived oxysterol) cross the blood brain barrier and have been associated with Alzheimer’s disease (AD). We investigated whether oxysterols were associated with markers of cerebrovascular disease prior to the onset of cognitive impairment.

Oxysterols were quantified in 105 participants (average age was 80±4 years) from the Pittsburgh Cardiovascular Health Study Cognition Study (CHS-CS) who remained cognitively normal at blood draw in 2002, had MRI in 1992 and 1998 and annual cognitive assessment for incident AD and mild cognitive impairment (MCI) made by consensus conference between 1998 and 2010.

Higher plasma levels of 24-OHC were associated with age, gender, the presence of high grade white matter hyperintensities (WMH) and brain infarcts on prior MRI. Participants with higher plasma 24-OHC and a greater ratio of 24-OHC/27-OHC were also more likely to develop incident cognitive impairment over 8 years of follow-up.

Higher levels of 24-OHC suggest increased cholesterol metabolism occurring in the brains of participants with cerebrovascular disease prior to the onset of cognitive impairment.

Measurement of oxysterols may provide information about cholesterol metabolism and brain disease over the cognitive impairment process.

Objectives

To evaluate associations between mid- and late-life obesity and risk of dementia.

Design

Prospective cohort followed 5.4 years from 1992/4 through 1999.

Setting

Community-dwelling sample in four US sites recruited from Medicare eligibility files.

Participants

2,798 adults without dementia, mean age 74.7 years, 59.1% women, participating in the Cardiovascular Health Cognition Study completing a magnetic resonance image, measured for height and weight at baseline (late-life) and self-reporting weight at age 50 (mid-life). Body mass index (BMI) was calculated at both times.

Main Outcome Measures

Dementia, Alzheimer’s disease (AD) and vascular dementia (VaD) classified by a multidisciplinary committee using standardized criteria.

Results

Classification resulted in 480 persons with incident dementia, 245 with AD (no VaD) and 213 with VaD (with or without AD). In evaluations of mid-life obesity, an increased risk of dementia was found for obese (BMI >30) compared to normal (BMI 20-25) persons adjusted for demographics (HR: 1.39, 95% CI: 1.03-1.87) and for caradiovascularl risk factors (HR: 1.36, 95% CI: 0.94-1.95). The risk estimates reversed in assessments of late-life BMI. Underweight persons (BMI < 20) had an increased risk of dementia (HR: 1.62, 95% CI: 1.02-2.64) while being overweight (BMI 25-30) was not associated (HR: 0.92, 95% CI: 0.72-1.18) and being obese reduced the risk of dementia (HR: 0.63, 95% CI: 0.44-0.91) compared to those with normal BMI.

Conclusions

These results help explain the “obesity paradox” as differences in dementia risk over time are consistent with physical changes in the trajectory toward disability.

Purpose of review

This review describes the evolution of the clinical criteria for Alzheimer’s disease over the past 25 years, with special emphasis on those recently published that have incorporated the use of biomarkers.

Recent findings

One of the most important advances in the knowledge of Alzheimer’s disease was the development of cerebrospinal fluid, PET and MRI biomarkers. These have shown that the Alzheimer’s disease is present in cognitively normal individuals, suggesting that there is a long incubation process that precedes the onset of the symptoms. Although there are diagnostic criteria for Alzheimer’s disease, the National Institute on Aging and the Alzheimer’s Association has proposed a set of diagnostic criteria oriented to provide a unified vision of the pathological process from preclinical, to mild cognitive impairment, and to full-blown dementia. These new criteria take advantage of different biomarkers to support the clinical diagnosis of the different stages of the disease.

Summary

The new guidelines provide a definition of the dementia syndrome and core diagnostic features to be used in research and clinical practice, although they caution about the use of biomarkers, since they still require validation, and the longitudinal interaction and dynamics of these biomarkers in relationship to the manifestation of the symptoms are not fully understood.

Late-onset Alzheimer’s disease (LOAD) is a complex and multifactorial disease. So far ten loci have been identified for LOAD, including APOE, PICALM, CLU, BIN1, CD2AP, CR1, CD33, EPHA1, ABCA7, and MS4A4A/MS4A6E, but they explain about 50% of the genetic risk and thus additional risk genes need to be identified. Amyloid beta (Aβ) plaques develop in the brains of LOAD patients and are considered to be a pathological hallmark of this disease. Recently 12 new Aβ toxicity modifier genes (ADSSL1, PICALM, SH3KBP1, XRN1, SNX8, PPP2R5C, FBXL2, MAP2K4, SYNJ1, RABGEF1, POMT2, and XPO1) have been identified that potentially play a role in LOAD risk. In this study, we have examined the association of 222 SNPs in these 12 candidate genes with LOAD risk in 1291 LOAD cases and 958 cognitively normal controls. Single site and haplotype analyses were performed using PLINK. Following adjustment for APOE genotype, age, sex, and principal components, we found single nucleotide polymorphisms (SNPs) in PPP2R5C, PICALM, SH3KBP1, XRN1, and SNX8 that showed significant association with risk of LOAD. The top SNP was located in intron 3 of PPP2R5C (P=0.009017), followed by an intron 19 SNP in PICALM (P=0.0102). Haplotype analysis revealed significant associations in ADSSL1, PICALM, PPP2R5C, SNX8, and SH3KBP1 genes. Our data indicate that genetic variation in these new candidate genes affects the risk of LOAD. Further investigation of these genes, including additional replication in other case-control samples and functional studies to elucidate the pathways by which they affect Aβ, are necessary to determine the degree of involvement these genes have for LOAD risk.

Normal human aging is accompanied by progressive brain tissue loss and cognitive decline; however, several factors are thought to influence brain aging. We applied tensor-based morphometry to high-resolution brain MRI scans to determine whether educational level or physical activity was associated with brain tissue volumes in the elderly, particularly in regions susceptible to age-related atrophy. We mapped the 3D profile of brain volume differences in 226 healthy elderly subjects (130F/96M; 77.9 ± 3.6 SD years) from the Cardiovascular Health Study-Cognition Study. Statistical maps revealed the 3D profile of brain regions whose volumes were associated with educational level and physical activity (based on leisure-time energy expenditure). After controlling for age, sex, and physical activity, higher educational levels were associated with ~2–3% greater tissue volumes, on average, in the temporal lobe gray matter. After controlling for age, sex, and education, greater physical activity was associated with ~2–2.5% greater average tissue volumes in the white matter of the corona radiata extending into the parietal-occipital junction. Body mass index (BMI) was highly correlated with both education and physical activity, so we examined BMI as a contributing factor by including physical activity, education, and BMI in the same model; only BMI effects remained significant. This is one of the largest MRI studies of factors influencing structural brain aging, and BMI may be a key factor explaining the observed relationship between education, physical activity, and brain structure. Independent contributions to brain structure could not be teased apart as all these factors were highly correlated with one another.

Late-onset Alzheimer’s disease (LOAD) is a complex and multifactorial disease. So far ten loci have been identified for LOAD, including APOE, PICALM, CLU, BIN1, CD2AP, CR1, CD33, EPHA1, ABCA7, and MS4A4A/MS4A6E, but they explain about 50% of the genetic risk and thus additional risk genes need to be identified. Amyloid beta (Aβ) plaques develop in the brains of LOAD patients and are considered to be a pathological hallmark of this disease. Recently 12 new Aβ toxicity modifier genes (ADSSL1, PICALM, SH3KBP1, XRN1, SNX8, PPP2R5C, FBXL2, MAP2K4, SYNJ1, RABGEF1, POMT2, and XPO1) have been identified that potentially play a role in LOAD risk. In this study, we have examined the association of 222 SNPs in these 12 candidate genes with LOAD risk in 1291 LOAD cases and 958 cognitively normal controls. Single site and haplotype analyses were performed using PLINK. Following adjustment for APOE genotype, age, sex, and principal components, we found single nucleotide polymorphisms (SNPs) in PPP2R5C, PICALM, SH3KBP1, XRN1, and SNX8 that showed significant association with risk of LOAD. The top SNP was located in intron 3 of PPP2R5C (P=0.009017), followed by an intron 19 SNP in PICALM (P=0.0102). Haplotype analysis revealed significant associations in ADSSL1, PICALM, PPP2R5C, SNX8, and SH3KBP1 genes. Our data indicate that genetic variation in these new candidate genes affects the risk of LOAD. Further investigation of these genes, including additional replication in other case-control samples and functional studies to elucidate the pathways by which they affect Aβ, are necessary to determine the degree of involvement these genes have for LOAD risk.

Abstract

As the incidence of HIV-associated dementia has decreased, the survival of HIV-infected individuals with milder forms of cognitive impairment has increased. Detecting this milder impairment in its earliest stages has great clinical and research importance. We report here the results of an initial evaluation of the Computer Assessment of Mild Cognitive Impairment (CAMCI®), a computerized screening tool designed to assess abnormal cognitive decline with reduced respondent and test administrator burden. Fifty-nine volunteers (29 HIV infected; age=50.9 years; education=14.9 years; 36/59 males) completed the CAMCI® and a battery of neuropsychological tests. The CAMCI was repeated 12 and 24 weeks later. The results from the CAMCI were compared to Global and Domain Impairment scores derived from the full neuropsychological test battery. The CAMCI detected mild impairment (compared with normal and borderline test performance) with a sensitivity of 0.72, specificity of 0.97, positive predictive rate of 0.93, and a negative predictive rate of 0.89. Median stability over 12 and 24 weeks of follow-up was 0.32 and 0.46, respectively. These rates did not differ as a function of serostatus. A discriminant function analysis correctly classified 90% of the subjects with respect to their overall Global Impairment Rating from six of the CAMCI scores. This preliminary study demonstrates that the CAMCI is sensitive to mild forms of cognitive impairment, and is stable over 24 weeks of follow-up. A larger trial to obtain risk-group appropriate normative data will be necessary to make the instrument useful in both clinical practice and research (e.g., clinical trials).

In recognition of the global problem posed by Alzheimer's disease and other dementias, an international think-tank meeting was convened by Biocat, the Pasqual Maragall Foundation, and the Lou Ruvo Brain Institute in February 2009. The meeting initiated the planning of a European Union-North American collaborative research enterprise to expedite the delay and ultimate prevention of dementing disorders. The key aim is to build parallel and complementary research infrastructure that will support international standardization and inter-operability among researchers in both continents. The meeting identified major challenges, opportunities for research resources and support, integration with ongoing efforts, and identification of key domains to influence the design and administration of the enterprise.

Psychotic symptoms occur in approximately 40% of subjects with Alzheimer disease (AD with Psychosis, AD+P) and identify a subgroup with more rapid cognitive decline. We evaluated in 867 AD subjects the association of AD+P with genes which may modify the pathologic process via effects on the accumulation of amyloid beta (Aβ) protein and/or hyperphosphorylated microtubule-associated protein tau (MAPT): amyloid precursor protein (APP), beta-site amyloid precursor protein cleaving enzyme (BACE1), sortilin-related receptor (SORL1), and MAPT. Each gene was thoroughly interrogated with tag SNPs, and gene-based tests were used to enhance power. We found no association of these genes with AD+P.

Objective

To compare the trajectories of cognitive decline between groups with, and without, the later development of psychotic symptoms during Alzheimer disease (AD) or Mild Cognitive Impairment (MCI).

Design

We examined cognitive function in a new analysis of an existing data set, The Cardiovascular Health Study (CHS), an epidemiologic, longitudinal follow-up study. Our analyses examined 9 years of follow-up data.

Setting

Community.

Participants

We examined subjects who were without dementia at study entry, received a diagnosis of AD or MCI during follow up and had been rated on the Neuropsychiatric Inventory for the presence of psychosis; 362 for the Modified Mini-Mental State Examination (3MS) analysis and 350 for the Digit Symbol Substitution Test (DSST) analysis had sufficient follow-up data and APOE genotyping.

Measurements

The 3MS and DSST were administered annually and analyzed using mixed effects models including APOE4 status.

Results

Mean 3MS and DSST scores did not differ between AD with psychosis and without psychosis groups at baseline. 3MS and DSST scores decreased more rapidly in subjects who ultimately developed psychosis.

Conclusions

Individuals who ultimately develop psychosis have more rapid cognitive deterioration during the earliest phases of AD than individuals with AD not developing psychosis. The genetic and other neurobiologic factors leading to the expression of AD+P may exert their effects via acceleration of the neurodegenerative process.

Obesity is associated with lower brain volumes in early Alzheimer’s disease, but its effects on hippocampal volumes are unclear, as weight loss is also associated with Alzheimer’s disease. To address this question, we applied an automated hippocampal mapping method to brain MRI scans for 162 patients with Alzheimer’s disease. We hypothesized that obesity, measured by body mass index, would be associated with lower hippocampal volumes in mildly affected patients. Statistical maps showed a selective pattern of hippocampal volume differences that were significantly associated with body mass index. Associations were detected in the anterior hippocampus, and confirmed by permutation testing. Cardiovascular risk factors, such as high body mass index, may promote additional neurodegenerative changes, and should therefore be considered in epidemiological studies and clinical trials.

Background.

There are few studies on the long-term associations of physical activity (PA) to cognition. Here, we examine the association of midlife PA to late-life cognitive function and dementia.

Methods.

The sample consisted of a population-based cohort of men and women (born in 1907–1935) participating in the Age Gene/Environment Susceptibility—Reykjavik Study. The interval between the midlife ascertainment of PA and late-life cognitive function was 26 years. Composite scores of speed of processing, memory, and executive function were assessed with a battery of neuropsychological tests, and dementia was diagnosed according to international guidelines. There were 4,761 nondemented participants and 184 (3.7%) with a diagnosis of dementia, with complete data for the analysis.

Results.

Among the participants, no midlife PA was reported by 68.8%, ≤5 hours PA by 26.5%, and >5 hours PA by 4.5%. Excluding participants with dementia compared with the no PA group, both PA groups had significantly faster speed of processing (≤5 hours, β = .22; >5 hours, β = .32, p trend < .0001), better memory (≤5 hours, β = .15; >5 hours, β = .18, p trend < .0001), and executive function (≤5 hours, β = .09; >5 hours, β = .18, p trend< .0001), after controlling for demographic and cardiovascular factors. The ≤5 hours PA group was significantly less likely to have dementia in late life (odds ratio: 0.6, 95% confidence interval: 0.40–0.88) after adjusting for confounders.

Conclusion.

Midlife PA may contribute to maintenance of cognitive function and may reduce or delay the risk of late-life dementia.

Background

Large clinical trials databases, developed over the course of a comprehensive clinical trial programme, represent an invaluable resource for clinical researchers. Data mining projects sponsored by industry that use these databases, however, are often not viewed favourably in the academic medical community because of concerns that commercial, rather than scientific, goals are the primary purpose of such endeavours. Thus, there are few examples of sustained collaboration between leading academic clinical researchers and industry professionals in a large-scale data mining project. We present here a successful example of this type of collaboration in the field of dementia.

Methods

The Donepezil Data Repository comprised 18 randomised, controlled trials conducted between 1991 and 2005. The project team at Pfizer determined that the data mining process should be guided by a diverse group of leading Alzheimer's disease clinical researchers called the "Expert Working Group." After development of a list of potential faculty members, invitations were extended and a group of seven members was assembled. The Working Group met regularly with Eisai/Pfizer clinicians and statisticians to discuss the data, identify issues that were currently of interest in the academic and clinical communities that might lend themselves to investigation using these data, and note gaps in understanding or knowledge of Alzheimer's disease that these data could address. Leadership was provided by the Pfizer Clinical Development team leader; Working Group members rotated responsibility for being lead and co-lead for each investigation and resultant publication.

Results

Six manuscripts, each published in a leading subspecialty journal, resulted from the group's work. Another project resulted in poster presentations at international congresses and two were cancelled due to resource constraints.

Conclusions

The experience represents a particular approach to optimising the value of data mining of large clinical trial databases for the combined purpose of furthering clinical research and improving patient care. Fruitful collaboration between industry and academia was fostered while the donepezil data repository was used to advance clinical and scientific knowledge. The Expert Working Group approach warrants consideration as a blueprint for conducting similar research ventures in the future.

Population-based brain mapping provides great insight into the trajectory of aging and dementia, as well as brain changes that normally occur over the human life span. We describe three novel brain mapping techniques, cortical thickness mapping, tensor-based morphometry (TBM), and hippocampal surface modeling, which offer enormous power for measuring disease progression in drug trials, and shed light on the neuroscience of brain degeneration in Alzheimer’s disease (AD) and mild cognitive impairment (MCI).We report the first time-lapse maps of cortical atrophy spreading dynamically in the living brain, based on averaging data from populations of subjects with Alzheimer’s disease and normal subjects imaged longitudinally with MRI. These dynamic sequences show a rapidly advancing wave of cortical atrophy sweeping from limbic and temporal cortices into higher-order association and ultimately primary sensorimotor areas, in a pattern that correlates with cognitive decline. A complementary technique, TBM, reveals the 3D profile of atrophic rates, at each point in the brain. A third technique, hippocampal surface modeling, plots the profile of shape alterations across the hippocampal surface. The three techniques provide moderate to highly automated analyses of images, have been validated on hundreds of scans, and are sensitive to clinically relevant changes in individual patients and groups undergoing different drug treatments. We compare time-lapse maps of AD, MCI, and other dementias, correlate these changes with cognition, and relate them to similar time-lapse maps of childhood development, schizophrenia, and HIV-associated brain degeneration. Strengths and weaknesses of these different imaging measures for basic neuroscience and drug trials are discussed.

Obesity is associated with lower brain volumes in cognitively normal elderly subjects, but no study has yet investigated the effects of obesity on brain structure in patients with mild cognitive impairment (MCI) or Alzheimer’s disease (AD). To determine if higher body mass index (BMI) is associated with brain volume deficits in cognitively impaired elderly subjects, we analyzed brain magnetic resonance imaging (MRI) scans of 700 MCI or AD patients from two different cohorts: the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Cardiovascular Health Study-Cognition Study (CHS-CS). Tensor-based morphometry (TBM) was used to create 3-dimensional maps of regional tissue excess or deficits in subjects with MCI (ADNI, N=399; CHS, N=77) and AD (ADNI, N=188; CHS, N=36). In both AD and MCI groups, higher BMI was associated with brain volume deficits in frontal, temporal, parietal, and occipital lobes; the atrophic pattern was consistent in both ADNI and CHS populations. Cardiovascular risk factors, especially obesity, should be considered as influencing brain structure in those already afflicted by cognitive impairment and dementia.

35% of HIV-infected patients have cognitive impairment, but the profile of HIV-induced brain damage is still not well understood. Here we used tensor-based morphometry (TBM) to visualize brain deficits and clinical/anatomical correlations in HIV/AIDS. To perform TBM, we developed a new MRI-based analysis technique that uses fluid image warping, and a new α-entropy-based information-theoretic measure of image correspondence, called the Jensen–Rényi divergence (JRD).

Methods

3D T1-weighted brain MRIs of 26 AIDS patients (CDC stage C and/or 3 without HIV-associated dementia; 47.2 ± 9.8 years; 25M/1F; CD4+ T-cell count: 299.5 ± 175.7/µl; log10 plasma viral load: 2.57 ± 1.28 RNA copies/ml) and 14 HIV-seronegative controls (37.6 ± 12.2 years; 8M/6F) were fluidly registered by applying forces throughout each deforming image to maximize the JRD between it and a target image (from a control subject). The 3D fluid registration was regularized using the linearized Cauchy–Navier operator. Fine-scale volumetric differences between diagnostic groups were mapped. Regions were identified where brain atrophy correlated with clinical measures.

Results

Severe atrophy (~15–20% deficit) was detected bilaterally in the primary and association sensorimotor areas. Atrophy of these regions, particularly in the white matter, correlated with cognitive impairment (P=0.033) and CD4+ T-lymphocyte depletion (P=0.005).

Conclusion

TBM facilitates 3D visualization of AIDS neuropathology in living patients scanned with MRI. Severe atrophy in frontoparietal and striatal areas may underlie early cognitive dysfunction in AIDS patients, and may signal the imminent onset of AIDS dementia complex.

Background

The modern era of Alzheimer’s disease (AD) research began in the early 1980s with the establishment of AD research centers and expanded research programs at the National Institute on Aging.

Methods

Over the past 30 years, there has been success in defining criteria for AD and dementia, association of important genetic disorders related to premature dementia in families, the association of apolipoprotein-E4, and measurement of incidence and prevalence and selected risk factors. However, prevention and treatment have been elusive.

Results

The development of new technologies, especially magnetic resonance imaging, positron emission tomography to measure amyloid in vivo in the brain and glucose metabolism, cerebrospinal fluid examination, better genetic markers, large-scale longitudinal epidemiology studies, and preventive clinical trials has rapidly begun a new era of research that offers opportunities to better understand etiology, that is, determinants of amyloid biology in the brain, neurofibrillary tangles, synaptic loss, and dementia.

Conclusions

There are three major hypotheses related to dementia: amyloid deposition and secondary synaptic loss as a unique disease, vascular injury, and “aging.” New research must be hypothesis-driven and lead to testable approaches for treatment and prevention.

Approximately 50% of late-onset Alzheimer's disease (AD) patients develop psychosis (AD+P), a heritable phenotype associated with more rapid cognitive decline. Prior studies conflict regarding whether apolipoprotein E (APOE) ϵ4 alleles are associated with AD+P, possibly due to small sample sizes, inconsistent diagnostic criteria, and different methodologies to assess psychosis. We used the National Alzheimer's Coordinating Center Uniform Data Set to evaluate the largest uniformly characterized sample of AD+P subjects studied to date for the association of APOE ϵ4 genotype, along with other demographic and clinical variables. Greater cognitive impairment and depressive symptoms were associated with AD+P, while the Caucasian race was protective. Neither APOE ϵ4 carrier status nor allele number was associated with psychosis. The AD+P phenotype is not associated with the APOE ϵ4 genotype. AD+P may represent a useful phenotype for the discovery of non-APOE ϵ4 genetic variation contributing to the risk of AD.

Obesity is associated with increased risk for cardiovascular health problems including diabetes, hypertension, and stroke. These cardiovascular afflictions increase risk for cognitive decline and dementia, but it is unknown whether these factors, specifically obesity and type II diabetes, are associated with specific patterns of brain atrophy. We used tensor-based morphometry (TBM) to examine gray matter (GM) and white matter (WM) volume differences in 94 elderly subjects who remained cognitively normal for at least 5 years after their scan. Bivariate analyses with corrections for multiple comparisons strongly linked body mass index (BMI), fasting plasma insulin (FPI) levels, and Type II Diabetes Mellitus (DM2) with atrophy in frontal, temporal, and subcortical brain regions. A multiple regression model, also correcting for multiple comparisons, revealed that BMI was still negatively correlated with brain atrophy (FDR < 5%), while DM2 and FPI were no longer associated with any volume differences. In an Analysis of Covariance (ANCOVA) model controlling for age, gender, and race, obese subjects with a high BMI (BMI > 30) showed atrophy in the frontal lobes, anterior cingulate gyrus, hippocampus, and thalamus compared to individuals with a normal BMI (18.5–25). Overweight subjects (BMI: 25–30) had atrophy in the basal ganglia and corona radiata of the WM. Overall brain volume did not differ between overweight and obese persons. Higher body mass index was associated with lower brain volumes in overweight and obese elderly subjects. Obesity is therefore associated with detectable brain volume deficits in cognitively normal elderly subjects.

Background

Late-onset Alzheimer disease (LOAD) is a clinically heterogeneous complex disease defined by progressively disabling cognitive impairment. Psychotic symptoms which affect approximately one-half of LOAD subjects have been associated with more rapid cognitive decline. However, the variety of cognitive trajectories in LOAD, and their correlates have not been well defined. We therefore used latent class modeling to characterize trajectories of cognitive and behavioral decline in a cohort of AD subjects.

Methods

201 Caucasian subjects with possible or probable AD were evaluated for cognitive and psychotic symptoms at regular intervals for up to 13.5 years. Cognitive symptoms were evaluated serially with the Mini-Mental State Examination (MMSE), and psychotic symptoms were rated using the CERAD behavioral rating scale (CBRS). Analyses undertaken were latent class mixture models of quadratic trajectories including a random intercept, with initial MMSE score, age, gender, education, and APOE ε4 count modeled as concomitant variables. In a secondary analysis, psychosis status was also included.

Results

AD subjects showed six trajectories with significantly different courses and rates of cognitive decline. The concomitant variables included in the best latent class trajectory model were initial MMSE and age. Greater burden of psychotic symptoms increased the probability of following a trajectory of more rapid cognitive decline in all age and initial MMSE groups. APOE ε4 was not associated with any trajectory.

Conclusion

Trajectory modeling of longitudinal cognitive and behavioral data may provide enhanced resolution of phenotypic variation in Alzheimer disease.

Here we developed a new method, called multivariate tensor-based surface morphometry (TBM), and applied it to study lateral ventricular surface differences associated with HIV/AIDS. Using concepts from differential geometry and the theory of differential forms, we created mathematical structures known as holomorphic one-forms, to obtain an efficient and accurate conformal parameterization of the lateral ventricular surfaces in the brain. The new meshing approach also provides a natural way to register anatomical surfaces across subjects, and improves on prior methods as it handles surfaces that branch and join at complex 3D junctions. To analyze anatomical differences, we computed new statistics from the Riemannian surface metrics - these retain multivariate information on local surface geometry. We applied this framework to analyze lateral ventricular surface morphometry in 3D MRI data from 11 subjects with HIV/AIDS and 8 healthy controls. Our method detected a 3D profile of surface abnormalities even in this small sample. Multivariate statistics on the local tensors gave better effect sizes for detecting group differences, relative to other TBM-based methods including analysis of the Jacobian determinant, the largest and smallest eigenvalues of the surface metric, and the pair of eigenvalues of the Jacobian matrix. The resulting analysis pipeline may improve the power of surface-based morphometry studies of the brain.

Background

Accumulating evidence suggests that ginkgo biloba is cardioprotective, in part, through its vasodilatory and antihypertensive properties. However, definitive data on its blood pressure-lowering effects in humans is lacking.

Methods

We determined the effects of ginkgo biloba extract (240 mg/day) on blood pressure and incident hypertension in 3,069 participants (mean age, 79 yrs; 46% female; 96% White) from the Ginkgo Evaluation of Memory study. We also examined whether the treatment effects are modified by baseline hypertension status.

Results

At baseline 54% of the study participants were hypertensive, 28% were pre-hypertensive, and 17% were normotensive. Over a median follow-up of 6.1 years, there were similar changes in blood pressure and pulse pressure in the ginkgo biloba and placebo groups. Although baseline hypertension status did not modify the antihypertensive effects of ginkgo biloba, it did influence the changes in blood pressure variables observed during follow-up, with decreases in hypertensives, increases in normotensives, and no changes in pre-hypertensives. Among participants who were not on antihypertensive medications at baseline, there was no difference between treatment groups in medication use over time, as the OR (95% CI) for being a never-user in the ginkgo biloba group was 0.75 (0.48–1.16). The rate of incident hypertension also did not differ between participants assigned to ginkgo biloba vs. placebo (HR, 0.99, 95% CI, 0.84–1.15).

Conclusions

Our data indicate that ginkgo biloba does not reduce blood pressure or the incidence of hypertension in elderly men and women.