Accuracy of clinical criteria for AD in the Honolulu-Asia Aging Study, a population-based study

A systematic review/meta-analysis of prevalence and incidence rates illustrates systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research

We investigate Alzheimer's disease and related dementia (ADRD) prevalence, incidence rate, and risk factors in individuals racialized as Asian and/or Asian-American and assess sample representation. Prevalence, incidence rate, risk factors, and heterogeneity of samples were assessed. Random-effects meta-analysis was conducted, generating pooled estimates. Of 920 records across 14 databases, 45 studies were included. Individuals racialized as Asian and/or Asian-American were mainly from Eastern and Southern Asia, had higher education, and constituted a smaller sample relative to non-Hispanic white cohorts. The average prevalence was 10.9%, ranging from 0.4% to 46%. The average incidence rate was 20.03 (12.01-33.8) per 1000 person-years with a range of 75.19-13.59 (12.89-14.33). Risk factors included physiological, genetic, psychological, behavioral, and social factors. This review underscores the systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research and the need for inclusive approaches accounting for culture, language, and immigration status. HIGHLIGHTS: There is considerable heterogeneity in the prevalence of ADRD among studies of Asian-Americans. There is limited data on group-specific risk factors for ADRD among Asian-Americans. The average prevalence of (ADRD) among Asian-Americans was found to be 7.4%, with a wide range from 0.5% to 46%.

Quantification of race/ethnicity representation in Alzheimer's disease neuroimaging research in the USA: a systematic review

BACKGROUND

Racial and ethnic minoritized groups are disproportionately at risk for Alzheimer's Disease (AD), but are not sufficiently recruited in AD neuroimaging research in the United States. This is important as sample composition impacts generalizability of findings, biomarker cutoffs, and treatment effects. No studies have quantified the breadth of race/ethnicity representation in the AD literature.

METHODS

This review identified median race/ethnicity composition of AD neuroimaging US-based research samples available as free full-text articles on PubMed. Two types of published studies were analyzed: studies that directly report race/ethnicity data (i.e., direct studies), and studies that do not report race/ethnicity but used data from a cohort study/database that does report this information (i.e., indirect studies).

RESULTS

Direct studies (n = 719) have median representation of 88.9% white or 87.4% Non-Hispanic white, 7.3% Black/African American, and 3.4% Hispanic/Latino ethnicity, with 0% Asian American, Native Hawaiian/Pacific Islander, and American Indian/Alaska Native, Multiracial, and Other Race participants. Cohort studies/databases (n = 44) from which indirect studies (n = 1745) derived are more diverse, with median representation of 84.2% white, 83.7% Non-Hispanic white, 11.6% Black/African American, 4.7% Hispanic/Latino, and 1.75% Asian American participants. Notably, 94% of indirect studies derive from just 10 cohort studies/databases. Comparisons of two time periods using a median split for publication year, 1994-2017 and 2018-2022, indicate that sample diversity has improved recently, particularly for Black/African American participants (3.39% from 1994-2017 and 8.29% from 2018-2022).

CONCLUSIONS

There is still underrepresentation of all minoritized groups relative to Census data, especially for Hispanic/Latino and Asian American individuals. The AD neuroimaging literature will benefit from increased representative recruitment of ethnic/racial minorities. More transparent reporting of race/ethnicity data is needed.

Mid- and later-life risk factors for predicting neuropathological brain changes associated with Alzheimer's and vascular dementia: The Honolulu Asia Aging Study and the Age, Gene/Environment Susceptibility-Reykjavik Study

INTRODUCTION

Dementia prediction models are necessary to inform the development of dementia risk reduction strategies. Here, we examine the utility of neuropathological-based risk scores to predict clinical dementia.

METHODS

Models were developed for predicting Alzheimer's disease (AD) and non-AD neuropathologies using the Honolulu Asia Aging neuropathological sub-study (HAAS; n = 852). Model accuracy for predicting clinical dementia, over 30 years, was tested in the non-autopsied HAAS sample (n = 2960) and the Age, Gene/Environment Susceptibility-Reykjavik Study (n = 4614).

RESULTS

Different models were identified for predicting neurodegenerative and vascular neuropathology (c-statistic range: 0.62 to 0.72). These typically included age, APOE, and a blood pressure-related measure. The neurofibrillary tangle and micro-vascular lesion models showed good accuracy for predicting clinical vascular dementia.

DISCUSSION

There may be shared risk factors across dementia-related lesions, suggesting common pathways. Strategies targeting these models may reduce risk or postpone clinical symptoms of dementia as well as reduce neuropathological burden associated with AD and vascular lesions.

When Does Alzheimer's Disease Really Start? The Role of Biomarkers

(Appeared originally in Int J Mol Sci 2019, 20 5536).

Voxel-based morphometry focusing on medial temporal lobe structures has a limited capability to detect amyloid β, an Alzheimer's disease pathology

Voxel-based morphometry (VBM) analysis of nuclear Magnetic Resonance Imaging (MRI) data allows the identification of medial temporal lobe (MTL) atrophy and is widely used to assist the diagnosis of Alzheimer's disease (AD). However, its reliability in the clinical environment has not yet been confirmed. To determine the credibility of VBM, amyloid positron emission tomography (PET) and VBM studies were compared retrospectively. Patients who underwent Pittsburgh Compound B (PiB) PET were retrospectively recruited. Ninety-seven patients were found to be amyloid negative and 116 were amyloid positive. MTL atrophy in the PiB positive group, as quantified by thin sliced 3D MRI and VBM software, was significantly more severe (p =0.0039) than in the PiB negative group. However, data histogram showed a vast overlap between the two groups. The area under the ROC curve (AUC) was 0.646. MMSE scores of patients in the amyloid negative and positive groups were also significantly different (p = 0.0028), and the AUC was 0.672. Thus, MTL atrophy could not reliably differentiate between amyloid positive and negative patients in a clinical setting, possibly due to the wide array of dementia-type diseases that exist other than AD.

Age-stratified longitudinal study of Alzheimer's and vascular dementia patients

INTRODUCTION

Similar symptoms, comorbidities and suboptimal diagnostic tests make the distinction between different types of dementia difficult, although this is essential for improved work-up and treatment optimization.

METHODS

We calculated temporal disease trajectories of earlier multi-morbidities in Alzheimer's disease (AD) dementia and vascular dementia (VaD) patients using the Danish National Patient Registry covering all hospital encounters in Denmark (1994 to 2016). Subsequently, we reduced the comorbidity space dimensionality using a non-linear technique, uniform manifold approximation and projection.

RESULTS

We found 49,112 and 24,101 patients that were diagnosed with AD or VaD, respectively. Temporal disease trajectories showed very similar disease patterns before the dementia diagnosis. Stratifying patients by age and reducing the comorbidity space to two dimensions, showed better discrimination between AD and VaD patients in early-onset dementia.

DISCUSSION

Similar age-associated comorbidities, the phenomenon of mixed dementia, and misdiagnosis create great challenges in discriminating between classical subtypes of dementia.

Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review

Alzheimer's Disease (AD) is one of the leading causes of death in developed countries. From a research point of view, impressive results have been reported using computer-aided algorithms, but clinically no practical diagnostic method is available. In recent years, deep models have become popular, especially in dealing with images. Since 2013, deep learning has begun to gain considerable attention in AD detection research, with the number of published papers in this area increasing drastically since 2017. Deep models have been reported to be more accurate for AD detection compared to general machine learning techniques. Nevertheless, AD detection is still challenging, and for classification, it requires a highly discriminative feature representation to separate similar brain patterns. This paper reviews the current state of AD detection using deep learning. Through a systematic literature review of over 100 articles, we set out the most recent findings and trends. Specifically, we review useful biomarkers and features (personal information, genetic data, and brain scans), the necessary pre-processing steps, and different ways of dealing with neuroimaging data originating from single-modality and multi-modality studies. Deep models and their performance are described in detail. Although deep learning has achieved notable performance in detecting AD, there are several limitations, especially regarding the availability of datasets and training procedures.

An Automatic Assessment System for Alzheimer's Disease Based on Speech Using Feature Sequence Generator and Recurrent Neural Network

Alzheimer disease and other dementias have become the 7th cause of death worldwide. Still lacking a cure, an early detection of the disease in order to provide the best intervention is crucial. To develop an assessment system for the general public, speech analysis is the optimal solution since it reflects the speaker's cognitive skills abundantly and data collection is relatively inexpensive compared with brain imaging, blood testing, etc. While most of the existing literature extracted statistics-based features and relied on a feature selection process, we have proposed a novel Feature Sequence representation and utilized a data-driven approach, namely, the recurrent neural network to perform classification in this study. The system is also shown to be fully-automated, which implies the system can be deployed widely to all places easily. To validate our study, a series of experiments have been conducted with 120 speech samples, and the score in terms of the area under the receiver operating characteristic curve is as high as 0.838.

When Does Alzheimer's Disease Really Start? The Role of Biomarkers

While Alzheimer’s disease (AD) classical diagnostic criteria rely on clinical data from a stablished symptomatic disease, newer criteria aim to identify the disease in its earlier stages. For that, they incorporated the use of AD’s specific biomarkers to reach a diagnosis, including the identification of Aβ and tau depositions, glucose hypometabolism, and cerebral atrophy. These biomarkers created a new concept of the disease, in which AD’s main pathological processes have already taken place decades before we can clinically diagnose the first symptoms. Therefore, AD is now considered a dynamic disease with a gradual progression, and dementia is its final stage. With that in mind, new models were proposed, considering the orderly increment of biomarkers and the disease as a continuum, or the variable time needed for the disease’s progression. In 2011, the National Institute on Aging and the Alzheimer’s Association (NIA-AA) created separate diagnostic recommendations for each stage of the disease continuum—preclinical, mild cognitive impairment, and dementia. However, new scientific advances have led them to create a unifying research framework in 2018 that, although not intended for clinical use as of yet, is a step toward shifting the focus from the clinical symptoms to the biological alterations and toward changing the future diagnostic and treatment possibilities. This review aims to discuss the role of biomarkers in the onset of AD.

Excessive daytime sleepiness and topographic expansion of Lewy pathology

OBJECTIVE

While excessive daytime sleepiness (EDS) can predate the clinical diagnosis of Parkinson disease (PD), associations with underlying PD pathogenesis are unknown. Our objective is to determine if EDS is related to brain Lewy pathology (LP), a marker of PD pathogenesis, using clinical assessments of EDS with postmortem follow-up.

METHODS

Identification of LP was based on staining for α-synuclein in multiple brain regions in a sample of 211 men. Data on EDS were collected at clinical examinations from 1991 to 1999 when participants were aged 72-97 years.

RESULTS

Although EDS was more common in the presence vs absence of LP (p = 0.034), the association became stronger in neocortical regions. When LP was limited to the olfactory bulb, brainstem, and basal forebrain (Braak stages 1-4), frequency of EDS was 10% (4/40) vs 17.5% (20/114) in decedents without LP (p = 0.258). In contrast, compared to the absence of LP, EDS frequency doubled (36.7% [11/30], p = 0.023) when LP reached the anterior cingulate gyrus, insula mesocortex, and midfrontal, midtemporal, and inferior parietal neocortex (Braak stage 5). With further infiltration into the primary motor and sensory neocortices (Braak stage 6), EDS frequency increased threefold (51.9% [14/27], p < 0.001). Findings were similar across sleep-related features and persisted after adjustment for age and other covariates, including the removal of PD and dementia with Lewy bodies.

CONCLUSIONS

The association between EDS and PD includes relationships with extensive topographic LP expansion. The neocortex could be especially vulnerable to adverse relationships between sleep disorders and aggregation of misfolded α-synuclein and LP formation.

Most cases with Lewy pathology in a population-based cohort adhere to the Braak progression pattern but 'failure to fit' is highly dependent on staging system applied

Braak et al.'s 2003 paper detailing the caudo-rostral progression of Lewy body pathology (LP) formed the foundation of current understanding of disease spread in Parkinson's disease (PD); however, its methods are difficult to recreate and consequently multiple new staging systems emerged to recapitulate Braak's staging system using standard neuropathological methods and to account for other patterns of LP. Studies using these systems have documented widely variable rates of cases that 'fail to fit' expected patterns of LP spread. This could be due to population differences, features of individual systems, or may constitute under-recognized patterns of disease. We examined 324 neuropathological cases from the Honolulu Asia Aging Study and applied four different LP staging systems to determine the proportion of cases adhering to different staging methodologies and those that 'fail to fit' expected patterns of LP. Of 141 cases with LP (24: PD, 8: Dementia with Lewy bodies (DLB), 109: Incidental Lewy body disease (ILBD)), our application of Braak et al., 2003 classified 83.7%, Müller et al., 2005 classified 87.9%, Beach et al., 2009 classified 100%, and Leverenz et al., 2008 classified 98.6%. There were significant differences in the cases classifiable by the Leverenz and Beach systems versus the Braak and Müller systems (p < 0.001 for each). In this population-based autopsy cohort with a high prevalence of ILBD, the majority of cases were consistent with the progression characterized by the Braak et al. however, the determination of cases as atypical is highly dependent on the staging system applied.

Association of brain heptachlor epoxide and other organochlorine compounds with lewy pathology

BACKGROUND

Organochlorine pesticides are associated with an increased risk of Parkinson's disease. A preliminary analysis from the Honolulu-Asia Aging Study suggested that heptachlor epoxide, a metabolite from an organochlorine pesticide extensively used in Hawaii, may be especially important. This was a cross sectional analysis to evaluate the association of heptachlor epoxide and other organochlorine compounds with Lewy pathology in an expanded survey of brain organochlorine residues from the longitudinal Honolulu-Asia Aging Study.

METHODS

Organochlorines were measured in frozen occipital or temporal lobes in 705 brains using gas chromatography with mass spectrometry. Lewy pathology was identified using hematoxylin and eosin- and α-synuclein immunochemistry-stained sections from multiple brain regions.

RESULTS

The prevalence of Lewy pathology was nearly doubled in the presence versus the absence of heptachlor epoxide (30.1% versus 16.3%, P < 0.001). Although associations with other compounds were weaker, hexachlorobenzene (P = 0.003) and α-chlordane (P = 0.007) were also related to Lewy pathology. Most of the latter associations, however, were a result of confounding from heptachlor epoxide. Neither compound was significantly related to Lewy pathology after adjustment for heptachlor epoxide. In contrast, the association of heptachlor epoxide with Lewy pathology remained significant after adjustments for hexachlorobenzene (P = 0.013) or α-chlordane (P = 0.005). Findings were unchanged after removal of cases of PD and adjustment for age and other characteristics.

CONCLUSIONS

Organochlorine pesticides are associated with the presence of Lewy pathology in the brain, even after exclusion of PD cases. Although most of the association is through heptachlor epoxide, the role of other organochlorine compounds is in need of clarification. © 2018 International Parkinson and Movement Disorder Society.

Neurodegenerative Diseases: Regenerative Mechanisms and Novel Therapeutic Approaches

Regeneration refers to regrowth of tissue in the central nervous system. It includes generation of new neurons, glia, myelin, and synapses, as well as the regaining of essential functions: sensory, motor, emotional and cognitive abilities. Unfortunately, regeneration within the nervous system is very slow compared to other body systems. This relative slowness is attributed to increased vulnerability to irreversible cellular insults and the loss of function due to the very long lifespan of neurons, the stretch of cells and cytoplasm over several dozens of inches throughout the body, insufficiency of the tissue-level waste removal system, and minimal neural cell proliferation/self-renewal capacity. In this context, the current review summarized the most common features of major neurodegenerative disorders; their causes and consequences and proposed novel therapeutic approaches.

Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies

Dementia can result from a number of distinct diseases with differing etiology and pathophysiology. Even within the same disease, there is considerable phenotypic heterogeneity with varying symptoms and disease trajectories. Dementia diagnosis is thus very complex, time-consuming, and expensive and can only be made definitively post-mortem with histopathological confirmation. These inherent difficulties combined with the overlap of some symptoms and even neuropathological features, present a challenging problem for research in the field. This has likely hampered progress in epidemiological studies of risk factors and preventative interventions, as well as genetic and biomarker research. Resource limitations in large epidemiologically studies mean that limited diagnostic criteria are often used, which can result in phenotypically heterogeneous disease states being grouped together, potentially resulting in misclassification bias. When biomarkers are identified for etiologically heterogeneous diseases, they will have low specificity for any utility in clinical practice, even if their sensitivity is high. We highlight several challenges in in the field which must be addressed for the success of future genetic and biomarker studies, and may be key to the development of the most effective treatments. As a step toward achieving this goal, defining the dementia as a biological construct based on the presence of specific pathological features, rather than clinical symptoms, will enable more precise predictive models. It has the potential to lead to the discovery of novel genetic variants, as well as the identification of individuals at heightened risk of the disease, even prior to the appearance of clinical symptoms.

Excess Costs Associated with Possible Misdiagnosis of Alzheimer's Disease Among Patients with Vascular Dementia in a UK CPRD Population

BACKGROUND

Prior diagnosis of Alzheimer's disease (AD) among patients later diagnosed with vascular dementia (VaD) has been associated with excess costs, suggesting potential benefits of earlier rule-out of AD diagnosis.

OBJECTIVE

To investigate whether prior diagnosis with AD among patients with VaD is associated with excess costs in the UK.

METHODS

Patients with a final VaD diagnosis, continuous data visibility for≥6 months prior to index date, and linkage to Hospital Episode Statistics data were retrospectively selected from de-identified Clinical Practice Research Datalink data. Patients with AD diagnosis before a final VaD diagnosis were matched to similar patients with no prior AD diagnosis using propensity score methods. Annual excess healthcare costs were calculated for 5 years post-index, stratified by time to final diagnosis.

RESULTS

Of 9,311 patients with VaD, 508 (6%) had prior AD diagnosis with a median time to VaD diagnosis exceeding 2 years from index date. Over the entire follow-up period, patients with prior AD diagnosis had accumulated healthcare costs that were approximately GBP2,000 higher than those for matched counterparts (mostly due to higher hospitalization costs). Cost differentials peaked particularly in the period including the final VaD diagnosis, with excess costs quickly declining thereafter.

CONCLUSION

Potential misdiagnosis of AD among UK patients with VaD resulted in substantial excess costs. The decline in excess costs following a final VaD diagnosis suggests potential benefits from earlier rule-out of AD.

Mixed dementia: A review of the evidence

Mixed dementia is the coexistence of Alzheimer's disease and cerebrovascular disease (CVD) in the same demented patient. Currently, its diagnosis and treatment remains a challenge for practitioners. To provide an overview of the epidemiology, pathogenesis, natural history, diagnosis, and therapy of Mixed Vascular-Alzheimer Dementia (MVAD). The literature was reviewed for articles published between 1990-2016 by using the keywords linked to MVAD. Neuropathological studies indicate that MVAD is a very common pathological finding in the elderly with a prevalence about of 22%. The distinction between Alzheimer's dementia and vascular dementia (VD) is complex because their clinical presentation can overlap. There are international criteria for the MVAD diagnosis. The pharmacologic therapy shows modest clinical benefits that are similar among all drugs used in patients with Alzheimer's dementia and VD. The non-pharmacologic therapy includes the rigorous management of cardiovascular risk factors (especially hypertension) and the promotion of a healthy diet. The diagnosis and treatment of MVAD cannot be improved without further studies. Currently available medications provide only modest clinical benefits once a patient has developed MVAD. In subjects at risk, the antihypertensive therapy and healthy diet should be recommend for preventing or slowing the progression of MVAD.

Erythrocytes as Potential Link between Diabetes and Alzheimer's Disease

Many studies support the existence of an association between type 2 diabetes (T2DM) and Alzheimer's disease (AD). In AD, in addition to brain, a number of peripheral tissues and cells are affected, including red blood cell (RBC) and because there are currently no reliable diagnostic biomarkers of AD in the blood, a gradually increasing attention has been given to the study of RBC's alterations. Recently it has been evidenced in diabetes, RBC alterations superimposable to the ones occurring in AD RBC. Furthermore, growing evidence suggests that oxidative stress plays a pivotal role in the development of RBC's alterations and vice versa. Once again this represents a further evidence of a shared pathway between AD and T2DM. The present review summarizes the two disorders, highlighting the role of RBC in the postulated common biochemical links, and suggests RBC as a possible target for clinical trials.

Factors Influencing Clinical Correlates of Chronic Traumatic Encephalopathy (CTE): a Review

Chronic traumatic encephalopathy (CTE) is a neuropathologically defined disease reportedly linked to a history of repetitive brain trauma. As such, retired collision sport athletes are likely at heightened risk for developing CTE. Researchers have described distinct pathological features of CTE as well a wide range of clinical symptom presentations, recently termed traumatic encephalopathy syndrome (TES). These clinical symptoms are highly variable, non-specific to individuals described as having CTE pathology in case reports, and are often associated with many other factors. This review describes the cognitive, emotional, and behavioral changes associated with 1) developmental and demographic factors, 2) neurodevelopmental disorders, 3) normal aging, 4) adjusting to retirement, 5) drug and alcohol abuse, 6) surgeries and anesthesia, and 7) sleep difficulties, as well as the relationship between these factors and risk for developing dementia-related neurodegenerative disease. We discuss why some professional athletes may be particularly susceptible to many of these effects and the importance of choosing appropriate controls groups when designing research protocols. We conclude that these factors should be considered as modifiers predominantly of the clinical outcomes associated with repetitive brain trauma within a broader biopsychosocial framework when interpreting and attributing symptom development, though also note potential effects on neuropathological outcomes. Importantly, this could have significant treatment implications for improving quality of life.

Clinical Amyloid Imaging

Amyloid plaques, along with neurofibrillary tangles, are a neuropathologic hallmark of Alzheimer disease (AD). Recently, amyloid PET radiotracers have been developed and approved for clinical use in the evaluation of suspected neurodegenerative disorders. In both research and clinical settings, amyloid PET imaging has provided important diagnostic and prognostic information for the management of patients with possible AD, mild cognitive impairment (MCI), and other challenging diagnostic presentations. Although the overall impact of amyloid imaging is still being evaluated, the Society of Nuclear Medicine and Molecular Imaging and Alzheimer's Association Amyloid Imaging Task Force have created appropriate use criteria for the standard clinical use of amyloid PET imaging. By the appropriate use criteria, amyloid imaging is appropriate for patients with (1) persistent or unexplained MCI, (2) AD as a possible but still uncertain diagnosis after expert evaluation and (3) atypically early-age-onset progressive dementia. To better understand the clinical and economic effect of amyloid imaging, the Imaging Dementia-Evidence for Amyloid Scanning (IDEAS) study is an ongoing large multicenter study in the United States, which is evaluating how amyloid imaging affects diagnosis, management, and outcomes for cognitively impaired patients who cannot be completely evaluated by clinical assessment alone. Multiple other large-scale studies are evaluating the prognostic role of amyloid PET imaging for predicting MCI progression to AD in general and high-risk populations. At the same time, amyloid imaging is an important tool for evaluating potential disease-modifying therapies for AD. Overall, the increased use of amyloid PET imaging has led to a better understanding of the strengths and limitations of this imaging modality and how it may best be used with other clinical, molecular, and imaging assessment techniques for the diagnosis and management of neurodegenerative disorders.

Alzheimer's Disease Normative Cerebrospinal Fluid Biomarkers Validated in PET Amyloid-β Characterized Subjects from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study

BACKGROUND

The cerebrospinal fluid (CSF) amyloid-β (Aβ)(1-42), total-tau (T-tau), and phosphorylated-tau (P-tau181P) profile has been established as a valuable biomarker for Alzheimer's disease (AD).

OBJECTIVE

The current study aimed to determine CSF biomarker cut-points using positron emission tomography (PET) Aβ imaging screened subjects from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, as well as correlate CSF analyte cut-points across a range of PET Aβ amyloid ligands.

METHODS

Aβ pathology was determined by PET imaging, utilizing ¹¹C-Pittsburgh Compound B, ¹⁸F-flutemetamol, or ¹⁸F-florbetapir, in 157 AIBL participants who also underwent CSF collection. Using an INNOTEST assay, cut-points were established (Aβ(1-42) >544 ng/L, T-tau <407 ng/L, and P-tau181P <78 ng/L) employing a rank based method to define a "positive" CSF in the sub-cohort of amyloid-PET negative healthy participants (n = 97), and compared with the presence of PET demonstrated AD pathology.

RESULTS

CSF Aβ(1-42) was the strongest individual biomarker, detecting cognitively impaired PET positive mild cognitive impairment (MCI)/AD with 85% sensitivity and 91% specificity. The ratio of P-tau181P or T-tau to Aβ(1-42) provided greater accuracy, predicting MCI/AD with Aβ pathology with ≥92% sensitivity and specificity. Cross-validated accuracy, using all three biomarkers or the ratio of P-tau or T-tau to Aβ(1-42) to predict MCI/AD, reached ≥92% sensitivity and specificity.

CONCLUSIONS

CSF Aβ(1-42) levels and analyte combination ratios demonstrated very high correlation with PET Aβ imaging. Our study offers additional support for CSF biomarkers in the early and accurate detection of AD pathology, including enrichment of patient cohorts for treatment trials even at the pre-symptomatic stage.

The New Criteria for Alzheimer's Disease - Implications for Geriatricians

Two new sets of criteria for Alzheimer’s disease (AD) are now in play, including one set released in 2014, and a proposal for a “new lexicon” for how to describe the disease spectrum. A 2012 Canadian consensus conference said that to then, none of the new criteria or terminology would change primary care practice; that is still likely to be so. For dementia consultants, however, the new criteria pose challenges and offer opportunities.

In general, the new criteria see an expanded role for bio-markers. Even so, the evidence base for this remains incomplete. Our understanding of the neuropathological criteria for dementia changed as the evidence base included more community cases. This is likely to inform the experience with biomarkers. At present, each of the criteria specifies an exclusive research role. Still, wider uptake is likely, especially in the United States.

Geriatricians should be aware of the fundamental change in the terminology now being employed: AD diagnosis no longer obliges a diagnosis of dementia. Until more data emerge—something to which geriatricians can contribute—there is reason to be cautious in the adoption of the new criteria, as they are likely to be least applicable to older adults.

[Not Available]

Deux nouvelles séries de critères pour le diagnostic de la maladie d’Alzheimer sont maintenant en vigueur, incluant une série publiée en 2014. Un « nouveau lexique » conceptualisant la maladie a également été proposé. En 2012, la Conférence consensuelle canadienne affirmait que, pour l’instant, ni les nouveaux critères ni la nouvelle terminologie ne modifiaient la pratique en première ligne. Néanmoins, pour les consultants spécialisés en démence, l’avènement de ces critères ouvre la porte à de nombreux défis et occasions.

En général, les nouveaux critères accordent une place grandissante aux biomarqueurs. Toutefois, les évidences qui sous-tendent leur utilisation demeurent incomplètes. L’étude de sujets provenant de la communauté ayant raffiné notre compréhension des critères neuropathologiques des démences, il est probable que notre expérience avec les biomarqueurs en bénéficierait également. Pour l’instant, ces critères sont réservés à la recherche. Cependant, leur adoption à plus large échelle est pressentie, particulièrement aux États-Unis.

Les gériatres canadiens doivent être conscients de la terminologie maintenant utilisée et du changement fondamental qui en découle : un diagnostic de maladie d’Alzheimer ne requiert plus un diagnostic de démence. Dans l’attente de nouvelles données – auxquelles les gériatres peuvent contribuer – il y a lieu de faire preuve de prudence dans l’adoption des nouveaux critères, car ils sont susceptibles de moins bien s’appliquer aux personnes âgées.

Midlife milk consumption and substantia nigra neuron density at death

OBJECTIVE

To examine the relationship between midlife milk intake and Parkinson disease (PD) incidence through associations with substantia nigra (SN) neuron density and organochlorine pesticide exposure in decedent brains from the Honolulu-Asia Aging Study.

METHODS

Milk intake data were collected from 1965 to 1968 in 449 men aged 45-68 years with postmortem examinations from 1992 to 2004. Neuron density (count/mm(2)) was measured in quadrants from a transverse section of the SN. Additional measures included brain residues of heptachlor epoxide, an organochlorine pesticide found at excessively high levels in the milk supply in Hawaii in the early 1980s.

RESULTS

Neuron density was lowest in nonsmoking decedents who consumed high amounts of milk (>16 oz/d). After removing cases of PD and dementia with Lewy bodies, adjusted neuron density in all but the dorsomedial quadrant was 41.5% lower for milk intake >16 oz/d vs intake that was less (95% confidence interval 22.7%-55.7%, p < 0.001). Among those who drank the most milk, residues of heptachlor epoxide were found in 9 of 10 brains as compared to 63.4% (26/41) for those who consumed no milk (p = 0.017). For those who were ever smokers, an association between milk intake and neuron density was absent.

CONCLUSIONS

Milk intake is associated with SN neuron loss in decedent brains unaffected by PD. Whether contamination of milk with organochlorine pesticides has a role in SN neurodegeneration warrants further study.

Florbetapir F18 PET Amyloid Neuroimaging and Characteristics in Patients With Mild and Moderate Alzheimer Dementia

BACKGROUND

Clinical diagnosis of Alzheimer disease (AD) is challenging, with a 70.9%-87.3% sensitivity and 44.3%-70.8% specificity, compared with autopsy diagnosis. Florbetapir F18 positron emission tomography (FBP-PET) estimates beta-amyloid plaque density antemortem.

METHODS

Of 2052 patients (≥55 years old) clinically diagnosed with mild or moderate AD dementia from 2 solanezumab clinical trials, 390 opted to participate in a FBP-PET study addendum. We analyzed baseline prerandomization characteristics.

RESULTS

A total of 22.4% had negative FBP-PET scans, whereas 72.5% of mild and 86.9% of moderate AD patients had positive results. No baseline clinical variable reliably differentiated negative from positive FBP-PET scan groups.

CONCLUSIONS

These data confirm the challenges of correctly diagnosing AD without using biomarkers. FBP-PET can aid AD dementia differential diagnosis by detecting amyloid pathology antemortem, even when the diagnosis of AD is made by expert clinicians.

Medical costs of Alzheimer's disease misdiagnosis among US Medicare beneficiaries

INTRODUCTION

Recent developments in diagnostic technology can support earlier, more accurate diagnosis of non-Alzheimer's disease (AD) dementias.

METHODS

To evaluate potential economic benefits of early rule-out of AD, annual medical resource use and costs for Medicare beneficiaries potentially misdiagnosed with AD prior to their diagnosis of vascular dementia (VD) or Parkinson's disease (PD) were compared with that of similar patients never diagnosed with AD.

RESULTS

Patients with prior AD diagnosis used substantially more medical services every year until their VD/PD diagnosis, resulting in incremental annual medical costs of approximately $9,500-$14,000. However, following their corrected diagnosis, medical costs converged with those of patients never diagnosed with AD.

DISCUSSION

The observed correlation between timing of correct diagnosis and subsequent reversal in excess costs is strongly suggestive of the role of misdiagnosis of AD - rather than AD comorbidity - in this patient population. Our findings suggest potential benefits from earlier, accurate diagnosis.

Feature Selection Based on the SVM Weight Vector for Classification of Dementia

Computer-aided diagnosis of dementia using a support vector machine (SVM) can be improved with feature selection. The relevance of individual features can be quantified from the SVM weights as a significance map (p-map). Although these p-maps previously showed clusters of relevant voxels in dementia-related brain regions, they have not yet been used for feature selection. Therefore, we introduce two novel feature selection methods based on p-maps using a direct approach (filter) and an iterative approach (wrapper). To evaluate these p-map feature selection methods, we compared them with methods based on the SVM weight vector directly, t-statistics, and expert knowledge. We used MRI data from the Alzheimer's disease neuroimaging initiative classifying Alzheimer's disease (AD) patients, mild cognitive impairment (MCI) patients who converted to AD (MCIc), MCI patients who did not convert to AD (MCInc), and cognitively normal controls (CN). Features for each voxel were derived from gray matter morphometry. Feature selection based on the SVM weights gave better results than t-statistics and expert knowledge. The p-map methods performed slightly better than those using the weight vector. The wrapper method scored better than the filter method. Recursive feature elimination based on the p-map improved most for AD-CN: the area under the receiver-operating-characteristic curve (AUC) significantly increased from 90.3% without feature selection to 92.0% when selecting 1.5%-3% of the features. This feature selection method also improved the other classifications: AD-MCI 0.1% improvement in AUC (not significant), MCI-CN 0.7%, and MCIc-MCInc 0.1% (not significant). Although the performance improvement due to feature selection was limited, the methods based on the p-map generally had the best performance, and were therefore better in estimating the relevance of individual features.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n=30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

[Hypertension and cognitive impairments: Possible mechanism of development, diagnosis, and approaches to therapy]

The review presents data on the role of hypertension in the development of cognitive impairments. It discusses issues of the early diagnosis of hypertension, the possibility of an integrated approach to therapy for cognitive disorders in hypertensive patients.

The temporospatial evolution of neuritic plaque-related and independent tauopathies: implications for dementia staging

Neuritic plaque (NP) formation can be dated in vivo. This analysis attempts to "date" the progression of neurofibrillary tangles (NFT) using the spatial distribution of NP as a reference. Autopsy data from 471 participants in the Honolulu-Asia Aging Study (HAAS) were combined into latent factor measures of NFT and NP counts. The variance in "early" and "late" NP pathology was used to estimate the spatial distribution of "early" and "late" NFT formation. A third latent factor representing "non-NP-related NFT" was also constructed. "Early" NP and "late" NP correlated significantly with objectively early and later cognitive performance, respectively. In contrast to our expectations, neocortical NFT correlated best with "early" NP pathology, while NFT in allocortical structures correlated best with "late" NP pathology. Therefore, the NP-related fraction of NFT appears to be co-localized spatially with NP. However, since the latter evolve corticofugally in time, this suggests that NP-related NFT do so as well. Corticotropic NFT formation must therefore be either unrelated to NP formation, a temporally distinct process, or both.

On the origin of Alzheimer's disease. Trials and tribulations of the amyloid hypothesis

The amyloid cascade hypothesis, which implicates the amyloid Aβ peptide as the pathological initiator of both familial and sporadic, late onset Alzheimer's disease (AD), continues to guide the majority of research. We believe that current evidence does not support the amyloid cascade hypothesis for late onset AD. Instead, we propose that Aβ is a key regulator of brain homeostasis. During AD, while Aβ accumulation may occur in the long term in parallel with disease progression, it does not contribute to primary pathogenesis. This view predicts that amyloid-centric therapies will continue to fail, and that progress in developing successful alternative therapies for AD will be slow until closer attention is paid to understanding the physiological function of Aβ and its precursor protein.

Alzheimer's disease pathology does not mediate the association between depressive symptoms and subsequent cognitive decline

BACKGROUND

Depressive symptoms in nondemented individuals appear to hasten the progression from mild cognitive impairment to clinical Alzheimer's disease (AD) and double the risk of incident AD. However, the mechanism(s) by which depression might affect this risk has not been well established. The purpose of this analysis was to test the hypothesis that AD pathology mediates depression's apparent effect on the risk of dementia conversion using longitudinally collected psychometric testing and autopsy data from the Honolulu-Asia Aging Study.

METHODS

Latent factor variables representing AD, cortical Lewy body (CLB), and ischemic neuropathology were tested as potential mediators of the association between the Center for Epidemiological Studies depression scale (CES-D) score and the 10-year prospective rate of cognitive decline, adjusted for baseline cognition, age, education, total number of medications, and brain weight at autopsy.

RESULTS

CES-D scores, neurofibrillary tangle counts, CLB counts, and ischemic lesions each made significant independent contributions to cognitive decline. However, CES-D scores were not significantly associated with any pathological variable; thus the pathological variables were not mediators of the effect of CES-D scores on cognitive decline.

CONCLUSIONS

Subsyndromal depressive symptoms are significantly associated with subsequent cognitive decline. Although the effect is relatively modest, it is stronger than that of amyloid-related neuropathologies and independent of that of neurofibrillary tangles, cortical Lewy bodies, and ischemic lesions. Our results argue against the role of AD-related neuropathology as a mediator of depression's effect on cognitive decline, but cannot rule out a significant mediation effect in a subset of cases, perhaps with more severe baseline depressive symptoms.

Estimating the temporal evolution of Alzheimer's disease pathology with autopsy data

The temporal growth of Alzheimer's disease (AD) neuropathology cannot be easily determined because autopsy data are available only after death. We combined autopsy data from 471 participants in the Honolulu-Asia Aging Study (HAAS) into latent factor measures of neurofibrillary tangle and neuritic plaque counts. These were associated with intercept and slope parameters from a latent growth curve (LGC) model of 9-year change in cognitive test performance in 3244 autopsied and non-autopsied HAAS participants. Change in cognition fully mediated the association between baseline cognitive performance and AD lesions counts. The mediation effect of cognitive change on both AD lesion models effectively dates them within the period of cognitive surveillance. Additional analyses could lead to an improved understanding of lesion propagation in AD.

Predicting AD conversion: comparison between prodromal AD guidelines and computer assisted PredictAD tool

Purpose

To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI and CSF biomarkers.

Methods

Altogether 391 MCI cases (158 AD converters) were selected from the ADNI cohort. All the cases had baseline cognitive tests, MRI and/or CSF levels of Aβ1–42 and Tau. Using baseline data, the status of MCI patients (AD or MCI) three years later was predicted using current diagnostic research guidelines and the PredictAD software tool designed for supporting clinical diagnostics. The data used were 1) clinical criteria for episodic memory loss of the hippocampal type, 2) visual MTA, 3) positive CSF markers, 4) their combinations, and 5) when the PredictAD tool was applied, automatically computed MRI measures were used instead of the visual MTA results. The accuracies of diagnosis were evaluated with the diagnosis made 3 years later.

Results

The PredictAD tool achieved the overall accuracy of 72% (sensitivity 73%, specificity 71%) in predicting the AD diagnosis. The corresponding number for a clinician’s prediction with the assistance of the PredictAD tool was 71% (sensitivity 75%, specificity 68%). Diagnosis with the PredictAD tool was significantly better than diagnosis by biomarkers alone or the combinations of clinical diagnosis of hippocampal pattern for the memory loss and biomarkers (p≤0.037).

Conclusion

With the assistance of PredictAD tool, the clinician can predict AD conversion more accurately than the current diagnostic criteria.

The Framingham Brain Donation Program: neuropathology along the cognitive continuum

The Framingham Heart Study has enrolled 3 generations of participants, the original cohort (gen 1) enrolled in 1948, the offspring cohort (gen 2) enrolled in 1971 and the third generation enrolled in 2002. Participants have been undergoing prospective surveillance for incident stroke and dementia and embedded within this cohort is the voluntary Framingham Brain Donation Program that was begun in 1997. Participants who register to become brain donors have had one or more brain MR and cognitive test batteries administered. In addition, they undergo neurological evaluation as indicated, record review and post-mortem next-of-kin interview to determine the presence, type and extent of antemortem, clinical neurological diagnoses and to assign a retrospective clinical dementia rating (CDR) Scale score. Between 1997 and 2009 there were 1806 deaths, 186 of which were among registered brain donors and of these 139 brains could be examined. 58% were deemed cognitively normal at death. We present results for 3 projects; the first was to examine the sensitivity and specificity of our clinical diagnosis against the gold standard of pathological AD in 59 persons who underwent detailed cognitive assessment in the two years prior to death; we observed a 77.3% sensitivity (2 persons with AD were diagnosed clinically as Lewy body dementia) and a 91.9% specificity. The second examined the correlation of regional Alzheimer-type pathology to cognitive status at death among 34 persons who were over the age of 75 and without any significant vascular or alternative neurodegenerative pathology and found that neurofibrillary tangle counts distinguished between persons who were controls, had mild cognitive impairment, mild or moderate dementia; tangles in dorsolateral frontal cortex best distinguished MCI and controls. The third project examined the extent and severity of vascular pathology, again in a larger sample of varying cognitive abilities and in a subsample of persons with either amnestic or nonamnestic MCI. We observed that an aggregate ischemic injury score was significantly higher in persons with a CDR score of 0.5 than in normal controls.

Brain organochlorines and Lewy pathology: the Honolulu-Asia Aging Study

Although organochlorines have been reported more frequently in Parkinson's disease (PD) brains than in controls, the association with brain Lewy pathology is unknown. Honolulu-Asia Aging Study (HAAS) participants, exposed to organochlorines from a variety of sources during midlife, represent a population well suited to determining the relationship of brain organochlorines with Lewy pathology in decedents from the longitudinal HAAS. The study design included the measurement of 21 organochlorine levels in frozen occipital lobe samples from HAAS decedents. Alpha-synuclein immunostaining performed on 225 brains was used to identify Lewy bodies and Lewy neurites. With the potential for spurious associations to appear between Lewy pathology and 17 organochlorine compounds found in at least 1 brain, initial assessments identified heptachlor epoxide isomer b, methoxychlor, and benzene hexachloride b as being most important. The prevalence of Lewy pathology was 75% (6 of 8) among brains with any 2 of the 3 compounds, 48.8% (79 of 162) among those with 1, and 32.7% (18 of 55) for those with neither (P = .007 test for trend). Although findings persisted after removing cases with PD and dementia with Lewy bodies and after adjustment for age at death, body mass index, pack-years of cigarette smoking, and coffee intake (P = .013), the results were insignificant when correcting for multiple testing. Although consistent with earlier accounts of an association between organochlorines and clinical PD, associations with Lewy pathology warrant further study.

[Markers of prodromal Alzheimer's disease]

The diagnosis of Alzheimer's disease has long been considered a diagnosis of probability, as the definitive diagnosis can only be established by histopathological examination. However, the development of in-vivo biomarkers, considered a reflection of physiopathological processes, has changed our view of the disease. New criteria have recently been proposed that integrate such biomarkers as found in the cerebrospinal fluid (CSF) using new diagnostic tools such as magnetic resonance imaging (MRI), brain scintigraphy, FDG-positron emission tomography (PET) and PET amyloid ligand uptake studies. The value of these new criteria for the diagnosis of prodromal Alzheimer's disease and the prospect of disease-modifying drugs are also discussed.

The profile of hippocampal metabolites differs between Alzheimer's disease and subcortical ischemic vascular dementia, as measured by proton magnetic resonance spectroscopy

Alzheimer's disease (AD) and subcortical ischemic vascular dementia (SIVD) have overlapping pathologies and risk factors, but their underlying neurodegenerative mechanisms are basically different. We performed magnetic resonance spectroscopy (MRS) to study metabolite differences between the two diseases in vivo. The subjects were 31 patients with SIVD and 99 with AD. Additionally, 45 elderly subjects were recruited as controls. We measured N-acetylaspartate (NAA), glutamine and glutamate (Glx), and myoinositol (mIns) concentration quantitatively using a 1.5-T MR scanner. N-acetylaspartate and Glx concentrations decreased in the hippocampus and cingulate/precuneal cortices (PCC) in both AD and SIVD patients, and the NAA decrease in the hippocampus was more prominent in AD than in SIVD. Interestingly, the pattern of mIns concentration changes differed between the two disorders; mIns was increased in AD but not increased in SIVD. If one differentiates between AD and SIVD by the mIns concentration in the hippocampus, the area under the receiver operating characteristic curve was 0.95, suggesting a high potential for discrimination. Our results suggest that proton MRS can provide useful information to differentiate between AD and SIVD. The difference of mIns concentrations in the hippocampus and PCC seems to reflect the different neurodegenerative mechanisms of the two disorders.

The prognostic value of amyloid imaging

Mild cognitive impairment is characterized by a decline in cognitive performance without interference with activities of daily living. The amnestic subtype of mild cognitive impairment progresses to Alzheimer's disease at a rate of 10-15% per year and in the majority the neuropathology is intermediate between the neuropathological changes of typical ageing and Alzheimer's disease. Amyloid deposition occurs over a decade before the development of noticeable cognitive symptoms in a continuous process that starts in healthy elderly individuals. Newly developed PET amyloid imaging agents provide noninvasive biomarkers for the early in vivo detection of Alzheimer's pathology in healthy elderly individuals and those with mild cognitive impairment. Exclusion of amyloid pathology should allow a more accurate prognosis to be given and ensure appropriate recruitment into clinical trials testing the efficacy of new putative antiamyloid agents at an earlier disease stage. The development of (18)F-labelled amyloid imaging agents has increased the availability of this new technology for clinical and research use since they can be used in PET centres where a cyclotron and radiochemistry are not available. This review discusses the role of PET imaging for assessing the amyloid load in cognitively normal elderly subjects and subjects with mild cognitive impairment at risk of conversion to Alzheimer's disease.

Accuracy of the clinical diagnosis of Alzheimer disease at National Institute on Aging Alzheimer Disease Centers, 2005-2010

The neuropathologic examination is considered to provide the gold standard for Alzheimer disease (AD). To determine the accuracy of currently used clinical diagnostic methods, clinical and neuropathologic data from the National Alzheimer's Coordinating Center, which gathers information from the network of National Institute on Aging (NIA)-sponsored Alzheimer Disease Centers (ADCs), were collected as part of the National Alzheimer's Coordinating Center Uniform Data Set (UDS) between 2005 and 2010. A database search initially included all 1198 subjects with at least one UDS clinical assessment and who had died and been autopsied; 279 were excluded as being not demented or because critical data fields were missing. The final subject number was 919. Sensitivity and specificity were determined based on "probable" and "possible" AD levels of clinical confidence and 4 levels of neuropathologic confidence based on varying neuritic plaque densities and Braak neurofibrillary stages. Sensitivity ranged from 70.9% to 87.3%; specificity ranged from 44.3% to 70.8%. Sensitivity was generally increased with more permissive clinical criteria and specificity was increased with more restrictive criteria, whereas the opposite was true for neuropathologic criteria. When a clinical diagnosis was not confirmed by minimum levels of AD histopathology, the most frequent primary neuropathologic diagnoses were tangle-only dementia or argyrophilic grain disease, frontotemporal lobar degeneration, cerebrovascular disease, Lewy body disease and hippocampal sclerosis. When dementia was not clinically diagnosed as AD, 39% of these cases met or exceeded minimum threshold levels of AD histopathology. Neurologists of the NIA-ADCs had higher predictive accuracy when they diagnosed AD in subjects with dementia than when they diagnosed dementing diseases other than AD. The misdiagnosis rate should be considered when estimating subject numbers for AD studies, including clinical trials and epidemiologic studies.

Coffee intake in midlife and risk of dementia and its neuropathologic correlates

While animal data suggest a protective effect of caffeine on cognition, studies in humans remain inconsistent. We examined associations of coffee and caffeine intake in midlife with risk of dementia, its neuropathologic correlates, and cognitive impairment among 3494 men in the Honolulu-Asia Aging Study (mean age 52 at cohort entry, 1965-1968) examined for dementia in 1991-1993, including 418 decedents (1992-2004) who underwent brain autopsy. Caffeine intake was determined according to self-reported coffee, tea, and cola consumption at baseline. Logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI) for overall dementia, Alzheimer's disease (AD), vascular dementia (VaD), cognitive impairment (Cognitive Abilities Screening Instrument score <74), and neuropathologic lesions at death (Alzheimer lesions, microvascular ischemic lesions, cortical Lewy bodies, hippocampal sclerosis, generalized atrophy), according to coffee and caffeine intake. Dementia was diagnosed in 226 men (including 118 AD, 80 VaD), and cognitive impairment in 347. There were no significant associations between coffee or caffeine intake and risk of cognitive impairment, overall dementia, AD, VaD, or moderate/high levels of the individual neuropathologic lesion types. However, men in the highest quartile of caffeine intake (>/=411.0 mg/d) [corrected] were less likely than men in the lowest quartile (</=137.0 mg) [corrected] to have any of the lesion types (adjusted-OR, 0.45; 95% CI, 0.23-0.89; p, trend = 0.04). Coffee and caffeine intake in midlife were not associated with cognitive impairment, dementia, or individual neuropathologic lesions, although higher caffeine intake was associated with a lower odds of having any of the lesion types at autopsy.

Lifestyle and the risk of dementia in Japanese-american men

OBJECTIVES

To determine whether adhering to a healthy lifestyle in midlife may reduce the risk of dementia.

DESIGN

Case-control study nested in a prospective cohort.

SETTING

The Honolulu-Asia Aging Study, Oahu, Hawaii.

PARTICIPANTS

Three thousand four hundred sixty-eight Japanese-American men (mean age 52 in 1965-1968) examined for dementia 25 years later.

MEASUREMENTS

Men at low risk were defined as those with the following midlife characteristics: nonsmoking, body mass index (BMI) less than 25.0 kg/m(2) , physically active, and having a healthy diet (based on alcohol, dairy, meat, fish, fruits, vegetables, cereals, and ratio of monounsaturated to saturated fat). Logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for developing overall dementia, Alzheimer's disease (AD), and vascular dementia (VaD), adjusting for potential confounders.

RESULTS

Dementia was diagnosed in 6.4% of men (52.5% with AD, 35.0% with VaD). Examining the risk factors individually, BMI was most strongly associated with greater risk of overall dementia (OR = 1.87, 95% CI = 1.26-2.77; BMI > 25.0 vs <22.6 kg/m(2) ). All of the individual risk factors except diet score were significantly associated with VaD, whereas none were significantly associated with AD alone. Men with all four low-risk characteristics (7.2% of the cohort) had the lowest OR for overall dementia (OR = 0.36, 95% CI = 0.15-0.84). There were no significant associations between the combined low-risk characteristics and the risk of AD alone.

CONCLUSION

Among Japanese-American men, having a healthy lifestyle in midlife is associated with a lower risk of dementia in late life.

Evolution of the diagnostic criteria for degenerative and cognitive disorders

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.