European intersocietal recommendations for the biomarker-based diagnosis of neurocognitive disorders.

The recent commercialisation of the first disease-modifying drugs for Alzheimer's disease emphasises the need for consensus recommendations on the rational use of biomarkers to diagnose people with suspected neurocognitive disorders in memory clinics. Most available recommendations and guidelines are either disease-centred or biomarker-centred. A European multidisciplinary taskforce consisting of 22 experts from 11 European scientific societies set out to define the first patient-centred diagnostic workflow that aims to prioritise testing for available biomarkers in individuals attending memory clinics. After an extensive literature review, we used a Delphi consensus procedure to identify 11 clinical syndromes, based on clinical history and examination, neuropsychology, blood tests, structural imaging, and, in some cases, EEG. We recommend first-line and, if needed, second-line testing for biomarkers according to the patient's clinical profile and the results of previous biomarker findings. This diagnostic workflow will promote consistency in the diagnosis of neurocognitive disorders across European countries.

European consensus for the diagnosis of MCI and mild dementia: Preparatory phase.

INTRODUCTION: Etiological diagnosis of neurocognitive disorders of middle-old age relies on biomarkers, although evidence for their rational use is incomplete. A European task force is defining a diagnostic workflow where expert experience fills evidence gaps for biomarker validity and prioritization. We report methodology and preliminary results. METHODS: Using a Delphi consensus method supported by a systematic literature review, 22 delegates from 11 relevant scientific societies defined workflow assumptions. RESULTS: We extracted diagnostic accuracy figures from literature on the use of biomarkers in the diagnosis of main forms of neurocognitive disorders. Supported by this evidence, panelists defined clinical setting (specialist outpatient service), application stage (MCI-mild dementia), and detailed pre-assessment screening (clinical-neuropsychological evaluations, brain imaging, and blood tests). DISCUSSION: The Delphi consensus on these assumptions set the stage for the development of the first pan-European workflow for biomarkers' use in the etiological diagnosis of middle-old age neurocognitive disorders at MCI-mild dementia stages. HIGHLIGHTS: Rational use of biomarkers in neurocognitive disorders lacks consensus in Europe. A consensus of experts will define a workflow for the rational use of biomarkers. The diagnostic workflow will be patient-centered and based on clinical presentation. The workflow will be updated as new evidence accrues.

Prioritization process for European Academy of Neurology clinical practice guidelines.

BACKGROUND AND PURPOSE: The development of high-quality clinical practice guidelines (CPGs) takes substantial time, effort, and resources. During the past years, the European Academy of Neurology (EAN) guideline production was significantly increased, so the need to develop clear, transparent, and methodologically solid criteria for prioritizing guideline topics became apparent. With this paper, we aim to define a set of criteria to be applied for prioritizing topics for future EAN guidelines, as well as the procedure for their implementation. METHODS: After review of the literature, we identified a recent systematic review that reported on the main prioritization criteria used by health organizations. Based on these, we developed a list of 20 preliminary criteria, which were voted on through a Delphi consensus procedure, including 160 stakeholders. Finally, we established a working procedure on how to submit and select new guideline topic proposals within the EAN. This procedure was reviewed by the EAN Scientific Committee and the Board. RESULTS: The first round, 61.3% of the participants voted, and 86% of them participated in the second round. Seven criteria were approved with this procedure. After the selection of the criteria, a prioritization procedure was launched, and the first 30 topics are reported in this paper. This bottom-up process that involved the whole EAN community was followed by a top-down process, using additional criteria for further selection by the EAN board members. CONCLUSIONS: We describe the development of prioritization criteria to be applied in the process of topic selection for future EAN CPGs. We will perform regular reviews and adjustments of the process.

Pharmacological Medical Treatment of Epilepsy in Patients with Dementia: A Systematic Review.

BACKGROUND: Patients with dementia have an increased risk of developing epilepsy, especially in patients with vascular dementia and Alzheimer's disease. In selecting the optimal anti- epileptic drug (AED), the possible side effects such as drowsiness and worsening of cognitive function should be taken into consideration, together with co-morbidities and type of epilepsy. OBJECTIVE: The current systematic review investigates the efficacy, tolerability, and changes in cognitive function after administration of AED in patients with dementia and epilepsy. METHODS: We searched six databases, including MEDLINE and CENTRAL, checked reference lists, contacted experts, and searched Google Scholar to identify studies reporting randomized trials. Studies identified were independently screened, data extracted, and quality appraised by two researchers. A narrative synthesis was used to report findings. RESULTS: We included one study with 95 patients with Alzheimer's disease randomized to either levetiracetam, lamotrigine, or phenobarbital. No significant differences were found for efficacy, but patients receiving levetiracetam showed an improvement in mini-mental state examination scores and had fewer adverse events. CONCLUSION: High-quality evidence in the form of randomized controlled trials to guide clinicians in choosing an AED in patients with dementia and concomitant epilepsy remains scarce. However, levetiracetam has previously been shown to possibly improve cognition in patients with both mild cognitive impairment and Alzheimer's disease, is better tolerated in the elderly population, and has no clinically relevant interaction with either cholinesterase inhibitors or NMDA receptor antagonists.

Comparing a Single Clinician Versus a Multidisciplinary Consensus Conference Approach for Dementia Diagnostics.

BACKGROUND: Evidence-based recommendations on the optimal evaluation approach for dementia diagnostics are limited. This impedes a harmonized workup across clinics and nations. OBJECTIVE: To evaluate the diagnostic performance of a multidisciplinary consensus conference compared to a single clinician approach. METHODS: In this prospective study, we enrolled 457 patients with suspected cognitive decline, from two European memory clinics. A diagnostic evaluation was performed at baseline independently in two ways: 1) by a single clinician and 2) at a multidisciplinary consensus conference. A syndrome diagnosis and an etiological diagnosis was made. The confidence in the diagnosis was recorded using a visual analogue scale. An expert panel re-evaluation diagnosis served as reference for the baseline syndrome diagnosis and a 12-24-month follow-up diagnosis for the etiological diagnosis. RESULTS: 439 patients completed the study. We observed 12.5%discrepancy (k = 0.81) comparing the baseline syndrome diagnoses of the single clinician to the consensus conference, and 22.3%discrepancy (k = 0.68) for the baseline etiological diagnosis. The accuracy of the baseline etiological diagnosis was significantly higher at the consensus conference and was driven mainly by increased accuracy in the MCI group. Confidence in the etiological diagnosis at baseline was significantly higher at the consensus conference (p < 0.005), especially for the frontotemporal dementia diagnosis. CONCLUSION: The multidisciplinary consensus conference performed better on diagnostic accuracy of disease etiology and increased clinicians' confidence. This highlights the importance of a multidisciplinary diagnostic evaluation approach for dementia diagnostics, especially when evaluating patients in the MCI stage.

[Chronic traumatic encephalopathy].

Chronic traumatic encephalopathy (CTE) is associated with a history of repetitive head impacts, such as those sustained through contact sports. Post-mortem assessment has revealed specific neuropathological characteristics related to the condition. The symptoms of CTE typically present several years after exposure and can include mood/behavioural changes, cognitive dysfunction and motor symptoms. The course of CTE can potentially be progressive and debilitating. In this review, we argue, that there is a need for validated neuropathological and clinical criteria in order to detect CTE ante-mortem in the population.

Biomarker counseling, disclosure of diagnosis and follow-up in patients with mild cognitive impairment: A European Alzheimer's disease consortium survey.

OBJECTIVES: Mild cognitive impairment (MCI) is associated with an increased risk of further cognitive decline, partly depending on demographics and biomarker status. The aim of the present study was to survey the clinical practices of physicians in terms of biomarker counseling, management, and follow-up in European expert centers diagnosing patients with MCI. METHODS: An online email survey was distributed to physicians affiliated with European Alzheimer's disease Consortium centers (Northern Europe: 10 centers; Eastern and Central Europe: 9 centers; and Southern Europe: 15 centers) with questions on attitudes toward biomarkers and biomarker counseling in MCI and dementia. This included postbiomarker counseling and the process of diagnostic disclosure of MCI, as well as treatment and follow-up in MCI. RESULTS: The response rate for the survey was 80.9% (34 of 42 centers) across 20 countries. A large majority of physicians had access to biomarkers and found them useful. Pre- and postbiomarker counseling varied across centers, as did practices for referral to support groups and advice on preventive strategies. Less than half reported discussing driving and advance care planning with patients with MCI. CONCLUSIONS: The variability in clinical practices across centers calls for better biomarker counseling and better training to improve communication skills. Future initiatives should address the importance of communicating preventive strategies and advance planning.

The role of physical and cognitive function in performance of activities of daily living in patients with mild-to-moderate Alzheimer's disease - a cross-sectional study.

BACKGROUND: Several factors may play a role in the ability of patients with Alzheimer's disease to perform activities of daily living (ADL). The aim of this study was to examine the impact of different aspects of physical performance and cognitive functions on ADL in patients suffering from mild-to-moderate Alzheimer's disease. METHODS: We conducted secondary analyses on cross-sectional baseline data from the randomized controlled multicentre study "Preserving quality of life, physical health and functional ability in Alzheimer's Disease: The effect of physical exercise" (ADEX). In total, 185 AD patients (76 women and 109 men), with a mean age on 70,4 years, were included. Data from physical performance tests (Astrand cycle test, Timed up & Go (TUG), Sit to Stand test (STS)) and cognitive tests (Mini Mental Status Examination (MMSE), Symbol Digit Modalities Test (SDMT), Stroop Color and Word test (Stroop)) were used. Their associations with ADL, measured on the ADCS-ADL scale was assessed in multivariable regression analyses. RESULTS: SDMT and MMSE had significant, moderate correlations with total ADL (SDMT: r = 0.33, MMSE: r = 0.42) and instrumental ADL (SDMT: r = 0.31, MMSE: r = 0.42), but not with basic ADL. Adjusting for age and sex, the associations between SDMT and MMSE to total ADL and instrumental ADL persisted. No significant associations were found between Astrand, TUG, STS or Stroop and total ADL, basic ADL or instrumental ADL. CONCLUSION: Total ADL and instrumental ADL are associated with cognitive functions, including executive function. No significant association between examined physical performance parameters and ADL functions was observed, and consequently does not support an impact of physical function on ADL functions in patients with mild-to-moderate Alzheimer's disease and relatively well-preserved physical function. Strategies aimed to improve cognition may be better suited to improve ADL function in patients with mild-to-moderate Alzheimer's disease. TRIAL REGISTRATION: NCT01681602 . Registered 10 September 2012, retrospectively registered.

Gait Disturbances are Associated with Increased Cognitive Impairment and Cerebrospinal Fluid Tau Levels in a Memory Clinic Cohort.

BACKGROUND: Gait analysis with accelerometers is a relatively inexpensive and easy to use method to potentially support clinical diagnoses of Alzheimer's disease and other dementias. It is not clear, however, which gait features are most informative and how these measures relate to Alzheimer's disease pathology. OBJECTIVE: In this study, we tested if calculated features of gait 1) differ between cognitively normal subjects (CN), mild cognitive impairment (MCI) patients, and dementia patients, 2) are correlated with cerebrospinal fluid (CSF) biomarkers related to Alzheimer's disease, and 3) predict cognitive decline. METHODS: Gait was measured using tri-axial accelerometers attached to the fifth lumbar vertebra (L5) in 58 CN, 58 MCI, and 26 dementia participants, while performing a walk and dual task. Ten gait features were calculated from the vertical L5 accelerations, following principal component analysis clustered in four domains, namely pace, rhythm, time variability, and length variability. Cognitive decline over time was measured using MMSE, and CSF biomarkers were available in a sub-group. RESULTS: Linear mixed models showed that dementia patients had lower pace scores than MCI patients and CN subjects (p < 0.05). In addition, we found associations between the rhythm domain and CSF-tau, especially in the dual task. Gait was not associated with CSF Aß42 levels and cognitive decline over time as measured with the MMSE. CONCLUSION: These findings suggest that gait - particularly measures related to pace and rhythm - are altered in dementia and have a direct link with measures of neurodegeneration.

Selection of memory clinic patients for CSF biomarker assessment can be restricted to a quarter of cases by using computerized decision support, without compromising diagnostic accuracy.

INTRODUCTION: An accurate and timely diagnosis for Alzheimer's disease (AD) is important, both for care and research. The current diagnostic criteria allow the use of CSF biomarkers to provide pathophysiological support for the diagnosis of AD. How these criteria should be operationalized by clinicians is unclear. Tools that guide in selecting patients in which CSF biomarkers have clinical utility are needed. We evaluated computerized decision support to select patients for CSF biomarker determination. METHODS: We included 535 subjects (139 controls, 286 Alzheimer's disease dementia, 82 frontotemporal dementia and 28 vascular dementia) from three clinical cohorts. Positive (AD like) and negative (normal) CSF biomarker profiles were simulated to estimate whether knowledge of CSF biomarkers would impact (confidence in) diagnosis. We applied these simulated CSF values and combined them with demographic, neuropsychology and MRI data to initiate CSF testing (computerized decision support approach). We compared proportion of CSF measurements and patients diagnosed with sufficient confidence (probability of correct class ≥0.80) based on an algorithm with scenarios without CSF (only neuropsychology, MRI and APOE), CSF according to the appropriate use criteria (AUC) and CSF for all patients. RESULTS: The computerized decision support approach recommended CSF testing in 140 (26%) patients, which yielded a diagnosis with sufficient confidence in 379 (71%) of all patients. This approach was more efficient than CSF in none (0% CSF, 308 (58%) diagnosed), CSF selected based on AUC (295 (55%) CSF, 350 (65%) diagnosed) or CSF in all (100% CSF, 348 (65%) diagnosed). CONCLUSIONS: We used a computerized decision support with simulated CSF results in controls and patients with different types of dementia. This approach can support clinicians in making a balanced decision in ordering additional biomarker testing. Computer-supported prediction restricts CSF testing to only 26% of cases, without compromising diagnostic accuracy.

Moderate- to high-intensity exercise does not modify cortical ß-amyloid in Alzheimer's disease.

INTRODUCTION: Animal models of Alzheimer's disease show that exercise may modify ß-amyloid (Aß) deposition. We examined the effect of a 16-week exercise intervention on cortical Aß in patients with mild-to-moderate Alzheimer's disease. METHODS: Thirty-six patients with Alzheimer's disease were randomized to either one hour of aerobic exercise three times weekly for 16 weeks or usual care. Pre and post intervention, 11Carbon-Pittsburgh compound B positron emission tomography was carried out to assess cortical Aß, and quantified using standardized uptake value rations (SUVRs). RESULTS: The intervention showed no effect on follow-up SUVRs in a covariance analysis with group allocation, baseline intervention SUVR, age, sex, and baseline Mini-Mental State Examination as predictors. Change in SUVRs did not correlate with changes in measures of physical or aerobic fitness. DISCUSSION: The present findings do not support an effect of exercise on Aß. However, the relatively short intervention period may account for a lack of efficacy. Further studies should test earlier and longer interventions.

Impact of a clinical decision support tool on prediction of progression in early-stage dementia: a prospective validation study.

BACKGROUND: In clinical practice, it is often difficult to predict which patients with cognitive complaints or impairment will progress or remain stable. We assessed the impact of using a clinical decision support system, the PredictND tool, to predict progression in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in memory clinics. METHODS: In this prospective multicenter study, we included 429 patients with SCD (n = 230) and MCI (n = 199) (female 54%, age 67 ± 9, MMSE 28 ± 2) and followed them for at least 12 months. Based on all available patient baseline data (demographics, cognitive tests, cerebrospinal fluid biomarkers, and MRI), the PredictND tool provides a comprehensive overview of the data and a classification defining the likelihood of progression. At baseline, a clinician defined an expected follow-up diagnosis and estimated the level of confidence in their prediction using a visual analogue scale (VAS, 0-100%), first without and subsequently with the PredictND tool. As outcome measure, we defined clinical progression as progression from SCD to MCI or dementia, and from MCI to dementia. Correspondence between the expected and the actual clinical progression at follow-up defined the prognostic accuracy. RESULTS: After a mean follow-up time of 1.7 ± 0.4 years, 21 (9%) SCD and 63 (32%) MCI had progressed. When using the PredictND tool, the overall prognostic accuracy was unaffected (0.4%, 95%CI - 3.0%; + 3.9%; p = 0.79). However, restricting the analysis to patients with more certain classifications (n = 203), we found an increase of 3% in the accuracy (95%CI - 0.6%; + 6.5%; p = 0.11). Furthermore, for this subgroup, the tool alone showed a statistically significant increase in the prognostic accuracy compared to the evaluation without tool (6.4%, 95%CI 2.1%; 10.7%; p = 0.004). Specifically, the negative predictive value was high. Moreover, confidence in the prediction increased significantly (∆VAS = 4%, p < .0001). CONCLUSIONS: Adding the PredictND tool to the clinical evaluation increased clinicians' confidence. Furthermore, the results indicate that the tool has the potential to improve prediction of progression for patients with more certain classifications.

Automatically computed rating scales from MRI for patients with cognitive disorders.

OBJECTIVES: The aims of this study were to examine whether visual MRI rating scales used in diagnostics of cognitive disorders can be estimated computationally and to compare the visual rating scales with their computed counterparts in differential diagnostics. METHODS: A set of volumetry and voxel-based morphometry imaging biomarkers was extracted from T1-weighted and FLAIR images. A regression model was developed for estimating visual rating scale values from a combination of imaging biomarkers. We studied three visual rating scales: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), and white matter hyperintensities (WMHs) measured by the Fazekas scale. Images and visual ratings from the Amsterdam Dementia Cohort (ADC) (N = 513) were used to develop the models and cross-validate them. The PredictND (N = 672) and ADNI (N = 752) cohorts were used for independent validation to test generalizability. RESULTS: The correlation coefficients between visual and computed rating scale values were 0.83/0.78 (MTA-left), 0.83/0.79 (MTA-right), 0.64/0.64 (GCA), and 0.76/0.75 (Fazekas) in ADC/PredictND cohorts. When performance in differential diagnostics was studied for the main types of dementia, the highest balanced accuracy, 0.75-0.86, was observed for separating different dementias from cognitively normal subjects using computed GCA. The lowest accuracy of about 0.5 for all the visual and computed scales was observed for the differentiation between Alzheimer's disease and frontotemporal lobar degeneration. Computed scales produced higher balanced accuracies than visual scales for MTA and GCA (statistically significant). CONCLUSIONS: MTA, GCA, and WMHs can be reliably estimated automatically helping to provide consistent imaging biomarkers for diagnosing cognitive disorders, even among less experienced readers. KEY POINTS: • Visual rating scales used in diagnostics of cognitive disorders can be estimated computationally from MRI images with intraclass correlations ranging from 0.64 (GCA) to 0.84 (MTA). • Computed scales provided high diagnostic accuracy with single-subject data (area under the receiver operating curve range, 0.84-0.94).

Detecting frontotemporal dementia syndromes using MRI biomarkers.

BACKGROUND: Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another. METHODS: In this retrospective multicenter cohort study, we included 1213 patients (age 67 ±â€¯9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200). RESULTS: The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative likelihood ratio = 0.2). The validation cohort provided corresponding results for the anterior vs. posterior index and temporal pole left index. CONCLUSION: This study presents three quantitative MRI biomarkers, which could provide additional information to the diagnostic assessment and assist clinicians in diagnosing frontotemporal dementia.

Impact of a Clinical Decision Support Tool on Dementia Diagnostics in Memory Clinics: The PredictND Validation Study.

BACKGROUND: Determining the underlying etiology of dementia can be challenging. Computer- based Clinical Decision Support Systems (CDSS) have the potential to provide an objective comparison of data and assist clinicians. OBJECTIVES: To assess the diagnostic impact of a CDSS, the PredictND tool, for differential diagnosis of dementia in memory clinics. METHODS: In this prospective multicenter study, we recruited 779 patients with either subjective cognitive decline (n=252), mild cognitive impairment (n=219) or any type of dementia (n=274) and followed them for minimum 12 months. Based on all available patient baseline data (demographics, neuropsychological tests, cerebrospinal fluid biomarkers, and MRI visual and computed ratings), the PredictND tool provides a comprehensive overview and analysis of the data with a likelihood index for five diagnostic groups; Alzheimer´s disease, vascular dementia, dementia with Lewy bodies, frontotemporal dementia and subjective cognitive decline. At baseline, a clinician defined an etiological diagnosis and confidence in the diagnosis, first without and subsequently with the PredictND tool. The follow-up diagnosis was used as the reference diagnosis. RESULTS: In total, 747 patients completed the follow-up visits (53% female, 69±10 years). The etiological diagnosis changed in 13% of all cases when using the PredictND tool, but the diagnostic accuracy did not change significantly. Confidence in the diagnosis, measured by a visual analogue scale (VAS, 0-100%) increased (ΔVAS=3.0%, p<0.0001), especially in correctly changed diagnoses (ΔVAS=7.2%, p=0.0011). CONCLUSION: Adding the PredictND tool to the diagnostic evaluation affected the diagnosis and increased clinicians' confidence in the diagnosis indicating that CDSSs could aid clinicians in the differential diagnosis of dementia.

Evaluating combinations of diagnostic tests to discriminate different dementia types.

INTRODUCTION: We studied, using a data-driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia. METHODS: In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls. We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation between dementia types. RESULTS: Cognitive tests had good performance in separating any type of dementia from controls. Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal dementia. Combining diagnostic tests increased the accuracy, with balanced accuracies ranging from 78% to 97%. DISCUSSION: Different diagnostic tests have their distinct roles in differential diagnostics of dementias. Our results indicate that combining different diagnostic tests may increase the accuracy further.

The effect of physical exercise on cerebral blood flow in Alzheimer's disease.

In recent years there has been an increasing focus on the relation between cerebrovascular health, physical exercise and Alzheimer's disease. The aim of the current study was to determine the effect of moderate-to-high-intensity aerobic exercise on cerebral blood flow in patients with mild to moderate Alzheimer's disease. Fifty-one patients were randomized to either usual care or moderate-to-high intensity aerobic exercise for 16 weeks. Exercise had no consistent effect on whole brain or regional cerebral blood flow. Sixteen weeks of exercise are, therefore, not sufficient to produce a consistent increase in cerebral blood flow in a relatively small sample of Alzheimer's patients.

Prevalence of the apolipoprotein E ε4 allele in amyloid ß positive subjects across the spectrum of Alzheimer's disease.

INTRODUCTION: Apolipoprotein E (APOE) ε4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid ß (Aß) pathology. METHODS: We included 3451 Aß+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE ε4 prevalence in relation to age, sex, education, and geographical location. RESULTS: The APOE ε4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in Aß+ cognitively normal and Aß+ mild cognitive impairment (P < .05) but not in Aß+ AD dementia (P = .66). The prevalence was highest in Northern Europe but did not vary by sex or education. DISCUSSION: The APOE ε4 prevalence in AD was higher than that in previous studies, which did not require presence of Aß pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location.

Moderate-to-High Intensity Physical Exercise in Patients with Alzheimer's Disease: A Randomized Controlled Trial.

BACKGROUND: Studies of physical exercise in patients with Alzheimer's disease (AD) are few and results have been inconsistent. OBJECTIVE: To assess the effects of a moderate-to-high intensity aerobic exercise program in patients with mild AD. METHODS: In a randomized controlled trial, we recruited 200 patients with mild AD to a supervised exercise group (60-min sessions three times a week for 16 weeks) or to a control group. Primary outcome was changed from baseline in cognitive performance estimated by Symbol Digit Modalities Test (SDMT) in the intention-to-treat (ITT) group. Secondary outcomes included changes in quality of life, ability to perform activities of daily living, and in neuropsychiatric and depressive symptoms. RESULTS: The ITT analysis showed no significant differences between intervention and control groups in change from baseline of SDMT, other cognitive tests, quality of life, or activities of daily living. The change from baseline in Neuropsychiatric Inventory differed significantly in favor of the intervention group (mean: -3.5, 95% confidence interval (CI) -5.8 to -1.3, p = 0.002). In subjects who adhered to the protocol, we found a significant effect on change from baseline in SDMT as compared with the control group (mean: 4.2, 95% CI 0.5 to 7.9, p = 0.028), suggesting a dose-response relationship between exercise and cognition. CONCLUSIONS: This is the first randomized controlled trial with supervised moderate-to-high intensity exercise in patients with mild AD. Exercise reduced neuropsychiatric symptoms in patients with mild AD, with possible additional benefits of preserved cognition in a subgroup of patients exercising with high attendance and intensity.

[Biomarkers for early diagnosis of Alzheimer's disease]. / Biomarkører ved diagnostik af Alzheimers sygdom i tidlig fase.

Alzheimer's disease is responsible for 40-50% of dementia cases. Future treatment may include disease-modifying compounds unlikely to be efficient if administered late in the course, thus necessitating early diagnosis. Furthermore, revised diagnostic research criteria that include biomarkers of pathological accumulation of cortical beta-amyloid (decreased beta-amyloid in cerebrospinal fluid and amyloid imaging) and neurodegeneration (structural MRI and 18F-FDG-PET), have been published. Future research is needed to determine specific evidence-based application of these biomarkers in the clinic as well as discovery of novel biomarkers.