Sensitivity and specificity of diagnostic accuracy in Alzheimer's disease: a synthesis of existing evidence

Effect of dorsolateral prefrontal cortex structural measures on neuroplasticity and response to paired-associative stimulation in Alzheimer's dementia

Long-term potentiation (LTP)-like activity can be induced by stimulation protocols such as paired associative stimulation (PAS). We aimed to determine whether PAS-induced LTP-like activity (PAS-LTP) of the dorsolateral prefrontal cortex (DLPFC) is associated with cortical thickness and other structural measures impaired in Alzheimer's dementia (AD). We also explored longitudinal relationships between these brain structures and PAS-LTP response after a repetitive PAS (rPAS) intervention. Mediation and regression analyses were conducted using data from randomized controlled trials with AD and healthy control participants. PAS-electroencephalography assessed DLPFC PAS-LTP. DLPFC thickness and surface area were acquired from T1-weighted magnetic resonance imaging. Fractional anisotropy and mean diffusivity (MD) of the superior longitudinal fasciculus (SLF)-a tract important to induce PAS-LTP-were measured with diffusion-weighted imaging. AD participants exhibited reduced DLPFC thickness and increased SLF MD. There was also some evidence that reduction in DLPFC thickness mediates DLPFC PAS-LTP impairment. Longitudinal analyses showed preliminary evidence that SLF MD, and to a lesser extent DLPFC thickness, is associated with DLPFC PAS-LTP response to active rPAS. This study expands our understanding of the relationships between brain structural changes and neuroplasticity. It provides promising evidence for a structural predictor to improving neuroplasticity in AD with neurostimulation. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Advances in blood biomarkers for Alzheimer disease (AD): A review

Alzheimer disease (AD) and Alzheimer Disease and Related Dementias (AD/ADRD) are growing public health challenges globally affecting millions of older adults, necessitating concerted efforts to advance our understanding and management of these conditions. AD is a progressive neurodegenerative disorder characterized pathologically by amyloid plaques and tau neurofibrillary tangles that are the primary cause of dementia in older individuals. Early and accurate diagnosis of AD dementia is crucial for effective intervention and treatment but has proven challenging to accomplish. Although testing for AD brain pathology with cerebrospinal fluid (CSF) or positron emission tomography (PET) has been available for over 2 decades, most patients never underwent this testing because of inaccessibility, high out-of-pocket costs, perceived risks, and the lack of AD-specific treatments. However, in recent years, rapid progress has been made in developing blood biomarkers for AD/ADRD. Consequently, blood biomarkers have emerged as promising tools for non-invasive and cost-effective diagnosis, prognosis, and monitoring of AD progression. This review presents the evolving landscape of blood biomarkers in AD/ADRD and explores their potential applications in clinical practice for early detection, prognosis, and therapeutic interventions. It covers recent advances in blood biomarkers, including amyloid beta (Aβ) peptides, tau protein, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP). It also discusses their diagnostic and prognostic utility while addressing associated challenges and limitations. Future research directions in this rapidly evolving field are also proposed.

Bayesian estimation for the accuracy of three neuropsychological tests in detecting Alzheimer's disease and mild cognitive impairment: a retrospective analysis of the ADNI database

BACKGROUND

The neuropathological confirmation serves as the gold standard for diagnosing Alzheimer's disease (AD), but it is usually not available to the living individuals. In addition, the gold standard for diagnosing Mild Cognitive Impairment (MCI) remains unclear yet. Neuropsychological testing, such as the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-cog), is commonly used tests in identifying AD and MCI, offering convenience, affordability, non-invasiveness, and accessibility in clinical settings. We aimed to accurately evaluate the discriminative ability of the three tests administrated at the same visit simultaneously in detecting AD and MCI due to AD in the absence of a gold standard.

METHODS

A total of 1289 participants aged over 65 were included from the baseline visits of Alzheimer's disease Neuroimaging Initiative. Bayesian latent class models, accounting for conditional dependence between MoCA and MMSE, were conducted to assess the diagnostic accuracy of the three tests for detecting AD and MCI.

RESULTS

In detecting AD, the ADAS-cog had the highest Youden's Index (0.829), followed by the MoCA(0.813) and MMSE(0.796). The ADAS-cog and MoCA showed similar sensitivity (0.922 vs 0.912) and specificity (0.907 vs 0.901), while the MMSE had lower sensitivity (0.874) and higher specificity (0.922). For MCI detection, the ADAS-cog had the highest Youden's Index (0.704) compared to the MoCA (0.614) and MMSE (0.478). The ADAS-cog exhibited the highest sensitivity, closely followed by the MoCA and MMSE (0.869 vs 0.845 vs 0.757), and the ADAS-cog also had good specificity (0.835 vs 0.769 vs 0.721). The estimated true prevalence of AD among individuals aged over 65 was 20.0%, and the estimated true prevalence of MCI due to AD was 24.8%.

CONCLUSIONS

The findings suggest that the ADAS-cog and MoCA are reliable tools for detecting AD and MCI, while the MMSE may be less sensitive in detecting these conditions. A large underdiagnosis of the MCI and Alzheimer's population still remains in clinical screening.

MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard

BACKGROUND

The statistical models developed for meta-analysis of diagnostic test accuracy studies require specialised knowledge to implement. This is especially true since recent guidelines, such as those in Version 2 of the Cochrane Handbook of Systematic Reviews of Diagnostic Test Accuracy, advocate more sophisticated methods than previously. This paper describes a web-based application - MetaBayesDTA - that makes many advanced analysis methods in this area more accessible.

RESULTS

We created the app using R, the Shiny package and Stan. It allows for a broad array of analyses based on the bivariate model including extensions for subgroup analysis, meta-regression and comparative test accuracy evaluation. It also conducts analyses not assuming a perfect reference standard, including allowing for the use of different reference tests.

CONCLUSIONS

Due to its user-friendliness and broad array of features, MetaBayesDTA should appeal to researchers with varying levels of expertise. We anticipate that the application will encourage higher levels of uptake of more advanced methods, which ultimately should improve the quality of test accuracy reviews.

Circulating long non-coding RNAs as novel diagnostic biomarkers for Alzheimer's disease (AD): A systematic review and meta-analysis

BACKGROUND

Long non-coding RNAs (lncRNAs) have been reported to be involved in the pathogenesis of neurodegenerative diseases. It has also been hypothesized that plasma exosomal lncRNAs may be used as Alzheimer's disease (AD) biomarkers. In this systematic review, we compiled all studies on the subject to evaluate the accuracy of lncRNAs in identifying AD cases through meta-analysis.

METHODS

A PRISMA-compliant systematic search was conducted in PubMed/MEDLINE, EMBASE, and Web of Science databases for English publications till September 2022. We included all observational studies published which investigated the sensitivity and specificity of various lncRNAs in plasma samples of AD diagnosis. Our search strategy included lncRNA and all the related spelling and abbreviation variations combined with the keyword Alzheimer's disease. Methodological quality was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-II) tool. The meta-analysis was carried out using the area under the Receiver Operator Characteristic (ROC) curves (AUC) and sensitivity and specificity values to assess the accuracy of the identified lncRNAs in AD diagnosis. To account for the predicted heterogeneity of the study, a random-effects model was used. All the statistical analyses and visualizations were conducted using Stata 17.0 software.

RESULTS

A total of seven studies (AD patients = 553, healthy controls = 513) were included in the meta-analysis. Three lncRNAs were upregulated (RNA BACE-AS1, RNA NEAT1, RNA GAS5), and one lncRNA (MALAT1) was downregulated in plasma samples of AD patients. RNA 51A and RNA BC200 were reported to have variable expression patterns. A lncRNA (RNA 17A) was not significantly different between AD and control groups. The pooled sensitivity, specificity, and AUC values of lncRNAs in identifying AD were (0.74; 95% CI [0.63, 0.82], I2 = 79.2%), (0.88; 95% CI [0.75, 0.94], I2 = 88.9%), and 0.86; 95% CI [0.82, 0.88], respectively. In addition, the pooled diagnostic odds ratio (DOR) of the five individual lncRNAs in AD diagnosis was 20.

CONCLUSION

lncRNAs had high accuracy in identifying AD and must be seen as a promising diagnostic biomarker of the disease.

Malignant Brain Aging: The Formidable Link Between Dysregulated Signaling Through Mechanistic Target of Rapamycin Pathways and Alzheimer's Disease (Type 3 Diabetes)

Malignant brain aging corresponds to accelerated age-related declines in brain functions eventually derailing the self-sustaining forces that govern independent vitality. Malignant brain aging establishes the path toward dementing neurodegeneration, including Alzheimer's disease (AD). The full spectrum of AD includes progressive dysfunction of neurons, oligodendrocytes, astrocytes, microglia, and the microvascular systems, and is mechanistically driven by insulin and insulin-like growth factor (IGF) deficiencies and resistances with accompanying deficits in energy balance, increased cellular stress, inflammation, and impaired perfusion, mimicking the core features of diabetes mellitus. The underlying pathophysiological derangements result in mitochondrial dysfunction, abnormal protein aggregation, increased oxidative and endoplasmic reticulum stress, aberrant autophagy, and abnormal post-translational modification of proteins, all of which are signature features of both AD and dysregulated insulin/IGF-1-mechanistic target of rapamycin (mTOR) signaling. This article connects the dots from benign to malignant aging to neurodegeneration by reviewing the salient pathologies associated with initially adaptive and later dysfunctional mTOR signaling in the brain. Effective therapeutic and preventive measures must be two-pronged and designed to 1) address complex and shifting impairments in mTOR signaling through the re-purpose of effective anti-diabetes therapeutics that target the brain, and 2) minimize the impact of extrinsic mediators of benign to malignant aging transitions, e.g., inflammatory states, obesity, systemic insulin resistance diseases, and repeated bouts of general anesthesia, by minimizing exposures or implementing neuroprotective measures.

Predictors of response to acetylcholinesterase inhibitors in dementia: A systematic review

Background

The mainstay of therapy for many neurodegenerative dementias still relies on acetylcholinesterase inhibitors (AChEI); however, there is debate on various aspects of such treatment. A huge body of literature exists on possible predictors of response, but a comprehensive review is lacking. Therefore, our aim is to perform a systematic review of the predictors of response to AChEI in neurodegenerative dementias, providing a categorization and interpretation of the results.

Methods

We conducted a systematic review of the literature up to December 31st, 2021, searching five different databases and registers, including studies on rivastigmine, donepezil, and galantamine, with clearly defined criteria for the diagnosis of dementia and the response to AChEI therapy. Records were identified through the string: predict * AND respon * AND (acetylcholinesterase inhibitors OR donepezil OR rivastigmine OR galantamine). The results were presented narratively.

Results

We identified 1,994 records in five different databases; after exclusion of duplicates, title and abstract screening, and full-text retrieval, 122 studies were finally included.

Discussion

The studies show high heterogeneity in duration, response definition, drug dosage, and diagnostic criteria. Response to AChEI seems associated with correlates of cholinergic deficit (hallucinations, fluctuating cognition, substantia innominate atrophy) and preserved cholinergic neurons (faster alpha on REM sleep EEG, increased anterior frontal and parietal lobe perfusion after donepezil); white matter hyperintensities in the cholinergic pathways have shown inconsistent results. The K-variant of butyrylcholinesterase may correlate with better response in late stages of disease, while the role of polymorphisms in other genes involved in the cholinergic system is controversial. Factors related to drug availability may influence response; in particular, low serum albumin (for donepezil), CYP2D6 variants associated with reduced enzymatic activity and higher drug doses are the most consistent predictors, while AChEI concentration influence on clinical outcomes is debatable. Other predictors of response include faster disease progression, lower serum cholesterol, preserved medial temporal lobes, apathy, absence of concomitant diseases, and absence of antipsychotics. Short-term response may predict subsequent cognitive response, while higher education might correlate with short-term good response (months), and long-term poor response (years). Age, gender, baseline cognitive and functional levels, and APOE relationship with treatment outcome is controversial.

Evaluation of the Accuracy of Cognitive Screening Tests in Detecting Dementia Associated with Alzheimer's Disease: A Hierarchical Bayesian Latent Class Meta-Analysis

BACKGROUND

Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) are neuropsychological tests commonly used by physicians for screening cognitive dysfunction of Alzheimer's disease (AD). Due to different imperfect reference standards, the performance of MoCA and MMSE do not reach consensus. It is necessary to evaluate the consistence and differentiation of MoCA and MMSE in the absence of a gold standard for AD.

OBJECTIVE

We aimed to assess the accuracy of MoCA and MMSE in screening AD without a gold standard reference test.

METHODS

Studies were identified from PubMed, Web of Science, CNKI, Chinese Wanfang Database, China Science and Technology Journal Database, and Cochrane Library. Our search was limited to studies published in English and Chinese before August 2021. A hierarchical Bayesian latent class model was performed in meta-analysis when the gold standard was absent.

RESULTS

A total of 67 studies comprising 5,554 individuals evaluated for MoCA and 76,862 for MMSE were included in this meta-analysis. The pooled sensitivity was 0.934 (95% CI 0.906 to 0.954) for MoCA and 0.883 (95% CI 0.859 to 0.903) for MMSE, while the pooled specificity was 0.899 (95% CI 0.859 to 0.928) for MoCA and 0.903 (95% CI 0.879 to 0.923) for MMSE. MoCA was useful to rule out dementia associated with AD with lower negative likelihood ratio (LR-) (0.074, 95% CI 0.051 to 0.108). MoCA showed better performance with higher diagnostic odds ratio (DOR) (124.903, 95% CI 67.459 to 231.260).

CONCLUSION

MoCA had better performance than MMSE in screening dementia associated with AD from patients with mild cognitive impairment or healthy controls.

Using Verb Fluency, Natural Language Processing, and Machine Learning to Detect Alzheimer's Disease

Alzheimer's disease (AD) causes significant impairments in memory and other cognitive domains. As there is no cure to the disease yet, early detection and delay of disease progression are critical for management of AD. Verbal fluency is one of the most common and sensitive neuropsychological methods used for detection and evaluation of the cognitive declines in AD, in which a subject is required to name as many items as possible in 30 or 60 seconds that belong to a certain category. In this study, we develop an approach to detect AD using a verb fluency (VF) task, a specific subset of verbal fluency analyzing the subjects' listing of verbs in a given time period. We use machine learning techniques including random forest (RF), neural network (NN), recurrent NN (RNN), and natural language processing (NLP) to detect the risk of AD. The results show that the developed models can stratify subjects into the corresponding AD and control groups with up to 76% accuracy using RF, but at a cost of having to preprocess the data. This accuracy is slightly lower, but not significantly, at 67% using RNN and NLP, which involves almost no manual preprocessing of the data. This study opens up a powerful approach of using simple VF tasks for early detection of AD.

Knowledge and Attitudes of two Latino Groups about Alzheimer Disease: a Qualitative Study

Clustering Latinos under a single group in Alzheimer Disease (AD) research, neglects, among other things cultural and environmental differences. To address this, we examine knowledge and attitudes about AD among two Latino groups. We held 5 focus groups and 2 interviews all in Spanish with Mexicans and Puerto Ricans between 40 and 60 years old living in the Grand Rapids area in Michigan. Using content analysis of the discussions, we identified themes related to knowledge, attitudes and concerns about AD and caregiving. A total of 20 Mexicans and 9 Puerto Ricans participated. Improving knowledge and awareness, barriers and home-based family care were important themes in both Latino groups. Puerto Rican groups raised more concerns about the disease, whereas lack of knowledge was a key theme among Mexican participants. The exploratory study is a first step in promoting research that is attentive to the commonalities and differences of Latino groups and in continuing efforts to enhance health literacy among these groups.

Association of APOE e2 genotype with Alzheimer's and non-Alzheimer's neurodegenerative pathologies

The apolipoprotein E (APOE) gene contains both the major common risk variant for late onset Alzheimer's disease (AD), e4, and the major neuroprotective variant, e2. Here we examine the association of APOE e2 with multiple neurodegenerative pathologies, leveraging the NACC v. 10 database of 1557 brains that included 130 e2 carriers and 679 e4 carriers in order to examine potential neuroprotective effects. For AD-related pathologies of amyloid plaques and Braak stage, e2 had large and highly significant protective effects contrasted with e3/e3 and e4 carriers with odds ratios of about 0.50 for e3 contrasts and 0.10 for e4 contrasts. When we separately examined e2/e4 carriers, risk for AD pathologies was similar to that of e4 carriers, not e2 carriers. For multiple fronto-temporal lobar pathologies and tauopathies, e2 was not significantly associated with pathology. In sum, we found that e2 was associated with large but circumscribed protective effects.

A Bayesian hierarchical change point model with parameter constraints

Alzheimer's disease is the leading cause of dementia among adults aged 65 or above. Alzheimer's disease is characterized by a change point signaling a sudden and prolonged acceleration in cognitive decline. The timing of this change point is of clinical interest because it can be used to establish optimal treatment regimens and schedules. Here, we present a Bayesian hierarchical change point model with a parameter constraint to characterize the rate and timing of cognitive decline among Alzheimer's disease patients. We allow each patient to have a unique random intercept, random slope before the change point, random change point time, and random slope after the change point. The difference in slope before and after a change point is constrained to be nonpositive, and its parameter space is partitioned into a null region (representing normal aging) and a rejection region (representing accelerated decline). Using the change point time, the estimated slope difference, and the threshold of the null region, we are able to (1) distinguish normal aging patients from those with accelerated cognitive decline, (2) characterize the rate and timing for patients experiencing cognitive decline, and (3) predict personalized risk of progression to dementia due to Alzheimer's disease. We apply the approach to data from the Religious Orders Study, a national cohort study of aging Catholic nuns, priests, and lay brothers.

The Neuropathological and Clinical Diagnostic Criteria of Chronic Traumatic Encephalopathy: A Critical Examination in Relation to Other Neurodegenerative Diseases

This work critically reviews chronic traumatic encephalopathy (CTE), with a specific focus on the single criterion necessary and sufficient for diagnosis. Herein, CTE is compared to other well-established neurodegenerative entities including Alzheimer's disease and dementia with Lewy bodies. Each neurodegenerative disorder is reviewed in five pertinent areas: 1) historical perspective, 2) guideline formation process, 3) clinical diagnostic criteria, 4) pathological diagnostic criteria, and 5) validation of previously described diagnostic criteria (e.g., sensitivity and specificity). These comparisons indicate that CTE is a disease in the earliest stages of formation and has yet to undergo rigorous development and refinement similar to other neurodegenerative diseases. Suggested future revisions to the diagnostic criterion of CTE include establishing a lower threshold for accumulation of pathology, as well as accounting for the presence of concomitant neuropathology and comorbid neurodegenerative disorders. Currently, while initial efforts have been attempted, agreed upon antemortem clinical criteria do not exist. As has been the scientific standard with similar neurodegenerative disorders, antemortem diagnostic guidelines should first be refined through subcommittees of neuroscientists from diverse institutional backgrounds with a subclassification of levels of diagnostic certainty (possible, probably, and definite). Validation studies should then assess the predictive value and accuracy of proposed antemortem diagnostic criteria in relation to potential pathological criteria.

Identifying subtypes of mild cognitive impairment from healthy aging based on multiple cortical features combined with volumetric measurements of the hippocampal subfields

Background

Mild cognitive impairment (MCI) is subtle cognitive decline with an estimated 10-15% yearly conversion rate toward Alzheimer's disease (AD). It remains unexplored in brain cortical association areas in different lobes and its changes with progression and conversion of MCI.

Methods

Brain structural magnetic resonance (MR) images were collected from 102 stable MCI (sMCI) patients. One hundred eleven were converted MCI (cMCI) patients, and 109 were normal control (NC). The cortical surface features and volumes of subcortical hippocampal subfields were calculated using the FreeSurfer software, followed by an analysis of variance (ANOVA) model, to reveal the differences between the NC-sMCI, NC-cMCI, and sMCI-cMCI groups. Afterward, the support vector machine-recursive feature elimination (SVM-RFE) method was applied to determine the differences between the groups.

Results

The experimental results showed that there were progressive degradations in either range or degree of the brain structure from NC to sMCI, and then to cMCI. The SVM classifier obtained accuracies with 64.62%, 78.96%, and 70.33% in the sMCI-NC, cMCI-NC, and cMCI-sMCI groups, respectively, using the volumes of hippocampal subfields independently. The combination of the volumes from the hippocampal subfields and cortical measurements could significantly increase the performance to 71.86%, 84.64%, and 76.86% for the sMCI-NC, cMCI-NC, and cMCI-sMCI classifications, respectively. Also, the brain regions corresponding to the dominant features with strong discriminative power were widely located in the temporal, frontal, parietal, olfactory cortexes, and most of the hippocampal subfields, which were associated with cognitive decline, memory impairment, spatial navigation, and attention control.

Conclusions

The combination of cortical features with the volumes of hippocampal subfields could supply critical information for MCI detection and its conversion.

Clinical utility of 18F-FDG-PET/MRI brain in dementia: Preliminary experience from a geriatric clinic in South India

BACKGROUND

¹⁸F-FDG-PET is a potential sensitive biomarker indicating neuronal damage. ¹⁸F-FDG-PET has proven to be useful in subtyping dementia. Utility of simultaneous ¹⁸F-FDG-PET and MRI-brain was investigated in the evaluation of dementia in this facility.

METHOD

All case notes of patients who underwent 18 F-FDG-PET/MRI brain attending the Geriatric Clinic for 18 month period between January 2017 and June 2018 were retrospectively reviewed. Their socio-demographic details, MRI-brain finding, ¹⁸F- FDG-PET findings and comorbid illnesses were studied.

RESULTS

A total of 21 patients underwent ¹⁸F-FDG-PET/MRI brain during study period. The mean age was 61.23, SD-8.6 years (range: 36-75 years). Among them 5 (23.8%) had Mild Cognitive Impairment (MCI) and 16 (76.2%) had dementia. Majority of patients had early onset cognitive decline (76.2%). Based on the pattern of hypometabolism, the MCI group had one patient each indicative of AD, Semantic-Frontotemporal dementia (Semantic-FTD), mixed Alzheimer's dementia (AD + FTD) and two patients had patterns suggestive of Behaviour Variant of FTD (Bv-FTD). In Dementia group the pattern of hypometabolism was indicative of Bv-FTD in seven, AD in four, Posterior Cortical Atrophy (PCA) in one, Semantic-FTD in one, Mixed AD-Diffuse Lewy Body Dementia (DLBD) in one and no specific pattern in two patients. MRI and 18 F-FDG-PET brain had concordance in 9 (56.26%) patients.

DISCUSSION

¹⁸F-FDG-PET/MRI helped in overall clinical diagnosis and management in 19 (90.5%) patients especially with early onset dementia. In MCI group it indicated underlying aetiology and in dementia group it helped in subtyping.

CONCLUSION

The study supports the role of ¹⁸F-FDG-PET/MRI as an emerging diagnostic tool to assist in dementia evaluation in India.

Alzheimer's disease: Only prevention makes sense

Alzheimer's disease therapeutics is one of the most important endeavours in today's clinical investigation. Over more than 30 years of research, no disease-modifying treatment has been approved by either the FDA or the EMA to treat Alzheimer's disease. Recently, the evidence of pathological alterations in the brain tissue has been gathered showing that the signs of brain damage appear more than 20 years before the onset of Alzheimer's dementia. The major aim of this review is to underpin the idea that in Alzheimer's therapeutics, only prevention makes sense. It is difficult to visualise that would-be patients may be treated with endovenous administration of antibodies for several years to delay the onset of dementia. Rather, changes in lifestyle that should be specific, stratified and personalised are a likely alternative to delay the transition from asymptomatic Alzheimer's to minimal cognitive impairment and from there to dementia. These efforts are of the utmost importance. If we could delay the onset of full-blown dementia by 5 years, the number of demented patients would be almost halved. Thus, emphasis on preventive measures that can be implemented for decades must be supported. This approach, where even mild changes in cognition are of the greatest importance, cannot be underestimated in terms of both the individual and society's viewpoints.

FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort

Background/aims

In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias.

Methods

We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as "typical-AD", "atypical-AD" (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), "non-AD" (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or "negative" patterns. To perform the statistical analyses, the individual patterns were grouped either as "AD dementia vs. non-AD dementia (all diseases)" or as "FTD vs. non-FTD (all diseases)". Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated.

Results

The multivariate logistic model identified FDG-PET "AD" SPM classification (Expβ = 19.35, 95% C.I. 4.8-77.8, p < 0.001) and CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64-25.43, p < 0.05) as the best predictors of conversion from MCI to AD dementia. The "FTD" SPM pattern significantly predicted conversion to FTD dementias at follow-up (Expβ = 14, 95% C.I. 3.1-63, p < 0.001). Overall, FDG-PET-SPM classification was the most accurate biomarker, able to correctly differentiate either the MCI subjects who converted to AD or FTD dementias, and those who remained stable or reverted to normal cognition (Expβ = 17.9, 95% C.I. 4.55-70.46, p < 0.001).

Conclusions

Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.

Can the retina be used to diagnose and plot the progression of Alzheimer's disease?

Alzheimer's disease (AD) is a neurodegenerative disease and the most common cause of senile dementia. It impairs the quality of life of a person and their family, posing a serious economic and social threat in developed countries. The fact that the diagnosis can only be definitively made post-mortem, or when the disease is fairly advanced, presents a serious problem if novel therapeutic interventions are to be devised and used early in the course of the disease. There is therefore a pressing need for more sensitive and specific diagnostic tests with which we can detect AD in the preclinical stage. The tau proteins and beta-amyloid proteins start to accumulate 20 years before the symptoms begin to manifest. Detecting them in the preclinical stage would be a potential breakthrough in the management of AD. A high degree of clinical suspicion is needed to correlate problems in cognition with the changes in the eye, particularly the retina, pupil and ocular movements, so that the disease can be detected early and managed in the prodromal phase. In this systematic review, we ask the question whether the retina can be used to make a specific and early diagnosis of AD.

Reference Intervals for Plasma Amyloid β in Korean Adults Without Cognitive Impairment

Amyloid β (Aβ) peptides are important components of plaques in patients with Alzheimer's disease (AD). Recent studies suggest that a low plasma ratio of Aβ42 to Aβ40 may precede the development of the sporadic form of AD. The aim of this study was to establish reference intervals for plasma Aβ in Korean adults. A total of 370 apparently healthy individuals (181 males and 189 females aged 40-69 yr) without cognitive impairment were enrolled. Plasma concentrations of Aβ40 and Aβ42 were measured by using a human amyloid β assay kit (Immuno-Biological Laboratories, Japan). Reference intervals were established according to the "CLSI guidelines for defining, establishing, and verifying reference intervals in the clinical laboratory". There was no need to partition the data with respect to gender or age group. The 95th percentile reference intervals for Aβ40 and Aβ42 were 127-331 pg/mL and 2.31-19.84 pg/mL, respectively. The reference interval for the Aβ42/Aβ40 ratio was 0.011-0.092. Plasma Aβ concentrations obtained in this study could be used as reference intervals for clinical purposes.

Recommendations for CSF AD biomarkers in the diagnostic evaluation of dementia

This article presents recommendations, based on the Grading of Recommendations, Assessment, Development, and Evaluation method, for the clinical application of cerebrospinal fluid (CSF) amyloid-β_1-42, tau, and phosphorylated tau in the diagnostic evaluation of patients with dementia. The recommendations were developed by a multidisciplinary working group based on the available evidence and consensus from focused discussions for (i) identification of Alzheimer's disease (AD) as the cause of dementia, (ii) prediction of rate of decline, (iii) cost-effectiveness, and (iv) interpretation of results. The working group found sufficient evidence to support a recommendation to use CSF AD biomarkers as a supplement to clinical evaluation, particularly in uncertain and atypical cases, to identify or exclude AD as the cause of dementia. Because of insufficient evidence, it was uncertain whether CSF AD biomarkers outperform imaging biomarkers. Operational recommendations for the interpretation of ambiguous CSF biomarker results were also provided.

A Primer on Health Economic Evaluations in Thoracic Oncology

There is growing interest for economic evaluation in oncology to illustrate the value of multiple new diagnostic and therapeutic interventions. As these analyses have started to move from specialist publications into mainstream medical literature, the wider medical audience consuming this information may need additional education to evaluate it appropriately. Here we review standard practices in economic evaluation, illustrating the different methods with thoracic oncology examples where possible. When interpreting and conducting health economic studies, it is important to appraise the method, perspective, time horizon, modeling technique, discount rate, and sensitivity analysis. Guidance on how to do this is provided. To provide a method to evaluate this literature, a literature search was conducted in spring 2015 to identify economic evaluations published in the Journal of Thoracic Oncology. Articles were reviewed for their study design, and areas for improvement were noted. Suggested improvements include using more rigorous sensitivity analyses, adopting a standard approach to reporting results, and conducting complete economic evaluations. Researchers should design high-quality studies to ensure the validity of the results, and consumers of this research should interpret these studies critically on the basis of a full understanding of the methodologies used before considering any of the conclusions. As advancements occur on both the research and consumer sides, this literature can be further developed to promote the best use of resources for this field.

Amyloid-β-Secondary Structure Distribution in Cerebrospinal Fluid and Blood Measured by an Immuno-Infrared-Sensor: A Biomarker Candidate for Alzheimer's Disease

The misfolding of the Amyloid-beta (Aβ) peptide into β-sheet enriched conformations was proposed as an early event in Alzheimer's Disease (AD). Here, the Aβ peptide secondary structure distribution in cerebrospinal fluid (CSF) and blood plasma of 141 patients was measured with an immuno-infrared-sensor. The sensor detected the amide I band, which reflects the overall secondary structure distribution of all Aβ peptides extracted from the body fluid. We observed a significant downshift of the amide I band frequency of Aβ peptides in Dementia Alzheimer type (DAT) patients, which indicated an overall shift to β-sheet. The secondary structure distribution of all Aβ peptides provides a better marker for DAT detection than a single Aβ misfold or the concentration of a specific oligomer. The discrimination between DAT and disease control patients according to the amide I frequency was in excellent agreement with the clinical diagnosis (accuracy 90% for CSF and 84% for blood). The amide I band maximum above or below the decisive marker frequency appears as a novel spectral biomarker candidate of AD. Additionally, a preliminary proof-of-concept study indicated an amide I band shift below the marker band already in patients with mild cognitive impairment due to AD. The presented immuno-IR-sensor method represents a promising, simple, robust, and label-free diagnostic tool for CSF and blood analysis.

Neuroimaging of hippocampal atrophy in early recognition of Alzheimer's disease--a critical appraisal after two decades of research

As a characteristic feature of Alzheimer's disease (AD) hippocampal atrophy (HA) can be demonstrated in the majority of patients by using neuroimaging techniques in particular magnetic resonance imaging (MRI). Hippocampal atrophy is associated with declarative memory deficits and can also be associated with changes of adjacent medial temporal substructures such as the parahippocampal gyrus or the the entorhinal cortex. Similar findings are present in patients with mild cognitive impairment (MCI) albeit to a lesser extent. While these finding facilitate the diagnostic process in patients with clinical suspicious AD, the metric properties of hippocampal atrophy for delineating healthy aging from MCI and mild AD still appear to be rather limited; as such it is not sufficient to establish the diagnosis of AD (and even more so of MCI). This limitation partly refers to methodological issues and partly to the fact that hippocampal tissue integrity is subject to various pathogenetic influences other than AD. Moreover,the effects of hippocampal atrophy on the behavioral level (e.g. cognitive deficits) are modulated by the individual's cognitive reserve. From a clinical standpoint these observations are in line with the hypothesis that the onset and course of AD is influenced by a number of peristatic factors which are partly conceptualized in the concepts of brain and/or cognitive reserve. These complex interactions have to be considered when using the presence of hippocampal atrophy in the routine diagnostic procedure of AD.

Florbetaben for PET Imaging of Beta-Amyloid Plaques in the Brain

Alzheimer's disease (AD) is a devastating neurodegenerative disorder affecting the elderly. Current clinical diagnostic tools are often ineffective in accurately diagnosing AD. However, new advances in diagnostic imaging, particularly positron emission tomography (PET) amyloid imaging, have shown increased sensitivity and specificity, as well as high inter-reader agreement. The most commonly studied tracer, PiB-C11, has shown high affinity binding to amyloid, but is limited in its use outside of research due to its short half-life. Instead, development of other PET ligands with increased half-life, such as fluorine-18-labeled ((18)F) tracers, allows for more widespread use of PET in clinical settings. In particular, recent phase II and III trials of (18)F-florbetaben have demonstrated the high accuracy of this PET tracer in identifying amyloid accumulation. This paper will examine the techniques of amyloid imaging, focusing particularly on the recently approved (18)F-florbetaben.