Plasma and cerebrospinal fluid amyloid beta for the diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

CSF tau and the CSF tau/ABeta ratio for the diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

BACKGROUND

Research suggests that measurable change in cerebrospinal fluid (CSF) biomarkers occurs years in advance of the onset of clinical symptoms (Beckett 2010). In this review, we aimed to assess the ability of CSF tau biomarkers (t-tau and p-tau) and the CSF tau (t-tau or p-tau)/ABeta ratio to enable the detection of Alzheimer's disease pathology in patients with mild cognitive impairment (MCI). These biomarkers have been proposed as important in new criteria for Alzheimer's disease dementia that incorporate biomarker abnormalities.

OBJECTIVES

To determine the diagnostic accuracy of 1) CSF t-tau, 2) CSF p-tau, 3) the CSF t-tau/ABeta ratio and 4) the CSF p-tau/ABeta ratio index tests for detecting people with MCI at baseline who would clinically convert to Alzheimer's disease dementia or other forms of dementia at follow-up.

SEARCH METHODS

The most recent search for this review was performed in January 2013. We searched MEDLINE (OvidSP), Embase (OvidSP), BIOSIS Previews (Thomson Reuters Web of Science), Web of Science Core Collection, including Conference Proceedings Citation Index (Thomson Reuters Web of Science), PsycINFO (OvidSP), and LILACS (BIREME). We searched specialized sources of diagnostic test accuracy studies and reviews. We checked reference lists of relevant studies and reviews for additional studies. We contacted researchers for possible relevant but unpublished data. We did not apply any language or data restriction to the electronic searches. We did not use any methodological filters as a method to restrict the search overall.

SELECTION CRITERIA

We selected those studies that had prospectively well-defined cohorts with any accepted definition of MCI and with CSF t-tau or p-tau and CSF tau (t-tau or p-tau)/ABeta ratio values, documented at or around the time the MCI diagnosis was made. We also included studies which looked at data from those cohorts retrospectively, and which contained sufficient data to construct two by two tables expressing those biomarker results by disease status. Moreover, studies were only selected if they applied a reference standard for Alzheimer's disease dementia diagnosis, for example, the NINCDS-ADRDA or Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by the electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies, and the full papers for eligibility. Two independent assessors performed data extraction and quality assessment. Where data allowed, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary receiver operating characteristic (ROC) curve.

MAIN RESULTS

In total, 1282 participants with MCI at baseline were identified in the 15 included studies of which 1172 had analysable data; 430 participants converted to Alzheimer's disease dementia and 130 participants to other forms of dementia. Follow-up ranged from less than one year to over four years for some participants, but in the majority of studies was in the range one to three years. Conversion to Alzheimer's disease dementia The accuracy of the CSF t-tau was evaluated in seven studies (291 cases and 418 non-cases).The sensitivity values ranged from 51% to 90% while the specificity values ranged from 48% to 88%. At the median specificity of 72%, the estimated sensitivity was 75% (95% CI 67 to 85), the positive likelihood ratio was 2.72 (95% CI 2.43 to 3.04), and the negative likelihood ratio was 0.32 (95% CI 0.22 to 0.47).Six studies (164 cases and 328 non-cases) evaluated the accuracy of the CSF p-tau. The sensitivities were between 40% and 100% while the specificities were between 22% and 86%. At the median specificity of 47.5%, the estimated sensitivity was 81% (95% CI: 64 to 91), the positive likelihood ratio was 1.55 (CI 1.31 to 1.84), and the negative likelihood ratio was 0.39 (CI: 0.19 to 0.82).Five studies (140 cases and 293 non-cases) evaluated the accuracy of the CSF p-tau/ABeta ratio. The sensitivities were between 80% and 96% while the specificities were between 33% and 95%. We did not conduct a meta-analysis because the studies were few and small. Only one study reported the accuracy of CSF t-tau/ABeta ratio.Our findings are based on studies with poor reporting. A significant number of studies had unclear risk of bias for the reference standard, participant selection and flow and timing domains. According to the assessment of index test domain, eight of 15 studies were of poor methodological quality.The accuracy of these CSF biomarkers for 'other dementias' had not been investigated in the included primary studies. Investigation of heterogeneity The main sources of heterogeneity were thought likely to be reference standards used for the target disorders, sources of recruitment, participant sampling, index test methodology and aspects of study quality (particularly, inadequate blinding).We were not able to formally assess the effect of each potential source of heterogeneity as planned, due to the small number of studies available to be included.

AUTHORS' CONCLUSIONS

The insufficiency and heterogeneity of research to date primarily leads to a state of uncertainty regarding the value of CSF testing of t-tau, p-tau or p-tau/ABeta ratio for the diagnosis of Alzheimer's disease in current clinical practice. Particular attention should be paid to the risk of misdiagnosis and overdiagnosis of dementia (and therefore over-treatment) in clinical practice. These tests, like other biomarker tests which have been subject to Cochrane DTA reviews, appear to have better sensitivity than specificity and therefore might have greater utility in ruling out Alzheimer's disease as the aetiology to the individual's evident cognitive impairment, as opposed to ruling it in. The heterogeneity observed in the few studies awaiting classification suggests our initial summary will remain valid. However, these tests may have limited clinical value until uncertainties have been addressed. Future studies with more uniformed approaches to thresholds, analysis and study conduct may provide a more homogenous estimate than the one that has been available from the included studies we have identified.

Cost-effectiveness of cerebrospinal biomarkers for the diagnosis of Alzheimer's disease

Background

Accurate and timely diagnosis of Alzheimer’s disease (AD) is important for prompt initiation of treatment in patients with AD and to avoid inappropriate treatment of patients with false-positive diagnoses.

Methods

Using a Markov model, we estimated the lifetime costs and quality-adjusted life-years (QALYs) of cerebrospinal fluid biomarker analysis in a cohort of patients referred to a neurologist or memory clinic with suspected AD who remained without a definitive diagnosis of AD or another condition after neuroimaging. Parametric values were estimated from previous health economic models and the medical literature. Extensive deterministic and probabilistic sensitivity analyses were performed to evaluate the robustness of the results.

Results

At a 12.7% pretest probability of AD, biomarker analysis after normal neuroimaging findings has an incremental cost-effectiveness ratio (ICER) of $11,032 per QALY gained. Results were sensitive to the pretest prevalence of AD, and the ICER increased to over $50,000 per QALY when the prevalence of AD fell below 9%. Results were also sensitive to patient age (biomarkers are less cost-effective in older cohorts), treatment uptake and adherence, biomarker test characteristics, and the degree to which patients with suspected AD who do not have AD benefit from AD treatment when they are falsely diagnosed.

Conclusions

The cost-effectiveness of biomarker analysis depends critically on the prevalence of AD in the tested population. In general practice, where the prevalence of AD after clinical assessment and normal neuroimaging findings may be low, biomarker analysis is unlikely to be cost-effective at a willingness-to-pay threshold of $50,000 per QALY gained. However, when at least 1 in 11 patients has AD after normal neuroimaging findings, biomarker analysis is likely cost-effective. Specifically, for patients referred to memory clinics with memory impairment who do not present neuroimaging evidence of medial temporal lobe atrophy, pretest prevalence of AD may exceed 15%. Biomarker analysis is a potentially cost-saving diagnostic method and should be considered for adoption in high-prevalence centers.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-017-0243-0) contains supplementary material, which is available to authorized users.

The usual suspects: why techno-fixing dementia is flawed

Dementia is highly prevalent and up until now, still incurable. If we may believe the narrative that is currently dominant in dementia research, in the future we will not have to suffer from dementia anymore, as there will be a simple techno-fix solution. It is just a matter of time before we can solve the growing public health problem of dementia. In this paper we take a critical stance towards overly positive narratives of techno-fixes by placing our empirical analysis of dementia research protocols and political statements in a framework of technology assessment. From this perspective, it becomes obvious that a techno-fix is just one of many ways to approach societal problems and more importantly that technologies are way less perfect than they are presented. We will argue that this narrow scope, which focusses on the usual suspects for solving illnesses, reduces dementia to organismic aspects, and may be counterproductive in finding a cure for dementia. We conclude with outlining how the narrow scope can be balanced with other narratives and why we should have a reasonable scepticism towards the usual suspects.

Validation of olfactory deficit as a biomarker of Alzheimer disease

BACKGROUND

We evaluated smell identification as a biomarker for Alzheimer disease (AD) by assessing its utility in differentiating normal aging from an amnestic disorder and determining its predictive value for conversion from amnestic mild cognitive impairment (aMCI) to AD.

METHODS

Cross-sectional study (AD = 262, aMCI = 110, controls = 194) measuring smell identification (University of Pennsylvania Smell Identification Test [UPSIT]) and cognitive status was performed, as well as longitudinal analysis of aMCI participants (n = 96) with at least 1 year follow-up (mean 477.6 ± 223.3 days), to determine conversion by National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association criteria.

RESULTS

Odor identification and disease status were highly correlated after correcting for age, sex, and APOE (p < 0.001). Receiver operating characteristic (ROC)/area under the curve (AUC) was similar for the 40-item UPSIT, the top 10 smells in our study, and the 10-item subset previously proposed. Smeller/nonsmeller based on the 10-item subset with a cutoff of 7 (≤7, nonsmeller; >7, smeller) had a sensitivity and specificity of 88% and 71% for identifying AD and 74% sensitivity and 71% specificity for identifying an amnestic disorder. A total of 36.4% of participants with impaired olfaction and 17.3% with intact olfaction converted to AD (p = 0.03). The ROC/AUC for prediction of conversion to AD was 0.62.

CONCLUSIONS

Olfactory identification deficit is a useful screening tool for AD-related amnestic disorder, with sensitivity and specificity comparable to other established biomarkers, with benefits such as ease of administration and low cost. Olfactory identification deficit can be utilized to stratify risk of conversion from aMCI to AD and enrich clinical trials of disease-modifying therapy.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that smell identification (10-item UPSIT subset) accurately identifies patients with amnestic disorders.

Environmental risk factors for dementia: a systematic review

BACKGROUND

Dementia risk reduction is a major and growing public health priority. While certain modifiable risk factors for dementia have been identified, there remains a substantial proportion of unexplained risk. There is evidence that environmental risk factors may explain some of this risk. Thus, we present the first comprehensive systematic review of environmental risk factors for dementia.

METHODS

We searched the PubMed and Web of Science databases from their inception to January 2016, bibliographies of review articles, and articles related to publically available environmental data. Articles were included if they examined the association between an environmental risk factor and dementia. Studies with another outcome (for example, cognition), a physiological measure of the exposure, case studies, animal studies, and studies of nutrition were excluded. Data were extracted from individual studies which were, in turn, appraised for methodological quality. The strength and consistency of the overall evidence for each risk factor identified was assessed.

RESULTS

We screened 4784 studies and included 60 in the review. Risk factors were considered in six categories: air quality, toxic heavy metals, other metals, other trace elements, occupational-related exposures, and miscellaneous environmental factors. Few studies took a life course approach. There is at least moderate evidence implicating the following risk factors: air pollution; aluminium; silicon; selenium; pesticides; vitamin D deficiency; and electric and magnetic fields.

CONCLUSIONS

Studies varied widely in size and quality and therefore we must be circumspect in our conclusions. Nevertheless, this extensive review suggests that future research could focus on a short list of environmental risk factors for dementia. Furthermore, further robust, longitudinal studies with repeated measures of environmental exposures are required to confirm these associations.

Rethinking on the concept of biomarkers in preclinical Alzheimer's disease

The neuropathological processes eventually leading to Alzheimer's disease (AD) are thought to start decades before the appearance of clinical symptoms and the clinical diagnosis of AD dementia. The term "preclinical AD" has been recently introduced to identify this "silent stage" of AD, when the disease is already present, but symptoms are not yet clinically evident. Advances in AD biomarkers have dramatically improved the ability to detect AD pathological processes in vivo in cognitively intact subjects, thus demonstrating the presence of AD pathology in the preclinical phase. This review focuses on the recent advances in the field of neuroimaging and CSF AD biomarkers specifically in the preclinical phase of AD, and aims to discuss the significance that such biomarkers could have in cognitively intact subjects. Even though the use of such biomarkers in AD preclinical phase has contributed to improve our understanding of AD early pathological processes, it raised also a number of new challenges that still remain to be overcome, such as a better definition of the clinical and individual significance of currently known biomarkers in preclinical stages and the development of novel biomarkers of different early AD-related events.

Development of Biomarkers Based on DNA Methylation in the NCAPH2/LMF2 Promoter Region for Diagnosis of Alzheimer's Disease and Amnesic Mild Cognitive Impairment

From the standpoint of early interventions for dementia, a convenient method of diagnosis using biomarkers is required for Alzheimer’s disease (AD) in the early stage as well as amnesic mild cognitive impairment (aMCI). Focusing on differences in DNA methylation due to AD and aMCI, in the present study, we first conducted genome-wide screening, measuring blood DNA methylation levels by the Illumina Infinium HD Methylation Assay in 3 small age-and gender-matched groups consisting of 4 subjects each: normal controls (NC), aMCI and AD. The genome-wide analysis produced 11 DNA methylation loci that distinguished the 3 groups. For confirmation, we increased group sizes and examined samples by pyrosequencing which revealed that DNA methylation in the NCAPH2/LMF2 promoter region was significantly decreased in the AD (n = 30) and aMCI (n = 28) groups as compared to the NC group (n = 30) (P < 0.0001, ANCOVA). No association was found between methylation levels and APOE genotype. NCAPH2/LMF2 methylation levels were considered to potentially be a convenient and useful biomarker for diagnosis of AD and aMCI.

Unfolded Protein Response and Macroautophagy in Alzheimer's, Parkinson's and Prion Diseases

Proteostasis are integrated biological pathways within cells that control synthesis, folding, trafficking and degradation of proteins. The absence of cell division makes brain proteostasis susceptible to age-related changes and neurodegeneration. Two key processes involved in sustaining normal brain proteostasis are the unfolded protein response and autophagy. Alzheimer’s disease (AD), Parkinson’s disease (PD) and prion diseases (PrDs) have different clinical manifestations of neurodegeneration, however, all share an accumulation of misfolded pathological proteins associated with perturbations in unfolded protein response and macroautophagy. While both the unfolded protein response and macroautophagy play an important role in the prevention and attenuation of AD and PD progression, only macroautophagy seems to play an important role in the development of PrDs. Macroautophagy and unfolded protein response can be modulated by pharmacological interventions. However, further research is necessary to better understand the regulatory pathways of both processes in health and neurodegeneration to be able to develop new therapeutic interventions.

A correlativity study of plasma APL1β28 and clusterin levels with MMSE/MoCA/CASI in aMCI patients

Amnestic mild cognitive impairment (aMCI) is a sub-clinical condition characterized by memory deficits that are not severe enough to affect daily functioning. Here we investigated two potential biomarkers found in the cerebrospinal fluid of AD patients, APLP1-derived Aβ-like peptides 28 (APL1β28) and clusterin plasma levels, in terms of their relationship to cognitive function, as reflected in the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA) and the Cognitive Assessment Screening Instrument (CASI) in aMCI patients. Forty-seven aMCI patients and thirty-five age- and gender-matched healthy adult controls were recruited for this study. Using the ELISA method, we found that the mean concentrations of both APL1β28 and clusterin were not significantly different between the control and aMCI groups. The APL1β28 levels were positively correlated with clusterin and that both were negatively correlated with the MMSE scores of the aMCI patients. Clusterin levels were negatively correlated with the MoCA and CASI scores of the aMCI patients. Using multivariate analysis, the correlation between clusterin and MMSE/MoCA/CASI was independent of other AD risk factors including age, education, sex, body mass index and ApoE genotype. The data presented here demonstrate that plasma clusterin levels reflect cognitive function in aMCI patients.

Is late-onset Alzheimer's disease really a disease of midlife?

INTRODUCTION

Increasing evidence suggests that Alzheimer's disease (AD) may begin decades before evidence of dementia, indicating that it may be a disorder of midlife rather than old age.

METHODS

In the absence of long-term prospective studies from early adulthood specifically designed to address this question, a group of international experts examined evidence presently available from previous clinical and population studies to provide an evidence-based opinion as to whether such a change in conceptualization may be justified.

RESULTS

Although still lacking confirmation from dedicated prospective biomarker studies, there is already considerable evidence to suggest both risk factor exposure and brain changes may be already present in midlife.

DISCUSSION

Current evidence suggests (1) that a change in clinical approach notably involving promotion of cardiovascular health in persons with a family history of AD may considerably reduce disease risk and (2) that the development of biomarkers at this early stage will lead to the possibility of clinical trials at a much earlier stage.

Oral glucose tolerance testing to modulate plasma amyloid levels: A novel biomarker

INTRODUCTION

Plasma levels of amyloid-beta (Aβ) do not correlate well with different stages of Alzheimer's disease (AD) in cross-sectional studies. Measuring the changes in Aβ plasma levels with an acute intervention may be more sensitive to distinguishing individuals in earlier stages of AD (mild cognitive impairment; MCI) from normal controls.

METHODS

57 participants (18 with AD/MCI and 39 cognitively normal controls) underwent oral glucose tolerance testing (OGTT). Blood samples were obtained over a 2 hour time period. Changes in plasma Aβ40 and42 levels were measured from either baseline or 5 minutes to the 10 minute time point.

RESULTS

Compared to normal controls, subjects with AD/MCI had significantly less change (Δ) in plasma levels for both Aβ40(-3.13(40.93)pg/ml vs. 41.34(57.16)pg/ml;p=0.002) and Aβ42(-0.15(3.77)pg/ml vs. 5.64(10.65)pg/ml; p=0.004).

DISCUSSION

OGTT combined with measures of plasma Aβ40 and 42 is potentially useful in distinguishing aging individuals who are in different stages of AD.

Dementia trials and dementia tribulations: methodological and analytical challenges in dementia research

Dementia is a substantial and increasing public health concern. Despite decades of research, a cure or effective preventative treatment for dementia remains elusive. We offer critical review of contemporary dementia research and discuss potential reasons why progress in the field has not been as rapid as in other disciplines. We adopt a broad approach in keeping with the broad nature of the topic. We cover the difficulties inherent in studying dementia from 'bench' to 'bedside' to 'population'. We make particular reference to issues of operationalisation of the dementia syndrome and our evolving understanding of dementia as a research 'outcome'. We discuss contemporary 'hot topics' in dementia research methodology focussing on dementia models, pre-dementia states and biomarkers. Recognising the importance of prospective epidemiological cohorts and large-scale clinical trials we pay particular attention to these approaches and the challenges of generating results that have 'real world' external validity. Based on our thoughts we end with suggestions for future dementia research. Our review is designed to be critical but not unnecessarily negative. There is reason for cautious optimism in dementia research. The recent G8 summit on dementia and subsequent establishment of the World Dementia Council are examples of initiatives that reflect societal and political will to increase research efforts in dementia.

Mini-Mental State Examination (MMSE) for the detection of Alzheimer's disease and other dementias in people with mild cognitive impairment (MCI)

BACKGROUND

Dementia is a progressive global cognitive impairment syndrome. In 2010, more than 35 million people worldwide were estimated to be living with dementia. Some people with mild cognitive impairment (MCI) will progress to dementia but others remain stable or recover full function. There is great interest in finding good predictors of dementia in people with MCI. The Mini-Mental State Examination (MMSE) is the best-known and the most often used short screening tool for providing an overall measure of cognitive impairment in clinical, research and community settings.

OBJECTIVES

To determine the diagnostic accuracy of the MMSE at various thresholds for detecting individuals with baseline MCI who would clinically convert to dementia in general, Alzheimer's disease dementia or other forms of dementia at follow-up.

SEARCH METHODS

We searched ALOIS (Cochrane Dementia and Cognitive Improvement Specialized Register of diagnostic and intervention studies (inception to May 2014); MEDLINE (OvidSP) (1946 to May 2014); EMBASE (OvidSP) (1980 to May 2014); BIOSIS (Web of Science) (inception to May 2014); Web of Science Core Collection, including the Conference Proceedings Citation Index (ISI Web of Science) (inception to May 2014); PsycINFO (OvidSP) (inception to May 2014), and LILACS (BIREME) (1982 to May 2014). We also searched specialized sources of diagnostic test accuracy studies and reviews, most recently in May 2014: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). No language or date restrictions were applied to the electronic searches and methodological filters were not used as a method to restrict the search overall so as to maximize sensitivity. We also checked reference lists of relevant studies and reviews, tracked citations in Scopus and Science Citation Index, used searches of known relevant studies in PubMed to track related articles, and contacted research groups conducting work on MMSE for dementia diagnosis to try to locate possibly relevant but unpublished data.

SELECTION CRITERIA

We considered longitudinal studies in which results of the MMSE administered to MCI participants at baseline were obtained and the reference standard was obtained by follow-up over time. We included participants recruited and clinically classified as individuals with MCI under Petersen and revised Petersen criteria, Matthews criteria, or a Clinical Dementia Rating = 0.5. We used acceptable and commonly used reference standards for dementia in general, Alzheimer's dementia, Lewy body dementia, vascular dementia and frontotemporal dementia.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by the electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies. We assessed the identified full papers for eligibility and extracted data to create two by two tables for dementia in general and other dementias. Two authors independently performed quality assessment using the QUADAS-2 tool. Due to high heterogeneity and scarcity of data, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary receiver operating characteristic curve.

MAIN RESULTS

In this review, we included 11 heterogeneous studies with a total number of 1569 MCI patients followed for conversion to dementia. Four studies assessed the role of baseline scores of the MMSE in conversion from MCI to all-cause dementia and eight studies assessed this test in conversion from MCI to Alzheimer´s disease dementia. Only one study provided information about the MMSE and conversion from MCI to vascular dementia. For conversion from MCI to dementia in general, the accuracy of baseline MMSE scores ranged from sensitivities of 23% to 76% and specificities from 40% to 94%. In relationship to conversion from MCI to Alzheimer's disease dementia, the accuracy of baseline MMSE scores ranged from sensitivities of 27% to 89% and specificities from 32% to 90%. Only one study provided information about conversion from MCI to vascular dementia, presenting a sensitivity of 36% and a specificity of 80% with an incidence of vascular dementia of 6.2%. Although we had planned to explore possible sources of heterogeneity, this was not undertaken due to the scarcity of studies included in our analysis.

AUTHORS' CONCLUSIONS

Our review did not find evidence supporting a substantial role of MMSE as a stand-alone single-administration test in the identification of MCI patients who could develop dementia. Clinicians could prefer to request additional and extensive tests to be sure about the management of these patients. An important aspect to assess in future updates is if conversion to dementia from MCI stages could be predicted better by MMSE changes over time instead of single measurements. It is also important to assess if a set of tests, rather than an isolated one, may be more successful in predicting conversion from MCI to dementia.

Peptides from adipose tissue in mental disorders

Adipose tissue is a dynamic endocrine organ that is essential to regulation of metabolism in humans. A new approach to mental disorders led to research on involvement of adipokines in the etiology of mental disorders and mood states and their impact on the health status of psychiatric patients, as well as the effects of treatment for mental health disorders on plasma levels of adipokines. There is evidence that disturbances in adipokine secretion are important in the pathogenesis, clinical presentation and outcome of mental disorders. Admittedly leptin and adiponectin are involved in pathophysiology of depression. A lot of disturbances in secretion and plasma levels of adipokines are observed in eating disorders with a significant impact on the symptoms and course of a disease. It is still a question whether observed dysregulation of adipokines secretion are primary or secondary. Moreover findings in this area are somewhat inconsistent, owing to differences in patient age, sex, socioeconomic status, smoking habits, level of physical activity, eating pathology, general health or medication. This was the rationale for our detailed investigation into the role of the endocrine functions of adipose tissue in mental disorders. It seems that we are continually at the beginning of understanding of the relation between adipose tissue and mental disorders.

Predictive accuracy of amyloid imaging for progression from mild cognitive impairment to Alzheimer disease with different lengths of follow-up: a meta-analysis. [Corrected]

In the past decade, amyloid deposition has been shown to begin many years before the clinical symptoms of dementia in mild cognitive impairment (MCI) due to Alzheimer disease (AD). Longitudinal studies with different follow-up durations have suggested that C-Pittsburgh compound B positron emission tomography (C-PIB-PET) may play a role in stratifying patients with MCI into risk levels for developing AD. However, the predictive accuracy of amyloid imaging for the progression from MCI to AD with different follow-up durations has not yet been systematically evaluated. A formal systematic evaluation of the sensitivity, specificity, and other properties of C-PIB-PET was performed.This study aimed to systematically review and meta-analyze published data on the diagnostic performance of C-PIB-PET for predicting conversion to AD in patients with MCI and to determine whether long-term follow-up has a positive effect on predictive accuracy. Relevant studies were systematically identified through electronic searches, which were performed in MEDLINE (OvidSP), EMBASE (OvidSP), BIOSIS Previews (ISI Web of Knowledge), Science Citation Index (ISI Web of Knowledge), PsycINFO (Ovid SP), and LILACS (Bireme). The methodological quality of each study was assessed by QUADAS-2. Sensitivities and specificities of C-PIB-PET in individual studies were calculated, and the studies underwent meta-analysis with a random-effects model. A summary receiver-operating characteristic curve (SROC) was constructed with the Moses-Shapiro-Littenberg method. Pooled estimates of sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), diagnostic odds ratio (DOR), and the SROC curve of each subgroup were determined. Heterogeneity was tested, and potential sources for heterogeneity were explored by assessing whether certain covariates significantly influenced the relative DOR.Eleven eligible studies consisting of a total of 352 patients with MCI at baseline were included. Overall, the studies were of moderate-to-high methodological quality. The sensitivity and specificity of C-PIB-PET for predicting conversion to AD ranged from 83.3% to 100% and 41.1% to 100%, respectively, with pooled estimates of 94.7% (95% confidence interval [CI]: 89.8%-97.7%) and 57.2% (95% CI: 50.1%-64.2%), respectively . Moderate heterogeneity was observed for specificity between the included studies (I = 42.1%). The pooled estimates for the long-term follow-up subgroup were 95.5% sensitivity (95% CI: 84.5%-99.4%) and 72.4% specificity (95% CI: 59.1%-83.3.8%), whereas the pooled estimates for the short-term follow-up subgroup were 94.4% sensitivity (95% CI: 88.2%-97.9%) and 51.0% specificity (95% CI: 42.6%-59.5%). Homogeneity in each subgroup was significantly higher than that of the included studies, and most diagnostic indicators in the long-term follow-up subgroup were far superior to those in the short-term follow-up subgroup or the entire group. Not all of the methodological quality scores of studies included in this systematic review were high. Current evidence suggests that prolongation of the follow-up duration tended to yield greater accuracy of C-PIB-PET for predicting the progression from MCI to AD. In particular, the specificity, which reflects the exploratory nature of the use of amyloid imaging to identify the process of MCI to AD, was improved with a longer follow-up period.