Longitudinal changes of CSF biomarkers in memory clinic patients

The Associations of Phosphorylated Tau 181 and Tau 231 Levels in Plasma and Cerebrospinal Fluid with Cognitive Function in Alzheimer's Disease: A Systematic Review and Meta-Analysis

Background

Cerebrospinal fluid (CSF) or blood biomarkers like phosphorylated tau proteins (p-tau) are used to detect Alzheimer's disease (AD) early. Increasing studies on cognitive function and blood or CSF p-tau levels are controversial.

Objective

Our study examined the potential of p-tau as a biomarker of cognitive status in normal control (NC), mild cognitive impairment (MCI), and AD patients.

Methods

We searched PubMed, Cochrane, Embase, and Web of Science for relevant material through 12 January 2023. 5,017 participants from 20 studies-1,033 AD, 2,077 MCI, and 1,907 NC-were evaluated. Quantitative analysis provided continuous outcomes as SMDs with 95% CIs. Begg tested publication bias.

Results

MCI patients had lower CSF p-tau181 levels than AD patients (SMD =-0.60, 95% CI (-0.85, -0.36)) but higher than healthy controls (SMD = 0.67). AD/MCI patients had greater plasma p-tau181 levels than healthy people (SMD =-0.73, 95% CI (-1.04, -0.43)). MCI patients had significantly lower p-tau231 levels than AD patients in plasma and CSF (SMD =-0.90, 95% CI (-0.82, -0.45)). MCI patients showed greater CSF and plasma p-tau231 than healthy controls (SMD = 1.34, 95% CI (0.89, 1.79) and 0.43, (0.23, 0.64)). Plasma p-tau181/231 levels also distinguished the three categories. MCI patients had higher levels than healthy people, while AD patients had higher levels than MCI patients.

Conclusions

CSF p-tau181 and p-tau231 biomarkers distinguished AD, MCI, and healthy populations. Plasma-based p-tau181 and p-tau231 biomarkers for AD and MCI need further study.

Importance of cerebrospinal fluid storage conditions for the Alzheimer's disease diagnostics on an automated platform

OBJECTIVES

Alzheimer's disease (AD) is considered the most common cause of dementia in older people. Cerebrospinal fluid (CSF) Aβ1-42, Aβ1-40, total Tau (t-Tau), and phospho Tau (p-Tau) are important biomarkers for the diagnosis, however, they are highly dependent on the pre-analytical conditions. Our aim was to investigate the potential influence of different storage conditions on the simultaneous quantification of these biomarkers in a fully-automated platform to accommodate easier pre-analytical conditions for laboratories.

METHODS

CSF samples were obtained from 11 consecutive patients. Aβ1-42, Aβ1-40, p-Tau, and t-Tau were quantified using the LUMIPULSE G600II automated platform.

RESULTS

Temperature and storage days significantly influenced Aβ1-42 and Aβ1-40 with concentrations decreasing with days spent at 4 °C. The use of the Aβ1-42/Aβ1-40 ratio could partly compensate it. P-Tau and t-Tau were not affected by any of the tested storage conditions. For conditions involving storage at 4 °C, a correction factor of 1.081 can be applied. Diagnostic agreement was almost perfect in all conditions.

CONCLUSIONS

Cutoffs calculated in samples stored at -80 °C can be safely used in samples stored at -20 °C for 15-16 days or up to two days at RT and subsequent freezing at -80 °C. For samples stored at 4 °C, cutoffs would require applying a correction factor, allowing to work with the certainty of reaching the same clinical diagnosis.

Amyloid Positive Hydrocephalus: A Hydrocephalic Variant of Alzheimer's Disease?

BACKGROUND

Alzheimer's disease (AD) and normal pressure hydrocephalus (NPH) commonly coexist.

OBJECTIVE

We aimed to characterize an overlapping syndrome of AD and NPH that presents with gait disturbance, ventriculomegaly on magnetic resonance imaging, and significant amyloid deposition on positron emission tomography (PET).

METHODS

Of 114 patients who underwent cerebrospinal fluid (CSF) drainage for a possible diagnosis of NPH between 2015 and 2020 in Samsung Medical Center, we identified 24 patients (21.1%) with the NPH patients with amyloid deposition on PET, which we referred to as hydrocephalic AD in this study. We compared their clinical and imaging findings with those of 123 typical AD without hydrocephalic signs/symptoms. We also investigated the frequency and potential predictors of the tap test response in hydrocephalic AD.

RESULTS

Evans' index was 0.36±0.03, and a disproportionately enlarged subarachnoid space was present in 54.2% of the hydrocephalic AD patients. The mean age (75.2±7.3 years) and the APOE4 frequency (68.2%) did not differ from those of AD controls. However, the hydrocephalic AD patients showed better memory and language performance, and a thinner cingulate cortex. About 42% of the hydrocephalic AD patients responded to the tap test, of whom seven underwent shunt surgery. Cognition did not improve, whereas gait improved after shunt surgery in all.

CONCLUSION

Hydrocephalic AD has different neuropsychological and imaging characteristics from typical AD. Future studies are warranted to further investigate the effect of CSF removal on their clinical course and to elucidate the pathophysiological interaction between amyloid and NPH.

Cerebrospinal Fluid Biomarker Levels as Markers for Nursing Home Placement and Survival Time in Alzheimer's Disease

BACKGROUND

Cerebrospinal fluid (CSF) biomarkers are associated with conversion from mild cognitive impairment to Alzheimer's disease (AD), but their predictive value for later end-points has been less evaluated with inconsistent results.

OBJECTIVE

We investigated potential relationships between CSF amyloid-β1-42 (Aβ42), phosphorylat- ed tau (P-tau), and total tau (T-tau) with time to nursing home placement (NHP) and life expectan- cy after diagnosis.

METHODS

This prospective observational study included 129 outpatients clinically diagnosed with mild-to-moderate AD who underwent a lumbar puncture. The CSF biomarkers were analysed with xMAP technology. Dates of institutionalisation and death were recorded.

RESULTS

After 20 years of follow-up, 123 patients (95%) were deceased. The participants with ab- normal P-tau and T-tau (A+ T+ (N)+) died earlier than those with normal P-tau/abnormal T-tau (A+ T- (N)+) (mean, 80.5 vs. 85.4 years). Linear associations were demonstrated between lower Aβ42 and shorter time to NHP (p = 0.017), and higher P-tau and younger age at death (p = 0.016). No correlations were detected between survival after AD diagnosis and CSF biomarkers. In sex- and-age-adjusted Cox regression models, higher P-tau and T-tau were independent predictors of shorter lifespan after diagnosis. In multivariate Cox models, older age and lower baseline cognitive status, but not elevated tau, significantly precipitated both institutionalisation and death.

CONCLUSION

These findings suggest that CSF biomarker levels plateau in the dementia phase of AD, which may limit their possible relationships with clinical end-points, such as NHP and survi- val time. However, the biomarkers reflect the central pathophysiologies of AD. In particular, patho- logic tau is associated with more advanced disease, younger age at onset, and earlier death.

Cerebral Blood Flow Is Associated with Diagnostic Class and Cognitive Decline in Alzheimer's Disease

BACKGROUND

Reliable cerebral blood flow (CBF) biomarkers using a noninvasive imaging technique are sought to facilitate early diagnosis and intervention in early Alzheimer's disease (AD).

OBJECTIVE

We aim to identify brain regions in which CBF values are affected and related to cognitive decline in early AD using a large cohort.

METHODS

Perfusion MRIs using continuous arterial spin labeling were acquired at 1.5 T in 58 normal controls (NC), 50 mild cognitive impairments (MCI), and 40 AD subjects from the Cardiovascular Health Study Cognition Study. Regional absolute CBF and normalized CBF (nCBF) values, without and with correction of partial volume effects, were compared across three groups. Association between regional CBF values and Modified Mini-Mental State Examination (3MSE) were investigated by multiple linear regression analyses adjusted for cardiovascular risk factors.

RESULTS

After correcting for partial volume effects and cardiovascular risk factors, ADs exhibited decreased nCBF with the strongest reduction in the bilateral posterior cingulate & precuneus region (p < 0.001) compared to NCs, and the strongest reduction in the bilateral superior medial frontal region (p < 0.001) compared to MCIs. MCIs exhibited the strongest nCBF decrease in the left hippocampus and nCBF increase in the right inferior frontal and insular region. The 3MSE scores within the symptomatic subjects were significantly associated with nCBF in the bilateral posterior and middle cingulate and parietal (p < 0.001), bilateral superior medial frontal (p < 0.001), bilateral temporoparietal (p < 0.02), and right hippocampus (p = 0.02) regions.

CONCLUSION

Noninvasive perfusion MRI can detect functional changes across diagnostic class and serve as a staging biomarker of cognitive status.

Cerebral Blood Flow Predicts Conversion of Mild Cognitive Impairment into Alzheimer's Disease and Cognitive Decline: An Arterial Spin Labeling Follow-up Study

BACKGROUND

This is the first longitudinal study to assess regional cerebral blood flow (rCBF) changes during the progression from normal control (NC) through mild cognitive impairment (MCI) and Alzheimer's disease (AD).

OBJECTIVE

We aim to determine if perfusion MRI biomarkers, derived from our prior cross-sectional study, can predict the onset and cognitive decline of AD.

METHODS

Perfusion MRIs using arterial spin labeling (ASL) were acquired in 15 stable-NC, 14 NC-to-MCI, 16 stable-MCI, and 18 MCI/AD-to-AD participants from the Cardiovascular Health Study (CHS) cognition study. Group comparisons, predictions of AD conversion and time to conversion, and Modified Mini-Mental State Examination (3MSE) from rCBF were performed.

RESULTS

Compared to the stable-NC group: 1) the stable-MCI group exhibited rCBF decreases in the right temporoparietal (p = 0.00010) and right inferior frontal and insula (p = 0.0094) regions; and 2) the MCI/AD-to-AD group exhibited rCBF decreases in the bilateral temporoparietal regions (p = 0.00062 and 0.0035). Compared to the NC-to-MCI group, the stable-MCI group exhibited a rCBF decrease in the right hippocampus region (p = 0.0053). The baseline rCBF values in the posterior cingulate cortex (PCC) (p = 0.0043), bilateral superior medial frontal regions (BSMF) (p = 0.012), and left inferior frontal (p = 0.010) regions predicted the 3MSE scores for all the participants at follow-up. The baseline rCBF in the PCC and BSMF regions predicted the conversion and time to conversion from MCI to AD (p < 0.05; not significant after multiple corrections).

CONCLUSION

We demonstrated the feasibility of ASL in detecting rCBF changes in the typical AD-affected regions and the predictive value of baseline rCBF on AD conversion and cognitive decline.

Comparison of Diagnostic Performances Between Cerebrospinal Fluid Biomarkers and Amyloid PET in a Clinical Setting

The diagnostic performances of cerebrospinal fluid (CSF) biomarkers and amyloid positron emission tomography (PET) were compared by examining the association and concordance or discordance between CSF Aβ1-42 and amyloid PET, after determining our own cut-off values for CSF Alzheimer's disease (AD) biomarkers. Furthermore, we evaluated the ability of CSF biomarkers and amyloid PET to predict clinical progression. CSF Aβ1-42, t-tau, and p-tau levels were analyzed in 203 individuals [27 normal controls, 38 mild cognitive impairment (MCI), 62 AD dementia, and 76 patients with other neurodegenerative diseases] consecutively recruited from two dementia clinics. We used both visual and standardized uptake value ratio (SUVR)-based amyloid PET assessments for analyses. The association of CSF biomarkers with amyloid PET SUVR, hippocampal atrophy, and cognitive function were investigated by linear regression analysis, and the risk of conversion from MCI to AD dementia was assessed using a Cox proportional hazards model. CSF p-tau/Aβ1-42 and t-tau/Aβ1-42 exhibited the best diagnostic accuracies among the CSF AD biomarkers examined. Correlations were observed between CSF biomarkers and global SUVR, hippocampal volume, and cognitive function. Overall concordance and discordance between CSF Aβ1-42 and amyloid PET was 77% and 23%, respectively. Baseline positive CSF Aβ1-42 for MCI demonstrated a 5.6-fold greater conversion risk than negative CSF Aβ1-42 .  However, amyloid PET findings failed to exhibit significant prognostic value. Therefore, despite presence of a significant correlation between the CSF Aβ1-42 level and SUVR of amyloid PET, and a relevant concordance between CSF Aβ1-42 and amyloid PET, baseline CSF Aβ1-42 better predicted AD conversion.

Hyperconnectivity of Self-Referential Network as a Predictive Biomarker of the Progression of Alzheimer's Disease

BACKGROUND

Self-referential processing is associated with the progression of Alzheimer's disease (AD), and cerebrospinal fluid (CSF) proteins have become accepted biomarkers of AD.

OBJECTIVE

Our objective in this study was to focus on the relationships between the self-referential network (SRN) and CSF pathology in AD-spectrum patients.

METHODS

A total of 80 participants, including 20 cognitively normal, 20 early mild cognitive impairment (EMCI), 20 late MCI (LMCI), and 20 AD, were recruited for this study. Independent component analysis was used to explore the topological SRN patterns, and the abnormalities of this network were identified at different stages of AD. Finally, CSF pathological characteristics (i.e., CSF Aβ, t-tau, and p-tau) that affected the abnormalities of the SRN were further determined during the progression of AD.

RESULTS

Compared to cognitively normal subjects, AD-spectrum patients (i.e., EMCI, LMCI, and AD) showed a reversing trend toward an association between CSF pathological markers and the abnormal SRN occurring during the progression of AD. However, a certain disease state (i.e., the present LMCI) with a low concentration of CSF tau could evoke more hyperconnectivity of the SRN than other patients with progressively increasing concentrations of CSF tau (i.e., EMCI and AD), and this fluctuation of CSF tau was more sensitive to the hyperconnectivity of the SRN than the dynamic changes of CSF Aβ.

CONCLUSION

The integrity of the SRN was closely associated with CSF pathological characteristics, and these findings support the view that the hyperconnectivity of the SRN will play an important role in monitoring the progression of the pre-dementia state to AD.

Bridging the Gap Between Fluid Biomarkers for Alzheimer's Disease, Model Systems, and Patients

Alzheimer’s disease (AD) is a debilitating neurodegenerative disease characterized by the accumulation of two proteins in fibrillar form: amyloid-β (Aβ) and tau. Despite decades of intensive research, we cannot yet pinpoint the exact cause of the disease or unequivocally determine the exact mechanism(s) underlying its progression. This confounds early diagnosis and treatment of the disease. Cerebrospinal fluid (CSF) biomarkers, which can reveal ongoing biochemical changes in the brain, can help monitor developing AD pathology prior to clinical diagnosis. Here we review preclinical and clinical investigations of commonly used biomarkers in animals and patients with AD, which can bridge translation from model systems into the clinic. The core AD biomarkers have been found to translate well across species, whereas biomarkers of neuroinflammation translate to a lesser extent. Nevertheless, there is no absolute equivalence between biomarkers in human AD patients and those examined in preclinical models in terms of revealing key pathological hallmarks of the disease. In this review, we provide an overview of current but also novel AD biomarkers and how they relate to key constituents of the pathological cascade, highlighting confounding factors and pitfalls in interpretation, and also provide recommendations for standardized procedures during sample collection to enhance the translational validity of preclinical AD models.

Advantages and Pitfalls in Fluid Biomarkers for Diagnosis of Alzheimer's Disease

Alzheimer’s disease (AD) is a commonly occurring neurodegenerative disease in the advanced-age population, with a doubling of prevalence for each 5 years of age above 60 years. In the past two decades, there has been a sustained effort to find suitable biomarkers that may not only aide with the diagnosis of AD early in the disease process but also predict the onset of the disease in asymptomatic individuals. Current diagnostic evidence is supportive of some biomarker candidates isolated from cerebrospinal fluid (CSF), including amyloid beta peptide (Aβ), total tau (t-tau), and phosphorylated tau (p-tau) as being involved in the pathophysiology of AD. However, there are a few biomarkers that have been shown to be helpful, such as proteomic, inflammatory, oral, ocular and olfactory in the early detection of AD, especially in the individuals with mild cognitive impairment (MCI). To date, biomarkers are collected through invasive techniques, especially CSF from lumbar puncture; however, non-invasive (radio imaging) methods are used in practice to diagnose AD. In order to reduce invasive testing on the patients, present literature has highlighted the potential importance of biomarkers in blood to assist with diagnosing AD.

Cerebrospinal fluid neuronal pentraxin receptor as a biomarker of long-term progression of Alzheimer's disease: a 24-month follow-up study

Lower cerebrospinal fluid (CSF) levels of neuronal pentraxin receptor (NPTXR) are associated with Alzheimer's disease (AD), but few studies show longitudinal changes in CSF NPTXR. In the present study, CSF NPTXR was measured at 0, 12, and 24 months using an enzyme-linked immunosorbent assay. The study groups included 28 patients with mild cognitive impairment (MCI) (MCI-MCI), 27 MCI patients who progressed to AD (MCI-AD) during the study, and 28 AD patients (AD-AD). Baseline levels were assessed for 46 control individuals. AD patients had lower baseline CSF NPTXR than controls (p = 0.023). Linear mixed models estimated a 6.7% annualized decrease in CSF NPTXR in the AD-AD group, significantly different from MCI-MCI (p = 0.03) and MCI-AD groups (p = 0.048). CSF NPTXR did not correlate with CSF Aβ42 and weakly correlated with CSF Aβ40, T-tau, P-tau (all R² < 0.22, p < 0.06). These trends suggest CSF NPTXR may be a candidate biomarker of AD progression but not sufficiently sensitive to resolve when patients convert from MCI to dementia.

Cerebro-spinal fluid biomarker levels: phosphorylated tau (T) and total tau (N) as markers for rate of progression in Alzheimer's disease

Background

We investigated the potential associations between cerebro-spinal fluid (CSF) levels of phosphorylated tau (P-tau) and total tau (T-tau) with short-term response to cholinesterase inhibitor (ChEI) treatment, longitudinal outcome and progression rates in Alzheimer’s disease (AD).

Methods

This prospective, observational study included 129 participants clinically diagnosed with mild-to-moderate AD, who underwent a lumbar puncture. The CSF biomarkers amyloid-β_1–42 (Aβ₄₂), P-tau and T-tau were analysed with xMAP technology. Cognitive, global, instrumental and basic activities of daily living (ADL) capacities at the start of ChEI therapy and semi-annually over 3 years were evaluated.

Results

All patients had abnormal Aβ₄₂ (A+). Fifty-eight individuals (45%) exhibited normal P-tau and T-tau (A+ T– (N)–), 12 (9%) abnormal P-tau/normal T-tau (A+ T+ (N)–), 17 (13%) normal P-tau/abnormal T-tau (A+ T– (N)+) and 42 (33%) abnormal P-tau and T-tau (A+ T+ (N)+). The participants with A+ T+ (N)+ were younger than A+ T– (N)+ at the estimated onset of AD and the initiation of ChEIs. The proportion of 6-month responders to ChEI and deterioration/year after start of treatment did not differ between the AT(N) profiles in any scales. A higher percentage of globally improved/unchanged patients was exhibited in the A+ T– (N)– group after 12, 30 and 36 months of ChEI therapy but not at other assessments. In apolipoprotein E (APOE) ε4-carriers, linear relationships were found between greater cognitive decline/year and higher tau; Mini-Mental State Examination score – T-tau (r_s = − 0.257, p = 0.014) and Alzheimer’s Disease Assessment Scale–cognitive subscale – P-tau (r_s = − 0.242, p = 0.022). A correlation between faster progression in instrumental ADL (IADL) and higher T-tau was also detected (r_s = − 0.232, p = 0.028). These associations were not demonstrated in non-ε4-carriers.

Conclusions

Younger age and faster global deterioration were observed in AD patients with pathologic tau and neurodegeneration, whereas more rapid cognitive and IADL decline were related to higher P-tau or T-tau in APOE ε4-carriers only. The results might indicate an association between more pronounced tau pathology/neuronal injury and the APOE ε4-allele leading to a worse prognosis. Our findings showed that the AT(N) biomarker profiles have limited utility to predict AD progression rates and, thus, measure change and interpreting outcomes from clinical trials of future therapies.

[¹⁸F]THK5351 PET Imaging in Patients with Mild Cognitive Impairment

Background and Purpose

Mild cognitive impairment (MCI) is a condition with diverse clinical outcomes and subgroups. Here we investigated the topographic distribution of tau in vivo using the positron emission tomography (PET) tracer [¹⁸F]THK5351 in MCI subgroups.

Methods

This study included 96 participants comprising 38 with amnestic MCI (aMCI), 21 with nonamnestic MCI (naMCI), and 37 with normal cognition (NC) who underwent 3.0-T MRI, [¹⁸F]THK5351 PET, and detailed neuropsychological tests. [¹⁸F]flutemetamol PET was also performed in 62 participants. The aMCI patients were further divided into three groups: 1) verbal-aMCI, only verbal memory impairment; 2) visual-aMCI, only visual memory impairment; and 3) both-aMCI, both visual and verbal memory impairment. Voxel-wise statistical analysis and region-of-interest -based analyses were performed to evaluate the retention of [¹⁸F]THK5351 in the MCI subgroups. Subgroup analysis of amyloid-positive and -negative MCI patients was also performed. Correlations between [¹⁸F]THK5351 retention and different neuropsychological tests were evaluated using statistical parametric mapping analyses.

Results

[¹⁸F]THK5351 retention in the lateral temporal, mesial temporal, parietal, frontal, posterior cingulate cortices and precuneus was significantly greater in aMCI patients than in NC subjects, whereas it did not differ significantly between naMCI and NC participants. [¹⁸F] THK5351 retention was greater in the both-aMCI group than in the verbal-aMCI and visualaMCI groups, and greater in amyloid-positive than amyloid-negative MCI patients. The cognitive function scores were significantly correlated with cortical [¹⁸F]THK5351 retention.

Conclusions

[¹⁸F]THK5351 PET might be useful for identifying distinct topographic patterns of [¹⁸F]THK5351 retention in subgroups of MCI patients who are at greater risk of the progression to Alzheimer's dementia.

Diagnosis of Alzheimer's disease utilizing amyloid and tau as fluid biomarkers

Current technological advancements in clinical and research settings have permitted a more intensive and comprehensive understanding of Alzheimer’s disease (AD). This development in knowledge regarding AD pathogenesis has been implemented to produce disease-modifying drugs. The potential for accessible and effective therapeutic methods has generated a need for detecting this neurodegenerative disorder during early stages of progression because such remedial effects are more profound when implemented during the initial, prolonged prodromal stages of pathogenesis. The aggregation of amyloid-β (Aβ) and tau isoforms are characteristic of AD; thus, they are considered core candidate biomarkers. However, research attempting to establish the reliability of Aβ and tau as biomarkers has culminated in an amalgamation of contradictory results and theories regarding the biomarker concentrations necessary for an accurate diagnosis. In this review, we consider the capabilities and limitations of fluid biomarkers collected from cerebrospinal fluid, blood, and oral, ocular, and olfactory secretions as diagnostic tools for AD, along with the impact of the integration of these biomarkers in clinical settings. Furthermore, the evolution of diagnostic criteria and novel research findings are discussed. This review is a summary and reflection of the ongoing concerted efforts to establish fluid biomarkers as a diagnostic tool and implement them in diagnostic procedures.

Markers from body fluids could help clinicians diagnose Alzheimer’s disease before cognitive decline appears. After numerous setbacks in treating advanced Alzheimer’s, researchers are eager to identify biological indicators that facilitate earlier disease detection and interception. A review by YoungSoo Kim and colleagues at Yonsei University in South Korea, explores the promise of ‘fluid biomarkers,’ which enables diagnosis using cerebrospinal fluid (CSF), blood, oral, ocular, and olfactory fluid samples. Shifts in CSF levels of amyloid beta and tau, two proteins central to Alzheimer’s pathology, can reliably monitor at-risk individuals. Although CSF collection is unpleasant for patients, it remains more promising than blood, where current data for candidate fluid biomarkers are relatively inconclusive. In this review, investigations to discover safer, cheaper, and more reliable diagnostic tools to shift treatment from alleviation to prevention are introduced.

Longitudinal cerebrospinal fluid biomarker trajectories along the Alzheimer's disease continuum in the BIOMARKAPD study

INTRODUCTION

Within-person trajectories of cerebrospinal fluid (CSF) biomarkers in Alzheimer's disease (AD) are not well defined.

METHODS

We included 467 subjects from the BIOMARKAPD study with at least two serial CSF samples. Diagnoses were subjective cognitive decline (n = 75), mild cognitive impairment (n = 128), and AD dementia (n = 110), and a group of cognitively unimpaired subjects (n = 154) were also included. We measured baseline and follow-up CSF levels of total tau (t-tau), phosphorylated tau (p-tau), YKL-40, and neurofilament light (NfL). Median CSF sampling interval was 2.1 years.

RESULTS

CSF levels of t-tau, p-tau, NfL, and YKL-40 were 2% higher per each year of baseline age in controls (P <.001). In AD, t-tau levels were 1% lower (P <.001) and p-tau levels did not change per each year of baseline age. Longitudinally, only NfL (P <.001) and YKL-40 (P <.02) increased during the study period.

DISCUSSION

All four CSF biomarkers increase with age, but this effect deviates in AD for t-tau and p-tau.

Comparative analyses of plasma amyloid-β levels in heterogeneous and monomerized states by interdigitated microelectrode sensor system

Detection of amyloid-β (Aβ) aggregates contributes to the diagnosis of Alzheimer disease (AD). Plasma Aβ is deemed a less invasive and more accessible hallmark of AD, as Aβ can penetrate blood-brain barriers. However, correlations between biofluidic Aβ concentrations and AD progression has been tenuous. Here, we introduce a diagnostic technique that compares the heterogeneous and the monomerized states of Aβ in plasma. We used a small molecule, EPPS [4-(2-hydroxyethyl)-1-piperazinepropanesulfonic acid], to dissociate aggregated Aβ into monomers to enhance quantification accuracy. Subsequently, Aβ levels of EPPS-treated plasma were compared to those of untreated samples to minimize inter- and intraindividual variations. The interdigitated microelectrode sensor system was used to measure plasma Aβ levels on a scale of 0.1 pg/ml. The implementation of this self-standard blood test resulted in substantial distinctions between patients with AD and individuals with normal cognition (NC), with selectivity and sensitivity over 90%.

An Efficient Classifier for Alzheimer's Disease Genes Identification

Alzheimer’s disease (AD) is considered to one of 10 key diseases leading to death in humans. AD is considered the main cause of brain degeneration, and will lead to dementia. It is beneficial for affected patients to be diagnosed with the disease at an early stage so that efforts to manage the patient can begin as soon as possible. Most existing protocols diagnose AD by way of magnetic resonance imaging (MRI). However, because the size of the images produced is large, existing techniques that employ MRI technology are expensive and time-consuming to perform. With this in mind, in the current study, AD is predicted instead by the use of a support vector machine (SVM) method based on gene-coding protein sequence information. In our proposed method, the frequency of two consecutive amino acids is used to describe the sequence information. The accuracy of the proposed method for identifying AD is 85.7%, which is demonstrated by the obtained experimental results. The experimental results also show that the sequence information of gene-coding proteins can be used to predict AD.

The Combination of Functional and Structural MRI Is a Potential Screening Tool in Alzheimer's Disease

Introduction: This study aimed to survey the discrimination power of parameters from cerebrospinal fluid (CSF) biomarkers, fluorodeoxyglucose uptake on PET (FDG-PET), structural magnetic resonance imaging (MRI), and functional MRI in high- and low-risk subjects or in converters and stable subjects of normal and mild cognitive impairment (MCI) statuses. Methods: We used baseline resting-state functional MRI (rfMRI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to analyze functional networks and recorded subjects' characteristics and results of the CSF study, FDG-PET, and structural MRI from the ADNI website. All parameters were evaluated based on the between-group difference among normal (NC), MCI, and Alzheimer's disease (AD) groups. The parameters other than CSF results were included to study the difference between high- and low-AD-risk subjects in NC or MCI groups, based on CSF results. On the basis of two-year follow-up conditions, all parameters were compared between stable subjects and converters in NC and MCI. Results: CSF biomarkers, FDG-PET, structural MRI, and functional MRI are all able to differentiate AD from MCI or NC but not between MCI and NC. As compared with low-AD-risk subjects, high-risk subjects present decreased FDG-PET in both MCI and NC groups but structural MRI change only in MCI status and rfMRI alteration only in NC status. As compared with stable subjects, converters have decreased FDG-PET, functional network changes, and structural changes in both MCI and NC groups. Conclusion: The combination of functional and structural MRI is a safer screening tool but with similar power as FDG-PET to reflect CSF change in the AD pathological process and to identify high-risk subjects and converters in NC and MCI.

Identification of Alzheimer's disease and mild cognitive impairment using multimodal sparse hierarchical extreme learning machine

Different modalities such as structural MRI, FDG-PET, and CSF have complementary information, which is likely to be very useful for diagnosis of AD and MCI. Therefore, it is possible to develop a more effective and accurate AD/MCI automatic diagnosis method by integrating complementary information of different modalities. In this paper, we propose multi-modal sparse hierarchical extreme leaning machine (MSH-ELM). We used volume and mean intensity extracted from 93 regions of interest (ROIs) as features of MRI and FDG-PET, respectively, and used p-tau, t-tau, and A β 42 as CSF features. In detail, high-level representation was individually extracted from each of MRI, FDG-PET, and CSF using a stacked sparse extreme learning machine auto-encoder (sELM-AE). Then, another stacked sELM-AE was devised to acquire a joint hierarchical feature representation by fusing the high-level representations obtained from each modality. Finally, we classified joint hierarchical feature representation using a kernel-based extreme learning machine (KELM). The results of MSH-ELM were compared with those of conventional ELM, single kernel support vector machine (SK-SVM), multiple kernel support vector machine (MK-SVM) and stacked auto-encoder (SAE). Performance was evaluated through 10-fold cross-validation. In the classification of AD vs. HC and MCI vs. HC problem, the proposed MSH-ELM method showed mean balanced accuracies of 96.10% and 86.46%, respectively, which is much better than those of competing methods. In summary, the proposed algorithm exhibits consistently better performance than SK-SVM, ELM, MK-SVM and SAE in the two binary classification problems (AD vs. HC and MCI vs. HC).

Multi-task fused sparse learning for mild cognitive impairment identification

BACKGROUND

Brain functional connectivity network (BFCN) has been widely applied to identify biomarkers for the brain function understanding and brain diseases analysis.

OBJECTIVE

Building a biologically meaningful brain network is a crucial work in these applications. For this task, sparse learning has been widely applied for the network construction. If multiple time-point data is added to the brain imaging application, the disease progression pattern in the longitudinal analysis can be better revealed.

METHODS

A novel longitudinal analysis for MCI classification is devised based on resting-state functional magnetic resonating imaging (rs-fMRI). Specifically, this paper proposes a novel multi-task learning method to integrate fused penalty by regularization. In addition, a novel objective function is developed for fused sparse learning via smoothness constraint.

RESULTS

The proposed method achieves the best classification performance with an accuracy of 95.74% for baseline and 93.64% for year 1 data.

CONCLUSIONS

The experimental results show that our proposed method achieves quite promising classification performance.

A Systematic Review of Longitudinal Studies Which Measure Alzheimer's Disease Biomarkers

Alzheimer’s disease (AD) is a progressive and fatal neurodegenerative disease, with no effective treatment or cure. A gold standard therapy would be treatment to slow or halt disease progression; however, knowledge of causation in the early stages of AD is very limited. In order to determine effective endpoints for possible therapies, a number of quantitative surrogate markers of disease progression have been suggested, including biochemical and imaging biomarkers. The dynamics of these various surrogate markers over time, particularly in relation to disease development, are, however, not well characterized. We reviewed the literature for studies that measured cerebrospinal fluid or plasma amyloid-β and tau, or took magnetic resonance image or fluorodeoxyglucose/Pittsburgh compound B-positron electron tomography scans, in longitudinal cohort studies. We summarized the properties of the major cohort studies in various countries, commonly used diagnosis methods and study designs. We have concluded that additional studies with repeat measures over time in a representative population cohort are needed to address the gap in knowledge of AD progression. Based on our analysis, we suggest directions in which research could move in order to advance our understanding of this complex disease, including repeat biomarker measurements, standardization and increased sample sizes.

Amsterdam Dementia Cohort: Performing Research to Optimize Care

The Alzheimer center of the VU University Medical Center opened in 2000 and was initiated to combine both patient care and research. Together, to date, all patients forming the Amsterdam Dementia Cohort number almost 6,000 individuals. In this cohort profile, we provide an overview of the results produced based on the Amsterdam Dementia Cohort. We describe the main results over the years in each of these research lines: 1) early diagnosis, 2) heterogeneity, and 3) vascular factors. Among the most important research efforts that have also impacted patients' lives and/or the research field, we count the development of novel, easy to use diagnostic measures such as visual rating scales for MRI and the Amsterdam IADL Questionnaire, insight in different subgroups of AD, and findings on incidence and clinical sequelae of microbleeds. Finally, we describe in the outlook how our research endeavors have improved the lives of our patients.

Label-aligned multi-task feature learning for multimodal classification of Alzheimer's disease and mild cognitive impairment

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer's disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI.

Cognitive function in very old men does not correlate to biomarkers of Alzheimer's disease

Background

The Alzheimer’s disease (AD) brain displays atrophy with amyloid-β (Aβ) and tau deposition, whereas decreased Aβ42 and increased tau are measured in cerebrospinal fluid (CSF). The aim of this study was to relate cognitive performance to the degree of brain atrophy, CSF biomarker levels and neuropathology in a cohort of aged men.

Methods

Fifty-eight 86–92-year-old men from the Uppsala Longitudinal Study of Adult Men (ULSAM) cohort underwent cognitive testing, brain computed tomography and lumbar puncture. Atrophy was graded with established scales. Concentrations of CSF Aβ42, t-tau and p-tau were measured by ELISA. Thirteen brains were examined post mortem.

Results

Forty-six of the individuals were considered non-demented, whereas twelve were diagnosed with dementia, either at baseline (n = 4) or during follow-up (n = 8). When comparing subjects with and without dementia, there were no differences in the degree of atrophy, although the mini mental state examination (MMSE) scoring correlated weakly with the degree of medial temporal atrophy (MTA) (p = 0.04). Moreover, the CSF biomarker levels did not differ significantly between healthy (n = 27) and demented (n = 8) subjects (median values 715 vs 472 pg/ml for Aβ42, 414 vs 427 pg/ml for t-tau and 63 vs 60 pg/ml for p-tau). Similarly, there were no differences in the biomarker levels between individuals with mild (n = 24) and severe (n = 11) MTA (median values 643 vs 715 pg/ml for Aβ42, 441 vs 401 pg/ml for t-tau and 64 vs 53 pg/ml for p-tau). Finally, the neuropathological changes did not correlate with any of the other measures.

Conclusion

In this cohort of aged men only a weak correlation could be seen between cognitive performance and MTA, whereas the various neuroradiological, biochemical and neuropathological measures did not correlate with each other. Thus, AD biomarkers seem to be less informative in subjects of an advanced age.

Alzheimer's disease and metabolic syndrome: A link from oxidative stress and inflammation to neurodegeneration

Alzheimer's disease (AD) is the most common cause of dementia and one of the most important causes of morbidity and mortality among the aging population. AD diagnosis is made post-mortem, and the two pathologic hallmarks, particularly evident in the end stages of the illness, are amyloid plaques and neurofibrillary tangles. Currently, there is no curative treatment for AD. Additionally, there is a strong relation between oxidative stress, metabolic syndrome, and AD. The high levels of circulating lipids and glucose imbalances amplify lipid peroxidation that gradually diminishes the antioxidant systems, causing high levels of oxidative metabolism that affects cell structure, leading to neuronal damage. Accumulating evidence suggests that AD is closely related to a dysfunction of both insulin signaling and glucose metabolism in the brain, leading to an insulin-resistant brain state. Four drugs are currently used for this pathology: Three FDA-approved cholinesterase inhibitors and one NMDA receptor antagonist. However, wide varieties of antioxidants are promissory to delay or prevent the symptoms of AD and may help in treating the disease. Therefore, therapeutic efforts to achieve attenuation of oxidative stress could be beneficial in AD treatment, attenuating Aβ-induced neurotoxicity and improve neurological outcomes in AD. The term inflammaging characterizes a widely accepted paradigm that aging is accompanied by a low-grade chronic up-regulation of certain pro-inflammatory responses in the absence of overt infection, and is a highly significant risk factor for both morbidity and mortality in the elderly.

Free and Cued Selective Reminding Test - accuracy for the differential diagnosis of Alzheimer's and neurodegenerative diseases: A large-scale biomarker-characterized monocenter cohort study (ClinAD)

INTRODUCTION

The International Working Group recommended the Free and Cued Selective Reminding Test (FCSRT) as a sensitive detector of the amnesic syndrome of the hippocampal type in typical Alzheimer's disease (AD). But does it differentiate AD from other neurodegenerative diseases?

METHODS

We assessed the FCSRT and cerebrospinal fluid (CSF) AD biomarkers in 992 cases. Experts, blinded to biomarker data, attributed in 650 cases a diagnosis of typical AD, frontotemporal dementia, posterior cortical atrophy, Lewy body disease, progressive supranuclear palsy, corticobasal syndrome, primary progressive aphasias, "subjective cognitive decline," or depression.

RESULTS

The FCSRT distinguished typical AD from all other conditions with a sensitivity of 100% and a specificity of 75%. Non-AD neurodegenerative diseases with positive AD CSF biomarkers ("atypical AD") did not have lower FCSRT scores than those with negative biomarkers.

DISCUSSION

The FCSRT is a reliable tool for diagnosing typical AD among various neurodegenerative diseases. At an individual level, however, its specificity is not absolute. Our findings also widen the spectrum of atypical AD to multiple neurodegenerative conditions.

CSF Biomarkers and Its Associations with 18F-AV133 Cerebral VMAT2 Binding in Parkinson's Disease-A Preliminary Report

OBJECTIVE

Cerebrospinal fluid (CSF) biomarkers, such as α-synuclein (α-syn), amyloid beta peptide 1-42 (Aβ1-42), phosphorylated tau (181P) (p-tau), and total tau (t-tau), have long been associated with the development of Parkinson disease (PD) and other neurodegenerative diseases. In this investigation, we reported the assessment of CSF biomarkers and their correlations with vesicular monoamine transporter 2 (VMAT2) bindings measured with 18F-9-fluoropropyl-(+)-dihydrotetrabenazine (18F-AV133) that is being developed as a biomarker for PD. We test the hypothesis that monoaminergic degeneration was correlated with CSF biomarker levels in untreated PD patients.

METHODS

The available online data from the Parkinson's Progression Markers Initiative study (PPMI) project were collected and analyzed, which include demographic information, clinical evaluations, CSF biomarkers (α-syn, Aβ1-42, p-tau, and t-tau), 18F-AV133 brain PET, and T1 weighted MRIs. Region of interest (ROI) and voxel-wise Pearson correlation between standardized uptake value ratio (SUVR) and CSF biomarkers were calculated.

RESULTS

Our major findings are: 1) Compared with controls, CSF α-syn and tau levels decreased significantly in PD; 2) α-syn was closely correlated with Aβ1-42 and tau in PD, especially in early-onset patients; and 3) hypothesis-driven ROI analysis found a significant negative correlation between CSF Aβ1-42 levels and VMAT2 densities in post cingulate, left caudate, left anterior putamen, and left ventral striatum in PDs. CSF t-tau and p-tau levels were significantly negatively related to VMAT2 SUVRs in substantia nigra and left ventral striatum, respectively. Voxel-wise analysis showed that left caudate, parahippocampal gyrus, insula and temporal lobe were negatively correlated with Aβ1-42. In addition, superior frontal gyrus and transverse temporal gyrus were negatively correlated with CSF p-tau levels.

CONCLUSION

These results suggest that monoaminergic degeneration in PD is correlated with CSF biomarkers associated with cognitive impairment in neurodegenerative diseases including Alzheimer's disease. The association between loss of dopamine synaptic function and pathologic protein accumulations in PD indicates an important role of CSF biomarkers in PD development.

Informants' Perception of Subjective Cognitive Decline Helps to Discriminate Preclinical Alzheimer's Disease from Normal Aging

BACKGROUND

Self-reported and informant-reported subjective cognitive decline (SCD) may be useful in the detection of preclinical Alzheimer's disease (Pre-AD) and cognitive impairment related to abnormal amyloid-β (Aβ 42) levels.

OBJECTIVES

a) To compare the Subjective Cognitive Decline Questionnaire (SCD-Q) ratings between Pre-AD subjects and cognitively healthy controls, b) to study the association of SCD-Q scores with levels of AD biomarkers in cognitively healthy and cognitively impaired subjects, and c) to compare SCD-Q ratings in cognitively impaired subjects with or without abnormal Aβ 42.

METHODS

Two hundred and seventeen participants (111 subjects; 106 informants) answered the SCD-Q. All subjects underwent a lumbar puncture to determine levels of Aβ 42 and tau, and an extensive neuropsychological battery. Healthy subjects were classified as Controls (CTR) or Pre-AD according to the absence or the presence of abnormal Aβ 42, and those with cognitive impairment (CI) into Non-amyloid (NonAB-CI) or Amyloid (AB-CI) impairment.

RESULTS

Informants' SCD-Q scores were significantly higher in the Pre-AD group than in the CTR group (F = 6.75; p = 0.01). No significant differences were found in self-ratings. In the cognitively impaired groups, there were no significant differences in the SCD-Q ratings. In the whole sample, informants' ratings of SCD-Q correlated with Aβ 42 (r = -0.21; p = 0.02) and tau levels (r = 0.28; p = 0.00).

CONCLUSIONS

Higher informants' ratings of SCD-Q differentiated Pre-AD subjects from CTR. Informants' ratings of SCD-Q correlated weakly with cerebrospinal fluid AD biomarkers.

Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment. However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper, we propose a novel temporallyconstrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term thatrequires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term thatrequires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers.

Graph-guided joint prediction of class label and clinical scores for the Alzheimer's disease

Accurate diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, is very important for early treatment. Over the last decade, various machine learning methods have been proposed to predict disease status and clinical scores from brain images. It is worth noting that many features extracted from brain images are correlated significantly. In this case, feature selection combined with the additional correlation information among features can effectively improve classification/regression performance. Typically, the correlation information among features can be modeled by the connectivity of an undirected graph, where each node represents one feature and each edge indicates that the two involved features are correlated significantly. In this paper, we propose a new graph-guided multi-task learning method incorporating this undirected graph information to predict multiple response variables (i.e., class label and clinical scores) jointly. Specifically, based on the sparse undirected feature graph, we utilize a new latent group Lasso penalty to encourage the correlated features to be selected together. Furthermore, this new penalty also encourages the intrinsic correlated tasks to share a common feature subset. To validate our method, we have performed many numerical studies using simulated datasets and the Alzheimer's Disease Neuroimaging Initiative dataset. Compared with the other methods, our proposed method has very promising performance.

Longitudinal cerebrospinal fluid biomarker measurements in preclinical sporadic Alzheimer's disease: A prospective 9-year study

Introduction

Ascertainment of the pattern and temporal change of biomarkers in preclinical (asymptomatic) sporadic Alzheimer's disease (AD) will increase knowledge about early pathogenesis and facilitate interventional therapeutic trials.

Methods

In this prospective longitudinal study, repeated cerebrospinal fluid (CSF) collections and cognitive evaluations were performed in cognitively healthy elderly individuals during a 9-year period.

Results

Low CSF β-amyloid (Aβ)₄₂ levels predicted subsequent development of clinical AD 9 years later. Noteworthy, one-third of individuals with pathologically low baseline Aβ₄₂ levels remained cognitively intact during follow-up. No further decrease in Aβ₄₂ was seen in those with low levels already at baseline.

Discussion

CSF Aβ₄₂ predicts sporadic AD at least 9 years before dementia onset and has plateaued already at this time. However, many individuals can harbor brain amyloid accumulation over a decade without signs of cognitive deterioration, which could implicate how CSF biomarkers are used to identify preclinical AD in future interventional therapeutic trials.

Cerebrospinal fluid VILIP-1 and YKL-40, candidate biomarkers to diagnose, predict and monitor Alzheimer's disease in a memory clinic cohort

Introduction

We examined the utility of cerebrospinal fluid (CSF) proteins, Chitinase-3-like protein 1 (CHI3L1 or YKL-40), a putative marker of inflammation, and Visinin-like protein-1 (VILIP-1), a marker for neuronal injury, for diagnostic classification and monitoring of disease progression in a memory clinic cohort.

Methods

CSF levels of YKL-40 and VILIP-1 were measured in 37 cognitively normal, 61 Mild Cognitive Impairment (MCI) and 65 Alzheimer’s disease (AD) patients from the memory clinic-based Amsterdam Dementia Cohort who underwent two lumbar punctures, with minimum interval of 6 months and a mean(SE) interval of 2.0(0.1) years. Mean(SE) cognitive follow-up was 3.8 (0.2) years. ANOVA was used to compare baseline differences of log-transformed CSF measures. Cox proportional hazard models were used to evaluate disease progression as a function of CSF tertiles. Linear mixed models were used to evaluate longitudinal change over time. All analyses were sex and age adjusted.

Results

Baseline levels of YKL-40, but not VILIP-1, were higher in MCI and AD patients compared to cognitively normal individuals (mean (SE) pg/mL, 304 (16) and 288 (12) vs. 231 (16), p = 0.03 and p = 0.006). Baseline levels of both YKL-40 and VILIP-1 in MCI predicted progression to AD (HR 95 % CI = 3.0 (1.1–7.9) and 4.4 (1.5–13.0), respectively, for highest vs. lowest tertile). YKL-40 increased longitudinally in patients with MCI and AD (mean (SE) pg/mL per year, 8.9 (3.0) and 7.1 (3.1), respectively), but not in cognitively normal individuals, whereas levels of VILIP-1 increased only in MCI (mean (SE), 10.7 (2.6) pg/mL per year).

Conclusions

CSF levels of YKL-40 may have utility for discriminating between cognitively normal individuals and patients with MCI or AD. Increased levels of both YKL-40 and VILIP-1 may be associated with disease progression. These CSF biomarkers should be considered for future evaluation in the characterization of the natural history of AD.

Boosting brain connectome classification accuracy in Alzheimer's disease using higher-order singular value decomposition

Alzheimer's disease (AD) is a progressive brain disease. Accurate detection of AD and its prodromal stage, mild cognitive impairment (MCI), are crucial. There is also a growing interest in identifying brain imaging biomarkers that help to automatically differentiate stages of Alzheimer's disease. Here, we focused on brain structural networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying different stages of Alzheimer's disease.

Update on the core and developing cerebrospinal fluid biomarkers for Alzheimer disease

Alzheimer disease (AD) is a complex neurodegenerative disorder, whose prevalence will dramatically rise by 2050. Despite numerous clinical trials investigating this disease, there is still no effective treatment. Many trials showed negative or inconclusive results, possibly because they recruited only patients with severe disease, who had not undergone disease-modifying therapies in preclinical stages of AD before severe degeneration occurred. Detection of AD in asymptomatic at risk individuals (and a few presymptomatic individuals who carry an autosomal dominant monogenic AD mutation) remains impractical in many of clinical situations and is possible only with reliable biomarkers. In addition to early diagnosis of AD, biomarkers should serve for monitoring disease progression and response to therapy. To date, the most promising biomarkers are cerebrospinal fluid (CSF) and neuroimaging biomarkers. Core CSF biomarkers (amyloid β_1-42, total tau, and phosphorylated tau) showed a high diagnostic accuracy but were still unreliable for preclinical detection of AD. Hence, there is an urgent need for detection and validation of novel CSF biomarkers that would enable early diagnosis of AD in asymptomatic individuals. This article reviews recent research advances on biomarkers for AD, focusing mainly on the CSF biomarkers. In addition to core CSF biomarkers, the potential usefulness of novel CSF biomarkers is discussed.

Homozygous carriers of APP A713T mutation in an autosomal dominant Alzheimer disease family

OBJECTIVE

To report, for the first time, a large autosomal dominant Alzheimer disease (AD) family in which the APP A713T mutation is present in the homozygous and heterozygous state. To date, the mutation has been reported as dominant, and in the heterozygous state associated with familial AD and cerebrovascular lesions.

METHODS

The family described here has been genealogically reconstructed over 6 generations dating back to the 19th century. Plasma β-amyloid peptide was measured. Sequencing of causative AD genes was performed.

RESULTS

Twenty-one individuals, all but 1 born from 2 consanguineous unions, were studied: 8 were described as affected through history, 5 were studied clinically and genetically, and 8 were asymptomatic at-risk subjects. The A713T mutation was detected in the homozygous state in 3 patients and in the heterozygous state in 8 subjects (6 asymptomatic and 2 affected).

CONCLUSIONS

Our findings, also supported by the β-amyloid plasma assay, confirm (1) the pathogenic role of the APP A713T mutation, (2) the specific phenotype (AD with cerebrovascular lesions) associated with this mutation, and (3) the large span of age at onset, not influenced by APOE, TOMM40, and TREM2 genes. No substantial differences concerning clinical phenotype were evidenced between heterozygous and homozygous patients, in line with the classic definition of dominance. Therefore, in this study, AD followed the classic definition of a dominant disease, contrary to that reported in a previously described AD family with recessive APP mutation. This confirms that genetic AD may be considered a disease with dominant and recessive traits of inheritance.

Assessment of CSF Aβ42 as an aid to discriminating Alzheimer's disease from other dementias and mild cognitive impairment: a meta-analysis of 50 studies

Mild Alzheimer's disease (AD) is usually difficult to differentiate from other dementias or mild cognitive impairment (MCI). The aim of our study is to evaluate the clinical importance of cerebrospinal fluid (CSF) β-amyloid 42 (Aβ42) in MCI, AD and other dementias, more specifically: frontotemporal dementia (FTD), dementia with Lewy bodies (DLB), Parkinson's disease (PD) with dementia (PDD) and vascular dementia (VaD). Fifty eligible articles were identified by search of databases including PubMed, EMBASE, Elsevier, Springer Link and the Cochrane Library, from January 1990 to May 2014. The random effects model was used to calculate the standardized mean difference (SMD) with corresponding 95% CI by STATA 9.0 software. The subgroup analyses were made on the method (ELISA, xMAP). We found that CSF Aβ42 concentrations were significantly lower in AD compared to MCI (SMD: -0.68, 95% CI: [-0.80, -0.56], z=11.34, P<0.001), FTD (SMD: -1.09, 95% CI: [-1.41, -0.76], z=6.62, P<0.001), PDD (SMD: -0.75, 95% CI: [-1.39, -0.10], z=2.27, P=0.023), VaD (SMD: -0.95, 95% CI: [-1.30, -0.61], z=5.43, P<0.001). In addition, compared to DLB, Aβ42 concentrations are moderately lower in AD (SMD: -0.27, 95% CI: [-0.51, -0.03], z=2.20, P=0.028). Results from this meta-analysis hinted that CSF Aβ42 is a good biomarker for discriminating Alzheimer's disease from other dementias and MCI.

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

BACKGROUND

According to the latest revised National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (now known as the Alzheimer's Association) (NINCDS-ADRDA) diagnostic criteria for Alzheimer's disease dementia of the National Institute on Aging and Alzheimer Association, the confidence in diagnosing mild cognitive impairment (MCI) due to Alzheimer's disease dementia is raised with the application of biomarkers based on measures in the cerebrospinal fluid (CSF) or imaging. These tests, added to core clinical criteria, might increase the sensitivity or specificity of a testing strategy. However, the accuracy of biomarkers in the diagnosis of Alzheimer's disease dementia and other dementias has not yet been systematically evaluated. A formal systematic evaluation of sensitivity, specificity, and other properties of plasma and CSF amyloid beta (Aß) biomarkers was performed.

OBJECTIVES

To determine the accuracy of plasma and CSF Aß levels for detecting those patients with MCI who would convert to Alzheimer's disease dementia or other forms of dementia over time.

SEARCH METHODS

The most recent search for this review was performed on 3 December 2012. We searched MEDLINE (OvidSP), EMBASE (OvidSP), BIOSIS Previews (ISI Web of Knowledge), Web of Science and Conference Proceedings (ISI Web of Knowledge), PsycINFO (OvidSP), and LILACS (BIREME). We also requested a search of the Cochrane Register of Diagnostic Test Accuracy Studies (managed by the Cochrane Renal Group).No language or date restrictions were applied to the electronic searches and methodological filters were not used so as to maximise sensitivity.

SELECTION CRITERIA

We selected those studies that had prospectively well defined cohorts with any accepted definition of cognitive decline, but no dementia, with baseline CSF or plasma Aß levels, or both, documented at or around the time the above diagnoses were 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 plasma and CSF Aß biomarker results by disease status. Moreover, studies were only selected if they applied a reference standard for Alzheimer's 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. We assessed the identified full papers for eligibility and extracted data to create standard two by two tables. Two independent assessors performed quality assessment using the QUADAS-2 tool. 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

Alzheimer's disease dementia was evaluated in 14 studies using CSF Aß42. Of the 1349 participants included in the meta-analysis, 436 developed Alzheimer's dementia. Individual study estimates of sensitivity were between 36% and 100% while the specificities were between 29% and 91%. Because of the variation in assay thresholds, we did not estimate summary sensitivity and specificity. However, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary ROC curve. At the median specificity of 64%, the sensitivity was 81% (95% CI 72 to 87). This equated to a positive likelihood ratio (LR+) of 2.22 (95% CI 2.00 to 2.47) and a negative likelihood ratio (LR-) of 0.31 (95% CI 0.21 to 0.48).The accuracy of CSF Aß42 for all forms of dementia was evaluated in four studies. Of the 464 participants examined, 188 developed a form of dementia (Alzheimer's disease and other forms of dementia).The thresholds used were between 209 mg/ml and 512 ng/ml. The sensitivities were between 56% and 75% while the specificities were between 47% and 76%. At the median specificity of 75%, the sensitivity was estimated to be 63% (95% CI 22 to 91) from the meta-analytic model. This equated to a LR+ of 2.51 (95% CI 1.30 to 4.86) and a LR- of 0.50 (95% CI 0.16 to 1.51).The accuracy of CSF Aß42 for non-Alzheimer's disease dementia was evaluated in three studies. Of the 385 participants examined, 61 developed non-Alzheimer's disease dementia. Since there were very few studies and considerable variation between studies, the results were not meta-analysed. The sensitivities were between 8% and 63% while the specificities were between 35% and 67%.Only one study examined the accuracy of plasma Aß42 and the plasma Aß42/Aß40 ratio for Alzheimer's disease dementia. The sensitivity of 86% (95% CI 81 to 90) was the same for both tests while the specificities were 50% (95% CI 44 to 55) and 70% (95% CI 64 to 75) for plasma Aß42 and the plasma Aß42/Aß40 ratio respectively. Of the 565 participants examined, 245 developed Alzheimer's dementia and 87 non-Alzheimer's disease dementia.There was substantial heterogeneity between studies. The accuracy of Aß42 for the diagnosis of Alzheimer's disease dementia did not differ significantly (P = 0.8) between studies that pre-specified the threshold for determining test positivity (n = 6) and those that only determined the threshold at follow-up (n = 8). One study excluded a sample of MCI non-Alzheimer's disease dementia converters from their analysis. In sensitivity analyses, the exclusion of this study had no impact on our findings. The exclusion of eight studies (950 patients) that were considered at high (n = 3) or unclear (n = 5) risk of bias for the patient selection domain also made no difference to our findings.

AUTHORS' CONCLUSIONS

The proposed diagnostic criteria for prodromal dementia and MCI due to Alzheimer's disease, although still being debated, would be fulfilled where there is both core clinical and cognitive criteria and a single biomarker abnormality. From our review, the measure of abnormally low CSF Aß levels has very little diagnostic benefit with likelihood ratios suggesting only marginal clinical utility. The quality of reports was also poor, and thresholds and length of follow-up were inconsistent. We conclude that when applied to a population of patients with MCI, CSF Aß levels cannot be recommended as an accurate test for Alzheimer's disease.

Identification of longitudinally dynamic biomarkers in Alzheimer's disease cerebrospinal fluid by targeted proteomics

Background

Alzheimer’s disease (AD) is the leading cause of dementia affecting greater than 26 million people worldwide. Although cerebrospinal fluid (CSF) levels of Aβ₄₂, tau, and p-tau₁₈₁ are well established as diagnostic biomarkers of AD, there is a need for additional CSF biomarkers of neuronal function that continue to change during disease progression and could be used as pharmacodynamic measures in clinical trials. Multiple proteomic discovery experiments have reported a range of CSF biomarkers that differ between AD and control subjects. These potential biomarkers represent multiple aspects of the disease pathology. The performance of these markers has not been compared with each other, and their performance has not been evaluated longitudinally.

Results

We developed a targeted-proteomic, multiple reaction monitoring (MRM) assay for the absolute quantitation of 39 peptides corresponding to 30 proteins. We evaluated the candidate biomarkers in longitudinal CSF samples collected from aged, cognitively-normal control (n = 10), MCI (n = 5), and AD (n = 45) individuals (age > 60 years). We evaluated each biomarker for diagnostic sensitivity, longitudinal consistency, and compared with CSF Aβ₄₂, tau, and p-tau₁₈₁. Four of 28 quantifiable CSF proteins were significantly different between aged, cognitively-normal controls and AD subjects including chitinase-3-like protein 1, reproducing published results. Four CSF markers demonstrated significant longitudinal change in AD: Amyloid precursor protein, Neuronal pentraxin receptor, NrCAM and Chromogranin A. Robust correlations were observed within some subgroups of proteins including the potential disease progression markers.

Conclusion

Using a targeted proteomics approach, we confirmed previous findings for a subset of markers, defined longitudinal performance of our panel of markers, and established a flexible proteomics method for robust multiplexed analyses.

Does CSF p-tau181 help to discriminate Alzheimer's disease from other dementias and mild cognitive impairment? A meta-analysis of the literature

To evaluate the clinical importance of cerebrospinal fluid (CSF) phosphorylated tau 181 (p-tau181) in mild cognitive impairment (MCI), Alzheimer's disease (AD) and other dementias, more specifically: frontotemporal degeneration (FTD), dementia with Lewy bodies (DLB), vascular dementia (VaD) and Parkinson's disease (PD) with dementia (PDD). Fifty eligible articles were identified by search of databases including PubMed, EMBASE, Elsevier, Springer Link and the Cochrane Library, up to December 2013. The random effects model was used to calculate the standardized mean difference (SMD) with corresponding 95% CI by STATA 9.0 software. The subgroup analyses were made on the methods or PD with dementia. We found that CSF p-tau181 concentrations were significantly higher in AD compared to MCI [SMD: 0.61, 95% CI: (0.46, 0.76), z = 8.07, P < 0.001], FTD [SMD: 1.23, 95% CI: (0.89, 1.56), z = 7.19, P < 0.001], DLB [SMD: 1.08, 95% CI: (0.80, 1.37), z = 7.41, P < 0.001], PDD [SMD: 1.05, 95% CI: (0.02, 2.07), z = 2.00, P = 0.045] and VaD [SMD: 1.28, 95% CI: (0.68, 1.88), z = 4.19, P < 0.001]. Results from this meta-analysis implied that CSF p-tau181 is a good biomarker for discriminating Alzheimer's disease from other dementias and mild cognitive impairment.

Comparing positron emission tomography imaging and cerebrospinal fluid measurements of β-amyloid

OBJECTIVE

We examined agreement and disagreement between 2 biomarkers of β-amyloid (Aβ) deposition (amyloid positron emission tomography [PET] and cerebrospinal fluid [CSF] Aβ1-42 ) in normal aging and dementia in a large multicenter study.

METHODS

Concurrently acquired florbetapir PET and CSF Aβ were measured in cognitively normal, mild cognitive impairment (MCI), and Alzheimer's disease participants (n = 374) from the Alzheimer's Disease Neuroimaging Initiative. We also compared Aβ measurements in a separate group with serial CSF measurements over 3.1 ± 0.8 years that preceded a single florbetapir session. Additional biomarker and cognitive data allowed us to further examine profiles of discordant cases.

RESULTS

Florbetapir and CSF Aβ were inversely correlated across all diagnostic groups, and dichotomous measurements were in agreement in 86% of subjects. Among subjects showing the most disagreement, the 2 discordant groups had different profiles: the florbetapir(+) /CSF Aβ(-) group was larger (n = 13) and was made up of only normal and early MCI subjects, whereas the florbetapir(-) /CSF Aβ(+) group was smaller (n = 7) and had poorer cognitive function and higher CSF tau, but no ApoE4 carriers. In the longitudinal sample, we observed both stable longitudinal CSF Aβ trajectories and those actively transitioning from normal to abnormal, but the final CSF Aβ measurements were in good agreement with florbetapir cortical retention.

INTERPRETATION

CSF and amyloid PET measurements of Aβ were consistent in the majority of subjects in the cross-sectional and longitudinal populations. Based on our analysis of discordant subjects, the available evidence did not show that CSF Aβ regularly becomes abnormal prior to fibrillar Aβ accumulation early in the course of disease.

Semi-supervised multimodal relevance vector regression improves cognitive performance estimation from imaging and biological biomarkers

Accurate estimation of cognitive scores for patients can help track the progress of neurological diseases. In this paper, we present a novel semi-supervised multimodal relevance vector regression (SM-RVR) method for predicting clinical scores of neurological diseases from multimodal imaging and biological biomarker, to help evaluate pathological stage and predict progression of diseases, e.g., Alzheimer's diseases (AD). Unlike most existing methods, we predict clinical scores from multimodal (imaging and biological) biomarkers, including MRI, FDG-PET, and CSF. Considering that the clinical scores of mild cognitive impairment (MCI) subjects are often less stable compared to those of AD and normal control (NC) subjects due to the heterogeneity of MCI, we use only the multimodal data of MCI subjects, but no corresponding clinical scores, to train a semi-supervised model for enhancing the estimation of clinical scores for AD and NC subjects. We also develop a new strategy for selecting the most informative MCI subjects. We evaluate the performance of our approach on 202 subjects with all three modalities of data (MRI, FDG-PET and CSF) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The experimental results show that our SM-RVR method achieves a root-mean-square error (RMSE) of 1.91 and a correlation coefficient (CORR) of 0.80 for estimating the MMSE scores, and also a RMSE of 4.45 and a CORR of 0.78 for estimating the ADAS-Cog scores, demonstrating very promising performances in AD studies.

Longitudinal change in CSF Tau and Aβ biomarkers for up to 48 months in ADNI

The dynamics of cerebrospinal fluid (CSF) tau and Aβ biomarkers over time in Alzheimer's disease (AD) patients from prodromal pre-symptomatic to severe stages of dementia have not been clearly defined and recent studies, most of which are cross-sectional, present conflicting findings. To clarify this issue, we analyzed the longitudinal CSF tau and Aβ biomarker data from 142 of the AD Neuroimaging Initiative (ADNI) study subjects [18 AD, 74 mild cognitive impairment (MCI), and 50 cognitively normal subjects (CN)]. Yearly follow-up CSF collections and studies were conducted for up to 48 months (median = 36 months) for CSF Aβ1-42, phosphorylated tau (p-tau181), and total tau (t-tau). An unsupervised analysis of longitudinal measurements revealed that for Aβ1-42 and p-tau181 biomarkers there was a group of subjects with stable longitudinal CSF biomarkers measures and a group of subjects who showed a decrease (Aβ1-42, mean = -9.2 pg/ml/year) or increase (p-tau181, mean = 5.1 pg/ml/year) of these biomarker values. Low baseline Aβ1-42 values were associated with longitudinal increases in p-tau181. Conversely, high baseline p-tau181 values were not associated with changes in Aβ1-42 levels. When the subjects with normal baseline biomarkers and stable concentrations during follow-up were excluded, the expected time to reach abnormal CSF levels and the mean AD values was significantly shortened. Thus, our data demonstrate for the first time that there are distinct populations of ADNI subjects with abnormal longitudinal changes in CSF p-tau181 and Aβ1-42 levels, and our longitudinal results favor the hypothesis that Aβ1-42 changes precede p-tau181 changes.

Cerebrospinal fluid biomarkers of Alzheimer's disease in healthy elderly

Numerous studies have shown that Alzheimer's Disease (AD) pathology begins before the onset of clinical symptoms. Because therapies are likely to be more effective if they are implemented early in the disease progression, it is necessary to identify reliable biomarkers to detect AD pathology in the early stages of the disease, ideally in presymptomatic individuals. Recent research has identified three candidate cerebrospinal fluid (CSF) biomarkers that reflect AD pathology: amyloid beta, total tau protein (t-tau), and tau protein phosphorylated at AD-specific epitopes (p-tau). They are useful in supporting the AD diagnosis and have predictive value for AD when patients are in the stage of mild cognitive impairment (MCI). However, their predictive utility in cognitively healthy subjects is still being evaluated. We conducted a review of studies published between 1993 and 2011 and summarized their findings on the role of CSF biomarkers for AD in healthy elderly.

Cerebrospinal fluid levels of phosphorylated tau and Aβ1-38/Aβ1-40/Aβ1-42 in Alzheimer's disease with PS1 mutations

We studied seven cases of Alzheimer's disease (AD). Six of the patients had presenilin 1 (PS1) mutations (PS1AD). Three novel PS1 mutations (T99A, H131R and L219R) and three other missense mutations (M233L, H163R and V272A) were found in the PS1AD group. We measured the levels of phosphorylated tau (ptau-181, ptau-199) and Aβ (Aβ1-42, Aβ1-40 and Aβ1-38) in the cerebrospinal fluid (CSF) of PS1AD patients, early-onset sporadic AD (EOSAD), late-onset sporadic AD (LOSAD) and non-demented subjects (ND). The CSF levels of Aβ1-42 in the three AD groups were significantly lower than those of the ND group (p < 0.0001). CSF levels of Aβ1-42 in the PS1AD group were significantly lower than those in the two sporadic AD groups. The Aβ1-40 and Aβ1-38 levels in the CSF of the PS1AD group were significantly lower than those of the three other groups (p < 0.0001, respectively). The levels of Aβ1-40, Aβ1-38 and Aβ1-42 in the CSF of the PS1AD group remained lower than those of the ND group for 4 years. Not only CSF Aβ1-42, but also Aβ1-40 and Aβ1-38 decreased in the advanced stages of PS1AD.

Subjective cognitive impairment: Towards early identification of Alzheimer disease

INTRODUCTION

Neurodegeneration in Alzheimer disease (AD) begins decades before dementia and patients with mild cognitive impairment (MCI) already demonstrate significant lesion loads. Lack of information about the early pathophysiology in AD complicates the search for therapeutic strategies.Subjective cognitive impairment is the description given to subjects who have memory-related complaints without pathological results on neuropsychological tests. There is no consensus regarding this heterogeneous syndrome, but at least some of these patients may represent the earliest stage in AD.

METHOD

We reviewed available literature in order to summarise current knowledge on subjective cognitive impairment.

RESULTS

Although they may not present detectable signs of disease, SCI patients as a group score lower on neuropsychological tests than the general population does, and they also have a higher incidence of future cognitive decline. Depression and psychiatric co-morbidity play a role but cannot account for all cognitive complaints. Magnetic resonance imaging studies in these patients reveal a pattern of hippocampal atrophy similar to that of amnestic mild cognitive impairment and functional MRI shows increased activation during cognitive tasks which might indicate compensation for loss of function. Prevalence of an AD-like pattern of beta-amyloid (Aβ42) and tau proteins in cerebrospinal fluid is higher in SCI patients than in the general population.

CONCLUSIONS

Memory complaints are relevant symptoms and may predict AD. Interpatient variability and methodological differences between clinical studies make it difficult to assign a definition to this syndrome. In the future, having a standard definition and longitudinal studies with sufficient follow-up times and an emphasis on quantifiable variables may clarify aspects of early AD.

Different patterns of gray matter atrophy in early- and late-onset Alzheimer's disease

We assessed patterns of gray matter atrophy according to-age-at-onset in a large sample of 215 Alzheimer's disease (AD) patients and 129 control subjects with voxel-based morphometry using 3-Tesla 3D T1-weighted magnetic resonance imaging. Local gray matter amounts were compared between late- and early-onset AD patients and older and younger control subjects, taking into account the effect of apolipoprotein E. Additionally, combined effects of age and diagnosis on volumes of hippocampus and precuneus were assessed. Compared with age-matched control subjects, late-onset AD patients exhibited atrophy of the hippocampus, right temporal lobe, and cerebellum, whereas early-onset AD patients showed gray matter atrophy in hippocampus, temporal lobes, precuneus, cingulate gyrus, and inferior frontal cortex. Direct comparisons between late- and early-onset AD patients revealed more pronounced atrophy of precuneus in early-onset AD patients and more severe atrophy in medial temporal lobe in late-onset AD patients. Age and diagnosis independently affected the hippocampus; moreover, the interaction between age and diagnosis showed that precuneus atrophy was most prominent in early-onset AD patients. Our results suggest that patterns of atrophy might vary in the spectrum of AD.

Does Alzheimer's disease with early onset progress faster than with late onset? A case-control study of clinical progression and cerebrospinal fluid biomarkers

BACKGROUND

Early-onset Alzheimer's disease (EOAD) is generally thought to have a more rapid course compared to late-onset Alzheimer's disease (LOAD). The faster progression of EOAD observed in some studies has also been thought to correlate with cerebrospinal fluid (CSF) biomarkers. Our clinical experience has not been suggestive of any difference in disease progression; therefore, we decided to investigate whether differences in clinical progression and CSF biomarkers between EOAD and LOAD could be demonstrated.

METHODS

Case-control study with 42 patients, 21 EOAD and 21 matched LOAD patients. Rates of progression were calculated and these, as well as CSF biomarker levels, were statistically compared.

RESULTS

There were no statistically significant differences in clinical progression between the EOAD group and the LOAD group. There was no significant difference in the absolute values of CSF biomarkers, but a tendency towards lower levels of β-amyloid in patients with EOAD was observed.

CONCLUSIONS

Our findings did not converge with results from the majority of previous studies, which have been suggestive of a faster clinical progression in EOAD. Possibly, the very strict algorithm by which our patients were matched explains our findings. However, the findings should be repeated in a larger study population.