Real-world comparison of brain [18F]FDG-PET imaging with CSF Alzheimer's disease biomarkers in a tertiary memory clinic setting.

BackgroundPositive CSF biomarkers have been shown to be a reliable predictor of post‐mortem Alzheimer's disease neuropathologic change (ADNC) and are often incorporated into clinical diagnosis of neurodegenerative disease. However, less is known about the predictive value of borderline or inconclusive results, which are not uncommon in clinical practice. The current project determined correspondence between CSF AD biomarkers and post‐mortem ADNC in a clinical research sample enriched for atypical dementia syndromes, focusing on borderline and inconclusive results.MethodAll participants in the Northwestern University Alzheimer's Disease Research Center (NUADRC) with available CSF AD biomarker results who donated their brain at the time of death were included (N = 74, Mean age at CSF = 64.99 [SD = 7.34], Mean years from CSF to death = 5.6 [range 1‐14 years], 43% female, 95% non‐Hispanic white; see Table 1 for breakdown of clinical syndromes and pathological diagnoses). CSF results were categorized as AD, Borderline, Inconclusive, or Not AD based on ADMark thresholds for amyloid‐b42/total tau index (ATI) and phosphorylated tau (pTau; Figure 1).ResultAcross clinical phenotypes, results consistent with AD on CSF were highly specific for High ADNC on autopsy (97%) but only moderately sensitive (68%); positive predictive value was also high (97%). Within Borderline and Inconclusive cases, abnormal ATI reliably predicted High ADNC on autopsy (sensitivity = 100%, specificity = 80%), regardless of pTau results. In this sample, there were no cases with pTau in the AD range but normal ATI that had High ADNC on autopsy. Abnormal CSF ATI and/or pTau were seen in some cases of FTLD‐tau, FTLD‐TDP, and other primary neuropathologic diagnoses.ConclusionConsistent with prior findings, CSF results categorized as consistent with AD were highly specific and predictive of primary ADNC pathology on post‐mortem analysis, regardless of clinical presentation. In the setting of Borderline or inconclusive results, ATI in the AD range reliably predicted high ADNC, regardless of pTau range. These findings help clarify the prognostic utility of ATI and pTau values in Borderline and Inconclusive CSF results, which can help inform differential diagnosis between AD and other neurodegenerative etiologies.

Given prior work demonstrating that mild cognitive impairment (MCI) can be empirically differentiated into meaningful cognitive subtypes, we applied actuarial methods to comprehensive neuropsychological data from the University of California San Diego Alzheimer's Disease Research Center (ADRC) in order to identify cognitive subgroups within ADRC participants without dementia and to examine cognitive, biomarker, and neuropathologic trajectories. Cluster analysis was performed on baseline neuropsychological data (n = 738; mean age 71.8). Survival analysis examined progression to dementia (mean follow-up 5.9 years). CSF Alzheimer disease (AD) biomarker status and neuropathologic findings at follow-up were examined in a subset with available data. Five clusters were identified: optimal cognitively normal (CN; n = 130) with above-average cognition, typical CN (n = 204) with average cognition, nonamnestic MCI (naMCI; n = 104), amnestic MCI (aMCI; n = 216), and mixed MCI (mMCI; n = 84). Progression to dementia differed across MCI subtypes (mMCI > aMCI > naMCI), with the mMCI group demonstrating the highest rate of CSF biomarker positivity and AD pathology at autopsy. Actuarial methods classified 29.5% more of the sample with MCI and outperformed consensus diagnoses in capturing those who had abnormal biomarkers, progressed to dementia, or had AD pathology at autopsy. We identified subtypes of MCI and CN with differing cognitive profiles, clinical outcomes, CSF AD biomarkers, and neuropathologic findings over more than 10 years of follow-up. Results demonstrate that actuarial methods produce reliable cognitive phenotypes, with data from a subset suggesting unique biological and neuropathologic signatures. Findings indicate that data-driven algorithms enhance diagnostic sensitivity relative to consensus diagnosis for identifying older adults at risk for cognitive decline.

Relationship Between Indices of CSF HPA AXIS Activity and AD Biomarkers in Late Life Depression

INTRODUCTIONCerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are reliable predictors of future AD risk. We investigated whether pre‐clinical changes in AD CSF biomarkers are reflected in blood DNA methylation (DNAm) levels in cognitively normal participants.METHODSWe profiled blood‐based DNAm with the EPIC array in participants without a diagnosis of cognitive impairment in the Emory Healthy Brain Study (EHBS; N = 495), Alzheimer's Disease Neuroimaging Initiative (N = 122), and Parkinson's Progression Markers Initiative (N = 118) cohorts. Their CSF amyloid beta 42, total tau (t‐tau), and phosphorylated tau181 levels were quantified using Elecsys immunoassays. We conducted epigenome‐wide association studies to assess associations between DNAm and CSF biomarkers of AD.RESULTSIn EHBS, no loci were Bonferroni significant after adjusting for confounding factors. In the meta‐analysis of all three cohorts, DNAm in cg22976567 (LMNA) was significantly associated with higher CSF t‐tau levels.DISCUSSIONOur study showed little evidence of an association between differential blood‐based DNAm and pre‐clinical AD CSF biomarkers.HighlightsWe conducted one of the largest (n = 735) blood DNA methylation (DNAm) studies of Alzheimer's disease cerebrospinal fluid (AD CSF) biomarkers.This is the first epigenome‐wide association study in cognitively normal participants examining AD CSF biomarkers.Limited associations between blood DNAm and AD CSF biomarkers were identified.

Alzheimer's disease and related dementias have a multifactorial aetiology and heterogeneous biology. The current study aims to identify different biological signatures in a deeply phenotyped memory clinic patient population. In this cross-sectional study, we analysed 49 pre-specified proteins using a multiplex antibody-based suspension bead array in 278 CSF samples from the real-world research database and biobank at the Karolinska University Hospital Memory Clinic, Solna, Sweden. Patients with a clinical diagnosis of subjective cognitive decline (N = 151), mild cognitive impairment (N = 61), Alzheimer's disease (N = 47), or other diagnoses (N = 19; vascular dementias, alcohol-related dementia, unspecified dementias, or other amnesias) were included. Principal component analyses were performed, and resulting principal components (PCs) were tested for associations with clinical variables and Alzheimer's disease biomarkers (CSF biomarkers beta-amyloid 42, beta-amyloid 42/40, phosphorylated tau 181, phosphorylated tau 181/beta-amyloid 42). PC 1 (explaining 52% of the variance between patients) was associated with the clinical Alzheimer's disease CSF biomarkers beta-amyloid 42, phosphorylated tau 181, and total tau but not with Alzheimer's disease-related neurodegeneration imaging markers, cognitive performance, or clinical diagnosis. PC 2 (explaining 9% of the variance) displayed an inflammatory profile with high contributions of chitinase 3 like 1 (CHI3L1) and triggering receptor expressed on myeloid cells 2 (TREM2) and significant correlation to CSF free light chain kappa. In contrast to PC 1, PC 3 (explaining 5% of the variance) showed associations with all the clinical Alzheimer's disease CSF biomarkers, the imaging markers, cognitive impairment and clinical diagnosis. Serpin family A member 3 (SERPINA3), chitinase 1 (CHIT1), and neuronal pentraxin 2 (NPTX2) contributed most to PC 3. PC 4 (explaining 4% of the variance) exhibited an inflammatory profile distinct from PC 2, with the largest contributions from TREM2, leucine-rich alpha-2-glycoprotein 1 (LRG1) and complement C9. The component was associated with peripheral inflammation. We found that CSF protein profiles in a memory clinic cohort reflect molecular differences across diagnostic groups. Our results emphasize that real-world memory clinic patients can have different ongoing biological processes despite receiving the same diagnosis. In the future, this information could be utilized to identify patient endotypes and uncover precision biomarkers and novel therapeutic targets.

CSF concentrations of β-amyloid 42 (Aβ42) and phosphorylated tau (p-tau) are well-established biomarkers of Alzheimer's disease and have been studied in relation to several neuropathological features both in patients and in cognitively unimpaired individuals. The CSF p-tau/Aβ42 ratio, a biomarker combining information from both pathophysiological processes, has emerged as a promising tool for monitoring disease progression, even at pre-clinical stages. Here, we studied the association between the CSF p-tau/Aβ42 ratio with downstream markers of pre-clinical Alzheimer's disease progression including brain structure, glucose metabolism, fibrillary Aβ deposition and cognitive performance in 234 cognitively unimpaired individuals, who underwent cognitive testing, a lumbar puncture, MRI, 18F-fluorodeoxyglucose and 18F-flutemetamol PET scanning. We evaluated both main effects and interactions with Alzheimer's disease risk factors, such as older age, female sex and the apoliporoptein E (APOE)-ɛ4 allele, in a priori defined regions of interest and further examined the associations on the whole-brain using voxel-wise regressions. In addition, as the association between CSF Alzheimer's disease biomarkers and brain structure and function may be non-linear, we tested the interaction between the CSF p-tau/Aβ42 ratio and stages of pre-clinical Alzheimer's disease defined using the amyloid (A) and tau (T) classification. We found significantly positive associations between CSF p-tau/Aβ42 and both cortical Aβ deposition and regional grey matter volume while no effect was observed for brain metabolism. A significant interaction with age indicated that, for the same level of CSF p-tau/Aβ42, older individuals displayed both increased Aβ deposition and lower grey matter volume, in widespread cortical areas. In addition, we found that women compared with men had a greater Aβ fibrillary accumulation in midline cortical areas and inferior temporal regions, for the same level of the CSF biomarker. The impact of CSF p-tau/Aβ42 on grey matter volume was modulated by AT stages, with A+T+ individuals displaying significantly less positive associations in areas of early atrophy in the Alzheimer's continuum. Finally, we found that sex and APOE-ɛ4 modulated the association between the CSF biomarker and episodic memory as well as abstract reasoning, respectively. Our data indicate that the CSF p-tau/Aβ42 ratio is strongly associated with multiple downstream neuropathological events in cognitively unimpaired individuals and may thus serve as a potent biomarker to investigate the earliest changes in pre-clinical Alzheimer's disease. Given that its impact on both Aβ deposition and grey matter volume is modulated by specific risk factors, our results highlight the need to take into account such predisposing variables in both clinical practice and prevention trials.

α-Synuclein (αSyn) seed amplification assays (SAAs) accurately detect αSyn pathology in dementia with Lewy bodies (DLB). Alzheimer disease (AD) copathology occurs in ∼70% of patients with DLB at autopsy. The association of different αSyn-SAA and AD biomarker profiles with clinical outcomes in DLB can aid prognostication and inform clinical trial design. This is a cross-sectional study of participants in the DLB Consortium (DLBC) study. The DLBC is a multicentered prospective longitudinal cohort study with participants recruited at tertiary care centers in the United States. CSF samples obtained within 1 year of baseline assessments were analyzed using αSyn-SAA and for β-amyloid (Aβ) 42/40, phosphorylated tau (p-tau) 181, and total tau (t-tau). Comparisons of baseline prevalence and degree of core DLB features, cognitive impairment, and hyposmia in participants with different CSF profiles were performed (AD-: normal Aβ42/40, p-tau181, and t-tau. AD+: Aβ42/40 abnormal, ±p-tau181, ±t-tau. Other non-AD: normal Aβ42/40 but elevated p-tau181 or t-tau levels). Longitudinal cognitive and motor declines were assessed in participants with different CSF profiles using linear mixed-effects models. Ninety-nine participants had CSF αSyn-SAA and AD biomarkers available for analysis (mean age 69.8 ± 6.6, 15% female); 68% (67/99) were αSyn-SAA+. αSyn-SAA+ participants had lower baseline Montreal Cognitive Assessment (MoCA) scores (19.0 ± 5.8 vs 21.6 ± 4.7, p = 0.03) and worse motor parkinsonism (Movement Disorder Society Unified Parkinson's Disease Rating Scale [MDS-UPDRS] part-III 32.3 ± 15.8 vs 22.1 ± 14.4, p = 0.003) and were more likely to be hyposmic (87% [46/53] vs 37% [10/27], p < 0.0001). αSyn-SAA+ participants had more progressive parkinsonism than αSyn-SAA- participants (MDS-UPDRS part-III: 3.70 points per year [95% CI 2.60-4.80] vs 0.47 points per year [95% CI -0.25 to 1.19], p < 0.0001). Of αSyn-SAA+ participants, 39% (26/67) were AD- and 52% (35/67) were AD+. αSyn-SAA+AD+ participants had greater declines in MoCA scores than αSyn-SAA+AD- participants (-3.24 points per year [95% CI -4.12 to -2.36] vs -1.19 points per year [95% CI -1.72 to -0.65], p < 0.0001). MDS-UPDRS part-I and part-II subscores increased more in αSyn-SAA+AD+ participants than in αSyn-SAA+AD- participants (2.72 points per year [95% CI 1.70-3.73] vs 1.21 points per year [95% CI 0.48-1.94], p = 0.03 and 4.60 points per year [95% CI 3.40-5.80] vs 1.93 points per year [95% CI 1.19-2.66], p < 0.001, respectively). In this well-characterized cohort of participants with clinically diagnosed DLB, αSyn-SAA positivity is associated with greater motor decline. AD copathology is common and confers additional risk of cognitive and functional decline.

BackgroundConcentration‐based fluid biomarkers represent an informative and cost‐effective way to detect and monitor Alzheimer's disease (AD) pathology. However, non‐AD‐related inter‐individual variation in biofluids can also affect biomarker concentrations. We previously identified several reference proteins that, in the AT(N) classification framework, improved concordance between CSF Aβ42 and Aβ‐positron emission tomography (PET), as well as between CSF p‐tau181 and tau‐PET.1 However, it is still unclear what effect reference proteins have on the relationship between CSF AD biomarkers and the load of AD pathology. It is also unclear if plasma AD biomarkers can be improved by accounting for reference proteins in a similar manner.MethodsUsing the Swedish BioFINDER‐2 cohort (n = 1702, 50.7% male, mean [SD] age 68.4 [12.2] years), we compared the associations between tau/Aβ‐PET load and CSF biomarkers (MTBR‐tau243, p‐tau217, p‐tau181, p‐tau205, Aβ42, SNAP‐25, neurogranin) alone versus in a ratio with a reference protein (e.g. CSF Aβ40 or non‐phosphorylated tau [np‐tau]) in univariate linear regression models. We repeated this analysis for plasma biomarkers.ResultsCSF Aβ40 normalization significantly strengthened the associations of several core CSF AD biomarkers, including CSF MTBR‐tau243, p‐tau isoforms and synaptic biomarkers, with tau‐PET (ΔR2=0.064‐0.24) and Aβ‐PET (ΔR2=0.016‐0.28), Figure 1. CSF np‐tau normalization mainly improved concordance between CSF biomarkers and Aβ‐PET (ΔR2=‐0.0059‐0.19). The strongest association with tau‐PET was observed for MTBR‐tau243/Aβ40 (R‐squared=0.78, compared to 0.65 for non‐normalized MTBR‐tau243), and with Aβ‐PET for p‐tau217/np‐tau (R‐squared= 0.65, compared to 0.46 for non‐normalized p‐tau217). For core plasma AD biomarkers, including MTBR‐tau243 and p‐tau isoforms, associations with tau‐PET were enhanced by using plasma Aβ40 or np‐tau as references (ΔR2=0.0019‐0.14), while associations with Aβ‐PET mainly improved with np‐tau (ΔR2=0.018‐0.16), Figure 2. The findings were successfully replicated in Knight ADRC and TRIAD for improved biomarker associations with both tau‐PET (Table 1) and Aβ‐PET.ConclusionsNormalization to reference proteins (i.e., Aβ40 or np‐tau) enhances the associations between CSF and plasma biomarkers with the load of tau and Aβ pathology in the brain, making already high‐performing AD and synaptic fluid biomarkers even more precise.Reference1. Karlsson, L. et al. Cerebrospinal fluid reference proteins increase accuracy and interpretability of biomarkers for brain diseases. Nat Commun15, (2024).

The entorhinal cortex is one of the first regions to exhibit neurodegeneration in Alzheimer's disease, and as such identification of entorhinal cortex dysfunction may aid detection of the disease in its earliest stages. Extensive evidence demonstrates that the entorhinal cortex is critically implicated in navigation underpinned by the firing of spatially modulated neurons. This study tested the hypothesis that entorhinal-based navigation is impaired in pre-dementia Alzheimer's disease. Forty-five patients with mild cognitive impairment (26 with CSF Alzheimer's disease biomarker data: 12 biomarker-positive and 14 biomarker-negative) and 41 healthy control participants undertook an immersive virtual reality path integration test, as a measure of entorhinal-based navigation. Behavioural performance was correlated with MRI measures of entorhinal cortex volume, and the classification accuracy of the path integration task was compared with a battery of cognitive tests considered sensitive and specific for early Alzheimer's disease. Biomarker-positive patients exhibited larger errors in the navigation task than biomarker-negative patients, whose performance did not significantly differ from controls participants. Path-integration performance correlated with Alzheimer's disease molecular pathology, with levels of CSF amyloid-β and total tau contributing independently to distance error. Path integration errors were negatively correlated with the volumes of the total entorhinal cortex and of its posteromedial subdivision. The path integration task demonstrated higher diagnostic sensitivity and specificity for differentiating biomarker positive versus negative patients (area under the curve = 0.90) than was achieved by the best of the cognitive tests (area under the curve = 0.57). This study demonstrates that an entorhinal cortex-based virtual reality navigation task can differentiate patients with mild cognitive impairment at low and high risk of developing dementia, with classification accuracy superior to reference cognitive tests considered to be highly sensitive to early Alzheimer's disease. This study provides evidence that navigation tasks may aid early diagnosis of Alzheimer's disease, and the basis of this in animal cellular and behavioural studies provides the opportunity to answer the unmet need for translatable outcome measures for comparing treatment effect across preclinical and clinical trial phases of future anti-Alzheimer's drugs.

BackgroundUnderstanding the relationship between Alzheimer's disease (AD) biomarkers and cognitive performance in diverse populations is essential to uncover how social and demographic factors influence brain pathology and clinical manifestations. Studying these associations in underrepresented groups, can enhance the global applicability of diagnosis using AD biomarkers and therapeutic strategies.MethodThis study included 72 participants with an average of 8.9 [SD ±5.1] years of education, ranging from 0 to 21 years, from a tertiary memory clinic in Brazil. All of them underwent CSF biomarker analysis and a neuropsychological evaluation as part of their diagnostic workup. Among the participants, 30 were diagnosed with AD (39 men and 33 women; mean age 65.1 years [SD ±8.2], range 43–83) with CSF biomarker levels of p‐tau 87.0 (±41.7), total tau 765 (±611), and AB‐42 579 (±195); 16 had behavioral variant frontotemporal dementia (bvFTD) (13 men and 3 women; mean age 64.3 years [SD ±7.9], range 43–76) with p‐tau 49.1 (±21.2), total tau 405 (±346), and AB‐42 875 (±334); seven had mild cognitive impairment (MCI) (1 men and 6 women; mean age 62.3 years [SD ±9.3], range 50–78) with p‐tau 63.4 (±36.7), total tau 315 (±322), and AB‐42 1050 (±330); and 19 had dementia without a specific classification (11 men and 8 women; mean age 63.8 years [SD ±9.7], range 43–82) with p‐tau 51.8 (±24.7), total tau 389 (±262), and AB‐42 941 (±379).ResultOur analysis revealed significant correlations between AD CSF biomarkers and cognitive performance. Total tau was negatively correlated with verbal memory performance (z_scoreRAVLT, Spearman's rho = ‐0.265, p = 0.025), while beta‐amyloid 42 (AB‐42) was positively correlated with verbal memory (z_scoreRAVLT, Spearman's rho = 0.266, p = 0.024). However, AB‐42 did not show significant correlation with global cognitive function (z_scoreMattis, Spearman's rho = 0.210, p = 0.076). No significant correlations between phosphorylated tau and cognitive measures emerged, as well.ConclusionIn a Brazilian population with a diverse educational level, total tau biomarkers showed significant correlations with verbal memory tests. However, phosphorylated tau and AB‐42 did not demonstrate such correlations. These findings suggest that the cognitive impairment does not follow amyloidosis, but seems to reflect neurodegeneration.

Electrophysiologic disturbances due to neurodegenerative disorders such as Alzheimer's disease and Lewy Body disease are detectable by scalp EEG and can serve as a functional measure of disease severity. Traditional quantitative methods of EEG analysis often require an a-priori selection of clinically meaningful EEG features and are susceptible to bias, limiting the clinical utility of routine EEGs in the diagnosis and management of neurodegenerative disorders. We present a data-driven tensor decomposition approach to extract the top 6 spectral and spatial features representing commonly known sources of EEG activity during eyes-closed wakefulness. As part of their neurologic evaluation at Mayo Clinic, 11 001 patients underwent 12 176 routine, standard 10-20 scalp EEG studies. From these raw EEGs, we developed an algorithm based on posterior alpha activity and eye movement to automatically select awake-eyes-closed epochs and estimated average spectral power density (SPD) between 1 and 45 Hz for each channel. We then created a three-dimensional (3D) tensor (record × channel × frequency) and applied a canonical polyadic decomposition to extract the top six factors. We further identified an independent cohort of patients meeting consensus criteria for mild cognitive impairment (30) or dementia (39) due to Alzheimer's disease and dementia with Lewy Bodies (31) and similarly aged cognitively normal controls (36). We evaluated the ability of the six factors in differentiating these subgroups using a Naïve Bayes classification approach and assessed for linear associations between factor loadings and Kokmen short test of mental status scores, fluorodeoxyglucose (FDG) PET uptake ratios and CSF Alzheimer's Disease biomarker measures. Factors represented biologically meaningful brain activities including posterior alpha rhythm, anterior delta/theta rhythms and centroparietal beta, which correlated with patient age and EEG dysrhythmia grade. These factors were also able to distinguish patients from controls with a moderate to high degree of accuracy (Area Under the Curve (AUC) 0.59-0.91) and Alzheimer's disease dementia from dementia with Lewy Bodies (AUC 0.61). Furthermore, relevant EEG features correlated with cognitive test performance, PET metabolism and CSF AB42 measures in the Alzheimer's subgroup. This study demonstrates that data-driven approaches can extract biologically meaningful features from population-level clinical EEGs without artefact rejection or a-priori selection of channels or frequency bands. With continued development, such data-driven methods may improve the clinical utility of EEG in memory care by assisting in early identification of mild cognitive impairment and differentiating between different neurodegenerative causes of cognitive impairment.

BackgroundSedentary behavior is a highly prevalent behavior in older adulthood that is related to many poor health outcomes, including an increased risk of dementia. Given the negative impact of sedentary behavior on physical health, there has been recent interest in examining its impact on cognitive health in older adulthood. However, the association between sedentary behavior and cognition has been somewhat mixed, and the neurobiological mechanisms that may underlie these associations are poorly understood. We sought to examine how sedentary behavior may interact with Alzheimer's Disease (AD) biomarkers on cognition in older adults without dementia.MethodA subset of University of Pittsburgh Alzheimer's Disease Research Center (ADRC) Clinical Core participants with at least one week of accelerometry data and positron emission tomography (PET) imaging were included (N = 41, age=75±8 years, 16±3years of education, 51% Male, 90% White). Participants wore the Fitbit Inspire 3 device to measure sedentary behavior, and underwent neuropsychological testing (Uniform Data Set), and PET Imaging (global amyloid beta (Aβ), tau in the meta‐temporal region). The interaction between sedentary behavior and AD biomarkers was related to neuropsychological outcomes using a moderation model that adjusted for age, sex, race, and education. Exploratory models were repeated stratifying by AD biomarker level to examine directionality of effects.ResultSedentary behavior interacted with global amyloid burden on letter fluency (β=‐0.05, p = 0.05), a language composite, (β=‐0.03, p = 0.04), and complex attention (β=‐0.004, p = 0.003). Sedentary behavior interacted with tau burden in meta‐temporal regions on confrontation naming (β=‐0.04, p = 0.02). When these significant interactions were probed, more sedentary time was associated with better cognition in those with low Aβ and tau burden; in those with high Aβ and tau burden, less sedentary time was associated with better cognition.ConclusionIn a sample of older adults, sedentary behavior interacted with AD biomarkers on cognition cross‐sectionally. Interestingly, the AD biomarker burden level was important in understanding the directionality of the associations between sedentary behavior and cognitive performance. This study is consistent with the importance of modifying sedentary behavior, particularly in those with elevated biomarker risk for AD.

Alzheimer's disease pathologies are common in dementia with Lewy bodies, but their clinical relevance is not clear. CSF biomarkers amyloid beta 1-42, total tau, and tau phosphorylated at threonine 181 reflect Alzheimer's disease neuropathology antemortem. In PD, low CSF amyloid beta 1-42 predict long-term cognitive decline, but little is known about these biomarkers as predictors for cognitive decline in Lewy body dementia. The aim of this study was to assess whether Alzheimer's disease CSF biomarkers predict cognitive decline in Lewy body dementia. From a large European dementia with Lewy bodies multicenter study, we analyzed baseline Alzheimer's disease CSF biomarkers and serial MMSE (baseline and 1- and 2-year follow-up) in 100 patients with Lewy body dementia. Linear mixed-effects analyses, adjusted for sex, age, baseline MMSE, and education, were performed to model the association between CSF biomarkers and rate of cognitive decline measured with MMSE. An Alzheimer's disease CSF profile was defined as pathological amyloid beta 1-42 plus pathological total tau or phosphorylated tau. The Alzheimer's disease CSF profile, and pathological levels of amyloid beta 1-42, were associated with a more rapid decline in MMSE (2.2 [P < 0.05] and 2.9 points difference [P < 0.01], respectively). Higher total tau values showed a trend toward association without statistical significance (2.0 points difference; P = 0.064), whereas phosphorylated tau was not associated with decline. Reduced levels of CSF amyloid beta 1-42 were associated with more rapid cognitive decline in Lewy body dementia patients. Future prospective studies should include larger samples, centralized CSF analyses, longer follow-up, and biomarker-pathology correlation. © 2016 International Parkinson and Movement Disorder Society.

BackgroundThe presence of brain β‐amyloid (Aβ) plaques among cognitively normal older adults has been related to steeper cognitive decline and an increased risk of Alzheimer’s disease (AD). The co‐presence of tau pathology in these individuals, however, makes it challenging to link AD pathologies to changes in specific cognitive function and brain structure. In addition, it remains unclear whether AD pathologies in the brain and their increased concentration in the cerebrospinal fluid (CSF) have similar effects on cognition.MethodWe assessed the relationship between Aβ and tau pathology, gray matter atrophy, and cognition among cognitively normal older adults in the Alzheimer's disease neuroimaging initiative whose brain Aβ deposition and tau‐protein neurofibrillary tangles were detected by 18F‐Florbetapir and 18F‐Flortaucipir, respectively. Within a subset of the sample, CSF measures of amyloid (Aβ40 and Aβ42) and tau (t‐tau and p‐tau) pathologies were assessed in relation to cognition and cortical thickness. Multiple regression models were applied to assess the relationships between AD pathologies, gray matter atrophy, and cognition using region‐of‐interest and whole‐brain surface‐based approaches.ResultHigher entorhinal tau PET counts corresponded to greater gray matter atrophy in the entorhinal cortex and hippocampus and poorer executive function performance, controlling for age, sex, and whole‐brain amyloid load. In the subset of the sample, whole‐brain amyloid load related to poorer memory and executive function performance, controlling for age, sex, and CSF total tau. Age was associated with memory and executive function performance, independent of entorhinal tau PET counts, CSF total tau, and whole‐brain amyloid load. Entorhinal tau PET counts did not correlate with CSF total tau or p‐tau among cognitively normal older adults.ConclusionAmyloid and tau pathology differentially influence cognition and brain structure. A low correlation between tau PET and CSF total tau measures in cognitively normal older adults may warrant further investigation on the source of discordance in these measures.

Parkinson's disease (PD) diagnosis is mainly based on clinical criteria, with a high risk of misdiagnosis. The identification of reliable biomarkers for disease diagnosis and progression has a key role for developing disease-modifying therapies. In this article, we investigated the longitudinal changes of CSF α-synuclein species in early PD patients and explored the potential use of these species as surrogate biomarkers for PD progression. We used our newly developed enzyme-linked immunosorbent assay systems for measuring different forms of α-synuclein, such as oligomeric-α-synuclein, phosphorylated-α-synuclein at serine 129, or total-α-synuclein in CSF from the longitudinal Deprenyl and Tocopherol Antioxidative Therapy for Parkinsonism study cohort (n = 121). CSF Alzheimer's disease biomarkers (total-tau, phosphorylated-tau, Aβ40 , and Aβ42 ) were also measured for this cohort. Interestingly, total-α-synuclein and oligomeric-α-synuclein levels significantly increased during the 2-year Deprenyl and Tocopherol Antioxidative Therapy for Parkinsonism study follow-up period, whereas phosphorylated-α-synuclein at serine 129 levels showed a longitudinal decrease. We have also noted an association between a change of the oligomeric-α-synuclein/total-α-synuclein ratio and a worsening of motor signs, in particular in the postural-instability and gait-difficulty dominant PD group. A strong positive correlation between the changes in CSF total-α-synuclein and oligomeric-α-synuclein during the 2-year Deprenyl and Tocopherol Antioxidative Therapy for Parkinsonism study was also noted (r = 0.84, P < .001). Our data show that CSF α-synuclein species have a dynamic pattern along the course of the disease, supporting their possible role as progression biomarkers for PD and their link with PD clinical phenotypes. © 2016 International Parkinson and Movement Disorder Society.