Cerebrospinal Fluid Aβ42 Research Articles

Serum neurofilament light chain levels in patients with cognitive deficits and movement disorders: comparison of cerebrospinal and serum neurofilament light chain levels with other biomarkers.

Serum neurofilament light chain (S NfL) is a non-specific marker of neuronal damage, including Alzheimer's disease (AD). We aimed to verify the reference interval (RI) of serum NfL using a highly sensitive ELISA, and to estimate the optimal cut-off value for neuronal damage. Our second objective was to compare NfL in cerebrospinal fluid (CSF) and serum (S) with the routine neurodegeneration biomarkers used in AD, and to assess their concentrations relative to the degree of cognitive deficit. Samples from 124 healthy volunteers were used to estimate the S NfL RI. For the comparison study, we used CSF and S samples from 112 patients with cognitive disorders. Cognitive functions were assessed using the mini-mental state examination. ELISA assays were used to determine the CSF and S NfL levels, CSF β-amyloid peptide42 (Aβ42), CSF β-amyloid peptide40 (Aβ40), CSF total tau protein (tTau), CSF phosphorylated tau protein (pTau), and CSF alpha-synuclein (αS). The estimated RI of S NfL were 2.25-9.19 ng.L-1. The cut-off value of S NfL for assessing the degree of neuronal impairment was 10.5 ng.L-1. We found a moderate statistically significant correlation between S NfL and CSF Aβ42 in the group with movement disorders, without dementia (rs = 0.631; p = 0.016); between S NfL and CSF Aβ40 in the group with movement disorder plus dementia (rs = -0.750; p = 0.052); between S NfL and CSF tTau in the control group (rs = 0.689; p = 0.009); and between S NfL and CSF pTau in the control group (rs = 0.749; p = 0.003). The non-parametric Kruskal-Wallis test revealed statistically significant differences between S NfL, CSF NfL, CSF Aβ42, CSF tTau, and CSF pTau and diagnosis within groups. The highest kappa coefficients were found between the concentrations of S NfL and CSF NfL (κ = 0.480) and between CSF NfL and CSF tTau (κ = 0.351). Our results suggested that NfL and tTau in CSF of patients with cognitive decline could be replaced by the less-invasive determination of S NfL using a highly sensitive ELISA method. S NfL reflected the severity of cognitive deficits assessed by mini-mental state examination (MMSE). However, S NfL is not specific to AD and does not appear to be a suitable biomarker for early diagnosis of AD.

Distinct Effects of Selective Serotonin Reuptake Inhibitors and Serotonin-Norepinephrine Reuptake Inhibitors on Soluble Biomarkers in Blood and Cerebrospinal Fluid of People With HIV.

Persistent inflammation affects people with HIV (PWH) despite antiretroviral therapy (ART). Selective serotonin and serotonin-norepinephrine reuptake inhibitors (SSRIs, SNRIs), HMG-CoA reductase-inhibitors (statins), and angiotensin-converting enzyme inhibitors (ACEIs) have immunomodulant properties. We evaluated the potential impact of these drugs on inflammation and neurodegeneration in PWH. Cross-sectional single-center (United States) analysis in 184 PWH on ART with plasma HIV RNA < 200 copies/mL. All participants had 10 biomarkers measured in blood and cerebrospinal fluid (CSF). To reduce dimensionality, hierarchical clustering and principal components (PCs) analysis were employed. The analyses were adjusted for duration of the drugs and clinical conditions. Participants were mostly middle-aged men, with median CD4+ T cells of 620/µL. In adjusted models, SSRI use was associated with 3 PCs: higher CSF and plasma Aβ42 and CSF CCL2 (aβ=.14, P = .040); lower CSF 8-oxo-dG, total tau, and sCD14 (aβ=-.12, P = .042); and higher plasma sCD14 with lower sCD40L (aβ=.15, P = .042). SNRI use was associated with higher values of CSF and plasma neopterin and CSF sTNFR-II (aβ=.22, P = .004). Statins and ACEIs showed no association. SSRIs and SNRIs had distinct biomarker signatures. SSRIs were associated with reduced neurodegeneration, immune activation, and oxidative stress in CSF, suggesting a role of SSRIs as adjunctive therapy in PWH.

PICALM Variation Moderates the Relationships of APOE ɛ4 with Alzheimer's Disease Cerebrospinal Biomarkers and Memory Function Among Non-Demented Population.

APOE ɛ4 and PICALM are established genes associated with risk of late-onset Alzheimer's disease (AD). Previous study indicated interaction of PICALM with APOE ɛ4 in AD patients. To explore whether PICALM variation could moderate the influences of APOE ɛ4 on AD pathology biomarkers and cognition in pre-dementia stage. A total of 1,034 non-demented participants (mean age 74 years, 56% females, 40% APOE ɛ4 carriers) were genotyped for PICALM rs3851179 and APOE ɛ4 at baseline and were followed for influences on changes of cognition and cerebrospinal fluid (CSF) AD markers in six years. The interaction effects were examined via regression models adjusting for age, gender, education, and cognitive diagnosis. The interaction term of rs3851179×APOE ɛ4 accounted for a significant amount of variance in baseline general cognition (p = 0.039) and memory function (p = 0.002). The relationships of APOE ɛ4 with trajectory of CSF Aβ42 (p = 0.007), CSF P-tau181 (p = 0.003), CSF T-tau (p = 0.001), and memory function (p = 0.017) were also moderated by rs3851179 variation. APOE ɛ4 carriers experienced slower clinical and pathological progression when they had more protective A alleles of PICALM rs3851179. These findings firstly revealed the gene-gene interactive effects of PICALM with APOE ɛ4 in pre-dementia stage.

Associations Between TREML2 Gene Variants and Alzheimer's Disease: Biomarkers, Neuroimage, and Cognition.

Recent genetic research identified a protective factor against late-onset Alzheimer's disease (AD) in Caucasians, a variant called rs3747742-C in the TREML2 gene. However, the roles of other TREML2 variants in AD have not been fully explored. We conducted a focused analysis of 16 TREML2 variants, examining their connection to AD by studying their correlation with cerebrospinal fluid (CSF) proteins, neuroimage, and cognition in the Alzheimer's Disease Neuroimaging Initiative database (ADNI). A multiple linear regression model was utilized to estimate potential associations between TREML2 genotypes and various endophenotypes in the entire ADNI sample at baseline, with age, gender, years of education, and APOE ɛ4 status included as covariates. To examine changes in clinical outcomes over time, linear mixed-effects models were employed. We found that the SNP rs17328707-A was associated with higher ADNI-VS scores, smaller ventricles, and larger middle temporal volume at baseline. The SNP rs6915083-G was linked to lower CSF t-tau and p-tau levels, and higher CSF Aβ levels. The SNP rs9394766-G was associated with a smaller hippocampus and larger ventricles at baseline. In longitudinal cohorts, the rs6915083-G SNP was associated with changes in ADNI-MEM and ADNI-EF scores, as well as the rate of hippocampal and middle temporal atrophy. Our findings reveal that TREML2 gene variants have different effects on AD. Two variants are protective, while one may be a risk factor. This enhances our understanding of AD genetics and could guide future research and personalized treatments.

Contribution of clinical information to the predictive performance of plasma Aβ levels for Aβ PET positivity

AbstractBackgroundEarly detection of β‐amyloid (Aβ) accumulation, a major biomarker for Alzheimer’s disease (AD), has become important. While Aβ deposition can be detected by positron emission tomography (PET), practical fluid Aβ biomarker is also being developed recently. In the present study, we aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of fluid Aβ levels for amyloid PET positivity.MethodsWe recruited 488 participants who underwent both plasma Aβ and Aβ PET studies (Cohort 1) and 217 participants who underwent both cerebrospinal fluid (CSF) Aβ and Aβ PET studies (Cohort 2). Plasma and CSF samples were analyzed using ABtest‐MS, an antibody‐free liquid chromatography‐differential mobility spectrometry‐triple quadrupole mass spectrometry method and INNOTEST enzyme‐linked immunosorbent assay kits, respectively. To evaluate the predictive performance of plasma Aβ and CSF Aβ, respectively, logistic regression and receiver operating characteristic analyses were performed.ResultsWhen predicting Aβ PET status, both plasma Aβ42/40 ratio and CSF Aβ42 showed high accuracy (plasma Aβ area under the curve (AUC) 0.814; CSF Aβ AUC 0.848). In the plasma Aβ models, the AUC values were higher than plasma Aβ alone model, when the models were combined with either cognitive stage (p &lt; 0.001) or APOE genotype (p = 0.011). On the other hand, there was no difference between the CSF Aβ models, when these variables were added.ConclusionsPlasma Aβ might be a useful predictor of Aβ PET status as much as CSF Aβ, particularly when considered with clinical information.

CSF Alzheimer’s Disease Biomarker Changes in Veterans with Mild Traumatic Brain Injury

AbstractBackgroundTraumatic brain injury (TBI) has been reported to increase risk of Alzheimer’s dementia (AD). It remains unknown whether mild TBI (mTBI) caused by blast in Veterans confers a similar increase of risk. This study investigated early AD changes defined by cerebrospinal fluid (CSF) AD biomarkers in Veterans with blast mTBI.MethodFifty‐one Veterans with mTBI, 34 non‐mTBI Veterans, and 51 non‐mTBI civilians were recruited from Seattle, Washington. Age‐matched Veteran and civilian non‐mTBI participants had no lifetime history of TBI. All blast‐mTBI Veterans had experienced at least one war zone blast or combined blast/impact exposure, with acute symptoms meeting VA/Department of Defense criteria for mTBI. All participants underwent standardized clinical and neuropsychological assessments and lumbar puncture for collection of CSF. CSF biomarkers were measured at the Clinical Neurochemistry Lab in Mölndal, Sweden, using Meso Scale Discovery (MSD) assays for Aβ40 and Aβ42, and Innotest ELISAs for phosphorylated Tau181 (pTau181) and total Tau (tTau).ResultDifferences in all 4 CSF AD biomarkers between participants with and without mTBI were highly age‐dependent and most pronounced in older ages (Figure 1). Both CSF Aβ40 and Aβ42 became lower as age increasing in the mTBI group starting around age 40‐45 years, while they increased with age in the non‐mTBI participants. In contrast, CSF tTau and pTau181 mean levels remained relatively constant with age in participants with mTBI, but increased after age 45 in the non‐mTBI participants. Consequently, for participants aged 50+ years, Veterans with mTBI had lower mean AD biomarkers than the non‐mTBI participants. Similarly, the differences in cognitive performance were age‐dependent, i.e., poorer performance in older Veterans with mTBI than in the non‐mTBI participants. Furthermore, the relationships between CSF Aβ42 and cognitive performance were also age‐dependent; specifically, in participants aged 45+ years, lower CSF Aβ42 level was associated with poorer performance on tests of verbal fluency and memory.ConclusionThe earliest AD biomarker, CSF Aβ42, started to decrease in middle‐aged Veterans with mTBI, more than a decade earlier than those without mTBI in our earlier study, suggesting mTBI may accelerate brain deposition of Aβ and increase risk for AD.

Modifiable dementia risk factor associations with AT(N) biomarkers: Findings from the European Prevention of Alzheimer’s Dementia study

AbstractBackgroundThere is strong evidence that targeting modifiable risk factors can maintain and improve cognitive function, as well as reducing risk for Alzheimer’s disease (AD) and other forms of dementia. Further, a discrete AT(N) profile exists for hallmark biomarkers: amyloid β (A), p‐tau (T) and neurodegeneration (N), to discriminate between AD and non‐AD pathological changes. Despite evidence of a biologically defined AD continuum and modifiable risk amelioration, there is a paucity of studies investigating modifiable risk factors with respect to AT(N) biomarkers. The aim of this study was to investigate how modifiable risk factors relate to the three hallmark AT(N) biomarkers of AD.MethodParticipants were drawn from the European Prevention of Alzheimer’s Disease (EPAD): a prospective, multicentre, pan‐European cohort study. Eligible participants underwent clinical and neurological assessments, brain magnetic resonance imaging, cerebrospinal fluid (CSF) collection, neuropsychological assessment and completed a variety of demographic, clinical, medical history and lifestyle surveys for 10 binary modifiable risk variables. Data were analysed via the NeuroToolKit Application (NTKApp, BetaVersion, 2022). Generalized additive models with penalized regression splines were used to model the associations between modifiable risk factor adherence and AT(N) biological criterion: A (CSF amyloid‐β 42 [Aβ42 pg/mL]); T (CSF phosphorylated‐tau 181 [p‐tau 181 pg/mL]); N (total hippocampal volume [mm3]).ResultOf the 2737 participants included, 56% were female (n = 1526), 39% had at least one APOE ε4 allele (n = 1598), with an average age of 66.0 years and 14.4 years of education. Adjusting for age, sex and APOE carrier status: age, APOE and traumatic brain injury (TBI) were significantly associated with CSF Aβ42; age, APOE, body mass index (BMI) and exercise were significantly associated with CSF p‐tau181; and age, sex and education were significantly associated with total hippocampal volume.ConclusionModifiable risk factors of less education, less exercise, TBI and higher BMI were all significantly associated with increased AD biomarker burden. Our results support previous studies identifying associations between modifiable risk factors and AD and suggest that early intervention strategies focused on education and lifestyle factors and improvements in prevention and treatment of TBI may modify risk profiles associated with cognitive decline.

Cognitive status modifies the association between elevated cerebrospinal fluid phosphorylated tau and longitudinal cerebral blood flow changes over a 7‐year follow‐up period

AbstractBackgroundAlzheimer’s disease (AD) is associated with widespread reductions in cerebral blood flow (CBF), but the precise link between AD pathology and CBF is unclear. Hypoperfusion is a late‐stage event associated with tau, but not amyloid, pathology. We assessed whether baseline levels of cerebrospinal fluid (CSF)‐measured core AD pathology [β‐amyloid42 (Aβ42), phosphorylated tau (p‐tau)] related to CBF changes over a 7‐year period and if associations differed by baseline cognitive status.MethodsVanderbilt Memory and Aging Project participants free of clinical dementia or stroke at enrollment [n = 153, 72±6 years, 37% mild cognitive impairment (MCI), 33% female] underwent lumbar puncture to obtain CSF at study entry and serial multimodal 3T brain magnetic resonance imaging over a 7‐year follow‐up period (mean = 5.4 years). Enzyme‐linked immunosorbent assays quantified CSF Aβ42 and p‐tau181. Pseudo‐continuous arterial spin‐labeling captured CBF in total and lobar grey matter regions of interest (ROI). Linear mixed‐effects models related biomarker x time to longitudinal CBF variables adjusting for baseline age and cognitive status, sex, race/ethnicity, education, Framingham Stroke Risk Profile (minus age), ROI volume, APOE‐ε4 status, and time. Models were repeated testing a cognitive status x biomarker x time interaction term.ResultsIn main effect models, neither CSF Aβ42 (p‐values&gt;0.31) nor p‐tau (p‐values&gt;0.28) related to CBF outcomes. Aβ42 did not interact with cognitive status on CBF outcomes (p‐values&gt;0.37), but p‐tau interacted with baseline cognitive status on longitudinal frontal, temporal, parietal, occipital, and total grey matter CBF trajectories (p‐values&lt;0.005). Among cognitively unimpaired participants, higher p‐tau was associated with slower reductions in frontal (β = 0.01, p = 0.03), parietal (β = 0.01, p = 0.04), occipital (β = 0.01, p = 0.02), and total grey matter CBF (β = 0.01, p = 0.04). Among individuals with MCI, higher p‐tau was associated with faster reductions in frontal (β = ‐0.03, p = 0.008), temporal (β = ‐0.02, p = 0.01), parietal (β = ‐0.04, p = 0.002), occipital (β = ‐0.03, p = 0.0004), and total grey matter CBF (β = ‐0.03, p = 0.005).ConclusionsResults linking CSF p‐tau to CBF decline in MCI support the theory that grey matter hypoperfusion is a later‐stage event tied to neurofibrillary tangle pathology. Associations between higher p‐tau and slower rates of CBF decline among cognitively unimpaired individuals warrants further investigation. Funding: R01‐AG034962, K24‐AG046373, F31‐AG079640, T32‐AG058524, P20‐AG068082

The role of biofluid markers in predicting near‐term cognitive impairment

AbstractBackgroundAlzheimer’s disease (AD) has been defined as a biological construct that can be determined using in vivo biomarkers. Recent studies confirmed the clinical value of the AT(N) framework when using Aβ and tau positron emission tomography (PET) scans in predicting progression from cognitively unimpaired to MCI. Our study aims to investigate if plasma biomarkers can yield similar predictive performance to PET biomarkers, and to also compare against cerebrospinal fluid (CSF) biomarkersMethodIndividuals from the PREVENT‐AD cohort were included in the study. Participants had Aβ and tau plasma measurements and at least one year of clinical follow‐up thereafter (n = 278). A subset of participants had CSF measurements (n = 102) and/or PET scans (n = 133) also with 1‐year clinical follow‐up. Participants were cognitively unimpaired at the time of all biomarker measurements. MCI diagnoses were made by clinical consensus among expert clinical and research staff blind to plasma, CSF, PET, MRI and APOE genotype. We established thresholds of plasma and CSF Aβ and tau positivity based on &gt;80% specificity in identifying individuals with significant levels of Aβ‐PET (plasma Aβ42/40 = 0.057; plasma pTau181 = 7.53 pg/mL; CSF Aβ42 = 961.37; CSF pTau181 = 66.59 pg/mL). Aβ ([18F]NAV4694) and tau ([18F]AV1451)PET thresholds were defined by the mean plus 2 standard deviations from young participants (Aβ SUVR cut‐off = 1.17; tau SUVR cut‐off = 1.24).Result36.8% (7/19) of the A+T+ plasma group progressed to MCI, 50% (4/8) of the A+T+ CSF group progressed to MCI, and 46.6% (7/15) A+T+ PET group progressed to MCI (Fig. 1).We found differences in MCI progression status between the A+T+ group compared to the A‐T‐ and A+T‐ groups across all biomarkers’ measurements, with the A+T+ group always showing a higher rate of progression than the other two groups (post‐hoc chi‐square analyses; p&lt;0.05).ConclusionAbnormal levels of Aβ and tau plasma biomarkers can help predict near‐ term progression to MCI. When plasma thresholds are derived based on PET data, however, plasma biomarkers have a slightly lower specificity than PET and CSF biomarkers, and both plasma and CSF biomarkers are less sensitive than PET biomarkers.

Mediterranean versus Western diet and the gut‐brain axis: Diet‐induced links between gut Oscillospira abundance, plasma branched‐chain amino acid concentrations and insulin resistance, and change in white matter volumes in nonhuman primates

AbstractBackgroundWestern vs. Mediterranean patterned diets have been associated with divergent effects on neurodegenerative diseases including Alzheimer’s Disease (AD). Such effects may be mediated through the gut microbiome, although the exact mechanisms linking diet, microbiome, and brain outcomes remain unclear. Oscillospira, a genus of gut‐dwelling bacteria, appears to be a good candidate which may help explain the mechanistic underpinnings of this relationship. Previous studies have shown associations between Oscillospira abundance, blood biomarkers, and brain physiology in rodents, and patients with neurodegenerative diseases including AD exhibit decreased gut Oscillospira abundances. Notably, Oscillospira may alter myelination by modifying branched‐chain amino acid (BCAA) concentrations in blood and preventing or minimizing insulin resistance.MethodIn the present study, we test a mechanistic role for Oscillospira on white matter volumes in cynomolgus monkeys (Macaca fascicularis) experimentally fed either a Mediterranean or Western‐type diet. We analyzed associations between gut Oscillospira abundances, plasma BCAA concentrations (i.e., leucine, isoleucine, and valine), plasma insulin, beta‐amyloid (Aβ) 42 to 40 ratio in cerebrospinal fluid (CSF), and magnetic resonance imaging‐derived white matter volumes.ResultWe found that Oscillospira abundance was significantly higher in the Mediterranean diet cohort than in the Western cohort (β = 0.258, SE = 0.084, p = 0.004). Oscillospira abundance was significantly negatively associated with plasma leucine (β = ‐0.169, SE = 0.059, p = 0.007) and valine concentrations (β = ‐0.206, SE = 0.069, p = 0.005); a similar, non‐significant (p = 0.066) trend was observed for isoleucine. Similarly, Oscillospira abundance was negatively associated with insulin area under the curve (AUC) at 26 months (β = ‐0.282, SE = 0.125, p = 0.031) and change in insulin AUC from baseline to 26 months (β = ‐14.6, SE = 6.97, p = 0.044), suggesting better insulin sensitivity in individuals with higher Oscillospira abundance. Oscillospira abundance was also positively associated with CSF Aβ42:40 ratio (β = 0.013, SE = 0.004, p = 0.007). Furthermore, the percent change in white matter volume over the study period was positively associated with Oscillospira abundance (β = 2.45, SE = 0.915, p = 0.012) and negatively associated with leucine (β = ‐2.39, SE = 0.920, p = 0.014), isoleucine (β = ‐2.67, SE = 0.895, p = 0.005), and valine concentrations (β = ‐2.28, SE = 0.929, p = 0.020) as well as change in insulin AUC (β = ‐2.04, SE = 0.947, p = 0.039).ConclusionThese results suggest that diet impacts the central nervous system by altering gut microbiome composition and highlight the complexity of relationships between BCAAs and brain health.

CSF proteome profiling reveals a protein panel detecting amyloidosis and progression to dementia in cognitively unimpaired individuals

AbstractBackgroundUnderstanding the earliest biochemical changes related to Alzheimer´s disease (AD) pathology is essential for the development of biomarkers and disease‐modifying therapies. Here, we aimed to map the cerebrospinal fluid (CSF) proteomic changes associated with amyloid ß (Aß) pathology in cognitively unimpaired individuals and identify a panel of CSF biomarkers detecting amyloid positivity as well as clinical progression to dementia.MethodProximity extension‐based multiplex immunoassays were used to measure 614 proteins in 297 CSF samples from cognitively unimpaired controls with and without amyloid pathology (232 CON/Aβ‐ (age: 68±8; sex: 37% female) and 65 CON/Aβ+ (age: 65±7; sex: 49% female) from the Amsterdam Dementia cohort. A total of 39 cases (13%) progressed to mild cognitive impairment (MCI; n = 19) or dementia (n = 20). An additional cognitively unimpaired control cohort from the EMIF‐twin60+ study (103 CON/Aβ‐ and 19 CON/Aβ+) was used to validate the panel. Data was analysed using nested linear models adjusted for multiple testing and penalized generalized linear modelling.ResultWe identified 110 CSF proteins with different levels in CON/Aβ+ compared to Aβ‐ (q&lt;0.05). Proteins were enriched in processes related to proteolysis, enzyme activation and immunity. Classification modelling revealed a panel of 12‐CSF markers that detect amyloid positivity with high accuracy in both the discovery (AUC: 0.93) and validation (AUC: 0.89) cohorts. This panel also predicted clinical progression to MCI and dementia with high accuracy (AUC: 0.83). Chow´s test analysis revealed a structural change in the relation between a subset of these proteins and CSF Aβ42 before the amyloid positivity threshold.ConclusionOverall, this study provides novel pathophysiological leads associated to distinct biological processes in individuals at risk of developing AD‐dementia and provides potential biomarker tools for clinical settings or trials.

Prediction of continuous amyloid PET values by CSF tau measures

AbstractBackgroundAlzheimer disease (AD) is a slowly progressive neurodegenerative disorder characterized by the presence of amyloid plaques that can be measured in vivo with positron emission tomography (PET). PET quantifies the lifetime accumulation of amyloid plaques, while cerebrospinal fluid (CSF) biomarkers reflect the production and clearance of Aβ and tau peptides at time of CSF collection. Previous work has demonstrated a relative plateau of CSF values at higher levels of amyloid burden. Our objective was to identify the range of amyloid PET values predicted by CSF measures of tau phosphorylation, which have been found to be strongly associated with amyloid PET burden.MethodCSF was collected within two years of an amyloid PET scan from 417 (63 cognitively impaired) participants enrolled in studies of memory and aging at the Knight Alzheimer Disease Research Center (mean age 69.8 years, standard deviation 8.9 years). PET imaging was performed with Pittsburgh Compound B (PiB). CSF Aβ42, p‐tau181 and Aβ40 were measured with Lumipulse automated immunoassays. The CSF tau phosphorylation occupancies (percent of tau phosphorylated) at T111, T153, T175, T181, S199, S202, T205, S208, T217, and T231 were evaluated with an immunoprecipitation‐mass spectrometry (IPMS) assay. We applied a neural network to generate a simulated PET‐PiB scan and cortical summary estimates using the fluid biomarkers as modeled inputs. We used asymptotic regression to evaluate the range of amyloid PET values predicted by each CSF measure (Figure 1).ResultCombining fluid biomarkers generated a cortical amyloid burden estimate within 12.6% mean average percent error (MAPE). Four of the assessed fluid biomarkers individually generated estimates within 20% MAPE (Figure 2). Of these, CSF Lumipulse p‐tau181/Aβ42, pS208/S208 (%), and pT231/T231 (%) predicted amyloid PET burden up until a high level (3.08 SUVR/91.1 Centiloids; 3.01 SUVR/88.0 Centiloids; 2.79 SUVR/78.1 Centiloids, respectively) (Figure 3). CSF pT217/217 (%) also had high accuracy but a slightly lower prediction threshold (2.65 SUVR/71.8 Centiloids).ConclusionCSF measures including phosphorylated tau predict amyloid PET over different ranges. Combining different measures of CSF tau phosphorylation can generate estimates of cortical amyloid burden. Future work will evaluate the prediction of tau PET by CSF measures.

Association between blood pressure and Alzheimer’s disease biomarkers in cognitively unimpaired adults

AbstractBackgroundHigh blood pressure is an established risk factor for dementia. However, the underlying mechanisms are not completely understood. We aimed to evaluate the association between blood pressure and Alzheimer’s disease (AD) biomarkers in cognitively unimpaired adults from the ALFA+ study.MethodWe analyzed data from 301 participants with available cross‐sectional blood pressure measures (acquired by trained staff with an oscillometric device after 5 minutes of rest) and cerebrospinal fluid (CSF) AD core biomarkers data (CSF p‐tau and t‐tau were measured with Elecsys® immunoassays and CSF Aβ42 and Aβ40 with the Roche NeuroToolKit, a panel of robust prototype assays, both from Roche Diagnostics International Ltd), and a subset of 278 participants with amyloid PET data, of whom 110 had a second follow‐up PET acquisition (3.4 years after in average). We used separate linear regression models to analyze the association of systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP = SBP‐DBP) with CSF and PET biomarkers at a cross‐sectional level, and their association with the annualized rate of change in amyloid PET [(follow‐up centiloids – baseline centiloids) / years between PET scan acquisition]. We adjusted all models by age, sex, APOE status, waist‐to‐hip ratio, dyslipidemia, diabetes, tobacco and alcohol consumption, physical activity, and antihypertensive treatment.ResultHigher baseline SBP (but not DBP or PP) was significantly associated with increased amyloid PET uptake over time (p = 0.043). In cross‐sectional analyses, DBP was negatively associated with Aβ42 (p = 0.013), Aβ40 (p = 0.026), and t‐tau (p = 0.045), and marginally associated with p‐tau (p = 0.069), but not with the Aβ42/40 ratio nor baseline amyloid PET uptake. Associations with Aβ42 and t‐tau were no longer significant after further adjustment by CSF Aβ40 levels. SBP and PP were not associated with CSF biomarkers or baseline amyloid PET uptake.ConclusionHigher SBP is associated with longitudinal brain amyloid accumulation, which reinforces the importance of blood pressure control in AD prevention. DBP is also associated at a cross‐sectional level with AD biomarker concentration in CSF, but the attenuation of this association after adjusting by Aβ40 suggests a non‐specific.

Comparison of plasma and cerebrospinal fluid protein markers and their significance for the characterization of dementia disease status

AbstractBackgroundAlthough Aβ42 and phosphorylated tau (p‐tau) in cerebrospinal fluid (CSF) are valuable to diagnose Alzheimer’s disease (AD), many patients are reluctant to accept lumbar puncture. In addition, there is lack of biomarkers for the different stages of AD dementia. This study sought to compare the plasma and CSF protein markers to characterize dementia status.MethodThis cohort study included Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants who had baseline levels of 73 proteins measured in plasma (566 total, 58 cognitively normal (CN), 396 mild cognitive impairment (MCI), and 112 AD) and in CSF (310 total, 92 CN, 149 MCI, and 69 AD). Univariate/multivariate logistic regression and least absolute shrinkage and selection operator (LASSO) were used to identify the protein candidates for the disease classification. The following three models were examined for CN vs. MCI and MCI vs. AD; model 1: proteins only, model 2: proteins adjusted for age, sex, education, and model 3: model 2 plus APOE4 status.ResultNine proteins in plasma and CSF were chosen based on their importance from LASSO. The area under the curve (AUC) for the final multivariate logistic regression including the 9 proteins was calculated for each disease group in plasma [CN vs. MCI: 0.895 (model 1), 0.899 (model 2), 0.921 (model 3), and MCI vs. AD: 0.828 (model 1), 0.842 (model 2), 0.856 (model 3)]. In addition, AUC in CSF [CN vs. MCI: 0.678 (model 1), 0.726 (model 2), 0.770 (model 3) and MCI vs. AD: 0.711 (model 1), 0.738 (model 2), 0.765 (model 3)] was also estimated. We observed that plasma proteins outperformed the CSF proteins to be associated with MCI and AD. Also, plasma proteins were significantly better than the established AD markers, namely CSF Aβ42 and p‐tau in CN vs. MCI [AUC: 0.836 (model 1), 0.842 (model 2), 0.862 (model 3)] and MCI vs. AD [AUC: 0.665 (model 1), 0.673 (model 2), 0.680 (model 3)].ConclusionThis study demonstrates that the combination of plasma proteins could be considered an effective marker for diagnosing AD and its early‐stage symptoms with better performance than the other markers.

Biological and methodological factors underlying a continuous amyloid CSF/PET imbalance model and its association with longitudinal cognition

AbstractBackgroundDiscordance between cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers of amyloid‐β (Aβ) occurs in up to 20% of individuals. Generally, Aβ discordance is defined using binary cut‐offs. Given the methodological limitations of this approach, we propose a continuous Aβ CSF/PET imbalance model. We investigated biological and methodological factors underlying discrepancy in these amyloid biomarkers and associations with longitudinal cognition.MethodWe included 383 non‐demented subjects (N unimpaired = 326, N mildly‐impaired = 57) from the AMYPAD‐PNHS cohort. Z‐scored CSF Aβ42 and amyloid‐PET (Centiloids [CL]) units were fitted to a hyperbolic regression model by minimizing the Euclidian distance of the observed datapoints to the fitted line. Subject‐specific standardized residuals were derived as a measure of continuous imbalance (Zimbalance), with Zimbalance&lt;0 reflecting greater Aβ abnormality in CSF relative to PET and Zimbalance&gt;0 greater Aβ abnormality in PET relative to CSF (Figure‐1). Linear models adjusted for relevant covariates (Figure‐2) were run between Zimbalance and (1) methodological factors (CSF‐PET interval, CSF kit, PET tracer, and PET injected dose); (2) demographics (age, sex, education, APOE genotype) and CSF p‐tau biomarker; (3) vascular burden (white matter hyperintensities measured as Fazekas scores). Linear mixed models were used to investigate the predictive value of Zimbalance on longitudinal cognition in several domains.ResultSample characteristics are shown in Table‐1. Methodological factors were not significantly associated with Zimbalance. Increased CSF p‐tau levels were significantly associated with a higher Zimbalance (i.e. greater Aβ abnormality in PET relative to CSF) (β = 0.06±0.03, p = .033) (Figure‐2). In addition, a lower Zimbalance (i.e. greater Aβ abnormality in CSF relative to PET) was associated with a higher Fazekas score (n = 189, β = ‐0.55±0.26, p = .038) and predictive of faster cognitive decline on a language categorical fluency test (β = ‐0.03±0.02, p = .038) (Figure‐2).ConclusionWe found that methodological factors did not contribute to a continuous model of Aβ CSF/PET imbalance, suggesting that this imbalance reflects distinct biological profiles. Indeed, continuous CSF/PET imbalance showed differential associations, with greater pathological levels of aggregated Aβ relative to soluble Aβ being related to increased CSF p‐tau levels and excess pathological levels of soluble Aβ relative to aggregated Aβ to increased white matter hyperintensities and steeper cognitive decline.

Longitudinal change in CSF β‐amyloid1−42 predicts PTSD symptomatology after the COVID‐19 lockdown in cognitively unimpaired older adults

AbstractBackgroundCognitively unimpaired (CU) adults with Alzheimer’s disease (AD) pathologic change may be more vulnerable to developing neuropsychiatric symptoms. We reported an association of higher β‐amyloid (Aβ) and increased anxiety/depression during the COVID‐19 lockdown in CU adults (Akinci et al., 2022). Here, we investigated whether changes in Aβ1−42 predict post‐traumatic stress disorder (PTSD) symptomatology following COVID‐19 lockdown in CU adults at risk for AD.MethodWe included 128 CU participants who underwent lumbar puncture 2.3±0.6 years before and 1.1±0.4 years after the lockdown. The outcome of interest was self‐reported PTSD symptomatology (Impact of Event Scale Revised) measured 1.7±0.1 years after the lockdown. The main predictor was annual rate of change in cerebrospinal fluid (CSF) Aβ1−42 measured with the NeuroToolKit panel of robust prototype assays (Roche Diagnostics International Ltd, Rotkreuz, Switzerland). Other predictors included sex, age, years of education, stressors during COVID‐19, and anxiety/depression (Hospital Anxiety and Depression Scale, HADS) and perceived stress (Perceived Stress Scale, PSS) measured during lockdown. We performed regression analyses to explore the association between annual rate of change in Aβ1‐42 with PTSD scores adjusting for demographic and stressor variables, and further adjusting for HADS and PSS scores. We then explored the mediating effect of HADS and PSS on the association between change in Aβ1‐42 and PTSD scores.ResultParticipant age ranged from 53−72 and 59% were women (Table 1). Independent of demographic variables and stressors experienced during COVID‐19, the rate of annual change in Aβ1‐42 predicted PTSD scores (p = .008; Table 2). This association attenuated after introducing HADS and PSS scores into the model (p = .066). We found full mediation effects of HADS and PSS scores, explaining 46% and 40% of the effect of annual change in Aβ1‐42 on PTSD scores, respectively (Figure 1).ConclusionCU older adults with longitudinal CSF Aβ1−42 increases are more vulnerable to developing PTSD symptomatology after a stressful event, such as the pandemic. Anxiety/depression is one plausible mechanism through which increases in Aβ might exacerbate PTSD symptomatology. The results suggest a window for stress regulation during stressful events to prevent further mental health worsening in people at risk for AD.

Associations between NIH‐Toolbox Flanker test and the Picture Sequence Memory Test and multimodal Alzheimer’s disease biomarkers in cognitively unimpaired individuals

AbstractBackgroundAlzheimer’s disease (AD) pathologic changes start years before cognitive symptoms appear; however, some early cognitive changes can be detected. We aimed to investigate the association between performance changes in two NIH‐Toolbox tests, Flanker test and Picture Sequence Memory Test (PSMT), and baseline AD biomarkers in cognitively unimpaired (CU) individuals.MethodWe studied 356 ALFA+ participants (mean [SD] age = 60.8 [4.72] years). The rate of cognitive change after 3 years was measured through delta scores (Follow‐up ‐ Baseline). Biomarker data included cerebrospinal fluid (CSF) β‐amyloid (Aβ) 42/40 ratio, phosphorylated‐tau‐181 (p‐tau), neurofilament light (NfL), and neuroimaging (MRI‐based cortical thickness AD signature, hippocampal volumes, and FDG‐PET‐SUVR (fluorodeoxyglucose ‐ positron emission tomography ‐ standardized uptake value ratio) metaROI) measures (Table 1). CSF Aβ40, Aβ42 and NfL were measured with the exploratory NTK robust immunoassays, while CSF p‐tau181 was measured using the electrochemiluminescence Elecsys® Phospho‐Tau (181P) CSF immunoassays (Roche Diagnostics International Ltd). AT groups were defined according to published cut‐offs (A+ Aβ 42/40 &lt;0.071; T+: p‐tau &gt; 24 pg/ml) (Milà‐Alomà et al., 2020). Baseline biomarker levels were used as predictors of cognitive change in linear models. Interactions and stratified analyses were also explored.ResultAT groups significantly differed in the change in the Flanker Test (p = 0.002), driven by poorer performance in A+T+ vs A‐T‐ groups (p = 0.001) (Figure1). Higher cortical thickness predicted better longitudinal cognitive performance in the Flanker Test in the whole group (p = 0.020; β = 0.983). We found a significant interaction between AT group and FDG‐PET‐SUVR (p = 0.042), and the right hippocampal volume (p = 0.001), but no significant associations were observed in analyses stratified by AT (Figure2A). A negative association between right hippocampal volume and Flanker test change was observed in A+T‐ (p = 0.026) and A+T+ (p = 0.029) (Figure2B). No associations were observed between the PSMT and AD biomarkers (Figure 1).ConclusionOur findings support the hypothesis that executive function show a steeper decline than episodic memory in CU individuals with evidence of pathologic AD biomarkers levels. We observed a negative association between executive change and neuroimaging neurodegeneration markers in A+T‐ and A+T+ groups. This is in accordance with previous studies that found non‐linear associations in incipient AD pathology.

Time of the day at sampling affects amyloid‐beta levels in CSF and plasma

AbstractBackgroundStudies suggest that cerebrospinal fluid (CSF) levels of Alzheimer’s disease (AD) biomarkers, amyloid‐β (Aβ) and tau, follow a circadian rhythm. However sustained sampling of CSF with indwelling intrathecal catheter used in most of these studies might have affected the observed fluctuations in the biomarker levels.MethodsWe included 38 individuals with either normal (N = 18) or abnormal (N = 20) CSF Aβ42/40 status. CSF and plasma were collected, at the same occasion, at two different visits separated by an average of 53 days with lumbar punctures and venepunctures performed either in the morning or evening. At the first visit, collection was performed in the morning for 17 participants and the order was reversed (evening collection first) for the remaining 21 participants. CSF and plasma samples were analyzed for Aβ42, Aβ40, GFAP, NfL, p‐tau181, p‐tau217 and p‐tau231. CSF samples were also tested for a battery of synaptic and lysosomal proteins.ResultsCSF Aβ42 (mean difference [MD] = 0.208ng/ml; p = 0.043), CSF Aβ40 (MD = 1.85ng/ml; p&lt;0.001), plasma Aβ42 (MD = 1.65pg/ml; p = 0.002) and plasma Aβ40 (MD, 0.011ng/ml, p = 0.003) levels were increased in the evening samples compared with morning samples by 4.2%‐17.0% (Figures 1‐2). However, changes between morning and evening samples were not significant for either CSF or plasma Aβ42/40. Additional proteins in CSF, APP, STX1B, NPTXR and NPTX1, were also found increased in the evening samples (MDrange, 0.087–0.243; p&lt;0.048) by 4.7%‐12.15% (Figure 3). No significant differences were found between morning and evening levels for any of the other biomarkers, including p‐tau’s, NfL and GFAP. There were no significant interactions between time of day at sample collection and either Aβ status or order in which samples were obtained.ConclusionOur findings provide further evidence for diurnal fluctuations in Aβ peptides, which is observed in both CSF and plasma. Additionally, CSF levels of some synaptic proteins followed circadian rhythm. Importantly, CSF and plasma Aβ42/40 ratios remained unaltered, suggesting that increased production or decreased clearance of Aβ peptides during daytime similarly affect the CSF and plasma levels of both Aβ42 and Aβ40. Thus, these ratios are more suitable for implementation as biomarkers of AD as they are not influenced by diurnal fluctuations.

Differential A/T/N Networks of Cerebrospinal Fluid and Neuroimaging Biomarkers and their Prediction of Cognition between Self‐reported Black/African American and Non‐Hispanic White Individuals

AbstractBackgroundDifferences in absolute levels of individual biomarkers from cerebrospinal fluid (CSF), amyloid PET, and MRI imaging between self‐reported Black and White individuals were reported. How the A/T/N network of AD biomarkers is biologically connected within a racialized group and whether it predicts cognition differentially between groups remain unknown.MethodThe Study of Race to Understand Alzheimer Biomarkers(SORTOUT‐AB) has centrally re‐processed the CSF samples and imaging scans collected at four AD Research Centers/studies: Washington University, University of Pennsylvania, Emory University, and the Harvard Aging Brain Study. A total of 286 Black and 2080 White participants had CSF biomarker data, 157 Black and 936 White participants provided PET amyloid biomarker data, 322 Black and 1530 White individuals had MRI structural data, and 67 Black and 492 White participants provided PET Tau biomarker data. Spearman correlations across biomarkers and cognition/memory were estimated within each race, then compared between groups, adjusting for age, sex, APOE ε4 status, dementia status, and education.ResultsThe absolute correlation between CSF Aβ42 and the centiloid scale of PET amyloid mean cortical SUVR was significantly larger in White(r = ‐0.45) versus Black(r = ‐0.04) participants, similar to the absolute correlations between Aβ42/40 ratio and each of below: PET amyloid centiloid(White r = ‐0.61, Black r = ‐0.12), CSF Tau(White r = ‐0.43, Black r = ‐0.25), and CSF pTau181(White r = ‐0.54, Black r = ‐0.33). Aβ42 alone did not correlate with Tau or pTau181 in White individuals, but positively correlated with Tau(r = 0.15) and pTau181(r = 0.16) in Black participants. Significantly larger positive correlations were observed in Black versus White individuals between CSF Aβ40 and pTau181(Black r = 0.68, White r = 0.55). PET amyloid centiloid, MRI hippocampal volume, and cortical thickness all predicted cognition, with no racial differences observed. However, cognition/memory was better predicted by Aβ42/40 for White verses Black participants(Black r = 0.07, White r = 0.22), Tau(Black r = ‐0.06, White r = ‐0.20), and pTau181(Black r = ‐0.02, White r = ‐0.23).ConclusionBiological associations of CSF and imaging biomarkers differed between Black and White groups, suggesting that current A/T/N research framework of AD biomarkers may not apply across racialized groups. The prediction of CSF biomarkers to cognition also differed between groups. Use of biomarkers in studying AD and designing/analyzing AD clinical trials must appropriately address racial differences.

ATN Cerebrospinal Fluid Biomarkers in Dementia with Lewy Bodies: Initial Results from the United States Dementia with Lewy Bodies Consortium

AbstractBackgroundNeuropathological hallmarks of AD, amyloid plaques and neurofibrillary tangles, have been described in dementia with Lewy bodies (DLB). Less is known about changes in pre‐mortem cerebrospinal fluid (CSF) amyloid and tau biomarker status in DLB. CSF biomarkers for amyloid (A), tau (T), and neurodegeneration (N) can be utilized to define pre‐mortem pathological status. The overall aim of this investigation was to utilize the ATN research framework to characterize pre‐mortem AD‐related pathology longitudinally in a rigorously characterized cohort of DLB from the Dementia with Lewy Bodies Consortium (DLBC) study. Our hypothesis was that ATN biomarkers would identify DLB with coexistent AD and ATN status would remain the same after 12 months.MethodCerebrospinal fluid (CSF) samples from an AD/ADRD cohort were obtained from the Cleveland Alzheimer’s Disease Research Center (CADRC), Cleveland Clinic Lou Ruvo Center for Brain Health Aging and Neurodegenerative Disease Biobank (CBH‐biobank) and DLBC. CSF Aβ40, Aβ42, Aβ42/40 (A), p‐Tau181 (T), and t‐Tau (N), were evaluated. The cohort was subtyped by CSF ATN category and sub‐group of DLB cases were neuropathologically evaluated. A sub‐cohort of DLB cases had longitudinal data with an evaluation at baseline and 12 months later.ResultDLB patients who were positive for both CSF Aβ42/40 (A+) and p‐Tau181 (T+) remained positive from baseline to 12 months. In contrast, some DLB patients who were positive for CSF Aβ42/40 (A+), but negative for p‐Tau181 (T‐), changed from CSF Aβ42/40 positive to negative at 12 months (p‐value = 0.0153) in the A+T‐N‐ and A+T‐N+ group. Findings from a small DLB subgroup with post‐mortem neuropathologic analyses indicated that most of the cases that were p‐Tau181 positive (T+) also had high Braak stage.ConclusionThese findings suggest that DLB patients who are positive for CSF Aβ42/40 (A+), but negative for p‐Tau181 (T‐), may have CSF Aβ42/40 levels that can fluctuate over time. In the small DLB subgroup with post‐mortem neuropathologic analysis, there appeared to be a relationship between AD pathologic change and ATN findings that warrants further study in a larger autopsied cohort to fully understand the relationship between ATN status and underlying AD neuropathologic change in DLB.