Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study

BACKGROUND

In people with genetic forms of Alzheimer's disease, such as in Down syndrome and autosomal-dominant Alzheimer's disease, pathological changes specific to Alzheimer's disease (ie, accumulation of amyloid and tau) occur in the brain at a young age, when comorbidities related to ageing are not present. Studies including these cohorts could, therefore, improve our understanding of the early pathogenesis of Alzheimer's disease and be useful when designing preventive interventions targeted at disease pathology or when planning clinical trials. We compared the magnitude, spatial extent, and temporal ordering of tau spread in people with Down syndrome and autosomal-dominant Alzheimer's disease.

METHODS

In this cross-sectional observational study, we included participants (aged ≥25 years) from two cohort studies. First, we collected data from the Dominantly Inherited Alzheimer's Network studies (DIAN-OBS and DIAN-TU), which include carriers of autosomal-dominant Alzheimer's disease genetic mutations and non-carrier familial controls recruited in Australia, Europe, and the USA between 2008 and 2022. Second, we collected data from the Alzheimer Biomarkers Consortium-Down Syndrome study, which includes people with Down syndrome and sibling controls recruited from the UK and USA between 2015 and 2021. Controls from the two studies were combined into a single group of familial controls. All participants had completed structural MRI and tau PET (18F-flortaucipir) imaging. We applied Gaussian mixture modelling to identify regions of high tau PET burden and regions with the earliest changes in tau binding for each cohort separately. We estimated regional tau PET burden as a function of cortical amyloid burden for both cohorts. Finally, we compared the temporal pattern of tau PET burden relative to that of amyloid.

FINDINGS

We included 137 people with Down syndrome (mean age 38·5 years [SD 8·2], 74 [54%] male, and 63 [46%] female), 49 individuals with autosomal-dominant Alzheimer's disease (mean age 43·9 years [11·2], 22 [45%] male, and 27 [55%] female), and 85 familial controls, pooled from across both studies (mean age 41·5 years [12·1], 28 [33%] male, and 57 [67%] female), who satisfied the PET quality-control procedure for tau-PET imaging processing. 134 (98%) people with Down syndrome, 44 (90%) with autosomal-dominant Alzheimer's disease, and 77 (91%) controls also completed an amyloid PET scan within 3 years of tau PET imaging. Spatially, tau PET burden was observed most frequently in subcortical and medial temporal regions in people with Down syndrome, and within the medial temporal lobe in people with autosomal-dominant Alzheimer's disease. Across the brain, people with Down syndrome had greater concentrations of tau for a given level of amyloid compared with people with autosomal-dominant Alzheimer's disease. Temporally, increases in tau were more strongly associated with increases in amyloid for people with Down syndrome compared with autosomal-dominant Alzheimer's disease.

INTERPRETATION

Although the general progression of amyloid followed by tau is similar for people Down syndrome and people with autosomal-dominant Alzheimer's disease, we found subtle differences in the spatial distribution, timing, and magnitude of the tau burden between these two cohorts. These differences might have important implications; differences in the temporal pattern of tau accumulation might influence the timing of drug administration in clinical trials, whereas differences in the spatial pattern and magnitude of tau burden might affect disease progression.

FUNDING

None.

Sex-specific associations between AD genotype and the microbiome of human amyloid beta knock-in (hAβ-KI) mice

INTRODUCTION

Emerging evidence links changes in the gut microbiome to late-onset Alzheimer's disease (LOAD), necessitating examination of AD mouse models with consideration of the microbiome.

METHODS

We used shotgun metagenomics and untargeted metabolomics to study the human amyloid beta knock-in (hAβ-KI) murine model for LOAD compared to both wild-type (WT) mice and a model for early-onset AD (3xTg-AD).

RESULTS

Eighteen-month female (but not male) hAβ-KI microbiomes were distinct from WT microbiomes, with AD genotype accounting for 18% of the variance by permutational multivariate analysis of variance (PERMANOVA). Metabolomic diversity differences were observed in females, however no individual metabolites were differentially abundant. hAβ-KI mice microbiomes were distinguishable from 3xTg-AD animals (81% accuracy by random forest modeling), with separation primarily driven by Romboutsia ilealis and Turicibacter species. Microbiomes were highly cage specific, with cage assignment accounting for more than 40% of the PERMANOVA variance between the groups.

DISCUSSION

These findings highlight a sex-dependent variation in the microbiomes of hAβ-KI mice and underscore the importance of considering the microbiome when designing studies that use murine models for AD.

HIGHLIGHTS

Microbial diversity and the abundance of several species differed in human amyloid beta knock-in (hAβ-KI) females but not males. Correlations to Alzheimer's disease (AD) genotype were stronger for the microbiome than the metabolome. Microbiomes from hAβ-KI mice were distinct from 3xTg-AD mice. Cage effects accounted for most of the variance in the microbiome and metabolome.

Cognitive and functional performance and plasma biomarkers of early Alzheimer's disease in Down syndrome

INTRODUCTION

People with Down syndrome (DS) have a 75% to 90% lifetime risk of Alzheimer's disease (AD). AD pathology begins a decade or more prior to onset of clinical AD dementia in people with DS. It is not clear if plasma biomarkers of AD pathology are correlated with early cognitive and functional impairments in DS, and if these biomarkers could be used to track the early stages of AD in DS or to inform inclusion criteria for clinical AD treatment trials.

METHODS

This large cross-sectional cohort study investigated the associations between plasma biomarkers of amyloid beta (Aβ)42/40, total tau, and neurofilament light chain (NfL) and cognitive (episodic memory, visual-motor integration, and visuospatial abilities) and functional (adaptive behavior) impairments in 260 adults with DS without dementia (aged 25-81 years).

RESULTS

In general linear models lower plasma Aβ42/40 was related to lower visuospatial ability, higher total tau was related to lower episodic memory, and higher NfL was related to lower visuospatial ability and lower episodic memory.

DISCUSSION

Plasma biomarkers may have utility in tracking AD pathology associated with early stages of cognitive decline in adults with DS, although associations were modest.

Highlights

Plasma Alzheimer's disease (AD) biomarkers correlate with cognition prior to dementia in Down syndrome.Lower plasma amyloid beta 42/40 was related to lower visuospatial abilities.Higher plasma total tau and neurofilament light chain were associated with lower cognitive performance.Plasma biomarkers show potential for tracking early stages of AD symptomology.

A critical appraisal of blood-based biomarkers for Alzheimer's disease

Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aβ1-42/Aβ1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.

The Abca7V1613M variant reduces Aβ generation, plaque load, and neuronal damage

BACKGROUND

Variants in ABCA7, a member of the ABC transporter superfamily, have been associated with increased risk for developing late onset Alzheimer's disease (LOAD).

METHODS

CRISPR-Cas9 was used to generate an Abca7V1613M variant in mice, modeling the homologous human ABCA7V1599M variant, and extensive characterization was performed.

RESULTS

Abca7V1613M microglia show differential gene expression profiles upon lipopolysaccharide challenge and increased phagocytic capacity. Homozygous Abca7V1613M mice display elevated circulating cholesterol and altered brain lipid composition. When crossed with 5xFAD mice, homozygous Abca7V1613M mice display fewer Thioflavin S-positive plaques, decreased amyloid beta (Aβ) peptides, and altered amyloid precursor protein processing and trafficking. They also exhibit reduced Aβ-associated inflammation, gliosis, and neuronal damage.

DISCUSSION

Overall, homozygosity for the Abca7V1613M variant influences phagocytosis, response to inflammation, lipid metabolism, Aβ pathology, and neuronal damage in mice. This variant may confer a gain of function and offer a protective effect against Alzheimer's disease-related pathology.

HIGHLIGHTS

ABCA7 recognized as a top 10 risk gene for developing Alzheimer's disease. Loss of function mutations result in increased risk for LOAD. V1613M variant reduces amyloid beta plaque burden in 5xFAD mice. V1613M variant modulates APP processing and trafficking in 5xFAD mice. V1613M variant reduces amyloid beta-associated damage in 5xFAD mice.

Alzheimer's polygenic risk scores are associated with cognitive phenotypes in Down syndrome

INTRODUCTION

This study aimed to investigate the influence of the overall Alzheimer's disease (AD) genetic architecture on Down syndrome (DS) status, cognitive measures, and cerebrospinal fluid (CSF) biomarkers.

METHODS

AD polygenic risk scores (PRS) were tested for association with DS-related traits.

RESULTS

The AD risk PRS was associated with disease status in several cohorts of sporadic late- and early-onset and familial late-onset AD, but not in familial early-onset AD or DS. On the other hand, lower DS Mental Status Examination memory scores were associated with higher PRS, independent of intellectual disability and APOE (PRS including APOE, PRSAPOE , p = 2.84 × 10-4 ; PRS excluding APOE, PRSnonAPOE , p = 1.60 × 10-2 ). PRSAPOE exhibited significant associations with Aβ42, tTau, pTau, and Aβ42/40 ratio in DS.

DISCUSSION

These data indicate that the AD genetic architecture influences cognitive and CSF phenotypes in DS adults, supporting common pathways that influence memory decline in both traits.

HIGHLIGHTS

Examination of the polygenic risk of AD in DS presented here is the first of its kind. AD PRS influences memory aspects in DS individuals, independently of APOE genotype. These results point to an overlap between the genes and pathways that leads to AD and those that influence dementia and memory decline in the DS population. APOE ε4 is linked to DS cognitive decline, expanding cognitive insights in adults.

Neurofilament light chain concentration mediates the association between regional medial temporal lobe structure and memory in adults with Down syndrome

INTRODUCTION

Virtually all people with Down syndrome (DS) develop neuropathology associated with Alzheimer's disease (AD). Atrophy of the hippocampus and entorhinal cortex (EC), as well as elevated plasma concentrations of neurofilament light chain (NfL) protein, are markers of neurodegeneration associated with late-onset AD. We hypothesized that hippocampus and EC gray matter loss and increased plasma NfL concentrations are associated with memory in adults with DS.

METHODS

T1-weighted structural magnetic resonance imaging (MRI) data were collected from 101 participants with DS. Hippocampus and EC volume, as well as EC subregional cortical thickness, were derived. In a subset of participants, plasma NfL concentrations and modified Cued Recall Test scores were obtained. Partial correlation and mediation were used to test relationships between medial temporal lobe (MTL) atrophy, plasma NfL, and episodic memory.

RESULTS

Hippocampus volume, left anterolateral EC (alEC) thickness, and plasma NfL were correlated with each other and were associated with memory. Plasma NfL mediated the relationship between left alEC thickness and memory as well as hippocampus volume and memory.

DISCUSSION

The relationship between MTL gray matter and memory is mediated by plasma NfL levels, suggesting a link between neurodegenerative processes underlying axonal injury and frank gray matter loss in key structures supporting episodic memory in people with DS.

Plasma NT1-tau and Aβ42 correlate with age and cognitive function in two large Down syndrome cohorts

INTRODUCTION

People with Down syndrome (DS) often develop Alzheimer's disease (AD). Here, we asked whether ultrasensitive plasma immunoassays for a tau N-terminal fragment (NT1-tau) and Aβ isoforms predict cognitive impairment.

METHODS

Plasma NT1-tau, Aβ37 , Aβ40 , and Aβ42 levels were measured in a longitudinal discovery cohort (N = 85 participants, 220 samples) and a cross-sectional validation cohort (N = 239). We developed linear models and predicted values in the validation cohort.

RESULTS

Discovery cohort linear mixed models for NT1-tau, Aβ42 , and Aβ37:42 were significant for age; there was no main effect of time. In cross-sectional models, NT1-tau increased and Aβ42 decreased with age. NT1-tau predicted cognitive and functional scores. The discovery cohort linear model for NT1-tau predicted levels in the validation cohort.

DISCUSSION

NT1-tau correlates with age and worse cognition in DS. Further validation of NT1-tau and other plasma biomarkers of AD neuropathology in DS cohorts is important for clinical utility.

Cerebrovascular disease drives Alzheimer plasma biomarker concentrations in adults with Down syndrome

Importance

By age 40 years over 90% of adults with Down syndrome (DS) have Alzheimer's disease (AD) pathology and most progress to dementia. Despite having few systemic vascular risk factors, individuals with DS have elevated cerebrovascular disease (CVD) markers that track with the clinical progression of AD, suggesting a role for CVD that is hypothesized to be mediated by inflammatory factors.

Objective

To examine the pathways through which small vessel CVD contributes to AD-related pathophysiology and neurodegeneration in adults with DS.

Design

Cross sectional analysis of neuroimaging, plasma, and clinical data.

Setting

Participants were enrolled in Alzheimer's Biomarker Consortium - Down Syndrome (ABC-DS), a multisite study of AD in adults with DS.

Participants

One hundred eighty-five participants (mean [SD] age=45.2 [9.3] years) with available MRI and plasma biomarker data were included. White matter hyperintensity (WMH) volumes were derived from T2-weighted FLAIR MRI scans and plasma biomarker concentrations of amyloid beta (Aβ42/Aβ40), phosphorylated tau (p-tau217), astrocytosis (glial fibrillary acidic protein, GFAP), and neurodegeneration (neurofilament light chain, NfL) were measured with ultrasensitive immunoassays.

Main Outcomes and Measures

We examined the bivariate relationships of WMH, Aβ42/Aβ40, p-tau217, and GFAP with age-residualized NfL across AD diagnostic groups. A series of mediation and path analyses examined causal pathways linking WMH and AD pathophysiology to promote neurodegeneration in the total sample and groups stratified by clinical diagnosis.

Results

There was a direct and indirect bidirectional effect through GFAP of WMH on p-tau217 concentration, which was associated with NfL concentration in the entire sample. Among cognitively stable participants, WMH was directly and indirectly, through GFAP, associated with p-tau217 concentration, and in those with MCI, there was a direct effect of WMH on p-tau217 and NfL concentrations. There were no associations of WMH with biomarker concentrations among those diagnosed with dementia.

Conclusions and Relevance

The findings suggest that among individuals with DS, CVD promotes neurodegeneration by increasing astrocytosis and tau pathophysiology in the presymptomatic phases of AD. This work joins an emerging literature that implicates CVD and its interface with neuroinflammation as a core pathological feature of AD in adults with DS.

Pathways linking pulse pressure to dementia in adults with Down syndrome

Individuals with Down syndrome (DS) are less likely to have hypertension than neurotypical adults. However, whether blood pressure measures are associated with brain health and clinical outcomes in this population has not been studied in detail. Here, we assessed whether pulse pressure is associated with markers of cerebrovascular disease, entorhinal cortical atrophy, and diagnosis of dementia in adults with DS. Participants with DS from the Biomarkers of Alzheimer's Disease in Adults with Down Syndrome study (ADDS; n=195, age=50.6±7.2 years, 44% women, 18% diagnosed with dementia) were included. Higher pulse pressure was associated with greater global, parietal, and occipital WMH volume. Pulse pressure was not related to enlarged PVS, microbleeds, infarcts, entorhinal cortical thickness, or dementia diagnosis. However, in a serial mediation model, we found that pulse pressure was indirectly related to dementia diagnosis through parieto-occipital WMH and, subsequently through entorhinal cortical thickness. Higher pulse pressure may be a risk factor for dementia in people with DS by promoting cerebrovascular disease, which in turn affects neurodegeneration. Pulse pressure is an important determinant of brain health and clinical outcomes in individuals with Down syndrome despite the low likelihood of frank hypertension.

Predictors of Cognitive Change in Parkinson Disease: A 2-year Follow-up Study

BACKGROUND

Mild cognitive impairment is common in Parkinson disease (PD-MCI). However, instability in this clinical diagnosis and variability in rates of progression to dementia raises questions regarding its utility for longitudinal tracking and prediction of cognitive change in PD. We examined baseline neuropsychological test and cognitive diagnosis predictors of cognitive change in PD.

METHODS

Persons with PD, without dementia PD (N=138) underwent comprehensive neuropsychological assessment at baseline and were followed up to 2 years. Level II Movement Disorder Society criteria for PD-MCI and PD dementia (PDD) were applied annually. Composite global and domain cognitive z -scores were calculated based on a 10-test neuropsychological battery.

RESULTS

Baseline diagnosis of PD-MCI was not associated with a change in global cognitive z -scores. Lower baseline attention and higher executive domain z -scores were associated with greater global cognitive z -score worsening regardless of cognitive diagnosis. Worse baseline domain z -scores in the attention and language domains were associated with progression to MCI or PDD, whereas higher baseline scores in all cognitive domains except executive function were associated with clinical and psychometric reversion to "normal" cognition.

CONCLUSIONS

Lower scores on cognitive tests of attention were predictive of worse global cognition over 2 years of follow-up in PD, and lower baseline attention and language scores were associated with progression to MCI or PDD. However, PD-MCI diagnosis per se was not predictive of cognitive decline over 2 years. The association between higher executive domain z -scores and greater global cognitive worsening is probably a spurious result.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

Plasma NT1-tau and Aβ 42 correlate with age and cognitive function in two large Down syndrome cohorts

Introduction

People with Down syndrome (DS) often develop Alzheimer disease (AD). Here we asked whether ultrasensitive plasma immunoassays for a tau N-terminal fragment (NT1-tau) and Aβ isoforms predict cognitive impairment.

Methods

Plasma NT1-tau, Aβ 37 , Aβ 40 , and Aβ 42 levels were measured in a longitudinal discovery cohort (N = 85 participants, 220 samples) and a cross-sectional validation cohort (N = 239). We developed linear models and predicted values in the validation cohort.

Results

Linear mixed models for NT1-tau, Aβ 42, and Aβ 37:42 were significant for age, there was no main effect of time in the discovery cohort. In cross-sectional models, NT1-tau and Aβ 42 increased with age. NT1-tau predicted DLD scores. The discovery cohort linear model for NT1-tau predicted NT1-tau levels in the validation cohort.

Discussion

NT1-tau correlates with age and worse cognition in DS. Further validation of NT1-tau and other plasma biomarkers of AD neuropathology in DS cohorts is important for clinical utility.

Comparison of amyloid burden in individuals with Down syndrome versus autosomal dominant Alzheimer's disease: a cross-sectional study

BACKGROUND

Important insights into the early pathogenesis of Alzheimer's disease can be provided by studies of autosomal dominant Alzheimer's disease and Down syndrome. However, it is unclear whether the timing and spatial distribution of amyloid accumulation differs between people with autosomal dominant Alzheimer's disease and those with Down syndrome. We aimed to directly compare amyloid changes between these two groups of people.

METHODS

In this cross-sectional study, we included participants (aged ≥25 years) with Down syndrome and sibling controls who had MRI and amyloid PET scans in the first data release (January, 2020) of the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. We also included carriers of autosomal dominant Alzheimer's disease genetic mutations and non-carrier familial controls who were within a similar age range to ABC-DS participants (25-73 years) and had MRI and amyloid PET scans at the time of a data freeze (December, 2020) of the Dominantly Inherited Alzheimer Network (DIAN) study. Controls from the two studies were combined into a single group. All DIAN study participants had genetic testing to determine PSEN1, PSEN2, or APP mutation status. APOE genotype was determined from blood samples. CSF samples were collected in a subset of ABC-DS and DIAN participants and the ratio of amyloid β42 (Aβ42) to Aβ40 (Aβ42/40) was measured to evaluate its Spearman's correlation with amyloid PET. Global PET amyloid burden was compared with regards to cognitive status, APOE ɛ4 status, sex, age, and estimated years to symptom onset. We further analysed amyloid PET deposition by autosomal dominant mutation type. We also assessed regional patterns of amyloid accumulation by estimated number of years to symptom onset. Within a subset of participants the relationship between amyloid PET and CSF Aβ42/40 was evaluated.

FINDINGS

192 individuals with Down syndrome and 33 sibling controls from the ABC-DS study and 265 carriers of autosomal dominant Alzheimer's disease mutations and 169 non-carrier familial controls from the DIAN study were included in our analyses. PET amyloid centiloid and CSF Aβ42/40 were negatively correlated in carriers of autosomal dominant Alzheimer's disease mutations (n=216; r=-0·565; p<0·0001) and in people with Down syndrome (n=32; r=-0·801; p<0·0001). There was no difference in global PET amyloid burden between asymptomatic people with Down syndrome (mean 18·80 centiloids [SD 28·33]) versus asymptomatic mutation carriers (24·61 centiloids [30·27]; p=0·11) and between symptomatic people with Down syndrome (77·25 centiloids [41·76]) versus symptomatic mutation carriers (69·15 centiloids [51·10]; p=0·34). APOE ɛ4 status and sex had no effect on global amyloid PET deposition. Amyloid deposition was elevated significantly earlier in mutation carriers than in participants with Down syndrome (estimated years to symptom onset -23·0 vs -17·5; p=0·0002). PSEN1 mutations primarily drove this difference. Early amyloid accumulation occurred in striatal and cortical regions for both mutation carriers (n=265) and people with Down syndrome (n=128). Although mutation carriers had widespread amyloid accumulation in all cortical regions, the medial occipital regions were spared in people with Down syndrome.

INTERPRETATION

Despite minor differences, amyloid PET changes were similar between people with autosomal dominant Alzheimer's disease versus Down syndrome and strongly supported early amyloid dysregulation in individuals with Down syndrome. Individuals with Down syndrome aged at least 35 years might benefit from early intervention and warrant future inclusion in clinical trials, particularly given the relatively high incidence of Down syndrome.

FUNDING

The National Institute on Aging, Riney and Brennan Funds, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the German Center for Neurodegenerative Diseases, and the Japan Agency for Medical Research and Development.

Weight Loss and Alzheimer's Disease in Down Syndrome

BACKGROUND

Virtually all adults with Down syndrome (DS) develop Alzheimer's disease (AD) pathology, but research gaps remain in understanding early signs of AD in DS.

OBJECTIVE

The goal of the present study was to determine if unintentional weight loss is part of AD in DS. The specific aims were to: 1) examine relation between chronological age, weight, AD pathology, and AD-related cognitive decline were assessed in a large cohort of adults with DS, and 2) determine if baseline PET amyloid-β (Aβ) and tau PET status (-versus+) and/or decline in memory and mental status were associated with weight loss prior to AD progression.

METHODS

Analyses included 261 adults with DS. PET data were acquired using [11C] PiB for Aβ and [18F] AV-1451 for tau. Body mass index (BMI) was calculated from weight and height. Direct measures assessed dementia and memory. Clinical AD status was determined using a case consensus process. Percent weight decline across 16-20 months was assessed in a subset of participants (n = 77).

RESULTS

Polynomial regressions indicated an 0.23 kg/m2 decrease in BMI per year beginning at age 36.5 years, which occurs alongside the period during which Aβ and tau increase and memory and mental status decline. At a within-person level, elevated Aβ, decline in memory and mental status were associated with higher percent weight loss across 16-20 months.

CONCLUSION

Unintentional weight loss occurs alongside Aβ deposition and prior to onset of AD dementia, and thus may be a useful sign of AD in DS.

Associations between saliva and plasma cytokines in cognitively normal, older adults

BACKGROUND

Inflammatory responses play key roles in the development and progression of many pathological conditions, including neurodegenerative diseases. Accurate quantification of inflammatory factors in saliva would be highly advantageous, given its convenience and non-invasive nature, especially in elderly populations.

METHODS

In this study, we measured levels of 10 cytokines, and the pro-inflammatory factor, YKL-40, in plasma and saliva samples from a cohort of nondemented older adults (n = 71; 62% female; 70.3 ± 6.4 years) using sensitive electrochemiluminescence-based immunoassays.

RESULTS

We found that the mean levels of all cytokines were higher in saliva compared to plasma and that strong sex differences were observed for both saliva and plasma cytokines in this population. Comparing each cytokine between the two biofluids, we found that levels of interferon-gamma (IFNγ), interleukin (IL)-6 and tumor necrosis factor-alpha (TNFα) in blood were significantly correlated with their respective levels in saliva. We further observed that levels of these cytokines in blood were significantly correlated with additional cytokines in saliva, including IL-1β, IL-10, IL-8, IL12p70 and IL-13.

CONCLUSIONS

These findings show that inflammatory markers in saliva are associated with those found in circulation, suggesting shared inflammatory mechanisms between these two fluids. The higher levels of cytokines measured in saliva suggest that it might represent a better peripheral fluid to gauge inflammatory processes. Finally, our findings of robust sex differences in several salivary cytokines could have important implications for their potential use as disease biomarkers in the elderly and might be related to sex differences in the prevalence of age-related conditions.

Timing of Alzheimer's Disease by Intellectual Disability Level in Down Syndrome

BACKGROUND

Trisomy 21 causes Down syndrome (DS) and is a recognized cause of early-onset Alzheimer's disease (AD).

OBJECTIVE

The current study sought to determine if premorbid intellectual disability level (ID) was associated with variability in age-trajectories of AD biomarkers and cognitive impairments. General linear mixed models compared the age-trajectory of the AD biomarkers PET Aβ and tau and cognitive decline across premorbid ID levels (mild, moderate, and severe/profound), in models controlling trisomy type, APOE status, biological sex, and site.

METHODS

Analyses involved adults with DS from the Alzheimer's Biomarkers Consortium-Down Syndrome. Participants completed measures of memory, mental status, and visuospatial ability. Premorbid ID level was based on IQ or mental age scores prior to dementia concerns. PET was acquired using [11C] PiB for Aβ, and [18F] AV-1451 for tau.

RESULTS

Cognitive data was available for 361 participants with a mean age of 45.22 (SD = 9.92) and PET biomarker data was available for 154 participants. There was not a significant effect of premorbid ID level by age on cognitive outcomes. There was not a significant effect of premorbid ID by age on PET Aβ or on tau PET. There was not a significant difference in age at time of study visit of those with mild cognitive impairment-DS or dementia by premorbid ID level.

CONCLUSION

Findings provide robust evidence of a similar time course in AD trajectory across premorbid ID levels, laying the groundwork for the inclusion of individuals with DS with a variety of IQ levels in clinical AD trials.

Detection of Brain Tau Pathology in Down Syndrome Using Plasma Biomarkers

Importance

Novel plasma biomarkers, especially phosphorylated tau (p-tau), can detect brain tau aggregates in Alzheimer disease.

Objective

To determine which plasma biomarker combinations can accurately detect tau pathological brain changes in Down syndrome (DS).

Design, Setting, and Participants

The cross-sectional, multicenter Alzheimer's Biomarker Consortium-Down Syndrome study included adults with DS and a control group of siblings without DS. All participants with plasma, positron emission tomography (PET), and cognitive measures available by the time of data freeze 1.0 were included. Participants were enrolled between 2016 and 2019, and data were analyzed from August 2021 to April 2022.

Exposures

Plasma p-tau217, glial fibrillary acidic protein (GFAP), amyloid β42/40 (Aβ42/Aβ40), neurofilament light (NfL), and total tau (t-tau); tau positron emission tomography (tau-PET) and Aβ-PET.

Main Outcomes and Measures

The primary outcome was tau-PET status. Secondary outcomes included Aβ-PET status and cognitive performance.

Results

Among 300 participants with DS and a control group of 37 non-DS siblings, mean (SD) age was 45.0 (10.1) years, and 167 (49.6%) were men. Among participants with DS who all underwent plasma p-tau217 and GFAP analyses, 258 had other plasma biomarker data available and 119, 213, and 288 participants had tau-PET, Aβ-PET, and cognitive assessments, respectively. Plasma p-tau217 and t-tau were significantly increased in Aβ-PET-positive tau-PET-positive (A+T+) DS and A+T- DS compared with A-T- DS while GFAP was only increased in A+T+ DS. Plasma p-tau217 levels were also significantly higher in A+T+ DS than A+T- DS. In participants with DS, plasma p-tau217 and GFAP (but not other plasma biomarkers) were consistently associated with abnormal tau-PET and Aβ-PET status in models covaried for age (odds ratio range, 1.59 [95% CI, 1.05-2.40] to 2.32 [95% CI, 1.36-3.96]; P < .03). A combination of p-tau217 and age performed best when detecting tau-PET abnormality in temporal and neocortical regions (area under the curve [AUC] range, 0.96-0.99). The most parsimonious model for Aβ-PET status included p-tau217, t-tau, and age (AUC range, 0.93-0.95). In multivariable models, higher p-tau217 levels but not other biomarkers were associated with worse performance on DS Mental Status Examination (β, -0.24, 95% CI, -0.36 to -0.12; P < .001) and Cued Recall Test (β, -0.40; 95% CI, -0.53 to -0.26; P < .001).

Conclusions and Relevance

Plasma p-tau217 is a very accurate blood-based biomarker of both tau and Aβ pathological brain changes in DS that could help guide screening and enrichment strategies for inclusion of individuals with DS in future AD clinical trials, especially when it is combined with age as a covariate.

Beyond amyloid: Immune, cerebrovascular, and metabolic contributions to Alzheimer disease in people with Down syndrome

People with Down syndrome (DS) have increased risk of Alzheimer disease (AD), presumably conferred through genetic predispositions arising from trisomy 21. These predispositions necessarily include triplication of the amyloid precursor protein (APP), but also other Ch21 genes that confer risk directly or through interactions with genes on other chromosomes. We discuss evidence that multiple genes on chromosome 21 are associated with metabolic dysfunction in DS. The resulting dysregulated pathways involve the immune system, leading to chronic inflammation; the cerebrovascular system, leading to disruption of the blood brain barrier (BBB); and cellular energy metabolism, promoting increased oxidative stress. In combination, these disruptions may produce a precarious biological milieu that, in the presence of accumulating amyloid, drives the pathophysiological cascade of AD in people with DS. Critically, mechanistic drivers of this dysfunction may be targetable in future clinical trials of pharmaceutical and/or lifestyle interventions.

Joint-label fusion brain atlases for dementia research in Down syndrome

Research suggests a link between Alzheimer's Disease in Down Syndrome (DS) and the overproduction of amyloid plaques. Using Positron Emission Tomography (PET) we can assess the in-vivo regional amyloid load using several available ligands. To measure amyloid distributions in specific brain regions, a brain atlas is used. A popular method of creating a brain atlas is to segment a participant's structural Magnetic Resonance Imaging (MRI) scan. Acquiring an MRI is often challenging in intellectually-imparied populations because of contraindications or data exclusion due to significant motion artifacts or incomplete sequences related to general discomfort. When an MRI cannot be acquired, it is typically replaced with a standardized brain atlas derived from neurotypical populations (i.e. healthy individuals without DS) which may be inappropriate for use in DS. In this project, we create a series of disease and diagnosis-specific (cognitively stable (CS-DS), mild cognitive impairment (MCI-DS), and dementia (DEM-DS)) probabilistic group atlases of participants with DS and evaluate their accuracy of quantifying regional amyloid load compared to the individually-based MRI segmentations. Further, we compare the diagnostic-specific atlases with a probabilistic atlas constructed from similar-aged cognitively-stable neurotypical participants. We hypothesized that regional PET signals will best match the individually-based MRI segmentations by using DS group atlases that aligns with a participant's disorder and disease status (e.g. DS and MCI-DS). Our results vary by brain region but generally show that using a disorder-specific atlas in DS better matches the individually-based MRI segmentations than using an atlas constructed from cognitively-stable neurotypical participants. We found no additional benefit of using diagnose-specific atlases matching disease status. All atlases are made publicly available for the research community.

Highlight

Down syndrome (DS) joint-label-fusion atlases provide accurate positron emission tomography (PET) amyloid measurements.A disorder-specific DS atlas is better than a neurotypical atlas for PET quantification.It is not necessary to use a disease-state-specific atlas for quantification in aged DS.Dorsal striatum results vary, possibly due to this region and dementia progression.

A blood screening tool for detecting mild cognitive impairment and Alzheimer's disease among community-dwelling Mexican Americans and non-Hispanic Whites: A method for increasing representation of diverse populations in clinical research

INTRODUCTION

Representation of Mexican Americans in Alzheimer's disease (AD) clinical research has been extremely poor.

METHODS

Data were examined from the ongoing community-based, multi-ethnic Health & Aging Brain among Latino Elders (HABLE) study. Participants underwent functional exams, clinical labs, neuropsychological testing, and 3T magnetic resonance imaging of the brain. Fasting proteomic markers were examined for predicting mild cognitive impairment (MCI) and AD using support vector machine models.

RESULTS

Data were examined from n = 1649 participants (Mexican American n = 866; non-Hispanic White n = 783). Proteomic profiles were highly accurate in detecting MCI (area under the curve [AUC] = 0.91) and dementia (AUC = 0.95). The proteomic profiles varied significantly between ethnic groups and disease state. Negative predictive value was excellent for ruling out MCI and dementia across ethnic groups.

DISCUSSION

A blood-based screening tool can serve as a method for increasing access to state-of-the-art AD clinical research by bridging between community-based and clinic-based settings.

TGFβ Drives Metabolic Perturbations during Epithelial Mesenchymal Transition in Pancreatic Cancer: TGFβ Induced EMT in PDAC

Simple Summary

Pancreatic cancer is an aggressive disease with most patients diagnosed at late stages resulting in poor outcomes. While it is known that pancreatic tumor cells undergo epithelial to mesenchymal transition, the metabolic alterations accompanying that transition are not characterized. This study leveraged a metabolomics approach to understand the small molecule and biochemical perturbations that can be targeted for designing strategies for improving outcomes in pancreatic cancer.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy wherein a majority of patients present metastatic disease at diagnosis. Although the role of epithelial to mesenchymal transition (EMT), mediated by transforming growth factor beta (TGFβ), in imparting an aggressive phenotype to PDAC is well documented, the underlying biochemical pathway perturbations driving this behaviour have not been elucidated. We used high-resolution mass spectrometry (HRMS) based molecular phenotyping approach in order to delineate metabolic changes concomitant to TGFβ-induced EMT in pancreatic cancer cells. Strikingly, we observed robust changes in amino acid and energy metabolism that may contribute to tumor invasion and metastasis. Somewhat unexpectedly, TGFβ treatment resulted in an increase in intracellular levels of retinoic acid (RA) that in turn resulted in increased levels of extracellular matrix (ECM) proteins including fibronectin (FN) and collagen (COL1). These findings were further validated in plasma samples obtained from patients with resectable pancreatic cancer. Taken together, these observations provide novel insights into small molecule dysregulation that triggers a molecular cascade resulting in increased EMT-like changes in pancreatic cancer cells, a paradigm that can be potentially targeted for better clinical outcomes.

Omics sciences for systems biology in Alzheimer's disease: State-of-the-art of the evidence

Alzheimer's disease (AD) is characterized by non-linear, genetic-driven pathophysiological dynamics with high heterogeneity in biological alterations and disease spatial-temporal progression. Human in-vivo and post-mortem studies point out a failure of multi-level biological networks underlying AD pathophysiology, including proteostasis (amyloid-β and tau), synaptic homeostasis, inflammatory and immune responses, lipid and energy metabolism, oxidative stress. Therefore, a holistic, systems-level approach is needed to fully capture AD multi-faceted pathophysiology. Omics sciences - genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics - embedded in the systems biology (SB) theoretical and computational framework can generate explainable readouts describing the entire biological continuum of a disease. Such path in Neurology is encouraged by the promising results of omics sciences and SB approaches in Oncology, where stage-driven pathway-based therapies have been developed in line with the precision medicine paradigm. Multi-omics data integrated in SB network approaches will help detect and chart AD upstream pathomechanistic alterations and downstream molecular effects occurring in preclinical stages. Finally, integrating omics and neuroimaging data - i.e., neuroimaging-omics - will identify multi-dimensional biological signatures essential to track the clinical-biological trajectories, at the subpopulation or even individual level.

Plasma Total-Tau and Neurofilament Light Chain as Diagnostic Biomarkers of Alzheimer's Disease Dementia and Mild Cognitive Impairment in Adults with Down Syndrome

BACKGROUND

The need for diagnostic biomarkers of cognitive decline is particularly important among aging adults with Down syndrome (DS). Growing empirical support has identified the utility of plasma derived biomarkers among neurotypical adults with mild cognitive impairment (MCI) and Alzheimer's disease (AD); however, the application of such biomarkers has been limited among the DS population.

OBJECTIVE

This study aimed to investigate the cross-sectional diagnostic performance of plasma neurofilament light chain (Nf-L) and total-tau, individually and in combination among a cohort of DS adults.

METHODS

Plasma samples were analyzed from n = 305 (n = 225 cognitively stable (CS); n = 44 MCI-DS; n = 36 DS-AD) participants enrolled in the Alzheimer's Biomarker Consortium -Down Syndrome.

RESULTS

In distinguishing DS-AD participants from CS, Nf-L alone produced an AUC of 90%, total-tau alone reached 74%, and combined reached an AUC of 86%. When age and gender were included, AUC increased to 93%. Higher values of Nf-L, total-tau, and age were all shown to be associated with increased risk for DS-AD. When distinguishing MCI-DS participants from CS, Nf-L alone produced an AUC of 65%, while total-tau alone reached 56%. A combined model with Nf-L, total-tau, age, and gender produced an AUC of 87%. Both higher values in age and total-tau were found to increase risk for MCI-DS; Nf-L levels were not associated with increased risk for MCI-DS.

CONCLUSION

Advanced assay techniques make total-tau and particularly Nf-L useful biomarkers of both AD pathology and clinical status in DS and have the potential to serve as outcome measures in clinical trials for future disease-modifying drugs.

Plasma Sphingomyelins in Late-Onset Alzheimer's Disease

BACKGROUND

Altered plasma levels of sphingolipids, including sphingomyelins (SM), have been found in mouse models of Alzheimer's disease (AD) and in AD patient plasma samples.

OBJECTIVE

This study assesses fourteen plasma SM species in a late-onset AD (LOAD) patient cohort (n = 138).

METHODS

Specimens from control, preclinical, and symptomatic subjects were analyzed using targeted mass-spectrometry-based metabolomic methods.

RESULTS

Total plasma SM levels were not significantly affected by age or cognitive status. However, one metabolite that has been elevated in manifest AD in several recent studies, SM OHC14:1, was reduced significantly in pre-clinical AD and MCI relative to normal controls.

CONCLUSION

We recommend additional comprehensive plasma lipidomics in experimental and clinical biospecimens related to LOAD that might advance the utility of plasma sphingomyelin levels in molecular phenotyping and interpretations of pathobiological mechanisms.

A Community-Based Study Identifying Metabolic Biomarkers of Mild Cognitive Impairment and Alzheimer's Disease Using Artificial Intelligence and Machine Learning

BACKGROUND

Currently, there is no objective, clinically available tool for the accurate diagnosis of Alzheimer's disease (AD). There is a pressing need for a novel, minimally invasive, cost friendly, and easily accessible tool to diagnose AD, assess disease severity, and prognosticate course. Metabolomics is a promising tool for discovery of new, biologically, and clinically relevant biomarkers for AD detection and classification.

OBJECTIVE

Utilizing artificial intelligence and machine learning, we aim to assess whether a panel of metabolites as detected in plasma can be used as an objective and clinically feasible tool for the diagnosis of mild cognitive impairment (MCI) and AD.

METHODS

Using a community-based sample cohort acquired from different sites across the US, we adopted an approach combining Proton Nuclear Magnetic Resonance Spectroscopy (1H NMR), Liquid Chromatography coupled with Mass Spectrometry (LC-MS) and various machine learning statistical approaches to identify a biomarker panel capable of identifying those patients with AD and MCI from healthy controls.

RESULTS

Of the 212 measured metabolites, 5 were identified as optimal to discriminate between controls, and individuals with MCI or AD. Our models performed with AUC values in the range of 0.72-0.76, with the sensitivity and specificity values ranging from 0.75-0.85 and 0.69-0.81, respectively. Univariate and pathway analysis identified lipid metabolism as the most perturbed biochemical pathway in MCI and AD.

CONCLUSION

A comprehensive method of acquiring metabolomics data, coupled with machine learning techniques, has identified a strong panel of diagnostic biomarkers capable of identifying individuals with MCI and AD. Further, our data confirm what other groups have reported, that lipid metabolism is significantly perturbed in those individuals suffering with dementia. This work may provide additional insight into AD pathogenesis and encourage more in-depth analysis of the AD lipidome.

The AT(N) framework for Alzheimer's disease in adults with Down syndrome

The National Institute on Aging in conjunction with the Alzheimer's Association (NIA-AA) recently proposed a biological framework for defining the Alzheimer's disease (AD) continuum. This new framework is based upon the key AD biomarkers (amyloid, tau, neurodegeneration, AT[N]) instead of clinical symptoms and represents the latest understanding that the pathological processes underlying AD begin decades before the manifestation of symptoms. By using these same biomarkers, individuals with Down syndrome (DS), who are genetically predisposed to developing AD, can also be placed more precisely along the AD continuum. The A/T(N) framework is therefore thought to provide an objective manner by which to select and enrich samples for clinical trials. This new framework is highly flexible and allows the addition of newly confirmed AD biomarkers into the existing AT(N) groups. As biomarkers for other pathological processes are validated, they can also be added to the AT(N) classification scheme, which will allow for better characterization and staging of AD in DS. These biological classifications can then be merged with clinical staging for an examination of factors that impact the biological and clinical progression of the disease. Here, we leverage previously published guidelines for the AT(N) framework to generate such a plan for AD among adults with DS.

Cognitively supernormal older adults maintain a unique structural connectome that is resistant to Alzheimer's pathology

Studying older adults with excellent cognitive capacities (Supernormals) provides a unique opportunity for identifying factors related to cognitive success - a critical topic across lifespan. There is a limited understanding of Supernormals' neural substrates, especially whether any of them attends shaping and supporting superior cognitive function or confer resistance to age-related neurodegeneration such as Alzheimer's disease (AD). Here, applying a state-of-the-art diffusion imaging processing pipeline and finite mixture modelling, we longitudinally examine the structural connectome of Supernormals. We find a unique structural connectome, containing the connections between frontal, cingulate, parietal, temporal, and subcortical regions in the same hemisphere that remains stable over time in Supernormals, relatively to typical agers. The connectome significantly classifies positive vs. negative AD pathology at 72% accuracy in a new sample mixing Supernormals, typical agers, and AD risk [amnestic mild cognitive impairment (aMCI)] subjects. Among this connectome, the mean diffusivity of the connection between right isthmus cingulate cortex and right precuneus most robustly contributes to predicting AD pathology across samples. The mean diffusivity of this connection links negatively to global cognition in those Supernormals with positive AD pathology. But this relationship does not exist in typical agers or aMCI. Our data suggest the presence of a structural connectome supporting cognitive success. Cingulate to precuneus white matter integrity may be useful as a structural marker for monitoring neurodegeneration and may provide critical information for understanding how some older adults maintain or excel cognitively in light of significant AD pathology.

The Alzheimer's Biomarker Consortium-Down Syndrome: Rationale and methodology

INTRODUCTION

Adults with Down syndrome (DS) are at exceptionally high risk for Alzheimer's disease (AD), with virtually all individuals developing key neuropathological features by age 40. Identifying biomarkers of AD progression in DS can provide valuable insights into pathogenesis and suggest targets for disease modifying treatments.

METHODS

We describe the development of a multi-center, longitudinal study of biomarkers of AD in DS. The protocol includes longitudinal examination of clinical, cognitive, blood and cerebrospinal fluid-based biomarkers, magnetic resonance imaging and positron emission tomography measures (at 16-month intervals), as well as genetic modifiers of AD risk and progression.

RESULTS

Approximately 400 individuals will be enrolled in the study (more than 370 to date). The methodological approach from the administrative, clinical, neuroimaging, omics, neuropathology, and statistical cores is provided.

DISCUSSION

This represents the largest U.S.-based, multi-site, biomarker initiative of AD in DS. Findings can inform other multidisciplinary networks studying AD in the general population.

Proteomic profiles for Alzheimer's disease and mild cognitive impairment among adults with Down syndrome spanning serum and plasma: An Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study

INTRODUCTION

Previously generated serum and plasma proteomic profiles were examined among adults with Down syndrome (DS) to determine whether these profiles could discriminate those with mild cognitive impairment (MCI-DS) and Alzheimer's disease (DS-AD) from those cognitively stable (CS).

METHODS

Data were analyzed on n = 305 (n = 225 CS; n = 44 MCI-DS; n = 36 DS-AD) enrolled in the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS).

RESULTS

Distinguishing MCI-DS from CS, the serum profile produced an area under the curve (AUC) = 0.95 (sensitivity [SN] = 0.91; specificity [SP] = 0.99) and an AUC = 0.98 (SN = 0.96; SP = 0.97) for plasma when using an optimized cut-off score. Distinguishing DS-AD from CS, the serum profile produced an AUC = 0.93 (SN = 0.81; SP = 0.99) and an AUC = 0.95 (SN = 0.86; SP = 1.0) for plasma when using an optimized cut-off score. AUC remained unchanged to slightly improved when age and sex were included. Eotaxin3, interleukin (IL)-10, C-reactive protein, IL-18, serum amyloid A , and FABP3 correlated fractions at r2 > = 0.90.

DISCUSSION

Proteomic profiles showed excellent detection accuracy for MCI-DS and DS-AD.

Metabolic correlates of prevalent mild cognitive impairment and Alzheimer's disease in adults with Down syndrome

INTRODUCTION

Disruption of metabolic function is a recognized feature of late onset Alzheimer's disease (LOAD). We sought to determine whether similar metabolic pathways are implicated in adults with Down syndrome (DS) who have increased risk for Alzheimer's disease (AD).

METHODS

We examined peripheral blood from 292 participants with DS who completed baseline assessments in the Alzheimer's Biomarkers Consortium-Down Syndrome (ABC-DS) using untargeted mass spectrometry (MS). Our sample included 38 individuals who met consensus criteria for AD (DS-AD), 43 who met criteria for mild cognitive impairment (DS-MCI), and 211 who were cognitively unaffected and stable (CS).

RESULTS

We measured relative abundance of 8,805 features using MS and 180 putative metabolites were differentially expressed (DE) among the groups at false discovery rate-corrected q< 0.05. From the DE features, a nine-feature classifier model classified the CS and DS-AD groups with receiver operating characteristic area under the curve (ROC AUC) of 0.86 and a two-feature model classified the DS-MCI and DS-AD groups with ROC AUC of 0.88. Metabolite set enrichment analysis across the three groups suggested alterations in fatty acid and carbohydrate metabolism.

DISCUSSION

Our results reveal metabolic alterations in DS-AD that are similar to those seen in LOAD. The pattern of results in this cross-sectional DS cohort suggests a dynamic time course of metabolic dysregulation which evolves with clinical progression from non-demented, to MCI, to AD. Metabolomic markers may be useful for staging progression of DS-AD.

Blood-based systems biology biomarkers for next-generation clinical trials in Alzheimer's disease

Alzheimer's disease (AD)-a complex disease showing multiple pathomechanistic alterations-is triggered by nonlinear dynamic interactions of genetic/epigenetic and environmental risk factors, which, ultimately, converge into a biologically heterogeneous disease. To tackle the burden of AD during early preclinical stages, accessible blood-based biomarkers are currently being developed. Specifically, next-generation clinical trials are expected to integrate positive and negative predictive blood-based biomarkers into study designs to evaluate, at the individual level, target druggability and potential drug resistance mechanisms. In this scenario, systems biology holds promise to accelerate validation and qualification for clinical trial contexts of use-including proof-of-mechanism, patient selection, assessment of treatment efficacy and safety rates, and prognostic evaluation. Albeit in their infancy, systems biology-based approaches are poised to identify relevant AD "signatures" through multifactorial and interindividual variability, allowing us to decipher disease pathophysiology and etiology. Hopefully, innovative biomarker-drug codevelopment strategies will be the road ahead towards effective disease-modifying drugs.
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Longitudinal Functional Brain Mapping in Supernormals

Prevention of age-related cognitive decline is an increasingly important topic. Recently, increased attention is being directed at understanding biological models of successful cognitive aging. Here, we examined resting-state brain regional low-frequency oscillations using functional magnetic resonance imaging in 19 older adults with excellent cognitive abilities (Supernormals), 28 older adults with normative cognition, 57 older adults with amnestic mild cognitive impairment, and 26 with Alzheimer's disease. We identified a "Supernormal map", a set of regions whose oscillations were resistant to the aging-associated neurodegenerative process, including the right fusiform gyrus, right middle frontal gyrus, right anterior cingulate cortex, left middle temporal gyrus, left precentral gyrus, and left orbitofrontal cortex. The map was unique to the Supernormals, differentiated this group from cognitive average-ager comparisons, and predicted a 1-year change in global cognition (indexed by the Montreal Cognitive Assessment scores, adjusted R2 = 0.68). The map was also correlated to Alzheimer's pathophysiological features (beta-amyloid/pTau ratio, adjusted R2 = 0.66) in participants with and without cognitive impairment. These findings in phenotypically successful cognitive agers suggest a divergent pattern of brain regions that may either reflect inherent neural integrity that contributes to Supernormals' cognitive success, or alternatively indicate adaptive reorganization to the demands of aging.

Plasma metabolites related to cellular energy metabolism are altered in adults with Down syndrome and Alzheimer's disease

Down syndrome (DS) is a well-known neurodevelopmental disorder most commonly caused by trisomy of chromosome 21. Because individuals with DS almost universally develop heavy amyloid burden and Alzheimer's disease (AD), biomarker discovery in this population may be extremely fruitful. Moreover, any AD biomarker in DS that does not directly involve amyloid pathology may be of high value for understanding broader mechanisms of AD generalizable to the neurotypical population. In this retrospective biomarker discovery study, we examined banked peripheral plasma samples from 78 individuals with DS who met clinical criteria for AD at the time of the blood draw (DS-AD) and 68 individuals with DS who did not (DS-NAD). We measured the relative abundance of approximately 5,000 putative features in the plasma using untargeted mass spectrometry (MS). We found significantly higher levels of a peak putatively annotated as lactic acid in the DS-AD group (q = .014), a finding confirmed using targeted MS (q = .011). Because lactate is the terminal product of glycolysis and subsequent lactic acid fermentation, we performed additional targeted MS focusing on central carbon metabolism which revealed significantly increased levels of pyruvic (q = .03) and methyladipic (q = .03) acids in addition to significantly lower levels of uridine (q = .007) in the DS-AD group. These data suggest that AD in DS is accompanied by a shift from aerobic respiration toward the less efficient fermentative metabolism and that bioenergetically derived metabolites observable in peripheral blood may be useful for detecting this shift.

Identify a shared neural circuit linking multiple neuropsychiatric symptoms with Alzheimer's pathology

Neuropsychiatric symptoms (NPS) are common in Alzheimer's disease (AD)-associated neurodegeneration. However, NPS lack a consistent relationship with AD pathology. It is unknown whether any common neural circuits can link these clinically disparate while mechanistically similar features with AD pathology. Here, we explored the neural circuits of NPS in AD-associated neurodegeneration using multivariate pattern analysis (MVPA) of resting-state functional MRI data. Data from 98 subjects (70 amnestic mild cognitive impairment and 28 AD subjects) were obtained. The top 10 regions differentiating symptom presence across NPS were identified, which were mostly the fronto-limbic regions (medial prefrontal cortex, caudate, etc.). These 10 regions' functional connectivity classified symptomatic subjects across individual NPS at 69.46-81.27%, and predicted multiple NPS (indexed by Neuropsychiatric Symptom Questionnaire-Inventory) and AD pathology (indexed by baseline and change of beta-amyloid/pTau ratio) all above 70%. Our findings suggest a fronto-limbic dominated neural circuit that links multiple NPS and AD pathology. With further examination of the structural and pathological changes within the circuit, the circuit may shed light on linking behavioral disturbances with AD-associated neurodegeneration.

Toward Reproducible Results from Targeted Metabolomic Studies: Perspectives for Data Pre-processing and a Basis for Analytic Pipeline Development

Contemporary metabolomics experiments generate a rich array of complex high-dimensional data. Consequently, there have been concurrent efforts to develop methodological standards and analytical workflows to streamline the generation of meaningful biochemical and clinical inferences from raw data generated using an analytical platform like mass spectrometry. While such considerations have been frequently addressed in untargeted metabolomics (i.e., the broad survey of all distinguishable metabolites within a sample of interest), this methodological scrutiny has seldom been applied to data generated using commercial, targeted metabolomics kits. We suggest that this may, in part, account for past and more recent incomplete replications of previously specified biomarker panels. Herein, we identify common impediments challenging the analysis of raw, targeted metabolomic abundance data from a commercial kit and review methods to remedy these issues. In doing so, we propose an analytical pipeline suitable for the pre-processing of data for downstream biomarker discovery. Operational and statistical considerations for integrating targeted data sets across experimental sites and analytical batches are discussed, as are best practices for developing predictive models relating pre-processed metabolomic data to associated phenotypic information.

Potential Metabolomic Linkage in Blood between Parkinson's Disease and Traumatic Brain Injury

The etiologic basis for sporadic forms of neurodegenerative diseases has been elusive but likely represents the product of genetic predisposition and various environmental factors. Specific gene-environment interactions have become more salient owing, in part, to the elucidation of epigenetic mechanisms and their impact on health and disease. The linkage between traumatic brain injury (TBI) and Parkinson's disease (PD) is one such association that currently lacks a mechanistic basis. Herein, we present preliminary blood-based metabolomic evidence in support of potential association between TBI and PD. Using untargeted and targeted high-performance liquid chromatography-mass spectrometry we identified metabolomic biomarker profiles in a cohort of symptomatic mild TBI (mTBI) subjects (n = 75) 3⁻12 months following injury (subacute) and TBI controls (n = 20), and a PD cohort with known PD (n = 20) or PD dementia (PDD) (n = 20) and PD controls (n = 20). Surprisingly, blood glutamic acid levels in both the subacute mTBI (increased) and PD/PDD (decreased) groups were notably altered from control levels. The observed changes in blood glutamic acid levels in mTBI and PD/PDD are discussed in relation to other metabolite profiling studies. Should our preliminary results be replicated in comparable metabolomic investigations of TBI and PD cohorts, they may contribute to an "excitotoxic" linkage between TBI and PD/PDD.

Temporospatial components of brain ERPs as biomarkers for Alzheimer's disease

Introduction

Developing biomarkers that distinguish individuals with Alzheimer's disease (AD) from those with normal cognition remains a crucial goal for improving the health of older adults. We investigated adding brain spatial information to temporal event-related potentials (ERPs) to increase AD identification accuracy over temporal ERPs alone.

Methods

With two-step principal components analysis, we applied multivariate analyses that incorporated temporal and spatial ERP information from a cognitive task. Discriminant analysis used temporospatial ERP scores to classify participants as belonging to either the AD or healthy control group.

Results

Temporospatial ERPs produced a cross-validated area under the curve of 0.84. Adding spatial information through a formal procedure significantly improves classification accuracy.

Discussion

A weighted combination of temporospatial ERP markers performs well in detecting AD. Because ERPs are noninvasive and inexpensive, they may be promising biomarkers for AD that can add functional information to other biomarker systems while providing the individual's probability of correct classification.

Plasma metabolomic biomarkers accurately classify acute mild traumatic brain injury from controls

Past and recent attempts at devising objective biomarkers for traumatic brain injury (TBI) in both blood and cerebrospinal fluid have focused on abundance measures of time-dependent proteins. Similar independent determinants would be most welcome in diagnosing the most common form of TBI, mild TBI (mTBI), which remains difficult to define and confirm based solely on clinical criteria. There are currently no consensus diagnostic measures that objectively define individuals as having sustained an acute mTBI. Plasma metabolomic analyses have recently evolved to offer an alternative to proteomic analyses, offering an orthogonal diagnostic measure to what is currently available. The purpose of this study was to determine whether a developed set of metabolomic biomarkers is able to objectively classify college athletes sustaining mTBI from non-injured teammates, within 6 hours of trauma and whether such a biomarker panel could be effectively applied to an independent cohort of TBI and control subjects.

A 6-metabolite panel was developed from biomarkers that had their identities confirmed using tandem mass spectrometry (MS/MS) in our Athlete cohort. These biomarkers were defined at ≤6 hours following mTBI and objectively classified mTBI athletes from teammate controls, and provided similar classification of these groups at the 2, 3, and 7 days post-mTBI. The same 6-metabolite panel, when applied to a separate, independent cohort provided statistically similar results despite major differences between the two cohorts. Our confirmed plasma biomarker panel objectively classifies acute mTBI cases from controls within 6 hours of injury in our two independent cohorts. While encouraged by our initial results, we expect future studies to expand on these initial observations.