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By age 40 years, over 90% of adults with Down syndrome have Alzheimer's disease pathology and most progress to dementia. Despite having few systemic vascular risk factors, individuals with Down syndrome have elevated cerebrovascular disease markers that track with the clinical progression of Alzheimer's disease, suggesting a role of cerebrovascular disease that is hypothesized to be mediated by inflammatory factors. This study examined the pathways through which small vessel cerebrovascular disease contributes to Alzheimer's disease-related pathophysiology and neurodegeneration in adults with Down syndrome. One hundred eighty-five participants from the Alzheimer's Biomarkers Consortium-Down Syndrome [mean (SD) age = 45.2 (9.3) years] with available MRI and plasma biomarker data were included in this study. White matter hyperintensity (WMH) volumes were derived from T2-weighted fluid-attenuated inversion recovery MRI scans, and plasma biomarker concentrations of amyloid beta 42/40, phosphorylated tau 217, astrocytosis (glial fibrillary acidic protein) and neurodegeneration (neurofilament light chain) were measured with ultrasensitive immunoassays. We examined the bivariate relationships of WMH, amyloid beta 42/40, phosphorylated tau 217 and glial fibrillary acidic protein with age-residualized neurofilament light chain across Alzheimer's disease diagnostic groups. A series of mediation and path analyses examined statistical pathways linking WMH and Alzheimer's disease pathophysiology to promote neurodegeneration in the total sample and groups stratified by clinical diagnosis. There was a direct and indirect bidirectional effect through the glial fibrillary acidic protein of WMH on phosphorylated tau 217 concentration, which was associated with neurofilament light chain concentration in the entire sample. Amongst cognitively stable participants, WMH was directly and indirectly, through glial fibrillary acidic protein, associated with phosphorylated tau 217 concentration, and in those with mild cognitive impairment, there was a direct effect of WMH on phosphorylated tau 217 and neurofilament light chain concentrations. There were no associations of WMH with biomarker concentrations among those diagnosed with dementia. The findings from this cross-sectional study suggest that among individuals with Down syndrome, cerebrovascular disease promotes neurodegeneration by increasing astrocytosis and tau pathophysiology in the presymptomatic phases of Alzheimer's disease, but future studies will need to confirm these associations with longitudinal data. This work joins an emerging literature that implicates cerebrovascular disease and its interface with neuroinflammation as a core pathological feature of Alzheimer's disease in adults with Down syndrome.

IntroductionEmerging 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.MethodsWe 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).ResultsEighteen-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.DiscussionThese 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.HighlightsMicrobial 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.

BackgroundVariants in ABCA7, a member of the ABC transporter superfamily, have been associated with increased risk for developing late onset Alzheimer's disease (LOAD).MethodsCRISPR-Cas9 was used to generate an Abca7V1613M variant in mice, modeling the homologous human ABCA7V1599M variant, and extensive characterization was performed.ResultsAbca7V1613M 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.DiscussionOverall, 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.HighlightsABCA7 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.

IntroductionLate-onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long-Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics.MethodsWe conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub-sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aβ) levels.ResultsWe identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10-9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aβ42/40 ratio compared to lower amyloid.DiscussionMTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology.HighlightsLong-Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

IntroductionPeople 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.MethodsThis 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).ResultsIn 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.DiscussionPlasma biomarkers may have utility in tracking AD pathology associated with early stages of cognitive decline in adults with DS, although associations were modest.HighlightsPlasma 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.

Adults with Down syndrome have a genetic form of Alzheimer's disease (AD) and evidence of cerebrovascular disease across the AD continuum, despite few systemic vascular risk factors. The onset and progression of AD in Down syndrome is highly age-dependent, but it is unknown at what age cerebrovascular disease emerges and what factors influence its severity. In the Alzheimer's Biomarker Consortium-Down Syndrome study (ABC-DS; n = 242; age = 25-72), we estimated the age inflection point at which MRI-based white matter hyperintensities (WMH), enlarged perivascular spaces (PVS), microbleeds, and infarcts emerge in relation to demographic data, risk factors, amyloid and tau, and AD diagnosis. Enlarged PVS and infarcts appear to develop in the early 30s, while microbleeds, WMH, amyloid, and tau emerge in the mid to late 30s. Age-residualized WMH were higher in women, in individuals with dementia, and with lower body mass index. Participants with hypertension and APOE-ε4 had higher age-residualized PVS and microbleeds, respectively. Lifespan trajectories demonstrate a dramatic cerebrovascular profile in adults with Down syndrome that appears to evolve developmentally in parallel with AD pathophysiology approximately two decades prior to dementia symptoms.

Adults with Down syndrome 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 and is linked to a diagnosis of dementia in adults with Down syndrome via structural imaging markers of cerebrovascular disease and atrophy. The study included participants with Down syndrome from the Alzheimers Disease - Down Syndrome study (n = 195, age = 50.6 ± 7.2 years, 44% women, 18% diagnosed with dementia). Higher pulse pressure was associated with greater global, parietal and occipital white matter hyperintensity volume but not with enlarged perivascular spaces, microbleeds or infarcts. Using a structural equation model, we found that pulse pressure was associated with greater white matter hyperintensity volume, which in turn was related to increased neurodegeneration, and subsequent dementia diagnosis. Pulse pressure is an important determinant of brain health and clinical outcomes in individuals with Down syndrome despite the low likelihood of frank hypertension.

INTRODUCTION: Virtually all people with Down syndrome (DS) develop neuropathology associated with Alzheimers 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.

BackgroundMild 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.MethodsPersons 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.ResultsBaseline 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.ConclusionsLower 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.

BackgroundImportant 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.MethodsIn 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.Findings192 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

BACKGROUND: Virtually all adults with Down syndrome (DS) develop Alzheimers 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.

BACKGROUND: Trisomy 21 causes Down syndrome (DS) and is a recognized cause of early-onset Alzheimers 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 Alzheimers 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.

BackgroundInflammatory 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.MethodsIn 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.ResultsWe 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.ConclusionsThese 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.

Recent reports implicate gut microbiome dysbiosis in the onset and progression of Alzheimer's disease (AD), yet studies involving model animals overwhelmingly omit the microbial perspective. Here, we evaluate longitudinal microbiomes and metabolomes from a popular transgenic mouse model for familial AD (5xfAD). Cecal and fecal samples from 5xfAD and wild-type B6J (WT) mice from 4 to 18 months of age were subjected to shotgun Illumina sequencing. Metabolomics was performed on plasma and feces from a subset of the same animals. Significant genotype, sex, age, and cage-specific differences were observed in the microbiome, with the variance explained by genotype at 4 and 18 months of age rising from 0.9 to 9% and 0.3 to 8% for the cecal and fecal samples, respectively. Bacteria at significantly higher abundances in AD mice include multiple Alistipes spp., two Ligilactobacillus spp., and Lactobacillus sp. P38, while multiple species of Turicibacter, Lactobacillus johnsonii, and Romboutsia ilealis were less abundant. Turicibacter is similarly depleted in people with AD, and members of this genus both consume and induce the production of gut-derived serotonin. Contradicting previous findings in humans, serotonin is significantly more concentrated in the blood of older 5xfAD animals compared to their WT littermates. 5xfAD animals exhibited significantly lower plasma concentrations of carnosine and the lysophospholipid lysoPC a C18:1. Correlations between the microbiome and metabolome were also explored. Taken together, these findings strengthen the link between Turicibacter abundance and AD, provide a basis for further microbiome studies of murine models for AD, and suggest that greater control over animal model microbiomes is needed in AD research. IMPORTANCE Microorganisms residing within the gastrointestinal tract are implicated in the onset and progression of Alzheimer's disease (AD) through the mediation of inflammation, exchange of small-molecules across the blood-brain barrier, and stimulation of the vagus nerve. Unfortunately, most animal models for AD are housed under conditions that do not reflect real-world human microbial exposure and do not sufficiently account for (or meaningfully consider) variations in the microbiome. An improved understanding of AD model animal microbiomes will increase model efficacy and the translatability of research findings into humans. Here, we present the characterization of the microbiome and metabolome of the 5xfAD mouse model, which is one of the most common animal models for familial AD. The manuscript highlights the importance of considering the microbiome in study design and aims to lay the groundwork for future studies involving mouse models for AD.

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.

BackgroundThe Down syndrome population has been disproportionately affected by Coronavirus 2019 (COVID-19) in terms of experiencing severe illness and death. Societal efforts to curb the spread of COVID-19 may also have taken a heavy toll on the daily lives of individuals with Down syndrome.Objective/hypothesisThe goal of the study was to understand how the COVID-19 pandemic has altered daily life (including residence, employment, and participation in adult disability day programs) and influenced the mood and behavior of adults with Down syndrome.MethodsBetween September 2020 and February 2021, caregivers of 171 adults with Down syndrome (aged 22-66 years) located across the United States and in the United Kingdom enrolled in the Alzheimer's Biomarker Research Consortium on Down Syndrome (ABC-DS) completed a survey.ResultsThe residence of 17% of individuals was altered, and 89% of those who had been employed stopped working during the pandemic. One-third (33%) of individuals were reported to be more irritable or easily angered, 52% were reported to be more anxious, and 41% were reported to be more sad/depressed/unhappy relative to prepandemic. The majority of changes in mood and behavior were of modest severity.ConclusionsThe COVID-19 pandemic has had widespread effects on the daily life and mood and behavior of adults with Down syndrome. In the short term, caregivers and providers should be prepared to help adults with Down syndrome with changes in daily routines, residence, employment, or adult disability day programs as society shifts away from COVID-19 safety protocols.

Recent reports have suggested that the reactivation of otherwise transcriptionally silent transposable elements (TEs) might induce brain degeneration, either by dysregulating the expression of genes and pathways implicated in cognitive decline and dementia or through the induction of immune-mediated neuroinflammation resulting in the elimination of neural and glial cells. In the work we present here, we test the hypothesis that differentially expressed TEs in blood could be used as biomarkers of cognitive decline and development of AD. To this aim, we used a sample of aging subjects (age > 70) that developed late-onset Alzheimer's disease (LOAD) over a relatively short period of time (12-48 months), for which blood was available before and after their phenoconversion, and a group of cognitive stable subjects as controls. We applied our developed and validated customized pipeline that allows the identification, characterization, and quantification of the differentially expressed (DE) TEs before and after the onset of manifest LOAD, through analyses of RNA-Seq data. We compared the level of DE TEs within more than 600,000 TE-mapping RNA transcripts from 25 individuals, whose specimens we obtained before and after their phenotypic conversion (phenoconversion) to LOAD, and discovered that 1790 TE transcripts showed significant expression differences between these two timepoints (logFC ± 1.5, logCMP > 5.3, nominal p value

IntroductionRepresentation of Mexican Americans in Alzheimer's disease (AD) clinical research has been extremely poor.MethodsData 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.ResultsData 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.DiscussionA 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.

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.HighlightDown 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.

BackgroundAltered plasma levels of sphingolipids, including sphingomyelins (SM), have been found in mouse models of Alzheimer's disease (AD) and in AD patient plasma samples.ObjectiveThis study assesses fourteen plasma SM species in a late-onset AD (LOAD) patient cohort (n = 138).MethodsSpecimens from control, preclinical, and symptomatic subjects were analyzed using targeted mass-spectrometry-based metabolomic methods.ResultsTotal 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.ConclusionWe 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.

BackgroundThe 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.ObjectiveThis 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.MethodsPlasma 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.ResultsIn 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.ConclusionAdvanced 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.

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.

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.

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.

IntroductionPreviously 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).MethodsData 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).ResultsDistinguishing 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.DiscussionProteomic profiles showed excellent detection accuracy for MCI-DS and DS-AD.

IntroductionAdults 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.MethodsWe 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.ResultsApproximately 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.DiscussionThis 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.

IntroductionDisruption 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).MethodsWe 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).ResultsWe 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.DiscussionOur 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.

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.

Alzheimers 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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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 Alzheimers 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 Alzheimers 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.

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.

The complex multifactorial nature of polygenic Alzheimer's disease (AD) presents significant challenges for drug development. AD pathophysiology is progressing in a non-linear dynamic fashion across multiple systems levels - from molecules to organ systems - and through adaptation, to compensation, and decompensation to systems failure. Adaptation and compensation maintain homeostasis: a dynamic equilibrium resulting from the dynamic non-linear interaction between genome, epigenome, and environment. An individual vulnerability to stressors exists on the basis of individual triggers, drivers, and thresholds accounting for the initiation and failure of adaptive and compensatory responses. Consequently, the distinct pattern of AD pathophysiology in space and time must be investigated on the basis of the individual biological makeup. This requires the implementation of systems biology and neurophysiology to facilitate Precision Medicine (PM) and Precision Pharmacology (PP). The regulation of several processes at multiple levels of complexity from gene expression to cellular cycle to tissue repair and system-wide network activation has different time delays (temporal scale) according to the affected systems (spatial scale). The initial failure might originate and occur at every level potentially affecting the whole dynamic interrelated systems within an organism. Unraveling the spatial and temporal dynamics of non-linear pathophysiological mechanisms across the continuum of hierarchical self-organized systems levels and from systems homeostasis to systems failure is key to understand AD. Measuring and, possibly, controlling space- and time-scaled adaptive and compensatory responses occurring during AD will represent a crucial step to achieve the capacity to substantially modify the disease course and progression at the best suitable timepoints, thus counteracting disrupting critical pathophysiological inputs. This approach will provide the conceptual basis for effective disease-modifying pathway-based targeted therapies. PP is based on an exploratory and integrative strategy to complex diseases such as brain proteinopathies including AD, aimed at identifying simultaneous aberrant molecular pathways and predicting their temporal impact on the systems levels. The depiction of pathway-based molecular signatures of complex diseases contributes to the accurate and mechanistic stratification of distinct subcohorts of individuals at the earliest compensatory stage when treatment intervention may reverse, stop, or delay the disease. In addition, individualized drug selection may optimize treatment safety by decreasing risk and amplitude of side effects and adverse reactions. From a methodological point of view, comprehensive "omics"-based biomarkers will guide the exploration of spatio-temporal systems-wide morpho-functional shifts along the continuum of AD pathophysiology, from adaptation to irreversible failure. The Alzheimer Precision Medicine Initiative (APMI) and the APMI cohort program (APMI-CP) have commenced to facilitate a paradigm shift towards effective drug discovery and development in AD.

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

INTRODUCTION: Developing biomarkers that distinguish individuals with Alzheimers 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 individuals probability of correct classification.

Alzheimers disease (AD) is marked by cognitive dysfunction emerging from neuropathological processes impacting brain function. AD affects brain dynamics at the local level, such as changes in the balance of inhibitory and excitatory neuronal populations, as well as long-range changes to the global network. Individual differences in these changes as they relate to behaviour are poorly understood. Here, we use a multi-scale neurophysiological model, The Virtual Brain (TVB), based on empirical multi-modal neuroimaging data, to study how local and global dynamics correlate with individual differences in cognition. In particular, we modeled individual resting-state functional activity of 124 individuals across the behavioural spectrum from healthy aging, to amnesic Mild Cognitive Impairment (MCI), to AD. The model parameters required to accurately simulate empirical functional brain imaging data correlated significantly with cognition, and exceeded the predictive capacity of empirical connectomes.

Background: Predicting the progression of cognitive decline in Alzheimer's disease (AD) is important for treatment selection and patient counseling. Structural MRI markers such as hippocampus or basal forebrain volumes might represent useful instruments for the prediction of cognitive decline. The primary objective was to determine the predictive value of hippocampus and basal forebrain volumes for global and domain specific cognitive decline in AD dementia during cholinergic treatment. Methods: We used MRI and cognitive data from 124 patients with the clinical diagnosis of AD dementia, derived from the ADNI-1 cohort, who were on standard of care cholinesterase inhibitor treatment during a follow-up period between 0.4 and 3.1 years. We used linear mixed effects models with cognitive function as outcome to assess the main effects as well as two-way interactions between baseline volumes and time controlling for age, sex, and total intracranial volume. This model accounts for individual variation in follow-up times. Results: Basal forebrain volume, but not hippocampus volume, was a significant predictor of rates of global cognitive decline. Larger volumes were associated with smaller rates of cognitive decline. Left hippocampus volume had a modest association with rates of episodic memory decline. Baseline performance in global cognition and memory was significantly associated with hippocampus and basal forebrain volumes; in addition, basal forebrain volume was associated with baseline performance in executive function. Conclusions: Our findings indicate that in AD dementia patients, basal forebrain volume may be a useful marker to predict subsequent cognitive decline during cholinergic treatment.

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.

Systems healthcare is a holistic approach to health premised on systems biology and medicine. The approach integrates data from molecules, cells, organs, the individual, families, communities, and the natural and man-made environment. Both extrinsic and intrinsic influences constantly challenge the biological networks associated with wellness. Such influences may dysregulate networks and allow pathobiology to evolve, resulting in early clinical presentation that requires astute assessment and timely intervention for successful mitigation. Herein, we describe the components of relevant biological systems and the nature of progression from at-risk to manifest disease. We illustrate the systems approach by examining two relevant clinical examples: Alzheimer's and cardiovascular diseases. The implications of systems healthcare management are examined through the lens of economics, ethics, policy and the law. Finally, we propose the need to develop new educational paradigms to enhance the training of the health professional in an era of systems medicine.

BackgroundMild cognitive impairment (MCI) has an uncertain etiology and prognosis and may be challenging for clinicians to discuss with patients and families. Amyloid imaging may aid specialists in determining MCI etiology and prognosis, but creates novel challenges related to disease labeling.MethodsWe convened a workgroup to formulate recommendations for clinicians providing care to MCI patients.ResultsClinicians should use the MCI diagnosis to validate patient and family concerns and educate them that the patient's cognitive impairment is not normal for his or her age and education level. The MCI diagnosis should not be used to avoid delivering a diagnosis of dementia. For patients who meet Appropriate Use Criteria after standard-of-care clinical workup, amyloid imaging may position specialists to offer more information about etiology and prognosis. Clinicians must set appropriate expectations, including ensuring that patients and families understand the limitations of amyloid imaging. Communication of negative results should include that patients remain at elevated risk for dementia and that negative scans do not indicate a specific diagnosis or signify brain health. Positive amyloid imaging results should elicit further monitoring and conversations about appropriate advance planning. Clinicians should offer written summaries, including referral to appropriate social services.ConclusionsIn patients with MCI, there is a need to devote considerable time and attention to patient education and shared decision-making. Amyloid imaging may be a tool to aid clinicians. Careful management of patient expectations and communication of scan results will be critical to the appropriate use of amyloid imaging information.

Our study aimed to investigate the short-term effect of combination antiretroviral therapy (cART) on cognitive performance and functional and structural connectivity and their relationship to plasma levels of antiretroviral (ARV) drugs. Seventeen ARV treatment-naïve HIV-infected individuals (baseline mean CD4 cell count, 479 ± 48 cells/mm3) were age matched with 17 HIV-uninfected individuals. All subjects underwent a detailed neurocognitive and functional assessment and magnetic resonance imaging. HIV-infected subjects were scanned before starting cART and 12 weeks after initiation of treatment. Uninfected subjects were assessed once at baseline. Functional connectivity (FC) was assessed within the default mode network while structural connectivity was assessed by voxel-wise analysis using tract-based spatial statistics (TBSS) and probabilistic tractography within the DMN. Tenofovir and emtricitabine blood concentration were measured at week 12 of cART. Prior to cART, HIV-infected individuals had significantly lower cognitive performance than control subjects as measured by the total Z-score from the neuropsychological tests assessing six cognitive domains (p = 0.020). After 12 weeks of cART treatment, there remained only a weak cognitive difference between HIV-infected and HIV-uninfected subjects (p = 0.057). Mean FC was lower in HIV-infected individuals compared with those uninfected (p = 0.008), but FC differences became non-significant after treatment (p = 0.197). There were no differences in DTI metrics between HIV-infected and HIV-uninfected individuals using the TBSS approach and limited evidence of decreased structural connectivity within the DMN in HIV-infected individuals. Tenofovir and emtricitabine plasma concentrations did not correlate with either cognitive performance or imaging metrics.ConclusionsTwelve weeks of cART improves cognitive performance and functional connectivity in ARV treatment-naïve HIV-infected individuals with relatively preserved immune function. Longer periods of observation are necessary to assess whether this effect is maintained.