Alzheimer disease (AD) related cognitive decline occurs at relatively young ages in individuals with Down syndrome (DS, early-mid 50s) and in those with autosomal dominant mutations (ADAD, 40-50s). Both groups show similar patterns of amyloid accumulation. We examined if brain volumes are similarly affected by AD pathology in individuals with DS and ADAD. Data for cognitively stable and declining participants was obtained from the Alzheimer Biomarker Consortium-Down Syndrome (ABC-DS) and the Dominantly Inherited Alzheimer Network (DIAN). Stability/decline was identified based on cognitive testing and interview of individuals and caregivers by trained assessors. Cognitively stable family members without DS/ADAD mutations were recruited as controls from both studies. Participants underwent MRI and amyloid positron emission tomography (PET) scans from which brain volumes and amyloid (centiloids) were derived, respectively. Participants from DIAN had Pittsburgh Compound-B (PIB) scans, ABC-DS had PIB or florbetapir. Nonlinear cross-sectional associations between regional brain volumes and estimated years to onset of cognitive decline (EYO, negative values before onset, positive after) and centiloid were evaluated using generalized additive models while controlling for sex and random effects of family. EYO was set to 52 for all participants with DS and based on parental decline/mutation type for participants with ADAD. EYO for controls was based on the EYO of their family member. Data from 239 participants with DS (47 declining), and 340 participants with ADAD (122 declining), and 263 familial controls were included. Higher EYO and centiloid values were associated with lower brain volumes in almost all regions. At earlier EYOs, individuals with DS typically had smaller regional volumes than ADAD or sibling controls, with volume declining linearly across the EYO range. By contrast, ADAD mutation carriers had similar volumes to non-carriers at early EYOs, with volumes diverging as early as 10 years before decline. Brain volumes and centiloid values were inversely related in ADAD and DSAD. Volume in key cortical regions were similar by the expected year of onset in both groups. ADAD and DSAD demonstrated different temporal patterns of regional neurodegeneration prior to cognitive change despite being similarly affected by early onset amyloid.

INTRODUCTION:Development of Alzheimer's disease (AD) pathology in Down's syndrome (DS) occurs within a compressed timeline compared to sporadic or other genetic forms of AD. METHODS:Plasma glial fibrillary acidic protein (GFAP) and plasma pTau-217 levels were compared by AD pathophysiology (amyloid (A+) and tau (T+) positron emission tomography [PET]) in persons with DS (N = 348) and sibling controls (N = 42). Plasma GFAP, plasma pTau-217, amyloid-PET, and tau-PET levels were compared with regard to estimated years to onset of clinical symptoms (52.5 years old). We evaluated if plasma GFAP mediated the relationship between amyloid PET and plasma pTau-217 or tau PET. RESULTS:Plasma GFAP, a measure of astrogliosis, was elevated in A+/T- and A+/T+ individuals with DS. Plasma pTau-217 was elevated in A+/T+ individuals with DS. GFAP partially mediated the relationship between amyloid-PET and tau-PET (15.3%) and amyloid-PET and plasma pTau-217 (42.1%). DISCUSSION:Astrogliosis is a key component in the advancement of preclinical AD pathophysiology in DS. HIGHLIGHTS:Amyloid may be a necessary precursor for stimulating astrocytes. Astrogliosis may play a key role in modifications to tau phosphorylation. Targeting neuroinflammation may only aid amyloid positive individuals. Alzheimer's disease timecourse is compressed in individuals with Down's syndrome.

BackgroundIn 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.MethodsIn 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.FindingsWe 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.InterpretationAlthough 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.FundingNone.

Background This study examined the effects of human immunodeficiency virus (HIV) on resting state functional connectivity (RSFC) in a large cohort of people with HIV (PWH) and healthy controls without HIV (PWoH). Within PWH analyses focused on the effects of viral suppression and cognitive impairment on RSFC. Methods A total of 316 PWH on stable combination antiretroviral therapy and 209 demographically matched PWoH were scanned at a single institution. Effects of the virus were examined by grouping PWH by detectable (viral load > 20 copies/mL; VLD) and undetectable (VLU) viral loads and as being cognitively impaired (CI) (Global Deficit Score ≥ 0.5) or cognitively normal (CN). Regression analysis, object oriented data analysis, and spring embedded graph models were applied to RSFC measures from 298 established brain regions of interest comprising 13 brain networks to examine group differences. Results No significant RSFC differences were observed between PWH and PWoH. Within PWH, there were no significant differences in RSFC between VLD and VLU subgroups and CI and CN subgroups. Conclusions There were no significant effects of HIV on RSFC in our relatively large cohort of PWH and PWoH. Future studies could increase the sample size and combine with other imaging modalities.

Adults with Down Syndrome (DS) develop Alzheimer disease (AD)-like pathology and dementia as they age. This is attributed to triplication of the amyloid precursor protein gene. Recent work demonstrated that amyloid is elevated in DS and accumulates in a similar topography to autosomal dominant AD (ADAD). Tau accumulation is the second hallmark of AD and may be measured using tau positron emission tomography (PET) imaging. The pattern of tau accumulation remains unknown in DS. In a cross-sectional analysis we evaluated amyloid and tau positron emission tomography (PET) in 124 participants with DS (109 cognitively stable, 8 symptomatic, 7 no consensus), 29 ADAD mutation carriers (26 asymptomatic, 3 symptomatic), and 201 cognitively normal non-mutation carriers (CN). Regional cortical standard uptake value ratios (SUVR) for tau imaging were obtained and compared by cognitive status. Similarly, regional cortical amyloid SUVR were obtained and converted to centiloids. We then compared the magnitude of tau burden as well as spatial spread of tau across groups relative to amyloid burden. Compared to CN, tau PET binding was elevated in participants with (µ DS = 2.12 ± 0.22 SUVR, µ ADAD = 2.52 ± 0.37 SUVR) and without (µ DS = 1.24 ± 0.15 SUVR, µ ADAD = 1.16 ± 0.19 SUVR) cognitive changes. For both groups, tau increased with increasing amyloid (centiloids). In some regions, DS had greater tau burden for a given amyloid level (centiloids) (Figure 1). There was increased spatial distribution of tau throughout the brain for participants with DS compared to CN. In contrast, tau burden was more focal in participants with ADAD with tau primarily elevated in posterior regions (Figure 2). While tau burden was higher with symptomatic disease for both groups, significant differences existed in the overall amount and spatial spread. Tau spread was greatest in participants with DS and more diffuse compared to ADAD. These results indicate a substantial tau burden is present in DS, and suggest not only anti-amyloid but also tau-reducing agents should be considered for treating cognitive decline in adults with DS.

Heterogeneity in progression to Alzheimer's disease (AD) poses challenges for both clinical prognosis and clinical trial implementation. Multiple AD-related subtypes have previously been identified, suggesting differences in receptivity to drug interventions. We identified early differences in preclinical AD biomarkers, assessed patterns for developing preclinical AD across the amyloid-tau-(neurodegeneration) [AT(N)] framework, and considered potential sources of difference by analysing the CSF proteome. Participants (n = 10) enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center completed four or more lumbar punctures. These individuals were cognitively normal at baseline. Cerebrospinal fluid measures of amyloid-β (Aβ)42, phosphorylated tau (pTau181), and neurofilament light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including PET amyloid and tau, and structural MRI, were repeatedly obtained when available. Individuals were staged according to the amyloid-tau-(neurodegeneration) framework. Growth mixture modelling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and Aβ42. Two groups (AD Biomarker Positive and Intermediate AD Biomarker) showed distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were re-classified using only proteomic profiles (AUCAD Biomarker Positive versus AD Biomarker Negative = 0.857, AUCAD Biomarker Positive versus Intermediate AD Biomarkers = 0.525, AUCIntermediate AD Biomarkers versus AD Biomarker Negative = 0.952). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified some individuals who became amyloid positive before the age of 50 years. A second group, Intermediate AD Biomarkers, developed elevated CSF ptau181 significantly before becoming amyloid positive. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing versus other agents) in clinical trials. CSF proteome analysis highlighted additional non-AT(N) biomarkers for potential therapies, including blood-brain barrier-, vascular-, immune-, and neuroinflammatory-related targets.

Abstract Background As people with human immunodeficiency virus (HIV) (PWH) age, it remains unclear whether they are at higher risk for age-related neurodegenerative disorders—for example, Alzheimer disease (AD)—and, if so, how to differentiate HIV-associated neurocognitive impairment from AD. We examined a clinically available blood biomarker test for AD (plasma amyloid-β [Aβ] 42/Aβ40 ratio) in PWH who were cognitively normal (PWH_CN) or cognitively impaired (PWH_CI) and people without HIV (PWoH) who were cognitively normal (PWoH_CN) or had symptomatic AD (PWoH_AD). Methods A total of 66 PWH (age >40 years) (HIV RNA <50 copies/mL) and 195 PWoH provided blood samples, underwent magnetic resonance imaging, and completed a neuropsychological battery or clinical dementia rating scale. Participants were categorized by impairment (PWH_CN, n = 43; PWH_CI, n = 23; PWoH_CN, n = 138; PWoH_AD, n = 57). Plasma Aβ42 and Aβ40 concentrations were obtained using a liquid chromatography–tandem mass spectrometry method to calculate the PrecivityAD amyloid probability score (APS). The APS incorporates age and apolipoprotein E proteotype into a risk score for brain amyloidosis. Plasma Aβ42/Aβ40 ratios and APSs were compared between groups and assessed for relationships with hippocampal volumes or cognition and HIV clinical characteristics (PWH only). Results The plasma Aβ42/Aβ40 ratio was significantly lower, and the APS higher, in PWoH_AD than in other groups. A lower Aβ42/Aβ40 ratio and higher APS was associated with smaller hippocampal volumes for PWoH_AD. The Aβ42/Aβ40 ratio and APS were not associated with cognition or HIV clinical measures for PWH. Conclusions The plasma Aβ42/Aβ40 ratio can serve as a screening tool for AD and may help differentiate effects of HIV from AD within PWH, but larger studies with older PWH are needed.

The plasma amyloid-beta (A beta) 42/A beta 40 ratio, a blood-based biomarker for brain amyloid in Alzheimer disease, is not abnormal in older cognitively normal or cognitively impaired people with human immunodeficiency virus (HIV), compared with similarly aged, cognitively normal people without HIV. Background As people with human immunodeficiency virus (HIV) (PWH) age, it remains unclear whether they are at higher risk for age-related neurodegenerative disorders-for example, Alzheimer disease (AD)-and, if so, how to differentiate HIV-associated neurocognitive impairment from AD. We examined a clinically available blood biomarker test for AD (plasma amyloid-beta [A beta] 42/A beta 40 ratio) in PWH who were cognitively normal (PWH_CN) or cognitively impaired (PWH_CI) and people without HIV (PWoH) who were cognitively normal (PWoH_CN) or had symptomatic AD (PWoH_Ad). Methods A total of 66 PWH (age >40 years) (HIV RNA <50 copies/mL) and 195 PWoH provided blood samples, underwent magnetic resonance imaging, and completed a neuropsychological battery or clinical dementia rating scale. Participants were categorized by impairment (PWH_CN, n = 43; PWH_CI, n = 23; PWoH_CN, n = 138; PWoH_Ad, n = 57). Plasma A beta 42 and A beta 40 concentrations were obtained using a liquid chromatography-tandem mass spectrometry method to calculate the PrecivityAD amyloid probability score (APS). The APS incorporates age and apolipoprotein E proteotype into a risk score for brain amyloidosis. Plasma A beta 42/A beta 40 ratios and APSs were compared between groups and assessed for relationships with hippocampal volumes or cognition and HIV clinical characteristics (PWH only). Results The plasma A beta 42/A beta 40 ratio was significantly lower, and the APS higher, in PWoH_AD than in other groups. A lower A beta 42/A beta 40 ratio and higher APS was associated with smaller hippocampal volumes for PWoH_AD. The A beta 42/A beta 40 ratio and APS were not associated with cognition or HIV clinical measures for PWH. Conclusions The plasma A beta 42/A beta 40 ratio can serve as a screening tool for AD and may help differentiate effects of HIV from AD within PWH, but larger studies with older PWH are needed.

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.

Triplication of the APP allele in Down syndrome (DS) leads to excess amyloid production and Alzheimer’s disease (AD) related cognitive decline. Key biomarkers (amyloid, tau, neurodegeneration) can identify pathological processes that occur before clinical symptoms and more precisely stage adults with DS along the AD continuum. Previous research has used changes in cortical thickness (CT) as an indicator of neurodegeneration in autosomal-dominant AD 1 , but not DS-related AD. It is unclear when and where cortical thinning occurs along the AD continuum in DS and if these differences are associated with increasing AD pathology. Cross-sectional analysis compared DS participants from the Alzheimer Biomarkers Consortium-Down Syndrome (106 amyloid-/cognitively unimpaired, nonclinical, 20% reserved for receiver-operating characteristic, ROC, analyses; 45 amyloid+/cognitively unimpaired, preclinical; 27 amyloid+/cognitively impaired, clinical) who had amyloid positron emission tomography and magnetic resonance imaging (MRI). Amyloid positivity was defined using standardized uptake value ratio (partial volume corrected) cortical mean values (1.42/1.19 for PIB/AV45 2 ) and impairment was based on consensus diagnosis. CT differences between nonclinical and clinical groups were calculated in FreeSurfer v5.3 for multiple thresholds (p<.05/.01/.005/.001/.0005/.0001) using a cluster-wise false discovery rate of .001, corrected across hemispheres, after controlling for age and sex. CT values were extracted for each threshold and used in ROC analyses (nonclinical reserved participants compared against preclinical and preclinical compared against clinical) to identify key cortical regions that best discriminated amyloid positivity and between unimpaired and impaired. Significant decreases in parietal and inferior temporal CT were observed between nonclinical and clinical (Figures 1 and 2). ROC analyses identified regions in the left (threshold .05) and right (threshold .005) hemispheres that best differentiated nonclinical from preclinical. Observed area under the curves (AUCs) of .772 and .830 exceeded those previously reported for autosomal-dominant AD (.547/.540) 1 . Analyses differentiating preclinical from clinical observed AUCs of .786 for left (threshold .0005) and .770 for right (threshold .0005) hemispheres. CT differences primarily within posterior cortical regions differentiated adults with DS by amyloid status and cognitive impairment. CT differences were more diffuse for amyloid positivity but more focal for impairment. 1. Dincer (2020). NeuroImage: Clinical , 28 , 102491. 2. Su (2019). Alzheimer’s Dement, 11 , 180-190.

BACKGROUND As people with HIV (PWH) age, it remains unclear whether they are at higher risk for age-related neurodegenerative disorders, e.g., Alzheimer disease (AD), and if so, how to differentiate HIV-associated neurocognitive impairment from AD. We examined a clinically-available blood biomarker test for AD (plasma Aβ42/Aβ40 ratio), in cognitively-normal (CN) or cognitively-impaired (CI) PWH and people without HIV (PWoH) who were CN or with symptomatic AD. METHODS 66 PWH (age >40 years) (HIV RNA <50 copies/mL) and 195 PWoH provided blood samples, magnetic resonance imaging (MRI), and completed a neuropsychological battery or Clinical Dementia Rating scale (CDR). Participants were categorized by impairment (PWH_CN n = 43; PWH_CI n = 23; PWoH_CN n = 138; PWoH_AD n = 57). Plasma Aβ42 and Aβ40 concentrations were obtained using a liquid chromatography-tandem mass spectrometry method to calculate the PrecivityAD® Amyloid Probability Score (APS). The APS incorporates age and apolipoprotein E proteotype into a risk score for brain amyloidosis. Plasma Aβ42/Aβ40 and APS were compared between groups and assessed for relationships with hippocampal volumes or cognition and HIV clinical characteristics (PWH only). RESULTS The plasma Aβ42/Aβ40 ratio was significantly lower, and APS higher, in PWoH_AD compared to other groups. A lower Aβ42/Aβ40 ratio and higher APS was associated with smaller hippocampal volumes for PWoH_AD. The Aβ42/Aβ40 ratio and APS were not associated with cognition or HIV clinical measures for PWH. CONCLUSIONS The plasma Aβ42/Aβ40 ratio can serve as a screening tool for AD and may help differentiate effects of HIV from AD within PWH, but larger studies with older PWH are needed.

Abstract Introduction Continuous measures of amyloid burden as measured by positron emission tomography (PET) are being used increasingly to stage Alzheimer's disease (AD). This study examined whether cerebrospinal fluid (CSF) and plasma amyloid beta (Aβ)42/Aβ40 could predict continuous values for amyloid PET. Methods CSF Aβ42 and Aβ40 were measured with automated immunoassays. Plasma Aβ42 and Aβ40 were measured with an immunoprecipitation–mass spectrometry assay. Amyloid PET was performed with Pittsburgh compound B (PiB). The continuous relationships of CSF and plasma Aβ42/Aβ40 with amyloid PET burden were modeled. Results Most participants were cognitively normal (427 of 491 [87%]) and the mean age was 69.0 ± 8.8 years. CSF Aβ42/Aβ40 predicted amyloid PET burden until a relatively high level of amyloid accumulation (69.8 Centiloids), whereas plasma Aβ42/Aβ40 predicted amyloid PET burden until a lower level (33.4 Centiloids). Discussion CSF Aβ42/Aβ40 predicts the continuous level of amyloid plaque burden over a wider range than plasma Aβ42/Aβ40 and may be useful in AD staging. Highlights Cerebrospinal fluid (CSF) amyloid beta (Aβ)42/Aβ40 predicts continuous amyloid positron emission tomography (PET) values up to a relatively high burden. Plasma Aβ42/Aβ40 is a comparatively dichotomous measure of brain amyloidosis. Models can predict regional amyloid PET burden based on CSF Aβ42/Aβ40. CSF Aβ42/Aβ40 may be useful in staging AD.

Introduction:Health disparities arise from biological-environmental interactions. Neuroimaging cohorts are reaching sufficiently large sample sizes such that analyses could evaluate how the environment affects the brain. We present a practical guide for applying geospatial methods to a neuroimaging cohort. Methods:We estimated brain age gap (BAG) from structural magnetic resonance imaging (MRI) from 239 city-dwelling participants in St. Louis, Missouri. We compared these participants to population-level estimates from the American Community Survey (ACS). We used geospatial analysis to identify neighborhoods associated with patterns of altered brain structure. We also evaluated the relationship between Area Deprivation Index (ADI) and BAG. Results:We identify areas in St. Louis, Missouri that were significantly associated with higher BAG from a spatially representative cohort. We provide replication code. Conclusion:We observe a relationship between neighborhoods and brain health, which suggests that neighborhood-based interventions could be appropriate. We encourage other studies to geocode participant information to evaluate biological-environmental interaction.

Given the triplication of chromosome 21 and the location of the amyloid precursor protein gene on chromosome 21, almost all adults with Down syndrome (DS) develop Alzheimer disease (AD)-like pathology and dementia during their lifetime. Comparing amyloid accumulation in DS to autosomal dominant AD (ADAD), another genetic form of AD, may improve our understanding of early AD pathology development. We assessed amyloid positron emission tomography (PET) imaging in 192 participants with DS and 33 sibling controls from the Alzheimer’s Biomarker Consortium-Down Syndrome (ABC-DS) and 265 mutation-carriers (MC) and 169 familial controls from the Dominantly Inherited Alzheimer Network (DIAN) ( Table 1 ). We calculated regional standard uptake value ratios (SUVR) using a cerebellar cortex reference region and converted global amyloid burden SUVR to centiloids. We compared amyloid PET by cognitive status and estimated-years-to-symptom-onset (EYO). EYO was calculated for DIAN participants by subtracting their age from parental age of symptom onset and for ABC-DS participants by subtracting their age from 50.2 years, a published average age of symptom onset in a large sample of individuals with DS (Fortea et al., 2020). In a subset of participants, we assessed the relationship between amyloid PET and CSF Aβ42/40. The relationship between CSF Aβ42/40 and amyloid PET was similar in DS and MC participants ( Figure 1 ). We did not observe significant differences between MC and DS grouped by cognitive status ( Figure 2 ). However, when assessed over EYO, global amyloid burden was significantly elevated in MC at EYO ≥ -23 but was not elevated in DS until EYO ≥ -15 ( Figure 3 ). We observed early cortical and subcortical amyloid PET increases in both groups, but we also measured some regional differences in amyloid PET changes between MC and DS, specifically in the medial occipital region ( Figure 4 and 5 ). These results demonstrate similarities in the relationship between amyloid biomarkers and the levels of amyloid accumulation in ADAD and DS. However, we also observed a 5-10 year delay and some regional differences in amyloid accumulation in DS. This is important for future clinical trials to consider when recruiting participants and determining treatment efficacy.

BACKGROUND:With implementation of combination antiretroviral therapy (cART), changes to brain integrity in people with HIV (PWH) are subtle compared to those observed in the pre-cART era. T1-weighted/T2-weighted (T1w/T2w) ratio has been proposed as a measure of cortical myelin. This study examines T1w/T2w values between virologically controlled PWH and persons without HIV (PWoH).METHODS:Virologically well-controlled PWH (n = 164) and PWoH (n = 120) were compared on global and regional T1w/T2w values. T1w/T2w values were associated with HIV disease variables (nadir and current CD4 T-cell count, and CNS penetration effectiveness of cART regimen) in PWH, and as a function of age for both PWoH and PWH.RESULTS:PWH had reduced global and regional T1w/T2w values compared to PWoH in the posterior cingulate cortex, caudal anterior cingulate cortex, and insula. T1w/T2w values did not correlate with HIV variables except for a negative relationship with CNS penetration effectiveness. Greater cardiovascular disease risk and older age were associated with lower T1w/T2w values only for PWH.CONCLUSIONS:T1w/T2w values obtained from commonly acquired MRI protocols differentiates virologically well-controlled PWH from PWoH. Changes in T1w/T2w ratio do not correlate with typical HIV measures. Future studies are needed to determine the biological mechanisms underlying this measure.

Background: Heterogeneity in progression to AD poses challenges for both clinical prognosis and clinical trial implementation. In the absence of a well-defined understanding of future disease trajectory, participants may receive unnecessary treatment or true effects of pharmacological intervention may be obscured. We identified early differences in preclinical Alzheimer Disease (AD) biomarkers, assessed patterns for developing preclinical AD across the Amyloid-Tau-(Neurodegeneration) (AT(N)) framework, and considered potential sources of difference by analyzing the CSF proteome.Methods: 108 participants enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center (ADRC) who completed four or more lumbar punctures and were cognitively normal at baseline were included. Cerebrospinal fluid (CSF) measures of Aβ42, pTau 181 , and Neurofilament Light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including positron emission tomography (PET) amyloid and tau and structural magnetic resonance imaging (MRI) were repeatedly obtained when available. This allowed for staging individuals according to the AT(N) framework.Results and Conclusion: Growth mixture modeling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau 181 and CSF Aβ42. Two groups (AD Biomarker Positive and AD Biomarker Intermediate) had distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were successfully re-classified using only proteomic profiles (AUC AD Biomarker Positive vs AD Biomarker Negatives = 0.970, AUC AD Biomarker Positive vs. Intermediate AD Biomarkers = 0.750, AUC Intermediate AD Biomarkers vs. AD Biomarker Negative = 0.698). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified individuals who became AD Biomarker Positive before age 50. A second group, AD Biomarker Intermediate, developed elevated CSF ptau 181 in their mid-60’s before becoming amyloid positive in their mid-70’s. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing vs. other agents) in clinical trials. CSF proteome analysis highlighted additional potential opportunities for non-AT(N) focused therapies, including blood brain barrier-, liver-, and neuroinflammatory-related targets.

Background: Combination antiretroviral therapy (cART) has allowed for viral load (VL) suppression and increased life expectancy for persons with HIV (PWH). Altered brain integrity, measured by neuropsychological (NP) performance and neuroimaging, is still prevalent among virally suppressed PWH. Age-related conditions such as cardiovascular disease may also affect brain integrity. This study investigated the effects of cardiovascular risk, VL, and HIV serostatus on cerebral blood flow (CBF), brain volumetrics, and cognitive function in PWH and persons without HIV (PWoH). Methods: Ten-year cardiovascular risk, using the Framingham Heart Study criteria, was calculated in PWH (n = 164) on cART with undetectable (≤20 copies/mL; n = 134) or detectable (>20 copies/mL; n = 30) VL and PWoH (n = 66). The effects of cardiovascular risk on brain integrity (CBF, volume, and cognition) were compared for PWH (undetectable and detectable VL) and PWoH. Results: PWH had smaller brain volumes and worse NP scores than PWoH. PWH with detectable and undetectable VL had similar brain integrity measures. Higher cardiovascular risk was associated with smaller volumes and lower CBF in multiple brain regions for PWH and PWoH. Significant interactions between HIV serostatus and cardiovascular risk on brain volumes were observed in frontal, orbitofrontal, and motor regions. Cardiovascular risk was not associated with cognition for PWH or PWoH. Conclusions: Neuroimaging, but not cognitive measures, was associated with elevated cardiovascular risk. HIV serostatus was associated with diminished brain volumes and worse cognition while CBF remained unchanged, reflecting potential protective effects of cART. Neuroimaging measures of structure (volume) and function (CBF) may identify contributions of comorbidities, but future longitudinal studies are needed.

BACKGROUND:The relationship between HIV infection, the functional organization of the brain, cognitive impairment, and aging remains poorly understood. Understanding disease progression over the life span is vital for the care of people living with HIV (PLWH).SETTING:Virologically suppressed PLWH (n = 297) on combination antiretroviral therapy and 1509 HIV-uninfected healthy controls were evaluated. PLWH were further classified as cognitively normal (CN) or cognitively impaired (CI) based on neuropsychological testing.METHODS:Feature selection identified resting-state networks (RSNs) that predicted HIV status and cognitive status within specific age bins (younger than 35 years, 35-55 years, and older than 55 years). Deep learning models generated voxelwise maps of RSNs to identify regional differences.RESULTS:Salience (SAL) and parietal memory networks (PMNs) differentiated individuals by HIV status. When comparing controls with PLWH CN, the PMN and SAL had the strongest predictive strength across all ages. When comparing controls with PLWH CI, the SAL, PMN, and frontal parietal network (FPN) were the best predictors. When comparing PLWH CN with PLWH CI, the SAL, FPN, basal ganglia, and ventral attention were the strongest predictors. Only minor variability in predictive strength was observed with aging. Anatomically, differences in RSN topology occurred primarily in the dorsal and rostral lateral prefrontal cortex, cingulate, and caudate.CONCLUSION:Machine learning identified RSNs that classified individuals by HIV status and cognitive status. The PMN and SAL were sensitive for discriminating HIV status, with involvement of FPN occurring with cognitive impairment. Minor differences in RSN predictive strength were observed by age. These results suggest that specific RSNs are affected by HIV, aging, and HIV-associated cognitive impairment.

Sleep monitoring may provide markers for future Alzheimer's disease; however, the relationship between sleep and cognitive function in preclinical and early symptomatic Alzheimer's disease is not well understood. Multiple studies have associated short and long sleep times with future cognitive impairment. Since sleep and the risk of Alzheimer's disease change with age, a greater understanding of how the relationship between sleep and cognition changes over time is needed. In this study, we hypothesized that longitudinal changes in cognitive function will have a non-linear relationship with total sleep time, time spent in non-REM and REM sleep, sleep efficiency and non-REM slow wave activity. To test this hypothesis, we monitored sleep-wake activity over 4-6 nights in 100 participants who underwent standardized cognitive testing longitudinally, APOE genotyping, and measurement of Alzheimer's disease biomarkers, total tau and amyloid-β42 in the CSF. To assess cognitive function, individuals completed a neuropsychological testing battery at each clinical visit that included the Free and Cued Selective Reminding test, the Logical Memory Delayed Recall assessment, the Digit Symbol Substitution test and the Mini-Mental State Examination. Performance on each of these four tests was Z-scored within the cohort and averaged to calculate a preclinical Alzheimer cognitive composite score. We estimated the effect of cross-sectional sleep parameters on longitudinal cognitive performance using generalized additive mixed effects models. Generalized additive models allow for non-parametric and non-linear model fitting and are simply generalized linear mixed effects models; however, the linear predictors are not constant values but rather a sum of spline fits. We found that longitudinal changes in cognitive function measured by the cognitive composite decreased at low and high values of total sleep time (P < 0.001), time in non-REM (P < 0.001) and REM sleep (P < 0.001), sleep efficiency (P < 0.01) and <1 Hz and 1-4.5 Hz non-REM slow wave activity (P < 0.001) even after adjusting for age, CSF total tau/amyloid-β42 ratio, APOE ε4 carrier status, years of education and sex. Cognitive function was stable over time within a middle range of total sleep time, time in non-REM and REM sleep and <1 Hz slow wave activity, suggesting that certain levels of sleep are important for maintaining cognitive function. Although longitudinal and interventional studies are needed, diagnosing and treating sleep disturbances to optimize sleep time and slow wave activity may have a stabilizing effect on cognition in preclinical or early symptomatic Alzheimer's disease.

Objective To evaluate temporal correlations between CSF and neuroimaging (PET and MRI) measures of amyloid, tau, and neurodegeneration in relation to Alzheimer disease (AD) progression. Methods A total of 371 cognitively unimpaired and impaired participants enrolled in longitudinal studies of AD had both CSF (β-amyloid [Aβ]42, phosphorylated tau181, total tau, and neurofilament light chain) and neuroimaging (Pittsburgh compound B [PiB] PET, flortaucipir PET, and structural MRI) measures. The pairwise time interval between CSF and neuroimaging measures was binned into 2-year periods. Spearman correlations identified the time bin when CSF and neuroimaging measures most strongly correlated. CSF and neuroimaging measures were then binarized as biomarker-positive or biomarker-negative using Gaussian mixture modeling. Cohen kappa coefficient identified the time bin when CSF measures best agreed with corresponding neuroimaging measures when determining amyloid, tau, and neurodegeneration biomarker positivity. Results CSF Aβ42 and PiB PET showed maximal correlation when collected within 6 years of each other (R ≈ −0.5). CSF phosphorylated tau181 and flortaucipir PET showed maximal correlation when CSF was collected 4 to 8 years prior to PET (R ≈ 0.4). CSF neurofilament light chain and cortical thickness showed low correlation, regardless of time interval (Ravg ≈ −0.3). Similarly, CSF total tau and cortical thickness had low correlation, regardless of time interval (Ravg < −0.2). Conclusions CSF Aβ42 and PiB PET best agree when acquired in close temporal proximity, whereas CSF phosphorylated tau precedes flortaucipir PET by 4 to 8 years. CSF and neuroimaging measures of neurodegeneration have low correspondence and are not interchangeable at any time interval.