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The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers.

INTRODUCTION: As knowledge about neurological examination findings in autosomal dominant Alzheimer disease (ADAD) is incomplete, we aimed to determine the frequency and significance of neurological examination findings in ADAD. METHODS: Frequencies of neurological examination findings were compared between symptomatic mutation carriers and non mutation carriers from the Dominantly Inherited Alzheimer Network (DIAN) to define AD neurological examination findings. AD neurological examination findings were analyzed regarding frequency, association with and predictive value regarding cognitive decline, and association with brain atrophy in symptomatic mutation carriers. RESULTS: AD neurological examination findings included abnormal deep tendon reflexes, gait disturbance, pathological cranial nerve examination findings, tremor, abnormal finger to nose and heel to shin testing, and compromised motor strength. The frequency of AD neurological examination findings was 65.1%. Cross-sectionally, mutation carriers with AD neurological examination findings showed a more than two-fold faster cognitive decline and had greater parieto-temporal atrophy, including hippocampal atrophy. Longitudinally, AD neurological examination findings predicted a significantly greater decline over time. DISCUSSION: ADAD features a distinct pattern of neurological examination findings that is useful to estimate prognosis and may inform clinical care and therapeutic trial designs.

INTRODUCTION: As the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others. METHODS: We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation. RESULTS: Three primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors. DISCUSSION: These results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.

One of the potential benefits of using data-independent acquisition (DIA) proteomics protocols is that information not originally targeted by the study may be present and discovered by subsequent analysis. Herein, we reanalyzed DIA data originally recorded for global proteomic analysis to look for isomerized peptides, which occur as a result of spontaneous chemical modifications to long-lived proteins. Examination of a large set of human brain samples revealed a striking relationship between Alzheimer's disease (AD) status and isomerization of aspartic acid in a peptide from tau. Relative to controls, a surprising increase in isomer abundance was found in both autosomal dominant and sporadic AD samples. To explore potential mechanisms that might account for these observations, quantitative analysis of proteins related to isomerization repair and autophagy was performed. Differences consistent with reduced autophagic flux in AD-related samples relative to controls were found for numerous proteins, including most notably p62, a recognized indicator of autophagic inhibition. These results suggest, but do not conclusively demonstrate, that lower autophagic flux may be strongly associated with loss of function in AD brains. This study illustrates that DIA data may contain unforeseen results of interest and may be particularly useful for pilot studies investigating new research directions. In this case, a promising target for future investigations into the therapy and prevention of AD has been identified.

Demonstrating a slowing in the rate of cognitive decline is a common outcome measure in clinical trials in Alzheimer's disease (AD). Selection of cognitive endpoints typically includes modeling candidate outcome measures in the many, richly phenotyped observational cohort studies available. An important part of choosing cognitive endpoints is a consideration of improvements in performance due to repeated cognitive testing (termed "practice effects"). As primary and secondary AD prevention trials are comprised predominantly of cognitively unimpaired participants, practice effects may be substantial and may have considerable impact on detecting cognitive change. The extent to which practice effects in AD prevention trials are similar to those from observational studies and how these potential differences impact trials is unknown. In the current study, we analyzed data from the recently completed DIAN-TU-001 clinical trial (TU) and the associated DIAN-Observational (OBS) study. Results indicated that asymptomatic mutation carriers in the TU exhibited persistent practice effects on several key outcomes spanning the entire trial duration. Critically, these practice related improvements were larger on certain tests in the TU relative to matched participants from the OBS study. Our results suggest that the magnitude of practice effects may not be captured by modeling potential endpoints in observational studies where assessments are typically less frequent and drug expectancy effects are absent. Using alternate instrument forms (represented in our study by computerized tasks) may partly mitigate practice effects in clinical trials but incorporating practice effects as outcomes may also be viable. Thus, investigators must carefully consider practice effects (either by minimizing them or modeling them directly) when designing cognitive endpoint AD prevention trials by utilizing trial data with similar assessment frequencies.

As prevention trials advance with autosomal dominant Alzheimer disease (ADAD) participants, understanding the similarities and differences between ADAD and “sporadic” late-onset AD (LOAD) is critical to determine generalizability of findings between these cohorts. Cognitive trajectories of ADAD mutation carriers (MCs) and autopsy-confirmed LOAD individuals were compared to address this question. Longitudinal rates of change on cognitive measures were compared in ADAD MCs (n = 310) and autopsy-confirmed LOAD participants (n = 163) before and after symptom onset (estimated/observed). LOAD participants declined more rapidly in the presymptomatic (preclinical) period and performed more poorly at symptom onset than ADAD participants on a cognitive composite. After symptom onset, however, the younger ADAD MCs declined more rapidly. The similar but not identical cognitive trajectories (declining but at different rates) for ADAD and LOAD suggest common AD pathologies but with some differences.

Timely and accurate diagnosis of Alzheimer's disease (AD) in clinical practice remains challenging. PET and CSF biomarkers are the most widely used biomarkers to aid diagnosis in clinical research but present limitations for clinical practice (i.e., cost, accessibility). Emerging blood-based markers have the potential to be accurate, cost-effective, and easily accessible for widespread clinical use, and could facilitate timely diagnosis. The EU/US CTAD Task Force met in May 2022 in a virtual meeting to discuss pathways to implementation of blood-based markers in clinical practice. Specifically, the CTAD Task Force assessed: the state-of-art for blood-based markers, the current use of blood-based markers in clinical trials, the potential use of blood-based markers in clinical practice, the current challenges with blood-based markers, and the next steps needed for broader adoption in clinical practice.

In Alzheimer’s disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNFVal66Met) is associated with worse impact of primary AD pathology (beta-amyloid, Aβ) on neurodegeneration and cognitive decline, rendering BDNFVal66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNFVal66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNFVal66Met on resting-state fMRI assessed functional networks. In seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNFVal66Met carriers compared to BDNFVal homozogytes. BDNFVal66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNFVal66Met could be also found in elderly subjects with sporadically occurring Aβ, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNFVal66Met was associated with a stronger effect of more abnormal Aβ-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medial-frontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNFVal66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment.

INTRODUCTION: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. METHODS: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. RESULTS: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. DISCUSSION: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials.

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels

Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer's disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer's disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T1-weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset -9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We

INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge. METHODS: We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid-PET and fluorodeoxyglucose positron-emission tomography (FDG-PET) to predict rates of cognitive decline. Prediction models were trained in autosomal-dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross-validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model-based risk enrichment was estimated. RESULTS: A model combining all biomarker modalities and established in ADAD predicted the 4-year rate of decline in global cognition (R2 = 24%) and memory (R2 = 25%) in sporadic AD. Model-based risk-enrichment reduced the sample size required for detecting simulated intervention effects by 50%-75%. DISCUSSION: Our independently validated machine-learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD.

Introduction: Quantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B–based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design. Methods: Pittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally. Results: Global amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers. Discussion: Although the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers.

Our objective was to assess the reported history of seizures in cognitively asymptomatic mutation carriers for autosomal dominant Alzheimer's disease (ADAD) and the predictive value of seizures for mutation carrier status in cognitively asymptomatic first-degree relatives of ADAD patients. Seizure occurrence in the Dominantly Inherited Alzheimer Network observational study was correlated with mutation carrier status in cognitively asymptomatic subjects. Of 276 cognitively asymptomatic individuals, 11 (4%) had experienced seizures, and nine of these carried an ADAD mutation. Thus, in the Dominantly Inherited Alzheimer Network population, seizure frequency in mutation carriers was significantly higher than in noncarriers (p = 0.04), and the positive predictive value of seizures for the presence of a pathogenic mutation was 81.8%. Among cognitively asymptomatic ADAD family members, the occurrence of seizures increases the a priori risk of 50% mutation-positive status to about 80%. This finding suggests that ADAD mutations increase the risk of seizures.

© 2018 American Neurological Association Objective: Previous studies suggest that the brain-derived neurotrophic factor (BDNF) Val66Met (rs6265) polymorphism may influence symptom onset in Alzheimer's disease (AD). Our recent cross-sectional findings suggest that Met66 may influence clinical expression in dominantly inherited AD (DIAD) through its effects on tau. However, it remains unclear whether carriage of Met66 in DIAD results in faster increases in cerebrospinal fluid (CSF) tau and ptau181, and whether these increases are associated with accelerated brain volume loss and memory decline. Methods: A total of 211 subjects (101 mutation noncarriers, 110 mutation carriers), who were cognitively normal, as defined by a Clinical Dementia Rating global score of 0, completed assessments of cognitive function, neuroimaging, and CSF sampling over 3.5 years as part of the Dominantly Inherited Alzheimer's Network. Results: In mutation carriers, Met66 carriers showed faster memory decline (4×), hippocampal volume loss (16×), and CSF tau and ptau181 increases (6×) than Val66 homozygotes. BDNF did not influence rates of cortical β-amyloid accumulation or change in CSF Aβ42 levels in mutation carriers. In mutation noncarriers, BDNF genotype had no effect on change in cognition, brain volume, cortical β-amyloid accumulation, or change in any CSF measures of tau, ptau181, and CSF Aβ42. Interpretation: As in sporadic AD, the deleterious effects of β-amyloid on cognitive function, brain volume loss, and CSF tau in DIAD mutation carriers are less in Val66 homozygotes. The BDNF Val66Met polymorphism should be considered as a potential moderator of clinical trial outcomes in current treatment and prevention trials in DIAD and sporadic AD. Ann Neurol 2018;84:424–435.

Background: Models of Alzheimer's disease propose a sequence of amyloid β (Aβ) accumulation, hypometabolism, and structural decline that precedes the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. In this study, we aimed to characterise where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal. Methods: Between Jan 1, 2009, and Dec 31, 2015, we analysed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers from families carrying gene mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) enrolled in the Dominantly Inherited Alzheimer's Network. We analysed 11C-Pittsburgh Compound B (11C-PiB) PET, 18F-Fluorodeoxyglucose (18F-FDG) PET, and structural MRI data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years to symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. This study is registered at ClinicalTrials.gov (number NCT00869817) Findings: 11C-PiB PET was available for 346 individuals (162 with longitudinal imaging), 18F-FDG PET was available for 352 individuals (175 with longitudinal imaging), and MRI data were available for 377 individuals (201 with longitudinal imaging). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across th

Introduction White matter hyperintensity (WMH) volume on MRI is increased among presymptomatic individuals with autosomal dominant mutations for Alzheimer’s disease (AD). One potential explanation is that WMH, conventionally considered a marker of cerebrovascular disease, are a reflection of cerebral amyloid angiopathy (CAA) and that increased WMH in this population is a manifestation of this vascular form of primary AD pathology. We examined whether the presence of cerebral microbleeds, a marker of CAA, mediates the relationship between WMH and estimated symptom onset in individuals with and without autosomal dominant mutations for AD. Participants and methods Participants (n = 175, mean age = 41.1 years) included 112 with an AD mutation and 63 first-degree non-carrier controls. We calculated the estimated years from expected symptom onset (EYO) and analyzed baseline MRI data for WMH volume and presence of cerebral microbleeds. Mixed effects regression and tests of mediation were used to examine microbleed and WMH differences between carriers and non-carriers and to test the whether the association between WMH and mutation status is dependent on the presence of microbleeds. Results Mutation carriers were more likely to have microbleeds than non-carriers (p<0.05) and individuals with microbleeds had higher WMH volume than those without (p<0.05). Total WMH volume was increased in mutation carriers compared with non-carriers, up to 20 years prior to EYO, after controlling for microbleed status, as we demonstrated previously. Formal testing of mediation demonstrated that 21% of the association between mutation status and WMH was mediated by presence of microbleeds (p = 0.03) but a significant direct effect of WMH remained (p = 0.02) after controlling for presence of microbleeds. Discussion Although there is some co-dependency between WMH and microbleeds, the observed increases in WMH among mutation carriers does not appear to be fully mediated by this marker of CAA. Th

White matter alterations are present in the majority of patients with Alzheimer's disease type dementia. However, the spatiotemporal pattern of white matter changes preceding dementia symptoms in Alzheimer's disease remains unclear, largely due to the inherent diagnostic uncertainty in the preclinical phase and increased risk of confounding age-related vascular disease and stroke in late-onset Alzheimer's disease. In early-onset autosomal-dominantly inherited Alzheimer's disease, participants are destined to develop dementia, which provides the opportunity to assess brain changes years before the onset of symptoms, and in the absence of ageing-related vascular disease. Here, we assessed mean diffusivity alterations in the white matter in 64 mutation carriers compared to 45 non-carrier family non-carriers. Using tract-based spatial statistics, we mapped the interaction of mutation status by estimated years from symptom onset on mean diffusivity. For major atlas-derived fibre tracts, we determined the earliest time point at which abnormal mean diffusivity changes in the mutation carriers were detectable. Lastly, we assessed the association between mean diffusivity and cerebrospinal fluid biomarkers of amyloid, tau, phosphorylated-tau, and soluble TREM2, i.e. a marker of microglia activity. Results showed a significant interaction of mutations status by estimated years from symptom onset, i.e. a stronger increase of mean diffusivity, within the posterior parietal and medial frontal white matter in mutation carriers compared with non-carriers. The earliest increase of mean diffusivity was observed in the forceps major, forceps minor and long projecting fibres-many connecting default mode network regions-between 5 to 10 years before estimated symptom onset. Higher mean diffusivity in fibre tracts was associated with lower grey matter volume in the tracts' projection zones. Global mean diffusivity was correlated with lower cerebrospinal fluid levels of amyloid-β 1-42 but

Introduction Identifying at what point atrophy rates first change in Alzheimer's disease is important for informing design of presymptomatic trials. Methods Serial T1-weighted magnetic resonance imaging scans of 94 participants (28 noncarriers, 66 carriers) from the Dominantly Inherited Alzheimer Network were used to measure brain, ventricular, and hippocampal atrophy rates. For each structure, nonlinear mixed-effects models estimated the change-points when atrophy rates deviate from normal and the rates of change before and after this point. Results Atrophy increased after the change-point, which occurred 1–1.5 years (assuming a single step change in atrophy rate) or 3–8 years (assuming gradual acceleration of atrophy) before expected symptom onset. At expected symptom onset, estimated atrophy rates were at least 3.6 times than those before the change-point. Discussion Atrophy rates are pathologically increased up to seven years before “expected onset”. During this period, atrophy rates may be useful for inclusion and tracking of disease progression.

Background: Mutations in amyloid precursor protein (APP), presenilin 1 (PSEN1) and presenilin 2 (PSEN2) cause autosomal dominant forms of Alzheimer disease (ADAD). More than 280 pathogenic mutations have been reported in APP, PSEN1, and PSEN2. However, understanding of the basic biological mechanisms that drive the disease are limited. The Dominantly Inherited Alzheimer Network (DIAN) is an international observational study of APP, PSEN1, and PSEN2 mutation carriers with the goal of determining the sequence of changes in presymptomatic mutation carriers who are destined to develop Alzheimer disease. Results: We generated a library of 98 dermal fibroblast lines from 42 ADAD families enrolled in DIAN. We have reprogrammed a subset of the DIAN fibroblast lines into patient-specific induced pluripotent stem cell (iPSC) lines. These cells were thoroughly characterized for pluripotency markers. Conclusions: This library represents a comprehensive resource that can be used for disease modeling and the development of novel therapeutics.

INTRODUCTION: White matter hyperintensity (WMH) volume on MRI is increased among presymptomatic individuals with autosomal dominant mutations for Alzheimer's disease (AD). One potential explanation is that WMH, conventionally considered a marker of cerebrovascular disease, are a reflection of cerebral amyloid angiopathy (CAA) and that increased WMH in this population is a manifestation of this vascular form of primary AD pathology. We examined whether the presence of cerebral microbleeds, a marker of CAA, mediates the relationship between WMH and estimated symptom onset in individuals with and without autosomal dominant mutations for AD. PARTICIPANTS AND METHODS: Participants (n = 175, mean age = 41.1 years) included 112 with an AD mutation and 63 first-degree non-carrier controls. We calculated the estimated years from expected symptom onset (EYO) and analyzed baseline MRI data for WMH volume and presence of cerebral microbleeds. Mixed effects regression and tests of mediation were used to examine microbleed and WMH differences between carriers and non-carriers and to test the whether the association between WMH and mutation status is dependent on the presence of microbleeds. RESULTS: Mutation carriers were more likely to have microbleeds than non-carriers (p<0.05) and individuals with microbleeds had higher WMH volume than those without (p<0.05). Total WMH volume was increased in mutation carriers compared with non-carriers, up to 20 years prior to EYO, after controlling for microbleed status, as we demonstrated previously. Formal testing of mediation demonstrated that 21% of the association between mutation status and WMH was mediated by presence of microbleeds (p = 0.03) but a significant direct effect of WMH remained (p = 0.02) after controlling for presence of microbleeds. DISCUSSION: Although there is some co-dependency between WMH and microbleeds, the observed increases in WMH among mutation carriers does not appear to be fully mediated by this marker of CAA

Patients with Alzheimer's disease vary in their ability to sustain cognitive abilities in the presence of brain pathology. A major open question is which brain mechanisms may support higher reserve capacity, i.e. relatively high cognitive performance at a given level of Alzheimer's pathology. Higher functional MRI-assessed functional connectivity of a hub in the left frontal cortex is a core candidate brain mechanism underlying reserve as it is associated with education (i.e. a protective factor often associated with higher reserve) and attenuated cognitive impairment in prodromal Alzheimer's disease. However, no study has yet assessed whether such hub connectivity of the left frontal cortex supports reserve throughout the evolution of pathological brain changes in Alzheimer's disease, including the presymptomatic stage when cognitive decline is subtle. To address this research gap, we obtained cross-sectional resting state functional MRI in 74 participants with autosomal dominant Alzheimer's disease, 55 controls from the Dominantly Inherited Alzheimer's Network and 75 amyloid-positive elderly participants, as well as 41 amyloid-negative cognitively normal elderly subjects from the German Center of Neurodegenerative Diseases multicentre study on biomarkers in sporadic Alzheimer's disease. For each participant, global left frontal cortex connectivity was computed as the average resting state functional connectivity between the left frontal cortex (seed) and each voxel in the grey matter. As a marker of disease stage, we applied estimated years from symptom onset in autosomal dominantly inherited Alzheimer's disease and cerebrospinal fluid tau levels in sporadic Alzheimer's disease cases. In both autosomal dominant and sporadic Alzheimer's disease patients, higher levels of left frontal cortex connectivity were correlated with greater education. For autosomal dominant Alzheimer's disease, a significant left frontal cortex connectivity × estimated years of onset intera

Progranulin (PGRN) is predominantly expressed by microglia in the brain, and genetic and experimental evidence suggests a critical role in Alzheimer's disease (AD). We asked whether PGRN expression is changed in a disease severity-specific manner in AD We measured PGRN in cerebrospinal fluid (CSF) in two of the best-characterized AD patient cohorts, namely the Dominant Inherited Alzheimer's Disease Network (DIAN) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). In carriers of AD causing dominant mutations, cross-sectionally assessed CSF PGRN increased over the course of the disease and significantly differed from non-carriers 10 years before the expected symptom onset. In late-onset AD, higher CSF PGRN was associated with more advanced disease stages and cognitive impairment. Higher CSF PGRN was associated with higher CSF soluble TREM2 (triggering receptor expressed on myeloid cells 2) only when there was underlying pathology, but not in controls. In conclusion, we demonstrate that, although CSF PGRN is not a diagnostic biomarker for AD, it may together with sTREM2 reflect microglial activation during the disease.

The relationship between body-mass index (BMI) and Alzheimeŕs disease (AD) has been extensively investigated. However, BMI alterations in preclinical individuals with autosomal dominant AD (ADAD) have not yet been investigated. We analyzed cross-sectional data from 230 asymptomatic members of families with ADAD participating in the Dominantly Inherited Alzheimer Network (DIAN) study including 120 preclinical mutation carriers (MCs) and 110 asymptomatic non-carriers (NCs). Differences in BMI and their relation with cerebral amyloid load and episodic memory as a function of estimated years to symptom onset (EYO) were analyzed. Preclinical MCs showed significantly lower BMIs compared to NCs, starting 11.2 years before expected symptom onset. However, the BMI curves begun to diverge already at 17.8 years before expected symptom onset. Lower BMI in preclinical MCs was significantly associated with less years before estimated symptom onset, higher global Aβ brain burden, and with lower delayed total recall scores in the logical memory test. The study provides cross-sectional evidence that weight loss starts one to two decades before expected symptom onset of ADAD. Our findings point toward a link between the pathophysiology of ADAD and disturbance of weight control mechanisms. Longitudinal follow-up studies are warranted to investigate BMI changes over time.

Background Autosomal dominant familial Alzheimer's disease (ADAD) is a rare disorder with non-amnestic neurological symptoms in some clinical presentations. We aimed to compile and compare data from symptomatic participants in the Dominantly Inherited Alzheimer Network observational study (DIAN-OBS) with those reported in the literature to estimate the prevalences of non-amnestic neurological symptoms in participants with ADAD. Methods We prospectively collected data from the DIAN-OBS database, which recruited participants from study centres in the USA, Europe, and Australia, between Feb 29, 2008, and July 1, 2014. We also did a systematic review of publications to extract individual-level clinical data for symptomatic participants with ADAD. We used data for age of onset (from first report of cognitive decline), disease course from onset to death, and the presence of 13 neurological findings that have been reported in association with ADAD. Using multivariable linear regression, we investigated the prevalences of various non-amnestic neurological symptoms and the contributions of age of onset and specific mutation type on symptoms. Findings The DIAN-OBS dataset included 107 individuals with detailed clinical data (forming the DIAN-OBS cohort). Our systematic review yielded 188 publications reporting on 1228 symptomatic individuals, with detailed neurological examination descriptions available for 753 individuals (forming the published data cohort). The most prevalent non-amnestic cognitive manifestations in participants in the DIAN-OBS cohort were those typical of mild to moderate Alzheimer's disease, including visual agnosia (55·1%, 95% CI 45·7–64·6), aphasia (57·9%, 48·6–67·3), and behavioural changes (61·7%, 51·5–70·0). Non-amnestic cognitive manifestations were less prevalent in the published data cohort (eg, visual agnosia [5·6%, 3·9–7·2], aphasia [23·0%, 20·0–26·0], and behavioural changes [31·7%, 28·4–35·1]). Prevalence of non-cognitive neurological manifest

Objective White matter hyperintensities (WMHs) are areas of increased signal on T2-weighted magnetic resonance imaging (MRI) scans that most commonly reflect small vessel cerebrovascular disease. Increased WMH volume is associated with risk and progression of Alzheimer's disease (AD). These observations are typically interpreted as evidence that vascular abnormalities play an additive, independent role contributing to symptom presentation, but not core features of AD. We examined the severity and distribution of WMH in presymptomatic PSEN1, PSEN2, and APP mutation carriers to determine the extent to which WMH manifest in individuals genetically determined to develop AD. Methods The study comprised participants (n = 299; age = 39.03 ± 10.13) from the Dominantly Inherited Alzheimer Network, including 184 (61.5%) with a mutation that results in AD and 115 (38.5%) first-degree relatives who were noncarrier controls. We calculated the estimated years from expected symptom onset (EYO) by subtracting the affected parent's symptom onset age from the participant's age. Baseline MRI data were analyzed for total and regional WMH. Mixed-effects piece-wise linear regression was used to examine WMH differences between carriers and noncarriers with respect to EYO. Results Mutation carriers had greater total WMH volumes, which appeared to increase approximately 6 years before expected symptom onset. Effects were most prominent for the parietal and occipital lobe, which showed divergent effects as early as 22 years before estimated onset. Interpretation Autosomal-dominant AD is associated with increased WMH well before expected symptom onset. The findings suggest the possibility that WMHs are a core feature of AD, a potential therapeutic target, and a factor that should be integrated into pathogenic models of the disease.

Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer's Network (DIAN), an autosomal dominant Alzheimer's disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer's disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted.

The autosomal dominant form of Alzheimer's disease (ADAD) is far less prevalent than late onset Alzheimer's disease (LOAD), but enables well-informed prospective studies, since symptom onset is near certain and age of onset is predictable. Our aim was to discover plasma proteins associated with early AD pathology by investigating plasma protein changes at the asymptomatic and symptomatic stages of ADAD. Eighty-one proteins were compared across asymptomatic mutation carriers (aMC, n = 15), symptomatic mutation carriers (sMC, n = 8) and related noncarriers (NC, n = 12). Proteins were also tested for associations with cognitive measures, brain amyloid deposition and glucose metabolism. Fewer changes were observed at the asymptomatic than symptomatic stage with seven and 16 proteins altered significantly in aMC and sMC, respectively. This included complement components C3, C5, C6, apolipoproteins A-I, A-IV, C-I and M, histidine-rich glycoprotein, heparin cofactor II and attractin, which are involved in inflammation, lipid metabolism and vascular health. Proteins involved in lipid metabolism differed only at the symptomatic stage, whereas changes in inflammation and vascular health were evident at asymptomatic and symptomatic stages. Due to increasing evidence supporting the usefulness of ADAD as a model for LOAD, these proteins warrant further investigation into their potential association with early stages of LOAD.

Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer's Network (DIAN), an autosomal dominant Alzheimer's disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer's disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted.

[This corrects the article DOI: 10.1371/journal.pone.0152082.].

IMPORTANCE: This study assesses factors associated with the most common adverse event following lumbar puncture. OBJECTIVE: To identify factors associated with the risk, onset, and persistence of post-dural puncture headache (PDPH). DESIGN, SETTING, AND PARTICIPANTS: We performed univariate and multivariable analyses of 338 lumbar punctures in the Dominantly Inherited Alzheimer Network observational study using linear mixed models, adjusting for participant-level and family-level random effects. MAIN OUTCOMES AND MEASURES: We directly evaluated associations of 3 post-lumbar puncture outcomes (immediate postprocedural headache, PDPH at 24-hour follow-up, and PDPH receiving a therapeutic blood patch) with participant age and sex, positioning, collection method, needle size, needle insertion site, and cerebrospinal fluid (CSF) volume collected. RESULTS: The incidence of adverse events included 73 immediate postprocedural headaches (21.6%), 59 PDPHs at 24-hour follow-up (17.5%), and 15 PDPHs receiving a therapeutic blood patch (4.4%). Greater volume of CSF collected was associated with increased risk of immediate postprocedural headache, largely owing to a nonlinear increase in risk on collection of volumes above 30 mL (odds ratio, 3.73 for >30 mL and 0.98 for <17 mL). In contrast, collection of higher volumes showed a protective effect in decreasing rates of PDPH at 24-hour follow-up and rates of PDPH receiving a therapeutic blood patch (odds ratio, 0.35 per 10 mL). Although differences in needle size did not reach statistical significance, no participant in the 24G needle group received a therapeutic blood patch compared to 8 of 253 for the larger 22G needles. CONCLUSIONS AND RELEVANCE: Factors that acutely lower CSF pressure (eg, seated positioning or extracting very high volumes of CSF) may be associated with transient post-lumbar puncture headache, without increasing rates of persistent PDPH or therapeutic blood patch. Collection of up to 30 mL of CSF appears to be

INTRODUCTION: Because of its genetic underpinnings and consistent age of onset within families, autosomal dominant Alzheimer's disease (ADAD) provides a unique opportunity to conduct clinical trials of investigational agents as preventative or symptom-delaying treatments. The design of such trials may be complicated by low rates of genetic testing and disclosure among persons at risk of inheriting disease-causing mutations. METHODS: To better understand the attitudes toward genetic testing and clinical trials of persons at risk for ADAD, we surveyed participants in the Dominantly Inherited Alzheimer's Network (DIAN), a multisite longitudinal study of clinical and biomarker outcomes in ADAD that does not require learning genetic status to participate. RESULTS: Eighty participants completed a brief anonymous survey by mail or on-line; 40 % reported knowing if they carried a gene mutation, 15 % did not know but expressed a desire to learn their genetic status, and 45 % did not know and did not desire to know their genetic status. Among participants who knew or wished to know their genetic status, 86 % were interested in participating in a clinical trial. Seventy-two percent of participants who did not wish to learn their genetic status reported that they would change their mind, if learning that they carried a mutation gave them the opportunity to participate in a clinical trial. Nearly all participants responded that they would be interested if an open-label extension were offered. CONCLUSIONS: These results suggest that the availability of clinical trials to prevent ADAD can affect persons' desire to undergo genetic testing and that consideration can be given to performing studies in which such testing is required.

IMPORTANCE: Autosomal dominant Alzheimer disease (ADAD) is caused by rare genetic mutations in 3 specific genes in contrast to late-onset Alzheimer disease (LOAD), which has a more polygenetic risk profile. OBJECTIVE: To assess the similarities and differences in functional connectivity changes owing to ADAD and LOAD. DESIGN, SETTING, AND PARTICIPANTS: We analyzed functional connectivity in multiple brain resting state networks (RSNs) in a cross-sectional cohort of participants with ADAD (n = 79) and LOAD (n = 444), using resting-state functional connectivitymagnetic resonance imaging at multiple international academic sites. MAIN OUTCOMES AND MEASURES: For both types of AD, we quantified and compared functional connectivity changes in RSNs as a function of dementia severity measured by the Clinical Dementia Rating Scale. In ADAD, we qualitatively investigated functional connectivity changes with respect to estimated years from onset of symptoms within 5 RSNs. RESULTS: A decrease in functional connectivity with increasing Clinical Dementia Rating scores were similar for both LOAD and ADAD in multiple RSNs. Ordinal logistic regression models constructed in one type of Alzheimer disease accurately predicted clinical dementia rating scores in the other, further demonstrating the similarity of functional connectivity loss in each disease type. Among participants with ADAD, functional connectivity in multiple RSNs appeared qualitatively lower in asymptomatic mutation carriers near their anticipated age of symptom onset compared with asymptomatic mutation noncarriers. CONCLUSIONS AND RELEVANCE: Resting-state functional connectivity magnetic resonance imaging changes with progressing AD severity are similar between ADAD and LOAD. Resting-state functional connectivitymagnetic resonance imagingmay be a useful end point for LOAD and ADAD therapy trials. Moreover, the disease process of ADAD may be an effective model for the LOAD disease process.

Major imaging biomarkers of Alzheimer's disease include amyloid deposition [imaged with [(11)C]Pittsburgh compound B (PiB) PET], altered glucose metabolism (imaged with [(18)F]fluro-deoxyglucose PET), and structural atrophy (imaged by MRI). Recently we published the initial subset of imaging findings for specific regions in a cohort of individuals with autosomal dominant Alzheimer's disease. We now extend this work to include a larger cohort, whole-brain analyses integrating all three imaging modalities, and longitudinal data to examine regional differences in imaging biomarker dynamics. The anatomical distribution of imaging biomarkers is described in relation to estimated years from symptom onset. Autosomal dominant Alzheimer's disease mutation carrier individuals have elevated PiB levels in nearly every cortical region 15 y before the estimated age of onset. Reduced cortical glucose metabolism and cortical thinning in the medial and lateral parietal lobe appeared 10 and 5 y, respectively, before estimated age of onset. Importantly, however, a divergent pattern was observed subcortically. All subcortical gray-matter regions exhibited elevated PiB uptake, but despite this, only the hippocampus showed reduced glucose metabolism. Similarly, atrophy was not observed in the caudate and pallidum despite marked amyloid accumulation. Finally, before hypometabolism, a hypermetabolic phase was identified for some cortical regions, including the precuneus and posterior cingulate. Additional analyses of individuals in which longitudinal data were available suggested that an accelerated appearance of volumetric declines approximately coincides with the onset of the symptomatic phase of the disease.

OBJECTIVE: To assess regional patterns of gray and white matter atrophy in familial Alzheimer disease (FAD) mutation carriers. METHODS: A total of 192 participants with volumetric T1-weighted MRI, genotyping, and clinical diagnosis were available from the Dominantly Inherited Alzheimer Network. Of these, 69 were presymptomatic mutation carriers, 50 were symptomatic carriers (31 with Clinical Dementia Rating [CDR] = 0.5, 19 with CDR > 0.5), and 73 were noncarriers from the same families. Voxel-based morphometry was used to identify cross-sectional group differences in gray matter and white matter volume. RESULTS: Significant differences in gray matter (p < 0.05, family-wise error-corrected) were observed between noncarriers and mildly symptomatic (CDR = 0.5) carriers in the thalamus and putamen, as well as in the temporal lobe, precuneus, and cingulate gyrus; the same pattern, but with more extensive changes, was seen in those with CDR > 0.5. Significant white matter differences between noncarriers and symptomatic carriers were observed in the cingulum and fornix; these form input and output connections to the medial temporal lobe, cingulate, and precuneus. No differences between noncarriers and presymptomatic carriers survived correction for multiple comparisons, but there was a trend for decreased gray matter in the thalamus for carriers closer to their estimated age at onset. There were no significant increases of gray or white matter in asymptomatic or symptomatic carriers compared to noncarriers. CONCLUSIONS: Atrophy in FAD is observed early, both in areas commonly associated with sporadic Alzheimer disease and also in the putamen and thalamus, 2 regions associated with early amyloid deposition in FAD mutation carriers.