Search

We used a data-driven Bayesian model to automatically identify distinct latent factors of overlapping atrophy patterns from voxelwise structural MRIs of late-onset Alzheimer's disease (AD) dementia patients. Our approach estimated the extent to which multiple distinct atrophy patterns were expressed within each participant rather than assuming that each participant expressed a single atrophy factor. The model revealed a temporal atrophy factor (medial temporal cortex, hippocampus, and amygdala), a subcortical atrophy factor (striatum, thalamus, and cerebellum), and a cortical atrophy factor (frontal, parietal, lateral temporal, and lateral occipital cortices). To explore the influence of each factor in early AD, atrophy factor compositions were inferred in beta-amyloid-positive (Aβ+) mild cognitively impaired (MCI) and cognitively normal (CN) participants. All three factors were associated with memory decline across the entire clinical spectrum, whereas the cortical factor was associated with executive function decline in Aβ+ MCI participants and AD dementia patients. Direct comparison between factors revealed that the temporal factor showed the strongest association with memory, whereas the cortical factor showed the strongest association with executive function. The subcortical factor was associated with the slowest decline for both memory and executive function compared with temporal and cortical factors. These results suggest that distinct patterns of atrophy influence decline across different cognitive domains. Quantification of this heterogeneity may enable the computation of individual-level predictions relevant for disease monitoring and customized therapies. Factor compositions of participants and code used in this article are publicly available for future research.

BackgroundPathogenic mutations in PSEN1 are known to cause familial early-onset Alzheimer's disease (EOAD) but common variants in PSEN1 have not been found to strongly influence late-onset AD (LOAD). The association of rare variants in PSEN1 with LOAD-related endophenotypes has received little attention. In this study, we performed a rare variant association analysis of PSEN1 with quantitative biomarkers of LOAD using whole genome sequencing (WGS) by integrating bioinformatics and imaging informatics.MethodsA WGS data set (N = 815) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort was used in this analysis. 757 non-Hispanic Caucasian participants underwent WGS from a blood sample and high resolution T1-weighted structural MRI at baseline. An automated MRI analysis technique (FreeSurfer) was used to measure cortical thickness and volume of neuroanatomical structures. We assessed imaging and cerebrospinal fluid (CSF) biomarkers as LOAD-related quantitative endophenotypes. Single variant analyses were performed using PLINK and gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O).ResultsA total of 839 rare variants (MAF

ImportanceThe use of anticholinergic (AC) medication is linked to cognitive impairment and an increased risk of dementia. To our knowledge, this is the first study to investigate the association between AC medication use and neuroimaging biomarkers of brain metabolism and atrophy as a proxy for understanding the underlying biology of the clinical effects of AC medications.ObjectiveTo assess the association between AC medication use and cognition, glucose metabolism, and brain atrophy in cognitively normal older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Indiana Memory and Aging Study (IMAS).Design, setting, and participantsThe ADNI and IMAS are longitudinal studies with cognitive, neuroimaging, and other data collected at regular intervals in clinical and academic research settings. For the participants in the ADNI, visits are repeated 3, 6, and 12 months after the baseline visit and then annually. For the participants in the IMAS, visits are repeated every 18 months after the baseline visit (402 cognitively normal older adults in the ADNI and 49 cognitively normal older adults in the IMAS were included in the present analysis). Participants were either taking (hereafter referred to as the AC+ participants [52 from the ADNI and 8 from the IMAS]) or not taking (hereafter referred to as the AC- participants [350 from the ADNI and 41 from the IMAS]) at least 1 medication with medium or high AC activity. Data analysis for this study was performed in November 2015.Main outcomes and measuresCognitive scores, mean fludeoxyglucose F 18 standardized uptake value ratio (participants from the ADNI only), and brain atrophy measures from structural magnetic resonance imaging were compared between AC+ participants and AC- participants after adjusting for potential confounders. The total AC burden score was calculated and was related to target measures. The association of AC use and longitudinal clinical decline (mean [SD] follow-up period, 32.1 [24.7] months [range, 6-108 months]) was examined using Cox regression.ResultsThe 52 AC+ participants (mean [SD] age, 73.3 [6.6] years) from the ADNI showed lower mean scores on Weschler Memory Scale-Revised Logical Memory Immediate Recall (raw mean scores: 13.27 for AC+ participants and 14.16 for AC- participants; P = .04) and the Trail Making Test Part B (raw mean scores: 97.85 seconds for AC+ participants and 82.61 seconds for AC- participants; P = .04) and a lower executive function composite score (raw mean scores: 0.58 for AC+ participants and 0.78 for AC- participants; P = .04) than the 350 AC- participants (mean [SD] age, 73.3 [5.8] years) from the ADNI. Reduced total cortical volume and temporal lobe cortical thickness and greater lateral ventricle and inferior lateral ventricle volumes were seen in the AC+ participants relative to the AC- participants.Conclusions and relevanceThe use of AC medication was associated with increased brain atrophy and dysfunction and clinical decline. Thus, use of AC medication among older adults should likely be discouraged if alternative therapies are available.

ObjectiveTo estimate points along the spectrum of β-amyloid pathology at which rates of change of several measures of neuronal injury and cognitive decline begin to accelerate.MethodsIn 460 patients with mild cognitive impairment (MCI), we estimated the points at which rates of florbetapir PET, fluorodeoxyglucose (FDG) PET, MRI, and cognitive and functional decline begin to accelerate with respect to baseline CSF Aβ42. Points of initial acceleration in rates of decline were estimated using mixed-effects regression.ResultsRates of neuronal injury and cognitive and even functional decline accelerate substantially before the conventional threshold for amyloid positivity, with rates of florbetapir PET and FDG PET accelerating early. Temporal lobe atrophy rates also accelerate prior to the threshold, but not before the acceleration of cognitive and functional decline.ConclusionsA considerable proportion of patients with MCI would not meet inclusion criteria for a trial using the current threshold for amyloid positivity, even though on average, they are experiencing cognitive/functional decline associated with prethreshold levels of CSF Aβ42. Future trials in early Alzheimer disease might consider revising the criteria regarding β-amyloid thresholds to include the range of amyloid associated with the first signs of accelerating rates of decline.

ObjectiveTo examine sex differences in the relationship between clinical symptoms related to Alzheimer disease (AD) (verbal memory deficits) and neurodegeneration (hippocampal volume/intracranial volume ratio [HpVR]) across AD stages.MethodsThe sample included 379 healthy participants, 694 participants with amnestic mild cognitive impairment (aMCI), and 235 participants with AD and dementia from the Alzheimer's Disease Neuroimaging Initiative who completed the Rey Auditory Verbal Learning Test (RAVLT). Cross-sectional analyses were conducted using linear regression to examine the interaction between sex and HpVR on RAVLT across and within diagnostic groups adjusting for age, education, and APOE ε4 status.ResultsAcross groups, there were significant sex × HpVR interactions for immediate and delayed recall (p < 0.01). Women outperformed men among individuals with moderate to larger HpVR, but not among individuals with smaller HpVR. In diagnosis-stratified analyses, the HpVR × sex interaction was significant in the aMCI group, but not in the control or AD dementia groups, for immediate and delayed recall (p < 0.01). Among controls, women outperformed men on both outcomes irrespective of HpVR (p < 0.001). In AD dementia, better RAVLT performance was independently associated with female sex (immediate, p = 0.04) and larger HpVR (delayed, p = 0.001).ConclusionWomen showed an advantage in verbal memory despite evidence of moderate hippocampal atrophy. This advantage may represent a sex-specific form of cognitive reserve delaying verbal memory decline until more advanced disease stages.

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.

Background: There is growing evidence that epigenetic age acceleration may predict late life cognitive decline and dementia, but it is unknown whether this is due to accelerated neurodegeneration or reduction in cognitive resilience. We examined the relationship between epigenetic clocks and domain specific neuropsychological (NP) factor scores, mild cognitive impairment (MCI), Alzheimer's Disease (AD), and all‐cause dementia, before and after accounting for plasma total tau (t‐tau), a marker of neurodegeneration. Method: DNA methylation and plasma t‐tau (Simoa assay; Quanterix) data from 2091 Framingham Heart Study Offspring cohort participants were generated from blood at the same Exam 8 visit (2005‐2008). Three epigenetic clock measures: DunedinPACE, PC PhenoAge, and PC GrimAge were estimated from the DNA methylation data. Longitudinal NP factor scores were previously derived for memory, language, and executive function using confirmatory factor analysis. We tested the association of epigenetic age acceleration with cognitive trajectories using linear mixed effects models and with time to MCI, all‐cause dementia and AD using Cox‐proportional hazard models. Models were run with and without adjustment for plasma t‐tau. All models included APOE ε4‐carrier status, education, smoking, age, and sex as covariates. Epigenetic measures were standardized in all models. Result: At Exam 8, the sample was, on average, 66.3 (SD = 9.0) years of age, 54.8% female, and had 16.4 (SD = 2.7) years of education. DundeinPACE was significantly associated with faster decline in executive function (βtimeXepi_age = ‐0.005, 95% CI:[‐0.009,‐0.002], p = 0.0020), but not with baseline executive function. Older PhenoAge (βepi_age = ‐0.041, 95% CI:[‐0.067,‐0.014], p = 0.0028) and GrimAge (βepi_age = ‐0.042, 95% CI:[‐0.073,‐0.011], p = 0.0084) were significantly associated with worse baseline executive function, but not with rate of decline. Older PhenoAge also was significantly associated with worse baseline memory (βepi_age = ‐0.037, 95% CI:[‐0.061,‐0.012], p = 0.0036). DunedinPACE was significantly associated with time to MCI (HR = 1.20, 95% CI:[1.06,1.35], p = 0.0034), AD (HR = 1.30, 95% CI:[1.07,1.57], p = 0.0068) and all‐cause dementia (HR = 1.30, 95% CI:[1.10,1.53], p = 0.0017). Results remained similar after adjustment for plasma t‐tau. Conclusion: Epigenetic age acceleration may be a marker of cognitive resilience, particularly in executive function. Of the three epigenetic clocks examined, DundedinPACE showed the most robust associations with cognitive resilience, with lower DunedinPACE associated with greater cognitive resilience. [ABSTRACT FROM AUTHOR]

Background: Genome‐wide association studies (GWAS) in Alzheimer's disease (AD) leveraging endophenotypes beyond case/control diagnosis, such as brain amyloid β pathology, have shown promise in identifying novel variants and understanding their potential functional impact. In this study, we leverage two brain amyloid β pathology measurement modalities, PET imaging and neuropathology, to address sample size limitations and to discover novel genetic drivers of disease. Method: We conducted a meta‐analysis on an amyloid PET imaging GWAS (N = 7,036, 35% amyloid positive, 53.67% female, age = 71) and an autopsy GWAS of brain amyloidosis (N = 6,519, 63.08% amyloid positive, 51.34% female, age at death = 83), both adjusted for covariates including age, sex and principal components of genetic ancestry. All participants in both GWAS were unrelated individuals of European descent. We defined amyloid positivity as moderate or frequent neuritic plaques using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) staging scores within each autopsy cohort. A Gaussian mixture model (GMM) was applied to each amyloid PET imaging cohort to identify the cohort and tracer‐specific cut‐offs that differentiate amyloid positive and negative populations. Result: The genome‐wide significant results from the meta‐analysis identified three known AD loci (APOE, CR1, and BIN1) and a novel chromosome 17 locus (rs35635959, intergenic, MAF = 0.27, OR = 1.18, p = 1.47 × 10‐8). The MAGMA gene‐level analysis excluding the APOE region suggests significant associations between rs35635959 and COASY, PLEKHH3, and TUBG2 on chromosome 17, implying the potential roles of these genes on amyloidosis. Functional annotations of rs35635959 leveraging brain eQTL databases indicate its association with differential gene expression of COASY and TUBG2 in AD brains. ROSMAP bulk and single‐nucleus RNAseq analyses link TUBG2 downregulation to the higher amyloid burden and AD diagnosis while suggesting such observations are enriched in excitatory and inhibitory neurons, reaching FDR significance. Conclusion: This study is the most extensive European GWAS of brain amyloidosis, and our findings replicate known AD loci and identify a possible novel locus (index SNP rs35635959) on chromosome 17. Functional annotations of the novel variant indicate TUBG2, implicating in microtubule organization, warrants further assessment. Ongoing efforts aim to validate these novel effects using independent datasets. [ABSTRACT FROM AUTHOR]

Background: The relationship between Alzheimer's disease (AD) pathology and the associated clinical syndrome a patient presents with remains indeterminate. Cognitively‐defined subgroups of AD have revealed distinctions based on relative cognitive impairments, including AD‐Language, where challenges in language are substantial, and AD‐No Domain, where no relative asymmetries across cognitive domains occur. Pathological features of AD have been associated as the primary neuropathology of the logopenic variant of primary progressive aphasia (lvPPA). Hallmark clinical features of lvPPA include relatively spared comprehension in the face of decline in naming and repetition abilities. This work aimed to test the hypothesis that the lvPPA language profile was overrepresented in AD‐Language when compared to AD‐No Domain. Method: Measures of verbal comprehension, confrontation naming, and phrase‐level repetition were obtained from all participants from the Religious Orders Study (ROS), the RUSH Memory and Aging Project (MAP) and the Minority Aging Research Study (MARS) using confirmatory factor analyses. We subsetted the data to include participants belonging to the AD‐Language and AD‐No Domain groups at their initial AD diagnosis visit. We compared patterns of language profiles based on strengths and weaknesses in comprehension, naming, and repetition. Pearson's Chi‐squared tests with Yates continuity correction was used to test if the language patterns were statistically different between the two AD subgroups. Results: We analyzed language performance in 642 participants across AD‐Language (31.8%) and AD‐No Domain (68.2%) groups (Table 1). Thresholds were based on AD‐No Domain and set as the median for each subdomain (comprehension = ‐.101, naming = ‐.957, repetition =.233) to establish whether a score represented a relative strength or weakness in the language profile. Eight patterns of language profiles based on strengths and weaknesses in comprehension, naming, and repetition were formed (Figure 1). The distribution of language patterns differed significantly between AD‐Language and AD‐No Domain (χ2 = 97.6, p <.001). Furthermore, the lvPPA pattern was found more frequently in AD‐Language (χ2 = 28.1, p <.001). Conclusion: Heterogeneity within the AD‐Language spectrum includes a significant proportion that is consistent with the language profile of lvPPA. Relative performance in domains of verbal comprehension, confrontation naming, and phrase‐level repetition varied by AD subgroup. [ABSTRACT FROM AUTHOR]

ObjectiveTo investigate the association between periventricular white mater hyperintensities (PVWMH) and biomarkers of elevated cerebral β-amyloid (Aβ) in the Alzheimer's Disease Neuroimaging Initiative, a large prospective multicenter observational study.MethodsThe burden of frontal, parietal, and occipital PVWMH on 3T fluid-attenuated inversion recovery MRI was evaluated in 698 cognitively normal participants and participants with mild cognitive impairment (MCI) using a novel semiquantitative visual rating scale. Results were correlated with CSF-Aβ, florbetapir-PET, and fluorodeoxyglucose (FDG)-PET.ResultsIncreased burden of parietal, occipital, and frontal PVWMH was associated with elevated cerebral amyloid evidenced by high florbetapir-PET signal (p < 0.01) and low CSF-Aβ (p < 0.01). In logistic regression models, including PVWMH, age, sex, APOE status, vascular risk factors, pulse pressure, vascular secondary prevention medications, education, ethnicity, and race, parietal, occipital, and frontal PVWMH burden was independently associated with high florbetapir-PET uptake (p < 0.05). In a similar logistic regression model, parietal and occipital (p < 0.05) but not frontal (p = 0.05) PVWMH were independently associated with CSF-Aβ. Weaker associations were found between parieto-occipital PVWMH and elevated CSF-tau (p < 0.05) and occipital PVWMH and elevated CSF-phospho-tau (p < 0.05). PVWMH were associated with cerebral hypometabolism on FDG-PET independent of CSF-Aβ levels (p < 0.05). Absolute and consistency of agreement intraclass correlation coefficients were, respectively, 0.83 and 0.83 for frontal, 0.78 and 0.8 for parietal, and 0.45 and 0.75 for occipital PVWMH measurements.ConclusionsIncreased PVWMH were associated with elevated cerebral amyloid independent of potential confounders such as age, APOE genotype, and vascular risk factors. The mechanisms underlying the association between PVWMH and cerebral amyloid remain to be clarified.

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

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.

Observational research shows that higher body mass index (BMI) increases Alzheimer's disease (AD) risk, but it is unclear whether this association is causal. We applied genetic variants that predict BMI in Mendelian randomization analyses, an approach that is not biased by reverse causation or confounding, to evaluate whether higher BMI increases AD risk. We evaluated individual-level data from the AD Genetics Consortium (ADGC: 10,079 AD cases and 9613 controls), the Health and Retirement Study (HRS: 8403 participants with algorithm-predicted dementia status), and published associations from the Genetic and Environmental Risk for AD consortium (GERAD1: 3177 AD cases and 7277 controls). No evidence from individual single-nucleotide polymorphisms or polygenic scores indicated BMI increased AD risk. Mendelian randomization effect estimates per BMI point (95% confidence intervals) were as follows: ADGC, odds ratio (OR) = 0.95 (0.90-1.01); HRS, OR = 1.00 (0.75-1.32); GERAD1, OR = 0.96 (0.87-1.07). One subscore (cellular processes not otherwise specified) unexpectedly predicted lower AD risk.

IntroductionThis study assessed apolipoprotein E (APOE) ε4 carrier status effects on Alzheimer's disease imaging and cerebrospinal fluid (CSF) biomarkers in cognitively normal older adults with significant memory concerns (SMC).MethodsCognitively normal, SMC, and early mild cognitive impairment participants from Alzheimer's Disease Neuroimaging Initiative were divided by APOE ε4 carrier status. Diagnostic and APOE effects were evaluated with emphasis on SMC. Additional analyses in SMC evaluated the effect of the interaction between APOE and [(18)F]Florbetapir amyloid positivity on CSF biomarkers.ResultsSMC ε4+ showed greater amyloid deposition than SMC ε4-, but no hypometabolism or medial temporal lobe (MTL) atrophy. SMC ε4+ showed lower amyloid beta 1-42 and higher tau/p-tau than ε4-, which was most abnormal in APOE ε4+ and cerebral amyloid positive SMC.DiscussionSMC APOE ε4+ show abnormal changes in amyloid and tau biomarkers, but no hypometabolism or MTL neurodegeneration, reflecting the at-risk nature of the SMC group and the importance of APOE in mediating this risk.

BackgroundThe Montreal Cognitive Assessment (MoCA) was developed to enable earlier detection of mild cognitive impairment (MCI) relative to familiar multi-domain tests like the Mini-Mental State Exam (MMSE). Clinicians need to better understand the relationship between MoCA and MMSE scores.MethodsFor this cross-sectional study, we analyzed 219 healthy control (HC), 299 MCI, and 100 Alzheimer's disease (AD) dementia cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 database to evaluate MMSE and MoCA score distributions and select MoCA values to capture early and late MCI cases. Stepwise variable selection in logistic regression evaluated relative value of four test domains for separating MCI from HC. Functional Activities Questionnaire (FAQ) was evaluated as a strategy to separate dementia from MCI. Equi-percentile equating produced a translation grid for MoCA against MMSE scores. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases.ResultsMost dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. Most MCI cases scored ≥ 17 on MoCA (96.3%) and ≥ 24 on MMSE (98.3%). The ceiling effect (28-30 points) for MCI and HC was less using MoCA (18.1%) versus MMSE (71.4%). MoCA and MMSE scores correlated most for dementia (r = 0.86; versus MCI r = 0.60; HC r = 0.43). Equi-percentile equating showed a MoCA score of 18 was equivalent to MMSE of 24. ROC analysis found MoCA ≥ 17 as the cutoff between MCI and dementia that emphasized high sensitivity (92.3%) to capture MCI cases. The core and orientation domains in both tests best distinguished HC from MCI groups, whereas comprehension/executive function and attention/calculation were not helpful. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC.ConclusionsMoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. A cutoff of ≥ 17 on the MoCA may help capture early and late MCI cases; depending on the level of sensitivity desired, ≥ 18 or 19 could be used. Functional assessment can help exclude dementia cases. MoCA scores are translatable to the MMSE to facilitate comparison.

ObjectiveWe investigated the association between apoE protein plasma levels and brain amyloidosis and the effect of the top 10 Alzheimer disease (AD) risk genes on this association.MethodsOur dataset consisted of 18 AD, 52 mild cognitive impairment, and 3 cognitively normal Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) participants with available [(11)C]-Pittsburgh compound B (PiB) and peripheral blood protein data. We used cortical pattern matching to study associations between plasma apoE and cortical PiB binding and the effect of carrier status for the top 10 AD risk genes.ResultsLow plasma apoE was significantly associated with high PiB SUVR, except in the sensorimotor and entorhinal cortex. For BIN1 rs744373, the association was observed only in minor allele carriers. For CD2AP rs9349407 and CR1 rs3818361, the association was preserved only in minor allele noncarriers. We did not find evidence for modulation by CLU, PICALM, ABCA7, BIN1, and MS4A6A.ConclusionsOur data show that BIN1 rs744373, CD2AP rs9349407, and CR1 rs3818361 genotypes modulate the association between apoE protein plasma levels and brain amyloidosis, implying a potential epigenetic/downstream interaction.

Brain amyloid deposition is thought to be a seminal event in Alzheimer's disease. To identify genes influencing Alzheimer's disease pathogenesis, we performed a genome-wide association study of longitudinal change in brain amyloid burden measured by (18)F-florbetapir PET. A novel association with higher rates of amyloid accumulation independent from APOE (apolipoprotein E) ε4 status was identified in IL1RAP (interleukin-1 receptor accessory protein; rs12053868-G; P = 1.38 × 10(-9)) and was validated by deep sequencing. IL1RAP rs12053868-G carriers were more likely to progress from mild cognitive impairment to Alzheimer's disease and exhibited greater longitudinal temporal cortex atrophy on MRI. In independent cohorts rs12053868-G was associated with accelerated cognitive decline and lower cortical (11)C-PBR28 PET signal, a marker of microglial activation. These results suggest a crucial role of activated microglia in limiting amyloid accumulation and nominate the IL-1/IL1RAP pathway as a potential target for modulating this process.

ObjectiveWe studied the biomarker signatures and prognoses of 3 different subtle cognitive impairment (SCI) groups (executive, memory, and multidomain) as well as the subjective memory complaints (SMC) group.MethodsWe studied 522 healthy controls in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cutoffs for executive, memory, and multidomain SCI were defined using participants who remained cognitively normal (CN) for 7 years. CSF Alzheimer disease (AD) biomarkers, composite and region-of-interest (ROI) MRI, and fluorodeoxyglucose-PET measures were compared in these participants.ResultsUsing a stringent cutoff (fifth percentile), 27.6% of the ADNI participants were classified as SCI. Most single ROI or global-based measures were not sensitive to detect differences between groups. Only MRI-SPARE-AD (Spatial Pattern of Abnormalities for Recognition of Early AD), a quantitative MRI pattern-based global index, showed differences between all groups, excluding the executive SCI group. Atrophy patterns differed in memory SCI and SMC. The CN and the SMC groups presented a similar distribution of preclinical dementia stages. Fifty percent of the participants with executive, memory, and multidomain SCI progressed to mild cognitive impairment or dementia at 7, 5, and 2 years, respectively.ConclusionsOur results indicate that (1) the different SCI categories have different clinical prognoses and biomarker signatures, (2) longitudinally followed CN subjects are needed to establish clinical cutoffs, (3) subjects with SMC show a frontal pattern of brain atrophy, and (4) pattern-based analyses outperform commonly used single ROI-based neuroimaging biomarkers and are needed to detect initial stages of cognitive impairment.

IntroductionGenetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans.MethodsLymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated.ResultsADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD.DiscussionNumerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.

IntroductionWe describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1-42), t-tau, and p-tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids.MethodsReview publications authored or coauthored by ADNI Biomarker core faculty and selected non-ADNI studies to deepen the understanding and interpretation of CSF Aβ1-42, t-tau, and p-tau181 data.ResultsCSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non-ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies.DiscussionFurther studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease-modifying therapeutic trials.

IntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) was established in 2004 to facilitate the development of effective treatments for Alzheimer's disease (AD) by validating biomarkers for AD clinical trials.MethodsWe searched for ADNI publications using established methods.ResultsADNI has (1) developed standardized biomarkers for use in clinical trial subject selection and as surrogate outcome measures; (2) standardized protocols for use across multiple centers; (3) initiated worldwide ADNI; (4) inspired initiatives investigating traumatic brain injury and post-traumatic stress disorder in military populations, and depression, respectively, as an AD risk factor; (5) acted as a data-sharing model; (6) generated data used in over 600 publications, leading to the identification of novel AD risk alleles, and an understanding of the relationship between biomarkers and AD progression; and (7) inspired other public-private partnerships developing biomarkers for Parkinson's disease and multiple sclerosis.DiscussionADNI has made myriad impacts in its first decade. A competitive renewal of the project in 2015 would see the use of newly developed tau imaging ligands, and the continued development of recruitment strategies and outcome measures for clinical trials.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

ObjectiveTo examine whether the presence of sleep-disordered breathing (SDB) is associated with an earlier age at mild cognitive impairment (MCI) or Alzheimer disease (AD)-dementia onset in participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We also examined whether continuous positive airway pressure (CPAP) use is associated with delayed onset of cognitive decline.MethodsFrom the ADNI cohort, 3 subsets with progressively stringent criteria were created in a step-wise manner. Age at MCI or AD-dementia onset was the main outcome variable. Analyses were performed separately for each subset in untreated SDB+ vs SDB- and untreated SDB+ vs CPAP+ groups. Chi-square and t tests were performed to examine between-group differences. Survival analyses were performed using the Kaplan-Meier method, compared by the log-rank test, and assessed by multivariate Cox regression adjusting for potential confounders.ResultsSDB+ patients had a younger age at MCI onset in all subsets (MC1: 72.63 vs 83.67; MC2: 72.15 vs 83.45; MC3: 77.40 vs 89.89; p < 0.01). SDB+ patients had a younger age at AD-dementia onset only in our most conservative subset (AC3: 83.46 vs 88.13; p < 0.05). In a combined outcome analysis, SDB+ patients had a younger age at onset to MCI or AD-dementia in all subsets. In subsets 1 and 2, CPAP use delayed the age at MCI onset (CMC1: 72.63 vs 82.10; CMC2: 72.11 vs 82.10; p < 0.01).ConclusionsConsistent with our hypothesis, the presence of SDB was associated with an earlier age at cognitive decline. Our findings in CPAP+ participants suggest that CPAP treatment of SDB may delay progression of cognitive impairment.

ObjectiveThe objective of this study was to test whether effects of β-amyloid (Aβ) pathology on episodic memory were mediated by metabolism and gray matter volume in the early stages of Alzheimer disease.MethodsThis was a prospective cohort study. We measured baseline Aβ (using florbetapir-PET), brain function (using fluorodeoxyglucose-PET), and brain structure (using MRI). A mediation analysis was performed to test whether statistical effects of Aβ positivity on cross-sectional and longitudinal episodic memory were mediated by hypometabolism or regional gray matter volume in cognitively healthy controls (CN, n = 280) and mild cognitive impairment (MCI, n = 463).ResultsLower memory scores were associated with Aβ positivity (CN, mildly; MCI, strongly), smaller gray matter volumes (CN, few regions, including hippocampus; MCI, widespread), and hypometabolism. Smaller volumes and hypometabolism mediated effects of Aβ in MCI but not in CN. The strongest individual regions mediated up to approximately 25%. A combination of brain structure and function mediated up to approximately 40%. In several regions, gray matter atrophy and hypometabolism predicted episodic memory without being associated (at p < 0.05) with Aβ positivity.ConclusionsChanges in brain structure and function appear to be, in part, downstream events from Aβ pathology, ultimately resulting in episodic memory deficits. However, Aβ pathology is also strongly related to memory deficits through mechanisms that are not quantified by these imaging measurements, and episodic memory decline is partly caused by Alzheimer disease-like brain changes independently of Aβ pathology.

We used whole-exome sequencing to identify variants other than APOE associated with the rate of hippocampal atrophy in amnestic mild cognitive impairment. An in-silico predicted missense variant in REST (rs3796529) was found exclusively in subjects with slow hippocampal volume loss and validated using unbiased whole-brain analysis and meta-analysis across 5 independent cohorts. REST is a master regulator of neurogenesis and neuronal differentiation that has not been previously implicated in Alzheimer's disease. These findings nominate REST and its functional pathways as protective and illustrate the potential of combining next-generation sequencing with neuroimaging to discover novel disease mechanisms and potential therapeutic targets.