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Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.

INTRODUCTION: Well-chosen biomarkers have the potential to increase the efficiency of clinical trials and drug discovery and should show good precision as well as clinical validity. METHODS: We suggest measures that operationalize these criteria and describe a general approach that can be used for inference-based comparisons of biomarker performance. The methods are applied to measures obtained from structural magnetic resonance imaging (MRI) from individuals with mild dementia (n = 70) or mild cognitive impairment (MCI; n = 303) enrolled in the Alzheimers Disease Neuroimaging Initiative. RESULTS: Ventricular volume and hippocampal volume showed the best precision in detecting change over time in both individuals with MCI and with dementia. Differences in clinical validity varied by group. DISCUSSION: The methodology presented provides a standardized framework for comparison of biomarkers across modalities and across different methods used to generate similar measures and will help in the search for the most promising biomarkers. HIGHLIGHTS: A framework for comparison of biomarkers on pre-defined criteria is presented. Criteria for comparison include precision in capturing change and clinical validity. Ventricular volume has high precision in change for both dementia and mild cognitive impairment (MCI) trials. Imaging measures performance in clinical validity varies more for dementia than for MCI.

IntroductionAlzheimer's disease (AD) pathology is defined by β-amyloid (Aβ) plaques and neurofibrillary tau, but Lewy bodies (LBs; ?-synuclein aggregates) are a common co-pathology for which effective biomarkers are needed.MethodsA validated α-synuclein Seed Amplification Assay (SAA) was used on recent cerebrospinal fluid (CSF) samples from 1638 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, 78 with LB-pathology confirmation at autopsy. We compared SAA outcomes with neuropathology, Aβ and tau biomarkers, risk-factors, genetics, and cognitive trajectories.ResultsSAA showed 79% sensitivity and 97% specificity for LB pathology, with superior performance in identifying neocortical (100%) compared to limbic (57%) and amygdala-predominant (60%) LB-pathology. SAA+ rate was 22%, increasing with disease stage and age. Higher Aβ burden but lower CSF p-tau181 associated with higher SAA+ rates, especially in dementia. SAA+ affected cognitive impairment in MCI and Early-AD who were already AD biomarker positive.DiscussionSAA is a sensitive, specific marker for LB-pathology. Its increase in prevalence with age and AD stages, and its association with AD biomarkers, highlights the clinical importance of α-synuclein co-pathology in understanding AD's nature and progression.HighlightsSAA shows 79% sensitivity, 97% specificity for LB-pathology detection in AD. SAA positivity prevalence increases with disease stage and age. Higher Aβ burden, lower CSF p-tau181 linked with higher SAA+ rates in dementia. SAA+ impacts cognitive impairment in early disease stages. Study underpins need for wider LB-pathology screening in AD treatment.

IntroductionAbnormal amyloid-beta (Aβ) and tau deposition define Alzheimer's Disease (AD), but non-elevated tau is relatively frequent in patients on the AD pathway.MethodsWe examined characteristics and regional patterns of 397 Aβ+ unimpaired and impaired individuals with low tau (A+T-) in relation to their higher tau counterparts (A+T+).ResultsSeventy-one percent of Aβ+ unimpaired and 42% of impaired Aβ+ individuals were categorized as A+T- based on global tau. In impaired individuals only, A+T- status was associated with older age, male sex, and greater cardiovascular risk. α-synuclein was linked to poorer cognition, particularly when tau was low. Tau burden was most frequently elevated in a common set of temporal regions regardless of T+/T- status.DiscussionLow tau is relatively common in patients on the AD pathway and is linked to comorbidities that contribute to impairment. These findings have implications for the selection of individuals for Aβ- and tau-modifying therapies.

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains problematic because it requires a large-scale, voxel-to-voxel correlation between PET and (immuno) histological signals. Large dimensionality of whole human brains, tissue deformation impacting co-registration, and computing requirements to process terabytes of information preclude proper validation. We developed a computational pipeline to identify and segment particles of interest in billion-pixel digital pathology images to generate quantitative, 3D density maps. The proposed convolutional neural network for immunohistochemistry samples, IHCNet, is at the pipeline's core. We have successfully processed and immunostained over 500 slides from two whole human brains with three phospho-tau antibodies (AT100, AT8, and MC1), spanning several terabytes of images. Our artificial neural network estimated tau inclusion from brain images, which performs with ROC AUC of 0.87, 0.85, and 0.91 for AT100, AT8, and MC1, respectively. Introspection studies further assessed the ability of our trained model to learn tau-related features. We present an end-to-end pipeline to create terabytes-large 3D tau inclusion density maps co-registered to MRI as a means to facilitate validation of PET tracers.

Alzheimer's disease (AD) is associated with reduced temporo-parietal cerebral blood flow (CBF). However, a substantial variability in CBF across the clinical spectrum of AD has been reported, possibly due to differences in primary AD pathologies. Here, we assessed CBF (ASL-MRI), tau (AV1451-PET) and amyloid (AV45/FBB-PET) in 156 subjects across the AD continuum. Using mixed-effect regression analyses, we assessed the local associations between amyloid-PET, tau-PET and CBF in a hypothesis-driven way focusing on each pathology's predilection areas. The contribution of Apolipoprotein E (APOE) genotype, and MRI markers of small vessel disease (SVD) to alterations in CBF were assessed as well. Tau-PET was associated with lower CBF in the entorhinal cortex, independent of Aβ. Amyloid-PET was associated with lower CBF in temporo-parietal regions. No associations between MRI markers of SVD and CBF were observed. These results provide evidence that in addition to Aβ, pathologic tau is a major correlate of CBF in early Braak stages, independent of Aβ, APOE genotype and SVD markers.

ObjectiveTo evaluate the association between changes in functional disability and suicide ideation among older adults following psychotherapy for depression.MethodsSixty-five participants (65-91 years old, 72% White, and 66% female) with depression completed 12 sessions of problem solving therapy (PST) and completed measures of disability (WHO Disability Assessment Schedule 2.0) and suicide ideation (Geriatric Suicide Ideation Scale [GSIS]) at baseline and post-treatment.ResultsHierarchical linear regressions found that reductions in functional disability were associated with overall reductions in suicide ideation on the GSIS (F[4,60] = 4.06, p < 0.01), particularly with the Loss of Worth GSIS subscale (F[4,60] = 7.86, p < 0.001, ΔR2 = 0.140).ConclusionsResults suggest decreased functional disability following depression treatment is associated with decreased suicide ideation, especially thoughts regarding loss of worth. These results highlight the potential for treatments that reduce functional disability (e.g., PST) to reduce risk of suicide among older adults.

To improve understanding of Alzheimer's disease, large observational studies are needed to increase power for more nuanced analyses. Combining data across existing observational studies represents one solution. However, the disparity of such datasets makes this a non-trivial task. Here, a machine learning approach was applied to impute longitudinal neuropsychological test scores across two observational studies, namely the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) providing an overall harmonised dataset. MissForest, a machine learning algorithm, capitalises on the underlying structure and relationships of data to impute test scores not measured in one study aligning it to the other study. Results demonstrated that simulated missing values from one dataset could be accurately imputed, and that imputation of actual missing data in one dataset showed comparable discrimination (p

BackgroundCognitive impairment (CI) is a key feature of late life depression (LLD), but the contribution of underlying neurodegenerative pathology remains unclear.ObjectiveTo evaluate cognitive dysfunction in LLD relative to a sample of nondepressed (ND) older adults with matched levels of memory impairment and amyloid-β (Aβ) burden.MethodsParticipants included 120 LLD and 240 ND older adults matched on age, education, sex, Mini-Mental State Exam, mild cognitive impairment diagnosis, and PET Aβ burden.ResultsLLD showed higher rates of impairment relative to ND with 54.6% of the LLD sample demonstrating impairment in at least one cognitive domain compared to 42.9% of controls (H = 7.13, p = 0.008). LLD had poorer performance and higher rates of impairment on Rey Auditory Verbal Learning Test learning and memory compared to controls. In the overall sample, Aβ positivity was associated with worse performance on Logical Memory I (p = 0.044), Logical Memory II (p = 0.011), and Trail Making Test -B (p = 0.032), and APOEɛ4 genotype was associated with worse performance on Logical Memory I (p = 0.022); these relationships did not differ between LLD and ND.ConclusionLLD showed higher rates of CI driven by focal deficits in verbal learning and memory. Alzheimer's disease (AD) biomarkers were associated with worse performance on timed set-shifting and story learning and memory, and these relationships were not impacted by depression status. These findings suggest that AD may account for a portion of previously reported multi-domain CI in LLD and highlight the potential for AD to confound studies of cognition in LLD.

ObjectiveReduction in glucocerebrosidase (GCase; encoded by GBA) enzymatic activity has been linked to Parkinson's disease (PD). Here, we correlated GCase activity and PD phenotype in the Parkinson's Progression Markers Initiative (PPMI) cohort.MethodsWe measured GCase activity in dried blood spots from 1559 samples of participants in the inception PPMI cohort, collected in four annual visits (from baseline visit to Year-3). Participants (PD, n = 392; controls, n = 175) were fully sequenced for GBA variants by means of genome-wide genotyping arrays, whole-exome sequencing, whole-genome sequencing, Sanger sequencing, and RNA-sequencing.ResultsFifty-two PD participants (13.4%) and 13 (7.4%) controls carried a GBA variant. GBA status was strongly associated with GCase activity. Among noncarriers, GCase activity was similar between PD and controls. Among GBA p.E326K carriers (PD, n = 20; controls, n = 5), activity was significantly lower in PD carriers than control carriers (9.53 µmol/L/h vs. 11.68 µmol/L/h, P = 0.035). Glucocerebrosidase activity was moderately (r = 0.45) associated with white blood cell (WBC) count. Next, we divided the noncarriers with PD to tertiles based on WBC count-corrected enzymatic activity. Members of the lower tertile had higher MDS-Unified Parkinson's Disease Rating Scale motor score in the "off" medication examination at year-III exam. Longitudinal analyses demonstrated slight reduction of activity in samples collected earlier on in the study, likely because of longer storage time.InterpretationGCase activity is associated with GBA genotype, WBC count, and among p.E326K variant carriers, with PD status. Reduced activity may also be associated with worse phenotype but longer follow up is required to confirm this observation.

BackgroundThe Parkinson's Progression Markers Initiative (PPMI) is an ongoing observational, longitudinal cohort study of participants with Parkinson's disease, healthy controls, and carriers of the most common Parkinson's disease-related genetic mutations, which aims to define biomarkers of Parkinson's disease diagnosis and progression. All participants are assessed annually with a battery of motor and non-motor scales, 123-I Ioflupane dopamine transporter (DAT) imaging, and biological variables. We aimed to examine whether non-manifesting carriers of LRRK2 and GBA mutations have prodromal features of Parkinson's disease that correlate with reduced DAT binding.MethodsThis cross-sectional analysis is based on assessments done at enrolment in the subset of non-manifesting carriers of LRRK2 and GBA mutations enrolled into the PPMI study from 33 participating sites worldwide. The primary objective was to examine baseline clinical and DAT imaging characteristics in non-manifesting carriers with GBA and LRRK2 mutations compared with healthy controls. DAT deficit was defined as less than 65% of putamen striatal binding ratio expected for the individual's age. We used t tests, χ2 tests, and Fisher's exact tests to compare baseline demographics across groups. An inverse probability weighting method was applied to control for potential confounders such as age and sex. To account for multiple comparisons, we applied a family-wise error rate to each set of analyses. This study is registered with ClinicalTrials.gov, number NCT01141023.FindingsBetween Jan 1, 2014, and Jan 1, 2019, the study enrolled 208 LRRK2 (93% G2019S) and 184 GBA (96% N370S) non-manifesting carriers. Both groups were similar with respect to mean age, and about 60% were female. Of the 286 (73%) non-manifesting carriers that had DAT imaging results, 18 (11%) LRRK2 and four (3%) GBA non-manifesting carriers had a DAT deficit. Compared with healthy controls, both LRRK2 and GBA non-manifesting carriers had significantly increased mean scores on the Movement Disorders Society Unified Parkinson's Disease Rating Scale (total score 4·6 [SD 4·4] healthy controls vs 8·4 [7·3] LRRK2 vs 9·5 [9·2] GBA, p

The goal of this study was to compare regional brain atrophy patterns in cognitively unimpaired (CU) older adults with and without brain accumulation of amyloid-β (Aβ) to elucidate contributions of Aβ, age, and other variables to atrophy rates. In 80 CU participants from the Alzheimer's Disease Neuroimaging Initiative, we determined effects of Aβ and age on longitudinal, regional atrophy rates, while accounting for confounding variables including sex, APOE ε4 genotype, white matter lesions, and cerebrospinal fluid total and phosphorylated tau levels. We not only found overlapping patterns of atrophy in Aβ+ versus Aβ- participants but also identified regions where atrophy pattern differed between the 2 groups. Higher Aβ load was associated with increased longitudinal atrophy in the entorhinal cortex, amygdala, and hippocampus, even when accounting for age and other variables. Age was associated with atrophy in insula, fusiform gyrus, and isthmus cingulate, even when accounting for Aβ. We found age by Aβ interactions in the postcentral gyrus and lateral orbitofrontal cortex. These results elucidate the separate and related effects of age, Aβ, and other important variables on longitudinal brain atrophy rates in CU older adults.

ObjectiveTo determine the feasibility, safety and tolerability of lumbar punctures (LPs) in research participants with early Parkinson disease (PD), subjects without evidence of dopaminergic deficiency (SWEDDs) and healthy volunteers (HC).BackgroundCerebrospinal fluid (CSF) analysis is becoming an essential part of the biomarkers discovery effort in PD with still limited data on safety and feasibility of serial LPs in PD participants.Design/methodsParkinson's Progression Marker Initiative (PPMI) is a longitudinal observation study designed to identify PD progression biomarkers. All PPMI participants undergo LP at baseline, 6, 12 months and yearly thereafter. CSF collection is performed by a trained investigator using predominantly atraumatic needles. Adverse events (AEs) are monitored by phone one week after LP completion. We analyzed safety data from baseline LPs.ResultsPPMI enrolled 683 participants (423 PD/196 HC/64 SWEDDs) from 23 study sites. CSF was collected at baseline in 97.5% of participants, of whom 5.4% underwent collection under fluoroscopy. 23% participants reported any related AEs, 68% of all AE were mild while 5.6% were severe. The most common AEs were headaches (13%) and low back pain (6.5%) and both occurred more commonly in HC and SWEDDs compared to PD participants. Factors associated with higher incidence of AEs across the cohorts included female gender, younger age and use of traumatic needles with larger diameter. AEs largely did not impact compliance with the future LPs.ConclusionsLPs are safe and feasible in PD research participants. Specific LP techniques (needle type and gauge) may reduce the overall incidence of AEs.

Mounting evidence indicates that the polygenic basis of late-onset Alzheimer's disease can be harnessed to identify individuals at greatest risk for cognitive decline. We have previously developed and validated a polygenic hazard score comprising of 31 single nucleotide polymorphisms for predicting Alzheimer's disease dementia age of onset. In this study, we examined whether polygenic hazard scores are associated with: (i) regional tracer uptake using amyloid PET; (ii) regional volume loss using longitudinal MRI; (iii) post-mortem regional amyloid-β protein and tau associated neurofibrillary tangles; and (iv) four common non-Alzheimer's pathologies. Even after accounting for APOE, we found a strong association between polygenic hazard scores and amyloid PET standard uptake volume ratio with the largest effects within frontal cortical regions in 980 older individuals across the disease spectrum, and longitudinal MRI volume loss within the entorhinal cortex in 607 older individuals across the disease spectrum. We also found that higher polygenic hazard scores were associated with greater rates of cognitive and clinical decline in 632 non-demented older individuals, even after controlling for APOE status, frontal amyloid PET and entorhinal cortex volume. In addition, the combined model that included polygenic hazard scores, frontal amyloid PET and entorhinal cortex volume resulted in a better fit compared to a model with only imaging markers. Neuropathologically, we found that polygenic hazard scores were associated with regional post-mortem amyloid load and neuronal neurofibrillary tangles, even after accounting for APOE, validating our imaging findings. Lastly, polygenic hazard scores were associated with Lewy body and cerebrovascular pathology. Beyond APOE, we show that in living subjects, polygenic hazard scores were associated with amyloid deposition and neurodegeneration in susceptible brain regions. Polygenic hazard scores may also be useful for the identification of individuals at the highest risk for developing multi-aetiological dementia.

Background and purposeThe aging HIV-infected (HIV+) population has increased vascular comorbidities, including stroke, and increased cognitive deficits compared with the general population. Arterial spin-labeling is a technique to measure cerebral blood flow and is more sensitive than regional volume loss in assessing neurodegenerative diseases and cognitive aging. Previous studies have found global cerebral perfusion abnormalities in the HIV+ participants. In this study, we evaluated the specific regional pattern of CBF abnormalities in older HIV+ participants using quantitative whole-brain arterial spin-labeling.Materials and methodsCBF data from the UCSF HIV Over 60 Cohort and the Alzheimer Disease Neuroimaging Initiative were retrospectively evaluated to identify 19 HIV+ older adults, all with plasma viral suppression (including 5 with HIV-associated neurocognitive disorder); 13 healthy, age-matched controls; and 19 participants with early mild cognitive impairment. CBF values were averaged by ROI and compared among the 3 groups using generalized linear models.ResultsWhen we accounted for age, education, sex, and vascular risk factors, the HIV+ participants demonstrated alterations in regional cerebral perfusion, including hypoperfusion of bilateral temporal, parietal, and occipital brain regions compared with both clinically healthy participants and those with mild cognitive impairment. Arterial spin-labeling showed reasonable test characteristics in distinguishing those with HIV-associated neurocognitive disorder from healthy controls and participants with mild cognitive impairment.ConclusionsThis study found specific CBF patterns associated with HIV status despite viral suppression-data that should animate further investigations into the pathobiologic basis of vascular and cognitive abnormalities in HIV-associated neurocognitive disorders.

Although leukocyte telomere length (TL) shortens over the lifespan and is associated with diseases of aging, little is known about the relationships between TL, memory, and brain structure. Sixty-nine functionally normal older adults (mean age = 71.7) were assessed at 2 time points (mean interval = 2.9 years). Linear mixed models assessed relationships between TL and hippocampal volume, fractional anisotropy, and mean diffusivity (MD) of the fornix and verbal and visual episodic memory. Unstandardized coefficients are reported in the following, and p values are not corrected for multiple comparisons. A negative baseline trend was observed between TL and fornix MD (b = -0.01, p = 0.06), but no other cross-sectional associations were significant (ps > 0.16). Greater TL shortening at follow-up was associated with greater hippocampal volume loss (b = 27.09, p < 0.001), even after controlling for global volume loss (b = 10.83, p = 0.002). Greater telomere attrition was also associated with larger increases in fornix MD (b = -0.01, p = 0.012) and decreases in fornix fractional anisotropy (b = 0.004, p = 0.002). TL was not associated with changes in episodic memory (ps > 0.23). These relationships may reflect neurobiological influences that affect both TL and brain structure, as well as the effect of TL on brain aging via mechanisms such as cellular senescence and inflammation.

OBJECTIVE:The objective of this study was to assess longitudinal change in clinical and dopamine transporter imaging outcomes in early, untreated PD. METHODS:We describe 5-year longitudinal change of the MDS-UPDRS and other clinical measures using results from the Parkinson's Progression Markers Initiative, a longitudinal cohort study of early Parkinson's disease (PD) participants untreated at baseline. We also provide data on the longitudinal change in dopamine transporter 123-I Ioflupane striatal binding and correlation between the 2 measures. RESULTS:A total of 423 PD participants were recruited, and 358 remain in the study at year 5. Baseline MDS-UPDRS total score was 32.4 (standard deviation 13.1), and the average annual change (assessed medications OFF for the treated participants) was 7.45 (11.6), 3.11 (11.7), 4(11.9), 4.7 (11.1), and 1.74(11.9) for years 1, 2, 3, 4, and 5, respectively (P

Models of Alzheimer's disease (AD) hypothesize stereotyped progression via white matter (WM) fiber connections, most likely via trans-synaptic transmission of toxic proteins along neuronal pathways. An important question in the field is whether and how organization of fiber pathways is affected by disease. It remains unknown whether fibers act as conduits of degenerative pathologies, or if they also degenerate with the gray matter network. This work uses graph theoretic modeling in a longitudinal design to investigate the impact of WM network organization on AD pathology spread. We hypothesize if altered WM network organization mediates disease progression, then a previously published network diffusion model will yield higher prediction accuracy using subject-specific connectomes in place of a healthy template connectome. Neuroimaging data in 124 subjects from ADNI were assessed. Graph topology metrics show preserved network organization in patients compared to controls. Using a published diffusion model, we further probe the effect of network alterations on degeneration spread in AD. We show that choice of connectome does not significantly impact the model's predictive ability. These results suggest that, despite measurable changes in integrity of specific fiber tracts, WM network organization in AD is preserved. Further, there is no difference in the mediation of putative pathology spread between healthy and AD-impaired networks. This conclusion is somewhat at variance with previous results, which report global topological disturbances in AD. Our data indicates the combined effect of edge thresholding, binarization, and inclusion of subcortical regions to network graphs may be responsible for previously reported effects.

ObjectivesTo investigate the association between cognitive decline and cortical atrophy in individuals with mild cognitive impairment (MCI) and chronic subsyndromal symptoms of depression (SSD) over a 4-year period.DesignProspective cohort study.SettingMulticenter, clinic-based.ParticipantsWithin the Alzheimer's Disease Neuroimaging Initiative repository, the Neuropsychiatric Inventory was used to identify individuals with MCI and stable endorsement (SSD group N = 32) or no endorsement (non-SSD group N = 69) of depressive symptoms across time points.MeasurementsRepeated measures of cognitive outcomes, cortical atrophy, and their associations were evaluated with mixed effects models adjusting for age, education, sex, and APOE genotype.ResultsThe SSD group demonstrated accelerated decline on measures of global cognition (Alzheimer Disease Assessment Scale; df = 421, t = 2.242, p = 0.025), memory (Wechsler Memory Scale-Revised Logical Memory II; df = 244, t = -2.525, p = 0.011), information processing speed (Trail Making Test Parts A [df = 421, t = 2.376, p = 0.018] and B [df = 421, t = 2.533, p = 0.012]), and semantic fluency (Category Fluency; df = 424, t = -2.418, p = 0.016), as well as accelerated frontal lobe (df = 341, t = -2.648, p = 0.008) and anterior cingulate (df = 341, t = -3.786, p

See Vandenberghe and Schaeverbeke (doi:10.1093/awx065) for a scientific commentary on this article. A long-term goal of our field is to determine the sequence of pathological events, which ultimately lead to cognitive decline and dementia. In this study, we first assessed the patterns of brain tau tangle accumulation (measured with the positron emission tomography tracer 18F-AV-1451) associated with well-established Alzheimer's disease factors in a cohort including cognitively healthy elderly individuals and individuals at early symptomatic stages of Alzheimer's disease. We then explored highly associated patterns of greater 18F-AV-1451 binding and increased annualized change in cortical amyloid-β plaques measured as florbetapir positron emission tomography binding antecedent to 18F-AV-1451 positron emission tomography scans, and to what extent these multimodal pattern associations explained the variance in cognitive performance and clinical outcome measures, independently and jointly. We found that: (i) 18F-AV-1451 positron emission tomography retention was differentially associated with age, and cross-sectional florbetapir positron emission tomography retention, but not with years of education, gender, or APOE genotype; (ii) increased annualized change in florbetapir retention, antecedent to 18F-AV-1451 positron emission tomography scans, in the parieto-temporal and precuneus brain regions was associated with greater 18F-AV-1451 PET retention most prominently in the inferior temporal and inferior parietal regions in the full cohort, with florbetapir positive/negative-associated variability; and (iii) this 18F-AV-1451 positron emission tomography retention pattern significantly explained the variance in cognitive performance and clinical outcome measures, independent of the associated antecedent increased annualized change in florbetapir positron emission tomography retention. These findings are in agreement with the pathology literature, which suggests that tau tangles but not amyloid-β plaques correlate with cognition and clinical symptoms. Furthermore, non-local associations linking increased amyloid-β accumulation rates with increased tau deposition are of great interest and support the idea that the amyloid-β pathology might have remote effects in disease pathology spread potentially via the brain's intrinsic connectivity networks.

The purpose of this study was to determine whether white matter microstructure measured by diffusion magnetic resonance imaging (dMRI) provides independent information about baseline level or change in executive function (EF) or memory (MEM) in older adults with and without cognitive impairment. Longitudinal data was acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study from phases GO and 2 (2009-2015). ADNI participants included were diagnosed as cognitively normal (n = 46), early mild cognitive impairment (MCI) (n = 48), late MCI (n = 29), and dementia (n = 39) at baseline. We modeled the association between dMRI-based global white matter mean diffusivity (MD) and baseline level and change in EF and MEM composite scores, in models controlling for baseline bilateral hippocampal volume, regional cerebral FDG PET metabolism and global cerebral AV45 PET uptake. EF and MEM composite scores were measured at baseline, 6, 12, 24 and 36 months. In the baseline late MCI and dementia groups, greater global MD was associated with lesser baseline EF, but not EF change nor MEM baseline or change. As expected, lesser hippocampal volume and lesser FDG PET metabolism was associated with greater rates of EF and MEM decline. In ADNI-GO/2 participants, white matter integrity provided independent information about current executive function, but was not sensitive to future cognitive change. Since individuals experiencing executive function declines progress to dementia more rapidly than those with only memory impairment, better biomarkers of future executive function decline are needed.

ObjectivesTo assess the neurobiological substrate of initial cognitive decline in Parkinson's disease (PD) to inform patient management, clinical trial design, and development of treatments.MethodsWe longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models.ResultsBy year 3, cognitive impairment was diagnosed in 15-38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer's disease Aβ amyloid pathology (lower CSF Aβ 1-42); and (4) genes (COMT val/val and BDNF val/val genotypes).ConclusionsCognitive impairment in PD increases in frequency 50-200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer's disease plaque pathology, and genetic factors.

BackgroundDegradation of white matter microstructure has been demonstrated in frontotemporal lobar degeneration (FTLD) and Alzheimer's disease (AD). In preparation for clinical trials, ongoing studies are investigating the utility of longitudinal brain imaging for quantification of disease progression. To date only one study has examined sample size calculations based on longitudinal changes in white matter integrity in FTLD.ObjectiveTo quantify longitudinal changes in white matter microstructural integrity in the three canonical subtypes of frontotemporal dementia (FTD) and AD using diffusion tensor imaging (DTI).Methods60 patients with clinical diagnoses of FTD, including 27 with behavioral variant frontotemporal dementia (bvFTD), 14 with non-fluent variant primary progressive aphasia (nfvPPA), and 19 with semantic variant PPA (svPPA), as well as 19 patients with AD and 69 healthy controls were studied. We used a voxel-wise approach to calculate annual rate of change in fractional anisotropy (FA) and mean diffusivity (MD) in each group using two time points approximately one year apart. Mean rates of change in FA and MD in 48 atlas-based regions-of-interest, as well as global measures of cognitive function were used to calculate sample sizes for clinical trials (80% power, alpha of 5%).ResultsAll FTD groups showed statistically significant baseline and longitudinal white matter degeneration, with predominant involvement of frontal tracts in the bvFTD group, frontal and temporal tracts in the PPA groups and posterior tracts in the AD group. Longitudinal change in MD yielded a larger number of regions with sample sizes below 100 participants per therapeutic arm in comparison with FA. SvPPA had the smallest sample size based on change in MD in the fornix (n = 41 participants per study arm to detect a 40% effect of drug), and nfvPPA and AD had their smallest sample sizes based on rate of change in MD within the left superior longitudinal fasciculus (n = 49 for nfvPPA, and n = 23 for AD). BvFTD generally showed the largest sample size estimates (minimum n = 140 based on MD in the corpus callosum). The corpus callosum appeared to be the best region for a potential study that would include all FTD subtypes. Change in global measure of functional status (CDR box score) yielded the smallest sample size for bvFTD (n = 71), but clinical measures were inferior to white matter change for the other groups.ConclusionsAll three of the canonical subtypes of FTD are associated with significant change in white matter integrity over one year. These changes are consistent enough that drug effects in future clinical trials could be detected with relatively small numbers of participants. While there are some differences in regions of change across groups, the genu of the corpus callosum is a region that could be used to track progression in studies that include all subtypes.

Cross-sectional studies show that elevated cerebral amyloid is associated with greater white-matter hyperintensity (WMH) burden in cognitively normal (CN) older adults. However, the relative time courses of amyloid and WMH accrual are unclear. To address this, we tested the associations between known WMH correlates-age, hypertension, and amyloid-with WMH accrual rate. We used brain magnetic resonance imaging to measure WMH change in 112 CN Alzheimer's Disease Neuroimaging Initiative (GO/2) participants over a 2-year period. A linear mixed effects model assessed baseline cerebrospinal fluid amyloid beta (Aβ) 1-42, hypertension, age, and their interactions, as predictors of greater WMH accrual. Greater amyloid burden was associated with greater WMH accrual over time. Those with hypertension showed a stronger association between greater amyloid burden and WMH accrual rate. Greater age was not significantly associated with greater WMH accrual in this model. Although the direction of the relationship cannot be tested in this model, CN individuals harboring cerebral amyloid had greater accrual of WMH over a 2-year period after accounting for hypertension and age. Impaired amyloid clearance and cerebral small vessel disease may both underlie the more rapid emergence of WM lesions. The role of cerebral amyloid burden in white-matter injury should thus be considered as a relevant factor when WMHs are detected clinically.

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 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.

ObjectiveInvestigate the association of chronic depressive symptomatology (chrDS) with cortical atrophy rates and conversion to Alzheimer dementia (AD) over 3 years in mild cognitive impairment (MCI).MethodsIn a multicenter, clinic-based study, MCI elderly participants were selected from the Alzheimer's Disease Neuroimaging Initiative repository, based on availability of both serial structural magnetic resonance imaging and chrDS endorsed on three depression-related items from the Neuropsychiatric Inventory Questionnaire (chrDS N = 32 or no depressive symptoms N = 62) throughout follow-up. Clinical and laboratory investigations were performed every 6 months during the first 2 years and yearly thereafter (median follow-up: 3 years; interquartile range: 1.5-4.0 years). Cortical atrophy rates in 16 predefined frontotemporoparietal regions affected in major depression and AD and the rate of incident AD at follow-up.ResultsChrDS in a single domain amnestic MCI sample were associated with accelerated cortical atrophy in the frontal lobe and anterior cingulate but not with atrophy rates in temporomedial or other AD-affected regions. During follow-up, 38 participants (42.7%) developed AD. Participants with chrDS had 60% shorter conversion time to AD than those without depressive symptoms. This association remained significant in survival models adjusted for temporomedial atrophy rates and showed the same trend in models adjusted for frontal cortical atrophy rate, which all increased the risk of AD.ConclusionOur results suggest that chrDS associated with progressive atrophy of frontal regions may represent an additional risk factor for conversion to dementia in MCI as opposite to representing typical prodromal AD symptomatology.

This study aimed to identify the utility of diffusion tensor imaging (DTI) in measuring the regional distribution of abnormal microstructural progression in patients with Parkinson's disease who were enrolled in the Parkinson's progression marker initiative (PPMI). One hundred and twenty two de-novo PD patients (age = 60.5±9) and 50 healthy controls (age = 60.6±11) had DTI scans at baseline and 12.6±1 months later. Automated image processing included an intra-subject registration of all time points and an inter-subjects registration to a brain atlas. Annualized rates of DTI variations including fractional anisotropy (FA), radial (rD) and axial (aD) diffusivity were estimated in a total of 118 white matter and subcortical regions of interest. A mixed effects model framework was used to determine the degree to which DTI changes differed in PD relative to changes in healthy subjects. Significant DTI changes were also tested for correlations with changes in clinical measures, dopaminergic imaging and CSF biomarkers in PD patients. Compared to normal aging, PD was associated with higher rates of FA reduction, rD and aD increases predominantly in the substantia nigra, midbrain and thalamus. The highest rates of FA reduction involved the substantia nigra (3.6±1.4%/year from baseline, whereas the highest rates of increased diffusivity involved the thalamus (rD: 8.0±2.9%/year, aD: 4.0±1.5%/year). In PD patients, high DTI changes in the substantia nigra correlated with increasing dopaminergic deficits as well as with declining α-synuclein and total tau protein concentrations in cerebrospinal fluid. Increased DTI rates in the thalamus correlated with progressive decline in global cognition in PD. The results suggest that higher rates of regional microstructural degeneration are potential markers of PD progression.

BackgroundRecent studies have demonstrated that arterial spin labeling magnetic resonance imaging (ASL-MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) identify similar regional abnormalities and have comparable diagnostic accuracy in Alzheimer's disease (AD). The agreement between these modalities in the AD continuum, which is an important concept for early detection and disease monitoring, is yet unclear.ObjectiveWe aimed to assess the ability of the cerebral blood flow (CBF) measures from ASL-MRI and cerebral metabolic rate for glucose (CMRgl) measures from FDG-PET to distinguish amyloid-β-positive (Aβ+) subjects in the AD continuum from healthy controls.MethodsThe study included asymptomatic, cognitively normal (CN) controls and patients with early mild cognitive impairment (MCI), late MCI, and AD, all with significant levels of cortical Aβ based on their florbetapir PET scans to restrict the study to patients truly in the AD continuum. The discrimination power of each modality was based on the whole-brain patterns of CBF and CMRgl changes identified by partial least squares logistic regression, a multivariate analysis technique.ResultsWhile CBF changes in the posterior inferior aspects of the brain and a pattern of CMRgl changes in the superior aspects of the brain including frontal and parietal regions best discriminated the Aβ+ subjects in the early disease stages from the Aβ- CN subjects, there was a greater agreement in the whole-brain patterns of CBF and CMRgl changes that best discriminated the Aβ+ subjects from the Aβ- CN subjects in the later disease stages. Despite the differences in the whole-brain patterns of CBF and CMRgl changes, the discriminative powers of both modalities were similar with statistically nonsignificant performance differences in sensitivity and specificity.ConclusionThe results comparing measurements of CBF to CMRgl add to previous reports that MRI-measured CBF has a similar diagnostic ability to detect AD as has FDG-PET. Our findings that CBF and CMRgl changes occur in different brain regions in Aβ+ subjects across the AD continuum compared with Aβ- CN subjects may be the result of methodological differences. Alternatively, these findings may signal alterations in neurovascular coupling which alter relationships between brain perfusion and glucose metabolism in the AD continuum.

The medial temporal lobe is implicated as a key brain region involved in the pathogenesis of Alzheimer's disease (AD) and consequent memory loss. Tau tangle aggregation in this region may develop concurrently with cortical Aβ deposition in preclinical AD, but the pathological relationship between tau and Aβ remains unclear. We used task-free fMRI with a focus on the medical temporal lobe, together with Aβ PET imaging, in cognitively normal elderly human participants. We found that cortical Aβ load was related to disrupted intrinsic functional connectivity of the perirhinal cortex, which is typically the first brain region affected by tauopathies in AD. There was no concurrent association of cortical Aβ load with cognitive performance or brain atrophy. These findings suggest that dysfunction in the medial temporal lobe may represent a very early sign of preclinical AD and may predict future memory loss.

Background and purposeTo determine if a voxel-wise "co-analysis" of structural and diffusion tensor magnetic resonance imaging (MRI) together reveals additional brain regions affected in mild cognitive impairment (MCI) and Alzheimer's disease (AD) than voxel-wise analysis of the individual MRI modalities alone.MethodsTwenty-one patients with MCI, 21 patients with AD, and 21 cognitively normal healthy elderly were studied with MRI. Maps of deformation and fractional anisotropy (FA) were computed and used as dependent variables in univariate and multivariate statistical models.ResultsUnivariate voxel-wise analysis of macrostructural changes in MCI showed atrophy in the right anterior temporal lobe, left posterior parietal/precuneus region, WM adjacent to the cingulate gyrus, and dorsolateral prefrontal regions, consistent with prior research. Univariate voxel-wise analysis of microstructural changes in MCI showed reduced FA in the left posterior parietal region extending into the corpus callosum, consistent with previous work. The multivariate analysis, which provides more information than univariate tests when structural and FA measures are correlated, revealed additional MCI-related changes in corpus callosum and temporal lobe.ConclusionThese results suggest that in corpus callosum and temporal regions macro- and microstructural variations in MCI can be congruent, providing potentially new insight into the mechanisms of brain tissue degeneration.

ImportanceThe effect of β-amyloid (Aβ) accumulation on regional structural brain changes in early stages of Alzheimer disease (AD) is not well understood.ObjectiveTo test the hypothesis that the development of Aβ pathology is related to increased regional atrophy in the brains of cognitively normal (CN) persons.Design, setting, and participantsLongitudinal clinicobiomarker cohort study involving 47 CN control subjects and 15 patients with AD dementia. All participants underwent repeated cerebrospinal fluid Aβ42 and structural magnetic resonance imaging measurements for up to 4 years. Cognitively normal controls were classified using the longitudinal cerebrospinal fluid Aβ42 data and included 13 stable Aβ negative (normal baseline Aβ42 levels, with less than the median reduction over time), 13 declining Aβ negative (normal baseline Aβ42 levels, with greater than the median reduction over time), and 21 Aβ positive (pathologic baseline Aβ42 levels). All 15 patients with AD dementia were Aβ positive.Main outcomes and measuresGroup effects on regional gray matter volumes at baseline and over time, tested by linear mixed-effects models.ResultsBaseline gray matter volumes were similar among the CN Aβ groups, but atrophy rates were increased in frontoparietal regions in the declining Aβ-negative and Aβ-positive groups and in amygdala and temporal regions in the Aβ-positive group. Aβ-positive patients with AD dementia had further increased atrophy rates in hippocampus and temporal and cingulate regions.Conclusions and relevanceEmerging Aβ pathology is coupled to increased frontoparietal (but not temporal) atrophy rates. Atrophy rates peak early in frontoparietal regions but accelerate in hippocampus, temporal, and cingulate regions as the disease progresses to dementia. Early-stage Aβ pathology may have mild effects on local frontoparietal cortical integrity while effects in temporal regions appear later and accelerate, leading to the atrophy pattern typically seen in AD.

Patients with Alzheimer's disease have reduced cerebral blood flow measured by arterial spin labelling magnetic resonance imaging, but it is unclear how this is related to amyloid-β pathology. Using 182 subjects from the Alzheimer's Disease Neuroimaging Initiative we tested associations of amyloid-β with regional cerebral blood flow in healthy controls (n = 51), early (n = 66) and late (n = 41) mild cognitive impairment, and Alzheimer's disease with dementia (n = 24). Based on the theory that Alzheimer's disease starts with amyloid-β accumulation and progresses with symptoms and secondary pathologies in different trajectories, we tested if cerebral blood flow differed between amyloid-β-negative controls and -positive subjects in different diagnostic groups, and if amyloid-β had different associations with cerebral blood flow and grey matter volume. Global amyloid-β load was measured by florbetapir positron emission tomography, and regional blood flow and volume were measured in eight a priori defined regions of interest. Cerebral blood flow was reduced in patients with dementia in most brain regions. Higher amyloid-β load was related to lower cerebral blood flow in several regions, independent of diagnostic group. When comparing amyloid-β-positive subjects with -negative controls, we found reductions of cerebral blood flow in several diagnostic groups, including in precuneus, entorhinal cortex and hippocampus (dementia), inferior parietal cortex (late mild cognitive impairment and dementia), and inferior temporal cortex (early and late mild cognitive impairment and dementia). The associations of amyloid-β with cerebral blood flow and volume differed across the disease spectrum, with high amyloid-β being associated with greater cerebral blood flow reduction in controls and greater volume reduction in late mild cognitive impairment and dementia. In addition to disease stage, amyloid-β pathology affects cerebral blood flow across the span from controls to dementia patients. Amyloid-β pathology has different associations with cerebral blood flow and volume, and may cause more loss of blood flow in early stages, whereas volume loss dominates in late disease stages.

Biomarkers associated with Alzheimer's disease (AD)-like brain atrophy in healthy individuals may identify mechanisms involved in early stage AD. Aside from cerebrospinal fluid (CSF) β-amyloid42 (Aβ42) and tau, no studies have tested associations between CSF proteins and AD-like brain atrophy. We studied 90 healthy elders, who underwent lumbar puncture at baseline, and serial magnetic resonance imaging scans for up to 4 years. We tested statistical effects of baseline CSF proteins (N = 70 proteins related to Aβ42-metabolism, microglial activity, and synaptic/neuronal function) on atrophy rates in 7 AD-related regions. Besides the effects of Aβ42 and phosphorylated tau (P-tau) that were seen in several regions, novel CSF proteins were found to have effects in inferior and middle temporal cortex (including apolipoprotein CIII, apolipoprotein D, and apolipoprotein H). Several proteins (including S100β and matrix metalloproteinase-3) had effects that depended on the presence of brain Aβ pathology, as measured by CSF Aβ42. Other proteins (including P-tau and apolipoprotein D) had effects even after adjusting for CSF Aβ42. The statistical effects in this exploratory study were mild and not significant after correction for multiple comparisons, but some of the identified proteins may be associated with brain atrophy in healthy persons. Proteins interacting with CSF Aβ42 may be related to Aβ brain pathology, whereas proteins associated with atrophy even after adjusting for CSF Aβ42 may be related to Aβ-independent mechanisms.

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remain a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. © 2013 Wiley Periodicals, Inc.

The relationships between clinical phenotype, β-amyloid (Aβ) deposition and neurodegeneration in Alzheimer's disease (AD) are incompletely understood yet have important ramifications for future therapy. The goal of this study was to utilize multimodality positron emission tomography (PET) data from a clinically heterogeneous population of patients with probable AD in order to: (1) identify spatial patterns of Aβ deposition measured by ((11)C)-labeled Pittsburgh Compound B (PiB-PET) and glucose metabolism measured by FDG-PET that correlate with specific clinical presentation and (2) explore associations between spatial patterns of Aβ deposition and glucose metabolism across the AD population. We included all patients meeting the criteria for probable AD (NIA-AA) who had undergone MRI, PiB and FDG-PET at our center (N = 46, mean age 63.0 ± 7.7, Mini-Mental State Examination 22.0 ± 4.8). Patients were subclassified based on their cognitive profiles into an amnestic/dysexecutive group (AD-memory; n = 27), a language-predominant group (AD-language; n = 10) and a visuospatial-predominant group (AD-visuospatial; n = 9). All patients were required to have evidence of amyloid deposition on PiB-PET. To capture the spatial distribution of Aβ deposition and glucose metabolism, we employed parallel independent component analysis (pICA), a method that enables joint analyses of multimodal imaging data. The relationships between PET components and clinical group were examined using a Receiver Operator Characteristic approach, including age, gender, education and apolipoprotein E ε4 allele carrier status as covariates. Results of the first set of analyses independently examining the relationship between components from each modality and clinical group showed three significant components for FDG: a left inferior frontal and temporoparietal component associated with AD-language (area under the curve [AUC] 0.82, p = 0.011), and two components associated with AD-visuospatial (bilateral occipito-parieto-temporal [AUC 0.85, p = 0.009] and right posterior cingulate cortex [PCC]/precuneus and right lateral parietal [AUC 0.69, p = 0.045]). The AD-memory associated component included predominantly bilateral inferior frontal, cuneus and inferior temporal, and right inferior parietal hypometabolism but did not reach significance (AUC 0.65, p = 0.062). None of the PiB components correlated with clinical group. Joint analysis of PiB and FDG with pICA revealed a correlated component pair, in which increased frontal and decreased PCC/precuneus PiB correlated with decreased FDG in the frontal, occipital and temporal regions (partial r = 0.75, p

Modern machine learning algorithms are increasingly being used in neuroimaging studies, such as the prediction of Alzheimer's disease (AD) from structural MRI. However, finding a good representation for multivariate brain MRI features in which their essential structure is revealed and easily extractable has been difficult. We report a successful application of a machine learning framework that significantly improved the use of brain MRI for predictions. Specifically, we used the unsupervised learning algorithm of local linear embedding (LLE) to transform multivariate MRI data of regional brain volume and cortical thickness to a locally linear space with fewer dimensions, while also utilizing the global nonlinear data structure. The embedded brain features were then used to train a classifier for predicting future conversion to AD based on a baseline MRI. We tested the approach on 413 individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had baseline MRI scans and complete clinical follow-ups over 3 years with the following diagnoses: cognitive normal (CN; n=137), stable mild cognitive impairment (s-MCI; n=93), MCI converters to AD (c-MCI, n=97), and AD (n=86). We found that classifications using embedded MRI features generally outperformed (p

ObjectiveTo assess the effect of subsyndromal symptoms of depression (SSD) on ratings of disability for individuals with mild cognitive impairment (MCI).MethodsData from 405 MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were analyzed. Participants were evaluated at baseline and at 6-month intervals over 2 years. Severity of depressive symptoms was rated utilizing the Geriatric Depression Scale. Disability was assessed utilizing the Functional Assessment Questionnaire (FAQ). Other clinical variables included white matter lesion (WML) and intracranial brain (ICV) volumes derived from magnetic resonance imaging, ratings of overall cognitive function (Alzheimer's Disease Assessment Scale, ADAS), and apolipoprotein E (ApoE) status. Demographic variables included age, education, and gender.ResultsSSD individuals had a lower volume of WML and higher frequency of ApoE ε4 alleles than nondepressed participants but the two groups did not differ with respect to other clinical or demographic variables. At baseline, SSD individuals were 1.77 times more likely to have poorer FAQ scores than individuals with no symptoms of depression after controlling for the effect of cognitive functioning, ICV, WML, and ApoE status. The presence of SSD at baseline was not associated with a poorer course of disability outcomes, cognitive functioning, or conversion to dementia over 24 months.ConclusionsSSD demonstrated a significant impact on disability for MCI individuals, who are also at high risk for functional limitations related to neurodegenerative disease. Therefore, the treatment of SSD may represent a significant avenue to reduce the burden of disability in this vulnerable patient population.

β-amyloid (Aβ) plaque accumulation is a hallmark of Alzheimer's disease (AD). It is believed to start many years prior to symptoms and is reflected by reduced cerebrospinal fluid (CSF) levels of the peptide Aβ1-42 (Aβ42). Here we tested the hypothesis that baseline levels of CSF proteins involved in microglia activity, synaptic function and Aβ metabolism predict the development of Aβ plaques, assessed by longitudinal CSF Aβ42 decrease in cognitively healthy people. Forty-six healthy people with three to four serial CSF samples were included (mean follow-up 3 years, range 2-4 years). There was an overall reduction in Aβ42 from a mean concentration of 211-195 pg ml(-1) after 4 years. Linear mixed-effects models using longitudinal Aβ42 as the response variable, and baseline proteins as explanatory variables (n=69 proteins potentially relevant for Aβ metabolism, microglia or synaptic/neuronal function), identified 10 proteins with significant effects on longitudinal Aβ42. The most significant proteins were angiotensin-converting enzyme (ACE, P=0.009), Chromogranin A (CgA, P=0.009) and Axl receptor tyrosine kinase (AXL, P=0.009). Receiver-operating characteristic analysis identified 11 proteins with significant effects on longitudinal Aβ42 (largely overlapping with the proteins identified by linear mixed-effects models). Several proteins (including ACE, CgA and AXL) were associated with Aβ42 reduction only in subjects with normal baseline Aβ42, and not in subjects with reduced baseline Aβ42. We conclude that baseline CSF proteins related to Aβ metabolism, microglia activity or synapses predict longitudinal Aβ42 reduction in cognitively healthy elders. The finding that some proteins only predict Aβ42 reduction in subjects with normal baseline Aβ42 suggest that they predict future development of the brain Aβ pathology at the earliest stages of AD, prior to widespread development of Aβ plaques.

ObjectiveTo identify a neuroimaging signature predictive of brain amyloidosis as a screening tool to identify individuals with mild cognitive impairment (MCI) that are most likely to have high levels of brain amyloidosis or to be amyloid-free.MethodsThe prediction model cohort included 62 MCI subjects screened with structural magnetic resonance imaging (MRI) and (11) C-labeled Pittsburgh compound B positron emission tomography (PET). We identified an anatomical shape variation-based neuroimaging predictor of brain amyloidosis and defined a structural MRI-based brain amyloidosis score (sMRI-BAS). Amyloid beta positivity (Aβ(+) ) predictive power of sMRI-BAS was validated on an independent cohort of 153 MCI patients with cerebrospinal fluid Aβ1-42 biomarker data but no amyloid PET scans. We compared the Aβ(+) predictive power of sMRI-BAS to those of apolipoprotein E (ApoE) genotype and hippocampal volume, the 2 most relevant candidate biomarkers for the prediction of brain amyloidosis.ResultsAnatomical shape variations predictive of brain amyloidosis in MCI embraced a characteristic spatial pattern known for high vulnerability to Alzheimer disease pathology, including the medial temporal lobe, temporal-parietal association cortices, posterior cingulate, precuneus, hippocampus, amygdala, caudate, and fornix/stria terminals. Aβ(+) prediction performance of sMRI-BAS and ApoE genotype jointly was significantly better than the performance of each predictor separately (area under the curve [AUC] = 0.88 vs AUC = 0.70 and AUC = 0.81, respectively) with >90% sensitivity and specificity at 20% false-positive rate and false-negative rate thresholds. Performance of hippocampal volume as an independent predictor of brain amyloidosis in MCI was only marginally better than random chance (AUC = 0.56).InterpretationAs one of the first attempts to use an imaging technique that does not require amyloid-specific radioligands for identification of individuals with brain amyloidosis, our findings could lead to development of multidisciplinary/multimodality brain amyloidosis biomarkers that are reliable, minimally invasive, and widely available.

ObjectiveCortical atrophy has been associated with late-life depression (LLD) and recent findings suggest that reduced right hemisphere cortical thickness is associated with familial risk for major depressive disorder, but cortical thickness abnormalities in LLD have not been explored. Furthermore, cortical atrophy has been posited as a contributor to poor antidepressant treatment response in LLD, but the impact of cortical thickness on psychotherapy response is unknown. This study was conducted to evaluate patterns of cortical thickness in LLD and in relation to psychotherapy treatment outcomes.MethodsParticipants included 22 individuals with LLD and 12 age-matched comparison subjects. LLD participants completed 12 weeks of psychotherapy and treatment response was defined as a 50% reduction in depressive symptoms. All participants underwent magnetic resonance imaging of the brain, and cortical mapping of gray matter tissue thickness was calculated.ResultsLLD individuals demonstrated thinner cortex than controls prominently in the right frontal, parietal, and temporal brain regions. Eleven participants (50%) exhibited positive psychotherapy response after 12 weeks of treatment. Psychotherapy nonresponders demonstrated thinner cortex in bilateral posterior cingulate and parahippocampal cortices, left paracentral, precuneus, cuneus, and insular cortices, and the right medial orbitofrontal and lateral occipital cortices relative to treatment responders.ConclusionsOur findings suggest more distributed right hemisphere cortical abnormalities in LLD than have been previously reported. In addition, our findings suggest that reduced bilateral cortical thickness may be an important phenotypic marker of individuals at higher risk for poor response to psychotherapy.

BackgroundCerebrospinal fluid (CSF) α-synuclein is reduced in synucleinopathies, including dementia with Lewy bodies, and some studies have found increased CSF α-synuclein in Alzheimer's disease (AD). No study has explored effects of CSF α-synuclein on brain atrophy. Here we tested if baseline CSF α-synuclein affects brain atrophy rates and if these effects vary across brain regions, and across the cognitive spectrum from healthy elders (NL), to patients with mild cognitive impairment (MCI) and AD.MethodsBaseline CSF α-synuclein measurements and longitudinal structural brain magnetic resonance imaging was performed in 74 NL, 118 MCI patients and 55 AD patients. Effects of baseline CSF α-synuclein on regional atrophy rates were tested in 1) four pre-hoc defined regions possibly associated with Lewy body and/or AD pathology (amygdala, caudate, hippocampus, brainstem), and 2) all available regions of interest. Differences across diagnoses were tested by assessing the interaction of CSF α-synuclein and diagnosis (testing NL versus MCI, and NL versus AD).ResultsThe effects of CSF α-synuclein on longitudinal atrophy rates were not significant after correction for multiple comparisons. There were tendencies for effects in AD in caudate (higher atrophy rates in subjects with higher CSF α-synuclein, P=0.046) and brainstem (higher atrophy rates in subjects with lower CSF α-synuclein, P=0.063). CSF α-synuclein had significantly different effects on atrophy rates in NL and AD in brainstem (P=0.037) and caudate (P=0.006).DiscussionWith the possible exception of caudate and brainstem, the overall weak effects of CSF α-synuclein on atrophy rates in NL, MCI and AD argues against CSF α-synuclein as a biomarker related to longitudinal brain atrophy in these diagnostic groups. Any effects of CSF α-synuclein may be attenuated by possible simultaneous occurrence of AD-related neuronal injury and concomitant Lewy body pathology, which may elevate and reduce CSF α-synuclein levels, respectively.