ABSTRACT
BACKGROUND: Hearing loss has been proposed as a modifiable risk factor for dementia. However, the relationship between hearing, neurodegeneration, and cognitive change, and the extent to which pathological processes such as Alzheimer's disease and cerebrovascular disease influence these relationships, is unclear. METHODS: Data from 287 adults born in the same week of 1946 who underwent baseline pure tone audiometry (mean age=70.6 years) and two time point cognitive assessment/multimodal brain imaging (mean interval 2.4 years) were analysed. Hearing impairment at baseline was defined as a pure tone average of greater than 25 decibels in the best hearing ear. Rates of change for whole brain, hippocampal and ventricle volume were estimated from structural MRI using the Boundary Shift Integral. Cognition was assessed using the Pre-clinical Alzheimer's Cognitive Composite. Regression models were performed to evaluate how baseline hearing impairment associated with subsequent brain atrophy and cognitive decline after adjustment for a range of confounders including baseline ß-amyloid deposition and white matter hyperintensity volume. RESULTS: 111 out of 287 participants had hearing impairment. Compared with those with preserved hearing, hearing impaired individuals had faster rates of whole brain atrophy, and worse hearing (higher pure tone average) predicted faster rates of hippocampal atrophy. In participants with hearing impairment, faster rates of whole brain atrophy predicted greater cognitive change. All observed relationships were independent of ß-amyloid deposition and white matter hyperintensity volume. CONCLUSIONS: Hearing loss may influence dementia risk via pathways distinct from those typically implicated in Alzheimer's and cerebrovascular disease in cognitively unimpaired older adults.
ABSTRACT
BACKGROUND: Consistent patterns of reduced cortical thickness have been identified in early Alzheimer's disease (AD). However, the pathological factors that influence rates of cortical thinning within these AD signature regions remain unclear. METHODS: Participants were from the Insight 46 substudy of the MRC National Survey of Health and Development (NSHD; 1946 British birth cohort), a prospective longitudinal cohort study. Linear regression was used to examine associations of baseline cerebral ß-amyloid (Aß) deposition, measured using florbetapir positron emission tomography, and baseline white matter hyperintensity volume (WMHV) on MRI, a marker of cerebral small vessel disease, with subsequent longitudinal changes in AD signature cortical thickness quantified from baseline and repeat MRI (mean [SD] interval 2.4 [0.2] years). RESULTS: In a population-based sample of 337 cognitively normal older white adults (mean [SD] age at baseline 70.5 [0.6] years; 48.1% female), higher global WMHV at baseline related to faster subsequent rates of cortical thinning in both AD signature regions (~0.15%/year faster per 10 mL additional WMHV), whereas baseline Aß status did not. Among Aß positive participants (n=56), there was some evidence that greater global Aß standardised uptake value ratio at baseline related to faster cortical thinning in the AD signature Mayo region, but this did not reach statistical significance (p=0.08). CONCLUSIONS: Cortical thinning within AD signature regions may develop via cerebrovascular pathways. Perhaps reflecting the age of the cohort and relatively low prevalence of Aß-positivity, robust Aß-related differences were not detected. Longitudinal follow-up incorporating additional biomarkers will allow assessment of how these relationships evolve closer to expected dementia onset.
Subject(s)
Alzheimer Disease , Amyloid beta-Peptides , Cerebral Cortical Thinning , Magnetic Resonance Imaging , Positron-Emission Tomography , White Matter , Humans , Female , Male , Aged , Alzheimer Disease/diagnostic imaging , Alzheimer Disease/pathology , Alzheimer Disease/metabolism , Amyloid beta-Peptides/metabolism , Longitudinal Studies , White Matter/diagnostic imaging , White Matter/pathology , Cerebral Cortical Thinning/diagnostic imaging , Cerebral Cortical Thinning/pathology , Prospective Studies , Ethylene Glycols , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/pathology , Cerebral Cortex/metabolism , Cerebral Small Vessel Diseases/diagnostic imaging , Cerebral Small Vessel Diseases/pathology , Aniline CompoundsABSTRACT
BACKGROUND: Although age is the biggest known risk factor for dementia, there remains uncertainty about other factors over the life course that contribute to a person's risk for cognitive decline later in life. Furthermore, the pathological processes leading to dementia are not fully understood. The main goals of Insight 46-a multi-phase longitudinal observational study-are to collect detailed cognitive, neurological, physical, cardiovascular, and sensory data; to combine those data with genetic and life-course information collected from the MRC National Survey of Health and Development (NSHD; 1946 British birth cohort); and thereby contribute to a better understanding of healthy ageing and dementia. METHODS/DESIGN: Phase 1 of Insight 46 (2015-2018) involved the recruitment of 502 members of the NSHD (median age = 70.7 years; 49% female) and has been described in detail by Lane and Parker et al. 2017. The present paper describes phase 2 (2018-2021) and phase 3 (2021-ongoing). Of the 502 phase 1 study members who were invited to a phase 2 research visit, 413 were willing to return for a clinic visit in London and 29 participated in a remote research assessment due to COVID-19 restrictions. Phase 3 aims to recruit 250 study members who previously participated in both phases 1 and 2 of Insight 46 (providing a third data time point) and 500 additional members of the NSHD who have not previously participated in Insight 46. DISCUSSION: The NSHD is the oldest and longest continuously running British birth cohort. Members of the NSHD are now at a critical point in their lives for us to investigate successful ageing and key age-related brain morbidities. Data collected from Insight 46 have the potential to greatly contribute to and impact the field of healthy ageing and dementia by combining unique life course data with longitudinal multiparametric clinical, imaging, and biomarker measurements. Further protocol enhancements are planned, including in-home sleep measurements and the engagement of participants through remote online cognitive testing. Data collected are and will continue to be made available to the scientific community.
Subject(s)
Dementia , Aged , Female , Humans , Male , Aging , Ambulatory Care , Brain , Observational Studies as TopicABSTRACT
Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer's disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer's disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer's disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light. Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function. Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer's disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer's disease.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Connectome , Humans , Cross-Sectional Studies , Intermediate Filaments , Magnetic Resonance Imaging/methods , Brain/diagnostic imaging , Cognition , Nerve Net/diagnostic imagingABSTRACT
While frontotemporal dementia has been considered a neurodegenerative disease that starts in mid-life or later, it is now clearly established that cortical and subcortical volume loss is observed more than a decade prior to symptom onset and progresses with ageing. To test the hypothesis that genetic mutations causing frontotemporal dementia have neurodevelopmental consequences, we examined the youngest adults in the GENFI cohort of pre-symptomatic frontotemporal dementia mutation carriers who are between 19 and 30 years of age. Structural brain differences and improved performance on some cognitive tests were found for MAPT and GRN mutation carriers relative to familial non-carriers, while smaller volumes were observed in C9orf72 repeat expansion carriers at a mean age of 26 years. The detection of such early differences supports potential advantageous neurodevelopmental consequences of some frontotemporal dementia-causing genetic mutations. These results have implications for the design of therapeutic interventions for frontotemporal dementia. Future studies at younger ages are needed to identify specific early pathophysiologic or compensatory processes that occur during the neurodevelopmental period.
Subject(s)
Frontotemporal Dementia , Neurodegenerative Diseases , Pick Disease of the Brain , Humans , Young Adult , Adult , Frontotemporal Dementia/genetics , Progranulins/genetics , Brain , Mutation , C9orf72 Protein/genetics , tau Proteins/geneticsABSTRACT
INTRODUCTION: To support clinical trial designs focused on early interventions, our study determined reliable early amyloid-ß (Aß) accumulation based on Centiloids (CL) in pre-dementia populations. METHODS: A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease-Prognostic and Natural History Study (AMYPAD-PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid-PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub-populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision-recall analyses. Accumulation rates were examined using linear mixed-effect models. RESULTS: Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aß-accumulators. Rates of amyloid accumulation were tracer-independent, lower for APOE ε4 non-carriers, and for subjects with higher levels of education. DISCUSSION: Our results support a 12-20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations.
Subject(s)
Alzheimer Disease , Amyloid beta-Peptides , Aniline Compounds , Positron-Emission Tomography , Humans , Male , Female , Aged , Amyloid beta-Peptides/metabolism , Alzheimer Disease/diagnostic imaging , Alzheimer Disease/metabolism , Prognosis , Middle Aged , Longitudinal Studies , Stilbenes , Brain/diagnostic imaging , Brain/metabolism , BenzothiazolesABSTRACT
INTRODUCTION: Amyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin-1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre-/postcodon 200) influences these pathologic features and dementia at different stages. METHODS: Individuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross-sectionally evaluated regional Pittsburgh compound B-positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging-based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition. RESULTS: Postcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures. DISCUSSION: We demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials. HIGHLIGHTS: Mutation position influences Aß burden, SVD, and dementia. PSEN1 pre-200 group had stronger associations between Aß burden and disease stage. PSEN1 post-200 group had stronger associations between SVD markers and disease stage. PSEN1 post-200 group had worse dementia score than pre-200 in late disease stage. Diffusion tensor imaging-based SVD markers mediated mutation position effects on dementia in the late stage.
Subject(s)
Alzheimer Disease , Amyloidosis , Cerebral Small Vessel Diseases , Humans , Alzheimer Disease/diagnostic imaging , Alzheimer Disease/genetics , Alzheimer Disease/pathology , Cerebral Small Vessel Diseases/diagnostic imaging , Cerebral Small Vessel Diseases/genetics , Cerebral Small Vessel Diseases/complications , Diffusion Tensor Imaging , Magnetic Resonance Imaging , Mutation/genetics , Presenilin-1/geneticsABSTRACT
PURPOSE: Positron emission tomography (PET) provides in vivo quantification of amyloid-ß (Aß) pathology. Established methods for assessing Aß burden can be affected by physiological and technical factors. Novel, data-driven metrics have been developed to account for these sources of variability. We aimed to evaluate the performance of four of these amyloid PET metrics against conventional techniques, using a common set of criteria. METHODS: Three cohorts were used for evaluation: Insight 46 (N=464, [18F]florbetapir), AIBL (N=277, [18F]flutemetamol), and an independent test-retest data (N=10, [18F]flutemetamol). Established metrics of amyloid tracer uptake included the Centiloid (CL) and where dynamic data was available, the non-displaceable binding potential (BPND). The four data-driven metrics computed were the amyloid load (Aß load), the Aß-PET pathology accumulation index (Aß index), the Centiloid derived from non-negative matrix factorisation (CLNMF), and the amyloid pattern similarity score (AMPSS). These metrics were evaluated using reliability and repeatability in test-retest data, associations with BPND and CL, variability of the rate of change and sample size estimates to detect a 25% slowing in Aß accumulation. RESULTS: All metrics showed good reliability. Aß load, Aß index and CLNMF were strong associated with the BPND. The associations with CL suggest that cross-sectional measures of CLNMF, Aß index and Aß load are robust across studies. Sample size estimates for secondary prevention trial scenarios were the lowest for CLNMF and Aß load compared to the CL. CONCLUSION: Among the novel data-driven metrics evaluated, the Aß load, the Aß index and the CLNMF can provide comparable performance to more established quantification methods of Aß PET tracer uptake. The CLNMF and Aß load could offer a more precise alternative to CL, although further studies in larger cohorts should be conducted.
Subject(s)
Amyloid beta-Peptides , Benchmarking , Humans , Cross-Sectional Studies , Reproducibility of Results , Positron-Emission TomographyABSTRACT
BACKGROUND: Neurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches. METHODS: In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission. We included 392 mutation carriers (157 GRN, 164 C9orf72, 71 MAPT), together with 276 non-carrier cognitively healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in mutation carriers (relative to HC) are correlated with specific neurotransmitter systems in prodromal (CDR® plus NACC FTLD = 0.5) and in symptomatic (CDR® plus NACC FTLD≥1) FTD. RESULTS: In prodromal stages of C9orf72 disease, voxel-based brain changes were significantly associated with spatial distribution of dopamine and acetylcholine pathways; in prodromal MAPT disease with dopamine and serotonin pathways, while in prodromal GRN disease no significant findings were reported (p < 0.05, Family Wise Error corrected). In symptomatic FTD, a widespread involvement of dopamine, serotonin, glutamate and acetylcholine pathways across all genetic subtypes was found. Social cognition scores, loss of empathy and poor response to emotional cues were found to correlate with the strength of GMV colocalization of dopamine and serotonin pathways (all p < 0.01). CONCLUSIONS: This study, indirectly assessing neurotransmitter deficits in monogenic FTD, provides novel insight into disease mechanisms and might suggest potential therapeutic targets to counteract disease-related symptoms.
Subject(s)
Frontotemporal Dementia , Pick Disease of the Brain , Humans , Frontotemporal Dementia/diagnostic imaging , Frontotemporal Dementia/genetics , C9orf72 Protein/genetics , Acetylcholine , Dopamine , Serotonin , Mutation , Magnetic Resonance Imaging/methods , tau Proteins/geneticsABSTRACT
Carriers of mutations responsible for dominantly inherited Alzheimer disease provide a unique opportunity to study potential imaging biomarkers. Biomarkers based on routinely acquired clinical MR images, could supplement the extant invasive or logistically challenging) biomarker studies. We used 1104 longitudinal MR, 324 amyloid beta, and 87 tau positron emission tomography imaging sessions from 525 participants enrolled in the Dominantly Inherited Alzheimer Network Observational Study to extract novel imaging metrics representing the mean (µ) and standard deviation (σ) of standardized image intensities of T1-weighted and Fluid attenuated inversion recovery (FLAIR) MR scans. There was an exponential decrease in FLAIR-µ in mutation carriers and an increase in FLAIR and T1 signal heterogeneity (T1-σ and FLAIR-σ) as participants approached the symptom onset in both supramarginal, the right postcentral and right superior temporal gyri as well as both caudate nuclei, putamina, thalami, and amygdalae. After controlling for the effect of regional atrophy, FLAIR-µ decreased and T1-σ and FLAIR-σ increased with increasing amyloid beta and tau deposition in numerous cortical regions. In symptomatic mutation carriers and independent of the effect of regional atrophy, tau pathology demonstrated a stronger relationship with image intensity metrics, compared with amyloid pathology. We propose novel MR imaging intensity-based metrics using standard clinical T1 and FLAIR images which strongly associates with the progression of pathology in dominantly inherited Alzheimer disease. We suggest that tau pathology may be a key driver of the observed changes in this cohort of patients.
Subject(s)
Alzheimer Disease , Humans , Alzheimer Disease/diagnostic imaging , Alzheimer Disease/genetics , Alzheimer Disease/complications , Amyloid beta-Peptides , Magnetic Resonance Imaging/methods , Positron-Emission Tomography , Biomarkers , Atrophy , tau ProteinsABSTRACT
BACKGROUND: Current clinical rating scales in frontotemporal dementia (FTD) often do not incorporate neuropsychiatric features and may therefore inadequately measure disease stage. METHODS: 832 participants from the Genetic FTD Initiative (GENFI) were recruited: 522 mutation carriers and 310 mutation-negative controls. The standardised GENFI clinical questionnaire assessed the frequency and severity of 14 neuropsychiatric symptoms: visual, auditory, and tactile hallucinations, delusions, depression, anxiety, irritability/lability, agitation/aggression, euphoria/elation, aberrant motor behaviour, hypersexuality, hyperreligiosity, impaired sleep, and altered sense of humour. A principal component analysis (PCA) was performed to identify key groupings of neuropsychiatric and behavioural items in order to create a new neuropsychiatric module that could be used as an addition to the Clinical Dementia Rating (CDR) plus National Alzheimer's Coordinating Center Behaviour and Language Domains (NACC FTLD) rating scale. RESULTS: Overall, 46.4% of mutation carriers had neuropsychiatric symptoms (51.6% C9orf72, 40.8% GRN, 46.6% MAPT) compared with 24.5% of controls. Anxiety and depression were the most common in all genetic groups but fluctuated longitudinally and loaded separately in the PCA. Hallucinations and delusions loaded together, with the remaining neuropsychiatric symptoms loading with the core behavioural features of FTD. These results suggest using a single 'psychosis' neuropsychiatric module consisting of hallucinations and delusions. Adding this to the CDR plus NACC FTLD, called the CDR plus NACC FTLD-N, leads to a number of participants being scored more severely, including those who were previously considered asymptomatic now being scored as prodromal. CONCLUSIONS: Neuropsychiatric symptoms occur in mutation carriers at all disease stages across all three genetic groups. However, only psychosis features provided additional staging benefit to the CDR plus NACC FTLD. Inclusion of these features brings us closer to optimising the rating scale for use in trials.
Subject(s)
Frontotemporal Dementia , Psychotic Disorders , Humans , Frontotemporal Dementia/diagnosis , Frontotemporal Dementia/genetics , Hallucinations/genetics , Mental Status and Dementia Tests , AnxietyABSTRACT
Deposition of amyloid and tau pathology can be quantified in vivo using positron emission tomography (PET). Accurate longitudinal measurements of accumulation from these images are critical for characterizing the start and spread of the disease. However, these measurements are challenging; precision and accuracy can be affected substantially by various sources of errors and variability. This review, supported by a systematic search of the literature, summarizes the current design and methodologies of longitudinal PET studies. Intrinsic, biological causes of variability of the Alzheimer's disease (AD) protein load over time are then detailed. Technical factors contributing to longitudinal PET measurement uncertainty are highlighted, followed by suggestions for mitigating these factors, including possible techniques that leverage shared information between serial scans. Controlling for intrinsic variability and reducing measurement uncertainty in longitudinal PET pipelines will provide more accurate and precise markers of disease evolution, improve clinical trial design, and aid therapy response monitoring.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Humans , Alzheimer Disease/pathology , tau Proteins/metabolism , Amyloid beta-Peptides/metabolism , Positron-Emission Tomography/methods , Amyloidogenic Proteins/metabolism , Cognitive Dysfunction/metabolism , Brain/pathologyABSTRACT
INTRODUCTION: In Alzheimer's disease (AD), hyperphosphorylated tau is closely associated with focal neurodegeneration, but the mechanism remains uncertain. METHODS: We quantified cortical microstructure using neurite orientation dispersion and density imaging in 14 individuals with young onset AD. Diffusion tensor imaging measured mean diffusivity (MD). Amyloid beta and tau positron emission tomography were acquired and associations with microstructural measures were assessed. RESULTS: When regional volume was adjusted for, in the medial temporal lobe there was a significant negative association between neurite density and tau (partial R2 = 0.56, p = 0.008) and between orientation dispersion and tau (partial R2 = 0.66, p = 0.002), but not between MD and tau. In a wider cortical composite, there was an association between orientation dispersion and tau (partial R2 = 0.43, p = 0.030), but not between other measures and tau. DISCUSSION: Our findings are consistent with tau causing first dendritic pruning (reducing dispersion/complexity) followed by neuronal loss. Advanced magnetic resonance imaging (MRI) microstructural measures have the potential to provide information relating to underlying tau deposition.
Subject(s)
Alzheimer Disease , Humans , Alzheimer Disease/diagnostic imaging , Alzheimer Disease/pathology , Neurites , Diffusion Tensor Imaging/methods , Amyloid beta-Peptides , Magnetic Resonance Imaging/methods , Positron-Emission Tomography/methods , Biomarkers , tau ProteinsABSTRACT
BACKGROUND: Accelerated Long-term Forgetting (ALF) is the phenomenon whereby material is retained normally over short intervals (minutes or hours) but forgotten abnormally rapidly over longer periods (days or weeks). ALF may be an early marker of cognitive decline, but little is known about its relationships with preclinical Alzheimer's disease pathology in older adults, and how memory selectivity may influence which material is forgotten. METHOD: Participants in 'Insight 46', a sub-study of the MRC National Survey of Health and Development (British 1946 birth cohort), completed cognitive and neuroimaging assessments at two time-points (baseline at age â¼70; follow-up â¼2.4 years later). At follow-up, we assessed Complex Figure Drawing (copy; immediate recall; 30-minute recall; 7-day recall). Complex Figure items were categorized as 'outline' or 'detail' (Fig1), to test the hypothesis that forgetting the outline of the structure would be more sensitive to the effect of brain pathologies. ALF scores were calculated as the proportion of material retained after 7 days, relative to 30 minutes. Rates of cerebral atrophy between baseline and follow-up were quantified from T1-weighted MRI using the Brain Boundary Shift Integral (BBSI). ß-amyloid status (positive/negative) was determined from 18F-Florbetapir-PET. Baseline serum neurofilament light (NfL) was quantified (Quanterix Simoa assay). Multivariable regression models were used to investigate the effects (mutually adjusted) of ß-amyloid status, BBSI and NfL on ALF in n = 316 clinically-normal individuals (50% female; 22% ß-amyloid positive; 30% APOE-ε4 carriers), and to explore interactions between these predictors, adjusting for potential confounders including prospectively-collected childhood cognitive ability and education. RESULT: 'Outline' items were better retained than 'detail' (Fig1). ß-amyloid-positive participants had poorer ALF scores for 'outline' (but not 'detail') items (Fig1C; Table 1). Unexpectedly, higher NfL was associated with scores for 'outline' items (Table 1). Greater rate of cerebral atrophy predicted poorer retention among participants with elevated ß-amyloid and higher NfL (Table 1; Fig2). CONCLUSION: These results provide evidence of associations between biomarkers of brain pathologies and ALF in 73-year-olds. Interactions between different biomarkers merit further exploration. ALF may be a sensitive outcome measure for therapeutic trials in preclinical AD. Better retention of 'outline' (vs. 'detail') items illustrates the strategic role of memory selectivity.
Subject(s)
Alzheimer Disease , Magnetic Resonance Imaging , Humans , Female , Male , Aged , Alzheimer Disease/pathology , Alzheimer Disease/diagnostic imaging , Neuropsychological Tests/statistics & numerical data , Brain/diagnostic imaging , Brain/pathology , Atrophy/pathology , Cognitive Dysfunction , Memory Disorders , Aniline Compounds , Neurofilament Proteins/blood , Ethylene Glycols , Amyloid beta-Peptides/metabolism , Mental Recall/physiologyABSTRACT
BACKGROUND: Semantic and socioemotional knowledge, including person recognition, can be altered in frontotemporal dementia (FTD), and is often associated with the right temporal lobe variant. Using data from the Genetic FTD Initiative, we investigated person recognition deficits in genetic FTD. METHOD: 901 GENFI participants (279 mutation negative controls, 280 C9orf72 mutation carriers (MCs), 101 MAPTMCs and 241 GRN MCs) were grouped using the Clinical Dementia Rating scale plus National Alzheimer's Coordinating Centre Frontotemporal Lobar Degeneration (CDR plus NACC FTLD) global score where 0 denotes asymptomatic, 0.5 as prodromal, and 1+ as mild to severe symptoms (C9orf72: 135 = 0, 48 = 0.5, 97 = 1+; GRN: 143 = 0, 35 = 0.5, 63 = 1+; MAPT: 50 = 0, 20 = 0.5, 31 = 1+). Person recognition (PR) was assessed using a single question within a structured clinical questionnaire, scoring the ability to recognise people who should be familiar by face or voice to them, with a value between 0 (absent) to 3 (severe), similar to the CDR scale. The percentage of participants with PR deficits was calculated for each group. Logistic regression with bootstrapping compared the PR score between groups with age, gender, and education as covariates. RESULT: 16.1% of C9orf72 MCs (0 = 0.7%, 0.5 = 2.1%, 1+ = 44.3%), 7.5% of GRN (0 = 0.0%, 0.5 = 8.6%, 1+ = 23.8%) and 17.8% of MAPT carriers (0 = 2%, 0.5 = 10%, 1+ = 48.4%) showed PR deficits. Mean (standard deviation) severity in each group was: C9orf72 0 = 0.0(0.0), 0.5 = 0.0(0.1), 1+ = 0.6(0.9); GRN 0 = 0.0(0.0), 0.5 = 0.0(0.1), 1+ = 0.2(0.6); MAPT 0 = 0.0(0.2), 0.5 = 0.1(0.3), 1+ = 0.6(0.8). Each of the symptomatic genetic groups had a significantly greater PR deficit than the control group (p<0.001), with the prodromal MAPT (p = 0.006) and GRN (p<0.001) groups also showing a greater impairment than controls. There was a trend to significance in the C9orf72asymptomatic and prodromal groups compared with controls (p = 0.058 and p = 0.059 respectively). Symptomatic C9orf72 and MAPT carriers showed greater impairment than the symptomatic GRN carriers (both p = 0.005). CONCLUSION: Person recognition is a key early marker of disease in some individuals with genetic FTD and further imaging analyses will help to reveal the underlying mechanism of this deficit.
Subject(s)
C9orf72 Protein , Frontotemporal Dementia , Progranulins , tau Proteins , Humans , Male , Female , C9orf72 Protein/genetics , tau Proteins/genetics , Frontotemporal Dementia/genetics , Middle Aged , Progranulins/genetics , Aged , Mutation , Neuropsychological Tests/statistics & numerical data , Recognition, Psychology/physiologyABSTRACT
INTRODUCTION: As the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others. METHODS: We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation. RESULTS: Three primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors. DISCUSSION: These results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.
Subject(s)
Alzheimer Disease , Humans , Alzheimer Disease/diagnosis , Amyloid beta-Peptides/cerebrospinal fluid , Amyloidogenic Proteins , Biomarkers/cerebrospinal fluid , Cross-Sectional Studies , Inflammation , tau Proteins/genetics , tau Proteins/cerebrospinal fluidABSTRACT
Alzheimer's disease has a preclinical stage when cerebral amyloid-ß deposition occurs before symptoms emerge, and when amyloid-ß-targeted therapies may have maximum benefits. Existing amyloid-ß status measurement techniques, including amyloid PET and CSF testing, are difficult to deploy at scale, so blood biomarkers are increasingly considered for screening. We compared three different blood-based techniques-liquid chromatography-mass spectrometry measures of plasma amyloid-ß, and single molecule array (Simoa) measures of plasma amyloid-ß and phospho-tau181-to detect cortical 18F-florbetapir amyloid PET positivity (defined as a standardized uptake value ratio of >0.61 between a predefined cortical region of interest and eroded subcortical white matter) in dementia-free members of Insight 46, a substudy of the population-based British 1946 birth cohort. We used logistic regression models with blood biomarkers as predictors of amyloid PET status, with or without age, sex and APOE ε4 carrier status as covariates. We generated receiver operating characteristics curves and quantified areas under the curves to compare the concordance of the different blood tests with amyloid PET. We determined blood test cut-off points using Youden's index, then estimated numbers needed to screen to obtain 100 amyloid PET-positive individuals. Of the 502 individuals assessed, 441 dementia-free individuals with complete data were included; 82 (18.6%) were amyloid PET-positive. The area under the curve for amyloid PET status using a base model comprising age, sex and APOE ε4 carrier status was 0.695 (95% confidence interval: 0.628-0.762). The two best-performing Simoa plasma biomarkers were amyloid-ß42/40 (0.620; 0.548-0.691) and phospho-tau181 (0.707; 0.646-0.768), but neither outperformed the base model. Mass spectrometry plasma measures performed significantly better than any other measure (amyloid-ß1-42/1-40: 0.817; 0.770-0.864 and amyloid-ß composite: 0.820; 0.775-0.866). At a cut-off point of 0.095, mass spectrometry measures of amyloid-ß1-42/1-40 detected amyloid PET positivity with 86.6% sensitivity and 71.9% specificity. Without screening, to obtain 100 PET-positive individuals from a population with similar amyloid PET positivity prevalence to Insight 46, 543 PET scans would need to be performed. Screening using age, sex and APOE ε4 status would require 940 individuals, of whom 266 would proceed to scan. Using mass spectrometry amyloid-ß1-42/1-40 alone would reduce these numbers to 623 individuals and 243 individuals, respectively. Across a theoretical range of amyloid PET positivity prevalence of 10-50%, mass spectrometry measures of amyloid-ß1-42/1-40 would consistently reduce the numbers proceeding to scans, with greater cost savings demonstrated at lower prevalence.
Subject(s)
Alzheimer Disease/blood , Alzheimer Disease/diagnosis , Amyloid beta-Peptides/blood , Peptide Fragments/blood , Aged , Alzheimer Disease/metabolism , Biomarkers/blood , Early Diagnosis , Female , Hematologic Tests/methods , Humans , Male , Prospective Studies , Sensitivity and SpecificityABSTRACT
Accurate regional brain quantitative PET measurements, particularly when using partial volume correction, rely on robust image registration between PET and MR images. We argue here that the precision, and hence the uncertainty, of MR-PET image registration is mainly driven by the registration implementation and the quality of PET images due to their lower resolution and higher noise compared to the structural MR images. We propose a dedicated uncertainty analysis for quantifying the precision of MR-PET registration, centred around the bootstrap resampling of PET list-mode events to generate multiple PET image realisations with different noise (count) levels. The effects of PET image reconstruction parameters, such as the use of attenuation and scatter corrections and different number of iterations, on the precision and accuracy of MR-PET registration were investigated. In addition, the performance of four software packages with their default settings for rigid inter-modality image registration were considered: NiftyReg, Vinci, FSL and SPM. Four distinct PET image distributions made of two early time frames (similar to cortical FDG) and two late frames using two amyloid PET dynamic acquisitions of one amyloid positive and one amyloid negative participants were investigated. For the investigated four PET frames, the biggest impact on the uncertainty was observed between registration software packages (up to 10-fold difference in precision) followed by the reconstruction parameters. On average, the lowest uncertainty for different PET frames and brain regions was observed with SPM and two iterations of fully quantitative image reconstruction. The observed uncertainty for the varying PET count-level (from 5% to 60%) was slightly lower than for the reconstruction parameters. We also observed that the registration uncertainty in quantitative PET analysis depends on amyloid status of the considered PET frames, with increased uncertainty (up to three times) when using post-reconstruction partial volume correction. This analysis is applicable for PET data obtained from either PET/MR or PET/CT scanners.
Subject(s)
Brain/diagnostic imaging , Brain/metabolism , Image Processing, Computer-Assisted/standards , Magnetic Resonance Imaging/standards , Positron-Emission Tomography/standards , Uncertainty , Aged , Cohort Studies , Female , Humans , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Positron-Emission Tomography/methodsABSTRACT
OBJECTIVE: To investigate subjective cognitive decline (SCD) in relation to ß-amyloid pathology and to test for associations with anxiety, depression, objective cognition and family history of dementia in the Insight 46 study. METHODS: Cognitively unimpaired ~70-year-old participants, all born in the same week in 1946 (n=460, 49% female, 18% amyloid-positive), underwent assessments including the SCD-Questionnaire (MyCog). MyCog scores were evaluated with respect to 18F-Florbetapir-PET amyloid status (positive/negative). Associations with anxiety, depression, objective cognition (measured by the Preclinical Alzheimer Cognitive Composite, PACC) and family history of dementia were also investigated. The informant's perspective on SCD was evaluated in relation to MyCog score. RESULTS: Anxiety (mean (SD) trait anxiety score: 4.4 (3.9)) was associated with higher MyCog scores, especially in women. MyCog scores were higher in amyloid-positive compared with amyloid-negative individuals (adjusted means (95% CIs): 5.3 (4.4 to 6.1) vs 4.3 (3.9 to 4.7), p=0.044), after accounting for differences in anxiety. PACC (mean (SD) -0.05 (0.68)) and family history of dementia (prevalence: 23.9%) were not independently associated with MyCog scores. The informant's perception of SCD was generally in accordance with that of the participant. CONCLUSIONS: This cross-sectional study demonstrates that symptoms of SCD are associated with both ß-amyloid pathology, and more consistently, trait anxiety in a population-based cohort of older adults, at an age when those who are destined to develop dementia are still likely to be some years away from symptoms. This highlights the necessity of considering anxiety symptoms when assessing Alzheimer's disease pathology and SCD.
Subject(s)
Amyloid beta-Peptides/metabolism , Anxiety/psychology , Cognition/physiology , Depression/psychology , Mental Health , Aged , Anxiety/diagnostic imaging , Anxiety/metabolism , Brain/diagnostic imaging , Brain/metabolism , Cross-Sectional Studies , Depression/diagnostic imaging , Depression/metabolism , Female , Humans , Magnetic Resonance Imaging , Male , Neuropsychological Tests , Positron-Emission TomographyABSTRACT
INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease. METHODS: Longitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non-carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status. RESULTS: The Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R2 = 0.95), fluorodeoxyglucose (R2 = 0.93), and atrophy (R2 = 0.95) in mutation carriers compared to non-carriers. DISCUSSION: Results suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions.