Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed.

METHOD

Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis.

RESULTS

Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others.

CONCLUSIONS

This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.

Successful treatment of respiratory failure in Hirayama disease

Hirayama disease is a self-limiting cervical motor neuron disease, usually affecting the spinal cord at level C7-T1. We share an unusual case of Hirayama disease in a young man affecting roots C4-C6. He presented in coma due to diaphragm weakness and hypercapnic respiratory failure. Diagnosis was achieved via clinical presentation, neurophysiological examination, ultrasonography of the diaphragm and dynamic MR-imaging. Conservative treatment with a cervical collar resulted in remarkable improvement in respiratory and motor function.

Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning

BACKGROUND

Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences.

METHODS

We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects.

RESULTS

Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers.

CONCLUSIONS

These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.

Multiomics profiling of human plasma and cerebrospinal fluid reveals ATN-derived networks and highlights causal links in Alzheimer's disease

INTRODUCTION

This study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD.

METHODS

Using the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR).

RESULTS

AT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform.

DISCUSSION

This study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates.

Cerebral blood flow, amyloid burden, and cognition in cognitively normal individuals

PURPOSE

The role of cerebral blood flow (CBF) in the early stages of Alzheimer's disease is complex and largely unknown. We investigated cross-sectional and longitudinal associations between CBF, amyloid burden, and cognition, in cognitively normal individuals with subjective cognitive decline (SCD).

METHODS

We included 187 cognitively normal individuals with SCD from the SCIENCe project (65 ± 8 years, 39% F, MMSE 29 ± 1). Each underwent a dynamic (0-70 min) [18F]florbetapir PET and T1-weighted MRI scan, enabling calculation of mean binding potential (BPND; specific amyloid binding) and R1 (measure of relative (r)CBF). Eighty-three individuals underwent a second [18F]florbetapir PET (2.6 ± 0.7 years). Participants annually underwent neuropsychological assessment (follow-up time 3.8 ± 3.1 years; number of observations n = 774).

RESULTS

A low baseline R1 was associated with steeper decline on tests addressing memory, attention, and global cognition (range betas 0.01 to 0.27, p < 0.05). High BPND was associated with steeper decline on tests covering all domains (range betas - 0.004 to - 0.70, p < 0.05). When both predictors were simultaneously added to the model, associations remained essentially unchanged. Additionally, we found longitudinal associations between R1 and BPND. High baseline BPND predicted decline over time in R1 (all regions, range betasBP×time - 0.09 to - 0.14, p < 0.05). Vice versa, low baseline R1 predicted increase in BPND in frontal, temporal, and composite ROIs over time (range betasR1×time - 0.03 to - 0.08, p < 0.05).

CONCLUSION

Our results suggest that amyloid accumulation and decrease in rCBF are two parallel disease processes without a fixed order, both providing unique predictive information for cognitive decline and each process enhancing the other longitudinally.

Cerebrospinal fluid proteomic profiling of individuals with mild cognitive impairment and suspected non-Alzheimer's disease pathophysiology

BACKGROUND

Suspected non-Alzheimer's disease pathophysiology (SNAP) is a biomarker concept that encompasses individuals with neuronal injury but without amyloidosis. We aim to investigate the pathophysiology of SNAP, defined as abnormal tau without amyloidosis, in individuals with mild cognitive impairment (MCI) by cerebrospinal fluid (CSF) proteomics.

METHODS

Individuals were classified based on CSF amyloid beta (Aβ)1-42 (A) and phosphorylated tau (T), as cognitively normal A-T- (CN), MCI A-T+ (MCI-SNAP), and MCI A+T+ (MCI-AD). Proteomics analyses, Gene Ontology (GO), brain cell expression, and gene expression analyses in brain regions of interest were performed.

RESULTS

A total of 96 proteins were decreased in MCI-SNAP compared to CN and MCI-AD. These proteins were enriched for extracellular matrix (ECM), hemostasis, immune system, protein processing/degradation, lipids, and synapse. Fifty-one percent were enriched for expression in the choroid plexus.

CONCLUSION

The pathophysiology of MCI-SNAP (A-T+) is distinct from that of MCI-AD. Our findings highlight the need for a different treatment in MCI-SNAP compared to MCI-AD.

Rare variants in IFFO1, DTNB, NLRC3 and SLC22A10 associate with Alzheimer's disease CSF profile of neuronal injury and inflammation

Alzheimer's disease (AD) biomarkers represent several neurodegenerative processes, such as synaptic dysfunction, neuronal inflammation and injury, as well as amyloid pathology. We performed an exome-wide rare variant analysis of six AD biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and Neurogranin) to discover genes associated with these markers. Genetic and biomarker information was available for 480 participants from two studies: EMIF-AD and ADNI. We applied a principal component (PC) analysis to derive biomarkers combinations, which represent statistically independent biological processes. We then tested whether rare variants in 9576 protein-coding genes associate with these PCs using a Meta-SKAT test. We also tested whether the PCs are intermediary to gene effects on AD symptoms with a SMUT test. One PC loaded on NfL and YKL-40, indicators of neuronal injury and inflammation. Four genes were associated with this PC: IFFO1, DTNB, NLRC3, and SLC22A10. Mediation tests suggest, that these genes also affect dementia symptoms via inflammation/injury. We also observed an association between a PC loading on Neurogranin, a marker for synaptic functioning, with GABBR2 and CASZ1, but no mediation effects. The results suggest that rare variants in IFFO1, DTNB, NLRC3, and SLC22A10 heighten susceptibility to neuronal injury and inflammation, potentially by altering cytoskeleton structure and immune activity disinhibition, resulting in an elevated dementia risk. GABBR2 and CASZ1 were associated with synaptic functioning, but mediation analyses suggest that the effect of these two genes on synaptic functioning is not consequential for AD development.

Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort

BACKGROUND

physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives.

METHODS

We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD.

RESULTS

In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046).

CONCLUSIONS

metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.

Amyloid-driven disruption of default mode network connectivity in cognitively healthy individuals

Cortical accumulation of amyloid beta is one of the first events of Alzheimer’s disease pathophysiology, and has been suggested to follow a consistent spatiotemporal ordering, starting in the posterior cingulate cortex, precuneus and medio-orbitofrontal cortex. These regions overlap with those of the default mode network, a brain network also involved in memory functions. Aberrant default mode network functional connectivity and higher network sparsity have been reported in prodromal and clinical Alzheimer’s disease. We investigated the association between amyloid burden and default mode network connectivity in the preclinical stage of Alzheimer’s disease and its association with longitudinal memory decline. We included 173 participants, in which amyloid burden was assessed both in CSF by the amyloid beta 42/40 ratio, capturing the soluble part of amyloid pathology, and in dynamic PET scans calculating the non-displaceable binding potential in early-stage regions. The default mode network was identified with resting-state functional MRI. Then, we calculated functional connectivity in the default mode network, derived from independent component analysis, and eigenvector centrality, a graph measure recursively defining important nodes on the base of their connection with other important nodes. Memory was tested at baseline, 2- and 4-year follow-up. We demonstrated that higher amyloid burden as measured by both CSF amyloid beta 42/40 ratio and non-displaceable binding potential in the posterior cingulate cortex was associated with lower functional connectivity in the default mode network. The association between amyloid burden (CSF and non-displaceable binding potential in the posterior cingulate cortex) and aberrant default mode network connectivity was confirmed at the voxel level with both functional connectivity and eigenvector centrality measures, and it was driven by voxel clusters localized in the precuneus, cingulate, angular and left middle temporal gyri. Moreover, we demonstrated that functional connectivity in the default mode network predicts longitudinal memory decline synergistically with regional amyloid burden, as measured by non-displaceable binding potential in the posterior cingulate cortex. Taken together, these results suggest that early amyloid beta deposition is associated with aberrant default mode network connectivity in cognitively healthy individuals and that default mode network connectivity markers can be used to identify subjects at risk of memory decline.

TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels

INTRODUCTION

Neurofilament light (NfL), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are biomarkers for Alzheimer's disease (AD) to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively.

METHODS

We performed genome-wide association studies (GWAS) using DNA and cerebrospinal fluid (CSF) samples from the EMIF-AD Multimodal Biomarker Discovery study for discovery, and the Alzheimer's Disease Neuroimaging Initiative study for validation analyses. GWAS were performed for all three CSF biomarkers using linear regression models adjusting for relevant covariates.

RESULTS

We identify novel genome-wide significant associations between DNA variants in TMEM106B and CSF levels of NfL, and between CPOX and YKL-40. We confirm previous work suggesting that YKL-40 levels are associated with DNA variants in CHI3L1.

DISCUSSION

Our study provides important new insights into the genetic architecture underlying interindividual variation in three AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

Replication study of plasma proteins relating to Alzheimer's pathology

INTRODUCTION

This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis.

METHODS

Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively.

RESULTS

Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis.

DISCUSSION

Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.

Onset of Preclinical Alzheimer Disease in Monozygotic Twins

Objective

The present work was undertaken to study the genetic contribution to the start of Alzheimer's disease (AD) with amyloid and tau biomarkers in cognitively intact older identical twins.

Methods

We studied in 96 monozygotic twin‐pairs relationships between amyloid‐beta (Aβ) aggregation as measured by the Aβ1–42/1–40 ratio in cerebrospinal fluid (CSF; n = 126) and positron emission tomography (PET, n = 194), and CSF markers for Aβ production (beta‐secretase 1, Aβ1–40, and Aβ1–38) and CSF tau. Associations among markers were tested with generalized estimating equations including a random effect for twin status, adjusted for age, gender, and apolipoprotein E ε4 genotype. We used twin analyses to determine relative contributions of genetic and/or environmental factors to AD pathophysiological processes.

Results

Twenty‐seven individuals (14%) had an abnormal amyloid PET, and 14 twin‐pairs (15%) showed discordant amyloid PET scans. Within twin‐pairs, Aβ production markers and total‐tau (t‐tau) levels strongly correlated (r range = 0.73–0.86, all p < 0.0001), and Aβ aggregation markers and 181‐phosphorylated‐tau (p‐tau) levels correlated moderately strongly (r range = 0.50–0.64, all p < 0.0001). Cross‐twin cross‐trait analysis showed that Aβ1–38 in one twin correlated with Aβ1–42/1–40 ratios, and t‐tau and p‐tau levels in their cotwins (r range = −0.28 to 0.58, all p < .007). Within‐pair differences in Aβ production markers related to differences in tau levels (r range = 0.49–0.61, all p < 0.0001). Twin discordance analyses suggest that Aβ production and tau levels show coordinated increases in very early AD.

Interpretation

Our results suggest a substantial genetic/shared environmental background contributes to both Aβ and tau increases, suggesting that modulation of environmental risk factors may aid in delaying the onset of AD pathophysiological processes. ANN NEUROL 2021;89:987–1000

Amyloid-β, cortical thickness, and subsequent cognitive decline in cognitively normal oldest-old

Objective

To investigate the relationship between amyloid‐β (Aβ) deposition and markers of brain structure on cognitive decline in oldest‐old individuals with initial normal cognition.

Methods

We studied cognitive functioning in four domains at baseline and change over time in fifty‐seven cognitively intact individuals from the EMIF‐AD 90+ study. Predictors were Aβ status determined by [¹⁸F]‐flutemetamol PET (normal = Aβ − vs. abnormal = Aβ+), cortical thickness in 34 regions and hippocampal volume. Mediation analyses were performed to test whether effects of Aβ on cognitive decline were mediated by atrophy of specific anatomical brain areas.

Results

Subjects had a mean age of 92.7 ± 2.9 years, of whom 19 (33%) were Aβ+. Compared to Aβ−, Aβ+ individuals showed steeper decline on memory (β ± SE = −0.26 ± 0.09), and processing speed (β ± SE = −0.18 ± 0.08) performance over 1.5 years (P < 0.05). Furthermore, medial and lateral temporal lobe atrophy was associated with steeper decline in memory and language across individuals. Mediation analyses revealed that part of the memory decline observed in Aβ+ individuals was mediated through parahippocampal atrophy.

Interpretation

These results show that Aβ abnormality even in the oldest old with initially normal cognition is not part of normal aging, but is associated with a decline in cognitive functioning. Other pathologies may also contribute to decline in the oldest old as cortical thickness predicted cognitive decline similarly in individuals with and without Aβ pathology.

Are Apathy and Depressive Symptoms Related to Vascular White Matter Hyperintensities in Severe Late Life Depression?

OBJECTIVE

Apathy symptoms are defined as a lack of interest and motivation. Patients with late-life depression (LLD) also suffer from lack of interest and motivation and previous studies have linked apathy to vascular white matter hyperintensities (WMH) of the brain in depressed and nondepressed patients. The aim of this study was to investigate the relationship between apathy symptoms, depressive symptoms, and WMH in LLD. We hypothesize that late-onset depression (LOD; first episode of depression after 55 years of age) is associated with WMH and apathy symptoms.

METHODS

Apathy scores were collected for 87 inpatients diagnosed with LLD. Eighty patients underwent brain magnetic resonance imaging. Associations between depressive and apathy symptoms and WMH were analyzed using linear regression.

RESULTS

All 3 subdomains of the 10-item Montgomery-Åsberg Depression Rating Scale correlated significantly with the apathy scale score (all P < .05). In the total sample, apathy nor depressive symptoms were related to specific WMH. In LOD only, periventricular WMH were associated with depression severity (β = 5.21, P = .04), while WMH in the left infratentorial region were associated with apathy symptoms (β coefficient = 5.89, P = .03).

CONCLUSION

Apathy and depressive symptoms are highly overlapping in the current cohort of older patients with severe LLD, leading to the hypothesis that apathy symptoms are part of depressive symptoms in the symptom profile of older patients with severe LLD. Neither apathy nor depressive symptoms were related to WMH, suggesting that radiological markers of cerebrovascular disease, such as WMH, may not be useful in predicting these symptoms in severe LLD.

Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

What determines cognitive functioning in the oldest-old? The EMIF-AD 90+ Study

OBJECTIVES

Determinants of cognitive functioning in individuals aged 90 years and older, the oldest-old, remain poorly understood. We aimed to establish the association of risk factors, white matter hyperintensities (WMH), hippocampal atrophy and amyloid aggregation with cognition in the oldest-old.

METHODS

We included 84 individuals without cognitive impairment and 38 individuals with cognitive impairment from the EMIF-AD 90+ Study (mean age 92.4 years) and tested cross-sectional associations between risk factors (cognitive activity, physical parameters, nutritional status, inflammatory markers and cardiovascular risk factors), brain pathology biomarkers (WMH and hippocampal volume on MRI, and amyloid binding measured with PET) and cognition. Additionally, we tested whether the brain pathology biomarkers were independently associated with cognition. When applicable, we tested whether the effect of risk factors on cognition was mediated by brain pathology.

RESULTS

Lower values for handgrip strength, Short Physical Performance Battery (SPPB), nutritional status, HbA1c and hippocampal volume, and higher values for WMH volume and amyloid binding were associated with worse cognition. Higher past cognitive activity and lower BMI were associated with increased amyloid binding, lower muscle mass with more WMH, and lower SPPB scores with more WMH and hippocampal atrophy. The brain pathology markers were independently associated with cognition. The association of SPPB with cognition was partially mediated by hippocampal volume.

DISCUSSION

In the oldest-old, physical parameters, nutritional status, HbA1c, WMH, hippocampal atrophy and amyloid binding are associated with cognitive impairment. Physical performance may affect cognition through hippocampal atrophy. This study highlights the importance to consider multiple factors when assessing cognition in the oldest-old.

Ocular biomarkers for cognitive impairment in nonagenarians; a prospective cross-sectional study

Background

Ocular imaging receives much attention as a source of potential biomarkers for dementia. In the present study, we analyze these ocular biomarkers in cognitively impaired and healthy participants in a population aged over 90 years (= nonagenarian), and elucidate the effects of age on these biomarkers.

Methods

For this prospective cross-sectional study, we included individuals from the EMIF-AD 90+ study, consisting of a cognitively healthy (N = 67) and cognitively impaired group (N = 33), and the EMIF-AD PreclinAD study, consisting of cognitively healthy controls aged ≥60 (N = 198). Participants underwent Optical Coherence Tomography (OCT) and fundus photography of both eyes. OCT was used to asses total and individual inner retinal layer thickness in the macular region (Early Treatment Diabetic Retinopathy Study circles) as well as peripapillary retinal nerve fiber layer thickness, fundus images were analyzed with Singapore I Vessel Assessment to obtain 7 retinal vascular parameters. Values for both eyes were averaged. Differences in ocular biomarkers between the 2 nonagenarian groups were analyzed using linear regression, differences between the individual nonagenarian groups and controls were analyzed using generalized estimating equations.

Results

Ocular biomarkers did not differ between the healthy and cognitively impaired nonagenarian groups. 19 out of 22 ocular biomarkers assessed in this study differed between either nonagenarian group and the younger controls.

Conclusion

The ocular biomarkers assessed in this study were not associated with cognitive impairment in nonagenarians, making their use as a screening tool for dementing disorders in this group limited. However, ocular biomarkers were significantly associated with chronological age, which were very similar to those ascribed to occur in Alzheimer’s Disease.

Optical coherence tomography angiography in preclinical Alzheimer's disease

BACKGROUND/AIMS

As a protrusion from the brain, the retina might reflect the status of the brain. Previous studies showed a decrease in vessel density and foveal avascular zone (FAZ) enlargement on optical coherence tomography angiography (OCTA) in individuals suffering from Alzheimer's disease (AD). This study aims to assess whether such changes are already present in preclinical stages of AD, in a population of monozygotic (MZ) twins.

METHODS

124 cognitively healthy individuals (MZ twins, ages 60-93 years) underwent [18F]flutemetamol amyloid positron emission tomography (PET) scanning and OCTA. PET scans were visually rated for cortical amyloid-beta (Aβ) positivity. Parametric global cortical non-displaceable binding potential (BPND) was used as a continuous measure for Aβ aggregation. FAZ size and vessel densities for the inner and outer ring of the macular ETDRS grid and in a 3-6 mm ring around the optic nerve head (ONH) were measured.OCTA measures were associated with visual Aβ score, BPND and amyloid load estimated by twin concordance on visual Aβ score. Twin correlations were estimated as a measure of maximum heritability of OCTA measures.

RESULTS

13 of 124 participants were Aβ+. Aβ+ individuals had significantly higher vessel density than Aβ- individuals in all regions but did not differ in FAZ size. Twin analyses showed a positive association between and vessel densities in all regions. BPND tended to be associated with higher vessel density in the inner ring. Twin correlations were moderate/high for all OCTA parameters except vessel density around the ONH, which correlated weakly.

CONCLUSION

Retinal vessel density was higher in individuals with preclinical AD.

Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort

We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.

A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort

Introduction

Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer Disease (AD). Here we set out to test the performance of metabolites in blood to categorize AD when compared to CSF biomarkers.

Methods

This study analyzed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n = 883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV).

Results

On the test data, DL produced the AUC of 0.85 (0.80–0.89), XGBoost produced 0.88 (0.86–0.89) and RF produced 0.85 (0.83–0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively.

Discussion

This study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders.

Discovery and validation of plasma proteomic biomarkers relating to brain amyloid burden by SOMAscan assay

Introduction

Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins.

Methods

4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid.

Results

A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization.

Discussion

The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition.

Atrophy subtypes in prodromal Alzheimer's disease are associated with cognitive decline

Alzheimer's disease is a heterogeneous disorder. Understanding the biological basis for this heterogeneity is key for developing personalized medicine. We identified atrophy subtypes in Alzheimer's disease dementia and tested whether these subtypes are already present in prodromal Alzheimer's disease and could explain interindividual differences in cognitive decline. First we retrospectively identified atrophy subtypes from structural MRI with a data-driven cluster analysis in three datasets of patients with Alzheimer's disease dementia: discovery data (dataset 1: n = 299, age = 67 ± 8, 50% female), and two independent external validation datasets (dataset 2: n = 181, age = 66 ± 7, 52% female; dataset 3: n = 227, age = 74 ± 8, 44% female). Subtypes were compared on clinical, cognitive and biological characteristics. Next, we classified prodromal Alzheimer's disease participants (n = 603, age = 72 ± 8, 43% female) according to the best matching subtype to their atrophy pattern, and we tested whether subtypes showed cognitive decline in specific domains. In all Alzheimer's disease dementia datasets we consistently identified four atrophy subtypes: (i) medial-temporal predominant atrophy with worst memory and language function, older age, lowest CSF tau levels and highest amount of vascular lesions; (ii) parieto-occipital atrophy with poor executive/attention and visuospatial functioning and high CSF tau; (iii) mild atrophy with best cognitive performance, young age, but highest CSF tau levels; and (iv) diffuse cortical atrophy with intermediate clinical, cognitive and biological features. Prodromal Alzheimer's disease participants classified into one of these subtypes showed similar subtype characteristics at baseline as Alzheimer's disease dementia subtypes. Compared across subtypes in prodromal Alzheimer's disease, the medial-temporal subtype showed fastest decline in memory and language over time; the parieto-occipital subtype declined fastest on executive/attention domain; the diffuse subtype in visuospatial functioning; and the mild subtype showed intermediate decline in all domains. Robust atrophy subtypes exist in Alzheimer's disease with distinct clinical and biological disease expression. Here we observe that these subtypes can already be detected in prodromal Alzheimer's disease, and that these may inform on expected trajectories of cognitive decline.

Retinal and Cerebral Microvasculopathy: Relationships and Their Genetic Contributions

Purpose

Retinal microvasculopathy may reflect small vessel disease in the brain. Here we test the relationships between retinal vascular parameters and small vessel disease, the influence of cardiovascular risk factors on these relationships, and their common genetic background in a monozygotic twin cohort.

Methods

We selected 134 cognitively healthy individuals (67 monozygotic twin pairs) aged ≥60 years from the Netherlands Twin Register for the EMIF-AD PreclinAD study. We measured seven retinal vascular parameters averaged over both eyes using fundus images analyzed with Singapore I Vessel Assessment. Small vessel disease was assessed on MRI by a volumetric measurement of periventricular and deep white matter hyperintensities. We calculated associations between RVPs and WMH, estimated intratwin pair correlations, and performed twin-specific analyses on relationships of interest.

Results

Deep white matter hyperintensities volume was positively associated with retinal tortuosity in veins (P = 0.004) and fractal dimension in arteries (P = 0.001) and veins (P = 0.032), periventricular white matter hyperintensities volume was positively associated with retinal venous width (P = 0.028). Intratwin pair correlations were moderate to high for all small vessel disease/retinal vascular parameter variables (r = 0.49-0.87, P < 0.001). Cross-twin cross-trait analyses showed that retinal venous tortuosity of twin 1 could predict deep white matter hyperintensities volume of the co-twin (r = 0.23, P = 0.030). Within twin-pair differences for retinal venous tortuosity were associated with within twin-pair differences in deep white matter hyperintensities volume (r = 0.39, P = 0.001).

Conclusions

Retinal arterial fractal dimension and venous tortuosity have associations with deep white matter hyperintensities volume. Twin-specific analyses suggest that retinal venous tortuosity and deep white matter hyperintensities volume have a common etiology driven by both shared genetic factors and unique environmental factors, supporting the robustness of this relationship.

Assessing Amyloid Pathology in Cognitively Normal Subjects Using 18F-Flutemetamol PET: Comparing Visual Reads and Quantitative Methods

Our objective was to determine the optimal approach for assessing amyloid disease in a cognitively normal elderly population. Methods: Dynamic ¹⁸F-flutemetamol PET scans were acquired using a coffee-break protocol (a 0- to 30-min scan and a 90- to 110-min scan) on 190 cognitively normal elderly individuals (mean age, 70.4 y; 60% female). Parametric images were generated from SUV ratio (SUVr) and nondisplaceable binding potential (BP_ND) methods, with cerebellar gray matter as a reference region, and were visually assessed by 3 trained readers. Interreader agreement was calculated using κ-statistics, and semiquantitative values were obtained. Global cutoffs were calculated for both SUVr and BP_ND using a receiver-operating-characteristic analysis and the Youden index. Visual assessment was related to semiquantitative classifications. Results: Interreader agreement in visual assessment was moderate for SUVr (κ = 0.57) and good for BP_ND images (κ = 0.77). There was discordance between readers for 35 cases (18%) using SUVr and for 15 cases (8%) using BP_ND, with 9 overlapping cases. For the total cohort, the mean (±SD) SUVr and BP_ND were 1.33 (±0.21) and 0.16 (±0.12), respectively. Most of the 35 cases (91%) for which SUVr image assessment was discordant between readers were classified as negative based on semiquantitative measurements. Conclusion: The use of parametric BP_ND images for visual assessment of ¹⁸F-flutemetamol in a population with low amyloid burden improves interreader agreement. Implementing semiquantification in addition to visual assessment of SUVr images can reduce false-positive classification in this population.

Functional brain network centrality is related to APOE genotype in cognitively normal elderly

INTRODUCTION

Amyloid plaque deposition in the brain is an early pathological change in Alzheimer's disease (AD), causing disrupted synaptic connections. Brain network disruptions in AD have been demonstrated with eigenvector centrality (EC), a measure that identifies central regions within networks. Carrying an apolipoprotein (APOE)-ε4 allele is a genetic risk for AD, associated with increased amyloid deposition. We studied whether APOE-ε4 carriership is associated with EC disruptions in cognitively normal individuals.

METHODS

A total of 261 healthy middle-aged to older adults (mean age 56.6 years) were divided into high-risk (APOE-ε4 carriers) and low-risk (noncarriers) groups. EC was computed from resting-state functional MRI data. Clusters of between-group differences were assessed with a permutation-based method. Correlations between cluster mean EC with brain volume, CSF biomarkers, and psychological test scores were assessed.

RESULTS

Decreased EC in the visual cortex was associated with APOE-ε4 carriership, a genetic risk factor for AD. EC differences were correlated with age, CSF amyloid levels, and scores on the trail-making and 15-object recognition tests.

CONCLUSION

Our findings suggest that the APOE-ε4 genotype affects brain connectivity in regions previously found to be abnormal in AD as a sign of very early disease-related pathology. These differences were too subtle in healthy elderly to use EC for single-subject prediction of APOE genotype.

Disease trajectories in behavioural variant frontotemporal dementia, primary psychiatric and other neurodegenerative disorders presenting with behavioural change

Behavioural variant frontotemporal dementia (bvFTD) is characterized by behavioural and social cognitive disturbances, while various psychiatric and neurodegenerative disorders may have similar clinical symptoms. Since neurodegenerative disorders are eventually progressive, whereas primary psychiatric disorders are not, this study aimed to investigate whether the change in clinical symptoms over time differed between groups and which biomarkers predicted rate of decline. Disease trajectories (median follow-up = 3 years) of frontal and stereotyped behaviour, general and frontal cognitive functioning, and social cognition were examined in bvFTD (n = 34), other neurodegenerative (n = 28) and primary psychiatric disorders (n = 43), all presenting with late-onset frontal lobe syndrome (45-75 years), using linear mixed models. To gain more insight in underlying pathological processes driving disease progression, we studied the association of baseline cerebrospinal fluid (CSF) (neurofilament light (NfL) and YKL-40 levels, phosphotau₁₈₁ to total tau ratio) and neuroimaging markers with disease trajectories. Frontal behavioural symptoms (e.g., disinhibition, apathy) worsened over time in bvFTD, whereas they improved in psychiatric disorders and remained stable in other neurodegenerative disorders. General and frontal cognitive decline was observed in bvFTD and other neurodegenerative disorders, but not in psychiatric disorders. None of the groups showed change in stereotypy and social cognition. For all diagnostic groups, higher CSF NfL levels were associated with faster frontal cognitive decline. A modest association was observed between caudate volume and stereotyped behaviour. Tracking frontal behavioural symptoms and cognition has potential to distinguish bvFTD from other disorders. CSF NfL levels seem to be associated with decline in frontal cognitive functioning.

The EMIF-AD PreclinAD study: study design and baseline cohort overview

Background

Amyloid pathology is the pathological hallmark in Alzheimer’s disease (AD) and can precede clinical dementia by decades. So far it remains unclear how amyloid pathology leads to cognitive impairment and dementia. To design AD prevention trials it is key to include cognitively normal subjects at high risk for amyloid pathology and to find predictors of cognitive decline in these subjects. These goals can be accomplished by targeting twins, with additional benefits to identify genetic and environmental pathways for amyloid pathology, other AD biomarkers, and cognitive decline.

Methods

From December 2014 to October 2017 we enrolled cognitively normal participants aged 60 years and older from the ongoing Manchester and Newcastle Age and Cognitive Performance Research Cohort and the Netherlands Twins Register. In Manchester we included single individuals, and in Amsterdam monozygotic twin pairs. At baseline, participants completed neuropsychological tests and questionnaires, and underwent physical examination, blood sampling, ultrasound of the carotid arteries, structural and resting state functional brain magnetic resonance imaging, and dynamic amyloid positron emission tomography (PET) scanning with [¹⁸F]flutemetamol. In addition, the twin cohort underwent lumbar puncture for cerebrospinal fluid collection, buccal cell collection, magnetoencephalography, optical coherence tomography, and retinal imaging.

Results

We included 285 participants, who were on average 74.8 ± 9.7 years old, 64% female. Fifty-eight participants (22%) had an abnormal amyloid PET scan.

Conclusions

A rich baseline dataset of cognitively normal elderly individuals has been established to estimate risk factors and biomarkers for amyloid pathology and future cognitive decline.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0406-7) contains supplementary material, which is available to authorized users.

The EMIF-AD Multimodal Biomarker Discovery study: design, methods and cohort characteristics

Background

There is an urgent need for novel, noninvasive biomarkers to diagnose Alzheimer’s disease (AD) in the predementia stages and to predict the rate of decline. Therefore, we set up the European Medical Information Framework for Alzheimer’s Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study. In this report we describe the design of the study, the methods used and the characteristics of the participants.

Methods

Participants were selected from existing prospective multicenter and single-center European studies. Inclusion criteria were having normal cognition (NC) or a diagnosis of mild cognitive impairment (MCI) or AD-type dementia at baseline, age above 50 years, known amyloid-beta (Aβ) status, availability of cognitive test results and at least two of the following materials: plasma, DNA, magnetic resonance imaging (MRI) or cerebrospinal fluid (CSF). Targeted and untargeted metabolomic and proteomic analyses were performed in plasma, and targeted and untargeted proteomics were performed in CSF. Genome-wide SNP genotyping, next-generation sequencing and methylation profiling were conducted in DNA. Visual rating and volumetric measures were assessed on MRI. Baseline characteristics were analyzed using ANOVA or chi-square, rate of decline analyzed by linear mixed modeling.

Results

We included 1221 individuals (NC n = 492, MCI n = 527, AD-type dementia n = 202) with a mean age of 67.9 (SD 8.3) years. The percentage Aβ+ was 26% in the NC, 58% in the MCI, and 87% in the AD-type dementia groups. Plasma samples were available for 1189 (97%) subjects, DNA samples for 929 (76%) subjects, MRI scans for 862 (71%) subjects and CSF samples for 767 (63%) subjects. For 759 (62%) individuals, clinical follow-up data were available. In each diagnostic group, the APOE ε4 allele was more frequent amongst Aβ+ individuals (p < 0.001). Only in MCI was there a difference in baseline Mini Mental State Examination (MMSE) score between the A groups (p < 0.001). Aβ+ had a faster rate of decline on the MMSE during follow-up in the NC (p < 0.001) and MCI (p < 0.001) groups.

Conclusions

The characteristics of this large cohort of elderly subjects at various cognitive stages confirm the central roles of Aβ and APOE ε4 in AD pathogenesis. The results of the multimodal analyses will provide new insights into underlying mechanisms and facilitate the discovery of new diagnostic and prognostic AD biomarkers. All researchers can apply for access to the EMIF-AD MBD data by submitting a research proposal via the EMIF-AD Catalog.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0396-5) contains supplementary material, which is available to authorized users.

White matter hyperintensities and vascular risk factors in monozygotic twins

Cerebral white matter hyperintensities (WMHs) have been associated with vascular risk factors, both of which are under genetic influence. We examined in a monozygotic twin sample whether the association between vascular risk and WMHs is influenced by overlapping genetic factors. We included 195 cognitively normal monozygotic twins (age = 70 ± 7 years), including 94 complete pairs. Regional WMH load was estimated using an automated algorithm. Vascular risk was summarized with the Framingham score. The within-twin pair correlation for total WMHs was 0.76 and for Framingham score was 0.77. Within participants, Framingham score was associated with total and periventricular WMHs (r = 0.32). Framingham score in 1 twin was also associated with total WMHs in the co-twin (r = 0.26). Up to 83% of the relation between both traits could be explained by shared genetic effects. In conclusion, monozygotic twins have highly similar vascular risk and WMH burden, confirming a genetic background for these traits. The association between both traits is largely driven by overlapping genetic factors.

Gray Matter Network Disruptions and Regional Amyloid Beta in Cognitively Normal Adults

The accumulation of amyloid plaques is one of the earliest pathological changes in Alzheimer's disease (AD) and may occur 20 years before the onset of symptoms. Examining associations between amyloid pathology and other early brain changes is critical for understanding the pathophysiological underpinnings of AD. Alterations in gray matter networks might already start at early preclinical stages of AD. In this study, we examined the regional relationship between amyloid aggregation measured with positron emission tomography (PET) and gray matter network measures in elderly subjects with subjective memory complaints. Single-subject gray matter networks were extracted from T1-weigthed structural MRI in cognitively normal subjects (n = 318, mean age 76.1 ± 3.5, 64% female, 28% amyloid positive). Degree, clustering, path length and small world properties were computed. Global and regional amyloid load was determined using [¹⁸F]-Florbetapir PET. Associations between standardized uptake value ratio (SUVr) values and network measures were examined using linear regression models. We found that higher global SUVr was associated with lower clustering (β = -0.12, p < 0.05), and small world values (β = -0.16, p < 0.01). Associations were most prominent in orbito- and dorsolateral frontal and parieto-occipital regions. Local SUVr values showed less anatomical variability and did not convey additional information beyond global amyloid burden. In conclusion, we found that in cognitively normal elderly subjects, increased global amyloid pathology is associated with alterations in gray matter networks that are indicative of incipient network breakdown towards AD dementia.

Clinical validity of medial temporal atrophy as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

Research criteria for Alzheimer's disease recommend the use of biomarkers for diagnosis, but whether biomarkers improve the diagnosis in clinical routine has not been systematically assessed. The aim is to evaluate the evidence for use of medial temporal lobe atrophy (MTA) as a biomarker for Alzheimer's disease at the mild cognitive impairment stage in routine clinical practice, with an adapted version of the 5-phase oncology framework for biomarker development. A literature review on visual assessment of MTA and hippocampal volumetry was conducted with other biomarkers addressed in parallel reviews. Ample evidence is available for phase 1 (rationale for use) and phase 2 (discriminative ability between diseased and control subjects). Phase 3 (early detection ability) is partly achieved: most evidence is derived from research cohorts or clinical populations with short follow-up, but validation in clinical mild cognitive impairment cohorts is required. In phase 4, only the practical feasibility has been addressed for visual rating of MTA. The rest of phase 4 and phase 5 have not yet been addressed.

Gray matter networks and clinical progression in subjects with predementia Alzheimer's disease

We studied whether gray matter network parameters are associated with rate of clinical progression in nondemented subjects who have abnormal amyloid markers in the cerebrospinal fluid (CSF), that is, predementia Alzheimer's disease. Nondemented subjects (62 with subjective cognitive decline; 160 with mild cognitive impairment (MCI); age = 68 ± 8 years; Mini-Mental State Examination (MMSE) = 28 ± 2.4) were selected from the Amsterdam Dementia Cohort when they had abnormal amyloid in CSF (<640 pg/mL). Networks were extracted from gray matter structural magnetic resonance imaging (MRI), and 9 parameters were calculated. Cox proportional hazards models were used to test associations between each connectivity predictor and rate of progression to MCI or dementia. After a median time of 2.2 years, 122 (55%) subjects showed clinical progression. Lower network parameter values were associated with increased risk for progression, with the strongest hazard ratio of 0.29 for clustering (95% confidence interval = 0.12-0.70; p < 0.01). Results remained after correcting for tau, hippocampal volume, and MMSE scores. Our results suggest that at predementia stages, gray matter network parameters may have use to identify subjects who will show fast clinical progression.

Amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment

Background

Amyloid pathology in subjects with mild cognitive impairment (MCI) is an important risk factor for progression to dementia due to Alzheimer’s disease. Predicting the onset of dementia is challenging even in the presence of amyloid, as time to progression varies considerably among patients and depends on the onset of neurodegeneration. Survival analysis can account for variability in time to event, but has not often been applied to MRI measurements beyond singular predefined brain regions such as the hippocampus. Here we used a voxel-wise survival analysis to identify in an unbiased fashion brain regions where decreased gray matter volume is associated with time to dementia, and assessed the effects of amyloid on these associations.

Methods

We included 276 subjects with MCI (mean age 67 ± 8, 41% female, mean Mini-Mental State Examination 26.6 ± 2.4), baseline 3D T1-weighted structural MRI, baseline cerebrospinal fluid (CSF) biomarkers, and prospective clinical follow-up. We fitted for each voxel a proportional Cox hazards regression model to study whether decreased gray matter volume predicted progression to dementia in the total sample, and stratified for baseline amyloid status.

Results

Dementia at follow-up occurred in 122 (44%) subjects over an average follow-up period of 2.5 ± 1.5 years. Baseline amyloid positivity was associated with progression to dementia (hazard ratio 2.4, p < 0.001). Within amyloid-positive subjects, decreased gray matter volume in the hippocampal, temporal, parietal, and frontal regions was associated with more rapid progression to dementia (median (interquartile range) hazard ratio across significant voxels 1.35 (1.32–1.40)). Repeating the analysis in amyloid-negative subjects revealed similar patterns (median (interquartile range) hazard ratio 1.76 (1.66–1.91)).

Conclusions

In subjects with MCI, both abnormal amyloid CSF and decreased gray matter volume were associated with future progression to dementia. The spatial pattern of decreased gray matter volume associated with progression to dementia was consistent for amyloid-positive and amyloid-negative subjects.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-017-0299-x) contains supplementary material, which is available to authorized users.

Strategic roadmap for an early diagnosis of Alzheimer's disease based on biomarkers

The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.

White Matter Changes-Related Gait and Executive Function Deficits: Associations with Age and Parkinson's Disease

Background: White matter changes (WMC) are a common finding among older adults and patients with Parkinson's disease (PD), and have been associated with, e.g., gait deficits and executive dysfunction. How the factors age and PD influence WMC-related deficits is, to our best knowledge, not investigated to date. We hypothesized that advanced age and presence of PD leads to WMC-related symptoms while practicing tasks with a low complexity level, and low age and absence of PD leads to WMC-related symptoms while practicing tasks with a high complexity level.

Methods: Hundred and thirty-eight participants [65 young persons without PD (50–69 years, yPn), 22 young PD patients (50–69 years, yPD), 36 old persons without PD (70–89 years, oPn) and 15 old PD patients (70–89 years, oPD)] were included. Presence and severity of WMC were determined with the modified Fazekas score. Velocity of walking under single and dual tasking conditions and the Trail Making Test (TMT) were used as gait and executive function parameters. Correlations between presence and severity of WMC, and gait and executive function parameters were tested in yPn, yPD, oPn, and oPD using Spearman's rank correlation, and significance between groups was evaluated with Fisher's z-transformed correlation coefficient.

Results: yPn and yPD, as well as oPn and oPD did not differ regarding demographic and clinical parameters. Severity of WMC was not significantly different between groups. yPn and yPD displayed significant correlations of WMC with executive function parameters at low levels of task complexity, oPn at intermediate, and oPD at high complexity levels.

Conclusion: This study argues for a relevant association of age and PD-related brain pathology with WMC-related gait and executive function deficits.

Early- and Late-Onset Depression in Late Life: A Prospective Study on Clinical and Structural Brain Characteristics and Response to Electroconvulsive Therapy

OBJECTIVE

The clinical profile of late-life depression (LLD) is frequently associated with cognitive impairment, aging-related brain changes, and somatic comorbidity. This two-site naturalistic longitudinal study aimed to explore differences in clinical and brain characteristics and response to electroconvulsive therapy (ECT) in early- (EOD) versus late-onset (LOD) late-life depression (respectively onset <55 and ≥55 years).

METHODS

Between January 2011 and December 2013, 110 patients aged 55 years and older with ECT-treated unipolar depression were included in The Mood Disorders in Elderly treated with ECT study. Clinical profile and somatic health were assessed. Magnetic resonance imaging (MRI) scans were performed before the first ECT and visually rated.

RESULTS

Response rate was 78.2% and similar between the two sites but significantly higher in LOD compared with EOD (86.9 versus 67.3%). Clinical, somatic, and brain characteristics were not different between EOD and LOD. Response to ECT was associated with late age at onset and presence of psychotic symptoms and not with structural MRI characteristics. In EOD only, the odds for a higher response were associated with a shorter index episode.

CONCLUSION

The clinical profile, somatic comorbidities, and brain characteristics in LLD were similar in EOD and LOD. Nevertheless, patients with LOD showed a superior response to ECT compared with patients with EOD. Our results indicate that ECT is very effective in LLD, even in vascular burdened patients.

Impact of APOE-ɛ4 and family history of dementia on gray matter atrophy in cognitively healthy middle-aged adults

The apolipoprotein E ε4 allele (APOE4) and family history of dementia (FH) are well-known risk factors for the development of sporadic Alzheimer's disease. We assessed the effects of these risk factors on gray matter (GM) volume in 295 cognitively healthy middle-aged community-dwelling subjects. Voxel-based morphometry was used to study GM volume differences between high- and low-risk subjects, based on APOE4 carriership (n = 74), first-degree FH (n = 228), or both (n = 62). No significant results were found using a corrected p value. Using a more lenient threshold (p < 0.001 and minimum cluster size of 100 voxels), APOE4 carriers had reduced GM in the striatum compared to noncarriers. Subjects with FH had reduced GM in right precuneus compared to subjects without FH. Maternal and paternal FH provided similar atrophy patterns. APOE4 carriers with FH had GM reductions in bilateral insula compared to subjects with neither APOE4 nor FH. We conclude that a family history of dementia and APOE4 carriership are both associated with regional GM decreases in cognitively healthy middle-aged subjects, with differential effects on brain regions typically affected in Alzheimer's disease.

Gray matter network disruptions and amyloid beta in cognitively normal adults

Gray matter networks are disrupted in Alzheimer's disease (AD). It is unclear when these disruptions start during the development of AD. Amyloid beta 1-42 (Aβ42) is among the earliest changes in AD. We studied, in cognitively healthy adults, the relationship between Aβ42 levels in cerebrospinal fluid (CSF) and single-subject cortical gray matter network measures. Single-subject gray matter networks were extracted from structural magnetic resonance imaging scans in a sample of cognitively healthy adults (N = 185; age range 39-79, mini-mental state examination >25, N = 12 showed abnormal Aβ42 < 550 pg/mL). Degree, clustering coefficient, and path length were computed at whole brain level and for 90 anatomical areas. Associations between continuous Aβ42 CSF levels and single-subject cortical gray matter network measures were tested. Smoothing splines were used to determine whether a linear or nonlinear relationship gave a better fit to the data. Lower Aβ42 CSF levels were linearly associated at whole brain level with lower connectivity density, and nonlinearly with lower clustering values and higher path length values, which is indicative of a less-efficient network organization. These relationships were specific to medial temporal areas, precuneus, and the middle frontal gyrus (all p < 0.05). These results suggest that mostly within the normal spectrum of amyloid, lower Aβ42 levels can be related to gray matter networks disruptions.