Biology subjects

van der Flier, W. M.

Publications and source records attributed to van der Flier, W. M..

10 recordsLinked to original sources

bioRxiv2025

Soluble SORL1 in cerebrospinal fluid as a marker for functional impact of rare SORL1 variants.

BackgroundAs part of the retromer, sortilin-related receptor (SORL1) sorts cargo proteins away from the endosome to the trans-Golgi network or to the cell surface, where SORL1 is cleaved into sSORL1 and shed into the interstitial fluid and CSF. SORL1s cargo includes APP and A{beta}, which may explain why protein-truncating genetic variants (PTVs) in SORL1 are observed almost exclusively in Alzheimers Disease (AD) patients, and that rare, predicted pathogenic missense variants have been associated with a 10-fold increased risk of AD. However, functional evidence supporting variant pathogenicity is warranted. Here we investigated whether soluble SORL1 (sSORL1) concentrations in cerebrospinal fluid (CSF) offer a potential in vivo biomarker to support impaired SORL1 function in variant carriers. MethodsUsing an ELISA assay for SORL1 (ABCAM), we determined sSORL1 concentrations in CSF from 218 participants of the Alzheimer Dementia Cohort (ADC) (54% females). We compared sSORL1 in CSF derived from 90 carriers of diverse SORL1 variants with concentrations observed in 78 SORL1-WT AD patients, and 50 SORL1-WT controls for whom CSF-pTau-181, CSF-tTau, CSF-A{beta}42 concentrations were available. In a subset of 36 individuals, we used Western blotting (WB) to validate sSORL1 concentrations as determined by ELISA. ResultsCSF-sSORL1 concentrations did not differ between SORL1-WT AD patients and controls. While CSF-sSORL1 did not correlate with CSF-A{beta}42 concentrations in SORL1-WT AD patients (p=0.62), it correlated with sCSF-ptau-181 (p=9.7x10-6). The mean CSF-sSORL1 concentration in the SORL1 WT AD cases and controls was 466 pg/ml, with wide variance (SD = 133). Comparatively, concentrations were significantly lower in PTV carriers (260 pg/ml, p=3.2x10-7) and in carriers of predicted damaging SORL1 missense variants (323 pg/ml, p=2.4x10-7). CSF-sSORL1 concentrations measured by ELISA correlated strongly with concentrations estimated by WB ({rho}=0.552; p=5.0x10-4). ConclusionCSF-sSORL1 increases with CSF-ptau, suggesting that increased SORL1-retromer activity may serve to rescue cellular stress associated with AD-related processes. However, impairing SORL1 genetic variants may preclude SORL1 trafficking to the cell surface, as supported by lower CSF-sSORL1 protein concentrations in carriers. While further refinements are necessary, we present first evidence for the applicability of ELISA-based quantification of sSORL1 in CSF to evaluate the functional impact of rare SORL1 variants.

neuroscience↗

bioRxiv2025

Increased Genetic Protection Against Alzheimer's Disease in Centenarians

We constructed a polygenic protective score specific to Alzheimers disease (AD PPS) based on the current literature among the participants enrolled in five studies of healthy aging and extreme longevity in the US, Europe, and Asia. This AD PPS did not include variants on Apolipoprotein E (APOE) gene. Comparisons of AD PPS in different data sets of healthy agers and centenarians showed that centenarians have stronger genetic protection against AD compared to individuals without familial longevity. The current study also shows evidence that this genetic protection increases with increasingly older ages in centenarians (centenarians who died before reaching age 105 years, semi-supercentenarians who reached age 105 to 109 years, and supercentenarians who reached age 110 years and older). However, the genetic protection was of modest size: the average increase in AD PPS was approximately one additional protective allele per 5 years of gained lifetime. Additionally, we show that the higher AD PPS was associated with better cognitive function and decreased mortality. Taken together, this analysis suggests that individuals who achieve the most extreme ages, on average, have the greatest protection against AD. This finding is robust to different genetic backgrounds with important implications for universal applicability of therapeutics that target this AD PPS.

genetics↗

bioRxiv2023

Quantitative trait loci mapping of circulating metabolites in cerebrospinal fluid to uncover biological mechanisms involved in brain-related phenotypes

Genomic studies of molecular traits have provided mechanistic insights into complex disease, though these lag behind for brain-related traits due to the inaccessibility of brain tissue. We leveraged cerebrospinal fluid (CSF) to study neurobiological mechanisms in vivo, measuring 5,543 CSF metabolites, the largest panel in CSF to date, in 977 individuals of European ancestry. Individuals originated from two separate cohorts including cognitively healthy subjects (n=490) and a well-characterized memory clinic sample, the Amsterdam Dementia Cohort (ADC, n=487). We performed metabolite quantitative trait loci (mQTL) mapping on CSF metabolomics and found 126 significant mQTLs, representing 65 unique CSF metabolites across 51 independent loci. To better understand the role of CSF mQTLs in brain-related disorders, we performed a metabolome-wide association study (MWAS), identifying 40 associations between CSF metabolites and brain traits. Similarly, over 90% of significant mQTLs demonstrated colocalized associations with brain-specific gene expression, unveiling potential neurobiological pathways.

genomics↗

bioRxiv2022

What does heritability of Alzheimer's disease represent?

INTRODUCTIONBoth Alzheimers disease (AD) and ageing have a strong genetic component. In each case, many associated variants have been discovered, but how much missing heritability remains to be discovered is debated. Variability in the estimation of SNP-based heritability could explain the differences in reported heritability. METHODSWe compute heritability in five large independent cohorts (N=7,396, 1,566, 803, 12,528 and 3,963) to determine whether a consensus for the AD heritability estimate can be reached. These cohorts vary by sample size, age of cases and controls and phenotype definition. We compute heritability a) for all SNPs, b) excluding APOE region, c) excluding both APOE and genome-wide association study hit regions, and d) SNPs overlapping a microglia gene-set. RESULTSSNP-based heritability of Alzheimers disease is between 38 and 66% when age and genetic disease architecture are correctly accounted for. The heritability estimates decrease by 12% [SD=8%] on average when the APOE region is excluded and an additional 1% [SD=3%] when genome-wide significant regions were removed. A microglia gene-set explains 69-84% of our estimates of SNP-based heritability using only 3% of total SNPs in all cohorts. CONCLUSIONThe heritability of neurodegenerative disorders cannot be represented as a single number, because it is dependent on the ages of cases and controls. Genome-wide association studies pick up a large proportion of total AD heritability when age and genetic architecture are correctly accounted for. Around 13% of SNP-based heritability can be explained by known genetic loci and the remaining heritability likely resides around microglial related genes. Author SummaryEstimates of heritability in Alzheimers disease, the proportion of phenotypic variance explained by genetics, are very varied across different studies, therefore, the amount of missing heritability not yet captured by current genome-wide association studies is debated. We investigate this in five independent cohorts, provide estimates based on these cohorts and detail necessary suggestions to accurately calculate heritability in age-related disorders. We also confirm the importance of microglia relevant genetic markers in Alzheimers disease. This manuscript provides suggestions for other researchers computing heritability in late-onset disorders and the microglia gene-set used in this study will be published alongside this manuscript and made available to other researchers. The correct assessment of disease heritability will aid in better understanding the amount of missing heritability in Alzheimers disease.

genetics↗

bioRxiv2020

Differential brain atrophy and neurogenetic profiles in cognitively-defined Alzheimer's disease subgroups

Elucidating mechanisms underlying the clinical heterogeneity observed among individuals with Alzheimers disease (AD) is key to facilitate personalized treatments. We categorized 679 individuals with AD into subgroups based on a relative impairment in one cognitive domain (i.e. AD-Memory, AD-Executive-Functioning, AD-Language and AD-Visuospatial-Functioning). We compared atrophy patterns derived from MRI and identified patterns that closely matched the respective cognitive profiles, i.e. medial temporal lobe atrophy in AD-Memory, fronto-parietal in AD-Executive-Functioning, asymmetric left-temporal in AD-Language, and posterior in AD-Visuospatial-Functioning. We then determined spatial correlations between subgroup-specific atrophy and a transcriptomic atlas of gene expression, which revealed both shared (e.g. mitochondrial respiration and synaptic function/plasticity) and subgroup-specific (e.g. cell-cycle for AD-Memory, protein metabolism in AD-Language, and modification of gene expression in AD-Visuospatial-Functioning) biological pathways associated with each subgroups atrophy patterns. We conclude that cognitive heterogeneity in AD is related to neuroanatomical differences, and specific biological pathways may be involved in their emergence.

neuroscience↗

bioRxiv2019

Identifying a task-invariant cognitive reserve network using task potency

Cognitive reserve (CR) is thought to protect against the consequence of age- or disease-related structural brain changes across multiple cognitive domains. The neural basis of CR may therefore comprise a functional network that is actively involved in many different cognitive processes. To investigate the existence of such a \"task-invariant\" CR network, we measured functional connectivity in a cognitively normal sample between 20-80 years old (N=265), both at rest and during the performance of 11 separate tasks that aim to capture four latent cognitive abilities (i.e. vocabulary, episodic memory, processing speed, and fluid reasoning). For each individual, we determined the change in functional connectivity from the resting state to each task state, which is referred to as \"task potency\" (Chauvin et al., 2017; Chauvin et al., 2018). Task potency was calculated for each pair among 264 nodes (Power et al., 2011) and then summarized across tasks reflecting the same cognitive ability. Subsequently, we established the correlation between task potency and premorbid IQ or education (i.e. CR factors). We identified a set of 57 pairs in which task potency showed significant correlations with IQ, but not education, across all four cognitive abilities. These pairs were included in a principal component analysis, from which we extracted the first component to obtain a latent variable reflecting task potency in this task-invariant CR network. This task potency variable moderated the relationship between cortical thickness and episodic memory performance ({beta}=-.64, p=.01), and showed a direct effect on fluid reasoning ({beta}=.08, p<.01) after adjusting for the effects of cortical thickness. Our identification of this task-invariant network contributes to a better understanding of the mechanism underlying CR, which may facilitate the development of CR-enhancing treatments. Our work also offers a useful alternative operational measure of CR future studies.

neuroscience↗

bioRxiv2019

Data-driven detection of latent atrophy factors related to phenotypical variants of posterior cortical atrophy

Posterior cortical atrophy is a clinical-radiological syndrome characterized by visual processing deficits and atrophy in posterior parts of the brain, most often caused by Alzheimers disease pathology. Recent consensus criteria describe four distinct phenotypical variants of posterior cortical atrophy defined by clinical and radiological features; i) object perception/occipitotemporal (ventral), ii) space perception/temporoparietal (dorsal), iii) non-visual/dominant parietal and iv) primary visual (caudal). We employed a data-driven approach to identify atrophy factors related to these proposed variants in a multi-center cohort of 119 individuals with posterior cortical atrophy (age: 64 SD 7, 38% male, MMSE: 21 SD 5, 71% amyloid-{beta} positive, 29% amyloid-{beta} status unknown). A Bayesian modelling framework based on latent Dirichlet allocation was used to compute four latent atrophy factors in accordance with the four proposed variants. The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, field strength and whole-brain gray matter volume) and provides voxelwise probabilistic maps for all atrophy factors, allowing every individual to express each factor to a degree without a priori classification. The model revealed four distinct yet partially overlapping atrophy factors; right-dorsal, right-ventral, left-ventral, and limbic. Individual participant profiles revealed that the vast majority of participants expressed multiple factors, rather than predominantly expressing a single factor. To assess the relationship between atrophy factors and cognition, neuropsychological test scores covering four posterior cortical atrophy-specific cognitive domains were assessed (object perception, space perception, non-visual parietal functions and primary visual processing) and we used general linear models to examine the association between atrophy factor expression and cognition. We found that object perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space perception was associated with atrophy that predominantly represents the right-ventral and right-dorsal factors. Similar to the atrophy factors, most participants had mixed clinical profiles with impairments across multiple domains. However, when selecting four participants with an isolated impairment, we observed atrophy patterns and factor expressions that were largely in accordance with the hypothesized variants. Taken together, our results indicate that variants of posterior cortical atrophy exist but these constitute phenotypical extremes and most individuals fall along a broad clinical-radiological spectrum, indicating that classification into four mutually exclusive variants is unlikely to be clinically useful.

neuroscience↗

bioRxiv2019

PET and CSF amyloid-β status are differently predicted by patient features: Information from discordant cases

BackgroundAmyloid-{beta} PET and CSF A{beta}42 yield discordant results in 10-20% of patients, possibly providing unique information. Although the predictive power of demographic, clinical, genetic and imaging features for amyloid-positivity has previously been investigated, it is unknown whether these features differentially predict amyloid-{beta} status based on PET or CSF, or whether this differs by disease stage.\n\nMethodsWe included 768 patients (subjective cognitive decline (SCD, n=194), mild cognitive impairment (MCI, n=127), dementia (AD and non-AD, n=447) with amyloid-{beta} PET and CSF A{beta}42 measurement within one year. 97(13%) patients had discordant PET/CSF amyloid-{beta} status. We performed parallel random forest models predicting separately PET and CSF status using 17 patient features (demographics, APOE4 positivity, CSF (p)tau, cognitive performance, and MRI visual ratings) in the total patient group and stratified by syndrome diagnosis. Thereafter, we selected features with the highest variable importance measure (VIM) as input for logistic regression models, where amyloid status on either PET or CSF was predicted by (i) the selected patient feature, and (ii) the patient feature adjusted for the status of the other amyloid modality.\n\nResultsAPOE4, CSF tau and p-tau had highest VIM for PET and CSF in all groups. In the amyloid-adjusted logistic regression models, p-tau was a significant predictor for PET-amyloid in SCD (OR=1.02[1.01-1.04], pFDR=0.03), MCI (OR=1.05[1.02-1.07], pFDR<0.01) and dementia (OR=1.04[1.03-1.05], pFDR<0.001), but not for CSF-amyloid. APOE4 (OR=3.07[1.33-7.07], punc<0.01) was associated with CSF-amyloid in SCD, while it was only predictive for PET-amyloid in MCI (OR=9.44[2.93,30.39], pFDR<0.01). Worse MMSE scores (OR=1.21[1.03-1.41], punc=0.02) were associated to CSF-amyloid status in SCD, whereas worse memory (OR=1.17[1.05-1.31], pFDR=0.02) only predicted PET positivity in dementia.\n\nConclusionAmyloid status based on either PET or CSF was predicted by different patient features and this varied by disease stage, suggesting that PET-CSF discordance yields unique information. The stronger associations of both APOE4 carriership and worse memory z-scores with CSF-amyloid in SCD suggests that CSF-amyloid is more sensitive early in the disease course. The higher predictive value of CSF p-tau for a positive PET scan suggests that PET is more specific to AD pathology. These findings can influence the choice between amyloid biomarkers in future studies or trials.

neuroscience↗

bioRxiv2018

Centenarian Controls Increase Variant Effect-sizes by an average two-fold in an Extreme Case-Extreme Control Analysis of Alzheimer’s Disease

The detection of genetic loci associated with Alzheimers disease (AD) requires large numbers of cases and controls because variant effect-sizes are mostly small. We hypothesized that variant effect-sizes should increase when individuals who represent the extreme ends of a disease spectrum are considered, as their genomes are assumed to be maximally enriched or depleted with disease-associated genetic variants.\n\nWe used 1,073 extensively phenotyped AD cases with relatively young age at onset as extreme cases (66.3{+/-}7.9 years), 1,664 age-matched controls (66.0{+/-}6.5 years) and 255 cognitively healthy centenarians as extreme controls (101.4{+/-}1.3 years). We estimated the effect-size of 29 variants that were previously associated with AD in genome-wide association studies.\n\nComparing extreme AD-cases with centenarian-controls increased the variant effect-size relative to published effect-sizes by on average 1.90-fold (SE=0.29, p=9.0x10-4). The effect-size increase was largest for the rare high-impact TREM2 (R74H) variant (6.5-fold), and significant for variants in/near ECHDC3 (4.6-fold), SLC24A4-RIN3 (4.5-fold), NME8 (3.8-fold), PLCG2 (3.3-fold), APOE-{varepsilon}2 (2.2-fold) and APOE-{varepsilon}4 (2.0-fold). Comparing extreme phenotypes enabled us to replicate the AD association for 10 variants (p<0.05) in relatively small samples. The increase in effect-sizes depended mainly on using centenarians as extreme controls: the average variant effect-size was not increased in a comparison of extreme AD cases and age-matched controls (0.94-fold, p=6.8x10-1), suggesting that on average the tested genetic variants did not explain the extremity of the AD-cases. Concluding, using centenarians as extreme controls in AD case-controls studies boosts the variant effect-size by on average two-fold, allowing the replication of disease-association in relatively small samples.

genetics↗

bioRxiv2018

Data-driven approaches improve Tau-PET biomarkers in Alzheimer’s disease

Previous positron emission tomography (PET) studies have quantified filamentous tau pathology using regions-of-interest (ROIs) based on observations of the topographical distribution of neurofibrillary tangles in post-mortem tissue. However, such approaches may not take full advantage of information contained in neuroimaging data. The present study employs an unsupervised data-driven method to identify spatial patterns of tau-PET distribution, and to compare these patterns to previously published \"pathology-driven\" ROIs. Tau-PET patterns were identified from a discovery sample comprised of 123 normal controls and patients with mild cognitive impairment or Alzheimers disease (AD) dementia from the Swedish BioFINDER cohort, who underwent [18F]AV1451 PET scanning. Associations with cognition were tested in a separate sample of 90 individuals from ADNI. BioFINDER [18F]AV1451 images were entered into a robust voxelwise stable clustering algorithm, which resulted in five clusters. Mean [18F]AV1451 uptake in the data-driven clusters, and in 35 previously published pathology-driven ROIs, was extracted from ADNI [18F]AV1451 scans. We performed linear models comparing [18F]AV1451 signal across all 40 ROIs to several tests of global cognition, adjusting for age, sex and education. Two data-driven ROIs consistently demonstrated the strongest or near-strongest effect sizes across all cognitive tests. Inputting all regions plus demographics into a feature selection routine resulted in selection of two ROIs (one data-driven, one pathology-driven) and education, which together explained 28% of the variance of a global cognitive composite score. Our findings suggest that [18F]AV1451-PET data naturally clusters into spatial patterns that are biologically meaningful and that may offer advantages as clinical tools.

neuroscience↗