Philip Scheltens

This paper personalizes tDCS intervention strategies for Alzheimer's disease using individual connectomes and MEG data, showing different optimal stimulation targets compared to a general model.

The paper analyzes exome data from 22,319 individuals to identify rare CNVs and 22q11.21 dosage as risk factors for Alzheimer's disease.

The paper develops a multivariate methylation risk score using blood DNA methylation data to predict dementia risk and cognitive impairment in Alzheimer's and Parkinson's disease cohorts.

The paper uses a virtual brain network model to optimize tDCS electrode placements in Alzheimer's disease, finding that right parietal anodal stimulation with contralateral supraorbital cathode improves functional network features.

The paper identifies high-priority missense variants in SORL1 associated with increased Alzheimer's Disease risk and earlier onset, suggesting clinical counseling considerations for carriers.

The paper identifies rare damaging variants in ATP8B4 and ABCA1 as novel risk factors for Alzheimer's Disease using exome sequencing data from 32,558 individuals.

This study performs GWAS on quantitative AD biomarkers and cognitive traits, identifying new loci associated with memory performance and cognitive decline.

This study examines how Alzheimer's disease-associated genetic variants influence longevity by analyzing their effects in centenarians and replicating findings in a parental-longevity GWAS.

The paper examines the independent associations of PET, CSF, and plasma tau biomarkers with Alzheimer's disease markers, finding that CSF and plasma p-tau181/p-tau217 are more linked to early AD markers, while tau-PET is strongly associated with cognitive and neurodegenerative progression.

The paper conducts GWAS on CSF Alzheimer's disease biomarkers, identifying genetic associations with NF-L, YKL-40, and Ng levels.

The paper conducts a genome-wide association study (GWAS) on Alzheimer’s disease CSF biomarkers in the EMIF-AD dataset, identifying novel genetic signals and confirming existing associations.

The paper identifies immune response and endocytosis pathways as associated with resilience against Alzheimer's Disease using polygenic risk scores across multiple cohorts.

The paper identifies cognitive subgroups in Alzheimer's disease based on MRI-derived atrophy patterns and links them to specific biological pathways using transcriptomic data.

The paper identifies four latent atrophy factors in posterior cortical atrophy using Bayesian modeling, finding that most patients exhibit mixed profiles rather than distinct variants.

This paper reports six novel genetic variants associated with Alzheimer's disease risk and demonstrates the utility of polygenic risk scores for risk stratification and age at onset prediction.

The paper finds that patient features differentially predict amyloid-β status based on PET or CSF, with variations by disease stage, suggesting PET and CSF discordance provides unique information.

The paper uses automated MRI segmentation to quantify SVD brain changes and shows they predict cognitive and functional decline.

The 100-plus Study characterizes Dutch centenarians with preserved cognitive health, finding associations between APOE alleles and mortality, and higher education and socio-economic status.

This study uses data-driven clustering to identify spatial patterns of tau-PET distribution in Alzheimer’s disease and compares them to pathology-driven ROIs, finding two clusters with strong cognitive associations.

This study shows that using centenarians as extreme controls increases AD variant effect-sizes by two-fold, enabling replication in small samples.

This study examines neuropathological hallmarks in centenarians' brains and their association with cognitive performance, finding that some pathologies correlate with lower cognitive test results.