Result of external validation using ADNI multimodal dataset in NC vs. MCI vs. AD classification (mean ± SD).

Mean gray matter hypometabolism in UCSF cohort (W-score). Gray-matter masked.
Higher W values indicate lower FDG-SUVR values in patients compared to controls.

Collection description

Data from Strom et al, MedRxiv (2020), Brain (2021).
Summary mean images of FDG-PET, tau-PET, amyloid-PET, and MRI volume for UCSF and ADNI cohorts.

Subject species

homo sapiens

Modality

PET FDG

Analysis level

group

Cognitive paradigm (task)

None / Other

Map type

Other

Mean Flortaucipir SUVR in ADNI cohort. Gray-matter masked.

Collection description

Data from Strom et al, MedRxiv (2020), Brain (2021).
Summary mean images of FDG-PET, tau-PET, amyloid-PET, and MRI volume for UCSF and ADNI cohorts.

Subject species

homo sapiens

Modality

PET other

Analysis level

group

Cognitive paradigm (task)

None / Other

Map type

Other

Mean (SD) of the volumes (in mm3) in the left hippocampus in the baseline images of the labelled ADNI data set of 30 images for method validation.

Txt A, Use of prediction model. It explains the use of prediction models of TUM data. Mat B, Prediction model of NC against AD using grand mean saved in MATLAB format. Represents the saved prediction model in MATLAB file format. The model is used for NC against AD, and is trained using the grand mean intensity normalization. The brain voxels are divided into 50 bins, which shows the best predictive performance by an internal cross-validation. BIC is used as the model selection method. In short, the model can be denoted as “predictionModel_grandMean_50_NCAD”. The meaning of the following models can be inferred similarly. Mat C, Prediction model of NC against MCI using grand mean saved in MATLAB format. Represents “predictionModel_grandMean_60_NCMCI”. Mat D, Prediction model of MCI against AD using pSMC saved in MATLAB format. Represents “predictionModel_PSMC_110_MCIAD”. Mat E, Prediction model of NC against MCI using pSMC saved in MATLAB format. Represents “predictionModel_PSMC_80_NCMCI”. Mat F, Prediction model of NC against AD using pSMC saved in MATLAB format. Represents “predictionModel_PSMC_50_NCAD”. Mat G, Prediction model of MCI against AD using grand mean saved in MATLAB format. Represents “predictionModel_grandMean_90_MCIAD”. (ZIP)

Descriptive statistics (mean±sd for continuous variables, percentage for binary) of the variables included in the models for European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study (EPAD) and Alzheimer’s Diseasing Neuroimaging Initiative (ADNI).

Mean results of the incremental experiment with our system.

Summary statistics for all markers in Pfizer sample set. Note: Large file (41MB). (XLSX)

Proteolytic fragments of amyloid and post-translational modification of tau species in Cerebrospinal fluid (CSF) as well as cerebral amyloid deposition are important biomarkers for Alzheimer’s Disease. We conducted genome-wide association study to identify genetic factors influencing CSF biomarker level, cerebral amyloid deposition, and disease progression. The genome-wide association study was performed via a meta-analysis of two non-overlapping discovery sample sets to identify genetic variants other than APOE ε4 predictive of the CSF biomarker level (Aβ1–42, t-Tau, p-Tau181P, t-Tau:Aβ1–42 ratio, and p-Tau181P:Aβ1–42 ratio) in patients enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. Loci passing a genome-wide significance threshold of P < 5 x 10−8 were followed-up for replication in an independent sample set. We also performed joint meta-analysis of both discovery sample sets together with the replication sample set. In the discovery phase, we identified variants in FRA10AC1 associated with CSF Aβ1–42 level passing the genome-wide significance threshold (directly genotyped SNV rs10509663 PFE = 1.1 x 10−9, imputed SNV rs116953792 PFE = 3.5 x 10−10), rs116953792 (Pone-sided = 0.04) achieved replication. This association became stronger in the joint meta-analysis (directly genotyped SNV rs10509663 PFE = 1.7 x 10−9, imputed SNV rs116953792 PFE = 7.6 x 10−11). Additionally, we identified locus 15q21 (imputed SNV rs1503351 PFE = 4.0 x 10−8) associated with CSF Aβ1–42 level. No other variants passed the genome-wide significance threshold for other CSF biomarkers in either the discovery sample sets or joint analysis. Gene set enrichment analyses suggested that targeted genes mediated by miR-33, miR-146, and miR-193 were enriched in various GWAS analyses. This finding is particularly important because CSF biomarkers confer disease susceptibility and may be predictive of the likelihood of disease progression in Alzheimer’s Disease.

Basic demographic information of the three ADNI CSF Sample Sets.

Two variants at the BIN1 locus are associated with Alzheimer's disease susceptibility below the genome-wide significance level with limited LD between them.

ADNI neuropsychological test clinical data summary showing average values with standard deviation. Statistical significance (95% significance level) was tested using analysis of Kruskal-Wallis test for all Neuropsychological test and other variables.

Mean volumes, standard deviations and detectability index Az of various anatomical regions.

ADNI clinical data summary showing average values with standard deviation. Statistical significance (95% significance level) was tested using analysis of variance (ANOVA) for the age of onset and years of education, Chi-square contingency for gender proportions and APOE ϵ4 allele, and Kruskal-Wallis test for all other variables

Top markers with P

Demographics for ADNI and BF2 cohorts. A mean and standard deviations are provided in centiloids.

Leave-One-Out cross-validation mean classification performance for AD versus CN of multi-measure features at p-value = 0.05 with ADNI2 cohort.

Mean BrainAGE scores at baseline and last follow-up for all particular allelic isoforms within the diagnostic groups of the longitudinal sample.

AD Progression Analysis for validated variants in AD susceptibilitya.

Pathway Analysis Results in Three Independent Sample setsa.