European and African-specific plasma protein-QTL and metabolite-QTL analyses identify ancestry-specific T2D effector proteins and metabolites DOI
Carlos Cruchaga, Chengran Yang, Priyanka Gorijala

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: July 22, 2024

Initially focused on the European population, multiple genome-wide association studies (GWAS) of complex diseases, such as type-2 diabetes (T2D), have now extended to other populations. However, date, few ancestry-matched omics datasets been generated or further integrated with disease GWAS nominate key genes and/or molecular traits underlying risk loci. In this study, we and plasma proteomics metabolomics array-based genotype (EUR) African (AFR) ancestries identify ancestry-specific muti-omics quantitative trait loci (QTLs). We applied these QTLs ancestry-stratified T2D pinpoint proteins metabolites disease-associated genetic nominated five four in group one protein metabolite be part pathways an manner. Our study demonstrates integration omic different can used distinct effector same across diverse Specifically, AFR proteomic findings T2D, prioritized QSOX2; while metabolomic findings, pinpointed GlcNAc sulfate conjugate C21H34O2 steroid. Neither overlapped corresponding EUR results.

Language: Английский

Identification of potential therapeutic targets for Alzheimer's disease from the proteomes of plasma and cerebrospinal fluid in a multicenter Mendelian randomization study DOI
Shengnan Wang,

Jianxin Xi,

Mengyuan Zhang

et al.

International Journal of Biological Macromolecules, Journal Year: 2025, Volume and Issue: 294, P. 139394 - 139394

Published: Jan. 5, 2025

Language: Английский

Citations

2
Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum DOI Creative Commons
Muhammad Ali, Jigyasha Timsina, Daniel Western

et al.

Neuron, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Changes in β-amyloid (Aβ) and hyperphosphorylated tau (T) brain cerebrospinal fluid (CSF) precede Alzheimer's disease (AD) symptoms, making the CSF proteome a potential avenue to understand pathophysiology facilitate reliable diagnostics therapies. Using AT framework three-stage study design (discovery, replication, meta-analysis), we identified 2,173 analytes (2,029 unique proteins) dysregulated AD. Of these, 865 (43%) were previously reported, 1,164 (57%) are novel. The proteins cluster four different pseudo-trajectories groups spanning AD continuum enriched pathways including neuronal death, apoptosis, phosphorylation (early stages), microglia dysregulation endolysosomal dysfunction (mid plasticity longevity microglia-neuron crosstalk (late stages). machine learning, created validated highly accurate replicable (area under curve [AUC] > 0.90) models that predict biomarker positivity clinical status. These can also identify people will convert

Language: Английский

Citations

2
Benchmarking of a multi‐biomarker low‐volume panel for Alzheimer's disease and related dementia research DOI Creative Commons
Laura Ibáñez, Menghan Liu, Aleksandra Beric

et al.

Alzheimer s & Dementia, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 22, 2024

Abstract INTRODUCTION In the research setting, obtaining accurate established biomarker measurements and maximizing use of precious samples is key. Accurate technologies are available for Alzheimer's disease (AD), but no platform can measure all emerging biomarkers in one run. The NUcleic acid Linked Immuno‐Sandwich Assay (NULISA) a technology that requires 15 µL sample to more than 100 analytes. METHODS We compared AD‐relevant included NULISA against validated assays cerebrospinal fluid (CSF) plasma. RESULTS CSF measures amyloid beta 42/40, phosphorylated tau (p‐tau)217 highly correlated when measured by immunoassay, mass spectrometry, or NULISA. plasma, p‐tau217 performance similar reported with other predicting amyloidosis. Other show wide range correlation values depending on platform. DISCUSSION multiplexed produces reliable results useful settings, advantage measuring additional using minimal volume. Highlights tested novel dementia setting. Cerebrospinal

Language: Английский

Citations

8
Genetic architecture of cerebrospinal fluid and brain metabolite levels and the genetic colocalization of metabolites with human traits DOI
Ciyang Wang, Chengran Yang, Daniel Western

et al.

Nature Genetics, Journal Year: 2024, Volume and Issue: 56(12), P. 2685 - 2695

Published: Nov. 11, 2024

Language: Английский

Citations

6
Cerebrospinal fluid proteomics identification of biomarkers for amyloid and tau PET stages DOI Creative Commons
Zhibo Wang, Yuhan Chen,

Kezhuang Gong

et al.

Cell Reports Medicine, Journal Year: 2025, Volume and Issue: unknown, P. 102031 - 102031

Published: March 1, 2025

Accurate staging of Alzheimer's disease (AD) pathology is crucial for therapeutic trials and prognosis, but existing fluid biomarkers lack specificity, especially assessing tau deposition severity, in amyloid-beta (Aβ)-positive patients. We analyze cerebrospinal (CSF) samples from 136 participants the Disease Neuroimaging Initiative using more than 6,000 proteins. apply machine learning to predict AD pathological stages defined by amyloid positron emission tomography (PET). identify two distinct protein panels: 16 proteins, including neurofilament heavy chain (NEFH) SPARC-related modular calcium-binding 1 (SMOC1), that distinguished Aβ-negative/tau-negative (A-T-) A+ individuals nine such as HCLS1-associated X-1 (HAX1) glucose-6-phosphate isomerase (GPI), differentiated A+T+ A+T- stages. These signatures outperform established CSF (area under curve [AUC]: 0.92 versus 0.67-0.70) accurately predicted progression over a decade. The findings are validated both internal external cohorts. results underscore potential proteomic-based refine diagnostic criteria improve patient stratification clinical trials.

Language: Английский

Citations

0
Alzheimer's subtypes A supervised, unsupervised, multimodal, multilayered embedded recursive (SUMMER) AI study DOI Creative Commons
Sivan Kinreich,

A. Bingly,

Gayathri Pandey

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: May 14, 2025

Since Alzheimer's disease (AD) is a heterogeneous disease, different subtypes may have distinct biological, genetic, and clinical characteristics, requiring tailored interventions. While several proposed of AD exist, there still no clear consensus on definitive classification. By leveraging complementary AI approaches, including supervised unsupervised learning, within recursive pipeline (SUMMER) that integrates multimodal datasets encompassing MRI measurements, phenotypes, genetic data, our goal was to generate robust scientific evidence for identifying subtypes. Data downloaded from the Disease Neuroimaging Initiative (ADNI) database included neuroimaging data (MRI), genetics (SNPs), diagnosis, demographics. 1133 European American participants' images, aged 55-95, were in this study. The analysis multi-fold, where first step involved applying an application subset sample (AD + cognitively normal (CN) matched groups, 100 men 68-85 years, 76 women years). brain gray matter segmented into 44 regions interest (ROIs) according standard atlas, 618 features extracted, ROI voxel intensity measurements such as minimum, maximum, histogram variables. Results identified cluster subtype rest their respective samples. In next step, integrity clusters investigated using XGBoost machine learning with (SNPs, N=36,724) labels: vs. sample, stratified by sex. A significant model (accuracy=0.85, F1=0.72, AUC=0.83) (accuracy=0.81, F1=0.81, AUC=0.81) built, confirming homogeneity isolated clusters. Discriminative biomarkers extracted models, selected ROIs SNPs. Finally, models tested unseen ADNI data. genetic-based participants consisting 34% group 47% group. Phenotypic indicates lower body weight associated women's subtype. Complex diseases like demand sophisticated, approach precise diagnosis. Effectively enhances potential personalized treatment, ultimately improving patient outcomes.

Language: Английский

Citations

0
GWAS meta-analysis of CSF Alzheimer's disease biomarkers 18,948 individuals reveal novel loci and genes regulating lipid metabolism, brain volume and autophagy DOI
Carlos Cruchaga, Jigyasha Timsina, Chenyang Jiang

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: May 21, 2025

Cerebrospinal fluid (CSF) amyloid beta (Aβ42), total tau (t-tau), and phosphorylated (p-tau181) are well accepted markers of Alzheimer's disease. We performed a GWAS meta-analysis including 18,948 individuals European 416 non-European ancestry. identified 12 genome-wide significant loci across all three biomarkers, eight them novel. replicated the association CSF biomarkers with APOE , CR1 GMNC/CCDC50 C16orf95/MAP1LC3B . Novel included BIN1 for Aβ42 GNA12, MS4A6A, SLCO1A2 both t-tau p-tau181, as additional on chr. 8, near ANGPT1 9 SMARCA2 also demonstrated that these variants were not only associated level but showed AD risk, disease progression and/or brain amyloidosis. The genes implicated in lipid metabolism independent autophagy volume regulation driven by p-tau181 dysregulation.

Language: Английский

Citations

0
Therapeutic targets for Alzheimer's disease: Proteome-wide Mendelian randomization and colocalization analyses DOI

Kefu Yu,

Ruiqi Jiang, Dabiao Zhou

et al.

Journal of Alzheimer s Disease, Journal Year: 2025, Volume and Issue: unknown

Published: June 2, 2025

Background Alzheimer's disease (AD) is a major neurodegenerative disorder with limited treatment options. Objective This study aimed to identify novel therapeutic targets for AD using proteome-wide Mendelian randomization (MR) and colocalization analyses. Methods We conducted large-scale, MR analysis data from two extensive genome-wide association studies (GWASs) of plasma proteins: the UK Biobank Pharma Proteomics Project (UKB-PPP) deCODE Health Study. extracted genetic instruments proteins these utilized summary statistics European Bioinformatics Institute GWAS Catalog. Colocalization assessed whether identified associations were due shared causal variants. Phenome-wide drug repurposing analyses performed assess potential side effects existing drugs targeting proteins. Results Our significant between genetically predicted levels 9 in dataset 17 UKB-PPP risk after Bonferroni correction. Four (BCAM, CD55, CR1, GRN) showed consistent across both datasets. provided strong evidence variants GRN, AD. PheWAS revealed minimal CR1 but suggested possible pleiotropic GRN. Drug several FDA-approved GRN treatment. Conclusions identifies as promising These findings provide new directions development, further research clinical trials are warranted validate targets.

Language: Английский

Citations

0
Alzheimer’s Disease polygenic risk, the plasma proteome, and dementia incidence among UK older adults DOI Creative Commons
May A. Beydoun, Hind A. Beydoun, Zhiguang Li

et al.

GeroScience, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 26, 2024

Abstract Alzheimer’s Disease (AD) is a complex polygenic neurodegenerative disorder. Its genetic risk’s relationship with all-cause dementia may be influenced by the plasma proteome. Up to 40,139 UK Biobank participants aged ≥ 50y at baseline assessment (2006–2010) were followed-up for ≤ 15 y incidence. Plasma proteomics performed on sub-sample of ( k = 1,463 proteins). AD risk scores (PRS) used as primary exposure and Cox proportional hazards models conducted examine PRS-dementia relationship. A four-way decomposition model then partitioned total effect (TE) PRS into an due mediation only, interaction neither or both. The study found that tertiles significantly increased dementia, particularly among women. specifically was associated 79% higher each unit increase (HR 1.79, 95% CI: 1.70–1.87, P < 0.001). Eighty-six proteins predicted PRS, including positive association PLA2G7, BRK1, glial acidic fibrillary protein (GFAP), neurofilament light chain (NfL), negative TREM2. Both GFAP NfL interacted synergistically all-dementia (> 10% TE pure interaction), while also important consistent mediator in In summary, we detected significant interactions relation incidence, suggesting potential personalized prevention management.

Language: Английский

Citations

2
Head-to-Head Comparison of Aptamer- and Antibody-Based Proteomic Platforms in Human Cerebrospinal Fluid Samples from a Real-World Memory Clinic Cohort DOI Open Access
Raquel Puerta, Amanda Cano, Pablo García‐González

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 26(1), P. 286 - 286

Published: Dec. 31, 2024

High-throughput proteomic platforms are crucial to identify novel Alzheimer's disease (AD) biomarkers and pathways. In this study, we evaluated the reproducibility reliability of aptamer-based (SomaScan® 7k) antibody-based (Olink® Explore 3k) in cerebrospinal fluid (CSF) samples from Ace Alzheimer Center Barcelona real-world cohort. Intra- inter-platform were through correlations between two independent SomaScan® assays analyzing same samples, Olink® results. Association analyses performed measures, CSF biological traits, sample demographics, AD endophenotypes. Our 12-category metric combining correlation identified 2428 highly reproducible SomaScan with over 600 proteins well reproduced on another platform. The association among clinical phenotypes revealed that significant associations mainly involved proteins. validation these proteomics platforms, measured using scarce biomaterial, is essential for accurate analysis proper interpretation innovative This classification could enhance confidence multiplexed improve design future panels.

Language: Английский

Citations

1