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Meta-Analysis
. 2025 Mar 25;25(1):73.
doi: 10.1007/s10142-025-01581-6.

Linking genomic and proteomic signatures to brain amyloid burden: insights from GR@ACE/DEGESCO

Raquel Puerta  1   2 , Itziar de Rojas  1   3 , Pablo García-González  1   3 , Clàudia Olivé  1 , Oscar Sotolongo-Grau  1 , Ainhoa García-Sánchez  1 , Fernando García-Gutiérrez  1 , Laura Montrreal  1 , Juan Pablo Tartari  1 , Ángela Sanabria  1   3 , Vanesa Pytel  1   3 , Carmen Lage  3   4 , Inés Quintela  5 , Nuria Aguilera  1 , Eloy Rodriguez-Rodriguez  3   4 , Emilio Alarcón-Martín  1 , Adelina Orellana  1   3 , Pau Pastor  6   7 , Jordi Pérez-Tur  3   8   9 , Gerard Piñol-Ripoll  10   11 , Adolfo López de Munain  3   12   13   14 , Jose María García-Alberca  3   15 , Jose Luís Royo  16 , María J Bullido  3   17   18   19 , Victoria Álvarez  20   21 , Luis Miguel Real  22   23 , Arturo Corbatón Anchuelo  24 , Dulcenombre Gómez-Garre  24   25   26 , María Teresa Martínez Larrad  24   27 , Emilio Franco-Macías  28 , Pablo Mir  3   29 , Miguel Medina  3   30 , Raquel Sánchez-Valle  31 , Oriol Dols-Icardo  32 , María Eugenia Sáez  33 , Ángel Carracedo  5   34 , Lluís Tárraga  1   3 , Montse Alegret  1   3 , Sergi Valero  1   3 , Marta Marquié  1   3 , Mercè Boada  1   3 , Pascual Sánchez Juan  3   35 , Jose Enrique Cavazos  36   37 , Alfredo Cabrera-Socorro  38 , Amanda Cano  1   3 , Agustín Ruiz  39   40   41   42 ; Alzheimer’s Disease Neuroimaging Initiative
Affiliations
Meta-Analysis

Linking genomic and proteomic signatures to brain amyloid burden: insights from GR@ACE/DEGESCO

Raquel Puerta et al. Funct Integr Genomics. .

Abstract

Alzheimer's disease (AD) is a complex disease with a strong genetic component, yet many genetic risk factors remain unknown. We combined genome-wide association studies (GWAS) on amyloid endophenotypes measured in cerebrospinal fluid (CSF) and positron emission tomography (PET) as surrogates of amyloid pathology, which may provide insights into the underlying biology of the disease. We performed a meta-GWAS of CSF Aβ42 and PET measures combining six independent cohorts (n = 2,076). Given the opposite beta direction of Aβ phenotypes in CSF and PET measures, only genetic signals showing opposite directions were considered for analysis (n = 376,599). We explored the amyloidosis signature in the CSF proteome using SOMAscan proteomics (ACE cohort, n = 1,008), connected it with GWAS loci modulating amyloidosis and performed an enrichment analysis of overlapping hits. Finally, we compared our results with a large meta-analysis using publicly available datasets in CSF (n = 13,409) and PET (n = 13,116). After filtering the meta-GWAS, we observed genome-wide significance in the rs429358-APOE locus and annotated nine suggestive hits. We replicated the APOE loci using the large CSF-PET meta-GWAS, identifying multiple AD-associated genes including the novel GADL1 locus. Additionally, we found 1,387 FDR-significant SOMAscan proteins associated with CSF Aβ42 levels. The overlap among GWAS loci and proteins associated with amyloid burden was minimal (n = 35). The enrichment analysis revealed mechanisms connecting amyloidosis with the plasma membrane's anchored component, synapse physiology and mental disorders that were replicated in the large CSF-PET meta-analysis. Combining CSF and PET amyloid GWAS with CSF proteome analyses may effectively elucidate causative molecular mechanisms behind amyloid mobilization and AD physiopathology.

Keywords: Aβ42; CSF biomarkers; GWAS; PET tomography; Proteome.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: In accordance with Spanish regulations for the biomedical research field, all the protocols of this study were approved by the Clinical Research Ethics Commission of the Hospital Clinic (Barcelona, Spain) for ACE cohort and the Clinical Research Ethics Commission of Cantabria (Spain) for Valdecilla cohort. This research followed the Declaration of Helsinki. All participants were informed about the procedures and objectives of this study by a neurologist before signing an informed consent. Moreover, data confidentiality and privacy of patients were protected as specified in applicable laws. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Workflow of this study for each cohort and endophenotypes. ACE cohort used both Innotest ELISA kits (1) and CLEIA Lumipulse (2) for measuring CSF Aβ42 endophenotypes. This Flowchart was created using the Lucidchart online tool (https://www.lucidchart.com)
Fig. 2
Fig. 2
Plots of the Aβ burden meta-analysis combining data of CSF-PET endophenotypes. A (upper) Manhattan plot of our CSF-PET meta-analysis (n = 2,076). Results were filtered according to beta direction and dataset missingness. Suggestive independent markers were annotated with the nearest gene name. Mapped genes coloured in grey represent those that were not replicated in the PAD CSF-PET meta-GWAS. (lower) Manhattan plot of the PAD CSF-PET meta-analysis filtered (n = 23,532). Genome-wide significant independent markers were annotated with the nearest gene name. The Y-axis was restricted to visualize suggestive signals. The genome-wide significance threshold was set to P < 5e-08 (red line) and the suggestive threshold was set to P < 1e-05 (blue line). B Venn diagram representing the overlap between the top 500 ranking of independent genetic markers comparing the PAD and our amyloid burden meta-analysis. C Venn diagram representing the overlap between the top 500 ranking of independent genes in the PAD and our gene-based analysis
Fig. 3
Fig. 3
Forest plot of the meta-analysis association between the AD PRS. A CSF Aβ42, and (B) Aβ PET endophenotypes. The significance threshold was set to 0.05
Fig. 4
Fig. 4
Forest plot of the meta-analysis association between the AD PRS and dementia status as case–control. In ACE (305 cases and 703 controls, 30.25%), ADNI1 (94 cases and 285 controls, 24.80%) and ADNI2GO cohorts (27 cases and 385 controls, 6.55%)
Fig. 5
Fig. 5
Forest plot of the association between the AD, Aβ PRS and case–control status. PRS for AD (76 SNPs from Bellenguez et al. 2022) and Aβ42 (30 SNPs from Jansen et al. , 9 SNPs from our meta-analysis). The GR@ACE cohort included 7,437 cases and 8,999 controls
Fig. 6
Fig. 6
Associations between CSF SOMAscan and CSF Aβ42 levels. A Volcano plot only considering proteins with good inter-assay correlation (n = 2,682), significant proteins (FDR < 1.864e-05) were highlighted in red (n = 1,387). B) Top 10 results of the enrichment analysis of significant protein associations with CSF Aβ42 levels using the WebGestalt tool
Fig. 7
Fig. 7
Overlapping loci/proteins in genomic and proteomic analysis. A Venn diagram of the top 500 ranking of CSF Aβ42-associated proteins in the SOMAscan panel (orange), our gene-based MAGMA analysis (red), GWAS of CSF Aβ42 (Jansen et al. 2022) (dark blue) and our amyloid burden meta-analysis of filtered CSF-PET endophenotypes (light blue). B) Venn diagram of the top 500 ranking of CSF Aβ42-associated proteins in the SOMAscan panel (orange), PAD gene-based MAGMA meta-analysis (red) and PAD amyloid burden meta-analysis of filtered CSF-PET endophenotypes (light blue). C Top 10 enrichment analysis results of the overlapping proteins between our genomic and proteomic analyses. C Top 10 enrichment analysis results of the overlapping proteins between proteomic and PAD genomic analyses. The analysis was done using the WebGestalt tool
See this image and copyright information in PMC

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