
==== Front
medRxiv
MEDRXIV
medRxiv
Cold Spring Harbor Laboratory

10.1101/2024.09.06.24313124
preprint
1
Article
Connecting genomic and proteomic signatures of amyloid burden in the brain
Puerta Raquel
de Rojas Itziar
García-González Pablo
Olivé Clàudia
Sotolongo-Grau Oscar
García-Sánchez Ainhoa
García-Gutiérrez Fernando
Montrreal Laura
Tartari Juan Pablo
Sanabria Ángela
Pytel Vanesa
Lage Carmen
Quintela Inés
Aguilera Nuria
Rodriguez-Rodriguez Eloy
Alarcón-Martín Emilio
Orellana Adelina
Pastor Pau
Pérez-Tur Jordi
Piñol-Ripoll Gerard
López de Munian Adolfo
García-Alberca Jose María
Royo Jose Luís
Bullido María Jesús
Álvarez Victoria
Real Luis Miguel
Anchuelo Arturo Corbatón
Gómez-Garre Dulcenombre
Martínez Larrad María Teresa
Franco-Macías Emilio
Mir Pablo
Medina Miguel
Sánchez-Valle Raquel
Icardo Oriol Dols-
Sáez María Eugenia
Carracedo Ángel
Tárraga Lluís
Alegret Montse
Valero Sergi
Marquié Marta
Boada Mercè
Juan Pascual Sánchez
Cavazos Jose Enrique
Cabrera Alfredo
Cano Amanda
Ruiz Agustín
Alzheimer’s Disease Neuroimaging Initiative
06 9 2024
2024.09.06.24313124https://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
http://medrxiv.org/lookup/doi/10.1101/2024.09.06.24313124
nihpp-2024.09.06.24313124.pdf
Abstract

Background

Alzheimer’s disease (AD) has a high heritable component characteristic of complex diseases, yet many of the 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 be helpful to understand the underlying biology of the disease.

Methods

We performed a meta-analysis of GWAS of CSF Aβ42 and PET measures combining six independent cohorts (n=2,076). Due to the opposite effect direction of Aβ phenotypes in CSF and PET measures, only genetic signals in the opposite direction were considered for analysis (n=376,599). Polygenic risk scores (PRS) were calculated and evaluated for AD status and amyloid endophenotypes. We then searched the CSF proteome signature of brain amyloidosis using SOMAscan proteomic data (Ace cohort, n=1,008) and connected it with GWAS results of loci modulating amyloidosis. Finally, we compared our results with a large meta-analysis using publicly available datasets in CSF (n=13,409) and PET (n=13,116). This combined approach enabled the identification of overlapping genes and proteins associated with amyloid burden and the assessment of their biological significance using enrichment analyses.

Results

After filtering the meta-GWAS, we observed genome-wide significance in the rs429358- APOE locus and nine suggestive hits were annotated. We replicated the APOE loci using the large CSF-PET meta-GWAS and identified multiple AD-associated genes as well as the novel GADL1 locus. Additionally, we found a significant association between the AD PRS and amyloid levels, whereas no significant association was found between any Aβ PRS with AD risk. CSF SOMAscan analysis identified 1,387 FDR-significant proteins associated with CSF Aβ42 levels. The overlap among GWAS loci and proteins associated with amyloid burden was very poor (n=35). The enrichment analysis of overlapping hits strongly suggested several signalling pathways connecting amyloidosis with the anchored component of the plasma membrane, synapse physiology and mental disorders that were replicated in the large CSF-PET meta-analysis.

Conclusions

The strategy of combining CSF and PET amyloid endophenotypes GWAS with CSF proteome analyses might be effective for identifying signals associated with the AD pathological process and elucidate causative molecular mechanisms behind the amyloid mobilization in AD.
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