2026-04-17T20:14:12Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/429492025-12-13T21:15:44Zcom_2072_6col_2072_452952

00925njm 22002777a 4500 dc Nevado-Holgado, Alejo J. author Ribe, Elena author Thei, Laura author Furlong, Laura I., 1971- author Mayer, Miguel Ángel, 1960- author Quan, Jie author Richardson, Jill C. author Cavanagh, Jonathan author NIMA Consortium author Lovestone, Simon author 2019-11-25T08:30:53Z 2019-11-25T08:30:53Z 2019 As genome-wide association studies (GWAS) have grown in size, the number of genetic variants that have been associated per disease has correspondingly increased. Despite this increase in the number of single-nucleotide polymorphisms (SNPs) identified per disease, their biological interpretation has in many cases remained elusive. To address this, we have combined GWAS results with orthogonal sources of evidence, namely the current knowledge of molecular pathways; real-world clinical data from six million patients; RNA expression across tissues from Alzheimer's disease (AD) patients, and purpose-built rodent models for experimental validation. In more detail, first we show that when examined at a pathway level, analysis of all GWAS studies groups AD in a cluster with disorders of immunity and inflammation. Using clinical data, we show that the degree of comorbidity of these diseases with AD correlates with the strength of their genetic association with molecular participants in the Janus kinases/signal transducer and activator of transcription (JAK-STAT) pathway. Using four independent RNA expression datasets we then find evidence for the altered regulation of JAK-STAT pathway genes in AD. Finally, we use both in vitro and in vivo rodent models to demonstrate that Aβ induces gene expression of the key drivers of this pathway, providing experimental evidence to validate these data-driven observations. These results therefore nominate JAK-STAT anomalies as a prominent aetiopathological event in AD and hence a potential target for therapeutic development, and moreover demonstrate a de novo multi-modal approach to derive information from rapidly increasing genomic datasets. This work was supported by the Wellcome Trust [104025], the European Union’s Horizon 2020 research and innovation programme 2014-2020 under Grant Agreement No 634143, the MRC Data Pathfinder award [MC_PC_17215], and the NIHR Oxford Health Biomedical Research Centre. Alzheimer JAK-STAT Animal models Genomics Multimodal Transcriptomics Genetic and real-world clinical data, combined with empirical validation, nominate jak-stat signaling as a target for Alzheimer's disease therapeutic development