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Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function ( p  < 4.9E-5, n up to 7289). Of these, 45 were replicated using SomaScan data, and three were replicated using Olink data at Bonferroni-corrected significance. Enrichment analysis linked the proteins associated with general cognitive function to cell signaling pathways and synapse architecture. Mendelian randomization analysis implicated higher levels of NECTIN2, a protein mediating viral entry into neuronal cells, with higher Alzheimer’s disease (AD) risk ( p  = 2.5E-26). Levels of 14 other protein measures were implicated as consequences of AD susceptibility ( p  < 2.0E-4). Proteins implicated as causes or consequences of AD susceptibility may provide new insight into the potential relationship between immunity and AD susceptibility as well as potential therapeutic targets. Analysis of circulating proteins across multiple cohorts identifies proteins that are associated with cognitive function and may serve as targets to understand the relationship between immunity and Alzheimer’s disease risk.

Background Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia. Its underlying mechanisms remain elusive and specific mechanism‐based drugs are lacking. Method We integrated more than 2,800 CSF and 4,600 plasma pQTL, derived from the largest proteomic studies so far (SOMAscan 7k and 4k; in up to 35,559 individuals), and the two most prevalent MRI‐markers of cSVD (MRI‐cSVD, white matter hyperintensities and perivascular spaces burden; in up to 48,454 individuals) in a Mendelian Randomization (MR) framework to identify causal and druggable targets for cSVD. Identified association were followed‐up using a multipronged approach: across fluids, proteomics platforms (Olink 3072, N=8,590) and lifespan (N=1,748), using both MR and individual‐level data. Result We found 51 proteins associated with MRI‐cSVD of which 46 in CSF and 9 in plasma. Among available significant CSF‐ and plasma‐proteins, 32% and 31% replicated in cross‐fluid and cross‐platform follow‐up, and 47% were associated with stroke and/or dementia at least at nominal significance. We found converging evidence that protein‐cSVD associations are enriched in extracellular matrix and immune response pathways. Immunity‐related proteins already showed association with MRI‐cSVD already in young adults in their twenties. Furthermore, we provide genetic support for drug repositioning opportunities for cSVD, including compounds crossing the blood brain barrier. Conclusion Together, these findings provide a novel proteogenomic signature of cSVD and pave the way for novel therapeutic developments.

INTRODUCTION Dementia is a multifactorial disease with Alzheimer's disease (AD) and vascular dementia (VaD) pathologies making the largest contributions. Yet, most genome‐wide association studies (GWAS) focus on AD. METHODS We conducted a GWAS of all‐cause dementia (ACD) and examined the genetic overlap with VaD. Our dataset includes 800,597 individuals, with 46,902 and 8702 cases of ACD and VaD, respectively. Known AD loci for ACD and VaD were replicated. Bioinformatic analyses prioritized genes that are likely functionally relevant and shared with closely related traits and risk factors. RESULTS For ACD, novel loci identified were associated with energy transport (SEMA4D), neuronal excitability (ANO3), amyloid deposition in the brain (RBFOX1), and magnetic resonance imaging markers of small vessel disease (SVD; HBEGF). Novel VaD loci were associated with hypertension, diabetes, and neuron maintenance (SPRY2, FOXA2, AJAP1, and PSMA3). DISCUSSION Our study identified genetic risks underlying ACD, demonstrating overlap with neurodegenerative processes, vascular risk factors, and cerebral SVD. Highlights We conducted the largest genome‐wide association study of all‐cause dementia (ACD) and vascular dementia (VaD). Known genetic variants associated with AD were replicated for ACD and VaD. Functional analyses identified novel loci for ACD and VaD. Genetic risks of ACD overlapped with neurodegeneration, vascular risk factors, and cerebral small vessel disease.

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.