In advanced age, some individuals maintain a stable cognitive trajectory while others experience a rapid decline. Such variation in cognitive trajectory is only partially explained by traditional neurodegenerative pathologies. Hence, to identify new processes underlying variation in cognitive trajectory, we perform an unbiased proteome-wide association study of cognitive trajectory in a discovery ( n = 104) and replication cohort ( n = 39) of initially cognitively unimpaired, longitudinally assessed older-adult brain donors. We find 579 proteins associated with cognitive trajectory after meta-analysis. Notably, we present evidence for increased neuronal mitochondrial activities in cognitive stability regardless of the burden of traditional neuropathologies. Furthermore, we provide additional evidence for increased synaptic abundance and decreased inflammation and apoptosis in cognitive stability. Importantly, we nominate proteins associated with cognitive trajectory, particularly the 38 proteins that act independently of neuropathologies and are also hub proteins of protein co-expression networks, as promising targets for future mechanistic studies of cognitive trajectory.

Alzheimer’s disease (AD) is a complex genetic disorder with no effective treatments. More than 20 common markers have been identified, which are associated with AD. Recently, several rare variants have been identified in APP, TREM2, and UNC5C that affect risk for AD. Despite the many successes, the genetic architecture of AD remains unsolved. We used Genome-wide Complex Trait Analysis to 1) estimate phenotypic variance explained by genetics, 2) calculate genetic variance explained by known AD SNPs, and 3) identify the genomic locations of variation that explain the remaining unexplained genetic variance. In total, 53.24% of phenotypic variance is explained by genetics, but known AD SNPs only explain 30.62% of the genetic variance. Of the unexplained genetic variance, approximately 41% is explained by unknown SNPs in regions adjacent to known AD SNPs, and the remaining unexplained genetic variance outside these regions.

Identifying genes and proteins for cognitive resilience (ie, targets that may be associated with slowing or preventing cognitive decline regardless of the presence, number, or combination of common neuropathologic conditions) provides a complementary approach to developing novel therapeutics for the treatment and prevention of Alzheimer disease and related dementias.OBJECTIVE To identify proteins associated with cognitive resilience via a proteome-wide association study of the human dorsolateral prefrontal cortex. DESIGN, SETTING, AND PARTICIPANTSThis study used data from 391 community-dwelling older persons who participated in the Religious Orders Study and the Rush Memory and Aging Project.

Cerebral atherosclerosis contributes to dementia via unclear processes. We performed proteomic sequencing of dorsolateral prefrontal cortex in 438 older individuals and found associations between cerebral atherosclerosis and reduced synaptic signaling and RNA splicing and increased oligodendrocyte development and myelination. Consistently, single-cell RNA sequencing showed cerebral atherosclerosis associated with higher oligodendrocyte abundance. A subset of proteins and modules associated with cerebral atherosclerosis was also associated with Alzheimer’s disease, suggesting shared mechanisms.

Depression is a common condition but current treatments for depression are only effective in a subset of individuals. To identify novel treatment targets, we integrated depression GWAS results (N=500,199) with human brain proteomes (N=376) to perform a proteome-wide association study (PWAS) of depression, followed by Mendelian randomization. We identified 19 genes consistent with being causal in depression, acting via their cis -regulated brain protein abundance. We replicated 9 of these genes using an independent depression GWAS (N=307,353) and human brain proteomic dataset (N=152). Eleven of these 19 genes also had their cis -regulated mRNA levels associated with depression based on integration of the depression GWAS with human brain transcriptomes (N=888). Meta-analysis of the discovery and replication PWAS identified 25 brain proteins consistent with being causal in depression, and 20 were not previously implicated in depression by GWAS. Together, these findings provide novel promising brain protein targets for further mechanistic and therapeutic studies.