Novel modelling approaches to elucidate the genetic architecture of resilience to Alzheimer's disease

Abstract Up to 30% of older adults meet pathological criteria for a diagnosis of Alzheimer’s disease at autopsy yet never show signs of cognitive impairment. Recent work has highlighted genetic drivers of this resilience, or better-than-expected cognitive performance given a level of neuropathology, that allow the aged brain to protect itself from the downstream consequences of amyloid and tau deposition. However, models of resilience have been constrained by reliance on measures of neuropathology, substantially limiting the number of participants available for analysis. We sought to determine if novel approaches using APOE allele status, age, and other demographic variables as a proxy for neuropathology could still effectively quantify resilience and uncover novel genetic drivers associated with better-than-expected cognitive performance while vastly expanding sample size and statistical power. Leveraging 20,513 participants from eight well-characterized cohort studies of aging, we determined the effects of genetic variants on resilience metrics using mixed-effects regressions. The outcome of interest was residual cognitive resilience, quantified from residuals in three cognitive domains (memory, executive function, and language) and built within two frameworks: “silver” models, which obviate the requirement for neuropathological data (n=17,241), and “gold” models, which include post-mortem neuropathological assessments (n=3,272). We then performed cross-ancestry genome wide association studies (European ancestry n=18,269, African ancestry n=2,244), gene and pathway-based tests, and genetic correlation analyses. All analyses were conducted across all participants and repeated when restricted to those with unimpaired cognition at baseline. Despite different modeling approaches, the silver and gold phenotypes were highly correlated (R=0.77-0.88) and displayed comparable performance in quantifying better-than or worse-than-expected cognition, enabling silver-gold meta-analyses. Genetic correlation analyses highlighted associations of resilience with multiple neuropsychiatric and cardiovascular traits (PFDR values < 5.0x10-2). In pathway-level tests, we observed three significant associations with resilience: metabolism of amino acids and derivatives (PFDR=4.1x10-2), negative regulation of transforming growth factor beta production (PFDR=1.9x10-2), and severe acute respiratory syndrome (PFDR=3.9x10-4). Finally, in single-variant analyses, we identified a locus on chromosome 17 approaching genome-wide significance among cognitively unimpaired participants (index single nucleotide polymorphism: rs757022, minor allele frequency = 0.18, β=0.08, P=1.1x10-7). The top variant at this locus (rs757022) was significantly associated with expression of numerous ATP-binding cassette genes in brain. Overall, through validating a novel modeling approach, we demonstrate the utility of silver models of resilience to increase statistical power and participant diversity.