Genetic architecture of multiple domains of cognition among SuperAgers
Alaina Durant, Shubhabrata Mukherjee, Michael L. Lee, Seo‐Eun Choi, Phoebe Scollard, Emily H. Trittschuh, Jesse B. Mez, William S. Bush, Brian W. Kunkle, Adam C. Naj, Katherine A. Gifford, Michael L. Cuccaro, Carlos Cruchaga, Jason J. Hassenstab, Margaret A. Pericak‐Vance, Lindsay A. Farrer, Li‐San Wang, Jonathan L. Haines, Angela L. Jefferson, Walter A. Kukull, C Dirk Keene, Andrew J. Saykin, Paul M Thompson, Eden R. Martin, David A. A Bennett, Lisa L. Barnes, Julie A Schneider, Paul K Crane, Marilyn S. Albert, Sterling C Johnson, Corinne D. Engelman, Richard Mayeux, Badri N Vardarajan, Logan C Dumitrescu, Timothy J. Hohman,- Psychiatry and Mental health
- Cellular and Molecular Neuroscience
- Geriatrics and Gerontology
- Neurology (clinical)
- Developmental Neuroscience
- Health Policy
- Epidemiology
Abstract
Background
A recently recognized subset of older individuals are an anomaly of cognitive decline; the “SuperAgers”, unsurprisingly named, achieve cognitive scores equivalent to much younger cognitively normal (CN) middle‐aged adults. Using longitudinal cognitive data harmonized across eight cohorts of aging and Alzheimer’s Dementia (AD), we investigated the genetic drivers of SuperAging.
Method
Harmonized memory, executive function, and language scores were estimated leveraging latent variable modeling and made available through the ADSP Phenotype Harmonization Consortium. SuperAgers (N = 1,095) were defined as individuals over 80 years with a mean sex‐adjusted memory score equal or exceeding CN individuals aged 50‐60, score within one age and sex‐adjusted standard deviation in the other two cognitive domains, and remain CN for all longitudinal visits. Young Cases (N = 1,906) were defined as individuals aged 50‐75 with a clinical diagnosis of AD. Old Controls (N = 3,247) were defined as CN individuals over 80, scoring within one age‐ and sex‐adjusted standard deviation in all three domains. We performed a GWAS on non‐Hispanic Whites using logistic regression comparing SuperAgers and their counterparts (Young Cases and Old Controls) with covaried adjustment for age, sex, education, and principal components for population substructure.
Result
Comparing SuperAgers with Young Cases (Figure 1), only variants in the well‐established APOE region were associated with genome‐wide significance (GWAS; P<510−8). Additionally, we observed a locus on chromosome 13 approach GWS (rs138699163, P = 6.5610−8). The locus centered on a relatively uncharacterized ncRNA, MIR4500. Analyses comparing SuperAgers to Old Controls did not find any GWS associations, with the strongest association observed at rs116535931 on chromosome 5 (P = 1.5210−6).
Conclusion
Our extreme‐phenotype GWAS comparing SuperAgers to Young Cases identified established and novel loci for AD. However, larger sample sizes may allow better characterization of the genetic architecture of SuperAging. Future analyses will extend to Case comparison groups to include Old Cases (age>80 years) and All Cases (age>50 years) and Control comparison groups to include Young Controls (age between 50‐60) and Agnostic Controls (age>50 years) with similar criteria.