Genes and age reveal new insights into cognitive variability

A recent study published in Nature Medicine examines the effects of specific genes and age on cognitive performance. The researchers discuss the potential utility of their findings for creating cognitively and genotypically stratified cohorts for future epidemiological and intervention studies.

Current estimates indicate that up to 140 million people could develop dementia by 2050, despite the development of new treatments.

Many new drugs approved for the treatment of neurodegenerative diseases are initially tested in people with advanced and irreversible disease, which often results in limited effectiveness of these therapies. Thus, improving the current understanding of preclinical and early stages of neurodegeneration may help evaluate the effectiveness of new treatments to prevent further neurodegeneration and restore patients' quality of life.

This motivated the current study, which included people who could be followed over long periods to understand the development of dementia and perhaps the effect of medications on it.

All study participants were from the National Institute for Health and Care Research (NIHR) in England, which was originally set up as a volunteer database for experimental medicine and clinical trials.

Both genotypes and phenotypes of all study participants were available, with most of them being healthy at baseline. For this purpose, the Genes and Cognition (G&C) cohort, comprising over 21,000 participants within the NIHR BioResource, was identified for a targeted call.

The current study examined changes in cognitive performance (phenotype) with age, associated genotypes, and demographic and socioeconomic information. The study included eleven cognitive tests across various domains, as well as two new measures of cognitive ability, designated G6 and G4.

G4 is a summary score that includes short-term memory, fluid intelligence, and crystallized intelligence, while G6 is a score that summarizes reaction time, attention, processing speed, and executive function. The genetic background for both measures was used to identify new genetic loci that influence cognitive status throughout the human lifespan.

The results of the study showed that all 13 parameters were positively correlated with each other, with the exception of vocabulary (VY), which showed both positive and negative correlations.

Study results were adjusted for the type of device used, which would otherwise affect test scores. However, future research should also consider that device type varies by age, socioeconomic and educational status, which contributes to different phenotypes.

Cognitive performance decreased with age in all tests except VY, which increased with age. This observation contradicts earlier studies reporting a decrease in VY in people over 60 years of age.

Gender explained 0.1-1.33% of the variance in cognitive performance, indicating that both sexes experience similar types and degrees of cognitive decline over time. G4 and G6 explained most of the variance in each test.

The two groups with the least education performed the worst, with the education vs. Cognitive ability plot being linear. The presence of deprivation was negatively associated with cognitive performance in almost all tests.

Apolipoprotein E (APOE) genotype, for which data was available for nearly 10,000 participants, did not correlate with phenotype in any of the tests. The Alzheimer's disease polygenic risk score (AD-PRS) approach did not show a significant effect on cognitive performance.

Genotype-phenotype correlations were stronger than phenotypic correlations. Moreover, the heritability of the phenotype ranged from 0.06 to 0.28, which was similar to previous studies.

Functional mapping of G4-associated genes has identified genes involved in microglia-mediated immunological pathways in cognitive impairment in older adults. For G6, glycogen branching enzyme 1 (GBE1), which is involved in glycogen metabolism, was associated with cognitive performance, suggesting a role in overall cognitive performance.

Genome-wide association studies (GWAS) identified several new loci, one of which explained 185 times more variation in G4 compared to APOE. A strong genetic correlation was also found between IQ and G4 and G6.

The fluid and crystallized intelligence domain may be a better marker of future educational success, as G4 had more than twofold genetic correlation with educational achievement compared to G6. It is important to note that G4 and G6 did not show strong correlations with Alzheimer's disease (AD), indicating that normal cognition and AD have distinct genetic factors.

Conclusions The current study used multiple tools to distinguish genetic mechanisms of normal cognition from mechanisms of neurodegeneration. Recognition of these different pathways is necessary to identify molecular targets to prevent or alleviate age-related cognitive decline.

All study participants were Caucasian, which limits the generalizability of the results. Moreover, the current study did not assess all cognitive domains.

Future studies are needed to perform functional mapping of G4-associated genes. However, this is an extremely difficult task because animal cognition does not reflect changes in normal human cognition with age.

We are currently repeating cognitive profiling of all participants to identify cognitive trajectories over time, expanding it to include more diverse ethnic groups, and conducting long-read genome sequencing to enrich the potential challenge for both academics and industrial researchers.