Genes and age reveal new insights into cognitive variability, study finds

By Dr. Liji Thomas, MDMay 16 2024Reviewed by Benedette Cuffari, M.Sc.

A recent study published in the journal Nature Medicine explores the effect of specific genes and age on cognition. The researchers discuss the potential utility of their findings in creating genotype- and cognition-stratified cohorts available for future epidemiological and interventional studies.

Study: Dynamics of cognitive variability with age and its genetic underpinning in NIHR BioResource Genes and Cognition cohort participants. Image Credit: FOUR.STOCK / Shutterstock.com

About the study

Current estimates indicate that up to 140 million people may develop dementia by 2050, despite the development of novel therapies.

Many novel drugs that are approved to treat neurodegenerative diseases are initially tested in individuals with advanced and irreversible diseases, which often leads to limited efficacy of these therapeutics. Thus, by improving the current understanding of the preclinical and early stages of neurodegeneration, researchers could evaluate the efficacy of novel treatments in these patients to prevent further neurodegeneration and restore their quality of life.

This motivated the current study, which comprised individuals who can be followed up over long periods to elucidate the development of, and possibly the effects of drugs on, dementia.

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

Both the genotypes and phenotypes of all study participants were available, most of whom were healthy at baseline. To this end, the Genes and Cognition (G&C) cohort, which included over 21,000 participants within the NIHR BioResource, was identified for targeted recall.

The current study explored changes in cognitive performance (phenotype) with age, associated genotypes, as well as demographic and socioeconomic information. Eleven cognition tests over a range of domains were included in the study, as well as two new measures of cognitive ability denoted as G6 and G4.

G4 reflects a summary measure incorporating short-term memory, fluid, and crystallized intelligence, whereas G6 is a measure summarizing reaction time, attention, processing speed, and executive functioning. The genetic background for both G4 and G6 was used to identify new genetic loci that affected cognitive status throughout an individual’s life. 

What did the study show?

All 13 parameters positively correlated with each other, except for vocabulary (VY), which showed partly positive and negative correlations.

The study results were adjusted for the type of device used, which was otherwise reflected in the test scores. However, future studies should also account for the fact that device type differs with age, socioeconomic, and educational status, thus contributing to different phenotypes.

Cognitive performance decreased with age across all tests, except for VY, which increased with age. This observation contradicts earlier studies reporting a decline in VY in individuals 60 years of age and older.

Gender accounted for 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 accounted for most of the variance in each test.

The two groups with the least education exhibited the lowest performance, with the graph of education vs. cognitive ability being linear. The presence of deprivation had a negative relationship with cognitive performance across almost all tests.

The apolipoprotein E (APOE) genotype, for which data was available for nearly 10,000 participants, did not correlate with the phenotype in any of the tests. The Alzheimer’s disease-polygenic risk scores (AD-PRS) approach did not show any significant impact on cognition.

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

Functional mapping of G4-associated genes identified genes involved in microglia-mediated immunological pathways in cognitive impairment in the elderly. For G6, glycogen branching enzyme 1 (GBE1), which is a gene involved in glycogen metabolism, was associated with cognition, thus indicating its role in general cognitive ability.

Genome-wide association studies (GWAS) identified several novel loci, one of which explained 185-fold more variance in G4 compared to APOE. A strong genetic correlation was also observed between the intelligence quotient and G4 and G6.

Fluid and crystallized intelligence domains may be better markers of future educational success, as G4 had more than two-fold the genetic correlation of G6 with educational attainment. Importantly, G4 and G6 failed to show strong correlations with Alzheimer’s disease (AD), thus indicating that normal cognition and AD have different underlying genetic factors.

Conclusions

The current study used multiple tools to differentiate the genetic mechanisms of normal cognition from those of neurodegeneration. Recognizing these different pathways is essential to identifying molecular targets to avert or alleviate age-related cognitive impairment.

All study participants were White Europeans, which limited the generalizability of the results. Furthermore, the current study did not evaluate all cognitive domains.

Future studies are needed to perform functional mapping of the genes associated with G4. However, this is an extremely difficult task, as animal cognition fails to reflect changes in normal human cognition with age.

We are currently repeating the cognitive profiling of all participants to determine cognitive trajectories over time, expanding to include more diverse ethnic groups and carrying out long-read genome sequencing to enrich the recall potential for both academic and industry researchers.”