The following is a summary of “SNP rs6859 in NECTIN2 gene is associated with underlying heterogeneous trajectories of cognitive changes in older adults,” published in the February 2024 issue of Neurology by Rajendrakumar et al.
The variability in functional decline linked to dementia, including Alzheimer’s disease (AD), is not consistent among individuals, with some of this diversity potentially attributed to genetic differences.
Researchers conducted a retrospective study evaluating the impact of the SNP rs6859 in the nectin cell adhesion molecule 2 (NECTIN2) gene, a significant risk factor for AD, on cognitive decline trajectories in elderly participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
They analyzed data from 1,310 participants in the ADNI database for multivariate analysis. Longitudinal assessments of Mini-Mental State Examination (MMSE) scores were utilized to explore cognitive change trajectories in participants classified as cognitively normal, having AD, or experiencing other cognitive deficits. Various statistical methods were employed, including multiple linear regression, linear mixed models, and latent class analyses, to examine the relationship between the SNP rs6859 and MMSE scores.
The results showed that the regression coefficient per one allele dose of the SNP rs6859 was independently associated with MMSE in both cross-sectional (-2.23, P<0.01) and linear mixed models (-2.26, P<0.01) analyses. The latent class model with three distinct subgroups (class 1: stable and gradual decline, class 2: intermediate and late decline, and class 3: lowest and irregular) performed best in the posterior classification, with 42.67% (n = 559), 21.45% (n = 281), and 35.88% (n = 470) classified as class 1, class 2, and class 3. In the heterogeneous linear mixed model, the regression coefficient per one allele dose of rs6859 – A risk allele was significantly associated with MMSE class 1 and class 2 memberships and related decline: Class 1 (-2.28, 95% CI: -4.05, -0.50, P<0.05), Class 2 (-5.56, 95% CI: -9.61, -1.51, P<0.01), and Class 3 (-0.37, 95% CI: -1.62, 0.87, P=0.55).
Investigators concluded three distinct latent subclass groups in the ADNI cohort, with the SNP rs6859 potentially serving as a genetic predictor for MMSE trajectory variation. They also identified classes with higher baseline MMSE.
Source: bmcneurol.biomedcentral.com/articles/10.1186/s12883-024-03577-4