Association between polygenic risk for Alzheimer’s disease, brain structure and cognitive abilities in UK Biobank

Abstract

Previous studies testing associations between polygenic risk for late-onset Alzheimer’s disease (LOAD-PGR) and brain magnetic resonance imaging (MRI) measures have been limited by small samples and inconsistent consideration of potential confounders. This study investigates whether higher LOAD-PGR is associated with differences in structural brain imaging and cognitive values in a relatively large sample of non-demented, generally healthy adults (UK Biobank). Summary statistics were used to create PGR scores for n = 32,790 participants using LDpred. Outcomes included 12 structural MRI volumes and 6 concurrent cognitive measures. Models were adjusted for age, sex, body mass index, genotyping chip, 8 genetic principal components, lifetime smoking, apolipoprotein (APOE) e4 genotype and socioeconomic deprivation. We tested for statistical interactions between APOE e4 allele dose and LOAD-PGR vs. all outcomes. In fully adjusted models, LOAD-PGR was associated with worse fluid intelligence (standardised beta [β] = −0.080 per LOAD-PGR standard deviation, p = 0.002), matrix completion (β = −0.102, p = 0.003), smaller left hippocampal total (β = −0.118, p = 0.002) and body (β = −0.069, p = 0.002) volumes, but not other hippocampal subdivisions. There were no significant APOE x LOAD-PGR score interactions for any outcomes in fully adjusted models. This is the largest study to date investigating LOAD-PGR and non-demented structural brain MRI and cognition phenotypes. LOAD-PGR was associated with smaller hippocampal volumes and aspects of cognitive ability in healthy adults and could supplement APOE status in risk stratification of cognitive impairment/LOAD.

Associations of Polygenic Risk Score for Late-Onset Alzheimer's Disease With Biomarkers

“…It should be noted that, although some limitations about AD-PRS still need to be addressed, the advanced development of large-GWAS studies and data-sharing policies are driving the AD-PRS to be constantly optimized and updated for drawing unambiguous conclusions about LOAD. For example, many researchers have identified that AD-PRS was associated with lower hippocampal volume in different target samples using different P T when using the publicly available International Genomics of Alzheimer's Project (IGAP) as the base sample (Mormino et al, 2016 ; Axelrud et al, 2018 ; Heidi et al, 2021 ; Tank et al, 2022 ). The underlying reason may be that the base sample from IGAP or UK Biobank is very large which can reduce the deviation caused by a small sample, and also offer the same risk alleles for the AD-PRS calculation which makes the most important risk alleles always included.…”

“…Alzheimer's disease (AD) which accounts for about 70% of dementia is an irreversible progressive polygenic neurodegenerative disease with insidious onset (Kametani and Hasegawa, 2018 ; Breijyeh and Karaman, 2020 ; Tank et al, 2022 ). By age at onset, AD can be classified into early-onset AD (EOAD) and late-onset AD (LOAD).…”

History of traumatic brain injury is associated with impaired cognition and imaging evidence of altered white matter tract integrity in UK Biobank (n=47,920)

“…By example, Alzheimer's disease (AD) is considered to exist on a prodromal continuum where, prior to a dementia diagnosis, evidence of evolving, subclinical pathology might be detectable through in tests of cognition and biomarkers studies, including brain imaging studies 11,12 . In line with this, known risk factors for AD have been shown to associate with poorer cognitive performance and measurable brain imaging changes 4 in individuals without dementia 13,14 . Diffusion tensor MRI (DT-MRI) includes multiple highly-sensitive metrics of WM integrity, which has previously been shown to decline with age, is influenced by risk factors for AD and is disrupted in patients with a diagnosis of AD 15,16 Previous imaging studies in individuals with prior histories of TBI and no known NDD diagnosis have shown relatively widespread effects in measures of WM integrity.…”

The Effect of Long-Term or Repeated Use of Antibiotics in Children and Adolescents on Cognitive Impairment in Middle-Aged and Older Person(s) Adults: A Cohort Study

“…Fluid intelligence (FI) is defined as the ability to reason and to solve new problems independently of previously acquired knowledge, and is related to working memory ( Salthouse and Pink, 2008 ), attention ( Cochrane et al, 2019 ), executive functions ( Lyall et al, 2016 ). FI is used as a tool to evaluate cognitive function ( Kindermann et al, 2012 ; Kendall et al, 2019 ; Tank et al, 2022 ). Cognitive impairment was defined as >1 standard deviation (SD) reduction in FI score ( Folley et al, 2019 ).…”