Alzheimer disease genetic risk factor<i>APOE</i>e4 and cognitive abilities in 111,739 UK Biobank participants

Lyall, Donald M.; Ritchie, Stuart J.; Davies, Gail; Cullen, Breda; López-de-Celis, Carlos; Bailey, Mark E.S.; Anderson, Jana; Evans, Jennifer; McKay, D; McIntosh, Andrew M.; Sattar, Naveed; Smith, Daniel J.; Deary, Ian J.; Pell, Jill P.

doi:10.1093/ageing/afw068

Cited by 49 publications

(48 citation statements)

References 24 publications

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“…For genotyping, we used the UK Biobank version 3 imputed data, which has undergone extensive quality control procedures as described by the UK Biobank genetics team (79). The APOE e genotype was approximated based on the two APOE e single-nucleotide polymorphisms -rs7412 and rs429358 (80). Further information on the genotyping process is available in the UK Biobank documentation (www.ukbiobank.ac.uk/scientists-3/genetic-data), including detailed technical documentation (genotyping_workflow.pdf).…”

Section: Genotypingmentioning

confidence: 99%

Women’s brain aging: effects of sex-hormone exposure, pregnancies, and genetic risk for Alzheimer’s disease

A-M.

Barth

Kaufmann

et al. 2019

Preprint

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Estrogen exposure may influence women's risk of Alzheimer's disease, but little is known about how it affects normal brain aging. Recent findings from the UK Biobank demonstrate less evidence of brain aging in women with a history of multiple childbirths. Here, we investigated the link between brain aging, estrogen exposure, and APOE genotype beyond the effects of parity in 16,854 UK Biobank women. Machine learning was used to predict brain age based on neuroimaging-derived measures, and the difference between an individual's predicted and chronological age was used as an estimate of brain aging. Cumulative estrogen exposure was estimated using an index including age at menarche and menopause, BMI, time since menopause, and duration of hormone replacement therapy. Endogenous hormone exposure was approximated by reproductive span, while exogenous exposure was estimated by usage, onset, and duration of hormone replacement therapy and oral contraceptives. Higher cumulative, endogenous, and exogenous estrogen exposure were each linked to higher brain age relative to chronological age. Earlier onset of hormone replacement therapy, particularly before menopause, was associated with less evident brain aging in APOE e4 carriers only, while higher circulating estradiol levels during menopause were linked to more evident brain aging in carriers and less evident brain aging in non-carriers. The results indicate that estrogen exposure and parity may differentially relate to women's brain aging, and that APOE e4-specific associations between estrogen and brain aging may be of importance for optimizing hormone replacement therapy regimes in perimenopausal women. Women's health | Estrogens | Parity | Apolipoproteins E | Neuroimaging | Machine learningCorrespondence: a.m.g.d.lange@psykologi.uio.no claudia.barth@medisin.uio.no

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Section: Genotypingmentioning

confidence: 99%

Women’s brain aging: effects of sex-hormone exposure, pregnancies, and genetic risk for Alzheimer’s disease

A-M.

Barth

Kaufmann

et al. 2019

Preprint

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“…The failure to detect an APOE effect may be cohort specific, as previous UK Biobank analyses have not detected the hypothesized APOE effects (14). The worldwide frequency of APOE e2, e3 and e4 alleles are 8.4%, 77.9% and 13.7%, respectively (15).…”

Section: Discussionmentioning

confidence: 98%

Sex-Dependent Age Trajectories of Subcortical Brain Structures: Analysis of Large-Scale Percentile Models and Shape Morphometry

Ching

Abaryan

Santhalingam

et al. 2020

Preprint

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Modeling of structural brain variation over the lifespan is important to better understand factors contributing to healthy aging and risk for neurological conditions such as Alzheimer's disease. Even so, we lack normative data on brain morphometry across the adult lifespan in large, well-powered samples. Here, in a large population-based sample of 26,440 adults from the UK Biobank (age: 44-81 yrs.), we created normative percentile charts for MRI-derived subcortical volumes. Next, we investigated associations between these morphometric measures and the strongest known genetic risk factor for late-onset Alzheimer's disease (APOE genotype) and mapped the spatial distribution of age-by-sex interactions using computational surface mesh modeling and shape analysis. Vertex-wise shape mapping supplements traditional gross volumetric approaches to reveal finer-grained variations across functionally important brain subcompartments. Normative curves revealed volumetric loss with age, as expected, for all subcortical brain structures except for the lateral ventricles, which expanded with age. Surprisingly, no volumetric associations with APOE genotype were detected, despite the very large sample size. Age-related trajectories for volumes differed in women versus men, and surface-based statistical maps revealed the spatial distribution of the age-by-sex interaction. Subcortical volumes declined faster in men than women over the full age range, but after age 60, fewer structures showed sex-dependent trajectories, indicating similar volumetric changes in older men and women. Large-scale statistical modeling of age effects on brain structures may drive new insights into individual differences in brain aging and help to identify factors that promote healthy brain aging and risk for disease.

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“…However, AD itself does not necessarily increase the risk of CAD. In fact, a recent study showed that APOE ε 4 does not interact with CAD [ 24 ]. Interestingly, our results implied that patients with AD might have protective factors to CAD, with the underdiagnosis of CAD or ischemic stroke in AD having been one possible explanation.…”

Section: Discussionmentioning

confidence: 99%

Metabolic Risk Factors of Alzheimer’s Disease, Dementia with Lewy Bodies, and Normal Elderly: A Population-Based Study

Cheng

Tsao

et al. 2018

Behavioural Neurology

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Background Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) share many risk factors. Evidence suggests that metabolic risk factors are important to AD; however, their association with DLB is unclear. The risk of cardiovascular diseases (CVD) associated with AD and DLB is also uncertain. Thus, this nationwide, population-based study was designed to evaluate the metabolic and CVD risks in AD and DLB. Materials and Methods Data were obtained from the Taiwan National Health Insurance Research Database. AD patients, DLB patients, and normal control (NC) individuals from 1996 to 2013 were enrolled for risk assessment. Results In total, 7544 NC individuals, 1324 AD patients, and 562 DLB patients were enrolled. Participants with one or more metabolic risk factors had significantly higher odds of AD or DLB. No significant differences in metabolic risk factors were observed between DLB and AD patients. AD patients had a lower risk of CVD (aHR = 0.67, 95% CI = 0.59–0.76, p value < 0.001) and coronary artery disease (CAD) (aHR = 0.59, 95% CI = 0.51–0.69, p value < 0.001) than NC. DLB patients had a higher risk of ischemic stroke (aHR = 2.27, 95% CI = 1.68–3.06, p value < 0.001) than NC. Conclusion Metabolic risk factors are important in AD and DLB. Patients with AD might have a lower risk of CAD and ischemic strokes. Patients with DLB might have a higher risk of ischemic stroke.

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Alzheimer disease genetic risk factorAPOEe4 and cognitive abilities in 111,739 UK Biobank participants

Abstract: future research in large independent cohorts should continue to investigate this important question, which has potential implications for aetiology related to dementia and cognitive impairment.

Cited by 49 publications

References 24 publications

Women’s brain aging: effects of sex-hormone exposure, pregnancies, and genetic risk for Alzheimer’s disease

Women’s brain aging: effects of sex-hormone exposure, pregnancies, and genetic risk for Alzheimer’s disease

Sex-Dependent Age Trajectories of Subcortical Brain Structures: Analysis of Large-Scale Percentile Models and Shape Morphometry

Metabolic Risk Factors of Alzheimer’s Disease, Dementia with Lewy Bodies, and Normal Elderly: A Population-Based Study

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