Accelerated aging in the brain, epigenetic aging in blood, and polygenic risk for schizophrenia

Teeuw, Jalmar; Ori, Anil P.S.; Brouwer, Rachel M.; Zwarte, Sonja M C de; Schnack, Hugo G.; Pol, Hilleke E. Hulshoff; Ophoff, Roel A.

doi:10.1016/j.schres.2021.04.005

Cited by 31 publications

(28 citation statements)

References 72 publications

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“…The second key finding highlights that brain age was found to be largely independent of methylation ages in late adolescence. This interpretation is consistent with Teeuw et al (2021), Zheng et al (2022) and Cole et al (2018), whereby only weak associations were detected between brain age and methylation age in a sample of younger or older adults. Our findings, however, do contradict previous research in older individuals, which reported associations between neuron density or brain vascular lesions, as measures of brain age, and methylation age (Hillary et al, 2021; Lu et al, 2017).…”

Section: Discussionsupporting

confidence: 87%

“…Similar results were reported by Zheng et al (2022) in a sample of 326 adults. Teeuw et al (2021) also found little evidence that two measures of methylation age associated with brain age in 172 adults with and without schizophrenia. An additional study, using genetic data, reported low genetic correlations between different measures of methylation age and brain age (Gialluisi et al, 2021).…”

Section: Introductionmentioning

confidence: 94%

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Associations between methylation age and brain age in late adolescence

Sanders

Baltramonaityte

Donohoe

et al. 2022

Preprint

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Recent research suggests that biological age, based on DNA methylation or neuroimaging measures, may predict health traits in adulthood more accurately than chronological age. However, whether these findings apply to earlier stages in life is unknown. We therefore aimed to characterise the performance of and interdependence between measures of biological age during adolescence, leveraging longitudinal data from a subsample of young adolescents from the population-based ALSPAC cohort (n=386). We derived four methylation age measures in late adolescence (17-19 years) and a measure of brain age derived from structural neuroimaging data (18-24 years). We then examined associations between these measures of biological age, and their relationship with five measures of physical, cognitive and mental health (8-18 years). Brain age was largely independent of different measures of methylation age, even after accounting for age, cell type composition, array and study (beta range: -0.60 to 0.17, all p>0.05). Smoking and BMI predicted three measures of advanced methylation age (beta range: -0.39 to 0.52, all p<0.05), but not brain age. Depressive symptoms and cognitive ability were unrelated to all measures of biological age. Our findings emphasize the variability of and independence between these methylation- and brain-based measures of age in adolescents. They also highlight the importance of tracking the mosaic of ageing in younger populations.

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Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 94%

Associations between methylation age and brain age in late adolescence

Sanders

Baltramonaityte

Donohoe

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…It was reported that accelerated brain aging occurred in the early stage of the disease course ( Schnack et al, 2016 ). Also, the extent of advanced brain age might be correlated with polygenic risk for SZ ( Teeuw et al, 2021 ). In addition, advanced WM aging has been observed in SZ by using diffusion MRI techniques ( Tonnesen et al, 2020 , Wang et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Detection of advanced brain aging in schizophrenia and its structural underpinning by using normative brain age metrics

Chen

Hwang

Tung

et al. 2022

NeuroImage: Clinical

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“…Studies of brain age gap estimation (brainAGE) suggest a hypothesis of accelerated brain aging in neuropsychiatric disorders ( Dunlop et al, 2021 , Han et al, 2020 , Han et al, 2021 , Teeuw et al, 2021 ). The hypothesis posits that a greater gap between chronological age and estimated brain age is associated with unfavorable clinical outcomes in patients with neuropsychiatric illnesses.…”

Section: Introductionmentioning

confidence: 99%