Literature DB >> 33495545

Accelerated brain aging predicts impulsivity and symptom severity in depression.

Katharine Dunlop1,2, Lindsay W Victoria3,4, Jonathan Downar5,6, Faith M Gunning7,8, Conor Liston9,10.   

Abstract

Multiple structural and functional neuroimaging measures vary over the course of the lifespan and can be used to predict chronological age. Accelerated brain aging, as quantified by deviations in the MRI-based predicted age with respect to chronological age, is associated with risk for neurodegenerative conditions, bipolar disorder, and mortality. Whether age-related changes in resting-state functional connectivity are accelerated in major depressive disorder (MDD) is unknown, and, if so, it is unclear if these changes contribute to specific cognitive weaknesses that often occur in MDD. Here, we delineated age-related functional connectivity changes in a large sample of normal control subjects and tested whether brain aging is accelerated in MDD. Furthermore, we tested whether accelerated brain aging predicts individual differences in cognitive function. We trained a support vector regression model predicting age using resting-state functional connectivity in 710 healthy adults aged 18-89. We applied this model trained on normal aging subjects to a sample of actively depressed MDD participants (n = 109). The difference between predicted brain age and chronological age was 2.11 years greater (p = 0.015) in MDD patients compared to control participants. An older MDD brain age was significantly associated with increased impulsivity and, in males, increased depressive severity. Unexpectedly, accelerated brain aging was also associated with increased placebo response in a sham-controlled trial of high-frequency repetitive transcranial magnetic stimulation targeting the dorsomedial prefrontal cortex. Our results indicate that MDD is associated with accelerated brain aging, and that accelerated aging is selectively associated with greater impulsivity and depression severity.

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Year:  2021        PMID: 33495545      PMCID: PMC8115107          DOI: 10.1038/s41386-021-00967-x

Source DB:  PubMed          Journal:  Neuropsychopharmacology        ISSN: 0893-133X            Impact factor:   7.853


  79 in total

1.  Decreased functional connectivity by aging is associated with cognitive decline.

Authors:  Keiichi Onoda; Masaki Ishihara; Shuhei Yamaguchi
Journal:  J Cogn Neurosci       Date:  2012-07-11       Impact factor: 3.225

2.  Age-associated cognitive decline.

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3.  Age-related prefrontal impairments implicate deficient prediction of future reward in older adults.

Authors:  Ben Eppinger; Hauke R Heekeren; Shu-Chen Li
Journal:  Neurobiol Aging       Date:  2015-04-25       Impact factor: 4.673

4.  Cognitive reserve is associated with quality of life: A population-based study.

Authors:  Elvira Lara; Ai Koyanagi; Félix Caballero; Joan Domènech-Abella; Marta Miret; Beatriz Olaya; Laura Rico-Uribe; Jose Luis Ayuso-Mateos; Josep Maria Haro
Journal:  Exp Gerontol       Date:  2016-11-05       Impact factor: 4.032

Review 5.  Selective review of cognitive aging.

Authors:  Timothy A Salthouse
Journal:  J Int Neuropsychol Soc       Date:  2010-08-02       Impact factor: 2.892

Review 6.  Resting-state functional connectivity in normal brain aging.

Authors:  Luiz Kobuti Ferreira; Geraldo F Busatto
Journal:  Neurosci Biobehav Rev       Date:  2013-01-17       Impact factor: 8.989

Review 7.  Functional brain connectivity using fMRI in aging and Alzheimer's disease.

Authors:  Emily L Dennis; Paul M Thompson
Journal:  Neuropsychol Rev       Date:  2014-02-23       Impact factor: 7.444

8.  Reduced functional segregation between the default mode network and the executive control network in healthy older adults: A longitudinal study.

Authors:  Kwun Kei Ng; June C Lo; Joseph K W Lim; Michael W L Chee; Juan Zhou
Journal:  Neuroimage       Date:  2016-03-19       Impact factor: 6.556

9.  Mild cognitive impairment in the elderly: predictors of dementia.

Authors:  C Flicker; S H Ferris; B Reisberg
Journal:  Neurology       Date:  1991-07       Impact factor: 9.910

Review 10.  Subjective wellbeing, health, and ageing.

Authors:  Andrew Steptoe; Angus Deaton; Arthur A Stone
Journal:  Lancet       Date:  2014-11-06       Impact factor: 79.321

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  5 in total

1.  Machine learning assessment of risk factors for depression in later adulthood.

Authors:  Fengqing Zhang; Jiangtao Gou
Journal:  Lancet Reg Health Eur       Date:  2022-05-11

Review 2.  Brain-based mechanisms of late-life depression: Implications for novel interventions.

Authors:  Faith M Gunning; Lauren E Oberlin; Maddy Schier; Lindsay W Victoria
Journal:  Semin Cell Dev Biol       Date:  2021-05-12       Impact factor: 7.499

3.  Age-Related Decrease in Default-Mode Network Functional Connectivity Is Accelerated in Patients With Major Depressive Disorder.

Authors:  Shixiong Tang; Zhipeng Wu; Hengyi Cao; Xudong Chen; Guowei Wu; Wenjian Tan; Dayi Liu; Jie Yang; Yicheng Long; Zhening Liu
Journal:  Front Aging Neurosci       Date:  2022-01-10       Impact factor: 5.750

4.  Editorial: Accelerated Brain Aging: Different Diseases-Different Imaging Patterns.

Authors:  Dusko B Kozic; Majda M Thurnher; Jasmina Boban; Pia C Sundgren
Journal:  Front Neurol       Date:  2022-04-07       Impact factor: 4.003

5.  Accelerated functional brain aging in major depressive disorder: evidence from a large scale fMRI analysis of Chinese participants.

Authors:  Yunsong Luo; Wenyu Chen; Jiang Qiu; Tao Jia
Journal:  Transl Psychiatry       Date:  2022-09-21       Impact factor: 7.989

  5 in total

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