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Cárdenas SI, Waizman Y, Truong V, Sellery P, Stoycos SA, Yeh FC, Rajagopalan V, Saxbe DE. White matter microstructure organization across the transition to fatherhood. Dev Cogn Neurosci 2024; 67:101374. [PMID: 38615555 PMCID: PMC11021911 DOI: 10.1016/j.dcn.2024.101374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 03/27/2024] [Accepted: 04/02/2024] [Indexed: 04/16/2024] Open
Abstract
The transition to parenthood remains an understudied window of potential neuroplasticity in the adult brain. White matter microstructural (WMM) organization, which reflects structural connectivity in the brain, has shown plasticity across the lifespan. No studies have examined how WMM organization changes from the prenatal to postpartum period in men becoming fathers. This study investigates WMM organization in men transitioning to first-time fatherhood. We performed diffusion-weighted imaging to identify differences in WMM organization, as indexed by fractional anisotropy (FA). We also investigated whether FA changes were associated with fathers' postpartum mental health. Associations between mental health and WMM organization have not been rarely examined in parents, who may be vulnerable to mental health problems. Fathers exhibited reduced FA at the whole-brain level, especially in the cingulum, a tract associated with emotional regulation. Fathers also displayed reduced FA in the corpus callosum, especially in the forceps minor, which is implicated in cognitive functioning. Postpartum depressive symptoms were linked with increases and decreases in FA, but FA was not correlated with perceived or parenting stress. Findings provide novel insight into fathers' WMM organization during the transition to parenthood and suggest postpartum depression may be linked with fathers' neuroplasticity during the transition to parenthood.
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Affiliation(s)
- Sofia I Cárdenas
- Department of Psychology, University of Southern California, USA
| | - Yael Waizman
- Department of Psychology, University of Southern California, USA
| | - Van Truong
- Department of Psychology, University of Southern California, USA
| | - Pia Sellery
- Department of Psychology, University of Southern California, USA
| | - Sarah A Stoycos
- Department of Psychiatry and the Behavioral Sciences, Keck School of Medicine, University of Southern California, USA
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, USA
| | - Vidya Rajagopalan
- Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, USA
| | - Darby E Saxbe
- Department of Psychology, University of Southern California, USA.
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Dong C, Thalamuthu A, Jiang J, Mather KA, Sachdev PS, Wen W. Brain structural covariances in the ageing brain in the UK Biobank. Brain Struct Funct 2024; 229:1165-1177. [PMID: 38625555 PMCID: PMC11147885 DOI: 10.1007/s00429-024-02794-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 03/21/2024] [Indexed: 04/17/2024]
Abstract
The morphologic properties of brain regions co-vary or correlate with each other. Here we investigated the structural covariances of cortical thickness and subcortical volumes in the ageing brain, along with their associations with age and cognition, using cross-sectional data from the UK Biobank (N = 42,075, aged 45-83 years, 53% female). As the structural covariance should be estimated in a group of participants, all participants were divided into 84 non-overlapping, equal-sized age groups ranging from the youngest to the oldest. We examined 84 cortical thickness covariances and subcortical covariances. Our findings include: (1) there were significant differences in the variability of structural covariance in the ageing process, including an increased variance, and a decreased entropy. (2) significant enrichment in pairwise correlations between brain regions within the occipital lobe was observed in all age groups; (3) structural covariance in older age, especially after the age of around 64, was significantly different from that in the youngest group (median age 48 years); (4) sixty-two of the total 528 pairs of cortical thickness correlations and 10 of the total 21 pairs of subcortical volume correlations showed significant associations with age. These trends varied, with some correlations strengthening, some weakening, and some reversing in direction with advancing age. Additionally, as ageing was associated with cognitive decline, most of the correlations with cognition displayed an opposite trend compared to age associated patterns of correlations.
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Affiliation(s)
- Chao Dong
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW, Sydney, Australia.
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW, Sydney, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW, Sydney, Australia
| | - Karen A Mather
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW, Sydney, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW, Sydney, Australia
- Neuropsychiatric Institute (NPI), Prince of Wales Hospital, Randwick, NSW, 2031, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW, Sydney, Australia
- Neuropsychiatric Institute (NPI), Prince of Wales Hospital, Randwick, NSW, 2031, Australia
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Shen T, Sheriff S, You Y, Jiang J, Schulz A, Francis H, Mirzaei M, Saks D, Palanivel V, Basavarajappa D, Chitranshi N, Gupta V, Wen W, Sachdev PS, Jia H, Sun X, Graham SL, Gupta VK. Brain-Derived Neurotrophic Factor Val66Met is Associated with Variation in Cortical Structure in Healthy Aging Subjects. Aging Dis 2024:AD.2024.0346. [PMID: 38916728 DOI: 10.14336/ad.2024.0346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 05/13/2024] [Indexed: 06/26/2024] Open
Abstract
Aging is associated with progressive brain atrophy and declines in learning and memory, often attributed to hippocampal or cortical deterioration. The role of brain-derived neurotrophic factor (BDNF) in modulating the structural and functional changes in the brain and visual system, particularly in relation to BDNF Val66Met polymorphism, remains underexplored. In this present cross-sectional observational study, we aimed to assess the effects of BDNF polymorphism on brain structural integrity, cognitive function, and visual pathway alterations. A total of 108 older individuals with no evidence of dementia and a mean (SD) age of 67.3 (9.1) years were recruited from the Optic Nerve Decline and Cognitive Change (ONDCC) study cohort. The BDNF Met allele carriage had a significant association with lower entorhinal cortex volume (6.7% lower compared to the Val/Val genotype, P = 0.02) and posterior cingulate volume (3.2% lower than the Val/Val group, P = 0.03), after adjusting for confounding factors including age, sex and estimated total intracranial volumes (eTIV). No significant associations were identified between the BDNF Val66Met genotype and other brain volumetric or diffusion measures, cognitive performances, or vision parameters except for temporal retinal nerve fibre layer thickness. Small but significant correlations were found between visual structural and functional, cognitive, and brain morphological metrics. Our findings suggest that carriage of BDNF Val66Met polymorphism is associated with lower entorhinal cortex and posterior cingulate volumes and may be involved in modulating the cortical morphology along the aging process.
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Affiliation(s)
- Ting Shen
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, National Clinical Research Center for Eye Diseases, Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
- Save Sight Institute, The University of Sydney, Sydney, NSW 2000, Australia
| | - Samran Sheriff
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
| | - Yuyi You
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
- Save Sight Institute, The University of Sydney, Sydney, NSW 2000, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Angela Schulz
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
| | - Heather Francis
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
- Neurology Department, Royal North Shore Hospital, St Leonards NSW 2065, Australia
| | - Mehdi Mirzaei
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
| | - Danit Saks
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
| | | | | | - Nitin Chitranshi
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
| | - Veer Gupta
- Faculty of Health, Deakin University, VIC 3125, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Randwick NSW 2031, Australia
| | - Huixun Jia
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, National Clinical Research Center for Eye Diseases, Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Xiaodong Sun
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, National Clinical Research Center for Eye Diseases, Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Stuart L Graham
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
- Save Sight Institute, The University of Sydney, Sydney, NSW 2000, Australia
| | - Vivek K Gupta
- Macquarie Medical School, Macquarie University, Sydney, NSW 2109, Australia
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Mewton L, Visontay R, Hughes G, Browning C, Wen W, Topiwala A, Draper B, Crawford JD, Brodaty H, Sachdev PS. Longitudinal alcohol-related brain changes in older adults: The Sydney Memory and Ageing Study. Addict Biol 2024; 29:e13402. [PMID: 38797559 PMCID: PMC11128337 DOI: 10.1111/adb.13402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 03/25/2024] [Accepted: 04/22/2024] [Indexed: 05/29/2024]
Abstract
Increases in harmful drinking among older adults indicate the need for a more thorough understanding of the relationship between later-life alcohol use and brain health. The current study investigated the relationships between alcohol use and progressive grey and white matter changes in older adults using longitudinal data. A total of 530 participants (aged 70 to 90 years; 46.0% male) were included. Brain outcomes assessed over 6 years included total grey and white matter volume, as well as volume of the hippocampus, thalamus, amygdala, corpus callosum, orbitofrontal cortex and insula. White matter integrity was also investigated. Average alcohol use across the study period was the main exposure of interest. Past-year binge drinking and reduction in drinking from pre-baseline were additional exposures of interest. Within the context of low-level average drinking (averaging 11.7 g per day), higher average amount of alcohol consumed was associated with less atrophy in the left (B = 7.50, pFDR = 0.010) and right (B = 5.98, pFDR = 0.004) thalamus. Past-year binge-drinking was associated with poorer white matter integrity (B = -0.013, pFDR = 0.024). Consuming alcohol more heavily in the past was associated with greater atrophy in anterior (B = -12.73, pFDR = 0.048) and posterior (B = -17.88, pFDR = 0.004) callosal volumes over time. Across alcohol exposures and neuroimaging markers, no other relationships were statistically significant. Within the context of low-level drinking, very few relationships between alcohol use and brain macrostructure were identified. Meanwhile, heavier drinking was negatively associated with white matter integrity.
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Affiliation(s)
- Louise Mewton
- The Matilda Centre for Mental Health and Substance Use, Faculty of Medicine and HealthUniversity of SydneySydneyAustralia
| | - Rachel Visontay
- The Matilda Centre for Mental Health and Substance Use, Faculty of Medicine and HealthUniversity of SydneySydneyAustralia
| | - Gerard Hughes
- Centre for Healthy Brain Ageing, Faculty of Medicine and HealthUniversity of New South WalesSydneyAustralia
| | - Catherine Browning
- Centre for Healthy Brain Ageing, Faculty of Medicine and HealthUniversity of New South WalesSydneyAustralia
| | - Wei Wen
- Centre for Healthy Brain Ageing, Faculty of Medicine and HealthUniversity of New South WalesSydneyAustralia
| | - Anya Topiwala
- Nuffield Department Population Health, Big Data InstituteUniversity of OxfordOxfordUK
| | - Brian Draper
- Centre for Healthy Brain Ageing, Faculty of Medicine and HealthUniversity of New South WalesSydneyAustralia
| | - John D. Crawford
- Centre for Healthy Brain Ageing, Faculty of Medicine and HealthUniversity of New South WalesSydneyAustralia
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, Faculty of Medicine and HealthUniversity of New South WalesSydneyAustralia
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, Faculty of Medicine and HealthUniversity of New South WalesSydneyAustralia
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Du J, Pan Y, Jiang J, Lam BCP, Thalamuthu A, Chen R, Tsang IW, Sachdev PS, Wen W. White matter brain age as a biomarker of cerebrovascular burden in the ageing brain. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01758-3. [PMID: 38424358 DOI: 10.1007/s00406-024-01758-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 01/13/2024] [Indexed: 03/02/2024]
Abstract
As the brain ages, it almost invariably accumulates vascular pathology, which differentially affects the cerebral white matter. A rich body of research has investigated the link between vascular risk factors and the brain. One of the less studied questions is that among various modifiable vascular risk factors, which is the most debilitating one for white matter health? A white matter specific brain age was developed to evaluate the overall white matter health from diffusion weighted imaging, using a three-dimensional convolutional neural network deep learning model in both cross-sectional UK biobank participants (n = 37,327) and a longitudinal subset (n = 1409). White matter brain age gap (WMBAG) was the difference between the white matter age and the chronological age. Participants with one, two, and three or more vascular risk factors, compared to those without any, showed an elevated WMBAG of 0.54, 1.23, and 1.94 years, respectively. Diabetes was most strongly associated with an increased WMBAG (1.39 years, p < 0.001) among all risk factors followed by hypertension (0.87 years, p < 0.001) and smoking (0.69 years, p < 0.001). Baseline WMBAG was associated significantly with processing speed, executive and global cognition. Significant associations of diabetes and hypertension with poor processing speed and executive function were found to be mediated through the WMBAG. White matter specific brain age can be successfully targeted for the examination of the most relevant risk factors and cognition, and for tracking an individual's cerebrovascular ageing process. It also provides clinical basis for the better management of specific risk factors.
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Affiliation(s)
- Jing Du
- Centre for Healthy Brain Aging (CHeBA), School of Psychiatry, UNSW Sydney, Kensington, New South Wales, 2052, Australia.
| | - Yuangang Pan
- Centre for Frontier AI Research (CFAR), A*STAR, Singapore, 138623, Singapore
- Australian Artificial Intelligence Institute (AAII), UTS, Sydney, NSW, 2007, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Aging (CHeBA), School of Psychiatry, UNSW Sydney, Kensington, New South Wales, 2052, Australia
| | - Ben C P Lam
- Centre for Healthy Brain Aging (CHeBA), School of Psychiatry, UNSW Sydney, Kensington, New South Wales, 2052, Australia
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Aging (CHeBA), School of Psychiatry, UNSW Sydney, Kensington, New South Wales, 2052, Australia
| | - Rory Chen
- Centre for Healthy Brain Aging (CHeBA), School of Psychiatry, UNSW Sydney, Kensington, New South Wales, 2052, Australia
| | - Ivor W Tsang
- Centre for Frontier AI Research (CFAR), A*STAR, Singapore, 138623, Singapore
- Australian Artificial Intelligence Institute (AAII), UTS, Sydney, NSW, 2007, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Aging (CHeBA), School of Psychiatry, UNSW Sydney, Kensington, New South Wales, 2052, Australia
- Neuropsychiatric Institute (NPI), Euroa Centre, Prince of Wales Hospital, Randwick, NSW, 2031, Australia
| | - Wei Wen
- Centre for Healthy Brain Aging (CHeBA), School of Psychiatry, UNSW Sydney, Kensington, New South Wales, 2052, Australia.
- Neuropsychiatric Institute (NPI), Euroa Centre, Prince of Wales Hospital, Randwick, NSW, 2031, Australia.
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