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Lv S, Tai H, Sun J, Zhuo Z, Duan Y, Liu S, Wang A, Zhang Z, Liu Y. Mapping macrostructural and microstructural brain alterations in patients with neuronal intranuclear inclusion disease. Neuroradiology 2024:10.1007/s00234-024-03406-y. [PMID: 38866958 DOI: 10.1007/s00234-024-03406-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 06/09/2024] [Indexed: 06/14/2024]
Abstract
BACKGROUND AND PURPOSE Neuronal intranuclear inclusion disease (NIID) is a rare complex neurodegenerative disorder presents with various radiological features. The study aimed to investigate the structural abnormalities in NIID using multi-shell diffusion MR. MATERIALS AND METHODS Twenty-eight patients with adult-onset NIID and 32 healthy controls were included. Volumetric and diffusion MRI measures, including volume, fractional anisotropy (FA), mean diffusivity (MD), intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF) of six brain structures, including cortex, subcortical GM, cerebral WM, cerebellar GM and WM, and brainstem, were obtained and compared between NIID and healthy controls. Associations between MRI measures and clinical variables were investigated. RESULTS Brain lesions of NIID included corticomedullary junction lesions on DWI, confluent leukoencephalopathy, lesions on callosum, cerebellar middle peduncle, cerebellar paravermal area and brainstem, and brain atrophy. Compared to healthy controls, NIID showed extensive volume loss of all the six brain regions (all p < 0.001); lower FA in cerebral WM (p < 0.001); higher MD in all WM regions; lower ODI in cortex (p < 0.001); higher ODI in subcortical GM (p < 0.001) and brainstem (p = 0.016); lower ICVF in brainstem (p = 0.001), and cerebral WM (p < 0.001); higher ISOVF in all the brain regions (p < 0.001). Higher MD of cerebellar WM was associated with worse cognitive level as evaluated by MoCA scores (p = 0.011). CONCLUSIONS NIID patients demonstrated widespread brain atrophy but heterogeneous diffusion alterations. Cerebellar WM integrity impairment was correlated with the cognitive decline. The findings of the current study offer a sophisticated picture of brain structural alterations in NIID.
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Affiliation(s)
- Shan Lv
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Hongfei Tai
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jun Sun
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhizheng Zhuo
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Shaocheng Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - An Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Zaiqiang Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
- China National Clinical Research Center for Neurological Diseases, Beijing, China.
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
- Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, China.
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Cong CH, Li PL, Qiao Y, Li YN, Yang JT, Zhao L, Zhu XR, Tian S, Cao SS, Liu JR, Su JJ. Association between household size and risk of incident dementia in the UK Biobank study. Sci Rep 2024; 14:11026. [PMID: 38744903 PMCID: PMC11094068 DOI: 10.1038/s41598-024-61102-6] [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: 11/21/2023] [Accepted: 05/02/2024] [Indexed: 05/16/2024] Open
Abstract
Currently, the relationship between household size and incident dementia, along with the underlying neurobiological mechanisms, remains unclear. This prospective cohort study was based on UK Biobank participants aged ≥ 50 years without a history of dementia. The linear and non-linear longitudinal association was assessed using Cox proportional hazards regression and restricted cubic spline models. Additionally, the potential mechanisms driven by brain structures were investigated by linear regression models. We included 275,629 participants (mean age at baseline 60.45 years [SD 5.39]). Over a mean follow-up of 9.5 years, 6031 individuals developed all-cause dementia. Multivariable analyses revealed that smaller household size was associated with an increased risk of all-cause dementia (HR, 1.06; 95% CI 1.02-1.09), vascular dementia (HR, 1.08; 95% CI 1.01-1.15), and non-Alzheimer's disease non-vascular dementia (HR, 1.09; 95% CI 1.03-1.14). No significant association was observed for Alzheimer's disease. Restricted cubic splines demonstrated a reversed J-shaped relationship between household size and all-cause and cause-specific dementia. Additionally, substantial associations existed between household size and brain structures. Our findings suggest that small household size is a risk factor for dementia. Additionally, brain structural differences related to household size support these associations. Household size may thus be a potential modifiable risk factor for dementia.
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Affiliation(s)
- Chao-Hua Cong
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizhaoju Road, Huangpu District, Shanghai, 200011, China
| | - Pan-Long Li
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, No. 7 Weiwu Road, Zhengzhou, 450001, China
- School of Electrical and Information Engineering, Zhengzhou University of Light Industry, No. 5 Dongfeng Road, Zhengzhou, 450001, China
| | - Yuan Qiao
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizhaoju Road, Huangpu District, Shanghai, 200011, China
| | - Yu-Na Li
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizhaoju Road, Huangpu District, Shanghai, 200011, China
| | - Jun-Ting Yang
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizhaoju Road, Huangpu District, Shanghai, 200011, China
| | - Lei Zhao
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizhaoju Road, Huangpu District, Shanghai, 200011, China
| | - Xi-Rui Zhu
- School of Electrical and Information Engineering, Zhengzhou University of Light Industry, No. 5 Dongfeng Road, Zhengzhou, 450001, China
| | - Shan Tian
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizhaoju Road, Huangpu District, Shanghai, 200011, China
| | - Shan-Shan Cao
- Department of Neurology, Gongli Hospital of Shanghai Pudong New Area, No. 219 Miaopu Road, Pudong New District, Shanghai, 200135, China
| | - Jian-Ren Liu
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizhaoju Road, Huangpu District, Shanghai, 200011, China.
| | - Jing-Jing Su
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizhaoju Road, Huangpu District, Shanghai, 200011, China.
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Lotter LD, Saberi A, Hansen JY, Misic B, Paquola C, Barker GJ, Bokde ALW, Desrivieres S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Bruehl R, Martinot JL, Paillere ML, Artiges E, Papadopoulos Orfanos D, Paus T, Poustka L, Hohmann S, Froehner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Nees F, Banaschewski T, Eickhoff SB, Dukart J. Regional patterns of human cortex development colocalize with underlying neurobiology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.05.539537. [PMID: 37205539 PMCID: PMC10187287 DOI: 10.1101/2023.05.05.539537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cerebral cortex development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8,000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.
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Jiang GQ, He YK, Li TF, Qin QR, Wang DN, Huang F, Sun YH, Li J. Association of psychological resilience and cognitive function in older adults: Based on the Ma' anshan Healthy Aging Cohort Study. Arch Gerontol Geriatr 2024; 116:105166. [PMID: 37639840 DOI: 10.1016/j.archger.2023.105166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 08/17/2023] [Accepted: 08/20/2023] [Indexed: 08/31/2023]
Abstract
OBJECTIVES The purpose of this study was to explore whether psychological resilience can influence changes in cognitive function in older adults and provide clues and rationale for improving cognitive function and preventing the onset of dementia in the geriatric population. METHODS A total of 2495 older adults aged 60 years or older from the Ma' anshan Healthy Aging Cohort were included in the study. Participants' cognitive functioning and psychological resilience were measured using the MMSE (mini-mental state examination) scale and the SRQS (stress resilience quotient scale) scale during the 5 years of follow-up, and the association was explored. Those with MMSE scores ≤ 17 in the illiterate group, ≤ 20 in the elementary school group, and ≤ 24 in the secondary school and above group were considered cognitive impairment. RESULTS The prevalence of cognitive impairment increased from 6.89% to 14.30% during the five years of follow-up. At 5-year follow-up, the group with the highest psychological resilience had 41 (6.83%) individuals whose cognitive functioning changed from normal to cognitive impairment, while the group with the worst psychological resilience had 114 (18.33%) individuals. The study also found a significant effect of different levels of psychological resilience on changes in cognitive functioning after adjusting for potential confounders. Compared with Q1 (the reference group), the Odds ratio of cognitive decline in Q2, Q3 and Q4 groups were 0.51(0.42,0.64), 0.37(0.29,0.47) and 0.19(0.13,0.27), respectively. CONCLUSIONS Improving the level of psychological resilience in older adults may be one way to prevent the incidence of cognitive impairment.
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Affiliation(s)
- Guo-Qing Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Ye-Ke He
- School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Teng-Fei Li
- School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Qi-Rong Qin
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Ma'anshan Center for Disease Control and prevention, Ma'anshan, Anhui, 243011, China
| | - Dan-Ni Wang
- School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Fen Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Ye-Huan Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Center for Evidence-Based Practice, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Jie Li
- School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China.
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Huang X, Yuan S, Ling Y, Cheng H, Tan S, Xu A, Lyu J. Evaluating the effect of kidney function on brain volumes and dementia risk in the UK Biobank. Arch Gerontol Geriatr 2024; 116:105157. [PMID: 37634304 DOI: 10.1016/j.archger.2023.105157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/06/2023] [Accepted: 08/10/2023] [Indexed: 08/29/2023]
Abstract
OBJECTIVE To investigate the association between kidney function with the risk of dementia and brain volumes. METHODS A total of 452,996 UK Biobank participants with calculated glomerular filtration rate (eGFR) and albumin-to-creatinine ratio (ACR) were included. We utilized Cox proportional hazards regression models and restricted cubic spline analyses to examine the relationships between kidney function and the risk of all-cause dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VD). Additionally, we explored the correlations between kidney function and brain magnetic resonance indicators among 40,380 participants. RESULTS During a median follow-up of 12 years, 5,258 incident ACD cases were identified. The deterioration of kidney function was associated with an increased risk of ACD. When compared to eGFR ≥ 90 ml/min/1.73 m², the highest risk increase was evident for eGFRcre < 30 ml/min/1.73 m² (adjusted HR = 2.372, 95% CI: 1.444-3.897, P < 0.001), with eGFRcys showing greater significance (adjusted HR = 3.045, 95% CI: 2.212-4.191, P < 0.001), especially in relation to AD. Compared to the ACR level in the range of 3-30 mg/mmol, the category of > 30 mg/mmol was associated with an increased risk of ACD (adjusted HR = 1.720, 95% CI: 1.350-2.190, P < 0.001). Moreover, the decline in kidney function was associated with the total brain volume atrophy and reduction in certain subcortical areas. CONCLUSIONS Our study indicates that diminished kidney function, as evidenced by a drop in eGFR and aggravated proteinuria, elevates dementia risk. Associated brain structural changes further underpin this connection from a neuro-pathophysiological perspective.
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Affiliation(s)
- Xiaxuan Huang
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Shiqi Yuan
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Yitong Ling
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Hongtao Cheng
- School of Nursing, Jinan University, Guangzhou 510630, China
| | - Shanyuan Tan
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Anding Xu
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Jun Lyu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou 510630, China.
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Han JDJ. LncRNAs: the missing link to senescence nuclear architecture. Trends Biochem Sci 2023; 48:618-628. [PMID: 37069045 DOI: 10.1016/j.tibs.2023.03.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/24/2023] [Accepted: 03/24/2023] [Indexed: 04/19/2023]
Abstract
During cellular senescence and organismal aging, cells display various molecular and morphological changes. Although many aging-related long noncoding RNAs (lncRNAs) are highly associated with senescence-associated secretory phenotype, the roles of lncRNAs in senescence-associated nuclear architecture and morphological changes are just starting to emerge. Here I review lncRNAs associated with nuclear structure establishment and maintenance, their aging-related changes, and then focus on the pervasive, yet underappreciated, role of RNA double-strand DNA triplexes for lncRNAs to recognize targeted genomic regions, making lncRNAs the nexus between DNA and proteins to regulate nuclear structural changes. Finally, I discuss the future of deciphering direct links of lncRNA changes to various nuclear morphology changes assisted by artificial intelligence and genetic perturbations.
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Affiliation(s)
- Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, China; International Center for Aging and Cancer (ICAC), The First Affiliated Hospital, Hainan Medical University, Haikou, China.
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7
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Mennecke A, Khakzar KM, German A, Herz K, Fabian MS, Liebert A, Blümcke I, Kasper BS, Nagel AM, Laun FB, Schmidt M, Winkler J, Dörfler A, Zaiss M. 7 tricks for 7 T CEST: Improving the reproducibility of multipool evaluation provides insights into the effects of age and the early stages of Parkinson's disease. NMR IN BIOMEDICINE 2023; 36:e4717. [PMID: 35194865 DOI: 10.1002/nbm.4717] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 02/10/2022] [Accepted: 02/21/2022] [Indexed: 05/23/2023]
Abstract
The objective of the current study was to optimize the postprocessing pipeline of 7 T chemical exchange saturation transfer (CEST) imaging for reproducibility and to prove this optimization for the detection of age differences and differences between patients with Parkinson's disease versus normal subjects. The following 7 T CEST MRI experiments were analyzed: repeated measurements of a healthy subject, subjects of two age cohorts (14 older, seven younger subjects), and measurements of 12 patients with Parkinson's disease. A slab-selective, B 1 + -homogeneous parallel transmit protocol was used. The postprocessing, consisting of motion correction, smoothing, B 0 -correction, normalization, denoising, B 1 + -correction and Lorentzian fitting, was optimized regarding the intrasubject and intersubject coefficient of variation (CoV) of the amplitudes of the amide pool and the aliphatic relayed nuclear Overhauser effect (rNOE) pool within the brain. Seven "tricks" for postprocessing accomplished an improvement of the mean voxel CoV of the amide pool and the aliphatic rNOE pool amplitudes of less than 5% and 3%, respectively. These postprocessing steps are: motion correction with interpolation of the motion of low-signal offsets (1) using the amide pool frequency offset image as reference (2), normalization of the Z-spectrum using the outermost saturated measurements (3), B 0 correction of the Z-spectrum with moderate spline smoothing (4), denoising using principal component analysis preserving the 11 highest intensity components (5), B 1 + correction using a linear fit (6) and Lorentzian fitting using the five-pool fit model (7). With the optimized postprocessing pipeline, a significant age effect in the amide pool can be detected. Additionally, for the first time, an aliphatic rNOE contrast between subjects with Parkinson's disease and age-matched healthy controls in the substantia nigra is detected. We propose an optimized postprocessing pipeline for CEST multipool evaluation. It is shown that by the use of these seven "tricks", the reproducibility and, thus, the statistical power of a CEST measurement, can be greatly improved and subtle changes can be detected.
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Affiliation(s)
- Angelika Mennecke
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Katrin M Khakzar
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Alexander German
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Kai Herz
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
| | - Moritz S Fabian
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Andrzej Liebert
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Ingmar Blümcke
- Institute of Neuropathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Burkhard S Kasper
- Department of Neurology, Epilepsy Centre, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Armin M Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Frederik B Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Manuel Schmidt
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jürgen Winkler
- Department of Neurology, Epilepsy Centre, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Arnd Dörfler
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Moritz Zaiss
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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Fingelkurts AA, Fingelkurts AA. Turning Back the Clock: A Retrospective Single-Blind Study on Brain Age Change in Response to Nutraceuticals Supplementation vs. Lifestyle Modifications. Brain Sci 2023; 13:brainsci13030520. [PMID: 36979330 PMCID: PMC10046544 DOI: 10.3390/brainsci13030520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 03/17/2023] [Accepted: 03/19/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND There is a growing consensus that chronological age (CA) is not an accurate indicator of the aging process and that biological age (BA) instead is a better measure of an individual's risk of age-related outcomes and a more accurate predictor of mortality than actual CA. In this context, BA measures the "true" age, which is an integrated result of an individual's level of damage accumulation across all levels of biological organization, along with preserved resources. The BA is plastic and depends upon epigenetics. Brain state is an important factor contributing to health- and lifespan. METHODS AND OBJECTIVE Quantitative electroencephalography (qEEG)-derived brain BA (BBA) is a suitable and promising measure of brain aging. In the present study, we aimed to show that BBA can be decelerated or even reversed in humans (N = 89) by using customized programs of nutraceutical compounds or lifestyle changes (mean duration = 13 months). RESULTS We observed that BBA was younger than CA in both groups at the end of the intervention. Furthermore, the BBA of the participants in the nutraceuticals group was 2.83 years younger at the endpoint of the intervention compared with their BBA score at the beginning of the intervention, while the BBA of the participants in the lifestyle group was only 0.02 years younger at the end of the intervention. These results were accompanied by improvements in mental-physical health comorbidities in both groups. The pre-intervention BBA score and the sex of the participants were considered confounding factors and analyzed separately. CONCLUSIONS Overall, the obtained results support the feasibility of the goal of this study and also provide the first robust evidence that halting and reversal of brain aging are possible in humans within a reasonable (practical) timeframe of approximately one year.
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Knodt AR, Meier MH, Ambler A, Gehred MZ, Harrington H, Ireland D, Poulton R, Ramrakha S, Caspi A, Moffitt TE, Hariri AR. Diminished Structural Brain Integrity in Long-term Cannabis Users Reflects a History of Polysubstance Use. Biol Psychiatry 2022; 92:861-870. [PMID: 36008158 PMCID: PMC9637748 DOI: 10.1016/j.biopsych.2022.06.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/26/2022] [Accepted: 06/14/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cannabis legalization and use are outpacing our understanding of its long-term effects on brain and behavior, which is fundamental for effective policy and health practices. Existing studies are limited by small samples, cross-sectional measures, failure to separate long-term from recreational use, and inadequate control for other substance use. Here, we address these limitations by determining the structural brain integrity of long-term cannabis users in the Dunedin Study, a longitudinal investigation of a population-representative birth cohort followed to midlife. METHODS We leveraged prospective measures of cannabis, alcohol, tobacco, and other illicit drug use in addition to structural neuroimaging in 875 study members at age 45 to test for differences in both global and regional gray and white matter integrity between long-term cannabis users and lifelong nonusers. We additionally tested for dose-response associations between continuous measures of cannabis use and brain structure, including careful adjustments for use of other substances. RESULTS Long-term cannabis users had a thinner cortex, smaller subcortical gray matter volumes, and higher machine learning-predicted brain age than nonusers. However, these differences in structural brain integrity were explained by the propensity of long-term cannabis users to engage in polysubstance use, especially with alcohol and tobacco. CONCLUSIONS These findings suggest that diminished midlife structural brain integrity in long-term cannabis users reflects a broader pattern of polysubstance use, underlining the importance of understanding comorbid substance use in efforts to curb the negative effects of cannabis on brain and behavior as well as establish more effective policy and health practices.
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Affiliation(s)
- Annchen R Knodt
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina
| | - Madeline H Meier
- Department of Psychology, Arizona State University, Tempe, Arizona
| | - Antony Ambler
- Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom; Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Maria Z Gehred
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina
| | - HonaLee Harrington
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina; Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina; Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom
| | - Ahmad R Hariri
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina.
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Chen H, Zhou Y, Huang L, Xu X, Yuan C. Multimorbidity burden and developmental trajectory in relation to later‐life dementia: A prospective study. Alzheimers Dement 2022; 19:2024-2033. [PMID: 36427050 DOI: 10.1002/alz.12840] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 09/09/2022] [Accepted: 09/28/2022] [Indexed: 11/27/2022]
Abstract
INTRODUCTION This study assessed the associations of multimorbidity burden and its developmental trajectory with later-life dementia. METHODS Among 5923 Health and Retirement Study participants, major chronic conditions including hypertension, diabetes mellitus, cancer, lung diseases, heart disease, stroke, psychological disorders, and arthritis were self- or proxy-reported in 1994-2008. Dementia diagnosis was self- or proxy-reported in 2008-2018. We used Cox regression to assess the associations of multimorbidity with incident dementia. RESULTS During follow-up (median = 8 years), 701 participants developed dementia. Each additional chronic condition in 2008 was related to 15% (confidence interval: 9% to 22%) higher hazard of dementia. Multimorbidity trajectories in 1994-2008 were classified as "rapid growth", "steady growth", "slow growth", and "no new condition" by the group-based trajectory modelling methods. Compared to "no new condition", the "rapid growth" trajectory was related to 32% (3% to 69%) higher dementia risk. CONCLUSIONS Both multimorbidity burden and its developmental trajectory were prospectively associated with risk of dementia.
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Affiliation(s)
- Hui Chen
- School of Public Health and the Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou Zhejiang China
| | - Yaguan Zhou
- School of Public Health and the Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou Zhejiang China
| | - Liyan Huang
- School of Public Health and the Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou Zhejiang China
| | - Xiaolin Xu
- School of Public Health and the Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou Zhejiang China
- School of Public Health Faculty of Medicine The University of Queensland Brisbane Australia
| | - Changzheng Yuan
- School of Public Health and the Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou Zhejiang China
- Department of Nutrition Harvard T.H. Chan School of Public Health Boston Massachusetts USA
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11
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Zhou L, Yang H, Zhang Y, Li H, Zhang S, Li D, Ma Y, Hou Y, Lu W, Wang Y. Association of impaired lung function with dementia, and brain magnetic resonance imaging indices: a large population-based longitudinal study. Age Ageing 2022; 51:6834143. [PMID: 36413587 DOI: 10.1093/ageing/afac269] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 09/04/2022] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVE to examine the association between different patterns of impaired lung function with the incident risk of dementia and magnetic resonance imaging (MRI)-based brain structural features. METHODS in UK Biobank, a total of 308,534 dementia-free participants with valid lung function measures (forced expiratory volume in 1 s [FEV1] and forced vital capacity [FVC]) were included. Association was assessed using Cox proportional hazards regression model. Furthermore, the association between impaired lung function and brain MRI biomarkers related to cognitive function was analysed among 30,159 participants. RESULTS during a median follow-up of 12.6 years, 3,607 incident all-cause dementia cases were recorded. Restrictive impairment (hazard ratio [HR], 1.42; 95% confidence interval [CI], 1.27-1.60) and obstructive impairment (HR, 1.28; 95% CI, 1.15-1.42) were associated with higher risk of all-cause dementia. The restricted cubic splines indicated FEV1% predicted and FVC % predicted had reversed J-shaped associations with dementia. Participants with impaired lung function have higher risks of all-cause dementia across all apolipoprotein E (APOE) risk categories, whereas associations were stronger among those of low APOE risk (P for interaction = 0.034). In addition, restrictive and obstructive impairment were linked to lower total (β: -0.075, SE: 0.021, Pfdr = 0.002; β: -0.033, SE: 0.017, Pfdr = 0.069) and frontoparietal grey matter volumes, higher white matter hyperintensity, poorer white matter integrity, lower hippocampus (β: -0.066, SE: 0.024, Pfdr = 0.017; β: -0.051, SE: 0.019, Pfdr = 0.019) and other subcortical volumes. CONCLUSIONS participants with restrictive and obstructive impairments had a higher risk of dementia. Brain MRI indices further supported adverse effects and provided insight into potential pathophysiology biomarkers.
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Affiliation(s)
- Lihui Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Yuan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Huiping Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.,Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Shunming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.,Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Dun Li
- Department of Basic Integrated Medicine, School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yue Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yabing Hou
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Wenli Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yaogang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.,Department of Basic Integrated Medicine, School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
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12
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Frank D, Garo-Pascual M, Velasquez PAR, Frades B, Peled N, Zhang L, Strange BA. Brain structure and episodic learning rate in cognitively healthy ageing. Neuroimage 2022; 263:119630. [PMID: 36113738 DOI: 10.1016/j.neuroimage.2022.119630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 09/08/2022] [Accepted: 09/12/2022] [Indexed: 10/31/2022] Open
Abstract
Memory normally declines with ageing and these age-related cognitive changes are associated with changes in brain structure. Episodic memory retrieval has been widely studied during ageing, whereas learning has received less attention. Here we examined the neural correlates of episodic learning rate in ageing. Our study sample consisted of 982 cognitively healthy female and male older participants from the Vallecas Project cohort, without a clinical diagnosis of mild cognitive impairment or dementia. The learning rate across the three consecutive recall trials of the verbal memory task (Free and Cued Selective Reminding Test) recall trials was used as a predictor of grey matter (GM) using voxel-based morphometry, and WM microstructure using tract-based spatial statistics on fractional anisotropy (FA) and mean diffusivity (MD) measures. Immediate Recall improved by 1.4 items per trial on average, and this episodic learning rate was faster in women and negatively associated with age. Structurally, hippocampal and anterior thalamic GM volume correlated positively with learning rate. Learning also correlated with the integrity of WM microstructure (high FA and low MD) in an extensive network of tracts including bilateral anterior thalamic radiation, fornix, and long-range tracts. These results suggest that episodic learning rate is associated with key anatomical structures for memory functioning, motivating further exploration of the differential diagnostic properties between episodic learning rate and retrieval in ageing.
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Affiliation(s)
- Darya Frank
- Laboratory for Clinical Neuroscience, Centro de Tecnología Biomédica, CTB, Universidad Politécnica de Madrid, Madrid 28223, Spain.
| | - Marta Garo-Pascual
- Laboratory for Clinical Neuroscience, Centro de Tecnología Biomédica, CTB, Universidad Politécnica de Madrid, Madrid 28223, Spain; Alzheimer's Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid 28031, Spain; PhD Program in Neuroscience, Autonoma de Madrid University, Madrid 28049, Spain.
| | - Pablo Alejandro Reyes Velasquez
- Laboratory for Clinical Neuroscience, Centro de Tecnología Biomédica, CTB, Universidad Politécnica de Madrid, Madrid 28223, Spain
| | - Belén Frades
- Alzheimer's Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid 28031, Spain
| | - Noam Peled
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Linda Zhang
- Alzheimer's Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid 28031, Spain
| | - Bryan A Strange
- Laboratory for Clinical Neuroscience, Centro de Tecnología Biomédica, CTB, Universidad Politécnica de Madrid, Madrid 28223, Spain; Alzheimer's Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid 28031, Spain.
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13
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Adkins-Jackson PB, Belsky DW. Alzheimer's disease risk biomarkers: progress and challenges. THE LANCET. HEALTHY LONGEVITY 2022; 3:e575-e576. [PMID: 36102768 DOI: 10.1016/s2666-7568(22)00191-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 08/12/2022] [Indexed: 01/15/2023] Open
Affiliation(s)
- Paris B Adkins-Jackson
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Daniel W Belsky
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY 10032, USA; Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY 10032, USA.
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14
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Jiang R, Scheinost D, Zuo N, Wu J, Qi S, Liang Q, Zhi D, Luo N, Chung Y, Liu S, Xu Y, Sui J, Calhoun V. A Neuroimaging Signature of Cognitive Aging from Whole-Brain Functional Connectivity. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2201621. [PMID: 35811304 PMCID: PMC9403648 DOI: 10.1002/advs.202201621] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 06/02/2022] [Indexed: 05/14/2023]
Abstract
Cognitive decline is amongst one of the most commonly reported complaints during normal aging. Despite evidence that age and cognition are linked with similar neural correlates, no previous studies have directly ascertained how these two constructs overlap in the brain in terms of neuroimaging-based prediction. Based on a long lifespan healthy cohort (CamCAN, aged 19-89 years, n = 567), it is shown that both cognitive function (domains spanning executive function, emotion processing, motor function, and memory) and human age can be reliably predicted from unique patterns of functional connectivity, with models generalizable in two external datasets (n = 533 and n = 453). Results show that cognitive decline and normal aging both manifest decrease within-network connections (especially default mode and ventral attention networks) and increase between-network connections (somatomotor network). Whereas dorsal attention network is an exception, which is highly predictive on cognitive ability but is weakly correlated with aging. Further, the positively weighted connections in predicting fluid intelligence significantly mediate its association with age. Together, these findings offer insights into why normal aging is often associated with cognitive decline in terms of brain network organization, indicating a process of neural dedifferentiation and compensational theory.
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Affiliation(s)
- Rongtao Jiang
- Department of Radiology and Biomedical ImagingYale School of MedicineNew HavenCT06520USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical ImagingYale School of MedicineNew HavenCT06520USA
- Interdepartmental Neuroscience ProgramYale UniversityNew HavenCT06520USA
- Department of Statistics and Data ScienceYale UniversityNew HavenCT06520USA
- Child Study CenterYale School of MedicineNew HavenCT06510USA
| | - Nianming Zuo
- Brainnetome Center and National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing100190P. R. China
- School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijing100049P. R. China
| | - Jing Wu
- Department of Medical OncologyBeijing You‐An HospitalCapital Medical UniversityBeijing100069P. R. China
| | - Shile Qi
- College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing211106P. R. China
| | - Qinghao Liang
- Department of Biomedical EngineeringYale UniversityNew HavenCT06520USA
| | - Dongmei Zhi
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijing100088P. R. China
| | - Na Luo
- Brainnetome Center and National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing100190P. R. China
- School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijing100049P. R. China
| | - Young‐Chul Chung
- Department of PsychiatryJeonbuk National University Medical SchoolJeonju54907Republic of Korea
- Department of PsychiatryChonbuk National University HospitalJeonju54907Republic of Korea
| | - Sha Liu
- Department of Psychiatry and MDT Center for Cognitive Impairment and Sleep DisordersFirst HospitalFirst Clinical Medical College of Shanxi Medical UniversityTaiyuan030001P. R. China
| | - Yong Xu
- Department of Psychiatry and MDT Center for Cognitive Impairment and Sleep DisordersFirst HospitalFirst Clinical Medical College of Shanxi Medical UniversityTaiyuan030001P. R. China
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijing100088P. R. China
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia Institute of TechnologyEmory University and Georgia State UniversityAtlantaGA30303USA
| | - Vince Calhoun
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia Institute of TechnologyEmory University and Georgia State UniversityAtlantaGA30303USA
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15
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Frizzell TO, Glashutter M, Liu CC, Zeng A, Pan D, Hajra SG, D’Arcy RC, Song X. Artificial intelligence in brain MRI analysis of Alzheimer's disease over the past 12 years: A systematic review. Ageing Res Rev 2022; 77:101614. [PMID: 35358720 DOI: 10.1016/j.arr.2022.101614] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 03/02/2022] [Accepted: 03/24/2022] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Multiple structural brain changes in Alzheimer's disease (AD) and mild cognitive impairment (MCI) have been revealed on magnetic resonance imaging (MRI). There is a fast-growing effort in applying artificial intelligence (AI) to analyze these data. Here, we review and evaluate the AI studies in brain MRI analysis with synthesis. METHODS A systematic review of the literature, spanning the years from 2009 to 2020, was completed using the PubMed database. AI studies using MRI imaging to investigate normal aging, mild cognitive impairment, and AD-dementia were retrieved for review. Bias assessment was completed using the PROBAST criteria. RESULTS 97 relevant studies were included in the review. The studies were typically focused on the classification of AD, MCI, and normal aging (71% of the reported studies) and the prediction of MCI conversion to AD (25%). The best performance was achieved by using the deep learning-based convolution neural network algorithms (weighted average accuracy 89%), in contrast to 76-86% using Logistic Regression, Support Vector Machines, and other AI methods. DISCUSSION The synthesized evidence is paramount to developing sophisticated AI approaches to reliably capture and quantify multiple subtle MRI changes in the whole brain that exemplify the complexity and heterogeneity of AD and brain aging.
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16
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Association between gratitude, the brain and cognitive function in older adults: results from the NEIGE study. Arch Gerontol Geriatr 2022; 100:104645. [DOI: 10.1016/j.archger.2022.104645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/19/2022] [Accepted: 01/28/2022] [Indexed: 11/18/2022]
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17
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Xing XX. Globally Aging Cortical Spontaneous Activity Revealed by Multiple Metrics and Frequency Bands Using Resting-State Functional MRI. Front Aging Neurosci 2021; 13:803436. [PMID: 35027890 PMCID: PMC8748263 DOI: 10.3389/fnagi.2021.803436] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/09/2021] [Indexed: 11/24/2022] Open
Abstract
Most existing aging studies using functional MRI (fMRI) are based on cross-sectional data but misinterpreted their findings (i.e., age-related differences) as longitudinal outcomes (i.e., aging-related changes). To delineate aging-related changes the of human cerebral cortex, we employed the resting-state fMRI (rsfMRI) data from 24 healthy elders in the PREVENT-AD cohort, obtaining five longitudinal scans per subject. Cortical spontaneous activity is measured globally with three rsfMRI metrics including its amplitude, homogeneity, and homotopy at three different frequency bands (slow-5: 0.02-0.03 Hz, slow-4: 0.03-0.08 Hz, and slow-3 band: 0.08-0.22 Hz). General additive mixed models revealed a universal pattern of the aging-related changes for the global cortical spontaneous activity, indicating increases of these rsfMRI metrics during aging. This aging pattern follows specific frequency and spatial profiles where higher slow bands show more non-linear curves and the amplitude exhibits more extensive and significant aging-related changes than the connectivity. These findings provide strong evidence that cortical spontaneous activity is aging globally, inspiring its clinical utility as neuroimaging markers for neruodegeneration disorders.
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Affiliation(s)
- Xiu-Xia Xing
- Department of Applied Mathematics, College of Mathematics, Faculty of Science, Beijing University of Technology, Beijing, China
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18
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Yang Y, Zhang Q, Ren J, Zhu Q, Wang L, Zhang Y, Geng Z. Evolution of Brain Morphology in Spontaneously Hypertensive and Wistar-Kyoto Rats From Early Adulthood to Aging: A Longitudinal Magnetic Resonance Imaging Study. Front Aging Neurosci 2021; 13:757808. [PMID: 34916922 PMCID: PMC8670306 DOI: 10.3389/fnagi.2021.757808] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 11/08/2021] [Indexed: 11/21/2022] Open
Abstract
The influence of hypertension and aging alone on brain structure has been described extensively. Our understanding of the interaction of hypertension with aging to brain morphology is still limited. We aimed to detect the synergistic effects of hypertension and aging on brain morphology and to describe the evolution patterns of cerebral atrophy from spatial and temporal perspectives. In 8 spontaneously hypertensive rats (SHRs) and 5 Wistar-Kyoto rats, high-resolution magnetic resonance imaging scans were longitudinally acquired at 10, 24, 52, and 80 weeks. We analyzed the tissue volumes of gray matter, white matter, cerebral spinal fluid, and total intracranial volume (TIV), and then evaluated gray matter volume in detail using voxel-based morphometry (VBM) and region of interest-based methods. There were interactive effects on hypertension and aging in tissue volumes of gray matter, white matter, and TIV, of which gray matter atrophy was most pronounced, especially in elderly SHRs. We identified the vulnerable gray matter volume with combined effects of hypertension and aging in the septal region, bilateral caudate putamen, hippocampus, primary somatosensory cortex, cerebellum, periaqueductal gray, right accumbens nucleus, and thalamus. We automatically extracted the septal region, anterior cingulate cortex, primary somatosensory cortex, caudate putamen, hippocampus, and accumbens nucleus and revealed an inverted-U trajectory of volume change in SHRs, with volume increase at the early phase and decline at the late phase. Hypertension interacts with aging to affect brain volume changes such as severe atrophy in elderly SHRs.
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Affiliation(s)
- Yingying Yang
- Graduate School, Hebei Medical University, Shijiazhuang, China.,Department of Imaging, The First Hospital of Qinhuangdao, Qinhuangdao, China
| | - Quan Zhang
- Tianjin Key Laboratory of Functional Imaging, Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | | | - Qingfeng Zhu
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Lixin Wang
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yongzhi Zhang
- Graduate School, Hebei Medical University, Shijiazhuang, China
| | - Zuojun Geng
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, China
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19
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Eickhoff CR, Hoffstaedter F, Caspers J, Reetz K, Mathys C, Dogan I, Amunts K, Schnitzler A, Eickhoff SB. Advanced brain ageing in Parkinson's disease is related to disease duration and individual impairment. Brain Commun 2021; 3:fcab191. [PMID: 34541531 PMCID: PMC8445399 DOI: 10.1093/braincomms/fcab191] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 06/22/2021] [Accepted: 06/30/2021] [Indexed: 11/13/2022] Open
Abstract
Machine learning can reliably predict individual age from MRI data, revealing that patients with neurodegenerative disorders show an elevated biological age. A surprising gap in the literature, however, pertains to Parkinson's disease. Here, we evaluate brain age in two cohorts of Parkinson's patients and investigated the relationship between individual brain age and clinical characteristics. We assessed 372 patients with idiopathic Parkinson's disease, newly diagnosed cases from the Parkinson's Progression Marker Initiative database and a more chronic local sample, as well as age- and sex-matched healthy controls. Following morphometric preprocessing and atlas-based compression, individual brain age was predicted using a multivariate machine learning model trained on an independent, multi-site reference sample. Across cohorts, healthy controls were well predicted with a mean error of 4.4 years. In turn, Parkinson's patients showed a significant (controlling for age, gender and site) increase in brain age of ∼3 years. While this effect was already present in the newly diagnosed sample, advanced biological age was significantly related to disease duration as well as worse cognitive and motor impairment. While biological age is increased in patients with Parkinson's disease, the effect is at the lower end of what is found for other neurological and psychiatric disorders. We argue that this may reflect a heterochronicity between forebrain atrophy and small but behaviourally salient midbrain pathology. Finally, we point to the need to disentangle physiological ageing trajectories, lifestyle effects and core pathological changes.
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Affiliation(s)
- Claudia R Eickhoff
- Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Julian Caspers
- Institute of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Kathrin Reetz
- Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,Department of Neurology, University Hospital RWTH Aachen, Aachen, Germany
| | | | - Imis Dogan
- Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,Department of Neurology, University Hospital RWTH Aachen, Aachen, Germany
| | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
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20
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Xia X, Wang Y, Yu Z, Chen J, Han JDJ. Assessing the rate of aging to monitor aging itself. Ageing Res Rev 2021; 69:101350. [PMID: 33940202 DOI: 10.1016/j.arr.2021.101350] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 04/05/2021] [Accepted: 04/26/2021] [Indexed: 12/22/2022]
Abstract
Healthy aging is the prime goal of aging research and interventions. Healthy aging or not can be quantified by biological aging rates estimated by aging clocks. Generation and accumulation of large scale high-dimensional biological data together with maturation of artificial intelligence among other machine learning techniques, have enabled and spurred the rapid development of various aging rate estimators (aging clocks). Here we review the data sources and compare the algorithms of recent human aging clocks, and the applications of these clocks in both researches and daily life. We envision that not only more and multiscale data on cross-sectional data will add momentum to the aging clock development, new longitudinal and interventional data will further raise the aging clock development to the next level to be trained by true biological age such as morbidity and mortality age.
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21
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d'Arbeloff T, Elliott ML, Knodt AR, Sison M, Melzer TR, Ireland D, Ramrakha S, Poulton R, Caspi A, Moffitt TE, Hariri AR. Midlife Cardiovascular Fitness Is Reflected in the Brain's White Matter. Front Aging Neurosci 2021; 13:652575. [PMID: 33889085 PMCID: PMC8055854 DOI: 10.3389/fnagi.2021.652575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 03/05/2021] [Indexed: 12/18/2022] Open
Abstract
Disappointing results from clinical trials designed to delay structural brain decline and the accompanying increase in risk for dementia in older adults have precipitated a shift in testing promising interventions from late in life toward midlife before irreversible damage has accumulated. This shift, however, requires targeting midlife biomarkers that are associated with clinical changes manifesting only in late life. Here we explored possible links between one putative biomarker, distributed integrity of brain white matter, and two intervention targets, cardiovascular fitness and healthy lifestyle behaviors, in midlife. At age 45, fractional anisotropy (FA) derived from diffusion weighted MRI was used to estimate the microstructural integrity of distributed white matter tracts in a population-representative birth cohort. Age-45 cardiovascular fitness (VO2Max; N = 801) was estimated from heart rates obtained during submaximal exercise tests; age-45 healthy lifestyle behaviors were estimated using the Nyberg Health Index (N = 854). Ten-fold cross-validated elastic net predictive modeling revealed that estimated VO2Max was modestly associated with distributed FA. In contrast, there was no significant association between Nyberg Health Index scores and FA. Our findings suggest that cardiovascular fitness levels, but not healthy lifestyle behaviors, are associated with the distributed integrity of white matter in the brain in midlife. These patterns could help inform future clinical intervention research targeting ADRDs.
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Affiliation(s)
- Tracy d'Arbeloff
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
| | - Maxwell L Elliott
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
| | - Annchen R Knodt
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
| | - Maria Sison
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
| | - Tracy R Melzer
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Avshalom Caspi
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States.,Social, Genetic, & Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom.,Department of Psychiatry & Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States.,Center for Genomic and Computational Biology, Duke University, Durham, NC, United States
| | - Terrie E Moffitt
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States.,Social, Genetic, & Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom.,Department of Psychiatry & Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States.,Center for Genomic and Computational Biology, Duke University, Durham, NC, United States
| | - Ahmad R Hariri
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
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22
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Hedderich DM, Menegaux A, Schmitz-Koep B, Nuttall R, Zimmermann J, Schneider SC, Bäuml JG, Daamen M, Boecker H, Wilke M, Zimmer C, Wolke D, Bartmann P, Sorg C, Gaser C. Increased Brain Age Gap Estimate (BrainAGE) in Young Adults After Premature Birth. Front Aging Neurosci 2021; 13:653365. [PMID: 33867970 PMCID: PMC8047054 DOI: 10.3389/fnagi.2021.653365] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 03/12/2021] [Indexed: 11/17/2022] Open
Abstract
Recent evidence suggests increased metabolic and physiologic aging rates in premature-born adults. While the lasting consequences of premature birth on human brain development are known, its impact on brain aging remains unclear. We addressed the question of whether premature birth impacts brain age gap estimates (BrainAGE) using an accurate and robust machine-learning framework based on structural MRI in a large cohort of young premature-born adults (n = 101) and full-term (FT) controls (n = 111). Study participants are part of a geographically defined population study of premature-born individuals, which have been followed longitudinally from birth until young adulthood. We investigated the association between BrainAGE scores and perinatal variables as well as with outcomes of physical (total intracranial volume, TIV) and cognitive development (full-scale IQ, FS-IQ). We found increased BrainAGE in premature-born adults [median (interquartile range) = 1.4 (-1.3-4.7 years)] compared to full-term controls (p = 0.002, Cohen's d = 0.443), which was associated with low Gestational age (GA), low birth weight (BW), and increased neonatal treatment intensity but not with TIV or FS-IQ. In conclusion, results demonstrate elevated BrainAGE in premature-born adults, suggesting an increased risk for accelerated brain aging in human prematurity.
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Affiliation(s)
- Dennis M. Hedderich
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Aurore Menegaux
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Benita Schmitz-Koep
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Rachel Nuttall
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Anesthesiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Juliana Zimmermann
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sebastian C. Schneider
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Josef G. Bäuml
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marcel Daamen
- Functional Neuroimaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
- Department of Neonatology, University Hospital Bonn, Venusberg-Campus, Bonn, Germany
| | - Henning Boecker
- Functional Neuroimaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Marko Wilke
- Department of Pediatric Neurology and Developmental Medicine and Experimental Pediatric Neuroimaging group, University of Tübingen, Tübingen, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dieter Wolke
- Department of Psychology, University of Warwick, Coventry, United Kingdom
- Warwick Medical School, University of Warwick, Coventry, United Kingdom
| | - Peter Bartmann
- Department of Neonatology, University Hospital Bonn, Venusberg-Campus, Bonn, Germany
| | - Christian Sorg
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Psychiatry, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Gaser
- Department of Psychiatry, University Hospital Jena, Jena, Germany
- Department of Neurology, University Hospital Jena, Jena, Germany
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23
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Elliott ML, Caspi A, Houts RM, Ambler A, Broadbent JM, Hancox RJ, Harrington H, Hogan S, Keenan R, Knodt A, Leung JH, Melzer TR, Purdy SC, Ramrakha S, Richmond-Rakerd LS, Righarts A, Sugden K, Thomson WM, Thorne PR, Williams BS, Wilson G, Hariri AR, Poulton R, Moffitt TE. Disparities in the pace of biological aging among midlife adults of the same chronological age have implications for future frailty risk and policy. NATURE AGING 2021; 1:295-308. [PMID: 33796868 PMCID: PMC8009092 DOI: 10.1038/s43587-021-00044-4] [Citation(s) in RCA: 107] [Impact Index Per Article: 35.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 02/10/2021] [Indexed: 02/07/2023]
Abstract
Some humans age faster than others. Variation in biological aging can be measured in midlife, but the implications of this variation are poorly understood. We tested associations between midlife biological aging and indicators of future frailty-risk in the Dunedin cohort of 1037 infants born the same year and followed to age 45. Participants' Pace of Aging was quantified by tracking declining function in 19 biomarkers indexing the cardiovascular, metabolic, renal, immune, dental, and pulmonary systems across ages 26, 32, 38, and 45 years. At age 45 in 2019, participants with faster Pace of Aging had more cognitive difficulties, signs of advanced brain aging, diminished sensory-motor functions, older appearance, and more pessimistic perceptions of aging. People who are aging more rapidly than same-age peers in midlife may prematurely need supports to sustain independence that are usually reserved for older adults. Chronological age does not adequately identify need for such supports.
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Affiliation(s)
- Maxwell L. Elliott
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Renate M. Houts
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Antony Ambler
- King’s College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, London, UK
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | | | - Robert J. Hancox
- Department of Preventive and Social Medicine, Otago Medical School, University of Otago, New Zealand
| | - HonaLee Harrington
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Sean Hogan
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Ross Keenan
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand
- Christchurch Radiology group, Christchurch, New Zealand
| | - Annchen Knodt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Joan H. Leung
- School of Psychology, University of Auckland, New Zealand
- Eisdell Moore Centre, University of Auckland, New Zealand
| | - Tracy R. Melzer
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Suzanne C. Purdy
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand
- School of Psychology, University of Auckland, New Zealand
- Eisdell Moore Centre, University of Auckland, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | | | - Antoinette Righarts
- Department of Preventive and Social Medicine, Otago Medical School, University of Otago, New Zealand
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | | | - Peter R. Thorne
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand
- Eisdell Moore Centre, University of Auckland, New Zealand
- School of Population Health, University of Auckland, New Zealand
| | | | - Graham Wilson
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Ahmad R. Hariri
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Terrie E. Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
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