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Scheffler F, Ipser J, Pancholi D, Murphy A, Cao Z, Ottino-González J, Thompson PM, Shoptaw S, Conrod P, Mackey S, Garavan H, Stein DJ. Mega-analysis of the brain-age gap in substance use disorder: An ENIGMA Addiction working group study. Addiction 2024; 119:1937-1946. [PMID: 39165145 DOI: 10.1111/add.16621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 06/19/2024] [Indexed: 08/22/2024]
Abstract
BACKGROUND AND AIMS The brain age gap (BAG), calculated as the difference between a machine learning model-based predicted brain age and chronological age, has been increasingly investigated in psychiatric disorders. Tobacco and alcohol use are associated with increased BAG; however, no studies have compared global and regional BAG across substances other than alcohol and tobacco. This study aimed to compare global and regional estimates of brain age in individuals with substance use disorders and healthy controls. DESIGN This was a cross-sectional study. SETTING This is an Enhancing Neuro Imaging through Meta-Analysis Consortium (ENIGMA) Addiction Working Group study including data from 38 global sites. PARTICIPANTS This study included 2606 participants, of whom 1725 were cases with a substance use disorder and 881 healthy controls. MEASUREMENTS This study used the Kaufmann brain age prediction algorithms to generate global and regional brain age estimates using T1 weighted magnetic resonance imaging (MRI) scans. We used linear mixed effects models to compare global and regional (FreeSurfer lobestrict output) BAG (i.e. predicted minus chronological age) between individuals with one of five primary substance use disorders as well as healthy controls. FINDINGS Alcohol use disorder (β = -5.49, t = -5.51, p < 0.001) was associated with higher global BAG, whereas amphetamine-type stimulant use disorder (β = 3.44, t = 2.42, p = 0.02) was associated with lower global BAG in the separate substance-specific models. CONCLUSIONS People with alcohol use disorder appear to have a higher brain-age gap than people without alcohol use disorder, which is consistent with other evidence of the negative impact of alcohol on the brain.
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Affiliation(s)
- Freda Scheffler
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Jonathan Ipser
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Devarshi Pancholi
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, USA
| | - Alistair Murphy
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, USA
| | - Zhipeng Cao
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, USA
| | - Jonatan Ottino-González
- Department of Pediatrics, Division of Endocrinology, Diabetes, and Metabolism, Children's Hospital Los Angeles, Los Angeles, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Steve Shoptaw
- Department of Family Medicine, UCLA, Los Angeles, CA, USA
- University of Cape Town, Cape Town, South Africa
| | - Patricia Conrod
- Department of Psychiatry, Université de Montreal, CHU Ste Justine Hospital, Montreal, Canada
| | - Scott Mackey
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, USA
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, USA
| | - Dan J Stein
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
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Li T, Chen J, Zhao B, Garden GA, Giovanello KS, Wu G, Zhu H. The Interaction Effects of Sex, Age, APOE and Common Health Risk Factors on Human Brain Functions. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.05.24311482. [PMID: 39148839 PMCID: PMC11326347 DOI: 10.1101/2024.08.05.24311482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Importance Nonlinear changes in brain function during aging are shaped by a complex interplay of factors, including sex, age, genetics, and modifiable health risk factors. However, the combined effects and underlying mechanisms of these factors on brain functional connectivity remain poorly understood. Objective To comprehensively investigate the combined associations of sex, age, APOE genotypes, and ten common modifiable health risk factors with brain functional connectivities during aging. Design Setting and Participants This analysis used data from 36,630 UK Biobank participants, aged 44-81, who were assessed for sex, age, APOE genotypes, 10 health risk factors, and brain functional connectivities through resting-state functional magnetic resonance imaging. Main Outcomes and Measures Brain functional connectivities were evaluated through within- and between-network functional connectivities and connectivity strength. Associations between risk factors and brain functional connectivities, including their interaction effects, were analyzed. Results Hypertension, BMI, and education were the top three influential factors. Sex-specific effects were also observed in interactions involving APOE4 gene, smoking, alcohol consumption, diabetes, BMI, and education. Notably, a negative sex-excessive alcohol interaction showed a stronger negative effect on functional connectivities in males, particularly between the dorsal attention network and the language network, while moderate alcohol consumption appeared to have protective effects. A significant negative interaction between sex and APOE4 revealed a greater reduction in functional connectivity between the cingulo-opercular network and the posterior multimodal network in male APOE4 carriers. Additional findings included a negative age-BMI interaction between the visual and dorsal attention networks, and a positive age-hypertension interaction between the frontoparietal and default mode networks. Conclusions and Relevance The findings highlight significant sex disparities in the associations between age, the APOE-ε4 gene, modifiable health risk factors, and brain functional connectivity, emphasizing the necessity of jointly considering these factors to gain a deeper understanding of the complex processes underlying brain aging.
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Affiliation(s)
- Tengfei Li
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jie Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bingxin Zhao
- Department of Statistics and Data Science, the Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Gwenn A. Garden
- Department of Neurology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kelly S. Giovanello
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Guorong Wu
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Statistics and Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Insititute for Developmental Disabilities, Chapel Hill, NC, USA
| | - Hongtu Zhu
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Statistics and Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Departments of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Christidi F, Drouka A, Brikou D, Mamalaki E, Ntanasi E, Karavasilis E, Velonakis G, Angelopoulou G, Tsapanou A, Gu Y, Yannakoulia M, Scarmeas N. The Association between Individual Food Groups, Limbic System White Matter Tracts, and Episodic Memory: Initial Data from the Aiginition Longitudinal Biomarker Investigation of Neurodegeneration (ALBION) Study. Nutrients 2024; 16:2766. [PMID: 39203902 PMCID: PMC11357525 DOI: 10.3390/nu16162766] [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: 07/22/2024] [Revised: 08/14/2024] [Accepted: 08/17/2024] [Indexed: 09/03/2024] Open
Abstract
(1) Background: Many studies link food intake with clinical cognitive outcomes, but evidence for brain biomarkers, such as memory-related limbic white matter (WM) tracts, is limited. We examined the association between food groups, limbic WM tracts integrity, and memory performance in community-dwelling individuals. (2) Methods: We included 117 non-demented individuals (ALBION study). Verbal and visual episodic memory tests were administered, and a composite z-score was calculated. Diffusion tensor imaging tractography was applied for limbic WM tracts (fornix-FX, cingulum bundle-CB, uncinate fasciculus-UF, hippocampal perforant pathway zone-hPPZ). Food intake was evaluated through four 24-h recalls. We applied linear regression models adjusted for demographics and energy intake. (3) Results: We found significant associations between (a) higher low-to-moderate alcohol intake and higher FX fractional anisotropy (FA), (b) higher full-fat dairy intake and lower hPPZ FA, and (c) higher red meat and cold cuts intake and lower hPPZ FA. None of the food groups was associated with memory performance. (4) Conclusions: Despite non-significant associations between food groups and memory, possibly due to participants' cognitive profile and/or compensatory mechanisms, the study documented a possible beneficial role of low-to-moderate alcohol and a harmful role of full-fat dairy and red meat and cold cuts on limbic WM tracts.
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Affiliation(s)
- Foteini Christidi
- First Department of Neurology, Aiginition Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece (G.A.)
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 NHY1 Dublin, Ireland
| | - Archontoula Drouka
- Department of Nutrition and Dietetics, Harokopio University, 17671 Athens, Greece
| | - Dora Brikou
- Department of Nutrition and Dietetics, Harokopio University, 17671 Athens, Greece
| | - Eirini Mamalaki
- Department of Nutrition and Dietetics, Harokopio University, 17671 Athens, Greece
| | - Eva Ntanasi
- First Department of Neurology, Aiginition Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece (G.A.)
| | - Efstratios Karavasilis
- Research Unit of Radiology and Medical Imaging, 2nd Department of Radiology, Attikon General University Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece
- School of Medicine, Democritus University of Alexandroupolis, 68100 Alexandroupolis, Greece
| | - Georgios Velonakis
- Research Unit of Radiology and Medical Imaging, 2nd Department of Radiology, Attikon General University Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece
| | - Georgia Angelopoulou
- First Department of Neurology, Aiginition Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece (G.A.)
| | - Angeliki Tsapanou
- First Department of Neurology, Aiginition Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece (G.A.)
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, The Gertrude H. Sergievsky Center, Columbia University, New York, NY 10032, USA;
| | - Yian Gu
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, The Gertrude H. Sergievsky Center, Columbia University, New York, NY 10032, USA;
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, Harokopio University, 17671 Athens, Greece
| | - Nikolaos Scarmeas
- First Department of Neurology, Aiginition Hospital, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece (G.A.)
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, The Gertrude H. Sergievsky Center, Columbia University, New York, NY 10032, USA;
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Liu Y, Huang C, Xiong Y, Wang X, Shen Z, Zhang M, Gao N, Wang N, Du G, Zhan H. The causal relationship between human brain morphometry and knee osteoarthritis: a two-sample Mendelian randomization study. Front Genet 2024; 15:1420134. [PMID: 39040992 PMCID: PMC11260717 DOI: 10.3389/fgene.2024.1420134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 06/20/2024] [Indexed: 07/24/2024] Open
Abstract
Background Knee Osteoarthritis (KOA) is a prevalent and debilitating condition affecting millions worldwide, yet its underlying etiology remains poorly understood. Recent advances in neuroimaging and genetic methodologies offer new avenues to explore the potential neuropsychological contributions to KOA. This study aims to investigate the causal relationships between brain-wide morphometric variations and KOA using a genetic epidemiology approach. Method Leveraging data from 36,778 UK Biobank participants for human brain morphometry and 487,411 UK Biobank participants for KOA, this research employed a two-sample Mendelian Randomization (TSMR) approach to explore the causal effects of 83 brain-wide volumes on KOA. The primary method of analysis was the Inverse Variance Weighted (IVW) and Wald Ratio (WR) method, complemented by MR Egger and IVW methods for heterogeneity and pleiotropy assessments. A significance threshold of p < 0.05 was set to determine causality. The analysis results were assessed for heterogeneity using the MR Egger and IVW methods. Brain-wide volumes with Q_pval < 0.05 were considered indicative of heterogeneity. The MR Egger method was employed to evaluate the pleiotropy of the analysis results, with brain-wide volumes having a p-value < 0.05 considered suggestive of pleiotropy. Results Our findings revealed significant causal associations between KOA and eight brain-wide volumes: Left parahippocampal volume, Right posterior cingulate volume, Left transverse temporal volume, Left caudal anterior cingulate volume, Right paracentral volume, Left paracentral volume, Right lateral orbitofrontal volume, and Left superior temporal volume. These associations remained robust after tests for heterogeneity and pleiotropy, underscoring their potential role in the pathogenesis of KOA. Conclusion This study provides novel evidence of the causal relationships between specific brain morphometries and KOA, suggesting that neuroanatomical variations might contribute to the risk and development of KOA. These findings pave the way for further research into the neurobiological mechanisms underlying KOA and may eventually lead to the development of new intervention strategies targeting these neuropsychological pathways.
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Affiliation(s)
- Yongming Liu
- Shi’s Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Traumatology and Orthopedics, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Chao Huang
- Yunyang County People’s Hospital Rehabilitation Medicine Department, Chongqing, China
| | - Yizhe Xiong
- Shi’s Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Traumatology and Orthopedics, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Xiang Wang
- Shi’s Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Traumatology and Orthopedics, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Zhibi Shen
- Shi’s Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Traumatology and Orthopedics, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Mingcai Zhang
- Shi’s Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Traumatology and Orthopedics, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Ningyang Gao
- Shi’s Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Traumatology and Orthopedics, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Nan Wang
- Department of Traditional Chinese Medicine, Shanghai Yangzhi Rehabilitation Hospital (Yangzhi Affiliated Rehabilitation Hospital), School of Medicine, Tongji University, Shanghai, China
| | - Guoqing Du
- Shi’s Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Traumatology and Orthopedics, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Hongsheng Zhan
- Shi’s Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Traumatology and Orthopedics, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
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Mudyanselage AW, Wijamunige BC, Kocoń A, Turner R, McLean D, Morentin B, Callado LF, Carter WG. Alcohol Triggers the Accumulation of Oxidatively Damaged Proteins in Neuronal Cells and Tissues. Antioxidants (Basel) 2024; 13:580. [PMID: 38790685 PMCID: PMC11117938 DOI: 10.3390/antiox13050580] [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: 04/09/2024] [Revised: 04/30/2024] [Accepted: 05/04/2024] [Indexed: 05/26/2024] Open
Abstract
Alcohol is toxic to neurons and can trigger alcohol-related brain damage, neuronal loss, and cognitive decline. Neuronal cells may be vulnerable to alcohol toxicity and damage from oxidative stress after differentiation. To consider this further, the toxicity of alcohol to undifferentiated SH-SY5Y cells was compared with that of cells that had been acutely differentiated. Cells were exposed to alcohol over a concentration range of 0-200 mM for up to 24 h and alcohol effects on cell viability were evaluated via MTT and LDH assays. Effects on mitochondrial morphology were examined via transmission electron microscopy, and mitochondrial functionality was examined using measurements of ATP and the production of reactive oxygen species (ROS). Alcohol reduced cell viability and depleted ATP levels in a concentration- and exposure duration-dependent manner, with undifferentiated cells more vulnerable to toxicity. Alcohol exposure resulted in neurite retraction, altered mitochondrial morphology, and increased the levels of ROS in proportion to alcohol concentration; these peaked after 3 and 6 h exposures and were significantly higher in differentiated cells. Protein carbonyl content (PCC) lagged behind ROS production and peaked after 12 and 24 h, increasing in proportion to alcohol concentration, with higher levels in differentiated cells. Carbonylated proteins were characterised by their denatured molecular weights and overlapped with those from adult post-mortem brain tissue, with levels of PCC higher in alcoholic subjects than matched controls. Hence, alcohol can potentially trigger cell and tissue damage from oxidative stress and the accumulation of oxidatively damaged proteins.
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Affiliation(s)
- Anusha W. Mudyanselage
- Clinical Toxicology Research Group, School of Medicine, University of Nottingham, Royal Derby Hospital Centre, Uttoxeter Road, Derby DE22 3DT, UK; (A.W.M.); (B.C.W.); (A.K.); (R.T.)
- Department of Export Agriculture, Faculty of Agricultural Sciences, Sabaragamuwa University of Sri Lanka, Belihuloya 70140, Sri Lanka
| | - Buddhika C. Wijamunige
- Clinical Toxicology Research Group, School of Medicine, University of Nottingham, Royal Derby Hospital Centre, Uttoxeter Road, Derby DE22 3DT, UK; (A.W.M.); (B.C.W.); (A.K.); (R.T.)
- Department of Export Agriculture, Faculty of Agricultural Sciences, Sabaragamuwa University of Sri Lanka, Belihuloya 70140, Sri Lanka
| | - Artur Kocoń
- Clinical Toxicology Research Group, School of Medicine, University of Nottingham, Royal Derby Hospital Centre, Uttoxeter Road, Derby DE22 3DT, UK; (A.W.M.); (B.C.W.); (A.K.); (R.T.)
| | - Ricky Turner
- Clinical Toxicology Research Group, School of Medicine, University of Nottingham, Royal Derby Hospital Centre, Uttoxeter Road, Derby DE22 3DT, UK; (A.W.M.); (B.C.W.); (A.K.); (R.T.)
| | - Denise McLean
- School of Life Sciences, University of Nottingham, Nottingham NG7 2UH, UK;
| | - Benito Morentin
- Section of Forensic Pathology, Basque Institute of Legal Medicine, E-48001 Bilbao, Spain;
| | - Luis F. Callado
- Department of Pharmacology, University of the Basque Country-UPV/EHU, E-48940 Leioa, Spain;
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain
| | - Wayne G. Carter
- Clinical Toxicology Research Group, School of Medicine, University of Nottingham, Royal Derby Hospital Centre, Uttoxeter Road, Derby DE22 3DT, UK; (A.W.M.); (B.C.W.); (A.K.); (R.T.)
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Kamarajan C, Ardekani BA, Pandey AK, Meyers JL, Chorlian DB, Kinreich S, Pandey G, Richard C, de Viteri SS, Kuang W, Porjesz B. Prediction of brain age in individuals with and at risk for alcohol use disorder using brain morphological features. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.01.582844. [PMID: 38496639 PMCID: PMC10942318 DOI: 10.1101/2024.03.01.582844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Brain age measures predicted from structural and functional brain features are increasingly being used to understand brain integrity, disorders, and health. While there is a vast literature showing aberrations in both structural and functional brain measures in individuals with and at risk for alcohol use disorder (AUD), few studies have investigated brain age in these groups. The current study examines brain age measures predicted using brain morphological features, such as cortical thickness and brain volume, in individuals with a lifetime diagnosis of AUD as well as in those at higher risk to develop AUD from families with multiple members affected with AUD (i.e., higher family history density (FHD) scores). The AUD dataset included a group of 30 adult males (mean age = 41.25 years) with a lifetime diagnosis of AUD and currently abstinent and a group of 30 male controls (mean age = 27.24 years) without any history of AUD. A second dataset of young adults who were categorized based on their FHD scores comprised a group of 40 individuals (20 males) with high FHD of AUD (mean age = 25.33 years) and a group of 31 individuals (18 males) with low FHD (mean age = 25.47 years). Brain age was predicted using 187 brain morphological features of cortical thickness and brain volume in an XGBoost regression model; a bias-correction procedure was applied to the predicted brain age. Results showed that both AUD and high FHD individuals showed an increase of 1.70 and 0.09 years (1.08 months), respectively, in their brain age relative to their chronological age, suggesting accelerated brain aging in AUD and risk for AUD. Increased brain age was associated with poor performance on neurocognitive tests of executive functioning in both AUD and high FHD individuals, indicating that brain age can also serve as a proxy for cognitive functioning and brain health. These findings on brain aging in these groups may have important implications for the prevention and treatment of AUD and ensuing cognitive decline.
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Affiliation(s)
- Chella Kamarajan
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Babak A. Ardekani
- Center for Advanced Brain Imaging, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
- Department of Psychiatry, Grossman School of Medicine, New York University, New York, NY 10016, USA
| | - Ashwini K. Pandey
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Jacquelyn L. Meyers
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - David B. Chorlian
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Sivan Kinreich
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Gayathri Pandey
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Christian Richard
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Stacey Saenz de Viteri
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Weipeng Kuang
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
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Funk-White M, Wing D, Eyler LT, Moore AA, Reas ET, McEvoy L. Neuroimaging-Derived Predicted Brain Age and Alcohol Use Among Community-Dwelling Older Adults. Am J Geriatr Psychiatry 2023; 31:669-678. [PMID: 36925380 PMCID: PMC11534213 DOI: 10.1016/j.jagp.2023.02.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/14/2023] [Accepted: 02/15/2023] [Indexed: 02/22/2023]
Abstract
OBJECTIVES Observational studies have suggested that moderate alcohol use is associated with reduced risk of dementia. However, the nature of this association is not understood. We investigated whether light to moderate alcohol use may be associated with slower brain aging, among a cohort of older community-dwelling adults using a biomarker of brain age based on structural neuroimaging measures. DESIGN Cross-sectional observational study. PARTICIPANTS Well-characterized members of a longitudinal cohort study who underwent neuroimaging. We categorized the 163 participants (mean age 76.7 ± 7.7, 60% women) into current nondrinkers, light drinkers (1-7 drinks/week) moderate drinkers (>7-14 drinks/week), or heavier drinkers (>14 drinks/week). MEASUREMENTS We calculated brain-predicted age using structural MRIs processed with the BrainAgeR program, and calculated the difference between brain-predicted age and chronological age (brain-predicted age difference, or brain-PAD). We used analysis of variance to determine if brain-PAD differed across alcohol groups, controlling for potential confounders. RESULTS Brain-PAD differed across alcohol groups (F[3, 150] = 4.02; p = 0.009) with heavier drinkers showing older brain-PAD than light drinkers (by about 6 years). Brain-PAD did not differ across light, moderate, and nondrinkers. Similar results were obtained after adjusting for potentially mediating health-related measures, and after excluding individuals with a history of heavier drinking. DISCUSSION Among this sample of healthy older adults, consumption of more than 14 drinks/week was associated with a biomarker of advanced brain aging. Light and moderate drinking was not associated with slower brain aging relative to non-drinking.
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Affiliation(s)
- Makaya Funk-White
- Interdisciplinary Research on Substance Use (MFW), University of California San Diego, La Jolla, CA
| | - David Wing
- Herbert Wertheim School of Public Health and Human Longevity Science (DW, LKM), University of California San Diego, La Jolla, CA
| | - Lisa T Eyler
- Department of Psychiatry (LTE), University of California San Diego, La Jolla, CA; Desert-Pacific Mental Illness Research (LTE), Education, and Clinical Center, VA San Diego Healthcare System, San Diego, CA
| | - Alison A Moore
- Division of Geriatrics, Gerontology, and Palliative Care, Department of Medicine (AAM), University of California San Diego, La Jolla, CA
| | - Emilie T Reas
- Department of Neurosciences (ETR), University of California San Diego, La Jolla, CA
| | - Linda McEvoy
- Herbert Wertheim School of Public Health and Human Longevity Science (DW, LKM), University of California San Diego, La Jolla, CA; Department of Radiology (LKM), University of California San Diego, La Jolla, CA
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8
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Pan Y, Shen J, Cai X, Chen H, Zong G, Zhu W, Jing J, Liu T, Jin A, Wang Y, Meng X, Yuan C, Wang Y. Adherence to a healthy lifestyle and brain structural imaging markers. Eur J Epidemiol 2023:10.1007/s10654-023-00992-8. [PMID: 37060500 DOI: 10.1007/s10654-023-00992-8] [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: 10/31/2022] [Accepted: 03/13/2023] [Indexed: 04/16/2023]
Abstract
Previous research has linked specific modifiable lifestyle factors to age-related cognitive decline in adults. Little is known about the potential role of an overall healthy lifestyle in brain structure. We examined the association of adherence to a healthy lifestyle with a panel of brain structural markers among 2,413 participants in PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study in China and 19,822 participants in UK Biobank (UKB). A healthy lifestyle score (0-5) was constructed based on five modifiable lifestyle factors: diet, physical activity, smoking, alcohol consumption, and body mass index. Validated multimodal neuroimaging markers were derived from brain magnetic resonance imaging. In the cross-sectional analysis of PRECISE, participants who adopted four or five low-risk lifestyle factors had larger total brain volume (TBV; β = 0.12, 95% CI: - 0.02, 0.26; p-trend = 0.05) and gray matter volume (GMV; β = 0.16, 95% CI: 0.01, 0.30; p-trend = 0.05), smaller white matter hyperintensity volume (WMHV; β = - 0.35, 95% CI: - 0.50, - 0.20; p-trend < 0.001) and lower odds of lacune (Odds Ratio [OR] = 0.48, 95% CI: 0.22, 1.08; p-trend = 0.03), compared to those with zero or one low-risk factors. Meanwhile, in the prospective analysis in UKB (with a median of 7.7 years' follow-up), similar associations were observed between the number of low-risk lifestyle factors (4-5 vs. 0-1) and TBV (β = 0.22, 95% CI: 0.16, 0.28; p-trend < 0.001), GMV (β = 0.26, 95% CI: 0.21, 0.32; p-trend < 0.001), white matter volume (WMV; β = 0.08, 95% CI: 0.01, 0.15; p-trend = 0.001), hippocampus volume (β = 0.15, 95% CI: 0.08, 0.22; p-trend < 0.001), and WMHV burden (β = - 0.23, 95% CI: - 0.29, - 0.17; p-trend < 0.001). Those with four or five low-risk lifestyle factors showed approximately 2.0-5.8 years of delay in aging of brain structure. Adherence to a healthier lifestyle was associated with a lower degree of neurodegeneration-related brain structural markers in middle-aged and older adults.
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Affiliation(s)
- Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jie Shen
- School of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xueli Cai
- Department of Neurology, Lishui Hospital, Zhejiang University School of Medicine, Lishui, China
| | - Hui Chen
- School of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Geng Zong
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wanlin Zhu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jing Jing
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Tao Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China
| | - Aoming Jin
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xia Meng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Changzheng Yuan
- School of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, USA.
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- China National Clinical Research Center for Neurological Diseases, Beijing, China.
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
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Gervasi T, Mandalari G. The Interplay Between Gut Microbiota and Central Nervous System. Curr Pharm Des 2023; 29:3274-3281. [PMID: 38062662 DOI: 10.2174/0113816128264312231101110307] [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: 06/11/2023] [Accepted: 09/14/2023] [Indexed: 01/26/2024]
Abstract
This review highlights the relationships between gastrointestinal microorganisms and the brain. The gut microbiota communicates with the central nervous system through nervous, endocrine, and immune signalling mechanisms. Our brain can modulate the gut microbiota structure and function through the autonomic nervous system, and possibly through neurotransmitters which directly act on bacterial gene expression. In this context, oxidative stress is one the main factors involved in the dysregulation of the gut-brain axis and consequently in neurodegenerative disorders. Several factors influence the susceptibility to oxidative stress by altering the antioxidant status or free oxygen radical generation. Amongst these, of interest is alcohol, a commonly used substance which can negatively influence the central nervous system and gut microbiota, with a key role in the development of neurodegenerative disorder. The role of "psychobiotics" as a novel contrast strategy for preventing and treating disorders caused due to alcohol use and abuse has been investigated.
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Affiliation(s)
- Teresa Gervasi
- Department of Biomedical and Dental Science and Morphofunctional Imaging, University of Messina, Messina 98166, Italy
| | - Giuseppina Mandalari
- Department of Chemical, Biological, Pharmaceutical and Environmental Science, University of Messina, Messina 98166, Italy
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10
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Listabarth S, Groemer M, Waldhoer T, Vyssoki B, Pruckner N, Vyssoki S, Glahn A, König-Castillo DM, König D. Cognitive decline and alcohol consumption in the aging population-A longitudinal analysis of the Survey of Health, Ageing and Retirement in Europe. Eur Psychiatry 2022; 65:e83. [PMID: 36398412 PMCID: PMC9748981 DOI: 10.1192/j.eurpsy.2022.2344] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Prevalence of cognitive decline and dementia is rising globally, with more than 10 million new cases every year. These conditions cause a significant burden for individuals, their caregivers, and health care systems. As no causal treatment for dementia exists, prevention of cognitive decline is of utmost importance. Notably, alcohol is among the most significant modifiable risk factors for cognitive decline. METHODS Longitudinal data across 15 years on 6,967 individuals of the Survey of Health, Ageing and Retirement in Europe were used to analyze the effect of alcohol consumption and further modifiable (i.e., smoking, depression, and educational obtainment) and non-modifiable risk factors (sex and age) on cognitive functioning (i.e., memory and verbal fluency). For this, a generalized estimating equation linear model was estimated for every cognitive test domain assessed. RESULTS Consistent results were revealed in all three regression models: A nonlinear association between alcohol consumption and cognitive decline was found-moderate alcohol intake was associated with overall better global cognitive function than low or elevated alcohol consumption or complete abstinence. Furthermore, female sex and higher educational obtainment were associated with better cognitive function, whereas higher age and depression were associated with a decline in cognitive functioning. No significant association was found for smoking. CONCLUSION Our data indicate that alcohol use is a relevant risk factor for cognitive decline in older adults. Furthermore, evidence-based therapeutic concepts to reduce alcohol consumption exist and should be of primary interest in prevention measures considering the aging European population.
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Affiliation(s)
- Stephan Listabarth
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Magdalena Groemer
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Thomas Waldhoer
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria
| | - Benjamin Vyssoki
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Nathalie Pruckner
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Sandra Vyssoki
- Department of Health Sciences, St. Pölten University of Applied Sciences, Sankt Pölten, Austria
| | - Alexander Glahn
- Department for Psychiatry, Social Psychiatry and Psychotherapy, Medical University of Hannover, Hannover, Germany
| | | | - Daniel König
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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11
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Bauer LO, Hesselbrock VM. Signal in the noise: Altered brain activation among adolescent alcohol users detected via the analysis of intra-individual variability 1. Psychopharmacology (Berl) 2022; 239:3595-3604. [PMID: 36102952 PMCID: PMC9471029 DOI: 10.1007/s00213-022-06234-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 09/02/2022] [Indexed: 11/30/2022]
Abstract
RATIONALE Unlike its average level, the variability in brain activation over time or trials can capture subtle and brief disruptions likely to occur among participants with low-to-moderate levels of substance use or misuse. OBJECTIVE The present study used this intra-individual variability measurement approach to detect neural processing differences associated with light-to-moderate use of alcohol among 14-19-year-old adolescents. METHOD A total of 128 participants reporting any level of alcohol use during the previous 6 months and 87 participants reporting no use during this period completed intake questionnaires and interviews as well as an assessment of P300 electroencephalographic responses to novel stimuli recorded during two separate tasks. RESULTS In addition to differing in recent alcohol use, the groups differed in nicotine and cannabis use, risk-taking behavior and conduct disorder symptoms, and P300 amplitude inter-trial variability (ITV) across both tasks. Across all participants, P300 ITV was positively correlated with a family history of depression but not with a family history of alcohol dependence. There were no group differences in P300 amplitude averaged across trials. CONCLUSIONS Recent reports attributing brain volume or brain function differences to an effect of light-to-moderate alcohol use should be viewed with great caution. In the present analysis of brain function differences among substance-using adolescents, the group differences were small, complicated by many factors coinciding with or preceding alcohol use, and not reflected in a stable central tendency.
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Affiliation(s)
- Lance O Bauer
- Department of Psychiatry, University of Connecticut School of Medicine, 263 Farmington Ave., Farmington, CT, 06030-1410, USA.
| | - Victor M Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, 263 Farmington Ave., Farmington, CT, 06030-1410, USA
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12
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Zhang G, Li N, Liu H, Zheng H, Zheng W. Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake. Front Neurosci 2022; 16:974778. [PMID: 36203810 PMCID: PMC9531019 DOI: 10.3389/fnins.2022.974778] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/02/2022] [Indexed: 02/04/2023] Open
Abstract
AIMS Currently, there are only a few studies concerning brain functional alterations after acute alcohol exposure, and the majority of existing studies attach more importance to the spatial properties of brain function without considering the temporal properties. The current study adopted sliding window to investigate the resting-state brain networks in healthy volunteers after acute alcohol intake and to explore the dynamic changes in network connectivity. MATERIALS AND METHODS Twenty healthy volunteers were enrolled in this study. Blood-oxygen-level-dependent (BOLD) data prior to drinking were obtained as control, while that 0.5 and 1 h after drinking were obtained as the experimental group. Reoccurring functional connectivity patterns (states) were determined following group independent component analysis (ICA), sliding window analysis and k-means clustering. Between-group comparisons were performed with respect to the functional connectivity states fractional windows, mean dwell time, and the number of transitions. RESULTS Three optimal functional connectivity states were identified. The fractional windows and mean dwell time of 0.5 h group and 1 h group increased in state 3, while the fraction window and mean dwell time of 1 h group decreased in state 1. State 1 is characterized by strong inter-network connections between basal ganglia network (BGN) and sensorimotor network (SMN), BGN and cognitive executive network (CEN), and default mode network (DMN) and visual network (VN). However, state 3 is distinguished by relatively weak intra-network connections in SMN, VN, CEN, and DMN. State 3 was thought to be a characteristic connectivity pattern of the drunk brain. State 1 was believed to represent the brain's main connection pattern when awake. Such dynamic changes in brain network connectivity were consistent with participants' subjective feelings after drinking. CONCLUSION The current study reveals the dynamic change in resting-state brain functional network connectivity before and after acute alcohol intake. It was discovered that there might be relatively independent characteristic functional network connection patterns under intoxication, and the corresponding patterns characterize the clinical manifestations of volunteers. As a valuable imaging biomarker, dynamic functional network connectivity (dFNC) offers a new approach and basis for further explorations on brain network alterations after alcohol consumption and the alcohol-related mechanisms for neurological damage.
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Affiliation(s)
- Gengbiao Zhang
- Department of Radiology, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Ni Li
- The Family Medicine Branch, Department of Radiology, The First Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Hongkun Liu
- Department of Radiology, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Hongyi Zheng
- Department of Radiology, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Wenbin Zheng
- Department of Radiology, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
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13
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Launes J, Uurainen H, Virta M, Hokkanen L. Self-administered online test of memory functions. NORDIC PSYCHOLOGY 2022. [DOI: 10.1080/19012276.2022.2074525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Jyrki Launes
- Faculty of Medicine, Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Hanna Uurainen
- Faculty of Medicine, Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Maarit Virta
- Faculty of Medicine, Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Laura Hokkanen
- Faculty of Medicine, Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
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14
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Associations between alcohol consumption and gray and white matter volumes in the UK Biobank. Nat Commun 2022; 13:1175. [PMID: 35246521 PMCID: PMC8897479 DOI: 10.1038/s41467-022-28735-5] [Citation(s) in RCA: 58] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 01/26/2022] [Indexed: 12/11/2022] Open
Abstract
Heavy alcohol consumption has been associated with brain atrophy, neuronal loss, and poorer white matter fiber integrity. However, there is conflicting evidence on whether light-to-moderate alcohol consumption shows similar negative associations with brain structure. To address this, we examine the associations between alcohol intake and brain structure using multimodal imaging data from 36,678 generally healthy middle-aged and older adults from the UK Biobank, controlling for numerous potential confounds. Consistent with prior literature, we find negative associations between alcohol intake and brain macrostructure and microstructure. Specifically, alcohol intake is negatively associated with global brain volume measures, regional gray matter volumes, and white matter microstructure. Here, we show that the negative associations between alcohol intake and brain macrostructure and microstructure are already apparent in individuals consuming an average of only one to two daily alcohol units, and become stronger as alcohol intake increases.
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Abstract
PURPOSE OF REVIEW Alcohol is gaining increased recognition as an important risk factor for dementia. This review summarises recent evidence on the relationship between alcohol use and dementia, focusing on studies published from January 2019 to August 2020. RECENT FINDINGS Epidemiological data continues to yield results consistent with protective effects of low-to-moderate alcohol consumption for dementia and cognitive function. However, recent literature highlights the methodological limitations of existing observational studies. The effects of chronic, heavy alcohol use are clearer, with excessive consumption causing alcohol-related brain damage. Several pathways to this damage have been suggested, including the neurotoxic effects of thiamine deficiency, ethanol and acetaldehyde. SUMMARY Future research would benefit from greater implementation of analytical and design-based approaches to robustly model the alcohol use-dementia relationship in the general population, and should make use of large, consortia-level data. Early intervention to prevent dementia is critical: thiamine substitution has shown potential but requires more research, and psychosocial interventions to treat harmful alcohol use have proven effective. Finally, diagnostic criteria for alcohol-related dementia require formal validation to ensure usefulness in clinical practice.
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Affiliation(s)
- Louise Mewton
- Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
| | - Briana Lees
- Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia
| | - Rahul Tony Rao
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
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