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Leyden GM, Urquijo H, Hughes AD, Davey Smith G, Richardson TG. Characterizing the Causal Pathway From Childhood Adiposity to Right Heart Physiology and Pulmonary Circulation Using Lifecourse Mendelian Randomization. J Am Heart Assoc 2024; 13:e030453. [PMID: 38456449 PMCID: PMC11010002 DOI: 10.1161/jaha.123.030453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 10/19/2023] [Indexed: 03/09/2024]
Abstract
BACKGROUND Observational epidemiological studies have reported an association between childhood adiposity and altered cardiac morphology and function in later life. However, whether this is due to a direct consequence of being overweight during childhood has been difficult to establish, particularly as accounting for other measures of body composition throughout the lifecourse can be exceptionally challenging. METHODS AND RESULTS In this study, we used human genetics to investigate this using a causal inference technique known as lifecourse Mendelian randomization. This approach allowed us to evaluate the effect of childhood body size on 11 measures of right heart and pulmonary circulation independent of other anthropometric traits at various stages in the lifecourse. We found strong evidence that childhood body size has a direct effect on an enlarged right heart structure in later life (eg, right ventricular end-diastolic volume: β=0.24 [95% CI, 0.15-0.33]; P=3×10-7) independent of adulthood body size. In contrast, childhood body size effects on maximum ascending aorta diameter attenuated upon accounting for body size in adulthood, suggesting that this effect is likely attributed to individuals remaining overweight into later life. Effects of childhood body size on pulmonary artery traits and measures of right atrial function became weaker upon accounting for adulthood fat-free mass and childhood height, respectively. CONCLUSIONS Our findings suggest that, although childhood body size has a long-term influence on an enlarged heart structure in adulthood, associations with the other structural components of the cardiovascular system and their function may be largely attributed to body composition at other stages in the lifecourse.
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Affiliation(s)
- Genevieve M. Leyden
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of BristolBristolUK
- Bristol Medical School: Translational Health Sciences, Dorothy Hodgkin BuildingUniversity of BristolBristolUK
| | - Helena Urquijo
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of BristolBristolUK
| | - Alun D. Hughes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental MedicineInstitute of Cardiovascular Science, University College LondonLondonUK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of BristolBristolUK
| | - Tom G. Richardson
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of BristolBristolUK
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Schuermans A, Vlasschaert C, Nauffal V, Cho SMJ, Uddin MM, Nakao T, Niroula A, Klarqvist MDR, Weeks LD, Lin AE, Saadatagah S, Lannery K, Wong M, Hornsby W, Lubitz SA, Ballantyne C, Jaiswal S, Libby P, Ebert BL, Bick AG, Ellinor PT, Natarajan P, Honigberg MC. Clonal haematopoiesis of indeterminate potential predicts incident cardiac arrhythmias. Eur Heart J 2024; 45:791-805. [PMID: 37952204 PMCID: PMC10919923 DOI: 10.1093/eurheartj/ehad670] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 09/07/2023] [Accepted: 09/26/2023] [Indexed: 11/14/2023] Open
Abstract
BACKGROUND AND AIMS Clonal haematopoiesis of indeterminate potential (CHIP), the age-related expansion of blood cells with preleukemic mutations, is associated with atherosclerotic cardiovascular disease and heart failure. This study aimed to test the association of CHIP with new-onset arrhythmias. METHODS UK Biobank participants without prevalent arrhythmias were included. Co-primary study outcomes were supraventricular arrhythmias, bradyarrhythmias, and ventricular arrhythmias. Secondary outcomes were cardiac arrest, atrial fibrillation, and any arrhythmia. Associations of any CHIP [variant allele fraction (VAF) ≥ 2%], large CHIP (VAF ≥10%), and gene-specific CHIP subtypes with incident arrhythmias were evaluated using multivariable-adjusted Cox regression. Associations of CHIP with myocardial interstitial fibrosis [T1 measured using cardiac magnetic resonance (CMR)] were also tested. RESULTS This study included 410 702 participants [CHIP: n = 13 892 (3.4%); large CHIP: n = 9191 (2.2%)]. Any and large CHIP were associated with multi-variable-adjusted hazard ratios of 1.11 [95% confidence interval (CI) 1.04-1.18; P = .001] and 1.13 (95% CI 1.05-1.22; P = .001) for supraventricular arrhythmias, 1.09 (95% CI 1.01-1.19; P = .031) and 1.13 (95% CI 1.03-1.25; P = .011) for bradyarrhythmias, and 1.16 (95% CI, 1.00-1.34; P = .049) and 1.22 (95% CI 1.03-1.45; P = .021) for ventricular arrhythmias, respectively. Associations were independent of coronary artery disease and heart failure. Associations were also heterogeneous across arrhythmia subtypes and strongest for cardiac arrest. Gene-specific analyses revealed an increased risk of arrhythmias across driver genes other than DNMT3A. Large CHIP was associated with 1.31-fold odds (95% CI 1.07-1.59; P = .009) of being in the top quintile of myocardial fibrosis by CMR. CONCLUSIONS CHIP may represent a novel risk factor for incident arrhythmias, indicating a potential target for modulation towards arrhythmia prevention and treatment.
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Affiliation(s)
- Art Schuermans
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | | | - Victor Nauffal
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - So Mi Jemma Cho
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Integrative Research Center for Cerebrovascular and Cardiovascular Diseases, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Md Mesbah Uddin
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
| | - Tetsushi Nakao
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Abhishek Niroula
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Laboratory Medicine, Lund University, Lund, Sweden
| | | | - Lachelle D Weeks
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Amy E Lin
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Kim Lannery
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
| | - Megan Wong
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
| | - Whitney Hornsby
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
| | - Steven A Lubitz
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| | | | - Siddhartha Jaiswal
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Peter Libby
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Benjamin L Ebert
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA, USA
| | - Alexander G Bick
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Patrick T Ellinor
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| | - Pradeep Natarajan
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| | - Michael C Honigberg
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
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Gurholt TP, Borda MG, Parker N, Fominykh V, Kjelkenes R, Linge J, van der Meer D, Sønderby IE, Duque G, Westlye LT, Aarsland D, Andreassen OA. Linking sarcopenia, brain structure and cognitive performance: a large-scale UK Biobank study. Brain Commun 2024; 6:fcae083. [PMID: 38510210 PMCID: PMC10953622 DOI: 10.1093/braincomms/fcae083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/15/2023] [Accepted: 03/06/2024] [Indexed: 03/22/2024] Open
Abstract
Sarcopenia refers to age-related loss of muscle mass and function and is related to impaired somatic and brain health, including cognitive decline and Alzheimer's disease. However, the relationships between sarcopenia, brain structure and cognition are poorly understood. Here, we investigate the associations between sarcopenic traits, brain structure and cognitive performance. We included 33 709 UK Biobank participants (54.2% female; age range 44-82 years) with structural and diffusion magnetic resonance imaging, thigh muscle fat infiltration (n = 30 561) from whole-body magnetic resonance imaging (muscle quality indicator) and general cognitive performance as indicated by the first principal component of a principal component analysis across multiple cognitive tests (n = 22 530). Of these, 1703 participants qualified for probable sarcopenia based on low handgrip strength, and we assigned the remaining 32 006 participants to the non-sarcopenia group. We used multiple linear regression to test how sarcopenic traits (probable sarcopenia versus non-sarcopenia and percentage of thigh muscle fat infiltration) relate to cognitive performance and brain structure (cortical thickness and area, white matter fractional anisotropy and deep and lower brain volumes). Next, we used structural equation modelling to test whether brain structure mediated the association between sarcopenic and cognitive traits. We adjusted all statistical analyses for confounders. We show that sarcopenic traits (probable sarcopenia versus non-sarcopenia and muscle fat infiltration) are significantly associated with lower cognitive performance and various brain magnetic resonance imaging measures. In probable sarcopenia, for the included brain regions, we observed widespread significant lower white matter fractional anisotropy (77.1% of tracts), predominantly lower regional brain volumes (61.3% of volumes) and thinner cortical thickness (37.9% of parcellations), with |r| effect sizes in (0.02, 0.06) and P-values in (0.0002, 4.2e-29). In contrast, we observed significant associations between higher muscle fat infiltration and widespread thinner cortical thickness (76.5% of parcellations), lower white matter fractional anisotropy (62.5% of tracts) and predominantly lower brain volumes (35.5% of volumes), with |r| effect sizes in (0.02, 0.07) and P-values in (0.0002, 1.9e-31). The regions showing the most significant effect sizes across the cortex, white matter and volumes were of the sensorimotor system. Structural equation modelling analysis revealed that sensorimotor brain regions mediate the link between sarcopenic and cognitive traits [probable sarcopenia: P-values in (0.0001, 1.0e-11); muscle fat infiltration: P-values in (7.7e-05, 1.7e-12)]. Our findings show significant associations between sarcopenic traits, brain structure and cognitive performance in a middle-aged and older adult population. Mediation analyses suggest that regional brain structure mediates the association between sarcopenic and cognitive traits, with potential implications for dementia development and prevention.
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Affiliation(s)
- Tiril P Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo 0424, Norway
| | - Miguel Germán Borda
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger 4068, Norway
- Faculty of Health Sciences, University of Stavanger, Stavanger 4036, Norway
- Semillero de Neurociencias y Envejecimiento, Ageing Institute, Medical School, Pontificia Universidad Javeriana, Bogota 111611, Colombia
| | - Nadine Parker
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo 0424, Norway
| | - Vera Fominykh
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo 0424, Norway
| | - Rikka Kjelkenes
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo 0424, Norway
- Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Jennifer Linge
- AMRA Medical AB, Linköping 58222, Sweden
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping 58183, Sweden
| | - Dennis van der Meer
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo 0424, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht 6200MD, The Netherlands
| | - Ida E Sønderby
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo 0424, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo 0424, Norway
| | - Gustavo Duque
- Dr. Joseph Kaufmann Chair in Geriatric Medicine, Department of Medicine and Research Institute of the McGill University Health Centre, McGill University, Montreal, QC H4A 3J1, Canada
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo 0424, Norway
- Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Dag Aarsland
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger 4068, Norway
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London WC2R 2LS, UK
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo 0424, Norway
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Green RE, Sudre CH, Warren‐Gash C, Butt J, Waterboer T, Hughes AD, Schott JM, Richards M, Chaturvedi N, Williams DM. Common infections and neuroimaging markers of dementia in three UK cohort studies. Alzheimers Dement 2024; 20:2128-2142. [PMID: 38248636 PMCID: PMC10984486 DOI: 10.1002/alz.13613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/13/2023] [Accepted: 11/25/2023] [Indexed: 01/23/2024]
Abstract
INTRODUCTION We aimed to investigate associations between common infections and neuroimaging markers of dementia risk (brain volume, hippocampal volume, white matter lesions) across three population-based studies. METHODS We tested associations between serology measures (pathogen serostatus, cumulative burden, continuous antibody responses) and outcomes using linear regression, including adjustments for total intracranial volume and scanner/clinic information (basic model), age, sex, ethnicity, education, socioeconomic position, alcohol, body mass index, and smoking (fully adjusted model). Interactions between serology measures and apolipoprotein E (APOE) genotype were tested. Findings were meta-analyzed across cohorts (Nmain = 2632; NAPOE-interaction = 1810). RESULTS Seropositivity to John Cunningham virus associated with smaller brain volumes in basic models (β = -3.89 mL [-5.81, -1.97], Padjusted < 0.05); these were largely attenuated in fully adjusted models (β = -1.59 mL [-3.55, 0.36], P = 0.11). No other relationships were robust to multiple testing corrections and sensitivity analyses, but several suggestive associations were observed. DISCUSSION We did not find clear evidence for relationships between common infections and markers of dementia risk. Some suggestive findings warrant testing for replication.
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Affiliation(s)
- Rebecca E. Green
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
| | - Carole H. Sudre
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of Medical Physics and Biomedical EngineeringCentre for Medical Image Computing (CMIC)University College London (UCL)LondonUK
| | - Charlotte Warren‐Gash
- Faculty of Epidemiology and Population HealthLondon School of Hygiene and Tropical MedicineLondonUK
| | - Julia Butt
- Division of Infections and Cancer EpidemiologyGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Tim Waterboer
- Division of Infections and Cancer EpidemiologyGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Alun D. Hughes
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
| | | | - Marcus Richards
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
| | - Dylan M. Williams
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
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Watt JK, Dickie DA, Ho FK, Lyall DM, Dawson J, Quinn TJ. Validation of the brain health index in the European Prevention of Alzheimer's Dementia cohort. Cereb Circ Cogn Behav 2024; 6:100214. [PMID: 38595911 PMCID: PMC11002803 DOI: 10.1016/j.cccb.2024.100214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/09/2024] [Accepted: 02/14/2024] [Indexed: 04/11/2024]
Abstract
Background Brain Health Index (BHI) assimilates various MRI sequences, giving a quantitative measure of brain health. To date, BHI validation has been cross-sectional and limited to selected populations. Further large-scale validation and assessment of temporal change is required to understand its clinical utility. Aim Assess 1) relationships between variables associated with cognitive decline and BHI 2) associations between BHI and measures of cognition and 3) longitudinal changes in BHI and relationship with cognitive function. Methods BHI computation involved Gaussian mixture-model cluster analysis of T1, T2, T2*, and T2 FLAIR MRI data from participants within the European Prevention of Alzheimer's Dementia (EPAD) cohort. Group differences (gender- and health-based) were evaluated using independent samples Welch's t-tests. Relationships between BHI, age and cognitive tests used linear regression. Longitudinal analysis (12/24 months) utilised mixed linear regression models to examine BHI changes, and paired BHI/cognition associations. Results Data from N = 1496 predominantly Caucasian participants (50-88 years old, 43.32% male) were used. BHI scores were lower in those with diabetes (p < 0.001, d = 0.419), hypertension (p < 0.001, d = 0.375), hypercholesterolemia (p < 0.001, d = 0.193) and stroke (p < 0.05, d = 0.512). APOE was not significantly related to BHI scores. After correction for age, cross-sectional BHI scores were significantly associated with all measures of cognitive function in males, but only the Four Mountains Test (4MT) in females. Longitudinal change in BHI and cognition were not consistently related. Conclusions BHI is a valid marker of cognitive decline and relatively stable over 1-2 year follow-up periods. Further work should assess temporal changes over a longer duration and determine relationships between BHI and cognition in more diverse populations.
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Affiliation(s)
- Jodi K. Watt
- School of Cardiovascular and Metabolic Health, University of Glasgow, Scotland, United Kingdom
| | - David Alexander Dickie
- School of Cardiovascular and Metabolic Health, University of Glasgow, Scotland, United Kingdom
| | - Frederick K. Ho
- School of Health and Wellbeing, University of Glasgow, Scotland, United Kingdom
| | - Donald M. Lyall
- School of Health and Wellbeing, University of Glasgow, Scotland, United Kingdom
| | - Jesse Dawson
- School of Cardiovascular and Metabolic Health, University of Glasgow, Scotland, United Kingdom
| | - Terence J. Quinn
- School of Cardiovascular and Metabolic Health, University of Glasgow, Scotland, United Kingdom
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Chen X, Wei D, Fang F, Song H, Yin L, Kaijser M, Gurholt TP, Andreassen OA, Valdimarsdóttir U, Hu K, Duan M. Peripheral vertigo and subsequent risk of depression and anxiety disorders: a prospective cohort study using the UK Biobank. BMC Med 2024; 22:63. [PMID: 38336700 PMCID: PMC10858592 DOI: 10.1186/s12916-023-03179-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 11/15/2023] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND Peripheral vertigo is often comorbid with psychiatric disorders. However, no longitudinal study has quantified the association between peripheral vertigo and risk of psychiatric disorders. Furthermore, it remains unknown how the white matter integrity of frontal-limbic network relates to the putative peripheral vertigo-psychiatric disorder link. METHODS We conducted a cohort study including 452,053 participants of the UK Biobank with a follow-up from 2006 through 2021. We assessed the risks of depression and anxiety disorders in relation to a hospitalization episode involving peripheral vertigo using Cox proportional hazards models. We also examined the associations of peripheral vertigo, depression, and anxiety with MRI fractional anisotropy (FA) in a subsample with brain MRI data (N = 36,087), using multivariable linear regression. RESULTS Individuals with an inpatient diagnosis of peripheral vertigo had elevated risks of incident depression (hazard ratio (HR) 2.18; 95% confidence interval (CI) 1.79-2.67) and anxiety (HR 2.11; 95% CI 1.71-2.61), compared to others, particularly within 2 years after hospitalization (HR for depression 2.91; 95% CI 2.04-4.15; HR for anxiety 4.92; 95% CI 3.62-6.69). Depression was associated with lower FA in most studied white matter regions, whereas anxiety and peripheral vertigo did not show statistically significant associations with FA. CONCLUSIONS Individuals with an inpatient diagnosis of peripheral vertigo have increased subsequent risks of depression and anxiety disorders, especially within 2 years after hospitalization. Our findings further indicate a link between depression and lower microstructural connectivity as well as integrity beyond the frontal-limbic network.
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Affiliation(s)
- Xiaowan Chen
- Department of Otolaryngology Head and Neck Surgery, the First Hospital of Lanzhou University, Lanzhou, Gansu Province, China
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
- Department of Otolaryngology Head and Neck Surgery & Audiology and Neurotology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Dang Wei
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Fang Fang
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Huan Song
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
- Centre of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Li Yin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Magnus Kaijser
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Tiril Pedersen Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital &, University of Oslo, Oslo, Norway
| | - Ole Andreas Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, Oslo University Hospital &, University of Oslo, Oslo, Norway
| | - Unnur Valdimarsdóttir
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
- Centre of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Epidemiology, Harvard TH Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Kejia Hu
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden.
| | - Maoli Duan
- Department of Otolaryngology Head and Neck Surgery & Audiology and Neurotology, Karolinska University Hospital, Stockholm, Sweden.
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 171 77, Stockholm, Sweden.
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Stolicyn A, Lyall LM, Lyall DM, Høier NK, Adams MJ, Shen X, Cole JH, McIntosh AM, Whalley HC, Smith DJ. Comprehensive assessment of sleep duration, insomnia, and brain structure within the UK Biobank cohort. Sleep 2024; 47:zsad274. [PMID: 37889226 PMCID: PMC10851840 DOI: 10.1093/sleep/zsad274] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/22/2023] [Indexed: 10/28/2023] Open
Abstract
STUDY OBJECTIVES To assess for associations between sleeping more than or less than recommended by the National Sleep Foundation (NSF), and self-reported insomnia, with brain structure. METHODS Data from the UK Biobank cohort were analyzed (N between 9K and 32K, dependent on availability, aged 44 to 82 years). Sleep measures included self-reported adherence to NSF guidelines on sleep duration (sleeping between 7 and 9 hours per night), and self-reported difficulty falling or staying asleep (insomnia). Brain structural measures included global and regional cortical or subcortical morphometry (thickness, surface area, volume), global and tract-related white matter microstructure, brain age gap (difference between chronological age and age estimated from brain scan), and total volume of white matter lesions. RESULTS Longer-than-recommended sleep duration was associated with lower overall grey and white matter volumes, lower global and regional cortical thickness and volume measures, higher brain age gap, higher volume of white matter lesions, higher mean diffusivity globally and in thalamic and association fibers, and lower volume of the hippocampus. Shorter-than-recommended sleep duration was related to higher global and cerebellar white matter volumes, lower global and regional cortical surface areas, and lower fractional anisotropy in projection fibers. Self-reported insomnia was associated with higher global gray and white matter volumes, and with higher volumes of the amygdala, hippocampus, and putamen. CONCLUSIONS Sleeping longer than recommended by the NSF is associated with a wide range of differences in brain structure, potentially indicative of poorer brain health. Sleeping less than recommended is distinctly associated with lower cortical surface areas. Future studies should assess the potential mechanisms of these differences and investigate long sleep duration as a putative marker of brain health.
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Affiliation(s)
- Aleks Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Laura M Lyall
- School of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - Donald M Lyall
- School of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - Nikolaj Kjær Høier
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Copenhagen Research Center for Mental Health CORE, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Mark J Adams
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - James H Cole
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Heather C Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Daniel J Smith
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
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8
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Thanaj M, Basty N, Whitcher B, Sorokin EP, Liu Y, Srinivasan R, Cule M, Thomas EL, Bell JD. Precision MRI phenotyping of muscle volume and quality at a population scale. Front Physiol 2024; 15:1288657. [PMID: 38370011 PMCID: PMC10869600 DOI: 10.3389/fphys.2024.1288657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 01/09/2024] [Indexed: 02/20/2024] Open
Abstract
Introduction: Magnetic resonance imaging (MRI) enables direct measurements of muscle volume and quality, allowing for an in-depth understanding of their associations with anthropometric traits, and health conditions. However, it is unclear which muscle volume measurements: total muscle volume, regional measurements, measurements of muscle quality: intermuscular adipose tissue (IMAT) or proton density fat fraction (PDFF), are most informative and associate with relevant health conditions such as dynapenia and frailty. Methods: We have measured image-derived phenotypes (IDPs) including total and regional muscle volumes and measures of muscle quality, derived from the neck-to-knee Dixon images in 44,520 UK Biobank participants. We further segmented paraspinal muscle from 2D quantitative MRI to quantify muscle PDFF and iron concentration. We defined dynapenia based on grip strength below sex-specific cut-off points and frailty based on five criteria (weight loss, exhaustion, grip strength, low physical activity and slow walking pace). We used logistic regression to investigate the association between muscle volume and quality measurements and dynapenia and frailty. Results: Muscle volumes were significantly higher in male compared with female participants, even after correcting for height while, IMAT (corrected for muscle volume) and paraspinal muscle PDFF were significantly higher in female compared with male participants. From the overall cohort, 7.6% (N = 3,261) were identified with dynapenia, and 1.1% (N = 455) with frailty. Dynapenia and frailty were positively associated with age and negatively associated with physical activity levels. Additionally, reduced muscle volume and quality measurements were associated with both dynapenia and frailty. In dynapenia, muscle volume IDPs were most informative, particularly total muscle exhibiting odds ratios (OR) of 0.392, while for frailty, muscle quality was found to be most informative, in particular thigh IMAT volume indexed to height squared (OR = 1.396), both with p-values below the Bonferroni-corrected threshold (p < 8.8 × 10 - 5 ). Conclusion: Our fully automated method enables the quantification of muscle volumes and quality suitable for large population-based studies. For dynapenia, muscle volumes particularly those including greater body coverage such as total muscle are the most informative, whilst, for frailty, markers of muscle quality were the most informative IDPs. These results suggest that different measurements may have varying diagnostic values for different health conditions.
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Affiliation(s)
- Marjola Thanaj
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, United Kingdom
| | - Nicolas Basty
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, United Kingdom
| | - Brandon Whitcher
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, United Kingdom
| | - Elena P. Sorokin
- Calico Life Sciences LLC, South San Francisco, CA, United States
| | - Yi Liu
- Calico Life Sciences LLC, South San Francisco, CA, United States
| | | | - Madeleine Cule
- Calico Life Sciences LLC, South San Francisco, CA, United States
| | - E. Louise Thomas
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, United Kingdom
| | - Jimmy D. Bell
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, United Kingdom
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Korbmacher M, van der Meer D, Beck D, de Lange AMG, Eikefjord E, Lundervold A, Andreassen OA, Westlye LT, Maximov II. Brain asymmetries from mid- to late life and hemispheric brain age. Nat Commun 2024; 15:956. [PMID: 38302499 PMCID: PMC10834516 DOI: 10.1038/s41467-024-45282-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/19/2024] [Indexed: 02/03/2024] Open
Abstract
The human brain demonstrates structural and functional asymmetries which have implications for ageing and mental and neurological disease development. We used a set of magnetic resonance imaging (MRI) metrics derived from structural and diffusion MRI data in N=48,040 UK Biobank participants to evaluate age-related differences in brain asymmetry. Most regional grey and white matter metrics presented asymmetry, which were higher later in life. Informed by these results, we conducted hemispheric brain age (HBA) predictions from left/right multimodal MRI metrics. HBA was concordant to conventional brain age predictions, using metrics from both hemispheres, but offers a supplemental general marker of brain asymmetry when setting left/right HBA into relationship with each other. In contrast to WM brain asymmetries, left/right discrepancies in HBA are lower at higher ages. Our findings outline various sex-specific differences, particularly important for brain age estimates, and the value of further investigating the role of brain asymmetries in brain ageing and disease development.
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Affiliation(s)
- Max Korbmacher
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway.
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway.
- Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway.
| | - Dennis van der Meer
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Dani Beck
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ann-Marie G de Lange
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Eli Eikefjord
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway
| | - Arvid Lundervold
- Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Ole A Andreassen
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ivan I Maximov
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway.
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway.
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10
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Jareebi MA, Lyall DM, Gharawi NF, Shami MO, Dahas N, Alfaifi RF, Hakami A, Darraj MA, Hakami FA, Hakami MH, Almalki HM, Hakami ZT, Alessa A, Alhazmi AA. Causal Associations of Modifiable Risk Factors With Migraine: Evidence From Mendelian Randomization Analysis. Cureus 2024; 16:e53448. [PMID: 38435140 PMCID: PMC10909377 DOI: 10.7759/cureus.53448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/02/2024] [Indexed: 03/05/2024] Open
Abstract
Background and objectives The exact etiology of migraine is unknown; however, it is likely a mixture of genetic and non-genetic factors including lifestyle variables like smoking and diet. This study aims to assess the causal effect of modifiable risk factors on the risk of migraine using two-sample Mendelian randomization. Materials and methods The study used publicly available genome-wide significant single nucleotide polymorphisms (SNPs). The study evaluated a diverse smoking exposure, encompassing age at smoking initiation, smoking intensity, and maternal smoking, alongside other pertinent risk factors, namely key dietary aspects, coffee consumption, BMI, and physical activity. Self-reported migraine was the outcome of the study. The genetic data for migraine were obtained from the FinnGen (Finland) and the UK Biobank (United Kingdom) cohorts. Results With sample sizes ranging from 64,949 to 632,802 for each risk factor collected from several consorts, the study included a total of 282 SNPs for all risk factors. The findings demonstrated that in the FinnGen consortium, genetically estimated dietary factors as well as BMI, were significantly associated with the risk of migraine (OR 0.765 per single unit of BMI, p = 0.011; OR 0.468 per one SD higher cheese intake, p = 0.012; OR 0.286 per one SD higher salad intake, p = 0.004, and 0.625 per one SD higher coffee consumption, p = 0.003, respectively). The results also showed that in the UK Biobank specifically, a genetically estimated history of maternal smoking was significantly associated with an elevated risk of migraine (OR=1.02, p=0.004). Conclusions The latest study implies a connection between maternal smoking and a heightened risk of migraines, whereas cheese intake, salad intake, coffee consumption, BMI, and physical activity are associated with a lower risk of migraine development.
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Affiliation(s)
| | - Donald M Lyall
- School of Health and Wellbeing, University of Glasgow, Glasgow, GBR
| | | | | | - Najwa Dahas
- Medicine and Surgery, Jazan University, Jazan, SAU
| | - Rashed F Alfaifi
- Directorate General of Health Affairs, Ministry of Health, Jazan, SAU
| | | | | | - Faris A Hakami
- Directorate General of Health Affairs, Ministry of Health, Jazan, SAU
| | - Mohammed H Hakami
- Directorate General of Health Affairs, Ministry of Health, Jazan, SAU
| | - Hassan M Almalki
- Directorate General of Health Affairs, Ministry of Health, Jazan, SAU
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11
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Gao Y, Su B, Luo Y, Tian Y, Hong S, Gao S, Xie J, Zheng X. HLA-C*07:01 and HLA-DQB1*02:01 protect against white matter hyperintensities and deterioration of cognitive function: A population-based cohort study. Brain Behav Immun 2024; 115:250-257. [PMID: 37884160 DOI: 10.1016/j.bbi.2023.10.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/14/2023] [Accepted: 10/22/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND Neuroinflammation and aberrant immune regulation are increasingly implicated in the pathophysiology of white matter hyperintensities (WMH), an imaging marker of cerebrovascular pathologies and predictor of cognitive impairment. The role of human leukocyte antigen (HLA) genes, critical in immunoregulation and associated with susceptibility to neurodegenerative diseases, in WMH pathophysiology remains unexplored. METHODS We performed association analyses between classical HLA alleles and WMH volume, derived from MRI scans of 38 302 participants in the UK Biobank. To identify independent functional alleles driving these associations, we conducted conditional forward stepwise regression and lasso regression. We further investigated whether these functional alleles showed consistent associations with WMH across subgroups characterized by varying levels of clinical determinants. Additionally, we validated the clinical relevance of the identified alleles by examining their association with cognitive function (n = 147 549) and dementia (n = 460 029) in a larger cohort. FINDINGS Four HLA alleles (DQB1*02:01, DRB1*03:01, C*07:01, and B*08:01) showed an association with reduced WMH volume after Bonferroni correction for multiple comparisons. Among these alleles, DQB1*02:01 exhibited the most significant association (β = -0.041, 95 % CI: -0.060 to -0.023, p = 1.04 × 10-5). Forward selection and lasso regression analyses indicated that DQB1*02:01 and C*07:01 primarily drove this association. The protective effect against WMH conferred by DQB1*02:01 and C*07:01 persisted in clinically relevant subgroups, with a stronger effect observed in older participants. Carrying DQB1*02:01 and C*07:01 was associated with higher cognitive function, but no association with dementia was found. INTERPRETATION Our population-based findings support the involvement of immune-associated mechanisms, particularly both HLA class I and class II genes, in the pathogenesis of WMH and subsequent consequence of cognitive functions.
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Affiliation(s)
- Yaqing Gao
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Binbin Su
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China
| | - Yanan Luo
- Department of Global Health, School of Public Health, Peking University, Beijing, China
| | - Yaohua Tian
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shenda Hong
- National Institute of Health Data Science, Peking University, Beijing, China; Institute of Medical Technology, Peking University Health Science Center, Beijing, China
| | - Song Gao
- Institute of Medical Technology, Peking University Health Science Center, Beijing, China
| | - Junqing Xie
- Centre for Statistics in Medicine and NIHR Biomedical Research Centre Oxford, NDORMS, University of Oxford, Oxford, UK.
| | - Xiaoying Zheng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China; HeSAY, Peking University, Beijing, China.
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12
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Thanaj M, Basty N, Cule M, Sorokin EP, Whitcher B, Srinivasan R, Lennon R, Bell JD, Thomas EL. Kidney shape statistical analysis: associations with disease and anthropometric factors. BMC Nephrol 2023; 24:362. [PMID: 38057740 PMCID: PMC10698953 DOI: 10.1186/s12882-023-03407-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 11/22/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND Organ measurements derived from magnetic resonance imaging (MRI) have the potential to enhance our understanding of the precise phenotypic variations underlying many clinical conditions. METHODS We applied morphometric methods to study the kidneys by constructing surface meshes from kidney segmentations from abdominal MRI data in 38,868 participants in the UK Biobank. Using mesh-based analysis techniques based on statistical parametric maps (SPMs), we were able to detect variations in specific regions of the kidney and associate those with anthropometric traits as well as disease states including chronic kidney disease (CKD), type-2 diabetes (T2D), and hypertension. Statistical shape analysis (SSA) based on principal component analysis was also used within the disease population and the principal component scores were used to assess the risk of disease events. RESULTS We show that CKD, T2D and hypertension were associated with kidney shape. Age was associated with kidney shape consistently across disease groups. Body mass index (BMI) and waist-to-hip ratio (WHR) were also associated with kidney shape for the participants with T2D. Using SSA, we were able to capture kidney shape variations, relative to size, angle, straightness, width, length, and thickness of the kidneys, within disease populations. We identified significant associations between both left and right kidney length and width and incidence of CKD (hazard ratio (HR): 0.74, 95% CI: 0.61-0.90, p < 0.05, in the left kidney; HR: 0.76, 95% CI: 0.63-0.92, p < 0.05, in the right kidney) and hypertension (HR: 1.16, 95% CI: 1.03-1.29, p < 0.05, in the left kidney; HR: 0.87, 95% CI: 0.79-0.96, p < 0.05, in the right kidney). CONCLUSIONS The results suggest that shape-based analysis of the kidneys can augment studies aiming at the better categorisation of pathologies associated with chronic kidney conditions.
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Affiliation(s)
- Marjola Thanaj
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
| | - Nicolas Basty
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | | | | | - Brandon Whitcher
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | | | - Rachel Lennon
- Wellcome Centre for Cell-Matrix Research, Division of Cell-Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
- Department of Paediatric Nephrology, Royal Manchester Children's Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Jimmy D Bell
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | - E Louise Thomas
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
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13
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Lyall DM, Kormilitzin A, Lancaster C, Sousa J, Petermann‐Rocha F, Buckley C, Harshfield EL, Iveson MH, Madan CR, McArdle R, Newby D, Orgeta V, Tang E, Tamburin S, Thakur LS, Lourida I, Llewellyn DJ, Ranson JM. Artificial intelligence for dementia-Applied models and digital health. Alzheimers Dement 2023; 19:5872-5884. [PMID: 37496259 PMCID: PMC10955778 DOI: 10.1002/alz.13391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 05/19/2023] [Accepted: 05/26/2023] [Indexed: 07/28/2023]
Abstract
INTRODUCTION The use of applied modeling in dementia risk prediction, diagnosis, and prognostics will have substantial public health benefits, particularly as "deep phenotyping" cohorts with multi-omics health data become available. METHODS This narrative review synthesizes understanding of applied models and digital health technologies, in terms of dementia risk prediction, diagnostic discrimination, prognosis, and progression. Machine learning approaches show evidence of improved predictive power compared to standard clinical risk scores in predicting dementia, and the potential to decompose large numbers of variables into relatively few critical predictors. RESULTS This review focuses on key areas of emerging promise including: emphasis on easier, more transparent data sharing and cohort access; integration of high-throughput biomarker and electronic health record data into modeling; and progressing beyond the primary prediction of dementia to secondary outcomes, for example, treatment response and physical health. DISCUSSION Such approaches will benefit also from improvements in remote data measurement, whether cognitive (e.g., online), or naturalistic (e.g., watch-based accelerometry).
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Affiliation(s)
- Donald M. Lyall
- School of Health and WellbeingCollege of Medical and Veterinary Sciences, University of GlasgowGlasgowUK
| | | | | | - Jose Sousa
- Personal Health Data ScienceSANO‐Centre for Computational Personalised MedicineKrakowPoland
- Faculty of MedicineHealth and Life Science, Queen's University BelfastBelfastUK
| | - Fanny Petermann‐Rocha
- School of Health and WellbeingCollege of Medical and Veterinary Sciences, University of GlasgowGlasgowUK
- Centro de Investigación BiomédicaFacultad de Medicina, Universidad Diego PortalesSantiagoChile
| | - Christopher Buckley
- Department of SportExercise and Rehabilitation, Northumbria UniversityNewcastle upon TyneUK
| | - Eric L. Harshfield
- Stroke Research Group, Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Matthew H. Iveson
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | | | - Ríona McArdle
- Translational and Clinical Research InstituteFaculty of Medical Sciences, Newcastle UniversityNewcastle upon TyneUK
| | | | | | - Eugene Tang
- Translational and Clinical Research InstituteFaculty of Medical Sciences, Newcastle UniversityNewcastle upon TyneUK
| | - Stefano Tamburin
- Department of NeurosciencesBiomedicine and Movement Sciences, University of VeronaVeronaItaly
| | | | | | | | - David J. Llewellyn
- University of Exeter Medical SchoolExeterUK
- Alan Turing InstituteLondonUK
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14
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Niedzwiedz CL, Aragón MJ, Breedvelt JJF, Smith DJ, Prady SL, Jacobs R. Severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions among the UK Biobank cohort. BJPsych Open 2023; 9:e211. [PMID: 37933539 PMCID: PMC10753948 DOI: 10.1192/bjo.2023.602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 09/29/2023] [Accepted: 10/08/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND People with mental disorders have worse physical health compared with the general population, which could be attributable to receiving poorer quality healthcare. AIMS To examine the relationship between severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions (ACSCs), and factors associated with increased risk. METHOD Baseline data for England (N = 445 814) were taken from UK Biobank, which recruited participants aged 37-73 years during 2006-2010, and linked to hospital admission records up to 31 December 2019. Participants were grouped into those with a history of either schizophrenia, bipolar disorder, depression or anxiety, or no mental disorder. Survival analysis was used to assess the risk of hospital admission for ACSCs among those with mental disorders compared with those without, adjusting for factors in different domains (sociodemographic, socioeconomic, health and biomarkers, health-related behaviours, social isolation and psychological). RESULTS People with schizophrenia had the highest (unadjusted) risk of hospital admission for ACSCs compared with those with no mental disorder (hazard ratio 4.40, 95% CI 4.04-4.80). People with bipolar disorder (hazard ratio 2.48, 95% CI 2.28-2.69) and depression or anxiety (hazard ratio 1.76, 95% CI 1.73-1.80) also had higher risk. Associations were more conservative when including all admissions, as opposed to first admissions only. The observed associations persisted after adjusting for a range of factors. CONCLUSIONS People with severe mental disorders have the highest risk of preventable hospital admissions. Ensuring people with mental disorders receive adequate ambulatory care is essential to reduce the large health inequalities they experience.
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Affiliation(s)
| | | | | | - Daniel J. Smith
- School of Health and Wellbeing, University of
Glasgow, UK; and Division of Psychiatry, Centre for
Clinical Brain Sciences, University of Edinburgh,
UK
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15
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Ranglani S, Ward J, Sattar N, Strawbridge RJ, Lyall DM. Testing for associations between HbA1c levels, polygenic risk and brain health in UK Biobank (N = 39 283). Diabetes Obes Metab 2023; 25:3136-3143. [PMID: 37435691 DOI: 10.1111/dom.15207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 06/09/2023] [Accepted: 06/18/2023] [Indexed: 07/13/2023]
Abstract
AIM To investigate whether continuous HbA1c levels and HbA1c-polygenic risk scores (HbA1c-PRS) are significantly associated with worse brain health independent of type 2 diabetes (T2D) diagnosis (vs. not), by examining brain structure and cognitive test score phenotypes. METHODS Using UK Biobank data (n = 39 283), we tested whether HbA1c levels and/or HbA1c-PRS were associated with cognitive test scores and brain imaging phenotypes. We adjusted for confounders of age, sex, Townsend deprivation score, level of education, genotyping chip, eight genetic principal components, smoking, alcohol intake frequency, cholesterol medication, body mass index, T2D and apolipoprotein (APOE) e4 dosage. RESULTS We found an association between higher HbA1c levels and poorer performance on symbol digit substitution scores (standardized beta [β] = -0.022, P = .001) in the fully adjusted model. We also found an association between higher HbA1c levels and worse brain MRI phenotypes of grey matter (GM; fully-adjusted β = -0.026, P < .001), whole brain volume (β = -0.072, P = .0113) and a general factor of frontal lobe GM (β = -0.022, P < .001) in partially and fully adjusted models. HbA1c-PRS were significantly associated with GM volume in the fully adjusted model (β = -0.010, P = .0113); however, when adjusted for HbA1c levels, the association was not significant. CONCLUSIONS Our findings suggest that measured HbA1c is associated with poorer cognitive health, and that HbA1c-PRS do not add significant information to this.
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Affiliation(s)
- Sanskar Ranglani
- School of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Joey Ward
- School of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Sciences, University of Glasgow, Glasgow, UK
| | - Rona J Strawbridge
- School of Health & Wellbeing, University of Glasgow, Glasgow, UK
- Division of Cardiovascular Medicine, Department of Medicine Solna, Karolinska Institutet, Solna, Sweden
- HDR-UK, London, UK
| | - Donald M Lyall
- School of Health & Wellbeing, University of Glasgow, Glasgow, UK
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Campbell T, Cullen B. Estimating the effect of physical activity on cognitive function within the UK Biobank cohort. Int J Epidemiol 2023; 52:1592-1611. [PMID: 36749099 PMCID: PMC10555922 DOI: 10.1093/ije/dyad009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 01/25/2023] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Physical activity (PA) has been associated with benefits for cognitive function (CF), but previous estimates of the strength of this relationship may have been biased due to limitations in statistical modelling practices that are common among observational studies. We aimed to address this by using a rigorously constructed conceptual causal model to guide an empirical analysis estimating the effect of PA on CF in the UK Biobank cohort of middle-aged and older adults. METHODS This study analysed a subsample of 334 227 adults from the UK Biobank prospective cohort study. PA was measured subjectively by self-report and by device using accelerometry, and CF was measured using objective cognitive tests. Composite CF measures were derived to represent general and domain-specific performance. Effect coefficients were estimated using regression models, adjusting for a wide range of confounders specified by the assumed causal model, including genetic risk factors, and relevant health, sociodemographic and behavioural variables from across the lifespan. RESULTS Results indicated very small effect sizes (standardized mean difference estimates all <0.01) of inconsistent direction, for both cross-sectional and longitudinal analyses. CONCLUSIONS The expected protective effect of PA on CF was not observed. This may reflect selection bias within UK Biobank, or the relatively young age of the sample at follow-up.
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Affiliation(s)
- Thomas Campbell
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
- NHS Lanarkshire Neuropsychology Service, Monklands Hospital, Airdrie, UK
| | - Breda Cullen
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
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17
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Tanguay-Sabourin C, Fillingim M, Guglietti GV, Zare A, Parisien M, Norman J, Sweatman H, Da-Ano R, Heikkala E, Perez J, Karppinen J, Villeneuve S, Thompson SJ, Martel MO, Roy M, Diatchenko L, Vachon-Presseau E. A prognostic risk score for development and spread of chronic pain. Nat Med 2023; 29:1821-1831. [PMID: 37414898 PMCID: PMC10353938 DOI: 10.1038/s41591-023-02430-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 05/31/2023] [Indexed: 07/08/2023]
Abstract
Chronic pain is a complex condition influenced by a combination of biological, psychological and social factors. Using data from the UK Biobank (n = 493,211), we showed that pain spreads from proximal to distal sites and developed a biopsychosocial model that predicted the number of coexisting pain sites. This data-driven model was used to identify a risk score that classified various chronic pain conditions (area under the curve (AUC) 0.70-0.88) and pain-related medical conditions (AUC 0.67-0.86). In longitudinal analyses, the risk score predicted the development of widespread chronic pain, the spreading of chronic pain across body sites and high-impact pain about 9 years later (AUC 0.68-0.78). Key risk factors included sleeplessness, feeling 'fed-up', tiredness, stressful life events and a body mass index >30. A simplified version of this score, named the risk of pain spreading, obtained similar predictive performance based on six simple questions with binarized answers. The risk of pain spreading was then validated in the Northern Finland Birth Cohort (n = 5,525) and the PREVENT-AD cohort (n = 178), obtaining comparable predictive performance. Our findings show that chronic pain conditions can be predicted from a common set of biopsychosocial factors, which can aid in tailoring research protocols, optimizing patient randomization in clinical trials and improving pain management.
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Affiliation(s)
- Christophe Tanguay-Sabourin
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada.
- Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada.
- Department of Anesthesia, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada.
| | - Matt Fillingim
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada
- Department of Anesthesia, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Gianluca V Guglietti
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada
- Department of Anesthesia, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Azin Zare
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Marc Parisien
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada
- Department of Anesthesia, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Jax Norman
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Hilary Sweatman
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Ronrick Da-Ano
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Eveliina Heikkala
- Research Unit of Population Health, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Oulu, Finland
| | - Jordi Perez
- Department of Anesthesia, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada
- Alan Edwards Pain Management Unit, McGill University Health Centre, Montreal, Quebec, Canada
| | - Jaro Karppinen
- Research Unit of Population Health, University of Oulu, Oulu, Finland
- Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland
- Rehabilitation Services of Southern Karelia Social and Health Care District, Lappeenranta, Finland
| | - Sylvia Villeneuve
- Douglas Mental Health Institute Research Centre, McGill University, Montreal, Quebec, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Scott J Thompson
- Department of Anesthesiology, University of Minnesota, Minneapolis, MN, USA
| | - Marc O Martel
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada
- Department of Anesthesia, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Mathieu Roy
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada
- Department of Anesthesia, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada
- Department of Psychology, McGill University, Montreal, Quebec, Canada
| | - Luda Diatchenko
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada
- Department of Anesthesia, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Etienne Vachon-Presseau
- Alan Edwards Centre for Research on Pain, McGill University, Montreal, Quebec, Canada.
- Department of Anesthesia, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada.
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada.
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18
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Mur J, Marioni RE, Russ TC, Muniz‐Terrera G, Cox SR. Anticholinergic burden in middle and older age is associated with lower cognitive function, but not with brain atrophy. Br J Clin Pharmacol 2023; 89:2224-2235. [PMID: 36813260 PMCID: PMC10953410 DOI: 10.1111/bcp.15698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/31/2023] [Accepted: 02/09/2023] [Indexed: 02/24/2023] Open
Abstract
AIMS The aim of this study is to estimate the association between anticholinergic burden, general cognitive ability and various measures of brain structural MRI in relatively healthy middle-aged and older individuals. METHODS In the UK Biobank participants with linked health-care records (n = 163,043, aged 40-71 at baseline), of whom about 17 000 had MRI data available, we calculated the total anticholinergic drug burden according to 15 different anticholinergic scales and due to different classes of drugs. We then used linear regression to explore the associations between anticholinergic burden and various measures of cognition and structural MRI, including general cognitive ability, 9 separate cognitive domains, brain atrophy, volumes of 68 cortical and 14 subcortical areas and fractional anisotropy and median diffusivity of 25 white-matter tracts. RESULTS Anticholinergic burden was modestly associated with poorer cognition across most anticholinergic scales and cognitive tests (7/9 FDR-adjusted significant associations, standardised betas (β) range: -0.039, -0.003). When using the anticholinergic scale exhibiting the strongest association with cognitive functions, anticholinergic burden due to only some classes of drugs exhibited negative associations with cognitive function, with β-lactam antibiotics (β = -0.035, PFDR < 0.001) and opioids (β = -0.026, PFDR < 0.001) exhibiting the strongest effects. Anticholinergic burden was not associated with any measure of brain macrostructure or microstructure (PFDR > 0.08). CONCLUSIONS Anticholinergic burden is weakly associated with poorer cognition, but there is little evidence for associations with brain structure. Future studies might focus more broadly on polypharmacy or more narrowly on distinct drug classes, instead of using purported anticholinergic action to study the effects of drugs on cognitive ability.
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Affiliation(s)
- Jure Mur
- Lothian Birth Cohorts Group, Department of PsychologyUniversity of EdinburghEdinburghUK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
- Alzheimer Scotland Dementia Research CentreUniversity of EdinburghEdinburghUK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
| | - Tom C. Russ
- Alzheimer Scotland Dementia Research CentreUniversity of EdinburghEdinburghUK
- Edinburgh Dementia PreventionUniversity of EdinburghEdinburghUK
- Division of Psychiatry, Centre for Clinical Brain ScienceUniversity of EdinburghEdinburghUK
| | - Graciela Muniz‐Terrera
- Edinburgh Dementia PreventionUniversity of EdinburghEdinburghUK
- Department of Social MedicineOhio UniversityAthensOhioUSA
| | - Simon R. Cox
- Lothian Birth Cohorts Group, Department of PsychologyUniversity of EdinburghEdinburghUK
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19
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Roelfs D, Frei O, van der Meer D, Tissink E, Shadrin A, Alnaes D, Andreassen OA, Westlye LT, Kaufmann T. Shared genetic architecture between mental health and the brain functional connectome in the UK Biobank. BMC Psychiatry 2023; 23:461. [PMID: 37353766 PMCID: PMC10290393 DOI: 10.1186/s12888-023-04905-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 05/26/2023] [Indexed: 06/25/2023] Open
Abstract
Psychiatric disorders are complex clinical conditions with large heterogeneity and overlap in symptoms, genetic liability and brain imaging abnormalities. Building on a dimensional conceptualization of mental health, previous studies have reported genetic overlap between psychiatric disorders and population-level mental health, and between psychiatric disorders and brain functional connectivity. Here, in 30,701 participants aged 45-82 from the UK Biobank we map the genetic associations between self-reported mental health and resting-state fMRI-based measures of brain network function. Multivariate Omnibus Statistical Test revealed 10 genetic loci associated with population-level mental symptoms. Next, conjunctional FDR identified 23 shared genetic variants between these symptom profiles and fMRI-based brain network measures. Functional annotation implicated genes involved in brain structure and function, in particular related to synaptic processes such as axonal growth (e.g. NGFR and RHOA). These findings provide further genetic evidence of an association between brain function and mental health traits in the population.
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Affiliation(s)
- Daniel Roelfs
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Oleksandr Frei
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Elleke Tissink
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, 1081 HV, The Netherlands
| | - Alexey Shadrin
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dag Alnaes
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Bjørknes College, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany.
- German Center for Mental Health (DZPG), Tübingen, Germany.
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20
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Cox SR, Welstead M. Steps in the right direction for physical frailty research. Lancet Digit Health 2023; 5:e329-e330. [PMID: 37061350 DOI: 10.1016/s2589-7500(23)00066-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 03/23/2023] [Indexed: 04/17/2023]
Affiliation(s)
- Simon R Cox
- Lothian Birth Cohorts, The University of Edinburgh, Edinburgh EH8 9JZ, UK; Department of Psychology, The University of Edinburgh, Edinburgh EH8 9JZ, UK.
| | - Miles Welstead
- Lothian Birth Cohorts, The University of Edinburgh, Edinburgh EH8 9JZ, UK; Department of Psychology, The University of Edinburgh, Edinburgh EH8 9JZ, UK
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21
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Madden RA, Atkinson K, Shen X, Green C, Hillary RF, Hawkins E, Såge E, Sandu AL, Waiter G, McNeil C, Harris M, Campbell A, Porteous D, Macfarlane JA, Murray A, Steele D, Romaniuk L, Lawrie SM, McIntosh AM, Whalley HC. Structural brain correlates of childhood trauma with replication across two large, independent community-based samples. Eur Psychiatry 2023; 66:e19. [PMID: 36697368 PMCID: PMC9970154 DOI: 10.1192/j.eurpsy.2022.2347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
INTRODUCTION Childhood trauma and adversity are common across societies and have strong associations with physical and psychiatric morbidity throughout the life-course. One possible mechanism through which childhood trauma may predispose individuals to poor psychiatric outcomes is via associations with brain structure. This study aimed to elucidate the associations between childhood trauma and brain structure across two large, independent community cohorts. METHODS The two samples comprised (i) a subsample of Generation Scotland (n=1,024); and (ii) individuals from UK Biobank (n=27,202). This comprised n=28,226 for mega-analysis. MRI scans were processed using Free Surfer, providing cortical, subcortical, and global brain metrics. Regression models were used to determine associations between childhood trauma measures and brain metrics and psychiatric phenotypes. RESULTS Childhood trauma associated with lifetime depression across cohorts (OR 1.06 GS, 1.23 UKB), and related to early onset and recurrent course within both samples. There was evidence for associations between childhood trauma and structural brain metrics. This included reduced global brain volume, and reduced cortical surface area with highest effects in the frontal (β=-0.0385, SE=0.0048, p(FDR)=5.43x10-15) and parietal lobes (β=-0.0387, SE=0.005, p(FDR)=1.56x10-14). At a regional level the ventral diencephalon (VDc) displayed significant associations with childhood trauma measures across both cohorts and at mega-analysis (β=-0.0232, SE=0.0039, p(FDR)=2.91x10-8). There were also associations with reduced hippocampus, thalamus, and nucleus accumbens volumes. DISCUSSION Associations between childhood trauma and reduced global and regional brain volumes were found, across two independent UK cohorts, and at mega-analysis. This provides robust evidence for a lasting effect of childhood adversity on brain structure.
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Affiliation(s)
- Rebecca A Madden
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Kimberley Atkinson
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Claire Green
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Robert F Hillary
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Emma Hawkins
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Emma Såge
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Anca-Larisa Sandu
- School of Medicine, University of Aberdeen, Aberdeen, United Kingdom
| | - Gordon Waiter
- School of Medicine, University of Aberdeen, Aberdeen, United Kingdom
| | | | - Mathew Harris
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Archie Campbell
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - David Porteous
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Jennifer A Macfarlane
- Medical Sciences and Nutrition, School of Medicine, University of Dundee, Dundee, United Kingdom
| | - Alison Murray
- School of Medicine, University of Aberdeen, Aberdeen, United Kingdom
| | - Douglas Steele
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Liana Romaniuk
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Heather C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
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22
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Williams CM, Peyre H, Ramus F. Brain volumes, thicknesses, and surface areas as mediators of genetic factors and childhood adversity on intelligence. Cereb Cortex 2022; 33:5885-5895. [PMID: 36533516 DOI: 10.1093/cercor/bhac468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 12/23/2022] Open
Abstract
Although genetic and environmental factors influence general intelligence (g-factor), few studies examined the neuroanatomical measures mediating environmental and genetic effects on intelligence. Here, we investigate the brain volumes, cortical mean thicknesses, and cortical surface areas mediating the effects of the g-factor polygenic score (gPGS) and childhood adversity on the g-factor in the UK Biobank. We first examined the global and regional brain measures that contribute to the g-factor. Most regions contributed to the g-factor through global brain size. Parieto-frontal integration theory (P-FIT) regions were not more associated with the g-factor than non-PFIT regions. After adjusting for global brain size and regional associations, only a few regions predicted intelligence and were included in the mediation analyses. We conducted mediation analyses on global measures, regional volumes, mean thicknesses, and surface areas, separately. Total brain volume mediated 7.04% of the gPGS' effect on the g-factor and 2.50% of childhood adversity's effect on the g-factor. In comparison, the fraction of the gPGS and childhood adversity's effects mediated by individual regional volumes, surfaces, and mean thicknesses was 10-15 times smaller. Therefore, genetic and environmental effects on intelligence may be mediated to a larger extent by other brain properties.
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Affiliation(s)
- Camille M Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, 29 rue d'ulm, 75005, Paris, France
| | - Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, 29 rue d'ulm, 75005, Paris, France
- INSERM UMR 1141, Paris Diderot University, 48 Bd Sérurier, 75019, Paris, France
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, 48 Bd Sérurier, 75019, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, 29 rue d'ulm, 75005, Paris, France
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23
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Russell ER, Mackay DF, Lyall D, Stewart K, MacLean JA, Robson J, Pell JP, Stewart W. Neurodegenerative disease risk among former international rugby union players. J Neurol Neurosurg Psychiatry 2022; 93:1262-1268. [PMID: 36195436 PMCID: PMC9669247 DOI: 10.1136/jnnp-2022-329675] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 08/09/2022] [Indexed: 12/04/2022]
Abstract
BACKGROUND Autopsy studies of former contact sports athletes, including soccer and rugby players, frequently report chronic traumatic encephalopathy, a neurodegenerative pathology associated with traumatic brain injury. Nevertheless, little is known about the risk of neurodegenerative disease in these populations. We hypothesised that neurodegenerative disease risk would be higher among former elite rugby union players than the general population. METHODS We conducted a retrospective cohort study accessing national electronic records on death certification, hospital admissions and dispensed prescriptions for a cohort of 412 male Scottish former international rugby union players and 1236 members of the general population, matched to former players by age, sex and area socioeconomic status. Mortality and incident neurodegenerative disease diagnoses among former rugby players were then compared with the matched comparison group. RESULTS Over a median 32 years follow-up from study entry at age 30 years, 121 (29.4%) former rugby players and 381 (30.8%) of the matched comparison group died. All-cause mortality was lower among former rugby players until 70 years of age with no difference thereafter. During follow-up, 47 (11.4%) former rugby players and 67 (5.4%) of the comparison group were diagnosed with incident neurodegenerative disease (HR 2.67, 95% CI 1.67 to 4.27, p<0.001). CONCLUSIONS This study adds to our understanding of the association between contact sports participation and the risk of neurodegenerative disease. While further research exploring this interaction is required, in the meantime strategies to reduce exposure to head impacts and head injuries in sport should be promoted.
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Affiliation(s)
- Emma R Russell
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Daniel F Mackay
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Donald Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Katy Stewart
- Hampden Sports Clinic, Glasgow, UK.,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - John A MacLean
- Hampden Sports Clinic, Glasgow, UK.,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | | | - Jill P Pell
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - William Stewart
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK .,Department of Neuropathology, Queen Elizabeth University Hospital, Glasgow, UK
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24
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Taschler B, Smith SM, Nichols TE. Causal inference on neuroimaging data with Mendelian randomisation. Neuroimage 2022; 258:119385. [PMID: 35714886 PMCID: PMC10933777 DOI: 10.1016/j.neuroimage.2022.119385] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/30/2022] [Accepted: 06/12/2022] [Indexed: 10/18/2022] Open
Abstract
While population-scale neuroimaging studies offer the promise of discovery and characterisation of subtle risk factors, massive sample sizes increase the power for both meaningful associations and those attributable to confounds. This motivates the need for causal modelling of observational data that goes beyond statements of association and towards deeper understanding of complex relationships between individual traits and phenotypes, clinical biomarkers, genetic variation, and brain-related measures of health. Mendelian randomisation (MR) presents a way to obtain causal inference on the basis of genetic data and explicit assumptions about the relationship between genetic variables, exposure and outcome. In this work, we provide an introduction to and overview of causal inference methods based on Mendelian randomisation, with examples involving imaging-derived phenotypes from UK Biobank to make these methods accessible to neuroimaging researchers. We motivate the use of MR techniques, lay out the underlying assumptions, introduce common MR methods and focus on several scenarios in which modelling assumptions are potentially violated, resulting in biased effect estimates. Importantly, we give a detailed account of necessary steps to increase the reliability of MR results with rigorous sensitivity analyses.
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Affiliation(s)
- Bernd Taschler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Thomas E Nichols
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, City Oxford, UK
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25
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Tracy DK, Joyce DW, Albertson DN, Shergill SS. Kaleidoscope. Br J Psychiatry 2022. [PMID: 35848385 DOI: 10.1192/bjp.2022.92] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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26
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O’Nunain K, Park C, Urquijo H, Leyden GM, Hughes AD, Davey Smith G, Richardson TG. A lifecourse mendelian randomization study highlights the long-term influence of childhood body size on later life heart structure. PLoS Biol 2022; 20:e3001656. [PMID: 35679339 PMCID: PMC9182693 DOI: 10.1371/journal.pbio.3001656] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 05/03/2022] [Indexed: 12/12/2022] Open
Abstract
Children with obesity typically have larger left ventricular heart dimensions during adulthood. However, whether this is due to a persistent effect of adiposity extending into adulthood is challenging to disentangle due to confounding factors throughout the lifecourse. We conducted a multivariable mendelian randomization (MR) study to separate the independent effects of childhood and adult body size on 4 magnetic resonance imaging (MRI) measures of heart structure and function in the UK Biobank (UKB) study. Strong evidence of a genetically predicted effect of childhood body size on all measures of adulthood heart structure was identified, which remained robust upon accounting for adult body size using a multivariable MR framework (e.g., left ventricular end-diastolic volume (LVEDV), Beta = 0.33, 95% confidence interval (CI) = 0.23 to 0.43, P = 4.6 × 10−10). Sensitivity analyses did not suggest that other lifecourse measures of body composition were responsible for these effects. Conversely, evidence of a genetically predicted effect of childhood body size on various other MRI-based measures, such as fat percentage in the liver (Beta = 0.14, 95% CI = 0.05 to 0.23, P = 0.002) and pancreas (Beta = 0.21, 95% CI = 0.10 to 0.33, P = 3.9 × 10−4), attenuated upon accounting for adult body size. Our findings suggest that childhood body size has a long-term (and potentially immutable) influence on heart structure in later life. In contrast, effects of childhood body size on other measures of adulthood organ size and fat percentage evaluated in this study are likely explained by the long-term consequence of remaining overweight throughout the lifecourse. Children with obesity typically have larger left ventricular heart dimensions during adulthood, but this is challenging to disentangle due to confounding factors throughout life. This study uses Mendelian randomization to provide evidence that being overweight in early life may indeed have a long-term influence on cardiac structure.
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Affiliation(s)
- Katie O’Nunain
- Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
| | - Chloe Park
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Helena Urquijo
- Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
| | - Genevieve M. Leyden
- Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
- Bristol Medical School: Translational Health Sciences, Dorothy Hodgkin Building, University of Bristol, Bristol, United Kingdom
| | - Alun D. Hughes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - George Davey Smith
- Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
| | - Tom G. Richardson
- Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
- Novo Nordisk Research Centre, Headington, Oxford, United Kingdom
- * E-mail:
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