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Vogelezang S, Bradfield JP, Grant SFA, Felix JF, Jaddoe VWV. Genetics of early-life head circumference and genetic correlations with neurological, psychiatric and cognitive outcomes. BMC Med Genomics 2022; 15:124. [PMID: 35659227 PMCID: PMC9166310 DOI: 10.1186/s12920-022-01281-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 05/30/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Head circumference is associated with intelligence and tracks from childhood into adulthood. METHODS We performed a genome-wide association study meta-analysis and follow-up of head circumference in a total of 29,192 participants between 6 and 30 months of age. RESULTS Seven loci reached genome-wide significance in the combined discovery and replication analysis of which three loci near ARFGEF2, MYCL1, and TOP1, were novel. We observed positive genetic correlations for early-life head circumference with adult intracranial volume, years of schooling, childhood and adult intelligence, but not with adult psychiatric, neurological, or personality-related phenotypes. CONCLUSIONS The results of this study indicate that the biological processes underlying early-life head circumference overlap largely with those of adult head circumference. The associations of early-life head circumference with cognitive outcomes across the life course are partly explained by genetics.
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Affiliation(s)
- Suzanne Vogelezang
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jonathan P Bradfield
- Division of Human Genetics, Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Quantinuum Research LLC, San Diego, CA, USA
| | - Struan F A Grant
- Division of Human Genetics, Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Endocrinology and Diabetes, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
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Sinclair LI, Ball HA, Bauermeister S, Gallacher JEJ, Bolea-Alamanac BM. Recurrent depression has persistent effects on cognition but this does not appear to be mediated by neuroinflammation. J Affect Disord 2022; 306:232-239. [PMID: 35337923 DOI: 10.1016/j.jad.2022.03.043] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 03/15/2022] [Accepted: 03/17/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND Later-life depression appears to be different to depression in younger adults. The underlying pathology may also differ. Depression is linked to dementia but whether it is a risk factor or an early sign of a developing dementia remains unclear. Neuroinflammation is increasingly recognised in both depression and Alzheimer's Disease. AIMS To investigate the link between depression, inflammation and dementia. We hypothesised that recurrent depression has adverse effects on performance in cognitive tests in middle to older age and that this effect is modified by anti-inflammatory medication. METHODS We identified UK based cohort studies which included individuals aged >50, had medical information, results from detailed cognitive testing and had used reliable measures to assess depression. Individuals with recurrent depression had ≥ 2 episodes of depression. Controls had no history of depression. The presence/absence of inflammatory illness was assessed using a standardised list of inflammatory conditions. Individuals with dementia, chronic neurological and psychotic conditions were excluded. Logistic and linear regression were used to examine the effect of depression on cognitive test performance and the mediating effect of chronic inflammation. RESULTS Unexpectedly in both studies there was evidence that those with recurrent depression performed better in some cognitive tasks (e.g Mill Hill vocabulary) but worse in others (e.g. reaction time). In UK Biobank there was no evidence that anti-inflammatories moderated this effect. LIMITATIONS Cross-sectional assessment of cognition. CONCLUSIONS Although previous recurrent depression has small effects on cognitive test performance this does not appear to be mediated by chronic inflammatory disease.
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Affiliation(s)
- Lindsey I Sinclair
- Department of Clinical Neuroscience, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Harriet A Ball
- Department of Clinical Neuroscience, Bristol Medical School, University of Bristol, Bristol, UK
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Song Z, Li WD, Li H, Zhang X, Wang N, Fan Q. Genetic basis of job attainment characteristics and the genetic sharing with other SES indices and well-being. Sci Rep 2022; 12:8902. [PMID: 35618877 PMCID: PMC9135765 DOI: 10.1038/s41598-022-12905-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 04/07/2022] [Indexed: 12/29/2022] Open
Abstract
Job attainment is an important component of socioeconomic status (SES). There is currently a paucity of genomic research on an individual's job attainment, as well as how it is related to other SES variables and overall well-being at the whole genome level. By incorporating O*NET occupational information into the UK Biobank database, we performed GWAS analyses of six major job attainment characteristics-job complexity, autonomy, innovation, information demands, emotional demands, and physical demands-on 219,483 individuals of European ancestry. The job attainment characteristics had moderate to high pairwise genetic correlations, manifested by three latent factors: cognitive, emotional, and physical requirements. The latent factor of overall job requirement underlying the job attainment traits represented a critical genetic path from educational attainment to income (P < 0.001). Job attainment characteristics were genetically positively correlated with positive health and well-being outcomes (i.e., subject well-being, overall health rating, number of non-cancer illnesses etc. (|rg|: 0.14-0.51), similar to other SES indices; however, the genetic correlations exhibited opposite directions for physical demands (|rg|: 0.14-0.51) and were largely negligible for emotional demands. By adopting a finer-grained approach to capture specific job attainment phenotypes, our study represents an important step forward in understanding the shared genetic architecture among job attainment characteristics, other SES indices, and potential role in health and well-being outcomes.
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Affiliation(s)
- Zhaoli Song
- Department of Management and Organization, National University of Singapore, Singapore, Singapore.
| | - Wen-Dong Li
- Department of Management, The Chinese University of Hong Kong, Hong Kong, China
| | - Hengtong Li
- Department of Statistics and Data Science, National University of Singapore, Singapore, Singapore
| | - Xin Zhang
- Department of Management, The Chinese University of Hong Kong, Hong Kong, China
| | - Nan Wang
- Department of Management, Lingnan University, Hong Kong, China
| | - Qiao Fan
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
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Poeppl TB, Dimas E, Sakreida K, Kernbach JM, Markello RD, Schöffski O, Dagher A, Koellinger P, Nave G, Farah MJ, Mišić B, Bzdok D. Pattern learning reveals brain asymmetry to be linked to socioeconomic status. Cereb Cortex Commun 2022; 3:tgac020. [PMID: 35702547 PMCID: PMC9188625 DOI: 10.1093/texcom/tgac020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 05/13/2022] [Accepted: 05/15/2022] [Indexed: 11/16/2022] Open
Abstract
Socioeconomic status (SES) anchors individuals in their social network layers. Our embedding in the societal fabric resonates with habitus, world view, opportunity, and health disparity. It remains obscure how distinct facets of SES are reflected in the architecture of the central nervous system. Here, we capitalized on multivariate multi-output learning algorithms to explore possible imprints of SES in gray and white matter structure in the wider population (n ≈ 10,000 UK Biobank participants). Individuals with higher SES, compared with those with lower SES, showed a pattern of increased region volumes in the left brain and decreased region volumes in the right brain. The analogous lateralization pattern emerged for the fiber structure of anatomical white matter tracts. Our multimodal findings suggest hemispheric asymmetry as an SES-related brain signature, which was consistent across six different indicators of SES: degree, education, income, job, neighborhood and vehicle count. Hence, hemispheric specialization may have evolved in human primates in a way that reveals crucial links to SES.
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Affiliation(s)
- Timm B Poeppl
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Department of Health Management, School of Business, Economics and Society, Friedrich-Alexander-Universität Erlangen-Nürnberg, Nürnberg, Germany
| | - Emile Dimas
- Department of Biomedical Engineering, McConnell Brain Imaging Center (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, School of Computer Science, McGill University, Montreal, Quebec, Canada
| | - Katrin Sakreida
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Julius M Kernbach
- Department of Neurosurgery, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Ross D Markello
- McConnell Brain Imaging Center (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Oliver Schöffski
- Department of Health Management, School of Business, Economics and Society, Friedrich-Alexander-Universität Erlangen-Nürnberg, Nürnberg, Germany
| | - Alain Dagher
- Montreal Neurological Institute (MNI), McGill University, Montreal, Quebec, Canada
| | - Philipp Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Gideon Nave
- Marketing Department, The Wharton School, University of Pennsylvania, Philadelphia, United States of America
| | - Martha J Farah
- Center for Neuroscience & Society, University of Pennsylvania, Philadelphia, United States of America
| | - Bratislav Mišić
- McConnell Brain Imaging Center (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Danilo Bzdok
- Department of Biomedical Engineering, McConnell Brain Imaging Center (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, School of Computer Science, McGill University, Montreal, Quebec, Canada
- Mila – Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada
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The Potential of Polygenic Risk Scores to Predict Antidepressant Treatment Response in Major Depression: A Systematic Review. J Affect Disord 2022; 304:1-11. [PMID: 35151671 DOI: 10.1016/j.jad.2022.02.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 12/29/2021] [Accepted: 02/09/2022] [Indexed: 12/28/2022]
Abstract
BACKGROUND Understanding the genetic underpinnings of antidepressant treatment response in unipolar major depressive disorder (MDD) can be useful in identifying patients at risk for poor treatment response or treatment resistant depression. A polygenic risk score (PRS) is a useful tool to explore genetic liability of a complex trait such as antidepressant treatment response. Here, we review studies that use PRSs to examine genetic overlap between any trait and antidepressant treatment response in unipolar MDD. METHODS A systematic search of literature was conducted in PubMed, Embase, and PsycINFO. Our search included studies examining associations between PRSs of psychiatric as well as non-psychiatric traits and antidepressant treatment response in patients with unipolar MDD. A quality assessment of the included studies was performed. RESULTS In total, eleven articles were included which contained PRSs for 30 traits. Studies varied in sample size and endpoints used for antidepressant treatment response. Overall, PRSs for attention-deficit hyperactivity disorder, the personality trait openness, coronary artery disease, obesity, and stroke have been associated with antidepressant treatment response in patients with unipolar MDD. LIMITATIONS The endpoints used by included studies differed significantly, therefore it was not possible to perform a meta-analysis. CONCLUSIONS Associations between a PRS and antidepressant treatment response have been reported for a number of traits in patients with unipolar MDD. PRSs could be informative to predict antidepressant treatment response in this population, given advances in the field. Most importantly, there is a need for larger study cohorts and the use of standardized outcome measures.
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Zhang ZQ, Yang MH, Guo ZP, Liao D, Sörös P, Li M, Walter M, Wang L, Liu CH. Increased prefrontal cortex connectivity associated with depression vulnerability and relapse. J Affect Disord 2022; 304:133-141. [PMID: 35219743 DOI: 10.1016/j.jad.2022.02.059] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 01/28/2022] [Accepted: 02/20/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) is a highly prevalent mood disorder, characterized by depressed mood, reduced capabilities to concentrate, impaired cognition, as well as a high risk of relapse. Unaffected siblings who have high risks for MDD development and yet without clinical symptoms may be helpful for understanding the neural mechanisms of MDD traits. METHODS We investigated both regional fluctuation and inter-regional synchronization in 31 fully remitted MDD patients, 29 unaffected siblings and 43 age, gender, and educational level matched helathy controls (HCs) using resting-state functional magnetic resonance imaging (rs-fMRI). The 17-item HAMD and neurocognitive scales were performed. Fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC) strength were investigated. RESULTS Compared with healthy control group, patients with remitted MDD and unaffected siblings showed increased fALFF in the left dorsomedial prefrontal cortex (dmPFC) and increased FC between the left dmPFC and the right ventromedial prefrontal cortex (vmPFC). In addition, a negative correlation was observed between the fALFF value in the left dmPFC and the speed of Trail Making Test in the remitted MDD patients. Higher vmPFC-dmPFC FC was positively correlated with Wisconsin Card Sorting Test (WCST) total correct, and negatively correlated with WCST random errors. CONCLUSIONS In the absence of clinical symptoms, individuals with remitted MDD and unaffected siblings showed increased fALFF in left dmPFC as well as the vmPFC-dmPFC connectivity. These results suggest a specific trait abnormality in the default mode network associated with vulnerability to MDD, which may have implications for developing effective therapies using this network as a target.
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Affiliation(s)
- Zhu-Qing Zhang
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China; Beijing Institute of Chinese Medicine, Beijing 100010, China
| | - Ming-Hao Yang
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China; Beijing Institute of Chinese Medicine, Beijing 100010, China
| | - Zhi-Peng Guo
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China; Beijing Institute of Chinese Medicine, Beijing 100010, China
| | - Dan Liao
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China; Beijing Institute of Chinese Medicine, Beijing 100010, China
| | - Peter Sörös
- Research Center Neurosensory Science, Carl von Ossietzky University of Oldenburg, Oldenburg 26129, Germany
| | - Meng Li
- Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg 39120, Germany; Department of Psychiatry and Psychotherapy, University Tuebingen, Tuebingen 72074, Germany; Department of Psychiatry and Psychotherapy, University Hospital Jena, Philosophenweg 3, 07743 Jena, Germany
| | - Martin Walter
- Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg 39120, Germany; Department of Psychiatry and Psychotherapy, University Tuebingen, Tuebingen 72074, Germany; Leibniz Institute for Neurobiology, Magdeburg 39118, Germany; Department of Psychiatry and Psychotherapy, University Hospital Jena, Philosophenweg 3, 07743 Jena, Germany
| | - Lihong Wang
- Department of Psychiatry, University of Connecticut Health Center, Farmington, CT 06030, USA.
| | - Chun-Hong Liu
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China; Beijing Institute of Chinese Medicine, Beijing 100010, China.
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Richard EL, McEvoy LK, Deary IJ, Davies G, Cao SY, Oren E, Alcaraz JE, LaCroix AZ, Bressler J, Salem RM. Markers of kidney function, genetic variation related to cognitive function, and cognitive performance in the UK Biobank. BMC Nephrol 2022; 23:159. [PMID: 35477353 PMCID: PMC9047316 DOI: 10.1186/s12882-022-02750-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 03/11/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Chronic kidney disease has been linked to worse cognition. However, this association may be dependent on the marker of kidney function used, and studies assessing modification by genetics are lacking. This study examined associations between multiple measures of kidney function and assessed effect modification by a polygenic score for general cognitive function. METHODS In this cross-sectional study of up to 341,208 European ancestry participants from the UK Biobank study, we examined associations between albuminuria and estimated glomerular filtration rate based on creatinine (eGFRcre) or cystatin C (eGFRcys) with cognitive performance on tests of verbal-numeric reasoning, reaction time and visual memory. Adjustment for confounding factors was performed using multivariate regression and propensity-score matching. Interaction between kidney function markers and a polygenic risk score for general cognitive function was also assessed. RESULTS Albuminuria was associated with worse performance on tasks of verbal-numeric reasoning (β(points) = -0.09, p < 0.001), reaction time (β(milliseconds) = 7.06, p < 0.001) and visual memory (β(log errors) = 0.013, p = 0.01). A polygenic score for cognitive function modified the association between albuminuria and verbal-numeric reasoning with significantly lower scores in those with albuminuria and a lower polygenic score (p = 0.009). Compared to participants with eGFRcre ≥ 60 ml/min, those with eGFRcre < 60 ml/min had lower verbal-numeric reasoning scores and slower mean reaction times (verbal numeric reasoning β = -0.11, p < 0.001 and reaction time β = 6.08, p < 0.001 for eGFRcre < 60 vs eGFRcre ≥ 60). Associations were stronger using cystatin C-based eGFR than creatinine-based eGFR (verbal numeric reasoning β = -0.21, p < 0.001 and reaction time β = 11.21, p < 0.001 for eGFRcys < 60 vs eGFRcys ≥ 60). CONCLUSIONS Increased urine albumin is associated with worse cognition, but this may depend on genetic risk. Cystatin C-based eGFR may better predict cognitive performance than creatinine-based estimates.
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Affiliation(s)
- Erin L Richard
- Department of Family Medicine and Public Health, University of California San Diego, 9500 Gilman Dr, La Jolla, San Diego, CA, USA
- Department of Family Medicine and Public Health, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, School of Medicine, 9500 Gilman Dr, La Jolla, CA, 92093-0841, San Diego, USA
| | - Linda K McEvoy
- Department of Family Medicine and Public Health, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, School of Medicine, 9500 Gilman Dr, La Jolla, CA, 92093-0841, San Diego, USA
- Department of Radiology, University of California San Diego, 9500 Gilman Dr, La Jolla, San Diego, CA, USA
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Steven Y Cao
- Department of Family Medicine and Public Health, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, School of Medicine, 9500 Gilman Dr, La Jolla, CA, 92093-0841, San Diego, USA
| | - Eyal Oren
- Graduate School of Public Health, San Diego State University, 5500 Campanile Dr, San Diego, CA, USA
| | - John E Alcaraz
- Graduate School of Public Health, San Diego State University, 5500 Campanile Dr, San Diego, CA, USA
| | - Andrea Z LaCroix
- Department of Family Medicine and Public Health, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, School of Medicine, 9500 Gilman Dr, La Jolla, CA, 92093-0841, San Diego, USA
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, School of Public Health, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Rany M Salem
- Department of Family Medicine and Public Health, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, School of Medicine, 9500 Gilman Dr, La Jolla, CA, 92093-0841, San Diego, USA.
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Raisi-Estabragh Z, M'Charrak A, McCracken C, Biasiolli L, Ardissino M, Curtis EM, Aung N, Suemoto CK, Mackay C, Suri S, Nichols TE, Harvey NC, Petersen SE, Neubauer S. Associations of cognitive performance with cardiovascular magnetic resonance phenotypes in the UK Biobank. Eur Heart J Cardiovasc Imaging 2022; 23:663-672. [PMID: 33987659 PMCID: PMC9016359 DOI: 10.1093/ehjci/jeab075] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 04/07/2021] [Indexed: 01/22/2023] Open
Abstract
AIMS Existing evidence suggests links between brain and cardiovascular health. We investigated associations between cognitive performance and cardiovascular magnetic resonance (CMR) phenotypes in the UK Biobank, considering a range of potential confounders. METHODS AND RESULTS We studied 29 763 participants with CMR and cognitive testing, specifically, fluid intelligence (FI, 13 verbal-numeric reasoning questions), and reaction time (RT, a timed pairs matching exercise); both were considered continuous variables for modelling. We included the following CMR metrics: left and right ventricular (LV and RV) volumes in end-diastole and end-systole, LV/RV ejection fractions, LV/RV stroke volumes, LV mass, and aortic distensibility. Multivariable linear regression models were used to estimate the association of each CMR measure with FI and RT, adjusting for age, sex, smoking, education, deprivation, diabetes, hypertension, high cholesterol, prior myocardial infarction, alcohol intake, and exercise level. We report standardized beta-coefficients, 95% confidence intervals, and P-values adjusted for multiple testing. In this predominantly healthy cohort (average age 63.0 ± 7.5 years), better cognitive performance (higher FI, lower RT) was associated with larger LV/RV volumes, higher LV/RV stroke volumes, greater LV mass, and greater aortic distensibility in fully adjusted models. There was some evidence of non-linearity in the relationship between FI and LV end-systolic volume, with reversal of the direction of association at very high volumes. Associations were consistent for men and women and in different ages. CONCLUSION Better cognitive performance is associated with CMR measures likely representing a healthier cardiovascular phenotype. These relationships remained significant after adjustment for a range of cardiometabolic, lifestyle, and demographic factors, suggesting possible involvement of alternative disease mechanisms.
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Affiliation(s)
- Zahra Raisi-Estabragh
- Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London EC1A 7BE, UK
| | - Amine M'Charrak
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Celeste McCracken
- Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Luca Biasiolli
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | | | - Elizabeth M Curtis
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Nay Aung
- Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London EC1A 7BE, UK
| | - Claudia K Suemoto
- Division of Geriatrics, Department of Internal Medicine, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Clare Mackay
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Thomas E Nichols
- Nuffield Department of Population Health, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, Oxford OX3 9DU, UK
| | - Nicholas C Harvey
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Steffen E Petersen
- Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London EC1A 7BE, UK
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
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Fu X, Yao T, Chen X, Li H, Wu J. MEF2C gene variations are associated with ADHD in the Chinese Han population: a case-control study. J Neural Transm (Vienna) 2022; 129:431-439. [PMID: 35357565 DOI: 10.1007/s00702-022-02490-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 03/12/2022] [Indexed: 11/30/2022]
Abstract
Myocyte enhancer factor 2C (MEF2C) is associated with hyperactivity and might be a novel risk gene for susceptibility to attention deficit hyperactivity disorder (ADHD). Therefore, this study aimed to explore the association between MEF2C genetic variants and ADHD in the Chinese Han population. A total of 215 patients with ADHD and 233 controls were recruited for this study. The Swanson, Nolan, and Pelham version IV questionnaire was used to evaluate the clinical features of ADHD. In silico analysis was used to annotate the biological functions of the promising single nucleotide polymorphisms. Our findings indicated that MEF2C rs587490 was significantly associated with ADHD in the multiplicative model (OR = 0.640, p = 0.002). Participants with the rs587490 TT allele exhibited less hyperactivity/impulsivity than those with the rs587490 CC allele. Furthermore, the expression quantitative trait loci analysis suggested that rs587490 could regulate the gene expression of MEF2C in the hippocampus, putamen, thalamus, and frontal white matter. Our study concluded that the MEF2C rs587490 T allele is significantly associated with a reduced risk of ADHD in the Chinese Han population, which provides new insight into the genetic etiology of ADHD.
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Affiliation(s)
- Xihang Fu
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13, Hangkong Road, Wuhan, 430030, Hubei, People's Republic of China
| | - Ting Yao
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13, Hangkong Road, Wuhan, 430030, Hubei, People's Republic of China
| | - Xinzhen Chen
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13, Hangkong Road, Wuhan, 430030, Hubei, People's Republic of China
| | - Huiru Li
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13, Hangkong Road, Wuhan, 430030, Hubei, People's Republic of China
| | - Jing Wu
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13, Hangkong Road, Wuhan, 430030, Hubei, People's Republic of China.
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Two neuroanatomical subtypes of males with autism spectrum disorder revealed using semi-supervised machine learning. Mol Autism 2022; 13:9. [PMID: 35197121 PMCID: PMC8867630 DOI: 10.1186/s13229-022-00489-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 02/10/2022] [Indexed: 11/14/2022] Open
Abstract
Background Clinical and etiological varieties remain major obstacles to decompose heterogeneity in autism spectrum disorders (ASD). Recently, neuroimaging raised new hope to identify neurosubtypes of ASD for further understanding the biological mechanisms behind the disorder. Methods In this study, brain structural MRI data and clinical measures of 221 male subjects with ASD and 257 healthy controls were selected from 7 independent sites from the Autism Brain Image Data Exchange database (ABIDE). Heterogeneity through discriminative analysis (HYDRA), a recently-proposed semi-supervised clustering method was utilized to divide individuals with ASD into several neurosubtypes by regional volumetric measures of gray matter, white matter, and cerebrospinal fluid. Voxel-wise volume, clinical measures, dynamic resting-state functional magnetic resonance imaging (R-fMRI) measures among different neurosubtypes of ASD were explored. In addition, support vector machine (SVM) model was applied to test whether the neurosubtyping of ASD could improve diagnostic accuracy of ASD. Results Two neurosubtypes of ASD with different voxel-wise volumetric patterns were revealed. The full-scale intelligence quotient (IQ), verbal IQ, Autism Diagnostic Observation Schedule (ADOS) total scores and ADOS severity scores were significantly different between the two neurosubtypes, the total intracranial volume was correlated with performance IQ in Subtype 1 and was correlated with ADOS communication score and ADOS social score in Subtype 2. Compared with Subtype 2, Subtype 1 showed lower dynamic R-fMRI measures, lower dynamic functional architecture stability, higher mean and lower standard deviation (SD) of concordance among dynamic R-fMRI measures in cerebellum. In addition, classification accuracies between ASD neurosubtypes and healthy controls were significantly improved compared with classification accuracy between entire ASD group and healthy controls. Limitations The present study excluded female subjects and left-handed subjects, which limited the ability to investigate the associations between these factors and the heterogeneity of ASD. Conclusions The two distinct neuroanatomical subtypes of ASD validated by other data modalities not only adds reliability of the result, but also bridges from brain phenomenology to clinical behavior. The current neurosubtypes of ASD could facilitate understanding the neuropathology of this disorder and could be potentially used to improve clinical decision-making process and optimize treatment. Supplementary Information The online version contains supplementary material available at 10.1186/s13229-022-00489-3.
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Charney E. The "Golden Age" of Behavior Genetics? PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2022; 17:1188-1210. [PMID: 35180032 DOI: 10.1177/17456916211041602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The search for genetic risk factors underlying the presumed heritability of all human behavior has unfolded in two phases. The first phase, characterized by candidate-gene-association (CGA) studies, has fallen out of favor in the behavior-genetics community, so much so that it has been referred to as a "cautionary tale." The second and current iteration is characterized by genome-wide association studies (GWASs), single-nucleotide polymorphism (SNP) heritability estimates, and polygenic risk scores. This research is guided by the resurrection of, or reemphasis on, Fisher's "infinite infinitesimal allele" model of the heritability of complex phenotypes, first proposed over 100 years ago. Despite seemingly significant differences between the two iterations, they are united in viewing the discovery of risk alleles underlying heritability as a matter of finding differences in allele frequencies. Many of the infirmities that beset CGA studies persist in the era of GWASs, accompanied by a host of new difficulties due to the human genome's underlying complexities and the limitations of Fisher's model in the postgenomics era.
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Affiliation(s)
- Evan Charney
- The Samuel DuBois Cook Center on Social Equity, Duke University
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62
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Thalamuthu A, Mills NT, Berger K, Minnerup H, Grotegerd D, Dannlowski U, Meinert S, Opel N, Repple J, Gruber M, Nenadić I, Stein F, Brosch K, Meller T, Pfarr JK, Forstner AJ, Hoffmann P, Nöthen MM, Witt S, Rietschel M, Kircher T, Adams M, McIntosh AM, Porteous DJ, Deary IJ, Hayward C, Campbell A, Grabe HJ, Teumer A, Homuth G, van der Auwera-Palitschka S, Schubert KO, Baune BT. Genome-wide interaction study with major depression identifies novel variants associated with cognitive function. Mol Psychiatry 2022; 27:1111-1119. [PMID: 34782712 PMCID: PMC7612684 DOI: 10.1038/s41380-021-01379-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 10/08/2021] [Accepted: 10/26/2021] [Indexed: 12/13/2022]
Abstract
Major Depressive Disorder (MDD) often is associated with significant cognitive dysfunction. We conducted a meta-analysis of genome-wide interaction of MDD and cognitive function using data from four large European cohorts in a total of 3510 MDD cases and 6057 controls. In addition, we conducted analyses using polygenic risk scores (PRS) based on data from the Psychiatric Genomics Consortium (PGC) on the traits of MDD, Bipolar disorder (BD), Schizophrenia (SCZ), and mood instability (MIN). Functional exploration contained gene expression analyses and Ingenuity Pathway Analysis (IPA®). We identified a set of significantly interacting single nucleotide polymorphisms (SNPs) between MDD and the genome-wide association study (GWAS) of cognitive domains of executive function, processing speed, and global cognition. Several of these SNPs are located in genes expressed in brain, with important roles such as neuronal development (REST), oligodendrocyte maturation (TNFRSF21), and myelination (ARFGEF1). IPA® identified a set of core genes from our dataset that mapped to a wide range of canonical pathways and biological functions (MPO, FOXO1, PDE3A, TSLP, NLRP9, ADAMTS5, ROBO1, REST). Furthermore, IPA® identified upstream regulator molecules and causal networks impacting on the expression of dataset genes, providing a genetic basis for further clinical exploration (vitamin D receptor, beta-estradiol, tadalafil). PRS of MIN and meta-PRS of MDD, MIN and SCZ were significantly associated with all cognitive domains. Our results suggest several genes involved in physiological processes for the development and maintenance of cognition in MDD, as well as potential novel therapeutic agents that could be explored in patients with MDD associated cognitive dysfunction.
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Affiliation(s)
- Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Natalie T Mills
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Heike Minnerup
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg - UKGM Marburg, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg - UKGM Marburg, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg - UKGM Marburg, Marburg, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg - UKGM Marburg, Marburg, Germany
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg - UKGM Marburg, Marburg, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Stephanie Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Faculty of Medicine Mannheim, University of Heidelberg, Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Faculty of Medicine Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg - UKGM Marburg, Marburg, Germany
| | - Mark Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | | | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Hans Jörgen Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Sandra van der Auwera-Palitschka
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - K Oliver Schubert
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
- Northern Adelaide Mental Health Service, Salisbury, SA, Australia
| | - Bernhard T Baune
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia.
- Department of Psychiatry and Psychotherapy, University Hospital Münster, University of Münster, Münster, Germany.
- Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia.
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia.
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Dutton E, Madison G. "Blessed are the Nations with High Levels of Schizophrenia": National Level Schizophrenia Prevalence and Its Relationship with National Levels of Religiosity. JOURNAL OF RELIGION AND HEALTH 2022; 61:6-22. [PMID: 34338953 PMCID: PMC8837564 DOI: 10.1007/s10943-021-01353-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/16/2021] [Indexed: 06/13/2023]
Abstract
Schizophrenia is correlated with religious delusions but, heretofore, the relationship between schizophrenia prevalence and religiosity has not been explored at the national level. Examining this relationship, we find that national level schizophrenia prevalence is correlated with national level religiosity and strongly negatively correlated with national level atheism across 125 countries. When controlling for cognitive performance and economic development in multiple regression analyses, the proportion of the variance explained was 2.9% (p < .005) for Religiousness and 5.1% for Atheism (p < .00005). Alternative causal interpretations of this association are discussed.
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Affiliation(s)
| | - Guy Madison
- Department of Psychology, Umeå University, Umeå, Sweden.
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Peters R, Breitner J, James S, Jicha GA, Meyer P, Richards M, Smith AD, Yassine HN, Abner E, Hainsworth AH, Kehoe PG, Beckett N, Weber C, Anderson C, Anstey KJ, Dodge HH. Dementia risk reduction: why haven't the pharmacological risk reduction trials worked? An in-depth exploration of seven established risk factors. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2021; 7:e12202. [PMID: 34934803 PMCID: PMC8655351 DOI: 10.1002/trc2.12202] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 06/03/2021] [Accepted: 06/18/2021] [Indexed: 12/21/2022]
Abstract
Identifying the leading health and lifestyle factors for the risk of incident dementia and Alzheimer's disease has yet to translate to risk reduction. To understand why, we examined the discrepancies between observational and clinical trial evidence for seven modifiable risk factors: type 2 diabetes, dyslipidemia, hypertension, estrogens, inflammation, omega-3 fatty acids, and hyperhomocysteinemia. Sample heterogeneity and paucity of intervention details (dose, timing, formulation) were common themes. Epidemiological evidence is more mature for some interventions (eg, non-steroidal anti-inflammatory drugs [NSAIDs]) than others. Trial data are promising for anti-hypertensives and B vitamin supplementation. Taken together, these risk factors highlight a future need for more targeted sample selection in clinical trials, a better understanding of interventions, and deeper analysis of existing data.
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Affiliation(s)
- Ruth Peters
- Neuroscience ResearchSydneyNew South WalesAustralia
- Department of Psychology University of New South WalesSydneyNew South WalesAustralia
| | - John Breitner
- Douglas Hospital Research Center and McGill UniversityQuebecCanada
| | - Sarah James
- MRC Unit for Lifelong Health and Ageing at UCLUniversity College LondonLondonUK
| | | | - Pierre‐Francois Meyer
- Center for Studies on the Prevention of Alzheimer's Disease (PREVENT‐AD)VerdunQuebecCanada
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCLUniversity College LondonLondonUK
| | - A. David Smith
- OPTIMADepartment of PharmacologyUniversity of OxfordOxfordUK
| | - Hussein N. Yassine
- Departments of Medicine and NeurologyUniversity of Southern CaliforniaCaliforniaUSA
| | - Erin Abner
- University of KentuckyLexingtonKentuckyUSA
| | - Atticus H. Hainsworth
- Molecular and Clinical Sciences Research InstituteSt GeorgesUniversity of LondonLondonUK
- Department of NeurologySt George's HospitalLondonUK
| | | | | | | | - Craig Anderson
- The George Institute for Global HealthSydneyNew South WalesAustralia
| | - Kaarin J. Anstey
- Neuroscience ResearchSydneyNew South WalesAustralia
- Department of Psychology University of New South WalesSydneyNew South WalesAustralia
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Richard EL, McEvoy LK, Cao SY, Oren E, Alcaraz JE, LaCroix AZ, Salem RM. Biomarkers of kidney function and cognitive ability: A Mendelian randomization study. J Neurol Sci 2021; 430:118071. [PMID: 34534883 PMCID: PMC8635776 DOI: 10.1016/j.jns.2021.118071] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 08/28/2021] [Accepted: 09/04/2021] [Indexed: 02/04/2023]
Abstract
BACKGROUND Estimated glomerular filtration rate (eGFR), albuminuria and serum uric acid (SUA) are markers of kidney function that have been associated with cognitive ability. However, whether these associations are causal is unclear. METHODS We performed one-sample Mendelian randomization (MR) to estimate the effects of kidney function markers on cognitive performance using data from the UK Biobank. Polygenic scores for SUA, urine albumin to creatinine ratio (ACR), estimated glomerular filtration rate based on serum creatinine (eGFRcre) and serum cystatin C (eGFRcys) were used as instrumental variables, and cognitive function outcomes included tests of verbal-numeric reasoning, reaction time, visual memory, and numeric memory. RESULTS We found no evidence of a causal effect of genetically determined SUA, eGFRcre or eGFRcys on cognitive function outcomes. There was no association between a polygenic score for ACR and verbal-numeric reasoning or numeric memory. However, there was suggestive evidence of a relationship between genetically increased ACR and slower reaction time and worse visual memory. ACR was no longer significantly associated with visual memory in analyses using an unweighted polygenic score and in analyses stratified by sex and age category. Pleiotropy adjusted estimates were directionally consistent with those of the principal analysis but overlapped with the null. CONCLUSIONS This MR study does not support causal effects of SUA, eGFRcre or eGFRcys on cognitive performance. Genetically increased ACR was associated with slower processing speed and visual memory, but results need confirmation in independent samples.
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Affiliation(s)
- Erin L Richard
- Department of Family Medicine and Public Health, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA; Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA.
| | - Linda K McEvoy
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA; Department of Radiology, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA
| | - Steven Y Cao
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA
| | - Eyal Oren
- Graduate School of Public Health, San Diego State University, 5500 Campanile Dr, San Diego, CA, USA
| | - John E Alcaraz
- Graduate School of Public Health, San Diego State University, 5500 Campanile Dr, San Diego, CA, USA
| | - Andrea Z LaCroix
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA
| | - Rany M Salem
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA
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66
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Ferri F, Deschênes SS, Power N, Schmitz N. Association between depressive symptoms, metabolic risk factors, and cognitive function: cross-sectional results from a community study in Quebec, Canada. Aging Ment Health 2021; 25:2003-2010. [PMID: 32662305 DOI: 10.1080/13607863.2020.1792412] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To investigate the cross-sectional association between depressive symptoms and metabolic risk factors with cognitive function in a middle-aged population. METHODS A stratified subsample of the CARTaGENE (CaG) cohort (n = 1991) was used to compare cognitive function outcomes between groups. The stratification was based on the presence of depressive symptoms and metabolic dysregulation (MetD): the presence of a) neither condition (reference group); b) MetD only; c) depressive symptoms only; and d) both depressive symptoms and MetD. Individuals with type 2 diabetes were excluded. Three cognitive domains were assessed: processing speed, episodic memory, and executive function. An overall cognitive function score, standardized for age and education, was computed. Poor cognitive function was defined as the lower quartile of the overall cognitive function distribution. Linear and logistic regression analyses were conducted. RESULTS The poorest cognitive performance was observed in the group with both depressive symptoms and MetD, followed by the group with depressive symptoms only, then the group with MetD only and the reference group. Mean (SD) overall cognition scores for the four groups were -0.25 (1.13), -0.13 (1.05), 0.11 (0.90), and 0.15 (0.93), respectively. Linear regression analyses suggested a linear increase in cognitive function across groups.In the logistic regression analyses, the highest risk of poor cognitive function was observed in the comorbid (depressive symptoms and MetD) group (adjusted OR = 1.99, 95% CI 1.46, 2.71). CONCLUSION Comorbidity of depressive symptoms and MetD was associated with reduced cognitive performance in middle-aged adults without diabetes.KEY POINTSPoor cognitive function is a major public health concern and can be potentially prevented by targeting its modifiable risk factors.Metabolic dysregulation and depression have both been independently associated with poor cognitive function.Comorbidity of metabolic dysregulation and depressive symptoms is associated with an increased risk of poor cognitive function in middle-aged individuals.Future health interventions might benefit by screening for comorbidity in patients with poor cognitive function and by targeting depression and metabolic dysregulation together.
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Affiliation(s)
- Floriana Ferri
- Department of Psychiatry, McGill University, Montreal, Canada.,Douglas Research Centre, Montreal, Canada
| | - Sonya S Deschênes
- Department of Psychiatry, McGill University, Montreal, Canada.,Douglas Research Centre, Montreal, Canada.,UCD School of Psychology, University College Dublin, Dublin, Ireland
| | - Niamh Power
- Department of Psychiatry, McGill University, Montreal, Canada.,Douglas Research Centre, Montreal, Canada
| | - Norbert Schmitz
- Department of Psychiatry, McGill University, Montreal, Canada.,Douglas Research Centre, Montreal, Canada.,Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Canada.,Montreal Diabetes Research Centre, Montréal, Canada
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Waddington F, Franke B, Hartman C, Buitelaar JK, Rommelse N, Mota NR. A polygenic risk score analysis of ASD and ADHD across emotion recognition subtypes. Am J Med Genet B Neuropsychiatr Genet 2021; 186:401-411. [PMID: 32815639 PMCID: PMC9290011 DOI: 10.1002/ajmg.b.32818] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 04/06/2020] [Accepted: 07/29/2020] [Indexed: 11/17/2022]
Abstract
This study investigated the genetic components of ADHD and ASD by examining the cross-disorder trait of emotion recognition problems. The genetic burden for ADHD and ASD on previously identified emotion recognition factors (speed and accuracy of visual and auditory emotion recognition) and classes (Class 1: Average visual, impulsive auditory; Class 2: Average-strong visual & auditory; Class 3: Impulsive & imprecise visual, average auditory; Class 4: Weak visual & auditory) was assessed using ASD and ADHD polygenic risk scores (PRS). Our sample contained 552 participants: 74 with ADHD, 85 with ASD, 60 with ASD + ADHD, 177 unaffected siblings of ADHD or ASD probands, and 156 controls. ADHD- and ASD-PRS, calculated from the latest ADHD and ASD GWAS meta-analyses, were analyzed across these emotion recognition factors and classes using linear mixed models. Unexpectedly, the analysis of emotion recognition factors showed higher ASD-PRS to be associated with faster visual emotion recognition. The categorical analysis of emotion recognition classes showed ASD-PRS to be reduced in Class 3 compared to the other classes (p value threshold [pT] = 1, p = .021). A dimensional analysis identified a high ADHD-PRS reduced the probability of being assigned to the Class 1 or Class 3 (pT = .05, p = .028 and p = .044, respectively). Though these nominally significant results did not pass FDR correction, they potentially indicate different indirect causative chains from genetics via emotion recognition to ADHD and ASD, which need to be verified in future research.
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Affiliation(s)
- Francesca Waddington
- Department of Human Genetics, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CenterNijmegenNetherlands,Donders Institute for Brain, Cognition and Behaviour, Centre for Medical NeuroscienceRadboud UniversityNijmegenNetherlands
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CenterNijmegenNetherlands,Donders Institute for Brain, Cognition and Behaviour, Centre for Medical NeuroscienceRadboud UniversityNijmegenNetherlands,Department of Psychiatry, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CenterNijmegenNetherlands
| | - Catharina Hartman
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University Medical Center GroningenUniversity of GroningenGroningenNetherlands
| | - Jan K. Buitelaar
- Donders Institute for Brain, Cognition and Behaviour, Centre for Medical NeuroscienceRadboud UniversityNijmegenNetherlands,Karakter Child and Adolescent Psychiatry University CentreNijmegenNetherlands,Department of Cognitive NeuroscienceRadboud University Medical CenterNijmegenNetherlands
| | - Nanda Rommelse
- Donders Institute for Brain, Cognition and Behaviour, Centre for Medical NeuroscienceRadboud UniversityNijmegenNetherlands,Department of Psychiatry, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CenterNijmegenNetherlands,Karakter Child and Adolescent Psychiatry University CentreNijmegenNetherlands
| | - Nina Roth Mota
- Department of Human Genetics, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CenterNijmegenNetherlands,Donders Institute for Brain, Cognition and Behaviour, Centre for Medical NeuroscienceRadboud UniversityNijmegenNetherlands
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Sewell MDE, Jiménez-Sánchez L, Shen X, Edmondson-Stait AJ, Green C, Adams MJ, Rifai OM, McIntosh AM, Lyall DM, Whalley HC, Lawrie SM. Associations between major psychiatric disorder polygenic risk scores and blood-based markers in UK biobank. Brain Behav Immun 2021; 97:32-41. [PMID: 34107350 DOI: 10.1016/j.bbi.2021.06.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 05/16/2021] [Accepted: 06/04/2021] [Indexed: 01/08/2023] Open
Abstract
Major depressive disorder (MDD), schizophrenia (SCZ), and bipolar disorder (BD) have both shared and discrete genetic risk factors, and are associated with peripheral abnormalities. The relationships between such genetic architectures and blood-based markers are, however, unclear. We investigated relationships between polygenic risk scores (PRS) for these disorders and peripheral markers in the UK Biobank cohort. We calculated polygenic risk scores for n = 367,329 (MDD PRS), n = 366,465 (SCZ PRS), and n = 366,383 (BD PRS) UK Biobank cohort subjects. We then examined associations between disorder PRS and 58 inflammatory/immune, hematological, bone, cardiovascular, hormone, liver, renal and diabetes-associated blood markers using two generalized linear regression models: 'minimally adjusted' controlling for variables such as age and sex, and 'fully adjusted' including additional lifestyle covariates: BMI, alcohol and smoking status, and medication intake. There were 38/58 MDD PRS, 32/58 SCZ PRS, and 20/58 BD PRS-blood marker associations detected for our minimally adjusted model. Of these, 13/38 (MDD PRS), 14/32 (SCZ PRS), and 10/20 (BD PRS) associations remained significant after controlling for lifestyle factors. Many were disorder-specific, with 8/13 unique MDD PRS associations identified. Several disorder-specific associations for MDD and SCZ were immune-related, with mostly positive and negative associations identified for MDD and SCZ PRS respectively. This study suggests that MDD, SCZ and BD have both shared and distinct peripheral markers associated with disorder-specific genetic risk. The results also implicate inflammatory dysfunction in MDD and SCZ, albeit with differences in patterns between the two conditions, and enrich our understanding of potential underlying pathophysiological mechanisms in major psychiatric disorders.
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Affiliation(s)
- Michael D E Sewell
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK.
| | - Lorena Jiménez-Sánchez
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
| | - Amelia J Edmondson-Stait
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
| | - Claire Green
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Olivia M Rifai
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Donald M Lyall
- Institute of Health & Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK
| | - Heather C Whalley
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
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Valge M, Meitern R, Hõrak P. Anthropometrics of Estonian children in relation to family disruption: Thrifty phenotype and Trivers-Willard effects. Evol Med Public Health 2021; 9:276-286. [PMID: 34540230 PMCID: PMC8445393 DOI: 10.1093/emph/eoab022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 07/19/2021] [Indexed: 12/29/2022] Open
Abstract
Background and objectives The thrifty phenotype hypothesis proposes that at resource limitation, the growth of some organs/tissues is selectively spared to preserve more critical ones, such as the brain or lungs. The Trivers–Willard hypothesis (TWH) predicts that boys are more vulnerable in the case of resource limitation than girls. Both hypotheses were tested in children from disrupted families, differing in the extent of deprivation/adversities imposed on them. Methodology In a retrospective cohort study in the mid-20th century Estonia (Juhan Aul’s database), different types of orphans and children of divorced parents (treatment groups; n = 106–1401) were compared with children from bi-parental families (control groups; n = 2548–8648) so that children from treatment groups were matched with control children on the basis of sex, age, year of birth, urban versus rural origin and socioeconomic position. Results Children in orphanages suffered strong growth suppression, best explained by psychosocial deprivation. Their feet were on average 0.5 SD shorter than the feet of the controls, followed by height, leg/torso ratio and cranial volume that differed from controls by ca 0.4 SD. Weight difference was 0.2 SD units, while body mass index did not differ from controls. The growth of boys and girls in orphanages was suppressed to the same extent. Boys whose mothers were dead were relatively smaller and less masculine than girls from such families. Fathers’ absence was unrelated to growth suppression. Sons of divorced parents had broader shoulders than boys whose fathers were dead. Conclusions and implications Prediction of TWH about the greater vulnerability of male growth may hold under some conditions but not universally. Predictions of the thrifty phenotype hypothesis were partly supported: trunk growth was spared at the expense of leg growth; however, no evidence for brain sparing was found. Comparison of children of divorced versus dead fathers may appear useful for indirect assessment of sexual selection on offspring quality. Lay Summary: Boys and girls in orphanages suffered similarly strong growth suppression, best explained by psychosocial deprivation. Boys whose mothers were dead were relatively smaller and less masculine than girls from such families. The occurrence of sex-specific associations between family structure and children’s growth depends on the type of family disruption.
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Affiliation(s)
- Markus Valge
- Department of Zoology, University of Tartu, Vanemuise 46, Tartu 51014, Estonia
| | - Richard Meitern
- Department of Zoology, University of Tartu, Vanemuise 46, Tartu 51014, Estonia
| | - Peeter Hõrak
- Department of Zoology, University of Tartu, Vanemuise 46, Tartu 51014, Estonia
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Eum S, Hill SK, Alliey-Rodriguez N, Stevenson JM, Rubin LH, Lee AM, Mills LJ, Reilly JL, Lencer R, Keedy SK, Ivleva E, Keefe RSE, Pearlson GD, Clementz BA, Tamminga CA, Keshavan MS, Gershon ES, Sweeney JA, Bishop JR. Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders. Neuropsychopharmacology 2021; 46:1802-1810. [PMID: 34145405 PMCID: PMC8358015 DOI: 10.1038/s41386-021-01057-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 05/17/2021] [Accepted: 06/03/2021] [Indexed: 12/13/2022]
Abstract
Identifying genetic contributors to cognitive impairments in psychosis-spectrum disorders can advance understanding of disease pathophysiology. Although CNS medications are known to affect cognitive performance, they are often not accounted for in genetic association studies. In this study, we performed a genome-wide association study (GWAS) of global cognitive performance, measured as composite z-scores from the Brief Assessment of Cognition in Schizophrenia (BACS), in persons with psychotic disorders and controls (N = 817; 682 cases and 135 controls) from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Analyses accounting for anticholinergic exposures from both psychiatric and non-psychiatric medications revealed five significantly associated variants located at the chromosome 3p21.1 locus, with the top SNP rs1076425 in the inter-alpha-trypsin inhibitor heavy chain 1 (ITIH1) gene (P = 3.25×E-9). The inclusion of anticholinergic burden improved association models (P < 0.001) and the number of significant SNPs identified. The effect sizes and direction of effect of the top variants remained consistent when investigating findings within individuals receiving specific antipsychotic drugs and after accounting for antipsychotic dose. These associations were replicated in a separate study sample of untreated first-episode psychosis. The chromosome 3p21.1 locus was previously reported to have association with the risk for psychotic disorders and cognitive performance in healthy individuals. Our findings suggest that this region may be a psychosis risk locus that is associated with cognitive mechanisms. Our data highlight the general point that the inclusion of medication exposure information may improve the detection of gene-cognition associations in psychiatric genetic research.
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Affiliation(s)
- Seenae Eum
- grid.412555.20000 0001 0511 4494Department of Pharmacogenomics, Shenandoah University, Fairfax, VA USA
| | - S. Kristian Hill
- grid.262641.50000 0004 0388 7807Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL USA
| | - Ney Alliey-Rodriguez
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - James M. Stevenson
- grid.21107.350000 0001 2171 9311Division of Clinical Pharmacology, Department of Medicine, Johns Hopkins University, Baltimore, MD USA
| | - Leah H. Rubin
- grid.21107.350000 0001 2171 9311Departments of Neurology, Psychiatry, and Epidemiology, Johns Hopkins University, Baltimore, MD USA
| | - Adam M. Lee
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN USA
| | - Lauren J. Mills
- grid.17635.360000000419368657Masonic Cancer Center and Department of Pediatrics, University of Minnesota, Minneapolis, MN USA
| | - James L. Reilly
- grid.16753.360000 0001 2299 3507Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL USA
| | - Rebekka Lencer
- grid.5949.10000 0001 2172 9288Institute of Translational Psychiatry and Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Muenster, Muenster, Germany ,grid.4562.50000 0001 0057 2672Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany
| | - Sarah K. Keedy
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - Elena Ivleva
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX USA
| | - Richard S. E. Keefe
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry, Duke University School of Medicine, Durham, NC USA
| | - Godfrey D. Pearlson
- grid.277313.30000 0001 0626 2712Departments of Psychiatry and Neuroscience, Yale School of Medicine, Olin Center, Institute of Living, Hartford Healthcare, Hartford, CT USA
| | - Brett A. Clementz
- grid.213876.90000 0004 1936 738XDepartment of Psychology, University of Georgia, Athens, GA USA
| | - Carol A. Tamminga
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX USA
| | - Matcheri S. Keshavan
- grid.239395.70000 0000 9011 8547Beth Israel Deaconess Medical Center, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Psychiatry, Harvard Medical School, Boston, MA USA
| | - Elliot S. Gershon
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - John A. Sweeney
- grid.413561.40000 0000 9881 9161Department of Psychiatry, University of Cincinnati Medical Center, Cincinnati, OH USA
| | - Jeffrey R. Bishop
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN USA ,grid.17635.360000000419368657Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN USA
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Jonsdottir GA, Einarsson G, Thorleifsson G, Magnusson SH, Gunnarsson AF, Frigge ML, Gisladottir RS, Unnsteinsdottir U, Gunnarsson B, Walters GB, Steinthorsdottir V, Helgadottir A, Jonsdottir I, Gislason T, Thorsteinsson HS, Sigurdsson E, Haraldsson M, Sigurdsson EL, Bjarnason R, Olafsson I, Thorgeirsson G, Sulem P, Holm H, Thorsteinsdottir U, Gudbjartsson DF, Bjornsdottir G, Thorgeirsson TE, Stefansson H, Stefansson K. Genetic propensities for verbal and spatial ability have opposite effects on body mass index and risk of schizophrenia. INTELLIGENCE 2021. [DOI: 10.1016/j.intell.2021.101565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Lam M, Chen CY, Ge T, Xia Y, Hill DW, Trampush JW, Yu J, Knowles E, Davies G, Stahl EA, Huckins L, Liewald DC, Djurovic S, Melle I, Christoforou A, Reinvang I, DeRosse P, Lundervold AJ, Steen VM, Espeseth T, Räikkönen K, Widen E, Palotie A, Eriksson JG, Giegling I, Konte B, Hartmann AM, Roussos P, Giakoumaki S, Burdick KE, Payton A, Ollier W, Chiba-Falek O, Koltai DC, Need AC, Cirulli ET, Voineskos AN, Stefanis NC, Avramopoulos D, Hatzimanolis A, Smyrnis N, Bilder RM, Freimer NB, Cannon TD, London E, Poldrack RA, Sabb FW, Congdon E, Conley ED, Scult MA, Dickinson D, Straub RE, Donohoe G, Morris D, Corvin A, Gill M, Hariri AR, Weinberger DR, Pendleton N, Bitsios P, Rujescu D, Lahti J, Le Hellard S, Keller MC, Andreassen OA, Deary IJ, Glahn DC, Huang H, Liu C, Malhotra AK, Lencz T. Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics. Neuropsychopharmacology 2021; 46:1788-1801. [PMID: 34035472 PMCID: PMC8357785 DOI: 10.1038/s41386-021-01023-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 02/22/2021] [Accepted: 04/12/2021] [Indexed: 02/05/2023]
Abstract
Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.
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Affiliation(s)
- Max Lam
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Institute of Mental Health, Singapore, Singapore
| | - Chia-Yen Chen
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Biogen, Inc, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Tian Ge
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Yan Xia
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China
- Psychiatry Department, SUNY Upstate Medical University, Syracuse, NY, USA
| | - David W Hill
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, Scotland, UK
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Joey W Trampush
- Department of Psychiatry and the Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jin Yu
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Emma Knowles
- Tommy Fuss Center for Neuropsychiatric Disease Research, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Olin Neuropsychic Research Center, Institute of Living, Hartford Hospital, Hartford, CT, USA
| | - Gail Davies
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, Scotland, UK
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Eli A Stahl
- Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Laura Huckins
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - David C Liewald
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ingrid Melle
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Andrea Christoforou
- Spaulding Rehabilitation Hospital Boston, Charlestown, MA, USA
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Ivar Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Pamela DeRosse
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Astri J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Vidar M Steen
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Thomas Espeseth
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Katri Räikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK
- Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland
| | - Johan G Eriksson
- Department of General Practice, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Folkhälsan Research Center, Helsinki, Finland
| | - Ina Giegling
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - Bettina Konte
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - Annette M Hartmann
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - Panos Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center (VISN 2), James J. Peters VA Medical Center, Bronx, NY, USA
| | | | - Katherine E Burdick
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center (VISN 2), James J. Peters VA Medical Center, Bronx, NY, USA
- Department of Psychiatry - Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Antony Payton
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, Manchester, UK
| | - William Ollier
- Centre for Epidemiology, Division of Population Health, Health Services Research & Primary Care, The University of Manchester, Manchester, UK
- School of Healthcare Sciences, Manchester Metropolitan University, Manchester, United Kingdom
| | - Ornit Chiba-Falek
- Division of Translational Brain Sciences, Department of Neurology, Bryan Alzheimer's Disease Research Center, and Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, USA
| | - Deborah C Koltai
- Psychiatry and Behavioral Sciences, Division of Medical Psychology, and Department of Neurology, Duke University Medical Center, Durham, NC, USA
| | - Anna C Need
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | | | - Aristotle N Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada
| | - Nikos C Stefanis
- 2nd Department of Psychiatry, National and Kapodistrian University of Athens Medical School, University General Hospital "ATTIKON", Athens, Greece
- University Mental Health Research Institute, Athens, Greece
- Neurobiology Research Institute, Theodor-Theohari Cozzika Foundation, Athens, Greece
| | - Dimitrios Avramopoulos
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alex Hatzimanolis
- 2nd Department of Psychiatry, National and Kapodistrian University of Athens Medical School, University General Hospital "ATTIKON", Athens, Greece
- University Mental Health Research Institute, Athens, Greece
- Neurobiology Research Institute, Theodor-Theohari Cozzika Foundation, Athens, Greece
| | - Nikolaos Smyrnis
- 2nd Department of Psychiatry, National and Kapodistrian University of Athens Medical School, University General Hospital "ATTIKON", Athens, Greece
- University Mental Health Research Institute, Athens, Greece
| | - Robert M Bilder
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - Nelson B Freimer
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - Tyrone D Cannon
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Edythe London
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | | | - Fred W Sabb
- Robert and Beverly Lewis Center for Neuroimaging, University of Oregon, Eugene, OR, USA
| | - Eliza Congdon
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | | | - Matthew A Scult
- Weill Cornell Psychiatry at NewYork-Presbyterian, Weill Cornell Medical Center, New York, NY, USA
- Laboratory of NeuroGenetics, Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
| | - Dwight Dickinson
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institute of Health, Bethesda, MD, USA
| | - Richard E Straub
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Gary Donohoe
- Neuroimaging, Cognition & Genomics (NICOG) Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland, Galway, Ireland
| | - Derek Morris
- Neuroimaging, Cognition & Genomics (NICOG) Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland, Galway, Ireland
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of Psychiatry and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Michael Gill
- Neuropsychiatric Genetics Research Group, Department of Psychiatry and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Ahmad R Hariri
- Laboratory of NeuroGenetics, Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Neil Pendleton
- Division of Neuroscience and Experimental Psychology/School of Biological Sciences, Faculty of Biology Medicine and Health, Manchester Academic Health Science Centre, Salford Royal NHS Foundation Trust, University of Manchester, Manchester, UK
| | - Panos Bitsios
- Department of Psychiatry and Behavioral Sciences, Faculty of Medicine, University of Crete, Heraklion, Crete, GR, Greece
| | - Dan Rujescu
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland
| | - Stephanie Le Hellard
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Matthew C Keller
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA
| | - Ole A Andreassen
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ian J Deary
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, Scotland, UK
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - David C Glahn
- Tommy Fuss Center for Neuropsychiatric Disease Research, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Olin Neuropsychic Research Center, Institute of Living, Hartford Hospital, Hartford, CT, USA
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Chunyu Liu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China
- Psychiatry Department, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Anil K Malhotra
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Todd Lencz
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY, USA.
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA.
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
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Ronan L, Alexander-Bloch A, Fletcher PC. Childhood Obesity, Cortical Structure, and Executive Function in Healthy Children. Cereb Cortex 2021; 30:2519-2528. [PMID: 31646343 PMCID: PMC7175011 DOI: 10.1093/cercor/bhz257] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The development of executive function is linked to maturation of prefrontal cortex (PFC) in childhood. Childhood obesity has been associated with changes in brain structure, particularly in PFC, as well as deficits in executive functions. We aimed to determine whether differences in cortical structure mediate the relationship between executive function and childhood obesity. We analyzed MR-derived measures of cortical thickness for 2700 children between the ages of 9 and 11 years, recruited as part of the NIH Adolescent Brain and Cognitive Development (ABCD) study. We related our findings to measures of executive function and body mass index (BMI). In our analysis, increased BMI was associated with significantly reduced mean cortical thickness, as well as specific bilateral reduced cortical thickness in prefrontal cortical regions. This relationship remained after accounting for age, sex, race, parental education, household income, birth-weight, and in-scanner motion. Increased BMI was also associated with lower executive function. Reduced thickness in the rostral medial and superior frontal cortex, the inferior frontal gyrus, and the lateral orbitofrontal cortex partially accounted for reductions in executive function. These results suggest that childhood obesity is associated with compromised executive function. This relationship may be partly explained by BMI-associated reduced cortical thickness in the PFC.
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Affiliation(s)
- Lisa Ronan
- Department of Psychiatry, University of Cambridge, Cambridge CB2 8HA UK
| | - Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, PA 19104, USA
| | - Paul C Fletcher
- Department of Psychiatry, University of Cambridge, Cambridge CB2 8HA UK.,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge CB21 5EF, UK.,The Wellcome-MRC Institute of Metabolic Science-Metabolic Research Laboratories (IMS-MRL), University of Cambridge, Cambridge CB2 0QQ, UK
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Kowalec K, Lu Y, Sariaslan A, Song J, Ploner A, Dalman C, Hultman CM, Larsson H, Lichtenstein P, Sullivan PF. Increased schizophrenia family history burden and reduced premorbid IQ in treatment-resistant schizophrenia: a Swedish National Register and Genomic Study. Mol Psychiatry 2021; 26:4487-4495. [PMID: 31712719 PMCID: PMC9731609 DOI: 10.1038/s41380-019-0575-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 09/23/2019] [Accepted: 10/23/2019] [Indexed: 01/29/2023]
Abstract
A high proportion of those with schizophrenia experience treatment non-response, placing them at higher risk for mortality and suicide attempts, compared to treatment responders. The clinical, social, and economic burden of treatment-resistant schizophrenia (TRS) are substantial. Previous genomic and epidemiological studies of TRS were often limited by sample size or lack of comprehensive genomic data. We aimed to systematically understand the clinical, demographic, and genomic correlates of TRS using epidemiological and genetic epidemiological modelling in a Swedish national population sample (n = 24,706) and then in a subgroup with common variant genetic risk scores, rare copy-number variant burden, and rare exonic burden (n = 4936). Population-based analyses identified increasing schizophrenia family history to be significantly associated with TRS (highest quartile of familial burden vs. lowest: adjusted odds ratio (aOR): 1.31, P = 4.8 × 10-8). In males, a decrease of premorbid IQ of one standard deviation was significantly associated with greater risk of TRS (minimal aOR: 0.94, P = 0.002). In a subset of cases with extensive genomic data, we found no significant association between the genetic risk scores of four psychiatric disorders and two cognitive traits with TRS (schizophrenia genetic risk score: aOR = 1.07, P = 0.067). The association between copy number variant and rare variant burden measures and TRS did not reach the pre-defined statistical significance threshold (all P ≥ 0.005). In conclusion, direct measures of genomic risk were not associated with TRS; however, premorbid IQ in males and schizophrenia family history were significantly correlated with TRS and points to new insights into the architecture of TRS.
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Affiliation(s)
- Kaarina Kowalec
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, College of Pharmacy, University of Manitoba, Winnipeg, MB, Canada
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Amir Sariaslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jie Song
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Alexander Ploner
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Christina Dalman
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Christina M. Hultman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Icahn School of Medicine, Department of Psychiatry, Mt. Sinai Hospital, New York, NY, USA
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, School of Medical Sciences, Örebo University, Örebo, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrick F. Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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75
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Huibregtse BM, Newell-Stamper BL, Domingue BW, Boardman JD. Genes Related to Education Predict Frailty Among Older Adults in the United States. J Gerontol B Psychol Sci Soc Sci 2021; 76:173-183. [PMID: 31362310 DOI: 10.1093/geronb/gbz092] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE This article expands on research that links education and frailty among older adults by considering the role of genes associated with education. METHOD Data come from a sample of 7,064 non-Hispanic, white adults participating in the 2004-2012 waves of the Health and Retirement Study. Frailty was measured with two indices: (a) The Frailty Index which corresponds to a deficit accumulation model; and (b) The Paulson-Lichtenberg Frailty Index which corresponds to the biological syndrome/phenotype model. Genes associated with education were quantified using an additive polygenic score. Associations between the polygenic score and frailty indices were tested using a series of multilevel models, controlling for multiple observations for participants across waves. RESULTS Results showed a strong and negative association between genes for education and frailty symptoms in later life. This association exists above and beyond years of completed education and we demonstrate that this association becomes weaker as older adults approach their 80s. DISCUSSION The results contribute to the education-health literature by highlighting new and important pathways through which education might be linked to successful aging.
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Affiliation(s)
- Brooke M Huibregtse
- Institute of Behavioral Science, University of Colorado Boulder.,Institute for Behavioral Genetics, University of Colorado Boulder
| | - Breanne L Newell-Stamper
- Institute of Behavioral Science, University of Colorado Boulder.,Institute for Behavioral Genetics, University of Colorado Boulder.,Department of Integrative Physiology, University of Colorado Boulder
| | - Benjamin W Domingue
- Institute of Behavioral Science, University of Colorado Boulder.,Graduate School of Education, Stanford University, California
| | - Jason D Boardman
- Institute of Behavioral Science, University of Colorado Boulder.,Institute for Behavioral Genetics, University of Colorado Boulder.,Department of Sociology, University of Colorado Boulder
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76
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Ferri F, Deschênes SS, Power N, Schmitz N. Associations between cognitive function, metabolic factors and depression: A prospective study in Quebec, Canada. J Affect Disord 2021; 283:77-83. [PMID: 33524662 DOI: 10.1016/j.jad.2021.01.039] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 12/09/2020] [Accepted: 01/09/2021] [Indexed: 10/22/2022]
Abstract
BACKGROUND Metabolic risk factors, low cognitive function and history of depression are known risk factors for future depressive episodes. This paper aims to evaluate the potential interactions between these factors on the risk of a major depressive episodes in middle-age. METHODS Baseline and follow-up data from a population-based study of Quebec, Canada were used. The sample consisted of 1788 adults between 40 and 69 years of age without diabetes. Cognitive function and metabolic risk factors were assessed at baseline. Three cognitive domains were assessed: processing speed, episodic memory and executive function. History of depression was assessed five years later by a clinical interview. Logistic regression analysis was conducted to evaluate interactions between individual metabolic factors, low cognitive function, and depression history. RESULTS Participants with a comorbidity of at least one metabolic factor, history of depression and low cognitive function had the highest risk of experiencing a depressive episode in middle age. The highest risk was observed in individuals with abdominal obesity, low cognitive function, and a history of depression (OR= 8.66, 95% CI 3.83-19.59). The risks for those with abdominal obesity only, depression history only, and low cognitive function were 1.20 (95%CI 0.71-2.02), 3.10 (95%CI 1.81-5.24), and 1.39 (95%CI 0.72-2.67), respectively. LIMITATIONS Depression was only assessed at follow-up. CONCLUSION Metabolic risk factors comorbid with low cognitive function in middle-aged individuals with a history of depression were associated with an increased risk of a future depressive episode. This study highlights the importance of screening for metabolic and cognitive comorbidities in patients with a history of depression.
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Affiliation(s)
- Floriana Ferri
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada; Douglas University Mental Health Institute, Montreal, QC, Canada
| | - Sonya S Deschênes
- Douglas University Mental Health Institute, Montreal, QC, Canada; School of Psychology, University College Dublin, Dublin, Ireland
| | - Niamh Power
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada; Douglas University Mental Health Institute, Montreal, QC, Canada
| | - Norbert Schmitz
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada; Douglas University Mental Health Institute, Montreal, QC, Canada; Department of Epidemiology, Biostatistics, and Occupational Health, Faculty of Medicine, McGill University, Montreal, QC, Canada; Montreal Diabetes Research Centre, Montreal, QC, Canada.
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77
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Nayar K, Sealock JM, Maltman N, Bush L, Cook EH, Davis LK, Losh M. Elevated Polygenic Burden for Autism Spectrum Disorder Is Associated With the Broad Autism Phenotype in Mothers of Individuals With Autism Spectrum Disorder. Biol Psychiatry 2021; 89:476-485. [PMID: 33229037 PMCID: PMC7901138 DOI: 10.1016/j.biopsych.2020.08.029] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 08/15/2020] [Accepted: 08/31/2020] [Indexed: 12/25/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder that encompasses a complex and heterogeneous set of traits. Subclinical traits that mirror the core features of ASD, referred to as the broad autism phenotype (BAP), have been documented repeatedly in unaffected relatives and are believed to reflect underlying genetic liability to ASD. The BAP may help inform the etiology of ASD by allowing the stratification of families into more phenotypically and etiologically homogeneous subgroups. This study explores polygenic scores related to the BAP. METHODS Phenotypic and genotypic information were obtained from 2614 trios from the Simons Simplex Collection. Polygenic scores of ASD (ASD-PGSs) were generated across the sample to determine the shared genetic overlap between the BAP and ASD. Maternal and paternal ASD-PGSs were explored in relation to BAP traits and their child's ASD symptomatology. RESULTS Maternal pragmatic language was related to child's social communicative atypicalities. In fathers, rigid personality was related to increased repetitive behaviors in children. Maternal (but not paternal) ASD-PGSs were related to the pragmatic language and rigid BAP domains. CONCLUSIONS Associations emerged between parent and child phenotypes, with more associations emerging in mothers than in fathers. ASD-PGS associations emerged with BAP in mothers only, highlighting the potential for a female protective factor, and implicating the polygenic etiology of ASD-related phenotypes in the BAP.
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Affiliation(s)
| | | | | | | | | | | | - Molly Losh
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois.
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79
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Socrates A, Maxwell J, Glanville KP, Di Forti M, Murray RM, Vassos E, O'Reilly PF. Investigating the effects of genetic risk of schizophrenia on behavioural traits. NPJ SCHIZOPHRENIA 2021; 7:2. [PMID: 33483511 PMCID: PMC7822841 DOI: 10.1038/s41537-020-00131-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 10/23/2020] [Indexed: 12/31/2022]
Abstract
To characterise the trait-effects of increased genetic risk for schizophrenia, and highlight potential risk mediators, we test the association between schizophrenia polygenic risk scores (PRSs) and 529 behavioural traits (personality, psychological, lifestyle, nutritional) in the UK Biobank. Our primary analysis is performed on individuals aged 38–71 with no history of schizophrenia or related disorders, allowing us to report the effects of schizophrenia genetic risk in the sub-clinical general population. Higher schizophrenia PRSs were associated with a range of traits, including lower verbal-numerical reasoning (P = 6 × 10–61), higher nervous feelings (P = 1 × 10−46) and higher self-reported risk-taking (P = 3 × 10−38). We follow-up the risk-taking association, hypothesising that the association may be due to a genetic propensity for risk-taking leading to greater migration, urbanicity or drug-taking — reported environmental risk factors for schizophrenia, and all positively associated with risk-taking in these data. Next, to identify potential disorder or medication effects, we compare the PRS–trait associations in the general population to the trait values in 599 medicated and non-medicated individuals diagnosed with schizophrenia in the biobank. This analysis highlights, for example, levels of BMI, physical activity and risk-taking in cases in the opposite directions than expected from the PRS–trait associations in the general population. Our analyses offer simple yet potentially revealing insights into the possible causes of observed trait–disorder associations, which can complement approaches such as Mendelian Randomisation. While we urge caution in causal interpretations in PRS cross-trait studies that are highly powered to detect weak horizontal pleiotropy or population structure, we propose that well-designed polygenic score analyses have the potential to highlight modifiable risk factors that lie on the path between genetic risk and disorder.
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Affiliation(s)
- Adam Socrates
- SGDP Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Jessye Maxwell
- SGDP Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Kylie P Glanville
- SGDP Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Marta Di Forti
- SGDP Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Robin M Murray
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Evangelos Vassos
- SGDP Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Paul F O'Reilly
- SGDP Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. .,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
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80
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The codevelopment of internalizing symptoms, externalizing symptoms, and cognitive ability across childhood and adolescence. Dev Psychopathol 2021; 32:1375-1389. [PMID: 31588887 DOI: 10.1017/s0954579419001330] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Cognitive ability, externalizing symptoms, and internalizing symptoms are correlated in children. However, it is not known why they combine in the general child population over time. To address this, we used data on 17,318 children participating in the UK Millennium Cohort Study and followed-up five times between ages 3 and 14 years. We fitted three parallel-process latent growth curve models to identify the parallel unfolding of children's trajectories of internalizing symptoms, externalizing symptoms, and cognitive ability across this period. We also examined the effects of time-invariant (ethnicity, birth weight, maternal education and age at birth, and breastfeeding status) and time-varying covariates (maternal psychological distress and socioeconomic disadvantage) on the growth parameters of the trajectories. The results showed that the intercepts of the trajectories of cognitive ability and, particularly, externalizing symptoms were inversely correlated. Their linear slopes were also inversely correlated, suggesting parallel development. Internalizing symptoms were correlated positively with externalizing symptoms and inversely (and more modestly) with cognitive ability at baseline, but the slope of internalizing symptoms correlated (positively) only with the slope of externalizing symptoms. The covariates predicted 9% to 41% of the variance in the intercepts and slopes of all domains, suggesting they are important common risk factors. Overall, it appears that externalizing symptoms develop in parallel with both cognitive ability and internalizing symptoms from early childhood through to middle adolescence. Children on an increasing trajectory of externalizing symptoms are likely both increasing in internalizing symptoms and decreasing in cognitive skills as well, and are thus an important group to target for intervention.
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81
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Mayer JS, Bernhard A, Fann N, Boxhoorn S, Hartman CA, Reif A, Freitag CM. Cognitive mechanisms underlying depressive disorders in ADHD: A systematic review. Neurosci Biobehav Rev 2021; 121:307-345. [PMID: 33359622 DOI: 10.1016/j.neubiorev.2020.12.018] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 12/01/2020] [Accepted: 12/09/2020] [Indexed: 01/06/2023]
Abstract
The risk for major depressive disorder (MDD) is considerably increased in young adults with attention-deficit/hyperactivity disorder (ADHD) but underlying mechanisms are poorly understood. This review explores ADHD-specific neurocognitive impairments as possible underlying mechanisms for ADHD-depression comorbidity. Two systematic literature searches were conducted in EBSCOhost, PubMED, and Cochrane Reviews databases according to PRISMA guidelines. The first search identified 18 meta-analyses of cross-sectional and longitudinal studies on cognitive dysfunctions in MDD across the lifespan. The second search identified six original studies on reaction time variability in MDD. During acute depression, children and adults showed cognitive deficits that overlapped with some of the ADHD-related impairments. Findings from remitted patients, high-risk individuals, and few prospective studies suggest that a subset of these shared impairments, specifically executive dysfunctions (selective attention, verbal fluency, working memory) and long-term memory problems, are candidate pre-existing risk markers of depression. We discuss if and how these specific neurocognitive mechanisms may mediate developmental pathways from ADHD to depression. If replicated by longitudinal studies, these findings may guide future prevention strategies.
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Affiliation(s)
- Jutta S Mayer
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Deutschordenstraße 50, 60528 Frankfurt am Main, Germany.
| | - Anka Bernhard
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Deutschordenstraße 50, 60528 Frankfurt am Main, Germany
| | - Nikola Fann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Deutschordenstraße 50, 60528 Frankfurt am Main, Germany
| | - Sara Boxhoorn
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Deutschordenstraße 50, 60528 Frankfurt am Main, Germany
| | - Catharina A Hartman
- Interdisciplinary Centre Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Centre Groningen, CC 72, P.O. Box 30.001, 9700 RB Groningen, the Netherlands
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Heinrich-Hoffmann-Str. 10, 60528 Frankfurt am Main, Germany
| | - Christine M Freitag
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Deutschordenstraße 50, 60528 Frankfurt am Main, Germany
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82
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de la Fuente J, Davies G, Grotzinger AD, Tucker-Drob EM, Deary IJ. A general dimension of genetic sharing across diverse cognitive traits inferred from molecular data. Nat Hum Behav 2021; 5:49-58. [PMID: 32895543 PMCID: PMC9346507 DOI: 10.1038/s41562-020-00936-2] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 07/27/2020] [Indexed: 01/28/2023]
Abstract
It has been known since 1904 that, in humans, diverse cognitive traits are positively intercorrelated. This forms the basis for the general factor of intelligence (g). Here, we directly test whether there is a partial genetic basis for individual differences in g using data from seven different cognitive tests (n = 11,263-331,679) and genome-wide autosomal single-nucleotide polymorphisms. A genetic g factor accounts for an average of 58.4% (s.e. = 4.8%) of the genetic variance in the cognitive traits considered, with the proportion varying widely across traits (range, 9-95%). We distil genetic loci that are broadly relevant for many cognitive traits (g) from loci associated specifically with individual cognitive traits. These results contribute to elucidating the aetiology of a long-known yet poorly understood phenomenon, revealing a fundamental dimension of genetic sharing across diverse cognitive traits.
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Affiliation(s)
- Javier de la Fuente
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - Gail Davies
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | | | - Elliot M Tucker-Drob
- Department of Psychology, University of Texas at Austin, Austin, TX, USA.
- Population Research Center, University of Texas at Austin, Austin, TX, USA.
| | - Ian J Deary
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK.
- Department of Psychology, University of Edinburgh, Edinburgh, UK.
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83
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de Las Heras B, Rodrigues L, Cristini J, Weiss M, Prats-Puig A, Roig M. Does the Brain-Derived Neurotrophic Factor Val66Met Polymorphism Modulate the Effects of Physical Activity and Exercise on Cognition? Neuroscientist 2020; 28:69-86. [PMID: 33300425 DOI: 10.1177/1073858420975712] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The Val66Met is a polymorphism of the brain-derived neurotrophic factor (BDNF) gene that encodes a substitution of a valine (Val) to methionine (Met) amino acid. Carrying this polymorphism reduces the activity-dependent secretion of the BDNF protein, which can potentially affect brain plasticity and cognition. We reviewed the biology of Val66Met and surveyed 26 studies (11,417 participants) that examined the role of this polymorphism in moderating the cognitive response to physical activity (PA) and exercise. Nine observational studies confirmed a moderating effect of Val66Met on the cognitive response to PA but differences between Val and Met carriers were inconsistent and only significant in some cognitive domains. Only five interventional studies found a moderating effect of Val66Met on the cognitive response to exercise, which was also inconsistent in its direction. Two studies showed a superior cognitive response in Val carriers and three studies showed a better response in Met carriers. These results do not support a general and consistent effect of Val66Met in moderating the cognitive response to PA or exercise. Both Val and Met carriers can improve specific aspects of cognition by increasing PA and engaging in exercise. Causes for discrepancies among studies, effect moderators, and future directions are discussed.
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Affiliation(s)
- Bernat de Las Heras
- Memory and Motor Rehabilitation Laboratory (MEMORY-LAB), Feil and Oberfeld Research Centre, Jewish Rehabilitation Hospital, Montreal Center for Interdisciplinary Research in Rehabilitation (CRIR), Laval, Quebec, Canada.,School of Physical and Occupational Therapy, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Lynden Rodrigues
- Memory and Motor Rehabilitation Laboratory (MEMORY-LAB), Feil and Oberfeld Research Centre, Jewish Rehabilitation Hospital, Montreal Center for Interdisciplinary Research in Rehabilitation (CRIR), Laval, Quebec, Canada.,School of Physical and Occupational Therapy, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Jacopo Cristini
- Memory and Motor Rehabilitation Laboratory (MEMORY-LAB), Feil and Oberfeld Research Centre, Jewish Rehabilitation Hospital, Montreal Center for Interdisciplinary Research in Rehabilitation (CRIR), Laval, Quebec, Canada.,School of Physical and Occupational Therapy, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Maxana Weiss
- Memory and Motor Rehabilitation Laboratory (MEMORY-LAB), Feil and Oberfeld Research Centre, Jewish Rehabilitation Hospital, Montreal Center for Interdisciplinary Research in Rehabilitation (CRIR), Laval, Quebec, Canada.,School of Physical and Occupational Therapy, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Anna Prats-Puig
- University School of Health and Sport (EUSES), University of Girona, Girona, Catalunya, Spain
| | - Marc Roig
- Memory and Motor Rehabilitation Laboratory (MEMORY-LAB), Feil and Oberfeld Research Centre, Jewish Rehabilitation Hospital, Montreal Center for Interdisciplinary Research in Rehabilitation (CRIR), Laval, Quebec, Canada.,School of Physical and Occupational Therapy, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
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84
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Soler J, Lera-Miguel S, Lázaro L, Calvo R, Ferentinos P, Fañanás L, Fatjó-Vilas M. Familial aggregation analysis of cognitive performance in early-onset bipolar disorder. Eur Child Adolesc Psychiatry 2020; 29:1705-1716. [PMID: 32052174 DOI: 10.1007/s00787-020-01486-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 01/27/2020] [Indexed: 01/03/2023]
Abstract
We analysed the familial aggregation (familiality) of cognitive dimensions and explored their role as liability markers for early-onset bipolar disorder (EOBD). The sample comprised 99 subjects from 26 families, each with an offspring diagnosed with EOBD. Four cognitive dimensions were assessed: reasoning skills; attention and working memory; memory; and executive functions. Their familiality was investigated in the total sample and in a subset of healthy relatives. The intra-family resemblance score (IRS), a family-based index of the similarity of cognitive performance among family members, was calculated. Familiality was detected for the attention and working memory (AW) dimension in the total sample (ICC = 0.37, p = 0.0004) and in the subsample of healthy relatives (ICC = 0.37, p = 0.016). The IRS reflected that there are families with similar AW mean scores (either high or low) and families with heterogeneous scores. Families with the most common background for the AW dimension (IRS > 0) were selected and dichotomized in two groups according to the mean family AW score. This allowed differentiating families whose members had similar high scores than those with similar low scores: both patients (t = - 4.82, p = 0.0005) and relatives (t = - 5.04, p < 0.0001) of the two groups differed in their AW scores. AW dimension showed familial aggregation, suggesting its putative role as a familial vulnerability marker for EOBD. The IRS estimation allowed the identification of families with homogeneous scores for this dimension. This represents a first step towards the investigation of the underlying mechanisms of AW dimension and the identification of etiological subgroups.
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Affiliation(s)
- Jordi Soler
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Sara Lera-Miguel
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clínic, Barcelona, Spain
- Department of Medicine, Faculty of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Luisa Lázaro
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clínic, Barcelona, Spain
- Institut d'Investigació Biomèdica August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Medicine, Faculty of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Rosa Calvo
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clínic, Barcelona, Spain
- Department of Medicine, Faculty of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Panagiotis Ferentinos
- 2nd Department of Psychiatry, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, Athens, Greece
| | - Lourdes Fañanás
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Mar Fatjó-Vilas
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain.
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Universitat de Barcelona, Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.
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86
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Li D, Choque-Olsson N, Jiao H, Norgren N, Jonsson U, Bölte S, Tammimies K. The influence of common polygenic risk and gene sets on social skills group training response in autism spectrum disorder. NPJ Genom Med 2020; 5:45. [PMID: 33083014 PMCID: PMC7550579 DOI: 10.1038/s41525-020-00152-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 09/15/2020] [Indexed: 12/14/2022] Open
Abstract
Social skills group training (SSGT) is a frequently used behavioral intervention in autism spectrum disorder (ASD), but the effects are moderate and heterogeneous. Here, we analyzed the effect of polygenic risk score (PRS) and common variants in gene sets on the intervention outcome. Participants from the largest randomized clinical trial of SSGT in ASD to date were selected (N = 188, 99 from SSGT, 89 from standard care) to calculate association between the outcomes in the SSGT trial and PRSs for ASD, attention-deficit hyperactivity disorder (ADHD), and educational attainment. In addition, specific gene sets were selected to evaluate their role on intervention outcomes. Among all participants in the trial, higher PRS for ADHD was associated with significant improvement in the outcome measure, the parental-rated Social Responsiveness Scale. The significant association was due to better outcomes in the standard care group for individuals with higher PRS for ADHD (post-intervention: β = −4.747, P = 0.0129; follow-up: β = −5.309, P = 0.0083). However, when contrasting the SSGT and standard care group, an inferior outcome in the SSGT group was associated with higher ADHD PRS at follow-up (β = 6.67, P = 0.016). Five gene sets within the synaptic category showed a nominal association with reduced response to interventions. We provide preliminary evidence that genetic liability calculated from common variants could influence the intervention outcomes. In the future, larger cohorts should be used to investigate how genetic contribution affects individual response to ASD interventions.
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Affiliation(s)
- Danyang Li
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm County Council, Stockholm, Sweden.,Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, Stockholm, Sweden.,Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Nora Choque-Olsson
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm County Council, Stockholm, Sweden.,Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.,Center for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Hong Jiao
- Department of Biosciences and Nutrition, Karolinska Institutet, and Clinical Research Centre, Karolinska University Hospital, Huddinge, Sweden
| | - Nina Norgren
- Department of Molecular Biology, National Bioinformatics Infrastructure Sweden (NBIS), Science for Life Laboratory, Umeå University, 901 87 Umeå, Sweden
| | - Ulf Jonsson
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm County Council, Stockholm, Sweden.,Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.,Department of Neuroscience, Child and Adolescent Psychiatry, Uppsala University, Uppsala, Sweden
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm County Council, Stockholm, Sweden.,Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.,Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, WA Australia
| | - Kristiina Tammimies
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm County Council, Stockholm, Sweden.,Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, Stockholm, Sweden.,Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
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87
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Look duration at the face as a developmental endophenotype: elucidating pathways to autism and ADHD. Dev Psychopathol 2020; 32:1303-1322. [DOI: 10.1017/s0954579420000930] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
AbstractIdentifying developmental endophenotypes on the pathway between genetics and behavior is critical to uncovering the mechanisms underlying neurodevelopmental conditions. In this proof-of-principle study, we explored whether early disruptions in visual attention are a unique or shared candidate endophenotype of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). We calculated the duration of the longest look (i.e., peak look) to faces in an array-based eye-tracking task for 335 14-month-old infants with and without first-degree relatives with ASD and/or ADHD. We leveraged parent-report and genotype data available for a proportion of these infants to evaluate the relation of looking behavior to familial (n = 285) and genetic liability (using polygenic scores, n = 185) as well as ASD and ADHD-relevant temperament traits at 2 years of age (shyness and inhibitory control, respectively, n = 272) and ASD and ADHD clinical traits at 6 years of age (n = 94).Results showed that longer peak looks at the face were associated with elevated polygenic scores for ADHD (β = 0.078, p = .023), but not ASD (β = 0.002, p = .944), and with elevated ADHD traits in mid-childhood (F(1,88) = 6.401, p = .013, $\eta _p^2$=0.068; ASD: F (1,88) = 3.218, p = .076), but not in toddlerhood (ps > 0.2). This pattern of results did not emerge when considering mean peak look duration across face and nonface stimuli. Thus, alterations in attention to faces during spontaneous visual exploration may be more consistent with a developmental endophenotype of ADHD than ASD. Our work shows that dissecting paths to neurodevelopmental conditions requires longitudinal data incorporating polygenic contribution, early neurocognitive function, and clinical phenotypic variation.
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88
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Sudre G, Frederick J, Sharp W, Ishii-Takahashi A, Mangalmurti A, Choudhury S, Shaw P. Mapping associations between polygenic risks for childhood neuropsychiatric disorders, symptoms of attention deficit hyperactivity disorder, cognition, and the brain. Mol Psychiatry 2020; 25:2482-2492. [PMID: 30700802 PMCID: PMC6667324 DOI: 10.1038/s41380-019-0350-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 11/16/2018] [Accepted: 11/26/2018] [Indexed: 12/29/2022]
Abstract
There are now large-scale data on which common genetic variants confer risk for attention deficit hyperactivity disorder (ADHD). Here, we use mediation analyses to explore how cognitive and neural features might explain the association between common variant (polygenic) risk for ADHD and its core symptoms. In total, 544 participants participated (mean 21 years, 212 (39%) with ADHD), most with cognitive assessments, neuroanatomic imaging, and imaging of white matter tract microstructure. We found that polygenic risk for ADHD was associated with symptoms of hyperactivity-impulsivity but not inattention. This association was mediated across multiple PRS thresholds by white matter microstructure, specifically by axial diffusivity of the right corona radiata, (maximum indirect effect β = -0.034 (CI: -0.065 to -0.01), by thickness of the left dorsomedial prefrontal (β = -0.029; CI: -0.061 to -0.0047) and area of the right lateral temporal cortex (β = 0.024; CI: 0.0034-0.054). In addition, modest serial mediation was found, mapping a pathway from polygenic risk, to white matter microstructure of the anterior corona radiata, then cognition (working memory, focused attention), and finally to hyperactivity-impulsivity (working memory β = -0.014 (CI: -0.038 to -0.0026); focused attention β = -0.011 (CI: -0.033 to -0.0017). These mediation pathways were diagnostically specific and were not found for polygenic risk for ASD or schizophrenia. In conclusion, using a deeply phenotyped cohort, we delineate a pathway from polygenic risk for ADHD to hyperactive-impulsive symptoms through white matter microstructure, cortical anatomy, and cognition.
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Affiliation(s)
- Gustavo Sudre
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, NHGRI/NIH, Bethesda, Bethesda, MD, 20892, USA
| | - Jennifer Frederick
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, NHGRI/NIH, Bethesda, Bethesda, MD, 20892, USA
| | - Wendy Sharp
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, NHGRI/NIH, Bethesda, Bethesda, MD, 20892, USA
| | - Ayaka Ishii-Takahashi
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, NHGRI/NIH, Bethesda, Bethesda, MD, 20892, USA
| | - Aman Mangalmurti
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, NHGRI/NIH, Bethesda, Bethesda, MD, 20892, USA
| | - Saadia Choudhury
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, NHGRI/NIH, Bethesda, Bethesda, MD, 20892, USA
| | - Philip Shaw
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, NHGRI/NIH, Bethesda, Bethesda, MD, 20892, USA.
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89
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Ritchie SJ, Hill WD, Marioni RE, Davies G, Hagenaars SP, Harris SE, Cox SR, Taylor AM, Corley J, Pattie A, Redmond P, Starr JM, Deary IJ. Polygenic predictors of age-related decline in cognitive ability. Mol Psychiatry 2020; 25:2584-2598. [PMID: 30760887 PMCID: PMC7515838 DOI: 10.1038/s41380-019-0372-x] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 11/13/2018] [Accepted: 01/11/2019] [Indexed: 12/11/2022]
Abstract
Polygenic scores can be used to distil the knowledge gained in genome-wide association studies for prediction of health, lifestyle, and psychological factors in independent samples. In this preregistered study, we used fourteen polygenic scores to predict variation in cognitive ability level at age 70, and cognitive change from age 70 to age 79, in the longitudinal Lothian Birth Cohort 1936 study. The polygenic scores were created for phenotypes that have been suggested as risk or protective factors for cognitive ageing. Cognitive abilities within older age were indexed using a latent general factor estimated from thirteen varied cognitive tests taken at four waves, each three years apart (initial n = 1091 age 70; final n = 550 age 79). The general factor indexed over two-thirds of the variance in longitudinal cognitive change. We ran additional analyses using an age-11 intelligence test to index cognitive change from age 11 to age 70. Several polygenic scores were associated with the level of cognitive ability at age-70 baseline (range of standardized β-values = -0.178 to 0.302), and the polygenic score for education was associated with cognitive change from childhood to age 70 (standardized β = 0.100). No polygenic scores were statistically significantly associated with variation in cognitive change between ages 70 and 79, and effect sizes were small. However, APOE e4 status made a significant prediction of the rate of cognitive decline from age 70 to 79 (standardized β = -0.319 for carriers vs. non-carriers). The results suggest that the predictive validity for cognitive ageing of polygenic scores derived from genome-wide association study summary statistics is not yet on a par with APOE e4, a better-established predictor.
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Affiliation(s)
- Stuart J Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.
- Department of Psychology, The University of Edinburgh, Edinburgh, UK.
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK.
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Saskia P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Adele M Taylor
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Alison Pattie
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
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90
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Andrews SJ, McFall GP, Booth A, Dixon RA, Anstey KJ. Association of Alzheimer's Disease Genetic Risk Loci with Cognitive Performance and Decline: A Systematic Review. J Alzheimers Dis 2020; 69:1109-1136. [PMID: 31156182 DOI: 10.3233/jad-190342] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The association of Apolipoprotein E (APOE) with late-onset Alzheimer's disease (LOAD) and cognitive endophenotypes of aging has been widely investigated. There is increasing interest in evaluating the association of other LOAD risk loci with cognitive performance and decline. The results of these studies have been inconsistent and inconclusive. We conducted a systematic review of studies investigating the association of non-APOE LOAD risk loci with cognitive performance in older adults. Studies published from January 2009 to April 2018 were identified through a PubMed database search using keywords and by scanning reference lists. Studies were included if they were either cross-sectional or longitudinal in design, included at least one genome-wide significant LOAD risk loci or a genetic risk score, and had one objective measure of cognition. Quality assessment of the studies was conducted using the quality of genetic studies (Q-Genie) tool. Of 2,466 studies reviewed, 49 met inclusion criteria. Fifteen percent of the associations between non-APOE LOAD risk loci and cognition were significant. However, these associations were not replicated across studies, and the majority were rendered non-significant when adjusting for multiple testing. One-third of the studies included genetic risk scores, and these were typically significant only when APOE was included. The findings of this systematic review do not support a consistent association between individual non-APOE LOAD risk and cognitive performance or decline. However, evidence suggests that aggregate LOAD genetic risk exerts deleterious effects on decline in episodic memory and global cognition.
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Affiliation(s)
- Shea J Andrews
- Ronald M. Loeb Center for Alzheimer's disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - G Peggy McFall
- Department of Psychology, University of Alberta, Edmonton, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Andrew Booth
- School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - Roger A Dixon
- Department of Psychology, University of Alberta, Edmonton, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Kaarin J Anstey
- UNSW Ageing Futures Institute, University of New South Wales, Australia.,School of Psychology, University of New South Wales, Australia.,Neuroscience Research Australia, Australia
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91
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Zhang L, Tang L, Xia K, Huang T, Fan D. Education, intelligence, and amyotrophic lateral sclerosis: A Mendelian randomization study. Ann Clin Transl Neurol 2020; 7:1642-1647. [PMID: 32810387 PMCID: PMC7480912 DOI: 10.1002/acn3.51156] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/25/2020] [Accepted: 07/09/2020] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE To systematically investigate causal relationships between educational attainment, cognitive-related phenotypes, and amyotrophic lateral sclerosis (ALS). METHODS Summary statistics from genome-wide association studies for educational attainment, math ability, highest math class taken, cognitive performance, intelligence, and ALS were used. A two-sample Mendelian randomization (MR) design was applied to explore the potential causal associations between them. RESULTS Genetically predisposition to longer educational attainment and harder math class taken were associated with significantly lower statistical odds ratio of ALS. For per year increase in education completed there was a 21% lower (95% confidence interval [CI] = 27-14%) in risk for ALS. For per 1-SD increase in the highest math class taken obtained there was a 19% lower (95% CI = 9-28%) in risk for ALS. Genetically predisposition to math ability, cognitive performance, and intelligence did not decrease the risk of ALS. INTERPRETATION This study provides genetic support for a causal association between higher educational attainment and a lower risk of ALS. The genes related to these phenotypes are involved in almost all aspects of neuron-to-neuron communication. ALS patients are occasionally accompanied by varying degrees of cognitive impairment. People with greater cognitive reserve may be better able to offset damages of degenerative brain changes associated with dementia or other brain diseases, such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, or ALS.
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Affiliation(s)
- Linjing Zhang
- Department of Neurology, Peking University Third Hospital, Beijing, China
| | - Lu Tang
- Department of Neurology, Peking University Third Hospital, Beijing, China
| | - Kailin Xia
- Department of Neurology, Peking University Third Hospital, Beijing, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.,Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, China
| | - Dongsheng Fan
- Department of Neurology, Peking University Third Hospital, Beijing, China.,Key Laboratory for Neuroscience, National Health Commission/Ministry of Education, Peking University, Beijing, China
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92
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Cornelis MC, Weintraub S, Morris MC. Caffeinated Coffee and Tea Consumption, Genetic Variation and Cognitive Function in the UK Biobank. J Nutr 2020; 150:2164-2174. [PMID: 32495843 PMCID: PMC7398783 DOI: 10.1093/jn/nxaa147] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 03/25/2020] [Accepted: 05/01/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Coffee and tea are the major contributors of caffeine in the diet. Evidence points to the premise that caffeine may benefit cognition. OBJECTIVE We examined the associations of habitual regular coffee or tea and caffeine intake with cognitive function whilst additionally accounting for genetic variation in caffeine metabolism. METHODS We included white participants aged 37-73 y from the UK Biobank who provided biological samples and completed touchscreen questionnaires regarding sociodemographic factors, medical history, lifestyle, and diet. Habitual caffeine-containing coffee and tea intake was self-reported in cups/day and used to estimate caffeine intake. Between 97,369 and 445,786 participants with data also completed ≥1 of 7 self-administered cognitive functioning tests using a touchscreen system (2006-2010) or on home computers (2014). Multivariable regressions were used to examine the association between coffee, tea, or caffeine intake and cognition test scores. We also tested interactions between coffee, tea, or caffeine intake and a genetic-based caffeine-metabolism score (CMS) on cognitive function. RESULTS After multivariable adjustment, reaction time, Pairs Matching, Trail Making test B, and symbol digit substitution, performance significantly decreased with consumption of 1 or more cups of coffee (all tests P-trend < 0.0001). Tea consumption was associated with poor performance on all tests (P-trend < 0.0001). No statistically significant CMS × tea, CMS × coffee, or CMS × caffeine interactions were observed. CONCLUSIONS Our findings, based on the participants of the UK Biobank, provide little support for habitual consumption of regular coffee or tea and caffeine in improving cognitive function. On the contrary, we observed decrements in performance with intakes of these beverages which may be a result of confounding. Whether habitual caffeine intake affects cognitive function therefore remains to be tested.
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Affiliation(s)
- Marilyn C Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Sandra Weintraub
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, USA,Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Martha Clare Morris
- Rush Institute for Healthy Aging, Rush University, Chicago, IL, USA,Address correspondence to MCC (e-mail: )
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93
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Dalsgaard S, McGrath J, Østergaard SD, Wray NR, Pedersen CB, Mortensen PB, Petersen L. Association of Mental Disorder in Childhood and Adolescence With Subsequent Educational Achievement. JAMA Psychiatry 2020; 77:797-805. [PMID: 32211833 PMCID: PMC7097843 DOI: 10.1001/jamapsychiatry.2020.0217] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
IMPORTANCE Onset of mental disorders during childhood or adolescence has been associated with underperformance in school and impairment in social and occupational life in adulthood, which has important implications for the affected individuals and society. OBJECTIVE To compare the educational achievements at the final examination of compulsory schooling in Denmark between individuals with and those without a mental disorder. DESIGN, SETTING, AND PARTICIPANTS This population-based cohort study was conducted in Denmark and obtained data from the Danish Civil Registration System and other nationwide registers. The 2 cohorts studied were (1) all children who were born in Denmark between January 1, 1988, and July 1, 1999, and were alive at age 17 years (n = 629 622) and (2) all children who took the final examination at the end of ninth grade in both Danish and mathematics subjects between January 1, 2002, and December 31, 2016 (n = 542 500). Data analysis was conducted from March 1, 2018, to March 1, 2019. EXPOSURES Clinical diagnosis by a psychiatrist of any mental disorder or 1 of 29 specific mental disorders before age 16 years. MAIN OUTCOMES AND MEASURES Taking the final examination at the end of ninth grade and mean examination grades standardized as z scores with differences measured in SDs (standardized mean grade difference). RESULTS Of the total study population (n = 629 622; 306 209 female and 323 413 male), 523 312 individuals (83%) took the final examination before 17 years of age and 38 001 (6%) had a mental disorder before that age. Among the 542 500 individuals (274 332 female and 268 168 male), the mean (SD) age was 16.1 (0.33) years for the females and 16.2 (0.34) years for the males. Among the 15 843 female and 22 158 male students with a mental disorder, a lower proportion took the final examination (0.52; 95% CI, 0.52-0.53) compared with individuals without a mental disorder (0.88; 95% CI, 0.88-0.88). Mental disorders affected the grades of male individuals (standardized mean grade difference, -0.30; 95% CI, -0.32 to -0.28) more than the grades of their female peers (standardized mean grade difference, -0.24; 95% CI, -0.25 to -0.22) when compared with same-sex individuals without mental disorders. Most specific mental disorders were associated with statistically significantly lower mean grades, with intellectual disability associated with the lowest grade in female and male students (standardized mean grade difference, -1.07 [95% CI, -1.23 to -0.91] and -1.03 [95% CI, -1.17 to -0.89]; P = .76 for sex differences in the mean grades). Female and male students with anorexia nervosa achieved statistically significantly higher grades on the final examination (standardized mean grade difference, 0.38 [95% CI, 0.32-0.44] and 0.31 [95% CI, 0.11-0.52]; P = .54 for sex differences in the mean grades) compared with their peers without this disorder. For those with anxiety, attachment, attention-deficit/hyperactivity, and other developmental disorders, female individuals attained relatively lower standardized mean grades compared with their male counterparts. CONCLUSIONS AND RELEVANCE Results of this study suggest that, in Denmark, almost all mental disorders in childhood or adolescence may be associated with a lower likelihood of taking the final examination at the end of ninth grade; those with specific disorders tended to achieve lower mean grades on the examination; and female, compared with male, individuals with certain mental disorders appeared to have relatively more impairment. These findings appear to emphasize the need to provide educational support to young people with mental disorders.
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Affiliation(s)
- Søren Dalsgaard
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark,The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
| | - John McGrath
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark,Queensland Brain Institute, The University of Queensland, St Lucia, Brisbane, Queensland, Australia,Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Richlands, Queensland, Australia
| | - Søren Dinesen Østergaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark,Department of Affective Disorders, Aarhus University Hospital–Psychiatry, Aarhus, Denmark,Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Naomi R. Wray
- Queensland Brain Institute, The University of Queensland, St Lucia, Brisbane, Queensland, Australia
| | - Carsten Bøcker Pedersen
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark,The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark,Centre for Integrated Register-Based Research at Aarhus University, Aarhus, Denmark
| | - Preben Bo Mortensen
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark,The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark,Centre for Integrated Register-Based Research at Aarhus University, Aarhus, Denmark
| | - Liselotte Petersen
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark,The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
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94
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The Course of Neurocognitive Functioning and Prediction of Behavioral Outcome of ADHD Affected and Unaffected Siblings. JOURNAL OF ABNORMAL CHILD PSYCHOLOGY 2020; 47:405-419. [PMID: 30079436 PMCID: PMC6397140 DOI: 10.1007/s10802-018-0449-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
Longitudinal studies on the course of neurocognitive functioning of children with ADHD and their unaffected siblings are scarce. Also, it is unclear to what extent that course is related to ADHD outcomes. A carefully phenotyped large sample of 838 Caucasian participants (ADHD-combined type: n = 339, unaffected siblings: n = 271, controls: n = 228; mean age at baseline = 11.4 years, mean age at follow-up = 17.3 years, SD = 3.2) was used to investigate differences in the course of neurocognitive functioning of ADHD affected and unaffected siblings versus controls, and to investigate the relationship between neurocognitive change and ADHD outcomes. At baseline, an aggregated measure of overall neurocognitive functioning and eight neurocognitive measures of working memory, timing (speed/variability), motor control, and intelligence were investigated. Outcomes at follow-up were dimensional measures of ADHD symptom severity and the Kiddie-Global Assessment Scale (K-GAS) for overall functioning. At follow up, affected and unaffected siblings trended to, or fully caught up with performance levels of controls on four (44.4%) and five (55.6%) of the nine dependent variables, respectively. In contrast, performance in remaining key neurocognitive measures (i.e. verbal working memory, variability in responding) remained impaired at follow-up. Change in neurocognitive functioning was not related to ADHD outcomes. Our results question the etiological link between neurocognitive deficits and ADHD outcomes in adolescents and young adults.
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95
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Kauppi K, Rönnlund M, Nordin Adolfsson A, Pudas S, Adolfsson R. Effects of polygenic risk for Alzheimer's disease on rate of cognitive decline in normal aging. Transl Psychiatry 2020; 10:250. [PMID: 32709845 PMCID: PMC7381667 DOI: 10.1038/s41398-020-00934-y] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 06/24/2020] [Accepted: 07/09/2020] [Indexed: 12/11/2022] Open
Abstract
Most people's cognitive abilities decline with age, with significant and partly genetically driven, individual differences in rate of change. Although APOE ɛ4 and genetic scores for late-onset Alzheimer's disease (LOAD) have been related to cognitive decline during preclinical stages of dementia, there is limited knowledge concerning genetic factors implied in normal cognitive aging. In the present study, we examined three potential genetic predictors of age-related cognitive decline as follows: (1) the APOE ɛ4 allele, (2) a polygenic score for general cognitive ability (PGS-cog), and (3) a polygenic risk score for late-onset AD (PRS-LOAD). We examined up to six time points of cognitive measurements in the longitudinal population-based Betula study, covering a 25-year follow-up period. Only participants that remained alive and non-demented until the most recent dementia screening (1-3 years after the last test occasion) were included (n = 1087). Individual differences in rate of cognitive change (composite score) were predicted by the PRS-LOAD and APOE ɛ4, but not by PGS-cog. To control for the possibility that the results reflected a preclinical state of Alzheimer's disease in some participants, we re-ran the analyses excluding cognitive data from the last test occasion to model cognitive change up-until a minimum of 6 years before potential onset of clinical Alzheimers. Strikingly, the association of PRS-LOAD, but not APOE ɛ4, with cognitive change remained. The results indicate that PRS-LOAD predicts individual difference in rate of cognitive decline in normal aging, but it remains to be determined to what extent this reflects preclinical Alzheimer's disease brain pathophysiology and subsequent risk to develop the disease.
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Affiliation(s)
- Karolina Kauppi
- Department of Integrative Medical Biologi, Umeå University, Umeå, Sweden. .,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Michael Rönnlund
- grid.12650.300000 0001 1034 3451Department of Psychology, Umeå University, Umeå, Sweden
| | | | - Sara Pudas
- grid.12650.300000 0001 1034 3451Department of Integrative Medical Biologi, Umeå University, Umeå, Sweden
| | - Rolf Adolfsson
- grid.12650.300000 0001 1034 3451Department of Clinical Sciences, Umeå University, Umeå, Sweden
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96
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Recent Caffeine Drinking Associates with Cognitive Function in the UK Biobank. Nutrients 2020; 12:nu12071969. [PMID: 32630669 PMCID: PMC7399821 DOI: 10.3390/nu12071969] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 06/16/2020] [Accepted: 06/29/2020] [Indexed: 11/17/2022] Open
Abstract
Clinical evidence points to the premise that caffeine may benefit cognition, but whether these findings extend to real life settings and amidst factors that impact caffeine metabolism is unclear. The aim of this study was to investigate the impact of recent caffeine drinking on cognitive ability while additionally accounting for lifestyle and genetic factors that impact caffeine metabolism. We included up to 434,900 UK Biobank participants aged 37–73 years, recruited in 2006–2010, who provided biological samples and completed touchscreen questionnaires regarding sociodemographic factors, medical history, lifestyle, and diet. Recent caffeine drinking (yes/no in the last hour) was recorded during a physical assessment. Participants completed at least one of four self-administered cognitive function tests using the touchscreen system: prospective memory (PM), pairs matching (Pairs), fluid intelligence (FI), and reaction time (RT). Multivariable regressions were used to examine the association between recent caffeine drinking and cognition test scores. We also tested interactions between recent caffeine drinking and a genetic caffeine-metabolism score (CMS) on cognitive function. Among white participants, recent caffeine drinking was associated with higher performance on RT but lower performance on FI, Pairs, and PM (p ≤ 0.004). Similar directions of associations for FI (p = 0.09), Pairs (p = 0.03), and PM (p = 0.34) were observed among non-white participants. No significant and consistent effect modification by age, sex, smoking, test time, habitual caffeine intake, or CMS was observed. Caffeine consumed shortly before tasks requiring shorter reaction times may improve task performance. Potential impairments in memory and reasoning tasks with recent caffeine drinking warrant further study.
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Harris MA, Shen X, Cox SR, Gibson J, Adams MJ, Clarke TK, Deary IJ, Lawrie SM, McIntosh AM, Whalley HC. Stratifying major depressive disorder by polygenic risk for schizophrenia in relation to structural brain measures. Psychol Med 2020; 50:1653-1662. [PMID: 31317844 DOI: 10.1017/s003329171900165x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Substantial clinical heterogeneity of major depressive disorder (MDD) suggests it may group together individuals with diverse aetiologies. Identifying distinct subtypes should lead to more effective diagnosis and treatment, while providing more useful targets for further research. Genetic and clinical overlap between MDD and schizophrenia (SCZ) suggests an MDD subtype may share underlying mechanisms with SCZ. METHODS The present study investigated whether a neurobiologically distinct subtype of MDD could be identified by SCZ polygenic risk score (PRS). We explored interactive effects between SCZ PRS and MDD case/control status on a range of cortical, subcortical and white matter metrics among 2370 male and 2574 female UK Biobank participants. RESULTS There was a significant SCZ PRS by MDD interaction for rostral anterior cingulate cortex (RACC) thickness (β = 0.191, q = 0.043). This was driven by a positive association between SCZ PRS and RACC thickness among MDD cases (β = 0.098, p = 0.026), compared to a negative association among controls (β = -0.087, p = 0.002). MDD cases with low SCZ PRS showed thinner RACC, although the opposite difference for high-SCZ-PRS cases was not significant. There were nominal interactions for other brain metrics, but none remained significant after correcting for multiple comparisons. CONCLUSIONS Our significant results indicate that MDD case-control differences in RACC thickness vary as a function of SCZ PRS. Although this was not the case for most other brain measures assessed, our specific findings still provide some further evidence that MDD in the presence of high genetic risk for SCZ is subtly neurobiologically distinct from MDD in general.
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Affiliation(s)
- Mathew A Harris
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Jude Gibson
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | | | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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98
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Richardson K. Polygenic scores are an even bigger social hazard: Commentary on: Baverstock, K. (2019) polygenic scores: Are they a public health hazard? Progress in Biophysics and Molecular Biology. Available online 6 August 2019. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2020; 153:13-16. [PMID: 31887314 DOI: 10.1016/j.pbiomolbio.2019.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Revised: 12/16/2019] [Accepted: 12/18/2019] [Indexed: 06/10/2023]
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99
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100
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Davies NM, Howe LJ, Brumpton B, Havdahl A, Evans DM, Davey Smith G. Within family Mendelian randomization studies. Hum Mol Genet 2020; 28:R170-R179. [PMID: 31647093 DOI: 10.1093/hmg/ddz204] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 08/13/2019] [Accepted: 08/14/2019] [Indexed: 01/08/2023] Open
Abstract
Mendelian randomization (MR) is increasingly used to make causal inferences in a wide range of fields, from drug development to etiologic studies. Causal inference in MR is possible because of the process of genetic inheritance from parents to offspring. Specifically, at gamete formation and conception, meiosis ensures random allocation to the offspring of one allele from each parent at each locus, and these are unrelated to most of the other inherited genetic variants. To date, most MR studies have used data from unrelated individuals. These studies assume that genotypes are independent of the environment across a sample of unrelated individuals, conditional on covariates. Here we describe potential sources of bias, such as transmission ratio distortion, selection bias, population stratification, dynastic effects and assortative mating that can induce spurious or biased SNP-phenotype associations. We explain how studies of related individuals such as sibling pairs or parent-offspring trios can be used to overcome some of these sources of bias, to provide potentially more reliable evidence regarding causal processes. The increasing availability of data from related individuals in large cohort studies presents an opportunity to both overcome some of these biases and also to evaluate familial environmental effects.
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Affiliation(s)
- Neil M Davies
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, United Kingdom.,Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom
| | - Laurence J Howe
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, United Kingdom.,Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom
| | - Ben Brumpton
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, United Kingdom.,K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.,Clinic of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Alexandra Havdahl
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, United Kingdom.,Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway.,Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - David M Evans
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, United Kingdom.,University of Queensland Diamantina Institute, University of Queensland, Brisbane, 4102, Australia
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, United Kingdom.,Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom
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