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Huang Y, Jia Z, Lu X, Wang Y, Li R, Zhou A, Chen L, Wang Y, Zeng HC, Li P, Ghassabian A, Yuan N, Kong F, Xu S, Liu H. Prenatal Exposure to Per- and Polyfluoroalkyl Substances and ASD-Related Symptoms in Early Childhood: Mediation Role of Steroids. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:16291-16301. [PMID: 39226190 DOI: 10.1021/acs.est.4c04500] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Previous studies regarding the associations between perfluoroalkyl and polyfluoroalkyl substances (PFAS) and autism spectrum disorder (ASD) have yielded inconsistent results, with the underlying mechanisms remaining unknown. In this study, we quantified 13 PFAS in cord serum samples from 396 neonates and followed the children at age 4 to assess ASD-related symptoms. Our findings revealed associations between certain PFAS and ASD-related symptoms, with a doubling of perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), and perfluoroundecanoic acid (PFUnDA) concentrations associated with respective increases of 1.79, 1.62, and 1.45 units in language-related symptoms and PFDA exhibiting an association with higher score of sensory stimuli. Nonlinear associations were observed in the associations of 6:2 chlorinated polyfluorinated ether sulfonate (Cl-PFAES) and 8:2 Cl-PFAES with ASD-related symptoms. Employing weighted quantile sum (WQS) regression, we observed significant mixture effects of multiple PFAS on all domains of ASD-related symptoms, with PFNA emerging as the most substantial contributor. Assuming causality, we found that 39-40% of the estimated effect of long-chain PFAS (PFUnDA and PFDoDA) exposure on sensory stimuli was mediated by androstenedione. This study provides novel epidemiological data about prenatal PFAS mixture exposure and ASD-related symptoms.
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Affiliation(s)
- Yun Huang
- Key Laboratory of Environment and Health (HUST), Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Zhenxian Jia
- Key Laboratory of Environment and Health (HUST), Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Xinhe Lu
- School of Environmental Science and Engineering, Hainan University, Haikou 570228, Hainan, China
| | - Yin Wang
- Key Laboratory of Environment and Health (HUST), Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Ruizhen Li
- Women and Children Medical and Healthcare Center of Wuhan, Wuhan 430016, Hubei, China
| | - Aifen Zhou
- Women and Children Medical and Healthcare Center of Wuhan, Wuhan 430016, Hubei, China
| | - Lei Chen
- Women and Children Medical and Healthcare Center of Wuhan, Wuhan 430016, Hubei, China
| | - Yuyan Wang
- Department of Population Health, New York University Grossman School of Medicine, 10016 New York, New York, United States
| | - Huai-Cai Zeng
- School of Public Health, Guilin Medical University, Guilin 541199, Guangxi, China
| | - Pei Li
- Department of Physiology and Biophysics, University of New York at Buffalo, 14260 New York, New York, United States
| | - Akhgar Ghassabian
- Department of Population Health, New York University Grossman School of Medicine, 10016 New York, New York, United States
| | - Ningxue Yuan
- Key Laboratory of Environment and Health (HUST), Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Fanjuan Kong
- Medical Record Management Department, Maternal and Child Health Hospital of Hunan Province, Changsha 410008, Hunan, China
| | - Shunqing Xu
- Key Laboratory of Environment and Health (HUST), Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
- School of Environmental Science and Engineering, Hainan University, Haikou 570228, Hainan, China
| | - Hongxiu Liu
- Key Laboratory of Environment and Health (HUST), Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
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Faquih T, Potts K, Yu B, Kaplan R, Isasi CR, Qi Q, Taylor KD, Liu PY, Tracy RP, Johnson C, Rich SS, Clish CB, Gerzsten RE, Rotter JI, Redline S, Sofer T, Wang H. Steroid Hormone Biosynthesis and Dietary Related Metabolites Associated with Excessive Daytime Sleepiness. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.12.24313561. [PMID: 39314973 PMCID: PMC11419218 DOI: 10.1101/2024.09.12.24313561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Background Excessive daytime sleepiness (EDS) is a complex sleep problem that affects approximately 33% of the United States population. Although EDS usually occurs in conjunction with insufficient sleep, and other sleep and circadian disorders, recent studies have shown unique genetic markers and metabolic pathways underlying EDS. Here, we aimed to further elucidate the biological profile of EDS using large scale single- and pathway-level metabolomics analyses. Methods Metabolomics data were available for 877 metabolites in 6,071 individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) and EDS was assessed using the Epworth Sleepiness Scale (ESS) questionnaire. We performed linear regression for each metabolite on continuous ESS, adjusting for demographic, lifestyle, and physiological confounders, and in sex specific groups. Subsequently, gaussian graphical modelling was performed coupled with pathway and enrichment analyses to generate a holistic interactive network of the metabolomic profile of EDS associations. Findings We identified seven metabolites belonging to steroids, sphingomyelin, and long chain fatty acids sub-pathways in the primary model associated with EDS, and an additional three metabolites in the male-specific analysis. The identified metabolites particularly played a role in steroid hormone biosynthesis. Interpretation Our findings indicate that an EDS metabolomic profile is characterized by endogenous and dietary metabolites within the steroid hormone biosynthesis pathway, with some pathways that differ by sex. Our findings identify potential pathways to target for addressing the causes or consequences of EDS and related sleep disorders. Funding Details regarding funding supporting this work and all studies involved are provided in the acknowledgments section.
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Affiliation(s)
- Tariq Faquih
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
- CardioVascular Institute (CVI), Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Sleep Medicine, Harvard University Medical School, Boston, MA, USA
| | - Kaitlin Potts
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard University Medical School, Boston, MA, USA
| | - Bing Yu
- Department of Epidemiology, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Carmen R Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Qibin Qi
- Department of Epidemiology, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kent D Taylor
- Department of Paediatrics, Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation, Harbor-UCLA Medical Centre, Torrance, CA, USA
| | - Peter Y Liu
- Department of Paediatrics, Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation, Harbor-UCLA Medical Centre, Torrance, CA, USA
| | - Russell P Tracy
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
| | - Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, USA
| | - Stephen S Rich
- Centre for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Clary B Clish
- Metabolite Profiling Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Robert E Gerzsten
- Broad Institute, Cambridge, MA, USA
- CardioVascular Institute (CVI), Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jerome I Rotter
- Department of Paediatrics, Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation, Harbor-UCLA Medical Centre, Torrance, CA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard University Medical School, Boston, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- CardioVascular Institute (CVI), Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Sleep Medicine, Harvard University Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
- Division of Sleep Medicine, Harvard University Medical School, Boston, MA, USA
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de Hoyos L, Verhoef E, Okbay A, Vermeulen JR, Figaroa C, Lense M, Fisher SE, Gordon RL, St Pourcain B. Preschool musicality is associated with school-age communication abilities through genes related to rhythmicity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.09.611603. [PMID: 39314312 PMCID: PMC11419103 DOI: 10.1101/2024.09.09.611603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Early-life musical engagement is an understudied but developmentally important and heritable precursor of later (social) communication and language abilities. This study aims to uncover the aetiological mechanisms linking musical to communication abilities. We derived polygenic scores (PGS) for self-reported beat synchronisation abilities (PGSrhythmicity) in children (N≤6,737) from the Avon Longitudinal Study of Parents and Children and tested their association with preschool musical (0.5-5 years) and school-age (social) communication and cognition-related abilities (9-12 years). We further assessed whether relationships between preschool musicality and school-age communication are shared through PGSrhythmicity, using structural equation modelling techniques. PGSrhythmicity were associated with preschool musicality (Nagelkerke-R2=0.70-0.79%), and school-age communication and cognition-related abilities (R2=0.08-0.41%), but not social communication. We identified links between preschool musicality and school-age speech- and syntax-related communication abilities as captured by known genetic influences underlying rhythmicity (shared effect β=0.0065(SE=0.0021), p=0.0016), above and beyond general cognition, strengthening support for early music intervention programmes.
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Affiliation(s)
- Lucía de Hoyos
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Ellen Verhoef
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Janne R Vermeulen
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Celeste Figaroa
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Miriam Lense
- Blair School of Music, Vanderbilt University, Nashville, TN, USA
- Department of Otolaryngology - Head & Neck Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Hearing and Speech Sciences, Vanderbilt University, Nashville, TN, USA
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Reyna L Gordon
- Blair School of Music, Vanderbilt University, Nashville, TN, USA
- Department of Otolaryngology - Head & Neck Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Hearing and Speech Sciences, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Beate St Pourcain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
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Poortman SR, Barendse ME, Setiaman N, van den Heuvel MP, de Lange SC, Hillegers MH, van Haren NE. Age Trajectories of the Structural Connectome in Child and Adolescent Offspring of Individuals With Bipolar Disorder or Schizophrenia. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100336. [PMID: 39040431 PMCID: PMC11260845 DOI: 10.1016/j.bpsgos.2024.100336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 04/08/2024] [Accepted: 05/09/2024] [Indexed: 07/24/2024] Open
Abstract
Background Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at elevated risk of developing psychiatric illness owing to both genetic predisposition and increased burden of environmental stress. Emerging evidence indicates a disruption of brain network connectivity in young offspring of patients with bipolar disorder and schizophrenia, but the age trajectories of these brain networks in this high-familial-risk population remain to be elucidated. Methods A total of 271 T1-weighted and diffusion-weighted scans were obtained from 174 offspring of at least 1 parent diagnosed with bipolar disorder (n = 74) or schizophrenia (n = 51) and offspring of parents without severe mental illness (n = 49). The age range was 8 to 23 years; 97 offspring underwent 2 scans. Anatomical brain networks were reconstructed into structural connectivity matrices. Network analysis was performed to investigate anatomical brain connectivity. Results Offspring of parents with schizophrenia had differential trajectories of connectivity strength and clustering compared with offspring of parents with bipolar disorder and parents without severe mental illness, of global efficiency compared with offspring of parents without severe mental illness, and of local connectivity compared with offspring of parents with bipolar disorder. Conclusions The findings of this study suggest that familial high risk of schizophrenia is related to deviations in age trajectories of global structural connectome properties and local connectivity strength.
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Affiliation(s)
- Simon R. Poortman
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
| | - Marjolein E.A. Barendse
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
| | - Nikita Setiaman
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, the Netherlands
| | - Martijn P. van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Department of Child Psychiatry, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Siemon C. de Lange
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Manon H.J. Hillegers
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, the Netherlands
| | - Neeltje E.M. van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, the Netherlands
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Wijnen CL, Botet R, van de Belt J, Deurhof L, de Jong H, de Snoo CB, Dirks R, Boer MP, van Eeuwijk FA, Wijnker E, Keurentjes JJB. A complete chromosome substitution mapping panel reveals genome-wide epistasis in Arabidopsis. Heredity (Edinb) 2024; 133:198-205. [PMID: 38982296 PMCID: PMC11350127 DOI: 10.1038/s41437-024-00705-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 07/02/2024] [Accepted: 07/03/2024] [Indexed: 07/11/2024] Open
Abstract
Chromosome substitution lines (CSLs) are tentatively supreme resources to investigate non-allelic genetic interactions. However, the difficulty of generating such lines in most species largely yielded imperfect CSL panels, prohibiting a systematic dissection of epistasis. Here, we present the development and use of a unique and complete panel of CSLs in Arabidopsis thaliana, allowing the full factorial analysis of epistatic interactions. A first comparison of reciprocal single chromosome substitutions revealed a dependency of QTL detection on different genetic backgrounds. The subsequent analysis of the complete panel of CSLs enabled the mapping of the genetic interactors and identified multiple two- and three-way interactions for different traits. Some of the detected epistatic effects were as large as any observed main effect, illustrating the impact of epistasis on quantitative trait variation. We, therefore, have demonstrated the high power of detection and mapping of genome-wide epistasis, confirming the assumed supremacy of comprehensive CSL sets.
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Affiliation(s)
- Cris L Wijnen
- Wageningen University and Research, Laboratory of Genetics, Wageningen, The Netherlands
| | - Ramon Botet
- Wageningen University and Research, Laboratory of Genetics, Wageningen, The Netherlands
| | - José van de Belt
- Wageningen University and Research, Laboratory of Genetics, Wageningen, The Netherlands
| | - Laurens Deurhof
- Wageningen University and Research, Laboratory of Genetics, Wageningen, The Netherlands
| | - Hans de Jong
- Wageningen University and Research, Laboratory of Genetics, Wageningen, The Netherlands
| | | | - Rob Dirks
- Rijk Zwaan, Molecular Biology Research, Fijnaart, The Netherlands
- Managerial Genetics Consulting, Maaseik, Belgium
| | - Martin P Boer
- Wageningen University and Research, Biometris, Wageningen, The Netherlands
| | - Fred A van Eeuwijk
- Wageningen University and Research, Biometris, Wageningen, The Netherlands
| | - Erik Wijnker
- Wageningen University and Research, Laboratory of Genetics, Wageningen, The Netherlands
| | - Joost J B Keurentjes
- Wageningen University and Research, Laboratory of Genetics, Wageningen, The Netherlands.
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Sabag I, Bi Y, Sahoo MM, Herrmann I, Morota G, Peleg Z. Leveraging genomics and temporal high-throughput phenotyping to enhance association mapping and yield prediction in sesame. THE PLANT GENOME 2024; 17:e20481. [PMID: 38926134 DOI: 10.1002/tpg2.20481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 05/16/2024] [Indexed: 06/28/2024]
Abstract
Sesame (Sesamum indicum) is an important oilseed crop with rising demand owing to its nutritional and health benefits. There is an urgent need to develop and integrate new genomic-based breeding strategies to meet these future demands. While genomic resources have advanced genetic research in sesame, the implementation of high-throughput phenotyping and genetic analysis of longitudinal traits remains limited. Here, we combined high-throughput phenotyping and random regression models to investigate the dynamics of plant height, leaf area index, and five spectral vegetation indices throughout the sesame growing seasons in a diversity panel. Modeling the temporal phenotypic and additive genetic trajectories revealed distinct patterns corresponding to the sesame growth cycle. We also conducted longitudinal genomic prediction and association mapping of plant height using various models and cross-validation schemes. Moderate prediction accuracy was obtained when predicting new genotypes at each time point, and moderate to high values were obtained when forecasting future phenotypes. Association mapping revealed three genomic regions in linkage groups 6, 8, and 11, conferring trait variation over time and growth rate. Furthermore, we leveraged correlations between the temporal trait and seed-yield and applied multi-trait genomic prediction. We obtained an improvement over single-trait analysis, especially when phenotypes from earlier time points were used, highlighting the potential of using a high-throughput phenotyping platform as a selection tool. Our results shed light on the genetic control of longitudinal traits in sesame and underscore the potential of high-throughput phenotyping to detect a wide range of traits and genotypes that can inform sesame breeding efforts to enhance yield.
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Affiliation(s)
- Idan Sabag
- The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
- School of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Ye Bi
- School of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Maitreya Mohan Sahoo
- The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Ittai Herrmann
- The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Gota Morota
- School of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
- Center for Advanced Innovation in Agriculture, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Zvi Peleg
- The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
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Visconti A, Rossi N, Bondt A, Ederveen AH, Thareja G, Koeleman CAM, Stephan N, Halama A, Lomax-Browne HJ, Pickering MC, Zhou XJ, Wuhrer M, Suhre K, Falchi M. The genetics and epidemiology of N- and O-immunoglobulin A glycomics. Genome Med 2024; 16:96. [PMID: 39123268 PMCID: PMC11312925 DOI: 10.1186/s13073-024-01369-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 07/26/2024] [Indexed: 08/12/2024] Open
Abstract
BACKGROUND Immunoglobulin (Ig) glycosylation modulates the immune response and plays a critical role in ageing and diseases. Studies have mainly focused on IgG glycosylation, and little is known about the genetics and epidemiology of IgA glycosylation. METHODS We generated, using a novel liquid chromatography-mass spectrometry method, the first large-scale IgA glycomics dataset in serum from 2423 twins, encompassing 71 N- and O-glycan species. RESULTS We showed that, despite the lack of a direct genetic template, glycosylation is highly heritable, and that glycopeptide structures are sex-specific, and undergo substantial changes with ageing. We observe extensive correlations between the IgA and IgG glycomes, and, exploiting the twin design, show that they are predominantly influenced by shared genetic factors. A genome-wide association study identified eight loci associated with both the IgA and IgG glycomes (ST6GAL1, ELL2, B4GALT1, ABCF2, TMEM121, SLC38A10, SMARCB1, and MGAT3) and two novel loci specifically modulating IgA O-glycosylation (C1GALT1 and ST3GAL1). Validation of our findings in an independent cohort of 320 individuals from Qatar showed that the underlying genetic architecture is conserved across ancestries. CONCLUSIONS Our study delineates the genetic landscape of IgA glycosylation and provides novel potential functional links with the aetiology of complex immune diseases, including genetic factors involved in IgA nephropathy risk.
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Affiliation(s)
- Alessia Visconti
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Center for Biostatistics, Epidemiology and Public Health, Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Niccolò Rossi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Albert Bondt
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Agnes Hipgrave Ederveen
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Gaurav Thareja
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Carolien A M Koeleman
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Nisha Stephan
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Anna Halama
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Hannah J Lomax-Browne
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, London, UK
| | - Matthew C Pickering
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, London, UK
| | - Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Beijing, China
- Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Ministry of Education, Peking University, Beijing, China
| | - Manfred Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Mario Falchi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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Tomasi J, Lisoway AJ, Zai CC, Zai G, Richter MA, Sanches M, Herbert D, Mohiuddin AG, Tiwari AK, Kennedy JL. Genetic and polygenic investigation of heart rate variability to identify biomarkers associated with Anxiety disorders. Psychiatry Res 2024; 338:115982. [PMID: 38850888 DOI: 10.1016/j.psychres.2024.115982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 05/11/2024] [Accepted: 05/26/2024] [Indexed: 06/10/2024]
Abstract
Given that anxiety disorders (AD) are associated with reduced vagally-mediated heart rate variability (HRV), genetic variants related to HRV may provide insight into anxiety etiology. This study used polygenic risk scores (PRS) to explore the genetic overlap between AD and HRV, and investigated whether HRV-related polymorphisms influence anxiety risk. Resting vagally-mediated HRV was measured using a wearable device in 188 European individuals (AD=101, healthy controls=87). AD PRS was tested for association with resting HRV, and HRV PRS for association with AD. We also investigated 15 significant hits from an HRV genome-wide association study (GWAS) for association with resting HRV and AD and if this association is mediated through resting HRV. The AD PRS and HRV PRS showed nominally significant associations with resting HRV and anxiety disorders, respectively. HRV GWAS variants associated with resting HRV were rs12980262 (NDUFA11), rs2680344 (HCN4), rs4262 and rs180238 (GNG11), and rs10842383 (LINC00477). Mediation analyses revealed that NDUFA11 rs12980262 A-carriers and GNG11 rs180238 and rs4262 C-carriers had higher anxiety risk through lower HRV. This study supports an anxiety-HRV genetic relationship, with HRV-related genetic variants translating to AD. This study encourages exploration of HRV genetics to understand mechanisms and identify novel treatment targets for anxiety.
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Affiliation(s)
- Julia Tomasi
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada.
| | - Amanda J Lisoway
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Clement C Zai
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Gwyneth Zai
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; General Adult Psychiatry and Health Systems Division, CAMH, Toronto, ON, Canada
| | - Margaret A Richter
- Institute of Medical Science, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Frederick W. Thompson Anxiety Disorders Centre, Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Marcos Sanches
- Biostatistics Core, Centre for Addiction and Mental Health, Toronto, Canada
| | - Deanna Herbert
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Ayeshah G Mohiuddin
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Arun K Tiwari
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada.
| | - James L Kennedy
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada
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59
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Millard LAC, Davey Smith G, Tilling K. Using the global randomization test as a Mendelian randomization falsification test for the exclusion restriction assumption. Eur J Epidemiol 2024; 39:843-855. [PMID: 38421485 PMCID: PMC11410989 DOI: 10.1007/s10654-024-01097-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 01/06/2024] [Indexed: 03/02/2024]
Abstract
Mendelian randomization may give biased causal estimates if the instrument affects the outcome not solely via the exposure of interest (violating the exclusion restriction assumption). We demonstrate use of a global randomization test as a falsification test for the exclusion restriction assumption. Using simulations, we explored the statistical power of the randomization test to detect an association between a genetic instrument and a covariate set due to (a) selection bias or (b) horizontal pleiotropy, compared to three approaches examining associations with individual covariates: (i) Bonferroni correction for the number of covariates, (ii) correction for the effective number of independent covariates, and (iii) an r2 permutation-based approach. We conducted proof-of-principle analyses in UK Biobank, using CRP as the exposure and coronary heart disease (CHD) as the outcome. In simulations, power of the randomization test was higher than the other approaches for detecting selection bias when the correlation between the covariates was low (r2 < 0.1), and at least as powerful as the other approaches across all simulated horizontal pleiotropy scenarios. In our applied example, we found strong evidence of selection bias using all approaches (e.g., global randomization test p < 0.002). We identified 51 of the 58 CRP genetic variants as horizontally pleiotropic, and estimated effects of CRP on CHD attenuated somewhat to the null when excluding these from the genetic risk score (OR = 0.96 [95% CI: 0.92, 1.00] versus 0.97 [95% CI: 0.90, 1.05] per 1-unit higher log CRP levels). The global randomization test can be a useful addition to the MR researcher's toolkit.
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Affiliation(s)
- Louise A C Millard
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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60
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Mahmoudiandehkordi S, Maadooliat M, Schrodi SJ. gwid: an R package and Shiny application for Genome-Wide analysis of IBD data. BIOINFORMATICS ADVANCES 2024; 4:vbae115. [PMID: 39246385 PMCID: PMC11379470 DOI: 10.1093/bioadv/vbae115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 06/13/2024] [Accepted: 07/29/2024] [Indexed: 09/10/2024]
Abstract
Summary Genome-wide identity by descent (gwid) is an R package developed for the analysis of identity-by-descent (IBD) data pertaining to dichotomous traits. This package offers a set of tools to assess differential IBD levels for the two states of a binary trait, yielding informative and meaningful results. Furthermore, it provides convenient functions to visualize the outcomes of these analyses, enhancing the interpretability and accessibility of the results. To assess the performance of the package, we conducted an evaluation using real genotype data derived from the SNPs to investigate rheumatoid arthritis susceptibility from the Marshfield Clinic Personalized Medicine Research Project. Availability and implementation gwid is available as an open-source R package. Release versions can be accessed on CRAN (https://cran.r-project.org/package=gwid) for all major operating systems. The development version is maintained on GitHub (https://github.com/soroushmdg/gwid) and full documentation with examples and workflow templates is provided via the package website (http://tinyurl.com/gwid-tutorial). An interactive R Shiny dashboard is also developed (https://tinyurl.com/gwid-shiny).
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Affiliation(s)
- Soroush Mahmoudiandehkordi
- Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI 53233, United States
- Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI 53706, United States
| | - Mehdi Maadooliat
- Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, WI 53233, United States
- Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI 53706, United States
| | - Steven J Schrodi
- Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI 53706, United States
- Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, WI 53706, United States
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61
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Couch CA, Ament Z, Patki A, Kijpaisalratana N, Bhave V, Jones AC, Armstrong ND, Cheung KL, Kimberly WT, Tiwari HK, Irvin MR. The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) Diet and Metabolites in Chronic Kidney Disease. Nutrients 2024; 16:2458. [PMID: 39125339 PMCID: PMC11314466 DOI: 10.3390/nu16152458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Revised: 07/24/2024] [Accepted: 07/25/2024] [Indexed: 08/12/2024] Open
Abstract
The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) is a hybrid of the Mediterranean and DASH (Dietary Approaches to Stop Hypertension) diets, and its association with renal outcomes remains unclear. In the REasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort, diet data were collected at baseline using food frequency questionnaires. Modified Poisson regression was used to examine the association of MIND diet with incident chronic kidney disease (CKD). In the REGARDS stroke case-cohort, 357 metabolites were measured in baseline plasma. Weighted linear regression was used to test associations between MIND diet and metabolites. Weighted logistic regression was used to test associations between MIND-associated metabolites and incident CKD. Mediation analyses were conducted to determine whether metabolites mediated the relationship between MIND diet and CKD. A higher MIND diet score was associated with a decreased risk of incident CKD (risk ratio 0.90, 95% CI (0.86-0.94); p = 2.03 × 10-7). Fifty-seven metabolites were associated with MIND diet (p < 3 × 10-4). Guanosine was found to mediate the relationship between MIND diet and incident CKD (odds ratio for indirect effects 0.93, 95% CI (0.88-0.97); p < 0.05). These findings suggest a role of the MIND diet in renal outcomes.
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Affiliation(s)
- Catharine A. Couch
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (A.C.J.); (N.D.A.); (M.R.I.)
| | - Zsuzsanna Ament
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA; (Z.A.); (N.K.); (W.T.K.)
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Amit Patki
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35233, USA; (A.P.); (H.K.T.)
| | - Naruchorn Kijpaisalratana
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA; (Z.A.); (N.K.); (W.T.K.)
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Division of Neurology, Department of Medicine and Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Varun Bhave
- Harvard Medical School, Boston, MA 02115, USA;
| | - Alana C. Jones
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (A.C.J.); (N.D.A.); (M.R.I.)
| | - Nicole D. Armstrong
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (A.C.J.); (N.D.A.); (M.R.I.)
| | - Katharine L. Cheung
- Division of Nephrology, Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT 05405-0068, USA;
| | - W. Taylor Kimberly
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA; (Z.A.); (N.K.); (W.T.K.)
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA;
| | - Hemant K. Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35233, USA; (A.P.); (H.K.T.)
| | - Marguerite Ryan Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (A.C.J.); (N.D.A.); (M.R.I.)
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Bhatt RR, Gadewar SP, Shetty A, Ba Gari I, Haddad E, Javid S, Ramesh A, Nourollahimoghadam E, Zhu AH, de Leeuw C, Thompson PM, Medland SE, Jahanshad N. The Genetic Architecture of the Human Corpus Callosum and its Subregions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.22.603147. [PMID: 39091796 PMCID: PMC11291056 DOI: 10.1101/2024.07.22.603147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses, performing associative/executive functions, and representing information in multiple dimensions. Understanding which genetic variants underpin corpus callosum morphometry, and their shared influence on cortical structure and susceptibility to neuropsychiatric disorders, can provide molecular insights into the CC's role in mediating cortical development and its contribution to neuropsychiatric disease. To characterize the morphometry of the midsagittal corpus callosum, we developed a publicly available artificial intelligence based tool to extract, parcellate, and calculate its total and regional area and thickness. Using the UK Biobank (UKB) and the Adolescent Brain Cognitive Development study (ABCD), we extracted measures of midsagittal corpus callosum morphometry and performed a genome-wide association study (GWAS) meta-analysis of European participants (combined N = 46,685). We then examined evidence for generalization to the non-European participants of the UKB and ABCD cohorts (combined N = 7,040). Post-GWAS analyses implicate prenatal intracellular organization and cell growth patterns, and high heritability in regions of open chromatin, suggesting transcriptional activity regulation in early development. Results suggest programmed cell death mediated by the immune system drives the thinning of the posterior body and isthmus. Global and local genetic overlap, along with causal genetic liability, between the corpus callosum, cerebral cortex, and neuropsychiatric disorders such as attention-deficit/hyperactivity and bipolar disorders were identified. These results provide insight into variability of corpus callosum development, its genetic influence on the cerebral cortex, and biological mechanisms related to neuropsychiatric dysfunction.
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Affiliation(s)
- Ravi R Bhatt
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Shruti P Gadewar
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ankush Shetty
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Iyad Ba Gari
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Elizabeth Haddad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Shayan Javid
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Abhinaav Ramesh
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Elnaz Nourollahimoghadam
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Alyssa H Zhu
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Christiaan de Leeuw
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, VU University, Amsterdam, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane 4006, Australia
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
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Kravitz A, Liao M, Morota G, Tyler R, Cockrum R, Manohar BM, Ronald BSM, Collins MT, Sriranganathan N. Retrospective Single Nucleotide Polymorphism Analysis of Host Resistance and Susceptibility to Ovine Johne's Disease Using Restored FFPE DNA. Int J Mol Sci 2024; 25:7748. [PMID: 39062990 PMCID: PMC11276633 DOI: 10.3390/ijms25147748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 06/26/2024] [Accepted: 06/28/2024] [Indexed: 07/28/2024] Open
Abstract
Johne's disease (JD), also known as paratuberculosis, is a chronic, untreatable gastroenteritis of ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP) infection. Evidence for host genetic resistance to disease progression exists, although it is limited due to the extended incubation period (years) and diagnostic challenges. To overcome this, previously restored formalin-fixed paraffin embedded tissue (FFPE) DNA from archived FFPE tissue cassettes was utilized for a novel retrospective case-control genome-wide association study (GWAS) on ovine JD. Samples from known MAP-infected flocks with ante- and postmortem diagnostic data were used. Cases (N = 9) had evidence of tissue infection, compared to controls (N = 25) without evidence of tissue infection despite positive antemortem diagnostics. A genome-wide efficient mixed model analysis (GEMMA) to conduct a GWAS using restored FFPE DNA SNP results from the Illumina Ovine SNP50 Bead Chip, identified 10 SNPs reaching genome-wide significance of p < 1 × 10-6 on chromosomes 1, 3, 4, 24, and 26. Pathway analysis using PANTHER and the Kyoto Encyclopedia of Genes and Genomes (KEGG) was completed on 45 genes found within 1 Mb of significant SNPs. Our work provides a framework for the novel use of archived FFPE tissues for animal genetic studies in complex diseases and further evidence for a genetic association in JD.
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Affiliation(s)
- Amanda Kravitz
- Center for One Health Research, Department of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
| | - Mingsi Liao
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
| | - Gota Morota
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
| | - Ron Tyler
- Center for One Health Research, Department of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
| | - Rebecca Cockrum
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
| | - B. Murali Manohar
- Department of Veterinary Pathology, Tamilnadu Veterinary and Animal Sciences University, Madhavaram Milk Colony, Chennai 600051, Tamil Nadu India, India
| | - B. Samuel Masilamoni Ronald
- Department of Veterinary Pathology, Tamilnadu Veterinary and Animal Sciences University, Madhavaram Milk Colony, Chennai 600051, Tamil Nadu India, India
| | - Michael T. Collins
- Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Nammalwar Sriranganathan
- Center for One Health Research, Department of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
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64
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Sadeh R, Ben-David R, Herrmann I, Peleg Z. Spectral-genomic chain-model approach enhances the wheat yield component prediction under the Mediterranean climate. PHYSIOLOGIA PLANTARUM 2024; 176:e14480. [PMID: 39187437 DOI: 10.1111/ppl.14480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 06/25/2024] [Accepted: 06/27/2024] [Indexed: 08/28/2024]
Abstract
In light of the changing climate that jeopardizes future food security, genomic selection is emerging as a valuable tool for breeders to enhance genetic gains and introduce high-yielding varieties. However, predicting grain yield is challenging due to the genetic and physiological complexities involved and the effect of genetic-by-environment interactions on prediction accuracy. We utilized a chained model approach to address these challenges, breaking down the complex prediction task into simpler steps. A diversity panel with a narrow phenological range was phenotyped across three Mediterranean environments for various morpho-physiological and yield-related traits. The results indicated that a multi-environment model outperformed a single-environment model in prediction accuracy for most traits. However, prediction accuracy for grain yield was not improved. Thus, in an attempt to ameliorate the grain yield prediction accuracy, we integrated a spectral estimation of spike number, being a major wheat yield component, with genomic data. A machine learning approach was used for spike number estimation from canopy hyperspectral reflectance captured by an unmanned aerial vehicle. The spectral-based estimated spike number was utilized as a secondary trait in a multi-trait genomic selection, significantly improving grain yield prediction accuracy. Moreover, the ability to predict the spike number based on data from previous seasons implies that it could be applied to new trials at various scales, even in small plot sizes. Overall, we demonstrate here that incorporating a novel spectral-genomic chain-model workflow, which utilizes spectral-based phenotypes as a secondary trait, improves the predictive accuracy of wheat grain yield.
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Affiliation(s)
- Roy Sadeh
- The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Roi Ben-David
- Institute of Plant Sciences, Agriculture Research Organization (ARO)-Volcani Institute, Rishon LeZion, Israel
| | - Ittai Herrmann
- The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Zvi Peleg
- The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
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65
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Winters J, Kawczynski MJ, Gilbers MD, Isaacs A, Zeemering S, Bidar E, Maesen B, Rienstra M, van Gelder I, Verheule S, Maessen JG, Schotten U. Circulating BMP10 Levels Associate With Late Postoperative Atrial Fibrillation and Left Atrial Endomysial Fibrosis. JACC Clin Electrophysiol 2024; 10:1326-1340. [PMID: 38639699 DOI: 10.1016/j.jacep.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/05/2024] [Accepted: 03/08/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Serum bone morphogenetic protein 10 (BMP10) blood levels are a marker for history of atrial fibrillation (AF) and for major adverse cardiovascular events in patients with AF, including stroke, AF recurrences after catheter ablations, and mortality. The predictive value of BMP10 in patients undergoing cardiac surgery and association with morphologic properties of atrial tissues are unknown. OBJECTIVES This study sought to study the correlation between BMP10 levels and preoperative clinical traits, occurrence of early and late postoperative atrial fibrillation (POAF), and atrial fibrosis in patients undergoing cardiac surgery. METHODS Patients with and without preoperative AF history undergoing first cardiac surgery were included (RACE V, n = 147). Preoperative blood biomarkers were analyzed, left (n = 114) and right (n = 125) atrial appendage biopsy specimens were histologically investigated after WGA staining, and postoperative rhythm was monitored continuously with implantable loop recorders (n = 133, 2.5 years). RESULTS Adjusted multinomial logistic regression indicated that BMP10 accurately reflected a history of persistent AF (OR: 1.24, 95% CI: 1.10-1.40, P = 0.001), similar to NT-pro-BNP. BMP10 levels were associated with increased late POAF90 occurrence after adjustment for age, sex, AF history, and early POAF occurrence (HR: 1.07 [per 0.1 ng/mL increase], 95% CI: 1.00-1.14, P = 0.041). Left atrial endomysial fibrosis (standardized β = 0.22, P = 0.041) but not overall fibrosis (standardized Β = 0.12, P = 0.261) correlated with circulating BMP10 after adjustment for age, sex, AF history, reduced LVF, and valvular surgery indication. CONCLUSIONS Increased BMP10 levels were associated with persistent AF history, increased late POAF incidence, and LAA endomysial fibrosis in a diverse sample of patients undergoing cardiac surgery.
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Affiliation(s)
- Joris Winters
- Department of Physiology, Maastricht University, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands
| | - Michal J Kawczynski
- Department of Physiology, Maastricht University, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands; Department of Cardiothoracic Surgery, Heart and Vascular Centre Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Martijn D Gilbers
- Department of Physiology, Maastricht University, Maastricht, the Netherlands
| | - Aaron Isaacs
- Department of Physiology, Maastricht University, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands; Maastricht Centre for Systems Biology, University Maastricht, Maastricht, the Netherlands
| | - Stef Zeemering
- Department of Physiology, Maastricht University, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands
| | - Elham Bidar
- Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands; Department of Cardiothoracic Surgery, Heart and Vascular Centre Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Bart Maesen
- Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands; Department of Cardiothoracic Surgery, Heart and Vascular Centre Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Michiel Rienstra
- Department of Cardiology, University of Groningen, University Medical Centre, Groningen, the Netherlands
| | - Isabelle van Gelder
- Department of Cardiology, University of Groningen, University Medical Centre, Groningen, the Netherlands
| | - Sander Verheule
- Department of Physiology, Maastricht University, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands
| | - Jos G Maessen
- Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands; Department of Cardiothoracic Surgery, Heart and Vascular Centre Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Ulrich Schotten
- Department of Physiology, Maastricht University, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht, Maastricht, the Netherlands.
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66
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Ao L, Noordam R, Rensen PCN, van Heemst D, Willems van Dijk K. The role of genetically-influenced phospholipid transfer protein activity in lipoprotein metabolism and coronary artery disease. J Clin Lipidol 2024; 18:e579-e587. [PMID: 38906750 DOI: 10.1016/j.jacl.2024.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 02/20/2024] [Accepted: 03/26/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Phospholipid transfer protein (PLTP) transfers surface phospholipids between lipoproteins and as such plays a role in lipoprotein metabolism, but with unclear effects on coronary artery disease (CAD) risk. We aimed to investigate the associations of genetically-influenced PLTP activity with 1-H nuclear magnetic resonance (1H-NMR) metabolomic measures and with CAD. Furthermore, using factorial Mendelian randomization (MR), we examined the potential additional effect of genetically-influenced PLTP activity on CAD risk on top of genetically-influenced low-density lipoprotein-cholesterol (LDL-C) lowering. METHODS Using data from UK Biobank, genetic scores for PLTP activity and LDL-C were calculated and dichotomised based on the median, generating four groups with combinations of high/low PLTP activity and high/low LDL-C levels for the factorial MR. Linear and logistic regressions were performed on 168 metabolomic measures (N = 58,514) and CAD (N = 318,734, N-cases=37,552), respectively, with results expressed as β coefficients (in standard deviation units) or odds ratios (ORs) and 95% confidence interval (CI). RESULTS Irrespective of the genetically-influenced LDL-C, genetically-influenced low PLTP activity was associated with a higher high-density lipoprotein (HDL) particle concentration (β [95% CI]: 0.03 [0.01, 0.05]), smaller HDL size (-0.14 [-0.15, -0.12]) and higher triglyceride (TG) concentration (0.04 [0.02, 0.05]), but not with CAD (OR 0.99 [0.97, 1.02]). In factorial MR analyses, genetically-influenced low PLTP activity and genetically-influenced low LDL-C had independent associations with metabolomic measures, and genetically-influenced low PLTP activity did not show an additional effect on CAD risk. CONCLUSIONS Low PLTP activity associates with higher HDL particle concentration, smaller HDL particle size and higher TG concentration, but no association with CAD risk was observed.
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Affiliation(s)
- Linjun Ao
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands (MMed Ao and Dr Willems van Dijk).
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands (Drs Noordam and van Heemst)
| | - Patrick C N Rensen
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands (Drs Rensen and Willems van Dijk); Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands (Drs Rensen and Willems van Dijk)
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands (Drs Noordam and van Heemst)
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands (MMed Ao and Dr Willems van Dijk); Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands (Drs Rensen and Willems van Dijk); Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands (Drs Rensen and Willems van Dijk)
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67
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Rossi N, Syed N, Visconti A, Aliyev E, Berry S, Bourbon M, Spector TD, Hysi PG, Fakhro KA, Falchi M. Rare variants at KCNJ2 are associated with LDL-cholesterol levels in a cross-population study. NPJ Genom Med 2024; 9:36. [PMID: 38942744 PMCID: PMC11213907 DOI: 10.1038/s41525-024-00417-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 05/03/2024] [Indexed: 06/30/2024] Open
Abstract
Leveraging whole genome sequencing data of 1751 individuals from the UK and 2587 Qatari subjects, we suggest here an association of rare variants mapping to the sour taste-associated gene KCNJ2 with reduced low-density lipoprotein cholesterol (LDL-C, P = 2.10 × 10-12) and with a 22% decreased dietary trans-fat intake. This study identifies a novel candidate rare locus for LDL-C, adding insights into the genetic architecture of a complex trait implicated in cardiovascular disease.
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Affiliation(s)
- Niccolò Rossi
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Najeeb Syed
- Department of Human Genetics, Sidra Medical and Research Center, Doha, Qatar
| | - Alessia Visconti
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
- Center for Biostatistics, Epidemiology and Public Health, Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Elbay Aliyev
- Department of Human Genetics, Sidra Medical and Research Center, Doha, Qatar
| | - Sarah Berry
- Department of Nutritional Sciences, King's College London, London, UK
| | - Mafalda Bourbon
- Cardiovascular Research Group, Department of Health Promotion and Prevention of non-Communicable Diseases, Instituto Nacional de Saúde Dr. Ricardo Jorge, Lisbon, Portugal
| | - Tim D Spector
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Pirro G Hysi
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Khalid A Fakhro
- Department of Human Genetics, Sidra Medical and Research Center, Doha, Qatar
- Department of Genetic Medicine, Weill-Cornell Medical College, Doha, Qatar
| | - Mario Falchi
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK.
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68
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AL-Eitan L. PTPRD gene variant rs10739150: A potential game-changer in hypertension diagnosis. PLoS One 2024; 19:e0304950. [PMID: 38935682 PMCID: PMC11210811 DOI: 10.1371/journal.pone.0304950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/22/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND High blood pressure, also known as hypertension (HTN), is a complicated disorder that is controlled by a complex network of physiological processes. Untreated hypertension is associated with increased death incidence, rise the need for understanding the genetic basis affecting hypertension susceptibility and development. The current study sought to identify the genetic association between twelve single nucleotide polymorphisms (SNPs) within seven candidate genes (NOS3, NOS1AP, REN, PLA2G4A, TCF7L, ADRB1, and PTPRD). METHODS The current study included 200 Jordanian individuals diagnosed with hypertension, compared to 224 healthy controls. Whole blood samples were drawn from each individual for DNA isolation and genotyping. The SNPStats tool was used to assess haplotype, genotype, and allele frequencies by the mean of chi-square (χ2). RESULTS Except for rs10739150 of PTPRD (P = 0.0003), the genotypic and allelic distribution of the SNP was identical between patients and controls. The prevalence of the G/G genotype in healthy controls (45.5%) was lower than in hypertension patients (64.3%), suggesting that it might be a risk factor for the disease. PTPRD TTC genetic haplotypes were strongly linked with hypertension (P = 0.003, OR = 4.03). CONCLUSION This study provides a comprehensive understanding of the involvement of rs10739150 within the PTPRD gene in hypertension. This new knowledge could potentially transform the way we approach hypertension diagnosis, providing an accurate diagnostic tool for classifying individuals who are at a higher risk of developing this condition.
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Affiliation(s)
- Laith AL-Eitan
- Department of Biotechnology and Genetic Engineering, Faculty of Science and Arts, Jordan University of Science and Technology, Irbid, Jordan
- Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA, United States of America
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69
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AL-Eitan L, Al-Khaldi S, Ibdah RK. ACE gene polymorphism and susceptibility to hypertension in a Jordanian adult population. PLoS One 2024; 19:e0304271. [PMID: 38917192 PMCID: PMC11198757 DOI: 10.1371/journal.pone.0304271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/09/2024] [Indexed: 06/27/2024] Open
Abstract
Hypertension is one of the most common and complicated disorders associated with genetic and environmental risk factors. The angiotensin-converting enzyme (ACE) is important in the renin-angiotensin-system pathway. The gene expression of ACE has been investigated as a possible hypertension marker. This study investigates the association between polymorphisms within the ACE1 and ACE2 genes and hypertension susceptibility in a Jordanian population. The study comprised a total of 200 hypertensive patients and 180 healthy controls. A polymerase chain reaction (PCR) was performed to genotype the candidate polymorphism (rs4646994) of the ACE1gene. The Luminex DNA array technique was used for genotyping SNPs (rs4359, rs4344, rs4341, rs4343, and rs2106809) of the ACE1 and ACE2 genes. Our findings suggest no association between SNPs and hypertension regarding allelic and genotypic frequencies. However, rs4359 was significantly associated with diet (pP = 0.049), know HTN (P = 0.042), and number of years DM (P = 0.003). rs4341 was associated with diet (P = 0.032), peripheral vascular disease (P = 0.005), and chronic kidney disease (p = 0.049). While rs4343 was associated with diet (P = 0.031), diabetes mellitus (P = 0.032), and other medication (P = 0.025). Furthermore, the haplotypes of four SNPs of the ACE1 gene showed no significant association with HTN patients and healthy controls. Our findings indicate no association between the polymorphisms in the ACE gene and the risk of hypertension development in the Jordanian adult population.
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Affiliation(s)
- Laith AL-Eitan
- Department of Biotechnology and Genetic Engineering, Jordan University of Science and Technology, Irbid, Jordan
- Department of Applied Biological Sciences, Jordan University of Science and Technology, Irbid, Jordan
| | - Sara Al-Khaldi
- Department of Applied Biological Sciences, Jordan University of Science and Technology, Irbid, Jordan
| | - Rasheed k. Ibdah
- Internal Medicine Department, College of Medicine, Jordan University of Science and Technology, Irbid, Jordan
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Li Y, Xu Y, Le Sayec M, Yan X, Spector TD, Steves CJ, Bell JT, Small KS, Menni C, Gibson R, Rodriguez-Mateos A. Development of a (Poly)phenol Metabolic Signature for Assessing (Poly)phenol-Rich Dietary Patterns. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:13439-13450. [PMID: 38829321 PMCID: PMC11181312 DOI: 10.1021/acs.jafc.4c00959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 04/14/2024] [Accepted: 04/30/2024] [Indexed: 06/05/2024]
Abstract
The objective assessment of habitual (poly)phenol-rich diets in nutritional epidemiology studies remains challenging. This study developed and evaluated the metabolic signature of a (poly)phenol-rich dietary score (PPS) using a targeted metabolomics method comprising 105 representative (poly)phenol metabolites, analyzed in 24 h of urine samples collected from healthy volunteers. The metabolites that were significantly associated with PPS after adjusting for energy intake were selected to establish a metabolic signature using a combination of linear regression followed by ridge regression to estimate penalized weights for each metabolite. A metabolic signature comprising 51 metabolites was significantly associated with adherence to PPS in 24 h urine samples, as well as with (poly)phenol intake estimated from food frequency questionnaires and diaries. Internal and external data sets were used for validation, and plasma, spot urine, and 24 h urine samples were compared. The metabolic signature proposed here has the potential to accurately reflect adherence to (poly)phenol-rich diets, and may be used as an objective tool for the assessment of (poly)phenol intake.
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Affiliation(s)
- Yong Li
- Department
of Nutritional Sciences, School of Life Course and Population Sciences,
Faculty of Life Sciences and Medicine, King’s
College London, London SE1 9NH, U.K.
| | - Yifan Xu
- Department
of Nutritional Sciences, School of Life Course and Population Sciences,
Faculty of Life Sciences and Medicine, King’s
College London, London SE1 9NH, U.K.
| | - Melanie Le Sayec
- Department
of Nutritional Sciences, School of Life Course and Population Sciences,
Faculty of Life Sciences and Medicine, King’s
College London, London SE1 9NH, U.K.
| | - Xinyu Yan
- Department
of Twin Research & Genetic Epidemiology, School of Life Course
and Population Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 7EH, U.K.
| | - Tim D. Spector
- Department
of Twin Research & Genetic Epidemiology, School of Life Course
and Population Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 7EH, U.K.
| | - Claire J. Steves
- Department
of Twin Research & Genetic Epidemiology, School of Life Course
and Population Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 7EH, U.K.
| | - Jordana T. Bell
- Department
of Twin Research & Genetic Epidemiology, School of Life Course
and Population Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 7EH, U.K.
| | - Kerrin S. Small
- Department
of Twin Research & Genetic Epidemiology, School of Life Course
and Population Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 7EH, U.K.
| | - Cristina Menni
- Department
of Twin Research & Genetic Epidemiology, School of Life Course
and Population Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 7EH, U.K.
| | - Rachel Gibson
- Department
of Nutritional Sciences, School of Life Course and Population Sciences,
Faculty of Life Sciences and Medicine, King’s
College London, London SE1 9NH, U.K.
| | - Ana Rodriguez-Mateos
- Department
of Nutritional Sciences, School of Life Course and Population Sciences,
Faculty of Life Sciences and Medicine, King’s
College London, London SE1 9NH, U.K.
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Al-Eitan L, Shatnawi M, Alghamdi M. Investigating CHRNA5, CHRNA3, and CHRNB4 variants in the genetic landscape of substance use disorder in Jordan. BMC Psychiatry 2024; 24:436. [PMID: 38862938 PMCID: PMC11167846 DOI: 10.1186/s12888-024-05898-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 06/06/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND Substance use disorder (SUD) is a complex illness that can be attributed to the interaction between environmental and genetic factors. The nicotinic receptor gene cluster on chromosome 15 has a plausible association with SUD, particularly with nicotine dependence. METHODS This study investigated 15 SNPs within the CHRNA5, CHRNA3, and CHRNB4 genes. Sequencing was used for genotyping 495 Jordanian males with SUD and 497 controls matched for age, gender, and descent. RESULTS Our findings revealed that none of the tested alleles or genotypes were correlated with SUD. However, our analysis suggests that the route of substance use was linked to rs1051730 (P value = 0.04), rs8040868 (P value = 0.01) of CHRNA3, and rs16969968 (P value = 0.03) of CHRNA5. Additionally, a correlation was identified between rs3813567 of the CHRNB4 gene and the age at substance use onset (P value = 0.04). CONCLUSIONS Variants in CHRNA5, CHRNA3, and CHRNB4 may interact with SUD features that can influence the development and progression of the disorder among Jordanians.
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Affiliation(s)
- Laith Al-Eitan
- Department of Biotechnology and Genetic Engineering, Jordan University of Science and Technology, Irbid, 22110, Jordan.
| | - Mohammad Shatnawi
- Department of Biotechnology and Genetic Engineering, Jordan University of Science and Technology, Irbid, 22110, Jordan
| | - Mansour Alghamdi
- Department of Anatomy, College of Medicine, King Khalid University, Abha, 62529, Saudi Arabia
- Genomics and Personalized Medicine Unit, College of Medicine, King Khalid University, Abha, 62529, Saudi Arabia
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72
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Bhatt IS, Garay JAR, Bhagavan SG, Ingalls V, Dias R, Torkamani A. A genome-wide association study reveals a polygenic architecture of speech-in-noise deficits in individuals with self-reported normal hearing. Sci Rep 2024; 14:13089. [PMID: 38849415 PMCID: PMC11161523 DOI: 10.1038/s41598-024-63972-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 06/04/2024] [Indexed: 06/09/2024] Open
Abstract
Speech-in-noise (SIN) perception is a primary complaint of individuals with audiometric hearing loss. SIN performance varies drastically, even among individuals with normal hearing. The present genome-wide association study (GWAS) investigated the genetic basis of SIN deficits in individuals with self-reported normal hearing in quiet situations. GWAS was performed on 279,911 individuals from the UB Biobank cohort, with 58,847 reporting SIN deficits despite reporting normal hearing in quiet. GWAS identified 996 single nucleotide polymorphisms (SNPs), achieving significance (p < 5*10-8) across four genomic loci. 720 SNPs across 21 loci achieved suggestive significance (p < 10-6). GWAS signals were enriched in brain tissues, such as the anterior cingulate cortex, dorsolateral prefrontal cortex, entorhinal cortex, frontal cortex, hippocampus, and inferior temporal cortex. Cochlear cell types revealed no significant association with SIN deficits. SIN deficits were associated with various health traits, including neuropsychiatric, sensory, cognitive, metabolic, cardiovascular, and inflammatory conditions. A replication analysis was conducted on 242 healthy young adults. Self-reported speech perception, hearing thresholds (0.25-16 kHz), and distortion product otoacoustic emissions (1-16 kHz) were utilized for the replication analysis. 73 SNPs were replicated with a self-reported speech perception measure. 211 SNPs were replicated with at least one and 66 with at least two audiological measures. 12 SNPs near or within MAPT, GRM3, and HLA-DQA1 were replicated for all audiological measures. The present study highlighted a polygenic architecture underlying SIN deficits in individuals with self-reported normal hearing.
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Affiliation(s)
- Ishan Sunilkumar Bhatt
- Department of Communication Sciences and Disorders, University of Iowa, 250 Hawkins Dr, Iowa City, IA, 52242, USA.
| | - Juan Antonio Raygoza Garay
- Department of Communication Sciences and Disorders, University of Iowa, 250 Hawkins Dr, Iowa City, IA, 52242, USA
- Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, 52242, USA
| | - Srividya Grama Bhagavan
- Department of Communication Sciences and Disorders, University of Iowa, 250 Hawkins Dr, Iowa City, IA, 52242, USA
| | - Valerie Ingalls
- Department of Communication Sciences and Disorders, University of Iowa, 250 Hawkins Dr, Iowa City, IA, 52242, USA
| | - Raquel Dias
- Department of Microbiology and Cell Science, University of Florida, Gainesville, FL, 32608, USA
| | - Ali Torkamani
- Department of Integrative Structural and Computational Biology, Scripps Research Institute, La Jolla, CA, 92037, USA
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Andreu‐Sánchez S, Ahmad S, Kurilshikov A, Beekman M, Ghanbari M, van Faassen M, van den Munckhof ICL, Steur M, Harms A, Hankemeier T, Ikram MA, Kavousi M, Voortman T, Kraaij R, Netea MG, Rutten JHW, Riksen NP, Zhernakova A, Kuipers F, Slagboom PE, van Duijn CM, Fu J, Vojinovic D. Unraveling interindividual variation of trimethylamine N-oxide and its precursors at the population level. IMETA 2024; 3:e183. [PMID: 38898991 PMCID: PMC11183189 DOI: 10.1002/imt2.183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/28/2024] [Accepted: 02/28/2024] [Indexed: 06/21/2024]
Abstract
Trimethylamine N-oxide (TMAO) is a circulating microbiome-derived metabolite implicated in the development of atherosclerosis and cardiovascular disease (CVD). We investigated whether plasma levels of TMAO, its precursors (betaine, carnitine, deoxycarnitine, choline), and TMAO-to-precursor ratios are associated with clinical outcomes, including CVD and mortality. This was followed by an in-depth analysis of their genetic, gut microbial, and dietary determinants. The analyses were conducted in five Dutch prospective cohort studies including 7834 individuals. To further investigate association results, Mendelian Randomization (MR) was also explored. We found only plasma choline levels (hazard ratio [HR] 1.17, [95% CI 1.07; 1.28]) and not TMAO to be associated with CVD risk. Our association analyses uncovered 10 genome-wide significant loci, including novel genomic regions for betaine (6p21.1, 6q25.3), choline (2q34, 5q31.1), and deoxycarnitine (10q21.2, 11p14.2) comprising several metabolic gene associations, for example, CPS1 or PEMT. Furthermore, our analyses uncovered 68 gut microbiota associations, mainly related to TMAO-to-precursors ratios and the Ruminococcaceae family, and 16 associations of food groups and metabolites including fish-TMAO, meat-carnitine, and plant-based food-betaine associations. No significant association was identified by the MR approach. Our analyses provide novel insights into the TMAO pathway, its determinants, and pathophysiological impact on the general population.
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Affiliation(s)
- Sergio Andreu‐Sánchez
- Department of Genetics, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
- Department of Pediatrics, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
| | - Shahzad Ahmad
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
- Metabolomics & Analytics Centre, Leiden Academic Center for Drug ResearchLeiden UniversityLeidenThe Netherlands
| | - Alexander Kurilshikov
- Department of Genetics, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data SciencesLeiden University Medical CenterLeidenThe Netherlands
| | - Mohsen Ghanbari
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
| | - Martijn van Faassen
- Department of Laboratory Medicine, University Medical Center GroningenUniversity of GroningenGroningenThe Netherland
| | - Inge C. L. van den Munckhof
- Department of Internal Medicine and Radboud Institute for Molecular Life SciencesRadboud University Medical CenterNijmegenThe Netherlands
| | - Marinka Steur
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
| | - Amy Harms
- Metabolomics & Analytics Centre, Leiden Academic Center for Drug ResearchLeiden UniversityLeidenThe Netherlands
| | - Thomas Hankemeier
- Metabolomics & Analytics Centre, Leiden Academic Center for Drug ResearchLeiden UniversityLeidenThe Netherlands
| | - M. Arfan Ikram
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
| | - Maryam Kavousi
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
| | - Trudy Voortman
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
| | - Robert Kraaij
- Department of Internal MedicineErasmus University Medical CenterRotterdamThe Netherlands
| | - Mihai G. Netea
- Department of Internal Medicine and Radboud Institute for Molecular Life SciencesRadboud University Medical CenterNijmegenThe Netherlands
| | - Joost H. W. Rutten
- Department of Internal Medicine and Radboud Institute for Molecular Life SciencesRadboud University Medical CenterNijmegenThe Netherlands
| | - Niels P. Riksen
- Department of Internal Medicine and Radboud Institute for Molecular Life SciencesRadboud University Medical CenterNijmegenThe Netherlands
| | - Alexandra Zhernakova
- Department of Genetics, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
| | - Folkert Kuipers
- Department of Pediatrics, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
- Department of Laboratory Medicine, University Medical Center GroningenUniversity of GroningenGroningenThe Netherland
- European Institute for the Biology of Ageing, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
| | - P. Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data SciencesLeiden University Medical CenterLeidenThe Netherlands
| | | | - Jingyuan Fu
- Department of Genetics, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
- Department of Pediatrics, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
| | - Dina Vojinovic
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
- Molecular Epidemiology, Department of Biomedical Data SciencesLeiden University Medical CenterLeidenThe Netherlands
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Bazdar S, Bloemsma LD, Baalbaki N, Blankestijn JM, Cornelissen MEB, Beijers RJHCG, Sondermeijer BM, van Wijck Y, Downward GS, Maitland-van der Zee AH. Hemoglobin and Its Relationship with Fatigue in Long-COVID Patients Three to Six Months after SARS-CoV-2 Infection. Biomedicines 2024; 12:1234. [PMID: 38927441 PMCID: PMC11201257 DOI: 10.3390/biomedicines12061234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 06/28/2024] Open
Abstract
Background: While some long-term effects of COVID-19 are respiratory in nature, a non-respiratory effect gaining attention has been a decline in hemoglobin, potentially mediated by inflammatory processes. In this study, we examined the correlations between hemoglobin levels and inflammatory biomarkers and evaluated the association between hemoglobin and fatigue in a cohort of Long-COVID patients. Methods: This prospective cohort study in the Netherlands evaluated 95 (mostly hospitalized) patients, aged 40-65 years, 3-6 months post SARS-CoV-2 infection, examining their venous hemoglobin concentration, anemia (hemoglobin < 7.5 mmol/L in women and <8.5 mmol/L in men), inflammatory blood biomarkers, average FSS (Fatigue Severity Score), demographics, and clinical features. Follow-up hemoglobin was compared against hemoglobin during acute infection. Spearman correlation was used for assessing the relationship between hemoglobin concentrations and inflammatory biomarkers, and the association between hemoglobin and fatigue was examined using logistic regression. Results: In total, 11 (16.4%) participants were suffering from anemia 3-6 months after SARS-CoV-2 infection. The mean hemoglobin value increased by 0.3 mmol/L 3-6 months after infection compared to the hemoglobin during the acute phase (p-value = 0.003). Whilst logistic regression showed that a 1 mmol/L greater increase in hemoglobin is related to a decrease in experiencing fatigue in Long-COVID patients (adjusted OR 0.38 [95%CI 0.13-1.09]), we observed no correlations between hemoglobin and any of the inflammatory biomarkers examined. Conclusion: Our results indicate that hemoglobin impairment might play a role in developing Long-COVID fatigue. Further investigation is necessary to identify the precise mechanism causing hemoglobin alteration in these patients.
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Affiliation(s)
- Somayeh Bazdar
- Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.B.); (L.D.B.); (J.M.B.); (M.E.B.C.)
- Amsterdam Institute for Infection and Immunity, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
| | - Lizan D. Bloemsma
- Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.B.); (L.D.B.); (J.M.B.); (M.E.B.C.)
- Amsterdam Institute for Infection and Immunity, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
| | - Nadia Baalbaki
- Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.B.); (L.D.B.); (J.M.B.); (M.E.B.C.)
- Amsterdam Institute for Infection and Immunity, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
| | - Jelle M. Blankestijn
- Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.B.); (L.D.B.); (J.M.B.); (M.E.B.C.)
- Amsterdam Institute for Infection and Immunity, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
| | - Merel E. B. Cornelissen
- Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.B.); (L.D.B.); (J.M.B.); (M.E.B.C.)
- Amsterdam Institute for Infection and Immunity, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
| | - Rosanne J. H. C. G. Beijers
- Department of Respiratory Medicine, Nutrim Institute of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6202 AZ Maastricht, The Netherlands;
| | | | - Yolanda van Wijck
- Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.B.); (L.D.B.); (J.M.B.); (M.E.B.C.)
- Amsterdam Institute for Infection and Immunity, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
| | - George S. Downward
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, 3584 CL Utrecht, The Netherlands;
- Department of Global Public Health & Bioethics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Anke H. Maitland-van der Zee
- Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.B.); (L.D.B.); (J.M.B.); (M.E.B.C.)
- Amsterdam Institute for Infection and Immunity, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
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75
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Vilar-Ribó L, Cabana-Domínguez J, Alemany S, Llonga N, Arribas L, Grau-López L, Daigre C, Cormand B, Fernàndez-Castillo N, Ramos-Quiroga JA, Soler Artigas M, Ribasés M. Disentangling heterogeneity in substance use disorder: Insights from genome-wide polygenic scores. Transl Psychiatry 2024; 14:221. [PMID: 38811559 PMCID: PMC11137038 DOI: 10.1038/s41398-024-02923-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 05/09/2024] [Accepted: 05/10/2024] [Indexed: 05/31/2024] Open
Abstract
Substance use disorder (SUD) is a global health problem with a significant impact on individuals and society. The presentation of SUD is diverse, involving various substances, ages at onset, comorbid conditions, and disease trajectories. Current treatments for SUD struggle to address this heterogeneity, resulting in high relapse rates. SUD often co-occurs with other psychiatric and mental health-related conditions that contribute to the heterogeneity of the disorder and predispose to adverse disease trajectories. Family and genetic studies highlight the role of genetic and environmental factors in the course of SUD, and point to a shared genetic liability between SUDs and comorbid psychopathology. In this study, we aimed to disentangle SUD heterogeneity using a deeply phenotyped SUD cohort and polygenic scores (PGSs) for psychiatric disorders and related traits. We explored associations between PGSs and various SUD-related phenotypes, as well as PGS-environment interactions using information on lifetime emotional, physical, and/or sexual abuse. Our results identify clusters of individuals who exhibit differences in their phenotypic profile and reveal different patterns of associations between SUD-related phenotypes and the genetic liability for mental health-related traits, which may help explain part of the heterogeneity observed in SUD. In our SUD sample, we found associations linking the genetic liability for attention-deficit hyperactivity disorder (ADHD) with lower educational attainment, the genetic liability for post-traumatic stress disorder (PTSD) with higher rates of unemployment, the genetic liability for educational attainment with lower rates of criminal records and unemployment, and the genetic liability for well-being with lower rates of outpatient treatments and fewer problems related to family and social relationships. We also found evidence of PGS-environment interactions showing that genetic liability for suicide attempts worsened the psychiatric status in SUD individuals with a history of emotional physical and/or sexual abuse. Collectively, these data contribute to a better understanding of the role of genetic liability for mental health-related conditions and adverse life experiences in SUD heterogeneity.
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Grants
- Instituto de Salud Carlos III: CP22/00128 Ministry of Science, Innovation and Universities: IJC2018-035346-I
- Instituto de Salud Carlos III: FI18/00285
- Ministry of Science, Innovation and Universities: RYC2021-031324-I Network Center for Biomedical Research (CIBER)
- Instituto de Salud Carlos III: CP22/00026
- Ministry of Science, Innovation and Universities: PID2021-1277760B-I100
- Ministry of Science, Innovation and Universities: PID2021-1277760B-I100 Ministry of Health, Social Services and Equality:PNSD-2020I042
- Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, 2017SGR-1461, 2021SGR-00840 and 2021-SGR-01093)., European Regional Development Fund (ERDF), the European Union H2020 Programme (H2020/2014-2020) under grant agreements no. 848228 (DISCOvERIE) and no. 2020604 (TIMESPAN), the ECNP Network ‘ADHD across the Lifespan’,“La Marató de TV3” (202228-30 and 202228-31) and ICREA Academia 2021
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Affiliation(s)
- Laura Vilar-Ribó
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Judit Cabana-Domínguez
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Silvia Alemany
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Natalia Llonga
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Lorena Arribas
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Lara Grau-López
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Addiction and Dual Diagnosis Unit, Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Constanza Daigre
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Addiction and Dual Diagnosis Unit, Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Bru Cormand
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
- Institut de Recerca Sant Joan de Déu (IRSJD), Esplugues de Llobregat, Catalonia, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain
| | - Noèlia Fernàndez-Castillo
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
- Institut de Recerca Sant Joan de Déu (IRSJD), Esplugues de Llobregat, Catalonia, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain
| | - Josep Antoni Ramos-Quiroga
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Addiction and Dual Diagnosis Unit, Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - María Soler Artigas
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain.
| | - Marta Ribasés
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain.
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Wang Z, Yang X, Li H, Wang S, Liu Z, Wang Y, Zhang X, Chen Y, Xu Q, Xu J, Wang Z, Wang J. Bidirectional two-sample Mendelian randomization analyses support causal relationships between structural and diffusion imaging-derived phenotypes and the risk of major neurodegenerative diseases. Transl Psychiatry 2024; 14:215. [PMID: 38806463 PMCID: PMC11133432 DOI: 10.1038/s41398-024-02939-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 05/10/2024] [Accepted: 05/16/2024] [Indexed: 05/30/2024] Open
Abstract
Previous observational investigations suggest that structural and diffusion imaging-derived phenotypes (IDPs) are associated with major neurodegenerative diseases; however, whether these associations are causal remains largely uncertain. Herein we conducted bidirectional two-sample Mendelian randomization analyses to infer the causal relationships between structural and diffusion IDPs and major neurodegenerative diseases using common genetic variants-single nucleotide polymorphism (SNPs) as instrumental variables. Summary statistics of genome-wide association study (GWAS) for structural and diffusion IDPs were obtained from 33,224 individuals in the UK Biobank cohort. Summary statistics of GWAS for seven major neurodegenerative diseases were obtained from the largest GWAS for each disease to date. The forward MR analyses identified significant or suggestively statistical causal effects of genetically predicted three structural IDPs on Alzheimer's disease (AD), frontotemporal dementia (FTD), and multiple sclerosis. For example, the reduction in the surface area of the left superior temporal gyrus was associated with a higher risk of AD. The reverse MR analyses identified significantly or suggestively statistical causal effects of genetically predicted AD, Lewy body dementia (LBD), and FTD on nine structural and diffusion IDPs. For example, LBD was associated with increased mean diffusivity in the right superior longitudinal fasciculus and AD was associated with decreased gray matter volume in the right ventral striatum. Our findings might contribute to shedding light on the prediction and therapeutic intervention for the major neurodegenerative diseases at the neuroimaging level.
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Affiliation(s)
- Zirui Wang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xuan Yang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
- Department of Radiology, Jining No.1 People's Hospital, Jining, Shandong, 272000, China
| | - Haonan Li
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Siqi Wang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Zhixuan Liu
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yaoyi Wang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xingyu Zhang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yayuan Chen
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Qiang Xu
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jiayuan Xu
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Zengguang Wang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Junping Wang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
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77
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Botey-Bataller J, Vrijmoeth HD, Ursinus J, Kullberg BJ, van den Wijngaard CC, Ter Hofstede H, Alaswad A, Gupta MK, Roesner LM, Huehn J, Werfel T, Schulz TF, Xu CJ, Netea MG, Hovius JW, Joosten LAB, Li Y. A comprehensive genetic map of cytokine responses in Lyme borreliosis. Nat Commun 2024; 15:3795. [PMID: 38714679 PMCID: PMC11076587 DOI: 10.1038/s41467-024-47505-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 04/02/2024] [Indexed: 05/10/2024] Open
Abstract
The incidence of Lyme borreliosis has risen, accompanied by persistent symptoms. The innate immune system and related cytokines are crucial in the host response and symptom development. We characterized cytokine production capacity before and after antibiotic treatment in 1,060 Lyme borreliosis patients. We observed a negative correlation between antibody production and IL-10 responses, as well as increased IL-1Ra responses in patients with disseminated disease. Genome-wide mapping the cytokine production allowed us to identify 34 cytokine quantitative trait loci (cQTLs), with 31 novel ones. We pinpointed the causal variant at the TLR1-6-10 locus and validated the regulation of IL-1Ra responses at transcritpome level using an independent cohort. We found that cQTLs contribute to Lyme borreliosis susceptibility and are relevant to other immune-mediated diseases. Our findings improve the understanding of cytokine responses in Lyme borreliosis and provide a genetic map of immune function as an expanded resource.
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Affiliation(s)
- Javier Botey-Bataller
- Department of Internal Medicine and Radboudumc Community for Infectious Diseases, Radboud university medical center, Nijmegen, the Netherlands
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Hedwig D Vrijmoeth
- Department of Internal Medicine and Radboudumc Community for Infectious Diseases, Radboud university medical center, Nijmegen, the Netherlands
- National Institute for Public Health and Environment (RIVM), Center for Infectious Disease Control, Bilthoven, the Netherlands
| | - Jeanine Ursinus
- National Institute for Public Health and Environment (RIVM), Center for Infectious Disease Control, Bilthoven, the Netherlands
- Department of Internal Medicine, Division of Infectious Diseases & Center for Experimental and Molecular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Bart-Jan Kullberg
- Department of Internal Medicine and Radboudumc Community for Infectious Diseases, Radboud university medical center, Nijmegen, the Netherlands
| | - Cees C van den Wijngaard
- National Institute for Public Health and Environment (RIVM), Center for Infectious Disease Control, Bilthoven, the Netherlands
| | - Hadewych Ter Hofstede
- Department of Internal Medicine and Radboudumc Community for Infectious Diseases, Radboud university medical center, Nijmegen, the Netherlands
| | - Ahmed Alaswad
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Manoj K Gupta
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Hannover, Germany
| | - Lennart M Roesner
- Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Hannover, Germany
- Department of Dermatology and Allergy, Hannover Medical School, Hannover, Germany
| | - Jochen Huehn
- Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Hannover, Germany
- Department of Experimental Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Thomas Werfel
- Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Hannover, Germany
- Department of Dermatology and Allergy, Hannover Medical School, Hannover, Germany
| | - Thomas F Schulz
- Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Hannover, Germany
- Institute of Virology, Hannover Medical School, Hannover, Germany
| | - Cheng-Jian Xu
- Department of Internal Medicine and Radboudumc Community for Infectious Diseases, Radboud university medical center, Nijmegen, the Netherlands
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Mihai G Netea
- Department of Internal Medicine and Radboudumc Community for Infectious Diseases, Radboud university medical center, Nijmegen, the Netherlands
- Department for Genomics and Immunoregulation, Life and Medical Sciences Institute (LIMES), University of Bonn, Bonn, Germany
| | - Joppe W Hovius
- Department of Internal Medicine, Division of Infectious Diseases & Center for Experimental and Molecular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Leo A B Joosten
- Department of Internal Medicine and Radboudumc Community for Infectious Diseases, Radboud university medical center, Nijmegen, the Netherlands
- Department of Medical Genetics, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Yang Li
- Department of Internal Medicine and Radboudumc Community for Infectious Diseases, Radboud university medical center, Nijmegen, the Netherlands.
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany.
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany.
- Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Hannover, Germany.
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78
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Meger J, Ulaszewski B, Pałucka M, Kozioł C, Burczyk J. Genomic prediction of resistance to Hymenoscyphus fraxineus in common ash ( Fraxinus excelsior L.) populations. Evol Appl 2024; 17:e13694. [PMID: 38707993 PMCID: PMC11069026 DOI: 10.1111/eva.13694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 03/28/2024] [Accepted: 04/10/2024] [Indexed: 05/07/2024] Open
Abstract
The increase in introduced insect pests and pathogens due to anthropogenic environmental changes has become a major concern for tree species worldwide. Common ash (Fraxinus excelsior L.) is one of such species facing a significant threat from the invasive fungal pathogen Hymenoscyphus fraxineus. Some studies have indicated that the susceptibility of ash to the pathogen is genetically determined, providing some hope for accelerated breeding programs that are aimed at increasing the resistance of ash populations. To address this challenge, we used a genomic selection strategy to identify potential genetic markers that are associated with resistance to the pathogen causing ash dieback. Through genome-wide association studies (GWAS) of 300 common ash individuals from 30 populations across Poland (ddRAD, dataset A), we identified six significant SNP loci with a p-value ≤1 × 10-4 associated with health status. To further evaluate the effectiveness of GWAS markers in predicting health status, we considered two genomic prediction scenarios. Firstly, we conducted cross-validation on dataset A. Secondly, we trained markers on dataset A and tested them on dataset B, which involved whole-genome sequencing of 20 individuals from two populations. Genomic prediction analysis revealed that the top SNPs identified via GWAS exhibited notably higher prediction accuracies compared to randomly selected SNPs, particularly with a larger number of SNPs. Cross-validation analyses using dataset A showcased high genomic prediction accuracy, predicting tree health status with over 90% accuracy across the top SNP sets ranging from 500 to 10,000 SNPs from the GWAS datasets. However, no significant results emerged for health status when the model trained on dataset A was tested on dataset B. Our findings illuminate potential genetic markers associated with resistance to ash dieback, offering support for future breeding programs in Poland aimed at combating ash dieback and bolstering conservation efforts for this invaluable tree species.
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Affiliation(s)
- Joanna Meger
- Department of Genetics, Faculty of Biological SciencesKazimierz Wielki UniversityBydgoszczPoland
| | - Bartosz Ulaszewski
- Department of Genetics, Faculty of Biological SciencesKazimierz Wielki UniversityBydgoszczPoland
| | | | | | - Jarosław Burczyk
- Department of Genetics, Faculty of Biological SciencesKazimierz Wielki UniversityBydgoszczPoland
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79
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Sargurupremraj M, Soumaré A, Bis JC, Surakka I, Jürgenson T, Joly P, Knol MJ, Wang R, Yang Q, Satizabal CL, Gudjonsson A, Mishra A, Bouteloup V, Phuah CL, van Duijn CM, Cruchaga C, Dufouil C, Chêne G, Lopez OL, Psaty BM, Tzourio C, Amouyel P, Adams HH, Jacqmin-Gadda H, Ikram MA, Gudnason V, Milani L, Winsvold BS, Hveem K, Matthews PM, Longstreth WT, Seshadri S, Launer LJ, Debette S. Genetic Complexities of Cerebral Small Vessel Disease, Blood Pressure, and Dementia. JAMA Netw Open 2024; 7:e2412824. [PMID: 38776079 PMCID: PMC11112447 DOI: 10.1001/jamanetworkopen.2024.12824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 03/21/2024] [Indexed: 05/25/2024] Open
Abstract
Importance Vascular disease is a treatable contributor to dementia risk, but the role of specific markers remains unclear, making prevention strategies uncertain. Objective To investigate the causal association between white matter hyperintensity (WMH) burden, clinical stroke, blood pressure (BP), and dementia risk, while accounting for potential epidemiologic biases. Design, Setting, and Participants This study first examined the association of genetically determined WMH burden, stroke, and BP levels with Alzheimer disease (AD) in a 2-sample mendelian randomization (2SMR) framework. Second, using population-based studies (1979-2018) with prospective dementia surveillance, the genetic association of WMH, stroke, and BP with incident all-cause dementia was examined. Data analysis was performed from July 26, 2020, through July 24, 2022. Exposures Genetically determined WMH burden and BP levels, as well as genetic liability to stroke derived from genome-wide association studies (GWASs) in European ancestry populations. Main Outcomes and Measures The association of genetic instruments for WMH, stroke, and BP with dementia was studied using GWASs of AD (defined clinically and additionally meta-analyzed including both clinically diagnosed AD and AD defined based on parental history [AD-meta]) for 2SMR and incident all-cause dementia for longitudinal analyses. Results In 2SMR (summary statistics-based) analyses using AD GWASs with up to 75 024 AD cases (mean [SD] age at AD onset, 75.5 [4.4] years; 56.9% women), larger WMH burden showed evidence for a causal association with increased risk of AD (odds ratio [OR], 1.43; 95% CI, 1.10-1.86; P = .007, per unit increase in WMH risk alleles) and AD-meta (OR, 1.19; 95% CI, 1.06-1.34; P = .008), after accounting for pulse pressure for the former. Blood pressure traits showed evidence for a protective association with AD, with evidence for confounding by shared genetic instruments. In the longitudinal (individual-level data) analyses involving 10 699 incident all-cause dementia cases (mean [SD] age at dementia diagnosis, 74.4 [9.1] years; 55.4% women), no significant association was observed between larger WMH burden and incident all-cause dementia (hazard ratio [HR], 1.02; 95% CI, 1.00-1.04; P = .07). Although all exposures were associated with mortality, with the strongest association observed for systolic BP (HR, 1.04; 95% CI, 1.03-1.06; P = 1.9 × 10-14), there was no evidence for selective survival bias during follow-up using illness-death models. In secondary analyses using polygenic scores, the association of genetic liability to stroke, but not genetically determined WMH, with dementia outcomes was attenuated after adjusting for interim stroke. Conclusions These findings suggest that WMH is a primary vascular factor associated with dementia risk, emphasizing its significance in preventive strategies for dementia. Future studies are warranted to examine whether this finding can be generalized to non-European populations.
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Affiliation(s)
- Muralidharan Sargurupremraj
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio
| | - Aicha Soumaré
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Tuuli Jürgenson
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Pierre Joly
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Maria J. Knol
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Ruiqi Wang
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Qiong Yang
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | | | - Aniket Mishra
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Vincent Bouteloup
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Chia-Ling Phuah
- Department of Neurology, Washington University School of Medicine & Barnes-Jewish Hospital, St Louis, Missouri
- NeuroGenomics and Informatics Center, Washington University in St Louis, St Louis, Missouri
| | - Cornelia M. van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Carlos Cruchaga
- NeuroGenomics and Informatics Center, Washington University in St Louis, St Louis, Missouri
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri
| | - Carole Dufouil
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Geneviève Chêne
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
- Department of Public Health, CHU de Bordeaux, Bordeaux, France
| | - Oscar L. Lopez
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
- Department of Health Systems and Population Health, University of Washington, Seattle
| | - Christophe Tzourio
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
- Department of Public Health, CHU de Bordeaux, Bordeaux, France
| | - Philippe Amouyel
- INSERM U1167, University of Lille, Institut Pasteur de Lille, Lille, France
- Department of Epidemiology and Public Health, CHRU de Lille, Lille, France
| | - Hieab H. Adams
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Hélène Jacqmin-Gadda
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Bendik S. Winsvold
- Division of Clinical Neuroscience, Department of Research and Innovation, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Paul M. Matthews
- Department of Brain Sciences, Imperial College London, London, United Kingdom
- UK Dementia Research Institute, Imperial College London, London, United Kingdom
- Data Science Institute, Imperial College London, London, United Kingdom
| | - W. T. Longstreth
- Department of Epidemiology, University of Washington, Seattle
- Department of Neurology, University of Washington, Seattle
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, Maryland
| | - Stéphanie Debette
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Institute for Neurodegenerative Diseases, Department of Neurology, Bordeaux University Hospital, Bordeaux, France
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80
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Hughes DA, Li-Gao R, Bull CJ, de Mutsert R, Rosendaal FR, Mook-Kanamori DO, Willems van Dijk K, Timpson NJ. The association between body mass index and metabolite response to a liquid mixed meal challenge: a Mendelian randomization study. Am J Clin Nutr 2024; 119:1354-1370. [PMID: 38494119 PMCID: PMC11130664 DOI: 10.1016/j.ajcnut.2024.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/30/2024] [Accepted: 03/12/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND Metabolite abundance is a dynamic trait that varies in response to environmental stimuli and phenotypic traits, such as food consumption and body mass index (BMI, kg/m2). OBJECTIVES In this study, we used the Netherlands Epidemiology of Obesity (NEO) study data to identify observational and causal associations between BMI and metabolite response to a liquid meal. METHODS A liquid meal challenge was performed, and Nightingale Health metabolite profiles were collected in 5744 NEO participants. Observational and one-sample Mendelian randomization (MR) analysis were conducted to estimate the effect of BMI on metabolites (n = 229) in the fasting, postprandial, and response (or change in abundance) states. RESULTS We observed 473 associations with BMI (175 fasting, 188 postprandial, and 110 response) in observational analyses. In MR analyses, we observed 20 metabolite traits (5 fasting, 12 postprandial, and 3 response) to be associated with BMI. MR associations included the glucogenic amino acid alanine, which was inversely associated with BMI in the response state (β: -0.081; SE: 0.023; P = 5.91 × 10-4), suggesting that as alanine increased in postprandial abundance, that increase was attenuated with increasing BMI. CONCLUSIONS Overall, this study showed that MR estimates were strongly correlated with observational effect estimates, suggesting that the broad associations seen between BMI and metabolite variation has a causal underpinning. Specific effects in previously unassessed postprandial and response states are detected, and these may likely mark novel life course risk exposures driven by regular nutrition.
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Affiliation(s)
- David A Hughes
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Caroline J Bull
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands; Division of Endocrinology, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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81
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Bruins S, van Bergen E, Masselink MW, Barzeva SA, Hartman CA, Otten R, Rommelse NNJ, Dolan CV, Boomsma DI. Are Genetic and Environmental Risk Factors for Psychopathology Amplified in Children with Below-Average Intelligence? A Population-Based Twin Study. Behav Genet 2024; 54:278-289. [PMID: 38353893 PMCID: PMC11032279 DOI: 10.1007/s10519-023-10174-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 12/20/2023] [Indexed: 04/21/2024]
Abstract
There is a negative association between intelligence and psychopathology. We analyzed data on intelligence and psychopathology to assess this association in seven-year-old Dutch twin pairs (ranging from 616 to 14,150 depending on the phenotype) and estimated the degree to which genetic and environmental factors common to intelligence and psychopathology explain the association. Secondly, we examined whether genetic and environmental effects on psychopathology are moderated by intelligence. We found that intelligence, as assessed by psychometric IQ tests, correlated negatively with childhood psychopathology, as assessed by the DSM-oriented scales of the Child Behavior Check List (CBCL). The correlations ranged between - .09 and - .15 and were mainly explained by common genetic factors. Intelligence moderated genetic and environmental effects on anxiety and negative affect, but not those on ADHD, ODD, and autism. The heritability of anxiety and negative affect was greatest in individuals with below-average intelligence. We discuss mechanisms through which this effect could arise, and we end with some recommendations for future research.
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Affiliation(s)
- Susanne Bruins
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
| | - Elsje van Bergen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maurits W Masselink
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Stefania A Barzeva
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Roy Otten
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Nanda N J Rommelse
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, The Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Research and Development (AR&D) Research Institute, Amsterdam, The Netherlands
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82
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Verhoef E, Allegrini AG, Jansen PR, Lange K, Wang CA, Morgan AT, Ahluwalia TS, Symeonides C, Eising E, Franken MC, Hypponen E, Mansell T, Olislagers M, Omerovic E, Rimfeld K, Schlag F, Selzam S, Shapland CY, Tiemeier H, Whitehouse AJO, Saffery R, Bønnelykke K, Reilly S, Pennell CE, Wake M, Cecil CAM, Plomin R, Fisher SE, St Pourcain B. Genome-Wide Analyses of Vocabulary Size in Infancy and Toddlerhood: Associations With Attention-Deficit/Hyperactivity Disorder, Literacy, and Cognition-Related Traits. Biol Psychiatry 2024; 95:859-869. [PMID: 38070845 DOI: 10.1016/j.biopsych.2023.11.025] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 11/26/2023] [Accepted: 11/29/2023] [Indexed: 02/17/2024]
Abstract
BACKGROUND The number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors. Here, we performed a meta-genome-wide association study of vocabulary acquisition and investigated polygenic overlap with literacy, cognition, developmental phenotypes, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD). METHODS We studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months), and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated single nucleotide polymorphism-based heritability (SNP-h2) and genetic correlations (rg) and modeled underlying factor structures with multivariate models. RESULTS Early-life vocabulary size was modestly heritable (SNP-h2 = 0.08-0.24). Genetic overlap between infant expressive and toddler receptive vocabulary was negligible (rg = 0.07), although each measure was moderately related to toddler expressive vocabulary (rg = 0.69 and rg = 0.67, respectively), suggesting a multifactorial genetic architecture. Both infant and toddler expressive vocabulary were genetically linked to literacy (e.g., spelling: rg = 0.58 and rg = 0.79, respectively), underlining genetic similarity. However, a genetic association of early-life vocabulary with educational attainment and intelligence emerged only during toddlerhood (e.g., receptive vocabulary and intelligence: rg = 0.36). Increased ADHD risk was genetically associated with larger infant expressive vocabulary (rg = 0.23). Multivariate genetic models in the ALSPAC (Avon Longitudinal Study of Parents and Children) cohort confirmed this finding for ADHD symptoms (e.g., at age 13; rg = 0.54) but showed that the association effect reversed for toddler receptive vocabulary (rg = -0.74), highlighting developmental heterogeneity. CONCLUSIONS The genetic architecture of early-life vocabulary changes during development, shaping polygenic association patterns with later-life ADHD, literacy, and cognition-related traits.
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Affiliation(s)
- Ellen Verhoef
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands.
| | - Andrea G Allegrini
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Philip R Jansen
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit, Amsterdam, the Netherlands; Section Clinical Genetics, Department Human Genetics, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Katherine Lange
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Carol A Wang
- School of Medicine and Public Health, The University of Newcastle, Newcastle, New South Wales, Australia; Mothers and Babies Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Angela T Morgan
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia; Department of Audiology and Speech Pathology, University of Melbourne, Parkville, Victoria, Australia; Royal Children's Hospital, Melbourne, Victoria, Australia
| | - Tarunveer S Ahluwalia
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark; Steno Diabetes Center Copenhagen, Herlev, Denmark; Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Christos Symeonides
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Royal Children's Hospital, Melbourne, Victoria, Australia; Minderoo Foundation, Perth, Western Australia, Australia
| | - Else Eising
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Marie-Christine Franken
- Erasmus University Medical Center, Sophia Children's Hospital, Department of Otorhinolaryngology and Head and Neck Surgery, Rotterdam, the Netherlands
| | - Elina Hypponen
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia; South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Toby Mansell
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Mitchell Olislagers
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands; Department of Urology, Erasmus University Medical Center, Erasmus University Medical Center Cancer Institute, Rotterdam, the Netherlands
| | - Emina Omerovic
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Department of Psychology, Royal Holloway University of London, London, UK
| | - Fenja Schlag
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Saskia Selzam
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Chin Yang Shapland
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Population Health Sciences, University of Bristol, Bristol, UK
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, the Netherlands; Harvard, T.H. Chan School of Public Health, Boston, Massachusetts
| | - Andrew J O Whitehouse
- Telethon Kids Institute, The University of Western Australia, Perth, Western Australia, Australia
| | - Richard Saffery
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia; Chongqing Medical University, Chongqing, China
| | - Klaus Bønnelykke
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Sheena Reilly
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia; Menzies Health Institute Queensland, Griffith University, Brisbane, Queensland, Australia
| | - Craig E Pennell
- School of Medicine and Public Health, The University of Newcastle, Newcastle, New South Wales, Australia; Mothers and Babies Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia; Maternity and Gynaecology John Hunter Hospital, Newcastle, New South Wales, Australia
| | - Melissa Wake
- Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia; Liggins Institute, The University of Auckland, Grafton, New Zealand
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Beate St Pourcain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.
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83
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Bottenhorn KL, Cardenas-Iniguez C, Schachner JN, Rosario MA, Mills KL, Laird AR, Herting MM. Adolescent Neurodevelopmental Variance Across Social Strata. JAMA Netw Open 2024; 7:e2410441. [PMID: 38717776 PMCID: PMC11079691 DOI: 10.1001/jamanetworkopen.2024.10441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 03/08/2024] [Indexed: 05/12/2024] Open
Abstract
This cohort study explores variability in neurodevelopment across sociodemographic factors among youths.
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Affiliation(s)
- Katherine L. Bottenhorn
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles
- Department of Psychology, Florida International University, Miami
| | - Carlos Cardenas-Iniguez
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles
| | - Jared N. Schachner
- Price School of Public Policy, University of Southern California, Los Angeles
| | - Michael A. Rosario
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles
| | | | - Angela R. Laird
- Department of Physics, Florida International University, Miami
| | - Megan M. Herting
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles
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84
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Cambi S, Solcà M, Micali N, Berchio C. Cardiac interoception in Anorexia Nervosa: A resting-state heartbeat-evoked potential study. EUROPEAN EATING DISORDERS REVIEW 2024; 32:417-430. [PMID: 38009624 DOI: 10.1002/erv.3049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 11/01/2023] [Accepted: 11/03/2023] [Indexed: 11/29/2023]
Abstract
OBJECTIVE A deficit in interoception - the ability to perceive, interpret and integrate afferent signals about the physiological state of the body - has been shown in Anorexia Nervosa (AN), and linked to altered hunger sensations, body dysmorphia, and abnormal emotional awareness. The present high-density electroencephalography (hdEEG) study aims to assess cardiac interoception in AN and to investigate its neural correlates, using an objective neurophysiological measure. METHOD Heartbeat-evoked potentials (HEPs) were computed from 5 min of resting-state EEG and electrocardiogram (ECG) data and compared between individuals with AN (N = 22) and healthy controls (HC) (N = 19) with waveform, topographic, and source imaging analyses. RESULTS Differences in the cortical representation of heartbeats were present between AN and HC at a time window of 332-348 ms after the ECG R-peak. Source imaging analyses revealed a right-sided hypoactivation in AN of brain regions linked to interoceptive processing, such as the anterior cingulate and orbitofrontal areas. CONCLUSIONS To the best of our knowledge, this is the first study using hdEEG to localise the underlying sources of HEPs in AN. Results point to altered interoceptive processing during resting-state in AN. As our participants had a short duration of illness, this might not be the consequence of prolonged starvation. Interventions targeted at interoception could provide an additional tool to facilitate recovery.
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Affiliation(s)
- Susanne Cambi
- Department of Psychiatry, Geneva University Hospital, Geneva, Switzerland
| | - Marco Solcà
- Department of Psychiatry, Geneva University Hospital, Geneva, Switzerland
| | - Nadia Micali
- Mental Health Services of the Capital Region of Denmark, Center for Eating and Feeding Disorders Research, Psychiatric Centre Ballerup, Ballerup, Denmark
- University College London, Great Ormond Street Institute of Child Health, London, UK
| | - Cristina Berchio
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
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85
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Tang R, Buchholz E, Dale AM, Rissman RA, Fennema-Notestine C, Gillespie NA, Hagler DJ, Lyons MJ, Neale MC, Panizzon MS, Puckett OK, Reynolds CA, Franz CE, Kremen WS, Elman JA. Associations of plasma neurofilament light chain with cognition and neuroimaging measures in community-dwelling early old age men. Alzheimers Res Ther 2024; 16:90. [PMID: 38664843 PMCID: PMC11044425 DOI: 10.1186/s13195-024-01464-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 04/21/2024] [Indexed: 04/28/2024]
Abstract
BACKGROUND Plasma neurofilament light chain (NfL) is a promising biomarker of neurodegeneration with potential clinical utility in monitoring the progression of neurodegenerative diseases. However, the cross-sectional associations of plasma NfL with measures of cognition and brain have been inconsistent in community-dwelling populations. METHODS We examined these associations in a large community-dwelling sample of early old age men (N = 969, mean age = 67.57 years, range = 61-73 years), who are either cognitively unimpaired (CU) or with mild cognitive impairment (MCI). Specifically, we investigated five cognitive domains (executive function, episodic memory, verbal fluency, processing speed, visual-spatial ability), as well as neuroimaging measures of gray and white matter. RESULTS After adjusting for age, health status, and young adult general cognitive ability, plasma NfL level was only significantly associated with processing speed and white matter hyperintensity (WMH) volume, but not with other cognitive or neuroimaging measures. The association with processing speed was driven by individuals with MCI, as it was not detected in CU individuals. CONCLUSIONS These results suggest that in early old age men without dementia, plasma NfL does not appear to be sensitive to cross-sectional individual differences in most domains of cognition or neuroimaging measures of gray and white matter. The revealed plasma NfL associations were limited to WMH for all participants and processing speed only within the MCI cohort. Importantly, considering cognitive status in community-based samples will better inform the interpretation of the relationships of plasma NfL with cognition and brain and may help resolve mixed findings in the literature.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA.
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA.
| | - Erik Buchholz
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, 92093, USA
| | - Robert A Rissman
- Department of Neurosciences, University of California San Diego, La Jolla, 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, 92093, USA
| | - Nathan A Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, 23284, USA
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Donald J Hagler
- Department of Neurosciences, University of California San Diego, La Jolla, 92093, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, 02215, USA
| | - Michael C Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, 23284, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Chandra A Reynolds
- Department of Psychology and Neurosciences, University of Colorado Boulder, Boulder, 80309, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
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86
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Ohlei O, Paul K, Nielsen SS, Gmelin D, Dobricic V, Altmann V, Schilling M, Bronstein JM, Franke A, Wittig M, Parkkinen L, Hansen J, Checkoway H, Ritz B, Bertram L, Lill CM. Genome-wide meta-analysis of short-tandem repeats for Parkinson's disease risk using genotype imputation. Brain Commun 2024; 6:fcae146. [PMID: 38863574 PMCID: PMC11166220 DOI: 10.1093/braincomms/fcae146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/20/2024] [Accepted: 02/26/2024] [Indexed: 06/13/2024] Open
Abstract
Idiopathic Parkinson's disease is determined by a combination of genetic and environmental factors. Recently, the first genome-wide association study on short-tandem repeats in Parkinson's disease reported on eight suggestive short-tandem repeat-based risk loci (α = 5.3 × 10-6), of which four were novel, i.e. they had not been implicated in Parkinson's disease risk by genome-wide association analyses of single-nucleotide polymorphisms before. Here, we tested these eight candidate short-tandem repeats in a large, independent Parkinson's disease case-control dataset (n = 4757). Furthermore, we combined the results from both studies by meta-analysis resulting in the largest Parkinson's disease genome-wide association study of short-tandem repeats to date (n = 43 844). Lastly, we investigated whether leading short-tandem repeat risk variants exert functional effects on gene expression regulation based on methylation quantitative trait locus data in human 'post-mortem' brain (n = 142). None of the eight previously reported short-tandem repeats were significantly associated with Parkinson's disease in our independent dataset after multiple testing correction (α = 6.25 × 10-3). However, we observed modest support for short-tandem repeats near CCAR2 and NCOR1 in the updated meta-analyses of all available data. While the genome-wide meta-analysis did not reveal additional study-wide significant (α = 6.3 × 10-7) short-tandem repeat signals, we identified seven novel suggestive Parkinson's disease short-tandem repeat risk loci (α = 5.3 × 10-6). Of these, especially a short-tandem repeat near MEIOSIN showed consistent evidence for association across datasets. CCAR2, NCOR1 and one novel suggestive locus identified here (LINC01012) emerged from colocalization analyses showing evidence for a shared causal short-tandem repeat variant affecting both Parkinson's disease risk and cis DNA methylation in brain. Larger studies, ideally using short-tandem repeats called from whole-sequencing data, are needed to more fully investigate their role in Parkinson's disease.
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Affiliation(s)
- Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Kimberly Paul
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA
| | - Susan Searles Nielsen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - David Gmelin
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Vivian Altmann
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
- Forensic Genetics Division, Instituto-Geral de Perícias do Rio Grande do Sul, Porto Alegre, RS 90230-010, Brazil
| | - Marcel Schilling
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
- Gene Regulation of Cell Identity, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), L’Hospitalet del Llobregat, Barcelona 0890x, Spain
- Department of Epidemiology, University of California Los Angeles (UCLA), Fielding School of Public Health, Los Angeles, CA 90095, USA
| | - Jeff M Bronstein
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA
- Brain Research Institute, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany
| | - Michael Wittig
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany
| | - Laura Parkkinen
- Nuffield Department of Clinical Neurosciences, Oxford Parkinson’s Disease Centre, University of Oxford, Oxford OX1 3PT, UK
| | - Johnni Hansen
- Danish Cancer Institute, Danish Cancer Society, 2100 Copenhagen, Denmark
| | - Harvey Checkoway
- Herbert Wertheim School of Public Health, University of California San Diego, La Jolla, CA 92093, USA
| | - Beate Ritz
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA
- Brain Research Institute, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Christina M Lill
- Institute of Epidemiology and Social Medicine, University of Münster, 48149 Münster, Germany
- School of Public Health, Imperial College, Ageing Epidemiology Research Unit, London SW71, UK
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87
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Garin V, Diallo C, Tékété ML, Théra K, Guitton B, Dagno K, Diallo AG, Kouressy M, Leiser W, Rattunde F, Sissoko I, Touré A, Nébié B, Samaké M, Kholovà J, Berger A, Frouin J, Pot D, Vaksmann M, Weltzien E, Témé N, Rami JF. Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping. Genetics 2024; 226:iyae003. [PMID: 38381593 PMCID: PMC10990433 DOI: 10.1093/genetics/iyae003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/20/2023] [Indexed: 02/23/2024] Open
Abstract
Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.
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Affiliation(s)
- Vincent Garin
- Crop Physiology Laboratory, International Crops Research Institute for the Semi-Arid Tropics, Patancheru, 502 324, India
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Chiaka Diallo
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
- Département d’Enseignement et de Recherche des Sciences et Techniques Agricoles, Institut polytechnique rural de formation et de recherche appliquée de Katibougou, Koulikoro, BP 06, Mali
| | - Mohamed Lamine Tékété
- Institut d’Economie Rurale, Bamako, BP 262, Mali
- Faculté des Sciences et Techniques, Université des Sciences des Techniques et des Technologies de Bamako, Bamako, BP E 3206, Mali
| | | | - Baptiste Guitton
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Karim Dagno
- Institut d’Economie Rurale, Bamako, BP 262, Mali
| | | | | | - Willmar Leiser
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
| | - Fred Rattunde
- Agronomy Department, University of Wisconsin, Madison, WI 53705, WI, USA
| | - Ibrahima Sissoko
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
| | - Aboubacar Touré
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
| | - Baloua Nébié
- Dryland Crops Program, International Maize and Wheat Improvement Center (CIMMYT-Senegal) U/C CERAAS, Thiès, Po Box 3320, Senegal
| | - Moussa Samaké
- Faculté des Sciences et Techniques, Université des Sciences des Techniques et des Technologies de Bamako, Bamako, BP E 3206, Mali
| | - Jana Kholovà
- Crop Physiology Laboratory, International Crops Research Institute for the Semi-Arid Tropics, Patancheru, 502 324, India
- Department of Information Technologies, Faculty of Economics and Management, Czech University of Life Sciences, Prague, 165 00, Czech Republic
| | - Angélique Berger
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Julien Frouin
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - David Pot
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Michel Vaksmann
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Eva Weltzien
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
- Agronomy Department, University of Wisconsin, Madison, WI 53705, WI, USA
| | - Niaba Témé
- Institut d’Economie Rurale, Bamako, BP 262, Mali
| | - Jean-François Rami
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
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88
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Andrade F, Howell L, Percival CJ, Richtsmeier JT, Marcucio RS, Hallgrímsson B, Cheverud JM. Genetic architecture of trait variance in craniofacial morphology. Genetics 2024; 226:iyae028. [PMID: 38386896 PMCID: PMC11090463 DOI: 10.1093/genetics/iyae028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 12/19/2023] [Accepted: 01/26/2024] [Indexed: 02/24/2024] Open
Abstract
The genetic architecture of trait variance has long been of interest in genetics and evolution. One of the earliest attempts to understand this architecture was presented in Lerner's Genetic Homeostasis (1954). Lerner proposed that heterozygotes should be better able to tolerate environmental perturbations because of functional differences between the alleles at a given locus, with each allele optimal for slightly different environments. This greater robustness to environmental variance, he argued, would result in smaller trait variance for heterozygotes. The evidence for Lerner's hypothesis has been inconclusive. To address this question using modern genomic methods, we mapped loci associated with differences in trait variance (vQTL) on 1,101 individuals from the F34 of an advanced intercross between LG/J and SM/J mice. We also mapped epistatic interactions for these vQTL in order to understand the influence of epistasis for the architecture of trait variance. We did not find evidence supporting Lerner's hypothesis, that heterozygotes tend to have smaller trait variances than homozygotes. We further show that the effects of most mapped loci on trait variance are produced by epistasis affecting trait means and that those epistatic effects account for about a half of the differences in genotypic-specific trait variances. Finally, we propose a model where the different interactions between the additive and dominance effects of the vQTL and their epistatic partners can explain Lerner's original observations but can also be extended to include other conditions where heterozygotes are not the least variable genotype.
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Affiliation(s)
- Fernando Andrade
- Department of Biology, Loyola University Chicago, Chicago, IL 60660, USA
| | - Lisa Howell
- Department of Anthropology, Penn State University, University Park, PA 16802, USA
| | | | - Joan T Richtsmeier
- Department of Anthropology, Penn State University, University Park, PA 16802, USA
| | - Ralph S Marcucio
- Department of Orthopedic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA 94110, USA
| | - Benedikt Hallgrímsson
- Department of Cell Biology and Anatomy, Cumming School of Medicine, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - James M Cheverud
- Department of Biology, Loyola University Chicago, Chicago, IL 60660, USA
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89
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Golan G, Weiner J, Zhao Y, Schnurbusch T. Agroecological genetics of biomass allocation in wheat uncovers genotype interactions with canopy shade and plant size. THE NEW PHYTOLOGIST 2024; 242:107-120. [PMID: 38326944 DOI: 10.1111/nph.19576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 01/21/2024] [Indexed: 02/09/2024]
Abstract
How plants distribute biomass among organs influences resource acquisition, reproduction and plant-plant interactions, and is essential in understanding plant ecology, evolution, and yield production in agriculture. However, the genetic mechanisms regulating allocation responses to the environment are largely unknown. We studied recombinant lines of wheat (Triticum spp.) grown as single plants under sunlight and simulated canopy shade to investigate genotype-by-environment interactions in biomass allocation to the leaves, stems, spikes, and grains. Size-corrected mass fractions and allometric slopes were employed to dissect allocation responses to light limitation and plant size. Size adjustments revealed light-responsive alleles associated with adaptation to the crop environment. Combined with an allometric approach, we demonstrated that polymorphism in the DELLA protein is associated with the response to shade and size. While a gibberellin-sensitive allelic effect on stem allocation was amplified when plants were shaded, size-dependent effects of this allele drive allocation to reproduction, suggesting that the ontogenetic trajectory of the plant affects the consequences of shade responses for allocation. Our approach provides a basis for exploring the genetic determinants underlying investment strategies in the face of different resource constraints and will be useful in predicting social behaviours of individuals in a crop community.
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Affiliation(s)
- Guy Golan
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, 06466, Seeland, Germany
| | - Jacob Weiner
- Department of Plant and Environmental Sciences, University of Copenhagen, DK-1871, Frederiksberg, Denmark
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, 06466, Seeland, Germany
| | - Thorsten Schnurbusch
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, 06466, Seeland, Germany
- Martin Luther University Halle-Wittenberg, Faculty of Natural Sciences III, Institute of Agricultural and Nutritional Sciences, 06120, Halle, Germany
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90
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Schippers LM, Greven CU, Hoogman M. Associations between ADHD traits and self-reported strengths in the general population. Compr Psychiatry 2024; 130:152461. [PMID: 38335571 DOI: 10.1016/j.comppsych.2024.152461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/26/2024] [Accepted: 02/04/2024] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND ADHD research has had a clear focus on symptoms, their negative consequences and the treatment of ADHD. However, previous qualitative research found that people with a diagnosis of ADHD also self-report to experience strengths related to their ADHD. This is one of the first quantitative studies to investigate multiple self-reported strengths in relation to ADHD traits in a general population sample. Therefore, our aim was to investigate the relationship between multiple self-reported strengths with ADHD traits in the general population using quantitative measures. METHODS Our sample consisted of individuals from the general population in the UK, aged 18-60, n = 694. Next to assessing ADHD traits, we collected data on ten instruments investigating strengths that in qualitative research were reported to be related to ADHD. Correlation analysis (primary) was supplemented by factor and network analyses (exploratory). RESULTS We found positive correlations between ADHD traits and hyperfocus, sensory processing sensitivity, and cognitive flexibility. CONCLUSIONS People with more ADHD traits score higher on several strengths, for other strengths we were not able to show a positive correlation in this population-bases sample. Information on strengths may aid people with elevated ADHD traits cope with their condition, and has potential to provide new angles for treatment.
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Affiliation(s)
- L M Schippers
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Human Genetics, the Netherlands; Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Psychiatry, the Netherlands
| | - C U Greven
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, the Netherlands; Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, the Netherlands
| | - M Hoogman
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Human Genetics, the Netherlands; Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Psychiatry, the Netherlands.
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91
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Nandudu L, Strock C, Ogbonna A, Kawuki R, Jannink JL. Genetic analysis of cassava brown streak disease root necrosis using image analysis and genome-wide association studies. FRONTIERS IN PLANT SCIENCE 2024; 15:1360729. [PMID: 38562560 PMCID: PMC10982329 DOI: 10.3389/fpls.2024.1360729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 03/07/2024] [Indexed: 04/04/2024]
Abstract
Cassava brown streak disease (CBSD) poses a substantial threat to food security. To address this challenge, we used PlantCV to extract CBSD root necrosis image traits from 320 clones, with an aim of identifying genomic regions through genome-wide association studies (GWAS) and candidate genes. Results revealed strong correlations among certain root necrosis image traits, such as necrotic area fraction and necrotic width fraction, as well as between the convex hull area of root necrosis and the percentage of necrosis. Low correlations were observed between CBSD scores obtained from the 1-5 scoring method and all root necrosis traits. Broad-sense heritability estimates of root necrosis image traits ranged from low to moderate, with the highest estimate of 0.42 observed for the percentage of necrosis, while narrow-sense heritability consistently remained low, ranging from 0.03 to 0.22. Leveraging data from 30,750 SNPs obtained through DArT genotyping, eight SNPs on chromosomes 1, 7, and 11 were identified and associated with both the ellipse eccentricity of root necrosis and the percentage of necrosis through GWAS. Candidate gene analysis in the 172.2kb region on the chromosome 1 revealed 24 potential genes with diverse functions, including ubiquitin-protein ligase, DNA-binding transcription factors, and RNA metabolism protein, among others. Despite our initial expectation that image analysis objectivity would yield better heritability estimates and stronger genomic associations than the 1-5 scoring method, the results were unexpectedly lower. Further research is needed to comprehensively understand the genetic basis of these traits and their relevance to cassava breeding and disease management.
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Affiliation(s)
- Leah Nandudu
- School of Integrative Plant Sciences, Section of Plant Breeding and Genetics, Cornell University, Ithaca, NY, United States
- Root Crops Department, National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Christopher Strock
- School of Integrative Plant Sciences, Section of Plant Breeding and Genetics, Cornell University, Ithaca, NY, United States
| | - Alex Ogbonna
- School of Integrative Plant Sciences, Section of Plant Breeding and Genetics, Cornell University, Ithaca, NY, United States
| | - Robert Kawuki
- Root Crops Department, National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Jean-Luc Jannink
- School of Integrative Plant Sciences, Section of Plant Breeding and Genetics, Cornell University, Ithaca, NY, United States
- US Department of Agriculture, Agricultural Research Service (USDA-ARS), Ithaca, NY, United States
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92
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Hoque A, Anderson JV, Rahman M. Genomic prediction for agronomic traits in a diverse Flax (Linum usitatissimum L.) germplasm collection. Sci Rep 2024; 14:3196. [PMID: 38326469 PMCID: PMC10850546 DOI: 10.1038/s41598-024-53462-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 01/31/2024] [Indexed: 02/09/2024] Open
Abstract
Breeding programs require exhaustive phenotyping of germplasms, which is time-demanding and expensive. Genomic prediction helps breeders harness the diversity of any collection to bypass phenotyping. Here, we examined the genomic prediction's potential for seed yield and nine agronomic traits using 26,171 single nucleotide polymorphism (SNP) markers in a set of 337 flax (Linum usitatissimum L.) germplasm, phenotyped in five environments. We evaluated 14 prediction models and several factors affecting predictive ability based on cross-validation schemes. Models yielded significant variation among predictive ability values across traits for the whole marker set. The ridge regression (RR) model covering additive gene action yielded better predictive ability for most of the traits, whereas it was higher for low heritable traits by models capturing epistatic gene action. Marker subsets based on linkage disequilibrium decay distance gave significantly higher predictive abilities to the whole marker set, but for randomly selected markers, it reached a plateau above 3000 markers. Markers having significant association with traits improved predictive abilities compared to the whole marker set when marker selection was made on the whole population instead of the training set indicating a clear overfitting. The correction for population structure did not increase predictive abilities compared to the whole collection. However, stratified sampling by picking representative genotypes from each cluster improved predictive abilities. The indirect predictive ability for a trait was proportionate to its correlation with other traits. These results will help breeders to select the best models, optimum marker set, and suitable genotype set to perform an indirect selection for quantitative traits in this diverse flax germplasm collection.
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Affiliation(s)
- Ahasanul Hoque
- Department of Plant Sciences, North Dakota State University, Fargo, ND, USA
- Department of Genetics and Plant Breeding, Bangladesh Agricultural University, Mymensingh, 2202, Bangladesh
| | - James V Anderson
- USDA-ARS, Edward T. Schafer Agricultural Research Center, Fargo, ND, USA
| | - Mukhlesur Rahman
- Department of Plant Sciences, North Dakota State University, Fargo, ND, USA.
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93
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Jacobson MH, Hamra GB, Monk C, Crum RM, Upadhyaya S, Avalos LA, Bastain TM, Barrett ES, Bush NR, Dunlop AL, Ferrara A, Firestein MR, Hipwell AE, Kannan K, Lewis J, Meeker JD, Ruden DM, Starling AP, Watkins DJ, Zhao Q, Trasande L. Prenatal Exposure to Nonpersistent Environmental Chemicals and Postpartum Depression. JAMA Psychiatry 2024; 81:67-76. [PMID: 37728908 PMCID: PMC10512164 DOI: 10.1001/jamapsychiatry.2023.3542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 07/20/2023] [Indexed: 09/22/2023]
Abstract
Importance Postpartum depression (PPD) affects up to 20% of childbearing individuals, and a significant limitation in reducing its morbidity is the difficulty in modifying established risk factors. Exposure to synthetic environmental chemicals found in plastics and personal care products, such as phenols, phthalates, and parabens, are potentially modifiable and plausibly linked to PPD and have yet to be explored. Objective To evaluate associations of prenatal exposure to phenols, phthalates, parabens, and triclocarban with PPD symptoms. Design, Setting, and Participants This was a prospective cohort study from 5 US sites, conducted from 2006 to 2020, and included pooled data from 5 US birth cohorts from the National Institutes of Health Environmental Influences on Child Health Outcomes (ECHO) consortium. Participants were pregnant individuals with data on urinary chemical concentrations (phenols, phthalate metabolites, parabens, or triclocarban) from at least 1 time point in pregnancy and self-reported postnatal depression screening assessment collected between 2 weeks and 12 months after delivery. Data were analyzed from February to May 2022. Exposures Phenols (bisphenols and triclosan), phthalate metabolites, parabens, and triclocarban measured in prenatal urine samples. Main Outcomes and Measures Depression symptom scores were assessed using the Edinburgh Postnatal Depression Scale (EPDS) or the Center for Epidemiologic Studies Depression Scale (CES-D), harmonized to the Patient-Reported Measurement Information System (PROMIS) Depression scale. Measures of dichotomous PPD were created using both sensitive (EPDS scores ≥10 and CES-D scores ≥16) and specific (EPDS scores ≥13 and CES-D scores ≥20) definitions. Results Among the 2174 pregnant individuals eligible for analysis, nearly all (>99%) had detectable levels of several phthalate metabolites and parabens. PPD was assessed a mean (SD) of 3 (2.5) months after delivery, with 349 individuals (16.1%) and 170 individuals (7.8%) screening positive for PPD using the sensitive and specific definitions, respectively. Linear regression results of continuous PROMIS depression T scores showed no statistically significant associations with any chemical exposures. Models examining LMW and HMW phthalates and di (2-ethylhexyl) phthalate had estimates in the positive direction whereas all others were negative. A 1-unit increase in log-transformed LMW phthalates was associated with a 0.26-unit increase in the PROMIS depression T score (95% CI, -0.01 to 0.53; P = .06). This corresponded to an odds ratio (OR) of 1.08 (95% CI, 0.98-1.19) when modeling PPD as a dichotomous outcome and using the sensitive PPD definition. HMW phthalates were associated with increased odds of PPD (OR, 1.11; 95% CI, 1.00-1.23 and OR, 1.10; 95% CI, 0.96-1.27) for the sensitive and specific PPD definitions, respectively. Sensitivity analyses produced stronger results. Conclusions and Relevance Phthalates, ubiquitous chemicals in the environment, may be associated with PPD and could serve as important modifiable targets for preventive interventions. Future studies are needed to confirm these observations.
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Affiliation(s)
- Melanie H. Jacobson
- Department of Pediatrics, Division of Environmental Pediatrics, NYU Grossman School of Medicine, New York, New York
| | - Ghassan B. Hamra
- Johns Hopkins University, Department of Epidemiology, Baltimore, Maryland
| | - Catherine Monk
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, New York
- Department of Psychiatry, Columbia University Irving Medical Center, Division of Behavioral Medicine, New York State Psychiatric Institute, New York, New York
| | - Rosa M. Crum
- Johns Hopkins University, Department of Epidemiology, Baltimore, Maryland
| | | | - Lyndsay A. Avalos
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Theresa M. Bastain
- Department of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles
| | - Emily S. Barrett
- Rutgers School of Public Health, Environmental and Occupational Health Sciences Institute, Piscataway, New Jersey
- University of Rochester Medical Center School of Medicine and Dentistry, Rochester, New York
| | - Nicole R. Bush
- Department of Psychiatry, University of California, San Francisco
- Department of Pediatrics, University of California, San Francisco
| | - Anne L. Dunlop
- Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, Georgia
| | - Assiamira Ferrara
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Morgan R. Firestein
- Department of Psychiatry, Columbia University Irving Medical Center, Division of Behavioral Medicine, New York State Psychiatric Institute, New York, New York
| | - Alison E. Hipwell
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Kurunthachalam Kannan
- Department of Pediatrics, Division of Environmental Pediatrics, NYU Grossman School of Medicine, New York, New York
| | - Johnnye Lewis
- Community Environmental Health Program, College of Pharmacy, University of New Mexico Health Sciences Center, Albuquerque
| | - John D. Meeker
- University of Michigan, Department of Environmental Health Sciences, Ann Arbor
| | - Douglas M. Ruden
- Department of Obstetrics and Gynecology, Wayne State University, Detroit, Michigan
| | - Anne P. Starling
- Center for Lifecourse Epidemiology of Adiposity and Diabetes, University of Colorado Anschutz Medical Campus, Aurora
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill
| | - Deborah J. Watkins
- University of Michigan, Department of Environmental Health Sciences, Ann Arbor
| | - Qi Zhao
- The University of Tennessee Health Science Center, Memphis
| | - Leonardo Trasande
- Department of Pediatrics, Division of Environmental Pediatrics, NYU Grossman School of Medicine, New York, New York
- Department of Population Health, NYU Grossman School of Medicine, New York, New York
- Division of Environmental Medicine, NYU Grossman School of Medicine, New York, New York
- NYU Wagner School of Public Service, New York, New York
- NYU College of Global Public Health, New York, New York
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94
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Oddy J, Chhetry M, Awal R, Addy J, Wilkinson M, Smith D, King R, Hall C, Testa R, Murray E, Raffan S, Curtis TY, Wingen L, Griffiths S, Berry S, Elmore JS, Cryer N, Moreira de Almeida I, Halford NG. Genetic control of grain amino acid composition in a UK soft wheat mapping population. THE PLANT GENOME 2023; 16:e20335. [PMID: 37138544 DOI: 10.1002/tpg2.20335] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/23/2022] [Accepted: 03/13/2023] [Indexed: 05/05/2023]
Abstract
Wheat (Triticum aestivum L.) is a major source of nutrients for populations across the globe, but the amino acid composition of wheat grain does not provide optimal nutrition. The nutritional value of wheat grain is limited by low concentrations of lysine (the most limiting essential amino acid) and high concentrations of free asparagine (precursor to the processing contaminant acrylamide). There are currently few available solutions for asparagine reduction and lysine biofortification through breeding. In this study, we investigated the genetic architecture controlling grain free amino acid composition and its relationship to other traits in a Robigus × Claire doubled haploid population. Multivariate analysis of amino acids and other traits showed that the two groups are largely independent of one another, with the largest effect on amino acids being from the environment. Linkage analysis of the population allowed identification of quantitative trait loci (QTL) controlling free amino acids and other traits, and this was compared against genomic prediction methods. Following identification of a QTL controlling free lysine content, wheat pangenome resources facilitated analysis of candidate genes in this region of the genome. These findings can be used to select appropriate strategies for lysine biofortification and free asparagine reduction in wheat breeding programs.
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Affiliation(s)
| | | | - Rajani Awal
- John Innes Centre, Norwich Research Park, Norwich, UK
| | | | | | | | | | | | | | | | | | | | - Luzie Wingen
- John Innes Centre, Norwich Research Park, Norwich, UK
| | | | | | - J Stephen Elmore
- Department of Food & Nutritional Sciences, University of Reading, Reading, UK
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95
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Liu J, Hu S, Chen L, Daly C, Prada Medina CA, Richardson TG, Traylor M, Dempster NJ, Mbasu R, Monfeuga T, Vujkovic M, Tsao PS, Lynch JA, Voight BF, Chang KM, Million VA, Cobbold JF, Tomlinson JW, van Duijn CM, Howson JMM. Profiling the genome and proteome of metabolic dysfunction-associated steatotic liver disease identifies potential therapeutic targets. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.30.23299247. [PMID: 38076879 PMCID: PMC10705663 DOI: 10.1101/2023.11.30.23299247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
BACKGROUND & AIMS Metabolic dysfunction-associated steatotic liver disease (MASLD) affects over 25% of the population and currently has no effective treatments. Plasma proteins with causal evidence may represent promising drug targets. We aimed to identify plasma proteins in the causal pathway of MASLD and explore their interaction with obesity. METHODS We analysed 2,941 plasma proteins in 43,978 European participants from UK Biobank. We performed genome-wide association study (GWAS) for all MASLD-associated proteins and created the largest MASLD GWAS (109,885 cases/1,014,923 controls). We performed Mendelian Randomization (MR) and integrated proteins and their encoding genes in MASLD ranges to identify candidate causal proteins. We then validated them through independent replication, exome sequencing, liver imaging, bulk and single-cell gene expression, liver biopsies, pathway, and phenome-wide data. We explored the role of obesity by MR and multivariable MR across proteins, body mass index, and MASLD. RESULTS We found 929 proteins associated with MASLD, reported five novel genetic loci associated with MASLD, and identified 17 candidate MASLD protein targets. We identified four novel targets for MASLD (CD33, GRHPR, HMOX2, and SCG3), provided protein evidence supporting roles of AHCY, FCGR2B, ORM1, and RBKS in MASLD, and validated nine previously known targets. We found that CD33, FCGR2B, ORM1, RBKS, and SCG3 mediated the association of obesity and MASLD, and HMOX2, ORM1, and RBKS had effect on MASLD independent of obesity. CONCLUSIONS This study identified new protein targets in the causal pathway of MASLD, providing new insights into the multi-omics architecture and pathophysiology of MASLD. These findings advise further therapeutic interventions for MASLD.
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Affiliation(s)
- Jun Liu
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Sile Hu
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Lingyan Chen
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Charlotte Daly
- Department of Discovery Technology and Genomics, Novo Nordisk Research Centre Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | | | - Tom G Richardson
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Traylor
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Niall J Dempster
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | - Richard Mbasu
- Department of Discovery Technology and Genomics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Thomas Monfeuga
- AI & Digital Research, Research & Early Development, Novo Nordisk Research Centre Oxford, UK
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - V A Million
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
- Department of Discovery Technology and Genomics, Novo Nordisk Research Centre Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- AI & Digital Research, Research & Early Development, Novo Nordisk Research Centre Oxford, UK
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, USA
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, Utah, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Jeremy F Cobbold
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Jeremy W Tomlinson
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
| | | | - Joanna M M Howson
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
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96
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Goovaerts S, Hoskens H, Eller RJ, Herrick N, Musolf AM, Justice CM, Yuan M, Naqvi S, Lee MK, Vandermeulen D, Szabo-Rogers HL, Romitti PA, Boyadjiev SA, Marazita ML, Shaffer JR, Shriver MD, Wysocka J, Walsh S, Weinberg SM, Claes P. Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape. Nat Commun 2023; 14:7436. [PMID: 37973980 PMCID: PMC10654897 DOI: 10.1038/s41467-023-43237-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 11/01/2023] [Indexed: 11/19/2023] Open
Abstract
The cranial vault in humans is highly variable, clinically relevant, and heritable, yet its genetic architecture remains poorly understood. Here, we conduct a joint multi-ancestry and admixed multivariate genome-wide association study on 3D cranial vault shape extracted from magnetic resonance images of 6772 children from the ABCD study cohort yielding 30 genome-wide significant loci. Follow-up analyses indicate that these loci overlap with genomic risk loci for sagittal craniosynostosis, show elevated activity cranial neural crest cells, are enriched for processes related to skeletal development, and are shared with the face and brain. We present supporting evidence of regional localization for several of the identified genes based on expression patterns in the cranial vault bones of E15.5 mice. Overall, our study provides a comprehensive overview of the genetics underlying normal-range cranial vault shape and its relevance for understanding modern human craniofacial diversity and the etiology of congenital malformations.
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Affiliation(s)
- Seppe Goovaerts
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium.
| | - Hanne Hoskens
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Ryan J Eller
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Noah Herrick
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Anthony M Musolf
- Statistical Genetics Section, Computational and Statistical Genomics Branch, NHGRI, NIH, MD, Baltimore, USA
| | - Cristina M Justice
- Genometrics Section, Computational and Statistical Genomics Branch, Division of Intramural Research, NHGRI, NIH, Baltimore, MD, USA
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Meng Yuan
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Departments of Genetics and Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Myoung Keun Lee
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dirk Vandermeulen
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Heather L Szabo-Rogers
- Department of Anatomy, Physiology and Pharmacology, University of Saskatchewan, Saskatchewan, Canada
| | - Paul A Romitti
- Department of Epidemiology, College of Public Health, The University of Iowa, Iowa City, IA, USA
| | - Simeon A Boyadjiev
- Department of Pediatrics, University of California Davis, Sacramento, CA, USA
| | - Mary L Marazita
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - John R Shaffer
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, State College, PA, USA
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Susan Walsh
- Department of Biology, Indiana University Indianapolis, Indianapolis, IN, USA
| | - Seth M Weinberg
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Anthropology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium.
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium.
- Murdoch Children's Research Institute, Melbourne, VIC, Australia.
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97
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Gelfman S, Moscati A, Huergo SM, Wang R, Rajagopal V, Parikshak N, Pounraja VK, Chen E, Leblanc M, Hazlewood R, Freudenberg J, Cooper B, Ligocki AJ, Miller CG, Van Zyl T, Weyne J, Romano C, Sagdullaev B, Melander O, Baras A, Stahl EA, Coppola G. A large meta-analysis identifies genes associated with anterior uveitis. Nat Commun 2023; 14:7300. [PMID: 37949852 PMCID: PMC10638276 DOI: 10.1038/s41467-023-43036-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 10/30/2023] [Indexed: 11/12/2023] Open
Abstract
Anterior Uveitis (AU) is the inflammation of the anterior part of the eye, the iris and ciliary body and is strongly associated with HLA-B*27. We report AU exome sequencing results from eight independent cohorts consisting of 3,850 cases and 916,549 controls. We identify common genome-wide significant loci in HLA-B (OR = 3.37, p = 1.03e-196) and ERAP1 (OR = 0.86, p = 1.1e-08), and find IPMK (OR = 9.4, p = 4.42e-09) and IDO2 (OR = 3.61, p = 6.16e-08) as genome-wide significant genes based on the burden of rare coding variants. Dividing the cohort into HLA-B*27 positive and negative individuals, we find ERAP1 haplotype is strongly protective only for B*27-positive AU (OR = 0.73, p = 5.2e-10). Investigation of B*27-negative AU identifies a common signal near HLA-DPB1 (rs3117230, OR = 1.26, p = 2.7e-08), risk genes IPMK and IDO2, and several additional candidate risk genes, including ADGFR5, STXBP2, and ACHE. Taken together, we decipher the genetics underlying B*27-positive and -negative AU and identify rare and common genetic signals for both subtypes of disease.
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Affiliation(s)
- Sahar Gelfman
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Arden Moscati
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | | | - Rujin Wang
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Veera Rajagopal
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Neelroop Parikshak
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Vijay Kumar Pounraja
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Esteban Chen
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Michelle Leblanc
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Ralph Hazlewood
- Regeneron Pharmaceuticals, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Jan Freudenberg
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Blerta Cooper
- Regeneron Pharmaceuticals, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Ann J Ligocki
- Regeneron Pharmaceuticals, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Charles G Miller
- Regeneron Pharmaceuticals, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Tavé Van Zyl
- Regeneron Pharmaceuticals, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Jonathan Weyne
- Regeneron Pharmaceuticals, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Carmelo Romano
- Regeneron Pharmaceuticals, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Botir Sagdullaev
- Regeneron Pharmaceuticals, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Olle Melander
- Department of Clinical Sciences Malmö, Lund University, 221 00, Malmö, Sweden
| | - Aris Baras
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA
| | - Eli A Stahl
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA.
| | - Giovanni Coppola
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY, 10591, USA.
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98
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Keleher F, Lindsey HM, Kerestes R, Amiri H, Asarnow RF, Babikian T, Bartnik-Olson B, Bigler ED, Caeyenberghs K, Esopenko C, Ewing-Cobbs L, Giza CC, Goodrich-Hunsaker NJ, Hodges CB, Hoskinson KR, Irimia A, Königs M, Max JE, Newsome MR, Olsen A, Ryan NP, Schmidt AT, Stein DJ, Suskauer SJ, Ware AL, Wheeler AL, Zielinski BA, Thompson PM, Harding IH, Tate DF, Wilde EA, Dennis EL. Multimodal Analysis of Secondary Cerebellar Alterations After Pediatric Traumatic Brain Injury. JAMA Netw Open 2023; 6:e2343410. [PMID: 37966838 PMCID: PMC10652147 DOI: 10.1001/jamanetworkopen.2023.43410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 10/04/2023] [Indexed: 11/16/2023] Open
Abstract
Importance Traumatic brain injury (TBI) is known to cause widespread neural disruption in the cerebrum. However, less is known about the association of TBI with cerebellar structure and how such changes may alter executive functioning. Objective To investigate alterations in subregional cerebellum volume and cerebral white matter microstructure after pediatric TBI and examine subsequent changes in executive function. Design, Setting, and Participants This retrospective cohort study combined 12 data sets (collected between 2006 and 2020) from 9 sites in the Enhancing Neuroimaging Genetics Through Meta-Analysis Consortium Pediatric TBI working group in a mega-analysis of cerebellar structure. Participants with TBI or healthy controls (some with orthopedic injury) were recruited from trauma centers, clinics, and institutional trauma registries, some of which were followed longitudinally over a period of 0.7 to 1.9 years. Healthy controls were recruited from the surrounding community. Data analysis occurred from October to December 2022. Exposure Accidental mild complicated-severe TBI (msTBI) for those in the TBI group. Some controls received a diagnosis of orthopedic injury. Main Outcomes and Measures Volume of 18 cerebellar lobules and vermal regions were estimated from 3-dimensional T1-weighted magnetic resonance imaging (MRI) scans. White matter organization in 28 regions of interest was assessed with diffusion tensor MRI. Executive function was measured by parent-reported scores from the Behavior Rating Inventory of Executive Functioning. Results A total of 598 children and adolescents (mean [SD] age, 14.05 [3.06] years; range, 5.45-19.70 years; 386 male participants [64.5%]; 212 female participants [35.5%]) were included in the study, with 314 participants in the msTBI group, and 284 participants in the non-TBI group (133 healthy individuals and 151 orthopedically injured individuals). Significantly smaller total cerebellum volume (d = -0.37; 95% CI, -0.52 to -0.22; P < .001) and subregional cerebellum volumes (eg, corpus medullare; d = -0.43; 95% CI, -0.58 to -0.28; P < .001) were observed in the msTBI group. These alterations were primarily seen in participants in the chronic phase (ie, >6 months postinjury) of injury (total cerebellar volume, d = -0.55; 95% CI, -0.75 to -0.35; P < .001). Smaller cerebellum volumes were associated with higher scores on the Behavior Rating Inventory of Executive Functioning Global Executive Composite score (β = -208.9 mm3; 95% CI, -319.0 to -98.0 mm3; P = .008) and Metacognition Index score (β = -202.5 mm3; 95% CI, -319.0 to -85.0 mm3; P = .02). In a subset of 185 participants with longitudinal data, younger msTBI participants exhibited cerebellum volume reductions (β = 0.0052 mm3; 95% CI, 0.0013 to 0.0090 mm3; P = .01), and older participants slower growth rates. Poorer white matter organization in the first months postinjury was associated with decreases in cerebellum volume over time (β=0.52 mm3; 95% CI, 0.19 to 0.84 mm3; P = .005). Conclusions and Relevance In this cohort study of pediatric msTBI, our results demonstrated robust cerebellar volume alterations associated with pediatric TBI, localized to the posterior lobe. Furthermore, longitudinal cerebellum changes were associated with baseline diffusion tensor MRI metrics, suggesting secondary cerebellar atrophy. These results provide further understanding of secondary injury mechanisms and may point to new opportunities for intervention.
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Affiliation(s)
- Finian Keleher
- TBI and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City
| | - Hannah M. Lindsey
- TBI and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, Utah
| | - Rebecca Kerestes
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Houshang Amiri
- Institute of Neuropharmacology, Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran
| | - Robert F. Asarnow
- Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
- Brain Research Institute, University of California, Los Angeles
- Department of Psychology, University of California, Los Angeles
| | - Talin Babikian
- Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
- Steve Tisch BrainSPORT Program, University of California, Los Angeles
| | - Brenda Bartnik-Olson
- Department of Radiology, Loma Linda University Medical Center, Loma Linda, California
| | - Erin D. Bigler
- TBI and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City
- Department of Psychology, Brigham Young University, Provo, Utah
- Neuroscience Center, Brigham Young University, Provo, Utah
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Carrie Esopenko
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Linda Ewing-Cobbs
- Children’s Learning Institute, Department of Pediatrics, University of Texas Health Science Center at Houston
| | - Christopher C. Giza
- Steve Tisch BrainSPORT Program, University of California, Los Angeles
- Division of Neurology, Department of Pediatrics, Mattel Children’s Hospital University of California, Los Angeles
- Department of Neurosurgery, David Geffen School of Medicine at the University of California, Los Angeles
| | - Naomi J. Goodrich-Hunsaker
- TBI and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, Utah
- Department of Psychology, Brigham Young University, Provo, Utah
| | - Cooper B. Hodges
- Department of Psychology, Brigham Young University, Provo, Utah
- School of Social and Behavioral Sciences, Andrews University, Berrien Springs, Michigan
| | - Kristen R. Hoskinson
- Center for Biobehavioral Health, The Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, Ohio
- Department of Pediatrics, The Ohio State University College of Medicine, Columbus
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles
| | - Marsh Königs
- Emma Neuroscience Group, Emma Children’s Hospital, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Jeffrey E. Max
- Department of Psychiatry, University of California, San Diego, La Jolla
- Department of Psychiatry, Rady Children’s Hospital, San Diego, California
| | - Mary R. Newsome
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas
| | - Alexander Olsen
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Rehabilitation, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- NorHEAD-Norwegian Centre for Headache Research, Trondheim, Norway
| | - Nicholas P. Ryan
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
- Department of Clinical Sciences, Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Adam T. Schmidt
- Department of Psychological Sciences, Texas Tech University, Lubbock
| | - Dan J. Stein
- South African Medical Research Council Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Cape Town University, Cape Town, South Africa
- South African Medical Research Council Unit on Risk and Resilience in Mental Disorders, Neuroscience Institute, Cape Town University, Cape Town, South Africa
| | - Stacy J. Suskauer
- Kennedy Krieger Institute, Baltimore, Maryland
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Ashley L. Ware
- TBI and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City
- Department of Psychology, Georgia State University, Atlanta
| | - Anne L. Wheeler
- Neuroscience and Mental Health Program, Hospital for Sick Children, Toronto, Ontario, Canada
- Physiology Department, University of Toronto, Toronto, Ontario, Canada
| | - Brandon A. Zielinski
- TBI and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City
- Department of Pediatrics, University of Florida, Gainesville
- Department of Pediatrics, University of Utah School of Medicine, Salt Lake City
- Department of Neurology, University of Florida, Gainesville
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey
- Department of Neurology, University of Southern California, Los Angeles
- Department of Pediatrics, University of Southern California, Los Angeles
- Department of Psychiatry, University of Southern California, Los Angeles
- Department of Radiology, University of Southern California, Los Angeles
- Department of Engineering, University of Southern California, Los Angeles
- Department of Ophthalmology, University of Southern California, Los Angeles
| | - Ian H. Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - David F. Tate
- TBI and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, Utah
- Department of Psychology, Brigham Young University, Provo, Utah
| | - Elisabeth A. Wilde
- TBI and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, Utah
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas
| | - Emily L. Dennis
- TBI and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, Utah
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99
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Margaritte-Jeannin P, Vernet R, Budu-Aggrey A, Ege M, Madore AM, Linhard C, Mohamdi H, von Mutius E, Granell R, Demenais F, Laprise C, Bouzigon E, Dizier MH. TNS1 and NRXN1 Genes Interacting With Early-Life Smoking Exposure in Asthma-Plus-Eczema Susceptibility. ALLERGY, ASTHMA & IMMUNOLOGY RESEARCH 2023; 15:779-794. [PMID: 37957795 PMCID: PMC10643854 DOI: 10.4168/aair.2023.15.6.779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 05/15/2023] [Accepted: 06/13/2023] [Indexed: 11/15/2023]
Abstract
PURPOSE Numerous genes have been associated with allergic diseases (asthma, allergic rhinitis, and eczema), but they explain only part of their heritability. This is partly because most previous studies ignored complex mechanisms such as gene-environment (G-E) interactions and complex phenotypes such as co-morbidity. However, it was recently evidenced that the co-morbidity of asthma-plus-eczema appears as a sub-entity depending on specific genetic factors. Besides, evidence also suggest that gene-by-early life environmental tobacco smoke (ETS) exposure interactions play a role in asthma, but were never investigated for asthma-plus-eczema. To identify genetic variants interacting with ETS exposure that influence asthma-plus-eczema susceptibility. METHODS To conduct a genome-wide interaction study (GWIS) of asthma-plus-eczema according to ETS exposure, we applied a 2-stage strategy with a first selection of single nucleotide polymorphisms (SNPs) from genome-wide association meta-analysis to be tested at a second stage by interaction meta-analysis. All meta-analyses were conducted across 4 studies including a total of 5,516 European-ancestry individuals, of whom 1,164 had both asthma and eczema. RESULTS Two SNPs showed significant interactions with ETS exposure. They were located in 2 genes, NRXN1 (2p16) and TNS1 (2q35), never reported associated and/or interacting with ETS exposure for asthma, eczema or more generally for allergic diseases. TNS1 is a promising candidate gene because of its link to lung and skin diseases with possible interactive effect with tobacco smoke exposure. CONCLUSIONS This first GWIS of asthma-plus-eczema with ETS exposure underlines the importance of studying sub-phenotypes such as co-morbidities as well as G-E interactions to detect new susceptibility genes.
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Affiliation(s)
- Patricia Margaritte-Jeannin
- Université Paris Cité, UMRS 1124, INSERM, Genomic Epidemiology and Multifactorial Diseases Group, Paris, France
| | - Raphaël Vernet
- Université Paris Cité, UMRS 1124, INSERM, Genomic Epidemiology and Multifactorial Diseases Group, Paris, France
| | - Ashley Budu-Aggrey
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Markus Ege
- Dr von Hauner Children's Hospital, Ludwig Maximilian University; Institute of Asthma and Allergy prevention, Helmholtz Centre Munich; Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research, Munich, Germany
| | - Anne-Marie Madore
- Département des sciences fondamentales, Centre intersectoriel en santé durable (CISD), Université du Québec à Chicoutimi, Saguenay, QC, Canada
| | - Christophe Linhard
- Université Paris Cité, UMRS 1124, INSERM, Genomic Epidemiology and Multifactorial Diseases Group, Paris, France
| | - Hamida Mohamdi
- Université Paris Cité, UMRS 1124, INSERM, Genomic Epidemiology and Multifactorial Diseases Group, Paris, France
| | - Erika von Mutius
- Dr von Hauner Children's Hospital, Ludwig Maximilian University; Institute of Asthma and Allergy prevention, Helmholtz Centre Munich; Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research, Munich, Germany
| | - Raquell Granell
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Florence Demenais
- Université Paris Cité, UMRS 1124, INSERM, Genomic Epidemiology and Multifactorial Diseases Group, Paris, France
| | - Cathrine Laprise
- Département des sciences fondamentales, Centre intersectoriel en santé durable (CISD), Université du Québec à Chicoutimi, Saguenay, QC, Canada
| | - Emmanuelle Bouzigon
- Université Paris Cité, UMRS 1124, INSERM, Genomic Epidemiology and Multifactorial Diseases Group, Paris, France
| | - Marie-Hélène Dizier
- Université Paris Cité, UMRS 1124, INSERM, Genomic Epidemiology and Multifactorial Diseases Group, Paris, France.
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100
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Bojsen-Møller KN, Svane MS, Martinussen C, Dirksen C, Jørgensen NB, Jensen JEB, Jensen CZ, Torekov SS, Kristiansen VB, Rehfeld JF, Bork-Jensen J, Grarup N, Hansen T, Hartmann B, Holst JJ, Madsbad S. Primary weight loss failure after Roux-en-Y gastric bypass is characterized by impaired gut-hormone mediated regulation of food intake. Int J Obes (Lond) 2023; 47:1143-1151. [PMID: 37653071 PMCID: PMC10599997 DOI: 10.1038/s41366-023-01372-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 08/11/2023] [Accepted: 08/17/2023] [Indexed: 09/02/2023]
Abstract
BACKGROUND/OBJECTIVES After Roux-en-Y gastric bypass (RYGB) a subset of patients never obtain excess BMI loss (EBMIL) > 50% and are categorized as having primary weight loss (WL) failure. We hypothesized that postprandial concentrations of glucagon-like peptide 1 (GLP-1) and peptide YY (PYY) would be lower in patients with primary WL failure compared with patients with successfully maintained WL. Furthermore, that inhibition of gut hormone secretions would increase ad libitum food intake less in patients with primary WL failure. SUBJECTS/METHODS Twenty women with primary WL failure (LowEBMIL < 50%) were individually matched to twenty women with successful WL (HighEBMIL > 60%) on age, preoperative BMI and time from RYGB. On separate days performed in a random order, patient-blinded subcutaneous injections of octreotide or saline (placebo) were followed by a fixed breakfast and an ad libitum lunch with blood sampling for appetite regulating hormones and Visual-Analogue-Scale (VAS)-scoring of hunger/satiety. Furthermore, participants underwent gene variant analysis for GLP-1, PYY and their receptors, indirect calorimetry, dual-energy X-ray absorptiometry (DXA)-scans, 4-days at-home food registration and 14-days step counting. RESULTS On placebo days, postprandial GLP-1, PYY and cholecystokinin (CCK) concentrations were similar between groups after breakfast. Fasting ghrelin was lower in LowEBMIL, but the postprandial suppression was similar. LowEBMIL had lower satiety VAS-scores and less suppression of hunger VAS-scores. Gene variants did not differ between groups. Octreotide diminished GLP-1, PYY, CCK and ghrelin concentrations in both groups. Octreotide did not affect ad libitum food intake in LowEBMIL (-1% [-13, 12], mean [95%CI]), while food intake increased in HighEBMIL (+23% [2,44]). CONCLUSIONS Primary WL failure after RYGB was not characterized by impaired secretions of appetite regulating gut hormones. Interestingly, inhibition of gut hormone secretions with octreotide only increased food intake in patients with successful WL post-RYGB. Thus, an impaired central anorectic response to gut hormones may contribute to primary WL failure after RYGB.
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Affiliation(s)
- Kirstine Nyvold Bojsen-Møller
- Dept. of Endocrinology, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark.
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
| | - Maria Saur Svane
- Dept. of Endocrinology, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Christoffer Martinussen
- Dept. of Endocrinology, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Carsten Dirksen
- Dept. of Endocrinology, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Dept. of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Nils Bruun Jørgensen
- Dept. of Endocrinology, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Jens-Erik Beck Jensen
- Dept. of Endocrinology, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
- Dept. of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christian Zinck Jensen
- Dept. of Endocrinology, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Signe Sørensen Torekov
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Dept. of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Bolette Hartmann
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Dept. of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens Juul Holst
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Dept. of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sten Madsbad
- Dept. of Endocrinology, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Dept. of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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