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Hubers N, Hagenbeek FA, Pool R, Déjean S, Harms AC, Roetman PJ, van Beijsterveldt CEM, Fanos V, Ehli EA, Vermeiren RRJM, Bartels M, Hottenga JJ, Hankemeier T, van Dongen J, Boomsma DI. Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32955. [PMID: 37534875 DOI: 10.1002/ajmg.b.32955] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 06/13/2023] [Accepted: 07/11/2023] [Indexed: 08/04/2023]
Abstract
The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.
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Affiliation(s)
- Nikki Hubers
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Sébastien Déjean
- Toulouse Mathematics Institute, UMR 5219, University of Toulouse, CNRS, Toulouse, France
| | - Amy C Harms
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, the Netherlands
- The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Peter J Roetman
- LUMC-Curium, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Vassilios Fanos
- Department of Surgical Sciences, University of Cagliari and Neonatal Intensive Care Unit, Cagliari, Italy
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, South Dakota, USA
| | - Robert R J M Vermeiren
- LUMC-Curium, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
- Youz, Parnassia Group, the Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Thomas Hankemeier
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, the Netherlands
- The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
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Lu M, Feng R, Zhang C, Xiao Y, Yin C. Identifying Novel Drug Targets for Epilepsy Through a Brain Transcriptome-Wide Association Study and Protein-Wide Association Study with Chemical-Gene-Interaction Analysis. Mol Neurobiol 2023; 60:5055-5066. [PMID: 37246165 PMCID: PMC10415436 DOI: 10.1007/s12035-023-03382-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 05/04/2023] [Indexed: 05/30/2023]
Abstract
Epilepsy is a severe neurological condition affecting 50-65 million individuals worldwide that can lead to brain damage. Nevertheless, the etiology of epilepsy remains poorly understood. Meta-analyses of genome-wide association studies involving 15,212 epilepsy cases and 29,677 controls of the ILAE Consortium cohort were used to conduct transcriptome-wide association studies (TWAS) and protein-wide association studies (PWAS). Furthermore, a protein-protein interaction (PPI) network was generated using the STRING database, and significant epilepsy-susceptible genes were verified using chip data. Chemical-related gene set enrichment analysis (CGSEA) was performed to determine novel drug targets for epilepsy. TWAS analysis identified 21,170 genes, of which 58 were significant (TWASfdr < 0.05) in ten brain regions, and 16 differentially expressed genes were verified based on mRNA expression profiles. The PWAS identified 2249 genes, of which 2 were significant (PWASfdr < 0.05). Through chemical-gene set enrichment analysis, 287 environmental chemicals associated with epilepsy were identified. We identified five significant genes (WIPF1, IQSEC1, JAM2, ICAM3, and ZNF143) that had causal relationships with epilepsy. CGSEA identified 159 chemicals that were significantly correlated with epilepsy (Pcgsea < 0.05), such as pentobarbital, ketone bodies, and polychlorinated biphenyl. In summary, we performed TWAS, PWAS (for genetic factors), and CGSEA (for environmental factors) analyses and identified several epilepsy-associated genes and chemicals. The results of this study will contribute to our understanding of genetic and environmental factors for epilepsy and may predict novel drug targets.
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Affiliation(s)
- Mengnan Lu
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710054, Shanxi, China
| | - Ruoyang Feng
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shanxi, China
| | - Chenglin Zhang
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710054, Shanxi, China
| | - Yanfeng Xiao
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710054, Shanxi, China.
| | - Chunyan Yin
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710054, Shanxi, China.
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Lu M, Feng R, Liu Y, Qin Y, Deng H, Xiao Y, Yin C. Identifying celiac disease-related chemicals by transcriptome-wide association study and chemical-gene interaction analyses. Front Genet 2022; 13:990483. [PMID: 36118884 PMCID: PMC9478571 DOI: 10.3389/fgene.2022.990483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Accepted: 08/16/2022] [Indexed: 11/22/2022] Open
Abstract
Celiac disease (CeD) is one of the most common intestinal inflammatory diseases, and its incidence and prevalence have increased over time. CeD affects multiple organs and systems in the body, and environmental factors play a key role in its complex pathogenesis. Although gluten exposure is known to be the causative agent, many unknown environmental factors can trigger or exacerbate CeD. In this study, we investigated the influence of genetic and environmental factors on CeD. Data from a CeD genome-wide association study that included 12,041 CeD cases and 12,228 controls were used to conduct a transcriptome-wide association study (TWAS) using FUSION software. Gene expression reference data were obtained for the small intestine, whole blood, peripheral blood, and lymphocytes. We performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the significant genes identified by the TWAS and conducted a protein–protein interaction network analysis based on the STRING database to detect the function of TWAS-identified genes for CeD. We also performed a chemical-related gene set enrichment analysis (CGSEA) using the TWAS-identified genes to test the relationships between chemicals and CeD. The TWAS identified 8,692 genes, including 101 significant genes (padjusted < 0.05). The CGSEA identified 2,559 chemicals, including 178 chemicals that were significantly correlated with CeD. This study performed a TWAS (for genetic factors) and CGSEA (for environmental factors) and identified several CeD-associated genes and chemicals. The findings expand our understanding of the genetic and environmental factors related to immune-mediated diseases.
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Affiliation(s)
- Mengnan Lu
- Department of Pediatrics, The Second Affiliated Hospital of Xi’an Jiao Tong University, Xi’an, China
| | - Ruoyang Feng
- Department of Joint Surgery, HongHui Hospital, Xi’an Jiao Tong University, Xi’an, China
| | - Yuesheng Liu
- Department of Pediatrics, The Second Affiliated Hospital of Xi’an Jiao Tong University, Xi’an, China
| | - Yujie Qin
- Department of Pediatrics, The Second Affiliated Hospital of Xi’an Jiao Tong University, Xi’an, China
| | - Hongyang Deng
- Department of Pediatrics, The Second Affiliated Hospital of Xi’an Jiao Tong University, Xi’an, China
| | - Yanfeng Xiao
- Department of Pediatrics, The Second Affiliated Hospital of Xi’an Jiao Tong University, Xi’an, China
- *Correspondence: Yanfeng Xiao, ; Chunyan Yin,
| | - Chunyan Yin
- Department of Pediatrics, The Second Affiliated Hospital of Xi’an Jiao Tong University, Xi’an, China
- *Correspondence: Yanfeng Xiao, ; Chunyan Yin,
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Associations of parental mental disorders and age with childhood mental disorders: a population-based cohort study with four million offspring. Eur Child Adolesc Psychiatry 2021; 32:825-833. [PMID: 34802066 DOI: 10.1007/s00787-021-01914-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 11/11/2021] [Indexed: 12/13/2022]
Abstract
This Taiwan study examined the associations of parental age and mental disorders with the offspring risks of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), major depressive disorder (MDD), and bipolar disorder (BD). Children born between January 1991 and December 2004 in Taiwan were enrolled as the birth cohort (n = 4,138,151) and followed up until December 2011. A logistic regression analysis was performed to identify the odds ratio (OR). The advanced age effects were significant in ADHD (range of OR: 1.04 to 1.49) and ASD (range of OR: 1.35 to 2.27). Teenage mothers, teenage fathers, and fathers ≥ 50 years had higher offspring risks of MDD (range of OR: 1.24 to 1.46); and teenage mothers and fathers ≥ 50 years had increased offspring risks of BD (range of OR: 1.23 to 1.87). Both paternal and maternal mental disorders were associated with higher risks of within-disorder transmission for ADHD, ASD, MDD, and BD (range of OR: 2.64 to 30.41). Besides, parents with one of these four mental disorders (ADHD, ASD, MDD, and BD) might have higher risk of cross-disorder transmission to at least one of the other three mental disorders in the offspring (range of OR: 1.35 to 7.15). Parental age and mental disorders had complex and nuanced patterns in association with offspring mental disorders.
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Davis AP, Wiegers TC, Wiegers J, Grondin CJ, Johnson RJ, Sciaky D, Mattingly CJ. CTD Anatomy: analyzing chemical-induced phenotypes and exposures from an anatomical perspective, with implications for environmental health studies. Curr Res Toxicol 2021; 2:128-139. [PMID: 33768211 PMCID: PMC7990325 DOI: 10.1016/j.crtox.2021.03.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 02/01/2021] [Accepted: 03/01/2021] [Indexed: 12/12/2022] Open
Abstract
The Comparative Toxicogenomics Database (CTD) is a freely available public resource that curates and interrelates chemical, gene/protein, phenotype, disease, organism, and exposure data. CTD can be used to address toxicological mechanisms for environmental chemicals and facilitate the generation of testable hypotheses about how exposures affect human health. At CTD, manually curated interactions for chemical-induced phenotypes are enhanced with anatomy terms (tissues, fluids, and cell types) to describe the physiological system of the reported event. These same anatomy terms are used to annotate the human media (e.g., urine, hair, nail, blood, etc.) in which an environmental chemical was assayed for exposure. Currently, CTD uses more than 880 unique anatomy terms to contextualize over 255,000 chemical-phenotype interactions and 167,000 exposure statements. These annotations allow chemical-phenotype interactions and exposure data to be explored from a novel, anatomical perspective. Here, we describe CTD's anatomy curation process (including the construction of a controlled, interoperable vocabulary) and new anatomy webpages (that coalesce and organize the curated chemical-phenotype and exposure data sets). We also provide examples that demonstrate how this feature can be used to identify system- and cell-specific chemical-induced toxicities, help inform exposure data, prioritize phenotypes for environmental diseases, survey tissue and pregnancy exposomes, and facilitate data connections with external resources. Anatomy annotations advance understanding of environmental health by providing new ways to explore and survey chemical-induced events and exposure studies in the CTD framework.
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Affiliation(s)
- Allan Peter Davis
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, United States
| | - Thomas C. Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, United States
| | - Jolene Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, United States
| | - Cynthia J. Grondin
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, United States
| | - Robin J. Johnson
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, United States
| | - Daniela Sciaky
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, United States
| | - Carolyn J. Mattingly
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, United States
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC 27695, United States
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