1
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Treutlein J, Löhlein S, Einenkel KE, Picotin R, Diekhof EK, Gruber O. Association of Unc-51-like Kinase 4 ( ULK4) with the reactivity of the extended reward system in response to conditioned stimuli. World J Biol Psychiatry 2024:1-8. [PMID: 39185807 DOI: 10.1080/15622975.2024.2393381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 08/05/2024] [Accepted: 08/13/2024] [Indexed: 08/27/2024]
Abstract
OBJECTIVES ULK4 is an established candidate gene for mental disorders and antipsychotic treatment response. We investigated the association of functional genetic variation at the ULK4 locus with the human extended dopaminergic reward system using fMRI during the performance of a well-established reward paradigm. METHODS Two hundred and thirty-four patients were included in this study. Association of genetic variation in the ULK4 gene with reward system functioning were determined using the Desire-Reason-Dilemma (DRD) paradigm which allows to assess brain activation in response to conditioned reward stimuli. RESULTS Variant prioritisation revealed the strongest functional signatures for the ULK4 variant rs17215589, coding for amino acid exchange Ala715Thr. For rs17215589 minor allele carriers, we detected increased activation responses to conditioned reward stimuli in the ventral tegmental area, nucleus accumbens and several cortical brain regions of the extended reward system. CONCLUSIONS Our findings provide further evidence in humans that genetic variation in ULK4 may increase the vulnerability to mental disorders, by modulating the extended reward system function. Future studies are needed to confirm the modulation of the extended reward system by ULK4 and to specify the role of this mechanism in the pathogenesis of psychiatric disorders.
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Affiliation(s)
- Jens Treutlein
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Simone Löhlein
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
- Institute of Flight Systems, University of the Bundeswehr Munich, Munich, Germany
| | - Karolin E Einenkel
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Rosanne Picotin
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Esther K Diekhof
- Institute for Cell- and Systemsbiology of Animals, Department of Biology, Neuroendocrinology Unit, Universität Hamburg, Hamburg, Germany
- Department of Psychiatry and Psychotherapy, Center for Translational Research in Systems Neuroscience and Clinical Psychiatry, Georg August University Göttingen, Göttingen, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
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Zhao S, Chi L, Chen H. CEGA: a method for inferring natural selection by comparative population genomic analysis across species. Genome Biol 2023; 24:219. [PMID: 37789379 PMCID: PMC10548728 DOI: 10.1186/s13059-023-03068-8] [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: 07/26/2022] [Accepted: 09/20/2023] [Indexed: 10/05/2023] Open
Abstract
We developed maximum likelihood method for detecting positive selection or balancing selection using multilocus or genomic polymorphism and divergence data from two species. The method is especially useful for investigating natural selection in noncoding regions. Simulations demonstrate that the method outperforms existing methods in detecting both positive and balancing selection. We apply the method to population genomic data from human and chimpanzee. The list of genes identified under selection in the noncoding regions is prominently enriched in pathways related to the brain and nervous system. Therefore, our method will serve as a useful tool for comparative population genomic analysis.
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Affiliation(s)
- Shilei Zhao
- CAS Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
- China National Center for Bioinformation, Beijing, 100101, China
- School of Future Technology, College of Life Sciences and Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lianjiang Chi
- CAS Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
- China National Center for Bioinformation, Beijing, 100101, China
| | - Hua Chen
- CAS Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.
- China National Center for Bioinformation, Beijing, 100101, China.
- School of Future Technology, College of Life Sciences and Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100049, China.
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
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3
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Abrishamcar S, Chen J, Feil D, Kilanowski A, Koen N, Vanker A, Wedderburn CJ, Donald KA, Zar HJ, Stein DJ, Hüls A. DNA methylation as a potential mediator of the association between prenatal tobacco and alcohol exposure and child neurodevelopment in a South African birth cohort. Transl Psychiatry 2022; 12:418. [PMID: 36180424 PMCID: PMC9525659 DOI: 10.1038/s41398-022-02195-3] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 09/09/2022] [Accepted: 09/20/2022] [Indexed: 01/12/2023] Open
Abstract
Prenatal tobacco exposure (PTE) and prenatal alcohol exposure (PAE) have been associated with an increased risk of delayed neurodevelopment in children as well as differential newborn DNA methylation (DNAm). However, the biological mechanisms connecting PTE and PAE, DNAm, and neurodevelopment are largely unknown. Here we aim to determine whether differential DNAm mediates the association between PTE and PAE and neurodevelopment at 6 (N = 112) and 24 months (N = 184) in children from the South African Drakenstein Child Health Study. PTE and PAE were assessed antenatally using urine cotinine measurements and the ASSIST questionnaire, respectively. Cord blood DNAm was measured using the EPIC and 450 K BeadChips. Neurodevelopment (cognitive, language, motor, adaptive behavior, socioemotional) was measured using the Bayley Scales of Infant and Toddler Development, Third Edition. We constructed methylation risk scores (MRS) for PTE and PAE and conducted causal mediation analysis (CMA) with these MRS as mediators. Next, we conducted a high-dimensional mediation analysis to identify individual CpG sites as potential mediators, followed by a CMA to estimate the average causal mediation effects (ACME) and total effect (TE). PTE and PAE were associated with neurodevelopment at 6 but not at 24 months. PTE MRS reached a prediction accuracy (R2) of 0.23 but did not significantly mediate the association between PTE and neurodevelopment. PAE MRS was not predictive of PAE (R2 = 0.006). For PTE, 31 CpG sites and eight CpG sites were identified as significant mediators (ACME and TE P < 0.05) for the cognitive and motor domains at 6 months, respectively. For PAE, 16 CpG sites and 1 CpG site were significant mediators for the motor and adaptive behavior domains at 6 months, respectively. Several of the associated genes, including MAD1L1, CAMTA1, and ALDH1A2 have been implicated in neurodevelopmental delay, suggesting that differential DNAm may partly explain the biological mechanisms underlying the relationship between PTE and PAE and child neurodevelopment.
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Affiliation(s)
- Sarina Abrishamcar
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Junyu Chen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Dakotah Feil
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Anna Kilanowski
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany
| | - Nastassja Koen
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Aneesa Vanker
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
| | - Catherine J Wedderburn
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- Department of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK
| | - Kirsten A Donald
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
| | - Heather J Zar
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
| | - Dan J Stein
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
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Li W, Zhang CY, Liu J, Guan F, Shao M, Zhang L, Liu Q, Yang Y, Su X, Zhang Y, Xiao X, Luo XJ, Li M, Lv L. Identification of a Risk Locus at 7p22.3 for Schizophrenia and Bipolar Disorder in East Asian Populations. Front Genet 2021; 12:789512. [PMID: 34976021 PMCID: PMC8719163 DOI: 10.3389/fgene.2021.789512] [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: 10/05/2021] [Accepted: 11/23/2021] [Indexed: 12/03/2022] Open
Abstract
Background: Shared psychopathological features and mechanisms have been observed between schizophrenia (SZ) and bipolar disorder (BD), but their common risk genes and full genetic architectures remain to be fully characterized. The genome-wide association study (GWAS) datasets offer the opportunity to explore this scientific question using combined genetic data from enormous samples, ultimately allowing a better understanding of the onset and development of these illnesses. Methods: We have herein performed a genome-wide meta-analysis in two GWAS datasets of SZ and BD respectively (24,600 cases and 40,012 controls in total, discovery sample), followed by replication analyses in an independent sample of 4,918 SZ cases and 5,506 controls of Han Chinese origin (replication sample). The risk SNPs were then explored for their correlations with mRNA expression of nearby genes in multiple expression quantitative trait loci (eQTL) datasets. Results: The single nucleotide polymorphisms (SNPs) rs1637749 and rs3800908 at 7p22.3 region were significant in both discovery and replication samples, and exhibited genome-wide significant associations when combining all East Asian SZ and BD samples (29,518 cases and 45,518 controls). The risk SNPs were also significant in GWAS of SZ and BD among Europeans. Both risk SNPs significantly predicted lower expression of MRM2 in the whole blood and brain samples in multiple datasets, which was consistent with its reduced mRNA level in the brains of SZ patients compared with normal controls. The risk SNPs were also associated with MAD1L1 expression in the whole blood sample. Discussion: We have identified a novel genome-wide risk locus associated with SZ and BD in East Asians, adding further support for the putative common genetic risk of the two illnesses. Our study also highlights the necessity and importance of mining public datasets to explore risk genes for complex psychiatric diseases.
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Affiliation(s)
- Wenqiang Li
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Chu-Yi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Jiewei Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Fanglin Guan
- Department of Forensic Psychiatry, School of Medicine and Forensics, Xi’an Jiaotong University Health Science Center, Xi’an, China
| | - Minglong Shao
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Luwen Zhang
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Qing Liu
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Yongfeng Yang
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Xi Su
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Yan Zhang
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Xiong-Jian Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- *Correspondence: Ming Li, ; Luxian Lv,
| | - Luxian Lv
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
- Henan Province People’s Hospital, Zhengzhou, China
- *Correspondence: Ming Li, ; Luxian Lv,
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5
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Liu X, Xie H, Fu Z, Yao Q, Han T, Zhan D, Lin Z, Zhu H. MAD1L1 and TSNARE gene polymorphisms are associated with schizophrenia susceptibility in the Han Chinese population. BMC Med Genomics 2021; 14:218. [PMID: 34481484 PMCID: PMC8418747 DOI: 10.1186/s12920-021-01070-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 08/23/2021] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Schizophrenia (SCZ) is a severe mental illness with high heritability. This study aimed to explore the correlation between MAD1L1, TSNARE polymorphisms and SCZ susceptibility. METHODS A total of 493 SCZ patients and 493 healthy controls were included. The genotypes of MAD1L1 and TSNARE polymorphisms were identified by Agena MassARRAY platform. Odds ratio (OR) and 95% confidence intervals (CIs) were tested via logistic regression analysis in multiple genetic models and different subgroups. RESULTS We observed that AG genotype of rs1107592, AG genotype of rs4976976, and CA genotype of rs67756423 decreased the susceptibility to SCZ (p < 0.05). Age stratification analysis showed that the TC genotype of rs12666575, AG genotype of rs1107592, and AG genotype of rs4976976 decreased the risk of SCZ individuals older than 36 years (p < 0.05). In addition, the AG and AA genotype of rs4976976, the CA genotype of rs67756423 were associated with a lower risk of SCZ in males (p < 0.05). In females, the TT genotype of rs12666575 in recessive model, the AG and AA-AG genotype of rs1107592 in heterozygote and dominant model, could reduce the susceptibility to SCZ (p < 0.05). However, no significant association was found after Bonferroni correction. CONCLUSIONS Our results suggest that MAD1L1 and TSNARE genetic polymorphisms exert a protective role in the risk of SCZ. These findings provide evidence that MAD1L1 and TSNARE may serve as potential biomarkers of SCZ. However, a replication experiment in a cohort with large sample size are required to confirm our findings. Trial registration Not applicable.
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Affiliation(s)
- Xianglai Liu
- Institute of Mental Health, Hainan Provincial Anning Hospital, No 10, Nanhai Avenue East, Haikou, 571100, Hainan, China.
| | - Hailing Xie
- First Department of Psychiatry, Hainan Provincial Anning Hospital, Haikou, 571100, Hainan, China
| | - Zejuan Fu
- Department of Nursing, Hainan Provincial Anning Hospital, Haikou, 571100, Hainan, China
| | - Qiankun Yao
- Department of Prevention Section, Hainan Provincial Anning Hospital, Haikou, 571100, Hainan, China
| | - Tianming Han
- Institute of Mental Health, Hainan Provincial Anning Hospital, No 10, Nanhai Avenue East, Haikou, 571100, Hainan, China
| | - Dafei Zhan
- Institute of Mental Health, Hainan Provincial Anning Hospital, No 10, Nanhai Avenue East, Haikou, 571100, Hainan, China
| | - Zhan Lin
- Institute of Mental Health, Hainan Provincial Anning Hospital, No 10, Nanhai Avenue East, Haikou, 571100, Hainan, China
| | - Hong Zhu
- Institute of Mental Health, Hainan Provincial Anning Hospital, No 10, Nanhai Avenue East, Haikou, 571100, Hainan, China
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6
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Quilter CR, Harvey KM, Bauer J, Skinner BM, Gomez M, Shrivastava M, Doel AM, Drammeh S, Dunger DB, Moore SE, Ong KK, Prentice AM, Bernstein RM, Sargent CA, Affara NA. Identification of methylation changes associated with positive and negative growth deviance in Gambian infants using a targeted methyl sequencing approach of genomic DNA. FASEB Bioadv 2021; 3:205-230. [PMID: 33842847 PMCID: PMC8019263 DOI: 10.1096/fba.2020-00101] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 11/25/2020] [Accepted: 12/16/2020] [Indexed: 12/20/2022] Open
Abstract
Low birthweight and reduced height gain during infancy (stunting) may arise at least in part from adverse early life environments that trigger epigenetic reprogramming that may favor survival. We examined differential DNA methylation patterns using targeted methyl sequencing of regions regulating gene activity in groups of rural Gambian infants: (a) low and high birthweight (DNA from cord blood (n = 16 and n = 20, respectively), from placental trophoblast tissue (n = 21 and n = 20, respectively), and DNA from peripheral blood collected from infants at 12 months of age (n = 23 and n = 17, respectively)), and, (b) the top 10% showing rapid postnatal length gain (high, n = 20) and the bottom 10% showing slow postnatal length gain (low, n = 20) based on z score change between birth and 12 months of age (LAZ) (DNA from peripheral blood collected from infants at 12 months of age). Using BiSeq analysis to identify significant methylation marks, for birthweight, four differentially methylated regions (DMRs) were identified in trophoblast DNA, compared to 68 DMRs in cord blood DNA, and 54 DMRs in 12‐month peripheral blood DNA. Twenty‐five DMRs were observed to be associated with high and low length for age (LAZ) at 12 months. With the exception of five loci (associated with two different genes), there was no overlap between these groups of methylation marks. Of the 194 CpG methylation marks contained within DMRs, 106 were located to defined gene regulatory elements (promoters, CTCF‐binding sites, transcription factor‐binding sites, and enhancers), 58 to gene bodies (introns or exons), and 30 to intergenic DNA. Distinct methylation patterns associated with birthweight between comparison groups were observed in DNA collected at birth (at the end of intrauterine growth window) compared to those established by 12 months (near the infancy/childhood growth transition). The longitudinal differences in methylation patterns may arise from methylation adjustments, changes in cellular composition of blood or both that continue during the critical postnatal growth period, and in response to early nutritional and infectious environmental exposures with impacts on growth and longer‐term health outcomes.
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Affiliation(s)
- Claire R Quilter
- Department of Pathology University of Cambridge Cambridge UK.,Present address: East Midlands & East of England NHS Genomic Laboratory Hub, Genomics Laboratories Cambridge University Hospitals NHS Foundation Trust Cambridge UK
| | - Kerry M Harvey
- Department of Pathology University of Cambridge Cambridge UK
| | - Julien Bauer
- Department of Pathology University of Cambridge Cambridge UK
| | - Benjamin M Skinner
- Department of Pathology University of Cambridge Cambridge UK.,School of Life Sciences University of Essex Colchester UK
| | - Maria Gomez
- Department of Pathology University of Cambridge Cambridge UK.,Present address: Kennedy Institute of Rheumatology University of Oxford Oxford UK
| | - Manu Shrivastava
- Department of Pathology University of Cambridge Cambridge UK.,Present address: Oxford University Hospitals Oxford UK
| | - Andrew M Doel
- Department of Women and Children's Health King's College London London UK.,MRC Unit The Gambia at London School of Hygiene and Tropical Medicine Banjul The Gambia
| | - Saikou Drammeh
- MRC Unit The Gambia at London School of Hygiene and Tropical Medicine Banjul The Gambia
| | - David B Dunger
- MRC Epidemiology Unit University of Cambridge School of Clinical Medicine Cambridge UK
| | - Sophie E Moore
- Department of Women and Children's Health King's College London London UK.,MRC Unit The Gambia at London School of Hygiene and Tropical Medicine Banjul The Gambia
| | - Ken K Ong
- MRC Epidemiology Unit University of Cambridge School of Clinical Medicine Cambridge UK.,Department of Paediatrics University of Cambridge School of Clinical Medicine Cambridge UK.,Institute of Metabolic Science Cambridge Biomedical Campus Cambridge Cambridge UK
| | - Andrew M Prentice
- MRC Unit The Gambia at London School of Hygiene and Tropical Medicine Banjul The Gambia
| | - Robin M Bernstein
- Growth and Development Lab Department of Anthropology University of Colorado Boulder CO USA.,Institute of Behavioural Science University of Colorado Boulder CO USA
| | | | - Nabeel A Affara
- Department of Pathology University of Cambridge Cambridge UK
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7
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Nakamura Y, Okada N, Koshiyama D, Kamiya K, Abe O, Kunimatsu A, Okanoya K, Kasai K, Koike S. Differences in Functional Connectivity Networks Related to the Midbrain Dopaminergic System-Related Area in Various Psychiatric Disorders. Schizophr Bull 2020; 46:1239-1248. [PMID: 31901932 PMCID: PMC7505191 DOI: 10.1093/schbul/sbz121] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Disruptions in the dopamine system have been observed in psychiatric disorders. Since dopamine is mainly produced in the ventral tegmental area (VTA), elucidating the differences in the VTA neural network across psychiatric disorders would facilitate a greater understanding of the pathophysiological mechanisms underlying these disorders. However, no study has compared VTA-seed-based functional connectivity across psychiatric disorders. Therefore, we conducted a resting-state functional magnetic resonance imaging (rs-fMRI) study to perform a seed-based fMRI analysis, using the VTA as a seed. METHODS We included participants with major depressive disorder (MDD; n = 45), schizophrenia (n = 32), and bipolar disorder (BPD; n = 30), along with healthy control participants (n = 46) who were matched for age, gender, and handedness. RESULTS The results showed that patients with MDD and BPD had altered VTA-related connectivity in the superior frontal gyrus, frontal pole regions, hippocampus, cerebellum, and posterior cingulate cortex. Some of these differences in connectivity were also found between affective disorders and schizophrenia; however, there were no differences between the schizophrenia and control groups. Connectivity between the VTA and the hippocampus was correlated with positive symptoms in the schizophrenia group. The connectivity was not associated with medication dose, and the results remained significant after controlling for dose. CONCLUSIONS The results suggest that altered brain functional connectivity related to VTA networks could be associated with the distinctive pathophysiologies of psychiatric disorders, especially affective disorders.
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Affiliation(s)
- Yuko Nakamura
- Center for Integrative Science of Human Behavior, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science at the University of Tokyo, Tokyo, Japan
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan
| | - Daisuke Koshiyama
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kouhei Kamiya
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Akira Kunimatsu
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Department of Radiology, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Kazuo Okanoya
- Center for Integrative Science of Human Behavior, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science at the University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
| | - Kiyoto Kasai
- Center for Integrative Science of Human Behavior, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science at the University of Tokyo, Tokyo, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
| | - Shinsuke Koike
- Center for Integrative Science of Human Behavior, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science at the University of Tokyo, Tokyo, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
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8
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Goodman SJ, Burton CL, Butcher DT, Siu MT, Lemire M, Chater-Diehl E, Turinsky AL, Brudno M, Soreni N, Rosenberg D, Fitzgerald KD, Hanna GL, Anagnostou E, Arnold PD, Crosbie J, Schachar R, Weksberg R. Obsessive-compulsive disorder and attention-deficit/hyperactivity disorder: distinct associations with DNA methylation and genetic variation. J Neurodev Disord 2020; 12:23. [PMID: 32799817 PMCID: PMC7429807 DOI: 10.1186/s11689-020-09324-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 07/28/2020] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND A growing body of research has demonstrated associations between specific neurodevelopmental disorders and variation in DNA methylation (DNAm), implicating this molecular mark as a possible contributor to the molecular etiology of these disorders and/or as a novel disease biomarker. Furthermore, genetic risk variants of neurodevelopmental disorders have been found to be enriched at loci associated with DNAm patterns, referred to as methylation quantitative trait loci (mQTLs). METHODS We conducted two epigenome-wide association studies in individuals with attention-deficit/hyperactivity disorder (ADHD) or obsessive-compulsive disorder (OCD) (aged 4-18 years) using DNA extracted from saliva. DNAm data generated on the Illumina Human Methylation 450 K array were used to examine the interaction between genetic variation and DNAm patterns associated with these disorders. RESULTS Using linear regression followed by principal component analysis, individuals with the most endorsed symptoms of ADHD or OCD were found to have significantly more distinct DNAm patterns from controls, as compared to all cases. This suggested that the phenotypic heterogeneity of these disorders is reflected in altered DNAm at specific sites. Further investigations of the DNAm sites associated with each disorder revealed that despite little overlap of these DNAm sites across the two disorders, both disorders were significantly enriched for mQTLs within our sample. CONCLUSIONS Our DNAm data provide insights into the regulatory changes associated with genetic variation, highlighting their potential utility both in directing GWAS and in elucidating the pathophysiology of neurodevelopmental disorders.
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Affiliation(s)
- Sarah J Goodman
- Genetics and Genome Biology, SickKids Hospital, Toronto, ON, Canada
| | - Christie L Burton
- Neurosciences and Mental Health Program, SickKids Hospital, Toronto, ON, Canada
| | - Darci T Butcher
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Michelle T Siu
- Biochemical Genetics Laboratory, Alberta Children's Hospital, Calgary, AB, Canada
| | - Mathieu Lemire
- Neurosciences and Mental Health Program, SickKids Hospital, Toronto, ON, Canada
| | | | - Andrei L Turinsky
- Genetics and Genome Biology, SickKids Hospital, Toronto, ON, Canada
- Centre for Computational Medicine, SickKids Hospital, Toronto, ON, Canada
| | - Michael Brudno
- Genetics and Genome Biology, SickKids Hospital, Toronto, ON, Canada
- Centre for Computational Medicine, SickKids Hospital, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
| | - Noam Soreni
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - David Rosenberg
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA
| | - Kate D Fitzgerald
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Gregory L Hanna
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Evdokia Anagnostou
- Holland Bloorview Kids Rehabilitation Hospital Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Paul D Arnold
- Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada
- Departments of Psychiatry and Medical Genetics, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Jennifer Crosbie
- Neurosciences and Mental Health Program, SickKids Hospital, Toronto, ON, Canada
| | - Russell Schachar
- Neurosciences and Mental Health Program, SickKids Hospital, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Rosanna Weksberg
- Genetics and Genome Biology, SickKids Hospital, Toronto, ON, Canada.
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Division of Clinical and Metabolic Genetics, SickKids Hospital, Toronto, ON, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
- Department of Paediatrics, University of Toronto, Toronto, ON, Canada.
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9
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Le-Niculescu H, Roseberry K, Levey DF, Rogers J, Kosary K, Prabha S, Jones T, Judd S, McCormick MA, Wessel AR, Williams A, Phalen PL, Mamdani F, Sequeira A, Kurian SM, Niculescu AB. Towards precision medicine for stress disorders: diagnostic biomarkers and targeted drugs. Mol Psychiatry 2020; 25:918-938. [PMID: 30862937 PMCID: PMC7192849 DOI: 10.1038/s41380-019-0370-z] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Revised: 01/14/2019] [Accepted: 01/23/2019] [Indexed: 01/09/2023]
Abstract
The biological fingerprint of environmental adversity may be key to understanding health and disease, as it encompasses the damage induced as well as the compensatory reactions of the organism. Metabolic and hormonal changes may be an informative but incomplete window into the underlying biology. We endeavored to identify objective blood gene expression biomarkers for psychological stress, a subjective sensation with biological roots. To quantify the stress perception at a particular moment in time, we used a simple visual analog scale for life stress in psychiatric patients, a high-risk group. Then, using a stepwise discovery, prioritization, validation, and testing in independent cohort design, we were successful in identifying gene expression biomarkers that were predictive of high-stress states and of future psychiatric hospitalizations related to stress, more so when personalized by gender and diagnosis. One of the top biomarkers that survived discovery, prioritization, validation, and testing was FKBP5, a well-known gene involved in stress response, which serves as a de facto reassuring positive control. We also compared our biomarker findings with telomere length (TL), another well-established biological marker of psychological stress and show that newly identified predictive biomarkers such as NUB1, APOL3, MAD1L1, or NKTR are comparable or better state or trait predictors of stress than TL or FKBP5. Over half of the top predictive biomarkers for stress also had prior evidence of involvement in suicide, and the majority of them had evidence in other psychiatric disorders, providing a molecular underpinning for the effects of stress in those disorders. Some of the biomarkers are targets of existing drugs, of potential utility in patient stratification, and pharmacogenomics approaches. Based on our studies and analyses, the biomarkers with the best overall convergent functional evidence (CFE) for involvement in stress were FKBP5, DDX6, B2M, LAIR1, RTN4, and NUB1. Moreover, the biomarker gene expression signatures yielded leads for possible new drug candidates and natural compounds upon bioinformatics drug repurposing analyses, such as calcium folinate and betulin. Our work may lead to improved diagnosis and treatment for stress disorders such as PTSD, that result in decreased quality of life and adverse outcomes, including addictions, violence, and suicide.
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Affiliation(s)
- H Le-Niculescu
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - K Roseberry
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - D F Levey
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - J Rogers
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - K Kosary
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - S Prabha
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - T Jones
- Indianapolis VA Medical Center, Indianapolis, IN, USA
| | - S Judd
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - M A McCormick
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - A R Wessel
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - A Williams
- Indianapolis VA Medical Center, Indianapolis, IN, USA
| | - P L Phalen
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - F Mamdani
- Department of Psychiatry and Human Behavior, UC Irvine, Irvine, CA, USA
| | - A Sequeira
- Department of Psychiatry and Human Behavior, UC Irvine, Irvine, CA, USA
| | - S M Kurian
- Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA, USA
| | - A B Niculescu
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indianapolis VA Medical Center, Indianapolis, IN, USA.
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA.
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10
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Espeso-Gil S, Halene T, Bendl J, Kassim B, Ben Hutta G, Iskhakova M, Shokrian N, Auluck P, Javidfar B, Rajarajan P, Chandrasekaran S, Peter CJ, Cote A, Birnbaum R, Liao W, Borrman T, Wiseman J, Bell A, Bannon MJ, Roussos P, Crary JF, Weng Z, Marenco S, Lipska B, Tsankova NM, Huckins L, Jiang Y, Akbarian S. A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons. Genome Med 2020; 12:19. [PMID: 32075678 PMCID: PMC7031924 DOI: 10.1186/s13073-020-0715-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 01/30/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Midbrain dopaminergic neurons (MDN) represent 0.0005% of the brain's neuronal population and mediate cognition, food intake, and metabolism. MDN are also posited to underlay the neurobiological dysfunction of schizophrenia (SCZ), a severe neuropsychiatric disorder that is characterized by psychosis as well as multifactorial medical co-morbidities, including metabolic disease, contributing to markedly increased morbidity and mortality. Paradoxically, however, the genetic risk sequences of psychosis and traits associated with metabolic disease, such as body mass, show very limited overlap. METHODS We investigated the genomic interaction of SCZ with medical conditions and traits, including body mass index (BMI), by exploring the MDN's "spatial genome," including chromosomal contact landscapes as a critical layer of cell type-specific epigenomic regulation. Low-input Hi-C protocols were applied to 5-10 × 103 dopaminergic and other cell-specific nuclei collected by fluorescence-activated nuclei sorting from the adult human midbrain. RESULTS The Hi-C-reconstructed MDN spatial genome revealed 11 "Euclidean hot spots" of clustered chromatin domains harboring risk sequences for SCZ and elevated BMI. Inter- and intra-chromosomal contacts interconnecting SCZ and BMI risk sequences showed massive enrichment for brain-specific expression quantitative trait loci (eQTL), with gene ontologies, regulatory motifs and proteomic interactions related to adipogenesis and lipid regulation, dopaminergic neurogenesis and neuronal connectivity, and reward- and addiction-related pathways. CONCLUSIONS We uncovered shared nuclear topographies of cognitive and metabolic risk variants. More broadly, our PsychENCODE sponsored Hi-C study offers a novel genomic approach for the study of psychiatric and medical co-morbidities constrained by limited overlap of their respective genetic risk architectures on the linear genome.
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Affiliation(s)
- Sergio Espeso-Gil
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tobias Halene
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- J.J. Peters Veterans Affairs Hospital, Bronx, NY, USA
| | - Jaroslav Bendl
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bibi Kassim
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gabriella Ben Hutta
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marina Iskhakova
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Neda Shokrian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pavan Auluck
- Human Brain Collection Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Behnam Javidfar
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Prashanth Rajarajan
- MDPhD Program in the Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sandhya Chandrasekaran
- MDPhD Program in the Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Cyril J Peter
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alanna Cote
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rebecca Birnbaum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Will Liao
- New York Genome Center, New York, NY, 10013, USA
| | - Tyler Borrman
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, 01605, USA
| | - Jennifer Wiseman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aaron Bell
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael J Bannon
- Department of Pharmacology, Wayne State University, Detroit, MI, USA
| | - Panagiotis Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- J.J. Peters Veterans Affairs Hospital, Bronx, NY, USA
- Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Crary
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, 01605, USA
| | - Stefano Marenco
- Human Brain Collection Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Barbara Lipska
- Human Brain Collection Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Nadejda M Tsankova
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Laura Huckins
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yan Jiang
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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11
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Snijders C, Maihofer AX, Ratanatharathorn A, Baker DG, Boks MP, Geuze E, Jain S, Kessler RC, Pishva E, Risbrough VB, Stein MB, Ursano RJ, Vermetten E, Vinkers CH, Smith AK, Uddin M, Rutten BPF, Nievergelt CM. Longitudinal epigenome-wide association studies of three male military cohorts reveal multiple CpG sites associated with post-traumatic stress disorder. Clin Epigenetics 2020; 12:11. [PMID: 31931860 PMCID: PMC6958602 DOI: 10.1186/s13148-019-0798-7] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 12/19/2019] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Epigenetic mechanisms have been suggested to play a role in the development of post-traumatic stress disorder (PTSD). Here, blood-derived DNA methylation data (HumanMethylation450 BeadChip) collected prior to and following combat exposure in three cohorts of male military members were analyzed to assess whether DNA methylation profiles are associated with the development of PTSD. A total of 123 PTSD cases and 143 trauma-exposed controls were included in the analyses. The Psychiatric Genomics Consortium (PGC) PTSD EWAS QC pipeline was used on all cohorts, and results were combined using a sample size weighted meta-analysis in a two-stage design. In stage one, we jointly analyzed data of two new cohorts (N = 126 and 78) for gene discovery, and sought to replicate significant findings in a third, previously published cohort (N = 62) to assess the robustness of our results. In stage 2, we aimed at maximizing power for gene discovery by combining all three cohorts in a meta-analysis. RESULTS Stage 1 analyses identified four CpG sites in which, conditional on pre-deployment DNA methylation, post-deployment DNA methylation was significantly associated with PTSD status after epigenome-wide adjustment for multiple comparisons. The most significant (intergenic) CpG cg05656210 (p = 1.0 × 10-08) was located on 5q31 and significantly replicated in the third cohort. In addition, 19 differentially methylated regions (DMRs) were identified, but failed replication. Stage 2 analyses identified three epigenome-wide significant CpGs, the intergenic CpG cg05656210 and two additional CpGs located in MAD1L1 (cg12169700) and HEXDC (cg20756026). Interestingly, cg12169700 had an underlying single nucleotide polymorphism (SNP) which was located within the same LD block as a recently identified PTSD-associated SNP in MAD1L1. Stage 2 analyses further identified 12 significant differential methylated regions (DMRs), 1 of which was located in MAD1L1 and 4 were situated in the human leukocyte antigen (HLA) region. CONCLUSIONS This study suggests that the development of combat-related PTSD is associated with distinct methylation patterns in several genomic positions and regions. Our most prominent findings suggest the involvement of the immune system through the HLA region and HEXDC, and MAD1L1 which was previously associated with PTSD.
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Affiliation(s)
- Clara Snijders
- Department of Psychiatry and Neuropsychology, School for Mental health and Neuroscience, Maastricht University, Maastricht, Limburg, Netherlands
| | - Adam X Maihofer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | | | - Dewleen G Baker
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Psychiatry Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Marco P Boks
- Department of Psychiatry, UMC Utrecht Brain Center, Utrecht, Utrecht, Netherlands
| | - Elbert Geuze
- Department of Psychiatry, UMC Utrecht Brain Center, Utrecht, Utrecht, Netherlands
- Brain Research & Innovation Centre, Netherlands Ministry of Defense, Utrecht, Utrecht, Netherlands
| | - Sonia Jain
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | - Ehsan Pishva
- Department of Psychiatry and Neuropsychology, School for Mental health and Neuroscience, Maastricht University, Maastricht, Limburg, Netherlands
- College of Medicine and Health, University of Exeter Medical School, Exeter, UK
| | - Victoria B Risbrough
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Psychiatry Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Million Veteran Program, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Robert J Ursano
- Department of Psychiatry, Uniformed Services University, Bethesda, MD, USA
| | - Eric Vermetten
- Arq, Psychotrauma Research Expert Group, Diemen, North Holland, Netherlands
- Department of Psychiatry, Leiden University Medical Center, Leiden, South Holland, Netherlands
- Military Mental Healthcare, Netherlands Ministry of Defense, Utrecht, Utrecht, Netherlands
- Department of Psychiatry, New York University School of Medicine, New York, NY, USA
| | - Christiaan H Vinkers
- Department of Anatomy and Neurosciences, Amsterdam UMC (location VUmc), Amsterdam, Holland, Netherlands
- Department of Psychiatry, Amsterdam UMC (location VUmc), Amsterdam, Holland, Netherlands
| | - Alicia K Smith
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
- Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA
| | - Monica Uddin
- Genomics Program, University of South Florida College of Public Health, Tampa, FL, USA
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental health and Neuroscience, Maastricht University, Maastricht, Limburg, Netherlands
| | - Caroline M Nievergelt
- Department of Psychiatry and Neuropsychology, School for Mental health and Neuroscience, Maastricht University, Maastricht, Limburg, Netherlands.
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA.
- Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA.
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12
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Liu S, Rao S, Xu Y, Li J, Huang H, Zhang X, Fu H, Wang Q, Cao H, Baranova A, Jin C, Zhang F. Identifying common genome-wide risk genes for major psychiatric traits. Hum Genet 2019; 139:185-198. [DOI: 10.1007/s00439-019-02096-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 11/24/2019] [Indexed: 10/25/2022]
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13
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Schepers ST, Arndt DL, Rogers RD, Hedeker D, de Wit H. Subjective responses to amphetamine in young adults with previous mood elevation experiences. Psychopharmacology (Berl) 2019; 236:3363-3370. [PMID: 31209507 PMCID: PMC7053220 DOI: 10.1007/s00213-019-05295-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Accepted: 06/02/2019] [Indexed: 12/17/2022]
Abstract
RATIONALE One risk factor for alcohol and substance misuse is hypomanic experiences, or periods of mood elevation. Young people who report hypomanic states are more likely to develop bipolar disorder (BP), and BP and other mood disorders increase the risk of addiction. We recently reported that young adults with a history of mood elevation experience less subjective effects from a low dose of alcohol, which may be predictive of future alcohol use. The finding with alcohol raised the question of whether this dampened response to a drug also applies to other drugs, such as amphetamine. OBJECTIVE This study assessed responses of d-amphetamine in healthy young adults with varying experiences of mood elevation, as measured by the Mood Disorders Questionnaire (MDQ). METHODS Healthy 18-19-year-olds (N = 30) with a range of MDQ scores participated in three 4-h laboratory sessions in which they received placebo, 10 mg, or 20 mg d-amphetamine. They completed mood questionnaires and cardiovascular measures. RESULTS Individuals with higher MDQ scores reported less stimulation and euphoria after 10 mg, but not 20 mg, d-amphetamine, than individuals with lower scores. MDQ scores were not related to cardiovascular responses to the drug. CONCLUSIONS A history of mood elevation experiences or hypomania states is related to dampened response to a low dose of a psychostimulant drug, extending previous findings with dampened response to alcohol. This phenotype for mood disorders of dampened responses to drugs may contribute to risk for subsequent drug use or misuse.
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Affiliation(s)
- Scott T. Schepers
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, 5841 S Maryland Ave, MC3077, Chicago, IL 60637, USA
| | - David L. Arndt
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, 5841 S Maryland Ave, MC3077, Chicago, IL 60637, USA
| | | | - Donald Hedeker
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Harriet de Wit
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, 5841 S Maryland Ave, MC3077, Chicago, IL, 60637, USA.
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14
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Zhao L, Chang H, Zhou DS, Cai J, Fan W, Tang W, Tang W, Li X, Liu W, Liu F, He Y, Bai Y, Sun Y, Dai J, Li L, Xiao X, Zhang C, Li M. Replicated associations of FADS1, MAD1L1, and a rare variant at 10q26.13 with bipolar disorder in Chinese population. Transl Psychiatry 2018; 8:270. [PMID: 30531795 PMCID: PMC6286364 DOI: 10.1038/s41398-018-0337-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 10/07/2018] [Accepted: 11/13/2018] [Indexed: 12/12/2022] Open
Abstract
Genetic analyses of psychiatric illnesses, such as bipolar disorder (BPD), have revealed essential information regarding the underlying pathological mechanisms. While such studies in populations of European ancestry have achieved prominent success, understanding the genetic risk factors of these illnesses (especially BPD) in Chinese population remains an urgent task. Given the lack of genome-wide association study (GWAS) of BPD in Chinese population from Mainland China, replicating the previously reported GWAS hits in distinct populations will provide valuable information for future GWAS analysis in Han Chinese. In the present study, we have recruited 1146 BPD cases and 1956 controls from Mainland China for genetic analyses, as well as 65 Han Chinese brain amygdala tissues for mRNA expression analyses. Using this clinical sample, one of the largest Han Chinese BPD samples till now, we have conducted replication analyses of 21 single nucleotide polymorphisms (SNPs) extracted from previous GWAS of distinct populations. Among the 21 tested SNPs, 16 showed the same direction of allelic effects in our samples compared with previous studies; 6 SNPs achieved nominal significance (p < 0.05) at one-tailed test, and 2 additional SNPs showed marginal significance (p < 0.10). Aside from replicating previously reported BPD risk SNPs, we herein also report several intriguing findings: (1) the SNP rs174576 was associated with BPD in our Chinese sample and in the overall global meta-analysis, and was significantly correlated with FADS1 mRNA in diverse public RNA-seq datasets as well as our in house collected Chinese amygdala samples; (2) two (partially) independent SNPs in MAD1L1 were both significantly associated with BPD in our Chinese sample, which was also supported by haplotype analysis; (3) a rare SNP rs78089757 in 10q26.13 region was a genome-wide significant variant for BPD in East Asians, and this SNP was near monomorphic in Europeans. In sum, these results confirmed several significant BPD risk genes. We hope this Chinese BPD case-control sample and the current brain amygdala tissues (with continuous increasing sample size in the near future) will provide helpful resources in elucidating the genetic and molecular basis of BPD in this major world population.
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Affiliation(s)
- Lijuan Zhao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Hong Chang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China
| | - Dong-Sheng Zhou
- Department of Psychiatry, Ningbo Kangning Hospital, Ningbo, Zhejiang, China
| | - Jun Cai
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weixing Fan
- Jinhua Second Hospital, Jinhua, Zhejiang, China
| | - Wei Tang
- Wenzhou Kangning Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Wenxin Tang
- Hangzhou Seventh People's Hospital, Hangzhou, Zhejiang, China
| | - Xingxing Li
- Department of Psychiatry, Ningbo Kangning Hospital, Ningbo, Zhejiang, China
| | - Weiqing Liu
- Department of Psychiatry, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Fang Liu
- Department of Psychiatry, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Yuanfang He
- Department of Psychiatry, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Yan Bai
- Department of Psychiatry, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Yan Sun
- Wuhan Institute for Neuroscience and Neuroengineering, South-Central University for Nationalities, Wuhan, Hubei, China
- Chinese Brain Bank Center, Wuhan, Hubei, China
| | - Jiapei Dai
- Wuhan Institute for Neuroscience and Neuroengineering, South-Central University for Nationalities, Wuhan, Hubei, China
- Chinese Brain Bank Center, Wuhan, Hubei, China
| | - Lingyi Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China.
| | - Chen Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
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