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Momin MM, Zhou X, Hyppönen E, Benyamin B, Lee SH. Cross-ancestry genetic architecture and prediction for cholesterol traits. Hum Genet 2024; 143:635-648. [PMID: 38536467 DOI: 10.1007/s00439-024-02660-7] [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: 06/30/2023] [Accepted: 02/13/2024] [Indexed: 05/18/2024]
Abstract
While cholesterol is essential, a high level of cholesterol is associated with the risk of cardiovascular diseases. Genome-wide association studies (GWASs) have proven successful in identifying genetic variants that are linked to cholesterol levels, predominantly in white European populations. However, the extent to which genetic effects on cholesterol vary across different ancestries remains largely unexplored. Here, we estimate cross-ancestry genetic correlation to address questions on how genetic effects are shared across ancestries. We find significant genetic heterogeneity between ancestries for cholesterol traits. Furthermore, we demonstrate that single nucleotide polymorphisms (SNPs) with concordant effects across ancestries for cholesterol are more frequently found in regulatory regions compared to other genomic regions. Indeed, the positive genetic covariance between ancestries is mostly driven by the effects of the concordant SNPs, whereas the genetic heterogeneity is attributed to the discordant SNPs. We also show that the predictive ability of the concordant SNPs is significantly higher than the discordant SNPs in the cross-ancestry polygenic prediction. The list of concordant SNPs for cholesterol is available in GWAS Catalog. These findings have relevance for the understanding of shared genetic architecture across ancestries, contributing to the development of clinical strategies for polygenic prediction of cholesterol in cross-ancestral settings.
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Affiliation(s)
- Md Moksedul Momin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia.
- Department of Genetics and Animal Breeding, Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University (CVASU), Khulshi, Chattogram, 4225, Bangladesh.
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia.
| | - Xuan Zhou
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
| | - Elina Hyppönen
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Beben Benyamin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
| | - S Hong Lee
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia.
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia.
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2
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Momin MM, Shin J, Lee S, Truong B, Benyamin B, Lee SH. A method for an unbiased estimate of cross-ancestry genetic correlation using individual-level data. Nat Commun 2023; 14:722. [PMID: 36759513 PMCID: PMC9911789 DOI: 10.1038/s41467-023-36281-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 01/24/2023] [Indexed: 02/11/2023] Open
Abstract
Cross-ancestry genetic correlation is an important parameter to understand the genetic relationship between two ancestry groups. However, existing methods cannot properly account for ancestry-specific genetic architecture, which is diverse across ancestries, producing biased estimates of cross-ancestry genetic correlation. Here, we present a method to construct a genomic relationship matrix (GRM) that can correctly account for the relationship between ancestry-specific allele frequencies and ancestry-specific allelic effects. Through comprehensive simulations, we show that the proposed method outperforms existing methods in the estimations of SNP-based heritability and cross-ancestry genetic correlation. The proposed method is further applied to anthropometric and other complex traits from the UK Biobank data across ancestry groups. For obesity, the estimated genetic correlation between African and European ancestry cohorts is significantly different from unity, suggesting that obesity is genetically heterogenous between these two ancestries.
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Affiliation(s)
- Md Moksedul Momin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia
- Department of Genetics and Animal Breeding, Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University (CVASU), Khulshi, Chattogram, 4225, Bangladesh
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
| | - Jisu Shin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Soohyun Lee
- Division of Animal Breeding and Genetics, National Institute of Animal Science (NIAS), Cheonan, South Korea
| | - Buu Truong
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
| | - Beben Benyamin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
| | - S Hong Lee
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia.
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia.
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3
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Garvert L, Kirchner K, Grabe HJ, Van der Auwera S. Genome-wide gene-gene interaction of the 5-HTTLPR promoter polymorphism emphasizes the important role of neuroplasticity in depression. Prog Neuropsychopharmacol Biol Psychiatry 2022; 119:110614. [PMID: 35977647 DOI: 10.1016/j.pnpbp.2022.110614] [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: 03/08/2022] [Revised: 07/27/2022] [Accepted: 08/10/2022] [Indexed: 10/15/2022]
Abstract
Recent genome-wide association studies (GWAS) have identified numerous single nucleotide polymorphisms affecting depressive disorders. GWAS results support the heterogeneity of depression as a disorder affected by a large number of genetic variants with mainly small effect sizes. However, not much is known about the interplay of different genetic risk factors. Moreover, recent studies are questioning the role of common candidate genes in the development of depressive disorders. One such candidate variant is the serotonin-transporter-promoter-polymorphism 5-HTTLPR in the SLC6A4 gene. We hypothesize that 5-HTTLPR exerts its effect on depressive disorders in interaction with other genetic variants. In the present study we test this hypothesis using a genome-wide gene-gene interaction approach on a large sample from the UK Biobank (N = 127,558). We identified a region in the DPF1 gene that displayed a genome-wide significant (p = 3.31 × 10-7) interaction effect with the biallelic version of 5-HTTLPR on lifetime depression. DPF1 has not previously been described as risk factor for depressive disorders but is exclusively expressed in the brain as a major regulator of neuronal development and neuroplasticity. This study stresses the need for further analyses that take into consideration the fact that genetic variants do operate in biological networks.
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Affiliation(s)
- Linda Garvert
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
| | - Kevin Kirchner
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; German Centre for Neurodegenerative Diseases (DZNE), Partner Site Rostock/Greifswald, Greifswald, Germany
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; German Centre for Neurodegenerative Diseases (DZNE), Partner Site Rostock/Greifswald, Greifswald, Germany
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4
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Carvalho MRS, Barbosa de Carvalho AH, Paiva GM, Andrade Jorge CDC, Dos Santos FC, Koltermann G, de Salles JF, Moeller K, Maia de Oliveira Wood G, Haase VG. MAOA-LPR polymorphism and math anxiety: A marker of genetic susceptibility to social influences in girls? Ann N Y Acad Sci 2022; 1516:135-150. [PMID: 35765118 DOI: 10.1111/nyas.14814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Math anxiety (MA) seems to result from an interaction of genetic vulnerability with negative experiences learning mathematics. Although mathematics achievement does not substantially differ between the sexes, MA levels are usually higher in girls. Molecular genetic markers of MA vulnerability have been seldom explored. This article examines the contribution of the monoamine oxidase A gene (MAOA) to MA and to sex differences in MA. Five hundred and sixty-eight third to fifth graders were genotyped for the MAOA-LPR polymorphism (a repetitive element in MAOA promoter that has been associated with MAOA enzymatic activity), and assessed on general cognitive ability, mathematics achievement, and the cognitive and affective dimensions of MA. MAOA-LPR genotypes were classified as high (MAOA-H) or low (MAOA-L) according to their predicted enzymatic activity. Mixed models controlling for effects of school, sex, general cognitive ability, and mathematics achievement were evaluated. The best fitting model included school, math achievement, sex, MAOA-LPR, and the MAOA-LPR by sex interaction. This indicated that under the MAOA-H dominant model, anxiety toward mathematics interacted with the MAOA genotype: girls with an MAOA-L genotype exhibited higher levels of MA, with a small but significant effect. The association between MAOA-L genotype and MA in girls may represent an example of developmental plasticity.
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Affiliation(s)
- Maria Raquel Santos Carvalho
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Programa de Pós-graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - André Henrique Barbosa de Carvalho
- Programa de Pós-graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Giulia Moreira Paiva
- Programa de Pós graduação em Neurociências, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Carolina de Castro Andrade Jorge
- Programa de Pós-graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Fernanda Caroline Dos Santos
- Programa de Pós-graduação em Genética, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Gabriella Koltermann
- Programa de Pós-graduação em Psicologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Jerusa Fumagalli de Salles
- Programa de Pós-graduação em Psicologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,Departamento de Psicologia do Desenvolvimento e da Personalidade, Instituto de Psicologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Korbinian Moeller
- Centre for Mathematical Cognition, Loughborough University, Loughborough, UK.,Leibniz-Institut fuer Wissensmedien, Tuebingen, Germany.,LEAD Graduate School & Research Network, University of Tuebingen, Tuebingen, Germany.,Individual Differences and Adaptive Education Centre, Frankfurt am Main, Germany
| | | | - Vitor Geraldi Haase
- Programa de Pós graduação em Neurociências, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Departamento de Psicologia, Faculdade de Filosofia e Ciências Humanas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Programa de Pós-graduação em Psicologia: Cognição e Comportamento, Faculdade de Filosofia e Ciências Humanas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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5
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van de Weijer MP, Pelt DHM, de Vries LP, Baselmans BML, Bartels M. A Re-evaluation of Candidate Gene Studies for Well-Being in Light of Genome-Wide Evidence. JOURNAL OF HAPPINESS STUDIES 2022; 23:3031-3053. [PMID: 35949913 PMCID: PMC9356956 DOI: 10.1007/s10902-022-00538-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/18/2022] [Indexed: 05/29/2023]
Abstract
UNLABELLED Ever since twin-family studies found that a substantial amount (± 40%) of the variation in well-being can be explained by genetic variation, several candidate genes have been proposed explaining this variation. However, these candidate gene and candidate gene-by-environment interaction studies have been surrounded by controversy regarding the validity and replication of their results. In the present study, we review the existing candidate gene literature for well-being. First, we perform a systematic literature search that results in the inclusion of 41 studies. After describing the results of the included studies, we evaluated the included candidate polymorphisms by (1) looking up the results for the studied candidate SNPs in a large well-being genome-wide association study, (2) performing association analyses in UK biobank (UKB) data for the candidate variable number tandem repeats (VNTR) and the APOE ε4 allele, and (3) studying possible candidate interactions with positive and negative environmental moderators using UKB data. We find no support for any of the candidate genes or candidate gene-environment interactions for well-being, with the exception of two SNPs that were chosen based on genome-wide evidence. While the generalizability of our findings is limited by our phenotype and environment definitions, we strongly advise well-being researchers to abandon the candidate gene approach in the field of well-being and move toward genome-wide approaches. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s10902-022-00538-x.
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Affiliation(s)
- Margot P. van de Weijer
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Dirk H. M. Pelt
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Lianne P. de Vries
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Bart M. L. Baselmans
- Biomedical Technology, Faculty of Technology, Amsterdam University of Applied Sciences, Amsterdam, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, The Netherlands
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6
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Xiao X, Zhang CY, Zhang Z, Hu Z, Li M, Li T. Revisiting tandem repeats in psychiatric disorders from perspectives of genetics, physiology, and brain evolution. Mol Psychiatry 2022; 27:466-475. [PMID: 34650204 DOI: 10.1038/s41380-021-01329-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 09/16/2021] [Accepted: 09/28/2021] [Indexed: 01/28/2023]
Abstract
Genome-wide association studies (GWASs) have revealed substantial genetic components comprised of single nucleotide polymorphisms (SNPs) in the heritable risk of psychiatric disorders. However, genetic risk factors not covered by GWAS also play pivotal roles in these illnesses. Tandem repeats, which are likely functional but frequently overlooked by GWAS, may account for an important proportion in the "missing heritability" of psychiatric disorders. Despite difficulties in characterizing and quantifying tandem repeats in the genome, studies have been carried out in an attempt to describe impact of tandem repeats on gene regulation and human phenotypes. In this review, we have introduced recent research progress regarding the genomic distribution and regulatory mechanisms of tandem repeats. We have also summarized the current knowledge of the genetic architecture and biological underpinnings of psychiatric disorders brought by studies of tandem repeats. These findings suggest that tandem repeats, in candidate psychiatric risk genes or in different levels of linkage disequilibrium (LD) with psychiatric GWAS SNPs and haplotypes, may modulate biological phenotypes related to psychiatric disorders (e.g., cognitive function and brain physiology) through regulating alternative splicing, promoter activity, enhancer activity and so on. In addition, many tandem repeats undergo tight natural selection in the human lineage, and likely exert crucial roles in human brain evolution. Taken together, the putative roles of tandem repeats in the pathogenesis of psychiatric disorders is strongly implicated, and using examples from previous literatures, we wish to call for further attention to tandem repeats in the post-GWAS era of psychiatric disorders.
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Affiliation(s)
- 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, Yunnan, 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, Yunnan, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Zhuohua Zhang
- Institute of Molecular Precision Medicine and Hunan Key Laboratory of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China.,Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Zhonghua Hu
- Institute of Molecular Precision Medicine and Hunan Key Laboratory of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China. .,Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China. .,Department of Critical Care Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China. .,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China. .,Hunan Key Laboratory of Animal Models for Human Diseases, School of Life Sciences, Central South University, Changsha, Hunan, China. .,Eye Center of Xiangya Hospital and Hunan Key Laboratory of Ophthalmology, Central South University, Changsha, Hunan, China. .,National Clinical Research Center on Mental Disorders, Changsha, Hunan, 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, Yunnan, China. .,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China. .,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
| | - Tao Li
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China. .,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China.
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7
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Majumdar A, Patel P, Pasaniuc B, Ophoff RA. A summary-statistics-based approach to examine the role of serotonin transporter promoter tandem repeat polymorphism in psychiatric phenotypes. Eur J Hum Genet 2021; 30:547-554. [PMID: 34949768 PMCID: PMC9091198 DOI: 10.1038/s41431-021-00996-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 10/01/2021] [Accepted: 10/26/2021] [Indexed: 01/24/2023] Open
Abstract
In genetic studies of psychiatric disorders in the pre-genome-wide association study (GWAS) era, one of the most commonly studied loci is the serotonin transporter (SLC6A4) promoter polymorphism, a 43-base-pair insertion/deletion polymorphism in the promoter region (5-HTTLPR). The genetic association signals between 5-HTTLPR and psychiatric phenotypes, however, have been inconsistent across many studies. Since the polymorphism cannot be tested via available SNP arrays, we had previously proposed an efficient machine learning algorithm to predict the genotypes of 5-HTTLPR based on the genotypes of eight nearby SNPs, which requires access to individual-level genotype and phenotype data. To utilize the advantage of publicly available GWAS summary statistics obtained from studies with very large sample sizes, we develop a GWAS summary-statistics-based approach for testing the variable number of tandem repeat (VNTR) associations with various phenotypes. We first cross-verify the accuracy of the summary-statistics-based approach for 61 phenotypes in the UK Biobank. Since we observed a strong similarity between the predicted individual-level 5-HTTLPR genotype-based approach and the summary-statistics-based approach, we applied our method to the available neurobehavioral GWAS summary statistics data obtained from large-scale GWAS. We found no genome-wide significant evidence for association between 5-HTTLPR and any of the neurobehavioral traits. We did observe, however, genome-wide significant evidence for association between this locus and human adult height, BMI, and total cholesterol. Our summary-statistics-based approach provides a systematic way to examine the role of VNTRs and related types of genetic polymorphisms in disease risk and trait susceptibility of phenotypes for which large-scale GWAS summary statistics data are available.
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8
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Li ZC, Fang BX, Yuan LX, Zheng K, Wu SX, Zhong N, Zeng XL. Analysis of Studies in Tinnitus-Related Gene Research. Noise Health 2021; 23:95-107. [PMID: 34975125 PMCID: PMC8772442 DOI: 10.4103/nah.nah_57_21] [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] [Indexed: 11/04/2022] Open
Abstract
Objective Summarize and analyze the current research results of tinnitus-related genes, explore the potential links between the results of each study, and provide reference for subsequent studies. Methods Collect and sort out the research literature related to tinnitus genes included in PubMed, Web of Science, China National Knowledge Infrastructure, and Wanfang Data Knowledge Service Platform before December 31, 2019. Then the relevant contents of the literature were sorted out and summarized. Results Fifty-one articles were finally selected for analysis: 31 articles (60.8%) were classified as researches on animal models of tinnitus, and 20 (39.2%) as researches on tinnitus patients. Existing studies have shown that genes related to oxidative stress, inflammatory response, nerve excitation/inhibition, and nerve growth are differentially expressed in tinnitus patients or animal models, and have presented the potential links between genes or proteins in the occurrence and development of tinnitus. Conclusion The research on tinnitus-related genes is still in the exploratory stage, and further high-quality research evidence is needed.
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Affiliation(s)
- Zhi-Cheng Li
- Department of Otolaryngology, Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Bi-Xing Fang
- Department of Otolaryngology, Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou; Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Sun Yat-sen University, China
| | - Lian-Xiong Yuan
- Department of Science and Research, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Ke Zheng
- Department of Otolaryngology, Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shi-Xin Wu
- Department of Otolaryngology, Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Nanbert Zhong
- Department of Human Genetics, New York State Institute for Basic Research in Developmental Disabilities, New York, USA
| | - Xiang-Li Zeng
- Department of Otolaryngology, Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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9
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Kendall KM, Van Assche E, Andlauer TFM, Choi KW, Luykx JJ, Schulte EC, Lu Y. The genetic basis of major depression. Psychol Med 2021; 51:2217-2230. [PMID: 33682643 DOI: 10.1017/s0033291721000441] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Major depressive disorder (MDD) is a common, debilitating, phenotypically heterogeneous disorder with heritability ranges from 30% to 50%. Compared to other psychiatric disorders, its high prevalence, moderate heritability, and strong polygenicity have posed major challenges for gene-mapping in MDD. Studies of common genetic variation in MDD, driven by large international collaborations such as the Psychiatric Genomics Consortium, have confirmed the highly polygenic nature of the disorder and implicated over 100 genetic risk loci to date. Rare copy number variants associated with MDD risk were also recently identified. The goal of this review is to present a broad picture of our current understanding of the epidemiology, genetic epidemiology, molecular genetics, and gene-environment interplay in MDD. Insights into the impact of genetic factors on the aetiology of this complex disorder hold great promise for improving clinical care.
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Affiliation(s)
- K M Kendall
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - E Van Assche
- Department of Psychiatry, University of Muenster, Muenster, Germany
| | - T F M Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - K W Choi
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA02114, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA02114, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA02115, USA
| | - J J Luykx
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Outpatient Second Opinion Clinic, GGNet Mental Health, Warnsveld, The Netherlands
| | - E C Schulte
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Y Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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10
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Abstract
The Colorado Twin Registry (CTR) is a population-based registry formed from birth and school records including twins born between 1968 and the present. Two previous reports on the CTR [Rhea et al., (2006). Twin Research and Human Genetics, 9, 941-949; Rhea et al., (2013).Twin Research and Human Genetics, 16, 351-357] covered developments in the CTR through 2012. This report briefly summarizes previously presented material on ascertainment and recruitment and the relationships between samples and studies, discusses developments since 2012 for four previously described twin samples, describes two new samples and their complementary studies and expands on two subjects briefly mentioned in the last report: a history of genotyping efforts involving CTR samples, and a survey of collaborations and consortia in which CTR twins have been included. The CTR remains an active resource for both ongoing, longitudinal research and the recruitment of new twin samples for newly identified research opportunities.
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11
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Ni G, Amare AT, Zhou X, Mills N, Gratten J, Lee SH. The genetic relationship between female reproductive traits and six psychiatric disorders. Sci Rep 2019; 9:12041. [PMID: 31427629 PMCID: PMC6700195 DOI: 10.1038/s41598-019-48403-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Accepted: 07/31/2019] [Indexed: 12/31/2022] Open
Abstract
Female reproductive behaviours have important implications for evolutionary fitness and health of offspring. Here we used the second release of UK Biobank data (N = 220,685) to evaluate the association between five female reproductive traits and polygenic risk scores (PRS) projected from genome-wide association study summary statistics of six psychiatric disorders (N = 429,178). We found that the PRS of attention-deficit/hyperactivity disorder (ADHD) were strongly associated with age at first birth (AFB) (genetic correlation of -0.68 ± 0.03), age at first sexual intercourse (AFS) (-0.56 ± 0.03), number of live births (NLB) (0.36 ± 0.04) and age at menopause (-0.27 ± 0.04). There were also robustly significant associations between the PRS of eating disorder (ED) and AFB (0.35 ± 0.06), ED and AFS (0.19 ± 0.06), major depressive disorder (MDD) and AFB (-0.27 ± 0.07), MDD and AFS (-0.27 ± 0.03) and schizophrenia and AFS (-0.10 ± 0.03). These associations were mostly explained by pleiotropic effects and there was little evidence of causal relationships. Our findings can potentially help improve reproductive health in women, hence better child outcomes. Our findings also lend partial support to the evolutionary hypothesis that causal mutations underlying psychiatric disorders have positive effects on reproductive success.
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Affiliation(s)
- Guiyan Ni
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, 5000, Australia
- School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia
| | - Azmeraw T Amare
- South Australian Academic Health Science and Translation centre, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia, Australia
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
| | - Xuan Zhou
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, 5000, Australia
| | - Natalie Mills
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
| | - Jacob Gratten
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
- Mater Research Institute, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - S Hong Lee
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, 5000, Australia.
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Border R, Johnson EC, Evans LM, Smolen A, Berley N, Sullivan PF, Keller MC. No Support for Historical Candidate Gene or Candidate Gene-by-Interaction Hypotheses for Major Depression Across Multiple Large Samples. Am J Psychiatry 2019; 176:376-387. [PMID: 30845820 PMCID: PMC6548317 DOI: 10.1176/appi.ajp.2018.18070881] [Citation(s) in RCA: 329] [Impact Index Per Article: 65.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Interest in candidate gene and candidate gene-by-environment interaction hypotheses regarding major depressive disorder remains strong despite controversy surrounding the validity of previous findings. In response to this controversy, the present investigation empirically identified 18 candidate genes for depression that have been studied 10 or more times and examined evidence for their relevance to depression phenotypes. METHODS Utilizing data from large population-based and case-control samples (Ns ranging from 62,138 to 443,264 across subsamples), the authors conducted a series of preregistered analyses examining candidate gene polymorphism main effects, polymorphism-by-environment interactions, and gene-level effects across a number of operational definitions of depression (e.g., lifetime diagnosis, current severity, episode recurrence) and environmental moderators (e.g., sexual or physical abuse during childhood, socioeconomic adversity). RESULTS No clear evidence was found for any candidate gene polymorphism associations with depression phenotypes or any polymorphism-by-environment moderator effects. As a set, depression candidate genes were no more associated with depression phenotypes than noncandidate genes. The authors demonstrate that phenotypic measurement error is unlikely to account for these null findings. CONCLUSIONS The study results do not support previous depression candidate gene findings, in which large genetic effects are frequently reported in samples orders of magnitude smaller than those examined here. Instead, the results suggest that early hypotheses about depression candidate genes were incorrect and that the large number of associations reported in the depression candidate gene literature are likely to be false positives.
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Affiliation(s)
- Richard Border
- Institute for Behavioral Genetics, University of Colorado Boulder, Stockholm, Sweden,Department of Psychology and Neuroscience, University of Colorado Boulder, Stockholm, Sweden,Department of Applied Mathematics, University of Colorado Boulder, Stockholm, Sweden
| | - Emma C. Johnson
- Institute for Behavioral Genetics, University of Colorado Boulder, Stockholm, Sweden,Department of Psychiatry, Washington University School of Medicine, Stockholm, Sweden
| | - Luke M. Evans
- Institute for Behavioral Genetics, University of Colorado Boulder, Stockholm, Sweden,Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Stockholm, Sweden
| | - Andrew Smolen
- Institute for Behavioral Genetics, University of Colorado Boulder, Stockholm, Sweden
| | - Noah Berley
- Department of Psychology and Neuroscience, University of Colorado Boulder, Stockholm, Sweden
| | - Patrick F. Sullivan
- Department of Genetics and Psychiatry, University of North Carolina at Chapel Hill, Stockholm, Sweden,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Matthew C. Keller
- Institute for Behavioral Genetics, University of Colorado Boulder, Stockholm, Sweden,Department of Psychology and Neuroscience, University of Colorado Boulder, Stockholm, Sweden
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