Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.101
Allan Kalungi , Segun Fatumo
Psychiatric genomics research tools frequently depend on terminology and notions that are predominantly derived from Western viewpoints, specifically designed for populations speaking English in Europe and the United States of America. Nevertheless, there is an increasing interest in incorporating African populations into genetic studies, as African genetic data possess significant potential for enhancing discovery in psychiatric genetics research. However, this undertaking has unique difficulties, including inefficiently conveying intricate genetic and psychiatric ideas and terminology to participants using their native African languages. The absence of obvious counterparts for terms such as "trauma" or "genome" necessitates the need for unique strategies to overcome linguistic barriers.
In 2011, we established the Uganda Genome Resource (UGR) – a well-characterized genomic database with a range of phenotypes for communicable and non-communicable diseases and risk factors generated from the Uganda General Population Cohort (GPC), a population-based open cohort. The UGR comprises genotype data on ∼5,000 and whole-genome sequence data on ∼2,000 Ugandan GPC individuals from 10 ethno-linguistic groups. We have since extended UGR to include studies focusing primarily on mental health conditions including major depressive disorder, post-traumatic stress disorder, generalized anxiety disorder, alcohol misuse and suicidality, among others.
To mitigate against the barrier poised by research tools which were developed in a foreign language to the participants, first, we engage the service of a professional linguistic translator to ensure accurate translation of all study materials. Additionally, we provide cultural sensitivity training to researchers to ensure respectful and ethical interactions with participants from diverse ethno-linguistic backgrounds. Secondly, following the translated study material, we set up a series of workshop including mental health experts and leading psychiatric geneticists and local scientists to agree on the translated content. Thirdly, we ask an independent local scientist to conduct a reverse translation of the study materials to ensure accuracy and consistency in the translated versions. This thorough process helps to minimize any potential misunderstandings or misinterpretations that may arise during the research study.
{"title":"BRIDGING LINGUISTIC AND CULTURAL DIVIDES IN PSYCHIATRIC GENOMICS RESEARCH: LESSONS FROM UGANDA","authors":"Allan Kalungi , Segun Fatumo","doi":"10.1016/j.euroneuro.2024.08.101","DOIUrl":"10.1016/j.euroneuro.2024.08.101","url":null,"abstract":"<div><div>Psychiatric genomics research tools frequently depend on terminology and notions that are predominantly derived from Western viewpoints, specifically designed for populations speaking English in Europe and the United States of America. Nevertheless, there is an increasing interest in incorporating African populations into genetic studies, as African genetic data possess significant potential for enhancing discovery in psychiatric genetics research. However, this undertaking has unique difficulties, including inefficiently conveying intricate genetic and psychiatric ideas and terminology to participants using their native African languages. The absence of obvious counterparts for terms such as \"trauma\" or \"genome\" necessitates the need for unique strategies to overcome linguistic barriers.</div><div>In 2011, we established the Uganda Genome Resource (UGR) – a well-characterized genomic database with a range of phenotypes for communicable and non-communicable diseases and risk factors generated from the Uganda General Population Cohort (GPC), a population-based open cohort. The UGR comprises genotype data on ∼5,000 and whole-genome sequence data on ∼2,000 Ugandan GPC individuals from 10 ethno-linguistic groups. We have since extended UGR to include studies focusing primarily on mental health conditions including major depressive disorder, post-traumatic stress disorder, generalized anxiety disorder, alcohol misuse and suicidality, among others.</div><div>To mitigate against the barrier poised by research tools which were developed in a foreign language to the participants, first, we engage the service of a professional linguistic translator to ensure accurate translation of all study materials. Additionally, we provide cultural sensitivity training to researchers to ensure respectful and ethical interactions with participants from diverse ethno-linguistic backgrounds. Secondly, following the translated study material, we set up a series of workshop including mental health experts and leading psychiatric geneticists and local scientists to agree on the translated content. Thirdly, we ask an independent local scientist to conduct a reverse translation of the study materials to ensure accuracy and consistency in the translated versions. This thorough process helps to minimize any potential misunderstandings or misinterpretations that may arise during the research study.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 41"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.038
Tao Li (Chair) , Fang Liu (Co-chair) , Zafiris Daskalakis (Discussant)
This symposium will feature cutting-edge research that leverages diverse genomic approaches to elucidate the complex etiology of schizophrenia. The presentations will span large-scale genetic association studies, novel sequencing technologies, and investigations of the gut microbiome - all with the goal of advancing our fundamental understanding of this debilitating psychiatric disorder.
The symposium will begin with a report on the largest genome-wide association study (GWAS) of schizophrenia conducted in an Eastern Asian population to date. The speaker will present findings on newly identified risk loci that provide insights into the unique genetic architecture of schizophrenia in this understudied ancestral group. Next, researchers will share results from a study utilizing long-read sequencing technology to comprehensively catalog de novo mutations in schizophrenia parent-offspring trios. This high-resolution approach has uncovered rare, disruptive variants missed by short-read sequencing that may confer substantial risk for the disorder. The symposium will also feature an investigation of the gut microbiome and its potential role in schizophrenia pathogenesis. The speaker will discuss metagenomic analyses revealing distinct microbiota signatures associated with the disease state, suggesting gut-brain axis mechanisms worthy of further exploration. Finally, the symposium will conclude with functional experiments probing the biological impact of D2R-DISC1 complex on antipsychotic treatment. The speaker will share findings from a comprehensive investigation using both patient-derived samples and mouse models of schizophrenia. Through a combination of proteomic analyses, pharmacological manipulations, and advanced molecular techniques, the researchers have uncovered novel insights into how the D2R-DISC1 signaling axis contribute to treatment response in schizophrenia.
Collectively, this symposium will showcase innovative genomic and experimental approaches that are revolutionizing our understanding of schizophrenia's complex etiology. The findings presented will inspire new hypotheses and accelerate the translation of genetic discoveries into improved diagnostic tools and targeted therapeutic strategies.
{"title":"UNCOVERING THE GENETIC AND BIOLOGICAL UNDERPINNINGS OF SCHIZOPHRENIA","authors":"Tao Li (Chair) , Fang Liu (Co-chair) , Zafiris Daskalakis (Discussant)","doi":"10.1016/j.euroneuro.2024.08.038","DOIUrl":"10.1016/j.euroneuro.2024.08.038","url":null,"abstract":"<div><div>This symposium will feature cutting-edge research that leverages diverse genomic approaches to elucidate the complex etiology of schizophrenia. The presentations will span large-scale genetic association studies, novel sequencing technologies, and investigations of the gut microbiome - all with the goal of advancing our fundamental understanding of this debilitating psychiatric disorder.</div><div>The symposium will begin with a report on the largest genome-wide association study (GWAS) of schizophrenia conducted in an Eastern Asian population to date. The speaker will present findings on newly identified risk loci that provide insights into the unique genetic architecture of schizophrenia in this understudied ancestral group. Next, researchers will share results from a study utilizing long-read sequencing technology to comprehensively catalog de novo mutations in schizophrenia parent-offspring trios. This high-resolution approach has uncovered rare, disruptive variants missed by short-read sequencing that may confer substantial risk for the disorder. The symposium will also feature an investigation of the gut microbiome and its potential role in schizophrenia pathogenesis. The speaker will discuss metagenomic analyses revealing distinct microbiota signatures associated with the disease state, suggesting gut-brain axis mechanisms worthy of further exploration. Finally, the symposium will conclude with functional experiments probing the biological impact of D2R-DISC1 complex on antipsychotic treatment. The speaker will share findings from a comprehensive investigation using both patient-derived samples and mouse models of schizophrenia. Through a combination of proteomic analyses, pharmacological manipulations, and advanced molecular techniques, the researchers have uncovered novel insights into how the D2R-DISC1 signaling axis contribute to treatment response in schizophrenia.</div><div>Collectively, this symposium will showcase innovative genomic and experimental approaches that are revolutionizing our understanding of schizophrenia's complex etiology. The findings presented will inspire new hypotheses and accelerate the translation of genetic discoveries into improved diagnostic tools and targeted therapeutic strategies.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 13"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.018
Philip Mitchell (Chair) , John Nurnberger (Co-chair) , Fernando Goes (Discussant)
Bipolar disorder (BD) is a highly familial condition, with a heritability of at least 70%, and with10-15% of first-degree relatives developing this illness. Unlike schizophrenia, there is no distinct prodromal (ultra high-risk) syndrome, making development of early intervention treatment programs difficult. Studies of high-risk young people with a family history of BD provide the potential for identifying clinical and/or biological changes that either predate or occur early in the development of BD, thereby presenting targets for early intervention therapies. This symposium will focus on what has been learnt from over a decade of BD high-risk studies globally, and what remains unknown or uncertain. Speakers will address these issues from both their own cohorts and the field more broadly. This symposium will comprise presentations by:
i)
John Nurnberger - Emeritus Professor, University of Indiana, USA. He led the NIMH Genetics Initiative Bipolar Group. His group has been active in the Bipolar Genome Study Consortium and in the Psychiatric Genomics Consortium. He established the US BD high-risk consortium, with sites at the universities of Indianapolis and Michigan, as well as Johns Hopkins University;
ii)
Janice Fullerton - Principal Research Scientist at Neuroscience Research Australia and Conjoint Associate Professor, University of New South Wales in Sydney, Australia. Jan will present genetics and neuroimaging data from the Australian Bipolar Kids and Sibs high-risk cohort;
iii)
Kathryn Freeman is a Research Assistant on the FORBOW Project, and PhD Student in Medical Neuroscience at Dalhousie University, Canada. Kate will present on bipolar disorder offspring findings from the FORBOW study; and
iv)
Philip Mitchell - Professor of Psychiatry at the University of New South Wales in Sydney who established the Australian Bipolar Kids and Sibs high-risk cohort. He will present findings from the 10-year follow-up of this sample.
{"title":"OVER A DECADE OF STUDIES IN BIPOLAR DISORDER HIGH RISK POPULATIONS: WHAT HAVE WE LEARNT AND WHAT ARE THE GAPS?","authors":"Philip Mitchell (Chair) , John Nurnberger (Co-chair) , Fernando Goes (Discussant)","doi":"10.1016/j.euroneuro.2024.08.018","DOIUrl":"10.1016/j.euroneuro.2024.08.018","url":null,"abstract":"<div><div>Bipolar disorder (BD) is a highly familial condition, with a heritability of at least 70%, and with10-15% of first-degree relatives developing this illness. Unlike schizophrenia, there is no distinct prodromal (ultra high-risk) syndrome, making development of early intervention treatment programs difficult. Studies of high-risk young people with a family history of BD provide the potential for identifying clinical and/or biological changes that either predate or occur early in the development of BD, thereby presenting targets for early intervention therapies. This symposium will focus on what has been learnt from over a decade of BD high-risk studies globally, and what remains unknown or uncertain. Speakers will address these issues from both their own cohorts and the field more broadly. This symposium will comprise presentations by:<ul><li><span>i)</span><span><div>John Nurnberger - Emeritus Professor, University of Indiana, USA. He led the NIMH Genetics Initiative Bipolar Group. His group has been active in the Bipolar Genome Study Consortium and in the Psychiatric Genomics Consortium. He established the US BD high-risk consortium, with sites at the universities of Indianapolis and Michigan, as well as Johns Hopkins University;</div></span></li><li><span>ii)</span><span><div>Janice Fullerton - Principal Research Scientist at Neuroscience Research Australia and Conjoint Associate Professor, University of New South Wales in Sydney, Australia. Jan will present genetics and neuroimaging data from the Australian Bipolar Kids and Sibs high-risk cohort;</div></span></li><li><span>iii)</span><span><div>Kathryn Freeman is a Research Assistant on the FORBOW Project, and PhD Student in Medical Neuroscience at Dalhousie University, Canada. Kate will present on bipolar disorder offspring findings from the FORBOW study; and</div></span></li><li><span>iv)</span><span><div>Philip Mitchell - Professor of Psychiatry at the University of New South Wales in Sydney who established the Australian Bipolar Kids and Sibs high-risk cohort. He will present findings from the 10-year follow-up of this sample.</div></span></li></ul></div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 5"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.056
Peter Kochunov , Tom Nichols , John Blangero , Sarah Medland , David Glahn , Elliot Hong
Worldwide efforts have led to large and inclusive imaging genetics datasets enabling examination of the contribution of genetic and environmental factors to development, clinical course and treatment effectiveness in psychiatric disorders. These datasets combine high-resolution neuroimaging and genetic data in large and inclusive samples. Classical genetic analyses can help to parse the variance in disorder-related brain patterns into additive genetic, specific SNP, household and environmental causes. Performing these inquiries at full imaging and genetic resolution is a formidable computational task where the computational complexity of classical genetic analyses rises as a square or cube of the sample size. We describe fast, non-iterative simplifications to accelerate classical variance component (VC) methods including heritability, genetic correlation, and genome-wide association in dense and complex empirical pedigrees derived in samples such as UKBB, HCP and ABCD. These approaches linearize computational effort while maintaining approximation fidelity (r∼0.95) with VC results and take advantage of parallel computing provided by central and graphics processing units (CPU and GPU). We show that the new approaches can help to tract the nature vs. nurture interaction in the development of major depressive disorder and psychosis in the longitudinal datasets such as ABCD. We also show how specific genetic risk factors for Alzheimer disease can interact with environment leading to development of brain patterns that are predictive of the risk of development of dementia.
{"title":"RESOLVING THE CHALLENGES OF BIG-DATA IMAGING GENETICS ANALYSIS TO UNDERSTAND GENETIC AND ENVIRONMENTAL RISK FACTORS IN PSYCHIATRIC DISORDERS","authors":"Peter Kochunov , Tom Nichols , John Blangero , Sarah Medland , David Glahn , Elliot Hong","doi":"10.1016/j.euroneuro.2024.08.056","DOIUrl":"10.1016/j.euroneuro.2024.08.056","url":null,"abstract":"<div><div>Worldwide efforts have led to large and inclusive imaging genetics datasets enabling examination of the contribution of genetic and environmental factors to development, clinical course and treatment effectiveness in psychiatric disorders. These datasets combine high-resolution neuroimaging and genetic data in large and inclusive samples. Classical genetic analyses can help to parse the variance in disorder-related brain patterns into additive genetic, specific SNP, household and environmental causes. Performing these inquiries at full imaging and genetic resolution is a formidable computational task where the computational complexity of classical genetic analyses rises as a square or cube of the sample size. We describe fast, non-iterative simplifications to accelerate classical variance component (VC) methods including heritability, genetic correlation, and genome-wide association in dense and complex empirical pedigrees derived in samples such as UKBB, HCP and ABCD. These approaches linearize computational effort while maintaining approximation fidelity (r∼0.95) with VC results and take advantage of parallel computing provided by central and graphics processing units (CPU and GPU). We show that the new approaches can help to tract the nature vs. nurture interaction in the development of major depressive disorder and psychosis in the longitudinal datasets such as ABCD. We also show how specific genetic risk factors for Alzheimer disease can interact with environment leading to development of brain patterns that are predictive of the risk of development of dementia.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Pages 21-22"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.025
Shansha Peng , Chunyu Liu
Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal technology for dissecting cellular heterogeneity and function. In an effort to assess the consistency and rigor of quality control (QC) measures across scRNA-seq studies, we systematically reviewed publications from high-impact journals, including Cell, Nature, Science, and their major sister journals. Our analysis revealed a lack of standardization in QC procedures, with significant variability in the parameters employed. Despite general agreement on the necessity of certain QC steps, such as the removal of low-quality cells and the detection of doublets, the specific criteria for these steps were often arbitrarily defined and not universally applied. Notably, the assessment of ambient RNA contamination and the precision of gene expression measurements were frequently overlooked, potentially leading to the inclusion of spurious data in downstream analyses. To address these inconsistencies, we propose a revised set of QC procedures and parameters, which yielded distinct results compared to the original publications when applied to existing datasets. Moreover, we also assessed the performance of the existing data-driven QC tools in distinguishing the low-quality cells from the high-quality cells. Our findings underscore the urgent need for a standardized approach to QC in scRNA-seq to ensure the reliability and reproducibility of biological insights derived from this powerful technology.
{"title":"STANDARDIZE QC PROCEDURE FOR SCRNA-SEQ","authors":"Shansha Peng , Chunyu Liu","doi":"10.1016/j.euroneuro.2024.08.025","DOIUrl":"10.1016/j.euroneuro.2024.08.025","url":null,"abstract":"<div><div>Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal technology for dissecting cellular heterogeneity and function. In an effort to assess the consistency and rigor of quality control (QC) measures across scRNA-seq studies, we systematically reviewed publications from high-impact journals, including Cell, Nature, Science, and their major sister journals. Our analysis revealed a lack of standardization in QC procedures, with significant variability in the parameters employed. Despite general agreement on the necessity of certain QC steps, such as the removal of low-quality cells and the detection of doublets, the specific criteria for these steps were often arbitrarily defined and not universally applied. Notably, the assessment of ambient RNA contamination and the precision of gene expression measurements were frequently overlooked, potentially leading to the inclusion of spurious data in downstream analyses. To address these inconsistencies, we propose a revised set of QC procedures and parameters, which yielded distinct results compared to the original publications when applied to existing datasets. Moreover, we also assessed the performance of the existing data-driven QC tools in distinguishing the low-quality cells from the high-quality cells. Our findings underscore the urgent need for a standardized approach to QC in scRNA-seq to ensure the reliability and reproducibility of biological insights derived from this powerful technology.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 9"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.054
Rujia Dai , Ming Zhang , Tianyao Chu , Richard Kopp , Chunling Zhang , Kefu Liu , Yue Wang , Xusheng Wang , Chao Chen , Chunyu Liu
Single-cell/nuclei RNA sequencing (sc/snRNA-seq) is widely used for profiling cell-type gene expression in brain research. An important but frequently underappreciated issue is the data quality in terms of precision and accuracy. We evaluated precision using data from 14 human brain studies with a total of 3,483,905 cells from 297 individuals, with technical replicates based on random grouping of cells of the same type from the same individual. We also evaluated accuracy with sample-matched scRNA-seq and pooled-cell RNA-seq data of cultured mononuclear phagocytes from four species. Low precision and accuracy at the single-cell level across all evaluated data were observed. Cell number was highlighted as a key factor determining the expression precision, accuracy, and reproducibility of differential expression analysis in sc/snRNA-seq. A high missing rate is likely the cause of the quantification quality problem. Downstream analysis results are severely affected by the expression quality issue. Many false findings can be produced when the noises are not properly controlled. This study underscores the necessity of sequencing enough cells per cell type per individual, preferably in the hundreds, to mitigate noise in expression quantification. Pseudo-bulk aggregation of expression data over cells of the same type is required when the high-quality expression quantification is desired.
{"title":"PRECISION AND ACCURACY IN SINGLE-CELL RNA-SEQ","authors":"Rujia Dai , Ming Zhang , Tianyao Chu , Richard Kopp , Chunling Zhang , Kefu Liu , Yue Wang , Xusheng Wang , Chao Chen , Chunyu Liu","doi":"10.1016/j.euroneuro.2024.08.054","DOIUrl":"10.1016/j.euroneuro.2024.08.054","url":null,"abstract":"<div><div>Single-cell/nuclei RNA sequencing (sc/snRNA-seq) is widely used for profiling cell-type gene expression in brain research. An important but frequently underappreciated issue is the data quality in terms of precision and accuracy. We evaluated precision using data from 14 human brain studies with a total of 3,483,905 cells from 297 individuals, with technical replicates based on random grouping of cells of the same type from the same individual. We also evaluated accuracy with sample-matched scRNA-seq and pooled-cell RNA-seq data of cultured mononuclear phagocytes from four species. Low precision and accuracy at the single-cell level across all evaluated data were observed. Cell number was highlighted as a key factor determining the expression precision, accuracy, and reproducibility of differential expression analysis in sc/snRNA-seq. A high missing rate is likely the cause of the quantification quality problem. Downstream analysis results are severely affected by the expression quality issue. Many false findings can be produced when the noises are not properly controlled. This study underscores the necessity of sequencing enough cells per cell type per individual, preferably in the hundreds, to mitigate noise in expression quantification. Pseudo-bulk aggregation of expression data over cells of the same type is required when the high-quality expression quantification is desired.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 21"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.055
{"title":"HARNESSING GENOMIC DATA FOR PRECISION MEDICINE IN ALZHEIMER'S DISEASE: CHALLENGES AND OPPORTUNITIES","authors":"","doi":"10.1016/j.euroneuro.2024.08.055","DOIUrl":"10.1016/j.euroneuro.2024.08.055","url":null,"abstract":"","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 21"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.040
Yamin Zhang , Tong Li , Shaozhong Yang , Zhi Xie , Tao Li
<div><h3>Backgrounds</h3><div>Genetic liability to schizophrenia involves various types of mutations from across the allele frequency spectrum and distributed across the genome. Findings from studies focusing on different types of mutations in schizophrenia converge partially on the same biological processes, while also providing complementary insights. This underscores the importance of studying the full spectrum of mutation. However, currently widely used genotyping technologies, microarrays and short read sequencing (SRS), have limited ability in detecting medium-sized structural variations (SVs) (e.g. 50-2000bp) compared to long-read sequencing (LRS), which is relatively new and has been rarely applied to genetic studies of schizophrenia so far, suggesting an opportunity to leverage this more comprehensive approach to uncover additional sources of genetic variation that may contribute to the disorder.</div></div><div><h3>Methods</h3><div>Utilizing both 20X LRS and 30X SRS, we performed comprehensive whole-genome analysis on 40 Han Chinese parent-offspring trios. We called single nucleotide variants (SNVs), insertions and deletions (indels), and SVs utilizing multiple algorithms. Our primary focus was on the detection and validation of de novo mutations (DNMs). Comparative analysis between LRS and SRS was conducted to assess their respective abilities in detecting SVs and de novo SVs. Subsequently, we annotated the de novo mutations and delved into their potential mechanisms in schizophrenia through mining public databases and conducting functional experiments. Finally, we compared the diagnostic yield of our approach to previous studies employing whole exome sequencing or whole genome sequencing using SRS.</div></div><div><h3>Results</h3><div>Our analysis identified an average of 71.55 DNMs per proband, including 12 de novo SVs. Notably, four of these de novo SVs were detected by more than three out of four algorithms employed for LRS, whereas none were detected by any of the four algorithms utilized for SRS. In addition, our analysis revealed a 2.8Mb region exclusively accessible via by LRS and not SRS. LRS demonstrated exceptional performance in phasing, while the call sets derived from both LRS and SRS exhibited comparable levels of Mendelian consistency. Of particular interest in our study is a de novo 11kb deletion encompassing the last intron, last exon, and 3’ UTR of PPP3CA. Through experimental investigations, we discovered a significant reduction in PPP3CA protein levels in blood cells from the schizophrenia patient harboring this DNM. Similar reductions in PPP3CA protein levels were also observed in HEK293T cell lines carrying a comparable mutation, indicating that the down regulation of PPP3CA results from the identified de novo SV. Subsequently, in mice model with targeted knockdown of PPP3CA in excitatory neurons within the hippocampus, we observed alterations indicative of schizophrenia-like behavior and impaired cognitive funct
{"title":"UNRAVELING THE ROLE OF DE NOVO STRUCTURAL VARIANTS IN SCHIZOPHRENIA THROUGH COMPREHENSIVE WHOLE GENOME SEQUENCING WITH LONG-READ AND SHORT-READ TECHNOLOGIES","authors":"Yamin Zhang , Tong Li , Shaozhong Yang , Zhi Xie , Tao Li","doi":"10.1016/j.euroneuro.2024.08.040","DOIUrl":"10.1016/j.euroneuro.2024.08.040","url":null,"abstract":"<div><h3>Backgrounds</h3><div>Genetic liability to schizophrenia involves various types of mutations from across the allele frequency spectrum and distributed across the genome. Findings from studies focusing on different types of mutations in schizophrenia converge partially on the same biological processes, while also providing complementary insights. This underscores the importance of studying the full spectrum of mutation. However, currently widely used genotyping technologies, microarrays and short read sequencing (SRS), have limited ability in detecting medium-sized structural variations (SVs) (e.g. 50-2000bp) compared to long-read sequencing (LRS), which is relatively new and has been rarely applied to genetic studies of schizophrenia so far, suggesting an opportunity to leverage this more comprehensive approach to uncover additional sources of genetic variation that may contribute to the disorder.</div></div><div><h3>Methods</h3><div>Utilizing both 20X LRS and 30X SRS, we performed comprehensive whole-genome analysis on 40 Han Chinese parent-offspring trios. We called single nucleotide variants (SNVs), insertions and deletions (indels), and SVs utilizing multiple algorithms. Our primary focus was on the detection and validation of de novo mutations (DNMs). Comparative analysis between LRS and SRS was conducted to assess their respective abilities in detecting SVs and de novo SVs. Subsequently, we annotated the de novo mutations and delved into their potential mechanisms in schizophrenia through mining public databases and conducting functional experiments. Finally, we compared the diagnostic yield of our approach to previous studies employing whole exome sequencing or whole genome sequencing using SRS.</div></div><div><h3>Results</h3><div>Our analysis identified an average of 71.55 DNMs per proband, including 12 de novo SVs. Notably, four of these de novo SVs were detected by more than three out of four algorithms employed for LRS, whereas none were detected by any of the four algorithms utilized for SRS. In addition, our analysis revealed a 2.8Mb region exclusively accessible via by LRS and not SRS. LRS demonstrated exceptional performance in phasing, while the call sets derived from both LRS and SRS exhibited comparable levels of Mendelian consistency. Of particular interest in our study is a de novo 11kb deletion encompassing the last intron, last exon, and 3’ UTR of PPP3CA. Through experimental investigations, we discovered a significant reduction in PPP3CA protein levels in blood cells from the schizophrenia patient harboring this DNM. Similar reductions in PPP3CA protein levels were also observed in HEK293T cell lines carrying a comparable mutation, indicating that the down regulation of PPP3CA results from the identified de novo SV. Subsequently, in mice model with targeted knockdown of PPP3CA in excitatory neurons within the hippocampus, we observed alterations indicative of schizophrenia-like behavior and impaired cognitive funct","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Pages 13-14"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.102
José J. Morosoli , Lucia Colodro-Conde , Fiona K. Barlow , Sarah E. Medland
<div><div>From my perspective, science communication goes beyond the mere transmission of information from experts to non-experts. Science communication is dynamic and influenced by personal characteristics and sociopolitical context. As scientists, we not only need to know our audience but also understand ourselves better. The main topics of this presentation are (i) literacy and the use of jargon when talking about genetics; and (ii) specific cognitive biases in how we process information about genetics, including how personal values and experiences can influence how we understand scientific information.</div><div>The talk will be structured in two sections: The first section synthesises our previous work on public understanding of genetics. First, I will discuss a survey study on genetic literacy and public attitudes towards genetic testing in mental health. In this study, we surveyed families that had previously participated in genetic research studies at QIMR Berghofer, Australia (N=3,974), and the general population from the U.K. (N=501) and the U.S. (N=500). Results showed a high interest in psychiatric genetic testing, but the potential for negative impact of such information is also high, with more than a third of the participants showing serious concerns relating to learning about personal genetic predisposition. Concerns were mitigated by higher levels of genetic literacy, leading to less worry about coping with learning about a high genetic predisposition for several mental health problems and less prejudice against people with a high genetic predisposition. Second, I will discuss our recent review on online media articles covering genome-wide association studies (GWAS). We show that we might be missing a major opportunity for increasing general knowledge about genetic findings. Indeed, ∼95% of the news sites and blogs on GWAS used a language too complex to be understood by most adults. Most news articles used the terms ‘RNA’, ‘risk’, ‘gene’, ‘genome’, and ‘DNA’, while the terms ‘marker, ‘polymorphism’, or ‘allele’, rarely appeared. To contextualise these results, I will present new data from our survey showing the results from a modified version of the Rapid Estimate of Adult Literacy in Genetics (REAL-G), which evaluates how familiar the public is with the terms ‘genetics’, ‘chromosome’, ‘susceptibility’, ‘mutation’, ‘genetic variant’, ‘heredity’, and ‘polygenic’. I will briefly touch on the concept of ‘framing’, or how interpretation of information can be influenced by the presence or absence of certain words or images. For example, media on GWAS tends to focus on ‘risk’ (mentioned in 63.7% of articles) versus ‘susceptibility’ (12.2%) or ‘protect’ (11.3%) – the stem of words such as ‘protective’.</div><div>In the second section, I will discuss previous research on genetic determinism as a cognitive bias, as well as the role of motivated cognition. That is, we are not passive or even objective recipients of scientific information, b
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