Nature genetics最新文献

{"title":"Integrative analyses highlight functional regulatory variants associated with neuropsychiatric diseases","authors":"Margaret G. Guo, David L. Reynolds, Cheen E. Ang, Yingfei Liu, Yang Zhao, Laura K. H. Donohue, Zurab Siprashvili, Xue Yang, Yongjin Yoo, Smarajit Mondal, Audrey Hong, Jessica Kain, Lindsey Meservey, Tania Fabo, Ibtihal Elfaki, Laura N. Kellman, Nathan S. Abell, Yash Pershad, Vafa Bayat, Payam Etminani, Mark Holodniy, Daniel H. Geschwind, Stephen B. Montgomery, Laramie E. Duncan, Alexander E. Urban, Russ B. Altman, Marius Wernig, Paul A. Khavari","doi":"10.1038/s41588-023-01533-5","DOIUrl":"10.1038/s41588-023-01533-5","url":null,"abstract":"Noncoding variants of presumed regulatory function contribute to the heritability of neuropsychiatric disease. A total of 2,221 noncoding variants connected to risk for ten neuropsychiatric disorders, including autism spectrum disorder, attention deficit hyperactivity disorder, bipolar disorder, borderline personality disorder, major depression, generalized anxiety disorder, panic disorder, post-traumatic stress disorder, obsessive-compulsive disorder and schizophrenia, were studied in developing human neural cells. Integrating epigenomic and transcriptomic data with massively parallel reporter assays identified differentially-active single-nucleotide variants (daSNVs) in specific neural cell types. Expression-gene mapping, network analyses and chromatin looping nominated candidate disease-relevant target genes modulated by these daSNVs. Follow-up integration of daSNV gene editing with clinical cohort analyses suggested that magnesium transport dysfunction may increase neuropsychiatric disease risk and indicated that common genetic pathomechanisms may mediate specific symptoms that are shared across multiple neuropsychiatric diseases. Epigenomic profiling and massively parallel reporter assays identify 892 functional differentially-active single-nucleotide variants (daSNVs) linked to ten neuropsychiatric diseases. CRISPRi and gene editing approaches show magnesium transport dysfunction as a common genetic pathomechanism.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 11","pages":"1876-1891"},"PeriodicalIF":30.8,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49679924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-wide association meta-analysis identifies risk loci for abdominal aortic aneurysm and highlights PCSK9 as a therapeutic target","authors":"Tanmoy Roychowdhury, Derek Klarin, Michael G. Levin, Joshua M. Spin, Yae Hyun Rhee, Alicia Deng, Colwyn A. Headley, Noah L. Tsao, Corry Gellatly, Verena Zuber, Fred Shen, Whitney E. Hornsby, Ina Holst Laursen, Shefali S. Verma, Adam E. Locke, Gudmundur Einarsson, Gudmar Thorleifsson, Sarah E. Graham, Ozan Dikilitas, Jack W. Pattee, Renae L. Judy, Ferran Pauls-Verges, Jonas B. Nielsen, Brooke N. Wolford, Ben M. Brumpton, Jaume Dilmé, Olga Peypoch, Laura Calsina Juscafresa, Todd L. Edwards, Dadong Li, Karina Banasik, Søren Brunak, Rikke L. Jacobsen, Minerva T. Garcia-Barrio, Jifeng Zhang, Lars M. Rasmussen, Regent Lee, Ashok Handa, Anders Wanhainen, Kevin Mani, Jes S. Lindholt, Lasse M. Obel, Ewa Strauss, Grzegorz Oszkinis, Christopher P. Nelson, Katie L. Saxby, Joost A. van Herwaarden, Sander W. van der Laan, Jessica van Setten, Mercedes Camacho, Frank M. Davis, Rachael Wasikowski, Lam C. Tsoi, Johann E. Gudjonsson, Jonathan L. Eliason, Dawn M. Coleman, Peter K. Henke, Santhi K. Ganesh, Y. Eugene Chen, Weihua Guan, James S. Pankow, Nathan Pankratz, Ole B. Pedersen, Christian Erikstrup, Weihong Tang, Kristian Hveem, Daniel Gudbjartsson, Solveig Gretarsdottir, Unnur Thorsteinsdottir, Hilma Holm, Kari Stefansson, Manuel A. Ferreira, Aris Baras, Iftikhar J. Kullo, Marylyn D. Ritchie, Alex H. Christensen, Kasper K. Iversen, Nikolaj Eldrup, Henrik Sillesen, Sisse R. Ostrowski, Henning Bundgaard, Henrik Ullum, Stephen Burgess, Dipender Gill, Katherine Gallagher, Maria Sabater-Lleal, DiscovEHR, Regeneron Genetics Center, UK Aneurysm Growth Study, DBDS Genomic Consortium, VA Million Veteran Program, Ida Surakka, Gregory T. Jones, Matthew J. Bown, Philip S. Tsao, Cristen J. Willer, Scott M. Damrauer","doi":"10.1038/s41588-023-01510-y","DOIUrl":"10.1038/s41588-023-01510-y","url":null,"abstract":"Abdominal aortic aneurysm (AAA) is a common disease with substantial heritability. In this study, we performed a genome-wide association meta-analysis from 14 discovery cohorts and uncovered 141 independent associations, including 97 previously unreported loci. A polygenic risk score derived from meta-analysis explained AAA risk beyond clinical risk factors. Genes at AAA risk loci indicate involvement of lipid metabolism, vascular development and remodeling, extracellular matrix dysregulation and inflammation as key mechanisms in AAA pathogenesis. These genes also indicate overlap between the development of AAA and other monogenic aortopathies, particularly via transforming growth factor β signaling. Motivated by the strong evidence for the role of lipid metabolism in AAA, we used Mendelian randomization to establish the central role of nonhigh-density lipoprotein cholesterol in AAA and identified the opportunity for repurposing of proprotein convertase, subtilisin/kexin-type 9 (PCSK9) inhibitors. This was supported by a study demonstrating that PCSK9 loss of function prevented the development of AAA in a preclinical mouse model. Genome-wide association meta-analysis of AAA identifies 121 independent risk loci and highlights potential therapeutic targets such as proprotein convertase, subtilisin/kexin-type 9 (PCSK9).","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 11","pages":"1831-1842"},"PeriodicalIF":30.8,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10632148/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41236921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regulatory controls of duplicated gene expression during fiber development in allotetraploid cotton","authors":"Jiaqi You, Zhenping Liu, Zhengyang Qi, Yizan Ma, Mengling Sun, Ling Su, Hao Niu, Yabing Peng, Xuanxuan Luo, Mengmeng Zhu, Yuefan Huang, Xing Chang, Xiubao Hu, Yuqi Zhang, Ruizhen Pi, Yuqi Liu, Qingying Meng, Jianying Li, Qinghua Zhang, Longfu Zhu, Zhongxu Lin, Ling Min, Daojun Yuan, Corrinne E. Grover, David D. Fang, Keith Lindsey, Jonathan F. Wendel, Lili Tu, Xianlong Zhang, Maojun Wang","doi":"10.1038/s41588-023-01530-8","DOIUrl":"10.1038/s41588-023-01530-8","url":null,"abstract":"Polyploidy complicates transcriptional regulation and increases phenotypic diversity in organisms. The dynamics of genetic regulation of gene expression between coresident subgenomes in polyploids remains to be understood. Here we document the genetic regulation of fiber development in allotetraploid cotton Gossypium hirsutum by sequencing 376 genomes and 2,215 time-series transcriptomes. We characterize 1,258 genes comprising 36 genetic modules that control staged fiber development and uncover genetic components governing their partitioned expression relative to subgenomic duplicated genes (homoeologs). Only about 30% of fiber quality-related homoeologs show phenotypically favorable allele aggregation in cultivars, highlighting the potential for subgenome additivity in fiber improvement. We envision a genome-enabled breeding strategy, with particular attention to 48 favorable alleles related to fiber phenotypes that have been subjected to purifying selection during domestication. Our work delineates the dynamics of gene regulation during fiber development and highlights the potential of subgenomic coordination underpinning phenotypes in polyploid plants. Genome and transcriptome analyses of 376 Gossypium hirsutum accessions uncover the regulation of gene expression during fiber development in allotetraploid cotton and highlight the potential for fiber quality improvement.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 11","pages":"1987-1997"},"PeriodicalIF":30.8,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10632151/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41236922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Precise identification of cell states altered in disease using healthy single-cell references","authors":"Emma Dann, Ana-Maria Cujba, Amanda J. Oliver, Kerstin B. Meyer, Sarah A. Teichmann, John C. Marioni","doi":"10.1038/s41588-023-01523-7","DOIUrl":"10.1038/s41588-023-01523-7","url":null,"abstract":"Joint analysis of single-cell genomics data from diseased tissues and a healthy reference can reveal altered cell states. We investigate whether integrated collections of data from healthy individuals (cell atlases) are suitable references for disease-state identification and whether matched control samples are needed to minimize false discoveries. We demonstrate that using a reference atlas for latent space learning followed by differential analysis against matched controls leads to improved identification of disease-associated cells, especially with multiple perturbed cell types. Additionally, when an atlas is available, reducing control sample numbers does not increase false discovery rates. Jointly analyzing data from a COVID-19 cohort and a blood cell atlas, we improve detection of infection-related cell states linked to distinct clinical severities. Similarly, we studied disease states in pulmonary fibrosis using a healthy lung atlas, characterizing two distinct aberrant basal states. Our analysis provides guidelines for designing disease cohort studies and optimizing cell atlas use. In single-cell studies, combining healthy reference atlases and designed control datasets allows more precise identification of disease-associated cell states.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 11","pages":"1998-2008"},"PeriodicalIF":30.8,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10632138/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41205962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuronal chromatin meta-domains","authors":"Tiago Faial","doi":"10.1038/s41588-023-01541-5","DOIUrl":"10.1038/s41588-023-01541-5","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 10","pages":"1609-1609"},"PeriodicalIF":30.8,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41205966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Calling SNVs in single cells","authors":"Kyle Vogan","doi":"10.1038/s41588-023-01544-2","DOIUrl":"10.1038/s41588-023-01544-2","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 10","pages":"1609-1609"},"PeriodicalIF":30.8,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41205965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Saving endangered species with genomic prediction","authors":"Michael Fletcher","doi":"10.1038/s41588-023-01542-4","DOIUrl":"10.1038/s41588-023-01542-4","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 10","pages":"1609-1609"},"PeriodicalIF":30.8,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41205968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Protein structural alignment using deep learning","authors":"Wei Li","doi":"10.1038/s41588-023-01543-3","DOIUrl":"10.1038/s41588-023-01543-3","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 10","pages":"1609-1609"},"PeriodicalIF":30.8,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41205967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying genetic subtypes of disease from hospital diagnosis records","authors":"","doi":"10.1038/s41588-023-01521-9","DOIUrl":"10.1038/s41588-023-01521-9","url":null,"abstract":"We developed a computational, age-dependent topic model to identify longitudinal comorbidity patterns from hospital diagnosis data. The inferred comorbidity patterns are robust across UK and US populations and identify disease subtypes with distinct genetic profiles.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 11","pages":"1788-1789"},"PeriodicalIF":30.8,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41183170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk","authors":"Xilin Jiang, Martin Jinye Zhang, Yidong Zhang, Arun Durvasula, Michael Inouye, Chris Holmes, Alkes L. Price, Gil McVean","doi":"10.1038/s41588-023-01522-8","DOIUrl":"10.1038/s41588-023-01522-8","url":null,"abstract":"The analysis of longitudinal data from electronic health records (EHRs) has the potential to improve clinical diagnoses and enable personalized medicine, motivating efforts to identify disease subtypes from patient comorbidity information. Here we introduce an age-dependent topic modeling (ATM) method that provides a low-rank representation of longitudinal records of hundreds of distinct diseases in large EHR datasets. We applied ATM to 282,957 UK Biobank samples, identifying 52 diseases with heterogeneous comorbidity profiles; analyses of 211,908 All of Us samples produced concordant results. We defined subtypes of the 52 heterogeneous diseases based on their comorbidity profiles and compared genetic risk across disease subtypes using polygenic risk scores (PRSs), identifying 18 disease subtypes whose PRS differed significantly from other subtypes of the same disease. We further identified specific genetic variants with subtype-dependent effects on disease risk. In conclusion, ATM identifies disease subtypes with differential genome-wide and locus-specific genetic risk profiles. Age-dependent topic modeling provides a low-rank representation of longitudinal disease records and identifies diseases with heterogeneous comorbidity profiles, defining subtypes that exhibit distinct genome-wide and locus-specific association patterns.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"55 11","pages":"1854-1865"},"PeriodicalIF":30.8,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10632146/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41183169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}