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Corradi C, Lencioni G, Felici A, Rizzato C, Gentiluomo M, Ermini S, Archibugi L, Mickevicius A, Lucchesi M, Malecka-Wojciesko E, Basso D, Arcidiacono PG, Petrone MC, Carrara S, Götz M, Bunduc S, Holleczek B, Aoki MN, Uzunoglu FG, Zanette DL, Mambrini A, Jamroziak K, Oliverius M, Lovecek M, Cavestro GM, Milanetto AC, Peduzzi G, Duchonova BM, Izbicki JR, Zalinkevicius R, Hlavac V, van Eijck CHJ, Brenner H, Vanella G, Vokacova K, Soucek P, Tavano F, Perri F, Capurso G, Hussein T, Kiudelis M, Kupcinskas J, Busch OR, Morelli L, Theodoropoulos GE, Testoni SGG, Adamonis K, Neoptolemos JP, Gazouli M, Pasquali C, Kormos Z, Skalicky P, Pezzilli R, Sperti C, Kauffmann E, Büchler MW, Schöttker B, Hegyi P, Capretti G, Lawlor RT, Canzian F, Campa D. Potential association between PSCA rs2976395 functional variant and pancreatic cancer risk. Int J Cancer 2024; 155:1432-1442. [PMID: 38924078 DOI: 10.1002/ijc.35046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 03/13/2024] [Accepted: 03/20/2024] [Indexed: 06/28/2024]
Abstract
Correlated regions of systemic interindividual variation (CoRSIV) represent a small proportion of the human genome showing DNA methylation patterns that are the same in all human tissues, are different among individuals, and are partially regulated by genetic variants in cis. In this study we aimed at investigating single-nucleotide polymorphisms (SNPs) within CoRSIVs and their involvement with pancreatic ductal adenocarcinoma (PDAC) risk. We analyzed 29,099 CoRSIV-SNPs and 133,615 CoRSIV-mQTLs in 14,394 cases and 247,022 controls of European and Asian descent. We observed that the A allele of the rs2976395 SNP was associated with increased PDAC risk in Europeans (p = 2.81 × 10-5). This SNP lies in the prostate stem cell antigen gene and is in perfect linkage disequilibrium with a variant (rs2294008) that has been reported to be associated with risk of many other cancer types. The A allele is associated with the DNA methylation level of the gene according to the PanCan-meQTL database and with overexpression according to QTLbase. The expression of the gene has been observed to be deregulated in many tumors of the gastrointestinal tract including pancreatic cancer; however, functional studies are needed to elucidate the function relevance of the association.
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Affiliation(s)
| | | | | | | | | | - Stefano Ermini
- Blood Transfusion Service, Azienda Ospedaliera-Universitaria Meyer, Children's Hospital, Florence, Italy
| | - Livia Archibugi
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
- Digestive and Liver Disease Unit, Sant'Andrea Hospital, Rome, Italy
| | - Antanas Mickevicius
- Department of Surgery, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Maurizio Lucchesi
- Oncology of Massa Carrara, Oncological Department, Azienda USL Toscana Nord Ovest, Carrara, Italy
| | | | - Daniela Basso
- Laboratory Medicine, Department DIMED, University of Padova, Padua, Italy
| | - Paolo Giorgio Arcidiacono
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
| | - Maria Chiara Petrone
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Carrara
- Endoscoopic Unit, Gastroenterology Department, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Mara Götz
- Department of General, Visceral and Thoracic Surgery, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Stefania Bunduc
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- Digestive Diseases and Liver Transplantation Center, Fundeni Clinical Institute, Bucharest, Romania
- Center for Translational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Diseases, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | | | - Mateus Nóbrega Aoki
- Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba, Parana, Brazil
| | - Faik G Uzunoglu
- Department of General, Visceral and Thoracic Surgery, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Dalila Lucíola Zanette
- Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba, Parana, Brazil
| | - Andrea Mambrini
- Oncology of Massa Carrara, Oncological Department, Azienda USL Toscana Nord Ovest, Carrara, Italy
| | - Krzysztof Jamroziak
- Department of Hematology, Transplantation and Internal Medicine, Medical University of Warsaw, Warsaw, Poland
| | - Martin Oliverius
- Department of Surgery, University Hospital Kralovske Vinohrady, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | | | - Giulia Martina Cavestro
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | | | | | - Jakob R Izbicki
- Department of General, Visceral and Thoracic Surgery, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Rimantas Zalinkevicius
- Clinics of Institute of Endocrinology, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Viktor Hlavac
- Faculty of Medicine in Pilsen, Biomedical Center, Charles University, Pilsen, Czech Republic
| | - Casper H J van Eijck
- Department of Surgery, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Giuseppe Vanella
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
- Digestive and Liver Disease Unit, Sant'Andrea Hospital, Rome, Italy
| | - Klara Vokacova
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Pavel Soucek
- Faculty of Medicine in Pilsen, Biomedical Center, Charles University, Pilsen, Czech Republic
| | - Francesca Tavano
- Division of Gastroenterology and Research Laboratory, Fondazione IRCCS "Casa Sollievo della Sofferenza" Hospital, San Giovanni Rotondo, Italy
| | - Francesco Perri
- Division of Gastroenterology and Research Laboratory, Fondazione IRCCS "Casa Sollievo della Sofferenza" Hospital, San Giovanni Rotondo, Italy
| | - Gabriele Capurso
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
- Digestive and Liver Disease Unit, Sant'Andrea Hospital, Rome, Italy
| | - Tamás Hussein
- Center for Translational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Diseases, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Mindaugas Kiudelis
- Department of Surgery, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Juozas Kupcinskas
- Gastroenterology Department, Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Olivier R Busch
- Department of Surgery, Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Luca Morelli
- General Surgery, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - George E Theodoropoulos
- First Propaedeutic University Surgery Clinic, Hippocratio General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Sabrina Gloria Giulia Testoni
- Pancreato-Biliary Endoscopy and Endoscopic Ultrasound, Pancreas Translational and Clinical Research Center, IRSSC San Raffaele Scientific Institute, Milan, Italy
| | - Kestutis Adamonis
- Gastroenterology Department, Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas, Lithuania
- Department of Surgery, Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - John P Neoptolemos
- First Propaedeutic University Surgery Clinic, Hippocratio General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Maria Gazouli
- Department of Basic Medical Sciences, Laboratory of Biology, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | | | - Zita Kormos
- Division of Pancreatic Diseases, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | | | | | - Cosimo Sperti
- Department of DiSCOG, University of Padova, Padua, Italy
| | - Emanuele Kauffmann
- Division of General and Transplant Surgery, Pisa University Hospital, Pisa, Italy
| | - Markus W Büchler
- Department of General Surgery, University of Heidelberg, Heidelberg, Germany
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Péter Hegyi
- Center for Translational Medicine, Semmelweis University, Budapest, Hungary
- Division of Pancreatic Diseases, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- Institute for Translational Medicine, Medical School, University of Pécs, Pécs, Hungary
- János Szentágothai Research Center, University of Pécs, Pécs, Hungary
| | - Giovanni Capretti
- Pancreatic Surgery Department, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
- Humanitas University, Rozzano, Milan, Italy
| | - Rita T Lawlor
- ARC-NET Centre for Applied Research on Cancer, University and Hospital Trust of Verona, Verona, Italy
| | - Federico Canzian
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniele Campa
- Department of Biology, University of Pisa, Pisa, Italy
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Wu Q, Zhang Y, Huang X, Ma T, Hong LE, Kochunov P, Chen S. A multivariate to multivariate approach for voxel-wise genome-wide association analysis. Stat Med 2024; 43:3862-3880. [PMID: 38922949 DOI: 10.1002/sim.10101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 03/02/2024] [Accepted: 04/24/2024] [Indexed: 06/28/2024]
Abstract
The joint analysis of imaging-genetics data facilitates the systematic investigation of genetic effects on brain structures and functions with spatial specificity. We focus on voxel-wise genome-wide association analysis, which may involve trillions of single nucleotide polymorphism (SNP)-voxel pairs. We attempt to identify underlying organized association patterns of SNP-voxel pairs and understand the polygenic and pleiotropic networks on brain imaging traits. We propose a bi-clique graph structure (ie, a set of SNPs highly correlated with a cluster of voxels) for the systematic association pattern. Next, we develop computational strategies to detect latent SNP-voxel bi-cliques and an inference model for statistical testing. We further provide theoretical results to guarantee the accuracy of our computational algorithms and statistical inference. We validate our method by extensive simulation studies, and then apply it to the whole genome genetic and voxel-level white matter integrity data collected from 1052 participants of the human connectome project. The results demonstrate multiple genetic loci influencing white matter integrity measures on splenium and genu of the corpus callosum.
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Affiliation(s)
- Qiong Wu
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Yuan Zhang
- Department of Statistics, Ohio State University, Columbus, Ohio, USA
| | - Xiaoqi Huang
- Department of Mathematics, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, Maryland, USA
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - L Elliot Hong
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Peter Kochunov
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland, Baltimore, Maryland, USA
- The University of Maryland Institute for Health Computing, University of Maryland, North Bethesda, USA
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Li C, Chen K, Fang Q, Shi S, Nan J, He J, Yin Y, Li X, Li J, Hou L, Hu X, Kellis M, Han X, Xiong X. Crosstalk between epitranscriptomic and epigenomic modifications and its implication in human diseases. CELL GENOMICS 2024; 4:100605. [PMID: 38981476 DOI: 10.1016/j.xgen.2024.100605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 04/17/2024] [Accepted: 06/14/2024] [Indexed: 07/11/2024]
Abstract
Crosstalk between N6-methyladenosine (m6A) and epigenomes is crucial for gene regulation, but its regulatory directionality and disease significance remain unclear. Here, we utilize quantitative trait loci (QTLs) as genetic instruments to delineate directional maps of crosstalk between m6A and two epigenomic traits, DNA methylation (DNAme) and H3K27ac. We identify 47 m6A-to-H3K27ac and 4,733 m6A-to-DNAme and, in the reverse direction, 106 H3K27ac-to-m6A and 61,775 DNAme-to-m6A regulatory loci, with differential genomic location preference observed for different regulatory directions. Integrating these maps with complex diseases, we prioritize 20 genome-wide association study (GWAS) loci for neuroticism, depression, and narcolepsy in brain; 1,767 variants for asthma and expiratory flow traits in lung; and 249 for coronary artery disease, blood pressure, and pulse rate in muscle. This study establishes disease regulatory paths, such as rs3768410-DNAme-m6A-asthma and rs56104944-m6A-DNAme-hypertension, uncovering locus-specific crosstalk between m6A and epigenomic layers and offering insights into regulatory circuits underlying human diseases.
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Affiliation(s)
- Chengyu Li
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou 311121, China; State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 311121, China
| | - Kexuan Chen
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou 311121, China; State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 311121, China
| | - Qianchen Fang
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou 311121, China; State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 311121, China
| | - Shaohui Shi
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou 311121, China; State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 311121, China
| | - Jiuhong Nan
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou 311121, China; State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 311121, China
| | - Jialin He
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou 311121, China; State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 311121, China
| | - Yafei Yin
- The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Xiaoyu Li
- The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Jingyun Li
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China
| | - Lei Hou
- Department of Medicine, Biomedical Genetics Section, Boston University, Boston, MA 02118, USA
| | - Xinyang Hu
- State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 311121, China; The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Xikun Han
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Xushen Xiong
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou 311121, China; State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 311121, China.
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Biddie SC, Weykopf G, Hird EF, Friman ET, Bickmore WA. DNA-binding factor footprints and enhancer RNAs identify functional non-coding genetic variants. Genome Biol 2024; 25:208. [PMID: 39107801 PMCID: PMC11304670 DOI: 10.1186/s13059-024-03352-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 07/25/2024] [Indexed: 08/10/2024] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) have revealed a multitude of candidate genetic variants affecting the risk of developing complex traits and diseases. However, the highlighted regions are typically in the non-coding genome, and uncovering the functional causative single nucleotide variants (SNVs) is challenging. Prioritization of variants is commonly based on genomic annotation with markers of active regulatory elements, but current approaches still poorly predict functional variants. To address this, we systematically analyze six markers of active regulatory elements for their ability to identify functional variants. RESULTS We benchmark against molecular quantitative trait loci (molQTL) from assays of regulatory element activity that identify allelic effects on DNA-binding factor occupancy, reporter assay expression, and chromatin accessibility. We identify the combination of DNase footprints and divergent enhancer RNA (eRNA) as markers for functional variants. This signature provides high precision, but with a trade-off of low recall, thus substantially reducing candidate variant sets to prioritize variants for functional validation. We present this as a framework called FINDER-Functional SNV IdeNtification using DNase footprints and eRNA. CONCLUSIONS We demonstrate the utility to prioritize variants using leukocyte count trait and analyze variants in linkage disequilibrium with a lead variant to predict a functional variant in asthma. Our findings have implications for prioritizing variants from GWAS, in development of predictive scoring algorithms, and for functionally informed fine mapping approaches.
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Affiliation(s)
- Simon C Biddie
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
- NHS Lothian, Edinburgh, UK.
| | - Giovanna Weykopf
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | - Elias T Friman
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Wendy A Bickmore
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
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Chen K, Nan J, Xiong X. Genetic regulation of m 6A RNA methylation and its contribution in human complex diseases. SCIENCE CHINA. LIFE SCIENCES 2024; 67:1591-1600. [PMID: 38764000 DOI: 10.1007/s11427-024-2609-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/02/2024] [Indexed: 05/21/2024]
Abstract
N6-methyladenosine (m6A) has been established as the most prevalent chemical modification in message RNA (mRNA), playing an essential role in determining the fate of RNA molecules. Dysregulation of m6A has been revealed to lead to abnormal physiological conditions and cause various types of human diseases. Recent studies have delineated the genetic regulatory maps for m6A methylation by mapping the quantitative trait loci of m6A (m6A-QTLs), thereby building up the regulatory circuits linking genetic variants, m6A, and human complex traits. Here, we review the recent discoveries concerning the genetic regulatory maps of m6A, describing the methodological and technical details of m6A-QTL identification, and introducing the key findings of the cis- and trans-acting drivers of m6A. We further delve into the tissue- and ethnicity-specificity of m6A-QTL, the association with other molecular phenotypes in light of genetic regulation, the regulators underlying m6A genetics, and importantly, the functional roles of m6A in mediating human complex diseases. Lastly, we discuss potential research avenues that can accelerate the translation of m6A genetics studies toward the development of therapies for human genetic diseases.
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Affiliation(s)
- Kexuan Chen
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
- State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Jiuhong Nan
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
- State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Xushen Xiong
- The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China.
- State Key Laboratory of Transvascular Implantation Devices, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 311121, China.
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Xia R, Jian X, Rodrigue AL, Bressler J, Boerwinkle E, Cui B, Daviglus ML, DeCarli C, Gallo LC, Glahn DC, Knowles EEM, Moon JY, Mosley TH, Satizabal CL, Sofer T, Tarraf W, Testai F, Blangero J, Seshadri S, González HM, Fornage M. Admixture mapping of cognitive function in diverse Hispanic and Latino adults: Results from the Hispanic Community Health Study/Study of Latinos. Alzheimers Dement 2024. [PMID: 38946675 DOI: 10.1002/alz.14082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 05/28/2024] [Accepted: 05/29/2024] [Indexed: 07/02/2024]
Abstract
INTRODUCTION We conducted admixture mapping and fine-mapping analyses to identify ancestry-of-origin loci influencing cognitive abilities. METHODS We estimated the association of local ancestry intervals across the genome with five neurocognitive measures in 7140 diverse Hispanic and Latino adults (mean age 55 years). We prioritized genetic variants in associated loci and tested them for replication in four independent cohorts. RESULTS We identified nine local ancestry-associated regions for the five neurocognitive measures. There was strong biological support for the observed associations to cognitive function at all loci and there was statistical evidence of independent replication at 4q12, 9p22.1, and 13q12.13. DISCUSSION Our study identified multiple novel loci harboring genes implicated in cognitive functioning and dementia, and uncovered ancestry-relevant genetic variants. It adds to our understanding of the genetic architecture of cognitive function in Hispanic and Latino adults and demonstrates the power of admixture mapping to discover unique haplotypes influencing cognitive function, complementing genome-wide association studies. HIGHLIGHTS We identified nine ancestry-of-origin chromosomal regions associated with five neurocognitive traits. In each associated region, we identified single nucleotide polymorphisms (SNPs) that explained, at least in part, the admixture signal and were tested for replication in independent samples of Black, non-Hispanic White, and Hispanic/Latino adults with the same or similar neurocognitive tests. Statistical evidence of independent replication of the prioritized SNPs was observed for three of the nine associations, at chr4q12, chr9p22.1, and chr13q12.13. At all loci, there was strong biological support for the observed associations to cognitive function and dementia, prioritizing genes such as KIT, implicated in autophagic clearance of neurotoxic proteins and on mast cell and microglial-mediated inflammation; SLC24A2, implicated in synaptic plasticity associated with learning and memory; and MTMR6, implicated in phosphoinositide lipids metabolism.
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Affiliation(s)
- Rui Xia
- Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Xueqiu Jian
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Amanda L Rodrigue
- Department of Psychiatry, Harvard Medical School, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Biqi Cui
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, Illinois, USA
| | - Charles DeCarli
- Department of Neurology, University of California Davis, Sacramento, California, USA
| | - Linda C Gallo
- Department of Psychology, San Diego State University, San Diego, California, USA
| | - David C Glahn
- Department of Psychiatry, Harvard Medical School, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Emma E M Knowles
- Department of Psychiatry, Harvard Medical School, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Jee-Young Moon
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Thomas H Mosley
- The MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
- Department of Population Health Sciences, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Tamar Sofer
- Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Wassim Tarraf
- Institute of Gerontology & Department of Healthcare Sciences, Wayne State University, Detroit, Michigan, USA
| | - Fernando Testai
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, Illinois, USA
| | - John Blangero
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, Texas, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Hector M González
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
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7
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Malik R, Beaufort N, Li J, Tanaka K, Georgakis MK, He Y, Koido M, Terao C, Japan B, Anderson CD, Kamatani Y, Zand R, Dichgans M. Genetically proxied HTRA1 protease activity and circulating levels independently predict risk of ischemic stroke and coronary artery disease. NATURE CARDIOVASCULAR RESEARCH 2024; 3:701-713. [PMID: 39196222 DOI: 10.1038/s44161-024-00475-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 04/23/2024] [Indexed: 08/29/2024]
Abstract
Genetic variants in HTRA1 are associated with stroke risk. However, the mechanisms mediating this remain largely unknown, as does the full spectrum of phenotypes associated with genetic variation in HTRA1. Here we show that rare HTRA1 variants are linked to ischemic stroke in the UK Biobank and BioBank Japan. Integrating data from biochemical experiments, we next show that variants causing loss of protease function associated with ischemic stroke, coronary artery disease and skeletal traits in the UK Biobank and MyCode cohorts. Moreover, a common variant modulating circulating HTRA1 mRNA and protein levels enhances the risk of ischemic stroke and coronary artery disease while lowering the risk of migraine and macular dystrophy in genome-wide association study, UK Biobank, MyCode and BioBank Japan data. We found no interaction between proxied HTRA1 activity and levels. Our findings demonstrate the role of HTRA1 for cardiovascular diseases and identify two mechanisms as potential targets for therapeutic interventions.
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Affiliation(s)
- Rainer Malik
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Nathalie Beaufort
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Jiang Li
- Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA
| | - Koki Tanaka
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
| | - Marios K Georgakis
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Yunye He
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
| | - Masaru Koido
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - BioBank Japan
- Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Christopher D Anderson
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Boston, MA, USA
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
| | - Ramin Zand
- Department of Neurology, Pennsylvania State University, Hershey, PA, USA
- Department of Neurology, Neuroscience Institute, Geisinger Health System, Danville, PA, USA
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig Maximilian University of Munich, Munich, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.
- German Center for Cardiovascular Research (DZHK), Munich, Germany.
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
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8
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Xu LL, Gan T, Li Y, Chen P, Shi SF, Liu LJ, Lv JC, Zhang H, Zhou XJ. Combined Genetic Association and Differed Expression Analysis of UBE2L3 Uncovers a Genetic Regulatory Role of (Immuno)proteasome in IgA Nephropathy. KIDNEY DISEASES (BASEL, SWITZERLAND) 2024; 10:167-180. [PMID: 38835407 PMCID: PMC11149991 DOI: 10.1159/000537987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/20/2024] [Indexed: 06/06/2024]
Abstract
Introduction IgA nephropathy (IgAN) is a leading cause of end-stage renal disease. The exact pathogenesis of IgAN is not well defined, but some genetic studies have led to a novel discovery that the (immuno)proteasome probably plays an important role in IgAN. Methods We firstly analyzed the association of variants in the UBE2L3 region with susceptibility to IgAN in 3,495 patients and 9,101 controls, and then analyzed the association between lead variant and clinical phenotypes in 1,803 patients with regular follow-up data. The blood mRNA levels of members of the ubiquitin-proteasome system including UBE2L3 were analyzed in peripheral blood mononuclear cells from 53 patients and 28 healthy controls. The associations between UBE2L3 and the expression levels of genes involved in Gd-IgA1 production were also explored. Results The rs131654 showed the most significant association signal in UBE2L3 region (OR: 1.10, 95% CI: 1.04-1.16, p = 2.29 × 10-3), whose genotypes were also associated with the levels of Gd-IgA1 (p = 0.04). The rs131654 was observed to exert cis-eQTL effects on UBE2L3 in various tissues and cell types, particularly in immune cell types in multiple databases. The UBE2L3, LUBAC, and proteasome subunits were highly expressed in patients compared with healthy controls. High expression levels of UBE2L3 were not only associated with higher proteinuria (r = 0.34, p = 0.01) and lower eGFR (r = -0.28, p = 0.04), but also positively correlated with the gene expression of LUBAC and other proteasome subunits. Additionally, mRNA expression levels of UBE2L3 were also positively correlated with IL-6 and RELA, but negatively correlated with the expression levels of the key enzyme in the process of glycosylation including C1GALT1 and C1GALT1C1. Conclusion In conclusion, by combined genetic association and differed expression analysis of UBE2L3, our data support a role of genetically conferred dysregulation of the (immuno)proteasome in regulating galactose-deficient IgA1 in the development of IgAN.
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Affiliation(s)
- Lin-Lin Xu
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Ting Gan
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Yang Li
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Pei Chen
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Su-Fang Shi
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Li-Jun Liu
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Ji-Cheng Lv
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Beijing, China
- Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
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Shen S, Sobczyk MK, Paternoster L, Brown SJ. From GWASs toward Mechanistic Understanding with Case Studies in Dermatogenetics. J Invest Dermatol 2024; 144:1189-1199.e8. [PMID: 38782533 DOI: 10.1016/j.jid.2024.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 02/13/2024] [Accepted: 03/06/2024] [Indexed: 05/25/2024]
Abstract
Many human skin diseases result from the complex interplay of genetic and environmental mechanisms that are largely unknown. GWASs have yielded insight into the genetic aspect of complex disease by highlighting regions of the genome or specific genetic variants associated with disease. Leveraging this information to identify causal genes and cell types will provide insight into fundamental biology, inform diagnostics, and aid drug discovery. However, the etiological mechanisms from genetic variant to disease are still unestablished in most cases. There now exists an unprecedented wealth of data and computational methods for variant interpretation in a functional context. It can be challenging to decide where to start owing to a lack of consensus on the best way to identify causal genetic mechanisms. This article highlights 3 key aspects of genetic variant interpretation: prioritizing causal genes, cell types, and pathways. We provide a practical overview of the main methods and datasets, giving examples from recent atopic dermatitis studies to provide a blueprint for variant interpretation. A collection of resources, including brief description and links to the packages and web tools, is provided for researchers looking to start in silico follow-up genetic analysis of associated genetic variants.
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Affiliation(s)
- Silvia Shen
- Centre for Genomic & Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom; Institute for Evolution and Ecology, School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom.
| | - Maria K Sobczyk
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Sara J Brown
- Centre for Genomic & Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom; Department of Dermatology, NHS Lothian, Edinburgh, United Kingdom
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10
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Ponomarenko I, Pasenov K, Churnosova M, Sorokina I, Aristova I, Churnosov V, Ponomarenko M, Reshetnikova Y, Reshetnikov E, Churnosov M. Obesity-Dependent Association of the rs10454142 PPP1R21 with Breast Cancer. Biomedicines 2024; 12:818. [PMID: 38672173 PMCID: PMC11048332 DOI: 10.3390/biomedicines12040818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 03/30/2024] [Accepted: 04/02/2024] [Indexed: 04/28/2024] Open
Abstract
The purpose of this work was to find a link between the breast cancer (BC)-risk effects of sex hormone-binding globulin (SHBG)-associated polymorphisms and obesity. The study was conducted on a sample of 1498 women (358 BC; 1140 controls) who, depending on the presence/absence of obesity, were divided into two groups: obese (119 BC; 253 controls) and non-obese (239 BC; 887 controls). Genotyping of nine SHBG-associated single nucleotide polymorphisms (SNP)-rs17496332 PRMT6, rs780093 GCKR, rs10454142 PPP1R21, rs3779195 BAIAP2L1, rs440837 ZBTB10, rs7910927 JMJD1C, rs4149056 SLCO1B1, rs8023580 NR2F2, and rs12150660 SHBG-was executed, and the BC-risk impact of these loci was analyzed by logistic regression separately in each group of obese/non-obese women. We found that the BC-risk effect correlated by GWAS with the SHBG-level polymorphism rs10454142 PPP1R21 depends on the presence/absence of obesity. The SHBG-lowering allele C rs10454142 PPP1R21 has a risk value for BC in obese women (allelic model: CvsT, OR = 1.52, 95%CI = 1.10-2.11, and pperm = 0.013; additive model: CCvsTCvsTT, OR = 1.71, 95%CI = 1.15-2.62, and pperm = 0.011; dominant model: CC + TCvsTT, OR = 1.95, 95%CI = 1.13-3.37, and pperm = 0.017) and is not associated with the disease in women without obesity. SNP rs10454142 PPP1R21 and 10 proxy SNPs have adipose-specific regulatory effects (epigenetic modifications of promoters/enhancers, DNA interaction with 51 transcription factors, eQTL/sQTL effects on five genes (PPP1R21, RP11-460M2.1, GTF2A1L, STON1-GTF2A1L, and STON1), etc.), can be "likely cancer driver" SNPs, and are involved in cancer-significant pathways. In conclusion, our study detected an obesity-dependent association of the rs10454142 PPP1R21 with BC in women.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (I.P.); (K.P.); (M.C.); (I.S.); (I.A.); (V.C.); (M.P.); (Y.R.); (E.R.)
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11
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Delgado D, Gillard M, Tong L, Demanelis K, Oliva M, Gleason KJ, Chernoff M, Chen L, Paner GP, Vander Griend D, Pierce BL. The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men. Cancer Epidemiol Biomarkers Prev 2024; 33:557-566. [PMID: 38294689 PMCID: PMC10990789 DOI: 10.1158/1055-9965.epi-23-0849] [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: 07/25/2023] [Revised: 09/29/2023] [Accepted: 01/29/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND American men of African ancestry (AA) have higher prostate cancer incidence and mortality rates compared with American men of European ancestry (EA). Differences in genetic susceptibility mechanisms may contribute to this disparity. METHODS To gain insights into the regulatory mechanisms of prostate cancer susceptibility variants, we tested the association between SNPs and DNA methylation (DNAm) at nearby CpG sites across the genome in benign and cancer prostate tissue from 74 AA and 74 EA men. Genome-wide SNP data (from benign tissue) and DNAm were generated using Illumina arrays. RESULTS Among AA men, we identified 6,298 and 2,641 cis-methylation QTLs (meQTL; FDR of 0.05) in benign and tumor tissue, respectively, with 6,960 and 1,700 detected in EA men. We leveraged genome-wide association study (GWAS) summary statistics to identify previously reported prostate cancer GWAS signals likely to share a common causal variant with a detected meQTL. We identified nine GWAS-meQTL pairs with strong evidence of colocalization (four in EA benign, three in EA tumor, two in AA benign, and three in AA tumor). Among these colocalized GWAS-meQTL pairs, we identified colocalizing expression quantitative trait loci (eQTL) impacting four eGenes with known roles in tumorigenesis. CONCLUSIONS These findings highlight epigenetic regulatory mechanisms by which prostate cancer-risk SNPs can modify local DNAm and/or gene expression in prostate tissue. IMPACT Overall, our findings showed general consistency in the meQTL landscape of AA and EA men, but meQTLs often differ by tissue type (normal vs. cancer). Ancestry-based linkage disequilibrium differences and lack of AA representation in GWAS decrease statistical power to detect colocalization for some regions.
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Affiliation(s)
- Dayana Delgado
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
| | - Marc Gillard
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
| | - Lin Tong
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
| | - Kathryn Demanelis
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15261
- UPMC Hillman Cancer Center, Pittsburgh, PA 15232
| | - Meritxell Oliva
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
- Genomics Research Center, AbbVie, North Chicago, IL 60064
| | | | - Meytal Chernoff
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
- Interdisciplinary Scientist Training Program, University of Chicago, Chicago, IL, USA
- University of Chicago Pritzker School of Medicine, Chicago, IL, USA
| | - Lin Chen
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
| | - Gladell P. Paner
- Department of Pathology, University of Chicago, Chicago, IL 60637
| | - Donald Vander Griend
- Department of Pathology, University of Illinois at Chicago, Chicago, IL 60607
- The University of Illinois Cancer Center, Chicago, IL
| | - Brandon L. Pierce
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60615
- Comprehensive Cancer Center, University of Chicago, Chicago, IL 60637
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12
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Pandey RK, Srivastava A, Mishra RK, Singh PP, Chaubey G. Novel genetic association of the Furin gene polymorphism rs1981458 with COVID-19 severity among Indian populations. Sci Rep 2024; 14:7822. [PMID: 38570613 PMCID: PMC10991378 DOI: 10.1038/s41598-024-54607-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 02/14/2024] [Indexed: 04/05/2024] Open
Abstract
SARS CoV-2, the causative agent for the ongoing COVID-19 pandemic, it enters the host cell by activating the ACE2 receptor with the help of two proteasesi.e., Furin and TMPRSS2. Therefore, variations in these genes may account for differential susceptibility and severity between populations. Previous studies have shown that the role of ACE2 and TMPRSS2 gene variants in understanding COVID-19 susceptibility among Indian populations. Nevertheless, a knowledge gap exists concerning the COVID-19 susceptibility of Furin gene variants among diverse South Asian ethnic groups. Investigating the role of Furin gene variants and their global phylogeographic structure is essential to comprehensively understanding COVID-19 susceptibility in these populations. We have used 450 samples from diverse Indian states and performed linear regression to analyse the Furin gene variant's with COVID-19 Case Fatality Rate (CFR) that could be epidemiologically associated with disease severity outcomes. Associated genetic variants were further evaluated for their expression and regulatory potential through various Insilco analyses. Additionally, we examined the Furin gene using next-generation sequencing (NGS) data from 393 diverse global samples, with a particular emphasis on South Asia, to investigate its Phylogeographic structure among diverse world populations. We found a significant positive association for the SNP rs1981458 with COVID-19 CFR (p < 0.05) among diverse Indian populations at different timelines of the first and second waves. Further, QTL and other regulatory analyses showed various significant associations for positive regulatory roles of rs1981458 and Furin gene, mainly in Immune cells and virus infection process, highlighting their role in host immunity and viral assembly and processing. The Furin protein-protein interaction suggested that COVID-19 may contribute to Pulmonary arterial hypertension via a typical inflammation mechanism. The phylogeographic architecture of the Furin gene demonstrated a closer genetic affinity of South Asia with West Eurasian populations. Therefore, it is worth proposing that for the Furin gene, the COVID-19 susceptibility of South Asians will be more similar to the West Eurasian population. Our previous studies on the ACE2 and TMPRSS2 genes showed genetic affinity of South Asian with East Eurasians and West Eurasians, respectively. Therefore, with the collective information from these three important genes (ACE2, TMPRSS2 and Furin) we modelled COVID-19 susceptibilityof South Asia in between these two major ancestries with an inclination towards West Eurasia. In conclusion, this study, for the first time, concluded the role of rs1981458 in COVID-19 severity among the Indian population and outlined its regulatory potential.This study also highlights that the genetic structure for COVID-19 susceptibilityof South Asia is distinct, however, inclined to the West Eurasian population. We believe this insight may be utilised as a genetic biomarker to identify vulnerable populations, which might be directly relevant for developing policies and allocating resources more effectively during an epidemic.
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Affiliation(s)
- Rudra Kumar Pandey
- Cytogenetics Laboratory, Department of Zoology, Banaras Hindu University, Varanasi, 221005, India.
| | - Anshika Srivastava
- Cytogenetics Laboratory, Department of Zoology, Banaras Hindu University, Varanasi, 221005, India
| | - Rahul Kumar Mishra
- Cytogenetics Laboratory, Department of Zoology, Banaras Hindu University, Varanasi, 221005, India
| | - Prajjval Pratap Singh
- Cytogenetics Laboratory, Department of Zoology, Banaras Hindu University, Varanasi, 221005, India
| | - Gyaneshwer Chaubey
- Cytogenetics Laboratory, Department of Zoology, Banaras Hindu University, Varanasi, 221005, India.
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Camerini L, Zurchimitten G, Bock B, Xavier J, Bastos CR, Martins E, Ardais AP, Dos Santos Motta JV, Pires AJ, de Matos MB, de Ávila Quevedo L, Pinheiro RT, Ghisleni G. Genetic Variations in Elements of the Oxytocinergic Pathway are Associated with Attention/Hyperactivity Problems and Anxiety Problems in Childhood. Child Psychiatry Hum Dev 2024; 55:552-563. [PMID: 36087156 DOI: 10.1007/s10578-022-01419-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 08/03/2022] [Accepted: 08/17/2022] [Indexed: 11/28/2022]
Abstract
Genetic alterations related to oxytocin system seem to influence the neurobiology of attention-deficit hyperactivity disorder and anxiety problems leading to greater functional, social and emotional impairment. Here, we analyzed the association of OXTR rs2254298 and CD38 rs6449182 variants with attention/hyperactivity problems and anxiety problems in children. The study enrolled 292 children and adjusted regression model revealed OXTR rs2254298 AA genotype as a risk factor for attention deficit/hyperactivity problems (PR: 2.37; PadjFDR = 0.006), attention problems (PR: 2.71; PadjFDR = 0.003) and anxiety problems (PR: 1.92; PadjFDR = 0.018). CD38 rs6449182 G allele showed as a risk factor for attention deficit/hyperactivity problems (PR: 1.56; PadjFDR = 0.028). Moreover, in silico approach for regulatory roles found markers that influence chromatin accessibility and transcription capacity. Together, these data provide genetic information of oxytocin in developmental and behavioral disorders opening a range of opportunities for future studies that clarify their neurobiology in childhood.
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Affiliation(s)
- Laísa Camerini
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Gabriel Zurchimitten
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Bertha Bock
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Janaína Xavier
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Clarissa Ribeiro Bastos
- Department of Neurosciences, Federal University of Santa Catarina, Florianopolis, Santa Catarina, Brazil
| | - Evânia Martins
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Ana Paula Ardais
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | | | - Andressa Jacondino Pires
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Mariana Bonati de Matos
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Luciana de Ávila Quevedo
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Ricardo Tavares Pinheiro
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Gabriele Ghisleni
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil.
- Post-Graduation Program of Health and Behavior, Laboratory of Clinical Neuroscience, Catholic University of Pelotas - UCPel, Center of Health Science, Rua Gonçalves Chaves 373, sala 324, CEP 96010-280, Pelotas, RS, Brasil.
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14
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Ponomarenko I, Pasenov K, Churnosova M, Sorokina I, Aristova I, Churnosov V, Ponomarenko M, Reshetnikov E, Churnosov M. Sex-Hormone-Binding Globulin Gene Polymorphisms and Breast Cancer Risk in Caucasian Women of Russia. Int J Mol Sci 2024; 25:2182. [PMID: 38396861 PMCID: PMC10888713 DOI: 10.3390/ijms25042182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 02/07/2024] [Accepted: 02/09/2024] [Indexed: 02/25/2024] Open
Abstract
In our work, the associations of GWAS (genome-wide associative studies) impact for sex-hormone-binding globulin (SHBG)-level SNPs with the risk of breast cancer (BC) in the cohort of Caucasian women of Russia were assessed. The work was performed on a sample of 1498 women (358 BC patients and 1140 control (non BC) subjects). SHBG correlated in previously GWAS nine polymorphisms such as rs780093 GCKR, rs17496332 PRMT6, rs3779195 BAIAP2L1, rs10454142 PPP1R21, rs7910927 JMJD1C, rs4149056 SLCO1B1, rs440837 ZBTB10, rs12150660 SHBG, and rs8023580 NR2F2 have been genotyped. BC risk effects of allelic and non-allelic SHBG-linked gene SNPs interactions were detected by regression analysis. The risk genetic factor for BC developing is an SHBG-lowering allele variant C rs10454142 PPP1R21 ([additive genetic model] OR = 1.31; 95%CI = 1.08-1.65; pperm = 0.024; power = 85.26%), which determines 0.32% of the cancer variance. Eight of the nine studied SHBG-related SNPs have been involved in cancer susceptibility as part of nine different non-allelic gene interaction models, the greatest contribution to which is made by rs10454142 PPP1R21 (included in all nine models, 100%) and four more SNPs-rs7910927 JMJD1C (five models, 55.56%), rs17496332 PRMT6 (four models, 44.44%), rs780093 GCKR (four models, 44.44%), and rs440837 ZBTB10 (four models, 44.44%). For SHBG-related loci, pronounced functionality in the organism (including breast, liver, fibroblasts, etc.) was predicted in silico, having a direct relationship through many pathways with cancer pathophysiology. In conclusion, our results demonstrated the involvement of SHBG-correlated genes polymorphisms in BC risk in Caucasian women in Russia.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (I.P.); (K.P.); (M.C.); (I.S.); (I.A.); (V.C.); (M.P.); (E.R.)
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15
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Sun K, Liu R. Genetic predisposition of BMP7 polymorphisms to lumbar disk herniation in the Chinese Han population. Cell Cycle 2024; 23:466-477. [PMID: 38651735 PMCID: PMC11174055 DOI: 10.1080/15384101.2024.2342703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 04/08/2024] [Indexed: 04/25/2024] Open
Abstract
Bone morphogenetic protein 7 (BMP7) can induce skeletal formation, promote the differentiation of chondrocytes and osteoblasts, and ameliorate intervertebral disc degeneration. The study was designed to evaluate the relationship of BMP7 variants to LDH risk in the Chinese Han population. BMP7 variants were genotyped with the Agena MassARRAY system among 690 LDH patients and 690 healthy controls. The odds ratio (OR) and 95% confidence interval (CI) were calculated by logistic regression. Multi-factor dimension reduction (MDR) (version 3.0.2) software was used to evaluate the effect of BMP7 variant-variant interaction on the susceptibility to LDH. Here, the risk-reducing association between rs230189 and LDH occurrence was found (p = 0.005, OR = 0.79). Specially, rs230189 was associated with decreased LDH risk in females (p = 0.001, OR = 0.60), elder group (p = 0.025, OR = 0.76), subjects with BMI < 24 kg/m2 (p = 0.027, OR = 0.48), nonsmokers (p = 0.001, OR = 0.66), and nondrinkers (p = 0.011, OR = 0.72). Moreover, rs1321862 might be the risk factor for LDH susceptibility among the participants with BMI < 24 kg/m2 (p = 0.024, OR = 1.84). MDR results displayed that rs230189 was the greatest attribution factor on LDH risk in the single-locus model, with an information gain of 0.44%. The present study demonstrated that BMP7 rs230189 g.55771443A>C may play a protective role against LDH risk. Our findings may help to understand the potential mechanism of BMP7 in LDH susceptibility.
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Affiliation(s)
- Kai Sun
- Department of Orthopedic, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- Department of Orthopedic, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China
| | - Ruiyu Liu
- Department of Orthopedic, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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16
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Pan S, Kang H, Liu X, Li S, Yang P, Wu M, Yuan N, Lin S, Zheng Q, Jia P. COLOCdb: a comprehensive resource for multi-model colocalization of complex traits. Nucleic Acids Res 2024; 52:D871-D881. [PMID: 37941154 PMCID: PMC10767919 DOI: 10.1093/nar/gkad939] [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: 08/15/2023] [Revised: 10/01/2023] [Accepted: 10/12/2023] [Indexed: 11/10/2023] Open
Abstract
Large-scale genome-wide association studies (GWAS) have provided profound insights into complex traits and diseases. Yet, deciphering the fine-scale molecular mechanisms of how genetic variants manifest to cause the phenotypes remains a daunting task. Here, we present COLOCdb (https://ngdc.cncb.ac.cn/colocdb), a comprehensive genetic colocalization database by integrating more than 3000 GWAS summary statistics and 13 types of xQTL to date. By employing two representative approaches for the colocalization analysis, COLOCdb deposits results from three key components: (i) GWAS-xQTL, pair-wise colocalization between GWAS loci and different types of xQTL, (ii) GWAS-GWAS, pair-wise colocalization between the trait-associated genetic loci from GWASs and (iii) xQTL-xQTL, pair-wise colocalization between the genetic loci associated with molecular phenotypes in xQTLs. These results together represent the most comprehensive colocalization analysis, which also greatly expands the list of shared variants with genetic pleiotropy. We expect that COLOCdb can serve as a unique and useful resource in advancing the discovery of new biological mechanisms and benefit future functional studies.
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Affiliation(s)
- Siyu Pan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Hongen Kang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Xinxuan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Shuhua Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Peng Yang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Mingqiu Wu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Na Yuan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Shiqi Lin
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Qiwen Zheng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
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17
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Dai Y, Hsu YC, Fernandes BS, Zhang K, Li X, Enduru N, Liu A, Manuel AM, Jiang X, Zhao Z. Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach. J Alzheimers Dis 2024; 97:1807-1827. [PMID: 38306043 DOI: 10.3233/jad-231020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
Background The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points. Objective To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach. Methods We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline. Results We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G > T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neurons and plays a role in controlling cell growth and differentiation. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Conclusions Our deep learning model effectively extracted relevant neuroimaging features and predicted individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene.
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Affiliation(s)
- Yulin Dai
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yu-Chun Hsu
- Center for Secure Artificial Intelligence for Healthcare, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Brisa S Fernandes
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kai Zhang
- Center for Secure Artificial Intelligence for Healthcare, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xiaoyang Li
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nitesh Enduru
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Andi Liu
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Astrid M Manuel
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xiaoqian Jiang
- Center for Secure Artificial Intelligence for Healthcare, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Zhongming Zhao
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
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18
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Abdel-Azim G, Patel P, Li S, Guo S, Black MH. Fast multiple-trait genome-wide association analysis for correlated longitudinal measurements. Sci Rep 2023; 13:20603. [PMID: 37996550 PMCID: PMC10667366 DOI: 10.1038/s41598-023-47555-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 11/15/2023] [Indexed: 11/25/2023] Open
Abstract
Large-scale longitudinal biobank data can be leveraged to identify genetic variation contributing to human diseases progression and traits trajectories. While methods for genome-wide association studies (GWAS) of multiple correlated traits have been proposed, an efficient multiple-trait approach to model longitudinal phenotypes is not currently available. We developed GAMUT, a genome-wide association approach for multiple longitudinal traits. GAMUT employs a mixed-effects model to fit longitudinal outcomes where a fast algorithm for inversion by recursive partitioning of the random effects submatrix is introduced. To evaluate performance of the algorithms introduced and assess their statistical power and type I error, stochastic simulation was conducted. Consistent with our expectation, power was greater for cross-sectional (CS) than longitudinal (LT) effects, particularly with a diminishing LT/CS ratio. With a minimum minor allele count of 3 within genotype by time categories, observed type I error was roughly equal to theoretical genome-wide significance. Additionally, 28 blood-based biomarkers measured at 2 time points on participants of the UK Biobank were used to compare GAMUT against single-trait standard and longitudinal GWAS (including rate of change). Across all biomarkers, we observed 539 (CS) and 248 (LT) significant independent variants for the GAMUT method, and 513 (CS) and 30 (LT) for single-trait longitudinal GWAS, respectively. Only 37 variants were identified by modeling rates of change using standard GWAS.
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Affiliation(s)
| | - Parth Patel
- Janssen Res. & Dev. (Johnson & Johnson), Spring House, PA, USA
| | - Shuwei Li
- Janssen Res. & Dev. (Johnson & Johnson), Spring House, PA, USA
| | - Shicheng Guo
- Janssen Res. & Dev. (Johnson & Johnson), Spring House, PA, USA
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19
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Ding R, Zou X, Qin Y, Gong L, Chen H, Ma X, Guang S, Yu C, Wang G, Li L. xQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs. Brief Bioinform 2023; 25:bbad440. [PMID: 38058186 PMCID: PMC10701093 DOI: 10.1093/bib/bbad440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 10/23/2023] [Accepted: 11/11/2023] [Indexed: 12/08/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified thousands of disease-associated non-coding variants, posing urgent needs for functional interpretation. Molecular Quantitative Trait Loci (xQTLs) such as eQTLs serve as an essential intermediate link between these non-coding variants and disease phenotypes and have been widely used to discover disease-risk genes from many population-scale studies. However, mining and analyzing the xQTLs data presents several significant bioinformatics challenges, particularly when it comes to integration with GWAS data. Here, we developed xQTLbiolinks as the first comprehensive and scalable tool for bulk and single-cell xQTLs data retrieval, quality control and pre-processing from public repositories and our integrated resource. In addition, xQTLbiolinks provided a robust colocalization module through integration with GWAS summary statistics. The result generated by xQTLbiolinks can be flexibly visualized or stored in standard R objects that can easily be integrated with other R packages and custom pipelines. We applied xQTLbiolinks to cancer GWAS summary statistics as case studies and demonstrated its robust utility and reproducibility. xQTLbiolinks will profoundly accelerate the interpretation of disease-associated variants, thus promoting a better understanding of disease etiologies. xQTLbiolinks is available at https://github.com/lilab-bioinfo/xQTLbiolinks.
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Affiliation(s)
- Ruofan Ding
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Xudong Zou
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Yangmei Qin
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Lihai Gong
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Hui Chen
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Xuelian Ma
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Shouhong Guang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of USTC, The USTC RNA Institute, Ministry of Education Key Laboratory for Membraneless Organelles & Cellular Dynamics, School of Life Sciences, Division of Life Sciences and Medicine, Biomedical Sciences and Health Laboratory of Anhui Province, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Chen Yu
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Gao Wang
- The Gertrude H. Sergievsky Center and the Department of Neurology, Columbia University, NY 10032, USA
| | - Lei Li
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
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20
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Zhu Z, Chen X, Zhang S, Yu R, Qi C, Cheng L, Zhang X. Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective. Hum Genet 2023; 142:1543-1560. [PMID: 37755483 DOI: 10.1007/s00439-023-02602-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/14/2023] [Indexed: 09/28/2023]
Abstract
Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.
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Affiliation(s)
- Zijun Zhu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Xinyu Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Sainan Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Rui Yu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Changlu Qi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China.
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China.
| | - Xue Zhang
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
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Acharya V, Fan KH, Snitz BE, Ganguli M, DeKosky ST, Lopez OL, Feingold E, Kamboh MI. Meta-analysis of age-related cognitive decline reveals a novel locus for the attention domain and implicates a COVID-19-related gene for global cognitive function. Alzheimers Dement 2023; 19:5010-5022. [PMID: 37089073 PMCID: PMC10590825 DOI: 10.1002/alz.13064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 03/01/2023] [Accepted: 03/08/2023] [Indexed: 04/25/2023]
Abstract
INTRODUCTION Cognitive abilities have substantial heritability throughout life, as shown by twin- and population-based studies. However, there is limited understanding of the genetic factors related to cognitive decline in aging across neurocognitive domains. METHODS We conducted a meta-analysis on 3045 individuals aged ≥65, derived from three population-based cohorts, to identify genetic variants associated with the decline of five neurocognitive domains (attention, memory, executive function, language, visuospatial function) and global cognitive decline. We also conducted gene-based and functional bioinformatics analyses. RESULTS Apolipoprotein E (APOE)4 was significantly associated with decline of memory (p = 5.58E-09) and global cognitive function (p = 1.84E-08). We identified a novel association with attention decline on chromosome 9, rs6559700 (p = 2.69E-08), near RASEF. Gene-based analysis also identified a novel gene, TMPRSS11D, involved in the activation of SARS-CoV-2, to be associated with the decline in global cognitive function (p = 4.28E-07). DISCUSSION Domain-specific genetic studies can aid in the identification of novel genes and pathways associated with decline across neurocognitive domains. HIGHLIGHTS rs6559700 was associated with decline of attention. APOE4 was associated with decline of memory and global cognitive decline. TMPRSS11D, a gene involved in the activation of SARS-CoV-2, was implicated in global cognitive decline. Cognitive domain abilities had both unique and shared molecular pathways across the domains.
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Affiliation(s)
- Vibha Acharya
- Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, PA 15261, USA
| | - Kang-Hsien Fan
- Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, PA 15261, USA
| | - Beth E. Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Mary Ganguli
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Steven T. DeKosky
- McKnight Brain Institute and Department of Neurology, College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Oscar L. Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Eleanor Feingold
- Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, PA 15261, USA
| | - M. Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, PA 15261, USA
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
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22
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Li C, Wei Q, Hou Y, Lin J, Ou R, Zhang L, Jiang Q, Xiao Y, Liu K, Chen X, Yang T, Song W, Zhao B, Wu Y, Shang H. Genome-wide analyses identify NEAT1 as genetic modifier of age at onset of amyotrophic lateral sclerosis. Mol Neurodegener 2023; 18:77. [PMID: 37872557 PMCID: PMC10594666 DOI: 10.1186/s13024-023-00669-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 10/16/2023] [Indexed: 10/25/2023] Open
Abstract
BACKGROUND Patients with amyotrophic lateral sclerosis (ALS) demonstrate great heterogeneity in the age at onset (AAO), which is closely related to the course of disease. However, most genetic studies focused on the risk of ALS, while the genetic background underlying AAO of ALS is still unknown. METHODS To identify genetic determinants influencing AAO of ALS, we performed genome-wide association analysis using a Cox proportional hazards model in 2,841 patients with ALS (Ndiscovery = 2,272, Nreplication = 569) in the Chinese population. We further conducted colocalization analysis using public cis-eQTL dataset, and Mendelian randomization analysis to identify risk factors for AAO of ALS. Finally, functional experiments including dual-luciferase reporter assay and RT-qPCR were performed to explore the regulatory effect of the target variant. RESULTS The total heritability of AAO of ALS was ~ 0.24. One novel locus rs10128627 (FRMD8) was significantly associated with earlier AAO by ~ 3.15 years (P = 1.54E-08, beta = 0.31, SE = 0.05). This locus was cis-eQTL of NEAT1 in multiple brain tissues and blood. Colocalization analysis detected association signals at this locus between AAO of ALS and expression of NEAT1. Furthermore, functional exploration supported the variant rs10128627 was associated with upregulated expression of NEAT1 in cell models and patients with ALS. Causal inference suggested higher total cholesterol, low-density lipoprotein, and eosinophil were nominally associated with earlier AAO of ALS, while monocyte might delay the AAO. CONCLUSIONS Collective evidence from genetic, bioinformatic, and functional results suggested NEAT1 as a key player in the disease progression of ALS. These findings improve the current understanding of the genetic role in AAO of ALS, and provide a novel target for further research on the pathogenesis and therapeutic options to delay the disease onset.
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Affiliation(s)
- Chunyu Li
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Qianqian Wei
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Yanbing Hou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Junyu Lin
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Ruwei Ou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Lingyu Zhang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Qirui Jiang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Yi Xiao
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Kuncheng Liu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Xueping Chen
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - TianMi Yang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Wei Song
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Bi Zhao
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Ying Wu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, West China Hospital, National Clinical Research Center for Geriatric, Sichuan University, Chengdu, China.
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Xue H, Xu X, Yan Z, Cheng J, Zhang L, Zhu W, Cui G, Zhang Q, Qiu S, Yao Z, Qin W, Liu F, Liang M, Fu J, Xu Q, Xu J, Xie Y, Zhang P, Li W, Wang C, Shen W, Zhang X, Xu K, Zuo XN, Ye Z, Yu Y, Xian J, Yu C. Genome-wide association study of hippocampal blood-oxygen-level-dependent-cerebral blood flow correlation in Chinese Han population. iScience 2023; 26:108005. [PMID: 37822511 PMCID: PMC10562876 DOI: 10.1016/j.isci.2023.108005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 07/29/2023] [Accepted: 09/18/2023] [Indexed: 10/13/2023] Open
Abstract
Correlation between blood-oxygen-level-dependent (BOLD) and cerebral blood flow (CBF) has been used as an index of neurovascular coupling. Hippocampal BOLD-CBF correlation is associated with neurocognition, and the reduced correlation is associated with neuropsychiatric disorders. We conducted the first genome-wide association study of the hippocampal BOLD-CBF correlation in 4,832 Chinese Han subjects. The hippocampal BOLD-CBF correlation had an estimated heritability of 16.2-23.9% and showed reliable genome-wide significant association with a locus at 3q28, in which many variants have been linked to neuroimaging and cerebrospinal fluid markers of Alzheimer's disease. Gene-based association analyses showed four significant genes (GMNC, CRTC2, DENND4B, and GATAD2B) and revealed enrichment for mast cell calcium mobilization, microglial cell proliferation, and ubiquitin-related proteolysis pathways that regulate different cellular components of the neurovascular unit. This is the first unbiased identification of the association of hippocampal BOLD-CBF correlation, providing fresh insights into the genetic architecture of hippocampal neurovascular coupling.
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Affiliation(s)
- Hui Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou 310009, China
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Longjiang Zhang
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Guangbin Cui
- Functional and Molecular Imaging Key Lab of Shaanxi Province & Department of Radiology, Tangdu Hospital, Air Force Medical University, Xi’an 710038, China
| | - Quan Zhang
- Department of Radiology, Characteristic Medical Center of Chinese People’s Armed Police Force, Tianjin 300162, China
| | - Shijun Qiu
- Department of Medical Imaging, the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou 510405, China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Meng Liang
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin 300203, China
| | - Jilian Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yingying Xie
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Peng Zhang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - Wei Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Wen Shen
- Department of Radiology, Tianjin First Center Hospital, Tianjin 300192, China
| | - Xiaochu Zhang
- Division of Life Science and Medicine, University of Science & Technology of China, Hefei 230027, China
| | - Kai Xu
- Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou 221006, China
| | - Xi-Nian Zuo
- Developmental Population Neuroscience Research Center at IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
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Aslam MM, Fan KH, Lawrence E, Bedison MA, Snitz BE, DeKosky ST, Lopez OL, Feingold E, Kamboh MI. Genome-wide analysis identifies novel loci influencing plasma apolipoprotein E concentration and Alzheimer's disease risk. Mol Psychiatry 2023; 28:4451-4462. [PMID: 37666928 PMCID: PMC10827653 DOI: 10.1038/s41380-023-02170-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 06/16/2023] [Accepted: 06/27/2023] [Indexed: 09/06/2023]
Abstract
The APOE 2/3/4 polymorphism is the greatest genetic risk factor for Alzheimer's disease (AD). This polymorphism is also associated with variation in plasma ApoE level; while APOE*4 lowers, APOE*2 increases ApoE level. Lower plasma ApoE level has also been suggested to be a risk factor for incident dementia. To our knowledge, no large genome-wide association study (GWAS) has been reported on plasma ApoE level. This study aimed to identify new genetic variants affecting plasma ApoE level as well as to test if baseline ApoE level is associated with cognitive function and incident dementia in a longitudinally followed cohort of the Ginkgo Evaluation of Memory (GEM) study. Baseline plasma ApoE concentration was measured in 3031 participants (95.4% European Americans (EAs)). GWAS analysis was performed on 2580 self-identified EAs where both genotype and plasma ApoE data were available. Lower ApoE concentration was associated with worse cognitive function, but not with incident dementia. As expected, the risk for AD increased from E2/2 through to E4/4 genotypes (P for trend = 4.8E-75). In addition to confirming the expected and opposite associations of APOE*2 (P = 4.73E-79) and APOE*4 (P = 8.73E-12) with ApoE level, GWAS analysis revealed nine additional independent signals in the APOE region, and together they explained about 22% of the variance in plasma ApoE level. We also identified seven new loci on chromosomes 1, 4, 5, 7, 11, 12 and 20 (P range = 5.49E-08 to 5.36E-10) that explained about 9% of the variance in ApoE level. Plasma ApoE level-associated independent variants, especially in the APOE region, were also associated with AD risk and amyloid deposition in the brain, indicating that genetically determined ApoE level variation may be a risk factor for developing AD. These results improve our understanding of the genetic determinants of plasma ApoE level and their potential value in affecting AD risk.
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Affiliation(s)
- M Muaaz Aslam
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kang-Hsien Fan
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Elizabeth Lawrence
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Margaret Anne Bedison
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Steven T DeKosky
- McKnight Brain Institute and Department of Neurology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Oscar L Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eleanor Feingold
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
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Lei H, Chen X, Cheng B, Song L, Luo R, Wang S, Kang T, Wang Q, Zheng Y. The effects of unsaturated fatty acids on psoriasis: A two-sample Mendelian randomization study. Food Sci Nutr 2023; 11:6073-6084. [PMID: 37823124 PMCID: PMC10563715 DOI: 10.1002/fsn3.3543] [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] [Received: 12/28/2022] [Revised: 06/12/2023] [Accepted: 06/20/2023] [Indexed: 10/13/2023] Open
Abstract
Unsaturated fatty acids have been reported to be associated with the risk of psoriasis. However, the causal relationship between them remains unclear This study aimed to explore the causal relationship between unsaturated FAs and psoriasis. Firstly, we obtained genome-wide association study (GWAS) data for psoriasis from the FINNGEN database (number of cases = 4510, number of controls = 212,242) and different FA levels (number of samples = 114,999) from the IEU OpenGWAS Project. Secondly, the genetic correlation coefficient was calculated using linkage disequilibrium fractional regression. Thirdly, a two-sample Mendelian randomization (MR) analysis was performed using independent instrumental variables (p < 5 × 10-8) to determine the direction of randomization. Finally, expression quantitative trait loci (eQTL)-related analyses of common single nucleotide polymorphisms (SNPs) were carried out to explore the potential molecular mechanisms of unsaturated FAs affecting psoriasis. We found that an increase in the ratio of monounsaturated fatty acids (MUFAs) to total fatty acids could increase the risk of psoriasis (inverse-variance weighted [IVW], adjusted odds ratio [OR] = 1.175; adjusted 95% confidence interval [CI] = 1.045-1.321; adjusted p = .007). However, an increase in the ratio of polyunsaturated fatty acids (PUFAa) to total fatty acids could decrease the risk of psoriasis (IVW, adjusted OR = 0.754; adjusted 95% CI = 0.631-0.901; adjusted p = .002). Moreover, an increase in the ratio of PUFAs to MUFAs could decrease the risk of psoriasis (IVW, adjusted OR = 0.823; adjusted 95% CI = 0.715-0.948; adjusted p = .007). The heterogeneity of data was eliminated, and pleiotropy was not detected. There was no statistical difference in the MR analysis of other fatty acids indices with psoriasis. Further, no statistically significant evidence was found to verify a causal relationship between psoriasis and fatty acid levels in reverse MR. Functional enrichment analysis showed that these eQTL related to common SNPs were mainly involved in organic ion transport, choline metabolism, and the expression of key metabolic factors mediated by PKA, ChREBP, and PP2A. Our study indicated that the ratio of MUFAs to total fatty acids had a positive causal effect on psoriasis, while the ratio of PUFAs to total fatty acids and the ratio of PUFAs to MUFAs had a negative causal effect on psoriasis. Moreover, PKA-, PP2A-, and ChREBP-mediated activation of metabolic factors may play an important role in this process.
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Affiliation(s)
- Hao Lei
- Department of DermatologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Xin Chen
- State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontics, School of StomatologyThe Fourth Military Medical UniversityXi'anChina
| | - Baochen Cheng
- Department of DermatologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Liumei Song
- Department of DermatologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Ruiting Luo
- Department of DermatologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Shengbang Wang
- Department of DermatologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Tong Kang
- Department of DermatologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Qian Wang
- Tangdu Hospital, Air Force Military Medical UniversityXi'anChina
| | - Yan Zheng
- Department of DermatologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
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Espuela-Ortiz A, Martin-Gonzalez E, Poza-Guedes P, González-Pérez R, Herrera-Luis E. Genomics of Treatable Traits in Asthma. Genes (Basel) 2023; 14:1824. [PMID: 37761964 PMCID: PMC10531302 DOI: 10.3390/genes14091824] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/12/2023] [Accepted: 09/16/2023] [Indexed: 09/29/2023] Open
Abstract
The astounding number of genetic variants revealed in the 15 years of genome-wide association studies of asthma has not kept pace with the goals of translational genomics. Moving asthma diagnosis from a nonspecific umbrella term to specific phenotypes/endotypes and related traits may provide insights into features that may be prevented or alleviated by therapeutical intervention. This review provides an overview of the different asthma endotypes and phenotypes and the genomic findings from asthma studies using patient stratification strategies and asthma-related traits. Asthma genomic research for treatable traits has uncovered novel and previously reported asthma loci, primarily through studies in Europeans. Novel genomic findings for asthma phenotypes and related traits may arise from multi-trait and specific phenotyping strategies in diverse populations.
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Affiliation(s)
- Antonio Espuela-Ortiz
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Tenerife, Spain; (A.E.-O.); (E.M.-G.)
| | - Elena Martin-Gonzalez
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Tenerife, Spain; (A.E.-O.); (E.M.-G.)
| | - Paloma Poza-Guedes
- Allergy Department, Hospital Universitario de Canarias, 38320 Santa Cruz de Tenerife, Tenerife, Spain; (P.P.-G.); (R.G.-P.)
- Severe Asthma Unit, Hospital Universitario de Canarias, 38320 San Cristóbal de La Laguna, Tenerife, Spain
| | - Ruperto González-Pérez
- Allergy Department, Hospital Universitario de Canarias, 38320 Santa Cruz de Tenerife, Tenerife, Spain; (P.P.-G.); (R.G.-P.)
- Severe Asthma Unit, Hospital Universitario de Canarias, 38320 San Cristóbal de La Laguna, Tenerife, Spain
| | - Esther Herrera-Luis
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
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27
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Sneha NP, Dharshini SAP, Taguchi YH, Gromiha MM. Investigating Neuron Degeneration in Huntington's Disease Using RNA-Seq Based Transcriptome Study. Genes (Basel) 2023; 14:1801. [PMID: 37761940 PMCID: PMC10530489 DOI: 10.3390/genes14091801] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 09/02/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
Huntington's disease (HD) is a progressive neurodegenerative disorder caused due to a CAG repeat expansion in the huntingtin (HTT) gene. The primary symptoms of HD include motor dysfunction such as chorea, dystonia, and involuntary movements. The primary motor cortex (BA4) is the key brain region responsible for executing motor/movement activities. Investigating patient and control samples from the BA4 region will provide a deeper understanding of the genes responsible for neuron degeneration and help to identify potential markers. Previous studies have focused on overall differential gene expression and associated biological functions. In this study, we illustrate the relationship between variants and differentially expressed genes/transcripts. We identified variants and their associated genes along with the quantification of genes and transcripts. We also predicted the effect of variants on various regulatory activities and found that many variants are regulating gene expression. Variants affecting miRNA and its targets are also highlighted in our study. Co-expression network studies revealed the role of novel genes. Function interaction network analysis unveiled the importance of genes involved in vesicle-mediated transport. From this unified approach, we propose that genes expressed in immune cells are crucial for reducing neuron death in HD.
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Affiliation(s)
- Nela Pragathi Sneha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India; (N.P.S.); (S.A.P.D.)
| | - S. Akila Parvathy Dharshini
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India; (N.P.S.); (S.A.P.D.)
| | - Y.-h. Taguchi
- Department of Physics, Chuo University, Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan;
| | - M. Michael Gromiha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India; (N.P.S.); (S.A.P.D.)
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Dai Y, Yu-Chun H, Fernandes BS, Zhang K, Xiaoyang L, Enduru N, Liu A, Manuel AM, Jiang X, Zhao Z. Disentangling accelerated cognitive decline from the normal aging process and unraveling its genetic components: A neuroimaging-based deep learning approach. RESEARCH SQUARE 2023:rs.3.rs-3328861. [PMID: 37720047 PMCID: PMC10503860 DOI: 10.21203/rs.3.rs-3328861/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/19/2023]
Abstract
Background The progressive cognitive decline that is an integral component of AD unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and Alzheimer's disease between different chronological points. Methods We developed a deep-learning framework based on dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline. Results We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G>T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neuron and plays a role in controlling cell growth and differentiation. In addition, MUC7 and PROL1/OPRPNon chromosome 4 were significant at the gene level. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Furthermore, we found that the cognitive decline slope GWAS was positively correlated with previous AD GWAS. Conclusion Our deep learning model was demonstrated effective on extracting relevant neuroimaging features and predicting individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene. Our approach has the potential to disentangle accelerated cognitive decline from the normal aging process and to determine its related genetic factors, leveraging opportunities for early intervention.
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Affiliation(s)
- Yulin Dai
- The University of Texas Health Science Center at Houston
| | - Hsu Yu-Chun
- The University of Texas Health Science Center at Houston
| | | | - Kai Zhang
- The University of Texas Health Science Center at Houston
| | - Li Xiaoyang
- The University of Texas Health Science Center at Houston
| | - Nitesh Enduru
- The University of Texas Health Science Center at Houston
| | - Andi Liu
- The University of Texas Health Science Center at Houston
| | | | - Xiaoqian Jiang
- The University of Texas Health Science Center at Houston
| | - Zhongming Zhao
- The University of Texas Health Science Center at Houston
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Wang YN, Gan T, Qu S, Xu LL, Hu Y, Liu LJ, Shi SF, Lv JC, Tsoi LC, Patrick MT, He K, Berthier CC, Xu HJ, Zhou XJ, Zhang H. MTMR3 risk alleles enhance Toll Like Receptor 9-induced IgA immunity in IgA nephropathy. Kidney Int 2023; 104:562-576. [PMID: 37414396 DOI: 10.1016/j.kint.2023.06.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 05/29/2023] [Accepted: 06/15/2023] [Indexed: 07/08/2023]
Abstract
Multiple genome-wide association studies (GWASs) have reproducibly identified the MTMR3/HORMAD2/LIF/OSM locus to be associated with IgA nephropathy (IgAN). However, the causal variant(s), implicated gene(s), and altered mechanisms remain poorly understood. Here, we performed fine-mapping analyses based on GWAS datasets encompassing 2762 IgAN cases and 5803 control individuals, and identified rs4823074 as the candidate causal variant that intersects the MTMR3 promoter in B-lymphoblastoid cells. Mendelian randomization studies suggested the risk allele may modulate disease susceptibility by affecting serum IgA levels through increased MTMR3 expression. Consistently, elevated MTMR3 expression in peripheral blood mononuclear cells was observed in patients with IgAN. Further mechanistic studies in vitro demonstrated that MTMR3 increased IgA production dependent upon its phosphatidylinositol 3-phosphate binding domain. Moreover, our study provided the in vivo functional evidence that Mtmr3-/- mice exhibited defective Toll Like Receptor 9-induced IgA production, glomerular IgA deposition, as well as mesangial cell proliferation. RNA-seq and pathway analyses showed that MTMR3 deficiency resulted in an impaired intestinal immune network for IgA production. Thus, our results support the role of MTMR3 in IgAN pathogenesis by enhancing Toll Like Receptor 9-induced IgA immunity.
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Affiliation(s)
- Yan-Na Wang
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Ting Gan
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Shu Qu
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Lin-Lin Xu
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Yong Hu
- Beijing Institute of Biotechnology, Beijing, People's Republic of China
| | - Li-Jun Liu
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Su-Fang Shi
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Ji-Cheng Lv
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Kevin He
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA; Kidney Epidemiology and Cost Center, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Celine C Berthier
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Hu-Ji Xu
- Department of Rheumatology and Immunology, Shanghai Changzheng Hospital, The Second Military Medical University, Shanghai, People's Republic of China
| | - Xu-Jie Zhou
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China.
| | - Hong Zhang
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China.
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30
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Iannuzo N, Dy ABC, Guerra S, Langlais PR, Ledford JG. The Impact of CC16 on Pulmonary Epithelial-Driven Host Responses during Mycoplasma pneumoniae Infection in Mouse Tracheal Epithelial Cells. Cells 2023; 12:1984. [PMID: 37566063 PMCID: PMC10416898 DOI: 10.3390/cells12151984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/27/2023] [Accepted: 07/31/2023] [Indexed: 08/12/2023] Open
Abstract
Club Cell Secretory Protein (CC16) plays many protective roles within the lung; however, the complete biological functions, especially regarding the pulmonary epithelium during infection, remain undefined. We have previously shown that CC16-deficient (CC16-/-) mouse tracheal epithelial cells (MTECs) have enhanced Mp burden compared to CC16-sufficient (WT) MTECs; therefore, in this study, we wanted to further define how the pulmonary epithelium responds to infection in the context of CC16 deficiency. Using mass spectrometry and quantitative proteomics to analyze proteins secreted apically from MTECs grown at an air-liquid interface, we investigated the protective effects that CC16 elicits within the pulmonary epithelium during Mycoplasma pneumoniae (Mp) infection. When challenged with Mp, WT MTECs have an overall reduction in apical protein secretion, whereas CC16-/- MTECs have increased apical protein secretion compared to their unchallenged controls. Following Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) assessment, many of the proteins upregulated from CC16-/- MTECS (unchallenged and during Mp infection) were related to airway remodeling, which were not observed by WT MTECs. These findings suggest that CC16 may be important in providing protection within the pulmonary epithelium during respiratory infection with Mp, which is the major causative agent of community-acquired pneumoniae.
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Affiliation(s)
- Natalie Iannuzo
- Department of Cellular and Molecular Medicine, University of Arizona, Tucson, AZ 85724, USA;
| | | | - Stefano Guerra
- Asthma and Airway Disease Research Center, Tucson, AZ 85724, USA
| | - Paul R. Langlais
- Department of Medicine, Division of Endocrinology, University of Arizona, Tucson, AZ 85724, USA
| | - Julie G. Ledford
- Department of Cellular and Molecular Medicine, University of Arizona, Tucson, AZ 85724, USA;
- Asthma and Airway Disease Research Center, Tucson, AZ 85724, USA
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31
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Chang L, Zhou G, Xia J. mGWAS-Explorer 2.0: Causal Analysis and Interpretation of Metabolite-Phenotype Associations. Metabolites 2023; 13:826. [PMID: 37512533 PMCID: PMC10384390 DOI: 10.3390/metabo13070826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 06/23/2023] [Accepted: 07/03/2023] [Indexed: 07/30/2023] Open
Abstract
Metabolomics-based genome-wide association studies (mGWAS) are key to understanding the genetic regulations of metabolites in complex phenotypes. We previously developed mGWAS-Explorer 1.0 to link single-nucleotide polymorphisms (SNPs), metabolites, genes and phenotypes for hypothesis generation. It has become clear that identifying potential causal relationships between metabolites and phenotypes, as well as providing deep functional insights, are crucial for further downstream applications. Here, we introduce mGWAS-Explorer 2.0 to support the causal analysis between >4000 metabolites and various phenotypes. The results can be interpreted within the context of semantic triples and molecular quantitative trait loci (QTL) data. The underlying R package is released for reproducible analysis. Using two case studies, we demonstrate that mGWAS-Explorer 2.0 is able to detect potential causal relationships between arachidonic acid and Crohn's disease, as well as between glycine and coronary heart disease.
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Affiliation(s)
- Le Chang
- Department of Human Genetics, McGill University, Montreal, QC H3A 0C7, Canada
| | - Guangyan Zhou
- Institute of Parasitology, McGill University, Montreal, QC H9X 3V9, Canada
| | - Jianguo Xia
- Department of Human Genetics, McGill University, Montreal, QC H3A 0C7, Canada
- Institute of Parasitology, McGill University, Montreal, QC H9X 3V9, Canada
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32
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Jeon Y, Jeon S, An K, Kim YJ, Kim BC, Ryu H, Choi WH, Choi H, Kim W, Lee SY, Bae JW, Hwang JY, Kang MG, An S, Kim Y, Kang Y, Kim BC, Bhak J, Shin ES. Identification and validation of six acute myocardial infarction-associated variants, including a novel prognostic marker for cardiac mortality. Front Cardiovasc Med 2023; 10:1226971. [PMID: 37465449 PMCID: PMC10350496 DOI: 10.3389/fcvm.2023.1226971] [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] [Received: 05/22/2023] [Accepted: 06/20/2023] [Indexed: 07/20/2023] Open
Abstract
Background Acute myocardial infarction (AMI) is one of the leading causes of death worldwide, and approximately half of AMI-related deaths occur before the affected individual reaches the hospital. The present study aimed to identify and validate genetic variants associated with AMI and their role as prognostic markers. Materials and methods We conducted a replication study of 29 previously identified novel loci containing 85 genetic variants associated with early-onset AMI using a new independent set of 2,920 Koreans [88 patients with early- and 1,085 patients with late-onset AMI, who underwent percutaneous coronary intervention (PCI), and 1,747 healthy controls]. Results Of the 85 previously reported early-onset variants, six were confirmed in our genome-wide association study with a false discovery rate of less than 0.05. Notably, rs12639023, a cis-eQTL located in the intergenic region between LINC02005 and CNTN3, significantly increased longitudinal cardiac mortality and recurrent AMI. CNTN3 is known to play a role in altering vascular permeability. Another variant, rs78631167, located upstream of PLAUR and known to function in fibrinolysis, was moderately replicated in this study. By surveying the nearby genomic region around rs78631167, we identified a significant novel locus (rs8109584) located 13 bp downstream of rs78631167. The present study showed that six of the early-onset variants of AMI are applicable to both early- and late-onset cases. Conclusion Our results confirm markers that can potentially be utilized to predict, screen, prevent, and treat candidate patients with AMI and highlight the potential of rs12639023 as a prognostic marker for cardiac mortality in AMI.
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Affiliation(s)
- Yeonsu Jeon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
- Clinomics Inc., Ulsan, Republic of Korea
| | | | - Kyungwhan An
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
| | | | | | | | - Whan-Hyuk Choi
- Department of Mathematics, Kangwon National University, ChunCheon, Republic of Korea
| | - HyunJoo Choi
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
| | - Weon Kim
- Division of Cardiology, Department of Internal Medicine, Kyung Hee University Hospital, Kyung Hee University, Seoul, Republic of Korea
| | - Sang Yeub Lee
- Division of Cardiology, Department of Internal Medicine, Chung-Ang University College of Medicine, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong, Republic of Korea
| | - Jang-Whan Bae
- Department of Internal Medicine, Chungbuk National University Hospital, College of Medicine, Chungbuk National University, Cheongju, Republic of Korea
| | - Jin-Yong Hwang
- Department of Internal Medicine, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
| | - Min Gyu Kang
- Department of Internal Medicine, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
| | - Seolbin An
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
| | | | | | | | - Jong Bhak
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
- Clinomics Inc., Ulsan, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
- Personal Genomics Institute (PGI), Genome Research Foundation (GRF), Osong, Republic of Korea
| | - Eun-Seok Shin
- Department of Cardiology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea
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Tang J, Zhang H, Zhang H, Zhu H. PopTradeOff: A database for exploring population-specificity of adaptive evolution, disease susceptibility, and drug responsiveness. Comput Struct Biotechnol J 2023; 21:3443-3451. [PMID: 37448726 PMCID: PMC10338148 DOI: 10.1016/j.csbj.2023.06.008] [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] [Received: 02/23/2023] [Revised: 05/26/2023] [Accepted: 06/08/2023] [Indexed: 07/15/2023] Open
Abstract
The influence of adaptive evolution on disease susceptibility has drawn attention; however, the extent of the influence, whether favored mutations also influence drug responses, and whether the associations between the three are population-specific remain unknown. Using a reported deep learning network to integrate seven statistical tests for detecting selection signals, we predicted favored mutations in the genomes of 17 human populations and integrated these favored mutations with reported GWAS sites and drug response-related variants into the database PopTradeOff (http://www.gaemons.net/PopFMIntro). The database also contains genome annotation information on the SNP, sequence, gene, and pathway levels. The preliminary data analyses suggest that substantial associations exist between adaptive evolution, disease susceptibility, and drug responses and that the associations are highly population-specific. The database may be valuable for disease studies, drug development, and personalized medicine.
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Affiliation(s)
- Ji Tang
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Huanlin Zhang
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Hai Zhang
- Network Center, Southern Medical University, Guangzhou 510515, China
| | - Hao Zhu
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou 510515, China
- Guangdong Provincial Key Lab of Single Cell Technology and Application, Southern Medical University, Guangzhou 510515, China
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Kobzeva KA, Soldatova MO, Stetskaya TA, Soldatov VO, Deykin AV, Freidin MB, Bykanova MA, Churnosov MI, Polonikov AV, Bushueva OY. Association between HSPA8 Gene Variants and Ischemic Stroke: A Pilot Study Providing Additional Evidence for the Role of Heat Shock Proteins in Disease Pathogenesis. Genes (Basel) 2023; 14:1171. [PMID: 37372351 DOI: 10.3390/genes14061171] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 05/18/2023] [Accepted: 05/23/2023] [Indexed: 06/29/2023] Open
Abstract
HSPA8 is involved in many stroke-associated cellular processes, playing a pivotal role in the protein quality control system. Here we report the results of the pilot study aimed at determining whether HSPA8 SNPs are linked to the risk of ischemic stroke (IS). DNA samples from 2139 Russians (888 IS patients and 1251 healthy controls) were genotyped for tagSNPs (rs1461496, rs10892958, and rs1136141) in the HSPA8 gene using probe-based PCR. SNP rs10892958 of HSPA8 was associated with an increased risk (risk allele G) of IS in smokers (OR = 1.37; 95% CI = 1.07-1.77; p = 0.01) and patients with low fruit and vegetable consumption (OR = 1.36; 95% CI = 1.14-1.63; p = 0.002). SNP rs1136141 of HSPA8 was also associated with an increased risk of IS (risk allele A) exclusively in smokers (OR = 1.68; 95% CI = 1.23-2.28; p = 0.0007) and in patients with a low fruit and vegetable intake (OR = 1.29; 95% CI = 1.05-1.60; p = 0.04). Sex-stratified analysis revealed an association of rs10892958 HSPA8 with an increased risk of IS in males (risk allele G; OR = 1.30; 95% CI = 1.05-1.61; p = 0.01). Thus, SNPs rs10892958 and rs1136141 in the HSPA8 gene represent novel genetic markers of IS.
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Affiliation(s)
- Ksenia A Kobzeva
- Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Maria O Soldatova
- Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Tatiana A Stetskaya
- Laboratory of Statistical Genetics and Bioinformatics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Vladislav O Soldatov
- Laboratory of Genome Editing for Biomedicine and Animal Health, Belgorod State National Research University, 308015 Belgorod, Russia
- Department of Pharmacology and Clinical Pharmacology, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Alexey V Deykin
- Laboratory of Genome Editing for Biomedicine and Animal Health, Belgorod State National Research University, 308015 Belgorod, Russia
- Department of Pharmacology and Clinical Pharmacology, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maxim B Freidin
- Department of Biology, School of Biological and Behavioural Sciences, Queen Mary University of London, London E1 4NS, UK
- Laboratory of Population Genetics, Research Institute of Medical Genetics, Tomsk National Research Medical Center, Russian Academy of Science, 634050 Tomsk, Russia
| | - Marina A Bykanova
- Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Mikhail I Churnosov
- Department of Medical Biological Disciplines, Belgorod State University, 308015 Belgorod, Russia
| | - Alexey V Polonikov
- Laboratory of Statistical Genetics and Bioinformatics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 305041 Kursk, Russia
| | - Olga Y Bushueva
- Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 305041 Kursk, Russia
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35
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Shilenok I, Kobzeva K, Stetskaya T, Freidin M, Soldatova M, Deykin A, Soldatov V, Churnosov M, Polonikov A, Bushueva O. SERPINE1 mRNA Binding Protein 1 Is Associated with Ischemic Stroke Risk: A Comprehensive Molecular-Genetic and Bioinformatics Analysis of SERBP1 SNPs. Int J Mol Sci 2023; 24:8716. [PMID: 37240062 PMCID: PMC10217814 DOI: 10.3390/ijms24108716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/05/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
The SERBP1 gene is a well-known regulator of SERPINE1 mRNA stability and progesterone signaling. However, the chaperone-like properties of SERBP1 have recently been discovered. The present pilot study investigated whether SERBP1 SNPs are associated with the risk and clinical manifestations of ischemic stroke (IS). DNA samples from 2060 unrelated Russian subjects (869 IS patients and 1191 healthy controls) were genotyped for 5 common SNPs-rs4655707, rs1058074, rs12561767, rs12566098, and rs6702742 SERBP1-using probe-based PCR. The association of SNP rs12566098 with an increased risk of IS (risk allele C; p = 0.001) was observed regardless of gender or physical activity level and was modified by smoking, fruit and vegetable intake, and body mass index. SNP rs1058074 (risk allele C) was associated with an increased risk of IS exclusively in women (p = 0.02), non-smokers (p = 0.003), patients with low physical activity (p = 0.04), patients with low fruit and vegetable consumption (p = 0.04), and BMI ≥25 (p = 0.007). SNPs rs1058074 (p = 0.04), rs12561767 (p = 0.01), rs12566098 (p = 0.02), rs6702742 (p = 0.036), and rs4655707 (p = 0.04) were associated with shortening of activated partial thromboplastin time. Thus, SERBP1 SNPs represent novel genetic markers of IS. Further studies are required to confirm the relationship between SERBP1 polymorphism and IS risk.
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Affiliation(s)
- Irina Shilenok
- Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
- Division of Neurology, Kursk Emergency Hospital, 305035 Kursk, Russia
| | - Ksenia Kobzeva
- Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Tatiana Stetskaya
- Laboratory of Statistical Genetics and Bioinformatics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Maxim Freidin
- Department of Biology, School of Biological and Behavioural Sciences, Queen Mary University of London, London E1 4NS, UK
- Laboratory of Population Genetics, Research Institute of Medical Genetics, Tomsk National Research Medical Center, Russian Academy of Science, 634050 Tomsk, Russia
| | - Maria Soldatova
- Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Alexey Deykin
- Laboratory of Genome Editing for Biomedicine and Animal Health, Belgorod State National Research University, 308015 Belgorod, Russia
- Department of Pharmacology and Clinical Pharmacology, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Vladislav Soldatov
- Laboratory of Genome Editing for Biomedicine and Animal Health, Belgorod State National Research University, 308015 Belgorod, Russia
- Department of Pharmacology and Clinical Pharmacology, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State University, 308015 Belgorod, Russia
| | - Alexey Polonikov
- Laboratory of Statistical Genetics and Bioinformatics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 305041 Kursk, Russia
| | - Olga Bushueva
- Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 305041 Kursk, Russia
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36
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Burns AC, Phillips AJK, Rutter MK, Saxena R, Cain SW, Lane JM. Genome-wide gene by environment study of time spent in daylight and chronotype identifies emerging genetic architecture underlying light sensitivity. Sleep 2023; 46:zsac287. [PMID: 36519390 PMCID: PMC9995784 DOI: 10.1093/sleep/zsac287] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/14/2022] [Indexed: 12/23/2022] Open
Abstract
STUDY OBJECTIVES Light is the primary stimulus for synchronizing the circadian clock in humans. There are very large interindividual differences in the sensitivity of the circadian clock to light. Little is currently known about the genetic basis for these interindividual differences. METHODS We performed a genome-wide gene-by-environment interaction study (GWIS) in 280 897 individuals from the UK Biobank cohort to identify genetic variants that moderate the effect of daytime light exposure on chronotype (individual time of day preference), acting as "light sensitivity" variants for the impact of daylight on the circadian system. RESULTS We identified a genome-wide significant SNP mapped to the ARL14EP gene (rs3847634; p < 5 × 10-8), where additional minor alleles were found to enhance the morningness effect of daytime light exposure (βGxE = -.03, SE = 0.005) and were associated with increased gene ARL14EP expression in brain and retinal tissues. Gene-property analysis showed light sensitivity loci were enriched for genes in the G protein-coupled glutamate receptor signaling pathway and genes expressed in Per2+ hypothalamic neurons. Linkage disequilibrium score regression identified Bonferroni significant genetic correlations of greater light sensitivity GWIS with later chronotype and shorter sleep duration. Greater light sensitivity was nominally genetically correlated with insomnia symptoms and risk for post-traumatic stress disorder (PTSD). CONCLUSIONS This study is the first to assess light as an important exposure in the genomics of chronotype and is a critical first step in uncovering the genetic architecture of human circadian light sensitivity and its links to sleep and mental health.
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Affiliation(s)
- Angus C Burns
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Broad Institute, Cambridge, MA, USA
| | - Andrew J K Phillips
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Martin K Rutter
- Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Broad Institute, Cambridge, MA, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Sean W Cain
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Jacqueline M Lane
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Broad Institute, Cambridge, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, 02115, USA
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An autoimmune pleiotropic SNP modulates IRF5 alternative promoter usage through ZBTB3-mediated chromatin looping. Nat Commun 2023; 14:1208. [PMID: 36869052 PMCID: PMC9984425 DOI: 10.1038/s41467-023-36897-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 02/22/2023] [Indexed: 03/05/2023] Open
Abstract
Genetic sharing is extensively observed for autoimmune diseases, but the causal variants and their underlying molecular mechanisms remain largely unknown. Through systematic investigation of autoimmune disease pleiotropic loci, we found most of these shared genetic effects are transmitted from regulatory code. We used an evidence-based strategy to functionally prioritize causal pleiotropic variants and identify their target genes. A top-ranked pleiotropic variant, rs4728142, yielded many lines of evidence as being causal. Mechanistically, the rs4728142-containing region interacts with the IRF5 alternative promoter in an allele-specific manner and orchestrates its upstream enhancer to regulate IRF5 alternative promoter usage through chromatin looping. A putative structural regulator, ZBTB3, mediates the allele-specific loop to promote IRF5-short transcript expression at the rs4728142 risk allele, resulting in IRF5 overactivation and M1 macrophage polarization. Together, our findings establish a causal mechanism between the regulatory variant and fine-scale molecular phenotype underlying the dysfunction of pleiotropic genes in human autoimmunity.
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Cheng L, Wu H, Zheng X, Zhang N, Zhao P, Wang R, Wu Q, Liu T, Yang X, Geng Q. GPGPS: a robust prognostic gene pair signature of glioma ensembling IDH mutation and 1p/19q co-deletion. Bioinformatics 2023; 39:6986965. [PMID: 36637205 PMCID: PMC9843586 DOI: 10.1093/bioinformatics/btac850] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 12/14/2022] [Indexed: 01/14/2023] Open
Abstract
MOTIVATION Many studies have shown that IDH mutation and 1p/19q co-deletion can serve as prognostic signatures of glioma. Although these genetic variations affect the expression of one or more genes, the prognostic value of gene expression related to IDH and 1p/19q status is still unclear. RESULTS We constructed an ensemble gene pair signature for the risk evaluation and survival prediction of glioma based on the prior knowledge of the IDH and 1p/19q status. First, we separately built two gene pair signatures IDH-GPS and 1p/19q-GPS and elucidated that they were useful transcriptome markers projecting from corresponding genome variations. Then, the gene pairs in these two models were assembled to develop an integrated model named Glioma Prognostic Gene Pair Signature (GPGPS), which demonstrated high area under the curves (AUCs) to predict 1-, 3- and 5-year overall survival (0.92, 0.88 and 0.80) of glioma. GPGPS was superior to the single GPSs and other existing prognostic signatures (avg AUC = 0.70, concordance index = 0.74). In conclusion, the ensemble prognostic signature with 10 gene pairs could serve as an independent predictor for risk stratification and survival prediction in glioma. This study shed light on transferring knowledge from genetic alterations to expression changes to facilitate prognostic studies. AVAILABILITY AND IMPLEMENTATION Codes are available at https://github.com/Kimxbzheng/GPGPS.git. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Lixin Cheng
- To whom correspondence should be addressed. or
| | | | - Xubin Zheng
- Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medicine College of Jinan University, Shenzhen 518020, China
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong
| | - Ning Zhang
- Guangdong Provincial Key Laboratory of Infectious Disease and Molecular Immunopathology, Shantou University Medical College, Shantou 515041, China
| | - Pengfei Zhao
- Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medicine College of Jinan University, Shenzhen 518020, China
- Department of Geriatrics, Shenzhen Clinical Research Center for Aging, Shenzhen 518020, China
| | - Ran Wang
- Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medicine College of Jinan University, Shenzhen 518020, China
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong
| | - Qiong Wu
- Hong Kong Genome Institute, Shatin, New Territories, Hong Kong
| | - Tao Liu
- International Digital Economy Academy, Shenzhen 518020, China
| | - Xiaojun Yang
- Guangdong Provincial Key Laboratory of Infectious Disease and Molecular Immunopathology, Shantou University Medical College, Shantou 515041, China
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Oliva M, Demanelis K, Lu Y, Chernoff M, Jasmine F, Ahsan H, Kibriya MG, Chen LS, Pierce BL. DNA methylation QTL mapping across diverse human tissues provides molecular links between genetic variation and complex traits. Nat Genet 2023; 55:112-122. [PMID: 36510025 PMCID: PMC10249665 DOI: 10.1038/s41588-022-01248-z] [Citation(s) in RCA: 53] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 10/26/2022] [Indexed: 12/14/2022]
Abstract
Studies of DNA methylation (DNAm) in solid human tissues are relatively scarce; tissue-specific characterization of DNAm is needed to understand its role in gene regulation and its relevance to complex traits. We generated array-based DNAm profiles for 987 human samples from the Genotype-Tissue Expression (GTEx) project, representing 9 tissue types and 424 subjects. We characterized methylome and transcriptome correlations (eQTMs), genetic regulation in cis (mQTLs and eQTLs) across tissues and e/mQTLs links to complex traits. We identified mQTLs for 286,152 CpG sites, many of which (>5%) show tissue specificity, and mQTL colocalizations with 2,254 distinct GWAS hits across 83 traits. For 91% of these loci, a candidate gene link was identified by integration of functional maps, including eQTMs, and/or eQTL colocalization, but only 33% of loci involved an eQTL and mQTL present in the same tissue type. With this DNAm-focused integrative analysis, we contribute to the understanding of molecular regulatory mechanisms in human tissues and their impact on complex traits.
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Affiliation(s)
- Meritxell Oliva
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
| | - Kathryn Demanelis
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yihao Lu
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Meytal Chernoff
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Farzana Jasmine
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Habibul Ahsan
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Institute for Population and Precision Health, University of Chicago, Chicago, IL, USA
| | - Muhammad G Kibriya
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
- Institute for Population and Precision Health, University of Chicago, Chicago, IL, USA
| | - Lin S Chen
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
| | - Brandon L Pierce
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
- Department of Human Genetics, University of Chicago, Chicago, IL, USA.
- Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA.
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Integrative Meta-Analysis of Huntington's Disease Transcriptome Landscape. Genes (Basel) 2022; 13:genes13122385. [PMID: 36553652 PMCID: PMC9777612 DOI: 10.3390/genes13122385] [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] [Received: 11/03/2022] [Revised: 11/24/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
Huntington's disease (HD) is a neurodegenerative disorder with autosomal dominant inheritance caused by glutamine expansion in the Huntingtin gene (HTT). Striatal projection neurons (SPNs) in HD are more vulnerable to cell death. The executive striatal population is directly connected with the Brodmann Area (BA9), which is mainly involved in motor functions. Analyzing the disease samples from BA9 from the SRA database provides insights related to neuron degeneration, which helps to identify a promising therapeutic strategy. Most gene expression studies examine the changes in expression and associated biological functions. In this study, we elucidate the relationship between variants and their effect on gene/downstream transcript expression. We computed gene and transcript abundance and identified variants from RNA-seq data using various pipelines. We predicted the effect of genome-wide association studies (GWAS)/novel variants on regulatory functions. We found that many variants affect the histone acetylation pattern in HD, thereby perturbing the transcription factor networks. Interestingly, some variants affect miRNA binding as well as their downstream gene expression. Tissue-specific network analysis showed that mitochondrial, neuroinflammation, vasculature, and angiogenesis-related genes are disrupted in HD. From this integrative omics analysis, we propose that abnormal neuroinflammation acts as a two-edged sword that indirectly affects the vasculature and associated energy metabolism. Rehabilitation of blood-brain barrier functionality and energy metabolism may secure the neuron from cell death.
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den Hollander AI, Mullins RF, Orozco LD, Voigt AP, Chen HH, Strunz T, Grassmann F, Haines JL, Kuiper JJW, Tumminia SJ, Allikmets R, Hageman GS, Stambolian D, Klaver CCW, Boeke JD, Chen H, Honigberg L, Katti S, Frazer KA, Weber BHF, Gorin MB. Systems genomics in age-related macular degeneration. Exp Eye Res 2022; 225:109248. [PMID: 36108770 PMCID: PMC10150562 DOI: 10.1016/j.exer.2022.109248] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 08/29/2022] [Accepted: 09/07/2022] [Indexed: 12/29/2022]
Abstract
Genomic studies in age-related macular degeneration (AMD) have identified genetic variants that account for the majority of AMD risk. An important next step is to understand the functional consequences and downstream effects of the identified AMD-associated genetic variants. Instrumental for this next step are 'omics' technologies, which enable high-throughput characterization and quantification of biological molecules, and subsequent integration of genomics with these omics datasets, a field referred to as systems genomics. Single cell sequencing studies of the retina and choroid demonstrated that the majority of candidate AMD genes identified through genomic studies are expressed in non-neuronal cells, such as the retinal pigment epithelium (RPE), glia, myeloid and choroidal cells, highlighting that many different retinal and choroidal cell types contribute to the pathogenesis of AMD. Expression quantitative trait locus (eQTL) studies in retinal tissue have identified putative causal genes by demonstrating a genetic overlap between gene regulation and AMD risk. Linking genetic data to complement measurements in the systemic circulation has aided in understanding the effect of AMD-associated genetic variants in the complement system, and supports that protein QTL (pQTL) studies in plasma or serum samples may aid in understanding the effect of genetic variants and pinpointing causal genes in AMD. A recent epigenomic study fine-mapped AMD causal variants by determing regulatory regions in RPE cells differentiated from induced pluripotent stem cells (iPSC-RPE). Another approach that is being employed to pinpoint causal AMD genes is to produce synthetic DNA assemblons representing risk and protective haplotypes, which are then delivered to cellular or animal model systems. Pinpointing causal genes and understanding disease mechanisms is crucial for the next step towards clinical translation. Clinical trials targeting proteins encoded by the AMD-associated genomic loci C3, CFB, CFI, CFH, and ARMS2/HTRA1 are currently ongoing, and a phase III clinical trial for C3 inhibition recently showed a modest reduction of lesion growth in geographic atrophy. The EYERISK consortium recently developed a genetic test for AMD that allows genotyping of common and rare variants in AMD-associated genes. Polygenic risk scores (PRS) were applied to quantify AMD genetic risk, and may aid in predicting AMD progression. In conclusion, genomic studies represent a turning point in our exploration of AMD. The results of those studies now serve as a driving force for several clinical trials. Expanding to omics and systems genomics will further decipher function and causality from the associations that have been reported, and will enable the development of therapies that will lessen the burden of AMD.
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Affiliation(s)
- Anneke I den Hollander
- Department of Ophthalmology, Radboud University Medical Center, Nijmegen, the Netherlands; AbbVie, Genomics Research Center, Cambridge, MA, USA.
| | - Robert F Mullins
- The University of Iowa Institute for Vision Research, Iowa City, IA, USA; Department of Ophthalmology and Visual Sciences, Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
| | | | - Andrew P Voigt
- The University of Iowa Institute for Vision Research, Iowa City, IA, USA; Department of Ophthalmology and Visual Sciences, Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
| | | | - Tobias Strunz
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
| | | | - Jonathan L Haines
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA; Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Jonas J W Kuiper
- Department of Ophthalmology, University Medical Center Utrecht, Utrecht, the Netherlands; Center of Translational Immunology, University Medical Center Utrecht, Utrecht, the Netherlands
| | | | - Rando Allikmets
- Department of Ophthalmology, Columbia University, NY, USA; Department of Pathology and Cell Biology, Columbia University, NY, USA
| | - Gregory S Hageman
- Sharon Eccles Steele Center for Translational Medicine, John A. Moran Eye Center, Department of Ophthalmology & Visual Sciences, University of Utah, Salt Lake City, UT, USA
| | - Dwight Stambolian
- Departments of Ophthalmology and Human Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Caroline C W Klaver
- Department of Ophthalmology, Radboud University Medical Center, Nijmegen, the Netherlands; Departments of Ophthalmology and Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands; Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland
| | - Jef D Boeke
- Institute for Systems Genetics, NYU Langone Health, NY, USA; Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, NY, USA; Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA
| | - Hao Chen
- Genentech, South San Francisco, CA, USA
| | | | | | - Kelly A Frazer
- Department of Pediatrics, University of California, San Diego, La Jolla, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, USA
| | - Bernhard H F Weber
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany; Institute of Clinical Human Genetics, University Hospital Regensburg, Regensburg, Germany
| | - Michael B Gorin
- Departments of Ophthalmology and Human Genetics, University of California, Los Angeles, CA, USA
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Gull N, Jones MR, Peng PC, Coetzee SG, Silva TC, Plummer JT, Reyes ALP, Davis BD, Chen SS, Lawrenson K, Lester J, Walsh C, Rimel BJ, Li AJ, Cass I, Berg Y, Govindavari JPB, Rutgers JKL, Berman BP, Karlan BY, Gayther SA. DNA methylation and transcriptomic features are preserved throughout disease recurrence and chemoresistance in high grade serous ovarian cancers. J Exp Clin Cancer Res 2022; 41:232. [PMID: 35883104 PMCID: PMC9327231 DOI: 10.1186/s13046-022-02440-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 07/13/2022] [Indexed: 11/18/2022] Open
Abstract
Background Little is known about the role of global DNA methylation in recurrence and chemoresistance of high grade serous ovarian cancer (HGSOC). Methods We performed whole genome bisulfite sequencing and transcriptome sequencing in 62 primary and recurrent tumors from 28 patients with stage III/IV HGSOC, of which 11 patients carried germline, pathogenic BRCA1 and/or BRCA2 mutations. Results Landscapes of genome-wide methylation (on average 24.2 million CpGs per tumor) and transcriptomes in primary and recurrent tumors showed extensive heterogeneity between patients but were highly preserved in tumors from the same patient. We identified significant differences in the burden of differentially methylated regions (DMRs) in tumors from BRCA1/2 compared to non-BRCA1/2 carriers (mean 659 DMRs and 388 DMRs in paired comparisons respectively). We identified overexpression of immune pathways in BRCA1/2 carriers compared to non-carriers, implicating an increased immune response in improved survival (P = 0.006) in these BRCA1/2 carriers. Conclusion These findings indicate methylome and gene expression programs established in the primary tumor are conserved throughout disease progression, even after extensive chemotherapy treatment, and that changes in methylation and gene expression are unlikely to serve as drivers for chemoresistance in HGSOC. Supplementary Information The online version contains supplementary material available at 10.1186/s13046-022-02440-z.
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Huang D, Feng X, Yang H, Wang J, Zhang W, Fan X, Dong X, Chen K, Yu Y, Ma X, Yi X, Li M. QTLbase2: an enhanced catalog of human quantitative trait loci on extensive molecular phenotypes. Nucleic Acids Res 2022; 51:D1122-D1128. [PMID: 36330927 PMCID: PMC9825467 DOI: 10.1093/nar/gkac1020] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 10/17/2022] [Accepted: 10/21/2022] [Indexed: 11/06/2022] Open
Abstract
Deciphering the fine-scale molecular mechanisms that shape the genetic effects at disease-associated loci from genome-wide association studies (GWAS) remains challenging. The key avenue is to identify the essential molecular phenotypes that mediate the causal variant and disease under particular biological conditions. Therefore, integrating GWAS signals with context-specific quantitative trait loci (QTLs) (such as different tissue/cell types, disease states, and perturbations) from extensive molecular phenotypes would present important strategies for full understanding of disease genetics. Via persistent curation and systematic data processing of large-scale human molecular trait QTLs (xQTLs), we updated our previous QTLbase database (now QTLbase2, http://mulinlab.org/qtlbase) to comprehensively analyze and visualize context-specific QTLs across 22 molecular phenotypes and over 95 tissue/cell types. Overall, the resource features the following major updates and novel functions: (i) 960 more genome-wide QTL summary statistics from 146 independent studies; (ii) new data for 10 previously uncompiled QTL types; (iii) variant query scope expanded to fit 195 QTL datasets based on whole-genome sequencing; (iv) supports filtering and comparison of QTLs for different biological conditions, such as stimulation types and disease states; (v) a new linkage disequilibrium viewer to facilitate variant prioritization across tissue/cell types and QTL types.
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Affiliation(s)
| | | | - Hongxi Yang
- Department of Pharmacology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Jianhua Wang
- Department of Pharmacology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Wenwen Zhang
- Department of Pharmacology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xutong Fan
- Department of Pharmacology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xiaobao Dong
- Department of Bioinformatics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Kexin Chen
- Department of Bioinformatics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Ying Yu
- Department of Pharmacology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xin Ma
- Correspondence may also be addressed to Xin Ma.
| | - Xianfu Yi
- Correspondence may also be addressed to Xianfu Yi.
| | - Mulin Jun Li
- To whom correspondence should be addressed. Tel: +86 22 83336668; Fax: +86 22 83336668;
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Andreas A, Maloy A, Nyunoya T, Zhang Y, Chandra D. The FoxP1 gene regulates lung function, production of matrix metalloproteinases and inflammatory mediators, and viability of lung epithelia. Respir Res 2022; 23:281. [PMID: 36221131 PMCID: PMC9554985 DOI: 10.1186/s12931-022-02213-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 09/27/2022] [Indexed: 12/02/2022] Open
Abstract
Background Genes involved in lung development may become dysregulated in adult life and contribute to the pathogenesis of lung diseases. Multiple genes regulate lung development, including Forkhead box protein P1-4 (FoxP1-4). Methods We examined the association between variants in the FoxP1-4 genes and lung function using data from a GWAS that included close to 400,000 individuals and 20 million SNPs. Results More than 100 variants in the FoxP1 gene, but none in the FoxP2-4 genes, are associated with lung function. The sentinel variant in the FoxP1 gene associated with FEV1 was rs1499894 (C > T), while the sentinel variant in the FoxP1 gene associated with FVC was rs35480566 (A > G). Those with the T allele instead of the C allele for rs1499894, or the G allele instead of the A allele for rs35480566 had increased FoxP1 mRNA levels in transcriptomic data, higher FEV1 and FVC, and reduced odds of being diagnosed with idiopathic pulmonary fibrosis. Further, knockdown of FoxP1 in lung epithelial cells by RNA interference led to increased mRNA levels for matrix metalloproteinases 1, 2, 3 and pro-inflammatory cytokines IL-6 & IL-8, as well as reduced cell viability after exposure to cigarette smoke—all processes implicated in the pathogenesis of COPD and IPF. Conclusions Our results suggest that the protein encoded by the FoxP1 gene may protect against the development of COPD and IPF. A causal role for FoxP1 in the pathogenesis of COPD and IPF may warrant further investigation, and FoxP1 may be a novel therapeutic target for these lung disorders. Supplementary Information The online version contains supplementary material available at 10.1186/s12931-022-02213-4.
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Affiliation(s)
- Alexis Andreas
- Department of Medicine, University of Pittsburgh, Pittsburgh, USA
| | - Abby Maloy
- Department of Medicine, University of Pittsburgh, Pittsburgh, USA
| | - Toru Nyunoya
- Department of Medicine, University of Pittsburgh, Pittsburgh, USA.,Medical Specialty Service Line, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Yingze Zhang
- Department of Medicine, University of Pittsburgh, Pittsburgh, USA
| | - Divay Chandra
- Department of Medicine, University of Pittsburgh, Pittsburgh, USA. .,Pulmonary, Allergy, and Critical Care Medicine, UPMC Montefiore Hospital-NW628, 3459 Fifth Avenue, Pittsburgh, PA, 15213, USA.
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Tang J, Huang M, He S, Zeng J, Zhu H. Uncovering the extensive trade-off between adaptive evolution and disease susceptibility. Cell Rep 2022; 40:111351. [PMID: 36103812 DOI: 10.1016/j.celrep.2022.111351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 06/13/2022] [Accepted: 08/23/2022] [Indexed: 11/03/2022] Open
Abstract
Favored mutations in the human genome may make the carriers adapt to changing environments and lifestyles but also susceptible to specific diseases. The scale and details of the trade-off between adaptive evolution and disease susceptibility are unclear because most favored mutations in different populations remain unidentified. As no statistical test can discriminate favored mutations from nearby hitchhiking neutral ones, we report a deep-learning network (DeepFavored) to integrate multiple statistical tests and divide identifying favored mutations into two subtasks. We identify favored mutations in three human populations and analyzed the correlation between favored/hitchhiking mutations and genome-wide association study (GWAS) sites. Both favored and hitchhiking neutral mutations are enriched in GWAS sites with population-specific features, and the enrichment and population specificity are prominent in genes in specific Gene Ontology (GO) terms. These provide evidence for extensive and population-specific trade-offs between adaptive evolution and disease susceptibility. The unveiled scale helps understand and investigate differences and diseases of humans.
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Affiliation(s)
- Ji Tang
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Maosheng Huang
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; School of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Sha He
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Junxiang Zeng
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Hao Zhu
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou 510515, China.
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Cheng B, Yang X, Cheng S, Li C, Zhang H, Liu L, Meng P, Jia Y, Wen Y, Zhang F. A large-scale polygenic risk score analysis identified candidate proteins associated with anxiety, depression and neuroticism. Mol Brain 2022; 15:66. [PMID: 35870967 PMCID: PMC9308259 DOI: 10.1186/s13041-022-00954-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 07/09/2022] [Indexed: 11/10/2022] Open
Abstract
Psychiatric disorders and neuroticism are closely associated with central nervous system, whose proper functioning depends on efficient protein renewal. This study aims to systematically analyze the association between anxiety / depression / neuroticism and each of the 439 proteins. 47,536 pQTLs of 439 proteins in brain, plasma and cerebrospinal fluid (CSF) were collected from recent genome-wide association study. Polygenic risk scores (PRS) of the 439 proteins were then calculated using the UK Biobank cohort, including 120,729 subjects of neuroticism, 255,354 subjects of anxiety and 316,513 subjects of depression. Pearson correlation analyses were performed to evaluate the correlation between each protein and each of the mental traits by using calculated PRSs as the instrumental variables of protein. In general population, six correlations were identified in plasma and CSF such as plasma protease C1 inhibitor (C1-INH) with neuroticism score (r = - 0.011, P = 2.56 × 10- 9) in plasma, C1-INH with neuroticism score (r = -0.010, P = 3.09 × 10- 8) in CSF, and ERBB1 with self-reported depression (r = - 0.012, P = 4.65 × 10- 5) in CSF. C1-INH and ERBB1 may induce neuroticism and depression by affecting brain function and synaptic development. Gender subgroup analyses found that BST1 was correlated with neuroticism score in male CSF (r = - 0.011, P = 1.80 × 10- 5), while CNTN2 was correlated with depression score in female brain (r = - 0.013, P = 6.43 × 10- 4). BST1 and CNTN2 may be involved in nervous system metabolism and brain health. Six common candidate proteins were associated with all three traits (P < 0.05) and were confirmed in relevant proteomic studies, such as C1-INH in plasma, CNTN2 and MSP in the brain. Our results provide novel clues for revealing the roles of proteins in the development of anxiety, depression and neuroticism.
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Affiliation(s)
- Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China
| | - Chun'e Li
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China
| | - Huijie Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 76 Yan Ta West Road, 710061, Xi'an, People's Republic of China. .,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, People's Republic of China.
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Herrera‐Luis E, Ortega VE, Ampleford EJ, Sio YY, Granell R, de Roos E, Terzikhan N, Vergara E, Hernandez‐Pacheco N, Perez‐Garcia J, Martin‐Gonzalez E, Lorenzo‐Diaz F, Hashimoto S, Brinkman P, Jorgensen AL, Yan Q, Forno E, Vijverberg SJ, Lethem R, Espuela‐Ortiz A, Gorenjak M, Eng C, González‐Pérez R, Hernández‐Pérez JM, Poza‐Guedes P, Sardón O, Corcuera P, Hawkins G, Marsico A, Bahmer T, Rabe KF, Hansen G, Kopp MV, Rios R, Cruz M, González‐Barcala F, Olaguibel JM, Plaza V, Quirce S, Canino G, Cloutier M, del Pozo V, Rodriguez‐Santana JR, Korta‐Murua J, Villar J, Potočnik U, Figueiredo C, Kabesch M, Mukhopadhyay S, Pirmohamed M, Hawcutt D, Melén E, Palmer CN, Turner S, Maitland‐van der Zee AH, von Mutius E, Celedón JC, Brusselle G, Chew FT, Bleecker E, Meyers D, Burchard EG, Pino‐Yanes M. Multi-ancestry genome-wide association study of asthma exacerbations. Pediatr Allergy Immunol 2022; 33:e13802. [PMID: 35754128 PMCID: PMC9671132 DOI: 10.1111/pai.13802] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/01/2022] [Accepted: 05/04/2022] [Indexed: 12/11/2022]
Abstract
BACKGROUND Asthma exacerbations are a serious public health concern due to high healthcare resource utilization, work/school productivity loss, impact on quality of life, and risk of mortality. The genetic basis of asthma exacerbations has been studied in several populations, but no prior study has performed a multi-ancestry meta-analysis of genome-wide association studies (meta-GWAS) for this trait. We aimed to identify common genetic loci associated with asthma exacerbations across diverse populations and to assess their functional role in regulating DNA methylation and gene expression. METHODS A meta-GWAS of asthma exacerbations in 4989 Europeans, 2181 Hispanics/Latinos, 1250 Singaporean Chinese, and 972 African Americans analyzed 9.6 million genetic variants. Suggestively associated variants (p ≤ 5 × 10-5 ) were assessed for replication in 36,477 European and 1078 non-European asthma patients. Functional effects on DNA methylation were assessed in 595 Hispanic/Latino and African American asthma patients and in publicly available databases. The effect on gene expression was evaluated in silico. RESULTS One hundred and twenty-six independent variants were suggestively associated with asthma exacerbations in the discovery phase. Two variants independently replicated: rs12091010 located at vascular cell adhesion molecule-1/exostosin like glycosyltransferase-2 (VCAM1/EXTL2) (discovery: odds ratio (ORT allele ) = 0.82, p = 9.05 × 10-6 and replication: ORT allele = 0.89, p = 5.35 × 10-3 ) and rs943126 from pantothenate kinase 1 (PANK1) (discovery: ORC allele = 0.85, p = 3.10 × 10-5 and replication: ORC allele = 0.89, p = 1.30 × 10-2 ). Both variants regulate gene expression of genes where they locate and DNA methylation levels of nearby genes in whole blood. CONCLUSIONS This multi-ancestry study revealed novel suggestive regulatory loci for asthma exacerbations located in genomic regions participating in inflammation and host defense.
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Affiliation(s)
- Esther Herrera‐Luis
- Genomics and Health GroupDepartment of Biochemistry, Microbiology, Cell Biology and GeneticsUniversidad de La Laguna (ULL)San Cristóbal de La Laguna, TenerifeSpain
| | - Victor E. Ortega
- Division of Respiratory MedicineDepartment of Internal MedicineMayo ClinicScottsdaleArizonaUSA
| | - Elizabeth J. Ampleford
- Department of Internal MedicineCenter for Precision MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Yang Yie Sio
- Department of Biological SciencesNational University of SingaporeSingapore CitySingapore
| | - Raquel Granell
- MRC Integrative Epidemiology Unit (IEU)Population Health SciencesBristol Medical SchoolUniversity of BristolBristolUK
| | - Emmely de Roos
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
- Department of Respiratory MedicineGhent University HospitalGhentBelgium
| | - Natalie Terzikhan
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
- Department of Respiratory MedicineGhent University HospitalGhentBelgium
| | - Ernesto Elorduy Vergara
- Institute of Computation BiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthMunichGermany
| | - Natalia Hernandez‐Pacheco
- Department of Clinical Sciences and EducationSödersjukhusetKarolinska InstitutetStockholmSweden
- CIBER de Enfermedades Respiratorias (CIBERES)MadridSpain
| | - Javier Perez‐Garcia
- Genomics and Health GroupDepartment of Biochemistry, Microbiology, Cell Biology and GeneticsUniversidad de La Laguna (ULL)San Cristóbal de La Laguna, TenerifeSpain
| | - Elena Martin‐Gonzalez
- Genomics and Health GroupDepartment of Biochemistry, Microbiology, Cell Biology and GeneticsUniversidad de La Laguna (ULL)San Cristóbal de La Laguna, TenerifeSpain
| | - Fabian Lorenzo‐Diaz
- Genomics and Health GroupDepartment of Biochemistry, Microbiology, Cell Biology and GeneticsUniversidad de La Laguna (ULL)San Cristóbal de La Laguna, TenerifeSpain
- Instituto Universitario de Enfermedades Tropicales y Salud Pública de Canarias (IUETSPC)Universidad de La Laguna (ULL)San Cristóbal de La Laguna, TenerifeSpain
| | - Simone Hashimoto
- Department of Respiratory MedicineAmsterdam University Medical CenterUniversity of AmsterdamAmsterdamThe Netherlands
| | - Paul Brinkman
- Department of Respiratory MedicineAmsterdam University Medical CenterUniversity of AmsterdamAmsterdamThe Netherlands
| | | | - Andrea L. Jorgensen
- Department of Health Data ScienceInstitute of Population HealthUniversity of LiverpoolLiverpoolUK
| | - Qi Yan
- Department of Obstetrics and GynecologyColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Erick Forno
- Division of Pediatric Pulmonary MedicineUPMC Children's Hospital of PittsburghUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Susanne J. Vijverberg
- Department of Respiratory MedicineAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
- Division of Pharmacoepidemiology and Clinical PharmacologyFaculty of ScienceUtrecht UniversityUtrechtThe Netherlands
- Department of Paediatric Respiratory Medicine and AllergyEmma's Children HospitalAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Ryan Lethem
- MRC Integrative Epidemiology Unit (IEU)Population Health SciencesBristol Medical SchoolUniversity of BristolBristolUK
| | - Antonio Espuela‐Ortiz
- Genomics and Health GroupDepartment of Biochemistry, Microbiology, Cell Biology and GeneticsUniversidad de La Laguna (ULL)San Cristóbal de La Laguna, TenerifeSpain
| | - Mario Gorenjak
- Center for Human Molecular Genetics and PharmacogenomicsFaculty of MedicineUniversity of MariborMariborSlovenia
| | - Celeste Eng
- Department of MedicineUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Ruperto González‐Pérez
- Allergy DepartmentHospital Universitario de CanariasSanta Cruz de TenerifeTenerifeSpain
- Severe Asthma Unit, Allergy DepartmentHospital Universitario de CanariasSanta Cruz de TenerifeTenerifeSpain
| | - José M. Hernández‐Pérez
- Pulmonary MedicineHospital Universitario de N.S de CandelariaSanta Cruz de TenerifeSpain
- Pulmonary MedicineHospital General de La PalmaLa Palma, Santa Cruz de TenerifeSpain
| | - Paloma Poza‐Guedes
- Allergy DepartmentHospital Universitario de CanariasSanta Cruz de TenerifeTenerifeSpain
- Severe Asthma Unit, Allergy DepartmentHospital Universitario de CanariasSanta Cruz de TenerifeTenerifeSpain
| | - Olaia Sardón
- Division of Pediatric Respiratory MedicineHospital Universitario DonostiaSan SebastiánSpain
- Department of PediatricsUniversity of the Basque Country (UPV/EHU)San SebastiánSpain
| | - Paula Corcuera
- Division of Pediatric Respiratory MedicineHospital Universitario DonostiaSan SebastiánSpain
| | - Greg A. Hawkins
- Department of BiochemistryWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Annalisa Marsico
- Computational Health CenterHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthMunichGermany
| | - Thomas Bahmer
- LungenClinic Grosshansdorf, PneumologyGrosshansdorfGermany
- Airway Research Center North (ARCN)Members of the Germany Center for Lung Research (DZL)GrosshansdorfGermany
| | - Klaus F. Rabe
- LungenClinic Grosshansdorf, PneumologyGrosshansdorfGermany
- Airway Research Center North (ARCN)Members of the Germany Center for Lung Research (DZL)GrosshansdorfGermany
| | - Gesine Hansen
- Department of Pediatric Pneumology, Allergology and NeonatologyHannover Medical SchoolHannoverGermany
| | - Matthias Volkmar Kopp
- Division of Pediatric Pneumology & AllergologyUniversity Medical Center Schleswig‐HolsteinLübeckGermany
- Airway Research Center North (ARCN)Members of the Germany Center for Lung Research (DZL)LübeckGermany
- Department of Paediatric Respiratory MedicineInselspitalUniversity Children's Hospital of BernUniversity of BernBernSwitzerland
| | - Raimon Rios
- Programa de Pós Graduação em Imunologia (PPGIm)Instituto de Ciências da SaúdeUniversidade Federal da Bahia (UFBA)SalvadorBrazil
| | - Maria Jesus Cruz
- CIBER de Enfermedades Respiratorias (CIBERES)MadridSpain
- Servicio de NeumologíaHospital Vall d’HebronBarcelonaSpain
| | | | - José María Olaguibel
- CIBER de Enfermedades Respiratorias (CIBERES)MadridSpain
- Servicio de AlergologíaComplejo Hospitalario de NavarraPamplonaNavarraSpain
| | - Vicente Plaza
- CIBER de Enfermedades Respiratorias (CIBERES)MadridSpain
- Departamento de Medicina RespiratoriaHospital de la Santa Creu i Sant PauInstituto de Investigación Biomédica Sant Pau (IIB Sant Pau)BarcelonaSpain
| | - Santiago Quirce
- CIBER de Enfermedades Respiratorias (CIBERES)MadridSpain
- Department of AllergyLa Paz University HospitalIdiPAZMadridSpain
| | - Glorisa Canino
- Behavioral Sciences Research InstituteUniversity of Puerto RicoSan JuanPuerto Rico
| | - Michelle Cloutier
- Department of PediatricsUniversity of ConnecticutFarmingtonConnecticutUSA
| | - Victoria del Pozo
- CIBER de Enfermedades Respiratorias (CIBERES)MadridSpain
- Immunology DepartmentInstituto de Investigación Sanitaria Hospital Universitario Fundación Jiménez DíazMadridSpain
| | | | - Javier Korta‐Murua
- Department of PediatricsUniversity of the Basque Country (UPV/EHU)San SebastiánSpain
| | - Jesús Villar
- CIBER de Enfermedades Respiratorias (CIBERES)MadridSpain
- Multidisciplinary Organ Dysfunction Evaluation Research NetworkResearch UnitHospital Universitario Dr. NegrínLas Palmas de Gran CanariaSpain
| | - Uroš Potočnik
- Laboratory for Biochemistry, Molecular Biology and GenomicsFaculty for Chemistry and Chemical EngineeringUniversity of MariborMariborSlovenia
| | - Camila Figueiredo
- Instituto de Ciências da SaúdeUniversidade Federal da BahiaSalvadorBrazil
| | - Michael Kabesch
- Department of Paediatric Pneumology and AllergyUniversity Children's Hospital Regensburg (KUNO)RegensburgGermany
| | - Somnath Mukhopadhyay
- Academic Department of PaediatricsBrighton and Sussex Medical School, Royal Alexandra Children's HospitalBrightonUK
- Population Pharmacogenetics GroupBiomedical Research InstituteNinewells Hospital and Medical SchoolUniversity of DundeeDundeeUK
| | - Munir Pirmohamed
- Department of Pharmacology and TherapeuticsInstitute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
| | - Daniel B. Hawcutt
- Department of Women's and Children's HealthUniversity of LiverpoolLiverpoolUK
- Alder Hey Children's HospitalLiverpoolUK
- NIHR Alder Hey Clinical Research FacilityAlder Hey Children's HospitalLiverpoolUK
| | - Erik Melén
- Department of Clinical Sciences and EducationSödersjukhusetKarolinska InstitutetStockholmSweden
- Sachs’ Children’s HospitalSouth General HospitalStockholmSweden
| | - Colin N. Palmer
- Population Pharmacogenetics GroupBiomedical Research InstituteNinewells Hospital and Medical SchoolUniversity of DundeeDundeeUK
| | | | - Anke H. Maitland‐van der Zee
- Department of Respiratory MedicineAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
- Division of Pharmacoepidemiology and Clinical PharmacologyFaculty of ScienceUtrecht UniversityUtrechtThe Netherlands
- Department of Paediatric Respiratory Medicine and AllergyEmma's Children HospitalAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Erika von Mutius
- Institute for Asthma and Allergy PreventionHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthMunichGermany
- Dr von Hauner Children's HospitalLudwig‐Maximilians‐UniversitätMunichGermany
- Comprehensive Pneumology Center Munich (CPC‐M)Member of the German Center for Lung ResearchMunichGermany
| | - Juan C. Celedón
- Division of Pediatric Pulmonary MedicineUPMC Children's Hospital of PittsburghUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Guy Brusselle
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
- Department of Respiratory MedicineGhent University HospitalGhentBelgium
- Department of Respiratory MedicineErasmus University Medical CenterRotterdamThe Netherlands
| | - Fook Tim Chew
- Department of Biological SciencesNational University of SingaporeSingapore CitySingapore
| | - Eugene Bleecker
- Division of Genetics, Genomics, and Precision MedicineDepartment of Internal MedicineUniversity of Arizona College of MedicineTucsonArizonaUSA
| | - Deborah Meyers
- Division of Genetics, Genomics, and Precision MedicineDepartment of Internal MedicineUniversity of Arizona College of MedicineTucsonArizonaUSA
| | - Esteban G. Burchard
- Severe Asthma Unit, Allergy DepartmentHospital Universitario de CanariasSanta Cruz de TenerifeTenerifeSpain
- Department of Bioengineering and Therapeutic SciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Maria Pino‐Yanes
- Genomics and Health GroupDepartment of Biochemistry, Microbiology, Cell Biology and GeneticsUniversidad de La Laguna (ULL)San Cristóbal de La Laguna, TenerifeSpain
- CIBER de Enfermedades Respiratorias (CIBERES)MadridSpain
- Instituto de Tecnologías Biomédicas (ITB)Universidad de La Laguna (ULL)San Cristóbal de La Laguna, TenerifeSpain
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Son JH, Park JS, Lee JU, Kim MK, Min SA, Park CS, Chang HS. A genome-wide association study on frequent exacerbation of asthma depending on smoking status. Respir Med 2022; 199:106877. [DOI: 10.1016/j.rmed.2022.106877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 04/13/2022] [Accepted: 05/08/2022] [Indexed: 10/18/2022]
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Multimorbidity landscape of schizophrenia: Insights from meta-analysis of genome wide association studies. Schizophr Res 2022; 243:214-216. [PMID: 35461043 DOI: 10.1016/j.schres.2022.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 03/25/2022] [Accepted: 03/26/2022] [Indexed: 11/20/2022]
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Xavier J, Bastos CR, Camerini L, Amaral PB, Jansen K, de Mattos Souza LD, da Silva RA, Pinheiro RT, Lara DR, Ghisleni G. Interaction between COMT Val 158 Met polymorphism and childhood trauma predicts risk for depression in men. Int J Dev Neurosci 2022; 82:385-396. [PMID: 35441426 DOI: 10.1002/jdn.10186] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 02/28/2022] [Accepted: 04/03/2022] [Indexed: 11/08/2022] Open
Abstract
Depression is a disabling illness with complex etiology. While the Catechol-O-Methyltransferase (COMT) gene, in particular the functional Val158 Met polymorphism, has been related to depression, the mechanisms underlying this gene-disease association are not completely understood. Therefore, we explore the association of COMT Val158 Met polymorphism with depression as well as its interaction with childhood trauma in 1,136 young adults from a population-based study carried out in the city of Pelotas-Brazil. The diagnosis was performed through the Mini International Neuropsychiatric Interview 5.0 (MINI 5.0), and trauma was assessed with the childhood trauma questionnaire (CTQ). Total DNA was extracted and genotyped by real-time PCR and the QTLbase dataset was queried to perform large-scale quantitative trait locus (QTL) analysis. Our research showed no direct association between the Val158 Met polymorphism and the diagnosis of depression (women: χ2=0.10, d=1, p=0.751 and men: χ2=0.003, df=1 p=0.956). However, the Met-allele of the Val158 Met polymorphism modified the effect of childhood trauma in men [OR=2.58 (95% CI:1.05-6.29); p=0.038] conferring risk for depression only on those who suffer from trauma. The conditional effect from moderation analysis showed that trauma impacts the risk of depression only in men carrying the Met-allele (Effect: 0.9490, Standard Error (SE): 0.2570; p=0.0002). QTLbase and dataset for Val158 Met polymorphism were consistent for markers that influence chromatin accessibility transcription capacity including histone methylation and acetylation. The changes caused in gene regulation by childhood trauma exposure and polymorphism may serve as evidence of the mechanism whereby the interaction increases susceptibility to this disorder in men.
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Affiliation(s)
- Janaína Xavier
- Center of Health Sciences, Post-Graduation Program of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Clarissa Ribeiro Bastos
- Center of Health Sciences, Post-Graduation Program of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Laísa Camerini
- Center of Health Sciences, Post-Graduation Program of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Paola Bajadares Amaral
- Center of Health Sciences, Post-Graduation Program of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Karen Jansen
- Center of Health Sciences, Post-Graduation Program of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Luciano Dias de Mattos Souza
- Center of Health Sciences, Post-Graduation Program of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Ricardo Azevedo da Silva
- Center of Health Sciences, Post-Graduation Program of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Ricardo Tavares Pinheiro
- Center of Health Sciences, Post-Graduation Program of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Diogo Rizzato Lara
- Department of Cellular and Molecular Biology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Gabriele Ghisleni
- Center of Health Sciences, Post-Graduation Program of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
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