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Duangjan C, Arpawong TE, Spatola BN, Curran SP. Hepatic WDR23 proteostasis mediates insulin homeostasis by regulating insulin-degrading enzyme capacity. GeroScience 2024; 46:4461-4478. [PMID: 38767782 PMCID: PMC11336002 DOI: 10.1007/s11357-024-01196-y] [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: 02/08/2024] [Accepted: 05/08/2024] [Indexed: 05/22/2024] Open
Abstract
Maintaining insulin homeostasis is critical for cellular and organismal metabolism. In the liver, insulin is degraded by the activity of the insulin-degrading enzyme (IDE). Here, we establish a hepatic regulatory axis for IDE through WDR23-proteostasis. Wdr23KO mice have increased IDE expression, reduced circulating insulin, and defective insulin responses. Genetically engineered human cell models lacking WDR23 also increase IDE expression and display dysregulated phosphorylation of insulin signaling cascade proteins, IRS-1, AKT2, MAPK, FoxO, and mTOR, similar to cells treated with insulin, which can be mitigated by chemical inhibition of IDE. Mechanistically, the cytoprotective transcription factor NRF2, a direct target of WDR23-Cul4 proteostasis, mediates the enhanced transcriptional expression of IDE when WDR23 is ablated. Moreover, an analysis of human genetic variation in WDR23 across a large naturally aging human cohort in the US Health and Retirement Study reveals a significant association of WDR23 with altered hemoglobin A1C (HbA1c) levels in older adults, supporting the use of WDR23 as a new molecular determinant of metabolic health in humans.
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Affiliation(s)
- Chatrawee Duangjan
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, 90089, USA
| | - Thalida Em Arpawong
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, 90089, USA
| | - Brett N Spatola
- Dornsife College of Letters, Arts, and Science, University of Southern California, Los Angeles, CA, 90089, USA
| | - Sean P Curran
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, 90089, USA.
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Dunn PO, Sly ND, Freeman-Gallant CR, Henschen AE, Bossu CM, Ruegg KC, Minias P, Whittingham LA. Sexually selected differences in warbler plumage are related to a putative inversion on the Z chromosome. Mol Ecol 2024:e17525. [PMID: 39268700 DOI: 10.1111/mec.17525] [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: 11/07/2023] [Accepted: 08/16/2024] [Indexed: 09/17/2024]
Abstract
Large structural variants in the genome, such as inversions, may play an important role in producing population structure and local adaptation to the environment through suppression of recombination. However, relatively few studies have linked inversions to phenotypic traits that are sexually selected and may play a role in reproductive isolation. Here, we found that geographic differences in the sexually selected plumage of a warbler, the common yellowthroat (Geothlypis trichas), are largely due to differences in the Z (sex) chromosome (males are ZZ), which contains at least one putative inversion spanning 40% (31/77 Mb) of its length. The inversions on the Z chromosome vary dramatically east and west of the Appalachian Mountains, which provides evidence of cryptic population structure within the range of the most widespread eastern subspecies (G. t. trichas). In an eastern (New York) and western (Wisconsin) population of this subspecies, female prefer different male ornaments; larger black facial masks are preferred in Wisconsin and larger yellow breasts are preferred in New York. The putative inversion also contains genes related to vision, which could influence mating preferences. Thus, structural variants on the Z chromosome are associated with geographic differences in male ornaments and female choice, which may provide a mechanism for maintaining different patterns of sexual selection in spite of gene flow between populations of the same subspecies.
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Affiliation(s)
- Peter O Dunn
- Department of Biological Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
| | - Nicholas D Sly
- Department of Biological Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
| | | | - Amberleigh E Henschen
- Department of Biological Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
| | - Christen M Bossu
- Department of Biology, Colorado State University, Ft. Collins, Colorado, USA
| | - Kristen C Ruegg
- Department of Biology, Colorado State University, Ft. Collins, Colorado, USA
| | - Piotr Minias
- Department of Biodiversity Studies and Bioeducation, Faculty of Biology and Environmental Protection, University of Łódź, Łódź, Poland
| | - Linda A Whittingham
- Department of Biological Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
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3
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Ahlström S, Reiterä P, Jokela R, Olkkola KT, Kaunisto MA, Kalso E. Influence of Clinical and Genetic Factors on Propofol Dose Requirements: A Genome-wide Association Study. Anesthesiology 2024; 141:300-312. [PMID: 38700459 DOI: 10.1097/aln.0000000000005036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
BACKGROUND Propofol is a widely used intravenous hypnotic. Dosing is based mostly on weight, with great interindividual variation in consumption. Suggested factors affecting propofol requirements include age, sex, ethnicity, anxiety, alcohol consumption, smoking, and concomitant valproate use. Genetic factors have not been widely explored. METHODS This study considered 1,000 women undergoing breast cancer surgery under propofol and remifentanil anesthesia. Depth of anesthesia was monitored with State Entropy (GE Healthcare, Finland). Propofol requirements during surgery were recorded. DNA from blood was genotyped with a genome-wide array. A multivariable linear regression model was used to assess the relevance of clinical variables and select those to be used as covariates in a genome-wide association study. Imputed genotype data were used to explore selected loci further. In silico functional annotation was used to explore possible consequences of the discovered genetic variants. Additionally, previously reported genetic associations from candidate gene studies were tested. RESULTS Body mass index, smoking status, alcohol use, remifentanil dose (ln[mg · kg-1 · min-1]), and average State Entropy during surgery remained statistically significant in the multivariable model. Two loci reached genome-wide significance (P < 5 × 10-8). The most significant associations were for single-nucleotide polymorphisms rs997989 (30 kb from ROBO3), likely affecting expression of another nearby gene, FEZ1, and rs9518419, close to NALCN (sodium leak channel); rs10512538 near KCNJ2 encoding the Kir2.1 potassium channel showed suggestive association (P = 4.7 × 10-7). None of these single-nucleotide polymorphisms are coding variants but possibly affect the regulation of nearby genes. None of the single-nucleotide polymorphisms previously reported as affecting propofol pharmacokinetics or pharmacodynamics showed association in the data. CONCLUSIONS In this first genome-wide association study exploring propofol requirements, This study discovered novel genetic associations suggesting new biologically relevant pathways for propofol and general anesthesia. The roles of the gene products of ROBO3/FEZ1, NALCN, and KCNJ2 in propofol anesthesia warrant further studies. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Sirkku Ahlström
- Department of Anesthesiology, Intensive Care and Pain Medicine, University of Helsinki and HUS Helsinki University Hospital, Helsinki, Finland
| | - Paula Reiterä
- Department of Public Health, University of Helsinki and HUS Helsinki University Hospital, Helsinki, Finland
| | - Ritva Jokela
- HUS Shared Group Services, University of Helsinki and HUS Helsinki University Hospital, Helsinki, Finland
| | - Klaus T Olkkola
- Department of Anesthesiology, Intensive Care and Pain Medicine, University of Helsinki and HUS Helsinki University Hospital, Helsinki, Finland; INDIVIDRUG Research Program, Faculty of Medicine, University of Helsinki, Finland
| | - Mari A Kaunisto
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Eija Kalso
- Department of Anesthesiology, Intensive Care and Pain Medicine, University of Helsinki and HUS Helsinki University Hospital, Helsinki, Finland; Department of Pharmacology, Faculty of Medicine, University of Helsinki, Finland; SleepWell Research Program, Faculty of Medicine, University of Helsinki, Finland
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Crone B, Boyle AP. Enhancing portability of trans-ancestral polygenic risk scores through tissue-specific functional genomic data integration. PLoS Genet 2024; 20:e1011356. [PMID: 39110742 PMCID: PMC11333000 DOI: 10.1371/journal.pgen.1011356] [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: 03/05/2024] [Revised: 08/19/2024] [Accepted: 06/27/2024] [Indexed: 08/21/2024] Open
Abstract
Portability of trans-ancestral polygenic risk scores is often confounded by differences in linkage disequilibrium and genetic architecture between ancestries. Recent literature has shown that prioritizing GWAS SNPs with functional genomic evidence over strong association signals can improve model portability. We leveraged three RegulomeDB-derived functional regulatory annotations-SURF, TURF, and TLand-to construct polygenic risk models across a set of quantitative and binary traits highlighting functional mutations tagged by trait-associated tissue annotations. Tissue-specific prioritization by TURF and TLand provide a significant improvement in model accuracy over standard polygenic risk score (PRS) models across all traits. We developed the Trans-ancestral Iterative Tissue Refinement (TITR) algorithm to construct PRS models that prioritize functional mutations across multiple trait-implicated tissues. TITR-constructed PRS models show increased predictive accuracy over single tissue prioritization. This indicates our TITR approach captures a more comprehensive view of regulatory systems across implicated tissues that contribute to variance in trait expression.
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Affiliation(s)
- Bradley Crone
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Alan P. Boyle
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
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Jonson C, Levine KS, Lake J, Hertslet L, Jones L, Patel D, Kim J, Bandres‐Ciga S, Terry N, Mata IF, Blauwendraat C, Singleton AB, Nalls MA, Yokoyama JS, Leonard HL. Assessing the lack of diversity in genetics research across neurodegenerative diseases: A systematic review of the GWAS Catalog and literature. Alzheimers Dement 2024; 20:5740-5756. [PMID: 39030740 PMCID: PMC11350004 DOI: 10.1002/alz.13873] [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: 01/19/2024] [Revised: 04/10/2024] [Accepted: 04/11/2024] [Indexed: 07/22/2024]
Abstract
The under-representation of non-European cohorts in neurodegenerative disease genome-wide association studies (GWAS) hampers precision medicine efforts. Despite the inherent genetic and phenotypic diversity in these diseases, GWAS research consistently exhibits a disproportionate emphasis on participants of European ancestry. This study reviews GWAS up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. We conducted a systematic review of GWAS results and publications up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. Rigorous article inclusion and quality assessment methods were employed. Of 123 neurodegenerative disease (NDD) GWAS reviewed, 82% predominantly featured European ancestry participants. A single European study identified over 90 risk loci, compared to a total of 50 novel loci in identified in all non-European or multi-ancestry studies. Notably, only six of the loci have been replicated. The significant under-representation of non-European ancestries in NDD GWAS hinders comprehensive genetic understanding. Prioritizing genomic diversity in future research is crucial for advancing NDD therapies and understanding. HIGHLIGHTS: Eighty-two percent of neurodegenerative genome-wide association studies (GWAS) focus on Europeans. Only 6 of 50 novel neurodegenerative disease (NDD) genetic loci have been replicated. Lack of diversity significantly hampers understanding of NDDs. Increasing diversity in NDD genetic research is urgently required. New initiatives are aiming to enhance diversity in NDD research.
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Affiliation(s)
- Caroline Jonson
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
- DataTecnica LLCWashingtonDistrict of ColumbiaUSA
- Pharmaceutical Sciences and Pharmacogenomics Graduate ProgramUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Kristin S. Levine
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
- DataTecnica LLCWashingtonDistrict of ColumbiaUSA
| | - Julie Lake
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
- Laboratory of NeurogeneticsNational Institutes on AgingNational Institutes of HealthBethesdaMarylandUSA
| | - Linnea Hertslet
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
| | - Lietsel Jones
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
- DataTecnica LLCWashingtonDistrict of ColumbiaUSA
| | - Dhairya Patel
- Integrative Neurogenomics UnitLaboratory of NeurogeneticsNational Institute on AgingNational Institutes of HealthBethesdaMarylandUSA
| | - Jeff Kim
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
- Laboratory of NeurogeneticsNational Institutes on AgingNational Institutes of HealthBethesdaMarylandUSA
| | - Sara Bandres‐Ciga
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
| | - Nancy Terry
- Division of Library ServicesOffice of Research ServicesNational Institutes of HealthBethesdaMarylandUSA
| | - Ignacio F. Mata
- Genomic Medicine Institute, Lerner Research Institute, Genomic MedicineCleveland Clinic FoundationClevelandOhioUSA
| | - Cornelis Blauwendraat
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
- Integrative Neurogenomics UnitLaboratory of NeurogeneticsNational Institute on AgingNational Institutes of HealthBethesdaMarylandUSA
| | - Andrew B. Singleton
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
- Laboratory of NeurogeneticsNational Institutes on AgingNational Institutes of HealthBethesdaMarylandUSA
| | - Mike A. Nalls
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
- DataTecnica LLCWashingtonDistrict of ColumbiaUSA
- Laboratory of NeurogeneticsNational Institutes on AgingNational Institutes of HealthBethesdaMarylandUSA
| | - Jennifer S. Yokoyama
- Pharmaceutical Sciences and Pharmacogenomics Graduate ProgramUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Hampton L. Leonard
- Center for Alzheimer's and Related DementiasNational Institutes of HealthBethesdaMarylandUSA
- DataTecnica LLCWashingtonDistrict of ColumbiaUSA
- Laboratory of NeurogeneticsNational Institutes on AgingNational Institutes of HealthBethesdaMarylandUSA
- German Center for Neurodegenerative Diseases (DZNE)TübingenGermany
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Benstock SE, Weaver K, Hettema JM, Verhulst B. Using Alternative Definitions of Controls to Increase Statistical Power in GWAS. Behav Genet 2024; 54:353-366. [PMID: 38869698 DOI: 10.1007/s10519-024-10187-w] [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: 01/12/2024] [Accepted: 05/29/2024] [Indexed: 06/14/2024]
Abstract
Genome-wide association studies (GWAS) are often underpowered due to small effect sizes of common single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the greatest statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.
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Affiliation(s)
- Sarah E Benstock
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - Katherine Weaver
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - John M Hettema
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - Brad Verhulst
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA.
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7
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Chen A, Zhao X, Wen J, Zhao X, Wang G, Zhang X, Ren X, Zhang Y, Cheng X, Yu X, Mei X, Wang H, Guo M, Jiang X, Wei G, Wang X, Jiang R, Guo X, Ning Z, Qu L. Genetic parameter estimation and molecular foundation of chicken beak shape. Poult Sci 2024; 103:103666. [PMID: 38703454 PMCID: PMC11087718 DOI: 10.1016/j.psj.2024.103666] [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: 01/08/2024] [Revised: 03/02/2024] [Accepted: 03/12/2024] [Indexed: 05/06/2024] Open
Abstract
The bird beak is mainly functioned as feeding and attacking, and its shape has extremely important significance for survival and reproduction. In chickens, since beak shape could lead to some disadvantages including pecking and waste of feed, it is important to understand the inheritance of chicken beak shape. In the present study, we firstly established 4 indicators to describe the chicken beak shapes, including upper beak length (UL), lower beak length (LL), distance between upper and lower beak tips (DB) and upper beak curvature (BC). And then, we measured the 4 beak shape indicators as well as some production traits including body weight (BW), shank length (SL), egg weight (EW), eggshell strength (ES) of a layer breed, Rhode Island Red (RIR), in order to estimate genetic parameters of chicken beak shape. The heritabilities of UL and LL were 0.41 and 0.37, and the heritabilities of DB and BC were 0.22 and 0.21, indicating that beak shape was a highly or mediumly heritable. There were significant positive genetic and phenotypic correlations among UL, LL, and DB. And UL was positively correlated with body weight (BW18) and shank length (SL18) at 18 weeks of age in genetics, and DB was positively correlated with BC in terms of genetics and phenotype. We also found that layers of chicken cages played a role on beak shape, which could be attributed to the difference of lightness in different cage layers. By a genome-wide association study (GWAS) for the chicken UL, we identified 9 significant candidate genes associated with UL in RIR. For the variants with low minor allele frequencies (MAF <0.01) and outside of high linkage disequilibrium (LD) regions, we also conducted rare variant association studies (RVA) and GWAS to find the association between genotype and phenotype. We also analyzed transcriptomic data from multiple tissues of chicken embryos and revealed that all of the 9 genes were highly expressed in beak of chicken embryos, indicating their potential function for beak development. Our results provided the genetic foundation of chicken beak shape, which could help chicken breeding on beak related traits.
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Affiliation(s)
- Anqi Chen
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaoyu Zhao
- Xingrui Agricultural Stock Breeding, Baoding 072550, Hebei Province, China
| | - Junhui Wen
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
| | - Xiurong Zhao
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Gang Wang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xinye Zhang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xufang Ren
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Yalan Zhang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xue Cheng
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaofan Yu
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaohan Mei
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Huie Wang
- Xinjiang Production and Construction Corps, Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, China
| | - Menghan Guo
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaoyu Jiang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Guozhen Wei
- Qingliu Animal Husbandry, Veterinary and Aquatic Products Center, Sanming, China
| | - Xue Wang
- VVBK Animal Medical Diagnostic Technology (Beijing) Co., Ltd, Beijing, China
| | - Runshen Jiang
- College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Xing Guo
- College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Zhonghua Ning
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Lujiang Qu
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Xinjiang Production and Construction Corps, Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, China.
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8
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Nikulkova M, Abdrabou W, Carlton JM, Idaghdour Y. Exploiting integrative metabolomics to study host-parasite interactions in Plasmodium infections. Trends Parasitol 2024; 40:313-323. [PMID: 38508901 PMCID: PMC10994734 DOI: 10.1016/j.pt.2024.02.007] [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: 11/29/2023] [Revised: 02/15/2024] [Accepted: 02/16/2024] [Indexed: 03/22/2024]
Abstract
Despite years of research, malaria remains a significant global health burden, with poor diagnostic tests and increasing antimalarial drug resistance challenging diagnosis and treatment. While 'single-omics'-based approaches have been instrumental in gaining insight into the biology and pathogenicity of the Plasmodium parasite and its interaction with the human host, a more comprehensive understanding of malaria pathogenesis can be achieved through 'multi-omics' approaches. Integrative methods, which combine metabolomics, lipidomics, transcriptomics, and genomics datasets, offer a holistic systems biology approach to studying malaria. This review highlights recent advances, future directions, and challenges involved in using integrative metabolomics approaches to interrogate the interactions between Plasmodium and the human host, paving the way towards targeted antimalaria therapeutics and control intervention methods.
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Affiliation(s)
- Maria Nikulkova
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 11101, USA; Johns Hopkins Malaria Research Institute, Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Wael Abdrabou
- Program in Biology, Division of Science and Mathematics, New York University, Abu Dhabi, United Arab Emirates
| | - Jane M Carlton
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 11101, USA; Johns Hopkins Malaria Research Institute, Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
| | - Youssef Idaghdour
- Program in Biology, Division of Science and Mathematics, New York University, Abu Dhabi, United Arab Emirates
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9
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Wang J, Li Y, Zhang J, Jiang H, Qi J, Gu Q, Sun Q, Chen L, Jiang Z, Liu A, Ying Z. Causal relationships between Sjögren's syndrome and Parkinson's disease: A Mendelian randomization study. Int J Rheum Dis 2024; 27:e15128. [PMID: 38509724 DOI: 10.1111/1756-185x.15128] [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: 11/02/2023] [Revised: 02/17/2024] [Accepted: 03/05/2024] [Indexed: 03/22/2024]
Abstract
BACKGROUND Epidemiological and observational studies have indicated an association between Sjögren's syndrome (SS) and Parkinson's disease (PD). However, consistent conclusions have not been reached due to various limitations. In order to determine whether SS and PD are causally related, we conducted a Mendelian randomization study (MR) with two samples. METHODS Data for SS derived from the FinnGen consortium's R9 release (2495 cases and 365 533 controls). Moreover, data for PD were acquired from the publicly available GWAS of European ancestry, which involved 33 674 cases and 449 056 controls. The inverse variance weighted, along with four other effective methodologies, were employed to comprehensively infer the causal relationships between SS and PD. To assess the estimation's robustness, a number of sensitivity studies were performed. To determine the probability of reverse causality, we performed a reverse MR analysis. RESULTS There was no evidence of a significant causal effect of SS on PD risks based on the MR [odds ratio (OR) = 1.03; 95% confidence interval (CI) = 0.95-1.11; p = .45]. Similarly, no evidence supported the causal effects of PD on SS (OR = 0.92; 95% CI = 0.81-1.04; p = .20). These findings held up under rigorous sensitivity analysis. CONCLUSIONS MR bidirectional analysis did not reveal any cause-and-effect relationship between SS and PD, or vice versa. Further study of the mechanisms that may underlie the probable causal association between SS and PD is needed.
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Affiliation(s)
- Jing Wang
- The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Yixuan Li
- The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Ju Zhang
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Huan Jiang
- The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Jiaping Qi
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Qinchen Gu
- The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Qiong Sun
- The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Lin Chen
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Zhaoyu Jiang
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Aihui Liu
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Zhenhua Ying
- The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
- Center for General Practice Medicine, Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
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Skytte HN, Roland MCP, Christensen JJ, Holven KB, Lekva T, Gunnes N, Michelsen TM. Maternal metabolic profiling across body mass index groups: An exploratory longitudinal study. Acta Obstet Gynecol Scand 2024; 103:540-550. [PMID: 38083835 PMCID: PMC10867396 DOI: 10.1111/aogs.14750] [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: 03/29/2023] [Revised: 11/20/2023] [Accepted: 11/24/2023] [Indexed: 02/16/2024]
Abstract
INTRODUCTION Increased BMI has been identified as a risk factor for most pregnancy complications, but the underlying metabolic factors mediating the detrimental effects of BMI are largely unknown. We aimed to compare metabolic profiles in overweight/obese women (body mass index [BMI] ≥ 25 kg/m2 ) and normal weight/underweight women (BMI < 25 kg/m2 ) across gestation. We also explored how gestational weight gain (GWG) affected maternal metabolic profiles. MATERIAL AND METHODS Exploratory nested case-control study based on a prospective longitudinal cohort of women who were healthy prior to pregnancy and gave birth at Oslo University Hospital from 2002 to 2008. The sample consisted of 48 women who were overweight/obese and 59 normal-weight/underweight women. Plasma samples from four time points in pregnancy (weeks 14-16, 22-24, 30-32 and 36-38) were analyzed by nuclear magnetic resonance spectroscopy and 91 metabolites were measured. Linear regression models were fitted for each of the metabolites at each time point. RESULTS Overweight or obese women had higher levels of lipids in very-low-density lipoprotein (VLDL), total triglycerides, triglycerides in VLDL, total fatty acids, monounsaturated fatty acids, saturated fatty acids, leucine, valine, and total branched-chain amino acids in pregnancy weeks 14-16 compared to underweight and normal-weight women. Docosahexaenoic acid and degree of unsaturation were significantly lower in overweight/obese women in pregnancy weeks 36-38. In addition, overweight or obese women had higher particle concentration of XXL-VLDL and glycoprotein acetyls (GlycA) at weeks 14-16 and 30-32. GWG did not seem to affect the metabolic profile, regardless of BMI group when BMI was treated as a dichotomous variable, ≥25 kg/m2 (yes/no). CONCLUSIONS Overweight or obese women had smaller pregnancy-related metabolic alterations than normal-weight/underweight women. There was a trend toward higher triglyceride and VLDL particle concentration in overweight/obese women. As this was a hypothesis-generating study, the similarities with late-onset pre-eclampsia warrant further investigation. The unfavorable development of fatty acid composition in overweight/obese women, with possible implication for the offspring, should also be studied further in the future.
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Affiliation(s)
- Hege Nyhus Skytte
- Norwegian Research Center for Women's HealthOslo University HospitalOsloNorway
- Faculty of MedicineUniversity of OsloOsloNorway
| | | | | | - Kirsten Bjørklund Holven
- Department of NutritionUniversity of OsloOsloNorway
- Norwegian National Advisory Unit on Familial HypercholesterolemiaOslo University HospitalOsloNorway
| | - Tove Lekva
- Research Institute of Internal MedicineOslo University HospitalOsloNorway
| | - Nina Gunnes
- Norwegian Research Center for Women's HealthOslo University HospitalOsloNorway
| | - Trond Melbye Michelsen
- Faculty of MedicineUniversity of OsloOsloNorway
- Division of Obstetrics and GynecologyOslo University HospitalOsloNorway
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Petrykey K, Lippé S, Sultan S, Robaey P, Drouin S, Affret-Bertout L, Beaulieu P, St-Onge P, Baedke JL, Yasui Y, Hudson MM, Laverdière C, Sinnett D, Krajinovic M. Genetic Factors and Long-term Treatment-Related Neurocognitive Deficits, Anxiety, and Depression in Childhood Leukemia Survivors: An Exome-Wide Association Study. Cancer Epidemiol Biomarkers Prev 2024; 33:234-243. [PMID: 38051303 PMCID: PMC10903523 DOI: 10.1158/1055-9965.epi-23-0634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 09/23/2023] [Accepted: 11/30/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND An increased risk of neurocognitive deficits, anxiety, and depression has been reported in childhood cancer survivors. METHODS We analyzed associations of neurocognitive deficits, as well as anxiety and depression, with common and rare genetic variants derived from whole-exome sequencing data of acute lymphoblastic leukemia (ALL) survivors from the PETALE cohort. In addition, significant associations were assessed using stratified and multivariable analyses. Next, top-ranking common associations were analyzed in an independent SJLIFE replication cohort of ALL survivors. RESULTS Significant associations were identified in the entire discovery cohort (N = 229) between the AK8 gene and changes in neurocognitive function, whereas PTPRZ1, MUC16, TNRC6C-AS1 were associated with anxiety. Following stratification according to sex, the ZNF382 gene was linked to a neurocognitive deficit in males, whereas APOL2 and C6orf165 were associated with anxiety and EXO5 with depression. Following stratification according to prognostic risk groups, the modulatory effect of rare variants on depression was additionally found in the CYP2W1 and PCMTD1 genes. In the replication SJLIFE cohort (N = 688), the male-specific association in the ZNF382 gene was not significant; however, a P value<0.05 was observed when the entire SJLIFE cohort was analyzed. ZNF382 was significant in males in the combined cohorts as shown by meta-analyses as well as the depression-associated gene EXO5. CONCLUSIONS Further research is needed to confirm whether the current findings, along with other known risk factors, may be valuable in identifying patients at increased risk of these long-term complications. IMPACT Our results suggest that specific genes may be related to increased neuropsychological consequences.
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Affiliation(s)
- Kateryna Petrykey
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Pharmacology and Physiology, Université de Montréal (Quebec), Canada
| | - Sarah Lippé
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Psychology, Université de Montréal (Quebec), Canada
| | - Serge Sultan
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Psychology, Université de Montréal (Quebec), Canada
| | - Philippe Robaey
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Children’s Hospital of Eastern Ontario, Ottawa (Ontario), Canada
- Department of Psychiatry, Université de Montréal (Quebec), Canada
- Department of Psychiatry, University of Ottawa (Ontario), Canada
| | - Simon Drouin
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
| | | | - Patrick Beaulieu
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
| | - Pascal St-Onge
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
| | - Jessica L. Baedke
- Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, Memphis (TN), USA
| | - Yutaka Yasui
- Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, Memphis (TN), USA
| | - Melissa M. Hudson
- Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, Memphis (TN), USA
- Department of Oncology, St. Jude Children’s Research Hospital, Memphis (TN), USA
| | - Caroline Laverdière
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Pediatrics, Université de Montréal (Quebec), Canada
| | - Daniel Sinnett
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Pediatrics, Université de Montréal (Quebec), Canada
| | - Maja Krajinovic
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Pharmacology and Physiology, Université de Montréal (Quebec), Canada
- Department of Pediatrics, Université de Montréal (Quebec), Canada
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12
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Sun J, Wang M, Kan Z. Causal relationship between gut microbiota and polycystic ovary syndrome: a literature review and Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1280983. [PMID: 38362275 PMCID: PMC10867277 DOI: 10.3389/fendo.2024.1280983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 01/12/2024] [Indexed: 02/17/2024] Open
Abstract
Introduction Numerous studies have suggested an association between gut microbiota and polycystic ovarian syndrome (PCOS). However, the causal relationship between these two factors remains unclear. Methods A review of observational studies was conducted to compare changes in gut microbiota between PCOS patients and controls. The analysis focused on four levels of classification, namely, phylum, family, genus, and species/genus subgroups. To further investigate the causal relationship, Mendelian randomization (MR) was employed using genome-wide association study (GWAS) data on gut microbiota from the MiBioGen consortium, as well as GWAS data from a large meta-analysis of PCOS. Additionally, a reverse MR was performed, and the results were verified through sensitivity analyses. Results The present review included 18 observational studies that met the inclusion and exclusion criteria. The abundance of 64 gut microbiota taxa significantly differed between PCOS patients and controls. Using the MR method, eight bacteria were identified as causally associated with PCOS. The protective effects of the genus Sellimonas on PCOS remained significant after applying Bonferroni correction. No significant heterogeneity or horizontal pleiotropy was found in the instrumental variables (IVs). Reverse MR analyses did not reveal a significant causal effect of PCOS on gut microbiota. Conclusion The differences in gut microbiota between PCOS patients and controls vary across observational studies. However, MR analyses identified specific gut microbiota taxa that are causally related to PCOS. Future studies should investigate the gut microbiota that showed significant results in the MR analyses, as well as the underlying mechanisms of this causal relationship and its potential clinical significance.
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Affiliation(s)
- Junwei Sun
- Department of Neurosurgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
- Department of Neurosurgery, Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Mingyu Wang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Zhisheng Kan
- Department of Neurosurgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
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Benstock SE, Weaver K, Hettema J, Verhulst B. Using Alternative Definitions of Controls to Increase Statistical Power in GWAS. RESEARCH SQUARE 2024:rs.3.rs-3858178. [PMID: 38352402 PMCID: PMC10862954 DOI: 10.21203/rs.3.rs-3858178/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Genome-wide association studies (GWAS) are underpowered due to small effect sizes of single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the most statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.
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Jonson C, Levine KS, Lake J, Hertslet L, Jones L, Patel D, Kim J, Bandres-Ciga S, Terry N, Mata IF, Blauwendraat C, Singleton AB, Nalls MA, Yokoyama JS, Leonard HL. Assessing the lack of diversity in genetics research across neurodegenerative diseases: a systematic review of the GWAS Catalog and literature. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.08.24301007. [PMID: 38260595 PMCID: PMC10802650 DOI: 10.1101/2024.01.08.24301007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Importance The under-representation of participants with non-European ancestry in genome-wide association studies (GWAS) is a critical issue that has significant implications, including hindering the progress of precision medicine initiatives. This issue is particularly significant in the context of neurodegenerative diseases (NDDs), where current therapeutic approaches have shown limited success. Addressing this under-representation is crucial to harnessing the full potential of genomic medicine in underserved communities and improving outcomes for NDD patients. Objective Our primary objective was to assess the representation of non-European ancestry participants in genetic discovery efforts related to NDDs. We aimed to quantify the extent of inclusion of diverse ancestry groups in NDD studies and determine the number of associated loci identified in more inclusive studies. Specifically, we sought to highlight the disparities in research efforts and outcomes between studies predominantly involving European ancestry participants and those deliberately targeting non-European or multi-ancestry populations across NDDs. Evidence Review We conducted a systematic review utilizing existing GWAS results and publications to assess the inclusion of diverse ancestry groups in neurodegeneration and neurogenetics studies. Our search encompassed studies published up to the end of 2022, with a focus on identifying research that deliberately included non-European or multi-ancestry cohorts. We employed rigorous methods for the inclusion of identified articles and quality assessment. Findings Our review identified a total of 123 NDD GWAS. Strikingly, 82% of these studies predominantly featured participants of European ancestry. Endeavors specifically targeting non-European or multi-ancestry populations across NDDs identified only 52 risk loci. This contrasts with predominantly European studies, which reported over 90 risk loci for a single disease. Encouragingly, over 65% of these discoveries occurred in 2020 or later, indicating a recent increase in studies deliberately including non-European cohorts. Conclusions and relevance Our findings underscore the pressing need for increased diversity in neurodegenerative research. The significant under-representation of non-European ancestry participants in NDD GWAS limits our understanding of the genetic underpinnings of these diseases. To advance the field of neurodegenerative research and develop more effective therapies, it is imperative that future investigations prioritize and harness the genomic diversity present within and across global populations.
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Affiliation(s)
- Caroline Jonson
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- DataTecnica LLC, Washington, DC USA 20037
- Pharmaceutical Sciences and Pharmacogenomics, UCSF, San Francisco, CA, USA
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA USA
| | - Kristin S. Levine
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- DataTecnica LLC, Washington, DC USA 20037
| | - Julie Lake
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- Laboratory of Neurogenetics, National Institutes on Aging, National Institutes of Health, Bethesda, MD USA 20892
| | - Linnea Hertslet
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
| | - Lietsel Jones
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- DataTecnica LLC, Washington, DC USA 20037
| | - Dhairya Patel
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jeff Kim
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- Laboratory of Neurogenetics, National Institutes on Aging, National Institutes of Health, Bethesda, MD USA 20892
| | - Sara Bandres-Ciga
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
| | - Nancy Terry
- Division of Library Services, Office of Research Services, National Institutes of Health, Bethesda, Maryland, U.S.A
| | - Ignacio F. Mata
- Genomic Medicine Institute, Lerner Research Institute, Genomic Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Cornelis Blauwendraat
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Andrew B. Singleton
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- Laboratory of Neurogenetics, National Institutes on Aging, National Institutes of Health, Bethesda, MD USA 20892
| | - Mike A. Nalls
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- DataTecnica LLC, Washington, DC USA 20037
- Laboratory of Neurogenetics, National Institutes on Aging, National Institutes of Health, Bethesda, MD USA 20892
| | - Jennifer S. Yokoyama
- Pharmaceutical Sciences and Pharmacogenomics, UCSF, San Francisco, CA, USA
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA USA
| | - Hampton L. Leonard
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- DataTecnica LLC, Washington, DC USA 20037
- Laboratory of Neurogenetics, National Institutes on Aging, National Institutes of Health, Bethesda, MD USA 20892
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
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Chatterjee S, Sanjeev BS. Over-representation analysis of angiogenic factors in immunosuppressive mechanisms in neoplasms and neurological conditions during COVID-19. Microb Pathog 2023; 185:106386. [PMID: 37865274 DOI: 10.1016/j.micpath.2023.106386] [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: 07/10/2023] [Revised: 09/27/2023] [Accepted: 10/09/2023] [Indexed: 10/23/2023]
Abstract
BACKGROUND Recent studies emphasized the necessity to identify key (human) biological processes and pathways targeted by the Coronaviridae family of viruses, especially Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronavirus Disease (COVID-19) caused up to 33-55 % death rates in COVID-19 patients with malignant neoplasms and Alzheimer's disease. Given this scenario, we identified biological processes and pathways involved in various diseases which are most likely affected by COVID-19. METHODS The COVID-19 DisGeNET data set (v4.0) contains the associations between various diseases and human genes known to interact with viruses from Coronaviridae family and were obtained from the IntAct Coronavirus data set annotated with DisGeNET data. We constructed the disease-gene network to identify genes that are involved in various comorbid diseased states. Communities from the disease-gene network were identified using Louvain method and functional enrichment through over-representation analysis methodology was used to discover significant biological processes and pathways shared between COVID-19 and other diseases. RESULT The COVID-19 DisGeNET data set (v4.0) comprised of 828 human genes and 10,473 diseases (including various phenotypes) that together constituted nodes in the disease-gene network. Each of the 70,210 edges connects a human gene with an associated disease. The top 10 genes linked to most number of diseases were VEGFA, BCL2, CTNNB1, ALB, COX2, AGT, HLA-A, HMOX1, FGF2 and COMT. The most vulnerable group of patients thus discovered had comorbid conditions such as carcinomas, malignant neoplasms and Alzheimer's disease. Finally, we identified 15 potentially useful biological processes and pathways for improved therapies. Vascular endothelial growth factor (VEGF) is the key mediator of angiogenesis in cancer. It is widely distributed in the brain and plays a crucial role in brain inflammation regulating the level of angiopoietins. With a degree of 1899, VEGFA was associated with maximum number of diseases in the disease-gene network. Previous studies have indicated that increased levels of VEGFA in the blood results in dyspnea, Pulmonary Edema (PE), Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). In case of COVID-19 patients with neoplasms and other neurological symptoms, our results indicate VEGFA as a therapeutic target for inflammation suppression. As VEGFs are known to disproportionately affect cancer patients, improving endothelial permeability and vasodilation with anti-VEGF therapy could lead to suppression of inflammation and also improve oxygenation. As an outcome of our study, we make case for clinical investigations towards anti-VEGF therapies for such comorbid conditions affected by COVID-19 for better therapeutic outcomes.
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Affiliation(s)
- S Chatterjee
- Department of Applied Sciences, Indian Institute of Information Technology, Allahabad, India.
| | - B S Sanjeev
- Department of Applied Sciences, Indian Institute of Information Technology, Allahabad, India.
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16
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Shapira G, Volkov H, Fabian I, Mohr DW, Bettinotti M, Shomron N, Avery RK, Arav-Boger R. Genomic Markers Associated with Cytomegalovirus DNAemia in Kidney Transplant Recipients. Viruses 2023; 15:2227. [PMID: 38005904 PMCID: PMC10674338 DOI: 10.3390/v15112227] [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: 10/05/2023] [Revised: 10/29/2023] [Accepted: 11/01/2023] [Indexed: 11/26/2023] Open
Abstract
Human cytomegalovirus (CMV) is a major pathogen after solid organ transplantation, leading to high morbidity and mortality. Transplantation from a CMV-seropositive donor to a CMV-seronegative recipient (D+/R-) is associated with high risk of CMV disease. However, that risk is not uniform, suggesting a role for host factors in immune control of CMV. To identify host genetic factors that control CMV DNAemia post transplantation, we performed a whole-exome association study in two cohorts of D+/R- kidney transplant recipients. Quantitative CMV DNA was measured for at least one year following transplantation. Several CMV-protective single-nucleotide polymorphisms (SNPs) were identified in the first cohort (72 patients) but were not reproducible in the second cohort (126 patients). A meta-analysis of both cohorts revealed several SNPs that were significantly associated with protection from CMV DNAemia. The copy number variation of several genes was significantly different between recipients with and without CMV DNAemia. Amongst patients with CMV DNAemia in the second cohort, several variants of interest (p < 5 × 10-5), the most common of which was NLRC5, were associated with peak viral load. We provide new predictive genetic markers for protection of CMV DNAemia. These markers should be validated in larger cohorts.
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Affiliation(s)
- Guy Shapira
- Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel; (G.S.)
- Edmond J. Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv 69978, Israel
| | - Hadas Volkov
- Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel; (G.S.)
- Edmond J. Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv 69978, Israel
| | - Itai Fabian
- Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel; (G.S.)
| | - David W. Mohr
- Johns Hopkins Genetic Resources Core Facility, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Maria Bettinotti
- Immunogenetics Laboratory, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA;
| | - Noam Shomron
- Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel; (G.S.)
- Edmond J. Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv 69978, Israel
| | - Robin K. Avery
- Department of Medicine, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA;
| | - Ravit Arav-Boger
- Department of Pediatrics, Division of Infectious Diseases, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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Mogahadam HK, Røsaeg MV. From viral load to survival: Unveiling new genetic links for resistance against PMCV in Atlantic Salmon (Salmo salar). JOURNAL OF FISH DISEASES 2023; 46:1285-1294. [PMID: 37579006 DOI: 10.1111/jfd.13847] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 07/26/2023] [Accepted: 07/31/2023] [Indexed: 08/16/2023]
Abstract
The infectious agent piscine myocarditis virus (PMCV) causes cardiomyopathy syndrome (CMS) and is responsible for substantial mortality and economic losses in the Atlantic salmon (Salmo salar) farming industry. Previous research has demonstrated that breeding for resistance against PMCV is an effective approach to mitigate the disease's impact. In this study, a new quantitative trait locus (QTL) is described on chromosome 23, together with previously described QTLs on chromosomes 12 and 27. The findings are based on two genome-wide association studies conducted on two different year-classes of Atlantic salmon of the Rauma strain. In this study, we utilized data from an experimental challenge trial with the viral load as the phenotype and a field outbreak of CMS with survival data as the phenotype. The estimated SNP-based heritability was 0.55 and 0.44 in the two studies, respectively. In the infection trial, the top associated SNP on chromosome 23 accounted for approximately 46% of the genetic and 25.53% of the phenotypic variations in the viral load. In the field outbreak, we identified a QTL on the same genomic region of chromosome 23. The most significantly associated marker on this chromosome explained 13.57% and 5.97% of the genetic and phenotypic variations. The QTL on chromosome 23 is in proximity to delta-5 fatty acyl desaturase and fatty acid desaturase 2 genes, both of which play a role in the production of polyunsaturated fatty acids. This proximity is particularly interesting as it offers valuable insights into enhancing our understanding of resistance against PMCV.
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Wang X, Hivert V, Groot S, Wang Y, Yengo L, McGrath JJ, Kemper KE, Visscher PM, Wray NR, Revez JA. Cross-ancestry analyses identify new genetic loci associated with 25-hydroxyvitamin D. PLoS Genet 2023; 19:e1011033. [PMID: 37963177 PMCID: PMC10684098 DOI: 10.1371/journal.pgen.1011033] [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: 01/17/2023] [Revised: 11/28/2023] [Accepted: 10/24/2023] [Indexed: 11/16/2023] Open
Abstract
Vitamin D status-a complex trait influenced by environmental and genetic factors-is tightly associated with skin colour and ancestry. Yet very few studies have investigated the genetic underpinnings of vitamin D levels across diverse ancestries, and the ones that have, relied on small sample sizes, resulting in inconclusive results. Here, we conduct genome-wide association studies (GWAS) of 25 hydroxyvitamin D (25OHD)-the main circulating form of vitamin D-in 442,435 individuals from four broad genetically-determined ancestry groups represented in the UK Biobank: European (N = 421,867), South Asian (N = 9,983), African (N = 8,306) and East Asian (N = 2,279). We identify a new genetic determinant of 25OHD (rs146759773) in individuals of African ancestry, which was not detected in previous analysis of much larger European cohorts due to low minor allele frequency. We show genome-wide significant evidence of dominance effects in 25OHD that protect against vitamin D deficiency. Given that key events in the synthesis of 25OHD occur in the skin and are affected by pigmentation levels, we conduct GWAS of 25OHD stratified by skin colour and identify new associations. Lastly, we test the interaction between skin colour and variants associated with variance in 25OHD levels and identify two loci (rs10832254 and rs1352846) whose association with 25OHD differs in individuals of distinct complexions. Collectively, our results provide new insights into the complex relationship between 25OHD and skin colour and highlight the importance of diversity in genomic studies. Despite the much larger rates of vitamin D deficiency that we and others report for ancestry groups with dark skin (e.g., South Asian), our study highlights the importance of considering ancestral background and/or skin colour when assessing the implications of low vitamin D.
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Affiliation(s)
- Xiaotong Wang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Valentin Hivert
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Shiane Groot
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Ying Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
| | - Loic Yengo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - John J. McGrath
- National Centre for Register-Based Research, Aarhus University, Aarhus V, Denmark
- Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Brisbane, Queensland, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Kathryn E. Kemper
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Peter M. Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Joana A. Revez
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
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Furman M, Thomas KW, George BJ. Separating Measurement Error and Signal in Environmental Data: Use of Replicates to Address Uncertainty. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:15356-15365. [PMID: 37796641 PMCID: PMC10733784 DOI: 10.1021/acs.est.3c02231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Abstract
Measurement uncertainty has long been a concern in the characterizing and interpreting environmental and toxicological measurements. We compared statistical analysis approaches when there are replicates: a Naı̈ve approach that omits replicates, a Hybrid approach that inappropriately treats replicates as independent samples, and a Measurement Error Model (MEM) approach in a random effects analysis of variance (ANOVA) model that appropriately incorporates replicates. A simulation study assessed the effects of sample size and levels of replication, signal variance, and measurement error on estimates from the three statistical approaches. MEM results were superior overall with confidence intervals for the observed mean narrower on average than those from the Naı̈ve approach, giving improved characterization. The MEM approach also featured an unparalleled advantage in estimating signal and measurement error variance separately, directly addressing measurement uncertainty. These MEM estimates were approximately unbiased on average with more replication and larger sample sizes. Case studies illustrated analyzing normally distributed arsenic and log-normally distributed chromium concentrations in tap water and calculating MEM confidence intervals for the true, latent signal mean and latent signal geometric mean (i.e., with measurement error removed). MEM estimates are valuable for study planning; we used simulation to compare various sample sizes and levels of replication.
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Affiliation(s)
- Marschall Furman
- Oak Ridge Institute for Science and Education (ORISE)
Research Participant at U.S. EPA, Office of Research and Development, Center for
Public Health and Environmental Assessment, Research Triangle Park, North Carolina
27711, United States
| | - Kent W. Thomas
- Center for Public Health and Environmental Assessment,
Office of Research and Development, U.S. EPA, Research Triangle Park, North Carolina
27711, United States
| | - Barbara Jane George
- Center for Public Health and Environmental Assessment,
Office of Research and Development, U.S. EPA, Research Triangle Park, North Carolina
27711, United States
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20
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Eldjarn GH, Ferkingstad E, Lund SH, Helgason H, Magnusson OT, Gunnarsdottir K, Olafsdottir TA, Halldorsson BV, Olason PI, Zink F, Gudjonsson SA, Sveinbjornsson G, Magnusson MI, Helgason A, Oddsson A, Halldorsson GH, Magnusson MK, Saevarsdottir S, Eiriksdottir T, Masson G, Stefansson H, Jonsdottir I, Holm H, Rafnar T, Melsted P, Saemundsdottir J, Norddahl GL, Thorleifsson G, Ulfarsson MO, Gudbjartsson DF, Thorsteinsdottir U, Sulem P, Stefansson K. Large-scale plasma proteomics comparisons through genetics and disease associations. Nature 2023; 622:348-358. [PMID: 37794188 PMCID: PMC10567571 DOI: 10.1038/s41586-023-06563-x] [Citation(s) in RCA: 54] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 08/22/2023] [Indexed: 10/06/2023]
Abstract
High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people2, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.
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Affiliation(s)
| | | | - Sigrun H Lund
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Hannes Helgason
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Bjarni V Halldorsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Technology, Reykjavik University, Reykjavik, Iceland
| | | | | | | | | | | | - Agnar Helgason
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, Iceland
| | | | | | - Magnus K Magnusson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Saedis Saevarsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Ingileif Jonsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen, Reykjavik, Iceland
| | | | - Pall Melsted
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Magnus O Ulfarsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE Genetics/Amgen, Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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21
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Al-Aamri A, Kamarul Azman S, Daw Elbait G, Alsafar H, Henschel A. Critical assessment of on-premise approaches to scalable genome analysis. BMC Bioinformatics 2023; 24:354. [PMID: 37735350 PMCID: PMC10512525 DOI: 10.1186/s12859-023-05470-2] [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: 05/27/2023] [Accepted: 09/08/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND Plummeting DNA sequencing cost in recent years has enabled genome sequencing projects to scale up by several orders of magnitude, which is transforming genomics into a highly data-intensive field of research. This development provides the much needed statistical power required for genotype-phenotype predictions in complex diseases. METHODS In order to efficiently leverage the wealth of information, we here assessed several genomic data science tools. The rationale to focus on on-premise installations is to cope with situations where data confidentiality and compliance regulations etc. rule out cloud based solutions. We established a comprehensive qualitative and quantitative comparison between BCFtools, SnpSift, Hail, GEMINI, and OpenCGA. The tools were compared in terms of data storage technology, query speed, scalability, annotation, data manipulation, visualization, data output representation, and availability. RESULTS Tools that leverage sophisticated data structures are noted as the most suitable for large-scale projects in varying degrees of scalability in comparison to flat-file manipulation (e.g., BCFtools, and SnpSift). Remarkably, for small to mid-size projects, even lightweight relational database. CONCLUSION The assessment criteria provide insights into the typical questions posed in scalable genomics and serve as guidance for the development of scalable computational infrastructure in genomics.
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Affiliation(s)
- Amira Al-Aamri
- Department of Electrical Engineering and Computer Science, College of Engineering, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates
| | - Syafiq Kamarul Azman
- Department of Electrical Engineering and Computer Science, College of Engineering, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates
| | - Gihan Daw Elbait
- Department of Biology, College of Arts and Sciences, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates
- Center for Biotechnology (BTC), Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates
| | - Habiba Alsafar
- Center for Biotechnology (BTC), Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates
- Department of Biomedical Engineering, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates
| | - Andreas Henschel
- Department of Electrical Engineering and Computer Science, College of Engineering, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates.
- Center for Biotechnology (BTC), Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates.
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22
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Pedersen EM, Agerbo E, Plana-Ripoll O, Steinbach J, Krebs MD, Hougaard DM, Werge T, Nordentoft M, Børglum AD, Musliner KL, Ganna A, Schork AJ, Mortensen PB, McGrath JJ, Privé F, Vilhjálmsson BJ. ADuLT: An efficient and robust time-to-event GWAS. Nat Commun 2023; 14:5553. [PMID: 37689771 PMCID: PMC10492844 DOI: 10.1038/s41467-023-41210-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 08/28/2023] [Indexed: 09/11/2023] Open
Abstract
Proportional hazards models have been proposed to analyse time-to-event phenotypes in genome-wide association studies (GWAS). However, little is known about the ability of proportional hazards models to identify genetic associations under different generative models and when ascertainment is present. Here we propose the age-dependent liability threshold (ADuLT) model as an alternative to a Cox regression based GWAS, here represented by SPACox. We compare ADuLT, SPACox, and standard case-control GWAS in simulations under two generative models and with varying degrees of ascertainment as well as in the iPSYCH cohort. We find Cox regression GWAS to be underpowered when cases are strongly ascertained (cases are oversampled by a factor 5), regardless of the generative model used. ADuLT is robust to ascertainment in all simulated scenarios. Then, we analyse four psychiatric disorders in iPSYCH, ADHD, Autism, Depression, and Schizophrenia, with a strong case-ascertainment. Across these psychiatric disorders, ADuLT identifies 20 independent genome-wide significant associations, case-control GWAS finds 17, and SPACox finds 8, which is consistent with simulation results. As more genetic data are being linked to electronic health records, robust GWAS methods that can make use of age-of-onset information will help increase power in analyses for common health outcomes.
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Affiliation(s)
- Emil M Pedersen
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark.
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
| | - Esben Agerbo
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrated Register-based Research at Aarhus University, Aarhus, Denmark
| | - Oleguer Plana-Ripoll
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark
| | - Jette Steinbach
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
| | - Morten D Krebs
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
| | - David M Hougaard
- Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
- Department of Clinical Sciences, Copenhagen University, Copenhagen, Denmark
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Science, Copenhagen University, Copenhagen, Denmark
| | - Merete Nordentoft
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- CORE- Copenhagen Centre for Research in Mental Health, Mental Health Center-Copenhagen, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
| | - Anders D Børglum
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Department of Biomedicine and iSEQ Centre, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, CGPM, Aarhus University, Aarhus, Denmark
| | - Katherine L Musliner
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Department of Affective Disorders, Aarhus University Hospital-Psychiatry, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Science, Copenhagen University, Copenhagen, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
| | - Preben B Mortensen
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
| | - John J McGrath
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
- Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, QLD, Australia
| | - Florian Privé
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
| | - Bjarni J Vilhjálmsson
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark.
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, the Broad Institute of MIT and Harvard, Massachusetts, USA.
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23
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Corte L, Liou L, O’Reilly PF, García-González J. Trumpet plots: visualizing the relationship between allele frequency and effect size in genetic association studies. GIGABYTE 2023; 2023:gigabyte89. [PMID: 37711278 PMCID: PMC10498096 DOI: 10.46471/gigabyte.89] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 08/29/2023] [Indexed: 09/16/2023] Open
Abstract
Recent advances in genome-wide association and sequencing studies have shown that the genetic architecture of complex traits and diseases involves a combination of rare and common genetic variants distributed throughout the genome. One way to better understand this architecture is to visualize genetic associations across a wide range of allele frequencies. However, there is currently no standardized or consistent graphical representation for effectively illustrating these results. Here we propose a standardized approach for visualizing the effect size of risk variants across the allele frequency spectrum. The proposed plots have a distinctive trumpet shape: with the majority of variants having high frequency and small effects, and a small number of variants having lower frequency and larger effects. To demonstrate the utility of trumpet plots in illustrating the relationship between the number of variants, their frequency, and the magnitude of their effects in shaping the genetic architecture of complex traits and diseases, we generated trumpet plots for more than one hundred traits in the UK Biobank. To facilitate their broader use, we developed an R package, 'TrumpetPlots' (available at the Comprehensive R Archive Network) and R Shiny application, 'Shiny Trumpets' (available at https://juditgg.shinyapps.io/shinytrumpets/) that allows users to explore these results and submit their own data.
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Affiliation(s)
- Lucia Corte
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
- Center for Excellence in Youth Education, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Lathan Liou
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Paul F. O’Reilly
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Judit García-González
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
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24
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Zheng Y, Jun J, Brennan K, Gevaert O. EpiMix is an integrative tool for epigenomic subtyping using DNA methylation. CELL REPORTS METHODS 2023; 3:100515. [PMID: 37533639 PMCID: PMC10391348 DOI: 10.1016/j.crmeth.2023.100515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 04/12/2023] [Accepted: 06/01/2023] [Indexed: 08/04/2023]
Abstract
DNA methylation (DNAme) is a major epigenetic factor influencing gene expression with alterations leading to cancer and immunological and cardiovascular diseases. Recent technological advances have enabled genome-wide profiling of DNAme in large human cohorts. There is a need for analytical methods that can more sensitively detect differential methylation profiles present in subsets of individuals from these heterogeneous, population-level datasets. We developed an end-to-end analytical framework named "EpiMix" for population-level analysis of DNAme and gene expression. Compared with existing methods, EpiMix showed higher sensitivity in detecting abnormal DNAme that was present in only small patient subsets. We extended the model-based analyses of EpiMix to cis-regulatory elements within protein-coding genes, distal enhancers, and genes encoding microRNAs and long non-coding RNAs (lncRNAs). Using cell-type-specific data from two separate studies, we discover epigenetic mechanisms underlying childhood food allergy and survival-associated, methylation-driven ncRNAs in non-small cell lung cancer.
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Affiliation(s)
- Yuanning Zheng
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - John Jun
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Kevin Brennan
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Olivier Gevaert
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
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25
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Yang Y, Liu H, Liu Y, Zhou L, Zheng X, Yue R, Mattson DL, Kidambi S, Liang M, Liu P, Pan X. E-value: a superior alternative to P-value and its adjustments in DNA methylation studies. Brief Bioinform 2023; 24:bbad241. [PMID: 37369639 PMCID: PMC10359086 DOI: 10.1093/bib/bbad241] [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: 03/22/2023] [Revised: 05/26/2023] [Accepted: 06/09/2023] [Indexed: 06/29/2023] Open
Abstract
DNA methylation plays a crucial role in transcriptional regulation. Reduced representation bisulfite sequencing (RRBS) is a technique of increasing use for analyzing genome-wide methylation profiles. Many computational tools such as Metilene, MethylKit, BiSeq and DMRfinder have been developed to use RRBS data for the detection of the differentially methylated regions (DMRs) potentially involved in epigenetic regulations of gene expression. For DMR detection tools, as for countless other medical applications, P-values and their adjustments are among the most standard reporting statistics used to assess the statistical significance of biological findings. However, P-values are coming under increasing criticism relating to their questionable accuracy and relatively high levels of false positive or negative indications. Here, we propose a method to calculate E-values, as likelihood ratios falling into the null hypothesis over the entire parameter space, for DMR detection in RRBS data. We also provide the R package 'metevalue' as a user-friendly interface to implement E-value calculations into various DMR detection tools. To evaluate the performance of E-values, we generated various RRBS benchmarking datasets using our simulator 'RRBSsim' with eight samples in each experimental group. Our comprehensive benchmarking analyses showed that using E-values not only significantly improved accuracy, area under ROC curve and power, over that of P-values or adjusted P-values, but also reduced false discovery rates and type I errors. In applications using real RRBS data of CRL rats and a clinical trial on low-salt diet, the use of E-values detected biologically more relevant DMRs and also improved the negative association between DNA methylation and gene expression.
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Affiliation(s)
- Yifan Yang
- Department of Mathematics, Shanghai Normal University, Shanghai, China
- Transwarp Technology Co., LTD, Shanghai, China
| | - Haoyuan Liu
- Department of Mathematics, Shanghai Normal University, Shanghai, China
| | - Yi Liu
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Department of Respiratory Medicine, Sir Run Run Shaw Hospital and Institute of Translational Medicine, Zhejiang University, Hangzhou, China
| | - Liyuan Zhou
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Department of Respiratory Medicine, Sir Run Run Shaw Hospital and Institute of Translational Medicine, Zhejiang University, Hangzhou, China
| | - Xiaoqi Zheng
- Department of Mathematics, Shanghai Normal University, Shanghai, China
| | - Rongxian Yue
- Department of Mathematics, Shanghai Normal University, Shanghai, China
| | - David L Mattson
- Department of Physiology, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Srividya Kidambi
- Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Mingyu Liang
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Pengyuan Liu
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Department of Respiratory Medicine, Sir Run Run Shaw Hospital and Institute of Translational Medicine, Zhejiang University, Hangzhou, China
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Xiaoqing Pan
- Department of Mathematics, Shanghai Normal University, Shanghai, China
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26
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Wang Q, Wang X, Yang T, Yang L, Liu H, Zheng Y, Jiang G, Liu H, Huang C, Chen J, Wang Z, Wang Z, Zhao W, Lin J, Zhang X, Shi J, Han K, Le X, Ren Y, Li Y, Hong Y, Shi W, Cui D, Qian M, Xu J, Zheng X, Gao Y, Li C, Lin J, Huang Z, Wu H. A common variant in AAK1 reduces risk of noise-induced hearing loss. Natl Sci Rev 2023; 10:nwad080. [PMID: 37547059 PMCID: PMC10401317 DOI: 10.1093/nsr/nwad080] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 03/14/2023] [Accepted: 03/17/2023] [Indexed: 08/08/2023] Open
Affiliation(s)
| | | | - Tao Yang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Lu Yang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Huihui Liu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Yihang Zheng
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Guixian Jiang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Hongchao Liu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Chenhui Huang
- Shanghai Institute of Precision Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Juan Chen
- Shanghai Institute of Precision Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Zhentao Wang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Zhaoyan Wang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Wei Zhao
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Jiannan Lin
- The Core Laboratory in the Medical Center of Clinical Research, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Xuejie Zhang
- Biobank, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Junbo Shi
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Kun Han
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Xingyu Le
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Yan Ren
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Yun Li
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Yingying Hong
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Wentao Shi
- Clinical Research Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Dongqi Cui
- Clinical Research Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Minfei Qian
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Jun Xu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Xiaofei Zheng
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Yunge Gao
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Ear Institute, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Translational Medicine on Ear and Nose Diseases, China
| | - Chen Li
- Network and Information Center, Shanghai Jiao Tong University, China
| | - James Lin
- Network and Information Center, Shanghai Jiao Tong University, China
| | | | - Hao Wu
- Corresponding authors. E-mail:
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Bhatraju PK, Stanaway IB, Palmer MR, Menon R, Schaub JA, Menez S, Srivastava A, Wilson FP, Kiryluk K, Palevsky PM, Naik AS, Sakr SS, Jarvik GP, Parikh CR, Ware LB, Ikizler TA, Siew ED, Chinchilli VM, Coca SG, Garg AX, Go AS, Kaufman JS, Kimmel PL, Himmelfarb J, Wurfel MM. Genome-wide Association Study for AKI. KIDNEY360 2023; 4:870-880. [PMID: 37273234 PMCID: PMC10371295 DOI: 10.34067/kid.0000000000000175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 04/03/2023] [Indexed: 06/06/2023]
Abstract
Key Points Two genetic variants in the DISP1-TLR5 gene locus were associated with risk of AKI. DISP1 and TLR5 were differentially regulated in kidney biopsy tissue from patients with AKI compared with no AKI. Background Although common genetic risks for CKD are well established, genetic factors influencing risk for AKI in hospitalized patients are poorly understood. Methods We conducted a genome-wide association study in 1369 participants in the Assessment, Serial Evaluation, and Subsequent Sequelae of AKI Study; a multiethnic population of hospitalized participants with and without AKI matched on demographics, comorbidities, and kidney function before hospitalization. We then completed functional annotation of top-performing variants for AKI using single-cell RNA sequencing data from kidney biopsies in 12 patients with AKI and 18 healthy living donors from the Kidney Precision Medicine Project. Results No genome-wide significant associations with AKI risk were found in Assessment, Serial Evaluation, and Subsequent Sequelae of AKI (P < 5×10 −8 ). The top two variants with the strongest association with AKI mapped to the dispatched resistance-nodulation-division (RND) transporter family member 1 (DISP1) gene and toll-like receptor 5 (TLR5) gene locus, rs17538288 (odds ratio, 1.55; 95% confidence interval, 1.32 to 182; P = 9.47×10 −8 ) and rs7546189 (odds ratio, 1.53; 95% confidence interval, 1.30 to 1.81; P = 4.60×10 −7 ). In comparison with kidney tissue from healthy living donors, kidney biopsies in patients with AKI showed differential DISP1 expression in proximal tubular epithelial cells (adjusted P = 3.9× 10−2) and thick ascending limb of the loop of Henle (adjusted P = 8.7× 10−3) and differential TLR5 gene expression in thick ascending limb of the loop of Henle (adjusted P = 4.9× 10−30). Conclusions AKI is a heterogeneous clinical syndrome with various underlying risk factors, etiologies, and pathophysiology that may limit the identification of genetic variants. Although no variants reached genome-wide significance, we report two variants in the intergenic region between DISP1 and TLR5 , suggesting this region as a novel risk for AKI susceptibility.
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Affiliation(s)
- Pavan K Bhatraju
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, Washington
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Ian B Stanaway
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Melody R Palmer
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington School of Medicine, Seattle, Washington
| | - Rajasree Menon
- Division of Nephrology, Department of Medicine, Michigan Medicine, Ann Arbor, Michigan
| | - Jennifer A Schaub
- Division of Nephrology, Department of Medicine, Michigan Medicine, Ann Arbor, Michigan
| | - Steven Menez
- Division of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Anand Srivastava
- Department of Medicine, Division of Nephrology and Hypertension, Northwestern University School of Medicine, Chicago, Illinois
| | - F Perry Wilson
- Program of Applied Translational Research, Yale School of Medicine, New Haven, Connecticut
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York City, New York
| | - Paul M Palevsky
- Kidney Medicine Section, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
- Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Abhijit S Naik
- Division of Nephrology, University of Michigan, Ann Arbor, Michigan
| | - Sana S Sakr
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, Washington
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington School of Medicine, Seattle, Washington
| | - Chirag R Parikh
- Division of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Lorraine B Ware
- Division of Allergy, Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, Tennessee
| | - T Alp Ikizler
- Division of Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Edward D Siew
- Division of Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Vernon M Chinchilli
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania
| | - Steve G Coca
- Section of Nephrology, Department of Internal Medicine, Mount Sinai School of Medicine, New York, New York
| | - Amit X Garg
- Division of Nephrology, Department of Medicine, Western University, London, Ontario, Canada
| | - Alan S Go
- Division of Nephrology, Department of Medicine, University of California, San Francisco, California
- Division of Research, Kaiser Permanente Northern California, Oakland, California
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California
| | - James S Kaufman
- Division of Nephrology, New York University School of Medicine, New York, New York
- Division of Nephrology, VA New York Harbor Healthcare System, New York, New York
| | - Paul L Kimmel
- Division of Renal Diseases and Hypertension, Department of Medicine, George Washington University Medical Center, Washington, DC
| | - Jonathan Himmelfarb
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Mark M Wurfel
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, Washington
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
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Katki HA, Berndt SI, Machiela MJ, Stewart DR, Garcia-Closas M, Kim J, Shi J, Yu K, Rothman N. Increase in power by obtaining 10 or more controls per case when type-1 error is small in large-scale association studies. BMC Med Res Methodol 2023; 23:153. [PMID: 37386403 PMCID: PMC10308790 DOI: 10.1186/s12874-023-01973-x] [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: 02/06/2023] [Accepted: 06/10/2023] [Indexed: 07/01/2023] Open
Abstract
BACKGROUND The rule of thumb that there is little gain in statistical power by obtaining more than 4 controls per case, is based on type-1 error α = 0.05. However, association studies that evaluate thousands or millions of associations use smaller α and may have access to plentiful controls. We investigate power gains, and reductions in p-values, when increasing well beyond 4 controls per case, for small α. METHODS We calculate the power, the median expected p-value, and the minimum detectable odds-ratio (OR), as a function of the number of controls/case, as α decreases. RESULTS As α decreases, at each ratio of controls per case, the increase in power is larger than for α = 0.05. For α between 10-6 and 10-9 (typical for thousands or millions of associations), increasing from 4 controls per case to 10-50 controls per case increases power. For example, a study with power = 0.2 (α = 5 × 10-8) with 1 control/case has power = 0.65 with 4 controls/case, but with 10 controls/case has power = 0.78, and with 50 controls/case has power = 0.84. For situations where obtaining more than 4 controls per case provides small increases in power beyond 0.9 (at small α), the expected p-value can decrease by orders-of-magnitude below α. Increasing from 1 to 4 controls/case reduces the minimum detectable OR toward the null by 20.9%, and from 4 to 50 controls/case reduces by an additional 9.7%, a result which applies regardless of α and hence also applies to "regular" α = 0.05 epidemiology. CONCLUSIONS At small α, versus 4 controls/case, recruiting 10 or more controls/cases can increase power, reduce the expected p-value by 1-2 orders of magnitude, and meaningfully reduce the minimum detectable OR. These benefits of increasing the controls/case ratio increase as the number of cases increases, although the amount of benefit depends on exposure frequencies and true OR. Provided that controls are comparable to cases, our findings suggest greater sharing of comparable controls in large-scale association studies.
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Affiliation(s)
- Hormuzd A Katki
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mitchell J Machiela
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Douglas R Stewart
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Montserrat Garcia-Closas
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jung Kim
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kai Yu
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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29
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Sahana G, Cai Z, Sanchez MP, Bouwman AC, Boichard D. Invited review: Good practices in genome-wide association studies to identify candidate sequence variants in dairy cattle. J Dairy Sci 2023:S0022-0302(23)00357-0. [PMID: 37349208 DOI: 10.3168/jds.2022-22694] [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: 08/24/2022] [Accepted: 02/01/2023] [Indexed: 06/24/2023]
Abstract
Genotype data from dairy cattle selection programs have greatly facilitated GWAS to identify variants related to economic traits. Results can enhance the accuracy of genomic prediction, analyze more complex models that go beyond additive effects, elucidate the genetic architecture of a trait, and finally, decipher the underlying biology of traits. The entire process, comprising data generation, quality control, statistical analyses, interpretation of association results, and linking results to biology should be designed and executed to minimize the generation of false-positive and false-negative associations and misleading links to biological processes. This review aims to provide general guidelines for data analysis that address data quality control, association tests, adjustment for population stratification, and significance evaluation to improve the reliability of conclusions. We also provide guidance on post-GWAS strategy and the interpretation of results. These guidelines are tailored to dairy cattle, which are characterized by long-range linkage disequilibrium, large half-sib families, and routinely collected phenotypes, requiring different approaches than those applied in human GWAS. We discuss common limitations and challenges that have been overlooked in the analysis and interpretation of GWAS to identify candidate sequence variants in dairy cattle.
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Affiliation(s)
- G Sahana
- Aarhus University, Center for Quantitative Genetic and Genomics, 8830 Tjele, Denmark.
| | - Z Cai
- Aarhus University, Center for Quantitative Genetic and Genomics, 8830 Tjele, Denmark
| | - M P Sanchez
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France
| | - A C Bouwman
- Wageningen University & Research, Animal Breeding and Genomics, 6700 AH Wageningen, the Netherlands
| | - D Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France
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30
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Xu Z, Yan S, Wu C, Duan Q, Chen S, Li Y. Next-Generation Sequencing Data-Based Association Testing of a Group of Genetic Markers for Complex Responses Using a Generalized Linear Model Framework. MATHEMATICS (BASEL, SWITZERLAND) 2023; 11:2560. [PMID: 38721066 PMCID: PMC11078158 DOI: 10.3390/math11112560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
Association testing has been widely used to study the relationship between genetic variants and phenotypes. Most association testing methods are genotype-based, i.e. first estimate genotype and then regress phenotype on estimated genotype and other variables. Directly testing methods based on next generation sequencing (NGS) data without genotype calling have been proposed and shown advantage over genotype-based methods in the scenarios when genotype calling is not accurate. NGS data-based single-variant testing have been proposed including our previously proposed single-variant testing method, i.e. UNC combo method [1]. NGS data-based group testing methods for continuous phenotype have also been proposed by us using a linear model framework which can handle continuous responses [2]. In this paper, we extend our linear model-based framework to a generalized linear model-based framework so that the methods can handle other types of responses especially binary responses which is commonly-faced in association studies. We have conducted extensive simulation studies to evaluate the performance of different estimators and compare our estimators with their corresponding genotype-based methods. We found that all methods have Type I errors controlled, and our NGS data-based testing methods have better performance than their corresponding genotype-based methods in the literature for other types of responses including binary responses (logistic regression) and count responses (Poisson regression especially when sequencing depth is low. In conclusion, we have extended our previous linear model (LM) framework to a generalized linear model (GLM) framework and derived NGS data-based testing methods for a group of genetic variants. Compared with our previously proposed LM-based methods [2], the new GLM-based methods can handle more complex responses (for example, binary responses and count responses) in addition to continuous responses. Our methods have filled the literature gap and shown advantage over their corresponding genotype-based methods in the literature.
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Affiliation(s)
- Zheng Xu
- Department of Mathematics and Statistics, Wright State University, Dayton, Ohio, 45324, USA
| | - Song Yan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Cong Wu
- Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE 68508, USA
| | - Qing Duan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Sixia Chen
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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31
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Moghadam HK, Fannemel B, Thorland I, Lozano C, Hillestad B. Identification and Genomic Localization of Autosomal sdY Locus in a Population of Atlantic Salmon (Salmo salar). MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2023:10.1007/s10126-023-10217-4. [PMID: 37233880 DOI: 10.1007/s10126-023-10217-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 05/14/2023] [Indexed: 05/27/2023]
Abstract
The determination of sex in salmonid fishes is controlled by genetic mechanisms, with males being the heterogametic sex. The master sex-determining gene, the sexually dimorphic gene on the Y chromosome (sdY), is a conserved gene across various salmonid species. Nevertheless, variations in the genomic location of sdY have been observed both within and between species. Furthermore, different studies have reported discordances in the association between the sdY and the phenotypic gender. While some males seem to lack this locus, there have been reports of females carrying sdY. Although the exact reasons behind this discordance remain under investigation, some recent studies have proposed the existence of an autosomal, non-functional copy of sdY as a potential cause. In this study, we confirmed the presence of this autosomal sdY in the SalmoBreed strain of Atlantic salmon using a genotyping platform through a novel approach that allows for high-throughput screening of a large number of individuals. We further characterized the segregation profile of this locus across families and found the ratio of genetically assigned female-to-male progeny to be in accordance with the expected profile of a single autosomal sdY locus. Additionally, our mapping efforts localized this locus to chromosome 3 and suggested a putative copy on chromosome 6.
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32
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Chatterjee S, Sanjeev BS. Community detection in Epstein-Barr virus associated carcinomas and role of tyrosine kinase in etiological mechanisms for oncogenesis. Microb Pathog 2023; 180:106115. [PMID: 37137346 DOI: 10.1016/j.micpath.2023.106115] [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: 03/12/2023] [Revised: 04/12/2023] [Accepted: 04/13/2023] [Indexed: 05/05/2023]
Abstract
BACKGROUND Epstein-Barr virus (EBV) affects more than 90% of global population. The role of the virus in causing infectious mononucleosis (IM) affecting B-cells and epithelial cells and in the development of EBV associated cancers is well documented. Investigating the associated interactions can pave way for the discovery of novel therapeutic targets for EBV associated lymphoproliferative (Burkitt's Lymphoma and Hodgkin's Lymphoma) and non-lymphoproliferative diseases (Gastric cancer and Nasopharyngeal cancer). METHODS Based on the DisGeNET (v7.0) data set, we constructed a disease-gene network to identify genes that are involved in various carcinomas, viz. Gastric cancer (GC), Nasopharyngeal cancer (NPC), Hodgkin's lymphoma (HL) and Burkitt's lymphoma (BL). We identified communities in the disease-gene network and performed functional enrichment using over-representation analysis to detect significant biological processes/pathways and the interactions between them. RESULT We identified the modular communities to explore the relation of this common causative pathogen (EBV) with different carcinomas such as GC, NPC, HL and BL. Through network analysis we identified the top 10 genes linked with EBV associated carcinomas as CASP10, BRAF, NFKBIA, IFNA2, GSTP1, CSF3, GATA3, UBR5, AXIN2 and POLE. Further, the tyrosine-protein kinase (ABL1) gene was significantly over-represented in 3 out of 9 critical biological processes, viz. in regulatory pathways in cancer, the TP53 network and the Imatinib and chronic myeloid leukemia biological processes. Consequently, the EBV pathogen appears to target critical pathways involved in cellular growth arrest/apoptosis. We make our case for BCR-ABL1 tyrosine-kinase inhibitors (TKI) for further clinical investigations in the inhibition of BCR-mediated EBV activation in carcinomas for better prognostic and therapeutic outcomes.
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Affiliation(s)
- S Chatterjee
- Department of Applied Sciences, Indian Institute of Information Technology, Allahabad, India.
| | - B S Sanjeev
- Department of Applied Sciences, Indian Institute of Information Technology, Allahabad, India.
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Wang S, Su Q, Qin W, Yu C, Liang M. Both fine-grained and coarse-grained spatial patterns of neural activity measured by functional MRI show preferential encoding of pain in the human brain. Neuroimage 2023; 272:120049. [PMID: 36963739 DOI: 10.1016/j.neuroimage.2023.120049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 01/31/2023] [Accepted: 03/21/2023] [Indexed: 03/26/2023] Open
Abstract
How pain emerges from human brain remains an unresolved question in pain neuroscience. Neuroimaging studies have suggested that all brain areas activated by painful stimuli were also activated by tactile stimuli, and vice versa. Nonetheless, pain-preferential spatial patterns of voxel-level activation in the brain have been observed when distinguishing painful and tactile brain activations using multivariate pattern analysis (MVPA). According to two hypotheses, the neural activity pattern preferentially encoding pain could exist at a global, coarse-grained, regional level, corresponding to the "pain connectome" hypothesis proposing that pain-preferential information may be encoded by the synchronized activity across multiple distant brain regions, and/or exist at a local, fine-grained, voxel level, corresponding to the "intermingled specialized/preferential neurons" hypothesis proposing that neurons responding specially or preferentially to pain could be present and intermingled with non-pain neurons within a voxel. Here, we systematically investigated the spatial scales of pain-distinguishing information in the human brain measured by fMRI using machine learning techniques, and found that pain-distinguishing information could be detected at both coarse-grained spatial scales across widely distributed brain regions and fine-grained spatial scales within many local areas. Importantly, the spatial distribution of pain-distinguishing information in the brain varies across individuals and such inter-individual variations may be related to a person's trait about pain perception, particularly the pain vigilance and awareness. These results provide new insights into the long-standing question of how pain is represented in the human brain and help the identification of characteristic neuroimaging measurements of pain.
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Affiliation(s)
- Sijia Wang
- School of Medical Technology, School of Medical Imaging, Tianjin Key Laboratory of Functional Imaging, The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China
| | - Qian Su
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for China, Tianjin 300060, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Chunshui Yu
- School of Medical Technology, School of Medical Imaging, Tianjin Key Laboratory of Functional Imaging, The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China; Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Meng Liang
- School of Medical Technology, School of Medical Imaging, Tianjin Key Laboratory of Functional Imaging, The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.
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34
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Aegisdottir HM, Thorolfsdottir RB, Sveinbjornsson G, Stefansson OA, Gunnarsson B, Tragante V, Thorleifsson G, Stefansdottir L, Thorgeirsson TE, Ferkingstad E, Sulem P, Norddahl G, Rutsdottir G, Banasik K, Christensen AH, Mikkelsen C, Pedersen OB, Brunak S, Bruun MT, Erikstrup C, Jacobsen RL, Nielsen KR, Sørensen E, Frigge ML, Hjorleifsson KE, Ivarsdottir EV, Helgadottir A, Gretarsdottir S, Steinthorsdottir V, Oddsson A, Eggertsson HP, Halldorsson GH, Jones DA, Anderson JL, Knowlton KU, Nadauld LD, Haraldsson M, Thorgeirsson G, Bundgaard H, Arnar DO, Thorsteinsdottir U, Gudbjartsson DF, Ostrowski SR, Holm H, Stefansson K. Genetic variants associated with syncope implicate neural and autonomic processes. Eur Heart J 2023; 44:1070-1080. [PMID: 36747475 DOI: 10.1093/eurheartj/ehad016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 11/22/2022] [Accepted: 01/05/2023] [Indexed: 02/08/2023] Open
Abstract
AIMS Syncope is a common and clinically challenging condition. In this study, the genetics of syncope were investigated to seek knowledge about its pathophysiology and prognostic implications. METHODS AND RESULTS This genome-wide association meta-analysis included 56 071 syncope cases and 890 790 controls from deCODE genetics (Iceland), UK Biobank (United Kingdom), and Copenhagen Hospital Biobank Cardiovascular Study/Danish Blood Donor Study (Denmark), with a follow-up assessment of variants in 22 412 cases and 286 003 controls from Intermountain (Utah, USA) and FinnGen (Finland). The study yielded 18 independent syncope variants, 17 of which were novel. One of the variants, p.Ser140Thr in PTPRN2, affected syncope only when maternally inherited. Another variant associated with a vasovagal reaction during blood donation and five others with heart rate and/or blood pressure regulation, with variable directions of effects. None of the 18 associations could be attributed to cardiovascular or other disorders. Annotation with regard to regulatory elements indicated that the syncope variants were preferentially located in neural-specific regulatory regions. Mendelian randomization analysis supported a causal effect of coronary artery disease on syncope. A polygenic score (PGS) for syncope captured genetic correlation with cardiovascular disorders, diabetes, depression, and shortened lifespan. However, a score based solely on the 18 syncope variants performed similarly to the PGS in detecting syncope risk but did not associate with other disorders. CONCLUSION The results demonstrate that syncope has a distinct genetic architecture that implicates neural regulatory processes and a complex relationship with heart rate and blood pressure regulation. A shared genetic background with poor cardiovascular health was observed, supporting the importance of a thorough assessment of individuals presenting with syncope.
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Affiliation(s)
- Hildur M Aegisdottir
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
| | | | | | | | | | | | | | | | | | - Egil Ferkingstad
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | - Patrick Sulem
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | | | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, Copenhagen 2200, Denmark
| | - Alex Hoerby Christensen
- The Unit for Inherited Cardiac Diseases, Department of Cardiology, The Heart Centre, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
- Department of Cardiology, Herlev-Gentofte Hospital, Copenhagen University Hospital, Borgmester Ib Juuls Vej 1, Herlev 2730, Denmark
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, Copenhagen 2200, Denmark
| | - Christina Mikkelsen
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3A, Copenhagen 2200, Denmark
| | - Ole Birger Pedersen
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, Copenhagen 2200, Denmark
- Department of Clinical Immunology, Zealand University Hospital - Køge, Lykkebækvej 1, Køge 4600, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, Copenhagen 2200, Denmark
| | - Mie Topholm Bruun
- Department of Clinical Immunology, Odense University Hospital, J. B. Winsløws Vej 4, Odense 5000, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus 8200, Denmark
- Department of Clinical Medicine, Aarhus University, Nordre Ringgade 1, Aarhus 8000, Denmark
| | - Rikke Louise Jacobsen
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Kaspar Rene Nielsen
- Department of Clinical Immunology, Aalborg University Hospital, Urbansgade 32, Aalborg 9000, Denmark
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Michael L Frigge
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | | | - Anna Helgadottir
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | | | - Asmundur Oddsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | | | - David A Jones
- Precision Genomics, Intermountain Healthcare, 600 S. Medical Center Drive, Saint George, UT 84790, USA
| | - Jeffrey L Anderson
- Intermountain Medical Center, Intermountain Heart Institute, 5171 S. Cottonwood Street Building 1, Salt Lake City, UT 84107, USA
- Department of Internal Medicine, University of Utah, 30 N 1900 E, Salt Lake City, UT 84132, USA
| | - Kirk U Knowlton
- Intermountain Medical Center, Intermountain Heart Institute, 5171 S. Cottonwood Street Building 1, Salt Lake City, UT 84107, USA
- School of Medicine, University of Utah, 30 N 1900 E, Salt Lake City, UT 84132, USA
| | - Lincoln D Nadauld
- Precision Genomics, Intermountain Healthcare, 600 S. Medical Center Drive, Saint George, UT 84790, USA
- School of Medicine, Stanford University, 291 Campus Drive, Stanford, CA 94305, USA
| | | | - Magnus Haraldsson
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
- Department of Psychiatry, Landspitali, The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Gudmundur Thorgeirsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
- Department of Medicine, Landspitali, The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Henning Bundgaard
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, Copenhagen 2200, Denmark
- The Capital Regions Unit for Inherited Cardiac Diseases, Department of Cardiology, The Heart Centre, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - David O Arnar
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
- Department of Medicine, Landspitali, The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Hjardarhagi 4, Reykjavik 107, Iceland
| | - Sisse R Ostrowski
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, Copenhagen 2200, Denmark
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
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Lee DJ, Tsai PH, Chen CC, Dai YH. Incorporating knowledge of disease-defining hub genes and regulatory network into a machine learning-based model for predicting treatment response in lupus nephritis after the first renal flare. J Transl Med 2023; 21:76. [PMID: 36737814 PMCID: PMC9898995 DOI: 10.1186/s12967-023-03931-z] [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: 11/15/2022] [Accepted: 01/25/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Identifying candidates responsive to treatment is important in lupus nephritis (LN) at the renal flare (RF) because an effective treatment can lower the risk of progression to end-stage kidney disease. However, machine learning (ML)-based models that address this issue are lacking. METHODS Transcriptomic profiles based on DNA microarray data were extracted from the GSE32591 and GSE112943 datasets. Comprehensive bioinformatics analyses were performed to identify disease-defining genes (DDGs). Peripheral blood samples (GSE81622, GSE99967, and GSE72326) were used to evaluate the effect of DDGs. Single-sample gene set enrichment analysis (ssGSEA) scores of the DDGs were calculated and correlated with specific immunology genes listed in the nCounter panel. GSE60681 and GSE69438 were used to examine the ability of the DDGs to discriminate LN from other renal diseases. K-means clustering was used to obtain the separate gene sets. The clustering results were extended to data derived using the nCounter technique. The least absolute shrinkage and selection operator (LASSO) algorithm was used to identify genes with high predictive value for treatment response after the first RF in each cluster. LASSO models with tenfold validation were built in GSE200306 and assessed by receiver operating characteristic (ROC) analysis with area under curve (AUC). The models were validated by using an independent dataset (GSE113342). RESULTS Forty-five hub genes specific to LN were identified. Eight optimal disease-defining clusters (DDCs) were identified in this study. Th1 and Th2 cell differentiation pathway was significantly enriched in DDC-6. LCK in DDC-6, whose expression positively correlated with various subsets of T cell infiltrations, was found to be differentially expressed between responders and non-responders and was ranked high in regulatory network analysis. Based on DDC-6, the prediction model had the best performance (AUC: 0.75; 95% confidence interval: 0.44-1 in the testing set) and high precision (0.83), recall (0.71), and F1 score (0.77) in the validation dataset. CONCLUSIONS Our study demonstrates that incorporating knowledge of biological phenotypes into the ML model is feasible for evaluating treatment response after the first RF in LN. This knowledge-based incorporation improves the model's transparency and performance. In addition, LCK may serve as a biomarker for T-cell infiltration and a therapeutic target in LN.
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Affiliation(s)
- Ding-Jie Lee
- grid.260565.20000 0004 0634 0356Division of Nephrology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Ping-Huang Tsai
- grid.260565.20000 0004 0634 0356Division of Nephrology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chien-Chou Chen
- grid.260565.20000 0004 0634 0356Division of Nephrology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan ,grid.260565.20000 0004 0634 0356Department of Internal Medicine, Tri-Service General Hospital Songshan Branch, National Defense Medical Center, Taipei, Taiwan
| | - Yang-Hong Dai
- Department of Radiation Oncology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
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Dubdub I. Artificial Neural Network Study on the Pyrolysis of Polypropylene with a Sensitivity Analysis. Polymers (Basel) 2023; 15:polym15030494. [PMID: 36771796 PMCID: PMC9918981 DOI: 10.3390/polym15030494] [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: 12/21/2022] [Revised: 01/09/2023] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
Among machine learning (ML) studies, artificial neural network (ANN) analysis is the most widely used technique in pyrolysis research. In this work, the pyrolysis of polypropylene (PP) polymers was established using a thermogravimetric analyzer (TGA) with five sets of heating rates (5-40 K min-1). TGA data was used to exploit an ANN network by achieving a feed-forward backpropagation optimization technique in order to predict the weight-left percentage. Two important ANN model input variables were identified as the heating rate (K min-1) and temperature (K). For the range of TGA values, a 2-10-10-1 network with two hidden layers (Logsig-Tansig) was concluded to be the best structure for predicting the weight-left percentage. The ANN demonstrated a good agreement between the experimental and calculated values, with a high correlation coefficient (R) of greater than 0.9999. The final network was then simulated with the new input data set for effective performance. In addition, a sensitivity analysis was performed to identify the uncertainties associated with the relationship between the output and input parameters. Temperature was found to be a more sensitive input parameter than the heating rate on the weight-left percentage calculation.
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Affiliation(s)
- Ibrahim Dubdub
- Department of Chemical Engineering, King Faisal University, Al-Hassa 31982, Saudi Arabia
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Sample Size Calculation in Genetic Association Studies: A Practical Approach. LIFE (BASEL, SWITZERLAND) 2023; 13:life13010235. [PMID: 36676184 PMCID: PMC9863799 DOI: 10.3390/life13010235] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/21/2022] [Accepted: 01/11/2023] [Indexed: 01/19/2023]
Abstract
Genetic association studies, testing the relationship between genetic variants and disease status, are useful tools for identifying genes that grant susceptibility to complex disorders. In such studies, an inadequate sample size may provide unreliable results: a small sample is unable to accurately describe the population, whereas a large sample makes the study expensive and complex to run. However, in genetic association studies, the sample size calculation is often overlooked or inadequately assessed for the small number of parameters included. In light of this, herein we list and discuss the role of the statistical and genetic parameters to be considered in the sample size calculation, show examples reporting incorrect estimation and, by using a genetic software program, we provide a practical approach for the assessment of the adequate sample size in a hypothetical study aimed at analyzing a gene-disease association.
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Zheng Y, Jun J, Brennan K, Gevaert O. EpiMix: an integrative tool for epigenomic subtyping using DNA methylation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.03.522660. [PMID: 36711917 PMCID: PMC9881910 DOI: 10.1101/2023.01.03.522660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
DNA methylation (DNAme) is a major epigenetic factor influencing gene expression with alterations leading to cancer, immunological, and cardiovascular diseases. Recent technological advances enable genome-wide quantification of DNAme in large human cohorts. So far, existing methods have not been evaluated to identify differential DNAme present in large and heterogeneous patient cohorts. We developed an end-to-end analytical framework named "EpiMix" for population-level analysis of DNAme and gene expression. Compared to existing methods, EpiMix showed higher sensitivity in detecting abnormal DNAme that was present in only small patient subsets. We extended the model-based analyses of EpiMix to cis-regulatory elements within protein-coding genes, distal enhancers, and genes encoding microRNAs and lncRNAs. Using cell-type specific data from two separate studies, we discovered novel epigenetic mechanisms underlying childhood food allergy and survival-associated, methylation-driven non-coding RNAs in non-small cell lung cancer.
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Affiliation(s)
- Yuanning Zheng
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - John Jun
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Kevin Brennan
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Olivier Gevaert
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
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Cusack SE, Aliev F, Bustamante D, Dick DM, Amstadter AB. A statistical genetic investigation of psychiatric resilience. Eur J Psychotraumatol 2023; 14:2178762. [PMID: 37052082 PMCID: PMC9987782 DOI: 10.1080/20008066.2023.2178762] [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: 09/20/2022] [Accepted: 01/28/2023] [Indexed: 03/06/2023] Open
Abstract
Background: Although trauma exposure (TE) is a transdiagnostic risk factor for many psychiatric disorders, not everyone who experiences TE develops a psychiatric disorder. Resilience may explain this heterogeneity; thus, it is critical to understand the etiologic underpinnings of resilience.Objective: The present study sought to examine the genetic underpinnings of psychiatric resilience using genome-wide association studies (GWAS), genome-wide complex trait analysis (GCTA), and polygenic risk score (PRS) analyses.Method: Participants were 6,634 trauma exposed college students attending a diverse, public university in the Mid Atlantic. GWAS and GCTA analyses were conducted, and using GWAS summary statistics from large genetic consortia, PRS analyses examined the shared genetic risk between resilience and various phenotypes.Results: Results demonstrate that nine single-nucleotide polymorphisms (SNPs) met the suggestive of significance threshold, heritability estimates for resilience were non-significant, and that there is genetic overlap between resilience and AD, as well as resilience and PTSD.Conclusion: Mixed findings from the present study suggest additional research to elucidate the etiological underpinnings of resilience, ideally with larger samples less biased by variables such as heterogeneity (i.e. clinical vs. population based) and population stratification. Genetic investigations of resilience have the potential to elucidate the molecular bases of stress-related psychopathology, suggesting new avenues for prevention and intervention efforts.
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Affiliation(s)
- Shannon E. Cusack
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
| | - Fazil Aliev
- Department of African American Studies, Virginia Commonwealth University, Richmond, VA, USA
| | - Daniel Bustamante
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Danielle M. Dick
- Brain Health Institute, Rutgers Biomedical and Health Sciences, Rutgers University, Piscataway, NJ, USA
| | - Ananda B. Amstadter
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
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40
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Odintsova VV, Hagenbeek FA, van der Laan CM, van de Weijer S, Boomsma DI. Genetics and epigenetics of human aggression. HANDBOOK OF CLINICAL NEUROLOGY 2023; 197:13-44. [PMID: 37633706 DOI: 10.1016/b978-0-12-821375-9.00005-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/28/2023]
Abstract
There is substantial variation between humans in aggressive behavior, with its biological etiology and molecular genetic basis mostly unknown. This review chapter offers an overview of genomic and omics studies revealing the genetic contribution to aggression and first insights into associations with epigenetic and other omics (e.g., metabolomics) profiles. We allowed for a broad phenotype definition including studies on "aggression," "aggressive behavior," or "aggression-related traits," "antisocial behavior," "conduct disorder," and "oppositional defiant disorder." Heritability estimates based on family and twin studies in children and adults of this broadly defined phenotype of aggression are around 50%, with relatively small fluctuations around this estimate. Next, we review the genome-wide association studies (GWAS) which search for associations with alleles and also allow for gene-based tests and epigenome-wide association studies (EWAS) which seek to identify associations with differently methylated regions across the genome. Both GWAS and EWAS allow for construction of Polygenic and DNA methylation scores at an individual level. Currently, these predict a small percentage of variance in aggression. We expect that increases in sample size will lead to additional discoveries in GWAS and EWAS, and that multiomics approaches will lead to a more comprehensive understanding of the molecular underpinnings of aggression.
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Affiliation(s)
- Veronika V Odintsova
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands; Mental Health Division, Amsterdam Public Health (APH) Research Institute, Amsterdam, The Netherlands
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Mental Health Division, Amsterdam Public Health (APH) Research Institute, Amsterdam, The Netherlands
| | - Camiel M van der Laan
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Netherlands Institute for the Study of Crime and Law Enforcement (NSCR), Amsterdam, The Netherlands
| | - Steve van de Weijer
- Netherlands Institute for the Study of Crime and Law Enforcement (NSCR), Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands.
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Association between PTPN1 polymorphisms and obesity-related phenotypes in European adolescents: influence of physical activity. Pediatr Res 2022:10.1038/s41390-022-02377-1. [PMID: 36369476 DOI: 10.1038/s41390-022-02377-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 10/06/2022] [Accepted: 10/23/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND To study the associations of Protein Tyrosine Phosphatase-N1 (PTPN1) polymorphisms with obesity-related phenotypes in European adolescents, and the influence of physical activity on these relationships. METHODS Five polymorphisms of PTPN1 were genotyped in 1057 European adolescents (12-18 years old). We measured several phenotypes related to obesity, such as adiposity markers, and biochemical and clinical parameters. Physical activity was objectively measured by accelerometry. RESULTS The T, A, T, T and G alleles of the rs6067472, rs10485614, rs2143511, rs6020608 and rs968701 polymorphisms, respectively, were associated with lower levels of obesity-related phenotypes (i.e., body mass index, body fat percentage, hip circumference, fat mass index, systolic blood pressure and leptin) in European adolescents. In addition, the TATTG haplotype was associated with lower body fat percentage and fat mass index compared to the AACCA haplotype. Finally, when physical activity levels were considered, alleles of the rs6067472, rs2143511, rs6020608 and rs968701 polymorphisms were only associated with lower adiposity in active adolescents. CONCLUSIONS PTPN1 polymorphisms were associated with adiposity in European adolescents. Specifically, alleles of these polymorphisms were associated with lower adiposity only in physically active adolescents. Therefore, meeting the recommendations of daily physical activity may reduce obesity risk by modulating the genetic predisposition to obesity. IMPACT Using gene-phenotype and gene*environment analyses, we detected associations between polymorphisms of the Protein Tyrosine Phosphatase-N1 (PTPN1) gene and obesity-related phenotypes, suggesting a mechanism that can be modulated by physical activity. This study shows that genetic variability of PTPN1 is associated with adiposity, while physical activity seems to modulate the genetic predisposition. This brings insights about the mechanisms by which physical activity positively influences obesity.
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42
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Wojcik GL, Murphy J, Edelson JL, Gignoux CR, Ioannidis AG, Manning A, Rivas MA, Buyske S, Hendricks AE. Opportunities and challenges for the use of common controls in sequencing studies. Nat Rev Genet 2022; 23:665-679. [PMID: 35581355 PMCID: PMC9765323 DOI: 10.1038/s41576-022-00487-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2022] [Indexed: 01/02/2023]
Abstract
Genome-wide association studies using large-scale genome and exome sequencing data have become increasingly valuable in identifying associations between genetic variants and disease, transforming basic research and translational medicine. However, this progress has not been equally shared across all people and conditions, in part due to limited resources. Leveraging publicly available sequencing data as external common controls, rather than sequencing new controls for every study, can better allocate resources by augmenting control sample sizes or providing controls where none existed. However, common control studies must be carefully planned and executed as even small differences in sample ascertainment and processing can result in substantial bias. Here, we discuss challenges and opportunities for the robust use of common controls in high-throughput sequencing studies, including study design, quality control and statistical approaches. Thoughtful generation and use of large and valuable genetic sequencing data sets will enable investigation of a broader and more representative set of conditions, environments and genetic ancestries than otherwise possible.
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Affiliation(s)
- Genevieve L Wojcik
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jessica Murphy
- Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, USA
| | - Jacob L Edelson
- Department of Biomedical Data Science, Stanford Medical School, Stanford, CA, USA
| | - Christopher R Gignoux
- Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Alexander G Ioannidis
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Alisa Manning
- Metabolism Program, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Manuel A Rivas
- Department of Biomedical Data Science, Stanford Medical School, Stanford, CA, USA
| | - Steven Buyske
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
| | - Audrey E Hendricks
- Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA.
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, USA.
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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Wu T, Liu Z, Mak TSH, Sham PC. Polygenic power calculator: Statistical power and polygenic prediction accuracy of genome-wide association studies of complex traits. Front Genet 2022; 13:989639. [PMID: 36299579 PMCID: PMC9589038 DOI: 10.3389/fgene.2022.989639] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 09/02/2022] [Indexed: 11/13/2022] Open
Abstract
Power calculation is a necessary step when planning genome-wide association studies (GWAS) to ensure meaningful findings. Statistical power of GWAS depends on the genetic architecture of phenotype, sample size, and study design. While several computer programs have been developed to perform power calculation for single SNP association testing, it might be more appropriate for GWAS power calculation to address the probability of detecting any number of associated SNPs. In this paper, we derive the statistical power distribution across causal SNPs under the assumption of a point-normal effect size distribution. We demonstrate how key outcome indices of GWAS are related to the genetic architecture (heritability and polygenicity) of the phenotype through the power distribution. We also provide a fast, flexible and interactive power calculation tool which generates predictions for key GWAS outcomes including the number of independent significant SNPs, the phenotypic variance explained by these SNPs, and the predictive accuracy of resulting polygenic scores. These results could also be used to explore the future behaviour of GWAS as sample sizes increase further. Moreover, we present results from simulation studies to validate our derivation and evaluate the agreement between our predictions and reported GWAS results.
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Affiliation(s)
- Tian Wu
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Zipeng Liu
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Timothy Shin Heng Mak
- Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Fano Labs, Hong Kong, Hong Kong SAR, China
| | - Pak Chung Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- *Correspondence: Pak Chung Sham,
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Chelu A, Williams SG, Keavney BD, Talavera D. Joint analysis of functionally related genes yields further candidates associated with Tetralogy of Fallot. J Hum Genet 2022; 67:613-615. [PMID: 35718831 PMCID: PMC7613636 DOI: 10.1038/s10038-022-01051-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 05/13/2022] [Accepted: 05/16/2022] [Indexed: 11/09/2022]
Abstract
Although several genes involved in the development of Tetralogy of Fallot have been identified, no genetic diagnosis is available for the majority of patients. Low statistical power may have prevented the identification of further causative genes in gene-by-gene survey analyses. Thus, bigger samples and/or novel analytic approaches may be necessary. We studied if a joint analysis of groups of functionally related genes might be a useful alternative approach. Our reanalysis of whole-exome sequencing data identified 12 groups of genes that exceedingly contribute to the burden of Tetralogy of Fallot. Further analysis of those groups showed that genes with high-impact variants tend to interact with each other. Thus, our results strongly suggest that additional candidate genes may be found by studying the protein interaction network of known causative genes. Moreover, our results show that the joint analysis of functionally related genes can be a useful complementary approach to classical single-gene analyses.
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Affiliation(s)
- Alexandru Chelu
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Simon G Williams
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Bernard D Keavney
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - David Talavera
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
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Attelind S, Hallberg P, Wadelius M, Hamberg AK, Siegbahn A, Granger CB, Lopes RD, Alexander JH, Wallentin L, Eriksson N. Genetic determinants of apixaban plasma levels and their relationship to bleeding and thromboembolic events. Front Genet 2022; 13:982955. [PMID: 36186466 PMCID: PMC9515473 DOI: 10.3389/fgene.2022.982955] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 08/18/2022] [Indexed: 11/13/2022] Open
Abstract
Apixaban is a direct oral anticoagulant, a factor Xa inhibitor, used for the prevention of ischemic stroke in patients with atrial fibrillation. Despite using recommended dosing a few patients might still experience bleeding or lack of efficacy that might be related to inappropriate drug exposure. We conducted a genome-wide association study using data from 1,325 participants in the pivotal phase three trial of apixaban with the aim to identify genetic factors affecting the pharmacokinetics of apixaban. A candidate gene analysis was also performed for pre-specified variants in ABCB1, ABCG2, CYP3A4, CYP3A5, and SULT1A1, with a subsequent analysis of all available polymorphisms within the candidate genes. Significant findings were further evaluated to assess a potential association with clinical outcome such as bleeding or thromboembolic events. No variant was consistently associated with an altered apixaban exposure on a genome-wide level. The candidate gene analyses showed a statistically significant association with a well-known variant in the drug transporter gene ABCG2 (c.421G > T, rs2231142). Patients carrying this variant had a higher exposure to apixaban [area under the curve (AUC), beta = 151 (95% CI 59–243), p = 0.001]. On average, heterozygotes displayed a 5% increase of AUC and homozygotes a 17% increase of AUC, compared with homozygotes for the wild-type allele. Bleeding or thromboembolic events were not significantly associated with ABCG2 rs2231142. This large genome-wide study demonstrates that genetic variation in the drug transporter gene ABCG2 is associated with the pharmacokinetics of apixaban. However, the influence of this finding on drug exposure was small, and further studies are needed to better understand whether it is of relevance for ischemic and bleeding events.
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Affiliation(s)
- Sofia Attelind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Pär Hallberg
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Mia Wadelius
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- *Correspondence: Mia Wadelius,
| | | | - Agneta Siegbahn
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- Uppsala Clinical Research Center, Uppsala University Hospital, Uppsala, Sweden
| | | | - Renato D. Lopes
- Duke Clinical Research Institute, Duke Medicine, Durham, NC, United States
| | - John H. Alexander
- Duke Clinical Research Institute, Duke Medicine, Durham, NC, United States
| | - Lars Wallentin
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- Uppsala Clinical Research Center, Uppsala University Hospital, Uppsala, Sweden
| | - Niclas Eriksson
- Uppsala Clinical Research Center, Uppsala University Hospital, Uppsala, Sweden
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46
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Cavalli M, Eriksson N, Sundbaum JK, Wallenberg M, Kohnke H, Baecklund E, Hallberg P, Wadelius M. Genome-wide association study of liver enzyme elevation in an extended cohort of rheumatoid arthritis patients starting low-dose methotrexate. Pharmacogenomics 2022; 23:813-820. [PMID: 36070248 DOI: 10.2217/pgs-2022-0074] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: A follow-up genome-wide association study (GWAS) in an extended cohort of rheumatoid arthritis (RA) patients starting low-dose methotrexate (MTX) treatment was performed to identify further genetic variants associated with alanine aminotransferase (ALT) elevation. Patients & methods: A GWAS was performed on 346 RA patients. Two outcomes within the first 6 months of MTX treatment were assessed: ALT >1.5-times the upper level of normal (ULN) and maximum level of ALT. Results: SPATA9 (rs72783407) was significantly associated with maximum level of ALT (p = 2.58 × 10-8) and PLCG2 (rs60427389) was tentatively associated with ALT >1.5 × ULN. Conclusion: Associations with SNPs in genes related to male fertility (SPATA9) and inflammatory processes (PLCG2) were identified.
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Affiliation(s)
- Marco Cavalli
- Department of Medical Sciences, Clinical Pharmacogenomics & Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden.,Department of Immunology, Genetics & Pathology, & Science for Life Laboratory, Uppsala University, SE-751 22, Uppsala, Sweden
| | - Niclas Eriksson
- Department of Medical Sciences, Clinical Pharmacogenomics & Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden.,Uppsala Clinical Research Center, SE-751 85, Uppsala, Sweden
| | - Johanna Karlsson Sundbaum
- Department of Medical Sciences, Rheumatology, Uppsala University, SE-751 85, Uppsala, Sweden.,Department of Health Sciences, Luleå University of Technology, SE-971 87, Luleå, Sweden
| | - Matilda Wallenberg
- Department of Medical Sciences, Clinical Pharmacogenomics & Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden.,Svensk Dos AB, Box 2, SE-751 03, Uppsala, Sweden
| | - Hugo Kohnke
- Department of Medical Sciences, Clinical Pharmacogenomics & Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden
| | - Eva Baecklund
- Department of Medical Sciences, Rheumatology, Uppsala University, SE-751 85, Uppsala, Sweden
| | - Pär Hallberg
- Department of Medical Sciences, Clinical Pharmacogenomics & Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden
| | - Mia Wadelius
- Department of Medical Sciences, Clinical Pharmacogenomics & Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden
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47
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Paszkiewicz-Kozik E, Kluska A, Piątkowska M, Bałabas A, Żeber-Lubecka N, Karczmarski J, Goryca K, Kulecka M, Wojciechowska-Lampka E, Osiadacz W, Romejko-Jarosińska J, Świerkowska M, Paziewska A, Ambrożkiewicz F, Walewski J, Mikula M, Ostrowski J. Genetic associations with lymphomas in Polish patients: A pooled-DNA genome-wide association analysis. Int J Immunogenet 2022; 49:353-363. [PMID: 36036752 DOI: 10.1111/iji.12596] [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: 05/16/2022] [Revised: 07/26/2022] [Accepted: 08/10/2022] [Indexed: 11/29/2022]
Abstract
Several single nucleotide polymorphisms (SNPs) associated with susceptibility to Hodgkin lymphoma (HL) and diffuse large B-cell lymphoma (DLBCL) have been identified. The aim of this study was to identify susceptibility loci for HL and DLBCL in Polish patients. Altogether, DLBCL (n = 218 and HL patients (n = 224) and healthy individuals (n = 1181) were recruited. Lymphoma diagnosis was based on standard criteria. Genome-wide association study (GWAS) was performed using pooled-DNA samples on llumina Infinium Omni2.5 Exome-8 v1.3, and selected loci were replicated by TaqMan SNP genotyping of individuals. GWAS detected thirteen and seven SNPs associated with DLBCL and HL, respectively. In the replication study, six and seven SNPs reached significance after correction for multiple testing in the DLBCL and HL cohorts, respectively. One and four SNPs associated with DLBCL and HL, respectively, were localized within, and two SNPs-near the major histocompatibility complex (MHC) region. In conclusion, the majority of loci associated with HL and DLBCL aetiology in previous studies have potential roles in immune function. Our pooled-DNA GWAS enabled the identification of several susceptibility loci for DLBCL and HL in the Polish population; some of them were mapped within or adjacent to the MHC, and other associated SNPs were located outside the MHC.
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Affiliation(s)
- Ewa Paszkiewicz-Kozik
- Department of Lymphoproliferative Diseases, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Anna Kluska
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Magdalena Piątkowska
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Aneta Bałabas
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Natalia Żeber-Lubecka
- Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - Jakub Karczmarski
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Krzysztof Goryca
- Genomics Core Facility, Centre of New Technologies, University of Warsaw, Warsaw, Poland
| | - Maria Kulecka
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland.,Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - Elżbieta Wojciechowska-Lampka
- Department of Lymphoproliferative Diseases, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Włodzimierz Osiadacz
- Department of Lymphoproliferative Diseases, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Joanna Romejko-Jarosińska
- Department of Lymphoproliferative Diseases, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Monika Świerkowska
- Department of Lymphoproliferative Diseases, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Agnieszka Paziewska
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland.,Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - Filip Ambrożkiewicz
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Jan Walewski
- Department of Lymphoproliferative Diseases, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Michał Mikula
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Jerzy Ostrowski
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland.,Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, Warsaw, Poland
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48
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Arab Y, Choueiter N, Dahdah N, El-Kholy N, Abu Al-Saoud SY, Abu-Shukair ME, Agha HM, Al-Saloos H, Al Senaidi KS, Alzyoud R, Bouaziz A, Boukari R, El Ganzoury MM, Elmarsafawy HM, ELrugige N, Fitouri Z, Ladj MS, Mouawad P, Salih AF, Rojas RG, Harahsheh AS. Kawasaki Disease Arab Initiative [Kawarabi]: Establishment and Results of a Multicenter Survey. Pediatr Cardiol 2022; 43:1239-1246. [PMID: 35624313 PMCID: PMC9140321 DOI: 10.1007/s00246-022-02844-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 02/03/2022] [Indexed: 11/13/2022]
Abstract
Studies on Kawasaki disease (KD) in Arab countries are scarce, often providing incomplete data. This along with the benefits of multicenter research collaboratives led to the creation of the KD Arab Initiative [Kawarabi] consortium. An anonymous survey was completed among potential collaborative Arab medical institutions to assess burden of KD in those countries and resources available to physicians. An online 32-item survey was distributed to participating institutions after conducting face validity. One survey per institution was collected. Nineteen physicians from 12 countries completed the survey representing 19 out of 20 institutions (response rate of 95%). Fifteen (79%) institutions referred to the 2017 American Heart Association guidelines when managing a patient with KD. Intravenous immunoglobulin (IVIG) is not readily available at 2 institutions (11%) yet available in the country. In one center (5%), IVIG is imported on-demand. The knowledge and awareness among countries' general population was graded (0 to 10) at median/interquartiles (IQR) 3 (2-5) and at median/IQR 7 (6-8) in the medical community outside their institution. Practice variations in KD management and treatment across Arab countries require solid proactive collaboration. The low awareness and knowledge estimates about KD among the general population contrasted with a high level among the medical community. The Kawarabi collaborative will offer a platform to assess disease burden of KD, among Arab population, decrease practice variation and foster population-based knowledge.
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Affiliation(s)
- Yousra Arab
- University of Sherbrooke, Sherbrooke, QC Canada
| | - Nadine Choueiter
- Department of Pediatrics, Albert Einstein College of Medicine, Children’s Hospital at Montefiore, 3415 Bainbridge Ave, Bronx, NY 10467 USA
| | - Nagib Dahdah
- Division of Pediatric Cardiology, CHU Ste-Justine, Université de Montréal, 3175 Côte Sainte-Catherine, Montreal, QC H3T 1C5 Canada
| | - Nermeen El-Kholy
- Pediatric Cardiology Department, AlJalila Children’s Specialty Hospital, Dubai, United Arab Emirates
- Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | - Sima Y. Abu Al-Saoud
- Department of Pediatrics, Makassed Hospital, Faculty of Medicine, Al- Quds University, East-Jerusalem, Palestine
| | | | - Hala M. Agha
- Pediatric Cardiology Division, Cairo University, Cairo, Egypt
| | - Hesham Al-Saloos
- Division of Cardiology, Sidra Medicine, Doha, Qatar
- Clinical Pediatrics, Weill Cornell Medicine, Doha, Qatar
| | | | - Raed Alzyoud
- Pediatric Immunology, Allergy, and Rheumatology Division, Queen Rania Children’s Hospital, Amman, Jordan
| | - Asma Bouaziz
- Headmaster of Children and Neonatal Department, Hôpital Régional, Ben Arous, Tunisia
| | - Rachida Boukari
- Pediatric Department, University Hospital Mustapha Bacha, Algiers University, Algiers, Algeria
| | - Mona M. El Ganzoury
- Pediatric Cardiology Division, Department of Pediatrics, Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - Hala M. Elmarsafawy
- Pediatric Cardiology Division, Children Hospital, Mansoura University, Mansoura, Egypt
| | - Najat ELrugige
- Pediatric Cardiology Department, Benghazi Children Hospital, Faculty of Medicine, Benghazi University, Benghazi, Libya
| | - Zohra Fitouri
- Unit of Rheumatology, Emergency and Outpatient Department, Pediatric Hospital of Béchir Hamza of Tunis, University Tunis El Manar, 1007 Djebel Lakhedher Bab Saadoun, Tunis, Tunisia
| | - Mohamed S. Ladj
- Pediatric Department, Djillali Belkhenchir University Hospital, Algiers, Algeria
- Faculty of Medicine, Algiers University, Algiers, Algeria
| | - Pierre Mouawad
- Pediatric Department, Saint George Hospital University Medical Center, Beirut, Lebanon
| | - Aso F. Salih
- Pediatric Cardiology Department/Children’s Heart Hospital- Sulaimani College of Medicine- Sulaimani University, Al-Sulaimaniyah, Iraq
| | - Rocio G. Rojas
- Clinical Research Program, Division of Pediatric Cardiology, CHU Sainte-Justine, Montreal, QC H3T 1C5 Canada
| | - Ashraf S. Harahsheh
- Division of Cardiology, Department of Pediatrics, Children’s National Hospital, George Washington University School of Medicine & Health Sciences, 111 Michigan Ave, NW, Washington, DC 20010 USA
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49
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Li Y, Nieuwenhuis LM, Keating BJ, Festen EA, de Meijer VE. The Impact of Donor and Recipient Genetic Variation on Outcomes After Solid Organ Transplantation: A Scoping Review and Future Perspectives. Transplantation 2022; 106:1548-1557. [PMID: 34974452 PMCID: PMC9311456 DOI: 10.1097/tp.0000000000004042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 11/16/2021] [Accepted: 11/25/2021] [Indexed: 11/25/2022]
Abstract
At the outset of solid organ transplantation, genetic variation between donors and recipients was recognized as a major player in mechanisms such as allograft tolerance and rejection. Genome-wide association studies have been very successful in identifying novel variant-trait associations, but have been difficult to perform in the field of solid organ transplantation due to complex covariates, era effects, and poor statistical power for detecting donor-recipient interactions. To overcome a lack of statistical power, consortia such as the International Genetics and Translational Research in Transplantation Network have been established. Studies have focused on the consequences of genetic dissimilarities between donors and recipients and have reported associations between polymorphisms in candidate genes or their regulatory regions with transplantation outcomes. However, knowledge on the exact influence of genetic variation is limited due to a lack of comprehensive characterization and harmonization of recipients' or donors' phenotypes and validation using an experimental approach. Causal research in genetics has evolved from agnostic discovery in genome-wide association studies to functional annotation and clarification of underlying molecular mechanisms in translational studies. In this overview, we summarize how the recent advances and progresses in the field of genetics and genomics have improved the understanding of outcomes after solid organ transplantation.
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Affiliation(s)
- Yanni Li
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Lianne M. Nieuwenhuis
- Department of Surgery, section of Hepatobiliary Surgery and Liver Transplantation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Brendan J. Keating
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Eleonora A.M. Festen
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Vincent E. de Meijer
- Department of Surgery, section of Hepatobiliary Surgery and Liver Transplantation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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50
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Grau-Pujol B, Gandasegui J, Escola V, Marti-Soler H, Cambra-Pellejà M, Demontis M, Brienen EAT, Jamine JC, Muchisse O, Cossa A, Sacoor C, Cano J, Van Lieshout L, Martinez-Valladares M, Muñoz J. Single-Nucleotide Polymorphisms in the Beta-Tubulin Gene and Its Relationship with Treatment Response to Albendazole in Human Soil-Transmitted Helminths in Southern Mozambique. Am J Trop Med Hyg 2022; 107:tpmd210948. [PMID: 35895348 PMCID: PMC9490645 DOI: 10.4269/ajtmh.21-0948] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 05/02/2022] [Indexed: 11/17/2022] Open
Abstract
Soil-transmitted helminth (STH) cornerstone control strategy is mass drug administration (MDA) with benzimidazoles. However, MDA might contribute to selection pressure for anthelmintic resistance, as occurred in livestock. The aim of this study is to evaluate the treatment response to albendazole and the relationship with the presence of putative benzimidazole resistance single-nucleotide polymorphisms (SNPs) in the β-tubulin gene of STH in Southern Mozambique. After screening 819 participants, we conducted a cohort study with 184 participants infected with STH in Manhiça district, Southern Mozambique. A pretreatment and a posttreatment stool samples were collected and the STH infection was identified by duplicate Kato-Katz and quantitative polymerase chain reaction (qPCR). Cure rate and egg reduction rates were calculated. Putative benzimidazole resistance SNPs (F167Y, F200T, and E198A) in Trichuris trichiura and Necator americanus were assessed by pyrosequencing. Cure rates by duplicate Kato-Katz and by qPCR were 95.8% and 93.6% for Ascaris lumbricoides, 28% and 7.8% for T. trichiura, and 88.9% and 56.7% for N. americanus. Egg reduction rate by duplicate Kato-Katz was 85.4% for A. lumbricoides, 34.9% for T. trichiura, and 40.5% for N. americanus. Putative benzimidazole resistance SNPs in the β-tubulin gene were detected in T. trichiura (23%) and N. americanus (21%) infected participants at pretreatment. No statistical difference was observed between pretreatment and posttreatment frequencies for none of the SNPs. Although treatment response to albendazole was low, particularly in T. trichiura, the putative benzimidazole resistance SNPs were not higher after treatment in the population studied. New insights are needed for a better understanding and monitoring of human anthelmintic resistance.
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Affiliation(s)
- Berta Grau-Pujol
- Barcelona Institute for Global Health (ISGlobal), Hospital Clínic – University of Barcelona, Barcelona, Spain
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
- Mundo Sano Foundation, Buenos Aires, Argentina
| | - Javier Gandasegui
- Instituto de Ganadería de Montaña (CSIC-Universidad de León), Grulleros, León, Spain
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana, León, Spain
| | - Valdemiro Escola
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | - Helena Marti-Soler
- Barcelona Institute for Global Health (ISGlobal), Hospital Clínic – University of Barcelona, Barcelona, Spain
| | - Maria Cambra-Pellejà
- Instituto de Ganadería de Montaña (CSIC-Universidad de León), Grulleros, León, Spain
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana, León, Spain
| | - Maria Demontis
- Department of Parasitology, Centre of Infectious Diseases, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Eric A. T. Brienen
- Department of Parasitology, Centre of Infectious Diseases, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | | | - Osvaldo Muchisse
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | - Anelsio Cossa
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | - Charfudin Sacoor
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | - Jorge Cano
- Expanded Special Project for Elimination of NTDs, World Health Organization Regional Office for Africa, Brazzaville, The Republic of the Congo
| | - Lisette Van Lieshout
- Department of Parasitology, Centre of Infectious Diseases, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Maria Martinez-Valladares
- Instituto de Ganadería de Montaña (CSIC-Universidad de León), Grulleros, León, Spain
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana, León, Spain
| | - Jose Muñoz
- Barcelona Institute for Global Health (ISGlobal), Hospital Clínic – University of Barcelona, Barcelona, Spain
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