1
|
Schweiger R, Lee S, Zhou C, Yang TP, Smith K, Li S, Sanghvi R, Neville M, Mitchell E, Nessa A, Wadge S, Small KS, Campbell PJ, Sudmant PH, Rahbari R, Durbin R. Insights into non-crossover recombination from long-read sperm sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.05.602249. [PMID: 39005338 PMCID: PMC11245106 DOI: 10.1101/2024.07.05.602249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Meiotic recombination is a fundamental process that generates genetic diversity by creating new combinations of existing alleles. Although human crossovers have been studied at the pedigree, population and single-cell level, the more frequent non-crossover events that lead to gene conversion are harder to study, particularly at the individual level. Here we show that single high-fidelity long sequencing reads from sperm can capture both crossovers and non-crossovers, allowing effectively arbitrary sample sizes for analysis from one male. Using fifteen sperm samples from thirteen donors we demonstrate variation between and within donors for the rates of different types of recombination. Intriguingly, we observe a tendency for non-crossover gene conversions to occur upstream of nearby PRDM9 binding sites, whereas crossover locations have a slight downstream bias. We further provide evidence for two distinct non-crossover processes. One gives rise to the vast majority of non-crossovers with mean conversion tract length under 50bp, which we suggest is an outcome of standard PRDM9-induced meiotic recombination. In contrast ~2% of non-crossovers have much longer mean tract length, and potentially originate from the same process as complex events with more than two haplotype switches, which is not associated with PRDM9 binding sites and is also seen in somatic cells.
Collapse
Affiliation(s)
- Regev Schweiger
- Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, United Kingdom
| | - Sangjin Lee
- Wellcome Sanger Institute, Cancer Ageing and Somatic Mutation, Hinxton, Cambridge CB10 1SA, United Kingdom
| | - Chenxi Zhou
- Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, United Kingdom
| | - Tsun-Po Yang
- Wellcome Sanger Institute, Cancer Ageing and Somatic Mutation, Hinxton, Cambridge CB10 1SA, United Kingdom
| | - Katie Smith
- Wellcome Sanger Institute, Cancer Ageing and Somatic Mutation, Hinxton, Cambridge CB10 1SA, United Kingdom
| | - Stacy Li
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
| | - Rashesh Sanghvi
- Wellcome Sanger Institute, Cancer Ageing and Somatic Mutation, Hinxton, Cambridge CB10 1SA, United Kingdom
| | - Matthew Neville
- Wellcome Sanger Institute, Cancer Ageing and Somatic Mutation, Hinxton, Cambridge CB10 1SA, United Kingdom
| | - Emily Mitchell
- Wellcome Sanger Institute, Cancer Ageing and Somatic Mutation, Hinxton, Cambridge CB10 1SA, United Kingdom
| | - Ayrun Nessa
- Kings College London, Department of Twin Research & Genetic Epidemiology, London, United Kingdom
| | - Sam Wadge
- Kings College London, Department of Twin Research & Genetic Epidemiology, London, United Kingdom
| | - Kerrin S Small
- Kings College London, Department of Twin Research & Genetic Epidemiology, London, United Kingdom
| | - Peter J Campbell
- Wellcome Sanger Institute, Cancer Ageing and Somatic Mutation, Hinxton, Cambridge CB10 1SA, United Kingdom
- Wellcome-MRC Cambridge Stem Cell Institute, Cambridge Biomedical Campus, Cambridge, UK
| | - Peter H Sudmant
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
- Center for Computational Biology, University of California Berkeley, Berkeley, USA
| | - Raheleh Rahbari
- Wellcome Sanger Institute, Cancer Ageing and Somatic Mutation, Hinxton, Cambridge CB10 1SA, United Kingdom
| | - Richard Durbin
- Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, United Kingdom
- Wellcome Sanger Institute, Cancer Ageing and Somatic Mutation, Hinxton, Cambridge CB10 1SA, United Kingdom
| |
Collapse
|
2
|
Xu R, Liu S, Li LY, Bu Y, Bai PM, Luo GC, Wang XJ. Exploring the causal association between serum metabolites and erectile dysfunction: a bidirectional Mendelian randomisation study. Int J Impot Res 2024:10.1038/s41443-024-00926-2. [PMID: 38858529 DOI: 10.1038/s41443-024-00926-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 05/23/2024] [Accepted: 05/31/2024] [Indexed: 06/12/2024]
Abstract
Erectile dysfunction is a common sexual disorder in men. Some studies have found a strong association between some serum metabolites and erectile dysfunction. To investigate this association further, we used bidirectional Mendelian randomisation to investigate causality and possible biological mechanisms.Firstly, this study screened the statistics of genome-wide association studies of serum metabolites and erectile dysfunction to obtain instrumental variables. Inverse variance weighting was used as the primary method for causal effect analysis of instrumental variables in forward or reverse Mendelian randomisation, and the results obtained by MR-Egger regression and the weighted median method were used as references. Subsequently, the metabolites causally associated with erectile dysfunction were subjected to replication analyses and meta-analyses, and the results of the meta-analyses were analysed by pathway analyses to find influential pathways. In this process, Mendelian randomisation results need to be assessed for stability and reliability using sensitivity analysis.It was found that a total of six serum metabolites were causally associated with erectile dysfunction in a forward Mendelian randomisation study. 1,3,7-trimethyluraten (0.85 (0.73-0.99), P = 0.0368), ergothioneine (0.65 (0.45-0.94), P = 0.0226) and gamma-glutamylglutamate (0.63 (0.46-0.88), P = 0.0059) were protective against the development of erectile dysfunction, whereas 2-hydroxyhippurate (1.10 (1.02-1.19), P = 0.0152), N2,N2-dimethylguanosine (1.57 (1.02-2.40), P = 0.0395) and octanoylcarnitine (1.38 (1.06-1.82), P = 0.0183) were able to induce the development of erectile dysfunction. In addition, metabolic pathway analysis showed that 1,3,7-trimethylurate was able to influence the development of erectile dysfunction via the caffeine metabolism pathway (P = 0.0454). On the other hand, reverse Mendelian randomisation analysis showed that erectile dysfunction reduced serum homocitrulline levels (0.99 (0.97-1.00), P = 0.0360). Sensitivity analyses, including heterogeneity tests and pleiotropy tests, confirmed the reliability of the results.In conclusion, this study demonstrated a bidirectional causal relationship between serum metabolites and erectile dysfunction using bidirectional Mendelian randomisation analysis and replication meta-analysis. On this basis, this study provides a new direction of thinking and strong evidence for the therapeutic application and adjunctive diagnosis of serum metabolites in erectile dysfunction, and provides a certain reference value for subsequent related studies.
Collapse
Affiliation(s)
- Ran Xu
- Department of Urology, Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Shuo Liu
- Department of Urology, Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Lu-Yi Li
- Department of Urology, Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Yue Bu
- Department of Urology, Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Pei-Ming Bai
- Department of Urology, Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Guang-Cheng Luo
- Department of Urology, Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen, China
- Department of Urology, Zhongshan Hospital Xiamen University, The School of Clinical Medicine, Fujian Medical University, Xiamen, China
| | - Xin-Jun Wang
- Department of Urology, Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
- Department of Urology, Zhongshan Hospital Xiamen University, The School of Clinical Medicine, Fujian Medical University, Xiamen, China.
| |
Collapse
|
3
|
Reyes-Pérez P, Hernández-Ledesma AL, Román-López TV, García-Vilchis B, Ramírez-González D, Lázaro-Figueroa A, Martinez D, Flores-Ocampo V, Espinosa-Méndez IM, Tinajero-Nieto L, Peña-Ayala A, Morelos-Figaredo E, Guerra-Galicia CM, Torres-Valdez E, Gordillo-Huerta MV, Gandarilla-Martínez NA, Salinas-Barboza K, Félix-Rodríguez G, Frontana-Vázquez G, Matuk-Pérez Y, Estrada-Bellmann I, Alpizar-Rodríguez D, Rodríguez-Violante M, Rentería ME, Ruíz-Contreras AE, Alcauter S, Medina-Rivera A. Building national patient registries in Mexico: insights from the MexOMICS Consortium. Front Digit Health 2024; 6:1344103. [PMID: 38895515 PMCID: PMC11183280 DOI: 10.3389/fdgth.2024.1344103] [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: 11/27/2023] [Accepted: 05/01/2024] [Indexed: 06/21/2024] Open
Abstract
Objective To introduce MexOMICS, a Mexican Consortium focused on establishing electronic databases to collect, cross-reference, and share health-related and omics data on the Mexican population. Methods Since 2019, the MexOMICS Consortium has established three electronic-based registries: the Mexican Twin Registry (TwinsMX), Mexican Lupus Registry (LupusRGMX), and the Mexican Parkinson's Research Network (MEX-PD), designed and implemented using the Research Electronic Data Capture web-based application. Participants were enrolled through voluntary participation and on-site engagement with medical specialists. We also acquired DNA samples and Magnetic Resonance Imaging scans in subsets of participants. Results The registries have successfully enrolled a large number of participants from a variety of regions within Mexico: TwinsMX (n = 2,915), LupusRGMX (n = 1,761) and MEX-PD (n = 750). In addition to sociodemographic, psychosocial, and clinical data, MexOMICS has collected DNA samples to study the genetic biomarkers across the three registries. Cognitive function has been assessed with the Montreal Cognitive Assessment in a subset of 376 MEX-PD participants. Furthermore, a subset of 267 twins have participated in cognitive evaluations with the Creyos platform and in MRI sessions acquiring structural, functional, and spectroscopy brain imaging; comparable evaluations are planned for LupusRGMX and MEX-PD. Conclusions The MexOMICS registries offer a valuable repository of information concerning the potential interplay of genetic and environmental factors in health conditions among the Mexican population.
Collapse
Affiliation(s)
- Paula Reyes-Pérez
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Ana Laura Hernández-Ledesma
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Talía V. Román-López
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Brisa García-Vilchis
- Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación de Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Diego Ramírez-González
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Alejandra Lázaro-Figueroa
- Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación de Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Domingo Martinez
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
- Unidad de Genómica Avanzada, Langebio, Centro de Investigación y Estudios Avanzados del Instituto Politécnico Nacional, Irapuato, Mexico
- Escuela Nacional de Estudios Superiores, Unidad Juriquilla, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Victor Flores-Ocampo
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Ian M. Espinosa-Méndez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Lizbet Tinajero-Nieto
- Hospital General Regional No. 1, Instituto Mexicano del Seguro Social, Querétaro, Santiago de Querétaro, Mexico
| | - Angélica Peña-Ayala
- Hospital General Regional No. 1, Instituto Mexicano del Seguro Social, Querétaro, Santiago de Querétaro, Mexico
- Instituto Nacional de Rehabilitación “Luis Guillermo Ibarra Ibarra”, Ciudad de México, Mexico
| | - Eugenia Morelos-Figaredo
- Hospital Regional, Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado, Morelia, Mexico
| | | | | | - María Vanessa Gordillo-Huerta
- Hospital General Querétaro, Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado, Santiago de Querétaro, Mexico
| | | | | | | | | | - Yamil Matuk-Pérez
- Facultad de Medicina, Universidad Autónoma de Querétaro. Unidad de Neurociencias, Hospital Angeles Centro Sur, Santiago de Querétaro, Mexico
| | - Ingrid Estrada-Bellmann
- Movement Disorders Clinic, Neurology Division, Internal Medicine Department, University Hospital “Dr. José E. González”, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | | | - Mayela Rodríguez-Violante
- Laboratorio Clínico de Enfermedades Neurodegenerativas, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City, Mexico
| | - Miguel E. Rentería
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Alejandra E. Ruíz-Contreras
- Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación de Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
| | - Sarael Alcauter
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Alejandra Medina-Rivera
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| |
Collapse
|
4
|
Bettim CA, da Silva AV, Kahmann A, Dorn M, Alho CS, Avila E. MC1R and age heteroclassification of face phenotypes in the Rio Grande do Sul population. Int J Legal Med 2024; 138:859-872. [PMID: 38087053 DOI: 10.1007/s00414-023-03143-6] [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: 06/01/2023] [Accepted: 11/22/2023] [Indexed: 04/11/2024]
Abstract
BACKGROUND Forensic DNA phenotyping (FDP) consists of the use of methodologies for predicting externally visible characteristics (EVCs) from the genetic material of biological samples found in crime scenes and has proven to be a promising tool in aiding human identification in police activities. Currently, methods based on multiplex assays and statistical models of prediction of EVCs related to hair, skin, and iris pigmentation using panels of SNP and INDEL biomarkers have already been developed and validated by the forensic scientific community. As well as traces of pigmentation, an individual's perceived age (PA) can also be considered an EVC and its estimation in unknown individuals can be useful for the progress of investigations. Liu and colleagues (2016) were pioneers in evidencing that, in addition to lifestyle and environmental factors, the presence of SNP and INDEL variants in the MC1R gene - which encodes a transmembrane receptor responsible for regulating melanin production - seems to contribute to an individual's PA. The group highlighted the association between these MC1R gene polymorphisms and the PA in the European population, where carriers of risk haplotypes appeared to be up to 2 years older in comparison to their chronological age (CA). PURPOSE Understanding that genotype-phenotype relationships cannot be extrapolated between different population groups, this study aimed to test this hypothesis and verify the applicability of this variant panel in the Rio Grande do Sul admixed population. METHODS Based on genomic data from a sample of 261 volunteers representative of gaucho population and using a multiple linear regression (MLR) model, our group was able to verify a significant association among nine intronic variants in loci adjacent to MC1R (e.g., AFG3L1P, TUBB3, FANCA) and facial age appearance, whose PA was defined after age heteroclassification of standard frontal face images through 11 assessors. RESULTS Different from that observed in European populations, our results show that the presence of effect alleles (R) of the selected variants in our sample influenced both younger and older face phenotypes. The influence of each variant on PA is expressed as β values. CONCLUSIONS There are important molecular mechanisms behind the effects of MC1R locus on PA, and the genomic background of each population seems to be crucial to determine this influence.
Collapse
Affiliation(s)
- Cássio Augusto Bettim
- Structural Bioinformatics and Computational Biology Lab, Institute of Informatics, Federal University of Rio Grande Do Sul, Porto Alegre, RS, Brazil
- National Science and Technology Institute for Forensic Science, Porto Alegre, RS, Brazil
| | - Alexsandro Vasconcellos da Silva
- National Science and Technology Institute for Forensic Science, Porto Alegre, RS, Brazil
- Technical Scientific and Identification Sections, Superintendency of Federal Police in Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Alessandro Kahmann
- National Science and Technology Institute for Forensic Science, Porto Alegre, RS, Brazil.
- National Science and Technology Institute for Children Cancer Biology and Pediatric Oncology, Porto Alegre, RS, Brazil.
- Interdisciplinary Department, Federal University of Rio Grande Do Sul, Tramandaí, RS, Brazil.
| | - Márcio Dorn
- Structural Bioinformatics and Computational Biology Lab, Institute of Informatics, Federal University of Rio Grande Do Sul, Porto Alegre, RS, Brazil
- National Science and Technology Institute for Forensic Science, Porto Alegre, RS, Brazil
- National Science and Technology Institute for Children Cancer Biology and Pediatric Oncology, Porto Alegre, RS, Brazil
| | - Clarice Sampaio Alho
- National Science and Technology Institute for Forensic Science, Porto Alegre, RS, Brazil
- National Science and Technology Institute for Children Cancer Biology and Pediatric Oncology, Porto Alegre, RS, Brazil
| | - Eduardo Avila
- National Science and Technology Institute for Forensic Science, Porto Alegre, RS, Brazil
- Technical Scientific and Identification Sections, Superintendency of Federal Police in Rio Grande do Sul, Porto Alegre, RS, Brazil
- National Science and Technology Institute for Children Cancer Biology and Pediatric Oncology, Porto Alegre, RS, Brazil
| |
Collapse
|
5
|
Liu S, Zhong H, Zhu J, Wu L. Identification of blood metabolites associated with risk of Alzheimer's disease by integrating genomics and metabolomics data. Mol Psychiatry 2024; 29:1153-1162. [PMID: 38216726 PMCID: PMC11176029 DOI: 10.1038/s41380-023-02400-9] [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: 04/04/2023] [Revised: 12/17/2023] [Accepted: 12/22/2023] [Indexed: 01/14/2024]
Abstract
Specific metabolites have been reported to be potentially associated with Alzheimer's disease (AD) risk. However, the comprehensive understanding of roles of metabolite biomarkers in AD etiology remains elusive. We performed a large AD metabolome-wide association study (MWAS) by developing blood metabolite genetic prediction models. We evaluated associations between genetically predicted levels of metabolites and AD risk in 39,106 clinically diagnosed AD cases, 46,828 proxy AD and related dementia (proxy-ADD) cases, and 401,577 controls. We further conducted analyses to determine microbiome features associated with the detected metabolites and characterize associations between predicted microbiome feature levels and AD risk. We identified fourteen metabolites showing an association with AD risk. Five microbiome features were further identified to be potentially related to associations of five of the metabolites. Our study provides new insights into the etiology of AD that involves blood metabolites and gut microbiome, which warrants further investigation.
Collapse
Affiliation(s)
- Shuai Liu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Hua Zhong
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Jingjing Zhu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA.
| |
Collapse
|
6
|
Scott B, Day EA, O'Brien KL, Scanlan J, Cromwell G, Scannail AN, McDonnell ME, Finlay DK, Lynch L. Metformin and feeding increase levels of the appetite-suppressing metabolite Lac-Phe in humans. Nat Metab 2024; 6:651-658. [PMID: 38499765 PMCID: PMC11052712 DOI: 10.1038/s42255-024-01018-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 02/22/2024] [Indexed: 03/20/2024]
Abstract
Metformin, a widely used first-line treatment for type 2 diabetes (T2D), is known to reduce blood glucose levels and suppress appetite. Here we report a significant elevation of the appetite-suppressing metabolite N-lactoyl phenylalanine (Lac-Phe) in the blood of individuals treated with metformin across seven observational and interventional studies. Furthermore, Lac-Phe levels were found to rise in response to acute metformin administration and post-prandially in patients with T2D or in metabolically healthy volunteers.
Collapse
Affiliation(s)
- Barry Scott
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Emily A Day
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Katie L O'Brien
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - John Scanlan
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Grace Cromwell
- Division of Endocrinology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Aine Ni Scannail
- Division of Endocrinology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marie E McDonnell
- Division of Endocrinology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - David K Finlay
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
- School of Pharmacy and Pharmaceutical Sciences, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Lydia Lynch
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
- Division of Endocrinology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
7
|
Reay WR, Kiltschewskij DJ, Di Biase MA, Gerring ZF, Kundu K, Surendran P, Greco LA, Clarke ED, Collins CE, Mondul AM, Albanes D, Cairns MJ. Genetic influences on circulating retinol and its relationship to human health. Nat Commun 2024; 15:1490. [PMID: 38374065 PMCID: PMC10876955 DOI: 10.1038/s41467-024-45779-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: 08/23/2023] [Accepted: 02/04/2024] [Indexed: 02/21/2024] Open
Abstract
Retinol is a fat-soluble vitamin that plays an essential role in many biological processes throughout the human lifespan. Here, we perform the largest genome-wide association study (GWAS) of retinol to date in up to 22,274 participants. We identify eight common variant loci associated with retinol, as well as a rare-variant signal. An integrative gene prioritisation pipeline supports novel retinol-associated genes outside of the main retinol transport complex (RBP4:TTR) related to lipid biology, energy homoeostasis, and endocrine signalling. Genetic proxies of circulating retinol were then used to estimate causal relationships with almost 20,000 clinical phenotypes via a phenome-wide Mendelian randomisation study (MR-pheWAS). The MR-pheWAS suggests that retinol may exert causal effects on inflammation, adiposity, ocular measures, the microbiome, and MRI-derived brain phenotypes, amongst several others. Conversely, circulating retinol may be causally influenced by factors including lipids and serum creatinine. Finally, we demonstrate how a retinol polygenic score could identify individuals more likely to fall outside of the normative range of circulating retinol for a given age. In summary, this study provides a comprehensive evaluation of the genetics of circulating retinol, as well as revealing traits which should be prioritised for further investigation with respect to retinol related therapies or nutritional intervention.
Collapse
Affiliation(s)
- William R Reay
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia.
- Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia.
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia.
| | - Dylan J Kiltschewskij
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Maria A Di Biase
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- Department of Anatomy and Physiology, The University of Melbourne, Melbourne, VIC, Australia
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Zachary F Gerring
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Kousik Kundu
- Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Praveen Surendran
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK, Wellcome Genome Campus and University of Cambridge, Hinxton, UK
| | - Laura A Greco
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Erin D Clarke
- School of Health Sciences, The University of Newcastle, Callaghan, NSW, Australia
- Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Clare E Collins
- School of Health Sciences, The University of Newcastle, Callaghan, NSW, Australia
- Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Alison M Mondul
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, MD, USA
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia.
- Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia.
| |
Collapse
|
8
|
Singh A, Georgy JT, Dhananjayan S, Sigamani E, John AO, Joel A, Chandramohan J, Abarna R, Rebekah G, Backianathan S, Abraham DT, Paul MJ, Chacko RT, Manipadam MT, Pai R. Comparative analysis of mutational patterns in triple negative breast cancer before and after neoadjuvant chemotherapy in patients with residual disease. Gene 2024; 895:147980. [PMID: 37951371 DOI: 10.1016/j.gene.2023.147980] [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: 06/07/2023] [Revised: 09/13/2023] [Accepted: 11/08/2023] [Indexed: 11/14/2023]
Abstract
Triple-negative breast cancer (TNBC) is a heterogeneous disease with poor survival compared to other subtypes. Patients with residual disease after neoadjuvant chemotherapy (NAC) face an increased risk of relapse and death. We aimed to characterize the mutational landscape of this subset to offer insights into relapse pathogenesis and potential therapeutic targets. We retrospectively analyzed archived paired (pre- and post-NAC) tumor samples from 25 patients with TNBC with residual disease using a targeted 72-gene next-generation sequencing panel. Our findings revealed a stable mutational burden in both pre- and post-NAC samples, with a median count of 12 variants (IQR 7-17.25) per sample. TP53, PMS2, PTEN, ERBB2, and NOTCH1 variants were observed in pre-NAC samples predominantly. Notably, post-NAC samples exhibited a significant increase in AR gene mutations, suggesting potential prognostic and predictive implications. No difference in mutational burden was found between patients who did and did not receive platinum (p = 0.94), or between those with and without recurrence (p = 0.49). We employed K-means clustering to categorize the patients based on their variant profiles, aiding in the prediction of possible patterns associated with recurrence. Our study was limited by its small sample size and retrospective design, suggesting the need for further validation in larger prospective cohorts.
Collapse
Affiliation(s)
- Ashish Singh
- Department of Medical Oncology, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Josh Thomas Georgy
- Department of Medical Oncology, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Sakthi Dhananjayan
- Department of Pathology, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Elanthenral Sigamani
- Department of Pathology, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Ajoy Oommen John
- Department of Medical Oncology, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Anjana Joel
- Department of Medical Oncology, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Jagan Chandramohan
- Department of Pathology, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Rajadurai Abarna
- Department of Pathology, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Grace Rebekah
- Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Selvamani Backianathan
- Department of Radiotherapy, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | - Deepak Thomas Abraham
- Department of Endocrine Surgery, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | | | - Raju Titus Chacko
- Department of Medical Oncology, Christian Medical College, Vellore, Tamil Nadu 632004, India
| | | | - Rekha Pai
- Department of Pathology, Christian Medical College, Vellore, Tamil Nadu 632004, India.
| |
Collapse
|
9
|
Xu X, Wu LY, Wang SY, Yan M, Wang YH, Li L, Sun ZL, Zhao JX. Investigating causal associations among gut microbiota, metabolites, and psoriatic arthritis: a Mendelian randomization study. Front Microbiol 2024; 15:1287637. [PMID: 38426052 PMCID: PMC10902440 DOI: 10.3389/fmicb.2024.1287637] [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: 09/02/2023] [Accepted: 01/24/2024] [Indexed: 03/02/2024] Open
Abstract
Background Currently, there has been observed a significant alteration in the composition of the gut microbiome (GM) and serum metabolites in patients with psoriatic arthritis (PsA) compared to healthy individuals. However, previous observational studies have shown inconsistent results regarding the alteration of gut microbiota/metabolites. In order to shed light on this matter, we utilized Mendelian randomization to determine the causal effect of GM/metabolites on PsA. Methods We retrieved summary-level data of GM taxa/metabolites and PsA from publicly available GWAS statistics. Causal relationships between GM/metabolites and PsA were determined using a two-sample MR analysis, with the IVW approach serving as the primary analysis method. To ensure the robustness of our findings, we conducted sensitivity analyses, multivariable MR analysis (MVMR), and additional analysis including replication verification analysis, LDSC regression, and Steiger test analysis. Furthermore, we investigated reverse causality through a reverse MR analysis. Finally, we conducted an analysis of expression quantitative trait loci (eQTLs) involved in the metabolic pathway to explore potential molecular mechanisms of metabolism. Results Our findings reveal that eight GM taxa and twenty-three serum metabolites are causally related to PsA (P < 0.05). Notably, a higher relative abundance of Family Rikenellaceae (ORIVW: 0.622, 95% CI: 0.438-0.883, FDR = 0.045) and elevated serum levels of X-11538 (ORIVW: 0.442, 95% CI: 0.250-0.781, FDR = 0.046) maintain significant causal associations with a reduced risk of PsA, even after adjusting for multiple testing correction and conducting MVMR analysis. These findings suggest that Family Rikenellaceae and X-11538 may have protective effects against PsA. Our sensitivity analysis and additional analysis revealed no significant horizontal pleiotropy, reverse causality, or heterogeneity. The functional enrichment analysis revealed that the eQTLs examined were primarily associated with glycerolipid metabolism and the expression of key metabolic factors influenced by bacterial infections (Vibrio cholerae and Helicobacter pylori) as well as the mTOR signaling pathway. Conclusion In conclusion, our study demonstrates that Family Rikenellaceae and X-11538 exhibit a strong and negative causal relationship with PsA. These particular GM taxa and metabolites have the potential to serve as innovative biomarkers, offering valuable insights into the treatment and prevention of PsA. Moreover, bacterial infections and mTOR-mediated activation of metabolic factors may play an important role in this process.
Collapse
Affiliation(s)
- Xiao Xu
- Department of Nursing, Nantong Health College of Jiangsu Province, Nantong, China
| | - Lin-yun Wu
- School of Nursing, Zhejiang Chinese Medical University, Hangzhou, China
| | - Shu-yun Wang
- Academic Affair Office, Nantong Vocational University, Nantong, China
| | - Min Yan
- Department of Epidemiology, School of Public Health, Changzhou University, Changzhou, China
- Faculty of Health and Welfare, Satakunta University of Applied Sciences, Pori, Finland
| | - Yuan-Hong Wang
- Department of Rheumatology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Li Li
- Department of Rheumatology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Zhi-ling Sun
- Department of Epidemiology, School of Public Health, Nanjing University of Chinese Medicine, Nanjing, China
| | - Ji-Xiang Zhao
- Department of Nursing, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| |
Collapse
|
10
|
Vergroesen JE, Jarrar ZA, Weiss S, Frost F, Ansari AS, Nguyen P, Kraaij R, Medina-Gomez C, Völzke H, Tost F, Amin N, van Duijn CM, Klaver CCW, Jürgens C, Hammond CJ, Ramdas WD. Glaucoma Patients Have a Lower Abundance of Butyrate-Producing Taxa in the Gut. Invest Ophthalmol Vis Sci 2024; 65:7. [PMID: 38315494 PMCID: PMC10851784 DOI: 10.1167/iovs.65.2.7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 01/19/2024] [Indexed: 02/07/2024] Open
Abstract
Purpose Glaucoma is an eye disease that is the most common cause of irreversible blindness worldwide. It has been suggested that gut microbiota can produce reactive oxygen species and pro-inflammatory cytokines that may travel from the gastric mucosa to distal sites, for example, the optic nerve head or trabecular meshwork. There is evidence for a gut-eye axis, as microbial dysbiosis has been associated with retinal diseases. We investigated the microbial composition in patients with glaucoma and healthy controls. Moreover, we analyzed the association of the gut microbiome with intraocular pressure (IOP; risk factor of glaucoma) and vertical cup-to-disc ratio (VCDR; quantifying glaucoma severity). Methods The discovery analyses included participants of the Rotterdam Study and the Erasmus Glaucoma Cohort. A total of 225 patients with glaucoma and 1247 age- and sex-matched participants without glaucoma were included in our analyses. Stool samples were used to generate 16S rRNA gene profiles. We assessed associations with 233 genera and species. We used data from the TwinsUK and the Study of Health in Pomerania (SHIP) to replicate our findings. Results Several butyrate-producing taxa (e.g. Butyrivibrio, Caproiciproducens, Clostridium sensu stricto 1, Coprococcus 1, Ruminococcaceae UCG 007, and Shuttleworthia) were less abundant in people with glaucoma compared to healthy controls. The same taxa were also associated with lower IOP and smaller VCDR. The replication analyses confirmed the findings from the discovery analyses. Conclusions Large human studies exploring the link between the gut microbiome and glaucoma are lacking. Our results suggest that microbial dysbiosis plays a role in the pathophysiology of glaucoma.
Collapse
Affiliation(s)
- Joëlle E. Vergroesen
- Department of Ophthalmology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Zakariya A. Jarrar
- Department of Ophthalmology, King's College London, London, United Kingdom
- Department of Twins Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Stefan Weiss
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- Department of Medicine A, University Medicine Greifswald, Greifswald, Germany
| | - Fabian Frost
- Department of Medicine A, University Medicine Greifswald, Greifswald, Germany
| | - Abdus S. Ansari
- Department of Ophthalmology, King's College London, London, United Kingdom
- Department of Twins Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Picard Nguyen
- Department of Ophthalmology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Robert Kraaij
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Frank Tost
- Department of Ophthalmology, University Medicine Greifswald, Greifswald, Germany
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Cornelia M. van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Caroline C. W. Klaver
- Department of Ophthalmology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, Radboud University Medical Center, Nijmegen, The Netherlands
- Institute of Molecular and Clinical Ophthalmology, University of Basel, Basel, Switzerland
| | - Clemens Jürgens
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Chris J. Hammond
- Department of Ophthalmology, King's College London, London, United Kingdom
- Department of Twins Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Wishal D. Ramdas
- Department of Ophthalmology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| |
Collapse
|
11
|
Fang F, Quach B, Lawrence KG, van Dongen J, Marks JA, Lundgren S, Lin M, Odintsova VV, Costeira R, Xu Z, Zhou L, Mandal M, Xia Y, Vink JM, Bierut LJ, Ollikainen M, Taylor JA, Bell JT, Kaprio J, Boomsma DI, Xu K, Sandler DP, Hancock DB, Johnson EO. Trans-ancestry epigenome-wide association meta-analysis of DNA methylation with lifetime cannabis use. Mol Psychiatry 2024; 29:124-133. [PMID: 37935791 PMCID: PMC11078760 DOI: 10.1038/s41380-023-02310-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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 10/16/2023] [Accepted: 10/23/2023] [Indexed: 11/09/2023]
Abstract
Cannabis is widely used worldwide, yet its links to health outcomes are not fully understood. DNA methylation can serve as a mediator to link environmental exposures to health outcomes. We conducted an epigenome-wide association study (EWAS) of peripheral blood-based DNA methylation and lifetime cannabis use (ever vs. never) in a meta-analysis including 9436 participants (7795 European and 1641 African ancestry) from seven cohorts. Accounting for effects of cigarette smoking, our trans-ancestry EWAS meta-analysis revealed four CpG sites significantly associated with lifetime cannabis use at a false discovery rate of 0.05 ( p < 5.85 × 10 - 7 ) : cg22572071 near gene ADGRF1, cg15280358 in ADAM12, cg00813162 in ACTN1, and cg01101459 near LINC01132. Additionally, our EWAS analysis in participants who never smoked cigarettes identified another epigenome-wide significant CpG site, cg14237301 annotated to APOBR. We used a leave-one-out approach to evaluate methylation scores constructed as a weighted sum of the significant CpGs. The best model can explain 3.79% of the variance in lifetime cannabis use. These findings unravel the DNA methylation changes associated with lifetime cannabis use that are independent of cigarette smoking and may serve as a starting point for further research on the mechanisms through which cannabis exposure impacts health outcomes.
Collapse
Affiliation(s)
- Fang Fang
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA.
| | - Bryan Quach
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Kaitlyn G Lawrence
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jesse A Marks
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Sara Lundgren
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Mingkuan Lin
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
| | - Veronika V Odintsova
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ricardo Costeira
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Linran Zhou
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Meisha Mandal
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Yujing Xia
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Jacqueline M Vink
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Laura J Bierut
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, St. Louis, MO, USA
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Jordana T Bell
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Dana B Hancock
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Eric O Johnson
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
- Fellow Program, RTI International, Research Triangle Park, NC, USA
| |
Collapse
|
12
|
Lee S, Kim J, Ohn JH. Exploring quantitative traits-associated copy number deletions through reanalysis of UK10K consortium whole genome sequencing cohorts. BMC Genomics 2023; 24:787. [PMID: 38110883 PMCID: PMC10729411 DOI: 10.1186/s12864-023-09903-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 12/13/2023] [Indexed: 12/20/2023] Open
Abstract
OBJECTIVES We performed comprehensive association analyses of common high-confidence gnomAD-reported copy number deletions (CNDs) with 60 quantitative traits from UK10K consortium WGS data. METHODS The study made use of data generated by the UK10K Consortium. UK10K consortium WGS data consist of TwinsUK (n = 1754, middle-aged females) and ALSPAC (n = 1867, birth to adolescence) cohorts. UK10K consortium called 18,739 CNDs (hg19) with GenomeSTRiP software. After filtering out variants with minor allele frequency < 0.05 or HWE P < 1.0 × 10- 6, 1222 (TwinsUK) and 1211 (ALSPAC) CNDs remained for association analyses with 60 normalized quantitative traits. RESULTS We identified 23 genome-wide significant associations at 13 loci, among which 2 associations reached experiment-wide significance. We found that two common deletions in chromosome 4, located between WDR1 and ZNF518B (23.3 kb, dbVar ID:nssv15888957, 4:10211262-10,234,569 and 9.8 kb, dbVar ID:nssv15888975, 4:10392422-10,402,191), were associated with uric acid levels (P = 5.23 × 10- 11 and 2.29 × 10- 8, respectively). We also discovered a novel deletion spanning chromosome 18 (823 bp, dbVar ID: nssv15841628, 8:74347187-74,348,010) associated with low HDL cholesterol levels (P = 4.15 × 10- 7). Additionally, we observed two red blood cell traits-associated loci with genome-wide significance, a 13.2 kb deletion in 7q22.1 (nssv15922542) and a 3.7 kb deletion in 12q24.12 (nssv15813226), both of which were located in regions previously reported to be associated with red blood cell traits. Two deletions in 11q11 (nssv15803200 and nssv15802240), where clusters of multiple olfactory receptor genes exist, and a deletion (nssv15929560) upstream to DOCK5 were associated with childhood obesity. Finally, when defining Trait-Associated copy number Deletions (TADs) as CNDs with phenotype associations at sub-threshold significance (P < 10- 3), we identified 157 (97.5%) out of 161 TADs in non-coding regions, with a mean size of 4 kb (range: 209 - 47,942 bp). CONCLUSION We conducted a reanalysis of the UK10K Whole Genome Sequencing cohort, which led to the identification of multiple high confidence copy number deletions associated with quantitative traits. These deletions have standard dbVar IDs and replicate previous findings, as well as reveal novel loci that require further replication studies.
Collapse
Affiliation(s)
- Sejoon Lee
- Precision Medicine Center, Future Innovation Research Division, Seoul National University Bundang Hospital, 173-82, Gumi-ro, Bundang-gu, Seongnam, Gyeonggi-do, 13620, South Korea
- Department of Pathology, Seoul National University Bundang Hospital, 173-82, Gumi-ro, Bundang-gu, Seongnam, Gyeonggi-do, 13620, South Korea
| | - Jinho Kim
- Precision Medicine Center, Future Innovation Research Division, Seoul National University Bundang Hospital, 173-82, Gumi-ro, Bundang-gu, Seongnam, Gyeonggi-do, 13620, South Korea
- Department of Laboratory Medicine, Seoul National University Bundang Hospital, 173-82, Gumi-ro, Bundang-gu, Seongnam, Gyeonggi-do, 13620, South Korea
| | - Jung Hun Ohn
- Precision Medicine Center, Future Innovation Research Division, Seoul National University Bundang Hospital, 173-82, Gumi-ro, Bundang-gu, Seongnam, Gyeonggi-do, 13620, South Korea.
- Department of Internal Medicine, Seoul National University Bundang Hospital, 173-82, Gumi-ro, Bundang-gu, Seongnam, Gyeonggi-do, 13620, South Korea.
- Department of Internal Medicine, College of Medicine, Seoul National University, 103, Daehak-ro, Jongno-gu, Seoul, 03080, South Korea.
| |
Collapse
|
13
|
Baron C, Cherkaoui S, Therrien-Laperriere S, Ilboudo Y, Poujol R, Mehanna P, Garrett ME, Telen MJ, Ashley-Koch AE, Bartolucci P, Rioux JD, Lettre G, Rosiers CD, Ruiz M, Hussin JG. Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results. iScience 2023; 26:108473. [PMID: 38077122 PMCID: PMC10709128 DOI: 10.1016/j.isci.2023.108473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 08/24/2023] [Accepted: 11/13/2023] [Indexed: 12/20/2023] Open
Abstract
Metabolite genome-wide association studies (mGWAS) have advanced our understanding of the genetic control of metabolite levels. However, interpreting these associations remains challenging due to a lack of tools to annotate gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we introduce the shortest reactional distance (SRD) metric, drawing from the comprehensive KEGG database, to enhance the biological interpretation of mGWAS results. We applied this approach to three independent mGWAS, including a case study on sickle cell disease patients. Our analysis reveals an enrichment of small SRD values in reported mGWAS pairs, with SRD values significantly correlating with mGWAS p values, even beyond the standard conservative thresholds. We demonstrate the utility of SRD annotation in identifying potential false negatives and inaccuracies within current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs, suitable to integrate statistical evidence to biological networks.
Collapse
Affiliation(s)
- Cantin Baron
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
| | - Sarah Cherkaoui
- Montreal Heart Institute, Montréal, QC, Canada
- Division of Oncology and Children’s Research Center, University Children’s Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Center, Université Paris-Saclay, Villejuif, France
| | | | - Yann Ilboudo
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
| | | | | | - Melanie E. Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Marilyn J. Telen
- Division of Hematology, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | | | - Pablo Bartolucci
- Université Paris Est Créteil, Hôpitaux Universitaires Henri Mondor, APHP, Sickle cell referral center – UMGGR, Créteil, France
- Université Paris Est Créteil, IMRB, Laboratory of excellence LABEX, Créteil, France
| | - John D. Rioux
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Médecine, Université de Montréal, Montréal, QC, Canada
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Médecine, Université de Montréal, Montréal, QC, Canada
| | - Christine Des Rosiers
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Nutrition, Université de Montréal, Montréal, QC, Canada
| | - Matthieu Ruiz
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Nutrition, Université de Montréal, Montréal, QC, Canada
| | - Julie G. Hussin
- Montreal Heart Institute, Montréal, QC, Canada
- Département de Médecine, Université de Montréal, Montréal, QC, Canada
| |
Collapse
|
14
|
Xu X, Zhang X, Cheng S, Li Q, Chen C, Ouyang M. Protective effect of uridine on atrial fibrillation: a Mendelian randomisation study. Sci Rep 2023; 13:19639. [PMID: 37950049 PMCID: PMC10638443 DOI: 10.1038/s41598-023-47025-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 11/08/2023] [Indexed: 11/12/2023] Open
Abstract
Uridine, a pyrimidine nucleoside, is crucial in the synthesis of metabolites. According to observational studies, a higher plasma uridine level is associated with a lower risk of atrial fibrillation (AF). However, the casual relationship between uridine and AF is still unknown. In this study, we used the Mendelian randomisation (MR) approach to explore causality. Three genetic variants associated with uridine were identified from the Metabolomics GWAS server (7824 participants); summary-level datasets associated with AF were acquired from a genome-wide association study (GWAS) meta-analysis with 1,030,836 European participants (60,620 AF cases). We duplicated the MR analyses using datasets from AF HRC studies and the FinnGen Consortium, and then conducted a meta-analysis which combined the main results. The risk of AF was significantly associated with the genetically determined plasma uridine level (odds ratio [OR] 0.27; 95% confidence interval [CI] 0.16, 0.47; p = 2.39 × 10-6). The association remained consistent in the meta-analysis of the various datasets (OR 0.27; 95% CI 0.17, 0.42; p = 1.34 × 10-8). In conclusion, the plasma uridine level is inversely associated with the risk of AF. Raising the plasma uridine level may have prophylactic potential against AF.
Collapse
Affiliation(s)
- Xintian Xu
- Department of Cardiology, The Sixth Affiliated Hospital, Sun Yat-Sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, People's Republic of China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Xiaoyu Zhang
- Department of Cardiology, The Sixth Affiliated Hospital, Sun Yat-Sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, People's Republic of China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Shiyao Cheng
- Department of Cardiology, The Sixth Affiliated Hospital, Sun Yat-Sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, People's Republic of China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Qinglang Li
- Department of Cardiology, The Sixth Affiliated Hospital, Sun Yat-Sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, People's Republic of China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Cai Chen
- Department of Cardiology, The Sixth Affiliated Hospital, Sun Yat-Sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, People's Republic of China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Mao Ouyang
- Department of Cardiology, The Sixth Affiliated Hospital, Sun Yat-Sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, People's Republic of China.
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China.
| |
Collapse
|
15
|
Gósy M, Bunta F, Pregitzer M. Speech processing performance of Hungarian-speaking twins and singletons. CLINICAL LINGUISTICS & PHONETICS 2023; 37:979-995. [PMID: 36052433 DOI: 10.1080/02699206.2022.2111274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 05/30/2022] [Accepted: 08/01/2022] [Indexed: 06/15/2023]
Abstract
Studying speech processing in twins versus their singleton peers provides opportunities to study both genetic and environmental effects on how children acquire these aspects of their speech and - by extension - their phonological systems. Our study focused on speech processing in typically developing Hungarian-speaking twins and their singleton peers between 5 and 9 years of age. Participants included 384 monolingual Hungarian-speaking children (192 twins, and 192 singletons). Data from four tasks - repetition of synthesised monosyllables, nonsense words, well-formed noisy sentences, and well-formed phonologically complex sentences - were analysed. There was a main effect for birth status, and singletons outperformed their twin peers on the majority of the speech processing tasks. Age and task also had effects on the performance of the participants, and there was a three-way task by age by twin versus singleton status indicating that the speech processing performance of twins versus singletons is interdependent with the type of task and age. Our results also indicate that monolingual Hungarian-speaking twins may be at higher risk for developmental speech delays relative to their singleton peers.
Collapse
Affiliation(s)
- Mária Gósy
- Department of Phonetics, Linguistics Institute ELKH and ELTE University, Budapest, Hungary
| | - Ferenc Bunta
- Department of Communication Sciences and Disorders, University of Houston, Houston, Texas, USA
| | | |
Collapse
|
16
|
Kouraki A, Kelly A, Vijay A, Gohir S, Astbury S, Georgopoulos V, Millar B, Walsh DA, Ferguson E, Menni C, Valdes AM. Reproducible microbiome composition signatures of anxiety and depressive symptoms. Comput Struct Biotechnol J 2023; 21:5326-5336. [PMID: 37954149 PMCID: PMC10637863 DOI: 10.1016/j.csbj.2023.10.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 10/17/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023] Open
Abstract
The gut microbiome is a significant contributor to mental health, with growing evidence linking its composition to anxiety and depressive disorders. Gut microbiome composition is associated with signs of anxiety and depression both in clinically diagnosed mood disorders and subclinically in the general population and may be influenced by dietary fibre intake and the presence of chronic pain. We provide an update of current evidence on the role of gut microbiome composition in depressive and anxiety disorders or symptoms by reviewing available studies. Analysing data from three independent cohorts (osteoarthritis 1 (OA1); n = 46, osteoarthritis 2 (OA2); n = 58, and healthy controls (CON); n = 67), we identified microbial composition signatures of anxiety and depressive symptoms at genus level and cross-validated our findings performing meta-analyses of our results with results from previously published studies. The genera Bifidobacterium (fixed-effect beta (95% CI) = -0.22 (-0.34, -0.10), p = 3.90e-04) and Lachnospiraceae NK4A136 group (fixed-effect beta (95% CI) = -0.09 (-0.13, -0.05), p = 2.53e-06) were found to be the best predictors of anxiety and depressive symptoms, respectively, across our three cohorts and published literature taking into account demographic and lifestyle covariates, such as fibre intake. The association with anxiety was robust in accounting for heterogeneity between cohorts and supports previous observations of the potential prophylactic effect of Bifidobacterium against anxiety symptoms.
Collapse
Affiliation(s)
- Afroditi Kouraki
- Academic Unit of Injury, Recovery and Inflammation Sciences, Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
| | - Anthony Kelly
- Academic Unit of Injury, Recovery and Inflammation Sciences, Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
| | - Amrita Vijay
- Academic Unit of Injury, Recovery and Inflammation Sciences, Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK
| | - Sameer Gohir
- Academic Unit of Injury, Recovery and Inflammation Sciences, Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
| | - Stuart Astbury
- Academic Unit of Injury, Recovery and Inflammation Sciences, Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK
- Nottingham Digestive Diseases Centre, Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Vasileios Georgopoulos
- Academic Unit of Injury, Recovery and Inflammation Sciences, Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Bonnie Millar
- Academic Unit of Injury, Recovery and Inflammation Sciences, Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - David Andrew Walsh
- Academic Unit of Injury, Recovery and Inflammation Sciences, Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Eamonn Ferguson
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
- School of Psychology, University of Nottingham, University Park, Nottingham, UK
- National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Ana M. Valdes
- Academic Unit of Injury, Recovery and Inflammation Sciences, Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| |
Collapse
|
17
|
Bermingham KM, Mazidi M, Franks PW, Maher T, Valdes AM, Linenberg I, Wolf J, Hadjigeorgiou G, Spector TD, Menni C, Ordovas JM, Berry SE, Hall WL. Characterisation of Fasting and Postprandial NMR Metabolites: Insights from the ZOE PREDICT 1 Study. Nutrients 2023; 15:nu15112638. [PMID: 37299601 DOI: 10.3390/nu15112638] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/12/2023] [Accepted: 05/18/2023] [Indexed: 06/12/2023] Open
Abstract
BACKGROUND Postprandial metabolomic profiles and their inter-individual variability are not well characterised. Here, we describe postprandial metabolite changes, their correlations with fasting values and their inter- and intra-individual variability, following a standardised meal in the ZOE PREDICT 1 cohort. METHODS In the ZOE PREDICT 1 study (n = 1002 (NCT03479866)), 250 metabolites, mainly lipids, were measured by a Nightingale NMR panel in fasting and postprandial (4 and 6 h after a 3.7 MJ mixed nutrient meal, with a second 2.2 MJ mixed nutrient meal at 4 h) serum samples. For each metabolite, inter- and intra-individual variability over time was evaluated using linear mixed modelling and intraclass correlation coefficients (ICC) were calculated. RESULTS Postprandially, 85% (of 250 metabolites) significantly changed from fasting at 6 h (47% increased, 53% decreased; Kruskal-Wallis), with 37 measures increasing by >25% and 14 increasing by >50%. The largest changes were observed in very large lipoprotein particles and ketone bodies. Seventy-one percent of circulating metabolites were strongly correlated (Spearman's rho >0.80) between fasting and postprandial timepoints, and 5% were weakly correlated (rho <0.50). The median ICC of the 250 metabolites was 0.91 (range 0.08-0.99). The lowest ICCs (ICC <0.40, 4% of measures) were found for glucose, pyruvate, ketone bodies (β-hydroxybutyrate, acetoacetate, acetate) and lactate. CONCLUSIONS In this large-scale postprandial metabolomic study, circulating metabolites were highly variable between individuals following sequential mixed meals. Findings suggest that a meal challenge may yield postprandial responses divergent from fasting measures, specifically for glycolysis, essential amino acid, ketone body and lipoprotein size metabolites.
Collapse
Affiliation(s)
- Kate M Bermingham
- Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK
- Department of Twins Research and Genetic Epidemiology, King's College London, London WC2R 2LS, UK
| | - Mohsen Mazidi
- Department of Twins Research and Genetic Epidemiology, King's College London, London WC2R 2LS, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX1 3QR, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Paul W Franks
- Department of Clinical Sciences, Lund University, 21428 Malmö, Sweden
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
| | - Tyler Maher
- Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK
| | - Ana M Valdes
- School of Medicine, University of Nottingham, Nottingham NG5 1PB, UK
- Nottingham NIHR Biomedical Research Centre, Nottingham NG7 2UH, UK
| | - Inbar Linenberg
- Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK
- ZOE Ltd., London SE1 7RW, UK
| | | | | | - Tim D Spector
- Department of Twins Research and Genetic Epidemiology, King's College London, London WC2R 2LS, UK
| | - Cristina Menni
- Department of Twins Research and Genetic Epidemiology, King's College London, London WC2R 2LS, UK
| | - Jose M Ordovas
- Jean Mayer USDA Human Nutrition Research Centre on Aging (JM-USDA-HNRCA), Tufts University, Boston, MA 02111, USA
- IMDEA Food Institute, CEI UAM + CSIC, 28049 Madrid, Spain
- Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Sarah E Berry
- Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK
| | - Wendy L Hall
- Department of Nutritional Sciences, King's College London, London WC2R 2LS, UK
| |
Collapse
|
18
|
Sharapov SZ, Timoshchuk AN, Aulchenko YS. Genetic control of N-glycosylation of human blood plasma proteins. Vavilovskii Zhurnal Genet Selektsii 2023; 27:224-239. [PMID: 37293449 PMCID: PMC10244589 DOI: 10.18699/vjgb-23-29] [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: 11/17/2022] [Revised: 01/20/2023] [Accepted: 01/23/2022] [Indexed: 06/10/2023] Open
Abstract
Glycosylation is an important protein modification, which influences the physical and chemical properties as well as biological function of these proteins. Large-scale population studies have shown that the levels of various plasma protein N-glycans are associated with many multifactorial human diseases. Observed associations between protein glycosylation levels and human diseases have led to the conclusion that N-glycans can be considered a potential source of biomarkers and therapeutic targets. Although biochemical pathways of glycosylation are well studied, the understanding of the mechanisms underlying general and tissue-specific regulation of these biochemical reactions in vivo is limited. This complicates both the interpretation of the observed associations between protein glycosylation levels and human diseases, and the development of glycan-based biomarkers and therapeutics. By the beginning of the 2010s, high-throughput methods of N-glycome profiling had become available, allowing research into the genetic control of N-glycosylation using quantitative genetics methods, including genome-wide association studies (GWAS). Application of these methods has made it possible to find previously unknown regulators of N-glycosylation and expanded the understanding of the role of N-glycans in the control of multifactorial diseases and human complex traits. The present review considers the current knowledge of the genetic control of variability in the levels of N-glycosylation of plasma proteins in human populations. It briefly describes the most popular physical-chemical methods of N-glycome profiling and the databases that contain genes involved in the biosynthesis of N-glycans. It also reviews the results of studies of environmental and genetic factors contributing to the variability of N-glycans as well as the mapping results of the genomic loci of N-glycans by GWAS. The results of functional in vitro and in silico studies are described. The review summarizes the current progress in human glycogenomics and suggests possible directions for further research.
Collapse
Affiliation(s)
- S Zh Sharapov
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - A N Timoshchuk
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - Y S Aulchenko
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| |
Collapse
|
19
|
Lockhart C, Bright J, Ahmadzadeh Y, Breen G, Bristow S, Boyd A, Downs J, Hotopf M, Palaiologou E, Rimfeld K, Maxwell J, Malanchini M, McAdams TA, McMillan A, Plomin R, Eley TC. Twins Early Development Study (TEDS): A genetically sensitive investigation of mental health outcomes in the mid-twenties. JCPP ADVANCES 2023; 3:e12154. [PMID: 37753150 PMCID: PMC10519737 DOI: 10.1002/jcv2.12154] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 02/13/2023] [Indexed: 04/03/2023] Open
Abstract
The Twins Early Development Study (TEDS) is a longitudinal study following a cohort of twins born 1994-1996 in England and Wales. Of the 13,759 families who originally consented to take part, over 10,000 families remain enrolled in the study. The current focus of TEDS is on mental health in the mid-twenties. Making use of over 25 years of genetically sensitive data, TEDS is uniquely placed to explore the longitudinal genetic and environmental influences on common mental health disorders in early adulthood. This paper outlines recent data collection efforts supporting this work, including a cohort-wide mental health assessment at age 26 and a multi-phase Covid-19 study. It will also provide an update on data linkage efforts and the Children of TEDS (CoTEDS) project.
Collapse
Affiliation(s)
- Celestine Lockhart
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
| | - Joanna Bright
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
| | - Yasmin Ahmadzadeh
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
- UK National Institute for Health Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Shannon Bristow
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
| | - Andy Boyd
- Population Health Sciences InstituteBristol Medical SchoolUniversity of BristolBristolUK
| | - Johnny Downs
- Department of Child and Adolescent PsychiatryInstitute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
- South London and Maudsley NHS Foundation TrustLondonUK
| | - Matthew Hotopf
- South London and Maudsley NHS Foundation TrustLondonUK
- Department of Psychological MedicineInstitute of Psychiatry Psychology and NeuroscienceKing's College LondonLondonUK
| | - Elisavet Palaiologou
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
| | - Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
- Department of PsychologyRoyal Holloway University of LondonEghamSurreyUK
| | - Jessye Maxwell
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
| | - Margherita Malanchini
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
- Queen Mary University of LondonLondonUK
| | - Tom A. McAdams
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
- Promenta Research CentreUniversity of OsloOsloUK
| | - Andrew McMillan
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
| | - Thalia C. Eley
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonCamberwellLondonUK
- UK National Institute for Health Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| |
Collapse
|
20
|
Ruf WP, Boros M, Freischmidt A, Brenner D, Grozdanov V, de Meirelles J, Meyer T, Grehl T, Petri S, Grosskreutz J, Weyen U, Guenther R, Regensburger M, Hagenacker T, Koch JC, Emmer A, Roediger A, Steinbach R, Wolf J, Weishaupt JH, Lingor P, Deschauer M, Cordts I, Klopstock T, Reilich P, Schoeberl F, Schrank B, Zeller D, Hermann A, Knehr A, Günther K, Dorst J, Schuster J, Siebert R, Ludolph AC, Müller K. Spectrum and frequency of genetic variants in sporadic amyotrophic lateral sclerosis. Brain Commun 2023; 5:fcad152. [PMID: 37223130 PMCID: PMC10202555 DOI: 10.1093/braincomms/fcad152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 02/24/2023] [Accepted: 05/05/2023] [Indexed: 05/25/2023] Open
Abstract
Therapy of motoneuron diseases entered a new phase with the use of intrathecal antisense oligonucleotide therapies treating patients with specific gene mutations predominantly in the context of familial amyotrophic lateral sclerosis. With the majority of cases being sporadic, we conducted a cohort study to describe the mutational landscape of sporadic amyotrophic lateral sclerosis. We analysed genetic variants in amyotrophic lateral sclerosis-associated genes to assess and potentially increase the number of patients eligible for gene-specific therapies. We screened 2340 sporadic amyotrophic lateral sclerosis patients from the German Network for motor neuron diseases for variants in 36 amyotrophic lateral sclerosis-associated genes using targeted next-generation sequencing and for the C9orf72 hexanucleotide repeat expansion. The genetic analysis could be completed on 2267 patients. Clinical data included age at onset, disease progression rate and survival. In this study, we found 79 likely pathogenic Class 4 variants and 10 pathogenic Class 5 variants (without the C9orf72 hexanucleotide repeat expansion) according to the American College of Medical Genetics and Genomics guidelines, of which 31 variants are novel. Thus, including C9orf72 hexanucleotide repeat expansion, Class 4, and Class 5 variants, 296 patients, corresponding to ∼13% of our cohort, could be genetically resolved. We detected 437 variants of unknown significance of which 103 are novel. Corroborating the theory of oligogenic causation in amyotrophic lateral sclerosis, we found a co-occurrence of pathogenic variants in 10 patients (0.4%) with 7 being C9orf72 hexanucleotide repeat expansion carriers. In a gene-wise survival analysis, we found a higher hazard ratio of 1.47 (95% confidence interval 1.02-2.1) for death from any cause for patients with the C9orf72 hexanucleotide repeat expansion and a lower hazard ratio of 0.33 (95% confidence interval 0.12-0.9) for patients with pathogenic SOD1 variants than for patients without a causal gene mutation. In summary, the high yield of 296 patients (∼13%) harbouring a pathogenic variant and oncoming gene-specific therapies for SOD1/FUS/C9orf72, which would apply to 227 patients (∼10%) in this cohort, corroborates that genetic testing should be made available to all sporadic amyotrophic lateral sclerosis patients after respective counselling.
Collapse
Affiliation(s)
- Wolfgang P Ruf
- Correspondence to: Dr Wolfgang P. Ruf Department of Neurology Medical Faculty, Ulm University Albert-Einstein-Allee 23, Ulm 89081, Germany E-mail:
| | - Matej Boros
- Institute of Human Genetics, Ulm University & Ulm University Medical Center, Ulm 89081, Germany
| | - Axel Freischmidt
- Department of Neurology, Ulm University, Ulm 89081, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), German Center for Neurodegenerative Diseases, Ulm 89081, Germany
| | - David Brenner
- Department of Neurology, Ulm University, Ulm 89081, Germany
| | | | - Joao de Meirelles
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), German Center for Neurodegenerative Diseases, Ulm 89081, Germany
| | - Thomas Meyer
- Department of Neurology, Center for ALS and other Motor Neuron Disorders, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 13353, Germany
| | - Torsten Grehl
- Department of Neurology, Alfried Krupp Hospital, Essen 45131, Germany
| | - Susanne Petri
- Department of Neurology, Medizinische Hochschule Hannover, Hannover 30625, Germany
| | | | - Ute Weyen
- Department of Neurology, University Hospital Bochum, Bochum 44789, Germany
| | - Rene Guenther
- Department of Neurology, Technische Universität Dresden, Dresden 01307, Germany
| | - Martin Regensburger
- Department of Neurology, University Hospital Erlangen, Erlangen 91054, Germany
| | - Tim Hagenacker
- Department of Neurology Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Medicine Essen, Essen 45147, Germany
| | - Jan C Koch
- Department of Neurology, University Medical Center Goettingen, Goettingen 37075, Germany
| | - Alexander Emmer
- University Clinic and Polyclinic for Neurology, University Hospital Halle, Halle 06120, Germany
| | | | - Robert Steinbach
- Department of Neurology, University Hospital Jena, Jena 07747, Germany
| | - Joachim Wolf
- Department of Neurology, Diako Mannheim, Mannheim 68163, Germany
| | - Jochen H Weishaupt
- Department of Neurology, University Hospital Mannheim, Mannheim 68167, Germany
| | - Paul Lingor
- Department of Neurology, Technical University Munich, Munich 80333, Germany
| | - Marcus Deschauer
- Department of Neurology, Technical University Munich, Munich 80333, Germany
| | - Isabell Cordts
- Department of Neurology, Technical University Munich, Munich 80333, Germany
| | - Thomas Klopstock
- Department of Neurology with Friedrich-Baur-Institute, University Hospital of Ludwig-Maximilians-University, München 80336, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), German Center for Neurodegenerative Diseases, Munich 81377, Germany
| | - Peter Reilich
- Department of Neurology with Friedrich-Baur-Institute, University Hospital of Ludwig-Maximilians-University, München 80336, Germany
| | - Florian Schoeberl
- Department of Neurology with Friedrich-Baur-Institute, University Hospital of Ludwig-Maximilians-University, München 80336, Germany
| | - Berthold Schrank
- Department of Neurology, DKD Helios Clinics, Wiesbaden 65191, Germany
| | - Daniel Zeller
- Department of Neurology, University Hospital Wuerzburg, Wuerzburg 97080, Germany
| | - Andreas Hermann
- Translational Neurodegeneration Section ‘Albrecht Kossel’, University Medical Center Rostock, Rostock 18146, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), German Center for Neurodegenerative Diseases, Rostock/Greifswald 17489, Germany
| | - Antje Knehr
- Department of Neurology, Ulm University, Ulm 89081, Germany
| | | | - Johannes Dorst
- Department of Neurology, Ulm University, Ulm 89081, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), German Center for Neurodegenerative Diseases, Ulm 89081, Germany
| | - Joachim Schuster
- Department of Neurology, Ulm University, Ulm 89081, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), German Center for Neurodegenerative Diseases, Ulm 89081, Germany
| | - Reiner Siebert
- Institute of Human Genetics, Ulm University & Ulm University Medical Center, Ulm 89081, Germany
| | - Albert C Ludolph
- Department of Neurology, Ulm University, Ulm 89081, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), German Center for Neurodegenerative Diseases, Ulm 89081, Germany
| | - Kathrin Müller
- Department of Neurology, Ulm University, Ulm 89081, Germany
- Institute of Human Genetics, Ulm University & Ulm University Medical Center, Ulm 89081, Germany
| |
Collapse
|
21
|
Balasundaram A, Kumar S U, D TK, Anil Dedge A, R G, K SS, R S, C GPD. The targeted next-generation sequence revealed SMAD4, AKT1, and TP53 mutations from circulating cell-free DNA of breast cancer and its effect on protein structure - A computational approach. J Biomol Struct Dyn 2023; 41:15584-15597. [PMID: 37011004 DOI: 10.1080/07391102.2023.2191122] [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: 07/22/2022] [Accepted: 03/06/2023] [Indexed: 04/04/2023]
Abstract
Breast cancer biomarkers that detect marginally advanced stages are still challenging. The detection of specific abnormalities, targeted therapy selection, prognosis, and monitoring of treatment effectiveness over time are all made possible by circulating free DNA (cfDNA) analysis. The proposed study will detect specific genetic abnormalities from the plasma cfDNA of a female breast cancer patient by sequencing a cancer-related gene panel (MGM455 - Oncotrack Ultima), including 56 theranostic genes (SNVs and small INDELs). Initially, we determined the pathogenicity of the observed mutations using PredictSNP, iStable, Align-GVGD, and ConSurf servers. As a next step, molecular dynamics (MD) was implemented to determine the functional significance of SMAD4 mutation (V465M). Lastly, the mutant gene relationships were examined using the Cytoscape plug-in GeneMANIA. Using ClueGO, we determined the gene's functional enrichment and integrative analysis. The structural characteristics of SMAD4 V465M protein by MD simulation analysis further demonstrated that the mutation was deleterious. The simulation showed that the native structure was more significantly altered by the SMAD4 (V465M) mutation. Our findings suggest that SMAD4 V465M mutation might be significantly associated with breast cancer, and other patient-found mutations (AKT1-E17K and TP53-R175H) are synergistically involved in the process of SMAD4 translocate to nuclease, which affects the target gene translation. Therefore, this combination of gene mutations could alter the TGF-β signaling pathway in BC. We further proposed that the SMAD4 protein loss may contribute to an aggressive phenotype by inhibiting the TGF-β signaling pathway. Thus, breast cancer's SMAD4 (V465M) mutation might increase their invasive and metastatic capabilities.Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- Ambritha Balasundaram
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Udhaya Kumar S
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Thirumal Kumar D
- Meenakshi Academy of Higher Education and Research (Deemed to be University), Chennai, Tamil Nadu, India
| | - Aditi Anil Dedge
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Gnanasambandan R
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Satish Srinivas K
- Department of Radiation Oncology, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, Tamil Nadu, India
| | - Siva R
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - George Priya Doss C
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| |
Collapse
|
22
|
Baron C, Cherkaoui S, Therrien-Laperriere S, Ilboudo Y, Poujol R, Mehanna P, Garrett ME, Telen MJ, Ashley-Koch AE, Bartolucci P, Rioux JD, Lettre G, Des Rosiers C, Ruiz M, Hussin JG. Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.22.533869. [PMID: 36993181 PMCID: PMC10055409 DOI: 10.1101/2023.03.22.533869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Studies combining metabolomics and genetics, known as metabolite genome-wide association studies (mGWAS), have provided valuable insights into our understanding of the genetic control of metabolite levels. However, the biological interpretation of these associations remains challenging due to a lack of existing tools to annotate mGWAS gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we computed the shortest reactional distance (SRD) based on the curated knowledge of the KEGG database to explore its utility in enhancing the biological interpretation of results from three independent mGWAS, including a case study on sickle cell disease patients. Results show that, in reported mGWAS pairs, there is an excess of small SRD values and that SRD values and p-values significantly correlate, even beyond the standard conservative thresholds. The added-value of SRD annotation is shown for identification of potential false negative hits, exemplified by the finding of gene-metabolite associations with SRD ≤1 that did not reach standard genome-wide significance cut-off. The wider use of this statistic as an mGWAS annotation would prevent the exclusion of biologically relevant associations and can also identify errors or gaps in current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs that can be used to integrate statistical evidence to biological networks.
Collapse
Affiliation(s)
- Cantin Baron
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Québec, Canada
- Montreal Heart Institute, Québec, Canada
| | - Sarah Cherkaoui
- Montreal Heart Institute, Québec, Canada
- Division of Oncology and Children’s Research Center, University Children’s Hospital Zurich, University of Zurich, Switzerland
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Center, Université Paris-Saclay, Villejuif, France
| | | | - Yann Ilboudo
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Québec, Canada
- Montreal Heart Institute, Québec, Canada
| | | | | | - Melanie E. Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Marilyn J. Telen
- Division of Hematology, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | | | - Pablo Bartolucci
- Université Paris Est Créteil, Hôpitaux Universitaires Henri Mondor, APHP, Sickle cell referral center – UMGGR, Créteil, France
- Université Paris Est Créteil, IMRB, Laboratory of excellence LABEX, Créteil, France
| | - John D. Rioux
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Québec, Canada
- Montreal Heart Institute, Québec, Canada
- Département de Médecine, Université de Montréal, Québec, Canada
| | - Guillaume Lettre
- Montreal Heart Institute, Québec, Canada
- Département de Médecine, Université de Montréal, Québec, Canada
| | - Christine Des Rosiers
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Québec, Canada
- Montreal Heart Institute, Québec, Canada
- Département de Nutrition, Université de Montréal, Québec, Canada
| | - Matthieu Ruiz
- Montreal Heart Institute, Québec, Canada
- Département de Nutrition, Université de Montréal, Québec, Canada
| | - Julie G. Hussin
- Montreal Heart Institute, Québec, Canada
- Département de Médecine, Université de Montréal, Québec, Canada
| |
Collapse
|
23
|
Escape from X-inactivation in twins exhibits intra- and inter-individual variability across tissues and is heritable. PLoS Genet 2023; 19:e1010556. [PMID: 36802379 PMCID: PMC9942974 DOI: 10.1371/journal.pgen.1010556] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 12/06/2022] [Indexed: 02/23/2023] Open
Abstract
X-chromosome inactivation (XCI) silences one X in female cells to balance sex-differences in X-dosage. A subset of X-linked genes escape XCI, but the extent to which this phenomenon occurs and how it varies across tissues and in a population is as yet unclear. To characterize incidence and variability of escape across individuals and tissues, we conducted a transcriptomic study of escape in adipose, skin, lymphoblastoid cell lines and immune cells in 248 healthy individuals exhibiting skewed XCI. We quantify XCI escape from a linear model of genes' allelic fold-change and XIST-based degree of XCI skewing. We identify 62 genes, including 19 lncRNAs, with previously unknown patterns of escape. We find a range of tissue-specificity, with 11% of genes escaping XCI constitutively across tissues and 23% demonstrating tissue-restricted escape, including cell type-specific escape across immune cells of the same individual. We also detect substantial inter-individual variability in escape. Monozygotic twins share more similar escape than dizygotic twins, indicating that genetic factors may underlie inter-individual differences in escape. However, discordant escape also occurs within monozygotic co-twins, suggesting environmental factors also influence escape. Altogether, these data indicate that XCI escape is an under-appreciated source of transcriptional differences, and an intricate phenotype impacting variable trait expressivity in females.
Collapse
|
24
|
Zhong H, Liu S, Zhu J, Wu L. Associations between genetically predicted levels of blood metabolites and pancreatic cancer risk. Int J Cancer 2023; 153:103-110. [PMID: 36757187 DOI: 10.1002/ijc.34466] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 01/14/2023] [Accepted: 01/30/2023] [Indexed: 02/10/2023]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive solid malignancies, which is featured by systematic metabolism. Thus, a better understanding of metabolic dysregulation in PDAC is important to better characterize its etiology. Here, we performed a large metabolome-wide association study (MWAS) to systematically explore associations between genetically predicted metabolite levels in blood and PDAC risk. Using data from 881 subjects of European descent in the TwinsUK Project, comprehensive genetic models were built to predict serum metabolite levels. These prediction models were applied to the genetic data of 8275 cases and 6723 controls included in the PanScan (I, II and III) and PanC4 consortia. After assessing the metabolite-PDAC risk associations by a slightly modified TWAS/FUSION framework, we identified five metabolites (including two dipeptides) showing significant associations with PDAC risk at false discovery rate (FDR) <0.05. Integrated with gut microbial information, two-sample Mendelian randomization (MR) analyses were further performed to investigate the relationship among serum metabolites, gut microbiome features and PDAC. The flavonoid-degrading bacteria Flavonifractor sp90199495 was found to be associated with metabolite X-21849 and it was also shown to be associated with PDAC risk. Collectively, our study identified novel candidate metabolites for PDAC risk, which could lead to new insights into the etiology of PDAC and improved treatment options.
Collapse
Affiliation(s)
- Hua Zhong
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Shuai Liu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Jingjing Zhu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| |
Collapse
|
25
|
R HC, Kumar S U, R G, Naayanan PJ, Sathiyarajeswaren P, Devi MSS, K SS, Doss C GP. An integrated investigation of structural and pathway alteration caused by PIK3CA and TP53 mutations identified in cfDNA of metastatic breast cancer. J Cell Biochem 2023; 124:188-204. [PMID: 36563059 DOI: 10.1002/jcb.30354] [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: 09/27/2022] [Revised: 11/12/2022] [Accepted: 11/24/2022] [Indexed: 12/24/2022]
Abstract
In peripheral blood, cell-free DNA (cfDNA) contains circulating tumor DNA (ctDNA), which indicates molecular abnormalities in metastatic breast tumor tissue. The sequencing of cfDNA of Metastatic Breast Cancer (MBC) patients allows assessment of therapy response and noninvasive treatment. In the proposed study, clinically significant alterations in PIK3CA and TP53 genes associated with MBC resulting in a missense substitution of His1047Arg and Arg282Trp from an next-generation sequencing-based multi-gene panel were reported in a cfDNA of a patient with MBC. To investigate the impact of the reported mutation, we used molecular docking, molecular dynamics simulation, network analysis, and pathway analysis. Molecular Docking analysis determined the distinct binding pattern revealing H1047R-ATP complex has a higher number of Hydrogen bonds (H-bonds) and binding affinity with a slight difference compared to the PIK3CA-ATP complex. Following, molecular dynamics simulation for 200 ns, of which H1047R-ATP complex resulted in the instability of PIK3CA. Similarly, for TP53 mutant R282W, the zinc-free state (apo) and zinc-bounded (holo) complexes were investigated for conformational change between apo and holo complexes, of which the holo complex mutant R282W was unstable. To validate the conformational change of PIK3CA and TP53, 80% mutation of H1047R in the kinase domain of p110α expressed ubiquitously in PIK3CA protein that alters PI3K pathway, while R282W mutation in DNA binding helix (H2) region of P53 protein inhibits the transcription factor in P53 pathway causing MBC. According to our findings, the extrinsic (hypoxia, oxidative stress, and acidosis); intrinsic factors (MYC amplification) in PIK3CA and TP53 mutations will provide potential insights for developing novel therapeutic methods for MBC therapy.
Collapse
Affiliation(s)
- Hephzibah Cathryn R
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Udhaya Kumar S
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Gnanasambandan R
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | | | | | - M S Shree Devi
- Siddha Central Research Institute (CCRS), Chennai, Tamil Nadu, India
| | - Satish Srinivas K
- Department of Radiation Oncology, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, India
| | - George Priya Doss C
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| |
Collapse
|
26
|
Brooks-Pollock E, Northstone K, Pellis L, Scarabel F, Thomas A, Nixon E, Matthews DA, Bowyer V, Garcia MP, Steves CJ, Timpson NJ, Danon L. Voluntary risk mitigation behaviour can reduce impact of SARS-CoV-2: a real-time modelling study of the January 2022 Omicron wave in England. BMC Med 2023; 21:25. [PMID: 36658548 PMCID: PMC9851586 DOI: 10.1186/s12916-022-02714-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 12/15/2022] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Predicting the likely size of future SARS-CoV-2 waves is necessary for public health planning. In England, voluntary "plan B" mitigation measures were introduced in December 2021 including increased home working and face coverings in shops but stopped short of restrictions on social contacts. The impact of voluntary risk mitigation behaviours on future SARS-CoV-2 burden is unknown. METHODS We developed a rapid online survey of risk mitigation behaviours ahead of the winter 2021 festive period and deployed in two longitudinal cohort studies in the UK (Avon Longitudinal Study of Parents and Children (ALSPAC) and TwinsUK/COVID Symptom Study (CSS) Biobank) in December 2021. Using an individual-based, probabilistic model of COVID-19 transmission between social contacts with SARS-CoV-2 Omicron variant parameters and realistic vaccine coverage in England, we predicted the potential impact of the SARS-CoV-2 Omicron wave in England in terms of the effective reproduction number and cumulative infections, hospital admissions and deaths. Using survey results, we estimated in real-time the impact of voluntary risk mitigation behaviours on the Omicron wave in England, if implemented for the entire epidemic wave. RESULTS Over 95% of survey respondents (NALSPAC = 2686 and NTwins = 6155) reported some risk mitigation behaviours, with vaccination and using home testing kits reported most frequently. Less than half of those respondents reported that their behaviour was due to "plan B". We estimate that without risk mitigation behaviours, the Omicron variant is consistent with an effective reproduction number between 2.5 and 3.5. Due to the reduced vaccine effectiveness against infection with the Omicron variant, our modelled estimates suggest that between 55% and 60% of the English population could be infected during the current wave, translating into between 12,000 and 46,000 cumulative deaths, depending on assumptions about severity and vaccine effectiveness. The actual number of deaths was 15,208 (26 November 2021-1 March 2022). We estimate that voluntary risk reduction measures could reduce the effective reproduction number to between 1.8 and 2.2 and reduce the cumulative number of deaths by up to 24%. CONCLUSIONS Predicting future infection burden is affected by uncertainty in disease severity and vaccine effectiveness estimates. In addition to biological uncertainty, we show that voluntary measures substantially reduce the projected impact of the SARS-CoV-2 Omicron variant but that voluntary measures alone would be unlikely to completely control transmission.
Collapse
Affiliation(s)
- Ellen Brooks-Pollock
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Kate Northstone
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Lorenzo Pellis
- Department of Mathematics, University of Manchester, Manchester, UK
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - Amy Thomas
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Emily Nixon
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- The Alan Turing Institute, London, UK
| | - David A Matthews
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Vicky Bowyer
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Maria Paz Garcia
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Claire J Steves
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Nicholas J Timpson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK
| | - Leon Danon
- Department of Engineering Mathematics, University of Bristol, Bristol, UK
| |
Collapse
|
27
|
Firdous A, Gopalakrishnan V, Vo N, Sowa G. Challenges and opportunities for omics-based precision medicine in chronic low back pain. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2022:10.1007/s00586-022-07457-8. [PMID: 36565345 DOI: 10.1007/s00586-022-07457-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/27/2022] [Accepted: 11/07/2022] [Indexed: 12/25/2022]
Abstract
PURPOSE Chronic low back pain (cLBP) is a common health condition worldwide and a leading cause of disability with an estimated lifetime prevalence of 80-90% in industrialized countries. However, we have had limited success in treating cLBP likely due to its non-specific heterogeneous nature that goes beyond detectable anatomical changes. We propose that omics technologies as precision medicine tools are well suited to provide insight into its pathophysiology and provide diagnostic markers and therapeutic targets. Therefore, in this review, we explore the current state of omics technologies in the diagnosis and classification of cLBP. We identify factors that may serve as markers to differentiate between acute and chronic cases of low back pain (LBP). Finally, we also discuss some challenges that must be overcome to successfully apply precision medicine to the diagnosis and treatment of cLBP. METHODS A literature search for the current applications of omics technologies to chronic low back pain was performed using the following search terms- "back pain," "low back pain," "proteomics," "transcriptomics", "epigenomics," "genomics," "omics." We reviewed molecular markers identified from 35 studies which hold promise in providing information regarding molecular insights into cLBP. RESULTS GWAS studies have found evidence for the role of single nucleotide polymorphisms (SNPs) associated with pain pathways in individuals with cLBP. Epigenomic modifications in patients with cLBP have been found to be enriched among genes involved in immune signaling and inflammation. Transcriptomics profiles of patients with cLBP show multiple lines of evidence for the role of inflammation in cLBP. The glycomics profiles of patients with cLBP are similar to those of patients with inflammatory conditions. Proteomics and microbiomics show promise but have limited studies currently. CONCLUSION Omics technologies have identified associations between inflammatory and pain pathways in the pathophysiology of cLBP. However, in order to integrate information across the range of studies, it is important for the field to identify and adopt standardized definitions of cLBP and control patients. Additionally, most papers have applied a single omics method to a sampling of cLBP patients which have yielded limited insight into the pathophysiology of cLBP. Therefore, we recommend a multi-omics approach applied to large global consortia for advancing subphenotyping and better management of cLBP, via improved identification of diagnostic markers and therapeutic targets.
Collapse
Affiliation(s)
- Ayesha Firdous
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
| | | | - Nam Vo
- Department of Orthopedic Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Gwendolyn Sowa
- Department of Orthopedic Surgery, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| |
Collapse
|
28
|
Nicolaou N, Kilduff M. Empowerment Mitigates Gender Differences in Tertius Iungens Brokering. ORGANIZATION SCIENCE 2022. [DOI: 10.1287/orsc.2022.1628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Tertius iungens brokering that brings together people who might not otherwise meet is crucial for organizational effectiveness. But we know little about whether and why women and men differ in their propensity to engage in this brokering. Our paper focuses on the origins and mitigation of gender differences in the propensity to bring people together. In study 1, we showed that the Totterdell et al. [Totterdell P, Holman D, Hukin A (2008) Social networkers: Measuring and examining individual differences in propensity to connect with others. Soc. Networks 30(4):283–296] propensity-to-join-others scale that we used in study 2 and the Obstfeld [Obstfeld D (2005) Social networks, the tertius iungens orientation, and involvement in innovation. Admin. Sci. Quart. 50(1):100–130] tertius iungens scale overlapped not only conceptually, but also empirically, and that these measures of tertius iungens were distinct from mediation- and separation-brokering propensities [Grosser TJ, Obstfeld D, Labianca G, Borgatti SP (2019) Measuring mediation and separation brokerage orientations: A further step toward studying the social network brokerage process. Acad. Management Discoveries 5(2):114–136]. In study 2, we used a natural experiment to examine the tertius iungens brokering propensities of 876 identical and 625 fraternal same-sex twins. We found that brokering propensity was lower for women than for men, although the propensity toward sociability in terms of making friends and acquaintances was lower for men. We also found that for women, relative to men, tertius iungens brokering propensity was largely affected by environmental influences, such as the experience of stereotyping and discrimination, rather than representing an inherited disposition. Moreover, the differences between men and women with respect to brokering were mitigated for empowered samples, such as well-educated or entrepreneurial individuals. Our research asks new questions about how environmental pressures and empowerment affect social networking. Gender differences in brokering may be amenable to mitigation through empowering practices that include education and entrepreneurial experience.
Collapse
Affiliation(s)
- Nicos Nicolaou
- Warwick Business School, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Martin Kilduff
- UCL School of Management, University College London, London E14 5AA, United Kingdom
| |
Collapse
|
29
|
Mamgain G, Naithani M, Patra P, Mamgain M, Morang S, Nayak J, Kumar K, Singh S, Bakliwal A, Rajoreya A, Vaniyath S, Chattopadhyay D, Chetia R, Gupta A, Dhingra G, Sundriyal D, Nath UK. Next-Generation Sequencing Highlights of Diffuse Large B-cell Lymphoma in a Tertiary Care Hospital in North India. Cureus 2022; 14:e28241. [PMID: 36158348 PMCID: PMC9489829 DOI: 10.7759/cureus.28241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/21/2022] [Indexed: 11/24/2022] Open
Abstract
Introduction: Next-generation sequencing (NGS) elucidates the diffuse large B-cell lymphoma (DLBCL) genetic characteristics by finding recurrent and novel somatic mutations. This observational study attempted to create an NGS panel with a focus on identifying novel somatic mutations which could have potential clinical and therapeutic implications. This panel was created to look for mutations in 133 genes chosen on basis of a literature review and it was used to sequence the tumor DNA of 20 DLBCL patients after a centralized histopathologic review. Methods: The study included 20 patients having DLBCL. The quality and quantity of tumor cells were accessed by H&E staining and correlated with histopathology and Immunohistochemistry (IHC) status. Patients were grouped as ABC (activated B-cell), PMBL (primary mediastinal large B-cell lymphoma), and other or unclassified subtypes. The lymphoma panel of 133 was designed on targeted sequencing of multiple genes for the coding regions through NGS. The libraries were prepared and sequenced using the Illumina platform. The alignment of obtained sequences was performed using Burrows-Wheeler Aligner and identification of somatic mutations was done using LoFreq (version 2) variant caller. The mutations were annotated using an annotation pipeline (VariMAT). Previously published literature and databases were used for the annotation of clinically relevant mutations. The common variants were filtered for reporting based on the presence in various population databases (1000G, ExAC, EVS, 1000Japanese, dbSNP, UK10K, MedVarDb). A custom read-depth-based algorithm was used to determine CNV (Copy Number Variants) from targeted sequencing experiments. Rare CNVs were detected using a comparison of the test data read-depths with the matched reference dataset. Reportable mutations were prioritized and prepared based on AMP-ASCO-CAP (Association for Molecular Pathology-American Society of Clinical Oncology-College of American Pathologists), WHO guidelines, and also based on annotation metrics from OncoMD (a knowledge base of genomic alterations). Results: The informativity of the panel was 95 percent. NOTCH 1 was the most frequently mutated gene in 16.1% of patients followed by 12.9% who had ARID1A mutations. MYD88 and TP53 mutations were detected in 9.6% of the patient while 6.4% of patients had CSF3R mutations. NOTCH 1 and TP 53 are the most frequently reported gene in the middle age group (40-60). Mutation in MYD88 is reported in every age group. MYD88 (51%) is the most common mutation in ABC subtypes of DLBCL, followed by NOTCH 1 (44%) and SOCS 1 (33%) according to our findings. NOTCH 1 mutations are frequent in ABC and PMBL subtypes. Closer investigation reveals missense mutation is the most frequent mutation observed in the total cohort targeting 68.4% followed by frameshift deletion reported in 26.3%. Six novel variants have been discovered in this study. Conclusions: This study demonstrates the high yield of information in DLBCL using the NGS Lymphoma panel. Results also highlight the molecular heterogeneity of DLBCL subtypes which indicates the need for further studies to make the results of the NGS more clinically relevant.
Collapse
|
30
|
El-Sayed Moustafa JS, Jackson AU, Brotman SM, Guan L, Villicaña S, Roberts AL, Zito A, Bonnycastle L, Erdos MR, Narisu N, Stringham HM, Welch R, Yan T, Lakka T, Parker S, Tuomilehto J, Seow J, Graham C, Huettner I, Acors S, Kouphou N, Wadge S, Duncan EL, Steves CJ, Doores KJ, Malim MH, Collins FS, Pajukanta P, Boehnke M, Koistinen HA, Laakso M, Falchi M, Bell JT, Scott LJ, Mohlke KL, Small KS. ACE2 expression in adipose tissue is associated with cardio-metabolic risk factors and cell type composition-implications for COVID-19. Int J Obes (Lond) 2022; 46:1478-1486. [PMID: 35589964 PMCID: PMC9119844 DOI: 10.1038/s41366-022-01136-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 04/21/2022] [Accepted: 04/28/2022] [Indexed: 01/14/2023]
Abstract
BACKGROUND COVID-19 severity varies widely. Although some demographic and cardio-metabolic factors, including age and obesity, are associated with increasing risk of severe illness, the underlying mechanism(s) are uncertain. SUBJECTS/METHODS In a meta-analysis of three independent studies of 1471 participants in total, we investigated phenotypic and genetic factors associated with subcutaneous adipose tissue expression of Angiotensin I Converting Enzyme 2 (ACE2), measured by RNA-Seq, which acts as a receptor for SARS-CoV-2 cellular entry. RESULTS Lower adipose tissue ACE2 expression was associated with multiple adverse cardio-metabolic health indices, including type 2 diabetes (T2D) (P = 9.14 × 10-6), obesity status (P = 4.81 × 10-5), higher serum fasting insulin (P = 5.32 × 10-4), BMI (P = 3.94 × 10-4), and lower serum HDL levels (P = 1.92 × 10-7). ACE2 expression was also associated with estimated proportions of cell types in adipose tissue: lower expression was associated with a lower proportion of microvascular endothelial cells (P = 4.25 × 10-4) and higher proportion of macrophages (P = 2.74 × 10-5). Despite an estimated heritability of 32%, we did not identify any proximal or distal expression quantitative trait loci (eQTLs) associated with adipose tissue ACE2 expression. CONCLUSIONS Our results demonstrate that individuals with cardio-metabolic features known to increase risk of severe COVID-19 have lower background ACE2 levels in this highly relevant tissue. Reduced adipose tissue ACE2 expression may contribute to the pathophysiology of cardio-metabolic diseases, as well as the associated increased risk of severe COVID-19.
Collapse
Affiliation(s)
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Sarah M Brotman
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Li Guan
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Amy L Roberts
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Antonino Zito
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Genetics, Harvard Medical School, Boston, MA, 02114, USA
| | - Lori Bonnycastle
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Michael R Erdos
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Narisu Narisu
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Ryan Welch
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Tingfen Yan
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Timo Lakka
- Institute of Biomedicine/Physiology, University of Eastern Finland, Kuopio, Finland
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
| | - Stephen Parker
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jaakko Tuomilehto
- University of Helsinki and Department of Medicine, Helsinki University Hospital, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Jeffrey Seow
- Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, UK
| | - Carl Graham
- Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, UK
| | - Isabella Huettner
- Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, UK
| | - Sam Acors
- Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, UK
| | - Neophytos Kouphou
- Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, UK
| | - Samuel Wadge
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Emma L Duncan
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Katie J Doores
- Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, UK
| | - Michael H Malim
- Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, UK
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Päivi Pajukanta
- Department of Human Genetics and Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Heikki A Koistinen
- University of Helsinki and Department of Medicine, Helsinki University Hospital, Helsinki, Finland
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland, Kuopio, Finland
- Kuopio University Hospital, Kuopio, Finland
| | - Mario Falchi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| |
Collapse
|
31
|
Gomari DP, Schweickart A, Cerchietti L, Paietta E, Fernandez H, Al-Amin H, Suhre K, Krumsiek J. Variational autoencoders learn transferrable representations of metabolomics data. Commun Biol 2022; 5:645. [PMID: 35773471 PMCID: PMC9246987 DOI: 10.1038/s42003-022-03579-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 06/10/2022] [Indexed: 01/14/2023] Open
Abstract
Dimensionality reduction approaches are commonly used for the deconvolution of high-dimensional metabolomics datasets into underlying core metabolic processes. However, current state-of-the-art methods are widely incapable of detecting nonlinearities in metabolomics data. Variational Autoencoders (VAEs) are a deep learning method designed to learn nonlinear latent representations which generalize to unseen data. Here, we trained a VAE on a large-scale metabolomics population cohort of human blood samples consisting of over 4500 individuals. We analyzed the pathway composition of the latent space using a global feature importance score, which demonstrated that latent dimensions represent distinct cellular processes. To demonstrate model generalizability, we generated latent representations of unseen metabolomics datasets on type 2 diabetes, acute myeloid leukemia, and schizophrenia and found significant correlations with clinical patient groups. Notably, the VAE representations showed stronger effects than latent dimensions derived by linear and non-linear principal component analysis. Taken together, we demonstrate that the VAE is a powerful method that learns biologically meaningful, nonlinear, and transferrable latent representations of metabolomics data.
Collapse
Affiliation(s)
- Daniel P. Gomari
- grid.4567.00000 0004 0483 2525Institute of Computational Biology, Helmholtz Center Munich—German Research Center for Environmental Health, 85764 Neuherberg, Germany ,grid.6936.a0000000123222966Technical University of Munich—School of Life Sciences, 85354 Freising, Germany ,grid.168010.e0000000419368956Department of Genetics, Stanford University School of Medicine, Stanford, CA USA
| | - Annalise Schweickart
- grid.5386.8000000041936877XDepartment of Physiology and Biophysics, Weill Cornell Medicine, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, New York, NY 10021 USA
| | - Leandro Cerchietti
- grid.5386.8000000041936877XDepartment of Medicine, Hematology and Oncology Division, Weill Cornell Medicine, New York, 10065 NY USA
| | - Elisabeth Paietta
- grid.251993.50000000121791997Albert Einstein College of Medicine-Montefiore Medical Center, Bronx, NY USA
| | - Hugo Fernandez
- grid.489080.d0000 0004 0444 4637Moffitt Malignant Hematology & Cellular Therapy at Memorial Healthcare System, Pembroke Pines, FL USA
| | - Hassen Al-Amin
- grid.416973.e0000 0004 0582 4340Department of Psychiatry, Weill Cornell Medicine—Qatar, Education City, P.O. Box 24144, Doha, Qatar
| | - Karsten Suhre
- grid.416973.e0000 0004 0582 4340Department of Physiology and Biophysics, Weill Cornell Medical College—Qatar Education City, Doha, Qatar
| | - Jan Krumsiek
- grid.5386.8000000041936877XDepartment of Physiology and Biophysics, Weill Cornell Medicine, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, New York, NY 10021 USA
| |
Collapse
|
32
|
Explainable Machine Learning for Longitudinal Multi-Omic Microbiome. MATHEMATICS 2022. [DOI: 10.3390/math10121994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Over the years, research studies have shown there is a key connection between the microbial community in the gut, genes, and immune system. Understanding this association may help discover the cause of complex chronic idiopathic disorders such as inflammatory bowel disease. Even though important efforts have been put into the field, the functions, dynamics, and causation of dysbiosis state performed by the microbial community remains unclear. Machine learning models can help elucidate important connections and relationships between microbes in the human host. Our study aims to extend the current knowledge of associations between the human microbiome and health and disease through the application of dynamic Bayesian networks to describe the temporal variation of the gut microbiota and dynamic relationships between taxonomic entities and clinical variables. We develop a set of preprocessing steps to clean, filter, select, integrate, and model informative metagenomics, metatranscriptomics, and metabolomics longitudinal data from the Human Microbiome Project. This study accomplishes novel network models with satisfactory predictive performance (accuracy = 0.648) for each inflammatory bowel disease state, validating Bayesian networks as a framework for developing interpretable models to help understand the basic ways the different biological entities (taxa, genes, metabolites) interact with each other in a given environment (human gut) over time. These findings can serve as a starting point to advance the discovery of novel therapeutic approaches and new biomarkers for precision medicine.
Collapse
|
33
|
Li R, Wang X, Zhang Y, Xu X, Wang L, Wei C, Liu L, Wang Z, Li Y. Analysis of Tryptophan and Its Main Metabolite Kynurenine and the Risk of Multiple Cancers Based on the Bidirectional Mendelian Randomization Analysis. Front Oncol 2022; 12:852718. [PMID: 35494045 PMCID: PMC9046840 DOI: 10.3389/fonc.2022.852718] [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: 01/11/2022] [Accepted: 03/15/2022] [Indexed: 12/14/2022] Open
Abstract
BackgroundTryptophan and its metabolites have been found related to various cancers, but the direction of this relationship is still unclear. The purpose of this study is to explore the causal associations of tryptophan and kynurenine with multiple cancers based on the bidirectional Mendelian randomization analysis.MethodsThe data of a genome-wide association study meta-analysis on 7,824 individuals was used to explore the genetic variants strongly associated with tryptophan and kynurenine. Genetic instruments of four specific cancers were obtained from available summary-level data of 323,590 European participants. Bidirectional Mendelian randomization analysis was conducted to examine possible causality. Sensitivity analysis was performed to test heterogeneity and horizontal pleiotropy. COX regression analysis was conducted to explore associations between dietary tryptophan and cancer mortality in NHANES 1988-1994.ResultsNo evidence of any causal association of tryptophan and kynurenine with the risk of four specific cancers was shown, except for weak correlations were suggested between lung or prostate cancer and kynurenine. Multiple sensitivity analyses generated similar results. Our findings from COX regression analysis were consistent with the above results.ConclusionsOur study did not find any causal relationship between tryptophan and kynurenine and multiple cancers. The associations still need further research.
Collapse
|
34
|
Cherny SS, Williams FMK, Livshits G. Genetic and environmental correlational structure among metabolic syndrome endophenotypes. Ann Hum Genet 2022; 86:225-236. [PMID: 35357000 DOI: 10.1111/ahg.12465] [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: 08/18/2021] [Revised: 03/02/2022] [Accepted: 03/09/2022] [Indexed: 11/29/2022]
Abstract
Metabolic syndrome (MetS) is diagnosed by the presence of high scores on three or more metabolic traits, including systolic and diastolic blood pressure (SBP, DBP), glucose and insulin levels, cholesterol and triglyceride (TG) levels, and central obesity. A diagnosis of MetS is associated with increased risk of cardiovascular disease and type 2 diabetes. The components of MetS have long been demonstrated to have substantial genetic components, but their genetic overlap is less well understood. The present paper takes a multi-prong approach to examining the extent of this genetic overlap. This includes the quantitative genetic and additive Bayesian network modeling of the large TwinsUK project and examination of the results of genome-wide association study (GWAS) of UK Biobank data through use of LD score regression and examination of the number of genes and pathways identified in the GWASes which overlap across MetS traits. Results demonstrate a modest genetic overlap, and the genetic correlations obtained from TwinsUK and UK Biobank are nearly identical. However, these correlations imply more genetic dissimilarity than similarity. Furthermore, examination of the extent of overlap in significant GWAS hits, both at the gene and pathway level, again demonstrates only modest but significant genetic overlap. This lends support to the idea that in clinical treatment of MetS, treating each of the components individually may be an important way to address MetS.
Collapse
Affiliation(s)
- Stacey S Cherny
- Department of Anatomy and Anthropology, Tel Aviv University, Tel Aviv, Israel
| | | | - Gregory Livshits
- Department of Anatomy and Anthropology, Tel Aviv University, Tel Aviv, Israel.,Department of Twin Research and Genetic Epidemiology, King's College London, UK.,Department of Morphological Sciences, The Adelson School of Medicine, Ariel University, Ariel, Israel
| |
Collapse
|
35
|
Le Roy CI, Kurilshikov A, Leeming ER, Visconti A, Bowyer RCE, Menni C, Fachi M, Koutnikova H, Veiga P, Zhernakova A, Derrien M, Spector TD. Yoghurt consumption is associated with changes in the composition of the human gut microbiome and metabolome. BMC Microbiol 2022; 22:39. [PMID: 35114943 PMCID: PMC8812230 DOI: 10.1186/s12866-021-02364-2] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Accepted: 10/18/2021] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Yoghurt contains live bacteria that could contribute via modulation of the gut microbiota to its reported beneficial effects such as reduced body weight gain and lower incidence of type 2 diabetes. To date, the association between yoghurt consumption and the composition of the gut microbiota is underexplored. Here we used clinical variables, metabolomics, 16S rRNA and shotgun metagenomic sequencing data collected on over 1000 predominantly female UK twins to define the link between the gut microbiota and yoghurt-associated health benefits. RESULTS According to food frequency questionnaires (FFQ), 73% of subjects consumed yoghurt. Consumers presented a healthier diet pattern (healthy eating index: beta = 2.17 ± 0.34; P = 2.72x10-10) and improved metabolic health characterised by reduced visceral fat (beta = -28.18 ± 11.71 g; P = 0.01). According to 16S rRNA gene analyses and whole shotgun metagenomic sequencing approach consistent taxonomic variations were observed with yoghurt consumption. More specifically, we identified higher abundance of species used as yoghurt starters Streptococcus thermophilus (beta = 0.41 ± 0.051; P = 6.14x10-12) and sometimes added Bifidobacterium animalis subsp. lactis (beta = 0.30 ± 0.052; P = 1.49x10-8) in the gut of yoghurt consumers. Replication in 1103 volunteers from the LifeLines-DEEP cohort confirmed the increase of S. thermophilus among yoghurt consumers. Using food records collected the day prior to faecal sampling we showed than an increase in these two yoghurt bacteria could be transient. Metabolomics analysis revealed that B. animalis subsp. lactis was associated with 13 faecal metabolites including a 3-hydroxyoctanoic acid, known to be involved in the regulation of gut inflammation. CONCLUSIONS Yoghurt consumption is associated with reduced visceral fat mass and changes in gut microbiome including transient increase of yoghurt-contained species (i.e. S. thermophilus and B. lactis).
Collapse
Affiliation(s)
- Caroline Ivanne Le Roy
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, SE1 7EH UK
| | - Alexander Kurilshikov
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Emily R. Leeming
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, SE1 7EH UK
| | - Alessia Visconti
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, SE1 7EH UK
| | - Ruth C. E. Bowyer
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, SE1 7EH UK
| | - Cristina Menni
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, SE1 7EH UK
| | - Mario Fachi
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, SE1 7EH UK
| | | | | | - Alexandra Zhernakova
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Tim D. Spector
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, SE1 7EH UK
| |
Collapse
|
36
|
Hupalo D, Forsberg CW, Goldberg J, Kremen WS, Lyons MJ, Soltis AR, Viollet C, Ursano RJ, Stein MB, Franz CE, Sun YV, Vaccarino V, Smith NL, Dalgard CL, Wilkerson MD, Pollard HB. Rare variant association study of veteran twin whole-genomes links severe depression with a nonsynonymous change in the neuronal gene BHLHE22. World J Biol Psychiatry 2022; 23:295-306. [PMID: 34664540 PMCID: PMC9148382 DOI: 10.1080/15622975.2021.1980316] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVES Major Depressive Disorder (MDD) is a complex neuropsychiatric disease with known genetic associations, but without known links to rare variation in the human genome. Here we aim to identify rare genetic variants associated with MDD using deep whole-genome sequencing data in an independent population. METHODS We report the sequencing of 1,688 whole genomes in a large sample of male-male Veteran twins. Depression status was classified based on a structured diagnostic interview according to DSM-III-R diagnostic criteria. Searching only rare variants in genomic regions from recent GWAS on MDD, we used the optimised sequence kernel association test and Fisher's Exact test to fine map loci associated with severe depression. RESULTS Our analysis identified one gene associated with severe depression, basic helix loop helix e22 (PAdjusted = 0.03) via SKAT-O test between unrelated severely depressed cases compared to unrelated non-depressed controls. The same gene BHLHE22 had a non-silent variant rs13279074 (PAdjusted = 0.032) based on a single variant Fisher's Exact test between unrelated severely depressed cases compared to unrelated non-depressed controls. CONCLUSION The gene BHLHE22 shows compelling genetic evidence of directly impacting the severe depression phenotype. Together these results advance understanding of the genetic contribution to major depressive disorder in a new cohort and link a rare variant to severe forms of the disorder.
Collapse
Affiliation(s)
- Daniel Hupalo
- The American Genome Center, Collaborative Health Initiative Research Program, and Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, MD, USA
| | - Christopher W. Forsberg
- Seattle Epidemiologic Research and Information Center, Office of Research and Development, U.S. Department of Veteran Affairs, Seattle, WA, USA
| | - Jack Goldberg
- Seattle Epidemiologic Research and Information Center, Office of Research and Development, U.S. Department of Veteran Affairs, Seattle, WA, USA;,Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - William S. Kremen
- Department of Psychiatry and of Family Medicine & Public Health, University of California, La Jolla, CA, USA;,VA San Diego Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Michael J. Lyons
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, USA
| | - Anthony R. Soltis
- The American Genome Center, Collaborative Health Initiative Research Program, and Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, MD, USA
| | - Coralie Viollet
- The American Genome Center, Collaborative Health Initiative Research Program, and Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, MD, USA
| | - Robert J. Ursano
- Department of Psychiatry, Uniformed Services University, Bethesda, MD, USA
| | - Murray B. Stein
- Department of Psychiatry and of Family Medicine & Public Health, University of California, La Jolla, CA, USA
| | - Carol E. Franz
- Department of Psychiatry and of Family Medicine & Public Health, University of California, La Jolla, CA, USA
| | - Yan V. Sun
- Department of Epidemiology, Emory University, Atlanta, GA, USA
| | - Viola Vaccarino
- Department of Epidemiology, Emory University, Atlanta, GA, USA
| | - Nicholas L. Smith
- Seattle Epidemiologic Research and Information Center, Office of Research and Development, U.S. Department of Veteran Affairs, Seattle, WA, USA;,Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Clifton L. Dalgard
- The American Genome Center, Collaborative Health Initiative Research Program, and Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, MD, USA;,Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, MD, USA
| | - Matthew D. Wilkerson
- The American Genome Center, Collaborative Health Initiative Research Program, and Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, MD, USA;,Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, MD, USA
| | - Harvey B. Pollard
- The American Genome Center, Collaborative Health Initiative Research Program, and Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, MD, USA;,Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, MD, USA
| |
Collapse
|
37
|
Clark KC, Kwitek AE. Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome. Compr Physiol 2021; 12:3045-3084. [PMID: 34964118 PMCID: PMC9373910 DOI: 10.1002/cphy.c210010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.
Collapse
Affiliation(s)
- Karen C Clark
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Anne E Kwitek
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| |
Collapse
|
38
|
van Dongen J, Gordon SD, McRae AF, Odintsova VV, Mbarek H, Breeze CE, Sugden K, Lundgren S, Castillo-Fernandez JE, Hannon E, Moffitt TE, Hagenbeek FA, van Beijsterveldt CEM, Jan Hottenga J, Tsai PC, Min JL, Hemani G, Ehli EA, Paul F, Stern CD, Heijmans BT, Slagboom PE, Daxinger L, van der Maarel SM, de Geus EJC, Willemsen G, Montgomery GW, Reversade B, Ollikainen M, Kaprio J, Spector TD, Bell JT, Mill J, Caspi A, Martin NG, Boomsma DI. Identical twins carry a persistent epigenetic signature of early genome programming. Nat Commun 2021; 12:5618. [PMID: 34584077 PMCID: PMC8479069 DOI: 10.1038/s41467-021-25583-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 07/19/2021] [Indexed: 02/08/2023] Open
Abstract
Monozygotic (MZ) twins and higher-order multiples arise when a zygote splits during pre-implantation stages of development. The mechanisms underpinning this event have remained a mystery. Because MZ twinning rarely runs in families, the leading hypothesis is that it occurs at random. Here, we show that MZ twinning is strongly associated with a stable DNA methylation signature in adult somatic tissues. This signature spans regions near telomeres and centromeres, Polycomb-repressed regions and heterochromatin, genes involved in cell-adhesion, WNT signaling, cell fate, and putative human metastable epialleles. Our study also demonstrates a never-anticipated corollary: because identical twins keep a lifelong molecular signature, we can retrospectively diagnose if a person was conceived as monozygotic twin.
Collapse
Affiliation(s)
- Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands.
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
| | - Scott D Gordon
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Veronika V Odintsova
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Hamdi Mbarek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | | | - Karen Sugden
- Department of Psychology and Neuroscience and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Sara Lundgren
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | | | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Catharina E M van Beijsterveldt
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Josine L Min
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, SD, USA
| | - Franziska Paul
- Institute of Molecular and Cellular Biology, A*STAR, Singapore, Singapore
| | - Claudio D Stern
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Lucia Daxinger
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Bruno Reversade
- Institute of Molecular and Cellular Biology, A*STAR, Singapore, Singapore
- Genome Institute of Singapore, A*STAR, Singapore, Singapore
- Medical Genetics Department, KOC University, School of Medicine, Istanbul, Turkey
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Avshalom Caspi
- Department of Psychology and Neuroscience and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nicholas G Martin
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| |
Collapse
|
39
|
Mukamel RE, Handsaker RE, Sherman MA, Barton AR, Zheng Y, McCarroll SA, Loh PR. Protein-coding repeat polymorphisms strongly shape diverse human phenotypes. Science 2021; 373:1499-1505. [PMID: 34554798 PMCID: PMC8549062 DOI: 10.1126/science.abg8289] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Many human proteins contain domains that vary in size or copy number because of variable numbers of tandem repeats (VNTRs) in protein-coding exons. However, the relationships of VNTRs to most phenotypes are unknown because of difficulties in measuring such repetitive elements. We developed methods to estimate VNTR lengths from whole-exome sequencing data and impute VNTR alleles into single-nucleotide polymorphism haplotypes. Analyzing 118 protein-altering VNTRs in 415,280 UK Biobank participants for association with 786 phenotypes identified some of the strongest associations of common variants with human phenotypes, including height, hair morphology, and biomarkers of health. Accounting for large-effect VNTRs further enabled fine-mapping of associations to many more protein-coding mutations in the same genes. These results point to cryptic effects of highly polymorphic common structural variants that have eluded molecular analyses to date.
Collapse
Affiliation(s)
- Ronen E Mukamel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
| | - Robert E Handsaker
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard University, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Maxwell A Sherman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Computer Science and Artificial Intelligence Laboratory, MIT, Boston, MA, USA
| | - Alison R Barton
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Bioinformatics and Integrative Genomics Program, Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Yiming Zheng
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard University, Boston, MA, USA
| | - Steven A McCarroll
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard University, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Boston, MA, USA
| |
Collapse
|
40
|
Abtahi H, Gholamzadeh M, Shahmoradi L, Shariat M. An information-based framework for development national twin registry: Scoping review and focus group discussion. Int J Health Plann Manage 2021; 36:1423-1444. [PMID: 34519094 DOI: 10.1002/hpm.3256] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 04/26/2021] [Accepted: 05/18/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Registries in various clinical domains have been established in the last decades. The specific genetic structure of twins has enabled researchers to find answers to the role of genetics and the environment in medical sciences. Thus, twin registries were developed across the world to support twin studies. Our main objective was to devise a conceptual model for developing the national twin registry to ensure the success of this registry. METHODS In this descriptive and qualitative study, the combination of literature review and focus group discussions was applied to achieve suitable models for developing a national twin registry based on lessons learned from founded registries. The qualitative synthesis and reporting results were conducted based on the COREQ checklist. RESULTS According to a systematic literature review, the characteristics and employed strategies employed by established twin registries were recognized. Moreover, based on our objectives, suitable models for registry development were defined. The source of information, the different levels of data, and the information flow were determined based on this model. CONCLUSION Suggesting a conceptual framework for twin registry development at the national level based on the experiences of other countries could contribute to a greater understanding of twin registry implementation efficiently.
Collapse
Affiliation(s)
- Hamidreza Abtahi
- Associate Professor of Pulmonary and Critical Care Department, Thoracic Research Center, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Marsa Gholamzadeh
- Ph.D. Student in Medical Informatics, Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Leila Shahmoradi
- Associate Professor of Health Information Management, Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Mamak Shariat
- Family Health Research Institute, Maternal-Fetal and Neonatal Research Center, Tehran University of Medical Science, Tehran, Iran
| |
Collapse
|
41
|
Meng W, Chan BW, Harris C, Freidin MB, Hebert HL, Adams MJ, Campbell A, Hayward C, Zheng H, Zhang X, Colvin LA, Hales TG, Palmer CNA, Williams FMK, McIntosh A, Smith BH. A genome-wide association study finds genetic variants associated with neck or shoulder pain in UK Biobank. Hum Mol Genet 2021; 29:1396-1404. [PMID: 32246137 PMCID: PMC7254846 DOI: 10.1093/hmg/ddaa058] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 12/19/2022] Open
Abstract
Background Common types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203 309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK. Methods A genome-wide association study was performed adjusting for age, sex, BMI and nine population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication. Results We identified three genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 × 10−11. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 × 10−10 for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 × 10−8 for rs62053992. In the replication stage, among four significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively). Conclusions We have identified three loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain.
Collapse
Affiliation(s)
- Weihua Meng
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Brian W Chan
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Cameron Harris
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Maxim B Freidin
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, SE1 7EH, UK
| | - Harry L Hebert
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Mark J Adams
- Division of Psychiatry, Edinburgh Medical School, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Hua Zheng
- Department of Anaesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xianwei Zhang
- Department of Anaesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lesley A Colvin
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Tim G Hales
- Institute for Academic Anaesthesia, Division of Systems Medicine, School of Medicine, Ninewells Hospital, University of Dundee, Dundee, UK
| | - Colin N A Palmer
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Frances M K Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, SE1 7EH, UK
| | - Andrew McIntosh
- Division of Psychiatry, Edinburgh Medical School, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Blair H Smith
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| |
Collapse
|
42
|
Bagheri M, Wang C, Shi M, Manouchehri A, Murray KT, Murphy MB, Shaffer CM, Singh K, Davis LK, Jarvik GP, Stanaway IB, Hebbring S, Reilly MP, Gerszten RE, Wang TJ, Mosley JD, Ferguson JF. The genetic architecture of plasma kynurenine includes cardiometabolic disease mechanisms associated with the SH2B3 gene. Sci Rep 2021; 11:15652. [PMID: 34341450 PMCID: PMC8329184 DOI: 10.1038/s41598-021-95154-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 07/21/2021] [Indexed: 01/11/2023] Open
Abstract
Inflammation increases the risk of cardiometabolic disease. Delineating specific inflammatory pathways and biomarkers of their activity could identify the mechanistic underpinnings of the increased risk. Plasma levels of kynurenine, a metabolite involved in inflammation, associates with cardiometabolic disease risk. We used genetic approaches to identify inflammatory mechanisms associated with kynurenine variability and their relationship to cardiometabolic disease. We identified single-nucleotide polymorphisms (SNPs) previously associated with plasma kynurenine, including a missense-variant (rs3184504) in the inflammatory gene SH2B3/LNK. We examined the association between rs3184504 and plasma kynurenine in independent human samples, and measured kynurenine levels in SH2B3-knock-out mice and during human LPS-evoked endotoxemia. We conducted phenome scanning to identify clinical phenotypes associated with each kynurenine-related SNP and with a kynurenine polygenic score using the UK-Biobank (n = 456,422), BioVU (n = 62,303), and Electronic Medical Records and Genetics (n = 32,324) databases. The SH2B3 missense variant associated with plasma kynurenine levels and SH2B3-/- mice had significant tissue-specific differences in kynurenine levels.LPS, an acute inflammatory stimulus, increased plasma kynurenine in humans. Mendelian randomization showed increased waist-circumference, a marker of central obesity, associated with increased kynurenine, and increased kynurenine associated with C-reactive protein (CRP). We found 30 diagnoses associated (FDR q < 0.05) with the SH2B3 variant, but not with SNPs mapping to genes known to regulate tryptophan-kynurenine metabolism. Plasma kynurenine may be a biomarker of acute and chronic inflammation involving the SH2B3 pathways. Its regulation lies upstream of CRP, suggesting that kynurenine may be a biomarker of one inflammatory mechanism contributing to increased cardiometabolic disease risk.
Collapse
Affiliation(s)
- Minoo Bagheri
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA
| | - Chuan Wang
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA
| | - Mingjian Shi
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ali Manouchehri
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Katherine T Murray
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Matthew B Murphy
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christian M Shaffer
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kritika Singh
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lea K Davis
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, USA
| | - Ian B Stanaway
- Division of Nephrology, School of Medicine, Harborview Medical Center Kidney Research Institute, University of Washington, Seattle, WA, USA
| | - Scott Hebbring
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Muredach P Reilly
- Irving Institute for Clinical and Translational Research and Division of Cardiology, Columbia University Medical Center, New York, NY, USA
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Thomas J Wang
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, USA
| | - Jonathan D Mosley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jane F Ferguson
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA.
| |
Collapse
|
43
|
Vijay A, Astbury S, Panayiotis L, Marques FZ, Spector TD, Menni C, Valdes AM. Dietary Interventions Reduce Traditional and Novel Cardiovascular Risk Markers by Altering the Gut Microbiome and Their Metabolites. Front Cardiovasc Med 2021; 8:691564. [PMID: 34336953 PMCID: PMC8319029 DOI: 10.3389/fcvm.2021.691564] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 06/08/2021] [Indexed: 11/24/2022] Open
Abstract
Aims: The current study investigates the role of diet in mediating the gut microbiome-cardiovascular association which has not yet been explored in humans. Methods and Results: Using a two-arm dietary intervention study in healthy participants (N = 70), we assessed the effects of omega-3 and fibre supplementation on gut microbiome composition and short-chain fatty acid (SCFA) production. We then investigated how changes in gut microbiome composition correlated with changes in traditional cardiovascular risk factors (cholesterol, triglycerides, blood pressure), cytokines, and novel validated markers such as GlycA and ceramides, previously linked to CVD incidence and mortality. Both interventions resulted in significant drops in blood pressure, cholesterol, proinflammatory cytokines, GlycA and ceramides (all P < 0.05). Decreases in the atherogenic low-density lipoprotein triglyceride fraction, in total serum cholesterol were correlated with increases in butyric acid-production [β(SE) = −0.58 (0.06), P < 0.001; −0.53 (0.04), P < 0.001] and nominally associated with increases in some butyrogenic bacteria. Drops in GlycA were linked to increases in Bifidobacterium [β(SE) = −0.32 (0.04), P = 0.02] and other SCFAs including acetic acid [β(SE) = −0.28 (0.04), P = 0.02] and propionic acid [β(SE) = −0.3 (0.04), P = 0.02]. Additionally, we report for the first-time reductions in specific ceramide ratios that have been shown to predict CVD mortality and major adverse cardiovascular events such as d18:1/16:0, d18:0/24:0, and d18:1/24:1 which were associated with the reduction in the abundance in Colinsella and increases in Bifidobacteriuim and Coprococcus 3 and SCFAs (all P < 0.05). Conclusion: Overall, these findings support the potential of using simple dietary interventions to alter validated biomarkers linked to cardiovascular risk via the gut microbiome composition and its metabolic functions.
Collapse
Affiliation(s)
- Amrita Vijay
- School of Medicine, University of Nottingham, Nottingham, United Kingdom.,Department of Twin Research, King's College London, London, United Kingdom
| | - Stuart Astbury
- School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Louca Panayiotis
- Department of Twin Research, King's College London, London, United Kingdom
| | - Francine Z Marques
- Hypertension Laboratory, School of Biological Sciences, Monash University, Melbourne, VIC, Australia.,Heart Failure Research Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Tim D Spector
- Department of Twin Research, King's College London, London, United Kingdom
| | - Cristina Menni
- Department of Twin Research, King's College London, London, United Kingdom
| | - Ana M Valdes
- School of Medicine, University of Nottingham, Nottingham, United Kingdom.,Department of Twin Research, King's College London, London, United Kingdom
| |
Collapse
|
44
|
Karabegović I, Portilla-Fernandez E, Li Y, Ma J, Maas SCE, Sun D, Hu EA, Kühnel B, Zhang Y, Ambatipudi S, Fiorito G, Huang J, Castillo-Fernandez JE, Wiggins KL, de Klein N, Grioni S, Swenson BR, Polidoro S, Treur JL, Cuenin C, Tsai PC, Costeira R, Chajes V, Braun K, Verweij N, Kretschmer A, Franke L, van Meurs JBJ, Uitterlinden AG, de Knegt RJ, Ikram MA, Dehghan A, Peters A, Schöttker B, Gharib SA, Sotoodehnia N, Bell JT, Elliott P, Vineis P, Relton C, Herceg Z, Brenner H, Waldenberger M, Rebholz CM, Voortman T, Pan Q, Fornage M, Levy D, Kayser M, Ghanbari M. Epigenome-wide association meta-analysis of DNA methylation with coffee and tea consumption. Nat Commun 2021; 12:2830. [PMID: 33990564 PMCID: PMC8121846 DOI: 10.1038/s41467-021-22752-6] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 03/26/2021] [Indexed: 02/03/2023] Open
Abstract
Coffee and tea are extensively consumed beverages worldwide which have received considerable attention regarding health. Intake of these beverages is consistently linked to, among others, reduced risk of diabetes and liver diseases; however, the mechanisms of action remain elusive. Epigenetics is suggested as a mechanism mediating the effects of dietary and lifestyle factors on disease onset. Here we report the results from epigenome-wide association studies (EWAS) on coffee and tea consumption in 15,789 participants of European and African-American ancestries from 15 cohorts. EWAS meta-analysis of coffee consumption reveals 11 CpGs surpassing the epigenome-wide significance threshold (P-value <1.1×10-7), which annotated to the AHRR, F2RL3, FLJ43663, HDAC4, GFI1 and PHGDH genes. Among them, cg14476101 is significantly associated with expression of the PHGDH and risk of fatty liver disease. Knockdown of PHGDH expression in liver cells shows a correlation with expression levels of genes associated with circulating lipids, suggesting a role of PHGDH in hepatic-lipid metabolism. EWAS meta-analysis on tea consumption reveals no significant association, only two CpGs annotated to CACNA1A and PRDM16 genes show suggestive association (P-value <5.0×10-6). These findings indicate that coffee-associated changes in DNA methylation levels may explain the mechanism of action of coffee consumption in conferring risk of diseases.
Collapse
Affiliation(s)
- Irma Karabegović
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Genetic Identification, Erasmus University Medical Center, Rotterdam, the Netherlands
- Epidemiology and Microbial Genomics, National Health Laboratory, Dudelange, Luxembourg
| | | | - Yang Li
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jiantao Ma
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland and the Framingham Heart Study, Framingham, MA, USA
| | - Silvana C E Maas
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Genetic Identification, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Daokun Sun
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Emily A Hu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Brigitte Kühnel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Srikant Ambatipudi
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- AMCHSS, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
- Epigenetics Group, International Agency for Research on Cancer (IARC), Lyon, Cedex 08, France
| | - Giovanni Fiorito
- Laboratory of Biostatistics, Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
| | - Jian Huang
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
- Imperial College NIHR Biomedical Research Centre, London, UK
| | - Juan E Castillo-Fernandez
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
- Epigenetics Programme, Babraham Institute, Cambridge, UK
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, CHRU, Seattle, WA, USA
| | - Niek de Klein
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Sara Grioni
- Epidemiology and Prevention Unit, IRCCS National Cancer Institute Foundation, Milan, Italy
| | - Brenton R Swenson
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, CHRU, Seattle, WA, USA
| | - Silvia Polidoro
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
- Italian Institute for Genomic Medicine (IIGM, former HuGeF), c/o IRCCS Candiolo, Candiolo, Italy
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam UMC, Amsterdam, the Netherlands
| | - Cyrille Cuenin
- Epigenetics Group, International Agency for Research on Cancer (IARC), Lyon, Cedex 08, France
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan
- Genomic Medicine Research Core Laboratory, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - Ricardo Costeira
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Veronique Chajes
- Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Kim Braun
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Niek Verweij
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Genomics plc, Park End St, Oxford, UK
| | - Anja Kretschmer
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Robert J de Knegt
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Abbas Dehghan
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
| | - Annette Peters
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sina A Gharib
- Computational Medicine Core at Center for Lung Biology, Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, CHRU, Seattle, WA, USA
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Paul Elliott
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
- Imperial College NIHR Biomedical Research Centre, London, UK
- Health Data Research UK-London, London, UK
| | - Paolo Vineis
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Zdenko Herceg
- Epigenetics Group, International Agency for Research on Cancer (IARC), Lyon, Cedex 08, France
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Trudy Voortman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Qiuwei Pan
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Myriam Fornage
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland and the Framingham Heart Study, Framingham, MA, USA
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
- Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
| |
Collapse
|
45
|
Stausberg J, Harkener S, Semler SC. Recent Trends in Patient Registries for Health Services Research. Methods Inf Med 2021; 60:e1-e8. [PMID: 33862662 PMCID: PMC8294939 DOI: 10.1055/s-0041-1724104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Background
Patient registries are an established methodology in health services research. Since more than 150 years, registries collect information concerning groups of similar patients to answer research questions. Elaborated recommendations about an appropriate development and an efficient operation of registries are available. However, the scene changes rapidly.
Objectives
The aim of the study is to describe current trends in registry research for health services research.
Methods
Registries developed within a German funding scheme for model registries in health services research were analyzed. The observations were compared with recent recommendations of the Agency for Healthcare Research and Quality (AHRQ) on registries in the 21st century.
Results
Analyzing six registries from the funding scheme revealed the following trends: recruiting healthy individuals, representing familial or other interpersonal relationships, recording of patient-reported experiences or outcomes, accepting participants as study sites, active informing of participants, integrating the registry with other data collections, and transferring data from the registry to electronic patient records. This list partly complies with the issues discussed by the AHRQ. The AHRQ structured its ideas in five chapters, increasing focus on the patient, engaging patients as partners, digital health and patient registries, direct-to-patient registry, and registry networks.
Conclusion
For the near future, it can be said that the concept and the design of a registry should place the patient in the center. Registries will be increasingly linked together and interconnected with other data collections. New challenges arise regarding the management of data quality and the interpretation of results from less controlled settings. Here, further research related to the methodology of registries is needed.
Collapse
Affiliation(s)
- Jürgen Stausberg
- Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), Faculty of Medicine, University Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany
| | - Sonja Harkener
- Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), Faculty of Medicine, University Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany
| | - Sebastian C Semler
- TMF Technology, Methods, and Infrastructure for Networked Medical Research, Berlin, Germany
| |
Collapse
|
46
|
Gu Z, El Bouhaddani S, Pei J, Houwing-Duistermaat J, Uh HW. Statistical integration of two omics datasets using GO2PLS. BMC Bioinformatics 2021; 22:131. [PMID: 33736604 PMCID: PMC7977326 DOI: 10.1186/s12859-021-03958-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 01/06/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Nowadays, multiple omics data are measured on the same samples in the belief that these different omics datasets represent various aspects of the underlying biological systems. Integrating these omics datasets will facilitate the understanding of the systems. For this purpose, various methods have been proposed, such as Partial Least Squares (PLS), decomposing two datasets into joint and residual subspaces. Since omics data are heterogeneous, the joint components in PLS will contain variation specific to each dataset. To account for this, Two-way Orthogonal Partial Least Squares (O2PLS) captures the heterogeneity by introducing orthogonal subspaces and better estimates the joint subspaces. However, the latent components spanning the joint subspaces in O2PLS are linear combinations of all variables, while it might be of interest to identify a small subset relevant to the research question. To obtain sparsity, we extend O2PLS to Group Sparse O2PLS (GO2PLS) that utilizes biological information on group structures among variables and performs group selection in the joint subspace. RESULTS The simulation study showed that introducing sparsity improved the feature selection performance. Furthermore, incorporating group structures increased robustness of the feature selection procedure. GO2PLS performed optimally in terms of accuracy of joint score estimation, joint loading estimation, and feature selection. We applied GO2PLS to datasets from two studies: TwinsUK (a population study) and CVON-DOSIS (a small case-control study). In the first, we incorporated biological information on the group structures of the methylation CpG sites when integrating the methylation dataset with the IgG glycomics data. The targeted genes of the selected methylation groups turned out to be relevant to the immune system, in which the IgG glycans play important roles. In the second, we selected regulatory regions and transcripts that explained the covariance between regulomics and transcriptomics data. The corresponding genes of the selected features appeared to be relevant to heart muscle disease. CONCLUSIONS GO2PLS integrates two omics datasets to help understand the underlying system that involves both omics levels. It incorporates external group information and performs group selection, resulting in a small subset of features that best explain the relationship between two omics datasets for better interpretability.
Collapse
Affiliation(s)
- Zhujie Gu
- Department of Data Science and Biostatistics, UMC Utrecht, div. Julius Centre, Huispost Str. 6.131, 3508 GA, Utrecht, The Netherlands.
| | - Said El Bouhaddani
- Department of Data Science and Biostatistics, UMC Utrecht, div. Julius Centre, Huispost Str. 6.131, 3508 GA, Utrecht, The Netherlands
| | - Jiayi Pei
- Department of Cardiology, UMC Utrecht, Huispost Str. 6.131, 3508 GA, Utrecht, The Netherlands
| | - Jeanine Houwing-Duistermaat
- Department of Data Science and Biostatistics, UMC Utrecht, div. Julius Centre, Huispost Str. 6.131, 3508 GA, Utrecht, The Netherlands.,Department of Statistics, University of Leeds, LS2 9JT, Leeds, UK.,Department of Statistical Sciences, University of Bologna, Bologna, Italy
| | - Hae-Won Uh
- Department of Data Science and Biostatistics, UMC Utrecht, div. Julius Centre, Huispost Str. 6.131, 3508 GA, Utrecht, The Netherlands
| |
Collapse
|
47
|
Jeon Y, Jeon S, Blazyte A, Kim YJ, Lee JJ, Bhak Y, Cho YS, Park Y, Noh EK, Manica A, Edwards JS, Bolser D, Kim S, Lee Y, Yoon C, Lee S, Kim BC, Park NH, Bhak J. Welfare Genome Project: A Participatory Korean Personal Genome Project With Free Health Check-Up and Genetic Report Followed by Counseling. Front Genet 2021; 12:633731. [PMID: 33633791 PMCID: PMC7900555 DOI: 10.3389/fgene.2021.633731] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 01/20/2021] [Indexed: 12/27/2022] Open
Abstract
The Welfare Genome Project (WGP) provided 1,000 healthy Korean volunteers with detailed genetic and health reports to test the social perception of integrating personal genetic and healthcare data at a large-scale. WGP was launched in 2016 in the Ulsan Metropolitan City as the first large-scale genome project with public participation in Korea. The project produced a set of genetic materials, genotype information, clinical data, and lifestyle survey answers from participants aged 20–96. As compensation, the participants received a free general health check-up on 110 clinical traits, accompanied by a genetic report of their genotypes followed by genetic counseling. In a follow-up survey, 91.0% of the participants indicated that their genetic reports motivated them to improve their health. Overall, WGP expanded not only the general awareness of genomics, DNA sequencing technologies, bioinformatics, and bioethics regulations among all the parties involved, but also the general public’s understanding of how genome projects can indirectly benefit their health and lifestyle management. WGP established a data construction framework for not only scientific research but also the welfare of participants. In the future, the WGP framework can help lay the groundwork for a new personalized healthcare system that is seamlessly integrated with existing public medical infrastructure.
Collapse
Affiliation(s)
- Yeonsu Jeon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea.,Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | - Sungwon Jeon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea.,Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | - Asta Blazyte
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea.,Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | | | - Jasmin Junseo Lee
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea.,Human Biology Program, Faculty of Arts and Sciences, University of Toronto, Toronto, ON, Canada
| | - Youngjune Bhak
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea.,Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | | | - Yeshin Park
- Clinomics Inc., Ulsan, South Korea.,Department of Medical Sciences, Graduate School of Ajou University School, Suwon, South Korea
| | - Eui-Kyu Noh
- Department of Hematology and Oncology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, South Korea
| | - Andrea Manica
- Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | - Jeremy S Edwards
- Department of Chemistry and Chemical Biology, University of New Mexico Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM, United States
| | - Dan Bolser
- Geromics Ltd., Cambridge, United Kingdom
| | - Sukyeon Kim
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | - Yuji Lee
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | - Changhan Yoon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea.,Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | - Semin Lee
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea.,Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | | | - Neung Hwa Park
- Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, South Korea
| | - Jong Bhak
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea.,Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea.,Clinomics Inc., Ulsan, South Korea.,Personal Genomics Institute (PGI), Genome Research Foundation (GRF), Osong, South Korea
| |
Collapse
|
48
|
Pinto CB, Bielefeld J, Jabakhanji R, Reckziegel D, Griffith JW, Apkarian AV. Neural and Genetic Bases for Human Ability Traits. Front Hum Neurosci 2021; 14:609170. [PMID: 33390920 PMCID: PMC7772246 DOI: 10.3389/fnhum.2020.609170] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 11/25/2020] [Indexed: 11/13/2022] Open
Abstract
The judgement of human ability is ubiquitous, from school admissions to job performance reviews. The exact make-up of ability traits, however, is often narrowly defined and lacks a comprehensive basis. We attempt to simplify the spectrum of human ability, similar to how five personality traits are widely believed to describe most personalities. Finding such a basis for human ability would be invaluable since neuropsychiatric disease diagnoses and symptom severity are commonly related to such differences in performance. Here, we identified four underlying ability traits within the National Institutes of Health Toolbox normative data (n = 1, 369): (1) Motor-endurance, (2) Emotional processing, (3) Executive and cognitive function, and (4) Social interaction. We used the Human Connectome Project young adult dataset (n = 778) to show that Motor-endurance and Executive and cognitive function were reliably associated with specific brain functional networks (r 2 = 0.305 ± 0.021), and the biological nature of these ability traits was also shown by calculating their heritability (31 and 49%, respectively) from twin data.
Collapse
Affiliation(s)
- Camila Bonin Pinto
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.,Center for Translational Pain Research, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Jannis Bielefeld
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.,Center for Translational Pain Research, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Rami Jabakhanji
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.,Center for Translational Pain Research, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Diane Reckziegel
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.,Center for Translational Pain Research, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - James W Griffith
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - A Vania Apkarian
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.,Center for Translational Pain Research, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.,Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.,Department of Anesthesiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| |
Collapse
|
49
|
Jin W, Chowienczyk P, Alastruey J. Estimating pulse wave velocity from the radial pressure wave using machine learning algorithms. PLoS One 2021; 16:e0245026. [PMID: 34181640 PMCID: PMC8238176 DOI: 10.1371/journal.pone.0245026] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 06/02/2021] [Indexed: 01/04/2023] Open
Abstract
One of the European gold standard measurement of vascular ageing, a risk factor for cardiovascular disease, is the carotid-femoral pulse wave velocity (cfPWV), which requires an experienced operator to measure pulse waves at two sites. In this work, two machine learning pipelines were proposed to estimate cfPWV from the peripheral pulse wave measured at a single site, the radial pressure wave measured by applanation tonometry. The study populations were the Twins UK cohort containing 3,082 subjects aged from 18 to 110 years, and a database containing 4,374 virtual subjects aged from 25 to 75 years. The first pipeline uses Gaussian process regression to estimate cfPWV from features extracted from the radial pressure wave using pulse wave analysis. The mean difference and upper and lower limits of agreement (LOA) of the estimation on the 924 hold-out test subjects from the Twins UK cohort were 0.2 m/s, and 3.75 m/s & -3.34 m/s, respectively. The second pipeline uses a recurrent neural network (RNN) to estimate cfPWV from the entire radial pressure wave. The mean difference and upper and lower LOA of the estimation on the 924 hold-out test subjects from the Twins UK cohort were 0.05 m/s, and 3.21 m/s & -3.11m/s, respectively. The percentage error of the RNN estimates on the virtual subjects increased by less than 2% when adding 20% of random noise to the pressure waveform. These results show the possibility of assessing the vascular ageing using a single peripheral pulse wave (e.g. the radial pressure wave), instead of cfPWV. The proposed code for the machine learning pipelines is available from the following online depository (https://github.com/WeiweiJin/Estimate-Cardiovascular-Risk-from-Pulse-Wave-Signal).
Collapse
Affiliation(s)
- Weiwei Jin
- Department of Biomedical Engineering, King’s College London, London, United Kingdom
- * E-mail: ,
| | - Philip Chowienczyk
- Department of Clinical Pharmacology, St. Thomas’ Hospital, King’s College London, London, United Kingdom
| | - Jordi Alastruey
- Department of Biomedical Engineering, King’s College London, London, United Kingdom
- World-Class Research Centre, Digital Biodesign and Personalized Healthcare, Sechenov University, Moscow, Russia
| |
Collapse
|
50
|
Bar N, Korem T, Weissbrod O, Zeevi D, Rothschild D, Leviatan S, Kosower N, Lotan-Pompan M, Weinberger A, Le Roy CI, Menni C, Visconti A, Falchi M, Spector TD, Adamski J, Franks PW, Pedersen O, Segal E. A reference map of potential determinants for the human serum metabolome. Nature 2020; 588:135-140. [DOI: 10.1038/s41586-020-2896-2] [Citation(s) in RCA: 121] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 09/29/2020] [Indexed: 12/13/2022]
|