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Parsons BL, Beal MA, Dearfield KL, Douglas GR, Gi M, Gollapudi BB, Heflich RH, Horibata K, Kenyon M, Long AS, Lovell DP, Lynch AM, Myers MB, Pfuhler S, Vespa A, Zeller A, Johnson GE, White PA. Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT). ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 2024. [PMID: 38828778 DOI: 10.1002/em.22599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/13/2024] [Accepted: 04/15/2024] [Indexed: 06/05/2024]
Abstract
Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.
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Affiliation(s)
- Barbara L Parsons
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | - Marc A Beal
- Bureau of Chemical Safety, Health Products and Food Branch, Health Canada, Ottawa, Ontario, Canada
| | - Kerry L Dearfield
- U.S. Environmental Protection Agency and U.S. Department of Agriculture, Washington, DC, USA
| | - George R Douglas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Min Gi
- Department of Environmental Risk Assessment, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | | | - Robert H Heflich
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | | | - Michelle Kenyon
- Portfolio and Regulatory Strategy, Drug Safety Research and Development, Pfizer, Groton, Connecticut, USA
| | - Alexandra S Long
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - David P Lovell
- Population Health Research Institute, St George's Medical School, University of London, London, UK
| | | | - Meagan B Myers
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | | | - Alisa Vespa
- Pharmaceutical Drugs Directorate, Health Products and Food Branch, Health Canada, Ottawa, Ontario, Canada
| | - Andreas Zeller
- Pharmaceutical Sciences, pRED Innovation Center Basel, Hoffmann-La Roche Ltd, Basel, Switzerland
| | - George E Johnson
- Swansea University Medical School, Swansea University, Swansea, Wales, UK
| | - Paul A White
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
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2
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Rick JA, Brock CD, Lewanski AL, Golcher-Benavides J, Wagner CE. Reference Genome Choice and Filtering Thresholds Jointly Influence Phylogenomic Analyses. Syst Biol 2024; 73:76-101. [PMID: 37881861 DOI: 10.1093/sysbio/syad065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 09/20/2023] [Accepted: 10/20/2023] [Indexed: 10/27/2023] Open
Abstract
Molecular phylogenies are a cornerstone of modern comparative biology and are commonly employed to investigate a range of biological phenomena, such as diversification rates, patterns in trait evolution, biogeography, and community assembly. Recent work has demonstrated that significant biases may be introduced into downstream phylogenetic analyses from processing genomic data; however, it remains unclear whether there are interactions among bioinformatic parameters or biases introduced through the choice of reference genome for sequence alignment and variant calling. We address these knowledge gaps by employing a combination of simulated and empirical data sets to investigate the extent to which the choice of reference genome in upstream bioinformatic processing of genomic data influences phylogenetic inference, as well as the way that reference genome choice interacts with bioinformatic filtering choices and phylogenetic inference method. We demonstrate that more stringent minor allele filters bias inferred trees away from the true species tree topology, and that these biased trees tend to be more imbalanced and have a higher center of gravity than the true trees. We find the greatest topological accuracy when filtering sites for minor allele count (MAC) >3-4 in our 51-taxa data sets, while tree center of gravity was closest to the true value when filtering for sites with MAC >1-2. In contrast, filtering for missing data increased accuracy in the inferred topologies; however, this effect was small in comparison to the effect of minor allele filters and may be undesirable due to a subsequent mutation spectrum distortion. The bias introduced by these filters differs based on the reference genome used in short read alignment, providing further support that choosing a reference genome for alignment is an important bioinformatic decision with implications for downstream analyses. These results demonstrate that attributes of the study system and dataset (and their interaction) add important nuance for how best to assemble and filter short-read genomic data for phylogenetic inference.
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Affiliation(s)
- Jessica A Rick
- School of Natural Resources & the Environment, University of Arizona, Tucson, AZ 85719, USA
| | - Chad D Brock
- Department of Biological Sciences, Tarleton State University, Stephenville, TX 76401, USA
| | - Alexander L Lewanski
- Department of Integrative Biology and W.K. Kellogg Biological Station, Michigan State University, East Lansing, MI 48824, USA
| | - Jimena Golcher-Benavides
- Department of Natural Resource Ecology and Management, Iowa State University, Ames, IA 50011, USA
| | - Catherine E Wagner
- Program in Ecology and Evolution, University of Wyoming, Laramie, WY 82071, USA
- Department of Botany, University of Wyoming, Laramie, WY 82071, USA
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3
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Biddanda A, Bandyopadhyay E, de la Fuente Castro C, Witonsky D, Urban Aragon JA, Pasupuleti N, Moots HM, Fonseca R, Freilich S, Stanisavic J, Willis T, Menon A, Mustak MS, Kodira CD, Naren AP, Sikdar M, Rai N, Raghavan M. Distinct positions of genetic and oral histories: Perspectives from India. HGG ADVANCES 2024; 5:100305. [PMID: 38720459 PMCID: PMC11153255 DOI: 10.1016/j.xhgg.2024.100305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 05/04/2024] [Accepted: 05/04/2024] [Indexed: 05/16/2024] Open
Abstract
Over the past decade, genomic data have contributed to several insights on global human population histories. These studies have been met both with interest and critically, particularly by populations with oral histories that are records of their past and often reference their origins. While several studies have reported concordance between oral and genetic histories, there is potential for tension that may stem from genetic histories being prioritized or used to confirm community-based knowledge and ethnography, especially if they differ. To investigate the interplay between oral and genetic histories, we focused on the southwestern region of India and analyzed whole-genome sequence data from 156 individuals identifying as Bunt, Kodava, Nair, and Kapla. We supplemented limited anthropological records on these populations with oral history accounts from community members and historical literature, focusing on references to non-local origins such as the ancient Scythians in the case of Bunt, Kodava, and Nair, members of Alexander the Great's army for the Kodava, and an African-related source for Kapla. We found these populations to be genetically most similar to other Indian populations, with the Kapla more similar to South Indian tribal populations that maximize a genetic ancestry related to Ancient Ancestral South Indians. We did not find evidence of additional genetic sources in the study populations than those known to have contributed to many other present-day South Asian populations. Our results demonstrate that oral and genetic histories may not always provide consistent accounts of population origins and motivate further community-engaged, multi-disciplinary investigations of non-local origin stories in these communities.
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Affiliation(s)
- Arjun Biddanda
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Esha Bandyopadhyay
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Constanza de la Fuente Castro
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA; Programa de Genética Humana, Instituto de Ciencias Biomédicas, Facultad de Medicina, Universidad de Chile, Santiago, Chile
| | - David Witonsky
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | | | - Nagarjuna Pasupuleti
- Department of Applied Zoology, Mangalore University, Mangalagangothri, Karnataka 574199, India
| | - Hannah M Moots
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA; Institute for the Study of Ancient Cultures Museum, University of Chicago, Chicago, IL, USA
| | - Renée Fonseca
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Suzanne Freilich
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA; Department of Evolutionary Anthropology, University of Vienna, Vienna 1090, Austria
| | - Jovan Stanisavic
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Tabitha Willis
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Anoushka Menon
- Department of Archaeology, University of Cambridge, Cambridge CB2 3DZ, UK
| | - Mohammed S Mustak
- Department of Applied Zoology, Mangalore University, Mangalagangothri, Karnataka 574199, India
| | | | - Anjaparavanda P Naren
- Division of Pulmonary Medicine, Cystic Fibrosis Research Center, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Mithun Sikdar
- Anthropological Survey of India, Mysore, Karnataka 570026, India
| | - Niraj Rai
- Birbal Sahni Institute of Palaeosciences, Uttar Pradesh, Lucknow, Uttar Pradesh 226007, India.
| | - Maanasa Raghavan
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
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4
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Alfayyadh MM, Maksemous N, Sutherland HG, Lea RA, Griffiths LR. Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches. Genes (Basel) 2024; 15:443. [PMID: 38674378 PMCID: PMC11049430 DOI: 10.3390/genes15040443] [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: 03/12/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024] Open
Abstract
Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.
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Affiliation(s)
| | | | | | | | - Lyn R. Griffiths
- Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4059, Australia; (M.M.A.); (N.M.); (H.G.S.); (R.A.L.)
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5
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Larrue R, Fellah S, Hennart B, Sabaouni N, Boukrout N, Van der Hauwaert C, Delage C, Cheok M, Perrais M, Cauffiez C, Allorge D, Pottier N. Integrating rare genetic variants into DPYD pharmacogenetic testing may help preventing fluoropyrimidine-induced toxicity. THE PHARMACOGENOMICS JOURNAL 2024; 24:1. [PMID: 38216550 PMCID: PMC10786722 DOI: 10.1038/s41397-023-00322-x] [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: 06/15/2023] [Revised: 10/23/2023] [Accepted: 12/05/2023] [Indexed: 01/14/2024]
Abstract
Variability in genes involved in drug pharmacokinetics or drug response can be responsible for suboptimal treatment efficacy or predispose to adverse drug reactions. In addition to common genetic variations, large-scale sequencing studies have uncovered multiple rare genetic variants predicted to cause functional alterations in genes encoding proteins implicated in drug metabolism, transport and response. To understand the functional importance of rare genetic variants in DPYD, a pharmacogene whose alterations can cause severe toxicity in patients exposed to fluoropyrimidine-based regimens, massively parallel sequencing of the exonic regions and flanking splice junctions of the DPYD gene was performed in a series of nearly 3000 patients categorized according to pre-emptive DPD enzyme activity using the dihydrouracil/uracil ([UH2]/[U]) plasma ratio as a surrogate marker of DPD activity. Our results underscore the importance of integrating next-generation sequencing-based pharmacogenomic interpretation into clinical decision making to minimize fluoropyrimidine-based chemotherapy toxicity without altering treatment efficacy.
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Affiliation(s)
- Romain Larrue
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France.
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France.
| | - Sandy Fellah
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Benjamin Hennart
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
| | - Naoual Sabaouni
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
| | - Nihad Boukrout
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Cynthia Van der Hauwaert
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Clément Delage
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
| | - Meyling Cheok
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Michaël Perrais
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Christelle Cauffiez
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Delphine Allorge
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
| | - Nicolas Pottier
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
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6
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Hua Z. Deciphering the protein ubiquitylation system in plants. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:6487-6504. [PMID: 37688404 DOI: 10.1093/jxb/erad354] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 09/07/2023] [Indexed: 09/10/2023]
Abstract
Protein ubiquitylation is a post-translational modification (PTM) process that covalently modifies a protein substrate with either mono-ubiquitin moieties or poly-ubiquitin chains often at the lysine residues. In Arabidopsis, bioinformatic predictions have suggested that over 5% of its proteome constitutes the protein ubiquitylation system. Despite advancements in functional genomic studies in plants, only a small fraction of this bioinformatically predicted system has been functionally characterized. To expand our understanding about the regulatory function of protein ubiquitylation to that rivalling several other major systems, such as transcription regulation and epigenetics, I describe the status, issues, and new approaches of protein ubiquitylation studies in plant biology. I summarize the methods utilized in defining the ubiquitylation machinery by bioinformatics, identifying ubiquitylation substrates by proteomics, and characterizing the ubiquitin E3 ligase-substrate pathways by functional genomics. Based on the functional and evolutionary analyses of the F-box gene superfamily, I propose a deleterious duplication model for the large expansion of this family in plant genomes. Given this model, I present new perspectives of future functional genomic studies on the plant ubiquitylation system to focus on core and active groups of ubiquitin E3 ligase genes.
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Affiliation(s)
- Zhihua Hua
- Department of Environmental and Plant Biology, Ohio University, Athens, OH 45701, USA
- Interdisciplinary Program in Molecular and Cellular Biology, Ohio University, Athens, OH 45701, USA
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7
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Joshi E, Biddanda A, Popoola J, Yakubu A, Osakwe O, Attipoe D, Dogbo E, Salako B, Nash O, Salako O, Oyedele O, Eze-Echesi G, Fatumo S, Ene-Obong A, O’Dushlaine C. Whole-genome sequencing across 449 samples spanning 47 ethnolinguistic groups provides insights into genetic diversity in Nigeria. CELL GENOMICS 2023; 3:100378. [PMID: 37719143 PMCID: PMC10504631 DOI: 10.1016/j.xgen.2023.100378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/23/2023] [Accepted: 07/13/2023] [Indexed: 09/19/2023]
Abstract
African populations have been drastically underrepresented in genomics research, and failure to capture the genetic diversity across the numerous ethnolinguistic groups (ELGs) found on the continent has hindered the equity of precision medicine initiatives globally. Here, we describe the whole-genome sequencing of 449 Nigerian individuals across 47 unique self-reported ELGs. Population structure analysis reveals genetic differentiation among our ELGs, consistent with previous findings. From the 36 million SNPs and insertions or deletions (indels) discovered in our dataset, we provide a high-level catalog of both novel and medically relevant variation present across the ELGs. These results emphasize the value of this resource for genomics research, with added granularity by representing multiple ELGs from Nigeria. Our results also underscore the potential of using these cohorts with larger sample sizes to improve our understanding of human ancestry and health in Africa.
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Affiliation(s)
- Esha Joshi
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | - Arjun Biddanda
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | - Jumi Popoola
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | - Aminu Yakubu
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | | | - Delali Attipoe
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | - Estelle Dogbo
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | | | - Oyekanmi Nash
- Center for Genomics Research and Innovation, National Agency for Biotechnology Development, Abuja 09004, Nigeria
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja 09004, Nigeria
| | - Omolola Salako
- College of Medicine University of Lagos, Lagos 101233, Nigeria
| | | | | | - Segun Fatumo
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja 09004, Nigeria
- The African Computational Genomics (TAGC) Research Group, MRC/UVRI and London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
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8
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Rakicevic L. DNA and RNA Molecules as a Foundation of Therapy Strategies for Treatment of Cardiovascular Diseases. Pharmaceutics 2023; 15:2141. [PMID: 37631355 PMCID: PMC10459020 DOI: 10.3390/pharmaceutics15082141] [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: 06/30/2023] [Revised: 07/27/2023] [Accepted: 08/11/2023] [Indexed: 08/27/2023] Open
Abstract
There has always been a tendency of medicine to take an individualised approach to treating patients, but the most significant advances were achieved through the methods of molecular biology, where the nucleic acids are in the limelight. Decades of research of molecular biology resulted in setting medicine on a completely new platform. The most significant current research is related to the possibilities that DNA and RNA analyses can offer in terms of more precise diagnostics and more subtle stratification of patients in order to identify patients for specific therapy treatments. Additionally, principles of structure and functioning of nucleic acids have become a motive for creating entirely new therapy strategies and an innovative generation of drugs. All this also applies to cardiovascular diseases (CVDs) which are the leading cause of mortality in developed countries. This review considers the most up-to-date achievements related to the use of translatory potential of DNA and RNA in treatment of cardiovascular diseases, and considers the challenges and prospects in this field. The foundations which allow the use of translatory potential are also presented. The first part of this review focuses on the potential of the DNA variants which impact conventional therapies and on the DNA variants which are starting points for designing new pharmacotherapeutics. The second part of this review considers the translatory potential of non-coding RNA molecules which can be used to formulate new generations of therapeutics for CVDs.
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Affiliation(s)
- Ljiljana Rakicevic
- Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Vojvode Stepe 444a, 11042 Belgrade, Serbia
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Haider M, Schilling MP, Moest MH, Steiner FM, Schlick‐Steiner BC, Arthofer W. Evolutionary history of an Alpine Archaeognath ( Machilis pallida): Insights from different variant. Ecol Evol 2023; 13:e10227. [PMID: 37404697 PMCID: PMC10316371 DOI: 10.1002/ece3.10227] [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: 07/29/2022] [Revised: 05/31/2023] [Accepted: 06/09/2023] [Indexed: 07/06/2023] Open
Abstract
Reconstruction of species histories is a central aspect of evolutionary biology. Patterns of genetic variation within and among populations can be leveraged to elucidate evolutionary processes and demographic histories. However, interpreting genetic signatures and unraveling the contributing processes can be challenging, in particular for non-model organisms with complex reproductive modes and genome organization. One way forward is the combined consideration of patterns revealed by different molecular markers (nuclear vs. mitochondrial) and types of variants (common vs. rare) that differ in their age, mode, and rate of evolution. Here, we applied this approach to RNAseq data generated for Machilis pallida (Archaeognatha), an Alpine jumping bristletail considered parthenogenetic and triploid. We generated de novo transcriptome and mitochondrial assemblies to obtain high-density data to investigate patterns of mitochondrial and common and rare nuclear variation in 17 M. pallida individuals sampled from all known populations. We find that the different variant types capture distinct aspects of the evolutionary history and discuss the observed patterns in the context of parthenogenesis, polyploidy, and survival during glaciation. This study highlights the potential of different variant types to gain insights into evolutionary scenarios even from challenging but often available data and the suitability of M. pallida and the genus Machilis as a study system for the evolution of sexual strategies and polyploidization during environmental change. We also emphasize the need for further research which will be stimulated and facilitated by these newly generated resources and insights.
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Affiliation(s)
- Marlene Haider
- Department of Ecology, Molecular Ecology GroupUniversity of InnsbruckInnsbruckAustria
| | - Martin P. Schilling
- Department of Ecology, Molecular Ecology GroupUniversity of InnsbruckInnsbruckAustria
| | - Markus H. Moest
- Department of Ecology, Molecular Ecology GroupUniversity of InnsbruckInnsbruckAustria
| | - Florian M. Steiner
- Department of Ecology, Molecular Ecology GroupUniversity of InnsbruckInnsbruckAustria
| | | | - Wolfgang Arthofer
- Department of Ecology, Molecular Ecology GroupUniversity of InnsbruckInnsbruckAustria
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10
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Efficient Two-Stage Analysis for Complex Trait Association with Arbitrary Depth Sequencing Data. STATS 2023. [DOI: 10.3390/stats6010029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2023] Open
Abstract
Sequencing-based genetic association analysis is typically performed by first generating genotype calls from sequence data and then performing association tests on the called genotypes. Standard approaches require accurate genotype calling (GC), which can be achieved either with high sequencing depth (typically available in a small number of individuals) or via computationally intensive multi-sample linkage disequilibrium (LD)-aware methods. We propose a computationally efficient two-stage combination approach for association analysis, in which single-nucleotide polymorphisms (SNPs) are screened in the first stage via a rapid maximum likelihood (ML)-based method on sequence data directly (without first calling genotypes), and then the selected SNPs are evaluated in the second stage by performing association tests on genotypes from multi-sample LD-aware calling. Extensive simulation- and real data-based studies show that the proposed two-stage approaches can save 80% of the computational costs and still obtain more than 90% of the power of the classical method to genotype all markers at various depths d≥2.
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11
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Targeted next-generation sequencing of genes involved in Warfarin Pharmacodynamics and pharmacokinetics pathways using the Saudi Warfarin Pharmacogenetic study (SWAP). THE PHARMACOGENOMICS JOURNAL 2023:10.1038/s41397-023-00300-3. [PMID: 36739459 DOI: 10.1038/s41397-023-00300-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 01/15/2023] [Accepted: 01/26/2023] [Indexed: 02/06/2023]
Abstract
BACKGROUND Warfarin is an oral anticoagulant commonly used for treatment and prophylaxis against thromboembolic events. Warfarins's narrow therapeutic index window is one of the main challenges in clinical practice; thus, it requires frequent monitoring and dose adjustment to maintain patients' therapeutic range. Warfarin dose variation and response are attributed to several inter-and intra-individuals factors, including genetic variants in enzymes involved in warfarin pharmacokinetics (PK) and pharmacodynamics (PD) pathways. Thus, we aim to utilize the next-generation sequencing (NGS) approach to identify rare and common genetic variants that might be associated with warfarin responsiveness. METHOD AND RESULTS A predesigned NGS panel that included 16 genes involved in Warfarin PK/PD pathways was used to sequence 786 patients from the Saudi Warfarin Pharmacogenetic Cohort (SWAP). Identified variants were annotated using several annotation tools to identify the pathogenicity and allele frequencies of these variants. We conducted variants-level association tests with warfarin dose. We identified 710 variants within the sequenced genes; 19% were novel variants, with the vast majority being scarce variants. The genetic association tests showed that VKORC1 (rs9923231, and rs61742245), CYP2C9 (rs98332238, rs9332172, rs1057910, rs9332230, rs1799853, rs1057911, and rs9332119), CYP2C19 (rs28399511, and rs3758581), and CYP2C8 (rs11572080 and rs10509681) were significantly associated with warfarin weekly dose. Our model included genetics, and non-genetic factors explained 40.1% of warfarin dose variation. CONCLUSION The study identifies novel variants associated with warfarin dose in the Saudi population. These variants are more likely to be population-specific variants, suggesting that population-specific studies should be conducted before adopting a universal warfarin genotype-guided dosing algorithm.
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12
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Nickchi P, Karunarathna C, Graham J. An exploration of linkage fine-mapping on sequences from case-control studies. Genet Epidemiol 2023; 47:78-94. [PMID: 36047334 PMCID: PMC10087369 DOI: 10.1002/gepi.22502] [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: 12/09/2021] [Revised: 05/30/2022] [Accepted: 08/09/2022] [Indexed: 02/01/2023]
Abstract
Linkage analysis maps genetic loci for a heritable trait by identifying genomic regions with excess relatedness among individuals with similar trait values. Analysis may be conducted on related individuals from families, or on samples of unrelated individuals from a population. For allelically heterogeneous traits, population-based linkage analysis can be more powerful than genotypic-association analysis. Here, we focus on linkage analysis in a population sample, but use sequences rather than individuals as our unit of observation. Earlier investigations of sequence-based linkage mapping relied on known sequence relatedness, whereas we infer relatedness from the sequence data. We propose two ways to associate similarity in relatedness of sequences with similarity in their trait values and compare the resulting linkage methods to two genotypic-association methods. We also introduce a procedure to label case sequences as potential carriers or noncarriers of causal variants after an association has been found. This post hoc labeling of case sequences is based on inferred relatedness to other case sequences. Our simulation results indicate that methods based on sequence relatedness improve localization and perform as well as genotypic-association methods for detecting rare causal variants. Sequence-based linkage analysis therefore has potential to fine-map allelically heterogeneous disease traits.
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Affiliation(s)
- Payman Nickchi
- Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Charith Karunarathna
- Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.,Department of Mathematics and Statistics, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Jinko Graham
- Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada
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13
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Esai Selvan M, Onel K, Gnjatic S, Klein RJ, Gümüş ZH. Germline rare deleterious variant load alters cancer risk, age of onset and tumor characteristics. NPJ Precis Oncol 2023; 7:13. [PMID: 36707626 PMCID: PMC9883433 DOI: 10.1038/s41698-023-00354-3] [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: 07/15/2022] [Accepted: 01/16/2023] [Indexed: 01/28/2023] Open
Abstract
Recent studies show that rare, deleterious variants (RDVs) in certain genes are critical determinants of heritable cancer risk. To more comprehensively understand RDVs, we performed the largest-to-date germline variant calling analysis in a case-control setting for a multi-cancer association study from whole-exome sequencing data of 20,789 participants, split into discovery and validation cohorts. We confirm and extend known associations between cancer risk and germline RDVs in specific gene-sets, including DNA repair (OR = 1.50; p-value = 8.30e-07; 95% CI: 1.28-1.77), cancer predisposition (OR = 1.51; p-value = 4.58e-08; 95% CI: 1.30-1.75), and somatic cancer drivers (OR = 1.46; p-value = 4.04e-06; 95% CI: 1.24-1.72). Furthermore, personal RDV load in these gene-sets associated with increased risk, younger age of onset, increased M1 macrophages in tumor and, increased tumor mutational burden in specific cancers. Our findings can be used towards identifying high-risk individuals, who can then benefit from increased surveillance, earlier screening, and treatments that exploit their tumor characteristics, improving prognosis.
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Affiliation(s)
- Myvizhi Esai Selvan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kenan Onel
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Sacha Gnjatic
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Oncological Sciences, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Zeynep H Gümüş
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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14
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Zhou Y, Lauschke VM. Challenges Related to the Use of Next-Generation Sequencing for the Optimization of Drug Therapy. Handb Exp Pharmacol 2023; 280:237-260. [PMID: 35792943 DOI: 10.1007/164_2022_596] [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] [Indexed: 06/15/2023]
Abstract
Over the last decade, next-generation sequencing (NGS) methods have become increasingly used in various areas of human genomics. In routine clinical care, their use is already implemented in oncology to profile the mutational landscape of a tumor, as well as in rare disease diagnostics. However, its utilization in pharmacogenomics is largely lacking behind. Recent population-scale genome data has revealed that human pharmacogenes carry a plethora of rare genetic variations that are not interrogated by conventional array-based profiling methods and it is estimated that these variants could explain around 30% of the genetically encoded functional pharmacogenetic variability.To interpret the impact of such variants on drug response a multitude of computational tools have been developed, but, while there have been major advancements, it remains to be shown whether their accuracy is sufficient to improve personalized pharmacogenetic recommendations in robust trials. In addition, conventional short-read sequencing methods face difficulties in the interrogation of complex pharmacogenes and high NGS test costs require stringent evaluations of cost-effectiveness to decide about reimbursement by national healthcare programs. Here, we illustrate current challenges and discuss future directions toward the clinical implementation of NGS to inform genotype-guided decision-making.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University of Tuebingen, Tuebingen, Germany.
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15
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Zhou Y, Koutsilieri S, Eliasson E, Lauschke VM. A paradigm shift in pharmacogenomics: From candidate polymorphisms to comprehensive sequencing. Basic Clin Pharmacol Toxicol 2022; 131:452-464. [PMID: 35971800 PMCID: PMC9805052 DOI: 10.1111/bcpt.13779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 07/28/2022] [Accepted: 08/09/2022] [Indexed: 01/09/2023]
Abstract
Genetic factors have long been recognized as important determinants of interindividual variability in drug efficacy and toxicity. However, despite the increasing number of established gene-drug associations, candidate polymorphisms can only explain a fraction of the genetically encoded functional variability in drug disposition. Advancements in genetic profiling methods now allow to analyse the landscape of human pharmacogenetic variations comprehensively, which opens new opportunities to identify novel factors that could explain the "missing heritability." Here, we provide an updated overview of the landscape of pharmacogenomic variability based on recent analyses of population-scale sequencing projects. We then summarize the current state-of-the-art how the functional consequences of variants with unknown effects can be quantitatively estimated while discussing challenges and peculiarities that are specific to pharmacogenes. In the last sections, we discuss the importance of considering ethnogeographic diversity to provide equitable benefits of pharmacogenomics and summarize current roadblocks for the implementation of sequencing-based guidance of clinical decision-making. Based on the current state of the field, we conclude that testing is likely to gradually shift from the interrogation of selected candidate polymorphisms to comprehensive sequencing, which allows to consider the full spectrum of pharmacogenomic variations for a true personalization of genomic prescribing.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and PharmacologyKarolinska InstitutetStockholmSweden,Department of Laboratory MedicineKarolinska InstitutetStockholmSweden
| | | | - Erik Eliasson
- Department of Laboratory MedicineKarolinska InstitutetStockholmSweden
| | - Volker M. Lauschke
- Department of Physiology and PharmacologyKarolinska InstitutetStockholmSweden,Dr Margarete Fischer‐Bosch Institute of Clinical PharmacologyStuttgartGermany,University of TübingenTübingenGermany
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16
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Zhou Y, Lauschke VM. The genetic landscape of major drug metabolizing cytochrome P450 genes-an updated analysis of population-scale sequencing data. THE PHARMACOGENOMICS JOURNAL 2022; 22:284-293. [PMID: 36068297 PMCID: PMC9674520 DOI: 10.1038/s41397-022-00288-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/05/2022] [Accepted: 08/19/2022] [Indexed: 06/15/2023]
Abstract
Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77, Stockholm, Sweden.
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University of Tuebingen, Tuebingen, Germany.
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17
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Mouterde M, Daali Y, Rollason V, Čížková M, Mulugeta A, Al Balushi KA, Fakis G, Constantinidis TC, Al-Thihli K, Černá M, Makonnen E, Boukouvala S, Al-Yahyaee S, Yimer G, Černý V, Desmeules J, Poloni ES. Joint Analysis of Phenotypic and Genomic Diversity Sheds Light on the Evolution of Xenobiotic Metabolism in Humans. Genome Biol Evol 2022; 14:6852765. [PMID: 36445690 PMCID: PMC9750130 DOI: 10.1093/gbe/evac167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 11/03/2022] [Accepted: 11/22/2022] [Indexed: 11/30/2022] Open
Abstract
Variation in genes involved in the absorption, distribution, metabolism, and excretion of drugs (ADME) can influence individual response to a therapeutic treatment. The study of ADME genetic diversity in human populations has led to evolutionary hypotheses of adaptation to distinct chemical environments. Population differentiation in measured drug metabolism phenotypes is, however, scarcely documented, often indirectly estimated via genotype-predicted phenotypes. We administered seven probe compounds devised to target six cytochrome P450 enzymes and the P-glycoprotein (P-gp) activity to assess phenotypic variation in four populations along a latitudinal transect spanning over Africa, the Middle East, and Europe (349 healthy Ethiopian, Omani, Greek, and Czech volunteers). We demonstrate significant population differentiation for all phenotypes except the one measuring CYP2D6 activity. Genome-wide association studies (GWAS) evidenced that the variability of phenotypes measuring CYP2B6, CYP2C9, CYP2C19, and CYP2D6 activity was associated with genetic variants linked to the corresponding encoding genes, and additional genes for the latter three. Instead, GWAS did not indicate any association between genetic diversity and the phenotypes measuring CYP1A2, CYP3A4, and P-gp activity. Genome scans of selection highlighted multiple candidate regions, a few of which included ADME genes, but none overlapped with the GWAS candidates. Our results suggest that different mechanisms have been shaping the evolution of these phenotypes, including phenotypic plasticity, and possibly some form of balancing selection. We discuss how these contrasting results highlight the diverse evolutionary trajectories of ADME genes and proteins, consistent with the wide spectrum of both endogenous and exogenous molecules that are their substrates.
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Affiliation(s)
| | - Youssef Daali
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Victoria Rollason
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Martina Čížková
- Institute of Archaeology of the Academy of Sciences of the Czech Republic, Prague, Czech Republic
| | - Anwar Mulugeta
- Department of Pharmacology and Clinical Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Khalid A Al Balushi
- College of Pharmacy, National University of Science and Technology, Muscat, Sultanate of Oman
| | - Giannoulis Fakis
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
| | | | - Khalid Al-Thihli
- Department of Genetics, Sultan Qaboos University Hospital, Muscat, Sultanate of Oman
| | - Marie Černá
- Department of Medical Genetics, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Eyasu Makonnen
- Department of Pharmacology and Clinical Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia,Center for Innovative Drug Development and Therapeutic Trials for Africa, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Sotiria Boukouvala
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
| | - Said Al-Yahyaee
- Department of Genetics, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman
| | - Getnet Yimer
- Center for Global Genomics & Health Equity, Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Viktor Černý
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
| | - Jules Desmeules
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
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18
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Simon M, Yang J, Gigas J, Earley EJ, Hillpot E, Zhang L, Zagorulya M, Tombline G, Gilbert M, Yuen SL, Pope A, Van Meter M, Emmrich S, Firsanov D, Athreya A, Biashad SA, Han J, Ryu S, Tare A, Zhu Y, Hudgins A, Atzmon G, Barzilai N, Wolfe A, Moody K, Garcia BA, Thomas DD, Robbins PD, Vijg J, Seluanov A, Suh Y, Gorbunova V. A rare human centenarian variant of SIRT6 enhances genome stability and interaction with Lamin A. EMBO J 2022; 41:e110393. [PMID: 36215696 PMCID: PMC9627671 DOI: 10.15252/embj.2021110393] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 07/31/2022] [Accepted: 08/08/2022] [Indexed: 02/02/2023] Open
Abstract
Sirtuin 6 (SIRT6) is a deacylase and mono-ADP ribosyl transferase (mADPr) enzyme involved in multiple cellular pathways implicated in aging and metabolism regulation. Targeted sequencing of SIRT6 locus in a population of 450 Ashkenazi Jewish (AJ) centenarians and 550 AJ individuals without a family history of exceptional longevity identified enrichment of a SIRT6 allele containing two linked substitutions (N308K/A313S) in centenarians compared with AJ control individuals. Characterization of this SIRT6 allele (centSIRT6) demonstrated it to be a stronger suppressor of LINE1 retrotransposons, confer enhanced stimulation of DNA double-strand break repair, and more robustly kill cancer cells compared with wild-type SIRT6. Surprisingly, centSIRT6 displayed weaker deacetylase activity, but stronger mADPr activity, over a range of NAD+ concentrations and substrates. Additionally, centSIRT6 displayed a stronger interaction with Lamin A/C (LMNA), which was correlated with enhanced ribosylation of LMNA. Our results suggest that enhanced SIRT6 function contributes to human longevity by improving genome maintenance via increased mADPr activity and enhanced interaction with LMNA.
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Affiliation(s)
- Matthew Simon
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Jiping Yang
- Department of Obstetrics and Gynecology, Columbia University, New York, NY, USA
| | - Jonathan Gigas
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Eric J Earley
- Biostatistics and Epidemiology, RTI International, Durham, NC, USA
| | - Eric Hillpot
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Lei Zhang
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, Minneapolis, MN, USA
| | - Maria Zagorulya
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Greg Tombline
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Michael Gilbert
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Samantha L Yuen
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, Minneapolis, MN, USA
| | - Alexis Pope
- Department of Obstetrics and Gynecology, Columbia University, New York, NY, USA
| | | | - Stephan Emmrich
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Denis Firsanov
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Advait Athreya
- Department of Biology, University of Rochester, Rochester, NY, USA
| | | | - Jeehae Han
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Seungjin Ryu
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Archana Tare
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Yizhou Zhu
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Adam Hudgins
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Gil Atzmon
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Biology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel
| | - Nir Barzilai
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | | | | | - Benjamin A Garcia
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David D Thomas
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, Minneapolis, MN, USA
| | - Paul D Robbins
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, Minneapolis, MN, USA
| | - Jan Vijg
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Andrei Seluanov
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Yousin Suh
- Department of Obstetrics and Gynecology, Columbia University, New York, NY, USA
| | - Vera Gorbunova
- Department of Biology, University of Rochester, Rochester, NY, USA
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19
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Jang SK, Evans L, Fialkowski A, Arnett DK, Ashley-Koch AE, Barnes KC, Becker DM, Bis JC, Blangero J, Bleecker ER, Boorgula MP, Bowden DW, Brody JA, Cade BE, Jenkins BWC, Carson AP, Chavan S, Cupples LA, Custer B, Damrauer SM, David SP, de Andrade M, Dinardo CL, Fingerlin TE, Fornage M, Freedman BI, Garrett ME, Gharib SA, Glahn DC, Haessler J, Heckbert SR, Hokanson JE, Hou L, Hwang SJ, Hyman MC, Judy R, Justice AE, Kaplan RC, Kardia SLR, Kelly S, Kim W, Kooperberg C, Levy D, Lloyd-Jones DM, Loos RJF, Manichaikul AW, Gladwin MT, Martin LW, Nouraie M, Melander O, Meyers DA, Montgomery CG, North KE, Oelsner EC, Palmer ND, Payton M, Peljto AL, Peyser PA, Preuss M, Psaty BM, Qiao D, Rader DJ, Rafaels N, Redline S, Reed RM, Reiner AP, Rich SS, Rotter JI, Schwartz DA, Shadyab AH, Silverman EK, Smith NL, Smith JG, Smith AV, Smith JA, Tang W, Taylor KD, Telen MJ, Vasan RS, Gordeuk VR, Wang Z, Wiggins KL, Yanek LR, Yang IV, Young KA, Young KL, Zhang Y, Liu DJ, Keller MC, Vrieze S. Rare genetic variants explain missing heritability in smoking. Nat Hum Behav 2022; 6:1577-1586. [PMID: 35927319 PMCID: PMC9985486 DOI: 10.1038/s41562-022-01408-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 06/10/2022] [Indexed: 12/11/2022]
Abstract
Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.
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Affiliation(s)
- Seon-Kyeong Jang
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Luke Evans
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department of Ecology & Evolution, University of Colorado Boulder, Boulder, CO, USA
| | | | - Donna K Arnett
- Dean's Office, University of Kentucky College of Public Health, Lexington, KY, USA
| | | | - Kathleen C Barnes
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Diane M Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | | | - Meher Preethi Boorgula
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Brian E Cade
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Brenda W Campbell Jenkins
- Jackson Heart Study Graduate Training and Education Center, Jackson State University School of Public Health, Jackson, MS, USA
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Sameer Chavan
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Brian Custer
- Vitalant Research Institute, San Francisco, CA, USA
| | - Scott M Damrauer
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Surgery, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Sean P David
- Department of Family Medicine, Prtizker School of Medicine, University of Chicago, Chicago, IL, USA
- NorthShore University HealthSystem, Evanston, IL, USA
| | - Mariza de Andrade
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Tasha E Fingerlin
- Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Center for Genes Environment and Health, National Jewish Health, Denver, CO, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Barry I Freedman
- Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Melanie E Garrett
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Sina A Gharib
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Center for Lung Biology, Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington, Seattle, WA, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hosptial and Harvard Medical School, Boston, MA, USA
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Susan R Heckbert
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
| | - John E Hokanson
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Shih-Jen Hwang
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Matthew C Hyman
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Renae Judy
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Anne E Justice
- Department of Population Health Sciences, Geisinger Health System, Danville, PA, USA
| | - Robert C Kaplan
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Shannon Kelly
- Department of Pediatrics, UCSF Benioff Children's Hospital Oakland, Oakland, CA, USA
| | - Wonji Kim
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | | | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ani W Manichaikul
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Mark T Gladwin
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Mehdi Nouraie
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | | | - Courtney G Montgomery
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Elizabeth C Oelsner
- Division of General Medicine, Columbia University Irving Medical Center, Columbia University, New York, NY, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Marinelle Payton
- Department of Epidemiology and Biostatistics, Jackson Heart Study Graduate Training and Education Center, Jackson State University School of Public Health, Jackson, MS, USA
| | - Anna L Peljto
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Michael Preuss
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, Epidemiology and Health Services, University of Washington, Seattle, WA, USA
| | - Dandi Qiao
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Daniel J Rader
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicholas Rafaels
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Robert M Reed
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - David A Schwartz
- Department of Medicine, School of Medicine, University of Colorado Denver, Aurora, CO, USA
- Department of Immunology, School of Medicine, University of Colorado Denver, Aurora, CO, USA
| | - Aladdin H Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
| | - J Gustav Smith
- Wallenberg Laboratory/Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg University, Gothenburg, Sweden
- Department of Cardiology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Albert V Smith
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Weihong Tang
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marilyn J Telen
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Ramachandran S Vasan
- Sections of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Victor R Gordeuk
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Zhe Wang
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ivana V Yang
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Kendra A Young
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Kristin L Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yingze Zhang
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Dajiang J Liu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Matthew C Keller
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Scott Vrieze
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA.
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20
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Developing CIRdb as a catalog of natural genetic variation in the Canary Islanders. Sci Rep 2022; 12:16132. [PMID: 36168029 PMCID: PMC9514705 DOI: 10.1038/s41598-022-20442-x] [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] [Received: 02/09/2022] [Accepted: 09/13/2022] [Indexed: 11/29/2022] Open
Abstract
The current inhabitants of the Canary Islands have a unique genetic makeup in the European diversity landscape due to the existence of African footprints from recent admixture events, especially of North African components (> 20%). The underrepresentation of non-Europeans in genetic studies and the sizable North African ancestry, which is nearly absent from all existing catalogs of worldwide genetic diversity, justify the need to develop CIRdb, a population-specific reference catalog of natural genetic variation in the Canary Islanders. Based on array genotyping of the selected unrelated donors and comparisons against available datasets from European, sub-Saharan, and North African populations, we illustrate the intermediate genetic differentiation of Canary Islanders between Europeans and North Africans and the existence of within-population differences that are likely driven by genetic isolation. Here we describe the overall design and the methods that are being implemented to further develop CIRdb. This resource will help to strengthen the implementation of Precision Medicine in this population by contributing to increase the diversity in genetic studies. Among others, this will translate into improved ability to fine map disease genes and simplify the identification of causal variants and estimate the prevalence of unattended Mendelian diseases.
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21
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Zhou Y, Tremmel R, Schaeffeler E, Schwab M, Lauschke VM. Challenges and opportunities associated with rare-variant pharmacogenomics. Trends Pharmacol Sci 2022; 43:852-865. [PMID: 36008164 DOI: 10.1016/j.tips.2022.07.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/15/2022] [Accepted: 07/29/2022] [Indexed: 12/26/2022]
Abstract
Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Roman Tremmel
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany
| | - Elke Schaeffeler
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany; Cluster of Excellence iFIT (EXC2180) Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany
| | - Matthias Schwab
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; Cluster of Excellence iFIT (EXC2180) Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany; Department of Clinical Pharmacology, and Department of Biochemistry and Pharmacy, University of Tübingen, Tübingen, Germany
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden; Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany.
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22
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Li MJ, Shi JY, Zhang BH, Chen QM, Shi B, Jia ZL. Targeted re-sequencing on 1p22 among non-syndromic orofacial clefts from Han Chinese population. Front Genet 2022; 13:947126. [PMID: 36061182 PMCID: PMC9428125 DOI: 10.3389/fgene.2022.947126] [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] [Received: 05/18/2022] [Accepted: 07/08/2022] [Indexed: 11/20/2022] Open
Abstract
Rs560426 at 1p22 was proved to be associated with NSCL/P (non-syndromic cleft lip with or without the palate) in several populations, including Han Chinese population. Here, we conducted a deep sequencing around rs560426 to locate more susceptibility variants in this region. In total, 2,293 NSCL/P cases and 3,235 normal controls were recruited. After sequencing, association analysis was performed. Western blot, RT-qPCR, HE, immunofluorescence staining, and RNA sequencing were conducted for functional analyses of the selected variants. Association analysis indicated that rs77179923 was the only SNP associated with NSCLP specifically (p = 4.70E-04, OR = 1.84), and rs12071152 was uniquely associated with LCLO (p = 4.00E-04, OR = 1.30, 95%CI: 1.12–1.51). Moreover, de novo harmful rare variant NM_004815.3, NP_004806.3; c.1652G>C, p.R551T in ARHGAP29 resulted in a decreased expression level of ARHGAP29, which in turn affected NSCL/P-related biological processes; however, no overt cleft palate (CP) phenotype was observed. In conclusion, rs12071152 was a new susceptible variant, which is specifically associated with LCLO among the Han Chinese population. Allele A of it could increase the risk of having a cleft baby. Rs77179923 and rare variant NM_004815.3, NP_004806.3; c.1652G>C, p.R551T at 1p22 were both associated with NSCLP among the Han Chinese population. However, this missense variation contributes to no overt CP phenotype due to dosage insufficiency or compensation from other genes.
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Affiliation(s)
- Mu-Jia Li
- State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
- Department of Cleft Lip and Palate, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Jia-Yu Shi
- Division of Growth and Development and Section of Orthodontics, School of Dentistry, University of California, Los Angeles, Los Angeles, CA, United States
| | - Bi-He Zhang
- State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
- Department of Cleft Lip and Palate, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Qian-Ming Chen
- State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Bing Shi
- State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
- Department of Cleft Lip and Palate, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Zhong-Lin Jia
- State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
- Department of Cleft Lip and Palate, West China Hospital of Stomatology, Sichuan University, Chengdu, China
- *Correspondence: Zhong-Lin Jia,
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23
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Risk factors for acute encephalitis and early seizure recurrence in complex febrile seizures. Eur J Pediatr 2022; 181:3103-3110. [PMID: 35713689 DOI: 10.1007/s00431-022-04529-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/01/2022] [Accepted: 06/09/2022] [Indexed: 11/03/2022]
Abstract
The purpose of this study is to elucidate risk factors for central nervous system infection and early seizure recurrence in children with febrile seizures (FSs) and thus facilitate outpatient management of complex FS. This single-center, retrospective cohort study investigated 688 children (6-60 months old) with FSs in Japan during 2011-2021. We investigated the incidence and clinical manifestations of children with acute encephalitis or bacterial meningitis. Logistic regression modeling was used to examine risk factors for seizure recurrence within 24 h. Among children with recurrent FSs, the distribution of intervals between first and second FS was assessed. Among 145 children with complex FSs, 2 patients (1.4%) had acute viral encephalitis and none had bacterial meningitis. Acute encephalitis was found in 2 of 8 patients (25%) with FSs prolonged ≥30 min and 2 of 3 patients (67%) requiring ≥2 intravenous anticonvulsants to stop seizures. Seizure recurrence within 24 h was observed in 16% of participants and was independently associated with preceding use of diazepam and family history of FS. In 82% of patients with FS recurrence within 24 h, early recurrences occurred within 8 h of the first seizure. Conclusion: Patients with prolonged or refractory FSs are still indicated for hospital admission due to the risk of acute encephalitis. FS patients with a family history of FS may be managed safely by 8-h observation or single-dose rectal diazepam as prophylaxis against early recurrent seizure. What is Known: • Hospitalization has been recommended for children with complex febrile seizures due to the increased risk of central nervous infections. • Recent studies showed low incidences of bacterial meningitis (<1%) in children with complex febrile seizures in the presence of routine immunization. What is New: • Acute encephalitis was identified in 1.4% of children with complex febrile seizures, characterized by prolonged seizures ≥30 min and refractory seizures. • Early recurrent seizures may be safely managed by prophylactic diazepam or 8-h expectant observation.
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24
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Thanh Nguyen D, Hoang Nguyen Q, Thuy Duong N, Vo NS. LmTag: functional-enrichment and imputation-aware tag SNP selection for population-specific genotyping arrays. Brief Bioinform 2022; 23:6627269. [PMID: 35780383 DOI: 10.1093/bib/bbac252] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 05/02/2022] [Accepted: 05/31/2022] [Indexed: 12/16/2022] Open
Abstract
Despite the rapid development of sequencing technology, single-nucleotide polymorphism (SNP) arrays are still the most cost-effective genotyping solutions for large-scale genomic research and applications. Recent years have witnessed the rapid development of numerous genotyping platforms of different sizes and designs, but population-specific platforms are still lacking, especially for those in developing countries. SNP arrays designed for these countries should be cost-effective (small size), yet incorporate key information needed to associate genotypes with traits. A key design principle for most current platforms is to improve genome-wide imputation so that more SNPs not included in the array (imputed SNPs) can be predicted. However, current tag SNP selection methods mostly focus on imputation accuracy and coverage, but not the functional content of the array. It is those functional SNPs that are most likely associated with traits. Here, we propose LmTag, a novel method for tag SNP selection that not only improves imputation performance but also prioritizes highly functional SNP markers. We apply LmTag on a wide range of populations using both public and in-house whole-genome sequencing databases. Our results show that LmTag improved both functional marker prioritization and genome-wide imputation accuracy compared to existing methods. This novel approach could contribute to the next generation genotyping arrays that provide excellent imputation capability as well as facilitate array-based functional genetic studies. Such arrays are particularly suitable for under-represented populations in developing countries or non-model species, where little genomics data are available while investment in genome sequencing or high-density SNP arrays is limited. $\textrm{LmTag}$ is available at: https://github.com/datngu/LmTag.
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Affiliation(s)
- Dat Thanh Nguyen
- Center for Biomedical Informatics, Vingroup Big Data Institute, 458 Minh Khai, 10000, Hanoi, Vietnam
| | - Quan Hoang Nguyen
- Institute for Molecular Bioscience, University of Queensland, st Lucia, QLD 4067, Brisbane, Australia
| | - Nguyen Thuy Duong
- Center for Biomedical Informatics, Vingroup Big Data Institute, 458 Minh Khai, 10000, Hanoi, Vietnam.,Institute of Genome Research, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet, 10000, Hanoi, Vietnam
| | - Nam S Vo
- Center for Biomedical Informatics, Vingroup Big Data Institute, 458 Minh Khai, 10000, Hanoi, Vietnam.,College of Engineering and Computer Science, VinUniversity, Vinhomes Ocean Park, 10000, Hanoi, Vietnam
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25
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Silgado-Guzmán DF, Angulo-Aguado M, Morel A, Niño-Orrego MJ, Ruiz-Torres DA, Contreras Bravo NC, Restrepo CM, Ortega-Recalde O, Fonseca-Mendoza DJ. Characterization of ADME Gene Variation in Colombian Population by Exome Sequencing. Front Pharmacol 2022; 13:931531. [PMID: 35846994 PMCID: PMC9280300 DOI: 10.3389/fphar.2022.931531] [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] [Received: 04/29/2022] [Accepted: 06/08/2022] [Indexed: 11/18/2022] Open
Abstract
In genes related to drug pharmacokinetics, molecular variations determine interindividual variability in the therapeutic efficacy and adverse drug reactions. The assessment of single-nucleotide variants (SNVs) is used with growing frequency in pharmacogenetic practice, and recently, high-throughput genomic analyses obtained through next-generation sequencing (NGS) have been recognized as powerful tools to identify common, rare and novel variants. These genetic profiles remain underexplored in Latin-American populations, including Colombia. In this study, we investigated the variability of 35 genes included in the ADME core panel (absorption, distribution, metabolism, and excretion) by whole-exome sequencing (WES) of 509 unrelated Colombian individuals with no previous reports of adverse drug reactions. Rare variants were filtered according to the minor allele frequencies (MAF) <1% and potential deleterious consequences. The functional impact of novel and rare missense variants was assessed using an optimized framework for pharmacogenetic variants. Bioinformatic analyses included the identification of clinically validated variants described in PharmGKB and ClinVar databases. Ancestry from WES data was inferred using the R package EthSEQ v2.1.4. Allelic frequencies were compared to other populations reported in the public gnomAD database. Our analysis revealed that rare missense pharmacogenetic variants were 2.1 times more frequent than common variants with 121 variants predicted as potentially deleterious. Rare loss of function (LoF) variants were identified in 65.7% of evaluated genes. Regarding variants with clinical pharmacogenetic effect, our study revealed 89 sequence variations in 28 genes represented by missense (62%), synonymous (22.5%), splice site (11.2%), and indels (3.4%). In this group, ABCB1, ABCC2, CY2B6, CYP2D6, DPYD, NAT2, SLC22A1, and UGTB2B7, are the most polymorphic genes. NAT2, CYP2B6 and DPYD metabolizer phenotypes demonstrated the highest variability. Ancestry analysis indicated admixture in 73% of the population. Allelic frequencies exhibit significant differences with other Latin-American populations, highlighting the importance of pharmacogenomic studies in populations of different ethnicities. Altogether, our data revealed that rare variants are an important source of variability in pharmacogenes involved in the pharmacokinetics of drugs and likely account for the unexplained interindividual variability in drug response. These findings provide evidence of the utility of WES for pharmacogenomic testing and into clinical practice.
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Affiliation(s)
| | - Mariana Angulo-Aguado
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Adrien Morel
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - María José Niño-Orrego
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Daniel-Armando Ruiz-Torres
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Nora Constanza Contreras Bravo
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Carlos Martin Restrepo
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Oscar Ortega-Recalde
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
- *Correspondence: Oscar Ortega-Recalde, ; Dora Janeth Fonseca-Mendoza,
| | - Dora Janeth Fonseca-Mendoza
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
- *Correspondence: Oscar Ortega-Recalde, ; Dora Janeth Fonseca-Mendoza,
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26
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Genomics facilitates evaluation and monitoring of McCloud River Redband Trout (Oncorhynchus mykiss stonei). CONSERV GENET 2022. [DOI: 10.1007/s10592-022-01453-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
AbstractThe McCloud River Redband Trout (MRRT; Oncorhynchus mykiss stonei) is a unique subspecies of rainbow trout that inhabits the isolated Upper McCloud River of Northern California. A major threat to MRRT is introgressive hybridization with non-native rainbow trout from historical stocking and contemporary unauthorized introductions. To help address this concern, we collected RAD-sequencing data on 308 total individuals from MRRT and other California O. mykiss populations and examined population structure using Principal Component and admixture analyses. Our results are consistent with previous studies; we found that populations of MRRT in Sheepheaven, Swamp, Edson, and Moosehead creeks are nonintrogressed. Additionally, we saw no evidence of introgression in Dry Creek, and suggest further investigation to determine if it can be considered a core MRRT conservation population. Sheepheaven Creek was previously thought to be the sole historical lineage of MRRT, but our analysis identified three: Sheepheaven, Edson, and Dry creeks, all of which should be preserved. Finally, we discovered diagnostic and polymorphic SNP markers for monitoring introgression and genetic diversity in MRRT. Collectively, our results provide a valuable resource for the conservation and management of MRRT.
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27
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Simulation Research on the Methods of Multi-Gene Region Association Analysis Based on a Functional Linear Model. Genes (Basel) 2022; 13:genes13030455. [PMID: 35328009 PMCID: PMC8954869 DOI: 10.3390/genes13030455] [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] [Received: 01/30/2022] [Revised: 02/26/2022] [Accepted: 02/27/2022] [Indexed: 11/16/2022] Open
Abstract
Genome-wide association analysis is an important approach to identify genetic variants associated with complex traits. Complex traits are not only affected by single gene loci, but also by the interaction of multiple gene loci. Studies of association between gene regions and quantitative traits are of great significance in revealing the genetic mechanism of biological development. There have been a lot of studies on single-gene region association analysis, but the application of functional linear models in multi-gene region association analysis is still less. In this paper, a functional multi-gene region association analysis test method is proposed based on the functional linear model. From the three directions of common multi-gene region method, multi-gene region weighted method and multi-gene region loci weighted method, that test method is studied combined with computer simulation. The following conclusions are obtained through computer simulation: (a) The functional multi-gene region association analysis test method has higher power than the functional single gene region association analysis test method; (b) The functional multi-gene region weighted method performs better than the common functional multi-gene region method; (c) the functional multi-gene region loci weighted method is the best method for association analysis on three directions of the common multi-gene region method; (d) the performance of the Step method and Multi-gene region loci weighted Step for multi-gene regions is the best in general. Functional multi-gene region association analysis test method can theoretically provide a feasible method for the study of complex traits affected by multiple genes.
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28
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Auwerx C, Sadler MC, Reymond A, Kutalik Z. From Pharmacogenetics to Pharmaco-Omics:Milestones and Future Directions. HGG ADVANCES 2022; 3:100100. [PMID: 35373152 PMCID: PMC8971318 DOI: 10.1016/j.xhgg.2022.100100] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.
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Epigenomic Modifications in Modern and Ancient Genomes. Genes (Basel) 2022; 13:genes13020178. [PMID: 35205223 PMCID: PMC8872240 DOI: 10.3390/genes13020178] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 01/12/2022] [Accepted: 01/13/2022] [Indexed: 12/26/2022] Open
Abstract
Epigenetic changes have been identified as a major driver of fundamental metabolic pathways. More specifically, the importance of epigenetic regulatory mechanisms for biological processes like speciation and embryogenesis has been well documented and revealed the direct link between epigenetic modifications and various diseases. In this review, we focus on epigenetic changes in animals with special attention on human DNA methylation utilizing ancient and modern genomes. Acknowledging the latest developments in ancient DNA research, we further discuss paleoepigenomic approaches as the only means to infer epigenetic changes in the past. Investigating genome-wide methylation patterns of ancient humans may ultimately yield in a more comprehensive understanding of how our ancestors have adapted to the changing environment, and modified their lifestyles accordingly. We discuss the difficulties of working with ancient DNA in particular utilizing paleoepigenomic approaches, and assess new paleoepigenomic data, which might be helpful in future studies.
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Jones AV, Curtiss D, Harris C, Southerington T, Hautalahti M, Wihuri P, Mäkelä J, Kallionpää RE, Makkonen E, Knopp T, Mannermaa A, Mäkinen E, Moilanen AM, Tezel TH, Waheed NK. An assessment of prevalence of Type 1 CFI rare variants in European AMD, and why lack of broader genetic data hinders development of new treatments and healthcare access. PLoS One 2022; 17:e0272260. [PMID: 36067162 PMCID: PMC9447915 DOI: 10.1371/journal.pone.0272260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 07/14/2022] [Indexed: 11/19/2022] Open
Abstract
PURPOSE Advanced age-related macular degeneration (AAMD) risk is associated with rare complement Factor I (FI) genetic variants associated with low FI protein levels (termed 'Type 1'), but it is unclear how variant prevalences differ between AMD patients from different ethnicities. METHODS Collective prevalence of Type 1 CFI rare variant genotypes were examined in four European AAMD datasets. Collective minor allele frequencies (MAFs) were sourced from the natural history study SCOPE, the UK Biobank, the International AMD Genomics Consortium (IAMDGC), and the Finnish Biobank Cooperative (FINBB), and compared to paired control MAFs or background population prevalence rates from the Genome Aggregation Database (gnomAD). Due to a lack of available genetic data in non-European AAMD, power calculations were undertaken to estimate the AAMD population sizes required to identify statistically significant association between Type 1 CFI rare variants and disease risk in different ethnicities, using gnomAD populations as controls. RESULTS Type 1 CFI rare variants were enriched in all European AAMD cohorts, with odds ratios (ORs) ranging between 3.1 and 7.8, and a greater enrichment was observed in dry AMD from FINBB (OR 8.9, 95% CI 1.49-53.31). The lack of available non-European AAMD datasets prevented us exploring this relationship more globally, however a statistical association may be detectable by future sequencing studies that sample approximately 2,000 AAMD individuals from Ashkenazi Jewish and Latino/Admixed American ethnicities. CONCLUSIONS The relationship between Type 1 CFI rare variants increasing odds of AAMD are well established in Europeans, however the lack of broader genetic data in AAMD has adverse implications for clinical development and future commercialisation strategies of targeted FI therapies in AAMD. These findings emphasise the importance of generating more diverse genetic data in AAMD to improve equity of access to new treatments and address the bias in health care.
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Affiliation(s)
- Amy V. Jones
- Gyroscope Therapeutics Limited, London, United Kingdom
| | - Darin Curtiss
- Gyroscope Therapeutics Limited, London, United Kingdom
| | - Claire Harris
- Gyroscope Therapeutics Limited, London, United Kingdom
| | - Tom Southerington
- Finnish Biobank Cooperative–FINBB, Turku, Finland
- University of Turku, Turku, Finland
| | | | - Pauli Wihuri
- Finnish Biobank Cooperative–FINBB, Turku, Finland
| | | | - Roosa E. Kallionpää
- Auria Biobank, Turku University Hospital and University of Turku, Turku, Finland
| | | | - Theresa Knopp
- Helsinki Biobank, HUS, Helsinki University Hospital, Helsinki, Finland
| | | | - Erna Mäkinen
- Biobank of Central Finland, Hospital Nova of Central Finland, Jyväskylä, Finland
| | - Anne-Mari Moilanen
- Biobank Borealis of Northern Finland, Oulu University Hospital, Oulu, Finland
| | - Tongalp H. Tezel
- Department of Ophthalmology, Edward S. Harkness Eye Institute, Columbia University College of Physicians and Surgeons, Columbia University Medical Center, New York, NY, United States of America
| | | | - Nadia K. Waheed
- Gyroscope Therapeutics Limited, London, United Kingdom
- Department of Ophthalmology, Tufts University School of Medicine, Boston, Massachusetts, United States of America
- * E-mail:
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31
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Agarwal I, Przeworski M. Mutation saturation for fitness effects at human CpG sites. eLife 2021; 10:e71513. [PMID: 34806592 PMCID: PMC8683084 DOI: 10.7554/elife.71513] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 11/21/2021] [Indexed: 01/06/2023] Open
Abstract
Whole exome sequences have now been collected for millions of humans, with the related goals of identifying pathogenic mutations in patients and establishing reference repositories of data from unaffected individuals. As a result, we are approaching an important limit, in which datasets are large enough that, in the absence of natural selection, every highly mutable site will have experienced at least one mutation in the genealogical history of the sample. Here, we focus on CpG sites that are methylated in the germline and experience mutations to T at an elevated rate of ~10-7 per site per generation; considering synonymous mutations in a sample of 390,000 individuals, ~ 99 % of such CpG sites harbor a C/T polymorphism. Methylated CpG sites provide a natural mutation saturation experiment for fitness effects: as we show, at nt sample sizes, not seeing a non-synonymous polymorphism is indicative of strong selection against that mutation. We rely on this idea in order to directly identify a subset of CpG transitions that are likely to be highly deleterious, including ~27 % of possible loss-of-function mutations, and up to 20 % of possible missense mutations, depending on the type of functional site in which they occur. Unlike methylated CpGs, most mutation types, with rates on the order of 10-8 or 10-9, remain very far from saturation. We discuss what these findings imply for interpreting the potential clinical relevance of mutations from their presence or absence in reference databases and for inferences about the fitness effects of new mutations.
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Affiliation(s)
- Ipsita Agarwal
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
| | - Molly Przeworski
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
- Department of Systems Biology, Columbia UniversityNew YorkUnited States
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32
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Lali R, Chong M, Omidi A, Mohammadi-Shemirani P, Le A, Cui E, Paré G. Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories. Nat Commun 2021; 12:5852. [PMID: 34615865 PMCID: PMC8494733 DOI: 10.1038/s41467-021-26114-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Accepted: 09/06/2021] [Indexed: 11/24/2022] Open
Abstract
Rare variants are collectively numerous and may underlie a considerable proportion of complex disease risk. However, identifying genuine rare variant associations is challenging due to small effect sizes, presence of technical artefacts, and heterogeneity in population structure. We hypothesize that rare variant burden over a large number of genes can be combined into a predictive rare variant genetic risk score (RVGRS). We propose a method (RV-EXCALIBER) that leverages summary-level data from a large public exome sequencing database (gnomAD) as controls and robustly calibrates rare variant burden to account for the aforementioned biases. A calibrated RVGRS strongly associates with coronary artery disease (CAD) in European and South Asian populations by capturing the aggregate effect of rare variants through a polygenic model of inheritance. The RVGRS identifies 1.5% of the population with substantial risk of early CAD and confers risk even when adjusting for known Mendelian CAD genes, clinical risk factors, and a common variant genetic risk score.
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Affiliation(s)
- Ricky Lali
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, L8L 2X2, Canada
- Department of Health Research Methodology, Evidence, and Impact, McMaster University, Faculty of Health Sciences, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada
| | - Michael Chong
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, L8L 2X2, Canada
- Department of Biochemistry and Biomedical Sciences, McMaster University, Faculty of Health Sciences, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada
| | - Arghavan Omidi
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, L8L 2X2, Canada
| | - Pedrum Mohammadi-Shemirani
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, L8L 2X2, Canada
- Department of Medical Sciences, McMaster University, Faculty of Health Sciences, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada
| | - Ann Le
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, L8L 2X2, Canada
- Department of Medical Sciences, McMaster University, Faculty of Health Sciences, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada
| | - Edward Cui
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, L8L 2X2, Canada
| | - Guillaume Paré
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, L8L 2X2, Canada.
- Department of Health Research Methodology, Evidence, and Impact, McMaster University, Faculty of Health Sciences, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada.
- Department of Biochemistry and Biomedical Sciences, McMaster University, Faculty of Health Sciences, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada.
- Department of Medical Sciences, McMaster University, Faculty of Health Sciences, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada.
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, L8L 2×2, Canada.
- Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada.
- Department of Clinical Epidemiology & Biostatistics, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada.
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Juhari WKW, Ahmad Amin Noordin KB, Zakaria AD, Rahman WFWA, Mokhter WMMWM, Hassan MRA, Sidek ASM, Zilfalil BA. Whole-Genome Profiles of Malay Colorectal Cancer Patients with Intact MMR Proteins. Genes (Basel) 2021; 12:genes12091448. [PMID: 34573430 PMCID: PMC8471947 DOI: 10.3390/genes12091448] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/17/2021] [Accepted: 09/18/2021] [Indexed: 12/12/2022] Open
Abstract
Background: This study aimed to identify new genes associated with CRC in patients with normal mismatch repair (MMR) protein expression. Method: Whole-genome sequencing (WGS) was performed in seven early-age-onset Malay CRC patients. Potential germline genetic variants, including single-nucleotide variations and insertions and deletions (indels), were prioritized using functional and predictive algorithms. Results: An average of 3.2 million single-nucleotide variations (SNVs) and over 800 indels were identified. Three potential candidate variants in three genes—IFNE, PTCH2 and SEMA3D—which were predicted to affect protein function, were identified in three Malay CRC patients. In addition, 19 candidate genes—ANKDD1B, CENPM, CLDN5, MAGEB16, MAP3K14, MOB3C, MS4A12, MUC19, OR2L8, OR51Q1, OR51AR1, PDE4DIP, PKD1L3, PRIM2, PRM3, SEC22B, TPTE, USP29 and ZNF117—harbouring nonsense variants were prioritised. These genes are suggested to play a role in cancer predisposition and to be associated with cancer risk. Pathway enrichment analysis indicated significant enrichment in the olfactory signalling pathway. Conclusion: This study provides a new spectrum of insights into the potential genes, variants and pathways associated with CRC in Malay patients.
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Affiliation(s)
- Wan Khairunnisa Wan Juhari
- Human Genome Centre, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia;
- Malaysian Node of the Human Variome Project, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia
| | | | - Andee Dzulkarnaen Zakaria
- Department of Surgery, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia; (A.D.Z.); (W.M.M.W.M.M.)
| | - Wan Faiziah Wan Abdul Rahman
- Department of Pathology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia;
| | | | | | | | - Bin Alwi Zilfalil
- Human Genome Centre, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia;
- Malaysian Node of the Human Variome Project, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia
- Correspondence: ; Tel.: +60-9-7676531
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34
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Zhou Y, Arribas GH, Turku A, Jürgenson T, Mkrtchian S, Krebs K, Wang Y, Svobodova B, Milani L, Schulte G, Korabecny J, Gastaldello S, Lauschke VM. Rare genetic variability in human drug target genes modulates drug response and can guide precision medicine. SCIENCE ADVANCES 2021; 7:eabi6856. [PMID: 34516913 PMCID: PMC8442892 DOI: 10.1126/sciadv.abi6856] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Interindividual variability in drug response constitutes a major concern in pharmacotherapy. While polymorphisms in genes involved in drug disposition have been extensively studied, drug target variability remains underappreciated. By mapping the genomic variability of all human drug target genes onto high-resolution crystal structures of drug target complexes, we identified 1094 variants localized within 6 Å of drug-binding pockets and directly affecting their geometry, topology, or physicochemical properties. We experimentally show that binding site variants affect pharmacodynamics with marked drug- and variant-specific differences. In addition, we demonstrate that a common BCHE variant confers resistance to tacrine and rivastigmine, which can be overcome by the use of derivatives based on squaric acid scaffolds or tryptophan conjugation. These findings underscore the importance of genetic drug target variability and demonstrate that integration of genomic data and structural information can inform personalized drug selection and genetically guided drug development to overcome resistance.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Gabriel Herras Arribas
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Ainoleena Turku
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
- Orion Pharma R&D, P.O. Box 65 (Orionintie 1), FI-02101 Espoo, Finland
| | - Tuuli Jürgenson
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Souren Mkrtchian
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Kristi Krebs
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Yi Wang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, 310058 Hangzhou, China
| | - Barbora Svobodova
- Biomedical Research Centre, University Hospital Hradec Králové, Sokolská 581, 500 05 Hradec Králové, Czech Republic
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Gunnar Schulte
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Jan Korabecny
- Biomedical Research Centre, University Hospital Hradec Králové, Sokolská 581, 500 05 Hradec Králové, Czech Republic
| | - Stefano Gastaldello
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Volker M. Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- Corresponding author.
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35
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Wright GEB, Caron NS, Ng B, Casal L, Casazza W, Xu X, Ooi J, Pouladi MA, Mostafavi S, Ross CJD, Hayden MR. Gene expression profiles complement the analysis of genomic modifiers of the clinical onset of Huntington disease. Hum Mol Genet 2021; 29:2788-2802. [PMID: 32898862 PMCID: PMC7530525 DOI: 10.1093/hmg/ddaa184] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 06/25/2020] [Accepted: 08/10/2020] [Indexed: 12/13/2022] Open
Abstract
Huntington disease (HD) is a neurodegenerative disorder that is caused by a CAG repeat expansion in HTT. The length of this repeat, however, only explains a proportion of the variability in age of onset in patients. Genome-wide association studies have identified modifiers that contribute toward a proportion of the observed variance. By incorporating tissue-specific transcriptomic information with these results, additional modifiers can be identified. We performed a transcriptome-wide association study assessing heritable differences in genetically determined expression in diverse tissues, with genome-wide data from over 4000 patients. Functional validation of prioritized genes was undertaken in isogenic HD stem cells and patient brains. Enrichment analyses were performed with biologically relevant gene sets to identify the core pathways. HD-associated gene coexpression modules were assessed for associations with neurological phenotypes in an independent cohort and to guide drug repurposing analyses. Transcriptomic analyses identified genes that were associated with age of HD onset and displayed colocalization with gene expression signals in brain tissue (FAN1, GPR161, PMS2, SUMF2), with supporting evidence from functional experiments. This included genes involved in DNA repair, as well as novel-candidate modifier genes that have been associated with other neurological conditions. Further, cortical coexpression modules were also associated with cognitive decline and HD-related traits in a longitudinal cohort. In summary, the combination of population-scale gene expression information with HD patient genomic data identified novel modifier genes for the disorder. Further, these analyses expanded the pathways potentially involved in modifying HD onset and prioritized candidate therapeutics for future study.
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Affiliation(s)
- Galen E B Wright
- Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia V5Z 4H4, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia V6H 3N1, Canada.,BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
| | - Nicholas S Caron
- Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia V5Z 4H4, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia V6H 3N1, Canada.,BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
| | - Bernard Ng
- Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia V5Z 4H4, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia V6H 3N1, Canada.,Department of Statistics, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Lorenzo Casal
- Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia V5Z 4H4, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia V6H 3N1, Canada.,BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
| | - William Casazza
- Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia V5Z 4H4, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia V6H 3N1, Canada.,Department of Statistics, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Xiaohong Xu
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR), Singapore 138648, Singapore
| | - Jolene Ooi
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR), Singapore 138648, Singapore
| | - Mahmoud A Pouladi
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR), Singapore 138648, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.,Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Sara Mostafavi
- Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia V5Z 4H4, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia V6H 3N1, Canada.,Department of Statistics, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Colin J D Ross
- BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada.,Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.,Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Michael R Hayden
- Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia V5Z 4H4, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia V6H 3N1, Canada.,BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
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36
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McCorkle ML, Kisor DF, Freiermuth CE, Sprague JE. Systematic review of Pharmacogenomics Knowledgebase evidence for pharmacogenomic links to the dopamine reward pathway for heroin dependence. Pharmacogenomics 2021; 22:849-857. [PMID: 34424051 DOI: 10.2217/pgs-2021-0023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Genetics play an important role in opioid use disorder (OUD); however, few specific gene variants have been identified. Therefore, there is a need to further understand the pharmacogenomics influences on the pharmacodynamics of opioids. The Pharmacogenomics Knowledgebase (PharmGKB), a database that links genetic variation and drug interaction in the body, was queried to identify polymorphisms associated with heroin dependence in the context of opioid related disorders/OUD. Eight genes with 22 variants were identified as linked to increased risk of heroin dependence, with three genes and variants linked to decreased risk, although the level of evidence was moderate to low. Therefore, continued exploration of biomarker influences on OUD, reward pathways and other contributing circuitries is necessary to understand the true impact of genetics on OUD before integration into clinical guidelines.
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Affiliation(s)
| | - David F Kisor
- Department of Pharmaceutical Sciences & Pharmacogenomics, College of Pharmacy, Natural & Health Sciences, Manchester University, Fort Wayne, IN 46845, USA
| | - Caroline E Freiermuth
- Department of Emergency Medicine, University of Cincinnati, Cincinnati, OH 45267, USA.,Center for Addiction Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Jon E Sprague
- The Ohio Attorney General's Office, Columbus, OH 43215, USA.,The Ohio Attorney General's Center for the Future of Forensic Science, Bowling Green State University, Bowling Green, OH 43403, USA
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37
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Pandi MT, Koromina M, Tsafaridis I, Patsilinakos S, Christoforou E, van der Spek PJ, Patrinos GP. A novel machine learning-based approach for the computational functional assessment of pharmacogenomic variants. Hum Genomics 2021; 15:51. [PMID: 34372920 PMCID: PMC8351412 DOI: 10.1186/s40246-021-00352-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 07/28/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The field of pharmacogenomics focuses on the way a person's genome affects his or her response to a certain dose of a specified medication. The main aim is to utilize this information to guide and personalize the treatment in a way that maximizes the clinical benefits and minimizes the risks for the patients, thus fulfilling the promises of personalized medicine. Technological advances in genome sequencing, combined with the development of improved computational methods for the efficient analysis of the huge amount of generated data, have allowed the fast and inexpensive sequencing of a patient's genome, hence rendering its incorporation into clinical routine practice a realistic possibility. METHODS This study exploited thoroughly characterized in functional level SNVs within genes involved in drug metabolism and transport, to train a classifier that would categorize novel variants according to their expected effect on protein functionality. This categorization is based on the available in silico prediction and/or conservation scores, which are selected with the use of recursive feature elimination process. Toward this end, information regarding 190 pharmacovariants was leveraged, alongside with 4 machine learning algorithms, namely AdaBoost, XGBoost, multinomial logistic regression, and random forest, of which the performance was assessed through 5-fold cross validation. RESULTS All models achieved similar performance toward making informed conclusions, with RF model achieving the highest accuracy (85%, 95% CI: 0.79, 0.90), as well as improved overall performance (precision 85%, sensitivity 84%, specificity 94%) and being used for subsequent analyses. When applied on real world WGS data, the selected RF model identified 2 missense variants, expected to lead to decreased function proteins and 1 to increased. As expected, a greater number of variants were highlighted when the approach was used on NGS data derived from targeted resequencing of coding regions. Specifically, 71 variants (out of 156 with sufficient annotation information) were classified as to "Decreased function," 41 variants as "No" function proteins, and 1 variant in "Increased function." CONCLUSION Overall, the proposed RF-based classification model holds promise to lead to an extremely useful variant prioritization and act as a scoring tool with interesting clinical applications in the fields of pharmacogenomics and personalized medicine.
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Affiliation(s)
- Maria-Theodora Pandi
- Erasmus University Medical Center, Faculty of Medicine and Health Sciences, Department of Pathology, Bioinformatics Unit, Rotterdam, the Netherlands
| | - Maria Koromina
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece.,The Golden Helix Foundation, London, UK
| | | | | | | | - Peter J van der Spek
- Erasmus University Medical Center, Faculty of Medicine and Health Sciences, Department of Pathology, Bioinformatics Unit, Rotterdam, the Netherlands
| | - George P Patrinos
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece. .,Zayed Center of Health Sciences, United Arab Emirates University, Al-Ain, United Arab Emirates. .,Department of Pathology, College of Medicine and Health Sciences, United Arab Emirates University, Al-Ain, United Arab Emirates.
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38
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Park Y, Heider D, Hauschild AC. Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence. Cancers (Basel) 2021; 13:3148. [PMID: 34202427 PMCID: PMC8269018 DOI: 10.3390/cancers13133148] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 06/16/2021] [Accepted: 06/21/2021] [Indexed: 12/18/2022] Open
Abstract
The rapid improvement of next-generation sequencing (NGS) technologies and their application in large-scale cohorts in cancer research led to common challenges of big data. It opened a new research area incorporating systems biology and machine learning. As large-scale NGS data accumulated, sophisticated data analysis methods became indispensable. In addition, NGS data have been integrated with systems biology to build better predictive models to determine the characteristics of tumors and tumor subtypes. Therefore, various machine learning algorithms were introduced to identify underlying biological mechanisms. In this work, we review novel technologies developed for NGS data analysis, and we describe how these computational methodologies integrate systems biology and omics data. Subsequently, we discuss how deep neural networks outperform other approaches, the potential of graph neural networks (GNN) in systems biology, and the limitations in NGS biomedical research. To reflect on the various challenges and corresponding computational solutions, we will discuss the following three topics: (i) molecular characteristics, (ii) tumor heterogeneity, and (iii) drug discovery. We conclude that machine learning and network-based approaches can add valuable insights and build highly accurate models. However, a well-informed choice of learning algorithm and biological network information is crucial for the success of each specific research question.
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Affiliation(s)
- Youngjun Park
- Department of Mathematics and Computer Science, Philipps-University of Marburg, 35032 Marburg, Germany; (Y.P.); (D.H.)
| | - Dominik Heider
- Department of Mathematics and Computer Science, Philipps-University of Marburg, 35032 Marburg, Germany; (Y.P.); (D.H.)
| | - Anne-Christin Hauschild
- Department of Mathematics and Computer Science, Philipps-University of Marburg, 35032 Marburg, Germany; (Y.P.); (D.H.)
- Department of Medical Informatics, University Medical Center Göttingen, 37075 Göttingen, Germany
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39
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Allen KE, Greenbaum E, Hime PM, Tapondjou N. WP, Sterkhova VV, Kusamba C, Rödel M, Penner J, Peterson AT, Brown RM. Rivers, not refugia, drove diversification in arboreal, sub-Saharan African snakes. Ecol Evol 2021; 11:6133-6152. [PMID: 34141208 PMCID: PMC8207163 DOI: 10.1002/ece3.7429] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 02/12/2021] [Accepted: 02/18/2021] [Indexed: 12/26/2022] Open
Abstract
The relative roles of rivers versus refugia in shaping the high levels of species diversity in tropical rainforests have been widely debated for decades. Only recently has it become possible to take an integrative approach to test predictions derived from these hypotheses using genomic sequencing and paleo-species distribution modeling. Herein, we tested the predictions of the classic river, refuge, and river-refuge hypotheses on diversification in the arboreal sub-Saharan African snake genus Toxicodryas. We used dated phylogeographic inferences, population clustering analyses, demographic model selection, and paleo-distribution modeling to conduct a phylogenomic and historical demographic analysis of this genus. Our results revealed significant population genetic structure within both Toxicodryas species, corresponding geographically to river barriers and divergence times from the mid-Miocene to Pliocene. Our demographic analyses supported the interpretation that rivers are indications of strong barriers to gene flow among populations since their divergence. Additionally, we found no support for a major contraction of suitable habitat during the last glacial maximum, allowing us to reject both the refuge and river-refuge hypotheses in favor of the river-barrier hypothesis. Based on conservative interpretations of our species delimitation analyses with the Sanger and ddRAD data sets, two new cryptic species are identified from east-central Africa. This study highlights the complexity of diversification dynamics in the African tropics and the advantages of integrative approaches to studying speciation in tropical regions.
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Affiliation(s)
- Kaitlin E. Allen
- Department of Ecology and Evolutionary BiologyUniversity of KansasLawrenceKSUSA
- Biodiversity InstituteUniversity of KansasLawrenceKSUSA
| | - Eli Greenbaum
- Department of Biological SciencesUniversity of Texas at El PasoEl PasoTXUSA
| | - Paul M. Hime
- Biodiversity InstituteUniversity of KansasLawrenceKSUSA
| | - Walter P. Tapondjou N.
- Department of Ecology and Evolutionary BiologyUniversity of KansasLawrenceKSUSA
- Biodiversity InstituteUniversity of KansasLawrenceKSUSA
| | - Viktoria V. Sterkhova
- Department of Ecology and Evolutionary BiologyUniversity of KansasLawrenceKSUSA
- Biodiversity InstituteUniversity of KansasLawrenceKSUSA
| | - Chifundera Kusamba
- Laboratoire d’Hérpétologie, Département de BiologieCentre de Recherche en Sciences NaturellesLwiroDemocratic Republic of Congo
| | - Mark‐Oliver Rödel
- Museum für Naturkunde – Leibniz Institute for Evolution and Biodiversity ScienceBerlinGermany
| | - Johannes Penner
- Museum für Naturkunde – Leibniz Institute for Evolution and Biodiversity ScienceBerlinGermany
- Chair of Wildlife Ecology and ManagementUniversity of FreiburgFreiburgGermany
| | - A. Townsend Peterson
- Department of Ecology and Evolutionary BiologyUniversity of KansasLawrenceKSUSA
- Biodiversity InstituteUniversity of KansasLawrenceKSUSA
| | - Rafe M. Brown
- Department of Ecology and Evolutionary BiologyUniversity of KansasLawrenceKSUSA
- Biodiversity InstituteUniversity of KansasLawrenceKSUSA
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40
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Russell LE, Zhou Y, Almousa AA, Sodhi JK, Nwabufo CK, Lauschke VM. Pharmacogenomics in the era of next generation sequencing - from byte to bedside. Drug Metab Rev 2021; 53:253-278. [PMID: 33820459 DOI: 10.1080/03602532.2021.1909613] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Pharmacogenetic research has resulted in the identification of a multitude of genetic variants that impact drug response or toxicity. These polymorphisms are mostly common and have been included as actionable information in the labels of numerous drugs. In addition to common variants, recent advances in Next Generation Sequencing (NGS) technologies have resulted in the identification of a plethora of rare and population-specific pharmacogenetic variations with unclear functional consequences that are not accessible by conventional forward genetics strategies. In this review, we discuss how comprehensive sequencing information can be translated into personalized pharmacogenomic advice in the age of NGS. Specifically, we provide an update of the functional impacts of rare pharmacogenetic variability and how this information can be leveraged to improve pharmacogenetic guidance. Furthermore, we critically discuss the current status of implementation of pharmacogenetic testing across drug development and layers of care. We identify major gaps and provide perspectives on how these can be minimized to optimize the utilization of NGS data for personalized clinical decision-support.
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Affiliation(s)
| | - Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Ahmed A Almousa
- Department of Pharmacy, London Health Sciences Center, Victoria Hospital, London, ON, Canada
| | - Jasleen K Sodhi
- Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, CA, USA.,Department of Drug Metabolism and Pharmacokinetics, Plexxikon, Inc., Berkeley, CA, USA
| | | | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
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41
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Highly diverse and rapidly spreading: Melanagromyza sojae threatens the soybean belt of South America. Biol Invasions 2021. [DOI: 10.1007/s10530-020-02447-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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42
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Guirao‐Rico S, González J. Benchmarking the performance of Pool-seq SNP callers using simulated and real sequencing data. Mol Ecol Resour 2021; 21:1216-1229. [PMID: 33534960 PMCID: PMC8251607 DOI: 10.1111/1755-0998.13343] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 12/21/2020] [Accepted: 01/27/2021] [Indexed: 12/13/2022]
Abstract
Population genomics is a fast-developing discipline with promising applications in a growing number of life sciences fields. Advances in sequencing technologies and bioinformatics tools allow population genomics to exploit genome-wide information to identify the molecular variants underlying traits of interest and the evolutionary forces that modulate these variants through space and time. However, the cost of genomic analyses of multiple populations is still too high to address them through individual genome sequencing. Pooling individuals for sequencing can be a more effective strategy in Single Nucleotide Polymorphism (SNP) detection and allele frequency estimation because of a higher total coverage. However, compared to individual sequencing, SNP calling from pools has the additional difficulty of distinguishing rare variants from sequencing errors, which is often avoided by establishing a minimum threshold allele frequency for the analysis. Finding an optimal balance between minimizing information loss and reducing sequencing costs is essential to ensure the success of population genomics studies. Here, we have benchmarked the performance of SNP callers for Pool-seq data, based on different approaches, under different conditions, and using computer simulations and real data. We found that SNP callers performance varied for allele frequencies up to 0.35. We also found that SNP callers based on Bayesian (SNAPE-pooled) or maximum likelihood (MAPGD) approaches outperform the two heuristic callers tested (VarScan and PoolSNP), in terms of the balance between sensitivity and FDR both in simulated and sequencing data. Our results will help inform the selection of the most appropriate SNP caller not only for large-scale population studies but also in cases where the Pool-seq strategy is the only option, such as in metagenomic or polyploid studies.
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Affiliation(s)
- Sara Guirao‐Rico
- Institute of Evolutionary BiologyCSIC‐Universitat Pompeu FabraBarcelonaSpain
| | - Josefa González
- Institute of Evolutionary BiologyCSIC‐Universitat Pompeu FabraBarcelonaSpain
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43
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Souza MG, Vallejo EE, Estrada K. Detecting Clustered Independent Rare Variant Associations Using Genetic Algorithms. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2021; 18:932-939. [PMID: 31403438 DOI: 10.1109/tcbb.2019.2930505] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The availability of an increasing collection of sequencing data provides the opportunity to study genetic variation with an unprecedented level of detail. There is much interest in uncovering the role of rare variants and their contribution to disease. However, detecting associations of rare variants with small minor allele frequencies (MAF) and modest effects remains a challenge for rare variant association methods. Due to this low signal-to-noise ratio, most methods are underpowered to detect associations even when conducting rare variant association tests at the gene level. We present a new method for detecting rare variant associations. The algorithm consists of two steps. In the first step, a genetic algorithm searches for a promising genomic region containing a collection of genes with causal rare variants. In the second step, a genetic algorithm aims at removing false positives from the located genomic region. We tested the proposed method with a collection of datasets obtained from real exome data. The proposed method possesses sufficient power for detecting associations of rare variants with complex phenotypes. This method can be used for studying the contribution of rare variants with complex disease, particularly in cases where single-variant or gene-based tests are underpowered.
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44
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Pathogenic missense protein variants affect different functional pathways and proteomic features than healthy population variants. PLoS Biol 2021; 19:e3001207. [PMID: 33909605 PMCID: PMC8110273 DOI: 10.1371/journal.pbio.3001207] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 05/10/2021] [Accepted: 03/26/2021] [Indexed: 12/27/2022] Open
Abstract
Missense variants are present amongst the healthy population, but some of them are causative of human diseases. A classification of variants associated with “healthy” or “diseased” states is therefore not always straightforward. A deeper understanding of the nature of missense variants in health and disease, the cellular processes they may affect, and the general molecular principles which underlie these differences is essential to offer mechanistic explanations of the true impact of pathogenic variants. Here, we have formalised a statistical framework which enables robust probabilistic quantification of variant enrichment across full-length proteins, their domains, and 3D structure-defined regions. Using this framework, we validate and extend previously reported trends of variant enrichment in different protein structural regions (surface/core/interface). By examining the association of variant enrichment with available functional pathways and transcriptomic and proteomic (protein half-life, thermal stability, abundance) data, we have mined a rich set of molecular features which distinguish between pathogenic and population variants: Pathogenic variants mainly affect proteins involved in cell proliferation and nucleotide processing and are enriched in more abundant proteins. Additionally, rare population variants display features closer to common than pathogenic variants. We validate the association between these molecular features and variant pathogenicity by comparing against existing in silico variant impact annotations. This study provides molecular details into how different proteins exhibit resilience and/or sensitivity towards missense variants and provides the rationale to prioritise variant-enriched proteins and protein domains for therapeutic targeting and development. The ZoomVar database, which we created for this study, is available at fraternalilab.kcl.ac.uk/ZoomVar. It allows users to programmatically annotate missense variants with protein structural information and to calculate variant enrichment in different protein structural regions. How do can one improve the classification of genetic variants as harmful or harmless? This study uses a robust statistical analysis to exploit the interplay between protein structure, proteomic measurements and functional pathways to enable better discrimination between missense variants in health and disease.
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Pang H, Xia Y, Luo S, Huang G, Li X, Xie Z, Zhou Z. Emerging roles of rare and low-frequency genetic variants in type 1 diabetes mellitus. J Med Genet 2021; 58:289-296. [PMID: 33753534 PMCID: PMC8086251 DOI: 10.1136/jmedgenet-2020-107350] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 01/06/2021] [Accepted: 01/10/2021] [Indexed: 12/12/2022]
Abstract
Type 1 diabetes mellitus (T1DM) is defined as an autoimmune disorder and has enormous complexity and heterogeneity. Although its precise pathogenic mechanisms are obscure, this disease is widely acknowledged to be precipitated by environmental factors in individuals with genetic susceptibility. To date, the known susceptibility loci, which have mostly been identified by genome-wide association studies, can explain 80%–85% of the heritability of T1DM. Researchers believe that at least a part of its missing genetic component is caused by undetected rare and low-frequency variants. Most common variants have only small to modest effect sizes, which increases the difficulty of dissecting their functions and restricts their potential clinical application. Intriguingly, many studies have indicated that rare and low-frequency variants have larger effect sizes and play more significant roles in susceptibility to common diseases, including T1DM, than common variants do. Therefore, better recognition of rare and low-frequency variants is beneficial for revealing the genetic architecture of T1DM and for providing new and potent therapeutic targets for this disease. Here, we will discuss existing challenges as well as the great significance of this field and review current knowledge of the contributions of rare and low-frequency variants to T1DM.
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Affiliation(s)
- Haipeng Pang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Ying Xia
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Shuoming Luo
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Gan Huang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Xia Li
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zhiguo Xie
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zhiguang Zhou
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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46
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Font-Porterias N, Caro-Consuegra R, Lucas-Sánchez M, Lopez M, Giménez A, Carballo-Mesa A, Bosch E, Calafell F, Quintana-Murci L, Comas D. The Counteracting Effects of Demography on Functional Genomic Variation: The Roma Paradigm. Mol Biol Evol 2021; 38:2804-2817. [PMID: 33713133 PMCID: PMC8233508 DOI: 10.1093/molbev/msab070] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Demographic history plays a major role in shaping the distribution of genomic variation. Yet the interaction between different demographic forces and their effects in the genomes is not fully resolved in human populations. Here, we focus on the Roma population, the largest transnational ethnic minority in Europe. They have a South Asian origin and their demographic history is characterized by recent dispersals, multiple founder events, and extensive gene flow from non-Roma groups. Through the analyses of new high-coverage whole exome sequences and genome-wide array data for 89 Iberian Roma individuals together with forward simulations, we show that founder effects have reduced their genetic diversity and proportion of rare variants, gene flow has counteracted the increase in mutational load, runs of homozygosity show ancestry-specific patterns of accumulation of deleterious homozygotes, and selection signals primarily derive from preadmixture adaptation in the Roma population sources. The present study shows how two demographic forces, bottlenecks and admixture, act in opposite directions and have long-term balancing effects on the Roma genomes. Understanding how demography and gene flow shape the genome of an admixed population provides an opportunity to elucidate how genomic variation is modeled in human populations.
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Affiliation(s)
- Neus Font-Porterias
- Departament de Ciències Experimentals i de la Salut, Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Rocio Caro-Consuegra
- Departament de Ciències Experimentals i de la Salut, Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Marcel Lucas-Sánchez
- Departament de Ciències Experimentals i de la Salut, Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Marie Lopez
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
| | - Aaron Giménez
- Facultat de Sociologia, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Elena Bosch
- Departament de Ciències Experimentals i de la Salut, Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Reus, Spain
| | - Francesc Calafell
- Departament de Ciències Experimentals i de la Salut, Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Lluís Quintana-Murci
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.,Human Genomics and Evolution, Collège de France, Paris, France
| | - David Comas
- Departament de Ciències Experimentals i de la Salut, Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
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47
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Fan R, Cui W, Chen J, Ma Y, Yang Z, Payne TJ, Ma JZ, Li MD. Gene-based association analysis reveals involvement of LAMA5 and cell adhesion pathways in nicotine dependence in African- and European-American samples. Addict Biol 2021; 26:e12898. [PMID: 32281736 DOI: 10.1111/adb.12898] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Revised: 03/07/2020] [Accepted: 03/09/2020] [Indexed: 01/01/2023]
Abstract
Nicotine dependence (ND) is a chronic brain disorder that causes heavy social and economic burdens. Although many susceptibility genetic loci have been reported, they can explain only approximately 5%-10% of the genetic variance for the disease. To further explore the genetic etiology of ND, we genotyped 242 764 SNPs using an exome chip from both European-American (N = 1572) and African-American (N = 3371) samples. Gene-based association analysis revealed 29 genes associated significantly with ND. Of the genes in the AA sample, six (i.e., PKD1L2, LAMA5, MUC16, MROH5, ATP8B1, and FREM1) were replicated in the EA sample with p values ranging from 0.0031 to 0.0346. Subsequently, gene enrichment analysis revealed that cell adhesion-related pathways were significantly associated with ND in both the AA and EA samples. Considering that LAMA5 is the most significant gene in cell adhesion-related pathways, we did in vitro functional analysis of this gene, which showed that nicotine significantly suppressed its mRNA expression in HEK293T cells (p < 0.001). Further, our cell migration experiment showed that the migration rate was significantly different in wild-type and LAMA5-knockout (LAMA5-KO)-HEK293T cells. Importantly, nicotine-induced cell migration was abolished in LAMA5-KO cells. Taken together, these findings indicate that LAMA5, as well as cell adhesion-related pathways, play an important role in the etiology of smoking addiction, which warrants further investigation.
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Affiliation(s)
- Rongli Fan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital Zhejiang University School of Medicine Hangzhou China
| | - Wenyan Cui
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital Zhejiang University School of Medicine Hangzhou China
| | - Jiali Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital Zhejiang University School of Medicine Hangzhou China
| | - Yunlong Ma
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital Zhejiang University School of Medicine Hangzhou China
| | - Zhongli Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital Zhejiang University School of Medicine Hangzhou China
| | - Thomas J. Payne
- ACT Center for Tobacco Treatment, Education and Research, Department of Otolaryngology and Communicative Sciences University of Mississippi Medical Center Jackson Mississippi USA
| | - Jennie Z. Ma
- Department of Public Health Sciences University of Virginia Charlottesville Virginia USA
| | - Ming D. Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital Zhejiang University School of Medicine Hangzhou China
- Research Center for Air Pollution and Health Zhejiang University Hangzhou China
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48
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Fitzgerald J, Wilson C, Kelly C, Gallagher L. 'More than a box of puzzles': Understanding the parental experience of having a child with a rare genetic condition". Eur J Med Genet 2021; 64:104164. [PMID: 33571692 DOI: 10.1016/j.ejmg.2021.104164] [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: 06/04/2020] [Revised: 01/25/2021] [Accepted: 02/04/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Chromosomal microarray (CMA) testing has been adopted as the first-tier diagnostic test for developmental disabilities. However, determining the clinical significance of the results is often complex. This qualitative study seeks to explore parental interpretation, adaption and coping in the context of ambiguous rare genetic findings in order to support parental adjustment and wellbeing. METHODS In-depth interviews were conducted with parents (n = 30) of children identified with a rare genetic chromosomal abnormality. RESULTS Three major themes were identified following a thematic analysis: 'Learning of the Genetic Diagnosis', "The Reality of the Rarity' and 'Beyond Genetics: The Child Takes Centre Stage'. Findings demonstrated that parental adjustment to their child's genetic results are mediated by several factors including child difficulties and stage of development, clinician communication, perception of genetics, intrinsic coping strategies, access to practical and emotional support as well as broader contextual experiences. CONCLUSION This study highlights the importance of considering the parental perspective in the context of genetic testing in clinical practice.
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Affiliation(s)
| | | | - Clare Kelly
- School of Psychology, Trinity College, Dublin, Ireland; Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Louise Gallagher
- Trinity Translational Medicine Institute, Trinity Centre for Health Sciences, Trinity College Dublin; Linn Dara Regional CAMHS Network, Cherry Orchard Hospital, Dublin 10, Ballyfermot; Children Health Ireland at Tallaght Hospital, Dublin 24
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49
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Susak H, Serra-Saurina L, Demidov G, Rabionet R, Domènech L, Bosio M, Muyas F, Estivill X, Escaramís G, Ossowski S. Efficient and flexible Integration of variant characteristics in rare variant association studies using integrated nested Laplace approximation. PLoS Comput Biol 2021; 17:e1007784. [PMID: 33606672 PMCID: PMC7928502 DOI: 10.1371/journal.pcbi.1007784] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 03/03/2021] [Accepted: 01/04/2021] [Indexed: 12/02/2022] Open
Abstract
Rare variants are thought to play an important role in the etiology of complex diseases and may explain a significant fraction of the missing heritability in genetic disease studies. Next-generation sequencing facilitates the association of rare variants in coding or regulatory regions with complex diseases in large cohorts at genome-wide scale. However, rare variant association studies (RVAS) still lack power when cohorts are small to medium-sized and if genetic variation explains a small fraction of phenotypic variance. Here we present a novel Bayesian rare variant Association Test using Integrated Nested Laplace Approximation (BATI). Unlike existing RVAS tests, BATI allows integration of individual or variant-specific features as covariates, while efficiently performing inference based on full model estimation. We demonstrate that BATI outperforms established RVAS methods on realistic, semi-synthetic whole-exome sequencing cohorts, especially when using meaningful biological context, such as functional annotation. We show that BATI achieves power above 70% in scenarios in which competing tests fail to identify risk genes, e.g. when risk variants in sum explain less than 0.5% of phenotypic variance. We have integrated BATI, together with five existing RVAS tests in the 'Rare Variant Genome Wide Association Study' (rvGWAS) framework for data analyzed by whole-exome or whole genome sequencing. rvGWAS supports rare variant association for genes or any other biological unit such as promoters, while allowing the analysis of essential functionalities like quality control or filtering. Applying rvGWAS to a Chronic Lymphocytic Leukemia study we identified eight candidate predisposition genes, including EHMT2 and COPS7A.
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Affiliation(s)
- Hana Susak
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Laura Serra-Saurina
- Biomedical Research Networking Centre consortium of Public Health and Epidemiology (CIBERESP), Madrid, Spain
- Center for research in occupational Health (CiSAL), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Research Group on Statistics, Econometrics and Health (GRECS), Universitat de Girona (UdG), Girona, Spain
| | - German Demidov
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
| | - Raquel Rabionet
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, IBUB, Universitat de Barcelona; CIBERER, IRSJD, Barcelona, Spain
| | - Laura Domènech
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Biomedical Research Networking Centre consortium of Public Health and Epidemiology (CIBERESP), Madrid, Spain
| | - Mattia Bosio
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Francesc Muyas
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
| | - Xavier Estivill
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Women’s Health Dexeus, Barcelona, Spain
| | - Geòrgia Escaramís
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Biomedical Research Networking Centre consortium of Public Health and Epidemiology (CIBERESP), Madrid, Spain
- Departament de Biomedicina, Facultat de Medicina i Ciències de la Salut, Institut de Neurociències, Universitat de Barcelona, Spain
| | - Stephan Ossowski
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
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Wong ML, Arcos-Burgos M, Liu S, Licinio AW, Yu C, Chin EWM, Yao WD, Lu XY, Bornstein SR, Licinio J. Rare Functional Variants Associated with Antidepressant Remission in Mexican-Americans: Short title: Antidepressant remission and pharmacogenetics in Mexican-Americans. J Affect Disord 2021; 279:491-500. [PMID: 33128939 PMCID: PMC7953425 DOI: 10.1016/j.jad.2020.10.027] [Citation(s) in RCA: 3] [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: 04/10/2020] [Revised: 08/24/2020] [Accepted: 10/11/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Rare genetic functional variants can contribute to 30-40% of functional variability in genes relevant to drug action. Therefore, we investigated the role of rare functional variants in antidepressant response. METHOD Mexican-American individuals meeting the Diagnostic and Statistical Manual-IV criteria for major depressive disorder (MDD) participated in a prospective randomized, double-blind study with desipramine or fluoxetine. The rare variant analysis was performed using whole-exome genotyping data. Network and pathway analyses were carried out with the list of significant genes. RESULTS The Kernel-Based Adaptive Cluster method identified functional rare variants in 35 genes significantly associated with treatment remission (False discovery rate, FDR <0.01). Pathway analysis of these genes supports the involvement of the following gene ontology processes: olfactory/sensory transduction, regulation of response to cytokine stimulus, and meiotic cell cycleprocess. LIMITATIONS Our study did not have a placebo arm. We were not able to use antidepressant blood level as a covariate. Our study is based on a small sample size of only 65 Mexican-American individuals. Further studies using larger cohorts are warranted. CONCLUSION Our data identified several rare functional variants in antidepressant drug response in MDD patients. These have the potential to serve as genetic markers for predicting drug response. TRIAL REGISTRATION ClinicalTrials.gov NCT00265291.
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Affiliation(s)
- Ma-Li Wong
- Department of Psychiatry and Behavioral Sciences, State University of New York, Upstate Medical University, Syracuse, NY, USA; Department of Neuroscience and Physiology, State University of New York, Upstate Medical University, Syracuse, NY, USA; Mind & Brain Theme, South Australian Health and Medical Research Institute Adelaide, South Australia, Australia; Department of Psychiatry, Flinders University College of Medicine and Public Health, Bedford Park, South Australia, Australia.
| | - Mauricio Arcos-Burgos
- Grupo de Investigación en Psiquiatría, Departamento de Psiquiatría, Instituto de Investigaciones Médicas, Facultad de Medicina, Universidad de Antioquia, Medellin, Antioquia, Colombia
| | - Sha Liu
- Mind & Brain Theme, South Australian Health and Medical Research Institute Adelaide, South Australia, Australia
| | - Alice W Licinio
- Mind & Brain Theme, South Australian Health and Medical Research Institute Adelaide, South Australia, Australia
| | - Chenglong Yu
- Mind & Brain Theme, South Australian Health and Medical Research Institute Adelaide, South Australia, Australia; Department of Psychiatry, Flinders University College of Medicine and Public Health, Bedford Park, South Australia, Australia
| | - Eunice W M Chin
- Department of Psychiatry and Behavioral Sciences, State University of New York, Upstate Medical University, Syracuse, NY, USA
| | - Wei-Dong Yao
- Department of Psychiatry and Behavioral Sciences, State University of New York, Upstate Medical University, Syracuse, NY, USA; Department of Neuroscience and Physiology, State University of New York, Upstate Medical University, Syracuse, NY, USA
| | - Xin-Yun Lu
- Department of Neuroscience & Regenerative Medicine, Medical College of Georgia at Augusta University, Augusta, GA, USA
| | - Stefan R Bornstein
- Medical Clinic III, Carl Gustav Carus University Hospital, Dresden University of Technology, Dresden, Germany
| | - Julio Licinio
- Department of Psychiatry and Behavioral Sciences, State University of New York, Upstate Medical University, Syracuse, NY, USA; Department of Neuroscience and Physiology, State University of New York, Upstate Medical University, Syracuse, NY, USA; Mind & Brain Theme, South Australian Health and Medical Research Institute Adelaide, South Australia, Australia; Department of Psychiatry, Flinders University College of Medicine and Public Health, Bedford Park, South Australia, Australia.
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