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Austin TR, Fink HA, Jalal DI, Törnqvist AE, Buzkova P, Barzilay JI, Lu T, Carbone L, Gabrielsen ME, Grahnemo L, Hveem K, Jonasson C, Kizer JR, Langhammer A, Mukamal KJ, Gerszten RE, Nethander M, Psaty BM, Robbins JA, Sun YV, Heidi Skogholt A, Åsvold BO, Valderrabano RJ, Zheng J, Brent Richards J, Coward E, Ohlsson C. Large-scale circulating proteome association study (CPAS) meta-analysis identifies circulating proteins and pathways predicting incident hip fractures. J Bone Miner Res 2024; 39:139-149. [PMID: 38477735 PMCID: PMC11070286 DOI: 10.1093/jbmr/zjad011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 11/09/2023] [Accepted: 11/23/2023] [Indexed: 03/14/2024]
Abstract
Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. In an exploratory search of the underlying biology as reflected through the circulating proteome, we performed a comprehensive Circulating Proteome Association Study (CPAS) meta-analysis for incident hip fractures. Analyses included 6430 subjects from two prospective cohort studies (Cardiovascular Health Study and Trøndelag Health Study) with circulating proteomics data (aptamer-based 5 K SomaScan version 4.0 assay; 4979 aptamers). Associations between circulating protein levels and incident hip fractures were estimated for each cohort using age and sex-adjusted Cox regression models. Participants experienced 643 incident hip fractures. Compared with the individual studies, inverse-variance weighted meta-analyses yielded more statistically significant associations, identifying 23 aptamers associated with incident hip fractures (conservative Bonferroni correction 0.05/4979, P < 1.0 × 10-5). The aptamers most strongly associated with hip fracture risk corresponded to two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR. High levels of several inflammation-related proteins (CD14, CXCL12, MMP12, ITIH3) were also associated with increased hip fracture risk. Ingenuity pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. These analyses identified several circulating proteins and pathways consistently associated with incident hip fractures. These findings underscore the usefulness of the meta-analytic approach for comprehensive CPAS in a similar manner as has previously been observed for large-scale human genetic studies. Future studies should investigate the underlying biology of these potential novel drug targets.
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Affiliation(s)
- Thomas R. Austin
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98195, United States
| | - Howard A. Fink
- Geriatric Research Education and Clinical Center, VA Health Care System, Minneapolis, MN, 56401, United States
| | - Diana I. Jalal
- Division of Nephrology, Department of Internal Medicine, Carver College of Medicine, Iowa City, IA, 52242, United States
- Iowa City VA Medical Center, Iowa City, IA, 52246, United States
| | - Anna E. Törnqvist
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
| | - Petra Buzkova
- Department of Biostatistics, University of Washington, Seattle, WA, 98115, United States
| | - Joshua I. Barzilay
- Division of Endocrinology, Kaiser Permanente of Georgia, Atlanta, GA, 30339, United States
| | - Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, H3T 1E2, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec, H3G 0B1, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, H3Y 2W4, Canada
| | - Laura Carbone
- Charlie Norwood VAMC, Augusta, GA, 30901, United States
- Department of Medicine, Medical College of Georgia, Augusta University, Augusta, GA, 30912, United States
| | - Maiken E. Gabrielsen
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Louise Grahnemo
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
| | - Kristian Hveem
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
- HUNT Research Centre, NTNU, 7600, Levanger, Norway
| | - Christian Jonasson
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Jorge R. Kizer
- Cardiology Section, San Francisco VA Health Care System, San Francisco, CA, 94121, United States
- Department of Medicine, Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, 94158, United States
| | - Arnulf Langhammer
- HUNT Research Centre, NTNU, 7600, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, 7600, Levanger, Norway
| | - Kenneth J. Mukamal
- Department of Medicine, Beth Israel Deaconess Medical Center, Brookline, MA, 2446, United States
| | - Robert E. Gerszten
- Department of Medicine, Beth Israel Deaconess Medical Center, Brookline, MA, 2446, United States
| | - Maria Nethander
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
- Bioinformatics and Data Center, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98195, United States
- Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, 98195, United States
| | - John A. Robbins
- Department of Medicine, University of California, Davis, CA, 95817, United States
| | - Yan V. Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, United States
| | - Anne Heidi Skogholt
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Bjørn Olav Åsvold
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, 7491, Trondheim, Norway
| | - Rodrigo J. Valderrabano
- Research Program in Men’s Health, Aging and Metabolism, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, 2130, United States
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai Jiao Tong University School of Medicine, Ruijin Hospital, Shanghai, 200025, China
- Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai National Clinical Research Center for Metabolic Diseases, Shanghai Digital Medicine Innovation Center, Shanghai Jiao Tong University School of Medicine, Ruijin Hospital, Shanghai, 200025, China
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Bristol, BS8 2BN, United Kingdom
| | - J. Brent Richards
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, H3T 1E2, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, H3Y 2W4, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
- Department of Medicine, McGill University, Montreal, Quebec, H4A 3J1, Canada
- Department of Twin Research, King’s College London, London, SE1 7EH, United Kingdom
| | - Eivind Coward
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
- Department of Drug Treatment, Region Västra Götaland, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden
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2
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Nethander M, Movérare-Skrtic S, Kämpe A, Coward E, Reimann E, Grahnemo L, Borbély É, Helyes Z, Funck-Brentano T, Cohen-Solal M, Tuukkanen J, Koskela A, Wu J, Li L, Lu T, Gabrielsen ME, Mägi R, Hoff M, Lerner UH, Henning P, Ullum H, Erikstrup C, Brunak S, Langhammer A, Tuomi T, Oddsson A, Stefansson K, Pettersson-Kymmer U, Ostrowski SR, Pedersen OBV, Styrkarsdottir U, Mäkitie O, Hveem K, Richards JB, Ohlsson C. An atlas of genetic determinants of forearm fracture. Nat Genet 2023; 55:1820-1830. [PMID: 37919453 PMCID: PMC10632131 DOI: 10.1038/s41588-023-01527-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 09/13/2023] [Indexed: 11/04/2023]
Abstract
Osteoporotic fracture is among the most common and costly of diseases. While reasonably heritable, its genetic determinants have remained elusive. Forearm fractures are the most common clinically recognized osteoporotic fractures with a relatively high heritability. To establish an atlas of the genetic determinants of forearm fractures, we performed genome-wide association analyses including 100,026 forearm fracture cases. We identified 43 loci, including 26 new fracture loci. Although most fracture loci associated with bone mineral density, we also identified loci that primarily regulate bone quality parameters. Functional studies of one such locus, at TAC4, revealed that Tac4-/- mice have reduced mechanical bone strength. The strongest forearm fracture signal, at WNT16, displayed remarkable bone-site-specificity with no association with hip fractures. Tall stature and low body mass index were identified as new causal risk factors for fractures. The insights from this atlas may improve fracture prediction and enable therapeutic development to prevent fractures.
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Grants
- Wellcome Trust
- IngaBritt och Arne Lundbergs Forskningsstiftelse (Ingabritt and Arne Lundberg Research Foundation)
- Novo Nordisk Fonden (Novo Nordisk Foundation)
- Knut och Alice Wallenbergs Stiftelse (Knut and Alice Wallenberg Foundation)
- the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALFGBG-720331 and ALFGBG-965235)
- the Hungarian Brain research Program 3.0, Hungarian National Research, Development and Innovation Office (OTKA K- 138046, OTKA FK-137951, TKP2021-EGA-16), New National Excellence Program of the Ministry for Innovation and Technology (ÚNKP-22-5-PTE-1447), János Bolyai János Scholarship (BO/00496/21/5) of the Hungarian Academy of Sciences, Eotvos Lorad Research Network, National Laboratory for Drug Research and Development.
- Vetenskapsrådet (Swedish Research Council)
- Svenska Läkaresällskapet (Swedish Society of Medicine)
- Kempestiftelserna (Kempe Foundations)
- the Swedish Sports Research Council (87/06) the Medical Faculty of Umeå University (ALFVLL:968:22-2005, ALFVLL: 937-2006, ALFVLL:223:11-2007, ALFVLL:78151-2009) the county council of Västerbotten (Spjutspetsanslag VLL:159:33-2007)
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Affiliation(s)
- Maria Nethander
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sofia Movérare-Skrtic
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anders Kämpe
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Eivind Coward
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ene Reimann
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Louise Grahnemo
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Éva Borbély
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Pécs, Hungary
- National Laboratory for Drug Research and Development, Budapest, Hungary
| | - Zsuzsanna Helyes
- Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Pécs, Hungary
- National Laboratory for Drug Research and Development, Budapest, Hungary
- Eotvos Lorand Research Network, Chronic Pain Research Group, University of Pécs, Pécs, Hungary
| | - Thomas Funck-Brentano
- BIOSCAR UMRS 1132, Université Paris Diderot, Sorbonne Paris Cité, INSERM, Paris, France
| | - Martine Cohen-Solal
- BIOSCAR UMRS 1132, Université Paris Diderot, Sorbonne Paris Cité, INSERM, Paris, France
| | - Juha Tuukkanen
- Department of Anatomy and Cell Biology, Faculty of Medicine, Institute of Cancer Research and Translational Medicine, University of Oulu, Oulu, Finland
| | - Antti Koskela
- Department of Anatomy and Cell Biology, Faculty of Medicine, Institute of Cancer Research and Translational Medicine, University of Oulu, Oulu, Finland
| | - Jianyao Wu
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Lei Li
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
| | - Maiken E Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Mari Hoff
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Rheumatology, St Olavs Hospital, Trondheim, Norway
| | - Ulf H Lerner
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Petra Henning
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Endocrinology, Abdominal Center, Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | - Kari Stefansson
- deCODE genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Sisse Rye Ostrowski
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Copenhagen Hospital Biobank Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Ole Birger Vesterager Pedersen
- Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Koege, Denmark
| | | | - Outi Mäkitie
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Folkhälsan Institute of Genetics, Helsinki, Finland
- Children's Hospital and Pediatric Research Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, and Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - J Brent Richards
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Drug Treatment, Gothenburg, Sweden.
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3
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Grahnemo L, Nethander M, Coward E, Gabrielsen ME, Sree S, Billod JM, Sjögren K, Engstrand L, Dekkers KF, Fall T, Langhammer A, Hveem K, Ohlsson C. Identification of three bacterial species associated with increased appendicular lean mass: the HUNT study. Nat Commun 2023; 14:2250. [PMID: 37080991 PMCID: PMC10119287 DOI: 10.1038/s41467-023-37978-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 04/05/2023] [Indexed: 04/22/2023] Open
Abstract
Appendicular lean mass (ALM) associates with mobility and bone mineral density (BMD). While associations between gut microbiota composition and ALM have been reported, previous studies rely on relatively small sample sizes. Here, we determine the associations between prevalent gut microbes and ALM in large discovery and replication cohorts with information on relevant confounders within the population-based Norwegian HUNT cohort (n = 5196, including women and men). We show that the presence of three bacterial species - Coprococcus comes, Dorea longicatena, and Eubacterium ventriosum - are reproducibly associated with higher ALM. When combined into an anabolic species count, participants with all three anabolic species have 0.80 kg higher ALM than those without any. In an exploratory analysis, the anabolic species count is positively associated with femoral neck and total hip BMD. We conclude that the anabolic species count may be used as a marker of ALM and BMD. The therapeutic potential of these anabolic species to prevent sarcopenia and osteoporosis needs to be determined.
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Affiliation(s)
- Louise Grahnemo
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
| | - Maria Nethander
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Eivind Coward
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Maiken Elvestad Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Satya Sree
- Bio-Me, Oslo Science Park, Gaustadalléen 21, N-0349, Oslo, Norway
| | - Jean-Marc Billod
- Bio-Me, Oslo Science Park, Gaustadalléen 21, N-0349, Oslo, Norway
| | - Klara Sjögren
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Lars Engstrand
- Department of Microbiology, Tumor and Cell Biology, Centre for Translational Microbiome Research, Karolinska Institutet, Karolinska Hospital, Biomedicum A8, Solnavägen 9, 171 65, Stockholm, Sweden
| | - Koen F Dekkers
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Tove Fall
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Drug Treatment, Gothenburg, Sweden
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4
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Lawenius L, Cowardin C, Grahnemo L, Scheffler JM, Horkeby K, Engdahl C, Wu J, Vandenput L, Koskela A, Tukkanen J, Coward E, Hveem K, Langhammer A, Abrahamsson S, Gordon JI, Sjögren K, Ohlsson C. Transplantation of gut microbiota from old mice into young healthy mice reduces lean mass but not bone mass. Gut Microbes 2023; 15:2236755. [PMID: 37475479 PMCID: PMC10364652 DOI: 10.1080/19490976.2023.2236755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 06/27/2023] [Accepted: 07/10/2023] [Indexed: 07/22/2023] Open
Abstract
Aging is associated with low bone and lean mass as well as alterations in the gut microbiota (GM). In this study, we determined whether the reduced bone mass and relative lean mass observed in old mice could be transferred to healthy young mice by GM transplantation (GMT). GM from old (21-month-old) and young adult (5-month-old) donors was used to colonize germ-free (GF) mice in three separate studies involving still growing 5- or 11-week-old recipients and 17-week-old recipients with minimal bone growth. The GM of the recipient mice was similar to that of the donors, demonstrating successful GMT. GM from old mice did not have statistically significant effects on bone mass or bone strength, but significantly reduced the lean mass percentage of still growing recipient mice when compared with recipients of GM from young adult mice. The levels of propionate in the cecum of mice receiving old donor GM were significantly lower than those in mice receiving young adult donor GM. Bacteroides ovatus was enriched in the microbiota of recipient mice harboring GM from young adult donors. The presence of B. ovatus was not only significantly associated with high lean mass percentage in mice, but also with lean mass adjusted for fat mass in the large human HUNT cohort. In conclusion, GM from old mice reduces lean mass percentage but not bone mass in young, healthy, still growing recipient mice. Future studies are warranted to determine whether GM from young mice improves the musculoskeletal phenotype of frail elderly recipient mice.
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Affiliation(s)
- Lina Lawenius
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Carrie Cowardin
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis, St. Louis, MO, USA
| | - Louise Grahnemo
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Julia M. Scheffler
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Rheumatology and Inflammation Research, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, Sahlgrenska Academy University of Gothenburg, Gothenburg, Sweden
| | - Karin Horkeby
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Cecilia Engdahl
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Rheumatology and Inflammation Research, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, Sahlgrenska Academy University of Gothenburg, Gothenburg, Sweden
| | - Jianyao Wu
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Liesbeth Vandenput
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Antti Koskela
- Department of Anatomy and Cell Biology, Faculty of Medicine, Institute of Cancer Research and Translational Medicine, University of Oulu, Oulu, Finland
| | - Juha Tukkanen
- Department of Anatomy and Cell Biology, Faculty of Medicine, Institute of Cancer Research and Translational Medicine, University of Oulu, Oulu, Finland
| | - Eivind Coward
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Sanna Abrahamsson
- Bioinformatics and Data Centre, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Jeffrey I. Gordon
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis, St. Louis, MO, USA
| | - Klara Sjögren
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Drug Treatment, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
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Giliberto M, Santana LM, Holien T, Misund K, Nakken S, Vodak D, Hovig E, Meza-Zepeda LA, Coward E, Waage A, Taskén K, Skånland SS. Mutational analysis and protein profiling predict drug sensitivity in multiple myeloma cell lines. Front Oncol 2022; 12:1040730. [PMID: 36523963 PMCID: PMC9745900 DOI: 10.3389/fonc.2022.1040730] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 10/31/2022] [Indexed: 12/03/2023] Open
Abstract
INTRODUCTION Multiple myeloma (MM) is a heterogeneous disease where cancer-driver mutations and aberrant signaling may lead to disease progression and drug resistance. Drug responses vary greatly, and there is an unmet need for biomarkers that can guide precision cancer medicine in this disease. METHODS To identify potential predictors of drug sensitivity, we applied integrated data from drug sensitivity screening, mutational analysis and functional signaling pathway profiling in 9 cell line models of MM. We studied the sensitivity to 33 targeted drugs and their association with the mutational status of cancer-driver genes and activity level of signaling proteins. RESULTS We found that sensitivity to mitogen-activated protein kinase kinase 1 (MEK1) and phosphatidylinositol-3 kinase (PI3K) inhibitors correlated with mutations in NRAS/KRAS, and PI3K family genes, respectively. Phosphorylation status of MEK1 and protein kinase B (AKT) correlated with sensitivity to MEK and PI3K inhibition, respectively. In addition, we found that enhanced phosphorylation of proteins, including Tank-binding kinase 1 (TBK1), as well as high expression of B cell lymphoma 2 (Bcl-2), correlated with low sensitivity to MEK inhibitors. DISCUSSION Taken together, this study shows that mutational status and signaling protein profiling might be used in further studies to predict drug sensitivities and identify resistance markers in MM.
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Affiliation(s)
- Mariaserena Giliberto
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Leonardo Miranda Santana
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Oslo Centre for Biostatistics and Epidemiology, University of Oslo, Oslo, Norway
| | - Toril Holien
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Hematology, St. Olav’s University Hospital, Trondheim, Norway
- Department of Immunology and Transfusion Medicine, St. Olav’s University Hospital, Trondheim, Norway
| | - Kristine Misund
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Sigve Nakken
- Norwegian Cancer Genomics Consortium, Oslo University Hospital, Oslo, Norway
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Daniel Vodak
- Norwegian Cancer Genomics Consortium, Oslo University Hospital, Oslo, Norway
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Genomics Core Facility, Department of Core Facilities, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Eivind Hovig
- Norwegian Cancer Genomics Consortium, Oslo University Hospital, Oslo, Norway
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Leonardo A. Meza-Zepeda
- Norwegian Cancer Genomics Consortium, Oslo University Hospital, Oslo, Norway
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Genomics Core Facility, Department of Core Facilities, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Eivind Coward
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anders Waage
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Hematology, St. Olav’s University Hospital, Trondheim, Norway
- Department of Immunology and Transfusion Medicine, St. Olav’s University Hospital, Trondheim, Norway
| | - Kjetil Taskén
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Sigrid S. Skånland
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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6
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Nethander M, Coward E, Reimann E, Grahnemo L, Gabrielsen ME, Wibom C, Mägi R, Funck-Brentano T, Hoff M, Langhammer A, Pettersson-Kymmer U, Hveem K, Ohlsson C. Assessment of the genetic and clinical determinants of hip fracture risk: Genome-wide association and Mendelian randomization study. Cell Rep Med 2022; 3:100776. [PMID: 36260985 PMCID: PMC9589021 DOI: 10.1016/j.xcrm.2022.100776] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 06/07/2022] [Accepted: 09/19/2022] [Indexed: 11/05/2022]
Abstract
Hip fracture is the clinically most important fracture, but the genetic architecture of hip fracture is unclear. Here, we perform a large-scale hip fracture genome-wide association study meta-analysis and Mendelian randomization study using five cohorts from European biobanks. The results show that five genetic signals associate with hip fractures. Among these, one signal associates with falls, but not with bone mineral density (BMD), while four signals are in loci known to be involved in bone biology. Mendelian randomization analyses demonstrate a strong causal effect of decreased femoral neck BMD and moderate causal effects of Alzheimer's disease and having ever smoked regularly on risk of hip fractures. The substantial causal effect of decreased femoral neck BMD on hip fractures in both young and old subjects and in both men and women supports the use of change in femoral neck BMD as a surrogate outcome for hip fractures in clinical trials.
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Affiliation(s)
- Maria Nethander
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Vita Stråket 11, 41345 Gothenburg, Sweden; Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Eivind Coward
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Ene Reimann
- Estonian Genome Center, Institute of Genomics, University of Tartu, Riia 23b, 51010 Tartu, Estonia
| | - Louise Grahnemo
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Vita Stråket 11, 41345 Gothenburg, Sweden
| | - Maiken E Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Carl Wibom
- Department of Radiation Sciences, Oncology, Umea University, Umea, Sweden
| | | | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Riia 23b, 51010 Tartu, Estonia
| | - Thomas Funck-Brentano
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Vita Stråket 11, 41345 Gothenburg, Sweden; Department of Rheumatology, Lariboisière Hospital, INSERM U1132, Université de Paris, Paris, France
| | - Mari Hoff
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway; Department of Rheumatology, St Olavs Hospital, Trondheim, Norway
| | - Arnulf Langhammer
- HUNT Research Centre, Forskningsveien 2, 7600 Levanger, Norway"; Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | | | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7491 Trondheim, Norway; HUNT Research Centre, Forskningsveien 2, 7600 Levanger, Norway"; Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Vita Stråket 11, 41345 Gothenburg, Sweden; Region Västra Götaland, Department of Drug Treatment, Sahlgrenska University Hospital, Gothenburg, Sweden.
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7
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Grahnemo L, Nethander M, Coward E, Gabrielsen ME, Sree S, Billod JM, Engstrand L, Abrahamsson S, Langhammer A, Hveem K, Ohlsson C. Cross-sectional associations between the gut microbe Ruminococcus gnavus and features of the metabolic syndrome. Lancet Diabetes Endocrinol 2022; 10:481-483. [PMID: 35662399 DOI: 10.1016/s2213-8587(22)00113-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 03/25/2022] [Accepted: 03/31/2022] [Indexed: 12/19/2022]
Affiliation(s)
- Louise Grahnemo
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research, Sahlgrenska Academy, University of Gothenburg, Gothenburg 413 45, Sweden
| | - Maria Nethander
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research, Sahlgrenska Academy, University of Gothenburg, Gothenburg 413 45, Sweden; Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg 413 45, Sweden
| | - Eivind Coward
- KG Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Maiken Elvestad Gabrielsen
- KG Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Lars Engstrand
- Department of Microbiology, Tumor and Cell Biology, Centre for Translational Microbiome Research, Karolinska Institutet, Karolinska Hospital, Biomedicum A8, Stockholm, Sweden
| | - Sanna Abrahamsson
- Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg 413 45, Sweden
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway; Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Kristian Hveem
- KG Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway; HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway; Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research, Sahlgrenska Academy, University of Gothenburg, Gothenburg 413 45, Sweden; Department of Drug Treatment, Sahlgrenska University Hospital, Gothenburg, Sweden.
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8
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Grahnemo L, Nethander M, Coward E, Gabrielsen ME, Langhammer A, Hveem K, Ohlsson C. Identification of three bacteria species associated with increased lean mass – The HUNT study. Bone Rep 2022. [DOI: 10.1016/j.bonr.2022.101202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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9
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Rustad EH, Misund K, Bernard E, Coward E, Yellapantula VD, Hultcrantz M, Ho C, Kazandjian D, Korde N, Mailankody S, Keats JJ, Akhlaghi T, Viny AD, Mayman DJ, Carroll K, Patel M, Famulare CA, Bruinink DH, Hutt K, Jacobsen A, Huang Y, Miller JE, Maura F, Papaemmanuil E, Waage A, Arcila ME, Landgren O. Stability and uniqueness of clonal immunoglobulin CDR3 sequences for MRD tracking in multiple myeloma. Am J Hematol 2019; 94:1364-1373. [PMID: 31571261 DOI: 10.1002/ajh.25641] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 09/12/2019] [Accepted: 09/16/2019] [Indexed: 12/26/2022]
Abstract
Minimal residual disease (MRD) tracking, by next generation sequencing of immunoglobulin sequences, is moving towards clinical implementation in multiple myeloma. However, there is only sparse information available to address whether clonal sequences remain stable for tracking over time, and to what extent light chain sequences are sufficiently unique for tracking. Here, we analyzed immunoglobulin repertoires from 905 plasma cell myeloma and healthy control samples, focusing on the third complementarity determining region (CDR3). Clonal heavy and/or light chain expression was identified in all patients at baseline, with one or more subclones related to the main clone in 3.2%. In 45 patients with 101 sequential samples, the dominant clonal CDR3 sequences remained identical over time, despite differential clonal evolution by whole exome sequencing in 49% of patients. The low frequency of subclonal CDR3 variants, and absence of evolution over time in active multiple myeloma, indicates that tumor cells at this stage are not under selective pressure to undergo antibody affinity maturation. Next, we establish somatic hypermutation and non-templated insertions as the most important determinants of light chain clonal uniqueness, identifying a potentially trackable sequence in the majority of patients. Taken together, we show that dominant clonal sequences identified at baseline are reliable biomarkers for long-term tracking of the malignant clone, including both IGH and the majority of light chain clones.
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Affiliation(s)
- Even H. Rustad
- Department of Medicine, Myeloma Service Memorial Sloan Kettering Cancer Center New York New York
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway
| | - Kristine Misund
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway
| | - Elsa Bernard
- Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York New York
| | - Eivind Coward
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway
| | - Venkata D. Yellapantula
- Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York New York
| | - Malin Hultcrantz
- Department of Medicine, Myeloma Service Memorial Sloan Kettering Cancer Center New York New York
| | - Caleb Ho
- Department of Pathology Memorial Sloan Kettering Cancer Center New York New York
| | - Dickran Kazandjian
- Myeloma Program, Lymphoid Malignancies Branch, Center for Cancer Research National Cancer Institute, National Institutes of Health Bethesda Maryland
| | - Neha Korde
- Department of Medicine, Myeloma Service Memorial Sloan Kettering Cancer Center New York New York
| | - Sham Mailankody
- Department of Medicine, Myeloma Service Memorial Sloan Kettering Cancer Center New York New York
| | | | - Theresia Akhlaghi
- Department of Medicine, Myeloma Service Memorial Sloan Kettering Cancer Center New York New York
| | - Aaron D. Viny
- Department of Medicine, Leukemia Service Memorial Sloan Kettering Cancer Center New York New York
- Human Oncology & Pathogenesis Program Memorial Sloan Kettering Cancer Center New York New York
| | - David J. Mayman
- Adult Reconstruction and Joint Replacement Division Hospital for Special Surgery New York New York
| | - Kaitlin Carroll
- Adult Reconstruction and Joint Replacement Division Hospital for Special Surgery New York New York
| | - Minal Patel
- Center for Hematological Malignancies, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York
| | - Christopher A. Famulare
- Center for Hematological Malignancies, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York
| | | | | | | | | | | | - Francesco Maura
- Department of Medicine, Myeloma Service Memorial Sloan Kettering Cancer Center New York New York
| | - Elli Papaemmanuil
- Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York New York
| | - Anders Waage
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway
| | - Maria E. Arcila
- Department of Pathology Memorial Sloan Kettering Cancer Center New York New York
| | - Ola Landgren
- Department of Medicine, Myeloma Service Memorial Sloan Kettering Cancer Center New York New York
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10
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Hardaker K, Panda H, Hulme K, Wong A, Coward E, Cooper P, Fitzgerald D, Pandit C, Towns S, Selvadurai H, Robinson P. Abnormal preschool Lung Clearance Index (LCI) reflects clinical status and predicts lower spirometry later in childhood in cystic fibrosis. J Cyst Fibros 2019; 18:721-727. [DOI: 10.1016/j.jcf.2019.02.007] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Revised: 02/11/2019] [Accepted: 02/12/2019] [Indexed: 11/26/2022]
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11
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Rustad EH, Coward E, Skytøen ER, Misund K, Holien T, Standal T, Børset M, Beisvag V, Myklebost O, Meza-Zepeda LA, Dai HY, Sundan A, Waage A. Monitoring multiple myeloma by quantification of recurrent mutations in serum. Haematologica 2017; 102:1266-1272. [PMID: 28385781 PMCID: PMC5566041 DOI: 10.3324/haematol.2016.160564] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 03/31/2017] [Indexed: 01/28/2023] Open
Abstract
Circulating tumor DNA is a promising biomarker to monitor tumor load and genome alterations. We explored the presence of circulating tumor DNA in multiple myeloma patients and its relation to disease activity during long-term follow-up. We used digital droplet polymerase chain reaction analysis to monitor recurrent mutations, mainly in mitogen activated protein kinase pathway genes NRAS, KRAS and BRAF. Mutations were identified by next-generation sequencing or polymerase chain reaction analysis of bone marrow plasma cells, and their presence analyzed in 251 archived serum samples obtained from 20 patients during a period of up to 7 years. In 17 of 18 patients, mutations identified in bone marrow during active disease were also found in a time-matched serum sample. The concentration of mutated alleles in serum correlated with the fraction in bone marrow plasma cells (r=0.507, n=34, P<0.002). There was a striking covariation between circulating mutation levels and M protein in ten out of 11 patients with sequential samples. When relapse evaluation by circulating tumor DNA and M protein could be directly compared, the circulating tumor DNA showed relapse earlier in two patients (3 and 9 months), later in one patient (4 months) and in three patients there was no difference. In three patients with transformation to aggressive disease, the concentrations of mutations in serum increased up to 400 times, an increase that was not seen for the M protein. In conclusion, circulating tumor DNA in myeloma is a multi-faceted biomarker reflecting mutated cells, total tumor mass and transformation to a more aggressive disease. Its properties are both similar and complementary to M protein.
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Affiliation(s)
- Even Holth Rustad
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Eivind Coward
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,Norwegian Cancer Genomics Consortium, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Emilie R Skytøen
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Kristine Misund
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Toril Holien
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Therese Standal
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,CEMIR - Center for Molecular Inflammation Research, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Magne Børset
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Vidar Beisvag
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Ola Myklebost
- Norwegian Cancer Genomics Consortium, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,Institute for Clinical Science, University of Bergen, Trondheim, Norway.,Institute for Cancer Research, Oslo University Hospital, Trondheim, Norway
| | - Leonardo A Meza-Zepeda
- Norwegian Cancer Genomics Consortium, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,Institute for Cancer Research, Oslo University Hospital, Trondheim, Norway
| | - Hong Yan Dai
- Department of Pathology and Medical Genetics, St. Olav's University Hospital, Trondheim, Norway
| | - Anders Sundan
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,CEMIR - Center for Molecular Inflammation Research, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Anders Waage
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway .,Norwegian Cancer Genomics Consortium, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,Department of Hematology, St. Olav's University Hospital, Trondheim, Norway
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12
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Våtsveen TK, Børset M, Dikic A, Tian E, Micci F, Lid AHB, Meza-Zepeda LA, Coward E, Waage A, Sundan A, Kuehl WM, Holien T. VOLIN and KJON-Two novel hyperdiploid myeloma cell lines. Genes Chromosomes Cancer 2016; 55:890-901. [PMID: 27311012 DOI: 10.1002/gcc.22388] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Accepted: 06/12/2016] [Indexed: 12/21/2022] Open
Abstract
Multiple myeloma can be divided into two distinct genetic subgroups: hyperdiploid (HRD) or nonhyperdiploid (NHRD) myeloma. Myeloma cell lines are important tools to study myeloma cell biology and are commonly used for preclinical screening and testing of new drugs. With few exceptions human myeloma cell lines are derived from NHRD patients, even though about half of the patients have HRD myeloma. Thus, there is a need for cell lines of HRD origin to enable more representative preclinical studies. Here, we present two novel myeloma cell lines, VOLIN and KJON. Both of them were derived from patients with HRD disease and shared the same genotype as their corresponding primary tumors. The cell lines' chromosomal content, genetic aberrations, gene expression, immunophenotype as well as some of their growth characteristics are described. Neither of the cell lines was found to harbor immunoglobulin heavy chain translocations. The VOLIN cell line was established from a bone marrow aspirate and KJON from peripheral blood. We propose that these unique cell lines may be used as tools to increase our understanding of myeloma cell biology. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Thea Kristin Våtsveen
- K.G. Jebsen Center for Myeloma Research, Department of Cancer Research and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.,Department of Pathology and Medical Genetics, St. Olav's University Hospital, Trondheim, Norway
| | - Magne Børset
- K.G. Jebsen Center for Myeloma Research, Department of Cancer Research and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.,Department of Immunology and Transfusion Medicine, St. Olav's University Hospital, Trondheim, Norway
| | - Aida Dikic
- K.G. Jebsen Center for Myeloma Research, Department of Cancer Research and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Erming Tian
- K.G. Jebsen Center for Myeloma Research, Department of Cancer Research and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | - Francesca Micci
- Section for Cancer Cytogenetics, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway
| | - Ana H B Lid
- Department of Core Facilities, Oslo University Hospital, Oslo, Norway
| | - Leonardo A Meza-Zepeda
- Department of Core Facilities, Oslo University Hospital, Oslo, Norway.,Department of Tumor Biology, Oslo University Hospital, Oslo, Norway
| | - Eivind Coward
- Bioinformatics Core Facility, Department of Cancer Research and Molecular Medicine, Faculty of Medicine, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
| | - Anders Waage
- K.G. Jebsen Center for Myeloma Research, Department of Cancer Research and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.,Department of Hematology, St. Olav's University Hospital, Trondheim, Norway
| | - Anders Sundan
- K.G. Jebsen Center for Myeloma Research, Department of Cancer Research and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.,Centre of Molecular Inflammation Research, NTNU-Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Toril Holien
- K.G. Jebsen Center for Myeloma Research, Department of Cancer Research and Molecular Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.
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13
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Bakke I, Coward E, Andersen T, Vadstein O. Selection in the host structures the microbiota associated with developing cod larvae (Gadus morhua). Environ Microbiol 2015; 17:3914-24. [PMID: 25923170 DOI: 10.1111/1462-2920.12888] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Revised: 04/22/2015] [Accepted: 04/22/2015] [Indexed: 01/11/2023]
Abstract
Marine fish larvae are immature upon hatching, and share their environment with high numbers of bacteria. The microbial communities associated with developing fish larvae might be structured by other factors than those important in developing terrestrial animals. Here, we analysed the beta (β)-diversity of the microbiota associated with developing cod larvae and compared it with the bacterial communities in water and live feed by applying pyrosequencing of bar coded v4 16S rDNA amplicons. A total of 15 phyla were observed in the cod larval microbiota. Proteobacteria was the most abundant, followed by Firmicutes, Bacteroidetes and Actinobacteria. The composition and diversity of the cod larval microbiota changed considerably with age. The temporal and spatial patterns of β-diversity could not be explained by stochastic processes, and did not coincide with changes in the rearing conditions. Furthermore, the larval microbiota was highly distinct from the water and the live feed microbiota, particularly at early developmental stages. However, the similarity between larval and water microbiota increased with age. This study suggests that strong selection in the host structures the cod larval microbiota. The changes in community structure observed with increasing age can be explained by altered selection pressure due to development of the intestinal system.
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Affiliation(s)
- Ingrid Bakke
- Department of Biotechnology, Faculty of Natural Sciences and Technology, NTNU Norwegian University of Science and Technology, Sem Saelands v. 6/8, N-7491, Trondheim, Norway.,NTNU Centre of Fisheries and Aquaculture, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Eivind Coward
- Department of Cancer Research and Molecular Medicine, Faculty of Medicine, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Tom Andersen
- Department of Bioscience, University of Oslo, Box 1066 Blindern, Oslo, 0316, Norway
| | - Olav Vadstein
- Department of Biotechnology, Faculty of Natural Sciences and Technology, NTNU Norwegian University of Science and Technology, Sem Saelands v. 6/8, N-7491, Trondheim, Norway.,NTNU Centre of Fisheries and Aquaculture, NTNU Norwegian University of Science and Technology, Trondheim, Norway
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Bakke I, Skjermo J, Attramadal K, Coward E, Kjørsvik E, Vo TA, Olsen Y, Vadstein O. Bacterial community assembly in developing cod larvae (Gadus morhua). Commun Agric Appl Biol Sci 2013; 78:23-24. [PMID: 25141610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
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15
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Lyon AR, Bannister ML, Coward E, Dubb SS, Garcia E, Kohlbrenner E, Hajjar RJ, Harding SE, Macleod KM. 011 Stabilisation of SR leak in heart failure after SERCA2A gene therapy. Heart 2010. [DOI: 10.1136/hrt.2010.195941.11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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16
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Gilson N, Coward E, Brown W, McKenn J. Physical infra-structure and workplace walking in an Australian university campus. J Sci Med Sport 2009. [DOI: 10.1016/j.jsams.2008.12.172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Abstract
MOTIVATION Repeat sequences in ESTs are a source of problems, in particular for clustering. ESTs are therefore commonly masked against a library of known repeats. High quality repeat libraries are available for the widely studied organisms, but for most other organisms the lack of such libraries is likely to compromise the quality of EST analysis. RESULTS We present a fast, flexible and library-less method for masking repeats in EST sequences, based on match statistics within the EST collection. The method is not linked to a particular clustering algorithm. Extensive testing on datasets using different clustering methods and a genomic mapping as reference shows that this method gives results that are better than or as good as those obtained using RepeatMasker with a repeat library. AVAILABILITY The implementation of RBR is available under the terms of the GPL from http://www.ii.uib.no/~ketil/bioinformatics CONTACT ketil.malde@bccs.uib.no SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Ketil Malde
- Computational Biology Unit, Bergen Centre for Computational Sciences, University of Bergen, Norway.
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Schneeberger K, Malde K, Coward E, Jonassen I. Masking repeats while clustering ESTs. Nucleic Acids Res 2005; 33:2176-80. [PMID: 15831790 PMCID: PMC1079970 DOI: 10.1093/nar/gki511] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2004] [Revised: 03/10/2005] [Accepted: 03/28/2005] [Indexed: 11/15/2022] Open
Abstract
A problem in EST clustering is the presence of repeat sequences. To avoid false matches, repeats have to be masked. This can be a time-consuming process, and it depends on available repeat libraries. We present a fast and effective method that aims to eliminate the problems repeats cause in the process of clustering. Unlike traditional methods, repeats are inferred directly from the EST data, we do not rely on any external library of known repeats. This makes the method especially suitable for analysing the ESTs from organisms without good repeat libraries. We demonstrate that the result is very similar to performing standard repeat masking before clustering.
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Affiliation(s)
| | - Ketil Malde
- Department of Informatics, University of BergenBergen, Norway
| | - Eivind Coward
- Department of Informatics, University of BergenBergen, Norway
| | - Inge Jonassen
- Computational Biology Unit, University of BergenBergen, Norway
- Department of Informatics, University of BergenBergen, Norway
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Abstract
MOTIVATION EST sequences constitute an abundant, yet error prone resource for computational biology. Expressed sequences are important in gene discovery and identification, and they are also crucial for the discovery and classification of alternative splicing. An important challenge when processing EST sequences is the reconstruction of mRNA by assembling EST clusters into consensus sequences. RESULTS In contrast to the more established assembly tools, we propose an algorithm that constructs a graph over sequence fragments of fixed size, and produces consensus sequences as traversals of this graph. We provide a tool implementing this algorithm, and perform an experiment where the consensus sequences produced by our implementation, as well as by currently available tools, are compared to mRNA. The results show that our proposed algorithm in a majority of the cases produces consensus of higher quality than the established sequence assemblers and at a competitive speed. AVAILABILITY The source code for the implementation is available under a GPL license from http://www.ii.uib.no/~ketil/bioinformatics/ CONTACT ketil@ii.uib.no.
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Affiliation(s)
- Ketil Malde
- Department of Informatics, University of Bergen, Norway.
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Abstract
MOTIVATION Efficient clustering is important for handling the large amount of available EST sequences. Most contemporary methods are based on some kind of all-against-all comparison, resulting in a quadratic time complexity. A different approach is needed to keep up with the rapid growth of EST data. RESULTS A new, fast EST clustering algorithm is presented. Sub-quadratic time complexity is achieved by using an algorithm based on suffix arrays. A prototype implementation has been developed and run on a benchmark data set. The produced clusterings are validated by comparing them to clusterings produced by other methods, and the results are quite promising. AVAILABILITY The source code for the prototype implementation is available under a GPL license from http://www.ii.uib.no/~ketil/bio/.
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Affiliation(s)
- Ketil Malde
- Department of Informatics, University of Bergen, HIB, N5020 Norway.
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Abstract
We have integrated the protein families from SYSTERS and the expressed sequence tag (EST) clusters from our database GeneNest with SpliceNest, a new database mapping EST contigs into genomic DNA. The SYSTERS protein sequence cluster set provides an automatically generated classification of all sequences of the SWISS-PROT, TrEMBL and PIR databases into disjoint protein family and superfamily clusters. GeneNest is a database and software package for producing and visualizing gene indices from ESTs and mRNAs. Currently, the database comprises gene indices of human, mouse, Arabidopsis thaliana and zebrafish. SpliceNest is a web-based graphical tool to explore gene structure, including alternative splicing, based on a mapping of the EST consensus sequences from GeneNest to the complete human genome. The integration of SYSTERS, GeneNest and SpliceNest into one framework now permits an overall exploration of the whole sequence space covering protein, mRNA and EST sequences, as well as genomic DNA. The databases are available for querying and browsing at http://cmb.molgen.mpg.de.
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Affiliation(s)
- Antje Krause
- Max-Planck-Institute for Molecular Genetics, Computational Molecular Biology, Ihnestrasse 73, 14195 Berlin, Germany.
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23
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Laprevotte I, Pupin M, Coward E, Didier G, Terzian C, Devauchelle C, Hénaut A. HIV-1 and HIV-2 LTR nucleotide sequences: assessment of the alignment by N-block presentation, "retroviral signatures" of overrepeated oligonucleotides, and a probable important role of scrambled stepwise duplications/deletions in molecular evolution. Mol Biol Evol 2001; 18:1231-45. [PMID: 11420363 DOI: 10.1093/oxfordjournals.molbev.a003909] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Previous analyses of retroviral nucleotide sequences, suggest a so-called "scrambled duplicative stepwise molecular evolution" (many sectors with successive duplications/deletions of short and longer motifs) that could have stemmed from one or several starter tandemly repeated short sequence(s). In the present report, we tested this hypothesis by focusing on the long terminal repeats (LTRs) (and flanking sequences) of 24 human and 3 simian immunodeficiency viruses. By using a calculation strategy applicable to short sequences, we found consensus overrepresented motifs (often containing CTG or CAG) that were congruent with the previously defined "retroviral signature." We also show many local repetition patterns that are significant when compared with simply shuffled sequences. First- and second-order Markov chain analyses demonstrate that a major portion of the overrepresented oligonucleotides can be predicted from the dinucleotide compositions of the sequences, but by no means can biological mechanisms be deduced from these results: some of the listed local repetitions remain significant against dinucleotide-conserving shuffled sequences; together with previous results, this suggests that interspersed and/or local mononucleotide and oligonucleotide repetitions could have biased the dinucleotide compositions of the sequences. We searched for suggestive evolutionary patterns by scrutinizing a reliable multiple alignment of the 27 sequences. A manually constructed alignment based on homology blocks was in good agreement with the polypeptide alignment in the coding sectors and has been exhaustively assessed by using a multiplied alphabet obtained by the promising mathematical strategy called the N-block presentation (taking into account the environment of each nucleotide in a sequence). Sector by sector, we hypothesize many successive duplication/deletion scenarios that fit our previous evolutionary hypotheses. This suggests an important duplication/deletion role for the reverse transcriptase, particularly in inducing stuttering cryptic simplicity patterns.
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Affiliation(s)
- I Laprevotte
- Laboratoire Génome et Informatique, Université de Versailles Saint Quentin-en-Yvelines, Versailles, France.
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Klaerr-Blanchard M, Chiapello H, Coward E. Detecting localized repeats in genomic sequences: a new strategy and its application to Bacillus subtilis and Arabidopsis thaliana sequences. ACTA ACUST UNITED AC 2000. [DOI: 10.1016/s0097-8485(00)80007-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Klaerr-Blanchard M, Chiapello H, Coward E. Detecting localized repeats in genomic sequences: a new strategy and its application to Bacillus subtilis and Arabidopsis thaliana sequences. Comput Chem 2000; 24:57-70. [PMID: 10642880 DOI: 10.1016/s0097-8485(99)00047-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A new method for the search of local repeats in long DNA sequences, such as complete genomes, is presented. It detects a large variety of repeats varying in length from one to several hundred bases, which may contain many mutations. By mutations we mean substitutions, insertions or deletions of one or more bases. The method is based on counting occurrences of short words (3-12 bases) in sequence fragments called windows. A score is computed for each window, based on calculating exact word occurrence probabilities for all the words of a given length in the window. The probabilities are defined using a Bernoulli model (independent letters) for the sequence, using the actual letter frequencies from each window. A plot of the probabilities along the sequence for high-scoring windows facilitates the identification of the repeated patterns. We applied the method to the 1.87 Mb sequence of chromosome 4 of Arabidopsis thaliana and to the complete genome of Bacillus subtilis (4.2 Mb). The repeats that we found were classified according to their size, number of occurrences, distance between occurrences, and location with respect to genes. The method proves particularly useful in detecting long, inexact repeats that are local, but not necessarily tandem. The method is implemented as a C program called EXCEP, which is available on request from the authors.
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Affiliation(s)
- M Klaerr-Blanchard
- Unité de Régulation de l'Expression Génétique, Institut Pasteur, Paris, France.
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Abstract
Shufflet is a program and a web-application that generates fast random shufflings of sequences (DNA, protein or others), conserving the exact k-let counts for a given k. The sequences are sampled uniformly from all the valid permutations.
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Affiliation(s)
- E Coward
- Laboratoire Génome et Informatique, Université de Versailles Saint-Quentin-en-Yvelines, France.
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Abstract
MOTIVATION The search for repeated patterns in DNA and protein sequences is important in sequence analysis. The rapid increase in available sequences, in particular from large-scale genome sequencing projects, makes it relevant to develop sensitive automatic methods for the identification of repeats. RESULTS A new method for finding periodic patterns in biological sequences is presented. The method is based on evolutionary distance and 'phase shifts' corresponding to insertions and deletions. A given sequence is aligned to itself in a certain sense, trying to minimize a distance to periodicity. Relationships between different such periodicity measures are discussed. An iterative algorithm is used, and the running time is nearly proportional to the sequence length. The alignment produces a periodic consensus pattern. A 'phase score' is used to indicate a statistical significance of the periodicity. Three examples using both DNA and protein sequences illustrate how the method can be used to find patterns. AVAILABILITY On request from the authors. CONTACT evindc@mat nu.no; finn.drablos@unimed.sintef.no
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Affiliation(s)
- E Coward
- Department of Mathematical Sciences, Norwegian University of Science and Technology, Norway.
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