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Integrative Personal Omics Profiles during Periods of Weight Gain and Loss.
Piening, Brian D; Zhou, Wenyu; Contrepois, Kévin; Röst, Hannes; Gu Urban, Gucci Jijuan; Mishra, Tejaswini; Hanson, Blake M; Bautista, Eddy J; Leopold, Shana; Yeh, Christine Y; Spakowicz, Daniel; Banerjee, Imon; Chen, Cynthia; Kukurba, Kimberly; Perelman, Dalia; Craig, Colleen; Colbert, Elizabeth; Salins, Denis; Rego, Shannon; Lee, Sunjae; Zhang, Cheng; Wheeler, Jessica; Sailani, M Reza; Liang, Liang; Abbott, Charles; Gerstein, Mark; Mardinoglu, Adil; Smith, Ulf; Rubin, Daniel L; Pitteri, Sharon; Sodergren, Erica; McLaughlin, Tracey L; Weinstock, George M; Snyder, Michael P.
Afiliación
  • Piening BD; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Zhou W; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Contrepois K; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Röst H; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Gu Urban GJ; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Immunology Genetics and Pathology, Uppsala University, Uppsala, Sweden.
  • Mishra T; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Hanson BM; The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
  • Bautista EJ; The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
  • Leopold S; The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
  • Yeh CY; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305, USA; Canary Center at Stanford, Stanford University School of Medicine, Stanford, CA 94305, USA; Biomedical Informatics Progra
  • Spakowicz D; The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
  • Banerjee I; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Chen C; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Kukurba K; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Perelman D; Division of Endocrinology, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Craig C; Division of Endocrinology, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Colbert E; Division of Endocrinology, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Salins D; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Rego S; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Lee S; Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.
  • Zhang C; Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.
  • Wheeler J; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Sailani MR; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Liang L; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Abbott C; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Gerstein M; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA; Department of Computer Science, Yale University, New Haven, CT, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
  • Mardinoglu A; Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden; Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
  • Smith U; Department of Molecular and Clinical Medicine, University of Gothenburg, Gothenburg, Sweden.
  • Rubin DL; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Pitteri S; Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305, USA; Canary Center at Stanford, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Sodergren E; The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
  • McLaughlin TL; Division of Endocrinology, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address: tmclaugh@stanford.edu.
  • Weinstock GM; The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA. Electronic address: george.weinstock@jax.org.
  • Snyder MP; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address: mpsnyder@stanford.edu.
Cell Syst ; 6(2): 157-170.e8, 2018 Feb 28.
Article en En | MEDLINE | ID: mdl-29361466
ABSTRACT
Advances in omics technologies now allow an unprecedented level of phenotyping for human diseases, including obesity, in which individual responses to excess weight are heterogeneous and unpredictable. To aid the development of better understanding of these phenotypes, we performed a controlled longitudinal weight perturbation study combining multiple omics strategies (genomics, transcriptomics, multiple proteomics assays, metabolomics, and microbiomics) during periods of weight gain and loss in humans. Results demonstrated that (1) weight gain is associated with the activation of strong inflammatory and hypertrophic cardiomyopathy signatures in blood; (2) although weight loss reverses some changes, a number of signatures persist, indicative of long-term physiologic changes; (3) we observed omics signatures associated with insulin resistance that may serve as novel diagnostics; (4) specific biomolecules were highly individualized and stable in response to perturbations, potentially representing stable personalized markers. Most data are available open access and serve as a valuable resource for the community.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aumento de Peso / Pérdida de Peso / Medicina de Precisión Tipo de estudio: Prognostic_studies Límite: Adult / Humans / Male Idioma: En Revista: Cell Syst Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aumento de Peso / Pérdida de Peso / Medicina de Precisión Tipo de estudio: Prognostic_studies Límite: Adult / Humans / Male Idioma: En Revista: Cell Syst Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos