1
|
Hédou J, Marić I, Bellan G, Einhaus J, Gaudillière DK, Ladant FX, Verdonk F, Stelzer IA, Feyaerts D, Tsai AS, Ganio EA, Sabayev M, Gillard J, Amar J, Cambriel A, Oskotsky TT, Roldan A, Golob JL, Sirota M, Bonham TA, Sato M, Diop M, Durand X, Angst MS, Stevenson DK, Aghaeepour N, Montanari A, Gaudillière B. Discovery of sparse, reliable omic biomarkers with Stabl. Nat Biotechnol 2024:10.1038/s41587-023-02033-x. [PMID: 38168992 PMCID: PMC11217152 DOI: 10.1038/s41587-023-02033-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 10/16/2023] [Indexed: 01/05/2024]
Abstract
Adoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facilitate this process, we introduce Stabl, a general machine learning method that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling. Evaluation of Stabl on synthetic datasets and five independent clinical studies demonstrates improved biomarker sparsity and reliability compared to commonly used sparsity-promoting regularization methods while maintaining predictive performance; it distills datasets containing 1,400-35,000 features down to 4-34 candidate biomarkers. Stabl extends to multi-omic integration tasks, enabling biological interpretation of complex predictive models, as it hones in on a shortlist of proteomic, metabolomic and cytometric events predicting labor onset, microbial biomarkers of pre-term birth and a pre-operative immune signature of post-surgical infections. Stabl is available at https://github.com/gregbellan/Stabl .
Collapse
Affiliation(s)
- Julien Hédou
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Ivana Marić
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Grégoire Bellan
- Télécom Paris, Institut Polytechnique de Paris, Paris, France
| | - Jakob Einhaus
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Pathology and Neuropathology, University Hospital and Comprehensive Cancer Center Tübingen, Tübingen, Germany
| | - Dyani K Gaudillière
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University, Stanford, CA, USA
| | | | - Franck Verdonk
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
- Sorbonne University, GRC 29, AP-HP, DMU DREAM, Department of Anesthesiology and Intensive Care, Hôpital Saint-Antoine, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Ina A Stelzer
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Dorien Feyaerts
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Amy S Tsai
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Edward A Ganio
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Maximilian Sabayev
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Joshua Gillard
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jonas Amar
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Amelie Cambriel
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Tomiko T Oskotsky
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Alennie Roldan
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Jonathan L Golob
- Department of Medicine, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Thomas A Bonham
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Masaki Sato
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Maïgane Diop
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | - Xavier Durand
- École Polytechnique, Institut Polytechnique de Paris, Paris, France
| | - Martin S Angst
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
| | | | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Andrea Montanari
- Department of Statistics, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Brice Gaudillière
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University, Stanford, CA, USA.
- Department of Pediatrics, Stanford University, Stanford, CA, USA.
| |
Collapse
|
2
|
Mittal P, Romero R, Tarca AL, Gonzalez J, Draghici S, Xu Y, Dong Z, Nhan-Chang CL, Chaiworapongsa T, Lye S, Kusanovic JP, Lipovich L, Mazaki-Tovi S, Hassan SS, Mesiano S, Kim CJ. Characterization of the myometrial transcriptome and biological pathways of spontaneous human labor at term. J Perinat Med 2010; 38:617-43. [PMID: 20629487 PMCID: PMC3097097 DOI: 10.1515/jpm.2010.097] [Citation(s) in RCA: 121] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
AIMS to characterize the transcriptome of human myometrium during spontaneous labor at term. METHODS myometrium was obtained from women with (n=19) and without labor (n=20). Illumina HumanHT-12 microarrays were utilized. Moderated t-tests and false discovery rate adjustment of P-values were applied. Real-time quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) was performed for a select set of differentially expressed genes in a separate set of samples. Enzyme-linked immunosorbent assay and Western blot were utilized to confirm differential protein production in a third sample set. RESULTS 1) Four hundred and seventy-one genes were differentially expressed; 2) gene ontology analysis indicated enrichment of 103 biological processes and 18 molecular functions including: a) inflammatory response; b) cytokine activity; and c) chemokine activity; 3) systems biology pathway analysis using signaling pathway impact analysis indicated six significant pathways: a) cytokine-cytokine receptor interaction; b) Jak-STAT signaling; and c) complement and coagulation cascades; d) NOD-like receptor signaling pathway; e) systemic lupus erythematosus; and f) chemokine signaling pathway; 4) qRT-PCR confirmed over-expression of prostaglandin-endoperoxide synthase-2, heparin binding epidermal growth factor (EGF)-like growth factor, chemokine C-C motif ligand 2 (CCL2/MCP1), leukocyte immunoglobulin-like receptor, subfamily A member 5, interleukin (IL)-8, IL-6, chemokine C-X-C motif ligand 6 (CXCL6/GCP2), nuclear factor of kappa light chain gene enhancer in B-cells inhibitor zeta, suppressor of cytokine signaling 3 (SOCS3) and decreased expression of FK506 binding-protein 5 and aldehyde dehydrogenase in labor; 5) IL-6, CXCL6, CCL2 and SOCS3 protein expression was significantly higher in the term labor group compared to the term not in labor group. CONCLUSIONS myometrium of women in spontaneous labor at term is characterized by a stereotypic gene expression pattern consistent with over-expression of the inflammatory response and leukocyte chemotaxis. Differential gene expression identified with microarray was confirmed with qRT-PCR using an independent set of samples. This study represents an unbiased description of the biological processes involved in spontaneous labor at term based on transcriptomics.
Collapse
Affiliation(s)
- Pooja Mittal
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, USA.
| | - Roberto Romero
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan, USA,Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Adi L. Tarca
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan, USA,Department of Computer Science, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Juan Gonzalez
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Sorin Draghici
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Department of Computer Science, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Yi Xu
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA
| | - Zhong Dong
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA
| | - Chia-Ling Nhan-Chang
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Tinnakorn Chaiworapongsa
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Stephen Lye
- Department of Obstetrics and Gynecology, University of Toronto, Toronto, Ontario, Canada
| | - Juan Pedro Kusanovic
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Leonard Lipovich
- Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan, USA,Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Shali Mazaki-Tovi
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Sonia S. Hassan
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Sam Mesiano
- Department of Reproductive Biology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Chong Jai Kim
- Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, Maryland, and Detroit, Michigan, USA,Department of Pathology, Wayne State University School of Medicine, Detroit, Michigan, USA
| |
Collapse
|