ArticleOmics : a journal of integrative biology2014
Novel multivariate methods for integration of genomics and proteomics data: applications in a kidney transplant rejection study.
Article in Omics : a journal of integrative biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Large Language Models for Accessible Reporting of Bioinformatics Analyses in Interdisciplinary Contexts.bioRxiv : the preprint server for biology · 2025Article
- Multi-Omics Integration in Nephrology: Advances, Challenges, and Future Directions.Seminars in nephrology · 2024Review
- Identification of Renal Transplantation Rejection Biomarkers in Blood Using the Systems Biology Approach.Iranian biomedical journal · 2023Article
- Identification of AKI signatures and classification patterns in ccRCC based on machine learning.Frontiers in medicine · 2023Article
- Evaluating the Link between BAFF System Gene Expression and Acute Rejection Development in Kidney Transplantation.Journal of clinical medicine · 2022Article
- Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection.Proteomes · 2022Review
- A statistical methodology to select covariates in high-dimensional data under dependence. Application to the classification of genetic profiles in oncology.Journal of applied statistics · 2022Article
- MicroRNA Expression Changes in Kidney Transplant: Diagnostic Efficacy of miR-150-5p as Potential Rejection Biomarker, Pilot Study.Journal of clinical medicine · 2021Article
- Integrative multiomics analysis of human atherosclerosis reveals a serum response factor-driven network associated with intraplaque hemorrhage.Clinical and translational medicine · 2021Article
- Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation.BMC medical genomics · 2020Article
- DNA Methylation Associated With Diabetic Kidney Disease in Blood-Derived DNA.Frontiers in cell and developmental biology · 2020Article
- An age-independent gene signature for monitoring acute rejection in kidney transplantation.Theranostics · 2020Article
- The Role of Systems Vaccinology in Understanding the Immune Defects to Vaccination in Solid Organ Transplant Recipients.Frontiers in immunology · 2020Review
- Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data.Metabolomics : Official journal of the Metabolomic Society · 2019Article
- Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community.Metabolites · 2019Article
- Batch adjustment by reference alignment (BARA): Improved prediction performance in biological test sets with batch effects.PloS one · 2019Article
- Integrative radiomics expression predicts molecular subtypes of primary clear cell renal cell carcinoma.Clinical radiology · 2018Article
- Modeling a linkage between blood transcriptional expression and activity in brain regions to infer the phenotype of schizophrenia patients.NPJ schizophrenia · 2017Article
- Proteomics for rejection diagnosis in renal transplant patients: Where are we now?World journal of transplantation · 2016Review
- Cross-platform comparison of independent datasets identifies an immune signature associated with improved survival in metastatic melanoma.Oncotarget · 2016Article
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Multi-omics research is a key ingredient of data-intensive life sciences research, permitting measurement of biological molecules at different functional levels in the same individual. For a complete picture at the biological systems level, appropriate statistical techniques must however be developed to integrate different 'omics' data sets (e.g., genomics and proteomics). We report here multivariate projection-based analyses approaches to genomics and proteomics data sets, using the case study of and applications to observations in kidney transplant patients who experienced an acute rejection event (n=20) versus non-rejecting controls (n=20). In this data sets, we show how these novel methodologies might serve as promising tools for dimension reduction and selection of relevant features for different analytical frameworks. Unsupervised analyses highlighted the importance of post transplant time-of-rejection, while supervised analyses identified gene and protein signatures that together predicted rejection status with little time effect. The selected genes are part of biological pathways that are representative of immune responses. Gene enrichment profiles revealed increases in innate immune responses and neutrophil activities and a depletion of T lymphocyte related processes in rejection samples as compared to controls. In all, this article offers candidate biomarkers for future detection and monitoring of acute kidney transplant rejection, as well as ways forward for methodological advances to better harness multi-omics data sets.
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