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Exp Biol Med (Maywood). 2016 Apr;241(7):772-81. doi: 10.1177/1535370216640150. Epub 2016 Mar 27.

Minireview: Multiomic candidate biomarkers for clinical manifestations of sickle cell severity: Early steps to precision medicine.

Author information

1
Department of Pediatrics and Department of Physiology, The University of Tennessee Health Science Center, Memphis, TN 38163, USA sgoodma5@uthsc.edu.
2
Department of Pediatrics, Augusta University, Augusta, GA 30912, USA.
3
Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, CO 80202, USA.
4
Biochemistry and Molecular Biology Department, University of Texas at Houston, TX 77030, USA.
5
University of Texas at Dallas, Richardson, TX 75080, USA.
6
Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY 13210, USA.

Abstract

In this review, we provide a description of those candidate biomarkers which have been demonstrated by multiple-omics approaches to vary in correlation with specific clinical manifestations of sickle cell severity. We believe that future clinical analyses of severity phenotype will require a multiomic analysis, or an omics stack approach, which includes integrated interactomics. It will also require the analysis of big data sets. These candidate biomarkers, whether they are individual or panels of functionally linked markers, will require future validation in large prospective and retrospective clinical studies. Once validated, the hope is that informative biomarkers will be used for the identification of individuals most likely to experience severe complications, and thereby be applied for the design of patient-specific therapeutic approaches and response to treatment. This would be the beginning of precision medicine for sickle cell disease.

KEYWORDS:

Genomics; interactomics; metabolomics; precision medicine; proteomics; sickle cell disease

PMID:
27022133
PMCID:
PMC4950385
DOI:
10.1177/1535370216640150
[Indexed for MEDLINE]
Free PMC Article

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