1608. Novel Meta-Analyses of Microarray Data First Step Toward Malaria Disease Signature Development
Session: Poster Abstract Session: Global Health
Saturday, October 10, 2015
Room: Poster Hall
Posters
  • Hadied_Mohamad_Malaria_Poster.pdf (959.7 kB)
  • Background:

    Malaria accounts for a considerable amount of mortality around the world, especially among young children. Artemisinin Combination Therapies (ACTs) remain the most potent treatment for uncomplicated cases of malaria.  Early signs of drug resistance have emerged in the form of delayed clearance of the parasite in Southeast Asia. There is a high demand for newer drugs and vaccines to help control the worldwide malaria burden pending complete drug resistance to ACTs.  The aim of this study is to characterize the disease signature of a malaria infection using meta-analysis of microarray data, and use this data to facilitate the pursuit of newer drugs and vaccines to fight malaria worldwide.

    Methods:

    Through a unique collaboration between medical students and computer scientists in systems biology, Search Tag & Analyze Resource (STAR) is a platform that was created that allows us to easily analyze gene signatures through meta-analyses of series in the Gene Expression Omnibus (GEO).  Experiment samples within the database are annotated with tags and run through meta-analysis.

    Results:

    Using STAR, we generated one preliminary gene signature using samples on GEO: whole blood samples from malaria infections versus blood samples from health controls. We have found LGR4 and p70-S6k to be the top upstream regulators (p=0.002 for both).  GBA and C15orf48 were the top significantly up-regulated genes. LEF1, PDCD4, and CNST were the top significantly down-regulated genes. GBA, LEF1, and the p70-S6k pathway have all been reported before as associated with malaria disease expression, the other genes have not.

    Conclusion:

    These preliminary results are proof-of-concept to the potential of STAR.  With the collaboration fully functional, thousands of samples will be added to improve the gene signature of malaria infection.  The study will also include parasite gene expression run with the same meta-analysis.  We report here a first step towards novel transitional opportunities for better biomarkers and drugs for infectious diseases like malaria and beyond.

    Mohamad Omar Hadied, BS1, Osama El-Sayed, BS2, Bilal Zaidi, BS3, Jihad Al-Jabban, BS4, Shuaib Raza, BS5, Imad Al-Jabban, BS4, James Pan, BA6, Tej Azad, BA6 and Dexter Hadley, MD/PhD7, (1)Wayne State University School of Medicine, Detroit, MI, (2)College of Medicine, University of Illinois at Chicago, Chicago, IL, (3)University of Michigan, Ann Arbor, MI, (4)Department of Immunology, Harvard University, Boston, MA, (5)Yale School of Medicine, Yale University, New Haven, CT, (6)Stanford University, Stanford, CA, (7)University of California San Francisco, San Francisco, CA

    Disclosures:

    M. O. Hadied, None

    O. El-Sayed, None

    B. Zaidi, None

    J. Al-Jabban, None

    S. Raza, None

    I. Al-Jabban, None

    J. Pan, None

    T. Azad, None

    D. Hadley, None

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    Findings in the abstracts are embargoed until 12:01 a.m. PDT, Wednesday Oct. 7th with the exception of research findings presented at the IDWeek press conferences.