Advertisement

Impact of Complexity on Population Biology

  • Anthony J. Hickey
  • Hugh D. C. Smyth
Chapter
  • 15 Downloads
Part of the AAPS Introductions in the Pharmaceutical Sciences book series (AAPSINSTR)

Abstract

The complexity of biological systems is recognized superficially, but there has been a tendency through reductionism to believe that fundamental understanding is achieved through examination of the smallest building blocks of life. There is steadily increasing understanding that looking at large populations particularly as the tools have become available to probe the underpinning rules of genetics and epigenetics will lead to a systematic understanding that may offer unique strategies for future disease therapy. Since the first edition of this book, many of the predictions with respect to unraveling the biological complexity through genomics, transcriptomics, metabolomics, and proteomics have come to pass, and a host of new therapies particularly for rare diseases are under development.

Keywords

Population biology Disease Genetic disorders Epidemiology Adverse events 

References

  1. Altshuler, D., Pollara, V., Cowles, C., Etten, W. V., & Baldwin, J. (2000). An SNP map of the human genome generated by reduced representation shotgun sequencing. Nature, 407, 513–516.CrossRefGoogle Scholar
  2. Anderson, R., & Francis, K. (2018). Modeling rare diseases with induced pluripotent stem cell technology. Molecular and Cellular Probes, 40, 52–59.CrossRefGoogle Scholar
  3. Anderson, R., & May, R. (1979). Population biology of infectious disease:Part I. Nature, 280, 361–367.CrossRefGoogle Scholar
  4. Berman, J. (2014). Rare diseases and orphan drug: Keys to understanding. Waltham, MA: Academic Press.Google Scholar
  5. Boycott, K., Vanstone, M., Bulman, D., & MacKenzie, A. E. (2013). Rare-disease genetics in the era of next-generation sequencing: Discovery to translation. Nature Reviews Genetics, 14, 681–691.CrossRefGoogle Scholar
  6. Cole, S., Brosch, R., Parkhill, R., Garnier, T., & Churcher, C. (1998). Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature, 393, 537–544.CrossRefGoogle Scholar
  7. Davis, A., Wiegers, T., King, B., Wiegers, J., Grondin, C., Sciaky, D., … Mattingly, C. (2016). Generating gene ontology-disease inferences to explore mechanisms of human disease at the comparative toxicogenomics database. PLoS One, 11(5), e0155530.CrossRefGoogle Scholar
  8. Dawkins, H., Draghia-Akli, R., Lasko, P., Lau, L., Jonker, A., Cutillo, C., … Austin, C. (2018). Progress in rare diseases research 2010-2016: An IRDiRC perspective. Clinical and Translational Science, 11(1), 11–20.CrossRefGoogle Scholar
  9. Dokoumoetzidis, A., & Macheras, P. (2006). A comment on “adverse drug reactions and avalanches: Life on the edge of chaos”. Journal of Clinical Pharmacology, 46(9), 1057–1058. (author reply 1059-1060).CrossRefGoogle Scholar
  10. Evans, W., & Relling, M. (2004). Moving toward individualizeed medicine with pharmacogenomics. Nature, 429, 464–468.CrossRefGoogle Scholar
  11. Frattarelli, D. (2005). Adverse drug reactions and avalanches: Life at the edge of chaos. Journal of Clinical Pharmacology, 45(8), 866–871.CrossRefGoogle Scholar
  12. Garone, C., & Viscomi, C. (2018). Towards a therapy for mitochondrial disease: An update. Biochemical Society Transactions, 46(5), 1247–1261.CrossRefGoogle Scholar
  13. Gatenby, R., & Vincent, T. (2003). Application of quantitative models from population biology and evolutionary game theory to tumor therapeutic strategies. Molecular Cancer Therapeutics, 2, 919–927.PubMedGoogle Scholar
  14. Glattre, E., & Nygard, J. (2004). Fractal meta-analysis and causality embedded in complexity: Advanced understanding of disease etiology. Nonlinear Dynamics, Psychology, and Life Sciences, 8(3), 315–344.PubMedGoogle Scholar
  15. Glew, R., Basu, A., Prence, E., & Remaley, A. (1985). Lysosomal storage diseases. Laboratory Investigation, 53(3), 250–269.PubMedGoogle Scholar
  16. Hirano, T. (2007). Cellular pharmacodynamics of immunosuppressive drugs for indivudualized medicine. International Immunopharamcol, 7, 3–22.CrossRefGoogle Scholar
  17. Horgan, R., & Kenny, L. (2011). ‘Omic’ technologies: Genomics, transcriptomics, proteomics and metabolomics. The Obstetrician & Gynaecologist, 13(3), 189.CrossRefGoogle Scholar
  18. Human Genome Sequencing Consortium. (2001). Initial sequencing and analysis of the human genome. Nature, 409, 860–921.CrossRefGoogle Scholar
  19. Kanehisa, M., Goto, S., Sato, Y., Kawashima, M., Furumichi, M., & Tanabe, M. (2014). Data, information, knowledge and principle: Back to metabolism in KEGG. Nucleic Acid Research, 42(D1), D199–D205.CrossRefGoogle Scholar
  20. Kennedy, T. (1998). Pharmaceutifcal project management. New York, NY: Marcel Dekker, Inc..Google Scholar
  21. Krumholz, H. (2014). Big data and new knowledge in medicine: The thinking, training, and tools needed for a learning health system. Health Affairs (Millwood), 33(7), 1163–1170.CrossRefGoogle Scholar
  22. Levy, S., Sutton, G., Ng, P., Feuk, L., & Halpern, A. (2007). The diploid genome sequence of an individual human. PLoS Biology, 5(10), e254.CrossRefGoogle Scholar
  23. O’Donovan, C., Apweiler, R., & Baroch, A. (2001). The human proteomics initiative. Trends in Biotechnology, 19, 178–181.CrossRefGoogle Scholar
  24. Pearson, H. (2007). Meet the human metabolome. Nature, 446, 8.  https://doi.org/10.1038/446008aCrossRefPubMedGoogle Scholar
  25. Quitaina-Murci, L. (2016). Understanding rare and common diseases in the context of human evolution. Genome Biology, 17, 225.CrossRefGoogle Scholar
  26. Sarntivijal, S., Vasant, D., Jupp, S., Saunders, G., Bento, A., Gonzalez, D., … Malone, J. (2016). Linking rare and common disease: Mapping clinical disease-phenotypes to ontologies in therapeutic target validation. Journal of Biomedical Semantics, 7, 8.CrossRefGoogle Scholar
  27. Turnbull, C., Ahmed, S., Morrison, J., Pernet, D., & Renwick, A. (2010). Genome-wide association study identifies five new breast cancer susceptible loci. Nature Genetics, 42, 504.CrossRefGoogle Scholar
  28. Venter, J., Adams, M., Myers, E., Li, P., & Muraj, R. (2001). The sequence of the human genome. Sicnece, 291, 1304–1351.CrossRefGoogle Scholar
  29. Vesper, J. (2006). Risk assessment and risk management in the pharmaceutical industry: Clear and simple. Washington, DC: Parenteral Drug Association.Google Scholar
  30. Westerhoff, H., Winder, C., Messiha, H., Simeonidis, E., Adamczyk, M., Verma, M., … Dunn, W. (2009). Systems biology: The elements and principles of life. FEBS Letters, 584(24), 3882–3890.CrossRefGoogle Scholar
  31. Winchester, B., Vellodi, A., & Young, E. (2000). The molecular basis for lysosomal storage diseases and their treatment. Biochemical Society Transactions, 28(2), 150–154.CrossRefGoogle Scholar

Copyright information

© American Association of Pharmaceutical Scientists 2020

Authors and Affiliations

  • Anthony J. Hickey
    • 1
  • Hugh D. C. Smyth
    • 2
  1. 1.RTI InternationalResearch Triangle ParkUSA
  2. 2.College of PharmacyThe University of Texas at AustinAustinUSA

Personalised recommendations