Front. Genet., 02 June 2014 | doi: 10.3389/fgene.2014.00162

Genetic-based prediction of disease traits: prediction is very difficult, especially about the future

  • 1Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI, USA
  • 2Department of Medicine, School of Medicine, University of Washington, Seattle, WA, USA
  • 3Departments of Human Genetics and Biostatistics, Graduate School of Public Health, University of Pittsburgh, PA, USA
  • 4Sigfried and Janet Weis Center for Research, Geisinger Health System, Danville, PA, USA
  • 5Subsidiary of Quest Diagnostics, Discovery Research, Celera Corporation, Alameda, CA, USA
  • 6Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
  • 7Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI, USA
  • 8Department of Epidemiology and Biostatistics, Case Western Reserve School of Medicine, Cleveland, OH, USA

Translation of results from genetic findings to inform medical practice is a highly anticipated goal of human genetics. The aim of this paper is to review and discuss the role of genetics in medically-relevant prediction. Germline genetics presages disease onset and therefore can contribute prognostic signals that augment laboratory tests and clinical features. As such, the impact of genetic-based predictive models on clinical decisions and therapy choice could be profound. However, given that (i) medical traits result from a complex interplay between genetic and environmental factors, (ii) the underlying genetic architectures for susceptibility to common diseases are not well-understood, and (iii) replicable susceptibility alleles, in combination, account for only a moderate amount of disease heritability, there are substantial challenges to constructing and implementing genetic risk prediction models with high utility. In spite of these challenges, concerted progress has continued in this area with an ongoing accumulation of studies that identify disease predisposing genotypes. Several statistical approaches with the aim of predicting disease have been published. Here we summarize the current state of disease susceptibility mapping and pharmacogenetics efforts for risk prediction, describe methods used to construct and evaluate genetic-based predictive models, and discuss applications.

Keywords: predictive model, genetic risk, human genetics, prognosis, clinical utility

Citation: Schrodi SJ, Mukherjee S, Shan Y, Tromp G, Sninsky JJ, Callear AP, Carter TC, Ye Z, Haines JL, Brilliant MH, Crane PK, Smelser DT, Elston RC and Weeks DE (2014) Genetic-based prediction of disease traits: prediction is very difficult, especially about the future. Front. Genet. 5:162. doi: 10.3389/fgene.2014.00162

Received: 13 February 2014; Accepted: 15 May 2014;
Published online: 02 June 2014.

Edited by:

Marylyn D. Ritchie, The Pennsylvania State University, USA

Reviewed by:

Andrew Skol, University of Chicago, USA
Hui-Qi Qu, The University of Texas School of Public Health, USA

Copyright © 2014 Schrodi, Mukherjee, Shan, Tromp, Sninsky, Callear, Carter, Ye, Haines, Brilliant, Crane, Smelser, Elston and Weeks. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Steven J. Schrodi, Center for Human Genetics, Marshfield Clinic Research Foundation, 1000 N Oak Ave. Marshfield, WI 54449, USA e-mail:

Back to top