Common-Variant Common-Disease

Common-Variant Common-Disease Hypothesis

Contributed by Michael Joyner

One widely assumed outcome of the Human Genome Project (HGP) was that a limited number of gene variants based on so-called single nucleotide polymorphisms (SNPs) would explain much of the risk of common non-communicable diseases like ischemic heart diseases, type II diabetes, hypertension and other conditions including some forms of cancer.   This is known as Common-Variant Common-Disease Hypothesis and was underpinned by the well-known observation that many diseases run in families and are heritable in a statistical sense.  However, these conditions do not have classic Mendelian patterns of heritability, as for example, certain forms of hemophilia, sickle cell anemia, or cystic fibrosis do.  In this context, the results of numerous Genome Wide Association Studies (GWAS) conducted in large populations of humans have found:

  • A large number of gene variants (sometimes hundreds) are associated with many common diseases.
  • The effect size of such variants is typically small.
  • The reproducibility GWAS studies from one study or population to the next can be problematic.
  • The distribution of variants in populations with and without a given disease is frequently similar.
  • The addition of gene scores to disease risk prediction algorithms derived from epidemiology studies has generally not improved the algorithms.

These findings highlight the ongoing problem of “missing heritability” which has been a concern since studies from the Victorian era on the relationship between the height of parents and their children.  For those who favor a DNA centric view of human phenotypic variability the assumption is that more detailed studies of the genome will shed light on DNA based mechanisms that might account for this missing heritability.  Those who favor the view that human phenotypic variability is due to complex interactions between the environment, behavior, physiological regulation and adaptation, and the genome see the continuing challenge of missing heritability as highlighting the limitations of the DNA centric view of human phenotypic variation.

 For more information see:

 Baker M (2010).  Genomics: The search for association.  Nature 467: 1135-1138. http://www.nature.com/nature/journal/v467/n7319/full/4671135a.html

 Collins FS (2001).  Contemplating the end of the beginning.  Genome Res 11: 641-643. http://genome.cshlp.org/content/11/5/641.full

 Cooper GM, Shendure J (2011). Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data.  Nat Rev Genet12:628-40. http://www.nature.com/nrg/journal/v12/n9/full/nrg3046.html

 Ganesh SK, et al Genetics and genomics for the prevention and treatment of cardiovascular disease: update: a scientific statement from the American Heart Association.  Circulation 128: 2813-2851. http://circ.ahajournals.org/content/128/25/2813

 Joyner MJ, Prendergast FG (2014). Chasing Mendel: five questions for personalized medicine.  J. Physiol in Press.

 Shields R (2011).  Common disease: are causative alleles common or rare?  PLoS Biol 9: e1001009. http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001009

 Talmud PJ et al (2010).  Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study.  Br Med J 340: b4838. http://www.bmj.com/content/340/bmj.b4838

2019-11-19T09:09:30+00:00