A comprehensive genetic approach shows that skin cancer risk includes more than UV exposure
Assessment skin cancer risk prediction is improved by accounting for genetic factors
- Date : 10 Dec 2012
- Topic : Melanoma
It is common knowledge that excessive UV exposure from sunlight raises chances for skin cancer, but predicting whether someone will actually develop skin cancer remains difficult. In a new research report, scientists from the University of Alabama at Birmingham (UAB) and the University of Wisconsin–Madison show that the risk for skin cancer involves numerous genetic factors including family history, ethnicity, and genetic variations specific to each individual. Using these factors, the researchers developed a more precise model for assessing risk, which is published in the December 2012 issue of the journal Genetics.
According to Ana Inés Vázquez, PhD, lead author of the study from UAB's Department of Biostatistics, a better understanding of the genetics of complex traits and diseases is essential for the development of methods that can be used for early and improved prediction of genetic predisposition to diseases. Prediction of genetic risk for disease is needed for preventive and personalised medicine. Genome-wide association studies have found unprecedented numbers of variants associated with complex human traits and diseases. However, these variants explain only a small proportion of genetic risk. Mounting evidence suggests that many traits, relevant to public health, are affected by large numbers of small-effect genes and that prediction of genetic risk to those traits and diseases could be improved by incorporating large numbers of markers into whole-genome prediction models.
To make this discovery, the scientists used phenotypic and genetic information from more than 5,000 familial participants in the Framingham Heart Study to develop various models for assessing skin cancer risk. The researchers' most basic risk evaluation model included standard risk factors such as sex. Additional predictive models were developed by adding information on family history, ethnicity, and data from 41,000 genetic markers across the human genome. The predictive power of each model was evaluated, with the best prediction accuracy obtained from models that include all predictive risk factors, those standard risk factors plus family history, ethnicity and genetic markers.
Although there is no doubt that sun exposure increases risk for skin cancer, it isn't clear how much of a risk it poses to each individual, according to Mark Johnston, Editor-in-Chief of the journal Genetics. This new model for assessing risk should prove useful to health care providers and public health officials, who play a crucial role in educating people about preventing skin cancer.
The authors summarised that prediction of skin cancer risk could be improved by considering genetic information and using a large number of single-nucleotide polymorphisms in a whole-genome prediction model, which allows for the detection of patterns of genetic risk that are above and beyond those that can be captured using family history. In their open access article, they discuss about avenues for improving prediction accuracy and speculate on the possible use of whole-genome prediction to prospectively identify individuals at high risk.
The authors acknowledge NIH (USA) grants R01GM077490, R01GM099992, R01GM101219 the Kraft grant, as well as the Wisconsin Agriculture Experiment Station for their financial support.
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