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Med Hypotheses. 2004;63(4):748-51.

The allelic spectra of common diseases may resemble the allelic spectrum of the full genome.

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  • 1Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 2XY, UK. william.wang@cimr.cam.ac.uk

Abstract

Identification of the genes responsible for common human diseases promises to be one of the most significant advances in medical knowledge and treatment. To date, the numerous attempts to identify the genes responsible for complex and multi-factorial common diseases have met with only a handful of successes. The key to calculating the optimal effort and ideal approach to successful identifications lies with understanding the likely allelic spectrum of the target disease. The allelic spectrum describes the number of disease loci and the frequency of each disease allele. It has been implicitly assumed that disease spectra are biased towards either commonness or rareness relative to the allelic spectrum of the overall human genome. We present a hypothesis that the allelic spectra of common diseases are generally similar to the spectrum that characterizes the entire genome. This hypothesis is supported by the fact that only a few loci have major significance to familial disease risks and that there may be many disease loci which each make a minor contribution to a disease. Additionally, although relatively few alleles of the human genome have been examined for disease involvement, current estimates of the number of disease genes are very high. Because selection will have been operating only weakly and for a relatively short time on most of the alleles associated with complex diseases, spectra that are characteristic of near-neutral selection may well apply. We thus propose that the hitherto neglected hypothesis that puts the likely allelic spectra of common diseases in the middle ground between the prevailing hypotheses of spectral skew towards rareness or commonness is the most likely. By using this hypothesis as the null, research resources may be optimally allocated and greater success in identifying disease genes may be achieved.

Copyright 2004 Elsevier Ltd.

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PMID:
15325027
[PubMed - indexed for MEDLINE]
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