Rare genetic variants and the risk of cancer
Introduction
The first and most clear-cut achievement in the study of inherited cancer risk that has come from the revolution in molecular genetics is the successful discovery of genes which cause the Mendelian cancer predisposition syndromes. We use the term “Mendelian” here to refer to patterns of familial inheritance that at least closely approximate to Mendelian expectations, implying penetrances of the associated variants that are usually at least of the order of 0.7. To date, about 100 such genes are known. Most of these have been discovered by a combination of positional cloning by linkage analysis, and choice of candidate genes. A variety of indirect, sometimes serendipitous, approaches, such as seeking rare, large deletions or finding a signature of genomic instability, have also made significant contributions.
In all cases, the disease-causing variants are, at least for dominant effects, very rare, being maintained in the population by mutation-selection balance. Whilst some founder mutations exist and other mutations are recurrent, possibly because of unusually high germline mutation rates, there is considerable within-locus variant heterogeneity. Thus, over 500 different adenomatous polyposis coli (APC) mutations have been reported in patients with familial adenomatous polyposis (FAP). Even for recessive cancer predisposing conditions, such as Xeroderma pigmentosum, the individual allele frequencies rarely exceed 0.005.
Although the relative risks associated with the Mendelian cancer genes are, by definition, very large and so should be readily detectable, there remains speculation that there may exist undiscovered cancer loci with high-penetrance variants. The evidence for this is largely based on comparisons with the clinical features of existing syndromes. Large cancer families of unknown cause, unusual cancers in consanguineous families, individuals with multiple tumours of one type and, occasionally, co-occurrence of specific cancers all suggest Mendelian inheritance. In some cases, such as hyperplastic polyposis syndrome, disease may be recessive and sometimes occult or of variable severity, and hence the condition might rarely present in families that would allow linkage analysis. In other cases, there might be considerable locus heterogeneity, confounding attempts at gene mapping and identification. However, it seems most unlikely that such new discoveries will significantly increase the overall population frequency of Mendelian cancer syndromes.
For the common cancers, a maximum of about 5% of cases are associated with known Mendelian susceptibility. For colorectal cancer (CRC), for example, Mendelian syndromes include FAP, Lynch syndrome (caused by mutations in DNA mismatch repair genes), the recessive MUTYH-associated polyposis (MAP) and a small number of rarer polyposis syndromes. However, overall, about 30% of the variation in CRC risk is thought to be due to inherited susceptibility, a proportion far too large to be explained by the Mendelian syndromes. Breast cancer has a similar gap between Mendelian and overall genetic risk and for prostate cancer, the risk is even higher, as very few cases are attributable to high-risk alleles. It is that gap which must be filled by studies to identify cancer predisposition alleles in the general population.
A priori, the missing cancer heritability must be derived from genetic variants of lower risk. In principle, these variants could exist at any frequency in the population. The first approach to looking for the basis of this heritability, exemplified by association studies on HLA and disease, was to search for associations between common polymorphic variants and a specific disease. Initially, this was based on candidate gene approaches, testing the hypothesis that either the discovery variant itself was disease-causing or that it was in linkage disequilibrium with the disease-causing variant. Candidate genes often produced conflicting results [1, 2, 3]. However, with the advent of high-throughput technology, it became possible to do genome-wide association (GWA) searches, with no a priori assumptions about mechanisms, on very large numbers of polymorphic variants and on very large cohorts of cases and controls. It became apparent, moreover, that large sets of thousands of cases and controls were needed when the observed odds ratios (ORs) for even the most significantly associated variants were quite low and rarely exceeded even 1.4 or 1.5. At this level of OR, only very large studies can give significance when allowance is made for the number of comparisons being tested.
GWA studies, based on what is now sometimes called the tagging SNPs model, have been used successfully by many groups, where success is measured by the significance of the association rather than its magnitude. However, the common cancer alleles detected to date typically account for only ∼10% of the familial relative risk of disease, still leaving open the question of what can explain the remaining genetic risk of cancer. The strong possibility is that rare variants with ‘subpolymorphic’ allele frequencies account for most of this remaining inherited risk [4•, 5•]. Direct evidence for this has come, for example, from the study of genetic variation in the level of plasma HDL-type cholesterol [6].
Section snippets
The ‘rare variant hypothesis’ for susceptibility to common diseases
The ‘rare variant hypothesis’ proposes that a significant proportion of the inherited susceptibility to relatively common human diseases may be due to the summation of the effects of a series of low frequency, perhaps dominantly acting and independently acting, variants of a variety of different genes, each conferring a moderate but detectable increase in relative risk. The number of different rare variants within any gene might vary considerably, as might the frequency of each variant. Variant
The search for rare variants
There are some theoretical reasons for believing that the ‘common disease-rare variant’ model might be correct. However, these generally rely on unproven assumptions, for example that common variants are unlikely to explain much of the disease trait variance unless they have a non-negligible effect on fitness [7••]. Currently, there is little or no evidence about the fitness effects of common, disease-associated variants and since evidence will be difficult to obtain, it is arguable that the
Alternative strategy
An alternative strategy to the above is to have a single assessment phase, rather than separate discovery and assessment phases. For example, a set of genes could be sequenced in large sets of cases and controls. This is probably a less efficient strategy, but might be used if, for example, case samples were limiting and/or there was a small number of strong candidate genes.
Lessons from variants of unknown or uncertain significance
When a Mendelian cancer predisposition gene is first identified, much of the evidence derives from the finding of several different variants in that gene that (i) a priori have strong functional effects (for example, protein-truncating mutations), (ii) are often accompanied by ‘second hits’ in the cancer themselves and (iii) are essentially absent from the general population and are hence associated with a very high relative risk. Given that many Mendelian cancer syndromes have specific
Definition and features of rare variants
Definitions of rare variants are currently imprecise and fluid. An essentially arbitrary lower threshold of 1% allele frequency has been proposed as the definition of polymorphic variation. This value is mostly above that attained by a dominant deleterious mutation maintained in the population by mutation-selection balance or drift. Even for completely recessive deleterious mutations, the corresponding maximum expected incidence is probably only just over 3%. Rare variants will mostly be
Conclusions
GWA studies have shown that common variants affect the risk of cancer in the general population. However, the effect sizes of these common alleles have been small and only a small proportion of the familial relative risk of cancer can be explained. It follows that unless many more common cancer alleles are discovered or unexpectedly strong gene–gene or gene–environment interactions are found, SNPs will have limited practical application in predicting whether an individual will develop disease.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
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