Localization of Cancer Susceptibility Genes by Genome-wide Single-Nucleotide Polymorphism Linkage-Disequilibrium Mapping

Search for inherited susceptibility to radiation-associated meningioma by genomewide SNP linkage disequilibrium mapping

Background:

Exposure to ionising radiation is a well-established risk factor for multiple types of tumours, including malignant brain tumours. In the 1950s, radiotherapy was used to treat Tinea Capitis (TC) in thousands of children, mostly of North-African and Middle Eastern origin, during the mass migration to Israel. The over-representation of radiation-associated meningioma (RAM) and other cancers in specific families provide support for inherited genetic susceptibility to radiation-induced cancer.

Methods:

To test this hypothesis, we genotyped 15 families segregating RAM using high-density single-nucleotide polymorphism (SNP) arrays. Using the family-based association test (FBAT) programme, we tested each polymorphism and haplotype for an association with RAM.

Results:

The strongest haplotype associations were attained at 18q21.1 (P=7.5 × 10⁻⁵), 18q21.31 (P=2.8 × 10⁻⁵) and 10q21.3 (P=1.6 × 10⁻⁴). Although associations were not formally statistically significant after adjustment for multiple testing, the 18q21.1 and 10q21.3 associations provide support for a variation in PIAS2, KATNAL2, TCEB3C, TCEB3CL and CTNNA3 genes as risk factors for RAM.

Conclusion:

These findings suggest that any underlying genetic susceptibility to RAM is likely to be mediated through the co-inheritance of multiple risk alleles rather than a single major gene locus determining radiosensitivity.

Analysis of genetic variation in Ashkenazi Jews by high density SNP genotyping

BACKGROUND

Genetic isolates such as the Ashkenazi Jews (AJ) potentially offer advantages in mapping novel loci in whole genome disease association studies. To analyze patterns of genetic variation in AJ, genotypes of 101 healthy individuals were determined using the Affymetrix EAv3 500 K SNP array and compared to 60 CEPH-derived HapMap (CEU) individuals. 435,632 SNPs overlapped and met annotation criteria in the two groups.

RESULTS

A small but significant global difference in allele frequencies between AJ and CEU was demonstrated by a mean FST of 0.009 (P < 0.001); large regions that differed were found on chromosomes 2 and 6. Haplotype blocks inferred from pairwise linkage disequilibrium (LD) statistics (Haploview) as well as by expectation-maximization haplotype phase inference (HAP) showed a greater number of haplotype blocks in AJ compared to CEU by Haploview (50,397 vs. 44,169) or by HAP (59,269 vs. 54,457). Average haplotype blocks were smaller in AJ compared to CEU (e.g., 36.8 kb vs. 40.5 kb HAP). Analysis of global patterns of local LD decay for closely-spaced SNPs in CEU demonstrated more LD, while for SNPs further apart, LD was slightly greater in the AJ. A likelihood ratio approach showed that runs of homozygous SNPs were approximately 20% longer in AJ. A principal components analysis was sufficient to completely resolve the CEU from the AJ.

CONCLUSION

LD in the AJ versus was lower than expected by some measures and higher by others. Any putative advantage in whole genome association mapping using the AJ population will be highly dependent on regional LD structure.

Effects of environment, genetics and data analysis pitfalls in an esophageal cancer genome-wide association study

BACKGROUND

The development of new high-throughput genotyping technologies has allowed fast evaluation of single nucleotide polymorphisms (SNPs) on a genome-wide scale. Several recent genome-wide association studies employing these technologies suggest that panels of SNPs can be a useful tool for predicting cancer susceptibility and discovery of potentially important new disease loci.

METHODOLOGY/PRINCIPAL FINDINGS

In the present paper we undertake a careful examination of the relative significance of genetics, environmental factors, and biases of the data analysis protocol that was used in a previously published genome-wide association study. That prior study reported a nearly perfect discrimination of esophageal cancer patients and healthy controls on the basis of only genetic information. On the other hand, our results strongly suggest that SNPs in this dataset are not statistically linked to the phenotype, while several environmental factors and especially family history of esophageal cancer (a proxy to both environmental and genetic factors) have only a modest association with the disease.

CONCLUSIONS/SIGNIFICANCE

The main component of the previously claimed strong discriminatory signal is due to several data analysis pitfalls that in combination led to the strongly optimistic results. Such pitfalls are preventable and should be avoided in future studies since they create misleading conclusions and generate many false leads for subsequent research.

Heritability and clinical features of multigenerational families with obsessive-compulsive disorder and hoarding

To date, only one complete genome screen for obsessive-compulsive disorder (OCD) has been published. That study identified a region of suggestive linkage (maximum lod score of 2.25) with a relatively small sample size (N = 56; 27 with OCD). Additional complete genome screens are needed to confirm this finding and identify other regions of linkage. We present the clinical characteristics and power to detect linkage of 11 multigenerational families with OCD and hoarding (N = 92; 44 with OCD), as well as heritability estimates for several quantitative traits. Families with at least two individuals with OCD were identified through probands with childhood-onset OCD. Expected lod scores were calculated for simulated genetic marker data under an additive and two dominant models assuming a dense SNP marker map. All affected individuals had an early age of onset (18 or younger). Hoarding was present in 46% of subjects. Obsessive-compulsive symptoms and hoarding were highly heritable. The maximum mean expected lod score was 3.31 for OCD and 1.39 for hoarding. We found reasonable power to detect regions of interest (lod = 2) for OCD in these families, but will need to expand our family collection to have adequate power to detect regions of interest for hoarding.

Environmental genotoxicants/carcinogens and childhood cancer: Bridgeable gaps in scientific knowledge

Cancer in children is a major concern in many countries. An important question is whether these childhood cancers are caused by something, or are just tragic random events. Causation of at least some children's cancers is suggested by direct and indirect evidence, including epidemiological data, and animal studies that predict early life sensitivity of humans to carcinogenic effects. Candidate risk factors include genotoxic agents (chemicals and radiation), but also diet/nutrition, and infectious agents/immune responses. With regard to likelihood of risks posed by genotoxicants, there are pros and cons. The biological properties of fetuses and infants are consistent with sensitivity to preneoplastic genotoxic damage. Recent studies of genetic polymorphisms in carcinogen-metabolizing enzymes confirm a role for chemicals. On the other hand, in numerous epidemiological studies, associations between childhood cancers and exposure to genotoxicants, including tobacco smoke, have been weak and hard to reproduce. Possibly, sensitive genetic or ontogenetic subpopulations, and/or co-exposure situations need to be discovered to allow identification of susceptible individuals and their risk factors. Among the critical knowledge gaps needing to be bridged to aid in this effort include detailed tissue and cellular ontogeny of carcinogen metabolism and DNA repair enzymes, and associations of polymorphisms in DNA repair enzymes with childhood cancers. Perinatal bioassays in animals of specific environmental candidates, for example, benzene, could help guide epidemiology. Genetically engineered animal models could be useful for identification of chemical effects on specific genes. Investigations of interactions between factors may be key to understanding risk. Finally, fathers and newborn infants should receive more attention as especially sensitive targets.

Localization of breast cancer susceptibility loci by genome-wide SNP linkage disequilibrium mapping

We studied the feasibility of a novel approach to localize breast cancer susceptibility genes, using a low-density genome-wide panel of single-nucleotide polymorphisms and taking advantage of large regions of linkage disequilibrium (LD) flanking Jewish disease genes in high-risk cases. With Affymetrix GeneChip arrays, we genotyped 8,576 polymorphisms in three sets of Ashkenazi Jewish breast cancer cases: a "validation" set of 27 breast cancer cases, all of whom carried the BRCA2*6174delT founder mutation; a "field" set of 19 breast cancer cases from male breast cancer kindreds, which simulated conditions for finding new genes; and a "test" set of 57 probands from breast cancer kindreds (4 or more cases/kindred), in which mutations in BRCA1 and BRCA2 had been excluded. To identify associations, we compared the frequency of genotypes and haplotypes in cases vs. controls by the Fisher's exact test and a maximum likelihood ratio test. In the "validation" set, we demonstrated the presence of a region of linkage disequilibrium on BRCA2*6174delT chromosomes that spanned over 5 million bases. In the "field" set, we showed that this large region of linkage disequilibrium flanking BRCA2 was detectable despite the presence of heterogeneity in the sample set. Finally, in the "test" set, at least three regions of interest emerged that could contain novel breast cancer genes, one of which had been identified previously by linkage analysis. While these results demonstrate the feasibility of genome-wide association strategies, further application of this approach will critically depend on optimizing the density and distribution of SNPs and the size and type of study design.

Genetics of restless legs syndrome

Restless legs syndrome (RLS) is a common disorder, although under-diagnosed, with a prevalence of up to 15% depending on the population sampled. Familial aggregation has been widely shown since Ekbom formerly described the condition in 1960; twin studies support a genetic contribution in the development of this disorder. Molecular genetic approaches have identified three genomic regions in RLS susceptibility, however no specific mutations have yet been identified. Herein, we review the current status of genetics in RLS, providing some methodological guidelines to help future research.

The power of single-nucleotide polymorphisms for large-scale parentage inference

Likelihood-based parentage inference depends on the distribution of a likelihood-ratio statistic, which, in most cases of interest, cannot be exactly determined, but only approximated by Monte Carlo simulation. We provide importance-sampling algorithms for efficiently approximating very small tail probabilities in the distribution of the likelihood-ratio statistic. These importance-sampling methods allow the estimation of small false-positive rates and hence permit likelihood-based inference of parentage in large studies involving a great number of potential parents and many potential offspring. We investigate the performance of these importance-sampling algorithms in the context of parentage inference using single-nucleotide polymorphism (SNP) data and find that they may accelerate the computation of tail probabilities >1 millionfold. We subsequently use the importance-sampling algorithms to calculate the power available with SNPs for large-scale parentage studies, paying particular attention to the effect of genotyping errors and the occurrence of related individuals among the members of the putative mother-father-offspring trios. These simulations show that 60-100 SNPs may allow accurate pedigree reconstruction, even in situations involving thousands of potential mothers, fathers, and offspring. In addition, we compare the power of exclusion-based parentage inference to that of the likelihood-based method. Likelihood-based inference is much more powerful under many conditions; exclusion-based inference would require 40% more SNP loci to achieve the same accuracy as the likelihood-based approach in one common scenario. Our results demonstrate that SNPs are a powerful tool for parentage inference in large managed and/or natural populations.

Applying a new generation of genetic maps to understand human inflammatory disease

The sequencing of the human genome and the intense study of its variation in different human populations have improved our understanding of the genome's architecture. It is now becoming clear that segments of the genome that are unbroken by reshuffling or recombination during meiosis create a mosaic of DNA 'haplotype blocks'. Here, we discuss the advantages and limitations of this block structure. Haplotype blocks hold the promise of reducing the complexity of analysing the human genome for association with disease. But can they deliver on this promise? First generation maps of these block patterns, such as the admixture and haplotype maps, are now emerging and, it is to be hoped, will accelerate the discovery of alleles that contribute to susceptibility to human inflammatory diseases.