Genome-wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients

Here we perform the first genome-wide association study (GWAS) of multiple myeloma (MM) survival. In a meta-analysis of 306 MM patients treated at UCSF and 239 patients treated at the Mayo clinic, we find a significant association between SNPs near the gene FOPNL on chromosome 16p13 and survival (rs72773978; P=6 × 10(-10)). Patients with the minor allele are at increased risk for mortality (HR: 2.65; 95% CI: 1.94-3.58) relative to patients homozygous for the major allele. We replicate the association in the IMMEnSE cohort including 772 patients, and a University of Utah cohort including 318 patients (rs72773978 P=0.044). Using publicly available data, we find that the minor allele was associated with increased expression of FOPNL and increased expression of FOPNL was associated with higher expression of centrosomal genes and with shorter survival. Polymorphisms at the FOPNL locus are associated with survival among MM patients.

A pooled analysis of cigarette smoking and risk of multiple myeloma from the international multiple myeloma consortium

BACKGROUND

Past investigations of cigarette smoking and multiple myeloma have been underpowered to detect moderate associations, particularly within subgroups. To clarify this association, we conducted a pooled analysis of nine case-control studies in the International Multiple Myeloma Consortium, with individual-level questionnaire data on cigarette smoking history and other covariates.

METHODS

Using a pooled population of 2,670 cases and 11,913 controls, we computed odds ratios (OR) and 95% confidence intervals (CI) relating smoking to multiple myeloma risk using unconditional logistic regression adjusting for gender, age group, race, education, body mass index, alcohol consumption, and study center.

RESULTS

Neither ever smokers (OR, 0.95; 95% CI, 0.87-1.05), current smokers (OR, 0.82; 95% CI, 0.73-0.93), nor former smokers (OR, 1.03; 95% CI, 0.92-1.14) had increased risks of multiple myeloma compared with never smokers. Analyses of smoking frequency, pack-years, and duration did not reveal significant or consistent patterns, and there was no significant effect modification by subgroups.

CONCLUSION

Findings from this large pooled analysis do not support the hypothesis of cigarette smoking as a causal factor for multiple myeloma.

IMPACT

Cigarette smoking is one of the most important risk factors for cancer, but the association with multiple myeloma was inconclusive. This study had excellent power to detect modest associations, and had individual-level data to evaluate confounding and effect modification by potentially important factors that were not evaluated in previous studies. Our findings confirm that smoking is not a risk factor for multiple myeloma. Cancer Epidemiol Biomarkers Prev; 24(3); 631-4. ©2014 AACR.

Identification and characterization of novel associations in the CASP8/ALS2CR12 region on chromosome 2 with breast cancer risk

Previous studies have suggested that polymorphisms in CASP8 on chromosome 2 are associated with breast cancer risk. To clarify the role of CASP8 in breast cancer susceptibility, we carried out dense genotyping of this region in the Breast Cancer Association Consortium (BCAC). Single-nucleotide polymorphisms (SNPs) spanning a 1 Mb region around CASP8 were genotyped in 46 450 breast cancer cases and 42 600 controls of European origin from 41 studies participating in the BCAC as part of a custom genotyping array experiment (iCOGS). Missing genotypes and SNPs were imputed and, after quality exclusions, 501 typed and 1232 imputed SNPs were included in logistic regression models adjusting for study and ancestry principal components. The SNPs retained in the final model were investigated further in data from nine genome-wide association studies (GWAS) comprising in total 10 052 case and 12 575 control subjects. The most significant association signal observed in European subjects was for the imputed intronic SNP rs1830298 in ALS2CR12 (telomeric to CASP8), with per allele odds ratio and 95% confidence interval [OR (95% confidence interval, CI)] for the minor allele of 1.05 (1.03-1.07), P = 1 × 10(-5). Three additional independent signals from intronic SNPs were identified, in CASP8 (rs36043647), ALS2CR11 (rs59278883) and CFLAR (rs7558475). The association with rs1830298 was replicated in the imputed results from the combined GWAS (P = 3 × 10(-6)), yielding a combined OR (95% CI) of 1.06 (1.04-1.08), P = 1 × 10(-9). Analyses of gene expression associations in peripheral blood and normal breast tissue indicate that CASP8 might be the target gene, suggesting a mechanism involving apoptosis.

Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease

Previous GWAS studies have reported significant associations between various common SNPs and prostate cancer risk using cases unselected for family history. How these variants influence risk in familial prostate cancer is not well studied. Here, we analyzed 25 previously reported SNPs across 14 loci from prior prostate cancer GWAS. The International Consortium for Prostate Cancer Genetics (ICPCG) previously validated some of these using a family-based association method (FBAT). However, this approach suffered reduced power due to the conditional statistics implemented in FBAT. Here, we use a case-control design with an empirical analysis strategy to analyze the ICPCG resource for association between these 25 SNPs and familial prostate cancer risk. Fourteen sites contributed 12,506 samples (9,560 prostate cancer cases, 3,368 with aggressive disease, and 2,946 controls from 2,283 pedigrees). We performed association analysis with Genie software which accounts for relationships. We analyzed all familial prostate cancer cases and the subset of aggressive cases. For the familial prostate cancer phenotype, 20 of the 25 SNPs were at least nominally associated with prostate cancer and 16 remained significant after multiple testing correction (p ≤ 1E (-3)) occurring on chromosomal bands 6q25, 7p15, 8q24, 10q11, 11q13, 17q12, 17q24, and Xp11. For aggressive disease, 16 of the SNPs had at least nominal evidence and 8 were statistically significant including 2p15. The results indicate that the majority of common, low-risk alleles identified in GWAS studies for all prostate cancer also contribute risk for familial prostate cancer, and that some may contribute risk to aggressive disease.

A pooled analysis of alcohol consumption and risk of multiple myeloma in the international multiple myeloma consortium

BACKGROUND

Recent findings suggest that alcohol consumption may reduce risk of multiple myeloma.

METHODS

To better understand this relationship, we conducted an analysis of six case-control studies participating in the International Multiple Myeloma Consortium (1,567 cases, 7,296 controls). Summary ORs and 95% confidence intervals (CI) relating different measures of alcohol consumption and multiple myeloma risk were computed by unconditional logistic regression with adjustment for age, race, and study center.

RESULTS

Cases were significantly less likely than controls to report ever drinking alcohol (men: OR = 0.72; 95% CI, 0.59-0.89; women: OR = 0.81; 95% CI, 0.68-0.95). The inverse association with multiple myeloma was stronger when comparing current to never drinkers (men: OR = 0.57; 95% CI, 0.45-0.72; women: OR = 0.55; 95% CI, 0.45-0.68), but null among former drinkers. We did not observe an exposure-response relationship with increasing alcohol frequency, duration, or cumulative lifetime consumption. Additional adjustment for body mass index, education, or smoking did not affect our results; and the patterns of association were similar for each type of alcohol beverage examined.

CONCLUSIONS

Our study is, to our knowledge, the largest of its kind to date, and our findings suggest that alcohol consumption may be associated with reduced risk of multiple myeloma.

IMPACT

Prospective studies, especially those conducted as pooled analyses with large sample sizes, are needed to confirm our findings and further explore whether alcohol consumption provides true biologic protection against this rare, highly fatal malignancy.

Associations of ATR and CHEK1 single nucleotide polymorphisms with breast cancer

DNA damage and replication checkpoints mediated by the ATR-CHEK1 pathway are key to the maintenance of genome stability, and both ATR and CHEK1 have been proposed as potential breast cancer susceptibility genes. Many novel variants recently identified by the large resequencing projects have not yet been thoroughly tested in genome-wide association studies for breast cancer susceptibility. We therefore used a tagging SNP (tagSNP) approach based on recent SNP data available from the 1000 genomes projects, to investigate the roles of ATR and CHEK1 in breast cancer risk and survival. ATR and CHEK1 tagSNPs were genotyped in the Sheffield Breast Cancer Study (SBCS; 1011 cases and 1024 controls) using Illumina GoldenGate assays. Untyped SNPs were imputed using IMPUTE2, and associations between genotype and breast cancer risk and survival were evaluated using logistic and Cox proportional hazard regression models respectively on a per allele basis. Significant associations were further examined in a meta-analysis of published data or confirmed in the Utah Breast Cancer Study (UBCS). The most significant associations for breast cancer risk in SBCS came from rs6805118 in ATR (p=7.6 x 10(-5)) and rs2155388 in CHEK1 (p=3.1 x 10(-6)), but neither remained significant after meta-analysis with other studies. However, meta-analysis of published data revealed a weak association between the ATR SNP rs1802904 (minor allele frequency is 12%) and breast cancer risk, with a summary odds ratio (confidence interval) of 0.90 (0.83-0.98) [p=0.0185] for the minor allele. Further replication of this SNP in larger studies is warranted since it is located in the target region of 2 microRNAs. No evidence of any survival effects of ATR or CHEK1 SNPs were identified. We conclude that common alleles of ATR and CHEK1 are not implicated in breast cancer risk or survival, but we cannot exclude effects of rare alleles and of common alleles with very small effect sizes.

Abstract LB-23: Meta-analysis of genome-wide association studies identifies multiple loci associated with chronic lymphocytic leukemia

Despite limited discovery stages (<1,125 cases), genome-wide association studies (GWAS) have successfully identified 13 loci associated with risk of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL); however, these loci only explain a portion of the heritability. To identify additional genetic loci associated with CLL susceptibility, we conducted the largest meta-analysis of GWAS, to date, including 3,100 CLL cases and 7,667 controls of European ancestry from 25 independent studies genotyped on four different SNP microarrays. Association testing was conducted assuming a log-additive genetic model, adjusting for age, sex, and significant principal components. Meta-analyses were performed using the fixed effects inverse variance method based on the beta estimates and standard errors from each study. Promising loci were taken forward for replication in three additional studies totaling 788 cases and 4,872 controls. In the meta-analysis of both the discovery and replication studies, we conclusively identified ten independent SNPs in nine novel loci that reached genome-wide significance (P<5 x 10−8): 10q23.31 (FAS; P=1.22x10−14), 18q21.33 (BCL2; P=2.66x10−12 and P=7.76x10−11), 11p15.5 (C11orf21; P=2.15x10−10), 4q25 (LEF1; P=4.24x10−10), 2q33.1 (CASP8; P=2.50x10−9), 9p21.3 (CDKN2B-AS1; P=1.27x10−8), 18q21.32 (PMAIP1; P=2.51x10−8), 15q15.1 (BMF; P=2.71x10−10), and 2p22.2 (QPCT; P=1.68x10−8) as well as an independent signal at an established locus (2q13, ACOXL, P=2.08x10−18). We also found evidence for two additional promising loci that reached marginal genome-wide significance (P<2.0x10−7) at 8q22.3 (ODF1; P=5.40x10−8) and 5p15.33 (TERT; P=1.92x10−7). Although further studies are required, the proximity of five of the novel loci to genes involved in apoptosis suggests a possible unifying underlying biological mechanism. Together with the previously established loci, these genetic loci explain ~17% of the familial risk of CLL.

Citation Format: Sonja I. Berndt, Christine F. Skibola, Vijai Joseph, Nicola J. Camp, Alexandra Nieters, Zhaoming Wang, Wendy Cozen, Alain Monnereau, Rachel S. Kelly, Silvia de Sanjose, Martha S. Linet, Elio Riboli, Paolo Vineis, Henrik Hjalgrim, James R. Cerhan, Stephen J. Chanock, Nathaniel Rothman, Susan L. Slager. Meta-analysis of genome-wide association studies identifies multiple loci associated with chronic lymphocytic leukemia. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-23. doi:10.1158/1538-7445.AM2013-LB-23

Mapping of the IRF8 gene identifies a 3'UTR variant associated with risk of chronic lymphocytic leukemia but not other common non-Hodgkin lymphoma subtypes

BACKGROUND

Our genome-wide association study (GWAS) of chronic lymphocytic leukemia (CLL) identified 4 highly correlated intronic variants within the IRF8 gene that were associated with CLL. These results were further supported by a recent meta-analysis of our GWAS with two other GWAS of CLL, supporting the IRF8 gene as a strong candidate for CLL risk.

METHODS

To refine the genetic association of CLL risk, we conducted Sanger sequencing of IRF8 in 94 CLL cases and 96 controls. We then conducted fine mapping by genotyping 39 variants (of which 10 were identified from sequencing) in 745 CLL cases and 1,521 controls. We also assessed these associations with risk of other non-Hodgkin lymphoma (NHL) subtypes.

RESULTS

The strongest association with CLL risk was observed with a common single-nucleotide polymorphism (SNP) located within the 3' untranslated region (UTR) of IRF8 (rs1044873, log additive OR = 0.7, P = 1.81 × 10(-6)). This SNP was not associated with the other NHL subtypes (all P > 0.05).

CONCLUSIONS

We provide evidence that rs1044873 in the IRF8 gene accounts for the initial GWAS signal for CLL risk. This association appears to be unique to CLL with little support for association with other common NHL subtypes. Future work is needed to assess functional role of IRF8 in CLL etiology.

IMPACT

These data provide support that a functional variant within the 3'UTR of IRF8 may be driving the GWAS signal seen on 16q24.1 for CLL risk.

HOXB13 is a susceptibility gene for prostate cancer: results from the International Consortium for Prostate Cancer Genetics (ICPCG)

Prostate cancer has a strong familial component but uncovering the molecular basis for inherited susceptibility for this disease has been challenging. Recently, a rare, recurrent mutation (G84E) in HOXB13 was reported to be associated with prostate cancer risk. Confirmation and characterization of this finding is necessary to potentially translate this information to the clinic. To examine this finding in a large international sample of prostate cancer families, we genotyped this mutation and 14 other SNPs in or flanking HOXB13 in 2,443 prostate cancer families recruited by the International Consortium for Prostate Cancer Genetics (ICPCG). At least one mutation carrier was found in 112 prostate cancer families (4.6 %), all of European descent. Within carrier families, the G84E mutation was more common in men with a diagnosis of prostate cancer (194 of 382, 51 %) than those without (42 of 137, 30 %), P = 9.9 × 10(-8) [odds ratio 4.42 (95 % confidence interval 2.56-7.64)]. A family-based association test found G84E to be significantly over-transmitted from parents to affected offspring (P = 6.5 × 10(-6)). Analysis of markers flanking the G84E mutation indicates that it resides in the same haplotype in 95 % of carriers, consistent with a founder effect. Clinical characteristics of cancers in mutation carriers included features of high-risk disease. These findings demonstrate that the HOXB13 G84E mutation is present in ~5 % of prostate cancer families, predominantly of European descent, and confirm its association with prostate cancer risk. While future studies are needed to more fully define the clinical utility of this observation, this allele and others like it could form the basis for early, targeted screening of men at elevated risk for this common, clinically heterogeneous cancer.

Pairwise shared genomic segment analysis in three Utah high-risk breast cancer pedigrees

Background

We applied a new weighted pairwise shared genomic segment (pSGS) analysis for susceptibility gene localization to high-density genomewide SNP data in three extended high-risk breast cancer pedigrees.

Results

Using this method, four genomewide suggestive regions were identified on chromosomes 2, 4, 7 and 8, and a borderline suggestive region on chromosome 14. Seven additional regions with at least nominal evidence were observed. Of particular note among these total twelve regions were three regions that were identified in two pedigrees each; chromosomes 4, 7 and 14. Follow-up two-pedigree pSGS analyses further indicated excessive genomic sharing across the pedigrees in all three regions, suggesting that the underlying susceptibility alleles in those regions may be shared in common. In general, the pSGS regions identified were quite large (average 32.2 Mb), however, the range was wide (0.3 – 88.2 Mb). Several of the regions identified overlapped with loci and genes that have been previously implicated in breast cancer risk, including NBS1, BRCA1 and RAD51L1.

Conclusions

Our analyses have provided several loci of interest to pursue in these high-risk pedigrees and illustrate the utility of the weighted pSGS method and extended pedigrees for gene mapping in complex diseases. A focused sequencing effort across these loci in the sharing individuals is the natural next step to further map the critical underlying susceptibility variants in these regions.

A family-based paradigm to identify candidate chromosomal regions for isolated congenital diaphragmatic hernia

Congenital diaphragmatic hernia (CDH) is a developmental defect of the diaphragm that causes high newborn mortality. Isolated or non-syndromic CDH is considered a multifactorial disease, with strong evidence implicating genetic factors. As low heritability has been reported in isolated CDH, family-based genetic methods have yet to identify the genetic factors associated with the defect. Using the Utah Population Database, we identified distantly related patients from several extended families with a high incidence of isolated CDH. Using high-density genotyping, seven patients were analyzed by homozygosity exclusion rare allele mapping (HERAM) and phased haplotype sharing (HapShare), two methods we developed to map shared chromosome regions. Our patient cohort shared three regions not previously associated with CDH, that is, 2q11.2-q12.1, 4p13 and 7q11.2, and two regions previously involved in CDH, that is, 8p23.1 and 15q26.2. The latter regions contain GATA4 and NR2F2, two genes implicated in diaphragm formation in mice. Interestingly, three patients shared the 8p23.1 locus and one of them also harbored the 15q26.2 segment. No coding variants were identified in GATA4 or NR2F2, but a rare shared variant was found in intron 1 of GATA4. This work shows the role of heritability in isolated CDH. Our family-based strategy uncovers new chromosomal regions possibly associated with disease, and suggests that non-coding variants of GATA4 and NR2F2 may contribute to the development of isolated CDH. This approach could speed up the discovery of the genes and regulatory elements causing multifactorial diseases, such as isolated CDH.

Shared genomic segment analysis: the power to find rare disease variants

Shared genomic segment (SGS) analysis uses dense single nucleotide polymorphism genotyping in high-risk (HR) pedigrees to identify regions of sharing between cases. Here, we illustrate the power of SGS to identify dominant rare risk variants. Using simulated pedigrees, we consider 12 disease models based on disease prevalence, minor allele frequency and penetrance to represent disease loci that explain 0.2-99.8% of total disease risk. Pedigrees were required to contain ≥ 15 meioses between all cases and to be HR based on significant excess of disease (P < 0.001 or P < 0.00001). Across these scenarios, the power for a single pedigree ranged widely. Nonetheless, fewer than 10 pedigrees were sufficient for excellent power in the majority of models. Power increased with the risk attributable to the disease locus, penetrance and the excess of disease in the pedigree. Sharing allowing for one sporadic case was uniformly more powerful than sharing using all cases. Furthermore, an SGS analysis using a large attenuated familial adenomatous polyposis pedigree identified a 1.96 Mb region containing the known causal APC gene with genome-wide significance. SGS is a powerful method for detecting rare variants and a valuable complement to genome-wide association studies and linkage analysis.

Common variants within 6p21.31 locus are associated with chronic lymphocytic leukaemia and, potentially, other non-Hodgkin lymphoma subtypes

A recent meta-analysis of three genome-wide association studies of chronic lymphocytic leukaemia (CLL) identified two common variants at the 6p21.31 locus that are associated with CLL risk. To verify and further explore the association of these variants with other non-Hodgkin lymphoma (NHL) subtypes, we genotyped 1196 CLL cases, 1699 NHL cases, and 2410 controls. We found significant associations between the 6p21.31 variants and CLL risk (rs210134: P = 0·01; rs210142: P = 6·8 × 10(-3)). These variants also showed a trend towards association with some of the other NHL subtypes. Our results validate the prior work and support specific genetic pathways for risk among NHL subtypes.

Validation of prostate cancer risk-related loci identified from genome-wide association studies using family-based association analysis: evidence from the International Consortium for Prostate Cancer Genetics (ICPCG)

Multiple prostate cancer (PCa) risk-related loci have been discovered by genome-wide association studies (GWAS) based on case-control designs. However, GWAS findings may be confounded by population stratification if cases and controls are inadvertently drawn from different genetic backgrounds. In addition, since these loci were identified in cases with predominantly sporadic disease, little is known about their relationships with hereditary prostate cancer (HPC). The association between seventeen reported PCa susceptibility loci was evaluated with a family-based association test using 1,979 hereditary PCa families of European descent collected by members of the International Consortium for Prostate Cancer Genetics, with a total of 5,730 affected men. The risk alleles for 8 of the 17 loci were significantly over-transmitted from parents to affected offspring, including SNPs residing in 8q24 (regions 1, 2 and 3), 10q11, 11q13, 17q12 (region 1), 17q24 and Xp11. In subgroup analyses, three loci, at 8q24 (regions 1 and 2) plus 17q12, were significantly over-transmitted in hereditary PCa families with five or more affected members, while loci at 3p12, 8q24 (region 2), 11q13, 17q12 (region 1), 17q24 and Xp11 were significantly over-transmitted in HPC families with an average age of diagnosis at 65 years or less. Our results indicate that at least a subset of PCa risk-related loci identified by case-control GWAS are also associated with disease risk in HPC families.

Analysis of Xq27-28 linkage in the international consortium for prostate cancer genetics (ICPCG) families

BACKGROUND

Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive.

METHODS

Parametric and non-parametric linkage analyses were performed using 26 microsatellite markers in each of 11 groups of multiple-case prostate cancer families from the International Consortium for Prostate Cancer Genetics (ICPCG). Meta-analyses of the resultant family-specific linkage statistics across the entire 1,323 families and in several predefined subsets were then performed.

RESULTS

Meta-analyses of linkage statistics resulted in a maximum parametric heterogeneity lod score (HLOD) of 1.28, and an allele-sharing lod score (LOD) of 2.0 in favor of linkage to Xq27-q28 at 138 cM. In subset analyses, families with average age at onset less than 65 years exhibited a maximum HLOD of 1.8 (at 138 cM) versus a maximum regional HLOD of only 0.32 in families with average age at onset of 65 years or older. Surprisingly, the subset of families with only 2-3 affected men and some evidence of male-to-male transmission of prostate cancer gave the strongest evidence of linkage to the region (HLOD = 3.24, 134 cM). For this subset, the HLOD was slightly increased (HLOD = 3.47 at 134 cM) when families used in the original published report of linkage to Xq27-28 were excluded.

CONCLUSIONS

Although there was not strong support for linkage to the Xq27-28 region in the complete set of families, the subset of families with earlier age at onset exhibited more evidence of linkage than families with later onset of disease. A subset of families with 2-3 affected individuals and with some evidence of male to male disease transmission showed stronger linkage signals. Our results suggest that the genetic basis for prostate cancer in our families is much more complex than a single susceptibility locus on the X chromosome, and that future explorations of the Xq27-28 region should focus on the subset of families identified here with the strongest evidence of linkage to this region.

Chromosomes 4 and 8 implicated in a genome wide SNP linkage scan of 762 prostate cancer families collected by the ICPCG

BACKGROUND

In spite of intensive efforts, understanding of the genetic aspects of familial prostate cancer (PC) remains largely incomplete. In a previous microsatellite-based linkage scan of 1,233 PC families, we identified suggestive evidence for linkage (i.e., LOD ≥ 1.86) at 5q12, 15q11, 17q21, 22q12, and two loci on 8p, with additional regions implicated in subsets of families defined by age at diagnosis, disease aggressiveness, or number of affected members.

METHODS

In an attempt to replicate these findings and increase linkage resolution, we used the Illumina 6000 SNP linkage panel to perform a genome-wide linkage scan of an independent set of 762 multiplex PC families, collected by 11 International Consortium for Prostate Cancer Genetics (ICPCG) groups.

RESULTS

Of the regions identified previously, modest evidence of replication was observed only on the short arm of chromosome 8, where HLOD scores of 1.63 and 3.60 were observed in the complete set of families and families with young average age at diagnosis, respectively. The most significant linkage signals found in the complete set of families were observed across a broad, 37 cM interval on 4q13-25, with LOD scores ranging from 2.02 to 2.62, increasing to 4.50 in families with older average age at diagnosis. In families with multiple cases presenting with more aggressive disease, LOD scores over 3.0 were observed at 8q24 in the vicinity of previously identified common PC risk variants, as well as MYC, an important gene in PC biology.

CONCLUSIONS

These results will be useful in prioritizing future susceptibility gene discovery efforts in this common cancer.

Pairwise shared genomic segment analysis in high-risk pedigrees: application to Genetic Analysis Workshop 17 exome-sequencing SNP data

We applied our method of pairwise shared genomic segment (pSGS) analysis to high-risk pedigrees identified from the Genetic Analysis Workshop 17 (GAW17) mini-exome sequencing data set. The original shared genomic segment method focused on identifying regions shared by all case subjects in a pedigree; thus it can be sensitive to sporadic cases. Our new method examines sharing among all pairs of case subjects in a high-risk pedigree and then uses the mean sharing as the test statistic; in addition, the significance is assessed empirically based on the pedigree structure and linkage disequilibrium pattern of the single-nucleotide polymorphisms. Using all GAW17 replicates, we identified 18 unilineal high-risk pedigrees that contained excess disease (p < 0.01) and at least 15 meioses between case subjects. Eighteen rare causal variants were polymorphic in this set of pedigrees. Based on a significance threshold of 0.001, 72.2% (13/18) of these pedigrees were successfully identified with at least one region that contains a true causal variant. The regions identified included 4 of the possible 18 polymorphic causal variants. On average, 1.1 true positives and 1.7 false positives were identified per pedigree. In conclusion, we have demonstrated the potential of our new pSGS method for localizing rare disease causal variants in common disease using high-risk pedigrees and exome sequence data.

A comprehensive study of polymorphisms in the ABCB1, ABCC2, ABCG2, NR1I2 genes and lymphoma risk

Owing to their role in controlling the efflux of toxic compounds, transporters are central players in the process of detoxification and elimination of xenobiotics, which in turn is related to cancer risk. Among these transporters, ATP-binding cassette B1/multidrug resistance 1 (ABCB1/MDR1), ABCC2/multidrug resistance protein 2 (MRP2) and ABCG2/breast cancer resistance protein (BCRP) affect susceptibility to many hematopoietic malignancies. The maintenance of regulated expression of these transporters is governed through the activation of intracellular "xenosensors" like the nuclear receptor 1I2/pregnane X receptor (NR1I2/PXR). SNPs in genes encoding these regulators have also been implicated in the risk of several cancers. Using a tagging approach, we tested the hypothesis that common polymorphisms in the transporter genes ABCB1, ABCC2, ABCG2 and the regulator gene NR1I2 could be implicated in lymphoma risk. We selected 68 SNPs in the four genes, and we genotyped them in 1,481 lymphoma cases and 1,491 controls of the European case-control study (EpiLymph) using the Illumina GoldenGate™ assay technology. Carriers of the SNP rs6857600 minor allele in ABCG2 was associated with a decrease in risk of B-cell lymphoma (B-NHL) overall (p < 0.001). Furthermore, a decreased risk of chronic lymphocytic leukemia (CLL) was associated with the ABCG2 rs2231142 variant (p = 0.0004), which could be replicated in an independent population. These results suggest a role for this gene in B-NHL susceptibility, especially for CLL.

Fine-mapping CASP8 risk variants in breast cancer

BACKGROUND

Multiple genome-wide and candidate gene association studies have been conducted in search of common risk variants for breast cancer. Recent large meta analyses, consolidating evidence from these studies, have been consistent in highlighting the caspase-8 (CASP8) gene as important in this regard. To define a risk haplotype and map the CASP8 gene region with respect to underlying susceptibility variant/s, we screened four genes in the CASP8 region on 2q33-q34 for breast cancer risk.

METHODS

Two independent data sets from the United Kingdom and the United States, including 3,888 breast cancer cases and controls, were genotyped for 45 tagging single nucleotide polymorphisms (tSNP) in the expanded CASP8 region. SNP and haplotype association tests were carried out using Monte Carlo-based methods.

RESULTS

We identified a three-SNP haplotype across rs3834129, rs6723097, and rs3817578 that was significantly associated with breast cancer (P < 5 × 10(-6)), with a dominant risk ratio and 95% CI of 1.28 (1.21-1.35) and frequency of 0.29 in controls. Evidence for this risk haplotype was extremely consistent across the two study sites and also consistent with previous data.

CONCLUSION

This three-SNP risk haplotype represents the best characterization so far of the chromosome upon which the susceptibility variant resides.

IMPACT

Characterization of the risk haplotype provides a strong foundation for resequencing efforts to identify the underlying risk variant, which may prove useful for individual-level risk prediction, and provide novel insights into breast carcinogenesis.

A role for XRCC2 gene polymorphisms in breast cancer risk and survival

BACKGROUND

The XRCC2 gene is a key mediator in the homologous recombination repair of DNA double strand breaks. It is hypothesised that inherited variants in the XRCC2 gene might also affect susceptibility to, and survival from, breast cancer.

METHODS

The study genotyped 12 XRCC2 tagging single nucleotide polymorphisms (SNPs) in 1131 breast cancer cases and 1148 controls from the Sheffield Breast Cancer Study (SBCS), and examined their associations with breast cancer risk and survival by estimating ORs and HRs, and their corresponding 95% CIs. Positive findings were further investigated in 860 cases and 869 controls from the Utah Breast Cancer Study (UBCS) and jointly analysed together with available published data for breast cancer risk. The survival findings were further confirmed in studies (8074 cases) from the Breast Cancer Association Consortium (BCAC).

RESULTS

The most significant association with breast cancer risk in the SBCS dataset was the XRCC2 rs3218408 SNP (recessive model p=2.3×10(-4), minor allele frequency (MAF)=0.23). This SNP yielded an OR(rec) of 1.64 (95% CI 1.25 to 2.16) in a two-site analysis of SBCS and UBCS, and a meta-OR(rec) of 1.33 (95% CI 1.12 to 1.57) when all published data were included. This SNP may mark a rare risk haplotype carried by two in 1000 of the control population. Furthermore, the XRCC2 coding R188H SNP (rs3218536, MAF=0.08) was significantly associated with poor survival, with an increased per-allele HR of 1.58 (95% CI 1.01 to 2.49) in a multivariate analysis. This effect was still evident in a pooled meta-analysis of 8781 breast cancer patients from the BCAC (HR 1.19, 95% CI 1.05 to 1.36; p=0.01).

CONCLUSIONS

These findings suggest that XRCC2 SNPs may influence breast cancer risk and survival.

National Cancer Institute Prostate Cancer Genetics Workshop

Compelling evidence supports a genetic component to prostate cancer susceptibility and aggressiveness. Recent genome-wide association studies have identified more than 30 single-nucleotide polymorphisms associated with prostate cancer susceptibility. It remains unclear, however, whether such genetic variants are associated with disease aggressiveness--one of the most important questions in prostate cancer research today. To help clarify this and substantially expand research in the genetic determinants of prostate cancer aggressiveness, the first National Cancer Institute Prostate Cancer Genetics Workshop assembled researchers to develop plans for a large new research consortium and patient cohort. The workshop reviewed the prior work in this area and addressed the practical issues in planning future studies. With new DNA sequencing technology, the potential application of sequencing information to patient care is emerging. The workshop, therefore, included state-of-the-art presentations by experts on new genotyping technologies, including sequencing and associated bioinformatics issues, which are just beginning to be applied to cancer genetics.

Genetic distance and markers used in linkage mapping

In this chapter, we focus on maps and markers used for a linkage analysis. More detail regarding the actual linkage analysis methodology follows in Chapter 11. There are two major types of maps: genetic maps and physical maps. Genetic maps indicate the expected number of meiotic crossover events between two loci on a chromosome and are measured in centiMorgans (cM). Physical maps use molecular techniques, such as DNA sequencing, to determine the location of markers on a chromosome and are measured in base pairs (bp). Linkage analysis relies on genetic maps, and hence they are discussed in this chapter. In addition to a discussion of genetic maps and various map functions, we also discuss the selection of markers for a linkage analysis, including the more traditional microsatellite markers and the newer single nucleotide polymorphism (SNP) markers.

Validity and power of association testing in family-based sampling designs: evidence for and against the common wisdom

Current common wisdom posits that association analyses using family-based designs have inflated type 1 error rates (if relationships are ignored) and independent controls are more powerful than familial controls. We explore these suppositions. We show theoretically that family-based designs can have deflated type-error rates. Through simulation, we examine the validity and power of family designs for several scenarios: cases from randomly or selectively ascertained pedigrees; and familial or independent controls. Family structures considered are as follows: sibships, nuclear families, moderate-sized and extended pedigrees. Three methods were considered with the χ(2) test for trend: variance correction (VC), weighted (weights assigned to account for genetic similarity), and naïve (ignoring relatedness) as well as the Modified Quasi-likelihood Score (MQLS) test. Selectively ascertained pedigrees had similar levels of disease enrichment; random ascertainment had no such restriction. Data for 1,000 cases and 1,000 controls were created under the null and alternate models. The VC and MQLS methods were always valid. The naïve method was anti-conservative if independent controls were used and valid or conservative in designs with familial controls. The weighted association method was generally valid for independent controls, and was conservative for familial controls. With regard to power, independent controls were more powerful for small-to-moderate selectively ascertained pedigrees, but familial and independent controls were equivalent in the extended pedigrees and familial controls were consistently more powerful for all randomly ascertained pedigrees. These results suggest a more complex situation than previously assumed, which has important implications for study design and analysis.