Awareness and use of genetic testing: An analysis of the Health Information National Trends Survey 2020

PURPOSE

Genetic testing is a tool used in a variety of settings for medical and nonhealth related purposes. The goal of this analysis was to better understand the awareness and use of genetic testing in the United States.

METHODS

Data from the 2020 Health Information National Trends Survey 5 cycle 4 were used to assess the awareness and use of genetic testing by demographic characteristics, personal cancer history, and family cancer history.

RESULTS

Overall, 75% of participants were aware of genetic testing and 19% of participants had genetic testing. Ancestry testing was the most common type of testing that the participants were aware of and had received. Non-Hispanic Asian, Non-Hispanic Black, and Hispanic respondents and participants with incomes less than $20,000 were less likely to be aware of and have received any type of genetic testing than the Non-Hispanic White participants and participants with higher income, respectively. Participants with a family history of cancer were more likely to be aware of cancer genetic testing than those without, and participants with a personal history of cancer were more likely to have had cancer genetic testing.

CONCLUSION

It appears awareness of genetic testing is increasing in the United States, and differences in awareness persist by race/ethnicity and income.

Facilitating cancer systems epidemiology research

Systems epidemiology offers a more comprehensive and holistic approach to studies of cancer in populations by considering high dimensionality measures from multiple domains, assessing the inter-relationships among risk factors, and considering changes over time. These approaches offer a framework to account for the complexity of cancer and contribute to a broader understanding of the disease. Therefore, NCI sponsored a workshop in February 2019 to facilitate discussion about the opportunities and challenges of the application of systems epidemiology approaches for cancer research. Eight key themes emerged from the discussion: transdisciplinary collaboration and a problem-based approach; methods and modeling considerations; interpretation, validation, and evaluation of models; data needs and opportunities; sharing of data and models; enhanced training practices; dissemination of systems models; and building a systems epidemiology community. This manuscript summarizes these themes, highlights opportunities for cancer systems epidemiology research, outlines ways to foster this research area, and introduces a collection of papers, "Cancer System Epidemiology Insights and Future Opportunities" that highlight findings based on systems epidemiology approaches.

Systems epidemiology and cancer: A review of the National Institutes of Health extramural grant portfolio 2013-2018

OBJECTIVES

Systems epidemiology approaches may lead to a better understanding of the complex and dynamic multi-level constellation of contributors to cancer risk and outcomes and help target interventions. This grant portfolio analysis aimed to describe the National Institutes of Health (NIH) and the National Cancer Institute (NCI) investments in systems epidemiology and to identify gaps in the cancer systems epidemiology portfolio.

METHODS

The analysis examined grants funded (2013-2018) through seven NIH systems science Funding Opportunity Announcements (FOAs) as well as cancer-specific systems epidemiology grants funded by NCI during that same time. Study characteristics were extracted from the grant abstracts and specific aims and coded.

RESULTS

Of the 137 grants awarded under the NIH FOAs, 52 (38%) included systems epidemiology. Only five (4%) were focused on cancer systems epidemiology. The NCI-wide search (N = 453 grants) identified 35 grants (8%) that included cancer systems epidemiology in their specific aims. Most of these grants examined epidemiology and surveillance-based questions (60%); fewer addressed clinical care or clinical trials (37%). Fifty-four percent looked at multiple scales within the individual (e.g., cell, tissue, organ), 49% looked beyond the individual (e.g., individual, community, population), and few (9%) included both. Across all grants examined, the systems epidemiology grants primarily focused on discovery or prediction, rather than on impacts of intervention or policy.

CONCLUSIONS

The most notable finding was that grants focused on cancer versus other diseases reflected a small percentage of the portfolio, highlighting the need to encourage more cancer systems epidemiology research. Opportunities include encouraging more multiscale research and continuing the support for broad examination of domains in these studies. Finally, the nascent discipline of systems epidemiology could benefit from the creation of standard terminology and definitions to guide future progress.

Epidemiologic Research of Rare Cancers: Trends, Resources, and Challenges

BACKGROUND

The goals of this project were to assess the status of NCI's rare cancer-focused population science research managed by the Division of Cancer Control and Population Sciences (DCCPS), to develop a framework for evaluation of rare cancer research activities, and to review available resources to study rare cancers.

METHODS

Cancer types with an overall age-adjusted incidence rate of less than 20 cases per 100,000 individuals were identified using NCI Surveillance, Epidemiology and End Results (SEER) Program data. SEER data were utilized to develop a framework based on statistical commonalities. A portfolio analysis of DCCPS-supported active grants and a review of three genomic databases were conducted.

RESULTS

For the 45 rare cancer types included in the analysis, 123 active DCCPS-supported rare cancer-focused grants were identified, of which the highest percentage (18.7%) focused on ovarian cancer. The developed framework revealed five clusters of rare cancer types. The cluster with the highest number of grants (n = 43) and grants per cancer type (10.8) was the cluster that included cancer types of higher incidence, average to better survival, and high prevalence (in comparison with other rare cancers). Resource review revealed rare cancers are represented in available genomic resources, but to a lesser extent compared with more common cancers.

CONCLUSIONS

This article provides an overview of the rare cancer-focused population sciences research landscape as well as information on gaps and opportunities.

IMPACT

The findings of this article can be used to develop efficient and comprehensive strategies to accelerate rare cancer research.See related commentary by James V. Lacey Jr, p. 1300.

Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

A Systematic Literature Review of Whole Exome and Genome Sequencing Population Studies of Genetic Susceptibility to Cancer

The application of next-generation sequencing (NGS) technologies in cancer research has accelerated the discovery of somatic mutations; however, progress in the identification of germline variation associated with cancer risk is less clear. We conducted a systematic literature review of cancer genetic susceptibility studies that used NGS technologies at an exome/genome-wide scale to obtain a fuller understanding of the research landscape to date and to inform future studies. The variability across studies on methodologies and reporting was considerable. Most studies sequenced few high-risk (mainly European) families, used a candidate analysis approach, and identified potential cancer-related germline variants or genes in a small fraction of the sequenced cancer cases. This review highlights the importance of establishing consensus on standards for the application and reporting of variants filtering strategies. It also describes the progress in the identification of cancer-related germline variation to date. These findings point to the untapped potential in conducting studies with appropriately sized and racially diverse families and populations, combining results across studies and expanding beyond a candidate analysis approach to advance the discovery of genetic variation that accounts for the unexplained cancer heritability.

Genome-wide association meta-analyses combining multiple risk phenotypes provide insights into the genetic architecture of cutaneous melanoma susceptibility

Most genetic susceptibility to cutaneous melanoma remains to be discovered. Meta-analysis genome-wide association study (GWAS) of 36,760 cases of melanoma (67% newly genotyped) and 375,188 controls identified 54 significant (P < 5 × 10-8) loci with 68 independent single nucleotide polymorphisms. Analysis of risk estimates across geographical regions and host factors suggests the acral melanoma subtype is uniquely unrelated to pigmentation. Combining this meta-analysis with GWAS of nevus count and hair color, and transcriptome association approaches, uncovered 31 potential secondary loci for a total of 85 cutaneous melanoma susceptibility loci. These findings provide insights into cutaneous melanoma genetic architecture, reinforcing the importance of nevogenesis, pigmentation and telomere maintenance, together with identifying potential new pathways for cutaneous melanoma pathogenesis.

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.

It is unclear how often genetic mosaicism of chromosome X arises. Here, the authors examine women with cancer and cancer-free controls and show that X chromosome mosaicism occurs more frequently than on autosomes, especially on the inactive X chromosome, but is not linked to non-haematologic cancer risk

Genome-wide association study confirms lung cancer susceptibility loci on chromosomes 5p15 and 15q25 in an African-American population

OBJECTIVES

Genome-wide association studies (GWAS) of lung cancer have identified regions of common genetic variation with lung cancer risk in Europeans who smoke and never-smoking Asian women. This study aimed to conduct a GWAS in African Americans, who have higher rates of lung cancer despite smoking fewer cigarettes per day when compared with Caucasians. This population provides a different genetic architecture based on underlying African ancestry allowing the identification of new regions and exploration of known regions for finer mapping.

MATERIALS AND METHODS

We genotyped 1,024,001 SNPs in 1737 cases and 3602 controls in stage 1, followed by a replication phase of 20 SNPs (p<1.51×10(-5)) in an independent set of 866 cases and 796 controls in stage 2.

RESULTS AND CONCLUSION

In the combined analysis, we confirmed two loci to be associated with lung cancer that achieved the threshold of genome-wide significance: 15q25.1 marked by rs2036527 (p=1.3×10(-9); OR=1.32; 95% CI=1.20-1.44) near CHRNA5, and 5p15.33 marked by rs2853677 (p=2.8×10(-9); OR=1.28; 95% CI=1.18-1.39) near TERT. The association with rs2853677 is driven by the adenocarcinoma subtype of lung cancer (p=1.3×10(-8); OR=1.37; 95% CI=1.23-1.54). No SNPs reached genome-wide significance for either of the main effect models examining smoking - cigarettes per day and current or former smoker. Our study was powered to identify strong risk loci for lung cancer in African Americans; we confirmed results previously reported in African Americans and other populations for two loci near plausible candidate genes, CHRNA5 and TERT, on 15q25.1 and 5p15.33 respectively, are associated with lung cancer. Additional work is required to map and understand the biological underpinnings of the strong association of these loci with lung cancer risk in African Americans.

Multiple Myeloma Mortality in Relation to Obesity Among African Americans

Multiple myeloma (MM) incidence and mortality are higher among African Americans (AAs) than among other population groups. The prevalence of obesity is also elevated among AAs, but few studies have examined risk of this cancer in relation to body size among AAs. We combined data from seven prospective cohorts tracking mortality among 239 597 AA adults and used Cox proportional hazards regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for death because of MM according to body mass index (BMI) at cohort entry, adjusted for age (as time-scale) and sex. Relative to those with normal BMIs (18.5-25 kg/m(2)), mortality increased monotonically as BMI increased, with hazard ratios reaching 1.43 (95% CI = 1.03 to 1.97) for BMIs of 35 kg/m(2) or greater. The findings suggest that obesity is a risk factor for MM and a contributor to the elevated rates and rising incidence trends of MM among AAs in the United States.

Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?

BACKGROUND

Risk of cancer is determined by a complex interplay of genetic and environmental factors. Although the study of gene-environment interactions (G×E) has been an active area of research, little is reported about the known findings in the literature.

METHODS

To examine the state of the science in G×E research in cancer, we performed a systematic review of published literature using gene-environment or pharmacogenomic flags from two curated databases of genetic association studies, the Human Genome Epidemiology (HuGE) literature finder and Cancer Genome-Wide Association and Meta Analyses Database (CancerGAMAdb), from January 1, 2001, to January 31, 2011. A supplemental search using HuGE was conducted for articles published from February 1, 2011, to April 11, 2013. A 25% sample of the supplemental publications was reviewed.

RESULTS

A total of 3,019 articles were identified in the original search. From these articles, 243 articles were determined to be relevant based on inclusion criteria (more than 3,500 interactions). From the supplemental search (1,400 articles identified), 29 additional relevant articles (1,370 interactions) were included. The majority of publications in both searches examined G×E in colon, rectal, or colorectal; breast; or lung cancer. Specific interactions examined most frequently included environmental factors categorized as energy balance (e.g., body mass index, diet), exogenous (e.g., oral contraceptives) and endogenous hormones (e.g., menopausal status), chemical environment (e.g., grilled meats), and lifestyle (e.g., smoking, alcohol intake). In both searches, the majority of interactions examined were using loci from candidate genes studies and none of the studies were genome-wide interaction studies (GEWIS). The most commonly reported measure was the interaction P-value, of which a sizable number of P-values were considered statistically significant (i.e., <0.05). In addition, the magnitude of interactions reported was modest.

CONCLUSION

Observations of published literature suggest that opportunity exists for increased sample size in G×E research, including GWAS-identified loci in G×E studies, exploring more GWAS approaches in G×E such as GEWIS, and improving the reporting of G×E findings.

Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma

Thirteen common susceptibility loci have been reproducibly associated with cutaneous malignant melanoma (CMM). We report the results of an international 2-stage meta-analysis of CMM genome-wide association studies (GWAS). This meta-analysis combines 11 GWAS (5 previously unpublished) and a further three stage 2 data sets, totaling 15,990 CMM cases and 26,409 controls. Five loci not previously associated with CMM risk reached genome-wide significance (P < 5 × 10(-8)), as did 2 previously reported but unreplicated loci and all 13 established loci. Newly associated SNPs fall within putative melanocyte regulatory elements, and bioinformatic and expression quantitative trait locus (eQTL) data highlight candidate genes in the associated regions, including one involved in telomere biology.

Robustness of Next Generation Sequencing on Older Formalin-Fixed Paraffin-Embedded Tissue

Next Generation Sequencing (NGS) technologies are used to detect somatic mutations in tumors and study germ line variation. Most NGS studies use DNA isolated from whole blood or fresh frozen tissue. However, formalin-fixed paraffin-embedded (FFPE) tissues are one of the most widely available clinical specimens. Their potential utility as a source of DNA for NGS would greatly enhance population-based cancer studies. While preliminary studies suggest FFPE tissue may be used for NGS, the feasibility of using archived FFPE specimens in population based studies and the effect of storage time on these specimens needs to be determined. We conducted a study to determine whether DNA in archived FFPE high-grade ovarian serous adenocarcinomas from Surveillance, Epidemiology and End Results (SEER) registries Residual Tissue Repositories (RTR) was present in sufficient quantity and quality for NGS assays. Fifty-nine FFPE tissues, stored from 3 to 32 years, were obtained from three SEER RTR sites. DNA was extracted, quantified, quality assessed, and subjected to whole exome sequencing (WES). Following DNA extraction, 58 of 59 specimens (98%) yielded DNA and moved on to the library generation step followed by WES. Specimens stored for longer periods of time had significantly lower coverage of the target region (6% lower per 10 years, 95% CI: 3-10%) and lower average read depth (40x lower per 10 years, 95% CI: 18-60), although sufficient quality and quantity of WES data was obtained for data mining. Overall, 90% (53/59) of specimens provided usable NGS data regardless of storage time. This feasibility study demonstrates FFPE specimens acquired from SEER registries after varying lengths of storage time and under varying storage conditions are a promising source of DNA for NGS.

Prevalence and correlates of receiving and sharing high-penetrance cancer genetic test results: findings from the Health Information National Trends Survey

BACKGROUND/AIMS

The aim of this study was to explore the prevalence and correlates of receiving and sharing high-penetrance cancer genetic test results.

METHODS

Participants completed the population-based, cross-sectional 2013 Health Information National Trends Survey. We examined sociodemographic characteristics of participants reporting having had BRCA1/2 or Lynch syndrome genetic testing, and sociodemographic and psychosocial correlates of sharing test results with health professionals and family members.

RESULTS

Participants who underwent BRCA1/2 or Lynch syndrome genetic testing (n = 77; 2.42% of respondents) were more likely to be female and to have a family or personal history of cancer than those not undergoing testing. Approximately three-quarters of participants shared results with health professionals and three-quarters with their family; only 4% did not share results with anyone. Participants who shared results with health professionals reported greater optimism, self-efficacy for health management, and trust in information from their doctors. Participants who shared results with their family were more likely to be female and to have a personal history of cancer, and had greater self-efficacy for health management, perceived less ambiguity in cancer prevention recommendations, and lower cancer prevention fatalism.

CONCLUSIONS

We identified several novel psychosocial correlates of sharing genetic information. Health professionals may use this information to identify patients less likely to share information with at-risk family members.

The use of biospecimens in population-based research: a review of the National Cancer Institute's Division of Cancer Control and Population Sciences grant portfolio

Over the past two decades, researchers have increasingly used human biospecimens to evaluate hypotheses related to disease risk, outcomes and treatment. We conducted an analysis of population-science cancer research grants funded by the National Cancer Institute (NCI) to gain a more comprehensive understanding of biospecimens and common derivatives involved in those studies and identify opportunities for advancing the field. Data available for 1,018 extramural, peer-reviewed grants (active as of July 2012) supported by the Division of Cancer Control and Population Sciences (DCCPS), the NCI Division that supports cancer control and population-science extramural research grants, were analyzed. 455 of the grants were determined to involve biospecimens or derivatives. The most common specimen types included were whole blood (51% of grants), serum or plasma (40%), tissue (39%), and the biospecimen derivative, DNA (66%). While use of biospecimens in molecular epidemiology has become common, biospecimens for behavioral and social research is emerging, as observed in our analysis. Additionally, we found the majority of grants were using already existing biospecimens (63%). Grants that involved use of existing biospecimens resulted in lower costs (studies that used existing serum/plasma biospecimens were 4.2 times less expensive) and more publications per year (1.4 times) than grants collecting new biospecimens. This analysis serves as a first step at understanding the types of biospecimen collections supported by NCI DCCPS. There is room to encourage increased use of archived biospecimens and new collections of rarer specimen and cancer types, as well as for behavioral and social research. To facilitate these efforts, we are working to better catalogue our funded resources and make that data available to the extramural community.

Fine mapping of genetic susceptibility loci for melanoma reveals a mixture of single variant and multiple variant regions

At least 17 genomic regions are established as harboring melanoma susceptibility variants, in most instances with genome-wide levels of significance and replication in independent samples. Based on genome-wide single nucleotide polymorphism (SNP) data augmented by imputation to the 1,000 Genomes reference panel, we have fine mapped these regions in over 5,000 individuals with melanoma (mainly from the GenoMEL consortium) and over 7,000 ethnically matched controls. A penalized regression approach was used to discover those SNP markers that most parsimoniously explain the observed association in each genomic region. For the majority of the regions, the signal is best explained by a single SNP, which sometimes, as in the tyrosinase region, is a known functional variant. However in five regions the explanation is more complex. At the CDKN2A locus, for example, there is strong evidence that not only multiple SNPs but also multiple genes are involved. Our results illustrate the variability in the biology underlying genome-wide susceptibility loci and make steps toward accounting for some of the "missing heritability."

Characterization of large structural genetic mosaicism in human autosomes

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.

Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33

Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.

Genetic simulation tools for post-genome wide association studies of complex diseases

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled "Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases" at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to (1) identify opportunities, challenges, and resource needs for the development and application of genetic simulation models; (2) improve the integration of tools for modeling and analysis of simulated data; and (3) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting, the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation.

Abstract 307: The use of biospecimens in cancer population science research

Background: Over the past two decades, researchers have increasingly used human biospecimens to help evaluate hypotheses related to disease risk, outcomes and treatment options. We conducted an analysis of the population science cancer research grants funded by NCI in order to gain a more comprehensive understanding of the biospecimens involved in those studies. Recognizing that there are many pre-existing collections of biospecimens, we investigated the cost and time efficiencies observed with studies involving the use of existing biospecimens versus collecting new specimens. Methods: Data available for 1,018 extramural, peer-reviewed grants (active as of July 2012) supported by the Division of Cancer Control and Population Sciences, (NCI Division that supports cancer control and population science extramural research grants) were analyzed. Results: 455 of the grants were determined to involve biospecimens. The most common specimen types included were DNA (66% of grants involved DNA), whole blood (51%), serum or plasma (40%), and tissue (39%). Grants that involved the use of existing biospecimens resulted in greater cost (serum/plasma studies were 4.2 times less expensive) and time efficiencies (1.4 times more publications per year resulted) than grants that collected new biospecimens. Conclusions: Clearly, there is an opportunity for NCI to promote future sharing. We are currently working to better catalogue our funded resources and make data available to the extramural community. Further work is being done to investigate possible trends based on year of grant award.

Citation Format: Danielle M. Carrick, Eliza Mette, Brittany Hoyle, Scott D. Rogers, Elizabeth M. Gillanders, Sheri D. Schully, Leah E. Mechanic. The use of biospecimens in cancer population science research. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 307. doi:10.1158/1538-7445.AM2014-307

The effect on melanoma risk of genes previously associated with telomere length

Telomere length has been associated with risk of many cancers, but results are inconsistent. Seven single nucleotide polymorphisms (SNPs) previously associated with mean leukocyte telomere length were either genotyped or well-imputed in 11108 case patients and 13933 control patients from Europe, Israel, the United States and Australia, four of the seven SNPs reached a P value under .05 (two-sided). A genetic score that predicts telomere length, derived from these seven SNPs, is strongly associated (P = 8.92x10(-9), two-sided) with melanoma risk. This demonstrates that the previously observed association between longer telomere length and increased melanoma risk is not attributable to confounding via shared environmental effects (such as ultraviolet exposure) or reverse causality. We provide the first proof that multiple germline genetic determinants of telomere length influence cancer risk.

Abstract 304: Feasibility study of next-generation sequencing on residual formalin-fixed paraffin-embedded tissues

Next Generation Sequencing (NGS) technologies are being used for detection of somatic mutations in tumors and studies of germline variation. However, most NGS studies used DNA isolated either from whole blood or fresh frozen tissue specimens. Meanwhile, the tissue specimens available from most National Cancer Institute (NCI) funded cohorts and the Surveillance, Epidemiology and End Results (SEER) registries (http://seer.cancer.gov/biospecimen/) are primarily formalin fixed paraffin embedded (FFPE). There are limited data, on a small number of FFPE tissue samples, which suggest NGS is feasible. Much less is known about the feasibility of these technologies for large scale studies or using older FFPE specimens (e.g. 5-30 years old).

The main objective of this project was to conduct a pilot study to determine whether the DNA obtained from archival FFPE tissue is of sufficient quality and quantity to conduct NGS. Sixty high-grade serous ovarian adenocarcinomas from FFPE tissues which were between 7 and 31 years old were obtained from three SEER registries. DNA was extracted, quantified, quality assessed, and subjected to whole exome sequencing. DNA extraction (yields and quality) and whole exome sequencing (depths of coverage and exome coverage obtained) results from this study will be presented. Ultimately, data derived from this analysis could serve as the basis for determining the utility of archival FFPE biospecimens for characterization and discovery projects utilizing NGS technologies instead of relying on frozen biospecimens.

Citation Format: Danielle Mercatante Carrick, Sean Altekruse, Corrine Camalier, Wendy Cozen, Brenda Hernandez, Charles Lynch, Paul McGregor, Michele G. Mehaffey, Lisa McShane, JoyAnn Phillips Rohan, Mickey Williams, Elizabeth M. Gillanders, Leah E. Mechanic, Sheri Schully. Feasibility study of next-generation sequencing on residual formalin-fixed paraffin-embedded tissues. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 304. doi:10.1158/1538-7445.AM2014-304

A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.

Approaches to integrating germline and tumor genomic data in cancer research

Cancer is characterized by a diversity of genetic and epigenetic alterations occurring in both the germline and somatic (tumor) genomes. Hundreds of germline variants associated with cancer risk have been identified, and large amounts of data identifying mutations in the tumor genome that participate in tumorigenesis have been generated. Increasingly, these two genomes are being explored jointly to better understand how cancer risk alleles contribute to carcinogenesis and whether they influence development of specific tumor types or mutation profiles. To understand how data from germline risk studies and tumor genome profiling is being integrated, we reviewed 160 articles describing research that incorporated data from both genomes, published between January 2009 and December 2012, and summarized the current state of the field. We identified three principle types of research questions being addressed using these data: (i) use of tumor data to determine the putative function of germline risk variants; (ii) identification and analysis of relationships between host genetic background and particular tumor mutations or types; and (iii) use of tumor molecular profiling data to reduce genetic heterogeneity or refine phenotypes for germline association studies. We also found descriptive studies that compared germline and tumor genomic variation in a gene or gene family, and papers describing research methods, data sources, or analytical tools. We identified a large set of tools and data resources that can be used to analyze and integrate data from both genomes. Finally, we discuss opportunities and challenges for cancer research that integrates germline and tumor genomics data.

A pooled analysis of body mass index and pancreatic cancer mortality in african americans

BACKGROUND

Pancreatic cancer is a leading cause of cancer-related mortality in the United States and both incidence and mortality are highest in African Americans. Obesity is also disproportionately high in African Americans, but limited data are available on the relation of obesity to pancreatic cancer in this population.

METHODS

Seven large prospective cohort studies pooled data from African American participants. Body mass index (BMI) was calculated from self-reported height and weight at baseline. Cox regression was used to calculate HRs and 95% confidence intervals (CI) for levels of BMI relative to BMI 18.5-24.9, with adjustment for covariates. Primary analyses were restricted to participants with ≥5 years of follow-up because weight loss before diagnosis may have influenced baseline BMI in cases who died during early follow-up.

RESULTS

In follow-up of 239,597 participants, 897 pancreatic cancer deaths occurred. HRs were 1.08 (95% CI, 0.90-1.31) for BMI 25.0 to 29.9, 1.25 (95% CI, 0.99-1.57) for BMI 30.0 to 34.9, and 1.31 (95% CI, 0.97-1.77) for BMI ≥35.0 among those with ≥5 years of follow-up (Ptrend = 0.03). The association was evident among both sexes and was independent of a history of diabetes. A stronger association was observed among never-smokers (BMI ≥30 vs. referent: HR = 1.44; 95% CI, 1.02-2.03) than among smokers (HR = 1.16; 95% CI, 0.87-1.54; Pinteraction = 0.02).

CONCLUSION

The findings suggest that obesity is independently associated with increased pancreatic cancer mortality in African Americans.

IMPACT

Interventions to reduce obesity may also reduce risk of pancreatic cancer mortality, particularly among never-smokers.

Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report

Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 < MAF < 0.05) genetic variants associated with cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1-1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment (G × E) interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a "Gene-Environment Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors.

Joint effects between five identified risk variants, allergy, and autoimmune conditions on glioma risk

Common variants in two of the five genetic regions recently identified from genome-wide association studies (GWAS) of risk of glioma were reported to interact with a history of allergic symptoms. In a pooled analysis of five epidemiologic studies, we evaluated the association between the five GWAS implicated gene variants and allergies and autoimmune conditions (AIC) on glioma risk (851 adult glioma cases and 3,977 controls). We further evaluated the joint effects between allergies and AIC and these gene variants on glioma risk. Risk estimates were calculated as odds ratios (OR) and 95 % confidence intervals (95 % CI), adjusted for age, gender, and study. Joint effects were evaluated by conducting stratified analyses whereby the risk associations (OR and 95 % CI) with the allergy or autoimmune conditions for glioma were evaluated by the presence or absence of the 'at-risk' variant, and estimated p interaction by fitting models with the main effects of allergy or autoimmune conditions and genotype and an interaction (product) term between them. Four of the five SNPs previously reported by others were statistically significantly associated with increased risk of glioma in our study (rs2736100, rs4295627, rs4977756, and rs6010620); rs498872 was not associated with glioma in our study. Reporting any allergies or AIC was associated with reduced risks of glioma (allergy: adjusted OR = 0.71, 95 % CI 0.55-0.91; AIC: adjusted OR = 0.65, 95 % CI 0.47-0.90). We did not observe differential association between allergic or autoimmune conditions and glioma by genotype, and there were no statistically significant p interactions. Stratified analysis by glioma grade (low and high grade) did not suggest risk differences by disease grade. Our results do not provide evidence that allergies or AIC modulate the association between the four GWAS-identified SNPs examined and risk of glioma.

A review of NCI's extramural grant portfolio: identifying opportunities for future research in genes and environment in cancer

BACKGROUND

Genetic and environmental factors jointly influence cancer risk. The NIH has made the study of gene-environment (GxE) interactions a research priority since the year 2000.

METHODS

To assess the current status of GxE research in cancer, we analyzed the extramural grant portfolio of the National Cancer Institute (NCI) from Fiscal Years 2007 to 2009. Publications attributed to selected grants were also evaluated.

RESULTS

From the 1,106 research grants identified in our portfolio analysis, a random sample of 450 grants (40%) was selected for data abstraction; of these, 147 (33%) were considered relevant. The most common cancer type was breast (20%, n = 29), followed by lymphoproliferative (10%, n = 14), colorectal (9%, n = 13), melanoma/other skin (9%, n = 13), and lung/upper aerodigestive tract (8%, n = 12) cancers. The majority of grants were studies of candidate genes (68%, n = 100) compared with genome-wide association studies (GWAS) (8%, n = 12). Approximately one-third studied environmental exposures categorized as energy balance (37%, n = 54) or drugs/treatment (29%, n = 43). From the 147 relevant grants, 108 publications classified as GxE or pharmacogenomic were identified. These publications were linked to 37 of the 147 grant applications (25%).

CONCLUSION

The findings from our portfolio analysis suggest that GxE studies are concentrated in specific areas. There is room for investments in other aspects of GxE research, including, but not limited to developing alternative approaches to exposure assessment, broadening the spectrum of cancer types investigated, and conducting GxE within GWAS.

IMPACT

This portfolio analysis provides a cross-sectional review of NCI support for GxE research in cancer.

Abstract 46: A review of the gene-environment interaction literature in cancer: What do we know?

Risk of cancer is determined by a complex interplay of genetic and environmental factors. Therefore, the study of gene-environment interactions has been an active area of research for several years. To examine the state of the science in the field of gene-environment interactions research in cancer, we performed a systematic review of the published literature. A total of 3019 articles were identified using the gene-environment or pharmacogenomic flags from the HuGE literature finder and CancerGAMAdb, curated databases of genetic association studies, from January 1, 2001 to January 31, 2010. From these articles, 243 articles were determined to be relevant based on the inclusion criteria of at least 1000 cases in the interaction studied, examining the combination of genes and environment, and investigating the interaction as related to cancer risk. Information from these articles was abstracted regarding cancer type, environmental exposure variables, genetic variables, and estimates of interaction effects. In these papers, over 3500 interactions were investigated. The majority of these interactions were examined in colon, rectal, or colorectal cancer types (40%) followed by breast cancer (30%). Most of these interactions were explored using candidate gene polymorphisms (82%) compared with polymorphisms identified from genome wide association studies (GWAS). The most common environmental exposure categories observed were “energy balance” (41%), e.g. BMI or diet, followed by “Lifestyle” (21%), e.g. smoking or alcohol intake. Further analysis regarding commonly observed interactions, analytical tests performed, number of statistically significant interactions and magnitudes of interactions is on-going. In conclusion, observations of published literature suggest that opportunity exists for more of an agnostic approach to the study of gene-environment interactions and exploring alternative environmental exposures.

Citation Format: Leah E. Mechanic, Naoko I. Simonds, Armen Ghazarian, Camilla B. Benedicto, Sheri D. Schully, Gary L. Ellison, Elizabeth M. Gillanders. A review of the gene-environment interaction literature in cancer: What do we know? [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 46.

Abstract 78: Genetic Associations and Mechanisms in Oncology (GAME-ON): A network approach to post-GWAS research

Genome-wide association studies (GWAS) provide the initial evidence that a genetic region harbors a cancer susceptibility locus. However, further research is needed to identify the causal variant(s) and understand the biology of complex diseases. The National Cancer Institute GAME-ON Network consists of five collaborating groups that pursue promising scientific leads from previously generated cancer GWAS and coordinate and accelerate integrative post-GWAS discovery research. The five site-specific groups are ColoRectal Transdisciplinary Study (CORECT), Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL).

Each GAME-ON group is structured into three components: 1) Discovery and replication, which works to find new associations through pooled analyses, conducting GWAS in minority populations, independent replication of associations, and fine mapping of association signals; 2) Biological studies, which focus on evaluating risk-modifying variants, determining the biological mechanisms of risk-enhancement, and understanding the functional consequences of variants; and 3) Epidemiology, to evaluate gene-gene and gene-environment interactions, assess penetrance and population attributable risk, and develop risk models and evaluate their clinical validity.

Six working groups were formed to facilitate collaborations and share methodological expertise across all groups: 1) Analytic and Risk Modeling, to develop analytic tools, share analytic approaches, develop and validate models to characterize risk factors for cancer, 2) Epidemiology and Clinical, to plan and assist collaborative epidemiologic analysis, such as analyzing pan-cancer genes or pathways common to many cancers and the use of standard control sets across consortia, 3) Functional Assays, to share approaches for the characterization of functional consequences of risk variants, including identification of specific gene targets and their interaction mechanisms, 4) Next-Generation Genomic Technologies, to evaluate current and emerging technologies and platforms for optimal genotyping and sequencing, and assist in the search for less common and rare variants, 5) Epigenetics, to explore modification of genetic expression from epidemiological factors, and 6) the hTERT working group, to evaluate the impact of hTERT variations on risk across multiple cancer sites. Descriptive data for the ongoing projects will be presented.

In the past two years, GAME-ON has developed a network infrastructure for post-GWAS research, which will provide an inventory of epidemiologic and clinical data as well as availability of blood and tissue samples. Each group has identified new GWAS variants, completed meta-analyses, and developed strategies for fine-mapping and functional characterization of novel loci. Utilizing the collaborative environment of the network, researchers are currently developing a GAME-ON Oncochip with SNP selection from breast, colon, prostate, ovarian, and lung cancer variants, which will be used to genotype a large and diverse group of cancer cases and controls. Members of GAME-ON have used data from The Cancer Genome Atlas (TCGA) to implement eQTL analyses, conducted methylation and copy number expression analyses, and developed and applied novel methods for gene-environment interaction and pathway analysis. Major achievements and challenges within the past two years will be discussed.

Citation Format: Brett M. Kaminski, Christopher I. Amos, Eric DeRycke, Elizabeth M. Gillanders, Stephen B. Gruber, Brian E. Henderson, David J. Hunter, Pascale K. Lepage, Thomas A. Sellers, Daniela Seminara. Genetic Associations and Mechanisms in Oncology (GAME-ON): A network approach to post-GWAS research. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 78.

Frontiers in cancer epidemiology: a challenge to the research community from the Epidemiology and Genomics Research Program at the National Cancer Institute

The Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) is developing scientific priorities for cancer epidemiology research in the next decade. We would like to engage the research community and other stakeholders in a planning effort that will include a workshop in December 2012 to help shape new foci for cancer epidemiology research. To facilitate the process of defining the future of cancer epidemiology, we invite the research community to join in an ongoing web-based conversation at http://blog-epi.grants.cancer.gov/ to develop priorities and the next generation of high-impact studies.

Detectable clonal mosaicism and its relationship to aging and cancer

In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases.

Next generation analytic tools for large scale genetic epidemiology studies of complex diseases

Over the past several years, genome-wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled "Next Generation Analytic Tools for Large-Scale Genetic Epidemiology Studies of Complex Diseases" on September 15-16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large-scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene-gene and gene-environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized.

Population sciences, translational research, and the opportunities and challenges for genomics to reduce the burden of cancer in the 21st century

Advances in genomics and related fields are promising tools for risk assessment, early detection, and targeted therapies across the entire cancer care continuum. In this commentary, we submit that this promise cannot be fulfilled without an enhanced translational genomics research agenda firmly rooted in the population sciences. Population sciences include multiple disciplines that are needed throughout the translational research continuum. For example, epidemiologic studies are needed not only to accelerate genomic discoveries and new biological insights into cancer etiology and pathogenesis, but to characterize and critically evaluate these discoveries in well-defined populations for their potential for cancer prediction, prevention and response to treatment. Behavioral, social, and communication sciences are needed to explore genomic-modulated responses to old and new behavioral interventions, adherence to therapies, decision making across the continuum, and effective use in health care. Implementation science, health services, outcomes research, comparative effectiveness research, and regulatory science are needed for moving validated genomic applications into practice and for measuring their effectiveness, cost-effectiveness, and unintended consequences. Knowledge synthesis, evidence reviews, and economic modeling of the effects of promising genomic applications will facilitate policy decisions and evidence-based recommendations. Several independent and multidisciplinary panels have recently made specific recommendations for enhanced research and policy infrastructure to inform clinical and population research for moving genomic innovations into the cancer care continuum. An enhanced translational genomics and population sciences agenda is urgently needed to fulfill the promise of genomics in reducing the burden of cancer.

The landscape of recombination in African Americans

Recombination, together with mutation, gives rise to genetic variation in populations. Here we leverage the recent mixture of people of African and European ancestry in the Americas to build a genetic map measuring the probability of crossing over at each position in the genome, based on about 2.1 million crossovers in 30,000 unrelated African Americans. At intervals of more than three megabases it is nearly identical to a map built in Europeans. At finer scales it differs significantly, and we identify about 2,500 recombination hotspots that are active in people of West African ancestry but nearly inactive in Europeans. The probability of a crossover at these hotspots is almost fully controlled by the alleles an individual carries at PRDM9 (P value < 10(-245)). We identify a 17-base-pair DNA sequence motif that is enriched in these hotspots, and is an excellent match to the predicted binding target of PRDM9 alleles common in West Africans and rare in Europeans. Sites of this motif are predicted to be risk loci for disease-causing genomic rearrangements in individuals carrying these alleles. More generally, this map provides a resource for research in human genetic variation and evolution.

Genetic architecture of cancer and other complex diseases: lessons learned and future directions

Genome-wide association studies have broadened our understanding of the genetic architecture of cancer to include common variants, in addition to the rare variants previously identified by linkage analysis. We review current knowledge on the genetic architecture of four cancers--breast, lung, prostate and colorectal--for which the balance of common and rare alleles identified ranges from fewer common alleles (lung cancer) to more common alleles (prostate cancer). Although most variants are cancer specific, pleiotropy has been observed for several variants, for example, variants at the 8q24 locus and breast, ovarian and prostate cancers or variants in KITLG in relation to hair color and testicular cancer. Although few studies have been adequately powered to investigate heterogeneity among ancestry groups, effect sizes associated with common variants have been reported to be fairly homogenous among ethnic groups. Some associations appear to be ancestry specific, such as HNF1B, which is associated with prostate cancer in European Americans and Latinos but not in African-Americans. Studies of cancer and other complex diseases suggest that a simple dichotomy between rare and common allelic architectures may be too simplistic and that future research is needed to characterize a fuller spectrum of allele frequency (common (>5%), uncommon (1-5%) and rare (<<1%) alleles) and effect size. In addition, a broadening of the concept of genetic architecture to encompass both population architecture, which reflects differences in exposures, genetic factors and population level risk among diverse groups of people, and genomic architecture, which includes structural, epigenomic and somatic variation, is envisioned.

Genome-wide search for breast cancer linkage in large Icelandic non-BRCA1/2 families

Introduction:

A significant proportion of high-risk breast cancer families are not explained by mutations in known genes. Recent genome-wide searches (GWS) have not revealed any single major locus reminiscent of BRCA1 and BRCA2, indicating that still unidentified genes may explain relatively few families each or interact in a way obscure to linkage analyses. This has drawn attention to possible benefits of studying populations where genetic heterogeneity might be reduced. We thus performed a GWS for linkage on nine Icelandic multiple-case non-BRCA1/2 families of desirable size for mapping highly penetrant loci. To follow up suggestive loci, an additional 13 families from other Nordic countries were genotyped for selected markers.

Methods:

GWS was performed using 811 microsatellite markers providing about five centiMorgan (cM) resolution. Multipoint logarithm of odds (LOD) scores were calculated using parametric and nonparametric methods. For selected markers and cases, tumour tissue was compared to normal tissue to look for allelic loss indicative of a tumour suppressor gene.

Results:

The three highest signals were located at chromosomes 6q, 2p and 14q. One family contributed suggestive LOD scores (LOD 2.63 to 3.03, dominant model) at all these regions, without consistent evidence of a tumour suppressor gene. Haplotypes in nine affected family members mapped the loci to 2p23.2 to p21, 6q14.2 to q23.2 and 14q21.3 to q24.3. No evidence of a highly penetrant locus was found among the remaining families. The heterogeneity LOD (HLOD) at the 6q, 2p and 14q loci in all families was 3.27, 1.66 and 1.24, respectively. The subset of 13 Nordic families showed supportive HLODs at chromosome 6q (ranging from 0.34 to 1.37 by country subset). The 2p and 14q loci overlap with regions indicated by large families in previous GWS studies of breast cancer.

Conclusions:

Chromosomes 2p, 6q and 14q are candidate sites for genes contributing together to high breast cancer risk. A polygenic model is supported, suggesting the joint effect of genes in contributing to breast cancer risk to be rather common in non-BRCA1/2 families. For genetic counselling it would seem important to resolve the mode of genetic interaction.

Translational research in cancer genetics: the road less traveled

Gene discoveries in cancer have the potential for clinical and public health applications. To take advantage of such discoveries, a translational research agenda is needed to take discoveries from the bench to population health impact. To assess the current status of translational research in cancer genetics, we analyzed the extramural grant portfolio of the National Cancer Institute (NCI) from Fiscal Year 2007, as well as the cancer genetic research articles published in 2007. We classified both funded grants and publications as follows: T0 as discovery research; T1 as research to develop a candidate health application (e.g., test or therapy); T2 as research that evaluates a candidate application and develops evidence-based recommendations; T3 as research that assesses how to integrate an evidence-based recommendation into cancer care and prevention; and T4 as research that assesses health outcomes and population impact. We found that 1.8% of the grant portfolio and 0.6% of the published literature was T2 research or beyond. In addition to discovery research in cancer genetics, a translational research infrastructure is urgently needed to methodically evaluate and translate gene discoveries for cancer care and prevention.

Establishing an adjusted p-value threshold to control the family-wide type 1 error in genome wide association studies

Background

By assaying hundreds of thousands of single nucleotide polymorphisms, genome wide association studies (GWAS) allow for a powerful, unbiased review of the entire genome to localize common genetic variants that influence health and disease. Although it is widely recognized that some correction for multiple testing is necessary, in order to control the family-wide Type 1 Error in genetic association studies, it is not clear which method to utilize. One simple approach is to perform a Bonferroni correction using all n single nucleotide polymorphisms (SNPs) across the genome; however this approach is highly conservative and would "overcorrect" for SNPs that are not truly independent. Many SNPs fall within regions of strong linkage disequilibrium (LD) ("blocks") and should not be considered "independent".

Results

We proposed to approximate the number of "independent" SNPs by counting 1 SNP per LD block, plus all SNPs outside of blocks (interblock SNPs). We examined the effective number of independent SNPs for Genome Wide Association Study (GWAS) panels. In the CEPH Utah (CEU) population, by considering the interdependence of SNPs, we could reduce the total number of effective tests within the Affymetrix and Illumina SNP panels from 500,000 and 317,000 to 67,000 and 82,000 "independent" SNPs, respectively. For the Affymetrix 500 K and Illumina 317 K GWAS SNP panels we recommend using 10^-5, 10^-7 and 10^-8 and for the Phase II HapMap CEPH Utah and Yoruba populations we recommend using 10^-6, 10^-7 and 10^-9 as "suggestive", "significant" and "highly significant" p-value thresholds to properly control the family-wide Type 1 error.

Conclusion

By approximating the effective number of independent SNPs across the genome we are able to 'correct' for a more accurate number of tests and therefore develop 'LD adjusted' Bonferroni corrected p-value thresholds that account for the interdepdendence of SNPs on well-utilized commercially available SNP "chips". These thresholds will serve as guides to researchers trying to decide which regions of the genome should be studied further.

Evidence against PALB2 involvement in Icelandic breast cancer susceptibility

Several mutations in the PALB2 gene (partner and localizer of BRCA2) have been associated with an increased risk of breast cancer, including a founder mutation, 1592delT, reported in Finnish breast cancer families. Although most often the risk is moderate, it doesn't exclude families with high-risk mutations to exist and such observations have been reported. To see if high-risk PALB2-mutations may be present in the geographically confined population of Iceland, linkage analysis was done on 111 individuals, thereof 61 breast cancer cases, from 9 high-risk non-BRCA1/BRCA2 breast cancer families, targeting the PALB2 region. Also, screening for the 1592delT founder mutation in the 9 high-risk families and in 638 unselected breast cancer cases was performed. The results indicate no linkage in any of the high-risk families and screening for the 1592delT mutation was negative in all samples. PALB2 appears not to be a significant factor in high-risk breast cancer families in Iceland and the 1592delT mutation is not seen to be associated with breast cancer in Iceland.

Examining the effect of linkage disequilibrium between markers on the Type I error rate and power of nonparametric multipoint linkage analysis of two-generation and multigenerational pedigrees in the presence of missing genotype data

Because most multipoint linkage analysis programs currently assume linkage equilibrium between markers when inferring parental haplotypes, ignoring linkage disequilibrium (LD) may inflate the Type I error rate. We investigated the effect of LD on the Type I error rate and power of nonparametric multipoint linkage analysis of two-generation and multigenerational multiplex families. Using genome-wide single nucleotide polymorphism (SNP) data from the Collaborative Study of the Genetics of Alcoholism, we modified the original data set into 30 total data sets in order to consider six different patterns of missing data for five different levels of SNP density. To assess power, we designed simulated traits based on existing marker genotypes. For the Type I error rate, we simulated 1,000 qualitative traits from random distributions, unlinked to any of the marker data. Overall, the different levels of SNP density examined here had only small effects on power (except sibpair data). Missing data had a substantial effect on power, with more completely genotyped pedigrees yielding the highest power (except sibpair data). Most of the missing data patterns did not cause large increases in the Type I error rate if the SNP markers were more than 0.3 cM apart. However, in a dense 0.25-cM map, removing genotypes on founders and/or founders and parents in the middle generation caused substantial inflation of the Type I error rate, which corresponded to the increasing proportion of persons with missing data. Results also showed that long high-LD blocks have severe effects on Type I error rates.

High-risk melanoma susceptibility genes and pancreatic cancer, neural system tumors, and uveal melanoma across GenoMEL

GenoMEL, comprising major familial melanoma research groups from North America, Europe, Asia, and Australia has created the largest familial melanoma sample yet available to characterize mutations in the high-risk melanoma susceptibility genes CDKN2A/alternate reading frames (ARF), which encodes p16 and p14ARF, and CDK4 and to evaluate their relationship with pancreatic cancer (PC), neural system tumors (NST), and uveal melanoma (UM). This study included 466 families (2,137 patients) with at least three melanoma patients from 17 GenoMEL centers. Overall, 41% (n = 190) of families had mutations; most involved p16 (n = 178). Mutations in CDK4 (n = 5) and ARF (n = 7) occurred at similar frequencies (2-3%). There were striking differences in mutations across geographic locales. The proportion of families with the most frequent founder mutation(s) of each locale differed significantly across the seven regions (P = 0.0009). Single founder CDKN2A mutations were predominant in Sweden (p.R112_L113insR, 92% of family's mutations) and the Netherlands (c.225_243del19, 90% of family's mutations). France, Spain, and Italy had the same most frequent mutation (p.G101W). Similarly, Australia and United Kingdom had the same most common mutations (p.M53I, c.IVS2-105A>G, p.R24P, and p.L32P). As reported previously, there was a strong association between PC and CDKN2A mutations (P < 0.0001). This relationship differed by mutation. In contrast, there was little evidence for an association between CDKN2A mutations and NST (P = 0.52) or UM (P = 0.25). There was a marginally significant association between NST and ARF (P = 0.05). However, this particular evaluation had low power and requires confirmation. This GenoMEL study provides the most extensive characterization of mutations in high-risk melanoma susceptibility genes in families with three or more melanoma patients yet available.

Fine-mapping the putative chromosome 17q21-22 prostate cancer susceptibility gene to a 10 cM region based on linkage analysis

Prostate cancer linkage studies have suggested the existence of a prostate cancer susceptibility gene on chromosome 17q21-22. We now report the results of an extended linkage analysis including 95 new multiplex prostate cancer families and 9 additional microsatellite markers resulting in a maximum LOD score of 2.99 at approximately 81-82 cM for all 453 pedigrees. Results from these 95 new pedigrees provide additional support for a chromosome 17q21-22 prostate cancer susceptibility gene. Inclusion of the 9 additional markers significantly reduced the size of the candidate region, as defined using a 1-LOD support interval, especially when focusing analyses on subsets of pedigrees with four or more confirmed affecteds or average age of diagnosis less than or equal to 65 years. A novel subset analysis of only those families (n = 147) that had four or more prostate cancer cases and an average age of prostate cancer diagnosis < or = 65 years results in a maximum LOD score of 5.49 at 78 cM with a 1-LOD support interval of 10 cM. This large set of pedigrees with four more prostate cancer cases characterized by early-onset disease will serve as a useful resource for identifying the putative 17q21-22 prostate cancer susceptibility gene.

The value of molecular haplotypes in a family-based linkage study

Novel methods that could improve the power of conventional methods of gene discovery for complex diseases should be investigated. In a simulation study, we aimed to investigate the value of molecular haplotypes in the context of a family-based linkage study. The term "haplotype" (or "haploid genotype") refers to syntenic alleles inherited on a single chromosome, and we use the term "molecular haplotype" to refer to haplotypes that have been determined directly by use of a molecular technique such as long-range allele-specific polymerase chain reaction. In our study, we simulated genotype and phenotype data and then compared the powers of analyzing these data under the assumptions that various levels of information from molecular haplotypes were available. (This information was available because of the simulation procedure.) Several conclusions can be drawn. First, as expected, when genetic homogeneity is expected or when marker data are complete, it is not efficient to generate molecular haplotyping information. However, with levels of heterogeneity and missing data patterns typical of complex diseases, we observed a 23%-77% relative increase in the power to detect linkage in the presence of heterogeneity with heterogeneity LOD scores >3.0 when all individuals are molecularly haplotyped (compared with the power when only standard genotypes are used). Furthermore, our simulations indicate that most of the increase in power can be achieved by molecularly haplotyping a single individual in each family, thereby making molecular haplotyping a valuable strategy for increasing the power of gene mapping studies of complex diseases. Maximization of power, given an existing family set, can be particularly important for late-onset, often-fatal diseases such as cancer, for which informative families are difficult to collect.

Features associated with germline CDKN2A mutations: a GenoMEL study of melanoma-prone families from three continents

BACKGROUND

The major factors individually reported to be associated with an increased frequency of CDKN2A mutations are increased number of patients with melanoma in a family, early age at melanoma diagnosis, and family members with multiple primary melanomas (MPM) or pancreatic cancer.

METHODS

These four features were examined in 385 families with > or =3 patients with melanoma pooled by 17 GenoMEL groups, and these attributes were compared across continents.

RESULTS

Overall, 39% of families had CDKN2A mutations ranging from 20% (32/162) in Australia to 45% (29/65) in North America to 57% (89/157) in Europe. All four features in each group, except pancreatic cancer in Australia (p = 0.38), individually showed significant associations with CDKN2A mutations, but the effects varied widely across continents. Multivariate examination also showed different predictors of mutation risk across continents. In Australian families, > or =2 patients with MPM, median age at melanoma diagnosis < or =40 years and > or =6 patients with melanoma in a family jointly predicted the mutation risk. In European families, all four factors concurrently predicted the risk, but with less stringent criteria than in Australia. In North American families, only > or =1 patient with MPM and age at diagnosis < or =40 years simultaneously predicted the mutation risk.

CONCLUSIONS

The variation in CDKN2A mutations for the four features across continents is consistent with the lower melanoma incidence rates in Europe and higher rates of sporadic melanoma in Australia. The lack of a pancreatic cancer-CDKN2A mutation relationship in Australia probably reflects the divergent spectrum of mutations in families from Australia versus those from North America and Europe. GenoMEL is exploring candidate host, genetic and/or environmental risk factors to better understand the variation observed.

A novel missense mutation in ACTG1 causes dominant deafness in a Norwegian DFNA20/26 family, but ACTG1 mutations are not frequent among families with hereditary hearing impairment

The gamma-actin gene (ACTG1) encodes a major cytoskeletal protein of the sensory hair cells of the cochlea. Recently, mutations in ACTG1 were found to cause autosomal dominant, progressive, sensorineural hearing impairment linked to the DFNA20/26 locus on chromosome 17q25.3 in four American families and in one Dutch family. We report here the linkage of autosomal dominant, progressive, sensorineural hearing impairment in a large Norwegian family to the DFNA20/26 locus. Sequencing of ACTG1 identified a novel missense mutation (c.1109T>C; p.V370A) segregating with the hearing loss. Functional analysis in yeast showed that the p.V370A mutation restricts cell growth at elevated temperature or under hyperosmolar stress. Molecular modelling suggested that the p.V370A mutation modestly alters a site for protein-protein interaction in gamma-actin and thereby modestly alters gamma-actin-based cytoskeletal structures. Nineteen Norwegian and Danish families with autosomal, dominant hearing impairment were analyzed for mutations in ACTG1 by sequencing, but no disease-associated mutations were identified. Finally, a long-term follow-up of the hearing loss progression associated with the p.V370A mutation in ACTG1 is provided. The present study expands our understanding of the genotype-phenotype relationship of this deafness gene and provides a sensitive and simple functional assay for missense mutations in this gene, which may assist future molecular diagnosis of autosomal-dominant hearing impairment. Finally, the present results do not indicate that mutations in ACTG1 are a frequent cause of autosomal-dominant postlingual sensorineural hearing impairment in Norway nor Denmark.

Genome-wide linkage scan for prostate cancer susceptibility genes in men with aggressive disease: significant evidence for linkage at chromosome 15q12

Epidemiological and twin studies have consistently demonstrated a strong genetic component to prostate cancer (PCa) susceptibility. To date, numerous linkage studies have been performed to identify chromosomal regions containing PCa susceptibility genes. Unfortunately, results from these studies have failed to form any obvious consensus regarding which regions are most likely to contain genes that may contribute to PCa predisposition. One plausible explanation for the difficulty in mapping susceptibility loci is the existence of considerable heterogeneity in the phenotype of PCa, with significant variation in clinical stage and grade of disease even among family members. To address this issue, we performed a genome-wide linkage scan on 71 informative families with two or more men with aggressive PCa. When only men with aggressive PCa were coded as affected, statistically significant evidence for linkage at chromosome 15q12 was detected (LOD=3.49; genome-wide p=0.005). Furthermore, the evidence for linkage increased when analyses were restricted to Caucasian-American pedigrees (n=65; LOD=4.05) and pedigrees with two confirmed aggressive cases (n=42, LOD=4.76). Interestingly, a 1-LOD support interval about our peak at 15q12 overlaps a region of suggestive linkage, 15q11, identified by a recent linkage study on 1,233 PCa families by the International Consortium for Prostate Cancer Genetics. Using a more rigid definition of PCa in linkage studies will result in a severe reduction in sample sizes available for study, but may ultimately prove to increase statistical power to detect susceptibility genes for this multigenic trait.

Investigation of altering single-nucleotide polymorphism density on the power to detect trait loci and frequency of false positive in nonparametric linkage analyses of qualitative traits

Genome-wide linkage analysis using microsatellite markers has been successful in the identification of numerous Mendelian and complex disease loci. The recent availability of high-density single-nucleotide polymorphism (SNP) maps provides a potentially more powerful option. Using the simulated and Collaborative Study on the Genetics of Alcoholism (COGA) datasets from the Genetics Analysis Workshop 14 (GAW14), we examined how altering the density of SNP marker sets impacted the overall information content, the power to detect trait loci, and the number of false positive results. For the simulated data we used SNP maps with density of 0.3 cM, 1 cM, 2 cM, and 3 cM. For the COGA data we combined the marker sets from Illumina and Affymetrix to create a map with average density of 0.25 cM and then, using a sub-sample of these markers, created maps with density of 0.3 cM, 0.6 cM, 1 cM, 2 cM, and 3 cM. For each marker set, multipoint linkage analysis using MERLIN was performed for both dominant and recessive traits derived from marker loci. Our results showed that information content increased with increased map density. For the homogeneous, completely penetrant traits we created, there was only a modest difference in ability to detect trait loci. Additionally, as map density increased there was only a slight increase in the number of false positive results when there was linkage disequilibrium (LD) between markers. The presence of LD between markers may have led to an increased number of false positive regions but no clear relationship between regions of high LD and locations of false positive linkage signals was observed.

Identification of tag single-nucleotide polymorphisms in regions with varying linkage disequilibrium

We compared seven different tagging single-nucleotide polymorphism (SNP) programs in 10 regions with varied amounts of linkage disequilibrium (LD) and physical distance. We used the Collaborative Studies on the Genetics of Alcoholism dataset, part of the Genetic Analysis Workshop 14. We show that in regions with moderate to strong LD these programs are relatively consistent, despite different parameters and methods. In addition, we compared the selected SNPs in a multipoint linkage analysis for one region with strong LD. As the number of selected SNPs increased, the LOD score, mean information content, and type I error also increased.