Chromosome 8q24 markers: Risk of early-onset and familial prostate cancer

Recent admixture mapping and linkage/association studies have implicated an ∼1 Mb region on chromosome 8q24 in prostate cancer susceptibility. In a subsequent follow-up investigation, Haiman et al. (Nat Genet 2007;39:638-44) observed significant, independent associations between 7 markers within this region and sporadic prostate cancer risk in a multi-ethnic sample. To clarify the risk associated with hereditary prostate cancer, we tested for prostate cancer association with 6 of these 7 markers in a sample of 1,015 non-Hispanic white men with and without prostate cancer from 403 familial and early-onset prostate cancer families. Single nucleotide polymorphisms (SNPs) rs6983561 and rs6983267 showed the strongest evidence of prostate cancer association. Using a family-based association test, the minor (“C”) allele of rs6983561 and the major (“G”) allele of rs6983267 were preferentially transmitted to affected men ( p < 0.05), with estimated odds ratios (ORs) of 2.26 (95% confidence interval of 1.06–4.83) and 1.30 (95% confidence interval of 0.99–1.71), respectively, for an additive model. Notably, rs6983561 was significantly associated with prostate cancer among men diagnosed at an early (<50 years) but not later age ( p = 0.03 versus p = 0.21). Similarly, the association with rs6983267 was (not) statistically significant among men with(out) clinically aggressive disease ( p = 0.007 versus p = 0.34). Our results confirm the association of prostate cancer with several of the SNPs on chromosome 8q24 initially reported by Haiman et al. In addition, our results suggest that the increased risk associated with these SNPs is approximately doubled in individuals predisposed to develop early onset or clinically aggressive disease. © 2008 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58546/1/23471_ftp.pd

A Simulation-Based Workflow to Assess Human-Centric Daylight Performance

This paper will present an annual simulation-based workflow for assessing human perceptual and non-visual responses to daylight across a series of view positions in an architectural case study. Through the integration of mathematical models used to predict visual interest and non-visual health potential, this paper will introduce an automated workflow to assess an array of view positions (located at eye level) under varied sky conditions and across multiple view directions to analyze the predicted impacts of daylight on perception and health in architecture. This approach allows for a spatial and occupant centric analysis of daylight using an integrated simulation-based approach

Common genetic variants associated with disease from genome-wide association studies are mutually exclusive in prostate cancer and rheumatoid arthritis

Objectives: To investigate if potential common pathways exist for the pathogenesis of autoimmune disease and prostate cancer (PrCa). To ascertain if the single nucleotide polymorphisms (SNPs) reported by genome-wide association studies (GWAS) as being associated with susceptibility to PrCa are also associated with susceptibility to the autoimmune disease rheumatoid arthritis (RA). Materials and Methods: The original Wellcome Trust Case Control Consortium (WTCCC) UK RA GWAS study was expanded to include a total of 3221 cases and 5272 controls. In all, 37 germline autosomal SNPs at genome-wide significance associated with PrCa risk were identified from a UK/Australian PrCa GWAS. Allele frequencies were compared for these 37 SNPs between RA cases and controls using a chi-squared trend test and corrected for multiple testing (Bonferroni). Results: In all, 33 SNPs were able to be analysed in the RA dataset. Proxies could not be located for the SNPs in 3q26, 5p15 and for two SNPs in 17q12. After applying a Bonferroni correction for the number of SNPs tested, the SNP mapping to CCHCR1 (rs130067) retained statistically significant evidence for association (P = 6 × 10–4; odds ratio [OR] = 1.15, 95% CI: 1.06–1.24); this has also been associated with psoriasis. However, further analyses showed that the association of this allele was due to confounding by RA-associated HLA-DRB1 alleles. Conclusions: There is currently no evidence that SNPs associated with PrCa at genome-wide significance are associated with the development of RA. Studies like this are important in determining if common genetic risk profiles might predispose individuals to many diseases, which could have implications for public health in terms of screening and chemoprevention

SNPFile – A software library and file format for large scale association mapping and population genetics studies

<p>Abstract</p> <p>Background</p> <p>High-throughput genotyping technology has enabled cost effective typing of thousands of individuals in hundred of thousands of markers for use in genome wide studies. This vast improvement in data acquisition technology makes it an informatics challenge to efficiently store and manipulate the data. While spreadsheets and at text files were adequate solutions earlier, the increased data size mandates more efficient solutions.</p> <p>Results</p> <p>We describe a new binary file format for SNP data, together with a software library for file manipulation. The file format stores genotype data together with any kind of additional data, using a flexible serialisation mechanism. The format is designed to be IO efficient for the access patterns of most multi-locus analysis methods.</p> <p>Conclusion</p> <p>The new file format has been very useful for our own studies where it has significantly reduced the informatics burden in keeping track of various secondary data, and where the memory and IO efficiency has greatly simplified analysis runs. A main limitation with the file format is that it is only supported by the very limited set of analysis tools developed in our own lab. This is somewhat alleviated by a scripting interfaces that makes it easy to write converters to and from the format.</p

Early onset prostate cancer has a significant genetic component

BACKGROUND Prostate cancer (PCa) affects more than 190,000 men each year with ∼10% of men diagnosed at ≤55 years, that is, early onset (EO) PCa. Based on historical findings for other cancers, EO PCa likely reflects a stronger underlying genetic etiology. METHODS We evaluated the association between EO PCa and previously identified single nucleotide polymorphisms (SNPs) in 754 Caucasian cases from the Michigan Prostate Cancer Genetics Project (mean 49.8 years at diagnosis), 2,713 Caucasian controls from Illumina's iControlDB database and 1,163 PCa cases diagnosed at >55 years from the Cancer Genetic Markers of Susceptibility Study (CGEMS). RESULTS Significant associations existed for 13 of 14 SNPs (rs9364554 on 6q25, rs10486567 on 7p15, rs6465657 on 7q21, rs6983267 on 8q24, rs1447295 on 8q24, rs1571801 on 9q33, rs10993994 on 10q11, rs4962416 on 10q26, rs7931342 on 11q13, rs4430796 on 17q12, rs1859962 on 17q24.3, rs2735839 on 19q13, and rs5945619 on Xp11.22, but not rs2660753 on 3p12). EO PCa cases had a significantly greater cumulative number of risk alleles (mean 12.4) than iControlDB controls (mean 11.2; P  = 2.1 × 10 −33 ) or CGEMS cases (mean 11.9; P  = 1.7 × 10 −5 ). Notably, EO PCa cases had a higher frequency of the risk allele than CGEMS cases at 11 of 13 associated SNPs, with significant differences for five SNPs. EO PCa cases diagnosed at <50 (mean 12.8) also had significantly more risk alleles than those diagnosed at 50–55 years (mean 12.1; P  = 0.0003). CONCLUSIONS These results demonstrate the potential for identifying PCa‐associated genetic variants by focusing on the subgroup of men diagnosed with EO disease. Prostate 72:147–156, 2012. © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/89538/1/21414_ftp.pd

Cancer as a Complex Phenotype: Pattern of Cancer Distribution within and beyond the Nuclear Family

BACKGROUND: The contribution of low-penetrant susceptibility variants to cancer is not clear. With the aim of searching for genetic factors that contribute to cancer at one or more sites in the body, we have analyzed familial aggregation of cancer in extended families based on all cancer cases diagnosed in Iceland over almost half a century. METHODS AND FINDINGS: We have estimated risk ratios (RRs) of cancer for first- and up to fifth-degree relatives both within and between all types of cancers diagnosed in Iceland from 1955 to 2002 by linking patient information from the Icelandic Cancer Registry to an extensive genealogical database, containing all living Icelanders and most of their ancestors since the settlement of Iceland. We evaluated the significance of the familial clustering for each relationship separately, all relationships combined (first- to fifth-degree relatives) and for close (first- and second-degree) and distant (third- to fifth-degree) relatives. Most cancer sites demonstrate a significantly increased RR for the same cancer, beyond the nuclear family. Significantly increased familial clustering between different cancer sites is also documented in both close and distant relatives. Some of these associations have been suggested previously but others not. CONCLUSION: We conclude that genetic factors are involved in the etiology of many cancers and that these factors are in some cases shared by different cancer sites. However, a significantly increased RR conferred upon mates of patients with cancer at some sites indicates that shared environment or nonrandom mating for certain risk factors also play a role in the familial clustering of cancer. Our results indicate that cancer is a complex, often non-site-specific disease for which increased risk extends beyond the nuclear family

Estimates of heritable and environmental components of familial breast cancer using family history information

Using the Swedish Family-Cancer Database, the increased risk of breast cancer in women with relatives with the disease did not vary with paternal/maternal lineage. Familial breast cancer heritable component was 73% and the environmental proportion 27%. Familial aggregation of breast cancer in women below age 51 years is mainly due to heritable causes

Comprehensive resequence analysis of a 136 kb region of human chromosome 8q24 associated with prostate and colon cancers

Recently, genome-wide association studies have identified loci across a segment of chromosome 8q24 (128,100,000–128,700,000) associated with the risk of breast, colon and prostate cancers. At least three regions of 8q24 have been independently associated with prostate cancer risk; the most centromeric of which appears to be population specific. Haplotypes in two contiguous but independent loci, marked by rs6983267 and rs1447295, have been identified in the Cancer Genetic Markers of Susceptibility project (http://cgems.cancer.gov), which genotyped more than 5,000 prostate cancer cases and 5,000 controls of European origin. The rs6983267 locus is also strongly associated with colorectal cancer. To ascertain a comprehensive catalog of common single-nucleotide polymorphisms (SNPs) across the two regions, we conducted a resequence analysis of 136 kb (chr8: 128,473,000–128,609,802) using the Roche/454 next-generation sequencing technology in 39 prostate cancer cases and 40 controls of European origin. We have characterized a comprehensive catalog of common (MAF > 1%) SNPs within this region, including 442 novel SNPs and have determined the pattern of linkage disequilibrium across the region. Our study has generated a detailed map of genetic variation across the region, which should be useful for choosing SNPs for fine mapping of association signals in 8q24 and investigations of the functional consequences of select common variants

A fast algorithm for genome-wide haplotype pattern mining

<p>Abstract</p> <p>Background</p> <p>Identifying the genetic components of common diseases has long been an important area of research. Recently, genotyping technology has reached the level where it is cost effective to genotype single nucleotide polymorphism (SNP) markers covering the entire genome, in thousands of individuals, and analyse such data for markers associated with a diseases. The statistical power to detect association, however, is limited when markers are analysed one at a time. This can be alleviated by considering multiple markers simultaneously. The <it>Haplotype Pattern Mining </it>(HPM) method is a machine learning approach to do exactly this.</p> <p>Results</p> <p>We present a new, faster algorithm for the HPM method. The new approach use patterns of haplotype diversity in the genome: locally in the genome, the number of observed haplotypes is much smaller than the total number of possible haplotypes. We show that the new approach speeds up the HPM method with a factor of 2 on a genome-wide dataset with 5009 individuals typed in 491208 markers using default parameters and more if the pattern length is increased.</p> <p>Conclusion</p> <p>The new algorithm speeds up the HPM method and we show that it is feasible to apply HPM to whole genome association mapping with thousands of individuals and hundreds of thousands of markers.</p

The ‘Common Disease-Common Variant’ Hypothesis and Familial Risks

The recent large genotyping studies have identified a new repertoire of disease susceptibility loci of unknown function, characterized by high allele frequencies and low relative risks, lending support to the common disease-common variant (CDCV) hypothesis. The variants explain a much larger proportion of the disease etiology, measured by the population attributable fraction, than of the familial risk. We show here that if the identified polymorphisms were markers of rarer functional alleles they would explain a much larger proportion of the familial risk. For example, in a plausible scenario where the marker is 10 times more common than the causative allele, the excess familial risk of the causative allele is over 10 times higher than that of the marker allele. However, the population attributable fractions of the two alleles are equal. The penetrance mode of the causative locus may be very difficult to deduce from the apparent penetrance mode of the marker locus