Association of CD14 variant with prostate cancer in African American men.

BACKGROUND: African American men have the highest rates of prostate cancer worldwide, and immunogenetic studies suggest that people of African descent have increased susceptibility to diseases of inflammation. Since genetic susceptibility is an etiological factor in prostate cancer, we hypothesize that sequence variants in the promoter region of the CD14 gene that regulate inflammation may modify individual susceptibility to this disease. METHODS: The CD14 promoter was screened for single-nucleotide polymorphisms (SNPs) using dHPLC. One variant, -260 C>T (rs2569190), was genotyped via restriction digest in all study participants (264 cases and 188 controls). The association of disease status and the polymorphism was analyzed by unconditional logistic regression. Odds ratios with 95% confidence intervals were calculated, stratifying by ethnicity and adjusting for age. Two-sided P-values of < or =0.05 were considered as statistically significant. RESULTS: Eleven variants (four novel) were identified in the promoter region of CD14. A marginal association between the C genotypes (C/C + C/T) and prostate cancer was found (P = 0.07). When stratified by age, among men > or =55 years of age, the C genotypes were significantly associated with prostate cancer (P < 0.05). When stratified by self-reported ethnicity, African American males who had the C genotypes were at a higher risk for prostate cancer (P < 0.05). CONCLUSIONS: This is the first study to show an association between the C genotypes of the CD14 (-260) variant and prostate cancer which supports the hypothesis that genetic variation in the inflammatory process can contribute to prostate cancer susceptibility in African American men.

Admixture Mapping Links RACGAP1 Regulation to Prostate Cancer in African Americans.

BACKGROUND/AIM: Prostate cancer is the most common malignancy in US males. African American men have higher incidence and mortality rates than European Americans. Five single nucleotide polymorphisms are associated with PCa. We hypothesized haplotypes inferred from these SNPs are also associated with PCa. PATIENTS AND METHODS: We genotyped SNPs in a case-control admixture mapping study. SNP haplotypes inferred for 157 PCa cases and 150 controls were used in the regression analysis. RESULTS: We found an association between "GTCCC", "ATTCT", and "ACCCC" haplotypes and PCa after ancestry adjustment (OR=3.62, 95%CI=1.42-9.21, p=0.0070; OR=7.89, 95%CI=2.36-26.31, p=0.0008; OR=4.34, 95%CI=1.75-10.78, p=0.0016). The rs615382 variant disrupts the recombination signal binding protein with immunoglobulin kappa J binding site in Rac GTPase activating protein 1 (RACGAP1). CONCLUSION: Disruption of notch 1 mediated-repression of RACGAP1 may contribute to PCa in African Americans.

Information Dynamics of Whole Genome Adaptation.

The human genome is a complex, dynamic information system that encodes principles of life and living systems. These principles are incorporated in the structure of human genome sequence variation and are foundational for the continuity of life and human survival. Using first principles of thermodynamics and statistical physics, we have developed analogous "genodynamic tools" for population genomic studies. Characterizing genomic information through the lens of physics has allowed us to develop energy measures for modeling genome-environment interactions. In developing biophysical parameters for genome-environment homeostasis, we found that stable genomic free energy trades off low genomic energy (genomic conservation and increased order) and high genomic entropy (genomic variation) with an environmental potential that drives the variation. In our approach, we assert that common variants are dynamic sites in the genome of a population and that the stability of whole genome adaptation is reflected in the frequencies of maintained diversity in common variants for the population in its environment. In this paper, we address the relativity of whole genome adaptation towards homeostasis. By this we mean that adaptive forces are directly reflected in the frequency distribution of alleles and/or haplotypes of the population relative to its environment, with adaptive forces driving the genome towards homeostasis. The use of genomic energy units as a biophysical metric in DNA sequence variation analyses provides new insights into the foundations of population biology and diversity. Using our biophysical tools, population differences directly reflect the adaptive influences of the environment on populations.

Single Nucleotide Polymorphisms: A Window into the Informatics of the Living Genome.

Nested in the environment of the nucleus of the cell, the 23 sets of chromosomes that comprise the human genome function as one integrated whole system, orchestrating the expression of thousands of genes underlying the biological characteristics of the cell, individual and the species. The extraction of meaningful information from this complex data set depends crucially upon the lens through which the data are examined. We present a biophysical perspective on genomic information encoded in single nucleotide polymorphisms (SNPs), and introduce metrics for modeling information encoded in the genome. Information, like energy, is considered to be a conserved physical property of the universe. The information structured in SNPs describes the adaptation of a human population to a given environment. The maintained order measured by the information content is associated with entropies, energies, and other state variables for a dynamic system in homeostasis. "Genodynamics" characterizes the state variables for genomic populations that are stable under stochastic environmental stresses. The determination of allelic energies allows the parameterization of specific environmental influences upon individual alleles across populations. The environment drives population-based genome variation. From this vantage point, the genome is modeled as a complex, dynamic information system defined by patterns of SNP alleles and SNP haplotypes.

Development of genodynamic metrics for exploring the biophysics of DNA polymorphisms.

Single nucleotide polymorphisms (SNPs) represent an important type of dynamic sites within the human genome. These common variants often locally correlate within more complex multi-SNP haploblocks that are maintained throughout generations in a stable population. Information encoded in the structure of SNPs and SNP haploblock variation can be characterized through a normalized information content metric. Genodynamics is being developed as the analogous "thermodynamics" characterizing the state variables for genomic populations that are stable under stochastic environmental stresses. Since living systems have not been found to develop in the absence of environmental influences, this paper describes the analogous genomic free energy metrics in a given environment. SNP haploblocks were constructed by Haploview v4.2 for five chromosomes from phase III HapMap data, and the genomic state variables for each chromosome were calculated. An in silico analysis was performed on SNP haploblocks with the lowest genomic energy measures. Highly favorable genomic energy measures were found to correlate with highly conserved SNP haploblocks. Moreover, the most conserved haploblocks were associated with an evolutionarily conserved regulatory element and domain.

A new biophysical metric for interrogating the information content in human genome sequence variation: Proof of concept.

The 21st century emergence of genomic medicine is shifting the paradigm in biomedical science from the population phenotype to the individual genotype. In characterizing the biology of disease and health disparities in population genetics, human populations are often defined by the most common alleles in the group. This definition poses difficulties when categorizing individuals in the population who do not have the most common allele(s). Various epidemiological studies have shown an association between common genomic variation, such as single nucleotide polymorphisms (SNPs), and common diseases. We hypothesize that information encoded in the structure of SNP haploblock variation in the human leukocyte antigen-disease related (HLA-DR) region of the genome illumines molecular pathways and cellular mechanisms involved in the regulation of host adaptation to the environment. In this paper we describe the development and application of the normalized information content (NIC) as a novel metric based on SNP haploblock variation. The NIC facilitates translation of biochemical DNA sequence variation into a biophysical quantity derived from Boltzmann's canonical ensemble in statistical physics and used widely in information theory. Our normalization of this information metric allows for comparisons of unlike, or even unrelated, regions of the genome. We report here NIC values calculated for HLA-DR SNP haploblocks constructed by Haploview, a product of the International Haplotype Map Project. These haploblocks were scanned for potential regulatory elements using ConSite and miRBase, publicly available bioinformatics tools. We found that all of the haploblocks with statistically low NIC values contained putative transcription factor binding sites and microRNA motifs, suggesting correlation with genomic regulation. Thus, we were able to relate a mathematical measure of information content in HLA-DR SNP haploblocks to biologically relevant functional knowledge embedded in the structure of DNA sequence variation. We submit that NIC may be useful in analyzing the regulation of molecular pathways involved in host adaptation to environmental pathogens and in decoding the functional significance of common variation in the human genome.