Quantifying rare, deleterious variation in 12 human cytochrome P450 drug-metabolism genes in a large-scale exome dataset.

The study of genetic influences on drug response and efficacy ('pharmacogenetics') has existed for over 50 years. Yet, we still lack a complete picture of how genetic variation, both common and rare, affects each individual's responses to medications. Exome sequencing is a promising alternative method for pharmacogenetic discovery as it provides information on both common and rare variation in large numbers of individuals. Using exome data from 2203 AA and 4300 Caucasian individuals through the NHLBI Exome Sequencing Project, we conducted a survey of coding variation within 12 Cytochrome P450 (CYP) genes that are collectively responsible for catalyzing nearly 75% of all known Phase I drug oxidation reactions. In addition to identifying many polymorphisms with known pharmacogenetic effects, we discovered over 730 novel nonsynonymous alleles across the 12 CYP genes of interest. These alleles include many with diverse functional effects such as premature stop codons, aberrant splicesites and mutations at conserved active site residues. Our analysis considering both novel, predicted functional alleles as well as known, actionable CYP alleles reveals that rare, deleterious variation contributes markedly to the overall burden of pharmacogenetic alleles within the populations considered, and that the contribution of rare variation to this burden is over three times greater in AA individuals as compared with Caucasians. While most of these impactful alleles are individually rare, 7.6-11.7% of individuals interrogated in the study carry at least one newly described potentially deleterious alleles in a major drug-metabolizing CYP.

Cytokine and cytokine receptor genes of the adaptive immune response are differentially associated with breast cancer risk in American women of African and European ancestry.

Disparities in breast cancer biology are evident between American women of African ancestry (AA) and European ancestry (EA) and may be due, in part, to differences in immune function. To assess the potential role of constitutional host immunity on breast carcinogenesis, we tested associations between breast cancer risk and 47 single nucleotide polymorphisms (SNPs) in 26 cytokine-related genes of the adaptive immune system using 650 EA (n = 335 cases) and 864 AA (n = 458 cases) women from the Women's Circle of Health Study (WCHS). With additional participant accrual to the WCHS, promising SNPs from the initial analysis were evaluated in a larger sample size (1,307 EAs and 1,365 AAs). Multivariate logistic regression found SNPs in genes important for T helper type 1 (Th1) immunity (IFNGR2 rs1059293, IL15RA rs2296135, LTA rs1041981), Th2 immunity (IL4R rs1801275), and T regulatory cell-mediated immunosuppression (TGFB1 rs1800469) associated with breast cancer risk, mainly among AAs. The combined effect of these five SNPs was highly significant among AAs (P-trend = 0.0005). When stratified by estrogen receptor (ER) status, LTA rs1041981 was associated with ER-positive breast cancers among EAs and marginally among AAs. Only among AA women, IL15 rs10833 and IL15RA rs2296135 were associated with ER-positive tumors, and IL12RB1 rs375947, IL15 rs10833 and TGFB1 rs1800469 were associated with ER-negative tumors. Our study systematically identified genetic variants in the adaptive immune response pathway associated with breast cancer risk, which appears to differ by ancestry groups, menopausal status and ER status.

Hormone-receptor expression and ovarian cancer survival: an Ovarian Tumor Tissue Analysis consortium study.

BACKGROUND: Few biomarkers of ovarian cancer prognosis have been established, partly because subtype-specific associations might be obscured in studies combining all histopathological subtypes. We examined whether tumour expression of the progesterone receptor (PR) and oestrogen receptor (ER) was associated with subtype-specific survival. METHODS: 12 studies participating in the Ovarian Tumor Tissue Analysis consortium contributed tissue microarray sections and clinical data to our study. Participants included in our analysis had been diagnosed with invasive serous, mucinous, endometrioid, or clear-cell carcinomas of the ovary. For a patient to be eligible, tissue microarrays, clinical follow-up data, age at diagnosis, and tumour grade and stage had to be available. Clinical data were obtained from medical records, cancer registries, death certificates, pathology reports, and review of histological slides. PR and ER statuses were assessed by central immunohistochemistry analysis done by masked pathologists. PR and ER staining was defined as negative (<1% tumour cell nuclei), weak (1 to <50%), or strong (≥50%). Associations with disease-specific survival were assessed. FINDINGS: 2933 women with invasive epithelial ovarian cancer were included: 1742 with high-grade serous carcinoma, 110 with low-grade serous carcinoma, 207 with mucinous carcinoma, 484 with endometrioid carcinoma, and 390 with clear-cell carcinoma. PR expression was associated with improved disease-specific survival in endometrioid carcinoma (log-rank p<0·0001) and high-grade serous carcinoma (log-rank p=0·0006), and ER expression was associated with improved disease-specific survival in endometrioid carcinoma (log-rank p<0·0001). We recorded no significant associations for mucinous, clear-cell, or low-grade serous carcinoma. Positive hormone-receptor expression (weak or strong staining for PR or ER, or both) was associated with significantly improved disease-specific survival in endometrioid carcinoma compared with negative hormone-receptor expression, independent of study site, age, stage, and grade (hazard ratio 0·33, 95% CI 0·21-0·51; p<0·0001). Strong PR expression was independently associated with improved disease-specific survival in high-grade serous carcinoma (0·71, 0·55-0·91; p=0·0080), but weak PR expression was not (1·02, 0·89-1·18; p=0·74). INTERPRETATION: PR and ER are prognostic biomarkers for endometrioid and high-grade serous ovarian cancers. Clinical trials, stratified by subtype and biomarker status, are needed to establish whether hormone-receptor status predicts response to endocrine treatment, and whether it could guide personalised treatment for ovarian cancer. FUNDING: Carraresi Foundation and others.

Natural selection and functional genetic variation in the p53 pathway.

The allele frequencies of two functional single-nucleotide polymorphisms (SNPs) in the p53 pathway, the MDM2 SNP309 and TP53 Arg72Pro, vary dramatically among populations. That the frequencies of the TP53 SNP follow a clinal distribution may suggest that selective pressure from environmental variables correlated with latitude contributed to these observed population differences. Recently, winter temperature and UV radiation were found to be significantly correlated with the TP53 and the MDM2 SNPs, respectively, in East Asians; whether these correlations are more extreme than expected based upon nonselective factors such as patterns of human migration remains unclear. Here, we genotyped these two SNPs in 971 unrelated individuals from 52 unique populations worldwide and tested for correlations with both latitude and a number of climate-related environmental variables on a global scale, controlling for these neutral processes. The TP53 SNP was associated with a significant selection signal for a few climate variables, such as short-wave radiation flux in the winter, but these signals were no longer significant after correction for multiple tests. The MDM2 SNP did not exhibit a significant signal with any climate variable. Therefore, these SNPs are unlikely to be under selective pressure driven by these variables. Thus, these data underscore the need to incorporate population history when assessing signatures of selection.

IMA: an R package for high-throughput analysis of Illumina's 450K Infinium methylation data.

UNLABELLED: The Illumina Infinium HumanMethylation450 BeadChip is a newly designed high-density microarray for quantifying the methylation level of over 450 000 CpG sites within human genome. Illumina Methylation Analyzer (IMA) is a computational package designed to automate the pipeline for exploratory analysis and summarization of site-level and region-level methylation changes in epigenetic studies utilizing the 450K DNA methylation microarray. The pipeline loads the data from Illumina platform and provides user-customized functions commonly required to perform exploratory methylation analysis for individual sites as well as annotated regions. AVAILABILITY: IMA is implemented in the R language and is freely available from http://www.rforge.net/IMA.

Epigenetic control of a VDR-governed feed-forward loop that regulates p21(waf1/cip1) expression and function in non-malignant prostate cells.

In non-malignant RWPE-1 prostate epithelial cells signaling by the nuclear receptor Vitamin D Receptor (VDR, NR1I1) induces cell cycle arrest through targets including CDKN1A (encodes p21((waf1/cip1))). VDR dynamically induced individual histone modification patterns at three VDR binding sites (R1, 2, 3) on the CDKN1A promoter. The magnitude of these modifications was specific to each phase of the cell cycle. For example, H3K9ac enrichment occurred rapidly only at R2, whereas parallel accumulation of H3K27me3 occurred at R1; these events were significantly enriched in G(1) and S phase cells, respectively. The epigenetic events appeared to allow VDR actions to combine with p53 to enhance p21((waf1/cip1)) activation further. In parallel, VDR binding to the MCM7 gene induced H3K9ac enrichment associated with rapid mRNA up-regulation to generate miR-106b and consequently regulate p21((waf1/cip1)) expression. We conclude that VDR binding site- and promoter-specific patterns of histone modifications combine with miRNA co-regulation to form a VDR-regulated feed-forward loop to control p21((waf1/cip1)) expression and cell cycle arrest. Dissection of this feed-forward loop in a non-malignant prostate cell system illuminates mechanisms of sensitivity and therefore possible resistance in prostate and other VDR responsive cancers.

OSAT: a tool for sample-to-batch allocations in genomics experiments.

BACKGROUND: Batch effect is one type of variability that is not of primary interest but ubiquitous in sizable genomic experiments. To minimize the impact of batch effects, an ideal experiment design should ensure the even distribution of biological groups and confounding factors across batches. However, due to the practical complications, the availability of the final collection of samples in genomics study might be unbalanced and incomplete, which, without appropriate attention in sample-to-batch allocation, could lead to drastic batch effects. Therefore, it is necessary to develop effective and handy tool to assign collected samples across batches in an appropriate way in order to minimize the impact of batch effects. RESULTS: We describe OSAT (Optimal Sample Assignment Tool), a bioconductor package designed for automated sample-to-batch allocations in genomics experiments. CONCLUSIONS: OSAT is developed to facilitate the allocation of collected samples to different batches in genomics study. Through optimizing the even distribution of samples in groups of biological interest into different batches, it can reduce the confounding or correlation between batches and the biological variables of interest. It can also optimize the homogeneous distribution of confounding factors across batches. It can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideally balanced designs.

Variants in the vitamin D pathway, serum levels of vitamin D, and estrogen receptor negative breast cancer among African-American women: a case-control study.

INTRODUCTION: American women of African ancestry (AA) are more likely than European Americans (EA) to have estrogen receptor (ER)-negative breast cancer. 25-hydroxyvitamin D (25OHD) is low in AAs, and was associated with ER-negative tumors in EAs. We hypothesized that racial differences in 25OHD levels, as well as in inherited genetic variations, may contribute, in part, to the differences in tumor characteristics. METHODS: In a case (n = 928)-control (n = 843) study of breast cancer in AA and EA women, we measured serum 25OHD levels in controls and tested associations between risk and tag single nucleotide polymorphisms (SNPs) in VDR, CYP24A1 and CYP27B1, particularly by ER status. RESULTS: More AAs had severe vitamin D deficiency (< 10 ng/ml) than EAs (34.3% vs 5.9%), with lowest levels among those with the highest African ancestry. Associations for SNPs differed by race. Among AAs, VDR SNP rs2239186, associated with higher serum levels of 25OHD, decreased risk after correction for multiple testing (OR = 0.53, 95% CI = 0.31-0.79, p by permutation = 0.03), but had no effect in EAs. The majority of associations were for ER-negative breast cancer, with seven differential associations between AA and EA women for CYP24A1 (p for interaction < 0.10). SNP rs27622941 was associated with a > twofold increased risk of ER-negative breast cancer among AAs (OR = 2.62, 95% CI = 1.38-4.98), but had no effect in EAs. rs2209314 decreased risk among EAs (OR = 0.38, 95% CI = 0.20-0.73), with no associations in AAs. The increased risk of ER-negative breast cancer in AAs compared to EAs was reduced and became non-significant (OR = 1.20, 95% CI = 0.80-1.79) after adjusting for these two CYP24A1 SNPs. CONCLUSIONS: These data suggest that genetic variants in the vitamin D pathway may be related to the higher prevalence of ER-negative breast cancer in AA women.

Evaluation of chromosome 6p22 as a breast cancer risk modifier locus in a follow-up study of BRCA2 mutation carriers.

Several common germline variants identified through genome-wide association studies of breast cancer risk in the general population have recently been shown to be associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers. When combined, these variants can identify marked differences in the absolute risk of developing breast cancer for mutation carriers, suggesting that additional modifier loci may further enhance individual risk assessment for BRCA1 and BRCA2 mutation carriers. Recently, a common variant on 6p22 (rs9393597) was found to be associated with increased breast cancer risk for BRCA2 mutation carriers [hazard ratio (HR) = 1.55, 95 % confidence interval (CI) 1.25-1.92, p = 6.0 × 10(-5)]. This observation was based on data from GWAS studies in which, despite statistical correction for multiple comparisons, the possibility of false discovery remains a concern. Here, we report on an analysis of this variant in an additional 6,165 BRCA1 and 3,900 BRCA2 mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). In this replication analysis, rs9393597 was not associated with breast cancer risk for BRCA2 mutation carriers (HR = 1.09, 95 % CI 0.96-1.24, p = 0.18). No association with ovarian cancer risk for BRCA1 or BRCA2 mutation carriers or with breast cancer risk for BRCA1 mutation carriers was observed. This follow-up study suggests that, contrary to our initial report, this variant is not associated with breast cancer risk among individuals with germline BRCA2 mutations.

The aromatase gene CYP19A1: several genetic and functional lines of evidence supporting a role in reading, speech and language.

Inspired by the localization, on 15q21.2 of the CYP19A1 gene in the linkage region of speech and language disorders, and a rare translocation in a dyslexic individual that was brought to our attention, we conducted a series of studies on the properties of CYP19A1 as a candidate gene for dyslexia and related conditions. The aromatase enzyme is a member of the cytochrome P450 super family, and it serves several key functions: it catalyzes the conversion of androgens into estrogens; during early mammalian development it controls the differentiation of specific brain areas (e.g. local estrogen synthesis in the hippocampus regulates synaptic plasticity and axonal growth); it is involved in sexual differentiation of the brain; and in songbirds and teleost fishes, it regulates vocalization. Our results suggest that variations in CYP19A1 are associated with dyslexia as a categorical trait and with quantitative measures of language and speech, such as reading, vocabulary, phonological processing and oral motor skills. Variations near the vicinity of its brain promoter region altered transcription factor binding, suggesting a regulatory role in CYP19A1 expression. CYP19A1 expression in human brain correlated with the expression of dyslexia susceptibility genes such as DYX1C1 and ROBO1. Aromatase-deficient mice displayed increased cortical neuronal density and occasional cortical heterotopias, also observed in Robo1-/- mice and human dyslexic brains, respectively. An aromatase inhibitor reduced dendritic growth in cultured rat neurons. From this broad set of evidence, we propose CYP19A1 as a candidate gene for human cognitive functions implicated in reading, speech and language.

Information metrics in genetic epidemiology.

Information-theoretic metrics have been proposed for studying gene-gene and gene-environment interactions in genetic epidemiology. Although these metrics have proven very promising, they are typically interpreted in the context of communications and information transmission, diminishing their tangibility for epidemiologists and statisticians. In this paper, we clarify the interpretation of information-theoretic metrics. In particular, we develop the methods so that their relation to the global properties of probability models is made clear and contrast them with log-linear models for multinomial data. Hopefully, a better understanding of their properties and probabilistic implications will promote their acceptance and correct usage in genetic epidemiology. Our novel development also suggests new approaches to model search and computation.

Genetic predictors of taxane-induced neurotoxicity in a SWOG phase III intergroup adjuvant breast cancer treatment trial (S0221).

Taxanes have resulted in improved survival for breast cancer patients, but often cause neurological toxicities. Identification of biomarkers related to toxicities could be important for dictating treatment regimen. We evaluated single nucleotide polymorphisms (SNPs) in the Fanconi Anemia (FA)/BRCA pathway in relation to grade 3/4 neurotoxicities in patients (n = 888) from SWOG0221, a phase III adjuvant trial for breast cancer of 4 dose/schedules of cyclophosphamide (C), doxorubicin (A), and paclitaxel (T). In a separate cohort, we measured the correlation of significant FANCD2 SNPs with corresponding gene expression. For FANCD2, permutation testing revealed that 4 (out of 20) SNPs were significantly associated with an almost two-fold increased risk of toxicity. Two FANCD2 haplotypes were also associated with neurological toxicity, with odds ratios (OR) in the overall population of 1.8 (95% confidence interval (CI) 1.3, 2.5) and 1.7 (95% CI, 1.2, 2.4). Although numbers were small, an African-American-specific haplotype was associated with an almost 3-fold increase in risk of neurologic toxicity (OR = 2.84, 95% CI = 1.2, 6.9). Expression analyses revealed that significant FANCD2 SNPs were associated with FANCD2 expression levels (P = 0.03). There were no associations between SNPs in BRCA1 and neurotoxicities. In this trial of CA+T for breast cancer, SNPs in FANCD2, but not in BRCA1, were associated with a 70-80% increase in the odds of grade 3/4 neurological toxicities and increased expression of the gene. If replicated, women with these genotypes should be closely monitored for toxicities and could be targeted for preventive measures or alternative therapeutic approaches.

Association of Rad51 polymorphism with DNA repair in BRCA1 mutation carriers and sporadic breast cancer risk.

BACKGROUND: Inter-individual variation in DNA repair capacity is thought to modulate breast cancer risk. The phenotypic mutagen sensitivity assay (MSA) measures DNA strand breaks in lymphocytes; women with familial and sporadic breast cancers have a higher mean number of breaks per cell (MBPC) than women without breast cancer. Here, we explore the relationships between the MSA and the Rad51 gene, which encodes a DNA repair enzyme that interacts with BRCA1 and BRCA2, in BRCA1 mutation carriers and women with sporadic breast cancer. METHODS: Peripheral blood lymphoblasts from women with known BRCA1 mutations underwent the MSA (n = 138 among 20 families). BRCA1 and Rad51 genotyping and sequencing were performed to identify SNPs and haplotypes associated with the MSA. Positive associations from the study in high-risk families were subsequently examined in a population-based case-control study of breast cancer (n = 1170 cases and 2115 controls). RESULTS: Breast cancer diagnosis was significantly associated with the MSA among women from BRCA1 families (OR = 3.2 95%CI: 1.5-6.7; p = 0.004). The Rad51 5'UTR 135 C>G genotype (OR = 3.64; 95% CI: 1.38, 9.54; p = 0.02), one BRCA1 haplotype (p = 0.03) and in a polygenic model, the E1038G and Q356R BRCA1 SNPs were significantly associated with MBPC (p = 0.009 and 0.002, respectively). The Rad51 5'UTR 135C genotype was not associated with breast cancer risk in the population-based study. CONCLUSIONS: Mutagen sensitivity might be a useful biomarker of penetrance among women with BRCA1 mutations because the MSA phenotype is partially explained by genetic variants in BRCA1 and Rad51.

Elevated NCOR1 disrupts PPARalpha/gamma signaling in prostate cancer and forms a targetable epigenetic lesion.

The loss of anti-proliferative responsiveness in prostate cancer cell lines toward ligands for vitamin D receptor, retinoic acid receptors/retinoid X receptors and peroxisome proliferator activated receptor (PPAR)alpha/gamma may entail underlying epigenetic events, as ligand insensitivity reflects significantly altered messenger RNA expression of corepressors and histone-modifying enzymes. Expression patterns were dependent on phases of the cell cycle and associated with repressed basal gene expression of vitamin D receptor and PPARalpha/gamma target genes, for example CDKN1A [encodes p21((waf1/cip1))]. Elevated nuclear corepressor 1 (NCOR1) and nuclear corepressor 2/silencing mediator of retinoic acid and thyroid hormone receptor protein levels were detected in prostate cancer cell lines compared with non-malignant counterparts. Knockdown of the corepressor NCOR1 significantly elevated basal expression of a cohort of target genes, including CDKN1A. Both chemical [histone deacetylases inhibitor (HDACi)] and NCOR1 knockdown targeting enhanced anti-proliferative sensitivity toward PPARalpha/gamma ligands in prostate cancer cell lines. Pursuing PPARalpha/gamma signaling, microarray approaches were undertaken to identify pathways and genes regulated uniquely by a combination of PPARalpha/gamma activation and HDAC inhibition. Again, HDACi and knockdown approaches demonstrated that elevated NCOR1 expression and activity distorted PPARalpha/gamma gene targets centered on, for example cell cycle control, including CDKN1A and TGFBRAP1. Quantitative real time polymerase chain reaction validation and chromatin immunoprecipitation assays both confirmed that elevated NCOR1 disrupted the ability of PPARalpha/gamma to regulate key target genes (CDKN1A and TGFBRAP1). Interrogation of these relationships in prostate cancer samples using principal component and partial correlation analyses established significant interdependent relationships between NCOR1-PPARalpha/gamma and representative target genes, independently of androgen receptor expression. Therefore, we conclude that elevated NCOR1 distorts the actions of PPARalpha/gamma selectively and generates a potential epigenetic lesion with diagnostic and prognostic significance.

Comparison of information-theoretic to statistical methods for gene-gene interactions in the presence of genetic heterogeneity.

BACKGROUND: Multifactorial diseases such as cancer and cardiovascular diseases are caused by the complex interplay between genes and environment. The detection of these interactions remains challenging due to computational limitations. Information theoretic approaches use computationally efficient directed search strategies and thus provide a feasible solution to this problem. However, the power of information theoretic methods for interaction analysis has not been systematically evaluated. In this work, we compare power and Type I error of an information-theoretic approach to existing interaction analysis methods. METHODS: The k-way interaction information (KWII) metric for identifying variable combinations involved in gene-gene interactions (GGI) was assessed using several simulated data sets under models of genetic heterogeneity driven by susceptibility increasing loci with varying allele frequency, penetrance values and heritability. The power and proportion of false positives of the KWII was compared to multifactor dimensionality reduction (MDR), restricted partitioning method (RPM) and logistic regression. RESULTS: The power of the KWII was considerably greater than MDR on all six simulation models examined. For a given disease prevalence at high values of heritability, the power of both RPM and KWII was greater than 95%. For models with low heritability and/or genetic heterogeneity, the power of the KWII was consistently greater than RPM; the improvements in power for the KWII over RPM ranged from 4.7% to 14.2% at for α = 0.001 in the three models at the lowest heritability values examined. KWII performed similar to logistic regression. CONCLUSIONS: Information theoretic models are flexible and have excellent power to detect GGI under a variety of conditions that characterize complex diseases.

A deletion polymorphism in glutathione-S-transferase mu (GSTM1) and/or theta (GSTT1) is associated with an increased risk of toxicity after autologous blood and marrow transplantation.

Toxicity after blood and marrow transplantation (BMT) has interindividual variability that may be explained by common genetic polymorphisms in critical pathways. The glutathione-S-transferase (GST) isoenzymes detoxify the reactive oxygen species generated by chemotherapy agents and radiation. We investigated whether deletion polymorphisms in 2 GST genes (GSTM1 and GSTT1) were associated with toxicity after autologous or allogeneic BMT. The study population was selected from 699 consecutive BMT patients from 2 centers in Buffalo, NY, and Moscow, Russia, of whom 321 (203 autologous, 118 allogeneic BMT) had available banked samples and amplifiable DNA. Fifty percent of patients were homozygous null for GSTM1, which did not vary by center; however, the GSTT1 homozygous null deletion polymorphism occurred more frequently in patients treated in Moscow (38% versus 18%, P < .001). Overall grade 2-4 regimen-related toxicity occurred in 56%, with nearly 1 in 5 patients having 2 or more organ systems affected. Among autologous BMT patients, a deletion polymorphism in 1 or both genes was significantly associated with increased occurrence of overall toxicity (71% versus 56%, P = .034) and mucositis (74% versus 55%, P = .006). GSTM1 and/or GSTT1 deletion polymorphisms were not associated with toxicity after allogeneic BMT. Future studies may allow for individualized genetic risk stratification.

Comparative survival analysis of breast cancer microarray studies identifies important prognostic genetic pathways.

BACKGROUND: An estimated 12% of females in the United States will develop breast cancer in their lifetime. Although, there are advances in treatment options including surgery and chemotherapy, breast cancer is still the second most lethal cancer in women. Thus, there is a clear need for better methods to predict prognosis for each breast cancer patient. With the advent of large genetic databases and the reduction in cost for the experiments, researchers are faced with choosing from a large pool of potential prognostic markers from numerous breast cancer gene expression profile studies. METHODS: Five microarray datasets related to breast cancer were examined using gene set analysis and the cancers were categorized into different subtypes using a scoring system based on genetic pathway activity. RESULTS: We have observed that significant genes in the individual studies show little reproducibility across the datasets. From our comparative analysis, using gene pathways with clinical variables is more reliable across studies and shows promise in assessing a patient's prognosis. CONCLUSIONS: This study concludes that, in light of clinical variables, there are significant gene pathways in common across the datasets. Specifically, several pathways can further significantly stratify patients for survival. These candidate pathways should help to develop a panel of significant biomarkers for the prognosis of breast cancer patients in a clinical setting.

Information-theoretic gene-gene and gene-environment interaction analysis of quantitative traits.

BACKGROUND: The purpose of this research was to develop a novel information theoretic method and an efficient algorithm for analyzing the gene-gene (GGI) and gene-environmental interactions (GEI) associated with quantitative traits (QT). The method is built on two information-theoretic metrics, the k-way interaction information (KWII) and phenotype-associated information (PAI). The PAI is a novel information theoretic metric that is obtained from the total information correlation (TCI) information theoretic metric by removing the contributions for inter-variable dependencies (resulting from factors such as linkage disequilibrium and common sources of environmental pollutants). RESULTS: The KWII and the PAI were critically evaluated and incorporated within an algorithm called CHORUS for analyzing QT. The combinations with the highest values of KWII and PAI identified each known GEI associated with the QT in the simulated data sets. The CHORUS algorithm was tested using the simulated GAW15 data set and two real GGI data sets from QTL mapping studies of high-density lipoprotein levels/atherosclerotic lesion size and ultra-violet light-induced immunosuppression. The KWII and PAI were found to have excellent sensitivity for identifying the key GEI simulated to affect the two quantitative trait variables in the GAW15 data set. In addition, both metrics showed strong concordance with the results of the two different QTL mapping data sets. CONCLUSION: The KWII and PAI are promising metrics for analyzing the GEI of QT.

AMBIENCE: a novel approach and efficient algorithm for identifying informative genetic and environmental associations with complex phenotypes.

We developed a computationally efficient algorithm AMBIENCE, for identifying the informative variables involved in gene-gene (GGI) and gene-environment interactions (GEI) that are associated with disease phenotypes. The AMBIENCE algorithm uses a novel information theoretic metric called phenotype-associated information (PAI) to search for combinations of genetic variants and environmental variables associated with the disease phenotype. The PAI-based AMBIENCE algorithm effectively and efficiently detected GEI in simulated data sets of varying size and complexity, including the 10K simulated rheumatoid arthritis data set from Genetic Analysis Workshop 15. The method was also successfully used to detect GGI in a Crohn's disease data set. The performance of the AMBIENCE algorithm was compared to the multifactor dimensionality reduction (MDR), generalized MDR (GMDR), and pedigree disequilibrium test (PDT) methods. Furthermore, we assessed the computational speed of AMBIENCE for detecting GGI and GEI for data sets varying in size from 100 to 10(5) variables. Our results demonstrate that the AMBIENCE information theoretic algorithm is useful for analyzing a diverse range of epidemiologic data sets containing evidence for GGI and GEI.

FTO polymorphisms moderate the association of food reinforcement with energy intake.

Food reinforcement (RRVfood) is related to increased energy intake, cross-sectionally related to obesity, and prospectively related to weight gain. The fat mass and obesity-associated (FTO) gene is related to elevated body mass index and increased energy intake. The primary purpose of the current study was to determine whether any of 68 FTO single nucleotide polymorphisms (SNPs) or a FTO risk score moderate the association between food reinforcement and energy or macronutrient intake. Energy and macronutrient intake was measured using a laboratory ad libitum snack food consumption task in 237 adults of varying BMI. Controlling for BMI, the relative reinforcing value of reading (RRVreading) and proportion of African ancestry, RRVfood predicted 14.2% of the variance in energy intake, as well as predicted carbohydrate, fat, protein and sugar intake. In individual analyses, six FTO SNPs (rs12921970, rs9936768, rs12446047, rs7199716, rs8049933 and rs11076022, spanning approximately 251kbp) moderated the relationship between RRVfood and energy intake to predict an additional 4.9-7.4% of variance in energy intake. We created an FTO risk score based on 5 FTO SNPs (rs9939609, rs8050136, rs3751812, rs1421085, and rs1121980) that are related to BMI in multiple studies. The FTO risk score did not increase variance accounted for beyond individual FTO SNPs. rs12921970 and rs12446047 served as moderators of the relationship between RRVfood and carbohydrate, fat, protein, and sugar intake. This study shows for the first time that the relationship between RRVfood and energy intake is moderated by FTO SNPs. Research is needed to understand how these processes interact to predict energy and macronutrient intake.