PGA: power calculator for case-control genetic association analyses

<p>Abstract</p> <p>Background</p> <p>Statistical power calculations inform the design and interpretation of genetic association studies, but few programs are tailored to case-control studies of single nucleotide polymorphisms (SNPs) in unrelated subjects.</p> <p>Results</p> <p>We have developed the "Power for Genetic Association analyses" (PGA) package which comprises algorithms and graphical user interfaces for sample size and minimum detectable risk calculations using SNP or haplotype effects under different genetic models and study constrains. The software accounts for linkage disequilibrium and statistical multiple comparisons. The results are presented in graphs or tables and can be printed or exported in standard file formats.</p> <p>Conclusion</p> <p>PGA is user friendly software that can facilitate decision making for association studies of candidate genes, fine-mapping studies, and whole-genome scans. Stand-alone executable files and a Matlab toolbox are available for download at: <url>http://dceg.cancer.gov/bb/tools/pga</url></p

Global Change Could Amplify Fire Effects on Soil Greenhouse Gas Emissions

Background: Little is known about the combined impacts of global environmental changes and ecological disturbances on ecosystem functioning, even though such combined impacts might play critical roles in shaping ecosystem processes that can in turn feed back to climate change, such as soil emissions of greenhouse gases.[br/] Methodology/Principal Findings: We took advantage of an accidental, low-severity wildfire that burned part of a long-term global change experiment to investigate the interactive effects of a fire disturbance and increases in CO(2) concentration, precipitation and nitrogen supply on soil nitrous oxide (N(2)O) emissions in a grassland ecosystem. We examined the responses of soil N(2)O emissions, as well as the responses of the two main microbial processes contributing to soil N(2)O production - nitrification and denitrification - and of their main drivers. We show that the fire disturbance greatly increased soil N(2)O emissions over a three-year period, and that elevated CO(2) and enhanced nitrogen supply amplified fire effects on soil N(2)O emissions: emissions increased by a factor of two with fire alone and by a factor of six under the combined influence of fire, elevated CO(2) and nitrogen. We also provide evidence that this response was caused by increased microbial denitrification, resulting from increased soil moisture and soil carbon and nitrogen availability in the burned and fertilized plots. [br/] Conclusions/Significance: Our results indicate that the combined effects of fire and global environmental changes can exceed their effects in isolation, thereby creating unexpected feedbacks to soil greenhouse gas emissions. These findings highlight the need to further explore the impacts of ecological disturbances on ecosystem functioning in the context of global change if we wish to be able to model future soil greenhouse gas emissions with greater confidence

PADB : Published Association Database

<p>Abstract</p> <p>Background</p> <p>Although molecular pathway information and the International HapMap Project data can help biomedical researchers to investigate the aetiology of complex diseases more effectively, such information is missing or insufficient in current genetic association databases. In addition, only a few of the environmental risk factors are included as gene-environment interactions, and the risk measures of associations are not indexed in any association databases.</p> <p>Description</p> <p>We have developed a published association database (PADB; <url>http://www.medclue.com/padb</url>) that includes both the genetic associations and the environmental risk factors available in PubMed database. Each genetic risk factor is linked to a molecular pathway database and the HapMap database through human gene symbols identified in the abstracts. And the risk measures such as odds ratios or hazard ratios are extracted automatically from the abstracts when available. Thus, users can review the association data sorted by the risk measures, and genetic associations can be grouped by human genes or molecular pathways. The search results can also be saved to tab-delimited text files for further sorting or analysis. Currently, PADB indexes more than 1,500,000 PubMed abstracts that include 3442 human genes, 461 molecular pathways and about 190,000 risk measures ranging from 0.00001 to 4878.9.</p> <p>Conclusion</p> <p>PADB is a unique online database of published associations that will serve as a novel and powerful resource for reviewing and interpreting huge association data of complex human diseases.</p

A Covering Method for Detecting Genetic Associations between Rare Variants and Common Phenotypes

Genome wide association (GWA) studies, which test for association between common genetic markers and a disease phenotype, have shown varying degrees of success. While many factors could potentially confound GWA studies, we focus on the possibility that multiple, rare variants (RVs) may act in concert to influence disease etiology. Here, we describe an algorithm for RV analysis, RARECOVER. The algorithm combines a disparate collection of RVs with low effect and modest penetrance. Further, it does not require the rare variants be adjacent in location. Extensive simulations over a range of assumed penetrance and population attributable risk (PAR) values illustrate the power of our approach over other published methods, including the collapsing and weighted-collapsing strategies. To showcase the method, we apply RARECOVER to re-sequencing data from a cohort of 289 individuals at the extremes of Body Mass Index distribution (NCT00263042). Individual samples were re-sequenced at two genes, FAAH and MGLL, known to be involved in endocannabinoid metabolism (187Kbp for 148 obese and 150 controls). The RARECOVER analysis identifies exactly one significantly associated region in each gene, each about 5 Kbp in the upstream regulatory regions. The data suggests that the RVs help disrupt the expression of the two genes, leading to lowered metabolism of the corresponding cannabinoids. Overall, our results point to the power of including RVs in measuring genetic associations.National Science Foundation (U.S.) (grant (IIS-0810905)National Institutes of Health (U.S.) (U19 AG023122-05)National Institutes of Health (U.S.) (R01 MH078151-03)Louis & Harold Price FoundationNational Institutes of Health (U.S.) (N01 MH22005)National Institutes of Health (U.S.) (U01-DA024417-01)National Institutes of Health (U.S.) (P50 MH081755-01)National Institutes of Health (U.S.) (R01 AG030474-02)National Institutes of Health (U.S.) (N01 MH022005)National Institutes of Health (U.S.) (R01 HL089655-02)National Institutes of Health (U.S.) (R01 MH080134-03)National Institutes of Health (U.S.) (U54 CA143906-01)National Institutes of Health (U.S.) (UL1 RR025774-03)Scripps Genomic Medicine ProgramNational Human Genome Research Institute (U.S.) (Grant Number T32 HG002295

IGF-1, IGFBP-1, and IGFBP-3 Polymorphisms Predict Circulating IGF Levels but Not Breast Cancer Risk: Findings from the Breast and Prostate Cancer Cohort Consortium (BPC3)

IGF-1 has been shown to promote proliferation of normal epithelial breast cells, and the IGF pathway has also been linked to mammary carcinogenesis in animal models. We comprehensively examined the association between common genetic variation in the IGF1, IGFBP1, and IGFBP3 genes in relation to circulating IGF-I and IGFBP-3 levels and breast cancer risk within the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). This analysis included 6,912 breast cancer cases and 8,891 matched controls (n = 6,410 for circulating IGF-I and 6,275 for circulating IGFBP-3 analyses) comprised primarily of Caucasian women drawn from six large cohorts. Linkage disequilibrium and haplotype patterns were characterized in the regions surrounding IGF1 and the genes coding for two of its binding proteins, IGFBP1 and IGFBP3. In total, thirty haplotype-tagging single nucleotide polymorphisms (htSNP) were selected to provide high coverage of common haplotypes; the haplotype structure was defined across four haplotype blocks for IGF1 and three for IGFBP1 and IGFBP3. Specific IGF1 SNPs individually accounted for up to 5% change in circulating IGF-I levels and individual IGFBP3 SNPs were associated up to 12% change in circulating IGFBP-3 levels, but no associations were observed between these polymorphisms and breast cancer risk. Logistic regression analyses found no associations between breast cancer and any htSNPs or haplotypes in IGF1, IGFBP1, or IGFBP3. No effect modification was observed in analyses stratified by menopausal status, family history of breast cancer, body mass index, or postmenopausal hormone therapy, or for analyses stratified by stage at diagnosis or hormone receptor status. In summary, the impact of genetic variation in IGF1 and IGFBP3 on circulating IGF levels does not appear to substantially influence breast cancer risk substantially among primarily Caucasian postmenopausal women

Genome-Wide Association Study of Relative Telomere Length

Telomere function is essential to maintaining the physical integrity of linear chromosomes and healthy human aging. The probability of forming proper telomere structures depends on the length of the telomeric DNA tract. We attempted to identify common genetic variants associated with log relative telomere length using genome-wide genotyping data on 3,554 individuals from the Nurses' Health Study and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial that took part in the National Cancer Institute Cancer Genetic Markers of Susceptibility initiative for breast and prostate cancer. After genotyping 64 independent SNPs selected for replication in additional Nurses' Health Study and Women's Genome Health Study participants, we did not identify genome-wide significant loci; however, we replicated the inverse association of log relative telomere length with the minor allele variant [C] of rs16847897 at the TERC locus (per allele β = −0.03, P = 0.003) identified by a previous genome-wide association study. We did not find evidence for an association with variants at the OBFC1 locus or other loci reported to be associated with telomere length. With this sample size we had >80% power to detect β estimates as small as ±0.10 for SNPs with minor allele frequencies of ≥0.15 at genome-wide significance. However, power is greatly reduced for β estimates smaller than ±0.10, such as those for variants at the TERC locus. In general, common genetic variants associated with telomere length homeostasis have been difficult to detect. Potential biological and technical issues are discussed

Genome-wide association studies of cancer: current insights and future perspectives.

Genome-wide association studies (GWAS) provide an agnostic approach for investigating the genetic basis of complex diseases. In oncology, GWAS of nearly all common malignancies have been performed, and over 450 genetic variants associated with increased risks have been identified. As well as revealing novel pathways important in carcinogenesis, these studies have shown that common genetic variation contributes substantially to the heritable risk of many common cancers. The clinical application of GWAS is starting to provide opportunities for drug discovery and repositioning as well as for cancer prevention. However, deciphering the functional and biological basis of associations is challenging and is in part a barrier to fully unlocking the potential of GWAS

A common variant at 8q24.21 is associated with renal cell cancer

Contains fulltext : 128587.pdf (publisher's version ) (Open Access)Renal cell carcinoma (RCC) represents between 80 and 90% of kidney cancers. Previous genome-wide association studies of RCC have identified five variants conferring risk of the disease. Here we report the results from a discovery RCC genome-wide association study and replication analysis, including a total of 2,411 patients and 71,497 controls. One variant, rs35252396[CG] located at 8q24.21, is significantly associated with RCC after combining discovery and replication results (OR=1.27, Pcombined=5.4 x 10(-11)) and has an average risk allele frequency in controls of 46%. rs35252396[CG] does not have any strongly correlated variants in the genome and is located within a region predicted to have regulatory functions in several cell lines, including six originating from the kidney. This is the first RCC variant reported at 8q24.21 and it is largely independent (r(2)</=0.02) of the numerous previously reported cancer risk variants at this locus