Unsupervised discovery of ancestry-informative markers and genetic admixture proportions in biobank-scale datasets.

Admixture estimation plays a crucial role in ancestry inference and genome-wide association studies (GWASs). Computer programs such as ADMIXTURE and STRUCTURE are commonly employed to estimate the admixture proportions of sample individuals. However, these programs can be overwhelmed by the computational burdens imposed by the 105 to 106 samples and millions of markers commonly found in modern biobanks. An attractive strategy is to run these programs on a set of ancestry-informative SNP markers (AIMs) that exhibit substantially different frequencies across populations. Unfortunately, existing methods for identifying AIMs require knowing ancestry labels for a subset of the sample. This supervised learning approach creates a chicken and the egg scenario. In this paper, we present an unsupervised, scalable framework that seamlessly carries out AIM selection and likelihood-based estimation of admixture proportions. Our simulated and real data examples show that this approach is scalable to modern biobank datasets. OpenADMIXTURE, our Julia implementation of the method, is open source and available for free.

Facultative Parthenogenesis in California Condors.

Parthenogenesis is a relatively rare event in birds, documented in unfertilized eggs from columbid, galliform, and passerine females with no access to males. In the critically endangered California condor, parentage analysis conducted utilizing polymorphic microsatellite loci has identified two instances of parthenogenetic development from the eggs of two females in the captive breeding program, each continuously housed with a reproductively capable male with whom they had produced offspring. Paternal genetic contribution to the two chicks was excluded. Both parthenotes possessed the expected male ZZ sex chromosomes and were homozygous for all evaluated markers inherited from their dams. These findings represent the first molecular marker-based identification of facultative parthenogenesis in an avian species, notably of females in regular contact with fertile males, and add to the phylogenetic breadth of vertebrate taxa documented to have reproduced via asexual reproduction.

OPENMENDEL: a cooperative programming project for statistical genetics.

Statistical methods for genome-wide association studies (GWAS) continue to improve. However, the increasing volume and variety of genetic and genomic data make computational speed and ease of data manipulation mandatory in future software. In our view, a collaborative effort of statistical geneticists is required to develop open source software targeted to genetic epidemiology. Our attempt to meet this need is called the OPENMENDEL project (https://openmendel.github.io). It aims to (1) enable interactive and reproducible analyses with informative intermediate results, (2) scale to big data analytics, (3) embrace parallel and distributed computing, (4) adapt to rapid hardware evolution, (5) allow cloud computing, (6) allow integration of varied genetic data types, and (7) foster easy communication between clinicians, geneticists, statisticians, and computer scientists. This article reviews and makes recommendations to the genetic epidemiology community in the context of the OPENMENDEL project.

Diagnostic utility of transcriptome sequencing for rare Mendelian diseases.

PURPOSE: We investigated the value of transcriptome sequencing (RNAseq) in ascertaining the consequence of DNA variants on RNA transcripts to improve the diagnostic rate from exome or genome sequencing for undiagnosed Mendelian diseases spanning a wide spectrum of clinical indications. METHODS: From 234 subjects referred to the Undiagnosed Diseases Network, University of California-Los Angeles clinical site between July 2014 and August 2018, 113 were enrolled for high likelihood of having rare undiagnosed, suspected genetic conditions despite thorough prior clinical evaluation. Exome or genome sequencing and RNAseq were performed, and RNAseq data was integrated with genome sequencing data for DNA variant interpretation genome-wide. RESULTS: The molecular diagnostic rate by exome or genome sequencing was 31%. Integration of RNAseq with genome sequencing resulted in an additional seven cases with clear diagnosis of a known genetic disease. Thus, the overall molecular diagnostic rate was 38%, and 18% of all genetic diagnoses returned required RNAseq to determine variant causality. CONCLUSION: In this rare disease cohort with a wide spectrum of undiagnosed, suspected genetic conditions, RNAseq analysis increased the molecular diagnostic rate above that possible with genome sequencing analysis alone even without availability of the most appropriate tissue type to assess.

Obesity and associated lifestyles modify the effect of glucose metabolism-related genetic variants on impaired glucose homeostasis among postmenopausal women.

PURPOSE: Impaired glucose metabolism-related genetic variants likely interact with obesity-modifiable factors in response to glucose intolerance, yet their interconnected pathways have not been fully characterized. METHODS: With data from 1,027 postmenopausal participants of the Genomics and Randomized Trials Network study and 15 single-nucleotide polymorphisms (SNPs) associated with glucose homeostasis, we assessed whether obesity, physical activity, and high dietary fat intake interact with the SNP-glucose variations. We used regression analysis plus stratification and graphic approaches. RESULTS: Across carriers of the 15 SNPs, fasting levels of glucose, insulin, and homeostatic model assessment-insulin resistance (HOMA-IR) were higher in obese, inactive, and high fat-diet women than in their respective counterparts. Carriers within subgroups differently demonstrated the direction and/or magnitude of the variants' effect on glucose-relevant traits. Variants in GCKR, GCK, DGKB/TMEM195 (P for interactions = 0.02, 0.02, and 0.01), especially, showed interactions with obesity: obese, inactive, and high fat-diet women had greater increases in fasting glucose, insulin, and HOMA-IR levels. Obese carriers at TCF7L2 variant had greater increases in fasting glucose levels than nonobese carriers (P for interaction = 0.04), whereas active women had greater decreases in insulin and HOMA-IR levels than inactive women (P for interaction = 0.02 in both levels). CONCLUSIONS: Our data support the important role of obesity in modifying glucose homeostasis in response to glucose metabolism-relevant variants. These findings may inform research on the role of glucose homeostasis in the etiology of chronic disease and the development of intervention strategies to reduce risk in postmenopausal women.

Effect of genetic variants and traits related to glucose metabolism and their interaction with obesity on breast and colorectal cancer risk among postmenopausal women.

BACKGROUND: Impaired glucose metabolism-related genetic variants and traits likely interact with obesity and related lifestyle factors, influencing postmenopausal breast and colorectal cancer (CRC), but their interconnected pathways are not fully understood. By stratifying via obesity and lifestyles, we partitioned the total effect of glucose metabolism genetic variants on cancer risk into two putative mechanisms: 1) indirect (risk-associated glucose metabolism genetic variants mediated by glucose metabolism traits) and 2) direct (risk-associated glucose metabolism genetic variants through pathways other than glucose metabolism traits) effects. METHOD: Using 16 single-nucleotide polymorphisms (SNPs) associated with glucose metabolism and data from 5379 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies, we retrospectively assessed the indirect and direct effects of glucose metabolism-traits (fasting glucose, insulin, and homeostatic model assessment-insulin resistance [HOMA-IR]) using two quantitative tests. RESULTS: Several SNPs were associated with breast cancer and CRC risk, and these SNP-cancer associations differed between non-obese and obese women. In both strata, the direct effect of cancer risk associated with the SNP accounted for the majority of the total effect for most SNPs, with roughly 10% of cancer risk due to the SNP that was from an indirect effect mediated by glucose metabolism traits. No apparent differences in the indirect (glucose metabolism-mediated) effects were seen between non-obese and obese women. It is notable that among obese women, 50% of cancer risk was mediated via glucose metabolism trait, owing to two SNPs: in breast cancer, in relation to GCKR through glucose, and in CRC, in relation to DGKB/TMEM195 through HOMA-IR. CONCLUSIONS: Our findings suggest that glucose metabolism genetic variants interact with obesity, resulting in altered cancer risk through pathways other than those mediated by glucose metabolism traits.

Tobacco smoking, NBS1 polymorphisms, and survival in lung and upper aerodigestive tract cancers with semi-Bayes adjustment for hazard ratio variation.

PURPOSE: Although single nucleotide polymorphisms (SNPs) of NBS1 have been associated with susceptibility to lung and upper aerodigestive tract (UADT) cancers, their relations to cancer survival and measures of effect are largely unknown. METHODS: Using follow-up data from 611 lung cancer cases and 601 UADT cancer cases from a population-based case-control study in Los Angeles, we prospectively evaluated associations of tobacco smoking and 5 NBS1 SNPs with all-cause mortality. Mortality data were obtained from the Social Security Death Index. We used Cox regression to estimate adjusted hazard ratios (HR) for main effects and ratios of hazard ratios (RHR) derived from product terms to assess hazard ratio variations by each SNP. Bayesian methods were used to account for multiple comparisons. RESULTS: We observed 406 (66 %) deaths in lung cancer cases and 247 (41 %) deaths in UADT cancer cases with median survival of 1.43 and 1.72 years, respectively. Ever tobacco smoking was positively associated with mortality for both cancers. We observed an upward dose-response association between smoking pack-years and mortality in UADT squamous cell carcinoma. The adjusted HR relating smoking to mortality in non-small cell lung cancer (NSCLC) was greater for cases with the GG genotype of NBS1 rs1061302 than for cases with AA/AG genotypes (semi-Bayes adjusted RHR = 1.97; 95 % limits = 1.14, 3.41). CONCLUSIONS: A history of tobacco smoking at cancer diagnosis was associated with mortality among patients with lung cancer or UADT squamous cell carcinoma. The HR relating smoking to mortality appeared to vary with the NBS1 rs1061302 genotype among NSCLC cases.

Mendel: the Swiss army knife of genetic analysis programs.

UNLABELLED: Mendel is one of the few statistical genetics packages that provide a full spectrum of gene mapping methods, ranging from parametric linkage in large pedigrees to genome-wide association with rare variants. Our latest additions to Mendel anticipate and respond to the needs of the genetics community. Compared with earlier versions, Mendel is faster and easier to use and has a wider range of applications. Supported platforms include Linux, MacOS and Windows. AVAILABILITY: Free from www.genetics.ucla.edu/software/mendel.

Genetic variants of glucose metabolism and exposure to smoking in African American breast cancer.

Insulin resistance (IR) is a well-established risk factor for breast cancer (BC) development in African American (AA) postmenopausal women. While obesity and IR are more prevalent in AA than in white women, they are under-represented in genome-wide studies for systemic regulation of IR. By examining 780 genome-wide IR single-nucleotide polymorphisms (SNPs) available in our data, we tested 4689 AA women in a Random Survival Forest framework. With 37 BC-associated lifestyle factors, we conducted a gene-environment interaction analysis to estimate risk prediction for BC with the most influential genetic and behavioral factors and evaluated their combined and joint effects on BC risk. By accounting for variations of individual SNPs in BC in the prediction model, we detected four fasting glucose-associated SNPs in PCSK1, SPC25, ADCY5, and MTNR1B and three lifestyle factors (smoking, oral contraceptive use, and age at menopause) as the most predictive markers for BC risk. Our joint analysis of risk genotypes and lifestyle with smoking revealed a synergistic effect on the increased risk of BC, particularly estrogen/progesterone positive (ER/PR+) BC, in a gene-lifestyle dose-dependent manner. The joint effect of smoking was more substantial in women with prolonged exposure to cigarette smoking and female hormones. The top genome-wide association-SNPs associated with metabolic biomarkers in combination with lifestyles synergistically increase the predictability of invasive ER/PR+ BC risk among AA women. Our findings highlight generically targeted preventive interventions for women who carry particular risk genotypes and lifestyles.

Towards a Genetic Linkage Map of the California Condor, an Endangered New World Vulture Species.

The development of a linkage map is an important component for promoting genetic and genomic studies in California condors, an endangered New World vulture species. Using a set of designed anonymous microsatellite markers, we genotyped a reference condor population involving 121 individuals. After marker validation and genotype filtering, the genetic linkage analysis was performed using 123 microsatellite loci. This resulted in the identification of 15 linkage groups/subgroups that formed a first-generation condor genetic map, while no markers linked to a lethal chondrodystrophy mutation were found. A panel of polymorphic markers that is instrumental in molecular parentage diagnostics and other genetic studies in the California condor was selected. Further condor conservation genomics research will be focused on updating the linkage map and integrating it with cytogenetic and BAC-based physical maps and ultimately with the genome sequence assembly.

Synergistic Effects of Genetic Variants of Glucose Homeostasis and Lifelong Exposures to Cigarette Smoking, Female Hormones, and Dietary Fat Intake on Primary Colorectal Cancer Development in African and Hispanic/Latino American Women.

BACKGROUND: Disparities in cancer genomic science exist among racial/ethnic minorities. Particularly, African American (AA) and Hispanic/Latino American (HA) women, the 2 largest minorities, are underrepresented in genetic/genome-wide studies for cancers and their risk factors. We conducted on AA and HA postmenopausal women a genomic study for insulin resistance (IR), the main biologic mechanism underlying colorectal cancer (CRC) carcinogenesis owing to obesity. METHODS: With 780 genome-wide IR-specific single-nucleotide polymorphisms (SNPs) among 4,692 AA and 1,986 HA women, we constructed a CRC-risk prediction model. Along with these SNPs, we incorporated CRC-associated lifestyles in the model of each group and detected the topmost influential genetic and lifestyle factors. Further, we estimated the attributable risk of the topmost risk factors shared by the groups to explore potential factors that differentiate CRC risk between these groups. RESULTS: In both groups, we detected IR-SNPs in PCSK1 (in AA) and IFT172, GCKR, and NRBP1 (in HA) and risk lifestyles, including long lifetime exposures to cigarette smoking and endogenous female hormones and daily intake of polyunsaturated fatty acids (PFA), as the topmost predictive variables for CRC risk. Combinations of those top genetic- and lifestyle-markers synergistically increased CRC risk. Of those risk factors, dietary PFA intake and long lifetime exposure to female hormones may play a key role in mediating racial disparity of CRC incidence between AA and HA women. CONCLUSIONS: Our results may improve CRC risk prediction performance in those medically/scientifically underrepresented groups and lead to the development of genetically informed interventions for cancer prevention and therapeutic effort, thus contributing to reduced cancer disparities in those minority subpopulations.

Molecular Biology Networks and Key Gene Regulators for Inflammatory Biomarkers Shared by Breast Cancer Development: Multi-Omics Systems Analysis.

As key inflammatory biomarkers C-reactive protein (CRP) and interleukin-6 (IL6) play an important role in the pathogenesis of non-inflammatory diseases, including specific cancers, such as breast cancer (BC). Previous genome-wide association studies (GWASs) have neither explained the large proportion of genetic heritability nor provided comprehensive understanding of the underlying regulatory mechanisms. We adopted an integrative genomic network approach by incorporating our previous GWAS data for CRP and IL6 with multi-omics datasets, such as whole-blood expression quantitative loci, molecular biologic pathways, and gene regulatory networks to capture the full range of genetic functionalities associated with CRP/IL6 and tissue-specific key drivers (KDs) in gene subnetworks. We applied another systematic genomics approach for BC development to detect shared gene sets in enriched subnetworks across BC and CRP/IL6. We detected the topmost significant common pathways across CRP/IL6 (e.g., immune regulatory; chemokines and their receptors; interferon γ, JAK-STAT, and ERBB4 signaling), several of which overlapped with BC pathways. Further, in gene-gene interaction networks enriched by those topmost pathways, we identified KDs-both well-established (e.g., JAK1/2/3, STAT3) and novel (e.g., CXCR3, CD3D, CD3G, STAT6)-in a tissue-specific manner, for mechanisms shared in regulating CRP/IL6 and BC risk. Our study may provide robust, comprehensive insights into the mechanisms of CRP/IL6 regulation and highlight potential novel genetic targets as preventive and therapeutic strategies for associated disorders, such as BC.

Pro-inflammatory cytokine polymorphisms and interactions with dietary alcohol and estrogen, risk factors for invasive breast cancer using a post genome-wide analysis for gene-gene and gene-lifestyle interaction.

Molecular and genetic immune-related pathways connected to breast cancer and lifestyles in postmenopausal women are not fully characterized. In this study, we explored the role of pro-inflammatory cytokines such as C-reactive protein (CRP) and interleukin-6 (IL-6) in those pathways at the genome-wide level. With single-nucleotide polymorphisms (SNPs) in the biomarkers and lifestyles together, we further constructed risk profiles to improve predictability for breast cancer. Our earlier genome-wide association gene-environment interaction study used large cohort data from the Women's Health Initiative Database for Genotypes and Phenotypes Study and identified 88 SNPs associated with CRP and IL-6. For this study, we added an additional 68 SNPs from previous GWA studies, and together with 48 selected lifestyles, evaluated for the association with breast cancer risk via a 2-stage multimodal random survival forest and generalized multifactor dimensionality reduction methods. Overall and in obesity strata (by body mass index, waist, waist-to-hip ratio, exercise, and dietary fat intake), we identified the most predictive genetic and lifestyle variables. Two SNPs (SALL1 rs10521222 and HLA-DQA1 rs9271608) and lifestyles, including alcohol intake, lifetime cumulative exposure to estrogen, and overall and visceral obesity, are the most common and strongest predictive markers for breast cancer across the analyses. The risk profile that combined those variables presented their synergistic effect on the increased breast cancer risk in a gene-lifestyle dose-dependent manner. Our study may contribute to improved predictability for breast cancer and suggest potential interventions for the women with the risk genotypes and lifestyles to reduce their breast cancer risk.

Genome-wide Association Analysis of Proinflammatory Cytokines and Gene-lifestyle Interaction for Invasive Breast Cancer Risk: The WHI dbGaP Study.

Immune-related etiologic pathways to influence invasive breast cancer risk may interact with lifestyle factors, but the interrelated molecular genetic pathways are incompletely characterized. We used data from the Women's Health Initiative Database for Genotypes and Phenotypes Study including 16,088 postmenopausal women, a population highly susceptible to inflammation, obesity, and increased risk for breast cancer. With 21,784,812 common autosomal single-nucleotide polymorphisms (SNP), we conducted a genome-wide association (GWA) gene-environment interaction (G × E) analysis in six independent GWA Studies for proinflammatory cytokines [IL6 and C-reactive protein (CRP)] and their gene-lifestyle interactions. Subsequently, we tested for the association of the GWA SNPs with breast cancer risk. In women overall and stratified by obesity status (body mass index, waist circumference, and waist-to-hip ratio) and obesity-related lifestyle factors (exercise and high-fat diet), 88 GWA SNPs in 10 loci were associated with proinflammatory cytokines: 3 associated with IL6 (1 index SNP in MAPK1 and 1 independent SNP in DEC1); 85 with CRP (3 index SNPs in CRPP1, CRP, RP11-419N10.5, HNF1A-AS1, HNF1A, and C1q2orf43; and two independent SNPs in APOE and APOC1). Of those, 27 in HNF1A-AS1, HNF1A, and C1q2orf43 displayed significantly increased risk for breast cancer. We found a number of novel top markers for CRP and IL6, which interacted with obesity factors. A substantial proportion of those SNPs' susceptibility influenced breast cancer risk. Our findings may contribute to better understanding of genetic associations between pro-inflammation and cancer and suggest intervention strategies for women who carry the risk genotypes, reducing breast cancer risk. PREVENTION RELEVANCE: The top GWA-SNPs associated with pro-inflammatory biomarkers have implications for breast carcinogenesis by interacting with obesity factors. Our findings may suggest interventions for women who carry the inflammatory-risk genotypes to reduce breast cancer risk.

Genetically determined elevated C-reactive protein associated with primary colorectal cancer risk: Mendelian randomization with lifestyle interactions.

Systemic inflammation-related etiologic pathways via inflammatory cytokines in the development of colorectal cancer (CRC) have not been convincingly determined and may be confounded by lifestyle factors or reverse causality. We investigated the genetically predicted C-reactive protein (CRP) phenotype in the potential causal pathway of primary CRC risk in postmenopausal women in a Mendelian randomization (MR) framework. We employed individual-level data of the Women's Health Initiative Database for Genotypes and Phenotypes Study, which consists of 5 genome-wide association (GWA) studies, including 10,142 women, 737 of whom developed primary CRC. We examined 61 GWA single-nucleotide polymorphisms (SNPs) associated with CRP by using weighted/penalized MR weighted-medians and MR gene-environment interactions that allow some relaxation of the strict variable requirements and attenuate the heterogeneous estimates of outlying SNPs. In lifestyle-stratification analyses, genetically determined CRP exhibited its effects on the decreased CRC risk in non-viscerally obese and high-fat diet subgroups. In contrast, genetically driven CRP was associated with an increased risk for CRC in women who smoked ≥ 15 cigarettes/day, with significant interaction of the gene-smoking relationship. Further, a substantially increased risk of CRC induced by CRP was observed in relatively short-term users (< 5 years) of estrogen (E)-only and also longer-term users (5 to > 10 years) of E plus progestin. Our findings may provide novel evidence on immune-related etiologic pathways connected to CRC risk and suggest the possible use of CRP as a CRC-predictive biomarker in women with particular behaviors and CRP marker-informed interventions to reduce CRC risk.

Associations between NBS1 polymorphisms, haplotypes and smoking-related cancers.

Constituents of tobacco smoke can cause DNA double-strand breaks (DSBs), leading to tumorigenesis. The NBS1 gene product is a vital component in DSB detection and repair, thus genetic variations may influence cancer development. We examined the associations between NBS1 polymorphisms and haplotypes and newly incident smoking-related cancers in three case-control studies (Los Angeles: 611 lung and 601 upper aero-digestive tract (UADT) cancer cases and 1040 controls; Memorial Sloan-Kettering Cancer Center: 227 bladder cancer cases and 211 controls and Taixing, China: 218 esophagus, 206 stomach, 204 liver cancer cases and 415 controls). rs1061302 was associated with cancers of the lung [adjusted odds ratio (OR(adj)) = 1.6, 95% confidence interval (CI): 1.2, 2.4], larynx (OR(adj) = 0.56, 95% CI: 0.32, 0.97) and liver (OR(adj) = 1.7, 95% CI: 1.0, 2.9). Additionally, positive associations were found for rs709816 with bladder cancer (OR(adj) = 4.2, 95% CI: 1.4, 12) and rs1063054 with lung cancer (OR(adj) = 1.6, 95% CI: 1.0, 2.3). Some associations in lung and stomach cancers varied with smoking status. CAC haplotype was positively associated with smoking-related cancers: lung (OR(adj) = 1.7, 95% CI: 1.1, 2.9) and UADT (OR(adj) = 2.0, 95% CI: 1.1, 3.7), specifically, oropharynx (OR(adj) = 2.1, 95% CI: 1.0, 4.2) and larynx (OR(adj) = 4.8, 95% CI: 1.7, 14). Bayesian false-discovery probabilities were calculated to assess Type I error. It appears that NBS1 polymorphisms and haplotypes may be associated with smoking-related cancers and that these associations may differ by smoking status. Our findings also suggest that single-nucleotide polymorphisms located in the binding region of the MRE-RAD50-NBS1 complex or microRNA targeted pathways may influence tumor development. These hypotheses should be further examined in functional studies.

Single nucleotide polymorphisms of 8 inflammation-related genes and their associations with smoking-related cancers.

Tobacco smoke and its metabolites are carcinogens that increase tissue oxidative stress and induce target tissue inflammation. We hypothesized that genetic variation of inflammatory pathway genes plays a role in tobacco-related carcinogenesis and is modified by tobacco smoking. We evaluated the association of 12 single nucleotide polymorphisms of 8 inflammation-related genes with tobacco-related cancers (lung, oropharynx, larynx, esophagus, stomach, liver, bladder, and kidney) using 3 case-control studies from: Los Angeles (population-based; 611 lung and 553 upper aero-digestive tract cancer cases and 1,040 controls), Taixing, China (population-based; 218 esophagus, 206 stomach, 204 liver cancer cases, and 415 controls), and Memorial Sloan-Kettering Cancer Center (hospital-based; 227 bladder cancer cases and 211 controls). After adjusting for age, education, ethnicity, gender, and tobacco smoking, IL10 rs1800871 was inversely associated with oropharyngeal cancer (CT+TT vs. CC adjusted odds ratio [aOR]: 0.69, 95% confidence interval [CI]: 0.50-0.95), and was positively associated with lung cancer among never smokers (TT vs. CT+CC aOR: 2.5, 95% CI: 1.3-5.1) and inversely with oropharyngeal cancer among ever smokers (CT+TT vs. CC aOR: 0.63, 95% CI: 0.41-0.95). Among all pooled never smokers (588 cases and 816 controls), TNF rs1799964 was inversely associated with smoking-related cancer (CC vs. CT+TT aOR: 0.36, 95% CI: 0.17-0.77). Bayesian correction for multiple comparisons suggests that chance is unlikely to explain our findings (although epigenetic mechanisms may be in effect), which support our hypotheses, suggesting that IL10 rs1800871 is a susceptibility marker for oropharyngeal and lung cancers, and that TNF rs1799964 is associated with smoking-related cancers among never smokers.

Pathway analysis software: annotation errors and solutions.

Genetic databases contain a variety of annotation errors that often go unnoticed due to the large size of modern genetic data sets. Interpretation of these data sets requires bioinformatics tools that may contribute to this problem. While providing gene symbol annotations for identifiers (IDs) such as microarray probe set, RefSeq, GenBank, and Entrez Gene is seemingly trivial, the accuracy is fundamental to any subsequent conclusions. We examine gene symbol annotations and results from three commercial pathway analysis software (PAS) packages: Ingenuity Pathways Analysis, GeneGO, and Pathway Studio. We compare gene symbol annotations and canonical pathway results over time and among different input ID types. We find that PAS results can be affected by variation in gene symbol annotations across software releases and the input ID type analyzed. As a result, we offer suggestions for using commercial PAS and reporting microarray results to improve research quality. We propose a wiki type website to facilitate communication of bioinformatics software problems within the scientific community.

Associations between single nucleotide polymorphisms in double-stranded DNA repair pathway genes and familial breast cancer.

PURPOSE: DNA damage recognition and repair play a major role in risk for breast cancer. We investigated 104 single nucleotide polymorphisms (SNP) in 17 genes whose protein products are involved in double-stranded break repair (DSBR). EXPERIMENTAL DESIGN: We used a case-control design. Both the case individuals affected with breast cancer or with both breast and ovarian cancers and the controls had similar familial risk of breast cancer and were participants in a high-risk cancer registry. RESULTS: We found that 12 of the polymorphisms are associated with breast or breast and ovarian cancers, most notably rs16888927, rs16888997, and rs16889040, found in introns of RAD21, suggesting that SNPs in other genes in the DSBR pathway in addition to BRCA1 and BRCA2 may affect breast cancer risk. CONCLUSIONS: SNPs within or near several DSBR DNA repair pathway genes are associated with breast cancer in individuals from a high-risk population. In addition, our study reemphasizes the unique perspective that recruitment of cases and controls from family cancer registries has for gene discovery studies.