Heterogeneity In Allele Frequencies Research Articles

Molecular risk factors for locoregional recurrence in resected non-small cell lung cancer.

Locoregional recurrence is of high risk and is associated with a poor prognosis in terms of OS for non-small cell lung cancer (NSCLC). Local control is essential for radical cure of NSCLC. Previous studies have investigated the clinicopathological risk factors for locoregional recurrence, but the genomic biomarkers associated with locoregional recurrence have been inadequately studied. A total of 118 patients who underwent tumor resection with mutation-detected tumor specimens were included. Tumor samples at surgery and pretreatment/postoperative blood samples were collected for mutational profiling. Among 48 patients with disease recurrence, 46% developed locoregional recurrence (LR) and 75% developed distant metastasis (DM). The 3-year actuarial risk of LR and DM was 25% and 43%, respectively. The first sites of failure were locoregional only (29%), locoregional and distant (10%), and distant only (61%). Patients with LR showed significantly higher ctDNA level than those with only DM at the time of initial recurrence. On multivariate analysis of baseline risk factors, the presence of allele frequency heterogeneity and baseline ctDNA shedding were found to be independently associated with a higher risk of LR. Patients with disruptive TP53 mutations had significantly lower LR-free survival as compared to patients with wild-type TP53 or nondisruptive mutations. EGFR mutations showed a favorable prognostic value for LR and is not induced by EGFR tyrosine kinase inhibitor therapy. Both disruptive TP53 mutation and EGFR mutation remained the significant prognostic factor after adjustment for histological type, pathologic nodal stage and adjuvant therapy. Nearly half of disease recurrences after surgery for NSCC involved locoregional sites. We identified genomic biomarkers from baseline tumor and ctDNA samples which showed promising prognostic value for LR only. This can help identify patients who had a higher risk of locoregional recurrence regardless of the risk of distant metastasis.

Bronchoalveolar Lavage as Potential Diagnostic Specimens to Genetic Testing in Advanced Nonsmall Cell Lung Cancer.

Background: There is limited knowledge on the yield of performing capture-based targeted ultradeep sequencing on bronchoalveolar lavage (BAL) specimens from advanced nonsmall cell lung cancer (NSCLC) patients. This study aimed to evaluate gene variations and performance characteristics in BAL and tissue specimens using targeted sequencing. Methods: This cohort study retrospectively enrolled 20 patients with advanced NSCLC. The variant detection percentage, correlation of tumor mutation burden (TMB), and allele frequency heterogeneity (AFH) were compared between paired BAL and tissue samples. A three-tiered system was also applied for the interpretation of gene variants according to the guidelines. Results: No statistical difference was observed in variant detection between BAL and tissue samples (P = .591 for variant tier and P = .409 for variant type). In general, BAL achieved higher detection rates in tier I variants (96.2% vs 84.6%) and gene fusions (75% vs 50%) compared with tissue samples; tissue samples had better variants detection rates for other variants, such as tier II (89.6% vs 76.0%), tier III (87.1% vs 72.6%), single nucleotide variant (SNV, 89.6% vs 76.5%), insertion/deletion/duplication (InDel, 74.6% vs 69.8%) and copy number variation (CNV, 93.8% vs 43.8%). Besides, there were significant correlations of TMB (R2 = 0.96, P < .001) and AFH (R2 = 0.87, P < .001) between BALs and paired tissues. Conclusions: The findings demonstrate that BAL may serve as a supplement in liquid biopsy for mutation detection and for routine utilization in clinical settings.

A comparative analysis of genetic diversity of natural elk (Alces alces L.) populations from European Russia and Sumarokov elk farm population

AIM: The aim of the study is to compare the genetic diversity of two natural elk populations from the hunting farms in adjacent regions (Kostromskaya and Yaroslavskaya oblasts) with that of the man-made population of an elk farm.&#x0D; MATERIALS AND METHODS: The genetic diversity analysis was carried out using DNA-markers represented by nine microsatellite loci (169 samples).&#x0D; RESULTS: The genetic diversity level in the wild populations is reliably higher than in the elk farm population: the average allele-per-locus numbers (NA) for the natural populations are 9.0 and 8.6 respectively, for the elk farm population 5.9. All the populations studied do not differ in average heterozygosity level. The allele frequency heterogeneity test shows that all the populations differ in 6 loci and a sum of 9 loci, the natural populations differ in 5 loci, and the elk farm population differs from both the natural ones in the same 3 loci. The inbreeding coefficient for the Yaroslavskaya population (0.167) is way higher than for the Kostromskaya population (0.053), it is 0.165 for the elk farm population. With the identified gene flow (Nm = 16.7), the genetic divergence of the wild populations persists, so they do not stem from a single population.&#x0D; CONCLUSIONS: The slump found in the genetic diversity of natural elk population points to the necessity of gene pool enrichment, and the high inbreeding in wild populations implies that control over gene pool is needed.

Exploring Biologic Predictors Response Disparities to Atypical Antipsychotics among Blacks: A Quasi-Systematic Review.

Management of schizophrenia among Blacks in the United States is affected by persistent disparities. This review explored response to atypical antipsychotics among Blacks compared with other groups to assess systematic variation that may contribute to disparities. We conducted a quasi-systematic review of studies reporting response to atypical antipsychotics among Blacks compared with other groups, including effects of genetic variation. Of 48 identified research articles, 29 assessed differences in outcomes without inclusion of genetic variation and 20 explored effects of genetic variation; of note: one article included both types of data. Analysis of the 29 papers with clinical outcomes only suggests that while data on efficacy and risk of movement disorders were heterogeneous, findings indicate increased risk of metabolic effects and neutropenia among Blacks. Of the 20 articles exploring effects of genetic variation, allelic or genotypic variations involving several genes were associated with altered efficacy or safety among Blacks but not Whites, including risk of decreased response involving variation in DRD4 and DRD1, and improved efficacy associated with variants in DRD2, COMT, and RGS4. Others showed significant improvement in treatment response only among Whites, including variation in DTNBP1, DRD4, and GNB3. The current analysis can help tailor management among Blacks using an atypical antipsychotic. Heterogeneity in genetic variation effects and response allele frequency suggests that pharmacogenetics approaches for atypical antipsychotics will need to explicitly incorporate race and ethnicity.

Presence of allele frequency heterogeneity defined by ctDNA profiling predicts unfavorable overall survival of NSCLC.

The generation of subclonal (low-frequency) mutations is driven by tumor mutations and the relationship between the heterogeneity of tumor mutation abundance and non-small cell lung cancer (NSCLC) remains unknown. We investigate the role of allele frequency heterogeneity (AFH) defined by circulating tumor DNA (ctDNA) profiling in predicting prognosis in advanced NSCLC patients. Publicly available data set of POPLAR (N=211) and OAK (N=642) trials were used for analyzing. A low ratio of allele frequency (AF) of a mutation to the maximum-somatic-allele-frequency (MSAF) was used to define the presence of AFH. The prognostic value of AF/MSAF ratio that was below a defined cutoff point in overall survival (OS) was evaluated using Cox-proportional hazards regression; and the structural break point was determined by LOESS regression and Chow test. The derived AFH was also explored in an independent cohort (N=259) of advanced NSCLC receiving first-line EGFR-TKIs from the First Affiliated Hospital of Guangzhou Medical University. In the POPLAR and OAK cohort, low AF/MSAF ratio was found to be significantly associated with unfavorable OS in univariate and multivariate analysis. The structural break point analysis demonstrated that AF/MSAF <10% could yield the optimal value to stratify patients with poor OS, which was applied for defining the presence of AFH. The presence of AFH significantly correlated with unfavorable OS in advanced NSCLC regardless of treatment arms (overall: HR 1.52, immunotherapy: HR 1.81, chemotherapy: HR 1.32, all P<0.05). In the exploratory EGFR-TKIs cohort, the presence of AFH was also significantly associated with shorter OS (HR 1.72, P=0.039). Our results demonstrate that the presence of AFH predict unfavorable prognosis in advanced NSCLC despite which drug the patients used. The presence of AFH defined by ctDNA might provide an easily-accessible biomarker for risk stratification in the current clinical practice.

JAK2V617F Variant Allele Frequency Identifies Patients with Polycythemia Vera (PV) at High Risk for Venous Thrombosis

Background. Cardiovascular (CV) events are leading cause of morbidity and mortality in PV. Current risk stratification is based on variables predicting thrombotic risk, ie age >60y and history of thrombosis. Recent studies focused on additional thrombotic risk factors in PV, including generic CV factors and leukocytosis. PV patients (pts) are JAK2V617F mutated, and present wide heterogeneity in variant allele frequency (VAF); it was shown that a VAF >75% was associated with higher number of thrombotic events after diagnosis (Vannucchi AM, Leukemia 2007), but the prognostic role of JAK2 VAF is still debated.Aim. The aim of the study was to evaluate the impact of JAK2V617F VAF on rate of thrombosis in WHO-2016 defined PV pts.Patients and Method. In the CRIMM (Florence) database, a total of 577 pts with a JAK2VF VAF determined within 3 years from diagnosis, who met the 2016 WHO criteria for PV, were identified. All pts had information regarding thromboembolic events, including history of thrombosis, occurrence, type and date of thrombosis in the follow-up (FU) and presence of CV risk factors (smoking, hypertension, and diabetes mellitus). Thrombosis‐free survival (TFS) was determined from the time of diagnosis to the time the first thrombotic event occurred. Pts in whom thrombosis did not occur were censored at the time of last FU. Pre-receiver operating characteristic (ROC) plots were used to determine cutoff levels for continuous variables of interest. Differences in the distribution of continuous variables between categories were analyzed by Mann-Whitney or Kruskal-Wallis test. Pts' groups with nominal variables were compared by χ2 test. TFS was estimated by Kaplan Meier analysis; log rank test was used to compare TFS difference between groups. Cox proportional hazards regression was used for multivariable analysis. A two tailed P ≤ 0.05 was considered statistically significant.Results. The median age of pts at diagnosis was 61y, 308 (53.4%) were above 60y; 57.2% were males. All pts were mutated for JAK2V617F with a median VAF 43% (range 1-100%), 62% had at least one CV risk factor; 83 (14.4%) pts suffered from an episode of thrombosis within 3 yr from, or coincident with, diagnosis. The median FU was 7.3y (0.6-35.9y) during which 87 pts (15.1%) developed thrombosis. (50 arterial and 45 venous thrombosis). During the FU, 110 pts (19.1%) died.A JAK2VAF of ≥60% cutoff level, as determined by ROC analysis, correlated with measurements of stimulated erythropoiesis (higher hematocrit, lower mean cell volume and serum ferritin; all P<.01), leukocytosis (P<.0001), lower platelets count (P=.02) and elevated serum lactate dehydrogenase (LDH) (P<.03). Pts with ≥60% JAK2V617F VAF were at higher relative risk (RR) of having splenomegaly (RR 3.1; P<0.001), suffering from pruritus (RR 2.5; P<0.001) or constitutional symptoms (RR 1.9; P=0.01), harboring a BM fibrosis grade-1 (RR 3.1; P<0.001). Additionally, pts with a VAF>60% had greater risk to progress to PPV-MF (RR 8.5, P<.0001) and acute leukemia (RR 4.4, P=0.04) or to die (RR 3.8, P<0.0001). The JAK2VF VAF (continuous or ≥60%) did not correlate with occurrence of thrombosis at diagnosis, while the rate of thrombosis during FU was significantly increased in pts with VAF ≥60% (23.4% vs 11.0%, RR 2.4, 95%CI = 1.4-4.0; P<0.0001), more marked for venous (RR 3.7, 95%CI = 2.0-6.8; P<0.0001) than arterial (RR 1.8, 95%CI = 0.9-3.3; P=0.05) thrombosis. The impact of VAF on thrombosis during FU was then estimated according to the conventional risk category. In low risk pts (LR) (n=236), factors significantly associated with occurrence of FU thrombosis were CV risk factors (dyslipidemia (RR 3.3, P = 0.02) and hypertension (RR 1.8, P=0.048)), a G1 BM fibrosis (RR 5.3, P=0.006), presence of splenomegaly (RR, 3.2, P=0.001) or constitutional symptoms (RR 3.3, P=0.003) and a VAF ≥60% (RR 2.2, P = 0.024). In high risk pts (HR) (n=341), factors significant for FU thrombosis were splenomegaly (RR 2.0, P=0.03), elevated LDH (RR 4.0, P=0.009) and a VAF ≥60% (RR 2.3, P = 0.012). A VAF ≥60% was correlated with shortened venous TFS after diagnosis in HR (P = 0.01, HR = 3.2, 95%CI = 1.2−8.3; fig.) but not in LR pts (P = 0.20, HR = 1.1, 95%CI = 0.5−2.9).Conclusions. This study indicates that conventionally-defined high-risk PV pts with a JAK2V617F VAF ≥60% suffer from increased rate of venous events and might be worthwhile of more intensive antithrombotic prophylaxis. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Transition-transversion encoding and genetic relationship metric in ReliefF feature selection improves pathway enrichment in GWAS

BackgroundReliefF is a nearest-neighbor based feature selection algorithm that efficiently detects variants that are important due to statistical interactions or epistasis. For categorical predictors, like genotypes, the standard metric used in ReliefF has been a simple (binary) mismatch difference. In this study, we develop new metrics of varying complexity that incorporate allele sharing, adjustment for allele frequency heterogeneity via the genetic relationship matrix (GRM), and physicochemical differences of variants via a new transition/transversion encoding.MethodsWe introduce a new two-dimensional transition/transversion genotype encoding for ReliefF, and we implement three ReliefF attribute metrics: 1.) genotype mismatch (GM), which is the ReliefF standard, 2.) allele mismatch (AM), which accounts for heterozygous differences and has not been used previously in ReliefF, and 3.) the new transition/transversion metric. We incorporate these attribute metrics into the ReliefF nearest neighbor calculation with a Manhattan metric, and we introduce GRM as a new ReliefF nearest-neighbor metric to adjust for allele frequency heterogeneity.ResultsWe apply ReliefF with each metric to a GWAS of major depressive disorder and compare the detection of genes in pathways implicated in depression, including Axon Guidance, Neuronal System, and G Protein-Coupled Receptor Signaling. We also compare with detection by Random Forest and Lasso as well as random/null selection to assess pathway size bias.ConclusionsOur results suggest that using more genetically motivated encodings, such as transition/transversion, and metrics that adjust for allele frequency heterogeneity, such as GRM, lead to ReliefF attribute scores with improved pathway enrichment.

P3.02-032 Spatial Heterogeneity of EGFR and KRAS Variant Allele Frequencies Correlates with Histological Patterns of Lung Adenocarcinomas

P3.02-032 Spatial Heterogeneity of EGFR and KRAS Variant Allele Frequencies Correlates with Histological Patterns of Lung Adenocarcinomas

An urban stream can support a healthy population of coastal cutthroat trout

Urbanization presents numerous challenges to aquatic species. For fish, typical threats include altered flow dynamics, poor water quality, and degraded food webs. These threats can be detrimental to fish and whether urban environments can support healthy populations is unclear. Tryon Creek is one of the largest urban watersheds in Portland, Oregon where developed land accounts for 55.6% of total land use. We used demographic, life history, disease, and genetic indices to assess the overall health of the Coastal Cutthroat Trout (Oncorhynchus clarkii) population in Tryon Creek. Results of these population indicators were within ranges for streams with Coastal Cutthroat Trout populations not influenced by urbanization and considered healthy. Coastal Cutthroat Trout in Tryon Creek exhibited a mean condition factor of 1.07 (95% CI 0.95–1.19, range 0.94–1.24), four size-classes, an estimated density of 0.01–0.03 individuals/m2, and migratory behavior. The population did not exhibit excessive deviation from Hardy–Weinberg equilibrium. Genetic diversity in Tryon Creek (He = 0.76; allelic richness = 6.6) was comparable to that observed in non-urbanized streams in the Mt. Hood National Forest (He = 0.72; allelic richness = 5.6). Moreover, allele frequencies appeared stable, and no genetic divergence was detected among generations (F ST ~0.00; non-significant allele frequency heterogeneity tests). The population tested negative for 12 different pathogens and results for Renibacterium salmoninarum were inconclusive. The characteristics of Coastal Cutthroat Trout in Tryon Creek were similar to populations not influenced by urbanization which suggests an urban stream can support a healthy fish population.

Abstract 1315: Estimating sex-specific effects of genetic loci associated with glioma risk

Abstract BACKGROUND: Incidence of glioma varies significantly by sex, and most glioma histologies occur with greater incidence in males. Previous analyses have examined the impact of estrogen exposure as a risk factor for these tumors, but have found results of varying significance and low effect size. There may be differences in effect of previously discovered risk alleles that contribute to sex differences. METHODS: Using data collected for three previous glioma GWAS in European-ancestry populations (MD Anderson Cancer Center, the San Francisco Adult Glioma Study, and the Glioma International Case Control Study) we assessed sex-specific effects for 14 previously identified and 13 newly identified glioma risk SNPs (27 total) overall and for glioblastoma (GBM) and non-GBM tumors separately. There were 3,892 male cases (59% GBM), 4,522 male controls, 2,500 female cases (52% GBM) and 4,940 female controls. Sex-specific odds ratios (ORM and ORF), 95% confidence intervals (95% CI) and p values (pM and pF) were generated using stratified logistic regression models. Data from each study were analyzed separately and combined using inverse variance weighted meta-analysis. Results were considered statistically significant at p&amp;lt;6.2x10-4. RESULTS: In GBM, rs11979158 (7p11.2, pM=1.01x10-10, ORM=1.43 [95% CI: 1.28-1.59]; pF=3.43x10-3, ORF=1.22 [95% CI: 1.07-1.39]) and rs2562152 (16p13.3, pM=5.59x10-4, ORM=1.23 [95% CI: 1.09-1.39]; pF=1.22x10-1, ORF=1.12 [95% CI: 0.97-1.29]) had significant effect in males only. In non-GBM gliomas, rs12076373 (1q44, pM=3.56x10-7, ORM=1.41, 95% CI: 1.23-1.61; pF=1.76x10-2, ORF=1.20, 95% CI: 1.03-1.38), rs11979158 (7p11.2, pM=1.77x10-5, ORM=1.32 [95% CI: 1.16-1.49]; pF=2.73x10-1, ORF=1.08 [95% CI: 0.94-1.24]), and rs3751667 (16p13.3, pM=9.44x10-7, ORM=1.30 [95% CI: 1.17-1.44]; pF=5.18x10-2, ORF=1.13 [95% CI: 1.00-1.28]) had significant effect in males only. Effect size for rs55705857 (8q24.21) varied significantly by sex, with ORM=2.63 (95% CI: 2.24-3.09, pM=4.42x10-32), as compared to ORF=3.95 (95% CI: 3.28-4.76, pF=1.82x10-47). A sensitivity analysis was performed due to allele frequency heterogeneity by study and results did not change. CONCLUSIONS: Sex differences and other demographic differences in cancer susceptibility can provide important clues to etiology, and these differences can be leveraged for discovery in genetic association studies. Significant differences in effect size may suggest variation in genetic effect of risk alleles or in unidentified risk factors that vary in prevalence or effect by sex. There may also be differences in the distribution of molecular subtypes within each histology by sex. Further investigation using an agnostic approach may further elucidate the relationship between effect of risk alleles and sex. Citation Format: Quinn T. Ostrom, Ben Kinnersley, Margaret Wrensch, Jeanette E. Eckel-Passow, Georgina Armstrong, Terri Rice, Yanwen Chen, John Wiencke, Lucie McCoy, Helen Hansen, Christopher Amos, Jonine L. Bernstein, Elizabeth B. Claus, Dora Il'yasova, Christoffer Johansen, Daniel Lachance, Rose Lai, Ching C. Lau, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, Richard S. Houlston, Robert B. Jenkins, Beatrice Melin, Melissa Bondy, Jill S. Barnholtz-Sloan. Estimating sex-specific effects of genetic loci associated with glioma risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1315. doi:10.1158/1538-7445.AM2017-1315

Evaluating the association of multiple single nucleotide polymorphisms with response to gemcitabine and platinum combination chemotherapy in urothelial carcinoma of the bladder

To examine germline single nucleotide polymorphisms (SNPs) as markers of response to gemcitabine platinum (GP) combination chemotherapy in urothelial carcinoma (UC). Saliva or blood was prospectively collected from 216 patients treated with GP for UC of the bladder between 1991 and 2011. Based on reported associations with gemcitabine and cisplatin response or putative mechanisms of gemcitabine or cisplatin/carboplatin activity, we selected SNPs of interest and were able to genotype 59 SNPs (using the SequenomMass ARRAYiPLEX platform) in 261 patients randomly split 2/3 into a training set (n=174) and 1/3 into a test set (n=87). Logistic regression was used to test the association between response to GP and SNPs. The median age at diagnosis was 64 years (range: 28-85) for the discovery set and 67 years (range: 30-84) for the validation set. Males composed 76% and 69%, and white non-Hispanics composed 88% and 91% of the training and test validation sets, respectively. Three SNPs on GALNTL4 (rs7937567, rs12278731, and rs9988868) and one intergenic SNP (rs1321391) were significantly associated with response to GP in the training set and were used to build a SNP score. However, when assessed in the test set, the SNP score was not significantly associated with response. Multiple SNPs selected from previous studies failed to predict response to GP in this cohort. Larger studies capable of accounting for population-based allele frequency heterogeneity may be required for replication of genetic alterations important to pharmacogenomics. .

Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. I: Multivariate Gaussian priors for marker effects and derivation of the joint probability mass function of genotypes

It is important to consider heterogeneity of marker effects and allelic frequencies in across population genome-wide prediction studies. Moreover, all regression models used in genome-wide prediction overlook randomness of genotypes. In this study, a family of hierarchical Bayesian models to perform across population genome-wide prediction modeling genotypes as random variables and allowing population-specific effects for each marker was developed. Models shared a common structure and differed in the priors used and the assumption about residual variances (homogeneous or heterogeneous). Randomness of genotypes was accounted for by deriving the joint probability mass function of marker genotypes conditional on allelic frequencies and pedigree information. As a consequence, these models incorporated kinship and genotypic information that not only permitted to account for heterogeneity of allelic frequencies, but also to include individuals with missing genotypes at some or all loci without the need for previous imputation. This was possible because the non-observed fraction of the design matrix was treated as an unknown model parameter. For each model, a simpler version ignoring population structure, but still accounting for randomness of genotypes was proposed. Implementation of these models and computation of some criteria for model comparison were illustrated using two simulated datasets. Theoretical and computational issues along with possible applications, extensions and refinements were discussed. Some features of the models developed in this study make them promising for genome-wide prediction, the use of information contained in the probability distribution of genotypes is perhaps the most appealing. Further studies to assess the performance of the models proposed here and also to compare them with conventional models used in genome-wide prediction are needed.

Genetic and spatial structuring of the California vole (Microtus californicus) through a multiannual density peak and decline

Arvicoline rodents serve as model organisms for investigating the intricacies of ecological/evolutionary feedbacks that characterize multiannual fluctuations in abundance. A population of California voles (Microtus californicus) in central California was followed for 3.5 years using 4 small grids located 50 m apart. Blood samples were scored for 4 polymorphic allozyme loci by starch gel electrophoresis. These were carefully chosen for their potential to reveal details of genetic structuring among demes. A low density of voles developed into a peak followed by a rapid decline to low density. Heterozygosity averaged 20.2% (n = 709) with loci-specific shifts associated with density, season, and cyclic phase. Statistically significant heterogeneity in genotypic and allelic frequencies among the grids was found for 3 of the loci. Pairwise comparisons among the grids for each locus separately (n = 24) yielded 11 significantly disparate pairs for genotypic frequencies and 10 for alleles. Significant correlations...

Cross-population joint analysis of eQTLs: fine mapping and functional annotation.

Mapping expression quantitative trait loci (eQTLs) has been shown as a powerful tool to uncover the genetic underpinnings of many complex traits at molecular level. In this paper, we present an integrative analysis approach that leverages eQTL data collected from multiple population groups. In particular, our approach effectively identifies multiple independent cis-eQTL signals that are consistent across populations, accounting for population heterogeneity in allele frequencies and linkage disequilibrium patterns. Furthermore, by integrating genomic annotations, our analysis framework enables high-resolution functional analysis of eQTLs. We applied our statistical approach to analyze the GEUVADIS data consisting of samples from five population groups. From this analysis, we concluded that i) jointly analysis across population groups greatly improves the power of eQTL discovery and the resolution of fine mapping of causal eQTL ii) many genes harbor multiple independent eQTLs in their cis regions iii) genetic variants that disrupt transcription factor binding are significantly enriched in eQTLs (p-value = 4.93 × 10-22).

A2.5 Association study in portuguese patients with ankylosing spondylitis using the immunochip

Background and ObjectivesAnkylosing spondylitis (AS), a common inflammatory arthritis affecting primarily the spine and pelvis, is a highly heritable disease. In addition to HLA-B*27, 25 loci were associated with AS...

A Genome Wide Association Study Identifies Common Variants Associated with Lipid Levels in the Chinese Population

Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several lipid-associated loci, but these loci have been identified primarily in European populations. In order to identify genetic markers for lipid levels in a Chinese population and analyze the heterogeneity between Europeans and Asians, especially Chinese, we performed a meta-analysis of two genome wide association studies on four common lipid traits including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) in a Han Chinese population totaling 3,451 healthy subjects. Replication was performed in an additional 8,830 subjects of Han Chinese ethnicity. We replicated eight loci associated with lipid levels previously reported in a European population. The loci genome wide significantly associated with TC were near DOCK7, HMGCR and ABO; those genome wide significantly associated with TG were near APOA1/C3/A4/A5 and LPL; those genome wide significantly associated with LDL were near HMGCR, ABO and TOMM40; and those genome wide significantly associated with HDL were near LPL, LIPC and CETP. In addition, an additive genotype score of eight SNPs representing the eight loci that were found to be associated with lipid levels was associated with higher TC, TG and LDL levels (P = 5.52×10-16, 1.38×10-6 and 5.59×10-9, respectively). These findings suggest the cumulative effects of multiple genetic loci on plasma lipid levels. Comparisons with previous GWAS of lipids highlight heterogeneity in allele frequency and in effect size for some loci between Chinese and European populations. The results from our GWAS provided comprehensive and convincing evidence of the genetic determinants of plasma lipid levels in a Chinese population.

Heterogeneity of alleles encoding high‐ and low‐prevalence red blood cell antigens across Africa: useful data to facilitate transfusion in African patients

Ethnic variations in red blood cell (RBC) antigens can be a source of alloimmunization, especially in migrant populations. To improve transfusion safety in continental Africa and countries with African migrants, we performed RBC genotyping to determine allele frequencies coding for high- and low-prevalence antigens. A total of 481 blood samples were collected in ethnic groups from West, Central and East Africa. Molecular typing was performed using a polymerase chain reaction - reverse sequence specific oligonucleotide method. Results demonstrated no DI*1, DI*3, YT*2, SC*2, LW*7, KN*2 alleles in any sample and the CO*2 allele was rare. The frequency of LU*1 was comparable to that of European-Caucasians (2%) except in Biaka pygmies (8%). The frequency of CROM*-1 was high in Mbuti pygmies (13%). High frequency of KN*7 and KN*6 may reflect selection pressure in the countries investigated. Analysis of Dombrock allele patterns confirmed uneven distribution of the DO*1 and DO*2 alleles with high frequencies of DO*-4 and DO*-5 in all groups. Altogether, findings demonstrated extensive allele-frequency heterogeneity across Africa and suggested that knowledge of patient ethnicity gives information about the high-prevalence antigens that may be lacking. These data are medically useful to support transfusion care of African migrants living in countries where the majority of the population is from a different ethnical background.

To Replicate or Not to Replicate: The Case of Pharmacogenetic Studies

Replication of positive findings from genetic association studies has long served as the gold standard for establishing validity of observed genotype–phenotype associations.1–3 In addition to adequate statistical power and sound epidemiological design aimed at minimizing biases, suggested criteria for successful replication studies include: (1) same genetic variant, (2) same direction of association, (3) same definition of the phenotype, and (4) same ethnic group as reported in the discovery study.1 However, in the context of pharmacogenetics, the phenotype requirement is further constrained by the drug and intervention strategy of the initial investigation. As a result, and because many pharmacogenetic and pharmacogenomic studies arise from randomized clinical trials, replication of gene–drug response associations has proven to be a costly and logistically difficult endeavor.4,5 In light of these constraints, this review presents the case for rethinking the replication requirement and proposes several alternative approaches to validating pharmacogenomic findings. Response by Ioannidis on p 412 The prevailing view is that the requirement of replication, currently imposed or strongly suggested by most peer-reviewed journals, has improved the quality of published studies by reducing false-positive findings and overcoming the winner’s curse.6 At first glance, replication rates for findings from both candidate gene studies and agnostic approaches, such as genome-wide association studies (GWAS) and more commonly whole exome or whole genome scans, appear low. For example, of 70 previously reported candidate loci for common diseases, only 22 had P values <10−7 across 100 subsequently conducted GWAS.7 Similarly, a recent analysis of large-scale genetic studies including at least 50 variants and published between 2007 and 2010 suggests that only 1.2% of initial findings are replicated.8 In pharmacogenetic studies of cardiovascular outcomes, where the phenotype is defined as response to drug treatment, the replication rate (3.4%) is comparable to …

Estimating the numbers of malaria infections in blood samples using high-resolution genotyping data.

People living in endemic areas often habour several malaria infections at once. High-resolution genotyping can distinguish between infections by detecting the presence of different alleles at a polymorphic locus. However the number of infections may not be accurately counted since parasites from multiple infections may carry the same allele. We use simulation to determine the circumstances under which the number of observed genotypes are likely to be substantially less than the number of infections present and investigate the performance of two methods for estimating the numbers of infections from high-resolution genotyping data.The simulations suggest that the problem is not substantial in most datasets: the disparity between the mean numbers of infections and of observed genotypes was small when there was 20 or more alleles, 20 or more blood samples, a mean number of infections of 6 or less and where the frequency of the most common allele was no greater than 20%. The issue of multiple infections carrying the same allele is unlikely to be a major component of the errors in PCR-based genotyping.Simulations also showed that, with heterogeneity in allele frequencies, the observed frequencies are not a good approximation of the true allele frequencies. The first method that we proposed to estimate the numbers of infections assumes that they are a good approximation and hence did poorly in the presence of heterogeneity. In contrast, the second method by Li et al estimates both the numbers of infections and the true allele frequencies simultaneously and produced accurate estimates of the mean number of infections.

Correcting for Population Stratification in Genomewide Association Studies

Genomewide association studies have become the primary tool for discovering the genetic basis of complex human diseases. Such studies are susceptible to the confounding effects of population stratification, in that the combination of allele-frequency heterogeneity with disease-risk heterogeneity among different ancestral subpopulations can induce spurious associations between genetic variants and disease. This article provides a statistically rigorous and computationally feasible solution to this challenging problem of unmeasured confounders. We show that the odds ratio of disease with a genetic variant is identifiable if and only if the genotype is independent of the unknown population substructure conditional on a set of observed ancestry-informative markers in the disease-free population. Under this condition, the odds ratio of interest can be estimated by fitting a semiparametric logistic regression model with an arbitrary function of a propensity score relating the genotype probability to ancestry-informative markers. Approximating the unknown function of the propensity score by B-splines, we derive a consistent and asymptotically normal estimator for the odds ratio of interest with a consistent variance estimator. Simulation studies demonstrate that the proposed inference procedures perform well in realistic settings. An application to the well-known Wellcome Trust Case-Control Study is presented. Supplemental materials are available online, including a comment by Tchetgen Tchetgen and rejoinder.