PSCA rs2294008 Polymorphism with Increased Risk of Cancer

Background

Published data on the association between PSCA rs2294008 polymorphism and cancer risk have implicated inconclusive results. To determine the relationship and to precisely assess the effect size estimate of the association, we performed a meta-analysis.

Methods

We searched published literature in Embase and PubMed databases using the search terms “PSCA”, “prostate stem cell antigen”, “variants”, “polymorphism”, “polymorphisms”, and “cancer”. A total of 21 eligible articles were retrieved, with 27, 197 cancer cases and 48, 237 controls.

Results

On the whole, we found the association between PSCA rs2294008 polymorphism and cancer risk was statistically significant: TT vs CC: OR = 1.18, 95% CI, 1.10 to 1.27; TT + CT vs CC: OR = 1.08, 95% CI, 1.05 to 1.10; TT vs CT + CC: OR = 1.14, 95% CI, 1.07 to 1.21; T vs C: OR = 1.10, 95% CI, 1.06 to 1.14; CT vs CC: OR = 1.10, 95% CI, 1.06 to 1.13. Stratified analyses in cancer type and ethnicity showed similar results.

Conclusions

Based on the statistical evidence, we can draw a conclusion that the rs2294008 polymorphism of PSCA gene is likely to play a role in cancer carcinogenesis, especially in gastric cancer and bladder cancer.     

Classification of Epidermal Growth Factor Receptor Gene Mutation Status Using Serum Proteomic Profiling Predicts Tumor Response in Patients with Stage IIIB or IV Non-Small-Cell Lung Cancer

Objectives

Epidermal growth factor receptor (EGFR) gene mutations in tumors predict tumor response to EGFR tyrosine kinase inhibitors (EGFR-TKIs) in non-small-cell lung cancer (NSCLC). However, obtaining tumor tissue for mutation analysis is challenging. Here, we aimed to detect serum peptides/proteins associated with EGFR gene mutation status, and test whether a classification algorithm based on serum proteomic profiling could be developed to analyze EGFR gene mutation status to aid therapeutic decision-making.

Patients and Methods

Serum collected from 223 stage IIIB or IV NSCLC patients with known EGFR gene mutation status in their tumors prior to therapy was analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and ClinProTools software. Differences in serum peptides/proteins between patients with EGFR gene TKI-sensitive mutations and wild-type EGFR genes were detected in a training group of 100 patients; based on this analysis, a serum proteomic classification algorithm was developed to classify EGFR gene mutation status and tested in an independent validation group of 123 patients. The correlation between EGFR gene mutation status, as identified with the serum proteomic classifier and response to EGFR-TKIs was analyzed.

Results

Nine peptide/protein peaks were significantly different between NSCLC patients with EGFR gene TKI-sensitive mutations and wild-type EGFR genes in the training group. A genetic algorithm model consisting of five peptides/proteins (m/z 4092.4, 4585.05, 1365.1, 4643.49 and 4438.43) was developed from the training group to separate patients with EGFR gene TKI-sensitive mutations and wild-type EGFR genes. The classifier exhibited a sensitivity of 84.6% and a specificity of 77.5% in the validation group. In the 81 patients from the validation group treated with EGFR-TKIs, 28 (59.6%) of 47 patients whose matched samples were labeled as “mutant” by the classifier and 3 (8.8%) of 34 patients whose matched samples were labeled as “wild” achieved an objective response (p<0.0001). Patients whose matched samples were labeled as “mutant” by the classifier had a significantly longer progression-free survival (PFS) than patients whose matched samples were labeled as “wild” (p=0.001).

Conclusion

Peptides/proteins related to EGFR gene mutation status were found in the serum. Classification of EGFR gene mutation status using the serum proteomic classifier established in the present study in patients with stage IIIB or IV NSCLC is feasible and may predict tumor response to EGFR-TKIs.     

Network-Based Meta-Analyses of Associations of Multiple Gene Expression Profiles with Bone Mineral Density Variations in Women

Background

Existing microarray studies of bone mineral density (BMD) have been critical for understanding the pathophysiology of osteoporosis, and have identified a number of candidate genes. However, these studies were limited by their relatively small sample sizes and were usually analyzed individually. Here, we propose a novel network-based meta-analysis approach that combines data across six microarray studies to identify functional modules from human protein-protein interaction (PPI) data, and highlight several differentially expressed genes (DEGs) and a functional module that may play an important role in BMD regulation in women.

Methods

Expression profiling studies were identified by searching PubMed, Gene Expression Omnibus (GEO) and ArrayExpress. Two meta-analysis methods were applied across different gene expression profiling studies. The first, a nonparametric Fisher’s method, combined p-values from individual experiments to identify genes with large effect sizes. The second method combined effect sizes from individual datasets into a meta-effect size to gain a higher precision of effect size estimation across all datasets. Genes with Q test’s p-values < 0.05 or I² values > 50% were assessed by a random effects model and the remainder by a fixed effects model. Using Fisher’s combined p-values, functional modules were identified through an integrated analysis of microarray data in the context of large protein–protein interaction (PPI) networks. Two previously published meta-analysis studies of genome-wide association (GWA) datasets were used to determine whether these module genes were genetically associated with BMD. Pathway enrichment analysis was performed with a hypergeometric test.

Results

Six gene expression datasets were identified, which included a total of 249 (129 high BMD and 120 low BMD) female subjects. Using a network-based meta-analysis, a consensus module containing 58 genes (nodes) and 83 edges was detected. Pathway enrichment analysis of the 58 module genes revealed that these genes were enriched in several important KEGG pathways including Osteoclast differentiation, B cell receptor signaling pathway, MAPK signaling pathway, Chemokine signaling pathway and Insulin signaling pathway. The importance of module genes was replicated by demonstrating that most module genes were genetically associated with BMD in the GWAS data sets. Meta-analyses were performed at the individual gene level by combining p-values and effect sizes. Five candidate genes (ESR1, MAP3K3, PYGM, RAC1 and SYK) were identified based on gene expression meta-analysis, and their associations with BMD were also replicated by two BMD meta-analysis studies.

Conclusions

In summary, our network-based meta-analysis not only identified important differentially expressed genes but also discovered biologically meaningful functional modules for BMD determination. Our study may provide novel therapeutic targets for osteoporosis in women.     

Genome-Wide Association Study for Autism Spectrum Disorder in Taiwanese Han Population

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic components. Several recent genome-wide association (GWA) studies in Caucasian samples have reported a number of gene regions and loci correlated with the risk of ASD—albeit with very little consensus across studies.

Methods

A two-stage GWA study was employed to identify common genetic variants for ASD in the Taiwanese Han population. The discovery stage included 315 patients with ASD and 1,115 healthy controls, using the Affymetrix SNP array 6.0 platform for genotyping. Several gene regions were then selected for fine-mapping and top markers were examined in extended samples. Single marker, haplotype, gene-based, and pathway analyses were conducted for associations.

Results

Seven SNPs had p-values ranging from 3.4~9.9*10⁻⁶, but none reached the genome-wide significant level. Five of them were mapped to three known genes (OR2M4, STYK1, and MNT) with significant empirical gene-based p-values in OR2M4 (p = 3.4*10⁻⁵) and MNT (p = 0.0008). Results of the fine-mapping study showed single-marker associations in the GLIS1 (rs12082358 and rs12080993) and NAALADL2 (rs3914502 and rs2222447) genes, and gene-based associations for the OR2M3-OR2T5 (olfactory receptor genes, p = 0.02), and GLIPR1/KRR1 gene regions (p = 0.015). Pathway analyses revealed important pathways for ASD, such as olfactory and G protein–coupled receptors signaling pathways.

Conclusions

We reported Taiwanese Han specific susceptibility genes and variants for ASD. However, further replication in other Asian populations is warranted to validate our findings. Investigation in the biological functions of our reported genetic variants might also allow for better understanding on the underlying pathogenesis of autism.     

In-Silico Computing of the Most Deleterious nsSNPs in HBA1 Gene

Background

α-Thalassemia (α-thal) is a genetic disorder caused by the substitution of single amino acid or large deletions in the HBA1 and/or HBA2 genes.

Method

Using modern bioinformatics tools as a systematic in-silico approach to predict the deleterious SNPs in the HBA1 gene and its significant pathogenic impact on the functions and structure of HBA1 protein was predicted.

Results and Discussion

A total of 389 SNPs in HBA1 were retrieved from dbSNP database, which includes: 201 non-coding synonymous (nsSNPs), 43 human active SNPs, 16 intronic SNPs, 11 mRNA 3′ UTR SNPs, 9 coding synonymous SNPs, 9 5′ UTR SNPs and other types. Structural homology-based method (PolyPhen) and sequence homology-based tool (SIFT), SNPs&Go, PROVEAN and PANTHER revealed that 2.4% of the nsSNPs are pathogenic.

Conclusions

A total of 5 nsSNPs (G60V, K17M, K17T, L92F and W15R) were predicted to be responsible for the structural and functional modifications of HBA1 protein. It is evident from the deep comprehensive in-silico analysis that, two nsSNPs such as G60Vand W15R in HBA1 are highly deleterious. These “2 pathogenic nsSNPs” can be considered for wet-lab confirmatory analysis.     

5-HTTLPR Expression Outside the Skin: An Experimental Test of the Emotional Reactivity Hypothesis in Children

Background

There is increasing evidence that variation in the promoter region of the serotonin transporter gene SLC6A4 (i.e., the 5-HTTLPR polymorphism) moderates the impact of environmental stressors on child psychopathology. Emotional reactivity −the intensity of an individual’s response to other’s emotions− has been put forward as a possible mechanism underlying these gene-by-environment interactions (i.e., G×E). Compared to children homozygous for the L-allele (LL-genotypes), children carrying an S-allele (SS/SL-genotypes), specifically when they have been frequently exposed to negative emotions in the family environment, might be more emotionally reactive and therefore more susceptible to affective environmental stressors. However, the association between 5-HTTLPR and emotional reactivity in children has not yet been empirically tested. Therefore, the goal of this study was to test this association in a large-scale experiment.

Methods

Children (N = 521, 52.5% boys, Mage = 9.72 years) were genotyped and randomly assigned to happy, angry or neutral dynamic facial expressions and vocalizations. Motor and affective emotional reactivity were assessed through children’s self-reported negative and positive affect (n = 460) and facial electromyography activity (i.e., fEMG: the zygomaticus or “smile” muscle and the corrugator or “frown” muscle, n = 403). Parents reported on their negative and positive parenting behaviors.

Results

Children mimicked and experienced the emotion they were exposed to. However, neither motor reactivity nor affective reactivity to these emotions depended on children’s 5-HTTLPR genotype: SS/SL-genotypes did not manifest any stronger response to emotional stimuli than LL-genotypes. This finding remained the same when taking the broader family environment into account, controlling for kinship, age, gender and genetic ancestry, and when including a tri-allelic factor.

Conclusions

We found no evidence for an association between the 5-HTTLPR polymorphism and children’s emotional reactivity. This finding is important, in discounting one potential underlying endophenotype of G×E between the 5-HTTLPR and affective environmental stressors.     

A Common Variant Of Ubiquinol-Cytochrome c Reductase Complex Is Associated with DDH

Purpose

Genetic basis of Developmental dysplasia of the hip (DDH) remains largely unknown. To find new susceptibility genes for DDH, we carried out a genome-wide association study (GWAS) for DDH.

Methods

We enrolled 386 radiology confirmed DDH patients and 558 healthy controls (Set A) to conduct a genome-wide association study (GWAS). Quality-control was conducted at both the sample and single nucleotide polymorphism (SNP) levels. We then conducted a subsequent case-control study to replicate the association between a promising loci, rs6060373 in UQCC gene and DDH in an independent set of 755 cases and 944 controls (set B).

Results

In the DDH GWAS discovering stage, 51 SNPs showed significance of less than 10^-4, and another 577 SNPs showed significance of less than 10-3. In UQCC, all the 12 genotyped SNPs showed as promising risk loci. Genotyping of rs6060373 in set A showed the minor allele A as a promising risk allele (p = 4.82*10^-7). In set A, the odds ratio of allele A was 1.77. Genotyping of rs6060373 in Set B produced another significant result (p = 0.0338) with an odds ratio of 1.18 for risk allele A. Combining set A and set B, we identified a total p value of 3.63*10^-6 with the odds ratio of 1.35 (1.19–1.53) for allele A.

Conclusion

Our study demonstrates common variants of UQCC, specifically rs6060373, are associated with DDH in Han Chinese population.     

Association between Tooth Loss and Cognitive Function among 3063 Chinese Older Adults: A Community-Based Study

Background

Oral health has been found to be associated with cognitive function in basic research and epidemiology studies. Most of these studies had no comprehensive clinical diagnosis on cognitive function. This study firstly reported the association between tooth loss and cognitive function among Chinese older population.

Methods

The study included 3,063 community dwelling older adults aged 60 or above from the Shanghai Aging Study. Number of teeth missing was obtained from self-reporting questionnaire and confirmed by trained interviewers. Participants were diagnosed as “dementia”, “mild cognitive impairment (MCI)”, or “cognitive normal” by neurologists using DSM-IV and Petersen criteria. Multivariate logistic regression model was applied to examine the association between number of teeth missing and cognitive function.

Results

The study participants had an average of 10.2 teeth lost. Individuals with dementia lost 18.7 teeth on average, much higher than those with MCI (11.8) and cognitive normal (9.3) (p<0.001). After adjusted for sex, age, education year, living alone, body mass index, cigarette smoking, alcohol drinking, anxiety, depression, heart disease, hypertension, diabetes, and APOE-ε4, tooth loss of >16 were significantly associated with dementia with an OR of 1.56 (95%CI 1.12-2.18).

Conclusion

Having over 16 missing teeth was associated with severe cognitive impairment among Chinese older adults. Poor oral health might be considered as a related factor of neurodegenerative symptom among older Chinese population.     

More Realistic Face Model Surface Improves Relevance of Pediatric In-Vitro Aerosol Studies

Background

Various hard face models are commonly used to evaluate the efficiency of aerosol face masks. Softer more realistic “face” surface materials, like skin, deform upon mask application and should provide more relevant in-vitro tests. Studies that simultaneously take into consideration many of the factors characteristic of the in vivo face are lacking. These include airways, various application forces, comparison of various devices, comparison with a hard-surface model and use of a more representative model face based on large numbers of actual faces.

Aim

To compare mask to “face” seal and aerosol delivery of two pediatric masks using a soft vs. a hard, appropriately representative, pediatric face model under various applied forces.

Methods

Two identical face models and upper airways replicas were constructed, the only difference being the suppleness and compressibility of the surface layer of the “face.” Integrity of the seal and aerosol delivery of two different masks [AeroChamber (AC) and SootherMask (SM)] were compared using a breath simulator, filter collection and realistic applied forces.

Results

The soft “face” significantly increased the delivery efficiency and the sealing characteristics of both masks. Aerosol delivery with the soft “face” was significantly greater for the SM compared to the AC (p< 0.01). No statistically significant difference between the two masks was observed with the hard “face.”

Conclusions

The material and pliability of the model “face” surface has a significant influence on both the seal and delivery efficiency of face masks. This finding should be taken into account during in-vitro aerosol studies.     

Tumor Necrosis Factor (TNF) –308G>A,Nitric Oxide Synthase 3 (NOS3) +894G>T Polymorphisms and Migraine Risk: A Meta-Analysis

Background and Objective

Conflicting data have been reported on the association between tumor necrosis factor (TNF) –308G>A and nitric oxide synthase 3 (NOS3) +894G>T polymorphisms and migraine. We performed a meta-analysis of case-control studies to evaluate whether the TNF –308G>A and NOS3 +894G>T polymorphisms confer genetic susceptibility to migraine.

Method

We performed an updated meta-analysis for TNF –308G>A and a meta-analysis for NOS3 +894G>T based on studies published up to July 2014. We calculated study specific odds ratios (OR) and 95% confidence intervals (95% CI) assuming allele contrast, dominant model, recessive model, and co-dominant model as pooled effect estimates.

Results

Eleven studies in 6682 migraineurs and 22591 controls for TNF –308G>A and six studies in 1055 migraineurs and 877 controls for NOS3 +894G>T were included in the analysis. Neither indicated overall associations between gene polymorphisms and migraine risk. Subgroup analyses suggested that the “A” allele of the TNF –308G>A variant increases the risk of migraine among non-Caucasians (dominant model: pooled OR = 1.82; 95% CI 1.15 – 2.87). The risk of migraine with aura (MA) was increased among both Caucasians and non-Caucasians. Subgroup analyses suggested that the “T” allele of the NOS3 +894G>T variant increases the risk of migraine among non-Caucasians (co-dominant model: pooled OR = 2.10; 95% CI 1.14 – 3.88).

Conclusions

Our findings appear to support the hypothesis that the TNF –308G>A polymorphism may act as a genetic susceptibility factor for migraine among non-Caucasians and that the NOS3 +894G>T polymorphism may modulate the risk of migraine among non-Caucasians.     

Bacterial Factors Associated with Lethal Outcome of Enteropathogenic Escherichia coli Infection: Genomic Case-Control Studies

Background

Typical enteropathogenic Escherichia coli (tEPEC) strains were associated with mortality in the Global Enteric Multicenter Study (GEMS). Genetic differences in tEPEC strains could underlie some of the variability in clinical outcome.

Methods

We produced draft genome sequences of all available tEPEC strains from GEMS lethal infections (LIs) and of closely matched EPEC strains from GEMS subjects with non-lethal symptomatic infections (NSIs) and asymptomatic infections (AIs) to identify gene clusters (potential protein encoding sequences sharing ≥90% nucleotide sequence identity) associated with lethality.

Results

Among 14,412 gene clusters identified, the presence or absence of 392 was associated with clinical outcome. As expected, more gene clusters were associated with LI versus AI than LI versus NSI. The gene clusters more prevalent in strains from LI than those from NSI and AI included those encoding proteins involved in O-antigen biogenesis, while clusters encoding type 3 secretion effectors EspJ and OspB were among those more prevalent in strains from non-lethal infections. One gene cluster encoding a variant of an NleG ubiquitin ligase was associated with LI versus AI, while two other nleG clusters had the opposite association. Similar associations were found for two nleG gene clusters in an additional, larger sample of NSI and AI GEMS strains.

Conclusions

Particular genes are associated with lethal tEPEC infections. Further study of these factors holds potential to unravel the mechanisms underlying severe disease and to prevent adverse outcomes.     

Pathway Analysis Based on a Genome-Wide Association Study of Polycystic Ovary Syndrome

Background

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women of reproductive age, and it is affected by both environmental and genetic factors. Although the genetic component of PCOS is evident, studies aiming to identify susceptibility genes have shown controversial results. This study conducted a pathway-based analysis using a dataset obtained through a genome-wide association study (GWAS) to elucidate the biological pathways that contribute to PCOS susceptibility and the associated genes.

Methods

We used GWAS data on 636,797 autosomal single nucleotide polymorphisms (SNPs) from 1,221 individuals (432 PCOS patients and 789 controls) for analysis. A pathway analysis was conducted using meta-analysis gene-set enrichment of variant associations (MAGENTA). Top-ranking pathways or gene sets associated with PCOS were identified, and significant genes within the pathways were analyzed.

Results

The pathway analysis of the GWAS dataset identified significant pathways related to oocyte meiosis and the regulation of insulin secretion by acetylcholine and free fatty acids (all nominal gene-set enrichment analysis (GSEA) P-values < 0.05). In addition, INS, GNAQ, STXBP1, PLCB3, PLCB2, SMC3 and PLCZ1 were significant genes observed within the biological pathways (all gene P-values < 0.05).

Conclusions

By applying MAGENTA pathway analysis to PCOS GWAS data, we identified significant pathways and candidate genes involved in PCOS. Our findings may provide new leads for understanding the mechanisms underlying the development of PCOS.     

COL9A1 Gene Polymorphism Is Associated with Kashin-Beck Disease in a Northwest Chinese Han Population

Objective

We sought to determine whether genomic polymorphism in collagen IX genes (COL9A) was associated with Kashin-Beck disease (KBD).

Methods

Twenty seven single nucleotide polymorphisms (SNPs) in COL9AI, COL9A2 and COL9A3 were genotyped in 274 KBD cases and 248 healthy controls using the Sequenom MassARRAY system. Associations between the COL9A polymorphism and KBD risk were detected using an unconditional logistic regression model. Linkage disequilibrium (LD) and haplotypes analysis were performed with the Haploview software.

Results

After Bonferroni correction, the frequency distribution of genotypes in rs6910140 in COL9A1 was significantly different between the KBD and the control groups (X ² = 16.74, df = 2, P = 0.0002). Regression analysis showed that the allele “C” in SNP rs6910140 had a significant protective effect on KBD [odds ratio (OR) = 0.49, 95% confidence interval (CI) = 0.34–0.70, P = 0.0001]. The frequencies of alleles and genotypes in rs6910140 were significantly different among subjects of different KBD stages (allele: X ² = 7.82, df = 2, P = 0.02, genotype: X ² = 14.81, df = 4, P = 0.005). However, haplotype analysis did not detect any significant association between KBD and COL9A1, COL9A2 and COL9A3.

Conclusions

We observed a significant association between rs6910140 of COL9A1 and KBD, suggesting a role of COL9A1 in the development of KBD.     

“Attacks” or “Whistling”: Impact of Questionnaire Wording on Wheeze Prevalence Estimates

Background

Estimates of prevalence of wheeze depend on questionnaires. However, wording of questions may vary between studies. We investigated effects of alternative wording on estimates of prevalence and severity of wheeze, and associations with risk factors.

Methods

White and South Asian children from a population-based cohort (UK) were randomly assigned to two groups and followed up at one, four and six years (1998, 2001, 2003). Parents were asked either if their child ever had “attacks of wheeze” (attack group, N=535), or “wheezing or whistling in the chest” (whistling group, N=2859). All other study aspects were identical, including questions about other respiratory symptoms.

Results

Prevalence of wheeze ever was lower in the attack group than in the whistling group for all surveys (32 vs. 40% in white children aged one year, p<0.001). Prevalence of other respiratory symptoms did not differ between groups. Wheeze tended to be more severe in the attack group. The strength of association with risk factors was comparable in the two groups.

Conclusions

The wording of questions on wheeze can affect estimates of prevalence, but has less impact on measured associations with risk factors. Question wording is a potential source of between-study-heterogeneity in meta-analyses.     

An Integrated Approach to Uncover Driver Genes in Breast Cancer Methylation Genomes

Background

Cancer cells typically exhibit large-scale aberrant methylation of gene promoters. Some of the genes with promoter methylation alterations play “driver” roles in tumorigenesis, whereas others are only “passengers”.

Results

Based on the assumption that promoter methylation alteration of a driver gene may lead to expression alternation of a set of genes associated with cancer pathways, we developed a computational framework for integrating promoter methylation and gene expression data to identify driver methylation aberrations of cancer. Applying this approach to breast cancer data, we identified many novel cancer driver genes and found that some of the identified driver genes were subtype-specific for basal-like, luminal-A and HER2+ subtypes of breast cancer.

Conclusion

The proposed framework proved effective in identifying cancer driver genes from genome-wide gene methylation and expression data of cancer. These results may provide new molecular targets for potential targeted and selective epigenetic therapy.