Analysis of radiation-induced cell death in head and neck squamous cell carcinoma and rat liver maintained in microfluidic devices

Objective The aim of this study was to investigate how head and neck squamous cell carcinoma (HNSCC) tissue biopsies maintained in a pseudo in vivo environment within a bespoke microfluidic device respond to radiation treatment. Study Design Feasibility study. Setting Tertiary referral center. Subjects and Methods Thirty-five patients with HNSCC were recruited, and liver tissue from 5 Wistar rats was obtained. A microfluidic device was used to maintain the tissue biopsy samples in a viable state. Rat liver was used to optimize the methodology. HNSCC was obtained from patients with T1-T3 laryngeal or oropharyngeal SCC; N1-N2 metastatic cervical lymph nodes were also obtained. Irradiation consisted of single doses of between 2 Gy and 40 Gy and a fractionated course of 5×2 Gy. Cell death was assessed in the tissue effluent using the soluble markers lactate dehydrogenase (LDH) and cytochrome c and in the tissue by immunohistochemical detection of cleaved cytokeratin18 (M30 antibody). Results A significant surge in LDH release was demonstrated in the rat liver after a single dose of 20 Gy; in HNSCC, it was seen after 40 Gy compared with the control. There was no significant difference in cytochrome c release after 5 Gy or 10 Gy. M30 demonstrated a dose-dependent increase in apoptotic index for a given increase in single-dose radiotherapy. There was a significant increase in apoptotic index between 1×2 Gy and 5×2 Gy. Conclusion M30 is a superior method compared with soluble markers in detecting low-dose radiation-induced cell death. This microfluidic technique can be used to assess radiation-induced cell death in HNSCC and therefore has the potential to be used to predict radiation response

Genetic variation at CHRNA5-CHRNA3-CHRNB4 interacts with smoking status to influence body mass index

Cigarette smoking is associated with lower body mass index (BMI), and a commonly cited reason for unwillingness to quit smoking is a concern about weight gain. Common variation in the CHRNA5-CHRNA3-CHRNB4 gene region (chromosome 15q25) is robustly associated with smoking quantity in smokers, but its association with BMI is unknown. We hypothesized that genotype would accurately reflect smoking exposure and that, if smoking were causally related to weight, it would be associated with BMI in smokers, but not in never smokers

A study of association between common variation in the growth hormone-chorionic somatomammotropin hormone gene cluster and adult fasting insulin in a UK Caucasian population

BACKGROUND: Reduced growth during infancy is associated with adult insulin resistance. In a UK Caucasian cohort, the CSH1.01 microsatellite polymorphism in the growth hormone-chorionic somatomammotropin hormone gene cluster was recently associated with increases in adult fasting insulin of approximately 23 pmol/l for TT homozygote males compared to D1D1 or D2D2 homozygotes (P = 0.001 and 0.009; n = 206 and 92, respectively), but not for females. TT males additionally had a 547-g lower weight at 1 year (n = 270; P = 0.008) than D2D2 males. We sought to replicate these data in healthy UK Caucasian subjects. We genotyped 1396 subjects (fathers, mothers and children) from a consecutive birth study for the CSH1.01 marker and analysed genotypes for association with 1-year weight in boys and fasting insulin in fathers. RESULTS: We found no evidence for association of CSH1.01 genotype with adult male fasting insulin concentrations (TT/D1D1 P = 0.38; TT/D2D2 P = 0.18) or weight at 1 year in boys (TT/D1D1 P = 0.76; TT/D2D2 P = 0.85). For fasting insulin, our data can exclude the previously observed effect sizes as the 95 % confidence intervals for the differences observed in our study exclude increases in fasting insulin of 9.0 and 12.6 pmol/l for TT relative to D1D1 and D2D2 homozygotes, respectively. Whilst we have fewer data on boys' 1-year weight than the original study, our data can exclude a reduction in 1-year weight greater than 557 g for TT relative to D2D2 homozygotes. CONCLUSION: We have not found association of the CSH1.01 genotype with fasting insulin or weight at 1 year. We conclude that the original study is likely to have over-estimated the effect size for fasting insulin, or that the difference in results reflects the younger age of subjects in this study relative to those in the previous study

Weak or no association of TCF7L2 variants with Type 2 diabetes risk in an Arab population

<p>Abstract</p> <p>Background</p> <p>The rs7903146 and rs12255372 variants of <it>TCF7L2 </it>have been strongly associated with type 2 diabetes (T2D) risk in most populations studied to date. Meta-analysis of 27 different studies has resulted in a global OR of 1.46 [1.42–1.51] (rs7903146 variant). Thus far, despite a high incidence of T2D, the role of this variant in Arabs has not been established.</p> <p>Methods</p> <p>We performed a case-control association study using 522 Saudi T2D patients (WHO criteria), and 346 controls (age > 60; fasting plasma glucose < 7 mmol/L). Genotyping was performed by pyrosequencing. Statistical analyses were performed using SPSS version 13.0 for Windows (SPSS, Chicago, IL, USA).</p> <p>Results</p> <p>For rs7903146, the T allele frequency of the cases (0.415) was not different from that observed in the controls (0.405). The crude odds ratio (OR) was 1.04 with a 95% CI of 0.86–1.27 (P = 0.675). For rs12255372, the T allele frequency of the cases (0.368) was not different from that observed in the controls (0.355). Retrospective power calculations based upon an OR of 1.46 reported in a comprehensive meta-analysis of <it>TCF7L2 </it>risk, indicated this study was sufficiently powered (96.92%; α = 0.05) to detect an effect of similar magnitude to that reported for rs7903146.</p> <p>Conclusion</p> <p>Our study is consistent with weak or no association of T2D in Arabs with the two <it>TCF7L2 </it>variants, however it cannot rule out an effect of other SNPs in this gene. Future studies in this population are required to confirm our findings and may indicate the presence of yet to be defined genetic risk factors for T2D.</p

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Polymorphisms of the endothelial nitric oxide synthase (NOS3) gene in preeclampsia: a candidate-gene association study

<p>Abstract</p> <p>Background</p> <p>The endothelial nitric oxide synthase gene (<it>NOS3</it>) has been proposed as a candidate gene for preeclampsia. However, studies so far have produced conflicting results. This study examines the specific role of variants and haplotypes of the <it>NOS3 </it>gene in a population of Caucasian origin.</p> <p>Methods</p> <p>We examined the association of three common variants of the <it>NOS3 </it>gene (4b/a, T-786C and G894T) and their haplotypes in a case-control sample of 102 patients with preeclampsia and 176 women with a history of uncomplicated pregnancies. Genotyping for the <it>NOS3 </it>variants was performed and odds ratios and 95% confidence intervals were obtained to evaluate the association between <it>NOS3 </it>polymorphisms and preeclampsia.</p> <p>Results</p> <p>The single locus analysis for the three variants using various genetic models and a model-free approach revealed no significant association in relation to clinical status. The analysis of haplotypes also showed lack of significant association.</p> <p>Conclusions</p> <p>Given the limitations of the candidate-gene approach in investigating complex traits, the evidence of our study does not support the major contributory role of these common <it>NOS3 </it>variants in preeclampsia. Future larger studies may help in elucidating the genetics of preeclampsia further.</p

Reporting of Human Genome Epidemiology (HuGE) association studies: An empirical assessment

<p>Abstract</p> <p>Background</p> <p>Several thousand human genome epidemiology association studies are published every year investigating the relationship between common genetic variants and diverse phenotypes. Transparent reporting of study methods and results allows readers to better assess the validity of study findings. Here, we document reporting practices of human genome epidemiology studies.</p> <p>Methods</p> <p>Articles were randomly selected from a continuously updated database of human genome epidemiology association studies to be representative of genetic epidemiology literature. The main analysis evaluated 315 articles published in 2001–2003. For a comparative update, we evaluated 28 more recent articles published in 2006, focusing on issues that were poorly reported in 2001–2003.</p> <p>Results</p> <p>During both time periods, most studies comprised relatively small study populations and examined one or more genetic variants within a single gene. Articles were inconsistent in reporting the data needed to assess selection bias and the methods used to minimize misclassification (of the genotype, outcome, and environmental exposure) or to identify population stratification. Statistical power, the use of unrelated study participants, and the use of replicate samples were reported more often in articles published during 2006 when compared with the earlier sample.</p> <p>Conclusion</p> <p>We conclude that many items needed to assess error and bias in human genome epidemiology association studies are not consistently reported. Although some improvements were seen over time, reporting guidelines and online supplemental material may help enhance the transparency of this literature.</p

The Interplay of Variants Near LEKR and CCNL1 and Social Stress in Relation to Birth Size

Background We previously identified via a genome wide association study variants near LEKR and CCNL1 and in the ADCY5 genes lead to lower birthweight. Here, we study the impact of these variants and social stress during pregnancy, defined as social adversity and neighborhood disparity, on infant birth size. We aimed to determine whether the addition of genetic variance magnified the observed associations. Methodology/Principal Findings We analyzed data from the Northern Finland Birth Cohort 1986 (n = 5369). Social adversity was defined by young maternal age (<20 years), low maternal education (<11 years), and/or single marital status. Neighborhood social disparity was assessed by discrepancy between neighborhoods relative to personal socio-economic status. These variables are indicative of social and socioeconomic stress, but also of biological risk. The adjusted multiple regression analysis showed smaller birth size in both infants of mothers who experienced social adversity (birthweight by −40.4 g, 95%CI −61.4, −19.5; birth length −0.14 cm, 95%CI −0.23, −0.05; head circumference −0.09 cm 95%CI −0.15, −0.02) and neighborhood disparity (birthweight −28.8 g, 95%CI −47.7, −10.0; birth length −0.12 cm, 95%CI −0.20, −0.05). The birthweight-lowering risk allele (SNP rs900400 near LEKR and CCNL1) magnified this association in an additive manner. However, likely due to sample size restriction, this association was not significant for the SNP rs9883204 in ADCY5. Birth size difference due to social stress was greater in the presence of birthweight-lowering alleles. Conclusions/Significance Social adversity, neighborhood disparity, and genetic variants have independent associations with infant birth size in the mutually adjusted analyses. If the newborn carried a risk allele rs900400 near LEKR/CCNL1, the impact of stress on birth size was stronger. These observations give support to the hypothesis that individuals with genetic or other biological risk are more vulnerable to environmental influences. Our study indicates the need for further research to understand the mechanisms by which genes impact individual vulnerability to environmental insults

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.</p