Variants associated with susceptibility to pancreatic cancer and melanoma do not reciprocally affect risk

A rapid epistatic mixed-model association analysis by linear retransformations of genomic estimated values

Motivation

Epistasis provides a feasible way for probing potential genetic mechanism of complex traits. However, time-consuming computation challenges successful detection of interaction in practice, especially when linear mixed model (LMM) is used to control type I error in the presence of population structure and cryptic relatedness.

Results

A rapid epistatic mixed-model association analysis (REMMA) method was developed to overcome computational limitation. This method first estimates individuals' epistatic effects by an extended genomic best linear unbiased prediction (EG-BLUP) model with additive and epistatic kinship matrix, then pairwise interaction effects are obtained by linear retransformations of individuals' epistatic effects. Simulation studies showed that REMMA could control type I error and increase statistical power in detecting epistatic QTNs in comparison with existing LMM-based FaST-LMM. We applied REMMA to two real datasets, a mouse dataset and the Wellcome Trust Case Control Consortium (WTCCC) data. Application to the mouse data further confirmed the performance of REMMA in controlling type I error. For the WTCCC data, we found most epistatic QTNs for type 1 diabetes (T1D) located in a major histocompatibility complex (MHC) region, from which a large interacting network with 12 hub genes (interacting with ten or more genes) was established.

Availability and implementation

Our REMMA method can be freely accessed at https://github.com/chaoning/REMMA.

Contact

liujf@cau.edu.cn.

Supplementary information

Supplementary data are available at Bioinformatics online.

CYP Genetic Variants, CYP Metabolite Levels, and Symptomatic Carotid Stenosis in Ischemic Stroke Patients

AIM

To evaluate the relationship between CYP genetic polymorphisms and CYP metabolite levels with carotid artery stenosis in acute ischemic stroke (IS) patients.

METHODS

Eleven single nucleotide polymorphisms (SNPs) of seven CYP genes were genotyped in 136 IS patients with carotid stenosis and 158 patients without carotid stenosis. CYP plasma metabolite levels [20-hydroxyeicosatetraenoic acid (HETE), total epoxyeicosatrienoic acids (EETs), and dihydroxyeicosatrienoic acids (DiHETEs)] were assessed in a subsample of 90 patients with carotid stenosis and 96 patients without carotid stenosis. We evaluated the relationship between assessed variants and carotid stenosis risk, variants with CYP metabolite levels, and variants in mediating the differences of CYP metabolite levels between patients with carotid stenosis and those without. Additionally, gene-gene interactions were analyzed to assess the interactive role of the assessed variants in affecting CYP metabolite levels and risk of carotid stenosis.

RESULTS

The genotypes of rs17110453CC, rs751141GG, and rs9333025GG were significantly associated with carotid stenosis risk. Also these polymorphisms were associated with CYP plasma metabolite levels in patients with carotid stenosis. There was a significant gene-gene interaction between rs17110453 and rs9333025 in affecting the risk of carotid stenosis. Patients with rs17110453CC and rs9333025GG had a significantly higher risk of carotid stenosis than those with 17110453AA and rs9333025AA (OR=2.12, 95% CI: 1.13-7.26, P=0.013).

CONCLUSIONS

Specific CYP450 gene SNPs and their interactions are associated with CYP450 plasma metabolite levels, which may partially explain their associations with carotid stenosis. Further studies are needed to validate our findings.

Genetics and Genetic Testing in Pancreatic Cancer

Genetic testing of germline DNA is used in patients suspected of being at risk of pancreatic ductal adenocarcinoma (PDAC) to better define the individual's risk and to determine the mechanism of risk. A high genetic risk increases the pretest probability that a biomarker of early cancer is a true positive and warrants further investigation. The highest PDAC risk is generally associated with a hereditary predisposition. However, the majority of PDAC results from complex, progressive gene-environment interactions that currently fall outside the traditional risk models. Over many years, the combination of inflammation, exposure to DNA-damaging toxins, and failed DNA repair promote the accumulation of somatic mutations in pancreatic cells; PDAC risk is further increased by already present oncogenic germline mutations. Predictive models and new technologies are needed to classify patients into more accurate and mechanistic PDAC risk categories that can be linked to improved surveillance and preventative strategies.

Genetic Variants of PTPN2 Gene in Chinese Children with Type 1 Diabetes Mellitus

Background

Several studies have reported the association of PTPN2 gene with type 1 diabetes mellitus (T1DM) in many populations but not in the Chinese Han population. Therefore, the goal of our study was to replicate the reported association between 2 single-nucleotide polymorphisms (SNPs; rs478582 and rs2542151) in the PTPN2 gene and T1DM in Chinese Han children.

Material/Methods

This case-control study included 141 Chinese Han children with T1DM and 282 healthy controls. Genetic variants of rs478582 and rs2542151 in PTPN2 gene were performed by PCR amplification followed by restriction fragment length polymorphism method.

Results

No difference was observed in association of rs478582 in The PTPN2 gene and T1DM. The distribution of allele frequency of rs2542151 differed significantly between T1DM patients and healthy controls (OR, 0.6; 95%CI: 0.44 to 0.95; and P=0.024). Dominant model of rs254215 also was associated with T1DM (OR, 0.6; 95%CI: 0.40 to 0.96; and P=0.032). Younger age at onset in G carriers appeared to increase the risk for T1DM (P=0.030).

Conclusions

The findings suggested that rs2542151 SNP in The PTPN2 gene was associated with T1DM in Chinese Han children. Further studies with larger sample sizes involving gene-gene interactions are urgently needed.

Association of gastrointestinal gland cancer susceptibility loci with esophageal carcinoma among the Chinese Han population: a case-control study

Esophageal carcinoma (EC) is a common malignancy worldwide. Previous studies indicated that gastrointestinal gland cancer and EC share some susceptibility loci. Our aim was to identify new single nucleotide polymorphisms (SNPs) associated with EC by investigating whether known gastrointestinal cancers susceptibility loci are found in EC patients. A Chinese Han population case-control study was conducted to assess SNP associations with EC risk. Twenty-six SNPs were selected from gastrointestinal cancer susceptibility loci, and 360 EC patients and 310 controls were genotyped for these SNPs using Sequenom MassARRAY technology. The association of SNP frequencies with EC was analyzed by chi-square tests, and genetic model analysis. After Hardy-Weinberg equilibrium (HWE) p value screening, we excluded two SNPs. Based on chi-square tests, the minor alleles of rs13294589 (p = 0.046) and rs4924935 (p = 0.046) were correlated with reduced EC risk and rs4269383 (p = 0.010) and rs10953615 (p = 0.036) were correlated with increased EC risk. In the genetic model analyses, we found that the minor alleles "T" of rs401681, "A" of rs10088262, and "C" of rs4924935 may reduce the risk of EC. rs401681 has previously been reported to be associated with EC. To the best of our knowledge, we are the first to report an association of the other five SNPs with EC. Our findings provide evidence for the genetic variants associated with susceptibility to EC in the Chinese Han population, which might be used as potential molecular markers for detecting susceptibility to EC in Chinese Han people.

Pancreatic cancer-associated gene polymorphisms in a nation-wide cohort of p16-Leiden germline mutation carriers; a case-control study

Background

The p16-Leiden founder mutation in the CDKN2A gene is the most common cause of Familial Atypical Multiple Mole Melanoma (FAMMM) syndrome in the Netherlands. Individuals with this mutation are at increased risk for developing melanoma of the skin, as well as pancreatic cancer. However, there is a notable interfamilial variability in the occurrence of pancreatic cancer among p16-Leiden families. We aimed to test whether previously identified genetic risk factors for pancreatic cancer modify the risk for pancreatic cancer in p16-Leiden germline mutation carriers.

Methods

Seven pancreatic cancer-associated SNPs were selected from the literature and were genotyped in a cohort of 185 p16-Leiden germline mutation carriers from 88 families, including 50 cases (median age 55 years) with pancreatic cancer and 135 controls (median age 64 years) without pancreatic cancer. Allelic odds ratios per SNP were calculated.

Results

No significant association with pancreatic cancer was found for any of the seven SNPs.

Conclusions

Since genetic modifiers for developing melanoma have already been identified in CDKN2A mutation carriers, this study does not exclude that genetic modifiers do not play a role in the individual pancreatic cancer risk in this cohort of p16-Leiden germline mutation carriers. The search for these modifiers should therefore continue, because they can potentially facilitate more targeted pancreatic surveillance programs.

Saturated, Monounsaturated and Polyunsaturated Fatty Acids Intake and Risk of Pancreatic Cancer: Evidence from Observational Studies

Background

Although the relationship between dietary monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs), and saturated fatty acids (SFAs) intake and pancreatic cancer risk has been reported by several studies, the evidence is controversial. We firstly conducted this comprehensive meta-analysis to summarize the aforementioned evidence from observational studies.

Methods

The MEDLINE (PubMed), Embase, and ISI Web of Science databases were used to search for epidemiological studies of dietary SFA, MUFA, and PUFA and pancreatic cancer risk that were published until the end of June 2014. Random- or fixed-effects models were used to estimate the relative risks (RRs) and 95% confidence intervals (CIs). We also carried out subgroup, sensitivity, and publication bias analyses.

Results

We identified 13 case-control studies and 7 prospective studies which including 6270 pancreatic cancer cases in the meta-analysis of SFA, MUFA, and PUFA and risk of pancreatic cancer. The summary RR was 1.13 (95%CI = 0.94-1.35, I² = 70.7%) for SFA, 1.00 (95%CI = 0.87-1.14, I² = 43.4%) for MUFA, and 0.87 (95%CI = 0.75-1.00, I² = 55.3%) for PUFA for high versus low intake categories. We found no evidence of publication bias.

Conclusion

In summary, findings of this study supports an inverse association between diets high in PUFA and pancreatic cancer risk. Further large prospective studies are warranted to report the results stratified by the subtypes of MUFA and PUFA and adjust for other potential risk factors to eliminate residual confounding.

Mitochondrial DNA copy number in peripheral blood and melanoma risk

Mitochondrial DNA (mtDNA) copy number in peripheral blood has been suggested as risk modifier in various types of cancer. However, its influence on melanoma risk is unclear. We evaluated the association between mtDNA copy number in peripheral blood and melanoma risk in 500 melanoma cases and 500 healthy controls from an ongoing melanoma study. The mtDNA copy number was measured using real-time polymerase chain reaction. Overall, mean mtDNA copy number was significantly higher in cases than in controls (1.15 vs 0.99, P<0.001). Increased mtDNA copy number was associated with a 1.45-fold increased risk of melanoma (95% confidence interval: 1.12-1.97). Significant joint effects between mtDNA copy number and variables related to pigmentation and history of sunlight exposure were observed. This study supports an association between increased mtDNA copy number and melanoma risk that is independent on the known melanoma risk factors (pigmentation and history of sunlight exposure).

Pharmacologic Therapy of Diabetes and Overall Cancer Risk and Mortality: A Meta-Analysis of 265 Studies

Different anti-diabetic medications (ADMs) may modify cancer risk and mortality in patients with diabetes. We conducted a systematic review and meta-analysis to estimate the magnitude of association and quality of supporting evidence for each ADM. A total of 265 studies (44 cohort studies, 39 case-control studies, and 182 randomized controlled trials (RCT)) were identified, involving approximately 7.6 million and 137,540 patients with diabetes for observational studies and RCTs, respectively. The risk of bias overall was moderate. Meta-analysis demonstrated that the use of metformin or thiazolidinediones was associated with a lower risk of cancer incidence (RR = 0.86, 95% CI 0.83-0.90, I² = 88.61%; RR = 0.93, 95% CI 0.91-0.96, I² = 0.00% respectively). On the other hand, insulin, sulfonylureas and alpha glucosidase inhibitor use was associated with an increased risk of cancer incidence (RR = 1.21, 95% CI 1.08-1.36, I² = 96.31%; RR = 1.20, 95% CI 1.13-1.27, I² = 95.02%; RR = 1.10, 95% CI 1.05-1.15, I² = 0.00% respectively). Use of other types of ADMs was not significantly associated with cancer risk. This study indicates that some ADMs may modify the risk of cancer in individuals with diabetes. Knowledge of this risk may affect the choice of ADM in individuals concerned about cancer or at increased risk for cancer.

Zinc transporter genes and urological cancers: integrated analysis suggests a role for ZIP11 in bladder cancer

Although zinc transporters were shown to play roles in the development of prostate, bladder, and renal cancer, no study has evaluated the genetic variants in zinc transporter genes with risk of urological cancers. A candidate gene association study using genome-wide association study (GWAS) datasets was conducted for variants in 24 zinc transporter genes. Genotypes were analyzed using logistic regression models adjusted for covariates. The function of identified variants was assessed by using the Encyclopedia of DNA Elements (ENCODE). We further evaluated tumors for somatic change of the implicated gene(s) and the associations between identified variants and patient survival from data in The Cancer Genome Atlas (TCGA). A ZIP11 variant, rs8081059, was significantly associated with increased risk of renal cell carcinoma (odds ratios (OR) = 1.28, 95 % confidence intervals (CI) (1.13-1.45), p = 0.049). No zinc transporter variants were associated with prostate cancer risk. Four variants within ZIP11 were significantly associated with bladder cancer risk: rs11871756 (OR = 1.43, 95 % CI (1.24-1.63), p = 0.0002), rs11077654 (OR = 0.76, 95 % CI (0.68-0.85), p = 0.001), rs9913017 (OR = 0.76, 95 % CI (0.68-0.85), p = 0.002), and rs4969054 (OR = 0.78, 95 % CI (0.69-0.88), p = 0.02); the three protective variants were co-located and highly correlated. These variants were located within predicted transcribed or enhancer regions. Among the 253 bladder cancer patients in TCGA, two had tumors that contained deleterious missense mutations in ZIP11. Moreover, rs11077654 was significantly associated with survival of bladder cancer patients (p = 0.046). In conclusion, zinc transporter gene, ZIP11, may play an important role in bladder cancer. Further studies of the gene are warranted.

The imaging features of metanephric adenoma: a case report and review of literature

Metanephric adenoma (MA) is a rare epithelial tumor of the kidney with a characteristic histology. To date, the imaging features of the tumor have not been clearly described. Until now, MA was considered to be benign, but the majority of MA cases underwent nephrectomy. Here, we report a case of MA confirmed by surgical pathology, and we will analyze the ultrasound and computed tomography findings. The radiological features of MA are presented along with a brief review of the pertinent literature to deepen the understanding of MA’s imaging features.

Do variants associated with susceptibility to pancreatic cancer and type 2 diabetes reciprocally affect risk?

Objectives

Although type 2 diabetes mellitus is a known risk factor for pancreatic cancer, the existence of shared genetic susceptibility is largely unknown. We evaluated whether any reported genetic risk variants of either disease found by genome-wide association studies reciprocally confer susceptibility.

Methods

Data that were generated in previous genome-wide association studies (GENEVA Type 2 Diabetes; PanScan) were obtained through the National Institutes of Health database of Genotypes and Phenotypes (dbGaP). Using the PanScan datasets, we tested for association of 38 variants within 37 genomic regions known to be susceptibility factors for type 2 diabetes. We further examined whether type 2 diabetes variants predispose to pancreatic cancer risk stratified by diabetes status. Correspondingly, we examined the association of fourteen pancreatic cancer susceptibility variants within eight genomic regions in the GENEVA Type 2 Diabetes dataset.

Results

Four plausible associations of diabetes variants and pancreatic cancer risk were detected at a significance threshold of p = 0.05, and one pancreatic cancer susceptibility variant was associated with diabetes risk at threshold of p = 0.05, but none remained significant after correction for multiple comparisons.

Conclusion

Currently identified GWAS susceptibility variants are unlikely to explain the potential shared genetic etiology between Type 2 diabetes and pancreatic cancer.

Case-only exome sequencing and complex disease susceptibility gene discovery: study design considerations

Whole exome sequencing (WES) provides an unprecedented opportunity to identify the potential aetiological role of rare functional variants in human complex diseases. Large-scale collaborations have generated germline WES data on patients with a number of diseases, especially cancer, but less often on healthy controls under the same sequencing procedures. These data can be a valuable resource for identifying new disease susceptibility loci if study designs are appropriately applied. This review describes suggested strategies and technical considerations when focusing on case-only study designs that use WES data in complex disease scenarios. These include variant filtering based on frequency and functionality, gene prioritisation, interrogation of different data types and targeted sequencing validation. We propose that if case-only WES designs were applied in an appropriate manner, new susceptibility genes containing rare variants for human complex diseases can be detected.