Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases

Discovering the link between IL12RB1 gene polymorphisms and tuberculosis susceptibility: a comprehensive meta-analysis

Introduction

Numerous studies suggest that the risk of tuberculosis (TB) is linked to gene polymorphisms of the interleukin-12 receptor b subunit 1 (IL12RB1), but the association between IL12RB1 polymorphisms and TB susceptibility has not been thoroughly investigated.

Methods

A meta-analysis was conducted based on eight case-control studies with 10,112 individuals to further explore this topic. A systematic search of PubMed, Web of Science, Excerpt Medica Database, and Google Scholar up until April 6th, 2023 was performed. ORs and 95% CIs were pooled using the random-effect model. The epidemiological credibility of all significant associations was assessed using the Venice criteria and false-positive report probability (FPRP) analyses.

Results

The IL12RB1 rs11575934 and rs401502 showed solid evidence of no significant association with TB susceptibility. However, a weak association was observed between the IL12RB1 rs375947 biomarker and pulmonary tuberculosis (PTB) susceptibility (OR = 1.64, 95% CI: 1.22, 2.21).

Discussion

These findings should be confirmed through larger, better-designed studies to clarify the relationship between biomarkers in IL12RB1 gene and different types of TB susceptibility.

Colorectal Cancer Risk Prediction Using the rs4939827 Polymorphism of the SMAD7 Gene in the Romanian Population

Colorectal cancer (CRC) is globally recognized as a prevalent malignancy known for its significant mortality rate. Recent years have witnessed a rising incidence trend in colorectal cancer, emphasizing the necessity for early diagnosis. Our study focused on examining the impact of the SMAD7 gene variant rs4939827 on the risk of colorectal cancer occurrence. The composition of our study group included 340 individuals, comprising 170 CRC diagnosed patients and 170 healthy controls. We performed genotyping of all biological samples using the TaqMan assay on the ABI 7500 Real-Time PCR System (Applied Biosystems, Waltham, MA, USA). This investigation focused on the rs4939827 gene variant, assessing its association with CRC risk and clinicopathological characteristics. Genotyping results for the SMAD7 gene variant rs4939827 revealed a 42.6% prevalence of the C allele in CRC patients (p = 0.245) and a 22.8% prevalence of the T allele in control subjects (p = 0.109). This study concluded that there was an elevated risk of CRC in the dominant model for CC/CT+TT, with a p-value of 0.113 and an odds ratio (OR) of 2.781, within a 95% confidence interval (CI) of 0.998 to 3.456. The findings of our research indicate a correlation between variants of the SMAD7 gene and the likelihood of developing colorectal cancer in our study population. Consequently, these results could be instrumental in facilitating early diagnosis of colorectal cancer utilizing information on single-nucleotide polymorphism (SNP) and genetic susceptibility to the disease.

Epidemiological evidence for associations between variants in CHRNA genes and risk of lung cancer and chronic obstructive pulmonary disease

Background

Genetic studies have previously reported that single-nucleotide polymorphisms (SNPs) in CHRNA genes (such as CHRNA3, CHRNA4, CHRNA5, or CHRNA3-CHRNA5-CHRNB4 clusters) are linked to the risk of neoplastic and non-neoplastic diseases. However, these conclusions were controversial and no systematic research synopsis has been available. We aimed to synthesize current knowledge of variants in the CHRNA genes on the risk of diseases.

Methods

We systematically searched for publications using PubMed, Medline, and Web of Science on or before 25 August 2021. A total of 1,818 publications were identified, of which 29 were deemed eligible for inclusion that could be used to perform meta-analysis based on at least three data sources to assess whether the morbidity associated with neoplastic and non-neoplastic diseases can be attributed to SNPs in CHRNA genes. To further evaluate the authenticity of cumulative evidence proving significant associations, the present study covered the Venice criteria and false-positive report probability tests. Through the Encyclopedia of DNA Elements (ENCODE) project, we created functional annotations for strong associations.

Results

Meta-analyses were done for nine genetic variants with two diseases {chronic obstructive pulmonary disease (COPD) and lung cancer (LC)}that had at least three data sources. Interestingly, eight polymorphisms were significantly related to changes in the susceptibility COPD and LC (p < 0.05). Of these, strong evidence was assigned to six variants (28 significant associations): CHRNA3 rs1051730, CHRNA3 rs6495309, and CHRNA5 rs16969968 with COPD risk, and CHRNA3 rs1051730, CHRNA3 rs578776, CHRNA3 rs6495309, CHRNA3 rs938682, CHRNA5 rs16969968, and CHRNA5 rs588765 with LC risk; moderate evidence was assigned to five SNPs (12 total associations) with LC or COPD risk. Data from ENCODE and other public databases showed that SNPs with strong evidence may be located in presumptive functional regions.

Conclusions

Our study summarized comprehensive evidence showing that common mutations in CHRNA genes are strongly related to LC and COPD risk. The study also elucidated the vital function of CHRNA genes in genetic predispositions to human diseases.

Genetic architecture of tuberculosis susceptibility: A comprehensive research synopsis, meta-analyses, and epidemiological evidence

To date, many studies have been conducted to investigate associations between variants and tuberculosis risk; however, the results have been inconclusive. Here, we systematically provide a summary of the understanding of the genetic architecture of tuberculosis susceptibility. We searched PubMed, Embase and Web of Science to identify genetic association studies of tuberculosis published through October 31, 2021. We conducted meta-analyses for the genetic association with tuberculosis risk. We graded levels of cumulative epidemiological evidence of significant associations with risk of tuberculosis and false-positive report probability tests. We performed functional annotations for these variants using data from the Encyclopedia of DNA Elements (ENCODE) Project and other databases. We identified 703 eligible articles comprising 298,074 cases and 879,593 controls through screening a total of 24,398 citations. Meta-analyses were conducted for 614 genetic variants in 469 genes or loci. We found 39 variants that were nominally significantly associated with tuberculosis risk. Cumulative epidemiological evidence for a significant association was graded strong for 9 variants in or near 9 genes. Among them, 5 variants were associated with tuberculosis risk in at least three main ethnicity (African, Asian and White) which together explained approximately 9.59% of the familial relative risk of tuberculosis. Data from ENCODE and other databases suggested that 8 of these 9 genetic variants with strong evidence might fall within putative functional regions. Our study summarizes the current literature on the genetic architecture of tuberculosis susceptibility and provides useful data for designing future studies to investigate the genetic association with tuberculosis risk.

Polymorphisms in ERCC4 and ERCC5 and risk of cancers: Systematic research synopsis, meta-analysis, and epidemiological evidence

The variants of DNA repair genes have been widely reported to be associated with cancer risk in the past decades. As were two crucial members of nucleotide excision repair pathway, ERCC4 and ERCC5 polymorphisms are linked with susceptibility to multiple cancers, but the conclusions were controversial. In this updated meta-analysis concerned with ERCC4 and ERCC5 single-nucleotide polymorphisms (SNPs), 160 eligible publications were identified, and we exerted the meta-analysis of correlations between 24 variants and 19 types of cancer. Venice criteria and the false-positive report probability were used to evaluate a cumulative evidence of significant associations. We conducted functional annotations for those strong associations using data from the Encyclopedia of DNA Elements (ENCODE) Project. We obtained 11 polymorphisms significantly related to changed susceptibility to 11 cancers (p < 0.05). Strong evidence was assigned to four variant-related cancer risks in Asians (ERCC4 rs744154 with bladder cancer, ERCC5 rs2296147 with esophageal cancer, ERCC5 rs17655 with laryngeal cancer and uterine cancer, and ERCC5 rs751402 with gastric cancer), moderate to six SNPs with a risk of eight cancers, and weak to nine SNPs with nine cancers. Data from ENCODE and other public databases showed that the loci of these SNPs with strong evidence might fall in putative functional regions. In conclusion, this paper summarizes comprehensive evidence that common variants of ERCC4 and ERCC5 genes are strongly associated with the risk of bladder cancer, esophageal cancer, laryngeal cancer, uterine cancer, and gastric cancer and elucidates the crucial role of the DNA repair genes in the genetic predisposition to human cancers.

Epidemiological Evidence for Associations Between Genetic Variants and Osteosarcoma Susceptibility: A Meta-Analysis

Background

Previous studies have showed that single nucleotide polymorphisms (SNPs) might be implicated in the pathogenesis of osteosarcoma (OS). Numerous studies involving SNPs with OS risk have been reported; these results, however, remain controversial and no comprehensive research synopsis has been performed till now.

Objective

This study seeks to clarify the relationships between SNPs and OS risk using a comprehensive meta-analysis, and assess epidemiological evidence of significant associations.

Methods

The PubMed, Web of Science, and Medline were used to screen for articles that evaluated the association between SNP and OS susceptibility in humans before 24 December 2021. Furthermore, we used Venice Criteria and a false positive report probability (FPRP) test to assess the grades of epidemiological evidence for the statistical relationships.

Results

We extracted useful data based on 43 articles, including 10,255 cases and 13,733 controls. Our results presented that 25 SNPs in 17 genes were significantly associated with OS risk. Finally, we graded strong evidence for 17 SNPs in 14 genes with OS risk (APE1 rs1760944, BCAS1 rs3787547, CTLA4 rs231775, ERCC3 rs4150506, HOTAIR rs7958904, IL6 rs1800795, IL8 rs4073, MTAP rs7023329 and rs7027989, PRKCG rs454006, RECQL5 rs820196, TP53 rs1042522, VEGF rs3025039, rs699947 and rs2010963, VMP1 rs1295925, XRCC3 rs861539), moderate for 14 SNPs in 12 genes and weak for 14 SNPs in 11 genes.

Conclusion

In summary, this study offered a comprehensive meta-analysis between SNPs and OS susceptibility, then evaluated the credibility of statistical relationships, and provided useful information to identify the appropriate candidate SNPs and design future studies to evaluate SNP factors for OS risk.

Epidemiological evidence for associations between variants in microRNA and cancer risk

Numerous papers have reported variants in microRNAs associated with cancer risk; these results, however, are controversial. We seek to offer an updated, comprehensive synopsis of genetic associations between single nucleotide polymorphisms (SNPs) in microRNAs (miRNAs) and cancer risk. We did systematic a field synopsis and meta-analysis to investigate 29 SNPs in 24 miRNAs associated with risk of 18 different kinds of cancer based on data from 247 eligible articles. We graded levels of cumulative epidemiological evidence of significant association using Venice criteria and a false-positive report probability (FPRP) test. We constructed functional annotations for these variants using data from the Encyclopedia of DNA Elements Project. We used FPRP to find additional noteworthy associations between 278 SNPs in 117 miRNAs and risk of 26 cancers based on each SNP with one data source. 16 SNPs were statistically associated with risk of 17 cancers. We graded the cumulative epidemiological evidence as strong for statistical associations between 10 SNPs in eight miRNAs and risk of 11 cancers, moderate for nine SNPs with 12 cancers, and weak for 11 SNPs with 11 cancers. Bioinformatics analysis suggested that the SNPs with strong evidence might fall in putative functional regions. In addition, 38 significant associations were observed in 38 SNPs and risk of 13 cancers. This study offered the a comprehensive research on miRNA gene variants and cancer risk and provided referenced information for the genetic predisposition to cancer risk in future research.

Genetic Variants Associated with Thyroid Cancer Risk: Comprehensive Research Synopsis, Meta-Analysis, and Cumulative Epidemiological Evidence

Purpose

With the increasing incidence of thyroid cancer (TC), associations between genetic polymorphisms and TC risk have attracted a lot of attention. Considering that the results of associations of genetic variants with TC were usually inconsistent based on publications until now, we attempted to comprehensively evaluate the real evidence of associations between single nucleotide polymorphisms (SNPs) and TC risk.

Method

We performed meta-analyses on 36 SNPs in 23 genes associated with TC susceptibility based on the data from 99 articles and comprehensively valued the epidemiological evidence of significant associations through the Venice criteria and false-positive report probability (FPRP) test. OR and P value were also calculated for 19 SNPs in 13 genes based on the insufficient data from 22 articles.

Results

19 SNPs were found significantly associated with TC susceptibility. Of these, strong epidemiological evidence of associations was identified for the following seven SNPs: POU5F1B rs6983267, FOXE1 rs966423, TERT rs2736100, NKX2-1 rs944289, FOXE1 rs1867277, FOXE1 rs2439302, and RET rs1799939, in which moderate associations were found in four SNPs and weak associations were found in eight SNPs. In addition, probable significant associations with TC were found in nine SNPs.

Conclusion

Our study systematically evaluated associations between SNPs and TC risk and offered reference information for further understanding of polymorphisms and TC susceptibility.

Elucidation of the Genomic-Epigenomic Interaction Landscape of Aggressive Prostate Cancer

Background

Majority of prostate cancer (PCa) deaths are attributed to localized high-grade aggressive tumours which progress rapidly to metastatic disease. A critical unmet need in clinical management of PCa is discovery and characterization of the molecular drivers of aggressive tumours. The development and progression of aggressive PCa involve genetic and epigenetic alterations occurring in the germline, somatic (tumour), and epigenomes. To date, interactions between genes containing germline, somatic, and epigenetic mutations in aggressive PCa have not been characterized. The objective of this investigation was to elucidate the genomic-epigenomic interaction landscape in aggressive PCa to identify potential drivers aggressive PCa and the pathways they control. We hypothesized that aggressive PCa originates from a complex interplay between genomic (both germline and somatic mutations) and epigenomic alterations. We further hypothesized that these complex arrays of interacting genomic and epigenomic factors affect gene expression, molecular networks, and signaling pathways which in turn drive aggressive PCa.

Methods

We addressed these hypotheses by performing integrative data analysis combining information on germline mutations from genome-wide association studies with somatic and epigenetic mutations from The Cancer Genome Atlas using gene expression as the intermediate phenotype.

Results

The investigation revealed signatures of genes containing germline, somatic, and epigenetic mutations associated with aggressive PCa. Aberrant DNA methylation had effect on gene expression. In addition, the investigation revealed molecular networks and signalling pathways enriched for germline, somatic, and epigenetic mutations including the STAT3, PTEN, PCa, ATM, AR, and P53 signalling pathways implicated in aggressive PCa.

Conclusions

The study demonstrated that integrative analysis combining diverse omics data is a powerful approach for the discovery of potential clinically actionable biomarkers, therapeutic targets, and elucidation of oncogenic interactions between genomic and epigenomic alterations in aggressive PCa.

Non-genetic risk and protective factors and biomarkers for neurological disorders: a meta-umbrella systematic review of umbrella reviews

BACKGROUND

The etiologies of chronic neurological diseases, which heavily contribute to global disease burden, remain far from elucidated. Despite available umbrella reviews on single contributing factors or diseases, no study has systematically captured non-purely genetic risk and/or protective factors for chronic neurological diseases.

METHODS

We performed a systematic analysis of umbrella reviews (meta-umbrella) published until September 20th, 2018, using broad search terms in MEDLINE, SCOPUS, Web of Science, Cochrane Database of Systematic Reviews, Cumulative Index to Nursing and Allied Health Literature, ProQuest Dissertations & Theses, JBI Database of Systematic Reviews and Implementation Reports, DARE, and PROSPERO. The PRISMA guidelines were followed for this study. Reference lists of the identified umbrella reviews were also screened, and the methodological details were assessed using the AMSTAR tool. For each non-purely genetic factor association, random effects summary effect size, 95% confidence and prediction intervals, and significance and heterogeneity levels facilitated the assessment of the credibility of the epidemiological evidence identified.

RESULTS

We identified 2797 potentially relevant reviews, and 14 umbrella reviews (203 unique meta-analyses) were eligible. The median number of primary studies per meta-analysis was 7 (interquartile range (IQR) 7) and that of participants was 8873 (IQR 36,394). The search yielded 115 distinctly named non-genetic risk and protective factors with a significant association, with various strengths of evidence. Mediterranean diet was associated with lower risk of dementia, Alzheimer disease (AD), cognitive impairment, stroke, and neurodegenerative diseases in general. In Parkinson disease (PD) and AD/dementia, coffee consumption, and physical activity were protective factors. Low serum uric acid levels were associated with increased risk of PD. Smoking was associated with elevated risk of multiple sclerosis and dementia but lower risk of PD, while hypertension was associated with lower risk of PD but higher risk of dementia. Chronic occupational exposure to lead was associated with higher risk of amyotrophic lateral sclerosis. Late-life depression was associated with higher risk of AD and any form of dementia.

CONCLUSIONS

We identified several non-genetic risk and protective factors for various neurological diseases relevant to preventive clinical neurology, health policy, and lifestyle counseling. Our findings could offer new perspectives in secondary research (meta-research).

Systematic meta-analyses, field synopsis and global assessment of the evidence of genetic association studies in colorectal cancer

OBJECTIVE

To provide an understanding of the role of common genetic variations in colorectal cancer (CRC) risk, we report an updated field synopsis and comprehensive assessment of evidence to catalogue all genetic markers for CRC (CRCgene2).

DESIGN

We included 869 publications after parallel literature review and extracted data for 1063 polymorphisms in 303 different genes. Meta-analyses were performed for 308 single nucleotide polymorphisms (SNPs) in 158 different genes with at least three independent studies available for analysis. Scottish, Canadian and Spanish data from genome-wide association studies (GWASs) were incorporated for the meta-analyses of 132 SNPs. To assess and classify the credibility of the associations, we applied the Venice criteria and Bayesian False-Discovery Probability (BFDP). Genetic associations classified as 'positive' and 'less-credible positive' were further validated in three large GWAS consortia conducted in populations of European origin.

RESULTS

We initially identified 18 independent variants at 16 loci that were classified as 'positive' polymorphisms for their highly credible associations with CRC risk and 59 variants at 49 loci that were classified as 'less-credible positive' SNPs; 72.2% of the 'positive' SNPs were successfully replicated in three large GWASs and the ones that were not replicated were downgraded to 'less-credible' positive (reducing the 'positive' variants to 14 at 11 loci). For the remaining 231 variants, which were previously reported, our meta-analyses found no evidence to support their associations with CRC risk.

CONCLUSION

The CRCgene2 database provides an updated list of genetic variants related to CRC risk by using harmonised methods to assess their credibility.

Delineation of the Germline and Somatic Mutation Interaction Landscape in Triple-Negative and Non-Triple-Negative Breast Cancer

Background

Breast cancer development and progression involve both germline and somatic mutations. High-throughput genotyping and next-generation sequencing technologies have enabled discovery of genetic risk variants and acquired somatic mutations driving the disease. However, the possible oncogenic interactions between germline genetic risk variants and somatic mutations in triple-negative breast cancer (TNBC) and non-triple-negative breast cancer (non-TNBC) have not been characterized. Here, we delineated the possible oncogenic interactions between genes containing germline and somatic mutations in TNBC and non-TNBC and investigated whether there are differences in gene expression and mutation burden between the two types of breast cancer.

Methods

We addressed this problem by integrating germline mutation information from genome-wide association studies with somatic mutation information from next-generation sequencing using gene expression data as the intermediated phenotype. We performed network and pathway analyses to discover molecular networks and signalling pathways enriched for germline and somatic mutations.

Results

The investigation revealed signatures of differentially expressed and differentially somatic mutated genes between TNBC and non-TNBC. Network and pathway analyses revealed functionally related genes interacting in gene regulatory networks and multiple signalling pathways enriched for germline and somatic mutations for each type of breast cancer. Among the signalling pathways discovered included the DNA repair and Androgen and ATM signalling pathways for TNBC and the DNA damage response, molecular mechanisms of cancer, and ATM and GP6 signalling pathways for non-TNBC.

Conclusions

The results show that integrative genomics is a powerful approach for delineating oncogenic interactions between genes containing germline and genes containing somatic mutations in TNBC and non-TNBC and establishes putative functional bridges between genetic and somatic alterations and the pathways they control in the two types of breast cancer.

A Systematic Analysis of Interactions between Environmental Risk Factors and Genetic Variation in Susceptibility to Colorectal Cancer

BACKGROUND

The underlying etiology of colorectal cancer includes both genetic variation and environmental exposures. The main aim of this study was to search for interaction effects between well-established environmental risk factors and published common genetic variants exerting main effects on colorectal cancer risk.

METHODS

We used a two-phase approach: (i) discovery phase (2,652 incident colorectal cancer cases and 10,608 controls from UK Biobank) and (ii) validation phase (1,656 cases and 2,497 controls from the Study of Colorectal Cancer in Scotland). Interactions with nominal P < 0.05 in phase I were taken forward for validation in phase II. Furthermore, we constructed a weighted genetic risk score (GRS) of colorectal cancer risk for each individual and studied interactions between the GRS and the environmental risk factors.

RESULTS

Seventy of the 1,500 tested interactions were nominally significant in phase I. After testing these 70 interactions in phase II, an interaction between rs11903757 (2q32.3) and body mass index (BMI) was nominally significant (P = 0.02) with the same direction of effect. The rs11903757*BMI interaction was also significant (ratio of ORs = 1.26; 95% confidence interval, 1.10-1.44; P interaction = 6.03 × 10-4; P heterogeneity = 0.63) in a meta-analysis combining results from both phases. No interactions were significant in phase II after accounting for multiple testing. No interactions involving the GRS were found with statistical significance.

CONCLUSIONS

Limited evidence of gene-environment interactions in colorectal cancer risk was observed. There are potential modifications of the rs11903757 effect by BMI on colorectal cancer risk.

IMPACT

Our findings might contribute to identifying subpopulations with different susceptibility to the effect of BMI on colorectal cancer risk.

Genetic variants in migraine: a field synopsis and systematic re-analysis of meta-analyses

Objective

Numerous genetic variants from meta-analyses of observational studies and GWAS were reported to be associated with migraine susceptibility. However, due to the random errors in meta-analyses, the noteworthiness of the results showing statistically significant remains doubtful. Thus, we performed this field synopsis and re-analysis study to evaluate the noteworthiness using a Bayesian approach in hope of finding true associations.

Methods

Relevant meta-analyses from observational studies and GWAS examining correlation between all genetic variants and migraine risk were included in our study by a PubMed search. Identification of noteworthy associations were analyzed by false-positive rate probability (FPRP) and Bayesian false discovery probability (BFDP). Using noteworthy variants, GO enrichment analysis were conducted through DAVID online tool. Then, the PPI network and hub genes were performed using STRING database and CytoHubba software.

Results

As for 8 significant genetic variants from observational studies, none of which showed noteworthy at prior probability of 0.001. Out of 47 significant genetic variants in GWAS, 36 were noteworthy at prior probability of 0.000001 via FPRP or BFDP. We further found the pathways “positive regulation of cytosolic calcium ion concentration” and “inositol phosphate-mediated signaling” and hub genes including MEF2D, TSPAN2, PHACTR1, TRPM8 and PRDM16 related to migraine susceptibility.

Conclusion

Herein, we have identified several noteworthy variants for migraine susceptibility in this field synopsis. We hope these data would help identify novel genetic biomarkers and potential therapeutic target for migraine.

Cumulative Evidence for Associations between Genetic Variants and Risk of Esophageal Cancer

BACKGROUND

A large number of studies have been conducted to investigate associations between genetic variants and esophageal cancer risk in the past several decades. However, findings from these studies have been generally inconsistent. We aimed to provide a summary of the current understanding of the genetic architecture of esophageal cancer susceptibility.

METHODS

We performed a comprehensive field synopsis and meta-analysis to evaluate associations between 95 variants in 70 genes or loci and esophageal cancer risk using data from 304 eligible publications, including 104,904 cases and 159,797 controls, through screening a total of 21,328 citations. We graded levels of cumulative epidemiologic evidence of a significant association with esophageal cancer using the Venice criteria and false-positive report probability tests. We constructed functional annotations for these variants using data from the Encyclopedia of DNA Elements Project and other databases.

RESULTS

Thirty variants were nominally significantly associated with esophageal cancer risk. Cumulative epidemiologic evidence of a significant association with overall esophageal cancer, esophageal squamous cell carcinoma, or esophageal adenocarcinoma was strong for 13 variants in or near 13 genes (ADH1B, BARX1, CDKN1A, CHEK2, CLPTM1L, CRTC1, CYP1A1, EGF, LTA, MIR34BC, PLCE1, PTEN, and PTGS2). Bioinformatics analysis suggested that these variants and others correlated with them might fall in putative functional regions.

CONCLUSIONS

Our study summarizes the current literature on the genetic architecture of esophageal cancer susceptibility and identifies several potential polymorphisms that could be involved in esophageal cancer susceptibility.

IMPACT

These findings provide direction for future studies to identify new genetic factors for esophageal cancer.

Epidemiological evidence for associations between variants in microRNA or biosynthesis genes and lung cancer risk

In the past decade, the studies involving single nucleotide polymorphisms (SNPs) in microRNAs (miRNAs) with lung cancer (LC) risk have been performed, however, these results are inconsistent, and a systematic research synopsis has not been performed yet. Therefore, we attempted to perform comprehensive meta‐analyses to assess the relationships between SNPs in miRNAs or biosynthesis genes and LC risk and further evaluate the epidemiological credibility of these significant associations. We used PubMed, Medline, and Web of Science to search for relevant articles published before 30 May 2019 that assessed relationships between SNPs in miRNAs or biosynthesis genes and LC risk. The cumulative epidemiological evidence of statistical relationships was further assessed combining Venice Criteria and a false‐positive report probability test. Based on 20 publications with 15 969 cases and 17 174 controls, we found that six variants in miRNAs or biosynthesis genes that proved significant associations with LC risk, whereas five proved no association. Subgroup analyses by ethnicity and genetic models were performed, suggesting that four associations were rated as demonstrating strong evidence of relationship with LC risk, including miRNA‐146a rs2910164 in all populations under dominant model and in Asians under dominant and recessive models, and AGO1 rs595961 in Asians under allelic model. Three associations were graded as moderate, and seven associations were rated as weak. This study presents the relationships between SNPs in miRNAs or biosynthesis genes and LC risk, subsequently demonstrates the credibility of these significant associations, and highlights the role in the pathogenesis of LC.

Mapping the Germline and Somatic Mutation Interaction Landscape in Indolent and Aggressive Prostate Cancers

BACKGROUND

A majority of prostate cancers (PCas) are indolent and cause no harm even without treatment. However, a significant proportion of patients with PCa have aggressive tumors that progress rapidly to metastatic disease and are often lethal. PCa develops through somatic mutagenesis, but emerging evidence suggests that germline genetic variation can markedly contribute to tumorigenesis. However, the causal association between genetic susceptibility and tumorigenesis has not been well characterized. The objective of this study was to map the germline and somatic mutation interaction landscape in indolent and aggressive tumors and to discover signatures of mutated genes associated with each type and distinguishing the two types of PCa.

MATERIALS AND METHODS

We integrated germline mutation information from genome-wide association studies (GWAS) with somatic mutation information from The Cancer Genome Atlas (TCGA) using gene expression data from TCGA on indolent and aggressive PCas as the intermediate phenotypes. Germline and somatic mutated genes associated with each type of PCa were functionally characterized using network and pathway analysis.

RESULTS

We discovered gene signatures containing germline and somatic mutations associated with each type and distinguishing the two types of PCa. We discovered multiple gene regulatory networks and signaling pathways enriched with germline and somatic mutations including axon guidance, RAR, WINT, MSP-RON, STAT3, PI3K, TR/RxR, and molecular mechanisms of cancer, NF-kB, prostate cancer, GP6, androgen, and VEGF signaling pathways for indolent PCa and MSP-RON, axon guidance, RAR, adipogenesis, and molecular mechanisms of cancer and NF-kB signaling pathways for aggressive PCa.

CONCLUSION

The investigation revealed germline and somatic mutated genes associated with indolent and aggressive PCas and distinguishing the two types of PCa. The study revealed multiple gene regulatory networks and signaling pathways dysregulated by germline and somatic alterations. Integrative analysis combining germline and somatic mutations is a powerful approach to mapping germline and somatic mutation interaction landscape.

Variants in the PSCA gene associated with risk of cancer and nonneoplastic diseases: systematic research synopsis, meta-analysis and epidemiological evidence

Variants in the prostate stem cell antigen (PSCA) gene have been linked with risk of multiple cancers and other diseases. But results have been inconclusive and no systematic research synopsis has been available. We did a comprehensive meta-analysis to investigate associations between variants in this gene and risk of nine cancers and four nonneoplastic diseases based on data from 55 publications including 81 961 cases and 442 932 controls. We graded levels of cumulative epidemiological evidence of a significant association using the Venice criteria and false-positive report probability tests. We performed functional annotation for these variants using data from the Encyclopedia of DNA Elements Project and other public databases. We found that six variants were nominally significantly associated with an increased or reduced risk of three cancers and three nonneoplastic diseases (P < 0.05). Cumulative evidence of an association was graded as strong for rs2294008 [odds ratio (OR) = 1.32, P = 5.1 × 10-33], rs2976392 (OR = 1.29, P = 1.8 × 10-8), rs9297976 (OR = 0.75, P = 1.4 × 10-7), rs2976391 (OR = 1.38, P = 6.1 × 10-5) and rs138377917 (OR = 0.53, P = 0.008) with gastric cancer, rs2294008 with bladder cancer (OR = 1.15, P = 8.0 × 10-19), gastritis (OR = 1.35, P = 1.2 × 10-5), duodenal ulcer (OR = 0.68, P = 2.4 × 10-57) and gastric ulcer (OR = 0.88, P = 1.7 × 10-7). Data from the Encyclopedia of DNA Elements Project and other databases showed that these variants and other variants correlated with them might fall in putative functional regions. In conclusion, this study provides summary evidence that variants in the PSCA gene are associated with risk of gastric and bladder cancer, gastritis, as well as duodenal and gastric ulcer and highlights the significant role of this gene in the pathogenesis of these diseases.

Gene-environment interactions and colorectal cancer risk: An umbrella review of systematic reviews and meta-analyses of observational studies

The cause of colorectal cancer (CRC) is multifactorial, involving both genetic variants and environmental risk factors. We systematically searched the MEDLINE, EMBASE, China National Knowledge Infrastructure (CNKI) and Wanfang databases from inception to December 2016, to identify systematic reviews and meta-analyses of observational studies that investigated gene-environment (G×E) interactions in CRC risk. Then, we critically evaluated the cumulative evidence for the G×E interactions using an extension of the Human Genome Epidemiology Network's Venice criteria. Overall, 15 articles reporting systematic reviews of observational studies on 89 G×E interactions, 20 articles reporting meta-analyses of candidate gene- or single-nucleotide polymorphism-based studies on 521 G×E interactions, and 8 articles reporting 33 genome-wide G×E interaction analyses were identified. On the basis of prior and observed scores, only the interaction between rs6983267 (8q24) and aspirin use was found to have a moderate overall credibility score as well as main genetic and environmental effects. Though 5 other interactions were also found to have moderate evidence, these interaction effects were tenuous due to the lack of main genetic effects and/or environmental effects. We did not find highly convincing evidence for any interactions, but several associations were found to have moderate strength of evidence. Our conclusions are based on application of the Venice criteria which were designed to provide a conservative assessment of G×E interactions and thus do not include an evaluation of biological plausibility of an observed joint effect.

Deconvolution of the Genomic and Epigenomic Interaction Landscape of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer. Emerging evidenced suggests that both genetics and epigenetic factors play a role in the pathogenesis of TNBC. However, oncogenic interactions and cooperation between genomic and epigenomic variation have not been characterized. The objective of this study was to deconvolute the genomic and epigenomic interaction landscape in TNBC using an integrative genomics approach, which integrates information on germline, somatic, epigenomic and gene expression variation. We hypothesized that TNBC originates from a complex interplay between genomic (both germline and somatic variation) and epigenomic variation. We further hypothesized that these complex arrays of interacting genomic and epigenomic factors affect entire molecular networks and signaling pathways which, in turn, drive TNBC. We addressed these hypotheses using germline variation from genome-wide association studies and somatic, epigenomic and gene expression variation from The Cancer Genome Atlas (TCGA). The investigation revealed signatures of functionally related genes containing germline, somatic and epigenetic variations. DNA methylation had an effect on gene expression. Network and pathway analysis revealed molecule networks and signaling pathways enriched for germline, somatic and epigenomic variation, among them: Role of BRCA1 in DNA Damage Response, Hereditary Breast Cancer Signaling, Molecular Mechanisms of Cancer, Estrogen-Dependent Breast Cancer, p53, MYC Mediated Apoptosis, and PTEN Signaling pathways. The investigation revealed that integrative genomics is a powerful approach for deconvoluting the genomic-epigenomic interaction landscape in TNBC. Further studies are needed to understand the biological mechanisms underlying oncogenic interactions between genomic and epigenomic factors in TNBC.

MTNR1B genetic polymorphisms as risk factors for gestational diabetes mellitus: a case-control study in a single tertiary care center

BACKGROUND

Gestational diabetes mellitus (GDM) is a metabolic disease in pregnancy that causes carbohydrate intolerance and hyper-glycemia. Genome-wide association studies and meta-analyses have found that the single nucleotide polymorphisms (SNPs) rs1387153 and rs10830963 of the melatonin receptor 1B ( MTNR1B) gene are associated with GDM. No studies on the MTNR1B gene effect on GDM have been performed in Saudis, other Arabs, or other Middle Eastern populations.

OBJECTIVES

Investigate the association of genotype or allele frequencies of the two SNPs with GDM and with clinical parameters related to GDM.

DESIGN

Case-control study.

SETTINGS

Tertiary care center, Riyadh.

PATIENTS AND METHODS

We recruited 400 pregnant Saudi women ages 18-45 years (200 were diagnosed with GDM, and 200 were healthy controls). Biochemical assays were performed, and rs1387153 and rs10830963 polymorphisms were analyzed by polymerase chain reaction-restriction fragment length polymorphism analysis and real-time polymerase chain reaction with TaqMan genotyping.

MAIN OUTCOME MEASURES

The association of MTNR1B gene (rs1387153 and rs10830963 polymorphisms) with GDM and with biochemical parameters related to GDM.

SAMPLE SIZE

200 GDM cases and 200 non-GDM controls.

RESULTS

Differences in allele frequencies for GDM vs non-GMD were statistically significant or nearly significant for both SNPs after adjustment for age and body mass index. In a logistic regression analysis, genotype TT was positively associated with post-prandial blood glucose (P=.018), but other associations were not statistically significant.

CONCLUSION

The odds ratios for the associations between the rs1387153 and rs10830963 SNPs and GDM exceeded 1.5-fold, which is higher than typically reported for diseases with complex genetic background. These effect sizes for GDM suggest pregnancy-specific factors related to the MTNR1B risk genotypes.

LIMITATIONS

Only two SNPs were studied.

CONFLICT OF INTEREST

None.

Integrating Germline and Somatic Mutation Information for the Discovery of Biomarkers in Triple-Negative Breast Cancer

Recent advances in high-throughput genotyping and the recent surge of next generation sequencing of the cancer genomes have enabled discovery of germline mutations associated with an increased risk of developing breast cancer and acquired somatic mutations driving the disease. Emerging evidence indicates that germline mutations may interact with somatic mutations to drive carcinogenesis. However, the possible oncogenic interactions and cooperation between germline and somatic alterations in triple-negative breast cancer (TNBC) have not been characterized. The objective of this study was to investigate the possible oncogenic interactions and cooperation between genes containing germline and somatic mutations in TNBC. Our working hypothesis was that genes containing germline mutations associated with an increased risk developing breast cancer also harbor somatic mutations acquired during tumorigenesis, and that these genes are functionally related. We further hypothesized that TNBC originates from a complex interplay among and between genes containing germline and somatic mutations, and that these complex array of interacting genetic factors affect entire molecular networks and biological pathways which in turn drive the disease. We tested this hypothesis by integrating germline mutation information from genome-wide association studies (GWAS) with somatic mutation information on TNBC from The Cancer Genome Atlas (TCGA) using gene expression data from 110 patients with TNBC and 113 controls. We discovered a signature of 237 functionally related genes containing both germline and somatic mutations. We discovered molecular networks and biological pathways enriched for germline and somatic mutations. The top pathways included the hereditary breast cancer and role of BRCA1 in DNA damage response signaling pathways. In conclusion, this is the first large-scale and comprehensive analysis delineating possible oncogenic interactions and cooperation among and between genes containing germline and somatic mutations in TNBC. Genetic and somatic mutations, along with the genes discovered in this study, will require experimental functional validation in different ethnic populations. Functionally validated genetic and somatic variants will have important implications for the development of novel precision prevention strategies and discovery of prognostic markers in TNBC.

Interactions between Germline and Somatic Mutated Genes in Aggressive Prostate Cancer

Prostate cancer (PCa) is the most common diagnosed malignancy and the second leading cause of cancer-related deaths among men in the USA. Advances in high-throughput genotyping and next generation sequencing technologies have enabled discovery of germline genetic susceptibility variants and somatic mutations acquired during tumor formation. Emerging evidence indicates that germline variations may interact with somatic events in carcinogenesis. However, the possible oncogenic interactions and cooperation between germline and somatic variation and their role in aggressive PCa remain largely unexplored. Here we investigated the possible oncogenic interactions and cooperation between genes containing germline variation from genome-wide association studies (GWAS) and genes containing somatic mutations from tumor genomes of 305 men with aggressive tumors and 52 control samples from The Cancer Genome Atlas (TCGA). Network and pathway analysis were performed to identify molecular networks and biological pathways enriched for germline and somatic mutations. The analysis revealed 90 functionally related genes containing both germline and somatic mutations. Transcriptome analysis revealed a 61-gene signature containing both germline and somatic mutations. Network analysis revealed molecular networks of functionally related genes and biological pathways including P53, STAT3, NKX3-1, KLK3, and Androgen receptor signaling pathways enriched for germline and somatic mutations. The results show that integrative analysis is a powerful approach to uncovering the possible oncogenic interactions and cooperation between germline and somatic mutations and understanding the broader biological context in which they operate in aggressive PCa.

Integrating germline and somatic variation information using genomic data for the discovery of biomarkers in prostate cancer

BACKGROUND

Prostate cancer (PCa) is the most common diagnosed malignancy and the second leading cause of cancer-related deaths among men in the United States. High-throughput genotyping has enabled discovery of germline genetic susceptibility variants (herein referred to as germline mutations) associated with an increased risk of developing PCa. However, germline mutation information has not been leveraged and integrated with information on acquired somatic mutations to link genetic susceptibility to tumorigenesis. The objective of this exploratory study was to address this knowledge gap.

METHODS

Germline mutations and associated gene information were derived from genome-wide association studies (GWAS) reports. Somatic mutation and gene expression data were derived from 495 tumors and 52 normal control samples obtained from The Cancer Genome Atlas (TCGA). We integrated germline and somatic mutation information using gene expression data. We performed enrichment analysis to discover molecular networks and biological pathways enriched for germline and somatic mutations.

RESULTS

We discovered a signature of 124 genes containing both germline and somatic mutations. Enrichment analysis revealed molecular networks and biological pathways enriched for germline and somatic mutations, including, the PDGF, P53, MYC, IGF-1, PTEN and Androgen receptor signaling pathways.

CONCLUSION

Integrative genomic analysis links genetic susceptibility to tumorigenesis in PCa and establishes putative functional bridges between the germline and somatic variation, and the biological pathways they control.

An Integrative Genomics Approach for Associating Genetic Susceptibility with the Tumor Immune Microenvironment in Triple Negative Breast Cancer

Background

Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer. It is a heterogeneous disease with poor prognosis. Contributing to the worse prognosis in TNBC is the higher rates of relapse and rapid progression to metastatic disease which is often lethal. With the exception of cytotoxic chemotherapy, there is currently no effective targeted therapies. Immunotherapy such as vaccines offer new opportunities for treatment of TNBC. But realizing the potential of immunotherapy and vaccination may require understanding the association between the tumor immune microenvironment and genetic susceptibility to TNBC. The objective of this exploratory study was to investigate the potential association between genetic susceptibility and tumor immune microenvironment in TNBC.

Methods

We integrated information on genetic variants and genes associated with an increased risk of developing breast cancer with gene expression data from the Caucasian women diagnosed with the basal-like immune activated (N=54) and basal-like immune suppressed (N=60) subtypes of TNBC to discover and characterize immune modulated gene signatures, molecular networks and biological pathways enriched for genetic susceptibility variants.

Results

The investigation revealed immune modulated gene signatures, molecular networks and biological pathways enriched for genetic susceptibility variants. The discovered pathways included the role of BRCA1 in DNA damage response, hereditary breast cancer, aryl hydrocarbon receptor and molecular mechanisms of cancer signaling pathways.

Conclusion

The investigation suggests the link between genetic susceptibility and the tumor immune microenvironment in TNBC and establishes putative functional bridges between genetic predisposition and immune modulated pathways.

Cumulative evidence for association between genetic polymorphisms and esophageal cancer susceptibility: A review with evidence from meta-analysis and genome-wide association studies

An increasing number of publications had reported the association between single‐nucleotide polymorphisms (SNPs) and esophageal cancer (EC) risk in the past decades. Results from these publications were controversial. We used PubMed, Medline, and Web of Science to identify meta‐analysis articles published before 30 July 2018, that summarize a comprehensive investigation for cumulative evidence of genetic polymorphisms of EC and its subtype risk. Two methods, Venice criteria and false‐positive report probability (FPRP) tests, were used to assess cumulative evidence of significant associations. At last, 107 meta‐analyses were considered to be in conformity with the inclusion criteria, yielding 51 variants associated with EC or esophageal squamous cell carcinoma (ESCC). Thirty‐eight variants were considered to be nominally significant associated with risk of EC or ESCC, whereas the rest showed non‐association. In additional, five variants on five genes were rated as strong cumulative epidemiological evidence for a nominally significant association with EC and ESCC risk, including CYP1A1 rs1048943, EGF rs444903, HOTAIR rs920778, MMP2 rs243865, and PLCE1 rs2274223, 10 variants were rated as moderate, and 18 variants were rated as weak. Additionally, 17 SNPs were verified noteworthy in six genomewide association studies (GWAS) using FPRP methods. Collectively, this review offered a comprehensively referenced information with cumulative evidence of associations between genetic polymorphisms and EC and ESCC risk.

Single nucleotide polymorphisms and sporadic colorectal cancer susceptibility: a field synopsis and meta-analysis

Background

Although mounting non-hereditary colorectal cancer (NHCRC) associated single nucleotide polymorphisms (SNPs) have been observed, no field synopsis and meta-analysis has been conducted through systematically assessing cumulative evidence, during the past 5 years.

Methods

We retrieved the database via the PubMed, Web of Science and Embase gateways to identify publications concerning the associations between SNPs and risk of NHCRC, up to May 1st, 2017. To assess the finding credibility, cumulative evidence was graded based on the Venice criteria. Meta-analysis was also performed for three subgroups including ethnicity (Asian vs Caucasian), primary cancer site (colon vs rectum) and TNM stage (I II vs III IV). Then, we arranged those high quality SNPs into different regions according to their locations on genes to evaluate their functional roles on CRC development.

Results

5114 publications were collected and 1001 of them met our inclusion criteria, which totally included 1788 SNPs in 793 genes or distinct chromosomal loci. Totally, we performed 359 primary and subgroup meta-analyses for 160 SNPs in 96 distinct genes. By utilizing the Venice criteria, we identified 15 high quality SNPs with 25 high credibility significant associations. Furthermore, we artificially divided the high quality SNPs into different groups, based on their SNP loci (exon region, intron region, promoter region, downstream region, non-coding region and intergenic region).

Conclusion

We have identified 15 high quality SNPs which may act as promising genetic biomarkers for clinical NHCRC susceptibility screening and explored their functional roles on the NHCRC development based on their locations on genes.

Personalizing Environmental Health: At the Intersection of Precision Medicine and Occupational Health in the Military

: Recent efforts in precision medicine present unique opportunities for military environmental and occupational health. Risk assessments can be refined by individualized risk factors such as genomics, and health status can be monitored and informed using mobile health (mHealth) devices. The military currently monitors exposures with service-wide databases and has one of the world's largest biobanks of serum samples available for health surveillance. New approaches are being developed for risk assessment, novel exposure-based biomarkers, and mobile applications to combine the facile collection of exposure data with tracking and planning utility. Planning by military leaders and coordination with national efforts puts the Department of Defense (DoD) in a unique position to benefit both Service Members and the nation, as reviewed in a symposium cosponsored by the DoD and the Johns Hopkins University-Applied Physics Laboratory (October 27 to 28, 2015).

The FAIR guiding principles for data stewardship: fair enough?

The FAIR guiding principles for research data stewardship (findability, accessibility, interoperability, and reusability) look set to become a cornerstone of research in the life sciences. A critical appraisal of these principles in light of ongoing discussions and developments about data sharing is in order. The FAIR principles point the way forward for facilitating data sharing more systematically-provided that a number of ethical, methodological, and organisational challenges are addressed as well.

TNFSF15 is likely a susceptibility gene for systemic lupus erythematosus

We aim to explore the correlation of TNFSF15 genetic polymorphisms with susceptibility to systemic lupus erythematosus (SLE). This study enrolled SLE patients and healthy individuals to detect three single nucleotide polymorphisms (SNPs) of TNFSF15 (rs3810936, rs6478108 and rs4979462) through using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) to analyze the possible association of these three SNPs with the risk of SLE and the mRNA level of TNFSF15 was quantified by real-time PCR. The rs3810936 T allele carrier greatly decreased risk of SLE (OR = 0.620, 95% CI = 0.454-0.849, P = 0.003), while the risk of SLE for rs4979462 T allele carrier was significantly increased (OR = 1.66, 95% CI = 1.243-2.218, P < 0.001). The mRNA level of TNFSF15 was obviously higher in SLE patients, and specifically, the patients who carried the CC genotype of TNFSF15 rs3810936 had a higher TNFSF15 mRNA, but the rs4979462 CC genotype carriers appeared to be associated with the decreased TNFSF15 mRNA (all P < 0.05). Besides, the genotypes of rs3810936 and rs4979462 of TNFSF15 were significantly associated with butterfly rash, arthritis, serositis, renal nephritis, hematological disorder, immunological disorder and positive antinuclear antibody (ANA) of SLE patients (all P < 0.05). CCT and CTT haplotypes were risk factors of SLE, but CCC and TTT were protective factors of SLE (all P < 0.05). Logistic regression analysis showed that rs3810936 and rs4979462 of TNFSF15, histories of chilblain and wet living environment were independently associated with the risk of SLE (all P < 0.05).The current results suggested that TNFSF15 (rs3810936 and rs4979462) SNPs may confer susceptibility to SLE risk, which were significantly associated with the clinical phenotypes of SLE.

At the Crossroads Between Neurodegeneration and Cancer: A Review of Overlapping Biology and Its Implications

BACKGROUND

A growing body of epidemiologic evidence suggests that neurodegenerative diseases occur less frequently in cancer survivors, and vice versa. While unusual, this inverse comorbidity is biologically plausible and could be explained, in part, by the evolutionary tradeoffs made by neurons and cycling cells to optimize the performance of their very different functions. The two cell types utilize the same proteins and pathways in different, and sometimes opposite, ways. However, cancer and neurodegeneration also share many pathophysiological features.

OBJECTIVE

In this review, we compare three overlapping aspects of neurodegeneration and cancer.

METHOD

First, we contrast the priorities and tradeoffs of dividing cells and neurons and how these manifest in disease. Second, we consider the hallmarks of biological aging that underlie both neurodegeneration and cancer. Finally, we utilize information from genetic databases to outline specific genes and pathways common to both diseases.

CONCLUSION

We argue that a detailed understanding of the biologic and genetic relationships between cancer and neurodegeneration can guide future efforts in designing disease-modifying therapeutic interventions. Lastly, strategies that target aging may prevent or delay both conditions.

Cumulative evidence for relationships between multiple variants in the VTI1A and TCF7L2 genes and cancer incidence

Genetic studies have linked the VTI1A-TCF7L2 region with risk of multiple cancers. However, findings from these studies were generally inconclusive. We aimed to provide a synopsis of current understanding of associations between variants in the VTI1A-TCF7L2 region and cancer susceptibility. We conducted a comprehensive research synopsis and meta-analysis to evaluate associations between 17 variants in this region and risk of seven cancers using data from 32 eligible articles totaling 224,656 cancer cases and 324,845 controls. We graded cumulative evidence of significant associations using Venice criteria and false-positive report probability tests. We also conducted analyses to evaluate potential function of these variants using data from the Encyclopedia of DNA Elements (ENCODE) Project. Eight variants showed a nominally significant association with risk of individual cancer (p < 0.05). Cumulative epidemiological evidence of an association was graded as strong for rs7903146 [odds ratio (OR) = 1.05, p = 4.13 × 10^-5 ] and rs7904519 (OR = 1.07, p = 2.02 × 10^-14 ) in breast cancer, rs11196172 (OR = 1.11, p = 2.22 × 10^-16 ), rs12241008 (OR = 1.13, p = 1.36 × 10^-10 ) and rs10506868 (OR = 1.10, p = 3.98 × 10^-9 ) in colorectal cancer, rs7086803 in lung cancer (OR = 1.30, p = 3.54 × 10^-18 ) and rs11196067 (OR = 1.18, p = 3.59 × 10^-13 ) in glioma, moderate for rs12255372 (OR = 1.12, p = 2.52 × 10^-4 ) in breast cancer and weak for rs7903146 (OR = 1.11, p = 0.007) in colorectal cancer. Data from ENCODE suggested that seven variants with strong evidence and other correlated variants might fall within putative functional regions. Collectively, our study provides summary evidence that common variants in the VTI1A and TCF7L2 genes are associated with risk of breast, colorectal, lung cancer and glioma and highlights the significant role of the VTI1A-TCF7L2 region in the pathogenesis of human cancers.

Genetic polymorphisms and lung cancer risk: Evidence from meta-analyses and genome-wide association studies

A growing number of studies investigating the association between Single Nucleotide Polymorphisms (SNPs) and lung cancer risk have been published since over a decade ago. An updated integrative assessment on the credibility and strength of the associations is required. We searched PubMed, Medline, and Web of Science on or before August 29^th, 2016. A total of 198 articles were deemed eligible for inclusion, which addressed the associations between 108 variants and lung cancer. Among the 108 variants, 63 were reported to be significantly associated with lung cancer while the remaining 45 were reported non-significant. Further evaluation integrating the Venice Criteria and false-positive report probability (FPRP) was performed to determine the strength of cumulative epidemiological evidence for the 63 significant associations. As a result, 15 SNPs on or near 12 genes and one miRNA with strong evidence of association with lung cancer risk were identified, including TERT (rs2736098), CHRNA3 (rs1051730), AGPHD1 (rs8034191), CLPTM1L (rs401681 and rs402710), BAT3 (rs3117582), TRNAA (rs4324798), ERCC2 (Lys751Gln), miR-146a2 (rs2910164), CYP1B1 (Arg48Gly), GSTM1 (null/present), SOD2 (C47T), IL-10 (-592C/A and -819C/T), and TP53 (intron 6). 19 SNPs were given moderate rating and 17 SNPs were rated as having weak evidence. In addition, all of the 29 SNPs identified in 12 genome-wide association studies (GWAS) were proved to be noteworthy based on FPRP value. This review summarizes and evaluates the cumulative evidence of genetic polymorphisms and lung cancer risk, which can serve as a general and useful reference for further genetic studies.

An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes

High-throughput genotyping has enabled discovery of genetic variants associated with an increased risk of developing prostate cancer using genome-wide association studies (GWAS). The goal of this study was to associate GWAS information of patients with primary organ–confined and metastatic prostate cancer using gene expression data and to identify molecular networks and biological pathways enriched for genetic susceptibility variants involved in the 2 disease states. The analysis revealed gene signatures for the 2 disease states and a gene signature distinguishing the 2 patient groups. In addition, the analysis revealed molecular networks and biological pathways enriched for genetic susceptibility variants. The discovered pathways include the androgen, apoptosis, and insulinlike growth factor signaling pathways. This analysis established putative functional bridges between GWAS discoveries and the biological pathways involved in primary organ–confined and metastatic prostate cancer.

Meta-analysis for genome-wide association studies using case-control design: application and practice

This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy-Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The 'genhwcci' and 'metan' commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the 'metareg' command of STATA should be conducted to evaluate related factors of heterogeneities.

Further evidence of VRK2 rs2312147 associated with schizophrenia

OBJECTIVES

Previous genome-wide association studies (GWAS) have reported that rs2312147 near the VRK2 gene was significantly associated with schizophrenia in populations of European descent, but negative results have also been observed.

METHODS

To perform a systematic meta-analysis, we collected statistical data of rs2312147 from both GWAS and individual replication samples in European and Asian populations, which finally included up to 30,867 schizophrenia patients and 59,863 healthy controls.

RESULTS

The VRK2 rs2312147 was genome-wide significantly associated with schizophrenia in combined populations (P = 1.31 × 10(-15), odds ratio, OR = 1.10) as well as in Europeans only (P = 2.35 × 10(-12), OR =1.09). In Asian samples, the SNP did not reach genome-wide level of statistical significance (P = 1.23 × 10 (-) (5), OR =1.19), which is likely due to the limited power of small sample size in this population (2,974 cases and 4,786 controls). However, the effect size of rs2312147 did not alter significantly between populations, and is also in agreement with the observed effect sizes of other genetic risk loci in large scale studies.

CONCLUSIONS

Our data provides further evidence for the genetic contributions of VRK2 rs2312147 to schizophrenia susceptibility especially in Europeans, while further replication analyses in Asian populations are still needed, and future studies, e.g., the underlying molecular mechanisms of genetic risk, are necessary.

Systematic meta-analyses and field synopsis of genetic association studies in colorectal adenomas

BACKGROUND

Low penetrance genetic variants, primarily single nucleotide polymorphisms, have substantial influence on colorectal cancer (CRC) susceptibility. Most CRCs develop from colorectal adenomas (CRA). Here we report the first comprehensive field synopsis that catalogues all genetic association studies on CRA, with a parallel online database [http://www.chs.med.ed.ac.uk/CRAgene/].

METHODS

We performed a systematic review, reviewing 9750 titles, and then extracted data from 130 publications reporting on 181 polymorphisms in 74 genes. We conducted meta-analyses to derive summary effect estimates for 37 polymorphisms in 26 genes. We applied the Venice criteria and Bayesian False Discovery Probability (BFDP) to assess the levels of the credibility of associations.

RESULTS

We considered the association with the rs6983267 variant at 8q24 as 'highly credible', reaching genome-wide statistical significance in at least one meta-analysis model. We identified 'less credible' associations (higher heterogeneity, lower statistical power, BFDP > 0.02) with a further four variants of four independent genes: MTHFR c.677C>T p.A222V (rs1801133), TP53 c.215C>G p.R72P (rs1042522), NQO1 c.559C>T p.P187S (rs1800566), and NAT1 alleles imputed as fast acetylator genotypes. For the remaining 32 variants of 22 genes for which positive associations with CRA risk have been previously reported, the meta-analyses revealed no credible evidence to support these as true associations.

CONCLUSIONS

The limited number of credible associations between low penetrance genetic variants and CRA reflects the lower volume of evidence and associated lack of statistical power to detect associations of the magnitude typically observed for genetic variants and chronic diseases. The CRA gene database provides context for CRA genetic association data and will help inform future research directions.

Updated field synopsis and systematic meta-analyses of genetic association studies in cutaneous melanoma: the MelGene database

We updated a field synopsis of genetic associations of cutaneous melanoma (CM) by systematically retrieving and combining data from all studies in the field published as of August 31, 2013. Data were available from 197 studies, which included 83,343 CM cases and 187,809 controls and reported on 1,126 polymorphisms in 289 different genes. Random-effects meta-analyses of 81 eligible polymorphisms evaluated in >4 data sets confirmed 20 single-nucleotide polymorphisms across 10 loci (TYR, AFG3L1P, CDK10, MYH7B, SLC45A2, MTAP, ATM, CLPTM1L, FTO, and CASP8) that have previously been published with genome-wide significant evidence for association (P<5 × 10(-8)) with CM risk, with certain variants possibly functioning as proxies of already tagged genes. Four other loci (MITF, CCND1, MX2, and PLA2G6) were also significantly associated with 5 × 10(-8) Collapse

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MESH Headings

• Chromosome Mapping
• Databases, Genetic
• Gene Expression Regulation, Neoplastic
• Genetic Predisposition to Disease
• Genetic Variation
• Genome-Wide Association Study
• Germ-Line Mutation
• Humans
• Linkage Disequilibrium
• Melanoma/genetics
• Odds Ratio
• Polymorphism, Single Nucleotide
• Skin Neoplasms/genetics
• Melanoma, Cutaneous Malignant

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Grants Collapse

Affiliation(s)

Kyriaki Antonopoulou Department of Dermatology, University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
Irene Stefanaki Department of Dermatology, University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
Christina M Lill Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany; Department of Neurology, Focus Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
Foteini Chatzinasiou Department of Dermatology, University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
Katerina P Kypreou Department of Dermatology, University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
Fani Karagianni Department of Dermatology, University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
Emmanouil Athanasiadis Center of Systems Biology, Biomedical Research Foundation, Academy of Athens, Athens, Greece
George M Spyrou Center of Systems Biology, Biomedical Research Foundation, Academy of Athens, Athens, Greece
John P A Ioannidis Department of Medicine, Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, California, USA
Lars Bertram Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany; Department of Medicine, School of Public Health, Imperial College London, London, UK
Evangelos Evangelou Department of Hygiene and Epidemiology, Clinical and Molecular Epidemiology Unit, School of Medicine, University of Ioannina, Ioannina, Greece; Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, London, UK
Alexander J Stratigos Department of Dermatology, University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece.

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Gene-environment interplay in common complex diseases: forging an integrative model—recommendations from an NIH workshop

Although it is recognized that many common complex diseases are a result of multiple genetic and environmental risk factors, studies of gene-environment interaction remain a challenge and have had limited success to date. Given the current state-of-the-science, NIH sought input on ways to accelerate investigations of gene-environment interplay in health and disease by inviting experts from a variety of disciplines to give advice about the future direction of gene-environment interaction studies. Participants of the NIH Gene-Environment Interplay Workshop agreed that there is a need for continued emphasis on studies of the interplay between genetic and environmental factors in disease and that studies need to be designed around a multifaceted approach to reflect differences in diseases, exposure attributes, and pertinent stages of human development. The participants indicated that both targeted and agnostic approaches have strengths and weaknesses for evaluating main effects of genetic and environmental factors and their interactions. The unique perspectives represented at the workshop allowed the exploration of diverse study designs and analytical strategies, and conveyed the need for an interdisciplinary approach including data sharing, and data harmonization to fully explore gene-environment interactions. Further, participants also emphasized the continued need for high-quality measures of environmental exposures and new genomic technologies in ongoing and new studies.

Environmental variables as potential modifiable risk factors of preterm birth in Philadelphia, PA

OBJECTIVE

To examine whether variation in neighborhood context is associated with preterm birth (PTB) outcomes and gestational age (GA) at delivery in Philadelphia, and to determine whether these associations might persist when considering relevant individual-level variables.

STUDY DESIGN

We analyzed individual-level data collected for a prospective cohort study of singleton pregnancies with preterm labor. We merged block-group level data to each individual's home address. Unadjusted analyses were performed to determine the association between block-group variables and individual-level outcomes. Block-group variables identified as potential risk factors were incorporated into multivariable individual-level models to determine significance.

RESULTS

We analyzed data for 817 women. The prevalence of PTB <37 weeks was 41.5%. Although in unadjusted analyses several block-group variables were associated with PTB and GA at delivery, none retained significance in individual-level multivariable models.

CONCLUSION

Block-group level data were not associated with PTB outcomes or GA at delivery in Philadelphia.

A systematic appraisal of field synopses in genetic epidemiology: a HuGE review

Evidence from genetic association studies is accumulating rapidly. Field synopses have recently arisen as an unbiased way of systematically synthesizing this evidence. We performed a systematic review and appraisal of published field synopses in genetic epidemiology and assessed their main findings and methodological characteristics. We identified 61 eligible field synopses, published between January 1, 2007, and October 31, 2013, on 52 outcomes reporting 734 significant associations at the P < 0.05 level. The median odds ratio for these associations was 1.25 (interquartile range, 1.15-1.43). Egger's test was the most common method (n = 30 synopses) of assessing publication bias. Only 12 synopses (20%) used the Venice criteria to evaluate the epidemiologic credibility of their findings (n = 449 variants). Eleven synopses (18%) were accompanied by an online database that has been regularly updated. These synopses received more citations (P = 0.01) and needed a larger research team (P = 0.02) than synopses without an online database. Overall, field synopses are becoming a valuable tool for the identification of common genetic variants, especially when researchers follow relevant methodological guidelines. Our work provides a summary of the current status of the field synopses published to date and may help interested readers efficiently identify the online resources containing the relevant genetic evidence.

Bayesian methodology for the design and interpretation of clinical trials in critical care medicine: a primer for clinicians

OBJECTIVES

To review Bayesian methodology and its utility to clinical decision making and research in the critical care field.

DATA SOURCE AND STUDY SELECTION

Clinical, epidemiological, and biostatistical studies on Bayesian methods in PubMed and Embase from their inception to December 2013.

DATA SYNTHESIS

Bayesian methods have been extensively used by a wide range of scientific fields, including astronomy, engineering, chemistry, genetics, physics, geology, paleontology, climatology, cryptography, linguistics, ecology, and computational sciences. The application of medical knowledge in clinical research is analogous to the application of medical knowledge in clinical practice. Bedside physicians have to make most diagnostic and treatment decisions on critically ill patients every day without clear-cut evidence-based medicine (more subjective than objective evidence). Similarly, clinical researchers have to make most decisions about trial design with limited available data. Bayesian methodology allows both subjective and objective aspects of knowledge to be formally measured and transparently incorporated into the design, execution, and interpretation of clinical trials. In addition, various degrees of knowledge and several hypotheses can be tested at the same time in a single clinical trial without the risk of multiplicity. Notably, the Bayesian technology is naturally suited for the interpretation of clinical trial findings for the individualized care of critically ill patients and for the optimization of public health policies.

CONCLUSIONS

We propose that the application of the versatile Bayesian methodology in conjunction with the conventional statistical methods is not only ripe for actual use in critical care clinical research but it is also a necessary step to maximize the performance of clinical trials and its translation to the practice of critical care medicine.

A Web-based database of genetic association studies in cutaneous melanoma enhanced with network-driven data exploration tools

The publicly available online database MelGene provides a comprehensive, regularly updated, collection of data from genetic association studies in cutaneous melanoma (CM), including random-effects meta-analysis results of all eligible polymorphisms. The updated database version includes data from 192 publications with information on 1114 significantly associated polymorphisms across 280 genes, along with new front-end and back-end capabilities. Various types of relationships between data are calculated and visualized as networks. We constructed 13 different networks containing the polymorphisms and the genes included in MelGene. We explored the derived network representations under the following questions: (i) are there nodes that deserve consideration regarding their network connectivity characteristics? (ii) What is the relation of either the genome-wide or nominally significant CM polymorphisms/genes with the ones highlighted by the network representation? We show that our network approach using the MelGene data reveals connections between statistically significant genes/ polymorphisms and other genes/polymorphisms acting as 'hubs' in the reconstructed networks. To the best of our knowledge, this is the first database containing data from a comprehensive field synopsis and systematic meta-analyses of genetic polymorphisms in CM that provides user-friendly tools for in-depth molecular network visualization and exploration. The proposed network connections highlight potentially new loci requiring further investigation of their relation to melanoma risk. Database URL: http://www.melgene.org.

Maternal genotype and severe preeclampsia: a HuGE review

Severe preeclampsia is a common cause of maternal and perinatal morbidity worldwide. The disease clusters in families; however, individual genetic studies have produced inconsistent results. We conducted a review to examine relationships between maternal genotype and severe preeclampsia. We searched the MEDLINE and Embase databases for prospective and retrospective cohort and case-control studies reporting associations between genes and severe preeclampsia. Four reviewers independently undertook study selection, quality assessment, and data extraction. We performed random-effects meta-analyses by genotype and predefined functional gene group (thrombophilic, vasoactive, metabolic, immune, and cell signalling). Fifty-seven studies evaluated 50 genotypes in 5,049 cases and 16,989 controls. Meta-analysis showed a higher risk of severe preeclampsia with coagulation factor V gene (proaccelerin, labile factor) (F5) polymorphism rs6025 (odds ratio = 1.90, 95% confidence interval: 1.42, 2.54; 23 studies, I(2) = 29%), coagulation factor II (thrombin) gene (F2) mutation G20210A (rs1799963) (odds ratio = 2.01, 95% confidence interval: 1.14, 3.55, 9 studies, I(2) = 0%), leptin receptor gene (LEPR) polymorphism rs1137100 (odds ratio = 1.75, 95% confidence interval: 1.15, 2.65; 2 studies, I(2) = 0%), and the thrombophilic gene group (odds ratio = 1.87, 95% confidence interval: 1.43, 2.45, I(2) = 27%). There were no associations with other gene groups. There was moderate heterogeneity between studies and potential for bias from poor-quality genotyping and inconsistent definition of phenotype. Further studies with robust methods should investigate genetic factors that might potentially be used to stratify pregnancies according to risk of complications.

Integrative genomic analysis for the discovery of biomarkers in prostate cancer

Genome-wide association studies (GWAS) have achieved great success in identifying single nucleotide polymorphisms (SNPs, herein called genetic variants) and genes associated with risk of developing prostate cancer. However, GWAS do not typically link the genetic variants to the disease state or inform the broader context in which the genetic variants operate. Here, we present a novel integrative genomics approach that combines GWAS information with gene expression data to infer the causal association between gene expression and the disease and to identify the network states and biological pathways enriched for genetic variants. We identified gene regulatory networks and biological pathways enriched for genetic variants, including the prostate cancer, IGF-1, JAK2, androgen, and prolactin signaling pathways. The integration of GWAS information with gene expression data provides insights about the broader context in which genetic variants associated with an increased risk of developing prostate cancer operate.

Assessment of osteoarthritis candidate genes in a meta-analysis of nine genome-wide association studies

Objective

To assess candidate genes for association with osteoarthritis (OA) and identify promising genetic factors and, secondarily, to assess the candidate gene approach in OA.

Methods

A total of 199 candidate genes for association with OA were identified using Human Genome Epidemiology (HuGE) Navigator. All of their single-nucleotide polymorphisms (SNPs) with an allele frequency of >5% were assessed by fixed-effects meta-analysis of 9 genome-wide association studies (GWAS) that included 5,636 patients with knee OA and 16,972 control subjects and 4,349 patients with hip OA and 17,836 control subjects of European ancestry. An additional 5,921 individuals were genotyped for significantly associated SNPs in the meta-analysis. After correction for the number of independent tests, P values less than 1.58 × 10⁻⁵ were considered significant.

Results

SNPs at only 2 of the 199 candidate genes (COL11A1 and VEGF) were associated with OA in the meta-analysis. Two SNPs in COL11A1 showed association with hip OA in the combined analysis: rs4907986 (P = 1.29 × 10⁻⁵, odds ratio [OR] 1.12, 95% confidence interval [95% CI] 1.06−1.17) and rs1241164 (P = 1.47 × 10⁻⁵, OR 0.82, 95% CI 0.74−0.89). The sex-stratified analysis also showed association of COL11A1 SNP rs4908291 in women (P = 1.29 × 10⁻⁵, OR 0.87, 95% CI 0.82−0.92); this SNP showed linkage disequilibrium with rs4907986. A single SNP of VEGF, rs833058, showed association with hip OA in men (P = 1.35 × 10⁻⁵, OR 0.85, 95% CI 0.79−0.91). After additional samples were genotyped, association at one of the COL11A1 signals was reinforced, whereas association at VEGF was slightly weakened.

Conclusion

Two candidate genes, COL11A1 and VEGF, were significantly associated with OA in this focused meta-analysis. The remaining candidate genes were not associated.