Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Long-term outcomes of transoral incisionless fundoplication for gastro-esophageal reflux disease: systematic-review and meta-analysis

Background and study aims  Few reports exist about long-term outcomes of transoral incisionless fundoplication (TIF) for treating refractory gastro-esophageal reflux disease (GERD). Methods  A literature search of four major scientific databases was performed up to May 2020 for studies reporting on more than 3-year outcomes of TIF. Data on atient satisfaction, proton pump inhibitor (PPI) daily consumption, PPI use reduction, GERD health-related quality-of-life (GERD-HRQL) score, and normalization of heartburn and regurgitation scores were pooled and summarized with forest plots. Publication bias and heterogeneity were explored. Results  Overall, eight studies (418 patients, 232 men; 55.5 %) with a mean follow-up of 5.3 years (range: 3-10 years) were included. The pooled proportion of patient-reported satisfaction before and after TIF was 12.3 % (95 % CI:12.3-35.1 %, I (2)  = 87.4 %) and 70.6 % (95 % CI:51.2-84.6, I (2)  = 80 %), respectively, corresponding to an odds ratio of 21.4 (95 % CI:3.27-140.5). Pooled rates of patients completely off PPIs and on occasional PPIs were 53.8 % (95 %CI: 42.0 %-65.1 %) and 75.8 % (95 %CI: 67.6-82.6), respectively. The pooled estimated mean GERD-HRQL scores off PPI before and after TIF werey 26.1 (95 %CI: 21.5-30.7; range: 20.0-35.5) and 5.9, respectively (95 %CI:0.35.1-11.4; range: 5.3-9.8; P  < 0.001). The overall pooled rates of heartburn and regurgitation scores normalization were 73.0 % (95 %CI: 0.62-0.82) and 86 %, respectively (95 %CI: 75.0-91.0 %). Conclusion  Our study shows that TIF appears to offer a long-term safe therapeutic option for selected patients with GERD who refuse life-long medical therapy or surgery, are intolerant to PPIs, or are at increased surgical risk

Genome-wide scan of long noncoding RNA single nucleotide polymorphisms and pancreatic cancer susceptibility

Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second cancer-related cause of death by 2030. Identifying novel risk factors, including genetic risk loci, could be instrumental in risk stratification and implementation of prevention strategies. Long noncoding RNAs (lncRNAs) are involved in regulation of key biological processes, and the possible role of their genetic variability has been unexplored so far. Combining genome wide association studies and functional data, we investigated the genetic variability in all lncRNAs. We analyzed 9893 PDAC cases and 9969 controls and identified a genome-wide significant association between the rs7046076 SNP and risk of developing PDAC (P = 9.73\u2009 7\u200910-9 ). This SNP is located in the NONHSAG053086.2 (lnc-SMC2-1) gene and the risk allele is predicted to disrupt the binding of the lncRNA with the micro-RNA (miRNA) hsa-mir-1256 that regulates several genes involved in cell cycle, such as CDKN2B. The CDKN2B region is pleiotropic and its genetic variants have been associated with several human diseases, possibly though an imperfect interaction between lncRNA and miRNA. We present a novel PDAC risk locus, supported by a genome-wide statistical significance and a plausible biological mechanism

Identification of Recessively Inherited Genetic Variants Potentially Linked to Pancreatic Cancer Risk

Although 21 pancreatic cancer susceptibility loci have been identified in individuals of European ancestry through genome-wide association studies (GWASs), much of the heritability of pancreatic cancer risk remains unidentified. A recessive genetic model could be a powerful tool for identifying additional risk variants. To discover recessively inherited pancreatic cancer risk loci, we performed a re-analysis of the largest pancreatic cancer GWAS, the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including 8,769 cases and 7,055 controls of European ancestry. Six single nucleotide polymorphisms (SNPs) showed associations with pancreatic cancer risk according to a recessive model of inheritance. We replicated these variants in 3,212 cases and 3,470 controls collected from the PANcreatic Disease ReseArch (PANDoRA) consortium. The results of the meta-analyses confirmed that rs4626538 (7q32.2), rs7008921 (8p23.2) and rs147904962 (17q21.31) showed specific recessive effects (p10−3), although none of the six SNPs reached the conventional threshold for genome-wide significance (p < 5×10−8). Additional bioinformatic analysis explored the functional annotations of the SNPs and indicated a possible relationship between rs36018702 and expression of the BCL2L11 and BUB1 genes, which are known to be involved in pancreatic biology. Our findings, while not conclusive, indicate the importance of considering non-additive genetic models when performing GWAS analysis. The SNPs associated with pancreatic cancer in this study could be used for further meta-analysis for recessive association of SNPs and pancreatic cancer risk and might be a useful addiction to improve the performance of polygenic risk scores

Identification of Recessively Inherited Genetic Variants Potentially Linked to Pancreatic Cancer Risk

Although 21 pancreatic cancer susceptibility loci have been identified in individuals of European ancestry through genome-wide association studies (GWASs), much of the heritability of pancreatic cancer risk remains unidentified. A recessive genetic model could be a powerful tool for identifying additional risk variants. To discover recessively inherited pancreatic cancer risk loci, we performed a re-analysis of the largest pancreatic cancer GWAS, the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including 8,769 cases and 7,055 controls of European ancestry. Six single nucleotide polymorphisms (SNPs) showed associations with pancreatic cancer risk according to a recessive model of inheritance. We replicated these variants in 3,212 cases and 3,470 controls collected from the PANcreatic Disease ReseArch (PANDoRA) consortium. The results of the meta-analyses confirmed that rs4626538 (7q32.2), rs7008921 (8p23.2) and rs147904962 (17q21.31) showed specific recessive effects (p&lt;10(-5)) compared with the additive effects (p&gt;10(-3)), although none of the six SNPs reached the conventional threshold for genome-wide significance (p &lt; 5x10(-8)). Additional bioinformatic analysis explored the functional annotations of the SNPs and indicated a possible relationship between rs36018702 and expression of the BCL2L11 and BUB1 genes, which are known to be involved in pancreatic biology. Our findings, while not conclusive, indicate the importance of considering non-additive genetic models when performing GWAS analysis. The SNPs associated with pancreatic cancer in this study could be used for further meta-analysis for recessive association of SNPs and pancreatic cancer risk and might be a useful addiction to improve the performance of polygenic risk scores

Association of Genetic Variants Affecting microRNAs and Pancreatic Cancer Risk

Genetic factors play an important role in the susceptibility to pancreatic cancer (PC). However, established loci explain a small proportion of genetic heritability for PC; therefore, more progress is needed to find the missing ones. We aimed at identifying single nucleotide polymorphisms (SNPs) affecting PC risk through effects on micro-RNA (miRNA) function. We searched in silico the genome for SNPs in miRNA seed sequences or 3 prime untranslated regions (3'UTRs) of miRNA target genes. Genome-wide association data of PC cases and controls from the Pancreatic Cancer Cohort (PanScan) Consortium and the Pancreatic Cancer Case–Control (PanC4) Consortium were re-analyzed for discovery, and genotyping data from two additional consortia (PanGenEU and PANDoRA) were used for replication, for a total of 14,062 cases and 11,261 controls. None of the SNPs reached genome-wide significance in the meta-analysis, but for three of them the associations were in the same direction in all the study populations and showed lower value of p in the meta-analyses than in the discovery phase. Specifically, rs7985480 was consistently associated with PC risk (OR = 1.12, 95% CI 1.07–1.17, p = 3.03 × 10−6 in the meta-analysis). This SNP is in linkage disequilibrium (LD) with rs2274048, which modulates binding of various miRNAs to the 3'UTR of UCHL3, a gene involved in PC progression. In conclusion, our results expand the knowledge of the genetic PC risk through miRNA-related SNPs and show the usefulness of functional prioritization to identify genetic polymorphisms associated with PC risk

Polymorphic variants involved in methylation regulation: a strategy to discover risk loci for pancreatic ductal adenocarcinoma

Introduction: Only a small number of risk factors for pancreatic ductal adenocarcinoma (PDAC) has been established. Several studies identified a role of epigenetics and of deregulation of DNA methylation. DNA methylation is variable across a lifetime and in different tissues; nevertheless, its levels can be regulated by genetic variants like methylation quantitative trait loci (mQTLs), which can be used as a surrogate. Materials and methods: We scanned the whole genome for mQTLs and performed an association study in 14 705 PDAC cases and 246 921 controls. The methylation data were obtained from whole blood and pancreatic cancer tissue through online databases. We used the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium genome-wide association study (GWAS) data as discovery phase and the Pancreatic Disease Research consortium, the FinnGen project and the Japan Pancreatic Cancer Research consortium GWAS as replication phase. Results: The C allele of 15q26.1-rs12905855 showed an association with a decreased risk of PDAC (OR=0.90, 95% CI 0.87 to 0.94, p=4.93×10-8 in the overall meta-analysis), reaching genome-level statistical significance. 15q26.1-rs12905855 decreases the methylation of a 'C-phosphate-G' (CpG) site located in the promoter region of the RCCD1 antisense (RCCD1-AS1) gene which, when expressed, decreases the expression of the RCC1 domain-containing (RCCD1) gene (part of a histone demethylase complex). Thus, it is possible that the rs12905855 C-allele has a protective role in PDAC development through an increase of RCCD1 gene expression, made possible by the inactivity of RCCD1-AS1. Conclusion: We identified a novel PDAC risk locus which modulates cancer risk by controlling gene expression through DNA methylation