Using the ENCODE Resource for Functional Annotation of Genetic Variants

The importance of functional genomics studies in precision rheumatology

Rheumatic diseases, those that affect the musculoskeletal system, cause significant morbidity. Among risk factors of these diseases is a significant genetic component. Recent advances in high-throughput omics techniques now allow a comprehensive profiling of patients at a genetic level through genome-wide association studies. Without functional interpretation of variants identified through these studies, clinical insight remains limited. Strategies include statistical fine-mapping that refine the list of variants in loci associated with disease, whilst colocalization techniques attempt to attribute function to variants that overlap a genetically active chromatin annotation. Functional validation using genome editing techniques can be used to further refine genetic signals and identify key pathways in cell types relevant to rheumatic disease biology. Insight gained from the combination of genetic studies and functional validation can be used to improve precision medicine in rheumatic diseases by allowing risk prediction and drug repositioning.

Remote regulation of rs80245547 and rs72673891 mediated by transcription factors C-Jun and CREB1 affect GSTCD expression

Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is influenced by genetic factors. The genetic signal rs10516526 in the glutathione S-transferase C-terminal domain containing (GSTCD) gene is a highly significant and reproducible signal associated with lung function and COPD on chromosome 4q24. In this study, comprehensive bioinformatics analyses and experimental verifications were detailly implemented to explore the regulation mechanism of rs10516526 and GSTCD in COPD. The results suggested that low expression of GSTCD was associated with COPD (p = 0.010). And C-Jun and CREB1 transcription factors were found to be essential for the regulation of GSTCD by rs80245547 and rs72673891. Moreover, rs80245547T and rs72673891G had a stronger binding ability to these transcription factors, which may promote the allele-specific long-range enhancer-promoter interactions on GSTCD, thus making COPD less susceptible. Our study provides a new insight into the relationship between rs10516526, GSTCD, and COPD.

Identifying polymorphic cis-regulatory variants as risk markers for lung carcinogenesis and chemotherapy responses in tobacco smokers from eastern India

Aberrant expression of xenobiotic metabolism and DNA repair genes is critical to lung cancer pathogenesis. This study aims to identify the cis-regulatory variants of the genes modulating lung cancer risk among tobacco smokers and altering their chemotherapy responses. From a list of 2984 SNVs, prioritization and functional annotation revealed 22 cis-eQTLs of 14 genes within the gene expression-correlated DNase I hypersensitive sites using lung tissue-specific ENCODE, GTEx, Roadmap Epigenomics, and TCGA datasets. The 22 cis-regulatory variants predictably alter the binding of 44 transcription factors (TFs) expressed in lung tissue. Interestingly, 6 reported lung cancer-associated variants were found in linkage disequilibrium (LD) with 5 prioritized cis-eQTLs from our study. A case-control study with 3 promoter cis-eQTLs (p < 0.01) on 101 lung cancer patients and 401 healthy controls from eastern India with confirmed smoking history revealed an association of rs3764821 (ALDH3B1) (OR = 2.53, 95% CI = 1.57-4.07, p = 0.00014) and rs3748523 (RAD52) (OR = 1.69, 95% CI = 1.17-2.47, p = 0.006) with lung cancer risk. The effect of different chemotherapy regimens on the overall survival of lung cancer patients to the associated variants showed that the risk alleles of both variants significantly decreased (p < 0.05) patient survival.

Clinical application of next-generation sequencing to the practice of neurology

Next-generation sequencing technologies allow for rapid and inexpensive large-scale genomic analysis, creating unprecedented opportunities to integrate genomic data into the clinical diagnosis and management of neurological disorders. However, the scale and complexity of these data make them difficult to interpret and require the use of sophisticated bioinformatics applied to extensive datasets, including whole exome and genome sequences. Detailed analysis of genetic data has shown that accurate phenotype information is essential for correct interpretation of genetic variants and might necessitate re-evaluation of the patient in some cases. A multidisciplinary approach that incorporates bioinformatics, clinical evaluation, and human genetics can help to address these challenges. However, despite numerous studies that show the efficacy of next-generation sequencing in establishing molecular diagnoses, pathogenic mutations are generally identified in fewer than half of all patients with genetic neurological disorders, exposing considerable gaps in the understanding of the human genome and providing opportunities to focus research on improving the usefulness of genomics in clinical practice. Looking forward, the emergence of precision health in neurological care will increasingly apply genomic data analysis to pharmacogenetics, preventive medicine, and patient-targeted therapies.

Molecular networks in Network Medicine: Development and applications

Network Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein-protein interaction networks, correlation-based networks, gene regulatory networks, and Bayesian networks. Network Medicine applies these integrated approaches to Omics Big Data (including genetics, epigenetics, transcriptomics, metabolomics, and proteomics) using computational biology tools and, thereby, has the potential to provide improvements in the diagnosis, prognosis, and treatment of complex diseases. We discuss briefly the types of molecular data that are used in molecular network analyses, survey the analytical methods for inferring molecular networks, and review efforts to validate and visualize molecular networks. Successful applications of molecular network analysis have been reported in pulmonary arterial hypertension, coronary heart disease, diabetes mellitus, chronic lung diseases, and drug development. Important knowledge gaps in Network Medicine include incompleteness of the molecular interactome, challenges in identifying key genes within genetic association regions, and limited applications to human diseases. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Translational, Genomic, and Systems Medicine > Translational Medicine Analytical and Computational Methods > Analytical Methods Analytical and Computational Methods > Computational Methods.

Principles of RNA processing from analysis of enhanced CLIP maps for 150 RNA binding proteins

BACKGROUND

A critical step in uncovering rules of RNA processing is to study the in vivo regulatory networks of RNA binding proteins (RBPs). Crosslinking and immunoprecipitation (CLIP) methods enable mapping RBP targets transcriptome-wide, but methodological differences present challenges to large-scale analysis across datasets. The development of enhanced CLIP (eCLIP) enabled the mapping of targets for 150 RBPs in K562 and HepG2, creating a unique resource of RBP interactomes profiled with a standardized methodology in the same cell types.

RESULTS

Our analysis of 223 eCLIP datasets reveals a range of binding modalities, including highly resolved positioning around splicing signals and mRNA untranslated regions that associate with distinct RBP functions. Quantification of enrichment for repetitive and abundant multicopy elements reveals 70% of RBPs have enrichment for non-mRNA element classes, enables identification of novel ribosomal RNA processing factors and sites, and suggests that association with retrotransposable elements reflects multiple RBP mechanisms of action. Analysis of spliceosomal RBPs indicates that eCLIP resolves AQR association after intronic lariat formation, enabling identification of branch points with single-nucleotide resolution, and provides genome-wide validation for a branch point-based scanning model for 3' splice site recognition. Finally, we show that eCLIP peak co-occurrences across RBPs enable the discovery of novel co-interacting RBPs.

CONCLUSIONS

This work reveals novel insights into RNA biology by integrated analysis of eCLIP profiling of 150 RBPs with distinct functions. Further, our quantification of both mRNA and other element association will enable further research to identify novel roles of RBPs in regulating RNA processing.

The contribution of rare genetic variants to the pathogenesis of polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a highly heritable disorder, but only a small proportion of the heritability can be accounted for by common genetic risk variants identified to date. It is possible that variants with lower allele frequencies that cannot be detected using genome-wide association study arrays contribute to PCOS. Here, we discuss the challenges inherent to studying rare genetic variants in complex disease and review several recent studies that have used DNA sequencing techniques to investigate whether rare variants play a role in PCOS pathogenesis. We evaluate these findings in the context of the latest literature in PCOS and complex disease genetics.

Annot: a Django-based sample, reagent, and experiment metadata tracking system

Background

In biological experiments, comprehensive experimental metadata tracking – which comprises experiment, reagent, and protocol annotation with controlled vocabulary from established ontologies – remains a challenge, especially when the experiment involves multiple laboratory scientists who execute different steps of the protocol. Here we describe Annot, a novel web application designed to provide a flexible solution for this task.

Results

Annot enforces the use of controlled vocabulary for sample and reagent annotation while enabling robust investigation, study, and protocol tracking. The cornerstone of Annot’s implementation is a json syntax-compatible file format, which can capture detailed metadata for all aspects of complex biological experiments. Data stored in this json file format can easily be ported into spreadsheet or data frame files that can be loaded into R (https://www.r-project.org/) or Pandas, Python’s data analysis library (https://pandas.pydata.org/). Annot is implemented in Python3 and utilizes the Django web framework, Postgresql, Nginx, and Debian. It is deployed via Docker and supports all major browsers.

Conclusions

Annot offers a robust solution to annotate samples, reagents, and experimental protocols for established assays where multiple laboratory scientists are involved. Further, it provides a framework to store and retrieve metadata for data analysis and integration, and therefore ensures that data generated in different experiments can be integrated and jointly analyzed. This type of solution to metadata tracking can enhance the utility of large-scale datasets, which we demonstrate here with a large-scale microenvironment microarray study.

lncRNA PSORS1C3 is regulated by glucocorticoids and fine-tunes OCT4 expression in non-pluripotent cells

OCT4 is a transcription factor known for its regulatory roles in stemness, tumorigenesis and stress response. Considering its versatile functions, expression of OCT4 is regulated at different levels. PSORS1C3, a long non-coding RNA overlapped with OCT4, has a putative association with immune mediated diseases; however, its exact functions remained to be elucidated. Here, we demonstrated that PSORS1C3 is regulated by glucocorticoids (GC), has two endogenously active promoters, promoter 0 and 1, and two sets of transcripts, short and long variants. According to our findings, PSORS1C3 promoters behaved differently during neural differentiation of NT2 cells and glucocorticoid receptor (GR) activation. In both processes the expression pattern of short variants differed from that of long variants and was similar to OCT4 expression. Furthermore, our data revealed that PSORS1C3’s promoter 0 could act as an enhancer for OCT4 in non-pluripotent cells, where its deletion caused a significant decrease in OCT4 expression. Meanwhile, during GR activation promoter 0 functioned as a negative regulator and alleviated transcription induction of OCT4 after GC treatment. Altogether, our work clarified the structure and regulation of PSORS1C3, explained its relation to immune-related disease through GR signaling and introduced it as a novel fine-tuner of OCT4 expression in non-pluripotent cells.

Non-coding DNA in IBD: from sequence variation in DNA regulatory elements to novel therapeutic potential

Genome-wide association studies have identified over 200 loci associated with IBD. We and others have recently shown that, in addition to variants in protein-coding genes, the majority of the associated loci are related to DNA regulatory elements (DREs). These findings add a dimension to the already complex genetic background of IBD. In this review we summarise the existing evidence on the role of DREs in IBD. We discuss how epigenetic research can be used in candidate gene approaches that take non-coding variants into account and can help to pinpoint the essential pathways and cell types in the pathogenesis of IBD. Despite the increased level of genetic complexity, these findings can contribute to novel therapeutic options that target transcription factor binding and enhancer activity. Finally, we summarise the future directions and challenges of this emerging field.

Into the Wild: GWAS Exploration of Non-coding RNAs

Genome-wide association studies (GWAS) have proven a fundamental tool to identify common variants associated to complex traits, thus contributing to unveil the genetic components of human disease. Besides, the advent of GWAS contributed to expose unexpected findings that urged to redefine the framework of population genetics. First, loci identified by GWAS had small effect sizes and could only explain a fraction of the predicted heritability of the traits under study. Second, the majority of GWAS hits mapped within non-coding regions (such as intergenic or intronic regions) where new functional RNA species (such as lncRNAs or circRNAs) have started to emerge. Bigger cohorts, meta-analysis and technical improvements in genotyping allowed identification of an increased number of genetic variants associated to coronary artery disease (CAD) and cardiometabolic traits. The challenge remains to infer causal mechanisms by which these variants influence cardiovascular disease development. A tendency to assign potential causal variants preferentially to coding genes close to lead variants contributed to disregard the role of non-coding elements. In recent years, in parallel to an increased knowledge of the non-coding genome, new studies started to characterize disease-associated variants located within non-coding RNA regions. The upcoming of databases integrating single-nucleotide polymorphisms (SNPs) and non-coding RNAs together with novel technologies will hopefully facilitate the discovery of causal non-coding variants associated to disease. This review attempts to summarize the current knowledge of genetic variation within non-coding regions with a focus on long non-coding RNAs that have widespread impact in cardiometabolic diseases.

A functional genetic variation of SLC6A2 repressor hsa-miR-579-3p upregulates sympathetic noradrenergic processes of fear and anxiety

Increased sympathetic noradrenergic signaling is crucially involved in fear and anxiety as defensive states. MicroRNAs regulate dynamic gene expression during synaptic plasticity and genetic variation of microRNAs modulating noradrenaline transporter gene (SLC6A2) expression may thus lead to altered central and peripheral processing of fear and anxiety. In silico prediction of microRNA regulation of SLC6A2 was confirmed by luciferase reporter assays and identified hsa-miR-579-3p as a regulating microRNA. The minor (T)-allele of rs2910931 (MAF_cases = 0.431, MAF_controls = 0.368) upstream of MIR579 was associated with panic disorder in patients (p_allelic = 0.004, n_cases = 506, n_controls = 506) and with higher trait anxiety in healthy individuals (p_ASI = 0.029, p_ACQ = 0.047, n = 3112). Compared to the major (A)-allele, increased promoter activity was observed in luciferase reporter assays in vitro suggesting more effective MIR579 expression and SLC6A2 repression in vivo (p = 0.041). Healthy individuals carrying at least one (T)-allele showed a brain activation pattern suggesting increased defensive responding and sympathetic noradrenergic activation in midbrain and limbic areas during the extinction of conditioned fear. Panic disorder patients carrying two (T)-alleles showed elevated heart rates in an anxiety-provoking behavioral avoidance test (F(2, 270) = 5.47, p = 0.005). Fine-tuning of noradrenaline homeostasis by a MIR579 genetic variation modulated central and peripheral sympathetic noradrenergic activation during fear processing and anxiety. This study opens new perspectives on the role of microRNAs in the etiopathogenesis of anxiety disorders, particularly their cardiovascular symptoms and comorbidities.

Association of Novel ALX4 Gene Polymorphisms with Antidepressant Treatment Response: Findings from the CO-MED Trial

Genome-wide association studies (GWAS) were conducted in participants of the CO-MED (Combining Medications to Enhance Depression Outcomes) trial, a randomized, 3-treatment arm clinical trial of major depressive disorder (MDD) designed to identify markers of differential treatment outcome (response and remission). The QIDS-SR (Quick Inventory of Depressive Symptomatology, Self-Reported version) was used to measure response at week 6 (QIDS-SR ≤5) and remission at week 12 (QIDS-SR ≤6 and ≤8 at the last two study visits). Three treatment groups (escitalopram monotherapy, escitalopram + bupropion, and venlafaxine + mirtazapine) were evaluated. GWAS identified a potentially regulatory SNP rs10769025 in the ALX4 gene on chromosome 11 with a strong association (p value = 9.85925E-08) with response to escitalopram monotherapy in Caucasians. Further, haplotype analysis on 7 ALX4 variants showed that a regulatory haplotype CAAACTG was significantly associated (odds ratio = 3.4, p = 2.00E-04) with response to escitalopram monotherapy at week 6. Ingenuity pathway analyses in the present study suggest that ALX4 has an indirect connection with antidepressant gene pathways in MDD, which may account for the genetic association with treatment outcome. Functional genomics studies to investigate the role of ALX4 in antidepressant treatment outcome will be an interesting future direction.

Analytical Strategy to Prioritize Alzheimer's Disease Candidate Genes in Gene Regulatory Networks Using Public Expression Data

Alzheimer’s disease (AD) progressively destroys cognitive abilities in the aging population with tremendous effects on memory. Despite recent progress in understanding the underlying mechanisms, high drug attrition rates have put a question mark behind our knowledge about its etiology. Re-evaluation of past studies could help us to elucidate molecular-level details of this disease. Several methods to infer such networks exist, but most of them do not elaborate on context specificity and completeness of the generated networks, missing out on lesser-known candidates. In this study, we present a novel strategy that corroborates common mechanistic patterns across large scale AD gene expression studies and further prioritizes potential biomarker candidates. To infer gene regulatory networks (GRNs), we applied an optimized version of the BC3Net algorithm, named BC3Net10, capable of deriving robust and coherent patterns. In principle, this approach initially leverages the power of literature knowledge to extract AD specific genes for generating viable networks. Our findings suggest that AD GRNs show significant enrichment for key signaling mechanisms involved in neurotransmission. Among the prioritized genes, well-known AD genes were prominent in synaptic transmission, implicated in cognitive deficits. Moreover, less intensive studied AD candidates (STX2, HLA-F, HLA-C, RAB11FIP4, ARAP3, AP2A2, ATP2B4, ITPR2, and ATP2A3) are also involved in neurotransmission, providing new insights into the underlying mechanism. To our knowledge, this is the first study to generate knowledge-instructed GRNs that demonstrates an effective way of combining literature-based knowledge and data-driven analysis to identify lesser known candidates embedded in stable and robust functional patterns across disparate datasets.

A functional SNP upstream of the ADRB2 gene is associated with COPD

Background

Previous studies have suggested that β2-adrenergic receptor (ADRB2) is associated with COPD. However, the role of genetic polymorphisms in ADRB2 on COPD has not been evaluated yet.

Methods

In this study, SNaPshot genotyping, luciferase assay, chromatin immunoprecipitation and real-time polymerase chain reaction were adopted to investigate the association between ADRB2 genetic polymorphisms and COPD, comprehensively.

Results

One single nucleotide polymorphism (rs12654778), located upstream of ADRB2, showed a significant association with COPD by the logistic regression analysis after adjusting for age, sex and smoking history (p=0.04) in 200 COPD patients and 222 controls from southwest Chinese population. Furthermore, the luciferase assay indicated that rs12654778-A allele reduced the relative promoter activity by ~26% compared with rs12654778-G allele (p=0.0034). The chromatin immunoprecipitation analysis demonstrated that rs12654778 modulated the binding affinity of transcription factor neurofibromin 1. In addition, a significantly reduced expression of ADRB2 in COPD patients was observed, compared with normal controls (p=0.017).

Conclusion

Our findings suggest a previously unknown mechanism linking allele-specific effects of rs12654778 on ADRB2 expression to COPD onset, for the first time.

A functional variant at the miRNA binding site in HMGB1 gene is associated with risk of oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is a common malignancy that has been causally associated with both hereditary and acquired factors. The high mobility group box 1 (HMGB1) gene plays an important role as a DNA chaperone to help maintain nuclear homeostasis. Altered expression of HMGB1 has been implicated in a wide range of pathological processes, including inflammation and cancer. The present study explores the impact of HMGB1 gene polymorphisms, combined with environmental risks regarding susceptibility to oral tumorigenesis. Four single-nucleotide polymorphisms (SNPs) of the HMGB1 gene, rs1412125, rs2249825, rs1045411, and rs1360485, were evaluated in 1,200 normal controls and 772 patients with OSCC. We found an association between the wild-type allele of rs1045411 and genotypes CT and CT/TT (AOR=0.754, 95% CI=0.582-0.978 and AOR=0.778, 95% CI=0.609-0.995, respectively). Additionally, bioinformatics analysis was used to characterize the functional relevance of these variants for the miRNA-505-5p binding site and transcriptional regulation by the HMGB1 3’-UTR and promoter regions. Moreover, in considering behavioral exposure to environmental carcinogens, the presence of the four HMGB1 SNPs, combined with/without betel quid chewing and smoking showed, profoundly synergistic effects on the risk of OSCC. In conclusion, we present a potential clinical relevance for HMGB1 variants in OSCC, as well as associations between HMGB1 polymorphisms, haplotypes and environmental risk factors. The finding may help in development of optimal therapeutic approaches for OSCC patients.

Functional genetic variant in the Kozak sequence of WW domain-containing oxidoreductase (WWOX) gene is associated with oral cancer risk

In Taiwan, oral cancer is the fourth leading cancer in males and is associated with exposure to environmental carcinogens. WW domain-containing oxidoreductase (WWOX), a tumor suppressor gene, is associated with the development of various cancers. We hypothesized that genetic variants of WWOX influence the susceptibility to oral cancer. Five polymorphisms of WWOX gene from 761 male patients with oral cancer and 1199 male cancer-free individuals were genotyped. We observed that individuals carrying the polymorphic allele of WWOX rs11545028 are more susceptible to oral cancer. Furthermore, patients with advanced-stage oral cancer were associated with a higher frequency of WWOX rs11545028 polymorphisms with the variant genotype TT than did patients with the wild-type gene. An additional integrated in silico analysis confirmed that rs11545028 affects WWOX expression, which significantly correlates with tumor expression and subsequently with tumor development and aggressiveness. In conclusion, genetic variants of WWOX contribute to the occurrence of oral cancer, and the findings regarding these biomarkers provided a prediction model for risk assessment.

Associations between novel genetic variants in the promoter region of MALAT1 and risk of colorectal cancer

The metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), a well-known long non-coding RNA, is involved in pathogenesis and progress of multiple tumors. However, no study has been performed to investigate the relationship between the genetic variants in promoter region of MALAT1 and colorectal cancer risk. In this study, we conducted a two-stage case-control study to evaluate whether MALAT1 genetic variants were associated with colorectal cancer risk. We identified that a single nucleotide polymorphism (SNP) rs1194338 was significantly associated with the decreased colorectal cancer risk with an odds ratio (OR) of 0.70 [95% confidence interval (CI) = 0.49-0.99] in the combined stage. The subsequently stratified analyses showed that the protective effect of rs1194338 was more pronounced in several subgroups. Furthermore, gene expression profiling analysis revealed overexpression of MALAT1 mRNA in colorectal cancer tissue compared with normal controls. Confirmation studies with large sample size and further mechanistic investigations into the function of MALAT1 and its genetic variants are warranted to advance our understanding of their roles in colorectal carcinogenesis, and to aid in the development of novel and targeted therapeutic strategies.

Functional genetic variant of WW domain-containing oxidoreductase (WWOX) gene is associated with hepatocellular carcinoma risk

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Human WW domain-containing oxidoreductase (WWOX) gene has been identified as a tumor suppressor gene in multiple cancers. We hypothesize that genetic variations in WWOX are associated with HCC risk.

METHODOLOGY/PRINCIPAL FINDINGS

Five single-nucleotide polymorphisms (SNPs) of the WWOX gene were evaluated from 708 normal controls and 354 patients with HCC. We identified a significant association between a WWOX single nucleotide polymorphism (SNP), rs73569323, and decreased risk of HCC. After adjustment for potential confounders, patients with at least one T allele at rs11545028 of WWOX may have a significantly smaller tumor size, reduced levels of α-fetoprotein and alanine aminotransferase (ALT). Moreover, the A allele at SNP rs12918952 in WWOX conferred higher risk of vascular invasion. Additional in silico analysis also suggests that WWOX rs12918952 polymorphism tends to affect WWOX expression, which in turn contributes to tumor vascular invasion.

CONCLUSIONS

In conclusion, genetic variations in WWOX may be a significant predictor of early HCC occurrence and a reliable biomarker for disease progression.

SnoVault and encodeD: A novel object-based storage system and applications to ENCODE metadata

The Encyclopedia of DNA elements (ENCODE) project is an ongoing collaborative effort to create a comprehensive catalog of functional elements initiated shortly after the completion of the Human Genome Project. The current database exceeds 6500 experiments across more than 450 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the H. sapiens and M. musculus genomes. All ENCODE experimental data, metadata, and associated computational analyses are submitted to the ENCODE Data Coordination Center (DCC) for validation, tracking, storage, unified processing, and distribution to community resources and the scientific community. As the volume of data increases, the identification and organization of experimental details becomes increasingly intricate and demands careful curation. The ENCODE DCC has created a general purpose software system, known as SnoVault, that supports metadata and file submission, a database used for metadata storage, web pages for displaying the metadata and a robust API for querying the metadata. The software is fully open-source, code and installation instructions can be found at: http://github.com/ENCODE-DCC/snovault/ (for the generic database) and http://github.com/ENCODE-DCC/encoded/ to store genomic data in the manner of ENCODE. The core database engine, SnoVault (which is completely independent of ENCODE, genomic data, or bioinformatic data) has been released as a separate Python package.

Serpin peptidase inhibitor (SERPINB5) haplotypes are associated with susceptibility to hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents the second leading cause of cancer-related death worldwide. The serpin peptidase inhibitor SERPINB5 is a tumour-suppressor gene that promotes the development of various cancers in humans. However, whether SERPINB5 gene variants play a role in HCC susceptibility remains unknown. In this study, we genotyped 6 SNPs of the SERPINB5 gene in an independent cohort from a replicate population comprising 302 cases and 590 controls. Additionally, patients who had at least one rs2289520 C allele in SERPINB5 tended to exhibit better liver function than patients with genotype GG (Child-Pugh grade A vs. B or C; P = 0.047). Next, haplotype blocks were reconstructed according to the linkage disequilibrium structure of the SERPINB5 gene. A haplotype “C-C-C” (rs17071138 + rs3744941 + rs8089204) in SERPINB5-correlated promoter showed a significant association with an increased HCC risk (AOR = 1.450; P = 0.031). Haplotypes “T-C-A” and “C-C-C” (rs2289519 + rs2289520 + rs1455555) located in the SERPINB5 coding region had a decreased (AOR = 0.744; P = 0.031) and increased (AOR = 1.981; P = 0.001) HCC risk, respectively. Finally, an additional integrated in silico analysis confirmed that these SNPs affected SERPINB5 expression and protein stability, which significantly correlated with tumour expression and subsequently with tumour development and aggressiveness. Taken together, our findings regarding these biomarkers provide a prediction model for risk assessment.

Regulatory polymorphisms modulate the expression of HLA class II molecules and promote autoimmunity

Targeted sequencing of sixteen SLE risk loci among 1349 Caucasian cases and controls produced a comprehensive dataset of the variations causing susceptibility to systemic lupus erythematosus (SLE). Two independent disease association signals in the HLA-D region identified two regulatory regions containing 3562 polymorphisms that modified thirty-seven transcription factor binding sites. These extensive functional variations are a new and potent facet of HLA polymorphism. Variations modifying the consensus binding motifs of IRF4 and CTCF in the XL9 regulatory complex modified the transcription of HLA-DRB1, HLA-DQA1 and HLA-DQB1 in a chromosome-specific manner, resulting in a 2.5-fold increase in the surface expression of HLA-DR and DQ molecules on dendritic cells with SLE risk genotypes, which increases to over 4-fold after stimulation. Similar analyses of fifteen other SLE risk loci identified 1206 functional variants tightly linked with disease-associated SNPs and demonstrated that common disease alleles contain multiple causal variants modulating multiple immune system genes.