Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in hearing loss.

Hearing loss is one of the top contributors to years lived with disability and is a risk factor for dementia. Molecular evidence on the cellular origins of hearing loss in humans is growing. Here, we performed a genome-wide association meta-analysis of clinically diagnosed and self-reported hearing impairment on 723,266 individuals and identified 48 significant loci, 10 of which are novel. A large proportion of associations comprised missense variants, half of which lie within known familial hearing loss loci. We used single-cell RNA-sequencing data from mouse cochlea and brain and mapped common-variant genomic results to spindle, root, and basal cells from the stria vascularis, a structure in the cochlea necessary for normal hearing. Our findings indicate the importance of the stria vascularis in the mechanism of hearing impairment, providing future paths for developing targets for therapeutic intervention in hearing loss.

Understanding the complex genetic architecture connecting rheumatoid arthritis, osteoporosis and inflammation: discovering causal pathways.

Rheumatoid arthritis (RA) and osteoporosis (OP) are two comorbid complex inflammatory conditions with evidence of shared genetic background and causal relationships. We aimed to clarify the genetic architecture underlying RA and various OP phenotypes while additionally considering an inflammatory component, C-reactive protein (CRP). Genome-wide association study summary statistics were acquired from the GEnetic Factors for OSteoporosis Consortium, Cohorts for Heart and Aging Research Consortium and UK Biobank. Mendelian randomization (MR) was used to detect the presence of causal relationships. Colocalization analysis was performed to determine shared genetic variants between CRP and OP phenotypes. Analysis of pleiotropy between traits owing to shared causal single nucleotide polymorphisms (SNPs) was performed using PL eiotropic A nalysis under CO mposite null hypothesis (PLACO). MR analysis was suggestive of horizontal pleiotropy between RA and OP traits. RA was a significant causal risk factor for CRP (ß = 0.027, 95% confidence interval = 0.016-0.038). There was no evidence of CRP→OP causal relationship, but horizontal pleiotropy was apparent. Colocalization established shared genomic regions between CRP and OP, including GCKR and SERPINA1 genes. Pleiotropy arising from shared causal SNPs revealed through the colocalization analysis was all confirmed by PLACO. These genes were found to be involved in the same molecular function 'protein binding' (GO:0005515) associated with RA, OP and CRP. We identified three major components explaining the epidemiological relationship among RA, OP and inflammation: (1) Pleiotropy explains a portion of the shared genetic relationship between RA and OP, albeit polygenically; (2) RA contributes to CRP elevation and (3) CRP, which is influenced by RA, demonstrated pleiotropy with OP.

Deviation from baseline mutation burden provides powerful and robust rare-variants association test for complex diseases.

Identifying rare variants that contribute to complex diseases is challenging because of the low statistical power in current tests comparing cases with controls. Here, we propose a novel and powerful rare variants association test based on the deviation of the observed mutation burden of a gene in cases from a baseline predicted by a weighted recursive truncated negative-binomial regression (RUNNER) on genomic features available from public data. Simulation studies show that RUNNER is substantially more powerful than state-of-the-art rare variant association tests and has reasonable type 1 error rates even for stratified populations or in small samples. Applied to real case-control data, RUNNER recapitulates known genes of Hirschsprung disease and Alzheimer's disease missed by current methods and detects promising new candidate genes for both disorders. In a case-only study, RUNNER successfully detected a known causal gene of amyotrophic lateral sclerosis. The present study provides a powerful and robust method to identify susceptibility genes with rare risk variants for complex diseases.

Relationships between Circulating Biomarkers and Body Composition Parameters in Patients with Metabolic Syndrome: A Community-Based Study.

Metabolic syndrome (MetS) is a complex disease involving multiple physiological, biochemical, and metabolic abnormalities. The search for reliable biomarkers may help to better elucidate its pathogenesis and develop new preventive and therapeutic strategies. In the present population-based study, we looked for biomarkers of MetS among obesity- and inflammation-related circulating factors and body composition parameters in 1079 individuals (with age range between 18 and 80) belonging to an ethnically homogeneous population. Plasma levels of soluble markers were measured by using ELISA. Body composition parameters were assessed using bioimpedance analysis (BIA). Statistical analysis, including mixed-effects regression, with MetS as a dependent variable, revealed that the most significant independent variables were mainly adipose tissue-related phenotypes, including fat mass/weight (FM/WT) [OR (95% CI)], 2.77 (2.01-3.81); leptin/adiponectin ratio (L/A ratio), 1.50 (1.23-1.83); growth and differentiation factor 15 (GDF-15) levels, 1.32 (1.08-1.62); inflammatory markers, specifically monocyte to high-density lipoprotein cholesterol ratio (MHR), 2.53 (2.00-3.15), and a few others. Additive Bayesian network modeling suggests that age, sex, MHR, and FM/WT are directly associated with MetS and probably affect its manifestation. Additionally, MetS may be causing the GDF-15 and L/A ratio. Our novel findings suggest the existence of complex, age-related, and possibly hierarchical relationships between MetS and factors associated with obesity.

Glycoprotein Acetyls Is a Novel Biomarker Predicting Cardiovascular Complications in Rheumatoid Arthritis.

The relationship between rheumatoid arthritis (RA) and early onset atherosclerosis is well depicted, each with an important inflammatory component. Glycoprotein acetyls (GlycA), a novel biomarker of inflammation, may play a role in the manifestation of these two inflammatory conditions. The present study examined a potential mediating role of GlycA within the RA-atherosclerosis relationship to determine whether it accounts for the excess risk of cardiovascular disease over that posed by lipid risk factors. The UK Biobank dataset was acquired to establish associations among RA, atherosclerosis, GlycA, and major lipid factors: total cholesterol (TC), high- and low-density lipoprotein (HDL, LDL) cholesterol, and triglycerides (TGs). Genome-wide association study summary statistics were collected from various resources to perform genetic analyses. Causality among variables was tested using Mendelian Randomization (MR) analysis. Genes of interest were identified using colocalization analysis and gene enrichment analysis. MR results appeared to indicate that the genetic relationship between GlycA and RA and also between RA and atherosclerosis was explained by horizontal pleiotropy (p-value = 0.001 and <0.001, respectively), while GlycA may causally predict atherosclerosis (p-value = 0.017). Colocalization analysis revealed several functionally relevant genes shared between GlycA and all the variables assessed. Two loci were apparent in all relationships tested and included the HLA region as well as SLC22A1. GlycA appears to mediate the RA-atherosclerosis relationship through several possible pathways. GlycA, although pleiotropically related to RA, appears to causally predict atherosclerosis. Thus, GlycA is suggested as a significant factor in the etiology of atherosclerosis development in RA.

Genetic and environmental correlational structure among metabolic syndrome endophenotypes.

Metabolic syndrome (MetS) is diagnosed by the presence of high scores on three or more metabolic traits, including systolic and diastolic blood pressure (SBP, DBP), glucose and insulin levels, cholesterol and triglyceride (TG) levels, and central obesity. A diagnosis of MetS is associated with increased risk of cardiovascular disease and type 2 diabetes. The components of MetS have long been demonstrated to have substantial genetic components, but their genetic overlap is less well understood. The present paper takes a multi-prong approach to examining the extent of this genetic overlap. This includes the quantitative genetic and additive Bayesian network modeling of the large TwinsUK project and examination of the results of genome-wide association study (GWAS) of UK Biobank data through use of LD score regression and examination of the number of genes and pathways identified in the GWASes which overlap across MetS traits. Results demonstrate a modest genetic overlap, and the genetic correlations obtained from TwinsUK and UK Biobank are nearly identical. However, these correlations imply more genetic dissimilarity than similarity. Furthermore, examination of the extent of overlap in significant GWAS hits, both at the gene and pathway level, again demonstrates only modest but significant genetic overlap. This lends support to the idea that in clinical treatment of MetS, treating each of the components individually may be an important way to address MetS.

Potential role of regulatory DNA variants in modifying the risk of severe cutaneous reactions induced by aromatic anti-seizure medications.

OBJECTIVE: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are severe cutaneous adverse drug reactions. Antiseizure medications (ASMs) with aromatic ring structure, including carbamazepine, are among the most common culprits. Screening for human leukocyte antigen (HLA) allele HLA-B*15:02 is recommended prior to initiating treatment with carbamazepine in Asians, but this allele has low positive predictive value. METHODS: We performed whole genome sequencing and analyzed 6 199 696 common variants among 113 aromatic ASM-induced SJS/TEN cases and 84 tolerant controls of Han Chinese ethnicity. RESULTS: In the primary analysis, nine variants reached genome-wide significance (p < 5e-08), one in the carbamazepine subanalysis (85 cases vs. 77 controls) and a further eight identified in HLA-B*15:02-negative subanalysis (35 cases and 53 controls). Interaction analysis between each novel variant from the primary analysis found that five increased risk irrespective of HLA-B*15:02 status or zygosity. HLA-B*15:02-positive individuals were found to have reduced risk if they also carried a chromosome 12 variant, chr12.9426934 (heterozygotes: relative risk = .71, p = .001; homozygotes: relative risk = .23, p < .001). All significant variants lie within intronic or intergenic regions with poorly understood functional consequence. In silico functional analysis of suggestive variants (p < 5e-6) identified through the primary and subanalyses (stratified by HLA-B*15:02 status and drug exposure) suggests that genetic variation within regulatory DNA may contribute to risk indirectly by disrupting the regulation of pathology-related genes. The genes implicated were specific either to the primary analysis (CD9), HLA-B*15:02 carriers (DOCK10), noncarriers (ABCA1), carbamazepine exposure (HLA-E), or phenytoin exposure (CD24). SIGNIFICANCE: We identified variants that could explain why some carriers of HLA-B*15:02 tolerate treatment, and why some noncarriers develop ASM-induced SJS/TEN. Additionally, this analysis suggests that the mixing of HLA-B*15:02 carrier status in previous studies might have masked variants contributing to susceptibility, and that inheritance of risk for ASM-induced SJS/TEN is complex, likely involving multiple risk variants.

Revealing antibiotic cross-resistance patterns in hospitalized patients through Bayesian network modelling.

OBJECTIVES: Microbial resistance exhibits dependency patterns between different antibiotics, termed cross-resistance and collateral sensitivity. These patterns differ between experimental and clinical settings. It is unclear whether the differences result from biological reasons or from confounding, biasing results found in clinical settings. We set out to elucidate the underlying dependency patterns between resistance to different antibiotics from clinical data, while accounting for patient characteristics and previous antibiotic usage. METHODS: Additive Bayesian network modelling was employed to simultaneously estimate relationships between variables in a dataset of bacterial cultures derived from hospitalized patients and tested for resistance to multiple antibiotics. Data contained resistance results, patient demographics and previous antibiotic usage, for five bacterial species: Escherichia coli (n = 1054), Klebsiella pneumoniae (n = 664), Pseudomonas aeruginosa (n = 571), CoNS (n = 495) and Proteus mirabilis (n = 415). RESULTS: All links between resistance to the various antibiotics were positive. Multiple direct links between resistance of antibiotics from different classes were observed across bacterial species. For example, resistance to gentamicin in E. coli was directly linked with resistance to ciprofloxacin (OR = 8.39, 95% credible interval 5.58-13.30) and sulfamethoxazole/trimethoprim (OR = 2.95, 95% credible interval 1.97-4.51). In addition, resistance to various antibiotics was directly linked with previous antibiotic usage. CONCLUSIONS: Robust relationships among resistance to antibiotics belonging to different classes, as well as resistance being linked to having taken antibiotics of a different class, exist even when taking into account multiple covariate dependencies. These relationships could help inform choices of antibiotic treatment in clinical settings.

De novo mutations in Caudal Type Homeo Box transcription Factor 2 (CDX2) in patients with persistent cloaca.

The cloaca is an embryonic cavity that is divided into the urogenital sinus and rectum upon differentiation of the cloacal epithelium triggered by tissue-specific transcription factors including CDX2. Defective differentiation leads to persistent cloaca in humans (PC), a phenotype recapitulated in Cdx2 mutant mice. PC is linked to hypo/hyper-vitaminosis A. Although no gene has ever been identified, there is a strong evidence for a genetic contribution to PC. We applied whole-exome sequencing and copy-number-variants analyses to 21 PC patients and their unaffected parents. The damaging p.Cys132* and p.Arg237His de novo CDX2 variants were identified in two patients. These variants altered the expression of CYP26A1, a direct CDX2 target encoding the major retinoic acid (RA)-degrading enzyme. Other RA genes, including the RA-receptor alpha, were also mutated. Genes governing the development of cloaca-derived structures were recurrently mutated and over-represented in the basement-membrane components set (q-value < 1.65 × 10-6). Joint analysis of the patients' profile highlighted the extracellular matrix-receptor interaction pathway (MsigDBID: M7098, FDR: q-value < 7.16 × 10-9). This is the first evidence that PC is genetic, with genes involved in the RA metabolism at the lead. Given the CDX2 de novo variants and the role of RA, our observations could potentiate preventive measures. For the first time, a gene recapitulating PC in mouse models is found mutated in humans.

The Genes We Inherit and Those We Don't: Maternal Genetic Nurture and Child BMI Trajectories.

Recently, methods have been introduced using polygenic scores (PGS) to estimate the effects of genetic nurture, the environmentally-mediated effects of parental genotypes on the phenotype of their child above and beyond the effects of the alleles which are transmitted to the child. We introduce a simplified model for estimating genetic nurture effects and show, through simulation and analytical derivation, that our method provides unbiased estimates and offers an increase in power to detect genetic nurture of up to 1/3 greater than that of previous methods. Subsequently, we apply this method to data from the Avon Longitudinal Study of Parents and Children to estimate the effects of maternal genetic nurture on childhood body mass index (BMI) trajectories. Through mixed modeling, we observe a statistically significant age-dependent effect of maternal PGS on child BMI, such that the influence of maternal genetic nurture appears to increase throughout development.

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways.

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

Statistical Power and the Classical Twin Design.

Dr Nick Martin has made enormous contributions to the field of behavior genetics over the past 50 years. Of his many seminal papers that have had a profound impact, we focus on his early work on the power of twin studies. He was among the first to recognize the importance of sample size calculation before conducting a study to ensure sufficient power to detect the effects of interest. The elegant approach he developed, based on the noncentral chi-squared distribution, has been adopted by subsequent researchers for other genetic study designs, and today remains a standard tool for power calculations in structural equation modeling and other areas of statistical analysis. The present brief article discusses the main aspects of his seminal paper, and how it led to subsequent developments, by him and others, as the field of behavior genetics evolved into the present era.

Trans-ethnic meta-analysis of genome-wide association studies for Hirschsprung disease.

Hirschsprung disease (HSCR) is the most common cause of neonatal intestinal obstruction. It is characterized by the absence of ganglia in the nerve plexuses of the lower gastrointestinal tract. So far, three common disease-susceptibility variants at the RET, SEMA3 and NRG1 loci have been detected through genome-wide association studies (GWAS) in Europeans and Asians to understand its genetic etiologies. Here we present a trans-ethnic meta-analysis of 507 HSCR cases and 1191 controls, combining all published GWAS results on HSCR to fine-map these loci and narrow down the putatively causal variants to 99% credible sets. We also demonstrate that the effects of RET and NRG1 are universal across European and Asian ancestries. In contrast, we detected a European-specific association of a low-frequency variant, rs80227144, in SEMA3 [odds ratio (OR) = 5.2, P = 4.7 × 10-10]. Conditional analyses on the lead SNPs revealed a secondary association signal, corresponding to an Asian-specific, low-frequency missense variant encoding RET p.Asp489Asn (rs9282834, conditional OR = 20.3, conditional P = 4.1 × 10-14). When in trans with the RET intron 1 enhancer risk allele, rs9282834 increases the risk of HSCR from 1.1 to 26.7. Overall, our study provides further insights into the genetic architecture of HSCR and has profound implications for future study designs.

Actionable secondary findings from whole-genome sequencing of 954 East Asians.

Recently, the American College of Medical Genetics (ACMG) recommended the return of actionable secondary findings detected from clinical sequencing. The reported frequency of secondary findings in Asian populations were highly variable and it is unclear whether the uniformity in coverage offered by whole-genome sequencing (WGS) may impact the estimate. In this analysis, we aimed to refine the rate of secondary findings on East Asians through a large-scale WGS study. We classified 1256 protein-altering or splicing variants of the 59 actionable genes detected from WGS of 954 East Asians in strict accordance with the ACMG and the Association for Molecular Pathology guidelines. A total of 21 pathogenic or likely pathogenic variants were detected in 24 of the 954 East Asian genomes with an estimate of 2.5% of East Asians carrying actionable variants. Although the overall estimate of secondary findings was consistent with those reported for non-East Asian ethnicities, genetic and allelic heterogeneity was observed. WGS offers a wider breadth of coverage over WES, which highlights the need to further investigate the variable sensitivity of WES and WGS in the detection of secondary findings. Identifying secondary findings in populations underrepresented in previous genetic literature might improve variant interpretation and has a profound impact on local decision-making with regard to the cost-effectiveness of returning the secondary findings from clinical sequencing.

Genetic overlap between epilepsy and schizophrenia: Evidence from cross phenotype analysis in Hong Kong Chinese population.

Epilepsy and schizophrenia are common and typical neurological or mental illness respectively, and sometimes they comorbid in the same patients, however the underlying genetic relationship between the two brain diseases is still not fully understood. To investigate the possible genetic contribution to their comorbidity, we performed polygenic risk score (PRS) analyses and genetic correlation estimation so as to identify the overall genetic overlap between the two diseases. The global schizophrenia PRS is strongly associated with schizophrenia phenotype in Hong Kong population (odds ratio = 1.7, p = 2.26E-16), and focal epilepsy PRS is moderately associated with epilepsy phenotype in Hong Kong population (odds ratio = 1.14, p = 0.013). However the disease-specific PRS can only predict its own well-matched phenotype but not the other ones (p > 0.05). This pattern is further supported by non-significant pairwise genetic correlation and insufficient statistical power for PRS association from the cross-phenotype analyses. Our study reveals there's limited shared genetic aetiology between schizophrenia and epilepsy, and thus supports a model of shared environmental factors to explain the comorbidity between the two phenotypes.

Exome-chip association analysis reveals an Asian-specific missense variant in PAX4 associated with type 2 diabetes in Chinese individuals.

AIMS/HYPOTHESIS: Genome-wide association studies (GWASs) have identified many common type 2 diabetes-associated variants, mostly at the intronic or intergenic regions. Recent advancements of exome-array genotyping platforms have opened up a novel means for detecting the associations of low-frequency or rare coding variants with type 2 diabetes. We conducted an exomechip association analysis to identify additional type 2 diabetes susceptibility variants in the Chinese population. METHODS: An exome-chip association study was conducted by genotyping 5640 Chinese individuals from Hong Kong, using a custom designed exome array, the Asian Exomechip. Single variant association analysis was conducted on 77,468 single nucleotide polymorphisms (SNPs). Fifteen SNPs were subsequently genotyped for replication analysis in an independent Chinese cohort comprising 12,362 individuals from Guangzhou. A combined analysis involving 7189 cases and 10,813 controls was performed. RESULTS: In the discovery stage, an Asian-specific coding variant rs2233580 (p.Arg192His) in PAX4, and two variants at the known loci, CDKN2B-AS1 and KCNQ1, were significantly associated with type 2 diabetes with exome-wide significance (p discovery < 6.45 × 10-7). The risk allele (T) of PAX4 rs2233580 was associated with a younger age at diabetes diagnosis. This variant was replicated in an independent cohort and demonstrated a stronger association that reached genome-wide significance (p meta-analysis [p meta] = 3.74 × 10-15) in the combined analysis. CONCLUSIONS/INTERPRETATION: We identified the association of a PAX4 Asian-specific missense variant rs2233580 with type 2 diabetes in an exome-chip association analysis, supporting the involvement of PAX4 in the pathogenesis of type 2 diabetes. Our findings suggest PAX4 is a possible effector gene of the 7q32 locus, previously identified from GWAS in Asians.

Meta-analysis of GWAS on two Chinese populations followed by replication identifies novel genetic variants on the X chromosome associated with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a prototypic autoimmune disease that affects mainly females. What role the X chromosome plays in the disease has always been an intriguing question. In this study, we examined the genetic variants on the X chromosome through meta-analysis of two genome-wide association studies (GWAS) on SLE on Chinese Han populations. Prominent association signals from the meta-analysis were replicated in 4 additional Asian cohorts, with a total of 5373 cases and 9166 matched controls. We identified a novel variant in PRPS2 on Xp22.3 as associated with SLE with genome-wide significance (rs7062536, OR = 0.84, P = 1.00E-08). Association of the L1CAM-MECP2 region with SLE was reported previously. In this study, we identified independent contributors in this region in NAA10 (rs2071128, OR = 0.81, P = 2.19E-13) and TMEM187 (rs17422, OR = 0.75, P = 1.47E-15), in addition to replicating the association from IRAK1-MECP2 region (rs1059702, OR = 0.71, P = 2.40E-18) in Asian cohorts. The X-linked susceptibility variants showed higher effect size in males than that in females, similar to results from a genome-wide survey of associated SNPs on the autosomes. These results suggest that susceptibility genes identified on the X chromosome, while contributing to disease predisposition, might not contribute significantly to the female predominance of this prototype autoimmune disease.

Three SNPs in chromosome 11q23.3 are independently associated with systemic lupus erythematosus in Asians.

Systemic lupus erythematosus (SLE) has a complex etiology and is affected by both genetic and environmental factors. Although more than 40 loci have shown robust association with SLE, the details of these loci, such as the independent contributors and the genes involved, are still unclear. In this study, we performed meta-analysis of two existing genome-wide association studies (GWASs) on Chinese Han populations from Hong Kong and Anhui, China, and followed the findings by further replication on three additional Chinese and Thailand cohorts with a total of 4254 cases and 6262 controls matched geographically and ethnically. We discovered multiple susceptibility variants for SLE in the 11q23.3 region, including variants in/near PHLDB1 (rs11603023, P(_combined) = 1.25E-08, OR = 1.20), DDX6 (rs638893, P(_combined) = 5.19E-07, OR = 1.22) and CXCR5 (rs10892301, P(_combined) = 2.51E-08, OR = 0.85). Genetic contributions from the newly identified variants were all independent of SNP rs4639966, whose association was reported from the previous GWAS. In addition, the three newly identified variants all showed independent association with the disease through modeling by both stepwise and conditional logistic regression. The presence of multiple independent variants in this region emphasizes its role in SLE susceptibility, and also hints the possibility that distinct biological mechanisms might be involved in the disease involving this genomic region.

Novel pre-mRNA splicing of intronically integrated HBV generates oncogenic chimera in hepatocellular carcinoma.

BACKGROUND & AIMS: Hepatitis B virus (HBV) integration is common in HBV-associated hepatocellular carcinoma (HCC) and may play an important pathogenic role through the production of chimeric HBV-human transcripts. We aimed to screen the transcriptome for HBV integrations in HCCs. METHODS: Transcriptome sequencing was performed on paired HBV-associated HCCs and corresponding non-tumorous liver tissues to identify viral-human chimeric sites. Validation was further performed in an expanded cohort of human HCCs. RESULTS: Here we report the discovery of a novel pre-mRNA splicing mechanism in generating HBV-human chimeric protein. This mechanism was exemplified by the formation of a recurrent HBV-cyclin A2 (CCNA2) chimeric transcript (A2S), as detected in 12.5% (6 of 48) of HCC patients, but in none of the 22 non-HCC HBV-associated cirrhotic liver samples examined. Upon the integration of HBV into the intron of the CCNA2 gene, the mammalian splicing machinery utilized the foreign splice sites at 282nt. and 458nt. of the HBV genome to generate a pseudo-exon, forming an in-frame chimeric fusion with CCNA2. The A2S chimeric protein gained a non-degradable property and promoted cell cycle progression, demonstrating its potential oncogenic functions. CONCLUSIONS: A pre-mRNA splicing mechanism is involved in the formation of HBV-human chimeric proteins. This represents a novel and possibly common mechanism underlying the formation of HBV-human chimeric transcripts from intronically integrated HBV genome with functional impact. LAY SUMMARY: HBV is involved in the mammalian pre-mRNA splicing machinery in the generation of potential tumorigenic HBV-human chimeras. This study also provided insight on the impact of intronic HBV integration with the gain of splice sites in the development of HBV-associated HCC.