Human genetics. GTEx detects genetic effects

LncRNA Recognition-Associated CpG Island Detection and Methylation Analysis

CpG islands (CGIs) are rare, interspersed DNA sequences, which possess a significant deviation from background genomic distribution by exhibiting patterns of GC-rich and CpG-rich sequence, the density of which provides a good classification feature for long noncoding RNA (lncRNA) promoters. By reviewing previous CpG-related studies, we consider that the transcription regulation of about half of the human genes, mostly housekeeping (HK) genes, involves CGIs, their methylation states, CpG spacing, and other chromosomal parameters. However, the precise CGI definition and positioning of CGIs within gene structures, as well as specific CGI-associated regulatory mechanisms, all remain to be elucidated at individual gene and gene family levels, together with consideration of species and lineage specificity. Although previous studies have already classified CGIs into high-CpG (HCGI), intermediate-CpG (ICGI), and low-CpG (LCGI) densities based on CpG density variation, the correlation between CGI density and gene expression regulation, such as co-regulation of CGIs and TATA-box on HK genes, is not clear. Here, we introduce such a problem-solving protocol for human genome annotation, which is based on a combination of GTEx, JBLA, and GO analysis. Next, we discuss why CGI-associated genes are most likely regulated by HCGI and tend to be HK genes; The HCGI/TATA± and LCGI/TATA± combinations show different GO enrichment, whereas the ICGI/TATA± combination is less characteristic than LCGI/TATA± based on GO enrichment analysis.

Tensor decomposition reveals trans-regulated gene modules in maize drought response

When plants respond to drought stress, dynamic cellular changes occur, accompanied by alterations in gene expression, which often act through trans-regulation. However, the detection of trans-acting genetic variants and networks of genes is challenged by the large number of genes and markers. Using a tensor decomposition method, we identify trans-acting expression quantitative trait loci (trans-eQTLs) linked to gene modules, rather than individual genes, which were associated with maize drought response. Module-to-trait association analysis demonstrates that half of the modules are relevant to drought-related traits. Genome-wide association studies of the expression patterns of each module identify 286 trans-eQTLs linked to drought-responsive modules, the majority of which cannot be detected based on individual gene expression. Notably, the trans-eQTLs located in the regions selected during maize improvement tend towards relatively strong selection. We further prioritize the genes that affect the transcriptional regulation of multiple genes in trans, as exemplified by two transcription factor genes. Our analyses highlight that multidimensional reduction could facilitate the identification of trans-acting variations in gene expression in response to dynamic environments and serve as a promising technique for high-order data processing in future crop breeding.

TNS1 and NRXN1 Genes Interacting With Early-Life Smoking Exposure in Asthma-Plus-Eczema Susceptibility

PURPOSE

Numerous genes have been associated with allergic diseases (asthma, allergic rhinitis, and eczema), but they explain only part of their heritability. This is partly because most previous studies ignored complex mechanisms such as gene-environment (G-E) interactions and complex phenotypes such as co-morbidity. However, it was recently evidenced that the co-morbidity of asthma-plus-eczema appears as a sub-entity depending on specific genetic factors. Besides, evidence also suggest that gene-by-early life environmental tobacco smoke (ETS) exposure interactions play a role in asthma, but were never investigated for asthma-plus-eczema. To identify genetic variants interacting with ETS exposure that influence asthma-plus-eczema susceptibility.

METHODS

To conduct a genome-wide interaction study (GWIS) of asthma-plus-eczema according to ETS exposure, we applied a 2-stage strategy with a first selection of single nucleotide polymorphisms (SNPs) from genome-wide association meta-analysis to be tested at a second stage by interaction meta-analysis. All meta-analyses were conducted across 4 studies including a total of 5,516 European-ancestry individuals, of whom 1,164 had both asthma and eczema.

RESULTS

Two SNPs showed significant interactions with ETS exposure. They were located in 2 genes, NRXN1 (2p16) and TNS1 (2q35), never reported associated and/or interacting with ETS exposure for asthma, eczema or more generally for allergic diseases. TNS1 is a promising candidate gene because of its link to lung and skin diseases with possible interactive effect with tobacco smoke exposure.

CONCLUSIONS

This first GWIS of asthma-plus-eczema with ETS exposure underlines the importance of studying sub-phenotypes such as co-morbidities as well as G-E interactions to detect new susceptibility genes.

eNOS polymorphisms on male infertility: An updated systematic review and meta-analysis

BACKGROUND

This meta-analysis was performed to examine the association of 3 endothelial nitric oxide synthase (eNOS) gene polymorphisms with male infertility.

METHODS

The literature on the relation between the mutant of eNOS and male infertility before July 1, 2022, was conducted in Pubmed, Medline, and Web of Science. The search strategy is as follows: (eNOS OR ECNOS OR nitric oxide synthase 3 OR NOS3) AND (polymorphism OR mutation OR variation OR SNP OR genotype) AND (male infertility). Statistical analysis was performed with the web of MetaGenyo, Stata 12, trial sequential analysis 0.9Beta, and the web of GTEx.

RESULTS

Overall, 13 studies (26 case-controls) were included involving 6518 cases and 5461 controls for 3 polymorphisms (rs2070744, rs1799983, rs61722009) of eNOS. We found that eNOS rs2070744 was correlated with an increased risk of male infertility (C vs. T: odds ratio [OR], 1.48; 95% confidence interval [CI], [1.19-1.85]; CC vs. TT: OR, 2.59; 95% CI, [1.40-4.80]; CT vs. TT: OR, 1.17; 95% CI, [1.00-1.38]; CC vs. CT + TT: OR, 2.50; 95% CI, [1.35-4.62]; CC + CT vs. TT: OR, 1.41; 95% CI, [1.21-1.64]). And eNOS rs1799983 was correlated with an increased risk of male infertility (allele contrast T vs. G: OR, 1.41; 95% CI, [1.01-1.96]; P = .043; recessive model TT vs. TG + GG: OR, 2.00; 95% CI, [1.03-3.90]; P = .042). In the stratified analysis of rs61722009, we found Asians might be correlated with an increased risk of male infertility (4a vs. 4b: OR, 1.50; 95% CI, [0.94-2.38]; 4a4a vs. 4b4b: OR, 2.56; 95% CI, [0.70-9.38]; 4a4b vs. 4b4b: OR, 1.36; 95% CI, [0.87-2.13]; 4a4a vs. 4a4b + 4b4b: OR, 2.57; 95% CI, [0.91-7.30]; 4a4a + 4a4b vs. 4b4b: OR, 1.44; 95% CI, [0.87-2.40]).

CONCLUSION

The eNOS rs2070744 polymorphism and rs1799983 are associated with the risk of male infertility, and rs61722009 might be a risk factor for Asians.

Role of MDR1 Gene Polymorphisms in Human Male Infertility: A Meta-Analysis

The present meta-analysis is performed to determine the association of C1236T and C3435T polymorphisms in the MDR1 gene. Google Scholar, PubMed, and Science Direct were searched. A total of 47 studies were retrieved, of which only three case-control studies, consisting of 490 cases and 423 controls, met the selection criteria. Odds ratios (ORs) for MDR1 C1236T were as follows: Allelic model (T vs. C): OR = 1.06 [0.83, 1.35]; Additive model (TT vs. CC): OR = 0.91 [0.53, 1.56]; Dominant model (TT+CT vs. CC): OR = 0.83 [0.55, 1.24]; and Recessive model (TT vs. CT+CC): OR = 1.43 [0.95, 2.17]. However, for MDR1 C3435T: Allelic model (T vs. C): OR = 1.06 [0.83, 1.35]; Additive model (TT vs. CC): OR = 1.18 [0.75, 1.88]; Dominant model (TT+CT vs. CC): OR = 1.42 [0.99, 2.04]; and Recessive model (TT vs. CT+CC): OR = 0.90 [0.61, 1.33]. None of the four models presented a significant association of either polymorphism with the risk of infertility in men (p >.05). The present study indicates that MDR1 gene polymorphisms might not be a risk factor for male infertility. Further studies with a larger sample size are needed to be conducted to confirm the findings of the present study.

ACPY2 gene polymorphisms on cancer risk: a systematic review and meta-analysis

To provide a comprehensive account of the association of ACYP2 gene polymorphisms with susceptibility to cancer. A literature search for eligible candidate gene studies published before April 20, 2022 was conducted in the PubMed, Medline and Web of Science. The following combinations of main keywords were used: (ACYP2 OR acylphosphatase 2) AND (polymorphism OR mutation OR variation OR SNP OR genotype) AND (cancer OR tumor OR neoplasm OR malignancy OR carcinoma OR adenocarcinoma). Potential sources of heterogeneity were sought out via subgroup and sensitivity analysis. Publication bias were also estimated. Overall, a total of 10 articles with 5,230 cases and 5,086 controls for thirteen polymorphisms of ACYP2 gene were enrolled. We found that ACYP2 rs11125529, rs11896604, rs12615793, rs17045754, rs6713088, rs843645, rs843706, rs843711 and rs843752 were correlated with an increased risk of cancer. However, we found that ACYP2 rs12621038 might have less susceptibility to cancer. While for other polymorphisms, the results showed no significant association with cancer risk. ACYP2 rs11125529, rs11896604, rs12615793, rs17045754, rs6713088, rs843645, rs843706, rs843711 and rs843752 are associated with cancer risk. ACYP2 rs12621038 polymorphism is inversely associated with cancer risk.

Prognostic Implications of an Autophagy-related Gene Signature in Pancreatic Ductal Adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose and resistant to therapy and has a poor prognosis. Autophagy plays a vital role in PDAC development and progression. This study aimed to establish an autophagy-related gene (ARG) signature to predict the prognosis of patients with PDAC.

MATERIALS AND METHODS

The expression profiles of PDAC and healthy pancreatic tissues were obtained from The Cancer Genome of Atlas (TCGA) and GTEx (Genotype-Tissue Expression) databases, respectively. Univariate and multivariate Cox regression analyses were performed on differentially expressed ARGs to identify the optimal prognosis-related genes.

RESULTS

A total of 73 ARGs demonstrated significant differences in expression levels between PDAC and healthy pancreatic tissues. Several pathways that play crucial roles in biological processes were identified via enrichment analyses. Furthermore, an ARG signature was established based on overall survival-related ARGs (CASP4, BAK1, PIK3R4, CASP8, BIRC5, RPTOR, and CAPN1) using least absolute shrinkage and selection operator (LASSO) regression. Cox regression analysis confirmed that the 7-gene signature was an independent prognostic factor for patients with PDAC (P<0.001). In addition, the GSE21501 and GSE28735 datasets were used to validate the predictive value of the prognostic model for PDAC. We also constructed a clinical nomogram with a concordance index of 0.712 to predict the overall survival of patients by integrating clinical characteristics and the ARG signature. Calibration curves substantiated fine concordance between nomogram prediction and actual observation.

CONCLUSION

We constructed a new ARG-related prognostic model, which can be a prognostic biomarker and offers insights into identifying potential therapeutic targets for PDAC.

Association of genetic variants of FBXO32 and FOXO6 in the FOXO pathway with breast cancer risk

Forkhead box class O (FOXO) transcription factors play a pivotal role in regulating a variety of biological processes, including organismal development, cell signaling, cell metabolism, and tumorigenesis. Therefore, we hypothesize that genetic variants in FOXO pathway genes are associated with breast cancer (BC) risk. To test this hypothesis, we conducted a large meta-analysis using 14 published genome-wide association study (GWAS) data sets in the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) study. We assessed associations between 5214 (365 genotyped in DRIVE and 4849 imputed) common single-nucleotide polymorphisms (SNPs) in 55 FOXO pathway genes and BC risk. After multiple comparison corrections by the Bayesian false-discovery probability method, we found five SNPs to be significantly associated with BC risk. In stepwise multivariate logistic regression analysis with adjustment for age, principal components, and previously published SNPs in the same data set, three independent SNPs (i.e., FBXO32 rs10093411 A>G, FOXO6 rs61229336 C>T, and FBXO32 rs62521280 C>T) remained to be significantly associated with BC risk (p = 0.0008, 0.0011, and 0.0017, respectively). Additional expression quantitative trait loci analysis revealed that the FBXO32 rs62521280 T allele was associated with decreased messenger RNA (mRNA) expression levels in breast tissue, while the FOXO6 rs61229336 T allele was found to be associated with decreased mRNA expression levels in the whole blood cells. Once replicated by other investigators, these genetic variants may serve as new biomarkers for BC risk.

Identification of OCA2 as a novel locus for the co-morbidity of asthma-plus-eczema

BACKGROUND

Numerous genes have been associated with the three most common allergic diseases (asthma, allergic rhinitis or eczema) but these genes explain only a part of the heritability. In the vast majority of genetic studies, complex phenotypes such as co-morbidity of two of these diseases, have not been considered. This may partly explain missing heritability.

OBJECTIVE

To identify genetic variants specifically associated with the co-morbidity of asthma-plus-eczema.

METHODS

We first conducted a meta-analysis of four GWAS (Genome-Wide Association Study) of the combined asthma-plus-eczema phenotype (total of 8807 European-ancestry subjects of whom 1208 subjects had both asthma and eczema). To assess whether the association with SNP(s) was specific to the co-morbidity, we also conducted a meta-analysis of homogeneity test of association according to disease status ("asthma-plus-eczema" vs. the presence of only one disease "asthma only or eczema only"). We then used a joint test by combining the two test statistics from the co-morbidity-SNP association and the phenotypic heterogeneity of SNP effect meta-analyses.

RESULTS

Seven SNPs were detected for specific association to the asthma-plus-eczema co-morbidity, two with significant and five with suggestive evidence using the joint test after correction for multiple testing. The two significant SNPs are located in the OCA2 gene (Oculocutaneous Albinism II), a new locus never detected for significant evidence of association with any allergic disease. This gene is a promising candidate gene, because of its link to skin and lung diseases, and to epithelial barrier and immune mechanisms.

CONCLUSION

Our study underlines the importance of studying sub-phenotypes as co-morbidities to detect new susceptibility genes.

Assessing the Function of the ZFP90 Variant rs1170426 in SLE and the Association Between SLE Drug Target and Susceptibility Genes

A genome-wide association study (GWAS) has discovered that a polymorphism in the ZFP90 gene is associated with systemic lupus erythematosus (SLE). In this study, we explored the candidate function of a ZFP90 variant (rs1170426) in the context of SLE and detected the relationship between SLE susceptible genes and SLE drug target genes. First, we investigated the regulatory role of rs1170426 on ZFP90 expression by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells (PBMCs), T, B, and monocytes cells and annotated the regulatory function of rs1170426 using bioinformatic databases. Second, we compared the case-control difference in ZFP90 expression levels. Third, we analyzed the association of genotype and ZFP90 expression levels with SLE clinical characters. Last, we showed the interaction of SLE susceptibility genes with SLE drug target genes. Subjects with the risk allele “C” of rs1170426 had lower expression levels of ZFP90 in PBMCs (P = 0.006) and CD8+ T cells (P = 0.003) from controls. SLE cases also had lower expression levels compared with controls (P = 2.78E-9). After correction for multiple testing, the ZFP90 expression levels were related to serositis (FDR p = 0.004), arthritis (FDR p = 0.020), hematological involvement (FDR p = 0.021), and increased C-reactive protein (CRP) (FDR p = 0.005) in cases. Furthermore, the SLE susceptible genes and the recognized SLE drug target genes were more likely to act upon each other compared with non-SLE genetic genes (OR = 2.701, P = 1.80E-5). These findings suggest that ZFP90 might play a role in the pathogenesis of SLE, and SLE genetics would contribute to therapeutic drug discovery.

Secondary Genome-Wide Association Study Using Novel Analytical Strategies Disentangle Genetic Components of Cleft Lip and/or Cleft Palate in 1q32.2

Orofacial cleft (OFC) is one of the most prevalent birth defects, leading to substantial and long-term burdens in a newborn's quality of life. Although studies revealed several genetic variants associated with the birth defect, novel approaches may provide additional clues about its etiology. Using the Center for Craniofacial and Dental Genetics project data (n = 10,542), we performed linear mixed-model analyses to study the genetic compositions of OFC and investigated the dependence among identified loci using conditional analyses. To identify genes associated with OFC, we conducted a transcriptome-wide association study (TWAS) based on predicted expression levels. In addition to confirming the previous findings at four loci, 1q32.2, 8q24, 2p24.2 and 17p13.1, we untwined two independent loci at 1q32.2, TRAF3IP3 and IRF6. The sentinel SNP in TRAF3IP3 (rs2235370, p-value = 5.15 × 10^-9) was independent of the sentinel SNP at IRF6 (rs2235373, r² < 0.3). We found that the IRF6 effect became nonsignificant once the 8q24 effect was conditioned, while the TRAF3IP3 effect remained significant. Furthermore, we identified nine genes associated with OFC in TWAS, implicating a glutathione synthesis and drug detoxification pathway. We identified some meaningful additions to the OFC etiology using novel statistical methods in the existing data.

PreMedKB: an integrated precision medicine knowledgebase for interpreting relationships between diseases, genes, variants and drugs

One important aspect of precision medicine aims to deliver the right medicine to the right patient at the right dose at the right time based on the unique ‘omics’ features of each individual patient, thus maximizing drug efficacy and minimizing adverse drug reactions. However, fragmentation and heterogeneity of available data makes it challenging to readily obtain first-hand information regarding some particular diseases, drugs, genes and variants of interest. Therefore, we developed the Precision Medicine Knowledgebase (PreMedKB) by seamlessly integrating the four fundamental components of precision medicine: diseases, genes, variants and drugs. PreMedKB allows for search of comprehensive information within each of the four components, the relationships between any two or more components, and importantly, the interpretation of the clinical meanings of a patient's genetic variants. PreMedKB is an efficient and user-friendly tool to assist researchers, clinicians or patients in interpreting a patient's genetic profile in terms of discovering potential pathogenic variants, recommending therapeutic regimens, designing panels for genetic testing kits, and matching patients for clinical trials. PreMedKB is freely accessible and available at http://www.fudan-pgx.org/premedkb/index.html#/home.

The decreased expression of IKBKE in systemic lupus erythematosus

Objective

The IKBKE has been proven to be associated with systemic lupus erythematosus (SLE) in a genome-wide association study (GWAS) conducted by our group. The objective of the recent study is to investigate the contribution of IKBKE functional variants (rs2297550) to SLE.

Methods

We detected the regulatory effect of rs2297550 on IKBKE expression by expression quantitative trait loci (eQTL) study. Then, we investigated the differences of IKBKE mRNA expression levels in peripheral blood mononuclear cells (PBMCs) between 135 SLE patients and 130 healthy controls using quantitative real-time PCR (qRT-PCR). We further analyzed the association of SLE clinical characteristics with IKBKE mRNA expression and rs2297550 polymorphisms.

Results

The results of eQTL indicated the genotype “GG” of single-nucleotide polymorphism (SNP) rs2297550 was associated with lower expression levels of IKBKE (P = 0.022) in normal controls. Compared with the healthy control group, the expression levels of IKBKE mRNA in patients with SLE were significantly decreased (P = 2.32 × 10⁻¹²). In clinical characteristics, we found that IKBKE mRNA expression levels were associated with vasculitis (P = 0.015) and increased C-reactive protein (CRP) (P = 0.021) in SLE patients.

Conclusion

In this study, we not only detected that the variant rs2297550 of IKBKE may be closely related to SLE, but also proposed functional hypotheses for the association signals.

Key Points • The rs2297550 is located in a region with transcriptional regulatory function and may regulate the expression of IKBKE via these regulatory elements. • The genotype “GG” of SNP rs2297550 was associated with lower expression levels of IKBKE. • The expression of IKBKE mRNA was decreased in SLE patients compared with healthy controls. • IKBKE contributes to the clinical characteristics of SLE.

Electronic supplementary material

The online version of this article (10.1007/s10067-020-05006-6) contains supplementary material, which is available to authorized users.

CpG-island-based annotation and analysis of human housekeeping genes

By reviewing previous CpG-related studies, we consider that the transcription regulation of about half of the human genes, mostly housekeeping (HK) genes, involves CpG islands (CGIs), their methylation states, CpG spacing and other chromosomal parameters. However, the precise CGI definition and positioning of CGIs within gene structures, as well as specific CGI-associated regulatory mechanisms, all remain to be explained at individual gene and gene-family levels, together with consideration of species and lineage specificity. Although previous studies have already classified CGIs into high-CpG (HCGI), intermediate-CpG (ICGI) and low-CpG (LCGI) densities based on CpG density variation, the correlation between CGI density and gene expression regulation, such as co-regulation of CGIs and TATA box on HK genes, remains to be elucidated. First, this study introduces such a problem-solving protocol for human-genome annotation, which is based on a combination of GTEx, JBLA and Gene Ontology (GO) analysis. Next, we discuss why CGI-associated genes are most likely regulated by HCGI and tend to be HK genes; the HCGI/TATA± and LCGI/TATA± combinations show different GO enrichment, whereas the ICGI/TATA± combination is less characteristic based on GO enrichment analysis. Finally, we demonstrate that Hadoop MapReduce-based MR-JBLA algorithm is more efficient than the original JBLA in k-mer counting and CGI-associated gene analysis.

NAT1 genetic variation increases asthma risk in children with secondhand smoke exposure

OBJECTIVE

We previously reported that children exposed to secondhand smoke (SHS) that carried variants in the NAT1 gene had over two-fold higher hair cotinine levels. Our objective was to determine if NAT1 polymorphisms confer increased risk for developing asthma in children exposed to SHS.

METHODS

White participants in the Cincinnati Childhood Allergy and Air Pollution Study (n = 359) were genotyped for 10 NAT1 variants. Smoke exposure was defined by hair cotinine and parental report. Asthma was objectively assessed by spirometry and methacholine challenge. Findings were replicated in the Genomic Control Cohort (n = 638).

RESULTS

Significant associations between 5 NAT1 variants and asthma were observed in the CCAAPS exposed group compared to none in the unexposed group. There was a significant interaction between NAT1 rs13253389 and rs4921581 with smoke exposure (p = 0.02, p = 0.01) and hair cotinine level (p = 0.048, p = 0.042). Children wildtype for rs4921581 had increasing asthma risk with increasing hair cotinine level, whereas those carrying the NAT1 minor allele had an increased risk of asthma regardless of cotinine level. In the GCC, 13 NAT1 variants were associated with asthma in the smoke-exposed group, compared to 0 in the unexposed group, demonstrating gene-level replication.

CONCLUSIONS

Variation in the NAT1 gene modifies asthma risk in children exposed to secondhand-smoke. To our knowledge, this is the first report of a gene-environment interaction between NAT1 variants, smoke exposure, cotinine levels, and pediatric asthma. NAT1 genotype may have clinical utility as a biomarker of increased asthma risk in children exposed to smoke.

What is the impact of BIRC5 gene polymorphisms on urinary cancer susceptibility? Evidence from 9348 subjects

As a member of apoptosis inhibition gene family, baculoviral IAP repeat containing 5 (BIRC5) protein acts as a survival factor in oncology through multiple ways. There are huge inconsistent results between urinary cancer risk and BIRC5 polymorphisms, so we searched and documented all eligible articles to clear up the mystery with the help of meta-analysis. According to the inclusion and exclusion criteria, we performed an overall search in Web of Science, PubMed, Google Scholar, Medline, CNKI and Wanfang database with pre-set search strategy up to November 2019. Z-test was performed to determine the statistical difference by Odds ratios (ORs) and 95% confidence intervals (CIs). The stability of the pooled ORs was conducted by one-way sensitivity analyses, Begg's funnel plots and Egger's test were employed to access the potential publication bias. The relationship of polymorphisms and BIRC5 expression was exposed by in-silico analysis, as well as the effects to tumorigenesis and prognosis. Finally, we enrolled 19 case-control studies to conducted this meta-analysis. An upgrade risk in rs9904341 of BIRC5 were revealed to be associated with urinary cancer in allele contrast model (OR = 1.222, P = 0.012), homozygote contrast model (OR = 1.579, P = 0.0001) and recessive contrast model (OR = 1.433, P < 0.001), as well as rs2071214 polymorphism in the subgroup analysis of BCa in allele contrast model (OR = 1.362, P = 0.011) and recessive contrast model (OR = 1.417, P = 0.015). On the other hand, rs17878467 variant plays an important role in prevent the tumorigenicity of urinary cancer in allele contrast model (OR = 0.672, P = 0.009), heterozygote contrast model (OR = 0.585, P = 0.006) and dominant contrast model (OR = 0.595, P = 0.004). In conclusion, we found that BIRC5 rs9904341, rs2071214 polymorphisms might cause the increased risk of urinary cancer, while rs17878467 reduces risk.

Retinal Gene Distribution and Functionality Implicated in Inherited Retinal Degenerations Can Reveal Disease-Relevant Pathways for Pharmacologic Intervention

The advent of genetic therapies for inherited retinal diseases (IRDs) has spurred the need for precise diagnosis and understanding of pathways for therapeutic targeting. The majority of IRDs that are clinically diagnosed, however, lack an identifiable mutation in established disease-causing loci and thus can be investigated with limited rational drug discovery methods. Transcriptome profiling of the retina can reveal the functional state of the tissue, and geographic profiling can uncover the various clinical phenotypic presentations of IRDs and aid in pharmaceutical intervention. In this investigation, we detail the retinal geographic expression of known retinal disease-causing genes in the primate retina and functional targetable pathways in specific IRDs. Understanding the genetic basis as well as the resulting functional consequences will assist in the discovery of future therapeutic interventions and provide novel insights to medicinal chemists. Herein, we report that, despite the genetic heterogeneity of retinal diseases, potential functional pathways can be elucidated for therapeutic targeting and be used for predictive phenotypic and genotypic modeling of novel IRD presentations.

Genetic variants of genes in the NER pathway associated with risk of breast cancer: A large-scale analysis of 14 published GWAS datasets in the DRIVE study

A recent hypothesis-free pathway-level analysis of genome-wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta-analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis-driven approach, we selected 138 candidate genes from the NER pathway using the "Molecular Signatures Database (MsigDB)" and "PathCards". All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta-analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM-ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03-1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89-0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03-1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90-0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08-1.16, p_trend < 0.0001). The eQTL analysis revealed that BIVM-ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10^-22 , respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression.

FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs

FeatSNP is an online tool and a curated database for exploring 81 million common SNPs’ potential functional impact on the human brain. FeatSNP uses the brain transcriptomes of the human population to improve functional annotation of human SNPs by integrating transcription factor binding prediction, public eQTL information, and brain specific epigenetic landscape, as well as information of Topologically Associating Domains (TADs). FeatSNP supports both single and batched SNP searching, and its interactive user interface enables users to explore the functional annotations and generate publication-quality visualization results. FeatSNP is freely available on the internet at FeatSNP.org with all major web browsers supported.

FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs

FeatSNP is an online tool and a curated database for exploring 81 million common SNPs' potential functional impact on the human brain. FeatSNP uses the brain transcriptomes of the human population to improve functional annotation of human SNPs by integrating transcription factor binding prediction, public eQTL information, and brain specific epigenetic landscape, as well as information of Topologically Associating Domains (TADs). FeatSNP supports both single and batched SNP searching, and its interactive user interface enables users to explore the functional annotations and generate publication-quality visualization results. FeatSNP is freely available on the internet at FeatSNP.org with all major web browsers supported.

Interactive effect between ATPase-related genes and early-life tobacco smoke exposure on bronchial hyper-responsiveness detected in asthma-ascertained families

BACKGROUND

A positional cloning study of bronchial hyper-responsiveness (BHR) at the 17p11 locus in the French Epidemiological study on the Genetics and Environment of Asthma (EGEA) families showed significant interaction between early-life environmental tobacco smoke (ETS) exposure and genetic variants located in DNAH9. This gene encodes the heavy chain subunit of axonemal dynein, which is involved with ATP in the motile cilia function.Our goal was to identify genetic variants at other genes interacting with ETS in BHR by investigating all genes belonging to the 'ATP-binding' and 'ATPase activity' pathways which include DNAH9, are targets of cigarette smoke and play a crucial role in the airway inflammation.

METHODS

Family-based interaction tests between ETS-exposed and unexposed BHR siblings were conducted in 388 EGEA families. Twenty single-nucleotide polymorphisms (SNP) showing interaction signals (p≤5.10^-3) were tested in the 253 Saguenay-Lac-Saint-Jean (SLSJ) families.

RESULTS

One of these SNPs was significantly replicated for interaction with ETS in SLSJ families (p=0.003). Another SNP reached the significance threshold after correction for multiple testing in the combined analysis of the two samples (p=10^-5). Results were confirmed using both a robust log-linear test and a gene-based interaction test.

CONCLUSION

The SNPs showing interaction with ETS belong to the ATP8A1 and ABCA1 genes, which play a role in the maintenance of asymmetry and homeostasis of lung membrane lipids.

Splicing heterogeneity: separating signal from noise

Single-cell analyses have revealed a tremendous variety among cells in the abundance and chemical composition of RNA. Much of this heterogeneity is due to alternative splicing by the spliceosome. Little is known about how many of the resulting isoforms are biologically functional or just provide noise with little to no impact. The dynamic nature of the spliceosome provides numerous opportunities for regulation but is also the source of stochastic fluctuations. We discuss possible origins of splicing stochasticity, the experimental approaches for studying heterogeneity in isoforms, and the potential biological significance of noisy splicing in development and disease.

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.

Genetic variants in lncRNA H19 are associated with the risk of oral squamous cell carcinoma in a Chinese population

To evaluate whether the genetic variants in H19 influence the risk of oral squamous cell carcinoma (OSCC) in a Chinese population, a case-control study was conducted to analyze four functional single nucleotide polymorphisms (SNPs) in H19. The cohort comprised of 444 OSCC cases and 984 healthy controls, and the study further evaluated the biological effect by bioinformatics prediction and functional experiments. Two SNPs, rs217727 and rs2839701, were found to be associated with the risk of OSCC [rs217727: odds ratio (OR) = 1.32, 95% confidence interval (CI) = 1.11-1.58, P = 0.002; rs2839701: OR = 1.23, 95% CI = 1.04-1.46, P = 0.019].Bioinformatics predicted that rs2839701 C>G might alter the secondary structure of H19. In addition, rs2839701 C>G inhibited the transcription activity and was correlated with the decreased expression of downstream gene MRPL23-AS1 that was downregulated in OSCC. The current results suggested that the SNPs in H19 may play a major role in genetic susceptibility to OSCC.

Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record

OBJECTIVE

To compare three groupings of Electronic Health Record (EHR) billing codes for their ability to represent clinically meaningful phenotypes and to replicate known genetic associations. The three tested coding systems were the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, the Agency for Healthcare Research and Quality Clinical Classification Software for ICD-9-CM (CCS), and manually curated "phecodes" designed to facilitate phenome-wide association studies (PheWAS) in EHRs.

METHODS AND MATERIALS

We selected 100 disease phenotypes and compared the ability of each coding system to accurately represent them without performing additional groupings. The 100 phenotypes included 25 randomly-chosen clinical phenotypes pursued in prior genome-wide association studies (GWAS) and another 75 common disease phenotypes mentioned across free-text problem lists from 189,289 individuals. We then evaluated the performance of each coding system to replicate known associations for 440 SNP-phenotype pairs.

RESULTS

Out of the 100 tested clinical phenotypes, phecodes exactly matched 83, compared to 53 for ICD-9-CM and 32 for CCS. ICD-9-CM codes were typically too detailed (requiring custom groupings) while CCS codes were often not granular enough. Among 440 tested known SNP-phenotype associations, use of phecodes replicated 153 SNP-phenotype pairs compared to 143 for ICD-9-CM and 139 for CCS. Phecodes also generally produced stronger odds ratios and lower p-values for known associations than ICD-9-CM and CCS. Finally, evaluation of several SNPs via PheWAS identified novel potential signals, some seen in only using the phecode approach. Among them, rs7318369 in PEPD was associated with gastrointestinal hemorrhage.

CONCLUSION

Our results suggest that the phecode groupings better align with clinical diseases mentioned in clinical practice or for genomic studies. ICD-9-CM, CCS, and phecode groupings all worked for PheWAS-type studies, though the phecode groupings produced superior results.

Predictive single nucleotide polymorphism markers for acute oral mucositis in patients with nasopharyngeal carcinoma treated with radiotherapy

The aim of this study was to investigate the association between the susceptibility of severe oral mucositis (OM) in Chinese nasopharyngeal carcinoma (NPC) patients treated with radiotherapy and single nucleotide polymorphisms (SNPs) across the whole genome. SNPs were screened in a total of 24 patients with NPC and an additional 6 were subjected to mRNA expression analysis. Patients were subdivided into CTC 0-2 (CTC toxicity grade 0, 1, and 2) and CTC 3+ (CTC toxicity grade 3 and above) groups according to their CTC (common toxicity criteria) scores. The GTEx dataset was used to performed eQTL analyses and in-vitro functional assays were performed for eQTL-associated genes. Our data identified 7 functional SNPs associated with the development of OM. We observed that rs11081899-A, located in the 5′-UTR of the ZNF24 gene, was significantly correlated with a higher risk of severe mucositis (OR = 14.631, 95% CI = 2.61-105.46, p = 1.2 × 10⁻⁴), and positively associated with ZNF24 mRNA expression (p = 4.1 × 10⁻⁶) from GTEx dataset. In addition, high ZNF24 mRNA expression was associated with severe OM in patients with NPC (p = 0.02). Further functional assays revealed that ZNF24 knockdown reduced p65 expression and suppressed TNF-α-induced NF-κB activation and pro-inflammatory cytokines release. These findings suggested that rs11081899-A may be a genetic susceptibility factor for radiation-induced OM in patients with NPC, although its value in clinical application needs to be further verified in a large cohort. Also, we suggested that downregulation of ZNF24 may attenuate the development of mucositis by suppressing NF-κB activation.

Genetic diagnosis of Mendelian disorders via RNA sequencing

Across a variety of Mendelian disorders, ∼50-75% of patients do not receive a genetic diagnosis by exome sequencing indicating disease-causing variants in non-coding regions. Although genome sequencing in principle reveals all genetic variants, their sizeable number and poorer annotation make prioritization challenging. Here, we demonstrate the power of transcriptome sequencing to molecularly diagnose 10% (5 of 48) of mitochondriopathy patients and identify candidate genes for the remainder. We find a median of one aberrantly expressed gene, five aberrant splicing events and six mono-allelically expressed rare variants in patient-derived fibroblasts and establish disease-causing roles for each kind. Private exons often arise from cryptic splice sites providing an important clue for variant prioritization. One such event is found in the complex I assembly factor TIMMDC1 establishing a novel disease-associated gene. In conclusion, our study expands the diagnostic tools for detecting non-exonic variants and provides examples of intronic loss-of-function variants with pathological relevance.

MDM4 genetic variants and risk of gastric cancer in an Eastern Chinese population

MDM4 is a p53-interacting protein and plays an important role in carcinogenesis. In this study of 1,077 gastric cancer (GCa) cases and 1,173 matched cancer-free controls, we investigated associations between three tagging single nucleotide polymorphisms (SNPs) (rs11801299 G>A, rs1380576 C>G and rs10900598 G>T) in MDM4 and gastric cancer risk in an Eastern Chinese Population. In logistic regression analysis, a significantly decreased GCa risk was associated with the rs1380576 GG variant genotype (adjusted odds ratio [OR] =0.74, 95% confidence interval [CI] =0.56-0.98) under a recessive model, which remained significant after correction by the false-positive reporting probability. This risk was more evident in subgroups of older subjects, males, never smokers, never drinkers and cancers of non-cardia. We then performed SNP-mRNA expression correlation analysis and found that the GG variant genotype was associated with significantly decreased expression of MDM4 mRNA in normal cell lines for 44 Chinese (P=0.032 for GG vs. CC) as well as for 269 multi-ethnic subjects (P<0.0001 for GG vs. CC). Our results suggest that the MDM4 rs1380576 G variant may be markers for GCa susceptibility. Larger, independent studies are warranted to validate our findings.

A pathway-based association study reveals variants from Wnt signalling genes contributing to asthma susceptibility

BACKGROUND

Genetic susceptibility to asthma is currently linked to a handful of genes which have a limited ability to predict the overall disease risk, suggesting the existence of many other genes involved in disease development. Accumulated evidence from association studies in genes related by biological pathways could reveal novel asthma genes.

OBJECTIVE

To reveal novel asthma susceptibility genes by means of a pathway-based association study.

METHODS

Based on summary data from a previous a genomewide association study (GWAS) of asthma, we first identified significant biological pathways using a gene-set enrichment analysis. We then mapped all tested single nucleotide polymorphisms (SNPs) on the genes contributing to significant pathways and prioritized those with a disproportionate number of nominal significant associations for further studies. For those prioritized genes, association studies were performed for selected SNPs in independent case-control samples (n = 1765) using logistic regression models, and results were meta-analysed with those from the GWAS.

RESULTS

Two biological processes were significantly enriched: the cytokine-cytokine receptor interaction (P = 0.002) and the Wnt signalling (P = 0.012). From the 417 genes interacting in these two pathways, 10 showed an excess of nominal associations, including a known asthma susceptibility locus (encoding SMAD family member 3) and other novel candidate genes. From the latter, association studies of 14 selected SNPs evidenced replication in a locus near the frizzled class receptor 6 (FZD6) gene (P = 9.90 × 10^-4 ), which had a consistent direction of effects with the GWAS findings (meta-analysed odds ratio = 1.49; P = 5.87 × 10^-6 ) and was in high linkage disequilibrium with expression quantitative trait loci in lung tissues.

CONCLUSIONS AND CLINICAL RELEVANCE

This study revealed the importance of two biological pathways in asthma pathogenesis and identified a novel susceptibility locus near Wnt signalling genes.

Genes Interacting with Occupational Exposures to Low Molecular Weight Agents and Irritants on Adult-Onset Asthma in Three European Studies

BACKGROUND

The biological mechanisms by which cleaning products and disinfectants-an emerging risk factor-affect respiratory health remain incompletely evaluated. Studying genes by environment interactions (G × E) may help identify new genes related to adult-onset asthma.

OBJECTIVES

We identified interactions between genetic polymorphisms of a large set of genes involved in the response to oxidative stress and occupational exposures to low molecular weight (LMW) agents or irritants on adult-onset asthma.

METHODS

Our data came from three large European cohorts: Epidemiological Family-based Study of the Genetics and Environment of Asthma (EGEA), Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults (SAPALDIA), and European Community Respiratory Health Survey in Adults (ECRHS). A candidate pathway-based strategy identified 163 genes involved in the response to oxidative stress and potentially related to exposures to LMW agents/irritants. Occupational exposures were evaluated using an asthma job-exposure matrix and job-specific questionnaires for cleaners and healthcare workers. Logistic regression models were used to detect G × E interactions, adjusted for age, sex, and population ancestry, in 2,599 adults (mean age, 47 years; 60% women, 36% exposed, 18% asthmatics). p-Values were corrected for multiple comparisons.

RESULTS

Ever exposure to LMW agents/irritants was associated with current adult-onset asthma [OR = 1.28 (95% CI: 1.04, 1.58)]. Eight single nucleotide polymorphism (SNP) by exposure interactions at five loci were found at p < 0.005: PLA2G4A (rs932476, chromosome 1), near PLA2R1 (rs2667026, chromosome 2), near RELA (rs931127, rs7949980, chromosome 11), PRKD1 (rs1958980, rs11847351, rs1958987, chromosome 14), and PRKCA (rs6504453, chromosome 17). Results were consistent across the three studies and after accounting for smoking.

CONCLUSIONS

Using a pathway-based selection process, we identified novel genes potentially involved in adult asthma by interaction with occupational exposure. These genes play a role in the NF-κB pathway, which is involved in inflammation. Citation: Rava M, Ahmed I, Kogevinas M, Le Moual N, Bouzigon E, Curjuric I, Dizier MH, Dumas O, Gonzalez JR, Imboden M, Mehta AJ, Tubert-Bitter P, Zock JP, Jarvis D, Probst-Hensch NM, Demenais F, Nadif R. 2017. Genes interacting with occupational exposures to low molecular weight agents and irritants on adult-onset asthma in three European studies. Environ Health Perspect 125:207-214; http://dx.doi.org/10.1289/EHP376.

A Novel Approach to High-Quality Postmortem Tissue Procurement: The GTEx Project

The Genotype-Tissue Expression (GTEx) project, sponsored by the NIH Common Fund, was established to study the correlation between human genetic variation and tissue-specific gene expression in non-diseased individuals. A significant challenge was the collection of high-quality biospecimens for extensive genomic analyses. Here we describe how a successful infrastructure for biospecimen procurement was developed and implemented by multiple research partners to support the prospective collection, annotation, and distribution of blood, tissues, and cell lines for the GTEx project. Other research projects can follow this model and form beneficial partnerships with rapid autopsy and organ procurement organizations to collect high quality biospecimens and associated clinical data for genomic studies. Biospecimens, clinical and genomic data, and Standard Operating Procedures guiding biospecimen collection for the GTEx project are available to the research community.

Role of ATG10 expression quantitative trait loci in non-small cell lung cancer survival

The aim of this article was to evaluate whether genetic variants in autophagy-related genes affect the overall survival (OS) of non-small cell lung cancer (NSCLC) patients. We analyzed 14 single nucleotide polymorphisms (SNPs) in core autophagy-related genes for OS in 1,001 NSCLC patients. Three promising SNPs in ATG10 were subsequently annotated by the expression quantitative trait loci (eQTL) and methylation quantitative trait loci (meQTL) analyses based on Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) datasets. We observed that the variants of rs10514231, rs1864182 and rs1864183 were associated with poor lung cancer survival (HR = 1.33, 95% CI = 1.07-1.65; HR = 1.43, 95% CI = 1.13-1.81; HR = 1.38, 95% CI = 1.14-1.68, respectively) and positively correlated with ATG10 expression (all p < 0.05) from GTEx and TCGA datasets. The elevated expression of ATG10 may predict shorter survival time in lung cancer patients in TCGA dataset (HR = 2.10, 95% CI = 1.33-3.29). Moreover, the variants of rs10514231 and rs1864182 were associated with the increased methylation levels of cg17942617 (meQTL), which in turn contributed to the elevated ATG10 expression and decreased survival time. Further functional assays revealed that ATG10 facilitated lung cancer cell proliferation and migration. Our findings suggest that eQTL/meQTL variations of ATG10 could influence lung cancer survival through regulating ATG10 expression.

Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well.

Transcriptomics resources of human tissues and organs

Quantifying the differential expression of genes in various human organs, tissues, and cell types is vital to understand human physiology and disease. Recently, several large‐scale transcriptomics studies have analyzed the expression of protein‐coding genes across tissues. These datasets provide a framework for defining the molecular constituents of the human body as well as for generating comprehensive lists of proteins expressed across tissues or in a tissue‐restricted manner. Here, we review publicly available human transcriptome resources and discuss body‐wide data from independent genome‐wide transcriptome analyses of different tissues. Gene expression measurements from these independent datasets, generated using samples from fresh frozen surgical specimens and postmortem tissues, are consistent. Overall, the different genome‐wide analyses support a distribution in which many proteins are found in all tissues and relatively few in a tissue‐restricted manner. Moreover, we discuss the applications of publicly available omics data for building genome‐scale metabolic models, used for analyzing cell and tissue functions both in physiological and in disease contexts.

Hallmarks of therapeutic management of the cystic fibrosis functional landscape

The cystic fibrosis (CF) transmembrane conductance regulator (CFTR) protein does not operate in isolation, rather in a dynamic network of interacting components that impact its synthesis, folding, stability, intracellular location and function, referred to herein as the 'CFTR Functional Landscape (CFFL)'. For the prominent F508del mutation, many of these interactors are deeply connected to a protein fold management system, the proteostasis network (PN). However, CF encompasses an additional 2000 CFTR variants distributed along its entire coding sequence (referred to as CFTR2), and each variant contributes a differential liability to PN management of CFTR and to a protein 'social network' (SN) that directs the probability of the (patho)physiologic events that impact ion transport in each cell, tissue and patient in health and disease. Recognition of the importance of the PN and SN in driving the unique patient CFFL leading to disease highlights the importance of precision medicine in therapeutic management of disease progression. We take the view herein that it is not CFTR, rather the PN/SN, and their impact on the CFFL, that are the key physiologic forces driving onset and clinical progression of CF. We posit that a deep understanding of each patients PN/SN gained by merging genomic, proteomic (mass spectrometry (MS)), and high-content microscopy (HCM) technologies in the context of novel network learning algorithms will lead to a paradigm shift in CF clinical management. This should allow for generation of new classes of patient specific PN/SN directed therapeutics for personalized management of the CFFL in the clinic.