Risk-associated Single Nucleotide Polymorphisms Research Articles

Multi-GPA-Tree: Statistical approach for pleiotropy informed and functional annotation tree guided prioritization of GWAS results.

Genome-wide association studies (GWAS) have successfully identified over two hundred thousand genotype-trait associations. Yet some challenges remain. First, complex traits are often associated with many single nucleotide polymorphisms (SNPs), most with small or moderate effect sizes, making them difficult to detect. Second, many complex traits share a common genetic basis due to 'pleiotropy' and and though few methods consider it, leveraging pleiotropy can improve statistical power to detect genotype-trait associations with weaker effect sizes. Third, currently available statistical methods are limited in explaining the functional mechanisms through which genetic variants are associated with specific or multiple traits. We propose multi-GPA-Tree to address these challenges. The multi-GPA-Tree approach can identify risk SNPs associated with single as well as multiple traits while also identifying the combinations of functional annotations that can explain the mechanisms through which risk-associated SNPs are linked with the traits. First, we implemented simulation studies to evaluate the proposed multi-GPA-Tree method and compared its performance with existing statistical approaches. The results indicate that multi-GPA-Tree outperforms existing statistical approaches in detecting risk-associated SNPs for multiple traits. Second, we applied multi-GPA-Tree to a systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA), and to a Crohn's disease (CD) and ulcertive colitis (UC) GWAS, and functional annotation data including GenoSkyline and GenoSkylinePlus. Our results demonstrate that multi-GPA-Tree can be a powerful tool that improves association mapping while facilitating understanding of the underlying genetic architecture of complex traits and potential mechanisms linking risk-associated SNPs with complex traits.

Assessing the performance of genetic risk score for stratifying risk of post-sepsis cardiovascular complications.

Patients with sepsis are at increased risk for cardiovascular complications, including myocardial infarction (MI), ischemic stroke (IS), and venous thromboembolism (VTE). Our objective is to assess whether genetic risk score (GRS) can differentiate risk for these complications. A population-based prospective cohort of 483,177 subjects, derived from the UK Biobank, was followed for diagnosis of sepsis and its complications (MI, IS, and VTE) after the study recruitment. GRS for each complication was calculated based on established risk-associated single nucleotide polymorphisms (SNPs). Time to incident MI, IS, and VTE was compared between subjects with or without sepsis and GRS risk groups using Kaplan-Meier log-rank test and Cox-regression analysis. During an average of 12.6 years of follow-up, 10,757 (2.23%) developed sepsis. Patients with sepsis had an overall higher risk than non-sepsis subjects for each complication, but the risk differed by time after a sepsis diagnosis; exceedingly high in short-term (0-30 days), considerably high in mid-term (31 days to 2 years), and reduced in long-term (>2 years). Furthermore, in White subjects, GRS was a significant predictor of complications, independent of sepsis and other risk factors. For example, GRSMI further differentiated their risk in patients with sepsis; 3.49, 4.73, and 9.03% in those with low- (<0.5), intermediate- (0.5-1.99), high- GRSMI (≥2.0), Ptrend < 0.001. Risk for post-sepsis cardiovascular complications differed considerably by time after a sepsis diagnosis and GRS. These findings, if confirmed in other ancestry-specific populations, may guide personalized management for preventing post-sepsis cardiovascular complications.

Abstract C082: Breast cancer risk in Hispanic/Latina women and the 6q25 chromosomal region: Fine mapping and eQTL identification

Abstract Breast cancer subtype distribution differs between populations with dissimilar genetic ancestry backgrounds. Several breast cancer risk single nucleotide polymorphisms (SNPs) were discovered in individuals of European and Asian origin. Hispanic/Latina women remain underrepresented in studies and public databases. The 6q25 locus contains multiple breast cancer risk-associated SNPs. Some SNPs within this region have been associated with the expression of genes (eQTLs), such as the Estrogen Receptor 1 gene (ESR1). Two breast cancer genetic association studies in Hispanics/Latinas identified two SNPs (rs140068132 and rs3778609), near ESR1, that correlate with Indigenous American ancestry and reduce the odds of breast cancer, especially for Estrogen Receptor-negative (ER-) disease. The underrepresentation of Latin American populations in public databases has hindered the study of the mechanisms by which these SNPs confer a protective effect. We integrated genetic and transcriptomic data from breast cancer patients with high Indigenous American ancestry to test the association between the protective variants in the 6q25 region and tumor gene expression. Breast cancer patients were recruited at the National Cancer Institute in Peru to be part of The Peruvian Genetics and Genomics of Breast Cancer Study (PEGEN-BC, N=1809). Healthy women from a pregnancy outcomes study in Peru were included as controls (N=3334). Genome-wide genotype data were available and missing genotypes were imputed using the TOPMED Imputation Server to perform fine-mapping within the 6q25 locus. Logistic regression was used to test the association between each SNP and breast cancer risk. We exome-sequenced 155 breast tumors of these patients. Transcripts per million counts and imputed genotypes within the 6q25 region were used for eQTL analysis. Colocalization was performed using summary statistics from the fine-mapping and eQTL analysis, including SNPs with minor allele frequency &amp;gt;5%. Only two SNPs, rs140068132 and rs851984 were independently associated with breast cancer risk, as we previously reported. eQTL signals colocalized with the subregion in 6q25 that contains these breast cancer-associated SNPs. Within this subregion, the gene with more eQTLs using a nominal p-value of &amp;lt;=0.01 was MTHFD1L (136 eQTLs), followed by ESR1 (58) and CCDC170 (32). Colocalization showed that MTHFD1L and ESR1 eQTLs were more likely to overlap with breast cancer risk SNPs, including rs140068132. The protective rs140068132-G variant was associated with lower expression of MTHFD1L. MTHFD1L has been found deregulated in breast cancer and higher expression is associated with poor prognosis. Our preliminary results suggest that the rs140068132-G variant in the 6q25 region identified in Hispanic/Latina women might exert its protective effect through the downregulation of MTHFD1L. Analyses with additional samples will allow us to confirm this result and further explore the functional implications of the rs140068132 variant. Citation Format: Valentina A. Zavala, Xiaosong Huang, Sandro Casavilca-Zambrano, Jeannie Navarro-Vásquez, Carlos A. Castañeda, Guillermo Valencia, Zaida Morante, Monica Calderon, Julio E. Abugattas, Henry Gómez, Hugo A. Fuentes, Ruddy Liendo-Picoaga, Jose M. Cotrina, Silvia Neciosup, Katia Roque, Jule Vásquez, Luis MAs, Marco Gálvez-Nino, Sixto E. Sánchez, Michelle A. Williams, Elad Ziv, Jovanny Zabaleta, Bizu Gelaye, Tatiana Vidaurre Vidaurre, Laura Fejerman. Breast cancer risk in Hispanic/Latina women and the 6q25 chromosomal region: Fine mapping and eQTL identification [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C082.

Risk-associated single nucleotide polymorphisms of mitochondrial D-loop mediate imbalance of cytokines and redox in rheumatoid arthritis.

We have identified rheumatoid arthritis (RA) risk-associated single nucleotide polymorphisms (SNPs) in the mitochondrial displacement loop (D-loop) including the major alleles of nucleotides 195T/C, 16260C/T, and 16519C/T as well as the minor alleles of nucleotides 146T/C and 150C/T previously. We evaluated the potential relationships of these SNPs with status for oxidative stress and inflammation cytokines. The DNA was extracted from blood samples of RA patients, and the SNPs of DNA D-loop were verified by polymerase chain reaction amplification and sequence analysis. Serum levels of inflammatory cytokines including interferon-γ (IFN-γ), interleukin-2 (IL-2), IL-6, IL-10, and tumor necrosis factor-α (TNF-α) were determined by cytometric bead array. Plasma reactive oxygen species (ROS) levels were measured by fluorescent probe technology. The RA risk-related allele 16519C was significantly associated with high IFN-γ levels (100.576 ± 11.769 vs 64.268 ± 8.199, 95% confidence interval [CI] -66.317 to -6.299, P=0.018). This allele also associated with ROS at borderline statistics level (619.295 ± 36.687 vs 526.979 ± 25.896, 95% CI -186.145 to -1.513, P=0.054). The subsequent analysis also showed that the ROS levels were positively correlated with IFN-γ levels (R=0.291, P=0.002). Further analysis showed that RA patients with high C-reactive protein levels displayed a higher ROS level (P=0.001). Our results imply that the 16519C allele of the mtDNA D-loop might promote ROS and IFN-γ levels by altering the replication and transcription of mtDNA, thereby modifying RA development. The potential relationships of RA-associated SNPs in the mitochondrial D-loop with status for oxidative stress and inflammation were evaluated. The 16519C allele of the mtDNA D-loop might promote ROS and IFN-γ levels by altering the replication and transcription of mtDNA to modify RA development.

Genetic Risk Score Can Supplement Current Guidelines To Identify Patients At Elevated Risk For Abdominal Aortic Aneurysms

Genetic risk scores (GRS) based on multiple disease-specific risk-associated single nucleotide polymorphism (SNPs) have been shown to be effective tools for stratifying risks of various diseases. We tested associations of GRS of AAA (GRSAAA) and coronary artery disease (GRSCAD) with risk and severity of AAA. We also explored their clinical utility in identifying high-risk subjects for AAA screening by comparing with the current screening guidelines of the United States Preventive Services Task Force.

Reliability of Ancestry-specific Prostate Cancer Genetic Risk Score in Four Racial and Ethnic Populations

BackgroundReliability of prostate cancer (PCa) genetic risk score (GRS), that is, the concordance between its estimated risk and observed risk, is required for genetic testing at the individual level. Reliability data are lacking for non-European racial/ethnic populations, which hinders its clinical use and exacerbates racial disparity. ObjectiveTo calibrate PCa ancestry-specific GRS in four racial/ethnic populations. Design, setting, and participantsPCa ancestry-specific GRSs, calculated from published risk-associated single-nucleotide polymorphisms in corresponding racial/ethnic populations, were evaluated in men who participated in 23andMe, Inc. genetic testing and consented for research, including 888 086 of European (EUR), 81 109 of Hispanic (HIS), 30 472 of African (AFR), and 13 985 of East Asian (EAS) ancestry, as classified by 23andMe's ancestry composition algorithm. Outcome measurements and statistical analysisThe concordance between the observed and estimated PCa risks at ten ancestry-specific GRS deciles was measured primarily by using the calibration slope (β), where 1 represents a perfect calibration. Platt scaling was used to correct the systematic bias of GRS. Results and limitationsA linear trend of an increased observed PCa prevalence in men with higher ancestry-specific GRS deciles was found in each racial population (all p-trend < 0.001). A calibration analysis revealed a systematic bias of GRS; β was considerably lower than 1 (0.73, 0.64, 0.66, and 0.75 in EUR, HIS, AFR, and EAS ancestries, respectively). This bias was reduced after the Platt scaling correction: β for scaled GRS in the testing dataset (40% of individuals) approximated 1 for all groups (0.95, 1.05, 1.02, and 1.01 in EUR, HIS, AFR, and EAS populations, respectively). The generalizability of the Platt correction needs to be validated in independent cohorts. ConclusionsA systematic bias of ancestry-specific GRS in the direction of an overestimated risk for men in the highest decile was found in EUR and non-EUR populations. GRS is well calibrated after correction and is appropriate for genetic testing at the individual level for personalized PCa screening. Patient summaryA corrected genetic risk score is more reliable (supported by the observed prostate cancer [PCa] risk) and appropriate for genetic testing for personalized PCa screening.

Shared Inherited Genetics of Benign Prostatic Hyperplasia and Prostate Cancer

BackgroundThe association between benign prostatic hyperplasia (BPH) and prostate cancer (PCa) remains controversial, largely due to a detection bias in traditional observational studies. ObjectiveTo assess the association between BPH and PCa using inherited single nucleotide polymorphisms (SNPs). Design, setting, and participantsThe participants were White men from the population-based UK Biobank (UKB). Outcome measurements and statistical analysisThe association between BPH and PCa was tested for (1) phenotypic correlation using chi-square, (2) genetic correlation (rg) based on genome-wide SNPs using linkage disequilibrium score regression, and (3) cross-disease genetic associations based on known risk-associated SNPs (15 for BPH and 239 for PCa), individually and cumulatively using genetic risk score (GRS). Results and limitationsAmong 214717 White men in the UKB, 24623 (11%) and 14311 (6.7%) had a diagnosis of BPH and PCa, respectively. Diagnoses of these two diseases were significantly correlated (χ2 = 1862.80, p < 0.001). A significant genetic correlation was found (rg = 0.16; 95% confidence interval 0.03–0.28, p = 0.01). In addition, significant cross-disease genetic associations for established risk-associated SNPs were also found. Among the 250 established genome-wide association study–significant SNPs of PCa or BPH, 49 were significantly associated with the risk of the other disease at p < 0.05, significantly more than expected by chance (N = 12, p < 0.001; χ2 test). Furthermore, significant cross-disease GRS associations were also found; GRSBPH was significantly associated with PCa risk (odds ratio [OR] = 1.26 [1.18–1.36], p < 0.001), and GRSPCa was significantly associated with BPH risk (OR = 1.03 [1.02–1.04], p < 0.001). Moreover, GRSBPH was significantly and inversely associated with lethal PCa risk in a PCa case-case analysis (OR = 0.58 [0.41–0.81], p = 0.002). Only White men were studied. ConclusionsBPH and PCa share common inherited genetics, which suggests that the phenotypic association of these two diseases in observational studies is not entirely caused by the detection bias. Patient summaryFor the first time, we found that benign prostatic hyperplasia and prostate cancer are genetically related. This finding may have implications in disease etiology and risk stratification.

Inherited risk assessment and its clinical utility for predicting prostate cancer from diagnostic prostate biopsies.

Many studies on prostate cancer (PCa) germline variants have been published in the last 15 years. This review critically assesses their clinical validity and explores their utility in prediction of PCa detection rates from prostate biopsy. An integrative review was performed to (1) critically synthesize findings on PCa germline studies from published papers since 2016, including risk-associated single nucleotide polymorphisms (SNPs), polygenic risk score methods such as genetic risk score (GRS), and rare pathogenic mutations (RPMs); (2) exemplify the findings in a large population-based cohort from the UK Biobank (UKB); (3) identify gaps for implementing inherited risk assessment in clinic based on experience from a healthcare system; (4) evaluate available GRS data on their clinical utility in predicting PCa detection rates from prostate biopsies; and (5) describe a prospective germline-based biopsy trial to address existing gaps. SNP-based GRS and RPMs in four genes (HOXB13, BRCA2, ATM, and CHEK2) were significantly and consistently associated with PCa risk in large well-designed studies. In the UKB, positive family history, RPMs in the four implicated genes, and a high GRS (>1.5) identified 8.12%, 1.61%, and 17.38% of men to be at elevated PCa risk, respectively, with hazard ratios of 1.84, 2.74, and 2.39, respectively. Additionally, the performance of GRS for predicting PCa detection rate on prostate biopsy was consistently supported in several retrospective analyses of transrectal ultrasound (TRUS)-biopsy cohorts. Prospective studies evaluating the performance of all three inherited measures in predicting PCa detection rate from contemporary multiparametric MRI (mpMRI)-based biopsy are lacking. A multicenter germline-based biopsy trial to address these gaps is warranted. The complementary performance of three inherited risk measures in PCa risk stratification is consistently supported. Their clinical utility in predicting PCa detection rate, if confirmed in prospective clinical trials, may improve current decision-making for prostate biopsy.

Long Non-Coding RNAs at the Chromosomal Risk Loci Identified by Prostate and Breast Cancer GWAS.

Long non-coding RNAs (lncRNAs) are emerging as key players in a variety of cellular processes. Deregulation of the lncRNAs has been implicated in prostate and breast cancers. Recently, germline genetic variations associated with cancer risk have been correlated with lncRNA expression and/or function. In addition, single nucleotide polymorphisms (SNPs) at well-characterized cancer-associated lncRNAs have been analyzed for their association with cancer risk. These SNPs may occur within the lncRNA transcripts or spanning regions that may alter the structure, function, and expression of these lncRNA molecules and contribute to cancer progression and may have potential as therapeutic targets for cancer treatment. Additionally, some of these lncRNA have a tissue-specific expression profile, suggesting them as biomarkers for specific cancers. In this review, we highlight some of the cancer risk-associated SNPs that modulated lncRNAs with a potential role in prostate and breast cancers and speculate on how these lncRNAs may contribute to cancer development.

Mechanistic insights into genetic susceptibility to prostate cancer.

Prostate cancer (PCa) is the second most common cancer in men and is a highly heritable disease that affects millions of individuals worldwide. Genome-wide association studies have to date discovered nearly 270 genetic loci harboring hundreds of single nucleotide polymorphisms (SNPs) that are associated with PCa susceptibility. In contrast, the functional characterization of the mechanisms underlying PCa risk association is still growing. Given that PCa risk-associated SNPs are highly enriched in noncoding cis-regulatory genomic regions, accumulating evidence suggests a widespread modulation of transcription factor chromatin binding and allelic enhancer activity by these noncoding SNPs, thereby dysregulating gene expression. Emerging studies have shown that a proportion of noncoding variants can modulate the formation of transcription factor complexes at enhancers and CTCF-mediated 3D genome architecture. Interestingly, DNA methylation-regulated CTCF binding could orchestrate a long-range chromatin interaction between PCa risk enhancer and causative genes. Additionally, one-causal-variant-two-risk genes or multiple-risk-variant-multiple-genes are prevalent in some PCa risk-associated loci. In this review, we will discuss the current understanding of the general principles of SNP-mediated gene regulation, experimental advances, and functional evidence supporting the mechanistic roles of several PCa genetic loci with potential clinical impact on disease prevention and treatment.

GPA-Tree: statistical approach for functional-annotation-tree-guided prioritization of GWAS results.

In spite of great success of genome-wide association studies (GWAS), multiple challenges still remain. First, complex traits are often associated with many single nucleotide polymorphisms (SNPs), each with small or moderate effect sizes. Second, our understanding of the functional mechanisms through which genetic variants are associated with complex traits is still limited. To address these challenges, we propose GPA-Tree and it simultaneously implements association mapping and identifies key combinations of functional annotations related to risk-associated SNPs by combining a decision tree algorithm with a hierarchical modeling framework. First, we implemented simulation studies to evaluate the proposed GPA-Tree method and compared its performance with existing statistical approaches. The results indicate that GPA-Tree outperforms existing statistical approaches in detecting risk-associated SNPs and identifying the true combinations of functional annotations with high accuracy. Second, we applied GPA-Tree to a systemic lupus erythematosus (SLE) GWAS and functional annotation data including GenoSkyline and GenoSkylinePlus. The results from GPA-Tree highlight the dysregulation of blood immune cells, including but not limited to primary B, memory helper T, regulatory T, neutrophils and CD8+ memory T cells in SLE. These results demonstrate that GPA-Tree can be a powerful tool that improves association mapping while facilitating understanding of the underlying genetic architecture of complex traits and potential mechanisms linking risk-associated SNPs with complex traits. The GPATree software is available at https://dongjunchung.github.io/GPATree/. Supplementary data are available at Bioinformatics online.

Two distinct mechanisms underlie estrogen-receptor-negative breast cancer susceptibility at the 2p23.2 locus.

Genome wide-association studies (GWAS) have established over 400 breast cancer risk loci defined by common single nucleotide polymorphisms (SNPs), including several associated with estrogen-receptor (ER)-negative disease. Most of these loci have not been studied systematically and the mechanistic underpinnings of risk are largely unknown. Here we explored the landscape of genomic features at an ER-negative breast cancer susceptibility locus at chromosome 2p23.2 and assessed the functionality of 81 SNPs with strong evidence of association from previous fine mapping. Five candidateregulatory regions containing risk-associated SNPs were identified. Regulatory Region 1 in the first intron of WDR43 contains SNP rs4407214, which showed allele-specific interaction with the transcription factor USF1 in in vitro assays. CRISPR-mediated disruption of Regulatory Region 1 led to expression changes in the neighboring PLB1 gene, suggesting that the region acts as a distal enhancer. Regulatory Regions 2, 4, and 5 did not provide sufficient evidence for functionality in in silico and experimental analyses. Two SNPs (rs11680458 and rs1131880) in Regulatory Region 3, mapping to the seed region for miRNA-recognition sites in the 3' untranslated region of WDR43, showed allele-specific effects of ectopic expression of miR-376 on WDR43 expression levels. Taken together, our data suggest that risk of ER-negative breast cancer associated with the 2p23.2 locus is likely driven by a combinatorial effect on the regulation of WDR43 and PLB1.

Hepatocellular carcinoma risk variant modulates lncRNA HLA-DQB1-AS1 expression via a long-range enhancer-promoter interaction.

Substantial evidence highlighted the critical role of long non-coding RNAs (lncRNA) in driving hepatocarcinogenesis. We hypothesized that functional variants in genome-wide association studies (GWASs) associated loci might alter the expression levels of lncRNAs and contribute to the development of hepatocellular carcinoma (HCC). Here, we prioritized potentially cis-expression quantitative trait loci-based single nucleotide polymorphism (SNP)-lncRNA association together with the physical interaction by the analyses from Hi-C data in GWAS loci of chronic hepatitis B and HCC. Subsequently, by leveraging two-stage case-control study (1738 hepatitis B [HBV]) related HCC cases and 1988 HBV persistent carriers) and biological assays, we identified that rs2647046 was significantly associated with HCC risk (odds ratio = 1.26, 95% CI = 1.11 to 1.43, P = 4.14 × 10-4). Luciferase reporter assays and electrophoretic mobility shift assays showed that rs2647046 A allele significantly increased transcriptional activity via influencing transcript factor binding affinity. Allele-specific chromosome conformation capture assays revealed that enhancer with rs2647046 interacted with the HLA-DQB1-AS1 promoter to allele-specifically influence its expression by CTCF-mediated long-range loop. Cell proliferation assays indicated that HLA-DQB1-AS1 is a potential oncogene in HCC. Our study showed HLA-DQB1-AS1 regulated by a causal SNP in a long-range interaction manner conferred the susceptibility to HCC, suggesting an important mechanism of modulating lncRNA expression for risk-associated SNPs in the etiology of HCC.

A pleiotropic ATM variant (rs1800057 C>G) is associated with risk of multiple cancers.

ATM (ataxia-telangiectasia mutated) is an important cell-cycle checkpoint kinase required for cellular response to DNA damage. Activated by DNA double strand breaks, ATM regulates the activities of many downstream proteins involved in various carcinogenic events. Therefore, ATM or its genetic variants may have a pleiotropic effect on cancer development. We conducted a pleiotropic analysis to evaluate associations between genetic variants of ATM and risk of multiple cancers. With genotyping data extracted from previously published genome-wide association studies of various cancers, we performed multivariate logistic regression analysis, followed by a meta-analysis for each cancer site, to identify cancer risk-associated single-nucleotide polymorphisms (SNPs). In the ASSET two-sided analysis, we found that two ATM SNPs were significantly associated with risk of multiple cancers. One tagging SNP (rs1800057 C>G) was associated with risk of multiple cancers (two-sided P = 5.27 × 10-7). Because ATM rs1800057 is a missense variant, we also explored the intermediate phenotypes through which this variant may confer risk of multiple cancers and identified a possible immune-mediated effect of this variant. Our findings indicate that genetic variants of ATM may have a pleiotropic effect on cancer risk and thus provide an important insight into common mechanisms of carcinogenesis.

Parallel Reporter Assays Identify Altered Regulatory Role of rs684232 in Leading to Prostate Cancer Predisposition.

Functional characterization of cancer risk-associated single nucleotide polymorphism (SNP) identified by genome-wide association studies (GWAS) has become a big challenge. To identify the regulatory risk SNPs that can lead to transcriptional misregulation, we performed parallel reporter gene assays with both alleles of 213 prostate cancer risk-associated GWAS SNPs in 22Rv1 cells. We disclosed 32 regulatory SNPs that exhibited different regulatory activities with two alleles. For one of the regulatory SNPs, rs684232, we found that the variation altered chromatin binding of transcription factor FOXA1 on the DNA region and led to aberrant gene expression of VPS53, FAM57A, and GEMIN4, which play vital roles in prostate cancer malignancy. Our findings reveal the roles and underlying mechanism of rs684232 in prostate cancer progression and hold great promise in benefiting prostate cancer patients with prognostic prediction and target therapies.

Characterization of Rheumatoid Arthritis Risk-Associated SNPs and Identification of Novel Therapeutic Sites Using an In-Silico Approach.

Single-nucleotide polymorphisms (SNPs) are reported to be associated with many diseases, including autoimmune diseases. In rheumatoid arthritis (RA), about 152 SNPs are reported to account for ~15% of its heritability. These SNPs may result in the alteration of gene expression and may also affect the stability of mRNA, resulting in diseased protein. Therefore, in order to predict the underlying mechanism of these SNPs and identify novel therapeutic sites for the treatment of RA, several bioinformatics tools were used. The damaging effect of 23 non-synonymous SNPs on proteins using different tools suggested four SNPs, including rs2476601 in PTPN22, rs5029941 and rs2230926 in TNFAIP3, and rs34536443 in TYK2, to be the most damaging. In total, 42 of 76 RA-associated intronic SNPs were predicted to create or abolish potential splice sites. Moreover, the analysis of 11 RA-associated UTR SNPs indicated that only one SNP, rs1128334, located in 3'UTR of ETS1, caused functional pattern changes in BRD-BOX. For the identification of novel therapeutics sites to treat RA, extensive gene-gene interaction network interactive pathways were established, with the identification of 13 potential target sites for the development of RA drugs, including three novel target genes. The anticipated effect of these findings on RA pathogenesis may be further validated in both in vivo and in vitro studies.

Association of prostate cancer polygenic risk score with number and laterality of tumor cores in active surveillance patients.

Prostate cancer (PCa) is characterized by its tendency to be multifocal. However, few studies have investigated the endogenous factors that explain the multifocal disease. The primary objective of the current study is to test whether inherited PCa risk is associated with multifocal tumors in PCa patients. Subjects in this study were PCa patients of European ancestry undergoing active surveillanceat Johns Hopkins Hospital (N = 805) and NorthShore University HealthSystem (N = 432). The inherited risk was measured by genetic risk score (GRS), an odds ratio-weighted and population-standardized polygenic risk score based on known risk-associated single nucleotide polymorphisms. PCa multifocality was indirectly measured by the number and laterality of positive tumor cores from a 12-core systematic biopsy. In the combined cohort, 35.7% and 66.3% of patients had ≥2 tumor cores at the initial diagnostic biopsy and on at least one subsequent surveillance biopsy, respectively. For tumor laterality, 7.8% and 47.8% of patients had bilateral tumor cores at diagnostic and surveillance biopsies, respectively. We found, for the first time, that patients with higher numbers of positive cores at diagnostic and surveillance biopsies, respectively, had significantly higher mean GRS values; p = .01 and p = 5.94E-04. Additionally, patients with bilateral tumors at diagnostic and surveillance biopsies, respectively, had significantly higher mean GRS values than those with unilateral tumors; p = .04 and p = .01. In contrast, no association was found between GRS and maximum core length of tumor or tumor grade at diagnostic/surveillance biopsies (all p > .05). Finally, we observed a modest trend that patients with higher GRS quartiles had a higher risk for tumor upgrading on surveillance biopsies. The trend, however, was not statistically significant (p > .05). The associations of GRS with two measurements of PCa multifocality (core numbers and laterality) provide novel and consistent evidence for the link between inherited PCa risk and multifocal tumors.

Single-nucleotide polymorphism rs4142441 and MYC co-modulated long non-coding RNA OSER1-AS1 suppresses non-small cell lung cancer by sequestering ELAVL1.

Single‐nucleotide polymorphisms (SNP) and long non‐coding RNAs (lncRNAs) have been involved in the process of lung cancer. Following clues given by lung cancer risk‐associated SNP, we aimed to find novel functional lncRNAs as candidate targets in lung cancer. We identified a lncRNA Oxidative Stress Responsive Serine Rich 1 Antisense RNA 1 (OSER1‐AS1) through a lung cancer risk‐associated SNP rs4142441. OSER1‐AS1 was down‐regulated in tumor tissue and its low expression was significantly associated with poor overall survival among non‐smokers in non‐small cell lung cancer (NSCLC) patients. Gain‐ and loss‐of‐function studies showed that OSER1‐AS1 acted as a tumor suppressor by inhibiting lung cancer cell growth, migration and invasion in vitro. Xenograft tumor assays and a metastasis mouse model confirmed that OSER1‐AS1 suppressed tumor growth and metastasis in vivo. The promoter of OSER1‐AS1 was repressed by MYC, and the 3′‐end of OSER1‐AS1 was competitively targeted by microRNA hsa‐miR‐17‐5p and RNA‐binding protein ELAVL1. Our results indicated that OSER1‐AS1 exerted tumor‐suppressive functions by acting as an ELAVL1 decoy to keep it away from its target mRNAs. Our findings characterized OSER1‐AS1 as a new tumor‐suppressive lncRNA in NSCLC, suggesting that OSER1‐AS1 may be suitable as a potential biomarker for prognosis, and a potential target for treatment.

Mild catalytic defects of tert rs61748181 polymorphism affect the clinical presentation of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a disorder of accelerated lung aging. Multiple pieces of evidence support that the aging biomarker short telomeres, which can be caused by mutations in telomerase reverse transcriptase (TERT), contribute to COPD pathogenesis. We hypothesized that short telomere risk-associated single nucleotide polymorphisms (SNPs) in TERT, while not able to drive COPD development, nonetheless modify the disease presentation. We set out to test the SNP carrying status in a longitudinal study of smokers with COPD and found that rapid decline of FEV1 in lung function was associated with the minor allele of rs61748181 (adjusted odds ratio 2.49, p = 0.038). Biochemical evaluation of ex vivo engineered human cell models revealed that primary cells expressing the minor allele of rs61748181 had suboptimal telomere length maintenance due to reduced telomerase catalytic activity, despite having comparable cell growth kinetics as WT-TERT expressing cells. This ex vivo observation translated clinically in that shorter telomeres were found in minor allele carriers in a sub-population of COPD patients with non-declining lung function, over the 5-year period of the longitudinal study. Collectively, our data suggest that functional TERT SNPs with mild catalytic defects are nonetheless implicated in the clinical presentation of COPD.

SNPs associated with colorectal cancer at 15q13.3 affect risk enhancers that modulate GREM1 gene expression.

Several genome wide association studies of colorectal cancer (CRC) have identified single nucleotide polymorphisms (SNPs) on chromosome 15q13.3 associated with CRC risk. To identify functional variant(s) underlying this association, we investigated SNPs in linkage disequilibrium with the risk‐associated SNP rs4779584 that overlapped regulatory regions/enhancer elements characterized in colon‐related tissues and cells. We identified several SNP‐containing regulatory regions that exhibited enhancer activity in vitro, including one SNP (rs1406389) that correlated with allele‐specific effects on enhancer activity. Deletion of either this enhancer or another enhancer that had previously been reported in this region correlated with decreased expression of GREM1 following CRISPR/Cas9 genome editing. That GREM1 is one target of these enhancers was further supported by an expression quantitative trait loci correlation between rs1406389 and GREM1 expression in the transverse but not sigmoid colon in the Genotype‐Tissue Expression dataset. Taken together, we conclude that the 15q13.3 region contains at least two functional variants that map to distinct enhancers and impact CRC risk through modulation of GREM1 expression.