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Genome-wide association studies along with expression quantitative trait locus (eQTL) mapping have identified hundreds of single-nucleotide polymorphisms (SNPs) and their target genes in prostate cancer (PCa), yet functional characterization of these risk loci remains challenging. To screen for potential regulatory SNPs, we designed a CRISPRi library containing 9,133 guide RNAs (gRNAs) to cover 2,166 candidate SNP loci implicated in PCa and identified 117 SNPs that could regulate 90 genes for PCa cell growth advantage. Among these, rs60464856 was covered by multiple gRNAs significantly depleted in screening (FDR < 0.05). Pooled SNP association analysis in the PRACTICAL and FinnGen cohorts showed significantly higher PCa risk for the rs60464856 G allele (p value = 1.2 × 10-16 and 3.2 × 10-7, respectively). Subsequent eQTL analysis revealed that the G allele is associated with increased RUVBL1 expression in multiple datasets. Further CRISPRi and xCas9 base editing confirmed that the rs60464856 G allele leads to elevated RUVBL1 expression. Furthermore, SILAC-based proteomic analysis demonstrated allelic binding of cohesin subunits at the rs60464856 region, where the HiC dataset showed consistent chromatin interactions in prostate cell lines. RUVBL1 depletion inhibited PCa cell proliferation and tumor growth in a xenograft mouse model. Gene-set enrichment analysis suggested an association of RUVBL1 expression with cell-cycle-related pathways. Increased expression of RUVBL1 and activation of cell-cycle pathways were correlated with poor PCa survival in TCGA datasets. Our CRISPRi screening prioritized about one hundred regulatory SNPs essential for prostate cell proliferation. In combination with proteomics and functional studies, we characterized the mechanistic role of rs60464856 and RUVBL1 in PCa progression.
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Próstata , Neoplasias da Próstata , Animais , Humanos , Masculino , Camundongos , Alelos , ATPases Associadas a Diversas Atividades Celulares/genética , Proteínas de Transporte/genética , DNA Helicases/genética , Detecção Precoce de Câncer , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Polimorfismo de Nucleotídeo Único/genética , Próstata/metabolismo , Neoplasias da Próstata/genética , Neoplasias da Próstata/patologia , Proteômica , CoesinasRESUMO
Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. We developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas (TCGA). Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.
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Neoplasias da Próstata , Masculino , Humanos , Neoplasias da Próstata/genética , Proteínas Sanguíneas/genética , Biomarcadores Tumorais/genéticaRESUMO
Specific metabolites have been reported to be potentially associated with Alzheimer's disease (AD) risk. However, the comprehensive understanding of roles of metabolite biomarkers in AD etiology remains elusive. We performed a large AD metabolome-wide association study (MWAS) by developing blood metabolite genetic prediction models. We evaluated associations between genetically predicted levels of metabolites and AD risk in 39,106 clinically diagnosed AD cases, 46,828 proxy AD and related dementia (proxy-ADD) cases, and 401,577 controls. We further conducted analyses to determine microbiome features associated with the detected metabolites and characterize associations between predicted microbiome feature levels and AD risk. We identified fourteen metabolites showing an association with AD risk. Five microbiome features were further identified to be potentially related to associations of five of the metabolites. Our study provides new insights into the etiology of AD that involves blood metabolites and gut microbiome, which warrants further investigation.
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Doença de Alzheimer , Biomarcadores , Genômica , Metabolômica , Humanos , Doença de Alzheimer/sangue , Doença de Alzheimer/genética , Doença de Alzheimer/metabolismo , Metabolômica/métodos , Biomarcadores/sangue , Feminino , Masculino , Genômica/métodos , Idoso , Metaboloma , Estudo de Associação Genômica Ampla/métodos , Microbioma Gastrointestinal/fisiologia , Microbioma Gastrointestinal/genética , Fatores de Risco , Pessoa de Meia-Idade , Estudos de Casos e ControlesRESUMO
Regulatory modules for controlling the kinetics of toehold-mediated strand displacement (TMSD) play critical roles in designing dynamic and dissipative DNA chemical reaction networks (CRNs) but are hardwired into sequence designs. Herein, we introduce antitoehold (At), a plug-and-play module for reversible and continuous tuning of TMSD kinetics by temporarily occupying the toehold domain via a metastable duplex and base stacking. We demonstrate that kinetic control can be readily activated or deactivated in real time for any TMSD by simply adding At or anti-At. Continuous tuning of TMSD kinetics can also be achieved by altering the concentration of At. Moreover, the simple addition of At could readily reprogram existing TMSDs into a pulse-generation DNA CRN with continuous tunability. Our At approach also offers a new way for engineering continuously tunable DNA hybridization probes, which may find practical uses for discriminating clinically important mutations. Because of the simplicity, we anticipate that At will find wide applications for engineering DNA CRNs with diverse dynamic and dissipative behaviors, and DNA hybridization probes with tunable affinity and selectivity.
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DNA , DNA/química , Hibridização de Ácido Nucleico , Cinética , Sondas de DNARESUMO
Genome-wide association studies (GWAS) have identified two dozen genetic variants that are associated with the risk of pancreatic ductal adenocarcinoma (PDAC), a deadly malignancy. However, a majority of these variants are located in noncoding regions of the genome, which limits the translation of GWAS findings into clinical applications. The regulome-wide association study (RWAS) is a recently developed method for identifying TF binding-induced accessibility regions for diseases. However, their potential connection to PDAC has yet to be fully explored. We evaluated the associations between genetically predicted levels of chromatin accessibility and risk of PDAC by using pan-cancer chromatin accessibility genetic prediction models. Our analysis included 8275 cases and 6723 controls from the PanScan (I, II, and III) and PanC4 consortia. To further refine our results, we also integrated genes associated to allele-specific accessibility quantitative trait loci (as-aQTL) and TF motifs located in the as-aQTL. We found that 50 chromatin accessibility features were associated with PDAC risk at a false discovery rate (FDR) of less than 0.05. A total of 28 RWAS peaks were identified as conditionally significant. By integrating the results from as-aQTL, motif analysis, and RWAS, we identified candidate causal regulatory elements for two potential chromatin accessibility regions (THCA_89956 and ESCA_89167) that are associated with PDAC risk. Our study identified chromatin accessibility features in noncoding genomic regions that are associated with PDAC risk. We also predicted the associated genes and disrupt motifs. Our findings provide new insights into the regulatory mechanisms of noncoding regions for pancreatic tumorigenesis.
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Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Humanos , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla/métodos , Pâncreas , Neoplasias Pancreáticas/genética , Carcinoma Ductal Pancreático/genética , Cromatina/genética , Polimorfismo de Nucleotídeo ÚnicoRESUMO
Pancreatic ductal adenocarcinoma (PDAC) is an uncommon but highly fatal malignancy. Identifying causal metabolite biomarkers offers an opportunity to facilitate effective risk assessment strategies for PDAC. In this study, we performed a two-sample Mendelian randomization (MR) study to characterize the potential causal effects of metabolites in plasma on PDAC risk. Genetic instruments were determined for a total of 506 metabolites from one set of comprehensive genome-wide association studies (GWAS) involving 913 individuals of European ancestry from the INTERVAL/EPIC-Norfolk cohorts. Another set of genetic instruments was developed for 483 metabolites from an independent GWAS conducted with 8299 individuals of European ancestry from the Canadian Longitudinal Study on Aging (CLSA) cohort. We analyzed GWAS data of the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), comprising 8275 PDAC cases and 6723 controls of European ancestry. The association of metabolites with PDAC risk was assessed using the inverse-variance weighted (IVW) method, and complemented with sensitivity analyses of MR-Egger and MR-PRESSO tests. Potential side effects of targeting the identified metabolites for PDAC intervention were further evaluated by a phenome-wide MR (Phe-MR) analysis. Forty-four unique metabolites were identified to be significantly associated with PDAC risk, of which four top-ranking metabolites (X: 12798, X: 11787, X: 11308 and X: 19141) showed replication evidence when using instruments developed from both two cohorts. Our results highlight novel blood metabolites related to PDAC risk, which may help prioritize metabolic features for PDAC mechanistic research and further evaluation of their potential role in PDAC risk assessment.
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Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Humanos , Análise da Randomização Mendeliana , Estudo de Associação Genômica Ampla , Estudos Longitudinais , Canadá/epidemiologia , Neoplasias Pancreáticas/genética , Carcinoma Ductal Pancreático/genéticaRESUMO
Although previous studies identified numerous single nucleotide polymorphisms (SNPs) and their target genes predisposed to prostate cancer (PrCa) risks, SNP-related splicing associations are rarely reported. In this study, we applied distance-based sQTL analysis (sQTLseekeR) using RNA-seq and SNP genotype data from benign prostate tissue (n = 467) and identified significant associations in 3344 SNP-transcript pairs (P ≤ 0.05) at PrCa risk loci. We characterized a common SNP (rs7247241) and its target gene (PPP1R14A) located in chr19q13, an sQTL with risk allele T associated with upregulation of long isoform (P = 9.99E-7). We confirmed the associations in both TCGA (P = 2.42E-24) and GTEX prostate cohorts (P = 9.08E-78). To functionally characterize this SNP, we performed chromatin immunoprecipitation qPCR and confirmed stronger CTCF and PLAGL2 binding in rs7247241 C than T allele. We found that CTCF binding enrichment was negatively associated with methylation level at the SNP site in human cell lines (r = -0.58). Bisulfite sequencing showed consistent association of rs7247241-T allele with nearby sequence CpG hypermethylation in prostate cell lines and tissues. Moreover, the methylation level at CpG sites nearest to the CTCF binding and first exon splice-in (ψ) of PPP1R14A was significantly associated with aggressive phenotype in the TCGA PrCa cohort. Meanwhile, the long isoform of the gene also promoted cell proliferation. Taken together, with the most updated gene annotations, we reported a set of sQTL associated with multiple traits related to human prostate diseases and revealed a unique role of PrCa risk SNP rs7247241 on PPP1R14A isoform transition.
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Polimorfismo de Nucleotídeo Único , Neoplasias da Próstata , Alelos , Ilhas de CpG/genética , Metilação de DNA/genética , Proteínas de Ligação a DNA/genética , Humanos , Peptídeos e Proteínas de Sinalização Intracelular , Masculino , Proteínas Musculares , Polimorfismo de Nucleotídeo Único/genética , Neoplasias da Próstata/genética , Isoformas de Proteínas/genética , Proteínas de Ligação a RNA/genética , Fatores de Transcrição/genéticaRESUMO
BACKGROUND: Multiple novel protein biomarkers have been shown to be associated with prostate cancer risk using genetic instruments. This study aimed to externally validate the associations of 30 genetically predicted candidate proteins with prostate cancer risk using aptamer-based levels in US Black and White men in the Atherosclerosis Risk in Communities (ARIC) study. Plasma protein levels were previously measured by SomaScan® using the blood collected in 1990-1992. METHODS: Among 4864 eligible participants, we ascertained 667 first primary prostate cancer cases through 2015. Hazard ratios (HRs) of prostate cancer and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression for tertiles of each protein. We adjusted for age, race, and other risk factors. RESULTS: Of the 30 proteins and considering a nominal p trend < 0.05, two were positively associated with prostate cancer risk-RF1ML (tertile 3 vs. 1: HR = 1.23; 95% CI 1.02-1.48; p trend = 0.037) and TPST1 (1.28, 95% CI 1.06-1.55; p trend = 0.0087); two were inversely associated-ATF6A (HR = 0.80, 95% CI 0.65-0.98; p trend = 0.028) and SPINT2 (HR = 0.74, 95% CI 0.61-0.90; p trend = 0.0025). One protein, KDEL2, which was nonlinearly associated (test-for-linearity: p < 0.01) showed a statistically significant lower risk in the second tertile (HR = 0.79, 95% CI 0.65-0.95). Of these five, four proteins-ATF6A, KDEL2, RF1ML, and TPST1-were consistent in the direction of association with the discovery studies. CONCLUSION: This study validated some pre-diagnostic protein biomarkers of the risk of prostate cancer.
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High-throughput screening (HTS) is pivotal in the discovery of small molecules that bind to DNA, yet there are limited sensing mechanisms available for designing HTS assays for DNA binders. Herein, we introduce a binder-responsive toehold-mediated DNA strand displacement (BR-TMSD) technique featuring programmable reaction kinetics in response to DNA-binder interactions. When two DNA binders are used, BR-TMSD is initiated through a rapid binder displacement, followed by the DNA strand displacement. The orthogonal displacement reactions of BR-TMSD enables a high-fidelity, dual-channel HTS assay, returning 19 new DNA binders from a library of 1,170 compounds.
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BACKGROUND: Numerous studies have been conducted to investigate the relationship between ABO and Rhesus (Rh) blood groups and various health outcomes. However, a comprehensive evaluation of the robustness of these associations is still lacking. METHODS: We searched PubMed, Web of Science, Embase, Scopus, Cochrane, and several regional databases from their inception until Feb 16, 2024, with the aim of identifying systematic reviews with meta-analyses of observational studies exploring associations between ABO and Rh blood groups and diverse health outcomes. For each association, we calculated the summary effect sizes, corresponding 95% confidence intervals, 95% prediction interval, heterogeneity, small-study effect, and evaluation of excess significance bias. The evidence was evaluated on a grading scale that ranged from convincing (Class I) to weak (Class IV). We assessed the certainty of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation criteria (GRADE). We also evaluated the methodological quality of included studies using the A Measurement Tool to Assess Systematic Reviews (AMSTAR). AMSTAR contains 11 items, which were scored as high (8-11), moderate (4-7), and low (0-3) quality. We have gotten the registration for protocol on the PROSPERO database (CRD42023409547). RESULTS: The current umbrella review included 51 systematic reviews with meta-analysis articles with 270 associations. We re-calculated each association and found only one convincing evidence (Class I) for an association between blood group B and type 2 diabetes mellitus risk compared with the non-B blood group. It had a summary odds ratio of 1.28 (95% confidence interval: 1.17, 1.40), was supported by 6870 cases with small heterogeneity (I2 = 13%) and 95% prediction intervals excluding the null value, and without hints of small-study effects (P for Egger's test > 0.10, but the largest study effect was not more conservative than the summary effect size) or excess of significance (P < 0.10, but the value of observed less than expected). And the article was demonstrated with high methodological quality using AMSTAR (score = 9). According to AMSTAR, 18, 32, and 11 studies were categorized as high, moderate, and low quality, respectively. Nine statistically significant associations reached moderate quality based on GRADE. CONCLUSIONS: Our findings suggest a potential relationship between ABO and Rh blood groups and adverse health outcomes. Particularly the association between blood group B and type 2 diabetes mellitus risk.
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Sistema ABO de Grupos Sanguíneos , Metanálise como Assunto , Estudos Observacionais como Assunto , Sistema do Grupo Sanguíneo Rh-Hr , Revisões Sistemáticas como Assunto , Humanos , Revisões Sistemáticas como Assunto/métodos , Estudos Observacionais como Assunto/métodosRESUMO
BACKGROUND: Early-onset prostate cancer (EOPC, ≤ 55 years) has a unique clinical entity harboring high genetic risk, but the majority of EOPC patients still substantial opportunity to be early-detected thus suffering an unfavorable prognosis. A refined understanding of age-based polygenic risk score (PRS) for prostate cancer (PCa) would be essential for personalized risk stratification. METHODS: We included 167,517 male participants [4882 cases including 205 EOPC and 4677 late-onset PCa (LOPC)] from UK Biobank. A General-, an EOPC- and an LOPC-PRS were derived from age-specific genome-wide association studies. Weighted Cox proportional hazard models were applied to estimate the risk of PCa associated with PRSs. The discriminatory capability of PRSs were validated using time-dependent receiver operating characteristic (ROC) curves with additional 4238 males from PLCO and TCGA. Phenome-wide association studies underlying Mendelian Randomization were conducted to discover EOPC linking phenotypes. RESULTS: The 269-PRS calculated via well-established risk variants was more strongly associated with risk of EOPC [hazard ratio (HR) = 2.35, 95% confidence interval (CI) 1.99-2.78] than LOPC (HR = 1.95, 95% CI 1.89-2.01; I2 = 79%). EOPC-PRS was dramatically related to EOPC risk (HR = 4.70, 95% CI 3.98-5.54) but not to LOPC (HR = 0.98, 95% CI 0.96-1.01), while LOPC-PRS had similar risk estimates for EOPC and LOPC (I2 = 0%). Particularly, EOPC-PRS performed optimal discriminatory capability for EOPC (area under the ROC = 0.613). Among the phenomic factors to PCa deposited in the platform of ProAP (Prostate cancer Age-based PheWAS; https://mulongdu.shinyapps.io/proap ), EOPC was preferentially associated with PCa family history while LOPC was prone to environmental and lifestyles exposures. CONCLUSIONS: This study comprehensively profiled the distinct genetic and phenotypic architecture of EOPC. The EOPC-PRS may optimize risk estimate of PCa in young males, particularly those without family history, thus providing guidance for precision population stratification.
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Estratificação de Risco Genético , Neoplasias da Próstata , Humanos , Masculino , Estudo de Associação Genômica Ampla , Estudos de Coortes , Fatores de Risco , Predisposição Genética para DoençaRESUMO
BACKGROUND: Numerous meta-analyses have explored the association between the triglyceride-glucose (TyG) index and diverse health outcomes, yet the comprehensive assessment of the scope, validity, and quality of this evidence remains incomplete. Our aim was to systematically review and synthesise existing meta-analyses of TyG index and health outcomes and to assess the quality of the evidence. METHODS: A thorough search of PubMed, EMBASE, and Web of Science databases was conducted from their inception through to 8 April 2024. We assessed the quality of reviews using A Measurement Tool to Assess Systematic Reviews (AMSTAR) and the certainty of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system. This study was registered with PROSPERO (CRD: 42024518587). RESULTS: Overall, a total of 95 associations from 29 meta-analyses were included, investigating associations between TyG index and 30 health outcomes. Of these, 83 (87.4%) associations were statistically significant (P < 0.05) according to the random effects model. Based on the AMSTAR tool, 16 (55.2%) meta-analyses were high quality and none was low quality. The certainty of the evidence, assessed by the GRADE framework, showed that 6 (6.3%) associations were supported by moderate-quality evidence. When compared with the lowest category of the TyG index, the risk of contrast-induced nephropathy (CIN) [relative risk (RR) = 2.25, 95%CI 1.82, 2.77], the risk of stroke in patients with diabetes mellitus (RR = 1.26, 95%CI 1.18, 1.33) or with acute coronary syndrome disease (RR = 1.56, 95%CI 1.06, 2.28), the prognosis of coronary artery disease (CAD)-non-fatal MI (RR = 2.02, 95%CI 1.32, 3.10), and the severity of CAD including coronary artery stenosis (RR = 3.49, 95%CI 1.71, 7.12) and multi-vessel CAD (RR = 2.33, 95%CI 1.59, 3.42) increased with high TyG index. CONCLUSION: We found that the TyG index was positively associated with many diseases including the risk of CIN and stroke, the prognosis of CAD, and the severity of CAD which were supported by moderate-quality evidence. TyG index might be useful to identify people at high-risk for developing these diseases.
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Biomarcadores , Glicemia , Estudos Observacionais como Assunto , Triglicerídeos , Feminino , Humanos , Masculino , Biomarcadores/sangue , Glicemia/metabolismo , Doenças Cardiovasculares/sangue , Doenças Cardiovasculares/diagnóstico , Doenças Cardiovasculares/epidemiologia , Metanálise como Assunto , Valor Preditivo dos Testes , Prognóstico , Medição de Risco , Fatores de Risco , Revisões Sistemáticas como Assunto , Triglicerídeos/sangueRESUMO
BACKGROUND: The predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters for predicting AIP relapse is currently unknown. This study firstly explored the value of 18F-FDG PET/CT parameters as predictors of type 1 AIP relapse. METHODS: This multicenter retrospective cohort study analyzed 51 patients who received 18F-FDG PET/CT prior to treatment and did not receive maintenance therapy after remission. The study collected baseline characteristics and clinical data and conducted qualitative and semi-quantitative analysis of pancreatic lesions and extrapancreatic organs. The study used three thresholds to select the boundaries of pancreatic lesions to evaluate metabolic parameters, including the maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), total lesion glycolysis (TLG), metabolic tumor volume (MTV), and tumor-to-normal liver standard uptake value ratio (SUVR). Univariate and multivariate analyses were performed to identify independent predictors and build a recurrence prediction model. The model was internally validated using the bootstrap method and a nomogram was created for clinical application. RESULTS: In the univariable analysis, the relapsed group showed higher levels of SUVmax (6.0 ± 1.6 vs. 5.2 ± 1.1; P = 0.047), SUVR (2.3 [2.0-3.0] vs. 2.0 [1.6-2.4]; P = 0.026), and TLG2.5 (234.5 ± 149.1 vs. 139.6 ± 102.5; P = 0.020) among the 18F-FDG PET metabolic parameters compared to the non-relapsed group. In the multivariable analysis, serum IgG4 (OR, 1.001; 95% CI, 1.000-1.002; P = 0.014) and TLG2.5 (OR, 1.007; 95% CI, 1.002-1.013; P = 0.012) were independent predictors associated with relapse of type 1 AIP. A receiver-operating characteristic curve of the predictive model with these two predictors demonstrated an area under the curve of 0.806. CONCLUSION: 18F-FDG PET/CT metabolic parameters, particularly TLG2.5, are potential predictors for relapse in patients with type 1 AIP. A multiparameter model that includes IgG4 and TLG2.5 can enhance the ability to predict AIP relapse.
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Pancreatite Autoimune , Neoplasias Pancreáticas , Humanos , Fluordesoxiglucose F18/metabolismo , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodos , Estudos Retrospectivos , Recidiva , Carga Tumoral , Prognóstico , Compostos RadiofarmacêuticosRESUMO
In this work, a mixed precursor solvent system comprising isopropyl alcohol (IPA) and 2-methoxy ethanol (MOE) is introduced for the fabrication of Cu2ZnSn(S, Se)4 (CZTSSe) thin films under ambient conditions. The effects of different IPA/(MOE + IPA) ratios on the characteristics of CZTSSe films and the corresponding devices were investigated. Our research results indicate that the addition of IPA enhances the wettability of Cu-Zn-Sn-S precursor solution on the substrate, reduces Sn loss in the film during high-temperature annealing, and diminishes band tail states. Additionally, adding IPA leads to effective enlargement of grain size, improved crystallinity, and enhanced light absorption. However, excessive content of IPA negatively impacts CZTSSe film properties and the device's performance. Notably, when substituting 20% of MOE with IPA, the short-circuit current density (JSC) increased from 30.84 mA cm-2 to 35.55 mA cm-2 in the resulting CZTSSe device, and the efficiency improved from 9.19% to 10.63%. This work provides a new method of a solvent system for preparing efficient kesterite-based solar cells.
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BACKGROUND: Wrist fracture is one of the common limb fractures. Its incidence rate increases with age and osteoporosis. Nowadays, Sleep health is increasingly valued, but the relationship between wrist fractures and sleep time is not yet clear. METHODS: Data in this study were collected and screened from the NHANES from 2005 to 2010 and 2013 to 2014. The variables were extracted from interviews and compared between the wrist fractures and the sleep duration. The data was analyzed by weighted multivariate logistic regression. RESULTS: After excluding individuals who were not eligible and had invalid data, we finally identified 1835 participants for inclusion in this study. We found a negative association between the sleep duration and the fractured of the wrist (OR = 1.027,95% CI (1.027, 1.028), P < 0.00001). CONCLUSION: This study demons that the association between the sleep duration and the fractures of the wrist is significant. Our findings provide a better understanding of the relationship between sleep duration and wrist fractures. This study may help us reducing the incidence of wrist fractures in the population based on healthy sleep management in the future, and improve the quality of life of middle-aged and elderly patients. Provide evidence for clinical patients to manage healthy sleep.
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Inquéritos Nutricionais , Duração do Sono , Traumatismos do Punho , Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Transversais , Fraturas Ósseas/epidemiologia , Incidência , Fatores de Risco , Fatores de Tempo , Estados Unidos/epidemiologia , Fraturas do Punho , Traumatismos do Punho/epidemiologia , Traumatismos do Punho/fisiopatologiaRESUMO
A large proportion of the heritability of pancreatic cancer risk remains elusive, and the contribution of specific mRNA splicing events to pancreatic cancer susceptibility has not been systematically evaluated. In this study, we performed a large splicing transcriptome-wide association study (spTWAS) using three modeling strategies (Enet, LASSO and MCP) to develop alternative splicing genetic prediction models for identifying novel susceptibility loci and splicing introns for pancreatic cancer risk by assessing 8275 pancreatic cancer cases and 6723 controls of European ancestry. Data from 305 subjects of whom the majority are of European descent in the Genotype-Tissue Expression Project (GTEx) were used and both cis-acting and promoter-enhancer interaction regions were considered to build these models. We identified nine splicing events of seven genes (ABO, UQCRC1, STARD3, ETAA1, CELA3B, LGR4 and SFT2D1) that showed an association of genetically predicted expression with pancreatic cancer risk at a false discovery rate ≤0.05. Of these genes, UQCRC1 and LGR4 have not yet been reported to be associated with pancreatic cancer risk. Fine-mapping analyses supported likely causal associations corresponding to six splicing events of three genes (P4HTM, ABO and PGAP3). Our study identified novel genes and splicing events associated with pancreatic cancer risk, which can improve our understanding of the etiology of this deadly malignancy.
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Neoplasias Pancreáticas , Transcriptoma , Humanos , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Splicing de RNA , Neoplasias Pancreáticas/genética , Processamento Alternativo/genética , Polimorfismo de Nucleotídeo Único/genética , Antígenos de Superfície , Elastase Pancreática/genéticaRESUMO
Alzheimer's disease (AD) is a common neurodegenerative disease in aging individuals. Alternative splicing is reported to be relevant to AD development while their roles in etiology of AD remain largely elusive. We performed a comprehensive splicing transcriptome-wide association study (spTWAS) using intronic excision expression genetic prediction models of 12 brain tissues developed through three modelling strategies, to identify candidate susceptibility splicing introns for AD risk. A total of 111,326 (46,828 proxy) cases and 677,663 controls of European ancestry were studied. We identified 343 associations of 233 splicing introns (143 genes) with AD risk after Bonferroni correction (0.05/136,884 = 3.65 × 10-7). Fine-mapping analyses supported 155 likely causal associations corresponding to 83 splicing introns of 55 genes. Eighteen causal splicing introns of 15 novel genes (EIF2D, WDR33, SAP130, BYSL, EPHB6, MRPL43, VEGFB, PPP1R13B, TLN2, CLUHP3, LRRC37A4P, CRHR1, LINC02210, ZNF45-AS1, and XPNPEP3) were identified for the first time to be related to AD susceptibility. Our study identified novel genes and splicing introns associated with AD risk, which can improve our understanding of the etiology of AD.
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Doença de Alzheimer , Doenças Neurodegenerativas , Humanos , Doença de Alzheimer/genética , Doença de Alzheimer/metabolismo , Transcriptoma , Predisposição Genética para Doença/genética , Splicing de RNA , Polimorfismo de Nucleotídeo Único , Proteínas Repressoras/genética , Fatores de Transcrição Kruppel-Like/genética , Moléculas de Adesão Celular/genéticaRESUMO
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive solid malignancies, which is featured by systematic metabolism. Thus, a better understanding of metabolic dysregulation in PDAC is important to better characterize its etiology. Here, we performed a large metabolome-wide association study (MWAS) to systematically explore associations between genetically predicted metabolite levels in blood and PDAC risk. Using data from 881 subjects of European descent in the TwinsUK Project, comprehensive genetic models were built to predict serum metabolite levels. These prediction models were applied to the genetic data of 8275 cases and 6723 controls included in the PanScan (I, II and III) and PanC4 consortia. After assessing the metabolite-PDAC risk associations by a slightly modified TWAS/FUSION framework, we identified five metabolites (including two dipeptides) showing significant associations with PDAC risk at false discovery rate (FDR) <0.05. Integrated with gut microbial information, two-sample Mendelian randomization (MR) analyses were further performed to investigate the relationship among serum metabolites, gut microbiome features and PDAC. The flavonoid-degrading bacteria Flavonifractor sp90199495 was found to be associated with metabolite X-21849 and it was also shown to be associated with PDAC risk. Collectively, our study identified novel candidate metabolites for PDAC risk, which could lead to new insights into the etiology of PDAC and improved treatment options.
Assuntos
Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/patologia , Carcinoma Ductal Pancreático/patologia , Pâncreas/patologia , Metaboloma/genética , Neoplasias PancreáticasRESUMO
Genetically predicted proteins have been associated with pancreatic cancer risk previously. We aimed to externally validate the associations of 53 candidate proteins with pancreatic cancer risk using directly measured, prediagnostic levels. We conducted a prospective cohort study of 10 355 US Black and White men and women in the Atherosclerosis Risk in Communities (ARIC) study. Aptamer-based plasma proteomic profiling was previously performed using blood collected in 1993 to 1995, from which the proteins were selected. By 2015 (median: 20 years), 93 incident pancreatic cancer cases were ascertained. Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for protein tertiles, and adjust for age, race, and known risk factors. Of the 53 proteins, three were statistically significantly, positively associated with risk-GLCE (tertile 3 vs 1: HR = 1.88, 95% CI: 1.12-3.13; P-trend = 0.01), GOLM1 (aptamer 1: HR = 1.98, 95% CI: 1.16-3.37; P-trend = 0.01; aptamer 2: HR = 1.86, 95% CI: 1.07-3.24; P-trend = 0.05), and QSOX2 (HR = 1.96, 95% CI: 1.09-3.58; P-trend = 0.05); two were inversely associated-F177A (HR = 0.59, 95% CI: 0.35-1.00; P-trend = 0.05) and LIFsR (HR = 0.55, 95% CI: 0.32-0.93; P-trend = 0.03); and one showed a statistically significant lower risk in the middle tertile-endoglin (HR = 0.50, 95% CI: 0.29-0.86); by chance, we expected significant associations for 2.65 proteins. FAM3D, IP10, sTie-1 (positive); SEM6A and JAG1 (inverse) were suggestively associated with risk. Of these 11, 10 proteins-endoglin, FAM3D, F177A, GLCE, GOLM1, JAG1, LIFsR, QSOX2, SEM6A and sTie-1-were consistent in direction of association with the discovery studies. This prospective study validated or supports 10 proteins as associated with pancreatic cancer risk.
Assuntos
Aterosclerose , Neoplasias Pancreáticas , Masculino , Humanos , Feminino , Estudos Prospectivos , Endoglina , Proteômica , Fatores de Risco , Aterosclerose/epidemiologia , Aterosclerose/genética , Neoplasias Pancreáticas/epidemiologia , Neoplasias Pancreáticas/genética , Biomarcadores , Incidência , Modelos de Riscos Proporcionais , Oxirredutases atuantes sobre Doadores de Grupo Enxofre , Proteínas de Membrana , Neoplasias PancreáticasRESUMO
Alzheimer's disease (ad) adversely affects the health, quality of life and independence of patients. There is a critical need to identify novel blood gene biomarkers for ad risk assessment. We performed a transcriptome-wide association study to identify biomarker candidates for ad risk. We leveraged two sets of gene expression prediction models of blood developed using different reference panels and modeling strategies. By applying the prediction models to a meta-GWAS including 71 880 (proxy) cases and 383 378 (proxy) controls, we identified significant associations of genetically determined expression of 108 genes in blood with ad risk. Of these, 15 genes were differentially expressed between ad patients and controls with concordant directions in measured expression data. With evidence from the analyses based on both genetic instruments and directly measured expression levels, this study identifies 15 genes with strong support as biomarkers in blood for ad risk, which may enhance ad risk assessment and mechanism-focused studies.