Identify Regulatory eQTLs by Multiome Sequencing in Prostate Single Cells.

While genome-wide association studies and expression quantitative trait loci (eQTL) analysis have made significant progress in identifying noncoding variants associated with prostate cancer risk and bulk tissue transcriptome changes, the regulatory effect of these genetic elements on gene expression remains largely unknown. Recent developments in single-cell sequencing have made it possible to perform ATAC-seq and RNA-seq profiling simultaneously to capture functional associations between chromatin accessibility and gene expression. In this study, we tested our hypothesis that this multiome single-cell approach allows for mapping regulatory elements and their target genes at prostate cancer risk loci. We applied a 10X Multiome ATAC + Gene Expression platform to encapsulate Tn5 transposase-tagged nuclei from multiple prostate cell lines for a total of 65,501 high quality single cells from RWPE1, RWPE2, PrEC, BPH1, DU145, PC3, 22Rv1 and LNCaP cell lines. To address data sparsity commonly seen in the single-cell sequencing, we performed targeted sequencing to enrich sequencing data at prostate cancer risk loci involving 2,730 candidate germline variants and 273 associated genes. Although not increasing the number of captured cells, the targeted multiome data did improve eQTL gene expression abundance by about 20% and chromatin accessibility abundance by about 5%. Based on this multiomic profiling, we further associated RNA expression alterations with chromatin accessibility of germline variants at single cell levels. Cross validation analysis showed high overlaps between the multiome associations and the bulk eQTL findings from GTEx prostate cohort. We found that about 20% of GTEx eQTLs were covered within the significant multiome associations (p-value ≤ 0.05, gene abundance percentage ≥ 5%), and roughly 10% of the multiome associations could be identified by significant GTEx eQTLs. We also analyzed accessible regions with available heterozygous SNP reads and observed more frequent association in genomic regions with allelically accessible variants (p = 0.0055). Among these findings were previously reported regulatory variants including rs60464856-RUVBL1 (multiome p-value = 0.0099 in BPH1) and rs7247241-SPINT2 (multiome p-value = 0.0002- 0.0004 in 22Rv1). We also functionally validated a new regulatory SNP and its target gene rs2474694-VPS53 (multiome p-value = 0.00956 in BPH1 and 0.00625 in DU145) by reporter assay and SILAC proteomics sequencing. Taken together, our data demonstrated the feasibility of the multiome single-cell approach for identifying regulatory SNPs and their regulated genes.

MIMOSA: a resource consisting of improved methylome prediction models increases power to identify DNA methylation-phenotype associations.

Although DNA methylation (DNAm) has been implicated in the pathogenesis of numerous complex diseases, from cancer to cardiovascular disease to autoimmune disease, the exact methylation sites that play key roles in these processes remain elusive. One strategy to identify putative causal CpG sites and enhance disease etiology understanding is to conduct methylome-wide association studies (MWASs), in which predicted DNA methylation that is associated with complex diseases can be identified. However, current MWAS models are primarily trained using the data from single studies, thereby limiting the methylation prediction accuracy and the power of subsequent association studies. Here, we introduce a new resource, MWAS Imputing Methylome Obliging Summary-level mQTLs and Associated LD matrices (MIMOSA), a set of models that substantially improve the prediction accuracy of DNA methylation and subsequent MWAS power through the use of a large summary-level mQTL dataset provided by the Genetics of DNA Methylation Consortium (GoDMC). Through the analyses of GWAS (genome-wide association study) summary statistics for 28 complex traits and diseases, we demonstrate that MIMOSA considerably increases the accuracy of DNA methylation prediction in whole blood, crafts fruitful prediction models for low heritability CpG sites, and determines markedly more CpG site-phenotype associations than preceding methods. Finally, we use MIMOSA to conduct a case study on high cholesterol, pinpointing 146 putatively causal CpG sites.

Binder-Responsive DNA Strand Displacement Enables High-Throughput and High-Fidelity Discovering of Small Molecular DNA Binders.

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.

Transcriptome-wide association study and Mendelian randomization in pancreatic cancer identifies susceptibility genes and causal relationships with type 2 diabetes and venous thromboembolism.

BACKGROUND: Two important questions regarding the genetics of pancreatic adenocarcinoma (PDAC) are 1. Which germline genetic variants influence the incidence of this cancer; and 2. Whether PDAC causally predisposes to associated non-malignant phenotypes, such as type 2 diabetes (T2D) and venous thromboembolism (VTE). METHODS: In this study of 8803 patients with PDAC and 67,523 controls, we first performed a large-scale transcriptome-wide association study to investigate the association between genetically determined gene expression in normal pancreas tissue and PDAC risk. Secondly, we used Mendelian Randomization (MR) to analyse the causal relationships among PDAC, T2D (74,124 cases and 824,006 controls) and VTE (30,234 cases and 172,122 controls). FINDINGS: Sixteen genes showed an association with PDAC risk (FDR <0.10), including six genes not yet reported for PDAC risk (PPIP5K2, TFR2, HNF4G, LRRC10B, PRC1 and FBXL20) and ten previously reported genes (INHBA, SMC2, ABO, PDX1, MTMR6, ACOT2, PGAP3, STARD3, GSDMB, ADAM33). MR provided support for a causal effect of PDAC on T2D using genetic instruments in the HNF4G and PDX1 loci, and unidirectional causality of VTE on PDAC involving the ABO locus (OR 2.12, P < 1e-7). No evidence of a causal effect of PDAC on VTE was found. INTERPRETATION: These analyses identified candidate susceptibility genes and disease relationships for PDAC that warrant further investigation. HNF4G and PDX1 may induce PDAC-associated diabetes, whereas ABO may induce the causative effect of VTE on PDAC. FUNDING: National Institutes of Health (USA).

Genetic Evidence for a Causal Link between Intra-Pancreatic Fat Deposition and Pancreatitis: a Mendelian Randomization Study.

Introduction: Recent associative studies have linked intra-pancreatic fat deposition (IPFD) with risk of pancreatitis, but the causal relationship remains unclear. Methods: Utilizing Mendelian randomization, we evaluated the causal association between genetically predicted IPFD and pancreatitis. This approach utilized genetic variants from genome-wide association studies of IPFD (n=25,617), acute pancreatitis (n=6,787 cases/361,641 controls), and chronic pancreatitis (n=3,875 cases/361,641 controls). Results: Genetically predicted IPFD was significantly associated with acute pancreatitis (OR per 1-SD increase: 1.40[95%CI:1.12-1.76], p=0.0032) and chronic pancreatitis (OR:1.64[95%CI:1.13-2.39], p=0.0097). Discussion: Our findings support a causal role of IPFD in pancreatitis, suggesting that reducing IPFD could lower the risk of pancreatitis.

Analysis of the relationship between shorter sleep duration and wrist fractures: based on NHANES.

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.

Triglyceride-glucose index and health outcomes: an umbrella review of systematic reviews with meta-analyses of observational studies.

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.

ABO and Rhesus blood groups and multiple health outcomes: an umbrella review of systematic reviews with meta-analyses of observational studies.

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.

Improved multi-ancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk.

Multi-ancestry statistical fine-mapping of cis-molecular quantitative trait loci (cis-molQTL) aims to improve the precision of distinguishing causal cis-molQTLs from tagging variants. However, existing approaches fail to reflect shared genetic architectures. To solve this limitation, we present the Sum of Shared Single Effects (SuShiE) model, which leverages LD heterogeneity to improve fine-mapping precision, infer cross-ancestry effect size correlations, and estimate ancestry-specific expression prediction weights. We apply SuShiE to mRNA expression measured in PBMCs (n=956) and LCLs (n=814) together with plasma protein levels (n=854) from individuals of diverse ancestries in the TOPMed MESA and GENOA studies. We find SuShiE fine-maps cis-molQTLs for 16% more genes compared with baselines while prioritizing fewer variants with greater functional enrichment. SuShiE infers highly consistent cis-molQTL architectures across ancestries on average; however, we also find evidence of heterogeneity at genes with predicted loss-of-function intolerance, suggesting that environmental interactions may partially explain differences in cis-molQTL effect sizes across ancestries. Lastly, we leverage estimated cis-molQTL effect-sizes to perform individual-level TWAS and PWAS on six white blood cell-related traits in AOU Biobank individuals (n=86k), and identify 44 more genes compared with baselines, further highlighting its benefits in identifying genes relevant for complex disease risk. Overall, SuShiE provides new insights into the cis-genetic architecture of molecular traits.

An early-onset specific polygenic risk score optimizes age-based risk estimate and stratification of prostate cancer: population-based cohort study.

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.

Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC. SIGNIFICANCE: PDAC is a notoriously difficult-to-treat malignancy, and our limited understanding of causal protein markers hampers progress in developing effective early detection strategies and treatments. Our study identifies novel causal proteins using genetic instruments and subsequently functionally validates selected novel proteins. This dual approach enhances our understanding of PDAC etiology and potentially opens new avenues for therapeutic interventions.

Species distribution modeling combined with environmental DNA analysis to explore distribution of invasive alien mosquitofish (Gambusia affinis) in China.

China has become one of the most serious countries suffering from biological invasions in the world. In the context of global climate change, invasive alien species (IAS) are likely to invade a wider area, posing greater ecological and economic threats in China. Western mosquitofish (Gambusia affinis), which is known as one of the 100 most invasive alien species, has distributed widely in southern China and is gradually spreading to the north, causing serious ecological damage and economic losses. However, its distribution in China is still unclear. Hence, there is an urgent need for a more convenient way to detect and monitor the distribution of G. affinis to put forward specific management. Therefore, we detected the distribution of G. affinis in China under current and future climate change by combing Maxent modeling prediction and eDNA verification, which is a more time-saving and reliable method to estimate the distribution of species. The Maxent modeling showed that G. affinis has a broad habitat suitability in China (especially in southern China) and would continue to spread in the future with ongoing climate change. However, eDNA monitoring showed that occurrences can already be detected in regions that Maxent still categorized as unsuitable. Besides temperature, precipitation and human influence were the most important environmental factors affecting the distribution of G. affinis in China. In addition, by environmental DNA analysis, we verified the presence of G. affinis predicted by Maxent in the Qinling Mountains where the presence of G. affinis had not been previously recorded.

Intermittent fasting and health outcomes: an umbrella review of systematic reviews and meta-analyses of randomised controlled trials.

Background: Benefits of Intermittent fasting (IF) on health-related outcomes have been found in a range of randomised controlled trials (RCTs). Our umbrella review aimed to systematically analyze and synthesize the available causal evidence on IF and its impact on specific health-related outcomes while evaluating its evidence quality. Methods: We comprehensively searched the PubMed, Embase, Web of Science, and Cochrane databases (from inception up to 8 January 2024) to identify related systematic reviews and meta-analyses of RCTs investigating the association between IF and human health outcomes. We recalculated the effect sizes for each meta-analysis as mean difference (MD) or standardized mean difference (SMD) with corresponding 95% confidence intervals (CIs). Subgroup analyses were performed for populations based on three specific status: diabetes, overweight or obesity, and metabolic syndrome. The quality of systematic reviews was evaluated using A Measurement Tool to Assess Systematic Reviews (AMSTAR), and the certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) system. This study is registered with PROSPERO (CRD42023382004). Findings: A total of 351 associations from 23 meta-analyses with 34 health outcomes were included in the study. A wide range of outcomes were investigated, including anthropometric measures (n = 155), lipid profiles (n = 83), glycemic profiles (n = 57), circulatory system index (n = 41), appetite (n = 9), and others (n = 6). Twenty-one (91%) meta-analyses with 346 associations were rated as high confidence according to the AMSTAR criteria. The summary effects estimates were significant at p < 0.05 in 103 associations, of which 10 (10%) were supported by high certainty of evidence according to GRADE. Specifically, compared with non-intervention diet in adults with overweight or obesity, IF reduced waist circumference (WC) (MD = -1.02 cm; 95% CI: -1.99 to -0.06; p = 0.038), fat mass (MD = -0.72 kg; 95% CI: -1.32 to -0.12; p = 0.019), fasting insulin (SMD = -0.21; 95% CI: -0.40 to -0.02; p = 0.030), low-density lipoprotein cholesterol (LDL-C) (SMD = -0.20; 95% CI: -0.38 to -0.02; p = 0.027), total cholesterol (TC) (SMD = -0.29; 95% CI: -0.48 to -0.10; p = 0.003), and triacylglycerols (TG) (SMD = -0.23; 95% CI: -0.39 to -0.06; p = 0.007), but increased fat free mass (FFM) (MD = 0.98 kg; 95% CI: 0.18-1.78; p = 0.016). Of note, compared with the non-intervention diet, modified alternate-day fasting (MADF) reduced fat mass (MD = -0.70 kg; 95% CI: -1.38 to -0.02; p = 0.044). In people with overweight or obesity, and type 2 diabetes, IF increases high-density lipoprotein cholesterol (HDL-C) levels compared to continuous energy restriction (CER) (MD = 0.03 mmol/L; 95% CI: 0.01-0.05; p = 0.010). However, IF was less effective at reducing systolic blood pressure (SBP) than a CER diet in adults with overweight or obesity (SMD = 0.21; 95% CI: 0.05-0.36; p = 0.008). Interpretation: Our findings suggest that IF may have beneficial effects on a range of health outcomes for adults with overweight or obesity, compared to CER or non-intervention diet. Specifically, IF may decreased WC, fat mass, LDL-C, TG, TC, fasting insulin, and SBP, while increasing HDL-C and FFM. Notably, it is worth noting that the SBP lowering effect of IF appears to be weaker than that of CER. Funding: This work was supported by the National Key Research and Development Program of China (Q-JW), the Natural Science Foundation of China (Q-JW and T-TG), Outstanding Scientific Fund of Shengjing Hospital of China Medical University (Q-JW), and 345 Talent Project of Shengjing Hospital of China Medical University (T-TG).

Pan-cancer analyses of bromodomain containing 9 as a novel therapeutic target reveals its diagnostic, prognostic potential and biological mechanism in human tumours.

BACKGROUND: Mutations in one or more genes responsible for encoding subunits within the SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin-remodelling complexes are found in approximately 25% of cancer patients. Bromodomain containing 9 (BRD9) is a more recently identified protein coding gene, which can encode SWI/SNF chromatin-remodelling complexes subunits. Although initial evaluations of the potential of BRD9-based targeted therapy have been explored in the clinical application of a small number of cancer types, more detailed study of the diagnostic and prognostic potential, as well as the detailed biological mechanism of BRD9 remains unreported. METHODS: We used various bioinformatics tools to generate a comprehensive, pan-cancer analyses of BRD9 expression in multiple disease types described in The Cancer Genome Atlas (TCGA). Experimental validation was conducted in tissue microarrays and cell lines derived from lung and colon cancers. RESULTS: Our study revealed that BRD9 exhibited elevated expression in a wide range of tumours. Analysis of survival data and DNA methylation for BRD9 indicated distinct conclusions for multiple tumours. mRNA splicing and molecular binding were involved in the functional mechanism of BRD9. BRD9 may affect cancer progression through different phosphorylation sites or N6 -methyladenosine site modifications. BRD9 could potentially serve as a novel biomarker for diagnosing different cancer types, especially could accurately forecast the prognosis of melanoma patients receiving anti-programmed cell death 1 immunotherapy. BRD9 has the potential to serve as a therapeutic target, when pairing with etoposide in patients with melanoma. The BRD9/SMARCD1 axis exhibited promising discriminative performance in forecasting the prognosis of patients afflicted with liver hepatocellular carcinoma (LIHC) and mesothelioma. Additionally, this axis appears to potentially influence the immune response in LIHC by regulating the programmed death-ligand 1 immune checkpoint. For experimental validation, high expression levels of BRD9 were observed in tumour tissue samples from both lung and colon cancer patients. Knocking down BRD9 led to the inhibition of lung and colon cancer development, likely via the Wnt/ß-catenin signalling pathway. CONCLUSIONS: These pan-cancer study revealed the diagnostic and prognostic potential, along with the biological mechanism of BRD9 as a novel therapeutic target in human tumours.

Plug-and-Play Module for Reversible and Continuous Control of DNA Strand Displacement Kinetics.

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.

Identification of blood metabolites associated with risk of Alzheimer's disease by integrating genomics and metabolomics data.

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.

Evidence for a causal link between intra-pancreatic fat deposition and pancreatic cancer: A prospective cohort and Mendelian randomization study.

Prior observational studies suggest an association between intra-pancreatic fat deposition (IPFD) and pancreatic ductal adenocarcinoma (PDAC); however, the causal relationship is unclear. To elucidate causality, we conduct a prospective observational study using magnetic resonance imaging (MRI)-measured IPFD data and also perform a Mendelian randomization study using genetic instruments for IPFD. In the observational study, we use UK Biobank data (N = 29,463, median follow-up: 4.5 years) and find that high IPFD (>10%) is associated with PDAC risk (adjusted hazard ratio [HR]: 3.35, 95% confidence interval [95% CI]: 1.60-7.00). In the Mendelian randomization study, we leverage eight out of nine IPFD-associated genetic variants (p < 5 × 10-8) from a genome-wide association study in the UK Biobank (N = 25,617) and find that genetically determined IPFD is associated with PDAC (odds ratio [OR] per 1-standard deviation [SD] increase in IPFD: 2.46, 95% CI: 1.38-4.40) in the Pancreatic Cancer Cohort Consortium I, II, III (PanScan I-III)/Pancreatic Cancer Case-Control Consortium (PanC4) dataset (8,275 PDAC cases and 6,723 non-cases). This study provides evidence for a potential causal role of IPFD in the pathogenesis of PDAC. Thus, reducing IPFD may lower PDAC risk.

Associations between genetically predicted plasma protein levels and Alzheimer's disease risk: a study using genetic prediction models.

BACKGROUND: Specific peripheral proteins have been implicated to play an important role in the development of Alzheimer's disease (AD). However, the roles of additional novel protein biomarkers in AD etiology remains elusive. The availability of large-scale AD GWAS and plasma proteomic data provide the resources needed for the identification of causally relevant circulating proteins that may serve as risk factors for AD and potential therapeutic targets. METHODS: We established and validated genetic prediction models for protein levels in plasma as instruments to investigate the associations between genetically predicted protein levels and AD risk. We studied 71,880 (proxy) cases and 383,378 (proxy) controls of European descent. RESULTS: We identified 69 proteins with genetically predicted concentrations showing associations with AD risk. The drugs almitrine and ciclopirox targeting ATP1A1 were suggested to have a potential for being repositioned for AD treatment. CONCLUSIONS: Our study provides additional insights into the underlying mechanisms of AD and potential therapeutic strategies.

SH3RF2 contributes to cisplatin resistance in ovarian cancer cells by promoting RBPMS degradation.

Platinum-based chemotherapy remains one of the major choices for treatment of ovarian cancer (OC). However, primary or acquired drug resistance severely impairs their efficiency, thereby causing chemotherapy failure and poor prognosis. SH3 domain containing ring finger 2 (SH3RF2) has been linked to the development of cancer. Here we find higher levels of SH3RF2 in the tumor tissues from cisplatin-resistant OC patients when compared to those from cisplatin-sensitive patients. Similarly, cisplatin-resistant OC cells also express higher levels of SH3RF2 than normal OC cells. Through in vitro and in vivo loss-of-function experiments, SH3RF2 is identified as a driver of cisplatin resistance, as evidenced by increases in cisplatin-induced cell apoptosis and DNA damage and decreases in cell proliferation induced by SH3RF2 depletion. Mechanistically, SH3RF2 can directly bind to the RNA-binding protein mRNA processing factor (RBPMS). RBPMS has been reported as an inhibitor of cisplatin resistance in OC. As a E3 ligase, SH3RF2 promotes the K48-linked ubiquitination of RBPMS to increase its proteasomal degradation and activator protein 1 (AP-1) transactivation. Impairments in RBPMS function reverse the inhibitory effect of SH3RF2 depletion on cisplatin resistance. Collectively, the SH3RF2-RBPMS-AP-1 axis is an important regulator in cisplatin resistance and inhibition of SH3RF2 may be a potential target in preventing cisplatin resistance.