Colocalization Analysis Research Articles

Metabolically activated and highly polyfunctional intratumoral VISTA+ regulatory B cells are associated with tumor recurrence in early-stage NSCLC

B cells have emerged as central players in the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC). However, although there is clear evidence for their involvement in cancer immunity, scanty data exist on the characterization of B cell phenotypes, bioenergetic profiles and possible interactions with T cells in the context of NSCLC. In this study, using polychromatic flow cytometry, mass cytometry, and spatial transcriptomics we explored the intricate landscape of B cell phenotypes, bioenergetics, and their interaction with T cells in NSCLC. Our analysis revealed that TME contains diverse B cell clusters, including VISTA+ Bregs, with distinct metabolic and functional profiles. Target liquid chromatography-tandem mass spectrometry confirmed the expression of VISTA on B cells. VISTA+ Bregs displayed high metabolic demand and were able to produce different cytokines, including interleukin (IL)-10, transforming growth factor (TGF)-β, IL-6, tumor necrosis factor (TNF), and granulocyte–macrophage colony-stimulating factor (GM-CSF). Spatial analysis showed colocalization of B cells with CD4+/CD8+ T lymphocytes in TME. The computational analysis of intercellular communications that links ligands to target genes, performed by NicheNet, predicted B-T interactions via VISTA-PSGL-1 axis. Colocalization analyses revealed that PSGL-1 T cells and VISTA+ B cells are adjacent in the TME. Notably, tumor infiltrating CD8+ T cells expressing PSGL-1 exhibited enhanced metabolism and cytotoxicity. In NSCLC patients, prediction analysis performed by PENCIL revealed the presence of an association between PSGL-1+CD8+ T cells and VISTA+ Bregs with lung recurrence. Our findings suggest a potential interaction between Bregs and T cells through the VISTA-PSGL-1 axis, that could influence NSCLC recurrence.

Multi-omic quantitative trait loci link tandem repeat size variation to gene regulation in human brain.

Tandem repeat (TR) size variation is implicated in ~50 neurological disorders, yet its impact on gene regulation in the human brain remains largely unknown. In the present study, we quantified the impact of TR size variation on brain gene regulation across distinct molecular phenotypes, based on 4,412 multi-omics samples from 1,597 donors, including 1,586 newly sequenced ones. We identified ~2.2 million TR molecular quantitative trait loci (TR-xQTLs), linking ~139,000 unique TRs to nearby molecular phenotypes, including many known disease-risk TRs, such as the G2C4 expansion in C9orf72 associated with amyotrophic lateral sclerosis. Fine-mapping revealed ~18,700 TRs as potential causal variants. Our in vitro experiments further confirmed the causal and independent regulatory effects of three TRs. Additional colocalization analysis indicated the potential causal role of TR variation in brain-related phenotypes, highlighted by a 3'-UTR TR in NUDT14 linked to cortical surface area and a TG repeat in PLEKHA1, associated with Alzheimer's disease.

Potential drug targets for asthma identified through mendelian randomization analysis

BackgroundThe emergence of new molecular targeted drugs marks a breakthrough in asthma treatment, particularly for severe cases. Yet, options for moderate-to-severe asthma treatment remain limited, highlighting the urgent need for novel therapeutic drug targets. In this study, we aimed to identify new treatment targets for asthma using the Mendelian randomization method and large-scale genome-wide association data (GWAS).MethodsWe utilized GWAS data from the UK Biobank (comprising 56,167 patients and 352,255 control subjects) and the FinnGen cohort (including 23,834 patients and 228,085 control subjects). Genetic instruments for 734 plasma proteins and 154 cerebrospinal fluid proteins were derived from recently published GWAS. Bidirectional Mendelian randomization analysis, Steiger filtering, colocalization, and phenotype scanning were employed for reverse causal inference detection, further substantiating the Mendelian randomization results. A protein-protein interaction network was also constructed to reveal potential associations between proteins and asthma medications.ResultsUnder Bonferroni significance conditions, Mendelian randomization analysis revealed causal relationships between seven proteins and asthma. In plasma, we observed that an increase of one standard deviation in IL1R1[1.30 (95% CI 1.20–1.42)], IL7R[1.07 (95% CI 1.04–1.11)], ECM1[1.03 (95% CI 1.02–1.05)], and CD200R1[1.18 (95% CI 1.09–1.27)] were associated with an increased risk of asthma, while an increase in ADAM19 [0.87 (95% CI 0.82–0.92)] was found to be protective. In the brain, each 10-fold increase in IL-6 sRa [1.29 (95% CI 1.15–1.45)] was associated with an increased risk of asthma, while an increase in Layilin [0.61 (95% CI 0.51–0.73)] was found to be protective. None of the seven proteins exhibited a reverse causal relationship. Colocalization analysis indicated that ECM1 (coloc.abf-PPH4 = 0.953), IL-6 sRa (coloc.abf-PPH4 = 0.966), and layilin (coloc.abf-PPH4 = 0.975) shared the same genetic variation as in asthma.ConclusionA causal relationship exists between genetically determined protein levels of IL1R1, IL7R, ECM1, CD200R1, ADAM19, IL-6 sRa, and Layilin (LAYN) and asthma. Moreover, the identified proteins may serve as attractive drug targets for asthma, especially ECM1 and Layilin (LAYN). However, further research is required to comprehensively understand the roles of these proteins in the occurrence and progression of asthma.

Possible linking and treatment between Parkinson’s disease and inflammatory bowel disease: a study of Mendelian randomization based on gut–brain axis

BackgroundMounting evidence suggests that Parkinson’s disease (PD) and inflammatory bowel disease (IBD) are closely associated and becoming global health burdens. However, the causal relationships and common pathogeneses between them are uncertain. Furthermore, they are uncurable. Thus, we aimed to identify the causal relationships and novel therapeutic targets shared between them based on their common pathophysiological mechanisms in gut–brain-axis (GBA).MethodsA meta-analysis on bidirectional Mendelian randomization (MR) utilizing various datasets was performed to estimate their causal relationship. Then, pleiotropic analysis under the composite null hypothesis (PLACO) with functional mapping combined with annotation of genetic associations (FUMA) analysis were conducted to identify pleiotropic genes. Next, blood, brain and intestine expression quantitative trait locus (eQTL) were taken to perform drug-target MR finding common causal genes in two diseases. Colocalization analysis ensured the eQTLs of corresponding gene colocalized with disease. Enrichment analysis and protein‒protein interaction (PPI) network were done to explore common pathogenesis pathways. Genes passed all analysis were regarded as drug targets.ResultsOur MR meta-analysis revealed the bidirectional causal relationship between diseases, with combined ORs for PD on IBD, CD, UC (1.050 [95% CI 1.014–1.086], 1.044 [95% CI 0.995–1.095], 1.063 [95% CI 1.016–1.120]); for IBD, CD, UC on PD (1.003 [95% CI 0.973–1.034], 1.035 [95% CI 1.004–1.067], 1.008 [95% CI 0.977–1.040]). Overall, 277, 216 and 201 genes were identified as pleiotropic genes between PD and IBD, CD, UC. Total of 733 genes were classified as tier 3 (found in only one tissue) druggable targets, 57 as tier 2 (found in two tissues, 51 protein-coding genes) and 9 as tier 3 (found in three tissues). Among 60 protein-coding druggable targets over tier 2, 18 overlapped with pleiotropic genes and enriched in mitochondria, antigen presentation, processing and immune cell regulation pathways. Three druggable genes (LRRK2, RAB29 and HLA-DQA2) passed colocalization analysis. LRRK2 and RAB29 were reported to be pleiotropic genes, and RAB29 and HLA-DQA2 were reported for the first time as potential drug targets.ConclusionsThis study established a reliable causal relationship, possible shared drug targets and common pathogenesis pathways of two diseases, which had important implications for intervention and treatment of two diseases simultaneously.

Association of antihypertensive drug target genes with alzheimer’s disease: a mendelian randomization study

BackgroundEpidemiological and genetic studies have elucidated associations between antihypertensive medication and Alzheimer’s disease (AD), with the directionality of these associations varying upon the specific class of antihypertensive agents.MethodsGenetic instruments for the expression of antihypertensive drug target genes were identified using expression quantitative trait loci (eQTL) in blood, which are associated with systolic blood pressure (SBP). Exposure was derived from existing eQTL data in blood from the eQTLGen consortium and in the brain from the PsychENCODE and subsequently replicated in GTEx V8 and BrainMeta V2. We performed two-sample Mendelian randomization (MR) to estimate the potential effect of different antihypertensive drug classes on AD using summary statistics from a meta-analysis (111,326 cases and 677,663 controls) and further replicated in FinnGen cohorts (9301 cases and 367,976 controls). The reverse causality detection, assessing horizontal pleiotropy, Bayesian co-localization, phenotype scanning, and protein quantitative trait loci (pQTL) analysis were implemented to consolidate the MR findings further.ResultsA 1-standard deviation (SD) lower expression of the angiotensin-converting enzyme (ACE) gene in blood was associated with a lower SBP of 3.92 (95% confidence interval (CI), 2.69–5.15) mmHg but an increased risk of AD (odds ratio (OR), 2.46; 95% CI, 1.82–3.33). A similar direction of association was also observed between ACE expression in prefrontal cortex (OR, 1.19; 95% CI, 1.10–1.28), frontal cortex (OR, 1.19; 95% CI, 1.11–1.27), cerebellum (OR, 1.13; 95% CI, 1.09–1.17), cortex (OR, 1.59; 95% CI, 1.33–1.28) and ACE protein levels in plasma (OR, 1.13; 95% CI, 1.09–1.17) and AD risk. Colocalization supports these results. Similar results were found in external validation. We found no evidence for an association between genetically estimated blood pressure (BP) and AD risk.ConclusionsThere findings suggest an adverse association of lower ACE messenger RNA and protein levels with an elevated risk of AD, irrespective of its BP-lowering effects. These findings warrant greater pharmacovigilance and further investigation into the effect of ACE inhibitors, particularly those that are centrally acting, on neurodegenerative symptoms in patients with AD.

Integrative proteogenomic analyses provide novel interpretations of type 1 diabetes risk loci through circulating proteins

Circulating proteins may be promising biomarkers or drug targets. Leveraging genome-wide association studies of type 1 diabetes (18,942 cases and 501,638 controls of European ancestry) and circulating protein abundances (10,708 European ancestry individuals), Mendelian randomization analyses were conducted to assess the associations between circulating abundances of 1,560 candidate proteins and the risk of type 1 diabetes, followed by multiple sensitivity and colocalization analyses, horizontal pleiotropy examinations, and replications. Bulk tissue and single-cell gene expression enrichment analyses were performed to explore candidate tissues and cell types for prioritized proteins. After validating Mendelian randomization assumptions and colocalization evidence, we found that genetically predicted circulating abundances of CTSH (OR=1.17 per one standard deviation increase; 95% CI:1.10-1.24), IL27RA (OR=1.13; 95% CI:1.07-1.19), SIRPG (OR=1.37; 95% CI:1.26-1.49), and PGM1 (OR=1.66; 95% CI:1.40-1.96) were associated with the risk of type 1 diabetes. These findings were consistently replicated in other cohorts. CTSH, IL27RA, and SIRPG were strongly enriched in immune system-related tissues, while PGM1 was enriched in muscle and liver tissues. Amongst immune cells, CTSH was enriched in B cells and myeloid cells, while SIRPG was enriched in T cells and natural killer cells. These proteins may be explored as biomarkers or drug targets for type 1 diabetes.

Identification of therapeutic target genes for age-related hearing loss through systematic genome-wide mendelian randomization of druggable genes.

Age-related hearing loss (ARHL) is a common sensory disorder with significant public health implications. However, few effective treatment options are available. Mendelian randomization (MR) has been used to repurpose existing drugs and identify new therapeutic targets. Therefore, we performed a systematic genome-wide MR of drug-eligible individuals to explore potential therapeutic targets for ARHL. We obtained data on the expression quantitative trait locis (eQTLs) of druggable genes, which were then subjected to two-sample MR analyses and co-localisation analyses with data from the ARHL genome-wide association study to identify genes highly associated with ARHL. Additionally, we conducted phenome-wide research, enrichment analysis, protein network construction, drug prediction, and molecular docking to help develop more effective and targeted therapeutic treatments. Overall, the MR analysis of eQTL data showed that 14 drug targets were significantly associated with ARHL. GO analysis of 14 potential targets revealed their primary involvement in biological processes such as the endoplasmic reticulum unfolded protein response, ER-nucleus signaling pathway, and fibroblast apoptotic process. Additionally, important cellular components include the Bcl-2 family of proteins and the endoplasmic reticulum lumen. After filtering using methods such as phenome-wide research, enrichment analysis, protein network construction, drug prediction, and molecular docking, six potentially druggable genes (BAK1, AMFR, LAMP3, STK17B, ACP5, and CD9) and six drugs (beclomethasone, propyl pyrazole triol, momelotinib, monoisoamyl-2,3-dimercaptosuccinate, pterostilbene, and naftidrofuryl) that may affect ARHL outcomes were finally identified. Our findings identified 14 potential drug targets for ARHL. These findings offer promising leads for more effective treatments for ARHL and help determine the priority of drug development, potentially reducing costs.

Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank

Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, we use deep learning to measure bone marrow adiposity in the femoral head, total hip, femoral diaphysis, and spine from MRI scans of approximately 47,000 UK Biobank participants, including over 41,000 white and over 6300 non-white participants. We then establish the heritability and genome-wide significant associations for bone marrow adiposity at each site. Our meta-GWAS in the white population finds 67, 147, 134, and 174 independent significant single nucleotide polymorphisms, which map to 54, 90, 43, and 100 genes for the femoral head, total hip, femoral diaphysis, and spine, respectively. Transcriptome-wide association studies, colocalization analyses, and sex-stratified meta-GWASes in the white participants further resolve functional and sex-specific genes associated with bone marrow adiposity at each site. Finally, we perform a multi-ancestry meta-GWAS to identify genes associated with bone marrow adiposity across the different bone regions and across ancestry groups. Our findings provide insights into BMAT formation and function and provide a basis to study the impact of BMAT on human health and disease.

A cross-tissue transcriptome-wide association study identifies new key genes in ischemic stroke.

Ischemic stroke (IS) is an important disease causing death and disability worldwide, and further investigation of IS-related genes through genome-wide association study (GWAS) data is valuable. The study included GWAS data from 62,100 IS patients of European origin and 1,234,808 controls in a cross-tissue transcriptome association study (TWAS). A joint analysis was first performed by the Unified Test for Molecular Markers (UTMOST) and FUSION methods. The results of the joint analysis were also validated by fine-mapping through FOCUS. Mendelian randomisation analysis was performed to determine whether the obtained genes were causally related to IS. Genome Annotated Multiple Marker Analysis (MAGMA) explored which biological functions the genes associated with IS. We used Coloc to co-localise GWAS and eQTL of the genes. We also biologically validated the results by Western blotting and immunofluorescence staining in the middle cerebral artery occlusion/reperfusion (MCAO/R) mouse model. Four TWAS methods identified only one new susceptibility gene (USP38) associated with IS risk. Mendelian randomization and colocalization analysis found that USP38 may be protective against IS development. Functional enrichment analysis indicated IS-related genes were mainly associated with the intrinsic fibrinogen activation, acute myocardial infarction, exogenous fibrinogen activation, coagulation cascade response, TNF signalling pathway and GRB2 signalling pathway. Western blotting and immunofluorescence staining demonstrated a reduction in USP38 expression in MCAO/R mice. Our research indicates that USP38 is an essential gene related to IS, with its expression strongly connected with IS risk, thus providing new perspectives on the genetic framework of IS.

Investigating causal relationships of blood and urine biomarkers with urological cancer risks: a mendelian randomization study and colocalization analyses.

Background: Establishing the causal links between biomarkers and cancer enhances understanding of risk factors and facilitates the discovery of therapeutic targets. To this end, we used Mendelian randomization (MR) and colocalization analysis to explore the causal relationship of blood and urinary biomarkers (BUBs) with urological cancers (UCs). Methods: First, we used a two-sample MR study to explore the causal relationship between 33 BUBs and 4 UCs, while we performed reverse Mendelian randomization. After Bonferroni correction, for BUB and UC with significant causality we confirmed the direct causality by multivariate MR adjusting for relevant risk factors. We also applied two-step MR analysis to further explore the possible mediators between BUB and UC with significant causality, while colocalization analysis was performed for BUB, UC and possible mediators. Sensitivity analysis were performed to assess the robustness of the results. Results: A two-sample MR study found that there were 8 BUBs of CA, IGF-1, LPA, TP, CRE, BILD, TBIL and NAP with potential causality with some UCs (p<0.05), but after Bonferroni correction only IGF-1 had a significant causality with PCa (OR = 1.14, 95% CI: 1.06-1.23; p=0.0006<0.05/33). Moreover, the causal relationship between IGF-1 and PCa remained significant (P<0.05) after adjusting for relevant risk factors in the multivariate MR study. The two-step MR study found SHBG to be a mediator between IGF-1 and PCa, and the colocalization analysis found that there was a common causal variant (nearby gene TNS3) between IGF-1 and SHBG (PPH4=93.21%), which further confirmed the mediating effect of SHBG. Conclusion: Strong evidence from our study suggests that IGF-1 increases the risk of PCa by decreasing SHBG levels, and in addition some BUBs were found to have a potential causal relationship with UCs.

Proximity Labelling to Quantify Kv7.4 and Dynein Protein Interaction in Freshly Isolated Rat Vascular Smooth Muscle Cells.

Understanding protein-protein interactions is crucial for unravelling subcellular protein distribution, contributing to our understanding of cellular organisation. Moreover, interaction studies can reveal insights into the mechanisms that cover protein trafficking within cells. Although various techniques such as Förster resonance energy transfer (FRET), co-immunoprecipitation, and fluorescence microscopy are commonly employed to detect protein interactions, their limitations have led to more advanced techniques such as the in situ proximity ligation assay (PLA) for spatial co-localisation analysis. The PLA technique, specifically employed in fixed cells and tissues, utilises species-specific secondary PLA probes linked to DNA oligonucleotides. When proteins are within 40 nm of each other, the DNA oligonucleotides on the probes interact, facilitating circular DNA formation through ligation. Rolling-circle amplification then produces DNA circles linked to the PLA probe. Fluorescently labelled oligonucleotides hybridise to the circles, generating detectable signals for precise co-localisation analysis. We employed PLA to examine the co-localisation of dynein with the Kv7.4 channel protein in isolated vascular smooth muscle cells from rat mesenteric arteries. This method enabled us to investigate whether Kv7.4 channels interact with dynein, thereby providing evidence of their retrograde transport by the microtubule network. Our findings illustrate that PLA is a valuable tool for studying potential novel protein interactions with dynein, and the quantifiable approach offers insights into whether these interactions are changed in disease.

Integrative Multi-Omics Analysis of Crohn's Disease and Metabolic Syndrome: Unveiling the Underlying Molecular Mechanisms of Comorbidity

ObjectivesThe focus of this study is on identifying a potential association between Crohn's disease (CD), a chronic inflammatory bowel condition, and metabolic syndrome (Mets), characterized by a cluster of metabolic abnormalities, including high blood pressure, abnormal lipid levels, and overweight. While the link between CD and MetS has been suggested in the medical community, the underlying molecular mechanisms remain largely unexplored. MethodsUsing microarray data from the Gene Expression Omnibus (GEO) database, we conducted a differential gene expression analysis and applied Weighted Gene Co-expression Network Analysis (WGCNA) to identify genes shared between CD and MetS. To further elucidate the functions of these shared genes, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and constructed protein-protein interaction (PPI) networks. For key gene screening, we used Random Forest and Least Absolute Shrinkage and Selection Operator (LASSO) regression and constructed a diagnostic prediction model with the Extreme Gradient Boosting (XGBoost) algorithm. Additionally, CIBERSORT and Gene Set Variation Analysis (GSVA) were employed to examine the relationships between these genes and immune cell infiltration, as well as metabolic pathways. Mendelian randomization and colocalization analyses were also conducted to explore causal links between genes and disease. Lastly, single-cell RNA sequencing (scRNA-seq) was used to validate the functionality of these key genes. ResultsThrough the use of the limma R package and WGCNA, we identified 1,767 co-expressed genes common to both CD and MetS, which are notably enriched in pathways related to immune responses and metabolic regulation. After thorough analysis, 34 key genes were highlighted, demonstrating their potential utility in prognostic models. These genes were closely linked to tissue immune responses and metabolic functions. Subsequent scRNA-seq analysis confirmed the strong diagnostic potential of PIM2 and PBX2, with especially prominent expression in T and B cells. ConclusionThis study identifies shared regulatory genes between CD and MetS, advancing the development of precise diagnostic tools. In particular, PIM2 and PBX2 were found to be positively associated with hypoxia and hemoglobin metabolism pathways, suggesting their involvement in the modulation of cellular processes. These findings improve our understanding of the molecular mechanisms underlying the comorbidity of CD and MetS, offering novel targets for integrated therapeutic interventions.

Discovery and exploration of adaptive immune response-related drug targets in diabetic retinopathy by Mendelian randomization

Discovery and exploration of adaptive immune response-related drug targets in diabetic retinopathy by Mendelian randomization

Optical molecular imaging in oral- and oropharyngeal squamous cell carcinoma using a novel uPAR-targeting near-infrared imaging agent FG001 (ICG-Glu-Glu-AE105): An explorative phase II clinical trial.

Background: In oral and oropharyngeal squamous cell carcinoma (OSCC, OPSCC), frequent inadequate surgical margins highlight the importance of precise intraoperative identification and delineation of cancerous tissue for improving patient outcomes. Methods: A prospective, open-label, single-center, single dose, exploratory phase II clinical trial (EudraCT 2022-001361-12) to assess the efficacy of the novel uPAR-targeting near-infrared imaging agent, FG001, for intraoperative detection of OSCC and OPSCC. Macroscopic tumor detection was quantified with sensitivity and intraoperative tumor-to-background ratio (TBR). Microscopic tumor-specificity was assessed by analysis of morphological co-localization between tumor tissue, uPAR-expression, and optical signal. Blood samples were collected up to 44 hours post-injection to further characterize the pharmacokinetic profile of the agent. The trial was conducted with close safety monitoring. Results: Sixteen patients undergoing primary surgical resection were systemically administered 36 mg (n = 4), 16 mg (n = 8), or 4 mg (n = 4) of FG001 the evening prior to surgery. Intraoperatively, using a near-infrared imaging system, real-time optical imaging successfully identified all 16 tumors (sensitivity: 100%, mean TBR: 2.99 range: 2.02 - 3.95), and tumor-specificity was confirmed by histology. Clinical neck metastasis was detected with optical imaging. The maximal plasma concentrations were measured after 1 hour, and the half-life of FG001 was 12 hours. No drug-related or serious adverse events were observed. Conclusions: FG001 holds great potential for optical molecular imaging of OSCC and OPSCC. Further trials are warranted to explore FG001 for intraoperative margin delineation and as a decision-making tool.

Autophagy Associated Genes (ARGs) -Based Predictive Model AIDPS for Prostate Cancer.

Prostate cancer (PCa) is one of the most common cancers in men worldwide. Autophagy-related genes (ARGs) may play an important role in various biological processes of PCa. The aim of this study was to identify and evaluate autophagy-related features to predict clinical outcomes in patients with PCa. Single-cell sequencing data and RNA sequencing data was included from public GEO and TCGA databases. Cells were clustered and annotated by dimension reduction cluster analysis. Epithelial cells, T cells and fibroblasts were isolated to explore their heterogeneity. Autophagy-related genes were obtained from the HADb database. Survival analysis was conducted by K-M curve, and prognostic risk model was established using 101 machine learning algorithms. In addition, we performed gene colocalisation analysis and Mendelian randomisation analysis. Univariate Cox analysis was used to screen out prognostic genes from DEGs and ARGs in each dataset. Risk model was generated by artificial intelligence-derived prognostic signature (AIDPS), which showed better prognostic performance in every dataset than other published models for PCa. The disease-free period (DFS) of patients in the high-risk group was significantly worse than that in the low-risk group (all p < 0.05). The best model is the Ridge (C-index 0.726). We found significant differences in IC50 values of the Dactinomycin_1811, Dactolisib_1057, Luminespib_1559 and Paclitaxel_1080 between groups. In SNP sites rs2743987 and rs7768988, there was a significant correlation between prostate hyperplasia and prostate cancer. Our ARG-based predictive model AIDPS is a reliable and effective tool for prognosis and treatment of prostate cancer.

Genetically Predicted Gene Expression Effects on Changes in Red Blood Cell and Plasma Polyunsaturated Fatty Acids.

Polyunsaturated fatty acids (PUFAs) including omega-3 and omega-6 are obtained from diet and can be measured objectively in plasma or red blood cells (RBCs) membrane biomarkers, representing different dietary exposure windows. In vivo conversion of omega-3 and omega-6 PUFAs from short- to long-chain counterparts occurs via a shared metabolic pathway involving fatty acid desaturases and elongase. This analysis leveraged genome-wide association study (GWAS) summary statistics for RBC and plasma PUFAs, along with expression quantitative trait loci (eQTL) to estimate tissue-specific genetically predicted gene expression effects for delta-5 desaturase (FADS1), delta-6 desaturase (FADS2), and elongase (ELOVL2) on changes in RBC and plasma biomarkers. Using colocalization, we identified shared variants associated with both increased gene expression and changes in RBC PUFA levels in relevant PUFA metabolism tissues (i.e., adipose, liver, muscle, and whole blood). We observed differences in RBC versus plasma PUFA levels for genetically predicted increase in FADS1 and FADS2 gene expression, primarily for omega-6 PUFAs linoleic acid (LA) and arachidonic acid (AA). The colocalization analysis identified rs102275 to be significantly associated with a 0.69% increase in total RBC membrane-bound LA levels (p = 5.4 × 10-12). Future PUFA genetic studies examining long-term PUFA biomarkers are needed to confirm our results.

Mendelian randomization and genetic pleiotropy analysis for the connection between inflammatory bowel disease and Alzheimer's disease.

The gut-microbiome-brain axis (GMBA) implies the connection between inflammatory bowel disease (IBD) and Alzheimer's disease (AD). We aimed to comprehensively explore the relation between IBD (and its subtypes) and AD, early-onset AD (EOAD) and late-onset AD (LOAD) from a genetic pleiotropy perspective. Relying on summary statistics (N=472,868 for AD, 185,204 for EOAD, 191,061 for LOAD, 59,957 for IBD, 45,975 for CD, and 40,266 for UC), we first performed Mendelian Randomization to examine the causal association between IBD and AD by leveraging vertical pleiotropy. Then, we estimated global and local genetic correlations, followed by cross-trait association analysis to identify SNPs and genes with horizontal pleiotropy. Particularly, we utilized multi-trait colocalization analysis to assess the role of microbes in the common genetic etiology underlying the two types of diseases. Finally, we conducted functional enrichment analysis for pleiotropic genes. We discovered suggestively causal relations between IBD (and its subtypes) and EOAD (ORIBD=1.06 [1.01-1.11], ORCD=1.05 [1.01-1.10], ORUC=1.08 [1.01-1.15]) as well as between UC and LOAD (OR=1.04 [1.01-1.08]), and discovered 44 local regions showing suggestively significant genetic correlations between IBD (and its subtypes) and AD (and EODA and LOAD). We further detected substantial genetic overlap, as characterized by 182 AD-associated, 3 EOAD-associated and 51 LOAD-associated pleiotropic SNPs as well as 291 pleiotropic genes. Pleiotropic genes more likely enriched in the GMBA-relevant tissues such as brain, intestine and esophagus. Moreover, we identified three microorganisms related to these disease pairs, including the Catenibacterium, Clostridia, and Prevotella species. The suggestively causal associations and shared genetic basis between IBD and its subtypes with AD, EOAD and LOAD may commonly drive their co-occurrence, and gut microbes might partly explain the shared genetic etiology. Further studies are warranted to elaborate the possibly biological mechanisms underlying the two types of diseases.

Genetic Commonalities Between Metabolic Syndrome and Rheumatic Diseases Through Disease Interactome Modules.

This study aims to elucidate the potential genetic commonalities between metabolic syndrome (MetS) and rheumatic diseases through a disease interactome network, according to publicly available large-scale genome-wide association studies (GWAS). The analysis included linkage disequilibrium score regression analysis, cross trait meta-analysis and colocalisation analysis to identify common genetic overlap. Using modular partitioning, the network-based association between the two disease proteins in the protein-protein interaction set was divided and quantified. Clinical samples from public databases were used to confirm the mapped genes. Mendelian randomisation analyses were conducted using genetic instrumental variables for causal inference. MetS and rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), Sjogren's syndrome (SS) and their primary module networks shared topological overlap and genetic correlation. Functional analysis highlighted the significance of these shared targets in processes such as a diverse array of metabolic pathways involving glucose, lipids, energy, protein transport, inflammatory response, autophagy and cytokine regulation, elucidating the pathways through which MetS intersects with rheumatic diseases. Causal associations were determined between MetS phenotypes and rheumatic diseases. The persistence of MetS effects on rheumatic diseases remained evident even after adjusting for alcohol consumption and smoking. We have highlighted specific genetic associations between MetS and rheumatic diseases. Several genes (e.g., PRRC2A, PSMB8, BAG6, GPSM3, PBX2, etc.) have been identified with molecular commonalities in MetS and RA, AS, SLE and SS, which may serve as potential targets for shared treatments.

Identification of shared genetic etiology of cardiovascular and cerebrovascular diseases through common cardiometabolic risk factors

Cardiovascular diseases (CVDs) and cerebrovascular diseases (CeVDs) are closely related vascular diseases, sharing common cardiometabolic risk factors (RFs). Although pleiotropic genetic variants of these two diseases have been reported, their underlying pathological mechanisms are still unclear. Leveraging GWAS summary data and using genetic correlation, pleiotropic variants identification, and colocalization analyses, we identified 11 colocalized loci for CVDs-CeVDs-BP (blood pressure), CVDs-CeVDs-LIP (lipid traits), and CVDs-CeVDs-cIMT (carotid intima-media thickness) triplets. No shared causal loci were found for CVDs-CeVDs-T2D (type 2 diabetes) or CVDs-CeVDs-BMI (body mass index) triplets. The 11 loci were mapped to 12 genes, namely CASZ1, CDKN1A, TWIST1, CDKN2B, ABO, SWAP70, SH2B3, LRCH1, FES, GOSR2, RPRML, and LDLR, where both GOSR2 and RPRML were mapped to one locus. They were enriched in pathways related to cellular response to external stimulus and regulation of the phosphate metabolic process and were highly expressed in endothelial cells, epithelial cells, and smooth muscle cells. Multi-omics analysis revealed methylation of two genes (CASZ1 and LRCH1) may play a causal role in the genetic pleiotropy. Notably, these pleiotropic loci are highly enriched in the targets of antihypertensive drugs, which further emphasizes the role of the blood pressure regulation pathway in the shared etiology of CVDs and CeVDs.

A Modular Engineered DNA Nanodevice for Precise Profiling of Telomerase RNA Location and Activity.

Increased telomerase activity has been considered as a conspicuous sign of human cancers. The catalytic cores of telomerase involve a reverse transcriptase and the human telomerase RNA (hTR). However, current detection of telomerase is largely limited to its activity at the tissue and single-cell levels. To reveal the precise distribution of subcellular hTR and telomerase activity, here a modular engineered DNA nanodevice (DNA-ND) is designed capable of imaging hTR and telomerase activity in cytoplasm and nucleus, enabling colocalization analysis. DNA-ND is a modular DNA complex comprising hTR and telomerase activity detection modules, which respectively sense intercellular hTR and telomerase activity via target-sensitive allosteric transition of DNA switches, actuating orthogonal activation of fluorescence signals to achieve in situ co-imaging of hTR and telomerase activity. By integrating DNA-ND with specific localized signals, the DNA-ND based precise profiling of colocalization of hTR and telomerase activity in different cell lines as well as their dynamic changes during pharmacological interventions is demonstrated. Notably, the results suggest that the locations of hTR and telomerase activity are not exactly overlapped, indicating the influence of intracellular environment on the binding of hTR to telomerase.