Liver eQTL meta-analysis illuminates potential molecular mechanisms of cardiometabolic traits.

Understanding the molecular mechanisms of complex traits is essential for developing targeted interventions. We analyzed liver expression quantitative-trait locus (eQTL) meta-analysis data on 1,183 participants to identify conditionally distinct signals. We found 9,013 eQTL signals for 6,564 genes; 23% of eGenes had two signals, and 6% had three or more signals. We then integrated the eQTL results with data from 29 cardiometabolic genome-wide association study (GWAS) traits and identified 1,582 GWAS-eQTL colocalizations for 747 eGenes. Non-primary eQTL signals accounted for 17% of all colocalizations. Isolating signals by conditional analysis prior to coloc resulted in 37% more colocalizations than using marginal eQTL and GWAS data, highlighting the importance of signal isolation. Isolating signals also led to stronger evidence of colocalization: among 343 eQTL-GWAS signal pairs in multi-signal regions, analyses that isolated the signals of interest resulted in higher posterior probability of colocalization for 41% of tests. Leveraging allelic heterogeneity, we predicted causal effects of gene expression on liver traits for four genes. To predict functional variants and regulatory elements, we colocalized eQTL with liver chromatin accessibility QTL (caQTL) and found 391 colocalizations, including 73 with non-primary eQTL signals and 60 eQTL signals that colocalized with both a caQTL and a GWAS signal. Finally, we used publicly available massively parallel reporter assays in HepG2 to highlight 14 eQTL signals that include at least one expression-modulating variant. This multi-faceted approach to unraveling the genetic underpinnings of liver-related traits could lead to therapeutic development.

Alternative polyadenylation quantitative trait methylation mapping in human cancers provides clues into the molecular mechanisms of APA.

Genetic variants are involved in the orchestration of alternative polyadenylation (APA) events, while the role of DNA methylation in regulating APA remains unclear. We generated a comprehensive atlas of APA quantitative trait methylation sites (apaQTMs) across 21 different types of cancer (1,612 to 60,219 acting in cis and 4,448 to 142,349 in trans). Potential causal apaQTMs in non-cancer samples were also identified. Mechanistically, we observed a strong enrichment of cis-apaQTMs near polyadenylation sites (PASs) and both cis- and trans-apaQTMs in proximity to transcription factor (TF) binding regions. Through the integration of ChIP-signals and RNA-seq data from cell lines, we have identified several regulators of APA events, acting either directly or indirectly, implicating novel functions of some important genes, such as TCF7L2, which is known for its involvement in type 2 diabetes and cancers. Furthermore, we have identified a vast number of QTMs that share the same putative causal CpG sites with five different cancer types, underscoring the roles of QTMs, including apaQTMs, in the process of tumorigenesis. DNA methylation is extensively involved in the regulation of APA events in human cancers. In an attempt to elucidate the potential underlying molecular mechanisms of APA by DNA methylation, our study paves the way for subsequent experimental validations into the intricate biological functions of DNA methylation in APA regulation and the pathogenesis of human cancers. To present a comprehensive catalog of apaQTM patterns, we introduce the Pancan-apaQTM database, available at https://pancan-apaqtm-zju.shinyapps.io/pancanaQTM/.

Colocalization analysis of 3' UTR alternative polyadenylation quantitative trait loci reveals novel mechanisms underlying associations with lung function.

While many disease-associated single nucleotide polymorphisms (SNPs) are expression quantitative trait loci (eQTLs), a large proportion of genome-wide association study (GWAS) variants are of unknown function. Alternative polyadenylation (APA) plays an important role in posttranscriptional regulation by allowing genes to shorten or extend 3' untranslated regions (UTRs). We hypothesized that genetic variants that affect APA in lung tissue may lend insight into the function of respiratory associated GWAS loci. We generated alternative polyadenylation (apa) QTLs using RNA sequencing and whole genome sequencing on 1241 subjects from the Lung Tissue Research Consortium (LTRC) as part of the NHLBI TOPMed project. We identified 56 179 APA sites corresponding to 13 582 unique genes after filtering out APA sites with low usage. We found that a total of 8831 APA sites were associated with at least one SNP with q-value < 0.05. The genomic distribution of lead APA SNPs indicated that the majority are intronic variants (33%), followed by downstream gene variants (26%), 3' UTR variants (17%), and upstream gene variants (within 1 kb region upstream of transcriptional start site, 10%). APA sites in 193 genes colocalized with GWAS data for at least one phenotype. Genes containing the top APA sites associated with GWAS variants include membrane associated ring-CH-type finger 2 (MARCHF2), nectin cell adhesion molecule 2 (NECTIN2), and butyrophilin subfamily 3 member A2 (BTN3A2). Overall, these findings suggest that APA may be an important mechanism for genetic variants in lung function and chronic obstructive pulmonary disease (COPD).

MoCoLo: a testing framework for motif co-localization.

Sequence-level data offers insights into biological processes through the interaction of two or more genomic features from the same or different molecular data types. Within motifs, this interaction is often explored via the co-occurrence of feature genomic tracks using fixed-segments or analytical tests that respectively require window size determination and risk of false positives from over-simplified models. Moreover, methods for robustly examining the co-localization of genomic features, and thereby understanding their spatial interaction, have been elusive. We present a new analytical method for examining feature interaction by introducing the notion of reciprocal co-occurrence, define statistics to estimate it and hypotheses to test for it. Our approach leverages conditional motif co-occurrence events between features to infer their co-localization. Using reverse conditional probabilities and introducing a novel simulation approach that retains motif properties (e.g. length, guanine-content), our method further accounts for potential confounders in testing. As a proof-of-concept, motif co-localization (MoCoLo) confirmed the co-occurrence of histone markers in a breast cancer cell line. As a novel analysis, MoCoLo identified significant co-localization of oxidative DNA damage within non-B DNA-forming regions that significantly differed between non-B DNA structures. Altogether, these findings demonstrate the potential utility of MoCoLo for testing spatial interactions between genomic features via their co-localization.

Mendelian randomization and colocalization analysis reveal novel drug targets for myasthenia gravis.

OBJECTIVE: Myasthenia gravis (MG) is a complex autoimmune disease affecting the neuromuscular junction with limited drug options, but the field of MG treatment recently benefits from novel biological agents. We performed a drug-targeted Mendelian randomization (MR) study to identify novel therapeutic targets of MG. METHODS: Cis-expression quantitative loci (cis-eQTL), which proxy expression levels for 2176 druggable genes, were used for MR analysis. Causal relationships between genes and disease, identified by eQTL MR analysis, were verified by comprehensive sensitivity, colocalization, and protein quantitative loci (pQTL) MR analyses. The protein-protein interaction (PPI) analysis was also performed to extend targets, followed by enzyme-linked immunosorbent assay (ELISA) to explore the serum level of drug targets in MG patients. A phenome-wide MR analysis was then performed to assess side effects with a clinical trial review assessing druggability. RESULTS: The eQTL MR analysis has identified eight potential targets for MG, one for early-onset MG and seven for late-onset MG. Further colocalization analyses indicated that CD226, CDC42BPB, PRSS36, and TNFSF12 possess evidence for colocalization with MG or late-onset MG. pQTL MR analyses identified the causal relations of TNFSF12 and CD226 with MG and late-onset MG. Furthermore, PPI analysis has revealed the protein interaction between TNFSF12-TNFSF13(APRIL) and TNFSF12-TNFSF13B(BLyS). Elevated TNFSF13 serum level of MG patients was also identified by ELISA experiments. This study has ultimately proposed three promising therapeutic targets (TNFSF12, TNFSF13, TNFSF13B) of MG. CONCLUSIONS: Three drug targets associated with the BLyS/APRIL pathway have been identified. Multiple biological agents, including telitacicept and belimumab, are promising for MG therapy.

Plasma campesterol and ABCG5/ABCG8 gene loci on the risk of cholelithiasis and cholecystitis: evidence from Mendelian randomization and colocalization analyses.

The causal relationships between plasma metabolites and cholelithiasis/cholecystitis risks remain elusive. Using two-sample Mendelian randomization, we found that genetic proxied plasma campesterol level showed negative correlation with the risk of both cholelithiasis and cholecystitis. Furthermore, the increased risk of cholelithiasis is correlating with the increased level of plasma campesterol. Lastly, genetic colocalization study showed that the leading SNP, rs4299376, which residing at the ABCG5/ABCG8 gene loci, was shared by plasma campesterol level and cholelithiasis, indicating that the aberrant transportation of plant sterol/cholesterol from the blood stream to the bile duct/gut lumen might be the key in preventing cholesterol gallstone formation.

Initiation of acute pancreatitis in mice is independent of fusion between lysosomes and zymogen granules.

The co-localization of the lysosomal protease cathepsin B (CTSB) and the digestive zymogen trypsinogen is a prerequisite for the initiation of acute pancreatitis. However, the exact molecular mechanisms of co-localization are not fully understood. In this study, we investigated the role of lysosomes in the onset of acute pancreatitis by using two different experimental approaches. Using an acinar cell-specific genetic deletion of the ras-related protein Rab7, important for intracellular vesicle trafficking and fusion, we analyzed the subcellular distribution of lysosomal enzymes and the severity of pancreatitis in vivo and ex vivo. Lysosomal permeabilization was performed by the lysosomotropic agent Glycyl-L-phenylalanine 2-naphthylamide (GPN). Acinar cell-specific deletion of Rab7 increased endogenous CTSB activity and despite the lack of re-distribution of CTSB from lysosomes to the secretory vesicles, the activation of CTSB localized in the zymogen compartment still took place leading to trypsinogen activation and pancreatic injury. Disease severity was comparable to controls during the early phase but more severe at later time points. Similarly, GPN did not prevent CTSB activation inside the secretory compartment upon caerulein stimulation, while lysosomal CTSB shifted to the cytosol. Intracellular trypsinogen activation was maintained leading to acute pancreatitis similar to controls. Our results indicate that initiation of acute pancreatitis seems to be independent of the presence of lysosomes and that fusion of lysosomes and zymogen granules is dispensable for the disease onset. Intact lysosomes rather appear to have protective effects at later disease stages.

Colocalization by cross-correlation, a new method of colocalization suited for super-resolution microscopy.

BACKGROUND: A common goal of scientific microscopic imaging is to determine if a spatial correlation exists between two imaged structures. This is generally accomplished by imaging fluorescently labeled structures and measuring their spatial correlation with a class of image analysis algorithms known as colocalization. However, the most commonly used methods of colocalization have strict limitations, such as requiring overlap in the fluorescent markers and reporting requirements for accurate interpretation of the data, that are often not met. Due to the development of novel super-resolution techniques, which reduce the overlap of the fluorescent signals, a new colocalization method is needed that does not have such strict requirements. RESULTS: In order to overcome the limitations of other colocalization algorithms, I developed a new ImageJ/Fiji plugin, Colocalization by cross-correlation (CCC). This method uses cross-correlation over space to identify spatial correlations as a function of distance, removing the overlap requirement and providing more comprehensive results. CCC is compatible with 3D and time-lapse images, and was designed to be easy to use. CCC also generates new images that only show the correlating labeled structures from the input images, a novel feature among the cross-correlating algorithms. CONCLUSIONS: CCC is a versatile, powerful, and easy to use colocalization and spatial correlation tool that is available through the Fiji update sites. Full and up to date documentation can be found at https://imagej.net/plugins/colocalization-by-cross-correlation . CCC source code is available at https://github.com/andmccall/Colocalization_by_Cross_Correlation .

SpaceANOVA: Spatial Co-occurrence Analysis of Cell Types in Multiplex Imaging Data Using Point Process and Functional ANOVA.

Multiplex imaging platforms have enabled the identification of the spatial organization of different types of cells in complex tissue or the tumor microenvironment. Exploring the potential variations in the spatial co-occurrence or colocalization of different cell types across distinct tissue or disease classes can provide significant pathological insights, paving the way for intervention strategies. However, the existing methods in this context either rely on stringent statistical assumptions or suffer from a lack of generalizability. We present a highly powerful method to study differential spatial co-occurrence of cell types across multiple tissue or disease groups, based on the theories of the Poisson point process and functional analysis of variance. Notably, the method accommodates multiple images per subject and addresses the problem of missing tissue regions, commonly encountered due to data-collection complexities. We demonstrate the superior statistical power and robustness of the method in comparison with existing approaches through realistic simulation studies. Furthermore, we apply the method to three real data sets on different diseases collected using different imaging platforms. In particular, one of these data sets reveals novel insights into the spatial characteristics of various types of colorectal adenoma.

Causal effect of gut microbiota on pancreatic cancer: A Mendelian randomization and colocalization study.

The causal relationship between gut microbiota (GM) and pancreatic cancer (PC) remains unclear. This study aimed to investigate the potential genes underlying this mechanism. GM Genome-wide association study (GWAS) summary data were from the MiBioGen consortium. PC GWAS data were from the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) GWAS Catalogue. To detect the causal relationship between GM and PC, we implemented three complementary Mendelian randomization (MR) methods: Inverse Variance Weighting (IVW), MR-Egger and Weighted Median, followed by sensitivity analyses. Furthermore, we integrated GM GWAS data with blood cis-expression quantitative trait loci (eQTLs) and blood cis-DNA methylation QTL (mQTLs) using Summary data-based Mendelian Randomization (SMR) methods. This integration aimed to prioritize potential GM-affecting genes through SMR analysis of two molecular traits. PC cis-eQTLs and cis-mQTLs were summarized from The Cancer Genome Atlas (TCGA) data. Through colocalization analysis of GM cis-QTLs and PC cis-QTLs data, we identified common genes that influence both GM and PC. Our study found a causal association between GM and PC, including four protective and five risk-associated GM [Inverse Variance Weighted (IVW), p < 0.05]. No significant heterogeneity of instrumental variables (IVs) or horizontal pleiotropy was found. The gene SVBP was identified as a GM-affecting gene using SMR analysis of two molecular traits (FDR<0.05, P_HEIDI>0.05). Additionally, two genes, MCM6 and RPS26, were implicated in the interaction between GM and PC based on colocalization analysis (PPH4>0.5). In summary, this study provides evidence for future research aimed at developing suitable therapeutic interventions and disease prevention.

Cis-eQTLs in seven duck tissues identify novel candidate genes for growth and carcass traits.

BACKGROUND: Expression quantitative trait loci (eQTL) studies aim to understand the influence of genetic variants on gene expression. The colocalization of eQTL mapping and GWAS strategy could help identify essential candidate genes and causal DNA variants vital to complex traits in human and many farm animals. However, eQTL mapping has not been conducted in ducks. It is desirable to know whether eQTLs within GWAS signals contributed to duck economic traits. RESULTS: In this study, we conducted an eQTL analysis using publicly available RNA sequencing data from 820 samples, focusing on liver, muscle, blood, adipose, ovary, spleen, and lung tissues. We identified 113,374 cis-eQTLs for 12,266 genes, a substantial fraction 39.1% of which were discovered in at least two tissues. The cis-eQTLs of blood were less conserved across tissues, while cis-eQTLs from any tissue exhibit a strong sharing pattern to liver tissue. Colocalization between cis-eQTLs and genome-wide association studies (GWAS) of 50 traits uncovered new associations between gene expression and potential loci influencing growth and carcass traits. SRSF4, GSS, and IGF2BP1 in liver, NDUFC2 in muscle, ELF3 in adipose, and RUNDC1 in blood could serve as the candidate genes for duck growth and carcass traits. CONCLUSIONS: Our findings highlight substantial differences in genetic regulation of gene expression across duck primary tissues, shedding light on potential mechanisms through which candidate genes may impact growth and carcass traits. Furthermore, this availability of eQTL data offers a valuable resource for deciphering further genetic association signals that may arise from ongoing extensive endeavors aimed at enhancing duck production traits.

Identification and characterization of whole blood gene expression and splicing quantitative trait loci during early to mid-lactation of dairy cattle.

BACKGROUND: Characterization of regulatory variants (e.g., gene expression quantitative trait loci, eQTL; gene splicing QTL, sQTL) is crucial for biologically interpreting molecular mechanisms underlying loci associated with complex traits. However, regulatory variants in dairy cattle, particularly in specific biological contexts (e.g., distinct lactation stages), remain largely unknown. In this study, we explored regulatory variants in whole blood samples collected during early to mid-lactation (22-150 days after calving) of 101 Holstein cows and analyzed them to decipher the regulatory mechanisms underlying complex traits in dairy cattle. RESULTS: We identified 14,303 genes and 227,705 intron clusters expressed in the white blood cells of 101 cattle. The average heritability of gene expression and intron excision ratio explained by cis-SNPs is 0.28 ± 0.13 and 0.25 ± 0.13, respectively. We identified 23,485 SNP-gene expression pairs and 18,166 SNP-intron cluster pairs in dairy cattle during early to mid-lactation. Compared with the 2,380,457 cis-eQTLs reported to be present in blood in the Cattle Genotype-Tissue Expression atlas (CattleGTEx), only 6,114 cis-eQTLs (P < 0.05) were detected in the present study. By conducting colocalization analysis between cis-e/sQTL and the results of genome-wide association studies (GWAS) from four traits, we identified a cis-e/sQTL (rs109421300) of the DGAT1 gene that might be a key marker in early to mid-lactation for milk yield, fat yield, protein yield, and somatic cell score (PP4 > 0.6). Finally, transcriptome-wide association studies (TWAS) revealed certain genes (e.g., FAM83H and TBC1D17) whose expression in white blood cells was significantly (P < 0.05) associated with complex traits. CONCLUSIONS: This study investigated the genetic regulation of gene expression and alternative splicing in dairy cows during early to mid-lactation and provided new insights into the regulatory mechanisms underlying complex traits of economic importance.

Examination of the shared genetic architecture between multiple sclerosis and systemic lupus erythematosus facilitates discovery of novel lupus risk loci.

Systemic Lupus Erythematosus (SLE) is an autoimmune disease with heterogeneous manifestations, including neurological and psychiatric symptoms. Genetic association studies in SLE have been hampered by insufficient sample size and limited power compared to many other diseases. Multiple Sclerosis (MS) is a chronic relapsing autoimmune disease of the central nervous system (CNS) that also manifests neurological and immunological features. Here, we identify a method of leveraging large-scale genome wide association studies (GWAS) in MS to identify novel genetic risk loci in SLE. Statistical genetic comparison methods including linkage disequilibrium score regression (LDSC) and cross-phenotype association analysis (CPASSOC) to identify genetic overlap in disease pathophysiology, traditional 2-sample and novel PPI-based mendelian randomization to identify causal associations and Bayesian colocalization were applied to association studies conducted in MS to facilitate discovery in the smaller, more limited datasets available for SLE. Pathway analysis using SNP-to-gene mapping identified biological networks composed of molecular pathways with causal implications for CNS disease in SLE specifically, as well as pathways likely causal of both pathologies, providing key insights for therapeutic selection.

Association between inflammatory bowel disease and cancer risk: evidence triangulation from genetic correlation, Mendelian randomization, and colocalization analyses across East Asian and European populations.

BACKGROUND: Inflammatory bowel disease (IBD), which includes Crohn's disease (CD) and ulcerative colitis (UC), has been associated with several cancer risks in observational studies, but the observed associations have been inconsistent and may face the bias of confounding and reverse causality. The potential causal relationships between IBD and the risk of cancers remain largely unclear. METHODS: We performed genome-wide linkage disequilibrium score regression (LDSC), standard two-sample Mendelian randomization (MR), and colocalization analyses using summary genome-wide association study (GWAS) data across East Asian and European populations to evaluate the causal relationships between IBD and cancers. Sensitivity analyses for the MR approach were additionally performed to explore the stability of the results. RESULTS: There were no significant genetic correlations between IBD, CD, or UC and cancers (all P values > 0.05) in East Asian or European populations. According to the main MR analysis, no significant causal relationship was observed between IBD and cancers in the East Asian population. There were significant associations between CD and ovarian cancer (odds ratio [OR] = 0.898, 95% CI = 0.844-0.955) and between UC and nonmelanoma skin cancer (OR = 1.002, 95% CI = 1.000-1.004, P = 0.019) in the European population. The multivariable MR analysis did not find any of the above significant associations. There was no shared causal variant to prove the associations of IBD, CD, or UC with cancers in East Asian or European populations using colocalization analysis. CONCLUSIONS: We did not provide robust genetic evidence of causal associations between IBD and cancer risk. Exposure to IBD might not independently contribute to the risk of cancers, and the increased risk of cancers observed in observational studies might be attributed to factors accompanying the diagnosis of IBD.

Integrating single-nucleus RNA sequencing and spatial transcriptomics to elucidate a specialized subpopulation of astrocytes, microglia and vascular cells in brains of mouse model of lipopolysaccharide-induced sepsis-associated encephalopathy.

BACKGROUND: Understanding the mechanism behind sepsis-associated encephalopathy (SAE) remains a formidable task. This study endeavors to shed light on the complex cellular and molecular alterations that occur in the brains of a mouse model with SAE, ultimately unraveling the underlying mechanisms of this condition. METHODS: We established a murine model using intraperitoneal injection of lipopolysaccharide (LPS) in wild type and Anxa1-/- mice and collected brain tissues for analysis at 0-hour, 12-hour, 24-hour, and 72-hour post-injection. Utilizing advanced techniques such as single-nucleus RNA sequencing (snRNA-seq) and Stereo-seq, we conducted a comprehensive characterization of the cellular responses and molecular patterns within the brain. RESULTS: Our study uncovered notable temporal differences in the response to LPS challenge between Anxa1-/- (annexin A1 knockout) and wild type mice, specifically at the 12-hour and 24-hour time points following injection. We observed a significant increase in the proportion of Astro-2 and Micro-2 cells in these mice. These cells exhibited a colocalization pattern with the vascular subtype Vas-1, forming a distinct region known as V1A2M2, where Astro-2 and Micro-2 cells surrounded Vas-1. Moreover, through further analysis, we discovered significant upregulation of ligands and receptors such as Timp1-Cd63, Timp1-Itgb1, Timp1-Lrp1, as well as Ccl2-Ackr1 and Cxcl2-Ackr1 within this region. In addition, we observed a notable increase in the expression of Cd14-Itgb1, Cd14-Tlr2, and Cd14-C3ar1 in regions enriched with Micro-2 cells. Additionally, Cxcl10-Sdc4 showed broad upregulation in brain regions containing both Micro-2 and Astro-2 cells. Notably, upon LPS challenge, there was an observed increase in Anxa1 expression in the mouse brain. Furthermore, our study revealed a noteworthy increase in mortality rates following Anxa1 knockdown. However, we did not observe substantial differences in the types, numbers, or distribution of other brain cells between Anxa1-/- and wildtype mice over time. Nevertheless, when comparing the 24-hour post LPS injection time point, we observed a significant decrease in the proportion and distribution of Micro-2 and Astro-2 cells in the vicinity of blood vessels in Anxa1-/- mice. Additionally, we noted reduced expression levels of several ligand-receptor pairs including Cd14-Tlr2, Cd14-C3ar1, Cd14-Itgb1, Cxcl10-Sdc4, Ccl2-Ackr1, and Cxcl2-Ackr1. CONCLUSIONS: By combining snRNA-seq and Stereo-seq techniques, our study successfully identified a distinctive cellular colocalization, referred to as a special pathological niche, comprising Astro-2, Micro-2, and Vas-1 cells. Furthermore, we observed an upregulation of ligand-receptor pairs within this niche. These findings suggest a potential association between this cellular arrangement and the underlying mechanisms contributing to SAE or the increased mortality observed in Anxa1 knockdown mice.

Integrative multi-omics analysis identifies genetically supported druggable targets and immune cell specificity for myasthenia gravis.

BACKGROUND: Myasthenia gravis (MG) is a chronic autoimmune disorder characterized by fluctuating muscle weakness. Despite the availability of established therapies, the management of MG symptoms remains suboptimal, partially attributed to lack of efficacy or intolerable side-effects. Therefore, new effective drugs are warranted for treatment of MG. METHODS: By employing an analytical framework that combines Mendelian randomization (MR) and colocalization analysis, we estimate the causal effects of blood druggable expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs) on the susceptibility of MG. We subsequently investigated whether potential genetic effects exhibit cell-type specificity by utilizing genetic colocalization analysis to assess the interplay between immune-cell-specific eQTLs and MG risk. RESULTS: We identified significant MR results for four genes (CDC42BPB, CD226, PRSS36, and TNFSF12) using cis-eQTL genetic instruments and three proteins (CTSH, PRSS8, and CPN2) using cis-pQTL genetic instruments. Six of these loci demonstrated evidence of colocalization with MG susceptibility (posterior probability > 0.80). We next undertook genetic colocalization to investigate cell-type-specific effects at these loci. Notably, we identified robust evidence of colocalization, with a posterior probability of 0.854, linking CTSH expression in TH2 cells and MG risk. CONCLUSIONS: This study provides crucial insights into the genetic and molecular factors associated with MG susceptibility, singling out CTSH as a potential candidate for in-depth investigation and clinical consideration. It additionally sheds light on the immune-cell regulatory mechanisms related to the disease. However, further research is imperative to validate these targets and evaluate their feasibility for drug development.

The causal relationship between autoimmune thyroid disorders and telomere length: A Mendelian randomization and colocalization study.

This study aimed to evaluate whether there is a causal relationship between autoimmune thyroid disorders (AITDs) and telomere length (TL) in the European population and whether there is reverse causality. In this study, Mendelian randomization (MR) and colocalization analysis were conducted to assess the potential causal relationship between AITDs and TL using summary statistics from large-scale genome-wide association studies, followed by analysis of the relationship between TL and thyroid stimulating hormone and free thyroxine (FT4) to help interpret the findings. The inverse variance weighted (IVW) method was used to estimate the causal estimates. The weighted median, MR-Egger and leave-one-out methods were used as sensitivity analyses. The IVW method results showed a significant causal relationship between autoimmune hyperthyroidism and TL (ß = -1.93 × 10-2 ; p = 4.54 × 10-5 ). There was no causal relationship between autoimmune hypothyroidism and TL (ß = -3.99 × 10-3 ; p = 0.324). The results of the reverse MR analysis showed that genetically TL had a significant causal relationship on autoimmune hyperthyroidism (IVW: odds ratio (OR) = 0.49; p = 2.83 × 10-4 ) and autoimmune hypothyroidism (IVW: OR = 0.86; p = 7.46 × 10-3 ). Both horizontal pleiotropy and heterogeneity tests indicated the validity of our bidirectional MR study. Finally, colocalization analysis suggested that there were shared causal variants between autoimmune hyperthyroidism and TL, further highlighting the robustness of the results. In conclusion, autoimmune hyperthyroidism may accelerate telomere attrition, and telomere attrition is a causal factor for AITDs.

Clinically relevant plasma proteome for adiposity depots: evidence from systematic mendelian randomization and colocalization analyses.

BACKGROUND: The accumulation of visceral and ectopic fat comprise a major cause of cardiometabolic diseases. However, novel drug targets for reducing unnecessary visceral and ectopic fat are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on visceral and ectopic fat using Mendelian randomization (MR) approach. METHODS: We performed two-sample MR analyses based on five large genome-wide association study (GWAS) summary statistics of 2656 plasma proteins, to screen for causal associations of these proteins with traits of visceral and ectopic fat in over 30,000 participants of European ancestry, as well as to assess mediation effects by risk factors of outcomes. The colocalization analysis was conducted to examine whether the identified proteins and outcomes shared casual variants. RESULTS: Genetically predicted levels of 14 circulating proteins were associated with visceral and ectopic fat (P < 4.99 × 10- 5, at a Bonferroni-corrected threshold). Colocalization analysis prioritized ten protein targets that showed effect on outcomes, including FST, SIRT2, DNAJB9, IL6R, CTSA, RGMB, PNLIPRP1, FLT4, PPY and IL6ST. MR analyses revealed seven risk factors for visceral and ectopic fat (P < 0.0024). Furthermore, the associations of CTSA, DNAJB9 and IGFBP1 with primary outcomes were mediated by HDL-C and SHBG. Sensitivity analyses showed little evidence of pleiotropy. CONCLUSIONS: Our study identified candidate proteins showing putative causal effects as potential therapeutic targets for visceral and ectopic fat accumulation and outlined causal pathways for further prevention of downstream cardiometabolic diseases.

Circulating inflammatory proteins and abdominal aortic aneurysm: A two-sample Mendelian randomization and colocalization analyses.

OBJECTIVES: Inflammatory proteins are implicated in the progression of abdominal aortic aneurysms (AAA); however, it remains debated whether they are causal or consequential. This study aimed to assess the influence of circulating inflammatory proteins on AAA via two-sample Mendelian randomization (MR) and colocalization analysis. METHODS: Summary data on 91 circulating inflammatory protein levels were extracted from a comprehensive protein quantitative trait loci (pQTL) study involving 14,824 individuals. Genetic associations with AAA were derived from the FinnGen study (3,869 cases and 381,977 controls). MR analysis was conducted to assess the relationships between proteins and AAA risk. Colocalization analysis was employed to explore potential shared causal variants between identified proteins and AAA. RESULTS: Using a two-sample bidirectional MR study, our findings suggested that genetically predicted elevated levels of TGFB1 (OR = 1.21, P = 0.003), SIRT2 (OR = 1.196, P = 0.031) and TNFSF14 (OR = 1.129, P = 0.034) were linked to an increased risk of AAA. Conversely, genetically predicted higher levels of CD40 (OR = 0.912, P = 0.049), IL2RB (OR = 0.839, P = 0.028) and KITLG (OR = 0.827, P = 0.008) were associated with a decreased risk of AAA. Colocalization analyses supported the association of TGFB1 and SIRT2 levels with AAA risk. CONCLUSIONS: The proteome-wide MR and colocalization study identified TGFB1 and SIRT2 as being associated with the risk of AAA, warranting further investigation as potential therapeutic targets.

Associations between immune cells signatures and osteoarthritis: An integrated analysis of bidirectional Mendelian randomization and Bayesian colocalization.

BACKGROUND: Previous investigations have explored the associations between immune cell signatures and osteoarthritis (OA); however, causality remains unclear. This study employs an integrated analysis, combining bidirectional Mendelian randomization (MR) and Bayesian colocalization (Coloc), to investigate causal relationships between 731 immune cells signatures and OA, identifying shared causal variants. METHODS: Utilizing publicly available summary data, this study primarily employs inverse variance weighting (IVW). Supplementary methods include MR-Egger regression, weighted median, weight mode, and simple mode. Various sensitivity tests, including Cochran's Q test, MR pleiotropy Residual Sum and Outlier, and leave-one-out tests, were conducted to assess the robustness of the analysis results. Coloc was employed to identify shared causal genetic variants among potential associations. RESULTS: IVW analysis revealed 196 immune cell signatures potentially linked to OA across diverse subtypes. Reverse MR analyses indicated the causal impact of OA on the levels of 140 immune cell signatures, with subtype-specific variations. Notably, several specific associations, including CD64 on CD14-CD16 + monocyte for Hip OA (OR = 1.0593, 95 % CI: 1.0260-1.0938, P = 0.0004), HLA-DR on CD14 + CD16- monocyte (OR = 0.9664, 95 % CI: 0.9497-0.9834, P = 0.0001), HLA-DR on CD14 + monocyte (OR = 0.9680, 95 % CI: 0.9509-0.9853, P = 0.0003) in the Knee or Hip OA, PDL-1 on CD14-CD16 + monocyte by All OA (OR = 1.7091, 95 %CI:1.2494-2.3378, P = 0.0008), and herpesvirus entry mediator on effector memory CD4 + T cell by Spine OA (OR = 0.5200, 95 %CI:0.3577-0.7561, P = 0.0006) remained significant post-Bonferroni correction. Sensitivity tests validated the credibility of the IVW analysis. Additionally, Coloc revealed several potential associations among shared genetic variants, including rs115328872, rs1800973, and rs317667. CONCLUSIONS: Our findings provide evidence for the potential involvement of immune cell signatures in OA development, revealing avenues for early prevention and innovative therapeutic strategies.