Clinically Relevant Circulating Protein Biomarkers for Type 1 Diabetes: Evidence From a Two-Sample Mendelian Randomization Study

Genetic Connectivity of Gut Microbiota and Oral Ulcers: A Mendelian Randomization Study

OBJECTIVES

The aim of this study was to reveal the relationship, if any, between gut microbiota and oral ulcers.

METHODS

We performed a 2-sample Mendelian randomization (MR) study to estimate the roles of gut microbiota in mouth ulcers. The summary datasets of gut microbiota were from the largest genome-wide association study (GWAS) conducted by MiBioGen, and data of mouth ulcers were obtained from UK Biobank. Random effect inverse variance-weighted, weighted median, MR Egger, simple mode and weighted mode were used to estimate the relationship. Sensitivity analyses were conducted to assess the heterogeneity and pleiotropy of instrumental variables. MR Steiger filtering was also applied to orient the causal direction.

RESULTS

Three gut microbiota taxa were positively associated with mouth ulcers: Holdemania (odds ratio [OR] = 1.005, 95% confidence interval [CI]: 1.001-1.009, P = .019), Oxalobacter (OR = 1.004, 95% CI: 1.000-1.007, P = .032), and Ruminococcaceae UCG011 (OR = 1.006, 95% CI: 1.001-1.011, P = .029), while 4 gut microbiota taxa were negatively associated with mouth ulcers: Actinobacteria (OR = 0.992, 95% CI: 0.985-1.000, P = .042), Lactobacillales (OR = 0.995, 95% CI: 0.990-1.000, P = .034), Oscillospira (OR = 0.990, 95% CI: 0.984-0.997, P = .007) and Phascolarctobacterium (OR = 0.992, 95% CI: 0.986-0.997, P = .003). Sensitivity analyses validated the robustness of the association in between.

CONCLUSIONS

This MR study identified a strong association between the quality of gut microbiota and oral ulcers. The findings are likely to expand the therapeutic targets for mouth ulcers.

Integrating plasma proteome with genome reveals novel protein biomarkers in colorectal cancer

BACKGROUND

Biomarkers for colorectal cancer (CRC) can complement population screening methods, but so far, few plasma proteins have been identified as biomarkers for CRC. This study aims to identify potential protein biomarkers and therapeutic targets for CRC within the proteome range.

METHODS

We extracted summary-level data of circulating protein from 7 published genome-wide association studies (GWASs) of plasma proteome for Mendelian randomization (MR), summary-data-based MR (SMR), and co-localization analyses to screen and validate proteins with causal effects in CRC. In addition, we further conducted druggability evaluation, prognosis analysis at the transcriptional level, and enrichment expression at the single-cell level, highlighting the important role of these plasma protein biomarkers in CRC.

RESULTS

We identified 117 plasma protein biomarkers associated with CRC risk, with 9 proteins showing stronger genetic correlations in Bayesian co-localization (PP.H4 > 0.70). Further, we found 26 protein-coding genes already used in targeted drug development and may potentially become therapeutic targets for CRC. In prognosis analysis, the encoding genes of plasma proteins exhibited consistent effects with MR analysis and can serve as prognostic biomarkers for CRC. Additionally, we also found that the differentially expressed proteins are mainly expressed in fibroblasts, endothelial cells, macrophages, and T cells.

CONCLUSION

Our study has identified plasma protein biomarkers associated with CRC risk, which may complement population screening methods for CRC and achieve more precise treatment for patients.

Multicenter proteome-wide Mendelian randomization study identifies causal plasma proteins in melanoma and non-melanoma skin cancers

This study addresses the diagnostic and therapeutic challenges in malignant melanoma (MM) and non-melanoma skin cancers (NMSC). We aim to identify circulating proteins causally linked to MM and NMSC traits using a multicenter Mendelian randomization (MR) framework. We utilized large-scale cis-MR to estimate the impact of numerous plasma proteins on MM, NMSC, squamous cell carcinoma (SCC), and basal cell carcinoma (BCC). To ensure robustness, additional analyses like MR Steiger and Bayesian colocalization are conducted, followed by replication through meta-analytical methods. The associations between identified proteins and outcomes are also validated at the tissue level using Transcriptome-Wide Association Study methods. Furthermore, a protein-protein interaction analysis is conducted to explore the relationship between identified proteins and existing cancer medication targets. The MR analysis has identified associations of 13 plasma proteins with BCC, 2 with SCC, and 1 with MM. Specifically, ASIP and KRT5 are associated with BCC, with ASIP also potentially targeting MM. CTSS and TNFSF8 are identified as promising druggability candidates for BCC. This multidimensional approach nominates ASIP, KRT5, CTSS, and TNFSF8 as potential diagnostic and therapeutic targets for skin cancers.

Genetic and Epigenetic Landscape for Drug Development in Polycystic Ovary Syndrome

The treatment of polycystic ovary syndrome (PCOS) faces challenges as all known treatments are merely symptomatic. The US Food and Drug Administration has not approved any drug specifically for treating PCOS. As the significance of genetics and epigenetics rises in drug development, their pivotal insights have greatly enhanced the efficacy and success of drug target discovery and validation, offering promise for guiding the advancement of PCOS treatments. In this context, we outline the genetic and epigenetic advancement in PCOS, which provide novel insights into the pathogenesis of this complex disease. We also delve into the prospective method for harnessing genetic and epigenetic strategies to identify potential drug targets and ensure target safety. Additionally, we shed light on the preliminary evidence and distinctive challenges associated with gene and epigenetic therapies in the context of PCOS.

Association between primary biliary cholangitis with diabetes and cardiovascular diseases: A bidirectional multivariable Mendelian randomization study

BACKGROUND AND AIMS

Primary biliary cholangitis (PBC) is an autoimmune disease often accompanied by multisystem damage. This study aimed to explore the causal association between genetically predicted PBC and diabetes, as well as multiple cardiovascular diseases (CVDs).

METHODS

Genome-wide association studies (GWAS) summary data of PBC in 24,510 individuals of European ancestry from the European Association for the Study of the Liver was used to identify genetically predicted PBC. We conducted 2-sample single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR) to estimate the impacts of PBC on diabetes (N = 17,685 to 318,014) and 20 CVDs from the genetic consortium (N = 171,875 to 1,030,836).

RESULTS

SVMR provided evidence that genetically predicted PBC is associated with an increased risk of type 1 diabetes (T1D), type 2 diabetes (T2D), myocardial infarction (MI), heart failure (HF), hypertension, atrial fibrillation (AF), stroke, ischemic stroke, and small-vessel ischemic stroke. Additionally, there was no evidence of a causal association between PBC and coronary atherosclerosis. In the MVMR analysis, PBC maintained independent effects on T1D, HF, MI, and small-vessel ischemic stroke in most models.

CONCLUSION

Our findings revealed the causal effects of PBC on diabetes and 7 CVDs, and no causal relationship was detected between PBC and coronary atherosclerosis.

Evaluating the Causal Effects of Circulating Proteome on the Risk of Sepsis and Related Outcomes

The current investigation deployed Mendelian randomization (MR) to elucidate the causal relationship between circulating proteins and sepsis. A rigorous two-sample MR analysis evaluated the effect of plasma proteins on the sepsis susceptibility. To affirm the integrity of MR findings, a suite of supplementary analyses, including Bayesian colocalization, Steiger filtering, the assessment of protein-altering polymorphisms, and the correlation between expression quantitative trait loci and protein quantitative trait loci (pQTLs), was employed. The study further integrated the examination of protein-protein interactions and pathway enrichment, along with the identification of pharmacologically actionable targets, to advance our comprehension and outline potential sepsis therapies. Subsequent analyses leveraging cis-pQTLs within MR studies unveiled noteworthy relationships: 94 specific proteins exhibited significant links with sepsis-related 28 day mortality, while 96 distinct proteins correlated with survival outcomes in sepsis. Furthermore, incorporating both cis- and trans-pQTLs in MR investigations revealed more comprehensive findings, associating 201 unique proteins with sepsis-related 28 day mortality and 199 distinct proteins with survival outcomes in sepsis. Markedly, colocalization analyses confirmed that eight of these proteins exhibited prominent evidence for colocalization, emphasizing their potential criticality in sepsis pathophysiology. Further in silico analyses were conducted to delineate putative regulatory networks and to highlight prospective drug targets among these proteins. Employing the MR methodology has shed light on plasma proteins implicated in the etiopathogenesis of sepsis. This novel approach unveiled numerous biomarkers and targets, providing a scientific rationale for the development of new therapeutic strategies and prophylactic measures against sepsis.

Identifying therapeutic targets for breast cancer: insights from systematic Mendelian randomization analysis

Background

Breast cancer (BC) exhibits a high incidence rate, imposing a substantial burden on healthcare systems. Novel drug targets are urgently needed for BC. Mendelian randomization (MR) has gained widespread application for identifying fresh therapeutic targets. Our endeavor was to pinpoint circulatory proteins causally linked to BC risk and proffer potential treatment targets for BC.

Methods

Through amalgamating protein quantitative trait loci from 2,004 circulating proteins and comprehensive genome-wide association study data from the Breast Cancer Association Consortium, we conducted MR analyses. Employing Steiger filtering, bidirectional MR, Bayesian colocalization, phenotype scanning, and replication analyses, we further solidified MR study outcomes. Additionally, protein-protein interaction (PPI) network was harnessed to unveil latent associations between proteins and prevailing breast cancer medications. The phenome-wide MR (Phe-MR) was employed to assess potential side effects and indications for the druggable proteins of BC. Finally, we further affirmed the drugability of potential drug targets through mRNA expression analysis and molecular docking.

Results

Through comprehensive analysis, we identified five potential drug targets, comprising four (TLR1, A4GALT, SNUPN, and CTSF) for BC and one (TLR1) for BC_estrogen receptor positive. None of these five potential drug targets displayed reverse causation. Bayesian colocalization suggested that these five latent drug targets shared variability with breast cancer. All drug targets were replicated within the deCODE cohort. TLR1 exhibited PPI with current breast cancer therapeutic targets. Furthermore, Phe-MR unveiled certain adverse effects solely for TLR1 and SNUPN.

Conclusion

Our study uncovers five prospective drug targets for BC and its subtypes, warranting further clinical exploration.

Lessons and Applications of Omics Research in Diabetes Epidemiology

PURPOSE OF REVIEW

Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies.

RECENT FINDINGS

We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.

Mendelian randomization analysis demonstrates the causal effects of IGF family members in diabetes

Background

Observational studies have consistently shown significant associations between the IGF family and metabolic diseases, including diabetes. However, these associations can be influenced by confounding factors and reverse causation. This study aimed to assess the causal relationship between the IGF family and diabetes using Mendelian randomization (MR).

Methods

We conducted a two-sample MR analysis to investigate the causal effects of the IGF family on diabetes. Instrumental variables for the IGF family and diabetes were derived from summary-level statistics obtained from genome-wide association studies. Horizontal pleiotropy was assessed using MR-Egger regression and the weighted median method. We applied the inverse-variance weighted method as part of the conventional MR analysis to evaluate the causal impact of the IGF family on diabetes risk. To test the robustness of the results, we also employed MR-Egger regression, the weighted median method, and a leave-one-out analysis.

Results

Our study revealed that IGF-1 causally increases the risk of Type 2 Diabetes (T2D), while IGFBP-6, adiponectin and INSR decreases the risk (IGF-1, OR 1.02 [95% CI 1-1.03], p = 0.01; IGFBP-6, OR 0.92 [95% CI 0.87-0.98], p = 0.01; Adiponectin, OR 0.837 [95% CI 0.721-0.970], p = 0.018; INSR, OR 0.910 [95% CI 0.872-0.950], p = 1.52 × 10-5). Additionally, genetically lower levels of IGF-1 and IGFBP-5, along with higher levels of IGFBP-7, were associated with an increased risk of Type 1 Diabetes (T1D) (IGF-1, OR 0.981 [95% CI 0.963-0.999], p = 0.037; IGFBP-5, OR 0.882 [95% CI 0.778-0.999], p = 0.049; IGFBP-7, OR 1.103 [95% CI 1.008-1.206], p = 0.033).

Conclusion

In summary, our investigation has unveiled causal relationships between specific IGF family members and T1D and T2D through MR analysis. Generally, the IGF family appears to reduce the risk of T1D, but it presents a more complex and controversial role in the context of T2D. These findings provide compelling evidence that T2D is intricately linked with developmental impairment. Our study results offer fresh insights into the pathogenesis and the significance of serum IGF family member concentrations in assessing diabetes risk.

Potential disease biomarkers for diabetic retinopathy identified through Mendelian randomization analysis

Background

Diabetic retinopathy (DR), a leading cause of vision loss, has limited options for effective prevention and treatment. This study aims to utilize genomics and proteomics data to identify potential drug targets for DR.

Methods

We utilized plasma protein quantitative trait loci data from the Atherosclerosis Risk in Communities Study and the Icelandic Decoding Genetics Study for discovery and replication, respectively. Genetic associations with DR, including its subtypes, were derived from the FinnGen study. Mendelian Randomization (MR) analysis estimated associations between protein levels and DR risk, complemented by colocalization analysis to examine shared causal variants.

Results

Our MR analysis identified significant associations of specific plasma proteins with DR and proliferative DR (PDR). Elevated genetically predicted levels of WARS (OR = 1.16; 95% CI = 0.095-0.208, FDR = 1.31×10-4) and SIRPG (OR = 1.15; 95% CI = 0.071-0.201, FDR = 1.46×10-2) were associated with higher DR risk, while increased levels of ALDOC (OR = 1.56; 95% CI = 0.246-0.637, FDR = 5.48×10-3) and SIRPG (OR = 1.15; 95% CI = 0.068-0.208, FDR = 4.73×10-2) were associated with higher PDR risk. These findings were corroborated by strong colocalization evidence.

Conclusions

Our study highlights WARS, SIRPG, and ALDOC as significant proteins associated with DR and PDR, providing a basis for further exploration in drug development. Additional studies are needed to validate these proteins as disease biomarkers across diverse populations.

Targeting IL-12 family cytokines: A potential strategy for type 1 and type 2 diabetes mellitus

Diabetes is a common metabolic disease characterized by an imbalance in blood glucose levels. The pathogenesis of diabetes involves the essential role of cytokines, particularly the IL-12 family cytokines. These cytokines, which have a similar structure, play multiple roles in regulating the immune response. Recent studies have emphasized the importance of IL-12 family cytokines in the development of both type 1 and type 2 diabetes mellitus. As a result, they hold promise as potential therapeutic targets for the treatment of these conditions. This review focuses on the potential of targeting IL-12 family cytokines for diabetes therapy based on their roles in the pathogenesis of both types of diabetes. We have summarized various therapies that target IL-12 family cytokines, including drug therapy, combination therapy, cell therapy, gene therapy, cytokine engineering therapy, and gut microbiota modulation. By analyzing the advantages and disadvantages of these therapies, we have evaluated their feasibility for clinical application and proposed possible solutions to overcome any challenges. In conclusion, targeting IL-12 family cytokines for diabetes therapy provides updated insights into their potential benefits, such as controlling inflammation, preserving islet β cells, reversing the onset of diabetes, and impeding the development of diabetic complications.

Protein-centric omics integration analysis identifies candidate plasma proteins for multiple autoimmune diseases

It remains challenging to translate the findings from genome-wide association studies (GWAS) of autoimmune diseases (AIDs) into interventional targets, presumably due to the lack of knowledge on how the GWAS risk variants contribute to AIDs. In addition, current immunomodulatory drugs for AIDs are broad in action rather than disease-specific. We performed a comprehensive protein-centric omics integration analysis to identify AIDs-associated plasma proteins through integrating protein quantitative trait loci datasets of plasma protein (1348 proteins and 7213 individuals) and totally ten large-scale GWAS summary statistics of AIDs under a cutting-edge systematic analytic framework. Specifically, we initially screened out the protein-AID associations using proteome-wide association study (PWAS), followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, we performed both Mendelian randomization (MR) and colocalization analyses to further identify protein-AID pairs with putatively causal relationships. We finally prioritized the potential drug targets for AIDs. A total of 174 protein-AID associations were identified by PWAS. AIDs-associated plasma proteins were significantly enriched in immune-related biological process and pathways, such as inflammatory response (P = 3.96 × 10-10). MR analysis further identified 97 protein-AID pairs with potential causal relationships, among which 21 pairs were highly supported by colocalization analysis (PP.H4 > 0.75), 10 of 21 were the newly discovered pairs and not reported in previous GWAS analyses. Further explorations showed that four proteins (TLR3, FCGR2A, IL23R, TCN1) have corresponding drugs, and 17 proteins have druggability. These findings will help us to further understand the biological mechanism of AIDs and highlight the potential of these proteins to develop as therapeutic targets for AIDs.

Evaluating the causal effect of circulating proteome on the risk of osteoarthritis-related traits

OBJECTIVES

This study aims to identify circulating proteins that are causally associated with osteoarthritis (OA)-related traits through Mendelian randomisation (MR)-based analytical framework.

METHODS

Large-scale two-sample MR was employed to estimate the effects of thousands of plasma proteins on 12 OA-related traits. Additional analyses including Bayesian colocalisation, Steiger filtering analysis, assessment of protein-altering variants and mapping expression quantitative trait loci to protein quantitative trait loci were performed to investigate the reliability of the MR findings; protein-protein interaction, pathway enrichment analysis and evaluation of drug targets were conducted to deepen the understanding and identify potential therapeutic targets of OA.

RESULTS

Dozens of circulating proteins were identified to have putatively causal effects on OA-related traits, and a majority of these proteins were either drug targets or considered druggable.

CONCLUSIONS

Through MR analysis, we have identified numerous plasma proteins associated with OA-related traits, shedding light on protein-mediated mechanisms and offering promising therapeutic targets for OA.

Type 1 diabetes, glycemic traits, and risk of dental caries: a Mendelian randomization study

Background: Regarding past epidemiological studies, there has been disagreement over whether type 1 diabetes (T1DM) is one of the risk factors for dental caries. The purpose of this study was to determine the causative links between genetic susceptibility to T1DM, glycemic traits, and the risk of dental caries using Mendelian randomization (MR) approaches. Methods: Summary-level data were collected on genome-wide association studies (GWAS) of T1DM, fasting glucose (FG), glycated hemoglobin (HbA1c), fasting insulin (FI), and dental caries. MR was performed using the inverse-variance weighting (IVW) method, and sensitivity analyses were conducted using the MR-Egger method, weighted median, weighted mode, replication cohort, and multivariable MR conditioning on potential mediators. Results: The risk of dental caries increased as a result of genetic susceptibility to T1DM [odds ratio (OR) = 1.044; 95% confidence interval (CI) = 1.015-1.074; p = 0.003], with consistent findings in the replication cohort. The relationship between T1DM and dental caries was stable when adjusted for BMI, smoking, alcohol intake, and type 2 diabetes (T2DM) in multivariable MR. However, no significant correlations between the risk of dental caries and FG, HbA1c, or FI were found. Conclusion: These results indicate that T1DM has causal involvement in the genesis of dental caries. Therefore, periodic reinforcement of oral hygiene instructions must be added to the management and early multidisciplinary intervention of T1DM patients, especially among adolescents and teenagers, who are more susceptible to T1DM.

Identification of novel protein biomarkers and drug targets for colorectal cancer by integrating human plasma proteome with genome

BACKGROUND

The proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) study to identify candidate protein markers and therapeutic targets for colorectal cancer (CRC).

METHODS

Protein quantitative trait loci (pQTLs) were derived from seven published genome-wide association studies (GWASs) on plasma proteome, and summary-level data were extracted for 4853 circulating protein markers. Genetic associations with CRC were obtained from a large-scale GWAS meta-analysis (16,871 cases and 26,328 controls), the FinnGen cohort (4957 cases and 304,197 controls), and the UK Biobank (9276 cases and 477,069 controls). Colocalization and summary-data-based MR (SMR) analyses were performed sequentially to verify the causal role of candidate proteins. Single cell-type expression analysis, protein-protein interaction (PPI), and druggability evaluation were further conducted to detect the specific cell type with enrichment expression and prioritize potential therapeutic targets.

RESULTS

Collectively, genetically predicted levels of 13 proteins were associated with CRC risk. Elevated levels of two proteins (GREM1, CHRDL2) and decreased levels of 11 proteins were associated with an increased risk of CRC, among which four (GREM1, CLSTN3, CSF2RA, CD86) were prioritized with the most convincing evidence. These protein-coding genes are mainly expressed in tissue stem cells, epithelial cells, and monocytes in colon tumor tissue. Two interactive pairs of proteins (GREM1 and CHRDL2; MMP2 and TIMP2) were identified to be involved in osteoclast differentiation and tumorigenesis pathways; four proteins (POLR2F, CSF2RA, CD86, MMP2) have been targeted for drug development on autoimmune diseases and other cancers, with the potentials of being repurposed as therapeutic targets for CRC.

CONCLUSIONS

This study identified several protein biomarkers to be associated with CRC risk and provided new insights into the etiology and promising targets for the development of screening biomarkers and therapeutic drugs for CRC.

Genetic insight into the putative causal proteins and druggable targets of osteoporosis: a large-scale proteome-wide mendelian randomization study

Background: Osteoporosis is a major causative factor of the global burden of disease and disability, characterized by low bone mineral density (BMD) and high risks of fracture. We aimed to identify putative causal proteins and druggable targets of osteoporosis. Methods: This study utilized the largest GWAS summary statistics on plasma proteins and estimated heel BMD (eBMD) to identify causal proteins of osteoporosis by mendelian randomization (MR) analysis. Different GWAS datasets were used to validate the results. Multiple sensitivity analyses were conducted to evaluate the robustness of primary MR findings. We have also performed an enrichment analysis for the identified causal proteins and evaluated their druggability. Results: After Bonferroni correction, 67 proteins were identified to be causally associated with estimated BMD (eBMD) (p < 4 × 10^-5). We further replicated 38 of the 67 proteins to be associated with total body BMD, lumbar spine BMD, femoral neck BMD as well as fractures, such as RSPO3, IDUA, SMOC2, and LRP4. The findings were supported by sensitivity analyses. Enrichment analysis identified multiple Gene Ontology items, including collagen-containing extracellular matrix (GO:0062023, p = 1.6 × 10^-10), collagen binding (GO:0005518, p = 8.6 × 10^-5), and extracellular matrix structural constituent (GO:0005201, p = 2.7 × 10^-5). Conclusion: The study identified novel putative causal proteins for osteoporosis which may serve as potential early screening biomarkers and druggable targets. Furthermore, the role of plasma proteins involved in collagen binding and extracellular matrix in the development of osteoporosis was highlighted. Further studies are warranted to validate our findings and investigate the underlying mechanism.

Identification of potential drug targets for varicose veins: a Mendelian randomization analysis

Introduction

Varicose veins are a common chronic disease that creates a significant economic burden on the healthcare system. Current treatment options, including pharmacological treatments, are not always effective, and there is a need for more targeted therapies. A Mendelian randomization (MR) method uses genetic variants as instrumental variables to estimate the causal effect of an exposure on an outcome, and it has been successful in identifying therapeutic targets in other diseases. However, few studies have used MR to explore potential protein drug targets for varicose veins.

Methods

To identify potential drug targets for varicose veins of lower extremities, we undertook a comprehensive screen of plasma protein with a two-sample MR method. We used recently reported cis-variants as genetic instruments of 2,004 plasma proteins, then applied MR to a recent meta-analysis of genome-wide association study on varicose veins (22,037 cases and 437,665 controls). Furthermore, pleiotropy detection, reverse causality testing, colocalization analysis, and external replication were utilized to strengthen the causal effects of prioritized proteins. Phenome-wide MR (PheW-MR) of the prioritized proteins for the risk of 525 diseases was conducted to screen potential side effects.

Results

We identified eight plasma proteins that are significantly associated with the risk of varicose veins after Bonferroni correction (P < 2.495 × 10^-5), with five being protective (LUM, POSTN, RPN1, RSPO3, and VAT1) and three harmful (COLEC11, IRF3, and SARS2). Most identified proteins showed no pleiotropic effects except for COLLEC11. Bidirectional MR and MR Steiger testing excluded reverse causal relationship between varicose veins and prioritized proteins. The colocalization analysis indicated that COLEC11, IRF3, LUM, POSTN, RSPO3, and SARS2 shared the same causal variant with varicose veins. Finally, seven identified proteins replicated with alternative instruments except for VAT1. Furthermore, PheW-MR revealed that only IRF3 had potential harmful adverse side effects.

Conclusions

We identified eight potential causal proteins for varicose veins with MR. A comprehensive analysis indicated that IRF3, LUM, POSTN, RSPO3, and SARS2 might be potential drug targets for varicose veins.

The importance of biomarker development for monitoring type 1 diabetes progression rate and therapeutic responsiveness

Type 1 diabetes (T1D) is an autoimmune condition of children and adults in which immune cells target insulin-producing pancreatic β-cells for destruction. This results in a chronic inability to regulate blood glucose levels. The natural history of T1D is well-characterized in childhood. Evidence of two or more autoantibodies to the islet antigens insulin, GAD, IA-2 or ZnT8 in early childhood is associated with high risk of developing T1D in the future. Prediction of risk is less clear in adults and, overall, the factors controlling the progression rate from multiple islet autoantibody positivity to onset of symptoms are not fully understood. An anti-CD3 antibody, teplizumab, was recently shown to delay clinical progression to T1D in high-risk individuals including adults and older children. This represents an important proof of concept for those at risk of future T1D. Given their role in risk assessment, islet autoantibodies might appear to be the most obvious biomarkers to monitor efficacy. However, monitoring islet autoantibodies in clinical trials has shown only limited effects, although antibodies to the most recently identified autoantigen, tetraspanin-7, have not yet been studied in this context. Measurements of beta cell function remain fundamental to assessing efficacy and different models have been proposed, but improved biomarkers are required for both progression studies before onset of diabetes and in therapeutic monitoring. In this mini-review, we consider some established and emerging predictive and prognostic biomarkers, including markers of pancreatic function that could be integrated with metabolic markers to generate improved strategies to measure outcomes of therapeutic intervention.

Causal factors underlying diabetes risk informed by Mendelian randomisation analysis: evidence, opportunities and challenges

Diabetes and its complications cause a heavy disease burden globally. Identifying exposures, risk factors and molecular processes causally associated with the development of diabetes can provide important evidence bases for disease prevention and spur novel therapeutic strategies. Mendelian randomisation (MR), an epidemiological approach that uses genetic instruments to infer causal associations between an exposure and an outcome, can be leveraged to complement evidence from observational and clinical studies. This narrative review aims to summarise the evidence on potential causal risk factors for diabetes by integrating published MR studies on type 1 and 2 diabetes, and to reflect on future perspectives of MR studies on diabetes. Despite the genetic influence on type 1 diabetes, few MR studies have been conducted to identify causal exposures or molecular processes leading to increased disease risk. In type 2 diabetes, MR analyses support causal associations of somatic, mental and lifestyle factors with development of the disease. These studies have also identified biomarkers, some of them derived from the gut microbiota, and molecular processes leading to increased disease risk. These studies provide valuable data to better understand disease pathophysiology and explore potential therapeutic targets. Because genetic association studies have mostly been restricted to participants of European descent, multi-ancestry cohorts are needed to examine the role of different types of physical activity, dietary components, metabolites, protein biomarkers and gut microbiome in diabetes development.

ST2 and CSF-1 as potential druggable targets of inflammatory bowel diseases: Results from two-sample Mendelian randomization study

Novel druggable targets are warranted for inflammatory bowel disease (IBD) treatment. We aimed to identify novel circulating proteins with causal associations with the risk of IBDs and provide potential therapeutic targets for IBD treatment. We performed a two-sample Mendelian randomization (MR) study to explore the associations of 55 circulating biomarkers on the risk of IBD, Crohn's disease (CD), and ulcerative colitis (UC) by leveraging the summary statistics from large genomewide association studies and protein quantitative trait loci studies. The individual estimate was pooled together by meta-analyses to estimate the causal effects of each outcome. In univariable MR, we identified several circulating proteins showed potential correlation with IBD, UC, and CD. Of note, we observed that a genetically proxied increased level of suppression of tumorigenicity 2 (ST2) was associated with an elevated risk of IBD (odds ratios [ORs] 1.133, 95% confidence interval [CI] 1.091-1.176, p < 0.0001), CD (ORs 1.188, 95% CI 1.103-1.281, p < 0.0001), and UC cohorts (ORs 1.087, 95% CI 1.050-1.125, p < 0.0001). Additionally, we observed a consistent positive correlation between the level of CSF-1 and the increased risk of IBD in individual MR, with statistically significant causal associations in the meta-analyses with ORs equal to 1.217 (IBD, 95% CI 1.115-1.328, p < 0.0001), 1.223 (CD, 95% CI 1.082-1.382, p = 0.0013), and 1.179 (UC, 95% CI 1.055-1.317, p = 0.0037). This study provided evidence for potential casual associations between circulating ST2 and CSF-1 levels, and increased risks of IBD, UC, and CD, implicating potential treatment targets for IBD and subtypes.

Genetic susceptibility to COVID-19 may increase the risk of erectile dysfunction: A two-sample Mendelian randomization study

Coronavirus disease 19 (COVID‐19) and erectile dysfunction (ED) have been linked in some observational research, but the causality of this association in the European population is uncertain. Therefore, the research intended to investigate the causality of susceptibility to COVID‐19 on ED. We used Mendelian randomization (MR) analysis for this research. The subjects were from two genome‐wide association studies (GWAS) of the European population, including COVID‐19 (14,134 cases and 1,284,876 controls) and ED (6175 cases and 217,630 controls). We utilized the inverse variance‐weighted (IVW) to evaluate the causality of COVID‐19 genetic susceptibility on ED. Heterogeneity and pleiotropy were determined using the Cochran's Q test and MR‐Egger regression. The robustness of the findings was verified using the Leave‐one‐out method. We obtained six single nucleotide polymorphisms (SNPs) as COVID‐19 genetic instrumental variables (IVs), and there was no significant pleiotropy, heterogeneity or bias in these IVs. MR analysis revealed the causality of genetic susceptibility to COVID‐19 on elevated risk of ED (OR_IVW = 1.235, 95% CI: 1.044–1.462, p < 0.05). The present study suggested the causality of genetic susceptibility to COVID‐19 on elevated ED risk among the European population. Therefore, in order to decrease the ED risk, the European population ought to positively prevent COVID‐19.