Plasma proteins and onset of type 2 diabetes and diabetic complications: Proteome-wide Mendelian randomization and colocalization analyses

The causal relationship between plasma protein-to-protein ratios and type 2 diabetes and its complications: Proteomics mendelian randomization study

AIM

In recent years, proteomics research has surged, with numerous observational studies identifying associations between plasma proteins and type 2 diabetes. However, research specifically focusing on the ratios of plasma proteins in type 2 diabetes remains relatively scarce.

METHODS

This study primarily employed a two-sample, two-step Mendelian randomization (MR) approach, leveraging genetic data from several large, publicly accessible genome-wide association studies, wherein single nucleotide polymorphisms served as proxies for exposures and diseases. Within this framework, we applied two-sample MR to assess the associations between the 2821 plasma protein-to-protein ratios and type 2 diabetes along with its complications and utilized reverse MR to confirm the unidirectionality of these causal relationships. In addition, we employed two-step MR to investigate the potential mediating role of body mass index in these associations. To augment the robustness of our findings, we systematically implemented a series of sensitivity analyses.

RESULTS

The results gleaned from the inverse-variance weighted method elucidated that a cumulative sum of 23 protein-to-protein ratios bore a causal nexus with type 2 diabetes across both sample cohorts. With each incremental elevation of 1 standard deviation in the genetically anticipated protein-to-protein ratio, the susceptibility to type 2 diabetes oscillated from 0.93 (95% confidence interval: 0.87, 1.00) for the CNTN3/NCSS1 protein level ratio to 1.13 (1.06, 1.22) for the DBNL/NCK2 protein level ratio. Moreover, a tally of eight protein-to-protein ratios correlated with a minimum of one complication linked to type 2 diabetes. Diverse sensitivity analyses corroborated the robustness of these observations.

CONCLUSIONS

The outcomes of our investigation unveiled correlations between 23 plasma protein-to-protein ratios and type 2 diabetes, with eight of these ratios entwined with complications of type 2 diabetes. These discoveries offer novel perspectives on the diagnosis and management of type 2 diabetes and its associated complications.

Mitochondrial dysfunction and onset of type 2 diabetes along with its complications: a multi-omics Mendelian randomization and colocalization study

Background

Mitochondrial dysfunction plays a crucial role in Type 2 Diabetes Mellitus (T2DM) and its complications. However, the genetic pathophysiology remains under investigation. Through multi-omics Mendelian Randomization (MR) and colocalization analyses, we identified mitochondrial-related genes causally linked with T2DM and its complications.

Methods

Summary-level quantitative trait loci data at methylation, RNA, and protein levels were retrieved from European cohort studies. GWAS summary statistics for T2DM and its complications were collected from the DIAGRAM and FinnGen consortiums, respectively. Summary-data-based MR was utilized to estimate the causal effects. The heterogeneity in dependent instrument test assessed horizontal pleiotropy, while colocalization analysis determined whether genes and diseases share the same causal variant. Enrichment analysis, drug target analysis, and phenome-wide MR were conducted to further explore the biological functions, potential drugs, and causal associations with other diseases.

Results

Integrating evidence from multi-omics, we identified 18 causal mitochondrial-related genes. Enrichment analysis revealed they were not only related to nutrient metabolisms but also to the processes like mitophagy, autophagy, and apoptosis. Among these genes, Tu translation elongation factor mitochondrial (TUFM), 3-hydroxyisobutyryl-CoA hydrolase (HIBCH), and iron-sulfur cluster assembly 2 (ISCA2) were identified as Tier 1 genes, showing causal links with T2DM and strong colocalization evidence. TUFM and ISCA2 were causally associated with an increased risk of T2DM, while HIBCH showed an inverse causal relationship. The causal associations and colocalization effects for TUFM and HIBCH were validated in specific tissues. TUFM was also found to be a risk factor for microvascular complications in T2DM patients including retinopathy, nephropathy, and neuropathy. Furthermore, drug target analysis and phenome-wide MR underscored their significance as potential therapeutic targets.

Conclusions

This study identified 18 mitochondrial-related genes causally associated with T2DM at multi-omics levels, enhancing the understanding of mitochondrial dysfunction in T2DM and its complications. TUFM, HIBCH, and ISCA2 emerge as potential therapeutic targets for T2DM and its complications.

Identification of immunity- and ferroptosis-related signature genes as potential design targets for mRNA vaccines in AML patients

Immune-associated ferroptosis plays an important role in the progression of acute myeloid leukemia (AML); however, the targets that play key roles in this process are currently unknown. This limits the development of mRNA vaccines based on immune-associated ferroptosis for clinical therapeutic applications. In this study, based on the rich data resources of the TCGA-LAML cohort, we analyzed the tumor mutational burden (TMB), gene mutation status, and associations between immune and ferroptosis genes to reveal the disease characteristics of AML patients. To gain a deeper understanding of differentially expressed genes, we applied the Limma package for differential expression analysis and integrated data sources such as ImmPort Shared Data and FerrDb V2. Moreover, we established gene modules related to TMB according to weighted gene coexpression network analysis (WGCNA) and explored the functions of these modules in AML and their relationships with TMB. We focused on the top 30 most frequent genes through a detailed survey of missense mutations and single nucleotide polymorphisms (SNPs) and selected potentially critical gene targets for subsequent analysis. Based on the expression of these genes, we successfully subgrouped AML patients and found that the subgroups associated with TMB (C1 and C2) exhibited significant differences in survival. The differences in the tumor microenvironment and immune cells between C1 and C2 patients were investigated with the ESTIMATE and MCP-counter algorithms. A predictive model of TMB-related genes (TMBRGs) was constructed, and the validity of the model was demonstrated by categorizing patients into high-risk and low-risk groups. The differences in survival between the high-risk patients and high-TMB patients were further investigated, and potential vaccine targets were identified via immune cell-level analysis. The identification of immunity- and ferroptosis-associated signature genes is an independent predictor of survival in AML patients and provides new information on immunotherapy for AML.

Circulating Proteins and IgA Nephropathy: A Multiancestry Proteome-Wide Mendelian Randomization Study

Key Points

Background

The therapeutic options for IgA nephropathy are rapidly evolving, but early diagnosis and targeted treatment remain challenging. We aimed to identify circulating plasma proteins associated with IgA nephropathy by proteome-wide Mendelian randomization studies across multiple ancestry populations.

Methods

In this study, we applied Mendelian randomization and colocalization analyses to estimate the putative causal effects of 2615 proteins on IgA nephropathy in Europeans and 235 proteins in East Asians. Following two-stage network Mendelian randomization, multitrait colocalization analysis and protein-altering variant annotation were performed to strengthen the reliability of the results. A protein–protein interaction network was constructed to investigate the interactions between the identified proteins and the targets of existing medications.

Results

Putative causal effects of 184 and 13 protein–disease pairs in European and East Asian ancestries were identified, respectively. Two protein–disease pairs showed shared causal effects across them (CFHR1 and FCRL2). Supported by the evidence from colocalization analysis, potential therapeutic targets were prioritized and four drug-repurposing opportunities were suggested. The protein–protein interaction network further provided strong evidence for existing medications and pathways that are known to be therapeutically important.

Conclusions

Our study identified a number of circulating proteins associated with IgA nephropathy and prioritized several potential drug targets that require further investigation.

Coeliac disease and type 2 diabetes risk: a nationwide matched cohort and Mendelian randomisation study

AIMS/HYPOTHESIS

While the association between coeliac disease and type 1 diabetes is well documented, the association of coeliac disease with type 2 diabetes risk remains undetermined. We conducted a nationwide cohort and Mendelian randomisation analysis to investigate this link.

METHODS

This nationwide matched cohort used data from the Swedish ESPRESSO cohort including 46,150 individuals with coeliac disease and 219,763 matched individuals in the comparator group selected from the general population, followed up from 1969 to 2021. Data from 9053 individuals with coeliac disease who underwent a second biopsy were used to examine the association between persistent villous atrophy and type 2 diabetes. Multivariable Cox regression was employed to estimate the associations. In Mendelian randomisation analysis, 37 independent genetic variants associated with clinically diagnosed coeliac disease at p<5×10-8 were used to proxy genetic liability to coeliac disease. Summary-level data for type 2 diabetes were obtained from the DIAGRAM consortium (80,154 cases) and the FinnGen study (42,593 cases).

RESULTS

Over a median 15.7 years' follow-up, there were 6132 (13.3%) and 30,138 (13.7%) incident cases of type 2 diabetes in people with coeliac disease and comparator individuals, respectively. Those with coeliac disease were not at increased risk of incident type 2 diabetes with an HR of 1.00 (95% CI 0.97, 1.03) compared with comparator individuals. Persistent villous atrophy was not associated with an increased risk of type 2 diabetes compared with mucosal healing among participants with coeliac disease (HR 1.02, 95% CI 0.90, 1.16). Genetic liability to coeliac disease was not associated with type 2 diabetes in DIAGRAM (OR 1.01, 95% CI 0.99, 1.03) or in FinnGen (OR 1.01, 95% CI 0.99-1.04).

CONCLUSIONS/INTERPRETATION

Coeliac disease was not associated with type 2 diabetes risk.

The interplay between cytokines and stroke: a bi-directional Mendelian randomization study

Stroke, the second leading cause of death and disability, causes massive cell death in the brain followed by secondary inflammatory injury initiated by disease associated molecular patterns released from dead cells. Nonetheless, the evidence regarding the causal relationship between inflammatory cytokines and stroke subtypes is obscure. To leverage large scale genetic association data to investigate the interplay between circulating cytokines and stroke, we adopted a two-sample bi-directional Mendelian randomization (MR) analysis. Firstly, we performed a forward MR analysis to examine the associations of genetically determined 31 cytokines with 6 stroke subtypes. Secondly, we conducted a reverse MR analysis to check the associations of 6 stroke subtypes with 31 cytokines. In the forward MR analysis, genetic evidence suggests that 21 cytokines were significantly associated with certain stroke subtype risk with |β| ranging from 1.90 × 10-4 to 0.74. In the reverse MR analysis, our results found that five stroke subtypes (intracerebral hemorrhage (ICH), large artery atherosclerosis ischemic stroke (LAAS), lacunar stroke (LS), cardioembolic ischemic stroke (CEI), small-vessel ischemic stroke (SV)) caused significantly changes in 16 cytokines with |β| ranging from 1.08 × 10-4 to 0.69. In particular, those five stroke subtypes were statistically significantly associated with C-reactive protein (CRP). In addition, ICH, LAAS, LS and SV were significantly correlated with vascular endothelial growth factor (VEGF), while LAAS, LS, CEI and SV were significantly related to fibroblast growth factor (FGF). Moreover, integrated bi-directional MR analysis, these factors (IL-3Rα, IL-6R, IL-6Rα, IL-1Ra, insulin-like growth factor-1(IGF-1), IL-12Rβ2) can be used as predictors of some specific stroke subtypes. As well as, IL-16 and C-C motif chemokine receptor 7 (CCR7) can be used as prognostic factors of stroke. Our findings prognostic identify potential pharmacological opportunities, including perturbation of circulating cytokines for both predicting stroke risk and post stroke treatment effects. As we conducted a comprehensive search and analysis of stroke subtype and cytokines in the existing publicly available GWAS database, the results have good population-generalizability.

Association between genetically plasma proteins and osteonecrosis: a proteome-wide Mendelian randomization analysis

Background

Previous studies have explored the role of plasma proteins on osteonecrosis. This Mendelian randomization (MR) study further assessed plasma proteins on osteonecrosis whether a causal relationship exists and provides some evidence of causality.

Methods

Summary-level data of 4,907 circulating protein levels were extracted from a large-scale protein quantitative trait loci study including 35,559 individuals by the deCODE Genetics Consortium. The outcome data for osteonecrosis were sourced from the FinnGen study, comprising 1,543 cases and 391,037 controls. MR analysis was conducted to estimate the associations between protein and osteonecrosis risk. Additionally, Phenome-wide MR analysis, and candidate drug prediction were employed to identify potential causal circulating proteins and novel drug targets.

Results

We totally assessed the effect of 1,676 plasma proteins on osteonecrosis risk, of which 71 plasma proteins had a suggestive association with outcome risk (P < 0.05). Notably, Heme-binding protein 1 (HEBP1) was significant positively associated with osteonecrosis risk with convening evidence (OR, 1.40, 95% CI, 1.19 to 1.65, P = 3.96 × 10-5, P FDR = 0.044). This association was further confirmed in other MR analysis methods and did not detect heterogeneity and pleiotropy (all P > 0.05). To comprehensively explore the health effect of HEBP1, the phenome-wide MR analysis found it was associated with 136 phenotypes excluding osteonecrosis (P < 0.05). However, no significant association was observed after the false discovery rate adjustment.

Conclusion

This comprehensive MR study identifies 71 plasma proteins associated with osteonecrosis, with HEBP1, ITIH1, SMOC1, and CREG1 showing potential as biomarkers of osteonecrosis. Nonetheless, further studies are needed to validate this candidate plasma protein.

Integrated analyses of single-cell transcriptome and Mendelian randomization reveal the protective role of FCRL3 in multiple sclerosis

Background

Multiple sclerosis (MS) represents a multifaceted autoimmune ailment, prompting the development and widespread utilization of numerous therapeutic interventions. However, extant medications for MS have proven inadequate in mitigating relapses and halting disease progression. Innovative drug targets for preventing multiple sclerosis are still required. The objective of this study is to discover novel therapeutic targets for MS by integrating single-cell transcriptomics and Mendelian randomization analysis.

Methods

The study integrated MS genome-wide association study (GWAS) data, single-cell transcriptomics (scRNA-seq), expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data for analysis and utilized two-sample Mendelian randomization study to comprehend the causal relationship between proteins and MS. Sequential analyses involving colocalization and Phenome-wide association studies (PheWAS) were conducted to validate the causal role of candidate genes.

Results

Following stringent quality control preprocessing of scRNA-seq data, 1,123 expression changes across seven peripheral cell types were identified. Among the seven most prevalent cell types, 97 genes exhibiting at least one eQTL were discerned. Examination of MR associations between 28 proteins with available index pQTL signals and the risk of MS outcomes was conducted. Co-localization analyses and PheWAS indicated that FCRL3 may exert influence on MS.

Conclusion

The integration of scRNA-seq and MR analysis facilitated the identification of potential therapeutic targets for MS. Notably, FCRL3, implicated in immune function, emerged as a significant drug target in the deCODE databases. This research underscores the importance of FCRL3 in MS therapy and advocates for further investigation and clinical trials targeting FCRL3.

Mechanisms of Flavonoids and Their Derivatives in Endothelial Dysfunction Induced by Oxidative Stress in Diabetes

Diabetic complications pose a significant threat to life and have a negative impact on quality of life in individuals with diabetes. Among the various factors contributing to the development of these complications, endothelial dysfunction plays a key role. The main mechanism underlying endothelial dysfunction in diabetes is oxidative stress, which adversely affects the production and availability of nitric oxide (NO). Flavonoids, a group of phenolic compounds found in vegetables, fruits, and fungi, exhibit strong antioxidant and anti-inflammatory properties. Several studies have provided evidence to suggest that flavonoids have a protective effect on diabetic complications. This review focuses on the imbalance between reactive oxygen species and the antioxidant system, as well as the changes in endothelial factors in diabetes. Furthermore, we summarize the protective mechanisms of flavonoids and their derivatives on endothelial dysfunction in diabetes by alleviating oxidative stress and modulating other signaling pathways. Although several studies underline the positive influence of flavonoids and their derivatives on endothelial dysfunction induced by oxidative stress in diabetes, numerous aspects still require clarification, such as optimal consumption levels, bioavailability, and side effects. Consequently, further investigations are necessary to enhance our understanding of the therapeutic potential of flavonoids and their derivatives in the treatment of diabetic complications.

PTGES2 and RNASET2 identified as novel potential biomarkers and therapeutic targets for basal cell carcinoma: insights from proteome-wide mendelian randomization, colocalization, and MR-PheWAS analyses

Introduction

Basal cell carcinoma (BCC) is the most common skin cancer, lacking reliable biomarkers or therapeutic targets for effective treatment. Genome-wide association studies (GWAS) can aid in identifying drug targets, repurposing existing drugs, predicting clinical trial side effects, and reclassifying patients in clinical utility. Hence, the present study investigates the association between plasma proteins and skin cancer to identify effective biomarkers and therapeutic targets for BCC.

Methods

Proteome-wide mendelian randomization was performed using inverse-variance-weight and Wald Ratio methods, leveraging 1 Mb cis protein quantitative trait loci (cis-pQTLs) in the UK Biobank Pharma Proteomics Project (UKB-PPP) and the deCODE Health Study, to determine the causal relationship between plasma proteins and skin cancer and its subtypes in the FinnGen R10 study and the SAIGE database of Lee lab. Significant association with skin cancer and its subtypes was defined as a false discovery rate (FDR) < 0.05. pQTL to GWAS colocalization analysis was executed using a Bayesian model to evaluate five exclusive hypotheses. Strong colocalization evidence was defined as a posterior probability for shared causal variants (PP.H4) of ≥0.85. Mendelian randomization-Phenome-wide association studies (MR-PheWAS) were used to evaluate potential biomarkers and therapeutic targets for skin cancer and its subtypes within a phenome-wide human disease category.

Results

PTGES2, RNASET2, SF3B4, STX8, ENO2, and HS3ST3B1 (besides RNASET2, five other plasma proteins were previously unknown in expression quantitative trait loci (eQTL) and methylation quantitative trait loci (mQTL)) were significantly associated with BCC after FDR correction in the UKB-PPP and deCODE studies. Reverse MR showed no association between BCC and these proteins. PTGES2 and RNASET2 exhibited strong evidence of colocalization with BCC based on a posterior probability PP.H4 >0.92. Furthermore, MR-PheWAS analysis showed that BCC was the most significant phenotype associated with PTGES2 and RNASET2 among 2,408 phenotypes in the FinnGen R10 study. Therefore, PTGES2 and RNASET2 are highlighted as effective biomarkers and therapeutic targets for BCC within the phenome-wide human disease category.

Conclusion

The study identifies PTGES2 and RNASET2 plasma proteins as novel, reliable biomarkers and therapeutic targets for BCC, suggesting more effective clinical application strategies for patients.

Assessment of circulating proteins in thyroid cancer: Proteome-wide Mendelian randomization and colocalization analysis

The causality between circulating proteins and thyroid cancer (TC) remains unclear. We employed five large-scale circulating proteomic genome-wide association studies (GWASs) with up to 100,000 participants and a TC meta-GWAS (nCase = 3,418, nControl = 292,703) to conduct proteome-wide Mendelian randomization (MR) and Bayesian colocalization analysis. Protein and gene expressions were validated in thyroid tissue. Through MR analysis, we identified 26 circulating proteins with a putative causal relationship with TCs, among which NANS protein passed multiple corrections (P BH = 3.28e-5, 0.05/1,525). These proteins were involved in amino acids and organic acid synthesis pathways. Colocalization analysis further identified six proteins associated with TCs (VCAM1, LGMN, NPTX1, PLEKHA7, TNFAIP3, and BMP1). Tissue validation confirmed BMP1, LGMN, and PLEKHA7's differential expression between normal and TC tissues. We found limited evidence for linking circulating proteins and the risk of TCs. Our study highlighted the contribution of proteins, particularly those involved in amino acid metabolism, to TCs.

Novel Protein Biomarkers and Therapeutic Targets for Type 1 Diabetes and Its Complications: Insights from Summary-Data-Based Mendelian Randomization and Colocalization Analysis

Millions of patients suffer from type 1 diabetes (T1D) and its associated complications. Nevertheless, the pursuit of a cure for T1D has encountered significant challenges, with a crucial impediment being the lack of biomarkers that can accurately predict the progression of T1D and reliable therapeutic targets for T1D. Hence, there is an urgent need to discover novel protein biomarkers and therapeutic targets, which holds promise for targeted therapy for T1D. In this study, we extracted summary-level data on 4907 plasma proteins from 35,559 Icelanders and 2923 plasma proteins from 54,219 UK participants as exposures. The genome-wide association study (GWAS) summary statistics on T1D and T1D with complications were obtained from the R9 release results from the FinnGen consortium. Summary-data-based Mendelian randomization (SMR) analysis was employed to evaluate the causal associations between the genetically predicted levels of plasma proteins and T1D-associated outcomes. Colocalization analysis was utilized to investigate the shared genetic variants between the exposure and outcome. Moreover, transcriptome analysis and a protein-protein interaction (PPI) network further illustrated the expression patterns of the identified protein targets and their interactions with the established targets of T1D. Finally, a Mendelian randomization phenome-wide association study evaluated the potential side effects of the identified core protein targets. In the primary SMR analysis, we identified 72 potential protein targets for T1D and its complications, and nine of them were considered crucial protein targets. Within the group were five risk targets and four protective targets. Backed by evidence from the colocalization analysis, the protein targets were classified into four tiers, with MANSC4, CTRB1, SIGLEC5 and MST1 being categorized as tier 1 targets. Delving into the DrugBank database, we retrieved 11 existing medications for T1D along with their therapeutic targets. The PPI network clarified the interactions among the identified potential protein targets and established ones. Finally, the Mendelian randomization phenome-wide association study corroborated MANSC4 as a reliable target capable of mitigating the risk of various forms of diabetes, and it revealed the absence of adverse effects linked to CTRB1, SIGLEC5 and MST1. This study unveiled many protein biomarkers and therapeutic targets for T1D and its complications. Such advancements hold great promise for the progression of drug development and targeted therapy for T1D.

Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes

OBJECTIVE

Integrated analyses of plasma proteomics and genetic data in prospective studies can help assess the causal relevance of proteins, improve risk prediction, and discover novel protein drug targets for type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

We measured plasma levels of 2,923 proteins using Olink Explore among ∼2,000 randomly selected participants from China Kadoorie Biobank (CKB) without prior diabetes at baseline. Cox regression assessed associations of individual protein with incident T2D (n = 92 cases). Proteomic-based risk models were developed with discrimination, calibration, reclassification assessed using area under the curve (AUC), calibration plots, and net reclassification index (NRI), respectively. Two-sample Mendelian randomization (MR) analyses using cis-protein quantitative trait loci identified in a genome-wide association study of CKB and UK Biobank for specific proteins were conducted to assess their causal relevance for T2D, along with colocalization analyses to examine shared causal variants between proteins and T2D.

RESULTS

Overall, 33 proteins were significantly associated (false discovery rate <0.05) with risk of incident T2D, including IGFBP1, GHR, and amylase. The addition of these 33 proteins to a conventional risk prediction model improved AUC from 0.77 (0.73-0.82) to 0.88 (0.85-0.91) and NRI by 38%, with predicted risks well calibrated with observed risks. MR analyses provided support for the causal relevance for T2D of ENTR1, LPL, and PON3, with replication of ENTR1 and LPL in Europeans using different genetic instruments. Moreover, colocalization analyses showed strong evidence (pH4 > 0.6) of shared genetic variants of LPL and PON3 with T2D.

CONCLUSIONS

Proteomic analyses in Chinese adults identified novel associations of multiple proteins with T2D with strong genetic evidence supporting their causal relevance and potential as novel drug targets for prevention and treatment of T2D.

Impact of periodontitis on type 2 diabetes: a bioinformatic analysis

BACKGROUND

Periodontitis is strongly associated with type 2 diabetes (T2D) that results in serious complications and mortality. However, the pathogenic role of periodontitis in the development of T2D and the underlain mechanism have not been fully elucidated.

METHODS

A Mendelian randomization (MR) was performed to estimate the causality between two diseases. Bioinformatics tools, including gene ontology and pathway enrichment analyses, were employed to analyze the common differentially expressed genes (DEGs) in periodontitis and T2D. MR and colocalization analyses were then utilized to investigate the causal associations between potential pathogenic gene expression and the risk of T2D. Single cell-type expression analysis was further performed to detect the cellular localization of these genes.

RESULTS

Genetically predicted periodontitis was associated with a higher risk of T2D (OR, 1.469; 95% CI, 1.117-1.930; P = 0.006) and insulin resistance (OR 1.034; 95%CI 1.001-1.068; P = 0.041). 79 common DEGs associated with periodontitis and T2D were then identified and demonstrated enrichment mainly in CXC receptor chemokine receptor binding and interleutin-17 signaling pathway. The integration of GWAS with the expression quantitative trait locis of these genes from the peripheral blood genetically prioritized 6 candidate genes, including 2 risk genes (RAP2A, MCUR1) and 4 protective genes (WNK1, NFIX, FOS, PANX1) in periodontitis-related T2D. Enriched in natural killer cells, RAP2A (OR 4.909; 95% CI 1.849-13.039; P = 0.001) demonstrated high risk influence on T2D, and exhibited strong genetic evidence of colocalization (coloc.abf-PPH4 = 0.632).

CONCLUSIONS

This study used a multi-omics integration method to explore causality between periodontitis and T2D, and revealed molecular mechanisms using bioinformatics tools. Periodontitis was associated with a higher risk of T2D. MCUR1, RAP2A, FOS, PANX1, NFIX and WNK1 may play important roles in the pathogenesis of periodontitis-related T2D, shedding light on the development of potential drug targets.

Harnessing the power of proteomics in precision diabetes medicine

Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.

​Comprehensive mendelian randomization analysis of plasma proteomics to identify new therapeutic targets for the treatment of coronary heart disease and myocardial infarction

BACKGROUND

Ischemic heart disease is one of the leading causes of mortality worldwide, and thus calls for development of more effective therapeutic strategies. This study aimed to identify potential therapeutic targets for coronary heart disease (CHD) and myocardial infarction (MI) by investigating the causal relationship between plasma proteins and these conditions.

METHODS

A two-sample Mendelian randomization (MR) study was performed to evaluate more than 1600 plasma proteins for their causal associations with CHD and MI. The MR findings were further confirmed through Bayesian colocalization, Summary-data-based Mendelian Randomization (SMR), and Transcriptome-Wide Association Studies (TWAS) analyses. Further analyses, including enrichment analysis, single-cell analysis, MR analysis of cardiovascular risk factors, phenome-wide Mendelian Randomization (Phe-MR), and protein-protein interaction (PPI) network construction were conducted to verify the roles of selected causal proteins.

RESULTS

Thirteen proteins were causally associated with CHD, seven of which were also causal for MI. Among them, FES and PCSK9 were causal proteins for both diseases as determined by several analytical methods. PCSK9 was a risk factor of CHD (OR = 1.25, 95% CI: 1.13-1.38, P = 7.47E-06) and MI (OR = 1.36, 95% CI: 1.21-1.54, P = 2.30E-07), whereas FES was protective against CHD (OR = 0.68, 95% CI: 0.59-0.79, P = 6.40E-07) and MI (OR = 0.65, 95% CI: 0.54-0.77, P = 5.38E-07). Further validation through enrichment and single-cell analysis confirmed the causal effects of these proteins. Moreover, MR analysis of cardiovascular risk factors, Phe-MR, and PPI network provided insights into the potential drug development based on the proteins.

CONCLUSIONS

This study investigated the causal pathways associated with CHD and MI, highlighting the protective and risk roles of FES and PCSK9, respectively. FES. Specifically, the results showed that these proteins are promising therapeutic targets for future drug development.

Identification of potential drug targets for allergic diseases from a genetic perspective: A mendelian randomization study

BACKGROUND

Allergic diseases typically refer to a heterogeneous group of conditions primarily caused by the activation of mast cells or eosinophils, including atopic dermatitis (AD), allergic rhinitis (AR), and asthma. Asthma, AR, and AD collectively affect approximately one-fifth of the global population, imposing a significant economic burden on society. Despite the availability of drugs to treat allergic diseases, they have been shown to be insufficient in controlling relapses and halting disease progression. Therefore, new drug targets are needed to prevent the onset of allergic diseases.

METHOD

We employed a Mendelian randomization approach to identify potential drug targets for the treatment of allergic diseases. Leveraging 1798 genetic instruments for 1537 plasma proteins from the latest reported Genome-Wide Association Studies (GWAS), we analyzed the GWAS summary statistics of Ferreira MA et al. (nCase = 180,129, nControl = 180,709) using the Mendelian randomization method. Furthermore, we validated our findings in the GWAS data from the FinnGen and UK Biobank cohorts. Subsequently, we conducted sensitivity tests through reverse causal analysis, Bayesian colocalization analysis, and phenotype scanning. Additionally, we performed protein-protein interaction analysis to determine the interaction between causal proteins. Finally, based on the potential protein targets, we conducted molecular docking to identify potential drugs for the treatment of allergic diseases.

RESULTS

At Bonferroni significance (p < 3.25 × 10-5), the Mendelian randomization analysis revealed 11 significantly associated protein-allergic disease pairs. Among these, the increased levels of TNFAIP3, ERBB3, TLR1, and IL1RL2 proteins were associated with a reduced risk of allergic diseases, with corresponding odds ratios of 0.82 (0.76-0.88), 0.74 (0.66-0.82), 0.49 (0.45-0.55), and 0.81 (0.75-0.87), respectively. Conversely, increased levels of IL6R, IL1R1, ITPKA, IL1RL1, KYNU, LAYN, and LRP11 proteins were linked to an elevated risk of allergic diseases, with corresponding odds ratios of 1.04 (1.03-1.05), 1.25 (1.18-1.34), 1.48 (1.25-1.75), 1.14 (1.11-1.18), 1.09 (1.05-1.12), 1.96 (1.56-2.47), and 1.05 (1.03-1.07), respectively. Bayesian colocalization analysis suggested that LAYN (coloc.abf-PPH4 = 0.819) and TNFAIP3 (coloc.abf-PPH4 = 0.930) share the same variant associated with allergic diseases.

CONCLUSIONS

Our study demonstrates a causal association between the expression levels of TNFAIP3 and LAYN and the risk of allergic diseases, suggesting them as potential drug targets for these conditions, warranting further clinical investigation.

Gut microbiota and autism spectrum disorders: a bidirectional Mendelian randomization study

Background

In recent years, observational studies have provided evidence supporting a potential association between autism spectrum disorder (ASD) and gut microbiota. However, the causal effect of gut microbiota on ASD remains unknown.

Methods

We identified the summary statistics of 206 gut microbiota from the MiBioGen study, and ASD data were obtained from the latest Psychiatric Genomics Consortium Genome-Wide Association Study (GWAS). We then performed Mendelian randomization (MR) to determine a causal relationship between the gut microbiota and ASD using the inverse variance weighted (IVW) method, simple mode, MR-Egger, weighted median, and weighted model. Furthermore, we used Cochran's Q test, MR-Egger intercept test, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and leave-one-out analysis to identify heterogeneity and pleiotropy. Moreover, the Benjamin-Hochberg approach (FDR) was employed to assess the strength of the connection between exposure and outcome. We performed reverse MR analysis on the gut microbiota that were found to be causally associated with ASD in the forward MR analysis to examine the causal relationships. The enrichment analyses were used to analyze the biological function at last.

Results

Based on the results of IVW results, genetically predicted family Prevotellaceae and genus Turicibacter had a possible positive association with ASD (IVW OR=1.14, 95% CI: 1.00-1.29, P=3.7×10-2), four gut microbiota with a potential protective effect on ASD: genus Dorea (OR=0.81, 95% CI: 0.69-0.96, P=1.4×10-2), genus Ruminiclostridium5 (OR=0.81, 95% CI: 0.69-0.96, P=1.5×10-2), genus Ruminococcus1 (OR=0.83, 95% CI: 0.70-0.98, P=2.8×10-2), and genus Sutterella (OR=0.82, 95% CI: 0.68-0.99, P=3.6×10-2). After FDR multiple-testing correction we further observed that there were two gut microbiota still have significant relationship with ASD: family Prevotellaceae (IVW OR=1.24; 95% CI: 1.09-1.40, P=9.2×10-4) was strongly positively correlated with ASD and genus RuminococcaceaeUCG005 (IVW OR=0.78, 95% CI: 0.67-0.89, P=6.9×10-4) was strongly negatively correlated with ASD. The sensitivity analysis excluded the influence of heterogeneity and horizontal pleiotropy.

Conclusion

Our findings reveal a causal association between several gut microbiomes and ASD. These results deepen our comprehension of the role of gut microbiota in ASD's pathology, providing the foothold for novel ideas and theoretical frameworks to prevent and treat this patient population in the future.

Proteomic insights into the associations between obesity, lifestyle factors, and coronary artery disease

BACKGROUND

We aimed to investigate the protein pathways linking obesity and lifestyle factors to coronary artery disease (CAD).

METHODS

Summary-level genome-wide association statistics of CAD were obtained from the CARDIoGRAMplusC4D consortium (60,801 cases and 123,504 controls) and the FinnGen study (R8, 39,036 cases and 303,463 controls). Proteome-wide Mendelian randomization (MR) analysis was conducted to identify CAD-associated blood proteins, supplemented by colocalization analysis to minimize potential bias caused by linkage disequilibrium. Two-sample MR analyses were performed to assess the associations of genetically predicted four obesity measures and 13 lifestyle factors with CAD risk and CAD-associated proteins' levels. A two-step network MR analysis was conducted to explore the mediating effects of proteins in the associations between these modifiable factors and CAD.

RESULTS

Genetically predicted levels of 41 circulating proteins were associated with CAD, and 17 of them were supported by medium to high colocalization evidence. PTK7 (protein tyrosine kinase-7), RGMB (repulsive guidance molecule BMP co-receptor B), TAGLN2 (transgelin-2), TIMP3 (tissue inhibitor of metalloproteinases 3), and VIM (vimentin) were identified as promising therapeutic targets. Several proteins were found to mediate the associations between some modifiable factors and CAD, with PCSK9, C1S, AGER (advanced glycosylation end product-specific receptor), and MST1 (mammalian Ste20-like kinase 1) exhibiting highest frequency among the mediating networks.

CONCLUSIONS

This study suggests pathways explaining the associations of obesity and lifestyle factors with CAD from alterations in blood protein levels. These insights may be used to prioritize therapeutic intervention for further study.