Identification of novel proteins for lacunar stroke by integrating genome-wide association data and human brain proteomes

Application of proteomics for novel drug discovery and risk prediction optimisation in stroke and myocardial infarction: a review of in-human studies

The use of proteomics in human studies investigating stroke and myocardial infarction (MI) has been increasing, prompting a review of the literature. This revealed proteinaceous biomarkers of stroke from thrombi, brain tissue, cells, and particles, some of which cross the blood-brain barrier (BBB). Several proteins were also implicated in coronary artery disease (CAD), which often underlies MI, cholesterol transportation, and inflammation. Furthermore, the platelet proteome revealed itself as a potential therapeutic target, along with differentially expressed proteins associated with MI progression. Moreover, proteomic data enhanced the performance of conventional risk scores and causal protein discovery has improved interventions and drug development for patients with MI and other conditions. These findings suggest that proteomics holds much promise for future stroke and MI research.

Genetic insights into drug targets for sporadic Creutzfeldt-Jakob disease: Integrative multi-omics analysis

OBJECTIVE

Sporadic Creutzfeldt-Jakob disease (sCJD) is a fatal rapidly progressive neurodegenerative disorder with no effective therapeutic interventions. We aimed to identify potential genetically-supported drug targets for sCJD by integrating multi-omics data.

METHODS

Multi-omics-wide association studies, Mendelian randomization, and colocalization analyses were employed to explore potential therapeutic targets using expression, single-cell expression, DNA methylation, and protein quantitative trait locus data from blood and brain tissues. Outcome data was from a case-control genome-wide association study, which included 4110 sCJD patients and 13,569 controls. Further investigations encompassed druggability, potential side effects, and associated biological pathways of the identified targets.

RESULTS

Integrative multi-omics analysis identified 23 potential therapeutic targets for sCJD, with five targets (STX6, XYLT2, PDIA4, FUCA2, KIAA1614) having higher levels of evidence. One target (XYLT2) shows promise for repurposing, two targets (XYLT2, PDIA4) are druggable, and three (STX6, KIAA1614, and FUCA2) targets represent potential future breakthrough points. The expression level of STX6 and XYLT2 in neurons and oligodendrocytes was closely associated with an increased risk of sCJD. Brain regions with high expression of STX6 or causal links to sCJD were often those areas commonly affected by sCJD.

CONCLUSIONS

Our study identified five potential therapeutic targets for sCJD. Further investigations are warranted to elucidate the mechanisms underlying the new targets for developing disease therapies or initiate clinical trials.

Genome-Wide Mendelian Randomization Study Reveals Druggable Genes for Cerebral Small Vessel Disease

BACKGROUND

Cerebral small vessel disease (CSVD) is a group of neurological disorders that affect the small blood vessels within the brain, for which no effective treatments are currently available. We conducted a Mendelian randomization (MR) study to identify candidate therapeutic genes for CSVD.

METHODS

We retrieved genome-wide association study data from 6 recently conducted, extensive investigations focusing on CSVD magnetic resonance imaging markers and performed a 2-sample MR analysis to assess the potential causal effects of gene expression and protein level within druggable genes on CSVD in blood and brain tissues. Colocalization analyses and repeat studies were undertaken to verify the relationship. Additionally, mediation analysis was conducted to explore the potential mechanisms involving druggable genes and known risk factors for CSVD. Finally, phenome-wide MR analyses were applied to evaluate the potential adverse effects related to the identified druggable genes for CSVD treatment.

RESULTS

Overall, 5 druggable genes consistently showed associations with CSVD in MR analyses across both the discovery and validation cohorts. Notably, the ALDH2 and KLHL24 genes were identified as associated with CSVD in both blood and brain tissues, whereas the genes ADRB1, BTN3A2, and EFEMP1 were exclusively detected in brain tissue. Moreover, mediation analysis elucidated the proportion of the total effects mediated by CSVD risk factors through candidate druggable genes, which ranged from 5.5% to 18.5%, and offered potential explanations for the observed results. A comprehensive phenome-wide MR analysis further emphasized both the therapeutic benefits and potential side effects of targeting these candidate druggable genes.

CONCLUSIONS

This study provides genetic evidence supporting the potential therapeutic benefits of targeting druggable genes for treating CSVD, which will be useful for prioritizing CSVD drug development.

Cardiometabolic traits mediating the effect of education on the risk of DKD and CKD: a Mendelian randomization study

Background

Both diabetic kidney disease (DKD) and chronic kidney disease (CKD) are more prevalent among individuals with lower levels of education in observational studies. To quantify the mediation effect of recognized cardiometabolic traits, we obtain causal estimates between education and DKD as well as CKD.

Materials and methods

We assessed the causal effect of education on DKD and CKD, separately estimated the causal effect of 26 cardiometabolic traits on DKD and CKD, and finally calculated the mediating effects and mediating proportions of each using two-step, two-sample multivariable Mendelian randomization (MVMR). Furthermore, the genetic association between exposure, mediators, and outcomes was investigated using linkage disequilibrium score (LDSC) regression analysis. Expression quantitative trait loci (eQTL) were retrieved from the Genotype-Tissue Expression Project (GTEx) v8 to serve as genetic instrumental variables. Transcriptome-wide association studies (TWAS), Bayesian colocalization analysis, and Summary-data-based Mendelian Randomization (SMR) analysis were performed to explore underlying susceptibility genes between education, mediators, and kidney diseases.

Results

Higher education with a genetically predicted 1-SD (4.2 years) was linked to a 48.64% decreased risk of DKD and a 29.08% decreased risk of CKD. After extensive evaluation of 26 cardiometabolic traits, 7 and 6 causal mediators were identified as mediating the effects of education on DKD and CKD, respectively. The largest mediating factor between education and DKD was BMI, which was followed by WHR, T2D, fasting insulin, SBP, fasting glucose, and DBP. In contrast, candidate mediators in the education-to-CKD pathway included BMI, followed by cigarettes smoked per day, WHR, SBP, T2D, and DBP. MR analysis revealed that TP53INP1 was found to be a shared susceptibility gene for cardiometabolic traits and DKD, while L3MBTL3 was found to be a shared susceptibility gene for cardiometabolic traits and CKD.

Conclusion

Our findings provide solid evidence that education has a causally protective effect on the development of DKD and CKD. We additionally reveal significant directions for intervention on cardiometabolic traits that mitigate the negative effects of educational inequities on the onset of DKD and CKD. Our work demonstrates a shared genetic basis between education, cardiometabolic traits, and kidney diseases. Future research aiming at lowering kidney risk may benefit from these findings.

NMT2 alleviates depression-like behavior in a rat model of chronic unpredictable stress: An integrated proteomic and phosphoproteomic analysis

Proteomics has been widely used to investigate multiple diseases. Combining the analyses of proteomics with phosphoproteomics can be used to further explain the pathological mechanisms of depression. In this study, depression-like behavior was induced in a rat model of chronic unpredictable mild stress (CUMS). We subsequently conducted the sucrose preference test, open field experiment, and forced swimming test to assess depressive-like behavior. Proteomic and phosphoproteomic sequencing of the hippocampal tissues from depressive-like behavior and normal rats were analyzed to identify differentially expressed proteins (DEPs) and differentially phosphorylated proteins (DPPs). Differentially expressed phosphorylated proteins (DEPPs) were obtained by intersecting the DEPs and DPPs, and functional enrichment analysis, as well as ingenuity pathway analysis (IPA), were subsequently performed. The study also investigated correlations among the DEPPs and used qRT-PCR to quantify the expression levels of key genes. Five DEPPs were identified, Gys1, Nmt2, Lrp1, Bin1, and Atp1a1, which were found to activate the synaptogenesis signaling pathway, induce mitochondrial dysfunction, and activate the phosphoinositide biosynthesis and degradation pathways. The qRT-PCR results confirmed the proteomic findings for Gys1, Nmt2, Lrp1, and Atp1a1. Importantly, inhibiting Nmt2 was found to alleviate depression-like behavior and alleviate neuronal apoptosis in the hippocampus of CUMS rats. In conclusion, we identified five DEPPs associated with the synaptogenesis signaling pathway, mitochondrial dysfunction, and phosphoinositide biosynthesis and degradation in depression. Furthermore, NMT2 may be a potential target for the treatment or diagnosis of depression. Our findings provide novel insights into the molecular mechanisms of depression.

Integrating plasma proteomics with genome-wide association data to identify novel drug targets for inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic disease that includes Crohn's disease (CD) and ulcerative colitis (UC). Although genome-wide association studies (GWASs) have identified many relevant genetic risk loci, the impact of these loci on protein abundance and their potential utility as clinical therapeutic targets remain uncertain. Therefore, this study aimed to investigate the pathogenesis of IBD and identify effective therapeutic targets through a comprehensive and integrated analysis. We systematically integrated GWAS data related to IBD, UC and CD (N = 25,305) by the study of de Lange KM with the human blood proteome (N = 7213) by the Atherosclerosis Risk in Communities (ARIC) study. Proteome-wide association study (PWAS), mendelian randomisation (MR) and Bayesian colocalisation analysis were used to identify proteins contributing to the risk of IBD. Integrative analysis revealed that genetic variations in IBD, UC and CD affected the abundance of five (ERAP2, RIPK2, TALDO1, CADM2 and RHOC), three (VSIR, HGFAC and CADM2) and two (MST1 and FLRT3) cis-regulated plasma proteins, respectively (P < 0.05). Among the proteins identified via Bayesian colocalisation analysis, CADM2 was found to be an important common protein between IBD and UC. A drug and five druggable target genes were identified from DGIdb after Bayesian colocalisation analysis. Our study's findings from genetic and proteomic approaches have identified compelling proteins that may serve as important leads for future functional studies and potential drug targets for IBD (UC and CD).

Proteome-wide association studies have predicted that the protein abundance of LSM6, GMPPB, ICA1L, and CISD2 is associated with attention-deficit/hyperactivity disorder

Identification of changes in protein abundance for attention-deficit/hyperactivity disorder (ADHD) is important for potential disease mechanisms and therapeutic study for ADHD. In order to identify candidate proteins that confer risk for ADHD, a proteome-wide association study (PWAS) for ADHD was conducted by integrating two human brain proteome datasets and the ADHD genome-wide association study (GWAS) summary statistics released by the Psychiatric Genomics Consortium (PGC). A total of 11 risk proteins were identified as significant candidates that passed the bonferroni corrected proteome-wide significant (PWS) level. The predicted protein abundance level of LSM6, GMPPB, ICA1L and CISD2 are shown significantly associated with ADHD in both proteome datasets, highlighting their potential role in ADHD pathogenesis. A transcriptome-wide association study (TWAS) of ADHD was also conducted, and 13 genes with predicted expression changes related to ADHD were identified. GMPPB, ICA1L and NAT6 were supported by both TWAS and PWASs analysis. This study uncovers the predicted protein abundance changes that confer risk for ADHD and pinpoints a number of high-confidence protein candidates (e.g. LSM6, GMPPB, ICA1L, CISD2) for further functional exploration studies and drug development targeting these proteins.

Mendelian randomization analysis of the brain, cerebrospinal fluid, and plasma proteome identifies potential drug targets for attention deficit hyperactivity disorder

BACKGROUND

The need for new therapeutics for attention deficit hyperactivity disorder (ADHD) is evident. Brain, cerebrospinal fluid (CSF), and plasma protein biomarkers with causal genetic evidence could represent potential drug targets. However, a comprehensive screen of the proteome has not yet been conducted.

METHODS

We employed a three-pronged approach using Mendelian Randomization (MR) and Bayesian colocalization analysis. Firstly, we studied 608 brains, 214 CSF, and 612 plasma proteins as potential causal mediators of ADHD using MR analysis. Secondly, we analysed the consistency of the discovered biomarkers across three distinct subtypes of ADHD: childhood, persistent, and late-diagnosed ADHD. Finally, we extended our analysis to examine the correlation between identified biomarkers and Tourette syndrome and pervasive autism spectrum disorder (ASD), conditions often linked with ADHD. To validate the MR findings, we conducted sensitivity analysis. Additionally, we performed cell type analysis on the human brain to identify risk genes that are notably enriched in various brain cell types.

FINDINGS

After applying Bonferroni correction, we found that the risk of ADHD was increased by brain proteins GMPPB, NAA80, HYI, CISD2, and HYI, TIE1 in CSF and plasma. Proteins GMPPB, NAA80, ICA1L, CISD2, TIE1, and RMDN1 showed overlapped loci with ADHD risk through Bayesian colocalization. Overexpression of GMPPB protein was linked to an increase in the risk for all three ADHD subtypes. While ICA1L provided protection against both ASD and ADHD, CISD2 increased the probability of both disorders. Cell-specific studies revealed that GMPPB, NAA80, ICA1L, and CISD2 were predominantly present on the surface of excitatory-inhibitory neurons.

INTERPRETATION

Our comprehensive MR investigation of the brain, CSF, and plasma proteomes revealed seven proteins with causal connections to ADHD. Particularly, GMPPB and TIE1 emerged as intriguing targets for potential ADHD therapy.

FUNDING

This work was partly funded by the Key R & D Program of Zhejiang (T.L. 2022C03096); the National Natural Science Foundation of China Project (C.Z. 82001413); Postdoctoral Foundation of West China Hospital (C.Z. 2020HXBH163).

Plasma proteome analysis implicates novel proteins as potential therapeutic targets for chronic kidney disease: A proteome-wide association study

Chronic kidney disease (CKD) is prevalent globally with limited therapeutic drugs available. To systemically identify novel proteins involved in the pathogenesis of CKD and possible therapeutic targets, we integrated human plasma proteomes with the genome-wide association studies (GWASs) of CKD, estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN) to perform proteome-wide association study (PWAS), Mendelian Randomization and Bayesian colocalization analyses. The single-cell RNA sequencing data of healthy human and mouse kidneys were analyzed to explore the cell-type specificity of identified genes. Functional enrichment analysis was conducted to investigate the involved signaling pathways. The PWAS identified 22 plasma proteins significantly associated with CKD. Of them, the significant associations of three proteins (INHBC, LMAN2, and SNUPN) were replicated in the GWASs of eGFR, and BUN. Mendelian Randomization analyses showed that INHBC and SNUPN were causally associated with CKD, eGFR, and BUN. The Bayesian colocalization analysis identified shared causal variants for INHBC in CKD, eGFR, and BUN (all PP4 > 0.75). The single-cell RNA sequencing revealed that the INHBC gene was sparsely scattered within the kidney cells. This proteomic study revealed that INHBC, LMAN2, and SNUPN may be involved in the pathogenesis of CKD, which represent novel therapeutic targets and warrant further exploration in future research.

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.

​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.

Elucidating the susceptibility to breast cancer: an in-depth proteomic and transcriptomic investigation into novel potential plasma protein biomarkers

Objectives: This study aimed to identify plasma proteins that are associated with and causative of breast cancer through Proteome and Transcriptome-wide association studies combining Mendelian Randomization. Methods: Utilizing high-throughput datasets, we designed a two-phase analytical framework aimed at identifying novel plasma proteins that are both associated with and causative of breast cancer. Initially, we conducted Proteome/Transcriptome-wide association studies (P/TWAS) to identify plasma proteins with significant associations. Subsequently, Mendelian Randomization was employed to ascertain the causation. The validity and robustness of our findings were further reinforced through external validation and various sensitivity analyses, including Bayesian colocalization, Steiger filtering, heterogeneity and pleiotropy. Additionally, we performed functional enrichment analysis of the identified proteins to better understand their roles in breast cancer and to assess their potential as druggable targets. Results: We identified 5 plasma proteins demonstrating strong associations and causative links with breast cancer. Specifically, PEX14 (OR = 1.201, p = 0.016) and CTSF (OR = 1.114, p < 0.001) both displayed positive and causal association with breast cancer. In contrast, SNUPN (OR = 0.905, p < 0.001), CSK (OR = 0.962, p = 0.038), and PARK7 (OR = 0.954, p < 0.001) were negatively associated with the disease. For the ER-positive subtype, 3 plasma proteins were identified, with CSK and CTSF exhibiting consistent trends, while GDI2 (OR = 0.920, p < 0.001) was distinct to this subtype. In ER-negative subtype, PEX14 (OR = 1.645, p < 0.001) stood out as the sole protein, even showing a stronger causal effect compared to breast cancer. These associations were robustly supported by colocalization and sensitivity analyses. Conclusion: Integrating multiple data dimensions, our study successfully pinpointed plasma proteins significantly associated with and causative of breast cancer, offering valuable insights for future research and potential new biomarkers and therapeutic targets.

An augmented Mendelian randomization approach provides causality of brain imaging features on complex traits in a single biobank-scale dataset

Mendelian randomization (MR) is an effective approach for revealing causal risk factors that underpin complex traits and diseases. While MR has been more widely applied under two-sample settings, it is more promising to be used in one single large cohort given the rise of biobank-scale datasets that simultaneously contain genotype data, brain imaging data, and matched complex traits from the same individual. However, most existing multivariable MR methods have been developed for two-sample setting or a small number of exposures. In this study, we introduce a one-sample multivariable MR method based on partial least squares and Lasso regression (MR-PL). MR-PL is capable of considering the correlation among exposures (e.g., brain imaging features) when the number of exposures is extremely upscaled, while also correcting for winner's curse bias. We performed extensive and systematic simulations, and demonstrated the robustness and reliability of our method. Comprehensive simulations confirmed that MR-PL can generate more precise causal estimates with lower false positive rates than alternative approaches. Finally, we applied MR-PL to the datasets from UK Biobank to reveal the causal effects of 36 white matter tracts on 180 complex traits, and showed putative white matter tracts that are implicated in smoking, blood vascular function-related traits, and eating behaviors.

Proteome-wide mendelian randomization identifies causal plasma proteins in venous thromboembolism development

Genome-wide association studies (GWAS) have identified numerous risk loci for venous thromboembolism (VTE), but it is challenging to decipher the underlying mechanisms. We employed an integrative analytical pipeline to transform genetic associations to identify novel plasma proteins for VTE. Proteome-wide association studies (PWAS) were determined by functional summary-based imputation leveraging data from a genome-wide association analysis (14,429 VTE patients, 267,037 controls), blood proteomes (1348 cases), followed by Mendelian randomization, Bayesian colocalization, protein-protein interaction, and pathway enrichment analysis. Twenty genetically regulated circulating protein abundances (F2, F11, ABO, PLCG2, LRP4, PLEK, KLKB1, PROC, KNG1, THBS2, SERPINA1, RARRES2, CEL, GP6, SERPINE2, SERPINA10, OBP2B, EFEMP1, F5, and MSR1) were associated with VTE. Of these 13 proteins demonstrated Mendelian randomized correlations. Six proteins (F2, F11, PLEK, SERPINA1, RARRES2, and SERPINE2) had strong support in colocalization analysis. Utilizing multidimensional data, this study suggests PLEK, SERPINA1, and SERPINE2 as compelling proteins that may provide key hints for future research and possible diagnostic and therapeutic targets for VTE.

Proteome-wide mendelian randomization study implicates therapeutic targets in common cancers

BACKGROUND

The interest in targeted cancer therapies has been growing rapidly. While numerous cancer biomarkers and targeted treatment strategies have been developed and employed, there are still significant limitations and challenges in the early diagnosis and targeted treatment of cancers. Accordingly, there is an urgent need to identify novel targets and develop new targeted drugs.

METHODS

The study was conducted using combined cis-Mendelian randomization (cis-MR) and colocalization analysis. We analyzed data from 732 plasma proteins to identify potential drug targets associated with eight site-specific cancers. These findings were further validated using the UK Biobank dataset. Then, a protein-protein interaction network was also constructed to examine the interplay between the identified proteins and the targets of existing cancer medications.

RESULTS

This MR analysis revealed associations between five plasma proteins and prostate cancer, five with breast cancer, and three with lung cancer. Subsequently, these proteins were classified into four distinct target groups, with a focus on tier 1 and 2 targets due to their higher potential to become drug targets. Our study indicatied that genetically predicted KDELC2 (OR: 0.89, 95% CI 0.86-0.93) and TNFRSF10B (OR: 0.74, 95% CI 0.65-0.83) are inversely associated with prostate cancer. Furthermore, we observed an inverse association between CPNE1 (OR: 0.96, 95% CI 0.94-0.98) and breast cancer, while PDIA3 (OR: 1.19, 95% CI 1.10-1.30) were found to be associated with the risk of breast cancer. In addition, we also propose that SPINT2 (OR: 1.05, 95% CI 1.03-1.06), GSTP1 (OR: 0.82, 95% CI 0.74-0.90), and CTSS (OR: 0.91, 95% CI 0.88-0.95) may serve as potential therapeutic targets in prostate cancer. Similarly, GDI2 (OR: 0.85, 95% CI 0.80-0.91), ISLR2 (OR: 0.87, 95% CI 0.82-0.93), and CTSF (OR: 1.14, 95% CI 1.08-1.21) could potentially be targets for breast cancer. Additionally, we identified SFTPB (OR: 0.93, 95% CI 0.91-0.95), ICAM5 (OR: 0.95, 95% CI 0.93-0.97), and FLRT3 (OR: 1.10, 95% CI 1.05-1.15) as potential targets for lung cancer. Notably, TNFRSF10B, GSTP1, and PDIA3 were found to interact with the target proteins of current medications used in prostate or breast cancer treatment.

CONCLUSIONS

This comprehensive analysis has highlighted thirteen plasma proteins with potential roles in three site-specific cancers. Continued research in this area may reveal their therapeutic potential, particularly KDELC2, TNFRSF10B, CPNE1, and PDIA3, paving the way for more effective cancer treatments.

Identifying causal genes for migraine by integrating the proteome and transcriptome

BACKGROUND

While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine.

METHODS

We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes.

RESULTS

We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine.

CONCLUSIONS

Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.

Novel Functional Features of cGMP Substrate Proteins IRAG1 and IRAG2

The inositol triphosphate-associated proteins IRAG1 and IRAG2 are cGMP kinase substrate proteins that regulate intracellular Ca²⁺. Previously, IRAG1 was discovered as a 125 kDa membrane protein at the endoplasmic reticulum, which is associated with the intracellular Ca²⁺ channel IP₃R-I and the PKGIβ and inhibits IP₃R-I upon PKGIβ-mediated phosphorylation. IRAG2 is a 75 kDa membrane protein homolog of IRAG1 and was recently also determined as a PKGI substrate. Several (patho-)physiological functions of IRAG1 and IRAG2 were meanwhile elucidated in a variety of human and murine tissues, e.g., of IRAG1 in various smooth muscles, heart, platelets, and other blood cells, of IRAG2 in the pancreas, heart, platelets, and taste cells. Hence, lack of IRAG1 or IRAG2 leads to diverse phenotypes in these organs, e.g., smooth muscle and platelet disorders or secretory deficiency, respectively. This review aims to highlight the recent research regarding these two regulatory proteins to envision their molecular and (patho-)physiological tasks and to unravel their functional interplay as possible (patho-)physiological counterparts.

Polymorphism of SERF2, the gene encoding a heat-resistant obscure (Hero) protein with chaperone activity, is a novel link in ischemic stroke

Background

Ischemic stroke (IS) is one of the most serious cardiovascular events associated with high risk of death or disability. The growing body of evidence highlights molecular chaperones as especially important players in the pathogenesis of the disease. Since six small proteins called "Hero" have been recently identified as a novel class of chaperones we aimed to evaluate whether SNP rs4644832 in SERF2 gene encoding the member of Hero-proteins, is associated with the risk of IS.

Methods

A total of 1929 unrelated Russians (861 patients with IS and 1068 healthy individuals) from Central Russia were recruited into the study. Genotyping was done using a probe-based PCR approach. Statistical analysis was carried out in the whole group and stratified by age, gender and smoking status.

Results

Analysis of the link between rs4644832 SERF2 and IS showed that G allele is the risk factor of IS only in females (OR=1.29, 95%CI 1.02-1.64, Padj=0.035). In addition, the analysis of associations of rs4644832 SERF2 and IS depending on the smoking status revealed that this genetic variant is associated with an increased risk of IS exclusively in non-smoking individuals (OR=1.26, 95%CI 1.01-1.56, P = 0.041).

Discussion

Sex- and smoking interactions between rs4644832 polymorphism and IS may be related to the impact of tobacco components metabolism and sex hormones on SERF2 expression.

Conclusion

The present study reveals the novel genetic association between rs4644832 polymorphism and the risk of IS suggesting that SERF2, the part of the protein quality control system, contributes to the pathogenesis of the disease.