Genetic insights into therapeutic targets for aortic aneurysms: A Mendelian randomization study

Identification of potential therapeutic targeting in ovarian aging from genetic screening with clinical validation

PURPOSE

To screen drug targets of ovarian aging from a genetic perspective.

METHODS

Systematic analyses were conducted with cis-expression quantitative trait loci data of druggable genes extracted as instrument variables. Summary statistics were from large genome-wide association studies for age at menopause. The following colocalization analysis was utilized to examine whether identified genes and ovarian aging shared causal variants. Furthermore, clinical validation was conducted by comparing expression of identified genes in granulosa cells from women with normal or diminished ovarian reserve (DOR) who went through in vitro fertilization (IVF) and by evaluating correlation of targeted gene expression with ovarian function and IVF outcomes. Moreover, single-nuclear RNA (snRNA) seq and drug database were analyzed to find target cells within the ovary and potential drugs targeting identified genes.

RESULTS

Systematic analyses identified five therapeutic targets of ovarian aging, including four protective factors (BRCA1, KLHL18, PNP, SRPK1) and one risk factor (PDIA3). The change in expression level of four protective factors has been verified in clinical validation. Particularly, both BRCA1 and SRPK1 have been downregulated among advanced-aged women with DOR and were positively correlated with anti-Müllerian hormone and antral follicle count. Specific target cells and potential small molecule targeted drugs of these genes were identified through snRNA analysis and searching in the drug database.

CONCLUSIONS

By systematic genetic analyses combined with clinical validation, we identified five potential druggable genes for ovarian aging, providing theoretical basis and promising direction of therapeutic genetic targets for ovarian aging in the future.

Calbindin 2 as a Novel Biomarker and Therapeutic Target for Abdominal Aortic Aneurysm: Integrative Analysis of Human Proteomes and Genetics

BACKGROUND

Abdominal aortic aneurysm (AAA) is a clinical life-threatening issue. No pharmacological treatments are currently approved for the prevention and treatment of AAA. Therefore, identifying novel biomarkers and therapeutic targets is crucial for improving AAA management and outcomes.

METHODS

To identify plasma proteins with potential causal effects on AAA, we integrated genetic evidence from proteome-wide Mendelian randomization, genetic correlation, and colocalization analysis. The role of identified proteins in AAA was further explored through the phenome-wide association study and mediation analysis. Multiomics data analysis, including bulk RNA sequencing, single-cell/single-nucleus RNA sequencing, and spatial transcriptomics, was employed to characterize the expression patterns of these proteins. Experimental validation was performed using an AAA model in apolipoprotein E-deficient mice infused with angiotensin II. Druggability analysis was conducted to identify drug candidates, which were tested in preclinical mouse models.

RESULTS

CALB2 (calbindin 2) was identified as having a causal effect on AAA and may influence the progression of AAA through the regulation of lipid metabolism. Multiomics analysis revealed that CALB2 is predominantly expressed in the mesothelial cells of adipose tissues. Inhibition of CALB2 in an AAA mouse model alleviated AAA progression. Druggability analysis identified lenalidomide and genistein as potential therapeutic candidates, and experiments confirmed their efficacy in preventing AAA development.

CONCLUSIONS

This study identifies CALB2 as being associated with an increased risk of AAA and suggests that i might be a novel biomarker and therapeutic molecule for AAA management. Lenalidomide and genistein hold promising potential as treatments for patients with AAA.

TEX10: A Novel Drug Target and Potential Therapeutic Direction for Sleep Apnea Syndrome

Background

Sleep apnea syndrome (SAS) is a prevalent sleep disorder strongly associated with obesity, metabolic dysregulation, and cardiovascular diseases. While its underlying pathophysiological mechanisms remain incompletely understood, genetic factors likely play a pivotal role in SAS pathogenesis. This study investigates the causal relationships between potential drug target genes and SAS using multiple statistical approaches, aiming to provide novel insights for targeted therapeutic development.

Methods

We conducted a comprehensive genetic analysis integrating multiple methodologies to investigate gene-SAS relationships. Using publicly available GWAS and eQTL databases, we performed Mendelian Randomization (MR) analysis with the inverse variance weighted (IVW) method, validated by weighted median and MR-Egger approaches. Summary-data-based MR (SMR) analysis, coupled with HEIDI testing, assessed direct gene expression-SAS associations while controlling for linkage disequilibrium (LD). Colocalization analysis evaluated the probability of shared causal variants between SNPs, gene expression, and SAS. Statistical significance was determined using Benjamini-Hochberg multiple testing correction (FDR < 0.05). Additionally, mediation analysis explored TEX10's influence on SAS through metabolic intermediates including BMI, waist circumference, and HDL cholesterol.

Results

We identified 18 candidate drug target genes significantly associated with SAS, with MAPKAPK3, TNXB, MPHOSPH8, and TEX10 showing consistent associations across multiple analyses. TEX10, in particular, exhibited significant associations with SAS risk in blood, cerebral cortex, hippocampus, and basal ganglia (PP.H4 > 0.9). Mediation analysis suggested that TEX10 might influence SAS risk indirectly through BMI, waist circumference, and HDL cholesterol levels.

Conclusion

Our study identified multiple potential therapeutic targets causally linked to SAS, with TEX10 emerging as a key candidate gene. These findings advance our understanding of SAS pathogenesis and offer promising directions for personalized diagnostics and targeted therapies.

PRCP is a promising drug target for intracranial aneurysm rupture supported via multi-omics analysis

BACKGROUND

Cerebral aneurysms are life-threatening cerebrovascular disorders. Currently, there are no effective treatments for preventing disease progression. Mendelian randomisation (MR) is widely used to repurify licensed drugs and identify new therapeutic targets. Therefore, this study aims to investigate effective drug targets for preventing the formation and rupture of cerebral aneurysms and analyse their potential mechanisms.

METHODS

We performed a comprehensive study integrating two-sample MR analysis, colocalisation analysis and summary data-based Mendelian randomisation (SMR) to assess the causal effects of blood and brain druggable cis-expression quantitative trait loci (cis-eQTLs) on intracranial aneurysm (IA), unruptured intracranial aneurysm (UIA) and subarachnoid haemorrhage of IA rupture (SAH). Druggable genes were obtained from the study by Chris Finan et al, cis-eQTLs from the eQTLGen and PsychENCODE consortia. Results were validated using proteomic and transcriptomic data. Single-gene functional analyses probed potential mechanisms, culminating in the construction of a drug-gene regulation network.

RESULTS

Through the MR analysis, we identified four potential drug targets in the blood, including prolylcarboxypeptidase (PRCP), proteasome 20S subunit alpha 4 (PSMA4), LTBP4 and GPR160 for SAH. Furthermore, two potential drug targets (PSMA4 and SLC22A4) were identified for IA and one potential drug target (KL) for UIA after accounting for multiple testing (P(inverse-variance weighted)<8.28e-6). Strong evidence of colocalisation and SMR analysis confirmed the relevance of PSMA4 and PRCP in outcomes. Elevated PRCP circulating proteins correlated with a lower SAH risk. PRCP gene expression was significantly downregulated in the disease cohort.

CONCLUSIONS

This study supports that elevated PRCP gene expression in blood is causally associated with the decreased risk of IA rupture. Conversely, increased PSMA4 expression in the blood is causally related to an increased risk of IA rupture and formation.

Identification of circulating metabolites associated with chronic rhinosinusitis using Mendelian randomization analysis

OBJECTIVE

This study aims to employ Mendelian Randomization (MR) analysis to investigate causal relationships between serum metabolites and CRS, identifying key pathogenic and protective factors and analyzing their mechanisms of action.

METHODS

Utilizing data from the Genome-Wide Association Studies (GWAS) database, employing two-sample MR analysis to investigate the potential causal relationship between 233 circulating metabolites with the occurrence of CRS. Inverse Variance Weighted (IVW) model, MR-Egger method, Weighted Median, and Weighted model were employed. Sensitivity analyses were conducted with Bonferroni correction. This research aims to elucidate the impact of metabolites on the development and progression of CRS, providing valuable insights into the underlying mechanisms.

RESULTS

Following MR analysis, two metabolites were significantly associated with CRS: Tyrosine (OR = 1.223; 95% CI 1.115-1.341; p = 1.96E-05) and Creatinine (OR = 1.208; 95% CI 1.103-1.322; p = 4.11E-05). These two key risk factors may be further studied for their pathogenesis and could be targeted for modulation in the treatment of CRS. However, there are several protective factors also worth exploring, among which the correlation is more significant: Ratio of conjugated linoleic acid to total fatty acids (OR = 0.809; 95% CI 0.708‒0.923; p = 1.73E-03), Albumin (OR = 0.787; 95% CI 0.670‒0.926; p = 3.76E-03),Conjugated linoleic acid (OR = 0.664; 95% CI 0.491‒0.898; p = 7.85E-03), Diacylglycerol (OR = 0.804; 95% CI 0.654‒0.989; p = 3.87E-02), Apolipoprotein A-I (OR = 0.915; 95% CI 0.845‒0.991; p = 2.89E-02).

CONCLUSION

In our MR study, we discovered 28 circulating metabolites linked to CRS. Importantly, tyrosine and creatinine were identified as the most significant contributors to the pathogenesis of CRS, highlighting their potential as therapeutic targets. Additionally, several protective factors may offer new avenues for preventive strategies and therapeutic interventions. These findings underscore the clinical relevance of targeting these metabolites to modulate CRS progression and improve patient outcomes.

LEVEL OF EVIDENCE

Level 2*.1.

Genomic and GEO data integration identifies PDGFB as a potential therapeutic target for sepsis

Sepsis is a major contributor to global health loss, yet effective therapeutic options remain scarce. This study aims to identify potential therapeutic targets for sepsis. We integrated data from the druggable genome, expression quantitative trait loci (eQTLs) from human blood, and genome-wide association studies on sepsis. Mendelian randomization (MR) was employed to investigate causal relationships between drug target genes and sepsis. The eQTLGen Consortium data served as the discovery set and was validated using genotype-tissue expression (GTEx) eQTLs. Sensitivity and colocalization analyses were conducted to support causal inferences. Additionally, phenome-wide MR (Phe-MR) was used to assess potential side effects of druggable genes. The expression levels of the target genes were validated using the GSE154918 dataset. In the discovery MR analysis phase, we identified 26 potential targets with significant expression in blood (PFDR < 0.05). PDGFB and BPI were further validated in the replication MR analysis. Colocalization analysis provided strong evidence (PPH4 > 0.75) supporting PDGFB as a therapeutic candidate for sepsis. Phe-MR analysis suggested that targeting PDGFB is unlikely to cause adverse effects. PDGFB downregulation was confirmed in sepsis groups via the GEO dataset. PDGFB is identified as a promising druggable target for sepsis treatment, supported by strong evidence of its therapeutic potential.

Genetically druggable targets for MAPK-activated colorectal cancer by a two-sample mendelian randomization analysis

Colorectal cancer (CRC) is a significant worldwide health issue, ranking second in women and third in men. Predictions estimate a rise to 2.5 million cases by 2035, with CRC being the fourth deadliest cancer due to delayed diagnosis and the scarcity of effective treatment options. Over 60% of CRC cases involve MAPK-activated signal pathways, particularly driven by RAS oncogene mutations, which hinder treatment responses, making them 'undruggable.' This study conducts a two-sample Mendelian randomization protein quantitative trait loci (pQTL) analysis to investigate the causal association between plasma proteins and MAPK-activated CRCs. The study indicates that four plasma proteins-MHC class I polypeptide-related sequence B (MICB), complement C4A, C4B, and interleukin-21 (IL-21) are associated with an increased risk of MAPK-activated CRCs. These findings highlight the possibility of utilizing plasma proteins as therapeutic targets and diagnostic markers to advance the fight against CRCs, indicating promising results for more effective interventions. To ascertain and expand upon these discoveries, further research is imperative to fully harness the potential of these discoveries.

Identification and validation of five novel protein targets for type 2 diabetes mellitus

Despite advances in type 2 diabetes mellitus (T2DM) therapy, challenges remain due to the lack of novel therapeutic targets. We used Mendelian randomization to integrate cis-expression quantitative trait loci data for circulating proteins from the eQTLGen Consortium (31,684 individuals) with T2DM summary statistics from the Integrative Epidemiology Unit Open Genome-Wide Association Studies Project (61,714 cases, 593,952 controls). 42 genes were significantly associated with T2DM. Colocalization analysis revealed that six genes (CLSTN1, KCNJ11, MLX, DLD, RELA, and ULK1) shared common causal variants with T2DM. Among them, CLSTN1 (OR = 0.80, 95% CI: 0.70-0.90), KCNJ11 (OR = 0.66, 95% CI: 0.60-0.73), and MLX (OR = 0.73, 95% CI: 0.65-0.82) were negatively associated with T2DM, while DLD (OR = 1.38, 95% CI: 1.15-1.65), RELA (OR = 1.90, 95% CI: 1.41-2.55), and ULK1 (OR = 1.42, 95% CI: 1.17-1.71) were positively associated with T2DM. A matched case-control study further validated these associations, except for DLD, showing significant downregulation of CLSTN1, KCNJ11, and MLX (P < 0.05) alongside upregulation of RELA and ULK1 (P < 0.05) in T2DM patients. These findings underscore the potential of these proteins as drug targets, warranting further clinical investigation to confirm their therapeutic relevance.

Identification of therapeutic targets for chronic kidney disease through Mendelian randomization analysis of druggable genes

Chronic Kidney Disease (CKD) is a multifaceted and gradually advancing condition characterized by a complex pathogenesis. The current therapeutic options for CKD remain limited in efficacy. Consequently, the identification and exploration of novel drug targets for CKD are of paramount importance. We identified cis-expression quantitative trait loci (cis-eQTLs) with potential as drug targets from the eQTLGen Consortium database to serve as the exposure. For the outcome, we utilized a genome-wide association study (GWAS) of chronic kidney disease (CKD) from the FinnGen database, which comprised a case group of 11,265 individuals and a control group of 436,208 individuals. MR analysis was employed to investigate druggable genes closely associated with CKD. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to elucidate the functional roles of these significant genes. Finally, a colocalization analysis was conducted to determine the likelihood that a cis-eQTL for a druggable gene and CKD share a causal variant. The expression of 12 genes was found to be significantly associated with CKD risk, with a false discovery rate (FDR) of less than 0.05. GO and KEGG enrichment analyses indicated that these genes are primarily involved in the regulation of MAP kinase activity, regulation of protein serine/threonine kinase activity, Gap junction, Platelet activation and Oxytocin signaling pathway. The colocalization analysis results suggested that CKD and the TUBB gene may share a causal variant, with a posterior probability (PP.H4) exceeding 80% (TUBB: 97.27%). Compelling statistical evidence indicates that TUBB represents the most promising pharmacological target for the treatment of CKD. This study not only identifies potential therapeutic targets but also offers valuable insights for future drug development in the context of CKD.

Systematic druggable genome-wide Mendelian randomization to identify therapeutic targets and dominant flora for ulcerative colitis

The relationship and mechanism among gut microbiota (GM), metabolites and active ulcerative colitis (UC) are unclear. This study aims to infer the causal relationship between druggable-genes and active UC using Mendelian randomization (MR) and bioinformatics methods. The "microbiota-target" and "microbiota- metabolite" network was constructed to screen the microorganisms and metabolites associated with active UC, and the mechanism of GM, metabolites and active-UC was analyzed. These findings were verified through molecular docking, molecular dynamics (MD) simulations and co-localization analysis. Subsequently, the effects of key GM and targets on mice with UC induced by dextran sulfate sodium (DSS) was investigated. Our findings indicated that four drug targets (IFN-γ, IL24, CXCR6, PRKCZ) are closely associated with the risk of active UC, with IL24 specifically found to be colocalized with UC. These four targets were significantly correlated with differences of immune cell infiltration in active-UC. Faecalibacterium prausnitzii (F. prausnitzii) was predicted to inhibit IFN-γ and promote the remission of active UC. Additionally, seven GM were identified to be associated with the risk of active UC. Molecular docking and MD further confirmed the stable interactions between IFN-γ and metabolites of F. prausnitzii. We also verified the alleviating effect of F. prausnitzii on DSS-induced UC mice. The result indicated that F. prausnitzii can reduce inflammatory cell infiltration and goblet cell death in the colon, lower myeloperoxidase activity, and downregulate IFN-γ expression levels. This study revealed that GM can modify the immune microenvironment of active UC, providing new ideas for the prevention and treatment of UC.

WNT inhibitor SP5-mediated SERPING1 suppresses lung adenocarcinoma progression via TSC2/mTOR pathway

The long-term outlook for patients grappling with lung cancer (LC) remains bleak, with lung adenocarcinoma (LUAD) emerging as the most predominant histological subtype. Our Mendelian randomization (MR) investigation spotlighted that heightened levels of the circulating protein serpin peptidase inhibitor family G1 (SERPING1) substantially mitigated LC risk. The fusion of multi-omics strategies unveiled that SERPING1 exhibited diminished expression in LUAD patients compared to healthy individuals both in tissues and serum, with LUAD individuals showcasing elevated SERPING1 expression demonstrating improved prognoses. Furthermore, SERPING1 expression exhibited a robust correlation with the efficacy of immunotherapy. Through meticulous in vivo and in vitro analyses, we unraveled that SERPING1 impeded the proliferation, migration, invasion and wound healing of LUAD cells via the tuberous sclerosis 2 (TSC2)/mammalian target of rapamycin (mTOR) pathway. Mechanistically, WNT inhibitor- Specificity Protein (SP5) was delineated as facilitator of SERPING1 transcription by binding to the SERPING1 gene promoter. Intriguingly, aside from the association between SERPING1 and systolic blood pressure, glycosylated hemoglobin (HbA1c), type I diabetes, no discernible link between SERPING1 overexpression and heightened risks of other cardiometabolic conditions and diseases was evident. In summary, SERPING1 emerges as a novel tumor suppressor gene and SP5/SERPING1/TSC2 is a promising therapeutic target in the context of LUAD.

Mendelian Randomization and Colocalization Analysis Reveal New Drug Targets for Oral Ulcer: A Mendelian Randomization Analysis

Background and Aims

Oral ulcer (OU) is a complex issue with limited effective treatments. This study uses multi-omics data through summary Mendelian randomization (SMR) and colocalization analysis to identify specific gene associations with OU, aiming to find new therapeutic targets, repurpose existing drugs, and develop new treatment options.

Methods

Our study consists of two phases: first, extracting data from Genome-Wide Association Studies and using blood mQTL, eQTL, and pQTL data as exposure factors, then integrating these with OU gene data through SMR analysis. Then, we validate the results with UK Biobank data and perform colocalization analysis to confirm shared genetic variants.

Results

Genetically predicted levels of four circulating proteins are associated with OU. Under strong supportive evidence from mQTL, eQTL, and pQTL, genetically predicted levels of NFKB1 are negatively correlated with the risk of OU. With moderate supportive evidence from mQTL and pQTL, genetically predicted levels of FAIM3 are negatively correlated with the risk of OU. Meanwhile, under low supportive evidence from eQTL and pQTL, higher genetically predicted levels of JUND and lower levels of IL12β are associated with a higher risk of OU.

Conclusion

SMR approach employed in this study has pinpointed several proteins with tangible associations to the risk of OU. NFKB1, FAIM3, JUND, and IL12β stand out as promising therapeutic targets for OU, beckoning further exploration and research.

Potential drug targets for asthma identified through mendelian randomization analysis

BACKGROUND

The emergence of new molecular targeted drugs marks a breakthrough in asthma treatment, particularly for severe cases. Yet, options for moderate-to-severe asthma treatment remain limited, highlighting the urgent need for novel therapeutic drug targets. In this study, we aimed to identify new treatment targets for asthma using the Mendelian randomization method and large-scale genome-wide association data (GWAS).

METHODS

We utilized GWAS data from the UK Biobank (comprising 56,167 patients and 352,255 control subjects) and the FinnGen cohort (including 23,834 patients and 228,085 control subjects). Genetic instruments for 734 plasma proteins and 154 cerebrospinal fluid proteins were derived from recently published GWAS. Bidirectional Mendelian randomization analysis, Steiger filtering, colocalization, and phenotype scanning were employed for reverse causal inference detection, further substantiating the Mendelian randomization results. A protein-protein interaction network was also constructed to reveal potential associations between proteins and asthma medications.

RESULTS

Under Bonferroni significance conditions, Mendelian randomization analysis revealed causal relationships between seven proteins and asthma. In plasma, we observed that an increase of one standard deviation in IL1R1[1.30 (95% CI 1.20-1.42)], IL7R[1.07 (95% CI 1.04-1.11)], ECM1[1.03 (95% CI 1.02-1.05)], and CD200R1[1.18 (95% CI 1.09-1.27)] were associated with an increased risk of asthma, while an increase in ADAM19 [0.87 (95% CI 0.82-0.92)] was found to be protective. In the brain, each 10-fold increase in IL-6 sRa [1.29 (95% CI 1.15-1.45)] was associated with an increased risk of asthma, while an increase in Layilin [0.61 (95% CI 0.51-0.73)] was found to be protective. None of the seven proteins exhibited a reverse causal relationship. Colocalization analysis indicated that ECM1 (coloc.abf-PPH4 = 0.953), IL-6 sRa (coloc.abf-PPH4 = 0.966), and layilin (coloc.abf-PPH4 = 0.975) shared the same genetic variation as in asthma.

CONCLUSION

A causal relationship exists between genetically determined protein levels of IL1R1, IL7R, ECM1, CD200R1, ADAM19, IL-6 sRa, and Layilin (LAYN) and asthma. Moreover, the identified proteins may serve as attractive drug targets for asthma, especially ECM1 and Layilin (LAYN). However, further research is required to comprehensively understand the roles of these proteins in the occurrence and progression of asthma.

Dissecting the pathogenic effects of smoking in blood DNA methylation on allergic diseases

Background

Allergic diseases, such as asthma and allergic rhinitis, present significant health challenges globally. Elucidating the genetic and epigenetic foundations is crucial for developing effective interventions.

Methods

We performed two-sample Mendelian Randomization (MR) analyses to investigate the associations between smoking behaviors and various allergic diseases, leveraging data from the FinnGen database. Additionally, we examined the relationships of DNA methylation (CpG sites) with allergic diseases, employing mQTLs as epigenetic proxies. Furthermore, we conducted reverse MR analyses on CpG sites that exhibited cross-allergic disease effects.

Results

In our genomic MR analysis, smoking behaviors such as smoking initiation and the number of cigarettes smoked per day were identified to be causally associated with an increased risk of asthma. Additionally, there was suggestive evidence linking smoking initiation to atopic contact dermatitis. Our epigenetic MR analysis found that methylation changes at 46 CpG sites, assessed via mQTLs, were significantly associated with asthma risk. Notably, cg17272563 (PRRT1), cg03689048 (BAT3), cg20069688 (STK19), and cg20513976 (LIME1) were identified with cross-allergic effects. Crucially, reverse MR analysis substantiated these associations.

Conclusions

Our study has highlighted the associations between smoking behaviors and allergic diseases in the genetic and epigenetic landscape, notably asthma. We identified several DNA methylation-related CpG sites, such as cg03689048 (BAT3), cg17272563 (PRRT1), and cg20069688 (STK19), which demonstrate cross-allergic potential and reverse causal relationships.

Examining the potential causal relationships among smoking behaviors, blood DNA methylation profiles, and the development of coronary heart disease and myocardial infarction

BACKGROUND

Smoking has been identified as a standalone risk factor for coronary heart disease (CHD) and myocardial infarction (MI), but the precise underlying mechanisms remain incompletely elucidated.

RESULTS

In this study, we conducted a two-sample Mendelian randomization analysis to examine the impact of smoking behaviors (including smoking initiation, age of smoking initiation, cigarettes per day, and smoking cessation) and smoking-related DNA methylation at CpG sites on CHD and MI based on the UK Biobank dataset. Additionally, we included the FinnGen and Biobank Japan datasets as replications and performed a meta-analysis to combine the results from different data sources. We further validated our results using genetic colocalization analysis. In genomic analysis, we provided compelling evidence on the association between genetically predicted smoking initiation and increased susceptibility to CHD and MI. In epigenetic analysis, we identified 11 smoking-related CpG sites linked to CHD risk and 10 smoking-related CpG sites associated with the risk of MI based on the UK Biobank dataset. Subsequently, some of these CpG sites were further replicated using the FinnGen or BBJ datasets. Ultimately, a meta-analysis was conducted to integrate findings from various data sources (3 for CHD, and 2 for MI), revealing that 7 of 11 CpG sites were linked to CHD risk; whereas, 7 of 10 CpG sites were associated with MI risk. Furthermore, we performed genetic colocalization analysis and found that cg19744173 (FBLN7), cg00395063 (ARHGEF12), and cg16822035 (MCF2L) exhibited robust evidence of colocalization with coronary heart disease; whereas, cg19529732 (DIABLO), cg26405020 (FES), and cg08940075 (CNN3) demonstrated strong colocalization evidence with the risk of myocardial infarction.

CONCLUSIONS

Our research offers a novel insight into the impact of smoking on the susceptibility to CHD and MI through the lens of epigenetic DNA methylation.

Unveiling therapeutic targets for spinal stenosis from genetic insights: a Mendelian randomization analysis

Spinal stenosis is a commonly chronic spinal degenerative disease, which is a major cause of pain and dysfunction in the elderly. Mendelian randomization (MR) has been widely applied to repurpose licensed drugs and identify novel therapeutic targets. Consequently, we intended to identify new therapeutic targets for spinal stenosis and to analyze their possible mechanisms and potential side effects.We conducted the Mendelian randomization analysis to identify potential drug targets for the management of spinal stenosis. Cis-expressed quantitative trait loci (cis-eQTL) data as genetic instrumental variables were acquired from the eQTLGen consortium. The summary statistics for single nucleotide polymorphism (SNP) associations of spinal stenosis were obtained from the FinnGen study(20,807 cases and 294,770 controls). Co-localization analysis was performed to determine whether there was shared causal variation between the SNPs associated with spinal stenosis as well as the eQTL. Multiple external validations were performed to reinforce the reliability and stability of the findings utilizing the cis-eQTL from the GTEx portal, the Ferkingstad et al. pQTL dataset, and the Sun et al. pQTL dataset. The viability of the identified drug targets for future clinical applications was elucidated through the phenome-wide association study and drug candidate prediction. Three drug targets (BMP6, DLK1, and GFPT1) exhibited significant causal associations with spinal stenosis in the eQTLGen cohort by MR analysis, which was strongly supported by the results of the co-localization analysis. The causal association of DLK1 and GFPT1 with spinal stenosis remained remarkable with multiple external validations. Multivariate MR and phenome-wide association study analysis indicated that both targets were not associated with other traits. In addition, phenome-wide association study analysis and drug prediction analysis demonstrated the potential of these two targets for future clinical applications. In this study, DLK1 and GFPT1 were identified as promising novel therapeutic targets for spinal stenosis, providing initial genetic insights for drug development in spinal stenosis.

Genetically Supported Drug Targets and Dental Traits: A Mendelian Randomization Study

Current interventions for oral/dental diseases heavily rely on operative/surgical procedures, while the discovery of novel drug targets may enable access to noninvasive pharmacotherapy. Therefore, this study aims to leverage large-scale data and Mendelian randomization (MR) techniques, utilizing genetic variants as instruments, to identify potential therapeutic targets for oral and dental diseases supported by genetic evidence. By intersecting 4,302 druggable genes with expression quantitative trait loci from 31,684 blood samples, we identified 2,580 druggable targets as exposures. Single nucleotide polymorphisms associated with dental disease/symptom traits were collected from FinnGen R9, the Gene-Lifestyle Interactions in Dental Endpoints consortium, and the UK Biobank to serve as outcomes for both discovery and replication purposes. Through MR analysis, we identified 43 druggable targets for various dental disease/symptom traits. To evaluate the viability of these targets, we replicated the analysis using circulating protein quantitative trait loci as exposures. Additionally, we conducted sensitivity, colocalization, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes annotation, protein-protein interaction analyses, and validated dental trait-associated druggable gene expression in animal models. Among these targets, IL12RB1 (odds ratio [OR], 1.01; 95% confidence interval [CI], 1.01-1.01) and TNF (OR, 0.98; 95% CI, 0.97-0.99) exhibited therapeutic promise for oral ulcers, whereas CXCL10 (OR, 0.84; 95% CI, 0.76-0.91) was for periodontitis. Through a rigorous quality control and validation pipeline, our study yields compelling evidence for these druggable targets, which may enhance the clinical prognosis by developing novel drugs or repurposing existing ones.

Novel targets for the treatment and prevention of Alzheimer's disease in the European population, inspiration from amyloid beta and tau protein

Alzheimer's disease (AD) is a gradual neurodegenerative ailment that lacks any disease-modifying intervention. Our objective was to pinpoint pharmacological targets with a focus on amyloid beta (Aβ) and tau to treat and prevent AD in the European population. A proteome-wide Mendelian randomization (MR) analysis was carried out to estimate the associations between proteins and cerebrospinal fluid (CSF) Aβ-42 and phosphorylated Tau (p-Tau). We utilized colocalization and MR analysis to investigate whether the identified proteins were associated with the risk of AD. Additionally, we expanded our investigation to include non-AD phenotypes by conducting a phenome-wide MR analysis of 1646 disease traits based on the FinnGen and UK Biobank databases to explore potential side effects. We identified 11 proteins that were genetically associated with both CSF Aβ-42 and p-Tau levels. The genetically predicted levels of three proteins, GAL3ST2, POLR1C, and BIN1, were found to be associated with an increased risk of AD with high colocalization. In the phenome-wide MR analysis, two out of the three biomarkers were associated with at least one disease, except for GAL3ST2, which was not associated with any disease under the threshold of FDR <0.1. POLR1C was found to be associated with the most disease traits, and all disease associations with genetically inhibited BIN1 were protective. The proteome-wide MR investigation revealed 11 proteins that were associated with the level of CSF Aβ-42 and p-Tau. Among them, GAL3ST2, POLR1C, and BIN1 were identified as potential therapeutic targets for AD and warrant further investigation.

Therapeutic targets for lung cancer: genome-wide Mendelian randomization and colocalization analyses

Background

Lung cancer, categorized into non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), remains a significant global health challenge. The development of drug resistance and the heterogeneity of the disease necessitate the identification of novel therapeutic targets to improve patient outcomes.

Methods

We conducted a genome-wide Mendelian randomization (MR) and colocalization analysis using a comprehensive dataset of 4,302 druggable genes and cis-expressed quantitative trait loci (cis-eQTLs) from 31,884 blood samples. The study integrated genomic analysis with eQTL data to identify key genes associated with lung cancer risk.

Results

The analysis revealed five actionable therapeutic targets for NSCLC, including LTB4R, LTBP4, MPI, PSMA4, and TCN2. Notably, PSMA4 demonstrated a strong association with both NSCLC and SCLC risks, with odds ratios of 3.168 and 3.183, respectively. Colocalization analysis indicated a shared genetic etiology between these gene expressions and lung cancer risk.

Conclusion

Our findings contribute to precision medicine by identifying druggable targets that may be exploited for subtype-specific lung cancer therapies.

Causal relationships between allergic and autoimmune diseases with chronic rhinosinusitis

Chronic rhinosinusitis (CRS) is a prevalent inflammatory airway disease affecting over 10% of the global population, leading to considerable socio-economic impacts, especially in developing countries. The pathogenesis of CRS is multifactorial, involving potential contributions from both genetic and environmental factors. While the influence of allergic and autoimmune diseases on CRS has been observed, the causal relationships between these diseases and CRS remain unclear. We extracted data from large-scale genome-wide association studies (GWAS) and utilized a bidirectional two-sample Mendelian randomization (MR) analysis to explore the causal relationships between CRS and ten autoimmune and allergic diseases, including asthma, allergic rhinitis (AR), atopic dermatitis (AD), psoriasis, type 1 diabetes (T1D), hypothyroidism, celiac disease (CeD), multiple sclerosis (MS), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE). Additionally, we conducted colocalization analysis to determine whether the allergic/autoimmune diseases showing statistical causal relationships with CRS are driven by the same genetic variants. The MR analysis identified that AR (OR = 1.30; 95% CI = 1.21-1.40; P = 3.26E-13), asthma (OR = 1.35; 95% CI = 1.25-1.45; P = 1.35E-14), and AD (OR = 1.17; 95% CI = 1.06-1.30; P = 0.003) were significantly associated with an increased risk of developing CRS. Interestingly, psoriasis (OR = 0.05; 95% CI = 0.01-0.37; P = 0.004) appeared to have a protective effect against CRS. Associations for T1D and hypothyroidism were also suggestive as potential risk factors for CRS. No significant associations in the reverse MR analysis, suggesting a one-directional relationship. Colocalization analysis indicated that asthma (PP.H4 = 0.99) shared the same genetic variant (IL-33 rs3939286) with CRS. In conclusion, our study confirmed the causal relationships between allergic and autoimmune diseases (AR, asthma, AD, and psoriasis) and CRS. Notably, we identified a shared genetic variant, rs3939286 in the IL-33 gene, between asthma and CRS, suggesting that targeting the IL-33 pathway may provide a therapeutic strategy for both diseases.

Identifying HIF1A and HGF as two hub genes in aortic dissection and function analysis by integrating RNA sequencing and single-cell RNA sequencing data

Objective

Aortic dissection (AD) is a severe aortic disease with high mortality, and its pathogenesis remains elusive. To explore the regulatory mechanisms of AD, we integrated public RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) datasets to screen the hub genes of AD and further analyzed their functions, which may provide references to the diagnosis and treatment of AD.

Methods

Four AD-related datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis and differential expression analysis were applied to identify overlapping genes in dataset GSE153434. Protein-protein interaction (PPI) network was constructed based on overlapping genes. Five methods (closeness, degree, EPC, MCC, and MNN) were used to pick hub genes. The receiver operating characteristic curve was used to evaluate the diagnostic efficiency of the hub genes in extra datasets GSE98770 and GSE52093. scRNA-seq dataset GSE213740 was used to explore the expression and function of the hub genes at the single-cell level. Quantitative real-time polymerase chain reaction was used to verify the expression of hub genes in beta-aminopropionitrile (BAPN)-induced mouse thoracic aortic aneurysm and dissection (TAAD) model.

Results

A total of 71 overlapping genes were screened by intersecting the significant genes in the pink module and the differentially expressed genes. A PPI network with 45 nodes and 74 edges was generated, and five top hub genes (HIF1A, HGF, HMOX1, ITGA5, and ITGB3) were identified. All the hub genes had area under the curve values above 0.55. scRNA-seq data analysis showed that HIF1A was significantly upregulated in macrophages and HGF was significantly upregulated in vascular smooth muscle cells (SMCs) of the ascending aortas in AD patients. HIF1A may transcriptionally regulate multiple downstream target genes involving inflammation (TLR2, ALOX5AP, and MIF), glycolysis (ENO1, LDHA, and GAPDH), tissue remodeling (PLAU), and angiogenesis (SERPIN and VEGFA). HGF may participate in the signaling among SMCs, fibroblasts, and endothelial cells through binding to different receptors (MET, EGFR, IGF1R, and KDR). The mRNA expression of Hif1a, Hgf, and their target genes, including Alox5ap, Serpine1, Tlr2, Plau, Egfr, and Igf1r, was significantly upregulated in aortic tissues of BAPN-treated mice.

Conclusion

By integrating RNA-seq and scRNA-seq data, we identified HIF1A and HGF as two hub genes with good diagnostic efficiency for AD. HIF1A in macrophages may promote AD formation by promoting inflammation, glycolysis, tissue remodeling, and angiogenesis, and HGF may mediate signaling among SMCs, fibroblasts, and endothelial cells in the development of AD.

Validation of TYK2 and exploration of PRSS36 as drug targets for psoriasis using Mendelian randomization

Psoriasis is a chronic inflammatory skin disorder with multiple causes, including genetic and environmental factors. Despite advances in treatment, there remains a need to identify novel therapeutic targets. A Mendelian randomization (MR) analysis was conducted to identify therapeutic targets for psoriasis. Data on cis-expression quantitative trait loci were obtained from the eQTLGen Consortium (n = 31,684). Summary statistics for psoriasis (outcome) were sourced from the GWAS Catalog with a sample size of 484,598, including 5,427 cases and 479,171 controls. Colocalization analysis was used to assess whether psoriasis risk and gene expression were driven by shared single nucleotide polymorphisms. Drug prediction and molecular docking were utilized to validate the pharmacological value of the drug targets. The MR analysis found that 81 drug targets were significantly associated, and two (TYK2 and PRSS36) were supported by colocalization analysis (PP.H4 > 0.80). Phenome-wide association studies did not show any associations with other traits at the gene level. Biologically, these genes were closely related to immune function. Molecular docking revealed strong binding with drugs and proteins, as supported by available structural data. This study validated TYK2 as a drug target for psoriasis, in line with its existing clinical use, including the development of decucravacitinib. PRSS36 is a potential novel target requiring further investigation.

Potential drug targets for osteoporosis identified: A Mendelian randomization study

Background

Osteoporosis is a prevalent global health condition, primarily affecting the aging population, and several therapies for osteoporosis have been widely used. However, available drugs for osteoporosis are far from satisfactory because they cannot alleviate disease progression. This study aimed to explore potential drug targets for osteoporosis through Mendelian randomization analysis.

Methods

Using cis-expression quantitative trait loci (cis-eQTL) data of druggable genes and two genome-wide association studies (GWAS) datasets related to osteoporosis (UK Biobank and FinnGen cohorts), we employed mendelian randomization (MR) analysis to identify the druggable genes with causal relationships with osteoporosis. Subsequently, a series of follow-up analyses were conducted, such as colocalization analysis, cell-type specificity analysis, and correlation analysis with risk factors. The association between potential drug targets and osteoporosis was validated by qRT-PCR.

Results

Six druggable genes with causal relationships with osteoporosis were identified and successfully replicated, including ACPP, DNASE1L3, IL32, PPOX, ST6GAL1, and TGM3. Cell-type specificity analysis revealed that PPOX and ST6GAL1 were expressed in all cell types in the bone samples, while IL32, ACPP, DNASE1L3, and TGM3 were expressed in specific cell types. The GWAS data showed there were seven risk factors for osteoporosis, including vitamin D deficiency, COPD, physical activity, BMI, MMP-9, ALP and PTH. Furthermore, ACPP was associated with vitamin D deficiency and COPD; DNASE1L3 was linked to physical activity; IL32 correlated with BMI and MMP-9; and ST6GAL1 was related to ALP, physical activity, and MMP-9. Among these risk factors, only MMP-9 had a high genetic correlation with osteoporosis. The results of qRT-PCR demonstrated that IL32 was upregulated while ST6GAL1 was downregulated in peripheral blood of osteoporosis patients.

Conclusion

Our findings suggested that those six druggable genes offer potential drug targets for osteoporosis and require further clinical investigation, especially IL32 and ST6GAL1.

Systematic Druggable Genome-Wide Mendelian Randomization Identifies Therapeutic Targets for Functional Outcome After Ischemic Stroke

BACKGROUND

Stroke is a leading cause of death worldwide, with a lack of effective treatments for improving the prognosis. The aim of the present study was to identify novel therapeutic targets for functional outcome after ischemic stroke .

METHODS AND RESULTS

Cis-expression quantitative trait loci data for druggable genes were used as instrumental variables. The primary outcome was the modified Rankin Scale score at 3 months after ischemic stroke, evaluated as a dichotomous variable (3-6 versus 0-2) and also as an ordinal variable. Drug target Mendelian randomization, Steiger filtering analysis, and colocalization analysis were performed. Additionally, phenome-wide Mendelian randomization analysis was performed to identify the safety of the drug target genes at the genetic level. Among >2600 druggable genes, genetically predicted expression of 16 genes (ABCC2, ATRAID, BLK, CD93, CHST13, NR1H3, NRBP1, PI3, RIPK4, SEMG1, SLC22A4, SLC22A5, SLCO3A1, TEK, TLR4, and WNT10B) demonstrated the causal associations with ordinal modified Rankin Scale (P<1.892×10-5) or poor functional outcome (modified Rankin Scale 3-6 versus 0-2, P<1.893×10-5). Steiger filtering analysis suggested potential directional stability (P<0.05). Colocalization analysis provided further support for the associations between genetically predicted expression of ABCC2, NRBP1, PI3, and SEMG1 with functional outcome after ischemic stroke. Furthermore, phenome-wide Mendelian randomization revealed additional beneficial indications and few potential safety concerns of therapeutics targeting ABCC2, NRBP1, PI3, and SEMG1, but the robustness of these results was limited by low power.

CONCLUSIONS

The present study revealed 4 candidate therapeutic targets for improving functional outcome after ischemic stroke, while the underlying mechanisms need further investigation.

Integrating Mendelian randomization and single-cell RNA sequencing to identify therapeutic targets of baicalin for type 2 diabetes mellitus

Background

Alternative and complementary therapies play an imperative role in the clinical management of Type 2 diabetes mellitus (T2DM), and exploring and utilizing natural products from a genetic perspective may yield novel insights into the mechanisms and interventions of the disorder.

Methods

To identify the therapeutic target of baicalin for T2DM, we conducted a Mendelian randomization study. Druggable targets of baicalin were obtained by integrating multiple databases, and target-associated cis-expression quantitative trait loci (cis-eQTL) originated from the eQTLGen consortium. Summary statistics for T2DM were derived from two independent genome-wide association studies available through the DIAGRAM Consortium (74,124 cases vs. 824,006 controls) and the FinnGen R9 repository (9,978 cases vs. 12,348 controls). Network construction and enrichment analysis were applied to the therapeutic targets of baicalin. Colocalization analysis was utilized to assess the potential for the therapeutic targets and T2DM to share causative genetic variations. Molecular docking was performed to validate the potency of baicalin. Single-cell RNA sequencing was employed to seek evidence of therapeutic targets' involvement in islet function.

Results

Eight baicalin-related targets proved to be significant in the discovery and validation cohorts. Genetic evidence indicated the expression of ANPEP, BECN1, HNF1A, and ST6GAL1 increased the risk of T2DM, and the expression of PGF, RXRA, SREBF1, and USP7 decreased the risk of T2DM. In particular, SREBF1 has significant interaction properties with other therapeutic targets and is supported by strong colocalization. Baicalin had favorable combination activity with eight therapeutic targets. The expression patterns of the therapeutic targets were characterized in cellular clusters of pancreatic tissues that exhibited a pseudo-temporal dependence on islet cell formation and development.

Conclusion

This study identified eight potential targets of baicalin for treating T2DM from a genetic perspective, contributing an innovative analytical framework for the development of natural products. We have offered fresh insights into the connections between therapeutic targets and islet cells. Further, fundamental experiments and clinical research are warranted to delve deeper into the molecular mechanisms of T2DM.

ENPP2/Autotaxin: The potential drug target for alcoholic liver disease identified through Mendelian randomization analysis

BACKGROUND AND AIMS

At present, there is still a lack of radical drug targets for intervention in alcoholic liver disease (ALD), and drug discovery through randomized controlled trials is a lengthy, risky, and expensive undertaking, so we aimed to identify effective drug targets based on human genetics.

METHODS

We used Mendelian randomization (MR) and Bayesian colocalization analysis to investigate 2639 genes encoding druggable proteins and examined the causal effects on ALD (PMID 34737426: 456348 European with 451 cases and 455 897 controls). In addition, we conducted the mediation analysis to explore the potential mechanism using the genome-wide association study (GWAS) data of blood biomarkers as mediators.

RESULTS

We finally identified the drug target: ENPP2/Autotaxin and genetically proxied ENPP2/Autotaxin was causally associated with the risk of ALD (OR = 2.28, 95% CI: 1.64 to 3.16, p = 7.49E-7). In addition, we found that the effect of ENPP2/Autotaxin on ALD may be partly mediated by effector memory CD8+ T cell (the proportion of mediation effect: 8.49%).

CONCLUSIONS

Our integrative analysis suggested that genetically determined levels of circulating ENPP2/Autotaxin have a causal effect on ALD risk and are a promising drug target.

The Application of Mendelian Randomization in Cardiovascular Disease Risk Prediction: Current Status and Future Prospects

Cardiovascular disease (CVD), a leading cause of death and disability worldwide, and is associated with a wide range of risk factors, and genetically associated conditions. While many CVDs are preventable and early detection alongside treatment can significantly mitigate complication risks, current prediction models for CVDs need enhancements for better accuracy. Mendelian randomization (MR) offers a novel approach for estimating the causal relationship between exposure and outcome by using genetic variation in quasi-experimental data. This method minimizes the impact of confounding variables by leveraging the random allocation of genes during gamete formation, thereby facilitating the integration of new predictors into risk prediction models to refine the accuracy of prediction. In this review, we delve into the theory behind MR, as well as the strengths, applications, and limitations behind this emerging technology. A particular focus will be placed on MR application to CVD, and integration into CVD prediction frameworks. We conclude by discussing the inclusion of various populations and by offering insights into potential areas for future research and refinement.

Unraveling genetic threads: Identifying novel therapeutic targets for allergic rhinitis through Mendelian randomization

Background

Allergic rhinitis (AR) is a pervasive global health issue, and currently, there is a scarcity of targeted drug therapies available. This study aims to identify potential druggable target genes for AR using Mendelian randomization (MR) analysis.

Methods

MR analysis was conducted to assess the causal effect of expression quantitative trait loci (eQTL) in the blood on AR. Data on AR were collected from 2 datasets: FinnGen(R9) (11,009 cases and 359,149 controls) and UK Biobank (25,486 cases and 87,097 controls). Colocalization analysis was utilized to assess the common causal genetic variations between the identified drug target genes and AR. We also employed available genome-wide association studies (GWAS) data to gauge the impact of druggable genes on AR biomarkers and other allergic diseases.

Results

This study employs MR to analyze the relationship between 3410 druggable genes and AR. After Bonferroni correction, 10 genes were found to be significantly associated with AR risk (P < 0.05/3410). Colocalization analysis revealed a significant causal relationship between the expression variation of CFL1 and EFEMP2 genes and AR, sharing direct causal variants (colocalization probability PP.H3 + PP.H4 > 0.8), highlighting their importance as potential therapeutic targets for AR. The CFL1 gene showed a causal link with levels of thymic stromal lymphopoietin (TSLP), eosinophil count, and interleukin-13 (IL-13) (P = 0.016, 7.45E-16, 0.00091, respectively). EFEMP2 was also causally related to eosinophil count, IL-13, and interleukin-17 (IL-17) (P = 0.00012, 0.00091, 0.032, respectively). PheWAS analysis revealed significant associations of CFL1 with asthma, whereas EFEMP2 showed associations with both asthma and eczema. Protein-Protein Interaction (PPI) network analysis further unveiled the direct interactions of EFEMP2 and CFL1 with proteins related to immune regulation and inflammatory responses, with 77.64% of the network consisting of direct bindings, indicating their key roles in modulating AR-related immune and inflammatory responses. Notably, there was an 8.01% significant correlation between immune-related pathways and genes involved in inflammatory responses.

Conclusion

These genes present notable associations with AR biomarkers and other autoimmune diseases, offering valuable targets for developing new AR therapies.

Innovation in pathogenesis and management of aortic aneurysm

Aortic aneurysm (AA) refers to the persistent dilatation of the aorta, exceeding three centimeters. Investigating the pathophysiology of this condition is important for its prevention and management, given its responsibility for more than 25000 deaths in the United States. AAs are classified based on their location or morphology. various pathophysiologic pathways including inflammation, the immune system and atherosclerosis have been implicated in its development. Inflammatory markers such as transforming growth factor β, interleukin-1β, tumor necrosis factor-α, matrix metalloproteinase-2 and many more may contribute to this phenomenon. Several genetic disorders such as Marfan syndrome, Ehler-Danlos syndrome and Loeys-Dietz syndrome have also been associated with this disease. Recent years has seen the investigation of novel management of AA, exploring the implication of different immune suppressors, the role of radiation in shrinkage and prevention, as well as minimally invasive and newly hypothesized surgical methods. In this narrative review, we aim to present the new contributing factors involved in pathophysiology of AA. We also highlighted the novel management methods that have demonstrated promising benefits in clinical outcomes of the AA.

Genetic associations of childhood and adult BMI on chronic heart failure and ischemic stroke: A Mendelian randomization

Background

Obesity has been confirmed to be associated with cardiovascular disease, but previous studies have focused on adults, and whether childhood obesity is associated with cardiovascular disease in adulthood needs further research.

Objective

This Mendelian randomization (MR) study aimed to investigate the associations of childhood and adult body mass index (BMI) with the risk of chronic heart failure (CHF) and ischemic stroke (IS).

Methods

Independent genetic instruments, demonstrating a strong association with exposure at the genome-wide significance level (P < 5 × 10-8), were carefully selected from comprehensive genome-wide association studies conducted within relevant European populations. Summary-level data for CHF and IS were obtained from the EBI database and large consortia of European population. To enhance robustness and generalizability, the analysis was replicated in an East Asian population cohort.

Results

According to a MR analysis based on a European population, a higher adult BMI was associated with an increased risk of CHF [(odds ratio (OR) 1.594, 95% confidence interval (CI) 1.483-1.713)] and IS (OR 1.163, 95%CI 1.096-1.233). In addition, higher childhood BMI level was associated with a higher risk of CHF (OR 1.323, 95%CI 1.153-1.524).and the effect was mainly driven by adult BMI. Replication analyses of adult BMI in East Asian populations showed consistent findings that adult BMI was associated with the risk of CHF (OR 2.167, 95%CI 1.786-2.630) and IS (OR 1.259, 95%CI 1.128-1.406).

Conclusions

Our study findings provide compelling evidence for the significant influence of adult BMI on the occurrence of CHF and IS. Furthermore, our observations suggest that the positive association between childhood BMI and the risk of CHF in adulthood can largely be attributed to individuals who maintain obesity into later life.

Multi-Omic Analysis Reveals Genetic Determinants and Therapeutic Targets of Chronic Kidney Disease and Kidney Function

Chronic kidney disease (CKD) presents a significant global health challenge, characterized by complex pathophysiology. This study utilized a multi-omic approach, integrating genomic data from the CKDGen consortium alongside transcriptomic, metabolomic, and proteomic data to elucidate the genetic underpinnings and identify therapeutic targets for CKD and kidney function. We employed a range of analytical methods including cross-tissue transcriptome-wide association studies (TWASs), Mendelian randomization (MR), summary-based MR (SMR), and molecular docking. These analyses collectively identified 146 cross-tissue genetic associations with CKD and kidney function. Key Golgi apparatus-related genes (GARGs) and 41 potential drug targets were highlighted, with MAP3K11 emerging as a significant gene from the TWAS and MR data, underscoring its potential as a therapeutic target. Capsaicin displayed promising drug-target interactions in molecular docking analyses. Additionally, metabolome- and proteome-wide MR (PWMR) analyses revealed 33 unique metabolites and critical inflammatory proteins such as FGF5 that are significantly linked to and colocalized with CKD and kidney function. These insights deepen our understanding of CKD pathogenesis and highlight novel targets for treatment and prevention.

Leveraging pQTL-based Mendelian randomization to identify new treatment prospects for primary biliary cholangitis and primary sclerosing cholangitis

Primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) are autoimmune disorders characterized by progressive and chronic damage to the bile ducts, presenting clinicians with significant challenges. The objective of this study is to identify potential druggable targets to offer new avenues for treatment. A Mendelian randomization analysis was performed to identify druggable targets for PBC and PSC. This involved obtaining Cis-protein quantitative trait loci (Cis-pQTL) data from the deCODE database to serve as exposure. Outcome data for PBC (557 cases and 281,127 controls) and PSC (1,715 cases and 330,903 controls) were obtained from the FINNGEN database. Colocalization analysis was conducted to determine whether these features share the same associated SNPs. Validation of the expression level of druggable targets was done using the GSE119600 dataset and immunohistochemistry for clinical samples. Lastly, the DRUGBANK database was used to predict potential drugs. The MR analysis identified eight druggable targets each for PBC and PSC. Subsequent summary-data-based MR and colocalization analyses showed that LEFTY2 had strong evidence as a therapeutic candidate for PBC, while HSPB1 had moderate evidence. For PSC, only FCGR3B showed strong evidence as a therapeutic candidate. Additionally, upregulated expression of these genes was validated in PBC and PSC groups by GEO dataset and clinical samples. This study identifies two novel druggable targets with strong evidence for therapeutic candidates for PBC (LEFTY2 and HSPB1) and one for PSC (FCGR3B). These targets offer new therapeutic opportunities to address the challenging nature of PBC and PSC treatment.

Identifying potential drug targets for idiopathic pulmonary fibrosis: a mendelian randomization study based on the druggable genes

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic fibrotic interstitial lung disease characterized by progressive dyspnea and decreased lung function, yet its exact etiology remains unclear. It is of great significance to discover new drug targets for IPF.

METHODS

We obtained the cis-expression quantitative trait locus (cis-eQTL) of druggable genes from eQTLGen Consortium as exposure and the genome wide association study (GWAS) of IPF from the International IPF Genetics Consortium as outcomes to simulate the effects of drugs on IPF by employing mendelian randomization analysis. Then colocalization analysis was performed to calculate the probability of both cis-eQTL of druggable genes and IPF sharing a causal variant. For further validation, we conducted protein quantitative trait locus (pQTL) analysis to reaffirm our findings.

RESULTS

The expression of 45 druggable genes was significantly associated with IPF susceptibility at FDR < 0.05. The expression of 23 and 15 druggable genes was significantly associated with decreased forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLco) in IPF patients, respectively. IPF susceptibility and two significant genes (IL-7 and ABCB2) were likely to share a causal variant. The results of the pQTL analysis demonstrated that high levels of IL-7 in plasma are associated with a reduced risk of IPF (OR = 0.67, 95%CI: 0.47-0.97).

CONCLUSION

IL-7 stands out as the most promising potential drug target to mitigate the risk of IPF. Our study not only sheds light on potential drug targets but also provides a direction for future drug development in IPF.

Mendelian randomization and single-cell expression analyses identify the causal relationship between depression and chronic rhinosinusitis

Background

The causative relationship between chronic rhinosinusitis (CRS) and depression remains unclear. Herein we employed Mendelian randomization (MR) coupled with single-cell analysis to investigate the causality between CRS and depression.

Methods

Data pertaining to CRS and depression were mined from the genome-wide association study database, and a single-cell dataset was sourced from the literature. To explore causality, we conducted bidirectional MR analysis using MR-Egger, weighted median, inverse variance weighted (IVW), simple mode, and weighted mode, with IVW representing the most important method. Further, sensitivity analysis was performed to evaluate the robustness of MR analysis results. Candidate genes were analyzed via single-cell combined MR analysis.

Results

Forward MR analysis indicated depression as a risk factor for CRS when depression was the exposure factor and CRS was the outcome (OR = 1.425, P < 0.001). Reverse MR analysis revealed the same positive relationship between CRS and depression when CRS was the exposure factor and depression was the outcome (OR = 1.012, P = 0.038). Sensitivity analysis validated the robustness of bidirectional MR analysis results. Ten cell types (endothelial, ciliated, basal, myeloid, mast, apical, plasma, glandular, fibroblast, and T cells) were identified in the single-cell dataset. The network of receptor-ligand pairs showed that in normal samples, cell-cell interactions were present among various cell types, such as epithelial, mast, myeloid, and endothelial cells. In contrast, CRS samples featured only one specific receptor-ligand pair, confined to myeloid cells. TCF4 and MEF2C emerged as potentially crucial for CRS-associated depression development.

Conclusions

Our findings suggest a bidirectional causal relationship between CRS and depression, offering a new perspective on the association between CRS and depression.

Identifying potential drug targets for varicose veins through integration of GWAS and eQTL summary data

Background

Varicose veins (VV) are a common chronic venous disease that is influenced by multiple factors. It affects the quality of life of patients and imposes a huge economic burden on the healthcare system. This study aimed to use integrated analysis methods, including Mendelian randomization analysis, to identify potential pathogenic genes and drug targets for VV treatment.

Methods

This study conducted Summary-data-based Mendelian Randomization (SMR) analysis and colocalization analysis on data collected from genome-wide association studies and cis-expression quantitative trait loci databases. Only genes with PP.H4 > 0.7 in colocalization were chosen from the significant SMR results. After the above analysis, we screened 12 genes and performed Mendelian Randomization (MR) analysis on them. After sensitivity analysis, we identified four genes with potential causal relationships with VV. Finally, we used transcriptome-wide association studies and The Drug-Gene Interaction Database data to identify and screen the remaining genes and identified four drug targets for the treatment of VV.

Results

We identified four genes significantly associated with VV, namely, KRTAP5-AS1 [Odds ratio (OR) = 1.08, 95% Confidence interval (CI): 1.05-1.11, p = 1.42e-10] and PLEKHA5 (OR = 1.13, 95% CI: 1.06-1.20, p = 6.90e-5), CBWD1 (OR = 1.05, 95% CI: 1.01-1.11, p = 1.42e-2) and CRIM1 (OR = 0.87, 95% CI: 0.81-0.95, p = 3.67e-3). Increased expression of three genes, namely, KRTAP5-AS1, PLEKHA5, and CBWD1, was associated with increased risk of the disease, and increased expression of CRIM1 was associated with decreased risk of the disease. These four genes could be targeted for VV therapy.

Conclusion

We identified four potential causal proteins for varicose veins with MR. A comprehensive analysis indicated that KRTAP5-AS1, PLEKHA5, CBWD1, and CRIM1 might be potential drug targets for varicose veins.

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

OBJECTIVE

Myasthenia gravis (MG) is a complex autoimmune disease affecting the neuromuscular junction with limited drug options, but the field of MG treatment recently benefits from novel biological agents. We performed a drug-targeted Mendelian randomization (MR) study to identify novel therapeutic targets of MG.

METHODS

Cis-expression quantitative loci (cis-eQTL), which proxy expression levels for 2176 druggable genes, were used for MR analysis. Causal relationships between genes and disease, identified by eQTL MR analysis, were verified by comprehensive sensitivity, colocalization, and protein quantitative loci (pQTL) MR analyses. The protein-protein interaction (PPI) analysis was also performed to extend targets, followed by enzyme-linked immunosorbent assay (ELISA) to explore the serum level of drug targets in MG patients. A phenome-wide MR analysis was then performed to assess side effects with a clinical trial review assessing druggability.

RESULTS

The eQTL MR analysis has identified eight potential targets for MG, one for early-onset MG and seven for late-onset MG. Further colocalization analyses indicated that CD226, CDC42BPB, PRSS36, and TNFSF12 possess evidence for colocalization with MG or late-onset MG. pQTL MR analyses identified the causal relations of TNFSF12 and CD226 with MG and late-onset MG. Furthermore, PPI analysis has revealed the protein interaction between TNFSF12-TNFSF13(APRIL) and TNFSF12-TNFSF13B(BLyS). Elevated TNFSF13 serum level of MG patients was also identified by ELISA experiments. This study has ultimately proposed three promising therapeutic targets (TNFSF12, TNFSF13, TNFSF13B) of MG.

CONCLUSIONS

Three drug targets associated with the BLyS/APRIL pathway have been identified. Multiple biological agents, including telitacicept and belimumab, are promising for MG therapy.

Deciphering the role of CX3CL1-CX3CR1 in aortic aneurysm pathogenesis: insights from Mendelian randomization and transcriptomic analyses

Background

The crucial role of inflammation in aortic aneurysm (AA) is gaining prominence, while there is still a lack of key cytokines or targets for effective clinical translation.

Methods

Mendelian randomization (MR) analysis was performed to identify the causal relationship between 91 circulating inflammatory proteins and AA and between 731 immune traits and AA. Bulk RNA sequencing data was utilized to demonstrate the expression profile of the paired ligand-receptor. Gene enrichment analysis, Immune infiltration, and correlation analysis were employed to deduce the potential role of CX3CR1. We used single-cell RNA sequencing data to pinpoint the localization of CX3CL1 and CX3CR1, which was further validated by multiplex immunofluorescence staining. Cellchat analysis was utilized to infer the CX3C signaling pathway. Trajectory analysis and the Cytosig database were exploited to determine the downstream effect of CX3CL1-CX3CR1.

Results

We identified 4 candidates (FGF5, CX3CL1, IL20RA, and SCF) in multiple two-sample MR analyses. Subsequent analysis of the expression profile of the paired receptor revealed the significant upregulation of CX3CR1 in AA and its positive correlation with pro-inflammatory macrophages. Two sample MR between immune cell traits and AA demonstrated the potential causality between intermediate monocytes and AA. We finally deciphered in single-cell sequencing data that CX3CL1 sent by endothelial cells (ECs) acted on CX3CR1 of intermediated monocytes, leading to its recruitment and pro-inflammatory responses.

Conclusion

Our study presented a genetic insight into the pathogenetic role of CX3CL1-CX3CR1 in AA, and further deciphered the CX3C signaling pathway between ECs and intermediate monocytes.

Exploring inflammatory bowel disease therapy targets through druggability genes: a Mendelian randomization study

Background

Inflammatory bowel disease is an incurable group of recurrent inflammatory diseases of the intestine. Mendelian randomization has been utilized in the development of drugs for disease treatment, including the therapeutic targets for IBD that are identified through drug-targeted MR.

Methods

Two-sample MR was employed to explore the cause-and-effect relationship between multiple genes and IBD and its subtypes ulcerative colitis and Crohn's disease, and replication MR was utilized to validate this causality. Summary data-based Mendelian randomization analysis was performed to enhance the robustness of the outcomes, while Bayesian co-localization provided strong evidential support. Finally, the value of potential therapeutic target applications was determined by using the estimation of druggability.

Result

With our investigation, we identified target genes associated with the risk of IBD and its subtypes UC and CD. These include the genes GPBAR1, IL1RL1, PRKCB, and PNMT, which are associated with IBD risk, IL1RL1, with a protective effect against CD risk, and GPX1, GPBAR1, and PNMT, which are involved in UC risk.

Conclusion

In a word, this study identified several potential therapeutic targets associated with the risk of IBD and its subtypes, offering new insights into the development of therapeutic agents for IBD.

Using Mendelian randomization provides genetic insights into potential targets for sepsis treatment

Sepsis is recognized as a major contributor to the global disease burden, but there is a lack of specific and effective therapeutic agents. Utilizing Mendelian randomization (MR) methods alongside evidence of causal genetics presents a chance to discover novel targets for therapeutic intervention. MR approach was employed to investigate potential drug targets for sepsis. Pooled statistics from IEU-B-4980 comprising 11,643 cases and 474,841 controls were initially utilized, and the findings were subsequently replicated in the IEU-B-69 (10,154 cases and 454,764 controls). Causal associations were then validated through colocalization. Furthermore, a range of sensitivity analyses, including MR-Egger intercept tests and Cochran's Q tests, were conducted to evaluate the outcomes of the MR analyses. Three drug targets (PSMA4, IFNAR2, and LY9) exhibited noteworthy MR outcomes in two separate datasets. Notably, PSMA4 demonstrated not only an elevated susceptibility to sepsis (OR 1.32, 95% CI 1.20-1.45, p = 1.66E-08) but also exhibited a robust colocalization with sepsis (PPH4 = 0.74). According to the present MR analysis, PSMA4 emerges as a highly encouraging pharmaceutical target for addressing sepsis. Suppression of PSMA4 could potentially decrease the likelihood of sepsis.

Unveiling potential drug targets for hyperparathyroidism through genetic insights via Mendelian randomization and colocalization analyses

Hyperparathyroidism (HPT) manifests as a complex condition with a substantial disease burden. While advances have been made in surgical interventions and non-surgical pharmacotherapy for the management of hyperparathyroidism, radical options to halt underlying disease progression remain lacking. Identifying putative genetic drivers and exploring novel drug targets that can impede HPT progression remain critical unmet needs. A Mendelian randomization (MR) analysis was performed to uncover putative therapeutic targets implicated in hyperparathyroidism pathology. Cis-expression quantitative trait loci (cis-eQTL) data serving as genetic instrumental variables were obtained from the eQTLGen Consortium and Genotype-Tissue Expression (GTEx) portal. Hyperparathyroidism summary statistics for single nucleotide polymorphism (SNP) associations were sourced from the FinnGen study (5590 cases; 361,988 controls). Colocalization analysis was performed to determine the probability of shared causal variants underlying SNP-hyperparathyroidism and SNP-eQTL links. Five drug targets (CMKLR1, FSTL1, IGSF11, PIK3C3 and SLC40A1) showed significant causation with hyperparathyroidism in both eQTLGen and GTEx cohorts by MR analysis. Specifically, phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3) and solute carrier family 40 member 1 (SLC40A1) showed strong evidence of colocalization with HPT. Multivariable MR and Phenome-Wide Association Study analyses indicated these two targets were not associated with other traits. Additionally, drug prediction analysis implies the potential of these two targets for future clinical applications. This study identifies PIK3C3 and SLC40A1 as potential genetically proxied druggable genes and promising therapeutic targets for hyperparathyroidism. Targeting PIK3C3 and SLC40A1 may offer effective novel pharmacotherapies for impeding hyperparathyroidism progression and reducing disease risk. These findings provide preliminary genetic insight into underlying drivers amenable to therapeutic manipulation, though further investigation is imperative to validate translational potential from preclinical models through clinical applications.

Causal relationships of metabolites with allergic diseases: a trans-ethnic Mendelian randomization study

BACKGROUND

Allergic diseases exert a considerable impact on global health, thus necessitating investigations into their etiology and pathophysiology for devising effective prevention and treatment strategies. This study employs a Mendelian randomization (MR) analysis and meta-analysis to identify metabolite targets potentially associated with allergic diseases.

METHODS

A two-sample MR analysis was conducted to explore potential causal relationships between circulating and urinary metabolites and allergic diseases. Exposures were derived from a genome-wide association study (GWAS) of 486 circulating metabolites and a GWAS of 55 targeted urinary metabolites. Outcome data for allergic diseases, including atopic dermatitis (AD), allergic rhinitis (AR), and asthma, were obtained from the FinnGen biobank in Europe (cohort 1) and the Biobank Japan in Asia (cohort 2). MR results from both cohorts were combined using a meta-analysis.

RESULTS

MR analysis identified 50 circulating metabolites and 6 urinary metabolites in cohort 1 and 54 circulating metabolites and 2 urinary metabolites in cohort 2 as potentially causally related to allergic diseases. A meta-analysis of the MR results revealed stearoylcarnitine (OR 8.654; 95% CI 4.399-17.025; P = 4.06E-10) and 1-arachidonoylglycerophosphoinositol (OR 2.178; 95% CI 1.388-3.419; P = 7.15E-04) as the most reliable causal circulating metabolites for asthma and AR, respectively. Further, histidine (OR 0.734; 95% CI: 0.594-0.907; P = 0.004), tyrosine (OR 0.601; 95% CI: 0.380-0.952; P = 0.030), and alanine (OR 0.280; 95% CI: 0.125-0.628; P = 0.002) emerged as urinary metabolites with the greatest protective effects against asthma, AD, and AR, respectively.

CONCLUSIONS

Imbalances in numerous circulating and urinary metabolites may be implicated in the development and progression of allergic diseases. These findings have significant implications for the development of targeted strategies for the prevention and treatment of allergic diseases.

Genetic insights into associations of multisite chronic pain with common diseases and biomarkers using data from the UK Biobank

BACKGROUND

Chronic pain is a common, complex, and challenging condition, for which specialised healthcare is required. We investigated the relationship between multisite chronic pain (MCP) and different disease traits identify safe biomarker interventions that can prevent MCP.

METHODS

Univariable and multivariable Mendelian randomisation (MR) analysis were conducted to investigate associations between MCP and 36 common diseases in the UK Biobank. Subsequently, we estimated the potential effect of expression of 4774 proteins on MCP utilising existing plasma protein quantitative trait locus data. For the significant biomarkers, we performed phenome-wide MR (Phe-MR) with 1658 outcomes to predict potential safety profiles linked to biomarker intervention.

RESULTS

Multisite chronic pain had a substantial impact on psychiatric and neurodevelopmental traits (major depression and attention deficit hyperactivity disorder), cardiovascular diseases (myocardial infarction, coronary artery disease, and heart failure), respiratory outcomes (asthma, chronic obstructive pulmonary disease, and sleep apnoea), arthropathies, type 2 diabetes mellitus, and cholelithiasis. Higher genetically predicted levels of S100A6, DOCK9, ferritin, and ferritin light chain were associated with a risk of MCP, whereas PTN9 and NEUG were linked to decreased MCP risk. Phe-MR results suggested that genetic inhibition of DOCK9 increased the risk of 21 types of disease, whereas the other biomarker interventions were relatively safe.

CONCLUSIONS

We established that MCP has an effect on health conditions covering various physiological systems and identified six novel biomarkers for intervention. In particular, S100A6, PTN9, NEUG, and ferritin light chain represent promising targets for MCP prevention, as no significant side-effects were predicted in our study.

Using Genomics to Identify Novel Therapeutic Targets for Aortic Disease

Aortic disease, including dissection, aneurysm, and rupture, carries significant morbidity and mortality and is a notable cause of sudden cardiac death. Much of our knowledge regarding the genetic basis of aortic disease has relied on the study of individuals with Mendelian aortopathies and, until recently, the genetic determinants of population-level variance in aortic phenotypes remained unclear. However, the application of machine learning methodologies to large imaging datasets has enabled researchers to rapidly define aortic traits and mine dozens of novel genetic associations for phenotypes such as aortic diameter and distensibility. In this review, we highlight the emerging potential of genomics for identifying causal genes and candidate drug targets for aortic disease. We describe how deep learning technologies have accelerated the pace of genetic discovery in this field. We then provide a blueprint for translating genetic associations to biological insights, reviewing techniques for locus and cell type prioritization, high-throughput functional screening, and disease modeling using cellular and animal models of aortic disease.

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.

Association between circulating fatty acid metabolites and asthma risk: a two-sample bidirectional Mendelian randomization study

BACKGROUND

Fatty acids are involved in a wide range of immunological responses in humans. Supplementation of polyunsaturated fatty acids has been reported to help alleviate symptoms and airway inflammation in asthma patients, whereas the effects of fatty acids on the actual risk of asthma remain controversial. This study comprehensively investigated the causal effects of serum fatty acids on asthma risk using two-sample bidirectional Mendelian Randomization (MR) analysis.

METHODS

Genetic variants strongly associated with 123 circulating fatty acid metabolites were extracted as instrumental variables, and a large GWAS data of asthma was used to test effects of the metabolites on this outcome. The inverse-variance weighted method was used for primary MR analysis. The weighted median, MR-Egger regression, MR-PRESSO, and leave-one-out analyses were utilized to evaluate heterogeneity and pleiotropy. Potential confounders were adjusted by performing multivariable MR analyses. Reverse MR analysis was also conducted to estimate the causal effect of asthma on candidate fatty acid metabolites. Further, we performed colocalization analysis to examine the pleiotropy of variants within the fatty acid desaturase 1 (FADS1) locus between the significant metabolite traits and the risk of asthma. Cis-eQTL-MR and colocalization analysis were also performed to determine the association between RNA expression of FADS1 and asthma.

RESULTS

Genetically instrumented higher average number of methylene groups was causally associated with a lower risk of asthma in primary MR analysis, while inversely, the higher ratio of bis-allylic groups to double bonds and the higher ratio of bis-allylic groups to total fatty acids, were associated with higher probabilities of asthma. Consistent results were obtained in multivariable MR when adjusted for potential confounders. However, these effects were completely eliminated after SNPs correlated with the FADS1 gene were excluded. The reverse MR also found no causal association. The colocalization analysis suggested that the three candidate metabolite traits and asthma likely share causal variants within the FADS1 locus. In addition, the cis-eQTL-MR and colocalization analyses demonstrated a causal association and shared causal variants between FADS1 expression and asthma.

CONCLUSIONS

Our study supports a negative association between several PUFA traits and the risk of asthma. However, this association is largely attributed to the influence of FADS1 polymorphisms. The results of this MR study should be carefully interpreted given the pleiotropy of SNPs associated with FADS1.

Vascular Biology of arterial aneurysms

OBJECTIVE

This review aims to analyze biomolecular and cellular events responsible for arterial aneurysm formation with particular attention to vascular remodeling that determines the initiation and the progression of arterial aneurysm, till rupture.

METHODS

This review was conducted searching libraries such as Web of Science, Scopus, ScienceDirect and Medline. Used keywords with various combinations were: "arterial aneurysms", "biology", "genetics", "proteomics", "molecular", "pathophysiology" and extracellular matrix" RESULTS: There are several genetic alterations responsible of syndromic and non-syndromic disease that predispose to aneurysm formation. ECM imbalance, mainly due to the alteration of vascular smooth muscle cells (VSMCs) homeostasis, overexpression of metalloproteinases (MPs) and cytokines activation, determines weakness of the arterial wall that dilates thus causing aneurysmal disease. Altered mechanotransduction in the ECM may also trigger and sustain anomalous cellular and biochemical signaling. Different cell population such as VSMCs, macrophages, perivascular adipose tissue (PVAT) cells, vascular wall resident stem cells (VWRSCs) are all involved at different levels CONCLUSIONS: Improving knowledge in vascular biology may help researchers and physicians in better targeting aneurysmal disease in order to better prevent and better treat such important disease.