RESUMO
BACKGROUND: Genome-wide association studies (GWAS) have revealed numerous loci associated with multiple sclerosis (MS). However, the challenge lies in deciphering the mechanisms by which these loci influence the target traits. Here, we employed an integrative analytical pipeline to efficiently transform genetic associations to identify novel proteins for MS. METHODS: We systematically integrated MS GWAS data (N = 115,803) with human plasma proteome data (N = 7213) and conducted proteome-wide association studies (PWAS) to identify MS-associated pathogenic proteins. Following this, we employed Mendelian randomization and Bayesian colocalization analyses to verify the causal relationship between these significant plasma proteins and MS. Lastly, we utilized the Drug-Gene Interaction Database (DGIdb) to identify potential drug targets for MS. RESULTS: The PWAS identified 25 statistically significant cis-regulated plasma proteins associated with MS at a false discovery rate of P < 0.05. Further analysis revealed that the abundance of 7 of these proteins (PLEK, TNXB, CASP3, CD59, CR1, TAPBPL, ATXN3) was causally related to the incidence of MS. Our findings indicated that genetically predicted higher levels of TNXB and CD59 were associated with a lower risk of MS, whereas higher levels of PLEK, CASP3, CR1, TAPBPL, and ATXN3 were associated with an increased risk of MS. Three plasma proteins (PLEK, CR1, CD59) were validated by colocalization analysis. Among these, CR1 was prioritized as a target for Eculizumab due to its significant association with MS risk. Additionally, PLEK, CR1, and CD59 were identified as druggable target genes. CONCLUSIONS: Our proteomic analysis has identified PLEK, CR1, and CD59 as potential drug targets for MS treatment. Developing pharmacological inducers or inhibitors for these proteins could pave the way for new therapeutic approaches, potentially improving outcomes for MS patients.
Assuntos
Estudo de Associação Genômica Ampla , Esclerose Múltipla , Proteoma , Humanos , Esclerose Múltipla/tratamento farmacológico , Esclerose Múltipla/genética , Esclerose Múltipla/sangue , Teorema de Bayes , Proteínas Sanguíneas/metabolismo , Proteínas Sanguíneas/genética , Análise da Randomização Mendeliana , Antígenos CD59/genética , Predisposição Genética para Doença , Proteômica/métodosRESUMO
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).
Assuntos
Teorema de Bayes , Estudo de Associação Genômica Ampla , Doenças Inflamatórias Intestinais , Proteômica , Humanos , Proteômica/métodos , Doenças Inflamatórias Intestinais/genética , Doenças Inflamatórias Intestinais/tratamento farmacológico , Doenças Inflamatórias Intestinais/sangue , Colite Ulcerativa/genética , Colite Ulcerativa/tratamento farmacológico , Colite Ulcerativa/sangue , Predisposição Genética para Doença , Doença de Crohn/genética , Doença de Crohn/tratamento farmacológico , Doença de Crohn/sangue , Proteoma/metabolismo , Polimorfismo de Nucleotídeo Único , Proteínas Sanguíneas/genética , Proteínas Sanguíneas/metabolismo , Análise da Randomização MendelianaRESUMO
BACKGROUND: Ultrasound-guided microwave ablation (MWA) is recommended as a first-line treatment for early liver cancer due to its minimally invasive, efficient, and cost-effective nature. It utilizes microwave radiation to heat and destroy tumor cells as a local thermal therapy and offers the benefits of being minimally invasive, repeatable, and applicable to tumors of various sizes and locations. However, despite the efficacy of MWA, early recurrence after treatment remains a challenge, particularly when it occurs within a year and has a significant impact on the prognosis of the patient. OBJECTIVE: This study aimed to identify the risk factors for early recurrence after MWA in patients with hepatocellular carcinoma (HCC) and establish a predictive model. METHODS: A total of 119 patients with hepatocellular carcinoma (HCC) treated in the Department of Ultrasound at the First Affiliated Hospital of the Air Force Medical University from January, 2020 to April, 2022 were included in this study. Patients were categorized into the early recurrence group and the non-early recurrence group based on whether recurrence occurred within 1 year. We conducted univariate analysis on 29 variables. A predictive model was developed using multiple-factor logistic regression analysis, and a risk column graph was created. RESULTS: A total of 28 patients were included in the early recurrence group, with an early recurrence rate of 23%. Tumor size ≥ 3cm, multiple tumors, AST > 35 U/L, low pathological differentiation, CD34 positive, Ki67 level, quantitative parameters mean transit time (mTT), and rise time (RT) were confirmed as risk factors affecting early recurrence after ablation (P < 0.05). Furthermore, the model constructed based on these 5 predictive factors, including tumor size, tumor number, pathological differentiation, CD34, and quantitative analysis parameter mTT, demonstrated good predictive ability, with an AUC of 0.93 in the training set and 0.86 in the validation set. CONCLUSION: Our research indicates that the risk column graph can be utilized to predict the risk of early postoperative recurrence in patients after MWA. This contributes to guiding personalized clinical treatment decisions and provides important references for improving the prognosis of patients.