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Background <p>Metabolic dysfunction-associated steatotic liver disease (MASLD) affects &gt; 25% of the global population, potentially leading to severe hepatic and extrahepatic complications, including metabolic dysfunction-associated steatohepatitis. Given that the pathophysiology of MASLD is incompletely understood, identifying therapeutic targets and optimizing treatment strategies are crucial for addressing this severe condition.</p> Methods <p>Mendelian randomization (MR) analysis was conducted using two genome-wide association study datasets: a European meta-analysis (8,434 cases; 770,180 controls) and an additional study (3,954 cases; 355,942 controls), identifying therapeutic targets for MASLD. Of 4302 drug-target genes, 2,664 genetic instrument variables were derived from cis-expression quantitative trait loci (cis-eQTLs). Colocalization analyses assessed shared causal variants between MASLD-associated single nucleotide polymorphisms and eQTLs. Using the drug target gene cis-eQTL of liver tissue from the genotype-tissue expression project, we performed MR and summary MR to validate the significance of the gene results of the blood eQTL MR. RNA-sequencing data from liver biopsies were validated using immunohistochemistry and quantitative polymerase chain reaction (qPCR) tests to confirm gene expression findings.</p> Result <p>MR analysis across both datasets identified significant MR associations between MASLD and two drug targets—milk fat globule-EGF factor 8 (<i>MFGE8</i>) (odds ratio [OR] 0.89, 95% confidence interval [CI] 0.85–0.94; <i>P</i> = 2.15 × 10<sup>−6</sup>) and cluster of differentiation 33 (<i>CD33</i>) (OR 1.17, 95% CI 1.10–1.25; <i>P</i> = 1.39 × 10<sup>−6</sup>). Both targets exhibited strong colocalization with MASLD. Genetic manipulation indicating <i>MFGE8</i> activation and <i>CD33</i> inhibition did not increase the risk for other metabolic disorders. RNA-sequencing, qPCR, and immunohistochemistry validation demonstrated consistent differential expressions of <i>MFGE8</i> and <i>CD33</i> in MASLD.</p> Conclusion <p><i>CD33</i> inhibition can reduce MASLD risk, while <i>MFGE8</i> activation may offer therapeutic benefits for MASLD treatment.</p>

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Druggable genome-wide Mendelian randomization identifies therapeutic targets for metabolic dysfunction-associated steatotic liver disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月26日

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  • Xiaohui Ma,
  • Li Ding,
  • Shuo Li,
  • Yu Fan,
  • Xin Wang,
  • Yitong Han,
  • Hengjie Yuan,
  • Longhao Sun,
  • Qing He,
  • Ming Liu

摘要

Background

Metabolic dysfunction-associated steatotic liver disease (MASLD) affects > 25% of the global population, potentially leading to severe hepatic and extrahepatic complications, including metabolic dysfunction-associated steatohepatitis. Given that the pathophysiology of MASLD is incompletely understood, identifying therapeutic targets and optimizing treatment strategies are crucial for addressing this severe condition.

Methods

Mendelian randomization (MR) analysis was conducted using two genome-wide association study datasets: a European meta-analysis (8,434 cases; 770,180 controls) and an additional study (3,954 cases; 355,942 controls), identifying therapeutic targets for MASLD. Of 4302 drug-target genes, 2,664 genetic instrument variables were derived from cis-expression quantitative trait loci (cis-eQTLs). Colocalization analyses assessed shared causal variants between MASLD-associated single nucleotide polymorphisms and eQTLs. Using the drug target gene cis-eQTL of liver tissue from the genotype-tissue expression project, we performed MR and summary MR to validate the significance of the gene results of the blood eQTL MR. RNA-sequencing data from liver biopsies were validated using immunohistochemistry and quantitative polymerase chain reaction (qPCR) tests to confirm gene expression findings.

Result

MR analysis across both datasets identified significant MR associations between MASLD and two drug targets—milk fat globule-EGF factor 8 (MFGE8) (odds ratio [OR] 0.89, 95% confidence interval [CI] 0.85–0.94; P = 2.15 × 10−6) and cluster of differentiation 33 (CD33) (OR 1.17, 95% CI 1.10–1.25; P = 1.39 × 10−6). Both targets exhibited strong colocalization with MASLD. Genetic manipulation indicating MFGE8 activation and CD33 inhibition did not increase the risk for other metabolic disorders. RNA-sequencing, qPCR, and immunohistochemistry validation demonstrated consistent differential expressions of MFGE8 and CD33 in MASLD.

Conclusion

CD33 inhibition can reduce MASLD risk, while MFGE8 activation may offer therapeutic benefits for MASLD treatment.