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. 2025 Aug 20;2025:6664846. doi: 10.1155/ije/6664846

Association Between PNPLA3 Inhibition and Gout: A Drug Target Mendelian Randomization Study

Chen Wang 1, Pei Guo 1, Xiang Liu 1, Xingxing Xu 1, Li Zou 1, Shi Meng 1, Qing Guo 1, Qiang Wen 2, Chuang Yang 2,✉
PMCID: PMC12390521  PMID: 40881642

Abstract

Aims: Patatin-like phospholipase domain-containing protein 3 (PNPLA3) plays a crucial role in metabolic dysfunction–related steatotic liver disease. ARO-PNPLA3 is a therapeutic agent designed to target PNPLA3, but its long-term effects remain uncertain. The objective of this study was to ascertain the impact of PNPLA3 inhibition on the risk of gout through Mendelian randomization.

Methods: Mendelian randomization analysis was conducted by choosing single nucleotide polymorphisms (SNPs) in proximity to the PNPLA3 gene, which were significantly associated with the percentage of hepatic fat, to represent PNPLA3 suppression. Nonalcoholic fatty liver disease and hepatic fibrosis served as positive controls, while urate and gout were the outcomes.

Results: Genetically predicted PNPLA3 inhibition significantly increased the risk of gout (OR: 1.83, 95% CI: 1.49 to 2.26, p = 1.44 × 10−8), idiopathic gout (OR: 2.42, 95% CI: 1.60 to 3.65, p = 2.81 × 10−5) and urate (OR: 1.12, 95% CI: 1.01 to 1.23, p = 2.56 × 10−2), but not with gout due to impairment of renal function (OR: 1.25, 95% CI: 0.37 to 4.22, p = 7.23 × 10−1).

Conclusions: This study found that PNPLA3 inhibition increased the risk of high urate level and gout. In addition, PNPLA3 inhibition also increased triglyceride (TG) levels, which partially mediate the relationship between PNPLA3 inhibition and gout.

Trial Registration: ClinicalTrials.gov identifier: NCT04844450

Keywords: gout, Mendelian randomization, metabolic dysfunction–associated steatotic liver disease, PNPLA3, urate

1. Introduction

Metabolic dysfunction–associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease (NAFLD), represents one of the most pervasive chronic liver diseases globally [1]. This condition significantly impacts public health on an international scale. MASLD is characterized by hepatic steatosis and a combination of other metabolic risk factors and can progress to cirrhosis and hepatocellular carcinoma [2, 3]. Although previous studies have shown that beneficial lifestyle and exercise can slow the progression of fatty liver, they are incapable of reversing existing lesions [4]. Therefore, finding and developing pharmacologic interventions for MASLD is very attractive.

Genome-wide association studies (GWASs) are a method for identifying associations between genetic regions (genomes) and traits/diseases. Through GWAS analysis, the researchers found that genetic variants closely associated with MASLD were located near the patatin-like phospholipase domain-containing protein 3 (PNPLA3), TM6SF2, and HSD17B1 genes [4]. The results of the GWAS analysis suggest the involvement of these three genes in the development of MASLD and the potential as therapeutic targets for MASLD. Additionally, Liu et al. found that individuals carrying the PNPLA3 rs738409 C > G gene polymorphism (I148M) had a higher risk of developing MASLD and liver fibrosis [5]. Animal model studies have further demonstrated that variants of the PNPLA3 protein in the liver influence the equilibrium of hepatic lipid metabolism [6]. Such research implies that PNPLA3 might serve as a promising therapeutic target for impeding the progression of MASLD. Currently, ARO-PNPLA3 is a newly developed therapy for MASLD. ARO-PNPLA3 reduced liver PNPLA3 protein expression and decreases liver fat in MASLD patients [7]. In phase I clinical trial, ARO-PNPLA3 has shown exciting results and may bring a new and unique therapeutic approach to the treatment of MASLD. However, the restricted clinical trial data do not indicate safety in long-term therapy. Consequently, considering the correlation between MASLD onset and metabolic function, it is essential to further examine the impact of PNPLA3 inhibition on other metabolic-related diseases.

Gout is a metabolic disease caused by abnormal metabolism of purines, resulting in increased synthesis of blood urate or decreased excretion of urate [8]. Multiple cross-sectional investigations and meta-analyses have demonstrated the association between urate and MASLD [9–12]. Nevertheless, ARO-PNPLA3, a prospective therapeutic agent for MASLD, is still unknown for the effect of PNPLA3 inhibition on urate and gout.

Mendelian randomization (MR) has become a widely adopted analytical method to assess the relationship between genetically predicted exposure and outcomes [13]. In this study, we proposed a two-sample MR approach to explore the association between PNPLA3 inhibition and gout. Furthermore, given the strong correlation between lipids and MASLD, we employed a two-step MR to assess the potential role of plasma lipids in the relationship between PNPLA3 and gout. The objective of this research is to offer insights for subsequent clinical trials or future clinical applications of PNPLA3 inhibitors.

2. Methods

2.1. Study Design

This study was designed according to the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR). The design for MR was required to meet three assumptions: (1) a strong correlation exists between the instrumental variable representing the genetic variant and the exposure; (2) the genetic variant is not associated with confounders; and (3) the genetic variant influences the outcome exclusively through the exposure (Figure 1). Since this investigation solely utilized data from publicly accessible GWAS, it was not mandatory to seek additional ethical review from the institutional review board.

Figure 1.

Figure 1

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MR study design.

2.2. Selection of Instrumental Variables

The GWAS data for percent liver fat were derived from a real-world UK Biobank dataset encompassing 32,858 participants, in which liver fat was meticulously gauged and quantified by the researchers [14]. To symbolize the function of PNPLA3 inhibition, we employed the percentage of liver fat as a biomarker. We first extracted all single-nucleotide polymorphisms (SNPs) located ±250 kb around the PNPLA3 gene (GRCh37/hg19, chr22: 44,316,685–44,343,462) that were genome-wide significant for percentage of liver fat (P < 5 × 10−8). Then, we pruned these SNPs to remove linkage disequilibrium (r2 < 0.1) We further computed the F-statistics of SNPs to eliminate weak instrumental variables (F-statistics < 10). Based on the MR hypothesis, a total of 8 SNPs were identified (Table s1). The F-statistics of the selected IVs were all above 10, suggesting that the conclusions are unlikely to be influenced by weak IVs.

2.3. Genetic Instruments for Mediators and Outcomes

GWAS data related to gout outcomes were obtained from FINNGEN and encompassed gout (3576 instances and 147,221 counterparts), idiopathic gout (819 instances and 215,216 counterparts), and gout due to impaired renal function (92 cases and 215,216 controls) [15]. Urate data were derived from a GWAS analysis of 110,347 participants of European ancestry by the Global Urate Genetics Consortium (GUGC) [16]. Data on NAFLD (894 cases and 217,898 controls) and liver fibrosis and cirrhosis (811 cases and 213,592 controls) in the positive controls were also obtained from FINNGEN. Given the correlation between plasma lipid levels and the occurrence of MASLD, we also examined the potential mediating influence of several lipids, including triglyceride (TG), total cholesterol (TC), LDL cholesterol (LDL-C), apolipoprotein A-I (ApoA1), and apolipoprotein B (ApoB). The data for TC were sourced from the Global Lipids Genetics Consortium (GLGC) [17], while the data for the remaining lipids were derived from a study conducted by the UK Biobank [18].

2.4. Statistical Analysis

The primary analytical approach employed was inverse variance weighting (IVW). This was supplemented with MR Egger, weighted median, simple mode, and weighted mode techniques [19]. The pleiotropy of IVs was evaluated using the MR-PRESSO global test and MR-Egger regression, while Cochran's Q test was utilized to assess heterogeneity. Additionally, leave-one-out analyses were conducted to ascertain the impact of individual SNPs on MR estimates. We conducted a two-step MR analysis to investigate the role of lipid traits in mediating the relationship between PNPLA3 inhibition and gout. We first estimated the effect of PNPLA3 inhibition on lipid (β1). Subsequently, we assessed the impact of lipids on gout (β2). The proportion of each lipid mediating the association between PNPLA3 inhibition and gout was determined by multiplying β1 and β2 and then dividing by the total effect of PNPLA3 on gout. All analyses were executed using R software (Version 4.1.3), with MR analyses and sensitivity analyses performed utilizing the TwoSampleMR R package (Version 0.5.6) and the MRPRESSO package (Version 1.0).

3. Results

3.1. MR Analysis to Estimate the Effects of PNPLA3 Inhibition on Positive Controls

As shown in Figure 2, PNPLA3 inhibition was associated with a reduced risk of NAFLD (OR: 0.08, 95% CI: 0.05 to 0.14, p=1.157 × 10−20) and fibrosis and cirrhosis of the liver (OR: 0.17, 95% CI: 0.10 to 0.30, p=2.174 × 10−9) (Figure s1). Sensitivity analyses did not show heterogeneity and pleiotropy (Table s2). In addition, MR-PRESSO analysis did not identify any potential pleiotropic SNP associated with liver disease outcomes (Table s2). Leave-one-out analysis indicated that the association between PNPLA3 inhibition and liver diseases was unlikely to be significantly influenced by any single SNP (Figure s2).

Figure 2.

Figure 2

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Forest plot for estimating the effect of PNPLA3 inhibition on liver diseases. OR, odds ratio; CI, confidence interval.

3.2. MR Analysis to Estimate the Effects of PNPLA3 Inhibition on Gout and Urate

As shown in Figure 3, genetically predicted PNPLA3 inhibition resulted in an increased risk of gout (OR: 1.83, 95% CI: 1.49 to 2.26, p=1.44 × 10−8) and idiopathic gout (OR: 2.42, 95% CI: 1.60 to 3.65, p=2.81 × 10−5) (Figure s3), but not for gout due to impaired renal function (OR: 1.25, 95% CI: 0.37 to 4.22, p=7.23 × 10−1). In addition, genetically predicted PNPLA3 inhibition also elevated urate levels (OR: 1.12, 95% CI: 1.01 to 1.23, p=2.56 × 10−2). Sensitivity analyses did not show heterogeneity and pleiotropy (Table s3). MR-PRESSO analysis did not identify any potential pleiotropic SNP associated with gout and urate (Table s3). Leave-one-out analysis showed that the association between PNPLA3 inhibition and gout and urate was not significantly affected by any single SNP (Figure s4).

Figure 3.

Figure 3

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Forest plot for estimating the effect of PNPLA3 inhibition on gout and urate. OR, odds ratio; CI, confidence interval.

3.3. Mediation Analysis

For lipids, genetically predicted PNPLA3 inhibition elevated TG (β: 0.023, se: 0.008, p=3.77 × 10−3), LDL-C (β: 0.026, se: 0.008, p=1.51 × 10−3), and ApoA1 (β: 0.091, se: 0.009, p=4.60 × 10−26) levels but was not significantly associated with TC or ApoB (Table s4). Sensitivity analysis showed no pleiotropy or heterogeneity (Table s5). Subsequently, we confirmed whether TG, LDL-C, and ApoA1 played roles in the genetically predicted link between PNPLA3 inhibition and gout. The findings indicate that LDL-C and ApoA1 are improbable mediators of the genetically predicted association between PNPLA3 inhibition and gout (Table S6). However, blood TG may mediate the genetically predicted association between PNPLA3 inhibition and gout and urate (Figure 4 and Table s7).

Figure 4.

Figure 4

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Associations between PNPLA3 inhibition and gout mediated by blood TG. TG, triglyceride.

4. Discussion

As far as we know, this is the first study on the association between PNPLA3 inhibition and gout. In this study, we simulated the impact of PNPLA3 inhibition by choosing SNPs adjacent to the PNPLA3 gene as instrumental variables, utilizing liver fat percentage as a biomarker. The selected instrumental variables notably diminished the risk of NAFLD and liver fibrosis, indicating that these variables accurately represent the effects of PNPLA3 inhibition. Moreover, we discovered that genetically predicted PNPLA3 inhibition could elevate the risk of idiopathic gout, gout, and high urate levels. Further analysis revealed that PNPLA3 inhibition might elevate TG, LDL-C, and ApoA1 levels, and TG may partially mediate the association between PNPLA3 inhibition and gout.

MASLD, previously known as NAFLD, has a relatively complex pathogenesis [20]. Due to the increasing incidence of MASLD, the search for therapeutic MASLD targets has attracted extensive attention from researchers. With the progress of GWASs in recent years, researchers have found a strong link between PNPLA3 and MASLD [21, 22]. The PNPLA3 protein is predominantly localized on the cytosolic lipid droplets (LDs) of liver and adipose tissues. It is known to possess TG hydrolase activity, which facilitates TG metabolism [23]. The PNPLA3 I148M mutation impairs TG mobilization within the LP by preventing ubiquitination and reducing degradation, which consequently leads to TG accumulation [6]. Researchers have also discovered that treating mice with antisense oligonucleotides targeting the PNPLA3 gene suppressed the expression of the PNPLA3 I148M variant, slowed the progression of NAFLD, and improved liver fibrosis [24]. Inhibiting the expression of the PNPLA3 protein may serve as an effective therapeutic approach for MASLD patients harboring the I148M mutation. In addition to its association with MASLD, some prospective studies have also suggested that PNPLA3 variants are associated with chronic kidney disease [25], and patients carrying PNPLA3 variants have a higher risk of early glomerular and tubular damage [26]. Kidney disease may lead to impaired uric acid excretion, which in turn may affect the occurrence of gout.

ARO-PNPLA3, a therapeutic agent that targets PNPLA3 mRNA to reduce its expression in hepatocytes, has shown promising results in reducing liver fat content without causing serious adverse events in a phase I clinical trial [7]. However, the complete function of PNPLA3 is yet to be fully understood, and its role in the progression of MASLD requires further investigation. Consequently, it is imperative to continue evaluating the viability and safety of PNPLA3 as a potential therapeutic target for MASLD. Gout is a metabolic disease associated with urate levels. Persistently high levels of urate are a major risk factor for gout. In addition, impaired renal function, resulting in impaired urate excretion, can also lead to gout. Urate levels are also closely related to lipid metabolism. A study by Wang et al. demonstrated a correlation between elevated urate levels and increased TG and visceral fat content [27]. Additionally, another prospective study indicated that high levels of TG and LDL-C are associated with an increased risk of hyperuricemia [28]. In addition, the MR study by Yu et al. also showed that TG levels were also positively correlated with serum urate [29], which is consistent with our results. In this MR study, genetically predicted PNPLA3 inhibition was associated with an increased risk of elevated urate levels and gout. However, there was no association between PNPLA3 inhibition and gout due to impaired renal function. These findings suggest that the mechanism by which PNPLA3 inhibition might increase the risk of gout is unlikely to involve direct effects on kidney function. Further, mediation analyses revealed that elevated TG levels were associated with an increased risk of high urate level and gout. Additionally, these analyses indicated that blood TG levels may act as a mediator in the relationship between PNPLA3 inhibition and the increased risk of gout. Although there was no direct evidence to indicate the molecular mechanism of PNPLA3 inhibition in gout, based on previous studies of PNPLA3 and our MR results, we speculated that PNPLA3 inhibition leads to LD accumulation, thereby disrupting LD remodeling and triggering mitochondrial dysfunction, excessive ROS, and lipid peroxidation products [6, 30, 31]. The excessive ROS activated the NLRP3 inflammasome, promoting the release of proinflammatory factors such as IL-1β, which further damages renal tubular epithelial cells, inhibited the function of uric acid transporters such as ABCG2 and URAT1, and caused impaired uric acid excretion, ultimately leading to the onset of gout. Therefore, it is essential to closely monitor whether ARO-PNPLA3 administration results in alterations in blood TG levels and increased urate during subsequent clinical trials. Furthermore, additional research is needed to determine if the inhibition of PNPLA3 due to prolonged pharmacological use elevates the risk of gout.

There are several limitations to our study that should be considered. First, the data selected for analysis were derived exclusively from European populations and did not include individuals from other ethnic or racial backgrounds. Second, the genetic instrument used in this study represents the lifetime effect of PNPLA3 activity rather than the short-term inhibitory effects of a pharmacological agent. These limitations underscore the need for further research to validate and extend these findings to more diverse populations and to specifically assess the short-term effects of PNPLA3 inhibition as would occur with drug treatment.

5. Conclusion

In conclusion, this study found that PNPLA3 inhibition increased the risk of high uric acid levels and gout. Additionally, PNPLA3 inhibition was associated with elevated TG levels, which partially mediated the relationship between PNPLA3 inhibition and an increased risk of gout. These findings provide important insights that will aid in the design and assessment of future clinical trials involving PNPLA3 inhibitors.

Acknowledgments

Thanks are due to the investigators who performed GWAS analyses and shared the data available in this study.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Ethics Statement

Our data come from publicly accessible databases, and thus there is no need to seek further ethical clearance from institutional review boards.

Consent

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Author Contributions

Conceptualization: Chen Wang and Chuang Yang; investigation and data curation: Pei Guo, Xiang Liu, Xingxing Xu, Li Zou, Shi Meng, Qing Guo, Qiang Wen, and Chuang Yang; writing–original draft: Chen Wang; and writing–review and editing: Chen Wang and Chuang Yang.

Funding

This work had no funding support.

Supporting Information

Supporting Information

Additional supporting information can be found online in the Supporting Information section.

6664846.f1.docx (234.4KB, docx)

Figure s1. Scatter plots for the effect of PNPLA3 inhibition on liver diseases. A: nonalcoholic fatty liver disease; B: fibrosis and cirrhosis of liver.

Figure s2. Leave-one-out analysis of PNPLA3 inhibition on liver diseases. A, nonalcoholic fatty liver disease; B, fibrosis and cirrhosis of liver.

Figure s3. Scatter plots for the effect of PNPLA3 inhibition on gout and urate. A, gout; B, idiopathic gout; C, urate.

Figure s4. Leave-one-out analysis of PNPLA3 inhibition on gout and urate. A, gout; B, idiopathic gout; C, urate.

Table s1. Information for instrumental variables to represent PNPLA3 inhibition.

Table s2. Sensitivity analysis of PNPLA3 inhibition on liver diseases.

Table s3. Sensitivity analysis of PNPLA3 inhibition on gout and urate.

Table s4. The effect of PNPLA3 inhibition on blood lipids.

Table s5. Sensitivity analysis of PNPLA3 inhibition on blood lipids.

Table s6. The effect of blood lipids on gout.

Table s7. Associations between PNPLA3 inhibition and gout mediated by blood TG.

References

  • 1.Riazi K., Azhari H., Charette J. H., et al. The Prevalence and Incidence of NAFLD Worldwide: A Systematic Review and Meta-Analysis. The Lancet Gastroenterology & Hepatology . 2022;7(9):851–861. doi: 10.1016/s2468-1253(22)00165-0. [DOI] [PubMed] [Google Scholar]
  • 2.Campos-Murguía A., Ruiz-Margáin A., González-Regueiro J. A., Macías-Rodríguez R. U. Clinical Assessment and Management of Liver Fibrosis in Non-Alcoholic Fatty Liver Disease. World Journal of Gastroenterology . 2020;26(39):5919–5943. doi: 10.3748/wjg.v26.i39.5919. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Cataldo I., Sarcognato S., Sacchi D., et al. Pathology of Non-Alcoholic Fatty Liver Disease. Pathologica . 2021;113(3):194–202. doi: 10.32074/1591-951x-242. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Anstee Q. M., Darlay R., Cockell S., et al. Genome-Wide Association Study of Non-Alcoholic Fatty Liver and Steatohepatitis in a Histologically Characterised Cohort. Journal of Hepatology . 2020;73(3):505–515. doi: 10.1016/j.jhep.2020.04.003. [DOI] [PubMed] [Google Scholar]
  • 5.Liu Y. L., Patman G. L., Leathart J. B., et al. Carriage of the PNPLA3 rs738409 C >G Polymorphism Confers an Increased Risk of Non-alcoholic Fatty Liver Disease Associated Hepatocellular Carcinoma. Journal of Hepatology . 2014;61(1):75–81. doi: 10.1016/j.jhep.2014.02.030. [DOI] [PubMed] [Google Scholar]
  • 6.BasuRay S., Smagris E., Cohen J. C., Hobbs H. H. The PNPLA3 Variant Associated with Fatty Liver Disease (I148M) Accumulates on Lipid Droplets by Evading Ubiquitylation. Hepatology . 2017;66(4):1111–1124. doi: 10.1002/hep.29273. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Josephine B. Arrowhead Pharmaceuticals Gains Full Rights to NASH Candidate ARO-PNPLA3 with Promising Phase 1 Results . Arrowhead Pharmaceuticals Inc; 2024. https://ir.arrowheadpharma.com/news-releases/news-release-details/arrowhead-pharmaceuticals-gains-full-rights-nash-candidate-aro . [Google Scholar]
  • 8.Dalbeth N., Gosling A. L., Gaffo A., Abhishek A. Gout. Lancet . 2021;397(10287):1843–1855. doi: 10.1016/s0140-6736(21)00569-9. [DOI] [PubMed] [Google Scholar]
  • 9.Li Y., Xu C., Yu C., Xu L., Miao M. Association of Serum Uric Acid Level with Non-Alcoholic Fatty Liver Disease: A Cross-Sectional Study. Journal of Hepatology . 2009;50(5):1029–1034. doi: 10.1016/j.jhep.2008.11.021. [DOI] [PubMed] [Google Scholar]
  • 10.Shih M. H., Lazo M., Liu S. H., Bonekamp S., Hernaez R., Clark J. M. Association Between Serum Uric Acid and Nonalcoholic Fatty Liver Disease in the US Population. Journal of the Formosan Medical Association . 2015;114(4):314–320. doi: 10.1016/j.jfma.2012.11.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Sirota J. C., McFann K., Targher G., Johnson R. J., Chonchol M., Jalal D. I. Elevated Serum Uric Acid Levels are Associated With Non-Alcoholic Fatty Liver Disease Independently of Metabolic Syndrome Features in the United States: Liver Ultrasound Data from the National Health and Nutrition Examination Survey. Metabolism . 2013;62(3):392–399. doi: 10.1016/j.metabol.2012.08.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Liu Z., Que S., Zhou L., Zheng S. Dose-Response Relationship of Serum Uric Acid with Metabolic Syndrome and Non-Alcoholic Fatty Liver Disease Incidence: a meta-analysis of Prospective Studies. Scientific Reports . 2015;5(1):p. 14325. doi: 10.1038/srep14325. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Li Q., Guo R., Wu Z., Zhao C., Shen C. Key Genes Linking Gut Microbiota, Immune Cells, and Osteoporosis: A Multi-Omics Approach. Microbial Pathogenesis . 2025;202:p. 107412. doi: 10.1016/j.micpath.2025.107412. [DOI] [PubMed] [Google Scholar]
  • 14.Liu Y., Basty N., Whitcher B., et al. Genetic Architecture of 11 Organ Traits Derived from Abdominal MRI Using Deep Learning. Elife . 2021;10:p. e65554. doi: 10.7554/elife.65554. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Kurki M. I., Karjalainen J., Palta P., et al. FINNGEN Provides Genetic in Sights from a well-phenotyped Isolated Population. Nature . 2023;613(7944):508–518. doi: 10.1038/s41586-022-05473-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Köttgen A., Albrecht E., Teumer A., et al. Genome-Wide Association Analyses Identify 18 New Loci Associated With Serum Urate Concentrations. Nature Genetics . 2013;45(2):145–154. doi: 10.1038/ng.2500. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Global Lipids Genetics Consortium, Schmidt E. M., Sengupta S., et al. Discovery and Refinement of Loci Associated with Lipid Levels. Nature Genetics . 2013;45(11):1274–1283. doi: 10.1038/ng.2797. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Richardson T. G., Sanderson E., Palmer T. M., et al. Evaluating the Relationship Between Circulating Lipoprotein Lipids and Apolipoproteins With Risk of Coronary Heart Disease: a Multivariable Mendelian Randomisation Analysis. PLoS Medicine . 2020;17(3):p. e1003062. doi: 10.1371/journal.pmed.1003062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Li Q., Guo R., Wu Z., Zhao C., Shen C. Uncovering Novel Metabolic and Inflammatory Pathways in Gout Using Mendelian Randomization. Postgraduate Medical Journal . 2025 May;:p. qgaf083. doi: 10.1093/postmj/qgaf083. [DOI] [PubMed] [Google Scholar]
  • 20.Byrne C. D., Targher G. NAFLD: a Multisystem Disease. Journal of Hepatology . 2015;62(1):S47–S64. doi: 10.1016/j.jhep.2014.12.012. [DOI] [PubMed] [Google Scholar]
  • 21.Namjou B., Lingren T., Huang Y., et al. GWAS and Enrichment Analyses of Non-alcoholic Fatty Liver Disease Identify New trait-associated Genes and Pathways Across Emerge Network. BMC Medicine . 2019;17(1):p. 135. doi: 10.1186/s12916-019-1364-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.James G., Reisberg S., Lepik K., et al. An Exploratory Phenome Wide Association Study Linking Asthma and Liver Disease Genetic Variants to Electronic Health Records From the Estonian Biobank. PLoS One . 2019;14(4):p. e0215026. doi: 10.1371/journal.pone.0215026. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Salari N., Darvishi N., Mansouri K., et al. Association Between PNPLA3 rs738409 Polymorphism and Nonalcoholic Fatty Liver Disease: A Systematic Review and meta-analysis. BMC Endocrine Disorders . 2021;21(1):p. 125. doi: 10.1186/s12902-021-00789-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Lindén D., Ahnmark A., Pingitore P., et al. Pnpla3 Silencing with Antisense Oligonucleotides Ameliorates Nonalcoholic Steatohepatitis and Fibrosis in Pnpla3 I148M Knock-in Mice. Molecular Metabolism . 2019;22:49–61. doi: 10.1016/j.molmet.2019.01.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Mantovani A., Targher G. PNPLA3 Variation and Kidney Disease. Liver International . 2025;45(3):p. e16010. doi: 10.1111/liv.16010. [DOI] [PubMed] [Google Scholar]
  • 26.Sun D. Q., Zheng K. I., Xu G., et al. PNPLA3 rs738409 is Associated with Renal Glomerular and Tubular Injury in NAFLD Patients with Persistently Normal ALT Levels. Liver International . 2020;40(1):107–119. doi: 10.1111/liv.14251. [DOI] [PubMed] [Google Scholar]
  • 27.Wang H. P., Xu Y. Y., Xu B. L., et al. Correlation Between Abdominal Fat Distribution and Serum Uric Acid in Patients Recently Diagnosed with Type 2 Diabetes. Diabetes, Metabolic Syndrome and Obesity . 2023;16:3751–3762. doi: 10.2147/dmso.s430235. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Ni Q., Lu X., Chen C., Du H., Zhang R. Risk Factors for the Development of Hyperuricemia: a STROBE-Compliant Cross-Sectional and Longitudinal Study. Medicine (Baltimore) . 2019;98(42):p. e17597. doi: 10.1097/md.0000000000017597. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Yu X., Wang T., Huang S., Zeng P. Evaluation of the Causal Effects of Blood Lipid Levels on Gout with Summary Level GWAS Data: Two-Sample Mendelian Randomization and Mediation Analysis. Journal of Human Genetics . 2021;66(5):465–473. doi: 10.1038/s10038-020-00863-0. [DOI] [PubMed] [Google Scholar]
  • 30.Paolini E., Longo M., Meroni M., et al. A Defective Circulating Mitochondrial Bioenergetics Profile Reflects the Hepatic One and Outlines Genetic MASLD. Antioxidants . 2025;14(6):p. 618. doi: 10.3390/antiox14060618. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Reid M. V., Fredickson G., Mashek D. G. Mechanisms Coupling Lipid Droplets to MASLD Pathophysiology. Hepatology . 2024 October; doi: 10.1097/hep.0000000000001141. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supporting Information

Additional supporting information can be found online in the Supporting Information section.

6664846.f1.docx (234.4KB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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