Causal relationship between birth weight, uric acid levels, and risk of gout: New insights from a bidirectional two-sample Mendelian randomization study

Bidirectional two-sample Mendelian randomization (MR) was used to evaluate the potential causal effects of birth weight and uric acid levels (the exposures) and the development of gout (the outcome). Genetic instruments derived from aggregated genome-wide association study data of European ancestry were used to investigate the associations between birth weight (261,932 samples, 9,851,867 single-nucleotide polymorphisms [SNPs]), uric acid levels (110,347 samples, 4,865,122 SNPs), and gout (337,159 samples, including 4807 cases and 332,352 controls, 10,894,596 SNPs). The inverse variance weighting method was used for primary causal estimates, and a series of sensitivity analyses were performed to assess the robustness of the results. The study found that birth weight was negatively associated with uric acid levels (odds ratio [OR] = 0.849; 95% confidence interval [CI]: 0.786–0.917; P < .001) and correspondingly had a negative impact on gout risk (OR = 0.997; 95% CI: 0.994–0.9997; P = .032). In reverse MR analyses, genetic liability for gout was strongly associated with lower birth weight (OR = 0.380; 95% CI: 0.222–0.650; P < .001). This indicates that individuals with a higher genetic predisposition to gout have 62% lower odds of having a higher birth weight. However, the reverse MR analysis of birth weight and uric acid levels was influenced by horizontal pleiotropy and could not provide additional scientific insights. Genetically predicted higher birth weight demonstrated a protective causal effect on serum urate levels. Specifically, each 1-standard deviation increase in birth weight was associated with a 15.1% reduction in the odds of hyperuricemia (OR = 0.849; 95% CI: 0.786–0.917; P < .001). This causal estimate was robust across sensitivity analyses, including the weighted median and MR-Egger methods, with no evidence of directional pleiotropy (Egger intercept P > .05). Leave-one-out analysis confirmed that the results were not driven by any single influential genetic variant.