A total of 385,917 unrelated European individuals were included in the current study, containing 177,690 (46.0%) men and 208,227 (54.0%) women. The mean age of the population was 56.7 ± 8.0 years (SD) and the mean levels of urate were 5.2 ± 1.4 milligrams per deciliter. More details regarding socio-demographic information, lifestyle factors and biomarker levels, are presented in Table 1.
Table 1 Baseline characteristics of participants in the UK BiobankPhenome-wide associationsIn total 1,055 health and mortality-related [all-cause mortality and disease-specific mortality (e.g. circulatory disease, endocrine/metabolic disease, respiratory disease, digestive disease, genitourinary disease, neoplasm, mental disorder, neurological disease, hematopoietic disease, dermatologic disease and musculoskeletal disease) outcomes were included in the PheWAS. In Obs-PheWAS, uric acid levels were significantly associated with 397 phenotypes after FDR correction (2). In PRS-PheWAS, genetically predicted uric acid levels were related to the risk of 53 medical conditions (Supplementary Table 3). A total of 41 overlapping disease outcomes with consistent effect directions were identified by both methods (Fig. 2, Supplementary Table 4), including 17 circulatory diseases (e.g. essential hypertension), 7 endocrine/metabolic diseases (e.g. gout), 7 genitourinary diseases (e.g. chronic renal failure), 2 musculoskeletal diseases (e.g. polymyalgia rheumatica), 2 digestive diseases (e.g. celiac disease), 2 infectious diseases (e.g. tuberculosis), 1 respiratory disease (pneumonia), 1 hematopoietic disease (anemia) and 1 neoplasm (benign neoplasm of digestive system). Furthermore, higher uric acid levels were significantly related to increased risk in circulatory-specific mortality. For the observed linear associations, we also explored the co-existence of non-linear relationships by using a restricted cubic spline (RCS) function [23] with five knots located at the 5th, 25th, 50th, 75th, and 95th percentiles of genetically predicted uric acid levels. The results revealed that the associations of uric acid levels with gout, celiac disease and benign neoplasm of digestive system displayed not only a basic overall linear trend, but also a more complcated non-linear relationship. Detailed information about the effect estimates can be found in Supplementary Table 4.
Fig. 2Overlapping significant phenotypes identified by both observational- and PRS-based PheWASs
In addition, sex-stratified analysis was conducted to examine differences between male and female subgroups. The results showed that the majority of the effect estimates were consistent across sex with a heterogeneity P < 0.05, except for cerebral artery occlusion and pyogenic arthritis. The association between high uric acid levels and increased risk of cerebral artery occlusion remains significant exclusively among women (N = 2033, OR = 1.25, 95%CI: 1.12, 1.40, P = 4.24 × 10− 5) but not men (N = 3117, OR = 1.05, 95%CI: 0.96, 1.15, P = 0.259). While males with high uric acid levels are prone to develop pyogenic arthritis (N = 388, OR = 1.82, 95%CI: 1.43, 2.33, P = 1.55 × 10− 6) instead of females (N = 226, OR = 0.87, 95%CI: 0.63, 1.20, P = 0.385) (Supplementary Table 5). We also examined the effects of uric acid on the risk of associated kidney diseases both within general population and male and female subgroups, and found that high uric acid levels were significantly related to increased risk of kidney outcomes, particularly among participants with lower eGFR levels. However, no considerable heterogeneous effects were identified between the low-level and high-level eGFR groups, indicating the absence of interaction (Supplementary Table 6).
Disease trajectories following elevated uric acid levelsAmong a total of 595 possible disease pairs established for 35 unique health outcomes that were at an increased risk with elevated uric acid levels, 90 were retained based on the selection criteria in step 1. Then, step 2 identified 43 significant D1→D2 pairs with clear temporal orders. Step 3 estimated the effect size of developing D2 after diagnosed with D1 and all 43 pairs survived in the multiple correction test. We categorized these disease pairs according to the similarity of their underlying affected systems or their etiologies. As a result, one cluster mainly including diseases of cardiometabolic system was identified, where the disease tree thrived after the diagnoses of obesity, type 2 diabetes, hypercholesterolemia, [24] essential hypertension, coronary atherosclerosis and myocardial infarction, followed by anemia, pneumonia, heart failure, renal failure, and finally ended up on death (Fig. 3). Details regarding the number of disease pairs remaining at each step and the effect estimates are shown in Supplementary Fig. 2 and Supplementary Table 7.
Fig. 3Disease progression patterns subsequent to elevated uric acid levels
Repurposing of uric acid-lowering drugsThe uric acid-lowering drugs as well as their target genes were shown in Supplementary Table 8. A total of 35, 87 and 50 genetic variants were selected as instruments to proxy the effects of xanthine oxidase inhibitors (XOIs), uricosuric drugs targeting gene SLC22A12, and purine nucleoside phosphorylase (PNP) inhibitors, respectively Supplementary Table 8). As expected, uric acid-lowering drug proxies were associated with a reduced risk of gout and/or gouty arthropathy, which serves as a positive control for the selected genetic instruments (Fig. 4). XOIs were uniquely inversely associated with type 2 diabetes (OR = 0.80, 95%CI: 0.66, 0.98, P = 0.030), obesity (OR = 0.74, 95%CI: 0.61, 0.90, P = 0.003), congestive heart failure (OR = 0.64, 95%CI: 0.42, 0.99, P = 0.043), peripheral vascular disease (OR = 0.60, 95%CI: 0.38, 0.94, P = 0.025), and acute renal failure (OR = 0.75, 95%CI: 0.58, 0.97, P = 0.027). Uricosuric drugs targeting the SLC22A12 gene were associated with a reduced risk of tuberculosis (OR = 0.96, 95%CI: 0.93, 1.00, P = 0.032), hypothyroidism (OR = 0.96, 95%CI: 0.93, 1.00, P = 0.029), hypercholesterolemia (OR = 0.96, 95%CI: 0.94, 0.99, P = 0.004), coronary atherosclerosis (OR = 0.96, 95%CI: 0.93, 1.00, P = 0.047) and occlusion of cerebral arteries (OR = 0.93, 95%CI: 0.87, 1.00, P = 0.044). We did not identify any additional therapeutic effects for PNP inhibitors (Fig. 4). The effect estimates for all of the PheWAS-identified outcomes are displayed in Supplementary Table 10.
Fig. 4Effect of genetically predicted uric acid-lowering therapy on the risk of associated disease outcomes identified by PheWAS
To evaluate the joint effect of combination therapy aimed at lowering both uric acid levels and blood pressure on cardiovascular risk, we performed factorial MR analysis. The genetic instruments for antihypertensive drugs were extracted from previously publications [25, 26]. More details were presented in Supplementary Table 11. Compared to the reference group with genetically predicted higher levels of uric acid and higher blood pressure, the risk of coronary atherosclerosis, congestive heart failure, occlusion of cerebral arteries and peripheral vascular disease was lower in the group with genetically predicted lower levels of uric acid and blood pressure (Fig. 5). Especially in combination therapy integrating XOIs with calcium channel blockers (CCBs), genetically predicted lower levels of uric acid and blood pressure was associated with a 6% lower coronary atherosclerosis risk (OR = 0.94, 95%CI: 0.91, 0.97, P < 0.001), a 8% lower congestive heart failure risk (OR = 0.92, 95%CI: 0.86, 0.99, P = 0.023), a 8% lower occlusion of cerebral arteries risk (OR = 0.92, 95%CI: 0.86, 0.98, P = 0.011) and a 10% lower peripheral vascular disease risk (OR = 0.90, 95%CI: 0.84, 0.97, P = 0.004) (Supplementary Table 12).
Fig. 5Joint effect of combination therapy integrating XDH inhibitors and antihypertensive drugs on the risk of cardiovascular outcomes. CAO, occlusion of cerebral arteries; HF, heart failure; PVD, peripheral vascular disease
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