The role of diet in serum urate concentration

Watson, Lorraine; Roddy, Edward

doi:10.1136/bmj.k4140

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…These findings were further replicated by meta‐analyzing 3 separate cohorts of women of European ancestry. Our prospective findings shed light on longstanding debates about the comparative contributions of genetics and diet toward serum urate levels and gout risk cross‐sectionally (i.e., nature versus nurture) (22,23,46), by elucidating the important synergy of genetic predisposition and diet in combination (i.e., nature and nurture) for the development of female gout.…”

Section: Discussionmentioning

confidence: 78%

Interactions Between Genetic Risk and Diet Influencing Risk of Incident Female Gout: Discovery and Replication Analysis of Four Prospective Cohorts

Lin

McCormick

Yokose

et al. 2023

Arthritis & Rheumatology

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To examine whether the cross-sectional gene-diet interaction for prevalent hyperuricemia among women translates prospectively to risk of incident female gout.Methods. We analyzed the interaction between genetic predisposition and adherence to a healthy dietary pattern (i.e., Dietary Approaches to Stop Hypertension [DASH] score) on risk of incident female gout in 18,244 women from Nurses' Health Study (NHS; discovery) and 136,786 women from 3 additional prospective female cohorts from the US and UK (replication). Genetic risk score (GRS) was calculated from 114 urate-associated loci.Results. In the NHS and replication cohorts, association between diet and gout risk was larger and stronger among women with higher genetic risk. In all cohorts combined, compared to women with an unhealthy DASH score (less than the mean score), multivariable relative risk (RR) for incident gout among women with a healthy DASH score (greater than/equal to the mean score) was 0.67 (95% confidence interval [95% CI] 0.60-0.76) among higher GRS (greater than/ equal to the mean score) and 0.91 (0.78-1.05) among lower GRS (P for multiplicative interaction = 0.001); multivariable RR for higher versus lower GRS was 2.03 (95% CI 1.80-2.29) and 1.50 (95% CI 1.31-1.71) among unhealthy and healthy DASH score groups, respectively. Additive interaction was also significant, in both the discovery and replication cohorts (P < 0.001), with 51% of the excess risk attributable to the additive gene-diet interaction in all cohorts combined.Conclusion. The deleterious effect of genetic predisposition on risk of incident female gout was more pronounced among women with unhealthy diets, with nearly half the excess risk attributable to this gene-diet interaction. These data elucidate the important synergy of genetics and diet for female gout development.

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Section: Discussionmentioning

confidence: 78%

Interactions Between Genetic Risk and Diet Influencing Risk of Incident Female Gout: Discovery and Replication Analysis of Four Prospective Cohorts

Lin

McCormick

Yokose

et al. 2023

Arthritis & Rheumatology

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“…Granting that, the intake of fructose is just one confounding factor that could affect the concentration of serum UA ( 47 ). As a southeast coastal region, many other relevant factors such as excessive consumption of meat, seafood, and sugar-sweetened soft drinks ( 48 ), and even the single-nucleotide polymorphisms ( 49 ) in urate exchange gene, are possibly disparate in our geographic region. Although the microbes belonging to the genus Streptococcus have been implicated in the development of various metabolic disorders ( 50 ), the link between fructose intake and the entire genus Streptococcus has not been explored.…”

Section: Discussionmentioning

confidence: 99%

Altered Gut Microbiota in Children With Hyperuricemia

et al. 2022

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BackgroundIn adults, gut dysbiosis may contribute to the pathogenesis of gout. However, the characteristics of gut microbiota in children with hyperuricemia (HUA) in the absence of clinical gout have not been explored.ObjectiveThis present study analyzed the gut microbiota in children with HUA as compared to controls (Con) and explored bacterial associations that may account for differences.MethodsA total of 80 children were enrolled in this study; they were divided into HUA and Con according to the level of serum uric acid (UA). The composition of gut microbiota was investigated by 16S rRNA high-throughput sequencing.ResultsPrincipal coordinate analysis revealed that gut microbiota of the HUA group was clustered together and separated partly from the Con group. There was no difference in alpha-diversity between the two groups. However, Spearman’s correlation analysis revealed that serum UA level positively correlated with genera Actinomyces, Morganella, and Streptococcus, and negatively associated with the producers of short-chain fatty acids (SCFAs), such as Alistipes, Faecalibacterium, and Oscillospira, and the sulfidogenic bacteria Bilophila. The members of the genera Alistipes and Bilophila in the Con group were significantly more prevalent than the HUA subjects. Compared to the Con cohort, metabolic pathway predictions found that the superpathways of purine nucleotide de novo biosynthesis were decreased in HUA subjects, whereas the superpathway of purine deoxyribonucleoside de gradation was increased.ConclusionThe composition of the gut microbiota in children with HUA differs from Con. Although causality cannot be established, modification in the microbiota that produces SCFA and sulfide may promote HUA.

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“…Not the reverse, as is the case with a health condition like gout, where there is genetic variance in urate handling (the greatest risk for development of the disease). 31,32 Medsafe must also classify medicines according to the level of access deemed appropriate: general sales, prescription, pharmacy only, or restricted access (eg where pharmacist input is required).…”

Section: The Inequitable Legislative Context and Its Consequencesmentioning

confidence: 99%