Gout and Metabolic Disease: Investigation of Potential Relationship in the New Zealand Population

Hyperuricaemia, pathologically defined as the presence of higher levels of serum urate, results from a compromise in the delicate balance between the production and excretion of urate primarily in the liver and the kidneys, respectively. Hyperuricaemia is a prerequisite for gout, a painful inflammatory arthritis. The symptoms of gout arise from the body’s immune response to monosodium urate crystals that accumulate in the synovial fluid of the joints. Hyperuricaemia and gout are complex traits. A number of genetic loci confer risk to develop hyperuricaemia. Genome-wide association studies (GWAS), an indispensable tool in population genetics, has identified at least twenty eight genomic loci that contain variants affecting serum urate concentration. Gene-environment interactions also play a significant role in this context. Exogenous factors such as the intake of purine-rich foods increase the frequency of gout flares. Population-specific genetic effects on gout are as evident, if not more, as for other complex phenotypes. The prevalence of gout is much higher in the New Zealand Polynesian population compared to other populations. Approximately 7% of New Zealand Māori and Pacific Island people and 3% of New Zealand Europeans are affected by gout. The coexistence of metabolic conditions with gout, usually called gout-comorbidities, adds another level of complexity. However, not many studies have attempted to address the causal relationship between these traits. In fact, my research project was instigated as an attempt to study the causal associations between gout and its comorbidities and fill in some gap in the scientific literature. The research was, however, limited to three metabolic conditions/comorbidities of gout – imbalanced iron homeostasis, metabolic syndrome and disrupted lipid metabolism. My study shows an association between increased serum ferritin and the risk of gout and seeded an idea that the consumption of iron-rich diet may play a role in increasing the frequency and severity of gout flares. Genetic association analysis using two variants in the HFE gene was done to confirm the association between ferritin and urate, which showed positive association in a smaller dataset and provoked the idea to investigate the causality, if it exists, between gout and iron metabolism. Using the robust ‘Two-sample Mendelian randomisation’ approach and exploiting summary statistics data from two large GWA studies, I was able to find an evidence of a causal effect of iron on urate metabolism, but not urate on iron metabolism. In the context of the metabolic syndrome, the role of variants within/near the ADRB3, MC3R, MC4R and ADTRP genes were investigated. The positive effects identified for these variants supported the possible involvement of obesity and insulin resistance-related genes in gout pathophysiology. With the help of gene sequencing-based rare variant analyses, several novel population-specific association signals were found within the coding regions of two lipid-related genes, LRP2 and A1CF. Polynesian-specific novel genetic effects were identified to be predictive for gout for common variants within the LRP2 gene. Rare variants within the LRP2 gene were also identified and a higher prevalence of non-synonymous polymorphisms that can increase the risk of hyperuricaemia was observed in European individuals compared to Polynesians. These results indicated LRP2 to contribute to the difference in gout prevalence between Māori and Pacific Island individuals compared to the New Zealand European population. Collectively, my study reports a causal role of iron and ferritin in increasing serum urate concentration and the involvement of imbalanced iron homeostasis in hyperuricaemia. Also, positive genetic associations indicated that genes contributing to metabolic syndrome and lipid metabolism can increase the risk of gout, and also have population-specific effects for the Polynesian and European ancestral groups in New Zealand

The absolute risk of gout by clusters of gout-associated comorbidities and lifestyle factors—30 years follow-up of the Malmö Preventive Project

Background: Gout is predicted by a number of comorbidities and lifestyle factors. We aimed to identify discrete phenotype clusters of these factors in a Swedish population-based health survey. In these clusters, we calculated and compared the incidence and relative risk of gout. Methods: Cluster analyses were performed to group variables with close proximity and to obtain homogenous clusters of individuals (n = 22,057) in the Malmö Preventive Project (MPP) cohort. Variables clustered included obesity, kidney dysfunction, diabetes mellitus (DM), hypertension, cardiovascular disease (CVD), dyslipidemia, pulmonary dysfunction (PD), smoking, and the use of diuretics. Incidence rates and hazard ratios (HRs) for gout, adjusted for age and sex, were computed for each cluster. Results: Five clusters (C1–C5) were identified. Cluster C1 (n = 16,063) was characterized by few comorbidities. All participants in C2 (n = 750) had kidney dysfunction (100%), and none had CVD. In C3 (n = 528), 100% had CVD and most participants were smokers (74%). C4 (n = 3673) had the greatest fractions of obesity (34%) and dyslipidemia (74%). In C5 (n = 1043), proportions with DM (51%), hypertension (54%), and diuretics (52%) were highest. C1 was by far the most common in the population (73%), followed by C4 (17%). These two pathways included 86% of incident gout cases. The four smaller clusters (C2–C5) had higher incidence rates and a 2- to 3-fold increased risk for incident gout. Conclusions: Five distinct clusters based on gout-related comorbidities and lifestyle factors were identified. Most incident gout cases occurred in the cluster of few comorbidities, and the four comorbidity pathways had overall a modest influence on the incidence of gout

Association between serum urate and CSF markers of Alzheimer's disease pathology in a population-based sample of 70-year-olds

Introduction: The relationship between urate and biomarkers for Alzheimer's disease (AD) pathophysiology has not been investigated. Methods: We examined whether serum concentration of urate was associated with cerebrospinal fluid biomarkers, amyloid beta (Aβ)42, Aβ40, phosphorylated tau (p-tau), total tau (t-tau), neurofilament light (NfL), and Aβ42/Aβ40 ratio, in cognitively unimpaired 70-year-old individuals from Gothenburg, Sweden. We also evaluated whether possible associations were modulated by the apolipoprotein E (APOE) ε4 allele. Results: Serum urate was positively associated with Aβ42 in males (β = 0.55 pg/mL, P =.04). There was a positive urate–APOE ε4 interaction (1.24 pg/mL, Pinteraction =.02) in relation to Aβ42 association. The positive urate and Aβ42 association strengthened in male APOE ε4 carriers (β = 1.28 pg/mL, P =.01). Discussion: The positive association between urate and Aβ42 in cognitively healthy men may suggest a protective effect of urate against deposition of amyloid protein in the brain parenchyma, and in the longer term, maybe against AD dementia

Additional file 2: of Mediation analysis to understand genetic relationships between habitual coffee intake and gout

Table S1. Coding of food-frequency intakes for analysis. (DOC 40 kb

Additional file 4: of Mediation analysis to understand genetic relationships between habitual coffee intake and gout

Table S2. Complete dietary information for the study population. (DOCX 16 kb

Additional file 1: of Mediation analysis to understand genetic relationships between habitual coffee intake and gout

Figure S1. Regional association plots of genome-wide significant urate and habitual coffee loci. In each panel, SNPs identified as associated with both urate [2] and coffee intake [22] are plotted with their –log10 (P values) as a function of genomic position using HG build 19 and 1000 genomes European reference for LD (November 2014). Each SNP is coloured according to its correlation with the index SNP (demonstrating the lowest P value within the region, labelled in purple) according to a scale from r2 = 0 to r2 = 1. Urate-raising alleles are displayed on the left and coffee-associated alleles are on the right. LocusZoom plots were drawn from publicly available data ex [2] and taken from [22]. GCKR rs2911711 is in complete linkage disequilibrium with rs1260326. (PDF 826 kb

Additional file 6: of Mediation analysis to understand genetic relationships between habitual coffee intake and gout

Table S4. Association analysis of genotype with habitual coffee intake. (DOC 54 kb

Additional file 5: of Mediation analysis to understand genetic relationships between habitual coffee intake and gout

Table S3. Association analysis of genotype with gout risk. (DOC 57 kb

N-Acetyl Cysteine, Selenium, and Ascorbic Acid Rescue Diabetic Cardiac Hypertrophy via Mitochondrial-Associated Redox Regulators

Metabolic disorders often lead to cardiac complications. Metabolic deregulations during diabetic conditions are linked to mitochondrial dysfunctions, which are the key contributing factors in cardiac hypertrophy. However, the underlying mechanisms involved in diabetes-induced cardiac hypertrophy are poorly understood. In the current study, we initially established a diabetic rat model by alloxan-administration, which was validated by peripheral glucose measurement. Diabetic rats displayed myocardial stiffness and fibrosis, changes in heart weight/body weight, heart weight/tibia length ratios, and enhanced size of myocytes, which altogether demonstrated the establishment of diabetic cardiac hypertrophy (DCH). Furthermore, we examined the expression of genes associated with mitochondrial signaling impairment. Our data show that the expression of PGC-1α, cytochrome c, MFN-2, and Drp-1 was deregulated. Mitochondrial-signaling impairment was further validated by redox-system dysregulation, which showed a significant increase in ROS and thiobarbituric acid reactive substances, both in serum and heart tissue, whereas the superoxide dismutase, catalase, and glutathione levels were decreased. Additionally, the expression levels of pro-apoptotic gene PUMA and stress marker GATA-4 genes were elevated, whereas ARC, PPARα, and Bcl-2 expression levels were decreased in the heart tissues of diabetic rats. Importantly, these alloxan-induced impairments were rescued by N-acetyl cysteine, ascorbic acid, and selenium treatment. This was demonstrated by the amelioration of myocardial stiffness, fibrosis, mitochondrial gene expression, lipid profile, restoration of myocyte size, reduced oxidative stress, and the activation of enzymes associated with antioxidant activities. Altogether, these data indicate that the improvement of mitochondrial dysfunction by protective agents such as N-acetyl cysteine, selenium, and ascorbic acid could rescue diabetes-associated cardiac complications, including DCH