Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.
Chronic kidney disease (CKD) is a significant public health problem, and recent genetic studies have identified common CKD susceptibility variants. The CKDGen consortium performed a meta-analysis of genome-wide association data in 67,093 Caucasian individuals from 20 population-based studies to identify new susceptibility loci for reduced renal function, estimated by serum creatinine (eGFRcrea), cystatin C (eGFRcys), and CKD (eGFRcrea <60 ml/min/1.73m2; n = 5,807 CKD cases). Follow-up of the 23 genome-wide significant loci (p<5×10−8) in 22,982 replication samples identified 13 novel loci for renal function and CKD (in or near LASS2, GCKR, ALMS1, TFDP2, DAB2, SLC34A1, VEGFA, PRKAG2, PIP5K1B, ATXN2, DACH1, UBE2Q2, and SLC7A9) and 7 creatinine production and secretion loci (CPS1, SLC22A2, TMEM60, WDR37, SLC6A13, WDR72, BCAS3). These results further our understanding of biologic mechanisms of kidney function by identifying loci potentially influencing nephrogenesis, podocyte function, angiogenesis, solute transport, and metabolic functions of the kidney.
Chronic kidney disease (CKD), impairment of kidney function, is a serious public health problem, and the assessment of genetic factors influencing kidney function has substantial clinical relevance. Here, we report a meta-analysis of genome-wide association studies for kidney function–related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN). Our meta-analysis identified 17 loci newly associated with kidney function–related traits, including the concentrations of blood urea nitrogen, uric acid and serum creatinine and estimated glomerular filtration rate based on serum creatinine levels (eGFRcrea) (P < 5.0 × 10−8). We further examined these loci with in silico replication in individuals of European ancestry from the KidneyGen, CKDGen and GUGC consortia, including a combined total of ~110,347 individuals. We identify pleiotropic associations among these loci with kidney function–related traits and risk of CKD. These findings provide new insights into the genetics of kidney function.
In conclusion, changes in absolute and relative RMR in response to ST are influenced by gender but not age. In contrast to what has been suggested previously, changes in body composition in response to ST are not due to changes in physical activity outside of training.
Background and Purpose-The timely diagnosis of stroke at the initial examination is extremely important given the disease morbidity and narrow time window for intervention. The goal of this study was to develop a supervised learning method to recognize acute cerebral ischemia (ACI) and differentiate that from stroke mimics in an emergency setting. Methods-Consecutive patients presenting to the emergency department with stroke-like symptoms, within 4.5 hours of symptoms onset, in 2 tertiary care stroke centers were randomized for inclusion in the model. We developed an artificial neural network (ANN) model. The learning algorithm was based on backpropagation. To validate the model, we used a 10-fold cross-validation method. Results-A total of 260 patients (equal number of stroke mimics and ACIs) were enrolled for the development and validation of our ANN model. Our analysis indicated that the average sensitivity and specificity of ANN for the diagnosis of ACI based on the 10-fold cross-validation analysis was 80.0% (95% confidence interval, 71.8-86.3) and 86.2% (95% confidence interval, 78.7-91.4), respectively. The median precision of ANN for the diagnosis of ACI was 92% (95% confidence interval, 88.7-95.3). Conclusions-Our results show that ANN can be an effective tool for the recognition of ACI and differentiation of ACI from stroke mimics at the initial examination.
A comparison of salivary flow rates was made between three groups of female individuals according to their menopausal status. The three groups consisted of healthy, dentate, nonmedicated women (with the exception of the use of estrogen) from the Baltimore Longitudinal Study of Aging. One group consisted of premenopausal women (n = 51), their mean age was 39 years. Another group (n = 26) was perimenopausal with a mean age of 48 years. A third group (n = 76) was postmenopausal with a mean age of 69 years. The groups were evaluated for unstimulated (UPAR) and stimulated parotid gland flow rates (SPAR), unstimulated (USUB) and stimulated submandibular/sublingual gland flow rates (SSUB), and stimulated whole-saliva flow rates (SWHOLE). The parotid flow rates were determined using a Carlson-Crittenden cup, while the submandibular/sublingual flow rates were determined using the National Institute of Dental Research collector. A 2% citrate solution was used for stimulation in glandular collections. Chewing a 1-cm3 cube of paraffin was used to stimulate whole saliva. The results showed no significant differences in UPAR, SPAR, and SWHOLE between the three groups. However, the premenopausal women had higher USUB than the postmenopausal group. The premenopausal women also had higher SSUB than perimenopausal and postmenopausal groups. There were no differences in salivary flow rates between those taking estrogen and those that were not medicated.
We studied the association between impaired glucose tolerance in midlife (IGT) and subsequent changes in longitudinal brain function by measuring resting state cerebral blood flow (rCBF) in cognitively normal older individuals. We investigated whether individuals with IGT in midlife subsequently show regionally specific longitudinal changes in rCBF relative to those with normal glucose tolerance (NGT). 64 cognitively normal participants in the neuroimaging substudy of the Baltimore Longitudinal Study of Aging (BLSA) underwent serial 15O-water positron emission tomography (15O-water PET) (age at first PET; 69.6±7.5 years) and serial oral glucose tolerance tests (OGTT) 12 years earlier (age at first OGTT; 57.2±11.1 years). Using voxel-based analysis, we compared changes in rCBF over an 8-year period between 15 participants with IGT in midlife and 49 with NGT. Significant differences were observed in longitudinal change in rCBF between the IGT and NGT groups. The predominant pattern was greater rCBF decline in the IGT group. These differences were observed in the frontal, parietal, and temporal cortices. In some of these regions, the observed changes appear to be related to increased midlife body mass index in the IGT group. Some brain regions in the frontal and temporal cortices also showed greater longitudinal increments in rCBF in the IGT group. There were no significant differences in trajectories of cognitive performance between the two groups. Our findings suggest that impaired glucose tolerance in midlife is associated with subsequent longitudinal changes in brain function during aging even in cognitively normal older individuals. These findings complement the growing evidence linking glucose dyshomeostasis with early changes in brain function in individuals at increased risk for Alzheimer’s disease and age-related cognitive decline.
We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.