174 research outputs found

    Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis

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    Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10-8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10-11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry. © 2013 Cui et al

    Case-Control Analysis of SNPs in GLUT4, RBP4 and STRA6: Association of SNPs in STRA6 with Type 2 Diabetes in a South Indian Population

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    BACKGROUND: The inverse relationship between GLUT4 and RBP4 expression is known to play a role in the pathogenesis of type 2 diabetes. Elevated levels of RBP4 were shown to cause insulin resistance in muscles and liver. Identification of STRA6 as a cell surface receptor for RBP4 provides further link in this axis and hence we analyzed SNPs in these three genes for association with type 2 diabetes in a South Indian population. METHODOLOGY/PRINCIPAL FINDINGS: Selected SNPs in the three genes were analyzed in a total of 2002 individuals belonging to Dravidian ethnicity, South India, by Tetra Primer ARMS PCR or RFLP PCR. Allele frequencies and genotype distribution were calculated in cases and controls and were analyzed for association by Chi-squared test and Logistic regression. Haplotype analysis was carried out for each gene by including all the markers in a single block. We observed a significant association of three SNPs, rs974456, rs736118, and rs4886578 in STRA6 with type 2 diabetes (P = 0.001, OR 0.79[0.69-0.91], P = 0.003, OR 0.81[0.71-0.93], and P = 0.001, OR 0.74[0.62-0.89] respectively). None of the SNPs in RBP4 and GLUT4 showed any association with type 2 diabetes. Haplotype analysis revealed that two common haplotypes H1 (111, P = 0.001, OR 1.23[1.08-1.40]) and H2 (222, P = 0.002 OR 0.73[0.59-0.89]) in STRA6, H6 (2121, P = 0.006, OR 1.69[1.51-2.48]) in RBP4 and H4 (2121, P = 0.01 OR 1.41[1.07-1.85]) in GLUT4 were associated with type 2 diabetes. CONCLUSION: SNPs in STRA6, gene coding the cell surface receptor for RBP4, were significantly associated with type 2 diabetes and further genetic and functional studies are required to understand and ascertain its role in the manifestation of type 2 diabetes

    Dietary inflammatory index and inflammatory biomarkers in adolescents from LabMed physical activity study

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    Background/objectives The dietary inflammatory index (DII) is a tool to measure the diet’s inflammatory potential and has been used with adults to predict low-grade inflammation. The present study aims to assess whether this dietary score predicts low-grade inflammation in adolescents. Subjects/methods The sample comprises 329 adolescents (55.9% girls), aged 12–18 years, from LabMed Physical Activity Study. DII score was calculated based on a food-frequency questionnaire and categorized into tertiles. We collected blood samples to determine the follow inflammatory biomarkers: C-reactive protein (CRP), interleukin-6 (IL-6), complement component 3 (C3), and 4 (C4). In addition we calculated an overall inflammatory biomarker score. Odds ratios (OR) and 95% confidence intervals (95%CI) were computed from binary logistic regression models. Results DII score, comparing first with third tertile, was positively associated with IL-6 in crude model (OR = 1.88, 95% CI:1.09–3.24, ptrend = 0.011) and in fully adjusted (for biological and lifestyle variables) (OR = 3.38, 95%CI:1.24–9.20, ptrend = 0.023). Also, DII score was positively associated with C4, when fully adjusted (OR = 3.12, 95%CI:1.21–8.10, ptrend = 0.016). DII score was negatively associated with C3 in crude model, comparing first with second but not with third tertile, and no significant associations in fully adjusted model were observed, although a trend was found (OR = 1.71, 95% CI:0.63–4.66, ptrend = 0.044). No significant associations were observed between DII score and CRP. However, DII score was positively associated with the overall inflammatory biomarker score, when fully adjusted (OR = 5.61, 95% CI:2.00–15.78, ptrend = 0.002). Conclusions DII score can be useful to assess the diet’s inflammatory potential and its association with low-grade inflammation in adolescents.The authors gratefully acknowledged the participation of all adolescents and their parents, teachers and schools of the LabMed and Physical Activity Study, the cooperation of volunteer’s, the Department of Hygiene and Epidemiology (University of Porto) for the conversion food frequency questionnaire data into nutrients, and the Research Centre in Physical Activity, Health and Leisure (University of Porto) for the sponsoring the LabMed and Physical Activity Study.info:eu-repo/semantics/publishedVersio

    Vitamin A Metabolism: An Update

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    Retinoids are required for maintaining many essential physiological processes in the body, including normal growth and development, normal vision, a healthy immune system, normal reproduction, and healthy skin and barrier functions. In excess of 500 genes are thought to be regulated by retinoic acid. 11-cis-retinal serves as the visual chromophore in vision. The body must acquire retinoid from the diet in order to maintain these essential physiological processes. Retinoid metabolism is complex and involves many different retinoid forms, including retinyl esters, retinol, retinal, retinoic acid and oxidized and conjugated metabolites of both retinol and retinoic acid. In addition, retinoid metabolism involves many carrier proteins and enzymes that are specific to retinoid metabolism, as well as other proteins which may be involved in mediating also triglyceride and/or cholesterol metabolism. This review will focus on recent advances for understanding retinoid metabolism that have taken place in the last ten to fifteen years

    Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults.

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    BACKGROUND: Underweight, overweight, and obesity in childhood and adolescence are associated with adverse health consequences throughout the life-course. Our aim was to estimate worldwide trends in mean body-mass index (BMI) and a comprehensive set of BMI categories that cover underweight to obesity in children and adolescents, and to compare trends with those of adults. METHODS: We pooled 2416 population-based studies with measurements of height and weight on 128·9 million participants aged 5 years and older, including 31·5 million aged 5-19 years. We used a Bayesian hierarchical model to estimate trends from 1975 to 2016 in 200 countries for mean BMI and for prevalence of BMI in the following categories for children and adolescents aged 5-19 years: more than 2 SD below the median of the WHO growth reference for children and adolescents (referred to as moderate and severe underweight hereafter), 2 SD to more than 1 SD below the median (mild underweight), 1 SD below the median to 1 SD above the median (healthy weight), more than 1 SD to 2 SD above the median (overweight but not obese), and more than 2 SD above the median (obesity). FINDINGS: Regional change in age-standardised mean BMI in girls from 1975 to 2016 ranged from virtually no change (-0·01 kg/m2 per decade; 95% credible interval -0·42 to 0·39, posterior probability [PP] of the observed decrease being a true decrease=0·5098) in eastern Europe to an increase of 1·00 kg/m2 per decade (0·69-1·35, PP>0·9999) in central Latin America and an increase of 0·95 kg/m2 per decade (0·64-1·25, PP>0·9999) in Polynesia and Micronesia. The range for boys was from a non-significant increase of 0·09 kg/m2 per decade (-0·33 to 0·49, PP=0·6926) in eastern Europe to an increase of 0·77 kg/m2 per decade (0·50-1·06, PP>0·9999) in Polynesia and Micronesia. Trends in mean BMI have recently flattened in northwestern Europe and the high-income English-speaking and Asia-Pacific regions for both sexes, southwestern Europe for boys, and central and Andean Latin America for girls. By contrast, the rise in BMI has accelerated in east and south Asia for both sexes, and southeast Asia for boys. Global age-standardised prevalence of obesity increased from 0·7% (0·4-1·2) in 1975 to 5·6% (4·8-6·5) in 2016 in girls, and from 0·9% (0·5-1·3) in 1975 to 7·8% (6·7-9·1) in 2016 in boys; the prevalence of moderate and severe underweight decreased from 9·2% (6·0-12·9) in 1975 to 8·4% (6·8-10·1) in 2016 in girls and from 14·8% (10·4-19·5) in 1975 to 12·4% (10·3-14·5) in 2016 in boys. Prevalence of moderate and severe underweight was highest in India, at 22·7% (16·7-29·6) among girls and 30·7% (23·5-38·0) among boys. Prevalence of obesity was more than 30% in girls in Nauru, the Cook Islands, and Palau; and boys in the Cook Islands, Nauru, Palau, Niue, and American Samoa in 2016. Prevalence of obesity was about 20% or more in several countries in Polynesia and Micronesia, the Middle East and north Africa, the Caribbean, and the USA. In 2016, 75 (44-117) million girls and 117 (70-178) million boys worldwide were moderately or severely underweight. In the same year, 50 (24-89) million girls and 74 (39-125) million boys worldwide were obese. INTERPRETATION: The rising trends in children's and adolescents' BMI have plateaued in many high-income countries, albeit at high levels, but have accelerated in parts of Asia, with trends no longer correlated with those of adults. FUNDING: Wellcome Trust, AstraZeneca Young Health Programme

    Diminishing benefits of urban living for children and adolescents’ growth and development

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    Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being1–6. Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5–19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was <1.1 kg m–2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have amplified
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