6 research outputs found

    Association of Fc Gamma Receptor 3B Gene Copy Number Variation with Rheumatoid Arthritis Susceptibility

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    Structural variations such as copy number variants (CNVs) have been associated with multiple autoimmune diseases. In this study, we explored the association of the Fc gamma receptor 3B gene (FCGR3B) copy number variation (CNV) with rheumatoid arthritis (RA) susceptibility and related serological traits in the Pakistani population. We also performed a meta-analysis of four published FCGR3B CNV studies along with the current study. A total of 927 subjects (597 RA cases, 330 healthy controls) were recruited from three rheumatology centers in Pakistan. Anti-cyclic citrullinated peptide (anti-CCP) antibodies and rheumatoid factor (RF) were measured in RA patients. FCGR3B copy number was assayed using the TaqMan® CN assay (Hs04211858_cn, Applied Biosystems, Foster City, CA, USA) and the copy number was estimated by using CopyCaller® software (version 2.1; Applied Biosystems, USA). Logistic regression was applied to calculate the odds ratio (OR) of RA risk associated with FCGR3B CNV using sex and age as covariates in R. Meta-analysis on four previously published studies and the current study was performed using the random-effect model. We observed a significant association between FCGR3B copy number < 2 and RA susceptibility (OR = 1.53; 95% CI: 1.05 to 2.22; p = 0.0259) and anti-CCP seropositivity (OR 2.56; 95% CI: 1.34 to 4.89; p = 0.0045). A non-significant association of FCGR3B copy number < 2 was also observed between increased rheumatoid factor (RF) seropositivity (OR = 1.74; 95% CI:0.93 to 3.26; p = 0.0816). Meta-analysis on 13,915 subjects (7005 RA cases and 6907 controls) also showed significant association of copy number < 2 with the increased risk of RA (OR = 1.30; 95% CI: 1.07 to 1.56; p = 0.00671). FCGR3B copy number < 2 is associated with increased RA risk and anti-CCP seropositivity

    Association of VPREB1 Gene Copy Number Variation and Rheumatoid Arthritis Susceptibility

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    Objective. Copy number variation (CNV) is a structural variation in the human genome that has been associated with multiple clinical phenotypes. B cells are important components of rheumatoid arthritis- (RA-) mediated immune response; hence, CNV in the regulators of B cells (such as VPREB1) can influence RA susceptibility. In this study, we aimed to explore the association of CNV in the VPREB1 gene with RA susceptibility in the Pakistani population. Methods. A total of 1,106 subjects (616 RA cases, 490 healthy controls) were selected from three rheumatology centers in Pakistan. VPREB1 CNV was determined using the TaqMan® CN assay (Hs02879734_cn, Applied Biosystems, Foster City, CA, USA), and CNV was estimated by using CopyCaller® (version 2.1; Applied Biosystems, USA) software. Odds ratio (OR) was calculated by logistic regression with sex and age as covariates in R. Results. A significant association between >2 VPREB1 CNV and RA risk was observed with an OR of 3.92 (95% CI: 1.27 - 12.12; p=0.01746) in the total sample. Whereas 2 of VPREB1 is a risk factor for RA in the total Pakistani population, while CNV<2 is protective in women

    Investigating the GWAS-Implicated Loci for Rheumatoid Arthritis in the Pakistani Population

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    Rheumatoid arthritis (RA) is a complex and multifactorial autoimmune disorder with the involvement of multiple genetic and environmental factors. Genome-wide association studies (GWAS) have identified more than 50 RA genetic loci in European populations. Given the anticipated overlap of RA-relevant genes and pathways across different ethnic groups, we sought to replicate 58 GWAS-implicated SNPs reported in Europeans in Pakistani subjects. 1,959 unrelated subjects comprising 1,222 RA cases and 737 controls were collected from three rheumatology facilities in Pakistan. Genotyping was performed using iPLEX or TaqMan® methods. A total of 50 SNPs were included in the final association analysis after excluding those that failed assay design/run or postrun QC analysis. Fourteen SNPs (LINC00824/rs1516971, PADI4/rs2240336, CEP57/rs4409785, CTLA4/rs3087243, STAT4/rs13426947, HLA-B/MICA/rs2596565, C5orf30/rs26232, CCL21/rs951005, GATA3/rs2275806, VPS37C/rs595158, HLA-DRB1/rs660895, EOMES/rs3806624, SPRED2/rs934734, and RUNX1/rs9979383) were replicated in our Pakistani sample at false discovery rate (FDR) of <0.20 with nominal p values ranging from 4.73E-06 to 3.48E-02. Our results indicate that several RA susceptibility loci are shared between Pakistani and European populations, supporting the role of common genes/pathways

    Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

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    BackgroundFuture trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050.MethodsUsing forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline.FindingsIn the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]).InterpretationGlobally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions.FundingBill & Melinda Gates Foundation.</p
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