Host-specific genetic variation of highly pathogenic avian influenza viruses (H5N1)

The complete genome sequences of two isolates A/chicken/Egypt/CL6/07 (CL6/07) and A/duck/Egypt/D2br10/07 (D2br10/07) of highly pathogenic avian influenza virus (HPAI) H5N1 isolated at the beginning of 2007 outbreak in Egypt were determined and compared with all Egyptian HPAI H5N1 sequences available in the GenBank. Sequence analysis utilizing the RNA from the original tissue homogenate showed amino acid substitutions in seven of the viral segments in both samples. Interestingly, these changes were different between the CL6/07 and D2br10/07 when compared to other Egyptian isolates. Moreover, phylogenetic analysis showed independent sub-clustering of the two viruses within the Egyptian sequences signifying a possible differential adaptation in the two hosts. Further, pre-amplification analysis of H5N1 might be necessary for accurate data interpretation and identification of distinct factor(s) influencing the evolution of the virus in different poultry species

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Evidence-based nanoscopic and molecular framework for excipient functionality in compressed orally disintegrating tablets

The work investigates the adhesive/cohesive molecular and physical interactions together with nanoscopic features of commonly used orally disintegrating tablet (ODT) excipients microcrystalline cellulose (MCC) and D-mannitol. This helps to elucidate the underlying physico-chemical and mechanical mechanisms responsible for powder densification and optimum product functionality. Atomic force microscopy (AFM) contact mode analysis was performed to measure nano-adhesion forces and surface energies between excipient-drug particles (6-10 different particles per each pair). Moreover, surface topography images (100 nm2-10 μm2) and roughness data were acquired from AFM tapping mode. AFM data were related to ODT macro/microscopic properties obtained from SEM, FTIR, XRD, thermal analysis using DSC and TGA, disintegration testing, Heckel and tabletability profiles. The study results showed a good association between the adhesive molecular and physical forces of paired particles and the resultant densification mechanisms responsible for mechanical strength of tablets. MCC micro roughness was 3 times that of D-mannitol which explains the high hardness of MCC ODTs due to mechanical interlocking. Hydrogen bonding between MCC particles could not be established from both AFM and FTIR solid state investigation. On the contrary, D-mannitol produced fragile ODTs due to fragmentation of surface crystallites during compression attained from its weak crystal structure. Furthermore, AFM analysis has shown the presence of extensive micro fibril structures inhabiting nano pores which further supports the use of MCC as a disintegrant. Overall, excipients (and model drugs) showed mechanistic behaviour on the nano/micro scale that could be related to the functionality of materials on the macro scale. © 2014 Al-khattawi et al

A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data

Background: A polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening. / Methods: United Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3–T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups. / Results: The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age. / Conclusions: PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS. / Impact: Personalized genetic risk assessments could inform prostate cancer screening decisions

High-Density SNP Mapping of the HLA Region Identifies Multiple Independent Susceptibility Loci Associated with Selective IgA Deficiency

Selective IgA deficiency (IgAD; serum IgA<0.07 g/l) is the most common form of human primary immune deficiency, affecting approximately 1∶600 individuals in populations of Northern European ancestry. The polygenic nature of IgAD is underscored by the recent identification of several new risk genes in a genome-wide association study. Among the characterized susceptibility loci, the association with specific HLA haplotypes represents the major genetic risk factor for IgAD. Despite the robust association, the nature and location of the causal variants in the HLA region remains unknown. To better characterize the association signal in this region, we performed a high-density SNP mapping of the HLA locus and imputed the genotypes of common HLA-B, -DRB1, and -DQB1 alleles in a combined sample of 772 IgAD patients and 1,976 matched controls from 3 independent European populations. We confirmed the complex nature of the association with the HLA locus, which is the result of multiple effects spanning the entire HLA region. The primary association signal mapped to the HLA-DQB1*02 allele in the HLA Class II region (combined P = 7.69×10−57; OR = 2.80) resulting from the combined independent effects of the HLA-B*0801-DRB1*0301-DQB1*02 and -DRB1*0701-DQB1*02 haplotypes, while additional secondary signals were associated with the DRB1*0102 (combined P = 5.86×10−17; OR = 4.28) and the DRB1*1501 (combined P = 2.24×10−35; OR = 0.13) alleles. Despite the strong population-specific frequencies of HLA alleles, we found a remarkable conservation of these effects regardless of the ethnic background, which supports the use of large multi-ethnic populations to characterize shared genetic association signals in the HLA region. We also provide evidence for the location of association signals within the specific extended haplotypes, which will guide future sequencing studies aimed at characterizing the precise functional variants contributing to disease pathogenesis

High-Density SNP Screening of the Major Histocompatibility Complex in Systemic Lupus Erythematosus Demonstrates Strong Evidence for Independent Susceptibility Regions

A substantial genetic contribution to systemic lupus erythematosus (SLE) risk is conferred by major histocompatibility complex (MHC) gene(s) on chromosome 6p21. Previous studies in SLE have lacked statistical power and genetic resolution to fully define MHC influences. We characterized 1,610 Caucasian SLE cases and 1,470 parents for 1,974 MHC SNPs, the highly polymorphic HLA-DRB1 locus, and a panel of ancestry informative markers. Single-marker analyses revealed strong signals for SNPs within several MHC regions, as well as with HLA-DRB1 (global p = 9.99×10−16). The most strongly associated DRB1 alleles were: *0301 (odds ratio, OR = 2.21, p = 2.53×10−12), *1401 (OR = 0.50, p = 0.0002), and *1501 (OR = 1.39, p = 0.0032). The MHC region SNP demonstrating the strongest evidence of association with SLE was rs3117103, with OR = 2.44 and p = 2.80×10−13. Conditional haplotype and stepwise logistic regression analyses identified strong evidence for association between SLE and the extended class I, class I, class III, class II, and the extended class II MHC regions. Sequential removal of SLE–associated DRB1 haplotypes revealed independent effects due to variation within OR2H2 (extended class I, rs362521, p = 0.006), CREBL1 (class III, rs8283, p = 0.01), and DQB2 (class II, rs7769979, p = 0.003, and rs10947345, p = 0.0004). Further, conditional haplotype analyses demonstrated that variation within MICB (class I, rs3828903, p = 0.006) also contributes to SLE risk independent of HLA-DRB1*0301. Our results for the first time delineate with high resolution several MHC regions with independent contributions to SLE risk. We provide a list of candidate variants based on biologic and functional considerations that may be causally related to SLE risk and warrant further investigation

Computational Refinement of Functional Single Nucleotide Polymorphisms Associated with ATM Gene

gene are the most common forms of genetic variations that account for various forms of cancer. However, the extent to which SNPs interferes with the gene regulation and affects cancer susceptibility remains largely unknown. gene. gene function can aid in better understanding of genetic differences in disease susceptibility

Conditional meta-analysis stratifying on detailed HLA genotypes identifies a novel type 1 diabetes locus around TCF19 in the MHC

The human leukocyte antigen (HLA) class II genes HLA-DRB1, -DQA1 and -DQB1 are the strongest genetic factors for type 1 diabetes (T1D). Additional loci in the major histocompatibility complex (MHC) are difficult to identify due to the region’s high gene density and complex linkage disequilibrium (LD). To facilitate the association analysis, two novel algorithms were implemented in this study: one for phasing the multi-allelic HLA genotypes in trio families, and one for partitioning the HLA strata in conditional testing. Screening and replication were performed on two large and independent datasets: the Wellcome Trust Case–Control Consortium (WTCCC) dataset of 2,000 cases and 1,504 controls, and the T1D Genetics Consortium (T1DGC) dataset of 2,300 nuclear families. After imputation, the two datasets have 1,941 common SNPs in the MHC, of which 22 were successfully tested and replicated based on the statistical testing stratifying on the detailed DRB1 and DQB1 genotypes. Further conditional tests using the combined dataset confirmed eight novel SNP associations around 31.3 Mb on chromosome 6 (rs3094663, p = 1.66 × 10−11 and rs2523619, p = 2.77 × 10−10 conditional on the DR/DQ genotypes). A subsequent LD analysis established TCF19, POU5F1, CCHCR1 and PSORS1C1 as potential causal genes for the observed association