Genome-wide Polygenic Risk Scores Predict Risk of Glioma and Molecular Subtypes.

BACKGROUND: Polygenic risk scores (PRS) aggregate the contribution of many risk variants to provide a personalized genetic susceptibility profile. Since sample sizes of glioma genome-wide association studies (GWAS) remain modest, there is a need to efficiently capture genetic risk using available data. METHODS: We applied a method based on continuous shrinkage priors (PRS-CS) to model the joint effects of over 1 million common variants on disease risk and compared this to an approach (PRS-CT) that only selects a limited set of independent variants that reach genome-wide significance (P<5×10-8). PRS models were trained using GWAS stratified by histological (10,346 cases, 14,687 controls) and molecular subtype (2,632 cases, 2,445 controls), and validated in two independent cohorts. RESULTS: PRS-CS was generally more predictive than PRS-CT with a median increase in explained variance (R2) of 24% (interquartile range=11-30%) across glioma subtypes. Improvements were pronounced for glioblastoma (GBM), with PRS-CS yielding larger odds ratios (OR) per standard deviation (OR=1.93, P=2.0×10-54 vs. OR=1.83, P=9.4×10-50) and higher explained variance (R2=2.82% vs. R2=2.56%). Individuals in the 80th percentile of the PRS-CS distribution had significantly higher risk of GBM (0.107%) at age 60 compared to those with average PRS (0.046%, P=2.4×10-12). Lifetime absolute risk reached 1.18% for glioma and 0.76% for IDH wildtype tumors for individuals in the 95th PRS percentile. PRS-CS augmented the classification of IDH mutation status in cases when added to demographic factors (AUC=0.839 vs. AUC=0.895, PΔAUC=6.8×10-9). CONCLUSIONS: Genome-wide PRS has potential to enhance the detection of high-risk individuals and help distinguish between prognostic glioma subtypes.

Association of immunoglobulin E levels with glioma risk and survival.

Background: Previous epidemiological studies have reported an association of serum immunoglobulin E (IgE) levels with reduced glioma risk, but the association between IgE and glioma prognosis is not well characterized. This study aimed to examine how sex, tumor subtype, and IgE class modulate the association of serum IgE levels with glioma risk and survival. Methods: We conducted a case-control study using participants from the University of California, San Francisco Adult Glioma Study (1997-2010). Serum IgE levels for total, respiratory and food allergy were measured in adults diagnosed with glioma (n=1,696) and cancer-free controls (n=1,135) matched based on age, sex, and race/ethnicity. Logistic regression was adjusted for patient demographics to assess the association between IgE levels and glioma risk. Multivariable Cox regression adjusted for patient-specific and tumor-specific factors compared survival between the elevated and normal IgE groups. Results: Elevated total IgE was associated with reduced risk of IDH wildtype (OR=0.65, 95% CI: 0.54-0.78) and IDH mutant glioma (OR=0.65, 95% CI: 0.50-0.85). In multivariable Cox regression, elevated respiratory IgE was associated with improved survival for IDH wildtype glioma (HR=0.78, 95% CI: 0.67-0.91). The reduction in mortality risk was more pronounced in females (HR=0.71, 95% CI: 0.53-0.96) than in males (HR=0.80, 95% CI: 0.66-0.97), with improvements in median survival of 6.2 months (P<.001) and 1.6 months (P=0.003), respectively. Conclusion: Elevated serum IgE was associated with improved prognosis for IDH wildtype glioma, with a more pronounced protective effect in females. These results suggest a possible sexual dimorphism and antitumor activity of IgE-mediated immune responses.

The impact of sub-national heterogeneities in demography and epidemiology on the introduction of rubella vaccination programs in Nigeria.

Rubella infection during pregnancy can result in miscarriage or infants with a constellation of birth defects known as congenital rubella syndrome (CRS). When coverage is inadequate, rubella vaccination can increase CRS cases by increasing the average age of infection. Thus, the World Health Organisation recommends that countries introducing rubella vaccine be able to vaccinate at least 80% of each birth cohort. Previous studies have focused on national-level analyses and have overlooked sub-national variation in introduction risk. We characterised the sub-national heterogeneity in rubella transmission within Nigeria and modelled local rubella vaccine introduction under different scenarios to refine the set of conditions and strategies required for safe rubella vaccine use. Across Nigeria, the basic reproduction number ranged from 2.6 to 6.2. Consequently, the conditions for safe vaccination varied across states with low-risk areas requiring coverage levels well below 80 %. In high-risk settings, inadequate routine coverage needed to be supplemented by campaigns that allowed for gradual improvements in vaccination coverage over time. Understanding local heterogeneities in both short-term and long-term epidemic dynamics can permit earlier nationwide introduction of rubella vaccination and identify sub-national areas suitable for program monitoring, program improvement and campaign support.

Genome-wide Polygenic Risk Scores Predict Risk of Glioma and Molecular Subtypes.

Background: Polygenic risk scores (PRS) aggregate the contribution of many risk variants to provide a personalized genetic susceptibility profile. Since sample sizes of glioma genome-wide association studies (GWAS) remain modest, there is a need to find efficient ways of capturing genetic risk factors using available germline data. Methods: We developed a novel PRS (PRS-CS) that uses continuous shrinkage priors to model the joint effects of over 1 million polymorphisms on disease risk and compared it to an approach (PRS-CT) that selects a limited set of independent variants that reach genome-wide significance (P<5×10-8). PRS models were trained using GWAS results stratified by histological (10,346 cases, 14,687 controls) and molecular subtype (2,632 cases, 2,445 controls), and validated in two independent cohorts. Results: PRS-CS was consistently more predictive than PRS-CT across glioma subtypes with an average increase in explained variance (R2) of 21%. Improvements were particularly pronounced for glioblastoma tumors, with PRS-CS yielding larger effect sizes (odds ratio (OR)=1.93, P=2.0×10-54 vs. OR=1.83, P=9.4×10-50) and higher explained variance (R2=2.82% vs. R2=2.56%). Individuals in the 95th percentile of the PRS-CS distribution had a 3-fold higher lifetime absolute risk of IDH mutant (0.63%) and IDH wildtype (0.76%) glioma relative to individuals with average PRS. PRS-CS also showed high classification accuracy for IDH mutation status among cases (AUC=0.895). Conclusions: Our novel genome-wide PRS may improve the identification of high-risk individuals and help distinguish between prognostic glioma subtypes, increasing the potential clinical utility of germline genetics in glioma patient management.

Global transmission suitability maps for dengue virus transmitted by Aedes aegypti from 1981 to 2019.

Mosquito-borne viruses increasingly threaten human populations due to accelerating changes in climate, human and mosquito migration, and land use practices. Over the last three decades, the global distribution of dengue has rapidly expanded, causing detrimental health and economic problems in many areas of the world. To develop effective disease control measures and plan for future epidemics, there is an urgent need to map the current and future transmission potential of dengue across both endemic and emerging areas. Expanding and applying Index P, a previously developed mosquito-borne viral suitability measure, we map the global climate-driven transmission potential of dengue virus transmitted by Aedes aegypti mosquitoes from 1981 to 2019. This database of dengue transmission suitability maps and an R package for Index P estimations are offered to the public health community as resources towards the identification of past, current and future transmission hotspots. These resources and the studies they facilitate can contribute to the planning of disease control and prevention strategies, especially in areas where surveillance is unreliable or non-existent.

Genomic epidemiology unveils the dynamics and spatial corridor behind the Yellow Fever virus outbreak in Southern Brazil.

Despite the considerable morbidity and mortality of yellow fever virus (YFV) infections in Brazil, our understanding of disease outbreaks is hampered by limited viral genomic data. Here, through a combination of phylogenetic and epidemiological models, we reconstructed the recent transmission history of YFV within different epidemic seasons in Brazil. A suitability index based on the highly domesticated Aedes aegypti was able to capture the seasonality of reported human infections. Spatial modeling revealed spatial hotspots with both past reporting and low vaccination coverage, which coincided with many of the largest urban centers in the Southeast. Phylodynamic analysis unraveled the circulation of three distinct lineages and provided proof of the directionality of a known spatial corridor that connects the endemic North with the extra-Amazonian basin. This study illustrates that genomics linked with eco-epidemiology can provide new insights into the landscape of YFV transmission, augmenting traditional approaches to infectious disease surveillance and control.