Genome-wide association study of a semicontinuous trait: illustration of the impact of the modeling strategy through the study of Neutrophil Extracellular Traps levels

Over the last years, there has been a considerable expansion of genome-wide association studies (GWAS) for discovering biological pathways underlying pathological conditions or disease biomarkers. These GWAS are often limited to binary or quantitative traits analyzed through linear or logistic models, respectively. In some situations, the distribution of the outcome may require more complex modeling, such as when the outcome exhibits a semicontinuous distribution characterized by an excess of zero values followed by a non-negative and right-skewed distribution. We here investigate three different modeling for semicontinuous data: Tobit, Negative Binomial and Compound Poisson-Gamma. Using both simulated data and a real GWAS on Neutrophil Extracellular Traps (NETs), an emerging biomarker in immuno-thrombosis, we demonstrate that Compound Poisson-Gamma was the most robust model with respect to low allele frequencies and outliers. This model further identified the MIR155HG locus as significantly (P = 1.4 × 10^-8) associated with NETs plasma levels in a sample of 657 participants, a locus recently highlighted to be involved in NETs formation in mice. This work highlights the importance of the modeling strategy for GWAS of a semicontinuous outcome and suggests Compound Poisson-Gamma as an elegant but neglected alternative to Negative Binomial for modeling semicontinuous outcome in the context of genomic investigations.

Tweedie Model for Predicting Factors Associated with Distance Traveled to Access Inpatient Services in Kenya

Aim. This study aims to examine which factors influence the distance traveled by patients for inpatient care in Kenya. Methods. We used data from the fourth round of the Kenya Household Health Expenditure and Utilization survey. Our dependent variable was the self-reported distance traveled by patients to access inpatient care at public health facilities. As the clustered data were correlated, we used the generalized estimating equations approach with an exchangeable correlation under a Tweedie distribution. To select the best-fit covariates for predicting distance, we adopted a variable selection technique using the $QI{C}_u$ and $R^2$ criteria, wherein the lowest (highest) value for the former (latter) is preferred. Results. Using data for 451 participants from 47 counties, we found that three-fifths were admitted between 1 and 5 days, two-thirds resided in rural areas, and 90% were satisfied with the facilities’ service. Wealth quintiles were evenly distributed across respondents. Most admissions (81%) comprised $<$ 15, $>$ 65, and 25–54 years. Many households were of medium size (4–6 members) and had low education level (48%), and nine-tenths had no access to insurance. While two-thirds reported employment-based income, the same number reported not having cash to pay for inpatient services; 6 out of 10 paid over 3000 KES. Thus, differences in employment, ability to pay, and household size influence the distance traveled to access government healthcare facilities in Kenya. Interpretation. Low-income individuals more likely have large households and live in rural areas and, thus, are forced to travel farther to access inpatient care. Unlike the unemployed, the employed may have better socioeconomic status and possibly live near inpatient healthcare facilities, thereby explaining their short distances to access these services. Policymakers must support equal access to inpatient services, prioritize rural areas, open job opportunities, and encourage smaller families.

Estimation of actual evapotranspiration in barley crop through a generalized linear model

Evapotranspiration is a key variable of the water cycle. Its calculation requires several ground data that frequently are not available. This study contains a detailed method and measurements of meteorological and energy balance variables that can be used to estimate the daily actual evapotranspiration (ETa). A linear generalized model is obtained to calculate the ETa from common variables measured in meteorological stations. The method showed a good performance over a barley crop of easthern Argentine Pampas and can be applied and tested in other great plains.

Measurements of soil-plant-atmosphere are included

The routines to reproduce the method are included

The generalized method allows the calculation of daily ETa over crops and was tested over barley crops