Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health

Transfer of passive immunity and serum proteinogram in the first six months of life of Criollo Lageano and black and white holstein calves

The objective of this study was to evaluate and compare the transfer of passive immunity and the proteinogram in Criollo Lageano (CL) and Black and White Holstein (BWH) calves. Two groups were utilized with 13 Criollo Lageano and 10 BWH calves. Blood samples were collected for the measurement of total serum protein, electrophoresis of serum proteins, activity of the gamma glutamyl transferase, and concentration of IgG by the method of the zinc sulfate turbidity in periods between 24 and 36 hours of life, 15, 30, 60, 90, 120, 150 and 180 days. Statistical analysis was performed by ANOVA and Tukey test at 5% significance level, and correlations between variables were calculated. Variations of serum proteins followed a pattern of physiological behavior over the first six months of life and production of immunoglobulins was active earlier in BWH calves and slower in the Criollo Lageano, without causing any impact on their health. Gamma globulin in the first days of life (24-36h) was correlated with IgG (r=0.87 for CL and r=0.89 for BWH), PTS (r=0.91 for CL and r=0.92 for BWH), Glob (r=0.99 for CL and r=0.98 for BWH) and GGT (r=0.14 for CL and r=0.83 for BWH). It was concluded that there was no failure in the transfer of passive immunity in Criollo Lageano calves but this failure occurred in the BWH calves. IgG values estimated by the zinc sulfate turbidity and serum proteins were considered good indicators of the transfer of passive immunity in calves between 24 and 36 hours of life

Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits

Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits

An evolutionary algorithm for automated machine learning focusing on classifier ensembles: an improved algorithm and extended results

A large number of classification algorithms have been proposed in the machine learning literature. These algorithms have different pros and cons, and no algorithm is the best for all datasets. Hence, a challenging problem consists of choosing the best classification algorithm with its best hyper-parameter settings for a given input dataset. In the last few years, Automated Machine Learning (Auto-ML) has emerged as a promising approach for tackling this problem, by doing a heuristic search in a large space of candidate classification algorithms and their hyper-parameter settings. In this work we propose an improved version of our previous Evolutionary Algorithm (EA) – more precisely, an Estimation of Distribution Algorithm – for the Auto-ML task of automatically selecting the best classifier ensemble and its best hyper-parameter settings for an input dataset. The new version of this EA was compared against its previous version, as well as against a random forest algorithm (a strong ensemble algorithm) and a version of the well-known Auto-ML method Auto-WEKA adapted to search in the same space of classifier ensembles as the proposed EA. In general, in experiments with 21 datasets, the new EA version obtained the best results among all methods in terms of four popular predictive accuracy measures: error rate, precision, recall and F-measure