The History of Rome in Painting

There are many paths to reach Rome, immense field open to the eye through the centuries and days, where the presence of the story is haunting. All the artists came to Rome: Italians of various Italian and also French, Dutch, Flemish, Spanish, English and Americans. These painters whose works tell its long history for having lived in the glare of light forever are the Roman pantheon of arts: what are all the anonymous authors of the frescoes of ancient Rome and medieval, but Fabriano, Cimabue , Giotto, Botticelli, Raphael, Giulio Romano, Michelangelo, Caravaggio, Guido Reni, Guercino, Titian, Vasari, Velasquez, Le Nain, Poussin, Zuccari, Van Wittel, Eckersberg, Giraudet, David, Panini, Hubert Robert, Reynolds, Fuseli, Ingres, Sargent, Caffi, Vernet, Turner, Corot, Caffi, De Chirico, etc..

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.