Prospective Cohort Study

The assimilation, storage and use of energy from nutrients constitute a homeostatic system that is essential for life In vertebrates, the ability to store sufficient quantities of energy-dense triglyceride in adipose tissue allows survival during the frequent periods of food deprivation encountered during evolution However, the presence of excess adipose tissue can be maladaptive A complex physiological system has evolved to regulate fuel stores and energy balance at an optimum level Leptin, a hormone secreted by adipose tissue, and its receptor are integral components of this system Leptin also signals nutritional status to several other physiological systems and modulates their function Here we review the role of leptin in the control of body weight and its relevance to the pathogenesis of obesity

Leptin and the regulation of body weight in mammals

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

Integrative analysis of 111 reference human epigenomes

Medical genetics was revolutionized during the 1980s by the application of genetic mapping to locate the genes responsible for simple Mendelian diseases. Most diseases and traits, however, do not follow simple inheritance patterns. Genetics have thus begun taking up the even greater challenge of the genetic dissection of complex traits. Four major approaches have been developed: linkage analysis, allele-sharing methods, association studies, and polygenic analysis of experimental crosses. This article synthesizes the current state of the genetic dissection of complex traits--describing the methods, limitations, and recent applications to biological problems.

https://focus.psychiatryonline.org/doi/pdf/10.1176/foc.4.3.442

Genetic dissection of complex traits

Pathology and genetics of tumours of the urinary system and male genital organs

Epidemiology and genetics of cutaneous malignant melanoma in France: 214

Two linkage methods were used to detect loci underlying neurophysiological measures associated with alcohol dependence 1) the Haseman-Elston (H-E) sib pair method for genome-wide search, and 2) the combined segregation-linkage (CSL), based on regressive models, to confirm positive linkages found by the genome screening. Among 14 linkage results that were significant at the 0.5% level using H-E, the CSL method leads to similar p-values in only three cases but to higher p-values in all others. Investigation of these discrepancies shows that assumptions (normality and homoscedasticity of the error term) of H-E least-squares regression method are not verified. A robust estimator of slope parameters without assuming any distribution function for the linear model error terms increases the p-values and reduces the difference between H-E and CSL results. Alternatively, the CSL approach may lack power when multiple genes with small effects are involved.

Detection of quantitative trait loci associated with alcohol-dependence: use of model-free sib-pair method and combined segregation-linkage analysis based on regressive models.

We compare two simulation procedures used to determine empirical distributions of three affected sib-pair test-statistics in family samples with missing parental marker information. P1 and P2 procedures differ according to whether affected sibs' genotypes are ignored (P1) or accounted for (P2) to generate the unknown parental genotypes. Overall, our results show that P2 procedure performs better than P1, particularly when marker heterozygosity is high (H = 75%) or when marker data from unaffected siblings are available with low marker heterozygosity (H = 50%). These results are similar for all affected sib-pair tests.

Empirical affected-sib-pair statistics: two simulation strategies.

Familial concentrations of breast cancer, first described over 100 years ago (Broca 1866), may be due either to chance or to environmental factors common to members of the same family. They may also result from genetic susceptibility to the disease.

Florence Demenais

Papers

Epidemiology and genetics of cutaneous malignant melanoma in France: 214

Detection of quantitative trait loci associated with alcohol-dependence: use of model-free sib-pair method and combined segregation-linkage analysis based on regressive models.

Empirical affected-sib-pair statistics: two simulation strategies.

Familial Susceptibility to Breast Cancer

Genome screen in the French EGEA study: detection of