Estimating genetic effect sizes under joint disease-endophenotype models in presence of gene-environment interactions

ZBTB16 and metabolic syndrome: a network perspective

Metabolic syndrome is a prevalent, complex condition. The search for genetic determinants of the syndrome is currently undergoing a paradigm enhancement by adding systems genetics approaches to association studies. We summarize the current evidence on relations between an emergent new candidate, zinc finger and BTB domain containing 16 (ZBTB16) transcription factor and the major components constituting the metabolic syndrome. Information stemming from studies on experimental models with altered Zbtb16 expression clearly shows its effect on adipogenesis, cardiac hypertrophy and fibrosis, lipid levels and insulin sensitivity. Based on current evidence, we provide a network view of relations between ZBTB16 and hallmarks of metabolic syndrome in order to elucidate the potential functional links involving the ZBTB16 node. Many of the identified genes interconnecting ZBTB16 with all or most metabolic syndrome components are linked to immune function, inflammation or oxidative stress. In summary, ZBTB16 represents a promising pleiotropic candidate node for metabolic syndrome.

Recent progress in genetics, epigenetics and metagenomics unveils the pathophysiology of human obesity

In high-, middle- and low-income countries, the rising prevalence of obesity is the underlying cause of numerous health complications and increased mortality. Being a complex and heritable disorder, obesity results from the interplay between genetic susceptibility, epigenetics, metagenomics and the environment. Attempts at understanding the genetic basis of obesity have identified numerous genes associated with syndromic monogenic, non-syndromic monogenic, oligogenic and polygenic obesity. The genetics of leanness are also considered relevant as it mirrors some of obesity's aetiologies. In this report, we summarize ten genetically elucidated obesity syndromes, some of which are involved in ciliary functioning. We comprehensively review 11 monogenic obesity genes identified to date and their role in energy maintenance as part of the leptin-melanocortin pathway. With the emergence of genome-wide association studies over the last decade, 227 genetic variants involved in different biological pathways (central nervous system, food sensing and digestion, adipocyte differentiation, insulin signalling, lipid metabolism, muscle and liver biology, gut microbiota) have been associated with polygenic obesity. Advances in obligatory and facilitated epigenetic variation, and gene-environment interaction studies have partly accounted for the missing heritability of obesity and provided additional insight into its aetiology. The role of gut microbiota in obesity pathophysiology, as well as the 12 genes associated with lipodystrophies is discussed. Furthermore, in an attempt to improve future studies and merge the gap between research and clinical practice, we provide suggestions on how high-throughput '-omic' data can be integrated in order to get closer to the new age of personalized medicine.

When Is an Endophenotype Useful to Detect Association to a Disease? Exploring the Relationships between Disease Status, Endophenotype and Genetic Polymorphisms

OBJECTIVES

To investigate the conditions and analysis strategies required so that endophenotypes related to a disease help discover genetic variants involved in the disease.

METHODS

The association with disease susceptibility variants is examined as a function of the relationships between disease status, endophenotype values and the genotype at another disease or endophenotype susceptibility locus assumed to be previously known, using approximate linear models of allele frequencies as a function of these variables and simulations in the context of family studies when the endophenotype is dichotomous.

RESULTS

Under genetic mechanisms where the risk allele of the tested locus has an effect exclusively in subjects with the endophenotype, the risk allele frequency differences between affected and unaffected subjects are much greater in the subset of subjects with an endophenotype impairment than in those without such an impairment, and power gains are obtained when testing the association under a joint disease-endophenotype model, both with two-locus or single-locus tests. However, with moderate main effect on the risk of disease or endophenotype impairment, testing directly the association between risk allele and disease or endophenotype is more powerful than testing under a joint disease-endophenotype model.

CONCLUSIONS

Joint modeling of disease and endophenotype should be used only in parallel with standard disease association testing.

Isolation of a Genomic Region Affecting Most Components of Metabolic Syndrome in a Chromosome-16 Congenic Rat Model

Metabolic syndrome is a highly prevalent human disease with substantial genomic and environmental components. Previous studies indicate the presence of significant genetic determinants of several features of metabolic syndrome on rat chromosome 16 (RNO16) and the syntenic regions of human genome. We derived the SHR.BN16 congenic strain by introgression of a limited RNO16 region from the Brown Norway congenic strain (BN-Lx) into the genomic background of the spontaneously hypertensive rat (SHR) strain. We compared the morphometric, metabolic, and hemodynamic profiles of adult male SHR and SHR.BN16 rats. We also compared in silico the DNA sequences for the differential segment in the BN-Lx and SHR parental strains. SHR.BN16 congenic rats had significantly lower weight, decreased concentrations of total triglycerides and cholesterol, and improved glucose tolerance compared with SHR rats. The concentrations of insulin, free fatty acids, and adiponectin were comparable between the two strains. SHR.BN16 rats had significantly lower systolic (18-28 mmHg difference) and diastolic (10-15 mmHg difference) blood pressure throughout the experiment (repeated-measures ANOVA, P < 0.001). The differential segment spans approximately 22 Mb of the telomeric part of the short arm of RNO16. The in silico analyses revealed over 1200 DNA variants between the BN-Lx and SHR genomes in the SHR.BN16 differential segment, 44 of which lead to missense mutations, and only eight of which (in Asb14, Il17rd, Itih1, Syt15, Ercc6, RGD1564958, Tmem161a, and Gatad2a genes) are predicted to be damaging to the protein product. Furthermore, a number of genes within the RNO16 differential segment associated with metabolic syndrome components in human studies showed polymorphisms between SHR and BN-Lx (including Lpl, Nrg3, Pbx4, Cilp2, and Stab1). Our novel congenic rat model demonstrates that a limited genomic region on RNO16 in the SHR significantly affects many of the features of metabolic syndrome.