Genome-wide linkage analysis of multiple metabolic factors: evidence of genetic heterogeneity

Genome-Wide Linkage Analysis of Large Multiple Multigenerational Families Identifies Novel Genetic Loci for Coronary Artery Disease

Coronary artery disease (CAD) is the leading cause of death, and genetic factors contribute significantly to risk of CAD. This study aims to identify new CAD genetic loci through a large-scale linkage analysis of 24 large and multigenerational families with 433 family members (GeneQuest II). All family members were genotyped with markers spaced by every 10 cM and a model-free nonparametric linkage (NPL-all) analysis was carried out. Two highly significant CAD loci were identified on chromosome 17q21.2 (NPL score of 6.20) and 7p22.2 (NPL score of 5.19). We also identified four loci with significant NPL scores between 4.09 and 4.99 on 2q33.3, 3q29, 5q13.2 and 9q22.33. Similar analyses in individual families confirmed the six significant CAD loci and identified seven new highly significant linkages on 9p24.2, 9q34.2, 12q13.13, 15q26.1, 17q22, 20p12.3, and 22q12.1, and two significant loci on 2q11.2 and 11q14.1. Two loci on 3q29 and 9q22.33 were also successfully replicated in our previous linkage analysis of 428 nuclear families. Moreover, two published risk variants, SNP rs46522 in UBE2Z and SNP rs6725887 in WDR12 by GWAS, were found within the 17q21.2 and 2q33.3 loci. These studies lay a foundation for future identification of causative variants and genes for CAD.

Hypothesis of the neuroendocrine cortisol pathway gene role in the comorbidity of depression, type 2 diabetes, and metabolic syndrome

Depression, type 2 diabetes (T2D), and metabolic syndrome (MetS) are often comorbid. Depression per se increases the risk for T2D by 60%. This risk is not accounted for by the use of antidepressant therapy. Stress causes hyperactivation of the hypothalamic–pituitary–adrenal (HPA) axis, by triggering the hypothalamic corticotropin-releasing hormone (CRH) secretion, which stimulates the anterior pituitary to release the adrenocorticotropin hormone (ACTH), which causes the adrenal secretion of cortisol. Depression is associated with an increased level of cortisol, and CRH and ACTH at inappropriately “normal” levels, that is too high compared to their expected lower levels due to cortisol negative feedback. T2D and MetS are also associated with hypercortisolism. High levels of cortisol can impair mood as well as cause hyperglycemia and insulin resistance and other traits typical of T2D and MetS. We hypothesize that HPA axis hyperactivation may be due to variants in the genes of the CRH receptors (CRHR1, CRHR2), corticotropin receptors (or melanocortin receptors, MC1R-MC5R), glucocorticoid receptor (NR3C1), mineralocorticoid receptor (NR3C2), and of the FK506 binding protein 51 (FKBP5), and that these variants may be partially responsible for the clinical association of depression, T2D and MetS. In this review, we will focus on the correlation of stress, HPA axis hyperactivation, and the possible genetic role of the CRHR1, CRHR2, MCR1–5, NR3C1, and NR3C2 receptors and FKBP5 in the susceptibility to the comorbidity of depression, T2D, and MetS. New studies are needed to confirm the hypothesized role of these genes in the clinical association of depression, T2D, and MetS.

Association of genetic variants in the adiponectin gene with metabolic syndrome: a case-control study and a systematic meta-analysis in the Chinese population

Background

The prevalence of metabolic syndrome has been rising worldwide, including in China, but knowledge on specific genetic determinants of metabolic syndrome is very limited. A number of studies have reported that polymorphisms in the ADIPOQ gene are associated with metabolic syndrome in Chinese Han populations. However, data is still conflicting. The objective of this study was to examine the associations of the adiponectin genetic variants with metabolic syndrome by a case-control study and meta-analyses in Chinese.

Methods

We first investigated the association of ADIPOQ rs2241766 (+45T>G in exon 2), rs266729 (−11377C>G in promoter) and rs1501299 (+276G>T in intron 2) polymorphisms with metabolic syndrome in a Hubei Han Chinese population with 322 metabolic syndrome patients and 161 normal controls recruited from the Yichang, Hubei. Then we comprehensively reviewed the association between ADIPOQ rs2241766/rs266729/rs1501299 and metabolic syndrome in the Chinese populations via a meta-analysis. The strength of association was assessed by odds ratios (ORs) with 95% confidence intervals (CI).

Results

The G allele frequency of rs2241766 in metabolic syndrome patients was significantly higher than those of controls group (29.8% vs 23.3%, OR = 1.40, P = 0.033). The logistic regression analysis adjusted by gender and age showed a nominally significant association for rs2241766 GG+GT genotype (P = 0.065, OR = 1.55) and rs1501299 GG genotype in recessive model (OR = 1.54, P = 0.066). However, no association was observed for rs266729 in our sample. We identified thirteen studies for rs2241766 (2,684 metabolic syndrome patients and 2,864 controls), three studies for rs266729, and eleven studies for rs1501299 (2,889 metabolic syndrome patients and 3,304 controls) in Chinese. Meta-analysis indicated significant associations for the rs2241766 G allele (OR = 1.14, 95%CI = 1.05–1.24, P = 0.003), rs266729 GG+GT genotypes (OR = 0.80, 95%CI = 0.68–0.92, P = 0.003) and rs1501299 GG+TG genotypes (OR = 1.42, 95%CI 1.16–1.75, P = 0.001).

Conclusions

Our results demonstrated ADIPOQ as a pleiotropic locus for metabolic syndrome and its components in the Han Chinese population.

Principal component and interacting QTL analyses identify novel gene loci associated with metabolic traits in mice

Previously analyzed F2 mice between KK/Ta and RR/Sgn strains were further investigated by defining appropriate permutation-derived threshold levels for significance and by searching pairwise gene interactions. In addition, a principal component analysis was conducted to extract a potential parameter that accounts for the joint occurrence of metabolic abnormalities. As a result, one significant interaction, containing novel QTL on chromosome 15, was identified for plasma total-cholesterol levels. For the principal component that potentially accounted for the joint occurrence of metabolic abnormalities, one significant QTL was identified on chromosome 12. This locus was not significant for any single trait. These complex genetic bases could not be disclosed as long as a separate trait was analyzed by traditional single QTL scans.