Sexual Dimorphic Regulation of Body Weight Dynamics and Adipose Tissue Lipolysis

BACKGROUND: Successful reduction of body weight (BW) is often followed by recidivism to obesity. BW-changes including BW-loss and -regain is associated with marked alterations in energy expenditure (EE) and adipose tissue (AT) metabolism. Since these processes are sex-specifically controlled, we investigated sexual dimorphisms in metabolic processes during BW-dynamics (gain-loss-regain). RESEARCH DESIGN: Obesity was induced in C57BL/6J male (m) and female (f) mice by 15 weeks high-fat diet (HFD) feeding. Subsequently BW was reduced (-20%) by caloric restriction (CR) followed by adaptive feeding, and a regain-phase. Measurement of EE, body composition, blood/organ sampling were performed after each feeding period. Lipolysis was analyzed ex-vivo in gonadal AT. RESULTS: Male mice exhibited accelerated BW-gain compared to females (relative BW-gain m:140.5±3.2%; f:103.7±6.5%; p<0.001). In consonance, lean mass-specific EE was significantly higher in females compared to males during BW-gain. Under CR female mice reached their target-BW significantly faster than male mice (m:12.2 days; f:7.6 days; p<0.001) accompanied by a sustained sex-difference in EE. In addition, female mice predominantly downsized gonadal AT whereas the relation between gonadal and total body fat was not altered in males. Accordingly, only females exhibited an increased rate of forskolin-stimulated lipolysis in AT associated with significantly higher glycerol concentrations, lower RER-values, and increased AT expression of adipose triglyceride lipase (ATGL) and hormone sensitive lipase (HSL). Analysis of AT lipolysis in estrogen receptor alpha (ERα)-deficient mice revealed a reduced lipolytic rate in the absence of ERα exclusively in females. Finally, re-feeding caused BW-regain faster in males than in females. CONCLUSION: The present study shows sex-specific dynamics during BW-gain-loss-regain. Female mice responded to CR with an increase in lipolytic activity, and augmented lipid-oxidation leading to more efficient weight loss. These processes likely involve ERα-dependent signaling in AT and sexual dimorphic regulation of genes involved in lipid metabolism

Accounting for a Quantitative Trait Locus for Plasma Triglyceride Levels: Utilization of Variants in Multiple Genes

For decades, research efforts have tried to uncover the underlying genetic basis of human susceptibility to a variety of diseases. Linkage studies have resulted in highly replicated findings and helped identify quantitative trait loci (QTL) for many complex traits; however identification of specific alleles accounting for linkage remains elusive. The purpose of this study was to determine whether with a sufficient number of variants a linkage signal can be fully explained.We used comprehensive fine-mapping using a dense set of single nucleotide polymorphisms (SNPs) across the entire quantitative trait locus (QTL) on human chromosome 7q36 linked to plasma triglyceride levels. Analyses included measured genotype and combined linkage association analyses.Screening this linkage region, we found an over representation of nominally significant associations in five genes (MLL3, DPP6, PAXIP1, HTR5A, INSIG1). However, no single genetic variant was sufficient to account for the linkage. On the other hand, multiple variants capturing the variation in these five genes did account for the linkage at this locus. Permutation analyses suggested that this reduction in LOD score was unlikely to have occurred by chance (p = 0.008).With recent findings, it has become clear that most complex traits are influenced by a large number of genetic variants each contributing only a small percentage to the overall phenotype. We found that with a sufficient number of variants, the linkage can be fully explained. The results from this analysis suggest that perhaps the failure to identify causal variants for linkage peaks may be due to multiple variants under the linkage peak with small individual effect, rather than a single variant of large effect

Genetic architecture of the APM1 gene and its influence on adiponectin plasma levels and parameters of the metabolic syndrome in 1,727 healthy Caucasians

Copyright: Copyright 2008 Elsevier B.V., All rights reserved.The associations of the adiponectin (APM1) gene with parameters of the metabolic syndrome are inconsistent. We performed a systematic investigation based on fine-mapped single nucleotide polymorphisms (SNPs) highlighting the genetic architecture and their role in modulating adiponectin plasma concentrations in a particularly healthy population of 1,727 Caucasians avoiding secondary effects from disease processes. Genotyping 53 SNPs (average spacing of 0.7 kb) in the APM1 gene region in 81 Caucasians revealed a two-block linkage disequilibrium (LD) structure and enabled comprehensive tag SNP selection. We found particularly strong associations with adiponectin concentrations for 11 of the 15 tag SNPs in the 1,727 subjects (five P values <0.0001). Haplotype analysis provided a thorough differentiation of adiponectin concentrations with 9 of 17 haplotypes showing significant associations (three P values <0.0001). No significant association was found for any SNP with the parameters of the metabolic syndrome. We observed a two-block LD structure of APM1 pointing toward at least two independent association signals, one including the promoter SNPs and a second spanning the relevant exons. Our data on a large number of healthy subjects suggest a clear modulation of adiponectin concentrations by variants of APM1, which are not merely a concomitant effect in the course of type 2 diabetes or coronary artery disease.publishersversionPeer reviewe

Meta‐Analysis of Genome‐wide Linkage Studies in BMI and Obesity

Objective: The objective was to provide an overall assessment of genetic linkage data of BMI and BMI‐defined obesity using a nonparametric genome scan meta‐analysis. Research Methods and Procedures: We identified 37 published studies containing data on over 31,000 individuals from more than >10,000 families and obtained genome‐wide logarithm of the odds (LOD) scores, non‐parametric linkage (NPL) scores, or maximum likelihood scores (MLS). BMI was analyzed in a pooled set of all studies, as a subgroup of 10 studies that used BMI‐defined obesity, and for subgroups ascertained through type 2 diabetes, hypertension, or subjects of European ancestry. Results: Bins at chromosome 13q13.2‐ q33.1, 12q23‐q24.3 achieved suggestive evidence of linkage to BMI in the pooled analysis and samples ascertained for hypertension. Nominal evidence of linkage to these regions and suggestive evidence for 11q13.3‐22.3 were also observed for BMI‐defined obesity. The FTO obesity gene locus at 16q12.2 also showed nominal evidence for linkage. However, overall distribution of summed rank p values <0.05 is not different from that expected by chance. The strongest evidence was obtained in the families ascertained for hypertension at 9q31.1‐qter and 12p11.21‐q23 (p < 0.01). Conclusion: Despite having substantial statistical power, we did not unequivocally implicate specific loci for BMI or obesity. This may be because genes influencing adiposity are of very small effect, with substantial genetic heterogeneity and variable dependence on environmental factors. However, the observation that the FTO gene maps to one of the highest ranking bins for obesity is interesting and, while not a validation of this approach, indicates that other potential loci identified in this study should be investigated further.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93663/1/oby.2007.269.pd

Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes

Quantitative differences in gene expression are thought to contribute to phenotypic differences between individuals. We generated genome-wide transcriptional profiles of lymphocyte samples from 1,240 participants in the San Antonio Family Heart Study. The expression levels of 85% of the 19,648 detected autosomal transcripts were significantly heritable. Linkage analysis uncovered 41,000 cis-regulated transcripts at a false discovery rate of 5% and showed that the expression quantitative trait loci with the most significant linkage evidence are often located at the structural locus of a given transcript. To highlight the usefulness of this much-enlarged map of cis-regulated transcripts for the discovery of genes that influence complex traits in humans, as an example we selected high-density lipoprotein cholesterol concentration as a phenotype of clinical importance, and identified the cis-regulated vanin 1 (VNN1) gene as harboring sequence variants that influence high-density lipoprotein cholesterol concentrations. Phenotypic differences among individuals are partly the result of quantitative differences in transcript abundance. Although environmental stimuli may influence the location, timing, and/or level of transcription of specific genes, genetic differences among individuals are also known to have a significant role. Transcript levels may be thought of as quantitative endophenotypes that can be subjected to statistical genetic analyses in an effort to localize and identify the underlying genetic factors, an approach that is sometimes referred to as genetical genomics 1 . Using microarray technology, it is now possible to assess the abundance of many transcripts-and, indeed, of the entire known transcriptome-simultaneously. Studies that attempt to localize the genetic regulators of gene expression have been carried out in several species, including yeast 2-5 , plants (maize and eucalyptus) 6,7 , fly 8 , mouse 6,9,10 and rat 11 . Several recent investigations have also focused on humans. In most of these studies, microarray-based gene expression profiles were generated for transformed cell lines derived from lymphocytes from members of the Centre d&apos;Etude du Polymorphisme Humain (CEPH) families 12 , and linkage and/or linkage disequilibrium approaches were used to map the genetic determinants that regulate the expression of individual transcript

Association of Adiponectin SNP+45 and SNP+276 with Type 2 Diabetes in Han Chinese Populations: A Meta-Analysis of 26 Case-Control Studies

Recently, many studies have reported that the SNP+45(T>G) and SNP+276(G>T) polymorphisms in the adiponectin gene are associated with type 2 diabetes (T2DM) in the Chinese Han population. However, the previous studies yielded many conflicting results. Thus, a meta-analysis of the association of the adiponectin gene with T2DM in the Chinese Han population is required. In the current study, we first determined the distribution of the adiponectin SNP+276 polymorphism in T2DM and nondiabetes (NDM) control groups. Our results suggested that the genotype and allele frequencies for SNP+276 did not differ significantly between the T2DM and NDM groups. Then, a meta-analysis of 23 case-control studies of SNP+45, with a total of 4161 T2DM patients and 3709 controls, and 11 case-control studies of SNP+276, with 2533 T2DM patients and 2212 controls, was performed. All subjects were Han Chinese. The fixed-effects model and random-effects model were applied for dichotomous outcomes to combine the results of the included studies. The results revealed a trend towards an increased risk of T2DM for the SNP+45G allele as compared with the SNP+45T allele (OR = 1.34; 95% CI, 1.11–1.62; P<0.01) in the Chinese Han population. However, there was no association between SNP+276 and T2DM (OR = 0.90; 95% CI, 0.73–1.10; P = 0.31). The results of our association study showed there was no association between the adiponectin SNP+276 polymorphism and T2DM in the Yunnan Han population. The meta-analysis results suggested that the SNP+45G allele might be a susceptibility allele for T2DM in the Chinese Han population. However, we did not observe an association between SNP+276 and T2DM

Do obese but metabolically normal women differ in intra-abdominal fat and physical activity levels from those with the expected metabolic abnormalities? A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Obesity remains a major public health problem, associated with a cluster of metabolic abnormalities. However, individuals exist who are very obese but have normal metabolic parameters. The aim of this study was to determine to what extent differences in metabolic health in very obese women are explained by differences in body fat distribution, insulin resistance and level of physical activity.</p> <p>Methods</p> <p>This was a cross-sectional pilot study of 39 obese women (age: 28-64 yrs, BMI: 31-67 kg/m²) recruited from community settings. Women were defined as 'metabolically normal' on the basis of blood glucose, lipids and blood pressure. Magnetic Resonance Imaging was used to determine body fat distribution. Detailed lifestyle and metabolic profiles of participants were obtained.</p> <p>Results</p> <p>Women with a healthy metabolic profile had lower intra-abdominal fat volume (geometric mean 4.78 l [95% CIs 3.99-5.73] vs 6.96 l [5.82-8.32]) and less insulin resistance (HOMA 3.41 [2.62-4.44] vs 6.67 [5.02-8.86]) than those with an abnormality. The groups did not differ in abdominal subcutaneous fat volume (19.6 l [16.9-22.7] vs 20.6 [17.6-23.9]). A higher proportion of those with a healthy compared to a less healthy metabolic profile met current physical activity guidelines (70% [95% CIs 55.8-84.2] vs 25% [11.6-38.4]). Intra-abdominal fat, insulin resistance and physical activity make independent contributions to metabolic status in very obese women, but explain only around a third of the variance.</p> <p>Conclusion</p> <p>A sub-group of women exists who are metabolically normal despite being very obese. Differences in fat distribution, insulin resistance, and physical activity level are associated with metabolic differences in these women, but account only partially for these differences. Future work should focus on strategies to identify those obese individuals most at risk of the negative metabolic consequences of obesity and on identifying other factors that contribute to metabolic status in obese individuals.</p

Monomeric Tartrate Resistant Acid Phosphatase Induces Insulin Sensitive Obesity

Obesity is associated with macrophage infiltration of adipose tissue, which may link adipose inflammation to insulin resistance. However, the impact of inflammatory cells in the pathophysiology of obesity remains unclear

Fetuin-A Induces Cytokine Expression and Suppresses Adiponectin Production

BACKGROUND: The secreted liver protein fetuin-A (AHSG) is up-regulated in hepatic steatosis and the metabolic syndrome. These states are strongly associated with low-grade inflammation and hypoadiponectinemia. We, therefore, hypothesized that fetuin-A may play a role in the regulation of cytokine expression, the modulation of adipose tissue expression and plasma concentration of the insulin-sensitizing and atheroprotective adipokine adiponectin. METHODOLOGY AND PRINCIPAL FINDINGS: Human monocytic THP1 cells and human in vitro differenttiated adipocytes as well as C57BL/6 mice were treated with fetuin-A. mRNA expression of the genes encoding inflammatory cytokines and the adipokine adiponectin (ADIPOQ) was assessed by real-time RT-PCR. In 122 subjects, plasma levels of fetuin-A, adiponectin and, in a subgroup, the multimeric forms of adiponectin were determined. Fetuin-A treatment induced TNF and IL1B mRNA expression in THP1 cells (p<0.05). Treatment of mice with fetuin-A, analogously, resulted in a marked increase in adipose tissue Tnf mRNA as well as Il6 expression (27- and 174-fold, respectively). These effects were accompanied by a decrease in adipose tissue Adipoq mRNA expression and lower circulating adiponectin levels (p<0.05, both). Furthermore, fetuin-A repressed ADIPOQ mRNA expression of human in vitro differentiated adipocytes (p<0.02) and induced inflammatory cytokine expression. In humans in plasma, fetuin-A correlated positively with high-sensitivity C-reactive protein, a marker of subclinical inflammation (r = 0.26, p = 0.01), and negatively with total- (r = -0.28, p = 0.02) and, particularly, high molecular weight adiponectin (r = -0.36, p = 0.01). CONCLUSIONS AND SIGNIFICANCE: We provide novel evidence that the secreted liver protein fetuin-A induces low-grade inflammation and represses adiponectin production in animals and in humans. These data suggest an important role of fatty liver in the pathophysiology of insulin resistance and atherosclerosis