QTL-based association analyses reveal novel genes influencing pleiotropy of metabolic syndrome (MetS)

A Novel Gene ARHGAP44 for Longitudinal Changes in Glycated Hemoglobin (HbA1c) in Subjects without Type 2 Diabetes: Evidence from the Long Life Family Study (LLFS) and the Framingham Offspring Study (FOS)

Glycated hemoglobin (HbA1c) indicates average glucose levels over three months and is associated with insulin resistance and type 2 diabetes (T2D). Longitudinal changes in HbA1c (ΔHbA1c) are also associated with aging processes, cognitive performance, and mortality. We analyzed ΔHbA1c in 1,886 non-diabetic Europeans from the Long Life Family Study to uncover gene variants influencing ΔHbA1c. Using growth curve modeling adjusted for multiple covariates, we derived ΔHbA1c and conducted linkage-guided sequence analysis. Our genome-wide linkage scan identified a significant locus on 17p12. In-depth analysis of this locus revealed a variant rs56340929 (explaining 27% of the linkage peak) in the ARHGAP44 gene that was significantly associated with ΔHbA1c. RNA transcription of ARHGAP44 was associated with ΔHbA1c. The Framingham Offspring Study data further supported these findings on the gene level. Together, we found a novel gene ARHGAP44 for ΔHbA1c in family members without T2D. Follow-up studies using longitudinal omics data in large independent cohorts are warranted.

Systemic Blood Proteome Patterns Reflect Disease Phenotypes in Neovascular Age-Related Macular Degeneration

There is early evidence of extraocular systemic signals effecting function and morphology in neovascular age-related macular degeneration (nAMD). The prospective, cross-sectional BIOMAC study is an explorative investigation of peripheral blood proteome profiles and matched clinical features to uncover systemic determinacy in nAMD under anti-vascular endothelial growth factor intravitreal therapy (anti-VEGF IVT). It includes 46 nAMD patients stratified by the level of disease control under ongoing anti-VEGF treatment. Proteomic profiles in peripheral blood samples of every patient were detected with LC-MS/MS mass spectrometry. The patients underwent extensive clinical examination with a focus on macular function and morphology. In silico analysis includes unbiased dimensionality reduction and clustering, a subsequent annotation of clinical features, and non-linear models for recognition of underlying patterns. The model assessment was performed using leave-one-out cross validation. The findings provide an exploratory demonstration of the link between systemic proteomic signals and macular disease pattern using and validating non-linear classification models. Three main results were obtained: (1) Proteome-based clustering identifies two distinct patient subclusters with the smaller one (n = 10) exhibiting a strong signature for oxidative stress response. Matching the relevant meta-features on the individual patient's level identifies pulmonary dysfunction as an underlying health condition in these patients. (2) We identify biomarkers for nAMD disease features with Aldolase C as a putative factor associated with superior disease control under ongoing anti-VEGF treatment. (3) Apart from this, isolated protein markers are only weakly correlated with nAMD disease expression. In contrast, applying a non-linear classification model identifies complex molecular patterns hidden in a high number of proteomic dimensions determining macular disease expression. In conclusion, so far unconsidered systemic signals in the peripheral blood proteome contribute to the clinically observed phenotype of nAMD, which should be examined in future translational research on AMD.

Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI

This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E-7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.

MicroRNA let-7i inhibits granulosa-luteal cell proliferation and oestradiol biosynthesis by directly targeting IMP2

RESEARCH QUESTION

Increased granulosa cell division is associated with abnormal folliculogenesis in polycystic ovary syndrome (PCOS). Lethal-7i microRNA (let-7i) may play an important role in the follicular development and granulosa cell growth; therefore is let-7i involved in PCOS pathogenesis?

DESIGN

The expression of let-7i was measured in granulosa-luteal cells (GLC) from women with or without PCOS. A human granulosa cell line, KGN, was used for the functional study. Mimics and inhibitors of let-7i, lentiviruses expressing insulin-like growth factor 2 mRNA binding protein (IMP2), and small-interfering RNAs were transfected into KGN cells. KGN cell proliferation was determined by 5-ethynyl-2'-deoxyuridine (EdU) and Cell Counting Kit-8 (CCK-8) assays. The cell cycle and apoptosis were assessed by propidium iodide-annexin V (PI-A) staining and fluorescence-activated cell sorting. Oestradiol concentration was determined by enzyme-linked immunoassay. Bioinformatics analysis and luciferase reporter assay were applied to confirm the let-7i target genes.

RESULTS

The study showed that let-7i was down-regulated in PCOS GLC (P = 0.001). Mimics of let-7i inhibited KGN proliferation (P = 0.001), and decreased aromatase expression (P = 0.030) and oestradiol production (P = 0.029), whereas let-7i inhibitors had the opposite effect. Bioinformatics analysis and quantitative real-time (qRT) PCR identified IMP2 as a target of let-7i (P = 0.021). qRT-PCR and western blot analysis indicated that IMP2 was up-regulated in GLC in women with PCOS (P = 0.001 and P = 0.044), and IMP2 expression was suppressed by let-7i in KGN cells (P < 0.001). Luciferase reporter assay results (P = 0.002), combined with the rescue assay, confirmed that let-7i inhibited KGN cell proliferation and reduced oestradiol concentration by directly targeting IMP2.

CONCLUSIONS

let-7i was down-regulated in PCOS GLC. Overexpression of let-7i inhibited KGN cell proliferation and decreased oestradiol production in an IMP2-dependent manner, providing a new molecular mechanism for PCOS.

Genomic characterization of the world's longest selection experiment in mouse reveals the complexity of polygenic traits

BACKGROUND

Long-term selection experiments are a powerful tool to understand the genetic background of complex traits. The longest of such experiments has been conducted in the Research Institute for Farm Animal Biology (FBN), generating extreme mouse lines with increased fertility, body mass, protein mass and endurance. For >140 generations, these lines have been maintained alongside an unselected control line, representing a valuable resource for understanding the genetic basis of polygenic traits. However, their history and genomes have not been reported in a comprehensive manner yet. Therefore, the aim of this study is to provide a summary of the breeding history and phenotypic traits of these lines along with their genomic characteristics. We further attempt to decipher the effects of the observed line-specific patterns of genetic variation on each of the selected traits.

RESULTS

Over the course of >140 generations, selection on the control line has given rise to two extremely fertile lines (>20 pups per litter each), two giant growth lines (one lean, one obese) and one long-distance running line. Whole genome sequencing analysis on 25 animals per line revealed line-specific patterns of genetic variation among lines, as well as high levels of homozygosity within lines. This high degree of distinctiveness results from the combined effects of long-term continuous selection, genetic drift, population bottleneck and isolation. Detection of line-specific patterns of genetic differentiation and structural variation revealed multiple candidate genes behind the improvement of the selected traits.

CONCLUSIONS

The genomes of the Dummerstorf trait-selected mouse lines display distinct patterns of genomic variation harbouring multiple trait-relevant genes. Low levels of within-line genetic diversity indicate that many of the beneficial alleles have arrived to fixation alongside with neutral alleles. This study represents the first step in deciphering the influence of selection and neutral evolutionary forces on the genomes of these extreme mouse lines and depicts the genetic complexity underlying polygenic traits.

Innate-Immunity Genes in Obesity

The main functions of adipose tissue are thought to be storage and mobilization of the body’s energy reserves, active and passive thermoregulation, participation in the spatial organization of internal organs, protection of the body from lipotoxicity, and ectopic lipid deposition. After the discovery of adipokines, the endocrine function was added to the above list, and after the identification of crosstalk between adipocytes and immune cells, an immune function was suggested. Nonetheless, it turned out that the mechanisms underlying mutual regulatory relations of adipocytes, preadipocytes, immune cells, and their microenvironment are complex and redundant at many levels. One possible way to elucidate the picture of adipose-tissue regulation is to determine genetic variants correlating with obesity. In this review, we examine various aspects of adipose-tissue involvement in innate immune responses as well as variants of immune-response genes associated with obesity.

Tumor Necrosis Receptor Superfamily Interact with Fusion and Fission of Mitochondria of Adipose Tissue in Obese Patients without Type 2 Diabetes

Interactions between receptors and ligands of the tumor necrosis factor superfamily (TNFSF) provide costimulatory signals that control the survival, proliferation, differentiation, and effector function of immune cells. All components of the TNF superfamily are associated with NF-kB functions that are not limited to cell death and may promote survival in the face of adipose tissue inflammation in obesity. Inflammation dysfunction of mitochondria is a key factor associated with insulin resistance in obesity. The aim of the study was to analyze the relationship of soluble forms of receptors and ligands of the TNF superfamily in blood plasma with mitochondrial dynamics in adipose tissue (greater omentum (GO) and subcutaneous adipose tissue (Sat)) of obese patients with and without type 2 diabetes mellitus (T2DM). Increased plasma sTNF-R1, sTNF-R2, sTNFRSF8 receptors, and ligands TNFSF12, TNFSF13, TNFSF13B are characteristic of obese patients without T2DM. The TNF-a levels in blood plasma were associated with a decrease in MFN2 gene expression in GO and IL-10 in blood plasma. The TNFSF12 levels contributed to a decrease in glucose levels, a decrease in BMI, and an increase in IL-10 levels by influencing the MFN2 gene expression in GO, which supports mitochondrial fusion.

A combination of genetics and microbiota influences the severity of the obesity phenotype in diet-induced obesity

Obesity has emerged as a major global health problem and is associated with various diseases, such as metabolic syndrome, type 2 diabetes mellitus, and cardiovascular diseases. The inbred C57BL/6 mouse strain is often used for various experimental investigations, such as metabolic research. However, over time, genetically distinguishable C57BL/6 substrains have evolved. The manifestation of genetic alterations has resulted in behavioral and metabolic differences. In this study, a comparison of diet-induced obesity in C57BL/6JHanZtm, C57BL/6NCrl and C57BL/6 J mice revealed several metabolic and immunological differences such as blood glucose level and cytokine expression, respectively, among these C57BL/6 substrains. For example, C57BL/6NCrl mice developed the most pronounced adiposity, whereas C57BL/6 J mice showed the highest impairment in glucose tolerance. Moreover, our results indicated that the immunological phenotype depends on the intestinal microbiota, as the cell subset composition of the colon was similar in obese ex-GF B6NRj^B6JHanZtm and obese B6JHanZtm mice. Phenotypic differences between C57BL/6 substrains are caused by a complex combination of genetic and microbial alterations. Therefore, in performing metabolic research, considering substrain-specific characteristics, which can influence the course of study, is important. Moreover, for unbiased comparison of data, the entire strain name should be shared with the scientific community.

Association study between a polymorphic poly-T repeat sequence in the promoter of the somatostatin gene and metabolic syndrome

Background

Metabolic syndrome is a cluster of factors associated with an increased risk of developing type 2 diabetes mellitus (T2D) and coronary artery disease (CAD). It is a complex disorder resulting from the interaction between various environmental factors and genetic susceptibility. The somatostatin (SST) gene has been shown to regulate a wide range of functions, particularly in energy homeostasis. In addition, low levels of SST have been reported to have effects on the progression of metabolic syndrome components. The aim of this study was therefore to evaluate the association between polymorphic T sequences in the promoter of the SST gene and metabolic syndrome expression.

Methods

We studied 1725 French-Canadian subjects from a founder population selected on the basis of having a positive family history of dyslipidemia, CAD or T2D. The analysis were performed on four groups created according to the poly T polymorphism length in the 5′ flanking promoter region of SST. Anova, Ancova and logistic regression models and Chi 2 analyses were used to evaluate the association between the poly T polymorphisms and metabolic syndrome components expression.

Results

Analyses showed that means, frequencies and odds ratio of metabolic syndrome components expression increase as the number of poly-T repeats in the promoter region of SST increases. Women exhibit more significant differences than men. However, the trends are the same in both genders and differences for most of the components are significant in the entire sample.

Conclusion

Those results suggest that the poly T polymorphisms in the SST promoter region may influence several metabolic processes implicated in metabolic syndrome expression. More analyses are needed to document the mechanisms that could underlie genetic regulation effect of SST on metabolic syndrome components and to clarify its specific role.

A GWA study reveals genetic loci for body conformation traits in Chinese Laiwu pigs and its implications for human BMI

Pigs share numerous physiological and phenotypic similarities with human and thus have been considered as a good model in nonrodent mammals for the study of genetic basis of human obesity. Researches on candidate genes for obesity traits have successfully identified some common genes between humans and pigs. However, few studies have assessed how many similarities exist between the genetic architecture of obesity in pigs and humans by large-scale comparative genomics. Here, we performed a genome-wide association study (GWAS) using the porcine 60 K SNP Beadchip for BMI and other four conformation traits at three different ages in a Chinese Laiwu pig population, which shows a large variability in fat deposition. In total, 35 SNPs were found to be significant at Bonferroni-corrected 5 % chromosome-wise level (P = 2.13 × 10^-5) and 88 SNPs had suggestive (P < 10^-4) association with the conformation traits. Some SNPs showed age-dependent association. Intriguingly, out of 32 regions associated with BMI in pigs, 18 were homologous with the loci for BMI in humans. Furthermore, five closest genes to GWAS peaks including HIF1AN, SMYD3, COX10, SLMAP, and GBE1 have been already associated with BMI in humans, which makes them very promising candidates for these QTLs. The result of GO analysis provided strong support to the fact that mitochondria and synapse play important roles in obesity susceptibility, which is consistent with previous findings on human obesity, and it also implicated new gene sets related to chromatin modification and Ig-like C2-type 5 domain. Therefore, these results not only provide new insights into the genetic architecture of BMI in pigs but also highlight that humans and pigs share the significant overlap of obesity-related genes.

Genome-wide association study for carcass traits, fatty acid composition, chemical composition, sugar, and the effects of related candidate genes in Japanese Black cattle

We performed a genome-wide association study (GWAS) and candidate gene analysis to: (i) evaluate the effectiveness of the GWAS in our small population by performing GWAS for carcass weight (CW) and fatty acid composition; (ii) detect novel candidate regions affecting non-CW carcass traits, chemical composition and sugar; and (iii) evaluate the association of the candidate genes previously detected in CW and fatty acid composition with other economically important traits. A total of 574 Japanese Black cattle and 40 657 Single nucleotide polymorphisms were used. In addition, candidate gene analyses were performed to evaluate the association of three CW-related genes and two fatty acid-related genes with carcass traits, fatty acid composition, chemical composition and sugar. The significant regions with the candidate genes were detected for CW and fatty acid composition, and these results showed that a significant region would be detectable despite the small sample size. The novel candidate regions were detected on BTA23 for crude protein and on BTA19 for fructose. CW-related genes associated with the rib-eye area and fatty acid composition were identified, and fatty acid-related genes had no relationship with other traits. Moreover, the favorable allele of CW-related genes had an unfavorable effect on fatty acid composition.

A comprehensive analysis of adiponectin QTLs using SNP association, SNP cis-effects on peripheral blood gene expression and gene expression correlation identified novel metabolic syndrome (MetS) genes with potential role in carcinogenesis and systemic inflammation

BACKGROUND

Metabolic syndrome (MetS) is an aberration associated with increased risk for cancer and inflammation. Adiponectin, an adipocyte-produced abundant protein hormone, has countering effect on the diabetogenic and atherogenic components of MetS. Plasma levels of adiponectin are negatively correlated with onset of cancer and cancer patient mortality. We previously performed microsatellite linkage analyses using adiponectin as a surrogate marker and revealed two QTLs on chr5 (5p14) and chr14 (14q13).

METHODS

Using individuals from 85 extended families that contributed to the linkage and who were measured for 42 clinical and biologic MetS phenotypes, we tested QTL-based SNP associations, peripheral white blood cell (PWBC) gene expression, and the effects of cis-acting SNPs on gene expression to discover genomic elements that could affect the pathophysiology and complications of MetS.

RESULTS

Adiponectin levels were found to be highly intercorrelated phenotypically with the majority of MetS traits. QTL-specific haplotype-tagging SNPs associated with MetS phenotypes were annotated to 14 genes whose function could influence MetS biology as well as oncogenesis or inflammation. These were mechanistically categorized into four groups: cell-cell adhesion and mobility, signal transduction, transcription and protein sorting. Four genes were highly prioritized: cadherin 18 (CDH18), myosin X (MYO10), anchor protein 6 of AMPK (AKAP6), and neuronal PAS domain protein 3 (NPAS3). PWBC expression was detectable only for the following genes with multi-organ or with multi-function properties: NPAS3, MARCH6, MYO10 and FBXL7. Strong evidence of cis-effects on the expression of MYO10 in PWBC was found with SNPs clustered near the gene's transcription start site. MYO10 expression in PWBC was marginally correlated with body composition (p = 0.065) and adipokine levels in the periphery (p = 0.064). Variants of genes AKAP6, NPAS3, MARCH6 and FBXL7 have been previously reported to be associated with insulin resistance, inflammatory markers or adiposity studies using genome-wide approaches whereas associations of CDH18 and MYO10 with MetS traits have not been reported before.

CONCLUSIONS

Adiponectin QTLs-based SNP association and mRNA expression identified genes that could mediate the association between MetS and cancer or inflammation.