Leveraging cross-species transcription factor binding site patterns: from diabetes risk loci to disease mechanisms

Computational Assessment of the Expression-modulating Potential for Non-coding Variants

Large-scale genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) studies have identified multiple non-coding variants associated with genetic diseases by affecting gene expression. However, pinpointing causal variants effectively and efficiently remains a serious challenge. Here, we developed CARMEN, a novel algorithm to identify functional non-coding expression-modulating variants. Multiple evaluations demonstrated CARMEN's superior performance over state-of-the-art tools. Applying CARMEN to GWAS and eQTL datasets further pinpointed several causal variants other than the reported lead single-nucleotide polymorphisms (SNPs). CARMEN scales well with the massive datasets, and is available online as a web server at http://carmen.gao-lab.org.

Physiological and pathological roles of lipogenesis

Lipids are essential metabolites, which function as energy sources, structural components and signalling mediators. Most cells are able to convert carbohydrates into fatty acids, which are often converted into neutral lipids for storage in the form of lipid droplets. Accumulating evidence suggests that lipogenesis plays a crucial role not only in metabolic tissues for systemic energy homoeostasis but also in immune and nervous systems for their proliferation, differentiation and even pathophysiological roles. Thus, excessive or insufficient lipogenesis is closely associated with aberrations in lipid homoeostasis, potentially leading to pathological consequences, such as dyslipidaemia, diabetes, fatty liver, autoimmune diseases, neurodegenerative diseases and cancers. For systemic energy homoeostasis, multiple enzymes involved in lipogenesis are tightly controlled by transcriptional and post-translational modifications. In this Review, we discuss recent findings regarding the regulatory mechanisms, physiological roles and pathological importance of lipogenesis in multiple tissues such as adipose tissue and the liver, as well as the immune and nervous systems. Furthermore, we briefly introduce the therapeutic implications of lipogenesis modulation.

A non-coding variant linked to metabolic obesity with normal weight affects actin remodelling in subcutaneous adipocytes

Recent large-scale genomic association studies found evidence for a genetic link between increased risk of type 2 diabetes and decreased risk for adiposity-related traits, reminiscent of metabolically obese normal weight (MONW) association signatures. However, the target genes and cellular mechanisms driving such MONW associations remain to be identified. Here, we systematically identify the cellular programmes of one of the top-scoring MONW risk loci, the 2q24.3 risk locus, in subcutaneous adipocytes. We identify a causal genetic variant, rs6712203, an intronic single-nucleotide polymorphism in the COBLL1 gene, which changes the conserved transcription factor motif of POU domain, class 2, transcription factor 2, and leads to differential COBLL1 gene expression by altering the enhancer activity at the locus in subcutaneous adipocytes. We then establish the cellular programme under the genetic control of the 2q24.3 MONW risk locus and the effector gene COBLL1, which is characterized by impaired actin cytoskeleton remodelling in differentiating subcutaneous adipocytes and subsequent failure of these cells to accumulate lipids and develop into metabolically active and insulin-sensitive adipocytes. Finally, we show that perturbations of the effector gene Cobll1 in a mouse model result in organismal phenotypes matching the MONW association signature, including decreased subcutaneous body fat mass and body weight along with impaired glucose tolerance. Taken together, our results provide a mechanistic link between the genetic risk for insulin resistance and low adiposity, providing a potential therapeutic hypothesis and a framework for future identification of causal relationships between genome associations and cellular programmes in other disorders.

A leukemia-protective germline variant mediates chromatin module formation via transcription factor nucleation

Non-coding variants coordinate transcription factor (TF) binding and chromatin mark enrichment changes over regions spanning >100 kb. These molecularly coordinated regions are named “variable chromatin modules” (VCMs), providing a conceptual framework of how regulatory variation might shape complex traits. To better understand the molecular mechanisms underlying VCM formation, here, we mechanistically dissect a VCM-modulating noncoding variant that is associated with reduced chronic lymphocytic leukemia (CLL) predisposition and disease progression. This common, germline variant constitutes a 5-bp indel that controls the activity of an AXIN2 gene-linked VCM by creating a MEF2 binding site, which, upon binding, activates a super-enhancer-like regulatory element. This triggers a large change in TF binding activity and chromatin state at an enhancer cluster spanning >150 kb, coinciding with subtle, long-range chromatin compaction and robust AXIN2 up-regulation. Our results support a model in which the indel acts as an AXIN2 VCM-activating TF nucleation event, which modulates CLL pathology.

Non-coding variants can regulate transcription factor binding and gene expression at variable chromatin modules. Here, the authors show that a germline variant induces transcription factor nucleation through chromatin compaction leading to AXIN2 up-regulation and is associated to better prognosis in chronic lymphocytic leukaemia.

Long-read isoform sequencing reveals tissue-specific isoform expression between active and hibernating brown bears (Ursus arctos)

Understanding hibernation in brown bears (Ursus arctos) can provide insight into some human diseases. During hibernation, brown bears experience periods of insulin resistance, physical inactivity, extreme bradycardia, obesity, and the absence of urine production. These states closely mimic aspects of human diseases such as type 2 diabetes, muscle atrophy, as well as renal and heart failure. The reversibility of these states from hibernation to active season enables the identification of mediators with possible therapeutic value for humans. Recent studies have identified genes and pathways that are differentially expressed between active and hibernation seasons in bears. However, little is known about the role of differential expression of gene isoforms on hibernation physiology. To identify both distinct and novel mRNA isoforms, full-length RNA-sequencing (Iso-Seq) was performed on adipose, skeletal muscle, and liver from three individual bears sampled during both active and hibernation seasons. The existing reference genome annotation was improved by combining it with the Iso-Seq data. Short-read RNA-sequencing data from six individuals were mapped to the new reference annotation to quantify differential isoform usage (DIU) between tissues and seasons. We identified differentially expressed isoforms in all three tissues, to varying degrees. Adipose had a high level of DIU with isoform switching, regardless of whether the genes were differentially expressed. Our analyses revealed that DIU, even in the absence of differential gene expression, is an important mechanism for modulating genes during hibernation. These findings demonstrate the value of isoform expression studies and will serve as the basis for deeper exploration into hibernation biology.

Paired related homeobox 1 attenuates autophagy via acetyl-CoA carboxylase 1-regulated fatty acid metabolism in salivary adenoid cystic carcinoma

Autophagy can affect the invasion and metastasis of carcinoma. Our previous study has shown that invasion and epithelial‐mesenchymal transition in salivary adenoid cystic carcinoma (SACC) can be promoted by the metabolic reprogramming of free fatty acids (FFAs). However, the effect of FFA metabolism on autophagy in SACC remains unknown. In this study, we showed that overexpression of paired related homeobox 1 (PRRX1) reduced the number of autophagosomes and decreased the expression of LC3 and Beclin‐1 in SACC patients and SACC‐83 cells in vitro. Moreover, PRRX1‐mediating FFA reprogramming triggered to autophagy via regulating acetyl‐CoA carboxylase 1 (ACC1), leading to invasion and migration in SACC.

Gaining insight into metabolic diseases from human genetic discoveries

Human large-scale genetic association studies have identified sequence variations at thousands of genetic risk loci that are more common in patients with diverse metabolic disease compared with healthy controls. While these genetic associations have been replicated in multiple large cohorts and sometimes can explain up to 50% of heritability, the molecular and cellular mechanisms affected by common genetic variation associated with metabolic disease remains mostly unknown. A variety of new genome-wide data types, in conjunction with novel biostatistical and computational analytical methodologies and foundational experimental technologies, are paving the way for a principled approach to systematic variant-to-function (V2F) studies for metabolic diseases, turning associated regions into causal variants, cell types and states of action, effector genes, and cellular and physiological mechanisms. Identification of new target genes and cellular programs for metabolic risk loci will improve mechanistic understanding of disease biology and identification of novel therapeutic strategies.

REVA as A Well-curated Database for Human Expression-modulating Variants

More than 90% of disease- and trait-associated human variants are noncoding. By systematically screening multiple large-scale studies, we compiled REVA, a manually curated database for over 11.8 million experimentally tested noncoding variants with expression-modulating potentials. We provided 2424 functional annotations that could be used to pinpoint the plausible regulatory mechanism of these variants. We further benchmarked multiple state-of-the-art computational tools and found their limited sensitivity remains a serious challenge for effective large-scale analysis. REVA provides high-quality experimentally tested expression-modulating variants with extensive functional annotations, which will be useful for users in the noncoding variants community. REVA is available at http://reva.gao-lab.org.

Linking the FTO obesity rs1421085 variant circuitry to cellular, metabolic, and organismal phenotypes in vivo

Variants in FTO have the strongest association with obesity; however, it is still unclear how those noncoding variants mechanistically affect whole-body physiology. We engineered a deletion of the rs1421085 conserved cis-regulatory module (CRM) in mice and confirmed in vivo that the CRM modulates Irx3 and Irx5 gene expression and mitochondrial function in adipocytes. The CRM affects molecular and cellular phenotypes in an adipose depot-dependent manner and affects organismal phenotypes that are relevant for obesity, including decreased high-fat diet-induced weight gain, decreased whole-body fat mass, and decreased skin fat thickness. Last, we connected the CRM to a genetically determined effect on steroid patterns in males that was dependent on nutritional challenge and conserved across mice and humans. Together, our data establish cross-species conservation of the rs1421085 regulatory circuitry at the molecular, cellular, metabolic, and organismal level, revealing previously unknown contextual dependence of the variant's action.

A Variant Noncoding Region Regulates Prrx1 and Predisposes to Atrial Arrhythmias

[Figure: see text].

Extensive pleiotropism and allelic heterogeneity mediate metabolic effects of IRX3 and IRX5

Whereas coding variants often have pleiotropic effects across multiple tissues, noncoding variants are thought to mediate their phenotypic effects by specific tissue and temporal regulation of gene expression. Here, we investigated the genetic and functional architecture of a genomic region within the FTO gene that is strongly associated with obesity risk. We show that multiple variants on a common haplotype modify the regulatory properties of several enhancers targeting IRX3 and IRX5 from megabase distances. We demonstrate that these enhancers affect gene expression in multiple tissues, including adipose and brain, and impart regulatory effects during a restricted temporal window. Our data indicate that the genetic architecture of disease-associated loci may involve extensive pleiotropy, allelic heterogeneity, shared allelic effects across tissues, and temporally restricted effects.

Splice variants of metabolic nuclear receptors: Relevance for metabolic disease and therapeutic targeting

Metabolic nuclear receptors are ligand-activated transcription factors which control a wide range of metabolic processes and signaling pathways in response to nutrients and xenobiotics. Targeting these NRs is at the forefront of our endeavours to generate novel treatment options for diabetes, metabolic syndrome and fatty liver disease. Numerous splice variants have been described for these metabolic receptors. Structural changes, as a result of alternative splicing, lead to functional differences among NR isoforms, resulting in the regulation of different metabolic pathways by these NR splice variants. In this review, we describe known splice variants of FXR, LXRs, PXR, RXR, LRH-1, CAR and PPARs. We discuss their structure and functions, and elaborate on the regulation of splice variant abundance by nutritional signals. We conclude that NR splice variants pose an intriguing new layer of complexity in metabolic signaling, which needs to be taken into account in the development of treatment strategies for metabolic diseases.

Genetic Variants in Transcription Factor Binding Sites in Humans: Triggered by Natural Selection and Triggers of Diseases

Variants of transcription factor binding sites (TFBSs) constitute an important part of the human genome. Current evidence demonstrates close links between nucleotides within TFBSs and gene expression. There are multiple pathways through which genomic sequences located in TFBSs regulate gene expression, and recent genome-wide association studies have shown the biological significance of TFBS variation in human phenotypes. However, numerous challenges remain in the study of TFBS polymorphisms. This article aims to cover the current state of understanding as regards the genomic features of TFBSs and TFBS variants; the mechanisms through which TFBS variants regulate gene expression; the approaches to studying the effects of nucleotide changes that create or disrupt TFBSs; the challenges faced in studies of TFBS sequence variations; the effects of natural selection on collections of TFBSs; in addition to the insights gained from the study of TFBS alleles related to gout, its associated comorbidities (increased body mass index, chronic kidney disease, diabetes, dyslipidemia, coronary artery disease, ischemic heart disease, hypertension, hyperuricemia, osteoporosis, and prostate cancer), and the treatment responses of patients.

Single-cell chromatin accessibility identifies pancreatic islet cell type- and state-specific regulatory programs of diabetes risk

Single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq) creates new opportunities to dissect cell type-specific mechanisms of complex diseases. Since pancreatic islets are central to type 2 diabetes (T2D), we profiled 15,298 islet cells by using combinatorial barcoding snATAC-seq and identified 12 clusters, including multiple alpha, beta and delta cell states. We cataloged 228,873 accessible chromatin sites and identified transcription factors underlying lineage- and state-specific regulation. We observed state-specific enrichment of fasting glucose and T2D genome-wide association studies for beta cells and enrichment for other endocrine cell types. At T2D signals localized to islet-accessible chromatin, we prioritized variants with predicted regulatory function and co-accessibility with target genes. A causal T2D variant rs231361 at the KCNQ1 locus had predicted effects on a beta cell enhancer co-accessible with INS and genome editing in embryonic stem cell-derived beta cells affected INS levels. Together our findings demonstrate the power of single-cell epigenomics for interpreting complex disease genetics.

A regulatory variant at 3q21.1 confers an increased pleiotropic risk for hyperglycemia and altered bone mineral density

Skeletal and glycemic traits have shared etiology, but the underlying genetic factors remain largely unknown. To identify genetic loci that may have pleiotropic effects, we studied Genome-wide association studies (GWASs) for bone mineral density and glycemic traits and identified a bivariate risk locus at 3q21. Using sequence and epigenetic modeling, we prioritized an adenylate cyclase 5 (ADCY5) intronic causal variant, rs56371916. This SNP changes the binding affinity of SREBP1 and leads to differential ADCY5 gene expression, altering the chromatin landscape from poised to repressed. These alterations result in bone- and type 2 diabetes-relevant cell-autonomous changes in lipid metabolism in osteoblasts and adipocytes. We validated our findings by directly manipulating the regulator SREBP1, the target gene ADCY5, and the variant rs56371916, which together imply a novel link between fatty acid oxidation and osteoblast differentiation. Our work, by systematic functional dissection of pleiotropic GWAS loci, represents a framework to uncover biological mechanisms affecting pleiotropic traits.

Pancreatic progenitor epigenome maps prioritize type 2 diabetes risk genes with roles in development

Genetic variants associated with type 2 diabetes (T2D) risk affect gene regulation in metabolically relevant tissues, such as pancreatic islets. Here, we investigated contributions of regulatory programs active during pancreatic development to T2D risk. Generation of chromatin maps from developmental precursors throughout pancreatic differentiation of human embryonic stem cells (hESCs) identifies enrichment of T2D variants in pancreatic progenitor-specific stretch enhancers that are not active in islets. Genes associated with progenitor-specific stretch enhancers are predicted to regulate developmental processes, most notably tissue morphogenesis. Through gene editing in hESCs, we demonstrate that progenitor-specific enhancers harboring T2D-associated variants regulate cell polarity genes LAMA1 and CRB2. Knockdown of lama1 or crb2 in zebrafish embryos causes a defect in pancreas morphogenesis and impairs islet cell development. Together, our findings reveal that a subset of T2D risk variants specifically affects pancreatic developmental programs, suggesting that dysregulation of developmental processes can predispose to T2D.

Low PRRX1 expression and high ZEB1 expression are significantly correlated with epithelial-mesenchymal transition and tumor angiogenesis in non-small cell lung cancer

BACKGROUND

Paired related homeobox 1 (PRRX1) and zinc finger E-box binding homeobox 1 (ZEB1) have been observed to play a vital role in the epithelial-mesenchymal transition (EMT) process in different types of cancer. The microvessel density (MVD) is the most common indicator used to quantify angiogenesis. This study aimed to investigate expression of PRRX1 and ZEB1 in non-small cell lung cancer (NSCLC) and to explore associations between these factors and tumor prognosis, EMT markers and angiogenesis.

METHODS

Data for a total of 111 surgically resected NSCLC cases from January 2013 to December 2014 were collected. We used an immunohistochemical method to detect expression levels of PRRX1, ZEB1, and E-cadherin, and to assess MVD (marked by CD34 staining). SPSS 26.0 was employed to evaluate the connection between these factors and clinical and histopathological features, overall survival (OS) and tumor angiogenesis.

RESULTS

PRRX1 expression was obviously lower in tumor samples than in control samples. Low expression of PRRX1, which was more common in the high-MVD group than in the low-MVD group (P = .009), correlated positively with E-cadherin expression (P < .001). Additionally, we showed that ZEB1 was expressed at higher levels in tumor samples than in normal samples. High expression of ZEB1 was associated negatively with E-cadherin expression (P < .001) and positively associated with high MVD (P = .001). Based on Kaplan-Meier and multivariate survival analyses, we found that PRRX1, ZEB1, E-cadherin and the MVD had predictive value for OS in NSCLC patients.

CONCLUSIONS

These findings suggest that PRRX1 and ZEB1 may serve as novel prognostic biomarkers and potential therapeutic targets.

Molecular and evolutionary processes generating variation in gene expression

Heritable variation in gene expression is common within and between species. This variation arises from mutations that alter the form or function of molecular gene regulatory networks that are then filtered by natural selection. High-throughput methods for introducing mutations and characterizing their cis- and trans-regulatory effects on gene expression (particularly, transcription) are revealing how different molecular mechanisms generate regulatory variation, and studies comparing these mutational effects with variation seen in the wild are teasing apart the role of neutral and non-neutral evolutionary processes. This integration of molecular and evolutionary biology allows us to understand how the variation in gene expression we see today came to be and to predict how it is most likely to evolve in the future.

COL6A3 expression in adipose tissue cells is associated with levels of the homeobox transcription factor PRRX1

Fibrillar collagen COL6α3 in adipose tissue has been associated with obesity, inflammation, insulin resistance and cancer. We here aimed to identify novel transcriptional regulators of COL6A3 expression. Based on a transcriptome dataset of adipose tissue, we identified strong correlations for 56 genes with COL6A3 mRNA, including targets of TGF-β/SMAD signaling. Among the identified candidates, the homeobox transcription factor PRRX1 showed a particularly striking co-expression with COL6A3, validated across several different cohorts, including patients with extreme obesity, insulin sensitive and resistant obesity (subcutaneous and omental), after profound fat loss (subcutaneous), and lean controls (subcutaneous). In human and mouse adipose cells, PRRX1 knockdown reduced COL6A3 mRNA and PRRX1 overexpression transactivated a reporter construct with the endogenous human COL6A3 promoter. Stable PRRX1 overexpression in 3T3-L1 cells induced Col6a3 mRNA threefold specifically after adipogenic induction, whereas TGF-β1 treatment upregulated Col6a3 mRNA also in the preadipocyte state. Interestingly, pro-inflammatory stimulus (i.e., TNF-α treatment) decreased PRRX1-mediated Col6a3 transactivation and mRNA expression, supporting a role for this mechanism in the regulation of adipose tissue inflammation. In conclusion, we identified the homeobox factor PRRX1 as a novel transcriptional regulator associated with COL6A3 expression, providing new insight into the regulatory mechanisms of altered adipose tissue function in obesity and insulin resistance.

A lead candidate functional single nucleotide polymorphism within the WARS2 gene associated with waist-hip-ratio does not alter RNA stability

We have prioritised a single nucleotide polymorphism (SNP) rs2645294 as one candidate functional SNP in the TBX15-WARS2 waist-hip-ratio locus using posterior probability analysis. This SNP is located in the 3' untranslated region of the WARS2 (tryptophanyl tRNA synthetase 2, mitochondrial) gene with which it has an expression quantitative trait in subcutaneous white adipose tissue. We show that transcripts of the WARS2 gene in a human white adipose cell line, heterozygous for the rs2645294 SNP, showed allelic imbalance. We tested whether the rs2645294 SNP altered WARS2 RNA stability using three different methods: actinomycin-D inhibition and RNA decay, mature and nascent RNA analysis and luciferase reporter assays. We found no evidence of a difference in RNA stability between the rs2645294 alleles indicating that the allelic expression imbalance was likely due to transcriptional regulation.

A MicroRNA Linking Human Positive Selection and Metabolic Disorders

Positive selection in Europeans at the 2q21.3 locus harboring the lactase gene has been attributed to selection for the ability of adults to digest milk to survive famine in ancient times. However, the 2q21.3 locus is also associated with obesity and type 2 diabetes in humans, raising the possibility that additional genetic elements in the locus may have contributed to evolutionary adaptation to famine by promoting energy storage, but which now confer susceptibility to metabolic diseases. We show here that the miR-128-1 microRNA, located at the center of the positively selected locus, represents a crucial metabolic regulator in mammals. Antisense targeting and genetic ablation of miR-128-1 in mouse metabolic disease models result in increased energy expenditure and amelioration of high-fat-diet-induced obesity and markedly improved glucose tolerance. A thrifty phenotype connected to miR-128-1-dependent energy storage may link ancient adaptation to famine and modern metabolic maladaptation associated with nutritional overabundance.

Genetically programmed changes in transcription of the novel progranulin regulator

Abstract

Progranulin is a glycoprotein marking chronic inflammation in obesity and type 2 diabetes. Previous studies suggested PSRC1 (proline and serine rich coiled-coil 1) to be a target of genetic variants associated with serum progranulin levels. We aimed to identify potentially functional variants and characterize their role in regulation of PSRC1. Phylogenetic module complexity analysis (PMCA) prioritized four polymorphisms (rs12740374, rs629301, rs660240, rs7528419) altering transcription factor binding sites with an overall score for potential regulatory function of S_all > 7.0. The effects of these variants on transcriptional activity and binding of transcription factors were tested by luciferase reporter and electrophoretic mobility shift assays (EMSA). In parallel, blood DNA promoter methylation of two regions was tested in subjects with a very high (N = 100) or a very low (N = 100) serum progranulin. Luciferase assays revealed lower activities in vectors carrying the rs629301-A compared with the C allele. Moreover, EMSA indicated a different binding pattern for the two rs629301 alleles, with an additional prominent band for the A allele, which was finally confirmed with the supershift for the Yin Yang 1 transcription factor (YY1). Subjects with high progranulin levels manifested a significantly higher mean DNA methylation (P < 1 × 10⁻⁷) in one promoter region, which was in line with a significantly lower PSRC1 mRNA expression levels in blood (P = 1 × 10⁻³). Consistently, rs629301-A allele was associated with lower PSRC1 mRNA expression (P < 1 × 10⁻⁷). Our data suggest that the progranulin-associated variant rs629301 modifies the transcription of PSRC1 through alteration of YY1 binding capacity. DNA methylation studies further support the role of PSRC1 in regulation of progranulin serum levels.

Key messages

PSRC1 (proline and serine rich coiled-coil 1) SNPs are associated with serum progranulin levels.

rs629301 regulates PSRC1 expression by affecting Yin Yang 1 transcription factor (YY1) binding.

PSRC1 is also epigenetically regulated in subjects with high progranulin levels.

Electronic supplementary material

The online version of this article (10.1007/s00109-020-01942-7) contains supplementary material, which is available to authorized users.

The Rho GTPase RND3 regulates adipocyte lipolysis

BACKGROUND

Adipose tissue plays a crucial role in diet- and obesity-related insulin resistance, with implications for several metabolic diseases. Identification of novel target genes and mechanisms that regulate adipocyte function could lead to improved treatment strategies. RND3 (RhoE/Rho8), a Rho-related GTP-binding protein that inhibits Rho kinase (ROCK) signaling, has been linked to diverse diseases such as apoptotic cardiomyopathy, heart failure, cancer and type 2 diabetes, in part by regulating cytoskeleton dynamics and insulin-mediated glucose uptake.

RESULTS

We here investigated the expression of RND3 in adipose tissue in human obesity, and discovered a role for RND3 in regulating adipocyte metabolism. In cross-sectional and prospective studies, we observed 5-fold increased adipocyte levels of RND3 mRNA in obesity, reduced levels after surgery-induced weight loss, and positive correlations of RND3 mRNA with adipocyte size and surrogate measures of insulin resistance (HOMA2-IR and circulating triglyceride/high-density lipoprotein cholesterol (TAG/HDL-C) ratio). By screening for RND3-dependent gene expression following siRNA-mediated RND3 knockdown in differentiating human adipocytes, we found downregulation of inflammatory genes and upregulation of genes related to adipocyte ipolysis and insulin signaling. Treatment of adipocytes with tumor necrosis factor alpha (TNFα), lipopolysaccharide (LPS), hypoxia or cAMP analogs increased RND3 mRNA levels 1.5-2-fold. Functional assays in primary human adipocytes confirmed that RND3 knockdown reduces cAMP- and isoproterenol-induced lipolysis, which were mimicked by treating cells with ROCK inhibitor. This effect could partly be explained by reduced protein expression of adipose triglyceride lipase (ATGL) and phosphorylated hormone-sensitive lipase (HSL).

CONCLUSION

We here uncovered a novel differential expression of adipose RND3 in obesity and insulin resistance, which may at least partly depend on a causal effect of RND3 on adipocyte lipolysis.

PRRX1-induced epithelial-to-mesenchymal transition in salivary adenoid cystic carcinoma activates the metabolic reprogramming of free fatty acids to promote invasion and metastasis

Objectives

Increasing evidences demonstrate a close correlation between epithelial‐to‐mesenchymal transition (EMT) induction and cancer lipid metabolism. However, the molecular mechanisms have not been clarified.

Materials and methods

In our study, the relative expression level of PRRX1 was detected, its relationship with free fatty acid (FFA) and PPARG2 was analysed in 85 SACC tissues and 15 salivary glands from the benign salivary tumours. We also compared the FFAs composition and levels in these SACC cells. PPARG2 was detected in PRRX1‐induced FFAs treatment as well as Src and MMP‐9 were detected in FFAs treatment–induced invasion and migration of SACC cells, and ChIP test was performed to identify the target interactions.

Results

Our data showed that overexpression of PRRX1 induced EMT and facilitated the invasion and migration of SACC cells, and PRRX1 expression was closely associated with high FFAs level and poor prognosis of SACC patients. Furthermore, PRRX1 silence led to the increase of PPARG2 and the reduction of FFAs level and the migration and invasion of SACC cells. And inhibition of PPARG2 rescued FFAs level and migration and invasion capabilities of SACC cells. Free fatty acids treatment induced an increase of Stat5‐DNA binding activity via Src‐ and MMP‐9‐dependent pathway.

Conclusions

Collectively, our findings showed that the PRRX1/PPARG2/FFAs signalling in SACC was important for accelerating tumour metastasis through the induction of EMT and the metabolic reprogramming of FFAs.

A 16q22.1 variant confers susceptibility to colorectal cancer as a distal regulator of ZFP90

Genome-wide association studies (GWASs) implicate 16q22.1 locus in risk for colorectal cancer (CRC). However, the underlying oncogenic mechanisms remain unknown. Here, through comprehensive filtration, we prioritized rs7198799, a common SNP in the second intron of the CDH1, as the putative causal variant. In addition, we found an association of CRC-risk allele C of rs7198799 with elevated transcript level of biological plausible candidate gene ZFP90 via expression quantitative trait loci analysis. Mechanistically, causal variant rs7198799 resides in an enhancer element and remotely regulate ZFP90 expression by targeting the transcription factor NFATC2. Remarkably, CRISPR/Cas9-guided single-nucleotide editing demonstrated the direct effect of rs7198799 on ZFP90 expression and CRC cellular malignant phenotype. Furthermore, ZFP90 affects several oncogenic pathways, including BMP4, and promotes carcinogenesis in patients and in animal models with ZFP90 specific genetic manipulation. Taken together, these findings reveal a risk SNP-mediated long-range regulation on the NFATC2-ZFP90-BMP4 pathway underlying the initiation of CRC.

Dynamic modelling of an ACADS genotype in fatty acid oxidation - Application of cellular models for the analysis of common genetic variants

Background

Genome-wide association studies of common diseases or metabolite quantitative traits often identify common variants of small effect size, which may contribute to phenotypes by modulation of gene expression. Thus, there is growing demand for cellular models enabling to assess the impact of gene regulatory variants with moderate effects on gene expression. Mitochondrial fatty acid oxidation is an important energy metabolism pathway. Common noncoding acyl-CoA dehydrogenase short chain (ACADS) gene variants are associated with plasma C4-acylcarnitine levels and allele-specific modulation of ACADS expression may contribute to the observed phenotype.

Methods and findings

We assessed ACADS expression and intracellular acylcarnitine levels in human lymphoblastoid cell lines (LCL) genotyped for a common ACADS variant associated with plasma C4-acylcarnitine and found a significant genotype-dependent decrease of ACADS mRNA and protein. Next, we modelled gradual decrease of ACADS expression using a tetracycline-regulated shRNA-knockdown of ACADS in Huh7 hepatocytes, a cell line with high fatty acid oxidation-(FAO)-capacity. Assessing acylcarnitine flux in both models, we found increased C4-acylcarnitine levels with decreased ACADS expression levels. Moreover, assessing time-dependent changes of acylcarnitine levels in shRNA-hepatocytes with altered ACADS expression levels revealed an unexpected effect on long- and medium-chain fatty acid intermediates.

Conclusions

Both, genotyped LCL and regulated shRNA-knockdown are valuable tools to model moderate, gradual gene-regulatory effects of common variants on cellular phenotypes. Decreasing ACADS expression levels modulate short and surprisingly also long/medium chain acylcarnitines, and may contribute to increased plasma acylcarnitine levels.

Single cell transcriptomics based-MacSpectrum reveals novel macrophage activation signatures in diseases

Adipose tissue macrophages (ATM) are crucial for maintaining adipose tissue homeostasis and mediating obesity-induced metabolic abnormalities, including prediabetic conditions and type 2 diabetes mellitus. Despite their key functions in regulating adipose tissue metabolic and immunologic homeostasis under normal and obese conditions, a high-resolution transcriptome annotation system that can capture ATM multifaceted activation profiles has not yet been developed. This is primarily attributed to the complexity of their differentiation/activation process in adipose tissue and their diverse activation profiles in response to microenvironmental cues. Although the concept of multifaceted macrophage action is well-accepted, no current model precisely depicts their dynamically regulated in vivo features. To address this knowledge gap, we generated single-cell transcriptome data from primary bone marrow-derived macrophages under polarizing and non-polarizing conditions to develop new high-resolution algorithms. The outcome was creation of a two-index platform, MacSpectrum (https://macspectrum.uconn.edu), that enables comprehensive high-resolution mapping of macrophage activation states from diverse mixed cell populations. MacSpectrum captured dynamic transitions of macrophage subpopulations under both in vitro and in vivo conditions. Importantly, MacSpectrum revealed unique "signature" gene sets in ATMs and circulating monocytes that displayed significant correlation with BMI and homeostasis model assessment of insulin resistance (HOMA-IR) in obese human patients. Thus, MacSpectrum provides unprecedented resolution to decode macrophage heterogeneity and will open new areas of clinical translation.

Investigation of allele-specific expression of genes involved in adipogenesis and lipid metabolism suggests complex regulatory mechanisms of PPARGC1A expression in porcine fat tissues

Background

The expression of genes involved in regulating adipogenesis and lipid metabolism may affect economically important fatness traits in pigs. Allele-specific expression (ASE) reflects imbalance between allelic transcript levels and can be used to identify underlying cis-regulatory elements. ASE has not yet been intensively studied in pigs. The aim of this investigation was to analyze the differential allelic expression of four genes, PPARA, PPARG, SREBF1, and PPARGC1A, which are involved in the regulation of fat deposition in porcine subcutaneous and visceral fat and longissimus dorsi muscle.

Results

Quantification of allelic proportions by pyrosequencing revealed that both alleles of PPARG and SREBF1 are expressed at similar levels. PPARGC1A showed the greatest ASE imbalance in fat deposits in Polish Large White (PLW), Polish Landrace and Pietrain pigs; and PPARA in PLW pigs. Significant deviations of mean PPARGC1A allelic transcript ratio between cDNA and genomic DNA were detected in all tissues, with the most pronounced difference (p < 0.001) in visceral fat of PLW pigs. To search for potential cis-regulatory elements affecting ASE in the PPARGC1A gene we analyzed the effects of four SNPs (rs337351686, rs340650517, rs336405906 and rs345224049) in the promoter region, but none were associated with ASE in the breeds studied. DNA methylation analysis revealed significant CpG methylation differences between samples showing balanced (allelic transcript ratio ≈1) and imbalanced allelic expression for CpG site at the genomic position in chromosome 8 (SSC8): 18527678 in visceral fat (p = 0.017) and two CpG sites (SSC8:18525215, p = 0.030; SSC8:18525237, p = 0.031) in subcutaneous fat.

Conclusions

Our analysis of differential allelic expression suggests that PPARGC1A is subjected to cis-regulation in porcine fat tissues. Further studies are necessary to identify other regulatory elements localized outside the PPARGC1A proximal promoter region.

Electronic supplementary material

The online version of this article (10.1186/s12863-018-0696-6) contains supplementary material, which is available to authorized users.

Computational analyses of obesity associated loci generated by genome-wide association studies

OBJECTIVES

Genome-wide association studies (GWASs) have discovered associations of numerous SNPs and genes with obesity. However, the underlying molecular mechanisms through which these SNPs and genes affect the predisposition to obesity remain not fully understood. Aims of our study are to comprehensively characterize obesity GWAS SNPs and genes through computational approaches.

METHODS

For obesity GWAS identified SNPs, functional annotation, effects on miRNAs binding and impact on protein phosphorylation were performed via RegulomeDB and 3DSNP, miRNASNP, and the PhosSNP 1.0 database, respectively. For obesity associated genes, protein-protein interaction network construction, gene ontology and pathway enrichment analyses were performed by STRING, PANTHER and STRING, respectively.

RESULTS

A total of 445 SNPs are significantly associated with obesity related phenotypes at threshold P < 5×10-8. A number of SNPs were eQTLs for obesity associated genes, some SNPs located at binding sites of obesity related transcription factors. SNPs that might affect miRNAs binding and protein phosphorylation were identified. Protein-protein interaction network analysis identified the highly-interconnected "hub" genes. Obesity associated genes mainly involved in metabolic process and catalytic activity, and significantly enriched in 15 signal pathways.

CONCLUSIONS

Our results provided the targets for follow-up experimental testing and further shed new light on obesity pathophysiology.

Senescence Alters PPARγ (Peroxisome Proliferator–Activated Receptor Gamma)-Dependent Fatty Acid Handling in Human Adipose Tissue Microvascular Endothelial Cells and Favors Inflammation

Objective—

Adipose tissue (AT) dysfunction associated with obesity or aging is a major cause for lipid redistribution and the progression of cardiometabolic disorders. Our goal is to decipher the contribution of human AT microvascular endothelial cells (ECs) in the maintenance of fatty acid (FA) fluxes and the impact of senescence on their function.

Approach and Results—

We used freshly isolated primary microvascular ECs from human AT. Our data identified the endothelial FA handling machinery including FATPs (FA transport proteins) FATP1, FATP3, FATP4, and CD36 as well as FABP4 (FA binding protein 4). We showed that PPARγ (peroxisome proliferator–activated receptor gamma) regulates the expression of FATP1, CD36, and FABP4 and is a major regulator of FA uptake in human AT EC (hATEC). We provided evidence that endothelial PPARγ activity is modulated by senescence. Indeed, the positive regulation of FA transport by PPARγ agonist was abolished, whereas the emergence of an inflammatory response was favored in senescent hATEC. This was associated with the retention of nuclear FOXO1 (forkhead box protein O1), whereas nuclear PPARγ translocation was impaired.

Conclusions—

These data support the notion that PPARγ is a key regulator of primary hATEC function including FA handling and inflammatory response. However, the outcome of PPARγ activation is modulated by senescence, a phenomenon that may impact the ability of hATEC to properly respond to and handle lipid fluxes. Finally, our work highlights the role of hATEC in the regulation of FA fluxes and reveals that dysfunction of these cells with accelerated aging is likely to participate to AT dysfunction and the redistribution of lipids.

Emerging applications of genome-editing technology to examine functionality of GWAS-associated variants for complex traits

Over the last decade, genome-wide association studies (GWAS) have propelled the discovery of thousands of loci associated with complex diseases. The focus is now turning toward the function of these association signals, determining the causal variant(s) among those in strong linkage disequilibrium, and identifying their underlying mechanisms, such as long-range gene regulation. Genome-editing techniques utilizing zinc-finger nucleases (ZFN), transcription activator-like effector nucleases (TALENs), and clustered regularly-interspaced short palindromic repeats with Cas9 nuclease (CRISPR-Cas9) are becoming the tools of choice to establish functionality for these variants, due to the ability to assess effects of single variants in vivo. This review will discuss examples of how these technologies have begun to aid functional analysis of GWAS loci for complex traits such as cardiovascular disease, Type 2 diabetes, cancer, obesity, and autoimmune disease. We focus on analysis of variants occurring within noncoding genomic regions, as these comprise the majority of GWAS variants, providing the greatest challenges to determining functionality, and compare editing strategies that provide different levels of evidence for variant functionality. The review describes molecular insights into some of these potentially causal variants and how these may relate to the pathology of the trait and look toward future directions for these technologies in post-GWAS analysis, such as base-editing.

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

Integrating ChIP-seq with other functional genomics data

Transcription is regulated by transcription factor (TF) binding at promoters and distal regulatory elements and histone modifications that control the accessibility of these elements. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) has become the standard assay for identifying genome-wide protein-DNA interactions in vitro and in vivo. As large-scale ChIP-seq data sets have been collected for different TFs and histone modifications, their potential to predict gene expression can be used to test hypotheses about the mechanisms of gene regulation. In addition, complementary functional genomics assays provide a global view of chromatin accessibility and long-range cis-regulatory interactions that are being combined with TF binding and histone remodeling to study the regulation of gene expression. Thus, ChIP-seq analysis is now widely integrated with other functional genomics assays to better understand gene regulatory mechanisms. In this review, we discuss advances and challenges in integrating ChIP-seq data to identify context-specific chromatin states associated with gene activity. We describe the overall computational design of integrating ChIP-seq data with other functional genomics assays. We also discuss the challenges of extending these methods to low-input ChIP-seq assays and related single-cell assays.

Identification of Disease-Related Genes Using a Genome-Wide Association Study Approach

Genome-wide association studies (GWAS) provide a hypothesis-free approach to discover genetic variants contributing to the risk of a certain disease or disease-related trait. Ongoing efforts to annotate the human genome have helped to localize disease-causing variants and point to mechanisms by which genetic variants might exert functional effects. By integrating bioinformatics approaches with in vivo and in vitro genomic strategies to predict and subsequently validate the functional roles of GWAS-identified variants, disease-related pathways can be characterized, providing new possibilities for therapeutic intervention. Here, we describe a basic workflow, from sample preparation to data analysis, for performing a GWAS to identify disease genes. We also discuss resources for the annotation and interpretation of GWAS results.

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10^-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

The genetic underpinnings of body fat distribution

Obesity, defined as a body mass index (BMI) ≥ 30 kg/m², has reached epidemic proportions; people who are overweight (BMI > 25 kg/m²) or obese now comprise more than 25% of the world's population. Obese individuals have a higher risk of comorbidity development including type 2 diabetes, cardiovascular disease, cancer, and fertility complications. Areas covered: The study of monogenic and syndromic forms of obesity have revealed a small number of genes key to metabolic perturbations. Further, obesity and body shape in the general population are highly heritable phenotypes. Study of obesity at the population level, through genome-wide association studies of BMI and waist-to-hip ratio (WHR), have revealed > 150 genomic loci that associate with these traits, and highlight the role of adipose tissue and the central nervous system in obesity-related traits. Studies in animal models and cell lines have helped further elucidate the potential biological mechanisms underlying obesity. In particular, these studies implicate adipogenesis and expansion of adipose tissue as key biological pathways in obesity and weight gain. Expert commentary: Further work, including a focus on integrating genetic and additional genomic data types, as well as modeling obesity-like features in vitro, will be crucial in translating genome-wide association signals to the causal mechanisms driving disease.

Prioritising Causal Genes at Type 2 Diabetes Risk Loci

PURPOSE OF REVIEW

Genome-wide association studies (GWAS) for type 2 diabetes (T2D) risk have identified a large number of genetic loci associated with disease susceptibility. However, progress moving from association signals through causal genes to functional understanding has so far been slow, hindering clinical translation. This review discusses the benefits and limitations of emerging, unbiased approaches for prioritising causal genes at T2D risk loci.

RECENT FINDINGS

Candidate causal genes can be identified by a number of different strategies that rely on genetic data, genomic annotations, and functional screening of selected genes. To overcome the limitations of each particular method, integration of multiple data sets is proving essential for establishing confidence in the prioritised genes. Previous studies have also highlighted the need to support these efforts through identification of causal variants and disease-relevant tissues. Prioritisation of causal genes at T2D risk loci by integrating complementary lines of evidence promises to accelerate our understanding of disease pathology and promote translation into new therapeutics.

Mechanisms of Type 2 Diabetes Risk Loci

PURPOSE OF REVIEW

Deciphering the mechanisms of type 2 diabetes (T2DM) risk loci can greatly inform on disease pathology. This review discusses current knowledge of mechanisms through which genetic variants influence T2DM risk and considerations for future studies.

RECENT FINDINGS

Over 100 T2DM risk loci to date have been identified. Candidate causal variants at risk loci map predominantly to non-coding sequence. Physiological, epigenomic and gene expression data suggest that variants at many known T2DM risk loci affect pancreatic islet regulation, although variants at other loci also affect protein function and regulatory processes in adipose, pre-adipose, liver, skeletal muscle and brain. The effects of T2DM variants on regulatory activity in these tissues appear largely, but not exclusively, due to altered transcription factor binding. Putative target genes of T2DM variants have been defined at an increasing number of loci and some, such as FTO, may entail several genes and multiple tissues. Gene networks in islets and adipocytes have been implicated in T2DM risk, although the molecular pathways of risk genes remain largely undefined. Efforts to fully define the mechanisms of T2DM risk loci are just beginning. Continued identification of risk mechanisms will benefit from combining genetic fine-mapping with detailed phenotypic association data, high-throughput epigenomics data from diabetes-relevant tissue, functional screening of candidate genes and genome editing of cellular and animal models.

Allele-specific quantitative proteomics unravels molecular mechanisms modulated by cis-regulatory PPARG locus variation

Genome-wide association studies identified numerous disease risk loci. Delineating molecular mechanisms influenced by cis-regulatory variants is essential to understand gene regulation and ultimately disease pathophysiology. Combining bioinformatics and public domain chromatin information with quantitative proteomics supports prediction of cis-regulatory variants and enabled identification of allele-dependent binding of both, transcription factors and coregulators at the type 2 diabetes associated PPARG locus. We found rs7647481A nonrisk allele binding of Yin Yang 1 (YY1), confirmed by allele-specific chromatin immunoprecipitation in primary adipocytes. Quantitative proteomics also found the coregulator RING1 and YY1 binding protein (RYBP) whose mRNA levels correlate with improved insulin sensitivity in primary adipose cells carrying the rs7647481A nonrisk allele. Our findings support a concept with diverse cis-regulatory variants contributing to disease pathophysiology at one locus. Proteome-wide identification of both, transcription factors and coregulators, can profoundly improve understanding of mechanisms underlying genetic associations.

A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation

Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension). We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences. We obtained experimental data on the expression of 22 genes across five organs, over a time span that encompassed the development of autonomic nervous system dysfunction and hypertension. We pursued a unique approach for identification of continuous-time models that jointly described the dynamics and structure of multi-organ networks by estimating a sparse subset of ∼12,000 possible gene regulatory interactions. Our analyses revealed that an autonomic dysfunction-specific multi-organ sequence of gene expression activation patterns was associated with a distinct gene regulatory network. We analyzed the model structures for adaptation motifs, and identified disease-specific network motifs involving genes that exhibited aberrant temporal dynamics. Bioinformatic analyses identified disease-specific single nucleotide variants within or near transcription factor binding sites upstream of key genes implicated in maintaining physiological homeostasis. Our approach illustrates a novel framework for investigating the pathogenesis through model-based analysis of multi-organ system dynamics and network properties. Our results yielded novel candidate molecular targets driving the development of cardiovascular disease, metabolic syndrome, and immune dysfunction.

Complex diseases such as hypertension often involve maladaptive autonomic nervous system control over the cardiovascular, renal, hepatic, immune, and endocrine systems. We studied the pathogenesis of physiological homeostasis by examining the temporal dynamics of gene expression levels from multiple organs in an animal model of autonomic dysfunction characterized by cardiovascular disease, metabolic dysregulation, and immune system aberrations. We employed a data-driven modeling approach to jointly predict continuous gene expression dynamics and gene regulatory interactions across organs in the disease and control phenotypes. We combined our analyses of multi-organ gene regulatory network dynamics and connectivity with bioinformatic analyses of genetic mutations that could regulate gene expression. Our multi-organ modeling approach to investigate the mechanisms of complex disease pathogenesis revealed novel candidates for therapeutic interventions against the development and progression of complex diseases involving autonomic nervous system dysfunction.

10 Years of GWAS Discovery: Biology, Function, and Translation

Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.

Functional annotation of Alzheimer's disease associated loci revealed by GWASs

Genome-wide association studies (GWASs) discovered a number of SNPs and genes associated with Alzheimer's disease (AD). However, how these SNPs and genes influence the liability to AD is not fully understood. We deployed computational approaches to explore the function and action mechanisms of AD -related SNPs and genes identified by GWASs, including the effects of 195 GWAS lead SNPs and 338 proxy SNPs on miRNAs binding and protein phosphorylation, their RegulomeDB and 3DSNP scores, and gene ontology, pathway enrichment and protein-protein interaction network of 126 AD-associated genes. Our computational analysis identified 6 lead SNPs (rs10119, rs1048699, rs148763909, rs610932, rs6857 and rs714948) and 2 proxy SNPs (rs12539172 and rs2847655) that potentially impacted the miRNA binding. Lead SNP rs2296160 and proxy SNPs rs679620 and rs2228145 were identified as PhosSNPs potentially influencing protein phosphorylation. AD-associated genes showed enrichment of “regulation of beta-amyloid formation”, “regulation of neurofibrillary tangle assembly”, “leukocyte mediated immunity” and “protein-lipid complex assembly” signaling pathway. Protein-protein interaction network and functional module analyses identified highly-interconnected “hub” genes (APOE, PICALM, BIN1, ABCA7, CD2AP, CLU, CR1, MS4A4E and MS4A6A) and bottleneck genes (APOE, TOMM40, NME8, PICALM, CD2AP, ZCWPW1, FAM180B, GAB2 and PTK2B) that created three tight subnetworks. Our results provided the targets for further experimental assessment and further insight on AD pathophysiology.

Computational analyses of type 2 diabetes-associated loci identified by genome-wide association studies

BACKGROUND

Genome-wide association studies (GWAS) of type 2 diabetes (T2D) have discovered a number of loci that contribute to susceptibility to the disease. Future challenges include elucidation of functional mechanisms through which these GWAS-identified loci modulate T2D disease risk. The aim of the present study was to comprehensively characterize T2D associated single nucleotide polymorphisms (SNPs) and genes through computational approaches.

METHODS

Computational biology approaches used in the present study included comparative genomic analyses and functional annotation using GWAS3D and RegulomeDB, investigation of the effects of T2D-associated SNPs on miRNA binding and protein phosphorylation, and gene ontology, pathway enrichment, protein-protein interaction (PPI) networks and functional module analysis of T2D-associated genes from previously published GWAS.

RESULTS

Computational analysis identified a number of T2D GWAS-associated SNPs that were located at protein binding sites, including CCCTC-binding factor (CTCF), E1A binding protein p300 (EP300), hepatocyte nuclear factor 4alpha (HNF4A), transcription factor 7 like 2 (TCF7L2), forkhead box A1 (FOXA1) and A2 (FOXA2), and potentially affected the binding of miRNAs and protein phosphorylation. Pathway enrichment analysis confirmed two well-known maturity onset diabetes of the young and T2D pathways, whereas PPI network analysis identified highly interconnected "hub" genes, such as TCF7L2, melatonin receptor 1B (MTNR1B), and solute carrier family 30 (zinc transporter), member 8 (SLC30A8), that created two tight subnetworks.

CONCLUSIONS

The results provide objectives and clues for future experimental studies and further insights into the molecular pathogenesis of T2D.

Connecting genetic risk to disease end points through the human blood plasma proteome

Genome-wide association studies (GWAS) with intermediate phenotypes, like changes in metabolite and protein levels, provide functional evidence to map disease associations and translate them into clinical applications. However, although hundreds of genetic variants have been associated with complex disorders, the underlying molecular pathways often remain elusive. Associations with intermediate traits are key in establishing functional links between GWAS-identified risk-variants and disease end points. Here we describe a GWAS using a highly multiplexed aptamer-based affinity proteomics platform. We quantify 539 associations between protein levels and gene variants (pQTLs) in a German cohort and replicate over half of them in an Arab and Asian cohort. Fifty-five of the replicated pQTLs are located in trans. Our associations overlap with 57 genetic risk loci for 42 unique disease end points. We integrate this information into a genome-proteome network and provide an interactive web-tool for interrogations. Our results provide a basis for novel approaches to pharmaceutical and diagnostic applications.

Individual genetic variation can affect the levels of protein in blood, but detailed data sets linking these two types of data are rare. Here, the authors carry out a genome-wide association study of levels of over a thousand different proteins, and describe many new SNP-protein interactions.

The Genetics of Transcription Factor DNA Binding Variation

Most complex trait-associated variants are located in non-coding regulatory regions of the genome, where they have been shown to disrupt transcription factor (TF)-DNA binding motifs. Variable TF-DNA interactions are therefore increasingly considered as key drivers of phenotypic variation. However, recent genome-wide studies revealed that the majority of variable TF-DNA binding events are not driven by sequence alterations in the motif of the studied TF. This observation implies that the molecular mechanisms underlying TF-DNA binding variation and, by extrapolation, inter-individual phenotypic variation are more complex than originally anticipated. Here, we summarize the findings that led to this important paradigm shift and review proposed mechanisms for local, proximal, or distal genetic variation-driven variable TF-DNA binding. In addition, we discuss the biomedical implications of these findings for our ability to dissect the molecular role(s) of non-coding genetic variants in complex traits, including disease susceptibility.

Prospective functional classification of all possible missense variants in PPARG

Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty. For example, mutations in PPARG cause Mendelian lipodystrophy and increase risk of type 2 diabetes (T2D). Although approximately 1 in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants, we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single-amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning. When applied to 55 new missense variants identified in population-based and clinical sequencing, the classifier annotated 6 variants as pathogenic; these were subsequently validated by single-variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes.

Epigenomic and transcriptional control of insulin resistance

Insulin resistance is one of the defining features of type 2 diabetes and the metabolic syndrome and accompanies many other clinical conditions, ranging from obesity to lipodystrophy to glucocorticoid excess. Extraordinary efforts have gone into defining the mechanisms that underlie insulin resistance, with most attention focused on altered signalling as well as mitochondrial and endoplasmic reticulum stress. Here, nuclear mechanisms of insulin resistance, including transcriptional and epigenomic effects, will be discussed. Three levels of control involving transcription factors, transcriptional cofactors, and chromatin-modifying enzymes will be considered. Well-studied examples of the first include PPAR-γ in adipose tissue and the glucocorticoid receptor and FoxO1 in a variety of insulin-sensitive tissues. These proteins work in concert with cofactors such as PGC-1α and CRTC2, and chromatin-modifying enzymes including DNA methyltransferases and histone acetyltransferases, to regulate key genes that promote insulin-stimulated glucose uptake, gluconeogenesis or other pathways that affect systemic insulin action. Furthermore, genetic variation associated with increased risk of type 2 diabetes is often related to altered transcription factor binding, either by affecting the transcription factor itself, or more commonly by changing the binding affinity of a noncoding regulatory region. Finally, several avenues for therapeutic exploitation in the battle against metabolic disease will be discussed, including small-molecule inhibitors and activators of these factors and their related pathways.