A regulatory element associated to NAFLD in the promoter of DIO1 controls LDL-C, HDL-C and triglycerides in hepatic cells.

BACKGROUND: Genome-wide association studies (GWAS) have identified genetic variants linked to fat metabolism and related traits, but rarely pinpoint causative variants. This limitation arises from GWAS not considering functional implications of noncoding variants that can affect transcription factor binding and potentially regulate gene expression. The aim of this study is to investigate a candidate noncoding functional variant within a genetic locus flagged by a GWAS SNP associated with non-alcoholic fatty liver disease (NAFLD), a condition characterized by liver fat accumulation in non-alcohol consumers. METHODS: CRISPR-Cas9 gene editing in HepG2 cells was used to modify the regulatory element containing the candidate functional variant linked to NAFLD. Global gene expression in mutant cells was assessed through RT-qPCR and targeted transcriptomics. A phenotypic assay measured lipid droplet accumulation in the CRISPR-Cas9 mutants. RESULTS: The candidate functional variant, rs2294510, closely linked to the NAFLD-associated GWAS SNP rs11206226, resided in a regulatory element within the DIO1 gene's promoter region. Altering this element resulted in changes in transcription factor binding sites and differential expression of candidate target genes like DIO1, TMEM59, DHCR24, and LDLRAD1, potentially influencing the NAFLD phenotype. Mutant HepG2 cells exhibited increased lipid accumulation, a hallmark of NAFLD, along with reduced LDL-C, HDL-C and elevated triglycerides. CONCLUSIONS: This comprehensive approach, that combines genome editing, transcriptomics, and phenotypic assays identified the DIO1 promoter region as a potential enhancer. Its activity could regulate multiple genes involved in the NAFLD phenotype or contribute to defining a polygenic risk score for enhanced risk assessment in NAFLD patients.

Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes, and normal tissues.

Environmental and genetic factors cause defects in pancreatic islets driving type 2 diabetes (T2D) together with the progression of multi-tissue insulin resistance. Mass spectrometry proteomics on samples from five key metabolic tissues of a cross-sectional cohort of 43 multi-organ donors provides deep coverage of their proteomes. Enrichment analysis of Gene Ontology terms provides a tissue-specific map of altered biological processes across healthy, prediabetes (PD), and T2D subjects. We find widespread alterations in several relevant biological pathways, including increase in hemostasis in pancreatic islets of PD, increase in the complement cascade in liver and pancreatic islets of PD, and elevation in cholesterol biosynthesis in liver of T2D. Our findings point to inflammatory, immune, and vascular alterations in pancreatic islets in PD that are hypotheses to be tested for potential contributions to hormonal perturbations such as impaired insulin and increased glucagon production. This multi-tissue proteomic map suggests tissue-specific metabolic dysregulations in T2D.

scSPLAT, a scalable plate-based protocol for single cell WGBS library preparation.

DNA methylation is a central epigenetic mark that has diverse roles in gene regulation, development, and maintenance of genome integrity. 5 methyl cytosine (5mC) can be interrogated at base resolution in single cells by using bisulfite sequencing (scWGBS). Several different scWGBS strategies have been described in recent years to study DNA methylation in single cells. However, there remain limitations with respect to cost-efficiency and yield. Herein, we present a new development in the field of scWGBS library preparation; single cell Splinted Ligation Adapter Tagging (scSPLAT). scSPLAT employs a pooling strategy to facilitate sample preparation at a higher scale and throughput than previously possible. We demonstrate the accuracy and robustness of the method by generating data from 225 single K562 cells and from 309 single liver nuclei and compare scSPLAT against other scWGBS methods.

Machine Learning-Based Analysis of Glioma Grades Reveals Co-Enrichment.

Gliomas develop and grow in the brain and central nervous system. Examining glioma grading processes is valuable for improving therapeutic challenges. One of the most extensive repositories storing transcriptomics data for gliomas is The Cancer Genome Atlas (TCGA). However, such big cohorts should be processed with caution and evaluated thoroughly as they can contain batch and other effects. Furthermore, biological mechanisms of cancer contain interactions among biomarkers. Thus, we applied an interpretable machine learning approach to discover such relationships. This type of transparent learning provides not only good predictability, but also reveals co-predictive mechanisms among features. In this study, we corrected the strong and confounded batch effect in the TCGA glioma data. We further used the corrected datasets to perform comprehensive machine learning analysis applied on single-sample gene set enrichment scores using collections from the Molecular Signature Database. Furthermore, using rule-based classifiers, we displayed networks of co-enrichment related to glioma grades. Moreover, we validated our results using the external glioma cohorts. We believe that utilizing corrected glioma cohorts from TCGA may improve the application and validation of any future studies. Finally, the co-enrichment and survival analysis provided detailed explanations for glioma progression and consequently, it should support the targeted treatment.

The Thioesterase ACOT1 as a Regulator of Lipid Metabolism in Type 2 Diabetes Detected in a Multi-Omics Study of Human Liver.

Type 2 diabetes (T2D) is characterized by pathophysiological alterations in lipid metabolism. One strategy to understand the molecular mechanisms behind these abnormalities is to identify cis-regulatory elements (CREs) located in chromatin-accessible regions of the genome that regulate key genes. In this study we integrated assay for transposase-accessible chromatin followed by sequencing (ATAC-seq) data, widely used to decode chromatin accessibility, with multi-omics data and publicly available CRE databases to identify candidate CREs associated with T2D for further experimental validations. We performed high-sensitive ATAC-seq in nine human liver samples from normal and T2D donors, and identified a set of differentially accessible regions (DARs). We identified seven DARs including a candidate enhancer for the ACOT1 gene that regulates the balance of acyl-CoA and free fatty acids (FFAs) in the cytoplasm. The relevance of ACOT1 regulation in T2D was supported by the analysis of transcriptomics and proteomics data in liver tissue. Long-chain acyl-CoA thioesterases (ACOTs) are a group of enzymes that hydrolyze acyl-CoA esters to FFAs and coenzyme A. ACOTs have been associated with regulation of triglyceride levels, fatty acid oxidation, mitochondrial function, and insulin signaling, linking their regulation to the pathogenesis of T2D. Our strategy integrating chromatin accessibility with DNA binding and other types of omics provides novel insights on the role of genetic regulation in T2D and is extendable to other complex multifactorial diseases.

Genome-wide association study of liver enzyme elevation in rheumatoid arthritis patients starting methotrexate.

Aim: To identify novel genetic variants predisposing to elevation of Alanine aminotransferase (ALT) in rheumatoid arthritis (RA) patients after initiation of methotrexate (MTX) treatment. Patients & methods: We performed genome-wide association studies in 198 RA patients starting MTX. Outcomes were maximum level of ALT and ALT >1.5-times the upper level of normal within the first 6 months of treatment. Results:RAVER2 (rs72675408) was significantly associated with maximum level of ALT (p = 4.36 × 10-8). This variant is in linkage disequilibrium with rs72675451, which is associated with differential expression of JAK1 and RAVER2. Conclusion: We found an association between ALT elevation and genetic variants that may regulate the expression of JAK1 and RAVER2. JAK1 encodes a janus kinase involved in the pathogenesis of RA.

Functional annotation of noncoding mutations in cancer.

In a cancer genome, the noncoding sequence contains the vast majority of somatic mutations. While very few are expected to be cancer drivers, those affecting regulatory elements have the potential to have downstream effects on gene regulation that may contribute to cancer progression. To prioritize regulatory mutations, we screened somatic mutations in the Pan-Cancer Analysis of Whole Genomes cohort of 2,515 cancer genomes on individual bases to assess their potential regulatory roles in their respective cancer types. We found a highly significant enrichment of regulatory mutations associated with the deamination signature overlapping a CpG site in the CCAAT/Enhancer Binding Protein ß recognition sites in many cancer types. Overall, 5,749 mutated regulatory elements were identified in 1,844 tumor samples from 39 cohorts containing 11,962 candidate regulatory mutations. Our analysis indicated 20 or more regulatory mutations in 5.5% of the samples, and an overall average of six per tumor. Several recurrent elements were identified, and major cancer-related pathways were significantly enriched for genes nearby the mutated regulatory elements. Our results provide a detailed view of the role of regulatory elements in cancer genomes.

Multifaceted regulation of hepatic lipid metabolism by YY1.

Recent studies suggested that dysregulated YY1 plays a pivotal role in many liver diseases. To obtain a detailed view of genes and pathways regulated by YY1 in the liver, we carried out RNA sequencing in HepG2 cells after YY1 knockdown. A rigid set of 2,081 differentially expressed genes was identified by comparing the YY1-knockdown samples (n = 8) with the control samples (n = 14). YY1 knockdown significantly decreased the expression of several key transcription factors and their coactivators in lipid metabolism. This is illustrated by YY1 regulating PPARA expression through binding to its promoter and enhancer regions. Our study further suggest that down-regulation of the key transcription factors together with YY1 knockdown significantly decreased the cooperation between YY1 and these transcription factors at various regulatory regions, which are important in regulating the expression of genes in hepatic lipid metabolism. This was supported by the finding that the expression of SCD and ELOVL6, encoding key enzymes in lipogenesis, were regulated by the cooperation between YY1 and PPARA/RXRA complex over their promoters.

Polymorphisms rs55710213 and rs56334587 regulate SCD1 expression by modulating HNF4A binding.

The stearoyl-CoA desaturase 1 (SCD1) gene at 10q24.31 encodes the rate limiting enzyme SCD1 that catalyzes the biosynthesis of monounsaturated fatty acids (MUFAs) from saturated fatty acids (SFAs). Dysregulated SCD1 activity has been observed in many human diseases including non-alcoholic fatty liver disease (NAFLD), obesity, hypertension, hyperlipidemia, metabolic syndrome and several types of cancer. HNF4A is a central regulator of glucose and lipid metabolism and previous studies suggested that it is deeply involved in regulating the SCD1 activity in the liver. However, the underlying mechanisms on whether and how SCD1 is regulated by HNF4A have not been explored in detail. In this study, we found that HNF4A regulates SCD1 expression by directly binding to the key regulatory regions in the SCD1 locus. Knocking down of HNF4A significantly downregulated the expression of SCD1. Variants rs55710213 and rs56334587 in intron 5 of SCD1 directly reside in a canonical HNF4A binding site. The GG haplotype of rs55710213 and rs56334587 is associated with decreased SCD1 activity by disrupting the binding of HNF4A, which further decreased the enhancer activity and SCD1 expression. In conclusion, our study demonstrated that SCD1 is directly regulated by HNF4A, which may be helpful in the understanding of the altered metabolic pathways in many diseases associated with dysregulated SCD1 or HNF4A or both.

Single nucleus transcriptomics data integration recapitulates the major cell types in human liver.

AIM: The aim of this study was to explore the benefits of data integration from different platforms for single nucleus transcriptomics profiling to characterize cell populations in human liver. METHODS: We generated single-nucleus RNA sequencing data from Chromium 10X Genomics and Drop-seq for a human liver sample. We utilized state of the art bioinformatics tools to undertake a rigorous quality control and to integrate the data into a common space summarizing the gene expression variation from the respective platforms, while accounting for known and unknown confounding factors. RESULTS: Analysis of single nuclei transcriptomes from both 10X and Drop-seq allowed identification of the major liver cell types, while the integrated set obtained enough statistical power to separate a small population of inactive hepatic stellate cells that was not characterized in either of the platforms. CONCLUSIONS: Integration of droplet-based single nucleus transcriptomics data enabled identification of a small cluster of inactive hepatic stellate cells that highlights the potential of our approach. We suggest single-nucleus RNA sequencing integrative approaches could be utilized to design larger and cost-effective studies.

Integration of whole-body [18F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes.

Alteration of various metabolites has been linked to type 2 diabetes (T2D) and insulin resistance. However, identifying significant associations between metabolites and tissue-specific phenotypes requires a multi-omics approach. In a cohort of 42 subjects with different levels of glucose tolerance (normal, prediabetes and T2D) matched for age and body mass index, we calculated associations between parameters of whole-body positron emission tomography (PET)/magnetic resonance imaging (MRI) during hyperinsulinemic euglycemic clamp and non-targeted metabolomics profiling for subcutaneous adipose tissue (SAT) and plasma. Plasma metabolomics profiling revealed that hepatic fat content was positively associated with tyrosine, and negatively associated with lysoPC(P-16:0). Visceral adipose tissue (VAT) and SAT insulin sensitivity (Ki), were positively associated with several lysophospholipids, while the opposite applied to branched-chain amino acids. The adipose tissue metabolomics revealed a positive association between non-esterified fatty acids and, VAT and liver Ki. Bile acids and carnitines in adipose tissue were inversely associated with VAT Ki. Furthermore, we detected several metabolites that were significantly higher in T2D than normal/prediabetes. In this study we present novel associations between several metabolites from SAT and plasma with the fat fraction, volume and insulin sensitivity of various tissues throughout the body, demonstrating the benefit of an integrative multi-omics approach.

A Multi-Omics Approach to Liver Diseases: Integration of Single Nuclei Transcriptomics with Proteomics and HiCap Bulk Data in Human Liver.

The liver is the largest solid organ and a primary metabolic hub. In recent years, intact cell nuclei were used to perform single-nuclei RNA-seq (snRNA-seq) for tissues difficult to dissociate and for flash-frozen archived tissue samples to discover unknown and rare cell subpopulations. In this study, we performed snRNA-seq of a liver sample to identify subpopulations of cells based on nuclear transcriptomics. In 4282 single nuclei, we detected, on average, 1377 active genes and we identified seven major cell types. We integrated data from 94,286 distal interactions (p < 0.05) for 7682 promoters from a targeted chromosome conformation capture technique (HiCap) and mass spectrometry proteomics for the same liver sample. We observed a reasonable correlation between proteomics and in silico bulk snRNA-seq (r = 0.47) using tissue-independent gene-specific protein abundancy estimation factors. We specifically looked at genes of medical importance. The DPYD gene is involved in the pharmacogenetics of fluoropyrimidine toxicity and some of its variants are analyzed for clinical purposes. We identified a new putative polymorphic regulatory element, which may contribute to variation in toxicity. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and we investigated all known risk genes. We identified a complex regulatory landscape for the SLC2A2 gene with 16 candidate enhancers. Three of them harbor somatic motif breaking and other mutations in HCC in the Pan Cancer Analysis of Whole Genomes dataset and are candidates to contribute to malignancy. Our results highlight the potential of a multi-omics approach in the study of human diseases.

Genome-wide association study of angioedema induced by angiotensin-converting enzyme inhibitor and angiotensin receptor blocker treatment.

Angioedema in the mouth or upper airways is a feared adverse reaction to angiotensin-converting enzyme inhibitor (ACEi) and angiotensin receptor blocker (ARB) treatment, which is used for hypertension, heart failure and diabetes complications. This candidate gene and genome-wide association study aimed to identify genetic variants predisposing to angioedema induced by these drugs. The discovery cohort consisted of 173 cases and 4890 controls recruited in Sweden. In the candidate gene analysis, ETV6, BDKRB2, MME, and PRKCQ were nominally associated with angioedema (p < 0.05), but did not pass Bonferroni correction for multiple testing (p < 2.89 × 10-5). In the genome-wide analysis, intronic variants in the calcium-activated potassium channel subunit alpha-1 (KCNMA1) gene on chromosome 10 were significantly associated with angioedema (p < 5 × 10-8). Whilst the top KCNMA1 hit was not significant in the replication cohort (413 cases and 599 ACEi-exposed controls from the US and Northern Europe), a meta-analysis of the replication and discovery cohorts (in total 586 cases and 1944 ACEi-exposed controls) revealed that each variant allele increased the odds of experiencing angioedema 1.62 times (95% confidence interval 1.05-2.50, p = 0.030). Associated KCNMA1 variants are not known to be functional, but are in linkage disequilibrium with variants in transcription factor binding sites active in relevant tissues. In summary, our data suggest that common variation in KCNMA1 is associated with risk of angioedema induced by ACEi or ARB treatment. Future whole exome or genome sequencing studies will show whether rare variants in KCNMA1 or other genes contribute to the risk of ACEi- and ARB-induced angioedema.

rs953413 Regulates Polyunsaturated Fatty Acid Metabolism by Modulating ELOVL2 Expression.

Long-chain polyunsaturated fatty acids (LC-PUFAs) influence human health in several areas, including cardiovascular disease, diabetes, fatty liver disease, and cancer. ELOVL2 encodes one of the key enzymes in the in vivo synthesis of LC-PUFAs from their precursors. Variants near ELOVL2 have repeatedly been associated with levels of LC-PUFA-derived metabolites in genome-wide association studies (GWAS), but the mechanisms behind these observations remain poorly defined. In this study, we found that rs953413, located in the first intron of ELOVL2, lies within a functional FOXA and HNF4α cooperative binding site. The G allele of rs953413 increases binding of FOXA1/FOXA2 and HNF4α to an evolutionarily conserved enhancer element, conferring allele-specific upregulation of the rs953413-associated gene ELOVL2. The expression of ELOVL2 was significantly downregulated by both FOXA1 and HNF4α knockdown and CRISPR/Cas9-mediated direct mutation to the enhancer element. Our results suggest that rs953413 regulates LC-PUFAs metabolism by altering ELOVL2 expression through FOXA1/FOXA2 and HNF4α cooperation.

Author Correction: Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Contribution of genetics to visceral adiposity and its relation to cardiovascular and metabolic disease.

Visceral adipose tissue (VAT)-fat stored around the internal organs-has been suggested as an independent risk factor for cardiovascular and metabolic disease1-3, as well as all-cause, cardiovascular-specific and cancer-specific mortality4,5. Yet, the contribution of genetics to VAT, as well as its disease-related effects, are largely unexplored due to the requirement for advanced imaging technologies to accurately measure VAT. Here, we develop sex-stratified, nonlinear prediction models (coefficient of determination = 0.76; typical 95% confidence interval (CI) = 0.74-0.78) for VAT mass using the UK Biobank cohort. We performed a genome-wide association study for predicted VAT mass and identified 102 novel visceral adiposity loci. Predicted VAT mass was associated with increased risk of hypertension, heart attack/angina, type 2 diabetes and hyperlipidemia, and Mendelian randomization analysis showed visceral fat to be a causal risk factor for all four diseases. In particular, a large difference in causal effect between the sexes was found for type 2 diabetes, with an odds ratio of 7.34 (95% CI = 4.48-12.0) in females and an odds ratio of 2.50 (95% CI = 1.98-3.14) in males. Our findings bolster the role of visceral adiposity as a potentially independent risk factor, in particular for type 2 diabetes in Caucasian females. Independent validation in other cohorts is necessary to determine whether the findings can translate to other ethnicities, or outside the UK.

Detailed Functional Characterization of a Waist-Hip Ratio Locus in 7p15.2 Defines an Enhancer Controlling Adipocyte Differentiation.

We combined CAGE sequencing in human adipocytes during differentiation with data from genome-wide association studies to identify an enhancer in the SNX10 locus on chromosome 7, presumably involved in body fat distribution. Using reporter assays and CRISPR-Cas9 gene editing in human cell lines, we characterized the role of the enhancer in adipogenesis. The enhancer was active during adipogenesis and responded strongly to insulin and isoprenaline. The allele associated with increased waist-hip ratio in human genetic studies was associated with higher enhancer activity. Mutations of the enhancer resulted in less adipocyte differentiation. RNA sequencing of cells with disrupted enhancer showed reduced expression of established adipocyte markers, such as ADIPOQ and LPL, and identified CHI3L1 on chromosome 1 as a potential gene involved in adipocyte differentiation. In conclusion, we identified and characterized an enhancer in the SNX10 locus and outlined its plausible mechanisms of action and downstream targets.

Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes.

Type 2 diabetes (T2D) mellitus is a complex metabolic disease commonly caused by insulin resistance in several tissues. We performed a matched two-dimensional metabolic screening in tissue samples from 43 multi-organ donors. The intra-individual analysis was assessed across five key metabolic tissues (serum, visceral adipose tissue, liver, pancreatic islets and skeletal muscle), and the inter-individual across three different groups reflecting T2D progression. We identified 92 metabolites differing significantly between non-diabetes and T2D subjects. In diabetes cases, carnitines were significantly higher in liver, while lysophosphatidylcholines were significantly lower in muscle and serum. We tracked the primary tissue of origin for multiple metabolites whose alterations were reflected in serum. An investigation of three major stages spanning from controls, to pre-diabetes and to overt T2D indicated that a subset of lysophosphatidylcholines was significantly lower in the muscle of pre-diabetes subjects. Moreover, glycodeoxycholic acid was significantly higher in liver of pre-diabetes subjects while additional increase in T2D was insignificant. We confirmed many previously reported findings and substantially expanded on them with altered markers for early and overt T2D. Overall, the analysis of this unique dataset can increase the understanding of the metabolic interplay between organs in the development of T2D.

Studies of liver tissue identify functional gene regulatory elements associated to gene expression, type 2 diabetes, and other metabolic diseases.

BACKGROUND: Genome-wide association studies (GWAS) of diseases and traits have found associations to gene regions but not the functional SNP or the gene mediating the effect. Difference in gene regulatory signals can be detected using chromatin immunoprecipitation and next-gen sequencing (ChIP-seq) of transcription factors or histone modifications by aligning reads to known polymorphisms in individual genomes. The aim was to identify such regulatory elements in the human liver to understand the genetics behind type 2 diabetes and metabolic diseases. METHODS: The genome of liver tissue was sequenced using 10X Genomics technology to call polymorphic positions. Using ChIP-seq for two histone modifications, H3K4me3 and H3K27ac, and the transcription factor CTCF, and our established bioinformatics pipeline, we detected sites with significant difference in signal between the alleles. RESULTS: We detected 2329 allele-specific SNPs (AS-SNPs) including 25 associated to GWAS SNPs linked to liver biology, e.g., 4 AS-SNPs at two type 2 diabetes loci. Two hundred ninety-two AS-SNPs were associated to liver gene expression in GTEx, and 134 AS-SNPs were located on 166 candidate functional motifs and most of them in EGR1-binding sites. CONCLUSIONS: This study provides a valuable collection of candidate liver regulatory elements for further experimental validation.

Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases.

Several Genome Wide Association Studies (GWAS) have reported variants associated to immune diseases. However, the identified variants are rarely the drivers of the associations and the molecular mechanisms behind the genetic contributions remain poorly understood. ChIP-seq data for TFs and histone modifications provide snapshots of protein-DNA interactions allowing the identification of heterozygous SNPs showing significant allele specific signals (AS-SNPs). AS-SNPs can change a TF binding site resulting in altered gene regulation and are primary candidates to explain associations observed in GWAS and expression studies. We identified 17,293 unique AS-SNPs across 7 lymphoblastoid cell lines. In this set of cell lines we interrogated 85% of common genetic variants in the population for potential regulatory effect and we identified 237 AS-SNPs associated to immune GWAS traits and 714 to gene expression in B cells. To elucidate possible regulatory mechanisms we integrated long-range 3D interactions data to identify putative target genes and motif predictions to identify TFs whose binding may be affected by AS-SNPs yielding a collection of 173 AS-SNPs associated to gene expression and 60 to B cell related traits. We present a systems strategy to find functional gene regulatory variants, the TFs that bind differentially between alleles and novel strategies to detect the regulated genes.