From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus

Measured and genetically predicted protein levels and cardiovascular diseases in UK Biobank and China Kadoorie Biobank

Several large-scale studies have measured plasma levels of the proteome in individuals with cardiovascular diseases (CVDs)1-7. However, since the majority of such proteins are interrelated2, it is difficult for observational studies to distinguish which proteins are likely to be of etiological relevance. Here we evaluate whether plasma levels of 2,919 proteins measured in 52,164 UK Biobank participants are associated with incident myocardial infarction, ischemic stroke or heart failure. Of those proteins, 126 were associated with all three CVD outcomes and 118 were associated with at least one CVD in the China Kadoorie Biobank. Mendelian randomization and colocalization analyses indicated that genetically determined levels of 47 and 18 proteins, respectively, were associated with CVDs, including FGF5, PROCR and FURIN. While the majority of protein-CVD observational associations were noncausal, these three proteins showed evidence to support potential causality and are therefore promising targets for drug treatment for CVD outcomes.

Characterization of non-coding variants associated with transcription factor binding through ATAC-seq-defined footprint QTLs in liver

Non-coding variants discovered by genome-wide association studies (GWAS) are enriched in regulatory elements harboring transcription factor (TF) binding motifs, strongly suggesting a connection between disease association and the disruption of cis-regulatory sequences. Occupancy of a TF inside a region of open chromatin can be detected in ATAC-seq where bound TFs block the transposase Tn5, leaving a pattern of relatively depleted Tn5 insertions known as a "footprint". Here, we sought to identify variants associated with TF-binding, or "footprint quantitative trait loci" (fpQTLs) in ATAC-seq data generated from 170 human liver samples. We used computational tools to scan the ATAC-seq reads to quantify TF binding likelihood as "footprint scores" at variants derived from whole genome sequencing generated in the same samples. We tested for association between genotype and footprint score and observed 693 fpQTLs associated with footprint-inferred TF binding (FDR < 5%). Given that Tn5 insertion sites are measured with base-pair resolution, we show that fpQTLs can aid GWAS and QTL fine-mapping by precisely pinpointing TF activity within broad trait-associated loci where the underlying causal variant is unknown. Liver fpQTLs were strongly enriched across ChIP-seq peaks, liver expression QTLs (eQTLs), and liver-related GWAS loci, and their inferred effect on TF binding was concordant with their effect on underlying sequence motifs in 80% of cases. We conclude that fpQTLs can reveal causal GWAS variants, define the role of TF binding site disruption in disease and provide functional insights into non-coding variants, ultimately informing novel treatments for common diseases.

Genotype inference from aggregated chromatin accessibility data reveals genetic regulatory mechanisms

Background

Understanding the genetic causes for variability in chromatin accessibility can shed light on the molecular mechanisms through which genetic variants may affect complex traits. Thousands of ATAC-seq samples have been collected that hold information about chromatin accessibility across diverse cell types and contexts, but most of these are not paired with genetic information and come from diverse distinct projects and laboratories.

Results

We report here joint genotyping, chromatin accessibility peak calling, and discovery of quantitative trait loci which influence chromatin accessibility (caQTLs), demonstrating the capability of performing caQTL analysis on a large scale in a diverse sample set without pre-existing genotype information. Using 10,293 profiling samples representing 1,454 unique donor individuals across 653 studies from public databases, we catalog 23,381 caQTLs in total. After joint discovery analysis, we cluster samples based on accessible chromatin profiles to identify context-specific caQTLs. We find that caQTLs are strongly enriched for annotations of gene regulatory elements across diverse cell types and tissues and are often strongly linked with genetic variation associated with changes in expression (eQTLs), indicating that caQTLs can mediate genetic effects on gene expression. We demonstrate sharing of causal variants for chromatin accessibility and diverse complex human traits, enabling a more complete picture of the genetic mechanisms underlying complex human phenotypes.

Conclusions

Our work provides a proof of principle for caQTL calling from previously ungenotyped samples, and represents one of the largest, most diverse caQTL resources currently available, informing mechanisms of genetic regulation of gene expression and contribution to disease.

Liver eQTL meta-analysis illuminates potential molecular mechanisms of cardiometabolic traits

Understanding the molecular mechanisms of complex traits is essential for developing targeted interventions. We analyzed liver expression quantitative-trait locus (eQTL) meta-analysis data on 1,183 participants to identify conditionally distinct signals. We found 9,013 eQTL signals for 6,564 genes; 23% of eGenes had two signals, and 6% had three or more signals. We then integrated the eQTL results with data from 29 cardiometabolic genome-wide association study (GWAS) traits and identified 1,582 GWAS-eQTL colocalizations for 747 eGenes. Non-primary eQTL signals accounted for 17% of all colocalizations. Isolating signals by conditional analysis prior to coloc resulted in 37% more colocalizations than using marginal eQTL and GWAS data, highlighting the importance of signal isolation. Isolating signals also led to stronger evidence of colocalization: among 343 eQTL-GWAS signal pairs in multi-signal regions, analyses that isolated the signals of interest resulted in higher posterior probability of colocalization for 41% of tests. Leveraging allelic heterogeneity, we predicted causal effects of gene expression on liver traits for four genes. To predict functional variants and regulatory elements, we colocalized eQTL with liver chromatin accessibility QTL (caQTL) and found 391 colocalizations, including 73 with non-primary eQTL signals and 60 eQTL signals that colocalized with both a caQTL and a GWAS signal. Finally, we used publicly available massively parallel reporter assays in HepG2 to highlight 14 eQTL signals that include at least one expression-modulating variant. This multi-faceted approach to unraveling the genetic underpinnings of liver-related traits could lead to therapeutic development.

Deciphering the impact of genomic variation on function

Our genomes influence nearly every aspect of human biology-from molecular and cellular functions to phenotypes in health and disease. Studying the differences in DNA sequence between individuals (genomic variation) could reveal previously unknown mechanisms of human biology, uncover the basis of genetic predispositions to diseases, and guide the development of new diagnostic tools and therapeutic agents. Yet, understanding how genomic variation alters genome function to influence phenotype has proved challenging. To unlock these insights, we need a systematic and comprehensive catalogue of genome function and the molecular and cellular effects of genomic variants. Towards this goal, the Impact of Genomic Variation on Function (IGVF) Consortium will combine approaches in single-cell mapping, genomic perturbations and predictive modelling to investigate the relationships among genomic variation, genome function and phenotypes. IGVF will create maps across hundreds of cell types and states describing how coding variants alter protein activity, how noncoding variants change the regulation of gene expression, and how such effects connect through gene-regulatory and protein-interaction networks. These experimental data, computational predictions and accompanying standards and pipelines will be integrated into an open resource that will catalyse community efforts to explore how our genomes influence biology and disease across populations.

The biogenesis and transport of triglyceride-rich lipoproteins

Triglyceride-rich lipoproteins (TRLs) play essential roles in human health and disease by transporting bulk lipids into the circulation. This review summarizes the fundamental mechanisms and diverse factors governing lipoprotein production, secretion, and regulation. Emphasizing the broader implications for human health, we outline the intricate landscape of lipoprotein research and highlight the potential coordination between the biogenesis and transport of TRLs in physiology, particularly the unexpected coupling of metabolic enzymes and transport machineries. Challenges and opportunities in lipoprotein biology with respect to inherited diseases and viral infections are also discussed. Further characterization of the biogenesis and transport of TRLs will advance both basic research in lipid biology and translational medicine for metabolic diseases.

Identification of an Allele-Specific Transcription Factor Binding Interaction that May Regulate PLA2G2A Gene Expression

The secreted phospholipase A2 (sPLA2) isoform, sPLA2-IIA, has been implicated in a variety of diseases and conditions, including bacteremia, cardiovascular disease, COVID-19, sepsis, adult respiratory distress syndrome, and certain cancers. Given its significant role in these conditions, understanding the regulatory mechanisms impacting its levels is crucial. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs), including rs11573156, that are associated with circulating levels of sPLA2-IIA. The work in the manuscript leveraged 4 publicly available datasets to investigate the mechanism by which rs11573156 influences sPLA2-IIA levels via bioinformatics and modeling analysis. Through genotype-tissue expression (GTEx), 234 expression quantitative trait loci (eQTLs) were identified for the gene that encodes for sPLA2-IIA, PLA2G2A. SNP2TFBS was used to ascertain the binding affinities between transcription factors (TFs) to both the reference and alternative alleles of identified eQTL SNPs. Subsequently, candidate TF-SNP interactions were cross-referenced with the ChIP-seq results in matched tissues from ENCODE. SP1-rs11573156 emerged as the significant TF-SNP pair in the liver. Further analysis revealed that the upregulation of PLA2G2A transcript levels through the rs11573156 variant was likely affected by tissue SP1 protein levels. Using an ordinary differential equation based on Michaelis-Menten kinetic assumptions, we modeled the dependence of PLA2G2A transcription on SP1 protein levels, incorporating the SNP influence. Collectively, our analysis strongly suggests that the difference in the binding dynamics of SP1 to different rs11573156 alleles may underlie the allele-specific PLA2G2A expression in different tissues, a mechanistic model that awaits future direct experimental validation. This mechanism likely contributes to the variation in circulating sPLA2-IIA protein levels in the human population, with implications for a wide range of human diseases.

Pleiotropic effects of an eQTL in the CELSR2/PSRC1/SORT1 cluster that associates with LDL-C and resting metabolic rate

CONTEXT

The locus CELSR2-PSRC1-SORT1, a primary genetic signal for lipids, has recently been implicated in different metabolic processes. Our investigation identified its association with energy metabolism.

OBJECTIVE

To determine biological mechanisms that govern diverse functions of this locus.

METHODS

Genotypes for 491,265 variants in 7,000 clinically characterized American Indians were previously determined using a custom-designed array specific for this longitudinally studied American Indian population. Among the genotyped individuals, 5,205 had measures of fasting lipid levels and 509 had measures of resting metabolic rate (RMR) and substrate oxidation rate assessed through indirect calorimetry. A genome-wide association study (GWAS) for LDL-C levels identified a variant in CELSR2 and the molecular impact of this variant on gene expression was assessed in skeletal muscle biopsies from 207 participants, followed by functional validation in mouse myoblasts using a luciferase assay.

RESULTS

A GWAS in American Indians identified rs12740374 in CELSR2 as the top signal for LDL-C levels (P = 1 × 10-22); further analysis of this variant identified an unexpected correlation with reduced RMR (effect = -44.3 kcal/day/minor-allele) and carbohydrate oxidation rate (effect = -5.21 mg/hour/kg-EMBS). Tagged variants showed a distinct linkage disequilibrium architecture in American Indians, highlighting a potential functional variant, rs6670347 (minor-allele frequency = 0.20). Positioned in the glucocorticoid receptor's core binding motif, rs6670347 is part of a skeletal muscle-specific enhancer. Human skeletal muscle transcriptome analysis showed CELSR2 as the most differentially expressed gene (P = 1.9 × 10-7), with the RMR-lowering minor allele elevating gene expression. Experiments in mouse myoblasts confirmed enhancer-based regulation of CELSR2 expression, dependent on glucocorticoids. Rs6670347 also associated with increased oxidative phosphorylation gene expression; CELSR2 as a regulator of these genes, suggests potential influence on energy metabolism through muscle oxidative capacity.

CONCLUSION

Variants in the CELSR2/PSRC1/SORT1 locus exhibit tissue-specific effects on metabolic traits, with an independent role in muscle metabolism through glucocorticoid signaling.

Relative increase in production ratio of small dense low-density lipoprotein in acute coronary syndrome with high coronary plaque burden: an ex-vivo analysis

The absolute value of small dense low-density lipoprotein (sd-LDL) including small LDL (s-LDL) and very small LDL (vs-LDL) has been shown to be associated with increased incidence of atherosclerosis. However, the impact of short-timeframe increases in sd-LDL on arteriosclerosis has not yet been elucidated. Therefore, we investigated the clinical roles of ex-vivo induced sd-LDL in acute coronary syndrome (ACS) using a novel method. This is a prospective, single-blind, and observational study that screened patients who underwent coronary angiography (CAG) for the treatment of ACS or investigation of heart-failure etiology between June 2020 and April 2022 (n = 247). After excluding patients with known diabetes mellitus and advanced renal disease, the patients were further divided into the ACS (n = 34) and control (non-obstructive coronary artery, n = 34) groups. The proportion of sd-LDL (s-LDL + vs-LDL) in total lipoproteins was observed before and after 2-h incubation at 37 ℃ (to approximate physiologic conditions) using 3% polyacrylamide gel electrophoresis. The coronary plaque burden was quantified upon CAG in the ACS group. There were no significant differences between the ACS and control groups in terms of clinical coronary risk factors. The baseline of large, medium, small, and very small LDL were comparable between the two groups. Following a 2-h incubation period, significant increases were observed in the ratios of s-LDL and vs-LDL in both the ACS and control groups (ACS, p = 0.01*; control, p = 0.01*). Notably, the magnitude of increase in sd-LDL was more pronounced in the ACS group compared to the control group, with s-LDL showing a significant difference (p = 0.03*) and vs-LDL showing a tread toward significance (p = 0.08). In addition, in both groups, there was a decrease in IDL and L-LDL, while M-LDL remained unchanged. The plaque burden index and rate of short-timeframe changes in both s-LDL (p = 0.01*) and vs-LDL (p = 0.04*) before and after incubation were significantly correlated in the ACS group. The enhanced production rate of sd-LDL induced under short-term physiologic culture in an ex-vivo model was greater in patients with ACS than in the control group. The increase in sd-LDL is positively correlated with coronary plaque burden. Short-timeframe changes in sd-LDL may serve as markers for the severity of coronary artery disease.

Trans-eQTL hotspots shape complex traits by modulating cellular states

Regulatory genetic variation shapes gene expression, providing an important mechanism connecting DNA variation and complex traits. The causal relationships between gene expression and complex traits remain poorly understood. Here, we integrated transcriptomes and 46 genetically complex growth traits in a large cross between two strains of the yeast Saccharomyces cerevisiae. We discovered thousands of genetic correlations between gene expression and growth, suggesting potential functional connections. Local regulatory variation was a minor source of these genetic correlations. Instead, genetic correlations tended to arise from multiple independent trans-acting regulatory loci. Trans-acting hotspots that affect the expression of numerous genes accounted for particularly large fractions of genetic growth variation and of genetic correlations between gene expression and growth. Genes with genetic correlations were enriched for similar biological processes across traits, but with heterogeneous direction of effect. Our results reveal how trans-acting regulatory hotspots shape complex traits by altering cellular states.

A systems biology-based identification and in vivo functional screening of Alzheimer's disease risk genes reveal modulators of memory function

Genome-wide association studies (GWASs) have uncovered over 75 genomic loci associated with risk for late-onset Alzheimer's disease (LOAD), but identification of the underlying causal genes remains challenging. Studies of induced pluripotent stem cell (iPSC)-derived neurons from LOAD patients have demonstrated the existence of neuronal cell-intrinsic functional defects. Here, we searched for genetic contributions to neuronal dysfunction in LOAD using an integrative systems approach that incorporated multi-evidence-based gene mapping and network-analysis-based prioritization. A systematic perturbation screening of candidate risk genes in Caenorhabditis elegans (C. elegans) revealed that neuronal knockdown of the LOAD risk gene orthologs vha-10 (ATP6V1G2), cmd-1 (CALM3), amph-1 (BIN1), ephx-1 (NGEF), and pho-5 (ACP2) alters short-/intermediate-term memory function, the cognitive domain affected earliest during LOAD progression. These results highlight the impact of LOAD risk genes on evolutionarily conserved memory function, as mediated through neuronal endosomal dysfunction, and identify new targets for further mechanistic interrogation.

Association between augmented levels of the gut pro-hormone Proneurotensin and subclinical vascular damage

Elevated levels of the gut pro-hormone Proneurotensin (proNT) have been found to predict development of cardiovascular disease. However, it is still unknown whether higher proNT levels are associated with subclinical vascular damage. Herein, we investigated the relationship between higher proNT concentrations and augmented pulse pressure (PP) and carotid intima-media thickness (cIMT), indicators of increased arterial stiffness and subclinical atherosclerosis, respectively. Clinical characteristics, PP and cIMT were evaluated in 154 non-diabetic individuals stratified into tertiles according to fasting serum proNT concentrations. We found that, subjects with higher proNT levels exhibited a worse lipid profile and insulin sensitivity, increased C-reactive protein levels, along with higher values of PP and cIMT as compared to the lowest proNT tertile. Prevalence of elevated PP (≥ 60 mmHg) and subclinical carotid atherosclerosis (IMT > 0.9 mm) was increased in the highest tertile of proNT. In a logistic regression analysis adjusted for several confounders, subjects with higher proNT levels displayed a fivefold raised risk of having elevated PP values (OR 5.36; 95%CI 1.04-27.28; P = 0.05) and early carotid atherosclerosis (OR 4.81; 95%CI 1.39-16.57; P = 0.01) as compared to the lowest proNT tertile. In conclusion, higher circulating levels of proNT are a biomarker of subclinical vascular damage independent of other atherosclerotic risk factors.

Sortilin and its potential role in cardiovascular pathology

BACKGROUND

This comprehensive review explores the multifaceted role of sortilin, a key receptor in lipid metabolism, within the context of cardiovascular diseases (CVDs), the leading cause of global mortality.

MAIN BODY

Sortilin, encoded by the SORT1 gene, is implicated in the pathogenesis of atherosclerosis, primarily through its regulation of low-density lipoprotein cholesterol (LDL-C) and very low-density lipoproteins (VLDL). The review delves into the biological functions of sortilin, emphasizing its critical role in lipid and cholesterol homeostasis and its influence on hepatic secretion of lipoproteins and atherogenesis. We highlight sortilin's pathophysiological significance in atherosclerosis, underscoring its involvement in lipid metabolism pathways and vascular inflammation, and its impact on macrophage functions in atherosclerotic plaque formation. The potential of sortilin as a therapeutic target is discussed, considering evidence that suggests its modulation could ameliorate atherosclerosis. The review also acknowledges current inconsistencies and gaps in the evidence, calling for more comprehensive patient studies and in-depth mechanistic research. Finally, the article outlines future research directions, focusing on understanding sortilin's specific cellular mechanisms in cardiovascular health, exploring its genetic variability, therapeutic implications, and its broader relevance to other diseases.

CONCLUSION

This review underscores the significance of sortilin as a biomarker and a promising target for therapeutic intervention in cardiovascular pathology, while advocating for continued research to fully unravel its complex role.

Propolis Reduces Inflammation and Dyslipidemia Caused by High-Cholesterol Diet in Mice by Lowering ADAM10/17 Activities

Atherosclerosis is one of the most important causes of cardiovascular diseases. A disintegrin and metalloprotease (ADAM)10 and ADAM17 have been identified as important regulators of inflammation in recent years. Our study investigated the effect of inhibiting these enzymes with selective inhibitor and propolis on atherosclerosis. In our study, C57BL/6J mice (n = 16) were used in the control and sham groups. In contrast, ApoE-/- mice (n = 48) were used in the case, water extract of propolis (WEP), ethanolic extract of propolis (EEP), GW280264X (GW-synthetic inhibitor), and solvent (DMSO and ethanol) groups. The control group was fed a control diet, and all other groups were fed a high-cholesterol diet for 16 weeks. WEP (400 mg/kg/day), EEP (200 mg/kg/day), and GW (100 µg/kg/day) were administered intraperitoneally for the last four weeks. Animals were sacrificed, and blood, liver, aortic arch, and aortic root tissues were collected. In serum, total cholesterol (TC), triglycerides (TGs), and glucose (Glu) were measured by enzymatic colorimetric method, while interleukin-1β (IL-1β), paraoxonase-1 (PON-1), and lipoprotein-associated phospholipase-A2 (Lp-PLA2) were measured by ELISA. Tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), myeloperoxidase (MPO), interleukin-6 (IL-6), interleukin-10 (IL-10), and interleukin-12 (IL-12) levels were measured in aortic arch by ELISA and ADAM10/17 activities were measured fluorometrically. In addition, aortic root and liver tissues were examined histopathologically and immunohistochemically (ADAM10 and sortilin primary antibody). In the WEP, EEP, and GW groups compared to the case group, TC, TG, TNF-α, IL-1β, IL-6, IL-12, PLA2, MPO, ADAM10/17 activities, plaque burden, lipid accumulation, ADAM10, and sortilin levels decreased, while IL-10 and PON-1 levels increased (p < 0.003). Our study results show that propolis can effectively reduce atherosclerosis-related inflammation and dyslipidemia through ADAM10/17 inhibition.

Massively parallel dissection of RNA in RNA-protein interactions in vivo

Many of the biological functions performed by RNA are mediated by RNA-binding proteins (RBPs), and understanding the molecular basis of these interactions is fundamental to biology. Here, we present massively parallel RNA assay combined with immunoprecipitation (MPRNA-IP) for in vivo high-throughput dissection of RNA-protein interactions and describe statistical models for identifying RNA domains and parsing the structural contributions of RNA. By using custom pools of tens of thousands of RNA sequences containing systematically designed truncations and mutations, MPRNA-IP is able to identify RNA domains, sequences, and secondary structures necessary and sufficient for protein binding in a single experiment. We show that this approach is successful for multiple RNAs of interest, including the long noncoding RNA NORAD, bacteriophage MS2 RNA, and human telomerase RNA, and we use it to interrogate the hitherto unknown sequence or structural RNA-binding preferences of the DNA-looping factor CTCF. By integrating systematic mutation analysis with crosslinking immunoprecipitation, MPRNA-IP provides a novel high-throughput way to elucidate RNA-based mechanisms behind RNA-protein interactions in vivo.

Diagnostic potential of SORT1 gene in coronary artery disease

BACKGROUND

Genome-wide association studies identify SORT1 gene associated with risk of coronary artery disease (CAD). Sortilin protein enhances LDL absorption, form cell development, and atherosclerosis in macrophages.

AIM

We therefore explored SORT1 expression in CAD patients and its gene expression's predictive usefulness for the severity of the disease.

METHODOLOGY

This is a case control study and Quantitative real-time PCR; Sandwich ELISA and western blotting were used to determine the expression of SORT1 gene at the mRNA and protein level in two hundred healthy controls and two hundred patients with various CAD syndromes.

RESULTS

CAD patients exhibit higher SORT1 gene expression in CAD patients, a higher concentration of sortilin in their plasma, and distinct expression patterns in various CAD syndromes. The study reveals a positive correlation between gene expression and the severity of coronary artery stenosis, the number of diseased vessels, and the presence of diabetes. ROC curve analysis of SORT1 gene expression both at mRNA and protein level showed strong discrimination between significant CAD and control subjects.

CONCLUSION

Therefore, elevated SORT1 gene expression in various CAD syndromes may be a potential biomarker for the disease.

Probabilistic association of differentially expressed genes with cis-regulatory elements

Differential gene expression in response to perturbations is mediated at least in part by changes in binding of transcription factors (TFs) and other proteins at specific genomic regions. Association of these cis-regulatory elements (CREs) with their target genes is a challenging task that is essential to address many biological and mechanistic questions. Many current approaches rely on chromatin conformation capture techniques or single-cell correlational methods to establish CRE-to-gene associations. These methods can be effective but have limitations, including resolution, gaps in detectable association distances, and cost. As an alternative, we have developed DegCre, a nonparametric method that evaluates correlations between measurements of perturbation-induced differential gene expression and differential regulatory signal at CREs to score possible CRE-to-gene associations. It has several unique features, including the ability to use any type of CRE activity measurement, yield probabilistic scores for CRE-to-gene pairs, and assess CRE-to-gene pairings across a wide range of sequence distances. We apply DegCre to six data sets, each using different perturbations and containing a variety of regulatory signal measurements, including chromatin openness, histone modifications, and TF occupancy. To test their efficacy, we compare DegCre associations to Hi-C loop calls and CRISPR-validated CRE-to-gene associations, establishing good performance by DegCre that is comparable or superior to competing methods. DegCre is a novel approach to the association of CREs to genes from a perturbation-differential perspective, with strengths that are complementary to existing approaches and allow for new insights into gene regulation.

The association of Sort1 expression with LDL subfraction and inflammation in patients with coronary artery disease

BACKGROUND

Controversial effect of sortilin on lipoprotein metabolism in the development of atherosclerosis reveals the need for more extensive research.

OBJECTIVES

The aim of this study was to investigate the association between Sort1 gene expression and lipids, lipoprotein subfractions, and inflammation in CAD.

METHODS

The study population included 162 subjects with CAD and 49 healthy individuals. The Sort1 gene expression level was determined by qRT-PCR using Human Sortilin TaqMan Gene Expression Assays. Lipoprotein subclasses were analysed by the Lipoprint system. Serum levels of apolipoprotein and CRP were measured by autoanalyzer.

RESULTS

Sort1 gene expression and atherogenic subfraction (SdLDL) levels were significantly higher (p < 0.001) while atheroprotective subfraction (LbLDL) was lower in the subjects with CAD (p < 0.050). Also, increased Sort1 gene expression levels were observed in those with higher CRP values.

CONCLUSIONS

Our findings reveal that the high Sort1 gene expression has a prominent linear relationship with both the atherogenic LDL phenotype and proinflammation, thereby might contribute to the occurrence of CAD.

Identification of candidate causal cis -regulatory variants underlying electrocardiographic QT interval GWAS loci

Identifying causal variants among tens or hundreds of associated variants at each locus mapped by genome-wide association studies (GWAS) of complex traits is a challenge. As vast majority of GWAS variants are noncoding, sequence variation at cis -regulatory elements affecting transcriptional expression of specific genes is a widely accepted molecular hypothesis. Following this cis -regulatory hypothesis and combining it with the observation that nucleosome-free open chromatin is a universal hallmark of all types of cis -regulatory elements, we aimed to identify candidate causal regulatory variants underlying electrocardiographic QT interval GWAS loci. At a dozen loci, selected for higher effect sizes and a better understanding of the likely causal gene, we identified and included all common variants in high linkage disequilibrium with the GWAS variants as candidate variants. Using ENCODE DNase-seq and ATAC-seq from multiple human adult cardiac left ventricle tissue samples, we generated genome-wide maps of open chromatin regions marking putative regulatory elements. QT interval associated candidate variants were filtered for overlap with cardiac left ventricle open chromatin regions to identify candidate causal cis -regulatory variants, which were further assessed for colocalizing with a known cardiac GTEx expression quantitative trait locus variant as additional evidence for their causal role. Together, these efforts have generated a comprehensive set of candidate causal variants that are expected to be enriched for cis -regulatory potential and thereby, explaining the observed genetic associations.

Identification of novel genetic variations in ABCB6 and GRN genes associated with HIV-associated lipodystrophy

Protease inhibitors (PIs) are associated with an incidence of lipodystrophy among people living with HIV(PLHIV). Lipodystrophiesare characterised by the loss of adipose tissue. Evidence suggests that a patient's lipodystrophy phenotype is influenced by genetic mutation, age, gender, and environmental and genetic factors, such as single-nucleotide variants (SNVs). Pathogenic variants are considered to cause a more significant loss of adipose tissue compared to non-pathogenic. Lipid metabolising enzymes and transporter genes have a role in regulating lipoprotein metabolism and have been associated with lipodystrophy in HIV-infected patients (LDHIV). The long-term effect of the lipodystrophy syndrome is related to cardiovascular diseases (CVDs). Hence, we determined the SNVs of lipid metabolising enzymes and transporter genes in a total of 48 patient samples, of which 24 were with and 24 were without HIV-associated lipodystrophy (HIVLD) using next-generation sequencing. A panel of lipid metabolism, transport and elimination genes were sequenced. Three novel heterozygous non-synonymous variants at exon 8 (c.C1400A:p.S467Y, c.G1385A:p.G462E, and c.T1339C:p.S447P) in the ABCB6 gene were identified in patients with lipodystrophy. One homozygous non-synonymous SNV (exon5:c.T358C:p.S120P) in the GRN gene was identified in patients with lipodystrophy. One novelstop-gain SNV (exon5:c.C373T:p.Q125X) was found in the GRN gene among patients without lipodystrophy. Patients without lipodystrophy had one homozygous non-synonymous SNV (exon9:c.G1462T:p.G488C) in the ABCB6 gene. Our findings suggest that novel heterozygous non-synonymous variants in the ABCB6 gene may contribute to defective protein production, potentially intensifying the severity of lipodystrophy. Additionally, identifying a stop-gain SNV in the GRN gene among patients without lipodystrophy implies a potential role in the development of HIVLD.

Mechanosensitive super-enhancers regulate genes linked to atherosclerosis in endothelial cells

Vascular homeostasis and pathophysiology are tightly regulated by mechanical forces generated by hemodynamics. Vascular disorders such as atherosclerotic diseases largely occur at curvatures and bifurcations where disturbed blood flow activates endothelial cells while unidirectional flow at the straight part of vessels promotes endothelial health. Integrated analysis of the endothelial transcriptome, the 3D epigenome, and human genetics systematically identified the SNP-enriched cistrome in vascular endothelium subjected to well-defined atherosclerosis-prone disturbed flow or atherosclerosis-protective unidirectional flow. Our results characterized the endothelial typical- and super-enhancers and underscored the critical regulatory role of flow-sensitive endothelial super-enhancers. CRISPR interference and activation validated the function of a previously unrecognized unidirectional flow-induced super-enhancer that upregulates antioxidant genes NQO1, CYB5B, and WWP2, and a disturbed flow-induced super-enhancer in endothelium which drives prothrombotic genes EDN1 and HIVEP in vascular endothelium. Our results employing multiomics identify the cis-regulatory architecture of the flow-sensitive endothelial epigenome related to atherosclerosis and highlight the regulatory role of super-enhancers in mechanotransduction mechanisms.

Giant pandas in captivity undergo short-term adaptation in nerve-related pathways

BACKGROUND

Behaviors in captive animals, including changes in appetite, activity level, and social interaction, are often seen as adaptive responses. However, these behaviors may become progressively maladaptive, leading to stress, anxiety, depression, and other negative reactions in animals.

RESULTS

In this study, we investigated the whole-genome sequencing data of 39 giant panda individuals, including 11 in captivity and 28 in the wild. To eliminate the mountain range effect and focus on the factor of captivity only, we first performed a principal component analysis. We then enumerated the 21,474,180 combinations of wild giant pandas (11 chosen from 28) and calculated their distances from the 11 captive individuals. The 11 wild individuals with the closest distances were used for the subsequent analysis. The linkage disequilibrium (LD) patterns demonstrated that the population was almost eliminated. We identified 505 robust selected genomic regions harboring at least one SNP, and the absolute frequency difference was greater than 0.6 between the two populations. GO analysis revealed that genes in these regions were mainly involved in nerve-related pathways. Furthermore, we identified 22 GO terms for which the selection strength significantly differed between the two populations, and there were 10 nerve-related pathways among them. Genes in the differentially abundant regions were involved in nerve-related pathways, indicating that giant pandas in captivity underwent minor genomic selection. Additionally, we investigated the relationship between genetic variation and chromatin conformation structures. We found that nucleotide diversity (θπ) in the captive population was correlated with chromatin conformation structures, which included A/B compartments, topologically associated domains (TADs) and TAD-cliques. For each GO term, we then compared the expression level of genes regulated by the above four factors (AB index, TAD intactness, TAD clique and PEI) with the corresponding genomic background. The retained 10 GO terms were all coordinately regulated by the four factors, and three of them were associated with nerve-related pathways.

CONCLUSIONS

This study revealed that giant pandas in captivity undergo short-term adaptation in nerve-related pathways. Furthermore, it provides new insights into the molecular mechanism of gene expression regulation under short-term adaptation to environmental change.

Sex-stratified genome-wide association and transcriptome-wide Mendelian randomization studies reveal drug targets of heart failure

The prevalence of heart failure (HF) subtypes, which are classified by left ventricular ejection fraction (LVEF), demonstrate significant sex differences. Here, we perform sex-stratified genome-wide association studies (GWASs) on LVEF and transcriptome-wide Mendelian randomization (MR) on LVEF, all-cause HF, HF with reduced ejection fraction (HFrEF), and HF with preserved ejection fraction (HFpEF). The sex-stratified GWASs of LVEF identified three sex-specific loci that were exclusively detected in the sex-stratified GWASs. Three drug target genes show sex-differential effects on HF/HFrEF via influencing LVEF, with NPR2 as the target gene for the HF drug Cenderitide under phase 2 clinical trial. Our study highlights the importance of considering sex-differential genetic effects in sex-balanced diseases such as HF and emphasizes the value of sex-stratified GWASs and MR in identifying putative genetic variants, causal genes, and candidate drug targets for HF, which is not identifiable using a sex-combined strategy.

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.

Translational bioinformatics approach to combat cardiovascular disease and cancers

Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.

Genome-Wide Genetic Associations Prioritize Evaluation of Causal Mechanisms of Atherosclerotic Disease Risk

OBJECTIVE

The goal of this review is to discuss the implementation of genome-wide association studies to identify causal mechanisms of vascular disease risk.

APPROACH AND RESULTS

The history of genome-wide association studies is described, the use of imputation and the creation of consortia to conduct meta-analyses with sufficient power to arrive at consistent associated loci for vascular disease. Genomic methods are described that allow the identification of causal variants and causal genes and how they impact the disease process. The power of single-cell analyses to promote genome-wide association studies of causal gene function is described.

CONCLUSIONS

Genome-wide association studies represent a paradigm shift in the study of cardiovascular disease, providing identification of genes, cellular phenotypes, and disease pathways that empower the future of targeted drug development.

VLDL Biogenesis and Secretion: It Takes a Village

The production and secretion of VLDLs (very-low-density lipoproteins) by hepatocytes has a direct impact on liver fat content, as well as the concentrations of cholesterol and triglycerides in the circulation and thus affects both liver and cardiovascular health, respectively. Importantly, insulin resistance, excess caloric intake, and lack of physical activity are associated with overproduction of VLDL, hepatic steatosis, and increased plasma levels of atherogenic lipoproteins. Cholesterol and triglycerides in remnant particles generated by VLDL lipolysis are risk factors for atherosclerotic cardiovascular disease and have garnered increasing attention over the last few decades. Presently, however, increased risk of atherosclerosis is not the only concern when considering today's cardiometabolic patients, as they often also experience hepatic steatosis, a prevalent disorder that can progress to steatohepatitis and cirrhosis. This duality of metabolic risk highlights the importance of understanding the molecular regulation of the biogenesis of VLDL, the lipoprotein that transports triglycerides and cholesterol out of the liver. Fortunately, there has been a resurgence of interest in the intracellular assembly, trafficking, degradation, and secretion of VLDL by hepatocytes, which has led to many exciting new molecular insights that are the topic of this review. Increasing our understanding of the biology of this pathway will aid to the identification of novel therapeutic targets to improve both the cardiovascular and the hepatic health of cardiometabolic patients. This review focuses, for the first time, on this duality.

Distributed eQTL analysis with auxiliary information

Expression quantitative trait locus (eQTL) analysis is a useful tool to identify genetic loci that are associated with gene expression levels. Large collaborative efforts such as the Genotype-Tissue Expression (GTEx) project provide valuable resources for eQTL analysis in different tissues. Most existing methods, however, either focus on one tissue at a time, or analyze multiple tissues to identify eQTLs jointly present in multiple tissues. There is a lack of powerful methods to identify eQTLs in a target tissue while effectively borrowing strength from auxiliary tissues. In this paper, we propose a novel statistical framework to improve the eQTL detection efficacy in the tissue of interest with auxiliary information from other tissues. This framework can enhance the power of the hypothesis test for eQTL effects by incorporating shared and specific effects from multiple tissues into the test statistics. We also devise data-driven and distributed computing approaches for efficient implementation of eQTL detection when the number of tissues is large. Numerical studies in simulation demonstrate the efficacy of the proposed method, and the real data analysis of the GTEx example provides novel insights into eQTL findings in different tissues.

Context-dependent regulation of lipid accumulation in adipocytes by a HIF1α-PPARγ feedback network

Hypoxia-induced upregulation of HIF1α triggers adipose tissue dysfunction and insulin resistance in obese patients. HIF1α closely interacts with PPARγ, the master regulator of adipocyte differentiation and lipid accumulation, but there are conflicting results regarding how this interaction controls the excessive lipid accumulation that drives adipocyte dysfunction. To directly address these conflicts, we established a differentiation system that recapitulated prior seemingly opposing observations made across different experimental settings. Using single-cell imaging and coarse-grained mathematical modeling, we show how HIF1α can both promote and repress lipid accumulation during adipogenesis. Our model predicted and our experiments confirmed that the opposing roles of HIF1α are isolated from each other by the positive-feedback-mediated upregulation of PPARγ that drives adipocyte differentiation. Finally, we identify three factors: strength of the differentiation cue, timing of hypoxic perturbation, and strength of HIF1α expression changes that, when considered together, provide an explanation for many of the previous conflicting reports.

Construction and validation of a novel lysosomal signature for hepatocellular carcinoma prognosis, diagnosis, and therapeutic decision-making

Lysosomes is a well-recognized oncogenic driver and chemoresistance across variable cancer types, and has been associated with tumor invasiveness, metastasis, and poor prognosis. However, the significance of lysosomes in hepatocellular carcinoma (HCC) is not well understood. Lysosomes-related genes (LRGs) were downloaded from Genome Enrichment Analysis (GSEA) databases. Lysosome-related risk score (LRRS), including eight LRGs, was constructed via expression difference analysis (DEGs), univariate and LASSO-penalized Cox regression algorithm based on the TCGA cohort, while the ICGC cohort was obtained for signature validation. Based on GSE149614 Single-cell RNA sequencing data, model gene expression and liver tumor niche were further analyzed. Moreover, the functional enrichments, tumor microenvironment (TME), and genomic variation landscape between LRRSlow/LRRShigh subgroup were systematically investigated. A total of 15 Lysosomes-related differentially expressed genes (DELRGs) in HCC were detected, and then 10 prognosis DELRGs were screened out. Finally, the 8 optimal DELRGs (CLN3, GBA, CTSA, BSG, APLN, SORT1, ANXA2, and LAPTM4B) were selected to construct the LRRS prognosis signature of HCC. LRRS was considered as an independent prognostic factor and was associated with advanced clinicopathological features. LRRS also proved to be a potential marker for HCC diagnosis, especially for early-stage HCC. Then, a nomogram integrating the LRRS and clinical parameters was set up displaying great prognostic predictive performance. Moreover, patients with high LRRS showed higher tumor stemness, higher heterogeneity, and higher genomic alteration status than those in the low LRRS group and enriched in metabolism-related pathways, suggesting its underlying role in the progression and development of liver cancer. Meanwhile, the LRRS can affect the proportion of immunosuppressive cell infiltration, making it a vital immunosuppressive factor in the tumor microenvironment. Additionally, HCC patients with low LRRS were more sensitive to immunotherapy, while patients in the high LRRS group responded better to chemotherapy. Upon single-cell RNA sequencing, CLN3, GBA, and LAPTM4B were found to be specially expressed in hepatocytes, where they promoted cell progression. Finally, RT-qPCR and external datasets confirmed the mRNA expression levels of model genes. This study provided a direct links between LRRS signature and clinical characteristics, tumor microenvironment, and clinical drug-response, highlighting the critical role of lysosome in the development and treatment resistance of liver cancer, providing valuable insights into the prognosis prediction and treatment response of HCC, thereby providing valuable insights into prognostic prediction, early diagnosis, and therapeutic response of HCC.

Identification of an allele-specific transcription factor binding interaction that regulates PLA2G2A gene expression

The secreted phospholipase A 2 (sPLA 2 ) isoform, sPLA 2 -IIA, has been implicated in a variety of diseases and conditions, including bacteremia, cardiovascular disease, COVID-19, sepsis, adult respiratory distress syndrome, and certain cancers. Given its significant role in these conditions, understanding the regulatory mechanisms impacting its levels is crucial. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs), including rs11573156, that are associated with circulating levels of sPLA 2 -IIA. Through Genotype-Tissue Expression (GTEx), 234 expression quantitative trait loci (eQTLs) were identified for the gene that encodes for sPLA 2 -IIA, PLA2G2A . SNP2TFBS ( https://ccg.epfl.ch/snp2tfbs/ ) was utilized to ascertain the binding affinities between transcription factors (TFs) to both the reference and alternative alleles of identified SNPs. Subsequently, ChIP-seq peaks highlighted the TF combinations that specifically bind to the SNP, rs11573156. SP1 emerged as a significant TF/SNP pair in liver cells, with rs11573156/SP1 interaction being most prominent in liver, prostate, ovary, and adipose tissues. Further analysis revealed that the upregulation of PLA2G2A transcript levels through the rs11573156 variant was affected by tissue SP1 protein levels. By leveraging an ordinary differential equation, structured upon Michaelis-Menten enzyme kinetics assumptions, we modeled the PLA2G2A transcription's dependence on SP1 protein levels, incorporating the SNP's influence. Collectively, these data strongly suggest that the binding affinity differences of SP1 for the different rs11573156 alleles can influence PLA2G2A expression. This, in turn, can modulate sPLA2-IIA levels, impacting a wide range of human diseases.

Allele-specific binding (ASB) analyzer for annotation of allele-specific binding SNPs

BACKGROUND

Allele-specific binding (ASB) events occur when transcription factors (TFs) bind more favorably to one of the two parental alleles at heterozygous single nucleotide polymorphisms (SNPs). Evidence suggests that ASB events could reveal the impact of sequence variations on TF binding and may have implications for the risk of diseases.

RESULTS

Here we present ASB-analyzer, a software platform that enables the users to quickly and efficiently input raw sequencing data to generate individual reports containing the cytogenetic map of ASB SNPs and their associated phenotypes. This interactive tool thereby combines ASB SNP identification, biological annotation, motif analysis, phenotype associations and report summary in one pipeline. With this pipeline, we identified 3772 ASB SNPs from thirty GM12878 ChIP-seq datasets and demonstrated that the ASB SNPs were more likely to be enriched at important sites in TF-binding domains.

CONCLUSIONS

ASB-analyzer is a user-friendly tool that enables the detection, characterization and visualization of ASB SNPs. It is implemented in Python, R and bash shell and packaged in the Conda environment. It is available as an open-source tool on GitHub at https://github.com/Liying1996/ASBanalyzer .

Sortilin-Driven Cancer Secretome Enhances Tumorigenic Properties of Hepatocellular Carcinoma via de Novo Lipogenesis

A growing body of evidence suggests de novo lipogenesis as a key metabolic pathway adopted by cancers to fuel tumorigenic processes. While increased de novo lipogenesis has also been reported in hepatocellular carcinoma (HCC), understanding on molecular mechanisms driving de novo lipogenesis remains limited. In the present study, the functional role of sortilin, a member of the vacuolar protein sorting 10 protein receptor family, in HCC was investigated. Sortilin was overexpressed in HCC and was associated with poorer survival outcome. In functional studies, sortilin-overexpressing cells conferred tumorigenic phenotypes, namely, self-renewal and metastatic potential, of HCC cells via the cancer secretome. Proteomic profiling highlighted fatty acid metabolism as a potential molecular pathway associated with sortilin-driven cancer secretome. This finding was validated by the increased lipid content and expression of fatty acid synthase (FASN) in HCC cells treated with conditioned medium collected from sortilin-overexpressing cells. The enhanced tumorigenic properties endowed by sortilin-driven cancer secretome were partly abrogated by co-administration of FASN inhibitor C75. Further mechanistic dissection suggested protein stabilization by post-translational modification with O-GlcNAcylation as a major mechanism leading to augmented FASN expression. In conclusion, the present study uncovered the role of sortilin in hepatocarcinogenesis via modulation of the cancer secretome and deregulated lipid metabolism.

Missense variants in SORT1 are associated with LDL-C in an Amish population

Common noncoding variants at the human 1p13.3 locus associated with SORT1 expression are among those most strongly associated with low-density lipoprotein cholesterol (LDL-C) in human genome-wide association studies. However, validation studies in mice and cell lines have produced variable results regarding the directionality of the effect of SORT1 on LDL-C. This, together with the fact that the 1p13.3 variants are associated with expression of several genes, has raised the question of whether SORT1 is the causal gene at this locus. Using whole exome sequencing in members of an Amish population, we identified coding variants in SORT1 that are associated with increased (rs141749679, K302E) and decreased (rs149456022, Q225H) LDL-C. Further, analysis of plasma lipoprotein particle subclasses by ion mobility in a subset of rs141749679 (K302E) carriers revealed higher levels of large LDL particles compared to noncarriers. In contrast to the effect of these variants in the Amish, the sortilin K302E mutation introduced into a C57BL/6J mouse via CRISPR/Cas9 resulted in decreased non-high-density lipoprotein cholesterol, and the sortilin Q225H mutation did not alter cholesterol levels in mice. This is indicative of different effects of these mutations on cholesterol metabolism in the two species. To our knowledge, this is the first evidence that naturally occurring coding variants in SORT1 are associated with LDL-C, thus supporting SORT1 as the gene responsible for the association of the 1p13.3 locus with LDL-C.

Tissue-specific and tissue-agnostic effects of genome sequence variation modulating blood pressure

Genome-wide association studies (GWASs) have identified numerous variants associated with polygenic traits and diseases. However, with few exceptions, a mechanistic understanding of which variants affect which genes in which tissues to modulate trait variation is lacking. Here, we present genomic analyses to explain trait heritability of blood pressure (BP) through the genetics of transcriptional regulation using GWASs, multiomics data from different tissues, and machine learning approaches. Approximately 500,000 predicted regulatory variants across four tissues explain 33.4% of variant heritability: 2.5%, 5.3%, 7.7%, and 11.8% for kidney-, adrenal-, heart-, and artery-specific variants, respectively. Variation in the enhancers involved shows greater tissue specificity than in the genes they regulate, suggesting that gene regulatory networks perturbed by enhancer variants in a tissue relevant to a phenotype are the major source of interindividual variation in BP. Thus, our study provides an approach to scan human tissue and cell types for their physiological contribution to any trait.

TMED10 mediates the trafficking of insulin-like growth factor 2 along the secretory pathway for myoblast differentiation

The insulin-like growth factor 2 (IGF2) plays critical roles in cell proliferation, migration, differentiation, and survival. Despite its importance, the molecular mechanisms mediating the trafficking of IGF2 along the secretory pathway remain unclear. Here, we utilized a Retention Using Selective Hook system to analyze molecular mechanisms that regulate the secretion of IGF2. We found that a type I transmembrane protein, TMED10, is essential for the secretion of IGF2 and for differentiation of mouse myoblast C2C12 cells. Further analyses indicate that the residues 112-140 in IGF2 are important for the secretion of IGF2 and these residues directly interact with the GOLD domain of TMED10. We then reconstituted the release of IGF2 into COPII vesicles. This assay suggests that TMED10 mediates the packaging of IGF2 into COPII vesicles to be efficiently delivered to the Golgi. Moreover, TMED10 also mediates ER export of TGN-localized cargo receptor, sortilin, which subsequently mediates TGN export of IGF2. These analyses indicate that TMED10 is critical for IGF2 secretion by directly regulating ER export and indirectly regulating TGN export of IGF2, providing insights into trafficking of IGF2 for myoblast differentiation.

Allele biased transcription factor binding across human brain regions gives mechanistic insight into eQTLs

Transcription Factors (TFs) influence gene expression by facilitating or disrupting the formation of transcription initiation machinery at particular genomic loci. Because genomic localization of TFs is in part driven by TF recognition of DNA sequence, variation in TF binding sites can disrupt TF-DNA associations and affect gene regulation. To identify variants that impact TF binding in human brain tissues, we quantified allele bias for 93 TFs analyzed with ChIP-seq experiments of multiple structural brain regions from two donors. Using graph genomes constructed from phased genomic sequence data, we compared ChIP-seq signal between alleles at heterozygous variants within each tissue sample from each donor. Comparison of results from different brain regions within donors and the same regions between donors provided measures of allele bias reproducibility. We identified thousands of DNA variants that show reproducible bias in ChIP-seq for at least one TF. We found that alleles that are rarer in the general population were more likely than common alleles to exhibit large biases, and more frequently led to reduced TF binding. Combining ChIP-seq with RNA-seq, we identified TF-allele interaction biases with RNA bias in a phased allele linked to 6,709 eQTL variants identified in GTEx data, 3,309 of which were found in neural contexts. Our results provide insights into the effects of both common and rare variation on gene regulation in the brain. These findings can facilitate mechanistic understanding of cis-regulatory variation associated with biological traits, including disease.

The interaction between enhancer variants and environmental factors as an overlooked aetiological paradigm in human complex disease

The interactions between genetic and environmental risk factors contribute to the aetiology of complex human diseases. Genome-wide association studies (GWAS) have revealed that most of the genetic variants associated with complex diseases are located in the non-coding part of the genome, preferentially within enhancers. Enhancers are distal cis-regulatory elements composed of clusters of transcription factors binding sites that positively regulate the expression of their target genes. The generation of genome-wide maps for histone marks (e.g., H3K27ac), chromatin accessibility and transcription factor and coactivator (e.g., p300) binding profiles have enabled the identification of enhancers across many human cell types and tissues. Nonetheless, the functional and pathological consequences of the majority of disease-associated genetic variants located within enhancers seem to be rather minor under normal conditions, thus questioning their medical relevance. Here we propose that, due to the prevalence of enhancer redundancy, the pathological effects of many disease-associated non-coding genetic variants might be preferentially (or even only) manifested under environmental stress.

Spatially and temporally distinct patterns of expression for VPS10P domain receptors in human cerebral organoids

Vacuolar protein sorting 10 protein (VPS10P) domain receptors are a unique class of intracellular sorting receptors that emerge as major risk factors associated with psychiatric and neurodegenerative diseases, including bipolar disorders, autism, schizophrenia, as well as Alzheimer's disease and frontotemporal dementia. Yet, the lack of suitable experimental models to study receptor functions in the human brain has hampered elucidation of receptor actions in brain disease. Here, we have adapted protocols using human cerebral organoids to the detailed characterization of VPS10P domain receptor expression during neural development and differentiation, including single-cell RNA sequencing. Our studies uncovered spatial and temporal patterns of expression unique to individual receptor species in the human brain. While SORL1 expression is abundant in stem cells and SORCS1 peaks in neural progenitors at onset of neurogenesis, SORT1 and SORCS2 show increasing expression with maturation of neuronal and non-neuronal cell types, arguing for distinct functions in development versus the adult brain. In neurons, subcellular localization also distinguishes between types of receptor species, either mainly localized to the cell soma (SORL1 and SORT1) or also to neuronal projections (SORCS1 and SORCS2), suggesting divergent functions in protein sorting between Golgi and the endo-lysosomal system or along axonal and dendritic tracks. Taken together, our findings provide an important resource on temporal, spatial, and subcellular patterns of VPS10P domain receptor expression in cerebral organoids for further elucidation of receptor (dys) functions causative of behavioral and cognitive defects of the human brain.

Prioritization of therapeutic targets for dyslipidemia using integrative multi-omics and multi-trait analysis

Drug targets with genetic support are several-fold more likely to succeed in clinical trials. We introduce a genetic-driven approach based on causal inferences that can inform drug target prioritization, repurposing, and adverse effects of using lipid-lowering agents. Given that a multi-trait approach increases the power to detect meaningful variants/genes, we conduct multi-omics and multi-trait analyses, followed by network connectivity investigations, and prioritize 30 potential therapeutic targets for dyslipidemia, including SORT1, PSRC1, CELSR2, PCSK9, HMGCR, APOB, GRN, HFE2, FJX1, C1QTNF1, and SLC5A8. 20% (6/30) of prioritized targets from our hypothesis-free drug target search are either approved or under investigation for dyslipidemia. The prioritized targets are 22-fold higher in likelihood of being approved or under investigation in clinical trials than genome-wide association study (GWAS)-curated targets. Our results demonstrate that the genetic-driven approach used in this study is a promising strategy for prioritizing targets while informing about the potential adverse effects and repurposing opportunities.

Evolutionary Action-Machine Learning Model Identifies Candidate Genes Associated With Early-Onset Coronary Artery Disease

Background Coronary artery disease is a primary cause of death around the world, with both genetic and environmental risk factors. Although genome-wide association studies have linked >100 unique loci to its genetic basis, these only explain a fraction of disease heritability. Methods and Results To find additional gene drivers of coronary artery disease, we applied machine learning to quantitative evolutionary information on the impact of coding variants in whole exomes from the Myocardial Infarction Genetics Consortium. Using ensemble-based supervised learning, the Evolutionary Action-Machine Learning framework ranked each gene's ability to classify case and control samples and identified 79 significant associations. These were connected to known risk loci; enriched in cardiovascular processes like lipid metabolism, blood clotting, and inflammation; and enriched for cardiovascular phenotypes in knockout mouse models. Among them, INPP5F and MST1R are examples of potentially novel coronary artery disease risk genes that modulate immune signaling in response to cardiac stress. Conclusions We concluded that machine learning on the functional impact of coding variants, based on a massive amount of evolutionary information, has the power to suggest novel coronary artery disease risk genes for mechanistic and therapeutic discoveries in cardiovascular biology, and should also apply in other complex polygenic diseases.

Characterization of direct and/or indirect genetic associations for multiple traits in longitudinal studies of disease progression

When quantitative longitudinal traits are risk factors for disease progression and subject to random biological variation, joint model analysis of time-to-event and longitudinal traits can effectively identify direct and/or indirect genetic association of single nucleotide polymorphisms (SNPs) with time-to-event. We present a joint model that integrates: (1) a multivariate linear mixed model describing trajectories of multiple longitudinal traits as a function of time, SNP effects, and subject-specific random effects and (2) a frailty Cox survival model that depends on SNPs, longitudinal trajectory effects, and subject-specific frailty accounting for dependence among multiple time-to-event traits. Motivated by complex genetic architecture of type 1 diabetes complications (T1DC) observed in the Diabetes Control and Complications Trial (DCCT), we implement a 2-stage approach to inference with bootstrap joint covariance estimation and develop a hypothesis testing procedure to classify direct and/or indirect SNP association with each time-to-event trait. By realistic simulation study, we show that joint modeling of 2 time-to-T1DC (retinopathy and nephropathy) and 2 longitudinal risk factors (HbA1c and systolic blood pressure) reduces estimation bias in genetic effects and improves classification accuracy of direct and/or indirect SNP associations, compared to methods that ignore within-subject risk factor variability and dependence among longitudinal and time-to-event traits. Through DCCT data analysis, we demonstrate feasibility for candidate SNP modeling and quantify effects of sample size and Winner's curse bias on classification for 2 SNPs identified as having indirect associations with time-to-T1DC traits. Joint analysis of multiple longitudinal and multiple time-to-event traits provides insight into complex traits architecture.

Proteome-Wide Association Studies for Blood Lipids and Comparison with Transcriptome-Wide Association Studies

Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWAS) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWAS) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWAS) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWAS and TWAS can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p-values across all the genes, which suggests a high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

Association of single nucleotide polymorphisms with dyslipidemia and risk of metabolic disorders in the State of Qatar

BACKGROUND

Dyslipidemia is recognized as one of the risk factors of cardiovascular diseases (CVDs), type 2 diabetes mellitus (T2DM), and non-alcoholic fatty liver disease (NAFLD).

OBJECTIVE

The study aimed to investigate the association between selected single nucleotide polymorphisms (SNPs) with dyslipidemia and increased susceptibility risks of CVD, NAFLD, and/or T2DM in dyslipidemia patients in comparison with healthy control individuals from the Qatar genome project.

METHODS

A community-based cross-sectional study was conducted among 2933 adults (859 dyslipidemia patients and 2074 healthy control individuals) from April to December 2021 to investigate the association between 331 selected SNPs with dyslipidemia and increased susceptibility risks of CVD, NAFLD and/or T2DM, and covariates.

RESULTS

The genotypic frequencies of six SNPs were found to be significantly different in dyslipidemia patients subjects compared to the control group among males and females. In males, three SNPs were found to be significant, the rs11172113 in over-dominant model, the rs646776 in recessive and over-dominant models, and the rs1111875 in dominant model. On the other hand, two SNPs were found to be significant in females, including rs2954029 in recessive model, and rs1801251 in dominant and recessive models. The rs17514846 SNP was found for dominant and over-dominant models among males and only the dominant model for females. We found that the six SNPs linked to gender type had an influence in relation to disease susceptibility. When controlling for the four covariates (gender, obesity, hypertension, and diabetes), the difference between dyslipidemia and the control group remained significant for the six variants. Finally, males were three times more likely to have dyslipidemia in comparison with females, hypertension was two times more likely to be present in the dyslipidemia group, and diabetes was six times more likely to be in the dyslipidemia group.

CONCLUSION

The current investigation provides evidence of association for a common SNP to coronary heart disease and suggests a sex-dependent effect and encourage potential therapeutic applications.

Genetic Risk Factors Related to Coronary Artery Disease and Role of Transforming Growth Factor Beta 1 Polymorphisms

Coronary artery disease (CAD) is one of the leading causes of mortality globally and has long been known to be heritable; however, the specific genetic factors involved have yet to be identified. Recent advances have started to unravel the genetic architecture of this disease and set high expectations about the future use of novel susceptibility variants for its prevention, diagnosis, and treatment. In the past decade, there has been major progress in this area. New tools, like common variant association studies, genome-wide association studies, meta-analyses, and genetic risk scores, allow a better understanding of the genetic risk factors driving CAD. In recent years, researchers have conducted further studies that confirmed the role of numerous genetic factors in the development of CAD. These include genes that affect lipid and carbohydrate metabolism, regulate the function of the endothelium and vascular smooth muscles, influence the coagulation system, or affect the immune system. Many CAD-associated single-nucleotide polymorphisms have been identified, although many of their functions are largely unknown. The inflammatory process that occurs in the coronary vessels is very important in the development of CAD. One important mediator of inflammation is TGFβ1. TGFβ1 plays an important role in the processes leading to CAD, such as by stimulating macrophage and fibroblast chemotaxis, as well as increasing extracellular matrix synthesis. This review discusses the genetic risk factors related to the development of CAD, with a particular focus on polymorphisms of the transforming growth factor β (TGFβ) gene and its receptor.

Insulin Regulation of Hepatic Lipid Homeostasis

The incidence of obesity, insulin resistance, and type II diabetes (T2DM) continues to rise worldwide. The liver is a central insulin-responsive metabolic organ that governs whole-body metabolic homeostasis. Therefore, defining the mechanisms underlying insulin action in the liver is essential to our understanding of the pathogenesis of insulin resistance. During periods of fasting, the liver catabolizes fatty acids and stored glycogen to meet the metabolic demands of the body. In postprandial conditions, insulin signals to the liver to store excess nutrients into triglycerides, cholesterol, and glycogen. In insulin-resistant states, such as T2DM, hepatic insulin signaling continues to promote lipid synthesis but fails to suppress glucose production, leading to hypertriglyceridemia and hyperglycemia. Insulin resistance is associated with the development of metabolic disorders such as cardiovascular and kidney disease, atherosclerosis, stroke, and cancer. Of note, nonalcoholic fatty liver disease (NAFLD), a spectrum of diseases encompassing fatty liver, inflammation, fibrosis, and cirrhosis, is linked to abnormalities in insulin-mediated lipid metabolism. Therefore, understanding the role of insulin signaling under normal and pathologic states may provide insights into preventative and therapeutic opportunities for the treatment of metabolic diseases. Here, we provide a review of the field of hepatic insulin signaling and lipid regulation, including providing historical context, detailed molecular mechanisms, and address gaps in our understanding of hepatic lipid regulation and the derangements under insulin-resistant conditions. © 2023 American Physiological Society. Compr Physiol 13:4785-4809, 2023.

Role of non-coding variants in cardiovascular disease

Cardiovascular diseases (CVDs) constitute one of the significant causes of death worldwide. Different pathological states are linked to CVDs, which despite interventions and treatments, still have poor prognoses. The genetic component, as a beneficial tool in the risk stratification of CVD development, plays a role in the pathogenesis of this group of diseases. The emergence of genome-wide association studies (GWAS) have led to the identification of non-coding parts associated with cardiovascular traits and disorders. Variants located in functional non-coding regions, including promoters/enhancers, introns, miRNAs and 5'/3' UTRs, account for 90% of all identified single-nucleotide polymorphisms associated with CVDs. Here, for the first time, we conducted a comprehensive review on the reported non-coding variants for different CVDs, including hypercholesterolemia, cardiomyopathies, congenital heart diseases, thoracic aortic aneurysms/dissections and coronary artery diseases. Additionally, we present the most commonly reported genes involved in each CVD. In total, 1469 non-coding variants constitute most reports on familial hypercholesterolemia, hypertrophic cardiomyopathy and dilated cardiomyopathy. The application and identification of non-coding variants are beneficial for the genetic diagnosis and better therapeutic management of CVDs.

Dyslipidemia, inflammation, calcification, and adiposity in aortic stenosis: a genome-wide study

AIMS

Although highly heritable, the genetic etiology of calcific aortic stenosis (AS) remains incompletely understood. The aim of this study was to discover novel genetic contributors to AS and to integrate functional, expression, and cross-phenotype data to identify mechanisms of AS.

METHODS AND RESULTS

A genome-wide meta-analysis of 11.6 million variants in 10 cohorts involving 653 867 European ancestry participants (13 765 cases) was performed. Seventeen loci were associated with AS at P ≤ 5 × 10-8, of which 15 replicated in an independent cohort of 90 828 participants (7111 cases), including CELSR2-SORT1, NLRP6, and SMC2. A genetic risk score comprised of the index variants was associated with AS [odds ratio (OR) per standard deviation, 1.31; 95% confidence interval (CI), 1.26-1.35; P = 2.7 × 10-51] and aortic valve calcium (OR per standard deviation, 1.22; 95% CI, 1.08-1.37; P = 1.4 × 10-3), after adjustment for known risk factors. A phenome-wide association study indicated multiple associations with coronary artery disease, apolipoprotein B, and triglycerides. Mendelian randomization supported a causal role for apolipoprotein B-containing lipoprotein particles in AS (OR per g/L of apolipoprotein B, 3.85; 95% CI, 2.90-5.12; P = 2.1 × 10-20) and replicated previous findings of causality for lipoprotein(a) (OR per natural logarithm, 1.20; 95% CI, 1.17-1.23; P = 4.8 × 10-73) and body mass index (OR per kg/m2, 1.07; 95% CI, 1.05-1.9; P = 1.9 × 10-12). Colocalization analyses using the GTEx database identified a role for differential expression of the genes LPA, SORT1, ACTR2, NOTCH4, IL6R, and FADS.

CONCLUSION

Dyslipidemia, inflammation, calcification, and adiposity play important roles in the etiology of AS, implicating novel treatments and prevention strategies.

Exploring the genetic basis of coronary artery disease using functional genomics

Genome-wide Association Studies (GWAS) have identified more than 300 loci associated with coronary artery disease (CAD), defining the genetic risk map of the disease. However, the translation of the association signals into biological-pathophysiological mechanisms constitute a major challenge. Through a group of examples of studies focused on CAD, we discuss the rationale, basic principles and outcomes of the main methodologies implemented to prioritize and characterize causal variants and their target genes. Additionally, we highlight the strategies as well as the current methods that integrate association and functional genomics data to dissect the cellular specificity underlying the complexity of disease mechanisms. Despite the limitations of existing approaches, the increasing knowledge generated through functional studies helps interpret GWAS maps and opens novel avenues for the clinical usability of association data.