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

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.

Serum Sortilin Levels as a Biomarker for Metabolic and Hormonal Dysregulation in Polycystic Ovary Syndrome

Background/Objectives: Polycystic ovarian syndrome (PCOS) is a complex endocrine disorder affecting up to 15% of reproductive-age women, characterized by hyperandrogenism, chronic oligo-ovulation, and metabolic dysfunction. This study aims to evaluate serum sortilin levels in women with PCOS for the first time and investigate their potential associations with metabolic and hormonal alterations. Material and Methods: Eighty PCOS patients and 80 healthy controls were included; serum sortilin levels were measured using ELISA kits, with documented intra-assay and inter-assay variations below 6% and 8%, respectively, ensuring high specificity and sensitivity. Results: Serum sortilin levels were significantly elevated in PCOS patients (69.51 ± 27.75 pg/mL) versus controls (48.60 ± 21.20 pg/mL) (p < 0.001). PCOS patients exhibited higher mean HOMA-IR, free androgen index values, serum glucose, insulin, triglycerides, high-sensitivity C-reactive protein, luteinizing hormone, total testosterone, and DHEA-S levels, alongside reduced high-density lipoprotein cholesterol and sex hormone-binding globulin levels (all, p < 0.05). Notably, inverse correlations were observed between sortilin and low-density lipoprotein cholesterol levels in both groups (p = 0.028 and 0.033). Conclusions: This pioneering study indicates that serum sortilin may be implicated in PCOS pathogenesis and serves as a potential biomarker for metabolic dysfunction in PCOS. Larger, diverse studies with longitudinal designs are needed for further validation.

A Comprehensive Review of the Genetics of Dyslipidemias and Risk of Atherosclerotic Cardiovascular Disease

Dyslipidemias are often diagnosed based on an individual's lipid panel that may or may not include Lp(a) or apoB. But these values alone omit key information that can underestimate risk and misdiagnose disease, which leads to imprecise medical therapies that reduce efficacy with unnecessary adverse events. For example, knowing whether an individual's dyslipidemia is monogenic can granularly inform risk and create opportunities for precision therapeutics. This review explores the canonical and non-canonical causes of dyslipidemias and how they impact atherosclerotic cardiovascular disease (ASCVD) risk. This review emphasizes the multitude of genetic causes that cause primary hypercholesterolemia, hypertriglyceridemia, and low or elevated high-density lipoprotein (HDL)-cholesterol levels. Within each of these sections, this review will explore the evidence linking these genetic conditions with ASCVD risk. Where applicable, this review will summarize approved therapies for a particular genetic condition.

Causal modeling of gene effects from regulators to programs to traits: integration of genetic associations and Perturb-seq

Genetic association studies provide a unique tool for identifying causal links from genes to human traits and diseases. However, it is challenging to determine the biological mechanisms underlying most associations, and we lack genome-scale approaches for inferring causal mechanistic pathways from genes to cellular functions to traits. Here we propose new approaches to bridge this gap by combining quantitative estimates of gene-trait relationships from loss-of-function burden tests with gene-regulatory connections inferred from Perturb-seq experiments in relevant cell types. By combining these two forms of data, we aim to build causal graphs in which the directional associations of genes with a trait can be explained by their regulatory effects on biological programs or direct effects on the trait. As a proof-of-concept, we constructed a causal graph of the gene regulatory hierarchy that jointly controls three partially co-regulated blood traits. We propose that perturbation studies in trait-relevant cell types, coupled with gene-level effect sizes for traits, can bridge the gap between genetics and biology.

A cis-regulatory element controls expression of histone deacetylase 9 to fine-tune inflammasome-dependent chronic inflammation in atherosclerosis

Common genetic variants in a conserved cis-regulatory element (CRE) at histone deacetylase (HDAC)9 are a major risk factor for cardiovascular disease, including stroke and coronary artery disease. Given the consistency of this association and its proinflammatory properties, we examined the mechanisms whereby HDAC9 regulates vascular inflammation. HDAC9 bound and mediated deacetylation of NLRP3 in the NACHT and LRR domains leading to inflammasome activation and lytic cell death. Targeted deletion of the critical CRE in mice increased Hdac9 expression in myeloid cells to exacerbate inflammasome-dependent chronic inflammation. In human carotid endarterectomy samples, increased HDAC9 expression was associated with atheroprogression and clinical plaque instability. Incorporation of TMP195, a class IIa HDAC inhibitor, into lipoprotein-based nanoparticles to target HDAC9 at the site of myeloid-driven vascular inflammation stabilized atherosclerotic plaques, implying a lower risk of plaque rupture and cardiovascular events. Our findings link HDAC9 to atherogenic inflammation and provide a paradigm for anti-inflammatory therapeutics for atherosclerosis.

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

This work aimed to determine biological mechanisms that govern diverse functions of this locus.

METHODS

Genotypes for 491 265 variants in 7000 clinically characterized American Indians were previously determined using a custom-designed array specific for this longitudinally studied American Indian population. Among the genotyped individuals, 5205 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 low-density lipoprotein cholesterol (LDL-C) levels identified a variant in CELSR2, and the molecular effect 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 was also associated with increased oxidative phosphorylation gene expression; CELSR2, as a regulator of these genes, suggests a 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.

Research Progress and Clinical Translation Potential of Coronary Atherosclerosis Diagnostic Markers from a Genomic Perspective

Objective: Coronary atherosclerosis (CAD) is characterized by arterial intima lipid deposition, chronic inflammation, and fibrous tissue proliferation, leading to arterial wall thickening and lumen narrowing. As the primary cause of coronary heart disease and acute coronary syndrome, CAD significantly impacts global health. Recent genetic studies have demonstrated CAD's polygenic and multifactorial nature, providing molecular insights for early diagnosis and risk assessment. This review analyzes recent advances in CAD-related genetic markers and evaluates their diagnostic potential, focusing on their applications in diagnosis and risk stratification within precision medicine. Methods: We conducted a systematic review of CAD genomic studies from PubMed and Web of Science databases, analyzing findings from genome-wide association studies (GWASs), gene sequencing, transcriptomics, and epigenomics research. Results: GWASs and sequencing studies have identified key genetic variations associated with CAD, including JCAD/KIAA1462, GUCY1A3, PCSK9, and SORT1, which regulate inflammation, lipid metabolism, and vascular function. Transcriptomic and epigenomic analyses have revealed disease-specific gene expression patterns, DNA methylation signatures, and regulatory non-coding RNAs (miRNAs and lncRNAs), providing new approaches for early detection. Conclusions: While genetic marker research in CAD has advanced significantly, clinical implementation faces challenges including marker dynamics, a lack of standardization, and integration with conventional diagnostics. Future research should prioritize developing standardized guidelines, conducting large-scale prospective studies, and enhancing multi-omics data integration to advance genomic diagnostics in CAD, ultimately improving patient outcomes through precision medicine.

Abundant repressor binding sites in human enhancers are associated with the fine-tuning of gene regulation

The regulation of gene expression relies on the coordinated action of transcription factors (TFs) at enhancers, including both activator and repressor TFs. We employed deep learning (DL) to dissect HepG2 enhancers into positive (PAR), negative (NAR), and neutral activity regions. Sharpr-MPRA and STARR-seq highlight the dichotomy impact of NARs and PARs on modulating and catalyzing the activity of enhancers, respectively. Approximately 22% of HepG2 enhancers, termed "repressive impact enhancers" (RIEs), are predominantly populated by NARs and transcriptional repression motifs. Genes flanking RIEs exhibit a stage-specific decline in expression during late development, suggesting RIEs' role in trimming enhancer activities. About 16.7% of human NARs emerge from neutral rhesus macaque DNA. This gain of repressor binding sites in RIEs is associated with a 30% decrease in the average expression of flanking genes in humans compared to rhesus macaque. Our work reveals modulated enhancer activity and adaptable gene regulation through the evolutionary dynamics of TF binding sites.

Missing Regulation Between Genetic Association and Transcriptional Abundance for Hypercholesterolemia Genes

Background: Low-density lipoprotein cholesterol (LDL-C) is a well-established risk factor for cardiovascular disease, and it plays a causal role in the development of atherosclerosis. Genome-wide association studies (GWASs) have successfully identified hundreds of genetic variants associated with LDL-C. Most of these risk loci fall in non-coding regions of the genome, and it is unclear how these non-coding variants affect circulating lipid levels. One hypothesis is that genetically mediated variation in transcript abundance, detected via the analysis of expressed quantitative trait loci (eQTLs), is key to the biologic function of causal variants. Here, we investigate the hypothesis that non-coding GWAS risk variants affect the homeostatic expression of a nearby putatively causal gene for serum LDL-C levels. Methods: We establish a set of twenty-one expert-curated and validated genes implicated in hypercholesterolemia via dose-dependent pharmacologic modulation in human adults, for which the relevant tissue type has been established. We show that the expression of these LDL-C genes is impacted by eQTLs in relevant tissues and that there are significant genomic-risk loci in LDL-GWAS near these causal genes. We evaluate, using statistical colocalization, whether a single variant or set of variants in each genetic locus is responsible for the GWAS and eQTL signals. Results: Genome-wide association study results for serum LDL-C levels demonstrate that the 402 identified genomic-risk loci for LDL-C are highly enriched for known causal genes for LDL-C (OR 527, 95% CI 126-5376, p < 2.2 × 10-16). However, we find limited evidence for colocalization between GWAS signals near validated hypercholesterolemia genes and eQTLs in relevant tissues (colocalization rate of 26% at a locus-level colocalization probability > 50%). Conclusions: Our results highlight the complexity of genetic regulatory effects for causal hypercholesterolemia genes; we suggest that context-responsive eQTLs may explain the effects of non-coding GWAS hits that do not overlap with standard eQTLs.

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 (GWASs) 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 (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol 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 (PWASs) 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 (TWASs) 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 PWASs and TWASs 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 high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

Evaluation of diagnostic performances of Pro-neurotensin and Heart-type fatty acid binding protein as reliable biomarkers for cardiovascular diseases

AIM

In 2019, cardiovascular diseases accounted for 32% of global deaths. So, early detection of cardiac disorders is crucial. The study aimed to examine the suitability of Pro-neurotensin and Heart-type fatty acid binding protein as dependable biomarkers for cardiac patients with Heart failure as a primary diagnosis.

METHODOLOGY

The prospective study involved 204 Egyptian volunteers (100 cardiac patients and 104 controls) enrolled from El-Sahel Teaching Hospital in Cairo, Egypt, between October 2022 and May 2023. Inclusion criteria included a high risk of cardiovascular events with symptoms like a fast or irregular pulse, shortness of breath, and fatigue. Exclusion criteria included asymptomatic individuals, cognitive disorders, and psychiatric conditions. The Research Ethics Committee approved the protocol. The consultant conducted a clinical examination of all patients and assessed their heart state. Serum ProNT and H-FABP were detected using a kit for the sandwich ELISA technique.

RESULTS

ProNT and H-FABP were significantly elevated in patients compared to controls with p < 0.001. Demonstrated sensitivity of 81% and 84%, with a specificity of 89% and 91%, respectively.

CONCLUSION

Elevated ProNT and H-FABP levels are associated with severe CVDs, suggesting their potential as diagnostic biomarkers for patients, specifically those with heart failure, as a primary characteristic.

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.

VAREANT: a bioinformatics application for gene variant reduction and annotation

Motivation

The analysis of high-quality genomic variant data may offer a more complete understanding of the human genome, enabling researchers to identify novel biomarkers, stratify patients based on disease risk factors, and decipher underlying biological pathways. Although the availability of genomic data has sharply increased in recent years, the accessibility of bioinformatic tools to aid in its preparation is still lacking. Limitations with processing genomic data primarily include its large volume, associated computational and storage costs, and difficulty in identifying targeted and relevant information.

Results

We present VAREANT, an accessible and configurable bioinformatic application to support the preparation of variant data into a usable analysis-ready format. VAREANT is comprised of three standalone modules: (i) Pre-processing, (ii) Variant Annotation, (iii) AI/ML Data Preparation. Pre-processing supports the fine-grained filtering of complex variant datasets to eliminate extraneous data. Variant Annotation allows for the addition of variant metadata from the latest public annotation databases for subsequent analysis and interpretation. AI/ML Data Preparation supports the user in creating AI/ML-ready datasets suitable for immediate analysis with minimal pre-processing required. We have successfully tested and validated our tool on numerous variable-sized datasets and implemented VAREANT in two case studies involving patients with cardiovascular diseases.

Availability and implementation

The open-source code of VAREANT is available at GitHub: https://github.com/drzeeshanahmed/Gene_VAREANT.

Impaired chaperone-mediated autophagy leads to abnormal SORT1 (sortilin 1) turnover and CES1-dependent triglyceride hydrolysis

SORT1 (sortilin 1), a member of the the Vps10 (vacuolar protein sorting 10) family, is involved in hepatic lipid metabolism by regulating very low-density lipoprotein (VLDL) secretion and facilitating the lysosomal degradation of CES1 (carboxylesterase 1), crucial for triglyceride (TG) breakdown in the liver. This study explores whether SORT1 is targeted for degradation by chaperone-mediated autophagy (CMA), a selective protein degradation pathway that directs proteins containing KFERQ-like motifs to lysosomes via LAMP2A (lysosomal-associated membrane protein 2A). Silencing LAMP2A or HSPA8/Hsc70 with siRNA increased cytosolic SORT1 protein levels. Leupeptin treatment induced lysosomal accumulation of SORT1, unaffected by siLAMP2A co-treatment, indicating CMA-dependent degradation. Human SORT1 contains five KFERQ-like motifs (658VVTKQ662, 730VREVK734, 733VKDLK737, 734KDLKK738, and 735DLKKK739), crucial for HSPA8 recognition; mutating any single amino acid within these motifs decreased HSPA8 binding. Furthermore, compromised CMA activity resulted in elevated SORT1-mediated degradation of CES1, contributing to increased lipid accumulation in hepatocytes. Consistent with in vitro findings, LAMP2A knockdown in mice exacerbated high-fructose diet-induced fatty liver, marked by increased SORT1 and decreased CES1 levels. Conversely, LAMP2A overexpression promoted SORT1 degradation and CES1D accumulation, counteracting fasting-induced CES1D suppression through CMA activation. Our findings reveal that SORT1 is a substrate of CMA, highlighting its crucial role in directing CES1 to lysosomes. Consequently, disrupting CMA-mediated SORT1 degradation significantly affects CES1-dependent TG hydrolysis, thereby affecting hepatic lipid homeostasis.Abbreviations: APOB: apolipoprotein B; CES1: carboxylesterase 1; CMA: chaperone-mediated autophagy; HSPA8/Hsc70: heat shock protein family A (Hsp70) member 8; LAMP2A: lysosomal associated membrane protein 2A; LDL-C: low-density lipoprotein-cholesterol; PLIN: perilipin; SORT1: sortilin 1; TG: triglyceride; VLDL: very low-density lipoprotein; Vps10: vacuolar protein sorting 10.

Enhanced osteogenic potential of iPSC-derived mesenchymal progenitor cells following genome editing of GWAS variants in the RUNX1 gene

Recent genome-wide association studies (GWAS) identified 518 significant loci associated with bone mineral density (BMD), including variants at the RUNX1 locus (rs13046645, rs2834676, and rs2834694). However, their regulatory impact on RUNX1 expression and bone formation remained unclear. This study utilized human induced pluripotent stem cells (iPSCs) differentiated into osteoblasts to investigate these variants' regulatory roles. CRISPR/Cas9 was employed to generate mutant (Δ) iPSC lines lacking these loci at the RUNX1 locus. Deletion lines (Δ1 and Δ2) were created in iPSCs to assess the effects of removing regions containing these loci. Deletion lines exhibited enhanced osteogenic potential, with increased expression of osteogenic marker genes and Alizarin Red staining. Circularized chromosome conformation capture (4C-Seq) was utilized to analyze interactions between BMD-associated loci and the RUNX1 promoter during osteogenesis. Analysis revealed altered chromatin interactions with multiple gene promoters including RUNX1 isoform, as well as SETD4, a histone methyltransferase, indicating their regulatory influence. Interestingly, both deletion lines notably stimulated the expression of the long isoform of RUNX1, with more modest effects on the shorter isoform. Consistent upregulation of SETD4 and other predicted targets within the Δ2 deletion suggested its removal removed a regulatory hub constraining expression of multiple genes at this locus. In vivo experiments using a bone defect model in mice demonstrated increased bone regeneration with homozygous deletion of the Δ2 region. These findings indicate that BMD-associated variants within the RUNX1 locus regulate multiple effector genes involved in osteoblast commitment, providing valuable insights into genetic regulation of bone density and potential therapeutic targets.

Small-cohort GWAS discovery with AI over massive functional genomics knowledge graph

Genome-wide association studies (GWASs) have identified tens of thousands of disease associated variants and provided critical insights into developing effective treatments. However, limited sample sizes have hindered the discovery of variants for uncommon and rare diseases. Here, we introduce KGWAS, a novel geometric deep learning method that leverages a massive functional knowledge graph across variants and genes to improve detection power in small-cohort GWASs significantly. KGWAS assesses the strength of a variant's association to disease based on the aggregate GWAS evidence across molecular elements interacting with the variant within the knowledge graph. Comprehensive simulations and replication experiments showed that, for small sample sizes ( N =1-10K), KGWAS identified up to 100% more statistically significant associations than state-of-the-art GWAS methods and achieved the same statistical power with up to 2.67× fewer samples. We applied KGWAS to 554 uncommon UK Biobank diseases ( N case <5K) and identified 183 more associations (46.9% improvement) than the original GWAS, where the gain further increases to 79.8% for 141 rare diseases (N case <300). The KGWAS-only discoveries are supported by abundant functional evidence, such as rs2155219 (on 11q13) associated with ulcerative colitis potentially via regulating LRRC32 expression in CD4+ regulatory T cells, and rs7312765 (on 12q12) associated with the rare disease myasthenia gravis potentially via regulating PPHLN1 expression in neuron-related cell types. Furthermore, KGWAS consistently improves downstream analyses such as identifying disease-specific network links for interpreting GWAS variants, identifying disease-associated genes, and identifying disease-relevant cell populations. Overall, KGWAS is a flexible and powerful AI model that integrates growing functional genomics data to discover novel variants, genes, cells, and networks, especially valuable for small cohort diseases.

The breadth and impact of the Global Lipids Genetics Consortium

PURPOSE OF REVIEW

This review highlights contributions of the Global Lipids Genetics Consortium (GLGC) in advancing the understanding of the genetic etiology of blood lipid traits, including total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, and non-HDL cholesterol. We emphasize the consortium's collaborative efforts, discoveries related to lipid and lipoprotein biology, methodological advancements, and utilization in areas extending beyond lipid research.

RECENT FINDINGS

The GLGC has identified over 923 genomic loci associated with lipid traits through genome-wide association studies (GWASs), involving more than 1.65 million individuals from globally diverse populations. Many loci have been functionally validated by individuals inside and outside the GLGC community. Recent GLGC studies show increased population diversity enhances variant discovery, fine-mapping of causal loci, and polygenic score prediction for blood lipid levels. Moreover, publicly available GWAS summary statistics have facilitated the exploration of lipid-related genetic influences on cardiovascular and noncardiovascular diseases, with implications for therapeutic development and drug repurposing.

SUMMARY

The GLGC has significantly advanced the understanding of the genetic basis of lipid levels and serves as the leading resource of GWAS summary statistics for these traits. Continued collaboration will be critical to further understand lipid and lipoprotein biology through large-scale genetic assessments in diverse populations.

Modeling common and rare genetic risk factors of neuropsychiatric disorders in human induced pluripotent stem cells

Recent genome-wide association studies (GWAS) and whole-exome sequencing of neuropsychiatric disorders, especially schizophrenia, have identified a plethora of common and rare disease risk variants/genes. Translating the mounting human genetic discoveries into novel disease biology and more tailored clinical treatments is tied to our ability to causally connect genetic risk variants to molecular and cellular phenotypes. When combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas) nuclease-mediated genome editing system, human induced pluripotent stem cell (hiPSC)-derived neural cultures (both 2D and 3D organoids) provide a promising tractable cellular model for bridging the gap between genetic findings and disease biology. In this review, we first conceptualize the advances in understanding the disease polygenicity and convergence from the past decade of iPSC modeling of different types of genetic risk factors of neuropsychiatric disorders. We then discuss the major cell types and cellular phenotypes that are most relevant to neuropsychiatric disorders in iPSC modeling. Finally, we critically review the limitations of iPSC modeling of neuropsychiatric disorders and outline the need for implementing and developing novel methods to scale up the number of iPSC lines and disease risk variants in a systematic manner. Sufficiently scaled-up iPSC modeling and a better functional interpretation of genetic risk variants, in combination with cutting-edge CRISPR/Cas9 gene editing and single-cell multi-omics methods, will enable the field to identify the specific and convergent molecular and cellular phenotypes in precision for neuropsychiatric disorders.

Molecular Regulation and Therapeutic Targeting of VLDL Production in Cardiometabolic Disease

There exists a complex relationship between steatotic liver disease (SLD) and atherosclerotic cardiovascular disease (CVD). CVD is a leading cause of morbidity and mortality among individuals with SLD, particularly those with metabolic dysfunction-associated SLD (MASLD), a significant proportion of whom also exhibit features of insulin resistance. Recent evidence supports an expanded role of very low-density lipoprotein (VLDL) in the pathogenesis of CVD in patients, both with and without associated metabolic dysfunction. VLDL represents the major vehicle for exporting neutral lipid from hepatocytes, with each particle containing one molecule of apolipoproteinB100 (APOB100). VLDL production becomes dysregulated under conditions characteristic of MASLD including steatosis and insulin resistance. Insulin resistance not only affects VLDL production but also mediates the pathogenesis of atherosclerotic CVD. VLDL assembly and secretion therefore represents an important pathway in the setting of cardiometabolic disease and offers several candidates for therapeutic targeting, particularly in metabolically complex patients with MASLD at increased risk of atherosclerotic CVD. Here we review the clinical significance as well as the translational and therapeutic potential of key regulatory steps impacting VLDL initiation, maturation, secretion, catabolism, and clearance.

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.

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.

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.

Systemic mechanism of Panax noteginseng saponins in antiaging based on network pharmacology combined with experimental validation

This study aims to investigate the systemic mechanism of Panax notoginseng saponins (PNS) in antiaging using network pharmacology combined with experimental validation. String database and Cytoscape3.7.2 were used to perform the protein-protein interaction (PPI) and construct genes network. The key target genes were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Then, the aging-related genes were verified by reverse-transcription polymerase chain reaction in SAM-P/8 mice, and performed molecular docking with the main components of PNS. Moreover, it produced cluster between Hub genes and differential genes. A total of 169 crossover genes were obtained, and the results of GO and KEGG indicated that the antiaging effect of PNS was mediated by apoptosis, cancer, and neurodegeneration and that five of the eight Hub genes had good binding activity with the main components of PNS. In addition, animal experiments reported that MAP2, MAPKK4, RAB6A, and Sortilin-1 have different levels of expression in the brain tissues of aging mice, and bind well docking with the main active components of PNS. However, there was no crossover between the 169 PNS intersecting genes and the four differential genes, while they yielded a link from PPI in which MAP2K4 was only linked to AKT1 and CASP3; MAP2 was only linked to AKT1 and CASP3; RAB6A was only linked to AKT1; but Sortlin-1 did not link to the Hub genes. In summary, the antiaging effect of PNS is associated with the eight Hub genes and four differential genes. All of them consist of a cluster or group that is possibly related to the antiaging effect of PNS.

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.

Artificial Intelligence in Cardiology and Atherosclerosis in the Context of Precision Medicine: A Scoping Review

Cardiovascular diseases remain the main cause of death worldwide which makes it essential to better understand, diagnose, and treat atherosclerosis. Artificial intelligence (AI) and novel technological solutions offer us new possibilities and enable the practice of individually tailored medicine. The study was performed using the PRISMA protocol. As of January 10, 2023, the analysis has been based on a review of 457 identified articles in PubMed and MEDLINE databases. The search covered reviews, original articles, meta-analyses, comments, and editorials published in the years 2009-2023. In total, 123 articles met inclusion criteria. The results were divided into the subsections presented in the review (genome-wide association studies, radiomics, and other studies). This paper presents actual knowledge concerning atherosclerosis, in silico, and big data analyses in cardiology that affect the way medicine is practiced in order to create an individual approach and adjust the therapy of atherosclerosis.

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.