Functional Analysis of a Carotid Intima-Media Thickness Locus Implicates BCAR1 and Suggests a Causal Variant

Cfdp1 Is Essential for Cardiac Development and Function

Cardiovascular diseases (CVDs) are the prevalent cause of mortality worldwide. A combination of environmental and genetic effectors modulates the risk of developing them. Thus, it is vital to identify candidate genes and elucidate their role in the manifestation of the disease. Large-scale human studies have revealed the implication of Craniofacial Development Protein 1 (CFDP1) in Coronary Artery Disease (CAD). CFDP1 belongs to the evolutionary conserved Bucentaur (BCNT) family, and to date, its function and mechanism of action in Cardiovascular Development are still unclear. We utilized zebrafish to investigate the role of cfdp1 in the developing heart due to the high genomic homology, similarity in heart physiology, and ease of experimental manipulations. We showed that cfdp1 was expressed during development, and we tested two morpholinos and generated a cfdp1 mutant line. The cfdp1-/- embryos developed arrhythmic hearts and exhibited defective cardiac performance, which led to a lethal phenotype. Findings from both knockdown and knockout experiments showed that abrogation of cfdp1 leads to downregulation of Wnt signaling in embryonic hearts during valve development but without affecting Notch activation in this process. The cfdp1 zebrafish mutant line provides a valuable tool for unveiling the novel mechanism of regulating cardiac physiology and function. cfdp1 is essential for cardiac development, a previously unreported phenotype most likely due to early lethality in mice. The detected phenotype of bradycardia and arrhythmias is an observation with potential clinical relevance for humans carrying heterozygous CFDP1 mutations and their risk of developing CAD.

Causal analysis of plasma IL-8 on carotid intima media thickness, a measure of subclinical atherosclerosis

BACKGROUND

We investigated the causality of IL-8 on carotid intima-media thickness (c-IMT), a measure of sub-clinical atherosclerosis.

METHODS

The IMPROVE is a multicenter European study (n = 3,711). The association of plasma IL-8 with c-IMT (mm) was estimated by quantile regression. Genotyping was performed using the Illumina CardioMetabo and Immuno chips. Replication was attempted in three independent studies and a meta-analysis was performed using a random model.

RESULTS

In IMPROVE, each unit increase in plasma IL-8 was associated with an increase in median c-IMT measures (all p<0·03) in multivariable analyses. Linear regression identified rs117518778 and rs8057084 as associated with IL-8 levels and with measures of c-IMT. The two SNPs were combined in an IL-8-increasing genetic risk that showed causality of IL-8 on c-IMT in IMPROVE and in the UK Biobank (n = 22,179). The effect of IL-8 on c-IMT measures was confirmed in PIVUS (n = 1,016) and MDCCC (n = 6,103). The association of rs8057084 with c-IMT was confirmed in PIVUS and UK Biobank with a pooled estimate effect (β) of -0·006 with 95%CI (-0·008- -0·003).

CONCLUSION

Our results indicate that genetic variants associated with plasma IL-8 also associate with c-IMT. However, we cannot infer causality of this association, as these variants lie outside of the IL8 locus.

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

Integrative Analysis of Multi-Omics and Genetic Approaches-A New Level in Atherosclerotic Cardiovascular Risk Prediction

Genetics and environmental and lifestyle factors deeply affect cardiovascular diseases, with atherosclerosis as the etiopathological factor (ACVD) and their early recognition can significantly contribute to an efficient prevention and treatment of the disease. Due to the vast number of these factors, only the novel "omic" approaches are surmised. In addition to genomics, which extended the effective therapeutic potential for complex and rarer diseases, the use of "omics" presents a step-forward that can be harnessed for more accurate ACVD prediction and risk assessment in larger populations. The analysis of these data by artificial intelligence (AI)/machine learning (ML) strategies makes is possible to decipher the large amount of data that derives from such techniques, in order to provide an unbiased assessment of pathophysiological correlations and to develop a better understanding of the molecular background of ACVD. The predictive models implementing data from these "omics", are based on consolidated AI best practices for classical ML and deep learning paradigms that employ methods (e.g., Integrative Network Fusion method, using an AI/ML supervised strategy and cross-validation) to validate the reproducibility of the results. Here, we highlight the proposed integrated approach for the prediction and diagnosis of ACVD with the presentation of the key elements of a joint scientific project of the University of Milan and the Almazov National Medical Research Centre.

A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits

Genome-wide association studies (GWAS) have identified thousands of genomic regions affecting complex diseases. The next challenge is to elucidate the causal genes and mechanisms involved. One approach is to use statistical colocalization to assess shared genetic aetiology across multiple related traits (e.g. molecular traits, metabolic pathways and complex diseases) to identify causal pathways, prioritize causal variants and evaluate pleiotropy. We propose HyPrColoc (Hypothesis Prioritisation for multi-trait Colocalization), an efficient deterministic Bayesian algorithm using GWAS summary statistics that can detect colocalization across vast numbers of traits simultaneously (e.g. 100 traits can be jointly analysed in around 1 s). We perform a genome-wide multi-trait colocalization analysis of coronary heart disease (CHD) and fourteen related traits, identifying 43 regions in which CHD colocalized with ≥1 trait, including 5 previously unknown CHD loci. Across the 43 loci, we further integrate gene and protein expression quantitative trait loci to identify candidate causal genes.

Genetic overlap of chronic obstructive pulmonary disease and cardiovascular disease-related traits: a large-scale genome-wide cross-trait analysis

BACKGROUND

A growing number of studies clearly demonstrate a substantial association between chronic obstructive pulmonary disease (COPD) and cardiovascular diseases (CVD), although little is known about the shared genetics that contribute to this association.

METHODS

We conducted a large-scale cross-trait genome-wide association study to investigate genetic overlap between COPD (Ncase = 12,550, Ncontrol = 46,368) from the International COPD Genetics Consortium and four primary cardiac traits: resting heart rate (RHR) (N = 458,969), high blood pressure (HBP) (Ncase = 144,793, Ncontrol = 313,761), coronary artery disease (CAD)(Ncase = 60,801, Ncontrol = 123,504), and stroke (Ncase = 40,585, Ncontrol = 406,111) from UK Biobank, CARDIoGRAMplusC4D Consortium, and International Stroke Genetics Consortium data.

RESULTS

RHR and HBP had modest genetic correlation, and CAD had borderline evidence with COPD at a genome-wide level. We found evidence of local genetic correlation with particular regions of the genome. Cross-trait meta-analysis of COPD identified 21 loci jointly associated with RHR, 22 loci with HBP, and 3 loci with CAD. Functional analysis revealed that shared genes were enriched in smoking-related pathways and in cardiovascular, nervous, and immune system tissues. An examination of smoking-related genetic variants identified SNPs located in 15q25.1 region associated with cigarettes per day, with effects on RHR and CAD. A Mendelian randomization analysis showed a significant positive causal effect of COPD on RHR (causal estimate = 0.1374, P = 0.008).

CONCLUSION

In a set of large-scale GWAS, we identify evidence of shared genetics between COPD and cardiac traits.

Genetic overlap between birthweight and adult cardiometabolic diseases has implications for genomic medicine

Before implementing therapeutic genomic interventions for optimizing health in early life, comprehensive understanding of their effect on several traits across the life course is warranted. Abnorml  birthweight is associated with cardiometabolic disease risk in adulthood; however, the extent of genetic pleiotropy in the association has not been comprehensively investigated. We tested for pleiotropy and enrichment of functional loci between birthweight and 15 cardiometabolic disease traits (CMD). We found significantly abundant genetic pleiotropy (P < 3.3 × 10⁻³) and enrichment of functional annotations (P < 3.3 × 10⁻³) in loci influencing both birthweight and CMD. We did not observe consistent effect directions of pleiotropic loci on the traits. A total of 67 genetic loci, of which 65 loci have been reported in previous genome-wide association studies, were associated with both birthweight and CMD at a false discovery rate of 5%. Two novel loci were associated with birthweight and adult coronary artery disease (rs2870463 in CTRB1) and with birthweight and adult waist circumference (rs12704673 in CALCR). Both loci are known to have regulatory effects on expression of nearby genes. In all, our findings revealed pervasive genetic pleiotropy in early growth and adulthood cardiometabolic diseases, implying the need for caution when considering genetic loci as therapeutic targets.

A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10-8) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10-8). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).

Identifying low density lipoprotein cholesterol associated variants in the Annexin A2 (ANXA2) gene

BACKGROUND AND AIMS

Annexin-A2 (AnxA2) is an endogenous inhibitor of proprotein convertase subtilisin/kexin type-9 (PCSK9). The repeat-one (R1) domain of AnxA2 binds to PCSK9, blocking its ability to promote degradation of low-density lipoprotein cholesterol-receptors (LDL-R) and thereby regulate low-density lipoprotein cholesterol (LDL-C) levels. Here we identify variants in ANXA2 influencing LDL-C levels and we determine the molecular mechanisms of their effects.

RESULTS

The ANXA2 single nucleotide polymorphism (SNP) genotype-phenotype association was examined using the Second-Northwick-Park Heart Study (NPHSII) (n∼2700) and the UCL-LSHTM-Edinburgh-Bristol (UCLEB) consortium (n∼14,600). The ANXA2-R1 domain coding-SNP rs17845226 (V98L) associated with LDL-C, homozygotes for the minor allele having ≈18.8% higher levels of LDL-C (p = 0.004), and higher risk of coronary heart disease (CHD) (p = 0.04). The SNP is in modest linkage disequilibrium (r² > 0.5) with two intergenic SNPs, rs17191344 and rs11633032. Both SNPs showed allele-specific protein binding, and the minor alleles caused significant reduction in reporter gene expression (≈18%, p < 0.001). In the expression quantitative trait loci (eQTL) study, minor allele homozygotes have significantly lower levels of ANXA2-mRNA expression (p = 1.36 × 10^-05).

CONCLUSIONS

Both rs11633032 and rs17191344 SNPs are functional variants, where the minor alleles create repressor-binding protein sites for transcription factors that contribute to reduced ANXA2 gene expression. Lower AnxA2 levels could increase plasma levels of PCSK9 and thus increase LDL-C levels and risk of CHD. This supports, for the first time in humans, previous observations in mouse models that changes in the levels of AnxA2 directly influence plasma LDL-C levels, and thus implicate this protein as a potential therapeutic target for LDL-C lowering.

Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Functional Analysis of the Coronary Heart Disease Risk Locus on Chromosome 21q22

Background. The coronary heart disease (CHD) risk locus on 21q22 (lead SNP rs9982601) lies within a “gene desert.” The aim of this study was to assess if this locus is associated with CHD risk factors and to identify the functional variant(s) and gene(s) involved. Methods. A phenome scan was performed with UCLEB Consortium data. Allele-specific protein binding was studied using electrophoretic mobility shift assays. Dual-reporter luciferase assays were used to assess the impact of genetic variation on expression. Expression quantitative trait analysis was performed with Advanced Study of Aortic Pathology (ASAP) and Genotype-Tissue Expression (GTEx) consortium data. Results. A suggestive association between QT interval and the locus was observed (rs9982601  p = 0.04). One variant at the locus, rs28451064, showed allele-specific protein binding and its minor allele showed 12% higher luciferase expression (p = 4.82 × 10⁻³) compared to the common allele. The minor allele of rs9982601 was associated with higher expression of the closest upstream genes (SLC5A3 1.30-fold increase p = 3.98 × 10⁻⁵; MRPS6 1.15-fold increase p = 9.60 × 10⁻⁴) in aortic intima media in ASAP. Both rs9982601 and rs28451064 showed a suggestive association with MRPS6 expression in relevant tissues in the GTEx data. Conclusions. A candidate functional variant, rs28451064, was identified. Future work should focus on identifying the pathway(s) involved.

Genetic Research and Women's Heart Disease: a Primer

PURPOSE OF REVIEW

This review provides a brief synopsis of sexual dimorphism in atherosclerosis with an emphasis on genetic studies aimed to better understand the atherosclerotic process and clinical outcomes in women. Such studies are warranted because development of atherosclerosis, impact of several traditional risk factors, and burden of coronary heart disease (CHD) differ between women and men.

RECENT FINDINGS

While most candidate gene studies pool women and men and adjust for sex, some sex-specific studies provide evidence of association between candidate genes and prevalent and incident CHD in women. So far, most genome-wide association studies (GWAS) also failed to consider sex-specific associations. The few GWAS focused on women tended to have small sample sizes and insufficient power to reject the null hypothesis of no association even if associations exist. Few studies consider that sex can modify the effect of gene variants on CHD. Sufficiently large-scale genetic studies in women of different race/ethnic groups, taking into account possible gene-gene and gene-environment interactions as well as hormone-mediated epigenetic mechanisms, are needed. Using the same disease definition for women and men might not be appropriate. Accurate phenotyping and inclusion of relevant outcomes in women, together with targeting the entire spectrum of atherosclerosis, could help address the contribution of genes to sexual dimorphism in atherosclerosis. Discovered genetic loci should be taken forward for replication and functional studies to elucidate the plausible underlying biological mechanisms. A better understanding of the etiology of atherosclerosis in women would facilitate future prevention efforts and interventions.

From Loci to Biology: Functional Genomics of Genome-Wide Association for Coronary Disease

Genome-wide association studies have provided a rich collection of ≈ 58 coronary artery disease (CAD) loci that suggest the existence of previously unsuspected new biology relevant to atherosclerosis. However, these studies only identify genomic loci associated with CAD, and many questions remain even after a genomic locus is definitively implicated, including the nature of the causal variant(s) and the causal gene(s), as well as the directionality of effect. There are several tools that can be used for investigation of the functional genomics of these loci, and progress has been made on a limited number of novel CAD loci. New biology regarding atherosclerosis and CAD will be learned through the functional genomics of these loci, and the hope is that at least some of these new pathways relevant to CAD pathogenesis will yield new therapeutic targets for the prevention and treatment of CAD.