A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

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 (GWASs) 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 809 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 78% of cases. We conclude that fpQTLs can reveal causal GWAS variants, define the role of TF binding-site disruption in complex traits, and provide functional insights into non-coding variants, ultimately informing novel treatments for common 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.

A bidirectional Mendelian randomization study integrating genome-wide association studies, expression quantitative trait locus, and methylation quantitative trait locus data revealed causal relationship between heavy cigarette dependence and Barrett's esophagus

Background

The association between smoking dependence and the risk of developing Barrett's esophagus remains unclear. This study aimed to investigate whether a causal relationship exists between smoking dependence and Barrett's esophagus, using Mendelian randomization analysis.

Methods

Two-sample Mendelian randomization analysis was conducted to evaluate the impact of smoking and Barrett's esophagus. Additionally, we applied summary data-based Mendelian randomization techniques to combine information from genome-wide association studies (GWAS) with expression quantitative trait locus and methylation quantitative trait locus.

Results

Multivariable Mendelian randomization showed an association between smoking per day (odds ratio = 1.2, 95% confidence interval: 1.038-1.38, p = 0.014) or current smoking (odds ratio = 2.41, 95% confidence interval: 1.06-5.5, p = 0.037) and Barrett's esophagus. Inverse variance-weighted methods of bidirectional Mendelian randomization also revealed that smoking per day was significantly associated with elevated risks of Barrett's esophagus (odds ratio = 1.34, 95% confidence interval: 1.092-1.649, p = 0.005), while Barrett's esophagus was also a susceptibility factor for smoking per day (odds ratio = 1.05, 95% confidence interval: 1.017-1.087, p = 0.003). By incorporating consistent summary data-based Mendelian randomization associations between DNA methylation and smoke/Barrett's esophagus, gene expression and smoke/Barrett's esophagus, and DNA methylation and gene expression, we identified that the genetic variant-cg00935895-RBM43 (ENSG00000184898)-smoke/Barrett's esophagus axis exerted an effect on smoke/Barrett's esophagus by altering the DNA methylation level, which regulated the expression level of RBM43.

Conclusions

Our study provides evidence of a bidirectional causal association between smoking and Barrett's esophagus from a genetic perspective, which sheds new light on the potential role of RBM43 as a mediator in facilitating the impact of smoking and Barrett's esophagus.

Heterogeneity-aware integrative regression for ancestry-specific association studies

Ancestry-specific proteome-wide association studies (PWAS) based on genetically predicted protein expression can reveal complex disease etiology specific to certain ancestral groups. These studies require ancestry-specific models for protein expression as a function of SNP genotypes. In order to improve protein expression prediction in ancestral populations historically underrepresented in genomic studies, we propose a new penalized maximum likelihood estimator for fitting ancestry-specific joint protein quantitative trait loci models. Our estimator borrows information across ancestral groups, while simultaneously allowing for heterogeneous error variances and regression coefficients. We propose an alternative parameterization of our model that makes the objective function convex and the penalty scale invariant. To improve computational efficiency, we propose an approximate version of our method and study its theoretical properties. Our method provides a substantial improvement in protein expression prediction accuracy in individuals of African ancestry, and in a downstream PWAS analysis, leads to the discovery of multiple associations between protein expression and blood lipid traits in the African ancestry population.

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.

Enhancing portability of trans-ancestral polygenic risk scores through tissue-specific functional genomic data integration

Portability of trans-ancestral polygenic risk scores is often confounded by differences in linkage disequilibrium and genetic architecture between ancestries. Recent literature has shown that prioritizing GWAS SNPs with functional genomic evidence over strong association signals can improve model portability. We leveraged three RegulomeDB-derived functional regulatory annotations-SURF, TURF, and TLand-to construct polygenic risk models across a set of quantitative and binary traits highlighting functional mutations tagged by trait-associated tissue annotations. Tissue-specific prioritization by TURF and TLand provide a significant improvement in model accuracy over standard polygenic risk score (PRS) models across all traits. We developed the Trans-ancestral Iterative Tissue Refinement (TITR) algorithm to construct PRS models that prioritize functional mutations across multiple trait-implicated tissues. TITR-constructed PRS models show increased predictive accuracy over single tissue prioritization. This indicates our TITR approach captures a more comprehensive view of regulatory systems across implicated tissues that contribute to variance in trait expression.

Bidirectional causality between the levels of blood lipids and endometriosis: a two-sample mendelian randomization study

BACKGROUND

Observational studies have found a correlation between the levels of blood lipids and the development and progression of endometriosis (EM). However, the causality and direction of this correlation is unclear. This study aimed to examine the bidirectional connection between lipid profiles and the risk of EM using publicly available genome-wide association study (GWAS) summary statistics.

METHODS

Eligible exposure variables such as levels of triglycerides (TG), total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) were selected using a two-sample Mendelian randomization (MR) analysis method following a series of quality control procedures. Data on EM were obtained from the publicly available Finnish database of European patients. Inverse variance weighted (IVW), MR Egger, weighted median, and weighted mode methods were used to analyze the causal relationship between lipid exposure and EM, exclude confounders, perform sensitivity analyses, and assess the stability of the results. Reverse MR analyses were performed with EM as exposure and lipid results as study outcomes.

RESULTS

IVW analysis results identified HDL as a protective factor for EM, while TG was shown to be a risk factor for EM. Subgroup analyses based on the site of the EM lesion identified HDL as a protective factor for EM of the uterus, while TG was identified a risk factor for the EM of the fallopian tube, ovary, and pelvic peritoneum. Reverse analysis did not reveal any effect of EM on the levels of lipids.

CONCLUSION

Blood lipids, such as HDL and TG, may play an important role in the development and progression of EM. However, EM does not lead to dyslipidemia.

Dried fruit intake can lower the risk of ulcerative colitis: evidence from a Mendelian randomization study

BACKGROUND AND OBJECTIVES

This study aims to examine the causal relationship between dietary factors and ulcerative colitis (UC).

METHODS AND STUDY DESIGN

The analysis utilized data from genome-wide association studies (GWAS). Dried fruit, vegetables, processed meat, fresh fruit, and cereal intake were examined as exposure factors. UC was considered the outcome. Two-sample Mendelian randomization (TSMR) analysis was performed using methods. Heterogeneity and horizontal pleiotropy assessments were conducted to ensure the robustness of our findings. Additionally, we applied False Discovery Rate (FDR) corrections for multiple tests.

RESULTS

The analysis revealed a significant inverse causal relationship between dried fruit intake and UC risk (odds ratio [OR]: 0.488, 95% confidence interval [CI]: 0.261 to 0.915, p = 0.025). No significant association was observed between vegetable intake (OR: 1.742, 95% CI: 0.561 to 5.415, p = 0.337), processed meat intake (OR: 1.136, 95% CI: 0.552 to 2.339, p = 0.729), fresh fruit intake (OR: 0.977, 95% CI: 0.465 to 2.054, p = 0.952), cereal intake (OR: 1.195, 95% CI: 0.669 to 2.134, p = 0.547). The low heterogeneity observed across analyses and the confirmation of stability through leave-one-out analysis reinforce the reliability of these results. Moreover, after adjusting for multiple tests, none of the dietary factors reached a p-value below the conventional significance threshold of 0.05.

CONCLUSIONS

This study provides evidence of a potential association between dried fruit intake and a reduced risk of UC. Further MR studies incorporating larger GWAS datasets are needed to confirm these findings.

Large-scale transcriptomic and genomic analyses reveal a novel functional gene SERPINB6 for chicken carcass traits

BACKGROUND

Carcass traits are crucial indicators of meat production efficiency. However, the molecular regulatory mechanisms associated with these traits remain unclear.

RESULTS

In this study, we conducted comprehensive transcriptomic and genomic analyses on 399 Tiannong partridge chickens to identify key genes and variants associated with carcass traits and to elucidate the underlying regulatory mechanisms. Based on association analyses with the elastic net (EN) model, we identified 12 candidate genes (AMY1A, AP3B2, CEBPG, EEF2, EIF4EBP1, FGFR1, FOXD3, GOLM1, LOC107052698, PABPC1, SERPINB6 and TBC1D16) for 4 carcass-related traits, namely live weight, dressed weight, eviscerated weight, and breast muscle weight. SERPINB6 was identified as the only overlapping gene by 3 analyses, EN model analysis, weighted gene co-expression network analysis and differential expression analysis. Cell-level experiments confirmed that SERPINB6 promotes the proliferation of chicken DF1 cells and primary myoblasts. Further expression genome-wide association study and association analysis indicated that rs317934171 is the critical site that enhances SERPINB6 expression. Furthermore, a dual-luciferase reporter assay proved that gga-miR-1615 targets the 3'UTR of SERPINB6.

CONCLUSIONS

Collectively, our findings reveal that SERPINB6 serves as a novel gene for chicken carcass traits by promoting fibroblast and myoblast proliferation. Additionally, the downstream variant rs317934171 regulates SERPINB6 expression. These results identify a new target gene and molecular marker for the molecular mechanisms of chicken carcass traits.

A Comprehensive Analysis of Conventional Acupuncture and Pharmacological Approaches for Cardiac Arrhythmias: An Umbrella Review

With a global incidence of approximately 3.4% and an annual mortality rate of 3.7 million, cardiac arrhythmias (CAs) are a pressing global health issue. Their increasing prevalence, especially among older people, is intensifying the challenge for health care systems worldwide. This study aims to compare the safety and effectiveness of acupuncture and pharmacological treatments for CAs, addressing critical gaps in understanding optimal therapeutic approaches. A search of PubMed, EMBASE, and the Cochrane database of systematic reviews was performed to identify data compiled through September 2023 for this umbrella review. Randomized controlled trials (RCTs) as the foundation for meta-analyses and peer-reviewed systematic reviews were the primary focus of the literature search. The Grading of Recommendations Assessment, Development, and Evaluation method was used to assess the overall certainty of the evidence, whereas AMSTAR 2 and the Cochrane Collaboration tool were used to evaluate the quality of the included reviews. Following a comprehensive review, three systematic analyses of 27 RCTs were integrated. Acupuncture led to a slightly greater reduction in the recurrence rate of paroxysmal supraventricular tachycardia (SVT) compared to standard pharmaceutical therapy (risk ratio [RR], 1.06; 95% confidence interval [CI], 0.88-1.27; I2 = 56%; P = .55), although the difference was not statistically significant. In contrast, acupuncture significantly outperformed pharmacological treatment in the context of ventricular premature beats (VPBs) (RR, 1.16; 95 CI, 1.08-1.25; I2 = 0%; P < .0001). The reduction in paroxysmal atrial fibrillation (AF)/atrial flutter was increased with acupuncture, albeit without statistical significance (RR, 1.12; 95% CI, 0.88-1.42; I2 = 0%; P = .36). Acupuncture also led to a greater reduction in heart rate (HR) compared to pharmaceutical treatment despite notable heterogeneity and a lack of statistical significance (mean difference, -1.55; 95% CI, -41.37 to 38.28; I2 = 99%; P = .94). Adverse events were effectively managed, affirming the favorable safety profile of acupuncture. Our study suggests that acupuncture leads to a greater reduction in the recurrence rates of VPBs, AF, and atrial flutter but not significantly so in paroxysmal SVT or post-treatment HR. While promising for specific arrhythmias, the varying effectiveness of acupuncture underscores the need for further research and clinical assessment to determine its precise role and suitability in managing particular cardiac conditions.

Looking back on 30+ years of the Johnston County Osteoarthritis Project while looking forward with the Johnston County Health Study: A narrative review

Over the last 30 years, knowledge of the epidemiology of osteoarthritis (OA) has dramatically advanced, and Osteoarthritis and Cartilage has been on the forefront of disseminating research findings from large OA cohort studies, including the Johnston County OA Project (JoCoOA). The JoCoOA is a population-based, prospective longitudinal cohort that began roughly 30 years ago with a key focus on understanding prevalence, incidence, and progression of OA, as well as its risk factors, in a predominantly rural population of Black and White adults 45+ years old in a county in the southeastern United States. Selected OA results that will be discussed in this review include racial differences, lifetime risk, biomarkers, mortality, and OA risk factors. The new Johnston County Health Study will also be introduced. This new cohort study of OA and comorbid conditions builds upon current OA knowledge and JoCoOA infrastructure and is designed to reflect changes in demographics and urbanization in the county and the region.

Association of exposure factors and their causal relationship with oral cancer: A Mendelian randomization study

OBJECTIVES

There is a strong association among risk factors for oral cancer (ORCA), such as smoking, alcohol consumption, fiber intake, and red meat intake. The apparent synergistic effects reported in previous observational studies may also underestimate the independent effects. Our study aims to further explore the potential etiology and causality of oral cancer.

MATERIALS AND METHODS

This study used the genome-wide associations study database (GWAS) in European populations for Mendelian randomization (MR) analysis to explore exposure factors associated with ORCA and detect the genetic causality between these exposures and ORCA risk.

RESULTS

Our results demonstrated that in univariate MR analysis, the five exposure factors (celery intake, average weekly beer and cider intake, spirits intake, and pork intake) were risk factors, and oily fish intake was a safety factor, but in multivariate MR analysis, pork intake had the greatest impact on oral cancer when the five food/drink intakes were simultaneously consumed.

CONCLUSIONS

The causal relationship between the five exposure factors (oily fish intake, celery intake, pork intake, average weekly beer and cider intake, and spirits intake) and oral cancer was analyzed. The causal effects of pork on oral cancer may be underestimated.

CLINICAL RELEVANCE

Prevention of oral cancer requires better education about lifestyle-related risk factors, and improved awareness and tools for early diagnosis. Our study provides some risk factors that cannot be ignored for the cause prevention of oral cancer, such as pork intake, and its role in oral cancer prevention and control.

Genetic effects of sequence-conserved enhancer-like elements on human complex traits

BACKGROUND

The vast majority of findings from human genome-wide association studies (GWAS) map to non-coding sequences, complicating their mechanistic interpretations and clinical translations. Non-coding sequences that are evolutionarily conserved and biochemically active could offer clues to the mechanisms underpinning GWAS discoveries. However, genetic effects of such sequences have not been systematically examined across a wide range of human tissues and traits, hampering progress to fully understand regulatory causes of human complex traits.

RESULTS

Here we develop a simple yet effective strategy to identify functional elements exhibiting high levels of human-mouse sequence conservation and enhancer-like biochemical activity, which scales well to 313 epigenomic datasets across 106 human tissues and cell types. Combined with 468 GWAS of European (EUR) and East Asian (EAS) ancestries, these elements show tissue-specific enrichments of heritability and causal variants for many traits, which are significantly stronger than enrichments based on enhancers without sequence conservation. These elements also help prioritize candidate genes that are functionally relevant to body mass index (BMI) and schizophrenia but were not reported in previous GWAS with large sample sizes.

CONCLUSIONS

Our findings provide a comprehensive assessment of how sequence-conserved enhancer-like elements affect complex traits in diverse tissues and demonstrate a generalizable strategy of integrating evolutionary and biochemical data to elucidate human disease genetics.

Multi-tissue transcriptome-wide association study reveals susceptibility genes and drug targets for insulin resistance-relevant phenotypes

AIM

Genome-wide association studies (GWAS) have identified multiple susceptibility loci associated with insulin resistance (IR)-relevant phenotypes. However, the genes responsible for these associations remain largely unknown. We aim to identify susceptibility genes for IR-relevant phenotypes via a transcriptome-wide association study.

MATERIALS AND METHODS

We conducted a large-scale multi-tissue transcriptome-wide association study for IR (Insulin Sensitivity Index, homeostasis model assessment-IR, fasting insulin) and lipid-relevant traits (high-density lipoprotein cholesterol, triglycerides, low-density lipoprotein cholesterol and total cholesterol) using the largest GWAS summary statistics and precomputed gene expression weights of 49 human tissues. Conditional and joint analyses were implemented to identify significantly independent genes. Furthermore, we estimated the causal effects of independent genes by Mendelian randomization causal inference analysis.

RESULTS

We identified 1190 susceptibility genes causally associated with IR-relevant phenotypes, including 58 genes that were not implicated in the original GWAS. Among them, 11 genes were further supported in differential expression analyses or a gene knockout mice database, such as KRIT1 showed both significantly differential expression and IR-related phenotypic effects in knockout mice. Meanwhile, seven proteins encoded by susceptibility genes were targeted by clinically approved drugs, and three of these genes (H6PD, CACNB2 and DRD2) have been served as drug targets for IR-related diseases/traits. Moreover, drug repurposing analysis identified four compounds with profiles opposing the expression of genes associated with IR risk.

CONCLUSIONS

Our study provided new insights into IR aetiology and avenues for therapeutic development.

Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). P<0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04-1.12; P<0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; P=0.11) or in the reverse direction (β=-0.012; P=0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (β=-0.084; P<0.001), but the reverse direction was not significant (P=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (P=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=-0.092; P<0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.

Recent advances in regulating lipid metabolism to prevent coronary heart disease

The pathogenesis of coronary heart disease is a highly complex process, with lipid metabolism disorders being closely linked to its development. Therefore, this paper analyzes the various factors that influence lipid metabolism, including obesity, genes, intestinal microflora, and ferroptosis, through a comprehensive review of basic and clinical studies. Additionally, this paper delves deeply into the pathways and patterns of coronary heart disease. Based on these findings, it proposes various intervention pathways and therapeutic methods, such as the regulation of lipoprotein enzymes, lipid metabolites, and lipoprotein regulatory factors, as well as the modulation of intestinal microflora and the inhibition of ferroptosis. Ultimately, this paper aims to offer new ideas for the prevention and treatment of coronary heart disease.

Genome-wide association studies and fine-mapping identify genomic loci for n-3 and n-6 polyunsaturated fatty acids in Hispanic American and African American cohorts

Omega-3 (n-3) and omega-6 (n-6) polyunsaturated fatty acids (PUFAs) play critical roles in human health. Prior genome-wide association studies (GWAS) of n-3 and n-6 PUFAs in European Americans from the CHARGE Consortium have documented strong genetic signals in/near the FADS locus on chromosome 11. We performed a GWAS of four n-3 and four n-6 PUFAs in Hispanic American (n = 1454) and African American (n = 2278) participants from three CHARGE cohorts. Applying a genome-wide significance threshold of P < 5 × 10-8, we confirmed association of the FADS signal and found evidence of two additional signals (in DAGLA and BEST1) within 200 kb of the originally reported FADS signal. Outside of the FADS region, we identified novel signals for arachidonic acid (AA) in Hispanic Americans located in/near genes including TMX2, SLC29A2, ANKRD13D and POLD4, and spanning a > 9 Mb region on chromosome 11 (57.5 Mb ~ 67.1 Mb). Among these novel signals, we found associations unique to Hispanic Americans, including rs28364240, a POLD4 missense variant for AA that is common in CHARGE Hispanic Americans but absent in other race/ancestry groups. Our study sheds light on the genetics of PUFAs and the value of investigating complex trait genetics across diverse ancestry populations.

Blood cell traits' GWAS loci colocalization with variation in PU.1 genomic occupancy prioritizes causal noncoding regulatory variants

Genome-wide association studies (GWASs) have uncovered numerous trait-associated loci across the human genome, most of which are located in noncoding regions, making interpretation difficult. Moreover, causal variants are hard to statistically fine-map at many loci because of widespread linkage disequilibrium. To address this challenge, we present a strategy utilizing transcription factor (TF) binding quantitative trait loci (bQTLs) for colocalization analysis to identify trait associations likely mediated by TF occupancy variation and to pinpoint likely causal variants using motif scores. We applied this approach to PU.1 bQTLs in lymphoblastoid cell lines and blood cell trait GWAS data. Colocalization analysis revealed 69 blood cell trait GWAS loci putatively driven by PU.1 occupancy variation. We nominate PU.1 motif-altering variants as the likely shared causal variants at 51 loci. Such integration of TF bQTL data with other GWAS data may reveal transcriptional regulatory mechanisms and causal noncoding variants underlying additional complex traits.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.

Association between periodontitis and breast cancer: two-sample Mendelian randomization study

OBJECTIVES

The purpose of this study was to investigate whether there is a causal relationship between periodontitis and breast cancer by Mendelian randomization analysis.

MATERIALS AND METHODS

We performed a two-sample bidirectional Mendelian randomization (MR) analysis using publicly released genome-wide association studies (GWAS) statistics. The inverse-variance weighted (IVW) method was used as the primary analysis. We applied complementary methods, including weighted median, weighted mode, simple mode, MR-Egger regression, and MR-pleiotropy residual sum and outlier (MR-PRESSO) to detect and correct for the effect of horizontal pleiotropy.

RESULTS

IVW MR analysis showed no effect of periodontitis on breast cancer (IVW OR=0.99, P =0.14). Similarly, no significant causal relationship between breast cancer and periodontitis was found in reverse MR analysis (IVW OR=0.95, P =0.83). The results of MR-Egger regression, weighted median, and weighted mode methods were consistent with those of the IVW method. Based on sensitivity analyses, horizontal pleiotropy is unlikely to distort causal estimates.

CONCLUSIONS

Although observational studies have reported an association between periodontitis and breast cancer, the results of our MR analysis do not support a causal relationship between periodontitis and breast cancer.

CLINICAL RELEVANCE

Mendelian randomization study can more clearly analyze the causal relationship between periodontitis and breast cancer, in order to provide a certain reference for clinicians and deepen the understanding of the relationship between periodontitis and breast cancer, to explore more possible associations between periodontitis and systemic diseases.

Comparison of the structure-function properties of wild-type human apoA-V and a C-terminal truncation associated with elevated plasma triglycerides

Background

Plasma triglycerides (TGs) are causally associated with coronary artery disease and acute pancreatitis. Apolipoprotein A-V (apoA-V, gene APOA5) is a liver-secreted protein that is carried on triglyceride-rich lipoproteins and promotes the enzymatic activity of lipoprotein lipase (LPL), thereby reducing TG levels. Little is known about apoA-V structure-function; naturally occurring human APOA5 variants can provide novel insights.

Methods

We used hydrogen-deuterium exchange mass spectrometry to determine the secondary structure of human apoA-V in lipid-free and lipid-associated conditions and identified a C-terminal hydrophobic face. Then, we used genomic data in the Penn Medicine Biobank to identify a rare variant, Q252X, predicted to specifically eliminate this region. We interrogated the function of apoA-V Q252X using recombinant protein in vitro and in vivo in apoa5 knockout mice.

Results

Human apoA-V Q252X carriers exhibited elevated plasma TG levels consistent with loss of function. Apoa5 knockout mice injected with AAV vectors expressing wildtype and variant APOA5-AAV recapitulated this phenotype. Part of the loss of function is due to reduced mRNA expression. Functionally, recombinant apoA-V Q252X was more readily soluble in aqueous solutions and more exchangeable with lipoproteins than WT apoA-V. Despite lacking the C-terminal hydrophobic region (a putative lipid binding domain) this protein also decreased plasma TG in vivo.

Conclusions

Deletion of apoA-V's C-terminus leads to reduced apoA-V bioavailability in vivo and higher TG levels. However, the C-terminus is not required for lipoprotein binding or enhancement of intravascular lipolytic activity. WT apoA-V is highly prone to aggregation, and this property is markedly reduced in recombinant apoA-V lacking the C-terminus.

Systematic elucidation of genetic mechanisms underlying cholesterol uptake

Genetic variation contributes greatly to LDL cholesterol (LDL-C) levels and coronary artery disease risk. By combining analysis of rare coding variants from the UK Biobank and genome-scale CRISPR-Cas9 knockout and activation screening, we have substantially improved the identification of genes whose disruption alters serum LDL-C levels. We identify 21 genes in which rare coding variants significantly alter LDL-C levels at least partially through altered LDL-C uptake. We use co-essentiality-based gene module analysis to show that dysfunction of the RAB10 vesicle transport pathway leads to hypercholesterolemia in humans and mice by impairing surface LDL receptor levels. Further, we demonstrate that loss of function of OTX2 leads to robust reduction in serum LDL-C levels in mice and humans by increasing cellular LDL-C uptake. Altogether, we present an integrated approach that improves our understanding of genetic regulators of LDL-C levels and provides a roadmap for further efforts to dissect complex human disease genetics.