| 1. |
- Kanoni, Stavroula, et al.
(författare)
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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
- 2022
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Ingår i: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N=1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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| 2. |
- van de Vegte, Yordi, et al.
(författare)
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Genetic insights into resting heart rate and its role in cardiovascular disease
- 2023
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- The genetics and clinical consequences of resting heart rate (RHR) remain incompletely understood. Here, the authors discover new genetic variants associated with RHR and find that higher genetically predicted RHR decreases risk of atrial fibrillation and ischemic stroke. Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.
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| 3. |
- Carland, Corinne, et al.
(författare)
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Proteomic analysis of 92 circulating proteins and their effects in cardiometabolic diseases
- 2023
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Ingår i: Clinical Proteomics. - : BMC. - 1542-6416 .- 1559-0275. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Human plasma contains a wide variety of circulating proteins. These proteins can be important clinical biomarkers in disease and also possible drug targets. Large scale genomics studies of circulating proteins can identify genetic variants that lead to relative protein abundance.Methods: We conducted a meta-analysis on genome-wide association studies of autosomal chromosomes in 22,997 individuals of primarily European ancestry across 12 cohorts to identify protein quantitative trait loci (pQTL) for 92 cardiometabolic associated plasma proteins.Results: We identified 503 (337 cis and 166 trans) conditionally independent pQTLs, including several novel variants not reported in the literature. We conducted a sex-stratified analysis and found that 118 (23.5%) of pQTLs demonstrated heterogeneity between sexes. The direction of effect was preserved but there were differences in effect size and significance. Additionally, we annotate trans-pQTLs with nearest genes and report plausible biological relationships. Using Mendelian randomization, we identified causal associations for 18 proteins across 19 phenotypes, of which 10 have additional genetic colocalization evidence. We highlight proteins associated with a constellation of cardiometabolic traits including angiopoietin-related protein 7 (ANGPTL7) and Semaphorin 3F (SEMA3F).Conclusion: Through large-scale analysis of protein quantitative trait loci, we provide a comprehensive overview of common variants associated with plasma proteins. We highlight possible biological relationships which may serve as a basis for further investigation into possible causal roles in cardiometabolic diseases.
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| 4. |
- Holliday, Katelyn M., et al.
(författare)
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Gaseous air pollutants and DNA methylation in a methylome-wide association study of an ethnically and environmentally diverse population of US adults
- 2022
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Ingår i: Environmental Research. - : Elsevier. - 0013-9351 .- 1096-0953. ; 212
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Tidskriftsartikel (refereegranskat)abstract
- Epigenetic mechanisms may underlie air pollution-health outcome associations. We estimated gaseous air pollutant-DNA methylation (DNAm) associations using twelve subpopulations within Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) cohorts (n = 8397; mean age 61.3 years; 83% female; 46% African-American, 46% European-American, 8% Hispanic/Latino). We used geocoded participant address-specific mean ambient carbon monoxide (CO), nitrogen oxides (NO2; NOx), ozone (O-3), and sulfur dioxide (SO2) concentrations estimated over the 2-, 7-, 28-, and 365-day periods before collection of blood samples used to generate Illumina 450 k array leukocyte DNAm measurements. We estimated methylome-wide, subpopulation-and race/ethnicity-stratified pollutant-DNAm associations in multi-level, linear mixed-effects models adjusted for sociodemographic, behavioral, meteorological, and technical covariates. We combined stratum-specific estimates in inverse variance-weighted meta-analyses and characterized significant associations (false discovery rate; FDR<0.05) at Cytosine-phosphate-Guanine (CpG) sites without among-strata heterogeneity (P-Cochran's Q > 0.05). We attempted replication in the Cooperative Health Research in Region of Augsburg (KORA) study and Normative Aging Study (NAS). We observed a -0.3 (95% CI: -0.4, -0.2) unit decrease in percent DNAm per interquartile range (IQR, 7.3 ppb) increase in 28-day mean NO2 concentration at cg01885635 (chromosome 3; regulatory region 290 bp upstream from ZNF621; FDR = 0.03). At intragenic sites cg21849932 (chromosome 20; LIME1; intron 3) and cg05353869 (chromosome 11; KLHL35; exon 2), we observed a -0.3 (95% CI: -0.4, -0.2) unit decrease (FDR = 0.04) and a 1.2 (95% CI: 0.7, 1.7) unit increase (FDR = 0.04), respectively, in percent DNAm per IQR (17.6 ppb) increase in 7-day mean ozone concentration. Results were not fully replicated in KORA and NAS. We identified three CpG sites potentially susceptible to gaseous air pollution-induced DNAm changes near genes relevant for cardiovascular and lung disease. Further harmonized investigations with a range of gaseous pollutants and averaging durations are needed to determine the effect of gaseous air pollutants on DNA methylation and ultimately gene expression.
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| 5. |
- Jhun, Mina-A, et al.
(författare)
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A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids
- 2021
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups. Abnormal blood lipid levels are important risk factors for cardiovascular and other various diseases. Here the authors conduct a large-scale multi-ethnic epigenome-wide association study combined with epigenetic (cis-QTL and eQTM) data, and identify CpG-lipid traits associations that are specific to or common across racial/ethnic groups.
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| 6. |
- Klaric, Lucija, et al.
(författare)
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Mendelian randomisation identifies alternative splicing of the FAS death receptor as a mediator of severe COVID-19.
- 2021
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Ingår i: medRxiv : the preprint server for health sciences. - : Cold Spring Harbor Laboratory. ; , s. 1-28
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Severe COVID-19 is characterised by immunopathology and epithelial injury. Proteomic studies have identified circulating proteins that are biomarkers of severe COVID-19, but cannot distinguish correlation from causation. To address this, we performed Mendelian randomisation (MR) to identify proteins that mediate severe COVID-19. Using protein quantitative trait loci (pQTL) data from the SCALLOP consortium, involving meta-analysis of up to 26,494 individuals, and COVID-19 genome-wide association data from the Host Genetics Initiative, we performed MR for 157 COVID-19 severity protein biomarkers. We identified significant MR results for five proteins: FAS, TNFRSF10A, CCL2, EPHB4 and LGALS9. Further evaluation of these candidates using sensitivity analyses and colocalization testing provided strong evidence to implicate the apoptosis-associated cytokine receptor FAS as a causal mediator of severe COVID-19. This effect was specific to severe disease. Using RNA-seq data from 4,778 individuals, we demonstrate that the pQTL at the FAS locus results from genetically influenced alternate splicing causing skipping of exon 6. We show that the risk allele for very severe COVID-19 increases the proportion of transcripts lacking exon 6, and thereby increases soluble FAS. Soluble FAS acts as a decoy receptor for FAS-ligand, inhibiting apoptosis induced through membrane-bound FAS. In summary, we demonstrate a novel genetic mechanism that contributes to risk of severe of COVID-19, highlighting a pathway that may be a promising therapeutic target.
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| 7. |
- Lind, Lars, et al.
(författare)
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Large-scale plasma protein profiling of incident myocardial infarction, ischemic stroke, and heart failure
- 2021
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Ingår i: Journal of the American Heart Association. - : American Heart Association Inc.. - 2047-9980 .- 2047-9980. ; 10:23
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: We recently reported a link between plasma levels of 2 of 84 cardiovascular disease (CVD)– related proteins and the 3 major CVDs, myocardial infarction, ischemic stroke, and heart failure. The present study investigated whether measurement of almost 10 times the number of proteins could lead to discovery of additional risk markers for CVD. METHODS AND RESULTS: We measured 742 proteins using the proximity extension assay in 826 male participants of ULSAM (Uppsala Longitudinal Study of Adult Men) who were free from CVD at the age of 70 years. Cox proportional hazards models were adjusted for age only, as well as all traditional risk factors. During a 12.5-year median follow-up (maximal, 22.0 years), 283 incident CVDs occurred. Forty-one proteins were significantly (false discovery rate <0.05) related to the combined end point of incident CVD, with N-terminal pro– brain natriuretic peptide as the top finding, while 53 proteins were related to incident myocardial infarction. A total of 13 and 16 proteins were significantly related to incident ischemic stroke and heart failure, respectively. Growth differentiation factor 15, 4-disulfide core domain protein 2, and kidney injury molecule were related to all of the 3 major CVD outcomes. A lasso selection of 11 proteins improved discrimination of incident CVD by 5.0% (P=0.0038). CONCLUSIONS: Large-scale proteomics seem useful for the discovery of new risk markers for CVD and to improve risk prediction in an elderly population of men. Further studies are needed to replicate the findings in independent samples of both men and women of different ages. © 2021 The Authors.
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| 8. |
- Zanetti, Daniela, et al.
(författare)
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Comprehensive Investigation of Circulating Biomarkers and Their Causal Role in Atherosclerosis-Related Risk Factors and Clinical Events
- 2020
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Ingår i: Circulation. - : Lippincott Williams & Wilkins. - 2574-8300. ; 13:6, s. 671-685
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Tidskriftsartikel (refereegranskat)abstract
- Background: Circulating biomarkers have been previously associated with atherosclerosis-related risk factors, but the nature of these associations is incompletely understood.Methods: We performed multivariable-adjusted regressions and 2-sample Mendelian randomization analyses to assess observational and causal associations of 27 circulating biomarkers with 7 cardiovascular traits in up to 451 933 participants of the UK Biobank.Results: After multiple-testing correction (alpha=1.3x10(-4)), we found a total of 15, 9, 21, 22, 26, 24, and 26 biomarkers strongly associated with coronary artery disease, ischemic stroke, atrial fibrillation, type 2 diabetes, systolic blood pressure, body mass index, and waist-to-hip ratio; respectively. The Mendelian randomization analyses confirmed strong evidence of previously suggested causal associations for several glucose- and lipid-related biomarkers with type 2 diabetes and coronary artery disease. Particularly interesting findings included a protective role of IGF-1 (insulin-like growth factor 1) in systolic blood pressure, and the strong causal association of lipoprotein(a) in coronary artery disease development (beta, -0.13; per SD change in exposure and outcome and odds ratio, 1.28; P=2.6x10(-4) and P=7.4x10(-35), respectively). In addition, our results indicated a causal role of increased ALT (alanine aminotransferase) in the development of type 2 diabetes and hypertension (odds ratio, 1.59 and beta, 0.06, per SD change in exposure and outcome; P=4.8x10(-11) and P=6.0x10(-5)). Our results suggest that it is unlikely that CRP (C-reactive protein) and vitamin D play causal roles of any meaningful magnitude in development of cardiometabolic disease.Conclusions: We confirmed and extended known associations and reported several novel causal associations providing important insights about the cause of these diseases, which can help accelerate new prevention strategies.
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| 9. |
- Zanetti, Daniela, et al.
(författare)
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Plasma proteomic signatures of a direct measure of insulin sensitivity in two population cohorts
- 2023
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Ingår i: Diabetologia. - : Springer. - 0012-186X .- 1432-0428. ; 66:9, s. 1643-1654
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis The euglycaemic-hyperinsulinaemic clamp (EIC) is the reference standard for the measurement of whole-body insulin sensitivity but is laborious and expensive to perform. We aimed to assess the incremental value of high-through-put plasma proteomic profiling in developing signatures correlating with the M value derived from the EIC.Methods We measured 828 proteins in the fasting plasma of 966 participants from the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study and 745 participants from the Uppsala Longitudinal Study of Adult Men (ULSAM) using a high-throughput proximity extension assay. We used the least absolute shrinkage and selection operator (LASSO) approach using clinical variables and protein measures as features. Models were tested within and across cohorts. Our primary model performance metric was the proportion of the M value variance explained (R-2).Results A standard LASSO model incorporating 53 proteins in addition to routinely available clinical variables increased the M value R-2 from 0.237 (95% CI 0.178, 0.303) to 0.456 (0.372, 0.536) in RISC. A similar pattern was observed in ULSAM, in which the M value R-2 increased from 0.443 (0.360, 0.530) to 0.632 (0.569, 0.698) with the addition of 61 proteins. Models trained in one cohort and tested in the other also demonstrated significant improvements in R-2 despite differences in baseline cohort characteristics and clamp methodology (RISC to ULSAM: 0.491 [0.433, 0.539] for 51 proteins; ULSAM to RISC: 0.369 [0.331, 0.416] for 67 proteins). A randomised LASSO and stability selection algorithm selected only two proteins per cohort (three unique proteins), which improved R-2 but to a lesser degree than in standard LASSO models: 0.352 (0.266, 0.439) in RISC and 0.495 (0.404, 0.585) in ULSAM. Reductions in improvements of R-2 with randomised LASSO and stability selection were less marked in cross-cohort analyses (RISC to ULSAM R-2 0.444 [0.391, 0.497]; ULSAM to RISC R-2 0.348 [0.300, 0.396]). Models of proteins alone were as effective as models that included both clinical variables and proteins using either standard or randomised LASSO. The single most consistently selected protein across all analyses and models was IGF-binding protein 2.Conclusions/interpretation A plasma proteomic signature identified using a standard LASSO approach improves the cross-sectional estimation of the M value over routine clinical variables. However, a small subset of these proteins identified using a stability selection algorithm affords much of this improvement, especially when considering cross-cohort analyses. Our approach provides opportunities to improve the identification of insulin-resistant individuals at risk of insulin resistance-related adverse health consequences.
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