A point-of-care test of active matrix metalloproteinase-8 predicts triggering receptor expressed on myeloid cells-1 levels in saliva

Background This cross-sectional study aims to investigate if a point-of-care (PoC) test of active matrix metalloproteinase-8 (aMMP-8) predicts levels of inflammation amplifier triggering receptor expressed on myeloid cells-1 (TREM-1) and its putative ligand the neutrophil peptidoglycan recognition protein 1 (PGLYRP1) in saliva. Methods Forty-seven adolescents, aged 15 to 17 years, were tested with aMMP-8 PoC test, which was followed by a full-mouth clinical examination of the assessment of periodontal, mucosal, and oral health. TREM-1 and PGLYRP1 levels were analyzed by ELISA. The immunofluorometric assay (IFMA) specific for aMMP-8 was used as the reference method. Results Fourteen saliva samples out of a total of 47 showed positivity for aMMP-8 PoC test. Both the TREM-1 and the aMMP-8 (IFMA) levels were significantly elevated among the aMMP-8 PoC test positives compared with the PoC test negatives (P = 4 mm was significantly lower among the adolescents that had a negative aMMP-8 PoC test result, and TREM-1 levels = 4 mm (P <0.001). Conclusion The present study validated usability of aMMP-8 PoC test for predicting "proinflammatory" salivary profile and periodontal health status in adolescents.Peer reviewe

A nonsynonymous SNP within PCDH15 is associated with lipid traits in familial combined hyperlipidemia

Familial combined hyperlipidemia (FCHL) is a common lipid disorder characterized by the presence of multiple lipoprotein phenotypes that increase the risk of premature coronary heart disease. In a previous study, we identified an intragenic microsatellite marker within the protocadherin 15 (PCDH15) gene to be associated with high triglycerides (TGs) in Finnish dyslipidemic families. In this study we analyzed all four known nonsynonymous SNPs within PCDH15 in 1,268 individuals from Finnish and Dutch multigenerational families with FCHL. Association analyses of quantitative traits for SNPs were performed using the QTDT test. The nonsynonymous SNP rs10825269 resulted in a P = 0.0006 for the quantitative TG trait. Additional evidence for association was observed with the same SNP for apolipoprotein B levels (apo-B) (P = 0.0001) and total cholesterol (TC) levels (P = 0.001). None of the other three SNPs tested showed a significant association with any lipid-related trait. We investigated the expression of PCDH15 in different human tissues and observed that PCDH15 is expressed in several tissues including liver and pancreas. In addition, we measured the plasma lipid levels in mice with loss-of-function mutations in Pcdh15 (Pcdh15av-Tg and Pcdh15av-3J) to investigate possible abnormalities in their lipid profile. We observed a significant difference in plasma TG and TC concentrations for the Pcdh15av-3J carriers when compared with the wild type (P = 0.013 and P = 0.044, respectively). Our study suggests that PCDH15 is associated with lipid abnormalities

Family-specific aggregation of lipid GWAS variants confers the susceptibility to familial hypercholesterolemia in a large Austrian family

Background and aims: Hypercholesterolemia confers susceptibility to cardiovascular disease (CVD). Both serum total cholesterol (TC) and LDL-cholesterol (LDL-C) exhibit a strong genetic component (heritability estimates 0.41-0.50). However, a large part of this heritability cannot be explained by the variants identified in recent extensive genome-wide association studies (GWAS) on lipids. Our aim was to find genetic causes leading to high LDL-C levels and ultimately CVD in a large Austrian family presenting with what appears to be autosomal dominant inheritance for familial hypercholesterolemia (FH). Methods: We utilized linkage analysis followed by whole-exome sequencing and genetic risk score analysis using an Austrian multi-generational family with various dyslipidemias, including elevated TC and LDL-C, and one family branch with elevated lipoprotein (a) (Lp(a)). Results: We did not find evidence for genome-wide significant linkage for LDL-C or apparent causative variants in the known FH genes rather, we discovered a particular family-specific combination of nine GWAS LDL-C SNPs (p = 0.02 by permutation), and putative less severe familial hypercholesterolemia mutations in the LDLR and APOB genes in a subset of the affected family members. Separately, high Lp(a) levels observed in one branch of the family were explained primarily by the LPA locus, including short (<23) Kringle IV repeats and rs3798220. Conclusions: Taken together, some forms of FH may be explained by family-specific combinations of LDL-C GWAS SNPs. (c) 2017 Elsevier B.V. All rights reserved.Peer reviewe

Factors associated with postprandial lipemia and apolipoprotein A-V levels in individuals with familial combined hyperlipidemia

Peer reviewe

The Contribution of GWAS Loci in Familial Dyslipidemias

Familial combined hyperlipidemia (FCH) is a complex and common familial dyslipidemia characterized by elevated total cholesterol and/or triglyceride levels with over five-fold risk of coronary heart disease. The genetic architecture and contribution of rare Mendelian and common variants to FCH susceptibility is unknown. In 53 Finnish FCH families, we genotyped and imputed nine million variants in 715 family members with DNA available. We studied the enrichment of variants previously implicated with monogenic dyslipidemias and/or lipid levels in the general population by comparing allele frequencies between the FCH families and population samples. We also constructed weighted polygenic scores using 212 lipid-associated SNPs and estimated the relative contributions of Mendelian variants and polygenic scores to the risk of FCH in the families. We identified, across the whole allele frequency spectrum, an enrichment of variants known to elevate, and a deficiency of variants known to lower LDL-C and/or TG levels among both probands and affected FCH individuals. The score based on TG associated SNPs was particularly high among affected individuals compared to non-affected family members. Out of 234 affected FCH individuals across the families, seven (3%) carried Mendelian variants and 83 (35%) showed high accumulation of either known LDL-C or TG elevating variants by having either polygenic score over the 90th percentile in the population. The positive predictive value of high score was much higher for affected FCH individuals than for similar sporadic cases in the population. FCH is highly polygenic, supporting the hypothesis that variants across the whole allele frequency spectrum contribute to this complex familial trait. Polygenic SNP panels improve identification of individuals affected with FCH, but their clinical utility remains to be defined.Peer reviewe

OSBPL10, a novel candidate gene for high triglyceride trait in dyslipidemic Finnish subjects, regulates cellular lipid metabolism

Analysis of variants in three genes encoding oxysterol-binding protein (OSBP) homologues (OSBPL2, OSBPL9, OSBPL10) in Finnish families with familial low high-density lipoprotein (HDL) levels (N = 426) or familial combined hyperlipidemia (N = 684) revealed suggestive linkage of OSBPL10 single-nucleotide polymorphisms (SNPs) with extreme end high triglyceride (TG; >90th percentile) trait. Prompted by this initial finding, we carried out association analysis in a metabolic syndrome subcohort (Genmets) of Health2000 examination survey (N = 2,138), revealing association of multiple OSBPL10 SNPs with high serum TG levels (>95th percentile). To investigate whether OSBPL10 could be the gene underlying the observed linkage and association, we carried out functional experiments in the human hepatoma cell line Huh7. Silencing of OSBPL10 increased the incorporation of [3H]acetate into cholesterol and both [3H]acetate and [3H]oleate into triglycerides and enhanced the accumulation of secreted apolipoprotein B100 in growth medium, suggesting that the encoded protein ORP10 suppresses hepatic lipogenesis and very-low-density lipoprotein production. ORP10 was shown to associate dynamically with microtubules, consistent with its involvement in intracellular transport or organelle positioning. The data introduces OSBPL10 as a gene whose variation may contribute to high triglyceride levels in dyslipidemic Finnish subjects and provides evidence for ORP10 as a regulator of cellular lipid metabolism

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background 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. Results 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. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: 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. Results: 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. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD