Hyperlipidemias and Obesity
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ABSTRACT:
SUBMITTER: Thiriet M
PROVIDER: S-EPMC7123371 | biostudies-literature | 2018 Jan
REPOSITORIES: biostudies-literature
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Project description:Monogenic hyperlipidemias are a group of inherited disorders characterized by elevated plasma concentrations of lipids and lipoproteins. High plasma concentrations of lipids are the most frequent risk factor for cardiovascular disease. Monogenic hyperlipidemias are a minor cause with respect to multifactorial hyperlipidemias. Diagnosis is based on clinical findings and lipid panel measurements. Genetic testing is useful for confirming diagnosis and for differential diagnosis, recurrence risk calculation and prenatal diagnosis in families with a known mutation. Monogenic hyperlipidemias can have either autosomal dominant or recessive inheritance.
| S-EPMC7233650 | biostudies-literature
Project description:Background We asked whether, after excluding familial hypercholesterolemia, individuals with high low-density lipoprotein cholesterol ( LDL -C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population-based hyperlipidemias. Methods and Results We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first-degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias ( LDL -C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta-analysis of the hyperlipidemic families and the population cohort (high LDL -C: hazard ratio, 1.74 [95% CI, 1.48-2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09-1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid-lowering medication. In lipidomic profiling, high LDL -C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P-value range 0.038-2.3×10-56). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population ( LDL -C: r=0.80; triacylglycerides: r=0.96; no lipid species deviated between the cohorts). Conclusions Hyperlipidemias with family history conferred similar coronary artery disease risk as population-based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL -C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population-ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.
| S-EPMC6662358 | biostudies-literature
Project description:BACKGROUND:Hyperlipidemia is a highly heritable risk factor for coronary artery disease (CAD). While monogenic familial hypercholesterolemia associates with severely increased CAD risk, it remains less clear to what extent a high polygenic load of a large number of LDL (low-density lipoprotein) cholesterol (LDL-C) or triglyceride (TG)-increasing variants associates with increased CAD risk. METHODS:We derived polygenic risk scores (PRSs) with ?6M variants separately for LDL-C and TG with weights from a UK Biobank-based genome-wide association study with ?324K samples. We evaluated the impact of polygenic hypercholesterolemia and hypertriglyceridemia to lipid levels in 27 039 individuals from the National FINRISK Study (FINRISK) cohort and to CAD risk in 135 638 individuals (13 753 CAD cases) from the FinnGen project (FinnGen). RESULTS:In FINRISK, median LDL-C was 3.39 (95% CI, 3.38-3.40) mmol/L, and it ranged from 2.87 (95% CI, 2.82-2.94) to 3.78 (95% CI, 3.71-3.83) mmol/L between the lowest and highest 5% of the LDL-C PRS distribution. Median TG was 1.19 (95% CI, 1.18-1.20) mmol/L, ranging from 0.97 (95% CI, 0.94-1.00) to 1.55 (95% CI, 1.48-1.61) mmol/L with the TG PRS. In FinnGen, comparing the highest 5% of the PRS to the lowest 95%, CAD odds ratio was 1.36 (95% CI, 1.24-1.49) for the LDL-C PRS and 1.31 (95% CI, 1.19-1.43) for the TG PRS. These estimates were only slightly attenuated when adjusting for a CAD PRS (odds ratio, 1.26 [95% CI, 1.16-1.38] for LDL-C and 1.24 [95% CI, 1.13-1.36] for TG PRS). CONCLUSIONS:The CAD risk associated with a high polygenic load for lipid-increasing variants was proportional to their impact on lipid levels and partially overlapping with a CAD PRS. In contrast with a PRS for CAD, the lipid PRSs point to known and directly modifiable risk factors providing additional guidance for clinical translation.
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Project description:High fat feeding rather than obesity drives taxonomical and functional changes in the gut microbiota in mice
| PRJEB10308 | ENA
Project description:In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.
The SCOOP samples are part of the Obesity group and will undergo exome sequencing. Severe Childhood Onset Obesity Project (SCOOP) is a sub-cohort of the Genetics Of Obesity Study (GOOS) cohort established by Sadaf Farooqi and Steve O’Rahilly at the University of Cambridge over the last 12 years. The GOOS cohort contains >4,000 patients of diverse geographic origin, many of whom have monogenic and syndromic forms of obesity, and includes patients that are offspring of consanguineous union. SCOOP is a subset of >1500 UK Caucasian patients with severe, early onset obesity (all patients have a BMI Standard Deviation Score (SDS) > 3 and obesity onset before the age of 10 years), in whom all known monogenic causes of obesity have been excluded. GWAS data on the SCOOP cohort will be available (WTCCC2 independent study) at the time of the start of this study. Data from this cohort has demonstrated that the prevalence of the common obesity risk alleles in FTO, MC4R and NEGR1 are amongst the highest within SCOOP, demonstrating its value also in the study of genetic variants with an impact on more common obesity. For further information with regard to this cohort please contact Sadaf Farooqi (isf20@medschl.cam.ac.uk).
| EGAS00001000124 | EGA
Project description:In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. These TwinsUK samples are a subset of the TwinsUK cohort samples with a BMI>=40 that will be exome sequenced by the Obesity group.
| EGAS00001000306 | EGA
Project description:In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The GS samples are part of the Obesity group and will undergo exome sequencing.
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