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Heritability and family-based GWAS analyses of the N-acyl ethanolamine and ceramide plasma lipidome.

ABSTRACT: Signalling lipids of the N-acyl ethanolamine (NAE) and ceramide (CER) classes have emerged as potential biomarkers of cardiovascular disease (CVD). We sought to establish the heritability of plasma NAEs (including the endocannabinoid anandamide) and CERs, to identify common DNA variants influencing the circulating concentrations of the heritable lipids, and assess causality of these lipids in CVD using 2-sample Mendelian randomization (2SMR). Nine NAEs and 16 CERs were analyzed in plasma samples from 999 members of 196 British Caucasian families, using targeted ultra-performance liquid chromatography with tandem mass spectrometry. All lipids were significantly heritable (h2 = 36-62%). A missense variant (rs324420) in the gene encoding the enzyme fatty acid amide hydrolase (FAAH), which degrades NAEs, associated at genome-wide association study (GWAS) significance (P < 5 × 10-8) with four NAEs (DHEA, PEA, LEA and VEA). For CERs, rs680379 in the SPTLC3 gene, which encodes a subunit of the rate-limiting enzyme in CER biosynthesis, associated with a range of species (e.g. CER[N(24)S(19)]; P = 4.82 × 10-27). We observed three novel associations between SNPs at the CD83, SGPP1 and DEGS1 loci, and plasma CER traits (P < 5 × 10-8). 2SMR in the CARDIoGRAMplusC4D cohorts (60 801 cases; 123 504 controls) and in the DIAGRAM cohort (26 488 cases; 83 964 controls), using the genetic instruments from our family-based GWAS, did not reveal association between genetically determined differences in CER levels and CVD or diabetes. Two of the novel GWAS loci, SGPP1 and DEGS1, suggested a casual association between CERs and a range of haematological phenotypes, through 2SMR in the UK Biobank, INTERVAL and UKBiLEVE cohorts (n = 110 000-350 000).

SUBMITTER: McGurk KA

PROVIDER: S-EPMC8101358 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Protective mechanisms against drug-induced liver injury are actively being searched to identify new therapeutic targets. Among them, the anti-inflammatory N-acyl ethanolamide (NAE)-peroxisome proliferators activated receptor alpha (PPAR?) system has gained much interest after the identification of its protective role in steatohepatitis and liver fibrosis. An overdose of paracetamol (APAP), a commonly used analgesic/antipyretic drug, causes hepatotoxicity, and it is being used as a liver model. In the present study, we have analyzed the impact of APAP on the liver NAE-PPAR? system. A dose-response (0.5-5-10-20 mM) and time-course (2-6-24 h) study in human HepG2 cells showed a biphasic response, with a decreased PPAR? expression after 6-h APAP incubation followed by a generalized increase of NAE-PPAR? system-related components (PPAR?, NAPE-PLD, and FAAH), including the NAEs oleoyl ethanolamide (OEA) and docosahexaenoyl ethanolamide, after a 24-h exposure to APAP. These results were partially confirmed in a time-course study of mice exposed to an acute dose of APAP (750 mg/kg). The gene expression levels of Ppar? and Faah were decreased after 6 h of treatment and, after 24 h, the gene expression levels of Nape-pld and Faah, as well as the liver levels of OEA and palmitoyl ethanolamide, were increased. Repeated APAP administration (750 mg/kg/day) up to 4 days also decreased the expression levels of PPAR? and FAAH, and increased the liver levels of NAEs. A resting period of 15 days completely restored these impairments. Liver immunohistochemistry in a well-characterized human case of APAP hepatotoxicity confirmed PPAR? and FAAH decrements. Histopathological and hepatic damage (Cyp2e1, Caspase3, ?Sma, Tnf?, and Mcp1)-related alterations observed after repeated APAP administration were aggravated in the liver of Ppar?-deficient mice. Our results demonstrate that the anti-inflammatory NAE-PPAR? signaling system is implicated in liver toxicity after exposure to APAP overdose, and may contribute to its recovery through a long-term time-dependent response.

Project description:Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain 1.29 x more heritability than GWAS-associated SNPs on average (P=3.3 x 10??). For some diseases, this increase was individually significant: 2.07 x for Multiple Sclerosis (MS) (P=6.5 x 10??) and 1.48 x for Crohn's Disease (CD) (P = 1.3 x 10?³); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained 7.15 x more MS heritability than known MS SNPs (P < 1.0 x 10?¹? and 2.20 x more CD heritability than known CD SNPs (P = 6.1 x 10??), with an analogous increase for all autoimmune diseases analyzed. We also observed significant increases in an analysis of > 20,000 Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with 2.37 x more heritability from all SNPs at GWAS loci (P = 2.3 x 10??) and 5.33 x more heritability from all autoimmune disease loci (P < 1 x 10?¹? compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.

Project description:BackgroundCurrently, diabetes has become one of the leading causes of death worldwide. Fasting plasma glucose (FPG) levels that are higher than optimal, even if below the diagnostic threshold of diabetes, can also lead to increased morbidity and mortality. Here we intend to study the magnitude of the genetic influence on FPG variation by conducting structural equation modelling analysis and to further identify specific genetic variants potentially related to FPG levels by performing a genome-wide association study (GWAS) in Chinese twins.ResultsThe final sample included 382 twin pairs: 139 dizygotic (DZ) pairs and 243 monozygotic (MZ) pairs. The DZ twin correlation for the FPG level (rDZ = 0.20, 95% CI: 0.04-0.36) was much lower than half that of the MZ twin correlation (rMZ = 0.68, 95% CI: 0.62-0.74). For the variation in FPG level, the AE model was the better fitting model, with additive genetic parameters (A) accounting for 67.66% (95% CI: 60.50-73.62%) and unique environmental or residual parameters (E) accounting for 32.34% (95% CI: 26.38-39.55%), respectively. In the GWAS, although no genetic variants reached the genome-wide significance level (P < 5 × 10- 8), 28 SNPs exceeded the level of a suggestive association (P < 1 × 10- 5). One promising genetic region (2q33.1) around rs10931893 (P = 1.53 × 10- 7) was found. After imputing untyped SNPs, we found that rs60106404 (P = 2.38 × 10- 8) located at SPATS2L reached the genome-wide significance level, and 216 SNPs exceeded the level of a suggestive association. We found 1007 genes nominally associated with the FPG level (P < 0.05), including SPATS2L, KCNK5, ADCY5, PCSK1, PTPRA, and SLC26A11. Moreover, C1orf74 (P = 0.014) and SLC26A11 (P = 0.021) were differentially expressed between patients with impaired fasting glucose and healthy controls. Some important enriched biological pathways, such as β-alanine metabolism, regulation of insulin secretion, glucagon signaling in metabolic regulation, IL-1 receptor pathway, signaling by platelet derived growth factor, cysteine and methionine metabolism pathway, were identified.ConclusionsThe FPG level is highly heritable in the Chinese population, and genetic variants are significantly involved in regulatory domains, functional genes and biological pathways that mediate FPG levels. This study provides important clues for further elucidating the molecular mechanism of glucose homeostasis and discovering new diagnostic biomarkers and therapeutic targets for diabetes.

Project description:BackgroundCombining the results of within-population genome-wide association studies (GWAS) based on whole-genome sequences into a single meta-analysis (MA) is an accurate and powerful method for identifying variants associated with complex traits. As part of the H2020 BovReg project, we performed sequence-level MA for beef production traits. Five partners from France, Switzerland, Germany, and Canada contributed summary statistics from sequence-based GWAS conducted with 54,782 animals from 15 purebred or crossbred populations. We combined the summary statistics for four growth, nine morphology, and 15 carcass traits into 16 MA, using both fixed effects and z-score methods.ResultsThe fixed-effects method was generally more informative to provide indication on potentially causal variants, although we combined substantially different traits in each MA. In comparison with within-population GWAS, this approach highlighted (i) a larger number of quantitative trait loci (QTL), (ii) QTL more frequently located in genomic regions known for their effects on growth and meat/carcass traits, (iii) a smaller number of genomic variants within the QTL, and (iv) candidate variants that were more frequently located in genes. MA pinpointed variants in genes, including MSTN, LCORL, and PLAG1 that have been previously associated with morphology and carcass traits. We also identified dozens of other variants located in genes associated with growth and carcass traits, or with a function that may be related to meat production (e.g., HS6ST1, HERC2, WDR75, COL3A1, SLIT2, MED28, and ANKAR). Some of these variants overlapped with expression or splicing QTL reported in the cattle Genotype-Tissue Expression atlas (CattleGTEx) and could therefore regulate gene expression.ConclusionsBy identifying candidate genes and potential causal variants associated with beef production traits in cattle, MA demonstrates great potential for investigating the biological mechanisms underlying these traits. As a complement to within-population GWAS, this approach can provide deeper insights into the genetic architecture of complex traits in beef cattle.

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Heritability and family-based GWAS analyses of the N-acyl ethanolamine and ceramide plasma lipidome.

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