Metabolomics reveals a link between homocysteine and lipid metabolism and leukocyte telomere length: the ENGAGE consortium.

Telomere shortening has been associated with multiple age-related diseases such as cardiovascular disease, diabetes, and dementia. However, the biological mechanisms responsible for these associations remain largely unknown. In order to gain insight into the metabolic processes driving the association of leukocyte telomere length (LTL) with age-related diseases, we investigated the association between LTL and serum metabolite levels in 7,853 individuals from seven independent cohorts. LTL was determined by quantitative polymerase chain reaction and the levels of 131 serum metabolites were measured with mass spectrometry in biological samples from the same blood draw. With partial correlation analysis, we identified six metabolites that were significantly associated with LTL after adjustment for multiple testing: lysophosphatidylcholine acyl C17:0 (lysoPC a C17:0, p-value = 7.1 × 10-6), methionine (p-value = 9.2 × 10-5), tyrosine (p-value = 2.1 × 10-4), phosphatidylcholine diacyl C32:1 (PC aa C32:1, p-value = 2.4 × 10-4), hydroxypropionylcarnitine (C3-OH, p-value = 2.6 × 10-4), and phosphatidylcholine acyl-alkyl C38:4 (PC ae C38:4, p-value = 9.0 × 10-4). Pathway analysis showed that the three phosphatidylcholines and methionine are involved in homocysteine metabolism and we found supporting evidence for an association of lipid metabolism with LTL. In conclusion, we found longer LTL associated with higher levels of lysoPC a C17:0 and PC ae C38:4, and with lower levels of methionine, tyrosine, PC aa C32:1, and C3-OH. These metabolites have been implicated in inflammation, oxidative stress, homocysteine metabolism, and in cardiovascular disease and diabetes, two major drivers of morbidity and mortality.

Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA.

Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.

Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels.

Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platform. In a discovery sample of 7,478 individuals of European descent, we find 4,068 genome- and metabolome-wide significant (Z-test, P < 1.09 × 10(-9)) associations between single-nucleotide polymorphisms (SNPs) and metabolites, involving 59 independent SNPs and 85 metabolites. Five of the fifty-nine independent SNPs are new for serum metabolite levels, and were followed-up for replication in an independent sample (N = 1,182). The novel SNPs are located in or near genes encoding metabolite transporter proteins or enzymes (SLC22A16, ARG1, AGPS and ACSL1) that have demonstrated biomedical or pharmaceutical importance. The further characterization of genetic influences on metabolic phenotypes is important for progress in biological and medical research.

A metabolomic profile is associated with the risk of incident coronary heart disease.

BACKGROUND: Metabolomics, defined as the comprehensive identification and quantification of low-molecular-weight metabolites to be found in a biological sample, has been put forward as a potential tool for classifying individuals according to their risk of coronary heart disease (CHD). Here, we investigated whether a single-point blood measurement of the metabolome is associated with and predictive for the risk of CHD. METHODS AND RESULTS: We obtained proton nuclear magnetic resonance spectra in 79 cases who developed CHD during follow-up (median 8.1 years) and in 565 randomly selected individuals. In these spectra, 100 signals representing 36 metabolites were identified. Applying least absolute shrinkage and selection operator regression, we defined a weighted metabolite score consisting of 13 proton nuclear magnetic resonance signals that optimally predicted CHD. This metabolite score, including signals representing a lipid fraction, glucose, valine, ornithine, glutamate, creatinine, glycoproteins, citrate, and 1.5-anhydrosorbitol, was associated with the incidence of CHD independent of traditional risk factors (TRFs) (hazard ratio 1.50, 95% CI 1.12-2.01). Predictive performance of this metabolite score on its own was moderate (C-index 0.75, 95% CI 0.70-0.80), but after adding age and sex, the C-index was only modestly lower than that of TRFs (C-index 0.81, 95% CI 0.77-0.85 and C-index 0.82, 95% CI 0.78-0.87, respectively). The metabolite score was also associated with prevalent CHD independent of TRFs (odds ratio 1.59, 95% CI 1.19-2.13). CONCLUSION: A metabolite score derived from a single-point metabolome measurement is associated with CHD, and metabolomics may be a promising tool for refining and improving the prediction of CHD.

Familial resemblance for serum metabolite concentrations.

Metabolomics is the comprehensive study of metabolites, which are the substrates, intermediate, and end products of cellular metabolism. The heritability of the concentrations of circulating metabolites bears relevance for evaluating their suitability as biomarkers for disease. We report aspects of familial resemblance for the concentrations in human serum of more than 100 metabolites, measured using a targeted metabolomics platform. Age- and sex-corrected monozygotic twin correlations, midparent-offspring regression coefficients, and spouse correlations in subjects from two independent cohorts (Netherlands Twin Register and Leiden Longevity Study) were estimated for each metabolite. In the Netherlands Twin Register subjects, who were largely fasting, we found significant monozygotic twin correlations for 121 out of 123 metabolites. Heritability was confirmed by midparent-offspring regression. For most detected metabolites, the correlations between spouses were considerably lower than those between twins, indicating a contribution of genetic effects to familial resemblance. Remarkably high heritability was observed for free carnitine (monozygotic twin correlation 0.66), for the amino acids serine (monozygotic twin correlation 0.77) and threonine (monozygotic twin correlation 0.64), and for phosphatidylcholine acyl-alkyl C40:3 (monozygotic twin correlation 0.77). For octenoylcarnitine, a consistent point estimate of approximately 0.50 was found for the spouse correlations in the two cohorts as well as for the monozygotic twin correlation, suggesting that familiality for this metabolite is explained by shared environment. We conclude that for the majority of metabolites targeted by the used metabolomics platform, the familial resemblance of serum concentrations is largely genetic. Our results contribute to the knowledge of the heritability of fasting serum metabolite concentrations, which is relevant for biomarker research.

Markers of endogenous desaturase activity and risk of coronary heart disease in the CAREMA cohort study.

BACKGROUND: Intakes of n-3 polyunsaturated fatty acids (PUFAs), especially EPA (C20:5n-3) and DHA (C22:6n-3), are known to prevent fatal coronary heart disease (CHD). The effects of n-6 PUFAs including arachidonic acid (C20:4n-6), however, remain unclear. δ-5 and δ-6 desaturases are rate-limiting enzymes for synthesizing long-chain n-3 and n-6 PUFAs. C20:4n-6 to C20:3n-6 and C18:3n-6 to C18:2n-6 ratios are markers of endogenous δ-5 and δ-6 desaturase activities, but have never been studied in relation to incident CHD. Therefore, the aim of this study was to investigate the relation between these ratios as well as genotypes of FADS1 rs174547 and CHD incidence. METHODS: We applied a case-cohort design within the CAREMA cohort, a large prospective study among the general Dutch population followed up for a median of 12.1 years. Fatty acid profile in plasma cholesteryl esters and FADS1 genotype at baseline were measured in a random subcohort (n = 1323) and incident CHD cases (n = 537). Main outcome measures were hazard ratios (HRs) of incident CHD adjusted for major CHD risk factors. RESULTS: The AA genotype of rs174547 was associated with increased plasma levels of C204n-6, C20:5n-3 and C22:6n-3 and increased δ-5 and δ-6 desaturase activities, but not with CHD risk. In multivariable adjusted models, high baseline δ-5 desaturase activity was associated with reduced CHD risk (P for trend = 0.02), especially among those carrying the high desaturase activity genotype (AA): HR (95% CI) = 0.35 (0.15-0.81) for comparing the extreme quintiles. High plasma DHA levels were also associated with reduced CHD risk. CONCLUSION: In this prospective cohort study, we observed a reduced CHD risk with an increased C20:4n-6 to C20:3n-6 ratio, suggesting that δ-5 desaturase activity plays a role in CHD etiology. This should be investigated further in other independent studies.

Literature-based genetic risk scores for coronary heart disease: the Cardiovascular Registry Maastricht (CAREMA) prospective cohort study.

BACKGROUND: Genome-wide association studies (GWAS) have identified many single-nucleotide polymorphisms (SNPs) associated with coronary heart disease (CHD) or CHD risk factors (RF). Using a case-cohort study within the prospective Cardiovascular Registry Maastricht (CAREMA) cohort, we tested if genetic risk scores (GRS) based on GWAS-identified SNPs are associated with and predictive for future CHD. METHODS AND RESULTS: Incident cases (n=742), that is, participants who developed CHD during a median follow-up of 12.1 years (range, 0.0-16.9 years), were compared with a randomly selected subcohort of 2221 participants selected from the total cohort (n=21 148). We genotyped 179 SNPs previously associated with CHD or CHD RF in GWAS as published up to May 2, 2011. The allele-count GRS, composed of all SNPs, the 153 RF SNPs, or the 29 CHD SNPs were not associated with CHD independent of CHD RF. The weighted 29 CHD SNP GRS, with weights obtained from GWAS for every SNP, were associated with CHD independent of CHD RF (hazard ratio, 1.12 per weighted risk allele; 95% confidence interval, 1.04-1.21) and improved risk reclassification with 2.8% (P=0.031). As an exploratory approach to achieve weighting, we performed least absolute shrinkage and selection operator (LASSO) regression analysis on all SNPs and the CHD SNPs. The CHD LASSO GRS performed equal to the weighted CHD GRS, whereas the Overall LASSO GRS performed slightly better than the weighted CHD GRS. CONCLUSIONS: A GRS composed of CHD SNPs improves risk prediction when adjusted for the effect sizes of the SNPs. Alternatively LASSO regression analysis may be used to achieve weighting; however, validation in independent populations is required.

Lipid metabolism in long-lived families: the Leiden Longevity Study.

Mechanisms underlying the variation in human life expectancy are largely unknown, but lipid metabolism and especially lipoprotein size was suggested to play an important role in longevity. We have performed comprehensive lipid phenotyping in the Leiden Longevity Study (LLS). By applying multiple logistic regression analysis we tested for the first time the effects of parameters in lipid metabolism (i.e., classical serum lipids, lipoprotein particle sizes, and apolipoprotein E levels) on longevity independent of each other. Parameters in lipid metabolism were measured in offspring of nonagenarian siblings from 421 families of the LLS (n = 1,664; mean age, 59 years) and in the partners of the offspring as population controls (n = 711; mean age, 60 years). In the initial model, where lipoprotein particles sizes, classical serum lipids and apolipoprotein E were included, offspring had larger low-density lipoprotein (LDL) particle sizes (p = 0.017), and lower triglyceride levels (p = 0.026), indicating that they displayed a more beneficial lipid profile. After backwards regression only LDL size (p = 0.014) and triglyceride levels (p = 0.05) were associated with offspring from long-lived families. Sex-specific backwards regression analysis revealed that LDL particle sizes were associated with male longevity (increase in log odds ratio (OR) per unit = 0.21; p = 0.023). Triglyceride levels (decrease OR per unit = 0.22; p = 0.01), but not LDL particle size, were associated with female longevity. Due to the analysis of a comprehensive lipid profile, we confirmed an important role of lipid metabolism in human longevity, with LDL size and triglyceride levels as major predicting factors.

Exploring genetic determinants of plasma total cholesterol levels and their predictive value in a longitudinal study.

BACKGROUND: Plasma total cholesterol (TC) levels are highly genetically determined. Although ample evidence of genetic determination of separate lipoprotein cholesterol levels has been reported, using TC level directly as a phenotype in a relatively large broad-gene based association study has not been reported to date. METHODS AND RESULTS: We genotyped 361 single nucleotide polymorphisms (SNPs) across 243 genes based on pathways potentially relevant to cholesterol metabolism in 3575 subjects that were examined thrice over 11 years. Twenty-three SNPs were associated with TC levels after adjustment for multiple testing. We used 12 of them (rs7412 and rs429358 in APOE, rs646776 in CELSR2, rs1367117 in APOB, rs6756629 in ABCG5, rs662799 in APOA5, rs688 in LDLR, rs10889353 in DOCK7, rs2304130 in NCAN, rs3846662 in HMGCR, rs2275543 in ABCA1, rs7275 in SMARCA4) that were confirmed in previous candidate association or genome-wide-association studies to define a gene risk score (GRS). Average TC levels increased from 5.23 ± 0.82 mmol/L for those with 11 or less cholesterol raising alleles to 6.03 ± 1.11 mmol/L for those with 18 or more (P for trend<0.0001). The association with TC levels was slightly stronger when the weighted GRS that weighted the magnitude of allelic effects was used. CONCLUSION: A panel of common genetic variants in the genes pivotal in cholesterol metabolism could possibly help identify those people who are at risk of high cholesterol levels.

Theophylline prevents NAD+ depletion via PARP-1 inhibition in human pulmonary epithelial cells.

Oxidative DNA damage, as occurs during exacerbations in chronic obstructive pulmonary disease (COPD), highly activates the nuclear enzyme poly(ADP-ribose)polymerase-1 (PARP-1). This can lead to cellular depletion of its substrate NAD+, resulting in an energy crisis and ultimately in cell death. Inhibition of PARP-1 results in preservation of the intracellular NAD+ pool, and of NAD+-dependent cellular processes. In this study, PARP-1 activation by hydrogen peroxide decreased intracellular NAD+ levels in human pulmonary epithelial cells, which was found to be prevented in a dose-dependent manner by theophylline, a widely used compound in the treatment of COPD. This enzyme inhibition by theophylline was confirmed in an ELISA using purified human PARP-1 and was found to be competitive by nature. These findings provide new mechanistic insights into the therapeutic effect of theophylline in oxidative stress-induced lung pathologies.