Tracer-based lipidomics enables the discovery of disease-specific candidate biomarkers in mitochondrial ß-oxidation disorders.

Carnitine derivatives of disease-specific acyl-CoAs are the diagnostic hallmark for long-chain fatty acid ß-oxidation disorders (lcFAOD), including carnitine shuttle deficiencies, very-long-chain acyl-CoA dehydrogenase deficiency (VLCADD), long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHADD) and mitochondrial trifunctional protein deficiency (MPTD). The exact consequence of accumulating lcFAO-intermediates and their influence on cellular lipid homeostasis is, however, still unknown. To investigate the fate and cellular effects of the accumulating lcFAO-intermediates and to explore the presence of disease-specific markers, we used tracer-based lipidomics with deuterium-labeled oleic acid (D9-C18:1) in lcFAOD patient-derived fibroblasts. In line with previous studies, we observed a trend towards neutral lipid accumulation in lcFAOD. In addition, we detected a direct connection between the chain length and patterns of (un)saturation of accumulating acylcarnitines and the various enzyme deficiencies. Our results also identified two disease-specific candidate biomarkers. Lysophosphatidylcholine(14:1) (LPC(14:1)) was specifically increased in severe VLCADD compared to mild VLCADD and control samples. This was confirmed in plasma samples showing an inverse correlation with enzyme activity, which was better than the classic diagnostic marker C14:1-carnitine. The second candidate biomarker was an unknown lipid class, which we identified as S-(3-hydroxyacyl)cysteamines. We hypothesized that these were degradation products of the CoA moiety of accumulating 3-hydroxyacyl-CoAs. S-(3-hydroxyacyl)cysteamines were significantly increased in LCHADD compared to controls and other lcFAOD, including MTPD. Our findings suggest extensive alternative lipid metabolism in lcFAOD and confirm that lcFAOD accumulate neutral lipid species. In addition, we present two disease-specific candidate biomarkers for VLCADD and LCHADD, that may have significant relevance for disease diagnosis, prognosis, and monitoring.

Four-dimensional lipidomics profiling in X-linked adrenoleukodystrophy using trapped ion mobility mass spectrometry.

Lipids play pivotal roles in an extensive range of metabolic and physiological processes. In recent years, the convergence of trapped ion mobility spectrometry and MS has enabled 4D-lipidomics, a highly promising technology for comprehensive lipid analysis. 4D-lipidomics assesses lipid annotations across four distinct dimensions-retention time, collisional cross section, m/z (mass-to-charge ratio), and MS/MS spectra-providing a heightened level of confidence in lipid annotation. These advantages prove particularly valuable when investigating complex disorders involving lipid metabolism, such as adrenoleukodystrophy (ALD). ALD is characterized by the accumulation of very-long-chain fatty acids (VLCFAs) due to pathogenic variants in the ABCD1 gene. A comprehensive 4D-lipidomics strategy of ALD fibroblasts demonstrated significant elevations of various lipids from multiple classes. This indicates that the changes observed in ALD are not confined to a single lipid class and likely impacts a broad spectrum of lipid-mediated physiological processes. Our findings highlight the incorporation of mainly saturated and monounsaturated VLCFA variants into a range of lipid classes, encompassing phosphatidylcholines, triacylglycerols, and cholesterol esters. These include ultra-long-chain fatty acids with a length of up to thirty carbon atoms. Lipid species containing C26:0 and C26:1 were the most frequently detected VLCFA lipids in our study. Furthermore, we report a panel of 121 new candidate biomarkers in fibroblasts, exhibiting significant differentiation between controls and individuals with ALD. In summary, this study demonstrates the capabilities of a 4D-lipid profiling workflow in unraveling novel insights into the intricate lipid modifications associated with metabolic disorders like ALD.

Deleterious variants in CRLS1 lead to cardiolipin deficiency and cause an autosomal recessive multi-system mitochondrial disease.

Mitochondrial diseases are a group of inherited diseases with highly varied and complex clinical presentations. Here, we report four individuals, including two siblings, affected by a progressive mitochondrial encephalopathy with biallelic variants in the cardiolipin biosynthesis gene CRLS1. Three affected individuals had a similar infantile presentation comprising progressive encephalopathy, bull's eye maculopathy, auditory neuropathy, diabetes insipidus, autonomic instability, cardiac defects and early death. The fourth affected individual presented with chronic encephalopathy with neurodevelopmental regression, congenital nystagmus with decreased vision, sensorineural hearing loss, failure to thrive and acquired microcephaly. Using patient-derived fibroblasts, we characterized cardiolipin synthase 1 (CRLS1) dysfunction that impaired mitochondrial morphology and biogenesis, providing functional evidence that the CRLS1 variants cause mitochondrial disease. Lipid profiling in fibroblasts from two patients further confirmed the functional defect demonstrating reduced cardiolipin levels, altered acyl-chain composition and significantly increased levels of phosphatidylglycerol, the substrate of CRLS1. Proteomic profiling of patient cells and mouse Crls1 knockout cell lines identified both endoplasmic reticular and mitochondrial stress responses, and key features that distinguish between varying degrees of cardiolipin insufficiency. These findings support that deleterious variants in CRLS1 cause an autosomal recessive mitochondrial disease, presenting as a severe encephalopathy with multi-systemic involvement. Furthermore, we identify key signatures in cardiolipin and proteome profiles across various degrees of cardiolipin loss, facilitating the use of omics technologies to guide future diagnosis of mitochondrial diseases.

Hepatic triglyceride content is intricately associated with numerous metabolites and biochemical pathways.

BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is characterized by the pathological accumulation of triglycerides in hepatocytes and is associated with insulin resistance, atherogenic dyslipidaemia and cardiometabolic diseases. Thus far, the extent of metabolic dysregulation associated with hepatic triglyceride accumulation has not been fully addressed. In this study, we aimed to identify metabolites associated with hepatic triglyceride content (HTGC) and map these associations using network analysis. METHODS: To gain insight in the spectrum of metabolites associated with hepatic triglyceride accumulation, we performed a comprehensive plasma metabolomics screening of 1363 metabolites in apparently healthy middle aged (age 45-65) individuals (N = 496) in whom HTGC was measured by proton magnetic resonance spectroscopy. An atlas of metabolite-HTGC associations, based on univariate results, was created using correlation-based Gaussian graphical model (GGM) and genome scale metabolic model network analyses. Pathways associated with the clinical prognosis marker fibrosis 4 (FIB-4) index were tested using a closed global test. RESULTS: Our analyses revealed that 118 metabolites were univariately associated with HTGC (p-value <6.59 × 10-5 ), including 106 endogenous, 1 xenobiotic and 11 partially characterized/uncharacterized metabolites. These associations were mapped to several biological pathways including branched amino acids (BCAA), diglycerols, sphingomyelin, glucosyl-ceramide and lactosyl-ceramide. We also identified a novel possible HTGC-related pathway connecting glutamate, metabolonic lactone sulphate and X-15245 using the GGM network. These pathways were confirmed to be associated with the FIB-4 index as well. The full interactive metabolite-HTGC atlas is provided online: https://tofaquih.github.io/AtlasLiver/. CONCLUSIONS: The combined network and pathway analyses indicated extensive associations between BCAA and the lipids pathways with HTGC and the FIB-4 index. Moreover, we report a novel pathway glutamate-metabolonic lactone sulphate-X-15245 with a potential strong association with HTGC. These findings can aid elucidating HTGC metabolomic profiles and provide insight into novel drug targets for fibrosis-related outcomes.

The effect of mirabegron on energy expenditure and brown adipose tissue in healthy lean South Asian and Europid men.

AIM: To compare the effects of cold exposure and the ß3-adrenergic receptor agonist mirabegron on plasma lipids, energy expenditure and brown adipose tissue (BAT) activity in South Asians versus Europids. MATERIALS AND METHODS: Ten lean Dutch South Asian (aged 18-30 years; body mass index [BMI] 18-25 kg/m2 ) and 10 age- and BMI-matched Europid men participated in a randomized, double-blinded, cross-over study consisting of three interventions: short-term (~ 2 hours) cold exposure, mirabegron (200 mg one dose p.o.) and placebo. Before and after each intervention, we performed lipidomic analysis in serum, assessed resting energy expenditure (REE) and skin temperature, and measured BAT fat fraction by magnetic resonance imaging. RESULTS: In both ethnicities, cold exposure increased the levels of several serum lipid species, whereas mirabegron only increased free fatty acids. Cold exposure increased lipid oxidation in both ethnicities, while mirabegron increased lipid oxidation in Europids only. Cold exposure and mirabegron enhanced supraclavicular skin temperature in both ethnicities. Cold exposure decreased BAT fat fraction in both ethnicities. After the combination of data from both ethnicities, mirabegron decreased BAT fat fraction compared with placebo. CONCLUSIONS: In South Asians and Europids, cold exposure and mirabegron induced beneficial metabolic effects. When combining both ethnicities, cold exposure and mirabegron increased REE and lipid oxidation, coinciding with a higher supraclavicular skin temperature and lower BAT fat fraction.

Reduced Feed Intake, Rather than Increased Energy Losses, Explains Variation in Growth Rates of Normal-Birth-Weight Piglets.

Background: Substantial variation in growth rates exists in normal-birth-weight piglets, possibly due to differences in energy efficiency. Within this population, slow growth rates are associated with reduced insulin sensitivity. Slowly digestible starch (SDS) may improve growth efficiency in slowly growing pigs, because it reduces postprandial blood glucose. Objective: The aim of this study was to investigate maintenance energy requirements and efficiency of energy used for growth (incremental energy efficiency) of slow-growing or fast-growing piglets (SG-pigs and FG-pigs, respectively) with equal birth weight that were fed either an SDS or a rapidly digestible-starch (RDS) diet. Methods: Sixteen groups of either five 10-wk-old SG-pigs (mean ± SD: 11.3 ± 1.4 kg) or FG-pigs (15.1 ± 1.7 kg) were housed in climate respiration chambers and fed diets containing 40% RDS or SDS for 2 wk. In week 1, feed was available ad libitum. In week 2, feed supply was restricted to 65% of the observed weekly averaged feed intake [kJ · kg body weight (BW)-0.6 · d-1] in week 1. After week 2, pigs were feed deprived for 24 h, after which heat production was determined. Energy balances, apparent total tract digestibility (ATTD), and incremental energy efficiencies were calculated and analyzed using a general linear model. Results: Gross energy intake (kJ · kg BW-0.6 · d-1) was 4% greater (P = 0.047) for FG-pigs than for SG-pigs. ATTD of fat was 6%-units greater (P = 0.003) for RDS-fed than for SDS-fed pigs. Fasting heat production and incremental energy efficiencies did not differ between pig types or diets. Incremental use of metabolizable energy for fat retention was 2% units (P = 0.054) greater for RDS-fed than SDS-fed pigs. Conclusions: A lower energy intake rather than greater maintenance requirements or lower energy efficiency explains the slow growth of SG-pigs. Incremental RDS intake increased fat deposition more than SDS, whereas energy efficiency was not affected. Thus, feeding SDS instead of RDS does not improve growth efficiency but may result in slightly leaner pigs.

Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses.

Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10-32), PRODH with proline (P-value  = 1.11×10-19), SLC16A9 with carnitine level (P-value  = 4.81×10-14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10-19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10-8), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10-8) and 2p12 locus with valine (P-value  = 3.49×10-8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.

FluxModeCalculator: an efficient tool for large-scale flux mode computation.

UNLABELLED: Elementary flux mode (EFM) analysis is a powerful technique for determining the metabolic capacities and robustness of stoichiometric networks. Recently, several improvements have been made to the algorithm for enumerating the EFMs, making the study of large models possible. However, currently these tools require high performance workstations to perform large-scale EFM computations, thus limiting their applicability. We developed a more time and memory efficient implementation of the algorithm for EFM enumeration in MATLAB, called FluxModeCalculator, which enables large-scale EFM computation on ordinary desktop computers. AVAILABILITY AND IMPLEMENTATION: FluxModeCalculator is open source and freely available under the terms of the GNU General Public License v3.0 at http://www.lumc.nl/jan-bert-van-klinken CONTACT: j.b.van_klinken@lumc.nl SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetics of the human metabolome, what is next?

Increases in throughput and decreases in costs have facilitated large scale metabolomics studies, the simultaneous measurement of large numbers of biochemical components in biological samples. Initial large scale studies focused on biomarker discovery for disease or disease progression and helped to understand biochemical pathways underlying disease. The first population-based studies that combined metabolomics and genome wide association studies (mGWAS) have increased our understanding of the (genetic) regulation of biochemical conversions. Measurements of metabolites as intermediate phenotypes are a potentially very powerful approach to uncover how genetic variation affects disease susceptibility and progression. However, we still face many hurdles in the interpretation of mGWAS data. Due to the composite nature of many metabolites, single enzymes may affect the levels of multiple metabolites and, conversely, levels of single metabolites may be affected by multiple enzymes. Here, we will provide a global review of the current status of mGWAS. We will specifically discuss the application of prior biological knowledge present in databases to the interpretation of mGWAS results and discuss the potential of mathematical models. As the technology continuously improves to detect metabolites and to measure genetic variation, it is clear that comprehensive systems biology based approaches are required to further our insight in the association between genes, metabolites and disease. This article is part of a Special Issue entitled: From Genome to Function.

Long-term niacin treatment induces insulin resistance and adrenergic responsiveness in adipocytes by adaptive downregulation of phosphodiesterase 3B.

The lipid-lowering effect of niacin has been attributed to the inhibition of cAMP production in adipocytes, thereby inhibiting intracellular lipolysis and release of nonesterified fatty acids (NEFA) to the circulation. However, long-term niacin treatment leads to a normalization of plasma NEFA levels and induces insulin resistance, for which the underlying mechanisms are poorly understood. The current study addressed the effects of long-term niacin treatment on insulin-mediated inhibition of adipocyte lipolysis and focused on the regulation of cAMP levels. APOE*3-Leiden.CETP transgenic mice treated with niacin for 15 wk were subjected to an insulin tolerance test and showed whole body insulin resistance. Similarly, adipocytes isolated from niacin-treated mice were insulin resistant and, interestingly, exhibited an increased response to cAMP stimulation by 8Br-cAMP, ß1- and ß2-adrenergic stimulation. Gene expression analysis of the insulin and ß-adrenergic pathways in adipose tissue indicated that all genes were downregulated, including the gene encoding the cAMP-degrading enzyme phosphodiesterase 3B (PDE3B). In line with this, we showed that insulin induced a lower PDE3B response in adipocytes isolated from niacin-treated mice. Inhibiting PDE3B with cilostazol increased lipolytic responsiveness to cAMP stimulation in adipocytes. These data show that long-term niacin treatment leads to a downregulation of PDE3B in adipocytes, which could explain part of the observed insulin resistance and the increased responsiveness to cAMP stimulation.

Detrimental effects of constant light exposure and high-fat diet on circadian energy metabolism and insulin sensitivity.

Circadian rhythm disturbances are observed in, e.g., aging and neurodegenerative diseases and are associated with an increased incidence of obesity and diabetes. We subjected male C57Bl/6J mice to constant light [12-h light-light (LL) cycle] to examine the effects of a disturbed circadian rhythm on energy metabolism and insulin sensitivity. In vivo electrophysiological recordings in the central pacemaker of the suprachiasmatic nuclei (SCN) revealed an immediate reduction in rhythm amplitude, stabilizing at 44% of normal amplitude values after 4 d LL. Food intake was increased (+26%) and energy expenditure decreased (-13%), and we observed immediate body weight gain (d 4: +2.4%, d 14: +5.0%). Mixed model analysis revealed that weight gain developed more rapidly in response to LL as compared to high fat. After 4 wk in LL, the circadian pattern in feeding and energy expenditure was completely lost, despite continuing low-amplitude rhythms in the SCN and in behavior, whereas weight gain had stabilized. Hyperinsulinemic-euglycemic clamp analysis revealed complete abolishment of normal circadian variation in insulin sensitivity in LL. In conclusion, a reduction in amplitude of the SCN, to values previously observed in aged mice, is sufficient to induce a complete loss of circadian rhythms in energy metabolism and insulin sensitivity.

Apolipoprotein A5 deficiency aggravates high-fat diet-induced obesity due to impaired central regulation of food intake.

Mutations in apolipoprotein A5 (APOA5) have been associated with hypertriglyceridemia in humans and mice. This has been attributed to a stimulating role for APOA5 in lipoprotein lipase-mediated triglyceride hydrolysis and hepatic clearance of lipoprotein remnant particles. However, because of the low APOA5 plasma abundance, we investigated an additional signaling role for APOA5 in high-fat diet (HFD)-induced obesity. Wild-type (WT) and Apoa5(-/-) mice fed a chow diet showed no difference in body weight or 24-h food intake (Apoa5(-/-), 4.5±0.6 g; WT, 4.2±0.5 g), while Apoa5(-/-) mice fed an HFD ate more in 24 h (Apoa5(-/-), 2.8±0.4 g; WT, 2.5±0.3 g, P<0.05) and became more obese than WT mice. Also, intravenous injection of APOA5-loaded VLDL-like particles lowered food intake (VLDL control, 0.26±0.04 g; VLDL+APOA5, 0.11±0.07 g, P<0.01). In addition, the HFD-induced hyperphagia of Apoa5(-/-) mice was prevented by adenovirus-mediated hepatic overexpression of APOA5. Finally, intracerebroventricular injection of APOA5 reduced food intake compared to injection of the same mouse with artificial cerebral spinal fluid (0.40±0.11 g; APOA5, 0.23±0.08 g, P<0.01). These data indicate that the increased HFD-induced obesity of Apoa5(-/-) mice as compared to WT mice is at least partly explained by hyperphagia and that APOA5 plays a role in the central regulation of food intake.

Discovery of novel diagnostic biomarkers for Sjögren-Larsson syndrome by untargeted lipidomics.

AIM: Sjögren-Larsson syndrome (SLS) is a rare neurometabolic disorder that mainly affects brain, eye and skin and is caused by deficiency of fatty aldehyde dehydrogenase. Our recent finding of a profoundly disturbed brain tissue lipidome in SLS prompted us to search for similar biomarkers in plasma as no functional test in blood is available for SLS. METHODS AND RESULTS: We performed plasma lipidomics and used a newly developed bioinformatics tool to mine the untargeted part of the SLS plasma and brain lipidome to search for SLS biomarkers. Plasma lipidomics showed disturbed ether lipid metabolism in known lipid classes. Untargeted lipidomics of both plasma and brain (white and grey matter) uncovered two new endogenous lipid classes highly elevated in SLS. The first biomarker group were alkylphosphocholines/ethanolamines containing different lengths of alkyl-chains where some alkylphosphocholines were > 600-fold elevated in SLS plasma. The second group of biomarkers were a set of 5 features of unknown structure. Fragmentation studies suggested that they contain ubiquinol and phosphocholine and one feature was also found as a glucuronide conjugate in plasma. The plasma features were highly distinctive for SLS with levels >100-1000-fold the level in controls, if present at all. We speculate on the origin of the alkylphosphocholines/ethanolamines and the nature of the ubiquinol-containing metabolites. CONCLUSIONS: The metabolites identified in this study represent novel endogenous lipid classes thus far unknown in humans. They represent the first plasma metabolite SLS-biomarkers and may also yield more insight into SLS pathophysiology.

Automated workflow-based exploitation of pathway databases provides new insights into genetic associations of metabolite profiles.

BACKGROUND: Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) that associate with clinical phenotypes, but these SNPs usually explain just a small part of the heritability and have relatively modest effect sizes. In contrast, SNPs that associate with metabolite levels generally explain a higher percentage of the genetic variation and demonstrate larger effect sizes. Still, the discovery of SNPs associated with metabolite levels is challenging since testing all metabolites measured in typical metabolomics studies with all SNPs comes with a severe multiple testing penalty. We have developed an automated workflow approach that utilizes prior knowledge of biochemical pathways present in databases like KEGG and BioCyc to generate a smaller SNP set relevant to the metabolite. This paper explores the opportunities and challenges in the analysis of GWAS of metabolomic phenotypes and provides novel insights into the genetic basis of metabolic variation through the re-analysis of published GWAS datasets. RESULTS: Re-analysis of the published GWAS dataset from Illig et al. (Nature Genetics, 2010) using a pathway-based workflow (http://www.myexperiment.org/packs/319.html), confirmed previously identified hits and identified a new locus of human metabolic individuality, associating Aldehyde dehydrogenase family1 L1 (ALDH1L1) with serine/glycine ratios in blood. Replication in an independent GWAS dataset of phospholipids (Demirkan et al., PLoS Genetics, 2012) identified two novel loci supported by additional literature evidence: GPAM (Glycerol-3 phosphate acyltransferase) and CBS (Cystathionine beta-synthase). In addition, the workflow approach provided novel insight into the affected pathways and relevance of some of these gene-metabolite pairs in disease development and progression. CONCLUSIONS: We demonstrate the utility of automated exploitation of background knowledge present in pathway databases for the analysis of GWAS datasets of metabolomic phenotypes. We report novel loci and potential biochemical mechanisms that contribute to our understanding of the genetic basis of metabolic variation and its relationship to disease development and progression.

Alterations in ether lipid metabolism and the consequences for the mouse lipidome.

Alkylglycerol monooxygenase (AGMO) and plasmanylethanolamine desaturase (PEDS1) are enzymes involved in ether lipid metabolism. While AGMO degrades plasmanyl lipids by oxidative cleavage of the ether bond, PEDS1 exclusively synthesizes a specific subclass of ether lipids, the plasmalogens, by introducing a vinyl ether double bond into plasmanylethanolamine phospholipids. Ether lipids are characterized by an ether linkage at the sn-1 position of the glycerol backbone and they are found in membranes of different cell types. Decreased plasmalogen levels have been associated with neurological diseases like Alzheimer's disease. Agmo-deficient mice do not present an obvious phenotype under unchallenged conditions. In contrast, Peds1 knockout mice display a growth phenotype. To investigate the molecular consequences of Agmo and Peds1 deficiency on the mouse lipidome, five tissues from each mouse model were isolated and subjected to high resolution mass spectrometry allowing the characterization of up to 2013 lipid species from 42 lipid subclasses. Agmo knockout mice moderately accumulated plasmanyl and plasmenyl lipid species. Peds1-deficient mice manifested striking changes characterized by a strong reduction of plasmenyl lipids and a concomitant massive accumulation of plasmanyl lipids resulting in increased total ether lipid levels in the analyzed tissues except for the class of phosphatidylethanolamines where total levels remained remarkably constant also in Peds1 knockout mice. The rate-limiting enzyme in ether lipid metabolism, FAR1, was not upregulated in Peds1-deficient mice, indicating that the selective loss of plasmalogens is not sufficient to activate the feedback mechanism observed in total ether lipid deficiency.

Clustered Mendelian randomization analyses identify distinct and opposing pathways in the association between genetically influenced insulin-like growth factor-1 and type 2 diabetes mellitus.

BACKGROUND: There is inconsistent evidence for the causal role of serum insulin-like growth factor-1 (IGF-1) concentration in the pathogenesis of human age-related diseases such as type 2 diabetes (T2D). Here, we investigated the association between IGF-1 and T2D using (clustered) Mendelian randomization (MR) analyses in the UK Biobank. METHODS: We conducted Cox proportional hazard analyses in 451 232 European-ancestry individuals of the UK Biobank (55.3% women, mean age at recruitment 56.6 years), among which 13 247 individuals developed type 2 diabetes during up to 12 years of follow-up. In addition, we conducted two-sample MR analyses based on independent single nucleotide polymorphisms (SNPs) associated with IGF-1. Given the heterogeneity between the MR effect estimates of individual instruments (P-value for Q statistic = 4.03e-145), we also conducted clustered MR analyses. Biological pathway analyses of the identified clusters were performed by over-representation analyses. RESULTS: In the Cox proportional hazard models, with IGF-1 concentrations stratified in quintiles, we observed that participants in the lowest quintile had the highest relative risk of type 2 diabetes [hazard ratio (HR): 1.31; 95% CI: 1.23-1.39). In contrast, in the two-sample MR analyses, higher genetically influenced IGF-1 was associated with a higher risk of type 2 diabetes. Based on the heterogeneous distribution of MR effect estimates of individual instruments, six clusters of genetically determined IGF-1 associated either with a lower or a higher risk of type 2 diabetes were identified. The main clusters in which a higher IGF-1 was associated with a lower risk of type 2 diabetes consisted of instruments mapping to genes in the growth hormone signalling pathway, whereas the main clusters in which a higher IGF-1 was associated with a higher risk of type 2 diabetes consisted of instruments mapping to genes in pathways related to amino acid metabolism and genomic integrity. CONCLUSIONS: The IGF-1-associated SNPs used as genetic instruments in MR analyses showed a heterogeneous distribution of MR effect estimates on the risk of type 2 diabetes. This was likely explained by differences in the underlying molecular pathways that increase IGF-1 concentration and differentially mediate the effects of IGF-1 on type 2 diabetes.

Angiopoietin-like 4 governs diurnal lipoprotein lipase activity in brown adipose tissue.

OBJECTIVE: Brown adipose tissue (BAT) burns fatty acids (FAs) to produce heat, and shows diurnal oscillation in glucose and triglyceride (TG)-derived FA-uptake, peaking around wakening. Here we aimed to gain insight in the diurnal regulation of metabolic BAT activity. METHODS: RNA-sequencing, chromatin immunoprecipitation (ChIP)-sequencing, and lipidomics analyses were performed on BAT samples of wild type C57BL/6J mice collected at 3-hour intervals throughout the day. Knockout and overexpression models were used to study causal relationships in diurnal lipid handling by BAT. RESULTS: We identified pronounced enrichment of oscillating genes involved in extracellular lipolysis in BAT, accompanied by oscillations of FA and monoacylglycerol content. This coincided with peak lipoprotein lipase (Lpl) expression, and was predicted to be driven by peroxisome proliferator-activated receptor gamma (PPARγ) activity. ChIP-sequencing for PPARγ confirmed oscillation in binding of PPARγ to Lpl. Of the known LPL-modulators, angiopoietin-like 4 (Angptl4) showed the largest diurnal amplitude opposite to Lpl, and both Angptl4 knockout and overexpression attenuated oscillations of LPL activity and TG-derived FA-uptake by BAT. CONCLUSIONS: Our findings highlight involvement of PPARγ and a crucial role of ANGPTL4 in mediating the diurnal oscillation of TG-derived FA-uptake by BAT, and imply that time of day is essential when targeting LPL activity in BAT to improve metabolic health.

Adverse generational changes in obesity development converge at midlife without increased cardiometabolic risk.

OBJECTIVE: Obesity is becoming a global public health problem, but it is unclear how it impacts different generations over the life course. Here, a descriptive analysis of the age-related changes in anthropometric measures and related cardiometabolic risk factors across different generations was performed. METHODS: The development of anthropometric measures and related cardiometabolic risk factors was studied during 26 years of follow-up in the Doetinchem Cohort Study (N = 6,314 at baseline). All analyses were stratified by sex and generation, i.e., 10-year age groups (20-29, 30-39, 40-49, and 50-59 years) at baseline. Generalized estimating equations were used to test for generational differences. RESULTS: Weight, BMI, waist circumference, and prevalence of overweight and obesity were higher, in general, in the younger generations during the first 10 to 15 years of follow-up. From age 50 to 59 years onward, these measures converged in all generations of men and women. Among cardiometabolic risk factors, only type 2 diabetes showed an unfavorable shift between the two oldest generations of men. CONCLUSIONS: It was observed that, compared with the older generations, the younger generations had obesity at an earlier age but did not reach higher levels at midlife and beyond. This increased exposure to obesity was not (yet) associated with increased prevalence of cardiometabolic risk factors.

Genome-Wide Association Study of the Postprandial Triglyceride Response Yields Common Genetic Variation in LIPC (Hepatic Lipase).

BACKGROUND: The increase in serum triglyceride (TG) concentrations in response to a meal is considered a risk factor for cardiovascular disease. We aimed to elucidate the genetics of the postprandial TG response through genome-wide association studies (GWAS). METHODS: Participants of the NEO (Netherlands Epidemiology of Obesity) study (n=5630) consumed a liquid mixed meal after an overnight fast. GWAS of fasting and postprandial serum TG at 150 minutes were performed. To identify genetic variation of postprandial TG independent of fasting TG, we calculated the TG response at 150 minutes by the residuals of a nonlinear regression that predicted TG at 150 minutes as a function of fasting TG. Association analyses were adjusted for age, sex, and principal components in a linear regression model. Next, using the identified variants as determinants, we performed linear regression analyses on the residuals of the postprandial response of 149 nuclear magnetic resonance-based metabolite measures. RESULTS: GWAS of fasting TG and postprandial serum TG at 150 minutes resulted in completely overlapping loci, replicating previous GWAS. From GWAS of the TG response, we identified rs7350789-A (allele frequency=0.36), mapping to hepatic lipase (LIPC), to be associated with a smaller increase in TG concentrations at 150 minutes (ß=-0.11; P-value=5.1×10-8). Rs7350789-A was associated with responses of 33 metabolite measures (P-value <1.34×10-3), mainly smaller increases of the TG-component in almost all HDL (high-density lipoprotein) subparticles (HDL-TG), a smaller decrease of HDL diameter and smaller increases of most components of VLDL (very low density lipoprotein) subparticles. CONCLUSIONS: GWAS of the TG response identified a variant near LIPC as a main contributor to postprandial TG metabolism independent of fasting TG concentrations, resulting in smaller increases of HDL-TG and VLDL subparticles.

Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug-metabolite atlas.

Progress in high-throughput metabolic profiling provides unprecedented opportunities to obtain insights into the effects of drugs on human metabolism. The Biobanking BioMolecular Research Infrastructure of the Netherlands has constructed an atlas of drug-metabolite associations for 87 commonly prescribed drugs and 150 clinically relevant plasma-based metabolites assessed by proton nuclear magnetic resonance. The atlas includes a meta-analysis of ten cohorts (18,873 persons) and uncovers 1,071 drug-metabolite associations after evaluation of confounders including co-treatment. We show that the effect estimates of statins on metabolites from the cross-sectional study are comparable to those from intervention and genetic observational studies. Further data integration links proton pump inhibitors to circulating metabolites, liver function, hepatic steatosis and the gut microbiome. Our atlas provides a tool for targeted experimental pharmaceutical research and clinical trials to improve drug efficacy, safety and repurposing. We provide a web-based resource for visualization of the atlas (http://bbmri.researchlumc.nl/atlas/).