Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank.

Blood lipids and metabolites are markers of current health and future disease risk. Here, we describe plasma nuclear magnetic resonance (NMR) biomarker data for 118,461 participants in the UK Biobank. The biomarkers cover 249 measures of lipoprotein lipids, fatty acids, and small molecules such as amino acids, ketones, and glycolysis metabolites. We provide an atlas of associations of these biomarkers to prevalence, incidence, and mortality of over 700 common diseases ( nightingalehealth.com/atlas ). The results reveal a plethora of biomarker associations, including susceptibility to infectious diseases and risk of various cancers, joint disorders, and mental health outcomes, indicating that abundant circulating lipids and metabolites are risk markers beyond cardiometabolic diseases. Clustering analyses indicate similar biomarker association patterns across different disease types, suggesting latent systemic connectivity in the susceptibility to a diverse set of diseases. This work highlights the value of NMR based metabolic biomarker profiling in large biobanks for public health research and translation.

Genetic and observational evidence: No independent role for cholesterol efflux over static high-density lipoprotein concentration measures in coronary heart disease risk assessment.

BACKGROUND: Observational findings for high-density lipoprotein (HDL)-mediated cholesterol efflux capacity (HDL-CEC) and coronary heart disease (CHD) appear inconsistent, and knowledge of the genetic architecture of HDL-CEC is limited. OBJECTIVES: A large-scale observational study on the associations of HDL-CEC and other HDL-related measures with CHD and the largest genome-wide association study (GWAS) of HDL-CEC. PARTICIPANTS/METHODS: Six independent cohorts were included with follow-up data for 14,438 participants to investigate the associations of HDL-related measures with incident CHD (1,570 events). The GWAS of HDL-CEC was carried out in 20,372 participants. RESULTS: HDL-CEC did not associate with CHD when adjusted for traditional risk factors and HDL cholesterol (HDL-C). In contradiction, almost all HDL-related concentration measures associated consistently with CHD after corresponding adjustments. There were no genetic loci associated with HDL-CEC independent of HDL-C and triglycerides. CONCLUSION: HDL-CEC is not unequivocally associated with CHD in contrast to HDL-C, apolipoprotein A-I, and most of the HDL subclass particle concentrations.

Metabolic Profiles Help Discriminate Mild Cognitive Impairment from Dementia Stage in Alzheimer's Disease.

Accurate differentiation between neurodegenerative diseases is developing quickly and has reached an effective level in disease recognition. However, there has been less focus on effectively distinguishing the prodromal state from later dementia stages due to a lack of suitable biomarkers. We utilized the Disease State Index (DSI) machine learning classifier to see how well quantified metabolomics data compares to clinically used cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD). The metabolic profiles were quantified for 498 serum and CSF samples using proton nuclear magnetic resonance spectroscopy. The patient cohorts in this study were dementia (with a clinical AD diagnosis) (N = 359), mild cognitive impairment (MCI) (N = 96), and control patients with subjective memory complaints (N = 43). DSI classification was conducted for MCI (N = 51) and dementia (N = 214) patients with low CSF amyloid-ß levels indicating AD pathology and controls without such amyloid pathology (N = 36). We saw that the conventional CSF markers of AD were better at classifying controls from both dementia and MCI patients. However, quantified metabolic subclasses were more effective in classifying MCI from dementia. Our results show the consistent effectiveness of traditional CSF biomarkers in AD diagnostics. However, these markers are relatively ineffective in differentiating between MCI and the dementia stage, where the quantified metabolomics data provided significant benefit.

EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics.

MOTIVATION: An intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming. IMPLEMENTATION: EpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser. GENERAL FEATURES: Standard epidemiological analyses and self-organizing maps for data-driven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N >10 000). AVAILABILITY: The software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal].

Low Serum High-Density Lipoprotein Cholesterol Levels Associate with the C9orf72 Repeat Expansion in Frontotemporal Lobar Degeneration Patients.

Decreased levels of serum high-density lipoprotein (HDL) cholesterol have previously been linked to systemic inflammation and neurodegenerative diseases, such as Alzheimer's disease. Here, we aimed to analyze the lipoprotein profile and inflammatory indicators, the high-sensitivity C-reactive peptide (hs-CRP) and glycoprotein acetyls (GlycA), in sporadic and C9orf72 repeat expansion-associated frontotemporal lobar degeneration (FTLD) patients. The C9orf72 hexanucleotide repeat expansion is the most frequent genetic etiology underlying FTLD. The concentrations of different lipid measures in the sera of 67 FTLD patients (15 C9orf72 repeat expansion carriers), including GlycA, were analyzed by nuclear magnetic resonance spectroscopy. To verify the state of systemic inflammation, hs-CRP was also quantified from patient sera. We found that the total serum HDL concentration was decreased in C9orf72 repeat expansion carriers when compared to non-carriers. Moreover, decreased concentrations of HDL particles of different sizes and subclass were consistently observed. No differences were detected in the very low- and low-density lipoprotein subclasses between the C9orf72 repeat expansion carriers and non-carriers. Furthermore, hs-CRP and GlycA levels did not differ between the C9orf72 repeat expansion carriers and non-carriers. In conclusion, the HDL-related changes were linked with C9orf72 repeat expansion associated FTLD but were not seen to associate with systemic inflammation. The underlying reason for the HDL changes remains unclear.

Direct Estimation of HDL-Mediated Cholesterol Efflux Capacity from Serum.

BACKGROUND: HDL-mediated cholesterol efflux capacity (HDL-CEC) is a functional attribute that may have a protective role in atherogenesis. However, the estimation of HDL-CEC is based on in vitro cell assays that are laborious and hamper large-scale phenotyping. METHODS: Here, we present a cost-effective high-throughput nuclear magnetic resonance (NMR) spectroscopy method to estimate HDL-CEC directly from serum. We applied the new method in a population-based study of 7603 individuals including 574 who developed incident coronary heart disease (CHD) during 15 years of follow-up, making this the largest quantitative study for HDL-CEC. RESULTS: As estimated by NMR-spectroscopy, a 1-SD higher HDL-CEC was associated with a lower risk of incident CHD (hazards ratio, 0.86; 95%CI, 0.79-0.93, adjusted for traditional risk factors and HDL-C). These findings are consistent with published associations based on in vitro cell assays. CONCLUSIONS: These corroborative large-scale findings provide further support for a potential protective role of HDL-CEC in CHD and substantiate this new method and its future applications.

Association of circulating metabolites with healthy diet and risk of cardiovascular disease: analysis of two cohort studies.

Diet may modify metabolomic profiles towards higher or lower cardiovascular disease (CVD) risk. We aimed to identify metabolite profiles associated with high adherence to dietary recommendations - the Alternative Healthy Eating Index (AHEI) - and the extent to which metabolites associated with AHEI also predict incident CVD. Relations between AHEI score and 80 circulating lipids and metabolites, quantified by nuclear magnetic resonance metabolomics, were examined using linear regression models in the Whitehall II study (n = 4824, 55.9 ± 6.1 years, 28.0% women) and were replicated in the Cardiovascular Risk in Young Finns Study (n = 1716, 37.7 ± 5.0 years, 56.3% women). We used Cox models to study associations between metabolites and incident CVD over the 15.8-year follow-up in the Whitehall II study. After adjustment for confounders, higher AHEI score (indicating healthier diet) was associated with higher degree of unsaturation of fatty acids (FA) and higher ratios of polyunsaturated FA, omega-3 and docosahexaenoic acid relative to total FA in both Whitehall II and Young Finns studies. A concordance of associations of metabolites with higher AHEI score and lower CVD risk was observed in Whitehall II. Adherence to healthy diet seems to be associated with specific FA that reduce risk of CVD.

NAFLD risk alleles in PNPLA3, TM6SF2, GCKR and LYPLAL1 show divergent metabolic effects.

Fatty liver has been associated with unfavourable metabolic changes in circulation. To provide insights in fatty liver-related metabolic deviations, we compared metabolic association profile of fatty liver versus metabolic association profiles of genotypes increasing the risk of non-alcoholic fatty liver disease (NAFLD). The cross-sectional associations of ultrasound-ascertained fatty liver with 123 metabolic measures were determined in 1810 (Nfatty liver = 338) individuals aged 34-49 years from The Cardiovascular Risk in Young Finns Study. The association profiles of NAFLD-risk alleles in PNPLA3, TM6SF2, GCKR, and LYPLAL1 with the corresponding metabolic measures were obtained from a publicly available metabolomics GWAS including up to 24 925 Europeans. The risk alleles showed different metabolic effects: PNPLA3 rs738409-G, the strongest genetic NAFLD risk factor, did not associate with metabolic changes. Metabolic effects of GCKR rs1260326-T were comparable in many respects to the fatty liver associations. Metabolic effects of LYPLAL1 rs12137855-C were similar, but statistically less robust, to the effects of GCKR rs1260326-T. TM6SF2 rs58542926-T displayed opposite metabolic effects when compared with the fatty liver associations. The metabolic effects of the risk alleles highlight heterogeneity of the molecular pathways leading to fatty liver and suggest that the fatty liver-related changes in the circulating lipids and metabolites may vary depending on the underlying pathophysiological mechanism. Despite the robust cross-sectional associations on population level, the present results showing neutral or cardioprotective metabolic effects for some of the NAFLD risk alleles advocate that hepatic lipid accumulation by itself may not increase the level of circulating lipids or other metabolites.

Association of branched-chain amino acids and other circulating metabolites with risk of incident dementia and Alzheimer's disease: A prospective study in eight cohorts.

INTRODUCTION: Metabolite, lipid, and lipoprotein lipid profiling can provide novel insights into mechanisms underlying incident dementia and Alzheimer's disease. METHODS: We studied eight prospective cohorts with 22,623 participants profiled by nuclear magnetic resonance or mass spectrometry metabolomics. Four cohorts were used for discovery with replication undertaken in the other four to avoid false positives. For metabolites that survived replication, combined association results are presented. RESULTS: Over 246,698 person-years, 995 and 745 cases of incident dementia and Alzheimer's disease were detected, respectively. Three branched-chain amino acids (isoleucine, leucine, and valine), creatinine and two very low density lipoprotein (VLDL)-specific lipoprotein lipid subclasses were associated with lower dementia risk. One high density lipoprotein (HDL; the concentration of cholesterol esters relative to total lipids in large HDL) and one VLDL (total cholesterol to total lipids ratio in very large VLDL) lipoprotein lipid subclass was associated with increased dementia risk. Branched-chain amino acids were also associated with decreased Alzheimer's disease risk and the concentration of cholesterol esters relative to total lipids in large HDL with increased Alzheimer's disease risk. DISCUSSION: Further studies can clarify whether these molecules play a causal role in dementia pathogenesis or are merely markers of early pathology.

Effect of Dietary Counseling on a Comprehensive Metabolic Profile from Childhood to Adulthood.

OBJECTIVES: To study the effects of repeated, infancy-onset dietary counseling on a detailed metabolic profile. Effects of dietary saturated fat replacement on circulating concentrations of metabolic biomarkers still remain unknown. STUDY DESIGN: The Special Turku Coronary Risk Factor Intervention Project (STRIP) study is a longitudinal, randomized atherosclerosis prevention trial in which repeated dietary counseling aimed at reducing the proportion of saturated fat intake. Nuclear magnetic resonance metabolomics quantified circulating metabolites from serum samples assessed at age 9 (n = 554), 11 (n = 553), 13 (n = 508), 15 (n = 517), 17 (n = 457), and 19 (n = 417) years. RESULTS: The intervention reduced dietary intake of saturated fat (mean difference in daily percentage of total energy intake: -2.1 [95% CI -1.9 to -2.3]) and increased intake of polyunsaturated fat (0.6 [0.5-0.7]). The dietary counseling intervention led to greater serum proportions of polyunsaturated fatty acids (P < .001), with greater proportions of both circulating omega-3 (P = .02) and omega-6 (P < .001) fatty acids. The proportion of saturated fatty acids in serum was lower for both boys and girls in the intervention group (P < .001), whereas the serum proportion of monounsaturated fat was lower for boys in the intervention group only (P < .001). The intervention also reduced circulating intermediate-density lipoprotein and low-density lipoprotein lipid concentrations (P < .01). Dietary intervention effects on nonlipid biomarkers were minor except from greater concentrations of glutamine in the intervention group. CONCLUSIONS: Repeated dietary counseling from infancy to early adulthood yielded favorable effects on multiple circulating fatty acids and lipoprotein subclass lipids, particularly in boys. These molecular effects substantiate the beneficial role of saturated fat replacement on the metabolic risk profile. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00223600.

Identification of seven novel loci associated with amino acid levels using single-variant and gene-based tests in 8545 Finnish men from the METSIM study.

Comprehensive metabolite profiling captures many highly heritable traits, including amino acid levels, which are potentially sensitive biomarkers for disease pathogenesis. To better understand the contribution of genetic variation to amino acid levels, we performed single variant and gene-based tests of association between nine serum amino acids (alanine, glutamine, glycine, histidine, isoleucine, leucine, phenylalanine, tyrosine, and valine) and 16.6 million genotyped and imputed variants in 8545 non-diabetic Finnish men from the METabolic Syndrome In Men (METSIM) study with replication in Northern Finland Birth Cohort (NFBC1966). We identified five novel loci associated with amino acid levels (P = < 5×10-8): LOC157273/PPP1R3B with glycine (rs9987289, P = 2.3×10-26); ZFHX3 (chr16:73326579, minor allele frequency (MAF) = 0.42%, P = 3.6×10-9), LIPC (rs10468017, P = 1.5×10-8), and WWOX (rs9937914, P = 3.8×10-8) with alanine; and TRIB1 with tyrosine (rs28601761, P = 8×10-9). Gene-based tests identified two novel genes harboring missense variants of MAF <1% that show aggregate association with amino acid levels: PYCR1 with glycine (Pgene = 1.5×10-6) and BCAT2 with valine (Pgene = 7.4×10-7); neither gene was implicated by single variant association tests. These findings are among the first applications of gene-based tests to identify new loci for amino acid levels. In addition to the seven novel gene associations, we identified five independent signals at established amino acid loci, including two rare variant signals at GLDC (rs138640017, MAF=0.95%, Pconditional = 5.8×10-40) with glycine levels and HAL (rs141635447, MAF = 0.46%, Pconditional = 9.4×10-11) with histidine levels. Examination of all single variant association results in our data revealed a strong inverse relationship between effect size and MAF (Ptrend<0.001). These novel signals provide further insight into the molecular mechanisms of amino acid metabolism and potentially, their perturbations in disease.

DHA mediates the protective effect of fish consumption on new episodes of depression among women.

In a longitudinal cohort study of young Australian adults, we reported that for women higher baseline levels of fish consumption were associated with reduced incidence of new depressive episodes during the 5-year follow-up. Fish are high in both n-3 fatty acids and tyrosine. In this study, we seek to determine whether n-3 fatty acids or tyrosine explain the observed association. During 2004-2006, a FFQ (nine fish items) was used to estimate weekly fish consumption among 546 women aged 26-36 years. A fasting blood sample was taken and high-throughput NMR spectroscopy was used to measure 233 metabolites, including serum n-3 fatty acids and tyrosine. During 2009-2011, new episodes of depression since baseline were identified using the lifetime version of the Composite International Diagnostic Interview. Relative risks were calculated using log-binomial regression and indirect effects estimated using the STATA binary_mediation command. Potential mediators were added to separate models, and mediation was quantified as the proportion of the total effect due to the mediator. The n-3 DHA mediated 25·3 % of the association between fish consumption and depression when fish consumption was analysed as a continuous variable and 16·6 % when dichotomised (reference group: <2 serves/week). Tyrosine did not mediate the association (<0·1 %). Components in fish other than n-3 fatty acids and tyrosine might be beneficial for women's mental health.

Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies.

Detailed metabolic profiling in large-scale epidemiologic studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy has found widespread use, already profiling over 400,000 blood samples. Over 200 metabolic measures are quantified per sample; in addition to many biomarkers routinely used in epidemiology, the method simultaneously provides fine-grained lipoprotein subclass profiling and quantification of circulating fatty acids, amino acids, gluconeogenesis-related metabolites, and many other molecules from multiple metabolic pathways. Here we focus on applications of magnetic resonance metabolomics for quantifying circulating biomarkers in large-scale epidemiology. We highlight the molecular characterization of risk factors, use of Mendelian randomization, and the key issues of study design and analyses of metabolic profiling for epidemiology. We also detail how integration of metabolic profiling data with genetics can enhance drug development. We discuss why quantitative metabolic profiling is becoming widespread in epidemiology and biobanking. Although large-scale applications of metabolic profiling are still novel, it seems likely that comprehensive biomarker data will contribute to etiologic understanding of various diseases and abilities to predict disease risks, with the potential to translate into multiple clinical settings.

Common, low-frequency, and rare genetic variants associated with lipoprotein subclasses and triglyceride measures in Finnish men from the METSIM study.

Lipid and lipoprotein subclasses are associated with metabolic and cardiovascular diseases, yet the genetic contributions to variability in subclass traits are not fully understood. We conducted single-variant and gene-based association tests between 15.1M variants from genome-wide and exome array and imputed genotypes and 72 lipid and lipoprotein traits in 8,372 Finns. After accounting for 885 variants at 157 previously identified lipid loci, we identified five novel signals near established loci at HIF3A, ADAMTS3, PLTP, LCAT, and LIPG. Four of the signals were identified with a low-frequency (0.005

Differential Associations of Inflammatory Markers With Insulin Sensitivity and Secretion: The Prospective METSIM Study.

Context: Low-grade inflammation is involved in the development of type 2 diabetes and cardiovascular disease (CVD); however, prospective studies evaluating inflammatory markers as predictors of changes in insulin secretion and insulin sensitivity are lacking. Objective: We investigated the associations of glycoprotein acetyls (GlycA), interleukin-1 receptor antagonist (IL-1RA), and high-sensitivity C-reactive protein (hs-CRP) with insulin secretion, insulin sensitivity, incident type 2 diabetes, hypertension, CVD events, and total mortality in the prospective Metabolic Syndrome in Men (METSIM) study. Design: A prospective study. Participants: The cross-sectional METSIM study included 8749 nondiabetic Finnish men aged 45 to 73 years, who had been randomly selected from the population register of Kuopio, Finland. A total of 5401 men participated in the 6.8-year follow-up study. Main Outcome Measures: Changes in insulin secretion, insulin sensitivity, and cardiometabolic traits during the follow-up period and the incidence of type 2 diabetes, hypertension, CVD events, and total mortality. Results: During the follow-up period, GlycA was associated with impaired insulin secretion, hyperglycemia, incident type 2 diabetes (hazard ratio, 1.37; 95% confidence interval, 1.29 to 1.46) and CVD (hazard ratio, 1.21; 95% confidence interval, 1.12 to 1.32). IL-1RA and hs-CRP were associated with adverse changes in insulin sensitivity and obesity-related traits and with total mortality (hazard ratio, 1.13; 95% confidence interval, 1.07 to 1.20; and hazard ratio, 1.08; 95% confidence interval, 1.04 to 1.11, respectively). Conclusions: Inflammatory markers differentially predicted changes in insulin secretion and insulin sensitivity. GlycA predicted impaired insulin secretion, and IL-1RA and hs-CRP predicted changes in insulin sensitivity. Combining the three markers improved the prediction of disease outcomes, suggesting that they capture different aspects of low-grade inflammation.

An interaction map of circulating metabolites, immune gene networks, and their genetic regulation.

BACKGROUND: Immunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up. RESULTS: We identify topologically replicable gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. Modules of mast cell/basophil and neutrophil function show temporally stable metabolite associations over 7-year follow-up, providing evidence that these modules and their constituent gene products may play central roles in metabolic inflammation. Furthermore, the strongest mQTL in ARHGEF3 also displays clear temporal stability, supporting widespread trans effects at this locus. CONCLUSIONS: This study provides a detailed map of natural variation at the blood immunometabolic interface and its genetic basis, and may facilitate subsequent studies to explain inter-individual variation in cardiometabolic disease.

Association of pre-pregnancy body mass index with offspring metabolic profile: Analyses of 3 European prospective birth cohorts.

BACKGROUND: A high proportion of women start pregnancy overweight or obese. According to the developmental overnutrition hypothesis, this could lead offspring to have metabolic disruption throughout their lives and thus perpetuate the obesity epidemic across generations. Concerns about this hypothesis are influencing antenatal care. However, it is unknown whether maternal pregnancy adiposity is associated with long-term risk of adverse metabolic profiles in offspring, and if so, whether this association is causal, via intrauterine mechanisms, or explained by shared familial (genetic, lifestyle, socioeconomic) characteristics. We aimed to determine if associations between maternal body mass index (BMI) and offspring systemic cardio-metabolic profile are causal, via intrauterine mechanisms, or due to shared familial factors. METHODS AND FINDINGS: We used 1- and 2-stage individual participant data (IPD) meta-analysis, and a negative-control (paternal BMI) to examine the association between maternal pre-pregnancy BMI and offspring serum metabolome from 3 European birth cohorts (offspring age at blood collection: 16, 17, and 31 years). Circulating metabolic traits were quantified by high-throughput nuclear magnetic resonance metabolomics. Results from 1-stage IPD meta-analysis (N = 5327 to 5377 mother-father-offspring trios) showed that increasing maternal and paternal BMI was associated with an adverse cardio-metabolic profile in offspring. We observed strong positive associations with very-low-density lipoprotein (VLDL)-lipoproteins, VLDL-cholesterol (C), VLDL-triglycerides, VLDL-diameter, branched/aromatic amino acids, glycoprotein acetyls, and triglycerides, and strong negative associations with high-density lipoprotein (HDL), HDL-diameter, HDL-C, HDL2-C, and HDL3-C (all P < 0.003). Slightly stronger magnitudes of associations were present for maternal compared with paternal BMI across these associations; however, there was no strong statistical evidence for heterogeneity between them (all bootstrap P > 0.003, equivalent to P > 0.05 after accounting for multiple testing). Results were similar in each individual cohort, and in the 2-stage analysis. Offspring BMI showed similar patterns of cross-sectional association with metabolic profile as for parental pre-pregnancy BMI associations but with greater magnitudes. Adjustment of parental BMI-offspring metabolic traits associations for offspring BMI suggested the parental associations were largely due to the association of parental BMI with offspring BMI. Limitations of this study are that inferences cannot be drawn about the role of circulating maternal fetal fuels (i.e., glucose, lipids, fatty acids, and amino acids) on later offspring metabolic profile. In addition, BMI may not reflect potential effects of maternal pregnancy fat distribution. CONCLUSION: Our findings suggest that maternal BMI-offspring metabolome associations are likely to be largely due to shared genetic or familial lifestyle confounding rather than to intrauterine mechanisms.

Trans-ancestry Fine Mapping and Molecular Assays Identify Regulatory Variants at the ANGPTL8 HDL-C GWAS Locus.

Recent genome-wide association studies (GWAS) have identified variants associated with high-density lipoprotein cholesterol (HDL-C) located in or near the ANGPTL8 gene. Given the extensive sharing of GWAS loci across populations, we hypothesized that at least one shared variant at this locus affects HDL-C. The HDL-C-associated variants are coincident with expression quantitative trait loci for ANGPTL8 and DOCK6 in subcutaneous adipose tissue; however, only ANGPTL8 expression levels are associated with HDL-C levels. We identified a 400-bp promoter region of ANGPTL8 and enhancer regions within 5 kb that contribute to regulating expression in liver and adipose. To identify variants functionally responsible for the HDL-C association, we performed fine-mapping analyses and selected 13 candidate variants that overlap putative regulatory regions to test for allelic differences in regulatory function. Of these variants, rs12463177-G increased transcriptional activity (1.5-fold, P = 0.004) and showed differential protein binding. Six additional variants (rs17699089, rs200788077, rs56322906, rs3760782, rs737337, and rs3745683) showed evidence of allelic differences in transcriptional activity and/or protein binding. Taken together, these data suggest a regulatory mechanism at the ANGPTL8 HDL-C GWAS locus involving tissue-selective expression and at least one functional variant.

Experimental and Human Evidence for Lipocalin-2 (Neutrophil Gelatinase-Associated Lipocalin [NGAL]) in the Development of Cardiac Hypertrophy and heart failure.

BACKGROUND: Cardiac hypertrophy increases the risk of developing heart failure and cardiovascular death. The neutrophil inflammatory protein, lipocalin-2 (LCN2/NGAL), is elevated in certain forms of cardiac hypertrophy and acute heart failure. However, a specific role for LCN2 in predisposition and etiology of hypertrophy and the relevant genetic determinants are unclear. Here, we defined the role of LCN2 in concentric cardiac hypertrophy in terms of pathophysiology, inflammatory expression networks, and genomic determinants. METHODS AND RESULTS: We used 3 experimental models: a polygenic model of cardiac hypertrophy and heart failure, a model of intrauterine growth restriction and Lcn2-knockout mouse; cultured cardiomyocytes; and 2 human cohorts: 114 type 2 diabetes mellitus patients and 2064 healthy subjects of the YFS (Young Finns Study). In hypertrophic heart rats, cardiac and circulating Lcn2 was significantly overexpressed before, during, and after development of cardiac hypertrophy and heart failure. Lcn2 expression was increased in hypertrophic hearts in a model of intrauterine growth restriction, whereas Lcn2-knockout mice had smaller hearts. In cultured cardiomyocytes, Lcn2 activated molecular hypertrophic pathways and increased cell size, but reduced proliferation and cell numbers. Increased LCN2 was associated with cardiac hypertrophy and diastolic dysfunction in diabetes mellitus. In the YFS, LCN2 expression was associated with body mass index and cardiac mass and with levels of inflammatory markers. The single-nucleotide polymorphism, rs13297295, located near LCN2 defined a significant cis-eQTL for LCN2 expression. CONCLUSIONS: Direct effects of LCN2 on cardiomyocyte size and number and the consistent associations in experimental and human analyses reveal a central role for LCN2 in the ontogeny of cardiac hypertrophy and heart failure.