Cristina Menni

An atlas of genetic influences on human blood metabolites.

Genome-wide association scans with high-throughput metabolic profiling provide unprecedented insights into how genetic variation influences metabolism and complex disease. Here we report the most comprehensive exploration of genetic loci influencing human metabolism thus far, comprising 7,824 adult individuals from 2 European population studies. We report genome-wide significant associations at 145 metabolic loci and their biochemical connectivity with more than 400 metabolites in human blood. We extensively characterize the resulting in vivo blueprint of metabolism in human blood by integrating it with information on gene expression, heritability and overlap with known loci for complex disorders, inborn errors of metabolism and pharmacological targets. We further developed a database and web-based resources for data mining and results visualization. Our findings provide new insights into the role of inherited variation in blood metabolic diversity and identify potential new opportunities for drug development and for understanding disease.

Biomarkers for Type 2 Diabetes and Impaired Fasting Glucose Using a Nontargeted Metabolomics Approach

Using a nontargeted metabolomics approach of 447 fasting plasma metabolites, we searched for novel molecular markers that arise before and after hyperglycemia in a large population-based cohort of 2,204 females (115 type 2 diabetic [T2D] case subjects, 192 individuals with impaired fasting glucose [IFG], and 1,897 control subjects) from TwinsUK. Forty-two metabolites from three major fuel sources (carbohydrates, lipids, and proteins) were found to significantly correlate with T2D after adjusting for multiple testing; of these, 22 were previously reported as associated with T2D or insulin resistance. Fourteen metabolites were found to be associated with IFG. Among the metabolites identified, the branched-chain keto-acid metabolite 3-methyl-2-oxovalerate was the strongest predictive biomarker for IFG after glucose (odds ratio [OR] 1.65 [95% CI 1.39–1.95], P = 8.46 × 10−9) and was moderately heritable (h2 = 0.20). The association was replicated in an independent population (n = 720, OR 1.68 [ 1.34–2.11], P = 6.52 × 10−6) and validated in 189 twins with urine metabolomics taken at the same time as plasma (OR 1.87 [1.27–2.75], P = 1 × 10−3). Results confirm an important role for catabolism of branched-chain amino acids in T2D and IFG. In conclusion, this T2D-IFG biomarker study has surveyed the broadest panel of nontargeted metabolites to date, revealing both novel and known associated metabolites and providing potential novel targets for clinical prediction and a deeper understanding of causal mechanisms.

Lipidomics Profiling and Risk of Cardiovascular Disease in the Prospective Population-Based Bruneck Study

Background— The bulk of cardiovascular disease risk is not explained by traditional risk factors. Recent advances in mass spectrometry allow the identification and quantification of hundreds of lipid species. Molecular lipid profiling by mass spectrometry may improve cardiovascular risk prediction. Methods and Results— Lipids were extracted from 685 plasma samples of the prospective population-based Bruneck Study (baseline evaluation in 2000). One hundred thirty-five lipid species from 8 different lipid classes were profiled by shotgun lipidomics with the use of a triple-quadrupole mass spectrometer. Levels of individual species of cholesterol esters (CEs), lysophosphatidylcholines, phosphatidylcholines, phosphatidylethanolamines (PEs), sphingomyelins, and triacylglycerols (TAGs) were associated with cardiovascular disease over a 10-year observation period (2000–2010, 90 incident events). Among the lipid species with the strongest predictive value were TAGs and CEs with a low carbon number and double-bond content, including TAG(54:2) and CE(16:1), as well as PE(36:5) (P=5.1×10−7, 2.2×10−4, and 2.5×10−3, respectively). Consideration of these 3 lipid species on top of traditional risk factors resulted in improved risk discrimination and classification for cardiovascular disease (cross-validated &Dgr;C index, 0.0210 [95% confidence interval, 0.0010-0.0422]; integrated discrimination improvement, 0.0212 [95% confidence interval, 0.0031-0.0406]; and continuous net reclassification index, 0.398 [95% confidence interval, 0.175-0.619]). A similar shift in the plasma fatty acid composition was associated with cardiovascular disease in the UK Twin Registry (n=1453, 45 cases). Conclusions— This study applied mass spectrometry-based lipidomics profiling to population-based cohorts and identified molecular lipid signatures for cardiovascular disease. Molecular lipid species constitute promising new biomarkers that outperform the conventional biochemical measurements of lipid classes currently used in clinics.

Metabolomic markers reveal novel pathways of ageing and early development in human populations

Background Human ageing is a complex, multifactorial process and early developmental factors affect health outcomes in old age. Methods Metabolomic profiling on fasting blood was carried out in 6055 individuals from the UK. Stepwise regression was performed to identify a panel of independent metabolites which could be used as a surrogate for age. We also investigated the association with birthweight overall and within identical discordant twins and with genome-wide methylation levels. Results We identified a panel of 22 metabolites which combined are strongly correlated with age (R2 = 59%) and with age-related clinical traits independently of age. One particular metabolite, C-glycosyl tryptophan (C-glyTrp), correlated strongly with age (beta = 0.03, SE = 0.001, P = 7.0 × 10−157) and lung function (FEV1 beta = −0.04, SE = 0.008, P = 1.8 × 10−8 adjusted for age and confounders) and was replicated in an independent population (n = 887). C-glyTrp was also associated with bone mineral density (beta = −0.01, SE = 0.002, P = 1.9 × 10−6) and birthweight (beta = −0.06, SE = 0.01, P = 2.5 × 10−9). The difference in C-glyTrp levels explained 9.4% of the variance in the difference in birthweight between monozygotic twins. An epigenome-wide association study in 172 individuals identified three CpG-sites, associated with levels of C-glyTrp (P < 2 × 10−6). We replicated one CpG site in the promoter of the WDR85 gene in an independent sample of 350 individuals (beta = −0.20, SE = 0.04, P = 2.9 × 10−8). WDR85 is a regulator of translation elongation factor 2, essential for protein synthesis in eukaryotes. Conclusions Our data illustrate how metabolomic profiling linked with epigenetic studies can identify some key molecular mechanisms potentially determined in early development that produce long-term physiological changes influencing human health and ageing.

Glycans Are a Novel Biomarker of Chronological and Biological Ages

Fine structural details of glycans attached to the conserved N-glycosylation site significantly not only affect function of individual immunoglobulin G (IgG) molecules but also mediate inflammation at the systemic level. By analyzing IgG glycosylation in 5,117 individuals from four European populations, we have revealed very complex patterns of changes in IgG glycosylation with age. Several IgG glycans (including FA2B, FA2G2, and FA2BG2) changed considerably with age and the combination of these three glycans can explain up to 58% of variance in chronological age, significantly more than other markers of biological age like telomere lengths. The remaining variance in these glycans strongly correlated with physiological parameters associated with biological age. Thus, IgG glycosylation appears to be closely linked with both chronological and biological ages. Considering the important role of IgG glycans in inflammation, and because the observed changes with age promote inflammation, changes in IgG glycosylation also seem to represent a factor contributing to aging. Significance Statement Glycosylation is the key posttranslational mechanism that regulates function of immunoglobulins, with multiple systemic repercussions to the immune system. Our study of IgG glycosylation in 5,117 individuals from four European populations has revealed very extensive and complex changes in IgG glycosylation with age. The combined index composed of only three glycans explained up to 58% of variance in age, considerably more than other biomarkers of age like telomere lengths. The remaining variance in these glycans strongly correlated with physiological parameters associated with biological age; thus, IgG glycosylation appears to be closely linked with both chronological and biological ages. The ability to measure human biological aging using molecular profiling has practical applications for diverse fields such as disease prevention and treatment, or forensics.

The genetic architecture of the human immune system: A bioresource for autoimmunity and disease pathogenesis

Despite recent discoveries of genetic variants associated with autoimmunity and infection, genetic control of the human immune system during homeostasis is poorly understood. We undertook a comprehensive immunophenotyping approach, analyzing 78,000 immune traits in 669 female twins. From the top 151 heritable traits (up to 96% heritable), we used replicated GWAS to obtain 297 SNP associations at 11 genetic loci, explaining up to 36% of the variation of 19 traits. We found multiple associations with canonical traits of all major immune cell subsets and uncovered insights into genetic control for regulatory T cells. This data set also revealed traits associated with loci known to confer autoimmune susceptibility, providing mechanistic hypotheses linking immune traits with the etiology of disease. Our data establish a bioresource that links genetic control elements associated with normal immune traits to common autoimmune and infectious diseases, providing a shortcut to identifying potential mechanisms of immune-related diseases.

Association of systemic lupus erythematosus with decreased immunosuppressive potential of the IgG glycome.

Glycans attached to the Fc portion of IgG are important modulators of IgG effector functions. Interindividual differences in IgG glycome composition are large and they associate strongly with different inflammatory and autoimmune diseases. IKZF1, HLA–DQ2A/B, and BACH2 genetic loci that affect IgG glycome composition show pleiotropy with systemic lupus erythematosus (SLE), indicating a potentially causative role of aberrant IgG glycosylation in SLE. We undertook this large multicenter case–control study to determine whether SLE is associated with altered IgG glycosylation.

Whole-genome sequencing identifies common-to-rare variants associated with human blood metabolites

Genetic factors modifying the blood metabolome have been investigated through genome-wide association studies (GWAS) of common genetic variants and through exome sequencing. We conducted a whole-genome sequencing study of common, low-frequency and rare variants to associate genetic variations with blood metabolite levels using comprehensive metabolite profiling in 1,960 adults. We focused the analysis on 644 metabolites with consistent levels across three longitudinal data collections. Genetic sequence variations at 101 loci were associated with the levels of 246 (38%) metabolites (P ≤ 1.9 × 10−11). We identified 113 (10.7%) among 1,054 unrelated individuals in the cohort who carried heterozygous rare variants likely influencing the function of 17 genes. Thirteen of the 17 genes are associated with inborn errors of metabolism or other pediatric genetic conditions. This study extends the map of loci influencing the metabolome and highlights the importance of heterozygous rare variants in determining abnormal blood metabolic phenotypes in adults.

A rare variant in APOC3 is associated with plasma triglyceride and VLDL levels in Europeans

The analysis of rich catalogues of genetic variation from population-based sequencing provides an opportunity to screen for functional effects. Here we report a rare variant in APOC3 (rs138326449-A, minor allele frequency ~0.25% (UK)) associated with plasma triglyceride (TG) levels (−1.43 s.d. (s.e.=0.27 per minor allele (P-value=8.0 × 10−8)) discovered in 3,202 individuals with low read-depth, whole-genome sequence. We replicate this in 12,831 participants from five additional samples of Northern and Southern European origin (−1.0 s.d. (s.e.=0.173), P-value=7.32 × 10−9). This is consistent with an effect between 0.5 and 1.5 mmol l−1 dependent on population. We show that a single predicted splice donor variant is responsible for association signals and is independent of known common variants. Analyses suggest an independent relationship between rs138326449 and high-density lipoprotein (HDL) levels. This represents one of the first examples of a rare, large effect variant identified from whole-genome sequencing at a population scale.

Novel genetic variants associated with lumbar disc degeneration in northern Europeans: a meta-analysis of 4600 subjects

Objective Lumbar disc degeneration (LDD) is an important cause of low back pain, which is a common and costly problem. LDD is characterised by disc space narrowing and osteophyte growth at the circumference of the disc. To date, the agnostic search of the genome by genome-wide association (GWA) to identify common variants associated with LDD has not been fruitful. This study is the first GWA meta-analysis of LDD. Methods We have developed a continuous trait based on disc space narrowing and osteophytes growth which is measurable on all forms of imaging (plain radiograph, CT scan and MRI) and performed a meta-analysis of five cohorts of Northern European extraction each having GWA data imputed to HapMap V.2. Results This study of 4600 individuals identified four single nucleotide polymorphisms with p<5×10−8, the threshold set for genome-wide significance. We identified a variant in the PARK2 gene (p=2.8×10−8) associated with LDD. Differential methylation at one CpG island of the PARK2 promoter was observed in a small subset of subjects (β=8.74×10−4, p=0.006). Conclusions LDD accounts for a considerable proportion of low back pain and the pathogenesis of LDD is poorly understood. This work provides evidence of association of the PARK2 gene and suggests that methylation of the PARK2 promoter may influence degeneration of the intervertebral disc. This gene has not previously been considered a candidate in LDD and further functional work is needed on this hitherto unsuspected pathway.