Aoife O'Gorman

Metabolomics in the identification of biomarkers of dietary intake

Traditional methods for assessing dietary exposure can be unreliable, with under reporting one of the main problems. In an attempt to overcome such problems there is increasing interest in identifying biomarkers of dietary intake to provide a more accurate measurement. Metabolomics is an analytical technique that aims to identify and quantify small metabolites. Recently, there has been an increased interest in the application of metabolomics coupled with statistical analysis for the identification of dietary biomarkers, with a number of putative biomarkers identified. This minireview focuses on metabolomics based approaches and highlights some of the key successes.

Metabolic profiling of human follicular fluid identifies potential biomarkers of oocyte developmental competence

The use of metabolomic based techniques to aid oocyte and embryo selection has gained attention in recent years. Previous work from our laboratory has demonstrated that the (1)H NMR-based metabolic profile of follicular fluid correlates with oocyte developmental potential. Patients undergoing IVF at the Merrion Fertility Clinic had follicular fluid collected at the time of oocyte retrieval. The fatty acid composition of follicular fluid from follicles where oocytes fertilised and developed into multi-cell embryos (n=15) and from oocytes that fertilised normally but failed to cleave (n=9) (cleaved vs non-cleaved) was compared. Statistical analysis was performed on the data using univariate and multivariate techniques. Analysis of the fatty acid composition revealed that there were nine fatty acids significantly different between follicular fluid from the cleaved and the non-cleaved sample groups. Of particular interest were the higher concentration of total saturated (P=0.03) and the lower concentration of total polyunsaturated fatty acids in the non-cleaved sample group (P=0.001). Random forest classification models were used to predict successful cleavage in follicular fluid samples producing models with errors rates of <10%. Receiver operating characteristic analysis demonstrated that the model had good predictability with an area under the curve of 0.96. The panel of fatty acid biomarkers identified in this study indicates that the fatty acid composition of follicular fluid may be more predictive in comparison to other previously identified biomarkers. Following validation in a larger cohort, these biomarkers may have the potential to be used in fertility clinics to aid the selection of oocytes in the future.

Metabolomics as a tool in nutritional research.

Purpose of review Metabolomics is emerging as a powerful tool for studying metabolic processes and in recent years, the applications in the area of nutrition have risen rapidly. The present review gives an overview of the current applications in the field of nutrition and identifies areas in need of advancement. Recent findings Applications in nutrition research can in general be divided into three main areas: identification of dietary biomarkers, study of diet-related diseases and identification of biomarkers of disease and application to dietary intervention studies as a tool to identify molecular mechanisms. Summary Metabolomics has made a significant impact on all the areas identified above and is set to have a major impact on the study of diet–health relationships.

Negative energy balance affects imprint stability in oocytes recovered from postpartum dairy cows.

Ovarian follicle development in post-partum, high-producing dairy cows, occurs in a compromised endogenous metabolic environment (referred to as negative energy balance, NEB). Key events that occur during oocyte/follicle growth, such as the vital process of genomic imprinting, may be detrimentally affected by this altered ovarian environment. Imprinting is crucial for placental function and regulation of fetal growth, therefore failure to establish and maintain imprints during oocyte growth may contribute to early embryonic loss. Using ovum pick-up (OPU), oocytes and follicular fluid samples were recovered from cows between days 20 and 115 post-calving, encompassing the NEB period. In a complimentary study, cumulus oocyte complexes were in vitro matured under high non-esterified fatty acid (NEFA) concentrations and in the presence of the methyl-donor S-adenosylmethionine (SAM). Pyrosequencing revealed the loss of methylation at several imprinted loci in the OPU derived oocytes. The loss of DNA methylation was observed at the PLAGL1 locus in oocytes, following in vitro maturation (IVM) in the presence of elevated NEFAs and SAM. Finally, metabolomic analysis of postpartum follicular fluid samples revealed significant differences in several branched chain amino acids, with fatty acid profiles bearing similarities to those characteristic of lactating dairy cows. These results provide the first evidence that (1) the postpartum ovarian environment may affect maternal imprint acquisition and (2) elevated NEFAs during IVM can lead to the loss of imprinted gene methylation in bovine oocytes.

Metabolomic applications in nutritional research: a perspective

Metabolomics focuses on the global study of metabolites in cells, tissues and biofluids. Analytical technologies such as nuclear magnetic resonance (NMR) spectroscopy and hyphenated mass spectrometry (MS) combined with advanced multivariate statistical methods allow us to study perturbations in metabolism. The close link between metabolism and nutrition has seen the application of metabolomics in nutritional research increase in recent times. Such applications can be divided into three main categories, namely (1) the area of dietary biomarker identification, (2) diet-related diseases and (3) nutritional interventions. The present perspective gives an overview of these applications and an outlook to the future.

Lactation-induced changes in metabolic status and follicular-fluid metabolomic profile in postpartum dairy cows

The aim was to investigate the effect of lactation on the composition of pre-ovulatory follicular fluid (FF). Forty in-calf primiparous heifers and 20 maiden heifers were enrolled. Immediately after calving, half of the cows were dried off while the remainder were milked twice daily. Serum samples were collected twice weekly from two weeks pre- to 84 days postpartum (dpp). FF was analysed by gas chromatography-mass spectrometry. Serum concentrations of non-esterified fatty acids and β-hydroxybutyrate were higher, while glucose, insulin and Insulin-like growth factor 1 (IGF1) concentrations were lower in lactating cows compared with non-lactating cows and heifers (P<0.01). Principal component analysis of FF metabolites revealed a clear separation of the lactating group from both non-lactating cows and heifers. The amino acids tyrosine, phenylalanine and valine and fatty acids heneicosanoic acid and docosahexaenoic acid were all lower in FF from lactating compared with dry cows (P<0.05). FF from lactating cows was higher in aminoadipic acid, α-aminobutyric acid, glycine and serine while histidine, leucine, lysine, methionine and ornithine were all lower than in dry cows and heifers (P<0.05). The ratio of n6:n3 was higher in lactating cows compared with both non-lactating cows and heifers, whereas total n3 polyunsaturated fatty acids, pentadecanoic, linolenic, elaidic and arachidonic acids were all lower in the FF of lactating cows than both non-lactating cows and heifers (P<0.05). In conclusion, lactation induces distinct changes in the overall metabolic status of postpartum lactating dairy cows which are associated with divergent metabolite profiles in FF.

The role of metabolomics in determination of new dietary biomarkers

Traditional methods for the assessment of dietary intake are prone to error; in order to improve and enhance these methods increasing interest in the identification of dietary biomarkers has materialised. Metabolomics has emerged as a key tool in the area of dietary biomarker discovery and to date the use of metabolomics has identified a number of putative biomarkers. Applications to identify novel biomarkers of intake have in general taken three approaches: (1) specific acute intervention studies to identify specific biomarkers of intake; (2) searching for biomarkers in cohort studies by correlating to self-reported intake of a specific food/food group(s); (3) analysing dietary patterns in conjunction with metabolomic profiles to identify biomarkers and nutritypes. A number of analytical technologies are employed in metabolomics as currently there is no single technique capable of measuring the entire metabolome. These approaches each have their own advantages and disadvantages. The present review will provide an overview of current technologies and applications of metabolomics in the determination of new dietary biomarkers. In addition, it will address some of the current challenges in the field and future outlooks.

A systematic review of metabolite biomarkers of schizophrenia

Current diagnosis of schizophrenia relies exclusively on the potentially subjective interpretation of clinical symptoms and social functioning as more objective biological measurement and medical diagnostic tests are not presently available. The use of metabolomics in the discovery of disease biomarkers has grown in recent years. Metabolomic methods could aid in the discovery of diagnostic biomarkers of schizophrenia. This systematic review focuses on biofluid metabolites associated with schizophrenia. A systematic search of Web of Science and Ovid Medline databases was conducted and 63 studies investigating metabolite biomarkers of schizophrenia were included. A review of these studies revealed several potential metabolite signatures of schizophrenia including reduced levels of essential polyunsaturated fatty acids (EPUFAs), vitamin E and creatinine; and elevated levels of lipid peroxidation metabolites and glutamate. Further research is needed to validate these biomarkers and would benefit from large cohort studies and more homogeneous and well-defined subject groups.

Identification of a plasma signature of psychotic disorder in children and adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort

The identification of an early biomarker of psychotic disorder is important as early treatment is associated with improved patient outcome. Metabolomic and lipidomic approaches in combination with multivariate statistical analysis were applied to identify plasma alterations in children (age 11) (38 cases vs 67 controls) and adolescents (age 18) (36 cases vs 117 controls) preceeding or coincident with the development of psychotic disorder (PD) at age 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC). Overall, 179 lipids were identified at age 11, with 32 found to be significantly altered between the control and PD groups. Following correction for multiple comparisons, 8 of these lipids remained significant (lysophosphatidlycholines (LPCs) LPC(18:1), LPC(18:2), LPC(20:3); phosphatidlycholines (PCs) PC(32:2; PC(34:2), PC(36:4), PC(0-34-3) and sphingomyelin (SM) SM(d18:1/24:0)), all of which were elevated in the PD group. At age 18, 23 lipids were significantly different between the control and PD groups, although none remained significant following correction for multiple comparisons. In conclusion, the findings indicate that the lipidome is altered in the blood during childhood, long before the development of psychotic disorder. LPCs in particular are elevated in those who develop PD, indicating inflammatory abnormalities and altered phospholipid metabolism. These findings were not found at age 18, suggesting there may be ongoing alterations in the pathophysiological processes from prodrome to onset of PD.

Follicular fluid and serum metabolites in Holstein cows are predictive of genetic merit for fertility

The aims of the present study were to: (1) characterise the metabolome of follicular fluid and serum in dairy cows with similar genetic merit for milk production but with extremes of good (Fert+) or poor (Fert-) genetic merit for fertility; and (2) identify potential biomarkers of dairy cow fertility. Follicular fluid from the first wave dominant follicle and serum were collected on Day 7 of the oestrous cycle. The most pronounced effect of genotype was noted in the serum, where the abundance of total polyunsaturated fatty acids and n-6 polyunsaturated fatty acids was greater in Fert+ cows, and the abundance of total saturated fatty acids was greater in Fert- cows. The abundance of nine fatty acids (arachidic acid, heneicosanoic acid, myristic acid, behenic acid, myristoleic acid, heptadecenoic acid, cis-11-eicosanoic acid, nervonic acid and γ-linolenic acid) in follicular fluid was affected by genotype. Concentrations of cysteine, leucine, ornithine, proline and tyrosine in follicular fluid, and asparagine, creatinine, cysteine, methionine, proline and valine in serum, were also affected by genotype. Receiver operating characteristic curve analysis indicated that the follicular fluid and serum fatty acids and follicular fluid amino acids that were significantly affected by genotype were highly predictive of fertility genotype.