Changes in Oxidised Phospholipids in Response to Oxidative Stress in Microtubule-Associated Protein Tau (MAPT) Mutant Dopamine Neurons.

Microtubule-associated protein Tau (MAPT) is strongly associated with the development of neurodegenerative diseases. In addition to driving the formation of neurofibrillary tangles (NFT), mutations in the MAPT gene can also cause oxidative stress through hyperpolarisation of the mitochondria. This study explores the impact that MAPT mutation is having on phospholipid metabolism in iPSC-derived dopamine neurons, and to determine if these effects are exacerbated by mitochondrial and endoplasmic reticulum stress. Neurons that possessed a mutated copy of MAPT were shown to have significantly higher levels of oxo-phospholipids (Oxo-PL) than wild-type neurons. Oxidation of the hydrophobic fatty acid side chains changes the chemistry of the phospholipid leading to disruption of membrane function and potential cell lysis. In wild-type neurons, both mitochondrial and endoplasmic reticulum stress increased Oxo-PL abundance; however, in MAPT mutant neurons mitochondrial stress appeared to have a minimal effect. Endoplasmic reticulum stress, surprisingly, reduced the abundance of Oxo-PL in MAPT mutant dopamine neurons, and we postulate that this reduction could be modulated through hyperactivation of the unfolded protein response and X-box binding protein 1. Overall, the results of this study contribute to furthering our understanding of the regulation and impact of oxidative stress in Parkinson's disease pathology.

Medium-Chain Fatty Acids Rescue Motor Function and Neuromuscular Junction Degeneration in a Drosophila Model of Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease characterised by progressive degeneration of the motor neurones. An expanded GGGGCC (G4C2) hexanucleotide repeat in C9orf72 is the most common genetic cause of ALS and frontotemporal dementia (FTD); therefore, the resulting disease is known as C9ALS/FTD. Here, we employ a Drosophila melanogaster model of C9ALS/FTD (C9 model) to investigate a role for specific medium-chain fatty acids (MCFAs) in reversing pathogenic outcomes. Drosophila larvae overexpressing the ALS-associated dipeptide repeats (DPRs) in the nervous system exhibit reduced motor function and neuromuscular junction (NMJ) defects. We show that two MCFAs, nonanoic acid (NA) and 4-methyloctanoic acid (4-MOA), can ameliorate impaired motor function in C9 larvae and improve NMJ degeneration, although their mechanisms of action are not identical. NA modified postsynaptic glutamate receptor density, whereas 4-MOA restored defects in the presynaptic vesicular release. We also demonstrate the effects of NA and 4-MOA on metabolism in C9 larvae and implicate various metabolic pathways as dysregulated in our ALS model. Our findings pave the way to identifying novel therapeutic targets and potential treatments for ALS.

A comparative analyses of lipid ratios representing desaturase enzyme activity between preterm and term infants within the first ten weeks of life.

BACKGROUND: Desaturase enzymes play a key role in several pathways including biosynthesis of poly- and mono- unsaturated fatty acids (PUFAs, MUFA). In preterm infants, desaturase enzyme activity (DA) may be a rate-limiting step in maintaining PUFAs levels during this critical developmental window and impact on long term metabolic health. The study tested the hypothesis that DA is altered in preterm infants compared to term infants in early life and may be a marker of risk or contribute to later alterations in metabolic health. METHODS: Lipidomic analyses were conducted using blood samples from two established UK-based cohorts, involving very preterm (n = 105) and term (n = 259) infants. Blood samples were taken from term infants at birth, two and six weeks and from preterm infants when established on enteral feeds and at term corrected age. DA of the 2 groups of infants were estimated indirectly from product/precursor lipids ratios of phosphatidylcholine (PC) and triglycerides (TG) species and reported according to their postmenstrual and postnatal ages. RESULTS: There were changes in lipid ratios representing desaturase enzyme activity in preterm infants in the first weeks of life with higher delta 6 desaturases (D6D) triglyceride (TG) indices but significantly lower delta 9 desaturase (D9D) and D6D(PC) indices. In comparison to term infants, preterm have lower delta 5 desaturase (D5D) but higher D6D indices at all postnatal ages. Although point levels of desaturase indices were different, trajectories of changes in these indices over time were similar in preterm and term infants. CONCLUSIONS: This study findings suggest the patterns of desaturase indices in preterm infants differ from that of term infants but their trajectories of change in the first 10 weeks of life were similar. These differences of DA if they persist in later life could contribute to the mechanism of diseases in preterm adulthood and warrant further investigations.

Novel Metabolomic Approach for Identifying Pathology-Specific Biomarkers in Rare Diseases: A Case Study in Oculopharyngeal Muscular Dystrophy (OPMD).

The identification of metabolomic biomarkers relies on the analysis of large cohorts of patients compared to healthy controls followed by the validation of markers in an independent sample set. Indeed, circulating biomarkers should be causally linked to pathology to ensure that changes in the marker precede changes in the disease. However, this approach becomes unfeasible in rare diseases due to the paucity of samples, necessitating the development of new methods for biomarker identification. The present study describes a novel approach that combines samples from both mouse models and human patients to identify biomarkers of OPMD. We initially identified a pathology-specific metabolic fingerprint in murine dystrophic muscle. This metabolic fingerprint was then translated into (paired) murine serum samples and then to human plasma samples. This study identified a panel of nine candidate biomarkers that could predict muscle pathology with a sensitivity of 74.3% and specificity of 100% in a random forest model. These findings demonstrate that the proposed approach can identify biomarkers with good predictive performance and a higher degree of confidence in their relevance to pathology than markers identified in a small cohort of human samples alone. Therefore, this approach has a high potential utility for identifying circulating biomarkers in rare diseases.

Mitochondrial and Endoplasmic Reticulum Stress Trigger Triglyceride Accumulation in Models of Parkinson's Disease Independent of Mutations in MAPT.

The metabolic basis of Parkinson's disease pathology is poorly understood. However, the involvement of mitochondrial and endoplasmic reticulum stress in dopamine neurons in disease aetiology is well established. We looked at the effect of rotenone- and tunicamycin-induced mitochondrial and ER stress on the metabolism of wild type and microtubule-associated protein tau mutant dopamine neurons. Dopamine neurons derived from human isolated iPSCs were subjected to mitochondrial and ER stress using RT and TM, respectively. Comprehensive metabolite profiles were generated using a split phase extraction analysed by reversed phase lipidomics whilst the aqueous phase was measured using HILIC metabolomics. Mitochondrial and ER stress were both shown to cause significant dysregulation of metabolism with RT-induced stress producing a larger shift in the metabolic profile of both wild type and MAPT neurons. Detailed analysis showed that accumulation of triglycerides was a significant driver of metabolic dysregulation in response to both stresses in both genotypes. Whilst the consequence is similar, the mechanisms by which triglyceride accumulation occurs in dopamine neurons in response to mitochondrial and ER stress are very different. Thus, improving our understanding of how these mechanisms drive the observed triglyceride accumulation can potentially open up new therapeutic avenues.

Lipid profiling analyses from mouse models and human infants.

This protocol outlines a translational lipidomic approach to discover lipid biomarkers that could predict morphometric body and histological organ measurements (e.g., weight and adiposity gains) during specific stages of life (e.g., early life). We describe procedures ranging from animal experimentation and histological analyses to downstream analytical steps through lipid profiling, both in mice and humans. This protocol represents a reliable and versatile approach to translate and validate candidate lipid biomarkers from animal models to a human cohort. For complete details on the use and execution of this protocol, please refer to Olga et al. (2021).

Distinct infant feeding type-specific plasma metabolites at age 3 months associate with body composition at 2 years.

BACKGROUND & OBJECTIVES: Early life is a critical window for adiposity programming and metabolic profile may affect this programming. We investigated if plasma metabolites at age 3 months were associated with fat mass, fat free mass and abdominal subcutaneous and visceral fat outcomes at age 2 years in a cohort of healthy infants and if these associations were different between infants receiving exclusive breastfeeding (EBF) and those with exclusive formula feeding (EFF). METHODS: In 318 healthy term-born infants, we determined body composition by Dual Energy X-ray absorptiometry (DXA) and visceral fat by abdominal ultrasound at 2 age years. High-throughput metabolic profiling was performed on blood samples collected at age 3 months. Tertiles were generated for each body composition outcome and differences in plasma metabolite levels at age 3 months between infants with high and low body composition outcomes at age 2 years were evaluated in general, as well as separately in EBF- and EFF-infants. RESULTS: Distinct plasma metabolite variables identified at age 3 months were associated with body composition at 2 years. These metabolites included several classes of lyso-phospholipids. Associations between the metabolites at age 3 months and fat mass index, fat mass percentage, fat free mass index and visceral fat at 2 years were predominantly found in EBF-infants. CONCLUSION: Associations between plasma metabolite levels at age 3 months and high body fat mass at 2 years depend on infant feeding type. These findings contribute to our insight into the importance of infant feeding on adiposity programming in early life.

Variants in mitochondrial amidoxime reducing component 1 and hydroxysteroid 17-beta dehydrogenase 13 reduce severity of nonalcoholic fatty liver disease in children and suppress fibrotic pathways through distinct mechanisms.

Genome-wide association studies in adults have identified variants in hydroxysteroid 17-beta dehydrogenase 13 (HSD17B13) and mitochondrial amidoxime reducing component 1 (MTARC1) as protective against nonalcoholic fatty liver disease (NAFLD). We aimed to test their association with pediatric NAFLD liver histology and investigate their function using metabolomics. A total of 1450 children (729 with NAFLD, 399 with liver histology) were genotyped for rs72613567T>TA in HSD17B13, rs2642438G>A in MTARC1, and rs738409C>G in patatin-like phospholipase domain-containing protein 3 (PNPLA3). Genotype-histology associations were tested using ordinal regression. Untargeted hepatic proteomics and plasma lipidomics were performed in a subset of children. We found rs72613567T>TA in HSD17B13 to be associated with lower odds of NAFLD diagnosis (odds ratio, 0.7; 95% confidence interval, 0.6-0.9) and a lower grade of portal inflammation (p < 0.001). rs2642438G>A in MTARC1 was associated with a lower grade of hepatic steatosis (p = 0.02). Proteomics found reduced expression of HSD17B13 in carriers of the protective -TA allele. MTARC1 levels were unaffected by genotype. Both variants were associated with down-regulation of fibrogenic pathways. HSD17B13 perturbs plasma phosphatidylcholines and triglycerides. In silico modeling suggested p.Ala165Thr disrupts the stability and metal binding of MTARC1. Conclusion: Both HSD17B13 and MTARC1 variants are associated with less severe pediatric NAFLD. These results provide further evidence for shared genetic mechanisms between pediatric and adult NAFLD.

Comparison of the Lipidomic Signature of Fatty Liver in Children and Adults: A Cross-Sectional Study.

OBJECTIVE: Non-alcoholic fatty liver disease (NAFLD) is an increasingly common condition in children characterised by insulin resistance and altered lipid metabolism. Affected patients are at increased risk of cardiovascular disease (CVD) and children with NAFLD are likely to be at risk of premature cardiac events. Evaluation of the plasma lipid profile of children with NAFLD offers the opportunity to investigate these perturbations and understand how closely they mimic the changes seen in adults with cardiometabolic disease. METHODS: We performed untargeted liquid chromatography-mass spectrometry (LC-MS) plasma lipidomics on 287 children: 19 lean controls, 146 from an obese cohort, and 122 NAFLD cases who had undergone liver biopsy. Associations between lipid species and liver histology were assessed using regression adjusted for age and sex. Results were then replicated using data from 9500 adults with metabolic phenotyping. RESULTS: More severe paediatric NAFLD was associated with lower levels of long chain, polyunsaturated phosphatidylcholines (pC) and triglycerides (TG). Similar trends in pC and TG chain length and saturation were seen in adults with hepatic steatosis; however, many of the specific lipids associated with NAFLD differed between children and adults. Five lipids replicated in adults (including PC(36:4)) have been directly linked to death and cardiometabolic disease, as well as indirectly via genetic variants. CONCLUSION: These findings suggest that, whilst similar pathways of lipid metabolism are perturbed in paediatric NAFLD as in cardiometabolic disease in adults, the specific lipid signature in children is different.

Paternal nutritional programming of lipid metabolism is propagated through sperm and seminal plasma.

BACKGROUND: The paternal diet affects lipid metabolism in offspring for at least two generations through nutritional programming. However, we do not know how this is propagated to the offspring. OBJECTIVES: We tested the hypothesis that the changes in lipid metabolism that are driven by paternal diet are propagated through spermatozoa and not seminal plasma. METHODS: We applied an updated, purpose-built computational network analysis tool to characterise control of lipid metabolism systemically (Lipid Traffic Analysis v2.3) on a known mouse model of paternal nutritional programming. RESULTS: The analysis showed that the two possible routes for programming effects, the sperm (genes) and seminal plasma (influence on the uterine environment), both have a distinct effect on the offspring's lipid metabolism. Further, the programming effects in offspring suggest that changes in lipid distribution are more important than alterations in lipid biosynthesis. CONCLUSIONS: These results show how the uterine environment and genes both affect lipid metabolism in offspring, enhancing our understanding of the link between parental diet and metabolism in offspring.

Dietary PUFAs drive diverse system-level changes in lipid metabolism.

OBJECTIVE: Polyunsaturated fatty acid (PUFA) supplements have been trialled as a treatment for a number of conditions and produced a variety of results. This variety is ascribed to the supplements, that often comprise a mixture of fatty acids, and to different effects in different organs. In this study, we tested the hypothesis that the supplementation of individual PUFAs has system-level effects that are dependent on the molecular structure of the PUFA. METHODS: We undertook a network analysis using Lipid Traffic Analysis to identify both local and system-level changes in lipid metabolism using publicly available lipidomics data from a mouse model of supplementation with FA(20:4n-6), FA(20:5n-3), and FA(22:6n-3); arachidonic acid, eicosapentaenoic acid, and docosahexaenoic acid, respectively. Lipid Traffic Analysis is a new computational/bioinformatics tool that uses the spatial distribution of lipids to pinpoint changes or differences in control of metabolism, thereby suggesting mechanistic reasons for differences in observed lipid metabolism. RESULTS: There was strong evidence for changes to lipid metabolism driven by and dependent on the structure of the supplemented PUFA. Phosphatidylcholine and triglycerides showed a change in the variety more than the total number of variables, whereas phosphatidylethanolamine and phosphatidylinositol showed considerable change in both which variables and the number of them, in a highly PUFA-dependent manner. There was also evidence for changes to the endogenous biosynthesis of fatty acids and to both the elongation and desaturation of fatty acids. CONCLUSIONS: These results show that the full biological impact of PUFA supplementation is far wider than any single-organ effect and implies that supplementation and dosing with PUFAs require a system-level assessment.

Metabolomics in early life and the association with body composition at age 2 years.

BACKGROUND AND OBJECTIVES: Early life is a critical window for adiposity programming. Metabolic-profile in early life may reflect this programming and correlate with later life adiposity. We investigated if metabolic-profile at 3 months of age is predictive for body composition at 2 years and if there are differences between boys and girls and between infant feeding types. METHODS: In 318 healthy term-born infants, we determined body composition with skinfold measurements and abdominal ultrasound at 3 months and 2 years of age. High-throughput-metabolic-profiling was performed on 3-month-blood-samples. Using random-forest-machine-learning-models, we studied if the metabolic-profile at 3 months can predict body composition outcomes at 2 years of age. RESULTS: Plasma metabolite-profile at 3 months was found to predict body composition at 2 years, based on truncal: peripheral-fat-skinfold-ratio (T:P-ratio), with a predictive value of 75.8%, sensitivity of 100% and specificity of 50%. Predictive value was higher in boys (Q2  = 0.322) than girls (Q2  = 0.117). Of the 15 metabolite variables most strongly associated with T:P-ratio, 11 were also associated with visceral fat at 2 years of age. CONCLUSION: Several plasma metabolites (LysoPC(22:2), dimethylarginine and others) at 3 months associate with body composition outcome at 2 years. These results highlight the importance of the first months of life for adiposity programming.

Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort.

BACKGROUND: physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives. METHODS: We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD. RESULTS: In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046). CONCLUSIONS: metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.

Metabolic phenotyping reveals a reduction in the bioavailability of serotonin and kynurenine pathway metabolites in both the urine and serum of individuals living with Alzheimer's disease.

BACKGROUND: Both serotonergic signalling disruption and systemic inflammation have been associated with the pathogenesis of Alzheimer's disease (AD). The common denominator linking the two is the catabolism of the essential amino acid, tryptophan. Metabolism via tryptophan hydroxylase results in serotonin synthesis, whilst metabolism via indoleamine 2,3-dioxygenase (IDO) results in kynurenine and its downstream derivatives. IDO is reported to be activated in times of host systemic inflammation and therefore is thought to influence both pathways. To investigate metabolic alterations in AD, a large-scale metabolic phenotyping study was conducted on both urine and serum samples collected from a multi-centre clinical cohort, consisting of individuals clinically diagnosed with AD, mild cognitive impairment (MCI) and age-matched controls. METHODS: Metabolic phenotyping was applied to both urine (n = 560) and serum (n = 354) from the European-wide AddNeuroMed/Dementia Case Register (DCR) biobank repositories. Metabolite data were subsequently interrogated for inter-group differences; influence of gender and age; comparisons between two subgroups of MCI - versus those who remained cognitively stable at follow-up visits (sMCI); and those who underwent further cognitive decline (cMCI); and the impact of selective serotonin reuptake inhibitor (SSRI) medication on metabolite concentrations. RESULTS: Results revealed significantly lower metabolite concentrations of tryptophan pathway metabolites in the AD group: serotonin (urine, serum), 5-hydroxyindoleacetic acid (urine), kynurenine (serum), kynurenic acid (urine), tryptophan (urine, serum), xanthurenic acid (urine, serum), and kynurenine/tryptophan ratio (urine). For each listed metabolite, a decreasing trend in concentrations was observed in-line with clinical diagnosis: control > MCI > AD. There were no significant differences in the two MCI subgroups whilst SSRI medication status influenced observations in serum, but not urine. CONCLUSIONS: Urine and serum serotonin concentrations were found to be significantly lower in AD compared with controls, suggesting the bioavailability of the neurotransmitter may be altered in the disease. A significant increase in the kynurenine/tryptophan ratio suggests that this may be a result of a shift to the kynurenine metabolic route due to increased IDO activity, potentially as a result of systemic inflammation. Modulation of the pathways could help improve serotonin bioavailability and signalling in AD patients.

Urinary metabolic phenotyping for Alzheimer's disease.

Finding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer's Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer's Disease and Mild Cognitive Impairment. Feature reduction was performed using metabolomic Quantitative Trait Loci, resulting in the list of metabolites associated with the genetic variants. This approach helps accuracy in identification of disease states and provides a route to a plausible mechanistic link to pathological processes. Using these mQTLs we built a Random Forests model, which not only correctly discriminates between people with Alzheimer's Disease and age-matched controls, but also between individuals with Mild Cognitive Impairment who were later diagnosed with Alzheimer's Disease and those who were not. Further annotation of top-ranking metabolic features nominated by the trained model revealed the involvement of cholesterol-derived metabolites and small-molecules that were linked to Alzheimer's pathology in previous studies.

Development and Application of High-Throughput Single Cell Lipid Profiling: A Study of SNCA-A53T Human Dopamine Neurons.

Advances in single cell genomics and transcriptomics have shown that at tissue level there is complex cellular heterogeneity. To understand the effect of this inter-cell heterogeneity on metabolism it is essential to develop a single cell lipid profiling approach that allows the measurement of lipids in large numbers of single cells from a population. This will provide a functional readout of cell activity and membrane structure. Using liquid extraction surface analysis coupled with high-resolution mass spectrometry we have developed a high-throughput method for untargeted single cell lipid profiling. This technological advance highlighted the importance of cellular heterogeneity in the functional metabolism of individual human dopamine neurons, suggesting that A53T alpha-synuclein (SNCA) mutant neurons have impaired membrane function. These results demonstrate that this single cell lipid profiling platform can provide robust data that will expand the frontiers in biomedical research.

Combining lipidomics and machine learning to measure clinical lipids in dried blood spots.

INTRODUCTION: Blood-based sample collection is a challenge, and dried blood spots (DBS) represent an attractive alternative. However, for DBSs to be an alternative to venous blood it is important that these samples are able to deliver comparable associations with clinical outcomes. To explore this we looked to see if lipid profile data could be used to predict the concentration of triglyceride, HDL, LDL and total cholesterol in DBSs using markers identified in plasma. OBJECTIVES: To determine if DBSs can be used as an alternative to venous blood in both research and clinical settings, and to determine if machine learning could predict 'clinical lipid' concentration from lipid profile data. METHODS: Lipid profiles were generated from plasma (n = 777) and DBS (n = 835) samples. Random forest was applied to identify and validate panels of lipid markers in plasma, which were translated into the DBS cohort to provide robust measures of the four 'clinical lipids'. RESULTS: In plasma samples panels of lipid markers were identified that could predict the concentration of the 'clinical lipids' with correlations between estimated and measured triglyceride, HDL, LDL and total cholesterol of 0.920, 0.743, 0.580 and 0.424 respectively. When translated into DBS samples, correlations of 0.836, 0.591, 0.561 and 0.569 were achieved for triglyceride, HDL, LDL and total cholesterol. CONCLUSION: DBSs represent an alternative to venous blood, however further work is required to improve the combined lipidomics and machine learning approach to develop it for use in health monitoring.

An update on blood-based biomarkers for non-Alzheimer neurodegenerative disorders.

Cerebrospinal fluid analyses and neuroimaging can identify the underlying pathophysiology at the earliest stage of some neurodegenerative disorders, but do not have the scalability needed for population screening. Therefore, a blood-based marker for such pathophysiology would have greater utility in a primary care setting and in eligibility screening for clinical trials. Rapid advances in ultra-sensitive assays have enabled the levels of pathological proteins to be measured in blood samples, but research has been predominantly focused on Alzheimer disease (AD). Nonetheless, proteins that were identified as potential blood-based biomarkers for AD, for example, amyloid-ß, tau, phosphorylated tau and neurofilament light chain, are likely to be relevant to other neurodegenerative disorders that involve similar pathological processes and could also be useful for the differential diagnosis of clinical symptoms. This Review outlines the neuropathological, clinical, molecular imaging and cerebrospinal fluid features of the most common neurodegenerative disorders outside the AD continuum and gives an overview of the current status of blood-based biomarkers for these disorders.

Evidence from 3-month-old infants shows that a combination of postnatal feeding and exposures in utero shape lipid metabolism.

We tested the hypothesis that both postnatal feeding and conditions in utero affect lipid metabolism in infants. Infants who experienced restrictive growth conditions in utero and others exposed to maternal hyperglycaemia were compared to a control group with respect to feeding mode. Dried blood spots were collected from a pilot subset of infant participants of the Cambridge Baby Growth Study at 3mo. Groups: (a) a normal gestation (control, n = 40), (b) small for gestational age (SGA, n = 34) and (c) whose mothers developed hyperglycaemia (n = 59). These groups were further stratified by feeding mode; breastfed, formula-fed or received a mixed intake. Their phospholipid, glyceride and sterol fractions were profiled using direct infusion mass spectrometry. Statistical tests were used to identify molecular species that indicated differences in lipid metabolism. The abundance of several phospholipids identified by multivariate analysis, PC(34:1), PC(34:2) and PC-O(34:1), was 30-100% higher across all experimental groups. SM(39:1) was around half as abundant in in utero groups among breastfed infants only. The evidence from this pilot study shows that phospholipid metabolism is modulated by both conditions in utero and postnatal feeding in a cohort of 133 Caucasian infants, three months post partum.

Relationship between the lipid composition of maternal plasma and infant plasma through breast milk.

INTRODUCTION: This study was motivated by the report that infant development correlates with particular lipids in infant plasma. OBJECTIVE: The hypothesis was that the abundance of these candidate biomarkers is influenced by the dietary intake of the infant. METHODS: A cohort of 30 exclusively-breastfeeding mother-infant pairs from a small region of West Africa was used for this observational study. Plasma and milk from the mother and plasma from her infant were collected within 24 h, 3 months post partum. The lipid, sterol and glyceride composition was surveyed using direct infusion MS in positive and negative ion modes. Analysis employed a combination of univariate and multivariate tests. RESULTS: The lipid profiles of mother and infant plasma samples are similar but distinguishable, and both are distinct from milk. Phosphatidylcholines (PC), cholesteryl esters (CEs) and cholesterol were more abundant in mothers with respect to their infants, e.g. PC(34:1) was 5.66% in mothers but 3.61% in infants (p = 3.60 × 10-10), CE(18:2) was 8.05% in mothers but 5.18% in infants (p = 1.37 × 10-11) whilst TGs were lower in mothers with respect to their infants, e.g. TG(52:2) was 2.74% in mothers and 4.23% in infants (p = 1.63 × 10-05). A latent structure model showed that four lipids in infant plasma previously shown to be biomarkers clustered with cholesteryl esters in the maternal circulation. CONCLUSION: This study found evidence that the abundance of individual lipid isoforms associated with infant development are associated with the abundance of individual molecular species in the mother's circulation.