The Mediterranean diet (MD) is a dietary pattern well-known for its benefits in disease prevention. Monitoring adherence to the MD could be improved by discovery of novel dietary biomarkers. The MEDiterranean Diet in Northern Ireland (MEDDINI) intervention study monitored the adherence of participants to the MD for up to 12 months. This investigation aimed to profile plasma metabolites, correlating each against the MD score of participants (n = 58). Based on an established 14-point scale MD score, subjects were classified into two groups (“low” and “high”). 1H-Nuclear Magnetic Resonance (1H-NMR) metabolomic analysis found that citric acid was the most significant metabolite (p = 5.99 × 10−4*; q = 0.03), differing between ‘low’ and ‘high’. Furthermore, five additional metabolites significantly differed (p < 0.05; q < 0.35) between the two groups. Discriminatory metabolites included: citric acid, pyruvic acid, betaine, mannose, acetic acid and myo-inositol. Additionally, the top five most influential metabolites in multivariate models were also citric acid, pyruvic acid, betaine, mannose and myo-inositol. Metabolites significantly correlated with the consumption of certain food types. For example, citric acid positively correlated fruit, fruit juice and vegetable constituents of the diet, and negatively correlated with sweet foods alone or when combined with carbonated drinks. Citric acid was the best performing biomarker and this was enhanced by paired ratio with pyruvic acid. The present study demonstrates the utility of metabolomic profiling for effectively assessing adherence to MD and the discovery of novel dietary biomarkers.

Huntington's disease (HD) is a devastating, progressive neurodegenerative disease with a distinct phenotype characterized by chorea and dystonia, incoordination, cognitive decline and behavioral difficulties. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Herein DI/LC-MS/MS was used to accurately identify and quantify 185 metabolites in post mortem frontal lobe and striatum from HD patients and healthy control cases. The findings link changes in energy metabolism and phospholipid metabolism to HD pathology and also demonstrate significant reductions in neurotransmitters. Further investigation into the oxidation of fatty acids and phospholipid metabolism in pre-clinical models of HD are clearly warranted for the identification of potential therapies. Additionally, panels of 5 metabolite biomarkers were identified in both the frontal lobe (AUC = 0.962 (95% CI: 0.85-1.00) and striatum (AUC = 0.988 (95% CI: 0.899-1.00). This could have clinical utility in more accessible biomatrices such as blood serum for the early detection of those entering the prodromal phase of the disease, when treatment is believed to be most effective. Further evaluation of these biomarker panels in human cohorts is justified to determine their clinical efficacy.

AbstractThe MEDDINI intervention study investigated how advice improved the adoption of a Mediterranean diet (MD) in cardiovascular disease patients. Earlier research profiled the levels of blood metabolites in MEDDINI participants, in the process discovering a number dietary biomarkers indicative of a MD. However, a potential limitation of this approach is that MD scores are semi-quantitative, and don't reflect the absolute amounts of food consumed. Therefore, the present study identified distinct dietary patterns based on quantified food diary data from 58 MEDDINI participants by applying k-means clustering analysis. Previously measured blood metabolites (90) using targeted and untargeted methods were then assessed for their performance as dietary biomarkers. After careful standardisation (z-scores), optimisation and cross-validation dietary data were reduced to 6 specific food groups and this led to the formation of two clusters. Cluster 1 included participants who had the lowest intakes of fruit and vegetables, legumes, fish and whole grain cereals and the highest intake of meat and sweet foods (including carbonated drinks). Cluster 2 comprised the participants with highest intake of fruit and vegetables, legumes, fish and whole grain cereals and the lowest intake of meat and sweet foods (including carbonated drinks). Discriminatory metabolites (p derived from untargeted analysis included Citric acid, Tyrosine, Malonate, Pyroglutamic acid, Succinate, Betaine, L-asparagine and Fumaric acid which were significantly increased in cluster 2, and 2-Hydroxybutyric acid and Pyruvic acid which were significantly decreased in cluster 2. Targeted biomarker analysis showed 8 discriminatory metabolites which were significantly (p increased in cluster 2. These were Docosahexaenoic acid (DHA), alpha-Carotene, beta-Carotene, beta-Cryptoxanthin, Vitamin C, Lutein, alpha-Linolenic acid and Lycopene. Conversely Osbond acid, Cholesterol and Dihomo-γ-linolenic acid (DGLA) were significantly lower in cluster 2. Metabolites significantly correlated with some of the 6 groups in the clusters. For example, Citric acid, Betaine and Vitamin C positively correlated with combined fruit, fruit juice and vegetable intake: (r = 0.20, p = 0.018; r = 0.20, p = 0.02 and r = 0.34, p = 5.7E-5 respectively). DHA, alpha-Carotenoid and beta-Carotenoid significantly correlated with fish intake (r = 0.58, p = 1.94E-13; r = 0.40, p = 2E-6 and r = 0.30, p = 3.5E-4 respectively). The present study demonstrates the utility of clustering analysis for effectively assessing adherence to healthy dietary patterns and the discovery of novel dietary biomarkers.

Introduction Insomnia is one of the most prevalent health concerns in the general population. Cognitive behavioural therapy (CBT) and pharmacological interventions are recommended for the treatment of insomnia. However, CBT can be expensive and difficult to access, while the use of pharmacotherapy can be limited by reports of adverse events. Due to these limitations, there is a strong need for alternative measures to manage insomnia. Preliminary research indicates the potential that electrical vestibular nerve stimulation (VeNS) has as a non-invasive method for managing insomnia. The aim of this study is to evaluate the efficacy of VeNS as a method of managing sleep quantity and quality in individuals with insomnia, as compared to a sham control. Methods The study was a two-armed, double-blind randomized controlled trial that was conducted across two research sites in the United Kingdom (UK) and Hong Kong (HK). Participants aged over 18 years with an Insomnia Severity Index (ISI) score of 15 or higher were randomly assigned to intervention and control groups. The intervention group was instructed to use the VeNS device at home for 30 minutes daily for 4 weeks, while the control group was instructed to use the sham device for the same period. ISI values were captured at baseline, at 2 weeks and at 4 weeks. Sleep quality and quality of life (QoL) were assessed at baseline and at 4 weeks using the Pittsburgh Sleep Quality Index (PSQI) and the 36-item Short Form Health Survey (SF-36), respectively. Results A total of 146 participants were recruited from the HK (n=94) and UK (n=52) research sites. The study has recently been completed with the statistical analysis ongoing. The between-group change in ISI values (primary outcome), sleep quality and QoL from baseline to week 4 will be examined. Conclusion The results of this study will help determine whether the relatively inexpensive, and non-invasive technique of VeNS is effective in the management of insomnia. The data collected will be used to support regulatory submissions, primarily to the US Food and Drug Administration. Support (if any)

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