Effect of metformin on plasma metabolite profile in the Copenhagen Insulin and Metformin Therapy (CIMT) trial.

AIM: Metformin is the first-line treatment for Type 2 diabetes. However, not all people benefit from this drug. Our aim was to investigate the effects of metformin on the plasma metabolome and whether the pretreatment metabolite profile can predict HbA1c outcome. METHODS: Post hoc analysis of the Copenhagen Insulin and Metformin Therapy (CIMT) trial, a multicentre study from May 2008 to December 2012, was carried out. We used a non-target method to analyse 87 plasma metabolites in participants with Type 2 diabetes (n = 370) who were randomized in a 1 : 1 ratio to 18 months of metformin or placebo treatment. Metabolites were measured by liquid chromatography-mass spectrometry at baseline and at 18-month follow-up and the data were analysed using a linear mixed-effect model. RESULTS: At baseline, participants who were on metformin before the trial (n = 312) had higher levels of leucine/isoleucine and five lysophosphatidylethanolamines (LPEs), and lower levels of carnitine and valine compared with metformin-naïve participants (n = 58). At follow-up, participants randomized to metformin (n = 188) had elevated levels of leucine/isoleucine and reduced carnitine, tyrosine and valine compared with placebo (n = 182). At baseline, participants on metformin treatment with the highest levels of carnitine C10:1 and leucine/isoleucine had the lowest HbA1c (P-interaction = 0.02 and 0.03, respectively). This association was not significant with HbA1c at follow-up. CONCLUSIONS: Metformin treatment is associated with decreased levels of valine, tyrosine and carnitine, and increased levels of leucine/isoleucine. None of the identified metabolites can predict the HbA1c -lowering effect of metformin. Further studies of the association between metformin, carnitine and leucine/isoleucine are warranted.

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.

Serum metabolite profile associates with the development of metabolic co-morbidities in first-episode psychosis.

Psychotic patients are at high risk for developing obesity, metabolic syndrome and type 2 diabetes. These metabolic co-morbidities are hypothesized to be related to both treatment side effects as well as to metabolic changes occurring during the psychosis. Earlier metabolomics studies have shown that blood metabolite levels are predictive of insulin resistance and type 2 diabetes in the general population as well as sensitive to the effects of antipsychotics. In this study, we aimed to identify the metabolite profiles predicting future weight gain and other metabolic abnormalities in psychotic patients. We applied comprehensive metabolomics to investigate serum metabolite profiles in a prospective study setting in 36 first-episode psychosis patients during the first year of the antipsychotic treatment and 19 controls. While corroborating several earlier findings when comparing cases and controls and the effects of the antipsychotic medication, we also found that prospective weight gain in psychotic patients was associated with increased levels of triacylglycerols with low carbon number and double-bond count at baseline, that is, lipids known to be associated with increased liver fat. Our study suggests that metabolite profiles may be used to identify the psychotic patients most vulnerable to develop metabolic co-morbidities, and may point to a pharmacological approach to counteract the antipsychotic-induced weight gain.