Time window-dependent effect of perinatal maternal protein restriction on insulin sensitivity and energy substrate oxidation in adult male offspring

Epidemiological and experimental evidence suggests that a suboptimal environment during perinatal life programs offspring susceptibility to the development of metabolic syndrome and Type 2 diabetes. We hypothesized that the lasting impact of perinatal protein deprivation on mitochondrial fuel oxidation and insulin sensitivity would depend on the time window of exposure. To improve our understanding of underlying mechanisms, an integrative approach was used, combining the assessment of insulin sensitivity and untargeted mass spectrometry-based metabolomics in the offspring. A hyperinsulinemic-euglycemic clamp was performed in adult male rats born from dams fed a low-protein diet during gestation and/or lactation, and subsequently exposed to a Western diet (WD) for 10 wk. Metabolomics was combined with targeted acylcarnitine profiling and analysis of liver gene expression to identify markers of adaptation to WD that influence the phenotype outcome evaluated by body composition analysis. At adulthood, offspring of protein-restricted dams had impaired insulin secretion when fed a standard diet. Moreover, rats who demonstrated catch-up growth at weaning displayed higher gluconeogenesis and branched-chain amino acid catabolism, and lower fatty acid β-oxidation compared with control rats. Postweaning exposure of intrauterine growth restriction-born rats to a WD exacerbated incomplete fatty acid β-oxidation and excess fat deposition. Control offspring nursed by protein-restricted mothers showed peculiar low-fat accretion through adulthood and preserved insulin sensitivity even after WD-exposure. Altogether, our findings suggest a testable hypothesis about how maternal diet might influence metabolic outcomes (insulin sensitivity) in the next generation such as mitochondrial overload and/or substrate oxidation inflexibility dependent on the time window of perinatal dietary manipulation

Three-way clustering around latent variables approach with constraints on the configurations to facilitate interpretation

The set-up of comprehensive studies in life sciences involving a longitudinal dimension-as appears in time-scale metabolomics-calls for the use of dimension reduction techniques for three-way data structures (e.g., samples by variables by time points). For this purpose, a clustering around latent variables for three-way data approach, CLV3W, has been proposed. CLV3W aims at both partitioning the variables into nonoverlapping clusters and estimating within each cluster a rank-one Parafac model consisting of a latent component (resp. a weighting system) associated with the first mode (resp. third mode) and a vector of loadings reflecting the degree of closeness of each variable of the second mode to its cluster. In this paper, two constrained CLV3W models are discussed. First, a nonnegativity constraint is defined implying that clusters are composed of positively correlated variables. Second, it is proposed to constrain the weighting system to be the same for all clusters. These two constraints aim at providing more parsimonious models with configurations that are easier to interpret. The appropriateness of both constraints is evaluated in a simulation study and illustrated on two case studies pertaining to sensory evaluation and metabolomics data. Regarding the first case study, CLV3W yields the identification of two consumer segments together with one common emotional pleasantness dimension associated with coffee aromas. CLV3W analysis of human preterm breast milk metabolomics data provided three clusters of lipid species that are responsible for specific functions (i.e., milk fat globules membrane-constituents, fatty acid oxidation-products, lipid mediators as eicosanoids and endocannabinoids).</p