Family history of diabetes impacts on interactions between minimal model estimates of insulin sensitivity and glucose effectiveness.

AIMS/HYPOTHESIS: Insulin resistance and glucose effectiveness (S(G)) are major determinants of glucose tolerance and independently predict the development of type 2 diabetes in individuals with a family history of disease. We examined the inter-relationship between insulin sensitivity (S(I)) and S(G) in offspring of two parents with type 2 diabetes and in individuals with no family history of diabetes. METHODS: Fifty non-diabetic individuals, including 26 offspring of two type 2 diabetic parents (family history, FH+) and 24 with no family history of diabetes (FH-) similar in gender, age, ethnicity and body mass index (BMI) were studied. Each subject underwent a 100-g oral glucose tolerance test (OGTT) and insulin modified frequently sampled intravenous glucose tolerance, analysed using the Bergman's minimal model (MINMOD). RESULTS: Thirteen subjects of the FH+ group and nine of the FH- group had impaired glucose tolerance (IGT). S(I) and S(G) were independent variables in the FH+ group, while they correlated highly with each other in the FH- group (r = 0.69, p = 0.0002). The relationship between S(I) and S(G) persisted when analysing the IGT and normal glucose tolerance subgroups separately, demonstrating that these associations were not because of differences in glycaemia. Consistently, S(G) strongly correlated with additional measures of insulin resistance only in the FH- group, including fasting insulin (r = 0.56, p = 0.004), homeostasis model assessment of insulin resistance (r = 0.57 p = 0.003) and BMI (r = 0.66, p = 0.0004). CONCLUSIONS: These results demonstrate that familial factors impart important physiological differences in the inter-relationship between insulin-dependent and insulin-independent glucose disposal, which may be important in modulating risk for development of disease.

Alternatively Spliced Genes as Biomarkers for Schizophrenia, Bipolar Disorder and Psychosis: A Blood-Based Spliceome-Profiling Exploratory Study.

OBJECTIVE: Transcriptomic biomarkers of psychiatric diseases obtained from a query of peripheral tissues that are clinically accessible (e.g., blood cells instead of post-mortem brain tissue) have substantial practical appeal to discern the molecular subtypes of common complex diseases such as major psychosis. To this end, spliceome-profiling is a new methodological approach that has considerable conceptual relevance for discovery and clinical translation of novel biomarkers for psychiatric illnesses. Advances in microarray technology now allow for improved sensitivity in measuring the transcriptome while simultaneously querying the "exome" (all exons) and "spliceome" (all alternatively spliced variants). The present study aimed to evaluate the feasibility of spliceome-profiling to discern transcriptomic biomarkers of psychosis. METHODS: We measured exome and spliceome expression in peripheral blood mononuclear cells from 13 schizophrenia patients, nine bipolar disorder patients, and eight healthy control subjects. Each diagnostic group was compared to each other, and the combined group of bipolar disorder and schizophrenia patients was also compared to the control group. Furthermore, we compared subjects with a history of psychosis to subjects without such history. RESULTS: After applying Bonferroni corrections for the 21,866 full-length gene transcripts analyzed, we found significant interactions between diagnostic group and exon identity, consistent with group differences in rates or types of alternative splicing. Relative to the control group, 18 genes in the bipolar disorder group, eight genes in the schizophrenia group, and 15 genes in the combined bipolar disorder and schizophrenia group appeared differentially spliced. Importantly, thirty-three genes showed differential splicing patterns between the bipolar disorder and schizophrenia groups. More frequent exon inclusion and/or over-expression was observed in psychosis. Finally, these observations are reconciled with an analysis of the ontologies, the pathways and the protein domains significantly over-represented among the alternatively spliced genes, several of which support prior discoveries. CONCLUSIONS: To our knowledge, this is the first blood-based spliceome-profiling study of schizophrenia and bipolar disorder to be reported. The battery of alternatively spliced genes and exons identified in this discovery-oriented exploratory study, if replicated, may have potential utility to discern the molecular subtypes of psychosis. Spliceome-profiling, as a new methodological approach in transcriptomics, warrants further work to evaluate its utility in personalized medicine. Potentially, this approach could also permit the future development of tissue-sampling methodologies in a form that is more acceptable to patients and thereby allow monitoring of dynamic and time-dependent plasticity in disease severity and response to therapeutic interventions in clinical psychiatry.