Identifying Good Responders to Glucose Lowering Therapy in Type 2 Diabetes: Implications for Stratified Medicine

Aims

Defining responders to glucose lowering therapy can be important for both clinical care and for the development of a stratified approach to diabetes management. Response is commonly defined by either HbA1c change after treatment or whether a target HbA1c is achieved. We aimed to determine the extent to which the individuals identified as responders and non-responders to glucose lowering therapy, and their characteristics, depend on the response definition chosen.

Methods

We prospectively studied 230 participants commencing GLP-1 agonist therapy. We assessed participant characteristics at baseline and repeated HbA1c after 3 months treatment. We defined responders (best quartile of response) based on HbA1c change or HbA1c achieved. We assessed the extent to which these methods identified the same individuals and how this affected the baseline characteristics associated with treatment response.

Results

Different definitions of response identified different participants. Only 39% of responders by one definition were also good responders by the other. Characteristics associated with good response depend on the response definition chosen: good response by HbA1c achieved was associated with low baseline HbA1c (p<0.001), high C-peptide (p<0.001) and shorter diabetes duration (p = 0.01) whereas response defined by HbA1c change was associated with high HbA1c (p<0.001) only. We describe a simple novel method of defining treatment response based on a combination of HbA1c change and HbA1c achieved that defines response groups with similar baseline glycaemia.

Conclusions

The outcome of studies aiming to identify predictors of treatment response to glucose lowering therapy may depend on how response is defined. Alternative definitions of response should be considered which minimise influence of baseline glycaemia.     

The role of inflammatory pathway genetic variation on maternal metabolic phenotypes during pregnancy

Background

Since mediators of inflammation are associated with insulin resistance, and the risk of developing diabetes mellitus and gestational diabetes, we hypothesized that genetic variation in members of the inflammatory gene pathway impact glucose levels and related phenotypes in pregnancy. We evaluated this hypothesis by testing for association between genetic variants in 31 inflammatory pathway genes in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) cohort, a large multiethnic multicenter study designed to address the impact of glycemia less than overt diabetes on pregnancy outcome.

Results

Fasting, 1-hour, and 2-hour glucose, fasting and 1-hour C-peptide, and HbA1c levels were measured in blood samples obtained from HAPO participants during an oral glucose tolerance test at 24-32 weeks gestation. We tested for association between 458 SNPs mapping to 31 genes in the inflammatory pathway and metabolic phenotypes in 3836 European ancestry and 1713 Thai pregnant women. The strongest evidence for association was observed with TNF alpha and HbA1c (rs1052248; 0.04% increase per allele C; p-value = 4.4×10⁻⁵), RETN and fasting plasma glucose (rs1423096; 0.7 mg/dl decrease per allele A; p-value = 1.1×10⁻⁴), IL8 and 1 hr plasma glucose (rs2886920; 2.6 mg/dl decrease per allele T; p-value = 1.3×10⁻⁴), ADIPOR2 and fasting C-peptide (rs2041139; 0.55 ug/L decrease per allele A; p-value = 1.4×10⁻⁴), LEPR and 1-hour C-peptide (rs1171278; 0.62 ug/L decrease per allele T; p-value = 2.4×10⁻⁴), and IL6 and 1-hour plasma glucose (rs6954897; −2.29 mg/dl decrease per allele G, p-value = 4.3×10⁻⁴).

Conclusions

Based on the genes surveyed in this study the inflammatory pathway is unlikely to have a strong impact on maternal metabolic phenotypes in pregnancy although variation in individual members of the pathway (e.g. RETN, IL8, ADIPOR2, LEPR, IL6, and TNF alpha,) may contribute to metabolic phenotypes in pregnant women.     

Homology modeling, simulation and molecular docking studies of catechol-2, 3-Dioxygenase from Burkholderia cepacia: Involved in degradation of Petroleum hydrocarbons

Catechol 2, 3-dioxygenase is present in several types of bacteria and undergoes degradation of environmental pollutants through an important key biochemical pathways. Specifically, this enzyme cleaves aromatic rings of several environmental pollutants such as toluene, xylene, naphthalene and biphenyl derivatives. Hence, the importance of Catechol 2, 3-dioxygenase and its role in the degradation of environmental pollutants made us to predict the three-dimensional structure of Catechol 2, 3-dioxygenase from Burkholderia cepacia. The 10ns molecular dynamics simulation was carried out to check the stability of the modeled Catechol 2, 3- dioxygenase. The results show that the model was energetically stable, and it attains their equilibrium within 2000 ps of production MD run. The docking of various petroleum hydrocarbons into the Catechol 2,3-dioxygenase reveals that the benzene, O-xylene, Toluene, Fluorene, Naphthalene, Carbazol, Pyrene, Dibenzothiophene, Anthracene, Phenanthrene, Biphenyl makes strong hydrogen bond and Van der waals interaction with the active site residues of H150, L152, W198, H206, H220, H252, I254, T255, Y261, E271, L276 and F309. Free energy of binding and estimated inhibition constant of these compounds demonstrates that they are energetically stable in their binding cavity. Chrysene shows positive energy of binding in the active site atom of Fe. Except Pyrene all the substrates made close contact with Fe atom by the distance ranges from 1.67 to 2.43 Å. In addition to that, the above mentioned substrate except pyrene all other made π-π stacking interaction with H252 by the distance ranges from 3.40 to 3.90 Å. All these docking results reveal that, except Chrysene all other substrate has good free energy of binding to hold enough in the active site and makes strong VdW interaction with Catechol-2,3-dioxygenase. These results suggest that, the enzyme is capable of catalyzing the above-mentioned substrate.     

Inhibition of cytochrome c oxidase activity in rat cerebral cortex and human skeletal muscle by D-2-hydroxyglutaric acid in vitro.

L-2-Hydroxyglutaric (LGA) and D-2-hydroxyglutaric (DGA) acids are the characteristic metabolites accumulating in the neurometabolic disorders known as L-2-hydroxyglutaric aciduria and D-2-hydroxyglutaric aciduria, respectively. Although these disorders are predominantly characterized by severe neurological symptoms, the neurotoxic mechanisms of brain damage are virtually unknown. In this study we have evaluated the role of LGA and DGA at concentrations ranging from 0.01 to 5.0 mM on various parameters of energy metabolism in cerebral cortex slices and homogenates of 30-day-old Wistar rats, namely glucose uptake, CO(2) production and the respiratory chain enzyme activities of complexes I to IV. DGA significantly decreased glucose utilization (2.5 and 5.0 mM) by brain homogenates and CO(2) production (5 mM) by brain homogenates and slices, whereas LGA had no effect on either measurement. Furthermore, DGA significantly inhibited cytochrome c oxidase activity (complex IV) (EC 1.9.3.1) in a dose-dependent manner (35-95%) at doses as low as 0.5 mM, without compromising the other respiratory chain enzyme activities. In contrast, LGA did not interfere with these activities. Our results suggest that the strong inhibition of cytochrome c oxidase activity by increased levels of DGA could be related to the neurodegeneration of patients affected by D-2-hydroxyglutaric aciduria.     

Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.     

Exploring the developmental overnutrition hypothesis using parental-offspring associations and FTO as an instrumental variable

Background

The developmental overnutrition hypothesis suggests that greater maternal obesity during pregnancy results in increased offspring adiposity in later life. If true, this would result in the obesity epidemic progressing across generations irrespective of environmental or genetic changes. It is therefore important to robustly test this hypothesis.

Methods and Findings

We explored this hypothesis by comparing the associations of maternal and paternal pre-pregnancy body mass index (BMI) with offspring dual energy X-ray absorptiometry (DXA)–determined fat mass measured at 9 to 11 y (4,091 parent–offspring trios) and by using maternal FTO genotype, controlling for offspring FTO genotype, as an instrument for maternal adiposity. Both maternal and paternal BMI were positively associated with offspring fat mass, but the maternal association effect size was larger than that in the paternal association in all models: mean difference in offspring sex- and age-standardised fat mass z-score per 1 standard deviation BMI 0.24 (95% confidence interval [CI]: 0.22 to 0.26) for maternal BMI versus 0.13 (95% CI: 0.11, 0.15) for paternal BMI; p-value for difference in effect < 0.001. The stronger maternal association was robust to sensitivity analyses assuming levels of non-paternity up to 20%. When maternal FTO, controlling for offspring FTO, was used as an instrument for the effect of maternal adiposity, the mean difference in offspring fat mass z-score per 1 standard deviation maternal BMI was −0.08 (95% CI: −0.56 to 0.41), with no strong statistical evidence that this differed from the observational ordinary least squares analyses (p = 0.17).

Conclusions

Neither our parental comparisons nor the use of FTO genotype as an instrumental variable, suggest that greater maternal BMI during offspring development has a marked effect on offspring fat mass at age 9–11 y. Developmental overnutrition related to greater maternal BMI is unlikely to have driven the recent obesity epidemic.     

Historical Assessment of the Impacts of Chemical Contaminants in Sediments on Benthic Invertebrates in the Tidal Passaic River,New Jersey

A historical impact assessment was conducted for chemical contaminants in sediments of the tidal Passaic River in northern New Jersey. The assessment was based on sediment cores collected from 1990 to 1995. Each sediment core was segregated into fractions and the fractions dated using radioisotope analysis. Chemical concentrations, including a variety of metals and organic compounds, were estimated by decade for most of the 20th century in five reaches of the River. The chemical data for each decade were compared to available benchmark sediment quality values that represent levels of chemicals that may be toxic to benthic invertebrates in estuarine systems. Benchmark exceedances in the River were then calculated and characterized spatially and temporally using quantitative Geographic Information System (GIS) analyses, and the area of “impacted” sediments was calculated for each chemical and decade. Results of this assessment suggest that the ability of Passaic River sediments to support “normal” benthic invertebrate populations was limited by sediment contaminants throughout the 20^th century. Conditions have improved somewhat since the 1950s, although impacts to benthic populations remain from several metals and organic compounds despite some overall improvements in sediment quality in recent years.