Pooled sample-based GWAS: a cost-effective alternative for identifying colorectal and prostate cancer risk variants in the Polish population

Background

Prostate cancer (PCa) and colorectal cancer (CRC) are the most commonly diagnosed cancers and cancer-related causes of death in Poland. To date, numerous single nucleotide polymorphisms (SNPs) associated with susceptibility to both cancer types have been identified, but their effect on disease risk may differ among populations.

Methods

To identify new SNPs associated with PCa and CRC in the Polish population, a genome-wide association study (GWAS) was performed using DNA sample pools on Affymetrix Genome-Wide Human SNP 6.0 arrays. A total of 135 PCa patients and 270 healthy men (PCa sub-study) and 525 patients with adenoma (AD), 630 patients with CRC and 690 controls (AD/CRC sub-study) were included in the analysis. Allele frequency distributions were compared with t-tests and χ²-tests. Only those significantly associated SNPs with a proxy SNP (p<0.001; distance of 100 kb; r²>0.7) were selected. GWAS marker selection was conducted using PLINK. The study was replicated using extended cohorts of patients and controls. The association with previously reported PCa and CRC susceptibility variants was also examined. Individual patients were genotyped using TaqMan SNP Genotyping Assays.

Results

The GWAS selected six and 24 new candidate SNPs associated with PCa and CRC susceptibility, respectively. In the replication study, 17 of these associations were confirmed as significant in additive model of inheritance. Seven of them remained significant after correction for multiple hypothesis testing. Additionally, 17 previously reported risk variants have been identified, five of which remained significant after correction.

Conclusion

Pooled-DNA GWAS enabled the identification of new susceptibility loci for CRC in the Polish population. Previously reported CRC and PCa predisposition variants were also identified, validating the global nature of their associations. Further independent replication studies are required to confirm significance of the newly uncovered candidate susceptibility loci.     

Metabolic flux analysis of CHO cells at growth and non-growth phases using isotopic tracers and mass spectrometry

Chinese hamster ovary (CHO) cells are the main platform for production of biotherapeutics in the biopharmaceutical industry. However, relatively little is known about the metabolism of CHO cells in cell culture. In this work, metabolism of CHO cells was studied at the growth phase and early stationary phase using isotopic tracers and mass spectrometry. CHO cells were grown in fed-batch culture over a period of six days. On days 2 and 4, [1,2-¹³C] glucose was introduced and the labeling of intracellular metabolites was measured by gas chromatography-mass spectrometry (GC–MS) at 6, 12 and 24 h following the introduction of tracer. Intracellular metabolic fluxes were quantified from measured extracellular rates and ¹³C-labeling dynamics of intracellular metabolites using non-stationary ¹³C-metabolic flux analysis (¹³C-MFA). The flux results revealed significant rewiring of intracellular metabolic fluxes in the transition from growth to non-growth, including changes in energy metabolism, redox metabolism, oxidative pentose phosphate pathway and anaplerosis. At the exponential phase, CHO cell metabolism was characterized by a high flux of glycolysis from glucose to lactate, anaplerosis from pyruvate to oxaloacetate and from glutamate to α-ketoglutarate, and cataplerosis though malic enzyme. At the stationary phase, the flux map was characterized by a reduced flux of glycolysis, net lactate uptake, oxidative pentose phosphate pathway flux, and reduced rate of anaplerosis. The fluxes of pyruvate dehydrogenase and TCA cycle were similar at the exponential and stationary phase. The results presented here provide a solid foundation for future studies of CHO cell metabolism for applications such as cell line development and medium optimization for high-titer production of recombinant proteins.     

Exercise training in childhood-onset systemic lupus erythematosus: a controlled randomized trial

Introduction

Exercise training has emerged as a promising therapeutic strategy to counteract physical dysfunction in adult systemic lupus erythematosus. However, no longitudinal studies have evaluated the effects of an exercise training program in childhood-onset systemic lupus erythematosus (C-SLE) patients. The objective was to evaluate the safety and the efficacy of a supervised aerobic training program in improving the cardiorespiratory capacity in C-SLE patients.

Methods

Nineteen physically inactive C-SLE patients were randomly assigned into two groups: trained (TR, n = 10, supervised moderate-intensity aerobic exercise program) and non-trained (NT, n = 9). Gender-, body mass index (BMI)- and age-matched healthy children were recruited as controls (C, n = 10) for baseline (PRE) measurements only. C-SLE patients were assessed at PRE and after 12 weeks of training (POST). Main measurements included exercise tolerance and cardiorespiratory measurements in response to a maximal exercise (that is, peak VO₂, chronotropic reserve (CR), and the heart rate recovery (ΔHRR) (that is, the difference between HR at peak exercise and at both the first (ΔHRR1) and second (ΔHRR2) minutes of recovery after exercise).

Results

The C-SLE NT patients did not present changes in any of the cardiorespiratory parameters at POST (P > 0.05). In contrast, the exercise training program was effective in promoting significant increases in time-to-exhaustion (P = 0.01; ES = 1.07), peak speed (P = 0.01; ES = 1.08), peak VO₂ (P = 0.04; ES = 0.86), CR (P = 0.06; ES = 0.83), and in ΔHRR1 and ΔHRR2 (P = 0.003; ES = 1.29 and P = 0.0008; ES = 1.36, respectively) in the C-SLE TR when compared with the NT group. Moreover, cardiorespiratory parameters were comparable between C-SLE TR patients and C subjects after the exercise training intervention, as evidenced by the ANOVA analysis (P > 0.05, TR vs. C). SLEDAI-2K scores remained stable throughout the study.

Conclusion

A 3-month aerobic exercise training was safe and capable of ameliorating the cardiorespiratory capacity and the autonomic function in C-SLE patients.

Trial registration

NCT01515163.     

Towards a framework for the evolutionary genomics of Kinetoplastids: what kind of data and how much?

The current status of kinetoplastids phylogeny and evolution is discussed in view of the recent progresses on genomics. Some ideas on a potential framework for the evolutionary genomics of kinetoplastids are presented.     

Evaluation of regression models in metabolic physiology: predicting fluxes from isotopic data without knowledge of the pathway

This study explores the ability of regression models, with no knowledge of the underlying physiology, to estimate physiological parameters relevant for metabolism and endocrinology. Four regression models were compared: multiple linear regression (MLR), principal component regression (PCR), partial least-squares regression (PLS) and regression using artificial neural networks (ANN). The pathway of mammalian gluconeogenesis was analyzed using [U−¹³C]glucose as tracer. A set of data was simulated by randomly selecting physiologically appropriate metabolic fluxes for the 9 steps of this pathway as independent variables. The isotope labeling patterns of key intermediates in the pathway were then calculated for each set of fluxes, yielding 29 dependent variables. Two thousand sets were created, allowing independent training and test data. Regression models were asked to predict the nine fluxes, given only the 29 isotopomers. For large training sets (>50) the artificial neural network model was superior, capturing 95% of the variability in the gluconeogenic flux, whereas the three linear models captured only 75%. This reflects the ability of neural networks to capture the inherent non-linearities of the metabolic system. The effect of error in the variables and the addition of random variables to the data set was considered. Model sensitivities were used to find the isotopomers that most influenced the predicted flux values. These studies provide the first test of multivariate regression models for the analysis of isotopomer flux data. They provide insight for metabolomics and the future of isotopic tracers in metabolic research where the underlying physiology is complex or unknown.We acknowledge the support of NIH Grant DK58533 and the DuPont-MIT Alliance.     

Metabolic flux analysis in a nonstationary system: fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol

Metabolic fluxes estimated from stable-isotope studies provide a key to understanding cell physiology and regulation of metabolism. A limitation of the classical method for metabolic flux analysis (MFA) is the requirement for isotopic steady state. To extend the scope of flux determination from stationary to nonstationary systems, we present a novel modeling strategy that combines key ideas from isotopomer spectral analysis (ISA) and stationary MFA. Isotopic transients of the precursor pool and the sampled products are described by two parameters, D and G parameters, respectively, which are incorporated into the flux model. The G value is the fraction of labeled product in the sample, and the D value is the fractional contribution of the feed for the production of labeled products. We illustrate the novel modeling strategy with a nonstationary system that closely resembles industrial production conditions, i.e. fed-batch fermentation of Escherichia coli that produces 1,3-propanediol (PDO). Metabolic fluxes and the D and G parameters were estimated by fitting labeling distributions of biomass amino acids measured by GC/MS to a model of E. coli metabolism. We obtained highly consistent fits from the data with 82 redundant measurements. Metabolic fluxes were estimated for 20 time points during course of the fermentation. As such we established, for the first time, detailed time profiles of in vivo fluxes. We found that intracellular fluxes changed significantly during the fed-batch. The intracellular flux associated with PDO pathway increased by 10%. Concurrently, we observed a decrease in the split ratio between glycolysis and pentose phosphate pathway from 70/30 to 50/50 as a function of time. The TCA cycle flux, on the other hand, remained constant throughout the fermentation. Furthermore, our flux results provided additional insight in support of the assumed genotype of the organism.     

Characterization and quantitation of fatty acids covalently bound to erythrocyte membrane proteins: anion transporter contains 1 mol of fatty acid thiol ester

Human erythrocyte membranes which had been thoroughly extracted with organic solvents contained 20 nmol of fatty acids/mg dry wt. The major fatty acids were palmitic and stearic with their monoethenoic derivatives as minor constituents. No other fatty acids were detected. When solvent-extracted membranes were digested with Pronase about 90% of the original content of fatty acids was retained in the insoluble residue. Fatty acids were linked to membrane proteins through alkali-labile bonds of which 30% were of a thiol ester and the remainder of an O-ester type. This conclusion is based on differential liberation of fatty acids by hydroxylamine at pH 7.0 and pH 11.0. Two extracts of membranes enriched in peripheral proteins (bands 1, 2, 5 and 2.1, 4.1, 4.2, 6) were prepared and extracted with organic solvents but each contained about six times less fatty acids than the parent solvent-extracted membranes. Glycophorin A contains little if any covalently bound fatty acids. Anion transporter (band 3) contains about 1 mol of thiol ester of fatty acid. This accounts for about half of the thiol ester-linked fatty acids in the parent solvent-extracted membranes. Most of the O-ester-linked fatty acids are linked to an undisclosed membrane protein.