Method comparison of three serum free light chain assays on the Roche Cobas 6000 c501 chemistry analyzer.

OBJECTIVES: Free light chains (FLC) are important in the diagnosis, prognosis and monitoring of therapy response of patients with monoclonal gammopathies. In this study, we performed a method comparison of three FLC assays on the Cobas 6000 c501 chemistry analyzer of Roche Diagnostics. METHODS: Samples of 119 patients with various monoclonal gammopathies and 26 control patients were measured with the Freelite (The Binding Site), Diazyme (Diazyme Laboratories) and KLoneus (Trimero Diagnostics) FLC assays. A method comparison was performed and reference intervals of the three assays were validated. RESULTS: The analysis of the Bland-Altman agreement showed bias between the three FLC assays, ranging from -62.7 to 5.1% for κFLC and between -29.2 to 80.5% for λFLC. The Freelite and Diazyme assays have the highest agreement. The concordance of the FLC-ratio ranges from 41 to 75%, with the highest concordance between the Freelite and KLoneus assays. The FLC-ratio in 25 sera from healthy controls were within the reference ranges of the Freelite and KLoneus assays. The FLC-ratio was elevated in all 25 samples tested with the Diazyme assay. CONCLUSIONS: The agreement for the free light chains is highest between the Freelite and the Diazyme assay and fair for the KLoneus assay. However, concordance of the FLC-ratio is highest when the Freelite and KLoneus assays were compared. Our data suggest that concordance for the Diazyme assay could be improved by recalibration. Because of absolute differences between the three methods in individual patients, none of the three FLC assays can be used interchangeably.

Impact of body mass index on growth hormone stimulation tests in children and adolescents: a systematic review and meta-analysis.

Peak stimulated growth hormone (GH) levels are known to decrease with increasing body mass index (BMI), possibly leading to overdiagnosis of GH deficiency (GHD) in children with overweight and obesity. However, current guidelines do not guide how to interpret the peak GH values of these children. This systematic review and meta-analysis aimed to study the effect of the BMI standard deviation score (SDS) on stimulated peak GH values in children, to identify potential moderators of this association, and to quantify the extent to which peak GH values in children with obesity are decreased. This systematic review was performed by the PRISMA guidelines. Medline, Embase, Cochrane, Web of Science, and Google Scholar databases were searched for studies reporting the impact of weight status on peak GH in children. Where possible, individual participant data was extracted and/or obtained from authors. Quality and risk of bias were evaluated using the Scottish Intercollegiate Guidelines Network (SIGN) checklists. The primary outcome was the association between peak GH values and BMI SDS. The pooled correlation coefficient r, 95% confidence interval (CI), and heterogeneity statistic I2 were calculated under a multilevel, random-effects model. In addition, exploratory moderator analyses and meta-regressions were performed to investigate the effects of sex, pubertal status, presence of syndromic obesity, mean age and mean BMI SDS on the study level. For the individual participant dataset, linear mixed-models regression analysis was performed with BMI SDS as the predictor and ln(peak GH) as the outcome, accounting for the different studies and GH stimulation agents used. In total, 58 studies were included, providing data on n = 5135 children (576 with individual participant data). Thirty-six (62%) studies had high, 19 (33%) medium, and 3 (5%) low risks of bias. Across all studies, a pooled r of -0.32 (95% CI -0.41 to -0.23, n = 2434 patients from k = 29 subcohorts, I2 = 75.2%) was found. In meta-regressions, larger proportions of males included were associated with weaker negative correlations (p = 0.04). Pubertal status, presence of syndromic obesity, mean age, and mean BMI SDS did not moderate the pooled r (all p > 0.05). Individual participant data analysis revealed a beta of -0.123 (95% CI -0.160 to -0.086, p < 0.0001), i.e. per one-point increase in BMI SDS, peak GH decreases by 11.6% (95% CI 8.3-14.8%). To our knowledge, this is the first systematic review and meta-analysis to investigate the impact of BMI SDS on peak GH values in children. It showed a significant negative relationship. Importantly, this relationship was already present in the normal range of BMI SDS and could lead to overdiagnosis of GHD in children with overweight and obesity. With the ever-rising prevalence of pediatric obesity, there is a need for BMI (SDS)-specific cutoff values for GH stimulation tests in children. Based on the evidence from this meta-analysis, we suggest the following weight status-adjusted cutoffs for GH stimulation tests that have cutoffs for children with normal weight of 5, 7, 10, and 20 µg/L: for overweight children: 4.6, 6.5, 9.3, and 18.6 µg/L; and for children with obesity: 4.3, 6.0, 8.6, and 17.3 µg/L.

HR-MAS NMR Applications in Plant Metabolomics.

Metabolomics is used to reduce the complexity of plants and to understand the underlying pathways of the plant phenotype. The metabolic profile of plants can be obtained by mass spectrometry or liquid-state NMR. The extraction of metabolites from the sample is necessary for both techniques to obtain the metabolic profile. This extraction step can be eliminated by making use of high-resolution magic angle spinning (HR-MAS) NMR. In this review, an HR-MAS NMR-based workflow is described in more detail, including used pulse sequences in metabolomics. The pre-processing steps of one-dimensional HR-MAS NMR spectra are presented, including spectral alignment, baseline correction, bucketing, normalisation and scaling procedures. We also highlight some of the models which can be used to perform multivariate analysis on the HR-MAS NMR spectra. Finally, applications of HR-MAS NMR in plant metabolomics are described and show that HR-MAS NMR is a powerful tool for plant metabolomics studies.

A robust circadian rhythm of metabolites in Arabidopsis thaliana mutants with enhanced growth characteristics.

Climate change and the rising food demand provide a need for smart crops that yield more biomass. Recently, two Arabidopsis thaliana mutants with enhanced growth characteristics, VP16-02-003 and the VP16-05-014, were obtained by genome-wide reprogramming of gene expression, which led to the identification of novel biomarkers of these enhanced growth phenotypes. Since the circadian cycle strongly influences metabolic and physiological processes and exerts control over the photosynthetic machinery responsible for enhanced growth, in this study, we investigate the influences of the circadian clock on the metabolic rhythm of eighteen key biomarkers for the larger rosette surface area phenotype. The metabolic profile was studied in intact leaves at seven different time points throughout the circadian cycle using high-resolution magic angle spinning (HR-MAS) NMR. The results show that the circadian rhythm of biomarker metabolites are remarkably robust across wild-type Col-0 and VP16-02-003 and the VP16-05-014 mutants, with widely different metabolite levels of both mutants compared to Col-0 throughout the circadian cycle. Our analysis reveals that robustness is achieved through functional independence between the circadian clock and primary metabolic processes.

High-resolution magic angle spinning NMR studies for metabolic characterization of Arabidopsis thaliana mutants with enhanced growth characteristics.

Developing smart crops which yield more biomass to meet the increasing demand for plant biomass has been an active area of research in last few decades. We investigated metabolic alterations in two Arabidopsis thaliana mutants with enhanced growth characteristics that were previously obtained from a collection of plant lines expressing artificial transcription factors. The metabolic profiles were obtained directly from intact Arabidopsis leaves using high-resolution magic angle spinning (HR-MAS) NMR. Multivariate analysis showed significant alteration of metabolite levels between the mutants and the wild-type Col-0. Interestingly, most of the metabolites that were reduced in the faster-growing mutants are generally involved in the defence against stress. These results suggest a growth-defence trade-off in the phenotypically engineered mutants. Our results further corroborate the idea that plant growth can be enhanced by suppressing defence pathways.

An Arabidopsis mutant with high operating efficiency of Photosystem II and low chlorophyll fluorescence.

The overall light energy to biomass conversion efficiency of plant photosynthesis is generally regarded as low. Forward genetic screens in Arabidopsis have yielded very few mutants with substantially enhanced photochemistry. Here, we report the isolation of a novel Arabidopsis mutant with a high operating efficiency of Photosystem II (φPSII) and low chlorophyll fluorescence from a library of lines harboring T-DNA constructs encoding artificial transcription factors. This mutant was named Low Chlorophyll Fluorescence 1 (LCF1). Only a single T-DNA insertion was detected in LCF1, which interrupted the expression of the full length mRNA of the gene At4g36280 (MORC2). We demonstrate that the high φPSII and low levels of chlorophyll fluorescence were due to a decrease in PSII:PSI ratio. Although LCF1 plants had decreased rosette surface area and biomass under normal growth conditions, they contained more starch per gram fresh weight. The growth defect of LCF1 was alleviated by low light and short day conditions, and growth could even be enhanced after a period of dark-induced senescence, showing that the plant can utilize its excess photosynthetic conversion capacity as a resource when needed.

Enhancement of Arabidopsis growth characteristics using genome interrogation with artificial transcription factors.

The rapidly growing world population has a greatly increasing demand for plant biomass, thus creating a great interest in the development of methods to enhance the growth and biomass accumulation of crop species. In this study, we used zinc finger artificial transcription factor (ZF-ATF)-mediated genome interrogation to manipulate the growth characteristics and biomass of Arabidopsis plants. We describe the construction of two collections of Arabidopsis lines expressing fusions of three zinc fingers (3F) to the transcriptional repressor motif EAR (3F-EAR) or the transcriptional activator VP16 (3F-VP16), and the characterization of their growth characteristics. In total, six different 3F-ATF lines with a consistent increase in rosette surface area (RSA) of up to 55% were isolated. For two lines we demonstrated that 3F-ATF constructs function as dominant in trans acting causative agents for an increase in RSA and biomass, and for five larger plant lines we have investigated 3F-ATF induced transcriptomic changes. Our results indicate that genome interrogation can be used as a powerful tool for the manipulation of plant growth and biomass and that it might supply novel cues for the discovery of genes and pathways involved in these properties.