Comparison of Liver Fat Indices for the Diagnosis of Hepatic Steatosis and Insulin Resistance

Context

Hepatic steatosis, defined as increased hepatocellular lipid content (HCL), associates with visceral obesity and glucose intolerance. As exact HCL quantification by ¹H-magnetic resonance spectroscopy (¹H-MRS) is not generally available, various clinical indices are increasingly used to predict steatosis.

Objective

The purpose of this study was to test the accuracy of NAFLD liver fat score (NAFLD-LFS), hepatic steatosis index (HSI) and fatty liver index (FLI) against ¹H-MRS and their relationships with insulin sensitivity and secretion.

Design, Setting and Participants

Ninety-two non-diabetic, predominantly non-obese humans underwent clinical examination, ¹H-MRS and an oral glucose tolerance test (OGTT) to calculate insulin sensitivity and β-cell function. Accuracy of indices was assessed from the area under the receiver operating characteristic curve (AROC).

Results

Median HCL was 2.49% (0.62;4.23) and correlated with parameters of glycemia across all subjects. NAFLD-LFS, FLI and HSI yielded AROCs of 0.70, 0.72, and 0.79, respectively, and related positively to HCL, insulin resistance, fasting and post-load β-cell function normalized for insulin resistance. Upon adjustment for age, sex and HCL, regression analysis revealed that NAFLD-LFS, FLI and HSI still independently associated with both insulin sensitivity and β-cell function.

Conclusion

The tested indices offer modest efficacy to detect steatosis and cannot substitute for fat quantification by ¹H-MRS. However, all indices might serve as surrogate parameters for liver fat content and also as rough clinical estimates of abnormal insulin sensitivity and secretion. Further validation in larger collectives such as epidemiological studies is needed.     

Genbank accession #: AJ237597

Plant Molecular Biology -     

Reduction of Plasma Leptin Concentrations by Arginine but Not Lipid Infusion in Humans

Objective: We examined short-term effects of arginine infusion on plasma leptin in diabetic and healthy subjects. Research Methods and Procedures: Arginine stimulation tests were performed in C-peptide negative type 1 [DM1; hemoglobin A_1c; 7.3 ± 0.3%], hyperinsulinemic type 2 diabetic (DM2; 7.6 ± 0.7%), and nondiabetic subjects (CON; 5.4 ± 0.1%). Results: Fasting plasma leptin correlated linearly with body mass index among all groups (r = 0.61, p = 0.001). During arginine infusion, peak plasma insulin was lower in DM1 than in DM2 (p < 0.05) and CON (p < 0.01). Plasma leptin decreased within 30 minutes by ∼11% in DM1 (p < 0.001), DM2 (p < 0.01), and CON (p < 0.005), slowly returning to baseline thereafter. Plasma free fatty acids (FFAs) were higher in DM1 (0.6 ± 0.1 mM) and DM2 (0.6 ± 0.1 mM) than in CON (0.4 ± 0.1 mM, p < 0.05) and transiently declined by ∼50% (p < 0.05) at 45 minutes in all groups before rebounding toward baseline. To examine the direct effects of FFAs on plasma leptin, we infused healthy subjects with lipid/heparin and glycerol during fasting, and somatostatin-insulin (∼35 pM) -glucagon (∼90 ng/mL) clamps were performed. In both protocols, plasma leptin continuously declined by ∼25% (p < 0.05) during 540 minutes without any difference between the high and low FFA conditions. Discussion: Arginine infusion transiently decreased plasma leptin concentrations both in insulin-deficient and hyperinsulinemic diabetic patients, indicating a direct inhibitory effect of the amino acid but not of insulin or FFAs.     

Mining gene expression data by interpreting principal components

Background  

There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many instances the biologically important goal is to identify relatively small sets of genes that share coherent expression across only some conditions, rather than all or most conditions as required in traditional clustering; e.g. genes that are highly up-regulated and/or down-regulated similarly across only a subset of conditions. Equally important is the need to learn which conditions are the decisive ones in forming such gene sets of interest, and how they relate to diverse conditional covariates, such as disease diagnosis or prognosis.     

Lights,Rhythms, Infection: The Role of Light and the Circadian Clock in Determining the Outcome of Plant–Pathogen Interactions

The importance of light with respect to the outcome of plant–pathogen interactions is becoming increasingly evident: light affects both the host response and the virulence of some pathogens. The response of plants to environmental signals and stresses is modulated by the circadian clock, and it is apparent that this may include immune responses. Photo and temporal regulation of immune responses may allow plants to anticipate and react more effectively to particular pathogen infections. These aspects of regulation are sometimes overlooked when designing experiments to understand plant–pathogen interactions, complicating the interpretation of the outcomes and the direct comparisons of studies. We review recent key findings in these areas and discuss the implications for experimental design and analyses.     

Retention of cryptic genes in microbial populations

Cryptic genes are silenced genes that can still be reactivated by mutation. Since they can make no positive contribution to the fitness of their carriers, it is not clear why many cryptic genes in microbial populations have not degenerated into useless DNA sequences. Hall et al. (1983) have suggested that cryptic genes have persisted because of occasional strong environmental selection for reactivated genes. The present mathematical study supports their suggestion. It shows that a cryptic gene can be retained without having any selective advantage over a useless DNA sequence, if selection for the reactivated gene occasionally occurs for a substantially long time.