Leucine supplementation in maternal high-fat diet alleviated adiposity and glucose intolerance of adult mice offspring fed a postweaning high-fat diet

Background Combined maternal and postnatal high-fat (HF) diet intake predisposes offspring to metabolic dysregulation during adulthood. As the inhibitory effects of leucine consumption on obesity and metabolic disorders have been reported, the effects of maternal leucine supplementation on metabolic dysregulation in adult offspring were investigated. Methods Female mice were exposed to a control (C) or HF diet, with or without leucine (L) supplementation (1.5%, w/v), 3weeks before mating, during pregnancy, and during lactation (C, CL, HF, and HFL). Male offspring were exposed to an HF diet for 12weeks after weaning (C/HF, CL/HF, HF/HF, and HFL/HF). Serum biochemical parameters were determined for both the dams and offspring. Oral glucose tolerance test and qRT-PCR analysis were used to investigate metabolic dysregulation in the offspring. Results HFL dams exhibited higher relative adipose tissue weights than HF dams. Body weight, relative adipose tissue weight, and serum glucose levels were lower in the HFL/HF offspring than in the HF/HF offspring. Maternal leucine supplementation tended to alleviate glucose intolerance in the offspring of HF diet-fed dams. Additionally, mRNA levels of fibroblast growth factor 21 (FGF21), a hepatokine associated with glucose homeostasis, were higher in HFL/HF offspring than in HF/HF offspring and were negatively correlated with adiposity and serum glucose levels. ThemRNA levels of genes encoding a FGF21 receptor complex, Fgf receptor 1 and klotho β, and its downstream targets, proliferator‐activated receptor‐γ co‐activator 1α and sirtuin 1, were higher in adipose tissues of the HFL/HF offspring than in those of the HF/HF offspring. Serum lipid peroxide levels were lower in HFL dams than in HF dams and positively correlated with body and adipose tissue weights of offspring. Conclusions Leucine supplementation in HF diet-fed dams, but not in control diet-fed dams, resulted in an anti-obesity phenotype accompanied by glucose homeostasis in male offspring challenged with postnatal HF feeding. Activation of FGF21 signaling in the adipose tissue of offspring may be responsible for these beneficial effects of leucine.This work was supported by the National Research Foundation of Korea grant funded by the Ministry of Science, ICT and Future Planning (No. 2014R1A1A3052400)

Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data

Owing to recent improvement of genotyping technology, large-scale genetic data can be utilized to identify disease susceptibility loci and this successful finding has substantially improved our understanding of complex diseases. However, in spite of these successes, most of the genetic effects for many complex diseases were found to be very small, which have been a big hurdle to build disease prediction model. Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called "large P and small N" problem. Penalized regressions including least absolute selection and shrinkage operator (LASSO) and ridge regression limit the space of parameters, and this constraint enables the estimation of effects for very large number of SNPs. Various extensions have been suggested, and, in this report, we compare their accuracy by applying them to several complex diseases. Our results show that penalized regressions are usually robust and provide better accuracy than the existing methods for at least diseases under consideration

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179

Discovery of Q203, a potent clinical candidate for the treatment of tuberculosis

New therapeutic strategies are needed to combat the tuberculosis pandemic and the spread of multidrug-resistant (MDR) and extensively drug-resistant (XDR) forms of the disease, which remain a serious public health challenge worldwide1, 2. The most urgent clinical need is to discover potent agents capable of reducing the duration of MDR and XDR tuberculosis therapy with a success rate comparable to that of current therapies for drug-susceptible tuberculosis. The last decade has seen the discovery of new agent classes for the management of tuberculosis3, 4, 5, several of which are currently in clinical trials6, 7, 8. However, given the high attrition rate of drug candidates during clinical development and the emergence of drug resistance, the discovery of additional clinical candidates is clearly needed. Here, we report on a promising class of imidazopyridine amide (IPA) compounds that block Mycobacterium tuberculosis growth by targeting the respiratory cytochrome bc1 complex. The optimized IPA compound Q203 inhibited the growth of MDR and XDR M. tuberculosis clinical isolates in culture broth medium in the low nanomolar range and was efficacious in a mouse model of tuberculosis at a dose less than 1 mg per kg body weight, which highlights the potency of this compound. In addition, Q203 displays pharmacokinetic and safety profiles compatible with once-daily dosing. Together, our data indicate that Q203 is a promising new clinical candidate for the treatment of tuberculosis

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes