Cross-species replication of a resistin mRNA QTL, but not QTLs for circulating levels of resistin, in human and baboon

Amoeba predation of Cryptococcus: A quantitative and population genomic evaluation of the accidental pathogen hypothesis

The "Amoeboid Predator-Fungal Animal Virulence Hypothesis" posits that interactions with environmental phagocytes shape the evolution of virulence traits in fungal pathogens. In this hypothesis, selection to avoid predation by amoeba inadvertently selects for traits that contribute to fungal escape from phagocytic immune cells. Here, we investigate this hypothesis in the human fungal pathogens Cryptococcus neoformans and Cryptococcus deneoformans. Applying quantitative trait locus (QTL) mapping and comparative genomics, we discovered a cross-species QTL region that is responsible for variation in resistance to amoeba predation. In C. neoformans, this same QTL was found to have pleiotropic effects on melanization, an established virulence factor. Through fine mapping and population genomic comparisons, we identified the gene encoding the transcription factor Bzp4 that underlies this pleiotropic QTL and we show that decreased expression of this gene reduces melanization and increases susceptibility to amoeba predation. Despite the joint effects of BZP4 on amoeba resistance and melanin production, we find no relationship between BZP4 genotype and escape from macrophages or virulence in murine models of disease. Our findings provide new perspectives on how microbial ecology shapes the genetic architecture of fungal virulence, and suggests the need for more nuanced models for the evolution of pathogenesis that account for the complexities of both microbe-microbe and microbe-host interactions.

Baboons as a model to study genetics and epigenetics of human disease

A major challenge for understanding susceptibility to common human diseases is determining genetic and environmental factors that influence mechanisms underlying variation in disease-related traits. The most common diseases afflicting the US population are complex diseases that develop as a result of defects in multiple genetically controlled systems in response to environmental challenges. Unraveling the etiology of these diseases is exceedingly difficult because of the many genetic and environmental factors involved. Studies of complex disease genetics in humans are challenging because it is not possible to control pedigree structure and often not practical to control environmental conditions over an extended period of time. Furthermore, access to tissues relevant to many diseases from healthy individuals is quite limited. The baboon is a well-established research model for the study of a wide array of common complex diseases, including dyslipidemia, hypertension, obesity, and osteoporosis. It is possible to acquire tissues from healthy, genetically characterized baboons that have been exposed to defined environmental stimuli. In this review, we describe the genetic and physiologic similarity of baboons with humans, the ability and usefulness of controlling environment and breeding, and current genetic and genomic resources. We discuss studies on genetics of heart disease, obesity, diabetes, metabolic syndrome, hypertension, osteoporosis, osteoarthritis, and intrauterine growth restriction using the baboon as a model for human disease. We also summarize new studies and resources under development, providing examples of potential translational studies for targeted interventions and therapies for human disease.

Development of strategies for SNP detection in RNA-seq data: application to lymphoblastoid cell lines and evaluation using 1000 Genomes data

Next-generation RNA sequencing (RNA-seq) maps and analyzes transcriptomes and generates data on sequence variation in expressed genes. There are few reported studies on analysis strategies to maximize the yield of quality RNA-seq SNP data. We evaluated the performance of different SNP-calling methods following alignment to both genome and transcriptome by applying them to RNA-seq data from a HapMap lymphoblastoid cell line sample and comparing results with sequence variation data from 1000 Genomes. We determined that the best method to achieve high specificity and sensitivity, and greatest number of SNP calls, is to remove duplicate sequence reads after alignment to the genome and to call SNPs using SAMtools. The accuracy of SNP calls is dependent on sequence coverage available. In terms of specificity, 89% of RNA-seq SNPs calls were true variants where coverage is >10X. In terms of sensitivity, at >10X coverage 92% of all expected SNPs in expressed exons could be detected. Overall, the results indicate that RNA-seq SNP data are a very useful by-product of sequence-based transcriptome analysis. If RNA-seq is applied to disease tissue samples and assuming that genes carrying mutations relevant to disease biology are being expressed, a very high proportion of these mutations can be detected.

Novel adiponectin-resistin (AR) and insulin resistance (IRAR) indexes are useful integrated diagnostic biomarkers for insulin resistance, type 2 diabetes and metabolic syndrome: a case control study

Background

Adiponectin and resistin are adipokines which modulate insulin action, energy, glucose and lipid homeostasis. Meta-analyses showed that hypoadiponectinemia and hyperresistinemia are strongly associated with increased risk of insulin resistance, type 2 diabetes (T2DM), metabolic syndrome (MS) and cardiovascular disease. The aim of this study was to propose a novel adiponectin-resistin (AR) index by taking into account both adiponectin and resistin levels to povide a better indicator of the metabolic homeostasis and metabolic disorders. In addition, a novel insulin resistance (IR_AR) index was proposed by integration of the AR index into an existing insulin resistance index to provide an improved diagnostic biomarker of insulin sensitivity.

Methods

In this case control study, anthropometric clinical and metabolic parameters including fasting serum total adiponectin and resistin levels were determined in 809 Malaysian men (208 controls, 174 MS without T2DM, 171 T2DM without MS, 256 T2DM with MS) whose ages ranged between 40-70 years old. Significant differences in continuous variables among subject groups were confirmed by ANCOVA or MANCOVA test using 1,000 stratified bootstrap samples with bias corrected and accelerated (BCa) 95% CI. Spearman's rho rank correlation test was used to test the correlation between two variables.

Results

The AR index was formulated as 1+log₁₀(R₀)-log₁₀(A₀). The AR index was more strongly associated with increased risk of T2DM and MS than hypoadiponectinemia and hyperresistinemia alone. The AR index was more strongly correlated with the insulin resistance indexes and key metabolic endpoints of T2DM and MS than adiponectin and resistin levels alone. The AR index was also correlated with a higher number of MS components than adiponectin and resistin levels alone. The IR_AR index was formulated as log₁₀(I₀G₀)+log₁₀(I₀G₀)log₁₀(R₀/A₀). The normal reference range of the IR_AR index for insulin sensitive individuals was between 3.265 and 3.538. The minimum cut-off values of the IR_AR index for insulin resistance assessment were between 3.538 and 3.955.

Conclusions

The novel AR and IR_AR indexes are cost-effective, precise, reproducible and reliable integrated diagnostic biomarkers of insulin sensitivity for screening subjects with increased risk of future development of T2DM and MS.

A at single nucleotide polymorphism-358 is required for G at -420 to confer the highest plasma resistin in the general Japanese population

Insulin resistance is a feature of type 2 diabetes. Resistin, secreted from adipocytes, causes insulin resistance in mice. We previously reported that the G/G genotype of single nucleotide polymorphism (SNP) at −420 (rs1862513) in the human resistin gene (RETN) increased susceptibility to type 2 diabetes by enhancing its promoter activity. Plasma resistin was highest in Japanese subjects with G/G genotype, followed by C/G, and C/C. In this study, we cross-sectionally analyzed plasma resistin and SNPs in the RETN region in 2,019 community-dwelling Japanese subjects. Plasma resistin was associated with SNP-638 (rs34861192), SNP-537 (rs34124816), SNP-420, SNP-358 (rs3219175), SNP+299 (rs3745367), and SNP+1263 (rs3745369) (P<10⁻¹³ in all cases). SNP-638, SNP -420, SNP-358, and SNP+157 were in the same linkage disequilibrium (LD) block. SNP-358 and SNP-638 were nearly in complete LD (r² = 0.98), and were tightly correlated with SNP-420 (r² = 0.50, and 0.51, respectively). The correlation between either SNP-358 (or SNP-638) or SNP-420 and plasma resistin appeared to be strong (risk alleles for high plasma resistin; A at SNP-358, r² = 0.5224, P = 4.94×10⁻³²⁴; G at SNP-420, r² = 0.2616, P = 1.71×10⁻¹³³). In haplotypes determined by SNP-420 and SNP-358, the estimated frequencies for C-G, G-A, and G-G were 0.6700, 0.2005, and 0.1284, respectively, and C-A was rare (0.0011), suggesting that subjects with A at −358, generally had G at −420. This G-A haplotype conferred the highest plasma resistin (8.24 ng/ml difference/allele compared to C-G, P<0.0001). In THP-1 cells, the RETN promoter with the G-A haplotype showed the highest activity. Nuclear proteins specifically recognized one base difference at SNP-358, but not at SNP-638. Therefore, A at -358 is required for G at −420 to confer the highest plasma resistin in the general Japanese population. In Caucasians, the association between SNP-420 and plasma resistin is not strong, and A at −358 may not exist, suggesting that SNP-358 could explain this ethnic difference.