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Abstract Background Many human diseases and phenotypes are related to RNA expression, levels of which are influenced by a wide spectrum of genetic and exposure-related factors. In a large genome-wide study of muscle tissue expression, we found that some genes exhibited a bimodal distribution of RNA expression, in contrast to what is usually assumed in studies of a single healthy tissue. As bimodality has classically been considered a hallmark of genetic control, we assessed the genome-wide prevalence, cause, and association of this phenomenon with diabetes-related phenotypes in skeletal muscle tissue from 225 healthy Pima Indians using exon array expression chips. Results Two independent batches of microarrays were used for bimodal assessment and comparison. Of the 17,881 genes analyzed, eight (GSTM1, HLA-DRB1, ERAP2, HLA-DRB5, MAOA, ACTN3, NR4A2, and THNSL2) were found to have bimodal expression replicated in the separate batch groups, while 24 other genes had evidence of bimodality in only one group. Some bimodally expressed genes had modest associations with pre-diabetic phenotypes, of note ACTN3 with insulin resistance. Most of the other bimodal genes have been reported to be involved with various other diseases and characteristics. Association of expression with cis genetic variation in a subset of 149 individuals found all but one of the confirmed bimodal genes and nearly half of all potential ones to be highly significant expression quantitative trait loci (eQTL). The rare prevalence of these bimodally expressed genes found after controlling for batch effects was much lower than the prevalence reported in other studies. Additional validation in data from separate muscle expression studies confirmed the low prevalence of bimodality we observed. Conclusions We conclude that the prevalence of bimodal gene expression is quite rare in healthy muscle tissue (cis-polymorphisms, indicating that such bimodal genes are, for the most part, eQTL. The high frequency of disease associations reported with these genes gives hope that this unique feature may identify or actually be an underlying factor responsible for disease development.

Objective: In an ongoing effort to identify the genetic variation that contributes to obesity in American Indians, known Bardet–Biedl syndrome (BBS) genes were analyzed for an effect on BMI and leptin signaling. Methods: Potentially deleterious variants (Combined Annotation Dependent Depletion score > 20) in BBS genes were identified in whole‐exome sequence data from 6,851 American Indians informative for BMI. Common variants (detected in ≥ 10 individuals) were analyzed for association with BMI; rare variants (detected in < 10 individuals) were analyzed for mean BMI of carriers. Functional assessment of variants' effect on signal transducer and activator of transcription 3 (STAT3) activity was performed in vitro. Results: One common variant, rs59252892 (Thr549Ile) in BBS9, was associated with BMI (P = 0.0008, β = 25% increase per risk allele). Among rare variants for which carriers had severe obesity (mean BMI > 40 kg/m2), four were in BBS9. In vitro analysis of BBS9 found the Ile allele at Thr549Ile had a 20% increase in STAT3 activity compared with the Thr allele (P = 0.01). Western blot analysis showed the Ile allele had a 15% increase in STAT3 phosphorylation (P = 0.006). Comparable functional results were observed with Ser545Gly and Val209Leu but not Leu665Phe and Lys810Glu. Conclusions: Potentially functional variants in BBS genes in American Indians are reported. However, functional evidence supporting a causal role for BBS9 in obesity is inconclusive. [ABSTRACT FROM AUTHOR]

Microbial resistance to currently available antibiotics poses a great threat in the global fight against infections. An important step in determining bacterial antibiotic resistance can be selective DNA sequence capture and fluorescence labeling. In this paper, we demonstrate the fabrication of simple, robust, inexpensive microfluidic devices for DNA capture and fluorescence detection of a model antibiotic resistance gene sequence. We laser micromachined polymethyl methacrylate microchannels and enclosed them using pressure-sensitive adhesive tapes. We then formed porous polymer monoliths with DNA capture probes in these microchannels and used them for sequence-specific capture, fluorescent labeling, and laser-induced fluorescence detection of picomolar (pM) concentrations of synthetic and plasmid antibiotic resistance gene targets. The relative fluorescence for the elution peaks increased with loaded target DNA concentration. We observed higher fluorescence signal and percent recovery for synthetic target DNA compared to plasmid DNA at the same loaded target concentration. A non-target gene was used for control experiments and produced < 3% capture relative to the same concentration of target. The full analysis process including device fabrication was completed in less than 90 min with a limit of detection of 30 pM. The simplicity of device fabrication and good DNA capture selectivity demonstrated herein have potential for application with processes for bacterial plasmid DNA extraction and single-particle counting to facilitate determination of antibiotic susceptibility. [ABSTRACT FROM AUTHOR]

Insulin is an essential hormone that regulates glucose homeostasis and metabolism. Insulin resistance (IR) arises when tissues fail to respond to insulin, and it leads to serious health problems including Type 2 Diabetes (T2D). Obesity is a major contributor to the development of IR and T2D. We previously showed that gene expression of alcohol dehydrogenase 1B (ADH1B) was inversely correlated with obesity and IR in subcutaneous adipose tissue of Mexican Americans. In the current study, a meta-analysis of the relationship between ADH1B expression and BMI in Mexican Americans, African Americans, Europeans, and Pima Indians verified that BMI was increased with decreased ADH1B expression. Using established human subcutaneous pre-adipocyte cell lines derived from lean (BMI < 30 kg m−2) or obese (BMI ≥ 30 kg m−2) donors, we found that ADH1B protein expression increased substantially during differentiation, and overexpression of ADH1B inhibited fatty acid binding protein expression. Mature adipocytes from lean donors expressed ADH1B at higher levels than obese donors. Insulin further induced ADH1B protein expression as well as enzyme activity. Knockdown of ADH1B expression decreased insulin-stimulated glucose uptake. Our findings suggest that ADH1B is involved in the proper development and metabolic activity of adipose tissues and this function is suppressed by obesity. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Prevalence of type 2 diabetes differs among human ancestry groups, and many hypotheses invoke differential natural selection to account for these differences. We sought to assess the potential role of differential natural selection across major continental ancestry groups for diabetes and related traits, by comparison of genetic and phenotypic differences. Methods: This was a cross-sectional comparison among 734 individuals from an urban sample (none of whom was more closely related to another than third-degree relatives), including 83 African Americans, 523 American Indians and 128 European Americans. Participants were not recruited based on diabetes status or other traits. BMI was calculated, and diabetes was diagnosed by a 75 g oral glucose tolerance test. In those with normal glucose tolerance (n = 434), fasting insulin and 30 min post-load insulin, adjusted for 30 min glucose, were taken as measures of insulin resistance and secretion, respectively. Whole exome sequencing was performed, resulting in 97,388 common (minor allele frequency ≥ 5%) variants; the coancestry coefficient (FST) was calculated across all markers as a measure of genetic divergence among ancestry groups. The phenotypic divergence index (PST) was also calculated from the phenotypic differences and heritability (which was estimated from genetic relatedness calculated empirically across all markers in 761 American Indian participants prior to the exclusion of close relatives). Under evolutionary neutrality, the expectation is PST = FST, while for traits under differential selection PST is expected to be significantly greater than FST. A bootstrap procedure was used to test the hypothesis PST = FST. Results: With adjustment for age and sex, prevalence of type 2 diabetes was 34.0% in American Indians, 12.4% in African Americans and 10.4% in European Americans (p = 2.9 × 10−10 for difference among groups). Mean BMI was 36.3, 33.4 and 33.0 kg/m2, respectively (p = 1.9 × 10−7). Mean fasting insulin was 63.8, 48.4 and 45.2 pmol/l (p = 9.2 × 10−5), while mean 30 min insulin was 559.8, 553.5 and 358.8 pmol/l, respectively (p = 5.7 × 10−8). FST across all markers was 0.130, while PST for liability to diabetes, adjusted for age and sex, was 0.149 (p = 0.35 for difference with FST). PST was 0.094 for BMI (p = 0.54), 0.095 for fasting insulin (p = 0.54) and 0.216 (p = 0.18) for 30 min insulin. For type 2 diabetes and BMI, the maximum divergence between populations was observed between American Indians and European Americans (PST-MAX = 0.22, p = 0.37, and PST-MAX = 0.14, p = 0.61), which suggests that a relatively modest 22% or 14% of the genetic variance, respectively, can potentially be explained by differential selection (assuming the absence of neutral drift). Conclusions/interpretation: These analyses suggest that while type 2 diabetes and related traits differ significantly among continental ancestry groups, the differences are consistent with neutral expectations based on heritability and genetic distances. While these analyses do not exclude a modest role for natural selection, they do not support the hypothesis that differential natural selection is necessary to explain the phenotypic differences among these ancestry groups. [ABSTRACT FROM AUTHOR]