A collaborative database of inbred mouse strain characteristics

A database and website (MPD: Mouse Phenome Database) have been developed to serve as a consolidated home for mouse strain characterization data being generated by the scientific community. Physiological, anatomical and behavioral data are being collected and integrated into a common framework for tabulation by strain and sex. Genotypic data are being collected as well. The current focus is on a set of 40 inbred strains. The MPD as of February 2004 contains approximately 500 phenotypic parameters relevant to human health, voluntarily contributed by several dozen investigators and laboratories. AVAILABILITY: www.jax.org/phenome     

Biomechanical response to acupuncture needling in humans.

During acupuncture treatments, acupuncture needles are manipulated to elicit the characteristic "de qi" reaction widely viewed as essential to acupuncture's therapeutic effect. De qi has a biomechanical component, "needle grasp," which we have quantified by measuring the force necessary to pull an acupuncture needle out of the skin (pullout force) in 60 human subjects. We hypothesized that pullout force is greater with both bidirectional needle rotation (BI) and unidirectional rotation (UNI) than no rotation (NO). Acupuncture needles were inserted, manipulated, and pulled out by using a computer-controlled acupuncture needling instrument at eight acupuncture points and eight control points. We found 167 and 52% increases in mean pullout force with UNI and BI, respectively, compared with NO (repeated-measures ANOVA, P < 0.001). Pullout force was on average 18% greater at acupuncture points than at control points (P < 0.001). Needle grasp is therefore a measurable biomechanical phenomenon associated with acupuncture needle manipulation.     

Methods to Develop an Electronic Medical Record Phenotype Algorithm to Compare the Risk of Coronary Artery Disease across 3 Chronic Disease Cohorts

Background

Typically, algorithms to classify phenotypes using electronic medical record (EMR) data were developed to perform well in a specific patient population. There is increasing interest in analyses which can allow study of a specific outcome across different diseases. Such a study in the EMR would require an algorithm that can be applied across different patient populations. Our objectives were: (1) to develop an algorithm that would enable the study of coronary artery disease (CAD) across diverse patient populations; (2) to study the impact of adding narrative data extracted using natural language processing (NLP) in the algorithm. Additionally, we demonstrate how to implement CAD algorithm to compare risk across 3 chronic diseases in a preliminary study.

Methods and Results

We studied 3 established EMR based patient cohorts: diabetes mellitus (DM, n = 65,099), inflammatory bowel disease (IBD, n = 10,974), and rheumatoid arthritis (RA, n = 4,453) from two large academic centers. We developed a CAD algorithm using NLP in addition to structured data (e.g. ICD9 codes) in the RA cohort and validated it in the DM and IBD cohorts. The CAD algorithm using NLP in addition to structured data achieved specificity >95% with a positive predictive value (PPV) 90% in the training (RA) and validation sets (IBD and DM). The addition of NLP data improved the sensitivity for all cohorts, classifying an additional 17% of CAD subjects in IBD and 10% in DM while maintaining PPV of 90%. The algorithm classified 16,488 DM (26.1%), 457 IBD (4.2%), and 245 RA (5.0%) with CAD. In a cross-sectional analysis, CAD risk was 63% lower in RA and 68% lower in IBD compared to DM (p<0.0001) after adjusting for traditional cardiovascular risk factors.

Conclusions

We developed and validated a CAD algorithm that performed well across diverse patient populations. The addition of NLP into the CAD algorithm improved the sensitivity of the algorithm, particularly in cohorts where the prevalence of CAD was low. Preliminary data suggest that CAD risk was significantly lower in RA and IBD compared to DM.     

High‐precision genetic mapping of behavioral traits in the diversity outbred mouse population

Historically our ability to identify genetic variants underlying complex behavioral traits in mice has been limited by low mapping resolution of conventional mouse crosses. The newly developed Diversity Outbred (DO) population promises to deliver improved resolution that will circumvent costly fine‐mapping studies. The DO is derived from the same founder strains as the Collaborative Cross (CC), including three wild‐derived strains. Thus the DO provides more allelic diversity and greater potential for discovery compared to crosses involving standard mouse strains. We have characterized 283 male and female DO mice using open‐field, light–dark box, tail‐suspension and visual‐cliff avoidance tests to generate 38 behavioral measures. We identified several quantitative trait loci (QTL) for these traits with support intervals ranging from 1 to 3 Mb in size. These intervals contain relatively few genes (ranging from 5 to 96). For a majority of QTL, using the founder allelic effects together with whole genome sequence data, we could further narrow the positional candidates. Several QTL replicate previously published loci. Novel loci were also identified for anxiety‐ and activity‐related traits. Half of the QTLs are associated with wild‐derived alleles, confirming the value to behavioral genetics of added genetic diversity in the DO. In the presence of wild‐alleles we sometimes observe behaviors that are qualitatively different from the expected response. Our results demonstrate that high‐precision mapping of behavioral traits can be achieved with moderate numbers of DO animals, representing a significant advance in our ability to leverage the mouse as a tool for behavioral genetics .     

Increased sensitivity to broadly neutralizing antibodies of end-stage disease R5 HIV-1 correlates with evolution in Env glycosylation and charge

Background

Induction of broadly neutralizing antibodies, such as the monoclonal antibodies IgGb12, 2F5 and 2G12, is the objective of most antibody-based HIV-1 vaccine undertakings. However, despite the relative conserved nature of epitopes targeted by these antibodies, mechanisms underlying the sensitivity of circulating HIV-1 variants to broadly neutralizing antibodies are not fully understood. Here we have studied sensitivity to broadly neutralizing antibodies of HIV-1 variants that emerge during disease progression in relation to molecular alterations in the viral envelope glycoproteins (Env), using a panel of primary R5 HIV-1 isolates sequentially obtained before and after AIDS onset.

Principal Findings

HIV-1 R5 isolates obtained at end-stage disease, after AIDS onset, were found to be more sensitive to neutralization by TriMab, an equimolar mix of the IgGb12, 2F5 and 2G12 antibodies, than R5 isolates from the chronic phase. The increased sensitivity correlated with low CD4⁺ T cell count at time of virus isolation and augmented viral infectivity. Subsequent sequence analysis of multiple env clones derived from the R5 HIV-1 isolates revealed that, concomitant with increased TriMab neutralization sensitivity, end-stage R5 variants displayed envelope glycoproteins (Envs) with reduced numbers of potential N-linked glycosylation sites (PNGS), in addition to increased positive surface charge. These molecular changes in Env also correlated to sensitivity to neutralization by the individual 2G12 monoclonal antibody (mAb). Furthermore, results from molecular modeling suggested that the PNGS lost at end-stage disease locate in the proximity to the 2G12 epitope.

Conclusions

Our study suggests that R5 HIV-1 variants with increased sensitivity to broadly neutralizing antibodies, including the 2G12 mAb, may emerge in an opportunistic manner during severe immunodeficiency as a consequence of adaptive molecular Env changes, including loss of glycosylation and gain of positive charge.