Citations

Celiac disease (CD) is an inflammatory disorder triggered by ingested gluten, causing immune-mediated damage to the small-intestinal mucosa. Gluten proteins are strikingly similar in amino acid composition and sequence to proline-rich proteins (PRPs) in human saliva. On the basis of this feature and their shared destination in the gastrointestinal tract, we hypothesized that salivary PRPs may modulate gluten-mediated immune responses in CD. Parotid salivary secretions were collected from CD patients, refractory CD patients, non-CD patients with functional gastrointestinal complaints, and healthy controls. Structural similarities of PRPs with gluten were probed with anti-gliadin antibodies. Immune responses to PRPs were investigated toward CD patient-derived peripheral blood mononuclear cells and in a humanized transgenic HLA-DQ2/DQ8 mouse model for CD. Anti-gliadin antibodies weakly cross-reacted with the abundant salivary amylase but not with PRPs. Likewise, the R5 antibody, recognizing potential antigenic gluten epitopes, showed negligible reactivity to salivary proteins from all groups. Inflammatory responses in peripheral blood mononuclear cells were provoked by gliadins whereas responses to PRPs were similar to control levels, and PRPs did not compete with gliadins in immune stimulation. In vivo, PRP peptides were well tolerated and nonimmunogenic in the transgenic HLA-DQ2/DQ8 mouse model. Collectively, although structurally similar to dietary gluten, salivary PRPs were nonimmunogenic in CD patients and in a transgenic HLA-DQ2/DQ8 mouse model for CD. It is possible that salivary PRPs play a role in tolerance induction to gluten early in life. Deciphering the structural basis for the lack of immunogenicity of salivary PRPs may further our understanding of the toxicity of gluten.

Abstract Background Renal imaging examinations provide high-resolution information about the anatomic structure of the kidneys and are used to measure total kidney volume (TKV) in autosomal dominant polycystic kidney disease (ADPKD) patients. TKV has become the gold-standard image biomarker for ADPKD progression at early stages of the disease and is used in clinical trials to characterize treatment efficacy. Automated methods to segment the kidneys and measure TKV are desirable because of the long time requirement for manual approaches such as stereology or planimetry tracings. However, ADPKD kidney segmentation is complicated by a number of factors, including irregular kidney shapes and variable tissue signal at the kidney borders. Methods We describe an image processing approach that overcomes these problems by using a baseline segmentation initialization to provide automatic segmentation of follow-up scans obtained years apart. We validated our approach using 20 patients with complete baseline and follow-up T1-weighted magnetic resonance images. Both manual tracing and stereology were used to calculate TKV, with two observers performing manual tracings and one observer performing repeat tracings. Linear correlation and Bland–Altman analysis were performed to compare the different approaches. Results Our automated approach measured TKV at a level of accuracy (mean difference ± standard error = 0.99 ± 0.79%) on par with both intraobserver (0.77 ± 0.46%) and interobserver variability (1.34 ± 0.70%) of manual tracings. All approaches had excellent agreement and compared favorably with ground-truth manual tracing with interobserver, stereological and automated approaches having 95% confidence intervals ∼±100 mL. Conclusions Our method enables fast, cost-effective and reproducible quantification of ADPKD progression that will facilitate and lower the costs of clinical trials in ADPKD and other disorders requiring accurate, longitudinal kidney quantification. In addition, it will hasten the routine use of TKV as a prognostic biomarker in ADPKD.

AbstractBackground Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM).Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms.Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility.Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.

Background: The lateral tibial posterior slope (LTPS) has been reported in multiple studies to correlate with an increased risk for native anterior cruciate ligament (ACL) tearing. To date, no study has examined the effect of an increased LTPS as measured on magnetic resonance imaging (MRI) on the likelihood of ACL graft failure. Hypothesis: An increased LTPS as measured on MRI would correlate with an increased risk for ACL graft failure. Study Design: Case-control study; Level of evidence, 3. Methods: Fifty-eight patients were initially identified who experienced graft failure after primary ACL reconstruction and underwent revision between 1998 and 2009. Exclusion criteria were clinical follow-up of less than 4 years, graft failure occurring greater than 2 years after primary surgery, skeletal immaturity, deep infection, lack of available preoperative MRI, and history of trauma to the proximal tibia. This left 35 patients with early (within 2 years) failure of primary ACL reconstruction. These patients were matched to 35 control participants who had undergone ACL reconstruction with a minimum of 4 years of clinical follow-up and no evidence of graft failure. Patients were matched by age, sex, date of primary surgery, and graft type. The LTPS was then determined on MRI in a blinded fashion. Results: The mean time to failure in patients in the study group was 1 year (range, 0.6-1.4 years). The mean follow-up of those in the matched control group was 6.9 years (range, 4.0-13.9 years). The mean LTPS in the early ACL failure group was found to be 8.4°, which was significantly larger than that in the control group at 6.5° ( P = .012). The odds ratio for graft failure considering a 2° increase in the LTPS was 1.6 (95% CI, 1.1-2.2) and continued to increase to 2.4 (95% CI, 1.2-5.0) and 3.8 (95% CI, 1.3-11.3) with 4° and 6° increases in the LTPS, respectively. No significant association was identified between graft type and graft failure. Conclusion: An increased LTPS is associated with an increased risk for early ACL graft failure, regardless of graft type. Orthopaedic surgeons should consider measuring the LTPS as part of the preoperative assessment of ACL-injured patients.

Background and Purpose— The ABC/2 score estimates intracerebral hemorrhage (ICH) volume, yet validations have been limited by small samples and inappropriate outcome measures. We determined accuracy of the ABC/2 score calculated at a specialized reading center (RC-ABC) or local site (site-ABC) versus the reference-standard computed tomography–based planimetry (CTP). Methods— In Minimally Invasive Surgery Plus Recombinant Tissue-Type Plasminogen Activator for Intracerebral Hemorrhage Evacuation-II (MISTIE-II), Clot Lysis Evaluation of Accelerated Resolution of Intraventricular Hemorrhage (CLEAR-IVH) and CLEAR-III trials. ICH volume was prospectively calculated by CTP, RC-ABC, and site-ABC. Agreement between CTP and ABC/2 was defined as an absolute difference up to 5 mL and relative difference within 20%. Determinants of ABC/2 accuracy were assessed by logistic regression. Results— In 4369 scans from 507 patients, CTP was more strongly correlated with RC-ABC ( r 2 =0.93) than with site-ABC ( r 2 =0.87). Although RC-ABC overestimated CTP-based volume on average (RC-ABC, 15.2 cm 3 ; CTP, 12.7 cm3), agreement was reasonable when categorized into mild, moderate, and severe ICH (κ=0.75; P <0.001). This was consistent with overestimation of ICH volume in 6 of 8 previous studies. Agreement with CTP was greater for RC-ABC (84% within 5 mL; 48% of scans within 20%) than for site-ABC (81% within 5 mL; 41% within 20%). RC-ABC had moderate accuracy for detecting ≥5 mL change in CTP volume between consecutive scans (sensitivity, 0.76; specificity, 0.86) and was more accurate with smaller ICH, thalamic hemorrhage, and homogeneous clots. Conclusions— ABC/2 scores at local or central sites are sufficiently accurate to categorize ICH volume and assess eligibility for the CLEAR-III and MISTIE III studies and moderately accurate for change in ICH volume. However, accuracy decreases with large, irregular, or lobar clots. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: MISTIE-II NCT00224770; CLEAR-III NCT00784134.

Abstract Objective To review and evaluate available software tools for electronic health record–driven phenotype authoring in order to identify gaps and needs for future development. Materials and Methods Candidate phenotype authoring tools were identified through (1) literature search in four publication databases (PubMed, Embase, Web of Science, and Scopus) and (2) a web search. A collection of tools was compiled and reviewed after the searches. A survey was designed and distributed to the developers of the reviewed tools to discover their functionalities and features. Results Twenty-four different phenotype authoring tools were identified and reviewed. Developers of 16 of these identified tools completed the evaluation survey (67% response rate). The surveyed tools showed commonalities but also varied in their capabilities in algorithm representation, logic functions, data support and software extensibility, search functions, user interface, and data outputs. Discussion Positive trends identified in the evaluation included: algorithms can be represented in both computable and human readable formats; and most tools offer a web interface for easy access. However, issues were also identified: many tools were lacking advanced logic functions for authoring complex algorithms; the ability to construct queries that leveraged un-structured data was not widely implemented; and many tools had limited support for plug-ins or external analytic software. Conclusions Existing phenotype authoring tools could enable clinical researchers to work with electronic health record data more efficiently, but gaps still exist in terms of the functionalities of such tools. The present work can serve as a reference point for the future development of similar tools.

Trafficking from bedside to bench Typically in translational research, a discovery in cell or molecular biology is later exploited to improve patient care. Occasionally, information flows in the opposite direction. Lo et al. found that patients with an autoimmune disorder caused by deficiency of a protein called LRBA responded dramatically to the drug abatacept (see the Perspective by Sansom). Abatacept contains a segment of a potent inhibitory immune receptor, CTLA4. Experiments prompted by this observation revealed the relationship between the two proteins: LRBA controls the intracellular trafficking and degradation of CTLA4. This information may further improve patient care, because other clinically approved drugs have the desired mechanism of action with potentially fewer side effects. Science , this issue p. 436 ; see also p. 377