Novel HLA associations with outcomes of Mycobacterium tuberculosis exposure and sarcoidosis in individuals of African ancestry using nearest-neighbor feature selection.

Tuberculosis and sarcoidosis are inflammatory diseases characterized by granulomas that may occur in any organ but are often found in the lung. The panoply of classical human leukocyte antigen (HLA) alleles associated with occurrence and/or severity of both diseases varies considerably across studies. This heterogeneity of results, due to variation in factors like ancestry and disease subphenotype, as well as the use of simple modeling strategies to elucidate likely complex relationships, has made conclusions about underlying commonalities difficult. Here we perform HLA association analyses in individuals of African ancestry, using a greater resolution to include subphenotypes of disease and employing more comprehensive analytical techniques. Using a novel application of nearest-neighbor feature selection to score allelic importance, we investigated HLA allele association with Mycobacterium tuberculosis exposure outcomes in the first analysis of both latent Mycobacterium tuberculosis infection and active disease compared with those who, despite long-term exposure to active index cases, have neither positive diagnostic tests nor display clinical symptoms. We also compared persistent to resolved sarcoidosis. This led to the identification of novel HLA associations and evidence of main effects and interaction effects. We found strikingly similar main effects and interaction effects at HLA-DRB1, -DQB1, and -DPB1 in those resistant to tuberculosis (either latent or active) and persistent sarcoidosis.

Multiple Correspondence Analysis and HLA-Associations of Organ Involvement in a Large Cohort of African-American and European-American Patients with Sarcoidosis.

Sarcoidosis is a systemic granulomatous disease with predominant pulmonary involvement and vast heterogeneity of clinical manifestations and disease outcomes. African American (AA) patients suffer greater morbidity and mortality. Using Multiple Correspondence Analysis, we identified seven clusters of organ involvement in European American (EA; n = 385) patients which were similar to those previously described in a Pan-European (GenPhenReSa) and a Spanish cohort (SARCOGEAS). In contrast, AA (n = 987) had six, less well-defined and overlapping clusters with little similarity to the cluster identified in the EA cohort evaluated at the same U.S. institutions. Association of cluster membership with two-digit HLA-DRB1 alleles demonstrated ancestry-specific patterns of association and replicated known HLA effects.These results further support the notion that genetically influenced immune risk profiles, which differ based on ancestry, play a role in phenotypic heterogeneity. Dissecting such risk profiles will move us closer to personalized medicine for this complex disease.

Nearest-neighbor Projected-Distance Regression (NPDR) for detecting network interactions with adjustments for multiple tests and confounding.

SUMMARY: Machine learning feature selection methods are needed to detect complex interaction-network effects in complicated modeling scenarios in high-dimensional data, such as GWAS, gene expression, eQTL and structural/functional neuroimage studies for case-control or continuous outcomes. In addition, many machine learning methods have limited ability to address the issues of controlling false discoveries and adjusting for covariates. To address these challenges, we develop a new feature selection technique called Nearest-neighbor Projected-Distance Regression (NPDR) that calculates the importance of each predictor using generalized linear model regression of distances between nearest-neighbor pairs projected onto the predictor dimension. NPDR captures the underlying interaction structure of data using nearest-neighbors in high dimensions, handles both dichotomous and continuous outcomes and predictor data types, statistically corrects for covariates, and permits statistical inference and penalized regression. We use realistic simulations with interactions and other effects to show that NPDR has better precision-recall than standard Relief-based feature selection and random forest importance, with the additional benefit of covariate adjustment and multiple testing correction. Using RNA-Seq data from a study of major depressive disorder (MDD), we show that NPDR with covariate adjustment removes spurious associations due to confounding. We apply NPDR to eQTL data to identify potentially interacting variants that regulate transcripts associated with MDD and demonstrate NPDR's utility for GWAS and continuous outcomes. AVAILABILITY AND IMPLEMENTATION: Available at: https://insilico.github.io/npdr/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Oral Potassium Malabsorption Following Bariatric Surgery.

Bariatric surgery is one of the most effective long-term solutions for treating obesity due to its sustained weight loss and reduction of obesity-related comorbidities. However, nutritional deficiencies are common due to the alteration of the anatomy and physiology of the gastrointestinal tract. These include the malabsorption of macronutrients, vitamins, minerals, trace elements, and drugs. In this report, we present the case of a female patient who underwent Roux-en-Y gastric bypass surgery and subsequently developed exclusive potassium malabsorption refractory to oral replenishment.

Genetics of neurosarcoidosis.

Sarcoidosis is a systemic, inflammatory, granulomatous disease characterized by great variability in organ involvement, clinical course, and severity. While pulmonary manifestations are almost universal, the central and peripheral nervous systems can also be affected. Neurosarcoidosis occurs in ∼5-15% of cases and is among the manifestations with the highest morbidity and mortality. It is known that sarcoidosis has genetic underpinnings and while multiple studies aimed at identifying associations to sarcoidosis susceptibility and prognosis, very few studies have focused on neurosarcoidosis. This review summarizes the genetic studies to date, compares and contrasts those findings with other genetic effects in sarcoidosis, and offers ideas for moving the field forward.

Primary Peritoneal Mesothelioma: Diagnostic Challenges of This Lethal Imposter.

Primary Peritoneal Mesothelioma is a rapidly aggressive and rare neoplasm that arises from the lining of mesothelial cells of the peritoneum and spreads extensively within the confines of the abdominal cavity. The pathogenesis of all forms of mesothelioma is strongly associated with industrial pollutants, of which asbestos is the principal carcinogen. Characteristically, asbestos exposure has a strong relationship with mesothelioma of the pleura, but the peritoneal cavity is the second most commonly affected site. Additionally, in contrast to pleural mesothelioma, which has a male predominance (male-female ratio of between four and five to one), women comprise approximately one-half of all cases of malignant peritoneal mesothelioma. A thorough history of occupational/paraoccupational exposure along with histopathology is the key to timely diagnosis and treatment.

Theoretical properties of distance distributions and novel metrics for nearest-neighbor feature selection.

The performance of nearest-neighbor feature selection and prediction methods depends on the metric for computing neighborhoods and the distribution properties of the underlying data. Recent work to improve nearest-neighbor feature selection algorithms has focused on new neighborhood estimation methods and distance metrics. However, little attention has been given to the distributional properties of pairwise distances as a function of the metric or data type. Thus, we derive general analytical expressions for the mean and variance of pairwise distances for Lq metrics for normal and uniform random data with p attributes and m instances. The distribution moment formulas and detailed derivations provide a resource for understanding the distance properties for metrics and data types commonly used with nearest-neighbor methods, and the derivations provide the starting point for the following novel results. We use extreme value theory to derive the mean and variance for metrics that are normalized by the range of each attribute (difference of max and min). We derive analytical formulas for a new metric for genetic variants, which are categorical variables that occur in genome-wide association studies (GWAS). The genetic distance distributions account for minor allele frequency and the transition/transversion ratio. We introduce a new metric for resting-state functional MRI data (rs-fMRI) and derive its distance distribution properties. This metric is applicable to correlation-based predictors derived from time-series data. The analytical means and variances are in strong agreement with simulation results. We also use simulations to explore the sensitivity of the expected means and variances in the presence of correlation and interactions in the data. These analytical results and new metrics can be used to inform the optimization of nearest neighbor methods for a broad range of studies, including gene expression, GWAS, and fMRI data.

Recurrent Acute Pancreatitis and Superior Mesenteric Venous Thrombosis - Cause or Course.

The management of pancreatitis can be daunting, especially when associated with other comorbidities. These complexities in management are conflicting in the presence of comorbidities with a similar presentation, such as abdominal pain. Acute pancreatitis (AP) has been associated with mesenteric thrombosis but less commonly with superior mesenteric vein thrombosis (SMVT) as a causal or complicating dilemma. This case report describes the careful intrigues and overlaps in presentation. Furthermore, this paper presents a dilemma in that contrast-enhanced computed tomography (CT) may not be recommended in the early stage of diagnosis of AP according to the 2013 American College of Gastroenterology (ACG) guideline, but SMVT, which can be fatal, sometimes, complicates AP, and contrast-enhanced CT is important in its diagnosis. This paper attempts to address this dilemma. Managing these two potentially fatal pathologies requires promptness and thoughtfulness in averting a deadly outcome. Because SMVT is fatal, in this paper, we reiterate the use of contrast-enhanced CT in the early stages of the management of AP. Fatal complications from AP should not be missed. Although contrast-enhanced CT is not recommended in the early stages of diagnosis of AP in the ACG guideline, fatal complications such as SMVT can be avoided.