Big Data Reveal Insights into Alopecia Areata Comorbidities.

Autoimmune diseases create a substantial burden of disease, and alopecia areata is among the more prevalent forms. Comorbidities are medical conditions that tend to occur together and may provide etiologic insights, suggest novel therapeutic strategies, and help patients and family members understand the risk of other health conditions. It is well established that having one autoimmune disease increases risk for others because of an underlying shared biology. Precision medicine initiatives are creating vast amounts of data that allow us to efficiently identify comorbidities. A survey across various datasets suggests that patients with autoimmune disease, and patients with alopecia areata in particular, may have comorbid neuropsychiatric and metabolic conditions.

Computational derivation of a molecular framework for hair follicle biology from disease genes.

Knowledge about genetic drivers of disease increases the efficiency of interpreting patient DNA sequence and helps to identify and prioritize biological points of intervention. Discoveries of genes with single mutations exerting substantial phenotypic impact reliably provide new biological insight, although such approaches tend to generate knowledge that is disjointed from the complexity of biological systems governed by elaborate networks. Here we sought to facilitate diagnostic sequencing for hair disorders and assess the underlying biology by compiling an archive of 684 genes discovered in studies of monogenic disorders and identifying molecular annotations enriched by them. To demonstrate utility for this dataset, we performed two data driven analyses. First, we extracted and analyzed data implicating enriched signaling pathways and identified previously unrecognized contributions from Hippo signaling. Second, we performed hierarchical clustering on the entire dataset to investigate the underlying causal structure of hair disorders. We identified 35 gene clusters representing genetically derived biological modules that provide a foundation for the development of a new disease taxonomy grounded in biology, rather than clinical presentations alone. This Resource will be useful for diagnostic sequencing in patients with diseases affecting the hair follicle, improved characterization of hair follicle biology, and methods development in precision medicine.

Patch Testing with Decyl and Lauryl Glucoside: How Well Does One Screen for Contact Allergic Reactions to the Other?

BACKGROUND: Alkyl glucoside surfactants, present in many cosmetic products, can cause allergic contact dermatitis. Decyl glucoside has been part of the North American Contact Dermatitis Group standard allergen panel since 2009. OBJECTIVES: This study aimed to identify rates and relevance of positive patch test reactions to decyl and lauryl glucosides and to determine how well one of these glucosides screens for contact allergic reactions to the other. METHODS: A retrospective analysis was performed on 897 patients suspected of having a cosmetic-related dermatitis and patch tested with both decyl and lauryl glucosides between 2009 and 2016. RESULTS: Forty-eight patients (5%) had positive reactions to decyl glucoside and/or lauryl glucoside. Among the alkyl glucoside-allergic patients, 65% had positive reactions to both decyl and lauryl glucosides. In 41% of cases, reactions were of definite or probable relevance. In approximately 55% of cases, reactions were of possible relevance. CONCLUSIONS: Sixty-five percent of glucoside-allergic patients exhibited co-reactions to decyl and lauryl glucosides. Thus, neither glucoside is an adequate screen for allergy to the other. Given that these reactions are often relevant, clinicians should patch test with decyl, lauryl, and other alkyl glucosides in cases of suspected cosmetic allergy.