Using a Machine Learning Approach to Identify Low-Frequency and Rare FLG Alleles Associated with Remission of Atopic Dermatitis

Intrinsic Effects of Exposome in Atopic Dermatitis: Genomics, Epigenomics and Regulatory Layers

Atopic dermatitis (AD) or atopic eczema is an increasingly manifested inflammatory skin disorder of complex etiology which is modulated by both extrinsic and intrinsic factors. The exposome includes a person's lifetime exposures and their effects. We recently reviewed the extrinsic exposome's environmental risk factors that contribute to AD. The periods of pregnancy, infancy, and teenage years are recognized as crucial stages in the formation of AD, where the exposome leads to enduring impacts on the immune system. However, research is now focusing on the interactions between intrinsic pathways that are modulated by the extrinsic exposome, including genetic variation, epigenetic modifications, and signals, such as diet, stress, and microbiome interactions. As a result, immune dysregulation, barrier dysfunction, hormonal fluctuations, and skin microbiome dysbiosis are important factors contributing to AD development, and their in-depth understanding is crucial not only for AD treatment but also for similar inflammatory disorders.

bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease

Introduction

Atopic dermatitis (AD) is an allergic disease with extreme itching that bothers patients. However, diagnosing AD depends on clinicians' subjective judgment, which may be missed or misdiagnosed sometimes.

Methods

This paper establishes a medical prediction model for the first time on the basis of the enhanced particle swarm optimization (SRWPSO) algorithm and the fuzzy K-nearest neighbor (FKNN), called bSRWPSO-FKNN, which is practiced on a dataset related to patients with AD. In SRWPSO, the Sobol sequence is introduced into particle swarm optimization (PSO) to make the particle distribution of the initial population more uniform, thus improving the population's diversity and traversal. At the same time, this study also adds a random replacement strategy and adaptive weight strategy to the population updating process of PSO to overcome the shortcomings of poor convergence accuracy and easily fall into the local optimum of PSO. In bSRWPSO-FKNN, the core of which is to optimize the classification performance of FKNN through binary SRWPSO.

Results

To prove that the study has scientific significance, this paper first successfully demonstrates the core advantages of SRWPSO in well-known algorithms through benchmark function validation experiments. Secondly, this article demonstrates that the bSRWPSO-FKNN has practical medical significance and effectiveness through nine public and medical datasets.

Discussion

The 10 times 10-fold cross-validation experiments demonstrate that bSRWPSO-FKNN can pick up the key features of AD, including the content of lymphocytes (LY), Cat dander, Milk, Dermatophagoides Pteronyssinus/Farinae, Ragweed, Cod, and Total IgE. Therefore, the established bSRWPSO-FKNN method practically aids in the diagnosis of AD.

Uncommon variants in FLG2 and TCHHL1 are associated with remission of atopic dermatitis in a large longitudinal US cohort

Atopic dermatitis (AD) is a relapsing inflammatory skin disease; filaggrin (FLG) variation has been consistently associated with its pathogenesis. Filaggrin-2 (FLG2) and trichohyalin-like-1 (TCHHL1) are members of the same protein family (S100 fused-type proteins), are similar in structure to FLG, and may be involved in AD pathogenesis. We sought to evaluate the association between variation in FLG2, TCHHL1 and AD remission. We sequenced FLG2 and TCHHL1 in a longitudinal AD cohort using targeted capture-based massively parallel sequencing. Association between individual alleles and AD remission was evaluated with generalized estimating equations for binary outcomes. Association between groups of alleles and AD remission was evaluated using a genetic algorithm to group alleles. We identified two loss-of-function (LoF) mutations in FLG2 (Ser2377Ter, Arg2207Ter) and 2 LoF mutations in TCHHL1 (Gln656Ter, Gln294Ter), none of which were associated with AD remission. Common (MAF > 5%) alleles in FLG2 were similarly unassociated with AD. No common alleles in TCHHL1 were associated with AD remission after multiple testing correction. Among self-described whites, a group of 34 uncommon alleles in FLG2 were associated with increased AD remission (OR 7.64e17; 95% CI 4.41e17-1.32e18; adjusted p < 1.0e-16). Twelve uncommon alleles in TCHHL1 trended toward association with increased AD remission (OR 23.46; 95% CI 7.07-77.89; adjusted p = 0.064). Among self-described African Americans, 13 uncommon FLG2 alleles were associated with increased AD remission (OR 21.01; 95% CI 11.90-37.09; adjusted p < 1.0e-16). No TCHHL1 uncommon allele groups were associated with AD remission among African Americans. Our study supports the role of uncommon alleles in FLG2 and TCHHL1 in AD pathogenesis.