Whole exome sequencing in Alopecia Areata identifies rare variants in KRT82.

Alopecia areata is a complex genetic disease that results in hair loss due to the autoimmune-mediated attack of the hair follicle. We previously defined a role for both rare and common variants in our earlier GWAS and linkage studies. Here, we identify rare variants contributing to Alopecia Areata using a whole exome sequencing and gene-level burden analyses approach on 849 Alopecia Areata patients compared to 15,640 controls. KRT82 is identified as an Alopecia Areata risk gene with rare damaging variants in 51 heterozygous Alopecia Areata individuals (6.01%), achieving genome-wide significance (p = 2.18E-07). KRT82 encodes a hair-specific type II keratin that is exclusively expressed in the hair shaft cuticle during anagen phase, and its expression is decreased in Alopecia Areata patient skin and hair follicles. Finally, we find that cases with an identified damaging KRT82 variant and reduced KRT82 expression have elevated perifollicular CD8 infiltrates. In this work, we utilize whole exome sequencing to successfully identify a significant Alopecia Areata disease-relevant gene, KRT82, and reveal a proposed mechanism for rare variant predisposition leading to disrupted hair shaft integrity.

Improved therapeutic efficacy of unmodified anti-tumor antibodies by immune checkpoint blockade and kinase targeted therapy in mouse models of melanoma.

The use of specific anti-tumor antibodies has transformed the solid cancer therapeutics landscape with the relative successes of therapies such as anti-HER2 in breast cancer, and anti-EGFR in HNSCC and colorectal cancer. However, these therapies result in toxicity and the emergence of resistant tumors. Here, we showed that removing immune suppression and enhancing stimulatory signals increased the anti-tumor activity of unmodified TA99 antibodies (anti-TYRP1) with a significant reduction of growth of solid tumors and lung metastases in mouse models of melanoma. Immune checkpoint blockade enhanced the efficacy of TA99, which was associated with greater CD8+/Foxp3+, NK1.1+ and dendritic cell infiltrates, suggestive of an increased anti-tumor innate and adaptive immune responses. Further, MEK inhibition in melanoma cell lines increased the expression of melanosomal antigens in vitro, and combining TA99 and MEKi in vivo resulted in enhanced tumor control. Moreover, we found an improved therapeutic effect when YUMM tumor-bearing mice were treated with TA99 combined with MEKi and immune checkpoint blockade (anti-PD1 and anti-CTLA4). Our findings suggest that MEKi induced an increased expression of tumor-associated antigens, which in combination with anti-tumor antibodies, generated a robust adaptive anti-tumor response that was sustained by immune checkpoint inhibition therapy. We postulate that combining anti-tumor antibodies with standard-of-care strategies such as immune checkpoint blockade or targeted therapy, will improve therapeutic outcomes in cancer.

A semi-supervised model to predict regulatory effects of genetic variants at single nucleotide resolution using massively parallel reporter assays.

MOTIVATION: Predicting regulatory effects of genetic variants is a challenging but important problem in functional genomics. Given the relatively low sensitivity of functional assays, and the pervasiveness of class imbalance in functional genomic data, popular statistical prediction models can sharply underestimate the probability of a regulatory effect. We describe here the presence-only model (PO-EN), a type of semi-supervised model, to predict regulatory effects of genetic variants at sequence-level resolution in a context of interest by integrating a large number of epigenetic features and massively parallel reporter assays (MPRAs). RESULTS: Using experimental data from a variety of MPRAs we show that the presence-only model produces better calibrated predicted probabilities and has increased accuracy relative to state-of-the-art prediction models. Furthermore, we show that the predictions based on pre-trained PO-EN models are useful for prioritizing functional variants among candidate eQTLs and significant SNPs at GWAS loci. In particular, for the costimulatory locus, associated with multiple autoimmune diseases, we show evidence of a regulatory variant residing in an enhancer 24.4 kb downstream of CTLA4, with evidence from capture Hi-C of interaction with CTLA4. Furthermore, the risk allele of the regulatory variant is on the same risk increasing haplotype as a functional coding variant in exon 1 of CTLA4, suggesting that the regulatory variant acts jointly with the coding variant leading to increased risk to disease. AVAILABILITY: The presence-only model is implemented in the R package 'PO.EN', freely available on CRAN. A vignette describing a detailed demonstration of using the proposed PO-EN model can be found on github at https://github.com/Iuliana-Ionita-Laza/PO.EN/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrative analysis of rare copy number variants and gene expression data in alopecia areata implicates an aetiological role for autophagy.

Alopecia areata (AA) is a highly prevalent autoimmune disease that attacks the hair follicle and leads to hair loss that can range from small patches to complete loss of scalp and body hair. Our previous linkage and genome-wide association studies (GWAS) generated strong evidence for aetiological contributions from inherited genetic variants at different population frequencies, including both rare mutations and common polymorphisms. Additionally, we conducted gene expression (GE) studies on scalp biopsies of 96 patients and controls to establish signatures of active disease. In this study, we performed an integrative analysis on these two datasets to test the hypothesis that rare CNVs in patients with AA could be leveraged to identify drivers of disease in our AA GE signatures. We analysed copy number variants (CNVs) in a case-control cohort of 673 patients with AA and 16 311 controls independent of the case-control cohort of 96 research participants used in our GE study. Using an integrative computational analysis, we identified 14 genes whose expression levels were altered by CNVs in a consistent direction of effect, corresponding to gene expression changes in lesional skin of patients. Four of these genes were affected by CNVs in three or more unrelated patients with AA, including ATG4B and SMARCA2, which are involved in autophagy and chromatin remodelling, respectively. Our findings identified new classes of genes with potential contributions to AA pathogenesis.