Autoimmune alleles at the major histocompatibility locus modify melanoma susceptibility.

Autoimmunity and cancer represent two different aspects of immune dysfunction. Autoimmunity is characterized by breakdowns in immune self-tolerance, while impaired immune surveillance can allow for tumorigenesis. The class I major histocompatibility complex (MHC-I), which displays derivatives of the cellular peptidome for immune surveillance by CD8+ T cells, serves as a common genetic link between these conditions. As melanoma-specific CD8+ T cells have been shown to target melanocyte-specific peptide antigens more often than melanoma-specific antigens, we investigated whether vitiligo- and psoriasis-predisposing MHC-I alleles conferred a melanoma-protective effect. In individuals with cutaneous melanoma from both The Cancer Genome Atlas (n = 451) and an independent validation set (n = 586), MHC-I autoimmune-allele carrier status was significantly associated with a later age of melanoma diagnosis. Furthermore, MHC-I autoimmune-allele carriers were significantly associated with decreased risk of developing melanoma in the Million Veteran Program (OR = 0.962, p = 0.024). Existing melanoma polygenic risk scores (PRSs) did not predict autoimmune-allele carrier status, suggesting these alleles provide orthogonal risk-relevant information. Mechanisms of autoimmune protection were neither associated with improved melanoma-driver mutation association nor improved gene-level conserved antigen presentation relative to common alleles. However, autoimmune alleles showed higher affinity relative to common alleles for particular windows of melanocyte-conserved antigens and loss of heterozygosity of autoimmune alleles caused the greatest reduction in presentation for several conserved antigens across individuals with loss of HLA alleles. Overall, this study presents evidence that MHC-I autoimmune-risk alleles modulate melanoma risk unaccounted for by current PRSs.

Low-Protein Diets Composed of Protein Recovered from Food Processing Supported Growth, but Induced Mild Hepatic Steatosis Compared with a No-Protein Diet in Young Female Rats.

BACKGROUND: Living in low-income countries often restricts the consumption of adequate protein and animal protein. OBJECTIVES: This study aimed to investigate the effects of feeding low-protein diets on growth and liver health using proteins recovered from animal processing. METHODS: Female Sprague-Dawley rats (aged 28 d) were randomly assigned (n = 8 rats/group) to be fed standard purified diets with 0% or 10% kcal protein that was comprised of either carp, whey, or casein. RESULTS: Rats that were fed low-protein diets showed higher growth but developed mild hepatic steatosis compared to rats that were fed a no-protein diet, regardless of the protein source. Real-time quantitative polymerase chain reactions targeting the expression of genes involved in liver lipid homeostasis were not significantly different among groups. Global RNA-sequencing technology identified 9 differentially expressed genes linked to folate-mediated 1-carbon metabolism, endoplasmic reticulum (ER) stress, and metabolic diseases. Canonical pathway analysis revealed that mechanisms differed depending on the protein source. ER stress and dysregulated energy metabolism were implicated in hepatic steatosis in carp- and whey-fed rats. In contrast, impaired liver one-carbon methylations, lipoprotein assembly, and lipid export were implicated in casein-fed rats. CONCLUSIONS: Carp sarcoplasmic protein showed comparable results to commercially available casein and whey protein. A better understanding of the molecular mechanisms in hepatic steatosis development can assist formulation of proteins recovered from food processing into a sustainable source of high-quality protein.

Predictive analyses of regulatory sequences with EUGENe.

Deep learning has become a popular tool to study cis-regulatory function. Yet efforts to design software for deep-learning analyses in regulatory genomics that are findable, accessible, interoperable and reusable (FAIR) have fallen short of fully meeting these criteria. Here we present elucidating the utility of genomic elements with neural nets (EUGENe), a FAIR toolkit for the analysis of genomic sequences with deep learning. EUGENe consists of a set of modules and subpackages for executing the key functionality of a genomics deep learning workflow: (1) extracting, transforming and loading sequence data from many common file formats; (2) instantiating, initializing and training diverse model architectures; and (3) evaluating and interpreting model behavior. We designed EUGENe as a simple, flexible and extensible interface for streamlining and customizing end-to-end deep-learning sequence analyses, and illustrate these principles through application of the toolkit to three predictive modeling tasks. We hope that EUGENe represents a springboard towards a collaborative ecosystem for deep-learning applications in genomics research.

From Acne to Black Heel: Common Skin Injuries in Sports.

In brief Sports activity exposes the skin brief to various stresses, including friction and pressure from clothing and equipment; prolonged wetness from perspiration; and sunlight, cold, and heat. A variety of injuries can result. Briefly described here are the diagnosis, treatment, and prevention of some of the most common ones: sunburn and sun-induced aging, frostnip and frostbite, acne mechanica, calluses and corns, friction blisters, jogger's nipples, and black heel.