The development of food allergy has been reported to be related with the changes in the gut microbiome, however the specific microbe associated with the pathogenesis of food allergy remains elusive. This study aimed to comprehensively characterize the gut microbiome and identify individual or group gut microbes relating to food-allergy using 16S rRNA gene sequencing with network analysis. Faecal samples were collected from children with IgE-mediated food allergies (n = 33) and without food allergy (n = 27). Gut microbiome was profiled by 16S rRNA gene sequencing. OTUs obtained from 16S rRNA gene sequencing were then used to construct a co-abundance network using Weighted Gene Co-expression Network Analysis (WGCNA) and mapped onto Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We identified a co-abundance network module to be positively correlated with IgE-mediated food allergy and this module was characterized by a hub taxon, namely Ruminococcaceae UCG-002 (phylum Firmicutes). Functional pathway analysis of all the gut microbiome showed enrichment of methane metabolism and glycerolipid metabolism in the gut microbiome of food-allergic children and enrichment of ubiquinone and other terpenoid-quinone biosynthesis in the gut microbiome of non-food allergic children. We concluded that Ruminococcaceae UCG-002 may play determinant roles in gut microbial community structure and function leading to the development of IgE-mediated food allergy.

A family history of ovarian or breast cancer is the strongest risk factor for epithelial ovarian cancer (EOC). Germline deleterious variants in the BRCA1 and BRCA2 genes confer EOC risks by age 80, of 44% and 17% respectively. The mismatch repair genes, particularly MSH2 and MSH6, are also EOC susceptibility genes. Several other DNA repair genes, BRIP1, RAD51C, RAD51D, and PALB2, have been identified as moderate risk EOC genes. EOC has five main histotypes; high-grade serous (HGS), low-grade serous (LGS), clear cell (CCC), endometrioid (END), and mucinous (MUC). This review examines the current understanding of the contribution of rare genetic variants to EOC, focussing on providing frequency data for each histotype. We provide an overview of frequency and risk for pathogenic variants in the known susceptibility genes as well as other proposed genes. We also describe the progress to-date to understand the role of missense variants and the different breast and ovarian cancer risks for each gene. Identification of susceptibility genes have clinical impact by reducing disease-associated mortality through improving risk prediction, with the possibility of prevention strategies, and developing new targeted treatments and these clinical implications are also discussed.

Background: Malaria is a deadly disease caused by Plasmodium spp. Several blood phenotypes have been associated with malarial resistance, which suggests a genetic component to immune protection. Methods: One hundred and eighty-seven single nucleotide polymorphisms (SNPs) in 37 candidate genes were genotyped and investigated for associations with clinical malaria in a longitudinal cohort of 349 infants from Manhiça, Mozambique, in a randomized controlled clinical trial (RCT) (AgeMal, NCT00231452). Malaria candidate genes were selected according to involvement in known malarial haemoglobinopathies, immune, and pathogenesis pathways. Results: Statistically significant evidence was found for the association of TLR4 and related genes with the incidence of clinical malaria (p = 0.0005). These additional genes include ABO, CAT, CD14, CD36, CR1, G6PD, GCLM, HP, IFNG, IFNGR1, IL13, IL1A, IL1B, IL4R, IL4, IL6, IL13, MBL, MNSOD, and TLR2. Of specific interest, the previously identified TLR4 SNP rs4986790 and the novel finding of TRL4 SNP rs5030719 were associated with primary cases of clinical malaria. Conclusions: These findings highlight a potential central role of TLR4 in clinical malarial pathogenesis. This supports the current literature and suggests that further research into the role of TLR4, as well as associated genes, in clinical malaria may provide insight into treatment and drug development.