First Isolation of Hepatitis E Virus Genotype 4 in Europe through Swine Surveillance in the Netherlands and Belgium

Hepatitis E virus (HEV) genotypes 3 and 4 are a cause of human hepatitis and swine are considered the main reservoir. To study the HEV prevalence and characterize circulating HEV strains, fecal samples from swine in the Netherlands and Belgium were tested by RT-PCR. HEV prevalence in swine was 7–15%. The Dutch strains were characterized as genotype 3, subgroups 3a, 3c and 3f, closely related to sequences found in humans and swine earlier. The HEV strains found in Belgium belonged to genotypes 3f and 4b. The HEV genotype 4 strain was the first ever reported in swine in Europe and an experimental infection in pigs was performed to isolate the virus. The genotype 4 strain readily infected piglets and caused fever and virus shedding. Since HEV4 infections have been reported to run a more severe clinical course in humans this observation may have public health implications

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P = 9.2 x 10(-20)), ER-negative BC (P = 1.1 x 10(-13)), BRCA1-associated BC (P = 7.7 x 10(-16)) and triple negative BC (P-diff = 2 x 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P = 2 x 10(-3)) and ABHD8 (PPeer reviewe

Relative abundance of the goat milk microbiome bacteria at the genus level of each farm.

Each farm is represented by a duplicate sample. The top ten genera are indicated; all other genera are represented by the term “other”. Farm 1: R029, R030; Farm 2: R004, R005; Farm 3: R015, R016; Farm 4: R011, R012; Farm 5: R018, R019; Farm 6: R020, R021; Farm 7: R026, R027; Farm 8: R034, R035; Farm 9: R036, R037; Farm 10: R039, R040.</p

Box plot of the alpha-diversity; Observed species richness showing the variation in the total number of observed bacterial species (genera in our data).

The two management systems were not different, but the Fig shows that the variation is larger among artisanal farms as compared with the mainstream farms.</p

Tables S1-S5: Detailed information about farms and samples selected for Mainstream (M) / Artisanal (A), Bacterial colony forming units / ml milk, Breed, Number of goats on the farm, and sampling date, respectively.

Table S6: Reads per sample. Tables S7 and S8: Goat raw milk microbiome information at phylum and genera levels per sample and farm, respectively. (XLSX)</p

Figs S1-S10: Goat raw milk microbiome information of farms 1 to 10.

Fig S11: Principal Coordinates Analysis (PCoA, multidimensional scaling) analysis showing the similarities and dissimilarities of the goat milk microbiome among the farms. (DOCX)</p

The Shannon diversity index.

The box plot shows the variation among the farms in the bacterial composition of the goat milk. On average the number of bacterial genera is a little higher in the mainstream farms, while the variation is higher in the artisanal farms, but the management systems were not different. The Shannon diversity index varies from 1 to 6, where 1 means low and 6 means high balanced bacterial diversity.</p