Factors influencing somatic cell counts and bacterial contamination in unpasteurized milk obtained from water buffalo in Bangladesh.

Little has been published on the factors influencing the safety and quality of milk derived from water buffalo in Bangladesh. This study aims to describe the milk hygiene parameters and milk chain characteristics of unpasteurized raw milk sold to consumers in order to improve milk hygiene. A quantitative study design evaluated somatic cell counts, total bacterial counts, and specific gram-negative (Enterobacteria) and gram-positive (staphylococci) pathogens in 377 aseptically collected milk samples. Samples were collected at multiple nodes along the buffalo milk value chain: 122 bulk tank milk samples were collected at the farm level, 109 milk samples at the middlemen level, and 111 milk samples at the milk collection centers. In addition, 35 samples were taken from various milk products at the retail level. It was found that progressively increasing somatic cell counts and bacterial counts, including potential pathogens, occurred along the milk chain. A seasonal increase in spring was found, varying based on the farming system (semi-intensive versus intensive). Other factors included water purity and cleanliness of containers, mixing buffalo and cow's milk, and the location of the water buffalo milk producer (coastal or river basin). This study demonstrated how improving udder health and milk hygiene along the water buffalo milk value chain would increase the safety and quality of water buffalo milk in the study area.

Occurrence and aetiology of subclinical mastitis in water buffalo in Bangladesh.

Subclinical mastitis (SCM) in water buffalo is a production disease associated with decreased milk yield and impaired milk quality and safety. Water buffalo is an important livestock species in Bangladesh, but information about the occurrence and aetiology of SCM in this species is scarce. A cross-sectional study was conducted as part of the Udder Health Bangladesh Programme to (i) determine the occurrence of SCM and bulk milk somatic cell count (SCC) in water buffalo in Bangladesh, (ii) identify pathogens causing SCM and (iii) evaluate penicillin resistance in isolated staphylococci strains. Sixteen buffalo farms in the Bagerhat and Noakhali regions of Bangladesh were selected for study and a bulk milk sample was collected from each farm. In addition, 299 udder quarter milk samples were collected from 76 animals. The bulk milk samples were assessed by direct SCC and the quarter milk samples by California mastitis test (CMT). The occurrence of SCM calculated at quarter and animal level was 42.5 and 81.6%, respectively. Milk samples from 108 CMT-positive quarters in 48 animals and 38 randomly selected CMT-negative quarters in 24 animals were investigated using bacteriological culture. Estimated mean bulk milk SCC was 195 000 cells/ml milk (range 47 000- 587 000 cells/ml milk). On culture, estimated quarter-level intramammary infection (IMI) was 40.4%. The identity of isolated bacteria was confirmed by MALDI-TOF mass spectrometry. Non-aureus staphylococci (NAS) were the most common pathogens (24.7%) and, among 36 NAS tested, 36.1% were resistant to penicillin. Thus there was high occurrence of SCM on the study farms, with relatively high penicillin resistance in NAS. Further studies are needed to identify underlying risk factors and develop an udder health control strategy for water buffalo in Bangladesh.

Cell-type-specific meQTLs extend melanoma GWAS annotation beyond eQTLs and inform melanocyte gene-regulatory mechanisms.

Although expression quantitative trait loci (eQTLs) have been powerful in identifying susceptibility genes from genome-wide association study (GWAS) findings, most trait-associated loci are not explained by eQTLs alone. Alternative QTLs, including DNA methylation QTLs (meQTLs), are emerging, but cell-type-specific meQTLs using cells of disease origin have been lacking. Here, we established an meQTL dataset by using primary melanocytes from 106 individuals and identified 1,497,502 significant cis-meQTLs. Multi-QTL colocalization with meQTLs, eQTLs, and mRNA splice-junction QTLs from the same individuals together with imputed methylome-wide and transcriptome-wide association studies identified candidate susceptibility genes at 63% of melanoma GWAS loci. Among the three molecular QTLs, meQTLs were the single largest contributor. To compare melanocyte meQTLs with those from malignant melanomas, we performed meQTL analysis on skin cutaneous melanomas from The Cancer Genome Atlas (n = 444). A substantial proportion of meQTL probes (45.9%) in primary melanocytes is preserved in melanomas, while a smaller fraction of eQTL genes is preserved (12.7%). Integration of melanocyte multi-QTLs and melanoma meQTLs identified candidate susceptibility genes at 72% of melanoma GWAS loci. Beyond GWAS annotation, meQTL-eQTL colocalization in melanocytes suggested that 841 unique genes potentially share a causal variant with a nearby methylation probe in melanocytes. Finally, melanocyte trans-meQTLs identified a hotspot for rs12203592, a cis-eQTL of a transcription factor, IRF4, with 131 candidate target CpGs. Motif enrichment and IRF4 ChIP-seq analysis demonstrated that these target CpGs are enriched in IRF4 binding sites, suggesting an IRF4-mediated regulatory network. Our study highlights the utility of cell-type-specific meQTLs.

Successful use of whole genome amplified DNA from multiple source types for high-density Illumina SNP microarrays.

BACKGROUND: The recommended genomic DNA input requirements for whole genome single nucleotide polymorphism microarrays can limit the scope of molecular epidemiological studies. We performed a large-scale evaluation of whole genome amplified DNA as input into high-density, whole-genome Illumina® Infinium® SNP microarray. RESULTS: Overall, 6622 DNA samples from 5970 individuals were obtained from three distinct biospecimen sources and genotyped using gDNA and/or wgaDNA inputs. When genotypes from the same individual were compared with standard, native gDNA input amount, we observed 99.94% mean concordance with wgaDNA input. CONCLUSIONS: Our results demonstrate that carefully conducted studies with wgaDNA inputs can yield high-quality genotyping results. These findings should enable investigators to consider expansion of ongoing studies using high-density SNP microarrays, currently challenged by small amounts of available DNA.

A comprehensive candidate gene approach identifies genetic variation associated with osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is a bone malignancy which occurs primarily in adolescents. Since it occurs during a period of rapid growth, genes important in bone formation and growth are plausible modifiers of risk. Genes involved in DNA repair and ribosomal function may contribute to OS pathogenesis, because they maintain the integrity of critical cellular processes. We evaluated these hypotheses in an OS association study of genes from growth/hormone, bone formation, DNA repair, and ribosomal pathways. METHODS: We evaluated 4836 tag-SNPs across 255 candidate genes in 96 OS cases and 1426 controls. Logistic regression models were used to estimate the odds ratios (OR) and 95% confidence intervals (CI). RESULTS: Twelve SNPs in growth or DNA repair genes were significantly associated with OS after Bonferroni correction. Four SNPs in the DNA repair gene FANCM (ORs 1.9-2.0, P = 0.003-0.004) and 2 SNPs downstream of the growth hormone gene GH1 (OR 1.6, P = 0.002; OR 0.5, P = 0.0009) were significantly associated with OS. One SNP in the region of each of the following genes was significant: MDM2, MPG, FGF2, FGFR3, GNRH2, and IGF1. CONCLUSIONS: Our results suggest that several SNPs in biologically plausible pathways are associated with OS. Larger studies are required to confirm our findings.

Telomere length and variation in telomere biology genes in individuals with osteosarcoma.

Osteosarcoma, the most common primary bone tumor, occurs most frequently in adolescents. Chromosomal aneuploidy is common in osteosarcoma cells, suggesting underlying chromosomal instability. Telomeres, located at chromosome ends, are essential for genomic stability; several studies have suggested that germline telomere length (TL) is associated with cancer risk. We hypothesized that TL and/or common genetic variation in telomere biology genes may be associated with risk of osteosarcoma. We investigated TL in peripheral blood DNA and 713 single nucleotide polymorphisms (SNPs) from 39 telomere biology genes in 98 osteosarcoma cases and 69 orthopedic controls. For the genotyping component, we added 1363 controls from the Prostate, Lung, Colorectal, and Ovarian Cancer ScreeningTrial. Short TL was not associated with osteosarcoma risk overall (OR 1.39, P=0.67), although there was a statistically significant association in females (OR 4.35, 95% Cl 1.20-15.74, P=0.03). Genotype analyses identified seven SNPs in TERF1 significantly associated with osteosarcoma risk after Bonferroni correction by gene. These SNPs were highly linked and associated with a reduced risk of osteosarcoma (OR 0.48-0.53, P=0.0001-0.0006). We also investigated associations between TL and telomere gene SNPs in osteosarcoma cases and orthopedic controls. Several SNPs were associated with TL prior to Bonferroni correction; one SNP in NOLA2 and one in MEN1 were marginally non-significant after correction (P(adj)=0.057 and 0.066, respectively). This pilot-study suggests that females with short telomeres may be at increased risk of osteosarcoma, and that SNPs in TERF1 are inversely associated with osteosarcoma risk.

Genetic variation at chromosome 8q24 in osteosarcoma cases and controls.

Osteosarcoma is a primary bone malignancy that typically occurs during the pubertal growth spurt. Only a few small association studies have evaluated common germ line variation in individuals with osteosarcoma. The 8q24 chromosomal region contains several loci that are associated with risk of many different cancers. We conducted an association study of common single-nucleotide polymorphisms (SNPs) across 8q24 to explore the role this region may play in osteosarcoma risk. We genotyped 214 tag SNPs in 99 osteosarcoma cases and 1430 controls (65 controls from a hospital-based case-control study and 1365 controls from a population-based study). Additive, dominant and recessive genetic models were evaluated using unconditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Analyses of nine SNPs previously associated with cancer did not show strong statistically significant associations. Of the remaining 205 SNPs, 7 were statistically significant (P