Saving Lives: The Principle of Distinction and the Realities of Modern War

WOS: 000332942700005PubMed ID: 24778561In this study, we assessed the feasibility of fetal RhD genotyping by analysis of cell-free fetal DNA(cffDNA) extracted from plasma samples of Rhesus (Rh) D-negative pregnant women by using real-time polymerase chain reaction (PCR). Fetal genotyping was performed on 30 RhD-negative women between 9 and 39 weeks of gestation who were referred to us for invasive testing [amniocentesis/chorionic villi sampling (CVS)]. The fetal RHD genotype was determined based on real-time PCR method. Exons 7 and 10 of the RHD and SRY genes were targeted. Among the pregnant women, 12 were carrying male and 17 were carrying female fetuses. Out of 29 pregnant women, 21 had RhD-positive and nine had RhD-negative fetuses. One sample) case 12, whose blood group was found to be AB Rh [+] (was excluded due to controversial results from repeated serological analyses. All prenatal results were in concordance with postnatal RhD status and fetal sex without false-positive or -negative results. Performing real-time PCR on cffDNA showed accurate, efficient and reliable results, allowing rapid and high throughput non invasive determination of fetal sex and RhD status in clinical samples

Identifying hypothetical genetic influences on complex disease phenotypes

<p>Abstract</p> <p>Background</p> <p>Statistical interactions between disease-associated loci of complex genetic diseases suggest that genes from these regions are involved in a common mechanism impacting, or impacted by, the disease. The computational problem we address is to discover relationships among genes from these interacting regions that may explain the observed statistical interaction and the role of these genes in the disease phenotype.</p> <p>Results</p> <p>We describe a heuristic algorithm for generating hypothetical gene relationships from loci associated with a complex disease phenotype. This approach, called Prioritizing Disease Genes by Analysis of Common Elements (PDG-ACE), mines biomedical keywords from text descriptions of genes and uses them to relate genes close to disease-associated loci. A keyword common to, and significantly over-represented in, a pair of gene descriptions may represent a preliminary hypothesis about the biological relationship between the genes, and suggest the role the genes play in the disease phenotype.</p> <p>Conclusion</p> <p>Our experimentation shows that the approach finds previously published relationships, while failing to find relationships that don't exist. The results also indicate that the approach is robust to differences in keyword vocabulary. We outline a brief case study in which results from a recently published Type 2 Diabetes association study are used to identify potential hypotheses.</p

Combined effect of CCND1 and COMT polymorphisms and increased breast cancer risk

<p>Abstract</p> <p>Background</p> <p>Estrogens are crucial tumorigenic hormones, which impact the cell growth and proliferation during breast cancer development. Estrogens are metabolized by a series of enzymes including COMT, which converts catechol estrogens into biologically non-hazardous methoxyestrogens. Several studies have also shown the relationship between estrogen and cell cycle progression through activation of CCND1 transcription.</p> <p>Methods</p> <p>In this study, we have investigated the independent and the combined effects of commonly occurring CCND1 (Pro241Pro, A870G) and COMT (Met108/158Val) polymorphisms to breast cancer risk in two independent Caucasian populations from Ontario (1228 breast cancer cases and 719 population controls) and Finland (728 breast cancer cases and 687 population controls). Both COMT and CCND1 polymorphisms have been previously shown to impact on the enzymatic activity of the coded proteins.</p> <p>Results</p> <p>Here, we have shown that the high enzymatic activity genotype of CCND1^High(AA) was associated with increased breast cancer risk in both the Ontario [OR: 1.3, 95%CI (1.0–1.69)] and the Finland sample [OR: 1.4, 95%CI (1.01–1.84)]. The heterozygous COMT^Medium(MetVal) and the high enzymatic activity of COMT^High(ValVal) genotype was also associated with breast cancer risk in Ontario cases, [OR: 1.3, 95%CI (1.07–1.68)] and [OR: 1.4, 95%CI (1.07–1.81)], respectively. However, there was neither a statistically significant association nor increased trend of breast cancer risk with COMT^High(ValVal) genotypes in the Finland cases [OR: 1.0, 95%CI (0.73–1.39)]. In the combined analysis, the higher activity alleles of the COMT and CCND1 is associated with increased breast cancer risk in both Ontario [OR: <b>2.22</b>, 95%CI (1.49–3.28)] and Finland [OR: <b>1.73</b>, 95%CI (1.08–2.78)] populations studied. The trend test was statistically significant in both the Ontario and Finland populations across the genotypes associated with increasing enzymatic activity.</p> <p>Conclusion</p> <p>Using two independent Caucasian populations, we have shown a stronger combined effect of the two commonly occurring CCND1 and COMT genotypes in the context of breast cancer predisposition.</p

Acute Regulation of Cardiac Metabolism by the Hexosamine Biosynthesis Pathway and Protein O-GlcNAcylation

OBJECTIVE: The hexosamine biosynthesis pathway (HBP) flux and protein O-linked N-acetyl-glucosamine (O-GlcNAc) levels have been implicated in mediating the adverse effects of diabetes in the cardiovascular system. Activation of these pathways with glucosamine has been shown to mimic some of the diabetes-induced functional and structural changes in the heart; however, the effect on cardiac metabolism is not known. Therefore, the primary goal of this study was to determine the effects of glucosamine on cardiac substrate utilization. METHODS: Isolated rat hearts were perfused with glucosamine (0-10 mM) to increase HBP flux under normoxic conditions. Metabolic fluxes were determined by (13)C-NMR isotopomer analysis; UDP-GlcNAc a precursor of O-GlcNAc synthesis was assessed by HPLC and immunoblot analysis was used to determine O-GlcNAc levels, phospho- and total levels of AMPK and ACC, and membrane levels of FAT/CD36. RESULTS: Glucosamine caused a dose dependent increase in both UDP-GlcNAc and O-GlcNAc levels, which was associated with a significant increase in palmitate oxidation with a concomitant decrease in lactate and pyruvate oxidation. There was no effect of glucosamine on AMPK or ACC phosphorylation; however, membrane levels of the fatty acid transport protein FAT/CD36 were increased and preliminary studies suggest that FAT/CD36 is a potential target for O-GlcNAcylation. CONCLUSION/INTERPRETATION: These data demonstrate that acute modulation of HBP and protein O-GlcNAcylation in the heart stimulates fatty acid oxidation, possibly by increasing plasma membrane levels of FAT/CD36, raising the intriguing possibility that the HBP and O-GlcNAc turnover represent a novel, glucose dependent mechanism for regulating cardiac metabolism

Release of Nitrogen and Phosphorus from Poultry Litter Amended with Acidified Biochar

Application of poultry litter (PL) to soil may lead to nitrogen (N) losses through ammonia (NH3) volatilization and to potential contamination of surface runoff with PL-derived phosphorus (P). Amending litter with acidified biochar may minimize these problems by decreasing litter pH and by retaining litter-derived P, respectively. This study evaluated the effect of acidified biochars from pine chips (PC) and peanut hulls (PH) on NH3 losses and inorganic N and P released from surface-applied or incorporated PL. Poultry litter with or without acidified biochars was surface-applied or incorporated into the soil and incubated for 21 d. Volatilized NH3 was determined by trapping it in acid. Inorganic N and P were determined by leaching the soil with 0.01 M of CaCl2 during the study and by extracting it with 1 M KCl after incubation. Acidified biochars reduced NH3 losses by 58 to 63% with surface-applied PL, and by 56 to 60% with incorporated PL. Except for PH biochar, which caused a small increase in leached NH4 +-N with incorporated PL, acidified biochars had no effect on leached or KCl-extractable inorganic N and P from surface-applied or incorporated PL. These results suggest that acidified biochars may decrease NH3 losses from PL but may not reduce the potential for P loss in surface runoff from soils receiving PL

Biomechanical Assessment of Liver Integrity: Prospective Evaluation of Mechanical Versus Acoustic MR Elastography

BACKGROUND: Magnetic resonance elastography (MRE) can quantify tissue biomechanics noninvasively, including pathological hepatic states like metabolic dysfunction-associated steatohepatitis. PURPOSE: To compare the performance of 2D/3D-MRE using the gravitational (GT) transducer concept with the current commercial acoustic (AC) solution utilizing a 2D-MRE approach. Additionally, quality index markers (QIs) were proposed to identify image pixels with sufficient quality for reliably estimating tissue biomechanics. STUDY TYPE: Prospective. POPULATION: One hundred seventy participants with suspected or confirmed liver disease (median age, 57 years [interquartile range (IQR), 46-65]; 66 females), and 11 healthy volunteers (median age, 31 years [IQR, 27-34]; 5 females). FIELD STRENGTH/SEQUENCE: Participants were scanned twice at 1.5 T and 60 Hz vibration frequency: first, using AC-MRE (2D-MRE, spin-echo EPI sequence, 11 seconds breath-hold), and second, using GT-MRE (2D- and 3D-MRE, gradient-echo sequence, 14 seconds breath-hold). ASSESSMENT: Image analysis was performed by four independent radiologists and one biomedical engineer. Additionally, superimposed analytic plane shear waves of known wavelength and attenuation at fixed shear modulus were used to propose pertinent QIs. STATISTICAL TESTS: Spearman's correlation coefficient (r) was applied to assess the correlation between modalities. Interreader reproducibility was evaluated using Bland-Altman bias and reproducibility coefficients. P-values <0.05 were considered statistically significant. RESULTS: Liver stiffness quantified via GT-2D/3D correlated well with AC-2D (r ≥ 0.89 [95% CI: 0.85-0.92]) and histopathological grading (r ≥ 0.84 [95% CI: 0.72-0.91]), demonstrating excellent agreement in Bland-Altman plots and between readers (κ ≥ 0.86 [95% CI: 0.81-0.91]). However, GT-2D showed a bias in overestimating stiffness compared to GT-3D. Proposed QIs enabled the identification of pixels deviating beyond 10% from true stiffness based on a combination of total wave amplitude, temporal sinusoidal nonlinearity, and wave signal-to-noise ratio for GT-3D. CONCLUSION: GT-MRE represents an alternative to AC-MRE for noninvasive liver tissue characterization. Both GT-2D and 3D approaches correlated strongly with the established commercial approach, offering advanced capabilities in abdominal imaging compared to AC-MRE. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2

Comprehensive association analysis of candidate genes for generalized vitiligo supports XBP1, FOXP3, and TSLP

We previously carried out a genome-wide association study of generalized vitiligo (GV) in non-Hispanic whites, identifying 13 confirmed susceptibility loci. In this study, we re-analyzed the genome-wide data set (comprising 1,392 cases and 2,629 controls) to specifically test association of all 33 GV candidate genes that have previously been suggested for GV, followed by meta-analysis incorporating both current and previously published data. We detected association of three of the candidate genes tested: TSLP (rs764916, P3.0E-04, odds ratio (OR)1.60; meta-P for rs38069333.1E-03), XBP1 (rs6005863, P3.6E-04, OR1.17; meta-P for rs22695779.5E-09), and FOXP3 (rs11798415, P5.8E-04, OR1.19). Association of GV with CTLA4 (rs12992492, P5.9E-05, OR1.20; meta-P for rs2317751.0E-04) seems to be secondary to epidemiological association with other concomitant autoimmune diseases. Within the major histocompatibility complex (MHC), at 6p21.33, association with TAP1-PSMB8 (rs3819721, P5.2E-06) seems to derive from linkage disequilibrium with major primary signals in the MHC class I and class II regions

AA9int: SNP interaction pattern search using non-hierarchical additive model set.

MOTIVATION: The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. RESULTS: We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. AVAILABILITY AND IMPLEMENTATION: The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Screening and association testing of common coding variation in steroid hormone receptor co-activator and co-repressor genes in relation to breast cancer risk: the Multiethnic Cohort

<p>Abstract</p> <p>Background</p> <p>Only a limited number of studies have performed comprehensive investigations of coding variation in relation to breast cancer risk. Given the established role of estrogens in breast cancer, we hypothesized that coding variation in steroid receptor coactivator and corepressor genes may alter inter-individual response to estrogen and serve as markers of breast cancer risk.</p> <p>Methods</p> <p>We sequenced the coding exons of 17 genes (<it>EP300, CCND1, NME1, NCOA1, NCOA2, NCOA3, SMARCA4, SMARCA2, CARM1, FOXA1, MPG, NCOR1, NCOR2, CALCOCO1, PRMT1, PPARBP </it>and <it>CREBBP</it>) suggested to influence transcriptional activation by steroid hormone receptors in a multiethnic panel of women with advanced breast cancer (n = 95): African Americans, Latinos, Japanese, Native Hawaiians and European Americans. Association testing of validated coding variants was conducted in a breast cancer case-control study (1,612 invasive cases and 1,961 controls) nested in the Multiethnic Cohort. We used logistic regression to estimate odds ratios for allelic effects in ethnic-pooled analyses as well as in subgroups defined by disease stage and steroid hormone receptor status. We also investigated effect modification by established breast cancer risk factors that are associated with steroid hormone exposure.</p> <p>Results</p> <p>We identified 45 coding variants with frequencies ≥ 1% in any one ethnic group (43 non-synonymous variants). We observed nominally significant positive associations with two coding variants in ethnic-pooled analyses (<it>NCOR2</it>: His52Arg, OR = 1.79; 95% CI, 1.05–3.05; <it>CALCOCO1</it>: Arg12His, OR = 2.29; 95% CI, 1.00–5.26). A small number of variants were associated with risk in disease subgroup analyses and we observed no strong evidence of effect modification by breast cancer risk factors. Based on the large number of statistical tests conducted in this study, the nominally significant associations that we observed may be due to chance, and will need to be confirmed in other studies.</p> <p>Conclusion</p> <p>Our findings suggest that common coding variation in these candidate genes do not make a substantial contribution to breast cancer risk in the general population. Cataloging and testing of coding variants in coactivator and corepressor genes should continue and may serve as a valuable resource for investigations of other hormone-related phenotypes, such as inter-individual response to hormonal therapies used for cancer treatment and prevention.</p