Correction: A european spectrum of pharmacogenomic biomarkers: Implications for clinical pharmacogenomics (PLoS ONE (2016) 11:9 (e0162866) DOI: 10.1371/journal.pone.0162866)

The thirty-Third author's name is spelled incorrectly. The correct name is: Jadranka Sertić

A European spectrum of pharmacogenomic biomarkers: Implications for clinical pharmacogenomics

Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicity with the underlying genetic composition, particularly in genes encoding for protein factors and enzymes involved in drug metabolism and transport. In several European populations, particularly in countries with lower income, information related to the prevalence of pharmacogenomic biomarkers is incomplete or lacking. Here, we have implemented the microattribution approach to assess the pharmacogenomic biomarkers allelic spectrum in 18 European populations, mostly from developing European countries, by analyzing 1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant interpopulation pharmacogenomic biomarker allele frequency differences, particularly in 7 clinically actionable pharmacogenomic biomarkers in 7 European populations, affecting drug efficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on the differences observed in the prevalence of high-risk genotypes in these populations, as far as common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMT pharmacogenes are concerned. Also, our data demonstrate notable differences in predicted genotype-based warfarin dosing among these populations. Our findings can be exploited not only to develop guidelines for medical prioritization, but most importantly to facilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomic testing. This may subsequently contribute towards significant cost-savings in the overall healthcare expenditure in the participating countries, where pharmacogenomics implementation proves to be cost-effective

Associations of autozygosity with a broad range of human phenotypes

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (F-ROH) for >1.4 million individuals, we show that F-ROH is significantly associated (p <0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: F-ROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of F-ROH are confirmed within full-sibling pairs, where the variation in F-ROH is independent of all environmental confounding.Peer reviewe

Replication of Type 2 diabetes-associated variants in a Saudi Arabian population

Clinical epidemiolog

Production, Characterization and Purification of Laccase by Yeasts Isolated from Ligninolytic Soil

Laccases are multi copper oxidases having wide substrate specificity for phenolic compounds, amines, inorganic compounds like iodine, using oxygen and producing water as by product. The aim of this study is to produce, characterize and purify laccase from yeast isolated from different samples. Yeast isolates were screened for laccase production using tannic acid, catechol, hydroquinone and acetaminophen. Two isolates from soil were selected for further study based on their positive response to screening compounds. Maximum laccase production was achieved with glucose as the best carbon source (10g/l) for Kluyveromyces sp.Dw1 and maltose for Pichia sp.Dw2; Sodium nitrate (3g/l) as the best nitrogen source, optimum pH of 6.0, optimum temperature of 30°C and 350C for Kluyveromyces sp.Dw1and Pichia sp.Dw2 respectively. Rice bran supported the highest laccase production of 88.625U/L in Kluyveromyces sp.Dw1and cane bagasse (79.107U/L) in Pichia sp.Dw2. The addition of inducers like copper sulphate and acetaminophen stimulated maximum laccase production. Maximum activity recorded at pH 9.0, 300C and 500C temperature for Kluyveromyces sp.Dw1and Pichia sp.Dw2 respectively. Laccase activity was retained in the presence of Ca2+, K+, Hg+, EDTA and Benzoic acid. Kluyveromyces sp.Dw1 had Km value of 0.08mM and 0.13mM for Pichia sp.Dw2 using ABTS as substrate. From this study, Kluyveromyces dobzhanskii Dw1 and Pichia manshurica Dw2 produced laccase that oxidized ABTS with higher laccase production using agro wastes and inducers

Accurately Predicting Glutarylation Sites Using Sequential Bi-Peptide-Based Evolutionary Features

Post Translational Modification (PTM) is defined as the alteration of protein sequence upon interaction with different macromolecules after the translation process. Glutarylation is considered one of the most important PTMs, which is associated with a wide range of cellular functioning, including metabolism, translation, and specified separate subcellular localizations. During the past few years, a wide range of computational approaches has been proposed to predict Glutarylation sites. However, despite all the efforts that have been made so far, the prediction performance of the Glutarylation sites has remained limited. One of the main challenges to tackle this problem is to extract features with significant discriminatory information. To address this issue, we propose a new machine learning method called BiPepGlut using the concept of a bi-peptide-based evolutionary method for feature extraction. To build this model, we also use the Extra-Trees (ET) classifier for the classification purpose, which, to the best of our knowledge, has never been used for this task. Our results demonstrate BiPepGlut is able to significantly outperform previously proposed models to tackle this problem. BiPepGlut achieves 92.0%, 84.8%, 95.6%, 0.82, and 0.88 in accuracy, sensitivity, specificity, Matthew&rsquo;s Correlation Coefficient, and F1-score, respectively. BiPepGlut is implemented as a publicly available online predictor

Effects of different souring methods on the protein quality and iron and zinc bioaccessibilities of non‐alcoholic beverages from sorghum and amaranth

Souring by lactic acid fermentation and lactic acid acidification as well as inclusion of amaranth were explored as ways of improving the protein quality and iron and zinc bioaccessibilities of non‐alcoholic sorghum‐based beverages. The bioaccessible iron and zinc increased by 128–372%, 24–194%, respectively, in the fermented and chemically acidified beverages compared to the beverages without fermentation or acidification. The protein digestibility, reactive lysine, and bioaccessible iron in sorghum‐amaranth beverages increased by 14–58%, 24–52% and 34–64%, respectively, compared with the 100% sorghum beverages. Both fermentation and acidification with lactic acid have the potentials for improving the nutritional quality of cereal‐based foods as a means of combating protein malnutrition and iron and zinc deficiencies.The Office of Agricultural Research and Policy, Bureau for Food Security, U.S. Agency for International Development, under the terms of Cooperative Agreement No. AID-OAA-L-14-00003.https://onlinelibrary.wiley.com/journal/13652621hj2020Consumer ScienceFood Scienc