A rigorous approach to facilitate and guarantee the correctness of the genetic testing management in human genome information systems

Abstract Background Recent medical and biological technology advances have stimulated the development of new testing systems that have been providing huge, varied amounts of molecular and clinical data. Growing data volumes pose significant challenges for information processing systems in research centers. Additionally, the routines of genomics laboratory are typically characterized by high parallelism in testing and constant procedure changes. Results This paper describes a formal approach to address this challenge through the implementation of a genetic testing management system applied to human genome laboratory. We introduced the Human Genome Research Center Information System (CEGH) in Brazil, a system that is able to support constant changes in human genome testing and can provide patients updated results based on the most recent and validated genetic knowledge. Our approach uses a common repository for process planning to ensure reusability, specification, instantiation, monitoring, and execution of processes, which are defined using a relational database and rigorous control flow specifications based on process algebra (ACP). The main difference between our approach and related works is that we were able to join two important aspects: 1) process scalability achieved through relational database implementation, and 2) correctness of processes using process algebra. Furthermore, the software allows end users to define genetic testing without requiring any knowledge about business process notation or process algebra. Conclusions This paper presents the CEGH information system that is a Laboratory Information Management System (LIMS) based on a formal framework to support genetic testing management for Mendelian disorder studies. We have proved the feasibility and showed usability benefits of a rigorous approach that is able to specify, validate, and perform genetic testing using easy end user interfaces.

CYP2C9 and VKORC1 Polymorphisms Are Differently Distributed in the Brazilian Population According to Self-Declared Ethnicity or Genetic Ancestry

Background: Warfarin-dosing pharmacogenetic algorithms have presented different performances across ethnicities, and the impact in admixed populations is not fully known. Aims: To evaluate the CYP2C9 and VKORC1 polymorphisms and warfarin-predicted metabolic phenotypes according to both self-declared ethnicity and genetic ancestry in a Brazilian general population plus Amerindian groups. Methods: Two hundred twenty-two Amerindians (Tupinikin and Guarani) were enrolled and 1038 individuals from the Brazilian general population who were self-declared as White, Intermediate (Brown, Pardo in Portuguese), or Black. Samples of 274 Brazilian subjects from Sao Paulo were analyzed for genetic ancestry using an Affymetrix 6.0 (R) genotyping platform. The CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), and VKORC1 g.-1639G>A (rs9923231) polymorphisms were genotyped in all studied individuals. Results: The allelic frequency for the VKORC1 polymorphism was differently distributed according to self-declared ethnicity: White (50.5%), Intermediate (46.0%), Black (39.3%), Tupinikin (40.1%), and Guarani (37.3%) (p < 0.001), respectively. The frequency of intermediate plus poor metabolizers (IM + PM) was higher in White (28.3%) than in Intermediate (22.7%), Black (20.5%), Tupinikin (12.9%), and Guarani (5.3%), (p < 0.001). For the samples with determined ancestry, subjects carrying the GG genotype for the VKORC1 had higher African ancestry and lower European ancestry (0.14 +/- 0.02 and 0.62 +/- 0.02) than in subjects carrying AA (0.05 +/- 0.01 and 0.73 +/- 0.03) (p = 0.009 and 0.03, respectively). Subjects classified as IM + PM had lower African ancestry (0.08 +/- 0.01) than extensive metabolizers (0.12 +/- 0.01) (p = 0.02). Conclusions: The CYP2C9 and VKORC1 polymorphisms are differently distributed according to self-declared ethnicity or genetic ancestry in the Brazilian general population plus Amerindians. This information is an initial step toward clinical pharmacogenetic implementation, and it could be very useful in strategic planning aiming at an individual therapeutic approach and an adverse drug effect profile prediction in an admixed population.

Differentiation of African Components of Ancestry to Stratify Groups in a Case-Control Study of a Brazilian Urban Population

Background: Balancing the subject composition of case and control groups to create homogenous ancestries between each group is essential for medical association studies. Methods: We explored the applicability of single-tube 34-plex ancestry informative markers (AIM) single nucleotide polymorphisms (SNPs) to estimate the African Component of Ancestry (ACA) to design a future case-control association study of a Brazilian urban sample. Results: One hundred eighty individuals (107 case group; 73 control group) self-described as white, brown-intermediate or black were selected. The proportions of the relative contribution of a variable number of ancestral population components were similar between case and control groups. Moreover, the case and control groups demonstrated similar distributions for ACA <0.25 and >0.50 categories. Notably a high number of outlier values (23 samples) were observed among individuals with ACA <0.25. These individuals presented a high probability of Native American and East Asian ancestral components; however, no individuals originally giving these self-described ancestries were observed in this study. Conclusions: The strategy proposed for the assessment of ancestry and adjustment of case and control groups for an association study is an important step for the proper construction of the study, particularly when subjects are taken from a complex urban population. This can be achieved using a straight forward multiplexed AIM-SNPs assay of highly discriminatory ancestry markers.

Narrowing the gap of personalized medicine in emerging countries: the case of multiple endocrine neoplasias in Brazil

The finished version of the human genome sequence was completed in 2003, and this event initiated a revolution in medical practice, which is usually referred to as the age of genomic or personalized medicine. Genomic medicine aims to be predictive, personalized, preventive, and also participative (4Ps). It offers a new approach to several pathological conditions, although its impact so far has been more evident in mendelian diseases. This article briefly reviews the potential advantages of this approach, and also some issues that may arise in the attempt to apply the accumulated knowledge from genomic medicine to clinical practice in emerging countries. The advantages of applying genomic medicine into clinical practice are obvious, enabling prediction, prevention, and early diagnosis and treatment of several genetic disorders. However, there are also some issues, such as those related to: (a) the need for approval of a law equivalent to the Genetic Information Nondiscrimination Act, which was approved in 2008 in the USA; (b) the need for private and public funding for genetics and genomics; (c) the need for development of innovative healthcare systems that may substantially cut costs (e.g. costs of periodic medical followup); (d) the need for new graduate and postgraduate curricula in which genomic medicine is emphasized; and (e) the need to adequately inform the population and possible consumers of genetic testing, with reference to the basic aspects of genomic medicine.

Schizophrenia, brain disease and meta-analyses: Integrating the pieces and testing Fusar-Poli`s hypothesis

This paper aims to discuss and test the hypothesis raised by Fusar-Poli [Fusar-Poli P. Can neuroimaging prove that schizophrenia is a brain disease? A radical hypothesis. Medical Hypotheses in press, corrected proof] that ""on the basis of the available imaging literature there is no consistent evidence to reject the radical and provocative hypothesis that schizophrenia is not a brain disease"". To achieve this goal, all meta-analyses on `fMRI and schizophrenia` published during the current decade and indexed in Pubmed were summarized, as much as some other useful information, e.g., meta-analyses on genetic risk factors. Our main conclusion is that the literature fully supports the hypothesis that schizophrenia is a syndrome (not a disease) associated with brain abnormalities, despite the fact that there is no singular and reductionist pathway from the nosographic entity (schizophrenia) to its causes. This irreducibility is due to the fact that the syndrome has more than one dimension (e.g., cognitive, psychotic and negative) and each of them is related to abnormalities in specific neuronal networks. A psychiatric diagnosis is a statistical procedure; these dimensions are not identically represented in each diagnosticated case and this explains the existence of more than one pattern of brain abnormalities related to schizophrenia. For example, chronification is associated with negativism while the first psychotic episode is not; in that sense, the same person living with schizophrenia may reveal different symptoms and fMRI patterns along the course of his life, and this is precisely what defines schizophrenia since the time when it was called Dementia Praecox (first by pick then by Kraepelin). It is notable that 100% of the collected meta-analyses on `fMRI and schizophrenia` reveal positive findings. Moreover, all meta-analyses that found positive associations between schizophrenia and genetic risk factors have to do with genes (SNPs) especially activated in neuronal tissue of the central nervous system (CNS), suggesting that, to the extent these polymorphisms are related to schizophrenia`s etiology, they are also related to abnormal brain activity. (C) 2009 Elsevier Ltd. All rights reserved.

Testing allele homogeneity: the problem of nested hypotheses

Background: The evaluation of associations between genotypes and diseases in a case-control framework plays an important role in genetic epidemiology. This paper focuses on the evaluation of the homogeneity of both genotypic and allelic frequencies. The traditional test that is used to check allelic homogeneity is known to be valid only under Hardy-Weinberg equilibrium, a property that may not hold in practice. Results: We first describe the flaws of the traditional (chi-squared) tests for both allelic and genotypic homogeneity. Besides the known problem of the allelic procedure, we show that whenever these tests are used, an incoherence may arise: sometimes the genotypic homogeneity hypothesis is not rejected, but the allelic hypothesis is. As we argue, this is logically impossible. Some methods that were recently proposed implicitly rely on the idea that this does not happen. In an attempt to correct this incoherence, we describe an alternative frequentist approach that is appropriate even when Hardy-Weinberg equilibrium does not hold. It is then shown that the problem remains and is intrinsic of frequentist procedures. Finally, we introduce the Full Bayesian Significance Test to test both hypotheses and prove that the incoherence cannot happen with these new tests. To illustrate this, all five tests are applied to real and simulated datasets. Using the celebrated power analysis, we show that the Bayesian method is comparable to the frequentist one and has the advantage of being coherent. Conclusions: Contrary to more traditional approaches, the Full Bayesian Significance Test for association studies provides a simple, coherent and powerful tool for detecting associations.

Gametic phase disequilibrium between the syntenic multiallelic HTG4 and HMS3 markers widely used for parentage testing in Thoroughbred horses

Validation of parentage and horse breed registries through DNA typing relies on estimates of random match probabilities with DNA profiles generated from multiple polymorphic loci. Of the twenty-seven microsatellite loci recommended by the International Society for Animal Genetics for parentage testing in Thoroughbred horses, eleven are located on five chromosomes. An important aspect in determining combined exclusion probabilities is the ascertainment of the genetic linkage status of syntenic markers, which may affect reliable use of the product rule in estimating random match probabilities. In principle, linked markers can be in gametic phase disequilibrium (GD). We aimed at determining the extent, by frequency and strength, of GD between the HTG4 and HMS3 multiallelic loci, syntenic on chromosome 9. We typed the qualified offspring (n (1) = 27; n (2) = 14) of two Quarter Bred stallions (registered by the Brazilian Association of Quarter Horse Breeders) and 121 unrelated horses from the same breed. In the 41 informative meioses analyzed, the frequency of recombination between the HTG4 and HMS3 loci was 0.27. Consistent with genetic map distances, this recombination rate does not fit to the theoretical distribution for independently segregated markers. We estimated sign-based D' coefficients as a measure of GD, and showed that the HTG4 and HMS3 loci are in significant, yet partial and weak, disequilibrium, with two allele pairs involved (HTG4*M/HMS3*P, D'(+) = 0.6274; and HTG4*K/HMS3*P, D'(-) = -0.6096). These results warn against the inadequate inclusion of genetically linked markers in the calculation of combined power of discrimination for Thoroughbred parentage validation.

Permanent Genetic Resources added to Molecular Ecology Resources Database 1 February 2012-31 March 2012

This article documents the addition of 171 microsatellite marker loci and 27 pairs of single nucleotide polymorphism (SNP) sequencing primers to the Molecular Ecology Resources Database. Loci were developed for the following species: Bombus pauloensis, Cephalorhynchus heavisidii, Cercospora sojina, Harpyhaliaetus coronatus, Hordeum vulgare, Lachnolaimus maximus, Oceanodroma monteiroi, Puccinia striiformis f. sp. tritici, Rhea americana, Salmo salar, Salmo trutta, Schistocephalus solidus, Sousa plumbea and Tursiops aduncus. These loci were cross-tested on the following species: Aquila heliaca, Bulweria bulwerii, Buteo buteo, Buteo swainsoni, Falco rusticolus, Haliaeetus albicilla, Halobaena caerulea, Hieraaetus fasciatus, Oceanodroma castro, Puccinia graminis f. sp. Tritici, Puccinia triticina, Rhea pennata and Schistocephalus pungitii. This article also documents the addition of 27 sequencing primer pairs for Puffinus baroli and Bulweria bulwerii and cross-testing of these loci in Oceanodroma castro, Pelagodroma marina, Pelecanoides georgicus, Pelecanoides urinatrix, Thalassarche chrysostoma and Thalassarche melanophrys.

The humankind genome: from genetic diversity to the origin of human diseases

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease’s etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.