Current genetic data do not improve the prediction of type 2 diabetes mellitus: the CoLaus study.

CONTEXT: Several genetic risk scores to identify asymptomatic subjects at high risk of developing type 2 diabetes mellitus (T2DM) have been proposed, but it is unclear whether they add extra information to risk scores based on clinical and biological data. OBJECTIVE: The objective of the study was to assess the extra clinical value of genetic risk scores in predicting the occurrence of T2DM. DESIGN: This was a prospective study, with a mean follow-up time of 5 yr. SETTING AND SUBJECTS: The study included 2824 nondiabetic participants (1548 women, 52 ± 10 yr). MAIN OUTCOME MEASURE: Six genetic risk scores for T2DM were tested. Four were derived from the literature and two were created combining all (n = 24) or shared (n = 9) single-nucleotide polymorphisms of the previous scores. A previously validated clinic + biological risk score for T2DM was used as reference. RESULTS: Two hundred seven participants (7.3%) developed T2DM during follow-up. On bivariate analysis, no differences were found for all but one genetic score between nondiabetic and diabetic participants. After adjusting for the validated clinic + biological risk score, none of the genetic scores improved discrimination, as assessed by changes in the area under the receiver-operating characteristic curve (range -0.4 to -0.1%), sensitivity (-2.9 to -1.0%), specificity (0.0-0.1%), and positive (-6.6 to +0.7%) and negative (-0.2 to 0.0%) predictive values. Similarly, no improvement in T2DM risk prediction was found: net reclassification index ranging from -5.3 to -1.6% and nonsignificant (P ≥ 0.49) integrated discrimination improvement. CONCLUSIONS: In this study, adding genetic information to a previously validated clinic + biological score does not seem to improve the prediction of T2DM.

Recommendations for locus-specific databases and their curation.

Expert curation and complete collection of mutations in genes that affect human health is essential for proper genetic healthcare and research. Expert curation is given by the curators of gene-specific mutation databases or locus-specific databases (LSDBs). While there are over 700 such databases, they vary in their content, completeness, time available for curation, and the expertise of the curator. Curation and LSDBs have been discussed, written about, and protocols have been provided for over 10 years, but there have been no formal recommendations for the ideal form of these entities. This work initiates a discussion on this topic to assist future efforts in human genetics. Further discussion is welcome.

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.

Genetic counseling for individuals with hemoglobin disorders and for their relatives: a systematic literature review

Objective: To identify genetic counseling programs that do not encourage therapeutic abortion for individuals with hemoglobin disorders and/or for their relatives. Method: Systematic literature review of articles published from 2001 to 2012 that are located in the PubMed, LILACS, SciELO and SCOPUS databases using keywords in Portuguese, English and Spanish and that met the inclusion and exclusion criteria described on a standardized form. Results: A total of 409 articles were located, but only eight (1.9%) were selected for analysis. Conclusion: Although seldom mentioned in the literature, educational/preventive programs targeting hemoglobinopathies are feasible and allow the affected individuals to acquire knowledge on the consequences of this condition and their odds of transmitting it.



Genetic Differentiation of the Cabo Verde Archipelago Population Analysed by STR Polymorphisms

Allele frequencies for 17 STR loci were analyzed in a sample of unrelated males from the Cabo Verde Archipelago. The samples were gathered in such a way that the origin of the subjects was perfectly identified, and they could be included in one of the leeward or windward groups of islands. This study reveals that there are significant differences between both groups of islands, and between Cabo Verdeans and other populations from sub-Sahara Africa including the Guineans, the most probable source population for Cabo Verdeans. This study confirms mtDNA data and, together with HLA and Y chromosome data already published, shows that the Cabo Verde population is substructured and atypical, diverging substantially from mainland sub-Saharan populations. Overall these differences are most probably due to admixture between sub-Saharan slaves brought into the islands and other settlers of European origin. In the absence of a clear indication of a different ethnic composition of the first sub-Saharan settlers of Cabo Verde, the differentiation exhibited in both groups of islands can be most probably be attributed to genetic drift.

Defining new criteria for selection of cell-based intestinal models using publicly available databases.

BACKGROUND: The criteria for choosing relevant cell lines among a vast panel of available intestinal-derived lines exhibiting a wide range of functional properties are still ill-defined. The objective of this study was, therefore, to establish objective criteria for choosing relevant cell lines to assess their appropriateness as tumor models as well as for drug absorption studies. RESULTS: We made use of publicly available expression signatures and cell based functional assays to delineate differences between various intestinal colon carcinoma cell lines and normal intestinal epithelium. We have compared a panel of intestinal cell lines with patient-derived normal and tumor epithelium and classified them according to traits relating to oncogenic pathway activity, epithelial-mesenchymal transition (EMT) and stemness, migratory properties, proliferative activity, transporter expression profiles and chemosensitivity. For example, SW480 represent an EMT-high, migratory phenotype and scored highest in terms of signatures associated to worse overall survival and higher risk of recurrence based on patient derived databases. On the other hand, differentiated HT29 and T84 cells showed gene expression patterns closest to tumor bulk derived cells. Regarding drug absorption, we confirmed that differentiated Caco-2 cells are the model of choice for active uptake studies in the small intestine. Regarding chemosensitivity we were unable to confirm a recently proposed association of chemo-resistance with EMT traits. However, a novel signature was identified through mining of NCI60 GI50 values that allowed to rank the panel of intestinal cell lines according to their drug responsiveness to commonly used chemotherapeutics. CONCLUSIONS: This study presents a straightforward strategy to exploit publicly available gene expression data to guide the choice of cell-based models. While this approach does not overcome the major limitations of such models, introducing a rank order of selected features may allow selecting model cell lines that are more adapted and pertinent to the addressed biological question.

Genetic Variants of Serum Uric Acid and Gout: An Analysis of > 170,000 Individuals

Background/Purpose: Gout is a common and excruciatingly painful inflammatory arthritis caused by hyperuricemia. In addition to various lifestyle risk factors, a substantial genetic predisposition to gout has long been recognized. The Global Urate Genetics Consortium (GUGC) has aimed to comprehensively investigate the genetics of serum uric acid and gout using data from _ 140,000 individuals of European-ancestry, 8,340 individuals of Indian ancestry, 5,820 African-Americans, and 15,286 Japanese. Methods: We performed discovery GWAS meta-analyses of serum urate levels (n_110,347 individuals) followed by replication analyses (n_32,813 different individuals). Our gout analysis involved 3,151 cases and 68,350 controls, including 1,036 incident gout cases that met the American College of Rheumatology Criteria. We also examined the association of gout with fractional excretion of uric acid (n_6,799). A weighted genetic urate score was constructed based on the number of risk alleles across urate-associated loci, and their association with the risk of gout was evaluated. Furthermore, we examined implicated transcript expression in cis (expression quantitative trait loci databases) for potential insights into the gene underlying the association signal. Finally, in order to further identify urate-associated genomic regions, we performed functional network analyses that incorporated prior knowledge on molecular interactions in which the gene products of implicated genes operate. Results: We identified and replicated 28 genome-wide significant loci in association with serum urate (P 5_10_8), including all previously-reported loci as well as 18 novel genetic loci. Unlike the majority of previouslyidentified loci, none of the novel loci appeared to be obvious candidates for urate transport. Rather, they were mapped to genes that encode for purine production, transcription, or growth factors with broad downstream responses. Besides SLC2A9 and ABCG2, no additional regions contained SNPs that differed significantly (P _ 5_10_8) between sexes. Urateincreasing alleles were associated with an increased risk of gout for all loci. The urate genetic risk score (ranging from 10 to 45) was significantly associated with an increased odds of prevalent gout (OR per unit increase, 1.11; 95% CI, 1.09-1.14) and incident gout (OR, 1.10; 95% CI, 1.08-1.13). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. Detailed characterization of the loci revealed associations with transcript expression and the fractional excretion of urate. Network analyses implicated the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. Conclusion: The novel genetic candidates identified in this urate/gout consortium study, the largest to date, highlight the importance of metabolic control of urate production and urate excretion. The modulation by signaling processes that influence metabolic pathways such as glycolysis and the pentose phosphate pathway appear to be central mechanisms underpinned by the novel GWAS candidates. These findings may have implications for further research into urate-lowering drugs to treat and prevent gout.

trome, trEST and trGEN: databases of predicted protein sequences.

We previously introduced two new protein databases (trEST and trGEN) of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Here, we present the updates made on these two databases plus a new database (trome), which uses alignments of EST data to HTG or full genomes to generate virtual transcripts and coding sequences. This new database is of higher quality and since it contains the information in a much denser format it is of much smaller size. These new databases are in a Swiss-Prot-like format and are updated on a weekly basis (trEST and trGEN) or every 3 months (trome). They can be downloaded by anonymous ftp from ftp://ftp.isrec.isb-sib.ch/pub/databases.

Evolutionary analysis of genetic variants involved in rare diseases

Next-generation sequencing techniques such as exome sequencing can successfully detect all genetic variants in a human exome and it has been useful together with the implementation of variant filters to identify causing-disease mutations. Two filters aremainly used for the mutations identification: low allele frequency and the computational annotation of the genetic variant. Bioinformatic tools to predict the effect of a givenvariant may have errors due to the existing bias in databases and sometimes show a limited coincidence among them. Advances in functional and comparative genomics are needed in order to properly annotate these variants.The goal of this study is to: first, functionally annotate Common Variable Immunodeficiency disease (CVID) variants with the available bioinformatic methods in order to assess the reliability of these strategies. Sencondly, as the development of new methods to reduce the number of candidate genetic variants is an active and necessary field of research, we are exploring the utility of gene function information at organism level as a filter for rare disease genes identification. Recently, it has been proposed that only 10-15% of human genes are essential and therefore we would expect that severe rare diseases are mostly caused by mutations on them. Our goal is to determine whether or not these rare and severe diseases are caused by deleterious mutations in these essential genes. If this hypothesis were true, taking into account essential genes as a filter would be an interesting parameter to identify causingdisease mutations.

Genetic polymorphisms in the Cytochrome P450 family and squamous cell carcinoma of the oral cavity, pharynx and larynx

Objective:To analyze the genetic polymorphisms of the cytochrome P450 family and their relationship with squamous cell carcinoma of the oral cavity, pharynx and larynx.Methods: We present a narrative literature review, conducted in Pubmed, Lilacs and Cochrane Databases of articles published in the last five years correlating genetic polymorphisms of the cytochrome P450 family and cancer risk in different populations worldwide.Results: We initially found 65 articles and, after selection criteria, 20 case-control studies with various populations worldwide were eligible. The most studied polymorphisms were those of CYP2E1 and CYP1A1 subfamilies. There is little about the other subfamilies. The association found between polymorphisms and cancer risk amounted to a countless number of variables, amongst them: population, selection methods, racial factors and different modes of exposure to carcinogens, genotyping methods, and nomenclature of the polymorphisms.Conclusion: so far, there is no proven link between genetic polymorphisms of cytochrome P450 family and squamous cell carcinoma of the oral cavity, pharynx and larynx relationship.

Implications for DNA identification arising from an analysis of Australian forensic databases

Previous analyses of Australian samples have suggested that populations of the same broad racial group (Caucasian, Asian, Aboriginal) tend to be genetically similar across states. This suggests that a single national Australian database for each such group may be feasible, which would greatly facilitate casework. We have investigated samples drawn from each of these groups in different Australian states, and have quantified the genetic homogeneity across states within each racial group in terms of the "coancestry coefficient" F(ST). In accord with earlier results, we find that F(ST) values, as estimated from these data, are very small for Caucasians and Asians, usually <0.5%. We find that "declared" Aborigines (which includes many with partly Aboriginal genetic heritage) are also genetically similar across states, although they display some differentiation from a "pure" Aboriginal population (almost entirely of Aboriginal genetic heritage).

A Bayesian approach for constructing genetic maps when markers are miscoded

The advent of molecular markers has created opportunities for a better understanding of quantitative inheritance and for developing novel strategies for genetic improvement of agricultural species, using information on quantitative trait loci (QTL). A QTL analysis relies on accurate genetic marker maps. At present, most statistical methods used for map construction ignore the fact that molecular data may be read with error. Often, however, there is ambiguity about some marker genotypes. A Bayesian MCMC approach for inferences about a genetic marker map when random miscoding of genotypes occurs is presented, and simulated and real data sets are analyzed. The results suggest that unless there is strong reason to believe that genotypes are ascertained without error, the proposed approach provides more reliable inference on the genetic map.

Characterization of the genetic diversity of Mycobacterium tuberculosis in São Paulo city, Brazil

Background: Tuberculosis is a major health problem in São Paulo, Brazil, which is the most populous and one of the most cosmopolitan cities in South America. To characterize the genetic diversity of Mycobacterium tuberculosis in the population of this city, the genotyping techniques of spoligotyping and MIRU were applied to 93 isolates collected in two consecutive years from 93 different tuberculosis patients residing in São Paulo city and attending the Clemente Ferreira Institute (the reference clinic for the treatment of tuberculosis). Findings. Spoligotyping generated 53 different spoligotype patterns. Fifty-one isolates (54.8%) were grouped into 13 spoligotyping clusters. Seventy- two strains (77.4%) showed spoligotypes described in the international databases (SpolDB4, SITVIT), and 21 (22.6%) showed unidentified patterns. The most frequent spoligotype families were Latin American Mediterranean (LAM) (26 isolates), followed by the T family (24 isolates) and Haarlem (H) (11 isolates), which together accounted for 65.4% of all the isolates. These three families represent the major genotypes found in Africa, Central America, South America and Europe. Six Spoligo-International- types (designated SITs by the database) comprised 51.8% (37/72) of all the identified spoligotypes (SIT53, SIT50, SIT42, SIT60, SIT17 and SIT1). Other SITs found in this study indicated the great genetic diversity of M. tuberculosis, reflecting the remarkable ethnic diversity of São Paulo city inhabitants. The MIRU technique was more discriminatory and did not identify any genetic clusters with 100% similarity among the 93 isolates. The allelic analysis showed that MIRU loci 26, 40, 23 and 10 were the most discriminatory. When MIRU and spoligotyping techniques were combined, all isolates grouped in the 13 spoligotyping clusters were separated. Conclusions: Our data indicated the genomic stability of over 50% of spoligotypes identified in São Paulo and the great genetic diversity of M. tuberculosis isolates in the remaining SITs, reflecting the large ethnic mix of the São Paulo city inhabitants. The results also indicated that in this city, M. tuberculosis isolates acquired drug resistance independently of genotype and that resistance was more dependent on the selective pressure of treatment failure and the environmental circumstances of patients. © 2011 Leite et al; licensee BioMed Central Ltd.

The genetic polymorphism of diabetic nephropathy

Introduction: The Diabetic Nephropathy (DN) affects approximately 40% of patients diagnosed with DM is associated with increased mortality from cardiovascular phenomena and is considered the main cause of Chronic Renal Failure (CRF) in patients dialectics. Methods: Searches were performed on Medline, SciELO, Lilacs and Cochrane databases using the crossing between the key-words: “genetic polymorphism” and “diabetic nephropathy”. Results: The selected studies indicated that diabetic nephropathy is the leading cause of chronic renal failure, which significantly reduces the life expectancy of diabetics. Currently, some factors may have connection with DN. They are: genetic predisposition based on family history, hypertension, and cardiovascular events, quality of glycemic control and lipid levels and blood pressure and smoking. Conclusion: Studies constants are essential to add new elements in the literature for the definition (s) of factor (s) gene (s) specific (s) of diabetic nephropathy.

Different approaches for dealing with rare variants in family-based genetic studies: application of a Genetic Analysis Workshop 17 problem

Rare variants are becoming the new candidates in the search for genetic variants that predispose individuals to a phenotype of interest. Their low prevalence in a population requires the development of dedicated detection and analytical methods. A family-based approach could greatly enhance their detection and interpretation because rare variants are nearly family specific. In this report, we test several distinct approaches for analyzing the information provided by rare and common variants and how they can be effectively used to pinpoint putative candidate genes for follow-up studies. The analyses were performed on the mini-exome data set provided by Genetic Analysis Workshop 17. Eight approaches were tested, four using the trait’s heritability estimates and four using QTDT models. These methods had their sensitivity, specificity, and positive and negative predictive values compared in light of the simulation parameters. Our results highlight important limitations of current methods to deal with rare and common variants, all methods presented a reduced specificity and, consequently, prone to false positive associations. Methods analyzing common variants information showed an enhanced sensibility when compared to rare variants methods. Furthermore, our limited knowledge of the use of biological databases for gene annotations, possibly for use as covariates in regression models, imposes a barrier to further research.