992 resultados para genotype phenotype correlations


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Purpose: Complete achromatopsia is a rare autosomal recessive disease due to CNGA3, CNGB3, GNAT2 and PDE6C mutations. We studied a large consanguineous Tunisian family including twelve individuals.Methods: Ophthalmic evaluation included a full clinical examination, color vision testing, optical coherence tomography and electroretinography. Linkage analysis using microsatellite markers flanking CNGA3, CNGB3, GNAT2 and PDE6C genes was performed. Mutations were screened by direct sequencing.Results: In all affected subjects, acuity ranged from 20/50 to 20/200. Fundus examination was normal except for two patients who had respectively 4 mm and 5 mm diameters of peripheral congenital hypertrophy. Likewise retinal layers exploration by OCT revealed no change in the thickness of the central retina. Color Vision with 100 Hue Farnsworth test described a profound color impairment along all three axes of color vision. The haplotype analysis of GNAT2 markers revealed that all affected offspring were homozygous by descent for the four polymorphic markers. The maximum lod score value, 4.33, confirmed the evidence for linkage to the GNAT2 gene.A homozygous novel nonsense mutation R313X was identified segregating with an identical GNAT2 haplotype in all affected subjects. This mutation could interrupt interaction with photoactivated rhodopsin, resulting in a failure of visual transduction. In fact, ERG showed a clearly abolished photopic b-wave and flicker responses with no residual cone function justifying the severe GNAT2 achromatopsia phenotype.Conclusions: This is the first report of the clinical and genetic investigation of complete achromatopsia in North Africa and of the largest family with recessive achromatopsia involving GNAT2, thus providing a unique opportunity for genotype phenotype correlation for this extremely rare condition.

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We sought to explore the genotype-phenotype of Jervell and Lange-Nielsen syndrome (JLNS) patients in Saudi Arabia. We have also assessed the plausible effect of consanguinity into the pathology of JLNS. Six families with at least one JLNS-affected member attended our clinic between 2011 and 2013. Retrospective and prospective clinical data were collected and genetic investigation was performed. Pathogenic mutations in the KCNQ1 gene were detected in all JLNS patients. The homozygous mutations detected were Leu273Phe, Asp202Asn, Ile567Thr, and c.1486_1487delCT and compound heterozygous mutations were c.820_ 830del and c.1251+1G>T. All living JLNS patients except one had a QTc of >500 ms and a history of recurrent syncope. β-Blockers abolished the cardiac-related events in all patients except two siblings with homozygous Ile567Thr mutation. Four of the six mutations were originally reported in autosomal dominant long QT syndrome (LQTS) patients. Eighty percent of the heterozygote mutation carriers showed prolongation of QTc, but majority of these reported no symptoms attributable to arrhythmias. Mutations detected in this study will be advantageous in tribe and region-specific cascade screening of LQTS in Saudi Arabia.

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Our understanding of how genotype determines phenotype in primary dystonia is limited. Familial young-onset primary dystonia is commonly due to the DYT1 gene mutation. A critical question, given the 30% penetrance of clinical symptoms in DYT1 mutation carriers, is why the same genotype leads to differential clinical expression and whether non-DYT1 adult-onset primary dystonia, with and without family history share pathophysiological mechanisms with DYT1 dystonia. This study examines the relationship between dystonic phenotype and the DYT1 gene mutation by monitoring whole-brain structure using voxel-based morphometry. We acquired magnetic resonance imaging data of symptomatic and asymptomatic DYT1 mutation carriers, of non-DYT1 primary dystonia patients, with and without family history and control subjects with normal DYT1 alleles. By crossing the factors genotype and phenotype we demonstrate a significant interaction in terms of brain anatomy confined to the basal ganglia bilaterally. The explanation for this effect differs according to both gene and dystonia status: non-DYT1 adult-onset dystonia patients and asymptomatic DYT1 carriers have significantly larger basal ganglia compared to healthy subjects and symptomatic DYT1 mutation carriers. There is a significant negative correlation between severity of dystonia and basal ganglia size in DYT1 mutation carriers. We propose that differential pathophysiological and compensatory mechanisms lead to brain structure changes in non-DYT1 primary adult-onset dystonias and DYT1 gene carriers. Given the range of age of onset, there may be differential genetic modulation of brain development that in turn determines clinical expression. Alternatively, a DYT1 gene dependent primary defect of motor circuit development may lead to stress-induced remodelling of the basal ganglia and hence dystonia.

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L-2-Hydroxyglutaric aciduria (L2HGA) is a rare, neurometabolic disorder with an autosomal recessive mode of inheritance. Affected individuals only have neurological manifestations, including psychomotor retardation, cerebellar ataxia, and more variably macrocephaly, or epilepsy. The diagnosis of L2HGA can be made based on magnetic resonance imaging (MRI), biochemical analysis, and mutational analysis of L2HGDH. About 200 patients with elevated concentrations of 2-hydroxyglutarate (2HG) in the urine were referred for chiral determination of 2HG and L2HGDH mutational analysis. All patients with increased L2HG (n=106; 83 families) were included. Clinical information on 61 patients was obtained via questionnaires. In 82 families the mutations were detected by direct sequence analysis and/or multiplex ligation dependent probe amplification (MLPA), including one case where MLPA was essential to detect the second allele. In another case RT-PCR followed by deep intronic sequencing was needed to detect the mutation. Thirty-five novel mutations as well as 35 reported mutations and 14 nondisease-related variants are reviewed and included in a novel Leiden Open source Variation Database (LOVD) for L2HGDH variants (http://www.LOVD.nl/L2HGDH). Every user can access the database and submit variants/patients. Furthermore, we report on the phenotype, including neurological manifestations and urinary levels of L2HG, and we evaluate the phenotype-genotype relationship.

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Recently, pathogenic variants in the MLL2 gene were identified as the most common cause of Kabuki (Niikawa-Kuroki) syndrome (MIM#147920). To further elucidate the genotype-phenotype correlation, we studied a large cohort of 86 clinically defined patients with Kabuki syndrome (KS) for mutations in MLL2. All patients were assessed using a standardized phenotype list and all were scored using a newly developed clinical score list for KS (MLL2-Kabuki score 0-10). Sequencing of the full coding region and intron-exon boundaries of MLL2 identified a total of 45 likely pathogenic mutations (52%): 31 nonsense, 10 missense and four splice-site mutations, 34 of which were novel. In five additional patients, novel, i.e. non-dbSNP132 variants of clinically unknown relevance, were identified. Patients with likely pathogenic nonsense or missense MLL2 mutations were usually more severely affected (median 'MLL2-Kabuki score' of 6) as compared to the patients without MLL2 mutations (median 'MLL2-Kabuki score' of 5), a significant difference (p < 0.0014). Several typical facial features such as large dysplastic ears, arched eyebrows with sparse lateral third, blue sclerae, a flat nasal tip with a broad nasal root, and a thin upper and a full lower lip were observed more often in mutation positive patients.

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Purpose: Wolfram syndrome is a degenerative, recessive rare disease with an onset in childhood. It is caused by mutations in WFS1 or CISD2 genes. More than 200 different variations in WFS1 have been described in patients with Wolfram syndrome, which complicates the establishment of clear genotype-phenotype correlation. The purpose of this study was to elucidate the role of WFS1 mutations and update the natural history of the disease. Methods: This study analyzed clinical and genetic data of 412 patients with Wolfram syndrome published in the last 15 years. Results: (i) 15% of published patients do not fulfill the current ­inclusion criterion; (ii) genotypic prevalence differences may exist among countries; (iii) diabetes mellitus and optic atrophy might not be the first two clinical features in some patients; (iv) mutations are nonuniformly distributed in WFS1; (v) age at onset of diabetes mellitus, hearing defects, and diabetes insipidus may depend on the patient"s genotypic class; and (vi) disease progression rate might depend on genotypic class. Conclusion: New genotype-phenotype correlations were established, disease progression rate for the general population and for the genotypic classes has been calculated, and new diagnostic criteria have been proposed. The conclusions raised could be important for patient management and counseling as well as for the development of treatments for Wolfram syndrome.

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We present clinical and molecular evaluation from a large cohort of patients with Stickler syndrome: 78 individuals from 21 unrelated Brazilian families. The patients were selected in a Hospital with a craniofacial dysmorphology assistance service and clinical diagnosis was based on the presence of cleft palate associated to facial and ocular anomalies of Stickler syndrome. Analysis of COL2A1 gene revealed 9 novel and 4 previously described pathogenic mutations. Except for the mutation c.556G>T (p.Gly186X), all the others were located in the triple helical domain. We did not find genotype/phenotype correlation in relation to type and position of the mutation in the triple helical domain. However, a significantly higher proportion of myopia in patients with mutations located in this domain was observed in relation to those with the mutation in the non-tripe helical domain (c.556G>T; P < 0.04). A trend towards a higher prevalence of glaucoma, although not statistically significant, was observed in the presence of the mutation c.556G>T. It is possible. that this mutation alters the splicing of the mRNA instead of only creating a premature stop codon and therefore it can lead to protein products of different ocular effects. One novel DNA variation (c.1266+7G>C) occurs near a splice site and it was observed to co-segregate with the phenotype in one of the two families with this DNA variation. As in silico analysis predicted that the c.1266+7G>C DNA variation can affect the efficiency of the splicing, we still cannot rule it out as non-pathogenic. Our study also showed that ascertainment through cleft palate associated to other craniofacial signs can be very efficient for identification of Stickler syndrome patients. Still, high frequency of familial cases and high frequency of underdevelopment of distal lateral tibial epiphyses observed in our patients suggested that the inclusion of this information can improve the clinical diagnosis of Stickler syndrome. (C) 2008 Elsevier Masson SAS. All rights reserved.

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Array-CGH enables the detection of submicroscopic chromosomal deletions and duplications and leads to an accurate delineation of the imbalances, raising the possibility of correlating genotype to phenotype and mapping minimal critical regions associated with particular patterns of clinical features. We report here on four patients sharing common clinical features (psychomotor retardation, coarse facies and ocular anomalies), with proximal 5q deletions identified by oligo array-CGH. The deletions range from 5.75 to 17.26-Mb in size and occurred de novo. A common 2.63-Mb region between the deletions described here can be defined in 5q12.1 (59,390,122-62,021,754 bp bp from 5pter, hg18) and includes 12 genes. Among them, KIF2A, which encodes a kinesin superfamily protein, is a particularly interesting candidate for the phenotype, as it suppresses the growth of axonal collateral branches and is involved in normal brain development. Ocular defects, albeit unspecific, seem to be common in the 5q12.1 deletion. Identification of additional cases of deletions involving the 5q12.1 region will allow more accurate genotype-phenotype correlations. (C) 2011 Wiley-Liss, Inc.

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Centronuclear myopathy (CNM) is a genetically heterogeneous disorder associated with general skeletal muscle weakness, type I fiber predominance and atrophy, and abnormally centralized nuclei. Autosomal dominant CNM is due to mutations in the large GTPase dynamin 2 (DNM2), a mechanochemical enzyme regulating cytoskeleton and membrane trafficking in cells. To date, 40 families with CNM-related DNM2 mutations have been described, and here we report 60 additional families encompassing a broad genotypic and phenotypic spectrum. In total, 18 different mutations are reported in 100 families and our cohort harbors nine known and four new mutations, including the first splice-site mutation. Genotype-phenotype correlation hypotheses are drawn from the published and new data, and allow an efficient screening strategy for molecular diagnosis. In addition to CNM, dissimilar DNM2 mutations are associated with Charcot-Marie-Tooth (CMT) peripheral neuropathy (CMTD1B and CMT2M), suggesting a tissue-specific impact of the mutations. In this study, we discuss the possible clinical overlap of CNM and CMT, and the biological significance of the respective mutations based on the known functions of dynamin 2 and its protein structure. Defects in membrane trafficking due to DNM2 mutations potentially represent a common pathological mechanism in CNM and CMT. Hum Mutat 33: 949-959, 2012. (C) 2012 Wiley Periodicals, Inc.

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OBJECTIVE: Wilson's disease (WD) is an inborn error of metabolism caused by abnormalities of the copper-transporting protein encoding gene ATP7B. In this study, we examined ATP7B for mutations in a group of patients living in southern Brazil. METHODS: 36 WD subjects were studied and classified according to their clinical and epidemiological data. In 23 subjects the ATP7B gene was analyzed. RESULTS: Fourteen distinct mutations were detected in at least one of the alleles. The c.3207C>A substitution at exon 14 was the most common mutation (allelic frequency=37.1%) followed by the c.3402delC at exon 15 (allelic frequency=11.4%). The mutations c.2018-2030del13 at exon 7 and c.4093InsT at exon 20 are being reported for the first time. CONCLUSION: The c.3207C>A substitution at exon 14, was the most common mutation, with an allelic frequency of 37.1%. This mutation is the most common mutation described in Europe.

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Abstract Mutations in the human gene coding for XPD lead to segmental progeria - the premature appearance of some of the phenotypes normally associated with aging - which may or may not be accompanied by increased cancer incidence. XPD is required for at least three different critical cellular functions: in addition to participating in the process of nucleotide excision repair (NER), which removes bulky DNA lesions, XPD also regulates transcription as part of the general transcription factor IIH (TFIIH) and controls cell cycle progression through its interaction with CAK, a pivotal activator of cyclin dependent kinases (CDKs). The study of inherited XPD disorders offers the opportunity to gain insights into the coordination of important cellular events and may shed light on the mechanisms that regulate the delicate equilibrium between cell proliferation and functional senescence, which is notably altered during physiological aging and in cancer. The phenotypic manifestations in the different XPD disorders are the sum of disturbances in the vital processes carried out by TFIIH and CAK. In addition, further TFIIH- and CAK-independent cellular activities of XPD may also play a role. This, added to the complex feedback networks that are in place to guarantee the coordination between cell cycle, DNA repair and transcription, complicates the interpretation of clinical observations. While results obtained from patient cell isolates as well as from murine models have been elementary in revealing such complexity, the Drosophila embryo has proven useful to analyze the role of XPD as a cell cycle regulator independently from its other cellular functions. Together with data from the biochemical and structural analysis of XPD and of the TFIIH complex these results combine into a new picture of the XPD activities that provides ground for a better understanding of the patophysiology of XPD diseases and for future development of diagnostic and therapeutic tools.

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With hundreds of single nucleotide polymorphisms (SNPs) in a candidate gene and millions of SNPs across the genome, selecting an informative subset of SNPs to maximize the ability to detect genotype-phenotype association is of great interest and importance. In addition, with a large number of SNPs, analytic methods are needed that allow investigators to control the false positive rate resulting from large numbers of SNP genotype-phenotype analyses. This dissertation uses simulated data to explore methods for selecting SNPs for genotype-phenotype association studies. I examined the pattern of linkage disequilibrium (LD) across a candidate gene region and used this pattern to aid in localizing a disease-influencing mutation. The results indicate that the r2 measure of linkage disequilibrium is preferred over the common D′ measure for use in genotype-phenotype association studies. Using step-wise linear regression, the best predictor of the quantitative trait was not usually the single functional mutation. Rather it was a SNP that was in high linkage disequilibrium with the functional mutation. Next, I compared three strategies for selecting SNPs for application to phenotype association studies: based on measures of linkage disequilibrium, based on a measure of haplotype diversity, and random selection. The results demonstrate that SNPs selected based on maximum haplotype diversity are more informative and yield higher power than randomly selected SNPs or SNPs selected based on low pair-wise LD. The data also indicate that for genes with small contribution to the phenotype, it is more prudent for investigators to increase their sample size than to continuously increase the number of SNPs in order to improve statistical power. When typing large numbers of SNPs, researchers are faced with the challenge of utilizing an appropriate statistical method that controls the type I error rate while maintaining adequate power. We show that an empirical genotype based multi-locus global test that uses permutation testing to investigate the null distribution of the maximum test statistic maintains a desired overall type I error rate while not overly sacrificing statistical power. The results also show that when the penetrance model is simple the multi-locus global test does as well or better than the haplotype analysis. However, for more complex models, haplotype analyses offer advantages. The results of this dissertation will be of utility to human geneticists designing large-scale multi-locus genotype-phenotype association studies. ^

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Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

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Introduction Gene expression is an important process whereby the genotype controls an individual cell’s phenotype. However, even genetically identical cells display a variety of phenotypes, which may be attributed to differences in their environment. Yet, even after controlling for these two factors, individual phenotypes still diverge due to noisy gene expression. Synthetic gene expression systems allow investigators to isolate, control, and measure the effects of noise on cell phenotypes. I used mathematical and computational methods to design, study, and predict the behavior of synthetic gene expression systems in S. cerevisiae, which were affected by noise. Methods I created probabilistic biochemical reaction models from known behaviors of the tetR and rtTA genes, gene products, and their gene architectures. I then simplified these models to account for essential behaviors of gene expression systems. Finally, I used these models to predict behaviors of modified gene expression systems, which were experimentally verified. Results Cell growth, which is often ignored when formulating chemical kinetics models, was essential for understanding gene expression behavior. Models incorporating growth effects were used to explain unexpected reductions in gene expression noise, design a set of gene expression systems with “linear” dose-responses, and quantify the speed with which cells explored their fitness landscapes due to noisy gene expression. Conclusions Models incorporating noisy gene expression and cell division were necessary to design, understand, and predict the behaviors of synthetic gene expression systems. The methods and models developed here will allow investigators to more efficiently design new gene expression systems, and infer gene expression properties of TetR based systems.

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Elucidating the genetic basis of human phenotypes is a major goal of contemporary geneticists. Logically, two fundamental and contrasting approaches are available, one that begins with a phenotype and concludes with the identification of a responsible gene or genes; the other that begins with a gene and works toward identifying one or more phenotypes resulting from allelic variation of it. This paper provides a conceptual overview of phenotype-based vs. gene-based procedures with emphasis on gene-based methods. A key feature of a gene-based approach is that laboratory effort first is devoted to developing an assay for mutations in the gene under regard; the assay then is applied to the evaluation of large numbers of unrelated individuals with a variety of phenotypes that are deemed potentially resulting from alleles at the gene. No effort is directed toward chromosomally mapping the loci responsible for the phenotypes scanned. Example is made of my laboratory’s successful use of a gene-based approach to identify genes causing hereditary diseases of the retina such as retinitis pigmentosa. Reductions in the cost and improvements in the speed of scanning individuals for DNA sequence anomalies may make a gene-based approach an efficient alternative to phenotype-based approaches to correlating genes with phenotypes.