Co-existence of Phenylketonuria and Fabry disease on a 3 year-old boy: case report

Background: The co-existence of two genetically distinct metabolic disorders in the same patient has rarely been reported. Phenylketonuria (PKU) is an inborn error of the metabolism resulting from a phenylalanine hydroxylase defi ciency. Fabry disease (FD) is an X-linked lysosomal storage disorder due to a defi ciency of the enzyme alpha-galactosidase A. Case presentation: We report a case of a 3-year-old boy affected by classic PKU and FD, both confi rmed by molecular data. The FD was suspected at the age of 21 months on the presence of non-specifi c GI symptoms (severe abdominal pain and periodically appearance of not specifi c episodes of gastroenteritis) apparently non related to PKU. Conclusion: This is the fi rst report of co-existence of FD and PKU, two different congenital inborn of metabolism and in consideration of the prevalence of each disease this chance association is a very unusual event. The co-existence of these diseases made very diffi cult the correct interpretation of clinical symptoms as lack of appetite, severe abdominal pain and non-specifi c gastroenteritis episodes. Furthermore, this case report helps to defi ne the early clinical phenotype of FD

SMN1 dosage analysis in spinal muscular atrophy from India

BACKGROUND: Spinal muscular atrophy (SMA) represents the second most common fatal autosomal recessive disorder after cystic fibrosis. Due to the high carrier frequency, the burden of this genetic disorder is very heavy in developing countries like India. As there is no cure or effective treatment, genetic counseling becomes very important in disease management. SMN1 dosage analysis results can be utilized for identifying carriers before offering prenatal diagnosis in the context of genetic counseling. METHODS: In the present study we analyzed the carrier status of parents and sibs of proven SMA patients. In addition, SMN1 copy number was determined in suspected SMA patients and parents of children with a clinical diagnosis of SMA. RESULTS: wenty nine DNA samples were analyzed by quantitative PCR to determine the number of SMN1 gene copies present, and 17 of these were found to have one SMN1 gene copy. The parents of confirmed SMA patients were found to be obligate carriers of the disease. Dosage analysis was useful in ruling out clinical suspicion of SMA in four patients. In a family with history of a deceased floppy infant and two abortions, both parents were found to be carriers of SMA and prenatal diagnosis could be offered in future pregnancies. CONCLUSION: SMN1 copy number analysis is an important parameter for identification of couples at risk for having a child affected with SMA and reduces unwarranted prenatal diagnosis for SMA. The dosage analysis is also useful for the counseling of clinically suspected SMA with a negative diagnostic SMA test

A Drastic Reduction in the Life Span of Cystatin C L68Q Carriers Due to Life-Style Changes during the Last Two Centuries

Hereditary cystatin C amyloid angiopathy (HCCAA) is an autosomal dominant disease with high penetrance, manifest by brain hemorrhages in young normotensive adults. In Iceland, this condition is caused by the L68Q mutation in the cystatin C gene, with contemporary carriers reaching an average age of only 30 years. Here, we report, based both on linkage disequilibrium and genealogical evidence, that all known copies of this mutation derive from a common ancestor born roughly 18 generations ago. Intriguingly, the genealogies reveal that obligate L68Q carriers born 1825 to 1900 experienced a drastic reduction in life span, from 65 years to the present-day average. At the same time, a parent-of-origin effect emerged, whereby maternal inheritance of the mutation was associated with a 9 year reduction in life span relative to paternal inheritance. As these trends can be observed in several different extended families, many generations after the mutational event, it seems likely that some environmental factor is responsible, perhaps linked to radical changes in the life-style of Icelanders during this period. A mutation with such radically different phenotypic effects in reaction to normal variation in human life-style not only opens the possibility of preventive strategies for HCCAA, but it may also provide novel insights into the complex relationship between genotype and environment in human disease

Mining phenotypes for gene function prediction

<p>Abstract</p> <p>Background</p> <p>Health and disease of organisms are reflected in their phenotypes. Often, a genetic component to a disease is discovered only after clearly defining its phenotype. In the past years, many technologies to systematically generate phenotypes in a high-throughput manner, such as RNA interference or gene knock-out, have been developed and used to decipher functions for genes. However, there have been relatively few efforts to make use of phenotype data beyond the single genotype-phenotype relationships.</p> <p>Results</p> <p>We present results on a study where we use a large set of phenotype data – in textual form – to predict gene annotation. To this end, we use text clustering to group genes based on their phenotype descriptions. We show that these clusters correlate well with several indicators for biological coherence in gene groups, such as functional annotations from the Gene Ontology (GO) and protein-protein interactions. We exploit these clusters for predicting gene function by carrying over annotations from well-annotated genes to other, less-characterized genes in the same cluster. For a subset of groups selected by applying objective criteria, we can predict GO-term annotations from the biological process sub-ontology with up to 72.6% precision and 16.7% recall, as evaluated by cross-validation. We manually verified some of these clusters and found them to exhibit high biological coherence, e.g. a group containing all available antennal Drosophila odorant receptors despite inconsistent GO-annotations.</p> <p>Conclusion</p> <p>The intrinsic nature of phenotypes to visibly reflect genetic activity underlines their usefulness in inferring new gene functions. Thus, systematically analyzing these data on a large scale offers many possibilities for inferring functional annotation of genes. We show that text clustering can play an important role in this process.</p

Haplotype analysis of TP53 polymorphisms, Arg72Pro and Ins16, in BRCA1 and BRCA2 mutation carriers of French Canadian descent

Research articl

Genes to Diseases (G2D) Computational Method to Identify Asthma Candidate Genes

Asthma is a complex trait for which different strategies have been used to identify its environmental and genetic predisposing factors. Here, we describe a novel methodological approach to select candidate genes for asthma genetic association studies. In this regard, the Genes to Diseases (G2D) computational tool has been used in combination with a genome-wide scan performed in a sub-sample of the Saguenay−Lac-St-Jean (SLSJ) asthmatic familial collection (n = 609) to identify candidate genes located in two suggestive loci shown to be linked with asthma (6q26) and atopy (10q26.3), and presenting differential parent-of-origin effects. This approach combined gene selection based on the G2D data mining analysis of the bibliographic and protein public databases, or according to the genes already known to be associated with the same or a similar phenotype. Ten genes (LPA, NOX3, SNX9, VIL2, VIP, ADAM8, DOCK1, FANK1, GPR123 and PTPRE) were selected for a subsequent association study performed in a large SLSJ sample (n = 1167) of individuals tested for asthma and atopy related phenotypes. Single nucleotide polymorphisms (n = 91) within the candidate genes were genotyped and analysed using a family-based association test. The results suggest a protective association to allergic asthma for PTPRE rs7081735 in the SLSJ sample (p = 0.000463; corrected p = 0.0478). This association has not been replicated in the Childhood Asthma Management Program (CAMP) cohort. Sequencing of the regions around rs7081735 revealed additional polymorphisms, but additional genotyping did not yield new associations. These results demonstrate that the G2D tool can be useful in the selection of candidate genes located in chromosomal regions linked to a complex trait

13C-phenylalanine breath test detects altered phenylalanine kinetics in schizophrenia patients

Phenylalanine is an essential amino acid required for the synthesis of catecholamines including dopamine. Altered levels of phenylalanine and its metabolites in blood and cerebrospinal fluid have been reported in schizophrenia patients. This study attempted to examine for the first time whether phenylalanine kinetics is altered in schizophrenia using L-[1-13C]phenylalanine breath test (13C-PBT). The subjects were 20 chronically medicated schizophrenia patients (DSM-IV) and the same number of age- and sex-matched controls. 13C-phenylalanine (99 atom% 13C; 100 mg) was administered orally and the breath 13CO2 /12CO2 ratio was monitored for 120 min. The possible effect of antipsychotic medication (risperidone (RPD) or haloperidol (HPD) treatment for 21 days) on 13C-PBT was examined in rats. Body weight (BW), age and diagnostic status were significant predictors of the area under the curve of the time course of Δ13CO2 (‰) and the cumulative recovery rate (CRR) at 120 min. A repeated measures analysis of covariance controlled for age and BW revealed that the patterns of CRR change over time differed between the patients and controls and that Δ13CO2 was lower in the patients than in the controls at all sampling time points during the 120 min test, with an overall significant difference between the two groups. Chronic administration of RPD or HPD had no significant effect on 13C-PBT indices in rats. Our results suggest that 13C-PBT is a novel laboratory test that can detect altered phenylalanine kinetics in chronic schizophrenia patients. Animal experiments suggest that the observed changes are unlikely to be attributable to antipsychotic medication