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Onset Disease (onset + disease)

Distribution by Scientific Domains
Life Sciences80%

Kinds of Onset Disease

  • late onset disease
    		•

    Selected Abstracts

    A single mutation in the GALC gene is responsible for the majority of late onset Krabbe disease patients in the Catania (Sicily, Italy) region,,

    HUMAN MUTATION, Issue 7 2007
    Willy Lissens
    Abstract A high proportion of patients with late onset forms of Krabbe disease is observed in a region north of Catania in Sicily. Molecular analysis in five families from this region shows that this condition is mainly due to a not previously described p.Gly41Ser substitution in the GALC gene that abolishes catalytic activity of the galactocerebrosidase enzyme, as shown by expression studies. Three patients were homozygous for this mutation, the other two were heterozygous, one with a frameshift mutation and one with a missense mutation on the second allele. Therefore, the mutation must be a mild one since it leads to late onset disease in all patients. In addition, it is on a unique haplotype indicating that it represents a founder mutation. This is also supported by the fact that the mutation was not found in three late onset patients from other regions in Sicily, in whom four novel mutations were identified. © 2007 Wiley-Liss, Inc. [source]

    Early onset preeclampsia and second trimester serum markers

    PRENATAL DIAGNOSIS, Issue 12 2009
    Geralyn M. Lambert-Messerlian
    Abstract Objective To examine serum markers measured in the second trimester to identify women who subsequently develop preeclampsia. Methods Clinically defined preeclampsia was confirmed in 45 women who had provided a serum sample as part of Down syndrome screening. Preeclampsia was categorized as mild or severe, as well as early (<32 weeks) or late onset. Each case was matched with five controls based on gestational age and date of serum collection. Stored sera were retrieved and tested for inhibin A, soluble vascular endothelial growth factor receptor 1 (sVEGF R1), placental growth factor (PlGF), and endoglin. Results were converted to multiples of the median (MoM) and compared in case and control pregnancies. Univariate analysis was used to identify the strongest markers, which were then used in a multivariate model. Results Inhibin A, PlGF, and endoglin were consistently associated with preeclampsia, especially for early onset disease. A multivariate model using the three markers could identify 50% of the pregnancies with early onset preeclampsia with a 2% false positive rate. Conclusion The levels of inhibin A, PlGF, and endoglin in the second trimester can be combined using a predictive model to provide individualized risk estimates for early onset preeclampsia. Copyright © 2009 John Wiley & Sons, Ltd. [source]

    Late and ultra late onset Streptococcus B meningitis: clinical and bacteriological data over 6 years in France

    ACTA PAEDIATRICA, Issue 1 2010
    J Guilbert
    Abstract Background:, Group B Streptococcus (GBS) is one of the leading causes of sepsis and meningitis in newborn. The objective of this study was to describe the characteristics of GBS meningitis in children aged between 7 and 89 days (late onset disease , LOD group) and to compare them with children aged more than 3 months (ultra late onset disease , ULOD group). Methods: Clinical and biological data were gathered by ACTIV/GPIP (a nationwide active surveillance network). The study population included 242 children hospitalized between 2001 and 2006 for GBS meningitis (220 in the LOD group and 22 in the ULOD group). Results:, Univariate analysis revealed that gestational age (GA) was significantly lower in the ULOD group as compared with the LOD group (respectively 35.6 weeks vs. 37.9 weeks, p = 0.002). Prevalence of early preterm birth (before the 32nd week GA) was significantly higher in the ULOD group than in the LOD group (32% vs. 7%, p = 0.002). No significant difference was found between the two groups for biological characteristics of lumbar puncture, GBS serotypes, complications and survival rate. Conclusion: These data suggest that LOD and ULOD would be the same clinical and bacteriological entity, except for prematurity, which seems significantly associated with ULOD. [source]

    Haplotype association analysis for late onset diseases using nuclear family data

    GENETIC EPIDEMIOLOGY, Issue 3 2006
    Chun Li
    Abstract In haplotype-based association studies for late onset diseases, one attractive design is to use available unaffected spouses as controls (Valle et al. [1998] Diab. Care 21:949,958). Given cases and spouses only, the standard expectation-maximization (EM) algorithm (Dempster et al. [1977] J. R. Stat. Soc. B 39:1,38) for case-control data can be used to estimate haplotype frequencies. But often we will have offspring for at least some of the spouse pairs, and offspring genotypes provide additional information about the haplotypes of the parents. Existing methods may either ignore the offspring information, or reconstruct haplotypes for the subjects using offspring information and discard data from those whose haplotypes cannot be reconstructed with high confidence. Neither of these approaches is efficient, and the latter approach may also be biased. For case-control data with some subjects forming spouse pairs and offspring genotypes available for some spouse pairs or individuals, we propose a unified, likelihood-based method of haplotype inference. The method makes use of available offspring genotype information to apportion ambiguous haplotypes for the subjects. For subjects without offspring genotype information, haplotypes are apportioned as in the standard EM algorithm for case-control data. Our method enables efficient haplotype frequency estimation using an EM algorithm and supports probabilistic haplotype reconstruction with the probability calculated based on the whole sample. We describe likelihood ratio and permutation tests to test for disease-haplotype association, and describe three test statistics that are potentially useful for detecting such an association. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source]