Genetic Analysis Workshop 14: microsatellite and single-nucleotide polymorphism marker loci for genome-wide scans.
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Biomedical subjects
Publications and source records attributed to Julia Bailey.
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Group 14 used data-mining strategies to evaluate a number of issues, including appropriate diagnosis, haplotype estimation, genetic linkage and association studies, and type I error. Methods ranged from exploratory analyses, to machine learning strategies (neural networks, supervised learning, and tree-based methods), to false discovery rate control of type I errors. The general motivations were to find the "story" in the data and to summarize information from a multitude of measures. Several methods illustrated strategies for better trait definition, using summarization of related traits. In the few studies that sought to identify genes for alcoholism, there was little agreement among the different strategies, likely reflecting the complexities of the disease. Nevertheless, Group 14 found that these methods offered strategies to gain a better understanding of the complex pathways by which disease develops.
Understanding the latest advances in the molecular genetics of the epilepsies is important, as it provides a basis for comprehending the new practice of epileptology. Epilepsies have traditionally been classified and subtyped on the basis of clinical and neurophysiologic concepts. However, the complexity and variability of phenotypes and overlapping clinical features limit the resolution of phenotype-based classification and confound epilepsy nosology. Identification of tightly linked epilepsy DNA markers and discovery of epilepsy-causing mutations provide a basis for refining the classification of epilepsies. Recent discoveries regarding the genetics surrounding certain epilepsy types (including Lafora's progressive myoclonic epilepsy, the severe myoclonic epilepsy of infancy of Dravet, and idiopathic generalized epilepsies) may be the beginning of a better understanding of how rare Mendelian epilepsy genes and their genetic architecture can explain some complexities of the common epilepsies.
Mutations in the EPM2A gene encoding a dual-specificity phosphatase (laforin) cause an autosomal recessive fatal disorder called Lafora's disease (LD) classically described as an adolescent-onset stimulus-sensitive myoclonus, epilepsy and neurologic deterioration. Here we related mutations in EPM2A with phenotypes of 22 patients (14 families) and identified two subsyndromes: (i) classical LD with adolescent-onset stimulus-sensitive grand mal, absence and myoclonic seizures followed by dementia and neurologic deterioration, and associated mainly with mutations in exon 4 (P = 0.0007); (ii) atypical LD with childhood-onset dyslexia and learning disorder followed by epilepsy and neurologic deterioration, and associated mainly with mutations in exon 1 (P = 0.0015). To understand the two subsyndromes better, we investigated the effect of five missense mutations in the carbohydrate-binding domain (CBD-4; coded by exon 1) and three missense mutations in the dual phosphatase domain (DSPD; coded by exons 3 and 4) on laforin's intracellular localization in HeLa cells. Expression of three mutant proteins (T194I, G279S and Y294N) in DSPD formed ubiquitin-positive cytoplasmic aggregates, suggesting that they were folding mutants set for degradation. In contrast, none of the three CBD-4 mutants showed cytoplasmic clumping. However, CBD-4 mutants W32G and R108C targeted both cytoplasm and nucleus, suggesting that laforin had diminished its usual affinity for polysomes. Our data, thus, represent the first report of a novel childhood syndrome for LD. Our results also provide clues for distinct roles for the CBD-4 and DSP domains of laforin in the etiology of two subsyndromes of LD.