RESUMEN
Hereditary spastic paraplegias (HSPs) are neurodegenerative motor neuron diseases characterized by progressive age-dependent loss of corticospinal motor tract function. Although the genetic basis is partly understood, only a fraction of cases can receive a genetic diagnosis, and a global view of HSP is lacking. By using whole-exome sequencing in combination with network analysis, we identified 18 previously unknown putative HSP genes and validated nearly all of these genes functionally or genetically. The pathways highlighted by these mutations link HSP to cellular transport, nucleotide metabolism, and synapse and axon development. Network analysis revealed a host of further candidate genes, of which three were mutated in our cohort. Our analysis links HSP to other neurodegenerative disorders and can facilitate gene discovery and mechanistic understanding of disease.
Asunto(s)
Exoma/genética , Estudios de Asociación Genética , Enfermedad de la Neurona Motora/genética , Neuronas/metabolismo , Tractos Piramidales/metabolismo , Paraplejía Espástica Hereditaria/genética , Animales , Axones/fisiología , Transporte Biológico/genética , Estudios de Cohortes , Redes Reguladoras de Genes , Humanos , Mutación , Nucleótidos/genética , Nucleótidos/metabolismo , Análisis de Secuencia de ADN , Sinapsis/fisiología , Transcriptoma , Pez CebraRESUMEN
Deletions of 16p13.11 have been associated with a variety of phenotypes, and have also been found in normal individuals. We report on two unrelated patients with severe microcephaly, agenesis of the corpus callosum, scalp rugae, and a fetal brain disruption (FBD)-like phenotype with inherited deletions of 16p13.11. The first patient was subsequently found on whole exome sequencing to have a nonsense mutation (p.R44X) in NDE1 on the non-deleted chromosome 16 homolog. We then undertook copy number studies of 16p13.11 and sequencing of NDE1 in nine additional patients with a similar severe microcephaly, agenesis of the corpus callosum, and FBD-like phenotype. The second patient was found to have an inherited deletion of the entire NDE1 gene combined with a frameshift mutation (c.1020-1021het_delGA) in the non-deleted NDE1. These observations broaden the phenotype seen in NDE1-related microcephaly to include FBD. These data also represent the second described syndrome, after Bernard-Soulier syndrome, where an autosomal recessive condition combines an inherited segmental duplication mediated deletion with a mutation in a gene within the non-deleted homolog. Finally, we performed informatics analysis of the 16p13.11 gene content, and found that there are many genes within the region with evidence for role(s) in brain development. Sequencing of other candidate genes in this region in patients with deletion 16p13.11 and more severe neurophenotypes may be warranted.
Asunto(s)
Deleción Cromosómica , Cromosomas Humanos Par 16 , Enfermedades Fetales/genética , Microcefalia/genética , Proteínas Asociadas a Microtúbulos/genética , Mutación , Adolescente , Encefalopatías/etiología , Cuerpo Calloso/patología , Mutación del Sistema de Lectura , Humanos , Lactante , Fenotipo , Duplicaciones Segmentarias en el GenomaRESUMEN
Genome-wide scans of nucleotide variation in human subjects are providing an increasing number of replicated associations with complex disease traits. Most of the variants detected have small effects and, collectively, they account for a small fraction of the total genetic variance. Very large sample sizes are required to identify and validate findings. In this situation, even small sources of systematic or random error can cause spurious results or obscure real effects. The need for careful attention to data quality has been appreciated for some time in this field, and a number of strategies for quality control and quality assurance (QC/QA) have been developed. Here we extend these methods and describe a system of QC/QA for genotypic data in genome-wide association studies (GWAS). This system includes some new approaches that (1) combine analysis of allelic probe intensities and called genotypes to distinguish gender misidentification from sex chromosome aberrations, (2) detect autosomal chromosome aberrations that may affect genotype calling accuracy, (3) infer DNA sample quality from relatedness and allelic intensities, (4) use duplicate concordance to infer SNP quality, (5) detect genotyping artifacts from dependence of Hardy-Weinberg equilibrium test P-values on allelic frequency, and (6) demonstrate sensitivity of principal components analysis to SNP selection. The methods are illustrated with examples from the "Gene Environment Association Studies" (GENEVA) program. The results suggest several recommendations for QC/QA in the design and execution of GWAS.
