Mutation analysis of the coding sequence of the MECP2 gene in infantile autism

Mutations in the coding region of the methyl-CpG-binding protein 2 ( MECP2) gene cause Rett syndrome and have also been reported in a number of X-linked mental retardation syndromes. Furthermore, such mutations have recently been described in a few autistic patients. In this study, a large sample of individuals with autism was screened in order to elucidate systematically whether specific mutations in MECP2 play a role in autism. The mutation analysis of the coding sequence of the gene was performed by denaturing high-pressure liquid chromatography and direct sequencing. Taken together, 14 sequence variants were identified in 152 autistic patients from 134 German families and 50 unrelated patients from the International Molecular Genetic Study of Autism Consortium affected relative-pair sample. Eleven of these variants were excluded for having an aetiological role as they were either silent mutations, did not cosegregate with autism in the pedigrees of the patients or represented known polymorphisms. The relevance of the three remaining mutations towards the aetiology of autism could not be ruled out, although they were not localised within functional domains of MeCP2 and may be rare polymorphisms. Taking into account the large size of our sample, we conclude that mutations in the coding region of MECP2 do not play a major role in autism susceptibility. Therefore, infantile autism and Rett syndrome probably represent two distinct entities at the molecular genetic level.     

CNTNAP2 is disrupted in a family with Gilles de la Tourette syndrome and obsessive compulsive disorder

Gilles de la Tourette syndrome (GTS) is a sporadic or inherited complex neuropsychiatric disorder characterized by involuntary motor and vocal tics. There is comorbidity with disorders like obsessive compulsive disorder and attention deficit hyperactivity disorder. Until now linkage analysis has pointed to a number of chromosomal locations, but has failed to identify a clear candidate gene(s). We have investigated a GTS family with a complex chromosomal insertion/translocation involving chromosomes 2 and 7. The affected father [46,XY,inv(2) (p23q22),ins(7;2) (q35-q36;p21p23)] and two affected children [46,XX,der(7)ins(7;2)(q35-q36;p21p23) and 46,XY,der(7)ins(7;2)(q35-q36;p213p23)] share a chromosome 2p21-p23 insertion on chromosome 7q35-q36, thereby interrupting the contactin-associated protein 2 gene (CNTNAP2). This gene encodes a membrane protein located in a specific compartment at the nodes of Ranvier of axons. We hypothesize that disruption or decreased expression of CNTNAP2 could lead to a disturbed distribution of the K(+) channels in the nervous system, thereby influencing conduction and/or repolarization of action potentials, causing unwanted actions or movements in GTS.     

Evaluation of a mass screening program for lysinuric protein intolerance in the northern part of Japan

Lysinuric protein intolerance (LPI:MIM 222700) is an autosomal recessive disease characterized by defective transport of the dibasic amino acids. We recently reported a local cluster of LPI in the northern part of Japan (Koizumi et al., 2000). Mutational analysis of the LPI patients in this local cluster revealed they were exclusively homozygous for the R410X mutation. The effectiveness of early intervention with citrulline therapy (200 mg/kg per day) and protein restriction (1.5 g/kg per day) was confirmed in these patients. Mass screening was conducted in 4,568 newborn babies between 1999 and 2002, which was estimated to cover 100% of almost all newborns delivered in the screened area. Forty heterozygous newborns were found (0.88%), leading to an estimated incidence of LPI of 1:51,984. The number of people that required screening to detect one case was 51,984, and the cost for mass screening was 30 cents/person (a total of dollars 15,600). This is comparable to, or even less than, the cost of currently screened diseases in Japan. Therefore, we conclude that a mass screening program for LPI can be introduced effectively and economically into an area where an LPI cluster is located as the result of a founder mutation.     

Longitudinal variance-components analysis of the Framingham Heart Study data

The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The RR accounted for the variation in genetic effects (including marker-specific quantitative trait locus (QTL) effects) across time by fitting polynomials of age. The use of a mixed model allowed both fixed (such as sex) and random (such as familial environment) effects to be accounted for appropriately. Using this method we performed a QTL analysis of all of the available adult phenotype data (26,106 phenotypic records). In addition to RR, conventional univariate variance component techniques were applied. The traits of interest were BMI, HDLC, total cholesterol, and height. The longitudinal method allowed the characterization of the change in QTL effects with aging. A QTL affecting BMI was shown to act mainly at early ages.     

Comparison of year-of-exam- and age-matched estimates of heritability in the Framingham Heart Study data

Several different approaches can be used to examine generational and temporal trends in family studies. The measurement of offspring and parents can be made over a short period of time with parents and offspring having quite different ages, or measurements can be made at the same ages but with decades between parent and offspring measures. A third approach, used in the Framingham Heart Study, has repeated examinations across a broad range of age and time, and provides a unique opportunity to compare these approaches. Parents and offspring were matched both on (year of exam) and on age. Heritability estimates for systolic blood pressure, body mass index, height, weight, cholesterol, and glucose were obtained by regressing offspring on midparent values with and without adjustment for age. Higher estimates of heritability were obtained for age-matched than for year-of-exam-matched data for all traits considered. For most traits, estimates of the heritability of the change over time (slope) of the trait were near zero. These results suggest that the optimal design to identify genetic effects in traits with large age-related effects may be to measure parents and offspring at similar ages and not to rely on age-adjustment or longitudinal measures to account for these temporal effects.     

Genome scan linkage results for longitudinal systolic blood pressure phenotypes in subjects from the Framingham Heart Study

The relationship between elevated blood pressure and cardiovascular and cerebrovascular disease risk is well accepted. Both systolic and diastolic hypertension are associated with this risk increase, but systolic blood pressure appears to be a more important determinant of cardiovascular risk than diastolic blood pressure. Subjects for this study are derived from the Framingham Heart Study data set. Each subject had five records of clinical data of which systolic blood pressure, age, height, gender, weight, and hypertension treatment were selected to characterize the phenotype in this analysis. We modeled systolic blood pressure as a function of age using a mixed modeling methodology that enabled us to characterize the phenotype for each individual as the individual's deviation from the population average rate of change in systolic blood pressure for each year of age while controlling for gender, body mass index, and hypertension treatment. Significant (p = 0.00002) evidence for linkage was found between this normalized phenotype and a region on chromosome 1. Similar linkage results were obtained when we estimated the phenotype while excluding values obtained during hypertension treatment. The use of linear mixed models to define phenotypes is a methodology that allows for the adjustment of the main factor by covariates. Future work should be done in the area of combining this phenotype estimation directly with the linkage analysis so that the error in estimating the phenotype can be properly incorporated into the genetic analysis, which, at present, assumes that the phenotype is measured (or estimated) without error.