RESUMEN
Shwachman-Diamond syndrome (SDS) is an autosomal recessive disorder characterized by exocrine pancreatic insufficiency and hematologic and skeletal abnormalities. A genomewide scan of families with SDS was terminated at approximately 50% completion, with the identification of chromosome 7 markers that showed linkage with the disease. Finer mapping revealed significant linkage across a broad interval that included the centromere. The maximum two-point LOD score was 8.7, with D7S473, at a recombination fraction of 0. The maximum multipoint LOD score was 10, in the interval between D7S499 and D7S482 (5.4 cM on the female map and 0 cM on the male map), a region delimited by recombinant events detected in affected children. Evidence from all 15 of the multiplex families analyzed provided support for the linkage, consistent with a single locus for SDS. However, the presence of several different mutations is suggested by the heterogeneity of disease-associated haplotypes in the candidate region.
Asunto(s)
Enfermedades de la Médula Ósea/genética , Centrómero/genética , Cromosomas Humanos Par 7/genética , Insuficiencia Pancreática Exocrina/genética , Ligamiento Genético/genética , Alelos , Enfermedades de la Médula Ósea/sangre , Enfermedades de la Médula Ósea/patología , Mapeo Cromosómico , Insuficiencia Pancreática Exocrina/patología , Femenino , Frecuencia de los Genes , Genes Recesivos/genética , Heterogeneidad Genética , Haplotipos/genética , Humanos , Escala de Lod , Masculino , Modelos Genéticos , Anomalías Musculoesqueléticas/genética , Anomalías Musculoesqueléticas/patología , Mutación/genética , Células Mieloides/patología , Linaje , Programas Informáticos , SíndromeRESUMEN
We explored methods for kinship and linkage analysis in a Hutterite pedigree comprising 1,544 individuals, 72 of whom were diagnosed with asthma. Subpedigrees were selected by (a) identifying nuclear families containing asthmatics, (b) identifying couples with many asthmatic descendants in an ad hoc manner, and (c) finding the most recent common ancestors of all asthmatics. Markov chain Monte Carlo (MCMC) methods were used to estimate allele sharing in the larger subpedigrees and transmission/disequilibrium tests were performed on nuclear families. On chromosome 5q near the cytokine cluster, modest evidence for linkage to asthma was obtained. Using MCMC, we were able to evaluate the evidence for linkage in complex subpedigrees of several hundred individuals, and hence, incorporate some of the co-ancestry of this founder population.
Asunto(s)
Asma/genética , Mapeo Cromosómico/estadística & datos numéricos , Consanguinidad , Adulto , Asma/epidemiología , Niño , Cromosomas Humanos Par 5 , Femenino , Marcadores Genéticos/genética , Genética de Población , Humanos , Desequilibrio de Ligamiento , Masculino , Cadenas de Markov , Método de Montecarlo , Linaje , South DakotaRESUMEN
Peroxisome proliferator-activated receptor alpha (PPARalpha) is a member of the steroid hormone receptor super family involved in the control of cellular lipid utilization. This makes PPARalpha a candidate gene for type 2 diabetes and dyslipidemia. The aim of this study was to investigate whether genetic variation in the human PPARalpha gene can influence the risk of type 2 diabetes and dyslipidemia among French Canadians. We therefore first determined the genomic structure of human PPARalpha, and then designed intronic primers to sequence the coding region and the exon-intron boundaries of the gene in 12 patients with type 2 diabetes and in 2 nondiabetic subjects. Sequence analysis revealed the presence of a L162V missense mutation in exon 5 of one diabetic patient. Leucine 162 is contained within the DNA binding domain of the human PPARalpha gene, and is conserved among humans, mice, rats, and guinea pigs. We subsequently screened a sample of 121 patients newly diagnosed with type 2 diabetes and their age and sex-matched nondiabetic controls, recruited from the Saguenay-Lac-St-Jean region of Northeastern Quebec, for the presence of the L162V mutation by a PCR-RFLP based method. There was no difference in L162 homozygote or V162 carrier frequencies between diabetics and nondiabetics. However, whether diabetic or not, carriers of the V162 allele had higher plasma apolipoprotein B levels compared to noncarriers (P 5 0.05). To further this association, we screened another sample of 193 nondiabetic subjects recruited in the greater Quebec City area. Carriers of the V162 allele compared with homozygotes of the L162 allele had significantly higher concentrations of plasma total and LDL-apolipoprotein B as well as LDL cholesterol (P = 0.02). These results suggest an association between the PPARalpha V162 allele and the atherogenic/hyperapolipoprotein B dyslipidemia.
Asunto(s)
Apolipoproteínas B/sangre , Hiperlipoproteinemias/genética , Mutación Missense , Receptores Citoplasmáticos y Nucleares/genética , Factores de Transcripción/genética , Animales , Secuencia de Bases , Estudios de Cohortes , Cartilla de ADN , Diabetes Mellitus Tipo 2/genética , Genotipo , Humanos , Masculino , Ratones , Persona de Mediana Edad , Polimorfismo Genético , RatasRESUMEN
After detecting linkage in one sample, most researchers will attempt to validate this finding in another sample. Three strategies for validating a primary linkage were compared, with a focus on methods that might be appropriate in the presence of gene x environment interaction. First, a validation sample was collected and analyzed using the same ascertainment procedure and methods as the primary sample. Second, a sample of families with particular exposure patterns were ascertained subsequent to a significant test for heterogeneity due to the exposure in the primary sample. A third strategy ascertained by exposure status when exposure-defined subgroup tests were significant in the primary sample. The second strategy reduced the number of false positive linkage signals identified through exposure subgroup identification (i.e., the third strategy), but in this GAW11 data that contained no qualitative gene x environment interactions, it had poor sensitivity. Power to detect heterogeneity depends on the differences in risk between exposed and unexposed.