Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 6 de 6
Filter
Add more filters











Database
Language
Publication year range
1.
J Endourol Case Rep ; 6(2): 96-98, 2020.
Article in English | MEDLINE | ID: mdl-32775689

ABSTRACT

Background: The first published report of a pediatric robotic extravesical transplant ureteral reimplantation for vesicoureteral reflux (VUR) in a renal allograft is described. Case Presentation: The patient is an 11-year-old Caucasian girl who had acute allograft pyelonephritis and was subsequently found to have dilating VUR. Conclusion: Robotic surgery facilitated an effective nondismembered extravesical reimplant with minimal morbidity.

2.
Adv Genet ; 60: 155-73, 2008.
Article in English | MEDLINE | ID: mdl-18358320

ABSTRACT

The logarithm of an odds ratio (LOD) score method originated in a seminal article by Newton Morton in 1955. The method is broadly concerned with issues of power and the posterior probability of linkage, ensuring that a reported linkage has a high probability of being a true linkage. In addition, the method is sequential so that pedigrees or LOD curves may be combined from published reports to pool data for analysis. This approach has been remarkably successful for 50 years in identifying disease genes for Mendelian disorders. After discussing these issues, we consider the situation for complex disorders where the maximum LOD score statistic shares some of the advantages of the traditional LOD score approach, but is limited by unknown power and the lack of sharing of the primary data needed to optimally combine analytic results. We may still learn from the LOD score method as we explore new methods in molecular biology and genetic analysis to utilize the complete human DNA sequence and the cataloging of all human genes.


Subject(s)
Chromosome Mapping/methods , Genetic Linkage , Models, Genetic , Humans
3.
Nutr Metab (Lond) ; 3: 41, 2006 Dec 05.
Article in English | MEDLINE | ID: mdl-17147796

ABSTRACT

BACKGROUND: We report longitudinal changes in the metabolic syndrome (MetS) in 2,458 participants from 480 families in the Family Heart Study. Participants were examined between 1994-96 (FHS-T1) and 2002-03 (FHS-T2), about 7.4 years apart. Additionally, the impact of medication on estimates of MetS prevalence, and associations of MetS with prevalent coronary heart disease (CHD) and type 2 diabetes (T2D) were studied. METHODS: Three definitions for MetS prevalence were considered. One represented the original (o) National Cholesterol Education Program (NCEP) MetS criteria. Two others considered the confounding of medications effects, respectively (m) lipid medications constituted a categorical diagnostic criterion for lipids variables, and (c) lipids and blood pressure variables were corrected with average clinical trials medications effects. Logistic regression of MetS on CHD and T2D, as well as the trend analysis of MetS by age, were performed. RESULTS: MetS increased from 17.1% in FHS-T1(o) to 28.8% in FHS-T2(o); from 19.7% in FHS-T1(m) to 42.5% in FHS-T2(m); and from 18.4% in FHS-T1(c) to 33.6% in FHS-T2(c). While we observed adverse changes in all risk factors, the greatest increase was for waist circumference (25%). The percentages of MetS were about 2 to almost 3 times higher in ages 50 years and older than in younger ages. The odds of having prevalent CHD were about 2.5 times higher in the subjects classified with MetS than without. CONCLUSION: MetS percentages increased noticeably longitudinally and cross-sectionally with older age. These conclusions were reached with and without considering medication use, but correcting risk factors for medications use affects the MetS prevalence estimates. As found in other studies, MetS was associated with increased odds for prevalent CHD.

4.
Hum Hered ; 57(1): 21-7, 2004.
Article in English | MEDLINE | ID: mdl-15133309

ABSTRACT

OBJECTIVES: Some traits, while naturally polychotomous, are routinely dichotomized for genetic analysis. Dichotomization, intuitively, leads to a loss of power to detect linkage, as some phenotypic variability is discarded. This paper examines this power loss in the context of a trichotomous trait. METHODS: To examine this power loss, we performed a simulation study where a trichotomous trait was simulated in a sample of 1,000 sib-pairs under various genetic models. The study was replicated 1,000 times. Linkage analysis using a variance components method, as implemented in Mx, was then performed on the trichotomous trait and compared with that on a dichotomized version of the trait. RESULTS: A comparison of the power and false positive rates of the analyses shows that power to detect linkage was increased by up to 22 percentage points simply by examining the trait as a trichotomy instead of a dichotomy. Under all models examined, the trichotomous analysis outperformed the dichotomous version. CONCLUSIONS: Comparable levels of false positive rates under both methods confirm that this power gain comes solely from the information lost upon dichotomization. Thus, dichotomizing tri- or poly-chotomous traits can lead to crippling power loss, especially in the case of many loci of small effect.


Subject(s)
Genetic Linkage , Quantitative Trait, Heritable , Alleles , False Positive Reactions , Family Health , Gene Frequency , Humans , Likelihood Functions , Models, Genetic , Models, Statistical , Nuclear Family , Phenotype
5.
Alcohol Clin Exp Res ; 27(1): 93-9, 2003 Jan.
Article in English | MEDLINE | ID: mdl-12544012

ABSTRACT

BACKGROUND: Epidemiological studies of traits such as alcohol dependence and depression have often found lifetime rates in younger individuals exceeding those found in older individuals. This suggests additional influences of birth cohort or period effects so that individuals in later-born cohorts have an increased lifetime risk. METHODS: Data from the Collaborative Study on the Genetics of Alcoholism were used to investigate secular trends for alcoholism and related conditions and to examine risk predictors while taking the cohort effect into account. We used data on 4099 interviewed parents and siblings of alcohol-dependent subjects and 1054 members of control families. We used survival analysis techniques and the Cox proportional hazards regression model to estimate the relative risk for demographic covariates. We used the relative sample to predict risk in the sibling of the proband and family history information to determine whether there was a bias when deceased individuals were excluded from analysis. RESULTS: In the control sample, we observed a 1.8% lifetime rate of DSM-III-R alcohol dependence in women born before 1940, as contrasted to a 13% rate in women born after 1960, and a 15% lifetime rate in men born before 1940, contrasted with a 28% rate in men born after 1960. As expected, lifetime rates in relatives were increased when compared with controls. Highly significant risk ratios (RR) were observed for gender (RR, 2.3), cohort of birth (RR, 1.5 over a decade), daily smoking (RR, 2.0), heavy smoking (RR, 3.0), and comorbid diagnoses of antisocial personality (RR, 2.2) and depression (RR, 1.6). Analysis of the family history data indicated higher rates of alcohol dependence in relatives who were deceased compared to those who were living. CONCLUSIONS: Marked cohort differences were observed and may reflect real changes over time, or artifacts of memory recall, differential mortality, or public awareness. The analysis of all relatives (living or deceased) indicates that associated mortality may, in part, explain the secular trends seen when analyses are restricted to living, personally interviewed individuals.


Subject(s)
Alcoholism/epidemiology , Alcoholism/genetics , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Chi-Square Distribution , Cohort Effect , Cohort Studies , Comorbidity/trends , Depression/epidemiology , Depression/genetics , Female , Humans , Logistic Models , Male , Middle Aged , Multivariate Analysis , Odds Ratio , Proportional Hazards Models
6.
BMC Genet ; 4 Suppl 1: S5, 2003 Dec 31.
Article in English | MEDLINE | ID: mdl-14975073

ABSTRACT

We used a random coefficient regression (RCR) model to estimate growth parameters for the time series of observed serum glucose levels in the Replicate 1 of the Genetic Analysis Workshop 13 simulated data. For comparison, a two time-point interval was also selected and the slope between these two observations was calculated. This process yielded four phenotypes: the RCR growth phenotype, a two time-point slope phenotype, and Time 1 and Time 2 serum glucose level phenotypes. These four phenotypes were used for linkage analyses on simulated chromosomes 5, 7, 9, and 21, those chromosomes that contained loci affecting the growth course for serum glucose levels. The linkage analysis of the RCR-derived phenotype showed overwhelming evidence for linkage at one locus (LOD 65.78 on chromosome 5), while showing elevated but nonsignificant LOD scores for two other loci (LOD 1.25 on chromosome 7, LOD 1.10 on chromosome 9), and no evidence of linkage for the final locus. The two time-point slope phenotype showed evidence for linkage at one locus (LOD 4.16 on chromosome 5) but no evidence for linkage at any of the other loci. A parallel cross-sectional approach, using as input phenotypes the endpoints of the two-point slope phenotype, gave strong linkage results for the major locus on chromosome 5 (maximal LOD scores of 17.90 and 27.24 for Time 1 and Time 2, respectively) while showing elevated but nonsignificant linkage results on chromosome 7 (maximal LOD scores of 1.71 and 1.48) and no evidence for linkage at the two remaining loci. The RCR growth parameter showed more power to detect linkage to the major locus than either the cross-sectional or two-point slope approach, but the cross-sectional approach gave a higher maximal LOD score for one of the minor loci.


Subject(s)
Growth/genetics , Models, Statistical , Adult Children , Blood Glucose/genetics , Blood Glucose/physiology , Chromosomes, Human, Pair 7/genetics , Computer Simulation/statistics & numerical data , Female , Genetic Linkage/genetics , Growth/physiology , Humans , Lod Score , Longitudinal Studies , Male , Phenotype , Population Surveillance/methods , Time Factors
SELECTION OF CITATIONS
SEARCH DETAIL