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Large Pedigrees (large + pedigree)

Distribution by Scientific Domains

Life Sciences	83%
Medical Sciences	16%

Selected Abstracts

Autosomal Dominant Early-onset Cortical Myoclonus, Photic-induced Myoclonus, and Epilepsy in a Large Pedigree

EPILEPSIA, Issue 10 2006
Elena Gardella
Summary:,Purpose: Cortical tremor, a form of rhythmic cortical myoclonus (rhythmic CM), and epilepsy have been described in families with autosomal dominant inheritance. Linkage analyses revealed two putative loci on chromosome 2p and 8q. Clinical photosensitivity was not a prominent feature in such families. We describe a large Italian family with rhythmic CM, photosensitivity, and epilepsy. Methods: Twenty-three individuals of a five-generation family were studied. Linkage analyses for the loci on chromosome 2p11.1 and 8q23.3 were performed. Results: Of the 23 studied family members, 16 were affected. Rhythmic CM of childhood onset was present in all 16 individuals (onset ranging from 3 to 12 years), was associated with photic-induced myoclonic jerks in seven, and with epileptic seizures in six (onset ranging from 23 to 34 years). Five children of the V generation manifested also episodes of arousal with generalized tremor in early infancy ("tremulous arousals"). Jerk-locked back-averaging of rhythmic CM of six affected individuals, documented a premyoclonic EEG correlate. C-reflex at rest was present in two affected adults. Linkage analyses excluded mapping to the 2p11.1 and 8q23.3 loci. Conclusions: Clinical variability and severity of the phenotypes in this family are in line with those of previously described pedigrees with autosomal dominant cortical myoclonus and epilepsy. In this family, a progression of symptoms was found: rhythmic CM and tremulous arousals occurred in childhood, whereas visually induced manifestations and epileptic seizures occurred during adolescence,adulthood. Exclusion of linkage to the two known loci is consistent with genetic heterogeneity of such familial clustering of symptoms. [source]

MQScore_SNP Software for Multipoint Parametric Linkage Analysis of Quantitative Traits in Large Pedigrees

ANNALS OF HUMAN GENETICS, Issue 3 2010
Tatiana I. Axenovich
Summary We describe software for multipoint parametric linkage analysis of quantitative traits using information about SNP genotypes. A mixed model of major gene and polygene inheritance is implemented in this software. Implementation of several algorithms to avoid computational underflow and decrease running time permits application of our software to the analysis of very large pedigrees collected in human genetically isolated populations. We tested our software by performing linkage analysis of adult height in a large pedigree from a Dutch isolated population. Three significant and four suggestive loci were identified with the help of our programs, whereas variance-component-based linkage analysis, which requires the pedigree fragmentation, demonstrated only three suggestive peaks. The software package MQScore_SNP is available at http://mga.bionet.nsc.ru/soft/index.html. [source]

PedStr Software for Cutting Large Pedigrees for Haplotyping, IBD Computation and Multipoint Linkage Analysis

ANNALS OF HUMAN GENETICS, Issue 5 2009
Anatoly V. Kirichenko
Summary We propose an automatic heuristic algorithm for splitting large pedigrees into fragments of no more than a user-specified bit size. The algorithm specifically aims to split large pedigrees where many close relatives are genotyped and to produce a set of sub-pedigrees for haplotype reconstruction, IBD computation or multipoint linkage analysis with the help of the Lander-Green-Kruglyak algorithm. We demonstrate that a set of overlapping pedigree fragments constructed with the help of our algorithm allows fast and effective haplotype reconstruction and detection of an allele's parental origin. Moreover, we compared pedigree fragments constructed with the help of our algorithm and existing programs PedCut and Jenti for multipoint linkage analysis. Our algorithm demonstrated significantly higher linkage power than the algorithm of Jenti and significantly shorter running time than the algorithm of PedCut. The software package PedStr implementing our algorithms is available at http://mga.bionet.nsc.ru/soft/index.html. [source]

Estimating the power of variance component linkage analysis in large pedigrees

GENETIC EPIDEMIOLOGY, Issue 6 2006
Wei-Min Chen
Abstract Variance component linkage analysis is commonly used to map quantitative trait loci (QTLs) in general pedigrees. Large pedigrees are especially attractive for these studies because they provide greater power per genotyped individual than small pedigrees. We propose accurate and computationally efficient methods to calculate the analytical power of variance component linkage analysis that can accommodate large pedigrees. Our analytical power computation involves the approximation of the noncentrality parameter for the likelihood-ratio test by its Taylor expansions. We develop efficient algorithms to compute the second and third moments of the identical by descent (IBD) sharing distribution and enable rapid computation of the Taylor expansions. Our algorithms take advantage of natural symmetries in pedigrees and can accurately analyze many large pedigrees in a few seconds. We verify the accuracy of our power calculation via simulation in pedigrees with 2,5 generations and 2,8 siblings per sibship. We apply this proposed analytical power calculation to 98 quantitative traits in a cohort study of 6,148 Sardinians in which the largest pedigree includes 625 phenotyped individuals. Simulations based on eight representative traits show that the difference between our analytical estimation of the expected LOD score and the average of simulated LOD scores is less than 0.05 (1.5%). Although our analytical calculations are for a fully informative marker locus, in the settings we examined power was similar to what could be attained with a single nucleotide polymorphism (SNP) mapping panel (with >1 SNP/cM). Our algorithms for power analysis together with polygenic analysis are implemented in a freely available computer program, POLY. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source]

Relationship uncertainty linkage statistics (RULS): affected relative pair statistics that model relationship uncertainty

GENETIC EPIDEMIOLOGY, Issue 4 2008
Amrita Ray
Abstract Linkage analysis programs invariably assume that the stated familial relationships are correct. Thus, it is common practice to resolve relationship errors by either discarding individuals with erroneous relationships or using an inferred alternative pedigree structure. These approaches are less than ideal because discarding data is wasteful and using inferred data can be statistically unsound. We have developed two linkage statistics that model relationship uncertainty by weighting over the possible true relationships. Simulations of data containing relationship errors were used to assess our statistics and compare them to the maximum-likelihood statistic (MLS) and the Sall non-parametric LOD score using true and discarded (where problematic individuals with erroneous relationships are discarded from the pedigree) structures. We simulated both small pedigree (SP) and large pedigree (LP) data sets typed genome-wide. Both data sets have several underlying true relationships; SP has one apparent relationship,full sibling,and LP has several different apparent relationship types. The results show that for both SP and LP, our relationship uncertainty linkage statistics (RULS) have power nearly as high as the MLS and Sall using the true structure. Also, the RULS have greater power to detect linkage than the MLS and Sall using the discarded structure. For example, for the SP data set and a dominant disease model, both the RULS had power of about 93%, while Sall and MLS have 90% and 83% power on the discarded structure. Thus, our RULS provide a statistically sound and powerful approach to the commonly encountered problem of relationship errors. Genet. Epidemiol. © 2008 Wiley-Liss, Inc. [source]

Multiple Endocrine Neoplasia , Introduction

JOURNAL OF INTERNAL MEDICINE, Issue 1 2005
S. J. MARX
Abstract. Each multiple endocrine neoplasia (MEN) syndrome expresses striking features of hormone oversecretion from its own characteristic group of tissues. Additional expressions include non-hormonal tumours in each MEN syndrome and selected cancers in some syndromes. The complexity of its stereotyped features results in difficult management issues that often justify cooperation across multiple specialties. MEN syndromes, though rare, have long received intense study as models for more common diseases. The syndromal nature often with a large pedigree has promoted recent discovery of the main gene that differs for each of the six MEN syndromes. Each mutant gene has been introduced into clinical decision-making and into further clarification of tumorigenesis. This mini-symposium is related to the 9th International Workshop on Multiple Endocrine Neoplasia in June 2004; it consists of six manuscripts. They report new developments in clinical practices and in basic understandings about this rapidly advancing field. [source]

MQScore_SNP Software for Multipoint Parametric Linkage Analysis of Quantitative Traits in Large Pedigrees

Summary of contributions to GAW Group 15: family-based samples are useful in identifying common polymorphisms associated with complex traits

GENETIC EPIDEMIOLOGY, Issue S1 2009
Stacey Knight
Abstract Traditionally, family-based samples have been used for genetic analyses of single-gene traits caused by rare but highly penetrant risk variants. The utility of family-based genetic data for analyzing common complex traits is unclear and contains numerous challenges. To assess the utility as well as to address these challenges, members of Genetic Analysis Workshop 16 Group 15 analyzed Framingham Heart Study data using family-based designs ranging from parent,offspring trios to large pedigrees. We investigated different methods including traditional linkage tests, family-based association tests, and population-based tests that correct for relatedness between subjects, and tests to detect parent-of-origin effects. The analyses presented an assortment of positive findings. One contribution found increased power to detect epistatic effects through linkage using ascertainment of sibships based on extreme quantitative values or presence of disease associated with the quantitative value. Another contribution found four single-nucleotide polymorphisms (SNPs) showing a maternal effect, two SNPs with an imprinting effect, and one SNP having both effects on a binary high blood pressure trait. Finally, three contributions illustrated the advantage of using population-based methods to detect association to complex binary or quantitative traits. Our findings highlight the contribution of family-based samples to the genetic dissection of complex traits. Genet. Epidemiol. 33 (Suppl. 1):S99,S104, 2009. © 2009 Wiley-Liss, Inc. [source]

A multiple splitting approach to linkage analysis in large pedigrees identifies a linkage to asthma on chromosome 12

GENETIC EPIDEMIOLOGY, Issue 3 2009
Céline Bellenguez
Abstract Large genealogies are potentially very informative for linkage analysis. However, the software available for exact non-parametric multipoint linkage analysis is limited with respect to the complexity of the families it can handle. A solution is to split the large pedigrees into sub-families meeting complexity constraints. Different methods have been proposed to "best" split large genealogies. Here, we propose a new procedure in which linkage is performed on several carefully chosen sub-pedigree sets from the genealogy instead of using just a single sub-pedigree set. Our multiple splitting procedure capitalizes on the sensitivity of linkage results to family structure and has been designed to control computational feasibility and global type I error. We describe and apply this procedure to the extreme case of the highly complex Hutterite pedigree and use it to perform a genome-wide linkage analysis on asthma. The detection of a genome-wide significant linkage for asthma on chromosome 12q21 illustrates the potential of this multiple splitting approach. Genet. Epidemiol. 2009. © 2008 Wiley-Liss, Inc. [source]

Estimating the power of variance component linkage analysis in large pedigrees

Robust estimation of critical values for genome scans to detect linkage

GENETIC EPIDEMIOLOGY, Issue 1 2005
Silviu-Alin BacanuArticle first published online: 15 SEP 200
Abstract Estimation of study specific critical values for linkage scans (suggestive and significant thresholds) is important to identify promising regions. In this report, I propose a fast and concrete recipe for finding study specific critical values. Previously, critical values were derived theoretically or empirically. Theoretically-derived values are often conservative due to their assumption of fully informative transmissions. Empirically-derived critical values are computer and skill intensive and may not even be computationally feasible for large pedigrees. In this report, I propose a method to estimate critical values for multipoint linkage analysis using standard, widely used statistical software. The proposed method estimates study-specific critical values by using Autoregressive (AR) models to estimate the correlation between standard normal statistics at adjacent map points and then use this correlation to estimate study-specific critical values. The AR-based method is evaluated using different family structures and density of markers, under both the null hypothesis of no linkage and the alternative hypothesis of linkage between marker and disease locus. Simulations results show the AR-based method accurately predicts critical values for a wide range of study designs. © 2004 Wiley-Liss, Inc. [source]

Linkage analysis with sequential imputation

GENETIC EPIDEMIOLOGY, Issue 1 2003
Zachary Skrivanek
Abstract Multilocus calculations, using all available information on all pedigree members, are important for linkage analysis. Exact calculation methods in linkage analysis are limited in either the number of loci or the number of pedigree members they can handle. In this article, we propose a Monte Carlo method for linkage analysis based on sequential imputation. Unlike exact methods, sequential imputation can handle large pedigrees with a moderate number of loci in its current implementation. This Monte Carlo method is an application of importance sampling, in which we sequentially impute ordered genotypes locus by locus, and then impute inheritance vectors conditioned on these genotypes. The resulting inheritance vectors, together with the importance sampling weights, are used to derive a consistent estimator of any linkage statistic of interest. The linkage statistic can be parametric or nonparametric; we focus on nonparametric linkage statistics. We demonstrate that accurate estimates can be achieved within a reasonable computing time. A simulation study illustrates the potential gain in power using our method for multilocus linkage analysis with large pedigrees. We simulated data at six markers under three models. We analyzed them using both sequential imputation and GENEHUNTER. GENEHUNTER had to drop between 38,54% of pedigree members, whereas our method was able to use all pedigree members. The power gains of using all pedigree members were substantial under 2 of the 3 models. We implemented sequential imputation for multilocus linkage analysis in a user-friendly software package called SIMPLE. Genet Epidemiol 25:25,35, 2003. © 2003 Wiley-Liss, Inc. [source]

MQScore_SNP Software for Multipoint Parametric Linkage Analysis of Quantitative Traits in Large Pedigrees

PedStr Software for Cutting Large Pedigrees for Haplotyping, IBD Computation and Multipoint Linkage Analysis

Non-progressive congenital ataxia with cerebellar hypoplasia in three families

ACTA PAEDIATRICA, Issue 2 2005
Z Yapici
Abstract Aim: Non-progressive ataxias with cerebellar hypoplasia are a rarely seen heterogeneous group of hereditary cerebellar ataxias. Method: Three sib pairs from three different families with this entity have been reviewed, and differential diagnosis has been discussed. Results: In two of the families, the parents were consanguineous. Walking was delayed in all the children. Truncal and extremity ataxia were then noticed. Ataxia was severe in one child, moderate in two children, and mild in the remaining three. Neurological examination revealed horizontal, horizonto-rotatory and/or vertical nystagmus, variable degrees of mental retardation, and pyramidal signs besides truncal and extremity ataxia. In all the cases, cerebellar hemisphere and vermis hypoplasia were detected in MRI. During the follow-up period, a gradual clinical improvement was achieved in all the children. Conclusion: Inheritance should be considered as autosomal recessive in some of the non-progressive ataxic syndromes. Congenital non-progressive ataxias are still being investigated due to the rarity of large pedigrees for genetic studies. If further information on the aetiopathogenesis and clinical progression of childhood ataxias associated with cerebellar hypoplasia is to be acquired, a combined evaluation of metabolic screening, long-term follow-up and radiological analyses is essential. [source]