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  • 1
    In: Human Heredity, S. Karger AG, Vol. 62, No. 1 ( 2006), p. 20-29
    Abstract: 〈 i 〉 Objective: 〈 /i 〉 To evaluate the relevance and necessity to account for the effects of population substructure on association studies under a case-control design in central Europe, we analysed three samples drawn from different geographic areas of Germany. Two of the three samples, POPGEN (n = 720) and SHIP (n = 709), are from north and north-east Germany, respectively, and one sample, KORA (n = 730), is from southern Germany. 〈 i 〉 Methods: 〈 /i 〉 Population genetic differentiation was measured by classical F-statistics for different marker sets, either consisting of genome-wide selected coding SNPs located in functional genes, or consisting of selectively neutral SNPs from ‘genomic deserts’. Quantitative estimates of the degree of stratification were performed comparing the genomic control approach [Devlin B, Roeder K: Biometrics 1999;55:997–1004] , structured association [Pritchard JK, Stephens M, Donnelly P: Genetics 2000;155:945–959] and sophisticated methods like random forests [Breiman L: Machine Learning 2001;45:5–32] . 〈 i 〉 Results: 〈 /i 〉 F-statistics showed that there exists a low genetic differentiation between the samples along a north-south gradient within Germany (F 〈 sub 〉 ST 〈 /sub 〉 (KORA/POPGEN): 1.7 · 10 〈 sup 〉 –4 〈 /sup 〉 ; F 〈 sub 〉 ST 〈 /sub 〉 (KORA/SHIP): 5.4 · 10 〈 sup 〉 –4 〈 /sup 〉 ; F 〈 sub 〉 ST 〈 /sub 〉 (POPGEN/SHIP): –1.3 · 10 〈 sup 〉 –5 〈 /sup 〉 ). 〈 i 〉 Conclusion: 〈 /i 〉 Although the F 〈 sub 〉 ST 〈 /sub 〉 -values are very small, indicating a minor degree of population structure, and are too low to be detectable from methods without using prior information of subpopulation membership, such as STRUCTURE [Pritchard JK, Stephens M, Donnelly P: Genetics 2000;155:945–959], they may be a possible source for confounding due to population stratification.
    Type of Medium: Online Resource
    ISSN: 0001-5652 , 1423-0062
    RVK:
    Language: English
    Publisher: S. Karger AG
    Publication Date: 2006
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    SSG: 12
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  • 2
    In: Human Heredity, S. Karger AG, Vol. 69, No. 4 ( 2010), p. 268-284
    Abstract: The Genome-Wide Association Study (GWAS) is the study design of choice for detecting common genetic risk factors for multifactorial diseases. The performance of full Genome-Wide Interaction Analyses (GWIA) has always been considered computationally challenging. Two-stage strategies to reduce the amount of numerical analysis require the detection of single marker effects or prior pathophysiological hypotheses before the analysis of interaction. This prevents the detection of pure epistatic effects. Our case-control study in idiopathic generalized epilepsy demonstrates that a full GWIA is feasible through use of data compression, specific data representation, interleaved data organization, and parallelization of the analysis on a multi-processor system. Following extensive quality control of the genotypes, our final list of top interaction hits contains only pairs of interacting SNPs with negligible marginal effects. The TOP HIT interaction was between a SNP-pair intragenic to gene 〈 i 〉 DNER 〈 /i 〉 (chr 2) and gene 〈 i 〉 CTNNA3 〈 /i 〉 (chr 10). Both of these genes are functionally involved in neuronal migration, synaptogenesis, and the formation of neuronal circuits. Our results therefore indicate a possible interaction between these two genes in epileptogenesis. Results from GWAS are beginning to reveal a ‘missing heritability’ in complex traits and diseases. Systematic, hypothesis-free analysis of epistatic interaction (GWIA) may help to close this increasingly recognized gap in heritability.
    Type of Medium: Online Resource
    ISSN: 0001-5652 , 1423-0062
    RVK:
    Language: English
    Publisher: S. Karger AG
    Publication Date: 2010
    detail.hit.zdb_id: 1482710-4
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  • 3
    In: The American Journal of Human Genetics, Elsevier BV, Vol. 66, No. 6 ( 2000-06), p. 1945-1957
    Type of Medium: Online Resource
    ISSN: 0002-9297
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2000
    detail.hit.zdb_id: 219384-X
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    S. Karger AG ; 2003
    In:  Human Heredity Vol. 56, No. 4 ( 2003), p. 200-211
    In: Human Heredity, S. Karger AG, Vol. 56, No. 4 ( 2003), p. 200-211
    Abstract: Complex traits are often governed by more than one trait locus. The first step towards an adequate model for such diseases is a linkage analysis with two trait loci. Such an analysis can be expected to have higher power to detect linkage than a standard single-trait-locus linkage analysis. However, it is crucial to accurately specify the parameters of the two-locus model. Here, we recapitulate the general two-locus model with and without genomic imprinting. We relate heterogeneity, multiplicative, and additive two-locus models to biological or pathophysiological mechanisms, and give the corresponding averaged (‘best-fitting’) single-trait-locus models for each of the two loci. Furthermore, we derive the two-locus penetrances from the averaged single-locus models, under the assumption of one of the three model classes mentioned above. Using these formulae, if the best-fitting single-locus models are available, investigators may perform a two-trait-locus linkage analysis under a realistic model. This procedure will maximize the power to detect linkage for traits which are governed by two or more loci, and lead to more accurate estimates of the disease-locus positions.
    Type of Medium: Online Resource
    ISSN: 0001-5652 , 1423-0062
    RVK:
    Language: English
    Publisher: S. Karger AG
    Publication Date: 2003
    detail.hit.zdb_id: 1482710-4
    detail.hit.zdb_id: 2424-7
    SSG: 12
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  • 5
    Online Resource
    Online Resource
    S. Karger AG ; 2004
    In:  Human Heredity Vol. 58, No. 1 ( 2004), p. 55-58
    In: Human Heredity, S. Karger AG, Vol. 58, No. 1 ( 2004), p. 55-58
    Abstract: We present a recoding scheme that allows for a parametric multipoint X-chromosomal linkage analysis of dichotomous traits in the context of a computer program for autosomes that can use trait models with imprinting. Furthermore, with this scheme, it is possible to perform a joint multipoint analysis of X-linked and pseudoautosomal loci. It is required that (1) the marker genotypes of all female nonfounders are available and that (2) there are no male nonfounders who have daughters in the pedigree. The second requirement does not apply if the trait locus is pseudoautosomal. The X-linked marker loci are recoded by adding a dummy allele to the males’ hemizygous genotypes. For modelling an X-linked trait locus, five different liability classes are defined, in conjunction with a paternal imprinting model for male nonfounders. The formulation aims at the mapping of a diallelic trait locus relative to an arbitrary number of codominant markers with known genetic distances, in cases where a program for a genuine X-chromosomal analysis is not available.
    Type of Medium: Online Resource
    ISSN: 0001-5652 , 1423-0062
    RVK:
    Language: English
    Publisher: S. Karger AG
    Publication Date: 2004
    detail.hit.zdb_id: 1482710-4
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  • 6
    Online Resource
    Online Resource
    Elsevier BV ; 2011
    In:  Forensic Science International: Genetics Vol. 5, No. 4 ( 2011-8), p. 297-302
    In: Forensic Science International: Genetics, Elsevier BV, Vol. 5, No. 4 ( 2011-8), p. 297-302
    Type of Medium: Online Resource
    ISSN: 1872-4973
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2011
    detail.hit.zdb_id: 2493339-9
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  • 7
    Online Resource
    Online Resource
    Wiley ; 1999
    In:  Genetic Epidemiology Vol. 17, No. S1 ( 1999-01)
    In: Genetic Epidemiology, Wiley, Vol. 17, No. S1 ( 1999-01)
    Abstract: Alcohol dependence often is a familial disorder and has a genetic component. Research in causative factors of alcoholism is coordinated by a multi‐center program, COGA [The Collaborative Study on the Genetics of Alcoholism, Begleiter et al., 1995]. We analyzed a subset of the COGA family sample, 84 pedigrees of Caucasian ancestry comprising 745 persons, 339 of whom are affected according to DSM‐III‐R and Feighner criteria. Using parametric and nonparametric methods, evidence for linkage was found on chromosome 1 (near markers D1S532, D1S1588, and D1S534), as well as on chromosome 15 (near marker D15S642). Other regions of the genome showed suggestive evidence for contributing loci. Related findings are discussed in recent publications investigating linkage in humans [Reich et al., 1998] and mice [Melo et al., 1996].
    Type of Medium: Online Resource
    ISSN: 0741-0395 , 1098-2272
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 1999
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    detail.hit.zdb_id: 1492643-X
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  • 8
    Online Resource
    Online Resource
    S. Karger AG ; 2003
    In:  Human Heredity Vol. 55, No. 4 ( 2003), p. 202-210
    In: Human Heredity, S. Karger AG, Vol. 55, No. 4 ( 2003), p. 202-210
    Abstract: Usually, when complex traits are at issue, not only are the loci of the responsible genes a priori unknown; the same also holds for the mode of inheritance of the trait, and sometimes even for the phenotype definition. The term mode of inheritance relates to both the genetic mechanism, i.e., the number of loci implicated in the etiology of the disease, and the genotype-phenotype relation, which describes the influence of these loci on the trait. Having an idea of the genetic model can crucially facilitate the mapping process. This holds especially in the context of linkage analysis, where an appropriate parametric model or a suitable nonparametric allele sharing statistic may accordingly be selected. Here, we review the difficulties with parametric and nonparametric linkage analysis when applied to multifactorial diseases. We address the question why it is necessary to adequately model a genetically complex trait in a linkage study, and elucidate the steps to do so. Furthermore, we discuss the value of including unaffected individuals into the analysis, as well as of looking at larger pedigrees, both with parametric and nonparametric methods. Our considerations and suggestions aim at guiding researchers to 〈 i 〉 genotyping individuals at a trait locus 〈 /i 〉 as accurately as possible.
    Type of Medium: Online Resource
    ISSN: 0001-5652 , 1423-0062
    RVK:
    Language: English
    Publisher: S. Karger AG
    Publication Date: 2003
    detail.hit.zdb_id: 1482710-4
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  • 9
    In: Genetic Epidemiology, Wiley, Vol. 17, No. S1 ( 1999-01)
    Abstract: We present an extension to parametric linkage analysis that allows modeling diseases with a parent‐of‐origin effect (i.e., imprinting). Different penetrances are assumed for individuals being heterozygous at the disease locus, depending on their having inherited the disease allele from the father or mother. Motivated by the finding of a maternally expressed locus influencing alcohol consumption in mice (A1cp2), the analysis method has been included into the program GENEHUNTER for application to Problem 1, Collaborative Study on the Genetics of Alcoholism of Genetic Analysis Workshop 11. By this extension, a powerful tool is provided for adequately modeling an inherited disease in linkage analysis that supposedly has imprinting effects. The program has been used to analyze the data set on alcohol dependence in humans and can be applied to other genetically determined traits as well.
    Type of Medium: Online Resource
    ISSN: 0741-0395 , 1098-2272
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 1999
    detail.hit.zdb_id: 605785-8
    detail.hit.zdb_id: 1492643-X
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  • 10
    Online Resource
    Online Resource
    Wiley ; 2001
    In:  Genetic Epidemiology Vol. 21, No. S1 ( 2001-01)
    In: Genetic Epidemiology, Wiley, Vol. 21, No. S1 ( 2001-01)
    Abstract: Asthma and atopy are two closely related, common complex traits in which a number of genetic and environmental factors are suspected to play a role. We have performed parametric and nonparametric multi‐marker linkage analysis for the Busselton data set, which is part of problem 1 of Genetic Analysis Workshop 12. In particular, we have focused on the dichotomous trait atopy, as well as on dichotomized versions of the quantitative traits RASTI and log e slope. The lod score analysis with adequate modeling of a parent‐of‐origin effect, by use of the program GENEHUNTER‐IMPRINTING, was of special interest. The most prominent findings are a multipoint mod score of 3.12 at D13S153 for RASTI, and a multipoint mod score of 4.32 at the same locus for atopy, both with four‐penetrance imprinting models that point to a gene subject to maternal imprinting. In addition, there are marked differences between imprinting and non‐imprinting mod scores. These results corroborate earlier findings of linkage between atopy and D13S153, but add the aspect of paternal gene expression. Furthermore, suggestive evidence for linkage to atopy is found near D6S291, D7S530, and D14S74. The best‐fitting models for chromosome 6 and 14 may suggest that genomic imprinting takes place at these two loci as well. © 2001 Wiley‐Liss, Inc.
    Type of Medium: Online Resource
    ISSN: 0741-0395 , 1098-2272
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2001
    detail.hit.zdb_id: 605785-8
    detail.hit.zdb_id: 1492643-X
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