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Family Design (family + design)

Distribution by Scientific Domains

Medical Sciences	33%
Life Sciences	33%

Selected Abstracts

Not by Twins Alone: Using the Extended Family Design to Investigate Genetic Influence on Political Beliefs

AMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 3 2010
Peter K. Hatemi
Variance components estimates of political and social attitudes suggest a substantial level of genetic influence, but the results have been challenged because they rely on data from twins only. In this analysis, we include responses from parents and nontwin full siblings of twins, account for measurement error by using a panel design, and estimate genetic and environmental variance by maximum-likelihood structural equation modeling. By doing so, we address the central concerns of critics, including that the twin-only design offers no verification of either the equal environments or random mating assumptions. Moving beyond the twin-only design leads to the conclusion that for most political and social attitudes, genetic influences account for an even greater proportion of individual differences than reported by studies using more limited data and more elementary estimation techniques. These findings make it increasingly difficult to deny that,however indirectly,genetics plays a role in the formation of political and social attitudes. [source]

FROM MICRO- TO MACROEVOLUTION THROUGH QUANTITATIVE GENETIC VARIATION: POSITIVE EVIDENCE FROM FIELD CRICKETS

EVOLUTION, Issue 10 2004
Mattieu Bégin
Abstract . -Quantitative genetics has been introduced to evolutionary biologists with the suggestion that microevolution could be directly linked to macroevolutionary patterns using, among other parameters, the additive genetic variance/ covariance matrix (G) which is a statistical representation of genetic constraints to evolution. However, little is known concerning the rate and pattern of evolution of G in nature, and it is uncertain whether the constraining effect of G is important over evolutionary time scales. To address these issues, seven species of field crickets from the genera Gryllus and Teleogryllus were reared in the laboratory, and quantitative genetic parameters for morphological traits were estimated from each of them using a nested full-sibling family design. We used three statistical approaches (T method, Flury hierarchy, and Mantel test) to compare G matrices or genetic correlation matrices in a phylogenetic framework. Results showed that G matrices were generally similar across species, with occasional differences between some species. We suggest that G has evolved at a low rate, a conclusion strengthened by the consideration that part of the observed across-species variation in G can be explained by the effect of a genotype by environment interaction. The observed pattern of G matrix variation between species could not be predicted by either morphological trait values or phylogeny. The constraint hypothesis was tested by comparing the multivariate orientation of the reconstructed ancestral G matrix to the orientation of the across-species divergence matrix (D matrix, based on mean trait values). The D matrix mainly revealed divergence in size and, to a much smaller extent, in a shape component related to the ovipositor length. This pattern of species divergence was found to be predictable from the ancestral G matrix in agreement with the expectation of the constraint hypothesis. Overall, these results suggest that the G matrix seems to have an influence on species divergence, and that macroevolution can be predicted, at least qualitatively, from quantitative genetic theory. Alternative explanations are discussed. [source]

The University of California, San Francisco Family Alcoholism Study.

ALCOHOLISM, Issue 10 2004

Background: The University of California, San Francisco (UCSF) Family Alcoholism Study is a project designed to identify genetic loci that influence susceptibility to alcohol dependence and related phenotypes. Evidence supports a substantial genetic contribution to alcoholism susceptibility. However, the genetic epidemiology of alcoholism is complex, and its clinical manifestation is heterogeneous, making phenotype definition and demonstration of linkage difficult. Despite these challenges, some progress has been made toward identifying genes. Methods: The UCSF Family Alcoholism Study used a small family design, focusing primarily on sibling pairs and parent-child trios for linkage and association studies. Alcoholism-related phenotypes were assessed through interview and self-report questionnaires, with a focus on unidimensional and subphenotypical traits. Data-driven approaches to determining the most promising phenotypes for genetic analysis are being used. Both genome-wide scan and candidate gene approaches were used. Results: The study enrolled 2154 individuals from 970 families from December 1995 through January 2003. Test-retest and interrater reliability for clinical data are very good, and power estimates suggest that this study will have adequate power by linkage analysis to detect loci with moderate effects. Design, methods, and sample demographics of the UCSF Family Study are presented, along with intrafamilial correlations for primary diagnostic phenotypes. Conclusions: Plans for genetic analysis, novel approaches to phenotype refinement, and the implications of ascertainment bias for heritability estimates are discussed. [source]

The impact of alcohol-specific rules, parental norms about early drinking and parental alcohol use on adolescents' drinking behavior

THE JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY AND ALLIED DISCIPLINES, Issue 12 2006
Haske Van Der Vorst
Background:, The present study explores the role of having rules about alcohol, parental norms about early alcohol use, and parental alcohol use in the development of adolescents' drinking behavior. It is assumed that parental norms and alcohol use affect the rules parents have about alcohol, which in turn prevents alcohol use by adolescent children. Methods:, Longitudinal data collected from 416 families consisting of both parents and two adolescents (aged 13 to 16 years) were used for the analyses. Results:, Results of structural equation modeling show that having clear rules decreases the likelihood of drinking in adolescence. However, longitudinally alcohol-specific rules have only an indirect effect on adolescents' alcohol use, namely through earlier drinking. Analyses focusing on explaining the onset of drinking revealed that having strict rules was related to the postponement of drinking initiation of older and younger adolescents. Further, parental norms about adolescents' early drinking and parental alcohol use were associated with having alcohol-specific rules. Parental norms were also related to adolescents' alcohol use. Conclusions:, The current study is one of the first using a full family design to provide insight into the role of alcohol-specific rules on adolescents' drinking. It was shown that having strict rules is related to postponement of drinking, and that having alcohol-specific rules depends on other factors, thus underlining the complexity of the influence of parenting on the development of adolescents' alcohol use. [source]

A new multimarker test for family-based association studies

GENETIC EPIDEMIOLOGY, Issue 1 2007
Cyril S. Rakovski
Abstract We propose a new multimarker test for family-based studies in candidate genes. We use simulations under different genetic models to assess the performance of competing testing strategies, characterized in this study as combinations of the following important factors: genes, statistical tests, tag single nucleotide polymorphisms (SNP) methods, number of tag SNPs and family designs. An ANOVA model is employed to provide descriptive summaries of the effects on power of the above-mentioned factors. We find that tag SNP methods, gene characteristics and family designs have minimal impact on the best testing strategy. The familywise error rate (FWER) controlling multiple comparison procedure and the new multimarker test offer the highest power followed by the asymptotic global haplotype test. Both the FWER and the multimarker test are invariant to family designs and gain power as we increase the number of tag SNPs. However, the performance of the global haplotype test is slightly degraded when analyzing larger numbers of tag SNPs. Within the framework of our study, the best strategy for family-based studies in candidate genes that emerged from our analysis is to use the FWER or the multimarker test and select 6,10 tag SNPs using any of the tag SNP methods considered. We confirm the conclusions of our study with an application to Alzheimer's disease data. Genet. Epidemiol. © 2006 Wiley-Liss, Inc. [source]

Generalized marker regression and interval QTL mapping methods for binary traits in half-sib family designs

JOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 5 2001
H. N. Kadarmideen
A Generalized Marker Regression Mapping (GMR) approach was developed for mapping Quantitative Trait Loci (QTL) affecting binary polygenic traits in a single-family half-sib design. The GMR is based on threshold-liability model theory and regression of offspring phenotype on expected marker genotypes at flanking marker loci. Using simulation, statistical power and bias of QTL mapping for binary traits by GMR was compared with full QTL interval mapping based on a threshold model (GIM) and with a linear marker regression mapping method (LMR). Empirical significance threshold values, power and estimates of QTL location and effect were identical for GIM and GMR when QTL mapping was restricted to within the marker interval. These results show that the theory of the marker regression method for QTL mapping is also applicable to binary traits and possibly for traits with other non-normal distributions. The linear and threshold models based on marker regression (LMR and GMR) also resulted in similar estimates and power for large progeny group sizes, indicating that LMR can be used for binary data for balanced designs with large families, as this method is computationally simpler than GMR. GMR may have a greater potential than LMR for QTL mapping for binary traits in complex situations such as QTL mapping with complex pedigrees, random models and models with interactions. Generalisierte Marker Regression und Intervall QTL Kartierungsmethoden für binäre Merkmale in einem Halbgeschwisterdesign Es wurde ein Ansatz zur generalisierten Marker Regressions Kartierung (GMR) entwickelt, um quantitative Merkmalsloci (QTL) zu kartieren, die binäre polygenetische Merkmale in einem Einfamilien-Halbgeschwisterdesign beeinflussen. Das GMR basiert auf der Theorie eines Schwellenwertmodells und auf der Regression des Nachkommenphänotyps auf den erwarteten Markergenotyp der flankierenden Markerloci. Mittels Simulation wurde die statistische Power und Schiefe der QTL Kartierung für binäre Merkmale nach GMR verglichen mit vollständiger QTL Intervallkartierung, die auf einem Schwellenmodell (GIM) basiert, und mit einer Methode zur linearen Marker Regressions Kartierung (LMR). Empirische Signifikanzschwellenwerte, Power und Schätzer für die QTL Lokation und der Effekt waren für GIM und GMR identisch, so lange die QTL Kartierung innerhalb des Markerintervalls definiert war. Diese Ergebnisse zeigen, dass die Theorie der Marker Regressions-Methode zur QTL Kartierung auch für binäre Merkmale und möglicherweise auch für Merkmale, die keiner Normalverteilung folgen, geeignet ist. Die linearen und Schwellenmodelle, die auf Marker Regression (LMR und GMR) basieren, ergaben ebenfalls ähnliche Schätzer und Power bei großen Nachkommengruppen, was schlussfolgern lässt, dass LMR für binäre Daten in einem balancierten Design mit großen Familien genutzt werden kann. Schließlich ist diese Methode computertechnisch einfacher als GMR. GMR mag für die QTL Kartierung bei binären Merkmalen in komplexen Situationen ein größeres Potential haben als LMR. Ein Beispiel dafür ist die QTL Kartierung mit komplexen Pedigrees, zufälligen Modellen und Interaktionsmodellen. [source]