Meta‐Analysis of Linkage Studies for Complex Diseases: An Overview of Methods and a Simulation Study

Dempfle, Astrid; Loesgen, Sabine

doi:10.1046/j.1529-8817.2003.00061.x

Cited by 28 publications

(22 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Mapping of the eight most prominent regions from mice to the human genome revealed 40 syntenic fragments on 13 human chromosomes, which contain 18 candidate genes and genetic loci from human studies, three genetic loci implicated in human genetic syndromes with obesity, and 13 genes that affect obesity-related traits in rodent models ( Figure 3). Collectively, the bins with the five highest LOD scores for body weight (8,11,14,41, and 62; P ¼ 1.1 Â 10 À13 -9.9 Â 10…”

Section: Syntenic Regions On Human Chromosomesmentioning

confidence: 99%

A meta-analysis of quantitative trait loci associated with body weight and adiposity in mice

et al. 2006

View full text Add to dashboard Cite

Objective: Cross-breeding experiments with different mouse strains have successfully been used by many groups to identify genetic loci that predispose for obesity. In order to provide a statistical assessment of these quantitative trait loci (QTL) as a basis for a systematic investigation of candidate genes, we have performed a meta-analysis of genome-wide linkage scans for body weight and body fat. Data: From a total of 34 published mouse cross-breeding experiments, we compiled a list of 162 non-redundant QTL for body weight and 117 QTL for fat weight and body fat percentage. Collectively, these studies include data from 42 different parental mouse strains and 414 500 individual mice. Methods: The results of the studies were analyzed using the truncated product method (TPM). Results: The analysis revealed significant evidence (logarithm of odds (LOD) score 44.3) for linkage of body weight and adiposity to 49 different segments of the mouse genome. The most prominent regions with linkage for body weight and body fat (LOD scores 14.8-21.8) on chromosomes 1, 2, 7, 11, 15, and 17 contain a total of 58 QTL for body weight and body fat. At least 34 candidate genes and genetic loci, which have been implicated in regulation of body weight and body composition in rodents and/or humans, are found in these regions, including CCAAT/enhancer-binding protein alpha (C/EBPA), sterol regulatory element-binding transcription factor 1 (SREBP-1), peroxisome proliferator activator receptor delta (PPARD), and hydroxysteroid 11-beta dehydrogenase 1 (HSD11B1). Our results demonstrate the presence of numerous distinct consensus QTL regions with highly significant LOD scores that control body weight and body composition. An interactive physical map of the QTL is available online at

show abstract

Section: Syntenic Regions On Human Chromosomesmentioning

confidence: 99%

A meta-analysis of quantitative trait loci associated with body weight and adiposity in mice

et al. 2006

View full text Add to dashboard Cite

show abstract

“…Genome-wide linkage scans in MI have shown that genetic factors play a role in the disease, but the exact inheritance pattern is still unknown. These genome scans on MI have produced inconclusive inferences, because the linkage signals tend to be rather low, the number of families and affected sibpairs are relatively small, and the individual genome scans identify linkage in different chromosomal regions (Dempfle and Loesgen 2004).…”

Section: Introductionmentioning

confidence: 99%

Identification of chromosomal regions linked to premature myocardial infarction: a meta-analysis of whole-genome searches

Ζιντζαράς

Kitsios

2006

J Hum Genet

View full text Add to dashboard Cite

Myocardial infarction (MI) is a complication of coronary artery disease and the leading cause of death in the Western world. MI is considered a distinct phenotype with an increased genetic component for its premature type. MI's exact inheritance pattern is still unknown. Genome searches for identifying susceptibility loci for premature MI produced inconclusive or inconsistent results. Thus, a genome search metaanalysis (GSMA) was applied to available genome search data on premature MI. GSMA is a non-parametric method to identify genetic regions that rank high, on average in terms of linkage statistics across genome searches unweighted or weighted by study size. The significance of each region's average and heterogeneity, unadjusted or adjusted by neighbouring average simulated ranks, was calculated using a Monte Carlo test. The meta-analysis involved five genome searches in Caucasians. 3) were found to have significant average rank by either unweighted or weighted analyses. In addition, region 8q24.21-8q24.3 produced significant low heterogeneity (P unadjusted =0.03 and P adjusted =0.05). Four regions (6p22.3-6p21.1, 14p13-14q13.1, 8q13.2-8q22.2, 8q24.21-8q24.3) were not identified by the individual studies. The meta-analysis suggests that these four regions should be further investigated for genes that confer susceptibility to MI.

show abstract

“…19,21,30 The scope and limitations of the GSMA method and alternatives to it have been well explored. 9,32 The method is at its most useful when there are many weakly linked loci seen across many studies. However, the main limitation in our analysis is not the method as such but the fact that we are limited to just five relatively heterogeneous studies.…”

Section: Meta-analysis Of Genome-wide Bmi Scans L Johnson Et Almentioning

confidence: 99%

Meta-analysis of five genome-wide linkage studies for body mass index reveals significant evidence for linkage to chromosome 8p

et al. 2005

View full text Add to dashboard Cite

OBJECTIVE:To perform a meta-analysis of genome-wide linkage scans using body mass index (BMI) to identify genetic loci predisposing to obesity. DATA: A total of 13 published genome scans on obesity have used BMI as their primary end point. Five of these 13 groups agreed to provide detailed results from their scans that were required for a meta-analysis. Collectively, these five studies included a total of 2814 individuals from 505 families. METHODS: The results of the five studies were analysed using the GSMA (genome scans meta-analysis) method. RESULTS: The analysis revealed significant evidence for linkage of the quantitative phenotype BMI to 8p (Po0.0005).

show abstract

Meta‐Analysis of Linkage Studies for Complex Diseases: An Overview of Methods and a Simulation Study

Cited by 28 publications

References 51 publications

A meta-analysis of quantitative trait loci associated with body weight and adiposity in mice

A meta-analysis of quantitative trait loci associated with body weight and adiposity in mice

Identification of chromosomal regions linked to premature myocardial infarction: a meta-analysis of whole-genome searches

Meta-analysis of five genome-wide linkage studies for body mass index reveals significant evidence for linkage to chromosome 8p

Contact Info

Product

Resources

About