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This version published online on June 27, 2006
Journal of Clinical Endocrinology & Metabolism, doi:10.1210/jc.2006-0150
A more recent version of this article appeared on September 1, 2006
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Submitted on January 23, 2006
Accepted on June 19, 2006

Weight-adjusted Genome Scan Analysis for mapping Quantitative Trait Loci for Menarchal Age

Anya Rothenbuhler, Delphine Fradin, Simon Heath, Hervé Lefevre, Claire Bouvattier, Marc Lathrop, and Pierre Bougnères*

Department of Pediatric Endocrinology and U561 - Institut National de la Santé et de la recherche Médicale, Hôpital Saint-Vincent de Paul, Paris, France; Centre National de Génotypage, Evry, France

* To whom correspondence should be addressed. E-mail: pierre.bougneres{at}wanadoo.fr.

Context: Twin and family studies indicate that genetic factors contribute to the variability of age at menarche (AAM), a multifactorial trait of major importance to human reproductive success. Individual variability of pre-menarcheal fatness is known to be an important determinant of AAM.

Objective: Mapping quantitative trait loci (QTLs) for AAM.

Design and methods: AAM was assessed in 98 sister-pairs of recent European ancestry whose growth charts were available. There was a negative correlation between menarcheal body weight SDS, and AAM (r=0.47, P < 0.0001). We designed a genome scan approach and used the variance components model implemented in Merlin for quantitative traits to evaluate linkage of AAM and AAM adjusted for menarcheal weight SDS to 418 genome-wide microsatellites.

Results: Multipoint linkage analysis for AAM revealed nominal QTLs defined by LOD scores between 1.06 and 1.69 on chromosomes 1p, 1q, 7p, 8q, 16p, 19q and 20q. The genome scan for AAM adjusted for menarcheal weight SDS revealed several QTLs with strongly suggestive LOD scores in 16q21 (LOD=3.33), 16q12 (LOD=3.12) and 8p12 (LOD=2.18) and a number of nominally significant other QTLs yet viewed as hypothetical.

Conclusions: We found several regions that may contain determinants of AAM, but there is still a long series of steps to confirm these QTLs and to identify the genomic polymorphisms implicated in AAM variability.




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