title: Bivariate genome-wide linkage analysis for traits BMD and AAM: effect of menopause on linkage signals.
abstract: Osteoporosis is an age-related systemic skeletal disease, characterized by low bone mineral density (BMD). Low BMD is closely associated with late age at menarche (AAM). Our previous bivariate genome-wide linkage analyses (GWLAs) between BMD and AAM identified two shared genomic regions in 2584 Caucasian females including both pre- and post-menopausal females. However, menopause often causes dramatic bone loss in post-menopausal females; this may introduce some confounding effects on the bivariate GWLA for BMD and AAM. To address the effect of menopause on the identification of genetic factors shared by BMD and AAM, we segregated the previously studied population of 2584 females into two separate subgroups consisting of 1462 pre-menopause subjects and 1122 post-menopausal subjects, and performed further bivariate GWLAs. The BMD was measured by Hologic Dual-energy X-ray (DXA) scanners (Hologic Inc., Bedford, MA, USA). Based on the genome-wide thresholds corrected for multiple testing, we found more significant genomic regions in the pre-menopausal group than in total group (including pre- and post-menopausal women), e.g., we found 4, 1, and 2 shared by spine BMD and AAM, femoral neck (FNK) BMD and AAM and ultra distal (UD) BMD and AAM, respectively. We did not found any significant linkage signals in the post-menopausal group. Importantly, the linkage signals at all significant regions were much stronger in pre-menopausal group than in the other groups: post-menopausal females and total females. For example, the linkage LOD score for FNK BMD and AAM is as high as 4.88 in pre-menopausal females, but only 0.24 and 0.31 in post-menopausal and total females, respectively. These results suggest that menopause introduces some noise signals into GWLAs when estimating the shared genetic factors by BMD and AAM. Therefore, it is very important to classify female subjects properly according to their menopause stage when performing such studies.
authors.affiliation: Key Laboratory of Biomedical Information Engineering, Ministry of Education and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an Shaanxi 710049, PR China.
authors.forename: Zhi-Xin
authors.initials: ZX
authors.lastname: Zhang
authors.forename: Shu-Feng
authors.initials: SF
authors.lastname: Lei
authors.forename: Fei-Yan
authors.initials: FY
authors.lastname: Deng
authors.forename: Feng
authors.initials: F
authors.lastname: Zhang
authors.forename: Yong-Jun
authors.initials: YJ
authors.lastname: Liu
authors.forename: Robert R
authors.initials: RR
authors.lastname: Recker
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Papasian
authors.forename: Hong-Wen
authors.initials: HW
authors.lastname: Deng
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015519:Bone Density / Q000235:genetics*; D005260:Female; D008040:Genetic Linkage; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D006801:Humans; D008572:Menarche / Q000235:genetics*; D008875:Middle Aged; D017351:N-Acetylglucosaminyltransferases / Q000235:genetics; D010375:Pedigree; D017698:Postmenopause; D017697:Premenopause / Q000235:genetics*; D044465:White People; D000099058:Exostosin 1
chemical_list: D017351:N-Acetylglucosaminyltransferases; D000099058:Exostosin 1