Article

Genome-wide association analyses identify SPOCK as a key novel gene underlying age at menarche.

School of Medicine, University of Missouri Kansas City, Kansas City, Missouri, United States of America.
PLoS Genetics (Impact Factor: 8.17). 03/2009; 5(3):e1000420. DOI: 10.1371/journal.pgen.1000420
Source: PubMed

ABSTRACT For females, menarche is a most significant physiological event. Age at menarche (AAM) is a trait with high genetic determination and is associated with major complex diseases in women. However, specific genes for AAM variation are largely unknown. To identify genetic factors underlying AAM variation, a genome-wide association study (GWAS) examining about 380,000 SNPs was conducted in 477 Caucasian women. A follow-up replication study was performed to validate our major GWAS findings using two independent Caucasian cohorts with 854 siblings and 762 unrelated subjects, respectively, and one Chinese cohort of 1,387 unrelated subjects--all females. Our GWAS identified a novel gene, SPOCK (Sparc/Osteonectin, CWCV, and Kazal-like domains proteoglycan), which had seven SNPs associated with AAM with genome-wide false discovery rate (FDR) q<0.05. Six most significant SNPs of the gene were selected for validation in three independent replication cohorts. All of the six SNPs were replicated in at least one cohort. In particular, SNPs rs13357391 and rs1859345 were replicated both within and across different ethnic groups in all three cohorts, with p values of 5.09 x 10(-3) and 4.37 x 10(-3), respectively, in the Chinese cohort and combined p values (obtained by Fisher's method) of 5.19 x 10(-5) and 1.02 x 10(-4), respectively, in all three replication cohorts. Interestingly, SPOCK can inhibit activation of MMP-2 (matrix metalloproteinase-2), a key factor promoting endometrial menstrual breakdown and onset of menstrual bleeding. Our findings, together with the functional relevance, strongly supported that the SPOCK gene underlies variation of AAM.

0 Bookmarks
 · 
109 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Various observational studies have focused on the relationship between menarcheal age and the risk of colorectal cancer (CRC). However, the association is still controversial because of inconsistent results. Therefore, we performed a meta-analysis to assess this issue from epidemiological studies. After a literature search in MEDLINE, EMBASE, and Web of Science for studies of menarcheal age and CRC risk published through the end of January 2013, we pooled the relative risks (RRs) from included studies using a fixed- or random-effects model and performed heterogeneity and publication bias analyses. All statistical tests were two-sided. Eleven case-control and 11 cohort studies were eligible for inclusion in our analysis. The random-effects pooled RR for oldest versus youngest menarcheal age was 0.95 [95% confidence intervals (CIs) = 0.85-1.06], with significant heterogeneity (Q = 61.03, P<0.001, I (2) = 65.6%). When separately analyzed, case-control (RR = 0.95, 95% CI = 0.75-1.21) and cohort studies (RR = 0.97, 95% CI = 0.90-1.04) yielded similar results. Moreover, similar results were also observed among the subgroup analyses by study quality, population, exposure assessment, anatomic cancer site, subsite of colon cancer, and several potential important confounders and risk factors. There was no evidence of publication bias and significant heterogeneity between subgroups detected by meta-regression analyses. Findings from this meta-analysis demonstrated that menarcheal age was not associated with the risk of CRC in humans. Further studies are warranted to stratify results by the subsite of colon cancer and menopause status in the future.
    PLoS ONE 06/2013; 8(6):e65645. · 3.53 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Human pygmy populations inhabit different regions of the world, from Africa to Melanesia. In Asia, short-statured populations are often referred to as "negritos." Their short stature has been interpreted as a consequence of thermoregulatory, nutritional, and/or locomotory adaptations to life in tropical forests. A more recent hypothesis proposes that their stature is the outcome of a life history trade-off in high-mortality environments, where early reproduction is favored and, consequently, early sexual maturation and early growth cessation have coevolved. Some serological evidence of deficiencies in the growth hormone/insulin-like growth factor axis have been previously associated with pygmies' short stature. Using genome-wide single-nucleotide polymorphism genotype data, we first tested whether different negrito groups living in the Philippines and Papua New Guinea are closely related and then investigated genomic signals of recent positive selection in African, Asian, and Papuan pygmy populations. We found that negritos in the Philippines and Papua New Guinea are genetically more similar to their nonpygmy neighbors than to one another and have experienced positive selection at different genes. These results indicate that geographically distant pygmy groups are likely to have evolved their short stature independently. We also found that selection on common height variants is unlikely to explain their short stature and that different genes associated with growth, thyroid function, and sexual development are under selection in different pygmy groups.
    Human Biology 12/2013; 85(1-3):251-84. · 1.52 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Systems genetics is a new discipline based on the transcription mapping, which is also called “genetical genomics”. In recent years, systems genetics has become more practical because of advances in science and technology. Analysis of expression quantitative trait loci (eQTLs) is an emerging technique in which individuals are genotyped across a panel of genetic markers and, simultaneously, phenotyped using DNA microarrays. Depending on eQTL mapping, one can infer the underlying regulatory network responsible for complex diseases or quantitative trait phenotypes. Systems genetics approaches integrate DNA sequence variation, variation in transcript abundance and other molecular phenotypes and variation in organismal phenotypes in a linkage or association mapping population, and allow us to interpret quantitative genetic variation in terms of biologically meaningful causal networks of correlated transcripts. These approaches have been made possible due to the development of massively parallel technologies for quantifying genome-wide levels of transcript abundance. The predictive power of the networks could be enhanced by more systematically integrating protein-protein interactions, protein-DNA interactions, protein-RNA interactions, RNA-RNA interactions, protein state information, methylation state, and interactions with metabolites. Systems genetics research will change the traditional approaches based on reductionism, and allows us to reconsider the living phenomenon and complex disease mechanism. Systems genetics benefits from varied “omics” researches (such as transcriptomics, metabolomics, and phenomics) and the development of bioinformatics tools and mathematical modeling, and will become mature in the near future like many other branches of genetics. Systems genetics is leading researchers to understand genetics systems from holism’s viewpoint, and will open a wide field of vision for genetics researchers in systems biology era.
    Biologia 06/2012; 67(3). · 0.70 Impact Factor

Full-text (2 Sources)

Download
48 Downloads
Available from
May 22, 2014