Dataset Information

Mammary-digital-nail (MDN) syndrome: a novel phenotype maps to human chromosome 22q12.3-13.1.

ABSTRACT: Mammary-digital-nail syndrome is a novel phenotypic association consisting of anonychia onychodystrophy with hypoplasia or absence of distal phalanges in males and females, accompanied by juvenile hypertrophy of the breast in affected females. This newly described genetic trait presents an autosomal dominant inheritance pattern, with either reduced penetrance or germ-line mosaicism. Analysis of the pedigree, linkage studies followed by a genome-wide screen and by haplotype analysis defined the locus for the phenotype within a 12 cM (4.3 Mb) interval on chromosome 22q12.3-13.1. This chromosomal region has not been implicated before in genetic disorders of the mammary tissue or limbs. These data suggest a possibly novel signaling pathway affecting the organogenesis of limbs and mammary glands in humans.

SUBMITTER: Genzer-Nir M

PROVIDER: S-EPMC2987341 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Mammary-digital-nail (MDN) syndrome: a novel phenotype maps to human chromosome 22q12.3-13.1.

Genzer-Nir Mira M Khayat Morad M Kogan Leonid L Cohen Hector I HI Hershkowitz Miriam M Geiger Dan D Falik-Zaccai Tzipora C TC

European journal of human genetics : EJHG 20100210 6

Mammary-digital-nail syndrome is a novel phenotypic association consisting of anonychia onychodystrophy with hypoplasia or absence of distal phalanges in males and females, accompanied by juvenile hypertrophy of the breast in affected females. This newly described genetic trait presents an autosomal dominant inheritance pattern, with either reduced penetrance or germ-line mosaicism. Analysis of the pedigree, linkage studies followed by a genome-wide screen and by haplotype analysis defined the l ...[more]

PMID: 20145678

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Project description:Turner syndrome (TS) is associated with a neurocognitive phenotype that includes selective nonverbal deficits, e.g., impaired visual-spatial abilities. We previously reported evidence that this phenotype results from haploinsufficiency of one or more genes on distal Xp. This inference was based on genotype/phenotype comparisons of individual girls and women with partial Xp deletions, with the neurocognitive phenotype considered a dichotomous trait. We sought to confirm our findings in a large cohort (n = 47) of adult women with partial deletions of Xp or Xq, enriched for subjects with distal Xp deletions.Subjects were recruited from North American genetics and endocrinology clinics. Phenotype assessment included measures of stature, ovarian function, and detailed neurocognitive testing. The neurocognitive phenotype was measured as a quantitative trait, the Turner Syndrome Cognitive Summary (TSCS) score, derived from discriminant function analysis. Genetic analysis included karyotyping, X inactivation studies, fluorescent in situ hybridization, microsatellite marker genotyping, and array comparative genomic hybridization.We report statistical evidence that deletion of Xp22.3, an interval containing 31 annotated genes, is sufficient to cause the neurocognitive phenotype described by the TSCS score. Two other cardinal TS features, ovarian failure and short stature, as well as X chromosome inactivation pattern and subject's age, were unrelated to the TSCS score.Detailed mapping suggests that haploinsufficiency of one or more genes in Xp22.3, the distal 8.3 megabases (Mb) of the X chromosome, is responsible for a TS neurocognitive phenotype. This interval includes the 2.6 Mb Xp-Yp pseudoautosomal region (PAR1). Haploinsufficiency of the short stature gene SHOX in PAR1 probably does not cause this TS neurocognitive phenotype. Two genes proximal to PAR1 within the 8.3 Mb critical region, STS and NLGN4X, are attractive candidates for this neurocognitive phenotype.

Dataset Information

Mammary-digital-nail (MDN) syndrome: a novel phenotype maps to human chromosome 22q12.3-13.1.

Publications

Mammary-digital-nail (MDN) syndrome: a novel phenotype maps to human chromosome 22q12.3-13.1.

Similar Datasets

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