bioRxiv Science⌕ Search

bioRxiv · 10.1101/177659

Phenotypes associated with female X chromosome aneuploidy in UK Biobank: an unselected, adult, population-based cohort

Abstract

Women with X chromosome aneuploidy such as 45,X (Turner syndrome) or 47,XXX (Triple X syndrome) present with characteristics including differences in stature, increased cardiovascular disease risk and primary ovarian insufficiency. Many women with X chromosome aneuploidy undergo lifetime clinical monitoring for possible complications. However, ascertainment of cases in the clinic may mean that the phenotypic penetrance is overestimated. Studies of prenatally ascertained X chromosome aneuploidy cases have limited follow-up data and so the long-term consequences into adulthood are often not reported. We aimed to characterise the prevalence and phenotypic consequences of X chromosome aneuploidy in a large population of women over 40 years of age. We detected 30 women with 45,X, 186 with mosaic 45,X/46,XX and 110 with 47,XXX among 244,848 UK Biobank women, using SNP array data. The prevalence of non-mosaic 45,X (1/8,162) and 47,XXX (1/2,226) was lower than expected, but was higher for mosaic 45,X/46,XX (1/1,316). The characteristics of women with 45,X were consistent with the characteristics of a clinically recognised Turner syndrome phenotype, including a 17.2cm shorter stature (SD = 5.72cm; P = 1.5 x 10-53) and 16/30 did not report an age at menarche. The phenotype of women with 47,XXX included taller stature (5.3cm; SD = 5.52cm; P = 5.8 x 10-20), earlier menopause age (5.12 years; SD = 5.1 years; P = 1.2 x 10-14) and a lower fluid intelligence score (24%; SD = 29.7%; P = 3.7 x 10-8). In contrast, the characteristics of women with mosaic 45,X/46,XX were much less pronounced than expected. Women with mosaic 45,X/46,XX were less short, had a normal reproductive lifespan and birth rate, and no reported cardiovascular complications. In conclusion, the availability of data from 244,848 women allowed us to assess the phenotypic penetrance of traits associated with X chromosome aneuploidy in an adult population setting. Our results suggest that the clinical management of women with 45,X/46,XX mosaicism should be minimal, particularly those identified incidentally.\n\nFundingNone

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tuke, M. A., Ruth, K. S., Wood, A. R., Beaumont, R. N., Tyrrell, J., Jones, S. E., Yaghootkar, H., Turner, C. L. S., Donohoe, M. E., Brooke, A. M., Collinson, M. N., Freathy, R. M., Weedon, M. N., Frayling, T. M., Murray, A.. 2017-08-18. Phenotypes associated with female X chromosome aneuploidy in UK Biobank: an unselected, adult, population-based cohort. https://doi.org/10.1101/177659

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Cellular context shapes the transcriptomic impact of somatic variants

Somatic SNVs are commonly prioritized by recurrence or sequence annotation, leaving the molecular consequences of private variants unresolved. We developed PrismSNV and Ligo-Seq, a single-cell full-length transcriptome sequencing platform, to quantify transcriptomic displacement associated with within-cell SNV-state toggling. Across 26 samples from three cancer types, more than 60% of candidate SNVs showed significant cell-type-specific displacement with over 30% variation in magnitude. Sequence-based deleteriousness was poorly aligned with cellular displacement, and fewer than 3% of top-displacement SNVs across six tumor types were catalogued in ClinVar. Displacement was strongest in transcriptionally plastic, less differentiated states. Analysis of 655,349 CD4+ T-cell transcriptomes further showed that SNV-gene associations changed in magnitude and sometimes direction during activation. Lack of recurrence or clinical annotation does not imply transcriptomic inertness; variant impact is shaped by cellular context rather than sequence alone, establishing the variant-cell pair as a critical unit for interpreting somatic variation.

genetics↗

Genetic and Epigenetic Landscape of Self-Identified Hispanics/Latino in All Of Us

Human genetic studies still underrepresent many populations, limiting discovery and interpretation of medically relevant variation. Extensive admixture in self-identified Hispanic/Latino populations increases the need for representative reference data and ancestry-aware interpretation of medically relevant variation. We used long-read sequencing to analyze genetic variation, ancestry, and DNA methylation in 1,490 self-identified Hispanic/Latino participants from the All of Us Research Program. We identified 10 million novel variants and more than 100 candidate phenotype associations, with fine-mapping prioritizing structural variants over nearby single-nucleotide variants in more than half. We linked 3,329 tandem repeats to DNA methylation, resolved widespread allele-specific methylation, and identified ancestry-linked regulation across paralogous genes. These results reveal previously inaccessible genetic and regulatory variation and show the value of long-read sequencing for diverse populations.

genetics↗

The genetic architecture of human DNA methylome variation

Population DNA methylome analyses remain largely confined to reference-defined genomic space despite extensive human genetic diversity. A central challenge is therefore to define comparable methylation phenotypes across diverse genomes and map the genetic architecture of methylome variation. Here, using 460 haplotypes from the Human Pangenome Reference Consortium Release 2, we develop two complementary pangenome-based frameworks: one compares methylation within homologous regions while retaining haplotype-specific structural configuration and CpG content; the other represents CpG island (CGI) variation at homologous loci as sequence-resolved alleles. We identified 47,039 CGI alleles, including 8,040 absent from CHM13; 62% were attributable to structural variants and 31% to small variants. Through local genealogies, we reconstructed CGI gain, loss and turnover, revealing how present-day methylation differences align with CGI evolutionary trajectories. We found that genome-wide, methylation variability was buffered against genetic diversity across more than 90% of the genome, with exceptions at extreme nucleotide diversity and locally around structural variants. Our methylation framework enabled population-scale allele-aware methylation quantitative trait locus (mQTL) mapping into non-reference and structurally complex sequence, where mQTL-associated intervals were enriched. mQTLs linked methylation to transcriptomic phenotypes, population differentiation and complex traits, supporting 8% of population differentially methylated regions and colocalizing with more than half of genome-wide association study loci. Together, our study redefines human methylome analysis and our findings reveal a genome-wide architecture of genetic-epigenetic coupling, reshaping how methylation variation is interpreted across human development and disease.

genetics↗