ArticleHuman genetics2023
Hemizygosity can reveal variant pathogenicity on the X-chromosome.
Article in Human genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- X-linked competition - implications for human development and disease.Nature reviews. Genetics · 2025Review
- Evolutionary divergence between homologous X-Y chromosome genes shapes sex-biased biology.Nature ecology & evolution · 2025Article
- Characterizing the pathogenicity of genetic variants: the consequences of context.NPJ genomic medicine · 2024Article
- Rare X-linked variants carry predominantly male risk in autism, Tourette syndrome, and ADHD.Nature communications · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Pathogenic variants on the X-chromosome can have more severe consequences for hemizygous males, while heterozygote females can avoid severe consequences due to diploidy and the capacity for nonrandom expression. Thus, when an allele is more common in females this could indicate that it increases the probability of early death in the male hemizygous state, which can be considered a measure of pathogenicity. Importantly, large-scale genomic data now makes it possible to compare allele proportions between the sexes. To discover pathogenic variants on the X-chromosome, we analyzed exome data from 125,748 ancestrally diverse participants in the Genome Aggregation Database (gnomAD). After filtering out duplicates and extremely rare variants, 44,606 of the original 348,221 remained for analysis. We divided the proportion of variant alleles in females by the proportion in males for all variant sites, and then placed each variant into one of three a priori categories: (1) Reference (Primarily synonymous and intronic), (2) Unlikely-to-be-tolerated (Primarily missense), and (3) Least-likely-to-be-tolerated (Primarily frameshift). To assess the impact of ploidy, we compared the distribution of these ratios between pseudoautosomal and non-pseudoautosomal regions. In the non-pseudoautosomal regions, mean female-to-male ratios were lowest among Reference (2.40), greater for Unlikely-to-be-tolerated (2.77) and highest for Least-likely-to-be-tolerated (3.28) variants. Corresponding ratios were lower in the pseudoautosomal regions (1.52, 1.57, and 1.68, respectively), with the most extreme ratio being just below 11. Because pathogenic effects in the pseudoautosomal regions should not drive ratio increases, this maximum ratio provides an upper bound for baseline noise. In the non-pseudoautosomal regions, 319 variants had a ratio over 11. In sum, we identified a measure with a dataset specific threshold for identifying pathogenicity in non-pseudoautosomal X-chromosome variants: the female-to-male allele proportion ratio.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.