ArticleMedical science monitor : international medical journal of experimental and clinical research2019
Targeted Next-Generation Sequencing Identifies Novel Sequence Variations of Genes Associated with Nonobstructive Azoospermia in the Han Population of Northeast China.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 15 citations in OpenAlex.
- A homozygous PIWIL1 frameshift variant triggers azoospermia and reveals a strong selective constraint on germline genome integrity.Journal of assisted reproduction and genetics · 2026Article
- Advances in PIWI-piRNA function in female reproduction in mammals.Acta biochimica et biophysica Sinica · 2024Review
- Article
- Whole-genome sequencing identifies new candidate genes for nonobstructive azoospermia.Andrology · 2022Article
- The novel BRDT inhibitor NHWD870 shows potential as a male contraceptive in mice.Acta biochimica et biophysica Sinica · 2022Article
- A homozygous PIWIL2 frameshift variant affects the formation and maintenance of human-induced pluripotent stem cell-derived spermatogonial stem cells and causes Sertoli cell-only syndrome.Stem cell research & therapy · 2022Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND This study aimed to screen common and low-frequency variants of nonobstructive azoospermia (NOA)-associated genes, and to construct a database for NOA-associated single nucleotide variants (SNVs). MATERIAL AND METHODS Next-generation sequencing of 466 NOA-associated genes was performed in 34 patients with NOA (mean age, 29.06±4.49 years) and 40 sperm donors (mean age, 25.08±5.75 years) from the Han population of northeast China. The SNV database was constructed by summarizing NOA non-negatively-associated SNVs showing statistical differences between NOA cases and controls, and then selecting low-frequency variants using Baylor's pipeline, to identify statistically valid SNVs. RESULTS There were 65 SNVs identified that were significantly different between both groups (p<0.05). Five genetic variants showed positive correlations with NOA: MTRR c.537T>C (rs161870), odds ratios (OR), 3.686, 95% confidence interval (CI), 1.228-11.066; MTRR, c.1049A>G (rs162036), OR, 3.686, 95% CI, 1.228-11.066; PIWIL1, c.1580G>A (rs1106042), OR, 4.737, 95% CI, 1.314-17.072; TAF4B, c.1815T>C (rs1677016), OR, 3.599, 95% CI, 1.255-10.327; and SOX10 c.927T>C (rs139884), OR, 3.192, 95% CI, 1.220-8.353. Also, 52 NOA non-negatively associated SNVs and 39 SNVs were identified by Baylor's pipeline and selected for the SNV database. CONCLUSIONS Five genetic variants were shown to have positive correlations with NOA. The SNV database constructed contained NOA non-negatively associated SNVs and low-frequency variants. This study showed that this approach was an effective strategy to identify risk alleles of NOA.
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