{"title":"Composition-Aware Analysis of Public Testis Transcriptomes Identifies Reproducible Tissue-State Signatures in Nonobstructive Azoospermia.","authors":"Zhibang Zhang","doi":"10.1177/15578100261495843","DOIUrl":null,"url":null,"abstract":"<p><p>Whole-testis transcriptomes can conflate loss of germ cells with transcriptional changes in retained somatic compartments. We used public human testis datasets to determine whether a composition-aware transcriptional pattern is reproducible in nonobstructive azoospermia (NOA). Donor-level single-cell analysis showed marked depletion of recovered spermatocyte and spermatid states in NOA. We held a germline signature and a GSE149512-derived stromal/macrophage-associated signature fixed during evaluation in two independent obstructive azoospermia (OA) comparator cohorts. In GSE145467 (10 OA and 10 NOA), NOA showed lower germline scores and higher tissue-state scores (Hedges' <i>g</i> = 1.70 for the tissue-state score, 95% confidence interval [CI] 0.92-3.77; exact permutation <i>p</i> = 0.00108). The same direction was observed in GSE9210 (11 OA and 47 NOA; <i>g</i> = 3.69, 95% CI: 2.28-7.26; 100,000-draw permutation <i>p</i> = 0.000010). The original mixed-control bulk cohort was retained only as a within-cohort sensitivity analysis because its within-cohort remodeling axis was strongly correlated with the NOA label (<i>r</i> = 0.899; variance inflation factor = 5.19). Small spermatocyte-focused data provided exploratory, rather than confirmatory, cell-state observations. These results support a reproducible bulk tissue-state pattern in NOA, but do not establish absolute cell-number changes, cell-intrinsic mechanisms, microdissection testicular sperm extraction prediction, or clinical utility.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":" ","pages":"15578100261495843"},"PeriodicalIF":2.0000,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Omics A Journal of Integrative Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1177/15578100261495843","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Whole-testis transcriptomes can conflate loss of germ cells with transcriptional changes in retained somatic compartments. We used public human testis datasets to determine whether a composition-aware transcriptional pattern is reproducible in nonobstructive azoospermia (NOA). Donor-level single-cell analysis showed marked depletion of recovered spermatocyte and spermatid states in NOA. We held a germline signature and a GSE149512-derived stromal/macrophage-associated signature fixed during evaluation in two independent obstructive azoospermia (OA) comparator cohorts. In GSE145467 (10 OA and 10 NOA), NOA showed lower germline scores and higher tissue-state scores (Hedges' g = 1.70 for the tissue-state score, 95% confidence interval [CI] 0.92-3.77; exact permutation p = 0.00108). The same direction was observed in GSE9210 (11 OA and 47 NOA; g = 3.69, 95% CI: 2.28-7.26; 100,000-draw permutation p = 0.000010). The original mixed-control bulk cohort was retained only as a within-cohort sensitivity analysis because its within-cohort remodeling axis was strongly correlated with the NOA label (r = 0.899; variance inflation factor = 5.19). Small spermatocyte-focused data provided exploratory, rather than confirmatory, cell-state observations. These results support a reproducible bulk tissue-state pattern in NOA, but do not establish absolute cell-number changes, cell-intrinsic mechanisms, microdissection testicular sperm extraction prediction, or clinical utility.
期刊介绍:
OMICS: A Journal of Integrative Biology is the only peer-reviewed journal covering all trans-disciplinary OMICs-related areas, including data standards and sharing; applications for personalized medicine and public health practice; and social, legal, and ethics analysis. The Journal integrates global high-throughput and systems approaches to 21st century science from “cell to society” – seen from a post-genomics perspective.