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Rongsheng Zhao

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Open access Aug 2026

Combined Letrozole and Growth Hormone Therapy in Late-Pubertal Males with Advanced Bone Age and Open Knee Physes

Highlights What are the main findings? In this single-arm retrospective study, combined letrozole and growth hormone therapy was associated with a mean gain of 6.58 ± 3.46 cm in final adult height relative to baseline predicted adult height in late-pubertal males with BA 15 –< 18 years and open knee physes (p < 0.001). The observed height gain diminished with advancing baseline bone age; the largest gain (10.04 ± 4.66 cm) was seen in the BA 15 –< 16 subgroup, where final height exceeded mid-parental height. What are the implications of the main findings? Knee epiphyseal patency may serve as an indicator of residual growth potential in adolescents with advanced wrist bone age, potentially broadening the therapeutic window for aromatase inhibitor plus GH therapy beyond conventional age thresholds. These preliminary findings suggest that baseline skeletal maturity, particularly knee physeal status, should be considered when individualizing treatment decisions; however, prospective controlled studies are needed to confirm these observations. Abstract Background/Objectives: The therapeutic window for growth hormone (GH) therapy in late-pubertal males with advanced bone age (BA ≥ 15 years) is generally considered closed. Yet, open knee physes may indicate residual growth potential. This single-arm retrospective study evaluated the efficacy and safety of letrozole combined with GH in Chinese males with short stature, advanced BA (15 –< 18 years), and open knee physes. Methods: We included 139 male adolescents stratified by baseline BA: 15 ≤ BA < 16 (n = 24), 16 ≤ BA < 17 (n = 31), and 17 ≤ BA < 18 (n = 84). All received subcutaneous GH (0.05–0.07 mg/kg/day) and oral letrozole (2.5 mg/day). The primary outcome was the change in final adult height (FAH) from baseline predicted adult height (PAH). Longitudinal changes in height velocity and height SDS-BA were also assessed. Results: Among 75 patients who reached FAH, combination therapy was associated with a mean gain of 6.58 ± 3.46 cm over baseline PAH (p < 0.001). The gain was inversely correlated with baseline BA; the largest gain occurred in the 15 ≤ BA < 16 subgroup (10.04 ± 4.66 cm), significantly exceeding gains in the 16 ≤ BA < 17 (6.30 ± 3.01 cm) and 17 ≤ BA < 18 (5.70 ± 2.52 cm) subgroups (p < 0.001). In the youngest subgroup, FAH exceeded mid-parental height. The safety profile was acceptable; acne was the most common adverse event (46.76%), and no severe metabolic or endocrine disorders were observed. Conclusions: Letrozole plus GH therapy may be associated with improved FAH in late-pubertal males with advanced BA and open knee physes, with gains varying by baseline skeletal maturity and being numerically greatest in those with BA 15 –< 16 years. Knee epiphyseal status may be a useful consideration when individualizing therapy in this population.

Hui Zhang, Pengxiang Zhou, Yunpu Cui et al. · 0 citations
Review Open access Aug 2026

Multi‐omics–driven precision medicine

Abstract Precision medicine is increasingly constrained not by a lack of molecular data but by the absence of frameworks that can translate multidimensional biological information into actionable clinical decisions. Multi‐omics‐driven precision medicine (MODPM) addresses this lack by integrating genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome, and clinical context into a multiscale framework that links molecular mechanisms, tissue organization, and patient trajectories. In this review, we propose a conceptual framework for MODPM and examine how advances in multi‐omics technologies, artificial intelligence (AI), and foundation models are reshaping disease modeling, drug development, and precision intervention. We summarize the biological contributions of major omics layers and discuss how AI supports cross‐modal representation learning, contextual modeling, and perturbation‐aware prediction. We highlight drug development as a key translational application of MODPM and further discuss its clinical relevance across three major disease contexts: cancer, autoimmune diseases, and metabolic disorders, including cardiometabolic and renal–metabolic diseases. These examples illustrate how MODPM can support target discovery, disease endotyping, treatment response prediction, and clinical monitoring by analyzing shared mechanisms such as immune dysregulation, metabolic remodeling, chronic inflammation, tissue microenvironmental changes, and gene–environment interactions. Across these settings, MODPM enables finer molecular stratification, the identification of pathway‐dominant disease states, improved response prediction, and dynamic treatment monitoring. We also discuss key barriers to implementation, including data heterogeneity, limited cohort diversity, polygenic complexity, workflow constraints, cost, and ethical issues related to privacy, consent, and data ownership. Overall, the value of MODPM lies not in stacking additional data layers but in building a multiscale, continuously learnable framework to link biological heterogeneity to clinically interpretable and actionable decisions.

Huibo Li, Zhe Zhao, Yi-Fan Zhang et al. · 0 citations

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