Twelve Loci Associated With Bone Density in Middle-aged and Elderly Chinese: The Shanghai Changfeng Study

The 100 top-cited articles in menopausal syndrome: a bibliometric analysis

BACKGROUND

Significant scientific research has been conducted concerning menopausal syndrome(MPS), yet few bibliometric analyses have been performed. Our aim was to recognise the 100 most highly cited published articles on MPS and to analytically evaluate their key features.

METHODS

To identify the 100 most frequently cited articles, a search was conducted on Web of Science using the term 'menopausal syndrome'. Articles that matched the predetermined criteria were scrutinised to obtain the following data: citation ranking, year of publication, publishing journal, journal impact factor, country of origin, academic institution, authors, study type, and keywords.

RESULTS

The publication period is from January 1, 2000, to August 31, 2022. The maximum number of citations was 406 and in 2012. The median citations per year was 39.70. Most of the articles focused on treatment and complications. These articles were published in 36 different journals, with the Journal of MENOPAUSE having published the greatest number (14%). Forty-eight articles (48%) were from the United States, with the University of Pittsburgh being the leading institute (9%). Joann E. Manson was the most frequent first author (n = 6). Observational studies were the most frequently conducted research type (n = 53), followed by experimental studies (n = 33). Keyword analysis identified classic research topics, including genitourinary syndrome of menopause, bone mineral density (BMD), and anti-mullerian hormone (AMH) loci.

CONCLUSION

Using bibliometrics, we conducted an analysis to identify the inadequacies, traditional focal points, and potential prospects in the study of MPS across current scientific areas. Treatment and complications are at the core of MPS research, whereas prediction and biomarkers have less literature of high quality. There is a necessity for innovative analytical metrics to measure the real effect of these papers with a high level of citation on clinical application.

Genome-Wide Association Study for Somatic Skeletal Traits in Duroc × (Landrace × Yorkshire) Pigs

The pig bone weight trait holds significant economic importance in southern China. To expedite the selection of the pig bone weight trait in pig breeding, we conducted molecular genetic research on these specific traits. These traits encompass the bone weight of the scapula (SW), front leg bone weight (including humerus and ulna) (FLBW), hind leg bone weight (including femur and tibia) (HLBW), and spine bone weight (SBW). Up until now, the genetic structure related to these traits has not been thoroughly explored, primarily due to challenges associated with obtaining the phenotype data. In this study, we utilized genome-wide association studies (GWAS) to discern single nucleotide polymorphisms (SNPs) and genes associated with four bone weight traits within a population comprising 571 Duroc × (Landrace × Yorkshire) hybrid pigs (DLY). In the analyses, we employed a mixed linear model, and for the correction of multiple tests, both the false discovery rate and Bonferroni methods were utilized. Following functional annotation, candidate genes were identified based on their proximity to the candidate sites and their association with the bone weight traits. This study represents the inaugural application of GWAS for the identification of SNPs associated with individual bone weight in DLY pigs. Our analysis unveiled 26 SNPs and identified 12 promising candidate genes (OPRM1, SLC44A5, WASHC4, NOPCHAP1, RHOT1, GLP1R, TGFB3, PLCB1, TLR4, KCNJ2, ABCA6, and ABCA9) associated with the four bone weight traits. Furthermore, our findings on the genetic mechanisms influencing pig bone weight offer valuable insights as a reference for the genetic enhancement of pig bone traits.

Identification of ROCK1 as a novel biomarker for postmenopausal osteoporosis and pan-cancer analysis

BACKGROUND

Postmenopausal osteoporosis (PMOP) is a prevalent bone disorder with significant global impact. The elevated risk of osteoporotic fracture in elderly women poses a substantial burden on individuals and society. Unfortunately, the current lack of dependable diagnostic markers and precise therapeutic targets for PMOP remains a major challenge.

METHODS

PMOP-related datasets GSE7429, GSE56814, GSE56815, and GSE147287, were downloaded from the GEO database. The DEGs were identified by "limma" packages. WGCNA and Machine Learning were used to choose key module genes highly related to PMOP. GSEA, DO, GO, and KEGG enrichment analysis was performed on all DEGs and the selected key hub genes. The PPI network was constructed through the GeneMANIA database. ROC curves and AUC values validated the diagnostic values of the hub genes in both training and validation datasets. xCell immune infiltration and single-cell analysis identified the hub genes' function on immune reaction in PMOP. Pan-cancer analysis revealed the role of the hub genes in cancers.

RESULTS

A total of 1278 DEGs were identified between PMOP patients and the healthy controls. The purple module and cyan module were selected as the key modules and 112 common genes were selected after combining the DEGs and module genes. Five Machine Learning algorithms screened three hub genes (KCNJ2, HIPK1, and ROCK1), and a PPI network was constructed for the hub genes. ROC curves validate the diagnostic values of ROCK1 in both the training (AUC = 0.73) and validation datasets of PMOP (AUC = 0.81). GSEA was performed for the low-ROCK1 patients, and the top enriched field included protein binding and immune reaction. DCs and NKT cells were highly expressed in PMOP. Pan-cancer analysis showed a correlation between low ROCK1 expression and SKCM as well as renal tumors (KIRP, KICH, and KIRC).

CONCLUSIONS

ROCK1 was significantly associated with the pathogenesis and immune infiltration of PMOP, and influenced cancer development, progression, and prognosis, which provided a potential therapy target for PMOP and tumors. However, further laboratory and clinical evidence is required before the clinical application of ROCK1 as a therapeutic target.