1.From Gene Expression to Transcriptome-wide Association Study: Development and Comparison of Methodology
Kun FANG ; Guozhuang LI ; Linting WANG ; Qing LI ; Kexin XU ; Lina ZHAO ; Zhihong WU ; Jianguo ZHANG ; Nan WU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):223-229
Over the past two decades, genome-wide association study(GWAS) has identified numerous genetic variants and loci associated with heritable diseases. With the gradual maturation and saturation of GWAS methodologies, transcriptome-wide association study(TWAS) offers a novel perspective by linkinggenetic phenotypes to gene expression levels. By integrating TWAS with other multi-omics analyses, researchers can gain a deeper understanding of heritable diseases. This article provides an overview of recent groundbreaking and representative TWAS methods and tools, analyzes their strengths and limitations, and discusses future trends in TWAS development.
2.Analysis of anti-TP detection and co-infection among blood donors in Hefei area
Feifei JIANG ; Suping LI ; Qing HE ; Ye FANG ; Mingrui LI ; Panpan WANG
Chinese Journal of Blood Transfusion 2026;39(5):629-635
Objective: To analyze the status of Treponema pallidum (TP) infection among blood donors in Hefei area by evaluating anti-TP reactive donors, and to provide data support for blood screening strategies, evaluation of reagent application, and public health prevention and control strategies. Methods: TPPA confirmation test were performed on 338 anti-TP positive samples of voluntary blood donors at Anhui Blood Center from February to April 2022, July to October 2022, February to June 2023. RPR tests were conducted on samples positive for TPPA. The test results, co-reactivity of TP with HBV, HCV, and HIV, and demographic characteristics of the donors were statistically analyzed. Results: The unqualified rate of anti-TP among blood donors in Hefei area was 0.30% (405/133 587), and the positive rate for TPPA was 67.46% (228/338). Among the TPPA-positive donors, 31.67% were RPR-positive. The co-positive rates of HBV, HCV and HIV in anti-TP reactive blood donors were 0.74% (3/405), 0.49% (2/405), and 1.73% (7/405), respectively, with HIV copositivity being the most common. Most co-positive donors were males aged 31-50 years with a high school education or lower, and all were first-time whole blood donors. Conclusion: The anti-TP unqualified rate among blood donors in Hefei area is at a low-to-mederate level. HIV is the most common co-infection with TP among anti-TP positive donors. The majority of co-infected donors are middle-aged men donating whole blood for the first time.
3.Mechanism of cofilin in regulating prostate cancer progression and potential therapeutic strategies
Fang-zhi FU ; Li-tong WU ; En-min FENG ; Xiang ZHAO ; Neng WANG ; Biao WANG ; Qing ZHOU
Chinese Pharmacological Bulletin 2025;41(7):1206-1211
The molecular mechanisms underlying the develop-ment and metastasis of prostate cancer remain elusive.This comprehensive review delves into the intricate role of cofilin,an actin-binding protein,in the pathogenesis and progression of prostate cancer.Cofilin is a significant protein in cytoskeletal dynamics,and any dysregulation may result in the morphological changes in normal cells and the invasion and metastasis of tumor cells.Research has revealed that the activity of cofilin is regula-ted by various mechanisms,including phosphorylation/dephos-phorylation and interactions with other molecules.Moreover,this review discusses promising therapeutic interventions,such as co-filin inhibitors and gene therapy,which have demonstrated effica-cy in preclinical models.The challenge of clinically preventing the transition to castration-resistant prostate cancer and tumor metastasis is widely recognized,necessitating the development of precise drug treatments and biomarker identification.As a key regulatory protein,cofilin provides a more comprehensive refer-ence for the prevention and treatment of prostate diseases.
4.Medication rules and mechanism of Xin'an physicians in the treatment of diabetes mellitus based on data mining and network pharmacology
Jinru ZHU ; Qing WU ; Kexin HU ; Mengfan WANG ; Zhaohui FANG
Chinese Journal of Pharmacoepidemiology 2025;34(3):260-272
Objective To explore the medication rules and mechanism of Xin'an physicians in the treatment of diabetes mellitus.Methods The prescriptions for the treatment of diabetes mellitus in Xin'an medical writings were collected.The core drug prescriptions were obtained by using IBM SPSS Modeler 18.0 for dispensing association rules as well as complex network analysis,and the cluster analysis of high-frequency traditional Chinese medicines was carried out by using IBM SPSS Statistics 25.0.The active ingredients and targets of the core drugs were extracted from the BATMAN-TCM database.The GeneCards database was used to search for diabetes gene targets,and after obtaining the intersecting targets,the STRING online platform was imported to construct the protein interactions network,and screened the core genes by using the Cytoscape 3.9.1 software,and imported into the DAVID database for GO function and KEGG pathway enrichment analysis.Results A total of 135 valid prescriptions were included,involving 184 flavors of traditional Chinese medicines,with cold and mild properties.Sweet,bitter and pungent flavors,and the main attributes of lung,spleen,kidney,stomach and heart meridians.The association rules mined 14 pairs of commonly used medicine pairs.Cluster analysis clustered the top 20 traditional Chinese medicines into five cluster groups.Complex network visualization analysis formed a core prescription consisting of honey-fried licorice root,ginseng,rhizoma anemarrhenae,ophiopogon japonicus,poria cocos.The core prescription drugs were screened for 164 effective active ingredients,1,498 action targets,1,995 diabetes gene targets,404 intersecting targets,10 core targets were extracted,and a total of 1,363 items covering BP were obtained from GO functional enrichment analysis,129 items involving CC,264 items containing MF,and 206 items of KEGG signaling pathway.Conclusion The prescriptions and medicines used by Xin'an doctors in the treatment of diabetes mellitus reflect the academic idea of"treating both the symptoms and the root cause"as well as the therapeutic thought of"using cold and warmth,supplementing with sweetness and warmth,opening up and lowering with bitterness,cultivating the earth and generating gold,and consolidating the root and cultivating the elements",which provide references for the treatment of diabetes mellitus in today's clinics.
5.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
6.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
7.Medication rules and mechanism of Xin'an physicians in the treatment of diabetes mellitus based on data mining and network pharmacology
Jinru ZHU ; Qing WU ; Kexin HU ; Mengfan WANG ; Zhaohui FANG
Chinese Journal of Pharmacoepidemiology 2025;34(3):260-272
Objective To explore the medication rules and mechanism of Xin'an physicians in the treatment of diabetes mellitus.Methods The prescriptions for the treatment of diabetes mellitus in Xin'an medical writings were collected.The core drug prescriptions were obtained by using IBM SPSS Modeler 18.0 for dispensing association rules as well as complex network analysis,and the cluster analysis of high-frequency traditional Chinese medicines was carried out by using IBM SPSS Statistics 25.0.The active ingredients and targets of the core drugs were extracted from the BATMAN-TCM database.The GeneCards database was used to search for diabetes gene targets,and after obtaining the intersecting targets,the STRING online platform was imported to construct the protein interactions network,and screened the core genes by using the Cytoscape 3.9.1 software,and imported into the DAVID database for GO function and KEGG pathway enrichment analysis.Results A total of 135 valid prescriptions were included,involving 184 flavors of traditional Chinese medicines,with cold and mild properties.Sweet,bitter and pungent flavors,and the main attributes of lung,spleen,kidney,stomach and heart meridians.The association rules mined 14 pairs of commonly used medicine pairs.Cluster analysis clustered the top 20 traditional Chinese medicines into five cluster groups.Complex network visualization analysis formed a core prescription consisting of honey-fried licorice root,ginseng,rhizoma anemarrhenae,ophiopogon japonicus,poria cocos.The core prescription drugs were screened for 164 effective active ingredients,1,498 action targets,1,995 diabetes gene targets,404 intersecting targets,10 core targets were extracted,and a total of 1,363 items covering BP were obtained from GO functional enrichment analysis,129 items involving CC,264 items containing MF,and 206 items of KEGG signaling pathway.Conclusion The prescriptions and medicines used by Xin'an doctors in the treatment of diabetes mellitus reflect the academic idea of"treating both the symptoms and the root cause"as well as the therapeutic thought of"using cold and warmth,supplementing with sweetness and warmth,opening up and lowering with bitterness,cultivating the earth and generating gold,and consolidating the root and cultivating the elements",which provide references for the treatment of diabetes mellitus in today's clinics.
8.Mechanism of cofilin in regulating prostate cancer progression and potential therapeutic strategies
Fang-zhi FU ; Li-tong WU ; En-min FENG ; Xiang ZHAO ; Neng WANG ; Biao WANG ; Qing ZHOU
Chinese Pharmacological Bulletin 2025;41(7):1206-1211
The molecular mechanisms underlying the develop-ment and metastasis of prostate cancer remain elusive.This comprehensive review delves into the intricate role of cofilin,an actin-binding protein,in the pathogenesis and progression of prostate cancer.Cofilin is a significant protein in cytoskeletal dynamics,and any dysregulation may result in the morphological changes in normal cells and the invasion and metastasis of tumor cells.Research has revealed that the activity of cofilin is regula-ted by various mechanisms,including phosphorylation/dephos-phorylation and interactions with other molecules.Moreover,this review discusses promising therapeutic interventions,such as co-filin inhibitors and gene therapy,which have demonstrated effica-cy in preclinical models.The challenge of clinically preventing the transition to castration-resistant prostate cancer and tumor metastasis is widely recognized,necessitating the development of precise drug treatments and biomarker identification.As a key regulatory protein,cofilin provides a more comprehensive refer-ence for the prevention and treatment of prostate diseases.
9.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
10.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

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