留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

The Taizhou Longitudinal Study: a population-based biobank resource of genetic and biochemical biomarkers for precision medicine in China

Yanfeng Jiang,  Linyao Lu,  Zhenqiu Liu,  Ziyu Yuan,  Huangbo Yuan,  Kelin Xu,  Tiejun Zhang,  Xiang Zhang,  Min Fan,  Yuguo Chen,  Weimin Ye,  Jiucun Wang,  Ming Lu,  Li Jin,  Chen Suo,  Xingdong Chen

downloadPDF
文章导航 > Journal of Genetics and Genomics  > 2026 > 优先出版
Yanfeng Jiang, Linyao Lu, Zhenqiu Liu, Ziyu Yuan, Huangbo Yuan, Kelin Xu, Tiejun Zhang, Xiang Zhang, Min Fan, Yuguo Chen, Weimin Ye, Jiucun Wang, Ming Lu, Li Jin, Chen Suo, Xingdong Chen. The Taizhou Longitudinal Study: a population-based biobank resource of genetic and biochemical biomarkers for precision medicine in China[J]. 遗传学报. doi: 10.1016/j.jgg.2026.02.004
引用本文: Yanfeng Jiang, Linyao Lu, Zhenqiu Liu, Ziyu Yuan, Huangbo Yuan, Kelin Xu, Tiejun Zhang, Xiang Zhang, Min Fan, Yuguo Chen, Weimin Ye, Jiucun Wang, Ming Lu, Li Jin, Chen Suo, Xingdong Chen. The Taizhou Longitudinal Study: a population-based biobank resource of genetic and biochemical biomarkers for precision medicine in China[J]. 遗传学报. doi: 10.1016/j.jgg.2026.02.004
shu
Yanfeng Jiang, Linyao Lu, Zhenqiu Liu, Ziyu Yuan, Huangbo Yuan, Kelin Xu, Tiejun Zhang, Xiang Zhang, Min Fan, Yuguo Chen, Weimin Ye, Jiucun Wang, Ming Lu, Li Jin, Chen Suo, Xingdong Chen. The Taizhou Longitudinal Study: a population-based biobank resource of genetic and biochemical biomarkers for precision medicine in China[J]. Journal of Genetics and Genomics. doi: 10.1016/j.jgg.2026.02.004
Citation: Yanfeng Jiang, Linyao Lu, Zhenqiu Liu, Ziyu Yuan, Huangbo Yuan, Kelin Xu, Tiejun Zhang, Xiang Zhang, Min Fan, Yuguo Chen, Weimin Ye, Jiucun Wang, Ming Lu, Li Jin, Chen Suo, Xingdong Chen. The Taizhou Longitudinal Study: a population-based biobank resource of genetic and biochemical biomarkers for precision medicine in China[J]. Journal of Genetics and Genomics. doi: 10.1016/j.jgg.2026.02.004
shu

The Taizhou Longitudinal Study: a population-based biobank resource of genetic and biochemical biomarkers for precision medicine in China

doi: 10.1016/j.jgg.2026.02.004

  • a. State Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Research and Innovation Center, Shanghai Pudong Hospital, Zhangjiang Fudan International Innovation Center, and National Clinical Research Center for Aging and Medicine, Fudan University, Shanghai 201203, China;

  • b. Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225300, China;

  • c. Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai 200032, China;

  • d. Taizhou Disease Control and Prevention Center, Taizhou, Jiangsu 225300, China;

  • e. Taixing Disease Control and Prevention Center, Taizhou, Jiangsu 225400, China;

  • f. Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan, Shandong 250012, China;

  • g. Department of Epidemiology and Health Statistics, Institute of Population Medicine, Fujian Medical University, Fuzhou, Fujian 350122, China;

  • h. Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, Shandong 250012, China

基金项目: 

D Program of China (2024YFC3405800, 2023YFC3606300), the National Natural Science Foundation of China (82473700), Shanghai Municipal Science and Technology Major Project (2023SHZDZX02).

The authors are grateful to all the participants in the Taizhou Longitudinal Study for their enthusiastic collaboration, the personnel from Fudan University Taizhou Institute of Health Sciences, the staff of Taizhou and Taixing Disease Control and Prevention Center (CDC) for their assistance in data collection. We acknowledge financial supports from the Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0510000, 2025ZD0552008), Science and Technology Innovation 2030 Major Projects (2022ZD0211600), the National Key R&

详细信息
    通讯作者:

    Yanfeng Jiang,E-mail:yanfengjiang@fudan.edu.cn

    Chen Suo,E-mail:suochen@fudan.edu.cn

    Xingdong Chen,E-mail:xingdongchen@fudan.edu.cn

The Taizhou Longitudinal Study: a population-based biobank resource of genetic and biochemical biomarkers for precision medicine in China

  • a. State Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Research and Innovation Center, Shanghai Pudong Hospital, Zhangjiang Fudan International Innovation Center, and National Clinical Research Center for Aging and Medicine, Fudan University, Shanghai 201203, China;

  • b. Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225300, China;

  • c. Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai 200032, China;

  • d. Taizhou Disease Control and Prevention Center, Taizhou, Jiangsu 225300, China;

  • e. Taixing Disease Control and Prevention Center, Taizhou, Jiangsu 225400, China;

  • f. Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan, Shandong 250012, China;

  • g. Department of Epidemiology and Health Statistics, Institute of Population Medicine, Fujian Medical University, Fuzhou, Fujian 350122, China;

  • h. Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, Shandong 250012, China

Funds: 

D Program of China (2024YFC3405800, 2023YFC3606300), the National Natural Science Foundation of China (82473700), Shanghai Municipal Science and Technology Major Project (2023SHZDZX02).

The authors are grateful to all the participants in the Taizhou Longitudinal Study for their enthusiastic collaboration, the personnel from Fudan University Taizhou Institute of Health Sciences, the staff of Taizhou and Taixing Disease Control and Prevention Center (CDC) for their assistance in data collection. We acknowledge financial supports from the Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0510000, 2025ZD0552008), Science and Technology Innovation 2030 Major Projects (2022ZD0211600), the National Key R&

    摘要
  • 摘要: The Taizhou Longitudinal Study (TZL) is a population-based prospective cohort initiated in 2007, recruiting over 201,000 adults aged 20 – 80 from urban and rural areas of Taizhou, Jiangsu Province, China. The cohort is extensively phenotyped through baseline questionnaire-based interviews, physical examinations, biochemical assays, and longitudinal follow-up using health records and repeated assessments. A wide range of biospecimens, including blood, urine, saliva, and feces, have been collected to enable omics-level profiling. Genome-wide genotyping has been performed for approximately 50,000 participants recruited from 2009 to 2014. Here, we present an integrated overview of the existing and planned genetic and phenotypic resources, describe genotyping and quality control procedures, and assess cryptic relatedness and population structure, followed by genome-wide association analyses of 66 physical and biochemical traits. In total, 533 independent loci reach Bonferroni significance after clumping. These analyses identify 55 previously unreported loci, demonstrating the capacity of the TZL to elucidate the genetic architecture of complex traits in East Asian populations. By integrating high-quality phenotypic and genotypic data, the TZL enables a comprehensive investigation of gene-environment interactions in Chinese population. With ongoing expansions and development of a controlled-access data-sharing platform, the TZL is positioned as a valuable resource for precision medicine and public health research.
    Abstract: The Taizhou Longitudinal Study (TZL) is a population-based prospective cohort initiated in 2007, recruiting over 201,000 adults aged 20 – 80 from urban and rural areas of Taizhou, Jiangsu Province, China. The cohort is extensively phenotyped through baseline questionnaire-based interviews, physical examinations, biochemical assays, and longitudinal follow-up using health records and repeated assessments. A wide range of biospecimens, including blood, urine, saliva, and feces, have been collected to enable omics-level profiling. Genome-wide genotyping has been performed for approximately 50,000 participants recruited from 2009 to 2014. Here, we present an integrated overview of the existing and planned genetic and phenotypic resources, describe genotyping and quality control procedures, and assess cryptic relatedness and population structure, followed by genome-wide association analyses of 66 physical and biochemical traits. In total, 533 independent loci reach Bonferroni significance after clumping. These analyses identify 55 previously unreported loci, demonstrating the capacity of the TZL to elucidate the genetic architecture of complex traits in East Asian populations. By integrating high-quality phenotypic and genotypic data, the TZL enables a comprehensive investigation of gene-environment interactions in Chinese population. With ongoing expansions and development of a controlled-access data-sharing platform, the TZL is positioned as a valuable resource for precision medicine and public health research.
    • HTML全文
    • 参考文献(47)
  • All of Us Research Program Investigators, 2019. The “All of Us” Research Program. N. Engl. J. Med. 381, 668-676.
    Aronica, A., Avagliano, L., Caretti, A., Tosi, D., Bulfamante, G.P., Trinchera, M., 2017. Unexpected distribution of CA19.9 and other type 1 chain Lewis antigens in normal and cancer tissues of colon and pancreas: Importance of the detection method and role of glycosyltransferase regulation. Biochim. Biophys. Acta. Gen. Subj. 1861, 3210-3220.
    Arora, K., Sherilraj, P.M., Abutwaibe, K.A., Dhruw, B., Mudavath, S.L., 2024. Exploring glycans as vital biological macromolecules: a comprehensive review of advancements in biomedical frontiers. Int. J. Biol. Macromol. 268, 131511.
    Auton, A., Brooks, L.D., Durbin, R.M., Garrison, E.P., Kang, H.M., Korbel, J.O., Marchini, J.L., McCarthy, S., McVean, G.A., Abecasis, G.R., 2015. A global reference for human genetic variation. Nature 526, 68-74.
    Browning, B.L., Tian, X., Zhou, Y., Browning, S.R., 2021. Fast two-stage phasing of large-scale sequence data. Am. J. Hum. Genet. 108, 1880-1890.
    Browning, B.L., Zhou, Y., Browning, S.R., 2018. A one-penny imputed genome from next-generation reference panels. Am. J. Hum. Genet. 103, 338-348.
    Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L.T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O'Connell, J., et al., 2018. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203-209.
    Byrska-Bishop, M., Evani, U.S., Zhao, X., Basile, A.O., Abel, H.J., Regier, A.A., Corvelo, A., Clarke, W.E., Musunuri, R., Nagulapalli, K., et al., 2022. High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios. Cell 185, 3426-3440.e3419.
    Bulik-Sullivan, B.K., Loh, P.R., Finucane, H.K., Ripke, S., Yang, J., Patterson, N., Daly, M.J., Price, A.L., Neale, B.M., 2015. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291-295.
    Chang, C.C., Chow, C.C., Tellier, L.C., Vattikuti, S., Purcell, S.M., Lee, J.J., 2015. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7.
    Chen, T., Chen, X., Zhang, S., Zhu, J., Tang, B., Wang, A., Dong, L., Zhang, Z., Yu, C., Sun, Y., et al., 2021. The Genome Sequence Archive family: toward explosive data growth and diverse data types. Genomics Proteomics Bioinformatics 19, 578-583.
    Chen, X., Giles, J., Yao, Y., Yip, W., Meng, Q., Berkman, L., Chen, H., Chen, X., Feng, J., Feng, Z., et al., 2022. The path to healthy ageing in China: A Peking University-Lancet Commission. Lancet 400, 1967-2006.
    Chen, Z., Lee, L., Chen, J., Collins, R., Wu, F., Guo, Y., Linksted, P., Peto, R., 2005. Cohort profile: the Kadoorie Study of Chronic Disease in China (KSCDC). Int. J. Epidemiol. 34, 1243-1249.
    CNCB-NGDC Members and Partners, 2024. Database resources of the National Genomics Data Center, China National Center for Bioinformation in 2024. Nucleic Acids Res. 52, D18-d32.
    Engle, D.D., Tiriac, H., Rivera, K.D., Pommier, A., Whalen, S., Oni, T.E., Alagesan, B., Lee, E.J., Yao, M.A., Lucito, M.S., et al., 2019. The glycan CA19-9 promotes pancreatitis and pancreatic cancer in mice. Science 364, 1156-1162.
    GBD 2021 Causes of Death Collaborators, 2024. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 403, 2100-2132.
    German National Cohort (GNC) Consortium, 2014. The German National Cohort: aims, study design and organization. Eur. J. Epidemiol. 29, 371-382.
    He, M., Wu, C., Xu, J., Guo, H., Yang, H., Zhang, X., Sun, J., Yu, D., Zhou, L., Peng, T., et al., 2014. A genome wide association study of genetic loci that influence tumour biomarkers cancer antigen 19-9, carcinoembryonic antigen and α fetoprotein and their associations with cancer risk. Gut 63, 143-151.
    Illumina, 2021. https://www.Illumina.Com/content/dam/illumina/gcs/assembled-assets/marketing-literature/infinium-chinese-genotyping-array-24-v1-0-m-us-00004/infinium-chinese-genotyping-array-24-v1.0-m-us-00004.Pdf. (accessed 2025.1.2).
    Jia, P., Dong, L., Yang, X., Wang, B., Bush, S.J., Wang, T., Lin, J., Wang, S., Zhao, X., Xu, T., et al., 2023. Haplotype-resolved assemblies and variant benchmark of a Chinese Quartet. Genome. Biol. 24, 277.
    Jiang, Y., Cui, M., Tian, W., Zhu, S., Chen, J., Suo, C., Liu, Z., Lu, M., Xu, K., Fan, M., et al., 2021. Lifestyle, multi-omics features, and preclinical dementia among Chinese: The Taizhou Imaging Study. Alzheimers. Dement. 17, 18-28.
    Jin, L., 2021. Welcome to the Phenomics Journal. Phenomics 1, 1-2.
    Kurki, M.I., Karjalainen, J., Palta, P., Sipila, T.P., Kristiansson, K., Donner, K.M., Reeve, M.P., Laivuori, H., Aavikko, M., Kaunisto, M.A., et al., 2023. Finngen provides genetic insights from a well-phenotyped isolated population. Nature 613, 508-518.
    Liu, Z., Jiang, Y., Suo, C., Yuan, H., Yuan, Z., Zhang, T., Jin, L., Chen, X., 2025. Cohort profile: Taizhou Study of Liver Diseases (T-SOLID). Int. J. Epidemiol. 54, dyaf030.
    Manichaikul, A., Mychaleckyj, J.C., Rich, S.S., Daly, K., Sale, M., Chen, W.M., 2010. Robust relationship inference in genome-wide association studies. Bioinformatics 26, 2867-2873.
    Mbatchou, J., Barnard, L., Backman, J., Marcketta, A., Kosmicki, J.A., Ziyatdinov, A., Benner, C., O'Dushlaine, C., Barber, M., Boutkov, B., et al., 2021. Computationally efficient whole-genome regression for quantitative and binary traits. Nat. Genet. 53, 1097-1103.
    McLaren, W., Gil, L., Hunt, S.E., Riat, H.S., Ritchie, G.R., Thormann, A., Flicek, P., Cunningham, F., 2016. The Ensembl Variant Effect Predictor. Genome. Biol. 17, 122.
    Nam, K., Kim, J., Lee, S., 2022. Genome-wide study on 72,298 individuals in Korean biobank data for 76 traits. Cell Genom. 2, 100189.
    Olafsson, S., Alexandersson, K.F., Gizurarson, J.G.K., Hauksdottir, K., Gunnarsson, O., Olafsson, K., Gudmundsson, J., Stacey, S.N., Sveinbjornsson, G., Saemundsdottir, J., et al., 2020. Common and rare sequence variants influencing tumor biomarkers in blood. Cancer Epidemiol. Biomarkers Prev. 29, 225-235.
    Pingault, J.B., O'Reilly, P.F., Schoeler, T., Ploubidis, G.B., Rijsdijk, F., Dudbridge, F., 2018. Using genetic data to strengthen causal inference in observational research. Nat. Rev. Genet. 19, 566-580.
    Pinho, S.S., Reis, C.A., 2015. Glycosylation in cancer: mechanisms and clinical implications. Nat. Rev. Cancer 15, 540-555.
    Plenge, R.M., Scolnick, E.M., Altshuler, D., 2013. Validating therapeutic targets through human genetics. Nat. Rev. Drug Discov. 12, 581-594.
    Sakaue, S., Kanai, M., Tanigawa, Y., Karjalainen, J., Kurki, M., Koshiba, S., Narita, A., Konuma, T., Yamamoto, K., Akiyama, M., et al., 2021. A cross-population atlas of genetic associations for 220 human phenotypes. Nat. Genet. 53, 1415-1424.
    Suo, C., Xu, H., Khor, C.C., Ong, R.T., Sim, X., Chen, J., Tay, W.T., Sim, K.S., Zeng, Y.X., Zhang, X., et al., 2012. Natural positive selection and north-south genetic diversity in East Asia. Eur. J. Hum. Genet. 20, 102-110.
    Suo, C., Yang, Y., Yuan, Z., Zhang, T., Yang, X., Qing, T., Gao, P., Shi, L., Fan, M., Cheng, H., et al., 2019. Alcohol intake interacts with functional genetic polymorphisms of aldehyde dehydrogenase (ALDH2) and alcohol dehydrogenase (ADH) to increase esophageal squamous cell cancer risk. J. Thorac. Oncol. 14, 712-725.
    Tang, Y., Wang, X., Wang, J., Huang, W., Gao, Y., Luo, Y., Lu, Y., 2015. Prevalence and causes of visual impairment in a Chinese adult population: the Taizhou Eye Study. Ophthalmology 122, 1480-1488.
    Taylor, P.N., Albrecht, D., Scholz, A., Gutierrez-Buey, G., Lazarus, J.H., Dayan, C.M., Okosieme, O.E., 2018. Global epidemiology of hyperthyroidism and hypothyroidism. Nat. Rev. Endocrinol. 14, 301-316.
    Walters, R.G., Millwood, I.Y., Lin, K., Schmidt Valle, D., McDonnell, P., Hacker, A., Avery, D., Edris, A., Fry, H., Cai, N., et al., 2023. Genotyping and population characteristics of the China Kadoorie Biobank. Cell Genom. 3, 100361.
    Wang, X., Lu, M., Qian, J., Yang, Y., Li, S., Lu, D., Yu, S., Meng, W., Ye, W., Jin, L., 2009. Rationales, design and recruitment of the Taizhou Longitudinal Study. BMC Public Health 9, 223.
    Xu, X., Peng, Q., Jiang, X., Tan, S., Yang, W., Han, Y., Oyang, L., Lin, J., Shen, M., Wang, J., et al., 2024. Altered glycosylation in cancer: molecular functions and therapeutic potential. Cancer Commun. (Lond) 44, 1316-1336.
    Xue, Y., Mezzavilla, M., Haber, M., McCarthy, S., Chen, Y., Narasimhan, V., Gilly, A., Ayub, Q., Colonna, V., Southam, L., et al., 2017. Enrichment of low-frequency functional variants revealed by whole-genome sequencing of multiple isolated European populations. Nat. Commun. 8, 15927.
    Yip, W., Fu, H., Jian, W., Liu, J., Pan, J., Xu, D., Yang, H., Zhai, T., 2023. Universal health coverage in China part 1: progress and gaps. Lancet Public Health 8, e1025-e1034.
    Yuan, H., Jiang, Y., Liu, Z., Zhao, R., Yuan, Z., Man, Q., Liu, S., Zhang, H., Xu, L., Zhang, Y., et al., 2025. Leveraging biomarkers and primary care embedding for scalable precision cancer prevention in China: insights from the FuSion study. The Innovation 101189.
    Yurkovich, J.T., Evans, S.J., Rappaport, N., Boore, J.L., Lovejoy, J.C., Price, N.D., Hood, L.E., 2024. The transition from genomics to phenomics in personalized population health. Nat. Rev. Genet. 25, 286-302.
    Zhao, R., Yuan, H., Jiang, Y., Liu, Z., Chen, R., Wang, S., Lu, L., Yuan, Z., Su, Z., He, Q., et al., 2025. Development and validation of an integrative 54 biomarker-based risk identification model for multi-cancer in 42,666 individuals: a population-based prospective study to guide advanced screening strategies. Biomark. Res. 13, 101.
    Zhao, Z., Yang, X., Dorn, S., Miao, J., Barcellos, S.H., Fletcher, J.M., Lu, Q., 2024. Controlling for polygenic genetic confounding in epidemiologic association studies. Proc. Natl. Acad. Sci. U. S. A. 121, e2408715121.
    Zhou, M., Wang, H., Zeng, X., Yin, P., Zhu, J., Chen, W., Li, X., Wang, L., Wang, L., Liu, Y., et al., 2019. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 394, 1145-1158.
    • 相关文章
    • 施引文献
  • 资源附件(0)
  • 加载中
WeChat 点击查看大图
计量
  • 文章访问数:  56
  • HTML全文浏览量:  27
  • PDF下载量:  0
  • 被引次数: 0
出版历程
  • 收稿日期:  2025-09-29
  • 录用日期:  2026-02-02
  • 修回日期:  2026-01-24
  • 网络出版日期:  2026-02-09

目录

    /

    返回文章
    返回

    Copyright © 2009《 石油钻探技术 》 All Rights Reserved.

    地址：北京市朝阳区北辰东路8号北辰时代大厦716室邮政编码：100101

    电话：010-84988317，84988356，84988357传真：021-64253812Email：syzt@vip.163.com

    京公网安备 11010502036328号　京ICP备17033152号

    本系统由 北京仁和汇智信息技术有限公司 开发