C
Table of International Programs
TABLE C-1 International Programs
| Name | Country/Region | Short Description | Population Descriptors Used |
| BioBank Japan (BBJ) | Japan | BBJ was started in 2003 as a disease biobank. Since 2018, the aim of the biobank is to use the registered samples and data for genomics and clinical research (BBJ, 2021). | None |
| Brazilian Initiative on Precision Medicine (BIPMed) | Brazil | The aim is to offer public access to genomic and phenotypic data from Brazil to scientists and clinicians around the world. It is the Brazilian Country Node of the Human Variome Project (HVP) (BIPMed, n.d.). | Birth location in Brazil |
| China Kadoorie Biobank (CKB) | China | The over half a million participants were recruited from 10 geographically defined and diverse regions of China (CKB, n.d.). | None |
| deCODE genetics | Iceland | This database is made up of genotypic and medical information for more than 160,000 participants which makes up over half of the adult population in Iceland. These data are used in gene discovery work (deCODE, 2016). | Geographic location in Iceland |
| Estonian Biobank | Estonia | Population-based biobank that has a cohort of over 200,000 individuals which makes up about 20% of the adult population in Estonia. The current cohort is reflective of the age, sex, and geographical distribution of adults in Estonia: Estonians represent 83%, Russians 14%, and other nationalities 3% (UT, 2021). | Place of birth, place(s) of living, nationality |
| Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI) | South Africa | Community-based cohort of 5,059 men and women who are 40 or older. The aim of the study is to identify characteristics of the aging process in rural South Africa (HAALSI, 2022). | Country of origin and languages spoken |
| Korea Biobank Project (KBP) | South Korea | The purpose of KBP is to collect and manage human bioresources for future use in research. In 2018, the biobank was made up of 852,769 participants (KBP, n.d.). | None |
| Malaysia Cohort Study | Malaysia | Aims to recruit 100,000 individuals aged 35–70 years to identify risk factors, gene–environment interactions, and biomarkers for cancer and other diseases (Jamal et al., 2015). | Ethnicity—Malay, Chinese, Indian, Other; Locality—urban or rural |
| Mexican Biobank (MXB) | Mexico | To date, they have genotyped 6,057 Mexican individuals who are linked with their demographic and medical data. The individuals were recruited from all 32 states with specific efforts made to include those who speak an Indigenous language (Sohail et al., 2022). | Geography and genetic ancestry |
| Prospective Epidemiological Research Studies in Iran (PERSIAN Cohort Study) | Iran | Aims to recruit 180,000 individuals aged 35–70 years from 18 regions in Iran. The study is designed to be ethnically representative and recruit across diverse geographies of the country (Poustchi et al., 2018). | Ethnicity |
| Qatar Biobank (QBB) | Qatar | The population cohort aims to recruit 60,000 participants. The goal of the biobank is to collect information to study how lifestyle, environment, and genes affect health locally in Qatar (Fthenou et al., 2019). | Ethnicity—Qataris, long-term residents who are members of Arab groups other than Qatari, and long-term residents of non-Arab groups. Members of Arab group other than Qatari include Algerian, Bahraini, Egyptian, Emirian, Iraqi, Jordanian, Kuwaiti, Lebanese, Mauritanian, Moroccan, Omani, Palestinian, Saudi Arabian, Somali, Sudanese, Syrian, Tunisian, Emirati, and Yemeni. Non-Arab groups include: American, Armenian, Bangladeshi, Canadian, Cypriot, Ethiopian, Indian, Iranian, Japanese, Dutch, Pakistani, Filipino, Tajikistani, and British (Al Thani et al., 2019). |
| Singapore National Precision Medicine Program | Singapore | Three-phase program to implement precision health. Phase I collected 10,000 genomes for a reference database, phase II aims to collect 100,000 genomes of healthy individuals and 50,000 from people with specific diseases, and phase III will implement precision medicine (PRECISE, 2022). | Self-reported ethnicity, inferred ethnicity, and inferred ancestry based on genotyping |
| Taiwan Biobank | Taiwan | The aim of the biobank is to improve medical care. The biobank was established in 2012 and has recruited over 176,000 individuals with a goal of 200,000 participants (Wei et al., 2021). | Ancestry—Han Chinese including Taiwanese Minnan, Taiwanese Hakka, and ancestries across China: East China, South Central China, North and Northeast China, and Southwest China and other East Asian groups |
| National Laboratory for the Genetics of Israeli Populations | Israel | The laboratory is meant to be a national repository for DNA samples and human cell lines that are representative of the variation in Israel and several Middle Eastern populations (Mcgonigle, 2021). | Self-identified ethnicity—Palestinian, Druze, Bedouin, and Jewish. Jewish is broken down further into the following subcategories: Ashkenazi (central European ancestry), Ethiopian, Georgian, Iranian, Iraqi, Kuchin (India), Libyan, Moroccan, Sephardi (Turkey and Bulgaria), Tunisian, Yemenite |
| UK Biobank | United Kingdom | Genetic and health information of over half a million participants in the UK (Fry et al., 2017). | Self-reported ethnicity which includes white (white British, white Irish, and other white background), black or black British (Caribbean, African, or other black background), Mixed (white and black Caribbean, white and black African, white and Asian, and other mixed ethnic background), Indian, Pakistani, Bangladeshi, Chinese, other Asian, other ethnic group (Fry et al., 2017). |
REFERENCES
Al Thani, A., E. Fthenou, S. Paparrodopoulos, A. Al Marri, Z. Shi, F. Qafoud, and N. Afifi. 2019. Qatar Biobank cohort study: Study design and first results. American Journal of Epidemiology 188(8):1420-1433.
BBJ (Biobank Japan). 2021. Biobank Japan. https://biobankjp.org/en/index.html (accessed October 24, 2022).
BIPMed (Brazilian Initiative on Precision Medicine). n.d. About BIPMed. https://bipmed.org/about.html (accessed October 24, 2022).
CKB (China Kadoorie Biobank). n.d. Aims and rationale. https://www.ckbiobank.org/about-us/aims-and-rationale (accessed October 25, 2022).
deCODE (deCODE Genetics). 2016. Science. https://www.decode.com/research/ (accessed October 25, 2022).
Fry, A., T. J. Littlejohns, C. Sudlow, N. Doherty, L. Adamska, T. Sprosen, R. Collins, and N. E. Allen. 2017. Comparison of sociodemographic and health-related characteristics of UK biobank participants with those of the general population. American Journal of Epidemiology 186(9):1026-1034.
Fthenou, E., A. Al Thani, A. Al Marri, and N. Afifi. 2019. Qatar Biobank: A paradigm of translating biobank science into evidence-based health care interventions. Biopreservation and Biobanking 17(6):491-493.
HAALSI (Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa). 2022. About HAALSI. https://haalsi.org/about (accessed October 24, 2022).
Jamal, R., S. Z. Syed Zakaria, M. A. Kamaruddin, N. Abd Jalal, N. Ismail, N. Mohd Kamil, N. Abdullah, N. Baharudin, N. H. Hussin, H. Othman, and N. M. Mahadi. 2015. Cohort profile: The Malaysian cohort (TMC) project: A prospective study of non-communicable diseases in a multi-ethnic population. International Journal of Epidemiology 44(2):423-431.
KBP (Korea Biobank Project). n.d. Policy and services. https://www.kdca.go.kr/contents.es?mid=a30326000000 (accessed October 25, 2022).
Mcgonigle, I. 2021. National biobanking in Qatar and Israel: Tracing how global scientific institutions mediate local ethnic identities. Science, Technology and Society 26(1):146-165.
Poustchi, H., S. Eghtesad, F. Kamangar, A. Etemadi, A. A. Keshtkar, A. Hekmatdoost, Z. Mohammadi, Z. Mahmoudi, A. Shayanrad, F. Roozafzai, M. Sheikh, A. Jalaeikhoo, M. H. Somi, F. Mansour-Ghanaei, F. Najafi, E. Bahramali, A. Mehrparvar, A. Ansari-Moghaddam, A. A. Enayati, A. Esmaeili Nadimi, A. Rezaianzadeh, N. Saki, F. Alipour, R. Kelishadi, A. Rahimi-Movaghar, N. Aminisani, P. Boffetta, and R. Malekzadeh. 2018. Prospective epidemiological research studies in Iran (the PERSIAN Cohort Study): Rationale, objectives, and design. American Journal of Epidemiology 187(4):647-655.
PRECISE (Singapore National Precision Medicine Program). 2022. About us. https://www.npm.sg/about-us/our-story/ (accessed October 25, 2022).
Sohail, M., A. Y. Chong, C. D. Quinto-Cortes, M. J. Palma-Martínez, A. Ragsdale, S. G. Medina-Muñoz, C. Barberena-Jonas, G. Delgado-Sánchez, L. P. Cruz-Hervert, L. Ferreyra-Reyes, E. Ferreira-Guerrero, N. Mongua-Rodríguez, A. Jimenez-Kaufmann, H. Moreno-Macías, C. A. Aguilar-Salinas, K. Auckland, A. Cortés, V. Acuña-Alonzo, A. G. Ioannidis, C. R. Gignoux, G. L. Wojcik, S. L. Fernández-Valverde, A. V. S. Hill, M. T. Tusié-Luna, A. J. Mentzer, J. Novembre, L. García-García, and A. Moreno-Estrada. 2022. Nationwide genomic biobank in Mexico unravels demographic history and complex trait architecture from 6,057 individuals. bioRxiv 2022.07.11.499652.
UT (University of Tartu). 2021. Estonian biobank. https://genomics.ut.ee/en/content/estonian-biobank (accessed October 25, 2022).
Wei, C.-Y., J.-H. Yang, E.-C. Yeh, M.-F. Tsai, H.-J. Kao, C.-Z. Lo, L.-P. Chang, W.-J. Lin, F.-J. Hsieh, S. Belsare, A. Bhaskar, M.-W. Su, T.-C. Lee, Y.-L. Lin, F.-T. Liu, C.-Y. Shen, L.-H. Li, C.-H. Chen, J. D. Wall, J.-Y. Wu, and P.-Y. Kwok. 2021. Genetic profiles of 103,106 individuals in the Taiwan biobank provide insights into the health and history of Han Chinese. Genomic Medicine 6(1):10.
