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Suggested Citation:"Appendix C: Table of International Programs." National Academies of Sciences, Engineering, and Medicine. 2023. Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field. Washington, DC: The National Academies Press. doi: 10.17226/26902.
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Suggested Citation:"Appendix C: Table of International Programs." National Academies of Sciences, Engineering, and Medicine. 2023. Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field. Washington, DC: The National Academies Press. doi: 10.17226/26902.
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Suggested Citation:"Appendix C: Table of International Programs." National Academies of Sciences, Engineering, and Medicine. 2023. Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field. Washington, DC: The National Academies Press. doi: 10.17226/26902.
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Page187
Suggested Citation:"Appendix C: Table of International Programs." National Academies of Sciences, Engineering, and Medicine. 2023. Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field. Washington, DC: The National Academies Press. doi: 10.17226/26902.
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Page188
Suggested Citation:"Appendix C: Table of International Programs." National Academies of Sciences, Engineering, and Medicine. 2023. Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field. Washington, DC: The National Academies Press. doi: 10.17226/26902.
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Page189
Suggested Citation:"Appendix C: Table of International Programs." National Academies of Sciences, Engineering, and Medicine. 2023. Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field. Washington, DC: The National Academies Press. doi: 10.17226/26902.
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C Table of International Programs TABLE C-1  International programs Country/ Name Region Short Description Population Descriptors Used BioBank Japan Japan BBJ was started in 2003 as a None (BBJ) disease biobank. Since 2018, the aim of the biobank is to use the registered samples and data for genomics and clinical research (BBJ, 2021). Brazilian Brazil The aim is to offer public Birth location in Brazil Initiative on access to genomic and Precision phenotypic data from Brazil Medicine to scientists and clinicians (BIPMed) around the world. It is the Brazilian Country Node of the Human Variome Project (HVP) (BIPMed, n.d.). China Kadoorie China The over half a million None Biobank (CKB) participants were recruited from 10 geographically defined and diverse regions of China (CKB, n.d.). continued 185 PREPUBLICATION COPY—Uncorrected Proofs

186 POPULATION DESCRIPTORS IN GENETICS AND GENOMICS RESEARCH TABLE C-1 Continued Country/ Name Region Short Description Population Descriptors Used deCODE Iceland This database is made up Geographic location in genetics of genotypic and medical Iceland information for more than 160,000 participants which makes up over half of the adult population in Iceland. This data is used in gene discovery work (deCODE, 2016). Estonian Estonia Population-based biobank Place of birth, place(s) of Biobank that has a cohort of over living, nationality 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). Health and South Community-based cohort Country of origin and Aging in Africa: Africa of 5,059 men and women languages spoken A Longitudinal who are 40 or older. The aim Study of an of the study is to identify INDEPTH characteristics of the aging Community in process in rural South Africa South Africa (HAALSI, 2022). (HAALSI) Korea Biobank South The purpose of KBP is to None Project (KBP) Korea collect and manage human bioresources for future use in research. In 2018, the biobank was made up of 852,769 participants (KBP, n.d.). Malaysia Cohort Malaysia Aims to recruit 100,000 Ethnicity—Malay, Chinese, Study individuals aged 35–70 years Indian, Other; Locality— to identify risk factors, gene– urban or rural environment interactions, and biomarkers for cancer and other diseases (Jamal et al., 2015). PREPUBLICATION COPY—Uncorrected Proofs

APPENDIX C 187 TABLE C-1 Continued Country/ Name Region Short Description Population Descriptors Used Mexican Mexico To date, they have genotyped Geography and genetic Biobank (MXB) 6,057 Mexican individuals ancestry that is 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). Prospective Iran Aims to recruit 180,000 Ethnicity Epidemiological individuals aged 35–70 years Research from 18 regions in Iran. Studies in Iran The study is designed to (PERSIAN be ethnically representative Cohort Study) and recruit across diverse geographies of the country (Poustchi et al., 2018). Qatar Biobank Qatar The population cohort aims Ethnicity—Qataris, long- (QBB) to recruit 60,000 participants. term residents who are The goal of the biobank is to members of Arab groups collect information to study other than Qatari, and long- how lifestyle, environment, term residents of non-Arab and genes affect health locally groups. Members of Arab in Qatar (Fthenou et al., group other than Qatari 2019). 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). continued PREPUBLICATION COPY—Uncorrected Proofs

188 POPULATION DESCRIPTORS IN GENETICS AND GENOMICS RESEARCH TABLE C-1 Continued Country/ Name Region Short Description Population Descriptors Used Singapore Singapore Three-phase program to Self-reported ethnicity, National implement precision health. inferred ethnicity, and Precision Phase I collected 10,000 inferred ancestry based on Medicine genomes for a reference genotyping Program 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). Taiwan Biobank Taiwan The aim of the biobank is to Ancestry—Han Chinese improve medical care. The including Taiwanese Minnan, biobank was established in Taiwanese Hakka, and 2012 and has recruited over ancestries across China: 176,000 individuals with a East China, South Central goal of 200,000 participants China, North and Northeast (Wei et al., 2021). China, and Southwest China and other East Asian groups National Israel The laboratory is meant to Self-identified ethnicity— Laboratory for be a national repository for Palestinian, Druze, Bedouin, the Genetics DNA samples and human cell and Jewish. Jewish is of Israeli lines that are representative broken down further into Populations of the variation in Israel the following subcategories: and several Middle Eastern Ashkenazi (central European populations (Mcgonigle, ancestry), Ethiopian, 2021). Georgian, Iranian, Iraqi, Kuchin (India), Libyan, Moroccan, Sephardi (Turkey and Bulgaria), Tunisian, Yemenite UK Biobank United Genetic and health Self-reported ethnicity Kingdom information of over half a which includes white (white million participants in the UK British, white Irish, and other (Fry et al., 2017). 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). PREPUBLICATION COPY—Uncorrected Proofs

APPENDIX C 189 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 Epide- miology 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-com- municable 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 in- stitutions 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): Ratio- nale, 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. Fer- reyra-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. PREPUBLICATION COPY—Uncorrected Proofs

190 POPULATION DESCRIPTORS IN GENETICS AND GENOMICS RESEARCH 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, . . . 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. PREPUBLICATION COPY—Uncorrected Proofs

Next: Appendix D: Decision Tree for the Use of Population Descriptors in Genomics Research »
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Genetic and genomic information has become far more accessible, and research using human genetic data has grown exponentially over the past decade. Genetics and genomics research is now being conducted by a wide range of investigators across disciplines, who often use population descriptors inconsistently and/or inappropriately to capture the complex patterns of continuous human genetic variation.

In response to a request from the National Institutes of Health, the National Academies assembled an interdisciplinary committee of expert volunteers to conduct a study to review and assess existing methodologies, benefits, and challenges in using race, ethnicity, ancestry, and other population descriptors in genomics research. The resulting report focuses on understanding the current use of population descriptors in genomics research, examining best practices for researchers, and identifying processes for adopting best practices within the biomedical and scientific communities.

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