Distributing human leukocyte antigen (HLA) database in histocompatibility: a shift in HLA data governance

Abstract

Aim: Human leukocyte antigen ( HLA) population genetics has been a historical field centralizing data resource. HLA genetics databases typically facilitate access to frequencies of allele, haplotype, and genotype format information. Among many resources, the Allele Frequency Net Database (AFND) is a typical centralized repository that allows users to research and analyze immune gene frequencies in different populations around the world. With the massive increase in medical data and the strengthening of data governance laws, the proposal for a new distributed and secure model for the historical centralization method in population genetics has become important. In this paper, a new model of HLA population genetic resources, an alternative distributed version of HLA databases has been developed. It allows users to perform the same research and analysis with other remote sites without sharing their original data and monitoring data access.
Methods: This new version uses the Master/Worker distributed model and offers distributed algorithms for the calculation of allelic frequencies, haplotypic frequencies and for individual genotypic calculations. The new model was evaluated on a distributed testbed for experiment-driven research Grid’5000 and has obtained good results of accuracy and execution time compared to the original centralized scheme used by researchers.
Results: The results show that distributed algorithm applied to HLA population genetics resources enables usage control and enables enforcing the security framework of the data-owning institution. It gives the same results for all counting methods in population immunogenetics. With the same frequencies’ estimations, it yields a much quicker computation time in many cases, in particular for large samples.
Conclusions: Distributing previously centralized resources is an interesting perspective enhancing better control of data sharing.

Keywords

Distributed analysis / precision medicine / data governance / security / allele frequency / haplotype / genotype

References

[1] statistics.wmda.info [Internet]. c2022 [cited 2022 Aug 1]. Available from: https://statistics.wmda.info/

[2] Robinson J, Halliwell JA, Hayhurst JD, Flicek P, Parham P, Marsh SG. The IPD and IMGT/HLA database: allele variant databases. Nucleic Acids Res. 2015; 43: D423-31.

[3] Link J, Kockum I, Lorentzen AR, Lie BA, Celius EG, Westerlind H, et al. Importance of human leukocyte antigen (HLA) class I and II alleles on the risk of multiple sclerosis. PLoS One. 2012 May; 7: e36779.

[4] Allele Frequency Net Database [Internet]. c2022 [cited 2022 Aug 1]. Available from: http://www.allelefrequencies.net/

[5] Gonzalez-Galarza FF, McCabe A, Melo dos Santos EJ, Jones J, Takeshita LY, Ortega-Rivera ND, et al. Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools, Nucleic Acid Res. 2020; 48: D783-8.

[6] Robinson J, Halliwell JA, McWilliam H, Lopez R, Parham P, Marsh SG. The IMGT/HLA database. Nucleic Acids Res. 2013; 41: D1222-7.

[7] Gonzalez-Galarza FF, Christmas S, Middleton D, Jones AR. Allele frequency net: a database and online repository for immune gene frequencies in worldwide populations. Nucleic Acids Res. 2011; 39: D913-9.

[8] Sayadi S, Geffard E, Südholt M, Vince N, Gourraud PA. Secure distribution of factor analysis of mixed data (FAMD) and its application to personalized medicine of transplanted patients. In: Barolli L, Woungang I, Enokido T, editors. Advanced information networking and applications. AINA 2021. 2021 May 1214; Toronto, Canada. Berlin: Springer; 2021. pp. 507-18.

[9] Add New HLA Population Study [Internet]. Allele Frequency Net Database; c2022 [cited 2022 Aug 1]. Available from: http://www.allelefrequencies.net/submit/Default.aspx

[10] InternationalGenome.org [Internet]. c2021 [cited 2022 Aug 1]. Available from: https://www.internationalgenome.org/1000-genomes-summary

[11] Balouek D, Amarie CA, Charrier G, Desprez F, Jeannot E, Jeanvoine E, et al. Adding virtualization capabilities to the Grid’5000 testbed. In: Ivanov II, Sinderen M, Leymann F, Shan T, editors. Second international conference on cloud computing and services science; 2012 Apr 18-21; Porto, Portugal. Berlin: Springer; 2013. pp. 3-20.

[12] Gitlab.inria.fr [Internet]. [cited 2022 Aug 1]. Available from: https://gitlab.inria.fr/ssayadi/distributed_afnd

[13] Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) [Internet]. EUR-lex; 2016 [cited 2021 Jul 28]. Available from: http://data.europa.eu/eli/reg/2016/679/oj

[14] Hipaa for dummies [Internet]. The hipaa guide: healthcare compliance; c2007- 2022 [cited 2022 Aug 1]. Available from: https://www.hipaaguide.net/hipaa-for-dummies/

[15] Data INPI. Recherche avancée dans la base Brevets [Internet]. [cited 2022 Aug 1]. Available from: https://bases-brevets.inpi.fr/fr/document/FR3091602/publications.html?p=5&s=1594642475255&cHash=462efb7d021bce0c34a691b065b05a1d. French.

[16] Mahsa S. Blockchain-based platforms for genomic data sharing: a de-centralized approach in response to the governance problems? J Am Med Inform Assoc. 2019 Jan 1; 26: 76-80.

[17] Silva S, Gutman BA, Romero E, Thompson PM, Altmann A, Lorenzi M. Federated learning in distributed medical databases: meta-analysis of large-scale subcortical brain data. 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019); 2019 Apr 8-11; Venice, Italy. Institue of Electrial and Electronics Engineers; 2019. pp. 270-4.