Biobanks Empower Personalized Treatment of Hypertension: Mechanism Exploration and Prospects

Siyuan Zhao

doi:10.54097/d4x2mb72

Authors

Siyuan Zhao

DOI:

https://doi.org/10.54097/d4x2mb72

Keywords:

Biobank, Hypertension, Personalized Treatment, Digital Health

Abstract

Recently, biobanks have significantly expanded in scale and functionality by systematically collecting diverse biological specimens, such as blood, urine, tissues, and DNA. This expansion provides crucial data support for precision medicine, particularly in disease diagnosis and treatment. As a highly prevalent chronic disease worldwide, hypertension presents limited efficacy with traditional therapeutic approaches due to its multifactorial pathogenesis. The deep integration of biobanks with hypertension research, however, is fostering a series of innovative pathways—by integrating multidimensional biological information from genomics, metabolomics, and other omics fields, combined with patients' clinical phenotypes and longitudinal follow-up data, individualized risk prediction models can be constructed to guide the selection of targeted drugs and optimize lifestyle intervention strategies. This data-driven precision medicine model provides a novel paradigm for addressing hypertension heterogeneity and establishes a scientific foundation for transitioning chronic disease management toward lifelong health stewardship.

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References

[1] Wierzejska E, Giernaś B, Lipiak A, Karasiewicz M, Cofta M, Staszewski R. A global perspective on the costs of hypertension: a systematic review. Arch Med Sci. 2020 Jan 31;16(5):1078-1091. doi: 10.5114/aoms.2020.92689. PMID: 32863997; PMCID: PMC7444692.

[2] Gheorghe A, Griffiths U, Murphy A, Legido-Quigley H, Lamptey P, Perel P. The economic burden of cardiovascular disease and hypertension in low- and middle-income countries: a systematic review. BMC Public Health. 2018 Aug 6;18(1):975. doi: 10.1186/s12889-018-5806-x. PMID: 30081871; PMCID: PMC 6090747.

[3] He J., Gu D., Chen J., Wu X., Kelly T.N., Huang J.F., Chen J.C., Chen C.S., Bazzano L.A., Reynolds K., et al. Premature deaths attributable to blood pressure in China: A prospective cohort study. Lancet. 2009; 374:1765–1772. doi: 10.1016/S0140-6736(09)61199-5.

[4] Armani C., Botto N., Andreassi M.G. Susceptibility genes in hypertension. Curr Pharm Des. 2011; 17: 2973–2986. doi: 10.2174/138161211798157667.

[5] Lalouel J.M., Rohrwasser A. Genetic susceptibility to essential hypertension: Insight from angiotensinogen. Hypertension. 2007; 49: 597–603. doi: 10.1161/01.HYP.0000257145.20363.9c.

[6] Cho SB, Jang J. A Genome-Wide Association Study of a Korean Population Identifies Genetic Susceptibility to Hypertension Based on Sex-Specific Differences. Genes (Basel). 2021 Nov 16; 12 (11): 1804. doi: 10.3390/genes12111804. PMID: 34828409; PMCID: PMC8622776.

[7] Bailey MA, Dhaun N. Salt Sensitivity: Causes, Consequences, and Recent Advances. Hypertension. 2024 Mar;81(3):476-489. doi: 10.1161/HYPERTENSIONAHA.123.17959. Epub 2023 Sep 18. PMID: 37721034; PMCID: PMC10863664.

[8] Bailey MA, Dhaun N. Salt Sensitivity: Causes, Consequences, and Recent Advances. Hypertension. 2024 Mar;81(3):476-489. doi: 10.1161/HYPERTENSIONAHA.123.17959. Epub 2023 Sep 18. PMID: 37721034; PMCID: PMC10863664.

[9] Elghazaly H, McCracken C, Szabo L, Malcolmson J, Manisty CH, Davies AH, Piechnik SK, Harvey NC, Neubauer S, Mohiddin SA, Petersen SE, Raisi-Estabragh Z. Characterizing the hypertensive cardiovascular phenotype in the UK Biobank. Eur Heart J Cardiovasc Imaging. 2023 Sep 26;24(10):1352-1360. doi: 10.1093/ehjci/jead123. PMID: 37309807; PMCID: PMC10531143.

[10] Recommendations | Hypertension in adults: diagnosis and management | Guidance | NICE.

[11] Crutchfield CA, Thomas SN, Sokoll LJ, Chan DW. Advances in mass spectrometry-based clinical biomarker discovery. Clin Proteomics. 2016 Jan 7; 13: 1. Doi: 10.1186/s12014-015-9102-9. PMID: 26751220; PMCID: PMC4705754.

[12] den Ouden H, Pellis L, Rutten GEHM, Geerars-van Vonderen IK, Rubingh CM, van Ommen B, van Erk MJ, Beulens JWJ. Metabolomic biomarkers for personalised glucose lowering drugs treatment in type 2 diabetes. Metabolomics. 2016; 12: 27. doi: 10.1007/s11306-015-0930-4. Epub 2016 Jan 6. PMID: 26770180; PMCID: PMC4703625.

[13] Garcia-Canaveras J.C., Jimenez N., Gomez-Lechon M.J., Castell J.V., Donato M.T., Lahoz A. LC-MS untargeted metabolomic analysis of drug-induced hepatotoxicity in HepG2 cells. Electrophoresis. 2015; 36: 2294–2302. doi: 10.1002/elps.201500095.

[14] Chen C, Gonzalez FJ, Idle JR. LC-MS-based metabolomics in drug metabolism. Drug Metab Rev. 2007;39(2-3):581-97. doi: 10.1080/03602530701497804. PMID: 17786640; PMCID: PMC2140249.

[15] Li B, He X, Jia W, Li H. Novel Applications of Metabolomics in Personalized Medicine: A Mini-Review. Molecules. 2017 Jul 13;22(7):1173. doi: 10.3390/molecules22071173. PMID: 28703775; PMCID: PMC6152045.

[16] Wikoff WR, Frye RF, Zhu H, Gong Y, Boyle S, Churchill E, Cooper-Dehoff RM, Beitelshees AL, Chapman AB, Fiehn O, Johnson JA, Kaddurah-Daouk R; Pharmacometabolomics Research Network. Pharmacometabolomics reveals racial differences in response to atenolol treatment. PLoS One. 2013;8(3):e57639. doi: 10.1371/journal.pone.0057639. Epub 2013 Mar 11. PMID: 23536766; PMCID: PMC3594230.

[17] Zhang S, Qian ZM, Chen L, Zhao X, Cai M, Wang C, Zou H, Wu Y, Zhang Z, Li H, Lin H. Exposure to Air Pollution during Pre-Hypertension and Subsequent Hypertension, Cardiovascular Disease, and Death: A Trajectory Analysis of the UK Biobank Cohort. Environ Health Perspect. 2023 Jan;131(1):17008. doi: 10.1289/EHP10967. Epub 2023 Jan 25. Erratum in: Environ Health Perspect. 2023 Feb;131(2):29001. doi: 10.1289/EHP12836. PMID: 36696106; PMCID: PMC9875843.

[18] Chen Z, Chen J, Collins R, Guo Y, Peto R, Wu F, Li L; China Kadoorie Biobank (CKB) collaborative group. China Kadoorie Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up. Int J Epidemiol. 2011 Dec;40(6):1652-66. doi: 10.1093/ije/dyr120. Epub 2011 Sep 21. PMID: 22158673; PMCID: PMC3235021.

[19] Armani C, Botto N, Andreassi MG. Susceptibility genes in hypertension. Curr Pharm Des. 2011;17(28):2973-86. doi: 10.2174/138161211798157667. PMID: 21861838.

[20] Lalouel JM, Rohrwasser A. Genetic susceptibility to essential hypertension: insight from angiotensinogen. Hypertension. 2007 Mar;49(3):597-603. doi: 10.1161/01.HYP.0000257145.20363.9c. Epub 2007 Jan 22. PMID: 17242300.

[21] Coppola L, Cianflone A, Grimaldi AM, Incoronato M, Bevilacqua P, Messina F, Baselice S, Soricelli A, Mirabelli P, Salvatore M. Biobanking in health care: evolution and future directions. J Transl Med. 2019 May 22;17(1):172. doi: 10.1186/s12967-019-1922-3. PMID: 31118074; PMCID: PMC6532145.

[22] Campbell LD, Astrin JJ, DeSouza Y, Giri J, Patel AA, Rawley-Payne M, Rush A, Sieffert N. The 2018 Revision of the ISBER Best Practices: Summary of Changes and the Editorial Team's Development Process. Biopreserv Biobank. 2018 Feb;16(1):3-6. doi: 10.1089/bio.2018.0001. Epub 2018 Feb 2. PMID: 29393664; PMCID: PMC5846567.

[23] Lake BB, Chen S, Hoshi M, Plongthongkum N, Salamon D, Knoten A, Vijayan A, Venkatesh R, Kim EH, Gao D, Gaut J, Zhang K, Jain S. A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys. Nat Commun. 2019 Jun 27;10(1):2832. doi: 10.1038/s41467-019-10861-2. PMID: 31249312; PMCID: PMC6597610.

[24] Tsai YC, Kuo MC, Huang JC, Chang WA, Wu LY, Huang YC, Chang CY, Lee SC, Hsu YL. Single-cell transcriptomic profiles in the pathophysiology within the microenvironment of early diabetic kidney disease. Cell Death Dis. 2023 Jul 17;14(7):442. doi: 10.1038/s41419-023-05947-1. PMID: 37460555; PMCID: PMC10352247.

[25] Mantri M, Hinchman MM, McKellar DW, Wang MFZ, Cross ST, Parker JSL, De Vlaminck I. Spatiotemporal transcriptomics reveals pathogenesis of viral myocarditis. Nat Cardiovasc Res. 2022 Oct;1(10):946-960. doi: 10.1038/s44161-022-00138-1. Epub 2022 Oct 10. PMID: 36970396; PMCID: PMC10035375.

[26] Alam, O. Single-cell spatial sequencing. Nat Genet 53, 1119 (2021).

[27] Ranzoni AM, Tangherloni A, Berest I, Riva SG, Myers B, Strzelecka PM, Xu J, Panada E, Mohorianu I, Zaugg JB, Cvejic A. Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Human Developmental Hematopoiesis. Cell Stem Cell. 2021 Mar 4;28(3):472-487.e7. doi: 10.1016/ j.stem. 2020. 11.015. Epub 2020 Dec 21. PMID: 33352111; PMCID: PMC7939551.

[28] Xu X, Jin H, Li X, Yan C, Zhang Q, Yu X, Liu Z, Liu S, Zhu F. Fecal Microbiota Transplantation Regulates Blood Pressure by Altering Gut Microbiota Composition and Intestinal Mucosal Barrier Function in Spontaneously Hypertensive Rats. Probiotics Antimicrob Proteins. 2024 Aug 22. doi: 10.1007/s12602-024-10344-x. Epub ahead of print. PMID: 39172216.

[29] O'Donnell JA, Zheng T, Meric G, Marques FZ. The gut microbiome and hypertension. Nat Rev Nephrol. 2023 Mar;19(3):153-167. doi: 10.1038/s41581-022-00654-0. Epub 2023 Jan 11. PMID: 36631562.

[30] Yang Z, Wang Q, Liu Y, Wang L, Ge Z, Li Z, Feng S, Wu C. Gut microbiota and hypertension: association, mechanisms and treatment. Clin Exp Hypertens. 2023 Dec 31;45(1):2195135. doi: 10.1080/ 10641 963.2023.2195135. PMID: 36994745.

[31] Sajeev JK, Koshy AN, Teh AW. Wearable devices for cardiac arrhythmia detection: a new contender? Intern Med J. 2019 May;49(5):570-573. doi: 10.1111/imj.14274. PMID: 31083804.

[32] Lin, M., Hu, H., Zhou, S. et al. Soft wearable devices for deep-tissue sensing. Nat Rev Mater 7, 850–869 (2022).

[33] Liu JJ, Borsari B, Li Y, Liu SX, Gao Y, Xin X, Lou S, Jensen M, Garrido-Martín D, Verplaetse TL, Ash G, Zhang J, Girgenti MJ, Roberts W, Gerstein M. Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations. Cell. 2025 Jan 23;188(2):515-529.e15. doi: 10.1016/j.cell.2024.11.012. Epub 2024 Dec 19. PMID: 39706190; PMCID: PMC12278733.