Single-cell transcriptome analyses of PBMCs reveal the immunological characteristics of individuals with phlegm-dampness constitution

Abstract

Ancient traditional Chinese medicine (TCM) doctrine says “The superior doctor prevents illnesses,” pointing out preventative medicine as the ultimate goal for medical care. TCM recognizes that genetic predisposition and environmental and lifestyle influences contribute to diseases. It divides people into eight constitutions in addition to one normal/healthy kind. People with one of the eight subhealth constitutions are prone to develop different kinds of corresponding illnesses. The goal for this type of categorization is to help people take preemptive measures to prevent or delay disease onset. As the peripheral immune system through surveying the body, it can capture information from essentially all organs and reflect anomalies occurring in each organ. Thus, the detailed profiling of the peripheral immune-system function can generally reflect a person’s overall heath state. In this study, we performed the single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from individuals with Tanshi (phlegm dampness) constitution. They were prone to develop metabolic disorders including diabetes. scRNA-seq revealed greatly reduced mucosal-associated invariable T cell content and heightened TNFα-NFκB, JAK-STAT, and interferon signaling. These findings indicated heightened chronic inflammation, as well as increased hypoxia/apoptosis responses, likely resulting from frequent sleep apnea that Tanshi individuals experienced. Altogether, this pilot study demonstrated effectiveness in using scRNA-seq to reveal molecular-immunological bases for constitution categorization, thereby substantiating that preventative medicine originated from TCM.

Keywords

scRNA-seq / PBMC / Tanshi constitution / TCM

References

[1] Liu S, Wang ZF, Su YS, Ray RS, Jing XH, Wang YQ, Ma Q. Somatotopic organization and intensity dependence in driving distinct NPY-expressing sympathetic pathways by electroacupuncture. Neuron 2020; 108(3): 436–450.e7

[2] Liu S, Wang Z, Su Y, Qi L, Yang W, Fu M, Jing X, Wang Y, Ma Q. A neuroanatomical basis for electroacupuncture to drive the vagal-adrenal axis. Nature 2021; 598(7882): 641–645

[3] Wang Q. Individualized medicine, health medicine, and constitutional theory in Chinese medicine. Front Med 2012; 6(1): 1–7

[4] Wu Y, Cun Y, Dong J, Shao J, Luo S, Nie S, Yu H, Zheng B, Wang Q, Xiao C. Polymorphisms in PPARD, PPARG and APM1 associated with four types of traditional Chinese medicine constitutions. J Genet Genomics 2010; 37(6): 371–379

[5] Wang J, Wang Q, Li L, Li Y, Zhang H, Zheng L, Yang L, Zheng Y, Yang Y, Peng G, Zhang Y, Han Y. Phlegm-dampness constitution: genomics, susceptibility, adjustment and treatment with traditional Chinese medicine. Am J Chin Med 2013; 41(2): 253–262

[6] Yao H, Mo S, Wang J, Li Y, Wang CZ, Wan JY, Zhang Z, Chen Y, Sun R, Yuan CS, Liu X, Li L, Wang Q. Genome-wide DNA methylation profiles of phlegm-dampness constitution. Cell Physiol Biochem 2018; 45(5): 1999–2008

[7] Li L, Yao H, Wang J, Li Y, Wang Q. The role of Chinese medicine in health maintenance and disease prevention: application of constitution theory. Am J Chin Med 2019; 47(3): 495–506

[8] Tan F, Chen X, Zhang H, Yuan J, Sun C, Xu F, Huang L, Zhang X, Guan H, Chen Z, Wang C, Fan S, Zeng L, Ma X, Ye W, He W, Lu P, Petritis B, Huang RP, Yang Z. Differences in serum proteins in traditional Chinese medicine constitutional population: analysis and verification. J Leukoc Biol 2020; 108(2): 547–557

[9] Kunz DJ, Gomes T, James KR. Immune cell dynamics unfolded by single-cell technologies. Front Immunol 2018; 9: 1435

[10] Monaco G, Lee B, Xu W, Mustafah S, Hwang YY, Carre C, Burdin N, Visan L, Ceccarelli M, Poidinger M, Zippelius A, Pedro de Magalhaes J, Larbi A. RNA-seq signatures normalized by mRNA abundance allow absolute deconvolution of human immune cell types. Cell Rep 2019; 26(6): 1627–1640.e7

[11] Liu J, Wang J, Xu J, Xia H, Wang Y, Zhang C, Chen W, Zhang H, Liu Q, Zhu R, Shi Y, Shen Z, Xing Z, Gao W, Zhou L, Shao J, Shi J, Yang X, Deng Y, Wu L, Lin Q, Zheng C, Zhu W, Wang C, Sun YE, Liu Z. Comprehensive investigations revealed consistent pathophysiological alterations after vaccination with COVID-19 vaccines. Cell Discov 2021; 7(1): 99

[12] Pizzolato G, Kaminski H, Tosolini M, Franchini DM, Pont F, Martins F, Valle C, Labourdette D, Cadot S, Quillet-Mary A, Poupot M, Laurent C, Ysebaert L, Meraviglia S, Dieli F, Merville P, Milpied P, Dechanet-Merville J, Fournie JJ. Single-cell RNA sequencing unveils the shared and the distinct cytotoxic hallmarks of human TCRVδ1 and TCRVδ2 γδ T lymphocytes. Proc Natl Acad Sci USA 2019; 116(24): 11906–11915

[13] Parrot T, Gorin JB, Ponzetta A, Maleki KT, Kammann T, Emgard J, Perez-Potti A, Sekine T, Rivera-Ballesteros O, Karolinska CSG, Gredmark-Russ S, Rooyackers O, Folkesson E, Eriksson LI, Norrby-Teglund A, Ljunggren HG, Bjorkstrom NK, Aleman S, Buggert M, Klingstrom J, Stralin K, Sandberg JK. MAIT cell activation and dynamics associated with COVID-19 disease severity. Sci Immunol 2020; 5(51): eabe1670

[14] Li L, Feng J, Yao H, Xie L, Chen Y, Yang L, Hou S, Zhao S, Sun R, Wu Y, Bai T, Li Y, Yu R, Wang J, Wang Q. Gene expression signatures for phlegm-dampness constitution of Chinese medicine. Sci China Life Sci 2017; 60(1): 105–107

[15] Wang X, Chen Y, Li Z, Huang B, Xu L, Lai J, Lu Y, Zha X, Liu B, Lan Y, Li Y. Single-cell RNA-Seq of T cells in B-ALL patients reveals an exhausted subset with remarkable heterogeneity. Adv Sci (Weinh) 2021; 8(19): 2101447

[16] Zhang JY, Wang XM, Xing X, Xu Z, Zhang C, Song JW, Fan X, Xia P, Fu JL, Wang SY, Xu RN, Dai XP, Shi L, Huang L, Jiang TJ, Shi M, Zhang Y, Zumla A, Maeurer M, Bai F, Wang FS. Single-cell landscape of immunological responses in patients with COVID-19. Nat Immunol 2020; 21(9): 1107–1118

[17] Shi J, Zhou J, Zhang X, Hu W, Zhao JF, Wang S, Wang FS, Zhang JY. Single-cell transcriptomic profiling of MAIT cells in patients with COVID-19. Front Immunol 2021; 12: 700152

[18] Yang J, Su W, Cai R, Liu X, Wei L. Analysis of TCM syndromes and constitution of 90 patients with common COVID-19. J Tradit Chin Med 2020; 61(8): 645–649

[19] Chen H, Wang K, Xiao H, Hu Z, Zhao L. Structural characterization and pro-inflammatory activity of a thaumatin-like protein from pulp tissues of Litchi chinensis. J Agric Food Chem 2020; 68(23): 6439–6447

[20] Wolf FA, Angerer P, Theis FJ. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol 2018; 19(1): 15

[21] Korsunsky I, Millard N, Fan J, Slowikowski K, Zhang F, Wei K, Baglaenko Y, Brenner M, Loh PR, Raychaudhuri S. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat Methods 2019; 16(12): 1289–1296

[22] Stassen SV, Siu DMD, Lee KCM, Ho JWK, So HKH, Tsia KK. PARC: ultrafast and accurate clustering of phenotypic data of millions of single cells. Bioinformatics 2020; 36(9): 2778–2786

[23] Zeisel A, Hochgerner H, Lonnerberg P, Johnsson A, Memic F, van der Zwan J, Haring M, Braun E, Borm LE, La Manno G, Codeluppi S, Furlan A, Lee K, Skene N, Harris KD, Hjerling-Leffler J, Arenas E, Ernfors P, Marklund U, Linnarsson S. Molecular architecture of the mouse nervous system. Cell 2018; 174(4): 999–1014.e22

[24] Li B, Gould J, Yang Y, Sarkizova S, Tabaka M, Ashenberg O, Rosen Y, Slyper M, Kowalczyk MS, Villani AC, Tickle T, Hacohen N, Rozenblatt-Rosen O, Regev A. Cumulus provides cloud-based data analysis for large-scale single-cell and single-nucleus RNA-seq. Nat Methods 2020; 17(8): 793–798

[25] Wolock SL, Lopez R, Klein AM. Scrublet: computational identification of cell doublets in single-cell transcriptomic data. Cell Syst 2019; 8(4): 281–291.e9

[26] Crowell HL, Soneson C, Germain PL, Calini D, Collin L, Raposo C, Malhotra D, Robinson MD. muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data. Nat Commun 2020; 11(1): 6077

Acknowledgements

We thank Chunxue Zhang, Xiaobo Sun, Yanfei Zheng, Yaqi Wang, Zhonggang Xing, Junbang Wang, Yinan Yao, and Changhong Zheng for their assistance in participant recruitment. This study was founded by grants from the Special Project of National Natural Science Foundation of China (No. T2341006); High Level Key Discipline of National Administration of Traditional Chinese Medicine – Traditional Chinese Constitutional Medicine (No. zyyzdxk-2023251); National Key R&D Program of China (No. 2024YFF1206400); Peak Disciplines (Type IV) of Institutions of Higher Learning in Shanghai; State Key Program of the National Natural Science Foundation of China (Nos. 82030035 and W2411081); the Clinical TCM Peak Discipline Construction Project of Pudong New Area Health Commission (No. PDZY-2018-0603); the Gaoyuan Discipline Development Program of Pudong New Area (No. YC-2023-0604); Research Project of Pudong New Area Health Commission (No. PW2024A-76).

Electronic supplementary material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11684-024-1113-3 and is accessible for authorized users.

Compliance with ethics guidelines

Conflicts of interest Weibo Zhao, Liqiang Zhou, Yixing Wang, Ji Wang, Yi Eve Sun, and Qi Wang declare that there is no conflict of interest.

The study was approved by the Ethics Committee of Shanghai East Hospital and the study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Informed consent was obtained from all patients for being included in the study.

RIGHTS & PERMISSIONS

2025 Higher Education Press