Whole-Genome Sequencing Reveals Age-Specific Changes in the Human Blood Microbiota
Abstract
:1. Introduction
2. Materials and Methods
2.1. Subjects
2.2. WGS and Materials
2.3. Mapping the WGS Data to Bacterial Genomes
2.4. Genomic Coverage
2.5. Taxonomic Analysis
2.6. Statistical Analysis
3. Results
3.1. Demographics of Subjects
3.2. Identification of the Blood Microbiota Using WGS Data
3.3. Overview of the Blood Microbiota Composition
3.4. Blood Microbial Diversity
3.5. Association between Blood Microbial Composition and Age
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristics | Overall | Young (N = 10) | Middle-Aged (N = 15) | Elderly (N = 12) | p |
---|---|---|---|---|---|
Age (year) a | 49.35 (20.30) | 23.00 (5.46) | 47.67 (3.68) | 73.42 (6.36) | <0.0001 *** |
Sex (men, %) b | 48.65 | 50.00 | 40.00 | 58.33 | 0.653 |
Weight (kg) a | 62.60 (13.22) | 59.81 (14.54) | 65.19 (14.37) | 61.69 (10.90) | 0.596 |
Height (cm) a | 162.69 (9.54) | 168.98 (8.92) | 160.90 (8.23) | 159.69 (9.80) | 0.043 * |
BMI (kg/m2) a | 23.57 (3.85) | 20.78 (3.70) | 24.95 (3.64) | 24.17 (3.22) | 0.019 * |
Glucose (mg/dL) a | 95.43 (22.72) | 90.30 (7.36) | 101.07 (32.63) | 92.67 (14.67) | 0.459 |
Type-2 diabetes (%) b | 8.11 | 0 | 6.67 | 16.67 | 0.349 |
Hypertension (%) b | 29.73 | 30 | 40 | 16.67 | 0.419 |
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Lee, E.-J.; Sung, J.; Kim, H.-L.; Kim, H.-N. Whole-Genome Sequencing Reveals Age-Specific Changes in the Human Blood Microbiota. J. Pers. Med. 2022, 12, 939. https://doi.org/10.3390/jpm12060939
Lee E-J, Sung J, Kim H-L, Kim H-N. Whole-Genome Sequencing Reveals Age-Specific Changes in the Human Blood Microbiota. Journal of Personalized Medicine. 2022; 12(6):939. https://doi.org/10.3390/jpm12060939
Chicago/Turabian StyleLee, Eun-Ju, Joohon Sung, Hyung-Lae Kim, and Han-Na Kim. 2022. "Whole-Genome Sequencing Reveals Age-Specific Changes in the Human Blood Microbiota" Journal of Personalized Medicine 12, no. 6: 939. https://doi.org/10.3390/jpm12060939