Mathematical model on HIV and nutrition. (English) Zbl 1533.92195
Summary: HIV continues to be a major global health issue, having claimed millions of lives in the last few decades. While several empirical studies support the fact that proper nutrition is useful in the fight against HIV, very few studies have focused on developing and using mathematical modelling approaches to assess the association between HIV, human immune response to the disease, and nutrition. We develop a within-host model for HIV that captures the dynamic interactions between HIV, the immune system and nutrition. We find that increased viral activity leads to increased serum protein levels. We also show that the viral production rate is positively correlated with HIV viral loads, as is the enhancement rate of protein by virus. Although our numerical simulations indicate a direct correlation between dietary protein intake and serum protein levels in HIV-infected individuals, further modelling and clinical studies are necessary to gain comprehensive understanding of the relationship.
Keywords:
HIV; nutrition; reproduction number; within-host mathematical model; backward bifurcation; proteinReferences:
| [1] | Lewthwaite, P.; Wilkins, E., Natural history of HIV/AIDS, Medicine, 37, 333-337 (2009) · doi:10.1016/j.mpmed.2009.04.015 |
| [2] | USAIDS. Global HIV & AIDS statistics, Fact sheet (Accessed on March 27, 2023). https://www.unaids.org/en/resources/fact-sheet. Online Version. |
| [3] | World Health Organization. HIV: global situation and trends. Global Health Observatory (Accessed on March 27, 2023). https://www.who.int/data/gho/data/themes/hiv-aids. Online Version. |
| [4] | Burg, D.; Rong, L.; Neumann, AU, Mathematical modeling of viral kinetics under immune control during primary HIV-1 infection, J Theor Biol, 259, 751-759 (2009) · Zbl 1402.92384 · doi:10.1016/j.jtbi.2009.04.010 |
| [5] | Perdomo, MF; Hosia, W.; Jejcic, A., Human serum protein enhances HIV-1 replication and up-regulates the transcription factor AP-1, Proc Natl Acad Sci, 109, 17639-17644 (2012) · doi:10.1073/pnas.1206893109 |
| [6] | Zhu, T.; Zhong, J.; Hu, R., Patterns of white matter injury in hiv infection after partial immune reconstitution: a DTI tract-based spatial statistics study, J Neurovirol, 19, 10-23 (2013) · doi:10.1007/s13365-012-0135-9 |
| [7] | Ciupe, M.; Bivort, B.; Bortz, D., Estimating kinetic parameters from HIV primary infection data through the eyes of three different mathematical models, Math Biosci, 200, 1-27 (2006) · Zbl 1086.92022 · doi:10.1016/j.mbs.2005.12.006 |
| [8] | Maartens, G.; Celum, C.; Lewin, SR, HIV infection: epidemiology, pathogenesis, treatment, and prevention, The Lancet, 384, 258-271 (2014) · doi:10.1016/S0140-6736(14)60164-1 |
| [9] | Conway, JM; Ribeiro, RM, Modeling the immune response to HIV infection, Curr Opin Syst Bio, 12, 61-69 (2018) · doi:10.1016/j.coisb.2018.10.006 |
| [10] | Nowak, M.; May, RM, Virus dynamics: mathematical principles of immunology and virology: mathematical principles of immunology and virology (2000), UK: Oxford University Press, UK · Zbl 1101.92028 |
| [11] | Wodarz, D., Killer cell dynamics: mathematical and computational approaches to immunology (2007), New York (NY): Springer · Zbl 1125.92032 |
| [12] | De Boer, RJ; Perelson, AS, Target cell limited and immune control models of HIV infection: a comparison, J Theor Biol, 190, 201-214 (1998) · doi:10.1006/jtbi.1997.0548 |
| [13] | Anderson, RM; May, RM, Infectious diseases of humans: dynamics and control (1991), Oxford (UK): Oxford University Press |
| [14] | Nowak, MA; Bangham, CR, Population dynamics of immune responses to persistent viruses, Science, 272, 74-79 (1996) · doi:10.1126/science.272.5258.74 |
| [15] | Wodarz, D.; Krakauer, DC, Defining CTL-induced pathology: implications for HIV, Virology, 274, 94-104 (2000) · doi:10.1006/viro.2000.0399 |
| [16] | Wodarz, D.; Lloyd, AL; Jansen, VA, Dynamics of macrophage and T cell infection by HIV, J Theor Biol, 196, 101-113 (1999) · doi:10.1006/jtbi.1998.0816 |
| [17] | Ganusov, VV; Neher, RA; Perelson, AS, Mathematical modeling of escape of HIV from cytotoxic T lymphocyte responses, J Stat Mech Theory Exp, 2013 (2013) · Zbl 1456.92080 · doi:10.1088/1742-5468/2013/01/P01010 |
| [18] | Ganusov, VV; De Boer, RJ, Estimating costs and benefits of CTL escape mutations in SIV/HIV infection, PLoS Comput Biol, 2, e24 (2006) · doi:10.1371/journal.pcbi.0020024 |
| [19] | Davenport, MP; Loh, L.; Petravic, J., Rates of HIV immune escape and reversion: implications for vaccination, Trends Microbiol, 16, 561-566 (2008) · doi:10.1016/j.tim.2008.09.001 |
| [20] | Mohammadi, P.; Ciuffi, A.; Beerenwinkel, N., Dynamic models of viral replication and latency, Curr Opin HIV AIDS, 10, 90-95 (2015) · doi:10.1097/COH.0000000000000136 |
| [21] | Selinger, C.; Katze, MG, Mathematical models of viral latency, Curr Opin Virol, 3, 402-407 (2013) · doi:10.1016/j.coviro.2013.06.015 |
| [22] | Rong, L.; Perelson, AS, Modeling latently infected cell activation: viral and latent reservoir persistence, and viral blips in HIV-infected patients on potent therapy, PLoS Comput Biol, 5 (2009) · doi:10.1371/journal.pcbi.1000533 |
| [23] | Akaraphanth, R.; Lim, H., HIV, UV and immunosuppression, Photodermatol Photoimmunol Photomed, 15, 28-31 (1999) · doi:10.1111/phpp.1999.15.issue-1 |
| [24] | dos SANTOS, LDC; Castro, GF; de SOUZA, IPR, Oral manifestations related to immunosuppression degree in HIV-positive children, Braz Dent J, 12, 135-8 (2001) |
| [25] | Alpert, PT, The role of vitamins and minerals on the immune system, Home Health Care Manag Pract, 29, 199-202 (2017) · doi:10.1177/1084822317713300 |
| [26] | Wintergerst, ES; Maggini, S.; Hornig, DH, Immune-enhancing role of vitamin C and zinc and effect on clinical conditions, Ann Nutr Metab, 50, 85-94 (2006) · doi:10.1159/000090495 |
| [27] | Maggini, S.; Beveridge, S.; Sorbara, PJ, Feeding the immune system: the role of micronutrients in restoring resistance to infections, CABI Rev, 1-21 (2009) · doi:10.1079/PAVSNNR20083098 |
| [28] | Tourkochristou, E.; Triantos, C.; Mouzaki, A., The influence of nutritional factors on immunological outcomes, Front Immunol, 12 (2021) · doi:10.3389/fimmu.2021.665968 |
| [29] | Beisel, WR, Nutrition and immune function: overview, J Nutr, 126, 2611S-2615S (1996) · doi:10.1093/jn/126.suppl_10.2611S |
| [30] | Duggal, S.; Chugh, TD; Duggal, AK, HIV and malnutrition: effects on immune system, Clin Dev Immunol, 2012 (2012) · doi:10.1155/2012/784740 |
| [31] | Yolken, R.; Hart, W.; Oung, I., Gastrointestinal dysfunction and disaccharide intolerance in children infected with human immunodeficiency virus, J Pediatr, 118, 359-363 (1991) · doi:10.1016/S0022-3476(05)82147-X |
| [32] | Guarino, A.; Albano, F.; Tarallo, L., Intestinal malabsorption of HIV-infected children: relationship to diarrhoea, failure to thrive, enteric micro-organisms and immune impairment, Aids, 7, 1435-1440 (1993) · doi:10.1097/00002030-199311000-00005 |
| [33] | Hsu, JW; Pencharz, PB; Macallan, D., Macronutrients and HIV/AIDS: a review of current evidence (2005), Durban, South Africa: World Health Organization, Durban, South Africa |
| [34] | Macallan, DC; McNurlan, MA; Milne, E., Whole-body protein turnover from leucine kinetics and the response to nutrition in human immunodeficiency virus infection, Am J Clin Nutr, 61, 818-826 (1995) · doi:10.1093/ajcn/61.4.818 |
| [35] | Macallan, DC; Noble, C.; Baldwin, C., Energy expenditure and wasting in human immunodeficiency virus infection, N Engl J Med, 333, 83-88 (1995) · doi:10.1056/NEJM199507133330202 |
| [36] | Macallan, DC, Wasting in HIV infection and AIDS, J Nutr, 129, 238S-242S (1999) · doi:10.1093/jn/129.1.238S |
| [37] | Macallan, DC, Metabolic abnormalities and wasting in human immunodeficiency virus infection, Proc Nutr Soc, 57, 373-380 (1998) · doi:10.1079/PNS19980054 |
| [38] | Macallan, DC, Metabolic syndromes in human immunodeficiency virus infection, Horm Res Paediatr, 55, 36-41 (2001) · doi:10.1159/000063461 |
| [39] | Harrison, TS; Macallan, DC; Rayner, CF, Treatment of tuberculosis in HIV-infected individuals, AIDS, 16, 1569-1570 (2002) · doi:10.1097/00002030-200207260-00022 |
| [40] | Boushey, CJ; Coulston, AM; Rock, CL, Nutrition in the prevention and treatment of disease (2001), Amsterdam: Elsevier |
| [41] | Dudgeon, W.; Phillips, K.; Carson, J., Counteracting muscle wasting in HIV-infected individuals, HIV Med, 7, 299-310 (2006) · doi:10.1111/hiv.2006.7.issue-5 |
| [42] | Coodley, GO; Loveless, MO; Merrill, TM, The HIV wasting syndrome: a review, J Acquir Immune Defic Syndr, 7, 681-694 (1994) |
| [43] | Keller, U., Nutritional laboratory markers in malnutrition, J Clin Med, 8, 775 (2019) · doi:10.3390/jcm8060775 |
| [44] | Thuppal, SV; Jun, S.; Cowan, A., The nutritional status of HIV-infected US adults, Curr Dev Nutr, 1 (2017) · doi:10.3945/cdn.117.001636 |
| [45] | Sarro, Y.; Tounkara, A.; Tangara, E., Serum protein electrophoresis: any role in monitoring for antiretroviral therapy?, Afr Health Sci, 10, 138-143 (2010) |
| [46] | Nozarian, Z.; Mehrtash, V.; Abdollahi, A., Serum protein electrophoresis pattern in patients living with HIV: frequency of possible abnormalities in Iranian patients, Iran J Microbiol, 11, 440 (2019) |
| [47] | Zemlin, AE; Ipp, H.; Maleka, S., Serum protein electrophoresis patterns in human immunodeficiency virus-infected individuals not on antiretroviral treatment, Ann Clin Biochem, 52, 346-351 (2015) · doi:10.1177/0004563214565824 |
| [48] | McGowan, JP; Shah, SS; Small, CB, Relationship of serum immunoglobulin and IgG subclass levels to race, ethnicity and behavioral characteristics in HIV infection, Med Sci Monit, 12, CR11-CR16 (2006) |
| [49] | Baral, S.; Antia, R.; Dixit, NM, A dynamical motif comprising the interactions between antigens and CD8 T cells may underlie the outcomes of viral infections, Proc Natl Acad Sci, 116, 17393-17398 (2019) · doi:10.1073/pnas.1902178116 |
| [50] | Conway, JM; Perelson, AS, Post-treatment control of HIV infection, Proc Natl Acad Sci, 112, 5467-5472 (2015) · doi:10.1073/pnas.1419162112 |
| [51] | Haase, AT, Perils at mucosal front lines for HIV and SIV and their hosts, Nat Rev Immunol, 5, 783-792 (2005) · doi:10.1038/nri1706 |
| [52] | Sreejithku, V, Ghods, K, Bandara, T, et al. Selecting the best model for complex interplay between HIV and nutrition; 2023. |
| [53] | Thieme, HR, Mathematics in population biology, Vol. 1 (2018), Princeton, NJ: Princeton University Press |
| [54] | Martcheva, M., An introduction to mathematical epidemiology, Vol. 61 (2015), New York (NY): Springer · Zbl 1333.92006 |
| [55] | Van den Driessche, P.; Watmough, J., Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math Biosci, 180, 29-48 (2002) · Zbl 1015.92036 · doi:10.1016/S0025-5564(02)00108-6 |
| [56] | Castillo-Chavez, C.; Song, B., Dynamical models of tuberculosis and their applications, Math Biosci Eng, 1, 361-404 (2004) · Zbl 1060.92041 · doi:10.3934/mbe.2004.1.361 |
| [57] | Martcheva, M., Methods for deriving necessary and sufficient conditions for backward bifurcation, J Biol Dyn, 13, 538-566 (2019) · Zbl 1447.92449 · doi:10.1080/17513758.2019.1647359 |
| [58] | University of Rochester Medical Center. Encyclopedia (Accessed on March 27, 2023). https://www.urmc.rochester.edu/encyclopedia/. Online Version. |
| [59] | Sharma, R, Sharma, S. Physiology, blood volume; 2018. |
| [60] | Healthline. Protein intake – how much protein should you eat per day? (Accessed on March 27, 2023). https://www.healthline.com/nutrition/how-much-protein-per-day. Online Version. |
| [61] | WebMD. HIV & AIDS resource center. (Accessed on March 27, 2023). https://www.webmd.com/hiv-aids/cd4-count-what-does-it-mean. Online Version. |
| [62] | Stafford, MA; Corey, L.; Cao, Y., Modeling plasma virus concentration during primary HIV infection, J Theor Biol, 203, 285-301 (2000) · doi:10.1006/jtbi.2000.1076 |
| [63] | POZ. Understanding your lab work (blood tests). (Accessed on March 27, 2023). https://www.poz.com/basics/hiv-basics/understanding-lab-work-blood-tests. Online Version. |
| [64] | Fidler, S.; Fox, J., Primary HIV infection: a medical and public health emergency requiring rapid specialist management, Clin Med, 16, 180-183 (2016) · doi:10.7861/clinmedicine.16-2-180 |
| [65] | McMichael, AJ; Borrow, P.; Tomaras, GD, The immune response during acute HIV-1 infection: clues for vaccine development, Nat Rev Immunol, 10, 11-23 (2010) · doi:10.1038/nri2674 |
| [66] | Wodarz, D.; Nowak, MA, Immune responses and viral phenotype: do replication rate and cytopathogenicity influence virus load?, Comput Math Methods Med, 2, 113-127 (2000) · Zbl 0943.92024 |
| [67] | Antonio, J.; Ellerbroek, A.; Silver, T., A high protein diet has no harmful effects: a one-year crossover study in resistance-trained males, J Nutr Metab, 2016 (2016) · doi:10.1155/2016/9104792 |
| [68] | Levitt, DG; Levitt, MD, Human serum albumin homeostasis: a new look at the roles of synthesis, catabolism, renal and gastrointestinal excretion, and the clinical value of serum albumin measurements, Int J Gen Med, 9, 229-255 (2016) · doi:10.2147/IJGM |
| [69] | Lugada, E.; Mermin, J.; Asjo, B., Immunoglobulin levels amongst persons with and without human immunodeficiency virus type 1 infection in Uganda and Norway, Scand J Immunol, 59, 203-208 (2004) · doi:10.1111/sji.2004.59.issue-2 |
| [70] | Butorov, EV, Impact of high protein intake on viral load and hematological parameters in HIV-infected patients, Curr HIV Res, 15, 345-354 (2017) · doi:10.2174/1570162X15666171002121209 |
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