| Literature DB >> 32911778 |
Sebastià Galmés1,2,3,4, Francisca Serra1,2,3,4, Andreu Palou1,2,3.
Abstract
The pandemic caused by the new coronavirus has caused shock waves in many countries, producing a global health crisis worldwide. Lack of knowledge of the biological mechanisms of viruses, plus the absence of effective treatments against the disease (COVID-19) and/or vaccines have pulled factors that can compromise the proper functioning of the immune system to fight against infectious diseases into the spotlight. The optimal status of specific nutrients is considered crucial to keeping immune components within their normal activity, helping to avoid and overcome infections. Specifically, the European Food Safety Authority (EFSA) evaluated and deems six vitamins (D, A, C, Folate, B6, B12) and four minerals (zinc, iron, copper and selenium) to be essential for the normal functioning of the immune system, due to the scientific evidence collected so far. In this report, an update on the evidence of the contribution of nutritional factors as immune-enhancing aspects, factors that could reduce their bioavailability, and the role of the optimal status of these nutrients within the COVID-19 pandemic context was carried out. First, a non-systematic review of the current state of knowledge regarding the impact of an optimal nutritional status of these nutrients on the proper functioning of the immune system as well as their potential role in COVID-19 prevention/treatment was carried out by searching for available scientific evidence in PubMed and LitCovid databases. Second, a compilation from published sources and an analysis of nutritional data from 10 European countries was performed, and the relationship between country nutritional status and epidemiological COVID-19 data (available in the Worldometers database) was evaluated following an ecological study design. Furthermore, the potential effect of genetics was considered through the selection of genetic variants previously identified in Genome-Wide Association studies (GWAs) as influencing the nutritional status of these 10 considered nutrients. Therefore, access to genetic information in accessible databases (1000genomes, by Ensembl) of individuals from European populations enabled an approximation that countries might present a greater risk of suboptimal status of the nutrients studied. Results from the review approach show the importance of maintaining a correct nutritional status of these 10 nutrients analyzed for the health of the immune system, highlighting the importance of Vitamin D and iron in the context of COVID-19. Besides, the ecological study demonstrates that intake levels of relevant micronutrients-especially Vitamins D, C, B12, and iron-are inversely associated with higher COVID-19 incidence and/or mortality, particularly in populations genetically predisposed to show lower micronutrient status. In conclusion, nutrigenetic data provided by joint assessment of 10 essential nutrients for the functioning of the immune system and of the genetic factors that can limit their bioavailability can be a fundamental tool to help strengthen the immune system of individuals and prepare populations to fight against infectious diseases such as COVID-19.Entities:
Keywords: COVID-19; SARS-CoV-2; epidemiology; genetic variant; immunity; micronutrient; nutrigenetics
Mesh:
Substances:
Year: 2020 PMID: 32911778 PMCID: PMC7551697 DOI: 10.3390/nu12092738
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
List of nutrients with contribution to the functioning of the immune system endorsed by the European Food Safety Authority (EFSA); Dietary Reference Values (DRVs); genetic factors that affect nutritional status and risk allele that predisposes to lower status; population in which the association was proven; and bibliographic citation of the genetic association paper. Dietary Reference Intakes were consulted on EFSA DRV Finder interactive tool [15]. Zinc PRIs * co-depend on Phytate intake levels and are expressed here as the mean of 300, 600, 900, and 1200 mg/day PRI values.
| Micronutrient | EFSA DRVs | SNP Affecting Status (Gene) | Associated Trait | Risk Allele | Population Based Discovery | Cite |
|---|---|---|---|---|---|---|
| Vitamin D | AI: 15 μg/day | rs7041 (GC) | ↑ vitamin D-binding protein | C | 1380 European | [ |
| rs1155563 (GC) | ↓ Serum Vitamin D | C | 761 European | [ | ||
| rs12785878 (NADSYN1) | Vitamin D Deficiency | C | 16125 European | [ | ||
| Vitamin A | PRI: 650 (w)/50 (m) μg RE/day | rs6564851 (BCO1) | ↓ Serum Carotenoids | T | 1191 European | [ |
| Vitamin C | PRI: 95 (w)/110 (m) mg/day | rs33972313 | ↓ Serum Vitamin C | A | 9234 European | [ |
| Folate | PRI: 330 μg DFE/day | rs1801133 (MTHFR) | ↓ Folic acid in red blood cells | T | 2232 European | [ |
| Vitamin B6 | AI: 1.6 (w)/1.7 (m) mg/day | rs4654748 (NBPF3) | ↓ Serum vitamin B6 | C | 2934 European | [ |
| Vitamin B12 | PRI: 4 μg/day | rs11254363 (CUBN) | ↓ Serum vitamin B12 | A | 2934 European | [ |
| rs526934 (TCN1) | ↓ Serum vitamin B12 | G | 2934 European | |||
| rs602662 (FUT2) | ↓ Serum vitamin B12 | G | 2934 European | |||
| ↓ Serum vitamin B12 | G | 1001 South Asian | [ | |||
| Zinc | PRI*: 10.1 (w)/12.9 (m) mg/day | rs2120019 (PPCDC) | ↓ Serum Zinc | C | 2603 European | [ |
| rs1532423 (CA1) | ↓ Serum Zinc | C | 2603 European | |||
| rs4826508 (NBDY) | ↓ Serum Zinc | C | 2603 European | |||
| PRI: 11 (w + m)/16 (w#) mg/day | rs1800562 (HFE) | ↑ Unsaturated iron-binding capacity | G | 679 European | [ | |
| ↑ Total iron-binding capacity | G | 679 European | ||||
| ↓ Transferrin saturation | G | 23986 European | [ | |||
| ↑ Transferrin levels | G | 23986 European | ||||
| ↓ Serum iron | G | 23986 European | ||||
| ↓ Ferritin levels | G | 23986 European | ||||
| ↓ Hemoglobin | G | 4818 European | ||||
| rs1799945 (HFE) | ↓ Transferrin saturation | C | 12375 Hispanic or Latin American | [ | ||
| ↓ Serum iron | C | 5633 European | [ | |||
| ↓ Serum iron | C | 12375 Hispanic or Latin American | [ | |||
| ↓ Hemoglobin | C | |||||
| rs3811647 (TF) | ↓ Unsaturated iron-binding capacity | G | 679 European | [ | ||
| ↓ Total iron-binding capacity | G | 679 European | ||||
| ↓ Transferrin | G | 5633 European | [ | |||
| rs7385804 (TFR2) | ↓ Serum iron | C | 23986 European | [ | ||
|
| AI: 1.3 (w)/1.6 (m) mg/day | rs2769264 (SELENBP1) | ↓ Serum copper | T | 2603 European | [ |
| rs1175550 (SMIM1) | ↓ Serum copper | A | 2603 European | [ | ||
|
| AI: 70 µg/day | rs891684 (SLC39A11) | ↓ Serum Selenium | A | 1203 European | [ |
| rs17823744 (DMGDH) | ↓ Toenail Selenium | A | 4162 European |
Abbreviations: SNP (Single Nucleotide Polymorphism); AI (Average Intake); PRI (Population Reference Intake); UL (Tolerable Upper Intake Level); RE (Retinol Equivalents); ND (Not defined, as data were inadequate to derive a value); DFE (Dietary Folate Equivalent); * (w) and (m) mean recommendations for women and males, respectively; and (w#) means for premenopausal women; ** Variant influence on vitamin D serum levels not been confirmed in European ethnic.
Figure 1Genetic influence on the micronutrient intake-plasma level relationship. Abbreviations: PRI (Population Reference Intake); DRV (Dietary Reference Values); Med (medium genetic risk).
COVID-19 epidemiological parameters and Vitamin and Mineral population intake levels (% vs. requirements) per country vs. recommended intake values.
| COVID-19 Parameters | Vitamin Intake | Mineral Intake | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
| I | M | D% | D | A | C | Folate | B6 | B12 | Zn | Fe | Cu | Se |
|
| 595.0 | 593.0 | 10.0 | 14.1 | 77.2 | 109.9 | 74.9 | 112.2 | 128.1 | 81.2 | 110.9 | 115.4 | 108.2 |
|
| 481.6 | 786.0 | 16.3 | 25.0 | 110.0 | 87.8 | 63.0 | ND | 111.3 | 112.4 | 94.5 | ND | ND |
|
| 373.5 | 529.0 | 14.2 | 17.0 | 160.0 | 112.5 | 91.1 | 117.9 | 143.8 | 108.2 | 99.5 | 96.5 | 59.6 |
|
| 363.2 | 513.0 | 14.1 | 21.0 | 162.5 | 75.3 | 78.1 | 117.8 | 149.6 | 79.4 | 86.9 | 70.2 | 64.3 |
|
| 288.5 | 122.0 | 4.2 | 23.9 | 210.0 | 119.4 | 85.8 | 125.8 | 166.9 | 95.9 | 126.1 | ND | ND |
|
| 275.7 | 433.0 | 15.7 | 15.7 | 150.0 | 86.9 | 84.0 | ND | 130.8 | 101.7 | 93.3 | 90.8 | 71.2 |
|
| 258.3 | 334.0 | 12.9 | 27.6 | 144.9 | 86.6 | 68.5 | 99.7 | 119.1 | 98.2 | 93.9 | 77.0 | 64.2 |
|
| 211.9 | 97.0 | 4.6 | 23.5 | 256.0 | 143.9 | 83.9 | 131.4 | 149.4 | 111.2 | 129.6 | 157.8 | ND |
|
| 190.7 | 95.0 | 5.0 | 22.5 | 152.0 | 103.2 | 92.8 | 86.2 | 130.6 | 99.1 | 89.2 | ND | 53.2 |
|
| 115.5 | 54.0 | 4.7 | 62.7 | 110.0 | 99.8 | 72.5 | 110.3 | 160.0 | 114.3 | 109.5 | 95.0 | 86.4 |
Abbreviations: I (Incidence); M (Mortality rate); D% (Death% vs. cases); Zn (Zinc); Fe (iron); Cu (Copper); Se (Selenium); and ND (no data shown for this item).
Figure 2Population intake of relevant immune system Vitamins (A) and Minerals (B) in European countries and their relationship with COVID-19 Incidence (number of COVID-19 cases per 100 k people) and Deaths (mortality rate per 1 M people). Nutritional data are shown as z-score of population with vitamin or mineral requirements fulfilled and referenced to the whole data of 10 countries analyzed. Negative values indicate that the country is generally below the general median of the percentage coverage of the population nutrition requirements of the countries analyzed, whereas positive values indicate that the country population% with covered requirements is above the general median.
Figure 3Pearson correlogram of COVID-19 epidemiological parameters: Incidence, Deaths (mortality rate), and Deaths% (relative mortality rate), and immune system micronutrient suboptimal intake. The size and color intensity of the spot indicate the degree of correlation between two parameters. The color red indicates a positive correlation, whereas blue indicates a negative correlation. Pearson correlation p-values (p) are indicated below each dot and p < 0.1 are highlighted in bold.
Genetic risk of lower status of 10 relevant Vitamins and Minerals for proper immune system function. Population% at low, medium, and high risk of low micronutrient status are shown calculated from individual SNP data for European Population (available in 1000genomes database) as described in the Materials and Methods. Statistical assessment of differences in population% at risk ranges for each country was carried out by Chi-Square with Finland used as reference country. p-values in bold means p < 0.05.
| Finnish | British | Italian | Spanish | |
|---|---|---|---|---|
| Vitamin D | ||||
| Low | 6.1 | 16.5 | 19.6 | 10.3 |
| Medium | 77.8 | 75.8 | 75.7 | 77.6 |
| High | 16.2 | 7.7 | 4.7 | 12.1 |
| χ2 ( | Ref. |
|
| 0.217 |
| Vitamin A | ||||
| Low | 31.3 | 28.6 | 13.1 | 18.7 |
| Medium | 56.6 | 48.4 | 54.2 | 46.7 |
| High | 12.1 | 23.1 | 32.7 | 34.6 |
| χ2 ( | Ref. |
|
|
|
| Vitamin C | ||||
| Low | 96.0 | 90.1 | 95.3 | 99.1 |
| Medium | 4.0 | 7.7 | 4.7 | 0.9 |
| High | 0.0 | 2.2 | 0.0 | 0.0 |
| χ2 ( | Ref. | 0.146 | 0.764 |
|
| Folate | ||||
| Low | 51.5 | 44.0 | 30.8 | 28.0 |
| Medium | 42.4 | 47.3 | 44.9 | 55.1 |
| High | 6.1 | 8.8 | 24.3 | 16.8 |
| χ2 ( | Ref. | 0.267 |
|
|
| Vitamin B6 | ||||
| Low | 21.2 | 18.7 | 29.0 | 23.4 |
| Medium | 54.5 | 51.6 | 50.5 | 46.7 |
| High | 24.2 | 29.7 | 20.6 | 29.9 |
| χ2 ( | Ref. | 0.473 | 0.216 | 0.275 |
| Vitamin B12 | ||||
| Low | 5.1 | 4.4 | 15.9 | 13.1 |
| Medium | 80.8 | 86.8 | 78.5 | 77.6 |
| High | 14.1 | 8.8 | 5.6 | 9.3 |
| χ2 ( | Ref. | 0.152 |
|
|
| Zinc | ||||
| Low | 29.3 | 31.9 | 21.5 | 21.5 |
| Medium | 62.6 | 59.3 | 55.1 | 59.8 |
| High | 8.1 | 8.8 | 23.4 | 18.7 |
| χ2 ( | Ref. | 0.800 |
|
|
| iron | ||||
| Low | 7.1 | 17.6 | 17.8 | 19.6 |
| Medium | 55.6 | 69.2 | 61.7 | 59.8 |
| High | 37.4 | 13.2 | 20.6 | 20.6 |
| χ2 ( | Ref. |
|
|
|
| Copper | ||||
| Low | 17.2 | 15.4 | 19.6 | 15.9 |
| Medium | 38.4 | 45.1 | 38.3 | 44.9 |
| High | 44.4 | 39.6 | 42.1 | 39.3 |
| χ2 ( | Ref. | 0.407 | 0.801 | 0.422 |
| Selenium | ||||
| Low | 26.3 | 20.9 | 24.3 | 17.8 |
| Medium | 69.7 | 67.0 | 69.2 | 73.8 |
| High | 4.0 | 12.1 | 6.5 | 8.4 |
| χ2 ( | Ref. |
| 0.571 |
|