| Literature DB >> 30687894 |
Martyna Pajewska-Szmyt1,2, Elena Sinkiewicz-Darol3,4, Renata Gadzała-Kopciuch5,6.
Abstract
Breastfeeding is a gold standard of neonate nutrition because human milk contains a lot of essential compounds crucial for proper development of a child. However, milk is also a biofluid which can contain environmental pollution, which can have effects on immune system and consequently on the various body organs. Polychlorinated biphenyls are organic pollutants which have been detected in human milk. They have lipophilic properties, so they can penetrate to fatty milk and ultimately to neonate digestive track. Another problem of interest is the presence in milk of heavy metals-arsenic, lead, cadmium, and mercury-as these compounds can lead to disorders in production of cytokines, which are important immunomodulators. The toxicants cause stimulation or suppression of this compounds. This can lead to health problems in children as allergy, disorders in the endocrine system, end even neurodevelopment delay and disorder. Consequently, correlations between pollutants and bioactive components in milk should be investigated. This article provides an overview of environmental pollutants found in human milk as well as of the consequences of cytokine disorder correlated with presence of heavy metals. Graphical abstract.Entities:
Keywords: Breast milk; Cytokine; Heavy metals; Polychlorinated biphenyls
Mesh:
Substances:
Year: 2019 PMID: 30687894 PMCID: PMC6447517 DOI: 10.1007/s11356-019-04141-1
Source DB: PubMed Journal: Environ Sci Pollut Res Int ISSN: 0944-1344 Impact factor: 4.223
Fig. 1Mechanism of cytokine production and action
Anthropogenic pollutants and examples of toxic effects
| Class of compounds | Examples of toxic effects | Literature |
|---|---|---|
| Pesticides | Delayed effects on central nervous system functioning | Ennaceur et al. |
| Disruption of endocrine system (hormonal imbalance) | Eskenazi et al. | |
| Increased risk of cancer | Ribas-Fitό et al. | |
| Genotoxic effects | Yamazaki et al. | |
| Abnormal behavior | ||
| Growth retardation | ||
| Organochlorines | Dermatitis | Gascon et al. |
| Disorders in the endocrine and reproductive system | Hansen et al. | |
| Neurological and behavior problems | Passatore et al. | |
| Metabolic diseases (diabetes, obesity) | Tang-Péronard et al. | |
| Reduced immune response | Taylor et al. | |
| Increased risk of asthma | ||
| Bisphenols | Neuroendocrine disorders (e.g., precocious puberty) | Braun et al. |
| Obsesity | Rochester | |
| Diabetes | ||
| Anxiety | ||
| Hyperactivity | ||
| Parabens | Endocrine related disorders: (e.g., obesity, thyroid gland disorders, female/male reproduction issues) | Nowak et al. |
| Phtalates | Adverse neurodevelopmental effects (e.g., autism spectrum disorders) | Benjamin et al. |
| Reproductive toxicity (testicular cancer, male infertility, reproductive abnormalities) | Katsikantami et al. | |
| Asthma and allergic symptoms, overweight, and obesity | ||
| Brominated flame retardants | Endocrine disruption | Műller et al. |
| Neurodevelopment and behavioral disorders | ||
| Potentially increased risk of cancer | ||
| Perofluoroalkyl substances | Delayed effects on development | Granum et al. |
| Decreased antibody response | ||
| *Heavy metals: | Immunotoxicity (weakening of the immune system) | Grandjean and Landrigan |
| Toxic effect on neurodevelopment | Samiee et al. | |
| Development of autoimmune diseases (i.e., allergies or atropy) | ||
| Clinical disorders (e.g., anemia, cancer, reproductive disorders, depression |
*One of the main topics described on this paper
Fig. 2Composition of human milk
Fig. 3Structure of polychlorinated biphenyls
Fig. 4Sources of exposition and bioaccumulation of PCBs
Monitoring of organic pollutants—PCBs in human milk
| Number of tested PCBs | Country | Number of mothers | Years | Concentrations (ng/g lipid) | Comments | Reference |
|---|---|---|---|---|---|---|
| Di-ortho PCBs | Sweden | 413 | 1996–2010 | ∑3 | The higher concentration of PCBs, the higher weight of the baby after birth. | (Lignell et al. |
| 35 PCBs | Czech Republic | 90 | 1999–2000 | ∑35 | High concentrations found in milk from mothers who live in industrial areas, PCB concentrations increased with mother’s age. | (Černá et al. |
| 33 PCBs | Spain | 20 | 2012 | ∑33 | Concentration of POPs was higher in milk from women living in urban areas than in industrial areas. The author suggests this may be caused by urban women eating a larger number of fish dishes. | (Schuhmacher et al. |
| 19 PCBs | Hungary | 22 | 2012 | ∑19 | PCB concentration decreased during lactation. The biggest fall occurred between day 5 and 12. | (Vigh et al. |
| 12 PCBs | Slovakia | 33 | 2006–2007 | ∑12 | In milk from women who live in industrial areas, concentration of POPs exceeded TDI limit (WHO). | (Chovancová et al. |
| 8 PCBs | Tunisia | 36 | 2010 | ∑8 | PCB concentration was positively correlated with the age of mothers, who gave birth for the first time Mothers with second-born and following children - no correlation. | (Hassine et al. |
| 18 PCBs | China | 60 | 2007 | ∑12 dl-PCBs | Body burden of PCBs was positively correlated with the period of residence in Shenzhen and fish consumption. | (Deng et al. |
| 7 PCBs | Ghana | 128 | 2014–2016 | ∑7indicate PCBs | In an electronic waste hot spot area, mean concentration of PCB was much higher than in non-spot area (4.43/0.03) | Asamoah et al. |
Example of study where cytokine were detected in milk and correlated with mastitis or allergy mother’s problem
| Diseases | Samples | Investigated cytokines* | Comments | Literature |
|---|---|---|---|---|
| Clinical mastitis | Selected pro-inflammatory cytokines (IL-6, IL-1β, TNF-α) | • TNF-α were evaluated in 6 from 8 samples, whereas IL-6 5/8 and Il = 1β 3/8. | Buescher and Hair | |
| IL-61 | • Level of IL-6 is higher in mastitic milk than milk from healthy mothers. If the women had a systemic symptoms, these differences are more significant. | Mizuno et al. | ||
| Subclinical mastitis | 25 cytokines IL-2, IL-2R, IL12p40/70, IL-15, IFN-α, IFN-γ, MIG, IP-10, IL-4,IL-5, IL-13,IL-7, IL-17, GMCSF, IL-10, EPO, IL-1RA, TNF-α, IL-6, IL-8, IL-1β, RANTES, EOTAXIN2 | • Factors associated with inflammation (e.g., TNF-α, IL-6, Il-8, IL-17) were significantly increased in SCM samples. | Tuaillon et al. | |
| IL-1β | • IL-8 and TNF-α where higher in SCM mothers (most notably in transitional milk) | Li et al. | ||
| Allergy | Colostrum milk (3 days after delivery) | IL-4, IL-6, IL-8, IL-10, _IL-12, IL-13, IFN-γ, TGF-β1, eotaxain, GRO-α, RANTES, TNF-α, EGF1 | • Cytokines present in colostrum with high quantities (mediana > 100 pg/mL): IL-4, IL-5, IL-10, IL-13, INF-γ, TGF-β, TNF-α, MCP-1, GRO-α, EGF | Zizka et al. |
| 9 healthy mothers | IL-2, IL-4, IL-8, IL-10, IL-13, IFN-γ, TGF-β1, EGF1,4 | • Expression of IL-4, IL-13, and EGF was higher and levels of IFN-γ decreased in the colostral cells of allergic mothers compared to healthy. | Hrdý et al. | |
| 13 allergic mothers | IL-10, TGF-β11 | • TGF-β concentration had a significant difference between colostrum and mature milk in milk from allergy mothers. | Rigotti et al. | |
| 21 allergic | IL-4, IL-5,IL-6,IL-10, IL-13. IFN-γ, TGF-β1 | • The tendency to higher concentration of IL-4 and IL-10 in milk from allergy mothers | Prokesová et al. |
*Detected by following method:
1ELISA
2Multiplex microbeads assay
3MILLIPLEX MAP Human High Sensitivity Cytokine panel
4PCR
Fig. 5Production and interactions of cytokines
Fig. 6Metabolism of arsenic
Arsenic in human milk
| Country | Lactation day (no. of samples) | Mean*/geometric mean**/(range μg/L) | Comments | Reference |
|---|---|---|---|---|
| Germany | Day 2 (18) | 0.20** (0.15–1.1) | 187 samples tested, in 154 As was below LOD (0.3 μg/L). | (Sternowsky et al. |
| Day 5 (93) | 0.21 (0.15–2.5) | |||
| Day 15 (18) | 0.16 (0.15–0.8) | |||
| Day 30 (11) | 0.54 (0.15–2.8) | |||
| Day 45 (11) | 0.19 (0.15–2.0) | |||
| Day 60 (12) | 0.20 (0.15–0.9) | |||
| Day 75 (11) | 0.16 (0.15–0.3) | |||
| Day 90 (13) | 0.17 (0.15–0.8) | |||
| Bangladesh | Month 1 (29) | 1.12* (0.5–8.90) | In mother’s milk, the content of arsenic compared to the mother’s and baby’s urine was low (e.g., mean As content in milk:child urine:mother urine (μg/L) 1.12:157.8:18.1). | (Islam et al. |
| Month 6 (25) | 0.78 (0.5–2.32) | |||
| Month 9 (19) | 0.70 (0.5–1.68) | |||
| Chile (Arica, Santiago) | Arica (24), mine tailing deposition | 0.36** (0.04–2.82) | In drinking water, concentration of arsenic was higher than in milk; as a result, children who are breastfed are less exposed. | (Castro et al. |
| Santiago (11), control area | 0.23** (0.08–0.61) | |||
| Taiwan | Days 1–4 | 1.50 | As lactation period progressed, the amount of arsenic in milk was decreasing. | (Chao et al. |
| Days 5–10 | 0.68 | |||
| Days 30–35 | 0.27 | |||
| Days 60–65 | 0.16 | |||
| Sweden | Days 14–21 (60) | 0.55* (0.041–4.6) | – | (Björklund et al. |
| Japan | Month 3 (9) | (0.18–4.20) | – | (Sakamoto et al. |
| Cyprus | 50 samples | 0.73* (0.03–1.97) | No significant correlation between moldy food consumption or the residential area | (Kunter et al. |
| Lebanon | 74 nursing mothers (3–8 weeks of delivery) | *2.36 (0.08–11.32) | Arsenic was found in 63.51% of samples and this contamination was associated with cereal and fish intake. | (Bassil et al. |
Fig. 7Mercury accumulation
Mercury in milk
| Country | Lactation day (no. of samples) | Mean*/geometric mean**/(range μg/L) | Comments | Reference |
|---|---|---|---|---|
| Germany | Days 2–7 (70) | (0.2–6.86) | Presence of mercury was linked with the number of amalgam fillings the mother had. The average content was below 0.2 μg/L; when mother had 1–4 fillings, 0.57 μg/L; if more than 7, the content was 2.11 μg/L. | (Drasch et al. |
| Week 1 (116) | 1.37* (< 0.25–20.3) | Number of amalgam fillings in mother’s teeth and eating habits (fish diet) influence mercury concentration in milk. | (Drexler and Schaller., 1998) | |
| Month 2 (84) | 0.64 (0.25–11.7) | |||
| Indonesia | Any day (46) | 8.11* (< 1.0–149.60) | Area of residence where mercury is present may be a source of hazard. | (Bose-O’Reilly et al. |
| Spain (Madrid) | Week 3 (100) | 0.53** (0.03–2.63) | Concentration of Hg increased with number of amalgam fillings and amount of consumed fish and seafood. | (García-Esquinas et al. |
| Japan | Month 3 (9) | (0.28–0.77) | – | (Sakamoto et al. |
| Brazil (Brasilia) | Σ(147) | In the first three months after birth, mercury content in milk was not correlated with the amount of fish consumed by the mother. | (Cunha et al. | |
| Day 15 | THg 6.66* | |||
| Day 30 | 6.03 | |||
| Day 45 | 6.02 | |||
| Day 60 | 5.31 | |||
| Day 74 | 6.01 | |||
| Day 75 | 6.52 | |||
| Day 76 | 7.29 | |||
| Day 90 | 7.89 | |||
| Cyprus | 50 samples | 0 (0–0.01) | No significant correlation between moldy food consumption or the residential area | (Kunter et al. |
| Brazil | 224 samples | THg 2.56* (< 0.76–8.40) | The limitation of this research was lack of information about time of sample collection, lack of food consumption information, or the number of amalgams of mothers. | (Rebelo et al. |
| Korea | 207 samples | 0.94* (0.08–5.66) | Mercury concentration was higher in milk form primipara mothers, and women over 30 years age, which are living in a big city. | (Park et al. |
| Day 15 | 1.19 | |||
| Day 30 | 0.79 |
Fig. 8Lead absorption, distribution, and excretion
Fig. 9Absorption, distribution, and metabolism of cadmium
Cadmium and lead in milk
| Country | Lactation day (no. of samples) | Mean*/geometric mean**/(range μg/L) | Comments | Reference |
|---|---|---|---|---|
| Croatia | Day 4 | Pb 2.4–10 | Smoking is a source of lead and cadmium intake. | (Grzunov Letinić et al., |
| Cd 0.6–1.4 | ||||
| Spain | Week 3 (100) | Pb 15.65 **(12.92–18.72) | Concentration of lead increased with the amount of potatoes consumed. | (García-Esquinas et al. |
| Cd 1.31* (1.15–1.48) | ||||
| Greece | Day 3 (180) | Pb 0.48* | Women from urban areas were more exposed. | (Leotsinidis et al. |
| Cd 0.19* | ||||
| Poland | 323 milk samples | Pb 6.33* | Higher concentrations of heavy metals were determined in milk from smokers and older women (aged 30+). | (Winiarska-Mleczan |
| Cd 2.11* | ||||
| Japan | Month 3 (9) | Pb (0.18–4.20) | – | Sakamoto et al. |
| Cd (0.40–1.80) | ||||
| Cyprus | 50 samples | Pb 1.19* (0–4.91) | No significant correlation between moldy food consumption or the residential area | Kunter et al. |
| Cd 0.45* (0.12–0.80) | ||||
| Lebanon | 74 samples | Pb 18.17* (1.38–62.61) | Cadmium was detected in 40.54% of samples and was significantly associated random smoke exposure. | Bassil et al. |
| Korea | 207 samples | Pb 8.79* | The highest level of lead was detected in breastmilk sample from a residential city in both sample dates (15 and 30 days) | Park et al. |
Ingredients of human milk and their main functions
| Ingredient | Functions |
|---|---|
| Proteins | • Nutritional (binding of essential ingredients, absorption through the intestinal mucosa) |
| Non-protein nitrogen | • Key role in cellular processes, i.e., changing enzymatic activity |
| Lipids | • The largest source of energy |
| Oligosaccharides | • Supporting growth of beneficial organisms (probiotics) |