Introduction
Macrophage migration inhibitory factor (MIF) is a
multifunctional cytokine with important functions in the regulation
of the immune system. It is primarily produced by the pituitary
gland to counteract the immunosuppressive effects of
glucocorticoids and is also secreted by diverse cell types,
including immune cells (B and T lymphocytes, monocytes and
macrophages), endothelial cells, adipocytes, smooth muscle cells,
red blood cells, pancreatic islet β-cells, specialized cells in the
nervous system and platelets, thus having autocrine, paracrine and
endocrine functions (1-3).
Physiologically, MIF has been shown to regulate the immune response
and microbial clearance, to participate in cell regeneration and
wound healing, to regulate insulin secretion, and to exert neuro-
and cardio-protective effects, among others. The best characterized
role of MIF involves regulation of innate immunity; it is
constitutively expressed and stored in most immune cells, including
macrophages, and is released in response to inflammatory factors
such as lipopolysaccharide, exotoxins, hypoxia, angiotensin II,
glucose, insulin, ultraviolet B irradiation and glucocorticoids
(1,4,5). MIF
thus acts as a first responder cytokine with the ability to promote
other inflammatory events. MIF can also reduce the effects of
glucocorticoids, which normally reduce inflammation, therefore
promoting inflammation under stressful conditions (4). After binding to its receptor CD74/44,
MIF induces the expression of pro-inflammatory cytokines, such as
tumor necrosis factor, IL-6, interferon-γ and IL-1β, and
upregulates Toll-like receptor 4, facilitating bacterial
recognition (1), or elicits
chemotactic responses by binding to CXCR2/4/7, influencing
leukocyte recruitment (6). Upon
receptor binding, MIF leads to the activation of Src kinase and
MAPK/ERK or PI3K/AKT pathways, thus signaling cell proliferation,
inflammation, migration, survival and the secretion of angiogenic
factors (1,3,4).
MIF has also been reported to be involved in
pathological conditions, and is elevated in inflammatory and
autoimmune diseases, including rheumatoid arthritis, vitiligo,
multiple sclerosis, psoriasis and lupus; in infectious diseases,
such as periodontitis, dengue, tuberculosis and sepsis; in
diabetes; and in some types of cancer, such as esophageal squamous
cell carcinoma, gastric and breast cancer. In addition,
polymorphisms associated with an increased regulation of MIF
expression have been associated with increased susceptibility to
and severity of inflammatory and autoimmune diseases, as well as
prostate and gastric cancer (3,5).
Notably, MIF has recently been identified as an important mediator
in type 2 diabetes mellitus pathogenesis and in obesity (2,7), where
high MIF plasma levels have been shown to regulate adipocyte lipid
storage, increasing plasma triacylglycerol concentration (2).
Chronic inflammation is defined as an activation of
the immune system, triggered by immunogenic compounds,
lifestyle-related or environmental factors, which lead to a
low-grade, chronic inflammation lacking the typical symptoms of
acute inflammation (8). This state
has been reported to be associated with states such as aging and in
the development of diverse chronic diseases, including cancer and
cardiovascular disease (9). Causes
of this chronic inflammatory state include chronic infections,
cellular senescence and obesity (9).
Obesity has been redefined as a complex systemic
disease, thus transcending caloric imbalance, which is driven by
metabolic, neuroendocrine, immune and epigenetic dysregulation
(10). Clinical obesity is defined
as a chronic, systemic illness caused by excess adiposity and
characterized by alterations in tissue or organ function,
alterations in the individual, or a combination thereof (11). The prevalence of obesity has
markedly increased in recent decades, and estimates suggest that
~50% of all adults in the world are currently overweight or obese
(8). This high prevalence of
obesity poses a global threat to human health, due to its
association with metabolic disorders, including insulin resistance
and diabetes, metabolic-associated fatty liver disease,
atherosclerosis and an increased risk of developing dementia
(8). Globally, obesity is slightly
more common in women than in men (12), and women are more likely to be
affected by obesity due to its effects on endocrine dysfunction,
which is related to menstrual irregularities, infertility,
polycystic ovary syndrome [PCOS; which is now referred to as
polyendocrine metabolic ovarian syndrome (PMOS)], and complications
in pregnancy outcomes (13).
Moreover, obesity in women increases the risk of developing heart
disease, diabetes and breast cancer (12), underscoring the need to implement
prophylactic and therapeutic measures to tackle obesity and prevent
the development of its associated alterations.
The accumulation of lipids in subcutaneous fat
depots, visceral adipose tissue (VAT), liver, muscle and other body
sites promotes the release of fatty acids and pro-inflammatory
cytokines, inducing a systemic, low-grade, subclinical chronic
inflammatory state (14). The white
adipose tissue (WAT) is normally populated by immune cells,
including macrophages, dendritic cells (DCs), type II innate
lymphoid cells (ILC2s), eosinophils, T helper (Th)2 cells and
regulatory T cells, which undergo reprogramming during obesity. In
obese conditions, infiltrating inflammatory macrophages are
increased due to enhanced recruitment, proliferation and
differentiation into inflammatory type I macrophages; these
macrophages have a key role in maintaining chronic, low-level
inflammation, thus decreasing ILC2s, activating DCs, and recruiting
Th1 cells and CD8 T lymphocytes (8). One of the cytokines involved in the
maintenance of this obesity-related chronic inflammation is MIF,
and its circulating levels have been linked to the development of
insulin resistance, type 2 diabetes and non-alcoholic fatty liver
disease, highlighting the need to delineate and understand the
precise role of MIF in metabolic disease.
The present study aimed to assess the possible
relationship between serum MIF levels and diverse risk factors
related to cancer development in women, to evaluate its possible
relationship with breast cancer risk factors or metabolic
disease.
Materials and methods
Patients
Blood samples were collected by forearm venipuncture
between January and August 2024 from women attending two different
Family Medicine Units (Instituto Mexicano del Seguro Social, Unidad
de Medicina Familiar #2 and 6) in Puebla, Mexico for routine
mammography screening. After collection, blood samples were
centrifuged at 1,200 x g for 10 min and sera were collected and
stored at 4˚C for 2-3 days and later at -80˚C until analysis. A
total of 162 patients, with a median age of 50 years (age range,
20-73 years) were included in the study. All patients who agreed to
participate and signed an informed consent form were included. A
questionnaire was applied to each patient to collect information
about risk-factor exposure. Patients were classified according to
the following parameters: BMI was calculated as mass/height
(kg/m2), and in agreement with adult guidelines
(11), patients were considered as
being underweight (BMI <18.5), normal weight (BMI 18.5-24.9),
overweight (BMI 25-29.9) or obese (BMI ≥30). WHR was considered
low, <0.85; moderate, 0.85-0.89; or high, >0.89; blood
pressure was classified as normal or high, as reported by the
patient (previous diagnosis of hypertension); mammary density was
classified as A, almost entirely fat; B, breasts with scattered
areas of fibroglandular densities; C, heterogeneously dense; or D,
extremely dense breasts (15); and
BI-RADS classification (15,16)
was categorized as 1, negative; 2, benign (noncancerous) findings;
3, probably benign finding, with a <2% chance of malignancy; 4,
suspicious, with a 2-95% probability of cancer; 5, highly
suggestive of malignancy, with a 95% chance of cancer; or 6, known
biopsy-proven malignancy, according to the mammography results.
Other risk factors were collected from the questionnaire completed
by the patients, including age, tobacco use (present and past),
alcohol consumption (present and past), number of births,
contraceptive use/type, previous breastfeeding, age of
menarche/menopause, previous mammary lesions, previous
tuberculosis, radiation exposure and a family history of breast
cancer. Patient data are shown in Table
I.
 | Table IClinical and sociodemographic
characteristics of the studied population (n=162 patients). |
Table I
Clinical and sociodemographic
characteristics of the studied population (n=162 patients).
| Variable | N (%) |
|---|
| Age, years | |
|
22-34 | 3 (1.85) |
|
35-44 | 38 (23.46) |
|
45-54 | 66 (40.74) |
|
55-64 | 43 (26.54) |
|
65-74 | 12 (7.41) |
| BMI
(kg/m2) | |
|
Underweight
(<18.5) | 1 (0.62) |
|
Normal
(18.5-24.9) | 38 (23.46) |
|
Overweight
(25-29.9) | 69 (42.59) |
|
Obese
(>30) | 54 (33.33) |
| WHR | |
|
Low
(<0.85) | 8 (4.94) |
|
Moderate
(0.85-0.89) | 46 (28.40) |
|
High
(>0.89) | 108 (66.67) |
| Mammary
density | |
|
A | 22 (13.580) |
|
B | 71 (43.827) |
|
C | 60 (37.037) |
|
D | 9 (5.556) |
| BI-RADS | |
|
1 | 16 (9.877) |
|
2 | 75 (46.296) |
|
3 | 56 (34.568) |
|
4 | 14 (8.642) |
|
5 | 0 (0.000) |
|
6 | 1 (0.617) |
| Tobacco use
(current and past) | |
|
Yes | 26 (16.05) |
|
No | 136 (83.95) |
| Alcohol
consumption | |
|
Yes | 56 (34.57) |
|
No | 106 (65.43) |
| Radiation
exposure | |
|
Yes | 8 (4.94) |
|
No | 154 (95.06) |
| Age of menarche,
years | |
|
<12 | 45 (27.78) |
|
12-15 | 117 (72.22) |
| Age of
menopause | |
|
<45
years | 26 (16.049) |
|
45-55
years | 67 (41.358) |
|
>55
years | 5 (3.084) |
|
Still
menstruating | 64 (39.506) |
| Breastfeeding
(past) | |
|
Yes | 125 (77.16) |
|
No | 37 (22.84) |
| Number of
births | |
|
0 | 24 (14.81) |
|
1 | 27 (16.67) |
|
≥2 | 111 (68.52) |
| Contraceptive
use/type | |
|
Yes/Oral | 13 (8.025) |
|
Yes/Others | 65 (40.124) |
|
No | 84 (51.852) |
| Blood pressure | |
|
Normal | 127 (78.40) |
|
High | 35 (21.60) |
| Previous mammary
lesions | |
|
Yes | 57 (35.19) |
|
No | 105 (64.81) |
| Family history of
cancer | |
|
Yes | 38 (23.46) |
|
No | 124 (76.54) |
| Previous
tuberculosis | |
|
Yes | 2 (1.23) |
|
No | 160 (98.77) |
Ethics approval
The present study was approved by the Local
Institutional Review Boards 21038 and 21048, in the Instituto
Mexicano del Seguro Social (Puebla, Mexico; approval nos.
R-2024-2104-048 and R-2021-2103-011, respectively). The authors
certify that the study was performed in accordance with the ethical
standards as laid down in the 1964 Declaration of Helsinki and its
later amendments.
Serum MIF level determination
Serum samples were stored at -80˚C until analysis.
MIF levels were determined using the Human MIF DuoSet ELISA kit
(cat. no. DY289; R&D Systems, Inc.), which uses the sandwich
ELISA method and has a limit of detection of 31.2 pg/ml. All
procedures were performed in accordance with the manufacturer's
instructions. No serum dilution was performed; 40 µl each sample
was added to each well, and tetramethylbenzidine was used as
chromogenic substrate for horseradish peroxidase in the
colorimetric reaction. The absorbance was measured using a BioTek
Synergy-4 plate reader (Agilent Technologies, Inc.) at 450 nm, and
a reading at 570 nm was used for background subtraction. Serum
concentrations of MIF were quantified with a standard curve and
expressed in pg/ml.
Statistical analysis
A Kolmogrov-Smimov test was used to analyze data
normality. Since data were not normally distributed, a Mann-Whitney
U test was used for two-sample comparisons and a Kruskal-Wallis
test with Dunn's post-hoc test was used for multiple comparisons.
Correlation analysis was performed with a one-tailed Spearman's
correlation test. Data in contingency tables were analyzed with a
χ2 test. Data were analyzed using GraphPad Prism 6.07
(Dotmatics). Data in the text are presented as the median and
interquartile range (IQR; Q1-Q3) for each parameter mentioned.
P<0.05 was considered to indicate a statistically significant
difference.
Results
MIF serum levels are elevated in women
with a high BMI, elevated WHR and hypertension
The present study detected increased levels of MIF
in women with a BMI indicative of obesity [median (IQR): 1,604.0
(1,208.0-2,720.0) pg/ml] when compared with those who were
overweight [1,342.0 (871.1-1,861.0) pg/ml; P=0.0197] or had a
normal BMI [970.0 (703.0-1,731.0) pg/ml; P=0.0002] (Fig. 1A). In addition, women with a high
WHR had higher levels of MIF [1,542.0 (1,126.0-2,393.0) pg/ml] than
those with a moderate ratio [1,149.0 (761.1-1698.0) pg/ml;
P=0.0126] (Fig. 1B). When both
indexes of obesity were combined, MIF levels were higher in obese
patients with a high WHR [2,030.0 (1,223.0-3,123.0) pg/ml] when
compared with patients with a normal BMI but with a high WHR
[1,076.0 (664.8-1,484.0) pg/ml; P=0.0146]; or with those with a
moderate WHR and a normal BMI [970.0 (751.8-1,912.0) pg/ml;
P=0.0279] or a BMI indicative of being overweight [1,139.0
(725.8-1,665.0) pg/ml; P=0.0284] (Fig.
1C). Notably, when considering only those patients with a high
BMI, MIF levels were higher in obese patients with a high WHR
[2,030.0 (1,223.0-3,123.0) pg/ml] than in those with a medium WHR
[1,328.0 (1,049.0-1,547.0) pg/ml; P=0.0372] (Fig. 1D), suggesting a relationship between
MIF levels and a higher metabolic risk.
MIF levels were also elevated in women with
hypertension [1,582.0 (1,131.0-2,544.0) pg/ml] when compared with
those with a normal blood pressure [1,342.0 (880.7-1,926.0) pg/ml,
P=0.0234] (Fig. 2), suggesting a
relationship between elevated MIF levels and metabolic
complications associated with obesity.
Serum MIF levels are decreased in
patients with BI-RADS classifications 2 and 3
BI-RADS is the standard method for mammogram
classification. This categorization provides information about the
risk of malignancy, from essentially zero (BI-RADS 1) to >95%
(BI-RADS 5) (17). Notably, a
decrease in MIF levels was observed in patients with BI-RADS
classifications 2 [1,468.0 (762.1-2,111.0) pg/ml; P=0.0189] and 3
[1,241.0 (881.4-1,754.0) pg/ml; P=0.0023] when compared with
BI-RADS 1 [2,146.0 (1,654.0-3,131.0) pg/ml] (Fig. 3A). In addition, when comparing high
and low MIF levels between BI-RADS categories (with the cut-off
value set on the median of patients with BI-RADS classification 1),
differences were observed among the BI-RADS categories (P=0.0273;
Table II).
| Table IIAssociation between MIF serum levels
and BI-RADS categories (n=162 patients). |
Table II
Association between MIF serum levels
and BI-RADS categories (n=162 patients).
| Category | BI-RADS 1, n
(%) | BI-RADS 2, n
(%) | BI-RADS 3, n
(%) | BI-RADS 4, n
(%) | P-value |
|---|
| MIF high | 8 (50.0) | 17 (22.6) | 8 (14.3) | 3 (21.4) | 0.0273a |
| MIF low | 8 (50.0) | 58 (77.3) | 48 (85.7) | 11 (78.6) | |
High mammary density is an important risk factor for
breast cancer (18). When comparing
MIF levels among patients with different breast densities, an
apparent decrease in MIF levels was observed with increasing
mammary density, without reaching statistical significance when
compared to A, ranging from [1,986.0 (1,071.0-2,655.0) pg/ml in A;
1,488.0 (1,024.0-2,106.0) in B with P=0.7934; 1,329.0
(844.4-1,860.0) pg/ml in C with P=0.2303; and 1,104.0
(823.3-1,689.0) pg/ml in D with P=0.3451] (Fig. 3B). In addition, no differences in
frequencies between high and low MIF levels were observed among
different classifications of breast density (P=0.0686; Table III). In Table III, the cut-off value for high and
low MIF was set as the median MIF level in all samples evaluated.
Furthermore, no differences were observed among different
classifications of breast density when the cut-off value was set as
the median MIF value in patients with mammary density
classification A [median 1,986.0 pg/ml; P=0.0956; data not
shown].
| Table IIIAssociation between MIF levels and
mammary density (n=162 patients). |
Table III
Association between MIF levels and
mammary density (n=162 patients).
| Category | A, n (%) | B, n (%) | C, n (%) | D, n (%) | P-value |
|---|
| MIF high | 15 (68.2) | 38 (53.5) | 26 (43.3) | 2 (22.2) | 0.0686 |
| MIF low | 7 (31.8) | 33 (46.5) | 34 (56.7) | 7 (77.8) | |
MIF serum levels increase with
aging
Aging has been described as a state related to
low-level systemic chronic inflammation (9). In agreement, the current study
identified a weak but significant positive correlation
(rS=0.1558, P=0.0239) between increased levels of MIF
and increased age (Fig. 4),
indicating that MIF may be related to chronic inflammation during
aging.
Serum MIF levels are not related to
other cancer risk factors
In humans, low levels of systemic chronic
inflammation have also been related to age-associated chronic
diseases, such as cancer (9). Thus,
it was hypothesized that low levels of chronic inflammation would
be evident in women exposed to diverse cancer risk factors.
However, no relationship was identified between the following risk
factors and increased MIF serum levels: Tobacco use (P=0.1260;
Fig. 5A), alcohol consumption
(P=0.0586; Fig. 5B), number of
births (P=0.4330; Fig. 5C),
contraceptive use/type (P=0.5279; Fig.
5D and P=0.1876; Fig. 5E),
breastfeeding (P=0.8093; Fig. 5F),
age of menarche (P=0.3906; Fig.
5G), age of menopause (P=0.1533; Fig. 5H), previous mammary lesions
(P=0.5147; Fig. 5I), previous
tuberculosis (P=0.4313; Fig. 5J),
radiation exposure (P=0.096; Fig.
5K) or a family history of cancer (P=0.6700; Fig. 5L).
 | Figure 5Evaluation of MIF serum levels and
their possible association with diverse cancer risk factors. MIF
serum levels were assessed by ELISA in women and classified
according to (A) tobacco use, (B) alcohol consumption, (C) number
of births, (D) contraceptive use, (E) type of contraceptive used,
(F) breastfeeding, (G) age of menarche, (H) age of menopause, (I)
previous mammary lesions, (J) previous tuberculosis, (K) exposure
to radiation and (L) family history of breast cancer. The graphs
show data from 162 samples with median and interquartile range
(Q1-Q3) for each category. (A, B, D, F, G and I-L) When two groups
were compared, a Mann-Whitney U test was used; (C, E and H) for
more than two group comparisons, a Kruskal-Wallis test with Dunn's
post-hoc test for multiple comparisons was used. No significant
differences were revealed (P<0.05). MIF, macrophage migration
inhibitory factor; mens, menstruating. |
Discussion
Recent evidence has shown that MIF has an important
role in diverse diseases, including inflammatory, metabolic disease
(19) and cancer (1,20,21).
The current study identified an association between high serum MIF
levels in women and a high BMI, high WHR and hypertension, and
revealed a slight correlation between MIF levels and increased age.
Furthermore, a decrease in MIF levels was detected in women with
BI-RADS classifications 2 and 3, which have a slightly higher
chance of having breast cancer when compared with patients
classified as BI-RADS 1. Notably, no difference was identified
between patients classified as BI-RADS 4, who have a higher chance
of having breast cancer, when compared with those classified as
BI-RADS 1. These findings indicate that elevated MIF serum levels
are related to metabolic disease and chronic inflammation, rather
than to exposure to breast cancer risk factors.
MIF has been implicated in obesity-related chronic
inflammation, and high levels of MIF and its receptors have been
reported in VAT (22,23). Elevated levels of MIF expression in
VAT were initially attributed to infiltrating macrophages, although
adipocytes have also been shown to express and secrete MIF, which
may contribute to its circulating levels in obese patients
(19,24). Thus, in obesity, VAT may be
considered an important source of MIF, with possible roles in the
maintenance of inflammation in visceral and peripheral tissues.
Besides regulating inflammation, MIF has been shown to have an
important role in the regulation of metabolism. MIF has been
reported to be increased in the plasma of male mice fed a high-fat
diet as well as in aged animals (2,25), and
it has been shown to favor lipid accumulation during obesity.
Notably, blocking extracellular MIF has been reported to decrease
obesity in high-fat diet-fed mice (25). Moreover, MIF secretion decreases WAT
lipoprotein lipase expression, avoiding circulating triglyceride
hydrolysis and lipid accumulation, inducing hypertriglyceridemia
(2). These studies underscore an
important role for MIF in the regulation of lipid accumulation in
adipocytes during obesity, in the promotion of obesity-associated
alterations, such as hypertriglyceridemia, and indicate a
therapeutic potential of inhibiting MIF in the treatment of obesity
and its related co-morbidities.
Previous studies have reported elevated MIF levels
in obese patients (19). For
example, MIF has been reported to be upregulated in subcutaneous
abdominal adipose tissue from obese individuals compared with in
lean male subjects (23).
Furthermore, the mRNA levels of MIF and one of its receptors, CCR2,
have been found to be elevated in VAT when compared with
subcutaneous adipose tissue in women (22), and MIF levels have been reported to
decrease upon weight loss (19).
Thus, circulating MIF levels could reflect adipocyte accumulation
and more specifically, VAT accumulation. Accordingly, the present
findings revealed that MIF levels were increased in obese patients
with a high WHR when compared with those with a moderate WHR,
suggesting that high serum MIF levels in women may be related to
the accumulation of visceral fat, possibly due to its direct
production by VAT.
Visceral fat is considered a marker of ectopic fat
deposition. It accumulates in or around organs and impairs their
function, increasing disease risk, secreting pro-inflammatory
cytokines, homing innate and adaptive immune cells, and has thus
been strongly associated with cardiometabolic disease (26,27).
Elevated circulating MIF levels have also been related to type 2
diabetes and insulin resistance (19), and, although some discrepancies
exist with respect to normal circulating MIF levels (19) or sex-dependent effects, it is
generally accepted that MIF is increased in obesity, type 2
diabetes, gestational diabetes and in patients with insulin
resistance (28). Moreover,
increased circulating MIF levels have been detected in women with
metabolic syndrome but not in men, suggesting a sex-specific effect
of circulating MIF in this condition and possibly, in its related
complications, such as atherosclerosis or type 2 diabetes (29). In this regard, both the estrogen
receptor, estradiol and progesterone have been shown to modulate
MIF expression in animal models of inflammatory disease (30,31),
suggesting a different regulation of MIF expression in women than
in men. Although the current study did not evaluate comorbidities
such as type 2 diabetes, elevated levels of MIF were found in women
with hypertension, implicating MIF in this obesity-associated
comorbidity. Future studies should evaluate the role of MIF in
hypertension and its possible association with
hypertriglyceridemia, or in other complications related to
metabolic syndrome such as type 2 diabetes and atherosclerosis.
MIF has also been demonstrated to be involved in
other metabolic disorders affecting women. MIF levels have been
shown to be elevated in women with PCOS (32), now referred to as PMOS (33), and MIF has been suggested to be
involved in the pathogenesis of PMOS in animal models through the
activation of MAPK or NF-κB pathways (34,35).
PMOS is characterized by metabolic, reproductive and dermatological
alterations, with obesity being prevalent in women with this
syndrome and contributing to its severity (33). Thus, the fact that MIF is involved
in the pathogenesis of metabolic disorders, together with the
present findings of increased MIF in obese women with a high WHR
and in patients with hypertension, indicated that further research
is needed to identify the precise role of MIF in metabolic
disorders and to evaluate its targeting for the treatment of these
highly prevalent pathologies.
Circulating MIF levels can bind to its receptors in
diverse target cells, activating MAPKs and cytosolic phospholipase
A2 (cPLA2). MIF-induced cPLA2 activation promotes the production of
inflammatory components, including prostaglandins, arachidonic acid
and leukotrienes (3,5). Arachidonic acid release activates
JNK/SAPK, which is responsible for inducing the translation of
TNF-α mRNA, thus serving a key role in the maintenance of cytokine
production and inflammation (5).
Chronic elevated MIF levels could contribute to the maintenance of
chronic inflammation associated with obesity and its
comorbidities.
Diagnosis of clinical obesity should contain
clinical confirmation of obesity, plus evidence of reduced organ or
tissue function, or notable age-adjusted limitations of day-to-day
activities associated with mobility or other basic activities due
to obesity. Although BMI has been widely used in the diagnosis of
obesity, it is not always an adequate measure for its diagnosis,
leading to alternative methods for the clinical assessment of
obesity. Thus, excess adiposity should be confirmed by other
anthropometric criteria, such as waist circumference or direct fat
measurement, to identify individuals at a higher metabolic risk
(11). Preclinical and clinical
obesity have been defined as conditions where negative health
effects might occur, or have occurred, respectively. Moreover,
metabolically healthy obese patients have been described, making it
imperative to distinguish those patients with a higher metabolic
risk (28). In the present study,
MIF levels were increased in obese patients who had an elevated WHR
and to hypertension. Since two criteria were used to define excess
adiposity, one of which was related to visceral fat accumulation,
the patients with a high BMI and elevated WHR may be considered as
obese with a high metabolic risk, and those with hypertension could
be considered as patients where negative health effects have
occurred. Thus, MIF may be proposed as an indicator of metabolic
risk, and its significance to metabolic risk and for the treatment
of obesity-associated complications should be assessed.
The BI-RADS system standardizes breast cancer risk
assessment and provides uniformity in mammography reports, where
risk of malignancy goes from essentially zero (negative
examination, BI-RADS 1), benign findings (BI-RADS 2), <2% chance
of malignancy (BI-RADS 3), low-to-high chance (2-95%) of malignancy
(BI-RADS 4) to a >95% chance of malignancy (BI-RADS 5). BI-RADS
6 classification is used to indicate a pathology-proven malignancy
(17). In the current study, women
with BI-RADS classifications 2 and 3 had decreased levels of MIF
when compared with those with BI-RADS 1 classification. As
aforementioned, MIF has been shown to be elevated in breast cancer
cells, patients or tissues when compared with healthy women,
non-tumorigenic controls or in women with higher stage cancers when
compared to those with stage I breast cancer (36,37).
In addition, abundant MIF expression in breast tumor tissue has
been shown to be associated with markers of favorable prognosis
(estrogen and progesterone receptor expression) and with increased
overall survival (37). Since
higher MIF levels are expected in patients with breast cancer when
compared with patients without cancer and the present data shows
decreased MIF levels in BI-RADS 2 or 3 patients, increased MIF
levels in patients with breast cancer would probably show a more
striking difference when compared to BI-RADS 2 or 3 patients, but
this assumption should be tested in the future. The reason as to
why MIF levels were decreased in these patients is not clear and
could be related to mammary density as discussed in the following
paragraph.
When evaluating mammary density, a non-significant
trend was observed, similar to the one observed regarding BI-RADS
classification. Increased mammary density has been related to an
enhanced breast cancer risk, increased breast calcifications and to
a higher chance of developing aggressive cancer types. In addition,
an increased BMI has been associated with decreased breast density
due to increased breast fat (non-dense tissue in a mammogram) and
reduced fibroglandular tissue (18,38).
Since breast density and BMI are likely to be inversely related
(38), the observed changes in MIF
concentration with BI-RADS classification, as well as those
apparent among mammary density classifications, might be related to
the relationship between MIF and obesity. Although this was an
unexpected finding, it indicates that high circulating MIF levels
are not related to breast cancer risk factors, since they would be
expected to be associated with increased BI-RADS classification or
to increased mammary density. Moreover, MIF levels were not related
to exposure to other breast cancer risk factors. These findings
indicate that high levels of circulating MIF may be related to
metabolic alterations, rather than to cancer risk factors.
Aging is associated with increased chronic
inflammation with local and systemic manifestations (39). Inflammatory cytokines and biomarkers
have been shown to increase with age, including C-reactive protein
and IL-6, which are associated with a decrease in immune function
(39). The present study identified
a weak positive correlation between increased MIF levels and
increasing age in women. Although MIF levels have been shown to be
elevated in aged mice (2), to the
best of our knowledge this is the first report showing increased
MIF levels in elderly women, connecting MIF to other inflammatory
biomarkers associated with aging. Since the current study
population comprised women who requested screening mammography, it
is important to enforce this conclusion with more data from younger
women. Furthermore, it is important to establish a precise role for
MIF in the regulation of organ and tissue decline with aging in
women, with the aim of effectively targeting this cytokine and
decreasing the effects of aging.
Several MIF inhibitors have been described with
diverse mechanisms of action (3,4,40), and
some natural products such as vanillic acid (41) or sulforaphane (42) have been used in diverse studies to
block MIF function. Among MIF-targeting drugs, clinical trials have
used drugs that inactivate MIF as an off-target, such as ibudilast,
with promising results for multiple sclerosis treatment, but it is
unclear to what extent its effects are due to MIF inhibition or to
its effects on other targets (phosphodiesterase or TLR4). Also, an
anti-oxidized MIF monoclonal antibody has been tested in patients
with malignancies, and anti-CD74 monoclonal antibodies have also
been tested for patients with systemic lupus erythematosus
(43). Therefore, MIF may also be
considered a promising target for the treatment of metabolic
disorders such as obesity and its related complications, and could
potentially decrease age-associated inflammation and its effects in
cell and organismal function.
In conclusion, elevated serum MIF levels were shown
to be related to states of chronic inflammation such as obesity,
high WHR and aging in women. These findings suggest an important
relationship between MIF and metabolic disease and VAT
accumulation, and indicate a possible implication for MIF in the
pathogenesis of obesity and its related comorbidities.
Acknowledgements
The authors would like to thank Miss Tania
Flores-Papaqui and Miss Monica Rugerio-Téllez (Unidad de Medicina
Familiar No. 2, IMSS) as well as Miss Gabriela Sánchez-Nava (Unidad
de Medicina Familiar No. 6, IMSS) for their invaluable support for
the acquisition and preservation of the samples.
Funding
Funding: Secretaría de Ciencia, Humanidades, Tecnología e
Innovación (SECIHTI), Mexico grant no. CF-2023-I-26 (P.M.); SECIHTI
scholarship no. 1031375.
Availability of data and materials
The data generated in the present study may be
requested from the corresponding author.
Authors' contributions
All authors contributed to the study conception and
design. Material preparation, data collection and analysis were
performed by FVD, KALR, NZB and JHP. LMFNLDG, FDASC and SOPZ were
involved in data and sample collection and study supervision. The
first draft of the manuscript was written by FVD, KALR, NZB and PM,
and all authors commented on previous versions of the manuscript.
FVC, KALR, NZB and PM confirm the authenticity of all the raw data.
All authors read and approved the final manuscript.
Ethics approval and consent to
participate
The present study was approved by the Local
Institutional Review Boards 21038 and 21048, from Instituto
Mexicano del Seguro Social (Puebla, Mexico; approval nos.
R-2024-2104-048 and R-2021-2103-011). Two ethics approval numbers
are provided since patients were from two different Units and the
protocol was registered in both local Review Boards. Written
informed consent for participation was obtained from all individual
participants included in the study. The authors certify that the
study was performed in accordance with the ethical standards as
laid down in the 1964 Declaration of Helsinki and its later
amendments.
Patient consent for publication
Written informed consent for publication was
obtained from all participants in the study.
Competing interests
The authors declare that they have no competing
interests.
Authors' information
ORCID IDs: 0009-0007-4421-5168 (F.V.-D.);
0000-0001-8049-8352 (K.A.L.-R); 0009-0001-8572-1135 (N.Z.-B.);
0009-0005-0653-1456 (J.H.-P.); 0009-0002-8034-7313
(L.M.F.-N.-L.-G.); 0000-0003-0576-8409 (F.A.S.-C.);
0000-0001-5710-0094 (S.O.P.-Z.); 0000-0003-4059-0554 (P.M.).
References
|
1
|
Youness RA, Elemam NM, Abdelhamid AM,
Mohamed AH, Elsherbiny LM, Ramzy A and Assal RA: Macrophage
migration inhibitory factor (MIF) and the tumor ecosystem: A tale
of inflammation, immune escape, and tumor growth. Front Immunol.
16(1636839)2025.PubMed/NCBI View Article : Google Scholar
|
|
2
|
Huang Y, Chen L, Li L, Qi Y, Tong H, Wu H,
Xu J, Leng L, Cheema S, Sun G, et al: Downregulation of adipose LPL
by PAR2 contributes to the development of hypertriglyceridemia. JCI
Insight. 9(e173240)2024.PubMed/NCBI View Article : Google Scholar
|
|
3
|
Camacho Meza G, Avalos Navarro G, De La
Cruz Mosso U, Ramírez Patiño R, Muñoz Valle JF and Bautista Herrera
LA: Macrophage migration inhibitory factor: Exploring physiological
roles and comparing health benefits against oncogenic and
autoimmune risks (review). Int J Mol Med. 56(149)2025.PubMed/NCBI View Article : Google Scholar
|
|
4
|
Aliyarbayova A, Sultanova T, Yaqubova S,
Najafova T, Sadiqova G and Salimova A: Macrophage migration
inhibitory factor: Its multifaceted role in inflammation and immune
regulation across organ systems. Cell Physiol Biochem. 59:569–588.
2025.PubMed/NCBI View Article : Google Scholar
|
|
5
|
Sumaiya K, Langford D, Natarajaseenivasan
K and Shanmughapriya S: Macrophage migration inhibitory factor
(MIF): A multifaceted cytokine regulated by genetic and
physiological strategies. Pharmacol Ther.
233(108024)2022.PubMed/NCBI View Article : Google Scholar
|
|
6
|
Altulea A, Nehme J and Demaria M: Dual
role of MIF in aging and cellular senescence. Cytokine Growth
Factor Rev. 89:5–14. 2026.PubMed/NCBI View Article : Google Scholar
|
|
7
|
Liu Y, Wang T, Wu R, Gao J, Cai J, Huo L,
Li X, Li J, Wang J, Wang Z, et al: Single-cell transcriptome atlas
and genome-wide Mendelian randomization reveal chemokine
involvement in diverse immune cells in type 2 diabetes. Int J Obes
(Lond). 49:2213–2228. 2025.PubMed/NCBI View Article : Google Scholar
|
|
8
|
Kardinal R and Wachten D: Macrophages in
metaflammation-fueling chronic inflammation in metabolic disease.
Pflugers Arch. 478(10)2025.PubMed/NCBI View Article : Google Scholar
|
|
9
|
Pawelec G, Goldeck D and Derhovanessian E:
Inflammation, ageing and chronic disease. Curr Opin Immunol.
29:23–28. 2014.PubMed/NCBI View Article : Google Scholar
|
|
10
|
Crasan IM, Tanase M, Delia CE,
Gradisteanu-Pircalabioru G, Cimpean A and Ionica E:
Metaflammation's role in systemic dysfunction in obesity: A
comprehensive review. Int J Mol Sci. 26(10445)2025.PubMed/NCBI View Article : Google Scholar
|
|
11
|
Rubino F, Cummings DE, Eckel RH, Cohen RV,
Wilding JPH, Brown WA, Stanford FC, Batterham RL, Farooqi IS,
Farpour-Lambert NJ, et al: Definition and diagnostic criteria of
clinical obesity. Lancet Diabetes Endocrinol. 13:221–262.
2025.PubMed/NCBI View Article : Google Scholar
|
|
12
|
NIH: Overweight and Obesity: Obesity and
Women's Health. National Heart, Lung and Blood Institute. Available
from: https://www.nhlbi.nih.gov/health/overweight-and-obesity/women.
Accessed at December 16, 2025.
|
|
13
|
Chen Y, Wang R, Zhang N and Xu L: The dual
burden of obesity: Decoding metabolism and female reproductive
endocrinology. Front Physiol. 16(1627607)2025.PubMed/NCBI View Article : Google Scholar
|
|
14
|
Weiskirchen R and Lonardo A: Semaglutide
from bench to bedside: The experimental journey towards a
transformative therapy for diabetes, obesity and metabolic liver
disorders. Med Sci (Basel). 13(265)2025.PubMed/NCBI View Article : Google Scholar
|
|
15
|
Gemici AA, Bayram E, Hocaoglu E and Inci
E: Comparison of breast density assessments according to BI-RADS 4
and 5th editions and experience level. Acta Radiol Open.
9(2058460120937381)2020.PubMed/NCBI View Article : Google Scholar
|
|
16
|
Newell MS, Destounis SV, Leung JWT,
DeMartini WB, Lee CH and Eby PR: ACR BI-RADS® v2025
Manual. American College of Radiology; Reston, VA, USA, 2025.
|
|
17
|
Magny SJ, Shikhman R and Keppke AL: Breast
Imaging Reporting and Data System. In: StatPearls. StatPearls
Publishing, Treasure Island, FL, 2026.
|
|
18
|
Zhang Z, Ray RM, An R, Klonoff-Cohen HS
and Thomas DB: Mammographic density as a mediator for breast cancer
risk: Pooled analysis of four population-based case-control studies
on women with screening mammograms under 50. Cancer Epidemiol
Biomarkers Prev. 35:465–474. 2026.PubMed/NCBI View Article : Google Scholar
|
|
19
|
Morrison MC and Kleemann R: Role of
macrophage migration inhibitory factor in obesity, insulin
resistance, type 2 diabetes, and associated hepatic co-morbidities:
A comprehensive review of human and rodent studies. Front Immunol.
6(308)2015.PubMed/NCBI View Article : Google Scholar
|
|
20
|
Mora Barthelmess R, Stijlemans B and Van
Ginderachter JA: Hallmarks of cancer affected by the MIF cytokine
family. Cancers (Basel). 15(395)2023.PubMed/NCBI View Article : Google Scholar
|
|
21
|
Bucala R and Donnelly SC: Macrophage
migration inhibitory factor: A probable link between inflammation
and cancer. Immunity. 26:281–285. 2007.PubMed/NCBI View Article : Google Scholar
|
|
22
|
Alvehus M, Burén J, Sjöström M, Goedecke J
and Olsson T: The human visceral fat depot has a unique
inflammatory profile. Obesity (Silver Spring). 18:879–883.
2010.PubMed/NCBI View Article : Google Scholar
|
|
23
|
González-Muniesa P, Marrades MP, Martínez
JA and Moreno-Aliaga MJ: Differential proinflammatory and oxidative
stress response and vulnerability to metabolic syndrome in habitual
high-fat young male consumers putatively predisposed by their
genetic background. Int J Mol Sci. 14:17238–17255. 2013.PubMed/NCBI View Article : Google Scholar
|
|
24
|
Skurk T, Herder C, Kräft I,
Müller-Scholze S, Hauner H and Kolb H: Production and release of
macrophage migration inhibitory factor from human adipocytes.
Endocrinology. 146:1006–1011. 2005.PubMed/NCBI View Article : Google Scholar
|
|
25
|
Chen L, Li L, Cui D, Huang Y, Tong H,
Zabihi H, Wang S, Qi Y, Lakowski T, Leng L, et al: Extracellular
macrophage migration inhibitory factor (MIF) downregulates adipose
hormone-sensitive lipase (HSL) and contributes to obesity. Mol
Metab. 79(101834)2024.PubMed/NCBI View Article : Google Scholar
|
|
26
|
Lee MJ and Kim J: The pathophysiology of
visceral adipose tissues in cardiometabolic diseases. Biochem
Pharmacol. 222(116116)2024.PubMed/NCBI View Article : Google Scholar
|
|
27
|
Khan S, Chan YT, Revelo XS and Winer DA:
The immune landscape of visceral adipose tissue during obesity and
aging. Front Endocrinol (Lausanne). 11(267)2020.PubMed/NCBI View Article : Google Scholar
|
|
28
|
Herder C, Klopp N, Baumert J, Müller M,
Khuseyinova N, Meisinger C, Martin S, Illig T, Koenig W and Thorand
B: Effect of macrophage migration inhibitory factor (MIF) gene
variants and MIF serum concentrations on the risk of type 2
diabetes: Results from the MONICA/KORA Augsburg Case-Cohort Study,
1984-2002. Diabetologia. 51:276–284. 2008.PubMed/NCBI View Article : Google Scholar
|
|
29
|
Kim H, Lee S, Kim HJ, Kong MH, Kim YR,
Kang SH, Lee K, Leng L, Lee B, Park CG, et al: Elevated levels of
macrophage migration inhibitory factor in women with metabolic
syndrome. Horm Metab Res. 43:642–645. 2011.PubMed/NCBI View Article : Google Scholar
|
|
30
|
Liu T, Zhang T, Guo C, Liang X, Wang P and
Zheng B: Murine double minute 2-mediated estrogen receptor 1
degradation activates macrophage migration inhibitory factor to
promote vascular smooth muscle cell dedifferentiation and oxidative
stress during thoracic aortic aneurysm progression. Biochim Biophys
Acta Mol Cell Res. 1871(119661)2024.PubMed/NCBI View Article : Google Scholar
|
|
31
|
Houdeau E, Moriez R, Leveque M,
Salvador-Cartier C, Waget A, Leng L, Bueno L, Bucala R and
Fioramonti J: Sex steroid regulation of macrophage migration
inhibitory factor in normal and inflamed colon in the female rat.
Gastroenterology. 132:982–993. 2007.PubMed/NCBI View Article : Google Scholar
|
|
32
|
Mejia-Montilla J, Álvarez-Mon M,
Reyna-Villasmil E, Torres-Cepeda D, Santos-Bolívar J,
Reyna-Villasmil N, Suarez-Torres I and Bravo-Henríquez A:
Macrophage migration inhibitory factor in obese and non obese women
with polycystic ovary syndrome. Endocrinol Nutr. 62:31–37.
2015.PubMed/NCBI View Article : Google Scholar : (In English,
Spanish).
|
|
33
|
Teede HJ, Khomami MB, Morman R, Laven JSE,
Joham AE, Costello MF, Patil M, Rees DA, Berry L, Cree MG, et al:
Polyendocrine metabolic ovarian syndrome, the new name for
polycystic ovary syndrome: A multistep global consensus process.
Lancet. 407:2329–2339. 2026.PubMed/NCBI View Article : Google Scholar
|
|
34
|
He Z, Wang Y, Zhuan L, Li Y, Tang ZO, Wu Z
and Ma Y: MIF-mediated NF-κB signaling pathway regulates the
pathogenesis of polycystic ovary syndrome in rats. Cytokine.
146(155632)2021.PubMed/NCBI View Article : Google Scholar
|
|
35
|
Zhou DN, Li SJ, Ding JL, Yin TL, Yang J
and Ye H: MIF May participate in pathogenesis of polycystic ovary
syndrome in rats through MAPK signalling pathway. Curr Med Sci.
38:853–860. 2018.PubMed/NCBI View Article : Google Scholar
|
|
36
|
Avalos-Navarro G, Muñoz-Valle JF,
Daneri-Navarro A, Quintero-Ramos A, Franco-Topete RA, Morán-Mendoza
AJ, Oceguera-Villanueva A, Bautista-Herrera LA, Topete-Camacho A
and Del Toro-Arreola A: Circulating soluble levels of MIF in women
with breast cancer in the molecular subtypes: Relationship with
Th17 cytokine profile. Clin Exp Med. 19:385–391. 2019.PubMed/NCBI View Article : Google Scholar
|
|
37
|
Verjans E, Noetzel E, Bektas N, Schütz AK,
Lue H, Lennartz B, Hartmann A, Dahl E and Bernhagen J: Dual role of
macrophage migration inhibitory factor (MIF) in human breast
cancer. BMC Cancer. 9(230)2009.PubMed/NCBI View Article : Google Scholar
|
|
38
|
Fernández-Morata J, Pollán M, Fernández de
Larrea-Baz N, Pachón-Olmos V, García-Pérez J, Castelló A, Sierra
MÁ, Lucas P, Llobet R, Stradella A, et al: Mammographic density and
breast cancer pathological subtypes by menopausal status and body
mass index. Breast Cancer Res. 27(187)2025.PubMed/NCBI View Article : Google Scholar
|
|
39
|
López-Otín C, Blasco MA, Partridge L,
Serrano M and Kroemer G: Hallmarks of aging: An expanding universe.
Cell. 186:243–278. 2023.PubMed/NCBI View Article : Google Scholar
|
|
40
|
Valdez CN, Sánchez-Zuno GA, Bucala R and
Tran TT: Macrophage migration inhibitory factor (MIF) and
D-dopachrome tautomerase (DDT): Pathways to tumorigenesis and
therapeutic opportunities. Int J Mol Sci. 25(4849)2024.PubMed/NCBI View Article : Google Scholar
|
|
41
|
Guo S, Zhao Y, Yuan Y, Liao Y, Jiang X,
Wang L, Lu W and Shi J: Progress in the development of macrophage
migration inhibitory factor small-molecule inhibitors. Eur J Med
Chem. 286(117280)2025.PubMed/NCBI View Article : Google Scholar
|
|
42
|
Treasure K, Harris J and Williamson G:
Exploring the anti-inflammatory activity of sulforaphane. Immunol
Cell Biol. 101:805–828. 2023.PubMed/NCBI View Article : Google Scholar
|
|
43
|
Harris J, VanPatten S, Deen NS, Al-Abed Y
and Morand EF: Rediscovering MIF: New tricks for an old cytokine.
Trends Immunol. 40:447–462. 2019.PubMed/NCBI View Article : Google Scholar
|
