Skip to main content
Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Alterations in the structural characteristics of rectus abdominis muscles caused by diabetes and pregnancy: A comparative study of the rat model and women

  • Giovana Vesentini ,

    Roles Conceptualization, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • Angélica M. P. Barbosa,

    Roles Project administration

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Physiotherapy and Occupational Therapy, São Paulo State University (UNESP), School of Philosophy and Sciences, Marilia, São Paulo, Brazil

  • Débora C. Damasceno,

    Roles Writing – review & editing

    Affiliation Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • Gabriela Marini,

    Roles Investigation, Writing – review & editing

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil, Department of Health Sciences, Universidade Sagrado Coração, Bauru, São Paulo, Brazil

  • Fernanda Piculo,

    Roles Visualization, Writing – review & editing

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • Selma M. M. Matheus,

    Roles Resources, Writing – review & editing

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Anatomy, São Paulo State University (UNESP), Institute of Biosciences, Botucatu, São Paulo, Brazil

  • Raghavendra L. S. Hallur,

    Roles Visualization, Writing – review & editing

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • Sthefanie K. Nunes,

    Roles Investigation

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • Bruna B. Catinelli,

    Roles Data curation

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • Claudia G. Magalhães,

    Roles Investigation, Project administration, Resources

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • Roberto Costa,

    Roles Investigation, Project administration, Resources

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • Joelcio F. Abbade,

    Roles Investigation, Project administration, Resources

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • José E. Corrente,

    Roles Formal analysis

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Biostatistics, São Paulo State University (UNESP), Bioscience Institute, Botucatu, São Paulo, Brazil

  • Iracema M. P. Calderon,

    Roles Writing – review & editing

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  • Marilza V. C. Rudge,

    Roles Funding acquisition, Supervision, Writing – review & editing

    Affiliations Perinatal Diabetes Research Center, University Hospital, Botucatu Medical School, Univ Estadual Paulista_UNESP, Botucatu, São Paulo, Brazil, Department of Gynecology and Obstetrics, São Paulo State University (UNESP), Botucatu Medical School, Botucatu, São Paulo, Brazil

  •  [ ... ],
  • The DIAMATER Study Group

    Membership of the Termite Genome Working Group is listed in the Acknowledgments.

  • [ view all ]
  • [ view less ]


Background and objective

In the present study, we compared the effect of diabetic pregnancy on the rectus abdominis muscle (RAM) in humans and rats. We hypothesized that our animal model could provide valuable information about alterations in the RAM of women with Gestational Diabetes (GDM).


Newborns female rats (n = 10/group) were administered streptozotocin (100 mg/kg body weight) subcutaneously and were mated on reaching adulthood, to develop the mild hyperglycemic pregnant (MHP) rat model. At the end of pregnancy, the mothers were sacrificed, and the RAM tissue was collected. Pregnant women without GDM (non-GDM group; n = 10) and those diagnosed with GDM (GDM group; n = 8) and undergoing treatment were recruited, and RAM samples were obtained at C-section. The RAM architecture and the distribution of the fast and slow fibers and collagen were studied by immunohistochemistry.


No statistically significant differences in the maternal and fetal characters were observed between the groups in both rats and women. However, significant changes in RAM architecture were observed. Diabetes in pregnancy increased the abundance of slow fibers and decreased fast fiber number and area in both rats and women. A decrease in collagen distribution was observed in GDM women; however, a similar change was not observed in the MHP rats.


Our results indicated that pregnancy- associated diabetes- induced similar structural adaptations in the RAM of women and rats with slight alterations in fiber type number and area. These findings suggest that the MHP rat model can be used for studying the effects of pregnancy-associated diabetes on the fiber structure of RAM.


Diabetes mellitus (DM) is a global health concern. Women who develop gestational diabetes (GDM) are more susceptible to develop type 2 diabetes later in life [1]. Pregnancy causes an insulin resistance state. When an increase in insulin secretion cannot meet the needs of the pregnancy-induced insulin resistance status, it results in the development of GDM [2]. DM is defined as a group of metabolic diseases associated with a hyperglycemic state due to metabolic or genetic malfunction in insulin release [3]. DM has also been associated with diabetic myopathy, a deficiency of healthy muscle maintenance [4]. Diabetic myopathy is a universal complication of diabetes and is related to the loss of muscle mass and strength (i.e., sarcopenia and dynapenia) [46].

The skeletal muscle is a heterogeneous tissue composed of different fiber types, all of which are characterized by myosin heavy chain isoforms [7]. The mammalian skeletal muscle is composed of two major fiber types—slow and fast- which differ in their size, metabolism, and contractile properties [8]. Another component of skeletal muscle is the extracellular matrix (ECM), which plays major roles in muscle fiber force transmission, maintenance, and repair [9]. The skeletal muscle is known to play a critical role in locomotion and glucose homeostasis [10].

Although significant improvements have been made over the past decade in the care and management of GDM with respect to adverse pregnancy outcomes [11, 12], there are only a few studies on the impact of GDM on urinary disorders such as urinary incontinence (UI). Data from a previous study suggested that up to 49% of women with GDM have a substantial risk of developing UI [13]. The consequences of UI persist not only during pregnancy but up to 2 years post-partum and have a negative impact on the quality of life [14, 15]. Previously, our research group conducted studies on the urethral tissue obtained from a pregnant Streptozotocin (STZ) rat model [1621]. The hyperglycemia status in these rats is manifested by STZ-induced necrosis of the pancreatic β-cells [22]. However, the individual animals, dose, route of administration, and life period of induction are key factors contribuiting to the intensity of the induced hyperglycemia [16]. A higher or lower hyperglycemic level caused an impairment of the urethral tissue [17, 18, 20]. We also investigated the changes in rectus abdominis muscle (RAM) in the same animal model and discovered that both the RAM and urethral muscles are subjected to similar morphological changes during diabetic myopathy [21].

The RAM is a typical glycolytic muscle with a predominance of fast fibers [21]. The increase in its abdominal content during pregnancy represents a chronic physiological stimulus in the muscle fibers of the abdominal wall [23]. During pregnancy, there is an increase in the abundance of slow fibers in the RAM, enabling it to be stretched [21, 23]. This stretching is hypothesized to be a result of an overload of hypertrophy, contributing to muscle tone and endurance [23]. There is growing scientific and clinical attention on the role of the abdominal muscles in the normal functioning of the pelvic floor muscle in women [24]. Changes in the structure of these muscles may jeopardize their support and continence [25].

Although previous studies have demonstrated the relationship between UI and GDM [1315], the pathophysiology of GDM leading to the development of UI is poorly understood. Investigation of the human urethra or pelvic floor muscles have many ethical constraints, and the studies on human UI predominantly rely on indirect assessments via clinical examination or imaging techniques [2628]. However, there are several unanswered questions regarding the pathogenesis of urinary disorders. Rodent models can be used as representative animal models to determine the possible events leading to the high prevalence of UI in women with GDM. The structure and histology of the abdominal wall muscles of rats are well characterized and are similar to those in humans, making them appropriate tissue models for studying the physiological changes in the muscle [29].

The purpose of this study is to compare the effects of diabetes and pregnancy in human and rodent RAM using histological and immunohistochemical techniques to elucidate the suitability of the rat model for studying the pathophysiology of human GDM-induced UI. This study provides a foundation for the use of the rat model for studying diabetic myopathy in humans as a reliable tool for future studies on GDM and the development of new therapeutic approaches.

Materials and methods

Ethics statement

All animal experiments were approved by the Institutional Animal Care and Use Committee, Faculdade de Medicina de Botucatu, São Paulo State University (UNESP), and complied with the applicable regulations and recommendations of the Brazilian authorities (protocol 1003–2013).

For human study, signed informed consent was obtained from all study participants before the start of the study. Participants were recruited at the University Hospital (Perinatal Diabetes Research Center), UNESP, Brazil, between March 2015 and December 2018. The study was registered in the Brazilian National Research Registry platform (Plataforma Brasil) and approved by the National Committee for Ethics in Research (CONEP) (CAAE: 26142614.0.0000.5411 and CAAE: 82225617.0.0000.5411) and adhered to the guidelines of the Declaration of Helsinki on Human Experimentation.

Animal model

Female and male Wistar (12–13 weeks-old and 250–300 g) rats were obtained from the Multidisciplinary Center for Biological Investigation (Campinas, SP, Brazil). Animals were housed in a facility with constant temperature (22±2°C) and humidity (55±5%) on a controlled 12 h light–12 h dark cycle with food and water ad libitum. After one week of acclimatization, the dams were mated. The female offspring, on the first day of life, were randomly assigned to two groups (n = 10/group) the mild hyperglycemic pregnant (MHP) group, which received STZ (SIGMA Chemical Company, St. Louis, MO, USA), diluted in 0.1 M citrate buffer (pH 4.5) at a dose of 100 mg/kg by subcutaneous injection [30], or the non-mild hyperglycemic pregnant (non-MHP) group, which received the same dose of citrate buffer. When these rats reached adulthood (around 12–13 weeks- old), they were housed with adult male rats overnight. The first day of gestation (GD0) was determined by examining the vaginal smear, and the rats were housed in individual cages after that. An oral glucose tolerance test (OGTT) was performed on the 17th day of pregnancy to assess the development of altered glucose metabolism [31]. Blood glucose concentrations were measured using a One-Touch Ultra glucometer (LifeScan, Johnson and Johnson®, Milpitas, CA, USA), and the values were expressed as mg/dL. At the end of pregnancy (GD21), the dams were euthanized by sodium thiopental injection (Thiopentax®, Brazil 80 mg/kg dose). The lower third of RAM was exposed, dissected, and removed. The edges were reduced, and the sample was wrapped in talc, frozen in liquid nitrogen, and kept at -80°C. About 500 mg non-random samples of RAM were obtained from a total of 10 rats in each group. The morphometric and immunohistochemical data from the maternal and fetal samples were published previously by Vesentini et al. [21].

Participant selection

Pregnant women were screened for GDM between 24–28 weeks of gestation and were diagnosed according to the ADA criteria using a 75 g-OGTT test [32, 33]. Women with known type 1 or type 2 DM, preterm delivery (<37 weeks of gestation), multiple pregnancies, or known fetal anomaly were excluded. All women with GDM underwent the same treatment in the Perinatal Diabetes Research Center (PDRC). This treatment protocol included adequate nutrition based on recommendations from a nutritionist, motivation to exercise regularly, and insulin administration. Participants with singleton pregnancies who were screened for GDM and met the inclusion criteria were invited at 34 weeks of pregnancy. Around 500 mg of non-random sampling of RAM was obtained from a total of 18 pregnant women who underwent C-section and were categorized into the non-GDM group (n = 10) or GDM group (n = 8) (Fig 1). RAM biopsies were obtained at the time of C-section within 10 min of delivery. The sample was stripped off from visible adipose and connective tissues, wrapped in talc, snap-frozen in liquid nitrogen, and stored below -80°C.

Histological examination, immunohistochemical staining, and morphometric analysis

Both the rat and human muscle samples were processed similarly. Muscle samples were cut into 10-μm-thick cross-sections using a cryostat (Leica CM 1800). The cross-sections were fixed on a microscope glass slides in cold acetone for 10 minutes and were stained using hematoxylin and eosin (H&E) and picrosirius red, or were processed for immunohistochemical analyses. The slides were examined by light microscopy and photographed (DMR, Leica® coupled with a CCD-IRIS/RGB digital camera, Sony®). The micrographs published by Vesentini et al. [21] previously were re-analyzed, and the morphometric area of the fiber types and collagen and fiber numbers were determined.

Picrosirius red staining was performed to determine the tissue area of collagen (red-stained). For quantitative morphometric analysis, ten sections were stained forcollagen area and imaged under 20× magnification. The images were analyzed using ImageJ (National Institutes of Health, USA).

For immunohistochemistry of fast and slow-type skeletal muscle fibers, the sections were incubated with antibodies directed against WB-myosin heavy chain, fast (WB-MHCf) Novocastra (rats, 1:120; human, 1:160) and WB-MHC slow (WB-MHCs) Novocastra (rats, 1:180; human, 1:120). The fiber type area and number were quantitatively determined, as described previously [21].

Statistical analysis

Categorical data were described by percentages and assessed by chi-square tests. Continuous data were described by their means ± standard deviations (SD) and compared by t-tests (clinical characteristics of participants, rats fetal weight, fiber area), ANOVA (rat maternal weight at day 0 and 21), or Poisson test (fiber type number). The OGTT results were calculated using the total area under the curve (AUC) [34] and compared by t-tests. Statistical significance was set as a p-value < 0.05. All analyses were performed using SAS for Windows, v.9.3 (Statistical Analysis System Institute Inc., USA).


Table 1 displays the socio-demographic and clinical characteristics of the study participants. No statistically significant differences were observed between the groups regarding any of the variables. Table 2 shows the maternal and fetal weight of the rats in the two groups. The absence of any significant differences highlights the homogeneity of the samples in both the pregnant women and rats. The GDM and MHP groups, presented higher AUC with elevated glucose levels compared to control groups (non-GDM = 12303.3 ± 2547.6 mg/dL X minutes; GDM = 18428.6 ± 1963.2 mg/dL X minutes, p<0.0001; non-MHP = 9662.5 ± 1339.2 mg/dL X minutes; MHP = 20142 ± 5194.6 mg/dL X minutes, p = 0.001) (Fig 2).

Fig 2.

A: Oral Glucose Tolerance Test (OGTT) performed at 24–28 weeks for pregnant women and on the 17th day of pregnancy for rats. B: The area under the curve of each group is expressed as the mean ± standard deviation. *p<0.05 shows a significant difference compared to the control group (t-test).

Table 1. Socio-demographic and clinical characteristics of the study participants.

Table 2. Maternal and fetal weights in the animal study groups.

Immunohistochemical analysis of the markers of fast and slow type skeletal muscle fibers during pregnancy in the non-GDM and non-MHP groups showed an increased abundance of fast fibers in the RAM (Fig 3). Despite the higher number of fast fibers (non-GDM = 66.98 ± 10.75%; GDM = 57.93 ± 8.22, p = 0.0012; non-MHP = 87.71 ± 6.24%; MHP = 77.58 ± 6.63, p<0.0001), a significant increase in the number of slow fibers (non-GDM = 33.02 ± 15.32%; GDM = 42.07 ± 9.65, p<0.0001; non-MHP = 12.29 ± 16.69%; MHP = 77.58 ± 6.63, p<0.0001) was observed both in the GDM and MHP groups compared to that in the respective controls. The GDM and MHP groups showed a decrease in the area of fast fibers (non-GDM = 4544.82 ± 825.54 μm2; GDM = 2895.8 ± 459.2 μm2, p<0.0001; non-MHP = 3363.29 ± 773.51 μm2, MHP = 2878.35 ± 640.3 μm2, p<0.0001). The distribution of the slow fiber area presented different patterns in the two groups. While in the GDM group (human) there was a decrease in the slow fiber area (non-GDM = 2820.89 ± 509.23; μm2; GDM = 1908.3 ± 294.3 <m2, p<0.0001), an increase (non-MHP = 1273.63 ± 233.9 μm2; MHP = 1324.85 ± 286.46 μm2, p = 0.0178) was observed in the MHP (rat) group.

Fig 3. Micrographs showing slow and fast fibers in a transverse RAM section.

Non-GDM (slow 1, fast 2), GDM (slow 3, fast 4), non-MHP (slow 5, fast 6), and MHP (slow 7, fast 8). (A) The abundance of each fiber type is expressed as percentages, and (B) the area of each fiber type is expressed as mean ± SD. Differences in the abundance of each fiber type between the groups were determined using Poisson distribution. Differences in the fiber area between the groups were determined using the Student’s t-test. *p<0.05 shows a significant difference compared to the control group. Abbreviations: GDM, Gestational Diabetes, MHP, mild hyperglycemic pregnant.

The collagen area in the GDM group was significantly reduced compared to that in the non-GDM group (non-GDM = 25194.2 ± 7579.1 μm2; GDM = 15208.3 ± 4181.2 μm2, p<0.0001). On the other hand, there were no differences in the collagen area between the rat groups (non-MHP = 35150.7 ± 4010.3 μm2; MHP = 34701.1 ± 6078.7 μm2, p = 0.5376) (Fig 4).Table 3 summarizes the morphological changes of the RAM in the rats and human diabetic groups.

Fig 4.

Transverse RAM sections stained with picrosirius red showing striated muscle (yellow) and collagen (red). (1) Non-GDM, (2) GDM, (3) non-MHP, and (4) MHP. Differences in the collagen area between the groups were evaluated using the Student’s t-test. *p<0.05 shows a significant difference compared to the control group. Abbreviations: GDM, Gestational Diabetes, MHP, mild hyperglycemic pregnant; RAM, rectus abdominis muscle.

Table 3. Morphological changes in the RAM of pregnant rats and women with diabetes.


Increased risk of adverse pregnancy outcomes such as the increased risk of developing metabolic syndrome or diabetes, traumatic delivery complications, macrosomia, stillbirths, and congenital anomalies are associated with GDM [3537]. The consequences of GDM for maternal and neonatal studies have been recognized for a long time [38], and as a result, treatment of GDM is primarily aimed at reducing the risk of adverse perinatal outcomes [12, 39].

The association between urinary disorders and GDM is not well understood. Urinary disorders have been a neglected aspect of GDM and are not addressed in the guidelines for the care of Gestational Diabetes [11, 40, 41]. This lack of consideration might be due to the lack of robust evidence supporting the association between GDM and urinary disorders. Few studies have pointed out the influence of GDM on skeletal muscle morphology. Given the ethical constraints associated with the use of a large amount of tissue for a comprehensive analysis of RAM in women, research involving animal models is critical to our understanding of the role of GDM in the development of urinary disorders. Therefore, the present study aimed to compare histological changes caused by diabetes and pregnancy in the RAM of humans and rats. The characteristics of muscle overload in rats (i.e., weight gain and fetal weight) and women (i.e., weight gain and baby weight) did not show any statistical differences, suggesting that the changes observed are related only to the hyperglycemic status. Previous studies showed that diabetes could cause skeletal muscle fibers to become atrophic, leading to a loss of muscle mass [42, 43].

Our findings revealed that among patterns of pregnant diabetic myopathy in rats and women, diabetes during pregnancy significantly impacted the structural characteristics of the RAM tissue. Despite this, the number of dominant fast fiber number in RAM samples was similar in women and rats, regardless of diabetes and pregnancy. Our results showed that diabetes during pregnancy modify the RAM fiber type number and decrease the fast fiber area. Moreover, in rats, no change in the collagen area was observed between the MHP and non-MHP groups. Together these findings demonstrate that RAM exposed to a diabetic environment is characterized by a decrease in the number and area of the fast fiber and an increase in the number of slow fibers. Although MHP and GDM showed similar changes in the fast fiber number, fast fiber area, and slow fiber number, the collagen area in GDM showed a decrease. Taken together, our results demonstrate that RAM is vulnerable to histological architecture changes due to GDM in humans. The alterations in the muscle fiber pattern of RAM could influence its functionality both in GDM or MHP rats.

Skeletal muscle atrophy is a complex molecular process that is not entirely understood. Reduced muscle fiber number and/or size is associated with a decrease in muscle function and can be caused by age [44], disuse [45] and illness [46]. Strong evidence suggests that diabetes is associated with muscular changes such as reduced muscle strength [47], power [48], mass [49], quality [48], and endurance and fiber type switch [6, 50] termed as diabetic myopathy [6, 51]. Our findings show that in the hyperglycemic environment, skeletal muscle in both rats and women decrease the number and area of fast fibers and an increase in the number of slow fibers. Diabetes is characterized by a fast-to-slow fiber type shift with preferential atrophy of fast glycolytic muscle fibers. The reason for the increase in the number of slow fibers in diabetes is currently unknown. Studies suggest that slow fibers have a stronger influence on muscle insulin action and glucose handling capacity [52]. This might be related to a compensatory response of skeletal muscle due to hyperglycemia to regulate metabolic homeostasis. Slow fiber type has a higher turnover of protein synthesis and degradation, an oxidative profile with larger mitochondrial content, higher myoglobin, increased insulin sensitivity, and a higher GLUT4 expression compared to fast fiber [52, 53]. Similar changes are seen in cancer cachexia [54], aging-related sarcopenia [55], and Huntington's Disease [56]. The differences in the slow fiber area between the MHP (rat) and GDM (human) groups may be due to the relatively short pregnancy time and the higher number of fetuses in the rats and high weight gain in the humans.

Collagen is the major structural component of the skeletal muscle ECM [9]. ECM is highly adaptavite and, therefore, capable of remodeling in response to physiological stimuli or disease [9]. Studies have shown that during late-pregnancy in rats, there are marked alterations in ECM components in the pelvic floor muscles [57], RAM [21], and vagina [58]. These passive mechanical structures undergo significant maternal adaptations during pregnancy in preparation for parturition and birth [59]. Previous studies show that diabetes is characterized by an increase in muscle collagen [60, 61]. According to Kang [62], the inflammatory response associated with insulin resistance has extensive effects on increased collagen deposition and ECM remodeling. Although we hypothesized that pregnancy-associated with diabetes would result in fibrosis, in our results, the distribution of muscle collagen in rats and humans showed different trends—in rats, there was no change in the collagen area while in humans, a significant decrease in collagen was observed. It is not known whether the decrease in collagen observed in our studies was due to a decrease in synthesis, an increase in collagen degradation or the excessive muscle stretching caused by pregnancy. Although pregnancy and diabetes are known to cause muscle fibrosis independent of each other, we speculate that they occur together in a muscle during pregnancy causing substantial muscle strain altering the various factors associated with collagen synthesis. However, further studies are necessary to understand the effect of diabetes and pregnancy on the distribution of collagen in the muscle fibers.

The RAM of rats during pregnancy undergo adaptations that change muscle architecture to facilitate fetal delivery [23]. However, diabetes affects the abdominal muscle substantially. Previous studies found that GDM causes alterations of important mediators of insulin resistance and inflammation [63, 64] in tissues of the abdominal wall obtained during C-section. Whether these alterations persist after delivery is unknown. These relationships deserve further attention as they may represent implications on the effectiveness of interventions on treatment and prevention of GDM consequences.

An ideal animal model for GDM research has not been established yet. Our results showing differences and similarities between GDM in humans and the MHP rats suggest that the MHP rats could be used as a preliminary prototype model for future research in the field of diabetic myopathy and the development of new therapeutical approaches. Accurate histopathological diagnosis and identification of the underlying mechanisms leading to skeletal muscle changes caused by GDM would result in a better understanding of the disease and development of new personalized patient management strategies.

One limitation of this study is the use of a quadrupedal animal model that differs from humans with respect to the effect of gravity on the biomechanics of RAM and the size and number of fetuses. However, our animal model provides the opportunity to test hypotheses more rigorously in a controlled environment. Rodents are attractive animal models because it is possible to work with large numbers of rodents in a cost-effective manner. Moreover, the pregnancy period in rodents is only 21 to 23 days [65]. In addition, the morphology and architecture of the abdominal wall of rats are similar to that of humans [29]. In this study, we present an animal model that is comparable with the glycemic levels of GDM in women and may, therefore, be applicable for future research on the molecular mechanism of GDM pathogenesis and for developing novel therapeutic approaches for GDM and UI.


The present study is the first to show that RAM fast fiber predominance is preserved in GDM women and MHP rats. Furthermore, our results demonstrate that RAM slow fiber and collagen are decreased in GDM. However, no changes in collagen patterns were detected in RAM samples of MHP rats. The comparison of skeletal muscle fibers between GDM women and MHP rats revealed that both underwent similar profound architectural changes, suggesting that they might have a comparable functional change in response to diabetes and pregnancy.

Supporting information

S1 Table. Mean SD values of morphological analysis in the study (Part A).


S2 Table. Mean SD values of morphological analysis in the study (Part B).



The study was supported by the human resources and infrastructure of PDRC- Botucatu Medical School-UNESP. The authors thank Talisia Moretto and Gelson Rodrigues for techinical assistance.

**The Diamater Study Group: Rudge MVC (Universidade Estadual Paulista), Barbosa AMP (Universidade Estadual Paulista), Calderon IMP (Universidade Estadual Paulista), Souza FP (Universidade Estadual Paulista), Hijas A (Case Western Reserve University), Sobrevia L (Pontificia Universidad Catolica de Chile), Palma MS (Universidade Estadual Paulista), Graeff CFO (Universidade Estadual Paulista), Arni RK (Universidade Estadual Paulista), Herculano RD (Universidade Estadual Paulista), Salvadori DF (Universidade Estadual Paulista), Matheus S (Universidade Estadual Paulista), Dal Pai Silva M (Universidade Estadual Paulista), Magalhães CG (Universidade Estadual Paulista), Costa RA (Universidade Estadual Paulista), Lima SAM (Universidade Estadual Paulista), Emanueli C (Imperial College London), Felisbino S (Universidade Estadual Paulista), Barbosa W (Universidade Estadual Paulista), Atallah A (Universidade Federal de São Paulo), Girão MJB (Universidade Federal de São Paulo), Di Bella Z (Universidade Federal de São Paulo), Uchoa SM (Universidade Católica de Pernambuco), Payão S (Faculdade de Medicina de Marília), Berghman B (Maastrich University), De Bie R (Maastrich University), Junginger B (Charité Universitätsmedizin Berlin), Alves FCB (Universidade Estadual Paulista), Rossignoli PS (Universidade Estadual Paulista), Abbade J (Universidade Estadual Paulista), Prudencio CB (Universidade Estadual Paulista), Orlandi MIG (Universidade Estadual Paulista), Gonçalves MI (Universidade Estadual Paulista), Nunes SK (Universidade Estadual Paulista), Catinelli BB (Universidade Estadual Paulista), Sarmento BV (Universidade Estadual Paulista), Pinheiro FA (Universidade Estadual Paulista), Sartorão CI (Universidade Estadual Paulista), Quiroz SBCV (Universidade Estadual Paulista), Reyes DRA (Universidade Estadual Paulista), Enriquez EMA (Universidade Estadual Paulista), Oliveira RG (Universidade Estadual Paulista), Floriano JF (Universidade Estadual Paulista), Marcondes JPC (Universidade Estadual Paulista), Costa SMB (Universidade Estadual Paulista), Dangió TD (Universidade Estadual Paulista), Pascon T (Universidade Estadual Paulista), Hallur LSR (Universidade Estadual Paulista), Melo JVF (Universidade Estadual Paulista), Takano L (Universidade Estadual Paulista), Reis FVDS (Universidade Estadual Paulista), Caldeirão TD (Universidade Estadual Paulista), Carr AM (Universidade Estadual Paulista), Garcia GA (Universidade Estadual Paulista), Rabadan GB (Universidade Estadual Paulista), Bassin HCM (Faculdade de Medicina de Marília), Suyama KS (Universidade Estadual Paulista), Damasceno LN (Universidade Estadual Paulista), Takemoto MLS (Universidade Estadual Paulista), Menezes MD (Universidade Estadual Paulista), Bussaneli DG (Universidade Estadual Paulista), Nogueira, VKC (Universidade Estadual Paulista), Lima PR (Universidade Estadual Paulista), Lourenço IO (Universidade Estadual Paulista), Marostica de Sá J (Universidade Estadual Paulista), Megid RA (Universidade Estadual Paulista), Caruso IP (Universidade Estadual Paulista), Rasmussen LT (Faculdade de Medicina de Marília), Prata GM (Universidade do Sagrado Coração), Piculo F (Faculdades Integradas de Bauru), Vesentini G (Universidade Estadual Paulista), Arantes MA (Universidade Estadual Paulista), Ferraz GAR (Universidade Estadual Paulista), Camargo LP (Universidade Estadual Paulista), Kron MR (Universidade Estadual Paulista), Corrente JE (Universidade Estadual Paulista), Nunes HRC (Universidade Estadual Paulista).

Lead author for The Diameter Study group: Rudge, MVC; Universidade Estadual Paulista (E-mail:


  1. 1. Bellamy L, Casas JP, Hingorani AD, Williams D. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet. 2009;373(9677):1773–9. pmid:19465232
  2. 2. Baz B, Riveline JP, Gautier JF. Endocrinology of pregnancy: Gestational diabetes mellitus: definition, aetiological and clinical aspects. Eur J Endocrinol. 2016;174(2):R43–51. pmid:26431552
  3. 3. American Diabetes A. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2019. Diabetes care. 2019;42(Suppl 1):S13–S28.
  4. 4. D'Souza DM, Al-Sajee D, Hawke TJ. Diabetic myopathy: impact of diabetes mellitus on skeletal muscle progenitor cells. Front Physiol. 2013;4:379. pmid:24391596
  5. 5. Hernandez-Ochoa EO, Vanegas C. Diabetic Myopathy and Mechanisms of Disease. Biochem Pharmacol (Los Angel). 2015;4(5).
  6. 6. Krause MP, Riddell MC, Gordon CS, Imam SA, Cafarelli E, Hawke TJ. Diabetic myopathy differs between Ins2Akita+/- and streptozotocin-induced Type 1 diabetic models. J Appl Physiol (1985). 2009;106(5):1650–9.
  7. 7. Johnson MA, Polgar J, Weightman D, Appleton D. Data on the distribution of fibre types in thirty-six human muscles. An autopsy study. J Neurol Sci. 1973;18(1):111–29. pmid:4120482
  8. 8. Billeter R, Weber H, Lutz H, Howald H, Eppenberger HM, Jenny E. Myosin types in human skeletal muscle fibers. Histochemistry. 1980;65(3):249–59. pmid:6445347
  9. 9. Gillies AR, Lieber RL. Structure and function of the skeletal muscle extracellular matrix. Muscle Nerve. 2011;44(3):318–31. pmid:21949456
  10. 10. DeFronzo RA, Jacot E, Jequier E, Maeder E, Wahren J, Felber JP. The effect of insulin on the disposal of intravenous glucose. Results from indirect calorimetry and hepatic and femoral venous catheterization. Diabetes. 1981;30(12):1000–7. pmid:7030826
  11. 11. Blumer I, Hadar E, Hadden DR, Jovanovic L, Mestman JH, Murad MH, et al. Diabetes and pregnancy: an endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2013;98(11):4227–49. pmid:24194617
  12. 12. Horvath K, Koch K, Jeitler K, Matyas E, Bender R, Bastian H, et al. Effects of treatment in women with gestational diabetes mellitus: systematic review and meta-analysis. BMJ. 2010;340:c1395. pmid:20360215
  13. 13. Kim C, McEwen LN, Sarma AV, Piette JD, Herman WH. Stress urinary incontinence in women with a history of gestational diabetes mellitus. J Womens Health (Larchmt). 2008;17(5):783–92.
  14. 14. Barbosa AM, Dias A, Marini G, Calderon IM, Witkin S, Rudge MV. Urinary incontinence and vaginal squeeze pressure two years post-cesarean delivery in primiparous women with previous gestational diabetes mellitus. Clinics (Sao Paulo). 2011;66(8):1341–6.
  15. 15. Chuang CM, Lin IF, Horng HC, Hsiao YH, Shyu IL, Chou P. The impact of gestational diabetes mellitus on postpartum urinary incontinence: a longitudinal cohort study on singleton pregnancies. BJOG. 2012;119(11):1334–43. pmid:22901044
  16. 16. Damasceno DC, Netto AO, Iessi IL, Gallego FQ, Corvino SB, Dallaqua B, et al. Streptozotocin-induced diabetes models: pathophysiological mechanisms and fetal outcomes. Biomed Res Int. 2014;2014:819065. pmid:24977161
  17. 17. Marini G, Piculo F, Vesentini G, Barbosa AM, Damasceno DC, Matheus SM, et al. Effects of short-term severe and long-term mild STZ-induced diabetes in urethral tissue of female rats. Neurourol Urodyn. 2017;36(3):574–9. pmid:26949929
  18. 18. Marini G, Piculo F, Vesentini G, Damasceno DC, Delella FK, Calderon IMP, et al. The influence of hyperglycemia on the remodeling of urethral connective tissue in pregnant rats. Eur J Obstet Gynecol Reprod Biol. 2018;221:81–8. pmid:29275277
  19. 19. Marini G, Barbosa AMP, Damasceno D, Matheus SMM, Castro RA, Girão MJBC, et al. Morphological changes in the fast vs slow fiber profiles of the urethras of diabetic pregnant rats. Urogynaecologia. 2011;25:31–6.
  20. 20. Piculo F, Marini G, Barbosa AM, Damasceno DC, Matheus SM, Felisbino SL, et al. Urethral striated muscle and extracellular matrix morphological characteristics among mildly diabetic pregnant rats: translational approach. Int Urogynecol J. 2014;25(3):403–15. pmid:24043129
  21. 21. Vesentini G, Marini G, Piculo F, Damasceno DC, Matheus SMM, Felisbino SL, et al. Morphological changes in rat rectus abdominis muscle induced by diabetes and pregnancy. Braz J Med Biol Res. 2018;51(4):e7035. pmid:29513796
  22. 22. Eleazu CO, Eleazu KC, Chukwuma S, Essien UN. Review of the mechanism of cell death resulting from streptozotocin challenge in experimental animals, its practical use and potential risk to humans. J Diabetes Metab Disord. 2013;12(1):60. pmid:24364898
  23. 23. Martin WD. A study of the effect of pregnancy on muscle fibers of the rectus abdominis muscle of the rat. Anat Rec. 1979;195(3):455–62. pmid:159648
  24. 24. Vesentini G, El Dib R, Righesso LAR, Piculo F, Marini G, Ferraz GAR, et al. Pelvic floor and abdominal muscle cocontraction in women with and without pelvic floor dysfunction: a systematic review and meta-analysis. Clinics (Sao Paulo). 2019;74:e1319.
  25. 25. Sapsford RR, Hodges PW. Contraction of the pelvic floor muscles during abdominal maneuvers. Arch Phys Med Rehabil. 2001;82(8):1081–8. pmid:11494188
  26. 26. Dumoulin C, Tang A, Pontbriand-Drolet S, Madill SJ, Morin M. Pelvic floor morphometry: a predictor of success of pelvic floor muscle training for women with stress and mixed urinary incontinence. Int Urogynecol J. 2017;28(8):1233–9. pmid:28083712
  27. 27. Hilde G, Staer-Jensen J, Siafarikas F, Engh ME, Braekken IH, Bo K. Impact of childbirth and mode of delivery on vaginal resting pressure and on pelvic floor muscle strength and endurance. Am J Obstet Gynecol. 2013;208(1):50 e1–7.
  28. 28. Sheng Y, Liu X, Low LK, Ashton-Miller JA, Miller JM. Association of Pubovisceral Muscle Tear with Functional Capacity of Urethral Closure: Evaluating Maternal Recovery from Labor and Delivery: Pubovisceral Muscle Tear and Urethral Closure Pressure. Am J Obstet Gynecol. 2019.
  29. 29. Brown SH, Banuelos K, Ward SR, Lieber RL. Architectural and morphological assessment of rat abdominal wall muscles: comparison for use as a human model. J Anat. 2010;217(3):196–202. pmid:20646108
  30. 30. Iessi IL, Bueno A, Sinzato YK, Taylor KN, Rudge MV, Damasceno DC. Evaluation of neonatally-induced mild diabetes in rats: Maternal and fetal repercussions. Diabetol Metab Syndr. 2010;2(1):37. pmid:20529353
  31. 31. Gallego FQ, Sinzato YK, Miranda CA, Iessi IL, Dallaqua B, Volpato GT, et al. Pancreatic islet response to diabetes during pregnancy in rats. Life Sci. 2018;214:1–10. pmid:30366036
  32. 32. American Diabetes A. Diagnosis and classification of diabetes mellitus. Diabetes care. 2011;34 Suppl 1:S62–9. pmid:21193628
  33. 33. International Association of D, Pregnancy Study Groups Consensus P, Metzger E, Gabbe SG, Persson B, Buchanan TA, et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes care. 2010;33(3):676–82. pmid:20190296
  34. 34. Tai MM. A mathematical model for the determination of total area under glucose tolerance and other metabolic curves. Diabetes care. 1994;17(2):152–4. pmid:8137688
  35. 35. Sacks DA, Black MH, Li X, Montoro MN, Lawrence JM. Adverse Pregnancy Outcomes Using The International Association of the Diabetes and Pregnancy Study Groups Criteria: Glycemic Thresholds and Associated Risks. Obstet Gynecol. 2015;126(1):67–73. pmid:26241258
  36. 36. Varner MW, Rice MM, Landon MB, Casey BM, Reddy UM, Wapner RJ, et al. Pregnancies After the Diagnosis of Mild Gestational Diabetes Mellitus and Risk of Cardiometabolic Disorders. Obstet Gynecol. 2017;129(2):273–80. pmid:28079773
  37. 37. Waters TP, Dyer AR, Scholtens DM, Dooley SL, Herer E, Lowe LP, et al. Maternal and Neonatal Morbidity for Women Who Would Be Added to the Diagnosis of GDM Using IADPSG Criteria: A Secondary Analysis of the Hyperglycemia and Adverse Pregnancy Outcome Study. Diabetes care. 2016;39(12):2204–10. pmid:27634392
  38. 38. Hod M, Merlob P, Friedman S, Schoenfeld A, Ovadia J. Gestational diabetes mellitus. A survey of perinatal complications in the 1980s. Diabetes. 1991;40 Suppl 2:74–8. pmid:1748270
  39. 39. Alwan N, Tuffnell DJ, West J. Treatments for gestational diabetes. Cochrane Database Syst Rev. 2009(3):CD003395. pmid:19588341
  40. 40. American Diabetes A. 14. Management of Diabetes in Pregnancy: Standards of Medical Care in Diabetes-2019. Diabetes care. 2019;42(Suppl 1):S165–S72. pmid:30559240
  41. 41. (2018) NIfHaCE. 2018 surveillance of diabetes in pregnancy: management from preconception to the postnatal period (NICE Guideline NG3). 2018.
  42. 42. Cohen S, Nathan JA, Goldberg AL. Muscle wasting in disease: molecular mechanisms and promising therapies. Nat Rev Drug Discov. 2015;14(1):58–74. pmid:25549588
  43. 43. Dumitru A, Radu BM, Radu M, Cretoiu SM. Muscle Changes During Atrophy. Adv Exp Med Biology. 2018;1088:73–92.
  44. 44. Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet. 2019.
  45. 45. Wall BT, Dirks ML, Snijders T, Senden JM, Dolmans J, van Loon LJ. Substantial skeletal muscle loss occurs during only 5 days of disuse. Acta Physiol (Oxf). 2014;210(3):600–11.
  46. 46. Peterson SJ, Braunschweig CA. Prevalence of Sarcopenia and Associated Outcomes in the Clinical Setting. Nutr Clin Pract. 2016;31(1):40–8. pmid:26703961
  47. 47. Andersen H, Schmitz O, Nielsen S. Decreased isometric muscle strength after acute hyperglycaemia in Type 1 diabetic patients. Diabet Med. 2005;22(10):1401–7. pmid:16176203
  48. 48. Volpato S, Bianchi L, Lauretani F, Lauretani F, Bandinelli S, Guralnik JM, et al. Role of muscle mass and muscle quality in the association between diabetes and gait speed. Diabetes care. 2012;35(8):1672–9. pmid:22596176
  49. 49. Sugimoto K, Tabara Y, Ikegami H, Takata Y, Kamide K, Ikezoe T, et al. Hyperglycemia in non-obese patients with type 2 diabetes is associated with low muscle mass: The Multicenter Study for Clarifying Evidence for Sarcopenia in Patients with Diabetes Mellitus. J Diabetes Investig. 2019. pmid:31074209
  50. 50. Armstrong RB, Gollnick PD, Ianuzzo CD. Histochemical properties of skeletal muscle fibers in streptozotocin-diabetic rats. Cell Tissue Res. 1975;162(3):387–94. pmid:126806
  51. 51. Andersen H, Gadeberg PC, Brock B, Jakobsen J. Muscular atrophy in diabetic neuropathy: a stereological magnetic resonance imaging study. Diabetologia. 1997;40(9):1062–9. pmid:9300243
  52. 52. Albers PH, Pedersen AJ, Birk JB, Kristensen DE, Vind BF, Baba O, et al. Human muscle fiber type-specific insulin signaling: impact of obesity and type 2 diabetes. Diabetes. 2015;64(2):485–97. pmid:25187364
  53. 53. Olsson AH, Ronn T, Elgzyri T, Hansson O, Eriksson KF, Groop L, et al. The expression of myosin heavy chain (MHC) genes in human skeletal muscle is related to metabolic characteristics involved in the pathogenesis of type 2 diabetes. Mol Genet Metab. 2011;103(3):275–81. pmid:21470888
  54. 54. Acharyya S, Butchbach ME, Sahenk Z, Wang H, Saji M, Carathers M, et al. Dystrophin glycoprotein complex dysfunction: a regulatory link between muscular dystrophy and cancer cachexia. Cancer cell. 2005;8(5):421–32. pmid:16286249
  55. 55. Nilwik R, Snijders T, Leenders M, Groen BB, van Kranenburg J, Verdijk LB, et al. The decline in skeletal muscle mass with aging is mainly attributed to a reduction in type II muscle fiber size. Exp Gerontol. 2013;48(5):492–8. pmid:23425621
  56. 56. Hering T, Braubach P, Landwehrmeyer GB, Lindenberg KS, Melzer W. Fast-to-Slow Transition of Skeletal Muscle Contractile Function and Corresponding Changes in Myosin Heavy and Light Chain Formation in the R6/2 Mouse Model of Huntington's Disease. PLoS One. 2016;11(11):e0166106. pmid:27820862
  57. 57. Alperin M, Lawley DM, Esparza MC, Lieber RL. Pregnancy-induced adaptations in the intrinsic structure of rat pelvic floor muscles. Am J Obstet Gynecol. 2015;213(2):191 e1–7.
  58. 58. Feola A, Moalli P, Alperin M, Duerr R, Gandley RE, Abramowitch S. Impact of pregnancy and vaginal delivery on the passive and active mechanics of the rat vagina. Ann Biomed Eng. 2011;39(1):549–58. pmid:20824342
  59. 59. Lowder JL, Debes KM, Moon DK, Howden N, Abramowitch SD, Moalli PA. Biomechanical adaptations of the rat vagina and supportive tissues in pregnancy to accommodate delivery. Obstet Gynecol. 2007;109(1):136–43. pmid:17197599
  60. 60. Richardson DK, Kashyap S, Bajaj M, Cusi K, Mandarino SJ, Finlayson J, et al. Lipid infusion decreases the expression of nuclear encoded mitochondrial genes and increases the expression of extracellular matrix genes in human skeletal muscle. J Biol Chem. 2005;280(11):10290–7. pmid:15598661
  61. 61. Berria R, Wang L, Richardson DK, Finlayson J, Belfort R, Pratipanawatr T, et al. Increased collagen content in insulin-resistant skeletal muscle. Am J Physiol Endocrinol Metab. 2006;290(3):E560–5. pmid:16249255
  62. 62. Kang L, Ayala JE, Lee-Young RS, Zhang Z, James FD, Neufer PD, et al. Diet-induced muscle insulin resistance is associated with extracellular matrix remodeling and interaction with integrin alpha2beta1 in mice. Diabetes. 2011;60(2):416–26. pmid:21270253
  63. 63. Liong S, Lappas M. Activation of AMPK improves inflammation and insulin resistance in adipose tissue and skeletal muscle from pregnant women. J Physiol Biochem. 2015;71(4):703–17. pmid:26407807
  64. 64. Liong S, Lappas M. Endoplasmic reticulum stress regulates inflammation and insulin resistance in skeletal muscle from pregnant women. Mol Cell Endocrinol. 2016;425:11–25. pmid:26902174
  65. 65. Abramowitch SD, Feola A, Jallah Z, Moalli PA. Tissue mechanics, animal models, and pelvic organ prolapse: a review. Eur J Obstet Gynecol Reprod Biol. 2009;144 Suppl 1:S146–58. pmid:19285776