Introduction
Angiogenesis is responsible for formation, development and maintenance of vascular tissue in corpus luteum, which in turn regulates the luteal functions during early pregnancy or second phase of menstrual cycle. Several integrated parameters regulate luteogenesis. Broadly, we can classify the process in three time scales. From early to the middle luteal phase, blood vessels are formed and stabilized and perivascular cells, also known as pericytes, increase in number.
In the absence of pregnancy, luteal regression takes place, resulting in degeneration of blood vessels and decrease in number of pericytes. In the event of pregnancy, angiogenesis continues further resulting in better stabilization of blood vessels in and corpus luteum, and sustained production of progesterone and oestrogen. The process of formation, stabilization and regression (degeneration) of vasiculator in corpus luteum involves interactive influence of hormonal and other protein factors, whose nature and functions are still not very clearly deciphered (Sugino et al. 2008).
Structural, biochemical and physiological investigations of angiogenesis need to be supported by mathematical modelling, especially using the variables and parameters like amounts and rates of production and loss of hormones, and protein factors regulating vasiculation. Such models are available for many complex physiological processes, e.g. pituitary-ovarian hormonal interaction at pre-ovulatory phase (Shack et al. 1971), and needs to be extended for corpus luteum development and regression. The regulation of angiogenesis can lead to regulation of pregnancies and therefore modulating the factors can improve the reproductive performances.
One of the reasons for luteal phase defect could be premature regression of corpus luteum, leading to poor progesterone production, resulting in infertility or frequent abortions. The drugs averting this problem can be developed which would help improvised blood supply to corpus luteum, thus ensuring supply of nutrients and release of hormones.
The development of new blood vessels in ovary is necessary to ensure adequate supply of nutrients and hormones related to follicular growth and formation of corpus luteum. In the short spell of corpus luteum growth, the capillary undergoes growth, maturation and subsequently degeneration (O’Shea et al. 1977). Hyperplasia and hypertrophy are commonly observed in arterial blood vessels during luteal regression (degeneration) phase.
During development stages of corpus luteum, number of non-capillary vessels increases accompanied with proliferation of smooth muscle cells. Consequently, as the capillaries start to degenerate during regression phase, the arterial blood vessels thicken due to accumulation of collagenous and elastic fibres, a process known as fibroelastosis (Bauer et al. 2004). One of the crucial parameters in testing the vascular impedance in any tissue is a pair of indices known as resistance index (RI) and pulsatility index (PI).
RI = (systolic peak – diastolic peak) / systolic peak, representing the highest resistance to forward flow, whereas PI = (systolic peak – diastolic peak) / mean flow velocity (Schwarz et al. 1998). These indices are highly useful in disease prognosis related to vascular artefacts. A healthy woman with normal luteal function would have low mid-luteal RI as compared to the patients with luteal defects. This attribute helps in diagnosing gastration problems and can provide warnings associated with pregnancies (Salim et al. 1994).
During follicular phase usually PI stays high and as luteal vascularization intensifies the diastolic pressure increases resulting in lowering in RI and PI values, typically known as Doppler waveforms. An inverse correlation is established between PI and volume density of blood vessels and therefore utrasonographic data can possibly be extrapolated as anatomical measures of vascular system. This indicates rapidly change once follicular to luteal stage is approached. Unhealthy ovary can be represented as continuously low RI/PI values.
In the early to middle luteal phase there is an up-regulation of blood vessel stabilizing protein, called angiopoietin (Ang)-1 and -2 and their receptors, Tie-2 (Wulff et al. 2000). The pre-existing endothelial cells of developing follicles later form the vascular system of corpus luteum. Some Angiogenesis-growth factors viz., vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (bFGF) make vessels more permeable to the nutrients and hormones, thus facilitating follicle rupture and subsequent organization of luteal vessels (Schams & Berisha 2002). However, following ovulation this attribute reverses.
There are many theories related to the cause of such degeneration. The capillaries and small venules during regression accumulate degenerated cells, remnants of nucleus and cytoplasm, and immotile blood cells. The degenerating endothelial cells and pericytes undergo structural changes prior to degeneration, namely folding of basal lamina, more intercellular gaps in endothelial lining, inclusion of autophagic vacuoles etc. which manifests as decay in vessels.
Macrophages reportedly invade the corpus luteum. A diagnostic protein called monocyte chemotactic protein-1 (MCP-1) is shown to be highly expressed at this stage, particularly on the surface of blood vessels attracting the macrophages (Senturk et al. 1999). Another hypothesis is that the endothelial cells and pericytes undergo prostaglandin-mediated apoptosis leading to self-destruction. Reports suggest the Prostaglandin F2α released into blood brings about an intracellular suppression of VEGF transcript / protein expression which could be a reason for luteolysis (Wang et al 2003).
The following methods are to be adopted for the investigation –
In vivo measurements of vascular indices
These experiments can be performed on experimental animals. Several known modulators that may affect
- vascular system viz. vasodilatory compounds,
- hormones and
- other stimulators/inhibitors of luteal cycle can be administered through intraperitoneal route and the indices that decide the condition of luteal vasiculation can be examined.
The doses and length of incubation can be decided depending on the preliminary test results.
The most fundamental indices should be RI and PI, which directly corresponds to blood supply to corpus luteum. The Intra-ovarian Doppler Ultrasound method rely on the fact that the sound waves from a transducer is reflected back and their frequency travels proportionate to velocity of blood cells in the vessels. Consequently, peak values of diastolic and systolic pressure can be measured in localized vascular network (Argollo et al. 2006).
High RI represents vascular constriction or low blood flow velocity, whereas low RI corresponds to vasodialation. First, luteal cycle should be established in controls and treatments based on calculating urinary LH levels. After predicting the onset of corpus luteum growth and regeneration, the RI/PI of ovarian vascular network can be periodically measured. Upon computing the data it is possible to predict the in vivo effect of blood flow modulators on vessel parameters directly affecting luteal development and regression.
At appropriate times, corpus luteum can be excised surgically using digital slide calliper, and volume density (percentage of corpus luteum occupied by blood vessels) can be estimated by factor VIII-related immunostaining of endothelial cells (Ottander et al. 2004). These vascularization parameters can establish the functional impact of vasomodulators on luteal cycle.
Examination of protein factors and hormones regulating luteal cycle
It would be necessary to examine whether one or many interacting factors contribute to the cycle and whether their impact is affected by vaso- or other modulators. For this, an appropriate method is Terminal Transferase dUTP Nick End Labeling (TUNEL) assay used to detect DNA degradation in apoptotic cells (Wang et al 2003). The luteolysis can be attributed to self-destruction. It would be interesting to observe whether the modulators accelerate or decelerate the process.
After recognizing the right treatments the molecular basis of apoptosis can be elucidated. First, density of vessels and pericytes can be determined using immunohistochemistry/immunofluorescence of cell-specific surface glycoprotein, CD34, and α-smooth muscle actin. For assessing the interactive role of the modulators and VEGF/ bFGF in luteal promotion and of MCP-1 / Prostaglandin F2α in reversion of the action during regression, their relative expression / amounts will be examined at every stage of the cycle. VEGF expression can be seen at mRNA expression level using specific primer sets and by applying Northern blot technique (Schams & Berisha 2002).
MCP-1 detection is possible using antisera raised against this protein and macrophages, as also by immunohistochemistry/immunofluorescence techniques. Alternatively, it is possible to apply Northern blot methods to see MCP-1 mRNA transcript size (Senturk et al. 1999). All these factors eventually lead us to determine the stability and fragileness of the blood vessels supplying corpus luteum.
In corpus luteum enzymes converting cholesterol to progesterone, namely cholesterol ester synthetase, esterase, desmolase, Δ-5, 3β-steroid dehydrogenase, and for transforming progesterone to inactive 20αOH derivative are present (Talwar & Srivastava 2003). Some of these enzymes are under control of hormones (LH, prolactin) mediating through transmembrane receptors, the G protein and cAMP. It would be interesting to examine the relative enzyme levels under above treatment in luteal extracts. The net serum progesterone content should also be estimated. If possible, procedures to detect receptors and intracellular cAMP can be applied to elucidate the modification in signal transduction eventually controlling progesterone systhesis.
In vitro assays on luteal tissues and endothelial cells
The hormonal role of progesterone is quite established but it has been also shown to influence luteal function, primarily by regulating prostaglandin E2 synthesis. An in vitro test system could be established, in which corpus lutea pieces can be excised and grown on Dulbecco’s Modified Eagle’s medium and Ham’s F-12 medium with serum albumin and gentamycin (Ferreira-Dias et al. 2006). Once established in tissue culture, endothelial cell proliferation spontaneously occurs.
The effect of different hormones and other vasomodulators can now be tested on promotion of endothelial cell proliferation activity. Such proliferation is most likely a mimic of in vivo luteal vasiculation. Therefore, upon addition a delay or advancement of, or extent of proliferation can be extrapolated as mediator’s effect on luteal cycle. Progesterone has been shown to increase prostaglandin and NO synthesis and this mediates the slowing of endothelial proliferation.
Another in vitro system that can be used is isolated and cultivated microvascular endothelial cells (cell culture) originating from corpus luteum (Christenson & Stouffer 1996). For this, lutea can be minced and enzymatically digested to get cell suspension. Endothelial cells can be separated by using magnetic beads labelled with lectin, a kind of agglutinin. Agglutinin binds to the sugars present on endothelial cells and can be separated in magnetic field.
Antiserum raised against platelet/endothelial cell adhesion molecule-1, can serve as detection antibody. The cells can be grown in Dulbecco’s Eagle’s modified medium or McCoy’s 5A medium in presence of serum. Under appropriate conditions, the proliferation can be induced. Here also, the effect of various modulators can be examined on proliferation process simply by adding the compounds in tissue / cell culture media.
Mathematical modelling of corpus luteum growth
Models can be formulated at macro- and micro-level. The determinable variables like RI / PI, and serum LH, FSH, PROG, EST etc. can be treated as macro-level variables. For the cellular models, luteal regulatory molecules viz. VEGF and Prostaglandin F2α and LH receptors, cAMP, enzymes etc. can be taken into account to simulate corpus luteum progression, regression and function. The ordinary differential equations for FSH and LH are as follows (Shack et al. 1971):
d(FSH)/dt = FSHT – CL1FSH – EST1 – PROG1 + d(SFSH)/dt(i)
d(LH)/dt = LHT – CL2LH – EST2 – PROG2 + d(SLH)/dt(ii)
Rate of hormone production equals to the tonic production minus the clearance rates and negative feedback effects of estrogen and progesterone plus the surge contribution of the respective hormone.
Likewise, d(EST)/dt = ESTT – CL4EST + EST(FL) + EST(CPL)(iii)
d(PROG)/dt = PROGT – CL3PROG + PROG(CPL)(iv)
Hormone production of adrenal cortex (under script T), and corpus luteum (CPL) and follicle (FL) are summed and clearance is negated.
Angiogenesis and progesterone production are highly correlated and advanced models need to be established by taking into account other variables, e.g. LH stimulation of PROG synthesis (cellular cAMP level) and PROG → 20αOH derivative transformation, both would regulate PROG(CPL) at micro-level. The following considerations may apply:
- Binding of LH to receptors (RLH) results in formation of XLH complex;
- Activation of enzyme (E) Adenyl cyclase by XLH to Active form (ELH);
- Synthesis of cAMP by ELH from ATP and Mg2+; and
- Hydrolysis of cAMP to AMP.
Therefore equation (iv) can most likely be extended as:
dPROG(CPL)/dt = PROG(CPL) + cAMP(CPL) – d20αOHPROG(CPL)/dt (v)
Other factors stabilizing or degenerating corpus luteum and consequently affecting progesterone production, can also be brought into ordinary differential equations. Based on the net effect, logic charts can be prepared and decision can be taken whether ovulation will follow corpus luteum formation or not, and whether progesterone will be produced or not.
The proposed project may contribute to understand the effect of vasodilators and other blood vessel modulators on corpus luteum development, sustenance and regression. Further, the role of hormones and cellular factors finely tuning the vascular network can also be determined with precision. These investigations can be extended at tissue and cellular level and the large number of variables can be used for mathematical modelling so as to arrive to some logics.
References
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