Vol. 278, Issue 5, R1247-R1257, May 2000
Explicating hypergonadotropism in postmenopausal
women: a statistical model
Daniel M.
Keenan1 and
Johannes D.
Veldhuis2,3
1 Department of Statistics,
2 Division of Endocrinology, Health Sciences
Center, 3 National Science Foundation Center for
Biological Timing, University of Virginia, Charlottesville, Virginia
22908
 |
ABSTRACT |
Neurohormone secretion is viewed here as a variable
(unknown) admixture of basal and pulsatile release mechanisms,
convolved with individually fitted biexponential elimination kinetics.
This construct allows maximum-likelihood estimates of both (regulated and constitutive) components of hormone secretion. Thereby, we infer
that a prolonged slow-component half-life of gonadotropin removal and
amplified pulsatile (and total) daily luteinizing hormone (LH)
secretion rates jointly explicate the postmenopausal elevation in serum
LH concentrations without a necessary rise in basal LH secretion rates.
This biomathematical formulation should be useful in exploring other
neuroregulatory mechanisms that underlie single or dual alterations in
the basal versus pulsatile modes of hormone secretion.
gonadotropin; human; methods; statistics; age; analysis; luteinizing hormone
 |
INTRODUCTION |
IN VIVO AND IN VITRO STUDIES of endocrine glands
suggest the existence of two physiologically distinguishable modes of
regulated secretion, namely, time-invariant basal hormone secretion and secretagogue-driven pulsatile hormone release (15). The basal mode may
represent a constitutive, unregulated, or slowly varying hormone
release process (3, 12, 19, 34, 39, 40). In contrast, pulsatile
secretion likely reflects rapid exocytosis of previously accumulated
neurohormone (19, 43).
Pulsatile hormone release was recognized shortly after the development
of RIAs in the early 1970s. Subsequent studies revealed that, in some
cases, the magnitude and/or frequency of a pulse signal is critical to
its tissue actions; e.g., in the gonadotropin releasing
hormone-luteinizing hormone (GnRH-LH)-gonadal axis; for
insulin secretion and action; in the growth hormone-insulin-like growth
factor-I (GH-IGF-I) axis, and, for the actions of
parathyroid hormone (PTH), oxytocin, or glucagon (15, 17,
29, 31, 35, 36, 38, 41). In contrast, knowledge of the mechanisms underlying basal hormone secretion and its tissue impact has lagged considerably. Indeed, in the case of several hormones, such as GH,
physiological basal secretion was not demonstrable until the recent
emergence of ultrahigh-sensitivity assays (14). On the other hand,
apparently elevated basal hormone release is evident in various
neuroendocrine pathologies, such as GH, ACTH, and prolactin-secreting pituitary tumors (12) and aldosteronomas (39).
A variable admixture of basal and pulsatile secretion seems to typify
the release of some neurohormones, e.g., prolactin, GnRH during the
preovulatory LH surge, and PTH, wherein 30-70% of hormone release
appears to be nonpulsatile (10, 14, 23, 34).
Admixed basal and pulsatile hormone release also seems to characterize
feedback withdrawn states, e.g., hypersecretion of PTH in hypocalcemia
(34) or LH in response to testosterone withdrawal (49). Thus accurately
partitioning basal versus pulsatile hormone secretion, albeit
technically challenging (44, 47), should aid in separating normal
physiology (low basal release), pathophysiology (jointly increased
basal and pulsatile secretion), and pathology (elevated basal hormone
production). To date, reliable segmentation of basal versus pulsatile
release has been confounded technically by strong correlations among
hormone half-life and basal and pulsatile secretion rates (44, 47). A
recent step toward addressing this impasse is nonparametric or
waveform-free half-life-dependent deconvolution techniques (7, 16, 24),
which to date have received limited or no validated application to
extended hormone profiles. As an alternative strategy, here we
illustrate a physiologically motivated analytic construct that embodies
variably combined basal and pulsatile hormone release, random secretory
bursting, and fitted estimates of slow and fast half-lives.
 |
METHODOLOGY |
Overall model.
Our general formulation defines Z(t) as the
hormone secretion rate at time t (units for LH = IU · l
1 · min
1)
|
(1)
|
where
0 is the unknown basal secretion rate and
P(·) is the (nonconstant) pulsatile
secretion rate. As a disappearance model, we allow for a fast and slow
elimination component, where a and 1
a are their
respective proportions. In Ref. 21 we show that rate of change in the
blood hormone concentration [X(t)] is then described by differential equations, whose solution
is
|
(2)
|
Here, we add the consideration of biexponential fitting of both the
elimination process and estimation of each of three constructs of basal
secretion (
0). The three models are 1)
freely varying or analytically fitted
0 (F model,
above); 2) zero basal (Z model); 3) basal secretion
constrained a) to a known steady-state [C(SS) model] hormone
concentration (e.g., measured before experimental hormone injections)
or b) to a percentage of total secretion [C(
) model, where
is a literature-based population parameter (e.g.,
= 11% of
the LH concentration for men). If pulsatile secretion is eliminated
selectively in equation 2, then the steady-state hormone
concentration [X(t)] is the first term. To
indirectly estimate basal LH release in models 3a or
3b, we use data from earlier clinical experiments that used
GnRH agonists or antagonists to largely eliminate (GnRH stimulated) LH
pulses (6, 11, 30). First, we injected a GnRH agonist (leuprolide) to
achieve a low known rate of basal LH release, superimposed on which we infused known (pulsatile) amounts of recombinant LH. This experiment identified terms for construct C(SS) above, consisting of a known basal
LH. Second, we used our own and literature-based experiments with GnRH
antagonists that preferentially disable (GnRH stimulated) pulsatile LH
release, thus allowing estimates of (fractional) basal secretion:
construct C(
) above. In addition, on the basis of the published
biexponential kinetics of highly purified human LH in hypopituitary
volunteers (46), we further validated quantitative model recovery from
distribution volume estimates.
Clinical methods.
Serum immunoreactive LH concentration time series were obtained and
reported previously by sampling blood in healthy women at 10-min
intervals for 24 h, after provision of written informed consent
approved by the Human Investigation Committee (8, 32). Six volunteers
were studied in each of the following categories: for each of three
separate phases of the normal menstrual cycles [early follicular (EF),
late follicular (LF), and midluteal (MI) phases] and
estrogen-unreplaced postmenopausal women (ages 55-75). The ranges
of the intra- and interassay coefficients of variations in the LH
immunoradiometric assay (IRMA) are 4.5-8.3% and
6.8-10%, and assay sensitivity is 0.8 IU/l (First International
Reference Preparation).
As one biological validation strategy, we administered the GnRH
agonist, leuprolide acetate (3.75 mg im), to downregulate endogenous LH
release in five healthy men. Three weeks thereafter, volunteers
received intravenous bolus injections of human recombinant LH (Serono
Laboratories, Norwell, MA) at 2-h intervals. LH was infused at a fixed
dose of 7.5, 15, 30, 50, or 75 IU/pulse over 1 or 8 minutes for a total
of four to eight consecutive infusion pulses. Blood was withdrawn at
10-min intervals beginning immediately before the first infused LH
pulse (0800 clock time) and throughout the infusion until 3 h after the
last injection. Serum was later assayed for LH content by IRMA (above).
Preinjection serum testosterone concentrations were <85 ng/dl (2.5 nmol/l) during leuprolide-induced suppression of the gonadotropic axis.
 |
RESULTS |
In the five LH-suppressed men infused with variable but known amounts
of recombinant human LH, we estimated the several masses of LH infused
(known amounts were 7.5, 15, 30, 50 and 75 IU/pulse; Serono). To this
end, we applied each of the three separate formulations of
"basal" LH secretion: 1) freely varying or analytically
fitted (F model); 2) zero basal (Z model); 3a)
constrained by the preinjection steady-state [C(SS) model] measured
serum LH concentration or 3b) constrained by a percentage of
total secretion [C(11) model: e.g. 11% for men (30)]. For any model,
the calculated slope of the plot of infused LH dose (IU) versus
estimated LH pulse mass (IU/l) is the reciprocal of the LH distribution
volume, which was determined independently earlier (46). As illustrated
in Fig. 1, the slopes for the four models
predict LH distribution volumes of 3.7 (F model), 4.2 (Z model), 4.6 [C(SS) model], and 4.8 liters [C(11) model]. The values fall within
the estimated adult male range of 3-5 liters based on highly
purified human pituitary LH extracts (46), although this could vary
depending on LH isoforms and/or gender. The application of all four
models of freely varying, zero, and constrained (steady state and 11%) basal secretion is shown. Figure 2
illustrates that, in the experimentally known basal [C(SS)] model,
the second (slow)-component LH half-life is proportionate
(r = +0.93, P = 0.02) to the dose of recombinant human LH injected.

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Fig. 1.
Plots of linear fits of dose (mass) of recombinant human luteinizing
hormone (LH) injected (IU) vs. calculated mass (IU/l) of LH recovered
in 5 leuprolide-suppressed men given 1 or 8 min intravenous infusions
of 7.5, 15, 30, 50, or 75 IU of LH. LH distribution volume
(V0) is estimated by reciprocal of slope.
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Fig. 2.
Plots of mass of human recombinant LH infused vs. first (rapid)- or
second (slow)-phase LH half-lives (t1/2)
calculated for steady-state constrained (pre-LH injection) model of
basal LH secretion for experiment defined in Fig. 1. Linear regression
analyses are shown with corresponding correlation coefficients and
P values in 5 men evaluated.
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|
Serum LH time series in women sampled every 10 min over 24 h were
analyzed next according to the foregoing three formulations of basal
secretion: freely varying, zero, or constrained. On the basis of
earlier published GnRH antagonist studies in women, constrained basal
secretion rates (basal secretion as percentages of total secretion)
were taken as nominally 24% in premenopausal females (EF, LF, and ML,
respectively) and 34% in postmenopausal women (6, 11). ANOVA applied
to the resultant data revealed several major points summarized in Fig.
3, A-E, which shows
slow-component LH half-lives; LH pulse frequency; and daily basal,
pulsatile, and total LH secretory rates. Illustrative individual
women's data (parameter estimates with corresponding estimated SEs)
are given in Tables
1-3.





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Fig. 3.
Estimates of daily pulsatile LH secretion (A), slow-component
LH half-lives (B), daily basal (absolute) LH secretion
(C), daily total (pulsatile plus basal) LH secretion
(D), and LH pulse frequency (E) in individual
healthy premenopausal women studied in early follicular (EF), late
follicular (LF), or midluteal (ML) phases of menstrual cycle and
postmenopausal (PM) women. Data are means ± SE of separate estimates
for the 3 (or 2) principal models of basal LH secretion 1) zero
basal; 2) freely varying (fitted or analytically estimated);
and 3) constrained (residual LH secretion continuing after
gonadotropin-releasing hormone (GnRH)-antagonist administration;
namely, 24% in young and 34% in older women;
METHODOLOGY). Each woman underwent blood sampling at 10-min
intervals for 24 h beginning at 0800 (clock time). LH measures by IRMA
are IU/l (First International Reference Preparation). For each model,
P values were determined by ANOVA after logarithmic
transformation of data in 4 study groups. Different letters denote
significantly different means by post hoc testing by Duncan's
new multiple-range test.
|
|
An unexpected finding was a high within-subject agreement (low
variability) among estimates of LH pulse mass (and daily pulsatile LH
secretion) across the various basal-secretion models. For example, the
median (and range) coefficients of variation (SD/mean × 100%) among the four model-based estimates of LH burst mass within subjects were 3.2 (1.5-9.2%) in EF, 5.4 (3.8-14%) in LF, and 5.8 (2.3-16%) in ML phase young women and 4.5 (1.7-5.0%) in
postmenopausal women.
Second, according to all three models, daily pulsatile (and total) LH
secretion was maximal in postmenopausal women, and minimal in the ML
phase of the menstrual cycle (Fig 3A). Third, two-component LH half-life values fell within the published normal range in the
human, namely, for the (freely varying) rapid and slow components, respectively, 7-36 and 46-240 min (8, 46; Fig. 3B).
These estimates in women compare with (mean ± SD) values of 18 ± 5 and 90 ± 22 min reported earlier for rapid- and slow-phase LH
half-lives in four LH-injected hypopituitary men (46). The
corresponding LH half-life ranges were 7-25 (rapid phase) and
58-130 min (slow phase) in the C(SS) model using literature-based
GnRH-antagonist data to estimate the percentage basal.
In both non-zero basal models, the calculated percentage basal LH
secretion ranged absolutely from 1 to 54% within the four groups of
woman studied here (see Tables 1-3). In postmenopausal women,
percentage basal LH release (variable, analytically estimated) was
2-52%, similar to the values in younger women (1-54%). Thus (in the non-zero basal models) increased absolute basal LH secretion (but not greater fractional partitioning of basal versus pulsatile LH
release) characterized post (versus pre-)-menopausal women (Fig.
3C).
The highest daily total LH secretion rates (freely varying basal model)
were attained in older women (260-980
IU · l
1 · 24 h
1). The range of
values in LF phase premenopausal women was 47-850 IU · l
1 · 24 h
1, in the EF phase
was 63-140 IU · l
1 · 24 h
1,
and in ML phase was 25-150 IU · l
1 · 24
h
1 (Fig. 3D).
On the assumption of zero basal LH secretion (daily) LH pulse mass
estimates remained remarkably similar to those in the two other models
(freely varying vs. literature-constrained basal secretion). In the
zero basal model, estimated second-component LH half-lives also tended
(P = not significant by ANOVA, P < 0.05 by the
Kruskal-Wallis test) to be longer in postmenopausal women and shorter in ML phase young women (Fig. 3B).
Use of a literature-constrained (GnRH antagonist predicted) percentage
basal rate of LH secretion sometimes predicted lower basal secretion
than freely varying (fitted) estimates and lower slow-phase LH
half-lives than the zero basal model. The calculated daily LH pulse
mass was similar to those in the other two models (Fig. 3A).
Pulse frequency estimates were model independent and showed slowing
only in the ML phase (Fig. 3E).
Illustrative observed 24-h serum LH concentration profiles, calculated
(fitted) profiles, and estimated pulsatile and basal LH secretion
curves are given in Fig. 4 for each of the three different formulations of basal LH release. The individual profiles highlight 1) variability among menstrual contexts and
2) distinctions among the three analytic constructs of basal
(LH) secretion.

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Fig. 4.
Illustrative 24-h serum LH concentration profiles in 3 of 18 healthy
premenopausal women respectively, 1 individual in each of EF, LF, and
ML phases of menstrual cycle) and 1 of 6 PM individuals. There are 2 subpanels for EF, top left; LF, top right; ML,
bottom left; and PM, bottom right. Each pair of
subpanels shows measured and fitted serum LH concentrations obtained by
sampling every 10 min for 24 h beginning at 0800 (clock time) (top
line), as well as the model-calculated LH secretory rates
(bottom line). Three constructs of basal LH secretion are
illustrated by various interrupted lines: dotted, zero basal;
dashed-dotted, constrained basal; and dashed, freely varying basal
(METHODOLOGY).
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|
As a general modeling comment, which is applicable to Tables 2 and
3, for those parameters that describe the pulsatile
structure, mass accumulation (
0,
1),
pulse shape (
1,
2,
3),
and the variance of pulse mass random effects
(
2A), the
precision of their estimators is determined as much by the number of
pulses as by the actual number of observations. In Tables 2 and 3,
illustrating the individual parameter estimates for an EF female and a
postmenopausal female, the number of pulse times were 10 and 16, respectively. In Table 2, particularly, some of the (estimated) SEs are
large enough that several of the above parameters could not be
individually rejected from being zero. In part, this is the consequence
of allowing for the flexibility necessary for describing the broad
range of profiles encountered in practice; for example, sometimes two
of the three pulse shape parameters will suffice, but which two of the
three can vary among individuals, and, in some women, there appears to
be large basal secretion, whereas for others there is not. The modeling
implication of all of this is somewhat dependent on one's specific
goal. If the purpose is to find the most parsimonious model for a
particular individual, then one might attempt to eliminate potential
parameters in a manner analogous to stepwise regression. However, in
the present context, these structural parameters are, in some sense, more like nuisance parameters, whose importance rests in their combination allowing one to soundly estimate total daily pulsatile secretion and to assign a justified SE (Table 1). These resulting aggregates are in general well separated from zero.
 |
DISCUSSION |
We here present, validate, and then apply a random-effects and
maximum-likelihood methodology to evaluate hormone biexponential elimination and pulsatile and basal neurohormone secretion according to
different renditions of basal secretory behavior. This new analytic
formulation extends our earlier efforts by 1) delineating three
distinct possible notions of basal secretion; 2) implementing biexponential kinetics; 3) requiring independent biological
validation using recombinant human LH infusions; and 4)
analyzing full 24-h-long serum LH concentration profiles in women in
different menstrual contexts to clarify normal physiology. Indeed,
evaluating LH secretion in a relatively large cohort (n = 24)
of healthy pre- and postmenopausal women unmasked an unanticipated,
remarkably robust within-subject uniformity of estimates of LH
secretory burst mass across the three analytically distinct strategies
for defining basal gonadotropin release: 1) zero basal and thus
purely pulsatile LH secretion; 2) freely varying analytically
estimated basal LH secretion; or 3) constrained or putatively
non-GnRH-dependent basal LH release. In particular, in any given
menstrual context, the three structurally distinct assumptions
regarding basal LH secretion predicted a similar mean mass of LH
secreted in pulses for any woman. The median within-subject
coefficients of variation of estimated LH pulse mass among the three
models fell within the range of 3-6%. This primary observation
suggests the thesis that, for a fitted two-compartment LH elimination
process, the investigator's choice of a particular model of basal LH
secretion does not uniquely dictate the estimate of endogenous LH
secretory pulse mass. In accordance with this inference, daily
pulsatile LH secretion can be estimated robustly within subject
independently of the basal secretion analytic construct, conditional on
determinable LH pulse frequency and two-component LH
half-lives.
Model-independent within-subject estimation of LH pulse mass has
several important implications. First, the pulsatile mode of LH
secretion, presumptively activated by hypothalmic GnRH impulses, should
be a more robust measurable endpoint of neuroendocrine regulation.
Second, unlike our own and other earlier highly parameterized constructs (21), the present more parsimonious formulation of basal and
pulsatile LH secretion along with biexponential kinetics obviates some
of the strong mathematical confounds that impede maximum-likelihood
estimates (44). Third, because the sum of the estimated random mass
effects within any given time series is (theoretically) zero (21), we
can calculate by maximum-likelihood analysis statistically valid
confidence intervals for pulsatile and basal LH secretion and LH
half-lives. We showed earlier that this cannot be accomplished reliably
for a one-component disappearance idiom (21, 44). Fourth, by comparing
basal and pulsatile secretion of LH among reproductive states in
healthy women, we could examine gonadotropin regulation across the
normal adult human female lifetime.
Comparison of LH profiles disclosed that postmenopausal women have a
pronounced augmentation of LH secretory burst mass. In principle, such
unleashing of pulsatile LH release in the gonadoprival state may
reflect an expanded gonadotroph-cell secretory capacity and/or enhanced
endogenous GnRH drive (8). In contrast, in premenopausal women, LH
pulse mass remained nearly constant across the menstrual cycle, except
for the ML phase.
Half-life variations might occur in postmenopausal versus premenopausal
women. In particular, according to the zero-basal and constrained-basal
models, the calculated LH half-life rises postmenopausally and falls in
the ML phase. The former inference was suggested recently in GnRH
antagonist-based studies (37). In this regard, a recent kinetic
analysis of 14 human LH isoforms in a heterologous assay disclosed up
to a twofold range in their in vivo half-lives (3). Analogously, in the
human and animals, gonadal status (e.g., postovariectomy) may alter
evident rates of in vivo LH disappearance (1, 3, 5, 27, 47, 49, 50).
Postmenopausally increased basal LH secretion was implied only in the
constrained basal model. This is in accord with the literature-based
inference that the percentage of basal LH secretion, when defined as
non-GnRH dependent, is elevated after a GnRH antagonist in
postmenopausal women (6, 11, 30). In contrast, according to a fitted
basal secretion model, the absolute, but not percentage, basal LH
secretion rate is higher in postmenopausal individuals. In neither
construction was the variation in basal LH secretion rate the dominant
mechanism regulating total daily LH secretion and hence mean serum LH
concentrations in premenopausal women. Because estrogen concentrations
vary remarkably across the menstrual cycle, these analyses allow one to
conjecture further that estrogen or one of its gonadal covariates
controls primarily pulsatile (rather than basal) LH secretion. Estrogen
may also influence the slow-component half-life of LH, because the
latter is elevated in the face of estrogen withdrawal. Whereas clinical
studies with GnRH antagonists have suggested a lower percentage of
ostensibly GnRH-independent LH secretion in young versus older women
(6, 11, 30), such measures are derived in the face of near-maximal inhibition of endogenous GnRH action and thus, by definition, do not
reflect the interpulse rate of basal LH release that actually occurs in
the presence of physiological endogenous GnRH drive. Indeed, GnRH
itself might contribute in part to maintaining some fraction of basal
or nonpulsatile gonadotrope secretory activity. In fact, our freely
varying fitted basal secretion construct predicts higher LH interpulse
secretion than that suggested by GnRH antagonist studies.
The present strategy of partitioning total daily hormone release into
respective basal and pulsatile components, conditional on pulse times
and with the inclusion of random LH pulse-mass effects, simplifies
several earlier numerical deconvolution approaches (44). Here we
estimate approximately seven principal parameters of hormone secretion
and two of hormone elimination, rather than 20-30 parameters as
required in some previous efforts (8, 44). The core estimates include
basal secretion (
0); the average rate of interpulse
hormone (mass) accumulation (
0) and a constant (
1) relating this value to the prior interpulse
interval; (one or more of) three key features of the secretory burst
shape: rate of secretory burst ascent, peakedness, and steepness of
descent; a random-effects term, defining stochastic variability in
pulse mass accumulation; and the rapid versus slow hormone half-lives. If one used an a priori hormone secretory pulse shape, e.g., as determined by direct venous catheterization (2), this knowledge would
eliminate the fitting of pulse-shape parameters, allowing further
simplification. Analogously, independent ascertainment of elimination
kinetics would obviate the need to solve for these terms in the
analysis. Importantly, the foregoing core parameters all mirror basic
physiological processes. For example, the rapid increase and slow
decrease in secretion rates within a burst would likely correspond to
prompt exocytotic discharge of prestored hormone granules and delayed
de novo biosynthesis and release of additional hormone, respectively
(19). Similarly, the slow component of hormone (LH) removal would seem
to reflect its irreversible metabolic clearance from the body (3, 46).
These analyses uncover other challenging issues in appraising basal
hormone secretion. First, absolute basal LH secretion rates can vary by
severalfold across the reproductive life span and among individuals.
Second, independent knowledge of rapid and slow hormone half-lives
would aid in distinguishing the contribution of basal secretion from
that of the slower half-life to the mean hormone concentration. In
addition, accurate a priori defined hormone half-lives could help to
discriminate between otherwise statistically comparable models of
combined pulsatile and basal secretion. In contrast, we show here that
estimation of the pulse mass of hormone secreted is largely basal model
free. Because kinetic values are not always easily established for an
individual in any particular clinical or experimental setting, we can
suggest in the future also implementing a Bayesian modification of the present approach with preconditioning on the expected population hormone half-life and/or anticipated basal secretion rate.
The present LH time series were collected by blood withdrawal every 10 min for 24 h and show good precision in the estimation of daily LH
secretion and several key secretory parameters, as well as the more
prolonged half-life phase (see Table 1-3). Pulse shape is less
well estimated, in view of relatively infrequent sampling compared with
the brevity of LH secretory pulses. Similarly, the rapid half-life
component can only be estimated with an adequate sampling interval,
t. That is, the half-life cannot be less than log(2) ×
t; thus, for
t = 10 min, the lower bound is 6.93 min.
Although the random-effects maximum-likelihood appraisal of basal and
pulsatile LH secretion is illustrated here only in healthy women, this
analytic strategem should have relevance in other contexts, e.g., in
assessing LH pathophysiology in various study populations and in
evaluating the secretory control of other neurohormones. In addition,
by incorporating relevant physiological linkages and dose-response
interfaces, e.g., as suggested earlier for the integrated male
GnRH-LH-testosterone feedforward and feedback axis (20), this core
construct might be extended to allow appraisal of joint secretion by
coupled glands within an interconnected endocrine network.
Perspectives
The challenge of correctly partitioning an unknown admixture of
episodic and basal (nonpulsatile) neurohormone secretion into the two
corresponding contributions has been difficult to surmount analytically
(44). Here, we extend the notion of dissecting comingled pulsatile and
nonpulsatile hormone release given serial measurements of their
combined output convolved with elimination processes in peripheral
blood. Critical factors making such estimates possible include first
the introduction of a biexponential (and hence 2 compartmental)
disappearance function, which incorporates several unobserved features
of the dissipation phenomenon. Second, both the number and
cross-correlated nature of secretion parameters are restricted in the
analysis by conditioning the deconvolution solution on predetermined
pulse times estimated independently (18). Available a priori knowledge
of the biexponential kinetics or the percentage admixture of pulsatile
and basal components in the release process would aid further. However,
major issues remain unresolved. For example, to date there are few
objective in vivo validation strategies that combine constant
neurohormone infusions with superimposed pulselike injections of
varying defined amplitudes (33). Analogously, more studies are needed
that sample blood at high frequency and over a prolonged duration near
the site of neurohormone outflow to monitor the patterns of joint basal
and pulsatile secretion directly (4, 9, 26, 28, 42). Moreover, more
refined analyses will need to incorporate the nonlinear impact of one
or multiple binding proteins in plasma and/or tissues on the
partitioning of hormone removal (47a, 48). Indeed, empirical
biexponential kinetics oversimplify the true physics and physiology
that presumably underlie the hormone dispersal process in the
circulatory tree. For example, one might envision rapid postsecretory
diffusion of molecules in the aqueous space of blood, high-velocity
advection along the primary direction of flow in the arterial and
proximal venous systems, geometric dilution of hormone molecules by the
arborizing vasculature, capillary transit, and secondary confluence
into proximal venous trunks. Within this whole body circuitry, there is
the region-specific irreversible removal of hormone molecules (e.g., in
liver, spleen, kidney, etc.) at some probability level. We reason that
an empirically estimated biexponential elimination model approximates
the aggregate of these nonlinear processes. Another strategy to be
considered will be the simultaneous analytic evaluation of two or more
physiologically interlinked hormone series. Joint analyses could allow
for more statistically reliable reconstruction of secretion and removal processes, while incorporating the necessary feedback and feedforward relationships between the hormones. For example, this concept might be
implemented in relation to corelease of LH and testosterone (men) and
LH, progesterone, and/or estradiol (women). In addition, enhanced
understanding of the cellular mechanisms that govern constitutive
versus regulated facets of nonpulsatile (basal) hormone secretion
should also be useful. In principle, combining several of the foregoing
strategies could allow insights into and predictions about the dynamic
behavior of unobserved signals within the feedback system, such as the
hypothalamic release of GnRH in the case of threefold interrelated
GnRH, LH, and sex steroid feedback regulation. Therefore, continuing
interdisciplinary efforts in integrative physiology and supporting
analytic tools should engender continuing new insights into the
operating properties of more complex neurophysiological networks.
Indeed, more comprehensive biomathematical constructs should eventually
encapsulate the full array of functionally interdependent processes
within a macroscopic physiological axis, including the intracellular
biosynthesis and release of secretory molecules; their postsecretory
association with transport proteins; intravascular aqueous diffusion,
rapid advection, geometric dispersion, partial recirculation and
site-specific saturable removal from the bloodstream; time-delayed
feedforward actions on selected target tissues; and the subsequent
feedback-controlled synthesis and secretion of new effector molecules.
 |
APPENDIX |
Structural Features of the Basal Secretion Models
General structure of secretory formulation.
As defined in equation 1 (METHODOLOGY),
0 is the basal and P( · ) the
pulsatile hormone secretion rate. We reason that the cellular basis for
basal secretion is constitutive hormone release and for pulsatile
secretion is the discharge of available intracellular (peptide) hormone
contained within secretory granules, which accumulate during the
interpulse interval. Hormone molecules synthesized in the cell starting
at pulse time Tj
1 are stored
until the next pulse time, Tj. As
reviewed in Refs. 8, 19, and 47, several techniques have been validated
to estimate GnRH-LH pulse times. Here, we evaluate secretion
conditional on the pulse times, as determined in Ref. 19. We define the
mass of the jth pulse Mj to be the
amount of hormone accumulated between pulse times
Tj
1 and
Tj. Here, we assume that the LH
pulse masses are given by
where
0 is the basal (intracellular)
accumulation rate, and
1 is a constant, which relates
pulse mass accumulation to the immediately preceding interpulse
interval length. This relationship reflects the fact that gonadotrope
cells accumulate more LH during prolonged interpulse intervals (8). We
assume that the Ajs are independent and
identically distributed normal random variables with mean zero and
variance
2A, thus
allowing for stochastic variability (random effects) in pulse mass. To
accommodate variably skewed pulse shape(s), a function
( · ) is
specified, which is the normalized rate of secretion given as hormone
mass per unit distribution volume per unit time, as a Generalized-Gamma
family of densities (i.e., normalized to integrate to 1)
|
(A1)
|
where
1 > 0,
2 > 0, and
3 > 0 are three parameters that delimit the secretory burst shape. The
resulting overall secretion rate [Z(t)] is thus
given by
In the case of two elimination components, the foregoing formulation
results in equation 2 (METHODOLOGY). Infusions of
human pituitary LH have suggested that the rapid LH half-life component is approximated by a
0.63 and a half-life of
18 min
[
1 = log(2)/18] and the longer half-life component
by (1
a)
0.37 and a half-life of
90 min
[
2 = log(2)/90] (46). Here, we initially fix
a
0.63 for the kinetic estimates.
What is then observed is a discrete time sampling of this process, plus
measurement error
where
ks represent measurement error (e.g., due to
assaying). In Refs. 21 and 51, the asymptotic normality is shown for
the maximum-likelihood estimators of the above parameters
0,
1,
2,
0,
1,
1,
2,
3,
2A,
2e. More
importantly, their variances and covariances are estimable, as well as
variances and covariances for such constructions as total daily
secretion and its partition into total daily basal secretion and total
daily pulsatile secretion. For example, to calculate total daily LH secretion, we integrate the (reconstructed) LH secretion rate, Z( · ), from 0 to 1,440 min
Models of basal secretion.
Given the foregoing, we next consider three models for basal secretion.
In our original construction (19, 21, 51), basal secretion was free to
vary (
0 was unconstrained) and we allowed a single
exponential elimination process. The three models evaluated here are
1) freely varying, i.e., analytically fitted (F model); 2) zero basal (Z model); 3a) constrained by
preinjection steady-state [C(SS) model] measured serum LH
concentration; or 3b) constrained by a percentage of total
secretion [C(
) model, where
is a literature-based population
parameter]. The zero basal (Z) model is a minor adaptation of the
estimation methodology for that of the freely varying basal model;
there is one fewer parameter (no basal term:
0), and
the modifications necessary for the appropriate formulas are minor. SEs
can be calculated for the parameter estimates and for such constructions as total daily secretion, mass per pulse, etc. These standard errors are given in Tables 1-3.
The constrained basal (C) model is, however, slightly different, and
below we describe its framework briefly. In the constrained basal (C)
model, the proportion of (daily) basal secretion to total (basal plus
pulsatile) secretion is assumed to be constrained; let
be the
proportionality constant, a literature-based population parameter. On
the basis of published estimates, for premenopausal women
was
assumed to be ~24%, and for postmenopausal women, 34%. This model
differs from the preceding, because the constraint is global. For
example, total daily secretion, total daily basal secretion, and the
basal rate (
0) are now functions of total daily
pulsatile
secretion
|
(A2)
|
The basal rate
0 is now a random variable, as
a consequence of the random effects: Ajs in
the pulsatile secretion rate P( · ). Because the global
constraint (equation A2) is a linear constraint, the resulting
model is still Gaussian and the likelihood function is of the same
basic form as that derived in Ref. 21, but with the mean function and
covariances modified. The general asymptotic results of Refs. 21 and 51 are still applicable and were implemented in the estimation algorithms. Because total daily secretion and total daily basal secretion are now
multiples of total daily pulsatile secretion, their SEs are multiples
of the SE of total daily pulsatile secretion. Thus, in the constrained
[C(24) and C(34)] model entries in Table 1, the SE for total daily
secretion is now the sum of the SEs of total daily basal secretion and
pulsatile secretion.
 |
ACKNOWLEDGEMENTS |
We thank Dr. William S. Evans (University of Virginia) for sharing
reanalysis of the female LH data sets in this study, Dr. Thomas
Mulligan (Virginia Commonwealth University) for allowing use of the LH
infusion data, Paula P. Azimi for assistance in data presentation and
graphics, and Patsy Craig for manuscript assembly.
 |
FOOTNOTES |
This work was supported by the National Science Foundation Center for
Biological Timing, the General Clinical Research Center (RR-00847), National Institutes of Health (NIH) Research Career Development Award 1K04-HD-00634, NIH Center for
Specialized Reproduction Research U54 HD-96008, and NIH R01 AG-14799.
The costs of publication of this
article were defrayed in part by the
payment of page charges. The article
must therefore be hereby marked
"advertisement"
in accordance with 18 U.S.C. §1734 solely to indicate this fact.
Address for reprint requests and other correspondence: J. D. Veldhuis,
Dept. of Medicine, Dir. Endocrinology and Metabolism, Univ. of VA
Health Sciences Center, Box 202, McKim Hall, Charlottesville VA 22908 (E-mail: jdv{at}virginia.edu).
Received 28 July 1999; accepted in final form 18 October 1999.
 |
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