"Step" vs. "dynamic" autoregulation: implications for susceptibility to hypertensive injury

Anil K. Bidani,1 Rifat Hacioglu,2 Isam Abu-Amarah,1 Geoffrey A. Williamson,2 Rodger Loutzenhiser,3 and Karen A. Griffin1

Department of 1Internal Medicine, Loyola University Medical Center and Edward Hines, Jr., Veterans Affairs Hospital, Maywood 60153; Department of 2Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, Illinois 60616; and Department of 3Pharmacology and Therapeutics, University of Calgary, Alberta T2N 4N1, Canada

Submitted 13 January 2003 ; accepted in final form 5 March 2003


    ABSTRACT
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 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Renal autoregulatory (AR) mechanisms provide the primary protection against transmission of systemic pressures, and their impairment is believed to be responsible for the enhanced susceptibility to hypertensive renal damage in renal mass reduction (RMR) models. Assessment of AR capacity by the "step" change methodology under anesthesia was compared with that by "dynamic" methods in separate conscious control Sprague-Dawley rats and after uninephrectomy (UNX) and 3/4 RMR (RK-NX) (n = 7–10/group). Substantially less AR capacity was seen by the dynamic vs. the step methodology in control rats. Moreover, dynamic AR capacity did not differ among controls, UNX, and RK-NX rats (fractional gain in admittance ~0.4–0.5 in all groups at frequencies in the range of 0.0025–0.025 Hz). By contrast, significant impairment of step AR was seen in RK-NX vs. control or UNX rats (AR indexes 0.7 ± 0.1 vs. 0.1 ± 0.02 and 0.2 ± 0.04, respectively, P < 0.01). We propose that the step and dynamic methods evaluate the renal AR responses to different components of blood pressure (BP) power with the step AR assessing the ability to buffer large changes in average BP (DC power), whereas the present "dynamic" methods assess the AR ability to buffer slow BP fluctuations (<0.25 Hz) superimposed on the average BP (AC power), a substantially smaller component of total BP power. We further suggest that step but not dynamic AR methods as presently performed provide a valid index of the underlying susceptibility to hypertensive glomerular damage after RMR.

renal hemodynamics; hypertension; nephrosclerosis; myogenic response; tubuloglomerular feedback


CHRONIC RENAL DISEASE regardless of etiology tends to follow a progressively downhill course (8, 36). Experimental animal models of renal mass reduction (RMR) exhibit a similar course of progressive glomerulosclerosis (GS) and nephron loss. On the basis of investigations in such models, it has been proposed that the loss of a critical degree of functional renal mass results in the initiation and perpetuation of pathogenetic mechanisms that are intrinsic to the reduced functional renal mass state (8, 19, 35, 36, 39, 40). Several lines of evidence have indicated that an exaggerated transmission of systemic blood pressure (BP) to the glomerular capillaries is one such major pathogenetic mechanism (37, 2326, 3941). The pathophysiological basis for this enhanced glomerular BP transmission after RMR has been postulated to be due to an impairment of the renal autoregulatory (AR) mechanisms that normally provide the primary protection against BP increases, episodic or sustained, from being transmitted to the renal microvasculature (3, 5, 7, 2327, 3741).

To date, such renal AR impairment in RMR models has only been demonstrated using the conventional "step" AR methodology in which graded step changes in renal perfusion pressure (RPP) were imposed in anesthetized animals and the "steady-state" changes in renal blood flow (RBF) were measured (57, 2123, 25). AR capacity is assessed by the calculation of AR indexes (AI; fractional changes in RBF/fractional changes in RPP) with an AI of zero, indicating perfect AR, i.e., no change in RBF for any given change in RPP (46). However, the physiological validity of such assessments has been questioned (11, 20, 30, 33, 42), as BP in conscious animals does not change from one steady state to another but rather fluctuates simultaneously over a wide range of time scales (frequencies) (28, 29, 42). Moreover, AR is not instantaneous (9, 15, 16, 2933, 45, 47) and impairments in AR allowing an enhanced BP transmission could occur due to either a diminished magnitude of the response or due to a slower rate of response (34). Conventional step AR studies assess only the potential magnitude of the steady-state AR response to BP steps, but not its dynamic aspects (17, 29, 30, 3234). Therefore, it has been suggested that "dynamic" AR studies may provide a more physiological and thus more valid assessment of AR capacity in addition to characterizing the operational characteristics of the myogenic and tubuloglomerular feedback (TGF) mechanisms through frequency domain analysis (1, 11, 12, 1417, 29, 30, 33, 34, 49). Simultaneous recordings of BP and RBF are typically obtained at a sampling rate of >3 Hz. Fractional validations in flow and pressure are analyzed in terms of the transfer function between the input (BP) and the output (RBF) using fast Fourier transforms (FFT). AR capacity (efficiency) is assessed by the degree to which BP fluctuations at a given frequency lead to parallel fluctuations in RBF and is expressed as admittance gain at that frequency. Thus a fractional gain in admittance (FGA) of zero would indicate complete attenuation of the BP fluctuations and perfect AR. Such dynamic AR studies have shown that the maximum attenuation of RBF fluctuations is only achieved with the slower BP fluctuations that occur at frequencies <0.025 Hz and has been ascribed to the combined contribution of the myogenic and TGF mechanisms (1, 11, 15, 29, 30, 33, 42, 49). The apparent lack of ability to respond to fluctuations faster than ~0.3 Hz has been attributed to the time constraints of the response of these two AR control mechanisms with the myogenic mechanism exhibiting a time constant of ~4.0 s (0.25 Hz) and TGF of ~25 s in the rat (~0.04 Hz) (1, 11, 12, 1417, 29, 30, 37).

Although the primary focus of dynamic AR studies has been to investigate the operational characteristics of AR mechanisms and their relative contributions in both normotensive and hypertensive animals, such studies have recently also been used to investigate genetic susceptibility to hypertensive injury (34, 48). However, to date, such studies have not been performed in reduced renal mass states. The present studies were performed to directly compare and critically evaluate step and dynamic methodologies for the assessment of AR capacity after graded RMR from the perspective of BP transmission and potential susceptibility to hypertensive damage.


    METHODS
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 METHODS
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RMR. Male Sprague-Dawley rats (250–350 g body wt) were anesthetized with pentobarbital sodium (50 mg/kg ip) and underwent sham surgery (controls), right uninephrectomy (UNX), or 3/4 RMR (right UNX and surgical excision of both poles of the left kidney; RK-NX) as previously described (22, 23, 26). At ~3–4 wk after surgery, separate control, UNX, and RK-NX rats underwent either conventional step or dynamic AR studies (see below). All rats were fed a standard diet (Purina, Richmond, IN) and synchronized to a 12:12-h light (0600 to 1800)-dark (1800 to 0600) cycle. All rats received food and water ad libitum throughout the study. All animals were cared for in accordance with the Guide for the Care and Use of Laboratory Animals (National Academy Press, 1986).

Dynamic AR studies. Dynamic AR studies were performed 3–4 wk after surgery. The week before the scheduled studies, radiotransmitters (Data Sciences, St. Paul, MN) and chronic RBF probes (Transonic Systems, Ithaca, NY) were installed under pentobarbital sodium anesthesia (50 mg/kg ip). Each rat had a BP sensor (model TA11PA-C40) inserted into the aorta via a femoral artery below the level of the renal arteries, and the radio frequency transmitter was fixed to the peritoneum as previously described (4, 2326). An ultrasonic transit time flow probe (1RB, Transonic Systems) was placed around the renal artery and packed in a Dacron mesh to ensure proper alignment of the probe and vessel. The probe cable was secured to back muscles, routed subcutaneously, and exteriorized at the back of the neck. Flow probes were validated as previously described (6, 22). After rats were allowed to recover for 1 wk, the flow probes were connected to a transonic flowmeter (T106, Transonic Systems) and ~60-min simultaneous recordings of BP and RBF were obtained at a sampling rate of ≥20 Hz in conscious unrestrained rats. One to three recordings were obtained in each rat at intervals of 24 to 72 h and the results (see below) were averaged for each rat. Subsegments of 30 min in duration that were free of noise or other artifacts were then selected from each data record. The resulting 30-min signals were resampled to a sampling rate of 20 Hz if necessary using a low-pass antialiasing filter to remove variations in the signals at greater than 10 Hz rate. Each time sequence of 36,000 data points was then subjected to linear trend removal (44).

The transfer functions of the dynamic relationship between BP (input) and RBF (output) were analyzed using standard methods. The BP and RBF power spectra were determined using FFTs based on Welch's averaged periodogram method (50% overlap of 7 segments of 8,192 samples, detrended, and a Hanning window applied) (44). Input and output auto power spectra and cross power spectra were then calculated for each segment and averaged. The admittance function was computed as the ratio of cross spectrum to BP power spectrum (30, 32, 34). The coherence function was also computed from the cross and auto power spectra. Fractional gain was obtained by normalizing admittance gain by the conductance computed over the entire 30-min record. The natural frequencies of the myogenic and TGF mechanisms were determined from their characteristic signature resonance peaks in fractional gains between 0.1 and 0.3 Hz and between 0.025 and 0.1 Hz, respectively, by inspection of individual records and then averaged across each record. The peak phase angle in the phase responses between 0.08 and 0.2 Hz was similarly determined and averaged across each record.

Conventional step AR. These studies were performed at 3–4 wk after surgery in a separate group of control, UNX, and RK-NX rats. The rats were anesthetized with inactin (100 mg/kg ip) and surgically prepared as described previously (2126). In brief, a tracheostomy was performed using polyethylene (PE-200) tubing, and a carotid artery was cannulated with PE-50 tubing and connected to a Windograf recorder (model 40–8474, Gould, Glen Burnie, MD) for continuous recording of mean arterial pressure. A femoral vein was cannulated with PE-50 tubing and a 150 mM NaCl bolus equal to 1% of the body weight was administered, followed by a continuous maintenance infusion of 150 mM NaCl at 0.055 ml/min for replacement of surgical and ongoing fluid losses. An ultrasonic transit time flow probe (1 RB, Transonic Systems) was placed around the left renal artery for measurement of RBF by a flowmeter and AR studies were performed using aortic miniclamps positioned above and below the left renal artery to raise or lower RPP as previously described (57, 2123). The RBF was allowed to stabilize for 1 to 2 min at each pressure before RBF measurements were made. Flow probes were validated as previously described (6, 22). AI was calculated by the method of Semple and de Wardener (46) as follows: AI = [(RBF2 - RBF1)/RBF1]/[(RPP2 - RPP1)/RPP1]. An AI of zero indicates perfect autoregulation, whereas an AI of one indicates that the vessels act as passive conduits for blood flow.

Statistical analysis. All results are expressed as means ± SE. Statistical analysis was performed using analysis of variance, followed by a Student-Newman-Keuls test or by Kriskall-Wallis nonparametric analysis of variance, followed by Dunn's multiple comparison test, as appropriate. A P value of >0.05 was considered nonsignificant (20).


    RESULTS
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Figure 1, A-E, presents the transfer function analysis for the dynamic AR studies with the mean results for each individual parameter assessed for the three groups of rats (the quantitative comparisons are presented separately). The average BP during the conscious recording was not significantly different among the groups (control 95.3 ± 2.4; UNX 102.5 ± 3.0; and RK-NX 99.6 ± 2.7 mmHg). The average RBF, on the other hand, was significantly greater in both UNX (34.8 ± 3.8 ml·min-1·kg body wt-1) and RK-NX (31.6 ± 3.1 ml · min-1 · kg body wt-1) compared with control rats (21.2 ± 2.3 ml · min-1 · kg-1) (P < 0.05). As can be noted from the overview, the AC BP power spectra were not different among the three groups, but the RBF power was relatively greater in the two RMR groups. The mean coherence between BP and RBF signals was above 0.5 at frequencies >0.05 Hz in all groups, but it declined to 0.4–0.5 at frequencies <0.05 Hz. The two RMR groups exhibited differences from the control rats for both the phase angle of the myogenic response and the fractional gain at the myogenic "resonance" peak (see below).



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Fig. 1. Transfer function analysis between blood pressure (BP; input) and renal blood flow (RBF; output) computed over 30 min in conscious control (n = 9), right uninephrectomy (UNX; n = 7), or right kidney UNX and excision of both poles of left kidney (RK-NX; n = 10) rats. The group average data are shown. The standard error lines have been omitted for legibility (A), BP power spectra (B), RBF power spectra (C), coherence between BP and RBF (D), and admittance phase (E) fractional gain in admittance (FGA).

 

Figures 2 and 3 show the effects of graded RMR on the operational characteristics of TGF and myogenic mechanisms. RMR had no significant or consistent effect on the natural frequencies of either the myogenic or TGF system (Fig. 2). Figure 3 shows that similarly the resonance peak of the TGF system was not altered by RMR. By contrast, a significant attenuation of the myogenic resonance peak was observed in both RMR groups compared with control rats (P < 0.001), but no difference was observed between the UNX and RK-NX groups. This change is also reflected in the peak phase angle between 0.08 and 2 Hz (control 98.6 ± 6.1 vs. 76.2 ± 7.5 and 75.5 ± 4.9 for UNX and RK-NX groups, P < 0.05).



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Fig. 2. Effect of graded renal mass reduction on the natural frequencies of the myogenic and tubuloglomerular feedback (TGF) mechanisms determined from their characteristic resonance peaks in control (open bars), UNX (hatched bars), and RK-NX (filled bars) rats.

 


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Fig. 3. Effect of graded renal mass reduction on the magnitude of the FGA at the resonance peaks of the myogenic and TGF mechanisms in control (open bars), UNX (hatched bars), and RK-NX (filled bars) rats. A significant attenuation of the myogenic but not TGF resonance peak was observed in both UNX and RK-NX rats compared with control rats (*P < 0.001).

 

Figure 4 shows the results of conventional step AR studies after graded RMR. Step changes in RPP between 140 and 100 mmHg resulted in significant changes in RBF in the RK-NX (P < 0.01 maximum) but not in the control or UNX rats. As in conscious rats, the single-kidney RBF was significantly higher in anesthetized UNX compared with control rats at all RPPs (P < 0.05), but the RBF in RK-NX rats was not significantly different from either group. However, it should be noted that RBF for RK-NX rats represents the blood flow to renal mass that is only ~40–50% of that in an intact kidney and, therefore, substantially underestimates the markedly increased blood flow through the individual dilated resistance vessels in the remnant kidney.



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Fig. 4. RBF and its response to step changes in mean arterial pressure in separate anesthetized control (n = 9), UNX (n = 10), and RK-NX rats (n = 8) 3–4 wk after renal mass reduction surgery. RBF in UNX rats at all arterial pressures was significantly greater than in control rats (*P < 0.05 maximum). RBF in RK-NX rats was not significantly different from that of the other 2 groups.

 

Figure 5 compares the AR efficiency assessed (as the AI) using the step protocol against that assessed (as the FGA) by the dynamic AR protocol. For the latter, the mean FGAs attained at frequencies ranging from 0.0025 to 0.01 Hz and from 0.01 to 0.025 Hz are presented separately. Significantly better AR capacity is seen in normal rats with the step AR protocol (AI of <0.1) than with dynamic protocol (FGA of ~0.5 at frequencies <0.025 Hz). Moreover, in contrast to the significant AR impairment demonstrated in the RK-NX rats by the step AR protocol, no differences in dynamic AR were observed among the three groups.



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Fig. 5. Calculated autoregulatory (AR) indexes (AI) by the method of Semple and de Wardener (46) for RBF responses to changes in renal perfusion pressure (RPP) between ~140 and ~100 mmHg in anesthetized control (open bars), UNX (hatched bars), and RK-NX (filled bars) rats (Fig. 4). The AI for the 2 changes in RPP were not significantly different from each other in any of the groups; therefore, a single AI value for the RBF change between ~140 and ~100 mmHg is presented. Renal AR was significantly impaired in RK-NX rats as indicated by significantly higher AI compared with the control or UNX groups (*P < 0.001), which were not significantly different from each other. By contrast, AR efficiency during the dynamic AR studies in conscious rats as assessed by the mean FGA observed either at frequencies ranging from 0.0025 to 0.01 or 0.01 to 0.025 Hz was not significantly different among the 3 groups of rats (Fig. 1E).

 


    DISCUSSION
 TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Renal AR mechanisms, through proportionate increases in preglomerular resistance in response to increases in BP, provide the primary protection against hypertensive renal injury (3, 57, 10, 2327, 34, 3742). Although ample theoretical arguments and experimental evidence support this concept, several issues remain controversial and poorly defined. These include the relative merits and limitations of assessments of AR capacity by step vs. dynamic methods, the contribution and operational characteristics of the myogenic and TGF control mechanisms, the precise nature of the BP signals that trigger these responses, and the realtime mechanics by which AR responses protect against increased BP transmission and hypertensive injury.

The most striking difference in the present comparison of the assessment of the AR capacity by these two methodologies is the clear evidence of AR impairment after 3/4 RMR observed using the step protocol but not by dynamic AR assessment. Moreover, differing AR capacity estimates are obtained by these two methods even in control rats. A literal interpretation of the minimal FGA of ~0.5 obtained with the dynamic method is that ~50% of a given increase in BP would be buffered and ~50% would be transmitted to the glomerular capillaries (33). Thus AR would offer minimal protection against transmission of BP fluctuations even in normal animals. This is in contrast to >90% buffering capacity that is suggested by step AR studies in these animals (AI index of <0.1). Although the present step AR capacity estimates were obtained under anesthesia, essentially identical estimates have been obtained in conscious controls rats (13). One suggested explanation is that the full AR capacity is not employed under normal physiological conditions (15, 30, 33, 42). However, similar estimates of dynamic AR capacity are obtained in the spontaneously hypertensive rat (SHR) strain where hypertension would be expected to trigger the AR reserve (1, 11, 34). Another possible explanation is that the transfer function analysis as used in dynamic AR studies is strictly valid only for linear control systems, but AR is nonlinear (12, 29). Such nonlinear effects as well as concurrent BP-independent vasomotor events with slow time constants may account for the low coherence (<0.5) at frequencies <0.05 Hz (42). Such may also occur due to renal sympathetic nerve activity, but similar estimates of coherence and AR efficiency are noted in control rats with denervated kidneys (42). Moreover, a low coherence cannot fully account for the observed low AR efficiency, which is seen even with coherence estimates >0.5 (33). Of greater relevance, in contrast to step AR, dynamic methods failed to indicate greater BP transmission after severe RMR (≥3/4) compared with controls, despite the enhanced susceptibility to hypertensive GS in these models (37, 2326, 3941). Similarly, differences in dynamic AR capacity are not seen between SHR and Dahl salt-sensitive rats, despite marked differences in susceptibility to hypertensive damage (34).

One possible explanation for these observed differences is that the renal vascular responses assessed during step vs. dynamic AR are actually different. As Fig. 4 indicates, step AR assesses the ability to achieve proportionate changes in renal vascular resistance (RVR) in response to large step changes in mean BP. In contrast, dynamic AR studies analyze the relationship between the relatively small BP and RBF fluctuations around the ambient averages over short intervals. Accordingly, dynamic AR studies assess the ability of the preglomerular vasculature to affect additional changes in RVR in response to BP fluctuations in animals who may have already achieved a basal RVR in proportion to their AR capacity. The relatively small BP inputs that are typical during dynamic AR studies probably contribute to the low coherence and the poor AR efficiency estimates. A recent study by Pires et al. (42) supports this suggestion. Dynamic AR was examined in sinoaortic baroreceptor-denervated (SAD) rats, which exhibit much greater BP lability and BP power inputs. An FGA of ~0.2 at frequencies <0.01 Hz was observed in these rats compared with ~0.4 in controls. Moreover, AR curves similar to those obtained during step AR could be mathematically modeled from the data in SAD but not control rats (43). Thus, while step AR assesses the ability to buffer large changes in average BP, dynamic AR may only assess the ability to buffer BP fluctuations superimposed on this average BP.

In assessing which approach would likely provide the more accurate index of susceptibility to hypertensive injury, it is relevant to consider the relative impact of the two components of pressure power (energy/unit time) to which the renal microvasculature is exposed to, increases in average BP (DC power) and increased BP fluctuations or AC power (3, 43). The largest component of BP power derives from the average BP (3) and, indeed, most correlations of hypertensive target organ damage have been performed with mean BP. The component of BP power that emanates from BP fluctuations around this average BP, AC power, is substantially smaller and, of this, the largest fraction is due to the heartbeat (pulse pressure) (3, 37). In any event, the transmission of all BP power is expected to be a function of the achieved AR preglomerular tone (resistance). As increases in resistance dampen the transmission of the pressure pulse while decreases amplify it (39), the greater the achieved resistance, the less will be the flow and pressure delivered distally. This is illustrated by the normal RBF, glomerular filtration rate (GFR), and glomerular capillary pressure exhibited by the SHR strain despite severe hypertension (2).

Two separate but interrelated processes seem to be involved in protection from hypertensive injury. The first is the setting of an ambient basal preglomerular resistance in response to the average BP and the second is the capacity to adjust it in response to BP variations. Both step and dynamic AR evaluate the latter ability. Although step AR essentially examines the ability to maintain this basal tone in response to sustained and relatively large changes in DC power (average BP), dynamic AR assesses the response to slower and smaller BP variations (AC power at low frequencies). Both methods assess AR efficiency only in terms of fractional changes and factor out the differences in the absolute values of ambient BP and RVR. Such normalization is not inappropriate, given the fact that the ambient RVR not only reflects the AR response to the ambient BP but is also importantly modulated by BP-independent factors (neurohormonal, metabolic) (29, 38). This is illustrated by the increased RBF after RMR compared with control rats despite a similar ambient BP. Nevertheless, the differences between UNX and RK-NX groups illustrate the relative importance of both of these processes. Ambient fractional BP transmission would be enhanced in both groups because of the increased conductance (vasodilation) after RMR (18, 22, 23). The well-documented deleterious effects of superimposed UNX in renal injury models are consistent with such an interpretation (39). However, the ability to maintain a given basal tone in response to changes in average BP is impaired in RK-NX but not UNX rats. Consequently, sustained or episodic increases in BP would be poorly buffered in the RK-NX compared with UNX rats and may account for the differing time courses of GS between UNX (8–9 mo) and RK-NX rats (~4 mo) (22, 39).

Although step AR capacity estimates seem to correlate better with susceptibility to hypertensive injury, such step AR capacity assessments are conventionally performed using essentially static BP signals. However, all in vivo changes in BP are presented to the preglomerular vasculature as oscillating signals because of the heartbeat. Dynamic AR, on the other hand, does assess the response to oscillating BP signals but, at least as conventionally performed and interpreted, does not provide a mechanism for protection against the largest components of BP power, the DC power and the AC power at the heartbeat frequency. In fact, a central assumption of dynamic AR studies is that due to the relatively slow time constants of renal AR mechanisms, BP oscillations occurring at a rate faster than the myogenic frequency (~0.25 Hz) are handled passively and thus freely transmitted (29, 30, 49). In essence, renal AR is considered to function as a high-pass filter capable of responding only to the lower frequency signals. However, recent observations in the in vitro perfused hydronephrotic kidney model indicate that such assumptions are likely not valid (37). These observations demonstrate that the afferent arteriole does not respond passively to pressure oscillations presented at frequencies of 1–6 Hz as predicted by such concepts, but with a sustained vasoconstriction. Clearly, the preglomerular vasculature must sense the oscillating BP signals delivered at these faster frequencies. A central problem may be that the response time of AR mechanisms has been equated with the signal presentation and sensing mechanisms. In any event, the system still appears to behave like a high-pass filter, passing BP oscillations faster than 0.3 Hz, but the transmission of all components of BP power including DC power is attenuated in proportion to the vasoconstriction elicited by the high-frequency signals that are likely sensed in vivo at the heartbeat frequency (37). Although neither step nor dynamic protocols directly examine the response to high-frequency BP signals, the step protocol may indirectly assess the capacity of the renal vasculature to respond proportionately to the magnitude of these BP signals.

Although we found RMR had no effect on either the FGA or on the natural frequencies of either the myogenic or TGF mechanisms, an attenuation of the signature resonance peak of the myogenic mechanism was observed in both RMR groups. The significance of such changes remains to be defined. It has been suggested that the TGF resonance peak is due to an intrinsic oscillation, whereas the myogenic resonance peak has been postulated to represent an interaction between the myogenic mechanism and the passive elastic properties of the blood vessel (14, 15, 29, 30, 34, 37, 49). The structural vascular adaptations including vasodilation that occur after RMR may alter the intrinsic characteristics of the vasculature responsible for the myogenic resonance peak. Alternatively, such attenuation might indicate a less active myogenic mechanism. In this context, the studies of Karlsen et al. (34) are of note. A significant attenuation of the myogenic but not TGF resonance peak similar to that in the UNX and RK-NX rats was observed in the hypertensive damage-susceptible Dahl salt-sensitive rats even when on a low-salt diet (nonhypertensive) compared with the SHR and Sprague-Dawley rats.

The lack of any significant alteration in the operational characteristics of TGF in contrast to that of the myogenic mechanism after RMR in the present studies is consistent with observations reported in genetic models of increased susceptibility to hypertensive injury (34, 48). Such findings raise the intriguing possibility that the myogenic and TGF mechanisms regulate separate aspects of the AR response. This is supported by recent observations in a hydronephrotic kidney preparation, which indicate that the magnitude of the myogenic response to high-frequency oscillating BP signals may be determined by the peak (systolic) and not the average BP (37). As RBF and GFR are a function of the average BP, these data imply that the primary function of the myogenic component of the AR response is to protect the glomerular capillaries from systolic pressure rather than to regulate RBF and GFR. Because under most circumstances changes in mean BP parallel changes in systolic pressure, myogenic responses to changes in systolic BP would result in concurrent autoregulation of RBF and GFR. However, such responses may need to be modulated so as to achieve a regulation of GFR and volume status that is appropriate to the needs of the animal. This goal may be achieved by the setting of different basal levels of ambient RVR in response to the average BP as reflected in the preglomerular vasodilation (and increased GFR) in UNX rats but unimpaired step AR capacity. The slower signal presentation and response time of the TGF system are consistent with such a regulatory function. Such regulation would be additionally modulated by slower neurohormonal systems acting directly on the microvasculature and through alterations of the TGF response (38). The fact that impaired myogenic responses are associated with an increased susceptibility to hypertensive injury in both genetic and nongenetic models, but without significant dysregulation of volume homeostasis, is consistent with such interpretations, as are the interactions between the TGF and myogenic mechanisms (10, 12, 29, 30, 4749).

In conclusion, the present studies show that step and dynamic AR provide differing estimates of AR capacity with dynamic AR showing substantially less AR capacity in control animals. Moreover, step, but not dynamic, AR demonstrates an impairment in AR capacity after 3/4 RMR. Thus differences in the underlying susceptibility to GS after RMR correlate with step but not with dynamic AR capacity estimates. Although the reasons for these discrepant estimates remain to be fully defined, we suggest some potential explanations. First, the two methods assess the renal AR response to different components of the total BP power (energy). The step protocol assesses the ability to buffer the bulk of the BP load (the increase in mean BP), whereas the dynamic protocol as presently performed assesses the ability to buffer the AC BP power due to BP fluctuations occurring at the slower (<0.25 Hz) frequencies, the smallest component of the BP burden. Second, dynamic AR capacity estimates are compromised by the low coherence between the BP signals and RBF response and the low amplitude of BP fluctuations (inputs) at these low frequencies. Finally, recent findings suggest that the prevailing in vivo signal for AR responses may be the peak (systolic) BP, which is presented to the renal vasculature at the heart beat frequency. Step rather than present dynamic AR methods may provide a better indirect estimate of the capacity of the preglomerular vasculature to respond to these peak pressure signals.


    ACKNOWLEDGMENTS
 
The authors thank Angela Powell and Rizalita Redovan for technical assistance and Martha Prado for secretarial assistance.

This work was supported by National Institute of Diabetes and Digestive and Kidney Diseases Grants DK-40426 and DK-61653 and the Office of Research and Development of the Department of Veterans Affairs.


    FOOTNOTES
 

Address for reprint requests and other correspondence: A. K. Bidani, Loyola Univ. Medical Center, 2160 South First Ave., Bldg. 102, Rm. 3661, Maywood, IL 60153 (E-mail: abidani{at}lumc.edu).

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. Section 1734 solely to indicate this fact.


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