banting lecture 2006 - home | diabetes€¦ · (3,4). for some years, our laboratory has been...

Banting Lecture 2006

Orchestration of Glucose HomeostasisFrom a Small Acorn to the California OakRichard N. Bergman

Type 2 diabetes is increasing at alarming rates inthe U.S., in Westernized countries, and in thethird world. The increasing costs in terms ofhuman suffering as well as economics are well

recognized (1). Improved understanding of the pathogen-esis of diabetes should lead to better approaches topredict, forestall, or even prevent diabetes and to treatextant cases. Yet, the precise causes of this disease remainto be totally explained. There is little question that obesityper se is a primary contributor, but the causes of theso-called “obesity epidemic” are in debate (2), as are themechanisms by which obesity itself is linked to diabetes(3,4).

For some years, our laboratory has been engaged inefforts to understand causation of type 2 diabetes in termsof insulin secretion and resistance and to attempt toaccount for the role of obesity. The Banting Lectureprovided me with a rare opportunity to describe ourresearch efforts done over a prolonged history in a singlepresentation. It was my goal to address the several areas ofdiabetes research we have done. At first glance thesedifferent areas may appear unrelated. But these lines ofwork are closely linked within an overall effort to under-stand diabetes. I am deeply grateful to the members of theAmerican Diabetes Association for the great privilege ofmaking this presentation. I hope I will be able to empha-size the wonderful opportunity that I and my colleagueshave had to pursue original research in a highly deservingand important cause. One can scarcely ask for more inone’s professional life.

For several decades it has been popular to pursue a“reductionist” approach to studying disease (Fig. 1). Theunderlying concept is that understanding of disease willresult from describing events at increasingly more micro-scopic levels:

(organism3organ3receptor3organelle3substrates3pathway3enzyme3gene).

This reductionist approach emerged naturally fromthe revolutionary development of molecular biology andmolecular genetics. A plethora of animal models ofobesity and/or hyperglycemia have been produced (5–8). It is possible to sample tissues from such animalmodels and study function in vitro. From the reduction-ist approach has emerged the well-described signalingpathways by which insulin binds to cells and performsmultiple functions, including stimulating glucose dis-posal, reducing lipolysis, enhancing lipogenesis, andenhancing protein synthesis (9 –12). Equally importanthave been studies of the molecular events leading to thesynthesis and secretion of insulin and other importantglucoregulatory peptides (glucagon, glucagon-like pep-tide-1 [GLP-1], glucose-dependent insulinotropic pep-tide [GIP], and catecholamines). But it is becomingincreasingly clear that the massive amount of informa-tion provided by the molecular approach may not, initself, allow us to explain disease. Approaches to inte-grate this massively increasing body of material usingcomputer models are emerging with the moniker “sys-tems biology” (13), but principles of systems biologyhave long been applied to physiological regulation. Hasit been possible to apply concepts of systems biology tohelp us understand the causes of diabetes?

Using the systems approach, mathematical or computermodels are constructed based upon known intra- and/orinter-organ signaling patterns. The models are tested byexperiment, validated, or altered, and the parameters ofthe model, which represent real physiological processes,can be measured from experimental data. Such an ap-proach can potentially lead to an understanding of theimportance of inter-organ communication with blood glu-cose regulation and can tell us how a breakdown in thiscommunication breeds disease. But how should such amodel be constructed?

SYSTEMS ANALYSIS AND DIABETES

At this juncture it remains a daunting challenge to convertthe mountain of data emerging from the new technologiesto yield deep understanding of diabetes. In the course ofdealing with these newer technologies, it will be importantto reduce the data to a simplified comprehensive portraitamenable to clinical interpretation. It is critical to remem-ber the dictates of William of Occam (“Occam’s Razor”),“entia non sunt multiplicanda praeter necessitatem,”which translates to “entities should not be multipliedbeyond necessity” (14). Albert Einstein reminds us torepresent physical reality in its simplest form—but not toosimple (!!).

Some years ago we attempted to apply the principle of

From the Keck School of Medicine, University of Southern California, LosAngeles, California.

Address correspondence and reprint requests to Richard N. Bergman, PhD,Keck Professor of Medicine, and Chair, Department of Physiology andBiophysics, Keck School of Medicine, MMR626, 1333 San Pablo St., LosAngeles, CA 90033. E-mail: [email protected].

Received and accepted for publication 20 February 2007.Additional information for this article can be found in an online appendix at

http://dx.doi.org/10.2337/db07-9903.CNS, central nervous system; FFA, free fatty acid; GIP, glucose-dependent

insulinotropic peptide; GLP-1, glucagon-like pepetide-1.DOI: 10.2337/db07-9903© 2007 by the American Diabetes Association.

DIABETES, VOL. 56, JUNE 2007 1489

“Occam’s Razor” to describe glucose control (15). Havingmeasured glucose and insulin levels in blood minute byminute after intravenous glucose, we selected a decep-tively simple, but physiologically based, model that couldtotally and accurately account for the glucose and insulinkinetics measured after intravenous glucose injection (16–19). This “minimal model” cannot be said to be the onlyrepresentation that could be acceptable, but it has sur-vived several decades of investigation and probing by asignificant number of independent investigators, includingmathematicians (20–22). Every model is a hypothesis andis therefore imperfect by definition. But, given its survival,we may conclude that the minimal model is a reasonablyaccurate representation of glucose regulation.The minimal model. The minimal model is represented inFig. 2A; Fig. 2B presents a diagrammatic representation ofthe model revealing the underlying assumptions—theminimal assumptions required to describe glucose andinsulin kinetics after injection. The required processesincluded the following:

● Under overnight fasting conditions, endogenous hepatic(and renal) glucose production is balanced by basalglucose utilization by brain (50% of total) and othertissues.

● Prandial elevation in glycemia is renormalized in part byglucose’s ability to enhance its own disposal and sup-press liver production (16,23–25) independent of theplasma insulin response. This “glucose effectiveness” isreduced in type 2 diabetes (26).

● Intake of carbohydrate elicits a prompt insulin re-sponse critical to glucose renormalization. Impor-tantly, the renormalizing effects of insulin on glucoseproduction and uptake are not manifest immediately,but modeling required a significant temporal delay ininsulin’s actions. Trying to explain this temporal delayin insulin’s actions taught us much about insulinaction in vivo (see below).

Has the minimal model been useful? Its original publi-cation was hardly a barnstormer in that the model washardly cited in the literature for 5 years after appearing.What appears to have increased its significance since arethe following. 1) The model was validated by severalindependent laboratories (27–29). 2) The model, coupledwith experimental work, helped increase understanding ofphysiology and pathophysiology. 3) The model has led toclinical tools useful in the clinic and in epidemiologicaland genetic studies (30–32).

FIG. 1. Reductionist vs. holistic approaches to study carbohydrate homeostasis. Elegant molecular and genetic approaches have elucidatedcellular pathways of hormone action, including insulin (left) (ref. 12). Alternative approach (right) is to test the system in vivo and comparepredictions with computer model to hone hypotheses of hormone/substrate interactions.

ORCHESTRATION OF GLUCOSE HOMEOSTASIS

1490 DIABETES, VOL. 56, JUNE 2007

Emergent research. We can identify three main research“branches” which represent offspring of the minimalmodel (Fig. 3):

1. Applying the model resulted in the simultaneousmeasurement of insulin sensitivity and insulin re-sponse from a single clinically applicable protocol.These measurements led us to define the “dispositionindex,” an important index of �-cell functionality andpredictor of impaired glucose tolerance and diabetes(16 –18,33).

2. Studying the aforementioned insulin action delay re-vealed the importance of insulin movement across thecapillary endothelium (and possibly capillary recruit-ment) in insulin action and insulin resistance.

3. An unexpected temporal delay in insulin suppression of

liver glucose production evoked the role of free fattyacids as a mediator of insulin action on the liver.

The present exposition will follow the branches of themetaphorical tree shown in Fig. 3. I will describe ourjourneys to follow up the clues that the minimal model hasprovided us to climb branches that hopefully have in-creased to a measurable extent our understanding of whatcauses type 2 diabetes and what may be done to try topredict, prevent, and eventually cure it.

BRANCH #1: Clinical tools and the disposition index

After years of often contentious debate, a consensus hasemerged regarding the pathogenesis of type 2 diabetes(online appendix Fig. A1 [available in an online appendix

FIG. 2. The minimal model of glucose kinetics. A: Insulin in plasma [I(t)] crosses the endothelial barrier to enter interstitial fluid (I’). Productionof glucose (G) by liver and glucose disposal in periphery are controlled by “remote” (i.e., interstitial) insulin concentration. Later studiesconfirmed that slow effect of insulin on liver is due to indirect effect of the hormone to suppress glucose production (via free fatty acids; “singlegateway hypothesis,” ref. 83). Adapted from ref. 16. B: Diagrammatic representation of the minimal model. Fasting blood glucose level isdetermined by a balance between liver production and insulin-independent (brain) and insulin-dependent (skeletal muscle) mechanisms.Carbohydrate intake elicits insulin signal; insulin slowly crosses capillary endothelium to enhance glucose disposal to muscle and suppresslipolysis in adipose, which in turn contributes to reduction in liver glucose output.

R.N. BERGMAN


at http://dx.doi.org/10.2337/db07-9903]) (34,35). Insulin re-sistance is an important risk factor, necessary but notsufficient to cause the disease. There may be a geneticcomponent to resistance (36), but many nongenetic fac-tors can contribute, including obesity (particularly truncalobesity), lack of exercise, onset of puberty, pregnancy,and a group of conditions and therapies such as polycysticovarian syndrome, infection, and treatment for HIV. Weare now aware that a reduced compensatory response ofinsulin secretion in the face of insulin resistance is neces-sary for the development of frank type 2 diabetes. Tounderstand the pathogenesis of diabetes, both insulinresistance and �-cell function must be assessed. Oneapproach to assessment is the intravenous glucose toler-ance test, which is described as follows.

In a healthy individual, upon glucose injection, glucoserises immediately to an early peak due to distribution inthe extracellular fluid (online appendix Fig. A2). Immedi-ately after, glucose begins to return toward basal levelsdue to glucose’s own effect to enhance cellular uptake(due to mass action as well as glucose transporter mobi-lization to the membrane) (37) and glucose’s ability tosuppress hepatic glucose output (“autoregulation”)(23,24). We termed these two latter effects of glucose perse “glucose effectiveness” (16). The attendant hyperglyce-mia simultaneously provokes the �-cells to release insulin;soon the secreted insulin migrates from the plasma to theinterstitial space of skeletal muscle, binding to insulin-sensitive cells and enhancing glucose disposal. The latterinsulin effects accelerate the renormalization of glucose; insensitive individuals glucose may slide below basal beforerenormalization between 3–4 h. Accounting for the mea-sured time courses of glucose and insulin data with a

digital computer (online appendix Fig. A2) yields esti-mates of the physiological coefficients of the model. Suchfitting can be done even for a single individual. With RayBoston and colleagues at the University of Pennsylvania,we have provided software, “MINMOD Millennium” (copy-right R.N. Bergman) (38), that allows for this computer“fitting” process in a friendly computer environment. Theresulting metabolic profile allows us to distinguish amongdifferent individuals, groups, or populations in terms ofmetabolic function (31,39–42).Physiologic parameters from the minimal model.What are the physiological coefficients that emerge fromfitting the minimal model to real data from an individual?The most significant ones, along with normal glucosetolerance, impaired glucose tolerance, and diabetes val-ues, are listed in Table 1.Applications of the minimal model. The model has beenwidely applied to physiological and pathophysiologic sit-uations, in animals and in human subjects. A cursorysearch of the literature reveals nearly 900 minimal modelpublications about widely varying subjects, ranging fromarcane mathematical treatments (20–22) to studies inanimals (23,43,44) and humans (29,31,45). Many of theseapplications have employed the frequently sampled intra-venous glucose tolerance test to yield insulin sensitivityand secretory response. The use of the minimal model iscontinuing. It yields a useful metabolic profile that can beapplied to physiologic and pathophysiologic studies, com-parison of therapeutic regimens, population dynamics, andpopulation genetics.Disposition index. We hypothesized that in a normalindividual, insulin resistance would be compensated byincreased insulin secretion and that this compensation

FIG. 3. History of research in the Bergman Laboratory. Minimal model assumptions were tested experimentally, leading to the DI (DispositionIndex) concept, the role of transendothelial insulin transport, and role of FFAs in the “Metabolic Xyndrome.”



explains why normal glucose tolerance can be maintainedin the face of even large changes in insulin sensitivity dueto environmental or other nongenetic factors. This re-markable ability of the �-cells to precisely compensate isindicated in online appendix Fig. A3, in which a high-fatdiet in the normal dog model induces severe insulinresistance and frank hyperinsulinemia but absolutely nochange in either fasting or 24-h glucose excursions.

One significant outcome of minimal model studies wasan ability to express in quantitative terms the compensa-tory relationship between insulin resistance and insulinresponse. Again we were inspired by an engineeringconcept, that of “closed loop gain.” The regulation of theblood glucose concentration represents a classic closed-loop endocrine feedback system: nutrient ingestion in-creases glucose, leading to a reflexive stimulation ofinsulin release, which counters the tendency to hypergly-cemia. The ability of this closed-loop system to normalizeglucose quickly can be expressed as the product of therelease of the signal, plasma insulin response, and theeffect of that signal, insulin sensitivity. We thereforedefined the disposition index (DI) as a measure of theoverall ability of the glucose regulating system to renor-malize glycemia after perturbation by nutrient intake (16).The DI was defined as follows:

DI � AIR GLUCOSE � SI

where AIR is the acute insulin response. There is strongevidence for increased plasma insulin in the face ofinsulin resistance, at least in normal individuals (46).Therefore, the DI can be interpreted as the ability of theglucose regulating system to compensate for insulinresistance by increasing plasma insulin. We hypothe-sized that in normal individuals, a reduction in SI(insulin resistance) would be compensated by an equiv-alent increase in plasma insulin response, such that theDI remains relatively constant (Fig. 4, 2 SI compen-

sated by 1 in AIRGLUCOSE). The latter concept, imple-mented as Eq. 1, has been referred to as the “HyperbolicLaw of Glucose Tolerance” (47). Online appendix Fig.A4 shows the constancy of the DI in the face of insulinresistance.Interpretation of DI. Confusion regarding the relativeimportance of �-cell dysfunction to type 2 diabetes re-sulted from the fact that hyperinsulinemia often accompa-nies insulin resistance, even in the face of a latent �-celldefect. Thus, an individual with reduced DI may increaseplasma insulin in the face of insulin resistance (Fig. 4), but

TABLE 1Physiologic parameters emerging from the minimal model (data from refs. 39,42)

Parameters emerging from fitting the minimal model Normal IGTType 2

diabetes

SG Glucose effectiveness (min�1): This parameterreflects the effect of glucose per se to enhanceglucose disposal and suppress glucose output, atbasal insulin concentration.

0.021 � 0.008 0.016 � 0.007 0.015 � 0.011

AIRGLUCOSE Insulin response (�U/ml � min): This can belimited to first-phase release (0–10 min above basal)but can also yield second-phase response,depending upon which injection protocol is used

59.6 � 54.8 42.4 � 42.6 6.7 � 18.5

SI Insulin sensitivity (� 10�4 min�1 per �U/ml):

Probably the most important parameter is theinsulin sensitivity index (SI). This index reflects toability of insulin in blood to augment glucose’sability to activate its own disappearance and tosuppress glucose output. The SI is quantitative. It isnormalized to the size of the glucose distributionvolume, making SI values comparable amongindividuals, between genders, between ethnicgroups, and even between species.

2.62 � 2.21 1.27 � 1.20 0.57 � 0.82

DI Disposition index: The DI is the product of SI andAIRGLUCOSE. It represents the ability of the b-cellsto compensate for changes in insulin sensitivity (seetext).

1,249 � 1,559 430 � 594 30 � 95

IGT, impaired glucose tolerance.

FIG. 4. The Hyperbolic Law of Glucose Tolerance. Insulin resistance(abscissa) is normally compensated by a reflexive hyperinsulinemia, tomaintain glucose tolerance. The law states that in normal individuals,product of insulin sensitivity and secretion is constant—the DI. Inat-risk individuals, DI may be reduced (lower hyperbolic curve). Insuch individuals, hyperinsulinemia for a given reduction in insulinsensitivity may be inadequate (lower DI). Lower DI may portenteventual type 2 diabetes.

R.N. BERGMAN


the degree of compensation may be less than expected ifthe �-cells were healthy. Thus, while impaired glucosetolerance is often associated with increased risk for dia-betes, and with �-cell dysfunction, the degree of dysfunc-tion is represented by a reduced DI compared with healthyindividuals. Therefore, it is reasonable to suggest thatreduced DI is a harbinger of type 2 diabetes. In the PimaIndians, Weyer and colleagues identified the DI as thestrongest predictor of conversion from normal glucosetolerance to type 2 diabetes in a longitudinally observedpopulation over a period of 5 years (48), and a similarresult emerged from the Malmo Prospective Study ofpre-diabetes (49).

There is an emerging consensus that reduced �-cellfunction as reflected in the DI is the strongest predictor oftype 2 diabetes in at-risk populations. But does thisreduced islet function have a genetic component?Genetics of DI. Type 2 diabetes has higher concordancein monozygotic versus dizygotic twins (50), suggesting astrong genetic basis for this disease. Numerous studieshave attempted to identify the specific inherited metabolicfunction(s) or gene(s) that might be responsible. Herita-bility calculations have supported indices of �-cell func-tion as being important. The heritability of DI has beenestimated to be as high as 0.73 in an African-Americangroup (36). Poulsen and colleagues used state-of-the-artmethodology to measure a variety of metabolic parame-ters in monozygotic and dizygotic Danish twins (50). Theyreported heritabilities for the DI of 0.75 in younger andidentical twins but much lower values in younger fraternalsets (0.30). These data strongly support the inheritance of�-cell function and suggest that it is inheritance of reducedDI, which may contribute to increased genetic risk for type2 diabetes.

It is not known what gene or genes may explain inher-itance of DI. One clue has emerged from two disparatepopulation studies—the FUSION Study of type 2 diabetesin Finland and the IRAS Family Study of several ethnicitiesin the U.S. (51,52). Both studies have identified a locus onchromosome 11 related to diabetes risk and linked withthe DI. Given the heritability of DI and similarity of theseloci—logarithm of odds score of 4.80 at 80 cM for linkageto the DI in the IRAS Family Study and predisposition totype 2 diabetes at a similar locus in the FUSION Study—itis tempting to hypothesize that there may be a gene for DIin this region of chromosome 11 that predisposes todiabetes. Until the putative gene for DI and/or diabetes onchromosome 11 is identified, it will remain unknown whatis the true significance of this interesting region fordiabetes inheritance. Very recently, several groups havereported 10 genes emerging from genome-wide associa-tion studies that increase risk for type 2 diabetes (53–55).While the function of the genes are not all known, severalappear to be related to �-cell function.What is the mechanistic explanation for the “Hyper-bolic Law of Glucose Tolerance”? It would seem obvi-ous that the increase in insulin response that attends onsetof insulin resistance might be explained by the sequence ofevents of online appendix Fig. A5; that is, insulin resis-tance leads to a small reduction in glucose tolerance, mildhyperglycemia, and resultant increase in �-cell massand/or sensitivity to glucose stimulation. The glycemichypothesis has been strongly supported in a recent publi-cation (56). However, there is evidence that glycemia perse may not play a primary role. In fact, in the face ofobesity induced by either elevated fat-eucaloric or ele-

vated fat-hypercaloric diets, we observed the expectedincreased body weight, insulin resistance, and hyperinsu-linemia and relatively constant DI (online appendix Fig.A4) (43,57). Surprisingly, we did not observe any increasein fasting hyperglycemia. Not only were fasting glucoselevels either constant or slightly reduced by the fat intakeregimen, but there was absolutely no change in 24-hglucose values (online appendix Fig. A6) (58). Neither didwe observe increases in other putative signals, such ascortisol or active GLP-1. These data indicate that in theconscious dog model, glucose cannot be the signal respon-sible for �-cell upregulation in the face of fat-feeding/obesity-induced insulin resistance. Neither can steroids orthe gut peptide GLP-1 play this important role. As will bediscussed below, there is stronger evidence that free fattyacids (FFAs) may play the central role in accounting forthe increase in insulin secretory response in the face ofnutrient-induced insulin resistance. However, at this mo-ment in time, despite extensive evidence for the hyper-bolic relationship between insulin sensitivity and insulinsecretion (17,45,59,60), the precise signaling accountingfor this fundamental physiological relationship remainsunexplained! Needless to say, we continue the search forthe mechanism(s) that may explain the “Hyperbolic Law ofGlucose Tolerance.”

BRANCH #2: Transendothelial transport and insulinresistance

As discussed above, one requisite assumption in theminimal model is the sluggish or delayed effect of insulinto stimulate glucose disappearance. This model resultrecapitulated conclusions from Andres, Sherwin, and col-leagues (61) from the first clinical glucose clamp studies,showing that the rapid increase in plasma insulin byinjection resulted in a slow enhancement of glucosedisposal, which did not reach steady state before 3 h.Online appendix Fig. A7 compares the rapid effect ofinsulin in vitro to stimulate glucose uptake by adiposecells, with the sluggish effect in vivo. We were interested inunderstanding the physiologic basis underlying this slowinsulin effect, as well as understanding its possible role ininsulin resistance and diabetes pathogenesis.

Once secreted, insulin follows a tortuous path to stim-ulate glucose uptake. Entering the bloodstream from thepancreatic veins, it must survive passage through the liver(at least 50% of secreted insulin does not) and travel fromthe venous system to muscle or adipose capillaries ratherimpermeable to large proteins. The large protein moleculemust either pass through capillary endothelial cells orbetween them through paracellular routes to enter theinterstitium, diffuse to target cells, bind, and act via theinsulin pathway. The delay in insulin action might be dueto slow biochemical steps after receptor binding; alterna-tively, it may be the delivery of insulin to the sensitive cellsthat is slow (62). To examine the transendothelial trans-port process, and to compare the time course of plasmainsulin with that of interstitial insulin and glucose dis-posal, we exploited the use of lymph sampling to accessthe interstitial fluid. Our studies showed clearly that thereis a strong “hand-in-glove” temporal relationship betweeninterstitial insulin and glucose disposal but a weak rela-tionship between plasma insulin and glucose uptake(63,64). We concluded that the delay in insulin actionobserved in the glucose clamp experiments and imple-mented in the minimal model is due to sluggish movement



of insulin across capillary endothelium between plasmaand interstitium; but, once at the cell surface, insulin bindsand acts almost immediately (as observed in vitro, Fig. 5).Implications of sluggish transendothelial transportof insulin. When stimulated by rapid changes in plasmaglucose, insulin release from the �-cells is biphasic. Thisbiphasic pattern, originally described by Grodsky andcolleagues (65,66), has been much studied and reflects twopools of releasable insulin within the �-cells, which haverecently been imaged directly (67). It is interesting tocontemplate the possible significance of biphasic releasewith regards to overall glucose regulation. Is it possiblethat biphasic secretion evolved to compensate for slowtransendothelial insulin transport, which temporally limitsinsulin’s access to skeletal muscle and adipose tissues?

Lisa Getty, when in our laboratory, injected insulinintravenously to simulate the first-phase insulin release(online appendix Fig. A8). A quick but short first-phaseinsulin pattern obviates the usual delay in insulin action(seen during glucose clamp experiments, for example),resulting in a rapid and profound increase in glucosedisposal (68). It is tempting to hypothesize that the firstphase of insulin release was naturally selected to accordthe most rapid glucose disposal after nutrient ingestionand to limit the postprandial glycemia. Such a suppositioncan never be proved, but it does provide a potentiallysatisfying explanation for the evolution of a rapid first-phase insulin response.

A very important but still unanswered question relatesto the putative importance of transendothelial transport inpathogenesis of insulin resistance. Clear biochemical de-fects have been identified in insulin-resistant animal mod-els and humans, including receptor downregulation,

phosphatidylinositol 3-kinase defects, reduction in mito-chondrial function, and reduced numbers of glucose trans-porters. But, is there a defect in delivery of insulin to thesensitive cells?

Martin Ellmerer, in our laboratory, worked with JoyceRichey and used compartmental modeling to analyzedistribution of insulin in animals rendered obese with ahigh-fat diet (69). Their analysis suggested that obesitylimited access of insulin to skeletal muscle, accounting forabout one-half of the insulin resistance caused by high-fatfeeding. Very recently, to examine the possible effects ofobesity on insulin kinetics more directly, Jenny Chiuworked with Richey to examine the movement of insulinwithin the interstitial compartment of muscle tissue.These investigators injected insulin directly into muscleand measured insulin in the interstitium (lymph) andglucose disposal by the hindlimb. We found that glucoseuptake by skeletal muscle in normal animals is much moresensitive to the hormone than is suggested by systemicmeasurements and glucose clamps (Vmax �22 mg � min�1

� leg�1 and an ED50 of �120 pmol/l). The latter resultimplies that availability of insulin to the sensitive tissue islimited by either transport across endothelium or distribu-tion of blood flow between “nutritive” versus “non-nutri-tive” tissues, as suggested by Clark, Barrett, and theircolleagues (70,71). Even more interesting is the recentresult of Chiu and colleagues (69) that infusion of the lipidemulsion Liposyn, which raises peripheral FFA levels,appears to absent insulin from skeletal muscle tissue—when Liposyn is infused, insulin appears to exit skeletalmuscle rapidly, as there is virtually no increase in intersti-tial insulin despite direct injection of the hormone intomuscle tissue. The latter result suggests rapid washout of

FIG. 5. Proposed events in insulin stimulation of glucose disposal. Insulin crosses from capillary to interstitial compartment slowly; delay maybe due to intercellular or transcellular transport. Once in interstitium, insulin binds to receptors and rapidly stimulates glucose uptake.

R.N. BERGMAN


insulin from skeletal muscle, which could suggest a greatincrease in permeability of capillary endothelium to theinsulin molecule. It is clear that availability of insulin tothe sensitive tissues (muscle and adipose) is a major factordetermining insulin sensitivity. Thus, conclusions regard-ing insulin action from measurements of cellular andsubcellular function alone cannot reproduce insulin’s ac-tion in vivo, and the availability of insulin at skeletalmuscle deserves further study.

The slow action of insulin, revealed by minimal model-ing and glucose clamp experiments, have led to interestingand potentially important insights regarding the action ofinsulin and mechanisms of insulin resistance. Given thatinsulin resistance is an important factor, albeit not theonly factor in pathogenesis of type 2 diabetes, furtherstudy of insulin access to skeletal muscle and adiposetissue is justified.

BRANCH #3: The role of FFAs in insulin action andglucose homeostasis

In normal individuals, several factors guarantee that theblood glucose level is normalized rapidly after meals. Indogs in particular, this normalization process is remark-able, as there is little increase in the blood glucose afterglucose ingestion, despite the large increase in glucoseturnover (72). Rizza and his colleagues (73) have exam-ined the plethora of factors that play a role in thisnormalization, which involves suppression of endogenousglucose output (primarily by liver) and enhancement of

glucose disposal (primarily by skeletal muscle). One of themost interesting factors is the gut peptide GLP-1, whichhas several effects to normalize glucose: slowing of gastricemptying, enhancement of the plasma insulin response,and suppression of glucagon (74). Viorica Ionut, in ourlaboratory, and others have exciting results pointing toan additional and potentially potent effect of GLP-1 toincrease glucose effectiveness (75–77), possibly viaGLP-1 receptors in the porta hepatic circulation, via thecentral nervous system (CNS) to muscle (Fig. 6). Evi-dence emanating from Rossetti’s laboratory that glu-coreception in the CNS may control hepatic glucoseoutput by liver directly (78) adds to the concept that theCNS is more important than has been previouslythought (in glucoregulation).

Intravenous administration of glucose (as in the fre-quently sampled intravenous glucose tolerance test, forexample) bypasses effects of gastrointestinal peptides, andyet glucose is rapidly normalized. The euglycemic glucoseclamp examines effects of insulin per se on normalizationand, as discussed, reveals slow activation of glucoseuptake (online appendix Fig. A9). Traditional thinkingpresumed that suppression of glucose output, unlike acti-vation of disposal, would be very rapid, as insulin secretedby the �-cells has immediate access to the liver via theportal vein. In addition, portohepatic vessels have largefenestrations, allowing insulin entering the liver from theportal vein to access and bind to hepatocytes almostimmediately after appearance in the liver. Scintigraphy

FIG. 6. Possible indirect effect of gastrointestinal peptide GLP-1. GLP-1 degrades rapidly in plasma, suggesting that it may have a site of actionclose to its site of secretion (L-cells of gut). Putative receptors in the portal vein (or liver) are sensitive to GLP-1 and glucose; interaction withreceptors may send afferent signal to brain with efferent signals to enhance glucose utilization (e.g., increased insulin secretion, reducedglucagon, and/or increase in insulin-independent glucose uptake). Extant data show enhanced glucose disposal secondary to portal glucose/GLP-1administration (ref. 73).



confirms very rapid concentration of injected insulin mol-ecules in liver tissue (79). Yet, in modeling we were able toaccount for glucose kinetics by making the counterintui-tive assumption that insulin action to suppress endoge-nous glucose output was sluggish, similar to the effect ofstimulation of glucose disposal. This latter assumptionwas ultimately confirmed by David Bradley in our labora-tory using euglycemic glucose clamps (80)—stimulation ofglucose uptake and suppression of production wereequally slow, with almost identical kinetics (i.e., similart1/2). This latter result led to the counterintuitive hypoth-esis that the effect of insulin to suppress glucose output bythe liver was an indirect effect of the hormone (i.e.,mediated by one or more insulin-dependent extrahepaticsignals).Search for the signal mediating insulin action. Severalsignals seemed possible candidates for mediating theapparent indirect insulin effect (online appendix Fig. A10).Further investigation utilizing the glucose clamp revealeda remarkable similarity between insulin suppression ofglucose output and insulin suppression of lipolysis fromadipose tissue (81,82). It was known that 1) the delay ininsulin effect on disposal was due to slow transendothelialtransport. From early studies of Scow and colleagues (83),it was also known that 2) access of insulin to adipocytes(similar to skeletal muscle access) was relatively slow. Weattempted to explain these results by the “single gatewayhypothesis” (84) (online appendix Fig. A11). It was positedthat the slow effects of insulin on production and disposalwere explained by slow transport into muscle and adiposetissue. The former slowed increasing glucose disposal, andthe latter slowed suppression of FFA, hence slowing thesuppression of glucose output. There is still debate regard-ing what precise fraction of suppression of glucose outputis secondary to suppression of FFA (85). However, there isconsensus that FFA suppression accounts for at least partof the reduction in gluconeogenesis and glycogenolysisthat accompanies nutrient intake. What was important toour laboratory was the realization that FFAs play a moreimportant role than previously appreciated in glucosehomeostasis (7). A similar message was emanating fromother laboratories (86). Adding to this understanding wasepidemiologic evidence for the importance of adiposity—especially truncal adiposity—in the development of insulinresistance and as a risk factor for type 2 diabetes andcardiovascular disease. To further examine the role ofFFA, and adiposity per se, we developed a canine model ofobesity.The role of FFA in pathogenesis of the metabolicsyndrome. It is a truism that obesity is increasing in theU.S. and other Western countries and is also increasing inless–well-developed nations (87). Obesity is an importantrisk factor for type 2 diabetes due to its close relationshipwith insulin resistance. Yet, the mechanistic relationshipsamong obesity, insulin resistance, and diabetes are nottotally clarified. There is strong epidemiologic evidencethat central adiposity, in particular, carries risk. Experi-mental studies are needed to explain the causal relation-ships between central adipose depots and risk.

There are particular advantages in studying obesity inlarge animal models. Insulin resistance and obesity arecharacterized by communication among different tissuessuch as adipose and liver, and in the dog model it ispossible to access the abdominal portal vein reflectingvisceral fat signaling to the liver. In addition, in the caninemodel it is possible to study the development of obesity

longitudinally (or reversal thereof) while making repetitivemetabolic measurements. One such study followed thetime course of insulin resistance, insulin secretion, andinsulin clearance in the canine model fed a diet withelevated fat content (online appendix Fig. A3) (43). It isnoted that there was a reduction in insulin sensitivity thatwas followed by a slow increase in insulin response, whichreached a peak at 6 weeks. Complimenting increasedinsulin response was a reduction in first-pass clearance ofinsulin by liver, which accounted for at least as muchhyperinsulinemia as increased insulin release (43,88). Asdiscussed, despite these significant changes, there was nodetectable change in DI. What mechanisms account forthis well-orchestrated response to lipid intake withoutchanges in glucose tolerance in the normal animal?

Nuclear magnetic resonance confirmed a significantdeposition of lipid in both the central (omental) andsubcutaneous fat depots during fat feeding (online appen-dix Fig. A12). Very recent data obtained by Morvarid Kabirin our laboratory confirms that while there are increases inadipose deposition in visceral as well as subcutaneousdepots in fat-fed dogs, the visceral depot is unique. Aspreviously reported (89,90), we noted that visceral fattissue is more sensitive to adrenergic stimulation of lipol-ysis (ED50 of 1.31 � 10�7 mol/l compared with 2.77 � 10�7

mol/l for subcutaneous adipose tissue). Very interesting isthe appearance in the enlarged omental fat depot of aunique population of “new” smaller adipocytes, suggestingconversion of preadipocytes to fully developed adipocytespreferentially in the visceral depot. Euglycemic clampresults revealed that most of the developing insulin resis-tance after feeding the eucaloric high-fat diet was due toresistance of the liver (91). We observed failure of insulinto suppress endogenous glucose output before significantchanges in peripheral insulin sensitivity, measured asinsulin’s action to stimulate glucose disposal. Assessmentof expression of genes in visceral tissues as well as liverrevealed a pattern that favored increased turnover ofomental fat, as well as enhanced hepatic gluconeogenesis(92)—changes that favor an effect of FFA, released fromthe visceral adipose depot, to cause hepatic insulin resis-tance (online appendix Fig. A13). However, in this modelof modest obesity, we did not observe changes in expres-sion of genes for “adipokines” including tumor necrosisfactor-�, interleukin-6, leptin, or adiponectin. Therefore,central obesity induced by 6 weeks of elevated fat causesliver insulin resistance and hyperinsulinemia with a pat-tern supporting increased flux of FFA from visceral depotto liver but without measurable changes in expression ofadipokines in visceral adipose tissue. These data supportan important role for FFA release from the visceral fat inthe pathogenesis of insulin resistance associated withincreased truncal lipid deposition.

Access to the portal vein allowed us to measure the rateof release of FFA from the visceral depot. To our surprise,we found that visceral FFA release was oscillatory, with aburst observed about every 9–11 min (online appendixFig. A14) (93,94). That the release was lipolytic wassupported by a similar and coordinated pattern of glycerolrelease. Pulsatile visceral lipolysis was totally suppressedby bupranolol, a high-affinity antagonist to �-3 adrenergicreceptors, located in the visceral fat depot of the dog.Recent data obtained by Isabel Hsu in our laboratory havesupported the concept that oscillations imposed in theportal vein of the conscious animal have profound effectsto enhance insulin resistance of the liver.

R.N. BERGMAN


Our data has led us to support the original concept ofLandsberg (95) that the sympathetic nervous system playsa central role in the development of insulin resistance,secondary to deposition of visceral fat. We suggest that fatfeeding results in deposition of visceral fat. Adrenergicsignals from the CNS induce phasic lipolysis of the visceraldepot, which bathes the liver with FFA at regular intervals(online appendix Fig. A15). This FFA barrage inducesinsulin resistance in the liver by upregulating gluconeo-genic enzymes. Further studies are being performed toaddress the source of the central adrenergic signals, howthey may depend upon metabolic state, and what role thesignals may play in other insulin-resistant conditions.Hyperinsulinemic compensation for insulin resis-tance: putative role of nocturnal FFAs. As discussed,it remains unexplained why in the face of insulinresistance, plasma insulin response increases and insu-lin clearance decreases in a well-coordinated mannersuch that, in normal animals, glucose intolerance doesnot invariably result in the insulin-resistant state. Howdo the �-cells of the pancreatic islets “know” theappropriate enhancement of insulin release? How doesthe insulin-degrading mechanism of the liver establishthe appropriate downregulation of first-pass liver insulinclearance? As discussed above, careful investigation ofglycemia failed to explain insulinemic upregulation. Isthere a possibility that FFAs are involved in this highlyregulated inter-organ orchestration?

We considered a group of blood-borne signals that

could be put forth as mediating hyperinsulinemia in theface of fat-diet–induced insulin resistance (58). Amongthese candidates were GLP-1, known to cause pancre-atic islet-cell proliferation in rodents, and growth hor-mone and cortisol, each of which can result in increasedinsulin. After 6 weeks of a high-fat, hypercaloric diet,resulting in significant weight gain in the dog model, weobserved zero evidence for any increase in 24-h glyce-mia (online appendix Fig. A6). Even more surprising, wemeasured a paradoxical reduction in 24-h active GLP-1levels and no increases in either 24-h patterns of cortisolor growth hormone. On the contrary, and to our sur-prise, we observed a striking and powerful increase inplasma FFA levels in the middle of the night. Comparingthe fat-fed animal with the lean model, FFAs are in-creased beginning in the late afternoon and continue toelevate with a maximal elevation at 3 A.M. What is thesignificance of the nighttime FFA increase, and does itrelate to our sympathetic hypothesis of the causation ofthe metabolic syndrome?

We are attempting to understand the significance of thenighttime FFA increase. We would propose that it repre-sents lipolysis, stimulated by the sympathetic nervoussystem. If so, the increasing FFA may be oscillatory, andadrenergic blocking agents should suppress them specifi-cally. While it is indeed tedious to do rapid sampling toestablish oscillatory lipolysis, students in our laboratoryare doing these studies, led by Stella Kim, Isabel Hsu,Jenny Chiu, and Karyn Catalano. We plan to test whether

FIG. 7. Events resulting in the “Metabolic Xyndrome.” CNS and other factors result in lipolysis from visceral and subcutaneous fat depots.Visceral fat depots in particular cause flux of FFA to liver and hepatic insulin resistance; more stored fat causes insulin resistance of skeletalmuscle. In our experiments, compensation for insulin resistance (hyperinsulinemia) occurs in the absence of elevated glucose. FFAs themselvesmay be the compensating signal that causes the hyperinsulinemia by stimulating insulin release, increasing �-cell size or number, and reducingliver clearance of insulin. Hyperinsulinemia is adequate to compensate for insulin resistance, except in the face of a latent �-cell defect, whereinhyperglycemia ensues and type 2 diabetes results.



the lipolysis can be blocked with adrenergic blockingagents, and if so, whether this will reverse the putativeeffects of elevated nocturnal FFA on insulin secretion andaction.Hypothesis integrating the role of FFAs in the meta-bolic syndrome. Our working hypothesis for the role ofthe visceral fat depot in the development of the metabolicsyndrome (Fig. 7) is as follows: We suggest that theadrenergic nervous system plays a central role in thedevelopment of the syndrome. We suggest that fat feedingincreases the signaling from the brain to the adipose depotand that this signal is particularly evident at night, maxi-mized at 3:00 A.M. We further suggest that the sympatheticsignal results in bursts of FFA via the portal vein, bathingthe liver in lipid and rendering it insulin resistant. Theresistance, at least in the short term, does not appear toinvolve changes in adipokines, although it is certainlylikely that adipokines are important over the longer term.The resistance is associated with increase of expression ofenzymes that favor lipolysis and enhancement of glucone-ogenesis. It is possible that interfering with this pattern,for example by suppressing lipolysis during the nighttime,may break this pattern and reverse the insulin resistanceof the metabolic state.

THE TREE, ITS RICH SOIL, AND ITS FERTILIZERS

I have been a very lucky person. With my wonderfulcolleagues (see ACKNOWLEDGMENTS), we have been able tobegin with an arcane idea—development of a minimalmodel of glucose kinetics—and to follow this “acorn”where it led us, hopefully to some greater understandingof the pathogenesis of diabetes and associated metabolicdiseases. Trees will not flourish in the wilderness withoutrich soil and fertilizer. First is my wife Ronni and my kids,Doug and Beth, their spouses, Nancy and Guy, and mygrandchildren, Emily, Jessica, Samantha, and Hannah.

I am a lousy tree climber. I received very necessary “legsup” from many wonderful people and institutions: Myearly mentors included Oscar Hechter, I. Arthur Mirsky,and John Urquhart. Dan Porte, Jr., Mladen Vranic, andLarry Phillips were kind enough to appreciate our earlyresearch efforts and enabled us to test our ideas in theclinic. My wonderful peers Claudio Cobelli and DianeFinegood were there at the tree’s conception, birth, andearly life, and Marilyn Ader, Richard Watanabe, TomBuchanan, Joyce Richey, and Andrea Dunaif were presentduring the Cambrian adolescence and adulthood. I amtremendously grateful to the wonderful friends/colleagueswho chose to work with me on our journey, listed bynecessity in the ACKNOWLEDGMENTS. Finally, I thank theAmerican Diabetes Association, the National Institutes ofHealth, and the University of Southern California, all ofwhom translated their confidence in our work to thetangible resources without which our work not have beenperformed.

ACKNOWLEDGMENTS

R.B.’s work has been supported by the National Institutesof Health (DK 29867 and DK 27619) and the AmericanDiabetes Association (Mentor Award).

Beloved colleaguesRichard Watanabe, Diane Finegood, Giovanni Pacini, Clau-dio Cobelli, Jay Taborsky, Steve Mittelman, MartinEllmerer, Dave Bradley, Aage Volund, Joyce Richey, Gi-

anna Toffolo, Kerstin Rebrin, Katrin Hucking, Idit Liberty,Vivi Ionut, Mori Kabir, Chester Ni, Pat Crane, MariantheHamilton-Wessler, Lisa Getty, Dave Cohen, Melvin Dea,Jang Youn, Andrea Hevener, Gregg Van Citters, CaseyDonovan, Garry Steil, Y. Ziya Ider, Ray Boston, CharlieBowden, Renee Poulin, Lise Kjems, Stella Kim, KarynCatalano, Isabel Hsu, Jenny Chiu, Darko Stefanovski,Maya Lottati, Nicki Harrison, Orison Woolcott, Dan Zheng,Elza Demirchyan, Rita Thomas, Ed Zuniga, Erlinda Kirk-man, IRAS Investigators, FUSION family, Anne Sumner,Steve Kahn, Michael Goran, Mike Schwartz, and Jim Best.

I am deeply grateful to Dr. Marilyn Ader for helping mewith this manuscript and for many years of fruitful collab-oration and camaraderie.

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R.N. BERGMAN


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