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The Journal of Clinical Endocrinology & Metabolism Vol. 89, No. 1 266-271
Copyright © 2004 by The Endocrine Society

Low Central Nervous System Serotonergic Responsivity Is Associated with the Metabolic Syndrome and Physical Inactivity

Matthew F. Muldoon, Rachel H. Mackey, Katherine V. Williams, Mary T. Korytkowski, Janine D. Flory and Stephen B. Manuck

Divisions of Clinical Pharmacology (M.F.M.) and Endocrinology and Metabolism (K.V.W., M.T.K.), Department of Medicine, University of Pittsburgh School of Medicine; Department of Epidemiology, Graduate School of Public Health (R.H.M.); and Behavioral Physiology Laboratory, Department of Psychology (J.D.F., S.B.M.), University of Pittsburgh, Pittsburgh, Pennsylvania 15260

Address all correspondence and requests for reprints to: Dr. Matthew F. Muldoon, Old Engineering Hall, Room 506, University of Pittsburgh, Pittsburgh, Pennsylvania 15260. E-mail: mfm10{at}pitt.edu.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
The metabolic syndrome, recognized by the co-occurrence of general or abdominal obesity, hypertension, dyslipidemia, insulin resistance, and dysglycemia, appears to involve disturbances in metabolism, autonomic function, and health-related behaviors. However, physiological processes linking the components of the metabolic syndrome remain obscure. The current study examined associations of central nervous system serotonergic function with each metabolic syndrome risk variable, the metabolic syndrome, and physical activity. The subjects were 270 adult volunteers who participated in a study of cardiovascular disease risk factors and neurobehavioral functioning. Central serotonergic responsivity was indexed as the prolactin (PRL) response evoked by the serotonin-releasing agent, fenfluramine. Across the sample, low PRL response was associated with greater body mass index, higher concentrations of triglycerides, glucose, and insulin, higher systolic and diastolic blood pressure, greater insulin resistance, and less physical activity (P < 0.03–0.001). There also existed an inverse linear relationship between PRL response and the number of metabolic syndrome risk factors individuals possessed (P for trend = 0.002). Finally, a 1 SD decline in PRL response was associated with an odds ratio for the metabolic syndrome of 2.05 (95% confidence interval, 1.10–3.83; P = 0.002) and 5.70 (95% confidence interval, 1.69–19.25; P = 0.005), according to the definitions of the National Cholesterol Education Program and the World Health Organization, respectively. These findings reveal a heretofore unrecognized association between reduced central serotonergic responsivity and the metabolic syndrome.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
IT IS NOW well established that several cardiovascular disease (CVD) risk factors—general or abdominal obesity, hypertension, dyslipidemia, dysglycemia, and insulin resistance—tend to aggregate in individuals and covary within populations (1, 2). This constellation of risk factors, which is often labeled the "metabolic syndrome" (3, 4), increases risk of CVD mortality 3-fold, and does so independently of other risk factors (5). The metabolic syndrome affects over 20% of U.S. adults (4, 6) and may explain, in large part, the increased cardiovascular risk associated with obesity (7).

Much research on the metabolic syndrome has focused on relationships among the syndrome’s cardinal features: insulin resistance, excess abdominal adipose tissue, elevated blood pressure (BP), lipid abnormalities, and atherosclerosis (3, 8). It is also possible that central nervous system (CNS) processes are involved in the etiology of the syndrome. For instance, it is generally acknowledged that overeating and sedentary lifestyle contribute to the metabolic syndrome (9, 10, 11). The CNS, in addition to regulating health-related behavior, modulates metabolic processes through autonomic and neuroendocrine pathways, and the metabolic syndrome has been associated with chronic activation of the hypothalamic-adrenal axis (12, 13).

The brain’s serotonergic system, in particular, has neuroanatomic and functional features that suggest involvement in the metabolic syndrome. Serotonin (5-hydroxytryptamine; 5-HT)-containing neurons are concentrated in the raphé nuclei of the brainstem and connect to the cerebral cortex, hypothalamus, and major autonomic nuclei, where they appear to exert broad regulatory control. Central serotonergic activity influences many behaviors (e.g. eating, locomotion, reproduction, sleep, pain, aggression, and stress responses) (14), as well as autonomic functions (e.g. thermogenesis, cardiovascular control, circadian rhythms, and pancreatic function) (15, 16, 17). Moreover, preliminary evidence suggests that the metabolic syndrome may be associated with reduced serotonergic function. For example, insulin resistance has been reported to vary inversely with brain serotonergic activity (18), and genetic variation in two serotonin receptors has been associated with abdominal obesity and diabetes (19, 20).

The present investigation considered the hypothesis that individual differences in CNS serotonergic function are associated with the constellation of risk variables comprising the metabolic syndrome. We evaluated serotonergic function by use of a standard neuropharmacological challenge involving assessment of endocrine reactions to a drug, in this case fenfluramine, that enhances serotonergic neurotransmission. The fenfluramine challenge test exploits the role of serotonin, separate from that of dopamine, in regulating prolactin (PRL) release from the anterior pituitary. The magnitude of the rise in plasma PRL levels reflects central serotonergic responsivity. Based on the PRL response to fenfluramine, we previously reported that serotonergic function correlated inversely with BP in 270 adult men and women (21). Here, we extend these observations to encompass the remaining component features of the metabolic syndrome—obesity, elevated fasting glucose and insulin, hypertriglyceridemia, low high-density lipoprotein (HDL) cholesterol. Serotonergic function is also compared in persons with and without the metabolic syndrome (defined by current criteria) and examined in relation to estimated insulin resistance and physical activity.


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Subjects were participants in the University of Pittsburgh’s Cholesterol and Risk Evaluation Project, a study of the neurobehavioral correlates of CVD risk and lipid modification conducted between November 1992 and July 1996 (22). Subjects were recruited via locally distributed brochures, posters, and media advertisements. All participants were community volunteers 24–60 yr of age. In accordance with the study’s recruitment goals, half of the subjects had elevated low-density lipoprotein (LDL) cholesterol (160 mg/dl), one fourth had normal LDL cholesterol (101–159 mg/dl), and one fourth had low levels of LDL cholesterol (100 mg/dl). Exclusion criteria included diastolic BP of 100 mm Hg or greater, angina pectoris, congestive heart failure, stroke, cancer, chronic liver or kidney disease, and reported use of hypoglycemic, glucocorticoid, or psychotropic medications. Excluded from the present analyses were persons receiving any antihypertensive or cardiovascular medications. A total of 270 subjects meeting these criteria are included in the current analyses. Three subjects (1.1%) had a fasting blood sugar over 125 mg/dl (but none >145 mg/dl), and two (1%) reported a past history of coronary artery disease. Data were complete except for missing fasting glucose and insulin levels in five participants (1.9%). The protocol was approved by the University of Pittsburgh Institutional Review Board, and subjects gave informed consent.

Risk factor assessments

BP measurements and blood samples were obtained at two appointments, separated by 1 to 3 wk. Subjects arrived at the project office between 0800 and 1000 h after a 12-h overnight fast. After they rested in the seated position for 20 min, a registered nurse obtained a single BP measurement in the right arm using a mercury sphygmomanometer and a regular, large, or extra large adult cuff, according to the subject’s arm circumference. The average of the readings from the two visits was used as the subjects’ resting BP. Phlebotomy followed BP measurement. Body mass index (BMI) was calculated as the ratio of weight in kilograms to height in meters squared (kg/m2).

Determinations of serum total cholesterol, HDL cholesterol, and triglyceride concentrations were performed by the Heinz Nutrition Laboratory, Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, which has met the criteria of the Centers for Disease Control–National Heart, Lung, and Blood Institute Lipid Standardization Program since 1982. LDL cholesterol was calculated using the Friedewald equation. Fasting serum lipid concentrations from the two visits were averaged. Samples for fasting serum glucose and insulin, obtained on a single occasion, were analyzed by standard methods described previously (23). An estimate of insulin resistance was calculated based upon the homeostasis model assessment as follows: insulin resistance = serum insulin (µIU/ml) x fasting blood glucose (mmol/liter)/ 22.5 (24). Self-reported physical activity was obtained using the Paffenbarger questionnaire (25).

We used published definitions of the metabolic syndrome according to the criteria of the National Cholesterol Education Program (NCEP) (26) and the modified criteria of the World Health Organization (WHO) (27, 28). Using NCEP criteria, the metabolic syndrome was defined as three or more of the following: 1) fasting serum glucose >= 110 mg/dl; 2) serum triglycerides >= 150 mg/dl; 3) serum HDL cholesterol less than 40 mg/dl in men and less than 50 mg/dl in women; 4) BP >= 130/85 mm Hg; and 5) BMI >= 30 kg/m2. Note that obesity, defined as a BMI of 30 kg/m2 or more, was substituted for large waist circumference because the latter information was not available. According to WHO criteria, individuals have the metabolic syndrome if they have a fasting glucose >= 110 mg/dl or fasting insulin in the upper quartile of the study population, and two or more of the following: 1) fasting serum triglycerides >= 150 mg/dl, or HDL cholesterol less than 35 mg/dl in men and less than 39 mg/dl in women; 2) BP >= 140/90 mm Hg; and 3) BMI >= 30 kg/m2.

Fenfluramine challenge test

Central serotonergic responsivity was measured as the magnitude of the rise in plasma PRL after administration of D,L-fenfluramine hydrochloride. Fenfluramine increases serotonergic neurotransmission by release of serotonin stores, reuptake inhibition, and likely activation by its metabolite of postsynaptic receptors (29). Stimulation of hypothalamic serotonin receptors promotes the pituitary release of PRL, so that the relative increase in circulating PRL concentration induced by fenfluramine provides an index of net serotonergic responsivity in the hypothalamic-pituitary axis (30).

Participants reported to the laboratory in the morning after a 12-h fast, and a heparin-locked venous catheter was inserted. After a 30-min adaptation period, a heparinized blood sample was obtained for determination of baseline PRL concentration. Subjects then received 30, 40, 50, or 60 mg of fenfluramine orally to best approximate a dose of 0.60 mg/kg of body weight. Subsequent blood samples for plasma PRL were drawn 60, 120, 150, 180, and 210 min later. Samples for measurement of plasma fenfluramine and norfenfluramine concentrations were drawn at 150 and 210 min. All blood samples were centrifuged immediately, separated, and stored at -70 C until analysis. Methods for determining plasma PRL, fenfluramine, and norfenfluramine (the principal active metabolic) concentrations have been described previously (31). Validation of this 3.5-h protocol (relative to standard 5-h challenges) and retest reliability of fenfluramine-induced PRL responses are described elsewhere (32, 33).

Statistical analysis

The PRL area under the curve (PRLAUC) in nanograms/milliliter x hour, calculated by trapezoidal integration, was log-transformed to normalize its distribution, and log (PRLAUC) was used for all analyses. The distributions of serum triglycerides, insulin, insulin resistance, and physical activity were also log-transformed for multivariate and regression analyses. Bivariate associations between metabolic syndrome risk variables were evaluated with Spearman correlations. Linear regression was used to determine whether log (PRLAUC) was independently associated with each metabolic syndrome risk variable after adjustment for baseline PRL concentration, age, and gender. PRL responses were also adjusted for concomitant variation in plasma fenfluramine and norfenfluramine concentration (i.e. resulting from individual differences in bioavailability). Potential differences in associations by gender were assessed in models that included the interaction between log (PRLAUC) and gender. Potential differences in mean PRL response, expressed as a function of the number of metabolic syndrome risk factors that subjects possessed, were evaluated with analysis of covariance, with a contrast to test for linear trend. Covariates entered into this model were baseline PRL concentration, plasma fenfluramine and norfenfluramine levels, age, and gender. Finally, logistic regression was used to determine whether log (PRLAUC) was associated with the presence/absence of the metabolic syndrome as indicated by NCEP and WHO criteria, after adjustment for the standard covariates. Where possible, analyses included the five subjects with missing fasting glucose and insulin data, and results were unchanged by exclusion of those individuals.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
Table 1Go provides demographic information about the study sample, as well as mean values for BMI, BP, fasting serum lipids, glucose, insulin, insulin resistance, and physical activity. Among the various criteria used to define the metabolic syndrome by the NCEP and WHO, 32% of subjects had a BP >= 130/85 mm Hg, 31% had a serum triglyceride level >= 150 mg/dl, 38% had reduced HDL cholesterol (<40 mg/dl in men and <50 mg/dl in women), 7% had a glucose level >= 110 mg/dl, and 25% had a BMI >= 30 kg/m2 (the latter used in lieu of large waist circumference). The prevalence of the metabolic syndrome in the study population was 17%, based on the NCEP criterion of three or more of the above risk variables. Application of the more conservative WHO criteria yielded a prevalence of 9%.


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  		TABLE 1. Subject characteristics

 
Table 2Go lists the bivariate correlations between components of the metabolic syndrome, insulin resistance, and physical activity. The coefficients document extensive covariation between these risk variables. Although correlations with physical activity were weaker and less consistent than among other variables, physical activity nonetheless covaried significantly with BMI, triglycerides, insulin, and insulin resistance.


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  		TABLE 2. Relationships between components of the metabolic syndrome: correlation coefficients1

 
As stated, plasma PRL responses evoked by fenfluramine challenge were measured to index central serotonergic responsivity. The median baseline PRL concentration was 6.3 ng/ml, and the median peak value after fenfluramine administration was 9.6 ng/ml. The median PRLAUC over the 3.5-h challenge was 23.2 ng/ml*h. PRLAUC was adjusted for age, gender, plasma drug levels, and baseline plasma PRL.

Table 3Go summarizes relationships between fenfluramine-induced PRL response and variables related to the metabolic syndrome. A 1 SD decrease in PRLAUC was associated with statistically significant elevations in each of the following: BMI, systolic and diastolic BP, fasting serum concentration of triglycerides, glucose and insulin, and insulin resistance (P < 0.03). No relationship was observed for HDL cholesterol. In addition, a 1 SD decrease in PRLAUC was associated with about 300 fewer reported kilocalories expended per week in physical activity (P = 0.03). None of these relationships differed significantly as a function of gender. [The PRL response to fenfluramine is sometimes expressed as the peak PRL value observed (34). Parallel analyses using peak PRL, rather than PRLAUC, showed nearly identical associations (P < 0.002–0.02), except glucose (which approached significance at P < 0.06).]


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  		TABLE 3. Predicted change in metabolic syndrome risk variables for a 1 SD decrease in PRL response1

 
To explore the possibility that these relationships were each driven by obesity alone, we repeated these analyses for the component metabolic syndrome risk factors after excluding participants with a BMI of 30 kg/m2 or more. Results were unchanged with the exception of fasting insulin concentration, for which fenfluramine-induced PRL response was no longer a significant predictor using linear regression.

We next examined the association between central serotonergic responsivity and the number of NCEP metabolic syndrome criteria met by each individual. As illustrated in Fig. 1Go, a pattern of graded decline in PRLAUC exists across individuals characterized by 0, 1, 2, 3 and, finally, 4 or 5 metabolic syndrome criteria (P for linear trend = 0.002).



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  		FIG. 1. PRL response and the number of metabolic syndrome risk variables. Mean plasma PRL response to fenfluramine (log PRLAUC ± SE) in subjects grouped by the number of metabolic syndrome criteria met. Values are adjusted for age, gender, baseline PRL concentration, and plasma fenfluramine/norfenfluramine levels. P value for linear trend = 0.002. For reference, comparison values of PRLAUC were back-transformed and are listed on the right y-axis. (Note that the SE bars may be interpreted only with respect to the left y-axis.)

 
The relationship between PRL response to fenfluramine and the likelihood of having the metabolic syndrome was also evaluated. Applying the NCEP criteria, a 1 SD decline in PRLAUC is associated with a doubling of the odds of having the metabolic syndrome (odds ratio = 2.05; 95% confidence interval = 1.10–3.83; P = 0.002), adjusted for standard baseline covariates. When the modified WHO criteria were used, for a 1 SD decrease in PRLAUC the odds ratio for the metabolic syndrome was 5.70 (95% confidence interval = 1.69–19.25; P = 0.005). Again, these associations did not differ by gender.


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
We previously reported that a blunted PRL response to fenfluramine, reflecting reduced central serotonergic responsivity, was associated with elevated BP (20). Here, we extend these observations to show that a blunted fenfluramine-induced PRL response is similarly related to obesity, elevated fasting levels of glucose, triglycerides, and insulin, and insulin resistance. Across all subjects, serotonergic responsivity varies linearly with the number of syndromal variables that exceed criterion values and is related to the presence or absence of the metabolic syndrome itself, whether defined by NCEP or modified WHO criteria. Physical inactivity, a reversible cause of obesity, hypertension, and insulin resistance (35, 36, 37), was also associated with an attenuated PRL response.

Although novel, these results are consistent with several independent observations. Horacek et al. (18) found a strong inverse correlation between the PRL response to fenfluramine and insulin sensitivity, measured by euglycemic clamp in a small group of nondiabetic volunteers. Patients with type 2 diabetes appear to have increased numbers of brain 5-HT1A receptors, compared with nondiabetics (38), and polymorphisms of both the 5-HT2A and 5-HT2C receptor genes have been associated with obesity and diabetes (19, 20). Finally, selective serotonin reuptake inhibitors induce weight loss in the early months of treatment (39) and, even in the absence of weight loss, have been reported to improve glycemic control in diabetics (40, 41, 42).

Interpretation of the present findings rests on the relative specificity of the D,L-fenfluramine challenge as an index of serotonergic function. In this regard, the fenfluramine-stimulated increase in circulating PRL may be blocked by serotonin agonists (29, 43, 44, 45) and, in rats, by lesioning of the raphé nuclei (29). However, the levorotary isomer of fenfluramine may also affect dopaminergic and noradrenergic activity in rodents (46), and PRL release may reflect nonserotonergic influences on the secretory capacity of the lactotroph. Nonetheless, PRL responses to D,L-fenfluramine have been found to correlate highly with responses to the more selective D-fenfluramine (47, 48). It has also been reported that PRL responses evoked by D,L-fenfluramine are unrelated to the PRL response to TSH-releasing hormone, thus tending to exclude variability in lactotroph function and dopaminergic inhibition as an explanation for individual differences in the fenfluramine challenge test (48).

Any causal inference is precluded by the study’s observational design, but several possibilities may underlie the revealed associations between central serotonergic responsivity and the metabolic syndrome. Dysfunction of brain serotonergic pathways may affect eating habits, physical activity, or both, leading indirectly to the development of obesity, insulin resistance, and related phenomena. In this regard, serotonergic circuits regulate eating, both with respect to caloric consumption and preferential intake of carbohydrates (49, 50, 51), and some drugs that affect serotonergic function, such as fenfluramine, reduce overall caloric intake. From animal experiments, stimulation of one receptor subtype, 5-HT2C, appears to induce anorexia, whereas 5-HT1A receptor activation generally increases eating (52). It has also been postulated that macronutrient intake and brain serotonin may interact to affect resting metabolic rate, physical activity, and the symptom of muscular fatigue (53, 54).

Alternatively, central serotonergic neurons may act through the autonomic nervous system or hypothalamic-pituitary axis to affect BP and key metabolic processes (55). PRL itself appears to play a role in the deposition and mobilization of fat (56). Several decades of research have described the effects of central serotonin on sympathetic nervous system activity and cardiovascular regulation (15, 16). In certain brain loci, 5-HT2 receptors increase sympathetic activity and release of renin and vasopressin, whereas sympathetic activity is reduced by stimulation of 5-HT1A receptors in the medullary centers. Spontaneously hypertensive rats are insulin-resistant (57) and were recently noted to have blunted serotonergic responsivity relative to their genetic controls (58). Alternative models linking brain serotonin with metabolic syndrome variables are also plausible. For example, both insulin (59, 60) and cortisol (61) may affect the function of central serotonergic neurons. Therefore, reduced serotonergic responsivity may result from, rather than contribute to, the metabolic syndrome.

Depression is also associated with disturbed central serotonergic function and is responsive to treatment with selective serotonin reuptake inhibitors. Moreover, depressed and chronically stressed individuals tend to manifest the insulin resistance syndrome, an association hypothesized to be mediated by hypercortisolemia, sympathetic activation, or physical inactivity, (62, 63, 64, 65). The current findings are clearly relevant to the aforementioned studies and could indicate that central serotonergic dysfunction is a common mechanism for the heretofore unexplained links between depression, stress, and various CVD risk factors.

Further research is needed to confirm and extend the current study findings. Individuals with hypercholesterolemia were somewhat overrepresented in this study sample, but it is unlikely that this fact should have created spurious associations between the PRL response to fenfluramine and the metabolic syndrome risk factors. An association between obesity and serotonergic function could drive associations between central serotonin and the other risk factors. However, these associations persisted in analyses excluding obese individuals. Future studies should use more refined measurement of insulin sensitivity and assessment of visceral adipose tissue. No direct measures of central serotonergic function are feasible in humans. The fenfluramine challenge test, although indirect, has the advantages of being relatively noninvasive and free of radiation exposure, but is now highly restricted due to toxicities associated with chronic fenfluramine use. Fortunately, alternative neuroendocrine challenge tests using other selective serotonergic probes, such as citalopram (66), are now available, and new positron emission tomography imaging techniques (38) are being developed. Although serotonergic influences on the several components of the insulin resistance syndrome are undoubtedly complex, our present findings suggest that the metabolic syndrome risk factors not only cluster within individuals, but also share an association with reduced central serotonergic responsivity.


   Footnotes
 
This work was supported by National Institutes of Health Public Health Service Grants HL-40962 and HL-46328.

Abbreviations: BMI, Body mass index; BP, blood pressure; CNS, central nervous system; CVD, cardiovascular disease; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NCEP, National Cholesterol Education Program; PRL, prolactin; PRLAUC, PRL area under the curve; WHO, World Health Organization.

Received July 24, 2003.

Accepted September 24, 2003.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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