Reversed-phase liquid chromatography coupled on-line to estrogen receptor bioaffinity detection based on fluorescence polarization

We describe the development and validation of a high-resolution screening (HRS) platform which couples gradient reversed-phase high-performance liquid chromatography (RP-HPLC) on-line to estrogen receptor α (ERα) affinity detection using fluorescence polarization (FP). FP, which allows detection at high wavelengths, limits the occurrence of interference from the autofluorescence of test compounds in the bioassay. A fluorescein-labeled estradiol derivative (E2-F) was synthesized and a binding assay was optimized in platereader format. After subsequent optimization in flow-injection analysis (FIA) mode, the optimized parameters were translated to the on-line HRS bioassay. Proof of principle was demonstrated by separating a mixture of five compounds known to be estrogenic (17β-estradiol, 17α-ethinylestradiol and the phytoestrogens coumestrol, coumarol and zearalenone), followed by post-column bioaffinity screening of the individual affinities for ERα. Using the HRS-based FP setup, we were able to screen affinities of off-line-generated metabolites of zearalenone for ERα. It is concluded that the on-line FP-based bioassay can be used to screen for the affinity of compounds without the disturbing occurrence of autofluorescence.
Introduction
In recent years, the presence of endocrine-disrupting compounds (EDCs) in the environment has become a major issue of concern in view of their effects on both human health and ecosystem integrity. The classes of substances that possess estrogenic activities include diverse manmade and natural chemicals (e.g., pesticides, plasticizers, polychlorinated biphenyls, phytoestrogens, natural hormones) and pharmaceuticals (e.g., ethinylestradiol, tamoxifen) [1, 2]. EDCs can interfere with the endocrine system by binding to the estrogen receptors α (ERα) or β (ERβ) and mimicking the action of the naturally produced hormone estrogen or blocking the receptor for this hormone in target cells, thereby preventing its action [3]. Therefore, it is important to screen compounds and compound mixtures for their ability to bind to one of these receptors. Alternatively, the task of screening for compounds containing estrogenic and antiestrogenic properties is also very important from medical and pharmaceutical points of view [4].
Several biodetection methodologies have meanwhile been developed to determine the bioaffinities of ligands towards ERα. These assays include relatively cumbersome radioligand binding assays [5], fluorescence enhancement based assays [6] and fluorescence polarization (FP) based binding assays [7]. A major drawback of these assays is that, in the presence of cross-reactive compounds, the response provided by the bioassay reflects the sum of the concentrations of all individual compounds and their affinities for the ERα. Moreover, matrix components, which are sometimes present in far higher concentrations than the analyte(s), interfere with the binding assay signals, thereby leading to false-positive or false-negative results [8]. Therefore, none of these methods can be applied for the identification of individual ERα binding ligands in mixtures of compounds, as is the case with natural compound extracts, biological samples containing different EDCs, and drug metabolite mixtures.
However, the introduction of the on-line high-resolution screening (HRS) technology enabled the screening of individual compounds in mixtures by coupling a separation technology, usually gradient HPLC, to post-column biochemical detection assays on-line [9–14]. Oosterkamp et al. [10] developed a HRS system to screen mixtures for compounds with an affinity for ERα. A similar setup has been used to screen natural plant product extracts for ERα and ERβ binding activity [15] and to identify and screen cytochrome P450-derived metabolites of tamoxifen with ERα affinity [2, 16]. The reported HRS ERα bioaffinity assays are based on the increase of the fluorescent signal of the tracer compound coumestrol upon binding to the ERα ligand binding domain (LBD). When the tracer is displaced by a compound with ERα affinity that elutes from the HPLC column, it is seen as a negative peak in the baseline of the ERα bioassay. Coumestrol, the fluorescent probe, has short excitation (340 nm) and emission (410 nm) wavelengths when bound to the ERα LBD [6]. Since there are many potentially interfering fluorescent compounds that can be excited at 300–350 nm and emit at 360–430 nm in biomatrices, coumestrol is not appropriate for the precise and selective detection of EDCs in biosamples containing phytoestrogens such as flavonoids, coumestans or lignans. One solution to this problem is to use another tracer compound, thus making it possible to monitor the bioassay signal at higher excitation and emission wavelengths. However, no tracer compounds are currently available which also display the necessary fluorescence enhancement upon binding to the ERα, thus making it impossible to use them in a HRS ERα setup. Another option is fluorescence polarization (FP) detection. FP is based upon the principle that interaction of a receptor with a fluorophore-containing ligand increases the effective size of the fluorophore through the formation of a receptor ligand complex. The increase in effective size reduces the rate of fluorophore rotation and increases the polarization over that of the unbound fluorophore [7]. FP instruments measure the rate of fluorophore rotation in solution rather than fluorescence intensity [17]. The polarization value is independent of the fluorophore concentration and intensity and has the advantage that it is minimally affected by autofluorescence, solution opacity or color, and is more tolerant to fluorescence quenching and light scattering [18].
The objective of the present study was to develop and evaluate the use of FP detection in combination with the on-line HRS technology to provide information about the ERα affinities of individual compounds in complex mixtures. The assay is based on competition for the ERα LBD between eluting compounds and a fluorescein-labeled estradiol derivative (E2-F), which was synthesized based on tracer structures described by Parker et al. [7] and Ohno et al. [19] for off-line FP-based ER assays. After synthesis of the tracer E2-F, the ERα binding assay was first optimized in FP platereader format and subsequently transferred to flow-injection analysis (FIA) mode with FP detection by using an on-line FP detector cell, which was recently constructed by Kool et al. [20] to measure GPCR-mediated modulation of cAMP production. Finally, after optimization of the assay in FIA mode, the on-line FP detection system was coupled to a gradient HPLC system. In this so-called HRS setup we separated mixtures of known estrogenic compounds—e.g., 17β-estradiol, 17α-ethinylestradiol and the phytoestrogens coumestrol, coumarol and zearalenone—and screened the individual compounds for ERα affinities. We also showed that this HRS ERα-FP system was suitable for screening off-line-generated cytochrome P450 (Cyt P450) metabolites of zearalenone for ERα affinity. We conclude that we were able to incorporate an on-line FP detector cell into a HRS system to screen for the ERα affinities of individual compounds in complex mixtures without incurring interference from the autofluorescence of the compounds.
Materials and methods
Materials
Tween 20, 17β-estradiol (E2), estrone (E1), 17α-ethinyl estradiol (EE2), diethylstilbestrol (DES), estriol, zearalenone, fluorescein-5-isothiocyanate (5-FITC) and coumestrol were obtained from Sigma-Aldrich (Zwijndrecht, The Netherlands). ELISA blocking reagent was purchased from Roche (Mannheim, Germany). Dry THF was freshly distilled from LiAlH4. All other chemicals were of analytical grade and obtained from standard suppliers.
Synthesis
Fluorescein-labeled estradiol derivative (E2-F) The fluorescein-labeled estradiol derivative (E2-F) was synthesized in analogy to methods described previously [7, 19] from estrone as the starting material (Fig. 1). To a solution of estrone (1, 700 mg, 2.59 mmol) in dry DMF (3 mL), imidazole (250 mg) was added. Subsequently, tert-butyl dimethylsilyl chloride (tBDSC) dissolved in dry THF (2 mL) was slowly added and the reaction mixture was stirred at room temperature for 3 h. The resulting cloudy white mixture was extracted with ethyl acetate (EtOAc). The organic extract was washed with water once, with brine twice and then with water once again. The organic extract was dried over MgSO4, filtered, and concentrated by rotary evaporation at 45 °C. Recrystallization was performed using a mixture of 15 mL MeOH and 5 mL DCM to afford 2 (667.2 mg, 67%). Under an atmosphere of dry nitrogen, 3-butyn-1-ol (1.35 g) was dissolved in dry THF (27 mL) and cooled to −78 °C. n-Butyllithium (BuLi) in hexane (16.9 mL, 0.027 mol) was added dropwise at −78 °C. Compound 2 (3.60 g, 9.36 mmol) dissolved in dry THF (25 mL) was carefully added dropwise at −78 °C and the solution was allowed to warm to room temperature and was thereafter stirred at 40 °C for an additional 60 min. The remaining BuLi was neutralized by carefully adding 5 mL EtOAc/MeOH (1:1). Extraction was performed with EtOAc, as described above. The crude product was purified by column chromatography on silica gel (10% EtOAc in hexane) to afford 3 (1.62 g, 38%). To a solution of 3 (1.6 g, 3.52 mmol) dissolved in dry THF (25 mL) was added triethylamine (TEA, 718 μL) followed by MeSO2Cl (395 μL, 5.1 mmol) while stirring at 0 °C. Afterwards the solution was allowed to warm to room temperature. After 10 h the reaction mixture was extracted with DCM. The organic extract was treated as described above and concentrated by rotary evaporation to afford 4 (1.80 g, 96%). Under an atmosphere of dry nitrogen, NaN3 (8.0 g) was added to a solution of 4 (1.80 g, 3.38 mmol) dissolved in dry DMPU (25 mL) while stirring rapidly. After stirring the solution for three days, the resulting reaction mixture was extracted with EtOAc as described above to afford 5 (1.36 g, 84%). To a solution of 5 (1.36 g, 2.83 mmol) in MeOH (70 mL) and TEA (16 mL), 1,3-propane dithiol (12 mL) was added. The solution was stirred o/n at room temperature and was concentrated by rotary evaporation. The concentrated solution dissolved in 100 mL hexane was purified by column chromatography on silica gel. Elution of the purified product 6 (1.08 g, 84%) was performed using EtOAc/MeOH (1:1). To remove the protective tert-butyl dimethylsilyl group, TBAF.H2O (300 mg) was added to a solution of 6 (258 mg, 0.57 mmol) dissolved in dry THF (4 mL) at 0 °C. After stirring for 1 h and allowing the solution to warm to room temperature, the crude product was extracted with DCM. The product was purified with Flash Master chromatography with an EtOAc/MeOH gradient to afford 7 (176 mg, 91%). Fluorescein-5-isothiocyanate (5-FITC, 7 mg, 17.8 μmol) was added to a solution of 7 (5 mg, 14.7 μmol) dissolved in dry DMF (500 μL) and dry pyridine (25 μL). The solution was stirred o/n in the dark at room temperature. The crude product was extracted with DCM and purified first with Flash Master chromatography (silicagel-based; EtOAC/MeOH gradient) and then with preparative C18 HPLC to afford 8 (E2-F, 8.02 mg, 75%). 1H NMR (400.13 MHz, CD3OD): δ 8.04 (1 H, d, J = 1.9 Hz), 7.70 (1 H, dd, J = 8.2, 1.9 Hz), 7.10 (1 H, d, J = 8.2 Hz), 7.01 (1 H, d, J = 8.5 Hz), 6.89 (1 H, d, J = 8.9 Hz), 6.88 (1 H, d, J = 8.9 Hz), 6.66 (2 H, d, J = 2.3 Hz), 6.58 (2 H, dd, J = 8.9, 1.9 Hz), 6.47 (1 H, dd, J = 8.5, 2.6 Hz), 6.42 (1 H, d, J = 2.6 Hz), 3.80 (2 H, t, J = 6.6 Hz), 2.70 (1 H, d, J = 1.9 Hz), 2.65 (2 H, t, J = 6.6 Hz), 2.1–2.3 (3 H, m), 1.9–2.0 (2 H, m), 1.65–1.85 (4 H, m), 1.25–1.50 (5 H, m), 0.85 (3 H, s). ESI-MS: m/z 729 (M + H)+.
Fig. 1Synthesis of a fluorescein-labeled estradiol (E2-F) derivative (for abbreviations, see “Experimental” section)
7-Hydroxy-3-p-hydroxyphenylcoumarine (coumarol) The synthesis of coumarol was analogous to the synthesis of benzene-hydroxylated-3-aryl-coumarins described by Buu-Hoi et al. [21]. Briefly, 2,4-dimethoxybenzaldehyde was reacted with p-methoxyphenyl-acetonitrile to form α-p-methoxyphenyl-β-(2,4-dimethoxyphenyl)-acrylonitrile. The formed product formed was demethylated using pyridine hydrochloride to form the final product coumarol. 1H NMR (400.13 MHz, DMSO-d6): δ 10.57 (1 H, s), 9.68 (1 H, s), 8.00 (1 H, s), 7.56 (1 H, d, J = 8.6 Hz), 7.53 (2 H, d, J = 8.7 Hz), 6.81 (2 H, d, J = 8.7 Hz), 6.80 (1 H, dd, J = 10.8, 2.7 Hz), 6.73 (1 H, d, J = 2.2 Hz). ESI-MS: m/z 255 (M + H)+.
Biomaterials
Microsomes Rat liver microsomes were prepared from phenobarbital (PB)-induced rat liver, as described previously by Roosenboom et al. [22].
Estrogen receptor α The ERα ligand binding domain (LBD) was expressed in Escherichia coli according to the method of Eiler et al. [23], but without estradiol in the medium. The concentration of ERα LBD (250 nM) was measured by determining the Bmax value (by titration with radiolabeled estradiol) [24]. The Bmax value was measured as the maximum amount of ligand binding extrapolated to a very high concentration of ligand.
Microsomal incubations
Microsomal PB-induced rat liver incubations were carried out in a total volume of 500 μL. The reaction mixture consisted of 2.5 mM MgCl2 in 100 mM potassium phosphate buffer (pH 7.4), 100 μM zearalenone and 2.6 mg/mL rat liver microsomes. The reactions were initiated by the addition of a NADPH regenerating system, resulting in final concentrations of 0.1 mM NADPH, 0.3 mM glucose-6-phosphate, and 0.4 U/mL glucose-6-phosphate dehydrogenase. Incubation was carried out at 37 °C for 120 min and the reaction was terminated by the addition of 50 μL 10% HClO4. Following centrifugation at 14,000 rpm for 10 min, 450 μL of supernatant was applied to a strata_X 33 μm Polymeric Sorbent 200 mg / 3 mL (Phenomenex, Amstelveen, The Netherlands) column for SPE sample preparation. Before sample application the column was conditioned with 2 mL MeOH and subsequently equilibrated with 2 mL H2O. The sample was washed with 2 mL 5% (v/v) of aqueous methanol and elution was performed using 2 mL 50% (v/v) of MeOH in ACN. After evaporation, the residues were dissolved in 1 mL 40% (v/v) of aqueous methanol.
Instrumentation
A NOVOstar+ microplate fluorometer from BMG LABTECH GmbH (Offenburg, Germany) was used for the FP-based microplate reader assay. The excitation wavelength was set at 485 nm, the emission wavelength at 520 nm. Black-bottomed PP-96-well microtiter plates from Greiner Bio-one (Alphen a/d Rijn, The Netherlands) were used for all microplate reader experiments.
The setup we used was adapted from the homogeneous coumestrol-based ERα affinity detection system described by Kool et al. [2]. For the on-line FP assay, two Knauer K-500 HPLC pumps (Berlin, Germany) were used to control the 120-mL superloops, made in-house, containing receptor (ERα) and tracer ligand (E2-F), respectively, and one Knauer K-500 HPLC pump was used to deliver the injected samples. The ERα and E2-F solutions were prepared in sodium phosphate buffer (10 mM; pH 7.4) containing 150 mM NaCl and 0.4 mg/mL ELISA blocking reagent. Both superloops were kept on ice. Flow restrictors were inserted between the pumps and the superloops to ensure proper operation of the pumps at low flow rates. The flow restrictors consisted of natural PEEK tubing and resulted in back pressures of approximately 50 bar. The pressure limits of the pumps were set 20 bar higher than the working pressure, and VICI Jour backpressure regulators (Schenkon, Switzerland) were inserted after the superloops to prevent damage from possible clogging of the system. A Gilson 234 autoinjector (Villiers-le-Bel, France) equipped with a Rheodyne (Bensheim, Germany) six-port injection valve (different injection loops) was used to inject samples. To maintain the reaction coils at a constant temperature, a Shimadzu CTO-10AC column oven (Duisburg, Germany) was integrated into the system. An Agilent 1100 (Waldbronn, Germany) series fluorescence detector (λex 498 nm; λem 522 nm) was used to monitor fluorescence polarization, as described by Kool et al. [20]. Briefly, the standard 8 μL FLD cell was modified with parallel-placed (both mounted in the detector cell) fluorescence polarization filters from Melles Griot (Didam, The Netherlands). One filter (12.5 mm visible pol. 350–650 nm 03FPG019) was placed in the pathway of the excitation beam and one (Mount. Sheet Pol. 20.D- 16.9CA 03FPG001) in the pathway of the emission beam. All hardware was integrated into one HRS system by Kiadis B.V. (Groningen, the Netherlands), and was controlled by software developed by Kiadis B.V.
Coumestrol-based microplate reader assay of ERα affinity
The microplate reader assay for determining ERα binding based on the competition between fluorescent coumestrol and estrogenic compounds previously described by Gurer-Orhan et al. [6] was used to plot a competitive binding curve for E2-F.
FP-based microplate reader assay of ERα affinity
The microplate reader assay was used to optimize the FP ERα receptor affinity detection (RAD) system in FIA and HPLC modes. This assay is based on the competition between estrogenic compounds and the newly synthesized fluorescein-labeled estradiol derivative (E2-F) for binding to the ERα LBD. Displacement of E2-F was measured as the decrease in fluorescence polarization intensity. Different concentrations of E2-F tracer were tested first. Since Tween 20, a detergent also used by Kool et al. in their coumestrol-based HRS ERα assay [2], can improve the resolution of the assay in HRS mode, and since organic modifiers are necessary for the optimal performance of the gradient HPLC system, the next step in the optimization process was to vary these parameters. The experiments were carried out at 24 °C with well volumes of 250 μL binding buffer [potassium phosphate buffer (10 mM; pH 7.4) containing 0.4 mg/ml ELISA blocking reagent]. The ERα LBD was introduced into the binding assay buffer at a final concentration of 1.64 nM. The E2-F stock solution was prepared in DMSO and dilutions were made in binding buffer. Concentrations ranging from 0.42 nM to 3.31 μM were investigated for E2-F optimization. For the experiments to investigate the detergent and organic modifier effects, the final concentration of E2-F in the assay was 83.3 nM. Aliquots of 25 μL of organic modifier or detergent at various concentrations were pipetted into a 96-well plate that already contained either 75 μL binding buffer (equal to 0% displacement) or 75 μL 33.3 μM E2 in binding buffer (equal to 100% displacement). The 96-well plate was gently but thoroughly mixed after pipetting 75 μL E2-F into each well. Finally, 75 μL of the ERα LBD was pipetted into the wells. After an incubation time of 60 min at room temperature, the fluorescence polarization (FP) was recorded at 485 nm excitation and 520 nm emission. All experiments were performed in quadruplicate. The difference in FP (ΔFP) was calculated by subtracting the FP value found at 100% displacement from the FP value found when no E2 was present under different conditions.
FP-based ERα receptor affinity detection (RAD) in flow-injection analysis (FIA) mode
A schematic overview of the RAD system in FIA mode is depicted in Fig. 2. In this system the flow from a superloop containing ERα LBD is continuously mixed with flow from a superloop containing E2-F. Compound samples (10 μL) are introduced into the system by flow injection into a carrier solution (100 μL/min). During optimization, the carrier solution was water. Injected compounds and ERα, added to the carrier stream via an inverted Y-type mixing union at a flow rate of 100 μL/min, were allowed to bind in a Tefzel reaction coil (25 μL). This mixture was combined with the flow of the E2-F solution of 100 μL/min. The final equilibrium between ERα, compound, and E2-F was established in a knitted 0.5 mm i.d. PTFE reaction coil (250 μL). The temperatures of both reaction coils were maintained constant at 37 °C. Fluorescence polarization (FP) detection took place directly after the second reaction coil. When the binding of E2-F is decreased due to competition from an eluting ERα ligand, depolarization occurs. This decrease in fluorescence polarization is a measure of the affinity of the ligand towards ERα.
Fig. 2Schematic overview of the ERα fluorescence polarization receptor affinity detection (RAD) system in high-resolution screening (HRS) mode. Samples are injected with an autoinjector (A.I.) and are separated using a gradient reversed-phase high-performance liquid chromatography (HPLC) system controlled by P1 and P2, HPLC gradient pumps. After the column the flow is split by a flow spitter, S (split ratio 1:9). HPLC elution is monitored by UV or fluorescence detection. A makeup gradient, controlled by makeup gradient pumps P3 and P4, is introduced and eluting compounds are mixed in the first reaction coil with ERα delivered by superloop-1 (SL-1). In the second reaction coil, the probe ligand E2-F is added to the mix by superloop-2 (SL-2). ERα affinity detection is performed using a fluorescence detector (FLD). In FIA mode the samples are delivered directly by a carrier solution into the bioassay
FP-based ERα receptor affinity detection coupled on-line to gradient HPLC
Coupling of the homogeneous ERα FP RAD assay to HPLC was performed in a similar way to that described recently by Kool et al. [14] for a Cyt P450 affinity assay. When operating the ERα FP RAD system in HPLC mode (Fig. 2), two pumps were used to control the HPLC gradient and, directly after the HPLC column, the HPLC eluent was split into a 1:9 ratio where nine-tenths of the flow was directed to either an UV (Agilent 1100 series) or fluorescence detector (Agilent 1100 series). The choice of detector depended on the compounds to be analyzed. To compensate for increasing the organic modifier concentrations before the delivery of the HPLC eluent to the ERα FP RAD system, two pumps were used to supply a makeup flow consisting of an opposite H2O/MeOH gradient compared with the HPLC gradient in order to keep the MeOH concentration in the assay constant at 10%. One-tenth of the total makeup flow was combined with one-tenth of the HPLC eluent and this flow was directed to the ERα FP RAD at 160 μl/min. The remaining part of the flow in the ERα FP RAD was the same as described above, with the exception that the HPLC flow combined with the makeup flow replaced the carrier solution flow.
For HPLC analysis, test compounds were dissolved in 50% MeOH in water. For coumestrol, a linear gradient from 75% MeOH to 99% MeOH in 7.5 min, constant for 47.5 min, and back to 75% MeOH in 1 min was applied. The total flow of the HPLC pumps was 162 μL/min and detection took place by measuring UV at 254 nm. For the mixture containing estriol, coumestrol, coumarol, E2 and zearalenone, constant elution at 55% MeOH for 40 min, followed by a linear gradient from 55% MeOH to 70% MeOH in 50 min, constant for 50 min, and back to 55% MeOH in 1 min was applied. The total flow rate of the HPLC pumps was 229 μL/min and detection took place using UV at 254 nm. For zearalenone and its cytochrome P450-generated metabolites, a linear gradient from 40% MeOH to 99% MeOH in 40 min, constant for 30 min, and back to 40% MeOH in 1 min was applied. The total flow rate of the HPLC pumps was 162 μL/min and detection took place using a fluorescence detector (λex 279 nm; λem 440 nm). All HPLC separations were carried out on a 150 × 4.6 mm i.d. Luna C18(2) column protected with a 2.0 × 5.0 mm i.d. C18 guard column (Phenomenex, Amstelveen, The Netherlands). The HPLC column was thermostated at 25 °C.
Results and discussion
The aim of this research was to combine a recently developed on-line FP detector cell (Kool et al. [20]) with high-resolution screening (HRS) technology to develop a sensitive screening platform for measuring the ERα affinities of individual components in mixtures of compounds without incurring interference from autofluorescence at wavelengths below 450 nm. We first synthesized a suitable tracer compound and used this tracer to set up a FP-based ERα binding assay in FP microplate reader format. The optimized assay conditions for the FP microplate reader format were transferred to an on-line bioassay format in FIA mode. In this mode we subsequently optimized the on-line assay conditions and validated them by measuring IC50 values of known estrogenic compounds in both microplate reader format and in FIA mode. We used the optimized conditions in FIA mode to couple the ERα bioassay on-line to a gradient HPLC system. In HPLC mode we measured the ERα bioaffinities of different estrogenic compounds and screened mixtures with five known estrogenic compounds. Finally, we measured the individual ERα bioaffinities of zearalenone and its metabolites generated off-line by Cyt P450 in HPLC mode.
Synthesis of E2-F
Synthesis of the fluorescein-labeled derivative E2-F (Fig. 1) was relatively straightforward. The synthetic route described in this paper makes use of readily available chemicals. The yields of intermediate products are relatively high except for the product of the second reaction step, in which compound 2 is converted into 3. However, the required reactants for this step are not expensive, which makes it possible to perform this step on a large scale. The last and most expensive step involving the coupling of 5-FITC to 7 still gives a yield of 75% after extraction and purification. Overall, we conclude that this synthetic protocol offers a good alternative to the synthetic scheme described in the literature [7, 19] that is used to produce a fluorescein-labeled E2 derivative. We describe a seven-step synthesis with an overall yield of 12% compared with an eight-step synthesis in the literature with a total yield of 7% [19].
To test whether the newly synthesized E2-F had affinity for the ERα, a competitive binding curve for E2-F and ERα LBD was constructed (data not shown) using the coumestrol-based microplate reader assay described by Gurer-Orhan et al. [6]. E2-F was able to displace coumestrol from the ERα binding site, resulting in an IC50 value of 28.2 nM. This value is consistent with KD values found for similar tracers, which were also in the nanomolar range [7, 19]. Therefore, we concluded that the synthesized E2-F had affinity for the ERα and could be used to further develop a FP-based microplate reader assay.
FP-based microplate reader assay of ERα affinity
The first step in the optimization of the FP-based microplate reader ERα affinity assay was the investigation of the influence of E2-F tracer concentration upon the FP-based microplate reader assay response of ERα-ligands. To achieve this we compared the FP signal obtained with 0% ligand displacement (no E2 present in the incubation) with the FP signal with 100% ligand displacement (33.3 μM E2 present in the incubation). We also incubated different concentrations of E2-F tracer with a fixed concentration of ERα. The difference in fluorescence polarization [ΔFP in millipolarization (mP)] was plotted against decreasing E2-F concentrations (Fig. 3). From this figure it can be seen that ΔFP increases with decreasing tracer E2-F concentrations until it reaches a maximum at 166 nM. However, it should also be noted that when the E2-F tracer concentration decreases, the error bars increase, which means that the S/N ratios become worse. For the ERα-binding assay, we preferred to use a tracer concentration which is not too high, because high tracer concentrations make it necessary to use high concentrations of test compounds as well in order to displace the tracer from the receptor, which results in a decreased assay sensitivity. However, if we use a tracer concentration which is too low, this will also result in unfavorable S/N ratios. Based upon our results and the KD values of 10.4 and 3 nM found by Ohno et al. [19] and Parket et al. [7] respectively for structurally similar fluorescein-labeled E2 derivatives, we decided to use an E2-F tracer concentration of 83.3 nM for further optimization experiments. At this concentration the ERα response was high, which makes it easier to detect the tracer–receptor complex in an on-line assay, with a low S/N ratio, and with the concentration in the same range as the KD value, which makes it possible to determine IC50 values more accurately.
Fig. 3FP-based microplate reader tracer concentration optimization. Incubations in the presence of ERα ligand E2 (33.3 μM; equal to 100% tracer displacement) were compared with incubations without E2 (equal to 0% tracer displacement) at decreasing E2-F tracer concentrations
The second step in the optimization process was the investigation of the influence of the detergent Tween 20 and the solvents methanol (MeOH), acetonitrile (ACN) and isopropanol (iPrOH) on assay performance using the conditions as optimized in the previous step. Experiments revealed that Tween 20 was not compatible with the ERα FP assay (data not shown). At very low concentrations (0.04%), the presence of Tween 20 in the assay caused a large decrease in ΔFP between E2-F bound to ERα (0% displacement; absence of E2) and E2-F displaced by 33.3 μM E2 (100% displacement). Although the addition of Tween 20 can give improved resolution in terms of peak width [25], we decided not to use it due to the large decrease in the difference in polarization. In Fig. 4, the effect of increasing concentrations of MeOH, ACN and iPrOH on ΔFP is shown. It can be seen from this figure that ΔFP decreases with increasing organic modifier concentrations. ΔFP decreased to almost zero for ACN at the highest concentration. For MeOH and iPrOH, however, a signal difference between the E2-F bound to ERα and displaced by E2 could still be observed at the highest modifier concentration. Oosterkamp et al. [10] have stated that denaturation of the estrogen receptor occurs upon prolonged contact with organic solvents such as MeOH and ACN. It is therefore reasonable to assume that when the organic modifier is present at higher concentrations, the denaturation process for ERα LBD increases, which results in smaller fluorescence polarization signal differences.
Fig. 4FP-based microplate reader solvent optimization. Incubations in the presence of ERα ligand E2 (33.3 μM; equal to 100 % tracer displacement) were compared with incubations without E2 (equal to 0% displacement) at increasing MeOH, ACN and iPrOH concentrations at an E2-F concentration of 83.3 nM
FP-based ERα receptor affinity detection (RAD) in flow-injection analysis (FIA) mode
The optimized microplate reader assay conditions were transferred to the on-line ERα RAD system in FIA mode (Fig. 2). In this system, compounds introduced by a carrier solution are allowed to bind to the ERα LBD in a first reaction coil, and the E2-F tracer is introduced after this coil. The tracer compound can interact with the unbound receptor in a second reaction coil and detection takes place after the second reaction coil using FP detection. In a FIA setup, carrier solution replaces the gradient HPLC system, thereby allowing the direct injection of compounds and the optimization of on-line assay conditions before final on-line coupling to HPLC. The influence of the ERα LBD and E2-F tracer concentrations and the corresponding excitation and emission wavelengths were investigated in FIA mode in order to optimize the performance of the FP ERα RAD system. The influences of ACN and MeOH, later used in HPLC mode too, on the FP ERα RAD system performance were also tested in the FIA mode. All measurements were performed in duplicate.
ERα LBD and E2-F tracer optimization Different receptor concentrations (ERα LBD) were tested in combination with different tracer concentrations (E2-F) by varying the flows of SL-1 (containing 10 nM ERα in binding buffer) and SL-2 (containing 1 μM E2-F in binding buffer). The total flow rate was kept constant by introducing a compensating superloop containing only binding buffer. Water was used as carrier solution in order to inject 10 μL 100 μM E2 in 50% MeOH samples (100% ligand displacement) in duplicate followed by 10 μL injections of 50% MeOH (0% displacement) at a flow rate of 250 μL/min. The results obtained with these experiments are depicted in Fig. 5. This figure shows that as the E2-F tracer concentration increases the FP signal increases too, until it reaches a maximum. Using the present FIA FP ERα RAD setup, we were able to determine the KD and maximum response (Rmax) values for the E2-F tracer compound (Table 1) at different ERα concentrations. The KD values found were of the same order as observed by Ohno et al. [19] and Parker et al. [7] for an analogous FP tracer compound. It can be seen that  Rmax increases linearly with higher ERα concentrations, as was expected. Based upon these results, we conclude that the FP ERα RAD in FIA mode worked well, and we continued by investigating the influence of the organic modifier upon the assay performance.
Fig. 5Determination of KD and maximum response (Rmax) for E2-F in FIA mode. Different concentrations of E2-F were incubated with three different ERα concentrationsTable 1KD and maximum response (Rmax) determination for E2-F in FIA mode[ERα] (nM)KD (nM)Rmax (AUC)a0.743.6 ± 12.42.17 × 1061.526.4 ± 5.04.04 × 1063.034.5 ± 5.39.38 × 106aRmax was determined by integrating the decrease in FP signal, and arbitrary units were chosen to display this decrease
Organic modifier concentration Although we also investigated the influence of iPrOH upon the ERα bioaffinity assay performance in the FP-based microplate reader format, we decided to evaluate only MeOH and ACN in FIA mode based upon the fact that we planned to use only these two solvents in HPLC mode. Different concentrations of MeOH and ACN were used as the carrier solution in order to inject 10 μL 100 μM E2 ligand in 50% MeOH samples (100% ligand displacement) in duplicate followed by 10 μL injections of 50% MeOH (0 μM E2 ligand; 0% displacement) into the system. The ERα LBD concentration in the second reaction coil was 2.7 nM, the E2-F tracer concentration 110 nM and the total flow rate 300 μL/min. Increasing the concentration of MeOH decreased the S/N ratio in FIA mode (Fig. 6). A similar effect was observed with ACN. A possible explanation for this decreasing effect is the partial denaturation of the estrogen receptor due to the presence of high concentrations of organic modifier. Oosterkamp et al. [10] have described this phenomenon during the optimization of the ERα coumestrol-based RAD system when a decrease in response was observed upon the contact of the ERα with organic solvents such as MeOH and ACN. One advantage of a higher organic modifier concentration is that higher flow rates can be used in HPLC gradients, which may result in shorter analysis times and higher resolutions. Another advantage is that high concentrations of organic modifier prevent lipohilic compounds from adsorbing to the walls of the reaction coils and other tubing, which may increase resolution. Based upon our results during FP FIA setup, we concluded that both MeOH and ACN might be used in the on-line gradient HPLC system.
Fig. 6Effect of MeOH and ACN reaction coil concentrations upon the assay performance in FIA mode. The S/N ratios of the E2 injections equalling 100% tracer displacement are displayed
Excitation and emission wavelengths When the excitation and emission wavelengths were varied, the optimal FP signal responses in FIA mode were obtained at an excitation wavelength of 498 nm and an emission wavelength of 522 nm (data not shown). These wavelengths were therefore used to further optimize the on-line FP system in FIA mode.
Competitive receptor binding curves To validate the ERα FP RAD system, competitive binding curves for five known estrogenic test compounds—DES, E2, EE2, tamoxifen and coumestrol—were constructed using the FP-based microplate reader assay, and these values were compared with the IC50 values obtained using the ERα FP setup in FIA mode. The ERα LBD concentration was 1.6 nM and the E2-F tracer concentration was 80 nM for the microplate reader assay. In FIA mode, the ERα LBD concentration in the second reaction coil was 2.7 nM and the E2-F concentration was 110 nM. All five test compounds displayed sigmoidal concentration–response curves during both the microplate reader setup and in FIA mode, and from these curves we were able to determine the IC50 values (Table 2). The values found in the two different setups were similar for each individual compound and in agreement with values obtained from the literature [7, 26]. We thus demonstrated that the FP-based microplate reader assay and the ERα FP setup in FIA mode could be employed to determine the IC50 values of a wide range of typical ERα-binding ligands accurately. The next step in the process of developing the HRS platform was to couple the FIA ERα FP system to a gradient HPLC system on-line.
Table 2IC50 values determined in FIA mode and in microplate reader assay formatCompoundFIA mode IC50 (M ± SEM; n = 3)Microplate setup IC50 (M ± SEM; n = 3)Literature data IC50 (M)DES6.9 ± 0.3 × 10−96.1 ± 0.6 × 10−93.5 × 10−9 aTamoxifen1.2 ± 0.1 × 10−71.3 ± 0.4 × 10−71.9 × 10−7 aCoumestrol1.8 ± 0.2 × 10−72.5 ± 0.3 × 10−73.6 × 10−7 bE26.7 ± 0.8 × 10−93.3 ± 0.3 × 10−95.6 × 10−9 aEE21.6 ± 0.2 × 10−93.5 ± 0.8 × 10−92.3 × 10−9 bIC50 values of five estrogenic compounds towards the ERα, as measured with the RAD system in FIA mode and with the microplate reader assay format. Data from literature a[7], b[26] are also shown. DES, diethylstilbestrol; E2, 17β-estradiol; EE2, 17α-ethinyl estradiol
FP-based ERα receptor affinity detection coupled on-line to HPLC
Following assay optimization in the microplate reader and FIA modes, the ERα FP RAD assay was coupled on-line to gradient HPLC. In this HRS setup the flow eluting from an HPLC column was coupled directly to the FP RAD system, which enables compound separation prior to the screening of individually eluting compounds for their ERα affinities. This allowed us to screen for compounds with ERα affinities in mixtures. To test the performance of the on-line HRS FP ERα system, different concentrations of the phytoestrogen coumestrol were injected first. A negative peak in the ERα bioaffinity trace was observed at a retention time of 40 min, which is the exact time when coumestrol eluted from the HPLC column (data not shown). As expected, the negative bioaffinity peaks became larger upon injections of higher concentrations of coumestrol. The highest negative peaks were observed when all of the E2-F was displaced by coumestrol. Higher concentrations of coumestrol only caused more tailing of the bioaffinity peaks. These measurements illustrate that the ERα bioaffinity of the phytoestrogen coumestrol could be measured sensitively and efficiently with the new E2-F based HRS ERα FP system, which is not possible due to the occurrence of autofluorescence using the coumestrol-based ERα HRS system developed by Oosterkamp et al. [10].
Representative superimposed chromatograms of different concentrations of a mixture of five known estrogenic compounds—coumestrol, coumarol, estriol, 17β-estradiol and zearalenone—are depicted in Fig. 7. Although some baseline drift in time is observed over two hours, it is quite possible to detect the ERα bioaffinities of all five individual peaks in the mixture. The explanation for the baseline drift is most likely that the post-column makeup HPLC gradient does not totally compensate for the effect of variations in the organic modifier concentration. The FP ERα RAD system is sensitive to changes in the organic modifier concentration, as shown during FIA optimization, and this can lead to baseline drifts.
Fig. 7ERα FP RAD trace of a mixture of five estrogenic compounds injected into the ERα FP RAD HPLC system (injected compounds are as follows: estriol (1) [3.75 nmol; 49.5 min], coumestrol (2) [3.75 nmol; 53.7 min], coumarol (3) [37.5 nmol; 80.4 min], 17β-estradiol (4) [3.75 nmol; 102.8 min] and zearalenone (5) [12.5 nmol; 112.5 min]
To illustrate another application of the on-line HRS ERα FP system, metabolites of the phytoestrogen zearalenone, which were anticipated to show affinity for the ERα, were analyzed in the present FP-based HRS ERα system. For this purpose, zearalenone was metabolized by phenobarbital (PB)-induced rat liver microsomes in an off-line fashion, followed by analysis with the FP-based HRS system. The results are depicted in Fig. 8. The UV trace of the t = 0 min incubation shows that zearalenone (Z) elutes at 51.4 min. The corresponding bioaffinity trace shows that zearalenone has affinity for ERα. The FLD trace of the t = 120 min incubation shows that zearalenone is metabolized by rat liver microsomes into at least three major metabolites (M1: 33.5, M2: 39.5 and M3: 43.2 min). The corresponding bioaffinity trace demonstrates that all three major metabolites (M1–3) have affinity for ERα. LC/MS measurements were performed to identify the three major metabolites. M1 had a molecular ion at an m/z value of 333, which likely corresponds to a monohydroxylated zearalenone metabolite. M2 had a molecular ion at an m/z value of 317, which is the exact same m/z value as that of zearalenone itself. This can be explained by the relocation of the double carbon–carbon bond next to the aromatic ring. However, more research must be performed to confirm this. M3 had a molecular ion at an m/z value of 319, which corresponds well to the m/z value of the zearalenone metabolite zearalenol described in the literature [27]. The metabolism of zearalenone in vitro by rat liver microsomes has been described very recently by Pfeiffer et al. [28], and they confirm the findings of M1 and M3. The present Cyt P450 metabolism experiment illustrates that it is possible to screen metabolic mixtures of phytoestrogenic compounds for ERα affinity using the present FP-based HRS ERα setup. However, no further structural elucidation of the zearalenone metabolites has been performed, because the goal of the present experiment was only to show that the on-line FP HRS ERα assay can be used to screen for parent compounds and metabolites of phytoestrogens with ERα affinity.
Fig. 8a–ba HPLC FLD chromatograms of zearalenone (Z) incubated for 0 and 120 min with PB-induced rat liver microsomes. M1, M2 and M3 are metabolites formed during the 120-min incubation period. b The corresponding ERα FP affinity traces. The structure of zearalenone is depicted in the figure
We conclude that we succeeded in developing, for the first time, an on-line FP-based HRS platform to screen for ERα affinity using the novel on-line FP detector cell recently described in a FIA mode by Kool et al. [20]. The sensitivity of the FP-based HRS platform is comparable to that of the coumestrol-based HRS platform, and no interference from fluorescence was observed at wavelengths below 450 nm. The novel on-line FP detector cell can in principle be applied to other HPLC-based bioaffinity assays which require FP detection. The present HRS ERα FP system offers a novel technology for investigating the metabolic profiles of drugs and other compounds such as phytoestrogens which cannot be measured by the coumestrol-based HRS system due to the occurrence of autofluorescence from the test compounds.

fluorescence polarization
high-resolution screening (hrs)
estrogen receptor α
phytoestrogens
receptor affinity detection (rad)
on-line bioaffinity assay


Psychosocial Functioning, Personality, and Body Image Following Vertical Banded Gastroplasty

Background In addition to increased risks of morbidity and mortality, extreme obesity is substantially associated with psychosocial problems. Therefore, the ultimate goal of bariatric surgery should not only be reducing weight and counteracting comorbid conditions but also improving psychosocial functioning. In addition to being an important goal of bariatric surgery, enhanced psychosocial functioning may motivate patients to adhere to adequate health behavior to maintain the surgically established weight loss.
Introduction
Obesity is a major public health concern. Its prevalence is increasing globally [1]. In addition to an increased risk of morbidity and mortality caused by medical conditions [2], extreme obesity is associated with debilitating psychological and social consequences especially in patients seeking surgery [3–6]. Psychological consequences of extreme obesity are, among others, anxiety, depression, low self-esteem, and negative body image [5–10]. Socially, the extremely obese have to deal with prejudice, discrimination, and social isolation [11].
Because only surgical treatment results in long-term weight reduction and the improvement or cure of comorbidities, including reduction of psychopathology [3–6], the number of procedures performed has more than doubled within a few years [12]. However, studies show great variation in outcome. In contrast to research showing large and long-lasting improvements, other studies suggest that postoperative improvements lag behind functioning of normative groups or show a decline over the years [4, 5].
Enhanced psychosocial functioning is an important goal of bariatric surgery. It may motivate patients to adhere to adequate health behavior to maintain the surgically established weight loss [13]. In addition to medical–somatic and surgical–technical factors, success of bariatric surgery is especially influenced by the extent of successful adjustment of eating patterns, which, for a substantial part, can be attributed to psychological factors. Therefore, success after bariatric surgery should not only reflect weight loss and improvement or cure of comorbid conditions but also improvements in eating behavior, psychosocial variables, and quality of life [14]. However, in contrast to physical changes, psychosocial changes are not studied as systematically or diligently yet [15]. To facilitate the identification of the psychological variables that are related to success and the development of treatment interventions to enhance adjustment and success, a better understanding of patients’ psychosocial functioning after bariatric surgery is needed.
Materials and Methods
The present study was designed to increase our understanding of patients’ changes in psychosocial functioning, personality, and body image during the first 2 years after vertical banded gastroplasty (VBG). The main research questions were: what specific improvements can be achieved, is postoperative functioning noticeable different from functioning in relevant normative groups, and do all patients profit? These questions were examined based on data collection preoperatively and 6, 12, and 24 months after VBG.
Procedures
The restrictive operation technique used in our hospital is hand-assisted laparoscopic vertical banded gastroplasty, with a complete division between the vertical staple lines. VBG is a relative simple, safe, and cost-effective intervention with fewer side effects than other procedures [16]. Not withstanding this, mixed long-term results, such as weight regain and dietary problems, have been reported [17]. Contrary to the situation in the USA, in The Netherlands, the numbers of VBGs that have been performed in the last 5 years is rather stable, despite the fact that the number of adjustable gastric banding procedures is showing an enormous increase.
Materials
Earlier studies of psychosocial factors in the surgical treatment of extreme obesity have not provided consistent findings, which may, in part, be caused by the employment of a wide variety of non-standardized assessment procedures of questionable reliability and validity [11]. In the present study, we assessed preoperative as well as postoperative psychosocial functioning, personality, and body image using a semi-structured interview and three standardized questionnaires. As interview-based psychological studies may be questionable, we will report here only on the questionnaire data. Preoperatively as well as on three follow-up assessment points, patients filled in the Symptom Checklist-90 (SCL-90) [18], the Dutch Personality Questionnaire (NVP) [19], and the Body Attitude Test (BAT) [20]. The SCL-90 is a multidimensional psychopathology indicator with eight subscales and one summarized score (psychoneuroticism); its psychometric qualities are satisfactory to good [21]. In addition to neuroticism, the NPV measures six personality characteristics; its psychometric qualities are also satisfactory to good [22]. The BAT measures subjective body experience and the attitude towards one’s own body; it has three subscales and one summarized total score, is commonly used in Europe, and is a reliable and valid questionnaire [20].
Patients
In the context of standard preoperative evaluation, 131 patients who underwent VBG in our hospital between January 2001 and October 2004 were psychologically assessed. In addition to the inclusion criteria determined by IFSO [23], we required 10% preoperative weight loss with a minimum of 12 kg. From these 131 patients, 104 (79.4%) could be included in our study; others did not respond to our repeated requests for follow-up or sending back questionnaires. The studied patient group consisted of 91 (87.5%) female and 13 (12.5%) male patients. Preoperatively, they had a mean age of 38.4 ± 8.3 years, an average body mass index (BMI) of 45.4 ± 5.1, and a mean percentage excess weight of 104.5 ± 22.1%.
Statistical Analyses
Statistical analyses were performed using the SPSS 14.0-packet (SPSS for Windows, Rel. 14.0. 2005, SPSS Inc., Chicago). To study changes over time in weight, psychosocial functioning, personality, and body image, mixed between-within subjects analyses of variance for repeated measures were performed (ANOVA; time as within-subjects factor, gender as between-subjects factor). To identify waning of changes, Bonferroni post hoc equations were used. To compare patients’ questionnaire scores to normative data, we used one-sample t tests. To identify heterogeneity in postoperative psychosocial functioning, descriptive statistics were used using summarized scales whenever possible for reasons of clarity. In reporting excess weight (EW) and excess weight loss (EWL), we followed the guidelines of Deitel and Greenstein [24].
Results
Weight Loss
Over time, using ANOVA, substantial and significant changes in mean BMI, EW, and EWL were found. From preoperative status to 2 years after surgery, BMI and EW significantly (P ≤ 0.001) decreased 13.5 points and 58.6%, respectively, which represent a large size (partial η2 = 0.83) [25]. After 2 years, using the criterion that an operation can be conceived of as successful when EWL ≥50% [26], 61% of the patients had a successful operation. Preoperatively, 91.3% of the patients were extremely obese; in contrast, 2 years after surgery, only 12% was extremely obese.
Psychosocial Functioning
Our earlier literature review suggests that psychopathology is related to extreme obesity, manifesting itself mostly as depression or anxiety [11].
In assessing psychosocial functioning, we used the SCL-90 to assess short-term psychosocial functioning [18] and the NPV neuroticism scale to measure long-term neuroticism [19]. With respect to all aspects, except for hostility, significant changes over time were found (for most of the comparisons, P ≤ 0.001; for neuroticism, P ≤ 0.01; for sleeping problems, P ≤ 0.05). For the majority of alterations, large effect sizes were found [25]. Post hoc analyses showed that compared to the preoperative status, for most aspects of psychosocial functioning, scores were significantly lower on all follow-up assessment points, reflecting better psychosocial functioning. However, depressive symptoms and neuroticism were only significantly lower 6 months and 1 year after surgery; sleeping problems were lower only 6 months after surgery. For most aspects of psychosocial functioning, there was only a significant decrease in scores from preoperative status to 6 months postoperatively, however, not between 6 months and 1 year or between 1 and 2 years postoperatively (Table 1).
Table 1Postoperative changes in psychosocial functioning (mean ± SD)SCL-90Preoperative6 months1 year2 yearsPartial η2Anxiety14.3 ± 5.011.7 ± 2.4***12.1 ± 3.912.6 ± 5.6.23Phobic complaints9.3 ± 3.67.4 ± 1.1***7.5 ± 1.67.9 ± 3.1.20Depression24.8 ± 8.620.8 ± 6.3***20.9 ± 7.123.1 ± 11.3.18Somatic complaints21.2 ± 7.916.2 ± 3.5***17.0 ± 5.217.9 ± 6.7.29Obsessive15.0 ± 5.011.6 ± 2.7***12.0 ± 3.112.7 ± 5.1.28Sensitivity28.7 ± 10.423.0 ± 6.4***22.8 ± 6.124.2 ± 10.8.25Hostility7.3 ± 1.77.2 ± 2.07.1 ± 1.57.3 ± 2.4.06Sleeping problems5.7 ± 2.94.6 ± 2.3*4.9 ± 2.55.5 ± 3.1.09Psychoneuroticism139.5 ± 41.0113.0 ± 22.7***114.8 ± 26.4122.8 ± 45.2.30N93939393Neuroticism (NPV)11.98 ± 8.98.5 ± 7.4**8.0 ± 6.69.3 ± 8.8.15N94949494Because of listwise exclusion, n = 93 (SCL-90) or 94 (NPV) on all moments; Obsessive: obsessive compulsive behavior; Sensitivity: mistrust and interpersonal sensitivity.***P < 0.001**P < 0.01*P < 0.05
Furthermore, we compared patients’ mean scores on psychosocial functioning to corresponding scores obtained in relevant normative groups, reflecting the general population [18, 19]. Compared to those normative groups, mean preoperative scores for psychosocial functioning were significantly higher, except for hostility. However, with respect to preoperative neuroticism, no significant difference was found. Postoperatively, there was a mixed picture. In spite of these inconsistencies, the overall picture revealed that on most subscales and most follow-up assessment points, patients’ mean scores were not significantly different from the corresponding scores obtained in the normative groups. Two years after surgery, patients’ mean scores on measures of sleeping problems and somatic complaints were again significantly higher than the normative group’s scores. As to neuroticism, patients’ postoperative mean scores were significantly lower than the normative group’s scores on all follow-up assessment points. Despite these differences, all postoperative patients’ scores fell in the below mean, mean, or above mean categories of the normative groups’ scores.
Personality
Because personality substantially influences health behavior, personality characteristics may be relevant for adjustment to surgery [27]. According to earlier literature reviews, extremely obese individuals can be described as, among others, immature persons having a poor impulse control and a low self-esteem [28]. With respect to postoperative personality change, mixed results have been reported. For instance, some studies suggest that patients still have more pathology than comparison groups [13], whereas other research suggests that personality remains largely unchanged [3].
In assessing personality with the NPV [19], over time, we only found, with a large effect size [25], a significant (P ≤ 0.01) change in self-esteem. Post hoc analyses revealed that compared to the preoperative status, self-esteem was significantly higher 1 year postoperatively. Six months after surgery, there was a tendency to significance (P = 0.06). Two years postoperatively, however, no significant difference was found. Also, no significant differences were found between follow-up assessment points (Table 2).
Table 2Postoperative changes in personality characteristics (mean ± SD)NPV subscalesPreoperative6 months1 year2 yearsPartial η2Social anxiety8.9 ± 7.96.8 ± 6.57.0 ± 6.57.5 ± 7.1.0.07Rigidity24.4 ± 7.324.0 ± 7.924.2 ± 7.423.7 ± 7.80.03Hostility14.0 ± 8.514.1 ± 8.614.0 ± 8.915.3 ± 9.30.05.Egoism9.7 ± 4.710.6 ± 5.19.9 ± 4.810.4 ± 5.00.04Dominance13.9 ± 6.415.3 ± 7.515.3 ± 7.215.0 ± 7.30.06Self-esteem27.9 ± 6.029.7 ± 5.329.9 ± 5.5*28.6 ± 6.70.14N94949494Because of listwise exclusion, n = 94 on all moments.*P < 0.01
We did not find many significant personality changes, but compared to normative data [19], we did find some significant differences. Compared to a relevant normative group, reflecting the general population, patients’ mean preoperative scores on social anxiety, dominance, and self-esteem were not significantly different. However, they were after surgery, albeit not on all follow-up assessment points and not always for both sexes. Postoperatively, patients’ scores on social anxiety were lower, whereas their scores on dominance and self-esteem were higher than the corresponding scores obtained in the normative group. On scales of Hostility and Egoism, preoperatively, patients had significant lower mean scores; postoperatively, this was only the case for some small subgroups. On the Rigidity measure, patients had significantly lower mean scores on all measurement moments preoperatively as well as postoperatively. All patients’ mean scores fell in the below mean, mean, or above mean categories of the normative group’s scores.
Body Image
Some studies suggest that especially for female patients, the desire to improve their physical appearance and avoidance of embarrassment are the most common motivators for bariatric surgery [29]. Also, improved body image would be one of the main reasons for post-surgical psychological improvement, better social integration, and enhanced quality of life [30]. Weight loss after bariatric surgery leads to marked improvements in body image and attractiveness and to less shame. However, with time, some patients still feel overweight, are discontent with the increasing skin folds [13], or still may have more concern with their body shape and size than controls [31].
In our earlier study, we found that preoperatively, patients reported significantly higher body dissatisfaction and negative body image than general population samples [28]. In the present study, using the BAT [20], over time, we found significant (P ≤ 0.001) changes in negative appreciation of body size, lack of familiarity with one’s own body, general body dissatisfaction, and the summarized BAT score, reflecting improved body image and large effect sizes [25]. Post hoc analyses showed that compared to the preoperative status, scores were significantly (P ≤ 0.001) lower on all three follow-up assessment points. We found significant decreases between preoperative status and 6 months postoperatively, however, not between 6 months and 1 year or between 1 and 2 years after surgery (Table 3). Also, in contrast to the preoperative situation, on all three follow-up assessment points, body image was significantly correlated to BMI, reflecting a more positive body image when BMI was lower (r varied from 0.37, 6 months postoperatively, to 0.29, 1 year postoperatively, and 0.31, 2 years after surgery).
Table 3Postoperative changes in body image (mean ± SD) Preoperative6 months1 year2 yearsPartial η2Negative appreciation of body size26.2 ± 5.814.9 ± 7.1*14.4 ± 8.214.2 ± 8.20.59Lack of familiarity with one’s own body16.5 ± 7.27.5 ± 4.7*7.1 ± 4.87.5 ± 6.10.52General body dissatisfaction15.2 ± 3.68.1 ± 4.6*8.0 ± 4.68.3 ± 5.00.61Total BAT score64.0 ± 15.436.9 ± 15.6*35.8 ± 16.235.9 ± 17.40.63N97979797Because of listwise exclusion, n = 97 on all moments.*P < 0.001
Although we found significant improvements in body image over time, on all moments, preoperatively as well as postoperatively, and on all scales, patients’ mean scores were significantly (P ≤ 0.001 or P ≤ 0.01) higher than those of (female students) normative groups [20, 32].
Heterogeneity in Postoperative Psychosocial Functioning
Most studies report broad psychosocial improvements after bariatric surgery. However, a significant minority of extremely obese patients do not benefit from surgery [4]. Some patients may even have difficulties in adapting psychosocially to the various consequences of bariatric surgery [13].
In the present study, in addition to a large variation in EWL, we found substantial variance with respect to changes in psychosocial functioning. Especially with respect to psychoneuroticism and neuroticism, most patients reported postoperative improvements; however, this was not the case for all patients. For instance, in the case of psychoneuroticism, 77 out of 99 patients (77.8%) reported improvement after 6 months; in contrast, 21 patients (21.2%) had higher scores, and one patient did not change. After 24 months, approximately two thirds of the patient group (64.7%) still had better scores on psychoneuroticism, whereas one third (31.4%) showed signs of an increase in psychoneuroticism.
In the case of personality characteristics, a mixed picture was found; however, in general, there were only small differences between patients reporting positive or negative changes. Regarding body image, almost all patients reported improvements, and these were quite stable over time.
Discussion
After vertical banded gastroplasty, in addition to substantial and significant weight loss, patients also changed for the better in body image and most domains of psychosocial functioning. With respect to personality, only a significant improvement in self-esteem was found. Unfortunately, there was substantial variance in improvements, and some improvements waned over time.
Most of our findings are in line with other studies, with respect to weight loss [33], as well as regarding improvements in psychosocial functioning and body image [7, 8]. The fact that we could not demonstrate many significant changes in patients’ personality is in contrast to the results of some studies [34], but is consistent with the suggestion that there is no obese personality [35]; furthermore, because of the stability of personality, these findings might be expected. The impact of bariatric surgery seems to be more in the areas of symptoms of psychopathology.
Just like others, we found a decline of some psychosocial improvements over the years [13]. Various explanations have been suggested for waning psychosocial improvements, for example, stabilization or rising of patients’ weight, disappointment that life did not improve dramatically after substantial loss of weight, or difficulties in adapting psychologically to the consequences of bariatric surgery [13]. Also, our results concerning patients’ postoperative heterogeneity are in accordance with earlier findings [36]. These outcomes underscore the suggestion that vertical banded gastroplasty, just like other methods of bariatric surgery, is not equally effective for each patient.
Although our study has some assets, such as the employment of standardized, reliable questionnaires and the focus on psychosocial functioning in a wide variety of domains of life, some weaker points could also be indicated. For instance, we were not able to retain all patients of our preoperative sample. This problem is also identified by others who suggest that patients’ participation in psychological follow-up is much lower than in follow-up visits for other specialists of the bariatric team [37].
Although we found mixed results, the overall psychosocial improvements provide additional justification for vertical banded gastroplasty as a surgical treatment option for extreme obesity. However, as some improvements wane over time and not all patients profit in the same way, surgery alone may not be sufficient to sustain success. Consequently, additional behavioral treatment may be necessary.

psychosocial functioning
personality
body image
vertical banded gastroplasty
bariatric surgery
psychopathology
morbid obesity


Links between cardiovascular disease and osteoporosis in postmenopausal women: serum lipids or atherosclerosis per se?

Introduction and hypothesis Epidemiological observations suggest links between osteoporosis and risk of acute cardiovascular events and vice versa. Whether the two clinical conditions are linked by common pathogenic factors or atherosclerosis per se remains incompletely understood. We investigated whether serum lipids and polymorphism in the ApoE gene modifying serum lipids could be a biological linkage.
Introduction
Osteoporotic fractures and acute cardiovascular events remain the predominant contributors to morbidity and mortality among the elderly. Postmenopausal women with osteoporosis are at increased risk for acute cardiovascular events independent of their age and cardiovascular risk profile, and the increase in risk is proportional to the severity of osteoporosis at the time of the diagnosis [1]. Bone mineral density (BMD) at the hip is inversely correlated with the severity of aorta calcification (AC) and hence low hip BMD can be a surrogate marker of the atherosclerotic burden in elderly women [2]. Large cohort studies demonstrate that the rate of bone loss in metacarpals, proximal femur, and calcaneus is proportional to the progression of AC [3–5]. Finally, advanced AC is associated with increased risk of osteoporotic fractures [5, 6]. Collectively, numerous epidemiological observations document an overlap between the pathogenesis of the two diseases [7, 8].
An attractive concept is that cardiovascular disease and osteoporosis are linked by a common denominator acting in parallel on both vascular and bone cells [9, 10]. Plausible candidates of such linking factors are serum lipids, which in addition to their established role in atherogenesis, were also shown to act on osteoblasts [11–13] and osteoclasts [14] under experimental conditions. Although some smaller cross-sectional studies found associations between lipid profile and BMD in humans [15–17], neither large population-based studies (e.g., NHANES III) nor prospective studies support these initial observations [18, 19]. A possible explanation the discrepancies could be that the true driver of the association is obstructive vascular disease, meaning that the association of lipids to bone is not detectable before the severity of intraluminal lesions reaches a critical grade when blood supply to the anatomical region is considerably hampered. Until now there have been no epidemiological studies that investigated associations of lipids and lipoprotein components with bone independent of a direct surrogate of the atherosclerotic burden.
The aim of the present study was to test this hypothesis and investigate associations of a wide array of serum lipids and lipoproteins as well as of a genetic determinant of lipid profile with different surrogate measures of osteoporosis (BMD, fractures) and cardiovascular disease (AC, acute events) in 1176 Danish postmenopausal women providing full-set of data for such analyses.
Subjects and methods
Study population
The study population consisted of 1176 generally healthy postmenopausal women participating in the PERF study. Details on recruiting have been described elsewhere [20]. This subpopulation was selected based on those whose BMD and body composition were measured by the same DXA scanner. The population characteristics were not statistically significant from the total PERF population indicating that the results reported herein are generally applicable to elderly Caucasian women 60–85 years old. None of the women received any approved antiresorptive treatment or any other drugs with known effect on bone mass for more than 1 year. Forty-two patients reporting ongoing treatment with lipid-lowering drugs was excluded when analyzing associations of allelic variation in the ApoE gene with lipid profile.
All women gave written their informed consent to participation and the study was carried out in compliance with the Helsinki Declaration II and the European Standards for Good Clinical Practice. The study protocol was approved by the local ethical committee.
Demographic characteristics, risk factors, and clinical events
Body weight and height were measured to the closest 0.1 kg and 0.1 cm, respectively, in women wearing light indoor clothing and no shoes. Body mass index (BMI) was calculated as body weight (in kg) divided by height squared (in m). Information about age, years since menopause, smoking habits, regular alcohol and coffee consumption, weekly exercise, prevalent diabetes and cardiovascular diseases (stroke, coronary events, intermittent claudication, unstable angina) were collected during personal interview using a questionnaire [20].
Bone mineral density and fat mass measurement
Bone mineral density (BMD) of the lumbar spine L1-4 and total hip was measured by dual energy X-ray absorptiometry (DEXA) using a QDR-2000 scanner (Hologic Inc., Waltham, MA, USA). Daily phantom scans were performed each morning for proper quality control. Body composition also was measured by the same whole-body scanner. The two components measured were total body fat mass (TFM) in kilograms and total lean mass in kilograms [21]. Total body fat mass was divided into two depots: central fat mass (CFM, subcutaneous and visceral fat mass of the trunk) and peripheral fat mass (PFM, subcutaneous fat mass of the legs and arms). Body fat distribution was expressed by the CFM/PFM ratio, analogous to the well-known waist-to-hip ratio [22].
Fracture diagnosis
Lateral X-rays of the thoracic and lumbar spine were performed using standard X-ray equipment. Vertebral deformities from T4 to L4 were assessed by digital measurements of vertebral deformations using the Image Pro Image Analyzer software (version 4.5 for windows, Media Cybernetics Inc., Silver Spring, MD, USA). The ratio of the anterior and posterior heights of each vertebral body was determined and a difference between the anterior and posterior edges exceeding 20% was considered as a radiographic vertebral fracture. Information on prevalent non-vertebral fractures (wrist, hip, humeral fracture, rib, ankle, and foot) was collected during personal interview and later verified by X-rays or hospital discharge summaries.
Grading of aorta calcification
AC was assessed on lateral radiographs. Briefly, calcified deposits in the lumbar aorta adjacent to each lumbar vertebra (L1–L4) were assessed separately for the anterior and posterior wall of the aorta using the midpoint of the inter-vertebral space as the boundaries. Each wall of each segment was graded for the presence of calcified deposits with a score from 0 to 3 (0: no deposits, 1: less than one-third of the aortic wall, 2: one-third to two-thirds of the aortic wall. 3: more than two-thirds of the aortic wall covered with calcified deposits). The sum of the scores of individual aortic segments both for the anterior and posterior walls, termed as anterior-posterior severity score and was used to describe the overall severity of AC in the lumbar aorta. Maximum score possibly given was 4×2×3=24. The same investigator, who was blinded for all other results of the individual participants, carried out the evaluations. Intra-rater correlations between repeated measurements were in the range of r=0.92–98 (n=50).
Laboratory parameters
Blood samples were collected in the morning after fasting overnight (>12 h). Serum total cholesterol, triglyceride, and high-density lipoprotein (HDL) cholesterol were determined by enzymatic assay using a Vitros-250 (Johnson & Johnson, Taastrup, Denmark). LDL cholesterol was calculated by Friedewald formula (LDL−C = TC−HDL−C−0.45 × TG). Lipoprotein(a), ApoA1, and ApoB were measured by the Cobas Mira (Hoffman-La Roche, Mannheim, Germany) automatic blood analyzer.
Genotyping
DNA was isolated from peripheral blood samples. ApoE epsilon 2, epsilon 3 and epsilon 4 alleles were determined by enzymatic amplification of genomic DNA followed by restriction enzyme treatment of the amplified products (Ossendorf and Prellwitz, Qiangen News 2000, issue1, 11–13). Briefly, amplified products were treated with AflII and HaeII, respectively, and subjected to electrophoretic separation in agarose gels. The sequences of the amplification primers were 5’-ACTGACCCCGGTGGCGGAGGAGACGCGTGC-3’ and 5’-TGTTCCACCAGGGGCCCCAGGCGCTCGCGG-3’. One of these primers was deliberately designed with a mismatch (underlined) to create a non-polymorphic AflIII site permitting assessment of the efficiency of the digestion process.
Statistical analysis
Results are presented as mean ± SD, unless otherwise indicated. Confounders of hip BMD and AC were identified by univariate correlation analysis. We classified ApoE genotypes into two categories marked by absence or presence of the ɛ4 allele. General linear models (GLM) tested the differences in selected dependent variables after adjustment for possible confounders. Similar approach was used to identify factors showing differences between women with or without fractures. Logistic regression models were established to assess the age-dependent and age-independent relative risk of wrist, hip, or vertebral fractures in women with advanced aorta calcification or cardiovascular disease. Statistical analyses were carried out using the SPSS data analysis software (version 12, SPSS Inc., Chicago, IL). All statistical tests were two-tailed and differences were considered significant if the p-value was less than 0.05.
Results
Demographic characteristics
Demographic characteristics of the total population are shown in Table 1. Less than one fifth of the population with an average age of 69.3 years had one or more manifestations of osteoporosis in form of a low BMD T-score equal or below −2.5 and/or a fracture. In terms of cardiovascular status, the mean severity score of AC was 3.0 ± 3.8 and the number of women with history of an acute cardiovascular event was 50 (4.3%).
Table 1Demographic characteristics in the study populationCharacteristics and equivalent valuesNo. of women1176Age (years)69.3 ± 6.4Age at menopause (years)48.7 ± 5.0BMI (kg/m2)26.4 ± 4.4Current smoking (%)24.6%Regular intake of alcohol (%)55.2%Serum total cholesterol (mmol/l)6.3 ± 1.0Serum triglyciders (mmol/l)1.4 ± 0.7Serum HDL (mmol/l)1.7 ± 0.4Serum LDL (mmol/l)4.0 ± 0.9Serum ApoA1 (mmol/l)203.9 ± 37.1Serum ApoB (mmol/l)120.3 ± 24.5Serum Lp(a) (mmol/l)31.9 ± 34.6ApoE ɛ4 allele carrier367, 31.2%Total hip BMD (g/cm2)0.80 ± 0.1Lumbar spine BMD (g/cm2)0.92 ± 0.2Hip BMD T-score ≤−2.5 (no. of women,%)147, 12.5%Spine BMD T-score ≤−2.5 (no. of women,%)179, 15.2%Vertebral fracture (no. of women, %)204, 17.6%Hip fracture (no. of women,%)16, 1.4%Aorta calcification3.0 ± 3.8Cardiovascular disease (no. of women,%)50, 4.3%Data shown are mean±SD.
The ApoE genotype frequencies were 0.9% (n = 11) for ApoE ɛ2-2, 12.7% (n = 149) for ApoE ɛ2-3, 2.5% (n = 29) for ApoE ɛ2–4, 55.2% (n = 649) for ApoE ɛ3–3, 26.6% (n = 313) for ApoE ɛ3–4, and 2.1% (n = 25) for ApoE ɛ4–4, respectively. When classifying ApoE genotypes into absence of ApoE ɛ4 allele and presence of ApoE ɛ4 allele, 31.2% (n = 367) of women were ApoE ɛ4 allele carriers. These genotype proportions did not deviate significantly with those expected under conditions of Hardy-Weinberg equilibrium (X2 = 4.55; df = 3; p = 0.21), and they were similar to those previously reported for Danish populations [22, 23].
Correlates of hip and spine BMD and AC
In univariate analyses, summarized in Table 2, AC showed direct correlation with age, CFM/PFM ratio, smoking, treated hypertension, and inverse association with physical exercise, regular alcohol consumption, BMI, and TFM%. On the other hand, BMI, TFM% and CFM/PFM ratio were significant direct, whereas age, years since menopause, and smoking were inverse correlates of both spine and hip BMD. Treated hypertension was significantly associated with spine BMD, whereas the severity score of AC was a significant inverse correlate of hip BMD (p < 0.05).
Table 2Independent correlates of aorta calcification, hip BMD, and spine BMD (multiple regression models) Aorta CalcificationHip BMDSpine BMDAge0.35 (p < 0.001)−0.23 (p < 0.001)−0.03 (p = 0.45)YSM−0.06 (p = 0.16)−0.06 (p = 0.10)−0.08 (p = 0.04)BMI−0.09 (p = 0.07)0.48 (p < 0.001)0.45 (p < 0.001)TFM%−0.04 (p = 0.36)−0.10 (p = 0.04)−0.21 (p < 0.001)CFM/PFM ratio0.08 (p = 0.02)−0.004 (p = 0.85)0.05 (p = 0.21)Smoking0.19 (p < 0.001)−0.05 (p = 0.10)−0.01 (p = 0.66)Exercise−0.03 (p = 0.25)0.04 (p = 0.17)0.04 (p = 0.21)Treated hypertension0.08 (p = 0.006)0.006 (p = 0.81)0.05 (p = 0.09)Alcohol consumption−0.08 (p = 0.007)0.06 (p = 0.04)0.07 (p = 0.02)Apo e4−0.009 (p = 0.77)0.01 (p = 0.76)−0.03 (p = 0.22)Triglyceride0.02 (p = 0.63)0.03 (p = 0.43)0.04 (p = 0.32)HDL-C0.05 (p = 0.48)−0.06 (p = 0.29)0.02 (p = 0.74)LDL-CExcl.0.02 (p = 0.73)−0.10 (p = 0.10)Total cholesterol0.05 (p = 0.43)Excl.Excl.ApoA1−0.10 (p = 0.04)0.05 (p = 0.36)0.05 (p = 0.39)ApoB0.10 (p = 0.14)−0.03 (p = 0.60)0.10 (p = 0.85)Aorta Calcification−0.09 (p = 0.002)0.04 (p = 0.20)R = 0.44, SEE = 3.32 P < 0.001R = 0.55, SEE = 0.09 P < 0.001R = 0.34, SEE = 0.13 P < 0.001Excl.: excluded from the model due to strong co-linearity.
The independent role of the ApoE ɛ 4 allele
Results of comparing lipids and lipoproteins between women with or without the ApoE ɛ4 allele are summarized in Table 3. After adjustment for confounders, women with an ApoE ɛ4 allele had significantly higher serum total cholesterol, triglycerides, LDL-C, and ApoB levels than women without this allele. Furthermore, presence of the ApoE ɛ4 allele was associated with significantly lower HDL-C. In contrast, the differences in serum ApoA1 and Lp(a) did not reach statistical significance (Table 3). Finally, there were no significant differences in adjusted spine or hip BMD or the severity of AC (p > 0.05).
Table 3Lipid and bone profile in women with or without an ApoE epsilon 4 allele Absence of ApoE epsilon 4 allele (n = 809)Presence of ApoE epsilon 4 allele (n = 367)P valueSerum total cholersterol* (mmol/l)6.24 ± 0.036.51 ± 0.05<0.001Serum triglycides* (mmol/l)1.36 ± 0.021.48 ± 0.030.005Serum HDL* (mmol/l)1.72 ± 0.011.65 ± 0.020.006Serum LDL* (mmol/l)3.91 ± 0.034.19 ± 0.05<0.001Serum ApoA1* (mmol/l)205.8 ± 1.3201.3 ± 2.00.06Serum ApoB* (mmol/l)117.3 ± 0.8127.2 ± 1.3<0.001Serum Lp(a)* (mmol/l)31.9 ± 1.329.2 ± 2.00.24Total hip BMD (g/cm2)*0.803 ± 0.0040.804 ± 0.0050.89Spine BMD (g/cm2)*0.924 ± 0.0050.915 ± 0.0080.32Hip fracture1.7%0.5%0.17Vertebral fractures16.4%19.3%0.24Severity score of AC**2.81 ± 0.142.97 ± 0.210.13Cardiovascular disease4.0%4.9%0.44Values are mean±SEM.*Adjustment for age, years since menopause, BMI, TFM%, CFM/PFM ratio, current smoking, physical exercise, and regular alcohol consumption.**Adjustment for the aforementioned confounders + treated hypertension.
Associations of lipids with BMD and AC
In univariate analysis (Table 2), total cholesterol and triglycerides were common correlates of spine BMD, hip BMD, and AC. HDL-C and ApoA1 were common correlates of AC and hip BMD (p < 0.05), whereas LDL-C, but not ApoB, was a common correlate of AC (p < 0.05).
To obtain insights into the direct contribution of lipids to the variation of hip and spine BMD and the severity of AC, we established multiple regression models. The independent contributors to the variation in these surrogate markers are indicated in Table 2. Lipids were not independent contributors to the variation in BMD when assessed in the presence of the severity of AC and other confounders. However, ApoA1 levels did seem to contribute to the variation in AC.
Table 4Characteristics of women with or without at least one vertebral fracture Without vertebral fractureWith vertebral fracturep-valueAge68.9 ± 6.471.3 ± 6.4<0.001YSM12.7 ± 8.415.5 ± 8.6<0.001BMI26.4 ± 4.426.3 ± 4.4NSTFM%41.3 ± 7.640.7 ± 7.8NSCFM/PFM ratio0.88 ± 0.230.90 ± 0.24NSRegular exercise73.8%67.6%0.08ApoE ɛ4 allele +30.5%34.8%NSTotal cholesterol6.32 ± 1.006.31 ± 1.04NSTriglycerides1.42 ± 0.691.31 ± 0.540.02HDL-C1.68 ± 0.431.71 ± 0.39NSLDL-C3.98 ± 0.934.01 ± 0.96NSApoA1203.8 ± 37.8204.6 ± 33.4NSApoB120.6 ± 24.5119.1 ± 24.5NSLp(a)31.7 ± 34.932.5 ± 33.5NSSpine BMD0.93 ± 0.150.87 ± 0.14<0.001Hip BMD0.82 ± 0.110.75 ± 0.11<0.001Hip fracture1.0%2.9%0.04Wrist fracture11.4%14.6%0.04AC score2.8 ± 3.73.5 ± 3.40.03CVD3.6%7.4%0.02There were no significant differences in the frequency of smoking, regular alcohol, coffee, milk or seasonal vitamin D consumption, type 2 diabetes, treated hyperlipidemia or treated hypertension
Comparison of women with or without fractures
There were altogether 293 subjects who had an osteoporotic fracture after the menopause (i.e., prevalent hip, vertebral, or wrist fracture). Of the 204 women with at least one vertebral fracture, 33 also had a history of wrist fracture and 16 reported a history of hip fracture. Prevalence of non-vertebral fractures was significantly higher in women with compared with those without vertebral fracture(s). Characteristics of women with or without vertebral fractures are summarized in Table 4. Women with fractures were on average older and had a tendency for being physically less active. However, no significant differences in BMI, body adiposity, or body fat distribution were apparent. In addition, no significant differences in a wide array of lifestyle factors were apparent.
When comparing the lipid profile of women with or without osteoporotic fractures after adjustment for potential confounders (i.e., age, years since menopause, BMI, TFM%, CFM/PFM ratio, smoking, ApoE ɛ4 allele, physical exercise, alcohol consumption, and severity score of AC), only triglycerides showed significant differences between the two groups (p < 0.05). Thus, triglycerides in women with and without fractures were 1.31 ± 0.04 mmol/l and 1.42 ± 0.03 mmol/l, respectively. When analyzing fracture types separately, the difference between women with or without hip or wrist fractures were not statistically significant.
The relative risk of hip or vertebral fracture in women with severe AC or CVD
To assess the implications of atherosclerotic vascular disease for osteoporotic fracture risk, we calculated the odds ratio of the different types of fractures in women with severe AC (≥6) and/or manifest CVD. As indicated in Table 5, after adjustment for age, the risk of hip fractures but not wrist or vertebral fractures was increased in subjects with advanced vascular disease.
Table 5Relative risk of different types of osteoporotic fractures in women with severe aorta calcification (score ≥ 6) and/or manifest cardiovascular disease (n = 282)  Odds ratio (95% CI)p-valueHip fracture N = 16Crude4.4 (1.6–12.9)0.001Age-adjusted3.0 (1.1–8.8)0.04Vertebral fracture N = 204Crude1.2 (0.9–1.7)0.27Age-adjusted1.0 (0.7–1.4)0.93Wrist fracture N = 145Crude1.4 (1.0–2.1)0.06Age-adjusted1.2 (0.8–1.7)0.46
Discussion
In the present study, we investigated whether serum lipid and lipoproteins represent a biological linkage between osteoporosis and cardiovascular disease. The main findings were as follows: 1) neither allelic polymorphism in the ApoE gene nor serum lipids per se were independent correlates of BMD at any skeletal site, 2) ApoA1 levels were independent correlates of AC, which seem to play a role in the determination of hip BMD, 3) decreased triglycerides were independently associated with vertebral fractures, but not with non-vertebral fractures (hip and wrist), and 4) advanced vascular disease was a significant contributor to risk of hip fractures, but not to vertebral or wrist fractures. These observations suggest that the role of lipids as linking factors between cardiovascular disease and osteoporosis is indirect via promotion of atherogenesis, which in turn can contribute to bone loss, especially at skeletal sites with end-arterial blood supply. Antiatherogenic measures can also be expected to contribute to decreasing the burden of hip fractures among the elderly.
Univariate analysis pointed out several common correlates of BMD and atherosclerosis. Of these factors, aging, the duration of the menopause, BMI, and TFM% seemed to have reciprocal impact on BMD and AC. In multiple regression models, whereas BMI continued to correlate directly, TFM% became an inverse correlate of BMD. Accordingly, while weight-bearing may have a favourable impact on bone metabolism, adipose tissue accumulation exert an adverse influence. These findings corroborate the recent findings of Hsu YH et al. [24]. Although traditional views considered obesity a protective factor due to endogenous estrogen production, these more recent findings emphasize that other factors deriving from adipose tissue, e.g., adipokines, inflammatory cytokines, and perhaps even lipids/lipoprotein metabolism are also to be taken into account. In addition, these findings also draw attention to the need of proper adjustment for overall adiposity and body fat distribution when addressing the direct implication of selected potential mediators.
To address whether serum lipids represent a biological linkage between osteoporosis and vascular disease, one approach is to investigate whether polymorphism in a gene with known modulator effects on serum lipid profile is associated with variation in the severity of AC and BMD. Similar to previous observations [25, 26], we found that presence of the ɛ4 variant allele in the ApoE gene was independently associated with higher levels of total cholesterol, LDL-C and ApoB. In addition, we also observed subtle, yet statistically significant differences in serum triglycerides and HDL-C levels. Nevertheless, we were not able to document significant associations of the ɛ4 allele with either BMD or AC score. In male or mixed populations, the ɛ4 allele was reported as a risk factor for atherosclerosis [27, 28], suggesting that the association might be gender-specific for males. Total cholesterol and LDL-C are important predictors of cardiovascular risk in men, but less so in postmenopausal women in whom triglycerides and HDL-C carry greater importance [29, 30]. Another explanation to the apparent discrepancies could be geographic variation in the relative importance of allelic variation in the ApoE gene. In support, a study in Finnish men reported higher importance of the ɛ3 allele for atherogenesis compared with the ɛ4 allele [27]. Similar discrepancies exist concerning the relative importance of this gene polymorphism for the determination of bone mass. Although there are reports suggesting that presence of the ɛ4 allele is a contributor to accelerated bone loss and/or increased risk of osteoporotic fractures [31, 32], not all studies confirm this finding, particularly those undertaken in women [33–35]. Collectively, ApoE polymorphism with primary influence on total cholesterol, LDL-C, and apoB levels does not seem to provide a major biological linkage between the pathogenesis of osteoporosis and CVD.
Experimental observations proposed LDL-C and HDL-C as common modulators of bone cells and vascular smooth muscle cells [11–14]. On the clinical side, smaller cross-sectional studies found associations between lipid profile and BMD [15–17]. However, none of these studies adjusted systematically for a direct DEXA measure of body fat distribution and/or smoking habits, which are important confounders of lipid profile. Our multiple regression analyses could not reveal significant independent associations of any of the considered lipid and lipoprotein components with hip or spine BMD. These findings are in line with the largest population-based observational study, the NHAEMS III survey including more than 13,000 subjects [19]. In further support, a recent longitudinal analysis of results from the Framingham study cohort reported insignificant direct influence of serum lipids for changes of BMD during a 25-year observational period [18]. Collectively, these observations do not seem to nurture the concept that serum lipids and lipoproteins exert clinically detectable direct effects on bone mineralization in elderly women.
To further assess the potential implications of serum lipids and lipoproteins for osteoporosis, we also compared the profile of postmenopausal women with or without osteoporotic fractures. Interestingly, serum triglycerides were significantly lower in women with at least one vertebral fracture compared with those with no fractures, while no differences were seen between those with or without an osteoporotic non-vertebral fracture (i.e., hip or wrist fracture). This finding is similar to that reported by Yamaguchi et al. [15]. Since triglycerides were not associated with spine BMD, their direct contribution to fracture risk, if any, is via modulation of bone quality or bone strength. Given the cross-sectional design of this study, we cannot exclude the possibility that a confounder or confounders of triglyceride levels, which was not considered herein is the actual modulator of bone fragility and hence fracture risk.
Important finding of the multiple regression analysis was that the severity of AC was an independent correlate of hip BMD with no simultaneous independent contribution of lipids. This observation provides evidence that obstructive vascular disease rather than lipids/lipoproteins per se that drive bone loss from the hip. In a previous study, we showed that women with intermittent claudication have not only severe AC, but also very low BMD [2]. The direct contribution of atherosclerosis is also supported by the observation showing that asymmetric vascular disease is accompanied by asymmetric demineralization of this skeletal site [36]. Moreover, studies show that the rate of demineralization at the hip is significantly associated with the rate of atherogenesis [5] and even future risk of cardiovascular events [37]. On the other hand, we recently demonstrated in a large population-based cohort of postmenopausal women that accelerated atherogenesis is an independent predictor of hip fracture risk. Histological investigations of explants from elderly patients with femoral neck fractures indicate that both the larger (a. iliaca ext and a. femoris profunda) and the small vessels in the ligamentum teres supplying this skeletal site are frequently obstructed by atheromatous lesions [38, 39]. These observations provide strong support for the important role of atherosclerosis for the pathogenesis of osteoporosis in the proximal femur.
In summary, the results of the present observational study provide further evidence for the independent association of peripheral vascular disease with osteoporosis in the proximal femur. Since the association of lipids and lipoproteins to BMD and non-vertebral fractures is not independent of the severity of AC, it seems unlikely that these metabolites exert direct and clinically significant effects on bone turnover in postmenopausal women. Their contribution is via promotion of atherogenesis, in which regard ApoA1 levels seem to take a leading role. The remaining issue to be clarified is which genetic or environmental factors underlie the association of low triglycerides levels to vertebral fractures.

osteoporosis
lipids
cardiovascular events
aorta calcification
apoe polymorphism