Heat Shock Proteins and Amateur Chaperones in Amyloid-Beta Accumulation and Clearance in Alzheimer’s Disease

The pathologic lesions of Alzheimer’s disease (AD) are characterized by accumulation of protein aggregates consisting of intracellular or extracellular misfolded proteins. The amyloid-β (Aβ) protein accumulates extracellularly in senile plaques and cerebral amyloid angiopathy, whereas the hyperphosphorylated tau protein accumulates intracellularly as neurofibrillary tangles. “Professional chaperones”, such as the heat shock protein family, have a function in the prevention of protein misfolding and subsequent aggregation. “Amateur” chaperones, such as apolipoproteins and heparan sulfate proteoglycans, bind amyloidogenic proteins and may affect their aggregation process. Professional and amateur chaperones not only colocalize with the pathological lesions of AD, but may also be involved in conformational changes of Aβ, and in the clearance of Aβ from the brain via phagocytosis or active transport across the blood–brain barrier. Thus, both professional and amateur chaperones may be involved in the aggregation, accumulation, persistence, and clearance of Aβ and tau and in other Aβ-associated reactions such as inflammation associated with AD lesions, and may, therefore, serve as potential targets for therapeutic intervention.
Introduction
Pathological lesions consisting of intra- and/or extracellular accumulations of misfolded proteins are characteristic for neurodegenerative diseases such as Alzheimer’s disease (AD). AD is characterized by three distinct pathological lesions: senile plaques (SPs), neurofibrillary tangles (NFTs), and cerebrovascular amyloid angiopathy (CAA) [1]. Both SPs and CAA are formed by extracellular deposition of aggregated amyloid-beta protein (Aβ), whereas NFTs consist of intracellular aggregates of hyperphosphorylated tau protein in the cytoplasm of neurons [2, 3]. The Aβ protein is a 4-kDa proteolytic cleavage product [2] of the transmembrane amyloid-β precursor protein (APP). The two major forms of Aβ in human brain are Aβ1-40 and Aβ1-42, differing from each other only by two amino acids. Cerebral production of Aβ is balanced by clearance from the brain either via active transport across the blood–brain barrier (BBB) or via uptake and degradation of Aβ by microglial cells and astrocytes [4–6]. Active transport of Aβ is mediated by Aβ receptors that are capable of transporting Aβ, or Aβ in complex with other proteins, across the BBB [7]. In contrast to normal brain, the cerebral Aβ balance is disturbed in AD brains, resulting in accumulation and aggregation of Aβ.
Aβ aggregation includes the formation of Aβ oligomers, protofibrils, and eventually, mature fibrils. Both Aβ oligomers and protofibrils are considered the most toxic forms of Aβ that initiate degeneration of neurons and of cells within the vasculature, such as smooth muscle cells and pericytes [8, 9]. Aβ aggregates do not clear from the brain as efficiently as soluble Aβ, and thus, directly lead to increased levels of Aβ in the brain [10]. Furthermore, deposition of Aβ in SPs is accompanied by attraction and activation of both microglial cells and astrocytes [11–13]. Activation of these cell types results in increased secretion of pro-inflammatory cytokines as part of a neuro-inflammatory reaction.
Chaperones can be defined as proteins that: (1) have a role in the intracellular handling of misfolded proteins, (2) induce conformational changes of proteins, (3) act as transporter of proteins. “Professional” chaperones, such as the heat shock protein family (Hsp), are defined as proteins that have a specific function in facilitating normal folding of proteins and intracellular handling of misfolded proteins. Members of the Hsp family recognize misfolded proteins and transport them to the proteasome for degradation. Therefore, this protein family acts as the first line of defense against toxicity induced by misfolded proteins such as Aβ and tau. In contrast to professional chaperones, “amateur” chaperones can be defined as proteins that bind to other proteins and induce conformational changes or, alternatively, serve as transporter proteins. Examples of putative amateur chaperones are apolipoprotein E (ApoE), heparan sulfate proteoglycans (HSPGs), and complement factors such as C1q. They have, in contrast to the professional chaperones, primarly an extracellular function. In this paper, we will review the role of both amateur and professional chaperones in the pathogenesis of AD.
Aβ-Binding Proteins in Extracellular Interaction with Aβ
Apolipoproteins
The apolipoprotein family consists of proteins that conjugate with lipids to form different classes of lipoprotein particles. In human brain, several members of this protein family are expressed, such as apolipoprotein E (ApoE), apolipoprotein J (ApoJ), and apolipoprotein D (apoD).
ApoE is a major determinant of lipid transport and metabolism and is expressed in brain by astrocytes, microglia, pericytes, and smooth muscle cells [14–18]. In human, three common isoforms are expressed: apoE2, apoE3, and apoE4 which are all products of alleles at a single gene locus [19, 20].
The ɛ4 allele of ApoE is the major genetic risk factor for AD, whereas the ɛ2 allele appears to be protective against AD [21–24]. As ApoE immunoreactivity was found in extracellular amyloid deposits in subjects with AD, it has been suggested that it affects amyloidogenesis [25, 26]. In vitro studies provided evidence for a direct interaction of ApoE with Aβ and the formation of stable complexes [27, 28]. Binding of ApoE to Aβ is, however, ApoE isoform-dependent (ɛ2>ɛ3>>ɛ4) [29, 30] and depends on the degree of lipidation [29]. Lipidation of ApoE also seems a major factor in its effect on Aβ-mediated cellular toxicity [18]. In addition, ApoE4 promotes the conversion of soluble Aβ into β-sheet-rich amyloid more than ApoE3 [31–33].
In contrast to its effect on Aβ in vitro where a consistent accelerating effect of ApoE on Aβ aggregation is observed, the effect of ApoE on Aβ deposition in transgenic (Tg) mice studies is less equivocal. In early studies, both Aβ immunoreactivity and amyloid formation were reduced in ApoE knockout mice [31, 32]. In addition, CAA and associated microhemorrhages were also suppressed in ApoE knockout mice [34]. This effect might be due to the absence of ApoE/Aβ complexes [35]. In contrast to the effects of murine ApoE in the early studies, both human ApoE3 and ApoE4 suppressed Aβ deposition in Tg mice [36]. In addition, when these mice aged, ApoE4 induced a tenfold higher deposition of fibrillar Aβ than ApoE3 [37]. Consistent with these latter results, human ApoE4 accelerated Aβ deposition in APPSwe Tg mice relative to human ApoE3 [38]. In addition, when human ApoE3 or ApoE4 were knocked in in Tg mice, Aβ deposition was reduced compared to mice carrying endogenous ApoE at 9 months, and at 15 months, substantial CAA was observed in mice with human ApoE4, but not with human ApoE3, and, in either case, parenchymal Aβ was sparse [39]. Thus isoform- and species-specific differences in ApoE direct the aggregation or clearance of Aβ. Furthermore, it is suggested that the presence of ApoE facilitates internalization and degradation of Aβ from brain parenchyma by astrocytes [40] and human ApoE may reduce Aβ deposition in mouse brain by facilitating Aβ transport across the BBB [36]. Although these Tg mice studies seem contradictional, ApoE clearly affects conformational changes of Aβ and functions as an Aβ-transporter protein.
Besides colocalization of ApoE with Aβ in AD brains, ApoE is also found within neurons containing NFTs [25] where it is able to interact directly with tau protein [41]. Furthermore, ApoE has an isoform-dependent effect on tau phosphorylation, as ApoE3 binds to tau in vitro, whereas ApoE4 fails to bind tau [42]. In addition, an ApoE4-dependent increase in phosphorylated tau has been observed [43–45].
Neuroinflammation in AD comprises both activation of microglial cells and astrocytes and activation of the complement system. Aβ deposits in brain are associated with activated microglia and astrocytes, but also with elevated levels of complement [5, 6, 46]. ApoE may have an anti-inflammatory effect by suppressing microglial and astrocytic activation [47–50]. ApoE-deficient mice demonstrate increased levels of IL-6 and TNFα after LPS stimulation, suggesting a role of ApoE in inflammatory gene regulation [51]. In addition, ApoE isoform-dependent (ɛ2<ɛ3<ɛ4) differences in nitric oxide (NO) levels have been observed in microglia cells [52]. Transgenic mice expressing the ApoE4 protein isoform show a greater NO production than mice expressing the ApoE3 protein isoform. These data indicate that ApoE4 has a less efficient anti-inflammatory affect, and thus, may accelerate the development of AD.
Apolipoprotein J, also known as clusterin or SP-40/40, is a highly conserved heterodimeric secreted glycoprotein expressed in brain by epithelial and neuronal cells [53]. ApoJ colocalizes with fibrillar Aβ deposits, and it is suggested that it prevents misfolding and aggregation of soluble Aβ [54–56]. ApoD is a glycoprotein associated with high-density lipoproteins in human plasma and also has a high expression level in human brain [57], but neither its physiological role nor its ligand has been identified. ApoD levels are increased in the hippocampus of AD patients and in ApoE-deficient mice [58, 59].
In conclusion, ApoE and ApoJ can be regarded as amateur chaperones that regulate Aβ aggregation in vitro. By accelerating the Aβ aggregation process towards mature fibril formation, (human) ApoE prevents formation of toxic Aβ intermediates such as oligomers and protofibrils, and thus, may have a protective function towards development of AD. Moreover, ApoE protects against the development of AD by suppressing the inflammatory reactions associated with AD lesions. Besides its role in inducing conformational changes in Aβ, ApoE facilitates Aβ clearance from brain by serving as a transporter molecule of Aβ, which will be discussed in paragraph 4.
Heparan Sulfate Proteoglycans
Proteoglycans are members of a large family of macromolecules with a wide variety of functions ranging from simple physical support to various effects on cell adhesion, motility, proliferation, differentiation, and even tissue morphogenesis. They are composed of linear sulfated polysaccharides (glycosaminoglycans, GAGs), consisting of disaccharide units, covalently bound to a core protein. One of the members of this superfamily is the heparan sulfate proteoglycan (HSPG) family characterized by polymers of repeating disaccharides, N-acetylglucosamine and glucuronic acid, which can be subsequently modified by sulfatation [60, 61]. HSPGs can be subdivided into a family of extracellular matrix proteins, including perlecan, agrin, and collagen XVIII, and a family of cell surface proteins, including syndecans and glypicans [60, 62].
Ever since GAGs were demonstrated in amyloid deposits, the proteoglycans became of interest in amyloidogenesis. The presence of HSPGs in SPs, CAA, and NFTs in AD brains was already demonstrated in the late 1980s [63–65]. Only when antibodies became available that could identify the various individual HSPG species was it described that perlecan colocalized with all three lesions characteristic of AD brains [65–67]. However, we were not able to confirm these findings [68, 69]. Furthermore, it was shown that in both diffuse and classic SPs, several other HSPGs were found, such as agrin, glypican 1, and syndecan 1-3, whereas collagen XVIII is only present in classic SPs and CAA [69–72].
These data suggest that HSPGs interact with Aβ, thereby contributing to development or persistence of SPs or CAA. HSPGs isolated from Engelbreth–Holm–Swarm tumor prevented proteolytic breakdown of aggregated Aβ [73]. In addition, both agrin and perlecan directly interacted with Aβ and promoted conversion of non-fibrillar Aβ into fibrillar Aβ [70, 74–76]. Although the interaction between HSPGs and Aβ is likely mediated predominantly by the sulfate moieties of the GAGs, a role for the protein backbone in Aβ aggregation could not be excluded [77, 78]. As sulfated GAGs were also demonstrated in NFTs in AD brains [79], these macromolecules may also play a role in tangle development. Indeed, sulfated GAGs may induce the formation of paired helical filaments by stimulating tau phosphorylation [80].
As heparan sulfates bind to Aβ and interfere with its fibrillogenesis, they are interesting candidates for therapeutic intervention [81]. GAG mimetics are able to inhibit this binding and may block the formation of β-pleated sheets and adherence of Aβ to the cell surface [82]. The use of GAG mimetics has already been explored in mouse models where they reduced progression of inflammation-associated amyloidosis [83]. The efficacy of one of these compounds is currently being tested in a human phase III trial.
As exemplified by ApoE, Aβ-binding proteins may play a role in the inflammatory reactions in AD brains. Recently, it was demonstrated that the semi-synthetic proteoglycan analogue dextran sulfate blocks activation of the complement cascade [84]. In addition, chondroitin sulfate proteoglycans are also known to bind to C1q and prevent the formation of the C1 complex in vitro [85]. By doing so, chondroitin sulfate proteoglycans inhibit normal complement function. Furthermore, heparin has long been regarded as a potential complement inhibitor [86].
In conclusion, HSPGs do not only colocalize with Aβ and tau, but they also contribute to the development of these lesions. The role of HSPGs in Aβ aggregation might even be a protective one. HSPGs prevent the persistence of toxic Aβ forms, e.g., oligomers or protofibrils, and transform them into more harmless aggregates, i.e., the classic senile plaques containing mature Aβ fibrils that are less toxic than the intermediate aggregates. In addition, HSPGs might play a role in the development of AD lesions by inhibiting complement activation. According to the definitions, HSPGs can therefore be regarded as amateur chaperones. Their ability to recognize a variety of proteins may originate from the heterogeneous structure of the heparan sulfate chains. The negatively charged HS chains are structurally heterogeneous and bind a diverse repertoire of proteins, such as amyloid A, protease-resistant prion protein, α-synuclein, and tau, providing HSPGs with the ability to interact with a wide range of intracellular and extracellular amyloidogenic proteins [61].
Complement Factors
The complement system is an ancient host defense mechanism which is involved in boosting antibody activity. The system consists of a group of soluble serum proteins C1–C9 and is activated either by immunoglobulin M or G bound to a foreign particle or directly by microorganisms. Proteins such as Hageman factor, C4 binding protein, CDS46, CD59, and C1 inhibitor regulate the complement system. In AD, the complement system is overexpressed and activated [46]. The Aβ protein itself activates this system, and complement factor concentrations are increased in AD brains [87–89]. Aβ induces C3 and C4 in AD, and elevated levels of the membrane attack complex (MAC) composed of C5–C9 have been observed [90, 91]. In addition, factors such as Hageman factor, C1q, C3, and C5–9 are commonly found in SPs and NFTs [87, 92, 93]. C1q is associated with Aβ deposits and directly binds fibrillar Aβ which activates the complement cascade [94]. In contrast, the complement inhibitor (C1 INH) is downregulated in AD [95, 96]. Thus, an activated complement system is a general feature observed in AD. However, the contribution of complement to the pathogenesis of AD is controversial.
On the one hand, it is suggested that complement activation protects against Aβ-induced toxicity and even contributes to reducing the accumulation of Aβ in SPs [97]. Transgenic mice expressing complement inhibitors develop increased AD-pathology, whereas increased complement C3 production was associated with a reduction of Aβ deposition [97]. Thus, the complement activation in the brain may be beneficial in AD and possibly also other neurodegenerative diseases [98–100].
However, complement activation may lead to accelerated neurodegeneration as well. Activation of complement in an antibody-independent fashion is achieved by binding of aggregated, but not soluble, Aβ to C1q [12, 90, 101, 102]. This latter finding suggests that in AD, aggregated Aβ induces chronic complement activation. Thus, C1 binding to fibrillar Aβ deposits may precede microglial activation. Both Aβ and pro-inflammatory stimuli are able to activate microglia, which results in increased Aβ and cytokine production [103]. Furthermore, cultured human microglial cells show an increase in cytokine production after co-stimulation of Aβ with C1q and serum amyloid P (SAP) [104]. This suggests that microglia may get triggered by both Aβ- and SP-associated factors such as C1q, which results in the secretion of pro-inflammatory cytokines and Aβ, both accelerating neurodegeneration.
Although none of the complement factors directly regulate conformational changes of Aβ, complement activation as a whole plays a role in the Aβ aggregation in vivo. Therefore, complement factors might act as amateur chaperones, although their exact role in Aβ aggregation remains to be elucidated.
Professional Chaperones
Heat shock proteins (Hsp) are professional chaperones. They are highly conserved proteins constitutively expressed in most cells under normal conditions where they play a role in cellular metabolism and help normal folding processes [105]. In addition, during cell stress, they bind unfolded proteins to keep them in their native state [105]. Heat shock proteins can be divided into two different families based on size and function: classic Hsps such as Hsp100, Hsp90, Hsp70, Hsp60, and the small heat shock proteins (sHsps). Hsps with a molecular weight of 60 kD or more possess an ATP-binding site and are actively involved in the process of refolding of misfolded proteins [106]. Small Hsps, with a molecular weight of 40 kD or less, lack this ATP-binding site and assist the Hsps in their refolding function [107]. The role of Hsps in misfolded protein recognition and refolding is illustrated in Fig. 1.
Fig. 1The role of heat shock proteins (Hsp) and small heat shock proteins (sHsps) in recognition and refolding of unfolded and misfolded proteins. Unfolded or misfolded proteins are recognized by Hsps and sHsps. Together with these unfolded or misfolded proteins, Hsps and sHsps form a complex. In addition, Hsps recover unfolded or misfolded proteins back to their native form using ATP. If unfolded or misfolded protein are not recognized by the Hsp/sHsps, these unfolded or misfolded proteins are capable of forming aggregates
Small Heat Shock Proteins
Small Hsps function as molecular chaperones that can prevent proteins from adopting an incorrect conformation [108]. The sHsp family is characterized by the presence of an α-crystallin domain, a stretch of 80–100 amino acids in the C terminal half of the proteins [109]. So far, the sHsp family comprises ten sHsps, including αB-crystallin, Hsp27, Hsp20, HspB8, and HspB2/B3 [110]. Although sHsps are predominantly expressed in muscle cells, several family members are also found in human brain.
In AD, αB-crystallin and Hsp27 are upregulated and expressed by astrocytes surrounding SPs and NFTs [111–114], whereas Hsp20, HspB2, and HspB8 colocalize with Aβ in SPs and CAA [115, 116]. Although αB-crystallin or Hsp27 do not colocalize with Aβ in SPs, direct interaction between Aβ and these sHsps in addition to Hsp20 and HspB8 has been demonstrated [111, 117–119]. In addition, high-affinity binding of αB-crystallin and Aβ has been observed in eye lenses from AD patients [120]. Furthermore, αB-crystallin is able to prevent mature Aβ fibril formation, retaining it in a non-fibrillar, but likely a protofibrillar state, which is highly toxic to neurons [121]. Recently, we demonstrated that αB-crystallin, Hsp20, and HspB8 inhibit Aβ-mediated toxicity towards cerebrovascular cells probably by preventing aggregation of Aβ at the cell surface [116, 117]. Others showed that Hsp27 directly binds to hyperphosphorylated tau, thereby protecting against cell death [122].
Hsps are involved in the formation and persistence of misfolded protein aggregates. They are upregulated in several neurodegenerative diseases, such as AD, Creutzfeldt–Jakob disease, and Parkinson’s disease probably as a reaction to the formation of misfolded proteins [113, 123–126]. However, despite of increased intracellular levels, they are unable to prevent accumulation of Aβ in AD possibly because of decreased chaperone activity. In aged rats, this was illustrated by a significant decrease of Hsp90 function [127], resulting in diminished hepatic chaperone capacity. Furthermore, the increasing amount of damaged or misfolded proteins as a result of defects in protein degradation might lead to a total decrease in chaperone activity in aged cells [128]. Thus, the state of misfolded protein recognition and repair systems, such as the (s)Hsp system, might be of great importance in the development of neurodegenerative diseases.
Miscellaneous Proteins
Apart from the above-described proteins, several other molecules are also associated with the pathological lesions of AD, and some of these can be regarded as amateur chaperones. Acute phase proteins, such as α1-antichymotrypsin (ACT), α2-macroglobulin (α2M), and SAP, are all associated with Aβ deposition [129–132]. ACT is a serine protease inhibitor of the serpin family, and in AD, ACT levels are upregulated, and binding of ACT with Aβ induces Aβ fibrillogenesis [133–135]. Furthermore, when ACT is overexpressed in transgenic mice, an increased plaque load in the brains of these mice and impaired spatial learning is observed [134, 135]. α2M also binds Aβ, although in contrast to ACT, this binding prevents Aβ fibril formation and fibril-associated neurotoxicity [136, 137]. α2M promotes the protease-mediated degradation of α2M/Aβ complexes and contributes to clearance of Aβ from the brain (discussed in paragraph 4) [138, 139]. The glycoprotein SAP belongs to the pentraxin family and is a common component of all known types of amyloid fibrils. SAP is upregulated in AD and protects amyloid fibrils from proteolysis in vitro [140, 141]. SAP not only colocalizes with SPs and interacts with aggregated Aβ; SAP oligomers also bind and activate C1 [142]. Both C1 and SAP may bind to fibrillar Aβ deposits in vivo and induce microglial activation, as cultured human microglial cells show an increase in cytokine production after co-stimulation of Aβ with C1q and SAP [104]. These observations further strengthen the above-noted suggestion that not only Aβ, but also several Aβ-binding proteins, are capable of activating the complement system, and thus, contribute to neuroinflammation in AD. In addition, both α2M and ACT, in contrast to SAP, can be regarded as amateur chaperones, as they regulate conformational changes of Aβ.
Tissue-type plasminogen activator (tPA) regulates activation of plasminogen into plasmin and is expressed in various regions of the brain especially in the hippocampus [143]. Several reports suggested an important role for tPA in AD, as the tPA system is involved in Aβ turnover [144, 145]. Fibrillar forms of Aβ stimulate tPA activity in vitro, whereas in AD patients, a reduction of tPA activity is observed in the affected areas [144, 146]. Although tPA has no effect on conformational changes of Aβ, it might play a role in the clearance of Aβ from the brain (paragraph 4].
The actin-regulatory protein gelsolin is found both intracellularly and in plasma [147, 148]. Plasma gelsolin can be considered an amateur chaperone, as it binds Aβ and not only inhibits its Aβ fibrillization but is also capable of degrading preformed Aβ fibrils [149, 150]. Furthermore, gelsolin inhibits Aβ-mediated neurotoxicity [151].
One of the major gangliosides in the brain is GM1. Soluble Aβ binds GM1 and the formed complexes accelerate Aβ fibrillogenesis by acting as a seed for Aβ [152]. In the presence of GM1, Aβ is more neurotoxic than Aβ alone, and cholesterol-rich membranes demonstrate accelerated Aβ binding due to the formation of GM1 clusters [153, 154]. As GM1 is a major component of lipid rafts and recent studies suggest that Aβ accumulation in these lipid rafts is an early event in AD development, GM1 might play an important role in the early steps in AD pathogenesis [155, 156].
In summary, several proteins are associated with Aβ aggregates in the AD brain and contribute to the aggregation of Aβ and should, therefore, be considered as amateur chaperones. In addition, they might play a role in triggering inflammation.
Aβ-Binding Proteins and Intracellular Interactions with Aβ
Intracellular accumulation of Aβ already starts in the ER or in the Golgi apparatus of the cell [157–159]. Intracellular Aβ is associated with neuronal damage [160, 161], and intraneuronal accumulation of Aβ in transgenic mice was correlated with impairments in synaptic plasticity [162]. Intraneuronal accumulation of Aβ in those brain areas affected earliest in AD suggests a possible relation between intracellular Aβ and development of AD [160].
A few proteins that interact with intracellular Aβ and affect its intracellular fate have been identified. The endoplasmic reticulum amyloid beta-peptide-binding protein binds intracellular Aβ and mediates neurotoxicity in neuronal cells by forming an intracellular target for Aβ [163]. In addition, the mitochondrial enzyme amyloid-β alcohol dehydrogenase also binds Aβ inside neurons, resulting in the production of free radicals [164]. However, whether these intracellular Aβ-binding proteins affect aggregation of Aβ within the cells remains unknown. Therefore, both these proteins cannot, for the time being, be defined as amateur chaperones of Aβ.
The first lines of defense against misfolded and aggregated proteins are the professional chaperones, which counteract these processes and are able to stimulate clearance of misfolded proteins by proteosomal degradation. Newly synthesized proteins are folded by several other proteins, such as immunoglobulin-binding protein (BiP)/glucose-regulated protein (GRP78), and calnexin. GRP78 is a member of the Hsp70 protein family and interacts with intracellular APP. GRP78 regulates APP and Aβ secretion by intervening between APP and β-/γ-secretases within the cell [165].
It is not surprising that in AD, where misfolded protein molecules accumulate, both Hsp90 and Hsp70 synthesis is increased. Several members of the Hsp family directly interact with intracellular Aβ, but only recently, Hsp70 was identified as a protector against intracellular Aβ accumulation [166, 167]. Besides, immunoreactivity of both Hsp90, 70, and Hsp60 is found in SPs [132], which suggests that these professional chaperones may not only interact with misfolded protein in the cell interior [168–171]. In addition, it has also been postulated that up-regulation of Hsp90 and Hsp70 may suppress the formation of NFTs by partitioning tau into a productive folding pathway and thereby preventing its aggregation [172]. Recently, it was demonstrated that the chaperone CHIP–Hsc70 complex conjugates ubiquitin to hyperphosphorylated tau, which enhances cell survival by elimination of soluble hyperphosphorylated tau [173]. These data suggest that the cell increases production of the Hsps to cope with the presence of misfolded proteins such as hyperphosphorylated tau and accumulating Aβ. At some point, this protective mechanism seems to fail, however. In line with this hypothesis, it was shown that the actin and tubulin specific chaperone Hsp60 is decreased in AD, resulting in a decrease of cytoskeletal proteins in AD-affected neurons [174]. Thus, both production and function of Hsps seems to be disturbed in AD, which might result in the accumulation of misfolded proteins. The role of other Hsps in regulating intracellular Aβ or tau folding remains to be investigated (Table 1).
Table 1Summary of the expression of chaperones in AD brains and their interaction and effects on Aβ and tau SP/CAANFTDirect interactionEffects on Aβ or tau in generalApolipoproteins ApoE++Aβ/tau↑ Fibrillar Aβ /↓ hyperph. Tau ApoJ+?Aβ↓ Aβ aggregationHSPGs Perlecan±±AβHSPGs: Agrin+−Aβ↓ Proteolytic breakdown Aβ Glypican 1+−?↑ Non-fibrillar → fibrillar Aβ Syndecan 1–3+−?↑ Phosphorylation tau Collagen XVIII+−? GAGs++Aβ/tauComplement factors Hageman Factor++?Aβ activates complement in AD C1q++AβC3 ↓ Aβ deposition C3/C4++Aβ C5-9++?Heat shock proteins Hsp90+?Tau↓ Tau aggregation Hsp70+?Aβ/tau↓ Tau aggregationSmall Hsps αB-crystallin−−Aβ↓ Aβ fibril formation Hsp27−±Aβ/tau↓ Aβ fibril formation Hsp20+−Aβ↓ Aβ fibril formation HspB2/B3++–No effect HspB8+−Aβ↓ Aβ fibril formationAcute phase proteins α1-antichymotrypsin+−Aβ↑ Aβ fibrillization α2-macroglobulin+−Aβ serum amyloid P++Aβ↑ Aβ fibrillizationMiscellaneous compounds tPA−−Aβ↓ Aβ fibril formation Gelsolin−−Aβ↑ Aβ fibrillizationExpression of chaperones in a specific lesion is illustrated as follows: present (+), by conflicting reports (±), absence (−), and unknown (?); ↓ = inhibition or down-regulation, ↑ = induction or up-regulationSP Senile plaques, CAA cerebral amyloid angiopathy, NFT neurofibrillary tangles, HSPGs heparan sulphate proteoglycans, Aβ amyloid-beta, Hsp heat shock proteins, Apo apolipoproteins, SAP serum amyloid P, tPA tissue-type plasminogen activator, GAGs glycosaminoglycans, LDLR low-density lipoprotein receptor, LRP-1 LDL receptor protein-1, BBB blood–brain barrier
Aβ-Binding Proteins and Aβ Clearance
Aβ-binding proteins, amateur chaperones, play a role in the clearance of Aβ from brain by functioning as a transporter molecule. Two major pathways govern Aβ clearance. By the first pathway, Aβ is removed from brain to blood via active transport across the BBB. This active transport is performed by specialized transporters, so-called “Aβ-receptors”, expressed by endothelial cells. Second, Aβ is removed from brain via phagocytosis by both microglial cells and astrocytes. In both pathways, interaction of Aβ with cell surface Aβ-receptors is crucial; therefore, the expression levels of Aβ-binding proteins might contribute to Aβ clearance by regulating its binding with Aβ receptors.
The low-density lipoprotein receptor-related protein-1 (LRP-1) binds Aβ in a complex with ApoE at the abluminal side of the endothelium and internalizes these ApoE/Aβ complexes followed by degradation in lysosomes or transport into the plasma [4, 175]. However, LRP-1 also mediates transport of free Aβ across the BBB [10]. In contrast to LRP-1, the receptor for advanced glycation end products (RAGE) transports Aβ from the circulation into the central nervous system [176]. Similar to RAGE, the Aβ receptor megalin is also involved in the transport of Aβ from blood to brain, although megalin probably plays only a minor role in Aβ transport. Furthermore, megalin binds Aβ/ApoE complexes rather than free Aβ [177, 178]. Clearance of Aβ/ApoE complexes from brain might be ApoE isoform-dependent. ApoE4 forms less stable complexes with Aβ than ApoE3 or ApoE2; therefore, ApoE4 reduces Aβ transport efficiency across the BBB. Additionally, as described above (paragraph 2), ApoE4 enhances Aβ aggregation more efficiently than ApoE3, which also inhibits clearance. On the other hand, the LDL receptor shows a marked preference for the ApoE3 and ApoE4 isoforms and binds the ApoE2 isoform poorly [179]. Given the similarity between the LDL receptor family, other LDL receptors, such as the LRP-1 receptor, might display similar specificities towards the ApoE isoforms, but this has not been reported yet. Moreover, lipidation of ApoE also affects clearance of ApoE and ApoE/Aβ complexes from brain, as LRP preferentially binds lipid-rich forms of ApoE [179]. These data indicate that Aβ-binding proteins, especially ApoE, and possibly, ApoJ, play an important role in transport of Aβ across the BBB and that both the ApoE isoform and the ApoE lipidation state affect Aβ clearance. In addition to ApoE and ApoJ, the Aβ-binding protein α2M also forms complexes with Aβ. As α2M is a ligand for LRP-1, these α2M/Aβ complexes might undergo LRP-1-mediated endocytosis and degradation or translocation into the plasma [7, 139].
Stimulation of the transport of Aβ across the BBB demonstrated to be an effective therapeutic approach in AD, as several studies demonstrated elevated levels of Aβ in the plasma of mice after passive immunization with anti-Aβ antibodies or Fab fragments [180–182], and decline in cognitive performance was arrested in patients that received vaccination [183]. However, the occurrence of severe meningoencephalitis in human patients after active immunization with Aβ hampered widespread application of this type of therapy. Administration of Aβ-binding proteins that demonstrate similar positive effects, but possibly, without the severe immune reactions associated with antibody therapy, might provide an alternative strategy. An interesting example of such an Aβ-binding protein is gelsolin. This protein has high affinity for Aβ and reduces Aβ levels in a transgenic mouse model of AD [184]. Furthermore, administration of gelsolin or GM1 in PS/APP mice resulted in decreased Aβ aggregation in the brains [184]. Both gelsolin and GM1 act as a “peripheral sink” for Aβ. Although both compounds did not enter the brain, they lowered soluble Aβ concentrations in the blood, shifted the balance between blood and cerebral Aβ concentrations, and accordingly, stimulated Aβ transport over the BBB. Therefore, other Aβ-binding proteins administered in the circulation might also act as “peripheral sinks” [181, 184].
Both activated microglial cells and activated astrocytes are associated with Aβ deposition and may internalize Aβ fragments via phagocytosis [185–187]. Activation of the complement system is, among others, achieved by Hsps such as Hsp60 and Hsp70, which are able to induce phagocytosis by microglia, and thus, clearance of Aβ [132, 188, 189]. In addition, the absence of ApoE reduces internalization and degradation of Aβ by astrocytes in the brain, demonstrating that ApoE is directly involved in the clearance of Aβ from brain via phagocytosis by microglial cells and astrocytes [40]. tPA might also contribute to clearance of Aβ, as it accelerates Aβ clearance from transgenic mouse brains [146]. Thus, as Aβ-chaperones contribute to activation of the complement system or activation of microglial cells and astrocytes, these proteins might contribute to the clearance of Aβ from the brain via phagocytosis.
Concluding Remarks
Professional chaperones, such as the heat shock protein family, and amateur chaperones, such as apolipoproteins and HSPGs and several other proteins, have a role in the intracellular handling of misfolded proteins, induce conformational changes of proteins, or act as transporter of proteins (Fig. 2). This suggests that these chaperones form interesting therapeutic targets in the prevention and treatment of neurodegenerative diseases.
Fig. 2The putative role of chaperones in amyloid-β (Aβ) fibril formation, proteolytic breakdown, and clearance from the brain. In Alzheimer’s disease, soluble Aβ, predominantly produced in neurons, is converted into β-sheet rich protofibrils and eventually forms mature Aβ fibrils. The conversion from soluble Aβ to protofibrils and fibrils, which accumulate in senile plaques and cerebral amyloid angiopathy, is enhanced by chaperones as apolipoprotein E (ApoE), Gelsolin, α1-antichymotrypsin (ACT) and several heparan sulphate proteoglycans (HSPGs), which function as catalysts. In contrast, the heat shock protein family, tissue-type plasminogen activator (tPA) and complement factors prevent the transition of soluble Aβ into protofibrils and mature fibrils. Furthermore, heat shock proteins and tPA stimulate the proteolytic breakdown of (proto)fibrils, whereas HSPGs prevent this breakdown. Finally, the clearance of Aβ from the brain across the blood–brain barrier is stimulated by ApoE, ApoJ, and α2-macroglobulin (α2M), whereas complement factors stimulate phagocytosis-mediated clearance of Aβ by activated microglia and astrocytes
In the process of clearance of Aβ from the brain, Aβ-binding partners might play important roles by acting as Aβ transporter proteins in both the receptor-mediated clearance of Aβ across the BBB but also as a “peripheral sink” for Aβ. Both ApoE isotype and local concentrations in the brain might regulate Aβ transport across the BBB, but as this transport is receptor-mediated, other Aβ-binding proteins might also fulfill such a role. In addition, transport of aggregated Aβ across the BBB is less efficient than soluble Aβ. Thus, by preventing self-aggregation of Aβ, Aβ-binding proteins contribute to the clearance of Aβ from the brain. As a therapeutic strategy, Aβ-binding proteins serving as a “peripheral sink”, such as gelsolin, seem promising [184].
Overexpression of professional chaperones, such as the Hsps, to prevent aggregation of misfolded proteins will have to be evaluated carefully, as they also interact with other chaperones and are dependent on this interaction to fulfill some of their functions. This strategy may therefore result in instability of the cell-stress mechanism, which may cause the system to collapse. A solution may be found in the overexpression of several chaperones, which may be required to achieve an impact on the progression of the disease.
Another pitfall in the use of professional chaperones as therapeutic agents is their ability to bind misfolded proteins and keep them in an intermediate conformation. This type of conformation might even be more toxic than the aggregated state. As an example, co-incubations of αB-cystallin with Aβ are more toxic to neurons than Aβ alone [121]. Furthermore, Hsps are most likely to be involved in early development of neurodegenerative diseases, given their natural function. Yet, the role of this protein family in maturation of the neurodegenerative lesions remains to be elucidated.
In conclusion, studying the role of chaperones, both professional and amateur, in the pathophysiology of AD will provide us with a better understanding of the mechanisms underlying the formation and accumulation of toxic aggregates in AD, which, eventually, will lead to the design of more effective therapeutic strategies.

heat shock proteins
chaperones
amyloid
alzheimer’s disease
apolipoproteins
heparan sulfate proteoglycans
amyloid beta-protein


Evaluation of patients’ experiences with antidepressants reported by means of a medicine reporting system

Objective To assess experiences related to antidepressant use reported to an internet-based medicine reporting system and to compare the nature of the side effects reported by patients with those reported by health care professionals (HCPs).
Introduction
Non-adherence to prescribed medication regimens is a persistent problem in the treatment of depression with antidepressants. Premature discontinuation, dosing lapses and partial non-adherence often occur [1–3]. The illness itself as well as physician-, patient- and treatment-related factors have been suggested to contribute to antidepressant non-adherence, but the ability of health care professionals (HCP) to predict who discontinues medication remains poor [4–6]. Earlier studies provide scant information on how patients in clinical practice perceive their treatment with antidepressants, thus insight and an understanding of the patients’ perspectives on non-adherence and discontinuation are limited. Side effects and ineffectiveness are the major reasons cited for the discontinuation of antidepressant therapy [7, 8]. However, the information available on side effects is mostly based on controlled clinical trials, which standardly do not evaluate how bothersome side effects are to the individual patient. Moreover, both the side effects and the effectiveness of the antidepressant therapy observed in clinical trials may not reflect the experiences of the patients in real world settings. Many interventions have been developed to improve adherence to antidepressants, but to date these have failed to demonstrate a clear benefit [9, 10]. Treatment non-adherence remains one of the least understood health-related behaviours. Information received directly from the patient may improve our understanding of the relative importance of antidepressant treatment issues and, consequently, help to explain patients’ behaviour towards antidepressant use.
Reporting systems have shown to be a useful tool in collecting experiences and identifying issues related to the daily use of medicines [11]. In 2004, an internet-based medicine reporting system was established in The Netherlands where users of medicines are able to report all types of experiences with medicines – side effects as well as experiences with effectiveness and practical and reimbursement issues. We extracted data from this medicine reporting system in order to (1) assess the type of experiences related to antidepressant use reported by patients, (2) assess the relevance of these experiences and (3) compare the nature of the suspected side effects reported by patients with those reported by HCPs.
Methods
Setting
Reports were obtained from an internet-based medicine reporting system launched on 11 May 2004 in The Netherlands. This reporting system was initiated by DGV, The Dutch Institute for the Proper Use of Medicine, the Science Shop for Medicines and patient and consumer organisations. Individuals are able to report their experiences with medicines anonymously by completing a report form downloaded by accessing a website (http://www.meldpuntmedicijnen.nl). Users of the medicine themselves as well as their relatives, acquaintances or (professional) carers, can report an experience. All reports submitted between 11 May 2004 and 13 May 2005 related to the use of antidepressants were reviewed for the clarity and completeness of the description of the experience and checked for multiple reports from the same IP-address. One duplicate report had to be excluded. All other reports were included in the study. The data were stored in an Access database.
Report form
The report form contained items which requested information on age, gender, type of medicine used, nature of the experience, a description of the experience and the relevance of the experience. Individuals filling in the report had to indicate whether the experience was related to either effectiveness, a side effect, a practical issue (e.g. difficulties with swallowing tablets) or a reimbursement issue. More than one experience related to the same drug could be submitted. Experiences related to effectiveness had to be further specified by the individual by selecting one of the following categories: ineffectiveness, a positive effect or a different type of effect (e.g. drug interactions). Experiences related to side effects had to be further specified by selecting one of the following categories: negative side effects, positive side effects (e.g. less side effects as compared with previous medication) or the absence of side effects. Relevance of the experience was assessed by asking the individual filling in the report to indicate both the impact of the experience on a 5-point scale (ranging from very negative to very positive) and whether the experience caused a change in antidepressant use. To specify the change in antidepressant use, those reporting had to select one of the following categories: discontinuation, switching to other treatment, adjustment of dosage or administration, any other action taken or no action taken. In the case of discontinuation of the antidepressant, the report also asked whether the HCP has been informed.
Side effects
All reported side effects (including experiences on ineffectiveness) were coded by one of the authors (SvdW) and checked by a second author (EvG), using preferred terms of the World Health Organisation Adverse Reaction Terminology (WHO-ART) [12]. Preferred terms were combined into groups of similar side effects. Spontaneous reports of adverse drug reactions on antidepressants received from HCPs from May 2004 to May 2005 were included for comparison. These reports were received by The Netherlands Pharmacovigilance Centre Lareb either on paper forms or electronically via http://www.lareb.nl. Coding and assessment were carried out by qualified assessors from Lareb [13].
Data analysis
The relevance of the side effects was assessed by comparing the impact of the (grouped) side effects as a proportion of the side effects that were perceived as “very negative”. Relevance was also assessed by comparing the proportion of the side effects that caused discontinuation of initial antidepressant use, including the categories “discontinuation” and “switching to other treatment”. The impact and discontinuation proportions of the different groups of side effects were compared using the chi-square test.
For the comparison between patients and HCPs, the groups of side effects were compared and expressed as an Odds Ratio (OR) and 95% confidence interval (CI). The 15 most frequently reported (groups of) side effects by patients as well as the 15 most frequently reported (groups of) side effects by HCPs were included in the analysis.
Results
Characteristics
In total 2232 individuals submitted a report to the medicine reporting system during the study period, of whom 258 (12%) submitted a report on antidepressants. Of these 258 individuals, 248 (96%) reported for themselves and ten reported for a relative or acquaintance.
The mean (±SD) age of the of the antidepressant users was 42.8 (±13.5) years and 72% were female. The majority of those reporting on antidepressants (63%) were reporting on a serotonin-reuptake inhibitor (SSRI); 12% were reporting on a tricyclic antidepressant (TCA) and 25% on another type of antidepressant. The antidepressants most frequently reported on were paroxetine (35% of total), venlafaxine (15%), citalopram (10%) and mirtazapine (8%). The use of a benzodiazepine as a concomitant drug was reported by 19% of those reporting on antidepressant use.
Nature of experiences
The 258 individuals reporting on antidepressant use described 327 experiences. Table 1 shows the nature of the experiences described. Ninety-two individuals (36%) described an experience with effectiveness, of whom 40 (16%) described an experience with ineffectiveness. Four individuals claimed generic substitution as the reason for ineffectiveness, and 45 (17%) reported a positive experience with the effectiveness of an antidepressant. “Other type of effects” in terms of effectiveness that were submitted by seven (3%) individuals included experiences on suspected drug interactions.
Table 1Nature of the reported experiences related to antidepressant use reported to a medicine reporting system (http://www.meldpuntmedicijnen.nl)aIssueProportion of total number of individuals (n = 258) reporting on antidepressant useNature of issueProportion individuals reporting on a specific issueEffectiveness36% (n = 92)Ineffectiveness16% (n = 40)Positive effect17% (n = 45)Other3% (n = 7)Side effects84% (n = 217)Negative side effect78% (n = 202)Positive side effect1% (n = 3)Absence of side effect5% (n = 12)Practical issues5% (n = 14)Reimbursement and availability issues2% (n = 4)aA total of 258 reporters submitted 327 experiences. The reported experiences are expressed as a percentage of the total number of individuals submitting reports
In total, 217 of the 258 individuals (84%) reporting on antidepressant use submitted a report on side effects. Of these, 202 (78%) described a total of 630 side effects that were experienced as negative. The number of reported side effects ranged from 1 to 11 per reporter experiencing a negative side effect. Twelve individuals (5%) reported that they had not experienced any side effect at all, and three (1%) submitted a positive experience with side effects, reporting that their current antidepressant therapy caused fewer side effects than their previous medication.
Fourteen individuals (5%) reported a practical issue (such as problems with swallowing tablets or bad taste), and four (2%) reported a reimbursement or availability issue (receiving treatment for a relative short duration).
Box 1 shows a number of the reported experiences.
Relevance of side effects
Table 2 shows the relevance, impact and discontinuation rates of the most frequently reported side effects. Of all side effects, 48% resulted in discontinuation of the initial antidepressant therapy. The proportion of side effects that caused discontinuation of the initial antidepressant did not differ significantly between the different side effects. Of those individuals who simultaneously reported an experience on side effects and one on ineffectiveness, 59% (17/29) reported that their experience resulted in discontinuation of the initial antidepressant therapy. Of all individuals who reported discontinuation of therapy, 29% did not inform their HCP.
Table 2Relevance of the most frequently reported side effects related to antidepressant useSide effectNumber of reported experiences (n)Impact (% perceived as “very negative”)Discontinuation of antidepressant use (%)Sleep disorder684750 Somnolence, drowsiness, fatigue395159 Insomnia, sleeplessness294138Weight increase484656Sexual problems434433Discontinuation symptoms404350Ineffectiveness403553Apathy284654Excessive sweating234339Nausea, gagging233930Dizziness, fainting236535Headache226850Dry mouth185061Suicidal attempt, thought or tendencya97878aSuicidal attempts, thoughts or tendency is also included, although the number of reported experiences was less than 15.
Of all side effects, 52% were perceived as “very negative”. The impact of the side effects differed almost significantly between the groups of side effects (p = 0.052), with headache, dizziness and fainting perceived as most negative.
Side effects compared between patients and HCPs
Table 3 presents those side effects most frequently reported by patients and HCPs. Patients and HCPs differed in the nature of reported side effects. Compared with HCPs, patients reported significantly more events such as apathy, excessive sweating, ineffectiveness, discontinuation symptoms, somnolence, insomnia, sexual problems and weight increase. HCPs reported significantly more rash, pruritis, laboratory abnormalities, muscle and joint complaints, congenital disorders, eye disorders, extrapyramidal disorders and menstrual disorders than patients.
Table 3Reported side effects on antidepressants by patients compared with reported side effects on antidepressants by health care professionals (HCPs)Side effectNumber of reported side effects by patientsPercentage of total number of side effects (n = 670)Number of reported side effects by HCPsPercentage of total number of side effects (n = 471)Odds ratio (95% CI)aTop 15 most frequently reported side effects by patients  Weight increase487.261.35.98 (2.54–14.09)  Sexual problems436.461.35.31 (2.24–12.59)  Discontinuation symptoms406.030.614.14 (4.35–45.93)  Ineffectiveness406.030.614.14 (4.35–45.93)  Somnolence, drowsiness, fatigue395.881.73.58 (1.66–7.73)  Insomnia, sleeplessness294.340.85.28 (1.84–15.13)  Apathy284.200–  Excessive sweating233.400–  Nausea, gaggingb233.481.72.05 (0.91–4.64)  Dizziness, faintingb233.481.72.05 (0.91–4.64)  Headacheb223.3112.31.42 (0.68–2.96)  Dry mouth182.730.64.31 (1.26–14.71)  Abdominal pain142.130.63.33 (0.95–11.65)  Anxiety131.920.44.64 (1.04–20.66)  Depressed mood111.630.62.60 (0.72–9.39)Top 15 most frequently reported side effects by HCPs  Rash, urticaria and pruritis30.4234.90.09 (0.03–0.29)  Laboratory abnormalities00224.7–  Muscle and joint complaints30.4204.20.10 (0.03–0.34)  Congenital disorders00153.2–  Eye and vision disorders60.9153.20.27 (0.11–0.71)  Paraesthesia81.2122.50.46 (0.19–1.14)  Headacheb223.3112.31.42 (0.68–2.96)  Extrapyramidal disorders, Parkinsonism10.1102.10.07 (0.01–0.54)  Menstrual disorders, vaginal bleedings30.4102.10.21 (0.06–0.76)   Heart rhythm problems71.0102.10.49 (0.18–1.29)  Convulsions, epilepsy0091.9–  Drug substitution problems71.081.70.61 (0.22–1.70)  Serotonin syndrome0081.7–  Nausea, gaggingb233.481.72.06 (0.91–4.64)  Dizziness, faintingb233.481.72.06 (0.91–4.64)95% CI, 95% confidence intervalaOR > 1: Patients were more likely to report the side effect than the HCPs; OR < 1: HCPs were more likely to report the side effect than the patientsbSide effects that appear in both the patients’ and HCPs’ list
Discussion
Both side effects and a lack of effectiveness appear to be important treatment issues for patients who reported on antidepressants in our study. Most of the individuals reporting on antidepressant use described one or more side effects, of which the most frequent were weight increase, sexual problems, somnolence, insomnia and apathy. Ineffectiveness was also reported by a considerable number of individuals. Ineffectiveness is not often reported in literature as an adverse effect of treatment [14]. However, our study reveals that it is a relevant issue for patients during antidepressant therapy. The fact that side effects tend to occur before the therapeutic effect of the antidepressant is perceived may play an important part in explaining early discontinuation of the therapy. Ineffectiveness should therefore receive attention from HCPs in order to prevent early discontinuation of antidepressants.
One of the unique features of this medicine reporting system is the possibility to gather information on the relevance of the experiences – that is the impact of the experience and the change in initial treatment. Overall, half of the experiences were perceived as very negative. Experience of one or more bothersome side effects means an individual is threefold more likely to stop taking antidepressants [7]. Our results show that one half of the side effects resulted in discontinuation of the initial antidepressant therapy. Moreover, of all those individuals who reported discontinuation of therapy, 29% did not even inform their HCP. This supports the concept that this medicine reporting system provides data of which HCPs are often not aware, but which are of crucial importance to any understanding of patients’ behaviour related to the use of antidepressants.
Patients and HCPs differed in the nature of the side effects reported. Patients were found to report more frequently those events which may be less tangible and visible to HCPs, such as sleeping problems and apathy. In addition, HCPs may consider symptoms reported by patients with psychiatric disorders as a symptom of the disease rather than as one related to the medication. Other notable differences between patients and HCPs in terms of the frequency of reported side effects were those of weight increase, sexual problems, discontinuation symptoms and excessive sweating. The differences in the nature of the reported side effects show that patients and HCPs differ in which type of side effects can be considered to be bothersome and/or relevant to report. The burden of side effects is clearly underestimated by HCPs [15]. Although HCPs are knowledgeable on the side effects related to SSRI use, they underestimate the frequency of these side effects and how bothersome they are to patients [16]. In addition, HCPs may be reticent in reporting a side effect to a reporting system. More than patients, HCPs evaluate the side effect reported by the patient according to perceived relevance and causality related to the medication. Side effects which are considered by the HCP as well-known or not related to the medication consequently get lost to the health care system [17].
Patient reporting is not yet widely accepted, and the number of systems collecting experiences from patients is still limited. In the UK, the Prescription-Event Monitoring (PEM) system seeks to identify adverse events recorded following the use of newly marketed drugs selected for monitoring on the first 20,000–50,000 patients given the new drug [18]. Since the middle of 2003, the Danish Medicines Agency and the Netherlands Pharmacovigilance Centre Lareb also accept reports on adverse drug reactions from patients [19]. In Sweden, the KILEN Consumer Institute for Medicines and Health started a consumer database in 1997 that collects experiences related mainly to dependence and side effects of benzodiazepine and antidepressant use [19]. However, these systems focus only on adverse events, while other aspects of medicine use, including experiences on ineffectiveness, practical and reimbursement issues, have also been shown to be relevant to patients.
A limitation of this internet-based reporting system is that the reporters are anonymous and, therefore, further contact and feedback are not possible. Consequently, a thorough assessment of causality between the side effect and the antidepressant was not always possible. The Netherlands Pharmacovigilance Centre Lareb, on the other hand, whose primary aim is the early detection of new adverse drug reactions, has the facilities to request further medical information by contacting the patient and/or his/her HCP [20]. However, we believe this does not detract from our conclusion. The individuals reporting through the internet-based reporting system proved to be capable of providing clear descriptions of their experiences and of balancing the benefits and burden of treatment. The patient experiences provide important information on how patients in clinical practice perceive treatment with antidepressants. Such patients experience sleep disorders, weight increase, sexual problems, apathy and ineffectiveness as events which have a negative impact and which frequently lead to discontinuation of the antidepressant therapy. Because adherence decisions are mostly a rational balance of perceived benefits versus burden [21], an assessment of patient experiences may improve the understanding of patients’ behaviour towards antidepressant use. This information can be used in the development of more targeted adherence-enhancing strategies that may lead to optimisation of antidepressant treatment from the perspective of both HCPs and patients.

antidepressants
discontinuation
patient reporting
adverse events


Differential expression of HOX genes upon activation of leukocyte sub-populations

The HOX genes are key determinants of cellular identity both in early development and in the renewal and differentiation of adult blood cells. Although a number of studies have examined the expression of individual HOX genes in defined blood cell lineages, we have undertaken a comprehensive analysis of HOX gene expression in resting and activated lymphocytic and monocytic subpopulations. This has revealed distinct patterns of expression between different cell types and resting and activated states. (Main category A: Erythrocytes, Leukocytes and Hematopoiesis, subcategory: 8: Lymphocytes).
Introduction
The HOX genes are a family of homeodomain-containing transcription factors that define specific positional identities, both in vertebrate and invertebrate embryos [4]. They are also involved in the regulation of haemopoiesis (reviewed by [13]), and blocking HOX gene function by the use of antisense oligos or gene knock out perturbs a number of different haemopoietic events. Thus for example myeloid, erythroid and lymphoid haemopoiesis are all defective in HoxA9 knock out mice [8], and the antisense ablation of HoxB5, HoxB6, HoxB7 [15], or HoxA5 [5] blocks erythroid differentiation. Forced expression of HOXA10 in CD34+ progenitor cells purified from cord blood results in a significant reduction in the number of B cells and natural killer cells but a marked increase in monocytes [14]. There are also examples of specific regulatory functions for HOX genes, including the modulation of globin transcription by HOXB6 [12]. In addition, HOX genes can also act to regulate the proliferation of haemopoietic stem cells (HSCs). Hence HOXB4 is a strong, positive regulator of HSC self renewal (reviewed by [10]), and an estrogen-dependant version of HOXB8 can be used to drive the production of neutrophils and macrophages from their respective progenitor cells [16].
Despite these studies, relatively little is still known about the expression of HOX genes in the mature blood lineages (reviewed by [6]). In order to address this we purified different cell populations from human peripheral blood on the basis of their expression of the surface markers CD4, CD8, CD14 and CD19 that are present on T-lymphocytes (CD4 and CD8), monocytes, and B-lymphocytes respectively. HOX expression was compared in ‘resting’ cells and cells that had been activated by challenging with specific antigenic stimuli—antibodies against CD2, CD3 and CD28 for CD4+ and CD8+ cells, Lipopolysaccharide for CD14+ cells and anti-IgG for CD19+ cells. Each population of cells underwent proliferation in response to this treatment, as measured by [3H]thymidine incorporation (Fig. 1). RNA was extracted from each cell type and the expression of each of the 39 HOX genes was assed by quantitative PCR (QPCR), relative to the amount of Beta-actin transcript present (Fig. 2).
Fig. 1Proliferation of activated lymphocyte populations. Proliferation was measured by [3H]thymidine incorporation 4 h after activation. Values shown are the fold increase in incorporation compared to resting cells. Error bars: SEM from triplicate experimentsFig. 2HOX gene expression in resting (a) and activated (b) after 6 h, (c) after 24 h) lymphocytic and monocytic populations. Expression was assessed by quantitative PCR and is shown as a relative value to the number of beta-actin transcripts (‘Relative expression’). HOX genes are abbreviated to show only their family and paralogue position, hence HOXA2 is shown as ‘A2’. HOX genes for which no expression was detected are not shown in the figure. Each value shown is the mean from three experiments. Significant changes in expression levels (p < 0.05) 6 and 24 h after activation are marked (*). Error bars: SEM
The highest level of expression is generally shown by the HOXA and HOXC genes, with HOXD genes generally exhibiting a tenfold lower expression level and HOXB genes a 100 fold lower expression level, a feature that is also true for the other cell populations examined. For all of the HOX genes expressed in CD4+ cells there is a significant reduction in HOX expression upon activation. This is particularly striking for the most posterior genes of the HOXA, HOXC and HOXD clusters. A similar pattern is also observed in CD8+ cells, although there is a general reduction in HOX expression with every HOX gene except HOXC10 being present at lower levels in these cells.
There are a number of notable differences between the HOX expression profile of CD14+ cells and the CD4+/CD8+ populations. HOXC4, HOXC6 and HOXC8 are not expressed. The most striking difference though is the change of HOX expression upon activation—in contrast to CD4+/CD8+ cells, CD14+ cells show a large increase in HOXA2, HOXB13, HOXC10, HOXC13, HOXD1 and HOXD9. Other HOX genes such as HOXB4 and HOXA10 show no significant change in expression upon activation, which again contrasts with the response of CD4+/CD8+ cells.
CD19+ cells show a broadly similar pattern of HOX expression to CD14+ cells prior to activation, but have a distinct response to activation. Like CD4+/CD8+ cells, CD19+ cells exhibit a large reduction in expression of most HOX genes with the exception of HOXD10, HOXD11 and HOXD12 that show a very strong increase in expression upon activation.
To our knowledge this is the first comprehensive analysis of HOX gene expression in these leukocyte populations. Taking the data as a whole, each population shows a unique pattern of HOX expression that may define cellular identity. Generally the expression levels are in agreement with those previously reported for individual HOX genes in other studies [6, 7, 9]. However the changes of HOX gene expression upon cellular activation have not previously been reported. The magnitude of these changes is striking, with the activated T cell subsets exhibiting an almost complete loss of expression of many HOX genes especially the more posterior members of the groups (HOXA10, HOXC13, and HOXD12). Conversely, activated monocytic and B-lymphocyte cells show a large increase in expression of the same genes. Given the key regulatory roles of HOX genes it is likely that these changes in expression facilitate the cellular changes associated with activation. One of these is increased proliferation, a response that is known to be mediated by HOX genes in a number of hematopoietic lineages (reviewed by [1]). Indeed the antisense mediated ablation of HOXB2 or HOXB4 in T-lymphocytes was previously shown to block the proliferation of activated cells (Care et al. 1995). Furthermore HOXA10 deficiency causes a severe immunological disturbance in uterine tissues characterised by rapid T cell proliferation and a failure of progesterone-mediated immunosuppression [17]. The HOX genes are also likely to regulate lineage-specific transcription upon activation, and in this context the contrasting expression levels of these genes presumably reflect the dramatically different response of each cell type.
Materials and methods
CD4+, CD8+, CD14+ and CD19+ cells were isolated using the Dynabead system (Invitrogen) and cultured as previously described [2]. Quantitative PCR was performed as previously described [11]. [3H]thymidine incorporation was evaluated by a standard procedure. Briefly, 2 μCi of [3H]thymidine (20 Ci/mmol) was added for 4 h to each well. Cells were then recovered, washed, and processed for the determination of TCA precipitable radioactivity. Each evaluation was performed in triplicate. T cell activation was achieved using anti-CD2, anti-CD3 and anti-CD28 antibodies as supplied in the T cell activation/expansion kit (Miltenyi Biotec).

hox activation monocytes t-lymphocytes b-lymphocytes