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Posts Tagged ‘Transthyretin (TTR)’


Alzheimer’s disease, snake venome, amyloid and transthyretin

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Significant points:

  • Alzheimer’s Disease is characterized by amyloid plaques
  • The plaques have amyloid beta and tau
  • Toxic proteins accumulate in AD
  • snake venome activates enzymes (Endothelin Converting Enzyme-1 and Neprilysin) that break down the plaques that are sufficient in non-AD brain
  • Aβ peptides derive from proteolytic processing of a large (695/770 amino acids) type 1 transmembrane glycoprotein known as amyloid beta precursor protein (APP)
  • a natural variant of Amyloid-β (Aβ) carrying the A2V substitution protects heterozygous carriers from AD by its ability to interact with wild-type Aβ, hindering conformational changes and assembly
  • aggregated Aβ species, particularly oligomeric assemblies, trigger a cascade of events that lead to hyperphosphorylation, misfolding and assembly of the tau protein with formation of neurofibrillary tangles
  • [Aβ1-6A2VTAT(D)] revealed strong anti-amyloidogenic effects in vitro and protected human neuroblastoma cells from Aβ toxicity
  • while both Aβ1-6A2V and Aβ1-6WT display a predominant coil configuration, Aβ1-6A2V shows a slightly higher propensity to form secondary structure motifs involving two to three residues
  • Aβ1-6A2VTAT(D) maintains the in vitro anti-amyloidogenic properties of Aβ1-6A2V(D)
  • Transthyretin (TTR) influences plasma Aβ by reducing its levels
  • Transthyretin (TTR) binds Aβ peptide, preventing its deposition and toxicity
  • TTR facilitated peptide internalization of Aβ1-42 uptake by primary hepatocytes
  • Brain permeability to TTR
  • TTR regulates LRP1 levels, suggesting that TTR uses this receptor to promote Aβ clearance

 

Snake venom may hold key to breaking down plaques that cause Alzheimer’s disease

March 2, 2016  http://medicalxpress.com/news/2016-03-snake-venom-key-plaques-alzheimer.html

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4750079/bin/srep20949-f2.jpg

http://www.ncbi.nlm.nih.gov/pmc/articles/instance/4750079/bin/srep20949-f2.jpg

Alzheimer’s disease, snake venome, amyloid and transthyretin

 

Snake venom may hold key to breaking down plaques that cause Alzheimer’s disease

http://img.medicalxpress.com/newman/csz/news/800/2016/snakevenomma.jpg

A toxic protein called amyloid beta is thought to play a key role in the onset of Alzheimer’s disease. In healthy people, amyloid beta is degraded by enzymes as it forms. However, in patients with the disease, these enzymes appear unable to adequately perform their actions, causing the toxic protein to accumulate into plaque deposits, which many researchers consider leads to dementia.

One of the Holy Grails of the pharmaceutical industry has been to find a drug that stimulates these enzymes in people, particularly those who are in the early stages of dementia, when amyloid plaques are just starting to accumulate.

Monash researchers have discovered what could well be this elusive drug candidate– a molecule in snake venom that appears to activate the enzymes involved in breaking down the amyloid plaques in the brain that are the hallmark of Alzheimer’s disease. Dr Sanjaya Kuruppu and Professor Ian Smith from Monash University’s Biomedicine Discovery Institute have just published their research in Nature Scientific Reports.

Dr Kuruppu has spent most of his research life studying snake venoms, looking for drug candidates.  When he began researching Alzheimer’s disease he says that “snake venom was an obvious place for me to start.”

He was looking for a molecule that would stimulate the enzymes to break down the amyloid plaques.  What he found, when screening various snake venoms, was in fact one molecule with the ability to enhance the activity of two plaque degrading enzymes. This molecule was extracted from a venom of a pit viper found in South and Central America. Dr Kuruppu and his team have developed synthetic versions of this molecule. Initial tests done in the laboratory using human cells have shown it to have the same effects as the native version found in the snake venom.

Dr Kuruppu is one of the four researchers in Australia to receive funding from the National Foundation for Medical Research and Innovation to conduct further testing of this newly-identified molecule.

Explore further: Alzheimer protein’s structure may explain its toxicity

More information: A. Ian Smith et al. N-terminal domain of Bothrops asper Myotoxin II Enhances the Activity of Endothelin Converting Enzyme-1 and Neprilysin, Scientific Reports (2016).
http://dx.doi.org:/10.1038/srep22413

 

N-terminal domain of Bothrops asper Myotoxin II Enhances the Activity of Endothelin Converting Enzyme-1 and Neprilysin

  1. Ian Smith, Niwanthi W. Rajapakse, Oded Kleifeld, Bruno Lomonte,…, Helena C. Parkington, James C. Whisstock & Sanjaya Kuruppu

Scientific Reports 6, Article number: 22413 (2016)    http://www.nature.com/articles/srep22413

 

Neprilysin (NEP) and endothelin converting enzyme-1 (ECE-1) are two enzymes that degrade amyloid beta in the brain. Currently there are no molecules to stimulate the activity of these enzymes. Here we report, the discovery and characterisation of a peptide referred to as K49-P1-20, from the venom of Bothrops asper which directly enhances the activity of both ECE-1 and NEP. This is evidenced by a 2- and 5-fold increase in the Vmax of ECE-1 and NEP respectively. The K49-P1-20 concentration required to achieve 50% of maximal stimulation (AC50) of ECE-1 and NEP was 1.92 ± 0.07 and 1.33 ± 0.12 μM respectively. Using BLITZ biolayer interferometry we have shown that K49-P1-20 interacts directly with each enzyme. Intrinsic fluorescence of the enzymes change in the presence of K49-P1-20 suggesting a change in conformation. ECE-1 mediated reduction in the level of endogenous soluble amyloid beta 42 in cerebrospinal fluid is significantly higher in the presence of K49-P1-20 (31 ± 4% of initial) compared with enzyme alone (11 ± 5% of initial; N = 8, P = 0.005, unpaired t-test). K49-P1-20 could be an excellent research tool to study mechanism(s) of enzyme stimulation, and a potential novel drug lead in the fight against Alzheimer’s disease.

Metalloproteases play a central role in regulating many physiological processes and consequently abnormal activity of these enzymes contribute to a wide range of disease pathologies. These include cardiovascular1 and neurodegenerative disease2 as well as many types of cancers1. Inhibitors of metalloproteases are widely used in research applications with some also approved for use in the clinic. However, molecules which stimulate the activity of these enzymes are rarely encountered, and as such our understanding of the mechanism(s) behind enzyme stimulation remains poor. Stimulators of enzyme activity can provide novel insights into enzyme biology and potentially open up avenues for the design of a novel class of drugs. For instance, ECE-1 and NEP are two metalloproteases that degrade amyloid beta (Aβ), the accumulation of which is a hallmark of Alzheimer’s disease.

Therefore it is of great interest to regulate the production of, and more importantly, the degradation of Aβ by stimulating the activity of these enzymes2. This in turn could reverse, prevent or at least halt the progression of Alzheimer’s disease.

Previous studies using animal models of Alzheimer’s disease have shown that increasing the expression of ECE3 and NEP4 through DNA based techniques can have beneficial effects. However, DNA based approaches can pose challenges for clinical translation. Molecules which can directly stimulate the activity of ECE-1 and NEP, or increase their expression are more attractive alternatives. Several studies have reported on the presence of molecules which increase the expression of or activity of NEP5,6,7. However, there are no reports on molecules which stimulate the activity of ECE-1. For example, polyphenols in green tea have been reported to increase the activity of NEP in cell culture models5, while the neuroprotective hormone humanin has been shown to increase the expression of NEP in a mouse model of Alzheimer’s disease6. In addition, Kynurenic acid elevates NEP expression as well as activity in human neuroblastoma cultures and mouse cortical neurones7. Therefore this study aimed to identify a molecule which stimulates the activity of ECE-1. Here we report on the discovery of K49-P1-20, a 20 amino acid peptide from the venom of B. asper which stimulates the activity of both ECE-1 and NEP. The effect of this peptide on other closely related enzymes was also examined.

Identification of K49-P1-20

We screened venom from species across different geographical regions for their effects on ECE-1 activity. The venom from B. asper was found to stimulate the activity of ECE-1 (624 ± 27% of control; Fig. 1a). Fractionation of venom confirmed that ECE-1 stimulation was mediated by the previously isolated B. aspermyotoxin II (Fig. 1a), a lysine 49 (K49) type phospholipase A2 found in this venom which induces myonecrosis upon envenoming8. Digestion of B. asper myotoxin II with ArgC proteinase indicated that the stimulation of ECE-1 activity was mediated by its N-terminal region (Fig. 1a). The synthetic peptide K49-P1-34 corresponding to the N-terminal region mimicked the stimulator effects of B. asper myotoxin II (Fig. 1a,b). No significant difference in the activation was observed between peptides K49-P1-20 and K49-P1-34 (Fig. 1a). However, the level of stimulation observed in the presence of K49-P9-34 and inverted sequence of K49-P1-20 was significantly less compared with native K49-P1-20 (Fig. 1a). Further digestion of peptide K49-P1-20 resulted in a reduction in its ability to stimulate ECE-1 activity (Fig. 1c) indicating the importance of residues 1-20 for maximal stimulation of ECE-1 activity. Peptide K49-P1-20 failed to inhibit direct twitches of the chick biventer cervicis nerve muscle preparation, confirming its lack of myotoxic effects (Fig. 1d), in agreement with the previous mapping of toxicity determinants of B. asper myotoxin II to its C-terminal region9.

Figure 1

Figure 1

 

Discovery of K49-P1-20 (a) Comparison of ECE-1 stimulating effects of venom, B. asper myotoxin II, peptides K49-P1-20, K49-P1-34, K49-P9-34 and inverted K49-P1-20 (10 ng/μL); (b) Schematic showing the amino acid sequence of B. asper myotoxin II (ArgC mediated cleavage sites are indicated by arrows). The underlined sections correspond to the sequence of synthetic peptides tested for their effects on ECE-1 activity; (c) trypsin mediated cleavage of K49-P1-20 produces peptides K49-P1-7 and K49-P8-20 (cleavage sites indicated by arrows, top panel); the effect of K49-P1-20, peptides K49-P1-7 and K49-P8-20 on ECE-1 activity (bottom panel); (d) a representative trace showing the effect of K49-P1-20 (25 μg/mL) on direct twitches of the chick biventer cervices muscle. The arrow indicates the point of addition of peptide. *Significantly different than ECE-1 + peptide K49-P1-20, P < 0.05, unpaired t-test, n = 48.

Alanine scan

Alanine substitution of Leu(2) and Ile(9) failed to enhance ECE-1 activity, indicating their importance for stimulating ECE-1 (Fig. 3). Alanine substitution of Leu(2), Phe(3), Glu(4), Leu(10), Glu(12), Thr(13), Lys(15), Lys(19) and Ser(20) failed to enhance NEP activity, indicating their importance for stimulating NEP (Fig. 3).

Figure 3: Alanine scan.

A library of K49-P1-20 analogs were synthesised where each subsequent residue was replaced by an Ala. These analogs were tested for their ability to stimulate ECE-1 and NEP activity. The K49-P1-20 analogs are shown in the middle, with the Ala substitutions indicated in red. Closed bar denotes enzyme alone and the native peptide is indicated in blue *significantly different compared to enzyme alone; P < 0.05; One-way ANOVA; n = 4.

K49-P1-20 and enzyme interaction and conformational changes

BLITZ Biolayer interferometry

N-terminal biotinylation of K49-P1-20 had no significant effect on its ability to stimulate ECE-1 activity (Fig. 4a). Interaction of ECE-1 and NEP with biotinylated K49-P1-20 immobilised on a streptavidin biosensor was indicated by an increase in response units (nm) over time (Fig. 4b). The interaction was rapidly reversible. There was only a minimal interaction between each of the enzymes and biotinylated version of inverted K49-P1-20.

 

Figure 4: Association between K49-P1-20 and enzymes.

Figure 4

Figure 4

(a) Effect of N-terminal biotinylation of K49-P1-20 on the activity of ECE-1. (b) Representative traces obtained using Biolayer interferometry showing the level of interaction between enzymes and the biotinylated version of native or inverted K49-P1-20; representative traces showing the effect of K49-P1-20 on the intrinsic fluorescence of (c) ECE-1 and (d) NEP. Fluorescence of K49-P1-20 alone, and the sum of fluorescence intensities of K49-P1-20 and enzyme is also indicated.

K49-P1-20 stimulates ECE-1 activity in cerebrospinal fluid

K49-P1-20 (1–30 ng/μL) stimulated the activity of rhECE-1 in cerebrospinal fluid obtained from a patient with Alzheimer’s disease, as evidenced by the enhanced cleavage of bradykinin based QFS (Fig. 7a). Addition of stimulated ECE-1 to cerebrospinal fluid obtained from patients with Alzheimer’s disease (N = 8) resulted in a significant decrease (31 ± 4%) in the levels of endogenous soluble Aβ42 over 4 h, compared with the addition of non-stimulated ECE-1 (11 ± 5%; P = 0.005, unpaired t-testFig. 7b). This decrease was blocked by the ECE-1 specific inhibitor CGS35066 (Fig. 7b).

Figure 7: K49-P1-20 stimulates ECE-1 activity in cerebrospinal fluid

Figure 7

(a) the effect of K49-P1-20 (1–30 ng/μL) on the activity of rhECE-1(0.04–ng/μL) added to cerebrospinal fluid obtained from a patient with Alzheimer’s disease at post mortem. Enzyme activity was measured using the bradykinin based QFS. * & α significantly different compared to ECE-1 alone or K49-P1-20 (1 ng/μL) respectively; P < 0.001; n = 5; one-way ANOVA. (b) The effect of ECE-1 alone (0.04 ng/μL); ECE-1 incubated with K49-P1-20 (300 ng/μL); or ECE-1+ K49-P1-20 + ECE-1 inhibitor CGS35066 (500 nM), on the levels of endogenous Aβ42 in cerebrospinal fluid taken from a patient with Alzheimer’s disease at post-mortem was determined using a commercially available ELISA kit. Significantly different compared to *ECE-1 alone P = 0.005; or **ECE-1 + K49-P1-20, P = 0.009; unpaired t-test, N = 8–11.

Discussion

ECE-1 and NEP are two closely related metalloproteases that play a key role in many physiological and pathophysiological processes2,15,16. A common substrate to both enzymes is Aβ which plays a key role in the pathogenesis of Alzheimer’s disease2,15,16,17,18. Previous studies have reported the discovery of molecules which increase NEP activity5,6,7. However, there are no reports on molecules that increase ECE-1 activity. Here we report on the discovery of a peptide named K49-P1-20 from the venom of B. asper which stimulates the activity of both ECE-1 and NEP. Interaction of K49-P1-20 with ECE-1 or NEP appears to induce a change in its conformation leading to an increase in activity. Unlike the molecules reported in previous studies which increase NEP expression and therefore cellular NEP activity5,6,7, K49-P1-20 appears to allosterically regulate the activity of ECE-1 and NEP.

Animal venoms have long been a source of lead compounds for future pharmaceuticals and research tools19,20. We therefore screened venoms of snakes found in different geographical regions to identify a molecule that modulates the activity of ECE-1, and found that the venom of B. asper stimulated ECE-1 activity. Initial fractionation of venom indicated that this effect was mediated by a toxin known as B. asper myotoxin II which induces myonecrosis following envenoming8. B. aspermyotoxin II belongs to a class of toxins known as Lysine 49 phospholipase A2 myotoxins21. Asp to Lys substitution at position 49 is a key structural feature of these toxins and their toxic effects are independent of the phospholipase A2 activity. Digestion of this toxin with ArgC proteinase indicated that stimulation of ECE-1 activity was mediated by its N-terminal domain. The use of synthetic peptides of varying length corresponding to this region confirmed that these effects were in fact mediated by its first 20 amino acids. Inverted sequence of K49-P1-20 failed to induce an increase in ECE-1 activity (136 ± 12 as % of ECE-1 alone; n = 3-4), indicating that the specific sequence of K49-P1-20 is critical for the observed effects. Further shortening of this peptide resulted in a loss of ECE-1 stimulating effects. K49-P1-20 therefore appears to possess the shortest optimum sequence required for ECE-1 stimulation and was used in all downstream studies. Previous studies have shown that myotoxic effects of B. asper myotoxin II are mediated by is C-terminal domain9. In agreement with this result, K49-P1-20 showed no myotoxicity in chick biventer cervicis muscle.

Compared with enzyme alone, K49-P1-20 also significantly enhanced the activity (expressed as % of control) of closely related enzyme NEP (1606 ± 29), and two other metalloproteases ACE-2 (145 ± 8) and IDE (292 ± 38). The level of ACE-2 and IDE stimulation was however significantly less compared with NEP, therefore indicating degree of specificity towards ECE-1 and NEP. All further studies therefore focused on the effect of K49-P1-20 on ECE-1 and NEP activity. K49-P1-20 increased the activity of ECE-1 and NEP in a concentration dependant manner. The increase in activity of both enzymes become evident at a K49-P1-20 concentration of 0.23 μM, or a peptide: enzyme molar ratio of 1:368. The high level of ECE-1 and NEP stimulation observed in response to K49-P1-20 is most likely the result of a common binding region for K49-P1-20 within these enzymes. ECE-1 and NEP in deed share 40% sequence homology22. However the potential sites of interaction between the enzymes and K49-P1-20 are best identified through structural biology approaches that take into account the secondary and tertiary structure of the enzymes.

Physical interaction between the activating molecule and enzyme is a common characteristic in the mechanisms of enzyme activation23. We used biolayer interferometry to probe possible physical interaction between K49-P1-20 and ECE-1 or NEP. N-terminal biotinylation of K49-P1-20 had no significant impact on its ability to stimulate ECE-1 activity, thus facilitating its use as a tool in research applications. Biotinylated K49-P1-20 immobilised on a streptavidin biosensor interacted directly with both ECE-1 and NEP as evidenced by the increase in response units over time. This interaction however was not observed with the biotinylated version of inverted K49-P1-20.

It is logical to assume that a conformational change that occurs following interaction with K49-P1-20 mediates the increase in enzyme activity. We investigated this by examining the effect of K49-P1-20 on the intrinsic fluorescence of ECE-1 and NEP. Fluorescence spectra of each enzyme in the presence of K49-P1-20 were distinct from that of enzyme alone. In addition, the sum of individual spectra for K49-P1-20 and ECE-1 or NEP failed to overlap with the spectra obtained by incubating K49-P1-20 with enzymes. This suggests that spectral changes that occur in the presence of K49-P1-20 is the likely result of a change in conformation of the enzymes, which in turn is a possible consequence of a direct interaction with K49-P1-20.

 

Tackling amyloidogenesis in Alzheimer’s disease with A2V variants of Amyloid-β

Giuseppe Di Fede, Marcella Catania, Emanuela Maderna, Michela Morbin,…,,Fabio Moda, Matteo Salvalaglio, Mario Salmona  & Fabrizio Tagliavini

Scientific Reports 6, Article number: 20949 (2016)  http://dx.doi.org:/10.1038/srep20949

 

We developed a novel therapeutic strategy for Alzheimer’s disease (AD) exploiting the properties of a natural variant of Amyloid-β (Aβ) carrying the A2V substitution, which protects heterozygous carriers from AD by its ability to interact with wild-type Aβ, hindering conformational changes and assembly thereof. As prototypic compound we designed a six-mer mutated peptide (Aβ1-6A2V), linked to the HIV-related TAT protein, which is widely used for brain delivery and cell membrane penetration of drugs. The resulting molecule [Aβ1-6A2VTAT(D)] revealed strong anti-amyloidogenic effects in vitro and protected human neuroblastoma cells from Aβ toxicity. Preclinical studies in AD mouse models showed that short-term treatment with Aβ1-6A2VTAT(D) inhibits Aβ aggregation and cerebral amyloid deposition, but a long treatment schedule unexpectedly increases amyloid burden, although preventing cognitive deterioration. Our data support the view that the AβA2V-based strategy can be successfully used for the development of treatments for AD, as suggested by the natural protection against the disease in human A2V heterozygous carriers. The undesirable outcome of the prolonged treatment with Aβ1-6A2VTAT(D) was likely due to the TAT intrinsic attitude to increase Aβ production, avidly bind amyloid and boost its seeding activity, warning against the use of the TAT carrier in the design of AD therapeutics.

Alzheimer’s disease (AD) is the most common form of dementia in the elderly. Its clinical course is slow but irreversible since no disease-modifying treatments are currently available. As a result, this illness has a huge socio-sanitary impact and designing of effective therapies is considered a public health priority.

A central pathological feature of AD is the accumulation of misfolded Amyloid-beta (Aβ) peptides in the form of oligomers and amyloid fibrils in the brain1,2,3. It has been advanced that aggregated Aβ species, particularly oligomeric assemblies, trigger a cascade of events that lead to hyperphosphorylation, misfolding and assembly of the tau protein with formation of neurofibrillary tangles and disruption of the neuronal cytoskeleton, widespread synaptic loss and neurodegeneration. According to this view, altered Aβ species are the primary cause of AD and the primary target for therapeutic intervention3,4.

Aβ peptides derive from proteolytic processing of a large (695/770 amino acids) type 1 transmembrane glycoprotein known as amyloid beta precursor protein (APP). APP is cleaved at the N-terminus of the Aβ domain by β-secretase, forming a large, soluble ectodomain (sAPPβ) and a 99-residue, membrane-retained C-terminal fragment (C99). Subsequently, γ-secretase cleaves C99 to release Aβ with different carboxyl termini, including Aβ40, Aβ42 and other minor species5. APP may undergo an alternative, non-amyloidogenic processing where the protein is cleaved within the Aβ domain by α-secretase, forming a soluble ectodomain (sAPPα) and an 83-residue C-terminal fragment (C83)5,6.

We identified a novel mutation in the APP gene resulting in A-to-V substitution at codon 673, corresponding to position 2 in the Aβ sequence7. Studies on biological samples from an A673V homozygous carrier, and cellular and C. elegans models indicated that this mutation shifts APP processing towards the amyloidogenic pathway with increased production of amyloidogenic peptides. Furthermore, the A2V substitution in the Aβ sequence (AβA2V) increases the propensity of the full-length peptides (i.e., Aβ1-40 and Aβ1-42) to adopt a β-sheet structure, boosts the formation of oligomers both in vitroand in vivo and enhances their neurotoxicity8,9,10. Following the observation that humans carrying the mutation in the heterozygous state do not develop AD, we carried out in vitro studies with synthetic peptides that revealed the extraordinary ability of AβA2V to interact with wild-type Aβ (AβWT), interfering with its nucleation or nucleation-dependent polymerization7. This provides grounds for developing a disease-modifying therapy for AD based on modified AβA2V peptides retaining the key functional properties of parental full-length AβA2V.

Following this approach, we generated a mutated six-mer peptide (Aβ1-6A2V), constructed entirely by D-amino acids [Aβ1-6A2V(D)] to increase its stability in vivo, whose interaction with full-length AβWT hinders oligomer production and prevents amyloid fibril formation8.

These results prompted us to develop a prototypic compound by linking Aβ1-6A2V(D) to an all-D form of TAT sequence [TAT(D)], a peptide derived from HIV that powerfully increases virus transmission to neighbour cells11, and is widely used for brain delivery of drugs12,13,14. Here we report that this compound [Aβ1-6A2VTAT(D)] has strong anti-amyloidogenic effects in vitro, leading to inhibition of oligomer, amyloid fibril formation and of Aβ-dependent neurotoxicity. Preclinical studies showed that a short-term treatment with this peptide in an AD mouse model prevents Aβ aggregation and amyloid deposition in the brain but longer treatment unexpectedly increases amyloid burden, most likely due to the TAT intrinsic attitude to enhance Aβ production and to avidly bind amyloid and boost its seeding activity, warning against the use of this carrier in therapeutic approaches for AD.

In silico molecular modeling of AβA2V peptide variants

To predict the structural basis of the anti-amyloidogenic effect of Aβ1-6A2V(D), a comparative conformation analysis of WT and mutated Aβ1-6 was carried out with all-atom classical MD simulations in explicit solvent. Both Aβ1-6WT and Aβ1-6A2V are intrinsically disordered peptides characterized by high flexibility. Nevertheless, the substitution of Ala2 with a Val residue induces significant changes in the appearance of the peptide in solution, resulting in an increase of the apolar character of the solvent accessible surface (SAS) (Fig. 1A) and in a modification of the gyration radius distribution in the Aβ1-6A2V. Figure 1B shows that the probability distribution of the gyration radius is characterized by a global shift to smaller values and by the appearance of a shoulder in the distribution corresponding to gyration radii of 0.5 nm.

Figure 1: Analysis of 1.5 μs explicit solvent MD simulations of the Aβ1-6WT and Aβ1-6A2V peptides.

An external file that holds a picture, illustration, etc. Object name is srep20949-f1.jpg

(A) Apolar character of the peptide SAS represented as the ratio between SASapolar and the total SAS. (B) Gyration radius distribution. (C) Analysis of secondary structure propensity. “Structure” indicates residues possessing a defined secondary structure, in this case structure indicates residues in a “turn” configuration. “Coil” indicates residues that do not display a defined secondary structure. Analysis of the secondary structure was carried out with DSSP. (D) Typical compact “turn” and elongated “coil” configurations reported for the Aβ1-6A2V and Aβ1-6WT, respectively. (E) Analysis of the most populated structural clusters. Representative structures of the six most probable clusters were reported. The coil configuration has been highlighted in green, the turn in red and a partly folded turn in orange.

An analysis of the secondary structure content displayed by the peptides (Fig. 1C) shows that, while both Aβ1-6A2Vand Aβ1-6WT display a predominant coil configuration, Aβ1-6A2V shows a slightly higher propensity to form secondary structure motifs involving two to three residues. Aβ1-6A2V in fact displays a propensity to form a turn involving the Glu3, Phe4 and Arg5 residues (Fig. 1D). The most populated structural clusters15 (Fig. 1E), in Aβ1-6WT are characterized by an elongated coil structure accounting for 52.6% of the configurations, while the compact “turn” state is only the third most probable cluster, with a population of around 9%. Conversely, in the Aβ1-6A2V, while the most populated structure is still an elongated coil (32%), the “turn” configuration is the second most populated structural cluster (31%).

Both Aβ1-6WT and Aβ1-6A2V under physiological conditions are characterized by intramolecular salt bridges such as those between Asp1 and Arg5 or Glu3-Arg5. In the extended coil configuration (Fig. 1E), salt bridges can be dynamically formed and dissociated without requiring a specific rearrangement of the peptide backbone. However, in the turn configuration salt bridges are typically dissociated; the interaction of the apolar Val2 sidechain with the Arg5 sidechain stabilizes such a dissociated state. The additional sterical hindrance to the rearrangement induced by the Val2 sidechain also contributes to the stabilization of the turn configuration of the A2V peptide.

The propensity of the A2V mutant to adopt a Glu3-Arg5 turn configuration characterized by a significant lifetime can be interpreted as the probable source of the heterotypic interaction of the Aβ1-6A2V with full-length Aβ, which results in hindering its assembly.

Aβ1-6A2V retains the in vitro anti-amyloidogenic features of the parental full-length peptide

 

We previously showed that Aβ1-6A2V(D) destabilizes the secondary structure of Aβ1-42WT8 and is even more effective than the WT peptide [Aβ1-6WT(D)] and the A2V-mutated L-isomer [Aβ1-6A2V(L)] at preventing the aggregation of full-length AβWT8.

Treatment of SH-SY5Y cells with Aβ1-6WT(D) or Aβ1-6A2V(D) showed that neither is toxic for living cells even at high concentrations (20 μM) (Fig. 2A,B) and that both peptides are able to reduce the toxicity induced by Aβ1-42WT (Fig. 2C,D). However, Aβ1-6A2V(D) showed a stronger effect in counteracting the reduction of cell viability caused by Aβ1-42WT (Fig. 2D), suggesting that the A-to-V substitution actually amplifies the protective effects of the six-mer peptide.

Figure 2: Analysis of the effects of Aβ1-6WT(D), Aβ1-6A2V(D) and Aβ1-6A2VTAT(D) on neurotoxicity in cell models.

SH-SY5Y cells were differentiated with 10 μM retinoic acid. After 6 days the proper peptide was added to culture medium and cell viability was assessed after 24 h by MTT test. (A,B) Neither Aβ1-6WT(D) nor Aβ1-6A2V(D) are significantly toxic when added to culture medium of differentiated SH-SY5Y cells. Conversely, Aβ1-42WT reduces cell viability by 35%. * Significance vs non-treated cells. (C,D) Both Aβ1-6WT(D) and Aβ1-6A2V(D) are able to counteract the toxic effect of Aβ1-42WT. Aβ1-6A2V(D) showed a stronger effect than Aβ1-6WT(D). (E) Aβ1-6A2VTAT(D) is not toxic when added to culture medium at concentrations ranging between 1 and 5 μM, while it reduces cell viability at higher concentrations. * Significance vs non-treated cells. (F) Aβ1-6A2VTAT(D) showed a dose-dependent effect in reducing Aβ1-42wt toxicity. Comparison of cell viability was performed by Student t-test.

Aβ1-6A2VTAT(D) maintains the in vitro anti-amyloidogenic properties of Aβ1-6A2V(D)

Aβ1-6A2V(D) alone does not efficiently cross either the blood brain barrier (BBB) or cell membranes (data not shown). This is an important feature that would deeply limit its use as an in vivo anti-amyloidogenic drug. So, we linked this peptide to the all-D TAT sequence to improve the translocation of Aβ1-6A2V(D) across the BBB and cell membranes, minimize the degradation of the peptide and reduce the immune response elicited by the molecule. The resulting compound [Aβ1-6A2VTAT(D)] destabilizes the secondary structure of Aβ1-42WT. Indeed, CD spectroscopy studies showed that Aβ1-6A2VTAT(D) inhibits the acquisition of β-sheet conformation by Aβ1-42WT (data not shown), thus affecting the folding of the full-length peptide.

We tested the ability of Aβ1-6A2VTAT(D) to inhibit the fibrillogenic properties of the full-length Aβ in vitro and found that the compound hindered Aβ1-42WT aggregation (Fig. 3). Polarized light and electron microscopy studies on aggregates of Aβ1-42WT formed after 20 days incubation with or without Aβ1-6A2VTAT(D) revealed that the mutated peptide hinders the formation of amyloid structures (Fig. 3B) and reduces the amount of fibrils generated by the full-length peptide (Fig. 3D). Moreover, AFM analysis (Fig. 3E,H) showed that Aβ1-6A2VTAT(D) actually interferes with the oligomerization process of Aβ1-42WT. Indeed, monomeric Aβ1-42WT, incubated alone at a final concentration of 100 μM, formed a family of small oligomers of different size within a range of 6-20 nm in diameter (~ 70%) (Fig. 3E,G). Conversely, the co-incubation with Aβ1-6A2VTAT(D) resulted in the formation of very small globular structures with a range of 5-8 nm in diameter and height of 200-400 pm (~ 70%), large and thin structures, apparently very rich in water (width: 500–700 nm; height: 200–500 pm). Notably, only rare oligomeric structures were detected (Fig. 3F,H).

Figure 3: Inhibition of aggregation of Aβ1-42WT by Aβ1-6A2VTAT(D).

Figure 3

Polarized-light (A,B), electron microscopy (C,D) and atomic force microscopy (AFM) (E–H) studies showing the inhibitory effects of Aβ1-6A2VTAT(D) on amyloid formation, fibril production and oligomerization by Aβ1-42WT. In polarized-light and EM studies, both peptides were used at 0.125 mM, molar ratio = 1:1 or 1:4 respectively, with 20 days incubation. From 5–20 days, 1:1 co-incubation of the two peptides (B,D) displayed a lower amyloid fibril content respect to Aβ1-42WT alone (A,C), showing protofibrils, short fibrils and disaggregated granular material.E,F: Representative Tapping mode of AFM images as determined by amplitude error data of Aβ1-42WT oligomers. Aβ1-42WT peptide 100 μM in phosphate buffer 50 mM, pH 7.4 was incubated at 4 °C for 24 h alone (E) (Z range: -10/ + 10 mV) or in presence of Aβ1-6A2VTAT(D) (F) (Z range: -10/ + 25 mV). The molar ratio of Aβ1-42WT to Aβ1-6A2VTAT(D) was 1:4. Scale bar: 1 μm, inset: 200 nm. (G,H): height plot profiles obtained along different lines traced on the topographic AFM images. Overall, these effects were already evident in the 1:1 mixture of the two peptides (data not shown), suggesting that the inhibition of Aβ1-42WT aggregation by Aβ1-6A2VTAT(D) is a dose-dependent effect.

These effects were observed by incubating Aβ1-42WT and Aβ1-6A2VTAT(D) at a 1:4 molar ratio, but they were also evident at equimolar concentrations of the two peptides.

Moreover, treatment of differentiated SH-SY5Y cells with Aβ1-6A2VTAT(D) showed that the peptide is not toxic when administered at concentrations ranging between 1 and 5 μM (Fig. 2E). When co-incubated with Aβ1-42WT, Aβ1-6A2VTAT(D) displayed a significant dose-dependent reduction of the toxicity induced by full-length Aβ (Fig. 2F).

All these findings indicated that the designed Aβ1-6A2VTAT(D) peptide is particularly efficient at inhibiting Aβ polymerization and toxicity in vitro, and identified it as our lead compound for the subsequent in vivo studies.

During the last few decades, huge efforts have been made to develop disease-modifying therapies for Alzheimer, but the results of these attempts have been frustrating. The anticipated increase of AD patients in the next few decades makes the development of efficient treatments an urgent issue16. In order to prevent the disease and radically change its irreversible course, a long series of experimental strategies against the main molecular actors of the disease (Aβ and tau)17 or novel therapeutic targets18 have been designed based on purely theoretical grounds19 as well as on evidence mainly deriving from preclinical observations in AD animal models20. However, few strategies proved suitable for application in human clinical trials, and none proved to be really effective21.Our approach differs from previous strategies – mainly those involving modified Aβ peptides that have been found to inhibit amyloidogenesis19,22 – since it is based on a natural genetic variant of amyloid-β (AβA2V) that occurs in humans and prevents the development of the disease when present in the heterozygous state7.

In this context, we carried out in vitro and in vivo studies that revealed the extraordinary ability of AβA2V to interact with AβWT, interfering with its aggregation8. These findings were a proof of concept of the validity of therapeutic strategies based on the use of AβA2V variant, and prompted us to develop a new disease-modifying treatment for AD by designing a six-mer mutated D-isomer peptide [Aβ1-6A2V(D)] linked to the short amino acid sequence derived from the HIV TAT peptide, widely used for brain delivery, to make the translocation of Aβ1-6A2V(D) across the BBB feasible.

The use of TAT as a carrier for brain delivery of drugs has been employed in several experimental approaches for the treatment of AD-like pathology in mouse models12,13. Recently, intraperitoneal administration of a TAT-BDNF peptide complex for 1 month was shown to improve the cognitive functions in AD rodent models23.

A previous study showed that, following its peripheral injection, a fluorescein-labelled version of TAT is able to cross the BBB, bind amyloid plaques and activate microglia in the cerebral cortex of APPswe/PS1DE9 transgenic mice24. TAT was then conjugated with a peptide inhibitor (RI-OR2, Ac-rGffvlkGr-NH2) consisting of a retro-inverted version of Aβ16–20 sequence25 that was found to block the formation of Aβ aggregates in vitro and to inhibit the toxicity of Aβ on cultured cells25. Daily i.p. injection of RI-OR2-TAT for 21 days into 10-month-old APPswe/PS1DE9 mice resulted in a reduction in Aβ oligomer levels and amyloid-β burden in cerebral cortex24.

We followed a similar strategy and initially demonstrated that Aβ1-6A2V(D), with or without the TAT sequence, retains in vitro the anti-amyloidogenic properties of the parental full-length mutated Aβ, since it is effective at hindering in vitro the production of oligomers and fibrils, the formation of amyloid and the toxicity induced by Aβ1-42WT peptide on SYSH-5Y cells.

Based on these results, we then decided to test in vivothe anti-amyloidogenic ability of Aβ1-6A2VTAT(D). The compound proved stable in serum after i.p. administration in mice, able to cross the BBB and associated with an immune response that was not found to cause any brain damage.

Short-term treatment with Aβ1-6A2VTAT(D) in the APPswe/PS1DE9 mouse model prevented cognitive deterioration, Aβ aggregation and amyloid deposition in brain. Unexpectedly, a longer treatment schedule, while retaining the results for cognitive impairment, attenuated the effects on Aβ production and increased amyloid burden, most likely due to the intrinsic amyloidogenic properties of TAT.

 

Indeed, we found that TAT(D), unlike Aβ1-6A2V(D), has a strong ability to bind amyloid deposits. This avidity for amyloid could boost the intrinsic seeding activity of amyloid plaques via a continuous and self-sustained recruitment of Aβ aggregates, leading to an exacerbation of the amyloidogenesis.

A similar effect of TAT was described in a study26reporting that HIV TAT promotes AD-like pathology in an AD mouse model co-expressing human APP bearing the Swedish mutation and TAT peptide (PSAPP/TAT mice). These mice indeed showed more Aβ deposition, neurodegeneration, neuronal apoptotic signalling, and phospho-tau production than PSAPP mice.

Moreover, TAT was found to increase Aβ levels by inhibiting neprilysin27 or enhancing β-secretase cleavage of APP, resulting in increased levels of the C99 APP fragment and 5.5-fold higher levels of Aβ4228. The same study reported that stereotaxic injection of a lentiviral TAT expression construct into the hippocampus of APP/presenilin-1 (PS1) transgenic mice resulted in increased TAT-mediated production of Aβ in vivo as well as an increase in the number and size of Aβ plaques. This is consistent with our findings, indicating a shift in APP processing towards the amyloidogenic processing in vivo at the end of the 5-month treatment with Aβ1-6A2VTAT(D) that was not observed in shorter treatment schedules with the same compound.

Therefore, these data suggest that the final outcome of our in vivo studies with Aβ1-6A2VTAT(D) is the result of side effects of the TAT carrier, whose amyloidogenic intrinsic activity neutralized the anti-amyloidogenic properties of the AβA2V variant. Nevertheless, we believe that the approach based on the use of AβA2V variant can be successfully used in treating AD, because of its potential ability to tackle the main pathogenic events involved in the disease, as suggested by the natural protection against the disease which occurs in human heterozygous A673V carriers.

 

Transthyretin participates in beta-amyloid transport from the brain to the liver- involvement of the low-density lipoprotein receptor-related protein 1?

Mobina Alemi, Cristiana Gaiteiro, Carlos Alexandre Ribeiro, Luís Miguel Santos,João Rodrigues Gomes,…, Ignacio Romero, Maria João Saraiva  & Isabel Cardoso

Scientific Reports 6, Article number: 20164 (2016)   http://dx.doi.org:/10.1038/srep20164

Transthyretin (TTR) binds Aβ peptide, preventing its deposition and toxicity. TTR is decreased in Alzheimer’s disease (AD) patients. Additionally, AD transgenic mice with only one copy of the TTR gene show increased brain and plasma Aβ levels when compared to AD mice with both copies of the gene, suggesting TTR involvement in brain Aβ efflux and/or peripheral clearance. Here we showed that TTR promotes Aβ internalization and efflux in a human cerebral microvascular endothelial cell line, hCMEC/D3. TTR also stimulated brain-to-blood but not blood-to-brain Aβ permeability in hCMEC/D3, suggesting that TTR interacts directly with Aβ at the blood-brain-barrier. We also observed that TTR crosses the monolayer of cells only in the brain-to-blood direction, as confirmed by in vivo studies, suggesting that TTR can transport Aβ from, but not into the brain. Furthermore, TTR increased Aβ internalization by SAHep cells and by primary hepatocytes from TTR+/+ mice when compared to TTR−/− animals. We propose that TTR-mediated Aβ clearance is through LRP1, as lower receptor expression was found in brains and livers of TTR−/− mice and in cells incubated without TTR. Our results suggest that TTR acts as a carrier of Aβ at the blood-brain-barrier and liver, using LRP1.

Alzheimer’s disease (AD), described for the first time by Alois Alzheimer in 1906, is characterized by progressive loss of cognitive functions ultimately leading to death1. Pathologically, the disease is characterized by the presence of extraneuronal amyloid plaques consisting of aggregates of amyloid-beta (Aβ) peptide, and neurofibrillary tangles (NFTs) which are intracellular aggregates of abnormally hyperphosphorylated tau protein2. Aβ peptide is generated upon sequential cleavage of the amyloid precursor protein (APP), by beta- and gamma-secretases, and it is believed that an imbalance between Aβ production and clearance results in its accumulation in the brain.

Clearance of Aβ from the brain occurs via active transport at the blood-brain-barrier (BBB) and blood cerebrospinal fluid (CSF) barrier (BCSFB), in addition to the peptidolytic removal of the peptide by several enzymes. The receptors for Aβ at the BBB bind Aβ directly, or bind to one of its carrier proteins, and transport it across the endothelial cell. The low-density lipoprotein receptor-related protein 1 (LRP1) and the receptor for advanced glycation end products (RAGE) are involved in receptor-mediated flux of Aβ across the BBB3. Both LRP1 and RAGE are multi-ligand cell surface receptors that, in addition to Aβ, mediate the clearance of a large number of proteins. While LRP1 appears to mediate the efflux of Aβ from the brain to the periphery, RAGE has been strongly implicated in Aβ influx back into the central nervous system (CNS). With increasing age, the expression of the Aβ efflux transporters is decreased and the Aβ influx transporter expression is increased at the BBB, adding to the amyloid burden in the brain.

 

Transthyretin (TTR), a 55 kDa homotetrameric protein involved in the transport of thyroid hormones and retinol, has been proposed as a protective protein in AD in the mid-nineties, when Schwarzman and colleagues described this protein as the major Aβ binding protein in CSF. These authors described that TTR was able to inhibit Aβ aggregation and toxicity, suggesting that when TTR fails to sequester Aβ, amyloid formation occurs4,5. Data showing that TTR is decreased in both CSF6 and plasma7,8 of AD patients, strengthen the idea of neuroprotection by TTR. Evidence coming from in vivostudies in AD transgenic mice established in different TTR genetic backgrounds9,10 also suggests that TTR prevents Aβ deposition and protects against neurodegeneration, although the exact mechanism is still unknown. Ribeiro and colleagues reported increased Aβ levels in both brain and plasma of AD mice with only one copy of the TTR gene, when compared to animals with two copies of the gene11, suggesting a role for TTR in Aβ clearance. Growing evidence also suggests a wider role for TTR in CNS neuroprotection, including in ischemia12, regeneration13 and memory14.

The presence of TTR in brain areas other than its site of synthesis and secretion – the choroid plexus (CP) and CSF, respectively–in situations of injury, such as ischemia, has been shown using a mouse model with compromised heat-shock response12. Authors showed that TTR was not being locally synthesized, but instead should derive from CSF TTR. However, other studies demonstrated TTR synthesis by cortical15 or hippocampal neurons both in vitro16, and in vivo17, and some hints on its regulation have already been advanced. Kerridge and colleagues showed that TTR is expressed in SH-SY5Y neuroblastoma cell line, and that it is up-regulated by the AICD fragment of amyloid precursor protein (APP), specifically derived from the APP695 isoform. Induced accumulation of functional AICD resulted in TTR up-regulation and Aβ decreased levels16. Wang and colleagues reported that TTR expression in SH-SY5Y cells, primary hippocampal neurons and hippocampus of APP23 mice is significantly enhanced by heat shock factor 1 (HSF1)17. In any case, TTR is available in the brain and might participate in brain Aβ efflux by promoting BBB permeability to the peptide. With regard to Aβ peripheral elimination, it is known that Aβ bound to ApoE/cholesterol can be incorporated in HDL to be further delivered at the liver for degradation18 and curiously, a fraction of TTR is transported in HDL19. Furthermore, the liver is the major site for TTR degradation and although its hepatic receptor has never been unequivocally identified, it has been reported that it is a RAP-sensitive receptor20. Thus, in this work we assessed the role of TTR in Aβ transport, both from the brain and to the liver.

TTR clearance in vivo

TTR ability to cross the BBB, in both directions, was studied in vivo using TTR −/− mice and injecting h rTTR. To assess the brain-to-blood permeability, immediately before the injection, mice were weighed and anesthetized with intraperitoneal injection of an anesthetic combination of ketamine and medetomidine (7.5 mg/Kg and 0.1 mg/Kg, respectively) and placed in a stereotaxic apparatus (Stoelting Co.). The cranium was exposed using an incision in the skin and one small hole was drilled through the cranium over the right lateral ventricle injection site to the following coordinates: mediolateral −1.0 mm, anterior-posterior −0.22 mm and dorsal-ventral −1.88 mm, from bregma. Then, 10 μg of h rTTR were injected into the brain using a 10 μL motorized syringe (Hamilton Co.) connected to a 30 gauge needle (RN Needle 6 pK, Hamilton Co.) at a rate of 0.75 μL/min (4 μL final volume). After injection, the microsyringe was left in place for 3 minutes to minimize any backflow, and then the incision was closed with sutures (Surgicryl), and the wound was cleaned with 70% ethanol. After surgery, the animals were kept warm, using a warming pad, and blood samples were collected by the tail vein after 20, 40 and 60 minutes, in a capillary tube (previously coated with EDTA). At the time of sacrifice (after 60 minutes), the mice were re-anesthetized with 75 mg/Kg ketamine and 1 mg/Kg medetomidine, and after total absence of reflexes in the paw and tail, mice were perfused through the injection of sterile PBS pH 7.4 via the inferior vena cava until the liver becomes blanched. Then, the brain was rapidly collected and frozen at −80 °C until use.

To assess the blood-to-brain permeability, 10 μg of h rTTR were injected in the tail vein, and blood samples were collected after 20, 40 and 60 minutes. At 60 minutes, and after perfusion as described above, CSF and brain were also collected.

To determine TTR levels, brains were weighted and homogenized in 750 μL of 50 mM TBS pH 7.4 containing protease inhibitor cocktail. After centrifugation for 20 minutes at 14000 rpm at 4 °C, supernatants were collected. TTR concentration in brain, CSF and plasmas was determined by ELISA.

Characterization of the hCMEC/D3 cell line

The hCMEC/D3 cell line represents a valid and powerfulin vitro tool as a BBB model, and presents a less expensive and more logistically feasible alternative to primary hBMEC cells24,25. Thus, our first step was the validation of the hCMEC/D3 model by characterizing this cell line regarding two critical features for our studies: BBB integrity and LRP1 expression.

In the context of endothelial cell tight junctions (TJ), hCMEC/D3 cells were tested for claudin-5 and occludin expression by immunofluorescence. As shown in Fig. 1, hCMEC/D3 cells are positive for TJ structural proteins, claudin-5 and occludin, showing the expected membrane localization (as previously described). These results indicate that the integrity, tightness and structure, as well as the paracellular contact between endothelial cells are guaranteed by these TJ proteins. Along with other TJ proteins expressed by hCMEC/D3, claudin-5 and occludin ensure, with high efficiency, the control of transport across the cells monolayer.

Figure 1: Immunofluorescence localization of TJs components Claudin-5 and Occludin, and of LRP1, in hCMEC/D3.

 

Figure 1

The expression of the efflux transport receptor LRP1 by the hCMEC/D3 cell line is a key factor when validating this model, both for BBB studies purposes and for Aβ transport research. Thus, we performed immunofluorescence analysis to verify if LRP1 exists in the hCMEC/D3 cells. Our results show that LRP1 is expressed in these cells ensuring the Aβ transport through the cells monolayer (Fig. 1).

Effect of TTR in Aβ1-42 internalization by hCMEC/D3

Aβ1-42 is transported across the BBB, as expected, and is internalized by hCMEC/D3 cells. We firstly investigated FAM-labelled Aβ1-42 (FAM-Aβ1-42, 500 ng/mL)) uptake by these cells in the absence and presence of human recombinant TTR (h rTTR) (7.5 μg/mL), and analysed the results by flow cytometry.

Cells were incubated with FAM-Aβ1-42 at 37 °C producing a rapid uptake of the peptide (Fig. 2A). After 5 minutes of incubation, 35–39% of the cells were fluorescent and after an additional 5 minutes (10 minutes incubation) a significant increase was already measured as over 57% of the cells were fluorescent, although differences between the presence and absence of TTR were not significant. However, after 15 minutes the presence of TTR significantly increased Aβ internalization resulting in about 73% fluorescent cells, in contrast to 61.7% incubated in the absence of TTR (Fig. 2A). Finally after 30 minutes of incubation, and although the difference between internalization levels at 15 and 30 minutes was not statistically significant, FAM-Aβ1-42 internalization was significantly higher in the presence of TTR.

Figure 2: Interaction of FAM-Aβ1-42 with hCMEC/D3 cells in the presence and absence of TTR assessed by flow cytometry:

Figure 2

(A) Internalization levels of FAM-Aβ1-42 by hCMEC/D3 cells in the presence of h rTTR (white columns) was significantly higher than in the absence of the protein (black columns) after 15 and 30 minutes of incubations. (B) Efflux of FAM-Aβ1-42 from hCMEC/D3 measured after 10 minutes of incubation with the peptide was significantly increased at 20 minutes post-replacement with fresh FAM-Aβ1-42-free media, in the presence of h rTTR. N = 3 for each condition and data are expressed as mean±SEM.

Next to investigate the fate of internalized Aβ, we performed an efflux assay. For that, hCMEC/D3 cells were firstly incubated with FAM-Aβ1-42 for 10 minutes, in the absence or presence of h rTTR and then the media were replaced with fresh Aβ-free media. Cells were further incubated at 37 °C and levels of FAM-Aβ1-42 inside cells were measured by flow cytometry, after 10 and 20 minutes. Figure 2B depicts the results showing that in the presence of TTR, FAM-Aβ1-42 effluxes significantly faster than in the absence of this protein, after 20 minutes (45.5% and 67.6% fluorescent cells, respectively).

Effect of TTR in hCMEC/D3 brain-to-blood permeability to Aβ1-42 peptide

In order to investigate the effect of TTR in Aβ1-42 transport across a monolayer of cells, acting as a model of the BBB as previously described, Aβ1-42 transport experiments were performed in hCMEC/D3 cultured in transwells inserts, as shown in Fig. 3A. Cells were grown for 10 days until reaching maximal confluence and allowing TJ formation. Thus, at this point, the cell monolayer should show restricted paracellular permeability, and its confirmation was done using FITC-labelled dextran as a low molecular weight paracellular diffusion marker. In this approach, FITC-labelled dextran 0.25 mg/mL was added to the apical chamber, and then incubated for 1 hour. Wells in which FITC-labelled dextran exceeded 125 ng/mL on the basolateral chamber were considered to have the monolayer disrupted and thus were excluded from the experiment.

Figure 3: Brain-to-blood permeability of hCMEC/D3 cells to Aβ1-42:

Figure 3

(A) Schematic representation of the transwell system used showing the brain and blood sides; Aβ1-42 peptide was always added to the brain side, whereas TTR was added either to the brain or to the blood sides. (B) Brain-to-blood permeability was increased in the presence of h rTTR although without reaching significant differences. However, in the presence of (C) hTTR present in sera, brain-to-blood permeability of hCMEC/D3 cells to Aβ1-42 was significantly increased after 3 hours up to 48 hrs. As a control, Aβ peptide was also added to non-seeded filters to show free passage of the peptide when compared to cell-seeded ones. N = 3 for each condition and data are expressed as mean±SEM. To mimic the absence of TTR, we used TTR-depleted human sera obtained after affinity chromatography, and further analysed by western blot (D) lanes 1- human sera; 2- protein G sepharose beads/anti-human prealbumin antibody; 3-human sera TTR-depleted; 4-Eluted TTR; 5-r hTTR.

We added h rTTR either to the brain or to the blood side, whereas Aβ1-42 was always added to the brain side. Results are displayed in Fig. 3B and show increased permeability of the hCMEC/D3 monolayer to Aβ1-42, when h rTTR is in the brain side, as compared to the levels of Aβ1-42 passage when h rTTR is in the blood side, although the differences were not statistically significant.

To further evaluate the effect of TTR in Aβ1-42 transport across the BBB and in order to obtain a more complex environment in hCMEC/D3 model, we performed the same transwell experiments but using human sera as source of hTTR (TTR concentration 7.5 μg/ml). To mimic the absence of TTR, we used human sera after TTR depletion by affinity chromatography (Fig. 3D). Again, hTTR present in the brain side promoted significant Aβ1-42 transport across the hCMEC/D3, as compared to the situation where hTTR was in the blood side (Fig. 3C). This suggests that TTR participates in Aβ1-42 efflux from the brain through a mechanism that implies TTR/Aβ interaction at the BBB or in its vicinity.

Brain permeability to TTR

Given our evidence in TTR-assisted Aβ transport and to clarify if TTR might be co-transported during such process, we assessed TTR internalization by hCMEC/D3 cells, and as shown in Fig. 4A, TTR was uptaken by these cells.

Figure 4: Permeability of hCMEC/D3 cells to TTR:

Figure 4

(A) hCMEC/D3 cells internalize TTR, as assessed by fluorescence microscopy. (B) hCMEC/D3 cells are permeable to TTR in the brain-to-blood direction but not in the blood-to-brain direction. N = 3 for each condition and data are expressed as mean±SEM.

We next investigated if TTR could cross the hCMEC/D3 monolayer and to assess this, hTTR was added either to the apical or basolateral compartment of the transwells. TTR was then quantified in the media of both chambers and analysed as % TTR that passed to the opposite side. As shown in Fig. 4B, TTR crosses the monolayer in the brain-to-blood direction but not in the blood-to brain direction. This suggests TTR is using a receptor with main expression in the basolateral membrane of the hCMEC/D3 cells.

To confirm these results, we also evaluated TTR clearance in vivo, using TTR−/− mice injected with h rTTR, either intracranially (IC) in the right lateral ventricle or intravenously (IV) in the tail vein. As displayed in Table 1, TTR injected in the brain rapidly reached the periphery as TTR was easily detected in blood, whereas mice injected IV showed negligible levels of the protein in the CSF and brain. Thus, this data corroborates the results obtained in the transwell experiments. This also suggests that TTR can favour Aβ brain efflux but cannot favour its influx, contributing to neuroprotection in AD.

Effect of TTR in Aβ1-42 and Aβ1-40 in AD transgenic mice

Previous work using an AD transgenic model (APPswe/PS1A246E) with different TTR genetic backgrounds (AD/TTR) has demonstrated that Aβ1-42 plasma levels are increased in 7-month old TTR+/− female mice, when compared to TTR+/+ animals11, suggesting a role for TTR in Aβ peripheral clearance.

In this work, to obtain a better knowledge on the effect of TTR in plasma Aβ peptide levels, we extended the study by evaluating not only Aβ1-42 but also Aβ1-40 levels in 3-months old AD/TTR+/+, AD/TTR+/− and AD/TTR−/− female mice. Results are depicted in Fig. 5 and show a negative correlation between TTR and both Aβ1-42 and Aβ1-40. Differences between AD/TTR+/+ and AD/TTR−/− mice were found to be statistical significant for both Aβ peptides. In addition, for Aβ1-42 statistical significant differences were also observed between AD/TTR+/− and AD/TTR−/−.

Figure 5: Effect of TTR genetic reduction in plasma Aβ1-42 and Aβ1-40 levels: Results are shown for 3-month old female mice with three distinct genotypes for TTR: AD/TTR+/+ (N = 5 for Aβ1-42; N = 4 for Aβ1-40), AD/TTR+/− (N = 6 for Aβ1-42; N = 4 for Aβ1-40) and AD/TTR−/− (N = 5 for Aβ1-42; N = 4 for Aβ1-40).

Taken together, our results suggest that TTR influences plasma Aβ by reducing its levels.

Effect of TTR in Aβ1-42 internalization by SAHep cells and primary hepatocytes

Aβ is known to also be delivered at the liver for degradation; therefore, we analysed the effect of TTR in FAM-Aβ1-42 internalization using the SAHep cell line. Uptake of Aβ1-42 peptide increased in the presence of h rTTR showing a positive correlation between Aβ uptake and h rTTR concentration, reaching a maximum of 70% when using 4.5–7.5 μg/mL of TTR in 3 hours (Fig. 6A).

Figure 6: Effect of TTR in Aβ peptide internalization by hepatocytes:

Figure 6

(A) FAM-Aβ1-42 internalization by SAHep cells, in the absence or presence of increasing concentrations of h rTTR, as measured by flow cytometry. TTR concentrations up to 4.5–7.5 μg/mL resulted in increased Aβ internalization by cells. N = 3 for each condition. (B) Flow cytometry of primary cultures of hepatocytes derived from mice with different genetic TTR backgrounds; hepatocytes derived from TTR+/+ mice showed significantly more internalization of FAM-Aβ1-42 than those derived from TTR+/− and from TTR−/−. N =  11, N = 8, N = 14, N = 6 for hepatocytes derived from TTR +/+, TTR +/−, TTR −/− and h rTTR treated TTR −/− mice, respectively. (C) moTTR levels in supernatants of primary hepatocytes measured by ELISA confirmed the genetic reduction in TTR+/− which showed about half of the TTR in TTR+/+, while TTR−/− produced no TTR protein. N = 7 for TTR+/+ and −/− mice and N = 5 for TTR +/−.

 

To further study the effect of TTR in Aβ1-42 uptake by hepatocytes, and in order to avoid addition of exogenous TTR (since hepatocytes produce TTR), we prepared primary cultures of hepatocytes derived from mice with different TTR genetic backgrounds (TTR+/+, TTR+/− and TTR−/−). TTR secretion was evaluated by ELISA revealing values of approximately 70 and 40 ng/mL for TTR+/+ and TTR+/−, respectively, over a period of 3 hours (Fig. 6C). TTR−/− hepatocytes did not produce TTR, as expected.

As for Aβ1-42 uptake, we observed that TTR facilitated peptide internalization by primary hepatocytes as differences were statistically significant between genetic backgrounds (Fig. 6B). Importantly, addition of h rTTR to TTR−/− hepatocytes partially rescued the phenotype as internalization values equalized those of TTR+/− cells.

Influence of TTR on LRP1 levels

We firstly assessed LRP1 expression by qRT-PCR in total brain extracts of TTR+/+, TTR+/− and TTR−/− mice, and observed significant differences in the expression of this receptor: brains from TTR+/+ mice expressed LRP1 in significantly higher levels than brains from TTR−/− animals (Fig. 7A1). These results were corroborated by measuring LRP1 protein levels by western blot (Fig. 7A2).

Figure 7: LRP1 expression in the brain, liver and cell lines assessed by qRT-PCR, western blot and immunofluorescence: LRP1 levels investigated in the brains from TTR+/+, TTR+/− and TTR−/− mice by

(A1) qRT-PCR (n = 4) and (A2) by western blot (n = 3), showed to correlate directly with TTR levels. hCMEC/D3 cells (n = 3) incubated with TTR showed higher amounts of (B1) mRNA and (B2) protein than cells without TTR. Similarly, livers of TTR+/+ mice expressed more LRP1, both (C1) mRNA (n = 4) and (C2) protein (n = 3), than of TTR−/− mice. (D1) qRT-PCR for LRP1 in SAHep cells incubated with exogenous h rTTR increased their LRP1 mRNA levels (n = 3). (D2) Upon incubation with TTR, SAHep cells increased their LRP1 protein levels.

To further understand the importance of TTR in regulating LRP1 levels in the context of Aβ transport across the BBB, we incubated hCMEC/D3 cells with h rTTR and investigated LRP1 expression by qRT-PCR. As depicted in Fig. 7B1, hCMEC/D3 incubated with TTR displayed higher LRP1 expression, thus confirming the regulation of LRP1 by TTR in these endothelial cells; these results were also corroborated by protein levels, as evaluated by immunocytochemistry (Fig. 7B2)

Similarly to the internalization studies, we also evaluated the ability of TTR to regulate LRP1 levels in hepatocytes by performing qRT-PCR studies in livers from TTR+/+, TTR+/− and TTR−/− mice, as well as in the hepatocyte cell line, SAHep cells. Similarly to the brains, livers from TTR+/+ mice expressed higher levels of LRP1, when compared to the livers from TTR−/− animals (Fig. 7C1). Protein analysis confirmed the effect of TTR at increasing LRP1 and as for the brains, significant differences were observed between TTR+/+ and TTR−/− mice (Fig. 7C2). As for the cell line, SAHep cells analyzed by qRT-PCR (Fig. 7D1) and immunocytochemistry (Fig. 7D2) showed increased LRP1 mRNA and protein levels, respectively, when incubated with TTR.

 

Altogether, these results indicate that TTR regulates LRP1 levels, suggesting that TTR uses this receptor to promote Aβ clearance.

TTR is a transporter protein mainly synthesized in the liver and in the CP of the brain and secreted into the blood and CSF, respectively. TTR is known to transport several molecules, in particular T4 and retinol through binding to the retinol binding protein (RBP). In the CSF, TTR binds Aβ peptide impeding its deposition in the brain. However, the molecular mechanism underlying this process is not known. Given our earlier evidences that TTR lowers brain and plasma Aβ11, we hypothesized that TTR could function as an Aβ carrier that transports the peptide to its receptor at the brain barriers and at the liver.

Since the cerebral capillaries represent about the double of the total apical surface area of the CP27, we decided to start by studying the effect of TTR in Aβ transport at the BBB. Using the hCMEC/D3 in vitro model of the BBB, we showed that TTR significantly increased Aβ internalization by these cells. Both in the presence and absence of TTR, Aβ internalization levels were high after 15 minutes and no significant increase was measured after 30 minutes. Thus, we assessed efflux by removing media with FAM-Aβ1-42 after a period of incubation to show that TTR was also promoting Aβ efflux from these cells.

To further study the effect of TTR in Aβ transport using the hCMEC/D3 model and given the differential expression of receptors in polarized BBB endothelial cells, we next performed our experiments using transwell cultures. Brain-to-blood transport of Aβ peptide was investigated and we concluded that TTR increased Aβ transport, if added to the brain side but not if added to the blood side. This observation is consistent with a direct TTR/Aβ interaction, as previously demonstrated28. To understand if TTR was also being transported while carrying Aβ, we also evaluated TTR ability to cross the endothelial monolayer to show that this protein can cross in the brain-to-blood direction, but does not cross in the opposite direction. To confirm this, we analyzed in vivo TTR brain permeability using TTR−/− mice injected with h rTTR either into the brain ventricle or into the tail vein. The presence of TTR was then investigated in brain and blood. The results corroborated the in vitroobservations since upon IC administration of TTR, the protein was rapidly found in blood; however, after IV injection of TTR the protein was detected neither in CSF nor in the brain extracts. Our findings are also supported by previous work on TTR turnover and degradation29; in this work authors reported that rat TTR injected intraventricularly into the CSF of rats was mainly degraded in the liver and kidneys (therefore effluxing from the brain), whereas no specific transfer of plasma TTR to the nervous system or degradation of plasma TTR in the nervous system was observed. It is worthy to note that Makover and colleagues injected purified rat TTR in a system containing the same endogenous rat TTR29, and results are similar to the ones we describe now. Therefore, we can conclude that in our system the TTR−/− background did not significantly affected TTR clearance.

The differential brain permeability to TTR indicates the use of a receptor with preferential expression on the basolateral membrane of the endothelial cells forming the BBB, such as LRP1, which in turn is known to internalize Aβ peptide. Whether TTR can cross or not as a complex, namely with Aβ peptide, is not known and needs to be investigated.

 

TTR gene expression in the brain is usually described as being confined to the CP and meninges, although TTR can be transported to other brain cells. For instance, it is described that in situations of compromised heat-shock response, and as a response to cerebral ischemia, CSF TTR contributes to control neuronal cell death, edema and inflammation12. This implies that TTR is transported from CSF to other brain areas, and thus it is also possible that this protein participates in Aβ transport at the BBB. TTR gene expression has been also attributed to neurons and for instance, SH-SY5Y cells transfected with APP695 isoform showed up-regulation of TTR mRNA expression, with concomitant decrease in Aβ levels16. Other authors showed that the majority of hippocampal neurons from human AD and all those from APP23 mouse brains contain TTR. In addition, quantitative PCR for TTR mRNA and Western blot analysis showed that primary neurons from APP23 mice transcribe TTR mRNA, and that the cells synthesize and secrete TTR protein15. More recently, it has been shown that TTR transcription and protein production can be induced by heat shock factor 1 (HSF1) in hippocampal neurons but not in the liver, both using cell lines and in vivo approaches17.

Importantly, the BCSFB should also be investigated for TTR-assisted Aβ transport, since this protein is the major protein binding Aβ in CSF. In spite of the low TTR levels in CSF (~2 mg/mL), the choroid plexus is presented as the major site of TTR expression, expressed as a ratio of TTR/mass of tissue, corresponding to a ~30-fold higher than that found in plasma30. Interestingly, a recent report describes that in a triple transgenic mouse model of AD only the Aβ1-42 isoform is increased at the epithelial cytosol, and in stroma surrounding choroidal capillaries. Noteworthy, there was increased expression, presumably compensatory, of the choroidal Aβ transporters: LRP1 and RAGE. In addition, authors reported that the expression of TTR was attenuated as compared to non-transgenic mice31.

Previous works indicated that the genetic reduction of TTR in an AD mouse model results in increased Aβ brain levels9,10; another work using 7 month old female mice also showed increased Aβ1-42 plasma levels in AD/TTR+/− mice as compared to age-and gender-matched AD/TTR+/+ animals. In the present work, we extended our study and evaluated both plasma Aβ1-42 and Aβ1-40 isoforms in 3 months old AD/TTR+/+, AD/TTR/+/− and AD/TTR−/− animals, showing that TTR correlates negatively with both isoforms of Aβ. Further, these findings support the idea that plasma may also reflect disease disturbances in AD.

Thus, the following level of our study focused on the effect of TTR in Aβ peptide uptake by the liver. After showing that h rTTR produces a concentration-dependent increase in Aβ internalization by SAHep cells, we worked with primary hepatocytes derived from mice with different TTR backgrounds showing again higher levels of internalization in the presence of TTR.

Interestingly, previous work has shown that TTR is internalized by the liver using a RAP-sensitive receptor20, such as LRP1. Multiple factors influence the function of LRP1-mediated Aβ clearance, such as its expression, shedding, structural modifications and transcriptional regulation by other genes32. Recent studies have clarified how Aβ clearance mechanisms in the CNS are indirectly altered by vascular and metabolism-related genes via the sterol regulatory element binding protein (SREBP2)33. In addition, AD risk genes such as phosphatidylinositol binding clathrin assembly protein (PICALM)34 and apoE isoforms can differentially regulate Aβ clearance from the brain through LRP135.

Consequently, given the importance of this receptor in Aβ clearance both from the brain and at the liver, we evaluated the levels of gene and protein expression in different models. Both LRP1 transcript and protein levels were increased in TTR+/+ brains as compared to TTR−/−. To further confirm the importance of TTR in regulating the levels of LRP1 specifically at the BBB, and contributing to explain the importance of TTR in Aβ clearance, we measured LRP1 in hCMEC/D3 cells with and without incubation with TTR. We observed that the presence of TTR clearly increased the receptor expression, producing significant differences. A similar study was then undertaken for liver and SAHep cells, which again showed regulation of LRP1 expression by TTR. Whether liver TTR regulates liver LRP1 and CSF TTR regulates brain LRP1 is not known and further studies, namely differential silencing of the TTR gene (liver or CP), should be performed.

In a recent study, TTR has been described to regulate insulin-like growth factor receptor I (IGF-IR) expression in mouse hippocampus (but not in choroid plexus) and this effect is due to TTR mainly synthesized by the choroid plexus (and secreted into the CSF) and not by peripheral TTR36. Once more, the possibility for local TTR production has been advanced by some authors16,17, as already mentioned. Finally, it is also known that LRP1 and IGF-IR interact37,38 in a way that the extracellular ligand-binding domain of LRP1 is not involved thus remaining free to bind its ligands. A common link is now established as TTR can regulate the expression of both receptors, albeit in different areas of the brain, opening the possibility for TTR being involved in other processes in the CNS. Moreover, using mice with deleted APP and APLP2, APP has been shown to down-regulate expression of LRP139 via epigenetic events mediated through its intracellular domain (AICD) and to up-regulate TTR, as previously described16. Though it is not known if LRP1 and TTR regulation are part of the same AICD-pathway since TTR levels were not evaluated in the APP and APLP2-deleted mice.

In summary, we show that neuroprotective effects of TTR previously observed in the context of AD are consistent with its role in Aβ clearance at the BBB and liver, and that TTR regulates LRP1 expression, suggesting that TTR is also transported by this receptor. In the future, the TTR-LRP1 cascade should be further investigated for therapeutic targeting.

Summary

TTR decreases in the population of both men and women after age 45 years.  This has consequences with respect to AD.  TTR is mainly synthesized by the choroid plexus (and secreted into the CSF) and not by peripheral TTR36, but this declines even earlier than that produced by the liver. (Ingenbleek and Bernstein, 2016).  This suggests a significant role for these age related changes in the development of AD.  Moreover, what has been presented indicates a role for snake venum in increasing the removal of amyloid plaque that develops in AD.  TTR is important in A-beta clearance in liver and BBB.  There was a shift in APP processing towards the amyloidogenic processing in vivo at the end of the 5-month treatment with Aβ1-6A2VTAT(D) that was not observed in shorter treatment schedules with the same compound

 

MIT scientists find evidence that Alzheimer’s ‘lost memories’ may one day be recoverable    By Ariana Eunjung Cha

https://www.washingtonpost.com/news/to-your-health/wp/2016/03/17/mit-scientists-find-evidence-that-alzheimers-lost-memories-may-one-day-be-recoverable/?tid=pm_national_pop_b

Scientists had assumed for a long time that the disease destroys how those memories are encoded and makes them disappear forever. But what if they weren’t actually gone — just inaccessible?

A new paper published Wednesday by the Massachusetts Institute of Technology’s Nobel Prize-winning Susumu Tonegawa provides the first strong evidence of this possibility and raises the hope of future treatments that could reverse some of the ravages of the disease on memory.

“The important point is, this is a proof of concept,” Tonegawa said. “That is, even if a memory seems to be gone, it is still there. It’s a matter of how to retrieve it.”

Zane JaunmuktaneSimon MeadMatthew Ellis, …., A. Sarah WalkerPeter RudgeJohn Collinge & Sebastian Brandner
Nature (10 Sep 2015)
;525,247–250     
     doi:10.1038/nature15369

More than two hundred individuals developed Creutzfeldt–Jakob disease (CJD) worldwide as a result of treatment, typically in childhood, with human cadaveric pituitary-derived growth hormone contaminated with prions1, 2. Although such treatment ceased in 1985, iatrogenic CJD (iCJD) continues to emerge because of the prolonged incubation periods seen in human prion infections. Unexpectedly, in an autopsy study of eight individuals with iCJD, aged 36–51 years, in four we found moderate to severe grey matter and vascular amyloid-β (Aβ) pathology. The Aβ deposition in the grey matter was typical of that seen in Alzheimer’s disease and Aβ in the blood vessel walls was characteristic of cerebral amyloid angiopathy3 and did not co-localize with prion protein deposition. None of these patients had pathogenic mutations, APOE ε4 or other high-risk alleles4associated with early-onset Alzheimer’s disease. Examination of a series of 116 patients with other prion diseases from a prospective observational cohort study5 showed minimal or no Aβ pathology in cases of similar age range, or a decade older, without APOE ε4 risk alleles. We also analysed pituitary glands from individuals with Aβ pathology and found marked Aβ deposition in multiple cases. Experimental seeding of Aβ pathology has been previously demonstrated in primates and transgenic mice by central nervous system or peripheral inoculation with Alzheimer’s disease brain homogenate6, 7, 8, 9, 10, 11. The marked deposition of parenchymal and vascular Aβ in these relatively young patients with iCJD, in contrast with other prion disease patients and population controls, is consistent with iatrogenic transmission of Aβ pathology in addition to CJD and suggests that healthy exposed individuals may also be at risk of iatrogenic Alzheimer’s disease and cerebral amyloid angiopathy. These findings should also prompt investigation of whether other known iatrogenic routes of prion transmission may also be relevant to Aβ and other proteopathic seeds associated with neurodegenerative and other human diseases.

http://www.nih.gov/news-events/news-releases/decoding-molecular-ties-between-vascular-disease-alzheimers

The research, described in the journal Nature, involved two groups of mice. One was a normal control and the other was  genetically engineered to have Alzheimer’s-like symptoms. Both groups were given a mild electric shock to their feet. The first group appeared to remember the trauma of the incident by showing fear when placed back in the box where they had been given the shock. The Alzheimer’s mice, on the other hand, seemed to quickly forget what happened and did not have an upset reaction to the box.

Their reaction changed dramatically when the scientists stimulated tagged cells in their brains in the hippocampus — the part of the brain that encodes short-term memories — with a special blue light. When they were put back in the box following the procedure, their memories of the shock appeared to have returned, and they displayed the same fear as their healthy counterparts.

Tonegawa and his colleagues wrote that the treatment appears to have boosted neurons to regrow small buds called dendritic spines that form connections with other cells.

 

The revelations have “shattered a 20-year paradigm of how we’re thinking about the disease,” Rudy Tanzi, a Harvard neurology professor who is not involved in the research, told the Boston Herald. He said that since the 1980s, researchers believed the memories just weren’t getting stored properly.

The technique used in the study — optical stimulation of brain cells, or “optogenetics” — involves the insertion of a gene into parts of a brain to make them sensitive to blue light and then stimulating them with the light.

In a commentary accompanying the paper, Prerana Shrestha and Eric Klann of the Center for Neural Science at New York University said that the research employed a “clever strategy” and that “the potential to rescue long-term memory in dementia is exciting.”

Doug Brown, director of research at the Alzheimer’s Society, cautioned that the technique is not something that can be translated into a procedure that is safe for the estimated 44 million people worldwide with dementia just yet.

“While interesting,” he told the Guardian, “the practicalities of this approach — using a special blue light to stimulate memory — means that we’re still many years away from knowing if it would be possible to restore lost memories in people.”

Electrical stimulation of the brain may be one alternative scientists can pursue, according to Christine Denny, a neurobiologist at Columbia University. Nature reported that early trials showed that deep-brain stimulation of the hippocampus may improve memory in some Alzheimer’s patients.

 

Memory retrieval by activating engram cells in mouse models of early Alzheimer’s disease

Dheeraj S. RoyAutumn AronsTeryn I. MitchellMichele PignatelliTomás J. Ryan Susumu Tonegawa
Nature(2016)
       doi:10.1038/nature17172

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive memory decline and subsequent loss of broader cognitive functions1. Memory decline in the early stages of AD is mostly limited to episodic memory, for which the hippocampus has a crucial role2. However, it has been uncertain whether the observed amnesia in the early stages of AD is due to disrupted encoding and consolidation of episodic information, or an impairment in the retrieval of stored memory information. Here we show that in transgenic mouse models of early AD, direct optogenetic activation of hippocampal memory engram cells results in memory retrieval despite the fact that these mice are amnesic in long-term memory tests when natural recall cues are used, revealing a retrieval, rather than a storage impairment. Before amyloid plaque deposition, the amnesia in these mice is age-dependent3, 4, 5, which correlates with a progressive reduction in spine density of hippocampal dentate gyrus engram cells. We show that optogenetic induction of long-term potentiation at perforant path synapses of dentate gyrus engram cells restores both spine density and long-term memory. We also demonstrate that an ablation of dentate gyrus engram cells containing restored spine density prevents the rescue of long-term memory. Thus, selective rescue of spine density in engram cells may lead to an effective strategy for treating memory loss in the early stages of AD.

Figure 1: Optogenetic activation of memory engrams restores fear memory in early AD mice

Optogenetic activation of memory engrams restores fear memory in early AD mice.

ac, Amyloid-β (Aβ) plaques in 9-month-old AD mice (a), in the DG (b), and in the EC (c). d, Plaque counts in HPC sections (n = 4 mice per group). ND, not detected. e, CFC behavioural schedule (n = 10 mice per group). fi, Freezing leve…

Figure 2: Neural correlates of amnesia in early AD mice.close

Neural correlates of amnesia in early AD mice.

a, b, Images showing dendritic spines from DG engram cells of control (a) and AD (b) groups. c, Average spine density showing a decrease in AD mice (n = 7,032 spines) compared with controls (n = 9,437 spines, n = 4 mice per group).

 

Behavioural rescue and spine restoration by optical LTP is protein-synthesis dependent.

Behavioural rescue and spine restoration by optical LTP is protein-synthesis dependent.

a, Modified behavioural schedule for long-term rescue of memory recall in AD mice in the presence of saline or anisomycin (left). Memory recall 2 days after LTP induction followed by drug administration showed less freezing of AD mice

 

Turn Off Alzheimer’s Disease

Lomonosov Moscow State University   http://www.dddmag.com/news/2016/03/turn-alzheimers-disease

This image shows the three-dimensional structure of the dimer of the metal-binding domain of beta-amyloid peptide having 'English mutation'. Two peptide molecules connected to each other with the help of zinc ion. Source: This image shows the three-dimensional structure of the dimer of the metal-binding domain of beta-amyloid peptide having 'English mutation'.  Source: Lomonosov Moscow State University

This image shows the three-dimensional structure of the dimer of the metal-binding domain of beta-amyloid peptide having ‘English mutation’. Two peptide molecules connected to each other with the help of zinc ion. Source: This image shows the three-dimensional structure of the dimer of the metal-binding domain of beta-amyloid peptide having ‘English mutation’. Source: Lomonosov Moscow State University

A group of the Lomonosov Moscow State University scientists, together with their colleagues from the Institute of Molecular Biology, Russian Academy of Sciences and the King’s College London, succeeded in sorting out the mechanism of Alzheimer’s disease development and possibly distinguished its key trigger. Their article was published in Scientific Reports.

‘Alzheimer’s disease is a widespread degenerative damage of central nervous system leading to a loss of mental ability.’Until now it was considered incurable,’ tells Vladimir Polshakov, the leading researcher, MSU Faculty of Fundamental Medicine. Though now scientists managed to distinguish the mechanism ‘running’ the disease development, so, a chance appeared to elaborate some new chemical compounds, that may work as an efficient cure.

Several hypotheses are dedicated to the Alzheimer’s disease development. One of the most common is the so-called amyloid hypothesis.

Amyloids (to be precise, beta-amyloid peptides) are molecular constructions of a protein type and in its normal healthy state they provide a protection to the brain cells. They live fast, and having fulfilled their function they fall prey to the work of proteases, the cleaning enzymes that cut all the used protein elements into harmless ‘slags’ that are further reclaimed or removed from a body. However, according to the amyloid hypothesis, at some point something goes wrong, and the cells’ protectors turn to be their killers. Moreover, those peptides start gathering, forming aggregations and hence getting out of the reach of proteases’ cutting blades. Within the amyloid hypothesis this mechanism is more or less precisely described on the later stages of the disease, when the toxic aggregations appeared already and further, when the brain is covered with amyloid plaques. However, the early stage of a beta-amyloid transformation into harmful organic products is highly unexplored.

‘We knew, for example, that a crucial role in initiation of such processes is played by ions of several transition metals, first of all — zinc,’ tells Vladimir Polshakov. ‘Zinc actually conducts a number of useful and healthy functions in a brain, though in this case it was reasonably suspected as a ‘pest’, and particularly as an initiator of a cascade of processes, leading to theAlzheimer’sdisease. However, it remained unclear, what exactly happens during an interaction of zin? ions with peptide molecules, which amino acids bind zinc ions, and how such interaction stipulates a peptide aggregation. We set a goal to clarify at least some of those questions’.

Scientists studied various pathogenic beta-amyloid peptides, their so-called metal binding domains — relatively short peptide regions, capable to bind metal ions. A number of experimental techniques were applied, including nuclear magnetic resonance (NMR) spectroscopy, used to determine the structure of the forming molecular complexes. Some spectra requiring higher sensitivity were additionally measured in London. According to Polshakov, the choice of the studied pathogens was ‘partly a luck’. One of the specimens was the product of so-called ‘English mutation’ — peptide, different from a common beta-amyloid peptide only with one amino acid substitution. Using the NMR spectroscopy scientists managed to sort out chemical processes and structural changes while a peptide molecules interact with zinc ion and undergo further aggregation.

The second pathogen was an isomerized beta-amyloid peptide. It was not different from a normal one in its chemical composition, though one of its amino acid residues, aspartic acid, was in a form with a specific atomic positioning. Such isomerism happens spontaneously, without help of any enzymes, and is related to the ageing processes, another influential factor of the Alzheimer’s disease. Fellow biologists from the Moscow’s Institute of Molecular Biology showed recently, that administration of an isomerized peptide to transgenic mice led to an accelerated formation of amyloid plaques. With the presence of zinc ions, a metal binding domain of the isomerized peptide aggregated so fast that the forming structures were hard to detect. Though scientists managed to distinguish that despite all the differences in processes occurring to the ‘English mutant’ and isomerized peptide in presence of zinc ions, initial stages of these transformations were similar. The trigger happened to be the same — a role of a pathogenic aggregation’s seed was in both cases played by initially formed peptide dimers, i.e. two peptide molecules, connected to each other with help of zinc ion. Such dimers were also detected in normal human peptides, and the difference in all the studied forms could be explained by the speed of formation of corresponding dimer and its proneness to a further aggregation.

Based on their findings, researches proposed the mechanism of zinc-controlled transformation of a peptide-protector into a peptide-killer. That mechanism, scientists notice, explains multiple experimental data, not only gathered by the group, but also collected by their colleagues in other laboratories preoccupied with the Alzheimer’s disease studies. Researchers also hope that thanks to a very certain targeting their discovery would help to produce new medicine capable to block beta-amyloid peptide aggregation stipulated by zinc ions.

 

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Voluntary and Involuntary S- Insufficiency

Writer and Curator: Larry H Bernstein, MD, FCAP 

Transthyretin and the Stressful Condition

Introduction

This article is written among a series of articles concerned with stress, obesity, diet and exercise, as well as altitude and deep water diving for extended periods, and their effects.  There is a reason that I focus on transthyretin (TTR), although much can be said about micronutients and vitamins, and fat soluble vitamins in particular, and iron intake during pregnancy.    While the importance of vitamins and iron are well accepted, the metabolic basis for their activities is not fully understood.  In the case of a single amino acid, methionine, it is hugely important because of the role it plays in sulfur metabolism, the sulfhydryl group being essential for coenzyme A, cytochrome c, and for disulfide bonds.  The distribution of sulfur, like the distribution of iodine, is not uniform across geographic regions.  In addition, the content of sulfur found in plant sources is not comparable to that in animal protein.  There have been previous articles at this site on TTR, amyloid and sepsis.

Transthyretin and Lean Body Mass in Stable and Stressed State

https://pharmaceuticalintelligence.com/2013/12/01/transthyretin-and-lean-body-mass-in-stable-and-stressed-state/

A Second Look at the Transthyretin Nutrition Inflammatory Conundrum

https://pharmaceuticalintelligence.com/2012/12/03/a-second-look-at-the-transthyretin-nutrition-inflammatory-conundrum/

Stabilizers that prevent transthyretin-mediated cardiomyocyte amyloidotic toxicity

https://pharmaceuticalintelligence.com/2013/12/02/stabilizers-that-prevent-transthyretin-mediated-cardiomyocyte-amyloidotic-toxicity/

Thyroid Function and Disorders

https://pharmaceuticalintelligence.com/2015/02/05/thyroid-function-and-disorders/

Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation: a Compilation of Articles in the Journal http://pharmaceuticalintelligence.com

https://pharmaceuticalintelligence.com/2014/09/01/compilation-of-references-in-leaders-in-pharmaceutical-intelligence-about-proteomics-metabolomics-signaling-pathways-and-cell-regulation-2/

Malnutrition in India, high newborn death rate and stunting of children age under five years

https://pharmaceuticalintelligence.com/2014/07/15/malnutrition-in-india-high-newborn-death-rate-and-stunting-of-children-age-under-five-years/

Vegan Diet is Sulfur Deficient and Heart Unhealthy

https://pharmaceuticalintelligence.com/2013/11/17/vegan-diet-is-sulfur-deficient-and-heart-unhealthy/

How Methionine Imbalance with Sulfur-Insufficiency Leads to Hyperhomocysteinemia

https://pharmaceuticalintelligence.com/2013/04/04/sulfur-deficiency-leads_to_hyperhomocysteinemia/

Amyloidosis with Cardiomyopathy

https://pharmaceuticalintelligence.com/2013/03/31/amyloidosis-with-cardiomyopathy/

Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

https://pharmaceuticalintelligence.com/2012/10/22/advances-in-separations-technology-for-the-omics-and-clarification-of-therapeutic-targets/

Sepsis, Multi-organ Dysfunction Syndrome, and Septic Shock: A Conundrum of Signaling Pathways Cascading Out of Control

https://pharmaceuticalintelligence.com/2012/10/13/sepsis-multi-organ-dysfunction-syndrome-and-septic-shock-a-conundrum-of-signaling-pathways-cascading-out-of-control/

Automated Inferential Diagnosis of SIRS, sepsis, septic shock

https://pharmaceuticalintelligence.com/2012/08/01/automated-inferential-diagnosis-of-sirs-sepsis-septic-shock/

Transthyretin and the Systemic Inflammatory Response 

Transthyretin has been widely used as a biomarker for identifying protein-energy malnutrition (PEM) and for monitoring the improvement of nutritional status after implementing a nutritional intervention by enteral feeding or by parenteral infusion. This has occurred because transthyretin (TTR) has a rapid removal from the circulation in 48 hours and it is readily measured by immunometric assay. Nevertheless, concerns have been raised about the use of TTR in the ICU setting, which prompts a review of the actual benefit of using this test in a number of settings. TTR is easily followed in the underweight and the high risk populations in an ambulatory setting, which has a significant background risk of chronic diseases.  It is sensitive to the systemic inflammatory response syndrom (SIRS), and needs to be understood in the context of acute illness to be used effectively. There are a number of physiologic changes associated with SIRS and the injury/repair process that will affect TTR and will be put in context in this review. The most important point is that in the context of an ICU setting, the contribution of TTR is significant in a complex milieu.  copyright @ Bentham Publishers Ltd. 2009.

Transthyretin as a marker to predict outcome in critically ill patients.
Arun Devakonda, Liziamma George, Suhail Raoof, Adebayo Esan, Anthony Saleh, Larry H. Bernstein.
Clin Biochem Oct 2008; 41(14-15): 1126-1130

A determination of TTR level is an objective method od measuring protein catabolic loss of severly ill patients and numerous studies show that TTR levels correlate with patient outcomes of non-critically ill patients. We evaluated whether TTR level correlates with the prevalence of PEM in the ICUand evaluated serum TTR level as an indicator of the effectiveness of nutrition support and the prognosis in critically ill patients.

TTR showed excellent concordance with patients classified with PEM or at high malnutrition risk, and followed for 7 days, it is a measure of the metabolic burden. TTR levels did not respond early to nutrition support because of the delayed return to anabolic status. It is particularly helpful in removing interpretation bias, and it is an excellent measure of the systemic inflammatory response concurrent with a preexisting state of chronic inanition.

 The Stressful Condition as a Nutritionally Dependent Adaptive Dichotomy

Yves Ingenbleek and Larry Bernstein
Nutrition 1999;15(4):305-320 PII S0899-9007(99)00009-X

The injured body manifests a cascade of cytokine-induced metabolic events aimed at developing defense mechanisms and tissue repair. Rising concentrations of counterregulatory hormones work in concert with cytokines to generate overall insulin and insulin-like growth factor 1 (IGF-1), postreceptor resistance and energy requirements grounded on lipid dependency. Dalient features are self-sustained hypercortisolemia persisting as long as cytokines are oversecreted and down-regulation of the hypothalamo-pituitary-thyroid axis stabilized at low basal levels. Inhibition of thyroxine 5’deiodinating activity (5’DA) accounts for the depressed T3 values associated with the sparing of both N and energy-consuming processes. Both the liver and damaged territories adapt to stressful signals along up-regulated pathways disconnected from the central and peripheral control systems. Cytokines stimulate 5’DA and suppress the synthesis of TTR, causing the drop of retinol-binding protein (RBP) and the leakage of increased amounts of T4 and retinol in free form. TTR and RBP thus work as prohormonal reservoirs of precursor molecules which need to be converted into bioactive derivatives (T3 and retinoic acids) to reach transcriptional efficiency. The converting steps (5’DA and cellular retinol-binding protein-1) are activated to T4 and retinol, themselves operating as limiting factors to positive feedback loops. …The suicidal behavior of TBG, CBG, and IGFBP-3 allows the occurrence of peak endocrine and mitogenic influences at the site of inflammation. The production rate of TTR by the liver is the main determinant of both the hepatic release and blood transport of holoRBP, which explains why poor nutritional status concomitantly impairs thyroid- and retinoid-dependent acute phase responses, hindering the stressed body to appropriately face the survival crisis.  …
abbreviations: TBG, thyroxine-binding globulain; CBG, cortisol-binding globulin; IGFBP-3, insulin growth factor binding protein-3; TTR, transthyretin; RBP, retionol-binding protein.

Why Should Plasma Transthyretin Become a Routine Screening Tool in Elderly Persons? 

Yves Ingenbleek.
J Nutrition, Health & Aging 2009.

The homotetrameric TTR molecule (55 kDa as MM) was first identified in cerebrospinal fluid (CSF).  The initial name of prealbumin (PA)  was assigned based on the electrophoretic migration anodal to albumin. PA was soon recognized as a specific binding protein for thyroid hormone. and also of plasma retinol through the mediation of the small retinol-binding protein (RBP, 21 kDa as MM), which has a circulating half-life half that of TTR (24 h vs 48 h).

There exist at least 3 goos reasons why TTR should become a routine medical screening test in elderly persons.  The first id grounded on the assessment of protein nutritional status that is frequently compromized and may become a life threatening condition.  TTR was proposed as a marker of protein-energy malnutrition (PEM) in 1972. As a result of protein and energy deprivation, TTR hepatic synthesis is suppressed whereas all plasma indispensable amino acids (IAAs) manifest declining trends with the sole exception of methionine (Met) whose concentration usually remains unmodified. By comparison with ALB and transferrin (TF) plasma values, TTR did reveal a much higher degree of reactivity to changes in protein status that has been attributed to its shorter biological half-life and to its unusual tryptophan richness. The predictive ability of outcome offered by TTR is independent of that provided by ALB and TF. Uncomplicated PEM primarily affects the size of body nitrogen (N) pools, allowing reduced protein syntheses to levels compatible with survival.  These adaptiver changes are faithfully identified by the serial measurement of TTR whose reliability has never been disputed in protein-depleted states. On the contrary, the nutritional relevance of TTR has been controverted in acute and chronic inflammatory conditions due to the cytokine-induced transcriptional blockade of liver synthesis which is an obligatory step occurring independently from the prevailing nutritional status. Although PEM and stress ful disorders refer to distinct pathogenic mechanisms, their combined inhibitory effects on TTR liber production fueled a long-lasting strife regarding a poor specificity.  Recent body compositional studies have contributed to disentagling these intermingled morbidities, showing that evolutionary patterns displayed by plasma TTR are closely correlated with the fluctuations of lean body mass (LBM).

The second reason follows from advances describing the unexpected relationship established between TTR and homocysteine (Hcy), a S-containing AA not found in customary diets but resulting from the endogenous transmethylation of dietary methionine.  Hcy may be recycled to Met along a remethylation pathway (RM) or irreversibly degraded throughout the transsulfuration (TS) cascade to relase sulfaturia as end-product. Hcy is thus situated at the crossrad of RM and TS pathways which are in equilibrium keeping plasma Met values unaltered.  Three dietary water soluble B viatamins are implicated in the regulation of the Hcy-Met cycle. Folates (vit B9) are the most powerful agent, working as a supplier of the methyl group required for the RM process whereas cobalamines (vit B12) and pyridoxine (vit B6) operate as cofactors of Met-synthase and cystathionine-β-synthase.  Met synthase promotes the RM pathway whereas the rate-limiting CβS governs the TS degradative cascade. Dietary deficiency in any of the 3 vitamins may upregulate Hcy plasma values, an acquied biochemiucal anomaly increasingly encountered in aged populations.

The third reason refers to recent and fascinating data recorded in neurobiology and emphasizing the specific properties of TTR in the prevention of brain deterioration. TTR participates directly in the maintenance of memory and normal cognitive processes during the aging process by acting on the retinoid signaling pathway.  Moreover, TTR may bind amyloid β peptide in vitro, preventing its transformation into toxic amyloid fibrils and amyloid plaques.  TTR works as a limiting factor for the plasma transport of retinoid, which in turn operates as a limiting determinant of both physiologically active retinoic acid (RA) derivatives, implying that any fluctuation in protein status might well entail corresponding  alterations in cellular bioavailability of retinoid compounds.  Under normal aging circumstances, the concentration of retinoid compounds declines in cerebral tissues together with the downregulation of RA receptor expression. In animal models, depletion of RAs causes the deposition of amyloid-β peptides, favoring the formation of amyloid plaques.

Prealbumin and Nutritional Evaluation

Larry Bernstein, Walter Pleban
Nutrition Apr 1996; 12(4):255-259.
http://nutritionjrnl.com/article/S0899-9007(96)90852-7

We compressed 16-test-pattern classes of albumin (ALB), cholesterol (CHOL), and total protein (TPR) in 545 chemistry profiles to 4 classes by conveerting decision values to a number code to separate malnourished (1 or 2) from nonmalnourished (NM)(0) patients using as cutoff values for NM (0), mild (1), and moderate (2): ALB 35, 27 g/L; TPR 63, 53 g/L; CHOL 3.9, 2.8 mmol/L; and BUN 9.3, 3.6 mmol/L. The BUN was found to have  to have too low an S-value to make a contribution to the compressed classification. The cutoff values for classifying the data were assigned prior to statistical analysis, after examining information in the structured data. The data was obtained by a natural experiment in which the test profiles routinely done by the laboratory were randomly extracted. The analysis identifies the values used that best classify the data and are not dependent on distributional assumptions. The data were converted to 0, 1, or 2 as outcomes, to create a ternary truth table (eaxch row in nnn, the n value is 0 to 2). This allows for 3(81) possible patterns, without the inclusion of prealbumin (TTR). The emerging system has much fewer patterns in the information-rich truth table formed (a purposeful, far from random event). We added TTR, coded, and examined the data from 129 patients. The classes are a compressed truth table of n-coded patterns with outcomes of 0, 1, or 2 with protein-energy malnutrition (PEM) increasing from an all-0 to all-2 pattern.  Pattern class (F=154), PAB (F=35), ALB (F=56), and CHOL (F=18) were different across PEM class and predicted PEM class (R-sq. = 0.7864, F=119, p < E-5). Kruskall-Wallis analysis of class by ranks was significant for pattern class E-18), TTR (6.1E-15) ALB (E-16), CHOL (9E-10), and TPR (5E-13). The medians and standard error (SEM) for TTR, ALB, and CHOL of four TTR classes (NM, mild, mod, severe) are: TTR = 209, 8.7; 159, 9.3; 137, 10.4; 72, 11.1 mg/L. ALB – 36, 0.7; 30.5, 0.8; 25.0, 0.8; 24.5, 0.8 g/L. CHOL = 4.43, 0.17; 4.04, 0.20; 3.11, 0.21; 2.54, 0.22 mmol/L. TTR and CHOL values show the effect of nutrition support on TTR and CHOL in PEM. Moderately malnourished patients receiving nutrition support have TTR values in the normal range at 137 mg/L and at 159 mg/L when the ALB is at 25 g/L or at 30.5 g/L.

An Informational Approach to Likelihood of Malnutrition 

Larry Bernstein, Thomas Shaw-Stiffel, Lisa Zarney, Walter Pleban.
Nutrition Nov 1996;12(11):772-776.  PII: S0899-9007(96)00222-5.
http://dx.doi.org:/nutritionjrnl.com/article/S0899-9007(96)00222-5

Unidentified protein-energy malnutrition (PEM) is associated with comorbidities and increased hospital length of stay. We developed a model for identifying severe metabolic stress and likelihood of malnutrition using test patterns of albumin (ALB), cholesterol (CHOL), and total protein (TP) in 545 chemistry profiles…They were compressed to four pattern classes. ALB (F=170), CHOL (F = 21), and TP (F = 5.6) predicted PEM class (R-SQ = 0.806, F= 214; p < E^-6), but pattern class was the best predictor (R-SQ = 0.900, F= 1200, p< E^-10). Ktuskal-Wallis analysis of class by ranks was significant for pattern class (E^18), ALB (E^-18), CHOL (E^-14), TP (@E^-16). The means and SEM for tests in the three PEM classes (mild, mod, severe) were; ALB – 35.7, 0.8; 30.9, 0.5; 24.2, 0.5 g/L. CHOL – 3.93, 0.26; 3.98, 0.16; 3.03, 0.18 µmol/L, and TP – 68.8, 1.7; 60.0, 1.0; 50.6, 1.1 g/L. We classified patients at risk of malnutrition using truth table comprehension.

Downsizing of Lean Body Mass is a Key Determinant of Alzheimer’s Disease

Yves Ingenbleek, Larry Bernstein
J Alzheimer’s Dis 2015; 44: 745-754.
http://dx.doi.org:/10.3233/JAD-141950

Lean body mass (LBM) encompasses all metabolically active organs distributed into visceral and structural tissue compartments and collecting the bulk of N and K stores of the human body. Transthyretin (TTR)  is a plasma protein mainly secreted by the liver within a trimolecular TTR-RBP-retinol complex revealing from birth to old age strikingly similar evolutionary patterns with LBM in health and disease. TTR is also synthesized by the choroid plexus along distinct regulatory pathways. Chronic dietary methionine (Met) deprivation or cytokine-induced inflammatory disorders generates LBM downsizing following differentiated physiopathological processes. Met-restricted regimens downregulate the transsulfuration cascade causing upstream elevation of homocysteine (Hcy) safeguarding Met homeostasis and downstream drop of hydrogen sulfide (H2S) impairing anti-oxidative capacities. Elderly persons constitute a vulnerable population group exposed to increasing Hcy burden and declining H2S protection, notably in plant-eating communities or in the course of inflammatory illnesses. Appropriate correction of defective protein status and eradication of inflammatory processes may restore an appropriate LBM size allowing the hepatic production of the retinol circulating complex to resume, in contrast with the refractory choroidal TTR secretory process. As a result of improved health status, augmented concentrations of plasma-derived TTR and retinol may reach the cerebrospinal fluid and dismantle senile amyloid plaques, contributing to the prevention or the delay of the onset of neurodegenerative events in elderly subjects at risk of Alzheimer’s disease.

Amyloidogenic and non-amyloidogenic transthyretin variants interact differently with human cardiomyocytes: insights into early events of non-fibrillar tissue damage

Pallavi Manral and Natalia Reixach
Biosci.Rep.(2015)/35/art:e00172 http://dx.doi.org:/10.1042/BSR20140155

TTR (transthyretin) amyloidosis are diseases characterized by the aggregation and extracellular deposition of the normally soluble plasma protein TTR. Ex vivo and tissue culture studies suggest that tissue damage precedes TTR fibril deposition, indicating that early events in the amyloidogenic cascade have an impact on disease development. We used a human cardiomyocyte tissue culture model system to define these events. We previously described that the amyloidogenic V122I TTR variant is cytotoxic to human cardiac cells, whereas the naturally occurring, stable and non-amyloidogenic T119M TTR variant is not. We show that most of the V122I TTR interacting with the cells is extracellular and this interaction is mediated by a membraneprotein(s). In contrast, most of the non-amyloidogenic T119M TTR associated with the cells is intracellular where it undergoes lysosomal degradation. The TTR internalization process is highly dependent on membrane cholesterol content. Using a fluorescent labelled V122I TTR variant that has the same aggregation and cytotoxic potential as the native V122I TTR, we determined that its association with human cardiomyocytes is saturable with a KD near 650nM. Only amyloidogenic V122I TTR compete with fluorescent V122I force ll-binding sites. Finally, incubation of the human cardiomyocytes with V122I TTR but not with T119M TTR, generates superoxide species and activates caspase3/7. In summary, our results show that the interaction of the amyloidogenic V122I TTR is distinct from that of a non-amyloidogenic TTR variant and is characterized by its retention at the cell membrane, where it initiates the cytotoxic cascade.

Emerging roles for retinoids in regeneration and differentiation in normal and disease states

Lorraine J. Gudas
Biochimica et Biophysica Acta 1821 (2012) 213–221
http://dx.doi.org:/10.1016/j.bbalip.2011.08.002

The vitamin (retinol) metabolite, all-transretinoic acid (RA), is a signaling molecule that plays key roles in the development of the body plan and induces the differentiation of many types of cells. In this review the physiological and pathophysiological roles of retinoids (retinol and related metabolites) in mature animals are discussed. Both in the developing embryo and in the adult, RA signaling via combinatorial Hoxgene expression is important for cell positional memory. The genes that require RA for the maturation/differentiation of T cells are only beginning to be cataloged, but it is clear that retinoids play a major role in expression of key genes in the immune system. An exciting, recent publication in regeneration research shows that ALDH1a2(RALDH2), which is the rate-limiting enzyme in the production of RA from retinaldehyde, is highly induced shortly after amputation in the regenerating heart, adult fin, and larval fin in zebrafish. Thus, local generation of RA presumably plays a key role in fin formation during both embryogenesis and in fin regeneration. HIV transgenic mice and human patients with HIV-associated kidney disease exhibit a profound reduction in the level of RARβ protein in the glomeruli, and HIV transgenic mice show reduced retinol dehydrogenase levels, concomitant with a greater than 3-fold reduction in endogenous RA levels in the glomeruli. Levels of endogenous retinoids (those synthesized from retinol within cells) are altered in many different diseases in the lung, kidney, and central nervous system, contributing to pathophysiology.

The Membrane Receptor for Plasma Retinol-Binding Protein, A New Type of Cell-Surface Receptor

Hui Sun and Riki Kawaguchi
Intl Review Cell and Molec Biol, 2011; 288:Chap 1. Pp 1:34
http://dx.doi.org:/10.1016/B978-0-12-386041-5.00001-7

Vitamin A is essential for diverse aspects of life ranging from embryogenesis to the proper functioning of most adul torgans. Its derivatives (retinoids) have potent biological activities such as regulating cell growth and differentiation. Plasma retinol-binding protein (RBP) is the specific vitamin A carrier protein in the blood that binds to vitamin A with high affinity and delivers it to target organs. A large amount of evidence has accumulated over the past decades supporting the existence of a cell-surface receptor for RBP that mediates cellular vitamin A uptake. Using an unbiased strategy, this specific cell-surface RBP receptor has been identified as STRA6, a multi-transmembrane domain protein with previously unknown function. STRA6 is not homologous to any protein of known function and represents a new type of cell-surface receptor. Consistent with the diverse functions of vitamin A, STRA6 is widely expressed in embryonic development and in adult organ systems. Mutations in human STRA6 are associated with severe pathological phenotypes in many organs
such as the eye, brain, heart, and lung. STRA6 binds to RBP with high affinity and mediates vitamin A uptake into cells. This review summarizes the history of the RBP receptor research, its expression in the context of known functions of vitamin A in distinct human organs, structure/function analysis of this new type of membrane receptor, pertinent questions regarding its very existence, and its potential implication in treating human diseases.

Choroid plexus dysfunction impairs beta-amyloid clearance in a triple transgenic mouse model of Alzheimer’s disease

Ibrahim González-Marrero, Lydia Giménez-Llort, Conrad E. Johanson, et al.
Front Cell Neurosc  Feb2015; 9(17): 1-10
http://dx.doi.org:/10.3389/fncel.2015.00017

Compromised secretory function of choroid plexus (CP) and defective cerebrospinal fluid (CSF) production, along with accumulation of beta-amyloid (Aβ) peptides at the blood-CSF barrier (BCSFB), contribute to complications of Alzheimer’s disease (AD). The AD triple transgenic mouse model (3xTg-AD) at 16 month-old mimics critical hallmarks of the human disease: β-amyloid (Aβ) plaques and neurofibrillary tangles (NFT) with a temporal-and regional-specific profile. Currently, little is known about transport and metabolic responses by CP to the disrupted homeostasis of CNS Aβ in AD. This study analyzed the effects of highly-expressed AD-linked human transgenes (APP, PS1 and tau) on lateral ventricle CP function. Confocal imaging and immunohistochemistry revealed an increase only of Aβ42 isoform in epithelial cytosol and in stroma surrounding choroidal capillaries; this buildup may reflect insufficient clearance transport from CSF to blood. Still, there was increased expression, presumably compensatory, of the choroidal Aβ transporters: the low density lipoprotein receptor-related protein1 (LRP1) and the receptor for advanced glycation end product (RAGE). A thickening of the epithelial basal membrane and greater collagen-IV deposition occurred around capillaries in CP, probably curtailing solute exchanges. Moreover, there was attenuated expression of epithelial aquaporin-1 and transthyretin(TTR) protein compared to Non-Tg mice. Collectively these findings indicate CP dysfunction hypothetically linked to increasing Aβ burden resulting in less efficient ion transport, concurrently with reduced production of CSF (less sink action on brain Aβ) and diminished secretion of TTR (less neuroprotection against cortical Aβ toxicity). The putative effects of a disabled CP-CSF system on CNS functions are discussed in the context of AD.

Endoplasmic reticulum: The unfolded protein response is tangled In neurodegeneration

Jeroen J.M. Hoozemans, Wiep Scheper
Intl J Biochem & Cell Biology 44 (2012) 1295–1298
http://dx.doi.org/10.1016/j.biocel.2012.04.023

Organelle facts•The ER is involved in the folding and maturation ofmembrane-bound and secreted proteins.•The ER exerts protein quality control to ensure correct folding and to detect and remove misfolded proteins.•Disturbance of ER homeostasis leads to protein misfolding and induces the UPR.•Activation of the UPR is aimed to restore proteostasis via an intricate transcriptional and (post)translational signaling network.•In neurodegenerative diseases classified as tauopathies the activation of the UPR coincides with the pathogenic accumulation of the microtubule associated protein tau.•The involvement of the UPR in tauopathies makes it a potential therapeutic target.

The endoplasmic reticulum (ER) is involved in the folding and maturation of membrane-bound and secreted proteins. Disturbed homeostasis in the ER can lead to accumulation of misfolded proteins, which trigger a stress response called the unfolded protein response (UPR). In neurodegenerative diseases that are classified as tauopathies, activation of the UPR coincides with the pathogenic accumulation of the microtubule associated protein tau. Several lines of evidence indicate that UPR activation contributes to increased levels of phosphorylated tau, a prerequisite for the formation of tau aggregates. Increased understanding of the crosstalk between signaling pathways involved in protein quality control in the ERand tau phosphorylation will support the development of new therapeutic targets that promote neuronal survival.

Chemical and/or biological therapeutic strategies to ameliorate protein misfolding diseases

Derrick Sek Tong Ong and Jeffery W Kelly
Current Opin Cell Biol 2011; 23:231–238
http://dx.doi.org:/10.1016/j.ceb.2010.11.002

Inheriting a mutant misfolding-prone protein that cannot be efficiently folded in a given cell type(s) results in a spectrum of human loss-of-function misfolding diseases. The inability of the biological protein maturation pathways to adapt to a specific misfolding-prone protein also contributes to pathology. Chemical and biological therapeutic strategies are presented that restore protein homeostasis, or proteostasis, either by enhancing the biological capacity of the proteostasis network or through small molecule stabilization of a specific misfolding-prone protein. Herein, we review the recent literature on therapeutic strategies to ameliorate protein misfolding diseases that function through either of these mechanisms, or a combination thereof, and provide our perspective on the promise of alleviating protein misfolding diseases by taking advantage of proteostasis adaptation.

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Reporter and curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/12-2-2013/larryhbern/Stabilizers that prevent transthyretin-mediated cardiomyocyte amyloidotic toxicity

Transthyretin is a small protein with a half-life of < 48 hours, synthesized by the liver, and a major transport protein for thyroxin.  There are 80 variants known, and some variants that occur in the Portuguese, a small section of Japan, Sweden, and Brazil, are associated will primary amyloidosis, the only cure for which is liver transplantation.  It causes fibrillary inclusions in the heart, but also affects the autonomic nervous system.  Some of the major work on this has been done for many years in the laboratory of   Jeffery W. Kelly, at the Skaggs Institue for Chemical Biology, the Scripps Research Institute.  A recent publication is of considerable interest.

Potent Kinetic Stabilizers that Prevent Transthyretin-mediated Cardiomyocyte Proteotoxicity

 Mamoun M. Alhamadsheh1,6,7, Stephen Connelly2,7, Ahryon Cho1, Natàlia Reixach3, Evan T. Powers3,4,5, Dorothy W. Pan1, Ian A. Wilson2,5, Jeffery W. Kelly3,4,5, and Isabella A. Graef1,*
Sci Transl Med. Author manuscript; available in PMC 2012 August 24.
1Department of Pathology, Stanford University Medical School, Stanford, California, USA
2Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA
3Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California, USA
4Department of Chemistry, The Scripps Research Institute, La Jolla, California, USA
5The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, California, USA
6Department of Pharmaceutics & Medicinal Chemistry, University of the Pacific, Stockton, California, USA

Abstract

The V122I mutation that alters the stability of transthyretin (TTR) affects 3–4% of African Americans and leads to amyloidogenesis and development of cardiomyopathy. In addition, 10–15% of individuals over the age of 65 develop senile systemic amyloidosis (SSA) and cardiac
TTR deposits due to wild-type TTR amyloidogenesis. As no approved therapies for TTR amyloid cardiomyopathy are available, the development of drugs that prevent amyloid-mediated cardiotoxicity is desired. To this aim, we developed a fluorescence polarization-based HTS screen,
which identified several new chemical scaffolds targeting TTR. These novel compounds were potent kinetic stabilizers of TTR and
  • prevented tetramer dissociation,
  • unfolding and aggregation of both wild type and the most common cardiomyopathy-associated TTR mutant, V122I-TTR.
High-resolution co-crystal structures and characterization of the binding energetics revealed how these diverse structures bound to tetrameric TTR. Our study also showed that these compounds effectively inhibited the proteotoxicity of V122I-TTR towards human cardiomyocytes.
Several of these ligands stabilized TTR in human serum more effectively than diflunisal, which is one of the best known inhibitors of TTR aggregation, and may be promising leads for the treatment and/or prevention of TTR-mediated cardiomyopathy.

Author Contributions:

M.M.A. designed and performed most experiments, S.C. performed crystallographic structure determination, A.C peformed the serum TTR stabilization. N.R. performed the cell-based assays.   E.T.P. analyzed the ITC data. D.W.P. helped with probe synthesis. I.A.W. supervised the crystallographic work. J.W.K. supervised the work, S.C., N.R., I.A.W. and J.W.K. edited the paper. I.A.G supervised the work, M.M.A. and I.A.G prepared the manuscript.

 INTRODUCTION

The misassembly of soluble proteins into toxic amyloid aggregates underlies a large number of human degenerative diseases (1–3). TTR is one of more than 30 human amyloidogenic proteins whose misassembly can cause
  • a variety of degenerative gain-of-toxic-function diseases.
TTR is a tetrameric protein (54 kDa), secreted from the liver into the blood where, using orthogonal sites,
  • it transports thyroxine (T4) and
  • holo-retinol binding protein (4).
However, 99% of the TTR T4 binding sites remain unoccupied in humans
  • owing to the presence of two other T4 transport proteins in blood (3).
Familial TTR amyloid diseases, which are associated with one of more than 80 mutations in the TTR gene, include
  • the systemic neuropathies (familial amyloid polyneuropathy [FAP]),
  • cardiomyopathies (familial amyloid cardiomyopathy [FAC]), and
  • central nervous system amyloidoses (CNSA) (5–8).
Cardiac amyloidosis is most commonly caused by
  • deposition of immunoglobulin light chains or
  • TTR in the cardiac interstitium and conducting system.
It is a chronic and progressive condition, which can lead to arrhythmias, biventricular heart failure, and death (8–10). Two types of TTR-associated amyloid cardiomyopathies are clinically important.
  1. Wild-type (WT) TTR aggregation underlies the development of senile systemic amyloidosis (SSA). Cardiac TTR deposits can be found in 10 to 15% of the population over the age of 65 at autopsy (10,11). Many of these patients are asymptomatic, but there is little doubt that SSA is an underdiagnosed disease.
  2. In addition, a number of TTR mutations, including V122I, lead to amyloidogenesis and familial amyloid cardiomyopathy (FAC) (12–15). Population studies show that the V122I mutation is found in 3–4% of African Americans (~1.3 million people) and contributes to the increased prevalence of heart failure among this population segment (14,15).

The mutant TTR allele behaves as an autosomal dominant allele with age-dependent penetrance and

  • the frequency of cardiac amyloidosis from TTR in African-American individuals above age 60 is four times that seen in Caucasian-Americans of comparable age.
All of the TTR mutations associated with familial amyloidosis decrease tetramer stability, and
  • some decrease the kinetic barrier for tetramer dissociation (3, 16).
  • The latter is important because tetramer dissociation is the rate-limiting step in the TTR amyloidogenesis cascade (3).

Kinetic stabilization of the native, tetrameric structure of TTR by

  • interallelic trans suppression (incorporation of mutant subunits that raise the dissociative transition state energy) prevents
    1. post-secretory dissociation and aggregation, as well as the related disease 
    2. familial amyloid polyneuropathy (FAP), by slowing TTR tetramer dissociation (17).
Occupancy of the TTR T4 binding sites with rationally designed small molecules is known to stabilize the native tetrameric state of TTR over the dissociative transition state,
  • raising the kinetic barrier,
  • imposing kinetic stabilization on the tetramer and
  • preventing amyloidogenesis (3, 16, 18).
Previous studies have focused on rational ligand design and as a result
  • most of the TTR stabilizers reported to date are halogenated biaryl analogues of T4,
  • many resembling non-steroidal anti-inflammatory drugs (NSAIDs).
Some of these compounds, such as the NSAID diflunisal, which is currently tested in clinical trials in FAP patients for its efficacy to ameliorate
  • peripheral neuropathy resulting from TTR deposition, (19) have anti-inflammatory activity (20, 21).
The pharmacological effects of NSAIDs are due to inhibition of cyclo-oxygenase (COX) enzymes (22). Inhibition of COX-1 can produce side effects such as
  • gastrointestinal irritation, leading to ulcers and bleeding (23).
Inhibition of COX-2 has been associated with an
  • increased risk of severe cardiovascular events, including heart failure,
  • particularly in patients with preexisting cardiorenal dysfunction (20, 21, 24, 25).
Therefore, heart and kidney impairment are exclusion criteria for participation of patients in the diflunisal clinical trials to treat TTR-mediated FAP (19). Genomic variations can
  • increase the sensitivity of individuals to adverse side effects of NSAIDs.
Serum concentrations of NSAIDs depend on CYP2C9 and/or CYP2C8 activity. CYP2C9 polymorphism might play a significant role in the profile of adverse side effects of NSAID and alleles that affect the activity of CYP2C9 are found at different frequency in subjects of Caucasian, African or Asian descent (26, 27). Hence, the long-term therapy with drugs that have inhibitory effect on COX activity to prevent TTR aggregation is especially problematic in patients who suffer from TTR-mediated cardiomyopathy. The design and development of drugs to treat/prevent FAC or SSA thus presents the challenge
  1. not only to find compounds with a greater variety of chemical scaffolds that accomplish stabilization, but
  2. do so without the adverse side effects due to inhibition of COX activity.
 For these reasons, the development of a rapid and robust screen for compounds that bind to and stabilize TTR could be useful. To date, no high-throughput screening (HTS) methodology is available for the discovery of TTR ligands (28,29). Therefore, we developed a versatile
  • fluorescence polarization (FP) based HTS assay that can detect
  • binding of small molecules to the T4 binding pocket of TTR under physiological conditions.

RESULTS

Design and synthesis of the TTR FP probe

FP is used to study molecular interactions by monitoring changes in the apparent size of a fluorescently labeled molecule. Binding is measured by an increase in the FP signal, which is proportional to the decrease in the rate of tumbling of a fluorescent ligand upon association with macromolecules such as proteins (Fig. 1A). To synthesize a fluorescent TTR ligand 1, we initially started with the NSAID diflunisal analogue 2 (Fig. 1B) (30). The product of attaching a linker to 2, compound 3, had very low binding affinity to TTR (Kd1 >3290 nM, fig. S1A and fig. S1B).
The crystal structure of the diclofenac analog 4 showed that
  • the phenolic hydroxyl flanked by the two chlorine atoms is oriented out of the binding pocket into the solvent (31).
  • We reasoned that attaching a PEG amine linker to the phenol group of 4 would generate compound 5 which would bind to TTR (Fig. 1B and fig. S1C)

5 was coupled to fluorescein isothiocyanate (FITC) to produce the FITC-coupled TTR FP probe (1, Fig. 1B). The binding characteristics of the probe (Kd1 = 13 nM and Kd2 = 100 nM) were assessed with ITC (Fig. 2A).

Evaluation of the FP assay

The binding of 1 to TTR was evaluated to test its suitability for the FP assay with a standard saturation binding experiment. A fixed concentration of probe 1 (0.1 μM) was incubated with increasing concentrations of TTR (0.005 μM to 10 μM) and the formation of 1•TTR complex was quantified by the increase in FP signal (excitation λ 485 nm, emission λ 525 nm) relative to the concentration of TTR (Fig. 2B). The fluorescence polarization increased with the concentration of TTR until saturation was reached. A large dynamic range (70 – 330 mP) was measured for the assay. To validate the FP assay, we tested known TTR binders in a displacement assay (for detailed information see Supplemental Material). Compound 2 (Kapp = 231 nM, R2 = 0.997), Thyroxine (T4) (Kapp = 186 nM, R2 = 0.998) and diclofenac (Kapp = 4660 nM, R2 = 0.999) decreased the FP signal in a dose- dependent  manner  (Fig. 2C,  fig. S2B and S2C). The FP assay is a competitive displacement assay and therefore it provides apparent binding constants (Kapp). However, these apparent binding constants correlate well with the data obtained by ITC which measures direct interactions in solution and gives an actual (Kd) value.

  Adaptation of the FP assay for HTS

Next, we optimized the FP assay for HTS and screened a ~130,000 small molecule library for compounds that displaced probe 1 from the T4 binding sites of TTR. The FP assay was performed in 384-well plates with low concentrations of probe 1 (1.5 nM) and TTR (50 nM) in a 10  μL assay volume.  Detergent (0.01% Triton X-100) was added to the assay buffer to avoid false positive hits from aggregation of the small molecules. The assay demonstrated robust performance, with a, large dynamic range (~70–230 mP) and a Z′ factor (32, 33) in the range of 0.57–0.78 (fig. S3A and S3B).

Hits were defined as compounds, which resulted in at least 50% decrease in FP and demonstrated relative fluorescence between 70 and 130%. Many fluorescence quenchers and enhancers, which have less than 70% and greater than 130% total fluorescence relative to a control (compound without TTR), were excluded from the hit list. The excluded compounds have native fluorescence that is similar to fluorescein, which would interfere with the FP measurements and result in false positive hits. Two hundred compounds were designated as positive hits (0.167% hit rate). The top 33 compounds (compounds with lowest FP IC50) were assayed in a 10-point duplicate dose-response FP assay and displayed an IC50 (concentration that resulted in 50% decrease in the FP signal) between 0.277 and 10.957 μM (table S2).

Validation of the HTS hits

The top 33 compounds were retested with the FP assay (table S2) and with surface plasmon resonance (SPR) as another independent biophysical method. Solutions of the 33 hits were passed over immobilized, biotinylated TTR on a streptavidin coated chip. The binding of a small molecule to TTR on the sensor chip produces a SPR response signal (RU). The RU signal after addition of the top 33 compounds was measured and compared to a negative, solvent only, control. All compounds identified by the screen as hits were confirmed as TTR binders using SPR (fig. S4). We also found known TTR binders, such as NSAIDs (diclofenac, meclofenamic acid, and niflumic acid) and isoflavones (apigenin) in our screen (3, 34) (table S2). Among the best ligands (Fig. 2D) were the NSAID, niflumic acid, two catechol-O-methyl-tranferase (COMT) inhibitors, 3,5-dintrocatechol and Ro 41-0960 (35) and a number  of compounds   not previously known to bind to TTR. The chemical structures of these ligands were confirmed by 1H NMR and high-resolution mass spectrometry(HRMS) and the chemical purity was determined to be >95% (fig. S5).

Inhibition of TTR amyloidogenesis by the HTS hits

To test whether the new TTR ligands (7.2 μM) could function as kinetic stabilizers, we measured their ability to inhibit TTR (3.6 μM) amyloidogenesis at 72 hrs at pH 4.4 (fig. S6) (29). All 33 compounds inhibited TTR aggregation (<50% fibril formation, table S2). Of these, 23 were very good (<20% fibril formation) and 11 were excellent (<2% fibril formation) TTR kinetic stabilizers (Fig. 3A). All of the potent TTR stabilizers, except niflumic acid, and the two COMT inhibitors 3,5-dintrocatechol and Ro 41-0960, were chemical entities with no previously reported biological activity. Since occupancy of only
one T4 binding site within TTR is sufficient for kinetic stabilization of the tetramer (3), we tested the most potent ligands at substoichiometric concentrations (2.4 fold molar excess of TTR relative to ligand) in a kinetic aggregation assay monitored over 5 days (Fig. 3B). Under these conditions ligands 7, 14, 15 and Ro 41-0960 dramatically slowed fibril formation and outperformed the known TTR stabilizer, diclofenac, which blocked only ~55% of TTR aggregation.

Evaluating the TTR ligands for COX-1 enzymatic inhibition and binding to thyroid hormone receptor

A successful clinical candidate against TTR amyloid cardiomyopathy should have minimal off-target toxicity due to the potential need for life-long use of these drugs. Specifically, the TTR ligands should exhibit minimal binding to COX and the nuclear thyroid hormone receptor (THR). Inhibition of COX is contraindicated for treating FAC patients, since COX inhibition can not only lead to renal dysfunction and blood pressure elevation, but may precipitate heart failure in vulnerable individuals (20, 21, 24, 25). Therefore, the most potent TTR ligands were evaluated for their ability to inhibit COX-1 activity, as well as, for binding to THR, in comparison with the NSAID niflumic acid. Although niflumic acid exhibited substantial (94%) COX-1 inhibition, three of the 12 new compounds evaluated (7, 6 and 10) displayed less than 1% inhibition of COX-1. Only one ligand (compound 8) showed significant (58%) and two compounds (6 and 10) minor (5%) binding to THR (Fig. 3C).

Characterization of the binding energetics to TTR

Many reported TTR ligands, including T4, bind TTR with negative cooperativity, which appears to arise from subtle conformational changes in TTR upon ligand binding to the first T4 site (3, 16, 36). We used ITC to determine the binding constants and to evaluate cooperativity between the two TTR T4 sites (Fig. 2A, Fig. 4A, Fig. 4B and fig. S1 and fig. S7). The ITC data for compounds 1, 7, 14, and Ro 41-0906 binding to TTR were fit to a two-site binding model and show that these potent ligands bind TTR with low nanomolar affinity. The dissociation constants for these ligands indicated that they bound TTR with negative cooperativity (table S3). Analysis of the free energies associated with ligand binding to TTR indicates that binding was driven both by burial of the hydrophobic ligand in the TTR binding site (which leads to the favorable binding entropies) and specific ligand-TTR interactions (which leads to the favorable binding enthalpies) (Fig. 2A, Fig. 4A, Fig.4B, and fig. S7B) (37). The binding of compounds 7 (Kd1 = 58 nM and Kd2 = 500 nM) and 14 (Kd1 = 26 nM and Kd2 = 1800 nM) to TTR did not cause major conformational changes to the TTR tetramer structure (Fig. 5).
Remainder of document is found at publication site, including Figures.

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The role of biomarkers in the diagnosis of sepsis and patient management

Author: L. H. Bernstein, MD, FCAP

Key words: Systemic Inflammatory Response Syndrome (SIRS), sepsis, septic shock, mean arterial blood pressure (MAP), procalcitonin, combinatorial analysis, effect size

Highlights:
1.   The systemic inflammatory response syndrome (SIRS) is an acute response to trauma, burn, or infectious injury characterized by fever, hemodynamic and respiratory changes, and metabolic changes, not all of which are consistently present.

2.   The SIRS reaction involves hormonally driven changes in liver glycogen reserves, triggering of  lipolysis, lean body proteolysis, and reprioritization of hepatic protein synthesis with up-regulation of synthesis of acute phase proteins and down-regulation of albumin and important circulating transport proteins.

3.   Understanding of the processes leads to the identification of biomarkers for identification of sepsis and severe, moderate or early SIRS, which also can hasten treatment and recovery.

4.   The SIRS reaction unabated leads to a recurring cycle with hemodynamic collapse from septic shock, indistinguishable from cardiogenic shock, and death.

Abbreviations: Systemic Inflammatory Response Syndrome (SIRS), procalcitonin (PCT), C-reactive protein (CRP), mean arterial blood pressure (MAP), Intensive care unit (ICU), total white blood cell count (WBC), transthyretin(TTR)

Summary
By focusing on early and accurate diagnosis of infection in patients suspected of SIRS antibiotic overuse and its associated morbidity and mortality may be avoided, and therapeutic targets may be identified. This discussion investigates the performance of diagnostic algorithms and biomarkers for sepsis in patients presenting with leukocytosis and other findings. Suspected patients are usually identified by WBC above 12,000/mL  PCT level , SIRS and other criteria, such as serum biomarkers of sepsis. In this writer’s study of 435 patients, procalcitonin alone was a superior marker for sepsis. In patients with sepsis there was a marked increase in PCT (p = 0.0001). PCT was increased in patients requiring ICU admission, heart rate and blood pressure monitoring, and assisted ventilation.(p = 0.0001). Means for SIRS/non-SIRS were: CRP 802/404 mg/L; PCT 20.6/7.5 ng/mL; TTR 87.8/125 mg/L. A comprehensive overview of at least a decade of work is provided.

Introduction

Sepsis is a costly diagnosis in hospitalized patients and carries a high financial risk as a comorbidity and a payment penalty for failure to diagnose in a timely manner (1-4) under the severity of illness CMS reimbursement guidelines as a patient safety hazard, with pneumonia and sepsis among the ten most costly among hospital admissions. A polypeptide identical to a prohormone of calcitonin, procalcitonin, was initially described as a potential marker of bacterial disease by Assicot et al.(5). Procalcitonin is almost undetectable under physiological conditions (pg/ml range), but rises to very high values in response to bacteraemia or fungaemia, and appears to be related to the severity of infection.(6)  Sequential measurements in patients with bacteraemia have shown a rapid fall within 48 hours of antibiotic administration.

Is it an unlikely candidate sepsis biomarker? It is a precursor of calcitonin, and under ordinary circumstances can be accounted for by its production in the thyroid. It is widely produced extrathyroidally with sepsis. The main reason for such interest is the response seems to be uncoupled to the systemic inflammatory response, as CRP is.  What is it a response to? What is the role it has in primary cellular immune response? There is no question that it is found in very low level without serious infection, so that a low level would remove the necessity for a blood culture. In other words it predicts absence of sepsis. Is it fortuitous or serendipity?

On the other hand, we now refer to bacterial and abacterial sepsis. So there are a significant proportion of sepsis diagnoses for which cultures are negative. You might decide that the method of taking cultures x3 at different times and from different sites (not universally practiced) might account for the negative cultures. It was reported in the New York Times a week ago that a child came to the emergency room in a NY hospital with a simple sports injury abrasing the skin surface, was sent home, returned, and died in 24 hours. It’s not such an easy call, despite the result.

There have been numerous studies of the early recognition of sepsis and related diseases in patients related to admission and intensive care. The consensus  guideline has used a SIRS criteria (7, 8).  The SIRS criteria (7,8)  include temperature o C. >= 38o C., heart rate > 90 beats per minute, respiratory rate >20 breaths per minute or PaCO  < 32 mm of Hg, WBC > 12,000/mL or < 4,000/mL, or > 10% band forms. For the diagnosis of sepsis (2 or more SIRS criteria and confirmed or suspected infection) the SIRS criteria are insufficient with a very high false positive rate, so that there are medical institutions that require three.  The observation of fever, tachypnea, and tachycardia may well not be present early, and the observation of leukocytosis with or without band neutrophilia are unreliable.  The use of a plasma lactic acid measurement has been added, but it is basically a reflection of decreased splanchnic circulation to the superior mesenteric artery and liver bed.  A better case has been made for absolute neutophilia (9), with an adjustment for high lymphocyte counts in children in the first six months, and for the identification of increased immature myeloid precursors (myelocytes and metamyelocytes). The C-reactive protein, a long established acute phase protein, is not predictive at levels under 520 mg/L because it is elevated in a variety of chronic inflammatory conditions.  Moreover, it is infrequently used in adult medical practice for that reason, except for the high sensitivity CRP, which has been shown to be relevant to treatment of coronary heart disease by the Jupiter study (10), but also has raised the question of overuse of the statins with the undesirable side effect of skeletal muscle loss.  We can explore the validity of over ten years of studies in Europe and US, showing a debated benefit from using the procalcitonin biomarker (PCT, Brahms)(11-28).

The question arises whether there is a difference in PCT response between Gm- and Gm+, and there is, but it doesn’t matter. We can’t be certain that this reaction is  produced by vascular endothelium. I could identify at least one case where I knew the patient had no culture taken and died in cardiovascular shock. At that stage of decompensation what would make one think that it was other than pump failure? But in the evolution of cardiogenic shock, the perfusion of the superior mesentery artery could well be decompensated with the release of bacteria of intestinal organs. Quite a bit of work has been done in surgical research that indicates that there is bacterial migration to regional nodes, but it isn’t problematic unless there is a systemic insult.

Then there needs to be an explanation of events related to gene regulation and cell signaling, that is a blank screen. The cost of the test has been a factor limiting the use, which I think is not the key issue.

Results

A multivariable study with 435 patients to determine whether procalcitonin alone is a superior marker for sepsis established a difference between patients with and without sepsis , as the increase in PCT with sepsis was significant at p = 0.0001.  The PCT was also increased in patients who were admitted to the ICU, requiring assisted ventilation and monitoring of heart rate and blood pressure, significant at p = 0.0001.  The highest values occur in septic shock, even though mild elevations are seen with localized infection.  A PCT level distinguishes between four subgroups of the population: no infection, local infection, sepsis, and severe sepsis and septic shock. The PCT is very low with no infection and rises to levels above 5 with moderate to severe sepsis.  Table 1 compares the selected biomarker results for patients in ICU and not in ICU by the t test with adjustment for unequal variances.  The salient points are noted. PCT, not CRP, is significant for a difference between SIRS positive and SIRS negative patients in ICU (p=0.0001 vs 0.166), with a mean CRP of 495 mg/L in non ICU patients.  The result is expected because the CRP is elevated in other conditions without sepsis, and the patients in the ICU and outside the ICU may have a variety of inflammatory conditions.  There is a difference in PCT between ICU and non-ICU patients without SIRS (p = 0.0001), indicating that PCT is identifying infection, if not sepsis, in this cohort of patients.  Patients in the ICU with SIRS (vs without) have a mean PCT of 35.2 vs 3.7 ng/ml, a clinically as well as statistically significant increase in PCT (Mann-Whitney, p = 0.0001). On the other hand, patients without SIRS in the ICU also have higher CRP [1] and PCT [2] than those not in ICU (1, p = 0.032; 2, p = 0.004), but the CRP difference just reaches statistical significance while the unexpected PCT increase is a big effect.  The means obtained for SIRS/non-SIRS are: CRP [1] 802/404 mg/L; PCT [2] 20.6/7.5 ng/ml; TTR [3] 87.8/125 mg/L. So we see an increase of CRP and PCT with SIRS, as expected, and a decrease in TTR to below 100 mg/L as an obligatory response in relationship to the severity of the inflammatory state. The patients with SIRS and those with sepsis, respectively, had significant elevations of CRP [1] and PCT[2], and decrease of TTR[3] by Mann-Whitney test      (SIRS, p = 0.006, CRP [1]; 0.0001, PCT [2]; 0.0001 TTR[3]; sepsis, p = 0.010, CRP [1]; 0.014, PCT [2]; 0.004, TTR [3]).

Finally, we are particularly interested in combinations of variables for predicting infection and the stage of infection using PCT, MAP (mean arterial blood pressure), WBC.  The model fit looks good based on the chi-squared statistics.   The relationship between the predictor variables and SIRS or ICU is consistent with the large increases of PCT described.  In exploring this strong association between the chosen predictors for SIRS and ICU – PCT, WBC, MAP and TTR (CRP not used) demonstrated that each can be used in a classification matrix. (Table 2)   One might create a 4-letter code using M (MAP)_T (TTR)_W (WBC)_S (SIRS) to test for PCT effectiveness in the same way that one would test PCT against the clinical diagnosis of sepsis, but excluding the variable that we are interested in proving.  PCT can then be added as the fifth variable. The data was classified according to mean arterial blood pressure (MAP), TTR, white cell count (WBC), and SIRS as described and the PCT was kept out of the classification.  The PCT, MAP and SIRS differences were all significant at 0.0001, and the TTR had a p = 0.021 in the Kruskall Wallis analysis by ranks. A similar, but simpler classification did not include either PCT or MAP, resulting in three classes. The PCT increased within the subgroups of WTSIRS (2.5, 25, 50, 75 and 97.5 percentiles. Further, the subgroup of patients classified by MAP, TTR, WBC and SIRS, had a dramatic decline in the MAP by subclass, the last of which is comparable to septic shock.   We constructed a latent class model using the ordinals of PCT, MAP and WBC scaled to intervals. The combinatorial classes formed by the predictors have a defined contribution (percent) of each predictor.  The R2, L2 and C2 are shown.

Degrees of freedom (df)            282                  p-value

L-squared (L²)                         217.6904         1.00

X-squared                                235.4391         0.98

Cressie-Read                           209.1484         1.00

aBIC (based on LL)                  634.1041

bAIC (based on LL)                 494.7921

aBayes Information Criterion, bAkaike’s Information Criterion

Model for Dependent

Class1             0.7961

Class2             0.9136

Class3             0.9782

Class4             0.6410

Overall            0.9319

The chi-squared with a p-value close to 1 indicates that the partitioning of the combinatorial groups is excellent, and the model is not underfit or overfit.   A second cluster LCA model using SIRS as covariate also gives a good fit. The p-values are acceptable.

Chi-squared Statistics

Degrees of freedom (df)                        258                  p-value

L-squared (L²)                                     248.9633         0.65

X-squared                                            230.6279         0.89

Cressie-Read                                       222.0675         0.95

BIC (based on L²)                                -1238.4560

AIC (based on L²)                                -267.0367

Even though CRP has validity for identifying SIRS in our exploratory study, the specificity and its usefulness at a cutoff at 52 mg/dL raised significant concerns with respect to with respect to distinguishing SIRS with and without infection.  Keep in mind that large variances in CRP exist between the subgroups, which is problematic because of the CRP elevation in patients with metabolic syndrome and with chronic inflammatory diseases, but not necessarily sepsis. TTR is also decreased, as CRP is elevated, in patients with inflammatory conditions without sepsis.

The data demonstrated a clear relationship between high PCT and both SIRS and the ICU placement of the patient. We also showed the elevation of PCT in concert with severity of infection, as determined by medical record review.  Patients with sepsis are transferred to the ICU for management. These patients are on antibiotics and they are monitored for drop in mean arterial blood pressure over the first 72 hours, as a drop in MAP below 72 indicates septic shock. The progression from SIRS to septic shock goes from single organ (lung, kidney) to double organ, to multiple organ dysfunction syndrome is accompanied by increased lactic acid, tachycardia, decreased MAP, and finally, increase in serum bilirubin.  We would expect and find elevations of PCT with pneumonia, deep wounds, and pyelonephritis as well as sepsis, but these patients would be expected to meet the SIRS criteria.  Our study was not designed to demonstrate how PCT might detect sepsis in older patients with negative SIRS criteria in the ICU who are on ventilator assistance and who may not develop a febrile response. One has to consider that this is related to PCT elevation being partly independent of the SIRS response.

We then showed the same relationship to biomarker combinations that classify the data in accordance with the severity of infection. The WBC count is the weakest classification variable, but it is in the SIRS criteria and it is of greatest value with a finding of immature neutrophils. However, the band count is now considered part of the mature neutrophil count so that the absolute neutrophil count and the immature granulocytes measured by flow cytometry (myelocytes and metamyelocytes) are superior to the tWBC and bands (  ).  The MAP is valuable for identifying the patients at highest risk of circulatory collapse with a drop in the MAP and transfer to ICU (on pressors). The drop in MAP within 72 hours is important for making decisions about Activated protein C (Xygris), which is a critical decision.  APC has been removed from the market.  We included the TTR, which decreases in patients with SIRS in proportion to the severity of illness.  If we compare these predictors in patients with a diagnosis of sepsis, CRP, PCT (and TTR) all have significant differences between ICU and not ICU admission at p < 0.05. The elevation of white cell count and percent neutrophils, unexpectedly has no separatory power. This would not be the case for a postoperative patient who had an increase in WBC that was previously not elevated, or a failure to drop the WBC given antibiotics. On the other hand, for the combination of SIRS and elevated white cell count, the CRP, PCT and TTR all give good separation between ICU and non-ICU patients, an improvement over SIRS positive status alone. This reflects the non specificity with a high false positive rate of the SIRS criteria when neither of the two predictors is granulocytosis.  We asked whether we can combine the key predictor variable into combinatorial classes that would improve the accuracy of identification. CRP was not of interest with respect to this analysis as the poor specificity could only confound matters, and the test offers no additional information than PCT provides.   A more formal classification can then be designed using existing multivariate protocols, but keeping in mind that a mixed model or one using a log-linear model is preferred.

Our study is unique in at least two respects: It is the first to clearly demonstrate a graded response of PCT to severity of infectious challenge.  It is also a rare study to use a classification method to study the effect of combinations of variables associated with SIRS and infection on PCT elevation (11-13). We have created a graded classification by using feature extraction and forming an N-length class based on established information principles (Kullback entropy and Akaike Information Criteria).  The features used to classify the data were PCT, MAP, TTR, WBC and a SIRS score of at least two. The data was also classified without using PCT in order to establish validity for PCT independently of a classification using the feature being evaluated.The classifications have been extensively examined using one-way ANOVA, Kruskal Wallis analysis by ranks,  and latent class analyses. The Kruskal-Wallis analysis by ranks is a powerful tool for comparing the PCT levels within and across feature classes when the variance of PCT values across groups does not have the same distribution and the assumption of normal distribution doesn’t hold. Latent class analysis is a group of methods that can be used to classify data when the data is converted to ordinal classes under the assumption that there is a hidden or “latent” underlying classification. In defining latent classes we assume the criterion of “conditional independence,” so that, each variable is statistically independent of every other variable within each latent class, In our case, latent classes correspond to probabilities for and against the presence of a distinct medical syndrome. In this case we call attention to the classes representing no infection, soft tissue infection, sepsis, and severe sepsis or septic shock.  In reality, the variables used to form the classes are not independent, but they are used as ordinal variables and can be ranked in order of importance in forming a classification. There is a paper of some interest with regard to classification and prediction of severe sepsis that finds PCT, lactic acid and aminoterminal pro B-type natriuretic peptide correlating with sepsis severity scores (12) and another using PCT in combination with waveform analysis (13).  Classification and prediction has been of particular interest to the corresponding investigator for laboratory procedure validation for more than 10 years (20-22).  We provide valuable references to this approach (23-27).

In all respects, we find agreement with a large number of studies, including those recently cited (5-19). PCT has been shown to be useful for discriminating systemic inflammatory response, infection and sepsis (5,6) and identifying a high mortality subgroup with sepsis (15), for identifying sepsis at the onset with either gram negative or gram positive bacteremia (10), for evaluating time to treatment effectiveness (16), and for identifying sepsis in the febrile neutropenic patient (18).

What is it in our findings that makes the results compelling?  CRP has been used for many years, although more widely in European countries than in US until the high sensitivity assay association with risk of coronary artery disease generated a new interest in this test.  CRP increase is associated with SIRS and its production is driven by the cytokines TNFa and Il6.  The liver reprioritises the production of acute phase reactants (CRP, a1 acid glycoprotein [orosomucoid], a1 antitrypsin and transferrin with down-regulation of production of albumin, TTR, transcortin, and other serum transport proteins. However, if this happens in the extreme condition, it also is the case in the more chronic conditions, such as, rheumatoid arthritis and autoimmune diseases, and is a feature of the metabolic syndrome, characterized by type 2 diabetes, obesity, and insulin resistance with or without dyslipidemia. Consequently, CRP is quite high associated with a variety of non-septic conditions.  The emergence of PCT as a sepsis biomarker is somewhat serendipidous.  The protein is the precursor of the peptide calcitonin, produced in the thyroid.  Sepsis appears to upregulate the extrathyroidal production of procalcitonin by vascular endothelium by a mechanism not understood.  PCT can be elevated with non-septic shock, such a cardiogenic shock, but it is easy to comprehend that secondary sepsis could occur by loss of gut integrity and bacterial translocation in such a state.

The importance of pneumonia and pyelonephritis as a precursor of sepsis, and the rapid progression of sepsis in the hospitalised ICU patient can’t be taken lightly.  The identification of sepsis in the emergency room is problematic because the clinical presentation is variable and not so specific.  The SIRS criteria – tachycardia, tachypnea, fever, and leukocytosis – are all common presentations in patients without sepsis.   On the one hand, more accurate identification of the patients with sepsis should eliminate many patients who are screened for sepsis and subsequently have negative culture, and should identify patients who require prompt antimicrobial treatment at an early stage.

The progression from SIRS to sepsis to organ failure and septic shock should also be monitored effectively, which depends on the level of PCT reflecting the level of systemic disorder.  This would permit the best identification of patients who are improving and those who might require activated protein C intervention.  The progression from SIRS to sepsis and beyond is a complex process involving repeated events in the course of the acute illness.  This gives even more justification for combining PCT with other measures to manage the septic state.

Conclusion

We have demonstrated a clear relationship between high PCT and both SIRS and the ICU placement of the patient.  In addition, we have shown the strength of classifying these patients using PCT in combination with MAP, TTR, WBC and SIRS.

References

1. Martin MS, Mannino DM, et al. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003; 348:1546-1554.

2. NationalCenter for Health Statistics. National vital statistics reports. 2004; 53:9.

3. Angus DC, Linde-Zwirble WT, et al. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001; 29:1303-1310.

4.  Smith BS, Schroeder WS; Tataronis GR.Hospital reimbursement for adult Patients with severe sepsis treated with drotrecogin alfa (activated). Hospital pharmacy 2005; 40:146-153.

5.  Assicot M, Gendrel D, Cersin H, Raymond J, et al. High serum procalcitonin concentrations in patients withsepsis and infection.  Lancet 1993: 341: 515-18.

6.  Delveraux I, Andre M, Columbier M, Albuisson E, et al. Can procalcitonin measurement help in differentiating between bacterial and other kinds of inflammatory processes?  Ann Rheum Dis 2003; 62: 337-40.

7. Bone R, Balk R, Cerra F, Dellinger R, Fein W, et. Definitions of sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. Amer Coll of Chest Physicians/Soc of Critical Care Med. Chest 1992; 101(6): 1644-655.

8.Dellinger R, Phillip R, Levy MM, Carlet JM, et al. Surviving Sepsis Campaign: Internatl Guidelines for Management of Severe Sepsis and Septic Shock:2008. Crit Care Med 2008; 36(1): 296-377.

9. Bernstein LH and Rucinski R. The relationship between granulocyte maturation and the septic state measurement of granulocyte maturation may improve the early diagnosis of the septic state.  Clin Chem Lab Med 2011;         DOI 10.1515/CCLM.2011.xxx

10. Ridker PM, Danielson E, Fonseca FAH, Genest J, Gotto AM, et al.  Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein.  NEJM 2008; 359: 2195-2207.

11. Jensen JU, Heslet L,; Jensen TH, Espersen K, et al. Procalcitonin increase in early identification of critically ill patients at high risk of mortality. Crit Care Med 2006; 34(10):1-7.

12.  Luzzani A, Polati E, Dorizzi R, Rungatscher A, et al.  Comparison of procalcitonin and C-reactive protein as markers of sepsis. Critical Care Medicine 2003:31(6):1737-1741.

13.  Reith HB, Mittelkotter U, Wagner R, Thiede A. Procalcitonin (PCT) in patients with abdominal sepsis. Intensive Care Med 2000; 26 suppl2: S165-9.

14.  Rau B, Steinbach G, Baumgart K, Gansauge F, et al. The clinical value of procalcitonin in the prediction of infected necrosis in acute pancreatitis. Intensive Care Med 2000; 26, suppl2. S159-64.

15.  Cheval C, Timsit JF, Garrouste-Orgeas M, Assicot M, et al. Procalcitonin (PCT) is useful in predicting the bacterial origin of an acute circulatory failure in critically ill patients. Intensive Care Med 2000; 26, suppl2 S153-8.

16.  Brunkhorst FM, Wegscheider K, Forycki ZF, Brunkhorst R. Procalcitonin for early diagnosis and differentiation of SIRS, sepsis, severe sepsis and septic shock. Intensive Care Med 2000; 26, suppl2 S148-52.

17.  Becker KL, Snider R, Nylen ES. Procalcitonin assay in systemic inflammation, infection, and sepsis: clinical utility and limitations. Crit Care Med 2008; 36(3): 941-52.

18.  Charles PE, Ladoire S, Aho S, Quenot JP, Doise JM, et al. Serum procalcitonin elevation in critically ill patients at the onset of bacteremia caused by either Gram negative or Gram positive bacteria. BMC Infectious Diseases 2008, 8:38 (http://www.biomedcentral.com/1471-2334/8/38)

19.  Wanner GA, Keel M, Steckholzer U, Beier W, Stocker R, Ertel W.  Relationship between procalcitonin plasma levels and severity of injury, sepsis, organ failure, and mortality in injured patients. Critical Care Medicine. 2000; 28(4): 950-957.

20.   Harbath S, Holeckova K, Froidevaux C, Pittet D, et al. Diagnostic Value of Procalcitonin, Interleukin-6, and Interleukin-8 in Critically Ill Patients Admitted with Suspected Sepsis. Amer J Respir Crit Care Med 2001;164: 396-402.

21.   Simon L, Gauvin F, 2 Devendra K. Amre DK,Saint-Louis P, Lacroix J. Serum Procalcitonin and C-Reactive Protein Levels as Markers of Bacterial Infection: A Systematic Review and Meta-analysis. CID 2004: 39:206-217.

22.   Selberg O, Hecker H, Martin M, Klos A Bautsch, et al.  Discrimination of sepsis and systemic inflammatory response syndrome by determination of circulating plasma concentrations of procalcitonin, protein complement 3a, and interleukin-6. Critical Care Medicine. 2000; 28(8): 2793-2798.

23.   Phua J, Koay ES, Lee KH. Lactate, procalcitonin, and amino-terminal pro-B-type natriuretic peptide versus cytokine measurements and clinical severity scores for prognostication in septic shock. Shock 2008; 29(3):328-33.

24.   Zakariah AN ; Cozzi SM ; Van Nuffelen M ; Clausi CM ; Pradier O ; Vincent JL. Combination of biphasic transmittance waveform with blood procalcitonin levels for diagnosis of sepsis in acutely ill patients. Crit Care Med.  2008; 36(5): 1507-12

25.   Viallon A, Guyomarch S, Marjollet O, Berger C, et al. Can Emergency physicians identify a high mortality subgroup of patients with sepsis: role of procalcitonin? Eur J Emerg Med 2008; 15(1):26-33.

26.   Bobre V, Harbarth S, Graf JD, Rohner P, Pugin J. Use of procalcitonin to shorten antibiotic treatment duration in septic patients: a randomized trial. Am J Respir Crit Care Med 2008;177 (5):498-505.

27.   Indino P, Lemarchand P, Bady P, de Torrente A, et al. Prospective study on procalcitonin and other systemic infection markers in patients with leukocytosis. Int J Infect Dis 2008;12 (3):319-24.

The role of biomarkers in the diagnosis of sepsis and patient management
Author: L. H. Bernstein, MD
Key words: Systemic Inflammatory Response Syndrome (SIRS), sepsis, septic shock, mean arterial blood pressure (MAP), procalcitonin, combinatorial analysis, effect size
Highlights:
1. The systemic inflammatory response syndrome (SIRS) is an acute response to trauma, burn, or infectious injury characterized by fever, hemodynamic and respiratory changes, and metabolic changes, not all of which are consistently present.
2. The SIRS reaction involves hormonally driven changes in liver glycogen reserves, triggering of lipolysis, lean body proteolysis, and reprioritization of hepatic protein synthesis with up-regulation of synthesis of acute phase proteins and down-regulation of albumin and important circulating transport proteins.
3. Understanding of the processes leads to the identification of biomarkers for identification of sepsis and severe, moderate or early SIRS, which also can hasten treatment and recovery.
4. The SIRS reaction unabated leads to a recurring cycle with hemodynamic collapse from septic shock, indistinguishable from cardiogenic shock, and death.

Abbreviations: Systemic Inflammatory Response Syndrome (SIRS), procalcitonin (PCT), C-reactive protein (CRP), mean arterial blood pressure (MAP), Intensive care unit (ICU), total white blood cell count (WBC), transthyretin(TTR)

Summary
By focusing on early and accurate diagnosis of infection in patients suspected of SIRS antibiotic overuse and its associated morbidity and mortality may be avoided, and therapeutic targets may be identified. This discussion investigates the performance of diagnostic algorithms and biomarkers for sepsis in patients presenting with leukocytosis and other findings. Suspected patients are usually identified by WBC above 12,000/L PCT level , SIRS and other criteria, such as serum biomarkers of sepsis. In this writer’s study of 435 patients, procalcitonin alone was a superior marker for sepsis. In patients with sepsis there was a marked increase in PCT (p = 0.0001). PCT was increased in patients requiring ICU admission, heart rate and blood pressure monitoring, and assisted ventilation.(p = 0.0001). Means for SIRS/non-SIRS were: CRP 802/404 mg/L; PCT 20.6/7.5 ng/mL; TTR 87.8/125 mg/L. A comprehensive overview of at least a decade of work is provided.

Introduction
Sepsis is a costly diagnosis in hospitalized patients and carries a high financial risk as a comorbidity and a payment penalty for failure to diagnose in a timely manner (1-4) under the severity of illness CMS reimbursement guidelines as a patient safety hazard, with pneumonia and sepsis among the ten most costly among hospital admissions. A polypeptide identical to a prohormone of calcitonin, procalcitonin, was initially described as a potential marker of bacterial disease by Assicot et al.(5). Procalcitonin is almost undetectable under physiological conditions (pg/ml range), but rises to very high values in response to bacteraemia or fungaemia, and appears to be related to the severity of infection.(6) Sequential measurements in patients with bacteraemia have shown a rapid fall within 48 hours of antibiotic administration. There have been numerous studies of the early recognition of sepsis and related diseases in patients related to admission and intensive care. The consensus
guideline has used a SIRS criteria (7, 8). The SIRS criteria (7,8) include temperature </= 36o C. >= 38o C., heart rate > 90 beats per minute, respiratory rate >20 breaths per minute or PaCO2 < 32 mm of Hg, WBC > 12,000/L or < 4,000/L, or > 10% band forms. For the diagnosis of sepsis (2 or more SIRS criteria and confirmed or suspected infection) the SIRS criteria are insufficient with a very high false positive rate, so that there are medical institutions that require three. The observation of fever, tachypnea, and tachycardia may well not be present early, and the observation of leukocytosis with or without band neutrophilia are unreliable. The use of a plasma lactic acid measurement has been added, but it is basically a reflection of decreased splanchnic circulation to the superior mesenteric artery and liver bed. A better case has been made for absolute neutophilia (9), with an adjustment for high lymphocyte counts in children in the first six months, and for the identification of increased immature myeloid precursors (myelocytes and metamyelocytes). The C-reactive protein, a long established acute phase protein, is not predictive at levels under 520 mg/L because it is elevated in a variety of chronic inflammatory conditions. Moreover, it is infrequently used in adult medical practice for that reason, except for the high sensitivity CRP, which has been shown to be relevant to treatment of coronary heart disease by the Jupiter study (10), but also has raised the question of overuse of the statins with the undesirable side effect of skeletal muscle loss. We can explore the validity of over ten years of studies in Europe and US, showing a debated benefit from using the procalcitonin biomarker (PCT, Brahms)(11-28).
Results
A multivariable study with 435 patients to determine whether procalcitonin alone is a superior marker for sepsis established a difference between patients with and without sepsis , as the increase in PCT with sepsis was significant at p = 0.0001. The PCT was also increased in patients who were admitted to the ICU, requiring assisted ventilation and monitoring of heart rate and blood pressure, significant at p = 0.0001. The highest values occur in septic shock, even though mild elevations are seen with localized infection. A PCT level distinguishes between four subgroups of the population: no infection, local infection, sepsis, and severe sepsis and septic shock. The PCT is very low with no infection and rises to levels above 5 with moderate to severe sepsis. Patients in the ICU with SIRS (vs without) have a mean PCT of 35.2 vs 3.7 ng/ml, a clinically as well as statistically significant increase in PCT (Mann-Whitney, p = 0.0001). On the other hand, patients without SIRS in the ICU also have higher CRP [1] and PCT [2] than those not in ICU (1, p = 0.032; 2, p = 0.004), but the CRP difference just reaches statistical significance while the unexpected PCT increase is a big effect. The means obtained for SIRS/non-SIRS are: CRP [1] 802/404 mg/L; PCT [2] 20.6/7.5 ng/ml; TTR [3] 87.8/125 mg/L. So we see an increase of CRP and PCT with SIRS, as expected, and a decrease in TTR to below 100 mg/L as an obligatory response in relationship to the severity of the inflammatory state. The patients with SIRS and those with sepsis, respectively, had significant elevations of CRP [1] and PCT[2], and decrease of TTR[3] by Mann-Whitney test (SIRS, p = 0.006, CRP [1]; 0.0001, PCT [2]; 0.0001 TTR[3]; sepsis, p = 0.010, CRP [1]; 0.014, PCT [2]; 0.004, TTR [3]).
Finally, we are particularly interested in combinations of variables for predicting infection and the stage of infection using PCT, MAP (mean arterial blood pressure), WBC. The model fit looks good based on the chi-squared statistics.

Degrees of freedom (df) 282 p-value
L-squared (L²)       217.69       1.00
X-squared                235.44       0.98
Cressie-Read           209.15       1.00

aBIC (based on LL)      634
bAIC (based on LL)     495
aBayes Information Criterion, bAkaike’s Information Criterion

Model for Dependent
Class1    Class2       Class3    Class4     Overall
R² 0.7961    0.9136    0.9782   0.6410   0.9319

The chi-squared with a p-value close to 1 indicates that the partitioning of the combinatorial groups is excellent, and the model is not underfit or overfit. A second cluster LCA model using SIRS as covariate also gives a good fit. The p-values are acceptable.
Chi-squared Statistics
Degrees of freedom (df) 258      p-value
L-squared (L²)              248.96      0.65
X-squared                       230.62      0.89
Cressie-Read                  222.07     0.95
BIC (based on L²)       -1238.46
AIC (based on L²)        -267.04
Even though CRP has validity for identifying SIRS in our exploratory study, the specificity and its usefulness at a cutoff at 52 mg/dL raised significant concerns with respect to with respect to distinguishing SIRS with and without infection. Keep in mind that large variances in CRP exist between the subgroups, which is problematic because of the CRP elevation in patients with metabolic syndrome and with chronic inflammatory diseases, but not necessarily sepsis. TTR is also decreased, as CRP is elevated, in patients with inflammatory conditions without sepsis.
The data demonstrated a clear relationship between high PCT and both SIRS and the ICU placement of the patient. We also showed the elevation of PCT in concert with severity of infection, as determined by medical record review PWe would expect and find elevations of PCT with pneumonia, deep wounds, and pyelonephritis as well as sepsis, but these patients would be expected to meet the SIRS criteria. Our study was not designed to demonstrate how PCT might detect sepsis in older patients with negative SIRS criteria in the ICU who are on ventilator assistance and who may not develop a febrile response. One has to consider that this is related to PCT elevation being partly independent of the SIRS response.
We then showed the same relationship to biomarker combinations that classify the data in accordance with the severity of infection. The WBC count is the weakest classification variable, but it is in the SIRS criteria and it is of greatest value with a finding of immature neutrophils. However, the band count is now considered part of the mature neutrophil count so that the absolute neutrophil count and the immature granulocytes measured by flow cytometry (myelocytes and metamyelocytes) are superior to the tWBC and bands ( ). The MAP is valuable for identifying the patients at highest risk of circulatory collapse with a drop in the MAP and transfer to ICU (on pressors). The drop in MAP within 72 hours is important for making decisions about Activated protein C (Xygris), which is a critical decision. APC has been removed from the market. We included the TTR, which decreases in patients with SIRS in proportion to the severity of illness. We asked whether we can combine the key predictor variable into combinatorial classes that would improve the accuracy of identification. CRP was not of interest with respect to this analysis as the poor specificity could only confound matters, and the test offers no additional information than PCT provides.
Our study is unique in at least two respects: It is the first to clearly demonstrate a graded response of PCT to severity of infectious challenge. It is also a rare study to use a classification method to study the effect of combinations of variables associated with SIRS and infection on PCT elevation (11-13). We have created a graded classification by using feature extraction and forming an N-length class based on established information principles (Kullback entropy and Akaike Information Criteria). The features used to classify the data were PCT, MAP, TTR, WBC and a SIRS score of at least two. The data was also classified without using PCT in order to establish validity for PCT independently of a classification using the feature being evaluated.The classifications have been extensively examined using one-way ANOVA, Kruskal Wallis analysis by ranks, and latent class analyses. The Kruskal-Wallis analysis by ranks is a powerful tool for comparing the PCT levels within and across feature classes when the variance of PCT values across groups does not have the same distribution and the assumption of normal distribution doesn’t hold. Latent class analysis is a group of methods that can be used to classify data when the data is converted to ordinal classes under the assumption that there is a hidden or “latent” underlying classification. In defining latent classes we assume the criterion of “conditional independence,” so that, each variable is statistically independent of every other variable within each latent class, In our case, latent classes correspond to probabilities for and against the presence of a distinct medical syndrome. In this case we call attention to the classes representing no infection, soft tissue infection, sepsis, and severe sepsis or septic shock. In reality, the variables used to form the classes are not independent, but they are used as ordinal variables and can be ranked in order of importance in forming a classification. There is a paper of some interest with regard to classification and prediction of severe sepsis that finds PCT, lactic acid and aminoterminal pro B-type natriuretic peptide correlating with sepsis severity scores (12) and another using PCT in combination with waveform analysis (13). Classification and prediction has been of particular interest to the corresponding investigator for laboratory procedure validation for more than 10 years (20-22). We provide valuable references to this approach (23-27).
In all respects, we find agreement with a large number of studies, including those recently cited (5-19). PCT has been shown to be useful for discriminating systemic inflammatory response, infection and sepsis (5,6) and identifying a high mortality subgroup with sepsis (15), for identifying sepsis at the onset with either gram negative or gram positive bacteremia (10), for evaluating time to treatment effectiveness (16), and for identifying sepsis in the febrile neutropenic patient (18).
We have demonstrated a clear relationship between high PCT and both SIRS and the ICU placement of the patient. In addition, we have shown the strength of classifying these patients using PCT in combination with MAP, TTR, WBC and SIRS.

References

1. Martin MS, Mannino DM, et al. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003; 348:1546-1554.
2. National Center for Health Statistics. National vital statistics reports. 2004; 53:9.
3. Angus DC, Linde-Zwirble WT, et al. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001; 29:1303-1310.
4. Smith BS, Schroeder WS; Tataronis GR. Hospital reimbursement for adult Patients with severe sepsis treated with drotrecogin alfa (activated). Hospital pharmacy 2005; 40:146-153.
5. Assicot M, Gendrel D, Cersin H, Raymond J, et al. High serum procalcitonin concentrations in patients withsepsis and infection. Lancet 1993: 341: 515-18.
6. Delveraux I, Andre M, Columbier M, Albuisson E, et al. Can procalcitonin measurement help in differentiating between bacterial and other kinds of inflammatory processes? Ann Rheum Dis 2003; 62: 337-40.
7. Bone R, Balk R, Cerra F, Dellinger R, Fein W, et. Definitions of sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. Amer Coll of Chest Physicians/Soc of Critical Care Med. Chest 1992; 101(6): 1644-655.
8.Dellinger R, Phillip R, Levy MM, Carlet JM, et al. Surviving Sepsis Campaign: Internatl Guidelines for Management of Severe Sepsis and Septic Shock:2008. Crit Care Med 2008; 36(1): 296-377.
9. Bernstein LH and Rucinski R. The relationship between granulocyte maturation and the septic state
measurement of granulocyte maturation may improve the early diagnosis of the septic state. Clin Chem Lab Med 2011; DOI 10.1515/CCLM.2011.xxx
10. Ridker PM, Danielson E, Fonseca FAH, Genest J, Gotto AM, et al. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. NEJM 2008; 359: 2195-2207.
11. Jensen JU, Heslet L,; Jensen TH, Espersen K, et al. Procalcitonin increase in early identification of critically ill patients at high risk of mortality. Crit Care Med 2006; 34(10):1-7.
12. Luzzani A, Polati E, Dorizzi R, Rungatscher A, et al. Comparison of procalcitonin and C-reactive protein as markers of sepsis. Critical Care Medicine 2003:31(6):1737-1741.
13. 2008, 8:38 (http://www.biomedcentral.com/1471-2334/8/38)
19. Wanner GA, Keel M, Steckholzer U, Beier W, Stocker R, Ertel W. Relationship between procalcitonin plasma levels and severity of injury, sepsis, organ failure, and mortality in injured patients. Critical Care Medicine. 2000; 28(4): 950-957.
20. Harbath S, Holeckova K, Froidevaux C, Pittet D, et al. Diagnostic Value of Procalcitonin, Interleukin-6, and Interleukin-8 in Critically Ill Patients Admitted with Suspected Sepsis. Amer J Respir Crit Care Med 2001;164: 396-402.
21. Simon L, Gauvin F, 2 Devendra K. Amre DK,Saint-Louis P, Lacroix J. Serum Procalcitonin and C-Reactive Protein Levels as Markers of Bacterial Infection: A Systematic Review and Meta-analysis.
CID 2004: 39:206-217.
22. Selberg O, Hecker H, Martin M, Klos A Bautsch, et al. Discrimination of sepsis and systemic inflammatory response syndrome by determination of circulating plasma concentrations of procalcitonin, protein complement 3a, and interleukin-6. Critical Care Medicine. 2000; 28(8): 2793-2798.
23. Phua J, Koay ES, Lee KH. Lactate, procalcitonin, and amino-terminal pro-B-type natriuretic peptide versus cytokine measurements and clinical severity scores for prognostication in septic shock. Shock 2008; 29(3):328-33.
24. Zakariah AN ; Cozzi SM ; Van Nuffelen M ; Clausi CM ; Pradier O ; Vincent JL. Combination of biphasic transmittance waveform with blood procalcitonin levels for diagnosis of sepsis in acutely ill patients. Crit Care Med. 2008; 36(5): 1507-12
25. Viallon A, Guyomarch S, Marjollet O, Berger C, et al. Can Emergency physicians identify a high mortality subgroup of patients with sepsis: role of procalcitonin? Eur J Emerg Med 2008; 15(1):26-33.
26. Bobre V, Harbarth S, Graf JD, Rohner P, Pugin J. Use of procalcitonin to shorten antibiotic treatment duration in septic patients: a randomized trial. Am J Respir Crit Care Med 2008;177 (5):498-505.
27. Indino P, Lemarchand P, Bady P, de Torrente A, et al. Prospective study on procalcitonin and other systemic infection markers in patients with leukocytosis. Int J Infect Dis 2008;12 (3):319-24.
28. Massaro KS, Costa SF, Leone C, Chamone DA. Procalcitonin (PCT) and C-reactive Protein (CRP) as severe systemic infection markers in febrile neutropenic adults. BMC Infect Dis 2007; 22(7): 137 (http://www.biomedcentral.com/1471-2334-7-137).
29. Vermunt J and Magidson J. Latent Gold 4.5. http://www.statistical.innovations.com

Table 1. Comparison of key sepsis biomarkers by means between ICU and non-ICU, SIRS positive status, and sepsis status.

Marker

Mean

p

SIRS Positive

ICU vs not

CRP (mg/L) 780 495 0.166
PCT (ng/ml) 35.2 3.7 0.0001

SIRS negative

ICU vs not

PCT (ng/ml) 0.0001

Sepsis Diagnosis

ICU vs not

CRP (mg/L) 817 521 0.010
PCT (ng/ml) 0.014
WBC 0.921
% neutrophils 0.452

SIRS with WBC

ICU vs not

CRP (mg/L) 802 404 0.006
PCT (ng/ml) 20.6 7.5 0.0001

Table 2. Comparison of PCT, MAP, TTR and WBC means and variation in SIRS and ICU placement.

variable-by-variablea

Fisher’s Exact testb

t-testc

PCT*SIRS

0.0001

0.0210

PCT*ICU

0.0001

0.0001

MAP*SIRS

0.0130

MAP*ICU

0.0001

0.0001

WBC*SIRS

0.0001

0.0001

WBC*ICU

NS

TTR*SIRS

0.0001

0.0001

TTR*ICU

0.0001

atwo variables, b,cp-value

Archival Table

Table 3.  Classes and 4-variable contributions for 4-class LCA cluster model.

Cluster Size

0.3646             0.2738             0.2209             0.1408

Indicators

PCT0425         (PCT: < 0.4, 0.41-2.5, > 2.5)

0          0.6393             0.8894             0.1278             0.0000

1          0.3190             0.1076             0.3752             0.0013

2          0.0355             0.0029             0.2459             0.0285

3          0.0062             0.0001             0.2511             0.9702

MAP758088    (MAP: > 88, 81-87, 75-80, < 80)

0          0.5234             0.6186             0.3709             0.4228

1          0.1861             0.1794             0.1771             0.1828

2          0.1065             0.0838             0.1361             0.1272

3          0.1841             0.1181             0.3160             0.2673

WBC1217       (WBC: < 12, 12-17, > 17)

0          0.3325             0.1772             0.0002             0.3084

1          0.4152             0.3948             0.0216             0.4171

2          0.2523             0.4280             0.9782             0.2745

TTR7105         (TTR: > 10.5, 7.0-10.5, < 7)

0          0.2457             0.9805             0.2159             0.3920

1          0.3352             0.0192             0.3279             0.3391

2          0.4191             0.0003             0.4562             0.2688

            Table 1. Comparison of key sepsis biomarkers by means between ICU and non-ICU, SIRS positive status, and sepsis status.

Marker

Mean

p

SIRS Positive

ICU vs not

CRP (mg/L) 780 495 0.166
PCT (ng/ml) 35.2 3.7 0.0001

SIRS negative

ICU vs not

PCT (ng/ml) 0.0001

Sepsis Diagnosis

ICU vs not

CRP (mg/L) 817 521 0.010
PCT (ng/ml) 0.014
WBC 0.921
% neutrophils 0.452

SIRS with WBC

ICU vs not

CRP (mg/L) 802 404 0.006
PCT (ng/ml) 20.6 7.5 0.0001

Table 2. Comparison of PCT, MAP, TTR and WBC means and variation in SIRS and ICU placement.

variable-by-variablea

Fisher’s Exact testb

t-testc

PCT*SIRS

0.0001

0.0210

PCT*ICU

0.0001

0.0001

MAP*SIRS

0.0130

MAP*ICU

0.0001

0.0001

WBC*SIRS

0.0001

0.0001

WBC*ICU

NS

TTR*SIRS

0.0001

0.0001

TTR*ICU

0.0001

atwo variables, b,cp-value

Archival Table

Table 3.  Classes and 4-variable contributions for 4-class LCA cluster model.

Cluster Size

0.3646             0.2738             0.2209             0.1408

Indicators

PCT0425         (PCT: < 0.4, 0.41-2.5, > 2.5)

0          0.6393             0.8894             0.1278             0.0000

1          0.3190             0.1076             0.3752             0.0013

2          0.0355             0.0029             0.2459             0.0285

3          0.0062             0.0001             0.2511             0.9702

MAP758088    (MAP: > 88, 81-87, 75-80, < 80)

0          0.5234             0.6186             0.3709             0.4228

1          0.1861             0.1794             0.1771             0.1828

2          0.1065             0.0838             0.1361             0.1272

3          0.1841             0.1181             0.3160             0.2673

WBC1217       (WBC: < 12, 12-17, > 17)

0          0.3325             0.1772             0.0002             0.3084

1          0.4152             0.3948             0.0216             0.4171

2          0.2523             0.4280             0.9782             0.2745

TTR7105         (TTR: > 10.5, 7.0-10.5, < 7)

0          0.2457             0.9805             0.2159             0.3920

1          0.3352             0.0192             0.3279             0.3391

2          0.4191             0.0003             0.4562             0.2688

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