**Figure 11.** (a) The surface charge distribution of amyloid fibril as a function of the pH of buffer solution in which amy‐ loid fibril is prepared. The isoelectric point (p*I*) value of amyloid fibril is determined in such a way that the pH value, at which surface charge distribution becomes zero, is identical to p*I* value. (b) AFM topography and surface potential images of β-lg amyloid fibrils when they are prepared in buffer solutions, whose pH values are pH 3 and pH 6, respec‐

Moreover, in recent studies of amyloid fibril with AFM, some of scientists have reported about various structural features of amyloid fibrils such as steric zipper pattern [76, 77], helical pattern [48], and length [78], which is a key design parameter that determines the material properties of amyloid fibrils. Nevertheless, it is not quite understood yet how the molecular structures and conformational diversity (heterogeneous conformations) of amyloid fibrils are

To figure out how amyloid fibrils with heterogeneous conformations are formed, the synthesis of the β-lg fibrils with microwave-assisted chemistry method is considered, which enables the acceleration of biochemical reactions, and performed KPFM analysis of them [63]. It has been reported already that the microwave-assisted chemistry for the synthesis of amyloid fibrils makes the acceleration of fibrillation possible. The mechanism of amyloid fibrillation under microwave irradiation is still debated, but it seems to be related to the enhanced collision

tively. All scale bars are 250 nm. Figures reproduced with permission from Ref. [20], © 2012 AIP.

regulated.

11618 Exploring New Findings on Amyloidosis

**Figure 12** represents the topographic and surface potential images of amyloid fibrils that were synthesized based on microwave-assisted chemistry and their conformational heterogeneities. From these results, it is obvious that except for *λ* = 60 s, the surface potential and the fibril diameter of β-lg amyloid fibrils increase in monotone fashion as *λ* increases. This result revealed that heterogeneous conformations of β-lg amyloid fibrils are due to the wave-driven change of electrostatic interaction, which has a critical impact on the radial growth mechanisms of amyloid fibrils. As described above, KPFM indeed was a good analytical tool for monitoring the conformational change and the electrical properties of amyloid fibrils with respect to microwave-assisted chemistry.

**Figure 12.** (a) AFM images of amyloid fibrils that are synthesized based on microwave-assisted chemistry using differ‐ ent *λ* values. (b) KPFM images of the fibrils formed using different *λ* values. (c) Distribution of surface charges for amyloid fibril as a function of its diameter. The surface potential of an amyloid fibril is almost linearly proportional to its diameter. Figures reprinted with permission from Ref. [63], © 2015 NPG.

## **5. Conclusion and perspectives**

As we surveyed above, because of the marvelous capabilities of the conventional AFM device, it and its extensions as liquid AFM, PeakForce QNM, and KPFM have been widely used to perform accurate measurements of mechanical, electrical, and biophysical properties of various amyloid fibrils. AFM applications can provide researchers with the strong advantage of being able to measure the surface potentials of nanomaterials at the single-molecule level. Moreover, it has been demonstrated that AFM applications enable monitoring the fibrillation behavior of various proteins by measuring morphological properties of amyloid fibrils in air or liquid environments. The changes in morphology of the fibrils indicated that amyloid fibrils can be changed morphologically in liquid environments (e.g., human body) and that implies amyloid fibrils would interact differently with other biomolecules, cells, and tissues in human body. Liquid AFM enables measurement of the characteristics of amyloid fibrils in situ by monitoring the fibrillation and conformation changes of amyloid fibrils. Furthermore, AFM application techniques usually require no labeling with chemical dyes and no chemical reagents for improving the image quality or contrast. Accordingly, AFM is able to get highresolution images of amyloid fibrils for the detection of conformational changes, by topological imaging in air and liquid environments. We dealt with PeakForce QNM that can simultane‐ ously measure several mechanical properties of amyloid fibrils such as Young's modulus, deformation, and adhesion force by using a precisely operating oscillating probe. With a Kelvin probe, KPFM is highly important for imaging and characterizing the electrical properties (i.e., surface potential and surface potential density of amyloid fibrils) while getting high-resolution topological imaging. Because of these advantages, AFM application is expected to attract much attention as an analytical tool for amyloid research in the future. These AFM-related results shed light on understanding the fibrillation of amyloidogenic proteins and will be the cornerstone for the development of not only the effective prevention methods for amyloido‐ genic diseases but also therapeutic agents and drugs. These approaches could also contribute to the development of amyloid fibril-based functional nanomaterials such as biocompatible adhesives [80, 81], solar-cell devices [82], and gene delivery systems [83].

## **Author details**

Wonseok Lee1 , Hyungbeen Lee1 , Gyudo Lee2 and Dae Sung Yoon3\*

\*Address all correspondence to<EMAIL_ADDRESS>

## **References**

**5. Conclusion and perspectives**

11820 Exploring New Findings on Amyloidosis

As we surveyed above, because of the marvelous capabilities of the conventional AFM device, it and its extensions as liquid AFM, PeakForce QNM, and KPFM have been widely used to perform accurate measurements of mechanical, electrical, and biophysical properties of various amyloid fibrils. AFM applications can provide researchers with the strong advantage of being able to measure the surface potentials of nanomaterials at the single-molecule level. Moreover, it has been demonstrated that AFM applications enable monitoring the fibrillation behavior of various proteins by measuring morphological properties of amyloid fibrils in air or liquid environments. The changes in morphology of the fibrils indicated that amyloid fibrils can be changed morphologically in liquid environments (e.g., human body) and that implies amyloid fibrils would interact differently with other biomolecules, cells, and tissues in human body. Liquid AFM enables measurement of the characteristics of amyloid fibrils in situ by monitoring the fibrillation and conformation changes of amyloid fibrils. Furthermore, AFM application techniques usually require no labeling with chemical dyes and no chemical reagents for improving the image quality or contrast. Accordingly, AFM is able to get highresolution images of amyloid fibrils for the detection of conformational changes, by topological imaging in air and liquid environments. We dealt with PeakForce QNM that can simultane‐ ously measure several mechanical properties of amyloid fibrils such as Young's modulus, deformation, and adhesion force by using a precisely operating oscillating probe. With a Kelvin probe, KPFM is highly important for imaging and characterizing the electrical properties (i.e., surface potential and surface potential density of amyloid fibrils) while getting high-resolution topological imaging. Because of these advantages, AFM application is expected to attract much attention as an analytical tool for amyloid research in the future. These AFM-related results shed light on understanding the fibrillation of amyloidogenic proteins and will be the cornerstone for the development of not only the effective prevention methods for amyloido‐ genic diseases but also therapeutic agents and drugs. These approaches could also contribute to the development of amyloid fibril-based functional nanomaterials such as biocompatible

adhesives [80, 81], solar-cell devices [82], and gene delivery systems [83].

, Gyudo Lee2

1 Department of Biomedical Engineering, Yonsei University, Wonju, Korea

2 School of Public Health, Harvard University, Boston, Massachusetts, USA

3 Department of Bio-convergence Engineering, Korea University, Seoul, Korea

and Dae Sung Yoon3\*

**Author details**

, Hyungbeen Lee1

\*Address all correspondence to<EMAIL_ADDRESS>
Wonseok Lee1

[30] Muller DJ, Dufrene YF. Atomic force microscopy as a multifunctional molecular toolbox in nanobiotechnology. Nat Nanotechnol. 2008;3(5):261–9.

[16] Jeong JS, Ansaloni A, Mezzenga R, Lashuel HA, Dietler G. Novel mechanistic insight into the molecular basis of amyloid polymorphism and secondary nucleation during

[17] Adamcik J, Berquand A, Mezzenga R. Single-step direct measurement of amyloid fibrils stiffness by peak force quantitative nanomechanical atomic force microscopy. Appl

[18] Sweers K, van der Werf K, Bennink M, Subramaniam V. Nanomechanical properties of α-synuclein amyloid fibrils: a comparative study by nanoindentation, harmonic

[19] Adamcik J, Lara C, Usov I, Jeong JS, Ruggeri FS, Dietler G, et al. Measurement of intrinsic properties of amyloid fibrils by the peak force QNM method. Nanoscale.

[20] Lee G, Lee W, Lee H, Lee SW, Yoon DS, Eom K, et al. Mapping the surface charge

[21] Ruggeri FS, Adamcik J, Jeong JS, Lashuel HA, Mezzenga R, Dietler G. Influence of the β-sheet content on the mechanical properties of aggregates during amyloid fibrilliza‐

[22] Lamour G, Yip CK, Li H, Gsponer J. High intrinsic mechanical flexibility of mouse prion nanofibrils revealed by measurements of axial and radial Young's moduli. ACS Nano.

[23] Lee W, Jung H, Son M, Lee H, Kwak TJ, Lee G, et al. Characterization of the regrowth behavior of amyloid-like fragmented fibrils decomposed by ultrasonic treatment. RSC

[24] Jaroniec CP, MacPhee CE, Bajaj VS, McMahon MT, Dobson CM, Griffin RG. Highresolution molecular structure of a peptide in an amyloid fibril determined by magic angle spinning NMR spectroscopy. Proc Natl Acad Sci U S A. 2004;101(3):711–6. [25] Meersman F, Cabrera RQ, McMillan PF, Dmitriev V. Compressibility of insulin amyloid fibrils determined by X-ray diffraction in a diamond anvil cell. High Pressure Res.

[26] Westermark P, Benson MD, Buxbaum JN, Cohen AS, Frangione B, Ikeda S, et al.

[27] Khurana R, Coleman C, Ionescu-Zanetti C, Carter SA, Krishna V, Grover RK, et al. Mechanism of thioflavin T binding to amyloid fibrils. J Struct Biol. 2005;151(3):229–38.

[29] Binnig G, Quate CF, Gerber C. Atomic force microscope. Phys Rev Lett. 1986;56(9):930.

[28] Giessibl FJ. Advances in atomic force microscopy. Rev Mod Phys. 2003;75(3):949.

Amyloid fibril protein nomenclature—2002. Amyloid. 2002;9(3):197.

distribution of amyloid fibril. Appl Phys Lett. 2012;101(4):043703–4.

tion. Angew Chem Int Ed. 2015;54(8):2462–6.

force microscopy, and Peakforce QNM. Nanoscale Res Lett. 2011;6(1):1–10.

amyloid formation. J Mol Biol. 2013;425(10):1765–81.

Phys Lett. 2011;98(19):193701.

2012;4(15):4426–9.

12022 Exploring New Findings on Amyloidosis

2014;8(4):3851–61.

2009;29(4):665–70.

Adv 2014;4(100):56561–6.

[56] Bokvist M, Lindström F, Watts A, Gröbner G. Two types of Alzheimer's β-amyloid (1– 40) peptide membrane interactions: aggregation preventing transmembrane anchoring versus accelerated surface fibril formation. J Mol Biol. 2004;335(4):1039–49.

[43] Pfreundschuh M, Martinez-Martin D, Mulvihill E, Wegmann S, Muller DJ. Multipara‐ metric high-resolution imaging of native proteins by force-distance curve-based AFM.

[44] Ferencz R, Sanchez J, Blümich B, Herrmann W. AFM nanoindentation to determine Young's modulus for different EPDM elastomers. Polym Test. 2012;31(3):425–32. [45] Foster B. New atomic force microscopy (AFM) approaches life sciences gently, quan‐

[46] Trtik P, Kaufmann J, Volz U. On the use of peak-force tapping atomic force microscopy for quantification of the local elastic modulus in hardened cement paste. Cem Concr

[47] Lee G, Lee H, Nam K, Han J-H, Yang J, Lee SW, et al. Nanomechanical characterization of chemical interaction between gold nanoparticles and chemical functional groups.

[48] Knowles TP, Fitzpatrick AW, Meehan S, Mott HR, Vendruscolo M, Dobson CM, et al. Role of intermolecular forces in defining material properties of protein nanofibrils.

[49] Strohman R. Maneuvering in the complex path from genotype to phenotype. Science.

[50] Verdile G, Fuller S, Atwood CS, Laws SM, Gandy SE, Martins RN. The role of beta amyloid in Alzheimer's disease: still a cause of everything or the only one who got

[51] Drolle E, Hane F, Lee B, Leonenko Z. Atomic force microscopy to study molecular mechanisms of amyloid fibril formation and toxicity in Alzheimer's disease. Drug

[52] Bucciantini M, Giannoni E, Chiti F, Baroni F, Formigli L, Zurdo J, et al. Inherent toxicity of aggregates implies a common mechanism for protein misfolding diseases. Nature.

[53] Kayed R, Head E, Thompson JL, McIntire TM, Milton SC, Cotman CW, et al. Common structure of soluble amyloid oligomers implies common mechanism of pathogenesis.

[54] Glabe CG, Kayed R. Common structure and toxic function of amyloid oligomers implies a common mechanism of pathogenesis. Neurology. 2006;66(1 suppl 1):S74–S8.

[55] Hertel C, Terzi E, Hauser N, Jakob-Røtne R, Seelig J, Kemp J. Inhibition of the electro‐ static interaction between β-amyloid peptide and membranes prevents β-amyloid-

induced toxicity. Proc Natl Acad Sci. 1997;94(17):9412–6.

Nat Protoc. 2014;9(5):1113–30.

12224 Exploring New Findings on Amyloidosis

Res. 2012;42(1):215–21.

Nanoscale Res Lett. 2012;7(1):1–11.

Science. 2007;318(5858):1900–3.

Metab Rev. 2014;46(2):207–23.

Science. 2003;300(5618):486–9.

2002;416(6880):507–11.

caught? Pharmacol Res. 2004;50(4):397–409.

2002;296(5568):701–3.

titatively, and correlatively. Am Lab 2012(4):24–8.

## **Effects of Amyloid-β Deposition on Mitochondrial Complex I Activity in Brain: A PET Study in Monkeys**

Hideo Tsukada

[71] Lin Y-C, Yu B-Y, Lin W-C, Lee S-H, Kuo C-H, Shyue J-J. Tailoring the surface potential of gold nanoparticles with self-assembled monolayers with mixed functional groups.

[72] Conklin D, Nanayakkara S, Park T-H, Lagadec MF, Stecher JT, Therien MJ, et al. Electronic transport in porphyrin supermolecule-gold nanoparticle assemblies. Nano

[73] Stehlik S, Petit T, Girard HA, Kromka A, Arnault J-C, Rezek B. Surface potential of diamond and gold nanoparticles can be locally switched by surrounding materials or

[74] Gutiérrez-Sánchez C, Pita M, Vaz-Domínguez C, Shleev S, De Lacey AL. Gold nano‐ particles as electronic bridges for laccase-based biocathodes. J Am Chem Soc.

[75] Raschke G, Kowarik S, Franzl T, Sönnichsen C, Klar T, Feldmann J, et al. Biomolecular recognition based on single gold nanoparticle light scattering. Nano Lett. 2003;3(7):935–

[76] Yoon G, Lee M, Kim JI, Na S, Eom K. Role of sequence and structural polymorphism on the mechanical properties of amyloid fibrils. PLoS one. 2014;9(2):e88502.

[77] Sawaya MR, Sambashivan S, Nelson R, Ivanova MI, Sievers SA, Apostol MI, et al. Atomic structures of amyloid cross-β spines reveal varied steric zippers. Nature.

[78] Choi B, Yoon G, Lee SW, Eom K. Mechanical deformation mechanisms and properties

[79] Hettiarachchi CA, Melton LD, Gerrard JA, Loveday SM. Formation of β-lactoglobulin nanofibrils by microwave heating gives a peptide composition different from conven‐

[80] Mankar S, Anoop A, Sen S, Maji SK. Nanomaterials: amyloids reflect their brighter side.

[81] Mostaert AS, Higgins MJ, Fukuma T, Rindi F, Jarvis SP. Nanoscale mechanical characterisation of amyloid fibrils discovered in a natural adhesive. J Biol Phys.

[82] Bolisetty S, Adamcik J, Heier J, Mezzenga R. Amyloid directed synthesis of titanium dioxide nanowires and their applications in hybrid photovoltaic devices. Adv Funct

[83] Yolamanova M, Meier C, Shaytan AK, Vas V, Bertoncini CW, Arnold F, et al. Peptide nanofibrils boost retroviral gene transfer and provide a rapid means for concentrating

of amyloid fibrils. Phys Chem Chem Phys. 2015;17(2):1379–89.

tional heating. Biomacromolecules. 2012;13(9):2868–80.

J Colloid Interface Sci. 2009;340(1):126–30.

applied voltage. J Nanopart Res. 2014;16(4):1–11.

Lett. 2012;12(5):2414–9.

12426 Exploring New Findings on Amyloidosis

2012;134(41):17212–20.

2007;447(7143):453–7.

Nano Rev 2011;2.

2006;32(5):393–401.

Mater. 2012;22(16):3424–28.

viruses. Nat Nanotechnol. 2013;8(2):130–6.

8.

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/62901

## **Abstract**

This chapter discusses the capabilities of positron emission tomography (PET) imaging for the diagnosis of Alzheimer's disease (AD) with deposition of amyloid-β (Aβ). We conducted a PET scan using 18F-2-tert-butyl-4-chloro-5-{6-[2-(2-fluoroethoxy)-ethoxy] pyridin-3-ylmethoxy}-2H-pyridazin-3-one (18F-BCPP-EF), a novel PET probe for mitochondrial complex I (MC-I) activity, in young and aged monkeys to demonstrate the normal aging effects on MC-I activity in the brain. The results revealed an age-related impairment of MC-I activity in the brain. Then, we conducted PET scan using 11C-PIB to detect the Aβ deposition in the some parts, not all, of the brains of some part of aged monkeys. For further assessments, PET scans using 11C-PIB for Aβ, 11C-DPA-713 for inflammation, 18F-fluoro-2-deoxy-D-glucose (18F-FDG) for regional cerebral metabolic rate of glucose (rCMRglc), and 18F-BCPP-EF for MC-I were performed in aged animals. When 18F-BCPP-EF uptake is plotted against 11C-PIB uptake in the cerebral cortical regions, it showed a significant negative correlation between them. Plotting of 11C-DPA-713 uptake against 11C-PIB resulted in a significant positive correlation. In contrast, plotting of rCMRglc against 11C-PIB did not reach a statistically significant level. Taken together, these results strongly suggested that 18F-BCPP-EF could discriminate the neuronally damaged areas with neuroinflammation where 18F-FDG could not, owing to its high uptake into the activated microglia.

**Keywords:** Alzheimer's disease, aging, brain, mitochondrial complex I, PET

## **1. Introduction**

Alzheimer's disease (AD) is neuropathologically characterized by the presence of neurofibril‐ lary tangles with the deposition of hyperphosphorylated tau protein inside nerve cells and

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

senile plaques with extracellular aggregation of amyloid-β (Aβ) protein, and the imaging of tau and Aβ is expected to provide quantitative information noninvasively for the diagnosis of AD. Pathological aging processes are thought to be a degenerative process caused by accumulated damages, which leads to cellular dysfunction, tissue failure, and death, result‐ ing in detectable changes in brain structure and function. Modern *in vivo* imaging techni‐ ques, such as X-ray computed tomography (X-CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), provide useful ways to examine these alterations and to separate normal age-related changes from pathological states. Because functional distur‐ bances precede structural changes determined by X-CT or MRI, the *in vivo* imaging obtained with PET may be abnormal, whereas the brain anatomy appears normal.

One trend is to apply target-specific PET probes for quantitative imaging of the specific neurological target molecules related to diseases, such as the dopaminergic system for schizophrenia [1] and Parkinson's disease (PD) [2], the serotonergic system for depression [3], and the cholinergic system forAD-type dementia [4]. Anothertrend is to measure more general indices for the pathophysiological abnormalities in diseases. To diagnose these diseases and to assess the treatment efficacy of developing drug candidates noninvasively with PET, we have anticipatedPETprobes that canprovide general indices of brain function, such as regional cerebral blood flow (rCBF) and regional cerebral metabolic rate of oxygen (rCMRO2), both of which have been recognized to be the gold standard indices for cerebral functions [5]. Other useful indicators are the regional cerebral metabolic rate of glucose (rCMRglc) assessed with 18F-fluoro-2-deoxy-D-glucose (18F-FDG; **Figure 1C**) [6]. PET using 18F-FDG is a well-establish‐ ed technique for the quantitative imaging of brain function in the living brain. Some re‐ search demonstrated that 18F-FDG could predict an onset of AD. However, as demonstrated in the brains of rat and monkey ischemic models [7, 8], the unexpectedly high uptake of 18F-FDG in damaged areas suggested that 18F-FDG was taken up into not only normal tissues but also inflammatory regions with microglial activation, which hampers the accurate diagnosis of brain function using 18F-FDG.

**Figure 1.** PET probes used: (A) 11C-PIB for Aβ, (B) 11C-DPA-713 for TSPO, (C) 18F-FDG for rCMRglc, (D) 11C-(+)-3-MPB for mAChR, (E) 11C-(*R*)-MeQAA for α7-nAChR, and (F) 18F-BCPP-EF for MC-I.

Several hypotheses of aging at the molecular level, such as shortening of telomerase, DNA methylation, reactive oxygen species (ROS) generation, and mitochondrial abnormalities, have been proposed. Among these, the "mitochondrial free radical theory of aging" has been highlighted [9]. In mammalian cells, the electron transport chain in mitochondria consists of five complexes from I to V, and the main role of mitochondria was recognized to be energy transduction of ATP. Their dysfunction was thought to be limited to ATP deficiency result‐ ing in necrotic cell death; however, the mechanisms of cell death have been found to include mitochondrial contribution to oxidative stress and apoptosis [10]. Previous studies demon‐ strated an age-related increase in ROS production using rat brain homogenates [11], cortical slices [12], or synaptosomes [13]. Furthermore, mitochondrial dysfunction contributes to the pathophysiology of acute and chronic neurodegenerative disorders [14].

In the present chapter, the capability of assessment of mitochondrial complex I (MC-I) activity is introduced for detection of neurodegenerative damage associated with Aβ deposition. We recently developed and evaluated 18F-2-tert-butyl-4-chloro-5-{6-[2-(2-fluoroethoxy)-ethoxy] pyridin-3-ylmethoxy}-2H-pyridazin-3-one (18F-BCPP-EF), a novel PET probe for MC-I activity (**Figure 1E**) [15]. The translational research has been conducted using an animal PET to assess the aging as well as Aβ deposition effects on MC-I activity in the living brains of young (3–5 years old, corresponding to high-teens in humans) and aged (20–24 years old, corresponding to 75 years old and more) male monkeys [16, 17].

## **2. Aging and cholinergic neuronal system**

senile plaques with extracellular aggregation of amyloid-β (Aβ) protein, and the imaging of tau and Aβ is expected to provide quantitative information noninvasively for the diagnosis of AD. Pathological aging processes are thought to be a degenerative process caused by accumulated damages, which leads to cellular dysfunction, tissue failure, and death, result‐ ing in detectable changes in brain structure and function. Modern *in vivo* imaging techni‐ ques, such as X-ray computed tomography (X-CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), provide useful ways to examine these alterations and to separate normal age-related changes from pathological states. Because functional distur‐ bances precede structural changes determined by X-CT or MRI, the *in vivo* imaging obtained

One trend is to apply target-specific PET probes for quantitative imaging of the specific neurological target molecules related to diseases, such as the dopaminergic system for schizophrenia [1] and Parkinson's disease (PD) [2], the serotonergic system for depression [3], and the cholinergic system forAD-type dementia [4]. Anothertrend is to measure more general indices for the pathophysiological abnormalities in diseases. To diagnose these diseases and to assess the treatment efficacy of developing drug candidates noninvasively with PET, we have anticipatedPETprobes that canprovide general indices of brain function, such as regional cerebral blood flow (rCBF) and regional cerebral metabolic rate of oxygen (rCMRO2), both of which have been recognized to be the gold standard indices for cerebral functions [5]. Other useful indicators are the regional cerebral metabolic rate of glucose (rCMRglc) assessed with 18F-fluoro-2-deoxy-D-glucose (18F-FDG; **Figure 1C**) [6]. PET using 18F-FDG is a well-establish‐ ed technique for the quantitative imaging of brain function in the living brain. Some re‐ search demonstrated that 18F-FDG could predict an onset of AD. However, as demonstrated in the brains of rat and monkey ischemic models [7, 8], the unexpectedly high uptake of 18F-FDG in damaged areas suggested that 18F-FDG was taken up into not only normal tissues but also inflammatory regions with microglial activation, which hampers the accurate diagnosis

**Figure 1.** PET probes used: (A) 11C-PIB for Aβ, (B) 11C-DPA-713 for TSPO, (C) 18F-FDG for rCMRglc, (D) 11C-(+)-3-MPB

for mAChR, (E) 11C-(*R*)-MeQAA for α7-nAChR, and (F) 18F-BCPP-EF for MC-I.

with PET may be abnormal, whereas the brain anatomy appears normal.

of brain function using 18F-FDG.

126 128Exploring New Findings on Amyloidosis

There have been a number of reports on age-related alterations in neurochemical and neurophysiological functions in the brain, associated with changes in the neurotransmitter synthesis in presynaptic neurons, release into synaptic cleft, reuptake availability, binding to receptors, and signal transduction, all of which are related to the declines of specific motor, cognitive and emotional functions in primates. Among the variety of neurotransmitter receptors, we focused on the effects of aging process on cholinergic receptors, which had previously assessed in the postmortem primate brain tissues [18].

## **2.1. Aging effects on muscarinic cholinergic receptor function**

The cholinergic receptor (AChR) population is divided into muscarinic (mAChR) and nicotinic (nAChR) subclasses in the central nervous system (CNS), and the CNS mAChR system plays an important role in memory and cognitive functions. AD is neuropathological‐ ly characterized by the presence of neurofibrillary tangles with the deposition of Hyperphos‐ phorylated tau protein inside nerve cells and senile plaques with extracellular aggregation of Aβ protein [19, 20]. Accompanied with tau and Aβ depositions, loss of cholinergic neurons in the forebrain, reduced cholinergic activity in the hippocampus and cortical loss of choline acetyltransferase, and reduced central mAChR binding have been observed in the brain of AD patients [21]. The severity of these cholinergic abnormalities is closely correlated with the degree of memory impairment in aged monkeys [22] and dementia patients [21].

Several antagonist-based 11C-labeled PET probes for imaging mAChR have been developed and attempted to determine quantitatively the age-related alterations of mAChR in the living brain using 11C-benztropine [23], *N*-11C-methyl-4-piperidyl benzilate (11C-4-MPB) [24], and 11Ctropanyl benzilate (TBZ) [25]. These PET probes for mAChR, however, showed relatively low uptake to the brain and also slow dissociation rates from mAChR, which may limit the estimation of the density of binding sites *in vivo* [26]. To solve these problems, we proposed a novel mAChR probe, *N*-11C-methyl-3-piperidyl benzilate (11C-3-MPB) (**Figure 1D**) [27, 28], and assessed the aging effects on mAChR binding in comparison to young and aged monkeys [29].

11C-(+)3-MPB was labeled by *N*-methylation of respective nor-compound with 11C-methyl iodide converted from 11C-CO2 by LiAlH4 reduction followed by reaction with HI [27, 28]. A monkey (*Macaca mulatta*) was seated on a monkey chair under conscious condition and fixed with stereotactic coordinates under conscious state [30]. For the kinetic analysis of 11C-(+)3- MPB binding, arterial blood sampling was conducted to determine the input function using metabolic profile in plasma. The PET data obtained were reconstructed by the filtered backprojection (FBP) method. Volumes of interest (VOIs) in brain regions were drawn manually on the MRI, and VOIs of MRI were superimposed on the coregistered PET images to meas‐ ure the time activity curves (TACs) of each PET probe for kinetic analyses using Logan graphical analysis with metabolite-corrected plasma input in the living brain [31].

The TACs of 11C-(+)3-MPB in the frontal, temporal, and occipital cortices reached their peaks 40 min after injection, whereas the striatal and hippocampal regions reached peak values 60

**Figure 2.** MRI and PET images of 11C-(+)3-MPB in the young and aged monkey brains (*M. mulatta*). PET data were col‐ lected in the conscious state with a high-resolution PET scanner. Each PET image was generated by summation of im‐ age data from 60 to 91 min post-injection. The stereotactic coordinates of PET and MRI were adjusted based on the orbitomeatal (OM) line.

min after injection [28]. In aged monkeys, the TACs of 11C-(+)3-MPB in regions rich in mAChR peaked at earlier time points, with faster elimination rates than those in young monkeys. As a result of Logan graphical analysis using metabolite-corrected plasma input, significant agerelated alterations of the *in vivo* binding of 11C-(+)3-MPB were observed in the temporal and frontal cortices and the striatum (**Figure 2**). Aged animals showed the age-related reduction of the maximum number of binding sites (*B*max) of mAChR, whereas there were no age-related alterations of the affinity (1/Kd) of mAChR [29].

## **2.2. Aging effects on nicotinic cholinergic receptor function**

Several antagonist-based 11C-labeled PET probes for imaging mAChR have been developed and attempted to determine quantitatively the age-related alterations of mAChR in the living

tropanyl benzilate (TBZ) [25]. These PET probes for mAChR, however, showed relatively low uptake to the brain and also slow dissociation rates from mAChR, which may limit the estimation of the density of binding sites *in vivo* [26]. To solve these problems, we proposed a

assessed the aging effects on mAChR binding in comparison to young and aged monkeys [29]. 11C-(+)3-MPB was labeled by *N*-methylation of respective nor-compound with 11C-methyl iodide converted from 11C-CO2 by LiAlH4 reduction followed by reaction with HI [27, 28]. A monkey (*Macaca mulatta*) was seated on a monkey chair under conscious condition and fixed with stereotactic coordinates under conscious state [30]. For the kinetic analysis of 11C-(+)3- MPB binding, arterial blood sampling was conducted to determine the input function using metabolic profile in plasma. The PET data obtained were reconstructed by the filtered backprojection (FBP) method. Volumes of interest (VOIs) in brain regions were drawn manually on the MRI, and VOIs of MRI were superimposed on the coregistered PET images to meas‐ ure the time activity curves (TACs) of each PET probe for kinetic analyses using Logan

graphical analysis with metabolite-corrected plasma input in the living brain [31].

The TACs of 11C-(+)3-MPB in the frontal, temporal, and occipital cortices reached their peaks 40 min after injection, whereas the striatal and hippocampal regions reached peak values 60

**Figure 2.** MRI and PET images of 11C-(+)3-MPB in the young and aged monkey brains (*M. mulatta*). PET data were col‐ lected in the conscious state with a high-resolution PET scanner. Each PET image was generated by summation of im‐ age data from 60 to 91 min post-injection. The stereotactic coordinates of PET and MRI were adjusted based on the

11C-methyl-4-piperidyl benzilate (11C-4-MPB) [24], and 11C-

11C-methyl-3-piperidyl benzilate (11C-3-MPB) (**Figure 1D**) [27, 28], and

brain using 11C-benztropine [23], *N*-

novel mAChR probe, *N*-

128 130Exploring New Findings on Amyloidosis

orbitomeatal (OM) line.

The CNSAChRsystems, classified into mAChRand nAChR, play an importantrole in memory and cognitive functions. In the last two decades, 17 different nAChR subunits (α1–α10, β1– β4,γ, δ and ε) have been cloned, and the prominent nAChRs are the α4β2 heteromeric and α7 homomeric subtypes in the brain [32]. Among them, because α7 has high permeability for Ca2+, it can be assumed that, in addition to the ionotropic function induced by membrane depola‐ rization, α7-nAChR is associated with metabotropic activity coupled to Ca2+-regulated secondmessenger signaling required for the modulation of neuron excitability, neurotransmitter release, induction of long-term potentiation (LTP), and cognitive-associated processing of learning and memory. In addition, α7-nAChR may contribute to neuroprotection by modu‐ lating the neurotrophic system crucial for the maintenance of cholinergic neuron integrity and also by stimulating signal transduction pathways that support neuron survival [32].

A PET study indicated that decreases in 11C-nicotine brain uptake were significantly correlat‐ ed with cognitive deficits in AD patients [33]; however, nAChR deficits in the different types of dementia are assumed to be reflected by subtype and region specificity. For the noninva‐ sive imaging of α7-nAChR with more subtype specificity, several 11C-labeled PET probes have been developed and evaluated, including 11C-CHIBA-1001, 11C-A-582941, and 11C-A-844606 [34]. However, because of low brain uptake, high nonspecific binding, and/or low selectivity to α7-nAChR against 5-HT3R, almost none of these PET probes have demonstrated clinically useful specific binding to α7-nAChR in nonhuman primate brain. Because we recently developed novel PET probes for α7-nAChR, (*R*)-2-[11C]methylamino-benzoic acid 1-azabicycle[2.2.2]oct-3-yl ester [11C-(*R*)-MeQAA; **Figure 1E**] [35], the aging effects on α7-nAChR binding was assessed using 11C-(*R*)-MeQAA in comparison to young and aged monkeys [36].

11C-(*R*)-MeQAA was labeled by *N*-methylation of respective nor-compounds [(*R*)-BH3QAA] with 11C-methyl triflate prepared from 11C-methyl iodide through a glass column containing silver triflate [35]. PET measurements of conscious monkeys were conducted as described in Section 2.2 with arterial blood sampling for plasma metabolic analysis followed by PET image reconstruction and TAC acquisition in the VOIs for kinetic analyses. The values of nondis‐ placeable binding potential (BPND) were evaluated by two-compartment models (2-TC) analysis using the metabolite-corrected plasma input [37] and simplified reference tissue model (SRTM) analysis using the TAC in the cerebellum as an indirect input function [38].

11C-(*R*)-MeQAA images in the brain of young normal monkeys, showing high and heteroge‐ neous uptake of [11C](*R*)-MeQAA into the brain, were determined between 60 and 90 min after the bolus injection. The uptake of radioactivity was high in the thalamus and striatum,

intermediate in the hippocampus, frontal, temporal, and occipital cortices, and low in the cerebellum [35, 36]. The uptake of 11C-(*R*)-MeQAA was significantly higherthan that of 11C-(*S*)- MeQAA in the thalamus, hippocampus, and cortical regions, and the specific binding of 11C- (*R*)-MeQAA was inhibited by the preadministration of SSR180711, an α7-nAChR partial agonist [35]. In contrast, the uptake of 11C-(*R*)-MeQAA into the cerebellum of monkeys was not affected by SSR180711 [35], suggesting that the cerebellum could be applicable for the reference region for the quantitative analysis of 11C-(*R*)-MeQAA binding in the living brain. The clearance rate of 11C-(*R*)-MeQAA in plasma was rapid and relatively stable in plasma. To determine the practicality of the simplified analytical method of 11C-(*R*)-MeQAA with SRTM to calculate the BPND using the TAC in the cerebellum as an indirect input function, we verified it by correlation analyses with 2-TC-BPND values calculated using the metabolite-corrected plasma input. Because of a good correlation between 2-TC and SRTM analyses, 11C-(*R*)- MeQAA binding to α7-nAChRin young and aged monkey brain was determined as the SRTM-BPND values without arterial blood sampling to avoid excessive stress on aged animals. When determining the aging effects on 11C-(*R*)-MeQAA binding, all regions, except the occipital cortex, revealed no significant differences in the BPND values of 11C-(*R*)-MeQAA in the brains of aged and young animals [36]. Although human aging is known to preferentially affect the rCMRglc in the frontal and temporal lobes, our previous studies reported that the occipital cortex showed the most profound reductions of CBF [39], rCMRglc [39], and MC-I [16] in aged monkeys. Because the differences in cortical activity between monkey and human reflect the evolutionary significance of their frontal cortex, the most marked age-related alterations of α7-nAChR activity would be determined in regions such as the frontal cortex, not in the occipital cortex, in humans. These results apparently revealed that aging effects were much less on α7-nAChR compared to mAChR in the living brain.

## **3. Aging and MC-I activity**

Mitochondria are called "cellular power plants" because they generate most of the ATP used as a source of chemical energy. In mammalian cells, the electron transport chain in mitochon‐ dria consists of five complexes from I to V, and complex I (MC-I; NADH-ubiquinone oxidor‐ eductase, EC <IP_ADDRESS>) is the first and rate-limiting step of the overall respiratory activity and oxidative phosphorylation under physiological conditions. Glucose is converted to pyruvate followed by transformation into acetyl-CoA by pyruvate dehydrogenase (PDH) in the mitochondria, which is subsequently fed into the tricarboxylic acid (TCA) cycle, ultimately producing ATP via the electron transport system and oxidative phosphorylation (which is indispensable for cell survival). Mitochondrial dysfunction contributes to the pathophysiolo‐ gy of neurodegenerative diseases [40], some part of which has been considered to relate to the fact that mitochondria are the main intracellular source of ROS in cells and also the main target of ROS-mediated damage. Noninvasive assessment of living brain could be useful for the diagnostic, prognostic, and treatment monitoring of neurodegenerative diseases related to impaired MC-I function; however, no proper PET probes for MC-I imaging in the brain have been developed prior to those that we have recently described [15].

## **3.1. Development of PET probe for MC-I imaging**

intermediate in the hippocampus, frontal, temporal, and occipital cortices, and low in the cerebellum [35, 36]. The uptake of 11C-(*R*)-MeQAA was significantly higherthan that of 11C-(*S*)- MeQAA in the thalamus, hippocampus, and cortical regions, and the specific binding of 11C- (*R*)-MeQAA was inhibited by the preadministration of SSR180711, an α7-nAChR partial agonist [35]. In contrast, the uptake of 11C-(*R*)-MeQAA into the cerebellum of monkeys was not affected by SSR180711 [35], suggesting that the cerebellum could be applicable for the reference region for the quantitative analysis of 11C-(*R*)-MeQAA binding in the living brain. The clearance rate of 11C-(*R*)-MeQAA in plasma was rapid and relatively stable in plasma. To determine the practicality of the simplified analytical method of 11C-(*R*)-MeQAA with SRTM to calculate the BPND using the TAC in the cerebellum as an indirect input function, we verified it by correlation analyses with 2-TC-BPND values calculated using the metabolite-corrected plasma input. Because of a good correlation between 2-TC and SRTM analyses, 11C-(*R*)- MeQAA binding to α7-nAChRin young and aged monkey brain was determined as the SRTM-BPND values without arterial blood sampling to avoid excessive stress on aged animals. When determining the aging effects on 11C-(*R*)-MeQAA binding, all regions, except the occipital cortex, revealed no significant differences in the BPND values of 11C-(*R*)-MeQAA in the brains of aged and young animals [36]. Although human aging is known to preferentially affect the rCMRglc in the frontal and temporal lobes, our previous studies reported that the occipital cortex showed the most profound reductions of CBF [39], rCMRglc [39], and MC-I [16] in aged monkeys. Because the differences in cortical activity between monkey and human reflect the evolutionary significance of their frontal cortex, the most marked age-related alterations of α7-nAChR activity would be determined in regions such as the frontal cortex, not in the occipital cortex, in humans. These results apparently revealed that aging effects were much

Mitochondria are called "cellular power plants" because they generate most of the ATP used as a source of chemical energy. In mammalian cells, the electron transport chain in mitochon‐ dria consists of five complexes from I to V, and complex I (MC-I; NADH-ubiquinone oxidor‐ eductase, EC <IP_ADDRESS>) is the first and rate-limiting step of the overall respiratory activity and oxidative phosphorylation under physiological conditions. Glucose is converted to pyruvate followed by transformation into acetyl-CoA by pyruvate dehydrogenase (PDH) in the mitochondria, which is subsequently fed into the tricarboxylic acid (TCA) cycle, ultimately producing ATP via the electron transport system and oxidative phosphorylation (which is indispensable for cell survival). Mitochondrial dysfunction contributes to the pathophysiolo‐ gy of neurodegenerative diseases [40], some part of which has been considered to relate to the fact that mitochondria are the main intracellular source of ROS in cells and also the main target of ROS-mediated damage. Noninvasive assessment of living brain could be useful for the diagnostic, prognostic, and treatment monitoring of neurodegenerative diseases related to impaired MC-I function; however, no proper PET probes for MC-I imaging in the brain have

less on α7-nAChR compared to mAChR in the living brain.

been developed prior to those that we have recently described [15].

**3. Aging and MC-I activity**

130 132Exploring New Findings on Amyloidosis

As PET probe for MC-I imaging, BMS-747158-01 showed inhibitory activity on MC-I func‐ tion by binding to MC-I, and its F-18 derivative 18F-BMS-747158-01 was originally developed as a myocardial perfusion imaging agent [41]. However, we also realized that 18F-BMS-747158-01 revealed relatively high nonspecific binding in the brain based on the lower degree of inhibition with rotenone, a specific MC-I inhibitor, in both *in vitro* and *in vivo* assessments [7, 8]. To solve the problem, we redesigned to modify the chemical structure of 18F-BMS-747158-01 to induce lower lipophilicity and lower affinity [15, 42]. We recently developed a novel PET probe, 18F-BCPP-EF, and evaluated its properties in the *in vitro* and *in vivo* assessments [7, 8, 15, 16].

For the analysis of the affinity of 18F-BCPP-EF, an *in vitro* binding assay was conducted using 3 H-dihydrorotenone and bovine cardiomyocyte submitochondrial particles (SMP) to deter‐ mine the 50% inhibition (IC50) values, which were converted to the inhibition constant (Ki). 18F-BCPP-EF was radiolabeled by the nucleophilic 18F-fluorination of the corresponding tosylate precursor, toluene-4-sulfonic acid 2-{2-[5-(1-tert-butyl-5-chloro-6-oxo-1,6-dihydro-pyrida‐ zin-4-yloxymethyl)-pyridin-2-yloxy]-ethoxy}-ethyl ester [15]. For the assessment of binding specificity of the PET probe to MC-I, vehicle or rotenone, a specific MC-I inhibitor, at a dose of 0.1 mg/kg was infused to anesthetised rats or conscious monkeys through a vein for 1 h, and then 18F-BCPP-EF was injected as a bolus for PET measurement. PET measurements of young monkeys (3–5 years old) were conducted under conscious state as described in Section 2.2 with arterial blood sampling for plasma metabolic analysis followed by PET image reconstruction and TAC acquisition in the VOIs aided by MRI of individual animals for kinetic analyses [16, 17]. The total distribution volume (DV) values were evaluated by Logan plot graphical analysis using the metabolite-corrected plasma input [33].

18F-BCPP-EF showed the lower affinity (Ki=2.31 nM) with lower lipophilicity (logD7.4=3.03) for MC-I of bovine cardiomyocytes than that of BMS-747158-01 (Ki=0.95 nM, logD7.4=3.69). In PET study in rats, the radioactivity level of 18F-BCPP-EF in the brain showed rapid uptake and gradual decrease with time just after the injection under vehicle condition. In the heart, 18F-BCPP-EF exhibited slow accumulation up to 30 min after the injection followed by a slight washout. With preadministration of rotenone, although a dose escalation study of rotenone was impossible because of its lethal effects on cardiac function, a significant reduction of 18F-BCPP-EF uptake was observed in the brain and heart, even at a relatively low dose of 0.1 mg/ kg/h. 18F-BMS-747158-01 showed a tendency of decreased brain uptake with rotenone infusion but was not fully inhibited [7].

In the conscious monkey brain, TACs of 18F-BCPP-EF peaked between 10 and 20 min after the injection, except in the occipital cortex (40 min), followed by the gradual elimination with time. With preadministration of rotenone, a specific MC-I inhibitor, at a dose of 0.1 mg/kg/h, the uptake of 18F-BCPP-EF into the brain, especially in the frontal and temporal cortices and striatum, was significantly facilitated just afterthe injection followed by faster elimination than normal from the brain regions. The washout and metabolic rates of 18F-BCPP-EF in plasma were rapid; only 10% of nonmetabolized 18F-BCPP-EF was detected 60 min after the injection, which was were nearly identical with that of rotenone-treated animals. The DV values calculated by Logan plot graphical analysis were the highest in the occipital cortex, higher in the striatum, intermediate in the frontal and temporal cortices and cerebellum, and lowest in the hippocampus of young monkey. Rotenone administration resulted in a significant and marked reduction of the binding of 18F-BCPP-EF to MC-Iin the living monkey brain [16]. Taken together, these results clearly suggested that 18F-BCPP-EF was a useful PET probe for the quantitative imaging of MC-I activity in the living brain.

## **3.2. Aging effects on MC-I activity**

Several hypotheses of aging have been proposed, and mitochondrialrespiratory chain failures have been implicated as factors in the aging process, which was called the "mitochondrial free radical theory of aging" [9–13]. This theory is based on the results that (1) mitochondrial ROS production increases with age, (2) the activity of ROS-scavenging enzymes declines with age, (3) mutations of mitochondrial DNA (mtDNA) accumulate during aging, and (4) somatic mtDNA mutations impair respiratory chain function, which results in a further increase in ROS production [9–13]. Mitochondria are the main intracellular source of ROS and also the main target of oxyradical-mediated damage, and cumulative free radical damage leads to significant changes in brain mitochondrial function.

As described in Section 3.1, because we could confirm the capability of 18F-BCPP-EF as PET probe for the noninvasive assessment of MC-I activity in the living brain, we further ex‐ plored to see the aging effects on MC-I activity in comparison to young and aged monkeys under conscious condition [16]. All study procedures were identical as described in Section 3.1, except that the subjects were aged male monkeys (20–24 years old).

Aided by MRI of individual monkeys, the VOIs were set on PET images of 18F-BCPP-EF to obtain TACs. The peak of 18F-BCPP-EF slightly shifted to a later time period between 20 and 30 min after the injection and also provided significantly lower levels than those in young animals shown in Section 3.1. The washout and metabolic patterns of 18F-BCPP-EF in plasma of aged monkeys were nearly identical to those in young animals. When determining the effects of aging on 18F-BCPP-EF binding to MC-I assessed by Logan plot graphical analysis, the data revealed significantly lower DV values of 18F-BCPP-EF in every brain region ana‐ lyzed in aged animals compared to those in young ones [16].

The remarkable finding of the present study was that 18F-BCPP-EF detected the age-related reduction of MC-I activity in the living brain of monkey under conscious conditions with PET (**Figure 3**). It was of interest that the activity of complexes I and IV decreased with age in the brain of humans [43], whereas that of complexes II, III, and V remained mostly un‐ changed [44]. Because all these findings described above were obtained by the *in vitro* assessments of dissected organ samples, the present data are the first to demonstrate the alterations of MC-I activity in the living brain of a nonhuman primate by a noninvasive method using 18F-BCPP-EF and PET [16].

**Figure 3.** MRI and PET images of 18F-BCPP-EF in young and aged monkeys (*M. mulatta*). PET scans were acquired for 91 min after 18F-BCPP-EF injection with sequential arterial blood sampling. The binding of 18F-BCPP-EF to MC-I was calculated using Logan graphical analysis with metabolite-corrected plasma input.

## **4. Effects of Aβ deposition on AChR and MC-I**

calculated by Logan plot graphical analysis were the highest in the occipital cortex, higher in the striatum, intermediate in the frontal and temporal cortices and cerebellum, and lowest in the hippocampus of young monkey. Rotenone administration resulted in a significant and marked reduction of the binding of 18F-BCPP-EF to MC-Iin the living monkey brain [16]. Taken together, these results clearly suggested that 18F-BCPP-EF was a useful PET probe for the

Several hypotheses of aging have been proposed, and mitochondrialrespiratory chain failures have been implicated as factors in the aging process, which was called the "mitochondrial free radical theory of aging" [9–13]. This theory is based on the results that (1) mitochondrial ROS production increases with age, (2) the activity of ROS-scavenging enzymes declines with age, (3) mutations of mitochondrial DNA (mtDNA) accumulate during aging, and (4) somatic mtDNA mutations impair respiratory chain function, which results in a further increase in ROS production [9–13]. Mitochondria are the main intracellular source of ROS and also the main target of oxyradical-mediated damage, and cumulative free radical damage leads to

As described in Section 3.1, because we could confirm the capability of 18F-BCPP-EF as PET probe for the noninvasive assessment of MC-I activity in the living brain, we further ex‐ plored to see the aging effects on MC-I activity in comparison to young and aged monkeys under conscious condition [16]. All study procedures were identical as described in Section

Aided by MRI of individual monkeys, the VOIs were set on PET images of 18F-BCPP-EF to obtain TACs. The peak of 18F-BCPP-EF slightly shifted to a later time period between 20 and 30 min after the injection and also provided significantly lower levels than those in young animals shown in Section 3.1. The washout and metabolic patterns of 18F-BCPP-EF in plasma of aged monkeys were nearly identical to those in young animals. When determining the effects of aging on 18F-BCPP-EF binding to MC-I assessed by Logan plot graphical analysis, the data revealed significantly lower DV values of 18F-BCPP-EF in every brain region ana‐

The remarkable finding of the present study was that 18F-BCPP-EF detected the age-related reduction of MC-I activity in the living brain of monkey under conscious conditions with PET (**Figure 3**). It was of interest that the activity of complexes I and IV decreased with age in the brain of humans [43], whereas that of complexes II, III, and V remained mostly un‐ changed [44]. Because all these findings described above were obtained by the *in vitro* assessments of dissected organ samples, the present data are the first to demonstrate the alterations of MC-I activity in the living brain of a nonhuman primate by a noninvasive method

quantitative imaging of MC-I activity in the living brain.

significant changes in brain mitochondrial function.

3.1, except that the subjects were aged male monkeys (20–24 years old).

lyzed in aged animals compared to those in young ones [16].

using 18F-BCPP-EF and PET [16].

**3.2. Aging effects on MC-I activity**

132 134Exploring New Findings on Amyloidosis

Hallmark pathologies of AD have been assumed to the formation of extracellular aggrega‐ tion of Aβ protein (senile plaques) [19] and intraneuronal aggregation of phosphorylated tau protein (neurofibrillary tangle) [20], pathogenic microglial activation [45], and oxidative stress reactions [13]. Furthermore, recent reports suggested that nondeposited and nonfibrillar assemblies of Aβ peptides are considered to play a primary role in AD, which might be precursors in fibrillogenesis to mediate the neurotoxicity, including oxidative stress in AD [46]. This session discusses the effects of Aβ-related pathological changes on nAChR binding [36] and also on MC-I activity [17] assessed in aged monkey brain using animal PET.

## **4.1. Aging effects on Aβ deposition and neuroinflammation**

For the quantitative measurements of Aβ deposition in the living brain, 11C-PIB was synthe‐ sized by *N*-methylation of nor-compound *N*-desmethyl-PIB with 11C-methyl triflate (**Figure 1A**) [47]. For the assessment of neuroinflammation, 11C-DPA-713 was synthesized by *N*methylation of nor-compound*N*-desmethyl-DPA with 11C-methyltriflate (**Figure 1B**) [48]. PET measurements with these two PET probes were conducted under conscious state as descri‐ bed in Section 2.2. For the analysis of 11C-PIB uptake, standard uptake value (SUV) images were created, and the VOIs were set on each SUV images with the aid of MRI. For the analysis of 11C-DPA-713 uptake, SUV images were created, and VOIs were set on each SUV images.

We had previously found that some, but not all, of aged monkeys exhibited higher 11C-PIB uptake than young ones, suggesting Aβ deposition even in the brain of monkey [49]. Although the SUVs of 11C-PIB were slightly high in the striatal regions, hippocampus, parietal cortex, and thalamus in aged monkeys, it was reported that aged monkeys did not reveal as high Aβ deposition as determined in AD patients [50] and also that no species besides humans has yet shown drastic neuron loss or cognitive decline approaching clinical-grade AD in humans. The SUVs of 11C-DPA-713 were relatively high in the striatal regions, hippocampus, temporal cortex, and thalamus. The plot of SUV of 11C-DPA-713 against SUV of 11C-PIB revealed significant positive correlation both in the cortical regions. When rCMRglc ratio is plotted against SUV of 11C-DPA-713, the results provided the significant positive correlation in the cortical regions. There results strongly suggest that the Aβ deposition as measured with 11C-PIB induced neuroinflammation with microglial activation as determined with 11C-DPA-713 as well as 18F-FDG (**Figure 4**).

**Figure 4.**  Effects of Aβ deposition on nAChR binding**

Postmortem studies of human brains have suggested that a deficit of α7-nAChR is related to AD, dementia with Lewy bodies, and schizophrenia [32]. Aβ has a high affinity to α7-nAChR upon being enriched in basal forebrain areas, and initial Aβ deposition in early AD overlaps with α7-nAChR expression in these regions [51]. α7-nAChR facilitates binding, internaliza‐ tion, and accumulation of Aβ1–42 and may result in the selective vulnerability of specific cells expressing α7-nAChR [52]. Oligomers of Aβ disrupt synaptic plasticity and cognitive function when administered at nanomolar range concentration through the modulation of NMDA receptor function to depress NMDA-evoked currents [53, 54].

To assess the effect of Aβ deposition on α7-nAChR function, the correlation between 11C-PIB uptake and 11C-(*R*)-MeQAA was analyzed [36]. As described in Section 2.2, all regions, except

the occipital cortex, revealed no significant differences in the BPND values of 11C-(*R*)-MeQAA in the brains of aged and young animals. However, of interest, when the BPND values of 11C-(*R*)- MeQAA are plotted against the SUVR of 11C-PIB in the corresponding VOIs of aged animals, the results indicated a significant positive correlation between them (**Figure 5**). The α7-nAChR had been assumed to decrease with the aging process; however, the data seem to be contro‐ versial because of the dose-dependent interaction aspects between of Aβ and α7-nAChR. In young and normal conditions, there is an equilibrium between production and elimination of Aβ, which maintains Aβ in a steady state to perform physiologic roles by the interaction with α7-nAChR; thus, low (on the order of picomolar) concentrations of Aβ1–42 may play a role in modulating synaptic plasticity and enhancing cognitive function in mice via interaction with α7-nAChR, probably in presynaptic neurons [55]. In aging with pathologic conditions, the balance between Aβ formation and clearance is impaired, which leads to Aβ accumula‐ tion and α7-nAChR deficit as observed in postmortem brains of AD patients [32]. These results suggest that α7-nAChR-Aβ interaction has dual effects on brain function following aging or injury as well as preserving physiologic roles, causing the controversial results in the aging effects on the α7-nAChR level. One previous study clearly demonstrated the significant reduction of α7-nAChR level in neurons and also Aβ-induced up-regulation of α7-nAChR on astrocytes in postmortem AD brain compared to that in age-matched control [56]. α7-nAChR may be chronically inactivated in an antagonistic fashion through prolonged interaction with increased levels (on the order of nanomolar) ofAβ, resulting in the up-regulation of α7-nAChR.

and thalamus in aged monkeys, it was reported that aged monkeys did not reveal as high Aβ deposition as determined in AD patients [50] and also that no species besides humans has yet shown drastic neuron loss or cognitive decline approaching clinical-grade AD in humans. The SUVs of 11C-DPA-713 were relatively high in the striatal regions, hippocampus, temporal cortex, and thalamus. The plot of SUV of 11C-DPA-713 against SUV of 11C-PIB revealed significant positive correlation both in the cortical regions. When rCMRglc ratio is plotted against SUV of 11C-DPA-713, the results provided the significant positive correlation in the cortical regions. There results strongly suggest that the Aβ deposition as measured with 11C-PIB induced neuroinflammation with microglial activation as determined with 11C-DPA-713

**Figure 4.** PET/MRI fusion images of 11C-PIB, 11C-DPA-713, and 18F-BCPP-EF uptake in the brains of aged monkeys (*M. mulatta*). 18F-BCPP-EF brain imaging was performed in monkey 1 with the highest binding of all 20 animals in the

Postmortem studies of human brains have suggested that a deficit of α7-nAChR is related to AD, dementia with Lewy bodies, and schizophrenia [32]. Aβ has a high affinity to α7-nAChR upon being enriched in basal forebrain areas, and initial Aβ deposition in early AD overlaps with α7-nAChR expression in these regions [51]. α7-nAChR facilitates binding, internaliza‐ tion, and accumulation of Aβ1–42 and may result in the selective vulnerability of specific cells expressing α7-nAChR [52]. Oligomers of Aβ disrupt synaptic plasticity and cognitive function when administered at nanomolar range concentration through the modulation of NMDA

To assess the effect of Aβ deposition on α7-nAChR function, the correlation between 11C-PIB uptake and 11C-(*R*)-MeQAA was analyzed [36]. As described in Section 2.2, all regions, except

as well as 18F-FDG (**Figure 4**).

134 136Exploring New Findings on Amyloidosis

conscious state and in monkey 2 with the lowest binding.

**4.2. Effects of Aβ deposition on nAChR binding**

receptor function to depress NMDA-evoked currents [53, 54].

**Figure 5.**   Effects of Aβ deposition on MC-I activity**

As shown in Section 3.2, 18F-BCPP-EF binding to MC-I in each brain region indicated much larger variation (CV=25.1%) in aged animals than in young ones (7.4%) [16]. Since we had previously found that some of the aged monkeys exhibited high 11C-PIB uptake, suggesting Aβ deposition in the brain [49], the effects of Aβ deposition level assessed in Section 4.1 on MC-I activity evaluated in Section 3.2 were determined. When the 18F-BCPP-EF binding is plotted against the 11C-PIB uptake in the corresponding VOIs of all animals, the results indicated a significant reversal correlation (**Figure 4**). In contrast, no significant relationships were observed in the plot of rCMRglc measured using 18F-FDG against 11C-PIB uptake in the cerebral corticalregions [17]. There results strongly suggestthattheAβ deposition as measured with 11C-PIB induced neuroinflammation with microglial activation as determined with 11C-DPA-713 as well as 18F-FDG. Apart from developed cells such as neurons, activated inflam‐ matory cells produce lactate from glucose, known as the Warburg effect [57] or aerobic glycolysis, accounting for only approximately 5% glucose utilization in oxidative phosphor‐ ylation. Because activated inflammatory cells exclusively produce ATP through enhanced glycolysis with a low contribution of the electron transport system, these cells need more glucose to survive than normal neuronal and glial tissues, resulting in the higher 18F-FDG uptake in the neurodegenerative damaged regions. The present results demonstrated that 18F-BCPP-EF could be used to image MC-I activity specifically as well as to detect impaired MC-I activity correlated to Aβ deposition in the living brain of monkeys.

## **5. Conclusions**

In this chapter, the effects of Aβ deposition on α7-nAChR binding, TSPO activity, an estab‐ lished marker of microglial activation, and rCMRglc were assessed simultaneously with MC-I activity. PET using 18F-FDG is a well-established technique for the quantitative imaging of brain function as rCMRglc in the living brain. However, the unexpectedly high uptake of 18F-FDG in damaged brain regions suggested that 18F-FDG was taken up into not only normal tissues but also inflammatory regions with microglial activation, which hampers the accu‐ rate diagnosis of brain function using 18F-FDG. Neuroinflammation has recently emerged in several neurodegenerative diseases, including schizophrenia, depression, autism, PD, andAD. PET measurements of MC-I activity using 18F-BCPP-EF will be a superior diagnostic, prog‐ nostic, and treatment monitoring tool for AD-type dementia without being affected by inflammation.

## **Author details**

Hideo Tsukada\*

Address all correspondence to<EMAIL_ADDRESS>
Central Research Laboratory, Hamamatsu Photonics K.K., Hamamatsu, Japan

## **References**

**4.3. Effects of Aβ deposition on MC-I activity**

136 138Exploring New Findings on Amyloidosis

I activity correlated to Aβ deposition in the living brain of monkeys.

**5. Conclusions**

inflammation.

**Author details**

Hideo Tsukada\*

Address all correspondence to<EMAIL_ADDRESS>
As shown in Section 3.2, 18F-BCPP-EF binding to MC-I in each brain region indicated much larger variation (CV=25.1%) in aged animals than in young ones (7.4%) [16]. Since we had previously found that some of the aged monkeys exhibited high 11C-PIB uptake, suggesting Aβ deposition in the brain [49], the effects of Aβ deposition level assessed in Section 4.1 on MC-I activity evaluated in Section 3.2 were determined. When the 18F-BCPP-EF binding is plotted against the 11C-PIB uptake in the corresponding VOIs of all animals, the results indicated a significant reversal correlation (**Figure 4**). In contrast, no significant relationships were observed in the plot of rCMRglc measured using 18F-FDG against 11C-PIB uptake in the cerebral corticalregions [17]. There results strongly suggestthattheAβ deposition as measured with 11C-PIB induced neuroinflammation with microglial activation as determined with 11C-DPA-713 as well as 18F-FDG. Apart from developed cells such as neurons, activated inflam‐ matory cells produce lactate from glucose, known as the Warburg effect [57] or aerobic glycolysis, accounting for only approximately 5% glucose utilization in oxidative phosphor‐ ylation. Because activated inflammatory cells exclusively produce ATP through enhanced glycolysis with a low contribution of the electron transport system, these cells need more glucose to survive than normal neuronal and glial tissues, resulting in the higher 18F-FDG uptake in the neurodegenerative damaged regions. The present results demonstrated that 18F-BCPP-EF could be used to image MC-I activity specifically as well as to detect impaired MC-

In this chapter, the effects of Aβ deposition on α7-nAChR binding, TSPO activity, an estab‐ lished marker of microglial activation, and rCMRglc were assessed simultaneously with MC-I activity. PET using 18F-FDG is a well-established technique for the quantitative imaging of brain function as rCMRglc in the living brain. However, the unexpectedly high uptake of 18F-FDG in damaged brain regions suggested that 18F-FDG was taken up into not only normal tissues but also inflammatory regions with microglial activation, which hampers the accu‐ rate diagnosis of brain function using 18F-FDG. Neuroinflammation has recently emerged in several neurodegenerative diseases, including schizophrenia, depression, autism, PD, andAD. PET measurements of MC-I activity using 18F-BCPP-EF will be a superior diagnostic, prog‐ nostic, and treatment monitoring tool for AD-type dementia without being affected by

rat brain and their dietary modulation. Arch Pharm Res. 1999;22:361–366. DOI: 10.1007/ BF02979058.

measured with positron emission tomography (PET). J Neurosci Res. 1990;27:569–575. DOI: 10.1002/jnr.490270418.

[24] Zubieta JK, Koeppe RA, Frey KA, Kilbourn MR, Mangner TJ, Foster NL, Kuhl DE. Assessment of muscarinic receptor concentrations in aging and Alzheimer disease with 11C-NMPB and PET. Synapse. 2001;39:275–287.  Arch Pharm Res. 1999;22:361–366. DOI: 10.1007/

[12] Kannurpatti SS, Sanganahalli BG, Mishra S, Joshi PG, Joshi NB. Glutamate-induced differential mitochondrial response in young and adult rats. Neurochem Int.

[13] Choi BH. Oxidative stress and Alzheimer's disease. Neurobiol Aging. 1995;16:675–678.

[14] Schon EA, Przedborski S. Mitochondria: The next (neurode)generation. Neuron.

[15] Harada N, Nishiyama S, Kanazawa M, Tsukada H. Development of novel PET probes, [18F]BCPP-EF, [18F]BCPP-BF, and [11C]BCPP-EM for mitochondrial complex I imaging. J Labelled Compd Radiopharm. 2013;56:553–561. DOI: 10.1002/jlcr.3056. [16] Tsukada H, Ohba H, Kanazawa M, Kakiuchi T, Harada N. Evaluation of 18F-BCPP-EF for mitochondrial complex 1 imaging in conscious monkey brain using PET. EurJ Nucl

[17] Tsukada H, Nishiyama S, Ohba H, Kanazawa M, Kakiuchi T, Harada N. Comparing amyloid-β deposition, neuroinflammation, glucose metabolism, and mitochondrial complex I activity in brain: A PET study in aged monkeys. Eur J Nucl Med Mol

[18] Court JA, Lloyd S, Johnson M, Griffiths M, Birdsall NJM, Piggott MA, Oakley AE, Ince PG, Perry EK, Perry RH. Nicotinic and muscarinic cholinergic receptor binding in the human hippocampal formation during development and aging. Dev Brain Res.

[19] Hardy J, Selkoe DJ. The amyloid hypothesis of Alzheimer's disease: Progress and problems on the road to therapeutics. Science. 2002;297:353–356. DOI: 10.1126/science.

[20] Grundke-Iqbal I, Iqbal K, Tung YC, Quinlan M, Wisniewski HM, Binder LI. Abnor‐ mal phosphorylation of the microtubule-associated protein tau (τ) in Alzheimer

[21] Terry AV Jr, Buccafusco JJ. The cholinergic hypothesis of age and Alzheimer's diseaserelated cognitive deficits: Recent challenges and their implications for novel drug development. J Pharmacol Exp Ther. 2003;306:821–827. DOI: 10.1124/jpet.102.041616.

[22] Tsukada H, Nishiyama S, Fukumoto D, Ohba H, Sato K, Kakiuchi T. Effects of acute acetylcholinesterase inhibition on the cerebral cholinergic neuronal system and cognitive function: Functional imaging of the conscious monkey brain using animal PET in combination with microdialysis. Synapse. 2004;52:1–10. DOI: 10.1002/syn.10310.

[23] Dewey SL, Volkow ND, Logan J, MacGregor RR, Fowler JS, Schlyer DJ, Bendriem B. Age-related decrease in muscarinic cholinergic receptor binding in the human brain

cytoskeletal pathology. Proc Natl Acad Sci U S A. 1986;83:4913–4917.

Med Mol Imaging. 2014;41:755–763. DOI: 10.1007/s00259-014-2821-8.

Imaging. 2014;41:2127–2136. DOI: 10.1007/s00259-013-2628-z.

1997;101:93–105. DOI: 10.1016/S0165-3806(97)00052-7.

BF02979058.

138 140Exploring New Findings on Amyloidosis

1072994.

2004;44:361–369. DOI: 10.1007/BF02979058.

2011;70:1033–1053. DOI: 10.1016/j.neuron.2011.06.003.

DOI: 10.1016/0197-4580(95)00065-M.

[42] Waterhouse RN. Determination of lipophilicity and its use as a predictor of blood-brain barrier penetration of molecular imaging agents. Mol Imaging Biol. 2003;5:376–389. DOI: 10.1016/j.mibio.2003.09.014.

[32] Albuquerque EX, Pereira EF, Alkondon M, Rogers SW. Mammalian nicotinic acetyl‐ choline receptors: From structure to function. Physiol Rev. 2009;89:73–120. DOI:

[33] Kadir A, Almkvist O, Wall A, Långström B, Nordberg A. PET imaging of cortical 11Cnicotine binding correlates with the cognitive function of attention in Alzheimer's disease. Psychopharmacology. 2006;188:509–520. DOI: 10.1007/s00213-006-0447-7. [34] Wu J, Ishikawa M, Zhang J, Hashimoto K. Brain imaging of nicotinic receptors in Alzheimer's disease. Int J Alzheimer's Dis. 2010;2010:548913. DOI:

[35] Ogawa M, Nishiyama S, Tsukada H, Hatano K, Fuchigami T, Yamaguchi H, Matsushima Y, Ito K, Magata Y. Synthesis and evaluation of new imaging agent for central nicotinic acetylcholine receptor α7 subtype. Nucl Med Biol. 2010;37:347–355.

[36] Nishiyama S, Ohba H, Kanazawa M, Kakiuchi T, Tsukada H. Comparing α7 nicotinic acetylcholine receptor binding, amyloid-β deposition, and mitochondria complex-I function in living brain: A PET study in aged monkeys. Synapse. 2015;69:475–483.

[37] Mintun MA, Raichle ME, Kilbourn MR, Wooten GF, Welch MJ. A quantitative model for the *in vivo* assessment of drug binding sites with positron emission tomography.

[38] Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, Holden J, Houle S, Huang SC, Ichise M, Iida H, Kimura Y, Koeppe RA, Knudsen GM, Knuuti J, Lammertsma AA, Laruelle M, Logan J, Maguire RP, Mintun MA, Morris ED, Parsey R, Price JC, Slifstein M, Sossi V, Suhara T, Votaw JR, Wong DF, Carson RE. Consensus nomenclature for *in vivo* imaging of reversibly binding radioligands. J Cereb Blood

[39] Noda A, Takamatsu H, Minoshima S, Tsukada H, Nishimura S. Determination of kinetic rate constants for 2-[18F]fluoro-2-deoxy-D-glucose and partition coefficient of water in conscious macaques and alterations in aging or anesthesia examined on parametric images with an anatomic standardization technique. J Cereb Blood Flow

[40] Schild L, Huppelsberg J, Kahlert S, Keilhoff G, Reiser G. Brain mitochondria are primed by moderate Ca2+ rise upon hypoxia/reoxygenation for functional breakdown and morphological disintegration. J Biol Chem. 2003;278:25454–25460. DOI: 10.1074/

[41] Yalamanchili P, Wexler E, Hayes M, Yu M, Bozek J, Kagan M, Radeke HS, Azure M, Purohit A, Casebier DS, Robinson SP. Mechanism of uptake and retention of F-18 BMS-747158-02 in cardiomyocytes: A novel PET myocardial imaging agent. J Nucl

Ann Neurol. 1984;15:217–227. DOI: 10.1002/ana.410150302.

Flow Metab. 2007;27:1533–1539. DOI: 10.1038/sj.jcbfm.9600493.

Cardiol. 2007;14:782–788. DOI: 10.1016/j.nuclcard.2007.07.009.

10.1152/physrev.00015.2008.

140 142Exploring New Findings on Amyloidosis

10.4061/2010/548913.

DOI: 10.1002/syn.21842.

Metab. 2003;23:1441–1447.

jbc.M302743200.

DOI: 10.1016/j.nucmedbio.2009.11.007.

**Chapter 5**

## **Kinetics of Amyloid Formation by Different Proteins and Peptides: Polymorphism and Sizes of Folding Nuclei of Fibrils**

Oxana V. Galzitskaya, Nikita V. Dovidchenko and Olga M. Selivanova

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/63359

#### **Abstract**

[53] Cleary JP, Walsh DM, Hofmeister JJ, Shankar GM, Kuskowski MA, Selkoe DJ, Ashe KH. Natural oligomers of the amyloid-β protein specifically disrupt cognitive func‐

[54] Lesne S, Koh MT, Kotilinek L, Kayed R, Glabe CG, Yang A, Gallagher M, Ashe KH. A specific amyloid-β protein assembly in the brain impairs memory. Nature.

[55] Puzzo D, Privitera L, Leznik E, Fa M, Staniszewski A, Palmeri A, Arancio O. Picomo‐ lar amyloid-β positively modulates synaptic plasticity and memory in hippocampus.

[56] Yu WF, Guan ZZ, Bogdanovic N, Nordberg A. High selective expression of α7 nicotinic receptors on astrocytes in the brains of patients with sporadic Alzheimer's disease and patients carrying Swedish APP 670/671 mutation: A possible association with neurit‐ ic plaques. Exp Neurol. 2005;192:215–225. DOI: 10.1016/j.expneurol.2004.12.015.

[57] Warburg O. On respiratory impairment in cancer cells. Science. 1956;124:267–272.

J Neurosci. 2008;28:14537–14545. DOI: 10.1523/JNEUROSCI.2692-08.2008.

tion. Nat Neurosci. 2005;8:79–84. DOI: 10.1038/nn1372.

2006;440:352–357. DOI: 10.1038/nature04533.

142 144Exploring New Findings on Amyloidosis

DOI: 10.1126/science.124.3215.267.

Aggregation of peptides and proteins into amyloid structure is one of the most intensively studied biological phenomena at the moment. To date, there is no devel‐ oped theory that would allow one to determine what kind of mechanism presents in the given experiment on the basis of aggregation kinetic data. Debates concerning the mechanism of the amyloid fibrils formation and, in particular, the size of the amyloi‐ dogenic nucleus are still going on. We created such a theory on the basis of the kinetics of amyloid aggregates formation. In the presented chapter, theoretical and experimen‐ tal approaches were employed for studding the process of amyloid formation by different proteins and peptides. The current kinetic models described in this chapter adequately describe the key features of amyloid nucleation and growth.

**Keywords:** amyloidogenic regions, amyloid prediction methods, linear and exponen‐ tial mechanisms of amyloid growth, polymorphism, prion

## **1. Introduction**

Many studies show that the generation of an amyloid fibril is a fundamental property of all protein molecules, rather than being limited to a narrow range of the so-called amyloidforming proteins associated with amyloid diseases, as was believed until recently [1, 2]. Normal proteins become toxic upon fibril formation [3]. At the same time, greater cytotoxici‐ ty is characteristic of immature water-soluble fibrils compared to mature insoluble amyloid

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

fibrils. It seems that the mechanism of toxicity should be similar to that for fibrils formed by different proteins. The structure of toxic immature fibrils is certainly rich in β-strands and should be universal, because specific antibodies against the precursors of amyloid peptide Aβ, associated with Alzheimer's disease, recognize the precursors of amyloid fibrils formed by other proteins with different amino acid sequences [4]. It was demonstrated that samples of blood serum from patients with Parkinson's disease show an autoimmune response to insulin oligomers and fibrils, which should reveal the presence of insulin aggregates in this disease [5]. Fibril formation depends on the experimental conditions and is expedited by denatur‐ ants: to aggregate, proteins should be unfolded, at least partly [6]. Preliminary unfolding is not needed for the aggregation of peptides and proteins associated with amyloidosis such as type II diabetes or Alzheimer's and Parkinson's disease, because these proteins are already unfolded under physiological conditions [7]. However, the majority of natively unfolded proteins do not aggregate in vivo [8] suggesting that unfolding is necessary, but not suffi‐ cient for the formation of amyloid fibrils. Most likely, there are specific amino acid motifs that are exposed to the solvent and are more prone to aggregation as compared to other regions of the amino acid sequence. Experimental findings support the hypothesis that small protein regions are responsible for the amyloidogenic behavior [9–11].

## **2. Identification of aggregation sites in proteins responsible for amyloid formation**

We have done comparison of the prediction results for 30 amyloidogenic proteins [12] using seven methods with experimental data: PASTA2 [13], AmylPred2 [12], Tango [14], MetAmyl [15], Waltz [16], FoldAmyloid [17], ArchCandy [18]. More detail comparison with full list of proteins but without new method Archcandy was presented in our recent paper [19]. One can see that FoldAmyloid (which is a relatively old and simple approach) works better than Waltz and Archcandy. PASTA2 is a new more sophisticated approach that performs best among the non-meta-servers. As evident from **Table 1**, the accuracy and sensitivity of PASTA2 predic‐

**Table 1.** Averaged results of amyloid predictions for 30 proteins by various algorithms.

tions are only smaller better than those of FoldAmyloid. At the same time, comparison of the overall prediction quality shows only modest improvement, which is due to low sensitivity partly caused by overprediction and partly by the coarseness of the methods.

## **3. Possible kinetics schemes for amyloid and prion growth**

fibrils. It seems that the mechanism of toxicity should be similar to that for fibrils formed by different proteins. The structure of toxic immature fibrils is certainly rich in β-strands and should be universal, because specific antibodies against the precursors of amyloid peptide Aβ, associated with Alzheimer's disease, recognize the precursors of amyloid fibrils formed by other proteins with different amino acid sequences [4]. It was demonstrated that samples of blood serum from patients with Parkinson's disease show an autoimmune response to insulin oligomers and fibrils, which should reveal the presence of insulin aggregates in this disease [5]. Fibril formation depends on the experimental conditions and is expedited by denatur‐ ants: to aggregate, proteins should be unfolded, at least partly [6]. Preliminary unfolding is not needed for the aggregation of peptides and proteins associated with amyloidosis such as type II diabetes or Alzheimer's and Parkinson's disease, because these proteins are already unfolded under physiological conditions [7]. However, the majority of natively unfolded proteins do not aggregate in vivo [8] suggesting that unfolding is necessary, but not suffi‐ cient for the formation of amyloid fibrils. Most likely, there are specific amino acid motifs that are exposed to the solvent and are more prone to aggregation as compared to other regions of the amino acid sequence. Experimental findings support the hypothesis that small protein

**2. Identification of aggregation sites in proteins responsible for amyloid**

We have done comparison of the prediction results for 30 amyloidogenic proteins [12] using seven methods with experimental data: PASTA2 [13], AmylPred2 [12], Tango [14], MetAmyl [15], Waltz [16], FoldAmyloid [17], ArchCandy [18]. More detail comparison with full list of proteins but without new method Archcandy was presented in our recent paper [19]. One can see that FoldAmyloid (which is a relatively old and simple approach) works better than Waltz and Archcandy. PASTA2 is a new more sophisticated approach that performs best among the non-meta-servers. As evident from **Table 1**, the accuracy and sensitivity of PASTA2 predic‐

**AmylPred2 Tango MetAmyl**

Sensitivity 0.36 0.41 0.19 0.38 0.19 0.28 0.16 Specificity 0.91 0.86 0.95 0.86 0.94 0.92 0.92

**Table 1.** Averaged results of amyloid predictions for 30 proteins by various algorithms.

**high specificity**

38 121 37 88 37 31 15

33/**46** 42/**46** 17/**46** 33/**46** 22/**46** 29/**46** 8/**46**

**Waltz best perfo‐ mance**

**FoldAmy‐ loid**

**Archcandy default set‐ tings**

regions are responsible for the amyloidogenic behavior [9–11].

**formation**

1442 Exploring New Findings on Amyloidosis

False regions

gions/**total**

ic

predicted as amyloidogen‐

No. correctly predicted re‐

**Scoring type PASTA2**

**90% specificity**

To explain the kinetic features of the aggregation process of protein molecules, a large number of schemes were proposed. There are many approaches for describing the kinetics and mechanism of protein aggregation: kinetic, thermodynamic, and other empirical approaches. The purpose of the first two was the best approximation of the experimental data and obtain‐ ment of quantitative values of the rate constants describing such processes as nucleation, growth, and all other parts of the aggregation process. At present, there is no consensus whether a protofilament is formed by joining oligomers or by adding monomers. The following questions can be posed: How many different mechanisms exist in the literature for describing the protein aggregation? What is the essence of each mechanism? What mechanisms or models are used in the literature to describe the experimental kinetic curves? What are the similarities between various mechanisms? The large volume of publications describing the formation of amyloid fibrils allows us to reveal two general mechanisms. There are a mechanism of sequential addition of monomers (linear growth) and a mechanism for describing the aggre‐ gation of prions (exponentional growth). Most of these approaches somehow go back to the late fifties [20]. In this study, a kinetic scheme for polymerization of actin was proposed. The experimental data indicated that the polymerization process is very similar to the condensation reaction: The reaction occurs only when the monomer concentration exceeds the critical threshold. The assumption was justified. The cooperative polymerization reaction was confirmed by two facts: (1) The reaction rate in the early stages of the reaction increased upon increasing the concentration of actin; (2) an addition of seed with an already formed unit led to an immediate transition of all free actin to an aggregate. In 1974, Hofrichter et al. [21] used the mechanism of sequential monomer addition to the aggregate to explain the formation of hemoglobin fibrils in sickle cell anemia. To explain the observed effect of "extreme autocatal‐ ysis" and strong concentration dependence, Ferrone with the co-authors developed a model of "heterogeneous nucleation" [22]. This model assumes the following sequence of events: First, in the normal course of nucleation, fibrils, and then, subsequent fibrils may form on its surface. This model is included as an equation for the first stage—the homogeneous nucleation, and for the second step—heterogeneous nucleation; the equations were solved numerically. The notion of heterogeneous nucleation was a new and important contribution to the devel‐ opment of the theory of protein aggregation. In 1983, Frieden and Goddette [23] used a model of sequential monomer addition to the unit to describe the process of protein polymerization, with the proviso that each step of monomer addition had its own reaction rate constant. In 1986, Goldstein and Stryer [24] modified the model of sequential addition of monomers to the unit to describe the process of protein polymerization. They identified the nucleus as a "seed" of size s, after the formation of which the kinetic constants are changed. Using protein amylin, it was shown that nucleation can occur in two ways: fibril-independent (or primary nucleation) and fibril-dependent (secondary nucleation) paths. The contribution of each of these processes depends on the external interfaces (or surfaces). In the presence of such a surface, the primary nucleation mechanism is dominating; in the absence of such a surface, the secondary nucleation mechanism is dominating [25]. Heterogeneous nucleation can be seen from another point of view, as an autocatalytic growth in mature seeds. It was not shown experimentally whether seeds are formed on the existing surface of the unit, or the growth simply continues from the surface of the same aggregate. In 1967, Griffith [26] suggested three possible theoretical mechanisms that could explain the self-replication agent causing "scrapie" sheep (scrapie). In 1982, Prusiner [27] was able to provide enough experimental evidence that the "scrapie" infectious agent is the protein called a prion. In 1991, Prusiner suggested the scheme of transfer and development of prion infection [28]. Based on the Prusiner's work, in 1993, Lansbury his work published [29], in which the mechanism of sequential monomer addition to the seed was applied for analysis of kinetic data.

**Figure 1.** Alternative scenarios for amyloid growth and corresponding kinetic parameters. T2 is the time of inclusion of all monomers into the aggregate, Lrel is the ratio between the duration of the lag phase and the time of inclusion of all monomers into the growing polymer, [M∑] is the total monomer concentration, n\* is the size of the primary nucleus, and n2 is the size of the secondary nucleus. nS is the smallest number of monomers in the stable polymer. Modified from [33].

and fibril-dependent (secondary nucleation) paths. The contribution of each of these processes depends on the external interfaces (or surfaces). In the presence of such a surface, the primary nucleation mechanism is dominating; in the absence of such a surface, the secondary nucleation mechanism is dominating [25]. Heterogeneous nucleation can be seen from another point of view, as an autocatalytic growth in mature seeds. It was not shown experimentally whether seeds are formed on the existing surface of the unit, or the growth simply continues from the surface of the same aggregate. In 1967, Griffith [26] suggested three possible theoretical mechanisms that could explain the self-replication agent causing "scrapie" sheep (scrapie). In 1982, Prusiner [27] was able to provide enough experimental evidence that the "scrapie" infectious agent is the protein called a prion. In 1991, Prusiner suggested the scheme of transfer and development of prion infection [28]. Based on the Prusiner's work, in 1993, Lansbury his work published [29], in which the mechanism of sequential monomer addition to the seed was

**Figure 1.** Alternative scenarios for amyloid growth and corresponding kinetic parameters. T2 is the time of inclusion of all monomers into the aggregate, Lrel is the ratio between the duration of the lag phase and the time of inclusion of all monomers into the growing polymer, [M∑] is the total monomer concentration, n\* is the size of the primary nucleus, and n2 is the size of the secondary nucleus. nS is the smallest number of monomers in the stable polymer. Modified

applied for analysis of kinetic data.

1464 Exploring New Findings on Amyloidosis

from [33].

In 2004 in the paper by Collins et al. [30], the formation kinetics of sup35p prion was studied. It was shown that amyloid aggregate growth occurs upon monomer addition to the fiber ends. Also the authors performed experiments with agitation and observed catalysis due to fiber fragmentation, so their kinetic model consisted of three steps: at the first step, oligomers are formed; at the second step, amyloidal seeds are formed through nucleation-conversion, after that the autocatalytic growth occurs where autocatalysis takes place because of fragmentation. Thus, major schemes of amyloid aggregates formation were drawn. In general, schemes can be summed up into the following reaction: out of a pool of monomer nuclei (the most unstable species on the reaction path with the largest free energy) are formed, which then are somehow converted into seed (the smallest stable amyloid aggregate) which is able to attach monomers in a way that monomer free energy only decreases, the result of which is that after some time, all the monomers become associated into fibrils. In some cases, catalysis of reaction occurs through secondary nucleation or fragmentation. In the presence of a catalyst, the amyloidal growth regime can be named "exponential," whereas in the absence of catalysis, the amyloidal growth can be named linear. It should be mentioned that in this general scheme, it is not important what one means by the words "monomer protein"—the monomer itself or some protein aggregate. Despite overall success in the understanding of possible mechanisms hidden beneath amyloidal aggregation, the relation of the kinetic models to the experimentally measurable values was still unclear. Thus, the authors of the paper [31] have shown that despite possible different mechanisms of aggregation, all of the kinetic experimental data could be successfully approximated by a simple sigmoid curve. Fortunately in the same year, the careful introspection of the behavior of the logarithm of lag time versus logarithm of concentration for several amyloidogenic agents by Knowles et al. [32] revealed that different amyloidogenic agents possess a similar linear dependence in those coordinates and such dependence is Tlag/Tlag0 ≈(C/C0)−1/2, where Tlag0 and C0 are values corresponding to the smallest concentration. In the paper Dovidchenko et al. [33], the authors studied the variance in the mechanisms within scheme monomer ->nucleus->fibril growth with/without catalysis. In the work, the authors were lucky to find bridges between values which can be calculated directly from experimental data—characteristic times such as lag-time Tlag, time of inclusion of all monomers into aggregate T2 and relation Lrel = Tlag/T2 and mechanism of amyloidogenesis. It turned out that through the study of the concentration dependence of amyloid formation, one can estimate nuclei sizes (the size of the primary nucleus and size of the secondary nucleus if secondary nucleation takes place) and possible mechanisms. For example, linear growth (when no catalysis occurs) has a very narrow range of conditions: Lrel should be independent of the logarithm of concentration and its value should not exceed 0.2. In the case of exponential mechanism, one should plot a graph of two dependencies: lnT2 versus ln[MΣ] and Lrel versus ln[MΣ], where MΣ is the initial concentration of monomers. As one can see from **Figure 1**, the dependencies should be linear in those coordinates and thus the calculation of the tangent coefficient of a line drawn through experimental points will point out what mechanism takes place in the given reaction. However, several tangent coefficients (for example, −1/2 which can be either the result of a fragmentation mechanism or a bifurcation mechanism without secondary nucleation) are special cases and can be obtained in different scenarios; for those cases, additional experiments are needed to exclude excess mechanism variants.

## **4. Polymorphism of amyloid fibrils**

The fully matured fibers are not the most toxic species. The importance of intermediate species that define the pathway, toxicity, and even the type of fibers formed at the end should be emphasized. Usually electron microscopy (EM) is used for comprehensive characterization of the amyloid formation and for control of the amyloid morphology. The probes are collected for analyzing periodically over duration of all experiments. The main results of EM experi‐ ments at each of the time intervals are the properties of time-dependent structures and their variability (polymorphism). These analyses usually are performed using both commercial and recombinant samples. The use of EM in studying the process of amyloid formation is due to the importance of polymorphism for determining the protein folding pathways. On the other hand, protein folding pathway depends strongly on its amino acid sequence. Further, the resulting protein conformation affects the formation of amyloid fibrils, and the same poly‐ peptide sequence may correspond to the fibrils of different morphologies [34]. The fibril polymorphism is potentially important for the human disease progression, as it may be the reason for natural variability of amyloid-related pathologies such as amyloidosis of light chains of immunoglobulins (AL) and the phenomenon of strain variability of prion infection [34, 35]. The EM images of amyloid fibrils show insignificant morphological differences, and the fibrils are often represented as twisted or parallel clusters of thin protein filaments. One should note also that polymorphism is a serious obstacle in studying fibril structures. A mixture of fibrils of different morphology is always present in solution, and several different types of fibrils can be seen under the same conditions. This creates a problem for image analyses because it requires separation of fibrils by their morphology and performing separate analyses of each type of insulin, Aβ peptide, β2-microglobulin, glucagon, amylin, calcitonin, etc. It is not completely excluded that different fibril morphologies are due to similar but not identical fibril formation pathways. The differences may be formed at the initial steps of fibril formation including the step of nucleation. The size of the nucleus of a protofibril is still unknown for almost all proteins and peptides. Nucleation is the limiting step of the amyloid fibril formation which can start only when the concentration of amyloid proteins exceeds the critical one. After the nucleation, the fibrils grow rapidly. Proteins may have different sizes of the protofibril nuclei (see the next sections). Also, the conditions at which the fibrils are formed may affect its size. This may result in the formation of the fibrils of different morphologies. In other words, we assume that the fibril formation depends on the nucleation step and goes through different pathways, thus determining the final fibril morphology. Note also that both the morphology and molecular structure are sensitive to small differences under conditions when the fibrils are growing in *de novo* preparations (under fixed pH, temperature, buffer composition, and peptide concentration).

## **4.1. Polymorphism of Aβ fibrils**

It was shown previously that peptide Aβ40 forms fibrils of different morphologies even under the same conditions. For the fibrils formed without mixing, the dominating morphologies are twisted fibrils, while the activated fibrils will be less twisted yet inclined to form lateral associations. The inactivated twisted fibrils are the most toxic for the cells [36]. Therefore, it is important to study all possible formations including oligomers and fibrils, which determine the natural polymorphism. Moreover, it was shown previously that the fibrils associated with diseases have the same nucleation center structure called a β-arcade. The β-strands in these structures are parallel to each other. It is interesting to note that this kind of a nucleus structure is not found in normal proteins and the β-strands are antiparallel to each other [37].

#### *4.1.1. Morphology of recombinant Aβ40 peptides*

**4. Polymorphism of amyloid fibrils**

1486 Exploring New Findings on Amyloidosis

peptide concentration).

**4.1. Polymorphism of Aβ fibrils**

The fully matured fibers are not the most toxic species. The importance of intermediate species that define the pathway, toxicity, and even the type of fibers formed at the end should be emphasized. Usually electron microscopy (EM) is used for comprehensive characterization of the amyloid formation and for control of the amyloid morphology. The probes are collected for analyzing periodically over duration of all experiments. The main results of EM experi‐ ments at each of the time intervals are the properties of time-dependent structures and their variability (polymorphism). These analyses usually are performed using both commercial and recombinant samples. The use of EM in studying the process of amyloid formation is due to the importance of polymorphism for determining the protein folding pathways. On the other hand, protein folding pathway depends strongly on its amino acid sequence. Further, the resulting protein conformation affects the formation of amyloid fibrils, and the same poly‐ peptide sequence may correspond to the fibrils of different morphologies [34]. The fibril polymorphism is potentially important for the human disease progression, as it may be the reason for natural variability of amyloid-related pathologies such as amyloidosis of light chains of immunoglobulins (AL) and the phenomenon of strain variability of prion infection [34, 35]. The EM images of amyloid fibrils show insignificant morphological differences, and the fibrils are often represented as twisted or parallel clusters of thin protein filaments. One should note also that polymorphism is a serious obstacle in studying fibril structures. A mixture of fibrils of different morphology is always present in solution, and several different types of fibrils can be seen under the same conditions. This creates a problem for image analyses because it requires separation of fibrils by their morphology and performing separate analyses of each type of insulin, Aβ peptide, β2-microglobulin, glucagon, amylin, calcitonin, etc. It is not completely excluded that different fibril morphologies are due to similar but not identical fibril formation pathways. The differences may be formed at the initial steps of fibril formation including the step of nucleation. The size of the nucleus of a protofibril is still unknown for almost all proteins and peptides. Nucleation is the limiting step of the amyloid fibril formation which can start only when the concentration of amyloid proteins exceeds the critical one. After the nucleation, the fibrils grow rapidly. Proteins may have different sizes of the protofibril nuclei (see the next sections). Also, the conditions at which the fibrils are formed may affect its size. This may result in the formation of the fibrils of different morphologies. In other words, we assume that the fibril formation depends on the nucleation step and goes through different pathways, thus determining the final fibril morphology. Note also that both the morphology and molecular structure are sensitive to small differences under conditions when the fibrils are growing in *de novo* preparations (under fixed pH, temperature, buffer composition, and

It was shown previously that peptide Aβ40 forms fibrils of different morphologies even under the same conditions. For the fibrils formed without mixing, the dominating morphologies are twisted fibrils, while the activated fibrils will be less twisted yet inclined to form lateral associations. The inactivated twisted fibrils are the most toxic for the cells [36]. Therefore, it is **Figure 2** shows the preparation of recombinant Aβ40 peptide after 27 h incubation at 25°C at 50 mM Tris–HCl (pH 7, 5) and C = 0.2 mg/ml. Polymorphism of generated fibrils is seen. In

**Figure 2.** Electron microscopy images of recombinant Aβ40 peptide [0.2 mg/mL, 27 h incubation at 25°C, 50 mM Tris-HCl (pH 7, 5)]. (a) General view (field) of recombinant Aβ40 peptide after 27 h of incubation. (b–d) Gallery of types of Aβ40 peptide fibril images at higher magnification: (b) single fibrils; (c) ribbon-like type of fibrils; (d) bundle-like type of fibrils; (e, f) single fibrils: (e) at horizontal packing; (f) bending sites of the single fibrils. (g) Gallery of ring oligomers.

addition to single fibrils of several microns in length with a diameter of about 8–9 nm, there are also fibrils, forming bands of different widths, and bundles. It seems that single fibrils consist of two filaments. However, under high magnification, it is seen that the fibrils are formed of rounded ring structures. The matter is that upon staining the preparations, the staining agent dyes not only their contours, but also flows into different cavities and openings. This should be taken into account when interpreting EM images; otherwise, a tobacco mosaic virus fibril would consist of two parallel packed short filaments of 300 nm long. In the case of the Aβ40 peptide preparation, under high magnification, it is also seen that the staining agent flows into the openings of ring structures. These ring oligomer structures have a diameter of about 8–9 nm (the width of a single fibril) and a diameter of the internal opening of about 3 nm. Ring structures or Aβ40 oligomers form single fibrils in such a way, that ring oligomers are layered on each other. If a fibril is absorbed on the formvar film sideways, we see a thinner fibril with a diameter of about 4 nm. This size demonstrates an approximate height of a ringstructured oligomer. As a matter of fact, the height is smaller, because the degree of overlap‐ ping of ring-structured oligomers should be taken into account. The greater is the overlapping, the larger is the height of such packing of fibrils.

## *4.1.2. Morphology of synthetic Aβ42 peptide (Invitrogen, lot #73269340A)*

The EM image of Aβ42 peptide (Invitrogen, lot #73269340A) (**Figure 3**) shows that after 97 h of incubation at 37°C (water), fibrils of several microns long are formed. Polymorphism of

**Figure 3.** Electron microscopy images of Aβ42 peptide from Invitrogen (lot #73269340A). The sample was incubated at 37°C (water). (a) General view of the sample at 97-h incubation. (b, c) Gallery of types of Aβ42 peptide fibrils at higher magnification: (b) single thin and (c) thick fibrils. (d) Gallery of ring oligomers.

fibrils is observed. Thin fibrils with a diameter of about 7–8 nm and more are seen, and more pronounced polymorphism of the generated fibrils is observed (**Figure 3**). At the same time, fibrils of different diameters are present: thin ones of about 7–8 nm and wider fibrils up to 15 nm. Moreover, rounded ring-structured oligomers of about 8 nm in diameter can be seen; the internal diameter of the ring (the diameter of the hole) is about 3 nm (**Figure 3d**). At magnification, it can be seen that an oligomer consists of 4–6 smaller rounded particles (**Figure 3d**). It is notable that both thin and thick fibrils are formed of such ring-structured oligomers. Thin fibrils are characterized by more ordered interaction of separate oligomers, while thick fibrils are generated due to random sticking of additional oligomers along the fibril axis. Because of this way of generation, fibrils look uneven in EM images with a tendency to branching [38].

Thus, using the EM method, we have demonstrated that fibrils of these peptides are formed by association of rounded ring structures. Negatively stained TEM images of fibrils extracted from AD brain tissues [39] are very similar to our EM results. Moreover, similar structures are observed elsewhere [40].

## **4.2. Polymorphism of insulin fibrils**

addition to single fibrils of several microns in length with a diameter of about 8–9 nm, there are also fibrils, forming bands of different widths, and bundles. It seems that single fibrils consist of two filaments. However, under high magnification, it is seen that the fibrils are formed of rounded ring structures. The matter is that upon staining the preparations, the staining agent dyes not only their contours, but also flows into different cavities and openings. This should be taken into account when interpreting EM images; otherwise, a tobacco mosaic virus fibril would consist of two parallel packed short filaments of 300 nm long. In the case of the Aβ40 peptide preparation, under high magnification, it is also seen that the staining agent flows into the openings of ring structures. These ring oligomer structures have a diameter of about 8–9 nm (the width of a single fibril) and a diameter of the internal opening of about 3 nm. Ring structures or Aβ40 oligomers form single fibrils in such a way, that ring oligomers are layered on each other. If a fibril is absorbed on the formvar film sideways, we see a thinner fibril with a diameter of about 4 nm. This size demonstrates an approximate height of a ringstructured oligomer. As a matter of fact, the height is smaller, because the degree of overlap‐ ping of ring-structured oligomers should be taken into account. The greater is the overlapping,

The EM image of Aβ42 peptide (Invitrogen, lot #73269340A) (**Figure 3**) shows that after 97 h of incubation at 37°C (water), fibrils of several microns long are formed. Polymorphism of

**Figure 3.** Electron microscopy images of Aβ42 peptide from Invitrogen (lot #73269340A). The sample was incubated at 37°C (water). (a) General view of the sample at 97-h incubation. (b, c) Gallery of types of Aβ42 peptide fibrils at higher

magnification: (b) single thin and (c) thick fibrils. (d) Gallery of ring oligomers.

the larger is the height of such packing of fibrils.

1508 Exploring New Findings on Amyloidosis

*4.1.2. Morphology of synthetic Aβ42 peptide (Invitrogen, lot #73269340A)*

Insulin has a high tendency to aggregation and forms fibrils. Insulin fibrils were first described in 1940 by Waugh [41]. At present, the conditions leading to the formation of active insulin fibrils are known [42]. Insulin fibrillation occurs upon various environmental changes (pH, ionic conditions, temperature, organic solvents, and agitation); it also depends on the methods for producing insulin, its delivery, and storage. It should be noted that the human insulin fibrillation is slower than that of the best studied bovine insulin [42–47].

Currently, all insulin preparations for therapeutic purposes are prepared in the form of a Zncontaining hexamer, since in this condition it is more stable and resistant to the formation of fibrils. When treating diabetes, insulin penetrates into muscles by injection, where it typically forms deposits. The large size of the insulin hexamer slows its adsorption, because the hexamer must go through the dimers in the monomeric state and only in this way penetrate into the bloodstream. This leads to slowing down the interaction with insulin receptors and the need to take insulin 1–1.5 h before mealtime.

Despite intensive studies of fibrillogenesis of insulin, there is no generally accepted scheme for the formation of mature fibrils. The main difficulties arise in interpreting the beginning of the fibrillation process. Polymerization of insulin begins from the transition of the monomer protein from the native state to the partially unfolded conformation which can be amyloido‐ genic. The strong dependence of the reaction of polymerization on various external parameters leads to the formation of insulin fibrils with different morphology, which complicates the analysis of the general scheme of fibril formation.

For electron microscopy (EM) investigations, insulin samples were used at a concentration of 0.2 mg/ml. Zinc-free recombinant human insulin was obtained from "Gerofarm-Bio" (Obo‐ lensk, Russia) and was checked by the tandem mass spectrometry technique (LCQ Deca XP, Thermo Finnigan, USA). According to the EM data on polymerization of human insulin, the mature protein fibrils appeared only after 8 h of insulin incubation. Active polymerization of insulin occurs up to 10–11 h of incubation. This is accompanied by the elongation of the fibrils for both samples up to 10–12 μm. The fibrils interact laterally with each other, resulting in the formation of big clusters composed from ribbons, bundles, and twisting bundles (**Figure 4**). Protein aggregation is the result of increasing the incubation time up to 24 h. According to the EM data, the number of large fibril clusters increases in the samples after 24 h, but the length of the fibrils does not change (remains about 10–12 μm) [48].

**Figure 4.** Electron microscopy images of human zinc-free recombinant insulin (0.2 mg/ml, 24 h incubation at 37°C, 20% acetic acid (pH 2.0), 140 mM NaCl). (a) General view (field) of human insulin after 24 h of incubation. (b–d) Gallery of images of types of insulin fibrils at higher magnification: (b) single fibrils; (c) ribbon-like type of fibrils; (d) bundle-type of fibrils. (e, f) The thinnest fibrils: (e) at horizontal packing; (f) at vertical packing of ring oligomers.

## **5. Example of amyloid growth by the linear nucleation-elongation mechanism (actin, apolipoprotein C-II)**

Most quantitative models for linear polymerization stem from the work performed more than half a century ago [20] proposing a kinetic model for actin polymerization. Only two of the proteins (apolipoprotein C-II [49]: Lrel < 0.1 with the primary nucleus size *n*\* ≈ 4–5 and actin with *n*\* ≈ 3), studied in our analysis, exhibit linear growth. Formation of actin filaments occurs by linear growth—fibrils increase only due to attachment of monomers to the aggregate ends. This is supported by literature data [50] and by analysis of kinetic data (**Figure 1**). According to the theory advanced in [33] for linear growth (observed in actin), the characteristic time of the relative lag-period Lrel does not exceed 0.2 and is independent of ln[MΣ] as in the case of actin (**Figure 5**) [50]. The size of the primary nucleus was calculated from the slope to be *n* = 3.46 ± 0.28.

mature protein fibrils appeared only after 8 h of insulin incubation. Active polymerization of insulin occurs up to 10–11 h of incubation. This is accompanied by the elongation of the fibrils for both samples up to 10–12 μm. The fibrils interact laterally with each other, resulting in the formation of big clusters composed from ribbons, bundles, and twisting bundles (**Figure 4**). Protein aggregation is the result of increasing the incubation time up to 24 h. According to the EM data, the number of large fibril clusters increases in the samples after 24 h, but the length

**Figure 4.** Electron microscopy images of human zinc-free recombinant insulin (0.2 mg/ml, 24 h incubation at 37°C, 20% acetic acid (pH 2.0), 140 mM NaCl). (a) General view (field) of human insulin after 24 h of incubation. (b–d) Gallery of images of types of insulin fibrils at higher magnification: (b) single fibrils; (c) ribbon-like type of fibrils; (d) bundle-type

Most quantitative models for linear polymerization stem from the work performed more than half a century ago [20] proposing a kinetic model for actin polymerization. Only two of the proteins (apolipoprotein C-II [49]: Lrel < 0.1 with the primary nucleus size *n*\* ≈ 4–5 and actin

of fibrils. (e, f) The thinnest fibrils: (e) at horizontal packing; (f) at vertical packing of ring oligomers.

**mechanism (actin, apolipoprotein C-II)**

**5. Example of amyloid growth by the linear nucleation-elongation**

of the fibrils does not change (remains about 10–12 μm) [48].

15210 Exploring New Findings on Amyloidosis

**Figure 5.** (a) Dependence of normalized ThT fluorescence on time for actin [50]. (b) Dependence of Lrel on lnT2. (c) De‐ pendence of Lrel on ln[MΣ]. The slope angle of the fitted line is about −0.01, that is, Lrel is independent of ln[MΣ]. All Lrel values are also <0.2 which, according to the models of formation of fibrillar aggregates, means that the formation of actin fibrils proceeds by the linear mechanism (see [33]). The errors are computed with the Student's coefficients corre‐ sponding to 0.95 confidence level.

## **6. Examples of amyloid growth by the exponential mechanism and sizes of folding nuclei of fibrils formed by different agents**

In order to estimate the size of fibril nucleus (the most unstable state on the monomer to the fibril pathway) and a possible scenario for the formation of aggregates, it is necessary to make a number of kinetic experiments, where the only variable parameter is the monomer concen‐ tration. Characteristic times Tlag (the lag-period duration), T2 (the time of transition of all monomers into an aggregate), and Lrel (the Tlag/T2 ratio) are calculated for each experimental curve. It was demonstrated that the dependences of lnT2 and Lrel on ln[MΣ] (the logarithm of the initial concentration of monomers) are linear, with gradients that can be used for the computation of fibril nucleus sizes (including those of non-amyloid type) and for elucidation of the mechanism of aggregate formation.

If Lrel > 0.2, the linear growth model is excluded, and, independently of lnT2 and Lrel dependence on ln[MΣ], only the exponential growth scenario remains. The dependences of lnT2 on ln[MΣ] and Lrel on ln[MΣ] are formally different for different exponential scenarios (i.e., "growth from the surface," "fragmentation," and "bifurcation"). However, it is impossible, for example, to distinguish the bifurcation from the fragmentation scenario from the kinetics *alone* if the size

*n*2 of the secondary nucleus of bifurcation is zero; this implies the need for direct observations of fibril shapes to distinguish these cases (see Refs. [33, 48] for more details).

#### **6.1. Insulin**

Now we can present three general schemes of insulin amyloid formation, which differ by the size of folding nuclei of fibrils. For the first type, the size of nucleus is one monomer [44, 51– 53]. For the second scheme of fibril formation, the size of nucleus is two monomers and the dimers are precursors of fibrils [5, 54, 55]. For the third scheme of polymerization, oligomers are precursors of fibrils, and the size of oligomer can vary from three to six monomers [42, 43, 56–58].

The basis for choosing between different mechanisms of formation of fibrils is to detect various soluble oligomers. However, at low concentrations and at early times, it is difficult to accom‐ plish accurate detection of the initial aggregates. For this purpose, a variety of optical methods, as well as Cryo-transmission-EM, atom force microscopy, and small-angle X-ray scattering are used [55, 57–59]. However, all these methods are not quantitative, have no reliable standards, do not provide the full size distribution, may yield abnormal results (with microscopic approaches—interaction with the surface during adsorption of samples), and require the analysis of the results of certain programs to prove the statistical significance [52]. Although all these methods provide valuable information, none of them can convincingly demonstrate how an unstable nucleus grows to a stable seed for further growth of protofibrils, and many experimental and theoretical models are based on this assumption.

**Figure 6.** (a) Dependence of normalized ThT fluorescence on time for insulin [48]. The approximation line calculated for insulin amyloid formation with the experimental data from (a) by the least-squares method plotted in coordinates (b): {lnT2, ln[MΣ]} and (c): {Lrel, ln[MΣ]}; [MΣ] is in mg/ml, T2 in min. The tangent coefficients of the approximation lines are −0.51 ± 0.13 for d(lnT2)/d(ln[MΣ]) and 0.15 ± 0.31 for d(Lrel)/d(ln[MΣ]); the errors are computed with the Student's coefficients corresponding to 0.95 confidence level.

The growth of amyloid fibrils was studied by thioflavin T (ThT) fluorescence, which drastically increases when ThT is bound to fibrils (**Figure 6a**). The renormalized curves, presented in **Figure 6a**, are very similar to one another. They have large lag periods, thus excluding the linear growth scenario. The obtained analytical solution and computer modeling allowed us to determine the size of the nucleus from the experimentally obtained concentration depend‐ ences of the relationship between the lag-time duration and the time of growth of amyloid fibrils [33]. **Figure 6b, c** illustrates determination of the fibrillation scenario and the nuclei sizes (*n\*, n2*) for human insulin (see **Table 2**) [48]. The value *d*(lnT2)/*d*(ln[MΣ]) ≈ −0.5 is inconsistent with the "growth from the surface" model but consistent with "linear growth" (which, though, should have Lrel < 0.2, which is inconsistent with Lrel), "fragmentation" (which, though, is inconsistent with EM images shown in **Figure 4**), and "bifurcation" (consistent with the EM images), with the secondary nucleus size *n*2 = 0 calculated as −1 − *d*(lnT2)/*d*(ln[MΣ]); the primary nucleus size *n*\* = 1 + *n*2 − *d*(Lrel)/*d*(ln[MΣ]) = 1 (see **Table 2**). According to the elaborated theory, it means that the size of the primary nucleus corresponds to one monomer.

**Table 2.** The range of Lrel and lnT2 values, the sizes of the primary (*n*\*) and secondary (*n*2) nuclei and the amyloid growth scenarios obtained from experimental kinetic data alone.

#### **6.2. LysPro human analog insulin**

*n*2 of the secondary nucleus of bifurcation is zero; this implies the need for direct observations

Now we can present three general schemes of insulin amyloid formation, which differ by the size of folding nuclei of fibrils. For the first type, the size of nucleus is one monomer [44, 51– 53]. For the second scheme of fibril formation, the size of nucleus is two monomers and the dimers are precursors of fibrils [5, 54, 55]. For the third scheme of polymerization, oligomers are precursors of fibrils, and the size of oligomer can vary from three to six monomers [42, 43,

The basis for choosing between different mechanisms of formation of fibrils is to detect various soluble oligomers. However, at low concentrations and at early times, it is difficult to accom‐ plish accurate detection of the initial aggregates. For this purpose, a variety of optical methods, as well as Cryo-transmission-EM, atom force microscopy, and small-angle X-ray scattering are used [55, 57–59]. However, all these methods are not quantitative, have no reliable standards, do not provide the full size distribution, may yield abnormal results (with microscopic approaches—interaction with the surface during adsorption of samples), and require the analysis of the results of certain programs to prove the statistical significance [52]. Although all these methods provide valuable information, none of them can convincingly demonstrate how an unstable nucleus grows to a stable seed for further growth of protofibrils, and many

**Figure 6.** (a) Dependence of normalized ThT fluorescence on time for insulin [48]. The approximation line calculated for insulin amyloid formation with the experimental data from (a) by the least-squares method plotted in coordinates (b): {lnT2, ln[MΣ]} and (c): {Lrel, ln[MΣ]}; [MΣ] is in mg/ml, T2 in min. The tangent coefficients of the approximation lines are −0.51 ± 0.13 for d(lnT2)/d(ln[MΣ]) and 0.15 ± 0.31 for d(Lrel)/d(ln[MΣ]); the errors are computed with the Student's

The growth of amyloid fibrils was studied by thioflavin T (ThT) fluorescence, which drastically increases when ThT is bound to fibrils (**Figure 6a**). The renormalized curves, presented in **Figure 6a**, are very similar to one another. They have large lag periods, thus excluding the linear growth scenario. The obtained analytical solution and computer modeling allowed us to determine the size of the nucleus from the experimentally obtained concentration depend‐

of fibril shapes to distinguish these cases (see Refs. [33, 48] for more details).

experimental and theoretical models are based on this assumption.

coefficients corresponding to 0.95 confidence level.

**6.1. Insulin**

15412 Exploring New Findings on Amyloidosis

56–58].

We have investigated the kinetics of formation of fibrils by monomeric rapid-acting insulin LysPro [48]. According to our data, fibril formation of the insulin analog at pH 2 proceeds by

**Figure 7.** (a) Dependence of normalized ThT fluorescence on time for LysPro insulin [48] The approximation line calcu‐ lated for LysPro insulin amyloid formation with experimental data from (a) by the least-squares method plotted in co‐ ordinates (b): {lnT2, ln[MΣ]} and (c): {Lrel, ln[MΣ]}; [MΣ] is in mg/ml, T2 in min. The tangent coefficients of the approximation lines are −0.35 ± 0.25 for d(lnT2)/d(ln[MΣ]) and 0.07 ± 0. 80 for d(Lrel)/d(ln[MΣ]); the errors are computed with the Student's coefficients corresponding to 0.95 confidence level.

5 h longer than that of the recombinant human insulin. These data seem to us important because the rate of aggregation of insulin preparations is an important health problem not only in the production and storage of insulin, but also for its frequent injections. In this regard, the process of fibrillation should be analyzed for all developed analogs, already prepared for clinical trials and for mass production. Examination of EM images of growing insulin LysPro fibrils shows that they occurred with a kind of the "bifurcation plus lateral growth" scenario [48]. The growth of amyloid fibrils was studied (**Figure 7**) by thioflavin T (ThT) fluorescence, which drastically increases when ThT is bound to fibrils. The dependence of Lrel and lnT2 on ln[MΣ] (**Figure 7**) was used to estimate sizes of the primary and secondary nuclei. Similar to insulin fibrils, the size of the first nucleus is one monomer, and the size of the secondary nucleus is zero (see **Table 2**). It should be noted that "one monomer" may correspond to the oligomer structure consisting of 2–6 monomers, if we did not start from the pure monomers in solution.

#### **6.3. Aβ40**

The experimental kinetics data on the formation of amyloid aggregates, which we used to calculate the sizes of nuclei of amyloid protofibrils formed by Aβ40, were taken from paper [60]. For all the experimental data, we obtained Lrel >> 0.2, which means that the process goes by the exponential mechanism of fibril formation (**Figure 8**). For Aβ40, we obtained that the size of the primary nucleus is two monomers, and the secondary nucleus size is one monomer.

**Figure 8.** (a) Dependence of normalized ThT fluorescence on time for Aβ40 [60]. The approximation [Insert figure cap‐ tion here] line calculated for Aβ40 amyloid formation with experimental data from (a) by the least-squares method plotted in coordinates (b): {lnT2, ln[MΣ]} and (c): {Lrel, ln[MΣ]}; [MΣ] is in μM, T2 in hours. The tangent coefficients of the approximation lines are −0.79 ± 0.18 for d(lnT2)/d(ln[MΣ]) and −0.03 ± 0.32 for d(Lrel)/d(ln[MΣ]); the errors are computed with the Student's coefficients corresponding to 0.95 confidence level.

#### **6.4. Aβ42**

The exponential growth with branching takes place for both Aβ40 and Aβ42 peptides (see **Figures 8** and **9**). Interestingly, according to our analysis, for Aβ42, the size of the primary nucleus of the amyloid protofibril is larger than that of Aβ40, although the mechanism of amyloid fibril formation must be similar. This is consistent with the recent data, which compares the behavior of the two peptides during the aggregation process [60]. The primary nucleus size for Aβ42 is three monomers, and the secondary nucleus size is two monomers.

**Figure 9.** (a) Dependence of normalized ThT fluorescence on time for Aβ42 [61]. The approximation line calculated for Aβ42 amyloid formation with experimental data from (a) by the least-squares method plotted in coordinates (b): {lnT2, ln[MΣ]} and (c): {Lrel, ln[MΣ]}; [MΣ] is in μM, T2 in hours. The tangent coefficients of the approximation lines are −1.48 ± 0.14 for d(lnT2)/d(ln[MΣ]) and 0.22 ± 0.13 for d(Lrel)/d(ln[MΣ]); the errors are computed with the Student's coeffi‐ cients corresponding to 0.95 confidence level.

#### **6.5. Human cardiac titin immunoglobulin domain I27 (TI27)**

5 h longer than that of the recombinant human insulin. These data seem to us important because the rate of aggregation of insulin preparations is an important health problem not only in the production and storage of insulin, but also for its frequent injections. In this regard, the process of fibrillation should be analyzed for all developed analogs, already prepared for clinical trials and for mass production. Examination of EM images of growing insulin LysPro fibrils shows that they occurred with a kind of the "bifurcation plus lateral growth" scenario [48]. The growth of amyloid fibrils was studied (**Figure 7**) by thioflavin T (ThT) fluorescence, which drastically increases when ThT is bound to fibrils. The dependence of Lrel and lnT2 on ln[MΣ] (**Figure 7**) was used to estimate sizes of the primary and secondary nuclei. Similar to insulin fibrils, the size of the first nucleus is one monomer, and the size of the secondary nucleus is zero (see **Table 2**). It should be noted that "one monomer" may correspond to the oligomer structure consisting of 2–6 monomers, if we did not start from the pure monomers in solution.

The experimental kinetics data on the formation of amyloid aggregates, which we used to calculate the sizes of nuclei of amyloid protofibrils formed by Aβ40, were taken from paper [60]. For all the experimental data, we obtained Lrel >> 0.2, which means that the process goes by the exponential mechanism of fibril formation (**Figure 8**). For Aβ40, we obtained that the size of the primary nucleus is two monomers, and the secondary nucleus size is one monomer.

**Figure 8.** (a) Dependence of normalized ThT fluorescence on time for Aβ40 [60]. The approximation [Insert figure cap‐ tion here] line calculated for Aβ40 amyloid formation with experimental data from (a) by the least-squares method plotted in coordinates (b): {lnT2, ln[MΣ]} and (c): {Lrel, ln[MΣ]}; [MΣ] is in μM, T2 in hours. The tangent coefficients of the approximation lines are −0.79 ± 0.18 for d(lnT2)/d(ln[MΣ]) and −0.03 ± 0.32 for d(Lrel)/d(ln[MΣ]); the errors are computed

The exponential growth with branching takes place for both Aβ40 and Aβ42 peptides (see **Figures 8** and **9**). Interestingly, according to our analysis, for Aβ42, the size of the primary nucleus of the amyloid protofibril is larger than that of Aβ40, although the mechanism of amyloid fibril formation must be similar. This is consistent with the recent data, which

with the Student's coefficients corresponding to 0.95 confidence level.

**6.3. Aβ40**

15614 Exploring New Findings on Amyloidosis

**6.4. Aβ42**

To determine the sizes of folding nuclei for amyloid formation, calculations were done using the data of aggregation kinetics for the I27 immunoglobulin domain from human cardiac titin (TI27) [62]. The set of data was digitized, and in the case of TI27, part of the curve was excluded from the analysis. It was found that the growth of amyloids formed by TI27 is exponential, that is, in addition to the primary core nucleation secondary nucleation by a branching mechanism also takes place, accelerating the formation of new fibrils.