Disease-Driven Initiative on Protein-Aggregation Diseases of

Subscriber access provided by Kaohsiung Medical University

Perspective

The Biology and Disease-driven Initiative on Protein Aggregation Diseases of the Human Proteome Project: Goals and Progress to Date Paul J. Boersema, Andre Melnik, Bouke P.C. Hazenberg, Melinda Rezeli, György Marko-Varga, Junichi Kamiie, Erik Portelius, Kaj Blennow, Roman A. Zubarev, Magdalini Polymenidou, and Paola Picotti J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00401 • Publication Date (Web): 23 Aug 2018 Downloaded from http://pubs.acs.org on August 24, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Journal of Proteome Research

The Biology and Disease-driven Initiative on Protein Aggregation Diseases of the Human Proteome Project: Goals and Progress to Date

Paul J. Boersema*, Andre Melnik*, Bouke P.C. Hazenberg$, Melinda Rezeli#, György Marko-Varga#, Junichi Kamiie†, Erik Portelius‡, Kaj Blennow‡, Roman A. Zubarev∥, Magdalini Polymenidou▽, and Paola Picotti*

* Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Otto-Stern-Weg 3, 8093 Zurich, Switzerland. $

Department of Rheumatology & Clinical Immunology, University of Groningen, University Medical

Center Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands #

Clinical Protein Science & Imaging, Dept. of Biomedical Engineering, Lund University, BMC D13,

221 84 Lund, Sweden †

Laboratory of Veterinary Pathology, Azabu University, 1-17-71 Fuchinobe, Chuo-ku, Sagamihara,

Kanagawa 252-5201, Japan ‡

Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The

Sahlgrenska Academy at University of Gothenburg, S-431 80 Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal S-431 80, Sweden ∥

Department of Medical Biochemistry and Biophysics, Karolinska Institute, 17177 Stockholm,

Sweden ▽

Institute of Molecular Life Sciences, University of Zürich, Winterthurerstrasse 190, Zürich,

Switzerland

Correspondence to: Paola Picotti, [email protected], (+41) 44- 6332558 1 ACS Paragon Plus Environment

Journal of Proteome Research 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Abstract

The Biology and Disease-driven (B/D) working groups of the Human Proteome Project are alliances of research groups aimed at developing or improving proteomic tools to support a specific biological or disease-related research areas. Here we describe the activities and progress to date of the B/D working group focused on protein aggregation diseases (PADs). PADs are characterized by the intraor extracellular accumulation of aggregated proteins and include devastating diseases such as Parkinson’s and Alzheimer’s disease and systemic amyloidosis. The PAD B/D working group aims at the development of proteomic assays for the quantification of aggregation-prone proteins involved in PADs to support basic and clinical research on PADs. Since the proteins in PADs undergo aberrant conformational changes, a goal is to quantitatively resolve altered protein structures and aggregation states in complex biological specimens. We have developed protein extraction protocols and a set of mass spectrometric (MS) methods that enable the detection and quantification of proteins involved in systemic and localized amyloidosis and probing of aberrant protein conformational transitions in cell and tissue extracts. In several studies, we have demonstrated the potential of MS-based proteomics approaches for specific and sensitive clinical diagnoses and for the subtyping of PADs. The developed methods have been detailed in both protocol papers and manuscripts describing applications to facilitate implementation by non-specialized laboratories and assay coordinates are shared through public repositories and databases. Clinicians actively involved in the PAD working group are supporting the transfer to clinical practice of the developed methods, such as assays to quantify specific disease-related proteins and their fragments in biofluids and multiplexed MS-based methods for the diagnosis and typing of systemic amyloidosis. We believe that the increasing availability of tools to precisely measure proteins involved in PADs will positively impact research on the molecular bases of these diseases and support early disease diagnosis and a more confident subtyping.

2 ACS Paragon Plus Environment

Page 2 of 40

Page 3 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Keywords: Protein aggregation diseases, Human Proteome Project, Biology/Disease-driven HPP, Alzheimer’s disease, Parkinson’s disease, Amyotrophic lateral sclerosis, Frontotemporal Dementia, Systemic amyloidosis.



Protein aggregation diseases Protein aggregation diseases (PADs), also referred to as protein conformational or protein misfolding diseases or amyloidoses, are characterized by the intra- or extracellular accumulation of misfolded, oligomeric, or aggregated proteins. The aberrant proteins are either produced at the deposition site, as in localized amyloidosis, or distributed systemically after production at a specific site and may affect multiple organs and tissues.1 PADs can be classified based on the major components of the deposits. For example, Lewy bodies that contain aggregates of α-synuclein (α-Syn) are typically observed in patients with most types of Parkinsonism; proteins with lengthened polyglutamine (polyQ) stretches characterize polyQ disorders (e.g., huntingtin in Huntington’s disease); and TDP-43 inclusions are formed in patients with amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD).2-4 In some pathologies cellular damage results from the loss of physiological function of the misfolded protein (e.g., parkin, granulin). In other diseases, proteins (e.g., α-Syn, huntingtin, or the amyloid-β (Aβ) peptide) acquire a toxic function upon misfolding and aggregation.5-7 The toxicity effectors can be aberrant conformations of the monomeric protein, its aggregates, the aggregation process itself, or oligomeric intermediates.6-8 Intriguingly, even though proteins involved in PADs are characterized by a variety of seemingly unrelated sequences, upon misfolding and aggregation many adopt the same structural state, termed an amyloid.9 Amyloids are highly ordered, fibrillar, and polymeric structures, characterized by a cross-β-sheet fold and by a unique set of biophysical characteristics including extreme protease resistance and detergent insolubility, tinctorial properties (binding of dyes such as thioflavin T and Congo red), assembly by nucleated polymerization, and capability of specific selftemplating.10 Protein aggregation in PADs can be triggered by genetic abnormalities, increased levels of the precursor protein, aberrant proteolytic processing or post-translational modification, alterations of protein quality control systems, or environmental stresses such as high temperature or oxidative stress. The majority of protein aggregation diseases are sporadic in nature, although familial, transmissible, and iatrogenic cases have also been reported.11


Page 4 of 40

Page 5 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Over 30 amyloidoses and several other PADs have been reported. All are characterized by the presence of deposits of aggregates whose main constituent is a specific peptide or a protein. In Table 1, we catalogue the proteins and peptides that have been found to aggregate in humans and list the location and type of aggregation and diseases caused. Complicating study of PADs, the same amyloidogenic protein can be found in more than one disease and mixed proteinopathies are often reported. Deposits may also contain inflammatory molecules, metal ions, or antioxidants, and additional non-amyloidogenic proteins such as serum amyloid P component, apolipoprotein E, or clusterin are also observed in amyloid deposits.12


Journal of Proteome Research 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 6 of 40

Table 1. Proteins and peptides implicated in PADs and B/D HPP assays PURPOSE Precusor protein score

Amyloid fibril protein

Intra- or extracellular

Acquired (A) or hereditary (H)

extra, intra

Systemic (S) or Localized (L) L

Diseases

Affected sites

Developed MSbased assays

AαSyn

-

extra, intra

AIAPP

Chromosomal location

A, H

Parkinson's disease

CNSm, Lewy bodies

SRM assay (wildtype, three splice forms, A30P, E46K, A53T)a, SRM assay (different structural states)b

4q22.1

L

A, H

Amyotrophic lateral sclerosis, frontotemporal dementia

CNS

Untargeted LCMS/MSc

1p36.22

extra

L

A

Type II diabetes

Islets of Langerhans, insulinomas

LC-MS/MS (database)d

12p12.1

Huntington‘s disease

CNS, Huntington bodies

Untargeted LCMS/MSc

4p16.3

CNS

Untargeted LCMS/MS (12 isoforms)e, PRM (Aβ1-42)f

21q21.3

38.06

α-Synuclein (wildtype or variant)

35.656

TAR DNA-binding protein 43 (wild-type or variant)

34.818

Islet amyloid polypeptide

34.372

Huntingtin (trinucleotide repeat expansion)

-

intra

L

H

32.365

Aβ protein precursor (wild-type or variant)

Aβ

extra

L

A, H

Alzheimer's disease, hereditary cerebral hemorrhage with amyloidoses

31.789

Prion protein (wildtype or variant)

APrP

extra

S,L

A, H

Spongiform encephalopathies, CNS, PNS Creutzfeldt-Jakob disease, fatal insomnia, Gerstmann-Sträussler-Scheinker syndrome


30.561

Superoxide dismutase (wild-type or variant)

-

intra, extra

L

A, H

Amyotrophic lateral sclerosis

Motor neurons

Untargeted LCMS/MSc

21q22.11

30.387

Tau (wild-type or variant)

ATau

extra, intra

L

A

Fronto-temporal dementias, Alzheimer's disease, aging, other cerebral conditions

CNS, neurofibrillary tangles

Untargeted LCMS/MS (incl. phosphorylation sites)c

17q21.31

6

ACS Paragon Plus Environment

20p13

Page 7 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


27.919

Transthyretin (wildtype or variant)

ATTR

extra

S

A, H

Hereditary and wild-type ATTR amyloidosis

Heart mainly in males, ligaments, tenosynovium, PNS, ANS, heart, eye, leptomeninges

SRM assay (wildtype, A25E, V30M, A36P, A45G, G47E, L55P, V71A, E89K, V94A, Y114C, V122I)g, Untargeted LCMS/MS (wildtype)h

18q12.1

26.758

Chromosome 9 open reading frame 72 (hexanucleotide repeat expansion)

-

intra

L

A, H


CNS

Untargeted LCMS/MSc

9p21.2

24.61

Fibrinogen α, variants

AFib

extra

S

H

AFib amyloidosis

Primarily kidney

SRM assay (wildtype, E524K, E526V)g

4q31.3

24.456

Lysozyme, variants

ALys

extra

S

H

ALys amyloidosis

Kidney

SRM assay (wildtype, T70N)f, DIA assayi

12q15

22.993

Ataxins

-

intra

L

H

Cerebellar ataxias

Cerebellum


22.417

Fused in sarcoma (wild-type or variant)

-

intra

L

A, H


CNS

Untargeted LCMS/MSc

21.178

Insulin

AIns

extra

L

A

AIns amyloidosis

Iatrogenic, injection site


20.601

β2-microglobulin (wild-type or variant)

Aβ2M

extra

S

A, H

Aβ2M amyloidosis

Musculoskeletal system, ANS

SRM assay (wildtype)g

15q21.1

18.028

Apolipoprotein A-I,

AApoAI

extra

S

H

AApoAI amyloidosis

Heart, liver, kidney, PNS,

SRM assay (wild-

11q23.3

7


ATXN1 6p22.3, ATXN2, 12q24.12, ATXN3 14q32.12, ATXN7 3p14.1, ATXN8 13q21, ATXN10 22q13.31 16p11.2

N/A


variants

Page 8 of 40

testis, larynx, skin

type, G35V)g

ACys

extra

S

H

Hereditary cerebral hemorrhage with amyloidoses

PNS, skin

SRM assayg

20p11.21

Apolipoprotein C-II, variants

AApoCII

extra

S

H

AApoCII amyloidosis

Kidney

Untargeted LCMS/MS (wildtype, E69V)j

19q13.32

14.624

Androgen receptor

-

intra

L

H

Kennedy disease

CNS


Xq12

14.573

Gelsolin, variants

AGel

extra

S

H

AGel amyloidosis

PNS, cornea

SRM assayg

9q33.2

14.315

Lung surfactant protein

ASPC

extra

L

A

ASPC amyloidosis

Lung


8p21.3

13.742

(Pro-)calcitonin

ACal

extra

L, S

A

Medullary carcinoma of the thyroid

C-cell thyroid tumors


11p15.2

11.665

Prolactin

APro

extra

L

A

APro amyloidosis

Pituitary prolactinomas, aging pituitary glands


6p22.3

11.416

Corneodesmosin, variants

ACor

extra

L

A

Hypotrichosis simplex of the scalp

Cornified epithelial, hair follicles


6p21.33

10.251

Atrophin 1

-

intra

L

H

Dentatorubro-pallido-Luysian atrophy

CNS


12p13.31

9.295

Odontogenic ameloblastassociated protein

AOAAP

extra

L

A

AOAAP amyloidosis

Odontogenic tumors


4q13.3

8.102

(Apo) Serum amyloid A

AA

extra

S

A

AA amyloidosis

All organs, except CNS

SRM assayg, DIA assayi, untargeted LCMS/MSh

11p15.1

Immunoglobulin light chains

AL

extra

S, L

A, H

AL amyloidosis


SRM assay (κ Lambda and λ)g, 22q11.22, untargeted LCKappa 2p11.2 MS/MS (κ and λ)h

Immunoglobulin heavy chains

AH

extra

S, L

A

AH amyloidosis



14q32.33

ALECT2

extra

S

A

ALECT2 amyloidosis

Primarily kidney

SRM assayg

5q31.1

16.902

Cystatin C

16.722

Leukocyte

8


Page 9 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


chemotactic factor 2 Apolipoprotein A-II, variants

AApoAII

extra

S

H

AApoAII amyloidosis

Kidney

SRM assay (wildtype)g

1q23.3

Apolipoprotein A-IV, variants

AApoAIV

extra

S

A

AApoAIV amyloidosis

Kidney medulla and systemic

SRM assay (wildtype)g, DIA assayi

11q23.3

ASem1

extra

L

A

ASem1 amyloidosis

Vesicula seminalis


20q13.12

Lactadherin

AMed

extra

L

A

AMed amyloidosis

Senile aortic media


15q26.1

Lactoferrin

ALac

extra

L

A

Corneal dystrophy

Cornea


3p21.31

Kerato-epithelin

AKer

extra

L

A, H

Corneal dystrophy

Cornea


5q31.1

Galectin 7

AGal7

extra

L

A

Skin


19q13.2

Enfurvitide

AEnf

extra

L

A

AEnf amyloidosis

Skin, Iatrogenic

Untargeted LCMS/MSk

ADan, ABri

extra

L, S

H

Familial Danish dementia, Familial British CNS dementia,


13q14.2

AApoCIII

extra

S

H

AApoCIII amyloidosis

Kidney


11q23.3

AANF

extra

L

A

Atrial amyloidosis

Cardiac atria


1p36.22

AOSMRl

extra

L

H

Lichen amyloidosis

Skin


5p13.1

Actin

-

intra

L

H

Neurodegenerative disorders

CNS primarily, Hirano bodies


ACTB 7p22.1, ACTG 17q25.3

Neuroserpin

-

intra

L

H

Familial encephalopathy

CNS, Collins bodies


3q26.1

Ferritin

-

intra

L

H

Familial neurodegenerative disorders

CNS

Untargeted LCMS/MSc

Semenogelin 1

BRI2, Danish and British variants Apolipoprotein C-III, variants Atrial natriuretic factor Oncostatin M receptor

9


N/A

19q13.33


TATA box-binding protein

-

intra

L

H

Spino cerebellar ataxia 17

a

Empiric peptide retention time (RT) and fragmentation, Melinda Rezeli (personal communication) and 13.

b

Empiric peptide RT and fragmentation.14

c

Empiric peptide RT and fragmentation, Florent Laferriere and Magdalini Polymenidou (personal communication).

d

Empiric peptide fragmentation found in www.srmatlas.org.

e


f


g

Empiric peptide RT and fragmentation, further confirmed by synthetic peptides, Paul Boersema and Paola Picotti (personal communication).

h


Page 10 of 40

Cerebellum


i

Theoretical fragmentation for peptides of 31 amyloidogenic proteins; empiric peptide RT and fragmentation confirmed for SAA, ApoA4, and lysozyme, Junichi Kamiie (personal communication).

j


k


l

No official nomenclature has been established.

M

Abbreviations used: central nervous system (CNS); peripheral nervous system (PNS); autonomic nervous system (ANS)

10


6q27

Page 11 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Challenges in protein analytics in PADs The prognosis of patients with systemic amyloidosis can be poor, and treatment may require extreme measures such as chemotherapy or bone marrow or organ transplantation depending on the precursor protein and state of disease. An early and proper diagnosis and identification of the precursor protein (amyloidosis subtyping) is therefore important but is currently complicated.20 Often, identification relies on antibody-based assays to identify the main precursor protein present in the amyloid deposits. Antibody tests often do not provide conclusive diagnoses, however, and these assays are laborious and do not enable testing of the whole spectrum of precursor proteins due to the lack of suitable antibodies. Further, epitopes may be masked within the amyloid structure. Equally challenging can be the clinical evaluation of localized amyloidoses, in particular those of neurological origin, such as Parkinson’s disease (PD) or Alzheimer’s disease (AD), for which there are currently limited reliable biochemical diagnostic assays available in clinical practice. Variations in the concentration of amyloidogenic proteins in biological fluids from patients with neurological PADs have been reported21-26 and are currently considered as valuable biomarkers in panels including other -non-biochemical- assays, such as amyloid PET. These biomarkers are central for the novel research diagnostic criteria for AD.22 However, while some of the assays are increasingly used in clinical routine diagnostics and in clinical trials,24 findings about other potential markers have been inconsistent across different studies and levels of the measured species overlapped between patients and healthy controls or were affected also in other conditions.27 Although the concentration of amyloid precursor protein does not necessarily constitute a conclusive biomarker, accumulating evidence suggests that precursor proteins may undergo conformational transitions in biological fluids at early disease stages.28 This may hide epitopes precluding detection by antibody-based assays. Detecting and accurately quantifying such conformational changes may have the potential to overcome the limitations of current diagnostic approaches and may enable early disease detection and evaluation of prognosis.



In summary, the development of novel approaches to reliably and quantitatively measure proteins involved in PADs and to detect and quantify altered conformations is urgently needed for early disease diagnosis, for the assessment of disease severity and prognosis, and for assessment of efficacy of drugs in clinical trials. Such tools would also be extremely useful in basic biological research on the molecular bases of PADs, for the development of novel therapeutic agents, and in assessment of the efficacy of therapeutic approaches in preclinical models.

The Biology and Disease-driven Initiative on PADs of the Human Proteome Project In 2010, the Human Proteome Organization launched the Human Proteome Project (HPP), a coordinated effort of many research laboratories worldwide with the aims of promoting our understanding of the human proteome, enhancing the quality of proteomics data, and promoting the development of proteomics tools for biological and biomedical research. One of the resource pillars of the HPP are the Biology and Disease-driven (B/D) initiatives aimed at the development of targeted and high-throughput proteomic tools to study biological and disease-associated protein networks for diagnostic, prognostic, therapeutic, and preventive medical applications. The B/D HPP, which was launched in 2013, is organized into multiple working groups focused on specific biological or disease areas. Each working group is an alliance of independent research groups with interest in a particular topic. The goal of each alliance is to develop or improve proteomics tools to support the specific research area and to promote the adoption of such tools within the targeted biological or biomedical communities 29. The working group on Protein Aggregation Diseases was launched at the 13th HUPO Conference in 2014 in Madrid, Spain. The group works to develop mass spectrometry (MS) proteomics tools for the detection and quantification of proteins involved in PADs to support basic biological research on these devastating human diseases. In PADs, the structure and folding state of proteins, rather than their mere concentration or activity, play crucial roles in development of the disease. Thus, due to this specific molecular feature of PADs, the objectives of the B/D Initiative on PADs go beyond objectives of other B/D initiatives and will


Page 12 of 40

Page 13 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


attempt for the first time the development of proteomics tools to quantitatively resolve altered protein structures and protein aggregation states in complex biological and biomedical samples.

Organization and workflow of the PAD working group After its launch at the HUPO conference in Madrid in 2014, the PAD working group met for the second time during the 14th HUPO Conference in 2015 in Vancouver, Canada. The well-attended workshops included presentations from scientists focused on development of MS-based proteomics methods to study PADs as well as from clinicians who provided medical background on PADs and the current analytical challenges in the study, diagnosis, and treatment of these diseases. The group will organize another workshop in central Europe in the spring of 2019. The PAD working group follows the workflow developed within B/D HPP for its component initiatives30 (Figure 1). This workflow involves the following steps: 1) selection of biological focus areas, 2) generation of lists of proteins relevant to the chosen focus area, 3) generation of relevant assays and reagents for these targets, 4) dissemination of the generated knowledge and reagents, and 5) introduction of clinicians and biologists to the methodological developments implemented by the group that are relevant to basic research and clinical activities. In the following sections, we will review how each step has been implemented by the PAD B/D working group.

Figure 1. PAD working group workflow. 13 ACS Paragon Plus Environment


1) Selection of focus area The overarching focus area of the working group is basic biological research and clinical challenges connected to PADs. Given the large number and complexity of PADs, for some of the planned activities (e.g., application of the developed assays to biomedical samples), the group decided to focus on specific diseases as test cases. These diseases include PD, AD, ALS/FTD, and systemic amyloidosis (with special emphasis on amyloids of serum amyloid A (AA), transthyretin (ATTR), and immunoglobulin light chains (AL-Kappa and AL-Lambda)).

2) Generation of target protein list The working group decided to focus its efforts on disease-related amyloidogenic proteins associated with human disease based on a reference nomenclature paper by Sipe et al.31 that was recently updated.11 The target protein list was expanded with proteins that are known to aggregate and form intra- or extracellular inclusions that may or may not have amyloid properties32 resulting in a total of 47 proteins (Table 1). Assays will also be created for proteins that are not amyloidogenic per se but that are often found associated with amyloid plaques such as serum amyloid P component, apolipoprotein E, inflammatory molecules, clusterin, and SOD-1 and SOD-2.12 To prioritize the protein list, we incorporated the recently developed Protein Universal Reference PublicationOriginated Search Engine (PURPOSE) score.33 This score relies on an automated biomedical literature mining effort and quantifies the relevance of specific proteins to a specific focus area (e.g., a given disease) based on the number of papers and citations on the topic that involve the protein. A PURPOSE score could be calculated for around 60% of our target proteins. In the future, the group will consider expanding the target list to splice isoforms (e.g. from intron retention events) of diseaseassociated proteins and to other emerging targets (e.g. gamma-secretases in AD).34-37


Page 14 of 40

Page 15 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


3) Generation of relevant assays and datasets The most widespread approaches for the detection and identification of amyloid-forming proteins are antibody-based assays. A variety of antibodies targeting amyloidogenic proteins involved in human disease are commercially available and are applicable to biofluids and tissues including formalin-fixed paraffin-embedded (FFPE) tissue sections. Antibody-based approaches have pitfalls, however, that include false negatives (e.g., due to masking of epitopes within the aggregated structures) and false positives (e.g., due to non-specific staining).

Thanks to the pioneering work of members of our consortium and other groups, proteomic approaches based on MS have emerged as powerful alternatives to antibody-based assays for the quantification of proteins involved in PADs.17, 38-43 Two main mass spectrometric approaches, unbiased and targeted, are available for this purpose. Classical, unbiased proteomic analyses based on shotgun MS attempt the simultaneous analysis of the entire protein content of a sample and rely on automated peptide sequencing by liquid chromatography-coupled tandem MS (LC-MS/MS) followed by peptide identification from MS spectra by database searching. Unbiased approaches have been applied in the field of PADs to the characterization of the content of aggregates extracted from PAD patients,17 to the search for protein biomarkers,16, 44 and to the analysis of cellular and animal models of PAD with the aim of shedding light on the molecular bases of these pathologies.45, 46 More recent targeted proteomic approaches based on selected reaction monitoring (SRM) and related acquisition methods are the goldstandard for the measurement of predefined sets of proteins (typically fewer than 100) across multiple samples with high reproducibility, precision, and sensitivity.47 Typical applications of SRM assays are the targeted analysis of proteins of interest across differently perturbed samples, such as dosage series or time courses or the quantification of candidate protein biomarkers across samples from patient cohorts. The development of an SRM assay involves the extraction of a set of specific mass spectrometric coordinates for each protein of interest that enable the specific acquisition of their MS signals. Once developed and validated, SRM assays can be applied to a variety of samples and shared with the community, akin to libraries of antibodies. Data-independent acquisition methods, such as



SWATH MS, aim at the proteome-wide extension of targeted SRM-based protein analyses and are now starting to gain momentum.48

The PAD working group aims to collect and archive shotgun proteomic datasets from samples relevant to PADs to expand the inventory of proteins involved in these pathologies. Further, the group aims to develop standardized targeted proteomic assays based on SRM, parallel reaction monitoring (PRM), or data-independent acquisition (DIA) for the precise and reproducible quantification of proteins involved in PADs, their proteoforms, and their structural states across a variety of samples (Figure 1).

4) Dissemination of the generated datasets and assays

The utilization of MS datasets and assays developed by the PAD working group depends on the efficient storage and subsequent dissemination of knowledge and method details. The group will undertake this at two levels: First, we will publish reports of results and methods in peer-reviewed journals and will present results at scientific conferences in the proteomics and PAD fields. Second, we will archive quality-filtered datasets and associated meta-data and MS assay coordinates in publicly accessible repositories organized in the centralized infrastructure of ProteomeXchange.49 Specifically, MS/MS data from the PAD initiative will be regularly submitted to the PRIDE repository where a B/D PAD project repository branch has already been created. SRM data will be submitted to the PASSEL repository,50 a component of the PeptideAtlas database.51 5) Sharing of proteomic developments with clinicians and biologists operating in the PAD field The interdisciplinary undertakings of the PAD working group rely on close and synergistic interactions among proteomics experts, clinicians, biologists, and statisticians. Groups specialized in the development and application of proteomics technologies (P. Picotti, ETH Zurich, Switzerland; G. Marko-Varga, University of Lund, Sweden; R. Zubarev, Karolinska Institute, Stockholm, Sweden) aim to generate standardized datasets, validated assays, and improved and novel proteomic technologies for the study of PADs that can be transferred to other laboratories. A number of 16 ACS Paragon Plus Environment

Page 16 of 40

Page 17 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


clinicians and biologists focusing on clinical aspects or basic research in the field of PADs are involved in the PAD group either as direct participants or as collaborators (G. Merlini, University of Pavia, Italy; B.P.C. Hazenberg, University Hospital Groningen, The Netherlands; D. Aarsland, Karolinska Institute, Stockholm, Sweden; K. Blennow, University of Gothenburg, Sweden; M. Polymenidou, University of Zurich, Switzerland; and members of the clinical and pathological groups at Lund University, Sweden, King’s College, England, University of Debrecen, Hungary, and the Human Brain Tissue Bank at the Semmelweis University, Budapest, Hungary). The participation of clinicians and biologists is crucial to the success of the PAD working group in several ways. First, these experts guide the identification of protein targets that are relevant to the study, diagnosis, or therapy of PADs. Second, they provide access to relevant clinical samples and samples from cellular and animal models to apply and test the MS assays generated by the group. Third, the involvement of experts with a biological and clinical background will promote the implementation and effective exploitation of the generated assays and knowledge in clinical and biological laboratories.

Progress to date 1. Systemic amyloidosis In systemic amyloidosis, amyloid fibrils of specific proteins are widely distributed and deposited in organs and tissues and ultimately cause tissue damage and organ failure. The most common proteins found in an aggregated state in systemic amyloidosis are the immunoglobulin light chain, transthyretin, and the serum amyloid A protein. Amyloid is typically detected in tissue specimens after staining with the amyloid-specific Congo red dye: Upon binding to the dye, amyloid deposits are red in bright light and show green birefringence when observed in polarized light. After the detection of amyloid, the biochemical type of amyloid (precursor protein) must be assessed. Amyloid-forming proteins are typed in tissue samples or FFPE tissue sections by antibody-based techniques. The abovedescribed limitations of antibodies as well as hindrance by non-specific background staining make it difficult to type amyloids with confidence.52



The first project initiated by the PAD working group aims at the development of validated SRM-based MS assays for known amyloidogenic proteins to support the diagnosis and subtyping of systemic amyloidosis and the testing of a subset of these assays on clinical samples. The project relies on the close collaboration between the Picotti group (ETH, Zürich, Switzerland), focused on developing proteomics technologies, a clinical unit headed by Bouke Hazenberg (University of Groningen, the Netherlands), and the Vitek group (Northeastern University, Boston, MA, USA), specialized in statistical analysis of proteomics data.

In this project, a multiplexed LC-SRM method has been developed to simultaneously detect and quantify proteins involved in the 11 most common systemic amyloidoses including several mutated protein variants commonly found in western Europe. The target protein list includes amyloidogenic proteins known to be involved in systemic amyloidosis31 and other proteins found associated with amyloid aggregates (that do not necessarily form amyloid aggregates themselves) identified based on shotgun proteomic analyses of clinical samples performed by the Picotti group and on previous shotgun proteomic analyses by the Merlini laboratory (University of Pavia, Italy).17 SRM assays were developed for unique peptides with favorable MS properties and were validated by the use of isotopically labeled synthetic versions of each targeted peptide. SRM assays targeting peptides corresponding to the most commonly mutated protein variants were also developed. The multiplexed assay was applied to samples from subcutaneous fat aspirates. The sampling technique is relatively non-invasive, and the MS analysis requires only a few micrograms of total protein. Application of the assay to samples from a cohort of patients with different types of amyloidosis indicated that the 1hour, multiplexed SRM assay enabled diagnosis and subtyping of the three most common systemic amyloidoses with a 100% specificity and approximately 80% sensitivity. The group plans to transfer the multiplexed SRM assay to the clinical unit to attempt its implementation into routine clinical practice.

In another project, executed in the Kamiie lab at Azabu University (Sagamihara, Japan), a simple and sensitive novel MS methodology was developed for the identification of amyloidogenic proteins from 18 ACS Paragon Plus Environment

Page 18 of 40

Page 19 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


FFPE patient tissue samples. The approach was developed to address limitations in throughput and cost of previous methods based on laser capture microdissection.39,

53, 54

In the MS-based assay,

amyloid forming proteins are extracted with organic solvents from the FFPE sections. The resulting extracts are digested with trypsin and subsequently analyzed by MS. The raw DIA data are evaluated using theoretical precursor and fragment m/z values of peptides of interest to yield the abundances of 31 amyloidogenic proteins. The approach was applied to FFPE patient sections from four clinical biopsy specimens from patients diagnosed with amyloidosis. Section-specific proteins identified by DIA analysis were SAA, ApoA4, lysozyme, and cytokeratin 10. The analyses demonstrate that this extraction procedure coupled with DIA has the potential to provide accurate quantitative readouts required for the diagnosis of amyloidosis type.

2. Parkinson’s and Alzheimer’s disease and dementia with Lewy bodies The prevalence of neurodegenerative diseases such as PD and AD is steadily increasing as our societies age. These diseases pose challenges to modern healthcare, both in terms of increasing healthcare costs and the burdens on patients, families, and hospitals. The challenges associated with the diagnosis and treatment of these diseases are multifold and include the inherent difficulty of performing an accurate diagnosis with non-invasive high-resolution imaging technologies such as MRI, PET, or CT. Furthermore, although promising therapeutic approaches have been described, the potential therapies have had a limited impact on patients. Even though various research groups have contributed to the characterization of the molecular mechanisms of PD and AD, early pathogenic events and the causes of highly variable treatment responses remain largely unknown. The Marko-Varga research group at Lund University (Lund, Sweden) focuses on the development of MS-based quantitative assays for proteins linked to PD and AD with an emphasis on different proteoforms (e.g., mutations, splice variants). The group has access to patient samples accompanied by detailed clinical information and neuropathological diagnoses thanks to collaborations with clinical and pathological groups at Lund University, King's College London, the University of Debrecen, and the Human Brain Tissue Bank at Semmelweis University. The Marko-Varga group has developed an 19 ACS Paragon Plus Environment


assay for the quantitation of apolipoprotein E (ApoE) and its specific isoforms, which are strongly associated with late-onset AD. Originally, ApoE was thought to be synthesized in the brain only by astrocytes, oligodendrocytes, and ependymal layer cells. Increasing evidence, however, suggests that under diverse pathophysiological conditions, neurons, cells associated to blood vessels and choroid cells also express ApoE, which is thought to be the major source of ApoE in the CSF.55-58 The assay to quantify ApoE has been utilized for screening of biobanked samples of both blood plasma and cerebrospinal fluid (CSF).43 Further, the group developed an SRM assay that quantifies α-Syn proteoforms including the three splice forms and various PD related natural variants (Figure 2). Currently, the group is working on an extension of this assay to relevant truncated α-Syn species in order to increase our understanding of disease progression and its correlation to molecular alterations within the brain microenvironment.

3.0E+06

α-syn pep1 α-syn pep4

2.0E+06 Intensity

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 20 of 40

α-syn A30P

1.0E+06

α-syn iso3 α-syn A53T α-syn pep3 α-syn pep2 α-syn iso2 α-syn E46K 0.0E+00 5

10

15 RT (min)

20

25

Figure 2. SRM signals of nine peptides representing different α-Syn proteoforms (α-Syn pep1, QGVAEAAGK; α-Syn pep2, EGVVHGVATVAEK; α-Syn pep3, EQVTNVGGAVVTGVTAVAQK; α-Syn pep4, TVEGAGSIAAATGFVK; α-Syn iso2, EGYQDYEPEA; α-Syn iso3, EGVLYVVAEK; α-Syn A30P, QGVAEAPGK; α-Syn E46K, GVVHGVATVAEK; α-Syn A53T, EGVVHGVTTVAEK).


Page 21 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


In addition to developing assays for specific proteoforms of amyloidogenic proteins, the group is attempting to identify novel proteins related to PADs. Protein expression profiles of several anatomically well-defined brain regions from patients at different stages AD progression were measured to identify changes in the brain proteome during the course of disease. The objective is to provide insight into disease mechanisms and to identify proteins that can be used for prediction of disease risk, diagnosis, and/or monitoring of disease progression. AD and dementia with Lewy bodies (DLB) have different underlying causes but have similarities in pathophysiology making early diagnosis and differentiation difficult. DLB is therefore often misdiagnosed as AD 59. Correct diagnosis is essential because treatment approaches differ. A method was developed by the Zubarev lab (Karolinska Institute, Stockholm, Sweden) that takes advantage of the specificity and sensitivity of MS to identify and quantify antibodies and co-extracted proteins from patient serum samples in an endeavor to find biomarkers for the differentiation of AD and DLB.42 The method, christened SpotLight, uses Melon Gel to enrich polyclonal immunoglobulin G (IgG) and other proteins from blood serum. Due to the sequence diversity of IgGs, few complete IgG sequences are found in genome databases. Therefore, de novo sequencing is used to identify peptides from variable regions of IgGs and other proteins to uncover the ‘hidden proteome’. Quantification of peptides and proteins identified by SpotLight in AD and DLB samples, resulted in a model with predictive power of approximately 95% to separate the two types of dementia42.

The groups of Erik Portelius and Kaj Blennow at the Sahlgrenska University Hospital and University of Gothenburg in Sweden seek to implement MS techniques into clinical routine analysis to aid in the diagnostic work-up of patients with cognitive impairment. These groups focus on identification and validation of novel biomarkers for AD, PD, and other neurological diseases, focusing mainly on CSF samples and, in some projects, human brain tissue. In order to analyze such samples a purification step is needed. Immunoprecipitation (IP) in combination MALDI-TOF/TOF MS revealed that the expression of amyloid-beta (Aβ), a central peptide in AD pathogenesis, in CSF is far more complex than expected.15, 41 The assay developed has enabled the analysis of target engagement in clinical trials.60-62 Recently, the group developed and validated a method based on solid-phase extraction (SPE) 21 ACS Paragon Plus Environment


in combination with PRM for the absolute quantification of Aβ1-42, a highly amyloidogenic Aβ fragment, in CSF16. The method was accepted in 2015 as a reference measurement procedure by The Joint Committee for Traceability in Laboratory Medicine.

CSF contains several peptides that are fragments of endogenous neurogranin (Ng), a postsynaptic protein. Concentrations of several of these peptides are increased in AD patients compared to healthy controls.63 Based on these results, the Portelius and Blennow groups have produced monoclonal antibodies directed at specific Ng cleavage sites and have developed an ELISA that will be introduced into clinical use in the fall of 2018. Similarly, an IP-PRM assay was developed for the quantification of tryptic peptides originating from the presynaptic proteins synaptotagmin and SNAP-25. Increased CSF concentrations of both proteins in AD patients compared to controls were observed, even in the early stage of disease.64, 65 Since there is no ELISA available for these proteins, the IP-PRM MS method will be implemented into clinical routine in the fall of 2018.

3. Amyotrophic lateral sclerosis and frontotemporal dementia ALS is an adult-onset neurodegenerative disorder characterized by the accumulation of misfolded proteins in the central nervous system. ALS is tightly associated with another neurodegenerative disease, called FTD, which is the second most common type of dementia after Alzheimer’s disease. The most commonly misfolded protein in both ALS and FTD is the TAR DNA binding protein of 43 kDa (TDP-43), and these cases are often collectively referred to as TDP-43-proteinopathies. Indeed, the vast majority of ALS cases present with TDP-43 pathology, with rare exceptions, including familial cases with mutations in superoxide dismutase 1 (SOD1) or fused in sarcoma (FUS). TDP-43 is also the main aggregated protein in approximately half of FTD patients, while distinct pathological subtypes of FTD involve misfolding of Tau or in rare cases FUS. Unlike many of the other misfolded proteins discussed here, pathological TDP-43 accumulations do not seem to adopt classical amyloid conformations and their biochemical isolation had not been achieved.


Page 22 of 40

Page 23 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


The Polymenidou group at the University of Zurich, Switzerland has recently discovered that physiological TDP-43 forms dynamic and functional oligomers, which associate with RNAs in the cell nucleus 66 and which typically co-isolate with the pathological aggregates in disease brains. They have devised a new purification method that allows the separation of these two TDP-43 states. Biochemical analysis of isolated pathological TDP-43 species from patient brains revealed specific properties. Moreover, in collaboration with the Picotti group at ETH Zurich, they have used a DDA MS approach to identify proteins that co-purify with pathological TDP-43 in distinct disease subtypes. SRM assays to detect and quantify TDP43 have also been developed.

4. Monitoring of deregulated protein structures in PADs In PADs, proteins undergo aberrant conformational changes and aggregation events that lead to the generation of pathological protein structures. Detecting and quantifying non-pathological conformations and the aberrant structures in cells, tissues, and biological fluids would be of crucial importance to study the pathogenesis of PADs and may support early disease diagnosis and assessment of disease severity. One current hypothesis is that the levels of amyloidogenic proteins in biological fluids change only slightly in PADs but that these proteins undergo pronounced conformational transitions upon formation of pathological oligomeric and amyloid species. Therefore, a priority of our B/D PAD initiative is to attempt for the first time the development of proteomics assays for aberrant protein conformations. The idea relies on a recently published method involving MS and proteolytic markers that enables the analysis of protein structural changes on a proteome-wide scale.14,

67, 68

In this method, called LiP-MS (for limited proteolysis MS) proteins under native

conditions are exposed to a small amount of a broad-specificity protease for a limited amount of time. During this limited proteolysis step, proteolytic cleavage is restricted to the most flexible and proteaseaccessible regions and depends strongly on protein structure. The samples are then further denatured and trypsin digested to generate peptides amenable to bottom-up MS. Differences in protein structure will result in altered proteolytic patterns and different intensities of specific semi- and/or fully tryptic peptides. The Picotti group recently demonstrated that LiP-MS enables the analysis of subtle to large protein structural changes in a targeted or unbiased manner by systematically detecting proteins 23 ACS Paragon Plus Environment


undergoing structural alterations upon cellular perturbations, probing protein unfolding on a proteomewide scale,67 and detecting protein-small molecule interactions.68 Further, the group applied LiP-MS to analysis of amyloidogenic proteins involved in PADs and demonstrated that it enables to quantitatively probe and differentiate the monomeric (or healthy) and amyloid (or pathological) conformations of α-Syn directly in very complex biological samples.14 Peptides specific for a given protein conformation have been termed “conformotypic peptides” and serve as markers for detecting and quantifying the structural species of interest in a variety of samples. Proteomic assays based on SRM and DIA targeting α-Syn conformotypic peptides have been developed in the Picotti lab14 and have been applied to probing the structural states of α-Syn in cell extracts and proteome extracts from PD patient brains. Further efforts are underway focused on the application of the assay to biological fluids from patients and on the use of LiP-MS to identify conformotypic peptides for other aymloidogenic proteins.

Summary of assays developed and outlook In summary, the goal of the B/D PAD working group is to develop or improve proteomics tools to support basic and clinical research in the area of protein aggregation diseases. As the structure of amyloidogenic proteins is altered in PADs an objective of the PAD working group is to quantitatively resolve altered protein structures and protein aggregation states in complex biological and biomedical samples. To date, the B/D PAD working group has developed protein extraction protocols that simplify the processing of patient samples and improve the detection and quantification of proteins involved in systemic amyloidosis. Combining these isolation methods with targeted MS approaches to detect proteins specific to the different types of amyloidoses, we have established methods that support diagnosis and subtyping of systemic amyloidosis.


Page 24 of 40

Page 25 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Furthermore, we have developed diagnostic MS-based methods to support the measurement of the Aβ peptide and other proteins that are known to increase in abundance upon AD development in CSF samples16, 62-65 and to distinguish AD and DLB based on quantifying variable regions of IgGs.42 Our group has also addressed the detection of different proteoforms of proteins involved in amyloidoses, such as α-Syn, a protein involved in Parkinson’s disease, and apolipoprotein E, which is associated with late-onset AD.43 To detect aberrant structural states of amyloidogenic proteins, we developed an innovative approach to detect and quantify different types of protein structural alterations directly in complex biological samples such as patient specimens and showcased the power of this approach by the detection of amyloid aggregates of α-Syn.14 Finally, we generated LC-MS/MS-based protein expression data from brain tissues of patients with AD, ALS, and different types of systemic amyloidosis and corresponding healthy controls.69 These datasets will guide the generation of targeted proteomic assays for the remaining proteins from our target list (Table 1) and will support the identification of novel proteins involved in the development of these diseases. SRM or PRM assays are currently available for 14 proteins and proteoforms from our target protein list and LC-MS/MS data have been generated from clinical samples for an additional nine target proteins, resulting in the coverage of about half of the proteins known to be involved in PADs (Table 1). For the remaining proteins from our target list, MS coordinates have been generated by previous efforts through the measurements of large collections of synthetic peptides that are predicted to be the tryptic products of the proteins of interest. These coordinates are available through the proteomic repository SRMAtlas

70

, and further experimental evidence can be found in PeptideAtlas.51 These

repositories will constitute valuable starting points for the optimization of targeted proteomic assays. In the near future, the PAD working group will expand and optimize the generated assays and datasets and evaluate performance in analysis of clinical and biological samples. An important future focus will be on the adequate dissemination of these results. The primary and most effective way of sharing scientific results of the B/D PAD working group will be through publication in peer-reviewed scientific journals. At least 33 papers have been published that report on the efforts of members of the 25 ACS Paragon Plus Environment


PAD working group13,

14, 16, 18, 37, 42-44, 61, 63, 65, 67, 71-91

). To make the developed MS assays more

accessible to laboratories that are not part of the PAD working group, we are working on sharing the assay coordinates through public repositories and databases such as the SRMAtlas,70 the PeptideAtlas,51 and ProteomeTools.92 The group also aims to detail the developed methods in tutorial and protocol papers71, 93 to facilitate implementation by non-specialized laboratories. To promote the use of the generated tools in the relevant biological and clinical communities, members of our group also strive to attend and present at clinical conferences focused on protein aggregation diseases and biology-oriented meetings focused on protein quality control, protein misfolding, and proteostasis. For example, presentations describing the tools and the applications pioneered by members of the PAD working group have been given at the International Symposium on Amyloidosis (Uppsala, Sweden, 2016; Kumamoto, Japan, 2018), the Alzheimer's Association International Conference (Toronto, Canada, 2016; London, England, 2017), the International Conference on Alzheimer's and Parkinson's Diseases and Related Neurological Disorders (Nice, France, 2015; Vienna, Austria, 2017), and the EMBO Proteostasis meeting (Lisbon, Portugal, 2017). Moreover, our group recently connected with the European Amyloid Proteomics working group to mutually benefit due to the technical and clinical experience available in the two networks. We envision that assays developed by our group will be applicable also to the analysis of large (longitudinal) clinical cohorts and plan to soon explore the possibility of establishing connections with projects involving such cohorts. We believe that the increasing availability of dedicated tools to precisely measure proteins involved in PADs will positively influence research on the molecular bases of these diseases. Furthermore, in several studies we have demonstrated the potential of MS-based proteomics approaches for specific and sensitive clinical diagnoses. Use of MS-based proteomics will facilitate early disease diagnosis and a more confident subtyping. Having several clinicians actively involved in the PAD working group will dramatically facilitate the transfer of methods to the clinic, the eventual goal of our undertaking. Acknowledgements


Page 26 of 40

Page 27 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


PB, AM and PP gratefully acknowledge the European Union Seventh Framework Programme (FP7)– European Research Council (ERC) Starting Grant (FP7-ERC-StG-337965), a “Foerderungsprofessur” grant from the Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (PP00P3_159266 / 1) and the ETH Domain Strategic Focus Area Personalized Health and Related Technologies (PHRT-506).



References

(1) Westermark, P.; Benson, M. D.; Buxbaum, J. N.; Cohen, A. S.; Frangione, B.; Ikeda, S.-I.; Masters, C. L.; Merlini, G.; Saraiva, M. J.; Sipe, J. D., A primer of amyloid nomenclature. Amyloid 2007, 14, (3), 179-183. (2) Aguzzi, A.; O'Connor, T., Protein aggregation diseases: pathogenicity and therapeutic perspectives. Nat Rev Drug Discov 2010, 9, (3), 237-48. (3) Frost, B.; Diamond, M. I., Prion-like mechanisms in neurodegenerative diseases. Nat Rev Neurosci 2010, 11, (3), 155-9. (4) Braun, R. J.; Buttner, S.; Ring, J.; Kroemer, G.; Madeo, F., Nervous yeast: modeling neurotoxic cell death. Trends Biochem Sci 2010, 35, (3), 135-44. (5) Winklhofer, K. F.; Tatzelt, J.; Haass, C., The two faces of protein misfolding: gain- and loss-offunction in neurodegenerative diseases. Embo j 2008, 27, (2), 336-49. (6) Kayed, R.; Head, E.; Thompson, J. L.; McIntire, T. M.; Milton, S. C.; Cotman, C. W.; Glabe, C. G., Common structure of soluble amyloid oligomers implies common mechanism of pathogenesis. Science 2003, 300, (5618), 486-9. (7) Lashuel, H. A.; Hartley, D.; Petre, B. M.; Walz, T.; Lansbury, P. T., Jr., Neurodegenerative disease: amyloid pores from pathogenic mutations. Nature 2002, 418, (6895), 291. (8) Reynolds, N. P.; Soragni, A.; Rabe, M.; Verdes, D.; Liverani, E.; Handschin, S.; Riek, R.; Seeger, S., Mechanism of membrane interaction and disruption by alpha-synuclein. J Am Chem Soc 2011, 133, (48), 19366-75. (9) Alberti, S.; Halfmann, R.; King, O.; Kapila, A.; Lindquist, S., A systematic survey identifies prions and illuminates sequence features of prionogenic proteins. Cell 2009, 137, (1), 146-58. (10) Knowles, T. P.; Vendruscolo, M.; Dobson, C. M., The amyloid state and its association with protein misfolding diseases. Nat Rev Mol Cell Biol 2014, 15, (6), 384-96.


Page 28 of 40

Page 29 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(11) Sipe, J. D.; Benson, M. D.; Buxbaum, J. N.; Ikeda, S.-i.; Merlini, G.; Saraiva, M. J. M.; Westermark, P., Amyloid fibril proteins and amyloidosis: chemical identification and clinical classification International Society of Amyloidosis 2016 Nomenclature Guidelines. Amyloid 2016, 23, (4), 209-213. (12) MacPhee, C., Amyloid Formation. In Encyclopedia of Biophysics, Roberts, G. C. K., Ed. Springer Berlin Heidelberg: Berlin, Heidelberg, 2013; pp 67-75. (13) Welinder, C.; Jonsson, G. B.; Ingvar, C.; Lundgren, L.; Baldetorp, B.; Olsson, H.; Breslin, T.; Rezeli, M.; Jansson, B.; Fehniger, T. E.; Laurell, T.; Wieslander, E.; Pawlowski, K.; Marko-Varga, G., Analysis of alpha-synuclein in malignant melanoma - development of a SRM quantification assay. PLoS One 2014, 9, (10), e110804. (14) Feng, Y.; De Franceschi, G.; Kahraman, A.; Soste, M.; Melnik, A.; Boersema, P. J.; de Laureto, P. P.; Nikolaev, Y.; Oliveira, A. P.; Picotti, P., Global analysis of protein structural changes in complex proteomes. Nat Biotech 2014, 32, (10), 1036-1044. (15) Portelius, E.; Brinkmalm, G.; Tran, A. J.; Zetterberg, H.; Westman-Brinkmalm, A.; Blennow, K., Identification of Novel APP/Aβ Isoforms in Human Cerebrospinal Fluid. Neurodegenerative Diseases 2009, 6, (3), 87-94. (16) Leinenbach, A.; Pannee, J.; Dülffer, T.; Huber, A.; Bittner, T.; Andreasson, U.; Gobom, J.; Zetterberg, H.; Kobold, U.; Portelius, E.; Blennow, K., Mass Spectrometry–Based Candidate Reference Measurement Procedure for Quantification of Amyloid-β in Cerebrospinal Fluid. Clinical Chemistry 2014, 60, (7), 987. (17) Brambilla, F.; Lavatelli, F.; Di Silvestre, D.; Valentini, V.; Rossi, R.; Palladini, G.; Obici, L.; Verga, L.; Mauri, P.; Merlini, G., Reliable typing of systemic amyloidoses through proteomic analysis of subcutaneous adipose tissue. Blood 2012, 119, (8), 1844-7. (18) Nasr, S. H.; Dasari, S.; Hasadsri, L.; Theis, J. D.; Vrana, J. A.; Gertz, M. A.; Muppa, P.; Zimmermann, M. T.; Grogg, K. L.; Dispenzieri, A.; Sethi, S.; Highsmith, W. E.; Merlini, G.; Leung, N.; Kurtin, P. J., Novel Type of Renal Amyloidosis Derived from Apolipoprotein-CII. Journal of the American Society of Nephrology 2017, 28, (2), 439-445. 29 ACS Paragon Plus Environment


(19) D'Souza, A.; Theis, J. D.; Vrana, J. A.; Dogan, A., Pharmaceutical amyloidosis associated with subcutaneous insulin and enfuvirtide administration. Amyloid 2014, 21, (2), 71-5. (20) Hazenberg, B. P.; van, G., II; Bijzet, J.; Jager, P. L.; van Rijswijk, M. H., Diagnostic and therapeutic approach of systemic amyloidosis. Neth J Med 2004, 62, (4), 121-8. (21) Blennow, K.; Hampel, H.; Weiner, M.; Zetterberg, H., Cerebrospinal fluid and plasma biomarkers in Alzheimer disease. Nat Rev Neurol 2010, 6, (3), 131-44. (22) Dubois, B.; Feldman, H. H.; Jacova, C.; Hampel, H.; Molinuevo, J. L.; Blennow, K., Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol 2014, 13. (23) Humpel, C., Identifying and validating biomarkers for Alzheimer's disease. Trends Biotechnol 2011, 29, (1), 26-32. (24) Olsson, B.; Lautner, R.; Andreasson, U.; Ohrfelt, A.; Portelius, E.; Bjerke, M.; Holtta, M.; Rosen, C.; Olsson, C.; Strobel, G.; Wu, E.; Dakin, K.; Petzold, M.; Blennow, K.; Zetterberg, H., CSF and blood biomarkers for the diagnosis of Alzheimer's disease: a systematic review and meta-analysis. Lancet Neurol 2016, 15, (7), 673-684. (25) Backstrom, D. C.; Eriksson Domellof, M.; Linder, J.; Olsson, B.; Ohrfelt, A.; Trupp, M.; Zetterberg, H.; Blennow, K.; Forsgren, L., Cerebrospinal Fluid Patterns and the Risk of Future Dementia in Early, Incident Parkinson Disease. JAMA Neurol 2015, 72, (10), 1175-82. (26) Hall, S.; Surova, Y.; Ohrfelt, A.; Zetterberg, H.; Lindqvist, D.; Hansson, O., CSF biomarkers and clinical progression of Parkinson disease. Neurology 2015, 84, (1), 57-63. (27) Giacomelli, C.; Daniele, S.; Martini, C., Potential biomarkers and novel pharmacological targets in protein aggregation-related neurodegenerative diseases. Biochem Pharmacol 2017, 131, 1-15. (28) Nienhuis, H. L. A.; Bijzet, J.; Hazenberg, B. P. C., The Prevalence and Management of Systemic Amyloidosis in Western Countries. Kidney Diseases 2016, 2, (1), 10-19. (29) Aebersold, R.; Bader, G. D.; Edwards, A. M.; van Eyk, J. E.; Kussmann, M.; Qin, J.; Omenn, G. S., The Biology/Disease-driven Human Proteome Project (B/D-HPP): Enabling Protein Research for the Life Sciences Community. Journal of Proteome Research 2013, 12, (1), 23-27. 30 ACS Paragon Plus Environment

Page 30 of 40

Page 31 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(30) Aebersold, R.; Bader, G. D.; Edwards, A. M.; van Eyk, J.; Kussman, M.; Qin, J.; Omenn, G. S., Highlights of B/D-HPP and HPP Resource Pillar Workshops at 12th Annual HUPO World Congress of Proteomics. PROTEOMICS 2014, 14, (9), 975-988. (31) Sipe, J. D.; Benson, M. D.; Buxbaum, J. N.; Ikeda, S.-i.; Merlini, G.; Saraiva, M. J. M.; Westermark, P., Nomenclature 2014: Amyloid fibril proteins and clinical classification of the amyloidosis. Amyloid 2014, 21, (4), 221-224. (32) Stefani, M., Protein misfolding and aggregation: new examples in medicine and biology of the dark side of the protein world. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 2004, 1739, (1), 5-25. (33) Yu, K. H.; Lee, T. M.; Wang, C. S.; Chen, Y. J.; Re, C.; Kou, S. C.; Chiang, J. H.; Kohane, I. S.; Snyder, M., Systematic Protein Prioritization for Targeted Proteomics Studies through Literature Mining. J Proteome Res 2018, 17, (4), 1383-1396. (34) Bateman, R. J.; Siemers, E. R.; Mawuenyega, K. G.; Wen, G.; Browning, K. R.; Sigurdson, W. C.; Yarasheski, K. E.; Friedrich, S. W.; Demattos, R. B.; May, P. C.; Paul, S. M.; Holtzman, D. M., A gammasecretase inhibitor decreases amyloid-beta production in the central nervous system. Ann Neurol 2009, 66. (35) Beher, D.; Wrigley, J. D.; Owens, A. P.; Shearman, M. S., Generation of C-terminally truncated amyloid-beta peptides is dependent on gamma-secretase activity. J Neurochem 2002, 82. (36) Dovey, H. F.; John, V.; Anderson, J. P.; Chen, L. Z.; de Saint Andrieu, P.; Fang, L. Y.; Freedman, S. B.; Folmer, B.; Goldbach, E.; Holsztynska, E. J.; Hu, K. L.; Johnson-Wood, K. L.; Kennedy, S. L.; Kholodenko, D.; Knops, J. E.; Latimer, L. H.; Lee, M.; Liao, Z.; Lieberburg, I. M.; Motter, R. N.; Mutter, L. C.; Nietz, J.; Quinn, K. P.; Sacchi, K. L.; Seubert, P. A.; Shopp, G. M.; Thorsett, E. D.; Tung, J. S.; Wu, J.; Yang, S., Functional gamma-secretase inhibitors reduce beta-amyloid peptide levels in brain. J Neurochem 2001, 76. (37) Holtta, M.; Dean, R. A.; Siemers, E.; Mawuenyega, K. G.; Sigurdson, W.; May, P. C.; Holtzman, D. M.; Portelius, E.; Zetterberg, H.; Bateman, R. J.; Blennow, K.; Gobom, J., A single dose of the gamma31 ACS Paragon Plus Environment


secretase inhibitor semagacestat alters the cerebrospinal fluid peptidome in humans. Alzheimers Res Ther 2016, 8, (1), 11. (38) Lavatelli, F.; Vrana, J. A., Proteomic typing of amyloid deposits in systemic amyloidoses. Amyloid 2011, 18, (4), 177-82. (39) Vrana, J. A.; Gamez, J. D.; Madden, B. J.; Theis, J. D.; Bergen, H. R.; Dogan, A., Classification of amyloidosis by laser microdissection and mass spectrometry–based proteomic analysis in clinical biopsy specimens. Blood 2009, 114, (24), 4957. (40) Brinkmalm, G.; Portelius, E.; Ohrfelt, A.; Mattsson, N.; Persson, R.; Gustavsson, M. K.; Vite, C. H.; Gobom, J.; Mansson, J. E.; Nilsson, J.; Halim, A.; Larson, G.; Ruetschi, U.; Zetterberg, H.; Blennow, K.; Brinkmalm, A., An online nano-LC-ESI-FTICR-MS method for comprehensive characterization of endogenous fragments from amyloid beta and amyloid precursor protein in human and cat cerebrospinal fluid. J Mass Spectrom 2012, 47. (41) Portelius, E.; Tran, A. J.; Andreasson, U.; Persson, R.; Brinkmalm, G.; Zetterberg, H.; Blennow, K.; Westman-Brinkmalm, A., Characterization of Amyloid β Peptides in Cerebrospinal Fluid by an Automated Immunoprecipitation Procedure Followed by Mass Spectrometry. Journal of Proteome Research 2007, 6, (11), 4433-4439. (42) Lundström, S. L.; Zhang, B.; Rutishauser, D.; Aarsland, D.; Zubarev, R. A., SpotLight Proteomics: uncovering the hidden blood proteome improves diagnostic power of proteomics. Scientific Reports 2017, 7, 41929. (43) Rezeli, M.; Zetterberg, H.; Blennow, K.; Brinkmalm, A.; Laurell, T.; Hansson, O.; Marko-Varga, G., Quantification of total apolipoprotein E and its specific isoforms in cerebrospinal fluid and blood in Alzheimer’s disease and other neurodegenerative diseases. EuPA Open Proteomics 2015, 8, 137-143. (44) Kvartsberg, H.; Portelius, E.; Andreasson, U.; Brinkmalm, G.; Hellwig, K.; Lelental, N.; Kornhuber, J.; Hansson, O.; Minthon, L.; Spitzer, P.; Maler, J. M.; Zetterberg, H.; Blennow, K.; Lewczuk, P., Characterization of the postsynaptic protein neurogranin in paired cerebrospinal fluid and plasma


Page 32 of 40

Page 33 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


samples from Alzheimer’s disease patients and healthy controls. Alzheimer's Research & Therapy 2015, 7, (1), 40. (45) Hayate, J.; Mohammad Amjad, K.; Shreesh, O., An Overview on the Role of α -Synuclein in Experimental Models of Parkinson’s Disease from Pathogenesis to Therapeutics. CNS & Neurological Disorders - Drug Targets 2016, 15, (10), 1240-1252. (46) Lina, J.; Xi, Z.; Weijie, L.; Qing, Z.; Zichun, H., Intracellular Aβ and its Pathological Role in Alzheimer’s Disease: Lessons from Cellular to Animal Models. Current Alzheimer Research 2016, 13, (6), 621-630. (47) Picotti, P.; Aebersold, R., Selected reaction monitoring–based proteomics: workflows, potential, pitfalls and future directions. Nature Methods 2012, 9, 555. (48) Gillet, L. C.; Navarro, P.; Tate, S.; Röst, H.; Selevsek, N.; Reiter, L.; Bonner, R.; Aebersold, R., Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis. Molecular & Cellular Proteomics 2012, 11, (6). (49) Vizcaino, J. A.; Deutsch, E. W.; Wang, R.; Csordas, A.; Reisinger, F.; Rios, D.; Dianes, J. A.; Sun, Z.; Farrah, T.; Bandeira, N.; Binz, P. A.; Xenarios, I.; Eisenacher, M.; Mayer, G.; Gatto, L.; Campos, A.; Chalkley, R. J.; Kraus, H. J.; Albar, J. P.; Martinez-Bartolome, S.; Apweiler, R.; Omenn, G. S.; Martens, L.; Jones, A. R.; Hermjakob, H., ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat Biotechnol 2014, 32, (3), 223-6. (50) Farrah, T.; Deutsch, E. W.; Kreisberg, R.; Sun, Z.; Campbell, D. S.; Mendoza, L.; Kusebauch, U.; Brusniak, M. Y.; Huttenhain, R.; Schiess, R.; Selevsek, N.; Aebersold, R.; Moritz, R. L., PASSEL: the PeptideAtlas SRMexperiment library. Proteomics 2012, 12, (8), 1170-5. (51) Desiere, F.; Deutsch, E. W.; King, N. L.; Nesvizhskii, A. I.; Mallick, P.; Eng, J.; Chen, S.; Eddes, J.; Loevenich, S. N.; Aebersold, R., The PeptideAtlas project. Nucleic Acids Res 2006, 34, (Database issue), D655-8.



(52) Picken, M. M., Proteomics and mass spectrometry in the diagnosis of renal amyloidosis. Clin Kidney J 2015, 8, (6), 665-72. (53) Mollee, P.; Boros, S.; Loo, D.; Ruelcke, J. E.; Lakis, V. A.; Cao, K.-A. L.; Renaut, P.; Hill, M. M., Implementation and evaluation of amyloidosis subtyping by laser-capture microdissection and tandem mass spectrometry. Clinical Proteomics 2016, 13, 30. (54) Sethi, S.; Vrana, J. A.; Theis, J. D.; Leung, N.; Sethi, A.; Nasr, S. H.; Fervenza, F. C.; Cornell, L. D.; Fidler, M. E.; Dogan, A., Laser microdissection and mass spectrometry–based proteomics aids the diagnosis and typing of renal amyloidosis. Kidney International 2012, 82, (2), 226-234. (55) Han, S. H.; Einstein, G.; Weisgraber, K. H.; Strittmatter, W. J.; Saunders, A. M.; Pericak-Vance, M.; Roses, A. D.; Schmechel, D. E., Apolipoprotein E is localized to the cytoplasm of human cortical neurons: a light and electron microscopic study. J Neuropathol Exp Neurol 1994, 53, (5), 535-44. (56) Aoki, K.; Uchihara, T.; Sanjo, N.; Nakamura, A.; Ikeda, K.; Tsuchiya, K.; Wakayama, Y., Increased expression of neuronal apolipoprotein E in human brain with cerebral infarction. Stroke 2003, 34, (4), 875-80. (57) Xu, P. T.; Gilbert, J. R.; Qiu, H. L.; Ervin, J.; Rothrock-Christian, T. R.; Hulette, C.; Schmechel, D. E., Specific regional transcription of apolipoprotein E in human brain neurons. Am J Pathol 1999, 154, (2), 601-11. (58) Xu, Q.; Bernardo, A.; Walker, D.; Kanegawa, T.; Mahley, R. W.; Huang, Y., Profile and regulation of apolipoprotein E (ApoE) expression in the CNS in mice with targeting of green fluorescent protein gene to the ApoE locus. J Neurosci 2006, 26, (19), 4985-94. (59) Walker, Z.; Possin, K. L.; Boeve, B. F.; Aarsland, D., Lewy body dementias. Lancet 2015, 386, (10004), 1683-97. (60) Coric, V.; van Dyck, C. H.; Salloway, S.; et al., Safety and tolerability of the γ-secretase inhibitor avagacestat in a phase 2 study of mild to moderate alzheimer disease. Archives of Neurology 2012, 69, (11), 1430-1440.


Page 34 of 40

Page 35 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(61) Portelius, E.; Dean, R. A.; Andreasson, U.; Mattsson, N.; Westerlund, A.; Olsson, M.; Demattos, R. B.; Racke, M. M.; Zetterberg, H.; May, P. C.; Blennow, K., β-site amyloid precursor protein-cleaving enzyme 1(BACE1) inhibitor treatment induces Aβ5-X peptides through alternative amyloid precursor protein cleavage. Alzheimer's Research & Therapy 2014, 6, (9-9), 75. (62) Portelius, E.; Dean, R. A.; Gustavsson, M. K.; Andreasson, U.; Zetterberg, H.; Siemers, E.; Blennow, K., A novel Aβ isoform pattern in CSF reflects γ-secretase inhibition in Alzheimer disease. Alzheimer's Research & Therapy 2010, 2, (2), 7-7. (63) Kvartsberg, H.; Duits, F. H.; Ingelsson, M.; Andreasen, N.; Ohrfelt, A.; Andersson, K., Cerebrospinal fluid levels of the synaptic protein neurogranin correlates with cognitive decline in prodromal Alzheimer’s disease. Alzheimers Dement 2015, 11, (10), 1180-90. (64) Brinkmalm, A.; Brinkmalm, G.; Honer, W. G.; Frolich, L.; Hausner, L.; Minthon, L., SNAP-25 is a promising novel cerebrospinal fluid biomarker for synapse degeneration in Alzheimer’s disease. Mol Neurodegener 2014, 9, 53. (65) Öhrfelt, A.; Brinkmalm, A.; Dumurgier, J.; Brinkmalm, G.; Hansson, O.; Zetterberg, H.; BouazizAmar, E.; Hugon, J.; Paquet, C.; Blennow, K., The pre-synaptic vesicle protein synaptotagmin is a novel biomarker for Alzheimer’s disease. Alzheimer's Research & Therapy 2016, 8, 41. (66) Afroz, T.; Hock, E. M.; Ernst, P.; Foglieni, C.; Jambeau, M.; Gilhespy, L. A. B.; Laferriere, F.; Maniecka, Z.; Pluckthun, A.; Mittl, P.; Paganetti, P.; Allain, F. H. T.; Polymenidou, M., Functional and dynamic polymerization of the ALS-linked protein TDP-43 antagonizes its pathologic aggregation. Nat Commun 2017, 8, (1), 45. (67) Leuenberger, P.; Ganscha, S.; Kahraman, A.; Cappelletti, V.; Boersema, P. J.; von Mering, C.; Claassen, M.; Picotti, P., Cell-wide analysis of protein thermal unfolding reveals determinants of thermostability. Science 2017, 355, (6327). (68) Piazza, I.; Kochanowski, K.; Cappelletti, V.; Fuhrer, T.; Noor, E.; Sauer, U.; Picotti, P., A Map of Protein-Metabolite Interactions Reveals Principles of Chemical Communication. Cell 2018, 172, (1-2), 358-372.e23. 35 ACS Paragon Plus Environment


(69) Brambilla, F.; Lavatelli, F.; Merlini, G.; Mauri, P., Clinical proteomics for diagnosis and typing of systemic amyloidoses. Proteomics Clin Appl 2013, 7, (1-2), 136-43. (70) Kusebauch, U.; Campbell, D. S.; Deutsch, E. W.; Chu, C. S.; Spicer, D. A.; Brusniak, M. Y.; Slagel, J.; Sun, Z.; Stevens, J.; Grimes, B.; Shteynberg, D.; Hoopmann, M. R.; Blattmann, P.; Ratushny, A. V.; Rinner, O.; Picotti, P.; Carapito, C.; Huang, C. Y.; Kapousouz, M.; Lam, H.; Tran, T.; Demir, E.; Aitchison, J. D.; Sander, C.; Hood, L.; Aebersold, R.; Moritz, R. L., Human SRMAtlas: A Resource of Targeted Assays to Quantify the Complete Human Proteome. Cell 2016, 166, (3), 766-778. (71) Schopper, S.; Kahraman, A.; Leuenberger, P.; Feng, Y.; Piazza, I.; Müller, O.; Boersema, P. J.; Picotti, P., Measuring protein structural changes on a proteome-wide scale using limited proteolysiscoupled mass spectrometry. Nature Protocols 2017, 12, 2391. (72) Brownjohn, P. W.; Smith, J.; Portelius, E.; Serneels, L.; Kvartsberg, H.; De Strooper, B.; Blennow, K.; Zetterberg, H.; Livesey, F. J., Phenotypic Screening Identifies Modulators of Amyloid Precursor Protein Processing in Human Stem Cell Models of Alzheimer's Disease. Stem Cell Reports 2017, 8, (4), 870-882. (73) Hansson, K. T.; Skillback, T.; Pernevik, E.; Kern, S.; Portelius, E.; Hoglund, K.; Brinkmalm, G.; Holmen-Larsson, J.; Blennow, K.; Zetterberg, H.; Gobom, J., Expanding the cerebrospinal fluid endopeptidome. Proteomics 2017, 17, (5). (74) Portelius, E.; Mattsson, N.; Pannee, J.; Zetterberg, H.; Gisslen, M.; Vanderstichele, H.; Gkanatsiou, E.; Crespi, G. A.; Parker, M. W.; Miles, L. A.; Gobom, J.; Blennow, K., Ex vivo (18)Olabeling mass spectrometry identifies a peripheral amyloid beta clearance pathway. Mol Neurodegener 2017, 12, (1), 18. (75) Pannee, J.; Blennow, K.; Zetterberg, H.; Portelius, E., Absolute Quantification of Abeta1-42 in CSF Using a Mass Spectrometric Reference Measurement Procedure. J Vis Exp 2017, (121). (76) Steen Jensen, C.; Portelius, E.; Siersma, V.; Hogh, P.; Wermuth, L.; Blennow, K.; Zetterberg, H.; Waldemar, G.; Gregers Hasselbalch, S.; Hviid Simonsen, A., Cerebrospinal Fluid Amyloid Beta and Tau


Page 36 of 40

Page 37 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Concentrations Are Not Modulated by 16 Weeks of Moderate- to High-Intensity Physical Exercise in Patients with Alzheimer Disease. Dement Geriatr Cogn Disord 2016, 42, (3-4), 146-158. (77) Bergstrom, P.; Agholme, L.; Nazir, F. H.; Satir, T. M.; Toombs, J.; Wellington, H.; Strandberg, J.; Bontell, T. O.; Kvartsberg, H.; Holmstrom, M.; Borestrom, C.; Simonsson, S.; Kunath, T.; Lindahl, A.; Blennow, K.; Hanse, E.; Portelius, E.; Wray, S.; Zetterberg, H., Amyloid precursor protein expression and processing are differentially regulated during cortical neuron differentiation. Sci Rep 2016, 6, 29200. (78) Pannee, J.; Portelius, E.; Minthon, L.; Gobom, J.; Andreasson, U.; Zetterberg, H.; Hansson, O.; Blennow, K., Reference measurement procedure for CSF amyloid beta (Abeta)1-42 and the CSF Abeta1-42 /Abeta1-40 ratio - a cross-validation study against amyloid PET. J Neurochem 2016, 139, (4), 651-658. (79) Portelius, E.; Durieu, E.; Bodin, M.; Cam, M.; Pannee, J.; Leuxe, C.; Mabondzo, A.; Oumata, N.; Galons, H.; Lee, J. Y.; Chang, Y. T.; Stupsilonber, K.; Koch, P.; Fontaine, G.; Potier, M. C.; Manousopoulou, A.; Garbis, S. D.; Covaci, A.; Van Dam, D.; De Deyn, P.; Karg, F.; Flajolet, M.; Omori, C.; Hata, S.; Suzuki, T.; Blennow, K.; Zetterberg, H.; Meijer, L., Specific Triazine Herbicides Induce Amyloid-beta42 Production. J Alzheimers Dis 2016, 54, (4), 1593-1605. (80) Leuzy, A.; Chiotis, K.; Hasselbalch, S. G.; Rinne, J. O.; de Mendonca, A.; Otto, M.; Lleo, A.; Castelo-Branco, M.; Santana, I.; Johansson, J.; Anderl-Straub, S.; von Arnim, C. A.; Beer, A.; Blesa, R.; Fortea, J.; Herukka, S. K.; Portelius, E.; Pannee, J.; Zetterberg, H.; Blennow, K.; Nordberg, A., Pittsburgh compound B imaging and cerebrospinal fluid amyloid-beta in a multicentre European memory clinic study. Brain 2016, 139, (Pt 9), 2540-53. (81) Sjodin, S.; Andersson, K. K.; Mercken, M.; Zetterberg, H.; Borghys, H.; Blennow, K.; Portelius, E., APLP1 as a cerebrospinal fluid biomarker for gamma-secretase modulator treatment. Alzheimers Res Ther 2015, 7, (1), 77. (82) Pannee, J.; Gobom, J.; Shaw, L. M.; Korecka, M.; Chambers, E. E.; Lame, M.; Jenkins, R.; Mylott, W.; Carrillo, M. C.; Zegers, I.; Zetterberg, H.; Blennow, K.; Portelius, E., Round robin test on 37 ACS Paragon Plus Environment


quantification of amyloid-beta 1-42 in cerebrospinal fluid by mass spectrometry. Alzheimers Dement 2016, 12, (1), 55-9. (83) Mc Donald, J. M.; O'Malley, T. T.; Liu, W.; Mably, A. J.; Brinkmalm, G.; Portelius, E.; Wittbold, W. M., 3rd; Frosch, M. P.; Walsh, D. M., The aqueous phase of Alzheimer's disease brain contains assemblies built from approximately 4 and approximately 7 kDa Abeta species. Alzheimers Dement 2015, 11, (11), 1286-305. (84) Cummings, D. M.; Liu, W.; Portelius, E.; Bayram, S.; Yasvoina, M.; Ho, S. H.; Smits, H.; Ali, S. S.; Steinberg, R.; Pegasiou, C. M.; James, O. T.; Matarin, M.; Richardson, J. C.; Zetterberg, H.; Blennow, K.; Hardy, J. A.; Salih, D. A.; Edwards, F. A., First effects of rising amyloid-beta in transgenic mouse brain: synaptic transmission and gene expression. Brain 2015, 138, (Pt 7), 1992-2004. (85) Moore, S.; Evans, L. D.; Andersson, T.; Portelius, E.; Smith, J.; Dias, T. B.; Saurat, N.; McGlade, A.; Kirwan, P.; Blennow, K.; Hardy, J.; Zetterberg, H.; Livesey, F. J., APP metabolism regulates tau proteostasis in human cerebral cortex neurons. Cell Rep 2015, 11, (5), 689-96. (86) Portelius, E.; Lashley, T.; Westerlund, A.; Persson, R.; Fox, N. C.; Blennow, K.; Revesz, T.; Zetterberg, H., Brain amyloid-beta fragment signatures in pathological ageing and Alzheimer's disease by hybrid immunoprecipitation mass spectrometry. Neurodegener Dis 2015, 15, (1), 50-7. (87) Fritschi, S. K.; Langer, F.; Kaeser, S. A.; Maia, L. F.; Portelius, E.; Pinotsi, D.; Kaminski, C. F.; Winkler, D. T.; Maetzler, W.; Keyvani, K.; Spitzer, P.; Wiltfang, J.; Kaminski Schierle, G. S.; Zetterberg, H.; Staufenbiel, M.; Jucker, M., Highly potent soluble amyloid-beta seeds in human Alzheimer brain but not cerebrospinal fluid. Brain 2014, 137, (Pt 11), 2909-2915. (88) Portelius, E.; Holtta, M.; Soininen, H.; Bjerke, M.; Zetterberg, H.; Westerlund, A.; Herukka, S. K.; Blennow, K.; Mattsson, N., Altered cerebrospinal fluid levels of amyloid beta and amyloid precursorlike protein 1 peptides in Down's syndrome. Neuromolecular Med 2014, 16, (2), 510-6. (89) Pannee, J.; Tornqvist, U.; Westerlund, A.; Ingelsson, M.; Lannfelt, L.; Brinkmalm, G.; Persson, R.; Gobom, J.; Svensson, J.; Johansson, P.; Zetterberg, H.; Blennow, K.; Portelius, E., The amyloid-beta


Page 38 of 40

Page 39 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


degradation pattern in plasma--a possible tool for clinical trials in Alzheimer's disease. Neurosci Lett 2014, 573, 7-12. (90) Martinez-Morillo, E.; Nielsen, H. M.; Batruch, I.; Drabovich, A. P.; Begcevic, I.; Lopez, M. F.; Minthon, L.; Bu, G.; Mattsson, N.; Portelius, E.; Hansson, O.; Diamandis, E. P., Assessment of peptide chemical modifications on the development of an accurate and precise multiplex selected reaction monitoring assay for apolipoprotein e isoforms. J Proteome Res 2014, 13, (2), 1077-87. (91) Portelius, E.; Appelkvist, P.; Stromberg, K.; Hoglund, K., Characterization of the effect of a novel gamma-secretase modulator on Abeta: a clinically translatable model. Curr Pharm Des 2014, 20, (15), 2484-90. (92) Zolg, D. P.; Wilhelm, M.; Schnatbaum, K.; Zerweck, J.; Knaute, T.; Delanghe, B.; Bailey, D. J.; Gessulat, S.; Ehrlich, H. C.; Weininger, M.; Yu, P.; Schlegl, J.; Kramer, K.; Schmidt, T.; Kusebauch, U.; Deutsch, E. W.; Aebersold, R.; Moritz, R. L.; Wenschuh, H.; Moehring, T.; Aiche, S.; Huhmer, A.; Reimer, U.; Kuster, B., Building ProteomeTools based on a complete synthetic human proteome. Nat Methods 2017, 14, (3), 259-262. (93) Feng, Y.; Picotti, P., Selected Reaction Monitoring to Measure Proteins of Interest in Complex Samples: A Practical Guide. In Proteomics in Systems Biology: Methods and Protocols, Reinders, J., Ed. Springer New York: New York, NY, 2016; pp 43-56.



For TOC only


Page 40 of 40

Disease-Driven Initiative on Protein-Aggregation Diseases of

Recommend Documents