Raman spectroscopy to diagnose Alzheimer's disease and dementia

Jun 4, 2018 - Accurate identification of Alzheimer's disease (AD) is still of major clinical ... of AD from dementia with Lewy bodies (DLB), as many c...
0 downloads 0 Views 1MB Size
Subscriber access provided by Kaohsiung Medical University

Article

Raman spectroscopy to diagnose Alzheimer’s disease and dementia with Lewy bodies in blood Maria Paraskevaidi, Camilo L. M. Morais, Diane E. Halliwell, David M. A. Mann, David Allsop, Pierre L Martin-Hirsch, and Francis Luke Martin ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.8b00198 • Publication Date (Web): 04 Jun 2018 Downloaded from http://pubs.acs.org on June 7, 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 29 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

ACS Chemical Neuroscience

1

Raman spectroscopy to diagnose Alzheimer’s disease and

2

dementia with Lewy bodies in blood

3

Maria Paraskevaidia,*, Camilo L. M. Moraisa, Diane E. Halliwella, David M. A. Mannb, David

4

Allsopc, Pierre L. Martin-Hirschd and Francis L. Martina,*

5

a

6

PR1 2HE, UK

7

b

8

University of Manchester, Greater Manchester Neurosciences Centre, Salford Royal Hospital,

9

Salford M6 8HD, UK

School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston

Division of Neuroscience and Experimental Psychology, School of Biological Sciences,

10

c

11

University, Lancaster LA1 4YQ, UK

12

d

13

Foundation Trust, Preston PR2 9HT, UK

Division of Biomedical and Life Sciences, Faculty of Health and Medicine, Lancaster

Department of Obstetrics and Gynaecology, Central Lancashire Teaching Hospitals NHS

14 15 16 17 18 19 20 21 22 23 24 25 26

*

27

[email protected]

To

whom

correspondence

should

be

addressed:

[email protected]

1 ACS Paragon Plus Environment

or

ACS Chemical Neuroscience 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 2 of 29

28 29

Abstract

30

Accurate identification of Alzheimer’s disease (AD) is still of major clinical importance

31

considering the current lack of non-invasive and low-cost diagnostic approaches. Detection of

32

early-stage AD is particularly desirable as it would allow early intervention and/or

33

recruitment of patients into clinical trials. There is also an unmet need for discrimination of

34

AD from dementia with Lewy bodies (DLB), as many cases of the latter are misdiagnosed as

35

AD. Biomarkers based on a simple blood test would be useful in research and clinical

36

practice. Raman spectroscopy has been implemented to analyse blood plasma of a cohort that

37

consisted of early-stage AD, late-stage AD, DLB and healthy controls. Classification

38

algorithms achieved high accuracy for the different groups: early-stage AD vs healthy with

39

84% sensitivity, 86% specificity; late-stage AD vs healthy with 84% sensitivity, 77%

40

specificity; DLB vs healthy with 83% sensitivity, 87% specificity; early-stage AD vs DLB

41

with 81% sensitivity, 88% specificity; late-stage AD vs DLB with 90% sensitivity, 93%

42

specificity; and lastly, early-stage AD vs late-stage AD 66% sensitivity and 83% specificity.

43

G-score values were also estimated between 74-91%, demonstrating that the overall

44

performance of the classification model was satisfactory. The wavenumbers responsible for

45

differentiation were assigned to important biomolecules which can serve as a panel of

46

biomarkers.

47

neurodegeneration in dementias.

These

results

suggest

a

cost-effective,

blood-based

biomarker

for

48 49 50 51

Keywords: Alzheimer’s disease; Dementia with Lewy bodies; Raman spectroscopy; blood

52

plasma; biomarkers 2 ACS Paragon Plus Environment

Page 3 of 29 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

ACS Chemical Neuroscience

53

Introduction

54

Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) constitute the two

55

most common causes of dementia. AD and DLB can share common symptoms and clinical

56

characteristics, which can lead to misdiagnosis. A clear distinction between these two causes

57

of dementia is necessary in terms of pharmacological treatment and outcome evaluation

58

The neuropathological hallmarks of AD include senile plaques (containing accumulated

59

amyloid-beta (Aβ) peptide) and neurofibrillary tangles (composed of hyperphosphorylated

60

tau protein), while in DLB the hallmark pathology is the abnormal aggregation of α-synuclein

61

into Lewy bodies and Lewy neurites

62

pathological features in very early stages (i.e., prodromal disease), or even before symptoms

63

occur (i.e., pre-clinical disease), would allow an earlier intervention before irreversible

64

neuronal death occurs, as well as facilitating early recruitment into clinical trials.

1, 2

.

3, 4

. The ability to index the presence of these

65

Accurate detection of dementia is essential for improving the lives of those affected.

66

Current diagnostic approaches employ neuroimaging techniques, such as magnetic resonance

67

imaging (MRI) and positron emission tomography (PET) scans (amyloid-PET and more

68

recently tau-PET), or cerebrospinal fluid (CSF) biomarkers, but these methods have many

69

limitations

70

memory and psychological tests is often required for diagnosis, but not all pathologically

71

similar cases will present with the same “clinical phenotype”; many studies have shown

72

contradictory results regarding the suitability of these biomarkers for accurate diagnosis.

73

Recently, blood biomarkers have emerged as a potential means to test for neurodegenerative

74

diseases, with some being capable of detecting early-stage disease

75

the use of blood samples is based on the daily release of 500 ml CSF into the bloodstream,

76

which potentially renders blood a rich source of brain biomarkers 12.

5-8

. A combination of family and clinical history, as well as a series of different

3 ACS Paragon Plus Environment

9-11

. The rationale behind

ACS Chemical Neuroscience 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

77

Raman is a spectroscopic technique that extracts biological information by applying a

78

monochromatic, laser light onto the sample under interrogation; electrons are thus excited to

79

virtual energy levels. When these electrons return to the original energy level, in the form of a

80

photon, there is no energy shift (known as elastic or Rayleigh scattering), whereas when they

81

return to a lower or a higher energy level there is a gain or loss of energy, respectively

82

(known as inelastic or Raman scattering) 13. The shift in the energy allows the generation of a

83

spectrum which is indicative of the chemical bonds present in the sample. The characteristic

84

spectra that are derived from Raman spectroscopy, represent a number of different

85

biomolecules within a sample (e.g., proteins, carbohydrates, lipids, DNA) 14. Recent studies

86

have employed Raman spectroscopy to study different diseases, such as malaria, oral and

87

colorectal cancer, in biological fluids 15-17.

88

The aim of the present study was to diagnose patients with Alzheimer’s disease, in

89

early and late disease stages, and patients with DLB, as well as to discriminate between AD

90

and DLB. To achieve this, blood plasma was analysed with Raman spectroscopy as a

91

minimally invasive procedure that would also allow repeated measurements for follow-up of

92

individuals.

93

Results

94

We enrolled 56 individuals into this study who were classified into 4 groups; early

95

stage AD (n=11; age range: 50-74 years), late stage AD (n=15; age range: 50-79 years), DLB

96

(n=15; age range: 23-73 years) and healthy controls (n=15; age range: 23-73 years) (Table 1).

97

Early and late-stage AD was defined according to the duration of illness, from designated age

98

at onset up to age at sample collection. P-values were calculated based on age and statistical

99

differences were detected only for the following two subgroup comparisons: Late AD vs

100

Healthy (P=0.004) and DLB vs Healthy (P 0.005) (Supplementary Table 1). Even

103

though there was age difference between the controls and AD individuals, no correlation was

104

observed between age and AD spectra after using partial least squares regression (R2 = 0.107,

105

2 latent variables with 99.93% cumulative explained variance) and no statistical difference

106

was observed in the spectra of AD patients with age lower and higher than 54 years of age

107

(average control age) with a 95% confidence level (P> 0.005). This indicates that age did not

108

affect the spectral distribution within the AD class. Similarly, no statistical differences were

109

observed in the Raman spectra of the different groups due to gender (male vs female)

110

(Supplementary Fig. 8).

111

Early stage AD vs healthy individuals.

112

principal component analysis followed by linear discriminant analysis (PCA-LDA) was

113

applied to the derived dataset. A one-dimensional (1D) scores plot was generated to account

114

for differences and similarities between early stage AD and healthy subjects (Fig. 1A); after

115

statistical analysis, the two classes showed significant differences (P