Elevated neurofilament light chain in plasma is associated with reduced right hippocampal and amygdala volume in Alzheimer's patients

doi:10.21203/rs.3.rs-18579/v1

PDF

Research

Elevated neurofilament light chain in plasma is associated with reduced right hippocampal and amygdala volume in Alzheimer's patients

https://doi.org/10.21203/rs.3.rs-18579/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted 23 Mar, 2020

You are reading this latest preprint version

Background

Plasma neurofilament light (NfL) levels have been considered as an especially promising biomarker for dementia, however, the mechanism of NfL regulating cognition is not very clear.

Methods

43 amnesic mild cognitive impairment(aMCI), 35 Alzheimer’s disease (AD) and 30 cognitively normal subjects were recruited. Plasma NfL levels were examined by the Single Molecule array (Simoa) technique; the volumes of the hippocampus and amygdala were calculated and compared by T1-weighted MRI; and cognitive function was assessed by the Beijing version of the Montreal Cognitive Assessment (MoCA)

Results

Our results showed significantly increased plasma NfL levels in AD group (29.42 pg/ml) compared to aMCI(15.92 pg/ml) group and normal (12.85 pg/ml) group (both p < 0.001), while there was no statistical difference (p>0.05) between aMCI group and normal group. And the results of partial correlation analysis showed that plasma NfL levels were negatively correlated (p<0.05)with MoCA total score (r=-0.415, p=0.013), right hippocampal volume(r=-0.335,p=0.036) and right amygdala volume(r=-0.337, p=0.048).

Conclusions

NfL in plasma of AD patients is significantly increased, and the protein is related to atrophy of right hippocampus and right amygdala.

Cognitive Neuroscience

NfL

aMCI

hippocampal

amygdala

Neurofilament light chain (NfL) plays an important role in axon transmission and function maintenance, and is the most abundant intermediate filament protein in myelinated subcortical axons ¹. Previous studies pointed that NFL is an ideal marker of large-caliber axonal degeneration, and increased NfL levels incerebrospinal fluid(CSF) are like to reflect neurodegeneration-related axonal injury², such as Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), multiple sclerosis and amyotrophic lateral sclerosis ^3,4. In addition, CSF NfL levels have also been proved to be an effective way to distingusih FTLD from early-onset AD given that NfL levels in AD are lower in early onset compared to those in late onset presentations^5,6. However, NfL in cerebrospinal fluid is not applicable and difficult to accept for many elderly people, Therefore, blood-based measurement of NfL might be more desirable, since the collection of blood sample is relatively less invasive and more applicable⁷.

So far, there have been a few studies on NfL expression patterns in the blood of AD patients in China. For example, Liu S ⁸et al found that gastric cancer subjects expressed lower plasma NfL levels but AD subjects expressed higher plasma NfL levels than normal controls. Hu H⁹ et al found that plasma NfL concentration and its rate of change had already increased abnormally in the preclinical phase of AD. And Lin YS¹⁰ et al also found that plasma NfL was significantly increased in the AD group, compared with the control, mild cognitive impairment (MCI), non-demented Parkinson's disease (PD), and Parkinson's disease dementia groups. These conclusions suggest NFL in plasma may represent a biomarker of cognitive decline in AD, and it is possible to mark the onset of neurodegeneration in subjects at risk for AD familial disease¹. However, the mechanism of NfL regulating cognition is not very clear.

Neuroimaging using Magnetic Resonance Imaging (MRI) has been widely used to describe the atrophy pattern of cognitive related brain regions in AD and FTLD as well as to find differential trajectories along the different disease stages^11–13. And structural MRI of medial temporal atrophy (MTA) is considered to be a biomarker for an early diagnosis of MCI and AD^14,15, specifically speaking, volume reduction of medial temporal lobe, including amygdala and hippocampus has been proved to be an early manifestation of AD¹⁶. The relationship between classical AD biochemical markers AD and neuroimaging features and their reciprocal influence have been studied during both the preclinical phases and clinical of the disease³. For example,Mattsson N¹⁷ et al pointed out that high plasma NfL levels in the MCI and AD cohort were associated with smaller hippocampal volumes, thinner cortices and larger ventricular. However, it is not known whether the above conclusions are applicable to Chinese people.

Therefore, in this context, our goals were (a) to provide a descriptive analysis of plasma NfL levels and structural patterns (amygdala volume and hippocampal volume) in early-onset AD, amnestic mild cognitive impairment (aMCI) and normal control(NC); (b) to study the relationship between early‐onset AD, aMCI and NC brain structural measures/cognitive function and plasma NfL levels.

2.1 Data base

Data were obtained from the China Longitudinal Aging Study (CLAS)¹⁸ database, which was launched in 2013 as a large scale longitudinal cohort study in China and was led by principal investigator Shifu Xiao, MD and PhD. The CLAS participants were recruited from 20 target communities (ie, 2 rural and 18 urban) located in the eastern, mid, and western parts of China, and all of them were permanent residents aged 60 years or older¹⁹.

2.2 Participants

Our study enrolled 30 normal controls (NC), 43 aMCI subjects and 35AD subjects, who were matched in age, gender and education. All subjects diagnosed with AD fulfilled the following criteria: (a) age ≥ 60 years; (b) met the National Institute on Aging-Alzheimer’s Association (NIA-AA) 2011 criteria for dementia and the DSM-V 2013 criteria²⁰; (c) global Clinical Dementia Rating (CDR) scores between 0.5 and 2; (d) Mini-Mental State Examination (MMSE) scores below 24. All subjects diagnosed with aMCI fulfilled the following criteria²¹:（a) age ≥ 60 years ; (b)memory complaints;（c) objective memory impairment：Mini-Mental State Examination (MMSE) scores below 25; (d) normal general cognitive function; (e)intact activities of daily living; and (f) absence of dementia: CDR scores of 0.5. The NCs fulfilled the following criteria: (a) age ≥ 60 years; (b) no reports of experiencing memory loss; (c) CDR scores of 0 and MMSE scores between 25 and 30; and (d) absence of serious mental and physical diseases.

2.3 General demographic data

General demographic data, such as age, gender, education, smoking history, drinking history, tea drinking history and disease history(diabetes and hypertension) were collected with standardized questionnaires, and in the form of self-report.

2.4 Plasma NfL

Plasma NFL was examined by a highly sensitive assay on the Single Molecule Array (Simoa™) platform²². SiMoA NfL assay advantage kits (product #103186) were commercially obtained from Quanterix corporation(MA, USA). Critical reagents including buffer quality controls and recombinant human NfL standards were supplied frozen for single use only²³. And all the samples were measured in duplicate.

2.5 Neuropsychological Tests

Montreal Cognitive Assessment-Chinese Version (MoCA-CV)²⁴ was used to assess the overall cognitive function of all subjects. The MOCA is an evaluation tool used to evaluate MCI, developed by Nasreddine ²⁵et al. And it is able to differentiate between MCI and early dementia as well as between normal and MCI²⁶. The MoCA cut-offs (–1 to –2 standard deviations) for cognitive impairment was ranged from <25 to <21 for the lowest educated and <26 to <24 for the highest educated, depending on different age groups²⁷.

2.6 Magnetic Resonance Imaging

MR images were scanned by using Siemens Magnetom Verio 3.0T scanner (Siemens, Munich, Germany). T1-weighted images were obtained from 176 sagittal slices using 3D magnetization prepared rapid gradient echo acquisition sequence with the following parameters: Spatial resolution = 1∗1∗1.2 mm3, TE = 2.98 ms ,TR = 2300 ms, Flip angle = 9°²⁸. The MRI FLAIR data acquisition setting used the following parameters: matrix 256 × 192, FOV = 24 cm ,NEX = 1, TE = 140, InVTime = 2200, TR = 8600²⁹.

Automated procedures were utilized to ascertain volumetric data. The automated assessment was described by using the Learning Embedding for Atlas Propagation (LEAP) algorithm³⁰. The volume and asymmetry with hippocampus and amygdala as well as the brain size index of each subject were extracted.

Continuous variables were expressed as mean ± SD and categorical variables were expressed as frequencies (%). Single sample Kolmogorov-Smirnov test was used to check whether the data conform to the normal distribution. Single factor ANOVA was used to compare the data of normal distribution among AD group, aMCI group and normal group, while Kruskal-Wallis H(K) test was used to compare the data of non -normal distribution. And chi square test was used to categorical variables among the three groups. Then partial correlation analysis(controlled for hypertension) was used to explore the association between plasma NfL and volume of cognitive related brain areas(hippocampus and amygdala). Two-tailed tests were utilized at a significance level of P < 0.05, and all statistical analyses were performed using SPSS 22.0 (IBM Corporation, Armonk, NY, USA).

There were statistical differences (p<0.05) in hypertenion, MoCA, left hippocampus, right hippocampus, left amygdala and right amygdala among AD group, aMCI group and normal group, but no significant differences (p>0.05) in age, education, gender, smoker, drinker, tea drinker and diabetes. Table 1 shows the results. Then further comparison showed that the MOCA scores of normal group, aMCI group and AD group decreased in turn. The volume of hippocampus and amygdala and in aMCI group and normal group were larger (p<0.05)than that in AD group, but there was no significant difference(p>0.05) between aMCI group and normal group. However, the concentration of plasma NfL in aMCI group and normal group were lower (p<0.05)than that in AD group, but there was no significant difference(p>0.05) between aMCI group and normal group(figure 1). And table 2 presents the results. Then by using partial correlation analysis and controlled of hypertension, we found that plasma NfL was negatively correlated (p<0.05)with MoCA total score (r=-0.415, p=0.013), right hippocampal volume(r=-0.335,p=0.036) and right amygdala volume(r=-0.337, p=0.048).

In the present study, we analyzed and compared the plasma concentration of NfL as well as the volume differences in hippocampus and amygdala among patients with AD, patients with aMCI and normal elderly. Finally, we reached some interesting conclusions: a) the concentration of plasma NfL in aMCI group and normal group were lower (p < 0.05)than that in AD group, but there was no significant difference(p > 0.05) between aMCI group and normal group; b) the volume(both left and right) of hippocampus and amygdala in aMCI group and normal group were larger (p < 0.05)than that in AD group, but there was no significant difference(p > 0.05) between aMCI group and normal group; c) plasma NfL was negatively correlated (p < 0.05)with MoCA total score (r=-0.415, p = 0.013), right hippocampal volume(r=-0.335,p = 0.036) and right amygdala volume(r=-0.337, p = 0.048).

NfL is an important cytoarchitectural protein present primarily in large-caliber myelinated axons³¹,and increased NfL in CSF will indicate damage or degeneration of these axons. This protein appears to be relatively independent of tau and amyloid levels, and might correlate with symptomology, progression, and survival³². Now NfL has been considered as an especially promising biomarker for neurodegeneration because it can be measurable in plasma³³. Single molecule array (SiMoA) digital immunoassay platform can offer heightened sensitivity by miniaturizing the reaction volume³⁴, and several biomarkers indicative of peptide fragmentation and neuronal dysfunction can be accurately quantified in peripheral blood. In our study, we used this Simoa technology to compare the plasma NFL concentrations of AD, aMCI and normal elderly people(their gender, age and education are matched), and found the concentration of plasma NfL in AD group were significantly higher(p < 0.05) than that in aMCI group and normal group. Previous studies had confirmed that AD was associated with elevated NFL in plasma, so our findings were consistent^8,9. However, we did not find any difference in plasma NfL between patients with aMCI and normal elderly, which was inconsistent with the conclusion of Zhow W⁷ et al. So the relationship between NfL and aMCI needs to be further verified.

Atrophy of the medial temporal lobe, a critical region involved in memory formation, is considered as a recognized marker for AD³⁵. The hippocampus and amygdala, both residing in the medial temporal lobe, are proved to be associated with declarative memory and emotional processing, respectively³⁶. As the atrophy of hippocampal and amygdalar are already evident in the prodromal stage of AD³⁷, the volumetric measurements of hippocampus and amygdala have been used to assist the clinical diagnosis of AD³⁸ and to predict the cognitive status of the elderly³⁹. As expected, the volume of hippocampus and amygdala in AD patients was significantly smaller than that in aMCI and normal old people, in concordance with previous publications^39–41. Then by using partial correlation analysis (adjusting hypertension), we found plasma NfL was negatively correlated with MoCA total score (r=-0.415, p = 0.013), right hippocampal volume(r=-0.335,p = 0.036) and right amygdala volume(r=-0.337, p = 0.048).

Parbo P⁴² et al pointed that plasma NfL levels were inverse correlated with levels of inflammation in cortical areas in AD. Mattsson N³³ et al found that faster increase in plasma NfL levels correlated with faster rates of atrophy and hypometabolism, and faster worsening in global cognition in aMCI and AD. And Weston PSJ⁴³ et al also found that serum NfL correlated with baseline brain volume and whole-brain atrophy rate in patients with familial Alzheimer disease. So we had jointly confirmed that there was a certain correlation between plasma NfL and cognitive related brain regions. However, we only found that plasma NfL was related to the right hippocampus and right amygdala, but not to the left. Wang L⁴⁴ et al found that the functional connectivity between the right hippocampus and a set of regions(such as medial prefrontal cortex, right inferotemporal cortex, right cuneus extending into precuneus, ventral anterior cingulate cortex, left cuneus, right superior and middle temporal gyrus and posterior cingulate cortex)was disrupted in AD. Sohn WS⁴⁵ et al also believed that the right hippocampal connectivity was relatively by AD progression. And López-Jaramillo C⁴⁶ et also found that lithium-treated bipolar I disorder patients had larger right thalamus than unmedicated patients and controls. Therefore, we speculated that plasma NFL had some intrinsic relationship with the right hippocampus and the right amygdala, although the mechanism was not fully understood.

Our study has certain limitations: first, it’s just a cross-sectional study that could not establish a causal link; second, the relatively small sample size reduced the reliability of the study; third, we lacked the gold standard to diagnose AD and aMCI.

NFL in plasma of AD patients was significantly increased, and the protein was related to atrophy of right hippocampus and right amygdala.

NfL Plasma neurofilament light

aMCI amnesic mild cognitive impairment

AD Alzheimer’s disease

Simoa Single Molecule array

MoCA Montreal Cognitive Assessment

CSF Incerebrospinal fluid

FTLD Frontotemporal lobar degeneration

MCI Mild cognitive impairment

PD Parkinson's disease

MRI Magnetic Resonance Imaging

MTA Medial temporal atrophy

NC Normal control

CLAS China Longitudinal Aging Study

NIA-AA National Institute on Aging-Alzheimer’s Association

CDR Clinical Dementia Rating

LEAP Learning Embedding for Atlas Propagation

8.1 Ethics approval and consent to participate

This study was conducted in accordance with the principles of Declaration of Helsinki, and approved by the Research Ethical Committee of the affiliated mental health center of Shanghai Jiaotong University School of Medicine. All participants had signed the informed consent written informed consent before the start of the study.

8.2 Consent for publication

Not applicable.

8.3 Availability of data and materials

The data base generated and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

8.4 Competing interests

The authors declare that they have no competing interests.

8.5 Funding

This work was supported by grants from the China Ministry of Science and Technology (2009BAI77B03), National Natural Science Foundation of China (number 81671402), Clinical research center project of Shanghai Mental Health Center (CRC2017ZD02), the National Key R&D program of China (2017YFC1310501500), the Cultivation of Multidisciplinary interdisciplinary Project in Shanghai Jiao Tong University (YG2019QNA10) and curriculum reform of Medical College of Shanghai Jiao Tong University.

8.6 Authors' contributions

Wei Li and Lin Sun contributed to the study concept and design. Ling Yue acquired the data. Ye

Wu collected the data. Shifu analyzed the data and drafted the manuscript. All authors have read and approved the final manuscript.

8.7 Acknowledgement

Not applicable.

Alirezaei Z, Pourhanifeh MH, Borran S, Nejati M, Mirzaei H, Hamblin MR. Neurofilament Light Chain as a Biomarker, and Correlation with Magnetic Resonance Imaging in Diagnosis of CNS-Related Disorders. Mol Neurobiol. 2020;57(1):469-491.
Zetterberg H, Hietala MA, Jonsson M, et al. Neurochemical aftermath of amateur boxing. Arch Neurol. 2006;63(9):1277-1280.
Falgas N, Ruiz-Peris M, Perez-Millan A, et al. Contribution of CSF biomarkers to early-onset Alzheimer's disease and frontotemporal dementia neuroimaging signatures. Hum Brain Mapp. 2020.
Hu YY, He SS, Wang XC, et al. Elevated levels of phosphorylated neurofilament proteins in cerebrospinal fluid of Alzheimer disease patients. Neurosci Lett. 2002;320(3):156-160.
Olsson B, Portelius E, Cullen NC, et al. Association of Cerebrospinal Fluid Neurofilament Light Protein Levels With Cognition in Patients With Dementia, Motor Neuron Disease, and Movement Disorders. JAMA Neurol. 2019;76(3):318-325.
Portelius E, Olsson B, Hoglund K, et al. Cerebrospinal fluid neurogranin concentration in neurodegeneration: relation to clinical phenotypes and neuropathology. Acta Neuropathol. 2018;136(3):363-376.
Zhou W, Zhang J, Ye F, et al. Plasma neurofilament light chain levels in Alzheimer's disease. Neurosci Lett. 2017;650:60-64.
Liu S, Huang Z, Zhang L, et al. Plasma Neurofilament Light Chain May Be a Biomarker for the Inverse Association Between Cancers and Neurodegenerative Diseases. Front Aging Neurosci. 2020;12:10.
Hu H, Chen KL, Ou YN, et al. Neurofilament light chain plasma concentration predicts neurodegeneration and clinical progression in nondemented elderly adults. Aging (Albany NY). 2019;11(17):6904-6914.
Lin YS, Lee WJ, Wang SJ, Fuh JL. Levels of plasma neurofilament light chain and cognitive function in patients with Alzheimer or Parkinson disease. Sci Rep. 2018;8(1):17368.
Canu E, Agosta F, Mandic-Stojmenovic G, et al. Multiparametric MRI to distinguish early onset Alzheimer's disease and behavioural variant of frontotemporal dementia. Neuroimage Clin. 2017;15:428-438.
Moller C, Hafkemeijer A, Pijnenburg YA, et al. Joint assessment of white matter integrity, cortical and subcortical atrophy to distinguish AD from behavioral variant FTD: A two-center study. Neuroimage Clin. 2015;9:418-429.
Sala-Llonch R, Llado A, Fortea J, et al. Evolving brain structural changes in PSEN1 mutation carriers. Neurobiol Aging. 2015;36(3):1261-1270.
Ten Kate M, Barkhof F, Boccardi M, et al. Clinical validity of medial temporal atrophy as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework. Neurobiol Aging. 2017;52:167-182.e161.
van de Pol LA, Korf ES, van der Flier WM, et al. Magnetic resonance imaging predictors of cognition in mild cognitive impairment. Arch Neurol. 2007;64(7):1023-1028.
Yue L, Wang T, Wang J, et al. Asymmetry of Hippocampus and Amygdala Defect in Subjective Cognitive Decline Among the Community Dwelling Chinese. Front Psychiatry. 2018;9:226.
Mattsson N, Andreasson U, Zetterberg H, Blennow K. Association of Plasma Neurofilament Light With Neurodegeneration in Patients With Alzheimer Disease. JAMA Neurol. 2017;74(5):557-566.
Xiao S, Li J, Tang M, et al. Methodology of China's national study on the evaluation, early recognition, and treatment of psychological problems in the elderly: the China Longitudinal Aging Study (CLAS). Shanghai Arch Psychiatry. 2013;25(2):91-98.
Xu H, Wang Y, Yuan Y, et al. Gender differences in the protective effects of green tea against amnestic mild cognitive impairment in the elderly Han population. Neuropsychiatr Dis Treat. 2018;14:1795-1801.
McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7(3):263-269.
Petersen RC, Doody R, Kurz A, et al. Current concepts in mild cognitive impairment. Arch Neurol. 2001;58(12):1985-1992.
Hendricks R, Baker D, Brumm J, et al. Establishment of neurofilament light chain Simoa assay in cerebrospinal fluid and blood. Bioanalysis. 2019;11(15):1405-1418.
Midde KK, Broadnax A, Binion B, et al. Evaluation of single molecule array digital immunoassay technology to quantitate neurofilament light chain. Bioanalysis. 2020;12(4):221-229.
Nasreddine ZS, Phillips NA, Bedirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695-699.
Atkins AS, Khan A, Ulshen D, et al. Assessment of Instrumental Activities of Daily Living in Older Adults with Subjective Cognitive Decline Using the Virtual Reality Functional Capacity Assessment Tool (VRFCAT). J Prev Alzheimers Dis. 2018;5(4):216-234.
Pinto TCC, Machado L, Costa MLG, et al. Accuracy and Psychometric Properties of the Brazilian Version of the Montreal Cognitive Assessment as a Brief Screening Tool for Mild Cognitive Impairment and Alzheimer's Disease in the Initial Stages in the Elderly. Dement Geriatr Cogn Disord. 2019;47(4-6):366-374.
Borland E, Nagga K, Nilsson PM, Minthon L, Nilsson ED, Palmqvist S. The Montreal Cognitive Assessment: Normative Data from a Large Swedish Population-Based Cohort. J Alzheimers Dis. 2017;59(3):893-901.
Lin S, Yang Y, Qi Q, et al. The Beneficial Effect of Physical Exercise on Cognitive Function in a Non-dementia Aging Chinese Population. Front Aging Neurosci. 2019;11:238.
Wang T, Shi F, Jin Y, Jiang W, Shen D, Xiao S. Abnormal Changes of Brain Cortical Anatomy and the Association with Plasma MicroRNA107 Level in Amnestic Mild Cognitive Impairment. Front Aging Neurosci. 2016;8:112.
Wolz R, Schwarz AJ, Yu P, et al. Robustness of automated hippocampal volumetry across magnetic resonance field strengths and repeat images. Alzheimers Dement. 2014;10(4):430-438.e432.
Elder GA, Friedrich VL, Jr., Bosco P, et al. Absence of the mid-sized neurofilament subunit decreases axonal calibers, levels of light neurofilament (NF-L), and neurofilament content. J Cell Biol. 1998;141(3):727-739.
Merluzzi AP, Vogt NM, Norton D, et al. Differential effects of neurodegeneration biomarkers on subclinical cognitive decline. Alzheimers Dement (N Y). 2019;5:129-138.
Mattsson N, Cullen NC, Andreasson U, Zetterberg H, Blennow K. Association Between Longitudinal Plasma Neurofilament Light and Neurodegeneration in Patients With Alzheimer Disease. JAMA Neurol. 2019;76(7):791-799.
Song L, Lachno DR, Hanlon D, et al. A digital enzyme-linked immunosorbent assay for ultrasensitive measurement of amyloid-beta 1-42 peptide in human plasma with utility for studies of Alzheimer's disease therapeutics. Alzheimers Res Ther. 2016;8(1):58.
Duara R, Loewenstein DA, Potter E, et al. Medial temporal lobe atrophy on MRI scans and the diagnosis of Alzheimer disease. Neurology. 2008;71(24):1986-1992.
Guzman-Velez E, Warren DE, Feinstein JS, Bruss J, Tranel D. Dissociable contributions of amygdala and hippocampus to emotion and memory in patients with Alzheimer's disease. Hippocampus. 2016;26(6):727-738.
Rozzini L, Chilovi BV, Trabucchi M, Padovani A. Re: Predictors of progression from mild cognitive impairment to Alzheimer disease. Neurology. 2008;70(9):735; author reply 735-736.
Tang X, Holland D, Dale AM, Younes L, Miller MI. Shape abnormalities of subcortical and ventricular structures in mild cognitive impairment and Alzheimer's disease: detecting, quantifying, and predicting. Hum Brain Mapp. 2014;35(8):3701-3725.
den Heijer T, Geerlings MI, Hoebeek FE, Hofman A, Koudstaal PJ, Breteler MM. Use of hippocampal and amygdalar volumes on magnetic resonance imaging to predict dementia in cognitively intact elderly people. Arch Gen Psychiatry. 2006;63(1):57-62.
Lin TW, Shih YH, Chen SJ, et al. Running exercise delays neurodegeneration in amygdala and hippocampus of Alzheimer's disease (APP/PS1) transgenic mice. Neurobiol Learn Mem. 2015;118:189-197.
Fjell AM, Walhovd KB, Fennema-Notestine C, et al. CSF biomarkers in prediction of cerebral and clinical change in mild cognitive impairment and Alzheimer's disease. J Neurosci. 2010;30(6):2088-2101.
Parbo P, Madsen LS, Ismail R, et al. Low plasma neurofilament light levels associated with raised cortical microglial activation suggest inflammation acts to protect prodromal Alzheimer's disease. Alzheimers Res Ther. 2020;12(1):3.
Weston PSJ, Poole T, Ryan NS, et al. Serum neurofilament light in familial Alzheimer disease: A marker of early neurodegeneration. Neurology. 2017;89(21):2167-2175.
Wang L, Zang Y, He Y, et al. Changes in hippocampal connectivity in the early stages of Alzheimer's disease: evidence from resting state fMRI. Neuroimage. 2006;31(2):496-504.
Sohn WS, Yoo K, Na DL, Jeong Y. Progressive changes in hippocampal resting-state connectivity across cognitive impairment: a cross-sectional study from normal to Alzheimer disease. Alzheimer Dis Assoc Disord. 2014;28(3):239-246.
Lopez-Jaramillo C, Vargas C, Diaz-Zuluaga AM, et al. Increased hippocampal, thalamus and amygdala volume in long-term lithium-treated bipolar I disorder patients compared with unmedicated patients and healthy subjects. Bipolar Disord. 2017;19(1):41-49.

Table 1. General demographic data and clinical characteristics of subjects

Characteristics	aMCI (n=43)	AD (n=35)	Normal (n=30)	p
Age, years	72.21±6.151	71.80±10.737	70.00±4.202	0.451
Education, years	11.84±3.804	12.14±5.621	12.33±2.631	0.316
Male, n(%)	17(39.5)	8(22.9)	11(36.7)	0.269
Smoker, n(%)	7(16.3)	7(6.5)	4(3.7)	0.769
Drinker,n(%)	10(9.3)	5(4.6)	2(1.9)	0.153
Tea drinker, n(%)	19(44.2)	10(28.6)	15(50)	0.181
Hypertension,n(%)	28(65.1)	9(25.7)	16(53.3)	0.002*
Diabetes, n(%)	5(11.6)	3(8.6)	5(16.7)	0.603
Moca	20.48±3.430	5.71±4.908	25.75±2.382	<0.001*
Left hippocampus,mm³	3401.71±389.866	2495.03±466.353	3383.87±189.653	<0.001*
Right hippocampus,mm³	3409.89±388.144	2684.93±418.750	3605.23±201.807	<0.001*
Left Amygdala,mm³	1275.81±250.030	688.208±248.970	1219.90±103.600	<0.001*
Right Amygdala,mm³	1345.66±173.892	873.992±199.471	1423.06±217.733	<0.001*
Plasma NFL, pg/ml	15.92±6.521	29.42±23.182	12.85±2.138	<0.001*

Table 2. Multiple comparison among three groups(aMCI, AD and Normal)

Variables	Group 1	Group 2	Mean difference	Standard error	p	95%confidence interval
MoCA	aMCI	AD	14.762	0.912	<0.001*	12.95~16.57
	aMCI	Normal	-5.274	0.972	<0.001*	-7.20~-3.35
	AD	Normal	-20.036	1.010	<0.001*	-22.04~-18.03
Left hippocampus	aMCI	AD	906.682	163.441	<0.001*	574.53~1238.83
	aMCI	Normal	17.84	177.932	0.921	-343.76~379.44
	AD	Normal	-888.84	186.086	<0.001*	-1267.01~-510.67
Right hippocampus	aMCI	AD	724.968	151.568	<0.001*	416.95~1032.99
	aMCI	Normal	-195.34	165.006	0.245	-530.673~139.99
	AD	Normal	-920.308	172.568	<0.001*	-1271.01~-569.61
Left Amygdala	aMCI	AD	587.605	96.963	<0.001*	390.552~784.658
	aMCI	Normal	55.913	105.560	0.600	-158.611~270.437
	AD	Normal	-531.692	110.397	<0.001*	-756.046~-307.337
Right Amygdala	aMCI	AD	471.668	79.833	<0.001*	309.428~633.909
	aMCI	Normal	-77.396	86.912	0.379	-254.021~99.230
	AD	Normal	-549.064	90.894	<0.001*	-733.783~-364.345
Plasma NFL	aMCI	AD	-13.495	3.157	<0.001*	-19.755~-7.236
	aMCI	Normal	3.075	3.299	0.353	-3.465~9.616
	AD	Normal	16.570	3.450	<0.001*	9.729~23.411

Table3. Results of partial correlation analysis (hypertension controlled)

Variable 1	Variable 2	relativity	p
Plasma NfL	Moca	-0.415	0.013*
	Left hippocampus	-0.207	0.232
	Right hippocampus	-0.355	0.036*
	Left Amygdala	-0.207	0.232
	Right Amygdala	-0.337	0.048*

PDF

Version 1

posted 23 Mar, 2020

You are reading this latest preprint version

Elevated neurofilament light chain in plasma is associated with reduced right hippocampal and amygdala volume in Alzheimer's patients

Status:

Version 1

Abstract

Figures

1. Introduction

2. Materials And Methods

3. Statistical Analyses

4. Results

5. Discussion

6. Conclusions

7. Abbreviations

8. Declarations

9. Reference

Tables

Status:

Version 1