RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      KCI등재 SCIE SCOPUS

      Serum Neurofilament Light Chain Levels Are Related to Small Vessel Disease Burden

      한글로보기

      https://www.riss.kr/link?id=A105366268

      • 0

        상세조회
      • 0

        다운로드
      서지정보 열기
      • 내보내기
      • 내책장담기
      • 공유하기
      • 오류접수

      부가정보

      다국어 초록 (Multilingual Abstract)

      Background and Purpose Neurofilament light chain (NfL) is a blood marker for neuroaxonal damage. We assessed the association between serum NfL and cerebral small vessel disease (SVD), which is highly prevalent in elderly individuals and a major cause...

      Background and Purpose Neurofilament light chain (NfL) is a blood marker for neuroaxonal damage.
      We assessed the association between serum NfL and cerebral small vessel disease (SVD), which is highly prevalent in elderly individuals and a major cause of stroke and vascular cognitive impairment.
      Methods Using a cross-sectional design, we studied 53 and 439 patients with genetically defined SVD (Cerebral Autosomal-Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy [CADASIL]) and sporadic SVD, respectively, as well as 93 healthy controls. Serum NfL was measured by an ultrasensitive single-molecule array assay. We quantified magnetic resonance imaging (MRI) markers of SVD, i.e., white matter hyperintensity volume, lacune volume, brain volume, microbleed count, and mean diffusivity obtained from diffusion tensor imaging. Clinical characterization included neuropsychological testing in both SVD samples. CADASIL patients were further characterized for focal neurological deficits (National Institutes of Health stroke scale [NIHSS]) and disability (modified Rankin scale [mRS]).
      Results Serum NfL levels were elevated in both SVD samples (P<1e-05 compared with controls) and associated with all SVD MRI markers. The strongest association was found for mean diffusivity (CADASIL, R2=0.52, P=1.2e-09; sporadic SVD, R2=0.21, P<1e-15). Serum NfL levels were independently related to processing speed performance (CADASIL, R2=0.27, P=7.6e-05; sporadic SVD, R2=0.06, P=4.8e-08), focal neurological symptoms (CADASIL, NIHSS, P=4.2e-05) and disability (CADASIL, mRS, P=3.0e-06).
      Conclusions We found serum NfL levels to be associated with both imaging and clinical features of SVD. Serum NfL might complement MRI markers in assessing SVD burden. Importantly, SVD needs to be considered when interpreting serum NfL levels in the context of other age-related diseases.

      더보기

      참고문헌 (Reference)

      1 Tombaugh TN, "Trail Making Test A and B: normative data stratified by age and education" 19 : 203-214, 2004

      2 Smith SM, "Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data" 31 : 1487-1505, 2006

      3 Charlton RA, "The cognitive profiles of CADASIL and sporadic small vessel disease" 66 : 1523-1526, 2006

      4 Van der Elst W, "The Concept Shifting Test: adult normative data" 18 : 424-432, 2006

      5 Gattringer T, "Serum neurofilament light is sensitive to active cerebral small vessel disease" 89 : 2108-2114, 2017

      6 Rohrer JD, "Serum neurofilament light chain protein is a measure of disease intensity in frontotemporal dementia" 87 : 1329-1336, 2016

      7 Disanto G, "Serum neurofilament light chain levels are increased in patients with a clinically isolated syndrome" 87 : 126-129, 2016

      8 Traenka C, "Serum neurofilament light chain levels are associated with clinical characteristics and outcome in patients with cervical artery dissection" 40 : 222-227, 2015

      9 Kuhle J, "Serum neurofilament light chain in early relapsing remitting MS is increased and correlates with CSF levels and with MRI measures of disease severity" 22 : 1550-1559, 2016

      10 De Guio F, "Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease" 36 : 1319-1337, 2016

      1 Tombaugh TN, "Trail Making Test A and B: normative data stratified by age and education" 19 : 203-214, 2004

      2 Smith SM, "Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data" 31 : 1487-1505, 2006

      3 Charlton RA, "The cognitive profiles of CADASIL and sporadic small vessel disease" 66 : 1523-1526, 2006

      4 Van der Elst W, "The Concept Shifting Test: adult normative data" 18 : 424-432, 2006

      5 Gattringer T, "Serum neurofilament light is sensitive to active cerebral small vessel disease" 89 : 2108-2114, 2017

      6 Rohrer JD, "Serum neurofilament light chain protein is a measure of disease intensity in frontotemporal dementia" 87 : 1329-1336, 2016

      7 Disanto G, "Serum neurofilament light chain levels are increased in patients with a clinically isolated syndrome" 87 : 126-129, 2016

      8 Traenka C, "Serum neurofilament light chain levels are associated with clinical characteristics and outcome in patients with cervical artery dissection" 40 : 222-227, 2015

      9 Kuhle J, "Serum neurofilament light chain in early relapsing remitting MS is increased and correlates with CSF levels and with MRI measures of disease severity" 22 : 1550-1559, 2016

      10 De Guio F, "Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease" 36 : 1319-1337, 2016

      11 Sing T, "ROCR: visualizing classifier performance in R" 21 : 3940-3941, 2005

      12 Benjamin P, "Progression of MRI markers in cerebral small vessel disease: sample size considerations for clinical trials" 36 : 228-240, 2016

      13 Behrens TE, "Probabilistic diffusion tractography with multiple fibre orientations: what can we gain?" 34 : 144-155, 2007

      14 Wiseman SJ, "Plasma biomarkers of inflammation, endothelial function and hemostasis in cerebral small vessel disease" 40 : 157-164, 2015

      15 Christensen RH, "Ordinal: regression models for ordinal data"

      16 Wardlaw JM, "Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration" 12 : 822-838, 2013

      17 Lu CH, "Neurofilament light chain: a prognostic biomarker in amyotrophic lateral sclerosis" 84 : 2247-2257, 2015

      18 Vilar-Bergua A, "N-terminal pro-brain natriuretic peptide and subclinical brain small vessel disease" 87 : 2533-2539, 2016

      19 Norgren N, "Monoclonal antibodies selective for low molecular weight neurofilaments" 21 : 53-59, 2002

      20 Markus HS, "Markers of endothelial and hemostatic activation and progression of cerebral white matter hyperintensities: longitudinal results of the Austrian Stroke Prevention Study" 36 : 1410-1414, 2005

      21 Gaiottino J, "Increased neurofilament light chain blood levels in neurodegenerative neurological diseases" 8 : e75091-, 2013

      22 Duering M, "Incident lacunes preferentially localize to the edge of white matter hyperintensities: insights into the pathophysiology of cerebral small vessel disease" 136 : 2717-2726, 2013

      23 Haller S, "Head motion parameters in fMRI differ between patients with mild cognitive impairment and Alzheimer disease versus elderly control subjects" 27 : 801-807, 2014

      24 Archer KJ, "Glmnetcr: fit a penalized constrained continuation ratio model for predicting an ordinal response"

      25 Williams DA, "Generalized linear model diagnostics using the deviance and single case deletions" 36 : 181-191, 1987

      26 Pearce LA, "Effects of long-term blood pressure lowering and dual antiplatelet treatment on cognitive function in patients with recent lacunar stroke: a secondary analysis from the SPS3 randomised trial" 13 : 1177-1185, 2014

      27 Zieren N, "Education modifies the relation of vascular pathology to cognitive function: cognitive reserve in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy" 34 : 400-407, 2013

      28 de Laat KF, "Diffusion tensor imaging and gait in elderly persons with cerebral small vessel disease" 42 : 373-379, 2011

      29 Wollenweber FA, "Cortical superficial siderosis in different types of cerebral small vessel disease" 48 : 1404-1407, 2017

      30 Kuhle J, "Comparison of three analytical platforms for quantification of the neurofilament light chain in blood samples: ELISA, electrochemiluminescence immunoassay and Simoa" 54 : 1655-1661, 2016

      31 Satizabal CL, "Circulating IL-6 and CRP are associated with MRI findings in the elderly: the 3C-Dijon Study" 78 : 720-727, 2012

      32 Behrens TE, "Characterization and propagation of uncertainty in diffusion-weighted MR imaging" 50 : 1077-1088, 2003

      33 Jonsson M, "Cerebrospinal fluid biomarkers of white matter lesions: cross-sectional results from the LADIS study" 17 : 377-382, 2010

      34 Pantoni L, "Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges" 9 : 689-701, 2010

      35 van Norden AG, "Causes and consequences of cerebral small vessel disease. The RUN DMC study: a prospective cohort study. Study rationale and protocol" 11 : 29-, 2011

      36 Schmidt R, "C-reactive protein, carotid atherosclerosis, and cerebral small-vessel disease: results of the Austrian Stroke Prevention Study" 37 : 2910-2916, 2006

      37 van Dijk EJ, "C-reactive protein and cerebral small-vessel disease: the Rotterdam Scan Study" 112 : 900-905, 2005

      38 Nagai M, "Association of prothrombotic status with markers of cerebral small vessel disease in elderly hypertensive patients" 25 : 1088-1094, 2012

      39 Mattsson N, "Association of plasma neurofilament light with neurodegeneration in patients with alzheimer disease" 74 : 557-566, 2017

      40 Harrison JK, "Assessment scales in stroke: clinimetric and clinical considerations" 8 : 201-211, 2013

      41 Van Der Elst W, "Assessment of information processing in working memory in applied settings: the paper and pencil memory scanning test" 37 : 1335-1344, 2007

      42 Voineskos AN, "Age-related decline in white matter tract integrity and cognitive performance: a DTI tractography and structural equation modeling study" 33 : 21-34, 2012

      43 Baykara E, "A novel imaging marker for small vessel disease based on skeletonization of white matter tracts and diffusion histograms" 80 : 581-592, 2016

      44 Kuhle J, "A comparative study of CSF neurofilament light and heavy chain protein in MS" 19 : 1597-1603, 2013

      45 R Core Team, "A Language and Environment for Statistical Computing"

      더보기

      동일학술지(권/호) 다른 논문

      동일학술지 더보기

      더보기

      분석정보

      View

      상세정보조회

      0

      Usage

      원문다운로드

      0

      대출신청

      0

      복사신청

      0

      EDDS신청

      0

      동일 주제 내 활용도 TOP

      더보기

      주제

      연도별 연구동향

      연도별 활용동향

      연관논문

      연구자 네트워크맵

      공동연구자 (7)

      유사연구자 (20) 활용도상위20명

      인용정보 인용지수 설명보기

      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2014-11-01 평가 SCIE 등재 (기타) KCI등재
      2013-01-01 평가 등재후보학술지 유지 (기타) KCI등재후보
      2011-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
      더보기

      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 3.63 0.55 3.13
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      2.37 1.91 1.175 0.1
      더보기

      이 자료와 함께 이용한 RISS 자료

      나만을 위한 추천자료

      해외이동버튼