DOI QR코드

DOI QR Code

Investigation of the Correlation between Seoul Neuropsychological Screening Battery Scores and the Gray Matter Volume after Correction of Covariates of the Age, Gender, and Genotypes in Patients with AD and MCI

알츠하이머 치매 및 경도인지기능장애 환자에서 나이, 성별, 유전자형을 고려한 뇌 회백질 부피와 표준신경심리검사와의 상관관계 연구

  • Lee, Seung-Yeon (Department of Medicine, School of Medicine, Kyung Hee University) ;
  • Yoon, Soo-Young (Department of Medicine, School of Medicine, Kyung Hee University) ;
  • Kim, Min-Ji (Department of Radiology, Kyung Hee University Hospital at Gangdong) ;
  • Rhee, Hak Young (Department of Neurology, Kyung Hee University Hospital at Gangdong, School of Medicine, Kyung Hee University) ;
  • Ryu, Chang-Woo (Department of Radiology, Kyung Hee University Hospital at Gangdong) ;
  • Jahng, Geon-Ho (Department of Radiology, Kyung Hee University Hospital at Gangdong)
  • 이승연 (경희대학교 의학전문대학원 의학과) ;
  • 윤수영 (경희대학교 의학전문대학원 의학과) ;
  • 김민지 (경희대학교 강동경희대학교병원 영상의학과) ;
  • 이학영 (경희대학교 의과대학 강동경희대학교병원 신경과) ;
  • 류창우 (경희대학교 강동경희대학교병원 영상의학과) ;
  • 장건호 (경희대학교 강동경희대학교병원 영상의학과)
  • Received : 2013.07.29
  • Accepted : 2013.09.09
  • Published : 2013.12.27

Abstract

Purpose : To investigate the correlations between Seoul Neuropsychological Screening Battery (SNSB) scores and the gray matter volumes (GMV) in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) and cognitively normal (CN) elderly subjects with correcting the genotypes. Materials and Methods: Total 75 subjects were enrolled with 25 subjects for each group. The apolipoprotein E (APOE) epsilon genotypes, SNSB scores, and the 3D T1-weighted images were obtained from all subjects. Correlations between SNSB scores and GMV were investigated with the multiple regression method for each subject group using both voxel-based and region-of-interest-based analyses with covariates of age, gender, and the genotype. Results: In the AD group, Rey Complex Figure Test (RCFT) delayed recall scores were positively correlated with GMV. In the MCI group, Seoul Verbal Learning Test (SVLT) scores were positively correlated with GMV. In the CN group, GMV negatively correlated with Boston Naming Test (K-BNT) scores and Mini-Mental State Examimation (K-MMSE) scores, but positively correlated with RCFT scores. Conclusion: When we used covariates of age, gender, and the genotype, we found statistically significant correlations between some SNSB scores and GMV at some brain regions. It may be necessary to further investigate a longitudinal study to understand the correlation.

목적 : 본 연구의 목적은 다양한 신경심리검사를 통해 알츠하이머 치매 및 경도인지장애 환자군과 정상 노인 대조군에서 뇌회색질 부피와 신경심리검사 (SNSB) 결과의 복셀 기반분석을 이용한 상관관계를 알아내는데 있다. 대상 및 방법 : 총 피험자는 75명으로, 정상노인 25명, 경도인지장애 환자 25명, 그리고 알츠하이머 치매 환자 25명이었다. 모든 피험자로부터 유전자검사, 표준신경심리검사 (SNSB), 해부학적인 삼차원 T1 강조영상을 자화준비 고속경사에코 시퀀스를 이용하여 얻었다. 각 피험자군에서 뇌 회색질의 용적변화와 신경심리검사 점수와의 상관관계를 관찰하기 위하여, 복셀기반과 관심영역 기반 방법을 이용하여 분할한 회색질 영상을 다중회기방식 (multiple regression)으로 통계처리 하였다. 이때 피험자 각각의 성별과 나이 및 유전자 보유형태를 공변량 (covariate) 값으로 넣어 그 차이를 고려하였다. 결과 : 알츠하이머 환자군에서는 레이 복합도형 그리기 지연회상 검사 (RCFT delayed recall) 점수가 낮을수록 뇌 회색질 용적이 감소했다. 경도인지 장애군에서는 서울 언어학습 검사 (SVLT) 점수가 낮을수록 뇌회색질 용적이 감소했다. 정상 피험자 군에서 한국형 보스턴 이름대기 검사 (K-BNT) 점수 및 한국형 간이정신상태 검사 (K-MMSE) 점수와 뇌 회색질 부피가 음의 상관관계가 있음을 보였고, 레이 복합도형 그리기 검사 (RCFT) 점수와는 양의 상관관계를 보여주고 있다. 결론 : 나이, 성별, 유전자형태를 공변량으로 사용하였을 때 뇌에서 신경심리검사 결과와 3D T1 강조영상에서 얻은 뇌 회색질 부피 사이에 통계적으로 유의한 상관관계가 있음을 밝혔다. 이들 피험자를 대상으로 하는 종적 연구가 이루어 져야 한다고 생각이 든다.

Keywords

References

  1. Jack CR, Jr., Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurol 2010;9:119-128 https://doi.org/10.1016/S1474-4422(09)70299-6
  2. Dickerson BC, Salat DH, Bates JF, et al. Medial temporal lobe function and structure in mild cognitive impairment. Ann Neurol 2004;56:27-35 https://doi.org/10.1002/ana.20163
  3. Karas GB, Scheltens P, Rombouts SA, et al. Global and local gray matter loss in mild cognitive impairment and Alzheimer's disease. Neuroimage 2004;23:708-716 https://doi.org/10.1016/j.neuroimage.2004.07.006
  4. Hampel H, Burger K, Teipel SJ, et al. Core candidate neurochemical and imaging biomarkers of Alzheimer's disease. Alzheimers Dement 2008;4:38-48 https://doi.org/10.1016/j.jalz.2007.08.006
  5. Corder EH, Saunders AM, Strittmatter WJ, et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science 1993;261(5123):921-923 https://doi.org/10.1126/science.8346443
  6. Hyman BT, Gomez-Isla T, West H, et al. Clinical and neuropathological correlates of apolipoprotein E genotype in Alzheimer's disease. Window on molecular epidemiology. Ann N Y Acad Sci 1996;777:158-165 https://doi.org/10.1111/j.1749-6632.1996.tb34414.x
  7. Nicoll JA, Savva GM, Stewart J, et al. Association between APOE genotype, neuropathology and dementia in the older population of England and Wales. Neuropathol Appl Neurobiol 2011;37(3):285-294 https://doi.org/10.1111/j.1365-2990.2010.01130.x
  8. Vemuri P, Wiste HJ, Weigand SD, et al. Effect of apolipoprotein E on biomarkers of amyloid load and neuronal pathology in Alzheimer disease. Ann Neurol 2010;67:308-316
  9. Filippini N, Rao A, Wetten S, et al. Anatomically-distinct genetic associations of APOE epsilon4 allele load with regional cortical atrophy in Alzheimer's disease. Neuroimage 2009;44: 724-728 https://doi.org/10.1016/j.neuroimage.2008.10.003
  10. Liu Y, Paajanen T, Westman E, et al. Effect of APOE epsilon4 allele on cortical thicknesses and volumes: the AddNeuroMed study. J Alzheimers Dis 2010;21:947-966 https://doi.org/10.3233/JAD-2010-100201
  11. Gauthier S, Reisberg B, Zaudig M, et al. Mild cognitive impairment. Lancet 2006;367(9518):1262-1270 https://doi.org/10.1016/S0140-6736(06)68542-5
  12. Davatzikos C, Bhatt P, Shaw LM, et al. Prediction of MCI to AD conversion, via MRI, CSF biomarkers, and pattern classification. Neurobiol Aging 2011;32:2322 e2319-2327
  13. Shin JH. Diagnosis of dementia: neuropsychological test. Korean J Fam Med 2010;31:253-266 https://doi.org/10.4082/kjfm.2010.31.4.253
  14. Bonekamp D, Yassa MA, Munro CA, et al. Gray matter in amnestic mild cognitive impairment: voxel-based morphometry. Neuroreport 2010;21:259-263 https://doi.org/10.1097/WNR.0b013e328335642a
  15. Choi SH, Moon WJ, Chung EC, et al. Optimized VBM in patients with Alzheimer's disease: gray matter loss and its correlation with cognitive function. J Korean Radiol Soc 2005;53:323-329
  16. Kim S, Youn YC, Hsiung GY, et al. Voxel-based morphometric study of brain volume changes in patients with Alzheimer's disease assessed according to the Clinical Dementia Rating score. J Clin Neurosci 2011;18:916-921 https://doi.org/10.1016/j.jocn.2010.12.019
  17. Lim HK, Choi EH, Lee CU. A Voxel-based morphometry of gray matter reduction in patients with dementia of the Alzheimer's type. Korean J Biol Psychiatry 2008;15:118-125
  18. Ashburner J, Friston KJ. Voxel-based morphometry--the methods. Neuroimage 2000;11(6 Pt 1):805-821 https://doi.org/10.1006/nimg.2000.0582
  19. Yoo B, Hahn C, Lee CU, et al. A voxel-based morphometry of gray matter volume reduction in patients with mild cognitive impairment. Korean J Biol Psychiatry 2011;18:232-238
  20. Kim MJ, Jahng GH, Lee HY, et al. Development of a Korean standard structural brain template in cognitive normals and patients with mild cognitive impairment and Alzheimer's disease. J Korean Soc Magn Reson Med 2010;14:103-114 https://doi.org/10.13104/jksmrm.2010.14.2.103
  21. Ahn HJ, Chin J, Park A, et al. Seoul Neuropsychological Screening Battery-dementia version (SNSB-D): a useful tool for assessing and monitoring cognitive impairments in dementia patients. J Korean Med Sci 2010;25:1071-1076 https://doi.org/10.3346/jkms.2010.25.7.1071
  22. Mortimer JA, Gosche KM, Riley KP, et al. Delayed recall, hippocampal volume and Alzheimer neuropathology: findings from the Nun Study. Neurology 2004;62:428-432 https://doi.org/10.1212/01.WNL.0000106463.66966.65
  23. Bigler ED, Mortensen S, Neeley ES, et al. Superior temporal gyrus, language function, and autism. Dev Neuropsychol 2007;31:217-238 https://doi.org/10.1080/87565640701190841
  24. Whitney C, Kirk M, O'Sullivan J, et al. The neural organization of semantic control: TMS evidence for a distributed network in left inferior frontal and posterior middle temporal gyrus. Cereb Cortex 2011;21:1066-1075 https://doi.org/10.1093/cercor/bhq180
  25. McFarland NR, Haber SN. Convergent inputs from thalamic motor nuclei and frontal cortical areas to the dorsal striatum in the primate. J Neurosci 2000;20:3798-3813
  26. Vidoni ED, Honea RA, Burns JM. Neural correlates of impaired functional independence in early Alzheimer's disease. J Alzheimers Dis 2010;19:517-527 https://doi.org/10.3233/JAD-2010-1245
  27. Packard MG, Knowlton BJ. Learning and memory functions of the Basal Ganglia. Annu Rev Neurosci 2002;25:563-593 https://doi.org/10.1146/annurev.neuro.25.112701.142937
  28. Molinuevo JL, Gomez-Anson B, Monte GC, et al. Neuropsychological profile of prodromal Alzheimer's disease (Prd- AD) and their radiological correlates. Arch Gerontol Geriatr 2011;52:190-196 https://doi.org/10.1016/j.archger.2010.03.016
  29. Duarte A, Hayasaka S, Du A et al. Volumetric correlates of memory and executive function in normal elderly, mild cognitive impairment and Alzheimer's disease. Neurosci Lett 2006;406:60-65 https://doi.org/10.1016/j.neulet.2006.07.029

Cited by

  1. Discourse Measures to Differentiate Between Mild Cognitive Impairment and Healthy Aging vol.11, pp.None, 2013, https://doi.org/10.3389/fnagi.2019.00221
  2. Use of the Clock Drawing Test and the Rey-Osterrieth Complex Figure Test-copy with convolutional neural networks to predict cognitive impairment vol.13, pp.1, 2013, https://doi.org/10.1186/s13195-021-00821-8