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Investigation of spatial transcriptomic signatures and therapeutic mode of action in Alzheimer's disease mouse model. : 알츠하이머병 모델에서 공간 전사체 시그니처 및 치료 작용 원리 규명

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dc.contributor.advisor이동수-
dc.contributor.author이은지-
dc.date.accessioned2022-12-29T08:40:34Z-
dc.date.available2022-12-29T08:40:34Z-
dc.date.issued2022-
dc.identifier.other000000172515-
dc.identifier.urihttps://hdl.handle.net/10371/188289-
dc.identifier.urihttps://dcollection.snu.ac.kr/common/orgView/000000172515ko_KR
dc.description학위논문(박사) -- 서울대학교대학원 : 융합과학기술대학원 분자의학 및 바이오제약학과, 2022. 8. 이동수.-
dc.description.abstractAlthough the pathophysiological changes that occur with the progression of Alzheimers disease (AD) are well-known, understanding the overall spatial heterogeneity of the brain is still required. Furthermore, there are insufficient methods to comprehensively verify the therapeutic effect in AD, a multifactorial disease. Advances in technology allow the use of spatial transcriptome data to identify key gene signatures and associated biological pathways in individual brain regions. In this study, I established a workflow to extensively perform each brain region-based spatial transcriptomic analysis to study the pathological changes in AD and evaluate the therapeutic action of immunomodulators that exhibit behavioral-improving effects.
First, I applied the workflow to compare AD model of different ages before and after definite accumulation of amyloid plaques. Early alterations of the AD model were identified exclusively in the white matter and were primarily involved in glial cell activation. In the later stage of AD, genes associated with glial cell activation were globally upregulated in both the white and gray matter, whereas the downregulated genes were region-specific. I also investigated spatial patterns of major brain cells using a curated reference-based marker panel. I identified the initial changes in the microglia and astrocytes-related signatures in the white matter, which eventually spread to the gray matter. Additionally, I observed various alterations in each brain regions, including genes involved in the diverse neuronal subclasses, metabolic process, and senescence, with the progression of AD pathology.
I evaluated the therapeutic effect of natural killer (NK) cell supplements and anti-CD4 antibody (aCD4), which improved behavior function identified via a Y-maze behavioral test in the AD model. NK cell therapy showed a decrease in glial cell-related genes and an increase in cellular respiration-related genes throughout the brain regions. Among the glial cell signatures, the decrease in the expression of activated microglial signatures was remarkable. The alteration was prominent in the cortex and thalamus but also occurred throughout the region. Moreover, a decrease in the inhibitory neuronal signatures in the amygdala was observed after NK cell administration in the AD model. In contrast, aCD4-injected AD model revealed region-specific changes exclusively in the white matter. Although not dramatic, synaptic function-related genes showed an increased expression level in the white matter. The changes in major brain cell signatures were insignificant after aCD4 administration in the AD model.
These results help to understand the spatiotemporal changes associated with the pathological progression of AD at a molecular level. Aberrantly altered major brain cell signatures were verified in each brain region of the AD model. Moreover, I demonstrated the feasibility of spatial transcriptome analysis as a method to validate the effects and modes of action in the AD model, taking two different drug administrations as examples. This workflow based on spatial transcriptomics can be harnessed to validate the therapeutic efficacy and mode of action via an in-depth transcriptional analysis in various diseases.
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dc.description.abstract알츠하이머병 진행에 따른 병태생리학적 변화는 다양한 연구를 통해 비교적 잘 검증되었지만 뇌의 공간적 이질성에 대한 이해를 기반으로 한 연구가 여전히 필요하다. 또한 다인성 질환인 알츠하이머병에 대한 치료 효과를 종합적으로 검증하기 위한 방법이 제한적이다. 최근, 공간 전사체 데이터를 통한 개별 뇌 영역에서의 주요 유전자 및 관련 기능에 대한 식별이 가능해졌다. 본 연구에서는 뇌 영역별 전체 유전자 발현 및 세포 유형 변화를 동시에 검출할 수 있는 공간 전사체 분석방법을 기반으로 알츠하이머병의 병리학적 변화를 연구하고 치료 효과를 평가하고자 하였다.
첫 번째로, 공간 전사체학을 기반으로 인지 장애 발생 전과 후의 알츠하이머병 모델을 분석하였다. 알츠하이머병 병리 초기의 백질에서 신경교세포의 활성화가 확인되었다. 병리의 진행에 따라 신경 교세포 활성 관련 유전자들은 백질과 회색질 모두에서 전체적으로 상향 조절되는 경향을 보였다. 반면, 하향 조절되는 유전자 관련 기능은 지역 별로 상이함을 확인하였다. 그에 더하여 선별된 유전자 조합을 사용하여 다양한 뇌세포의 공간 분포를 조사하였다. 백질에서 활성 미세아교세포와 성상 교세포 관련 유전자들의 초기 변화를 확인하였으며, 이는 결국 병리 진행에 따라 회색질로 퍼짐이 확인되었다. 추가적으로, 신경 세포, 대사, 노화, 및 항원 제시 관련 유전자에 대한 변화 분포가 조사되었다.
다음으로, 알츠하이머병 모델에서 Y형 미로 행동 분석을 통해 NK 세포 투여 및 항 CD4 항체에 대한 인지 기능 향상 효과를 확인하였다. NK 세포 치료는 뇌 전반에 걸쳐 신경 교세포 관련 유전자의 감소와 세포 호흡 관련 유전자의 증가를 보였다. 변화되는 세포 시그니처로는 활성 미세아교세포의 회색질에서의 감소와 억제성 신경 세포의 편도체에서의 지역 특이적 감소가 확인되었다. 반면, 항 CD4 항체 주입은 백질에서 지역 특이적으로 시냅스 기능 관련 유전자의 증가가 확인되었지만 효과가 미미했으며 주요 뇌 세포 시그니처의 변화도 유의하게 확인되지 않았다.
종합해 보면, 위 결과를 통해 알츠하이머병의 병리 진행에 따른 뇌 각 영역별 유전자 발현 및 뇌세포 시그니처의 시공각적 변화를 확인할 수 있었다. 두가지 약물 투여를 예로 들어 알츠하이머병 모델에서의 효과를 검증하는 방법으로 공간전사체 분석의 적용 가능성을 보여주었다. 상기 확립된 공간전사체 분석방법을 통해 다양한 질병에 적용하여 더욱 정확하고 종합적으로 질환의 진행 정도 및 치료제에 대한 효능/기전을 검증하는 데 활용될 것으로 기대하고 있다.
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dc.description.tableofcontents1. Introduction 1
1.1 Spatially resolved transcriptomics 1
1.2 Alzheimer's disease 4
1.3 Pathological change of glial cells in AD 6
1.4 AD therapeutics 8
1.5 Final goal of the study 9
2. Methods 11
2.1 Experimental models 11
2.1.1 AD models in different ages 11
2.1.2 Peripheral CD4 T cell blockade in AD model 11
2.1.3 NK cell supplement in AD model 11
2.2 Data Analysis 12
2.2.1 Spatial gene expression library construction 12
2.2.2 Generation of count matrix 13
2.2.3 Spatial transcriptome data: Integration and spot clustering 13
2.2.4 Differential gene expression analysis 14
2.2.5 Gene ontology analysis 15
2.2.6 Marker panel selection and curation 15
2.2.7 Cellular signatures of reference data 15
2.2.8 Spot-based correlation analysis 16
2.2.9 Statistical analysis 16
2.3 Validation 16
2.3.1 Immunofluorescence imaging for tissue sections 16
2.3.2 Behavior analysis, Y-maze 17
2.3.3 NK cell isolation and culture 17
2.3.4 Flow cytometry for NK cell characterization 17
2.3.5 IFN-gamma release assay by ELISA 18
2.3.6 Isolation of samples and live cell dissociation 18
2.3.7 MACS sorting of brain cells 19
2.3.8 Flow cytometry for T cell population identification 20
2.3.9 Statistical analysis 20
3. Results 21
3.1 Age-dependent change in the 5XFAD AD model 21
3.1.1 Analytical workflow for spatial transcriptome data 21
3.1.2 Identifying clusters corresponding to anatomical structures of the brain 24
3.1.3 Investigation of DEGs in the AD model of different ages 28
3.1.3.1 DEGs and related biological pathways in three-month-old AD model 30
3.1.3.2 DEGs and related biological pathways in 7.5-month-old AD model 31
3.1.3.3 Changes by brain regions according to the progression of amyloid pathology in AD model 36
3.1.4 Spatial distribution of diverse cell signatures in the AD model 41
3.1.4.1 Spatial distribution of the subtypes of glial cell signatures in AD model 45
3.1.4.2 Spatial distribution of myeloid and lymphoid cell signatures in AD model 51
3.1.4.3 Spatial distribution of the subclasses of neuronal signatures in AD model 55
3.1.5 Spatial distribution of brain cell state-related signatures in the AD model 59
3.1.5.1 Metabolism and senescence-related signatures 59
3.2 Effect of NK cell supplement administration in the 5XFAD AD model 63
3.2.1 Improvement of behavior function identified via the Y-maze in AD model after administration of NK cell supplements 63
3.2.2 Characterization of isolated mouse splenic NK cells 65
3.2.3 DEGs and related biological pathways after NK cell treatment in the AD model 68
3.2.4 Biological pathways showing changes after NK cell treatment in AD model 73
3.2.5 Changed spatial distribution of major brain cells after NK cell treatment in AD model 76
3.2.6 In vivo SPECT/CT images and biodistribution of 99mTc-HMPAO-NK cells 81
3.3 Effect of anti-CD4 antibody administration in the 5XFAD AD model 84
3.3.1 Improvement of behavior function identified via the Y-maze in the AD model injected with anti-CD4 antibody 84
3.3.2 Changes in each brain region after anti-CD4 antibody treatment in AD model 90
3.3.3 Changed spatial distribution of brain cell signatures after anti-CD4 antibody administration in AD model 94
4. Discussion 98
5. Conclusion 109
6. Reference 110
ABSTRACT in Korean 117
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dc.format.extentx,117-
dc.language.isoeng-
dc.publisher서울대학교 대학원-
dc.subjectSpatialtranscriptomics-
dc.subjectSpatialheterogeneityofbrain-
dc.subjectAlzheimer’sdisease-
dc.subjectBraincellsignatures-
dc.subjectImmunomodulatorydrugs-
dc.subjectNKcells-
dc.subjectCD4Tcells-
dc.subject.ddc610.28-
dc.titleInvestigation of spatial transcriptomic signatures and therapeutic mode of action in Alzheimer's disease mouse model.-
dc.title.alternative알츠하이머병 모델에서 공간 전사체 시그니처 및 치료 작용 원리 규명-
dc.typeThesis-
dc.typeDissertation-
dc.contributor.AlternativeAuthorEun Ji Lee-
dc.contributor.department융합과학기술대학원 분자의학 및 바이오제약학과-
dc.description.degree박사-
dc.date.awarded2022-08-
dc.identifier.uciI804:11032-000000172515-
dc.identifier.holdings000000000048▲000000000055▲000000172515▲-
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