{"id":{"repo_id":"penn","oai_identifier":"oai:repository.upenn.edu:20.500.14332/61383"},"canonical_url":"https://search.dev.ndltd.org/etd/penn/oai:repository.upenn.edu:20.500.14332/61383","repository":{"repo_id":"penn","name":"University of Pennsylvania","base_url":"https://repository.upenn.edu/server/oai/request"},"display":{"title":"Uncovering Functional Alzheimer’s Disease Variants and Their Effector Genes through Single-Cell CRISPRi Screening and 3D Genomics","abstract":"While genome-wide association studies (GWAS) have successfully linked variants to traits in complex human diseases, functional dissection of the discovered loci has lagged behind. We address this gap in the context of Alzheimer’s disease (AD) by performing variant-to-gene (V2G) mapping to implicate causal variants and effector genes from the latest AD GWAS meta-analyses that report 101 loci. Our V2G mapping was performed using three major approaches. First, we performed physical fine-mapping of GWAS variants by leveraging our genomics datasets comprising ATAC-seq, RNA-seq, and high-resolution promoter-focused Capture C from brain-relevant cell models. We identified 89 candidate causal SNPs and 69 effector genes. Second, we designed a single-cell CRISPRi screen to perturb 74 candidate regulatory regions and assessed their transcriptional response in the human microglial cell line, HMC3. We collected 96,639 single cells and identified 19 regulatory regions with 19 corresponding effector genes. Lastly, we functionally dissected our top hit, a locus linked to TSPAN14, and showed that an intronic region containing the AD-associated SNPs rs7080009, rs1870138, and rs1870137 is a microglia-specific enhancer, where the AD risk haplotype showed increased enhancer activity. Excising this region using CRISPR-Cas9 demonstrated decreased TSPAN14 expression, downregulated pathways related to cell adhesion, and decreased levels of secreted pro-inflammatory cytokines IL-6 and IL-8 — known biomarkers of AD and aging. This work provides a systematic framework to map GWAS signals to their effector genes for AD and other brain-related disorders and results in robust leads for follow-up with in-depth functional investigations.","abstract_html":"While genome-wide association studies (GWAS) have successfully linked variants to traits in complex human diseases, functional dissection of the discovered loci has lagged behind. We address this gap in the context of Alzheimer’s disease (AD) by performing variant-to-gene (V2G) mapping to implicate causal variants and effector genes from the latest AD GWAS meta-analyses that report 101 loci. Our V2G mapping was performed using three major approaches. First, we performed physical fine-mapping of GWAS variants by leveraging our genomics datasets comprising ATAC-seq, RNA-seq, and high-resolution promoter-focused Capture C from brain-relevant cell models. We identified 89 candidate causal SNPs and 69 effector genes. Second, we designed a single-cell CRISPRi screen to perturb 74 candidate regulatory regions and assessed their transcriptional response in the human microglial cell line, HMC3. We collected 96,639 single cells and identified 19 regulatory regions with 19 corresponding effector genes. Lastly, we functionally dissected our top hit, a locus linked to TSPAN14, and showed that an intronic region containing the AD-associated SNPs rs7080009, rs1870138, and rs1870137 is a microglia-specific enhancer, where the AD risk haplotype showed increased enhancer activity. Excising this region using CRISPR-Cas9 demonstrated decreased TSPAN14 expression, downregulated pathways related to cell adhesion, and decreased levels of secreted pro-inflammatory cytokines IL-6 and IL-8 — known biomarkers of AD and aging. This work provides a systematic framework to map GWAS signals to their effector genes for AD and other brain-related disorders and results in robust leads for follow-up with in-depth functional investigations.","abstract_has_math":false,"creators":["Laub, Shannon"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Chesi, Alessandra"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025","date_published":"2025","updated_at":"2026-07-24T03:47:17Z","subjects":["Engineering","Genetics and Genomics","Neuroscience and Neurobiology"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://repository.upenn.edu/handle/20.500.14332/61383","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Chesi, Alessandra"]},{"key":"dc:creator","label":"Author","values":["Laub, Shannon"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-06-11T19:17:27Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-06-11T19:17:27Z"]},{"key":"dc:date.issued","label":"Date","values":["2025"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation/Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering","Genetics and Genomics","Neuroscience and Neurobiology"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://repository.upenn.edu/handle/20.500.14332/61383"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["While genome-wide association studies (GWAS) have successfully linked variants to traits in complex human diseases, functional dissection of the discovered loci has lagged behind. We address this gap in the context of Alzheimer’s disease (AD) by performing variant-to-gene (V2G) mapping to implicate causal variants and effector genes from the latest AD GWAS meta-analyses that report 101 loci. Our V2G mapping was performed using three major approaches. First, we performed physical fine-mapping of GWAS variants by leveraging our genomics datasets comprising ATAC-seq, RNA-seq, and high-resolution promoter-focused Capture C from brain-relevant cell models. We identified 89 candidate causal SNPs and 69 effector genes. Second, we designed a single-cell CRISPRi screen to perturb 74 candidate regulatory regions and assessed their transcriptional response in the human microglial cell line, HMC3. We collected 96,639 single cells and identified 19 regulatory regions with 19 corresponding effector genes. Lastly, we functionally dissected our top hit, a locus linked to TSPAN14, and showed that an intronic region containing the AD-associated SNPs rs7080009, rs1870138, and rs1870137 is a microglia-specific enhancer, where the AD risk haplotype showed increased enhancer activity. Excising this region using CRISPR-Cas9 demonstrated decreased TSPAN14 expression, downregulated pathways related to cell adhesion, and decreased levels of secreted pro-inflammatory cytokines IL-6 and IL-8 — known biomarkers of AD and aging. This work provides a systematic framework to map GWAS signals to their effector genes for AD and other brain-related disorders and results in robust leads for follow-up with in-depth functional investigations."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Doctor of Philosophy (PhD)"]},{"key":"dc:title","label":"Title","values":["Uncovering Functional Alzheimer’s Disease Variants and Their Effector Genes through Single-Cell CRISPRi Screening and 3D Genomics"]}]}],"canonical_facts":{"dc:contributor.advisor":["Chesi, Alessandra"],"dc:creator":["Laub, Shannon"],"dc:date.accessioned":["2025-06-11T19:17:27Z"],"dc:date.available":["2025-06-11T19:17:27Z"],"dc:date.issued":["2025"],"dc:description.abstract":["While genome-wide association studies (GWAS) have successfully linked variants to traits in complex human diseases, functional dissection of the discovered loci has lagged behind. We address this gap in the context of Alzheimer’s disease (AD) by performing variant-to-gene (V2G) mapping to implicate causal variants and effector genes from the latest AD GWAS meta-analyses that report 101 loci. Our V2G mapping was performed using three major approaches. First, we performed physical fine-mapping of GWAS variants by leveraging our genomics datasets comprising ATAC-seq, RNA-seq, and high-resolution promoter-focused Capture C from brain-relevant cell models. We identified 89 candidate causal SNPs and 69 effector genes. Second, we designed a single-cell CRISPRi screen to perturb 74 candidate regulatory regions and assessed their transcriptional response in the human microglial cell line, HMC3. We collected 96,639 single cells and identified 19 regulatory regions with 19 corresponding effector genes. Lastly, we functionally dissected our top hit, a locus linked to TSPAN14, and showed that an intronic region containing the AD-associated SNPs rs7080009, rs1870138, and rs1870137 is a microglia-specific enhancer, where the AD risk haplotype showed increased enhancer activity. Excising this region using CRISPR-Cas9 demonstrated decreased TSPAN14 expression, downregulated pathways related to cell adhesion, and decreased levels of secreted pro-inflammatory cytokines IL-6 and IL-8 — known biomarkers of AD and aging. This work provides a systematic framework to map GWAS signals to their effector genes for AD and other brain-related disorders and results in robust leads for follow-up with in-depth functional investigations."],"dc:description.degree":["Doctor of Philosophy (PhD)"],"dc:identifier.uri":["https://repository.upenn.edu/handle/20.500.14332/61383"],"dc:language.iso":["en"],"dc:subject":["Engineering","Genetics and Genomics","Neuroscience and Neurobiology"],"dc:title":["Uncovering Functional Alzheimer’s Disease Variants and Their Effector Genes through Single-Cell CRISPRi Screening and 3D Genomics"],"dc:type":["Dissertation/Thesis"]},"updated_at":"2026-07-24T03:47:17Z"}