{"doi":"10.1002/alz.71203","title":"Spatially and temporally progressive hypoperfusion in Alzheimer's disease revealed by normative modeling","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:sec>\n                    <jats:title>INTRODUCTION</jats:title>\n                    <jats:p>Cerebral perfusion is implicated in Alzheimer's disease (AD), but its development in AD and mild cognitive impairment (MCI) is not well characterized.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS</jats:title>\n                    <jats:p>\n                      We constructed a normative model using &gt; 12,000 arterial spin labeling MRI scans and applied generalized additive models for location, scale, and shape (GAMLSS). Individual deviation\n                      <jats:italic>z</jats:italic>\n                      scores were derived by normative model, and outlier regions (\n                      <jats:italic>z</jats:italic>\n                       \n                      <jats:bold>≤ </jats:bold>\n                      2.3) were quantified as the total negative proportion (TNP) of extreme hypoperfusion. These metrics were then related to other AD biomarkers through linear modeling.\n                    </jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS</jats:title>\n                    <jats:p>\n                      Compared to cognitively normal controls, AD showed higher TNP and greater longitudinal increases (\n                      <jats:italic>p</jats:italic>\n                       = 0.003), indicating progressive hypoperfusion. Progressive MCI exhibited greater perfusion decline than stable MCI (\n                      <jats:italic>p</jats:italic>\n                       = 0.01). Perfusion changes correlated with cognition, brain volume, amyloid, and apolipoprotein E status (all\n                      <jats:italic>p</jats:italic>\n                       &lt; 0.05).\n                    </jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION</jats:title>\n                    <jats:p>Normative modeling revealed inter‐individual heterogeneity in cerebral perfusion trajectories, underscoring its potential relevance for AD development.</jats:p>\n                  </jats:sec>","journal":"Alzheimer's &amp; Dementia","year":2026,"id":609432,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":908240,"name":"Yiran Li","orcid":"0000-0002-4658-3876","position":1,"is_corresponding":false},{"id":1438943,"name":"Lin Hua","orcid":"0000-0001-6309-3572","position":2,"is_corresponding":false},{"id":1566402,"name":"Ruoxi Lu","orcid":null,"position":3,"is_corresponding":false},{"id":1566403,"name":"Lucas Lemos Franco","orcid":null,"position":4,"is_corresponding":false},{"id":227759,"name":"Peter Kochunov","orcid":"0000-0003-3656-4281","position":5,"is_corresponding":false},{"id":702194,"name":"Shuo Chen","orcid":"0000-0002-7145-1269","position":6,"is_corresponding":false},{"id":301392,"name":"John A. Detre","orcid":"0000-0002-8115-6343","position":7,"is_corresponding":false},{"id":290832,"name":"Ze Wang","orcid":"0000-0002-8339-5567","position":8,"is_corresponding":false},{"id":1152560,"name":"Xinglin Zeng","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Spatially and temporally progressive hypoperfusion in Alzheimer's disease revealed by normative modeling","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:sec>\n                    <jats:title>INTRODUCTION</jats:title>\n                    <jats:p>Cerebral perfusion is implicated in Alzheimer's disease (AD), but its development in AD and mild cognitive impairment (MCI) is not well characterized.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS</jats:title>\n                    <jats:p>\n                      We constructed a normative model using &gt; 12,000 arterial spin labeling MRI scans and applied generalized additive models for location, scale, and shape (GAMLSS). Individual deviation\n                      <jats:italic>z</jats:italic>\n                      scores were derived by normative model, and outlier regions (\n                      <jats:italic>z</jats:italic>\n                       \n                      <jats:bold>≤ </jats:bold>\n                      2.3) were quantified as the total negative proportion (TNP) of extreme hypoperfusion. These metrics were then related to other AD biomarkers through linear modeling.\n                    </jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS</jats:title>\n                    <jats:p>\n                      Compared to cognitively normal controls, AD showed higher TNP and greater longitudinal increases (\n                      <jats:italic>p</jats:italic>\n                       = 0.003), indicating progressive hypoperfusion. Progressive MCI exhibited greater perfusion decline than stable MCI (\n                      <jats:italic>p</jats:italic>\n                       = 0.01). Perfusion changes correlated with cognition, brain volume, amyloid, and apolipoprotein E status (all\n                      <jats:italic>p</jats:italic>\n                       &lt; 0.05).\n                    </jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION</jats:title>\n                    <jats:p>Normative modeling revealed inter‐individual heterogeneity in cerebral perfusion trajectories, underscoring its potential relevance for AD development.</jats:p>\n                  </jats:sec>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21097893","pmcid":null,"openalex_id":null,"authors":[],"funders":[{"funder_name":"National Institute on Aging","grant_id":"R01AG081693","title":null},{"funder_name":"National Institute on Aging","grant_id":"R01AG070227","title":null},{"funder_name":"National Institute on Aging","grant_id":"R33AG080518","title":null},{"funder_name":"Institute for Clinical and Translational Research, University of Maryland, Baltimore","grant_id":"1UL1TR003098","title":null}],"total_grants":4,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"hybrid","license":"cc-by-nc-nd","oa_locations":[{"url":"https://doi.org/10.1002/alz.71203","host_type":"publisher"},{"url":"https://alz-journals.onlinelibrary.wiley.com/doi/pdf/10.1002/alz.71203","host_type":"publisher"},{"url":"https://alz-journals.onlinelibrary.wiley.com/doi/full-xml/10.1002/alz.71203","host_type":"publisher"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13093283/","host_type":"repository"}],"fields_of_study":[],"mesh_terms":[],"keywords":[],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-31T07:47:59.642301Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}