{"doi":"10.1371/journal.pcbi.1009903","title":"Mapping the gene network landscape of Alzheimer’s disease through integrating genomics and transcriptomics","abstract":"Integration of multi-omics data with molecular interaction networks enables elucidation of the pathophysiology of Alzheimer's disease (AD). Using the latest genome-wide association studies (GWAS) including proxy cases and the STRING interactome, we identified an AD network of 142 risk genes and 646 network-proximal genes, many of which were linked to synaptic functions annotated by mouse knockout data. The proximal genes were confirmed to be enriched in a replication GWAS of autopsy-documented cases. By integrating the AD gene network with transcriptomic data of AD and healthy temporal cortices, we identified 17 gene clusters of pathways, such as up-regulated complement activation and lipid metabolism, down-regulated cholinergic activity, and dysregulated RNA metabolism and proteostasis. The relationships among these pathways were further organized by a hierarchy of the AD network pinpointing major parent nodes in graph structure including endocytosis and immune reaction. Control analyses were performed using transcriptomics from cerebellum and a brain-specific interactome. Further integration with cell-specific RNA sequencing data demonstrated genes in our clusters of immunoregulation and complement activation were highly expressed in microglia.","journal":"PLoS Computational Biology","year":2022,"id":269169,"datarank":0.7048425252123321,"base_score":2.833213344056216,"endowment":2.833213344056216,"self_citation_contribution":0.42498200160843247,"citation_network_contribution":0.2798605236038997,"self_endowment_contribution":0.42498200160843247,"citer_contribution":0.2798605236038997,"corpus_percentile":71.61754467393827,"corpus_rank":3670,"citation_count":16,"citer_count":16,"citers_with_citation_signal":15,"citers_with_endowment":15,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7613,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":66.6667,"fair_percentile":86.48731274839498,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":795383,"name":"Hao Wang","orcid":"0000-0002-1518-9702","position":1,"is_corresponding":false},{"id":307458,"name":"Da Shi","orcid":"0000-0002-1953-2299","position":2,"is_corresponding":false},{"id":854931,"name":"Cin Liu","orcid":"0000-0002-9178-1433","position":3,"is_corresponding":false},{"id":307460,"name":"Ruben Abagyan","orcid":"0000-0001-9309-2976","position":4,"is_corresponding":false},{"id":306871,"name":"Linda K. McEvoy","orcid":"0000-0003-4583-7798","position":5,"is_corresponding":false},{"id":795384,"name":"Chi‐Hua Chen","orcid":"0000-0001-5318-047X","position":6,"is_corresponding":false},{"id":103666,"name":"Sara Brin Rosenthal","orcid":"0000-0002-9072-8032","position":0,"is_corresponding":true}],"reference_count":79,"raw_metadata":null,"created_at":"2026-07-19T00:27:18.142851Z","pmid":"35213535","pmcid":"PMC8906581","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":83.3333,"fair_a":62.5,"fair_i":0.0,"fair_r":41.6667,"fair_zscore":1.2752,"fair_rationale":{"fair_score":66.67,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":83.33,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"10.5281/zenodo.5786722","grounded":true,"rationale":"The paper provides a DOI for its own dataset via Zenodo.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"All relevant data are within the paper, its Supporting Information files, and on Zenodo at https://zenodo.org/record/5786722#.Ybtti73MKC8 (DOI: 10.5281/zenodo.5786722 ).","grounded":true,"rationale":"Zenodo is a named data repository.","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"All relevant data are within the paper, its Supporting Information files, and on Zenodo at https://zenodo.org/record/5786722#.Ybtti73MKC8 (DOI: 10.5281/zenodo.5786722 ).","grounded":true,"rationale":"The statement points to a repository record (Zenodo with a DOI), which is Colavizza category 3.","anchors":["Colavizza, Hrynaszkiewicz, Staden, Whitaker & McGillivray (2020), 'The citation advantage of li","Springer Nature research data policy — Data Availability Statements: standard statement templat","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes"],"scored":false,"signal":null},{"key":"f_discovery_metadata","label":"Description of the dataset as an object","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"All relevant data are within the paper, its Supporting Information files, and on Zenodo at https://zenodo.org/record/5786722#.Ybtti73MKC8 (DOI: 10.5281/zenodo.5786722 ).","grounded":true,"rationale":"The dataset's content is described only in a generic sentence, not in an itemised inventory. 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A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not provide a persistent identifier (DOI, accession, RRID) for any external resource it uses (e.g., the GWAS summary statistics, the STRING database, the Mayo Clinic RNAseq data). [majority verdict 'no' (3/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No sentence states when the data are available or how long they persist. [majority verdict 'no' (3/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable.","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. 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