{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T21:37:48Z","timestamp":1793655468306,"version":"4.5.1"},"reference-count":95,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T00:00:00Z","timestamp":1769472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Mol. Biosci."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Metabolic disorders and neurocognitive diseases frequently co-occur, yet the specific mechanisms driving this comorbidity remain elusive. While epidemiological associations are well-documented, the causal links between these conditions are complex and incompletely understood, necessitating a systems-level investigation into their shared biological architecture.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This study integrates large-scale human genetics with experimental\n                      <jats:italic>in vivo<\/jats:italic>\n                      transcriptomics and computational chemistry to elucidate these shared pathways. Specifically, an AD-like murine model was used to experimentally prioritize a core network of 13 dysregulated genes within a pathologically relevant context.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Network-informed Mendelian randomization identified bidirectional causalities, including a 14% elevated dementia risk from type 2 diabetes and protective effects of obesity against parental Alzheimer\u2019s disease (AD). The study identified a signature encompassing key lipid metabolism hubs\n                      <jats:italic>APOE, CLU<\/jats:italic>\n                      , and\n                      <jats:italic>LDLR<\/jats:italic>\n                      . This signature serves as a critical biological filter, anchoring human genetic associations by providing direct evidence of their dysregulation in a neurodegenerative environment. Subsequent chemical enrichment and molecular docking analyses indicated that these experimentally-prioritized targets are engaged by both therapeutic agents (e.g., valproic acid) and environmental toxins (e.g., benzo[a]pyrene).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This multi-modal investigation provides a robust framework that converges on a high-confidence, 13-gene signature of lipid dysregulation as a central mechanistic interface, offering a powerful set of prioritized targets for future functional validation and therapeutic development at the metabolic-neurocognitive nexus.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmolb.2025.1712198","type":"journal-article","created":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T11:32:46Z","timestamp":1769513566000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Integrating causal human genetics and In vivo transcriptomics to uncover a shared lipid-centric architecture in metabolic and neurocognitive disease"],"prefix":"10.3389","volume":"12","author":[{"given":"Yi","family":"Li","sequence":"first","affiliation":[{"name":"School of Life Sciences, Anhui Medical University","place":["Hefei, Anhui, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhu","family":"Ni","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Anhui Medical University","place":["Hefei, Anhui, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Yong","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Anhui Medical University","place":["Hefei, Anhui, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Na","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Anhui Medical University","place":["Hefei, Anhui, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Bo","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Anhui Medical University","place":["Hefei, Anhui, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junwen","family":"He","sequence":"additional","affiliation":[{"name":"College of Informatics, Huazhong Agricultural University","place":["Wuhan, Hubei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"He","sequence":"additional","affiliation":[{"name":"College of Informatics, Huazhong Agricultural University","place":["Wuhan, Hubei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang-Yu","family":"Meng","sequence":"additional","affiliation":[{"name":"Health Science Center, Medical School, Hubei Minzu University","place":["Enshi, Hubei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Anhui Medical University","place":["Hefei, Anhui, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Anhui Medical University","place":["Hefei, Anhui, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,1,27]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"118070","DOI":"10.1016\/j.lfs.2020.118070","article-title":"The role of KATP channel blockade and activation in the protection against neurodegeneration in the rotenone model of Parkinson\u2019s disease","volume":"257","author":"Abdelkader","year":"2020","journal-title":"Life Sci."},{"key":"B2","doi-asserted-by":"publisher","first-page":"2024.06.17.599125","DOI":"10.1101\/2024.06.17.599125","article-title":"A Multi-Omics approach to defining target organ injury in youth with primary hypertension","volume":"2024","author":"Ananthamohan","year":"2024","journal-title":"bioRxiv"},{"key":"B3","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1002\/ana.25918","article-title":"Causal associations between modifiable risk factors and the Alzheimer\u2019s phenome","volume":"89","author":"Andrews","year":"2021","journal-title":"Ann. 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