{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T18:23:07Z","timestamp":1793125387463,"version":"4.5.0"},"reference-count":139,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T00:00:00Z","timestamp":1762387200000},"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. Aging Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>The review discusses the effect of biological determinants such as nutritional deficiency, systemic inflammation, and metabolic disorders affect blood-based biomarker (BBBM) levels, influencing their use in diagnosing, prognosticating, and treatment in Alzheimer\u2019s disease (AD). While the individual contributions of neuroinflammation, brain insulin resistance, and micronutrient deficiencies to AD pathology are well-established, a significant knowledge gap exists in understanding their intricate, synergistic interactions. This review proposes a novel integrated framework of bidirectional crosstalk where these three factors create a self-perpetuating cycle of neurodegeneration.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A comprehensive literature review was conducted, including all aspects of epidemiological and biological context associated with vitamins, micronutrients, and dietary patterns; inflammatory cytokines; insulin resistance; metabolic syndrome; and hormonal changes. Emerging integrative approaches such as multi-omics, AI modeling, and systems biology were also reviewed for their possible refinement in biomarker interpretation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The results prove that the deprivation of vitamins E, D, B12, and antioxidants contributes to oxidative stress and subsequent neuroinflammation that changes levels of blood-based biomarkers. A chronic state of inflammation caused by cytokines like IL-6, IL-18, and TNF-\u03b1 represents a major link to the formation of increased amyloid plaques and tau tangles. Metabolically deregulated states, such as insulin resistance, dyslipidemia, and thyroid imbalance, further alter variability in biomarkers. All these factors would act together to affect the expression of key biomarkers-A\u03b2, p-tau, and neurofilament light chain (NFL). Individualized interpretation, stratified clinical trials, and digital monitoring tools are potentially effective for achieving better diagnostic precision and boosting treatment efficacy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>To a large extent, factors must all be understood thoroughly from multiple biological angles to improve early diagnosis, risk prevention, and treatment personalization in AD. Future studies should develop integrative models that consider nutrition, metabolism, and inflammation to address and fully exploit biomarker utility as well as support precision medicine approaches.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnagi.2025.1614962","type":"journal-article","created":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T12:53:49Z","timestamp":1762433629000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Biological determinants of blood-based biomarker levels in Alzheimer\u2019s disease: role of nutrition, inflammation, and metabolic factors"],"prefix":"10.3389","volume":"17","author":[{"given":"Aparna","family":"Inamdar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Parashuram","family":"Bugadannavar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahesh","family":"Palled","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Savita","family":"Umarani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Preeti","family":"Salve","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bannimath","family":"Gurupadayya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priyanka","family":"Patil","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Himanshu","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,11,6]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e208054","DOI":"10.1212\/WNL.0000000000208054","article-title":"Contribution of global amyloid-PET imaging for predicting future cognition in the MEMENTO cohort","volume":"102","author":"Ackley","year":"2024","journal-title":"Neurology"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1215663","DOI":"10.3389\/fmed.2023.1215663","article-title":"Patients\u2019 perspectives related to ethical issues and risks in precision medicine: a systematic review","volume":"10","author":"Ahmed","year":"2023","journal-title":"Front. 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