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Hyperglycemic Neurodegeneration: The Molecular Pathophysiology of Glucose-Induced Alzheimer’s Disease Risk

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dr. Karunia Valeriani Japar

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Reviewed by dr. Hendy Million Samin, Sp.S, M.Biomed

Introduction

Elevated blood glucose levels have been increasingly recognized as a critical risk factor in the pathogenesis of Alzheimer’s disease (AD), with mounting evidence linking metabolic dysregulation and impaired glucose metabolism to accelerated neurodegeneration and cognitive decline. Epidemiological studies demonstrate that individuals with diabetes or persistent hyperglycemia have a significantly higher probability of developing Alzheimer’s, suggesting that abnormal glucose homeostasis may represent a modifiable risk for dementia. The underlying mechanisms appear multifactorial, involving chronic neuroinflammation, increased oxidative stress, protein glycation, and insulin resistance, all of which converge to promote amyloid-beta accumulation, tau hyperphosphorylation, and vascular damage within the aging brain. Recent translational research has revealed that excess glucose may directly damage key enzymes responsible for neuronal resilience and immune regulation, while also driving metabolic shifts that impair proteostasis and synaptic function. Collectively, these findings underscore the urgent need for targeted metabolic interventions to mitigate the escalating social and economic burden of AD as global rates of diabetes and hyperglycemia continue to rise [1,2,3,4,5,6,7].

Epidemiology: Hyperglycemia and Alzheimer’s Disease Risk

Extensive epidemiological research has established hyperglycemia- a state of chronically elevated blood glucose- as a significant and modifiable risk factor for the development of AD. Population-based studies show that individuals with diabetes, impaired fasting glucose, or higher post prandial glucose excursions experience a markedly increased incidence of dementia and AD compared with normoglycemic controls. For example, meta-analyses and longitudinal data indicate that diabetes confers a 50-73% higher relative risk for all-cause dementia, with AD risk rising in parallel with measures of chronic glycemic control such as elevated Haemoglobin A1c (HbA1c) or glycemic variability [2,8,9,10,11,12,13].

Prospective cohort studies have demonstrated a stepwise association between glucose status and dementia: higher post load glucose levels on oral glucose tolerance tests are predictive of increased AD risk and hippocampal atrophy, while even mild hyperglycemia is linked to lower cognitive performance and greater neurodegenerative burden. Notably, glucose fluctuations-independent of mean fasting glucose- also correlate with the probability of dementia, reinforcing the role of metabolic instability in age-related cognitive impairment [2,9,10,12,13].

Global analyses reveal that regions with rising rates of diabetes and hyperglycemia are experiencing parallel growth in AD incidence and disease burden. Importantly, targeted intervention studies show that optimal glycemic control (HbA1c between 6.5-7.5%) is associated with lower dementia risk, supporting the notion that metabolic regulation can meaningfully reduce the impact of AD on aging populations. Collectively, these findings underscore hyperglycemia as a major, preventable epidemiological driver of AD, highlighting the urgent need for improved screening and interventions in metabolic health [8,9,10,11,12,14,15].

Pathophysiology: Glucose Metabolism Dysregulation in Alzheimer’s

Glucose metabolism dysregulation is a central pathological feature of AD, reflecting impaired energy supply and altered signaling within the brain that precede clinical cognitive decline. In the healthy brain, glucose is transported from the blood via glucose transporter proteins (GLUTs)- primarily GLUT1, GLUT3, and GLUT4- with insulin facilitating optimal neuronal uptake and utilization. AD brains exhibit significant reductions in GLUT1 and GLUT3 expression and activity, resulting in marked cerebral hypometabolism and lower regional glucose utilization, particularly in the frontal, parietotemporal, and cingulate cortices-areas highly vulnerable to neurodegeneration [1,16,17,18,19,20,21].

Insulin resistance further aggravates this metabolic dysfunction: reduced responsiveness to insulin impairs glucose uptake, disrupts Insulin Receptor Substrate (IRS)/ Phosphoinositide-3-kinase (PI3K)/Protein Kinase B (Akt) signaling, and decreases translocation of GLUT4 to neuronal membranes. This leads to chronic mitochondrial dysfunction-characterized by abnormal fusion/division, mtDNA mutations, and oxidative phosphorylation defects-that promotes cellular energy deficits and increases the production of reactive oxygen species and advanced glycation end-products (AGEs), both of which contribute to amyloid-beta accumulation and tau hyperphosphorylation [1,16,17,19,20,21,22].

Aberrant glycolytic and TC cycle enzymes- such as hexokinase, phosphofructokinase, and triose-phosphate isomerase-are also reduced or dysfunctional in AD, further limiting glucose-driven Adenosine trisphosphate (ATP) production. Age-associated increases in lactate dehydrogenase activity and shifts toward abnormal glycolytic pathways decrease pyruvate levels, disrupt antioxidant defense systems, and exacerbate protein misfolding and neuroinflammation. Collectively, these molecular cascades underlie the profound bioenergetic crisis and progressive synaptic loss observed in AD, establishing glucose metabolism dysregulation as a mechanistic driver with direct therapeutic implications [17,18,19,20,21,22,23].

Figure 1. Dysfunctional Cerebral Glucose Metabolism in AD Development [1]

Mechanistic Insights: Insulin Resistance and Neurodegeneration

Insulin resistance, characterized by impaired insulin signaling in the brain, plays a pivotal role in promoting neurodegeneration and the progression of AD. Normally, insulin regulates neuronal glucose uptake and energy metabolism, as well as synaptic plasticity, learning, and memory through activation of insulin resistance lead to reduced insulin receptor density and blunted receptor activity, resulting in diminished PI3K-Akt pathway signaling, impaired glucose transporter function (e.g., GLUT4), and overall metabolic deficits within neural tissue [24,25,26,27,28,29].

Figure 2. Simplified mechanism of insulin resistance-induced Alzheimer’s disease [25]

Mechanistically, insulin resistance triggers a cascade of deleterious cellular events: the reduction in Akt activity releases inhibition on glycogen synthase kinase -3b (GSK-3b), a key kinase that phosphorylates tau protein and drives the formation of neurofibrillary tangles, a hallmark of AD pathology. Impaired insulin signaling also facilitates the accumulation of amyloid-beta (Aβ) plaques by decreasing the activity of insulin-degrading enzyme (IDE), which normally helps clear Aβ from the brain. This dual accumulation of hyperphosphorylated tau and Ab initiate neuroinflammatory responses and oxidative stress, further contributing to synaptic dysfunction, cytoskeletal collapse, and neuronal apoptosis [24,26,28,29,30,31].

Emerging research describes a “feed-forward” loop wherein insulin resistance aggravates AD neuropathology, while AD-associated inflammation and metabolic stress further intensify insulin signaling deficits- a cycle that underlies the progressive nature of neurodegeneration in AD. Collectively, these mechanistic insights establish brain insulin resistance as a central driver of neurodegeneration and cognitive decline in AD, highlighting its potential as a therapeutic target for disease modification and prevention [24,26,27,28,29,31].

Molecular Pathways: Amyloid-beta, Tau, and Metabolic Stress

Alzheimer’s disease is characterized by a complex interplay of molecular events, with Aβ peptides, tau protein abnormalities, and metabolic stress forming a pathological triad central to neurodegeneration. The amyloidogenic pathway initiates with the abnormal cleavage of amyloid precursor protein (APP) by β-secretase and χ-secretase, producing Aβ peptides that aggregate into oligomers and fibrils, culminating in extracellular plaques. These Aβ aggregates impair synaptic transmission, trigger microglial activation and promote neuroinflammatory cascades, ultimately driving neuronal death [32,33,34,35,36,37,38].

Concurrent with amyloid pathology, tau-a microtubule-associated protein-undergoes excessive phosphorylation due to dysregulation of kinases such as GSK-3b and Cyclin-dependent kinase 5 (CDK5), often exacerbated by upstream metabolic and inflammatory signals. Hyperphosphorylated tau dissociates from microtubules, aggregates into neurofibrillary tangles (NFTs), and disrupts axonal transport. This process is toxic to neurons, amplifies oxidative stress, and is tightly linked to memory loss and cognitive impairment in AD [39,40,41,42].

Figure 3. Proposed mechanism of neurofibrillary degeneration [39]

Metabolic stress further intensifies these molecular insults. Impaired glucose metabolism and mitochondrial dysfunction lead to energy deficits and increased reactive oxygen species (ROS) generation. These metabolic derangements promote both Aβ accumulation and tau hyperphosphorylation, while perpetuating chronic neuroinflammation and ER stress-a feed-forward loop accelerating synaptic loss and neurodegeneration. Metal dyshomeostasis, lipid peroxidation, and protein oxidation further aggravate cellular vulnerability, consolidating the role of metabolic stress as a co-contributor to AD’s molecular pathology [33,36,40,43,44,45].

Collectively, interactions among Aβ aggregation, tau pathology, and metabolic stress comprise the mechanistic foundation of AD, providing crucial targets for therapeutic intervention and biomarker discovery [33,36,40,43,44,45].

Chronic Inflammation and Oxidative Stress in Hyperglycemia

Chronic inflammation and oxidative stress are key mediators in the neuropathological consequences of hyperglycemia, driving both vascular and neuronal damage relevant to AD. Hyperglycemia triggers a sustained proinflammatory response via activation of pathways such as nuclear factor-kappa B (NF-kB), leading to enhanced production of cytokines including Tumor Necrosis Factor alpha (TNF-α), Interleukin 6 (IL-6), and Interleukin-1 beta (IL-1b), which disrupt the blood-brain barrier (BBB), activate microglia and astrocytes, and reinforce neuroinflammatory cycles. Receptors for advanced glycation end-products (RAGE) signaling becomes prominent; this receptor binds to AGEs formed during prolonged hyperglycemia and Aβ peptides, amplifying cytokine release and facilitating amyloidogenic processes [46,47,48,49,50,51].

Parallel to inflammation, excess glucose fuels the generation of ROS, overwhelming antioxidant defenses and provoking mitochondrial dysfunction. Lipid peroxidation, protein oxidation, and AGE formation impair neuronal membranes and synaptic machinery, directly contributing to neurodegeneration. The diabetic brain’s vulnerability to oxidative insults stems from its high oxygen consumption, low antioxidant reserves, and robust metabolic demands. Oxidative stress activates redox-sensitive inflammasomes and kinases such as c-Jun N-terminal kinase (JNK) and Mitogen-Activated Protein Kinase (MAPKs), afterward stimulating apoptosis and impairing neurogenesis in regions critical for cognition, including the hippocampus and prefrontal cortex [48,49,50,52,53,54].

Figure 4. Mechanisms behind the relationship between diabetic encelopathy and brain oxidative stress [54]

This chronic exposure to. Metabolic, inflammatory, and oxidative stressors in the setting of diabetes or persistent hyperglycemia sets up a vicious cycle: inflammation further stimulates ROS production, and oxidative stress in turn accentuates cytokine release and endothelial dysfunction. Together, these processes potentiate BBB disruption, glial activation, and synaptic loss, directly linking disturbed glucose metabolism to cognitive decline and AD risk [46,47,51,52,53,54].

Brain Structural and Functional Changes Linked to Metabolic Syndrome

Metabolic syndrome (MetS)- defined by the constellation of central obesity, hypertension, dyslipidemia, and insulin resistance-has substantial negative effects on both the structural and functional integrity of the brain. High-resolution neuroimaging studies reveal reductions in gray matter volume in regions such as the medial frontal gyrus, anterior cingulate cortex, thalamus, and hippocampus, as well as abnormal increases in select subcortical areas among individuals with MetS. White matter abnormalities reduced microstructural integrity and increased white matter hyperintensity (WMH) load- are consistently observed, which correlate with impaired cognitive processing speed and memory [55,56,57,58,59,60,61].

On the functional level, MetS is associated with decreased global and regional connectivity between core brain networks, including disruptions in the default mode, frontoparietal and attentional circuits. Resting-state functional Magnetic Resonance Imaging (fMRI)  indicates altered network synchrony and attenuated activation within domains linked to executive function, reward, decision-making, and working memory. Metabolic perturbations drive microvascular dysfunction, chronic neuroinflammation, and persistent oxidative stress, resulting in diminished oxygen and nutrient supply to critical neuronal population and further accelerating atrophy and functional decline [57,58,60,61,62,63,64,65].

Moreover, cognitive changes linked to MetS encompass lower memory function, reduced attention and psychomotor coordination, slowed motor speed, and impaired decision-making capacity. These deficits reflect both local tissue loss and widespread network dysfunction, partnering with metabolic and vascular risk factors to heighten the likelihood of dementia syndromes including AD. Collectively, these findings underscore the major impact of MetS on brain aging, cognition, and neurodegenerative trajectory [66].

Diagnostic Biomarkers: Glucose Indices in Dementia Prediction

Glucose metabolic indices-including fasting plasma glucose, HbA1c, and composite markers such as the triglyceride-glucose (TyG) index-are increasingly recognized as diagnostic biomarkers for dementia prediction, providing mechanistic and prognostic insight into the link between glycemic dysregulation and cognitive decline [12,67,68,69,70,71].

Diagnostic Value of Glucose Indices

Elevated fasting plasma glucose and sustained hyperglycemia are associated with higher risk of mild cognitive impairment (MCI) and progression to dementia, with binary logistic regression analysis revealing increased odds ratios for cognitive decline in individuals with abnormal glucose levels. The TyG index, a proxy for insulin resistance calculated from triglyceride and glucose measurements, has emerged as a robust marker; longitudinal studies demonstrate a 4-fold risk of rapid cognitive decline in early-stage Alzheimer’s patients with high TyG levels, correlating with steeper drops in Mini Mnetal State Examination (MMSE) score per year. HbA1c, reflecting average glycemia over time, demonstrate a U-shaped association: both elevated and excessively low levels are associated with increased dementia risk, due to contributions from chronic hyperglycemia and frequent hypoglycemic events. Increased HbA1c variability also predicts higher risk, independent of baseline glycemic control [12,67,68,69,70].

Pathophysiological Mechanisms

Chronic hyperglycemia induces oxidative stress, formation of AGEs, vascular injury, and neuroinflammation, all of which accelerate neuronal damage and cognitive deficits. Insulin resistance disrupts neuronal insulin signaling, impairs glucose uptake, and reduces neuroplasticity. These disruptions often precede clinical dementia by decades, with subclinical abnormalities in glucose metabolism detectable in at risk populations long before symptom onset. The TyG index and related composite measures also predict amyloid and tau burden in Alzheimer’s disease, providing a mechanistic link to neurodegeneration and disease progression [68,69,71,72,73,74].

Clinical Implications

Early identification of individuals with abnormal glucose indices enables risk stratification and focused prevention efforts for dementia. Incorporation of glucose biomarkers into clinical algorithms improves predictive accuracy compared to reliance on traditional risk factors alone. Emerging evidence suggests practical utility in routine screening for fasting glucose, HbA1c, and TyG index for dementia risk assessment, particularly in populations with diabetes, metabolic syndrome, or increased cardiovascular risk [12,68,69,70].

The Concept of “Type 3 Diabetes” in Alzheimer’s Disease

The concept of  “type 3 diabetes” is used to describe AD as a brain-specific form of diabetes that arises from insulin resistance and impaired insulin signaling within the central nervous system, independent that metabolic, molecular, and histopathological features of AD overlap with those of diabetes, but are localized to the brain [75,76,77,78].

Molecular and Pathological Basis

In AD, there is marked reduction in the expression of insulin insulin-like growth factors (IGF-1, IGF-2), and their receptors in the brain-even in patients without systemic diabetes. This leads to significant disruptions of insulin- and IGF-1 mediated neuronal survival pathways, energy metabolism, tau phosphorylation regulation, mitochondrial function, and synaptic integrity. Central insulin resistance impairs glucose uptake, resulting in cerebral hypometabolism. This biochemical dysfunction mirrors the pathophysiology of diabetes and underpins neurodegenerative changes and cognitive decline seen in AD [75,76,78,79].

Amyloid-β, Tau Pathology and Insulin

Impaired insulin signaling in the brain promotes Aβ accumulation and tau hyperphosphorylation, both of which are all marks of AD. IDE, which regulates both insulin and Aβ levels, becomes dysfunctional, resulting in Aβ buildup and neuronal loss. This creates a toxic feedback loop, where Aβ further interferes with insulin receptor function, amplifying neuronal insulin resistance and tau pathology [76,78,79].

Neuroinflammation, Oxidative Stress, and Vascular Dysfunction

Type 3 diabetes in AD is also characterized by heightened oxidate stress, neuroinflammation, production of AGEs, and disruption of cerebral blood flow. These processes converge to worsen neurodegeneration, synaptic failure, and cognitive impairment [75,65,80].

Clinical and Translational Significance

Patients with AD often show evidence of insulin resistance in brain tissue, measurable even in early or preclinical stages. Experimental models of “brain diabetes” (such as intracerebral streptozotocin administration) recapitulate AD-specific neurodegeneration, reinforcing the mechanistic link. Emerging therapeutic  approaches targeting insulin signaling- such as intranasal insulin or sensitizers- have shown promise in slowing AD progression and symptom burden. While “type 3 diabetes” is not universally adopted as a formal disease category, the term underscores the centrality of dysregulated insulin signaling in AD pathogenesis [75,76,77,78,81].

Future Directions: Integrating AI and Metabolic Interventions for Dementia Risk Reduction

Future directions in dementia risk reduction are rapidly converging on the integration of artificial intelligence (AI) with metabolic interventions, enabling individualized, precision-based strategies for early risk identification, preventive therapy, and dynamic monitoring of cognitive health [82,83,84,85].

AI for Dementia risk Assessment

AI-driven models, including deep learning algorithms, can process  multimodal data- blood metabolic indices, genetic markers, imaging, and behavioral variables- to quantitatively estimate risk for cognitive impairment and dementia at individual and population levels. Recent AI approaches correlate routine blood test data and systemic metabolic profiles with cognitive test scores, allowing non-invasive, high-throughput screening for dementia risk before symptoms emerge. Explainable AI models further identify specific metabolic disorders (e.g., malnutrition, anemia, insulin resistance) that contribute most to cognitive risk and stratify patient populations for tailored interventions [82,83,85,86].

AI-Powered Personalization of Metabolic Interventions

The integration of AI algorithms in clinical practice facilitates individualized, dynamic intervention protocol. AI quantifies the contribution of metabolic factors (glucose dysregulation, lipid profiles, renal and liver function) and optimizes nutritional, pharmacologic, and exercise therapies to attenuate risk according to each patient’s unique metabolic signature. Personalized dietary therapy is an emerging application, where AI recommends nutrient and diet adjustments based on predicted cognitive impact, sometimes integrating established dietary patterns like the Mediterranean-DASH Intervention  for Neurodegenerative Delay (MIND) diet with patient-specific modifications. AI also monitors intervention efficacy over time, automatically adjusting recommendations in response to changes in biomarkers and patient outcomes [83,87].

Multi-Omics and Digital Biomarker Integration

Advanced AI, including machine learning and large language models, fuses genomic, proteomic, metabolomic, neuroimaging, and digital biomarker data to facilitate early detection, molecular subtyping, and continuous tracking of dementia risk. This facilitates identification of new therapeutics targets, accelerates drug repurposing, and enables remote, scalable monitoring- potentially transforming dementia care into a proactive model rather than a reactive one [82,83,85,88,89].

Research and Implementation Challenges

Key future challenges include ensuring ethical data use, equitable access to AI tools, integration of AI platforms within clinical workflows, validation across diverse populations, and sustained multidisciplinary collaboration between data scientists, clinicians, and public health leaders. Building robust AI models using representative, high-quality datasets and embedding explainability and interpretability will be essential for successful translation [83,85,90].

Conclusion

Elevated blood glucose and metabolic dysregulation are strongly linked to increased probability and severity of Alzheimer’s disease, with key mechanisms involving chronic neuroinflammation, oxidative stress, glycation, and insulin resistance. The article concludes that hyperglycemia and diabetes significantly accelerate cognitive decline and neuropathology by impairing glucose metabolism, promoting amyloid-beta and tau pathology and damaging vascular and neuronal resilience, and that effective metabolic interventions-including optimal glycemic control-are urgently needed to mitigate dementia risk and progression.

This article underscores elevated glucose and insulin resistance as central, modifiable drivers of Alzheimer’s pathology, justifying metabolic screening and targeted therapeutic strategies, including lifestyle, dietary intervention, and AI-powered individualized approaches to reduce the global burden of dementia.

References

  1. Kumar V, Kim SH, Bishayee K. Dysfunctional Glucose Metabolism in Alzheimer’s Disease Onset and Potential Pharmacological Interventions. International Journal of Molecular Sciences [Internet]. 2022 Jan 1;23(17):9540. Available from: https://www.mdpi.com/1422-0067/23/17/9540
  2. Gonzales PNG, Ampil ER, Catindig-Dela Rosa JAS, Villaraza SG, Joson MLC. Increased Risk of Alzheimer’s Disease With Glycemic Variability: A Systematic Review and Meta-Analysis. Cureus [Internet]. 2024 Sep;16(11):e73353. Available from: https://pubmed.ncbi.nlm.nih.gov/39659303/
  3. Guo C, Zhang S, Li JY, Ding C, Yang ZH, Chai R, et al. Chronic hyperglycemia induced via the heterozygous knockout of Pdx1 worsens neuropathological lesion in an Alzheimer mouse model. Scientific Reports. 2016 Jul 12;6(1).
  4. Sugar’s “tipping point” link to Alzheimer’s disease revealed [Internet]. Bath.ac.uk. 2017. Available from: https://www.bath.ac.uk/announcements/sugars-tipping-point-link-to-alzheimers-disease-revealed/
  5. Zhang X, Tong T, Chang A, Ang TFA, Tao Q, Auerbach S, et al. Midlife lipid and glucose levels are associated with Alzheimer’s disease. Alzheimer’s & Dementia. 2022 Mar 23;
  6. Diabetes: A Modifiable Risk Factor for Alzheimer’s Disease [Internet]. BrightFocus Foundation. 2021. Available from: https://www.brightfocus.org/resource/diabetes-a-modifiable-risk-factor-for-alzheimers-disease/
  7. Crane PK, Walker R, Hubbard RA, Li G, Nathan DM, Zheng H, et al. Glucose Levels and Risk of Dementia. New England Journal of Medicine. 2013 Aug 8;369(6):540–8.
  8. Yu JH, Han K, Park S, Cho H, Lee DY, Kim JW, et al. Incidence and Risk Factors for Dementia in Type 2 Diabetes Mellitus: A Nationwide Population-Based Study in Korea. Diabetes & Metabolism Journal [Internet]. 2020 Feb 1;44(1):113–24. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043975/#:~:text=In several studies and meta
  9. Yu J, Lee KN, Kim HS, Han K, Lee SH. Cumulative effect of impaired fasting glucose on the risk of dementia in middle-aged and elderly people: a nationwide cohort study. Scientific Reports [Internet]. 2023 Nov 23;13(1):20600. Available from: https://www.nature.com/articles/s41598-023-47566-y#Sec2
  10. Barbagallo M. Type 2 diabetes mellitus and Alzheimer’s disease. World Journal of Diabetes [Internet]. 2014 Dec 15;5(6):889. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4265876/
  11. Cao F, Yang F, Li J, Guo W, Zhang C, Gao F, et al. The relationship between diabetes and the dementia risk: a meta-analysis. Diabetology & metabolic syndrome. 2024 May 14;16(1).
  12. Wang K, Zhao S, Eric Kam-Pui Lee, Susan Zi-May Yau, Wu Y, Hung CT, et al. Risk of Dementia Among Patients With Diabetes in a Multidisciplinary, Primary Care Management Program. JAMA network open [Internet]. 2024 Feb 12;7(2):e2355733–3. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10862158/#:~:text=Findings
  13. Mukai N, Ohara T, Hata J, Hirakawa Y, Yoshida D, Kishimoto H, et al. Alternative Measures of Hyperglycemia and Risk of Alzheimer’s Disease in the Community: The Hisayama Study. The Journal of Clinical Endocrinology & Metabolism. 2017 Jun 9;102(8):3002–10.
  14. Lin CL, Chien WC, Lin CP, Chung CH, Wu FL. Poor glycemic status as a risk factor for dementia in type 2 diabetes population: Findings from the Taiwan’s National Health Insurance Database. Diabetes Research and Clinical Practice. 2025 Apr;222:112065.
  15. He D, Liu M, Tang Y, Tian X, Zhou L, Chen Y, et al. Systematic analysis and prediction of the burden of Alzheimer’s disease and other dementias caused by hyperglycemia. Frontiers in Public Health. 2025 Feb 5;12.
  16. Yuan Y, Zhao G, Zhao Y. Dysregulation of energy metabolism in Alzheimer’s disease. Journal of Neurology. 2024 Dec 2;272(1).
  17. Yan X, Hu Y, Wang B, Wang S, Zhang X. Metabolic Dysregulation Contributes to the Progression of Alzheimer’s Disease. Frontiers in Neuroscience. 2020 Nov 5;14.
  18. McDonald TS, Lerskiatiphanich T, Woodruff TM, McCombe PA, Lee JD. Potential mechanisms to modify impaired glucose metabolism in neurodegenerative disorders. Journal of Cerebral Blood Flow and Metabolism: Official Journal of the International Society of Cerebral Blood Flow and Metabolism [Internet]. 2023 Jan 1;43(1):26–43. Available from: https://pubmed.ncbi.nlm.nih.gov/36281012/
  19. Willette AA, Bendlin BB, Starks EJ, Birdsill AC, Johnson SC, Christian BT, et al. Association of Insulin Resistance With Cerebral Glucose Uptake in Late Middle–Aged Adults at Risk for Alzheimer Disease. JAMA Neurology [Internet]. 2015 Sep 1;72(9):1013. Available from: https://jamanetwork.com/journals/jamaneurology/fullarticle/2398420
  20. Soltani S, Dolatshahi M, Soltani S, Khazaei K, Rahmani M, Raji CA. Relationships Between Brain Glucose Metabolism Patterns and Impaired Glycemic Status: A Systematic Review of FDG‐PET Studies With a Focus on Alzheimer’s Disease. Human Brain Mapping. 2025 Mar;46(4).
  21. Sędzikowska A, Szablewski L. Insulin and Insulin Resistance in Alzheimer’s Disease. International Journal of Molecular Sciences. 2021 Sep 15;22(18):9987.
  22. Dewanjee S, Chakraborty P, Bhattacharya H, Chacko L, Singh B, Chaudhary A, et al. Altered glucose metabolism in Alzheimer’s disease: Role of mitochondrial dysfunction and oxidative stress. Free Radical Biology and Medicine [Internet]. 2022 Nov 20;193:134–57. Available from: https://www.sciencedirect.com/science/article/pii/S0891584922006220
  23. Hai S, Hou Y, Zhang M, Gao X, Yang T, Shang X, et al. Glucose Metabolism, Lactate, Lactylation and Alzheimer’s Disease. Aging and Disease. 2025 Jan 1;
  24. Matioli MNPS, Nitrini R. Mechanisms linking brain insulin resistance to Alzheimer’s disease. Dementia & Neuropsychologia. 2015 Jun;9(2):96–102.
  25. Mohamed M. Insulin resistance as the molecular link between diabetes and Alzheimer’s disease. World Journal of Diabetes [Internet]. 2024 Jul 8;15(7):1430–47. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC11292327/
  26. Liu Y, Liu F, Grundke-Iqbal I, Iqbal K, Gong CX. Deficient brain insulin signalling pathway in Alzheimer’s disease and diabetes. The Journal of Pathology [Internet]. 2011 May 19;225(1):54–62. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/path.2912
  27. Wei Z, Koya J, Reznik SE. Insulin Resistance Exacerbates Alzheimer Disease via Multiple Mechanisms. Frontiers in Neuroscience. 2021 Jul 19;15.
  28. Singh SK, Maccioni R. A New Era in Alzheimer’s Research. Elsevier Health Sciences; 2024.
  29. Gabbouj S, Ryhänen S, Marttinen M, Wittrahm R, Takalo M, Kemppainen S, et al. Altered Insulin Signaling in Alzheimer’s Disease Brain – Special Emphasis on PI3K-Akt Pathway. Frontiers in Neuroscience [Internet]. 2019 Jun 18;13. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6591470/
  30. Yoon JH, Hwang J, Son SU, Choi J, You SW, Park H, et al. How Can Insulin Resistance Cause Alzheimer’s Disease? International Journal of Molecular Sciences. 2023 Feb 9;24(4):3506.
  31. Mullins RJ, Diehl TC, Chia CW, Kapogiannis D. Insulin Resistance as a Link between Amyloid-Beta and Tau Pathologies in Alzheimer’s Disease. Frontiers in Aging Neuroscience. 2017 May 3;9.
  32. Bharadwaj PR, Dubey AK, Masters CL, Martins RN, Macreadie IG. Aβ aggregation and possible implications in Alzheimer’s disease pathogenesis. Journal of Cellular and Molecular Medicine [Internet]. 2009 Mar 1;13(3):412–21. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3822505/
  33. De Felice FG, Lourenco MV. Brain metabolic stress and neuroinflammation at the basis of cognitive impairment in Alzheimerâ€s disease. Frontiers in Aging Neuroscience. 2015 May 19;7. TM
  34. Iqbal K, Liu F, Gong CX, Alonso A del C, Grundke-Iqbal I. Mechanisms of tau-induced neurodegeneration. Acta Neuropathologica. 2009 Jan 30;118(1):53–69.
  35. Chen G, Xu T, Yan Y, Zhou Y, Jiang Y, Melcher K, et al. Amyloid beta: structure, Biology and structure-based Therapeutic Development. Acta Pharmacologica Sinica [Internet]. 2017 Jul 17;38(9):1205–35. Available from: https://www.nature.com/articles/aps201728
  36. Iliyasu MO, Musa SA, Oladele SB, Iliya AI. Amyloid-beta aggregation implicates multiple pathways in Alzheimer’s disease: Understanding the mechanisms. Frontiers in Neuroscience. 2023 Apr 11;17.
  37. Castellani R, Zhu X, Lee HG, Smith M, Perry G. Molecular Pathogenesis of Alzheimer’s Disease: Reductionist versus Expansionist Approaches. International Journal of Molecular Sciences. 2009 Mar 26;10(3):1386–406.
  38. Hampel H, Hardy J, Blennow K, Chen C, Perry G, Kim SH, et al. The Amyloid-β Pathway in Alzheimer’s Disease. Molecular Psychiatry [Internet]. 2021 Aug 30;26(10). Available from: https://www.nature.com/articles/s41380-021-01249-0
  39. Gong CX ., Iqbal K. Hyperphosphorylation of Microtubule-Associated Protein Tau: a Promising Therapeutic Target for Alzheimer Disease. Current Medicinal Chemistry [Internet]. 2008 Oct 1;15(23):2321–8. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC2656563/
  40. Iqbal K, Liu F, Gong CX, Alonso A del C, Grundke-Iqbal I. Mechanisms of tau-induced neurodegeneration. Acta Neuropathologica. 2009 Jan 30;118(1):53–69.
  41. Basheer N, Smolek T, Hassan I, Liu F, Iqbal K, Zilka N, et al. Does modulation of tau hyperphosphorylation represent a reasonable therapeutic strategy for Alzheimer’s disease? From preclinical studies to the clinical trials. Molecular Psychiatry [Internet]. 2023 Jun 1;28(6):2197–214. Available from: https://www.nature.com/articles/s41380-023-02113-z
  42. Su J, Xiao Y, Wang X, Zheng J, Wang JZ. Development of tau phosphorylation-targeting therapies for the treatment of neurodegenerative diseases. Medicine Plus. 2024 Nov 1;100060–0.
  43. Xu L, Liu R, Qin Y, Wang T. Brain metabolism in Alzheimer’s disease: biological mechanisms of exercise. Translational Neurodegeneration. 2023 Jun 26;12(1).
  44. Zhang J, Zhang Y, Wang J, Xia Y, Zhang J, Chen L. Recent Advances in Alzheimer’s disease: Mechanisms, Clinical Trials and New Drug Development Strategies. Signal Transduction and Targeted Therapy [Internet]. 2024 Aug 23;9(1). Available from: https://www.nature.com/articles/s41392-024-01911-3
  45. Song T, Song X, Zhu C, Patrick R, Skurla M, Santangelo I, et al. Mitochondrial dysfunction, oxidative stress, neuroinflammation, and metabolic alterations in the progression of Alzheimer’s disease: A meta-analysis of in vivo magnetic resonance spectroscopy studies. Ageing Research Reviews. 2021 Dec;72:101503.
  46. Choudhary A. Neuroinflammation and Cognitive health in Type 2 Diabetes. Medical Research Archives. 2025 Jan 1;13(8).
  47. Abbatecola AM, Arosio B, Cerasuolo M, Auriemma MC, Meo ID, Langiano E, et al. Common neurodegenerative pathways in brain aging, cognitive decline, type 2 diabetes & metabolic syndrome. Journal of Gerontology and Geriatrics. 2024 Mar 1;72(1):43–9.
  48. Reddy VP, Zhu X, Perry G, Smith MA. Oxidative Stress in Diabetes and Alzheimer’s Disease. Bierhaus A, editor. Journal of Alzheimer’s Disease. 2009 Apr 17;16(4):763–74.
  49. Muriach M, Flores-Bellver M, Romero FJ, Barcia JM. Diabetes and the Brain: Oxidative Stress, Inflammation, and Autophagy. Oxidative Medicine and Cellular Longevity. 2014;2014:1–9.
  50. Khan MS, Ikram M, Park TJ, Kim MO. Pathology, Risk Factors, and Oxidative Damage Related to Type 2 Diabetes-Mediated Alzheimer’s Disease and the Rescuing Effects of the Potent Antioxidant Anthocyanin. Oxidative Medicine and Cellular Longevity [Internet]. 2021 Feb 27 [cited 2023 Aug 7];2021:e4051207. Available from: https://www.hindawi.com/journals/omcl/2021/4051207/
  51. Verdile G, Keane KN, Cruzat VF, Medic S, Sabale M, Rowles J, et al. Inflammation and Oxidative Stress: The Molecular Connectivity between Insulin Resistance, Obesity, and Alzheimer’s Disease. Mediators of Inflammation. 2015;2015:1–17.
  52. Dash UC, Nitish Kumar Bhol, Swain SK, Rashmi Rekha Samal, Nayak PK, Raina V, et al. Oxidative stress and inflammation in the pathogenesis of neurological disorders: Mechanisms and implications. Acta Pharmaceutica Sinica B [Internet]. 2024 Oct 1;15(1). Available from: https://www.sciencedirect.com/science/article/pii/S2211383524004040
  53. Oluwafemi Omoniyi Oguntibeju. Type 2 diabetes mellitus, oxidative stress and inflammation: examining the links. International Journal of Physiology, Pathophysiology and Pharmacology [Internet]. 2019 Jun 15;11(3):45. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6628012/
  54. Reis F, Soares, Nunes, Pereira. Diabetic encephalopathy: the role of oxidative stress and inflammation in type 2 diabetes. International Journal of Interferon, Cytokine and Mediator Research. 2012 Sep;75.
  55. Alkan E, Taporoski TP, Sterr A, Schantz M von, H. Vallada, Krieger JE, et al. Metabolic syndrome alters relationships between cardiometabolic variables, cognition and white matter hyperintensity load. Scientific Reports. 2019 Mar 13;9(1).
  56. Alfaro FJ, Gavrieli A, Saade-Lemus P, Lioutas VA, Upadhyay J, Novak V. White matter microstructure and cognitive decline in metabolic syndrome: a review of diffusion tensor imaging. Metabolism. 2018 Jan;78:52–68.
  57. Kordestani-Moghadam P, Assari S, Nouriyengejeh S, Mohammadipour F, Pourabbasi A. Cognitive Impairments and Associated Structural Brain Changes in Metabolic Syndrome and Implications of Neurocognitive Intervention. Journal of Obesity & Metabolic Syndrome. 2020 Sep 30;29(3):174–9.
  58. Yates KF, Sweat V, Yau PL, Turchiano MM, Convit A. Impact of Metabolic Syndrome on Cognition and Brain: A Selected Review of the Literature. Arteriosclerosis, thrombosis, and vascular biology [Internet]. 2012 Sep 1;32(9):2060–7. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3442257/
  59. Cakir H, Sunar M, Aydın S, Cakir OK, Gursoy E. Structural Brain Alterations in Metabolic Syndrome: A Comprehensive MRI Volumetric Analysis of Subcortical and Associated Structures. Metabolic Syndrome and Related Disorders. 2024 Oct 1;22(8):583–90.
  60. Dai P, Yu Y, Sun Q, Yang Y, Hu B, Xie H, et al. Abnormal changes of brain function and structure in patients with T2DM-related cognitive impairment: a neuroimaging meta-analysis and an independent validation. Nutrition and Diabetes [Internet]. 2024 Nov 11 [cited 2025 Sep 22];14(1). Available from: https://www.nature.com/articles/s41387-024-00348-5
  61. Ju T, Li Z, Zhang X, Liu Y, Gao X, Zhang H, et al. Multimodal Neuroimaging of Brain Structure, Metabolism, and Function in Obesity: Current Landscape and Future Perspectives. Obesity (Silver Spring, Md) [Internet]. 2025 Spring;10.1002/oby.24353. Available from: https://pubmed.ncbi.nlm.nih.gov/40841320/
  62. Rashid B, Poole VN, Fortenbaugh FC, Esterman M, Milberg WP, McGlinchey RE, et al. Association between metabolic syndrome and resting-state functional brain connectivity. Neurobiology of Aging. 2021 Aug 1;104:1–9.
  63. Qureshi D, Topiwala A, Abid A, Allen NE, Elżbieta Kuźma, Littlejohns TJ. Association of Metabolic Syndrome With Neuroimaging and Cognitive Outcomes in the UK Biobank. Diabetes Care [Internet]. 2024 Jun 19; Available from: https://diabetesjournals.org/care/article/47/8/1415/156809/Association-of-Metabolic-Syndrome-With
  64. Zouridis S, Nasir AB, Aspichueta P, Syn WK. The Link Between Metabolic Syndrome and the Brain. Digestion. 2024 Oct 5;
  65. Petersen M, Hoffstaedter F, Nägele FL, Mayer C, Schell M, Rimmele DL, et al. A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition. 2024 Feb 28 [cited 2025 Sep 22]; Available from: https://elifesciences.org/reviewed-preprints/93246
  66. Cakir H, Sunar M, Aydın S, Cakir OK, Gursoy E. Structural Brain Alterations in Metabolic Syndrome: A Comprehensive MRI Volumetric Analysis of Subcortical and Associated Structures. Metabolic Syndrome and Related Disorders. 2024 Oct 1;22(8):583–90.
  67. Yu J, Lee KN, Kim HS, Han K, Lee SH. Cumulative effect of impaired fasting glucose on the risk of dementia in middle-aged and elderly people: a nationwide cohort study. Scientific Reports [Internet]. 2023 Nov 23;13(1):20600. Available from: https://www.nature.com/articles/s41598-023-47566-y#Sec2
  68. Yang Y, Peng P, Huang H, Zhao Y, Li Y, Xu X, et al. The triglyceride-glucose index and risk of cognitive impairment: a systematic review and meta-analysis with inclusion of two national databases. Frontiers in Neurology [Internet]. 2024 Nov 29;15. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC11638587/
  69. Ehtewish H, Arredouani A, El-Agnaf O. Diagnostic, Prognostic, and Mechanistic Biomarkers of Diabetes Mellitus-Associated Cognitive Decline. International Journal of Molecular Sciences [Internet]. 2022 May 30;23(11):6144. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9181591/
  70. Li W, Yue L, Sun L, Xiao S. Elevated Fasting Plasma Glucose Is Associated With an Increased Risk of MCI: A Community-Based Cross-Sectional Study. Frontiers in Endocrinology. 2021 Nov 16;12.
  71. Zhang S, Zhang Y, Wen Z, Yang Y, Bu T, Bu X, et al. Cognitive dysfunction in diabetes: abnormal glucose metabolic regulation in the brain. Frontiers in Endocrinology. 2023 Jun 16;14.
  72. Liu X, Li Y, Chen X, Yin H, Li F, Chen N, et al. Revisiting the mechanisms linking blood glucose to cognitive impairment: new evidence for the potential important role of klotho. Frontiers in Endocrinology. 2024 Mar 5;15.
  73. Yu X, He H, Wen J, Xu X, Ruan Z, Hu R, et al. Diabetes-related cognitive impairment: Mechanisms, symptoms, and treatments. Open Medicine. 2025 Jan 1;20(1).
  74. Cao H, Zhao Y, Chen Z, Zou X, Du X, Yi L, et al. Triglyceride-glucose index predicts cognitive decline and striatal dopamine deficiency in Parkinson disease in two cohorts. npj Parkinson s Disease [Internet]. 2025 Aug 13 [cited 2025 Sep 22];11(1). Available from: https://www.nature.com/articles/s41531-025-01100-1
  75. Amin AM, Mostafa H, Hani. Insulin resistance in Alzheimer’s disease: The genetics and metabolomics links. Clinica Chimica Acta. 2023 Jan 1;539:215–36.
  76. de la Monte SM, Wands JR. Alzheimer’s Disease is Type 3 Diabetes—Evidence Reviewed. Journal of Diabetes Science and Technology [Internet]. 2008 Nov;2(6):1101–13. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2769828/
  77. Peng Y, Yao S, Chen Q, Jin H, Du M, Xue Y, et al. True or false? Alzheimer’s disease is type 3 diabetes: Evidences from bench to bedside. Ageing Research Reviews. 2024 Jun 30;99:102383–3.
  78. Nguyen TT, Ta QTH, Nguyen TKO, Nguyen TTD, Van Giau V. Type 3 Diabetes and Its Role Implications in Alzheimer’s Disease. International Journal of Molecular Sciences [Internet]. 2020;21(9). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246646/
  79. Yoon JH, Hwang J, Son SU, Choi J, You SW, Park H, et al. How Can Insulin Resistance Cause Alzheimer’s Disease? International Journal of Molecular Sciences. 2023 Feb 9;24(4):3506.
  80. Michailidis M, Moraitou D, Tata DA, Kalinderi K, Papamitsou T, Papaliagkas V. Alzheimer’s Disease as Type 3 Diabetes: Common Pathophysiological Mechanisms between Alzheimer’s Disease and Type 2 Diabetes. International Journal of Molecular Sciences. 2022 Feb 28;23(5):2687.
  81. Willette AA, Bendlin BB, Starks EJ, Birdsill AC, Johnson SC, Christian BT, et al. Association of Insulin Resistance With Cerebral Glucose Uptake in Late Middle–Aged Adults at Risk for Alzheimer Disease. JAMA Neurology [Internet]. 2015 Sep 1;72(9):1013. Available from: https://jamanetwork.com/journals/jamaneurology/fullarticle/2398420
  82. Winchester L, Harshfield EL, Shi L, AmanPreet Badhwar, Ahmad Al Khleifat, Clarke N, et al. Artificial intelligence for biomarker discovery in Alzheimer’s disease and dementia. Alzheimers & Dementia. 2023 Aug 31;19(12).
  83. Ren F, Wei J, Chen Q, Hu M, Yu L, Mi J, et al. Artificial intelligence-driven multi-omics approaches in Alzheimer’s disease: Progress, challenges, and future directions. Acta Pharmaceutica Sinica B [Internet]. 2025 Jul 25; Available from: https://www.sciencedirect.com/science/article/pii/S2211383525005088
  84. Kale MB, Wankhede NL, Pawar RS, Suhas Ballal, Rohit Kumawat, Goswami M, et al. AI-Driven Innovations in Alzheimer’s Disease: Integrating Early Diagnosis, Personalized Treatment, and Prognostic Modelling. Ageing Research Reviews [Internet]. 2024 Sep 1;101:102497–7. Available from: https://www.sciencedirect.com/science/article/pii/S1568163724003155
  85. Newby D, Orgeta V, Marshall CR, Ilianna Lourida, Albertyn CP, Stefano Tamburin, et al. Artificial intelligence for dementia prevention. Alzheimer’s & Dementia. 2023 Oct 14;19(12).
  86. García-Gutiérrez F, Hernández-Lorenzo L, María Nieves Cabrera-Martín, Matias-Guiu JA, Ayala JL. Predicting changes in brain metabolism and progression from mild cognitive impairment to dementia using multitask Deep Learning models and explainable AI. NeuroImage. 2024 Aug 1;297:120695–5.
  87. Kale MB, Wankhede NL, Pawar RS, Suhas Ballal, Rohit Kumawat, Goswami M, et al. AI-Driven Innovations in Alzheimer’s Disease: Integrating Early Diagnosis, Personalized Treatment, and Prognostic Modelling. Ageing Research Reviews [Internet]. 2024 Sep 1;101:102497–7. Available from: https://www.sciencedirect.com/science/article/pii/S1568163724003155
  88. Song J, Huang J, Liu R. Integrating NLP and LLMs to discover biomarkers and mechanisms in Alzheimer’s disease. SLAS Technology. 2025 Apr;31:100257.
  89. Qi W, Zhu X, Wang B, Shi Y, Dong C, Shen S, et al. Alzheimer’s disease digital biomarkers multidimensional landscape and AI model scoping review. npj Digital Medicine. 2025 Jun 16;8(1).
  90. Beeri MS, Gu Y. Midlife matters: metabolic syndrome and the risk of dementia. The Lancet Healthy Longevity [Internet]. 2024 Dec [cited 2025 Feb 13];5(12):100659. Available from: https://www.thelancet.com/journals/lanhl/article/PIIS2666-7568(24)00185-5/fulltext?rss=yes