Background: Type 2 Diabetes Mellitus (T2DM) and Alzheimer’s Disease (AD) are increasingly linked through shared pathophysiological mechanisms, giving rise to the concept of Type 3 Diabetes Mellitus (T3DM). Brain insulin resistance, oxidative stress, and neuroinflammation are central to both conditions, contributing to cognitive decline and AD progression. Aim: This review aims to explore this emerging relationship and its implications for prevention and management. Methods: Using an integrative review, 21 studies were systematically analyzed. The review focused on identifying demographic, genetic, and lifestyle factors contributing to T2DM and AD and examined shared molecular pathways such as insulin dysregulation and amyloid-beta accumulation. Results: The findings reveal that T3DM shares key features with T2DM and AD, including insulin resistance and chronic inflammation. Lifestyle interventions, such as diet and exercise, alongside routine cognitive and metabolic screenings, are critical in mitigating progression. Conclusions: Further research into diagnostic biomarkers and targeted therapies is essential to manage T3DM and its impact on AD. The role of nursing professionals in early detection, education, and holistic management is emphasized as vital in addressing this dual disease burden. This review offers actionable insights into integrated strategies for addressing these interconnected conditions.

What is already known about this topic:

• Diabetes Mellitus and Alzheimer’s Disease (AD) are interconnected through shared pathological mechanisms, including insulin resistance and chronic inflammation.
• Dysregulation of the brain’s insulin signaling pathway contributes to cognitive impairments observed in both AD and Type 2 Diabetes Mellitus (T2DM).
• The molecular crosstalk between T2DM and AD is increasingly evident, with emerging studies identifying overlapping pathophysiological and pathogenic pathways.

What this paper adds:

• Early detection of cognitive decline in Type 2 Diabetes Mellitus (T2DM) through routine insulin resistance screenings and cognitive assessments can significantly delay the onset of Alzheimer's Disease (AD).
• Integrating lifestyle modifications, such as anti-inflammatory diets and structured physical activity programs, is crucial for managing the dual burden of T3DM and AD.
• Future research should prioritize developing personalized therapeutic interventions targeting shared pathways like insulin signaling and neuroinflammation to improve outcomes in at-risk populations.

As the global population continues to age, the dual burden of metabolic and neurodegenerative diseases has become increasingly evident. Diabetes Mellitus, particularly Type 2 Diabetes Mellitus (T2DM), is now recognized not only for its systemic impact but also for its implications in cognitive decline and Alzheimer's Disease (AD). Research indicates that individuals with impaired glucose tolerance or diabetes are significantly more prone to developing AD compared to their healthy counterparts [1]. T2DM is characterized by persistent insulin resistance, which begins in a prediabetic state when the pancreas is unable to efficiently regulate glucose levels [2]. This resistance extends to insulin signaling in the brain, disrupting vital metabolic and neuronal processes and linking diabetes to the pathophysiology of AD [3, 4, 5, 6, 7]. Notably, studies highlight that impaired insulin signaling impacts glucose metabolism and exacerbates amyloid beta aggregation, a hallmark of Alzheimer’s pathology [9, 10]. This growing body of evidence underscores the urgent need to explore the complex interplay between metabolic dysfunction and neurodegenerative processes.

The metabolic and pathological overlap between T2DM and AD has led to the conceptualization of AD as “Type 3 Diabetes” [8]. Key mechanisms contributing to this overlap include oxidative stress, mitochondrial dysfunction, and abnormal protein processing, such as the aggregation of hyperphosphorylated tau proteins and amyloid-beta plaques [3, 9, 10]. Chronic inflammation, mediated by TLR4, exacerbates insulin resistance in both peripheral tissues and the brain, further fueling AD-related neurodegeneration [11, 8]. Additionally, mitochondrial dysfunction caused by oxidative damage has been implicated in the early stages of neurodegeneration, suggesting that interventions aimed at preserving mitochondrial health could provide neuroprotective benefits [12, 13]. Genetic factors, environmental exposures, and lifestyle habits also influence these processes, emphasizing the multifaceted nature of this disease intersection [6, 12]. Given the central role of insulin resistance in these conditions, targeting the insulin signaling pathway has emerged as a promising therapeutic approach [3, 7].

Emerging research has explored potential therapeutic interventions that target these shared pathways. Antidiabetic medications such as GLP-1 receptor agonists and metformin show promise in mitigating neuroinflammation, improving insulin sensitivity, and enhancing cognitive function in experimental models [3, 7, 13]. Notably, metformin, a widely used insulin-sensitizing drug, has shown potential benefits in improving cognitive performance and reducing AD-related biomarkers, although findings remain inconclusive [3]. Dietary and lifestyle modifications, such as incorporating antioxidant-rich foods and engaging in regular physical activity, may also reduce oxidative stress and improve metabolic health, potentially delaying AD onset [14, 15]. Studies have demonstrated that regular exercise enhances insulin sensitivity and promotes neurogenesis, suggesting a synergistic effect when combined with dietary interventions [14]. Biomarkers, including tau proteins and advanced glycation end products (AGEs), have shown diagnostic potential, paving the way for early detection and intervention [2, 6, 7]. Despite these advances, there remains a pressing need for further research to establish the safety and efficacy of these strategies in clinical settings [3]. Innovative treatment approaches, such as intranasal insulin and fibroblast growth factor 21 (FGF21), are also being explored for their ability to bypass systemic barriers and directly target brain insulin resistance [15, 16].

This study contributes to the growing body of evidence that identifies "Type 3 Diabetes" as a critical link between metabolic dysfunction and Alzheimer's Disease. By reviewing the existing literature, this research aims to address three key questions: (1) What is the current evidence supporting the relationship between Type 3 Diabetes and Alzheimer's Disease? (2) Why has Type 3 Diabetes not been formally recognized as a clinical diagnosis despite its significance? (3) What are the most compelling mechanistic links between Type 3 Diabetes and Alzheimer's Disease based on current understanding? This study provides a comprehensive analysis of the interconnected pathophysiological mechanisms, offering insights that may inform the development of diagnostic criteria and targeted therapies. The outcome of this research underscores the importance of integrating metabolic management into AD care regimens, potentially transforming clinical practice by emphasizing preventative strategies and personalized treatment approaches for at-risk populations. By bridging gaps in understanding and addressing the overlap of these two conditions, this research aims to contribute to more effective prevention, early detection, and treatment strategies, ultimately improving patient outcomes and quality of life.

3.1. Design

This study utilized an integrative review approach as proposed by Whittemore and Knafl [22]. The process involved five key steps: identifying the problem, conducting a systematic literature search, evaluating the quality and relevance of selected studies, analyzing the data to identify patterns, and synthesizing the findings. The integrative review was chosen because of its flexibility in evaluating diverse primary research using varying techniques and methodologies. As the sole method allowing the synthesis of multiple approaches, this review strategy offers significant potential to influence evidence-based healthcare practices. Although strategies for data extraction and collection within this method are well-developed, synthesis, analysis, and conclusion-drawing techniques remain inadequately standardized, presenting opportunities for further refinement in methodology [22].

3.2. Search Strategy

A comprehensive systematic search was conducted across multiple academic databases, including PubMed, Google Scholar, EBSCO/CINAHL, and ScienceDirect, to identify studies exploring the association between Type 3 Diabetes Mellitus (T3DM) and Alzheimer’s Disease (AD). The search, carried out between May and July 2024, utilized a combination of relevant keywords and Boolean operators, such as “Type 3 Diabetes Mellitus,” “T3DM,” “Alzheimer’s Disease,” “AD,” “Insulin Resistance,” “Brain Insulin Resistance,” “Cognitive Impairment,” “Shared Mechanisms,” and “Dysregulated Insulin Signaling.” Boolean operators were applied to combine terms effectively (e.g., (“T3DM” OR “Type 3 Diabetes Mellitus”) AND (“Alzheimer’s Disease” OR “AD”) AND (“Insulin Resistance” OR “Cognitive Impairment”)). The search was limited to peer-reviewed articles published in English within the last 10 years.

The search identified a total of n=972 records, including n=937 from databases and n=35 from manual searches of references and other sources. After removing n=211 duplicates, n=761 unique records remained for screening. Of these, n=489 were excluded for being outside the 10-year publication window, leaving n=272 records for title and abstract screening. During this step, n=112 records were excluded for irrelevance or insufficient focus on the T3DM-AD relationship.

A total of n=160 full-text articles were retrieved and assessed for eligibility. Of these, n=138 were excluded for the following reasons: n=29 were in non-English languages, n=36 were not peer-reviewed, n=16 were editorials, letters, or commentaries, n=4 focused on AD with other neurological deficits, n=12 addressed diabetes with severe comorbidities affecting cognition or glucose regulation, and n=41 were excluded for other reasons, such as insufficient data on the T3DM-AD relationship. Ultimately, n=21 studies met all inclusion criteria and were included in the qualitative synthesis.

This systematic process followed the PRISMA methodology to ensure rigorous identification, screening, eligibility assessment, and inclusion of relevant studies. The final selection provided robust insights into the shared pathophysiological mechanisms linking T3DM and AD, particularly the pivotal role of dysregulated insulin signaling in neurodegeneration.

These selected studies provided robust evidence of dysregulated insulin signaling's pivotal role in the pathogenesis of AD, a characteristic shared with Type 2 Diabetes [1, 3, 4, 6].

Figure 1 illustrates the PRISMA Flow Diagram for the study, summarizing the process of identifying, screening, and selecting relevant literature.

Figure 1

PRISMA flow diagram

3.3 Eligibility Criteria

The inclusion and exclusion criteria, summarized in Table 1, were designed to refine the literature to studies directly examining the association between diabetes and Alzheimer’s Disease.

3.4. Data Evaluation and Quality Appraisal

The selected studies were meticulously evaluated using a matrix table based on Sparbel and Anderson's tool [23]. Table 2 was categorized each article by author, year, study design, methodology, aims and objectives, level of evidence, and significant findings related to T3DM and AD (Table 4). Researchers independently appraised the methodological quality of all selected articles, ensuring adherence to the inclusion and exclusion criteria. Disagreements in the assessment were resolved through consensus in multiple collaborative meetings. To further assess study quality, the Levels of Evidence framework proposed by Melnyk [24] was applied. Three experts in systematic review were consulted for peer-review.

The final set of articles provided comprehensive insights into the intersection of insulin resistance, glucose dysregulation, and AD pathology, reinforcing the hypothesis that AD, characterized as T3DM, shares critical mechanistic pathways with T2DM [8, 13]. These insights support the broader aim of advancing diagnostic criteria and identifying targeted therapeutic interventions for T3DM and AD.

The synthesis of the reviewed literature, summarized in Table 2, highlights the demographic and clinical factors contributing to the progression and interplay between Alzheimer's Disease (AD) and Type 2 Diabetes Mellitus (T2DM). These factors are critical in understanding the pathophysiology and guiding strategies for prevention and intervention. The articles reviewed span across various countries, with the majority originating from the USA (n=4). Other countries contributing to the body of literature include China (n=2), Poland (n=2), and Vietnam (n=2). Countries like Spain, Germany, United Kingdom, Italy, Japan, India, Greece, Pakistan, Belgium, Taiwan, and Brazil each contributed one article (n=1) to the analysis. All studies were categorized as Review Papers (n=21), reflecting a consistent design approach across the included literature. The level of evidence for all articles was classified as Level V (n=21), as these studies primarily summarized and synthesized existing findings rather than presenting original experimental or clinical data. This distribution emphasizes the global interest in understanding the relationship between diabetes and Alzheimer's Disease, with notable contributions from developed countries where these conditions are highly prevalent. However, the limited representation from some regions, such as developing countries, suggests a potential gap in research coverage.

Exploring the relationship between insulin resistance and Alzheimer's Disease (n=4): These studies focus on the impact of insulin resistance on cognitive decline and its progression to Alzheimer's Disease [2, 4, 11, 27]. Investigating shared mechanisms and pathways linking diabetes and Alzheimer's (n=4): These articles delve into molecular and physiological overlaps, including inflammation, oxidative stress, and glucose dysregulation [1, 3, 8, 17]. Evaluating therapeutic interventions for diabetes and Alzheimer's (n=5): Studies in this category assess existing and novel treatments, such as anti-diabetic medications and lifestyle interventions [13, 9, 18, 15, 10]. Discussing biomarkers and early diagnosis strategies (n=3): These articles explore the potential of biomarkers like amyloid-beta and tau proteins for early detection of Alzheimer's Disease in diabetic patients [5, 19, 20]. Examining specific molecular or protein-related mechanisms (n=5): These studies focus on detailed biochemical pathways, such as the role of Toll-like receptor 4 (TLR4) and mitochondrial dysfunction [7, 12, 6, 16, 14].

Demographic Factors

Age remains a dominant risk factor, with both T2DM and AD predominantly affecting individuals over the age of 50. The incidence of these conditions escalates sharply in older adults, reflecting the cumulative impact of aging on metabolic and cognitive processes [15, 19]. Gender disparities are also evident, with women appearing more vulnerable to AD, likely due to hormonal changes during menopause and their generally longer lifespans [14]. Ethnic background further influences disease prevalence; for example, African Americans and Hispanic/Latino populations exhibit higher rates of T2DM and, consequently, greater susceptibility to T3DM and AD, while certain Asian groups display comparatively lower rates due to genetic and dietary differences [19, 20]. Socio-cultural factors, such as dietary habits and access to healthcare, modulate these risks, underscoring the importance of personalized public health approaches [18, 21].

Education and socioeconomic status play protective roles, with higher education levels associated with a greater cognitive reserve, delaying the onset of cognitive decline [9]. Conversely, lower socioeconomic status correlates with limited healthcare access, poorer nutrition, and reduced health literacy, compounding the risks of T2DM and AD [7, 20]. Obesity, reflected in higher Body Mass Index (BMI), is another modifiable risk factor closely linked to insulin resistance, inflammation, and metabolic dysfunction [14, 22].

Clinical and Lifestyle Factors

The coexistence of comorbidities, including cardiovascular disease, hypertension, and obesity, further exacerbates the risk of cognitive decline in diabetic patients, highlighting the need for integrated management approaches [18, 21]. Prolonged hyperglycemia, a hallmark of diabetes, directly contributes to neuronal damage and fosters the progression of Alzheimer's pathology through oxidative stress and chronic inflammation [14, 23]. Family history and genetic predisposition underline the hereditary component of these diseases, with specific gene-environment interactions playing a crucial role in their development [13, 22].

Lifestyle factors such as diet, exercise, and smoking emerge as pivotal determinants of health outcomes. Regular physical activity and a balanced diet rich in antioxidants protect against metabolic dysfunction and cognitive decline, while high-fat, high-sugar diets accelerate insulin resistance and increase the risk of T3DM and AD [16, 20]. Smoking and sedentary behavior exacerbate these risks, emphasizing the importance of lifestyle interventions as preventive measures [14].

Pathophysiological Insights

Key findings from the reviewed studies suggest that T2DM increases the risk of AD by disrupting insulin signaling, which is essential for neuronal survival and synaptic plasticity [19, 20]. Insulin resistance in the brain is linked to the accumulation of amyloid-beta (Aβ) plaques and hyperphosphorylated tau proteins, hallmark features of AD pathology. Experimental research using animal models supports these findings, demonstrating that both Type I and Type II diabetes aggravate AD pathology through abnormal insulin signaling pathways [12]. Notably, insulin treatment in animal models has shown promise in ameliorating AD-related pathology, offering a potential therapeutic avenue [12, 19].

Evidence Quality and Synthesis

The review synthesized evidence primarily from Level 5 studies, providing a broad base of qualitative and observational insights into the T3DM-AD connection. However, it also incorporates two Level 2 meta-analyses, which contribute more robust and reliable data to complement the findings from lower-level studies. These meta-analyses enhance the overall quality and depth of the synthesis, validating critical aspects of the proposed link between T2DM, T3DM, and AD.

This comprehensive analysis of demographic, clinical, and lifestyle factors, supported by evidence of shared pathophysiological mechanisms, underscores the multifaceted nature of the T3DM-AD relationship. The findings provide a solid foundation for future research to explore targeted interventions and diagnostic criteria for T3DM, potentially transforming the management of Alzheimer's Disease.

This integrative review explores the intricate relationship between Type 3 Diabetes Mellitus (T3DM) and Alzheimer’s Disease (AD), shedding light on their shared pathophysiological mechanisms and implications for healthcare practice. By synthesizing evidence from 21 studies, this review supports the conceptualization of AD as a metabolic disorder, expanding its traditional classification as a purely neurodegenerative disease. This understanding highlights the importance of demographic factors, lifestyle triggers, and genetic predispositions in influencing disease onset and progression. Nurses, as frontline healthcare providers, play a pivotal role in early detection, metabolic health monitoring, and interdisciplinary care planning, making their involvement crucial for addressing the complexities of T3DM and AD.

5.1. Triggering Factors

T3DM, commonly described as insulin resistance in the brain, serves as a critical link between diabetes and AD. A combination of genetic predispositions, lifestyle factors, and metabolic dysregulation contributes to its onset and progression. Insulin resistance disrupts glucose metabolism in the brain, leading to impaired neuronal function and cognitive decline in AD patients [2, 3, 15]. Chronic hyperglycemia exacerbates this process through the formation of advanced glycation end-products (AGEs), which increase oxidative stress and inflammation [7, 18]. Elevated pro-inflammatory cytokines and compromised blood-brain barrier integrity further amplify neuronal damage and accelerate the accumulation of amyloid-beta plaques and tau protein tangles—hallmarks of AD pathology [9, 13, 17].

Genetic factors, including the presence of the APOE4 allele, significantly heighten the risk of developing both diabetes and AD. This allele influences lipid metabolism and inflammatory processes, while epigenetic changes, driven by environmental and metabolic factors, modulate gene expression linked to neurodegeneration [10, 19]. Additionally, mitochondrial dysfunction, observed in both diseases, contributes to reduced energy metabolism and increased oxidative stress, hastening neuronal death and cognitive deterioration [12, 16, 18]. Poor dietary habits, physical inactivity, and exposure to environmental toxins further exacerbate insulin resistance and neuroinflammation, worsening T3DM and AD outcomes [14, 20]. Diabetes-related vascular complications also contribute to neurovascular dysfunction, emphasizing the need to prioritize cardiovascular health to mitigate AD risk [6, 10].

5.2. Consequences

The coexistence of T3DM and AD imposes significant physical, emotional, and financial burdens on patients, families, and healthcare systems. Patients with both conditions experience accelerated cognitive decline, impairing memory, executive function, and daily activities [4, 14]. This dependency increases caregiver stress and burnout, particularly in familial settings where long-term care demands are prevalent [12, 20]. Economically, managing these interconnected conditions involves costly interventions, including regular monitoring, polypharmacy, and institutional care, which strain both patients’ finances and healthcare systems [10, 15].

The presence of T3DM complicates AD management, as medications for diabetes can interact with cognitive treatments, potentially reducing efficacy or causing adverse effects [9, 21]. For instance, hypoglycemia induced by certain diabetes medications can exacerbate cognitive impairment, highlighting the need for individualized treatment plans [10]. Moreover, individuals with T3DM and AD are at heightened risk for comorbid conditions, such as cardiovascular disease and hypertension, complicating disease management and worsening prognosis [18]. Integrated care strategies addressing metabolic and neurodegenerative aspects are essential for reducing the cumulative health risks associated with T3DM and AD. Future research should prioritize biomarker identification and targeted therapies to mitigate disease progression and enhance patient quality of life [14, 17].

5.3. Implications for Practice

The intertwined relationship between T3DM and AD demands a proactive approach in nursing practice, emphasizing early detection, prevention, and patient education. Nurses are instrumental in identifying early signs of metabolic dysfunction and cognitive decline, allowing for timely interventions that can delay disease progression. Patient and caregiver education is a cornerstone of nursing care, enabling individuals to understand the connection between metabolic health and cognitive performance, thereby encouraging proactive lifestyle modifications [8, 15].

Healthcare professionals must adopt a multidisciplinary approach, collaborating with dietitians, endocrinologists, and neurologists to develop holistic care plans. Participating in continued education programs and seminars focused on the diabetes-AD relationship can enhance nursing competencies and improve patient care outcomes [22]. Furthermore, nurses should advocate for equitable healthcare access and support policies promoting lifestyle interventions, such as healthy diets and regular exercise, to reduce the prevalence of T3DM and AD in vulnerable populations [13, 20].

In conclusion, the findings of this review emphasize the critical role of public professionals in addressing the dual burden of T3DM and AD through comprehensive care strategies, early detection, and patient education. Strengthening practices in these areas has the potential to improve patient outcomes and reduce the impact of these interconnected conditions on individuals and healthcare systems.

5.4. Limitations and Recommendations

The current integrative review has several notable limitations. First, the body of literature exploring the relationship between Type 2 Diabetes Mellitus (T2DM) and Alzheimer’s Disease (AD) remains fragmented, with many studies emphasizing individual mechanisms, such as insulin resistance or inflammation, rather than adopting a comprehensive and integrative framework. This lack of holistic approaches limits the ability to fully elucidate the multifaceted relationship between the two conditions. Furthermore, most studies included in this review relied on observational or correlational designs, which restrict the ability to draw causal inferences. While some insights into potential shared pathophysiological pathways have been gained, the evidence remains insufficient to establish T3DM as a clinically recognized diagnosis or to define it as a distinct subtype of AD. Another limitation lies in the geographical and demographic scope of existing studies. Research from developing countries, where the prevalence of both T2DM and AD is rising rapidly, is underrepresented. These regions often face unique socio-economic, cultural, and healthcare challenges that may influence disease progression and outcomes. This geographical bias may limit the generalizability of findings to global populations. Finally, the inherent complexity of the relationship between metabolic dysfunction and neurodegeneration means that many studies have not adequately accounted for potential confounding factors, such as comorbidities, genetic predispositions, or environmental influences.

To address these limitations, future research should aim to adopt more integrative and interdisciplinary approaches to studying the interplay between T2DM and AD. Longitudinal studies and randomized controlled trials are essential to establish causal links between insulin resistance, oxidative stress, inflammation, and cognitive decline. Investigations should also explore the synergistic effects of these mechanisms to identify key therapeutic targets. Genetic and environmental factors influencing the diabetes-AD relationship warrant deeper exploration. For instance, studies examining the impact of the APOE4 allele on insulin resistance and neurodegeneration could provide valuable insights into the genetic basis of T3DM. Additionally, comparative research across diverse populations, particularly in underrepresented regions, is necessary to elucidate the influence of socio-economic, cultural, and healthcare variables on disease progression. Finally, there is a pressing need for translational research that evaluates the efficacy of potential therapeutic interventions targeting shared pathways between T2DM and AD. This includes investigating the role of antidiabetic medications, such as GLP-1 receptor agonists, in reducing cognitive decline and neuroinflammation. Advances in biomarker research are also crucial for developing diagnostic tools to identify at-risk individuals and monitor disease progression.

The hypothesis that Type 3 Diabetes Mellitus (T3DM) represents a convergence of pathophysiological characteristics shared by Type 2 Diabetes Mellitus (T2DM) and Alzheimer’s Disease (AD) has garnered increasing attention. This review synthesizes evidence suggesting that insulin resistance in the brain contributes to cognitive decline and neurodegeneration, supporting the conceptualization of AD as a metabolic disorder. Insufficient insulin signaling in the brain is a key factor in the accumulation of amyloid-beta plaques, tau protein hyperphosphorylation, and neuronal dysfunction, which are hallmarks of AD. Genetic factors, such as the APOE4 allele, and metabolic factors, including oxidative stress and lipid peroxidation, further compound the risk of developing T3DM and AD. While insulin dysfunction is a critical component of this relationship, the underlying causes of AD are likely multifactorial and extend beyond insulin resistance alone. Some researchers advocate classifying AD as a subtype of T3DM, yet this remains a hypothesis rather than an established medical diagnosis. There is currently no diagnostic test for T3DM, and further research is necessary to determine whether this classification would enhance our understanding and management of AD. Future studies should focus on unraveling the precise mechanisms linking insulin dysregulation to neurodegeneration, with the ultimate goal of developing targeted interventions for both T3DM and AD. As evidence accumulates, the integration of metabolic health into dementia care could yield innovative strategies for prevention and treatment, potentially transforming outcomes for at-risk populations. Continued exploration of this hypothesis may not only refine our understanding of AD’s etiology but also provide a pathway to novel therapeutic approaches that address the dual burden of metabolic and neurodegenerative diseases.

Author Contributions: MMD, VL, JM, MKP: Conceptualization, Methodology, Formal analysis, Investigation, Data curation, Writing - original draft, Project administration. RAN: Supervision, Validation, Formal Analysis, Visualization, Writing - review & editing.

Conflict of Interest: The authors declare no conflict of interest