Most people are aware of type 1 and type 2 diabetes, but did you know there is a type 3 diabetes as well! It is a more obscure term. Although it is not an accepted medical diagnosis, type 3 diabetes has been discussed in the literature as a possible relationship between insulin resistance in the brain and Alzheimer's disease. This link has been described to help explain how metabolic disorders impact brain health, causing cognitive decline and dementia.

What is Type 3 Diabetes?

Type 3 diabetes is more of a misnomer because it should not be confused with type 3c diabetes, which relates to pancreatic dysfunction. The term "type 3 diabetes," on the other hand, has been loosely used by some scientists to analogously propose that Alzheimer's disease is strongly implicated with insulin resistance in the brain.

This concept was conceptualized by Dr. Suzanne de la Monte and Dr. Jack Wands of Brown University in the year 2008. This hypothesis postulated that Alzheimer's disease may be called type 3 diabetes for it bears many similarities with glucose metabolism disorder type 2 diabetes. Their concept arises from the basic principle that insulin is fundamental to blood sugar regulation, but it is also the case with the brain. When brain cells become insulin-resistant, they lose access to glucose, impairing their function.

Research published in the Journal of Diabetes Science and Technology supports this hypothesis by indicating that insulin resistance can be a significant contributor to the occurrence of dementia, also referred to as Alzheimer's. The symptoms of memory loss and diminished reasoning are associated with impaired glucose metabolism in the body, especially in the cerebral tissue.

Symptoms of Type 3 Diabetes

Although type 3 diabetes is not a "medical term," its symptoms correlate well with Alzheimer's diseases that are known to reduce the ability to think in an efficient manner and bring down brain health. These signs are:

- Loss of memory, especially short-term.

- Poor judgment and judgment ability

- Failure in recognizing people or places familiar once.

- Failure in the process of reading, writing or processing numbers

- Anxiety, agitation, or mood changes.

- Disorganized thoughts or confusion

- Lack of impulse control

As the disease advances, patients may be afflicted with severe complications including an inability to swallow or control their bodily functions. In the final stages, most patients die from fatal complications such as aspiration pneumonia.

Causes of Type 3 Diabetes

This may not be well understood with regards to type 3 diabetes, or the exact link between insulin resistance and Alzheimer's disease. Some identified contributing factors include the following:

1. Insulin Resistance

Insulin acts as an important regulatory mechanism of brain functions such as memory and cognition. The reduction in insulin signaling may impair metabolism of brain cells, thus bringing about neurodegeneration.

2. Type 2 Diabetes

These diseases show a strong relationship and those individuals diagnosed with type 2 diabetes have double chances of getting Alzheimer's. In the two, the main causes can be chronic inflammation, oxidative stress, and a defect in glucose metabolism.

3. Environmental and Lifestyle Factors

Insulin resistance associated with obesity, stress, and an unhealthy diet is considered a cause that may increase the chances of Alzheimer's disease.

Researches in Frontiers in Neuroscience and The Lancet Neurology have also highlighted that drugs used for antidiabetic medication may be crucial for the prevention or at least slowing down the course of Alzheimer's.

Treatments for Type 3 Diabetes

In 2022, in a study in Pharmaceuticals, researchers studied biomarker uptake in brain regions implicated in the faulty uptake and metabolism of blood sugar in Alzheimer’s patients.

Emerging Therapies

Research into such treatments as intranasal insulin has also been promising. Intranasal delivery of insulin directly to the brain has been reported to enhance glucose uptake by brain cells, improve memory, and boost cognitive performance. While such clinical trials have been shown to be successful, additional research is needed for safety and efficacy.

Medications

For patients being aggressive or agitated, antipsychotic drugs may be prescribed; however, therapies such as cognitive rehabilitation as well as cognitive stimulation therapy serve to preserve memory and executive function.

Lifestyle Interventions

Diet, exercise, and stress management are critical in preventing and managing insulin resistance. A review in the Journal of Alzheimer's Disease also highlighted the benefits of Kirtan Kriya meditation, which can regulate genes involved in insulin and glucose metabolism, improve sleep, and reduce inflammation.

Can Type 3 Diabetes Be Prevented?

Although type 3 diabetes is not officially recognized, its connection to Alzheimer’s disease underscores the importance of proactive measures for brain health. Some prevention strategies include:

1. Healthy Diet

Consuming a balanced diet rich in antioxidants, whole grains, and healthy fats may support brain health.

2. Regular Exercise

Physical activity improves insulin sensitivity, reduces inflammation, and enhances overall metabolic health.

3. Stress Reduction

Mindfulness practices, including meditation, have been shown to lower stress levels, which can reduce the risk of cognitive decline.

The term type 3 diabetes brings out the complex relationship between metabolic disorders and brain health. Even though it is not a recognized medical condition, the concept emphasizes the crucial role of insulin in brain function and its possible contribution to Alzheimer's disease. Continued research will hopefully provide hope for therapies such as intranasal insulin and lifestyle modifications.

The United States has signed 24 bilateral health Memoranda of Understanding or MoUs with Latin America and African countries under the Trump administration's America First Global Health Strategy.

The first agreement with Panama is described as “strengthening Western hemisphere health security”, which it added is “a priority”. Thereafter, four Latin American agreements too involve smaller grants and focus on disease surveillance. Other 20 agreements all with African countries who have been previous recipients of health grants via the now disbanded US agency for International Development or USAID and decimated US President's Emergency Funds for AIDS Relief (PEPFAR).

The five-year MoUs aim to quickly shift financial responsibility for key health services to national governments. In several countries, including Kenya, Uganda and the Democratic Republic of Congo (DRC), more than half of HIV programme funding has traditionally come from donors, particularly the United States. In the DRC, for instance, at least half of the antiretroviral medicines used have been financed by the US.

What Do These MoUs Comprise?

The transitional Memorandums of Understanding (MoUs) signed between the United States and several countries come with a major condition. They require strong investment in infectious disease surveillance systems.

The goal is to ensure that pathogen information from outbreaks is shared with the US within a week. Officials say this helps detect global threats early and protect public health.

At the same time, it gives US pharmaceutical companies early access to pathogen data, allowing them to develop vaccines, medicines and diagnostics more quickly.

The US–DRC Health Agreement

The United States and the Democratic Republic of Congo (DRC) signed their health MoU on 26 February. According to the US State Department, the agreement focuses on strengthening the country’s ability to detect and contain infectious disease outbreaks before they spread internationally.

• The focus reflects the country’s recent health challenges.
• The DRC has experienced several Ebola outbreaks in recent years.
• It is also dealing with the world’s largest mpox outbreak.

Funding Commitments

Under the agreement:

• The US will invest up to $900 million over five years
• The DRC will increase its health spending by $300 million

Most of the funding will support a national integrated surveillance and outbreak response system.

This includes:

• A laboratory network capable of detecting outbreaks within seven days
• Faster outbreak investigations and response systems
• Coordination between the US and other global health partners

The MoU also aims to modernize health data systems through electronic medical records, interoperable platforms, better trained community health workers and expanded services for HIV, tuberculosis, malaria, polio and maternal and child health.

Minerals Before Health

In several cases, health agreements were preceded by deals related to natural resources.

The United States and the DRC first signed a strategic partnership on critical minerals. The deal aims to secure supplies of minerals needed for commercial and defense industries.

The DRC is one of the world’s largest sources of rare earth minerals, including cobalt and copper. China has historically dominated the purchasing and processing of these resources.

Recently, the DRC has begun opening its mineral sector to US investors. According to Reuters, the government sent Washington a shortlist of state owned assets involving:

• manganese
• copper
• cobalt
• gold
• lithium

Guinea followed a similar path. It signed a minerals MoU with the US on 5 February, followed by a health MoU on 27 February. The health agreement prioritizes strengthening laboratory networks and improving biosafety standards by 2027.

Legal Pushback and Rejected Deals

Not all countries are comfortable linking health support to access to resources or data.

In the DRC, a group of lawyers has challenged the minerals agreement in the Constitutional Court. They argue that the deal violates the constitution and undermines national sovereignty over natural resources.

Zimbabwe also withdrew from negotiations with the US over a similar agreement.

Officials said the country was asked to share biological resources and outbreak data for years without any guarantee that vaccines, treatments or diagnostics developed from that data would be available to Zimbabwe if a future crisis occurred. They also said the US did not offer reciprocal sharing of its own epidemiological data.

Concerns in Kenya and Zambia

Kenya’s agreement with the United States has also faced legal hurdles. The country’s High Court halted the MoU after two court challenges questioned provisions that could allow the US access to patient data and pathogen information.

Zambia has also expressed reservations about its proposed health deal with Washington. The agreement stalled after the US linked the billion dollar package to cooperation in the country’s mining sector, particularly copper and cobalt.

Zambia has since asked for revisions, saying parts of the deal do not align with its national interests.

Critics Call the Policy “Extractive”

Some experts argue that these agreements reflect a broader shift in US global health policy.

Sophie Harman, professor of international politics at Queen Mary University of London, wrote in the BMJ that extraction appears to be central to the approach.

According to her analysis, the policy focuses less on improving global health outcomes and more on strengthening US economic and geopolitical interests, including competition with China.

She warns that countries entering such agreements could risk giving up resources or scientific data while gaining relatively limited health benefits.

Rare diseases may be individually uncommon, but together they represent a large and persistent care gap. More than 300 million people globally live with a rare condition, and when families and caregivers are counted, the impact touches over one billion lives. The economic burden is estimated to exceed $7 trillion each year.

In India, the challenge is compounded by geography, uneven specialist availability and the lifelong nature of many rare conditions. The question is no longer whether the system recognises the need, but whether it can deliver continuous care at scale.

Why Patients Still Struggle To Reach Care

For most rare disease patients, the hardest part is not always the science but the pathway to care. Diagnosis is often delayed, sometimes by years. Patients move between providers carrying incomplete records. Specialist centres are concentrated in a few large cities, forcing families to travel repeatedly for consultations that may last only minutes. This is both financially draining and clinically inefficient.

Telemedicine is beginning to ease some of this pressure. Virtual consultations allow specialists to extend their reach beyond metropolitan clusters. For families in tier two and tier three locations, this can mean earlier clinical input and fewer avoidable journeys.

Remote monitoring tools are also shifting care from episodic hospital visits to continuous oversight, which is particularly valuable for conditions that require close tracking over time.

Why Data Matters More Than Ever

If access is the visible challenge, data fragmentation is the structural one. Rare disease information remains scattered across hospitals, laboratories and individual case files. This weak visibility affects everything from prevalence estimates to therapy development. Policymakers struggle to size the problem accurately. Clinicians miss longitudinal patterns. Industry investment becomes harder to justify.

Digital health systems can address this by creating longitudinal patient records that follow individuals across providers. Even relatively modest steps such as strengthening diagnostic reporting or building disease registries can significantly improve coordination. For rare diseases, where patient numbers are small and widely dispersed, structured data is not a luxury. It is the backbone of effective care.

India’s Digital Opportunity

India has begun building the rails needed for this transition. The Ayushman Bharat Digital Mission is creating a national health data architecture anchored in unique health IDs and interoperable records. If applied rigorously to rare diseases, this infrastructure can support lifelong patient tracking, improve referral accuracy and give policymakers clearer visibility into disease burden.

Interoperability will determine how far this effort goes. The growing adoption of FHIR standards and API led systems is slowly allowing previously disconnected hospital platforms to exchange clinical information. For rare disease patients, whose care often spans multiple providers and years of follow up, this continuity is not technical detail. It is essential to safe treatment.

AI Moves From Promise To Practice

Artificial intelligence is also starting to show practical value. Globally, AI based clinical decision support tools are being used to flag potential rare disease cases hidden within routine health records. This matters because many rare conditions present with non specific symptoms and are frequently missed in early stages.

Collaborations between technology firms and pharmaceutical companies are demonstrating how electronic health record analysis, suspect patient lists and longitudinal data can help clinicians triage cases earlier for confirmatory testing. As these tools mature and integrate into routine workflows, they could significantly shorten the diagnostic odyssey that rare disease families currently endure.

Engaging Patients Beyond The Clinic

At the patient level, the shift is becoming more practical and visible. Tools that let people log symptoms, get medication reminders and share updates in real time are helping them stay more consistent with treatment, while giving clinicians better insight between visits. For lifelong conditions, this kind of day to day support brings care into the flow of everyday life, where most disease management actually happens.

Federated data models add an important layer of trust. By enabling analysis across multiple small patient populations without moving sensitive personal data, they address both privacy concerns and the sample size limitations that have historically slowed rare disease research.

From Pilots to Systems

Progress is visible across both public and private sectors. Regulated digital health platforms are already supporting rare disease programmes in several countries. Industry collaborations are using AI to detect conditions that often go undiagnosed for years. Public genomic databases are generating new diagnoses by enabling experts to build on shared evidence.

India’s immediate task is to move beyond isolated pilots. Telemedicine networks must be tied to referral protocols and reimbursement pathways. Digital registries must be built with strong governance and patient trust. AI tools need to be embedded into everyday clinical workflows rather than remaining demonstration projects.

Why Investment Makes Fiscal Sense

Poorly managed rare diseases create avoidable hospitalisations, lost productivity and long term care costs. Evidence increasingly shows that targeted investments in data systems, screening and coordinated care can reduce downstream expenditure. For low- and middle-income countries working within tight health budgets, these are not marginal gains.

India already has many of the building blocks needed to improve rare disease care, from expanding digital health infrastructure to growing AI capabilities and increasing policy focus. The real test now is disciplined execution.

Telemedicine networks must deepen their reach, patient registries need to become reliable and usable, data must move securely across systems, and clinicians should have decision support tools that fit into everyday practice. Taken together, these steps can meaningfully narrow today’s access gaps.

Digital health will not make rare diseases any less complex. But if implemented thoughtfully, it can reduce distance, shorten delays and bring much needed continuity to care journeys that are currently fragmented. For families managing lifelong conditions, that would be a tangible and much overdue shift.

In India, it is not uncommon for families to travel across cities, sometimes across states, seeking answers for symptoms that simply don’t make sense. A child who is not meeting developmental milestones. A young adult with unexplained muscle weakness. Recurrent hospital visits with no clear diagnosis.

For many, this long and frustrating search for clarity is what medicine calls the diagnostic odyssey.

Rare diseases are individually uncommon, but collectively they affect millions of people worldwide. Rare diseases affect an estimated 263–446 million people worldwide, spanning every geography, healthcare system, and socioeconomic context. India alone is estimated to have 70 million people living with rare diseases.

Importantly, although 70%–80% of rare diseases are genetic in origin, routine medical practices often consider genetic testing only after years of inconclusive evaluations.

In India, this challenge is amplified by several factors, including limited awareness of rare conditions, uneven access to specialized testing across regions, and a tendency to treat symptoms individually rather than look for a unifying cause.

A child may see a neurologist for seizures, a gastroenterologist for feeding issues, and a developmental pediatrician for delays, without anyone connecting the dots.

Studies have shown that patients and their families frequently wait years before receiving a confirmed diagnosis. Globally, rare disease diagnosis can take anywhere between 5–30 years.

In a country like India, where healthcare expenses are often paid out-of-pocket, this prolonged uncertainty can be devastating. Beyond cost, there is the psychological toll; parents wondering if they missed something and adult patients often questioning whether their symptoms are “all in their head”. During this period, families undergo repeated tests, face conflicting opinions, and bear significant emotional and financial strains.

Research shows that families experience profound emotional burden during the diagnostic odyssey, including stress, anxiety, and feelings of isolation.

Why Do These Conditions Stay Undetected For Years?

In many cases, the explanation is written into a person’s DNA. Genetic disorders rarely announce themselves clearly; instead, they often mimic common illnesses. Fatigue may look like anemia, developmental delay may resemble a learning difficulty, and repeated infections might be treated as isolated events rather than part of a larger pattern. Because the symptoms overlap with more familiar conditions, doctors naturally begin by treating what appears most likely.

Most healthcare systems also follow a step-by-step diagnostic approach; rule out the common causes first, then move to less common ones if symptoms persist. While this method works well for typical illnesses, it can significantly delay answers for rare genetic conditions. Without looking directly at the genetic blueprint, the underlying cause may remain hidden, even as the visible symptoms are managed one at a time.

Today, advances in genomic technologies such as whole-exome sequencing (WES) and whole-genome sequencing (WGS) allow us to examine thousands of genes simultaneously. Rather than guessing which gene might be responsible, we can comprehensively analyze a patient’s DNA to search for answers.

Evidence increasingly supports the use of genomic sequencing earlier in the diagnosis and care of rare diseases. Similarly, studies highlight how genomic testing not only provides diagnoses but also directly influences treatment decisions and long-term care planning.

In the Indian context, integrating genetic testing earlier could transform care. Instead of years of fragmented consultations, patients could receive a precise diagnosis sooner. This clarity can:

• Prevent unnecessary or repeated investigations
• Guide appropriate treatment strategies
• Inform family members about potential risks
• Enable informed decisions about future pregnancies
• Equally important, it replaces uncertainty with understanding.

Encouragingly, awareness around rare diseases is growing in India, and conversations around early genomic testing are becoming more mainstream. As technology becomes more affordable and accessible, we have an opportunity to fundamentally change the patient journey.

No family should spend years searching for answers when science has the tools to help. By embracing genomic medicine earlier in the diagnostic pathway, we can shorten the odyssey, reduce suffering, and empower families with clarity.

Because when symptoms don’t add up, sometimes the answer lies written in our genes.