Diabetes

Posted on autoimmune conditions, Diabetes

Engineered immune cells may be able to tame inflammation

Immune cells that are designed to soothe could improve treatment for organ transplants, type 1 diabetes and other autoimmune conditions.
Immune cells designed to soothe could improve treatment for organ transplants, type 1 diabetes and other autoimmune conditions.

When the immune system overreacts and begins attacking the body, the only option may be to suppress the entire system, potentially risking infections or cancer.

Scientists at UC San Francisco have discovered a more precise method to regulate the immune system.

The technology uses engineered T cells that act as immune “referees” to soothe overreacting immune responses. They also can mop up inflammatory molecules. 

The new approach could prevent the body from rejecting transplanted organs and tissues, such as pancreatic islet cells, sometimes used to treat type 1 diabetes. Thus, recipients would not need to take harsh immunosuppressant drugs.

“This technology has the potential to restore balance to the immune system,” said Wendell Lim, PhD, a cellular and molecular pharmacology professor at UCSF and co-senior author of the paper published on December 5 in *Science*. “We view it as a potential platform for addressing various types of immune dysfunction.”

Lim and his colleagues were inspired by “suppressor” cells, the immune system’s natural brakes. They wanted to use suppressor cells to temper immune responses, such as inflammation.

Unfortunately, suppressor cells can’t always stop a dangerous immune response. In type 1 diabetes, for example, the immune system destroys pancreatic islet cells while these suppressor cells stand by. 

The team adapted the suppressor cells’ anti-inflammatory abilities to work in CD4 immune cells, the same cells that are used to make cancer-killing CAR T cells. They also gave these cells a molecular sensor to guide them to their target tissue in the body.

Proof of principle in type 1 diabetes 

The scientists tailored a batch of immune referees to search for human pancreatic islet cells and then produce TGF-Beta and CD25, molecules that can muzzle killer T cells.

They introduced the engineered referee cells into mice that had received a transplant of human islet cells, modelling the treatment for type 1 diabetes.

The referee cells found the vulnerable islet cells and stopped the killer T cells from attacking, and the islet cells survived.

“It would be life-changing for people with type 1 diabetes if they could get new islet cells without needing to take immunosuppressants and stop having to take insulin every day,” said Audrey Parent, PhD, associate professor in the UCSF Diabetes Center and a co-senior author of the paper.

Lim envisions a future in which organ transplant patients, or those with autoimmune diseases, receive therapies that only treat the specific regions of the body where the immune system is misbehaving. 

This could prevent the significant side effects from general immunosuppressants and the infections and cancers that arise when the immune system is disabled completely.

The new technology could also be used to fine-tune CAR T cell therapies for cancer so that these cells only attack tumors and not healthy tissue.

Posted on Diabetes, Diet

Eating dark chocolate linked with reduced risk of type 2 diabetes

Study participants who consumed at least five servings of any chocolate per week showed a 10% lower risk of type 2 diabetes (T2D) compared to those who rarely or never ate chocolate. Dark chocolate had an even bigger impact: Participants who consumed at least five servings of this chocolate per week showed a 21% lower risk of T2D.
Participants in the study who ate at least five servings of any chocolate per week had a 10% lower risk of developing type 2 diabetes (T2D) compared to those who rarely or never consumed chocolate. Dark chocolate had an even more significant effect; participants who drank at least five servings of dark chocolate per week experienced a 21% lower risk of T2D.

“Our research indicates that not all chocolate is the same,” said Binkai Liu, the lead author and a doctoral student in the Department of Nutrition. “For chocolate lovers, this reminds them that small choices, such as dark chocolate instead of milk chocolate, can positively impact their health.”

The existing research on chocolate and T2D shows inconsistent findings, with few studies differentiating between chocolate types, specifically dark and milk chocolate.

The researchers aimed to address a gap in knowledge by utilizing data from the Nurses’ Health Studies I and II, as well as the Health Professionals Follow-up Study. Over more than 30 years, 192,000 adult participants who were free of diabetes at the beginning of the study reported their dietary habits, including chocolate consumption, alongside updates on their diabetes status and body weight. By the end of the study, nearly 19,000 participants had reported a diagnosis of type 2 diabetes (T2D). Among the almost 112,000 participants who specifically reported their intake of dark and milk chocolate, around 5,000 were diagnosed with T2D.

The study found that participants who consumed at least five ounces of any type of chocolate per week had a 10% lower risk of developing type 2 diabetes (T2D) than those who never or rarely consumed chocolate. Dark chocolate had an even more significant impact: participants who ate at least five servings of dark chocolate each week showed a 21% lower risk of T2D. Additionally, the researchers observed a 3% reduction in risk for every serving of dark chocolate consumed weekly. In contrast, consumption of milk chocolate was not linked to a reduced risk of T2D. Moreover, increased intake of milk chocolate—unlike dark chocolate—was associated with long-term weight gain, which can contribute to the development of T2D.

“We were surprised to find a clear distinction between the effects of dark and milk chocolate on diabetes risk and long-term weight management,” said Qi Sun, the corresponding author and an associate professor in the Departments of Nutrition and Epidemiology. “Although dark and milk chocolate contain similar levels of calories and saturated fat, it seems that the rich polyphenols in dark chocolate may counteract the negative effects of saturated fat and sugar on weight gain and diabetes. This intriguing difference warrants further exploration.”

Posted on Diabetes

High blood sugar in healthy adults linked to lower brain activity

New research shows combined use of sodium glucose co-transporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP1-RAs) is likely to offer additional protection against heart and kidney disease in patients with diabetes

A recent study found that high blood sugar may negatively affect brain health even in individuals who do not have diabetes. Although the relationship between blood sugar levels and brain health is well established in those with diabetes, this study is the first to investigate this link in people without the condition.

“Our findings indicate that individuals who do not have a diabetes diagnosis may still have elevated blood sugar levels that could negatively affect their brain health,” said Dr Jean Chen, the senior author of the study and a Senior Scientist at the Rotman Research Institute. . “Blood sugar levels exist on a spectrum; they cannot simply be categorized as healthy or unhealthy.”

The study, “Associations Among Glycemic Control, Heart Rate Variability, and Autonomic Brain Function in Healthy Individuals: Age—and Sex-Related Differences,” was recently published in the journal Neurobiology of Aging. It examined 146 healthy adults aged 18 and older. Researchers analyzed each individual’s blood sugar levels, brain activity through magnetic resonance imaging (MRI) scans, and heart rate variability using electrocardiogram (ECG) readings.

“The findings emphasize the importance of managing blood sugar through a healthy diet and regular exercise, as this benefits not just your body but also your brain,” said Dr. Chen, who is Canada Research Chair in Neuroimaging of Aging and a Professor of Biomedical Physics at the University of Toronto. “Additionally, it’s crucial to have regular checkups and collaborate with a healthcare provider, especially if you have been diagnosed with pre-diabetes.”

Main study findings

  • Higher blood sugar was associated with decreased connections in brain networks. These networks play a crucial role in all aspects of cognition, including memory, attention, and emotion regulation.
  • The effect was more substantial in older adults, but it was present across all ages; older adults generally had higher blood sugar than younger adults.
  • The effect was also stronger in women than in men.
  • In addition, there was a link between higher blood sugar and lower heart rate variability – the beat-to-beat change in an individual’s heart rate. Previous research indicates that higher heart rate variability is associated with better brain health.

In future work, the researchers could investigate how to improve brain function by changing heart-rate variability. Heart rate variability is an easier target for intervention than blood sugar, especially in nondiabetic individuals.

Posted on Cardiovascular disease, Diabetes

World’s most common heart valve disease linked to insulin resistance in large study

Newly-established link could open doors for new treatments of aortic stenosis – which effects 2% of over 65s worldwide
Newly-established links could open doors for new treatments for aortic stenosis, affecting 2% of over 65s worldwide.

A sizeable new population study of men over 45 indicates insulin resistance may be an essential risk factor for the development of the world’s most common heart valve disease – aortic stenosis (AS). 

Published today in the peer-reviewed journal Annals of Medicine, the findings are believed to be the first to highlight this previously unrecognised risk factor for the disease. 

It is hoped that by demonstrating this link between AS and insulin resistance – when cells fail to respond effectively to insulin and the body makes more than necessary to maintain normal glucose levels – new avenues for preventing the disease could open.  

Aortic stenosis is a debilitating heart condition. It causes the aortic valve to narrow, restricting blood flow out of the heart. Over time, the valve thickens and stiffens, making the heart work harder to pump blood effectively around the body. If not addressed, this can gradually cause damage that can lead to life-threatening complications, such as heart failure. 

People living with AS can take years to develop symptoms, which include chest pain, tiredness, shortness of breath and heart palpitations. Some may never experience symptoms but may still be at risk of heart failure and death. Previously identified risk factors for AS include age, male sex, high blood pressure, smoking and diabetes. 

Insulin resistance, which often develops years before the onset of type 2 diabetes, occurs when cells fail to respond effectively to insulin, the hormone responsible for regulating blood glucose levels. In response, the body makes more insulin to maintain normal glucose levels – leading to elevated blood insulin levels (hyperinsulinemia).  

In the current study, researchers analysed data from 10,144 Finnish men aged 45 to 73, all initially free of AS, participating in the Metabolic Syndrome in Men (METSIM) Study. At the start of the study, the researchers measured several biomarkers, including those related to hyperinsulinemia and insulin resistance. After an average follow-up period of 10.8 years, 116 men (1.1%) were diagnosed with AS. 

The team identified several biomarkers related to insulin resistance – fasting insulin, insulin at 30 minutes and 120 minutes, proinsulin, and serum C-peptide – associated with increased AS risk. These biomarkers remained significant predictors of AS, even after adjusting for other known risk factors, such as body mass index (BMI) and high blood pressure, or excluding participants with diabetes or an aortic valve malformation. 

The researchers then used advanced statistical techniques to isolate key biomarker profiles, identifying two distinct patterns that indicate insulin resistance as a predictor of AS, independent of other cardiovascular risk factors, such as age, blood pressure, diabetes, and obesity. 

“This novel finding highlights that insulin resistance may be a significant and modifiable risk factor for AS,” says lead author Dr Johanna Kuusisto, from the Kuopio University Hospital in Finland. 

“As insulin resistance is common in Western populations, managing metabolic health could be a new approach to reduce the risk of AS and improve cardiovascular health in ageing populations. Future studies are warranted to determine whether improving insulin sensitivity through weight control and exercise measures can help prevent the condition.” 

This study’s major strengths include its large population-based cohort and long follow-up period. However, its limitations include the sole focus on male subjects and the relatively small number of AS cases, which may limit the generalisability of the findings to other populations. 

Posted on Diabetes, Diet

No ‘one size fits all’ treatment for Type 1 Diabetes, study finds

Researchers: "We have miscalculated for decades – half of an insulin dose may not work as expected"

A new study has found that factors beyond carbohydrates substantially influence blood glucose levels, meaning current automated insulin delivery systems miss vital information required for glucose regulation.

A team of researchers from the University of Bristol analysing automated insulin delivery data from people with Type 1 Diabetes (T1D) discovered that unexpected patterns in insulin needs are just as common as well-established ones.

The study, published today in JMIRx Med, aimed to identify patterns in insulin needs changes and analyse how frequently these occur in people with T1D who use OpenAPS, a state-of-the-art automated insulin delivery system (AID).

Lead author Isabella Degen from Bristol’s Faculty of Science and Engineering explained: “The results support our hypothesis that factors beyond carbohydrates play a substantial role in euglycemia – when blood glucose levels are within the standard range.

“However, without measurable information about these factors, AID systems are left to adjust insulin cautiously with the effect of blood glucose levels becoming too low or high.”

Type 1 Diabetes is a chronic condition in which the body produces too little insulin, a hormone that regulates blood glucose.

The principal treatment for T1D is insulin that is injected or pumped. The amount and timing of insulin must be skilfully matched to carbohydrate intake to avoid increased blood glucose levels. Beyond carbohydrates, other factors such as exercise, hormones, and stress impact insulin needs. However, how often these factors cause significant unexpected effects on blood glucose levels has been little explored, meaning that despite all advances, insulin dosing remains a complex task that can go wrong and result in blood glucose levels outside the range that protects people with T1D from adverse health effects.

The findings highlight the complexity of glucose regulation in T1D and demonstrate the heterogeneity in insulin needs among people with T1D, underlining the need for personalised treatment approaches.

For factors beyond carbohydrates to become more systematically included in clinical practice, scientists need to find a way to measure and quantify their impact and use this information in insulin dosing. This could also aid more accurate blood glucose forecasting, which the study showed is not consistently possible from information about insulin and carbohydrates alone.

Isabella added: “Our study highlights that managing Type 1 Diabetes is far more complex than counting carbs.

“The richness of insights that can be gained from studying automated insulin delivery data is worth the effort it takes to work with this type of real-life data.

“What surprised us most was the sheer variety of patterns we observed, even within our relatively small and homogenous group of participants.

“It’s clear that when it comes to diabetes management, one size doesn’t fit all.

“We hope our results inspire further research into lesser-explored factors that influence insulin needs to improve insulin dosing.”

The team is now advancing time series pattern-finding methods to handle real-life medical data’s diverse and complex nature, including irregular sampling and missing data. Their current focus is on developing innovative segmentation and clustering techniques for multivariate time series data tailored to uncover more granular patterns and handle the challenges AID data poses.

To support this future research, the team seeks long-term, open-access AID datasets that include a wide range of sensor measurements of possible factors and a diverse cohort of people with T1D. Additionally, they aim to collaborate with time series and machine learning experts to address technical challenges such as handling irregularly sampled data with varying intervals between variables and uncovering causalities behind observed patterns, ultimately driving innovations in personalised care.