Two patients with unique genetic mutations in a single gene sparked the investigation of 40 researchers into the effects of gene expression on diabetes��

The discovery and mapping of the complete human genome in 2003 introduced the possibility of individualized medicine to a person’s physical and genetic makeup. Increasing evidence is now demonstrating that a patient’s unique genetic profile can be used to detect a disease’s onset, prevent its progression, and optimize its treatment.

This has led to enhanced global efforts to implement precision (personalized) medicine and pharmacogenomics in clinical practice. One such area of clinical practice is the treatment of diabetes.

In contrast, the most common types of diabetes are caused by multiple genes or lifestyle factors. Most cases of monogenic diabetes are inherited.

Dr. Pierre Zalloua, Professor and Chair of the Department of Molecular Biology and Genetics, collaborated with researchers from France, Germany, Austria, the United States, and Singapore to determine the gene responsible for two cases of monogenic diabetes. Their results were published in.

“Diabetes affects over 350 million people worldwide, and the discovery and study of genes responsible provide important insights for understanding disease mechanisms,” Dr. Zalloua explained. “With better understanding, we can improve quality of life and develop cost-effective care for diabetes patients.”

Diabetes mellitus is a group of metabolic diseases, all of which are characterized by high blood glucose levels. If left untreated, diabetes can lead to severe complications including blindness, kidney and heart disease, stroke, loss of limbs, and reduced life expectancy. It is a major public health problem, affecting hundreds of millions of people worldwide and representing a substantial economic burden on society.��

There are two types of diabetes: Type 1 and Type 2 diabetes. Type 1 usually begins in childhood with individuals suffering from their body’s inability to produce enough insulin, while Type 2 is commonly associated with obesity and usually occurs during middle age. Both types tend to run in families and genetic factors contribute to the disease, with interactions between genetic and environmental factors being critical.��

Dr. Zalloua said. “Remarkably, many of these genes encode key proteins for pancreas development.”

To determine which genes play a part in the development of diabetes, the research team examined two different patients with diabetes: one, a young French boy with neonatal diabetes, and a second Turkish child with diabetes diagnosed at 14 months. They showed that the patients inherited mutated alleles of one particular gene, ONECUT1. Two mutated alleles led to a severe form of neonatal diabetes where the child developed a small pancreas and a missing gall bladder, while one mutated allele saw an increased risk of diabetes in the second patient. The researchers were able to determine that ONECUT1 and its expression is a major player in diabetes.

Dr. Zalloua was the person who originally identified additional cases from the region linked to this gene, including a case from a patient in Lebanon. Analysis of these patients revealed various different ONECUT1 mutations, all linked to a risk of diabetes.

ONECUT1 affects a variety of processes including glucose metabolism, an important factor in the disease mechanism of diabetes. Its expression also influences the development of the pancreas and the gallbladder. Previous studies of ONECUT1 have focused on the gene’s role in retinal development, but it is now clear that ONECUT1 acts to determine what type of cell a stem cell becomes. Some human stem cells are pluripotent, meaning they can become any kind of cell in the body, and genes including ONECUT1 are the deciders. Mutations in this gene can therefore disrupt a very complex process at various stages.

The pancreas plays an essential role in converting food to fuel in the body: it helps in digestion and in regulating blood sugar. Two of the main pancreatic hormones are insulin, which acts to lower blood sugar, and glucagon, which acts to raise blood sugar. A functioning healthy pancreas automatically produces the right amount of insulin; in people with diabetes, the pancreas either produces little or no insulin, or the cells do not respond to the insulin that is produced.

To further validate their findings, the researchers examined a cohort of over 2000 German people with presumed type 2 diabetes, and identified 13 incidences of ONECUT1 mutations. In another, larger and multi-ethnic, cohort of almost 20,000 people with type 2 diabetes, the researchers also found that people with variants of the ONECUT1 gene were more likely to develop type 2 diabetes. However, they noted that the risk varied with the specific variant.

Identifying the cause means we can pinpoint the best treatment, offering an opportunity to shift focus from broad population-based standards of care to tailored treatments targeted to an individual molecular profile.

“We found that ONECUT1 controls mechanisms regulating endocrine development, which is involved in a wide spectrum of diabetes types,” Dr. Zalloua said. “We highlighted the broad contribution of ONECUT1 to diabetes pathogenesis, marking an important step towards precision medicine for diabetes.”

Jade Sterling
Science Writer
18 January 2022

The post Khalifa University Researcher Contributes to the Finding of a Novel Gene Involved in Human Diabetes appeared first on Khalifa University.

Real-time monitoring of sugar molecules is crucial in diabetes treatment, but current methods are invasive and expensive. Researchers from Khalifa University collaborated with an international team to investigate holey graphene, a novel low-cost material, for glucose sensors.��

The World Health Organization estimates that over 382 million people worldwide have diabetes, a metabolic disorder affecting blood sugar levels. The underlying cause of diabetes varies by type, but each type can lead to excess sugar in the blood, which could cause serious health problems. For all patients, blood sugar monitoring plays a crucial role in treatment.

The sugar molecules adsorb onto a layer of holey graphene, which alters the electronic properties of the material. These changes can be measured and correspond to blood sugar monitoring data to check the blood sugar levels without invasive testing.

Dr. Muhammad Sajjad, Postdoctoral Fellow, and Dr. Nirpendra Singh, Assistant Professor, both in the Khalifa University Department of Physics, collaborated with Dr. Puspamitra Panigrahi, Hindustan Institute of Technology and Science, India, Dr. Deobrat Singh and Prof. Rajeev Ahuja, Uppsala University, Sweden, Dr. Tanveer Hussain, The University of Queensland, Australia, and Prof. J. Andreas Larsson, Lulea University of Technology, Sweden. They published their results in.

“Since the first invention of a biosensor for glucose detection, there has been tremendous demand for low-cost, portable, and reliable glucose sensors,” Dr. Singh said. “So far, most of the available devices are dependent on an expensive glucose oxidase enzyme-based recognition unit and require people to deal with the painful finger-pricking process.”

Continuous monitoring of glucose levels in people with diabetes is essential to managing the disease and avoiding the complications associated with poorly-managed treatment. There are two types of glucose monitoring sensors, enzymatic and non-enzymatic, currently available in the market.

Enzyme-based sensors use glucose dehydrogenase (GDH) or glucose oxidase (GOx), which interact with glucose molecules, resulting in an electrical response correlated to the concentration of glucose. However, these sensors are expensive to manufacture and are sensitive to environmental conditions. Non-enzymatic sensors allow glucose to be oxidized directly on the surface of the sensor, where the atoms at the surface act as the electrocatalysts, resulting in high stability with repeated use and cost-effective fabrication.

Different materials have been used to develop non-enzymatic sensors, and although each material has its own advantages and limitations, the research team focused on graphene—specifically, holey graphene.

Graphene is a unique material comprising densely packed carbon atoms arranged in a hexagonal honeycomb lattice and can be exfoliated from the graphite. It is extremely versatile and has potential applications in various fields, particularly thanks to its superior optical, electrical, thermal, and mechanical properties.

In its purest form, graphene offers myriad applications. However, in recent years, the nanoscale perforation of 2D materials has emerged as an effective strategy to enhance and widen the applications of the material beyond its pristine form.

Holey graphene is a form of graphene with nanopores in its plane. The performance of the material is affected by the pore size, density, shape, and volume. Uniform pore shape and size distribution are usually optimal as it leads to enhanced thermal, mechanical and electrical properties. These pores are perfect for adsorption, where target molecules are collected by attaching to the surface of the pores.

“Since the performance of an electrochemical biosensor depends on the surface area to improve charge transfer and catalytic activity, two-dimensional graphene-like nanomaterials and functionalized graphene are now the best possible materials for a new generation of highly sensitive glucose sensors,” Dr. Singh said. “The holey graphene is very sensitive even at very low concentrations of glucose.”

These fluids are easily accessed without the need for any finger pricking and can be examined to identify various biomarkers, such as those involved in cancer, Alzheimer’s disease, Parkinson’s disease, cystic fibrosis, systemic sclerosis and glaucoma, and blood sugar levels for diabetes management.

When saliva, tears, or sweat hit the surface, the sugars interact with a layer of nitrogenated holey graphene (C2N) that is only a single atom thick. Glucose, fructose and xylose are the sugar molecules found in the body and when they interact with the holey graphene layer, the electronic properties of the layer are altered. These changes are measured and interpreted as various levels of sugar in the bodily fluid tested.

This work was supported by the Swedish Research Council, the Abu Dhabi Department of Education and Knowledge, and Khalifa University of Science and Technology.

Jade Sterling
Science Writer
20 December 2021

The post A New Blood Glucose Monitoring Device Using Holey Graphene appeared first on Khalifa University.

Two Khalifa University student papers have been accepted at the 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

The and will cover diverse topics of cutting-edge research and innovation in biomedical engineering and healthcare technology.

Fitting the theme of ‘Changing Global Healthcare in the Twenty-First Century’, Dahlia Hassan investigated the efficacy of a model in determining how to help patients suffering from fainting, while Feryal Alskafi, MSc in Biomedical Engineering student, developed a model to identify emotions from bodily responses. Dahlia is currently a Teacher’s Assistant for Dr. Herbert Jelinek, Associate Professor of Biomedical Engineering, and will begin her Master’s degree in Spring 2022.

Heart Rate Model to Help Reduce Fainting

Vasovagal syncope is a medical condition that can lead to fainting. This is caused by a temporary drop in the amount of blood that flows to the brain from a sudden drop in blood pressure or a drop in heart rate. It is considered to be the most common cause of fainting that becomes even more common with age.

Patients with vasovagal syncope often undergo a self-training program at home to improve their condition. In the training program, the patients are asked to stand against a wall without moving, twice a day for up to 30 minutes. After a few weeks of doing this daily, the patients are given the ‘head-up tilt test’ to determine whether the standing practice helped decrease their symptoms.

In a head-up tilt test, the patient begins lying flat in bed and the bed is gradually tilted to a maximum angle of 80 degrees. Gravity causes blood to pool in the legs, resulting in a blood pressure drop above the patient’s center of gravity. Baroreceptors sense the decrease in blood pressure and cause an increase in heart rate. In healthy individuals, although the blood pressure initially increases, the heart rate quickly returns to normal. In syncope patients, the heart rate remains high. While useful for diagnosis, the head-up tilt test is time-consuming, not available in all clinics, and carries the risk of inducing cardiac arrest.

As an alternative to the head-up tilt test, Hassan proposed a new way of determining whether the self-training program can help patients with syncope. She developed a model that uses a patient’s electrocardiogram (ECG) data, which are electrical signals from the heart, to predict heart rate changes and determine the efficacy of the home-based training program.

The data from her model can be used by clinicians to assess whether extended periods of standing can help decrease the amount of fainting episodes the patient experiences based on subsequent five-minute heart rate recordings, without the need to perform a head-up tilt test.

While the model can be used to determine heart rate changes at any time of day, relying only on the heart rate as an input is limiting. Hassan plans to further her work by including blood pressure as a parameter for the model.����

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Monitoring Our Emotions

Wearable sensors are already used to monitor health—heart rate sensors are commonly used to keep an eye on heart health and predict any adverse events. Further advances in sensors have also been used to recognize emotions using physiological signals. However, there is no universally accepted model for emotions, which Alskafi set out to change.

Emotions play a vital role in human behavior and psychology, exerting a powerful influence on processes such as perception, attention, decision-making, and learning. Emotions can be categorized by how they are felt, using valence, arousal and dominance. Valence is the positivity or negativity of an emotion; arousal is the level of excitement different emotions elicit; and dominance relates to feeling in or out of control in our response.

In healthcare, an individual profile that recognizes sources of stress, anxiety, depression or chronic diseases can be built by tracking emotions using wearable trackers. Alskafi recognized that while emotions are usually conveyed through body language and facial expressions, physiological manifestations of emotions could provide a more accurate representation. These are much harder to conceal and more difficult to manipulate when compared to body language, but some conditions cause people to present emotions differently. The physiological responses should be the same among all people as expression of emotions is shown through changes in heart rate, temperature and breathing patterns.

Alskafi fed these parameters into her model to classify physiological responses into different emotions. Anger and joy tend to be high arousal emotions, while sadness and reflection have low arousal levels. Fear and anger tend to be negative valence emotions, while joy has positive valence.

Her results found that the model performed best when it had fewer emotions to choose between, showing that the study can be used as a basis for further research in machine learning classification and algorithm development.

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Jade Sterling
Science Writer
20 September 2021

The post Student Biomedical Engineering Papers Accepted at EMBC appeared first on Khalifa University.