Hacking the Human OS – IEEE

health_keyboard

A mind-blowing report from IEEE about the human body’s operating system

Can we harvest digital health data from trackers and sensors to improve our health and well-being? I summarized below what you will find on the IEEE dedicated web page. I was amazed by the variety and depth of all the innovations presented in these pages. Some of them have certainly the power to be game changers in the health care world. I’m looking forward to seeing all the advances coming to life!

Reading the Code

Several technologies are close to the market and will help us monitor our health. A very good example is the biostamps developed by John Rogers from the University of Illinois. These tiny, stretchable and skin-like sensors are able to send information and data to our smartphone alerting us whether something is happening in our body. More and more complex data could be sensed such as blood oxygen, blood glucose and even muscle weakness or sleep patterns.

Another fascinating example that could change the life of Type 1 diabetes patients is the artificial pancreas. It links “data from an implanted blood-sugar sensor to a computer, which then controls how a pump worn on the hip dribbles insulin under the skin through a pipette. In its fully realized form, the machine would take the patient out of the decision-making loop”. Advanced versions of the system are currently in clinical trials. Continuous monitoring is a huge advance in the field of disease management. It could strongly lighten the daily burden of each patient.

Another field where wearable are very popular: athletes. They are always eager to test the last innovation in the wearables arena. Physiological measurements can be extremely useful to optimize training and rest periods, improve performance and avoid injuries. Sleeves, wristbands, sensors equipped with highest technology can really make a difference in the way we monitor and track performance.

A device rapidly diagnosing any medical condition or disorder… Sounds like science fiction, right? Like in Star Trek… Some of you may recall the tricorder. And guess what? It’s about to become reality thank to a competition launched by Qualcomm. 300 teams registered, 10 finalists which are about to deliver their prototypes very soon. Once the winner has been chosen, real life clinical trials will start and we will know if it’s really working as expected. It’s a huge step forward as it will allow the diagnosis (and maybe the start of a treatment) for a lot of people, not only in US or Europe but also in emerging countries where the lack of medical infrastructure is killing human beings…

 

Analyzing the Code

Technology companies showed their interest in healthcare only recently… It’s welcomed because without technology you cannot do anything with data sets. However, some people are afraid of their data becoming public and being hacked. I think that between these two extreme opinions, we can take the good from both sides and see what this can bring us. “Apple, Google, Microsoft, and Samsung, have all launched e-health initiatives, mostly based around smartphones and wearables. Indeed, the fast-growing health care business would seem a natural next step for the tech giants”. A lot of deals have been signed between pharmaceutical companies and technology firms: Google and Novartis; IBM, Apple, Medtronic & JNJ… These are deals to follow in order to analyze the outcomes. Great initiatives could really emerge and I think we are at the beginning of a new era!

Long term analysis could help us understand in a more detailed way how we get sick, how the disease develop and how we could have anticipated it by looking at biomarkers trends.

The new era of precision medicine is making a big difference for patients. An open-source platform has transformed the way patients are being treated. Surgery is not always the best option in oncology for example and sometimes drug treatment is much more effective. A thorough and careful analysis of all the parameters will help doctors taking the right decision for the right patient at the right time.

Real-time epidemics modelling could have saved lives. Building treatment centers at the right locations, anticipating the spread of the disease (in this case, Ebola) and how to limit the contagion were several of the criteria used to run the model. We will never know what would have happen without such a model but globally we can say that modelling is critical in disease management. Additionally, it is not the use of a single model that will be helpful but the customized and accurate modelling for each and every epidemic, according to its characteristics.

 

Changing the Code

Performing surgical interventions at very small scales is becoming a reality. “Thanks to developments in microfabrication and other areas, researchers are pushing the limits on the size and capabilities of objects small enough to move through the human body”. “With the right design, researchers say, a microrobot—or a swarm of them—could deliver a highly targeted dose of drugs or radioactive seeds, clear a blood clot, perform a tissue biopsy, or even build a scaffold on which new cells could grow”. For the time being, tests have only been run in animals.

A new emerging medical field: electrical therapy. Vagus nerve stimulation has the potential to treat several conditions from migraine to asthma, even immune diseases. Progress is very slow and several failures have made history… but new startups are created and renew the interest in this type of technology.

W like Watson, the digital MD. Watson is based on machine learning: “bringing together computer scientists and clinicians to assemble a reference database, enter case studies, and ask thousands of questions. When the program makes mistakes, it self-adjusts. Researchers also evaluate the answers and manually tweak Watson’s underlying algorithms to generate better output. Here there’s a gulf between medicine as something that can be extrapolated in a straightforward manner from textbooks, journal articles, and clinical guidelines, and the much more complicated challenge of also codifying how a good doctor thinks.” Progress is under way.

 

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Immunology or Metabolism – What can we say about Type 1 Diabetes?

Diabetes

Not always easy to categorize this disorder. What is being said today? An overview of opinions around the litterature

I conducted a small litterature search with the keywords “Type 1 Diabetes”, “Immunology”, “Metabolism”, “Metabolic”. PubMed returned 534 results. Google Search returned over 5 million…

I will start with some definition as well as resources and then try to answer the question.

 

Definition

Diabetes is not a single disease.

An excellent starting point is the Diabetes Journal Article: Diagnosis and Classification of Diabetes Mellitus. It says that “Diabetes mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. The chronic hyperglycemia of diabetes is associated with long-term damage, dysfunction, and failure of various organs, especially the eyes, kidneys, nerves, heart, and blood vessels. Several pathogenic processes are involved in the development of diabetes. These range from autoimmune destruction of the β-cells of the pancreas with consequent insulin deficiency to abnormalities that result in resistance to insulin action.” We have a good point here saying its origins are coming from an immune system dysfunction.

The American Diabetes Association provides in-depth overview of the symptoms, diagnosis, Type 1 and Type 2 as well as gestational. The website is full of stats and resources.

The CDC also contributes to knowledge and awareness with this comprehensive infographics. The IDF – International Diabetes Federation – is another source of information together with the WHO dedicated page on diabetes and the European Foundation for the Study of Diabètes.

CDC_diabetes-infographic

 

Some possible answers – Immunology vs. Metabolism

Coming back to Type 1 diabetes and my quick litterature search. From the 534 articles, I selected 5 among them seeming more relevant to start answering the question.

One of the first article I read is clearly stating that “Type 1 diabetes mellitus (T1DM) is a T cell-mediated autoimmune disease characterized by the destruction of pancreatic β cells”. But authors of another article insist on the metabolic abnormalities in Type 1 diabetes: “Clinical onset of type 1 diabetes (T1D) is thought to result from a combination of overt beta cell loss and beta cell dysfunction. However, our understanding of how beta cell metabolic abnormalities arise during the pathogenesis of disease remains incomplete. Despite extensive research on the autoimmune nature of T1D, questions remain regarding the time frame and nature of beta cell destruction and dysfunction.” “Determining the time frame of beta cell destruction and identifying metabolic mechanisms that drive beta cell dysfunction has high potential for successful interventions to maintain insulin secretion for individuals with established T1D as well as those with prediabetes.”

A study has been done to see whether any genetic link could justify the apparition and severity of T1D in children by looking at autoimmune diseases in the extended family. The short conclusion is that approximately 30% of children with newly diagnosed T1D have a 1st and or 2nd-degree relative affected by an autoimmune disease like autoimmune thyroiditis, celiac disease, Addison’s disease, pernicious anemia, rheumatoid arthritis and multiple sclerosis. Moreover, between 9 and 19% of the children with T1D have another autoimmune disease.

An interesting point is made about the influence of the microbiome both on metabolism and immune system. For the time being only mice have been used but the results have good chances to be extrapolable to humans. “Emerging evidence suggests that both host metabolism and immune function is crucially regulated by the intestinal microbiome. Recently, we showed that in the non-obese diabetic (NOD) mouse model of Type 1 Diabetes (T1D), the gut commensal microbial community strongly impacts the pronounced sex bias in T1D risk by controlling serum testosterone and metabolic phenotypes”.

Additionally, LADA (Latent Autoimmune Diabetes of the Adult), Type 1 diabetes diagnosed during adulthood seems to have a mix of genetic characteristics from childhood-onset Type 1 diabetes and Type 2 diabetes. “Metabolic changes at diagnosis reflect a broad clinical phenotype ranging from diabetic ketoacidosis to mild non-insulin-requiring diabetes”, as said in the article. In this case, we probably have a mix of immunological and metabolic changes leading to the disease.

I’m not sure whether one day we will be able to really discover the autoimmune or metabolic origins of T1D. It is probably a mix of both as complex disruptions and dysfunctions in the human body are leading to T1D onset.

 

Selected articles used

Latent autoimmune diabetes of the adult: current knowledge and uncertainty – 2015

Alteration of regulatory T cells in type 1 diabetes mellitus: a comprehensive review – 2015

Metabolic abnormalities in the pathogenesis of type 1 diabetes – 2014

Microbiome manipulation modifies sex-specific risk for autoimmunity – 2014

Extended family history of autoimmune diseases and phenotype and genotype of children with newly diagnosed type 1 diabetes – 2013

 

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