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The future of predicting lifestyle diseases is here in Asia
Cardiovascular conditions and diabetes are pandemic and the Asia – Pacific region is one of the worse affected in the world. If risk is detected early, these lifestyle diseases can be averted with preventive care. However, current medical knowledge is mostly based on data from Western ancestry, which doesn’t consider Asian ethnic differences, local diet, and lifestyle. All of which are major parameters to consider when examining risk of lifestyle ailments. Thankfully, things are changing for the better.

The colossal rise in lifestyle diseases, especially type 2 diabetes and heart conditions is not news. The numbers have been staggering for a couple of decades now, especially in the Asia-Pacific region. In South – East Asia, every fourth death is due to cardiovascular conditions.1 Currently, more than 60 per cent of people with diabetes live in Asia, while the Western Pacific region has over 138.2 million patients who are affected by this ailment.2 The WHO predicts that this number may rise to over 190 million by 2030 in the Asia-Pacific alone.3

While the picture may look grim at first glance, the situation is salvable. After all, as high as 80 per cent of chronic diseases can be prevented before they develop into severe illnesses.4 However, these conditions should be detected early enough. Both diabetes and heart disease prevention can be achieved by taking prophylactic measures and making simple lifestyle changes, such as a better diet and more exercise.

That said, most of the data and knowledge that we have today is derived from medical research of chronic diseases that have focused on populations of European ancestry. On the other hand, it is an established fact that ethnic and cultural, and lifestyle differences play an important role in the development of ailments such as diabetes mellitus and cardiovascular conditions. For instance, studies have found that South Asians have an increased risk of diabetes compared with Europeans that is unexplained by obesity and traditional or established metabolic measures.5 This is due to differences in genetic background, environmental factors and diet.

The good news is that the industry is recognising the need for region-specific medical data and things are changing rapidly.

Soon, better biomarkers for Asia

In a first-of-its-kind research initiative, the National University of Singapore (NUS) has collaborated with Nightingale Health (a Finnish biotechnology start-up), where the latter will provide NUS with novel biomarker data for 5,000 local blood samples from the Singapore Multi-ethnic Cohort (MEC) collection. This means, for the first time, researchers will have broad metabolic data that represent the local Malay, Indian and Chinese populations in Singapore.

This study, with local multi-ethnic blood samples, is unique as it's aiming to improve the prediction of type 2 diabetes, coronary artery calcification and changes in cardiovascular risk factors in the Asian population to a greater extent. The researchers will study how the blood biomarkers are associated with local diet and other lifestyle factors and mediate their associations with cardiovascular disease and type 2 diabetes risks.

Based on the results of the first phase, NUS and Nightingale plan to expand this research and analyse thousands of other samples in Singapore. The aim of this study is to identify biomarkers that are unique to the local population and thus predict the onset of lifestyle ailments more accurately. Going forward, this aims to help millions of Asians take tailored preventive steps against many chronic diseases.

Current Roadblocks

A lack of local data and research isn’t the only problem. Current popular methods to predict lifestyle ailments aren’t accurate enough. Meaning, there is often a delay and lack of accuracy in detecting a developing disease, and by the time it is diagnosed, there is very little time left for preventive care to kick in to avert the situation.

For instance, the cholesterol test which is standard in cardiovascular risk assessments. Although high levels of low – density lipoprotein cholesterol (LDL-C) are consistently associated with an increased risk of cardiovascular disease (CVD), standard methods to measure LDL-C are inaccurate.

A regular cholesterol test takes simple biochemical measurements of total triglycerides (TG), total cholesterol and high – density lipoprotein cholesterol (HDL-C). Here, the LDL-C is not always measured but approximated from other lipid measurements. Furthermore, standard direct assays measuring LDL-C have limited accuracy in reflecting cholesterol in LDL particles, as they also capture cholesterol in other lipoproteins such as very – low density lipoprotein (VLDL) and intermediate – density lipoprotein (IDL). Moreover, standard lipid tests quantify the total cholesterol, TG, content of lipoproteins without providing size-specific lipoprotein particle information.6 This is suboptimal in cardiovascular risk assessment because only small VLDL, IDL and LDL particles are able to enter the arterial intima, and cause atherosclerosis.7 Formation of atherosclerotic plaque causes the arteries to narrow and interrupt blood flow, which can in turn cause heart attack and stroke.

Another commonly researched method to predict type 2 diabetes and cardiovascular diseases is genetic screening. Research has shown that these ailments could be hereditary. Studies have proven that the risk of developing diabetes is two times higher in individuals who have a first-degree family history of this disease.8 Same goes for CVD as well. For example, a recent study shows that genetic information can identify a subset of a population who have greater than threefold increased risk for type 2 diabetes and heart disease.9

Although genetic screening can be useful in identifying high-risk individuals at an early stage of their life, it cannot be used to track changes in one's health due to lifestyle modifications. However, tracking these health changes is extremely important as many studies have shown that an individual’s lifestyle has a significant effect on the person's overall disease risk. In fact, making the right lifestyle choices can even help individuals with increased genetic risk. 10, 11

The answer lies in metabolomics

This is where a comprehensive metabolomic report is necessary, as it can identify risks of both heart disease and diabetes up to 10 years before the onset of the illnesses. Since metabolomics track lifestyle-related parameters closely, they provide a tool to monitor one’s health through lifestyle interventions. This provides people with actionable information and an opportunity to prevent diseases such as diabetes and CVD.

A comprehensive metabolomic report in simple terms, is a blood analysis method that measures an extensive number of biomarkers that can identify metabolic disturbances associated with CVD and type 2 diabetes. These anomalies typically occur years before a person is diagnosed with the illnesses, making metabolomics an appropriate method to predict these lifestyle diseases. A comprehensive report combines metabolic biomarkers such as blood glucose, amino acids, apolipoprotiens, fatty acids, and other genetic and lifestyle-related parameters. Moreover, as we know, lifestyle illnesses are caused by both genetic and non-genetic factors. Which is the combination of metabolic biomarkers such as blood glucose, amino acids, apolipoproteins, fatty acids and other genetic and lifestyle-related parameters.

Characteristics of heart disease and type 2 diabetes can be identified by recognising disturbances across multiple metabolic pathways. For instance, medical evidence demonstrated an association between blood concentration of amino acids and type 2 diabetes. The new “blood test 2.0”, provides over 220 biomarkers12 from a single blood sample which includes simultaneous quantification of routine lipids, lipoprotein subclass profiling (with lipid concentrations within 14 subclasses), fatty acid composition, along with various low-molecular metabolites including amino acids, ketone bodies and gluconeogenesis-related metabolites, measured in molar concentration units.

Compared to this, standard cholesterol test detects only 4-5 blood biomarkers. The current risk models are based on these routine markers and their ability to predict illnesses is thus limited, especially among the Asian population. This is because the present-day biomarkers have been developed based on population data collected from European ancestry. Therefore, it is not representative of the Asian population at risk of getting a disease which could lead to possible complications for the patients at a later stage.

Metabolomics in Asia

Once profiled through metabolomics, the results can monitor aberrations across multiple molecular pathways and thus predict long-term risk of heart diseases and type 2 diabetes, even in young adults13 The NUS-Nightingale research project is trying to take this predictive method in Asia one step further by linking it with local data. Findings from Asia-focused data will make the new biomarkers even more accurate in predicting the risk factors of lifestyle ailments in the region.

So, how will a couple of hundred microliters of blood provide so many biomarkers? By using an analytical technique called nuclear magnetic resonance (NMR) spectroscopy along with Nightingale’s proprietary software that uses statistical analysis to convert the NMR readings into measurable medical data.

The NMR instrument exposes the blood sample to a magnetic field to measure resonance frequencies of different molecules. Different molecules present in the sample emit a unique signal of magnetic field fluctuations that is directly proportional to their concentration in the blood. This resonance data is then run through the software that uses advanced statistical methods to convert this information into measurable readings.

The NUS-Nightingale research project is unique as the study will use NMR technology and metabolomics to analyse blood samples from the Asian population. Researchers have already started working on the project and they hope to have the first set of findings out very soon.

What makes this project even more promising is that the NMR data produced by Nightingale’s software is standardised, fully automated and gives a real-time analysis. Since there is no human intervention, the chances of error are reduced. Moreover, making the markers standardised helps in further research as comparing, combining and replicating results becomes easier. This means that the findings and applications of the Singaporean study won’t be limited to Singapore alone. It can easily be adapted and replicated very quickly in other parts of Asia as well.

References

  1. http://www.searo.who.int/entity/noncommunicable_diseases/Factsheet_CVD.pdf?ua=1
  2. Arun Nanditha, Ronald C.W. Ma, Ambady Ramachandran, Chamukuttan Snehalatha, Juliana C.N. Chan, Kee Seng Chia, Jonathan E. Shaw, Paul Z. Zimmet, Diabetes in Asia and the Pacific: Implications for the Global Epidemic
  3. Diabetes Care Mar 2016, 39 (3) 472-485; DOI: 10.2337/dc15-1536
  4. https://www.who.int/diabetes/facts/world_figures/en/index6.html
  5. https://www.who.int/chp/chronic_disease_report/en/
  6. Tillin, T., Hughes, A. D., Wang, Q., Würtz, P., Ala-Korpela, M., Sattar, N., … Chaturvedi, N. (2015). Diabetes risk and amino acid profiles: cross-sectional and prospective analyses of ethnicity, amino acids and diabetes in a South Asian and European cohort from the SABRE (Southall And Brent REvisited) Study. Diabetologia, 58(5), 968–979. doi:10.1007/s00125-015-3517-8
  7. Manuel Mayr, Robert Gerszten, Stefan Kiechl, Cardiovascular Risk Beyond Low-Density Lipoprotein Choloesterol, Journal of the American College of Cardiology Feb 2018, 71 (6) 633-635; DOI: 10.1016/j.jacc.2017.12.040
  8. Micheal V. Holmes and Mika Ala-Korpela, What is ‘LDL choloesterol’? Nature Reviews Cardiology 16, 197 – 198 (2019)
  9. https://www.uclahealth.org/most-heart-attack-patients-cholesterol-levels-did-not-indicate-cardiac-risk
  10. Amit V. Khera, Mark Chaffin, Krishna G. Aragam, Mary E. Haas, Carolina Roselli, Seung Hoan Choi, Pradeep Natarajan, Eric S. Lander, Steven A. Lubitz, Patrick T. Ellinor and Sekar Kathiresan, Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations, Nature Genetics 50, 1219 – 1224 (2018)
  11. Khera, A. V., Emdin, C. A., Drake, I., Natarajan, P., Bick, A. G., Cook, N. R., … Kathiresan, S. (2016). Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease. The New England journal of medicine, 375(24), 2349–2358. doi:10.1056/NEJMoa1605086
  12. Tikkanen, E., Gustafsson, S., & Ingelsson, E. (2018). Associations of Fitness, Physical Activity, Strength, and Genetic Risk with Cardiovascular Disease: Longitudinal Analyses in the UK Biobank Study. Circulation, 137(24), 2583–2591. doi:10.1161/CIRCULATIONAHA.117.032432
  13. https://prismic-io.s3.amazonaws.com/nightingaleprod%2F4bef89a2-0892-4b56-9eb6-56b42e803e13_nightingale_blood-biomarkers.pdf
  14. Ari V. Ahola-Olli, Linda Mustelin, Maria Kalimeri, Johannes Kettunen, Jari Jokelainen, Juha Auvinen, Katri Puukka, Aki S. Havulinna, Terho Lehtimäki, Mika Kähönen, Markus Juonala, Sirkka Keinänen-Kiukaanniemi, Veikko Salomaa, Markus Perola, Marjo-Riitta Järvelin, Mika Ala-Korpela, Olli Raitakari, Peter Würtz, Circulating metabolites and the risk of type 2 diabetes: a prospective study of 11,896 young adults from four Finnish cohorts, bioRxiv 513648; doi: https://doi.org/10.1101/513648


Teemu Suna Co – founder and CEO at Nightingale Health


Dr. Peter Würtz Co – founder and Scientific Director at Nightingale Health


Dr. Emmi Tikkanen Senior Data Scientist at Nightingale Health


MD Viljami Aittomäki Medical Scientist at Nightingale Health

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APBN Editorial Calendar 2019
January:
Taiwan Medical tourism
February:
Marijuana as medicine — Legal marijuana will open up scientific research
March:
Driven by curiosity
April:
Career developments for researchers
May:
What's cracking — Antibodies in ostrich eggs
June:
Clinical trials — What's in a name?
July:
Traditional Chinese medicine in modern healthcare — Integrating both worlds
August:
Digitalization vs Digitization — Exploring Emerging Trends in Healthcare
September:
Healthy Ageing — How Science is chipping in
October:
Disruptive Urban Farming — Microbes, Plasmids, and Recycling
Editorial calendar is subjected to changes.
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