Origins of cardiometabolic syndrome


At the Amgen Australia Cardiometabolic Assembly in July 2022, experts discussed the intersection of cardiometabolic risk factors, current research, and the multidisciplinary management of cardiometabolic health. The opening session featured presentations on the origins of cardiometabolic syndrome as well as the genetic and socioeconomic determinants of the syndrome.

Speaking the same language of cardiometabolic syndrome

Professor Jonathan Shaw, Deputy Director of Clinical and Population Health at the Baker Heart and Diabetes Institute in Melbourne, began the session by asking, “What exactly is the cardiometabolic syndrome?” He explained the apparent degree of uncertainty about the terminology: while the term is often used interchangeably with metabolic syndrome, the term cardiometabolic syndrome, “emphasises the cardiovascular implications of metabolic disturbances,” he said.

Prof. Shaw highlighted the different approaches one could take to describe cardiometabolic syndrome, suggesting that the most useful way to consider the condition is as “a cluster of related factors – obesity, diabetes, dysglycaemia, hypertension, dyslipidaemia.” These factors are reflected in the published harmonised definition of metabolic syndrome.1

In reviewing the potential value of defining metabolic syndrome, Prof. Shaw suggested, “It provides a very useful emphasis on the metabolic and obesity factors that lead to cardiovascular disease that can help facilitate patient education on coexisting conditions, public health focus on lifestyle factors, and research into underlying causes.” He also pointed out that the definition is limited by a lack of consensus on factors and cut-offs to define the condition and clarity for risk prediction, and that it dichotomises continuous risk factors while omitting some major cardiovascular disease risk factors, such as age and smoking history.

Prof. Shaw presented an overview of recent studies that show glucose-lowering drugs can reduce risk for cardiovascular and renal disease,2-5 which he said suggested the importance of metabolic factors in the development of cardiovascular disease. He concluded with this call to action: “We have crossover and the need for people in different silos to understand how other silos work. In particular, cardiologists need to learn how to use diabetes and obesity drugs, and increasingly, people [working] in diabetes and other metabolic arenas need to upskill in cardiovascular management.”

Understanding the genetics of obesity and diabetes – how twinning can help

Prof. Emeritus Joe Proietto from the University of Melbourne and Austin Health, reviewed evidence supporting genetic drivers of obesity and type 2 diabetes.

Prof. Proietto presented data from studies in twins that demonstrate the importance of genetics for weight and fatness. He described a Danish study of individuals adopted as babies, which revealed that when it came to weight, genetic influences from the biological parents trumped environmental influences from the adoptive family.6

“So you might ask, how can obesity be genetic when the obesity epidemic is only recent? Genes, we know, don’t mutate that fast,” he pointed out. The answer lies in epigenetics: people who already had a genetic tendency to obesity developed severe obesity when exposed to obesogenic environmental factors, he explained. “But why is it possible to develop obesity, as opposed to mild overweight, without a gene?” Prof. Proietto asked. He described the two negative feedback systems that regulate body weight: leptin, which is produced by fat cells to inhibit hunger and increase energy expenditure, and an osteocyte-driven mechanism that is still not fully understood.7

“There are several lines of evidence that suggest that there is a strong genetic influence in type 2 diabetes,” noted Prof. Proietto. Evidence includes: differences in prevalence rates among indigenous tribes from South America and North America; an increased risk of developing type 2 diabetes when one or both parents have the disease; and concordance rates in twin studies. Prof. Proietto also described how over-expression of a specific gene – nicotinamide nucleotide transhydrogenase (NNT) can result in insulin hypersecretion and increased risk for type 2 diabetes.8

“Both obesity and type 2 diabetes have strong genetic causes, but we need more research, especially into the genetics of type 2 diabetes and the epigenetics of obesity,” Prof. Proietto concluded.

Socioeconomic factors in cardiometabolic disease – are we doing our job?

Professor Alex Brown (Aboriginal Health Equity Theme Leader at the South Australian Health and Medical Research Institute, Professor of Medicine at the University of Adelaide, and Scientific Director of the Aboriginal Health Grand Challenge and the Telethon Kids Institute) addressed the meeting to describe, “How social factors drive and pattern cardiovascular risk, and also the risk of diabetes.”

Prof. Brown referred to long-standing data from the Whitehall Study in the United Kingdom that demonstrated that people of lower socioeconomic status experienced higher mortality and disease burden, including that related to cardiovascular disease and type 2 diabetes.9 This inequality also exists in Australia, he explained: “Those in the lowest social strata have a much higher mortality burden than what we see in those in the more advantaged sectors of society,” adding that Aboriginal and Torres Strait Islander people carry a uniquely high burden that “seemingly operates outside of this social gradient phenomena in significant ways.”

But what drives this inequity in disease burden? In discussing different models of the social determinants of health, Prof. Brown highlighted, “Socioeconomic factors have a strong and enduring impact on the health of people in communities, and probably more so than just the physical environments in which they live, the behaviours which are either helpful or unhelpful, and the health care that people are able to access and receive”. When viewing a hierarchy of disease causality, where ‘upstream’, ‘midstream’, and ‘downstream’ determinants influence risk factors and subsequent disease development, Prof. Brown noted that it is important to remember, “No behaviour or risk is patterned within a vacuum.” Prof. Brown illustrated how interrelated socioeconomic factors affect health inequalities and burdens in type 2 diabetes (Figure)10 and described how maternal health and behaviour and adverse childhood experiences can drive generational risk.11,12

 

When it comes to cardiovascular disease, Prof. Brown explained, “The complexity of social factors influenced development of disease, not just from an individual level, but more importantly, on a population level.” These factors include socioeconomic status, work and neighbourhood environments, social relationships, race/ethnicity, sex, and access to healthcare.13

Returning to health inequities in Australia, Prof. Brown presented data from studies showing that for Aboriginal and Torres Strait Islander people, social factors including geographic location, income, poverty, and incarceration all impact cardiometabolic disease risk and outcomes.

“Socioeconomic status has been recurrently demonstrated to impact each stage of the [cardiometabolic] disease continuum. It can influence biological predictors of non-communicable disease in the future. We see variation in the prevalence of risk factors. We know that socioeconomic factors influence the patterning of this risk. It’s associated with differential access and receipt of care, and it’s associated with the development of a range of complications and reduced survival. So, if we’re not thinking about socioeconomic position and how it might influence the patient before us, we’re not doing our job,” Prof. Brown concluded.

Disclosure

This article was commissioned by Amgen. The content is based on studies and the presenter’s opinion. The views expressed do not necessarily reflect the views of the sponsor. Before prescribing please review the full product information of relevant products via the TGA website. Treatment decisions based on these data are the responsibility of the prescribing physician.

References

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  2. Zinman B, et al. N Engl J Med. 2015;373(22):2117-2128.
  3. Wiviott SD, et al. N Engl J Med. 2019;380(4):347-357.
  4. Marso SP, et al. N Engl J Med. 2016;375(19):1834-1844.
  5. Gerstein HC, et al. Lancet. 2019;394(10193):121-130.
  6. Stunkard AJ, et al. N Engl J Med. 1986;314(4):193-198.
  7. Jansson JO, et al. Proc Natl Acad Sci U S A. 2018;115(2):427-432.
  8. Aston-Mourney K, et al Diabetologia. 2007;50(12):2476-2485.
  9. Stringhini S, et al. PLoS Med. 2013;10(7):e1001479.
  10. Whiting D, et al. Diabetes: equity and social determinants. In: Blas E, Sivasankara Kurup A (Eds). Equity, social determinants and public health programmes. World Health Organization; 2010.
  11. Aizer A, Currie J. Science. 2014;344(6186):856-861.
  12. Dong M, et al. Circulation. 2004;110(13):1761-1766.
  13. Atkinson HG. SOCIAL DETERMINANTS OF CARDIOVASCULAR DISEASE. In: Fuster V, Harrington RA, Narula J, Eapen ZJ (Eds). Hurst’s The Heart, 14e. McGraw Hill; 2017.

 

 

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