Emerging Life Sciences Series: Q & A with the Editor: Genetics and Metabolism

Abstract

As part of our series on emerging life sciences, the editor speaks with Drs Mario Luca Morieri MD and Hongwen Zhou MD, principal investigators at University of Padova and Nanjing Medical University, respectively, about their research pathway into genetics and metabolic disease and their passion for advancing research in this area. Drs Morieri (MLM) and Zhou (HZ) reflect on personal and professional experiences motivating their research and the road ahead.

1. Can you share a life event or experience that led you to research the interplay of genetics and environmental factors driving metabolic disease?

MLM: As a young physician and scientist I was interested in a holistic approach to patient care and chose to specialize in internal medicine. When treating patients with diabetes, obesity, and dyslipidemia, I realized these conditions had multi-organ influences that differed from patient to patient. As an example, a young patient with a good life-style style developed diabetes or cardiovascular disease (CVD) in their 40s, while an older patient with longer exposure to multiple cardiometabolic risk factors did not develop CVD or diabetes. While on average there is no doubt that the overall accumulation of these and other cardio-metabolic risk factors (e.g., sedentary lifestyle, smoking, unhealthy diet, hypertension) are directly correlated with risk of cardiometabolic disease, there is clearly heterogeneity in outcomes. Those were the years of the first -omics studies (genome-wide studies, microbiomes studies) and renewed enthusiasm for precision medicine approaches. Driven by my interest in this topic, I pursued a fellowship at the Joslin Diabetes Center (Boston, USA) to study the interplay between genetics and environmental factors driving metabolic disease.

HZ: Among my patients with obesity there was one case I would like to share: I diagnosed and treated a 35-year-old female patient who complained of hyperphagia, early-onset progressive and refractory obesity with normal birth weight. Her BMI was 57.8 kg/m², with fat accumulation throughout the body and distributed in a pantaloon way. Lifestyle modification, medication, and surgical intervention, such as gastric bypass surgery, were all unhelpful. With further investigation, family history revealed a consanguineous marriage between her parents (first-degree cousins) with normal weight and blood glucose level. Whole Genome Sequencing indicated the presence of a loss of function mutation in the gene of the leptin receptor, leading to the symptoms the patient was experiencing. This case and others led me to think about the interplay of genetics and environmental factors driving metabolic disease.

2. What scientific insights have informed your view that obesity and diabetes are products of genetics and environment?

MLM: In our studies, evaluating the interplay between genetics and environment we were able to demonstrate that genetic background can be successfully used (and nowadays at relatively low cost) to distinguish patients with type 2 diabetes that have very similar general characteristics, but differ in cardiovascular risk.^[1] Similarly, we found that some genetic variants might help distinguish subjects with different cardiovascular response to preventative treatment.^[2-4] Several other groups are working in this emerging field of cardiometabolic disease with promising results.^{[5, 6]} I expect that these approaches will be implemented in clinical practice over the next ten years.

HZ: In 1994, Professor Jeffery Friedman at Rockefeller University cloned the mouse and human obese (ob) gene which produces leptin, a master adipokine that regulates appetite and body weight. Patients with mutations in the leptin gene are often extremely obese. We now know that not only the leptin and its receptor, but also genes in the melanocortin signaling pathway are essential players in modulating food-seeking behavior, appetite regulation, and systemic energy metabolism. Genetic studies have advanced our understanding of the nature of obesity to include monogenic obesity and polygenic obesity. Similarly to diabetes, genetic factors contribute to these diseases. For example, mutations in the insulin coding gene (ins) are one type of neonatal diabetes mellitus. To date, approximately twenty genes have been associated with monogenic diabetes. Genetic variation in metabolic genes influences both obesity and diabetes, however, the dramatic increase in prevalence of obesity and diabetes in recent decades cannot be fully explained by genetic variation. The term an “obesogenic environment”^[7] was proposed in 1999, which describes the interaction between environmental and innate biological factors and reveals the nature of many metabolic disorders. These scientific insights informed my view that both genetic and environmental factors contribute to obesity and diabetes.

3. Where do you see future progress in understanding pathophysiology in complex metabolic diseases?

LM: Thanks to the growing availability of large biobank databases leveraging “real-world”, routinely collected data combined with genome-wide or whole genome sequencing, I think that we will continue to see progress in this field. Increasing the sample size of these databases will allow us to evaluate “gene by gene” and “gene by gene by environment” interactions that will help us move toward the development of personalized algorithms.

HZ: Metabolic syndromes, including diabetes, hypertension and dyslipidemia, and their associated comorbidities, are global health epidemics that require multimodal approaches. Translational genomic approaches will likely be critical tools going forward. Professor Peng Li and colleagues have suggested that given the complexity of metabolism and metabolic diseases, it would be beneficial to focus on multi-center efforts for further collaboration locally and globally, including scientific clinical research and animal centers that can generate genetically modified animal models to better mimic metabolic health and disease in humans. These centers are also expected to perform standardized characterization of metabolic phenotypes and generate databases accessible to the wider scientific community.^[8]

4. Where do you see advances in risk prediction, given the different global geographic distribution of metabolic disease and likely different demographic exposures?

MLM: The consideration of populations with different genetic backgrounds is essential for target discovery.^{[9, 10]} It will be crucial to develop population-specific screening programs since the prevalence of diabetes is expected to rise in regions outside of Europe and North America where most of the studies are currently being conducted.^[11] I also believe that we will need to have, and will gain from, deeper and more detailed assessments of the environment, including socio-economic factors. This will help to better define “gene by environment” interactions that ultimately influence health outcomes.

HZ: With the aging of the global human population, the rate of developing metabolic diseases and associated comorbidities is increasing, potentially leading to a substantial clinical burden and a public health concern.^[11] There is an urgent need to implement effective risk prediction of metabolic diseases for early detection and intervention, such as the development of analytical tools for high-throughput sequencing techniques and metabolomics (e.g., UK Biobank^[12]). Another example, findings from the China 4C study revealed that systematic amino acids and microbiota-related metabolites play a potential role in prediction of T2DM.^[13] Genome-wide association studies (GWAS) coupled with artificial intelligence (e.g., machine learning) offer a promise of polygenic risk score development in early identification of risk for metabolic diseases. Moving forward, more effort should be placed in developing predictive tools for screening metabolic disease risk.

5. As guest editors, what are your goals for the upcoming thematic issue, “Genetics and Metabolism”, and how will you measure success?

MLM: The goal of the issue is to increase awareness of the interplay of genetics and environment in the context of different countries and continents. Success will be if Advanced Biology will increase the number of high-quality studies being published on genetic, epigenetic and other -omic approaches in the field of cardiometabolic risk and precision medicine.

HZ: It has been my honor to serve as a guest editor for this thematic issue, “Genetics and Metabolism”. The first goal for me is to make the readership Advanced Biology more familiar with the field of genetics and metabolism, and my second goal is to promote discussions and collaborations across different academic fields and build international support of investigations into genetic and metabolic disease research. Hopefully this will bring improvements in treatments and public awareness in this field.