In This Issue of Diabetes

A mouse model that combines type 1 diabetes and chronic activation of the renin-angiotensin system develops kidney disease characteristic of human diabetic nephropathy, according to Gurley et al. (p. 2096). Characteristics reportedly include high-grade albuminuria and nodular glomerulosclerosis, and depending on genetic background, the model has expression patterns associated with immune activation and inflammation. The findings come from a series of experiments in mice with different genetic backgrounds comparing the effects of diabetes and activation of the renin-angiotensin system on albuminuria and kidney damage. Further genomic analyses were included to understand the molecular mechanisms involved. The authors found that wild-type mice had barely detectable levels of albuminuria, whereas mice with an Akita mutation (i.e., with diabetes) had a modest increase in albuminuria. Likewise, the presence of RenTg (i.e., activation of the renin-angiotensin system) resulted in only modest albuminuria. However, mice on a 129 background with Akita and RenTg saw a dramatic increase in albuminuria in comparison to wild-type controls on the same background. Mice on a C57BL/6 background with Akita and RenTg only had a modest increase in albuminuria. Further histopathological analyses revealed that the 129-Akita-RenTg mice developed many of the pathological features of human diabetic nephropathy, whereas other groups did not. Gene expression profiles and further genetic work suggested that pathways involved in immune and inflammatory responses were likely contributing to the development of nephropathy in the model. While acknowledging that genetic determinants of diabetic nephrology likely differ between mice and humans, the authors believe that the molecular pathways that appear activated are similar and shared. On that basis, they suggest the pathways might be attractive biomarkers and targets for therapy. Author Thomas M. Coffman told Diabetes: “Our model highlights the powerful impact of genetic background on susceptibility to diabetic nephropathy and suggests that genetic pathways controlling inflammation and immunity play a key role in determining the severity of kidney disease with diabetes.”

Gurley et al. Inflammation and immunity pathways regulate genetic susceptibility to diabetic nephropathy. Diabetes 2018;67:2096–2106

Energy expenditure may be regulated via coordination between multiple cell organelles including lipid droplets, peroxisomes, and mitochondria, according to Zhou et al. (p. 1935). Moreover, it seems the effects are mediated via CIDE proteins (specifically Cidea and Cidec) and the adipocyte triglyceride lipase (ATGL)-peroxisome proliferator–activated receptor α (PPARα) pathway. The experiments center on a series of obese mouse models (ob/ob) that were deficient in either Cidea, Cidec, or both or were not deficient at all. The authors found that mice with the Cidea deficiency had a very similar phenotype to ob/ob mice in terms of growth, weight, and various serum parameters. The mice with the Cidec deficiency had increased liver and brown adipose tissue weights and higher serum triacylglycerol, hyaluronidase, and laminin. In comparison, when the two deficiencies were combined into one model, mice had improved metabolic status including lower body weight, improved oxygen and energy consumption, and lower levels of serum fatty acids and indicators of inflammation. In addition, the double-deficient mice had decreased triacylglycerol storage and much smaller lipid droplets in adipose tissues. Insulin sensitivity was also increased in the double-deficient mice. Further gene expression profiling to observe transcriptional changes in brown/white adipose tissue revealed significant activity in pathways relating to mitochondria and peroxisomes. Additional analysis then showed there was an increase in lipase levels and a lipolysis regulator in the double-deficient mice, which indicated to the authors that the effects were mediated by the ATGL-PPARα pathway. Author Li Xu commented: “It is difficult to observe organelles except lipid droplets in white adipocytes. The adipocytes of Cidea and Cidec double deficiency gave us a good cell model to study and observe the organelle interactions among lipid droplets, peroxisomes, and mitochondria, which coupled with activated lipolysis and oxidation of fatty acids. We proposed that simultaneously activated metabolism in brown and white adipose tissues of Cidea and Cidec double deficiency contributed to dramatically increased energy consumption, providing an effective way to alleviate obesity and related metabolic disorders.”

Zhou et al. Coordination among lipid droplets, peroxisomes, and mitochondria regulates energy expenditure through the CIDE-ATGL-PPARα pathway in adipocytes. Diabetes 2018;67:1935–1948

The development of a tracer method for detecting β-cell mass continues with ¹¹¹In-diethylenetriaminepentaacetic acid–exendin-3 (¹¹¹In-exendin) being tested in a BioBreeding diabetes-prone (BBDP) rat model. According to Brom et al. (p. 2012), the radio-labeled compound does accumulate specifically in islets and there is a strong linear correlation with β-cell mass. The authors suggest that ¹¹¹In-exendin is a promising tracer to determine β-cell mass during the development of type 1 diabetes. Previously, a linear relationship between the tracer and β-cell mass has been demonstrated but only in a model of type 1 diabetes that does not show typical patterns of inflammation and insulitis found in the disease. The use of the BBDP model should address that concern, according to the authors. The conclusions come from a series of experiments in which the rats received the tracer followed by single-photon emission computed tomography (SPECT). After acquisition, the pancreas was then dissected, fixed, and embedded in paraffin for further examination with autoradiography and histological approaches. Blood glucose and insulitis levels were also determined. They found that the BBDP rats were normoglycemic until 8 weeks of age and were hyperglycemic thereafter. Animals with high β-cell mass fraction had the most pancreatic accumulation of the tracer. Declining β-cell mass correlated with declining tracer accumulation in the pancreas, resulting in a Pearson correlation of r = 0.89 (P < 0.0001). Correcting for blood glucose and insulitis levels did not alter the result. Histological analysis and SPECT also revealed tracer accumulation in islets in rats with high β-cell mass that declined to zero in rats with no β-cell mass. The authors suggest that ¹¹¹In-exendin is a reliable technology for noninvasive determination of β-cell mass. Given that the method can overcome fluctuations in glucose levels and does not appear to be affected by insulitis, they also suggest it has the potential to be used clinically.

Brom et al. Validation of ¹¹¹In-exendin SPECT for the determination of the β-cell mass in BioBreeding diabetes-prone rats. Diabetes 2018;67:2012–2018

Precision medicine is almost certain to come into play for type 2 diabetes in the next few years. The question is how. In a Perspective, Fitipaldi et al. (p. 1911) chart one possible course, giving an overview of the evidence and barriers to the development of precision medicine for type 2 diabetes. Starting from the perspective that diabetes, and particularly type 2 diabetes, remains a major cause of morbidity and mortality (and that current treatments are insufficient), the authors suggest precision medicine is likely to provide many opportunities for type 2 diabetes prevention and treatment but that there is still much to resolve before it becomes a reality. They describe numerous precision medicine initiatives that are relevant to type 2 diabetes, highlighting the large investments being made around the world to make precision medicine a reality. They also discuss progress being made in terms of clinical translation, with a major theme emerging of an imbalance in investments being made in pharmacological approaches and lifestyle intervention approaches, the latter having clear benefits but receiving much less attention currently. Author Paul W. Franks said: “Precision medicine has in recent years taken center stage in diabetes research and practice. While precision medicine is driven by new technologies, the concept builds on existing medical practice, whereby data is used to optimize the clinical approach. The key difference today is that the information available to the clinician is becoming progressively more diverse and complex. This presents enormous opportunities in the fight against diabetes but also presents many challenges as these new data must be intelligently interpreted by both clinicians and patients and special considerations must be made about legal, social, and ethical implications related to their use. Determining that costs, risks, and benefits of precision diabetes medicine favorably outweigh traditional practice is equally important before precision diabetes medicine can become common practice.”

Fitipaldi et al. A global overview of precision medicine in type 2 diabetes. Diabetes 2018;67:1911–1922