A new article was recently published that I participated in during my time at NIH. The study was led by Tetsushi Yamashita and focuses on changes in blood pressure and heart rate during sepsis. Unlike previous articles that focused on the pathways involved in the progression of sepsis this study examined some of the treatment options that are typically used in patients.
Although this study built on our knowledge of the complex response to sepsis it also developed an existing mouse model of sepsis closer to what humans might experience during routine care. The more accurately our models can simulate human disease the more likely we are to successfully translate therapies from mice into humans.
Mice are widely used as models of disease including kidney disease and sepsis despite differences between these mouse models and humans. There are a variety of reasons for these differences with medical care being one we can reduce.
When sepsis is diagnosed common medical treatments include giving fluids, antibiotics and vasopressors such as norepinephrine (also called noradrenaline in the UK) to treat low blood pressure. Each of these treatments alter disease progression in humans but are relatively new developments in mouse models. Our lab had a long history of using fluids and antibiotics but vasopressors were not used.
The reason for this is simple: their use is technically very challenging. While fluids and antibiotics can be administered intermittently and via common injection routes vasopressors would need to be administered:
- directly into a vein
- and with careful monitoring
The experimental procedures necessary for this model were first brought together by Brianna Halasa and then finalised when Tetsushi joined the lab. Each mouse undergoes approximately one hour of surgery in which the jugular vein is catheterised to enable the infusion of a vasopressor and then the carotid artery is catheterised to implant a pressure transducer to monitor blood pressure. Although the exact procedures are slightly different these videos demonstrate the jugular vein and carotid artery catheterisations. Only when the mice have recovered does the more usual sepsis model surgeries begin.
I would like to congratulate Tetsushi on publishing this study. If you are interested in learning more the complete article is now freely available in PLoS One.
Last month the final study from my time at NIH was published. This study explored a promising, and relatively new, biomarker for acute kidney injury during critical illness. Although the biomarker had been previously tested in humans we were able to develop a potential refinement in a preclinical model.
During critical illness, such as sepsis, organ failure is a major complication increasing the risk of death. For the kidneys, treatment is limited to more focused management. This means avoiding further harm and keeping the patient alive long enough for kidney function to return.
The sooner kidney injury is detected the better the likely outcome but this can be surprisingly difficult. Some significantly improved options have been developed but further, even better, options are still desired. A new approach is giving the kidney something to do and measuring how well it performs. This idea is similar to the treadmill stress test commonly used to detect cardiovascular disease such as angina.
The test that was developed gave a dose of a drug called furosemide that is actively excreted by the kidneys and stimulates urine production. If the kidneys are healthy, the furosemide will be excreted and the amount of urine produced will increase. In a human clinical study this approach performed very well and there have been several subsequent studies in different settings.
Urine volume is altered by a variety of factors and we decided to investigate whether further improvements in performance would be possible by measuring furosemide excretion directly. When used in ideal conditions results were comparable. However, when we gave a drug called vasopressin that is commonly used to manage blood pressure during critical illness measuring urine volume gave erroneous results while furosemide excretion remained reliable.
The study is published in Critical Care Explorations and is freely available.
Many diseases are very complex, involving many biological pathways. It is very difficult to find a single drug with actions on enough pathways to slow or reverse many diseases. As an alternative there is excitement around using cells to treat disease. Cells can sense their environment and change their response to match.
Mesenchymal stem cells (MSCs) have performed well in many types of disease. I currently work in the Renal Diagnostics and Therapeutics Unit at NIDDK. Before I joined the group they found MSCs were beneficial in sepsis. Treatment had to be soon after injury limiting the clinical usefulness. One potential reason for this was most MSCs got stuck in the lungs. If more cells got to the kidneys they might work better. At the time it was not known how to guide more cells to the kidneys.
Recently, we have worked with Scott Burks and Joe Frank from the Clinical Center at NIH. They are able to use pulsed focused ultrasound to alter tissues to recruit more MSCs. We tested pulsed focused ultrasound in a cisplatin model. Cisplatin is a treatment for some types of cancer but often causes kidney injury. Pulsed focused ultrasound guided MSC treatment reduced damage from cisplatin.
Acute kidney injury (AKI) is a common complication in hospitalized patients. Patients with AKI are more likely to die or have a worse quality of life after leaving the hospital. Early treatment is our best option for preventing these bad outcomes. To start treatment we first need to detect AKI.
Several biomarkers go up when a patient has AKI. Doctors watch the biomarker levels and start treatment when they rise. There is still uncertainty about which biomarker is best.
I am co-author on a recently published article exploring this issue. We compared creatinine and cystatin C in the serum. Cystatin C predicted kidney function better than creatinine. There was no difference in predicting death.