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In the News: Type 1.5 Diabetes, Self-Driving, Glomerular Disease, Ewing Sarcoma
New perspectives on pediatric research problems are paving the way for breakthroughs at Children’s Hospital of Philadelphia Research Institute. In this edition of our biweekly news roundup, we share some of the unique ways our scientists are making waves by approaching basic and clinical research problems from a different lens. Discover how a newly identified genetic signature could change how clinicians diagnose an adult-onset form of diabetes, explore the human angle behind the exciting rise of self-driving cars, see how a computerized algorithm could change clinical trial recruitment for chronic kidney disease, and learn about developing innovative treatments to Ewing sarcoma.
Researchers Find Genetic Difference Helps Distinguish Diabetes Type
The discovery of a new genetic signature by CHOP researchers could help better distinguish latent autoimmune diabetes in adults (LADA) — an adult-onset form of diabetes that shares many characteristics with type 1 diabetes (T1D) — from childhood-onset type 1 diabetes (T1D). Whereas previously, LADA diagnosis might involve a complex and expensive antibody screening, the new genetic signature may mean clinicians can diagnose LADA using a simpler genotype array.
“This is our first insight into genetic differences between latent autoimmune diabetes in adults and T1D in children that may be diagnostically useful,” said study leader Struan F.A. Grant, PhD, co-director of the Center for Spatial and Functional Genomics at CHOP, in a press release. “We have found a genetic means of discriminating between the two conditions without expensive and cumbersome anti-autobody screening.”
LADA, also referred to as type 1.5 diabetes, shares characteristics with both T1D and type 2 diabetes (T2D). Because LADA often is misdiagnosed as T2D, patients do not always respond to the commonly inappropriate prescribed treatments. In fact, an earlier genome-wide association study led by CHOP researchers found that, from a genetic perspective, LADA actually has more in common with T1D than with T2D. The new findings, published in the journal Diabetes Care, take a deeper dive into LADA’s distinguishing differences, opening the door to more straightforward diagnostic tests and improved responses to appropriate treatments.
Read more in the press release.
New Study Highlights Human Factors in Self-Driving
A new blog post written by Helen Loeb, PhD, research scientist in the Center for Injury Research and Prevention (CIRP) sheds light on how age and gender may impact a person’s ability to respond to an emergency in a self-driving car. In a study published in the journal Traffic Injury Prevention, Dr. Loeb and her team used driving simulation to better understand people’s knowledge, anticipation, and reaction to self-driving vehicles. Among other findings, they discovered that women ages 35 to 50 performed better than any other, group and seniors had the highest crash rate (50 percent).
As Dr. Loeb writes, shedding light on these human factor elements is critical as auto manufacturers fine-tune the hardware and software of autonomous vehicles for commercial and personal use:
“When I recently presented on this research at the 2019 Autonomous Vehicles Symposium in Orlando, Florida and at the PennDOT Highly Automated Vehicle Summit, it was a welcome addition to the conferences, which often highlight sessions on sensors and algorithms, often forgetting the human factors element.As the need to educate drivers about the capabilities and limitations of their increasingly automated vehicles grows, our research will become even more vital.”
Read Dr. Loeb’s full post for CIRP’s Research in Action blog.
Identifying Glomerular Disease for Clinical Research With EHR-based Algorithm
Research published in the Journal of the American Society of Nephrology suggests that an algorithm powered by electronic health record (EHR) data could be a useful method to rapidly identify children with glomerular disease, a major cause of chronic kidney disease (CKD), for clinical research recruitment.
As reported in Cornerstone, gathering enough pediatric patients with CKD-related conditions for a clinical trial can be challenging since pediatric CKD is rare, and patients are often spread out across different hospitals. The computerized algorithm has the power to help researchers recruit patients for observational or prospective studies by primarily drawing on diagnostic and procedure codes. Led by Michelle Denburg, MD, MSCE, attending physician in the division of Nephrology, the study team developed and evaluated the algorithm by leveraging the population of over 6.5 million children from PEDSnet, a national network of eight pediatric health systems. The EHR-based algorithm identified the largest cohort of children with glomerular disease to date with 94 percent accuracy, 96 percent sensitivity, and 93 percent specificity.
Philadelphia Inquirer Features Novel CHOP Ewing Sarcoma Research
With news of Philadelphia Flyers’ left-winger Oskar Lindblom’s diagnosis of Ewing sarcoma, media outlets are shedding light on ongoing research to develop better treatments for the rare bone cancer. Characterized by chromosome changes that occur after birth, Ewing sarcoma often is treated with a combination of therapies such as chemotherapy, surgery, and radiation therapy.
In a recently published article, the Philadelphia Inquirer quotes our own Patrick Grohar, MD, PhD, physician-scientist in the Cancer Center and director of Translational Research in the Center for Childhood Cancer Research at CHOP. CHOP is on the cutting-edge of developing treatments for Ewing sarcoma: Currently, Dr. Grohar is working on human testing of two approved chemotherapies that lab research has suggested can inhibit a key mutation involved in the disease when combined.
“I feel like it’s an exciting time right now,” Dr. Grohar is quoted in the article. “I believe there will be a new targeted drug certainly in the next decade, and maybe in the next five years.”
Multicenter Study Shows Impact of Rare Recurrent Copy Number Variations
Rare but recurrent copy number variations (CNV) can influence a variety of common diseases, from autoimmune diseases to neuropsychological diseases, according to new findings from a large multicenter study led by CHOP experts. A CNV occurs when the number of copies of a particular gene varies from one individual to the next. Previously, researchers lacked a clear picture of the role of CNVs in disease development. The findings, published in Nature Communications, suggest that such genetic variations could play a greater role than formerly thought.
Comparing the data of more than 100,000 people of European ancestry using genome-wide SNP arrays or array comparative genomic hybridization platforms, the team found that the vast majority of CNV’s uncovered were recurrent (meaning they occurred in at least two individuals) but individually rare. Alongside confirming CNV regions associated with disease from previous studies, the researchers discovered several previously unreported regions that match genes that are already of clinical interest. These include deletions associated with autoimmune diseases, autoimmunity, and more.
“This analysis provides us with a dense map of the impact of rare recurrent copy number variations, which represent an important source of genetic variation in our genome, often predisposing us to, and sometimes causing, complex diseases,” said senior author Hakon Hakonarson, MD, PhD, director of the Center for Applied Genomics at CHOP, in a press release. “Our study showed that previous methods are likely not capturing the accurate incidence or prevalence of rare copy number variation regions that directly impact human health.”
Learn more in the press release.
Catch up on our headlines from our Jan. 3 In the News:
- Quality Improvement Project Reduces Use of Bronchodilators in Bronchiolitis
- Innovative Population Health Strategies Provide Customized Care
- PCORI Approves Outpatient Antibiotic Stewardship Project
- Updated Guidelines Emphasize Early Identification of Autism
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