NMR-Based Diabetes Risk Index Helps to Identify Normal-Weight Individuals at High Risk of Progressing to Type 2 Diabetes

A nuclear magnetic resonance (NMR)-based diabetes risk index (DRI) is being used to identify normal-weight individuals at high risk of progressing to type 2 diabetes, and may enable a more comprehensive risk assessment and intervention in at-risk patients.

LipoScience, Inc. (Raleigh NC, USA), a diagnostic company that develops personalized NMR diagnostics to further the quality of patient care in cardiovascular, metabolic, and other diseases, presented data demonstrating the utility of the company’s technology on June 14, 2014, at the 74th Scientific Sessions of the American Diabetes Association (ADA), held in San Francisco (CA, USA), and suggests that the DRI may enable more timely and focused risk assessment and intervention in at-risk individuals regardless of body weight, potentially preventing or slowing their progression to type 2 diabetes.

“Many clinicians are challenged about how to effectively manage patients with ‘intermediate’ blood glucose levels ranging from 90 to 110 mg/dL, as within this range there is often ambiguity as to whether a patient will progress to type 2 diabetes,” commented Margery Connelly, PhD, vice president, translational research of LipoScience. “The ambiguity is particularly pronounced in normal-weight individuals, who do not typically present with overtly visible risk factors. With our simple-to-use diabetes risk index, clinicians now have a tool to help them identify high-risk patients, providing guidance for implementing targeted risk-reduction strategies.”

The DRI is a clinical lab test that uses LipoScience’s proprietary NMR-derived markers of insulin resistance, inflammation, and potentially impaired B-cell function to determine a patient's risk of progressing to type 2 diabetes. DRI provides researchers and healthcare providers with the means to assess a patient’s risk of progressing to diabetes at any given level of fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c), or body mass index (BMI).

The investigators used NMR data gathered at baseline from participants in the Multi-Ethnic Study of Atherosclerosis (MESA), to develop the DRI assay, and then used data from and the Insulin Resistance Atherosclerosis Study (IRAS) to verify its ability to stratify a patient’s risk of progressing to type 2 diabetes. To determine whether the DRI score was capable of identifying normal-weight individuals with a high likelihood of developing diabetes, the investigators compared the percentage of patients progressing to type 2 diabetes across quartiles of the DRI score in three BMI categories—normal weight (BMI < 25), overweight (BMI 25–30), and obese (BMI ≥ 30). Regardless of the BMI category, as the DRI score increased there was an increased likelihood of becoming diabetic, even for patients whose BMI was within the normal range. Furthermore, DRI added predictive value independently of BMI in both the MESA and IRAS populations.

"Even in the absence of being overweight, DRI can help healthcare providers make a more timely prediction of whether a patient is on the path toward developing diabetes, before blood glucose reaches so-called ‘pre-diabetes’ levels,” noted William C. Cromwell, MD, chief medical officer of LipoScience. “By providing more precise risk-assessment information, DRI can facilitate initiation of individualized patient management strategies, while motivating high-risk patients to take steps to lower their risk.”

LipoScience is focused on the new field of personalized diagnostics based on nuclear magnetic resonance (NMR) technology. The NMR LipoProfile test, the company’s first proprietary test, is the only US Food and Drug Administration (FDA)-cleared blood test that directly quantifies low-density lipoprotein (LDL) particles and provides physicians and their patients with actionable information to personalize management of heart disease.

The Vantera clinical analyzer is the first FDA-cleared platform that utilizes NMR technology. Its ease of use and quick turnaround time helps maximize efficiency and throughput in the clinical laboratory.

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