Blood-Based Multiomics-Guided Detection of a Precancerous Pancreatic Tumor.

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

Urinary Vitamin D Binding Protein: A Marker of Kidney Tubular Dysfunction in Patients at Risk for Type 2 Diabetes.

Context: Recent studies have reported elevated urinary vitamin D binding protein (uVDBP) concentrations in patients with diabetic kidney disease, although the utility of uVDBP to predict deterioration of kidney function over time has not been examined. Objective: Our objective was to assess the association of uVDBP with longitudinal changes in kidney function. Methods: Adults at-risk for type 2 diabetes from the Prospective Metabolism and Islet Cell Evaluation (PROMISE) study had 3 assessments over 6 years (n = 727). Urinary albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) were used as measures of kidney function. Measurements of uVDBP were performed with enzyme-linked immunosorbent assay and normalized to urine creatinine (uVDBP:cr). Generalized estimating equations (GEEs) evaluated longitudinal associations of uVDBP and uVDBP:cr with measures of kidney function, adjusting for covariates. Results: Renal uVDBP loss increased with ACR severity at baseline. Individuals with normoalbuminuria, microalbuminuria, and macroalbuminuria had median log uVDBP:cr concentrations of 1.62 µg/mmol, 2.63 µg/mmol, and 2.48 µg/mmol, respectively, and ACR positively correlated with uVDBP concentrations (r = 0.37; P < .001). There was no significant association between uVDBP and eGFR at baseline. Adjusted longitudinal GEE models indicated that each SD increase both in baseline and longitudinal uVDBP:cr was significantly associated with higher ACR over 6 years (ß = 30.67 and ß = 32.91, respectively). Conversely, neither baseline nor longitudinal uVDBP:cr measures showed a significant association with changes in eGFR over time. These results suggest that loss of uVDBP:cr over time may be a useful marker for predicting renal tubular damage in individuals at risk for diabetes.

Value-based healthcare delivery through metabolomics-based personalized health platform.

Type 2 diabetes is routinely identified in clinical practice by tests that rely on a hyperglycemic index. However, people at risk for developing type 2 diabetes may not present with hyperglycemia. We identified several underlying risks for type 2 diabetes, insulin resistance, and associated co-morbidities, using a liquid chromatography mass spectrometry-based analysis of blood metabolites, in participants with normoglycemia and no clinical symptoms. Personalized lifestyle recommendations, including diet, exercise, and nutritional supplement recommendations, were conveyed to these participants by a web-based platform, and after 100 days of following their recommendations, these participants reported reductions in the health risks associated with type 2 diabetes and associated diseases. Our comprehensive metabolite-based assay can be used for type 2 diabetes risk stratification, and our personalized lifestyle recommendation system could be deployed as a preventative treatment option to improve health outcomes, reduce the incidence of chronic disease, and live healthier lives in an evidence-based way.