Molins, Claudia R.

Claudia R. Molins, PhD
Microbiologist
Division of Vector-Borne Diseases
Bacterial Diseases Branch
Centers for Disease Control and Prevention
Fort Collins, CO

Claudia R. Molins, PhD
Microbiologist
Division of Vector-Borne Diseases
Bacterial Diseases Branch
Centers for Disease Control and Prevention
Fort Collins, CO

Use of Metabolic Profiles as Diagnostic and Prognostic Biomarkers of Lyme Disease

Dr. Molins is a Microbiologist and Principle Investiagtor in the Microbiology and Pathogenesis Team within the Bacterial Diseases Branch of the Division of Vector-Borne Diseases (DVBD) at the Centers for Disease Control and Prevention (CDC). She received a Bachlors of Science degree from Iowa State University in 2002, and a Ph.D from Colorado State University in 2007. She was awarded an American Society of Microbiology (ASM)-CDC Post-Doctoral fellowship that was performed in the Diagnostic and Reference Team of the Bacterial Diseases Branch of DVBD, CDC. Prior to her current position, Dr. Molins also served as a Principle Investigator in the Diagnostic and Reference Team of DVBD, CDC from 2011 to 2015. Dr. Molins has studied multiple bacterial pathogens including Borrelia burgdorferi, Francisella tularensis and Yersinia pestis. These efforts have largely been directed at the development and testing of diagnostic tools, but have also included the development of animal models of tularemia and the elucidation of bacterial products and genomic regions associated with strain diversity and pathogenicity. Dr. Molins’s current research is primarily directed at the novel application of metabolomics and metabolic biosignatures as a next generation approach for diagnosing Lyme disease and other tick-borne diseases. This work also involves developing biosignatures that can be applied to the prognosis of treatment efficacy or disease outcome.

Conference Lecture Summary

Laboratory diagnosis of Lyme disease is currently performed using a two-tiered approach that is limited by low sensitivity in early stages of infection, its inability to differentiate active from previous infection and by difficulties in performing and interpreting immunoblots performed in the second tier. Similarly, there are no objective prognostic or diagnostic methods in place to confidently identify patients that develop Post-Treatment
Lyme Disease Symptoms/Syndrome (PTLDS), a condition defined by the persistence of subjective symptoms for at least 6 months following antibiotic treatment and resolution of an objective manifestation of Lyme disease, such as erythema migrans (EM). Our laboratory has been working with collaborators to apply a metabolomics approach for the development of novel tools for diagnosis and prognosis of early Lyme disease, including PTLDS. To date we have developed small molecule biosignatures that differentiate with high accuracy between early Lyme disease patients, healthy individuals and patients with diseases that have look-alike symptoms or that are cross-reactive with existing serology-based tests for Lyme disease, including Southern Tick-Associated Rash Illness (STARI) and infectious mononucleosis. Furthermore, metabolic biomarkers that differ between PTLDS and non-PTLDS patients have been identified. These efforts not only hold potential for new Lyme diagnostic and
prognostic tools, but will also provide new information about the biology of Lyme disease.