Mass Spectrometry in Precision Medicine --A Penn Experience in Metabolomics and TDM
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1 Mass Spectrometry in Precision Medicine --A Penn Experience in Metabolomics and TDM Ping Wang, PhD, DABCC, FACB Chief of Clinical Chemistry Director of Core Laboratory Hospital of University of Pennsylvania Associate Professor, Pathology and Laboratory Medicine University of Pennsylvania October 2018
2 Learning Objectives After this presentation, you should be able to: Describe the goals of precision medicine Describe the ways by which mass spectrometry can contribute to precision medicine Describe a couple of examples ongoing at Penn in which mass spectrometry is used in precision medicine initiatives 2
3 Outline Multi-faceted Face of Precision Medicine Ways mass spectrometry can contribute to Precision Medicine Projects ongoing at Penn Metabolomics-based heart failure staging and intervention Pain management testing and individualized interpretation Therapeutic drug monitoring for biologicals 3
4 Precision Medicine Diseases are heterogeneous Patients are different Individualized Health Care Healthcare Tailored to you 4
5 Clinical data Genomi c info Imaging data Biomarker s Precision Medicine TDM and PGx POC 5
6 Clinical data Genomi c info Imaging data Proteins Metabolites Hormones Biomarker s Precision Medicine TDM and PGx Disease stratification: --diagnosis --staging --prognosis --treatment/therapy selection POC 6
7 Penn Center for Precision Medicine 7
8 Use of Acylcarnitine Signature for Heart Failure Prognostication and Targeted Intervention 8
9 Background The human heart is a metabolic omnivore It is a massive energy consumer 100,000 cardiac cycles, ~7 tons of blood perfusion daily Cycle ~6kg ATP daily or equivalent of 12x its weight Metabolic adaptation in failing myocardium Switch to fetal gene program and glucose utilization Decreased oxidative phosphorylation to generate ATP Decreased fatty acid oxidation, resulting in acylcarnitine accumulation Increased branched chain amino acids Can we use these metabolites as biomarkers to stage, prognose heart failure, and decide the best timing and type of interventions (LVAD, transplant, new metabolic therapies)? 9
10 Clinical Impact Estimated 5.7 million HF patients in the US 500,000 in advanced stage refractory to standard evidence-based treatment Paradigm-shift towards metabolic staging of HF Stratification for Heart transplantation, LVAD placement and prognosis Pharmacologic Therapy impacting Metabolic Adaptation GLP-1 as proof of principle Implications for SGLT-2 inhibitors which are showing heart failure risk reduction in diabetes Improve clinical outcomes, reduce risks, decrease costs Potentially disruptive algorithm: emergence of precision medicines to treat metabolic diseases, including heart failure 10
11 Penn Heart Failure Study Prospective mutli-center large, real-world sample and clinical databases of chronic heart failure patients presented to tertiary heart failure clinics, with long-term (~10 yrs) follow-up 11
12 N=846 12
13 Distribution of acylcarnitines 13
14 Acylcarnitines are associated with time to outcome events Association with time to event Acylcarnitines Hazard ratio (95% CI) p-value Propionylcarnitine (C3) 1.89( ) Isovalerylcarnitine (C5) 0.53( ) OH-Butyrylcarnitine (C4-1.68( ) 0.01 OH) Malonylcarnitine (C3-DC) 0.54( ) 0.04 Methylmalonyl (C4-DC) 1.80( ) 0.02 Dodecadienoyl (C12:2) 0.58( )
15 Acylcarnitines are associated with clinical characteristics Acylcarnitines Hazard ratio p-value NYHA Diabetes Ischemic Ejection Fraction (95%CI) cause Acetylcarnitine (C2) 1.7( ) < < OH-Butyrylcarnitine (C4-1.8( ) < < < < OH) Malonylcarnitine (C3-DC) 1.3( ) 0.03 < < < Cis-4-Decenoyl (C10:1) 1.4( ) 0.01 < Decanoylcarnitine (C10) 1.2( ) Dodecadienoyl (C12:2) 1.3( ) 0.01 < < Dodecenoylcarnitine (C12:1) 1.4( ) < Dodecanoylcarnitine (C12) 1.5( ) < < Tetradecadienoylcarnitine 1.6( ) < < (C14:2) C18:1-Dicarboxylic 1.5( )
16 Using acylcarnitine to predict outcome events 16
17 Significance of the results Demonstrated the prognostic value of acylcarnitines in a large, clinically well characterized real-world cohort with long-term followup, using a real-world clinically-validated assay, instead of a research assay Generated machine-learning based algorithm for individual patient risk prediction 17
18 Next steps Validate the prognostic value of acylcarnitines in a longitudinal study of heart failure patients with LVAD, and the NHLBI Heart Failure Clinical Research Network GLP-1 trial. Cohort 1: longitudinal serum samples (n=90) from HF patients pre (baseline) and post-lvad implantation (1 week, 1 month, 6 months) from HUP VAD BioBank Cohort 2: Liraglutide (GLP-1 agonist) arm (n=154) of FIGHT trial with peripheral blood sample and clinical outcomes available Improvement in clinical symptoms and myocardial function decreased acylcarnitines Worse outcomes in the Liraglutide arm increased acylcarnitines Most reliant on ketones (increased acylcarnitines) would have this metabolic adaptation interrupted by GLP-1 agonist (enhances insulin sensitivity decreasing lipolysis and ketogenesis) Clinical implication: therapy selection and monitoring 18
19 Mass Spectrometry in Pain Management and Therapeutic Biologicals Monitoring 19
20 Clinical data Genomic info Imaging data Biomarkers Precision Medicine TDM and PGx PK/PD Concentration Genotyping POC Drug efficacy/toxicity --Increased off-label use of FDA-approved drugs and experimental drugs --Increased use of biologicals 20
21 Toxicology Laboratory at UPENN: Major developments during the past 8 years, Pain Management testing: Expanded to serve more than 20 CCA practices, and UPHS clinical practices Introduced an HPLC/tandem mass spectrometry-based panel of 11 opiates/opioids tests in Close working relationship with Pain medicine clinical team 2018: Major expansion just completed that includes 44 drugs & metabolites, in compliance with LDT requirements, that complies with and consistent with 2016 CDC guidelines for Pain medicine management, and the AACC Academy Guidelines and includes a new report format Slide from Dr. Leslie Shaw 21
22 New expanded Pain Management Testing Program at UPENN Includes 9 Drugs of abuse 16 Benzodiazepines/metabolites 19 Opiates & opioids/metabolites Report includes concentrations, cutoffs,standard & individualized comments DOA OPIOIDS BENZODIAZEPINES Benzoylecognine Buprenorphine Morphine Alprazolam Estazolam Amphetamine nor-buprenorphine Naloxone α-hydroxyalprazolam Hydroxyethylflurazepam methamphetamine Codeine Naltrexone 7-amino-clonazepam Hydroxytriazolam MDMA Dihydrocodeine Oxycodone Chlordizepoxide Lorazepam MDA Fentanyl Oxymorphone Clobazam 1-hydroxy-midazolam 6-MAM nor-fentanyl Tapentadol Diazepam Midazolam Phentermine Hydrocodone N-desmethyltapentadol nor-diazepam Oxazepam PCP Hydromorphone cis-tramadol Desalylflurazepam Temazepam THC Methadone N-desmethyltramadol EDDP Slide from Dr. Leslie Shaw 22
23 TDM/PGx example: Therapeutic Biologicals Monitoring Therapeutic antibodies widely used in targeted therapy, autoimmune diseases, check-point inhibitor immunotherapy Often require companion diagnostic assays to quantify the target of the drug Target + response Antibodies against these drugs may develop in some patients overtime Antibodies interfere with therapeutic efficacy as well as measurement Need objective ways to quantify both target and drug Achievable using hybrid approach of LBA/LC-MS Quantify in serum or tissue (fresh frozen or FFPE) 23
24 Example: Infliximab sendout 24
25 Immunotherapy 25
26 Mass spectrometry co-development program with CHOP Pool instrument and technical resources at both institutions Strategically prioritize resources for MS test development, according to existing technical strengths and institutional clinical program priorities 26
27 Summary Precision Medicine encompasses more than genomic testing Mass spectrometry has a lot of potential to contribute to precision medicine, eg. by quantifying biomarkers (proteomics, metabolomics) or TDM (eg. biologicals) Lab can contribute to precision medicine by leveraging clinical program strengths within the same institution 27
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