Protein biomarkers to predict pain outcomes after total pancreatectomy with islet autotransplant

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ABSTRACT Chronic pancreatitis (CP) is an often painful and disabling condition with few treatment options. For those with pain and impaired quality-of-life (QoL) who have failed medical and endoscopic therapies, complete removal of the pancreas may be considered with a procedure called total pancreatectomy with islet autotransplant (TPIAT). For many patients, TPIAT can be life-changing, with meaningful pain reduction. However, up to 20% have significant persistent pain after TPIAT. We lack objective measures to predict who will respond to TPIAT. In those who do respond, it is presumed that the pain is resolved simply because the pancreatectomy has removed the visceral source of pain, while non-responders have more complex pain syndromes involving changes in the central nervous system. Complementary work by our group in CP (without TPIAT) suggests that plasma or urinary biomarkers may distinguish pain phenotypes. The current proposal will leverage the largest TPIAT database and biorepository from a multicenter study of patients undergoing TPIAT (POST study) to develop biomarkers that predict response to TPIAT. Of note: Dr. M. Bellin, the PI of the POST study, is also PI on this application. In the NIDDK-funded POST study, over 400 enrolled participants underwent TPIAT, with detailed phenotyping for pain and QoL before and 1 year after TPIAT. In addition, biospecimens including plasma and urine were collected before TPIAT in all consenting participants (n=384) and 1 year after TPIAT in a subset (n=183) with in-person follow up. Based on preliminary data from our and other labs, we hypothesize that a set of objective biomarkers from blood and/or urine can distinguish those who benefit from TPIAT (pain reduction/relief) from those who respond poorly. This clinical question is particularly important because TPIAT is a major, costly intervention with irreversible lifelong health implications. In SA 1, we will identify plasma biomarkers collected before TPIAT that predict persistent pain after TPIAT using samples and data from POST. Samples will be divided into FDA-compliant discovery and validation groups. Pain response to TPIAT will be defined by opioid use and pain scores at 1 year. Secondary measures for QoL and pain interference with daily function will also be assessed. In SA 2, we will use the same approach to identify pre-TPIAT urine biomarkers that predict persistent pain after TPIAT. In SA 3, we will assess change in biomarkers from pre-TPIAT to 1 year using plasma and urine biomarkers validated in SA 1/2 (SA 3a) and also using a discovery and validation approach to identify additional plasma and urine biomarkers that may have distinct patterns over time in patients with vs. without persistent pain (SA 3b). Identifying plasma and urinary biomarkers will improve TPIAT patient selection, reducing negative impact on patients and health care infrastructure. Data from this study will identify biomarkers that can also be investigated in the larger populations with CP and other pain syndromes.