Progressive familial intrahepatic cholestasis—outcome and time to transplant after biliary diversion according to genetic subtypes

BackgroundProgressive familial intrahepatic cholestasis (PFIC) is a heterogeneous disease characterized by progressive cholestasis in early childhood. Surgical therapy aims at preventing bile absorption either by external or internal biliary diversion (BD). Several different genetic subtypes encode for defects in bile transport proteins, and new subtypes are being discovered ongoingly. Overall, the literature is scarce, however, accumulating evidence points to PFIC 2 having a more aggressive course and to respond less favorable to BD. With this knowledge, we aimed to retrospectively analyze the long-term outcome of PFIC 2 compared to PFIC 1 following BD in children at our center.MethodsClinical data and laboratory findings of all children with PFIC, who were treated and managed in our hospital between 1993 and 2022, were analyzed retrospectively.ResultsOverall, we treated 40 children with PFIC 1 (n = 10), PFIC 2 (n = 20) and PFIC 3 (n = 10). Biliary diversion was performed in 13 children (PFIC 1, n = 6 and 2, n = 7). Following BD, bile acids (BA) (p = 0.0002), cholesterol (p < 0.0001) and triglyceride (p < 0.0001) levels significantly decreased only in children with PFIC 1 but not in PFIC 2. Three out of 6 children (50%) with PFIC 1 and 4 out of 7 children (57%) with PFIC 2 required liver transplantation despite undergoing BD. On an individual case basis, BA reduction following BD predicted this outcome. Of the 10 children who had PFIC 3, none had biliary diversion and 7 (70%) required liver transplantation.ConclusionIn our cohort, biliary diversion was effective in decreasing bile acids, cholesterol levels as well as triglycerides in the serum only in children with PFIC 1 but not PFIC 2. On an individual case level, a decrease in BA following BD predicted the need for liver transplantation

Vasor: Accurate prediction of variant effects for amino acid substitutions in multidrug resistance protein 3

The phosphatidylcholine floppase multidrug resistance protein 3 (MDR3) is an essential hepatobiliary transport protein. MDR3 dysfunction is associated with various liver diseases, ranging from severe progressive familial intrahepatic cholestasis to transient forms of intrahepatic cholestasis of pregnancy and familial gallstone disease. Single amino acid substitutions are often found as causative of dysfunction, but identifying the substitution effect in in vitro studies is time and cost intensive. We developed variant assessor of MDR3 (Vasor), a machine learning‐based model to classify novel MDR3 missense variants into the categories benign or pathogenic. Vasor was trained on the largest data set to date that is specific for benign and pathogenic variants of MDR3 and uses general predictors, namely Evolutionary Models of Variant Effects (EVE), EVmutation, PolyPhen‐2, I‐Mutant2.0, MUpro, MAESTRO, and PON‐P2 along with other variant properties, such as half‐sphere exposure and posttranslational modification site, as input. Vasor consistently outperformed the integrated general predictors and the external prediction tool MutPred2, leading to the current best prediction performance for MDR3 single‐site missense variants (on an external test set: F1‐score, 0.90; Matthew's correlation coefficient, 0.80). Furthermore, Vasor predictions cover the entire sequence space of MDR3. Vasor is accessible as a webserver at https://cpclab.uni‐duesseldorf.de/mdr3_predictor/ for users to rapidly obtain prediction results and a visualization of the substitution site within the MDR3 structure. The MDR3‐specific prediction tool Vasor can provide reliable predictions of single‐site amino acid substitutions, giving users a fast way to initially assess whether a variant is benign or pathogenic

A rare cause of a cholestatic jaundice in a North African teenager

We report an unusual case of intermittent episodes of cholestasis in a young patient. The cholestatic attacks were preceded in each case by an infection and subsequent antibiotic therapies. After ruling out many possible causes of cholestatic hepatitis, the differential diagnoses were a benign recurrent intrahepatic cholestasis or a drug-induced liver injury. We discuss here the diagnostic approach and interpretation of the genetic analysis

Vasor: Accurate prediction of variant effects for amino acid substitutions in multidrug resistance protein 3

The phosphatidylcholine floppase multidrug resistance protein 3 (MDR3) is an essential hepatobiliary transport protein. MDR3 dysfunction is associated with various liver diseases, ranging from severe progressive familial intrahepatic cholestasis to transient forms of intrahepatic cholestasis of pregnancy and familial gallstone disease. Single amino acid substitutions are often found as causative of dysfunction, but identifying the substitution effect in in vitro studies is time and cost intensive. We developed variant assessor of MDR3 (Vasor), a machine learning‐based model to classify novel MDR3 missense variants into the categories benign or pathogenic. Vasor was trained on the largest data set to date that is specific for benign and pathogenic variants of MDR3 and uses general predictors, namely Evolutionary Models of Variant Effects (EVE), EVmutation, PolyPhen‐2, I‐Mutant2.0, MUpro, MAESTRO, and PON‐P2 along with other variant properties, such as half‐sphere exposure and posttranslational modification site, as input. Vasor consistently outperformed the integrated general predictors and the external prediction tool MutPred2, leading to the current best prediction performance for MDR3 single‐site missense variants (on an external test set: F1‐score, 0.90; Matthew's correlation coefficient, 0.80). Furthermore, Vasor predictions cover the entire sequence space of MDR3. Vasor is accessible as a webserver at https://cpclab.uni‐duesseldorf.de/mdr3_predictor/ for users to rapidly obtain prediction results and a visualization of the substitution site within the MDR3 structure. The MDR3‐specific prediction tool Vasor can provide reliable predictions of single‐site amino acid substitutions, giving users a fast way to initially assess whether a variant is benign or pathogenic