NR1H4 disease: rapidly progressing neonatal intrahepatic cholestasis and early death.

BACKGROUND: Clinical studies on progressive familial intrahepatic cholestasis (PFIC) type 5 caused by mutations in NR1H4 are limited. METHODS: New patients with biallelic NR1H4 variants from our center and all patients from literature were retrospectively analyzed. RESULTS: Three new patients were identified to be carrying five new variants. Liver phenotypes of our patients manifests as low-γ-glutamyl transferase cholestasis, liver failure and related complications. One patient underwent liver transplantation (LT) and survived, and two other patients died without LT. Nine other patients were collected through literature review. Twelve out of 13 patients showed neonatal jaundice, with the median age of onset being 7 days after birth. Reported clinical manifestations included cholestasis (13/13, 100%), elevated AFP (11/11, 100%), coagulopathy (11/11, 100%), hypoglycemia (9/13, 69%), failure to thrive (8/13, 62%), splenomegaly (7/13, 54%), hyperammonemia (7/13, 54%), and hepatomegaly (6/13, 46%). Six of 13 patients received LT at a median age of 6.2 months, and only one patient died of acute infection at one year after LT. Other 7 patients had no LT and died with a median age of 5 months (range 1.2-8). There were 8 patients with homozygous genotype and 5 patients with compound heterozygous genotype. In total, 13 different variants were detected, and 5 out of 12 single or multiple nucleotides variants were located in exon 5. CONCLUSIONS: We identified three newly-diagnosed patients and five novel mutations. NR1H4-related PFIC typically cause progressive disease and early death. LT may be the only lifesaving therapy leading to cure.

Body mass index and γ-glutamyl transferase expression in normal and cancerous breast tissue.

BACKGROUND: Localized to cell membrane, γ-glutamyl transferase (GGT) is a reliable marker for the evaluation of cell distress occurring in several pathological conditions including obesity, metabolic syndrome, and cancer. In particular, high GGT serum levels are associated with breast cancer incidence and progression. METHODS: The tissue expression of GGT1, the gene coding for GGT, was investigated in silico in a large case series of paired samples of breast cancer and adjacent histologically normal (HN) tissue, and in a collection of healthy breast tissues from reduction mammoplasty. The association of GGT1 with patient's body mass index (BMI), and the relationship between GGT1 and a panel of genes involved in apoptosis, IGF-1 signaling, or coding for adipokines and adipokine receptors were also investigated. RESULTS: GGT1 expression was significantly higher in tumor than in the adjacent HN tissue (P = 0.0002). Unexpectedly, the expression of GGT1 was inversely associated with BMI in normal and HN tissue, whereas no correlation was found in cancerous tissue. In all tissues, GGT1 correlated positively with TP53 and negatively with BCL2 and LEPR, whereas only in normal and HN tissue GGT1 correlated positively with IGF1R. The linear regression model, adjusted for BMI, showed no confounding effect on any correlation, except for the correlation of GGT1 with LEPR in normal tissue from healthy women. CONCLUSIONS: Even if present results provide interesting insights on the still elusive mechanism(s) underlying the association between obesity and epithelial cell proliferation, possibly promoting neoplastic transformation, such relationship deserves further investigation in other independent datasets.

The relationship between 25-hydroxyvitamin D concentration and liver enzymes in overweight or obese adults: Cross-sectional and interventional outcomes.

Vitamin D deficiency is prevalent in individuals with non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis. However, there is limited and inconsistent data on the effect of vitamin D supplementation on liver function. Hepatic enzymes have been used as surrogate markers for NAFLD and have been associated with metabolic syndrome. We examined the relationships between 25-hydroxyvitamin D (25(OH)D) and γ-glutamyl transferase (GGT), alanine aminotransferase (ALT), alkaline phosphatase (ALP) in 120 drug-naïve individuals with no history of liver disease. In addition, the effect of vitamin D supplementation (100,000 loading dose of cholecalciferol followed by 4000IU daily for 16 weeks) on hepatic enzymes was investigated in a subgroup of 54 vitamin D-deficient overweight or obese individuals (28 randomised to cholecalciferol and 26 to placebo). Hepatic enzymes, anthropometric parameters, lipid profile, insulin sensitivity (hyperinsulinaemic-euglycaemic clamp, M value) and high sensitivity C-reactive protein (hs-CRP) were measured before and after the intervention. In the cross-sectional study, levels of GGT and ALT were higher in men compared to women (both p=0.001). There were no significant differences in GGT, ALT and ALP between vitamin D categories (25(OH)D<25nmol/L, 25-50nmol/L, and >50nmol/L) and no relationships were found between the three enzymes and 25(OH)D before and after adjustment for age, sex, BMI, WHR, and insulin sensitivity (all p>0.5). In the randomised trial, 25(OH)D concentrations increased in the vitamin D group (mean change 57.0±21.3nmol/L) compared to the placebo group (mean change 1.9±15.1nmol/L). Mean changes in GGT, ALT and ALP were not significantly different between vitamin D and placebo groups (all p>0.2). Change in 25(OH)D concentration was not correlated with changes in GGT, ALT and ALP before and after adjustments for age and sex (all p>0.1). In summary, 25(OH)D concentrations were not related to hepatic enzymes in drug-naive adults with no history of liver disease, and vitamin D supplementation had no effect on the serum levels of hepatic enzymes in vitamin D-deficient and overweight or obese, otherwise healthy individuals. Hence, vitamin D supplementation is unlikely to prevent incident NAFLD.

Assessment of machine-learning techniques on large pathology data sets to address assay redundancy in routine liver function test profiles.

BACKGROUND: Routine liver function tests (LFTs) are central to serum testing profiles, particularly in community medicine. However there is concern about the redundancy of information provided to requesting clinicians. Large quantities of clinical laboratory data and advances in computational knowledge discovery methods provide opportunities to re-examine the value of individual routine laboratory results that combine for LFT profiles. METHODS: The machine learning methods recursive partitioning (decision trees) and support vector machines (SVMs) were applied to aggregate clinical chemistry data that included elevated LFT profiles. Response categories for γ-glutamyl transferase (GGT) were established based on whether the patient results were within or above the sex-specific reference interval. Single decision tree and SVMs were applied to test the accuracy of GGT prediction by the highest ranked predictors of GGT response, alkaline phosphatase (ALP) and alanine amino-transaminase (ALT). RESULTS: Through interrogating more than 20,000 individual cases comprising both sexes and all ages, decision trees predicted GGT category at 90% accuracy using only ALP and ALT, with a SVM prediction accuracy of 82.6% after 10-fold training and testing. Bilirubin, lactate dehydrogenase (LD) and albumin did not enhance prediction, or reduced accuracy. Comparison of abnormal (elevated) GGT categories also supported the primacy of ALP and ALT as screening markers, with serum urate and cholesterol also useful. CONCLUSIONS: Machine-learning interrogation of massive clinical chemistry data sets demonstrated a strategy to address redundancy in routine LFT screening by identifying ALT and ALP in tandem as able to accurately predict GGT elevation, suggesting that GGT can be removed from routine LFT screening.