13 research outputs found

    International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

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    Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist

    Corrigendum to ‘An international genome-wide meta-analysis of primary biliary cholangitis: Novel risk loci and candidate drugs’ [J Hepatol 2021;75(3):572–581]

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    Pretreatment prediction of response to ursodeoxycholic acid in primary biliary cholangitis: development and validation of the UDCA Response Score

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    Background Treatment guidelines recommend a stepwise approach to primary biliary cholangitis: all patients begin treatment with ursodeoxycholic acid (UDCA) monotherapy and those with an inadequate biochemical response after 12 months are subsequently considered for second-line therapies. However, as a result, patients at the highest risk can wait the longest for effective treatment. We determined whether UDCA response can be accurately predicted using pretreatment clinical parameters. Methods We did logistic regression analysis of pretreatment variables in a discovery cohort of patients in the UK with primary biliary cholangitis to derive the best-fitting model of UDCA response, defined as alkaline phosphatase less than 1·67 times the upper limit of normal (ULN), measured after 12 months of treatment with UDCA. We validated the model in an external cohort of patients with primary biliary cholangitis and treated with UDCA in Italy. Additionally, we assessed correlations between model predictions and key histological features, such as biliary injury and fibrosis, on liver biopsy samples. Findings 2703 participants diagnosed with primary biliary cholangitis between Jan 1, 1998, and May 31, 2015, were included in the UK-PBC cohort for derivation of the model. The following pretreatment parameters were associated with lower probability of UDCA response: higher alkaline phosphatase concentration (p&lt;0·0001), higher total bilirubin concentration (p=0·0003), lower aminotransferase concentration (p=0·0012), younger age (p&lt;0·0001), longer interval from diagnosis to the start of UDCA treatment (treatment time lag, p&lt;0·0001), and worsening of alkaline phosphatase concentration from diagnosis (p&lt;0·0001). Based on these variables, we derived a predictive score of UDCA response. In the external validation cohort, 460 patients diagnosed with primary biliary cholangitis were treated with UDCA, with follow-up data until May 31, 2016. In this validation cohort, the area under the receiver operating characteristic curve for the score was 0·83 (95% CI 0·79–0·87). In 20 liver biopsy samples from patients with primary biliary cholangitis, the UDCA response score was associated with ductular reaction (r=–0·556, p=0·0130) and intermediate hepatocytes (probability of response was 0·90 if intermediate hepatocytes were absent vs 0·51 if present). Interpretation We have derived and externally validated a model based on pretreatment variables that accurately predicts UDCA response. Association with histological features provides face validity. This model provides a basis to explore alternative approaches to treatment stratification in patients with primary biliary cholangitis

    Pretreatment prediction of response to ursodeoxycholic acid in primary biliary cholangitis: development and validation of the UDCA Response Score

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    Background Treatment guidelines recommend a stepwise approach to primary biliary cholangitis: all patients begin treatment with ursodeoxycholic acid (UDCA) monotherapy and those with an inadequate biochemical response after 12 months are subsequently considered for second-line therapies. However, as a result, patients at the highest risk can wait the longest for effective treatment. We determined whether UDCA response can be accurately predicted using pretreatment clinical parameters. Methods We did logistic regression analysis of pretreatment variables in a discovery cohort of patients in the UK with primary biliary cholangitis to derive the best-fitting model of UDCA response, defined as alkaline phosphatase less than 1·67 times the upper limit of normal (ULN), measured after 12 months of treatment with UDCA. We validated the model in an external cohort of patients with primary biliary cholangitis and treated with UDCA in Italy. Additionally, we assessed correlations between model predictions and key histological features, such as biliary injury and fibrosis, on liver biopsy samples. Findings 2703 participants diagnosed with primary biliary cholangitis between Jan 1, 1998, and May 31, 2015, were included in the UK-PBC cohort for derivation of the model. The following pretreatment parameters were associated with lower probability of UDCA response: higher alkaline phosphatase concentration (p<0·0001), higher total bilirubin concentration (p=0·0003), lower aminotransferase concentration (p=0·0012), younger age (p<0·0001), longer interval from diagnosis to the start of UDCA treatment (treatment time lag, p<0·0001), and worsening of alkaline phosphatase concentration from diagnosis (p<0·0001). Based on these variables, we derived a predictive score of UDCA response. In the external validation cohort, 460 patients diagnosed with primary biliary cholangitis were treated with UDCA, with follow-up data until May 31, 2016. In this validation cohort, the area under the receiver operating characteristic curve for the score was 0·83 (95% CI 0·79–0·87). In 20 liver biopsy samples from patients with primary biliary cholangitis, the UDCA response score was associated with ductular reaction (r=–0·556, p=0·0130) and intermediate hepatocytes (probability of response was 0·90 if intermediate hepatocytes were absent vs 0·51 if present). Interpretation We have derived and externally validated a model based on pretreatment variables that accurately predicts UDCA response. Association with histological features provides face validity. This model provides a basis to explore alternative approaches to treatment stratification in patients with primary biliary cholangitis

    Corrigendum to ‘An international genome-wide meta-analysis of primary biliary cholangitis: Novel risk loci and candidate drugs’ [J Hepatol 2021;75(3):572–581] (Journal of Hepatology (2021) 75(3) (572–581), (S0168827821003342), (10.1016/j.jhep.2021.04.055))

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    It has come to our attention that the name of one of the authors in our manuscript was incorrectly spelled ‘Jinyoung Byan’; the correct spelling is ‘Jinyoung Byun’ as in the author list above. In addition, the excel files of the supplementary tables were not included during the online publication of our article. These have now been made available online. We apologize for any inconvenience caused

    Corrigendum to \u2018An international genome-wide meta-analysis of primary biliary cholangitis: Novel risk loci and candidate drugs\u2019 [J Hepatol 2021;75(3):572\u2013581] (Journal of Hepatology (2021) 75(3) (572\u2013581), (S0168827821003342), (10.1016/j.jhep.2021.04.055))

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    It has come to our attention that the name of one of the authors in our manuscript was incorrectly spelled \u2018Jinyoung Byan\u2019; the correct spelling is \u2018Jinyoung Byun\u2019 as in the author list above. In addition, the excel files of the supplementary tables were not included during the online publication of our article. These have now been made available online. We apologize for any inconvenience caused

    An international genome-wide meta-analysis of primary biliary cholangitis: Novel risk loci and candidate drugs.

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    BACKGROUNDS & AIMS Primary biliary cholangitis (PBC) is a chronic liver disease in which autoimmune destruction of the small intrahepatic bile ducts eventually leads to cirrhosis. Many patients have inadequate response to licensed medications, motivating the search for novel therapies. Previous genome-wide association studies (GWAS) and meta-analyses (GWMA) of PBC have identified numerous risk loci for this condition, providing insight into its aetiology. We undertook the largest GWMA of PBC to date, aiming to identify additional risk loci and prioritise candidate genes for in silico drug efficacy screening. METHODS We combined new and existing genotype data for 10,516 cases and 20,772 controls from 5 European and 2 East Asian cohorts. RESULTS We identified 56 genome-wide significant loci (20 novel) including 46 in European, 13 in Asian, and 41 in combined cohorts; and a 57 genome-wide significant locus (also novel) in conditional analysis of the European cohorts. Candidate genes at newly identified loci include FCRL3, INAVA, PRDM1, IRF7, CCR6, CD226, and IL12RB1, which each play key roles in immunity. Pathway analysis reiterated the likely importance of pattern recognition receptor and TNF signalling, JAK-STAT signalling, and differentiation of T helper (T)1 and T17 cells in the pathogenesis of this disease. Drug efficacy screening identified several medications predicted to be therapeutic in PBC, some of which are well-established in the treatment of other autoimmune disorders. CONCLUSIONS This study has identified additional risk loci for PBC, provided a hierarchy of agents that could be trialled in this condition, and emphasised the value of genetic and genomic approaches to drug discovery in complex disorders. LAY SUMMARY Primary biliary cholangitis (PBC) is a chronic liver disease that eventually leads to cirrhosis. In this study, we analysed genetic information from 10,516 people with PBC and 20,772 healthy individuals recruited in Canada, China, Italy, Japan, the UK, or the USA. We identified several genetic regions associated with PBC. Each of these regions contains several genes. For each region, we used diverse sources of evidence to help us choose the gene most likely to be involved in causing PBC. We used these 'candidate genes' to help us identify medications that are currently used for treatment of other conditions, which might also be useful for treatment of PBC
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