D-SOLVE Cohorts (Cohort A and B)

Chronic Liver Disease Clinical Trial

— HDV750  

Official title:

D-SOLVE Cohorts (Cohort A and B)

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06160635
• Other study ID #: HDV750
• Status: Recruiting
• Start date: February 22, 2023
• Est. completion date: September 30, 2026

Study information

• Verified date: November 2023
• Source: Hannover Medical School
• Contact: Petra Dörge
• Phone: +495115326057
• Email: doerge.petra[@]mh-hannover.de
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

Hepatitis D is by far the most severe form of chronic viral hepatitis, frequently leading to liver failure, hepatocellular carcinoma and death. Hepatitis D is caused by coinfection Hepatitis D is caused by co-infection with hepatitis B virus (HBV) and hepatitis D virus (HDV).

This multicenter cohort should enable a comprehensive and unbiased biomarker screening of well-defined HDV-infected patients, followed by mechanistic studies to determine the functional role of distinct molecules. Patient surveillance strategies and antiviral treatment approaches could be personalized which should reduce clinical and social disease burden, improve quality of life and save direct and indirect costs caused by HDV infection.

Description:

The D-SOLVE consortium ("Understanding the individual host response against Hepatitis D Virus to develop a personalized approach for the management of hepatitis D"), aims for an unbiased screening of a large multicenter cohort of well-defined HDV-infected patients to better understand individual factors determining the outcome of infection and to identify subjects benefitting from currently available treatments.

The D-SOLVE cohorts will be collected retrospectively as well as prospectively with clinical and virological data and biomaterial for the biomarker analysis. The aim of the cohorts is as following:

Cohort A: To define the demographic, clinical, virological, and immunological features of a large cross-sectional cohort of 750 untreated and treated HDV patients at 4 EU centers. To compare these features among patients with different origin, gender, disease severity and treatment. To collect biological material to generate translational studies, aimed to better understand pathogenesis, natural history and treatment response.

Cohort B: To identify histological and immunological features that are associated with fibrosis progression and clinical complications in patients with chronic HDV infection.

The D-SOLVE consortium has received funding from the Horizon 2020 EU Horizon Call "Personalised medicine and infectious diseases: understanding the individual host response to viruses (e.g. SARS-CoV-2)" of the European Union (grant agreement No 101057917). The consortium is coordinated by Hannover Medical School (MHH) and the Centre for Individualised Infection Medicine (CiiM). Other partners are:

• Helmholtz-Zentrum für Infektionsforschung (HZI), Germany

• Institut national de la santé et de la recherche médicale (INSERM)

• Karolinska Institutet (KI), Sweden

• Karolinska University Hospital / Region Stockholm (KUH), Sweden

• Policlinico of Milan (PFM), Italy

• National Institute for Infectious Diseases "Prof Dr Matei Balș" (INBIMB), Romania

• Helmholtz-Zentrum für Informationssicherheit (CISPA), Germany

The Cohorts and the biomarker screening are part of the EU-funded D-SOLVE Consortium.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 750
• Est. completion date: September 30, 2026
• Est. primary completion date: September 30, 2026
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Anti-HDV positive

• =18 years old

• Sex: m/f/d

• Informed consent for prospective procedures

Exclusion Criteria:

• Anti-HDV negative

Related Conditions & MeSH terms

• Chronic Liver Disease
• HDV Infection
• Liver Diseases

Locations

Country	Name	City	State
Germany	Hannover Medical School, Department of Gastroenterology, Hepatology, Infectious Disease and Endocrinology	Hannover
Italy	Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (University of Milan)	Milan
Romania	Institutul de Boli Infectioase "Prof. Dr. Matei Bals"	Bucharest
Sweden	Karolinska University Hospital and Karolinska Institutet	Stockholm

Sponsors (6)

Lead Sponsor	Collaborator
Hannover Medical School	Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Helmholtz Centre for Infection Research, Karolinska Institutet, Karolinska University Hospital, National Institute of Infectious Diseases Matei Bals

Countries where clinical trial is conducted

Germany,  Italy,  Romania,  Sweden, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Biosample Screening	Identification of biomarkers that are associated with disease control, progression and treatment response by a multiomics approach that includes the investigation of: - the genome by the Illumina Infinium Global Screening array - the transcriptome by RNA-sequencing and single-cell RNA-sequencing (subset of samples) - the proteome by the Olink technology (high throughput proximity extension assay) - the metabolome by HPLC 1H-NMR (~2k metabolite features) - the methylome (Illumina 850k array) - immune phenotypes by high dimensional spectral flow cytometry - Spatial transcriptomics and multiplex imaging of HDV-patient liver biopsies	3 years
Secondary	Definition of the demographic, clinical and virological features of the cohort.	Identification of immunological determinants of liver disease progression, viral control and treatment response by - scRNA/ATAC sequencing of Ag-specific T cells, NK cells and MAIT cells (PBMC) - spatial multiomics with feature barcoding technology of liver core biopsies - Validation of findings by 29-color flow cytometry, hepatoma HDV infection system and respective mouse models	3 years
Secondary	Identification of virological and immunological features and characteristics that relate to disease severity and treatment response.	Establishment of a computational model to predict immune responses and disease phenotype	3 years