跳至主要内容
临床试验/NCT06060184
NCT06060184
尚未招募
不适用

Initiative for Clinical Long-read Sequencing - Towards Implementation of Long-read Genome Sequencing in Routine Diagnostics

University Hospital Tuebingen1 个研究点 分布在 1 个国家目标入组 500 人2023年12月1日

概览

阶段
不适用
干预措施
未指定
疾病 / 适应症
Genetic Predisposition
发起方
University Hospital Tuebingen
入组人数
500
试验地点
1
主要终点
Number of patients with Rare Disease (RD) or cancer predisposition syndromes with confirmed diagnosis by LR-GS compared to previous diagnostic methods including SR-GS
状态
尚未招募
最后更新
2年前

概览

简要总结

The study aims to comprehensively introduce Long-read Genome sequencing (LR-GS) based genetic testing into clinical routine. In order to demonstrate the superiority of untargeted LR-GS over Short-read Genome sequencing (SR-GS) to establish firm genetic diagnoses, the investigators will rely on a multi-center "Translate Nationale Aktionsbündnis für Menschen mit Seltenen Erkrankungen" (Translate National Action Alliance for People with Rare Diseases Germany, TNAMSE) cohort of unsolved patients with neurological, neurodevelopmental, and imprinting disorders that is expectedly enriched for complex genomic variation. Within the framework of genomDE, the investigators will then implement, for the first time, LR-GS in the diagnostic work-up of a prospective cohort of patients with a broad range of clinical indications including rare diseases and cancer predisposition.

详细描述

The proposed study aims to develop a blueprint for the implementation of LR-GS in clinical diagnostics. Hence Standard Operating Procedures (SOPs) and guidelines for library preparation, bioinformatic analysis, and clinical interpretation will be compiled. Furthermore, the investigators intend to develop an open source 'gold standard' bioinformatics pipeline, addressing all relevant types of genomic alterations, thus providing the bioinformatic basis for a streamlined implementation of LR-GS at other sites. In addition to in-depth phenotype information the availability of SR-GS will be instrumental to benchmark the ability to detect different types of genomic variation. Additional relevant issues for genetic testing such as variant calling in difficult-to-map genomic regions, detection of genomic methylation patterns, characterization of repeat expansion and duplicated genes, and haplotype-phased genome de novo assembly will be addressed. Moreover, based on the strong background in Artificial Intelligence (AI) driven variant prioritization in the consortium, the investigators aim to implement and/or develop tools that enable an efficient prioritization of disease-causing variants. Beyond the usage within the context of the proposed study, generated datasets will be made available according to the Findable, Accessible, Interoperable and Reusable (FAIR) principles for national (German Human Genome-Phenome Archive, GHGA) and international (European Genome-Phenome Archive, EGA, Genome-Phenome Analysis Platform, GPaP) data repositories. the investigators aim to establish a population scale reference dataset for Structural variants (SV), which is absolutely mandatory in the context of rare disease diagnostics.

注册库
clinicaltrials.gov
开始日期
2023年12月1日
结束日期
2026年12月1日
最后更新
2年前
研究类型
Interventional
研究设计
Parallel
性别
All

研究者

责任方
Sponsor

入排标准

入选标准

  • Unclear molecular cause of the disease (retrospective cohort)
  • Indication for genome diagnostics (prospective cohort; e.g. within the initiative for genomic medicine (genomDE) based on §64e SGB V)
  • Suspected genetic cause of the disease

排除标准

  • Missing informed consent of the patient or legal guardian

结局指标

主要结局

Number of patients with Rare Disease (RD) or cancer predisposition syndromes with confirmed diagnosis by LR-GS compared to previous diagnostic methods including SR-GS

时间窗: Day 1

A molecular diagnosis is considered confirmed when likely pathogenic or pathogenic variants are identified according to the American College of Medical Genetics and Genomics (ACMG). classification.

研究点 (1)

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