Dataset Information

The Brazilian Rare Genomes Project: Validation of Whole Genome Sequencing for Rare Diseases Diagnosis.

ABSTRACT: Rare diseases affect up to 13.2 million individuals in Brazil. The Brazilian Rare Genomes Project is envisioned to further the implementation of genomic medicine into the Brazilian public healthcare system. Here we report the validation results of a whole genome sequencing (WGS) procedure for implementation in clinical laboratories. In addition, we report data quality for the first 1,200 real-world patients sequenced. We sequenced a well-characterized group of 76 samples, including seven gold standard genomes, using a PCR-free WGS protocol on Illumina Novaseq 6,000 equipment. We compared the observed variant calls with their expected calls, observing good concordance for single nucleotide variants (SNVs; mean F-measure = 99.82%) and indels (mean F-measure = 99.57%). Copy number variants and structural variants events detection performances were as expected (F-measures 96.6% and 90.3%, respectively). Our WGS protocol presented excellent intra-assay reproducibility (coefficients of variation ranging between 0.03% and 0.20%) and inter-assay reproducibility (coefficients of variation ranging between 0.02% and 0.09%). Limitations of the WGS protocol include the inability to confidently detect variants such as uniparental disomy, balanced translocations, repeat expansion variants, and low-level mosaicism. In summary, the observed performance of the WGS protocol was in accordance with that seen in the best centers worldwide. The Rare Genomes Project is an important initiative to bring pivotal improvements to the quality of life of the affected individuals.

SUBMITTER: Coelho AVC

PROVIDER: S-EPMC9108541 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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The Brazilian Rare Genomes Project: Validation of Whole Genome Sequencing for Rare Diseases Diagnosis.

Coelho Antonio Victor Campos AVC Mascaro-Cordeiro Bruna B Lucon Danielle Ribeiro DR Nóbrega Maria Soares MS Reis Rodrigo de Souza RS de Alexandre Rodrigo Bertollo RB Moura Livia Maria Silva LMS de Oliveira Gustavo Santos GS Guedes Rafael Lucas Muniz RLM Caraciolo Marcel Pinheiro MP Zurro Nuria Bengala NB Cervato Murilo Castro MC Oliveira João Bosco JB

Frontiers in molecular biosciences 20220502

Rare diseases affect up to 13.2 million individuals in Brazil. The Brazilian Rare Genomes Project is envisioned to further the implementation of genomic medicine into the Brazilian public healthcare system. Here we report the validation results of a whole genome sequencing (WGS) procedure for implementation in clinical laboratories. In addition, we report data quality for the first 1,200 real-world patients sequenced. We sequenced a well-characterized group of 76 samples, including seven gold st ...[more]

PMID: 35586190

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Project description:BackgroundGenome sequencing (GS) has revolutionised the diagnostic odyssey of patients with rare genetic diseases (RDs) and accelerated large-scale genome projects globally. However, the impact of GS on patients with RDs is yet to be investigated among genome projects in Asia. The Hong Kong Genome Project (HKGP) was implemented to benefit patients and families with RDs in Hong Kong, and to increase the inclusiveness of Chinese genomic data. This study evaluated the impact of short read GS (srGS), complemented by long read GS (lrGS) in a subset, on individuals recruited in the pilot phase of the HKGP.MethodsGS was performed on a prospective cohort of patients with suspected genetic disease recruited by territory-wide referrals to the HKGP. All participants received srGS, while lrGS was applied to a subset to resolve technically challenging regions unclear from srGS and provide phasing information for potential compound heterozygous variants. A phenotypic-driven diagnostic workflow was implemented to filter and prioritise rare and likely disease-causing variants. The primary outcome was diagnostic yield. The impact on the diagnostic odyssey and clinical management was also assessed.FindingsA total of 1264 individuals from 520 families with a broad spectrum of RDs were recruited, with 94% of probands being Chinese. srGS was performed for all individuals and lrGS was performed in 21 individuals. The use of srGS achieved a molecular diagnosis in 24% (125/520) of probands, and an additional 4% (21/520) with the assistance from lrGS. Approximately one-third of the identified diagnostic variants being novel. Diagnostic yield was found to be significantly higher among adult probands compared to paediatric probands (32% vs 24%; p = 0.025). The diagnostic yield was significantly higher in probands without prior genetic testing (37%; n = 185) compared to those previously tested, including exome and genome sequencing (23%; n = 335) (p = 0.001). GS ended diagnostic odysseys with an average length of 15 years (0.5-59), and potentially impacted clinical management in 77% (113/146) of diagnosed probands.InterpretationThis population-based genome project shed light on the consideration of integrating srGS and lrGS in clinical workflows for RDs. The identification of unique and prevalent variants from Southeast Asia increased the inclusiveness of Chinese genomic data, contributing to greater representation and genomic diversity.FundingThe HKGP is a publicly funded genome sequencing initiative commissioned by the Health Bureau of the HKSAR Government.

Project description:BackgroundA major obstacle faced by rare disease families is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years, and causal variants are identified in under 50%. The Rare Genomes Project (RGP) is a direct-to-participant research study on the utility of genome sequencing (GS) for diagnosis and gene discovery. Families are consented for sharing of sequence and phenotype data with researchers, allowing development of a Critical Assessment of Genome Interpretation (CAGI) community challenge, placing variant prioritization models head-to-head in a real-life clinical diagnostic setting.MethodsPredictors were provided a dataset of phenotype terms and variant calls from GS of 175 RGP individuals (65 families), including 35 solved training set families, with causal variants specified, and 30 test set families (14 solved, 16 unsolved). The challenge tasked teams with identifying the causal variants in as many test set families as possible. Ranked variant predictions were submitted with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on rank position of true positive causal variants and maximum F-measure, based on precision and recall of causal variants across EPCR thresholds.ResultsSixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performing teams recalled the causal variants in up to 13 of 14 solved families by prioritizing high quality variant calls that were rare, predicted deleterious, segregating correctly, and consistent with reported phenotype. In unsolved families, newly discovered diagnostic variants were returned to two families following confirmatory RNA sequencing, and two prioritized novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant, in an unsolved proband with phenotype overlap with asparagine synthetase deficiency.ConclusionsBy objective assessment of variant predictions, we provide insights into current state-of-the-art algorithms and platforms for genome sequencing analysis for rare disease diagnosis and explore areas for future optimization. Identification of diagnostic variants in unsolved families promotes synergy between researchers with clinical and computational expertise as a means of advancing the field of clinical genome interpretation.

Dataset Information

The Brazilian Rare Genomes Project: Validation of Whole Genome Sequencing for Rare Diseases Diagnosis.

Publications

The Brazilian Rare Genomes Project: Validation of Whole Genome Sequencing for Rare Diseases Diagnosis.

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