12 research outputs found

    Beyond gene-disease validity: capturing structured data on inheritance, allelic requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

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    Background: As the availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including secondary findings. // Methods: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. // Results: For 36/65 gene-disease pairs, loss of function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using the CardiacG2P dataset as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. // Conclusions: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is a pre-requisite for scalable genomic testing

    Beyond gene-disease validity: capturing structured data on inheritance, allelic-requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

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    BACKGROUND: As availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including as secondary findings. METHODS: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. RESULTS: For 36/65 gene-disease pairs, loss-of-function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using CardiacG2P as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. CONCLUSIONS: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is pre-requisite for scalable genomic testing

    Beyond gene-disease validity: capturing structured data on inheritance, allelic requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

    Get PDF
    BACKGROUND: As the availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including secondary findings. METHODS: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. RESULTS: For 36/65 gene-disease pairs, loss of function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using the CardiacG2P dataset as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. CONCLUSIONS: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is a pre-requisite for scalable genomic testing

    The Clinical Application of Urine Soluble CD163 in ANCA-Associated Vasculitis.

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    BACKGROUND: Up to 70% of patients with ANCA-associated vasculitis (AAV) develop GN, with 26% progressing to ESKD. Diagnostic-grade and noninvasive tools to detect active renal inflammation are needed. Urinary soluble CD163 (usCD163) is a promising biomarker of active renal vasculitis, but a diagnostic-grade assay, assessment of its utility in prospective diagnosis of renal vasculitis flares, and evaluation of its utility in proteinuric states are needed. METHODS: We assessed a diagnostic-grade usCD163 assay in ( RESULTS: We established a diagnostic reference range, with a cutoff of 250 ng/mmol for active renal vasculitis (area under the curve [AUC], 0.978). Using this cutoff, usCD163 was elevated in renal vasculitis flare (AUC, 0.95) but remained low in flare mimics, such as nonvasculitic AKI. usCD163\u27s specificity declined in patients with AAV who had nephrotic-range proteinuria and in those with primary podocytopathy, with 62% of patients with nephrotic syndrome displaying a positive usCD163. In patients with AAV and significant proteinuria, usCD163 normalization to total urine protein rather than creatinine provided the greatest clinical utility for diagnosing active renal vasculitis. CONCLUSIONS: usCD163 is elevated in renal vasculitis flare and remains low in flare mimics. Nonspecific protein leakage in nephrotic syndrome elevates usCD163 in the absence of glomerular macrophage infiltration, resulting in false-positive results; this can be corrected with urine protein normalization
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