ClinVar Submission and Interpretation: How to Submit Variant Classifications and Use ClinVar Data for Clinical Decision-Making

By Dr. Zubair Khalid, DVM, MS, PhD · 2026-08-21

Key Takeaways

• Submitting all interpreted variants, including Variants of Uncertain Significance (VUS), is crucial for improving global variant representation and enabling future reclassification, particularly given the underrepresentation of African variants (under 2% of global submissions) which limits contextual interpretation.
• Adherence to the ACMG/AMP guidelines, augmented by disease-specific specifications from ClinGen Variant Curation Expert Panels (VCEPs), significantly enhances consistency and resolves discordant classifications, as demonstrated by the 70% resolution rate for previously ambiguous hearing loss variants.
• Multiplex Assay of Variant Effect (MAVE) data, when quantitatively validated, offers a powerful tool for refining clinical variant classifications, though ongoing challenges in standardization and dissemination necessitate continued collaboration between ClinVar and MaveDB.
• Programmatic access via the ClinVar API is recommended for targeted queries within automated interpretation pipelines, while the FTP site is optimal for large-scale analysis and full dataset downloads, allowing for integration into variant calling workflows.
• Population-specific frequency data, such as that from the African Genome Variation Database, provides critical sub-regional context that refines variant interpretations and improves classification accuracy by accounting for population-specific allele frequencies.
• Monitoring submitted variant records using ClinVar's "follow" feature is essential for passive tracking of new submissions or classification changes, thereby supporting timely reinterpretation decisions for VUS and conflicting assertions.

ClinVar is the National Center for Biotechnology Information (NCBI) database that aggregates human genetic variant classifications submitted by laboratories, research groups, and expert panels, and it serves as a shared reference for interpreting the clinical significance of genomic findings. For biology students, researchers, laboratory professionals, and life-science practitioners, the practical problem is twofold: knowing how to structure and submit variant interpretations correctly, and knowing how to retrieve and apply ClinVar data for clinical reporting and research without misreading the evidence behind each classification. This article walks through the submission process for single and multiple variants, explains how star ratings reflect review status, and provides concrete methods for using ClinVar's API and FTP resources to support variant interpretation workflows.

Scope and Reader Context

This guidance applies to laboratories and research groups that generate germline or somatic variant calls and need to deposit interpretations into ClinVar or use ClinVar records to support clinical decision-making. The intended readers are bioinformatics students, clinical laboratory scientists, genetic counselors, and researchers who work with variant calling pipelines and need a practical reference for the submission and retrieval side of variant interpretation. The content assumes familiarity with basic variant calling concepts such as read alignment, variant filtering, and annotation, but it does not require prior experience with ClinVar submission systems.

The scope covers the submission process for single variant records and batch submissions, the meaning and limitations of star ratings, the use of ClinVar's API and FTP for programmatic access, and the integration of ClinVar data into variant interpretation workflows. The article also addresses common failure patterns in submission and retrieval, the importance of expert panel specifications, and the role of functional data from multiplex assays in refining classifications. Clinical decision-making using ClinVar data requires understanding that a database entry is a snapshot of evidence at a point in time, and that classifications can change as new evidence accumulates.

At a Glance

The table below summarizes the key decisions a laboratory or researcher faces when working with ClinVar, the recommended approach, and the evidence basis for each decision.

ClinVar Database Structure and Data Model

ClinVar operates as a database of records that link a genetic variant to a clinical significance assertion, supporting evidence, and submitter information. The NCBI maintains ClinVar as part of its suite of data resources, which includes search systems, sequence resources, and analysis services that support genetic and genomic research [<a href="#ref-1">1</a>]. Understanding the data model is essential before making any submission, because the structure determines how your interpretation will be displayed, searched, and compared with other submissions.

A ClinVar record centers on the variant, which is described using a standardized notation that includes the genomic location, reference sequence, and alternate allele. Each record also includes the condition or phenotype being asserted, the clinical significance classification, the review status, and the evidence supporting the classification. The submission process requires that you provide these components in a structured format that ClinVar can validate and integrate.

The condition field requires a valid disease identifier. In a genetic counselor-led curation effort at the University of Cape Town, submitters identified gaps or inaccuracies in Monarch Disease Ontology (Mondo) identifiers for three variants and updated them, or created new Mondo disease entities to ensure gene-disease pairs were correctly represented [<a href="#ref-2">2</a>]. This practical detail matters because ClinVar submissions require valid Mondo identifiers, and an incorrect or missing identifier can delay submission or cause the record to be displayed incorrectly.

The variant description must follow the Human Genome Variation Society (HGVS) nomenclature or an equivalent standardized format. The NCBI provides validation tools that check whether the variant description is consistent with the reference sequence you provide. Submissions that fail validation are returned to the submitter for correction, which is a common source of delay in the submission process.

Preparing Variant Interpretations for Submission

Before you begin the submission process, you need to have completed variant interpretation using a recognized framework. The American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines provide the standard framework for classifying variants as pathogenic, likely pathogenic, uncertain significance, likely benign, or benign. The ClinGen Variant Curation Expert Panels (VCEPs) provide disease-specific rules that refine the general ACMG/AMP guidelines for particular genes and conditions [<a href="#ref-3">3</a>].

The evidence for variant classification comes from multiple data types. For BRCA1 and BRCA2 variants, the ENIGMA consortium developed a multifactorial likelihood model that incorporates clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information [<a href="#ref-4">4</a>]. This model was applied to 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants, of which 447 were classified as likely benign or benign and 94 as likely pathogenic or pathogenic [<a href="#ref-4">4</a>]. The study also found that 248 classifications were new or considerably altered relative to ClinVar submissions, demonstrating that ClinVar records can change substantially as more sophisticated analysis methods are applied [<a href="#ref-4">4</a>].

For laboratories preparing submissions, the practical implication is that your interpretation must be based on a documented evidence review that you can reproduce and defend. The submission form requires you to provide the evidence codes or a summary of the evidence supporting your classification. If you are submitting a variant that has been classified using a VCEP specification, you should note that in the submission so that the review status reflects the expert panel involvement.

The classification process should also incorporate population frequency data. The University of Cape Town curation effort used African Genome Variation Database frequencies to guide variant classification, which provided sub-regional context and highlighted population differences that refined interpretations [<a href="#ref-2">2</a>]. This approach matters because a variant that is common in one population may be rare or absent in another, and population-matched frequency data can provide supporting evidence for pathogenicity or benignity.

The ClinVar Submission Process for Single Variants

The single variant submission process is appropriate when you have a small number of variants to submit, such as a few clinically significant findings from a diagnostic case or a research study with limited variants to report. The process begins with creating an account in the NCBI submission system, which requires registration and verification of your affiliation.

The submission form for a single variant requires the following components:

• Submitter information, including the organization name and contact details
• Variant description in HGVS notation or genomic coordinates
• Reference sequence accession and version
• Condition or phenotype, using a valid Mondo identifier
• Clinical significance classification
• Review status, indicating whether the classification was made by a single submitter, multiple submitters, or an expert panel
• Evidence summary or evidence codes supporting the classification
• Citation information for published evidence, if applicable

The NCBI submission system validates the variant description against the reference sequence and checks that the condition identifier is valid. If the validation fails, you will receive an error message that identifies the problem, and you must correct the submission before it can be accepted.

One practical consideration is that the review status you select affects the star rating displayed on the record. A submission with a single submitter and no expert panel review receives a lower star rating than a submission that has been reviewed by multiple submitters or an expert panel. The star rating is not a measure of the quality of your interpretation but rather a measure of the level of review that has been applied.

After submission, the record enters a processing queue. The NCBI staff review the submission for completeness and consistency, and they may contact you if there are questions about the data. Once the record is accepted, it becomes visible in ClinVar and is assigned a submission ID that you can use for tracking and follow-up.

Batch Submission for Multiple Variants

When you have many variants to submit, such as results from a targeted next-generation sequencing panel or a whole exome study, the single variant submission process becomes impractical. ClinVar provides a batch submission process that allows you to upload a spreadsheet or tab-delimited file containing multiple variant records.

The batch submission process requires that you prepare a file with the same data fields as the single variant submission, but formatted as a table with one row per variant. The NCBI provides templates and validation tools that check the file format and flag errors before you submit. Common errors in batch submissions include incorrect HGVS notation, missing reference sequence accessions, invalid condition identifiers, and inconsistent clinical significance terms.

A targeted next-generation sequencing study of 191 patients with adrenal incidentalomas used a custom panel targeting 21 genes potentially involved in adrenal tumorigenesis, and the bioinformatic analysis was followed by variant classification using the ClinVar and VarSome databases in accordance with ACMG guidelines [<a href="#ref-5">5</a>]. The study identified germline variants in 12 of 191 patients (6.3%), affecting 7 different genes, and most of the detected variants were classified as variants of uncertain significance [<a href="#ref-5">5</a>]. This example illustrates the scale of variant interpretation that a research laboratory may need to submit, and it highlights the importance of an efficient batch submission process.

For batch submissions, you should validate your file carefully before uploading. The NCBI provides a validation tool that checks the file and returns a report of errors and warnings. You should correct all errors before submission, because errors in the file can cause the entire batch to be rejected or can result in individual records being held for manual review.

The batch submission process also requires that you specify the submission format, which can be either the ClinVar submission spreadsheet format or the Variant Call Format (VCF) with additional annotation columns. The VCF format is convenient if you are submitting variants that were called using a standard variant calling pipeline, because you can add the interpretation columns to your existing VCF file.

Star Ratings and Review Status

The star rating displayed on a ClinVar record indicates the level of review that the classification has received. The rating system is designed to help users understand how much confidence to place in a particular classification, and it is based on the number of submitters and the involvement of expert panels.

A record with zero stars indicates that the classification has not been reviewed by an expert panel and has only a single submitter, or that the submitter has not provided sufficient evidence for review. A record with one star indicates that the classification has been submitted by a single submitter with the assertion criteria provided. A record with two stars indicates that the classification has been submitted by multiple submitters with consistent interpretations, or that the classification has been reviewed by an expert panel. A record with three stars indicates that the classification has been reviewed by a ClinGen Variant Curation Expert Panel.

The star rating is an important consideration when using ClinVar data for clinical decision-making. A classification with a higher star rating has undergone more rigorous review and is generally more reliable than a classification with a lower star rating. However, the absence of a high star rating does not necessarily mean that the classification is incorrect. It may simply mean that the variant has not yet been reviewed by multiple submitters or an expert panel.

The Hearing Loss VCEP study provides a concrete example of how expert panel review can change the star rating and resolve discordant interpretations. A total of 157 variants across nine hearing loss genes, previously submitted to ClinVar, were curated by the Hearing Loss VCEP [<a href="#ref-3">3</a>]. Before expert curation, 75% of the variants had single or multiple VUS submissions or had conflicting interpretations in ClinVar, with 17 variants having VUS submissions and 100 variants having conflicting interpretations [<a href="#ref-3">3</a>]. After applying the hearing loss-specific ACMG/AMP guidelines, 24% of VUS and 69% of discordant variants were resolved into benign, likely benign, likely pathogenic, or pathogenic classifications, and overall 70% of the variants had unambiguous classifications [<a href="#ref-3">3</a>].

This study demonstrates that expert panel review can substantially improve the consistency of variant interpretation and resolve conflicts that arise when different laboratories apply the general ACMG/AMP guidelines without disease-specific specifications. For laboratories submitting variants, the practical implication is that you should check whether a ClinGen VCEP exists for the gene or condition you are interpreting, and if so, you should apply the disease-specific guidelines and note this in your submission.

Using ClinVar Data for Variant Interpretation

ClinVar data serves as a reference for interpreting variants identified in your own sequencing data. When you identify a variant in a patient sample or research sample, you can query ClinVar to determine whether the variant has been previously reported and what clinical significance has been asserted.

The NCBI provides multiple ways to access ClinVar data. The website search interface allows you to query by variant, gene, condition, or submitter. The API provides programmatic access for automated queries, and the FTP site provides full dataset downloads for large-scale analysis [<a href="#ref-1">1</a>]. The choice of access method depends on your use case.

For clinical reporting, the website search interface is often sufficient. You can search for a variant by its genomic coordinates or HGVS notation, and the search results will show the clinical significance assertions, review status, and supporting evidence. You should check all submissions for the variant, beyond the most recent one, because different submitters may have reached different conclusions.

For research applications, the API and FTP access are more appropriate. The API allows you to query ClinVar programmatically, which is useful for integrating ClinVar data into your variant calling or annotation pipeline. The FTP site provides the full ClinVar dataset in XML or VCF format, which you can download and use for local analysis.

A study of germline variants in adrenal incidentalomas used ClinVar and VarSome databases for variant classification in accordance with ACMG guidelines [<a href="#ref-5">5</a>]. The study found that most of the detected variants were classified as variants of uncertain significance, and no variants were classified as clearly pathogenic [<a href="#ref-5">5</a>]. This finding illustrates a common situation in clinical genomics: many variants identified in sequencing studies are VUS, and ClinVar data may not provide sufficient evidence to resolve their clinical significance.

The practical implication is that ClinVar should be used as one component of a comprehensive variant interpretation workflow, not as the sole source of truth. You should combine ClinVar data with population frequency data, functional evidence, segregation data, and other evidence types to reach a classification.

Accessing ClinVar Data Through the API

The ClinVar API provides programmatic access to variant records, submission data, and supporting evidence. The API is useful for laboratories that need to query ClinVar as part of an automated variant interpretation pipeline, and for researchers who need to retrieve data for large-scale analysis.

The API supports queries by variant identifier, genomic location, gene symbol, condition, and submitter. The API returns data in JSON or XML format, which you can parse and integrate into your analysis workflow. The NCBI provides documentation for the API, including examples of common queries and response formats [<a href="#ref-1">1</a>].

A practical use case for the API is checking whether a variant identified in your sequencing data has been previously submitted to ClinVar. You can write a script that queries the API for each variant in your variant call format (VCF) file and retrieves the clinical significance assertions. This approach allows you to annotate your variant calls with ClinVar data automatically, which is more efficient than manually searching the website for each variant.

The API also allows you to retrieve the full evidence record for a variant, including the submitter assertions, review status, and supporting citations. This information is useful for understanding why a particular classification was made and for assessing whether the classification is consistent with your own interpretation.

When using the API, you should be aware of rate limits and usage policies. The NCBI requires that API users register for an API key and comply with the usage guidelines. Excessive API usage can result in temporary suspension of access, so you should design your queries to be efficient and to minimize the number of requests.

Accessing ClinVar Data Through FTP

The ClinVar FTP site provides the full dataset in several formats, including XML, VCF, and tab-delimited text files. The FTP site is appropriate for users who need to download the entire dataset for local analysis, such as building a local database of variant classifications or performing large-scale comparisons.

The XML format provides the most detailed information, including the full evidence record for each variant. The VCF format provides variant calls with clinical significance annotations, which is convenient for users who work with VCF files in their variant calling pipelines. The tab-delimited text files provide a simplified view of the data, which is useful for quick lookups and for loading into spreadsheet applications.

The FTP site also provides summary files that list the clinical significance assertions for each variant, along with the review status and submitter information. These summary files are useful for getting an overview of the data without downloading the full XML files.

When downloading the full dataset, you should be aware of the file sizes, which can be large. The XML files for the full ClinVar dataset are several gigabytes in size, and the VCF files are also large. You should have sufficient storage space and bandwidth to handle the download, and you should consider using a download manager or a script that can resume interrupted downloads.

The FTP site is updated regularly, so you should check the update schedule and download the latest version of the data when you need current information. The NCBI provides release notes that describe the changes in each update, including new submissions, revised classifications, and corrections to existing records.

Integrating ClinVar Data into Variant Calling Workflows

Variant calling workflows generate lists of candidate variants that require interpretation before they can be reported clinically. The integration of ClinVar data into these workflows is a critical step that can improve the efficiency and accuracy of variant interpretation.

The variant calling workflow typically includes the following steps: read alignment, variant calling, variant filtering, and variant annotation. ClinVar data is most commonly integrated at the annotation step, where each variant is annotated with its clinical significance assertions from ClinVar.

For germline variant calling, the workflow processes DNA sequencing data from a patient sample and identifies variants that differ from the reference genome. The variant filtering step removes low-quality calls and common polymorphisms, and the annotation step adds information about the functional impact and clinical significance of each variant.

For somatic variant calling, the workflow processes DNA sequencing data from a tumor sample and identifies variants that are present in the tumor but not in the normal tissue. Somatic variant calling requires additional filtering steps to account for tumor purity, copy number alterations, and clonal heterogeneity.

The integration of ClinVar data into these workflows requires that you have a method for querying ClinVar for each variant in your call set. The API approach is suitable for small call sets, while the FTP download approach is more efficient for large call sets or for workflows that need to run offline.

A practical approach is to download the ClinVar VCF file from the FTP site and use it as an annotation resource in your variant calling pipeline. Many variant annotation tools support the use of custom annotation files, and you can configure your pipeline to add ClinVar annotations to each variant call.

The Galaxy Training Network provides accessible workflow training and analysis tutorials that cover variant calling and annotation, including the use of public databases for variant interpretation [<a href="#ref-6">6</a>]. The nf-core documentation describes community pipeline standards for reproducible workflow configuration, which is relevant for laboratories that use Nextflow pipelines for variant calling [<a href="#ref-7">7</a>]. The Bioconductor project provides packages and workflows for reproducible genomic analysis, including packages for variant annotation and interpretation [<a href="#ref-8">8</a>].

Quality Controls and Validation for ClinVar Submissions

The quality of ClinVar submissions depends on the accuracy of the variant description, the validity of the condition identifier, and the evidence supporting the clinical significance assertion. The NCBI provides validation tools that check these components, but submitters should also perform their own quality controls before submission.

The first quality control is verifying the variant description. The variant must be described using standard nomenclature, and the description must be consistent with the reference sequence. You should verify that the reference sequence accession and version are correct, and that the genomic coordinates or HGVS notation accurately describe the variant.

The second quality control is verifying the condition identifier. The condition must be represented by a valid Mondo identifier, and the identifier must correspond to the condition you are asserting. The University of Cape Town curation effort identified gaps or inaccuracies in Mondo identifiers for three variants and updated them, or created new Mondo disease entities to ensure gene-disease pairs were correctly represented [<a href="#ref-2">2</a>]. This example illustrates that condition identifiers can be a source of error in submissions, and that submitters should verify the identifier before submission.

The third quality control is verifying the evidence supporting the classification. The evidence must be documented and reproducible, and the classification must be consistent with the evidence. If you are using ACMG/AMP guidelines, you should document the evidence codes and the rationale for the classification.

The fourth quality control is verifying the review status. The review status you select must accurately reflect the level of review that the classification has received. If the classification has been reviewed by an expert panel, you should select the appropriate review status and provide the panel name.

The EMBL-EBI Training program provides bioinformatics learning pathways and data-resource training that cover quality control and validation in genomic analysis [<a href="#ref-9">9</a>]. The Carpentries lessons provide foundational computing and data skills that are relevant for implementing quality control workflows [<a href="#ref-10">10</a>].

Common Failure Patterns in ClinVar Submission

Several common failure patterns occur in ClinVar submission, and understanding these patterns can help you avoid delays and errors in the submission process.

The first failure pattern is incorrect variant description. This includes errors in HGVS notation, incorrect reference sequence accessions, and inconsistencies between the variant description and the reference sequence. These errors are typically detected by the NCBI validation tools, and the submission is returned to the submitter for correction.

The second failure pattern is invalid condition identifiers. This includes using a condition name that does not have a corresponding Mondo identifier, using an outdated identifier, or using an identifier that does not match the condition being asserted. The University of Cape Town curation effort encountered this issue and resolved it by updating or creating Mondo disease entities [<a href="#ref-2">2</a>].

The third failure pattern is incomplete evidence documentation. Submissions that do not provide sufficient evidence to support the classification may be returned for additional information, or the classification may be displayed with a lower review status.

The fourth failure pattern is inconsistent clinical significance terms. The clinical significance must be expressed using the standard terms, and the terms must be consistent with the evidence. For example, a variant cannot be classified as pathogenic if the evidence only supports a VUS classification.

The fifth failure pattern is duplicate submissions. If a variant has already been submitted by another laboratory, your submission will be displayed as an additional assertion for the same variant. This is not an error, but it can create conflicting interpretations if your classification differs from the existing submissions.

The sixth failure pattern is submission of variants without clinical significance. ClinVar is designed for variants that have been interpreted, and submissions of variants without a clinical significance assertion may be rejected or displayed with a limited record.

Limitations of ClinVar Data for Clinical Decision-Making

ClinVar data has several limitations that must be considered when using it for clinical decision-making. The most important limitation is that ClinVar records are snapshots of evidence at a point in time, and classifications can change as new evidence accumulates.

The ENIGMA study of BRCA1 and BRCA2 variants found that 248 classifications were new or considerably altered relative to ClinVar submissions when the multifactorial likelihood model was applied [<a href="#ref-4">4</a>]. This finding demonstrates that ClinVar classifications can change substantially when more sophisticated analysis methods are applied, and that a classification that is current today may be revised in the future.

Another limitation is the underrepresentation of certain populations in ClinVar. African genetic variants comprise under 2% of global ClinVar submissions, which limits the visibility, contextual interpretation, and re-evaluation of African genetic variation [<a href="#ref-2">2</a>]. This underrepresentation means that variants common in African populations may have limited ClinVar data, and interpretations based on data from other populations may not be directly applicable.

A third limitation is the predominance of variants of uncertain significance. The adrenal incidentaloma study found that most germline variants identified in the study were classified as VUS, and no variants were classified as clearly pathogenic [<a href="#ref-5">5</a>]. This finding is consistent with the broader experience in clinical genomics, where many variants lack sufficient evidence for a definitive classification.

A fourth limitation is the potential for conflicting interpretations. The Hearing Loss VCEP study found that 100 of 157 variants had conflicting interpretations in ClinVar before expert curation [<a href="#ref-3">3</a>]. Conflicting interpretations can arise when different laboratories apply the ACMG/AMP guidelines differently or when they have access to different evidence.

A fifth limitation is the variable quality of submissions. ClinVar accepts submissions from any registered submitter, and the quality of the evidence and the accuracy of the classification can vary. The star rating provides some indication of the level of review, but it does not guarantee the accuracy of the classification.

Functional Evidence and Multiplex Assays in Variant Classification

Multiplex assays of variant effect (MAVEs) represent an emerging source of functional evidence that can improve variant classification. MAVEs quantify the functional impact of many thousands of genomic variants in a single experiment, and the functional evidence they generate has the potential to empower more accurate clinical variant classification [<a href="#ref-11">11</a>].

The clinical application of MAVE data faces several challenges, including quantitative validation, variant truth-sets, platforms and standards for dissemination of MAVE data [<a href="#ref-11">11</a>]. A workshop held in July 2023 brought together 44 key scientific and clinical stakeholders to consider these challenges, and the outcomes included the development of focused workshops to develop consensus recommendations, the creation of a MAVE evaluation working group, and collaboration of ClinVar and MaveDB to enact software changes that support enhanced functional data submission [<a href="#ref-11">11</a>].

For laboratories and researchers, the practical implication is that MAVE data should be incorporated into variant classification workflows when available, but the data should be validated and interpreted with caution. The ENIGMA study found that altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity, and that variant absence in population datasets provided supporting evidence for variant pathogenicity [<a href="#ref-4">4</a>]. These findings support the use of functional evidence in variant classification, but they also emphasize the need for gene-specific calibration of evidence types.

The Bioconductor project provides packages and workflows for reproducible genomic analysis, including packages that may support the analysis of functional assay data [<a href="#ref-8">8</a>]. The nf-core documentation describes community pipeline standards that may be relevant for incorporating functional data into variant interpretation pipelines [<a href="#ref-7">7</a>].

Records and Measurements for Submission Tracking

Maintaining records of your ClinVar submissions is essential for tracking the status of your submissions, monitoring changes to your records, and supporting re-evaluation of variant classifications. The University of Cape Town curation effort maintained a structured follow-up of variant records using ClinVar's follow feature, which enabled passive monitoring of new submissions or classification changes [<a href="#ref-2">2</a>].

The follow feature allows you to receive notifications when a variant record is updated, such as when a new submission is added or when a classification is changed. This feature is useful for monitoring variants that you have submitted, particularly variants of uncertain significance or variants with conflicting assertions.

You should maintain the following records for each submission:

• Submission ID and date
• Variant description and reference sequence
• Condition and Mondo identifier
• Clinical significance classification and review status
• Evidence codes and supporting documentation
• Follow-up status and any classification changes

These records support the re-evaluation of variant classifications when new evidence becomes available. The University of Cape Town curation effort evaluated whether reinterpretation or resolution of variants of uncertain significance or those with conflicting assertions were warranted based on new submissions or classification changes [<a href="#ref-2">2</a>].

Professional Escalation Criteria

There are situations where a variant interpretation or a ClinVar submission issue requires escalation to a more experienced professional or to an expert panel. The following criteria indicate when escalation is appropriate.

Escalate to a clinical geneticist or genetic counselor when a variant classification has direct implications for patient management, particularly when the classification is pathogenic or likely pathogenic and the patient has not received genetic counseling. The adrenal incidentaloma study found that the detection of potentially pathogenic variants in patients with adrenal masses may have implications for clinical management, although the findings did not support widespread germline testing in routine clinical management [<a href="#ref-5">5</a>].

Escalate to a ClinGen Variant Curation Expert Panel when a variant has conflicting interpretations in ClinVar and the gene or condition has a VCEP. The Hearing Loss VCEP study demonstrated that expert panel review can resolve discordant interpretations, with 69% of discordant variants resolved into unambiguous classifications [<a href="#ref-3">3</a>].

Escalate to a bioinformatics specialist when you encounter technical issues with the ClinVar API or FTP access, or when you need to integrate ClinVar data into a complex variant calling pipeline. The NCBI provides documentation and support for the API and FTP services [<a href="#ref-1">1</a>].

Escalate to a laboratory director or clinical consultant when a variant classification has been changed based on new evidence, and the change affects previously reported results. The ENIGMA study found that 248 classifications were new or considerably altered relative to ClinVar submissions, demonstrating that classification changes are common and can have clinical implications [<a href="#ref-4">4</a>].

Safety and Regulatory Context

ClinVar submissions and the use of ClinVar data for clinical decision-making operate within a regulatory context that varies by jurisdiction. In the United States, clinical laboratories that report variant interpretations are regulated under the Clinical Laboratory Improvement Amendments (CLIA), and the reporting of genetic variants must comply with applicable regulations.

The use of ClinVar data for clinical decision-making requires that you understand the limitations of the data and that you do not rely solely on ClinVar classifications for patient management decisions. The adrenal incidentaloma study found that the clinical significance of germline variants remains unclear due to the predominance of VUS, and the findings did not support widespread germline testing in routine clinical management [<a href="#ref-5">5</a>].

The ENIGMA study emphasized the need for gene-specific calibration of evidence types used for variant classification [<a href="#ref-4">4</a>]. This finding has implications for the regulatory context, because it suggests that a one-size-fits-all approach to variant classification may not be appropriate, and that gene-specific guidelines may be needed.

The workshop on clinical application of MAVE data identified the need for consensus recommendations and standards for the dissemination of functional data [<a href="#ref-11">11</a>]. This work has regulatory implications, because the use of MAVE data in clinical variant classification will require validation and standardization.

Frequently Asked Questions

What is the difference between a single variant submission and a batch submission in ClinVar?

A single variant submission is used when you have a small number of variants to submit, and it involves completing an online form for each variant. A batch submission is used when you have many variants to submit, and it involves uploading a spreadsheet or tab-delimited file containing multiple variant records. The batch submission process requires that you prepare the file in a specific format and validate it before uploading.

How do star ratings on ClinVar records affect clinical decision-making?

Star ratings indicate the level of review that a classification has received. A higher star rating means that the classification has been reviewed by multiple submitters or an expert panel, which generally increases confidence in the classification. However, a lower star rating does not necessarily mean that the classification is incorrect, and you should review the evidence supporting the classification before making clinical decisions.

What is a Mondo identifier and why is it required for ClinVar submission?

A Mondo identifier is a standardized identifier for a disease or condition, maintained by the Monarch Disease Ontology. ClinVar requires a valid Mondo identifier for the condition field in each submission. The University of Cape Town curation effort identified gaps or inaccuracies in Mondo identifiers for three variants and updated them, or created new Mondo disease entities to ensure gene-disease pairs were correctly represented [<a href="#ref-2">2</a>].

How can I use the ClinVar API to retrieve variant data for interpretation?

The ClinVar API provides programmatic access to variant records, submission data, and supporting evidence. You can query the API by variant identifier, genomic location, gene symbol, condition, or submitter, and the API returns data in JSON or XML format. The API is useful for integrating ClinVar data into automated variant interpretation pipelines.

What is the difference between the ClinVar API and the FTP site?

The ClinVar API provides programmatic access to individual variant records and supports targeted queries. The FTP site provides the full ClinVar dataset for download, which is appropriate for large-scale analysis or for building a local database. The choice depends on whether you need to query individual records or analyze the entire dataset.

How do disease-specific ACMG/AMP guidelines improve variant interpretation?

Disease-specific ACMG/AMP guidelines from ClinGen Variant Curation Expert Panels provide rules that are tailored to specific genes and conditions. The Hearing Loss VCEP study found that applying the hearing loss-specific guidelines resolved 70% of previously discordant variants into unambiguous classifications [<a href="#ref-3">3</a>]. Disease-specific guidelines improve consistency because they account for gene-specific evidence types and thresholds.

What should I do if a variant I submitted to ClinVar has conflicting interpretations?

If a variant you submitted has conflicting interpretations, you should review the evidence supporting the other submissions and determine whether your classification should be revised. You should also consider escalating the variant to a ClinGen Variant Curation Expert Panel if one exists for the gene or condition. The Hearing Loss VCEP study demonstrated that expert panel review can resolve conflicting interpretations [<a href="#ref-3">3</a>].

How can I monitor changes to my ClinVar submissions?

ClinVar provides a follow feature that allows you to receive notifications when a variant record is updated. The University of Cape Town curation effort used this feature for passive monitoring of new submissions or classification changes, which supported decisions about whether reinterpretation or resolution of variants of uncertain significance or those with conflicting assertions were warranted [<a href="#ref-2">2</a>].

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• How to Set Hard Filters for Germline Variant Calling: A Practical Guide to GATK Best Practices

References and Further Reading

This article is educational and does not replace validated analysis plans, institutional policy, clinical interpretation, or specialist review.