Gathering of pathogenicity evidence for novel variants. By Lewis Pang

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1 Gathering of pathogenicity evidence for novel variants By Lewis Pang

2 Novel variants A newly discovered, distinct genetic alteration Within our lab a variant is deemed novel if we haven t seen it before. In Exeter it is the task of the GTs to gather evidence to aid in determining the pathogenicity of novel variants. This is performed by checking if the variant has been identified and reported anywhere else in the world. Any information regarding other indicators of pathogenicity such as conservational, in silico, functional and population based data is also collated. Based on the evidence gathered by the GTs a scientist then classifies the variant according to the ACMG (American college of Medical Genetics and Genomics) guidelines. ACMG Scale Pathogenic Likely Pathogenic Uncertain Significance Likely Benign Benign

3 Novel evidence gathered The number of novel variants identified is rapidly increasing As the number of patients being tested by NGS (especially whole exome sequencing, 4x increase over last two years) continues to rise so does the number of variants we haven t seen before. In less than two years the number novel variants requiring evidence gathered each month has tripled.

4 How is evidence gathered? Anyone in the lab can request that evidence is gathered for a variant by filling details of the variant on an evidence to collect excel sheet. Each week a GT is assigned responsibility for checking the list and gathering the evidence for the variants. To prevent evidence being unnecessarily gathered an initial check of the variant on HGMD is performed to see if the variant has been previously reported as pathogenic.

5 How is evidence gathered? = A stepwise excel file GTs work their way through separate tabs within an excel file filling out all the fields where possible. The majority of the information is gathered from AlamutVisual a human variant interpretation software which allows the user to visualise regions of the genome and simulate specific variations.

6 Initial Summary An initial summary page is filled out containing the basic information including the patients ID and variant details as well as a summary output from Alamut.

7 Database search A number of data bases are searched to identify if the variant has been reported anywhere in the world. Excel macros and links within the spread sheet take you directly to your variant of interest within each data base. The fields are then filled in with any information found within each database: The databases used are collections of variants that relate to specific phenotypes with supporting case-based evidence such as: - Human Gene Mutation Database (HGMD) - ClinVar - Leiden Open Variation Database (LOVD) - In-house databases (starlims, MODY database, SFs KATP mutation database)

8 Database search The variant is also searched for in Google. A search text that can be generated within Alamut contains several possible ways of describing the variant to maximise the chance of retrieving a result. Eg.: "RET" ("2556C>G" "2556C->G" "2556C-->G" "2556C/G" "Ile852Met" "I852M" rs ) Population based databases such as ExAC and gnomad provide allele frequencies for the variant. If the allele frequency is greater than expected for the disorder this suggests that the variant is more likely to be benign. The frequencies are broken down into ethnic groups so that the patient can be compared to those of a similar ethnicity.

9 Conservation Conservation of the amino acid/nucleotide across species is examined using UCSC browser and the Alamut browser. A variant in a highly conserved region is more likely to be pathogenic as the region is likely to have an important biological function. Consurf scores are generated automatically within the excel sheet and provide a number from 1-9 on the level of conservation

10 In silico predictions In silico tools refer to computational models to predict biological outcomes 4 main in silico tools are used which are all housed within Alamut. - Align GVGD: freely available, web-based program that combines the biophysical characteristics of amino acids and protein multiple sequence alignments. Places missense variants in a class from SIFT: based on sequence homology and physical properties of amino acids. Places missense variants into two classes : Deleterious or Tolerated. - PolyPhen: based on the sequence, phylogenetic and structural information. Places variants in class ranging from Benign - Damaging These tools are soon to be replaced by Revel - a precalculated meta-analysis tool that provides a single numerical output from 0-1. Every missense change possible has a pre-calculated pathogenicity score.

11 Splicing Within Alamut a splicing tool predictor collates information from 5 different splicing predictors. The reference is seen on the top and the mutant on the bottom. Each bar represents that a particular tool predicts their to be splice site at that genomic position, with a particular score /confidence

12 ACMG classification After the evidence has all been gathered a scientist will then score the variant according to criteria set out in the ACMG guidelines. The final score will place the variant into a classification that is put into the interpretation section of the patients final report.

13 Reporting Novel Variants

14 Consistency of Variant Classification The purpose of adopting the ACMG classification system is to have consistency in variant interpretation in laboratories across the country. Exeter organises a monthly Train the Trainer event with representatives from each regional genetics laboratory. This allows labs to classify variants and discuss their classifications. The monthly Train the Trainer cases are also used locally to discuss between scientists, clinicians and counsellors. Scientists discuss all cases before they are reported at a weekly ACMG meeting, this is soon to be reduced to difficult cases only. The laboratory partakes in annual EQA variant classification, this is used to assess competency.

15 Managing the increasing workload More GTs trained on gathering evidence Adding evidence gathering to the GT weekly rota to assign responsibility and allow equal distribution Setting clear guidelines so that no unnecessary evidence is gathered is it present on HGMD? Is that type of variant always pathogenic/benign? A database of null variant classifications has been established in Exeter to try to determine if these are always pathogenic and hence do not require evidence gathered. Future developments: Automated evidence gathering tools such as Revel to replace several in silico tools. Pathogenicity cut-offs have to be agreed upon prior to implementation Command-line based tools that gather several pieces of evidence at once into one graph such as the PM1 plot. (GTs to attend APs command-line tutorial?)

16 Thanks for Listening! Any Questions?