The 64th Korean Society of Medical Genetics and Genomics (KSMG) meeting was held at the Kim Koo Museum & Library on November 10, 2022. The meeting started off with a keynote presentation by Dr. Seong-Wook Lee from Dankook University, followed by two concurrent oral presentation sessions, award sessions for outstanding abstracts, another two concurrent sessions featuring ‘rasopathy’ and ‘single cell analysis in rare diseases’ and finally, a closing session ‘Beyond Conventional Genomics’. Throughout the meeting, the exhibitors including renowned pharmaceutical companies such as Novartis, Biogen, LG Chem, ISU Abxis and Takeda, a genetic testing company, GC genome and a next-generation sequencer manufacturer, Illumina showcased their products at their booths. Also, the posters were displayed next to the exhibit hall throughout the day for the attendees to visit.

Exhibition booths at the entrance of the conference hall

Exhibition booths at the entrance of the conference hall

3billion, Inc. also attended the meeting, presenting two posters and three oral presentations. Dr. Rin Khang from the Medical Genetics Team presented a poster titled “A case report of an Egyptian patient with a severe neurodevelopmental disorder and a novel biallelic loss-of-function variant in GOLGA2” and Researcher Yoo-Kyoung Cho from the Web Development Team presented a poster titled “SpliceVi: a visualization tool for predicting protein consequences based on SpliceAI data”. The three oral presentations were all in one session moderated by Dr. Hyun-Mee Ryu from CHA university. Starting with Researcher Ki-Sang Kwon from the Bioinformatics Team, the three presenters gave their talks in a row. I’ll briefly share their talks:

Variant reclassification based on the allele frequency information from exome sequencing data of 20,455 patients enriched with under-represented populations

Variant reclassification based on the allele frequency information from exome sequencing data of 20,455 patients enriched with under-represented populations by Ki-Sang Kwon

Researcher Ki-Sang Kwon from 3billion presented a study showing how variants can be reclassified from pathogenic/likely pathogenic/uncertain significance to likely benign/benign, purely based on the minor allele frequency information from 3billion’s internal dataset of 20,455 exome sequencing data. He showed that the reclassified variants were mainly found in individuals predicted to be east or south Asians, suggesting that even though a variant may look extremely rare in the public population databases such as gnomAD (Genome Aggregation Database), it may be common in specific ethnic group/population, and therefore it is important to put further efforts into sequencing more diverse populations.

Accelerating novel gene discovery utilizing a constraint-based method on exome sequencing data of 22,838 patients

Accelerating novel gene discovery utilizing a constraint-based method on exome sequencing data of 22,838 patients by Won-Chan Jeong

Researcher Won-Chan Jeong described a novel gene discovery pipeline he developed utilizing a constraint-based method. He introduced how the speed of novel gene discovery has accelerated with the advent of next-generation sequencing (NGS), how genotype to phenotype approach works for novel gene discovery and how novel gene discovery is a driving force of diagnosing exome/genome-negative patients when reanalyzing the existing data. He presented the variant filtering and sorting process to prioritize genes that are more likely to be novel gene candidates and shared a couple of real-case examples of novel genes discovered using the pipeline.

Explicable prioritization of genetic variants by integration of rule-based and deep learning algorithms for diagnosis of rare Mendelian disorders

Explicable prioritization of genetic variants by integration of rule-based and deep learning algorithms for diagnosis of rare Mendelian disorders by Dr. Kyoung-Yeul Lee

Dr. Kyoung-Yeul Lee presented how the AI model, 3CNet, can assist in predicting how likely a given variant may cause a rare disease. He described how his team was able to increase the performance of 3CNet by combining rule-based model and deep learning model. He also shared how 3CNet was applied to the test questions from the 6th Critical Assessment of Genome Interpretation (CAGI6) Challenge, a global AI genomic interpretation contest, and named as top-performing model.

Summarizing the meeting, one noticeable point was that more than half of the abstracts presented were related to diagnosing or treating rare diseases. This shows how studying rare diseases has become an important field in genetic and genomics clinical research in South Korea and it is exciting to see how such efforts will play a significant role in the diagnosis and treatment development for rare disease patients.

Lastly, I would like to mention that Dr. Kyoung-Yeul Lee from the artificial intelligence (AI) team won the best oral presentation award and researcher Yoo-Kyoung Cho from the bioinformatics (BI) team won the second best poster presentation award. The judges shared that the evaluation was based on the originality and applicability of the studies and how well the presenter communicated the study within the presentation time limit. Here are a couple of photos from the award ceremony and the poster session.

Dr. Kyoung-Yeul Lee receiving the best oral presentation award from Dr. Jong-Kwan Jun, the chairman of KSMG

Dr. Kyoung-Yeul Lee receiving the best oral presentation award from Dr. Jong-Kwan Jun, the chairman of KSMG

Dr. Go-Hun Seo, Chief Medical Officer of 3billion, receiving the second best poster award from Dr. Jong-Kwan Jun on behalf of researcher Yoo-Kyoung Cho

Dr. Go-Hun Seo, Chief Medical Officer of 3billion, receiving the second best poster award from Dr. Jong-Kwan Jun on behalf of researcher Yoo-Kyoung Cho

Researcher Won-Chan Jeong from the Bioinformatics Team (left) and Dr.Rin Khang from the Medical genetics Team (right) in front of the posters

Researcher Won-Chan Jeong from the Bioinformatics Team (left) and Dr.Rin Khang from the Medical genetics Team (right) in front of the posters

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