Introduction and Rapid Spread of SARS-CoV-2 Omicron Variant and Dynamics of BA.1 and BA.1.1 Sublineages, Finland, December 2021.

Multiple introductions of SARS-COV-2 Omicron variant BA.1 and BA.1.1. lineages to Finland were detected in early December 2021. Within 3 weeks, Omicron overtook Delta as the most common variant in the capital region. Sequence analysis demonstrated the emergence and spread through community transmission of a large cluster of BA.1.1 virus.

Haplotype information of large neuromuscular disease genes provided by linked-read sequencing has a potential to increase diagnostic yield.

Rare or novel missense variants in large genes such as TTN and NEB are frequent in the general population, which hampers the interpretation of putative disease-causing biallelic variants in patients with sporadic neuromuscular disorders. Often, when the first initial genetic analysis is performed, the reconstructed haplotype, i.e. phasing information of the variants is missing. Segregation analysis increases the diagnostic turnaround time and is not always possible if samples from family members are lacking. To overcome this difficulty, we investigated how well the linked-read technology succeeded to phase variants in these large genes, and whether it improved the identification of structural variants. Linked-read sequencing data of nemaline myopathy, distal myopathy, and proximal myopathy patients were analyzed for phasing, single nucleotide variants, and structural variants. Variant phasing was successful in the large muscle genes studied. The longest continuous phase blocks were gained using high-quality DNA samples with long DNA fragments. Homozygosity increased the number of phase blocks, especially in exome sequencing samples lacking intronic variation. In our cohort, linked-read sequencing added more information about the structural variation but did not lead to a molecular genetic diagnosis. The linked-read technology can support the clinical diagnosis of neuromuscular and other genetic disorders.

Individualized systems medicine strategy to tailor treatments for patients with chemorefractory acute myeloid leukemia.

UNLABELLED: We present an individualized systems medicine (ISM) approach to optimize cancer drug therapies one patient at a time. ISM is based on (i) molecular profiling and ex vivo drug sensitivity and resistance testing (DSRT) of patients' cancer cells to 187 oncology drugs, (ii) clinical implementation of therapies predicted to be effective, and (iii) studying consecutive samples from the treated patients to understand the basis of resistance. Here, application of ISM to 28 samples from patients with acute myeloid leukemia (AML) uncovered five major taxonomic drug-response subtypes based on DSRT profiles, some with distinct genomic features (e.g., MLL gene fusions in subgroup IV and FLT3-ITD mutations in subgroup V). Therapy based on DSRT resulted in several clinical responses. After progression under DSRT-guided therapies, AML cells displayed significant clonal evolution and novel genomic changes potentially explaining resistance, whereas ex vivo DSRT data showed resistance to the clinically applied drugs and new vulnerabilities to previously ineffective drugs. SIGNIFICANCE: Here, we demonstrate an ISM strategy to optimize safe and effective personalized cancer therapies for individual patients as well as to understand and predict disease evolution and the next line of therapy. This approach could facilitate systematic drug repositioning of approved targeted drugs as well as help to prioritize and de-risk emerging drugs for clinical testing.