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Minor histocompatibility antigens (mHAg) composed of peptides presented by HLA molecules can cause immune responses involved in graft-versus-host disease (GVHD) and graft-versus-leukemia effects after allogeneic hematopoietic cell transplantation (HCT). The current study was designed to identify individual graft-versus-host genomic mismatches associated with altered risks of acute or chronic GVHD or relapse after HCT between HLA-genotypically identical siblings. Our results demonstrate that in allogeneic HCT between a pair of HLA-identical siblings, a mHAg manifests as a set of peptides originating from annotated proteins and non-annotated open reading frames, which i) are encoded by a group of highly associated recipient genomic mismatches, ii) bind to HLA allotypes in the recipient, and iii) evoke a donor immune response. Attribution of the immune response and consequent clinical outcomes to individual peptide components within this set will likely differ from patient to patient according to their HLA types.

SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase the viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients; 388 inpatients (“cases”) and 295 outpatients (“controls”) from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes. To improve the analytic power, we accessed 7,137 viral sequences in Washington State to filter out viral single nucleotide variants (SNVs) that did not have significant expansions over the collection period. Applying this filter led to the identification of 53 SNVs that were statistically significant, of which 13 SNVs each had 3 or more variant copies in the discovery cohort. Correlating these selected SNVs with case/control status, eight SNVs were found to significantly associate with inpatient status (q-values−11) that appeared in April 2020, peaked in June, and persisted into January 2021. This association was replicated (OR=5.46, p-value=4.71*10−12) in an independent cohort of 964 COVID-19 patients (June 1, 2020 to March 31, 2021). The haplotype included a synonymous change N73N in endoRNase, and three non-synonymous changes coding residues R203K, R203S and G204R in the nucleocapsid protein. This discovery points to the potential functional role of the nucleocapsid protein in triggering “cytokine storms” and severe COVID-19 that led to hospitalization. The study further emphasizes a need for tracking and analyzing viral sequences in correlations with clinical status.

SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase the viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients; 388 inpatients (“cases”) and 295 outpatients (“controls”) from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes. To improve the analytic power, we accessed 7,137 viral sequences in Washington State to filter out viral single nucleotide variants (SNVs) that did not have significant expansions over the collection period. Applying this filter led to the identification of 53 SNVs that were statistically significant, of which 13 SNVs each had 3 or more variant copies in the discovery cohort. Correlating these selected SNVs with case/control status, eight SNVs were found to significantly associate with inpatient status (q-values

Background: SARS-CoV-2 is continuously evolving with the emergence of variants of interest (VOI) or with variants of concern (VOC). While Variants of High Consequence (VOHC) are well defined, no such variants have been formally documented. Here we propose an integrated strategy and application towards discovering VOHC. Methods: We utilized 7,137 viral sequences collected from COVID-19 cases in Washington State from January 19, 2020 to January 31, 2021, to identify genome-wide viral single nucleotide variants (SNVs). Utilizing a non-parametric regression model, we selected a subset of SNVs that had significant and substantial expansions over the collection period. Further, using unsupervised learning, we identified multiple SNVs forming haplotypes. To evaluate their clinical relevance, we assembled a discovery cohort of COVID-19 cases (388 inpatients and 295 outpatients) to identify SNVs and haplotypes associated with hospitalization status, a proxy for disease severity. A logistic regression model was used to assess associations of SNVs with hospitalization status in the discovery cohort. These results were validated on an independent cohort of 964 genome sequences derived from COVID-19 cases in Washington State from June 1, 2020 to March 31, 2021. Finding: The analysis of the 7,137 sequences led to identification of 107 SNVs that were statistically significant (false positive error rate q-value 0.10). Forty-one SNVs were considered urgent, because their SNV proportions persisted or expanded above 10% in January 2021, the last month of the current investigation period. Correlating with clinical data, eight SNVs were found to significantly associate with inpatient status (p-values