Cell-Free DNA Tissue Damage Mapping in Transplant Patients Infected with COVID-19

Purpose

Patients with COVID-19 show variable clinical course; transplant patients often show worse outcomes. The effect of COVID-19 on the allograft and the sources of tissue injury that contribute to such poor outcomes are poorly defined. This study leverages cell-free DNA (cfDNA) to measure allograft injury as donor-derived cfDNA (ddcfDNA) and injury from different tissue types using tissue-specific DNA methylomic signatures.

Methods

14 consecutive COVID-19 transplant patients (8 Kidney, 3 Lung, 1 Heart, 1 Liver, and one multi-organ transplant patients) and 30 healthy controls were included. Plasma nuclear cfDNA (ncfDNA) and mitochondrial cfDNA (mtcfDNA) level were measured via digital droplet PCR, and ddcfDNA using AlloSure (CareDx). cfDNA whole-genome bisulfite sequencing was performed to identify cfDNA tissues of origin leveraging tissue specific DNA methylomes and deconvolution algorithm.

Results

75% of the COVID-19 transplant patients showed high ddcfDNA level compared to published quiescent values, including all lung, 50% of the kidney, liver and multi-organ transplant patients (8.5, 4.4, 30 and 16-X fold change, respectively). Total ncfDNA and mtcfDNA were 15X and 310X higher in COVID-19 transplant patients compared to controls, respectively; < 0.0001.The predominant tissues contributing to cfDNA were hematopoietic cells (80%) (Figure). More importantly, COVID-19 transplant patients showed 10 to 100 fold higher tissue specific cfDNA derived from monocyte, neutrophil, erythroblast, vascular endothelium, adipocyte, hepatocyte, kidney, heart and lung compared to controls. Analysis comparing cfDNA in transplant and non-transplant COVID-19 patients is on-going.

Conclusion

The allograft undergoes significant injury following COVID-19. Further, cfDNA from multiple tissue types is significantly higher in COVID-19 transplant patients. Future studies in a larger cohorts of transplant and non-transplant patients are needed to elucidate why transplant patients show worse COVID-19 outcomes.

Genome-wide association of mood-incongruent psychotic bipolar disorder

Mood-incongruent psychotic features (MICP) are familial symptoms of bipolar disorder (BP) that also occur in schizophrenia (SZ), and may represent manifestations of shared etiology between the major psychoses. In this study we have analyzed three large samples of BP with imputed genome-wide association data and have performed a meta-analysis of 2196 cases with MICP and 8148 controls. We found several regions with suggestive evidence of association (P<10(-6)), although no marker met genome-wide significance criteria. The top associations were on chromosomes: 6q14.2 within the PRSS35/SNAP91 gene complex (rs1171113, P=9.67 × 10(-8)); 3p22.2 downstream of TRANK/LBA1 (rs9834970, P=9.71 × 10(-8)); and 14q24.2 in an intron of NUMB (rs2333194, P=7.03 × 10(-7)). These associations were present in all three samples, and both rs1171113 and rs2333194 were found to be overrepresented in an analysis of MICP cases compared with all other BP cases. To test the relationship of MICP with SZ, we performed polygenic analysis using the Psychiatric GWAS Consortium SZ results and found evidence of association between SZ polygenes and the presence of MICP in BP cases (meta-analysis P=0.003). In summary, our analysis of the MICP phenotype in BP has provided suggestive evidence for association of common variants in several genes expressed in the nervous system. The results of our polygenic analysis provides support for a modest degree of genetic overlap between BP with MICP and SZ, highlighting that phenotypic correlations across syndromes may be due to the influence of polygenic risk factors.