Coding mutations in TTR gene cause a rare hereditary form of systemic amyloidosis, which has a complex genotype-phenotype correlation. We investigated the role of non-coding variants in regulating TTR gene expression and consequently amyloidosis symptoms. We evaluated the genotype-phenotype correlation considering the clinical information of 129 Italian patients with TTR amyloidosis. Then, we conducted a re-sequencing of TTR gene to investigate how non-coding variants affect TTR expression and, consequently, phenotypic presentation in carriers of amyloidogenic mutations. Polygenic scores for genetically determined TTR expression were constructed using data from our re-sequencing analysis and the GTEx (Genotype-Tissue Expression) project. We confirmed a strong phenotypic heterogeneity across coding mutations causing TTR amyloidosis. Considering the effects of non-coding variants on TTR expression, we identified three patient clusters with specific expression patterns associated with certain phenotypic presentations, including late onset, autonomic neurological involvement, and gastrointestinal symptoms. This study provides novel data regarding the role of non-coding variation and the gene expression profiles in patients affected by TTR amyloidosis, also putting forth an approach that could be used to investigate the mechanisms at the basis of the genotype-phenotype correlation of the disease.

Risk factors and long-term consequences of COVID-19 infection are unclear but can be investigated with large-scale genomic data. To distinguish correlation from causation, we performed in-silico analyses of three COVID-19 outcomes (N > 1,000,000). We show genetic correlation and putative causality with depressive symptoms, metformin use (genetic causality proportion (gĉp) with severe respiratory COVID-19 = 0.576, p = 1.07 × 10−5 and hospitalized COVID-19 = 0.713, p = 0.003), and alcohol drinking status (gĉp with severe respiratory COVID-19 = 0.633, p = 7.04 × 10−5 and hospitalized COVID-19 = 0.848, p = 4.13 × 10−13). COVID-19 risk loci associated with several hematologic biomarkers. Comprehensive findings inform genetic contributions to COVID-19 epidemiology, molecular mechanisms, and risk factors and potential long-term health effects of severe response to infection.

doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.

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