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microbiomedataset A tidyverse-style framework for organizing and processing microbiome data

Semi-supervised Cooperative Learning for Multiomics Data Fusion

Pregnancy is a critical time that has long-term impacts on both maternal and fetal health. During pregnancy, the maternal metabolome undergoes dramatic systemic changes, although correlating longitudinal changes in maternal urine remain largely unexplored. We applied an LCMS-based untargeted metabolomics profiling approach to analyze 346 longitudinal maternal urine samples collected throughout pregnancy for 36 women from diverse ethnic backgrounds with differing clinical characteristics. We detected 20,314 metabolic peaks and annotated 875 metabolites. Altered metabolites include a broad panel of glucocorticoids, lipids, and amino acid derivatives, which revealed systematic pathway alterations during pregnancy. We also developed a machine-learning model to precisely predict gestational age (GA) at time of sampling using urine metabolites that provides a non-invasive method for pregnancy dating. This longitudinal maternal urine study demonstrates the clinical utility of using untargeted metabolomics in obstetric settings.

The determinants of severe COVID-19 in non-elderly adults are poorly understood, which limits opportunities for early intervention and treatment. Here we present novel machine learning frameworks for identifying common and rare disease-associated genetic variation, which outperform conventional approaches. By integrating single-cell multiomics profiling of human lungs to link genetic signals to cell-type-specific functions, we have discovered and validated over 1,000 risk genes underlying severe COVID-19 across 19 cell types. Identified risk genes are overexpressed in healthy lungs but relatively downregulated in severely diseased lungs. Genetic risk for severe COVID-19, within both common and rare variants, is particularly enriched in natural killer (NK) cells, which places these immune cells upstream in the pathogenesis of severe disease. Mendelian randomization indicates that failed NKG2D-mediated activation of NK cells leads to critical illness. Network analysis further links multiple pathways associated with NK cell activation, including type-I-interferon-mediated signalling, to severe COVID-19. Our rare variant model, PULSE, enables sensitive prediction of severe disease in non-elderly patients based on whole-exome sequencing; individualized predictions are accurate independent of age and sex, and are consistent across multiple populations and cohorts. Risk stratification based on exome sequencing has the potential to facilitate post-exposure prophylaxis in at-risk individuals, potentially based around augmentation of NK cell function. Overall, our study characterizes a comprehensive genetic landscape of COVID-19 severity and …

NGLY1 (N-glycanase 1) deficiency is a rare congenital recessive disorder caused by a mutation in the NGLY1 gene, which encodes the cytosol enzyme N-glycanase 1. The NGLY1 protein catalyzes the first step in protein deglycosylation, a process prerequisite for the cytosolic degradation of misfolded glycoproteins. By performing and combining metabolomics and proteomics profiles, we showed that NGLY1 deficiency induced the activation of immune response, disturbed lipid metabolism, biogenic amine synthesis and glutathione metabolism. The discovery was further validated by profiling of patient-derived induced pluripotent stem cells (iPSCs) and differentiated neural progenitor cells (NPCs), which serve as a personalized cellular model of the disease. This study provides new insights into the NGLY1 deficiency pathology and demonstrates that the upregulation of immune response and downregulation of lipid metabolism appear to be important molecular phenotypes of NGLY1 deficiency, together with the dysregulation of amino acid metabolism, biogenic amine synthesis and diverse signaling pathways, likely causing broad downstream syndromes. Collectively, such valuable multi-omics profiles identified broad molecular associations of potential pathological mechanisms during the onset of NGLY1 deficiency and suggested potential therapeutic targets for researchers and clinicians.