The drivers of critical coronavirus disease 2019 (COVID-19) remain unknown. Given major confounding factors such as age and comorbidities, true mediators of this condition have remained elusive. We ...used a multi-omics analysis combined with artificial intelligence in a young patient cohort where major comorbidities were excluded at the onset. The cohort included 47 “critical” (in the intensive care unit under mechanical ventilation) and 25 “non-critical” (in a non-critical care ward) patients with COVID-19 and 22 healthy individuals. The analyses included whole-genome sequencing, whole-blood RNA sequencing, plasma and blood mononuclear cell proteomics, cytokine profiling, and high-throughput immunophenotyping. An ensemble of machine learning, deep learning, quantum annealing, and structural causal modeling were used. Patients with critical COVID-19 were characterized by exacerbated inflammation, perturbed lymphoid and myeloid compartments, increased coagulation, and viral cell biology. Among differentially expressed genes, we observed up-regulation of the metalloprotease
. This gene signature was validated in a second independent cohort of 81 critical and 73 recovered patients with COVID-19 and was further confirmed at the transcriptional and protein level and by proteolytic activity. Ex vivo ADAM9 inhibition decreased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uptake and replication in human lung epithelial cells. In conclusion, within a young, otherwise healthy, cohort of individuals with COVID-19, we provide the landscape of biological perturbations in vivo where a unique gene signature differentiated critical from non-critical patients. We further identified
as a driver of disease severity and a candidate therapeutic target.
During the 1990s and the first several years of this century, microsatellites or short tandem repeats were the workhorse genetic markers for hypothesis-independent studies in human genetics, ...facilitating genome-wide linkage studies and allelic imbalance studies. However, the rise of higher throughput and cost-effective single-nucleotide polymorphism (SNP) platforms led to the era of the SNP for genome scans. Nevertheless, it is important to note that microsatellites remain highly informative and useful measures of genomic variation for linkage and association studies. Their continued advantage in complementing SNPs lies in their greater allelic diversity than biallelic SNPs as well as in their population history, in which single-step expansion or contraction of the tandem repeat on the background of ancestral SNP haplotypes can break up common haplotypes, leading to greater haplotype diversity within the linkage disequilibrium block of interest. In fact, microsatellites have starred in association studies leading to widely replicated discoveries of type 2 diabetes (TCF7L2) and prostate cancer genes (the 8q21 region). At the end of the day, it will be important to catalog all variation, including SNPs, microsatellites, copy number variations, and polymorphic inversions in human genetic studies. This article describes the utilities of microsatellites and experimental approaches in their use.
Chemical synthesis planning is a key aspect in many fields of chemistry, especially drug discovery. Recent implementations of machine learning and artificial intelligence techniques for ...retrosynthetic analysis have shown great potential to improve computational methods for synthesis planning. Herein, we present a multiscale, data-driven approach for retrosynthetic analysis with deep highway networks (DHN). We automatically extracted reaction rules (i.e., ways in which a molecule is produced) from a data set consisting of chemical reactions derived from U.S. patents. We performed the retrosynthetic reaction prediction task in two steps: first, we built a DHN model to predict which group of reactions (consisting of chemically similar reaction rules) was employed to produce a molecule. Once a reaction group was identified, a DHN trained on the subset of reactions within the identified reaction group, was employed to predict the transformation rule used to produce a molecule. To validate our approach, we predicted the first retrosynthetic reaction step for 40 approved drugs using our multiscale model and compared its predictive performance with a conventional model trained on all machine-extracted reaction rules employed as a control. Our multiscale approach showed a success rate of 82.9% at generating valid reactants from retrosynthetic reaction predictions. Comparatively, the control model trained on all machine-extracted reaction rules yielded a success rate of 58.5% on the validation set of 40 pharmaceutical molecules, indicating a significant statistical improvement with our approach to match known first synthetic reaction of the tested drugs in this study. While our multiscale approach was unable to outperform state-of-the-art rule-based systems curated by expert chemists, multiscale classification represents a marked enhancement in retrosynthetic analysis and can be easily adapted for use in a range of artificial intelligence strategies.
To define the role of ERK1/2 signaling in the quiescent endothelium, we induced endothelial
knockout in adult
mice. This resulted in a rapid onset of hypertension, a decrease in eNOS expression, and ...an increase in endothelin-1 plasma levels, with all mice dying within 5 wk. Immunostaining and endothelial fate mapping showed a robust increase in TGFβ signaling leading to widespread endothelial-to-mesenchymal transition (EndMT). Fibrosis affecting the cardiac conduction system was responsible for the universal lethality in these mice. Other findings included renal endotheliosis, loss of fenestrated endothelia in endocrine organs, and hemorrhages. An ensemble computational intelligence strategy, comprising deep learning and probabilistic programing of RNA-seq data, causally linked the loss of ERK1/2 in HUVECs in vitro to activation of TGFβ signaling, EndMT, suppression of eNOS, and induction of endothelin-1 expression. All in silico predictions were verified in vitro and in vivo. In summary, these data establish the key role played by ERK1/2 signaling in the maintenance of vascular normalcy.
The etiology of aortic aneurysms is poorly understood, but it is associated with atherosclerosis, hypercholesterolemia, and abnormal transforming growth factor β (TGF-β) signaling in smooth muscle. ...Here, we investigated the interactions between these different factors in aortic aneurysm development and identified a key role for smooth muscle cell (SMC) reprogramming into a mesenchymal stem cell (MSC)-like state. SMC-specific ablation of TGF-β signaling in Apoe
mice on a hypercholesterolemic diet led to development of aortic aneurysms exhibiting all the features of human disease, which was associated with transdifferentiation of a subset of contractile SMCs into an MSC-like intermediate state that generated osteoblasts, chondrocytes, adipocytes, and macrophages. This combination of medial SMC loss with marked increases in non-SMC aortic cell mass induced exuberant growth and dilation of the aorta, calcification and ossification of the aortic wall, and inflammation, resulting in aneurysm development.
We have previously reported suggestive linkage of type 2 diabetes mellitus to chromosome 10q. We genotyped 228 microsatellite markers in Icelandic individuals with type 2 diabetes and controls ...throughout a 10.5-Mb interval on 10q. A microsatellite, DG10S478, within intron 3 of the transcription factor 7-like 2 gene (TCF7L2; formerly TCF4) was associated with type 2 diabetes (P = 2.1 × 10−9). This was replicated in a Danish cohort (P = 4.8 × 10−3) and in a US cohort (P = 3.3 × 10−9). Compared with non-carriers, heterozygous and homozygous carriers of the at-risk alleles (38% and 7% of the population, respectively) have relative risks of 1.45 and 2.41. This corresponds to a population attributable risk of 21%. The TCF7L2 gene product is a high mobility group box-containing transcription factor previously implicated in blood glucose homeostasis. It is thought to act through regulation of proglucagon gene expression in enteroendocrine cells via the Wnt signaling pathway.
Common human diseases result from the interplay of many genes and environmental factors. Therefore, a more integrative biology approach is needed to unravel the complexity and causes of such ...diseases. To elucidate the complexity of common human diseases such as obesity, we have analysed the expression of 23,720 transcripts in large population-based blood and adipose tissue cohorts comprehensively assessed for various phenotypes, including traits related to clinical obesity. In contrast to the blood expression profiles, we observed a marked correlation between gene expression in adipose tissue and obesity-related traits. Genome-wide linkage and association mapping revealed a highly significant genetic component to gene expression traits, including a strong genetic effect of proximal (cis) signals, with 50% of the cis signals overlapping between the two tissues profiled. Here we demonstrate an extensive transcriptional network constructed from the human adipose data that exhibits significant overlap with similar network modules constructed from mouse adipose data. A core network module in humans and mice was identified that is enriched for genes involved in the inflammatory and immune response and has been found to be causally associated to obesity-related traits.
Bone mineral density influences the risk of osteoporosis later in life and is useful in the evaluation of the risk of fracture. We aimed to identify sequence variants associated with bone mineral ...density and fracture.
We performed a quantitative trait analysis of data from 5861 Icelandic subjects (the discovery set), testing for an association between 301,019 single-nucleotide polymorphisms (SNPs) and bone mineral density of the hip and lumbar spine. We then tested for an association between 74 SNPs (most of which were implicated in the discovery set) at 32 loci in replication sets of Icelandic, Danish, and Australian subjects (4165, 2269, and 1491 subjects, respectively).
Sequence variants in five genomic regions were significantly associated with bone mineral density in the discovery set and were confirmed in the replication sets (combined P values, 1.2x10(-7) to 2.0x10(-21)). Three regions are close to or within genes previously shown to be important to the biologic characteristics of bone: the receptor activator of nuclear factor-kappaB ligand gene (RANKL) (chromosomal location, 13q14), the osteoprotegerin gene (OPG) (8q24), and the estrogen receptor 1 gene (ESR1) (6q25). The two other regions are close to the zinc finger and BTB domain containing 40 gene (ZBTB40) (1p36) and the major histocompatibility complex region (6p21). The 1p36, 8q24, and 6p21 loci were also associated with osteoporotic fractures, as were loci at 18q21, close to the receptor activator of the nuclear factor-kappaB gene (RANK), and loci at 2p16 and 11p11.
We have discovered common sequence variants that are consistently associated with bone mineral density and with low-trauma fractures in three populations of European descent. Although these variants alone are not clinically useful in the prediction of risk to the individual person, they provide insight into the biochemical pathways underlying osteoporosis.
The global endemic of cardiovascular diseases calls for improved risk assessment and treatment. Here, we describe an association between myocardial infarction (MI) and a common sequence variant on ...chromosome 9p21. This study included a total of 4587 cases and 12,767 controls. The identified variant, adjacent to the tumor suppressor genes CDKN2A and CDKN2B, was associated with the disease with high significance. Approximately 21% of individuals in the population are homozygous for this variant, and their estimated risk of suffering myocardial infarction is 1.64 times as great as that of noncarriers. The corresponding risk is 2.02 times as great for early-onset cases. The population attributable risk is 21% for MI in general and 31% for early-onset cases.
Smooth muscle cell (SMC) proliferation has been thought to limit the progression of thoracic aortic aneurysm and dissection (TAAD) because loss of medial cells associates with advanced disease. We ...investigated effects of SMC proliferation in the aortic media by conditional disruption of Tsc1, which hyperactivates mTOR complex 1. Consequent SMC hyperplasia led to progressive medial degeneration and TAAD. In addition to diminished contractile and synthetic functions, fate-mapped SMCs displayed increased proteolysis, endocytosis, phagocytosis, and lysosomal clearance of extracellular matrix and apoptotic cells. SMCs acquired a limited repertoire of macrophage markers and functions via biogenesis of degradative organelles through an mTOR/β-catenin/MITF-dependent pathway, but were distinguishable from conventional macrophages by an absence of hematopoietic lineage markers and certain immune effectors even in the context of hyperlipidemia. Similar mTOR activation and induction of a degradative SMC phenotype in a model of mild TAAD due to Fbn1 mutation greatly worsened disease with near-uniform lethality. The finding of increased lysosomal markers in medial SMCs from clinical TAAD specimens with hyperplasia and matrix degradation further supports the concept that proliferation of degradative SMCs within the media causes aortic disease, thus identifying mTOR-dependent phenotypic modulation as a therapeutic target for combating TAAD.
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