Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

A systematic review of long-term outcomes in ADHD: global publication trends

There is increased global recognition of attention deficit hyperactivity disorder (ADHD) as a serious medical condition with long-term consequences. Although originally conceived of as a childhood disorder, ADHD is being increasingly recognized in adults. Individual geographic regions may have specific interests and objectives for the study of ADHD. A systematic review of long-term outcomes (LTOs) in ADHD was conducted to evaluate research on ADHD LTOs on a global scale. Studies that were at least two years in duration were examined. We identified nine outcomes of interest and classified studies by specific geographical regions, age groups studied and study design by region and over time. Published studies of LTOs in ADHD have increased in all geographical regions over the past three decades, with a peak number of publications in 2008. Although many world regions have published on ADHD LTOs, the majority of studies have emerged from the US and Canada, followed by Europe. While investigators in the US and Canada were predominantly interested in drug addiction as a LTO, European researchers were more interested in antisocial behavior, and Eastern Asian investigators focused on both of these LTOs as well as self-esteem. Proportionally fewer prospective longitudinal studies and proportionally more retrospective and cross-sectional studies have been published in more recent decades. Finally, more studies focusing on ADHD in adolescents and adults have been conducted in recent years, and particularly adolescents in Eastern Asia. This systematic review analysis of publication trends in ADHD LTOs reflects geographically-based interests that change over time

Protein-protein interactions: switch from classical methods to proteomics and bioinformatics-based approaches

Following the sequencing of the human genome and many other organisms, research on protein-coding genes and their functions (functional genomics) has intensified. Subsequently, with the observation that proteins are indeed the molecular effectors of most cellular processes, the discipline of proteomics was born. Clearly, proteins do not function as single entities but rather as a dynamic network of team players that have to communicate. Though genetic (yeast two-hybrid Y2H) and biochemical methods (co-immunoprecipitation Co-IP, affinity purification AP) were the methods of choice at the beginning of the study of protein-protein interactions (PPI), in more recent years there has been a shift towards proteomics-based methods and bioinformatics-based approaches. In this review, we first describe in depth PPIs and we make a strong case as to why unraveling the interactome is the next challenge in the field of proteomics. Furthermore, classical methods of investigation of PPIs and structure-based bioinformatics approaches are presented. The greatest emphasis is placed on proteomic methods, especially native techniques that were recently developed and that have been shown to be reliable. Finally, we point out the limitations of these methods and the need to set up a standard for the validation of PPI experiments

Proteomic analysis of plasma membranes isolated from undifferentiated and differentiated HepaRG cells

<p>Abstract</p> <p>Liver infection with hepatitis B virus (HBV), a DNA virus of the <it>Hepadnaviridae</it> family, leads to severe disease, such as fibrosis, cirrhosis and hepatocellular carcinoma. The early steps of the viral life cycle are largely obscure and the host cell plasma membrane receptors are not known. HepaRG is the only proliferating cell line supporting HBV infection <it>in vitro</it>, following specific differentiation, allowing for investigation of new host host-cell factors involved in viral entry, within a more robust and reproducible environment. Viral infection generally begins with receptor recognition at the host cell surface, following highly specific cell-virus interactions. Most of these interactions are expected to take place at the plasma membrane of the HepaRG cells. In the present study, we used this cell line to explore changes between the plasma membrane of undifferentiated (−) and differentiated (+) cells and to identify differentially-regulated proteins or signaling networks that might potentially be involved in HBV entry. Our initial study identified a series of proteins that are differentially expressed in the plasma membrane of (−) and (+) cells and are good candidates for potential cell-virus interactions. To our knowledge, this is the first study using functional proteomics to study plasma membrane proteins from HepaRG cells, providing a platform for future experiments that will allow us to understand the cell-virus interaction and mechanism of HBV viral infection.</p

Comparative Proteomics Reveals Novel Components at the Plasma Membrane of Differentiated HepaRG Cells and Different Distribution in Hepatocyte- and Biliary-Like Cells

<div><p>Hepatitis B virus (HBV) is a human pathogen causing severe liver disease and eventually death. Despite important progress in deciphering HBV internalization, the early virus-cell interactions leading to infection are not known. HepaRG is a human bipotent liver cell line bearing the unique ability to differentiate towards a mixture of hepatocyte- and biliary-like cells. In addition to expressing metabolic functions normally found in liver, differentiated HepaRG cells support HBV infection <i>in vitro,</i> thus resembling cultured primary hepatocytes more than other hepatoma cells. Therefore, extensive characterization of the plasma membrane proteome from HepaRG cells would allow the identification of new cellular factors potentially involved in infection. Here we analyzed the plasma membranes of non-differentiated and differentiated HepaRG cells using nanoliquid chromatography-tandem mass spectrometry to identify the differences between the proteomes and the changes that lead to differentiation of these cells. We followed up on differentially-regulated proteins in hepatocytes- and biliary-like cells, focusing on Cathepsins D and K, Cyclophilin A, Annexin 1/A1, PDI and PDI A4/ERp72. Major differences between the two proteomes were found, including differentially regulated proteins, protein-protein interactions and intracellular localizations following differentiation. The results advance our current understanding of HepaRG differentiation and the unique properties of these cells.</p></div