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Understanding of the immediate mechanisms of Mn-induced neurotoxicity is rapidly evolving. We seek to provide a summary of recent findings in the field, with an emphasis to clarify existing gaps and future research directions. We provide, here, a brief review of pertinent discoveries related to Mn-induced neurotoxicity research from the last five years. Significant progress was achieved in understanding the role of Mn transporters, such as SLC39A14, SLC39A8, and SLC30A10, in the regulation of systemic and brain manganese handling. Genetic analysis identified multiple metabolic pathways that could be considered as Mn neurotoxicity targets, including oxidative stress, endoplasmic reticulum stress, apoptosis, neuroinflammation, cell signaling pathways, and interference with neurotransmitter metabolism, to name a few. Recent findings have also demonstrated the impact of Mn exposure on transcriptional regulation of these pathways. There is a significant role of autophagy as a protective mechanism against cytotoxic Mn neurotoxicity, yet also a role for Mn to induce autophagic flux itself and autophagic dysfunction under conditions of decreased Mn bioavailability. This ambivalent role may be at the crossroad of mitochondrial dysfunction, endoplasmic reticulum stress, and apoptosis. Yet very recent evidence suggests Mn can have toxic impacts below the no observed adverse effect of Mn-induced mitochondrial dysfunction. The impact of Mn exposure on supramolecular complexes SNARE and NLRP3 inflammasome greatly contributes to Mn-induced synaptic dysfunction and neuroinflammation, respectively. The aforementioned effects might be at least partially mediated by the impact of Mn on α-synuclein accumulation. In addition to Mn-induced synaptic dysfunction, impaired neurotransmission is shown to be mediated by the effects of Mn on neurotransmitter systems and their complex interplay. Although multiple novel mechanisms have been highlighted, additional studies are required to identify the critical targets of Mn-induced neurotoxicity.

Despite the strong genetic basis of psychiatric disorders, the underlying molecular mechanisms are largely unmapped. RNA-binding proteins (RBPs) are responsible for most post-transcriptional regulation, from splicing to translation to localization. RBPs thus act as key gatekeepers of cellular homeostasis, especially in the brain. However, quantifying the pathogenic contribution of noncoding variants impacting RBP target sites is challenging. Here, we leverage a deep learning approach that can accurately predict the RBP target site dysregulation effects of mutations and discover that RBP dysregulation is a principal contributor to psychiatric disorder risk. RBP dysregulation explains a substantial amount of heritability not captured by large-scale molecular quantitative trait loci studies and has a stronger impact than common coding region variants. We share the genome-wide profiles of RBP dysregulation, which we use to identify DDHD2 as a candidate schizophrenia risk gene. This resource provides a new analytical framework to connect the full range of RNA regulation to complex disease. Genome-wide analysis of RNA-binding protein (RBP) target sites identifies a major role for RBP dysregulation in complex psychiatric disorders and implicates DDHD2 as a candidate risk gene for schizophrenia.

Insomnia is the second most prevalent mental disorder, with no sufficient treatment available. Despite substantial heritability, insight into the associated genes and neurobiological pathways remains limited. Here, we use a large genetic association sample ( n  = 1,331,010) to detect novel loci and gain insight into the pathways, tissue and cell types involved in insomnia complaints. We identify 202 loci implicating 956 genes through positional, expression quantitative trait loci, and chromatin mapping. The meta-analysis explained 2.6% of the variance. We show gene set enrichments for the axonal part of neurons, cortical and subcortical tissues, and specific cell types, including striatal, hypothalamic, and claustrum neurons. We found considerable genetic correlations with psychiatric traits and sleep duration, and modest correlations with other sleep-related traits. Mendelian randomization identified the causal effects of insomnia on depression, diabetes, and cardiovascular disease, and the protective effects of educational attainment and intracranial volume. Our findings highlight key brain areas and cell types implicated in insomnia, and provide new treatment targets. Genome-wide analyses in >1 million individuals identify new loci and pathways associated with insomnia. The findings implicate key brain areas and cell types in the neurobiology of insomnia and highlight potential targets for developing new treatments.

Long-read sequencing is driving rapid progress in genome assembly across all major groups of life, including species of the family Drosophilidae, a longtime model system for genetics, genomics, and evolution. We previously developed a cost-effective hybrid Oxford Nanopore (ONT) long-read and Illumina short-read sequencing approach and used it to assemble 101 drosophilid genomes from laboratory cultures, greatly increasing the number of genome assemblies for this taxonomic group. The next major challenge is to address the laboratory culture bias in taxon sampling by sequencing genomes of species that cannot easily be reared in the lab. Here, we build upon our previous methods to perform amplification-free ONT sequencing of single wild flies obtained either directly from the field or from ethanol-preserved specimens in museum collections, greatly improving the representation of lesser studied drosophilid taxa in whole-genome data. Using Illumina Novaseq X Plus and ONT P2 sequencers with R10.4.1 chemistry, we set a new benchmark for inexpensive hybrid genome assembly at US $150 per genome while assembling genomes from as little as 35 ng of genomic DNA from a single fly. We present 183 new genome assemblies for 179 species as a resource for drosophilid systematics, phylogenetics, and comparative genomics. Of these genomes, 62 are from pooled lab strains and 121 from single adult flies. Despite the sample limitations of working with small insects, most single-fly diploid assemblies are comparable in contiguity (>1 Mb contig N50), completeness (>98% complete dipteran BUSCOs), and accuracy (>QV40 genome-wide with ONT R10.4.1) to assemblies from inbred lines. We present a well-resolved multi-locus phylogeny for 360 drosophilid and 4 outgroup species encompassing all publicly available (as of August 2023) genomes for this group. Finally, we present a Progressive Cactus whole-genome, reference-free alignment built from a subset of 298 suitably high-quality drosophilid genomes. The new assemblies and alignment, along with updated laboratory protocols and computational pipelines, are released as an open resource and as a tool for studying evolution at the scale of an entire insect family.

Cyclic dinucleotides (CDNs) have central roles in bacterial homeostasis and virulence by acting as nucleotide second messengers. Bacterial CDNs also elicit immune responses during infection when they are detected by pattern-recognition receptors in animal cells. Here we perform a systematic biochemical screen for bacterial signalling nucleotides and discover a large family of cGAS/DncV-like nucleotidyltransferases (CD-NTases) that use both purine and pyrimidine nucleotides to synthesize a diverse range of CDNs. A series of crystal structures establish CD-NTases as a structurally conserved family and reveal key contacts in the enzyme active-site lid that direct purine or pyrimidine selection. CD-NTase products are not restricted to CDNs and also include an unexpected class of cyclic trinucleotide compounds. Biochemical and cellular analyses of CD-NTase signalling nucleotides demonstrate that these cyclic di- and trinucleotides activate distinct host receptors and thus may modulate the interaction of both pathogens and commensal microbiota with their animal and plant hosts. A bacterial family of cGAS/DncV-like nucleotidyltransferases synthesizes a diverse range of cyclic dinucleotide and trinucleotide compounds that are likely to modulate the interaction of both pathogens and commensal microbiota with their animal and plant hosts.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care. Drawing on 51,269 participants across 9 independent, geographically diverse datasets, an AI model identifies the etiologies contributing to dementia in individuals, harnessing a broad array of data, including demographics, medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging.

Twenty-seven models participated in the Earth System Model–Snow Model Intercomparison Project (ESM-SnowMIP), the most data-rich MIP dedicated to snow modeling. Our findings do not support the hypothesis advanced by previous snow MIPs: evaluating models against more variables and providing evaluation datasets extended temporally and spatially does not facilitate identification of key new processes requiring improvement to model snow mass and energy budgets, even at point scales. In fact, the same modeling issues identified by previous snow MIPs arose: albedo is a major source of uncertainty, surface exchange parameterizations are problematic, and individual model performance is inconsistent. This lack of progress is attributed partly to the large number of human errors that led to anomalous model behavior and to numerous resubmissions. It is unclear how widespread such errors are in our field and others; dedicated time and resources will be needed to tackle this issue to prevent highly sophisticated models and their research outputs from being vulnerable because of avoidable human mistakes. The design of and the data available to successive snow MIPs were also questioned. Evaluation of models against bulk snow properties was found to be sufficient for some but inappropriate for more complex snow models whose skills at simulating internal snow properties remained untested. Discussions between the authors of this paper on the purpose of MIPs revealed varied, and sometimes contradictory, motivations behind their participation. These findings started a collaborative effort to adapt future snow MIPs to respond to the diverse needs of the community.

Carl June and colleagues report the results of a phase I/II trial of adoptively transferred engineered T cells in patients with advanced multiple myeloma. Despite recent therapeutic advances, multiple myeloma (MM) remains largely incurable. Here we report results of a phase I/II trial to evaluate the safety and activity of autologous T cells engineered to express an affinity-enhanced T cell receptor (TCR) recognizing a naturally processed peptide shared by the cancer-testis antigens NY-ESO-1 and LAGE-1. Twenty patients with antigen-positive MM received an average 2.4 × 10 9 engineered T cells 2 d after autologous stem cell transplant. Infusions were well tolerated without clinically apparent cytokine-release syndrome, despite high IL-6 levels. Engineered T cells expanded, persisted, trafficked to marrow and exhibited a cytotoxic phenotype. Persistence of engineered T cells in blood was inversely associated with NY-ESO-1 levels in the marrow. Disease progression was associated with loss of T cell persistence or antigen escape, in accordance with the expected mechanism of action of the transferred T cells. Encouraging clinical responses were observed in 16 of 20 patients (80%) with advanced disease, with a median progression-free survival of 19.1 months. NY-ESO-1–LAGE-1 TCR–engineered T cells were safe, trafficked to marrow and showed extended persistence that correlated with clinical activity against antigen-positive myeloma.

Neuroticism is an important risk factor for psychiatric traits, including depression 1 , anxiety 2 , 3 , and schizophrenia 4 – 6 . At the time of analysis, previous genome-wide association studies 7 – 12 (GWAS) reported 16 genomic loci associated to neuroticism 10 – 12 . Here we conducted a large GWAS meta-analysis ( n  = 449,484) of neuroticism and identified 136 independent genome-wide significant loci (124 new at the time of analysis), which implicate 599 genes. Functional follow-up analyses showed enrichment in several brain regions and involvement of specific cell types, including dopaminergic neuroblasts ( P  = 3.49 × 10 −8 ), medium spiny neurons ( P  = 4.23 × 10 −8 ), and serotonergic neurons ( P  = 1.37 × 10 −7 ). Gene set analyses implicated three specific pathways: neurogenesis ( P  = 4.43 × 10 −9 ), behavioral response to cocaine processes ( P  = 1.84 × 10 −7 ), and axon part ( P  = 5.26 × 10 −8 ). We show that neuroticism’s genetic signal partly originates in two genetically distinguishable subclusters 13 (‘depressed affect’ and ‘worry’), suggesting distinct causal mechanisms for subtypes of individuals. Mendelian randomization analysis showed unidirectional and bidirectional effects between neuroticism and multiple psychiatric traits. These results enhance neurobiological understanding of neuroticism and provide specific leads for functional follow-up experiments. A meta-analysis of genome-wide association studies for neuroticism identifies novel loci, pathways and potential drug targets. Further analysis implicates specific brain regions and evaluates genetic overlap with other neuropsychiatric traits.