Biology subjects

Chen, R.

Publications and source records attributed to Chen, R..

At least 253 records · Page 14Linked to original sources

bioRxiv2022

Enhanced mTORC1 signaling and Protein Synthesis in Parkinson Disease Pathogenesis

Pathologic -syn destabilizes the TSC 1 and 2 complex leading to mTORC1 activation, enhanced protein translation and neurodegeneration in PD. AbstractPathological -synuclein (-syn) plays an important role in the pathogenesis of -synucleinopathies such as Parkinsons disease (PD). Disruption of protein homeostasis is thought be central to PD pathogenesis, however the molecular mechanism of this deregulation is poorly understood. Here we report that pathologic -syn binds to tuberous sclerosis protein (TSC) 2 and destabilizes the TSC1-TSC2 complex leading to activation of the mechanistic target of rapamycin (mTOR) complex 1 (mTORC1) and enhanced mRNA translation. Dopamine neuron loss, behavioral deficits and aberrant biochemical signaling in the -syn preformed fibril (PFF) and Drosophila -syn transgenic models of pathologic -syn induced degeneration were attenuated by genetic and pharmacologic inhibition of mTOR and protein translation. Our findings establish a potential molecular mechanism by which pathologic -syn activates mTORC1 leading to enhanced protein translation and concomitant neurodegeneration in PD.

neuroscience↗

bioRxiv2022

Effects of antennal segments defects on blood-sucking behavior in Aedes albopictus

After mating, female mosquitoes need a blood meal to promote the reproductive process. The blood-feeding transmits extremely harmful infections including malaria, yellow fever, dengue fever, and other arboviruses, making mosquitoes one of the most harmful creatures to human health. The selection and localization of the host by mosquitoes mainly depends on the trace chemical cues emitted by the host into the environment, and the sense of smell is the main way to perceive these trace chemical cues. However, the knowledge of the olfactory mechanism is not enough to meet the needs of mosquito control. Unlike previous studies that focused on the olfactory receptor recognition spectrum to reveal the olfactory mechanism of mosquito host localization. In this paper, we proposed that artificial defects in mosquito antennal flagellomeres may affect their blood-feeding behavior, and through rationally designed behavioral experiments, we found that the 6th and 7th flagellomeres on Aedes albopictus antenna are important in the olfactory detection of host searching. Meanwhile, the morphology and distribution of sensilla on each antenna flagellomere were also analyzed and discussed in this paper.

animal behavior and cognition↗

bioRxiv2022

Sequential Activation and Local Unfolding Control Poly(A)-Binding Protein Condensation

Eukaryotic cells form biomolecular condensates to sense and adapt to their environment1,2. Poly(A)-binding protein (Pab1), a canonical stress granule marker3,4, condenses upon heat shock or starvation, promoting adaptation5. The molecular basis of condensation has remained elusive due to a dearth of techniques to probe structure directly in condensates. Here we apply hydrogen-deuterium exchange/mass spectrometry (HDX-MS) to investigate the molecular mechanism of Pab1s condensation. We find that Pab1s four RNA recognition motifs (RRMs) undergo different levels of partial unfolding upon condensation, and the changes are similar for thermal and pH stresses. Although structural heterogeneity is observed, the ability of MS to describe individual subpopulations allows us to identify which regions become partially unfolded and contribute to the condensates interaction network. Our data yield a clear molecular picture of Pab1s stress-triggered condensation, which we term sequential activation, wherein each RRM becomes activated at a temperature where it partially unfolds and associates with other likewise activated RRMs to form the condensate. This model thus implies that sequential activation is dictated by the underlying free energy surface, an effect we refer to as thermodynamic specificity. Our study represents a methodological advance for elucidating the interactions that drive biomolecular condensation that we anticipate will be widely applicable. Furthermore, our findings demonstrate how condensation can use thermodynamic specificity to perform an acute response to multiple, stresses, a potentially general mechanism for stress-responsive proteins.

biophysics↗

bioRxiv2022

Dual control of lysogeny and phage defense by a phosphorylation-based toxin/antitoxin system

Regulatory systems that maintain prophage quiescence integrate phage and host gene expression with environmental conditions1,2. In the opportunistic bacterial pathogen Pseudomonas aeruginosa, Pf filamentous bacteriophages play critical roles in biofilm formation and virulence3-5, but mechanisms governing Pf prophage activation in biofilms are largely unknown. Here, we report a new type of prophage regulatory module in a widely-distributed P. aeruginosa lineage that not only controls virion production of co-resident Pf prophages, but also mediates defense against diverse lytic phages. By comparing two lineages of the prototype P. aeruginosa strain PAO1 that harbor different Pf prophages, we identified a prophage-encoded kinase-kinase-phosphatase (KKP) system that controls Pf production in biofilms. KKP components exhibit dynamic stoichiometry, where high kinase levels in planktonic conditions maintain phosphorylation of the host H-NS protein MvaU, repressing prophage activation. During biofilm formation, phosphatase expression is heightened, leading to MvaU dephosphorylation and alleviating repression of prophage gene expression. KKP clusters are present in hundreds of diverse temperate prophages and other mobile elements across Gram-negative bacteria. Characterization of KKP modules from different species revealed that, in addition to regulating Pf phage lysogeny, KKP functions as a tripartite toxin-antitoxin system that mediates host defense from predatory lytic phages. KKP represents a new phosphorylation-based mechanism for prophage regulation and for phage defense. The dual function of this module raises the question of whether other newly described phage defense systems6-9 also regulate intrinsic prophage biology in diverse hosts.

microbiology↗

bioRxiv2022

Integrated Immunopeptidomics and Proteomics Study Reveals Imbalanced Innate and Adaptive Immune Responses to SARS-Cov-2 Infection

We present an integrated immunopeptidomics and proteomics study of SARS-Cov-2 infection to comprehensively decipher the changes in host cells in response to viral infection. Our results indicated that innate immune response in Calu-3 cells was initiated by TLR3, followed by activation of interferon signaling pathway. Host cells also present viral antigens to the cell surface through both Class I and Class II MHC system for recognition by adaptive immune system. SARS-Cov-2 infection led to the disruption of antigen presentation as demonstrated by higher level of HLA proteins from the flow-through of MHC immunoprecipitation. Glycosylation analysis of HLA proteins from the elution and flow-through of immunoprecipitation revealed that the synthesis and degradation of HLA protein was affected by SARS-Cov-2 infection. This study provided many useful information to study the host response to SARS-Cov-2 infection and would be helpful for the development of therapeutics and vaccine for Covid-19 and future pandemic.

immunology↗

bioRxiv2022

Conserved and transcript-specific functions of the RESC factors, RESC13 and RESC14, in kinetoplastid RNA editing

Uridine insertion/deletion RNA editing is an extensive post-transcriptional modification of mitochondrial mRNAs in kinetoplastid organisms, including Trypanosoma brucei. This process is carried out using trans-acting gRNAs and complex protein machinery. The essential RNA Editing Substrate Binding Complex (RESC) serves as the scaffold that modulates protein and RNA interactions during editing, and contains the Guide RNA Binding Complex (GRBC), the RNA Editing Mediator Complexes (REMCs), and organizer proteins. Despite the importance of RESC in editing, the functions of each protein comprising this complex are not completely understood. Here, we further define the roles of a REMC protein, RESC13, and a RESC organizer, RESC14, using high-throughput sequencing on two large pan-edited mRNAs, A6 and COIII. When comparing our analyses to that of a previously published small pan-edited mRNA, RPS12, we find that RESC13 has conserved functions across the three transcripts with regards to editing initiation, gRNA utilization, gRNA exchange, and restricting the formation of long mis-edited junctions that likely arise from its ability to modulate RNA structure. However, RESC13 does have transcript-specific effects on the types of long junctions whose formation it restricts. RESC14 has a conserved effect on gRNA utilization across the three transcripts analyzed, but has transcript-specific effects on editing initiation, gRNA exchange, and junction formation. Our data suggest that transcript-specific effects of both proteins are due to differences in transcript length and sequences as well as transcript-specific protein interactions. These findings highlight the importance of studying multiple transcripts to determine the function of editing factors.

molecular biology↗

bioRxiv2022

From multi-omics data to the cancer druggable genediscovery: a novel machine learning-based approach

The development of targeted drugs allows precision medicine in cancer treatment and achieving optimal targeted therapies. Accurate identification of cancer drug genes is helpful to strengthen the understanding of targeted cancer therapy and promote precise cancer treatment. However, rare cancer-druggable genes have been found due to the multi-omics datas diversity and complexity. This study proposes DF-CAGE, a novel machine learning-based method for cancer-druggable gene discovery. DF-CAGE integrated the somatic mutations, copy number variants, DNA methylation, and RNA-Seq data across ~10000 TCGA profiles to identify the landscape of the cancer-druggable genes. We found that DF-CAGE discovers the commonalities of currently known cancer-druggable genes from the perspective of multi-omics data and achieved excellent performance on OncoKB, Target, and Drugbank data sets. Among the ~20,000 protein-coding genes, DF-CAGE pinpointed 465 potential cancer-druggable genes. We found that the candidate cancer druggable genes (CDG-genes) are clinically meaningful and can be divided into highly reliable, reliable, and potential gene sets. Finally, we analyzed the contribution of the omics data to the identification of druggable genes. We found that DF-CAGE reports druggable genes mainly based on the CNAs data, the gene rearrangements, and the mutation rates in the population. These findings may enlighten the study and development of new drugs in the future.

bioinformatics↗

bioRxiv2022

Talaromyces marneffei suppresses human macrophages inflammatory by producing the truncated protein NCOR2-013 via TUT1-regulated alternative splicing

Talaromyces marneffei (T. marneffei) immune-escaping is an important factor for high mortality of talaromycosis. It is currently known that T. marneffei performs these functions through a variety of strategies, however, the role of alternative splicing (AS) in this process is poorly understood. Here we depicted the AS landscape in the macrophage upon T. marneffei infection via high-throughput RNA sequencing. Moreover, we identified a truncated protein of NCOR2/SMRT, namedly NCOR2-013, was significantly upregulated upon T. marneffei infection. Mechanistic analysis indicates that NCOR2-013 forms a co-repression complex with TBL1XR1/TBLR1 and HDAC3, thereby inhibiting JunB-mediated transcriptional activation of pro-inflammatory cytokines via the inhibition of histone acetylation. Also, we identified TUT1 as the AS regulator that involved in facilitating T. marneffei immune evasion via regulation of NCOR2-013 production. Collectively, the findings indicate that T. marneffei escapes macrophages killing through the TUT1-mediated the alternative splicing of NCOR2-013, which providing a new insight into the molecular mechanisms of T. marneffei immune evasion, and a potential targets for talaromycosis therapy.

microbiology↗

bioRxiv2022

The Nucleocapsid Protein Of SARS-CoV-2, Combined With ODN-39M, Is A Potential Component For An Intranasal Bivalent Pancorona Vaccine

Despite the rapid development of vaccines and their reported efficacy for controlling the COVID-19 waves, two key challenges remain: the scope of the immunity against upcoming variants and zoonosis events, and the induction of mucosal immunity able to clear the virus in the upper respiratory tract for halting the transmission. The present study is aiming at assessing a potential component for a new generation of vaccines so as to overcome such limitations. The recombinant nucleocapsid (N) protein from SARS-CoV-2 Delta variant was combined with a phosphodiester backbone CpG ODN (ODN-39M), forming high molecular weight aggregates. The evaluation of its immunogenicity in Balb/C mice revealed that only administration by intranasal route induced a systemic cross-reactive Cell-Mediated-Immunity (CMI). In turn, this combination was able to induce anti-N IgA in lungs, which along with the specific IgG in sera and CMI in spleen, resulted cross-reactive against the nucleocapsid protein of SARS-CoV-1. Furthermore, the nasal administration of the N+ODN-39M preparation combined with the RBD Delta protein, as inductor of neutralizing Abs, enhanced the local and systemic immune response against RBD with a modulation toward a Th1 pattern. Taken together, these results make the N+ODN-39M preparation a suitable component for a future intranasal pancorona vaccine against Sarbecoviruses. Particularly, the bivalent vaccine formulation N+ODN-39M+RBD could be used as an effective nasal booster in previously vaccinated population.

immunology↗

bioRxiv2022

Systemic interindividual epigenetic variation in humans is associated with transposable elements and under strong genetic control

Genetic variants can modulate phenotypic outcomes via epigenetic intermediates, for example by affecting DNA methylation at CpG dinucleotides (methylation quantitative trait loci - mQTL). Here, we present the first large-scale assessment of mQTL at human genomic regions selected for interindividual variation in CpG methylation (correlated regions of systemic interindividual variation - CoRSIVs). We used target-capture bisulfite sequencing to assess DNA methylation at 4,086 CoRSIVs in multiple tissues from 188 donors in the NIH Genotype-Tissue Expression (GTEx) program (807 samples total). At CoRSIVs, as expected, DNA methylation in peripheral blood correlates with methylation and gene expression in internal organs. We also discovered unprecedented mQTL at these regions. Genetic influences on CoRSIV methylation are extremely strong (median R2=0.76), cumulatively comprising over 70-fold more human mQTL than detected in the most powerful previous study. Moreover, mQTL beta coefficients at CoRSIVs are highly skewed (i.e., the major allele predicts higher methylation). Both surprising findings were independently validated in a cohort of 47 non-GTEx individuals. Genomic regions flanking CoRSIVs show long-range enrichments for LINE-1 and LTR transposable elements; the skewed beta coefficients may therefore reflect evolutionary selection of genetic variants that promote their methylation and silencing. Analyses of GWAS summary statistics show that mQTL polymorphisms at CoRSIVs are associated with metabolic and other classes of disease. A focus on systemic interindividual epigenetic variants, clearly enhanced in mQTL content, should likewise benefit studies attempting to link human epigenetic variation to risk of disease. Our CoRSIV-capture reagents are commercially available from Agilent Technologies, Inc. Significance StatementPopulation epigeneticists have relied almost exclusively on CpG methylation arrays manufactured by Illumina. At most of the >400,000 CpG sites covered by those arrays, however, methylation does not vary appreciably between individuals. We previously identified genomic loci that exhibit systemic (i.e. not tissue-specific) interindividual variation in DNA methylation (CoRSIVs). These can be assayed in blood DNA and, unlike tissue-specific epigenetic variants, do not reflect interindividual variation in cellular composition. Here, studying just 4,086 CoRSIVs in multiple tissues of 188 individuals, we detect much stronger genetic influences on DNA methylation (mQTL) than ever before reported. Because interindividual epigenetic variation is essential for not only mQTL detection, but also for epigenetic epidemiology, our results indicate a major opportunity to advance this field.

genetics↗

bioRxiv2022

Striatal Mu-Opioid Receptor Activation Triggers Direct-Pathway GABAergic Plasticity to Induce Negative Affect

Withdrawal from chronic opioid use often causes hypodopaminergic states and negative affect, which drives relapse. Direct-pathway medium spiny neurons (dMSNs) in the striatal patch compartment contain high levels of {micro}-opioid receptors (MORs). It remains unclear how chronic opioid exposure affects these MOR-expressing dMSNs and their striatopallidal and striatonigral outputs to induce negative emotions and relapse. Here, we report that MOR activation acutely suppressed GABAergic striatopallidal transmission in habenula-projecting globus pallidus neurons. Notably, repeated administrations of a MOR agonist (morphine or fentanyl) potentiated this GABAergic transmission. We also discovered that intravenous self-administration of fentanyl enhanced GABAergic striatonigral transmission and reduced the firing activity of midbrain dopaminergic neurons. Importantly, fentanyl withdrawal caused depression-like behaviors and promoted the reinstatement of fentanyl-seeking behaviors. These data suggest that chronic opioid use triggers GABAergic striatopallidal and striatonigral plasticity to induce a hypodopaminergic state, promoting negative emotions and leading to relapse. HighlightsO_LIRepeated administration of morphine potentiates IPSCdMSN{lozenge}GPh neurotransmission. C_LIO_LIRepeated administration of fentanyl potentiates IPSCdMSN{lozenge}SNc neurotransmission. C_LIO_LIFentanyl withdrawal induces negative emotional states, which drive relapse. C_LI

neuroscience↗

bioRxiv2022

Accurate inference of genome-wide spatial expression with iSpatial

Spatially resolved transcriptomic analyses can reveal molecular insights underlying tissue structure and context-dependent cell-cell or cell-environment interaction. Due to the current technical limitation, obtaining genome-wide spatial transcriptome at single-cell resolution is challenging. Here we developed a new algorithm named iSpatial to derive spatial pattern of the entire transcriptome by integrating spatial transcriptomic and single-cell RNA-seq datasets. Compared to other existing methods, iSpatial has higher accuracy in predicting gene expression and their spatial distribution. Furthermore, it reduces false-positive and false-negative signals in the original datasets. By testing iSpatial with multiple spatial transcriptomic datasets, we demonstrate its wide applicability to datasets from different tissues and by different techniques. Thus, we innovated a computational approach to reveal spatial organization of the entire transcriptome at single cell resolution without the need of new technology development. With numerous high quality datasets available in the public domain, iSpatial provides a unique way for understanding the structure, function of complex tissues and disease processes. HIGHLIGHTSO_LIiSpatial infers genome-wide spatial gene expression pattern by integrating spatial transcriptomic and scRNA-seq data C_LIO_LIiSpatial outperforms existing approaches in inferring spatial gene expression patterns C_LIO_LIiSpatial reduces false-positive/negative signals of the original spatial transcriptome C_LIO_LIiSpatial is applicable to spatial transcriptomic datasets from different tissues and techniques C_LI

bioinformatics↗

bioRxiv2022

Characterizing transition cells in developmental processes from scRNA-seq data

Multi-cellular organism development involves orchestrated gene regulations of different cell types and cell states. Single-cell RNA-Seq, enable simultaneous observation of cells in various states, making it possible to study the underlying molecular mechanisms. However, most of the analytical methods do not make full use of the dynamics captured. Here, we model single-cell RNA-seq data obtained from a developmental process as a function of gene regulatory network using stochastic differential equations (SDEs). Based on dynamical systems theory, we showed that pair-wise gene expression correlation coefficients can accurately infer cell state transitions and validated it using mouse muscle cell regeneration scRNA-seq data. We then applied our analytical framework to the PDAC (Pancreatic ductal adenocarcinoma) mouse model scRNA-seq data. Through transition cells found in the pancreatic preinvasive lesions scRNA-seq data, we can better explain the heterogeneity and predict distinct cell fate even at early tumorigenesis stage. This suggests that the biomarkers identified by transition cells can be potentially used for diagnosis, prognosis and therapeutics of diseases.

bioinformatics↗

bioRxiv2022

Protein Lactylation and Metabolic Regulation of the Zoonotic Parasite Toxoplasma gondii

The biology of Toxoplasma gondii, the causative pathogen of one of the most wide-spread parasitic diseases remains poorly understood. Lactate, which is derived from glucose metabolic pathways, is considered to be not only an energy source in a variety of organisms including Toxoplasma gondii, but also a regulatory molecule that participates in gene activation and protein functioning. Lysine lactylation is a type of posttranslational modifications (PTMs) that was recently associated with chromatin remodeling, but lysine lactylation of histone and non-histone proteins has not yet been studied in T. gondii. To examine the prevalence and function of lactylation in T. gondii parasites, we mapped the lactylome of proliferating tachyzoite cells and found 1964 lactylation sites on 955 proteins in the T. gondii RH strain. The lactylated proteins were distributed in multiple subcellular compartments and were closely related to a wide variety of biological processes, including mRNA splicing, glycolysis, aminoacyl-tRNA biosynthesis, RNA transport, and multiple signaling pathways. We also performed chromatin immunoprecipitation sequencing (ChIP-seq) analysis with a lactylation specific antibody, the results revealed that histone H4K12la and H3K14la were enriched in the promoter and exon regions of Toxoplasma gondii genes associated with microtubule-based movement and cell invasion. We further confirmed the de-lactylase activity of histone deacetylase TgHDACs 2, 3, and 4, and that treatment with anti-histone acetyltransferase (TgMYST-A) antibodies profoundly reduced protein lactylation in the parasites. This study offers the first dataset of the global lactylation proteome and provides a basis for further dissection of the functional biology of Toxoplasma gondii.

microbiology↗

bioRxiv2022

TransCell: In silico characterization of genomic landscape and cellular responses from gene expressions through a two-step deep transfer learning

Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining comprehensive molecular characterization and cellular responses for a variety of cell lines, including those derived from underrepresented groups, is not trivial when resources are minimal. Using gene expression to predict other measurements has been actively explored; however, systematic investigation of its predictive power in various measurements has not been well studied. We evaluate commonly used machine learning methods and present TransCell, a two-step deep transfer learning framework that utilizes the knowledge derived from pan-cancer tumor samples to predict molecular features and responses. Among these models, TransCell has the best performance in predicting metabolite, gene effect score (or genetic dependency), and drug sensitivity, and has comparable performance in predicting mutation, copy number variation, and protein expression. Notably, TransCell improved the performance by over 50% in drug sensitivity prediction and achieved a correlation of 0.7 in gene effect score prediction. Furthermore, predicted drug sensitivities revealed potential repurposing candidates for new 100 pediatric cancer cell lines, and predicted gene effect scores reflected BRAF resistance in melanoma cell lines. Together, we investigate the predictive power of gene expression in six molecular measurement types and develop a web portal (http://apps.octad.org/transcell/) that enables the prediction of 352,000 genomic and cellular response features solely from gene expression profiles. Key PointsO_LIWe provide a systematic investigation on evaluating the predictive power of gene expression in six molecular measurement types including protein expression, copy number variation, mutation, metabolite, gene effect score, and drug sensitivity. C_LIO_LITransCell took advantage of the transfer learning technique, showing how to learn knowledge from the source tumors, and transfer learned weight initializations to the downstream tasks in cell lines. C_LIO_LICompared to the baseline methods, TransCell outperformed in metabolite, gene effect score, and drug sensitivity predictions. C_LIO_LITwo cases studies demonstrate that TransCell could identify new repurposing candidates for pediatric cancer cell lines as well as capture the differences of genetic dependencies in melanoma resistant cell lines. C_LI

bioinformatics↗

bioRxiv2022

Suppression of tumor/host intrinsic CMTM6 drives anti-tumor cytotoxicity in a PD-L1 independent manner

CKLF-like MARVEL transmembrane domain-containing 6 (CMTM6) has been identified as a regulator of membranal programmed death ligand 1 (PD-L1) stability and a factor associated with malignancy progression, but the effects and mechanisms of CMTM6 on tumor growth, as well as its potential for therapy, are still largely unknown. Here, we show that tumor CMTM6 increased with progression in both clinical patients and mice. Ablation of CMTM6 resulted in significant retardation of human and murine tumor growth dependent on T-lymphocyte immunity. Tumor CMTM6 suppression broke resistance to immune checkpoint inhibitors and remodeled the tumor immune microenvironment, as specific antitumor cytotoxicity was enhanced and contributed primarily to tumor inhibition. Further, without the PD-1/PD-L1 axis, CMTM6 suppression still significantly dampened tumor growth dependent on cytotoxic cells. Notably, we identified that CMTM6 was widely expressed on immune cells. T-cell CMTM6 increased with sustained immune activation and intratumoral immune exhaustion and affected the T-cell-intrinsic PD-L1 levels. Host CMTM6 knockout significantly restrained tumor growth dependent on CD8+ T-cells, and similarly, not entirely dependent on PD-L1. Thus, we developed and evaluated the antitumor efficacy of CMTM6-targeting adeno-associated virus (AAV), which effectively mobilized antitumor immunity and could be combined with various antitumor drugs. Our findings reveal that both tumor and host CMTM6 are deeply involved in tumor immunity with or without the PD-1/PD-L1 axis and that gene therapy targeting CMTM6 is a promising strategy for cancer immunotherapy. One Sentence SummaryEven in the absence of the PD-1/PD-L1 axis, tumor or host CMTM6 deficiency can mediate cytotoxicity-dependent anti-tumor immune responses, allowing CMTM6 to be a novel target for scAAV-mediated oncoimmunology gene therapy and combination treatment.

immunology↗

bioRxiv2022

Comprehensive multiomic profiling of somatic mutations in malformations of cortical development

Malformations of cortical development (MCD) are neurological conditions displaying focal disruption of cortical architecture and cellular organization arising during embryogenesis, largely from somatic mosaic mutations. Identifying the genetic causes of MCD has been a challenge, as mutations remain at low allelic fractions in brain tissue resected to treat epilepsy. Here, we report a genetic atlas from 317 brain resections, identifying 69 mutated genes through intensive profiling of somatic mutations, combining whole-exome and targeted-amplicon sequencing with functional validation and single-cell sequencing. Genotype-phenotype correlation analysis elucidated specific MCD gene sets associating distinct pathophysiological and clinical phenotypes. The unique spatiotemporal expression patterns identified by comparing single-nucleus transcriptional sequences of mutated genes in control and patient brains implicate critical roles in excitatory neurogenic pools during brain development, and in promoting neuronal hyperexcitability after birth.

genetics↗

bioRxiv2022

Population modeling with machine learning can enhance measures of mental health - Open-Data Replication

Efforts to predict trait phenotypes based on functional MRI data from large cohorts have been hampered by low prediction accuracy and/or small effect sizes. Although these findings are highly replicable, the small effect sizes are somewhat surprising given the presumed brain basis of phenotypic traits such as neuroticism and fluid intelligence. We aim to replicate previous work and additionally test multiple data manipulations that may improve prediction accuracy by addressing data pollution challenges. Specifically, we added additional fMRI features, averaged the target phenotype across multiple measurements to obtain more accurate estimates of the underlying trait, balanced the target phenotypes distribution through undersampling of majority scores, and identified data-driven subtypes to investigate the impact of between-participant heterogeneity. Our results replicated prior results from Dadi et a (2021) in a larger sample. Each data manipulation further led to small but consistent improvements in prediction accuracy, which were largely additive when combining multiple data manipulations. Combining data manipulations (i.e., extended fMRI features, averaged target phenotype, balanced target phenotype distribution) led to a three-fold increase in prediction accuracy for fluid intelligence compared to prior work. These findings highlight the benefit of several relatively easy and low-cost data manipulations, which may positively impact future work.

neuroscience↗