Biology subjects

Lee, S.

Publications and source records attributed to Lee, S..

At least 739 records · Page 41Linked to original sources

bioRxiv2018

Accurate Prediction of Alzheimer’s Disease Using Multi-Modal MRI and High-Throughput Brain Phenotyping

Accurate, reliable prediction of risk for Alzheimers disease (AD) is essential for early, disease-modifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, is likely to contain complementary information of neurodegenerative processes in AD. Here we tested the utility of commonly available multimodal MRI (T1-weighted structure and diffusion MRI), combined with high-throughput brain phenotyping--morphometry and connectomics--and machine learning, as a diagnostic tool for AD. We used, firstly, a clinical cohort at a dementia clinic (study 1: Ilsan Dementia Cohort; N=211; 110 AD, 64 mild cognitive impairment [MCI], and 37 subjective memory complaints [SMC]) to test and validate the diagnostic models; and, secondly, Alzheimers Disease Neuroimaging Initiative (ADNI)-2 (study 2) to test the generalizability of the approach and the prognostic models with longitudinal follow up data. Our machine learning models trained on the morphometric and connectome estimates (number of features=34,646) showed optimal classification accuracy (AD/SMC: 97% accuracy, MCI/SMC: 83% accuracy; AD/MCI: 97% accuracy) with iterative nested cross-validation in a single-site study, outperforming the benchmark model (FLAIR-based white matter hyperintensity volumes). In a generalizability study using ADNI-2, the combined connectome and morphometry model showed similar or superior accuracies (AD/HC: 96%; MCI/HC: 70%; AD/MCI: 75% accuracy) as CSF biomarker model (t-tau, p-tau, and Amyloid {beta}, and ratios). We also predicted MCI to AD progression with 69% accuracy, compared with the 70% accuracy using CSF biomarker model. The optimal classification accuracy in a single-site dataset and the reproduced results in multi-site dataset show the feasibility of the high-throughput imaging analysis of multimodal MRI and data-driven machine learning for predictive modeling in AD.

neuroscience↗

bioRxiv2018

Genome-wide association study of 1 million people identifies 111 loci for atrial fibrillation

To understand the genetic variation underlying atrial fibrillation (AF), the most common cardiac arrhythmia, we performed a genome-wide association study (GWAS) of > 1 million people, including 60,620 AF cases and 970,216 controls. We identified 163 independent risk variants at 111 loci and prioritized 165 candidate genes likely to be involved in AF. Many of the identified risk variants fall near genes where more deleterious mutations have been reported to cause serious heart defects in humans or mice (MYH6, NKX2-5, PITX2, TBC1D32, TBX5),1,2 or near genes important for striated muscle function and integrity (e.g. MYH7, PKP2, SSPN, SGCA). Experiments in rabbits with heart failure and left atrial dilation identified a heterogeneous distributed molecular switch from MYH6 to MYH7 in the left atrium, which resulted in contractile and functional heterogeneity and may predispose to initiation and maintenance of atrial arrhythmia.

genetics↗

bioRxiv2017

Somatic Mutations Predict Acute Myeloid Leukemia Years Before Diagnosis

BackgroundSomatic mutations observed in clonal hematopoiesis are associated with increased age and risk of hematological malignancies. However, the limited number of acute myeloid leukemia (AML) patients in studies of clonal hematopoiesis thus far has precluded determination of the spectrum of mutations leading to AML and their impact on risk and time to diagnosis.\n\nMethodsThe relationship between baseline mutations and subsequent AML was determined in a case-control study design. 212 women eventually diagnosed with AML (median time: 9.8 years) were identified from the Womens Health Initiative cohort alongside 212 matched AML-free controls. Deep sequencing of 67 genes was performed on DNA isolated from peripheral blood to detect subclonal mutations.\n\nResultsThe presence of any mutation was associated with increased odds of eventual AML (odds ratio [OR] 4.0; 95% confidence interval [CI], 2.5-6.3). These odds were further elevated with mutations in IDH1/2 (OR 8.4; 95% CI, 1.4-51.9), TP53 (OR 54.2; 95% CI, 2.9-1017.7), or spliceosome genes (OR 5.6; 95% CI, 1.5-20.6). Eventual AML diagnosis occurred in all or most participants with mutations in TP53 (N=23/23) or IDH1/2 (N=15/16). Mutations indicated sooner AML diagnosis (median 8.0 vs. 11.9 years; P < 0.001) with TP53 mutations demonstrating increased odds of AML within 5 years (OR 3.6; 95% CI, 1.4-9.1).\n\nConclusionsMutations are present in peripheral blood of AML patients a decade prior to AML diagnosis with mutations in TP53 producing especially rapid presentation. Strategies for monitoring of high-risk populations are needed and clinical trials of potential early interventions can be considered.

cancer biology↗

bioRxiv2017

Multi-SKAT: General framework to test multiple phenotype associations of rare variants

In genetic association analysis, a joint test of multiple distinct phenotypes can increase power to identify sets of trait-associated variants within genes or regions of interest. Existing multi-phenotype tests for rare variants make specific assumptions about the patterns of association with underlying causal variants and the violation of these assumptions can reduce power to detect association. Here we develop a general framework for testing pleiotropic effects of rare variants on multiple continuous phenotypes using multivariate kernel regression (Multi-SKAT). Multi-SKAT models effect sizes of variants on the phenotypes through a kernel matrix and performs a variance component test of association. We show that many existing tests are equivalent to specific choices of kernel matrices with the Multi-SKAT framework. To increase power of detecting association across tests with different kernel matrices, we developed a fast and accurate approximation of the significance of the minimum observed p-value across tests. To account for related individuals, our framework uses random effects for the kinship matrix. Using simulated data and amino acid and exome-array data from the METSIM study, we show that Multi-SKAT can improve power over single-phenotype SKAT-O test and existing multiple phenotype tests, while maintaining type I error rate.\n\nGrant NumbersThis research was conducted with support from the following grants from National Institute of Health: O_LIR01 HG008773 (D.D. and S.L.)\nC_LIO_LIR01 LM012535 (D.D. and S.L.)\nC_LIO_LIR01 HG000376 (L.S. and M.B.)\nC_LIO_LIU01 DK062370 (L.S. and M.B.)\nC_LI

genetics↗

bioRxiv2017

Label-free non-invasive quantitative measurement of lipid contents in individual microalgal cells using refractive index tomography

Microalgae are promising candidates for biofuel production due to their high lipid content. To facilitate utilization of the microalgae for biofuel, rapid quantification of the lipid contents in microalgae is necessary. However, conventional methods based on the chemical extraction of lipids require a time-consuming destructive extraction process. Here, we demonstrate label-free, non-invasive, rapid quantification of the lipid contents in individual micro-algal cells measuring the three-dimensional refractive index tomograms. We measure three-dimensional refractive index distributions within Nannochloropsis oculata cells and find that lipid droplets are identifiable in tomograms by their high refractive index. In addition, we alter N. oculata under nitrogen deficiency by measuring the volume, lipid weight, and dry cell weight of individual cells. Characterization of individual cells allows correlative analysis between the lipid content and size of individual cells.

bioengineering↗

bioRxiv2017

3D label-free imaging and analysis of Pinus pollen grains using optical diffraction tomography

O_LIThe structure of pollen grains is related to the reproductive function of the plants. Here, three-dimensional (3D) refractive index maps were obtained for individual conifer pollen grains using optical diffraction tomography (ODT).\nC_LIO_LIThe 3D morphological features of pollen grains from pine trees were investigated using measured refractive index maps, in which distinct substructures were clearly distinguished and analyzed.\nC_LIO_LIMorphological and physiochemical parameters of the pollen grains were quantified from the obtained refractive index (RI) maps and used to quantitatively study the interspecific differences of pollen grains from different strains.\nC_LIO_LIOur results demonstrate that ODT can assess the structure of pollen grains. This label-free and rapid 3D imaging approach may provide a new platform for understanding the physiology of pollen grains.\nC_LI

plant biology↗

bioRxiv2017

Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies

In genome-wide association studies (GWAS) for thousands of phenotypes in large biobanks, most binary traits have substantially fewer cases than controls. Both of the widely used approaches, linear mixed model and the recently proposed logistic mixed model, perform poorly - producing large type I error rates - in the analysis of phenotypes with unbalanced case-control ratios. Here we propose a scalable and accurate generalized mixed model association test that uses the saddlepoint approximation (SPA) to calibrate the distribution of score test statistics. This method, SAIGE, provides accurate p-values even when case-control ratios are extremely unbalanced. It utilizes state-of-art optimization strategies to reduce computational time and memory cost of generalized mixed model. The computation cost linearly depends on sample size, and hence can be applicable to GWAS for thousands of phenotypes by large biobanks. Through the analysis of UK Biobank data of 408,961 white British European-ancestry samples for >1400 binary phenotypes, we show that SAIGE can efficiently analyze large sample data, controlling for unbalanced case-control ratios and sample relatedness.

genomics↗

bioRxiv2017

Measurements of three-dimensional refractive index tomography and membrane deformability of live erythrocytes from Pelophylax nigromaculatus

Unlike mammalian erythrocytes, amphibian erythrocytes have distinct morphological features including large cell sizes and the presence of nuclei. The sizes of the cytoplasm and nuclei of erythrocytes vary significantly over different species, their environments, or pathophysiology, which makes hematological studies important for investigating amphibian species. Here, we present a label-free three-dimensional optical quantification of individual amphibian erythrocytes from frogs Pelophylax nigromaculatus (Rana nigromaculata). Using optical diffraction tomography, we measured three-dimensional refractive index (RI) tomograms of the cells, which clearly distinguished the cytoplasm and nuclei inside the erythrocytes. From the measured RI tomograms, we extracted the relevant biochemical parameters of the cells, including hemoglobin contents and hemoglobin concentrations. Furthermore, we measured dynamic membrane fluctuations and investigated the mechanical properties of the cell membrane. From the statistical and correlative analysis of these retrieved parameters, we investigated interspecific differences between frogs and previously studied mammals.

biophysics↗

bioRxiv2017

HSP90 inhibitors disrupt a transient HSP90-HSF1 interaction and identify a noncanonical model of HSP90-mediated HSF1 regulation

Heat shock factor 1 (HSF1) initiates a broad transcriptional response to proteotoxic stress while also mediating a cancer-specific transcriptional program. HSF1 is thought to be regulated by molecular chaperones, including Heat Shock Protein 90 (HSP90). HSP90 is proposed to sequester HSF1 in unstressed cells, but visualization of this interaction in vivo requires protein crosslinking. In this report, we show that HSP90 binding to HSF1 depends on HSP90 conformation and is only readily visualized for the ATP-dependent, N-domain dimerized chaperone, a conformation only rarely sampled by mammalian HSP90. We have used this mutationally fixed conformation to map HSP90 binding sites on HSF1. Further, we show that ATP-competitive, N-domain targeted HSP90 inhibitors disrupt this interaction, resulting in the increased duration of HSF1 occupancy of the hsp70 promoter and significant prolongation of both the constitutive and heat-induced HSF1 transcriptional activity. While our data do not support a role for HSP90 in sequestering HSF1 monomers to suppress HSF1 transcriptional activity, our findings do identify a noncanonical role for HSP90 in providing dynamic modulation of HSF1 activity by participating in removal of HSF1 trimers from heat shock elements in DNA, thus terminating the heat shock response.

biochemistry↗

bioRxiv2017

Integrative genomics analysis identifies ACVR1B as a candidate causal gene of emphysema distribution in non-alpha 1-antitrypsin deficient smokers

BackgroundSeveral genetic risk loci associated with emphysema apico-basal distribution (EABD) have been identified through genome-wide association studies (GWAS), but the biological functions of these variants are unknown. To characterize gene regulatory functions of EABD-associated variants, we integrated EABD GWAS results with 1) a multi-tissue panel of expression quantitative trait loci (eQTL) from subjects with COPD and the GTEx project and 2) epigenomic marks from 127 cell types in the Roadmap Epigenomics project. Functional validation was performed for a variant near ACVR1B.\n\nResultsSNPs from 168 loci with P-values<5x10-5 in the largest GWAS meta-analysis of EABD (Boueiz A. et al, AJRCCM 2017) were analyzed. 54 loci overlapped eQTL regions from our multi-tissue panel, and 7 of these loci showed a high probability of harboring a single, shared GWAS and eQTL causal variant (colocalization posterior probability[≥]0.9). 17 cell types exhibited greater than expected overlap between EABD loci and DNase-I hypersensitive peaks, DNaseI hotspots, enhancer marks, or digital DNaseI footprints (permutation P-value < 0.05), with the strongest enrichment observed in CD4+, CD8+, and regulatory T cells. A region near ACVR1B demonstrated significant colocalization with a lung eQTL and overlapped DNase-I hypersensitive regions in multiple cell types, and reporter assays in human bronchial epithelial cells confirmed allele-specific regulatory activity for the lead variant, rs7962469.\n\nConclusionsIntegrative analysis highlights candidate causal genes, regulatory variants, and cell types that may contribute to the pathogenesis of emphysema distribution. These findings will enable more accurate functional validation studies and better understanding of emphysema distribution biology.

genomics↗

bioRxiv2017

KoVariome: Korean National Standard Reference Variome database of whole genomes with comprehensive SNV, indel, CNV, and SV analyses

High-coverage whole-genome sequencing data of a single ethnicity can provide a useful catalogue of population-specific genetic variations. Herein, we report a comprehensive analysis of the Korean population, and present the Korean National Standard Reference Variome (KoVariome). As a part of the Korean Personal Genome Project (KPGP), we constructed the KoVariome database using 5.5 terabases of whole genome sequence data from 50 healthy Korean individuals with an average coverage depth of 31x. In total, KoVariome includes 12.7M single-nucleotide variants (SNVs), 1.7M short insertions and deletions (indels), 4K structural variations (SVs), and 3.6K copy number variations (CNVs). Among them, 2.4M (19%) SNVs and 0.4M (24%) indels were identified as novel. We also discovered selective enrichment of 3.8M SNVs and 0.5M indels in Korean individuals, which were used to filter out 1,271 coding-SNVs not originally removed from the 1,000 Genomes Project data when prioritizing disease-causing variants. CNV analyses revealed gene losses related to bone mineral densities and duplicated genes involved in brain development and fat reduction. Finally, KoVariome health records were used to identify novel disease-causing variants in the Korean population, demonstrating the value of high-quality ethnic variation databases for the accurate interpretation of individual genomes and the precise characterization of genetic variations.

genomics↗

bioRxiv2017

Paupar LncRNA Promotes KAP1 Dependent Chromatin Changes And Regulates Subventricular Zone Neurogenesis

Many long non-coding RNAs (lncRNAs) are expressed during central nervous system (CNS) development, yet their in vivo roles and molecular mechanisms of action remain poorly understood. Paupar, a CNS expressed lncRNA, controls neuroblastoma cell growth by binding and modulating the activity of genome-wide transcriptional regulatory elements. We show here that Paupar transcript directly binds KAP1, an essential epigenetic regulatory protein, and thereby regulates the expression of shared target genes important for proliferation and neuronal differentiation. Paupar promotes KAP1 chromatin occupancy and H3K9me3 deposition at a subset of distal targets, through formation of a DNA binding ribonucleoprotein complex containing Paupar, KAP1 and the PAX6 transcription factor. Paupar-KAP1 genome-wide co-occupancy reveals a 4-fold enrichment of overlap between Paupar and KAP1 bound sequences. Furthermore, both Paupar and Kap1 loss of function in vivo accelerates lineage progression in the mouse postnatal subventricular zone (SVZ) stem cell niche and disrupts olfactory bulb neurogenesis. These observations provide important conceptual insights into the trans-acting modes of lncRNA-mediated epigenetic regulation, the mechanisms of KAP1 genomic recruitment and identify Paupar and Kap1 as regulators of SVZ neurogenesis.

neuroscience↗

bioRxiv2017

No major flaws in "Identification of individuals by trait prediction using whole-genome sequencing data"

In a recently published PNAS article, we studied the identifiability of genomic samples using machine learning methods [Lippert et al., 2017]. In a response, Erlich [2017] argued that our work contained major flaws. The main technical critique of Erlich [2017] builds on a simulation experiment that shows that our proposed algorithm, which uses only a genomic sample for identification, performed no better than a strategy that uses demographic variables. Below, we show why this comparison is misleading and provide a detailed discussion of the key critical points in our analyses that have been brought up in Erlich [2017] and in the media. Further, not only faces may be derived from DNA, but a wide range of phenotypes and demographic variables. In this light, the main contribution of Lippert et al. [2017] is an algorithm that identifies genomes of individuals by combining multiple DNA-based predictive models for a myriad of traits.

genomics↗

bioRxiv2017

Universal target-enrichment baits for anthozoan (Cnidaria) phylogenomics: New approaches to long-standing problems

Anthozoans (e.g., corals, anemones) are an ecologically important and diverse group of marine metazoans that occur from shallow to deep waters worldwide. However, our understanding of the evolutionary relationships among the [~]7500 species within this class is hindered by the lack of phylogenetically informative markers that can be reliably sequenced across a diversity of taxa. We designed and tested 16,308 RNA baits to capture 720 Ultraconserved Element loci and 1,071 exon loci. Library preparation and target enrichment was performed on 33 taxa from all orders within the class Anthozoa. Following Illumina sequencing and Trinity assembly, we recovered 1,774 of 1,791 targeted loci. The mean number of loci recovered from each species was 638 {+/-} 222, with more loci recovered from octocorals (783 {+/-} 138 loci) than hexacorals (475 {+/-}187 loci). Phylogenetically informative sites ranged from 26-49% for alignments at differing hierarchical taxonomic levels (e.g., Anthozoa, Octocorallia, Hexacorallia). The percent of variable sites within each of three genera (Acropora, Alcyonium, and Sinularia) for which multiple species were sequenced ranged from 4.7-30%. Maximum likelihood analyses recovered highly resolved trees with topologies matching those supported by other studies, including the monophyly of the order Scleractinia. Our results demonstrate the utility of this target-enrichment approach to resolve phylogenetic relationships from relatively old to recent divergences. Re-designing the baits with improved affinities to capture loci within each sub-class will provide a valuable toolset to address systematic questions and further our understanding of the timing of diversifications in the class Anthozoa.

genomics↗

bioRxiv2017

Replacing reprogramming factors with antibodies selected from autocrine antibody libraries

Signaling pathways initiated at the membrane establish and maintain cell fate during development and can be harnessed in the nucleus to generate induced pluripotent stem cells (iPSCs) from differentiated cells. Yet, the impact of extracellular signaling on reprogramming to pluripotency has not been systematically addressed. Here, we screen a lentiviral library encoding {small tilde}100 million secreted and membrane-bound antibodies and identify multiple antibodies that can replace Sox2/c-Myc or Oct4 during reprogramming. We show that one Sox2-replacing antibody initiates reprogramming by antagonizing the membrane-associated protein Basp1, thereby inducing nuclear factors WT1 and Esrrb/Lin28 independent of Sox2. By successively manipulating this pathway we identify three new methods to generate iPSCs. This study expands current knowledge of reprogramming methods and mechanisms and establishes unbiased selection from autocrine antibody libraries as a powerful orthogonal platform to discover new biologics and pathways regulating pluripotency and cell fate.

cell biology↗

bioRxiv2017

Activity based checkpoints ensure circuit stability in the olfactory system

Olfactory circuits function at birth, yet are continuously remodeled through the integration of adult-born interneurons into the olfactory bulb in a manner that preserves olfactory perceptual stability throughout adult life. The mechanisms that ensure appropriate circuit stability in this dynamic context remain poorly understood. Since interneurons sculpt the excitatory output of mitral and tufted (MT) neurons to the olfactory cortex, we predicted that MT neurons might instruct interneuron wiring in the adult brain. By blocking synaptic transmission from MT neurons we show that MT neuronal activity is critical to maintain olfactory bulb integrity and interneuron survival. Blocking interneuron death uncovered a second activity-dependent checkpoint regulating dendrite branching. In contrast, cortical circuits and MT neurons remain stable in the face of these silent and degenerating olfactory circuits. These studies identify a circuit-specific role for non-sensory activity in regulating integration of neurons into the adult brain, as predicted by previous computational models.

neuroscience↗

bioRxiv2017

Interactive Phenotyping Of Large-Scale Histology Imaging Data With HistomicsML

Whole-slide imaging of histologic sections captures tissue microenvironments and cytologic details in expansive high-resolution images. These images can be mined to extract quantitative features that describe histologic elements, yielding measurements for hundreds of millions of objects. A central challenge in utilizing this data is enabling investigators to train and evaluate classification rules for identifying objects related to processes like angiogenesis or immune response. Here we present HistomicsML, an interactive machine-learning framework for large whole-slide imaging data. HistomicsML uses active learning direct user feedback, making classifier training efficient and scalable in datasets containing 108+ histologic objects. We demonstrate how HistomicsML can be used to phenotype microvascular structures in gliomas to predict survival, and to explore the molecular pathways associated with these phenotypes. Our approach enables researchers to unlock phenotypic information from digital pathology datasets to investigate prognostic image biomarkers and genotype-phenotype associations.

bioinformatics↗

bioRxiv2017

Research Waste In ME/CFS

ObjectiveTo compare the prevalence of selective reporting in ME/CFS research areas: psychosocial versus cellular.\n\nMethodA bias appraisal was conducted on three trials (1x psychosocial and 2x cellular) to compare risk of bias in study design, selection and measurement. The primary outcome compared evidence and justifications in resolving biases by proportions (%) and ORs (Odds Ratio); the secondary outcome determined the proportion (in %) of ME/CFS grants at risk of bias.\n\nResultsNS (cellular study) was twice as likely to present evidence in resolving biases over PACE (psychosocial trial) (OR = 2.16; 65.6% vs 46. 9%), but this difference was not significant (p = 0.13). However, NS was five times more likely to justify biases over PACE (OR = 4.76; 46.9% vs 15. 6%) and this difference was significant (p = 0.0095; p < 0.05). PACE was weak in place (operational aspects 32%) and NS for data practices (37%). The proportion of grants were more biased in PACE (72%) than NS (28%) for evidence, and also more biased in PACE (86%) than NS (14%) for justifications.\n\nConclusionPsychosocial trials on ME/CFS are more likely to engage in selective reporting indicative of research waste than cellular trials. Improvements to place may help reduce these biases, whereas cellular trials may benefit from adopting more translatable data methods. However, these findings are based on two trials. Further risk of bias appraisals are needed to determine the number of trials required to make robust these findings.

scientific communication and education↗