Search

Abstract Background Trans-differentiation of human-induced pluripotent stem cells into neurons via Ngn2-induction (hiPSC-N) has become an efficient system to quickly generate neurons a likely significant advance for disease modeling and in vitro assay development. Recent single-cell interrogation of Ngn2-induced neurons, however, has revealed some similarities to unexpected neuronal lineages. Similarly, a straightforward method to generate hiPSC-derived astrocytes (hiPSC-A) for the study of neuropsychiatric disorders has also been described. Results Here, we examine the homogeneity and similarity of hiPSC-N and hiPSC-A to their in vivo counterparts, the impact of different lengths of time post Ngn2 induction on hiPSC-N (15 or 21 days), and the impact of hiPSC-N/hiPSC-A co-culture. Leveraging the wealth of existing public single-cell RNA-seq (scRNA-seq) data in Ngn2-induced neurons and in vivo data from the developing brain, we provide perspectives on the lineage origins and maturation of hiPSC-N and hiPSC-A. While induction protocols in different labs produce consistent cell type profiles, both hiPSC-N and hiPSC-A show significant heterogeneity and similarity to multiple in vivo cell fates, and both more precisely approximate their in vivo counterparts when co-cultured. Gene expression data from the hiPSC-N show enrichment of genes linked to schizophrenia (SZ) and autism spectrum disorders (ASD) as has been previously shown for neural stem cells and neurons. These overrepresentations of disease genes are strongest in our system at early times (day 15) in Ngn2-induction/maturation of neurons, when we also observe the greatest similarity to early in vivo excitatory neurons. We have assembled this new scRNA-seq data along with the public data explored here as an integrated biologist-friendly web-resource for researchers seeking to understand this system more deeply: https://nemoanalytics.org/p?l=DasEtAlNGN2&g=NES . Conclusions While overall we support the use of the investigated cellular models for the study of neuropsychiatric disease, we also identify important limitations. We hope that this work will contribute to understanding and optimizing cellular modeling for complex brain disorders.

Summary: Recent collaborative genome-wide association studies (GWAS) have identified >200 independent loci contributing to risk for schizophrenia (SCZ). The genes closest to these loci have diverse functions, supporting the potential involvement of multiple relevant biological processes, yet there is no direct evidence that individual variants are functional or directly linked to specific genes. Nevertheless, overlap with certain epigenetic marks suggest that most GWAS-implicated variants are regulatory. Based on the strength of association with SCZ and the presence of regulatory epigenetic marks, we chose one such variant near TSNARE1 and ADGRB1, rs4129585, to test for functional potential and assay differences that may drive the pathogenicity of the risk allele. We observed that the variant-containing sequence drives reporter expression in relevant neuronal populations in zebrafish. Next, we introduced each allele into human induced pluripotent cells and differentiated four isogenic clones homozygous for the risk allele and five clones homozygous for the non-risk allele into neural progenitor cells. Employing RNA sequencing, we found that the two alleles yield significant transcriptional differences in the expression of 109 genes at a false discovery rate (FDR) of

Abstract We demonstrate a compact heterodyne Laser Doppler Vibrometer (LDV) based on the realization of optical frequency shift in the silicon nitride photonic integration platform (TriPleX). We theoretically study, and experimentally evaluate two different photonic integrated optical frequency shifters (OFSs), utilizing serrodyne and single-sideband (SSB) modulation. Both OFSs employ stress-optic modulators (SOMs) based on the non-resonant piezoelectrical actuation of lead zirconate titanate (PZT) thin-films, deposited on top of the silicon nitride waveguides with a wafer-scale process. To improve the modulation bandwidth of the SOMs we investigate a novel configuration of the electrodes used for the actuation, where both electrodes are placed on top of the PZT layer. Using this top-top electrode configuration we report frequency shift of 100 kHz and 2.5 MHz, and suppression ratio of the unwanted sidebands of 22.1 dB and 39 dB, using the serrodyne and the SSB OFS, respectively. The best performing SOM structure induces 0.25π peak-to-peak sinusoidal phase-shift with 156 mW power dissipation at 2.5 MHz. We use the SSB-OFS in our compact LDV system to demonstrate vibration measurements in the kHz regime. The system comprises a dual-polarization coherent detector built in the PolyBoard platform, utilizing hybrid integration of InP photodiodes (PDs). High quality LDV performance with measurement of vibration frequencies up to several hundreds of kHz and displacement resolution of 10 pm are supported with our system.

BackgroundPlasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants.MethodsProteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics).ResultsWe identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P=3.27×10-30) and MMP-3 (β=-0.60±0.05, P=1.67×10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P=1.34×10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure.ConclusionsTaken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.

We propose a novel approach to mitigate the limitations of high-speed Passive Optical Networks (PONs) by introducing an all-optical processor. This solution addresses the escalating demand for higher data rates and improved performance in future access networks. The all-optical processor leverages optical signal processing to enhance system efficiency and reduce power consumption compared to traditional electrical methods. Specifically, we explore the processor’s dual functionality in performing all-optical equalization and chromatic dispersion compensation. Our research includes a comprehensive analysis of the processor’s design, operational principles, and system validation through extensive simulation studies, demonstrating significant improvements in signal quality and overall network performance. The results indicate that the all-optical processor not only relaxes the DSP and power requirements but also outperforms the more sophisticated digital counterpart methods.

Satellite-based QKD is currently being developed to revolutionize global cryptographic key exchange by facilitating secure communication among remote parties at a global scale. By overcoming the exponential loss of fiber transmission, satellite-to-Earth communication can seamlessly interconnect vast distances as the link budget of such links is sufficient to support QKD links. In terms of this direction, DV-QKD implementations seems to be technologically ahead since key exchange has been experimentally demonstrated to perform much more efficiently by providing key rates that are orders of magnitude higher compared to entanglement-based key exchange. However, the specific requirements to support effectively functional DV-QKD satellite-to-ground links are yet to be defined. This work attempts to define the satellite and ground segment system requirements needed in order to achieve functional QKD service for various satellites orbits (LEO, MEO, and GEO). Finite key size effects are being considered to determine the minimum block sizes that are required for secure key generation between a satellite node and a ground terminal for a single satellite pass. The atmospheric link channel is modeled with consideration of the most important degradation effects such as turbulence and atmospheric and pointing loss. Critical Tx and Rx system parameters, such as the source’s intrinsic Quantum Bit Error Rate (iQBER), the Rx telescope aperture size, and detection efficiency, were investigated in order to define the minimum requirements to establish an operation satellite-to-ground QKD link under specific assumptions. The performance of each downlink scenario was evaluated for the wavelength of 1550 nm in terms of link availability, link budget, and in the distilling of secure key volumes over time. Finally, the feasibility and requirements for distributing the collected space photons via terrestrial telecom fibers was also studied and discussed, leading to the proposal of a more futuristic WDM-enabled satellite QKD architecture. This comprehensive analysis aims to contribute to the advancement and implementation of effective satellite-based QKD systems, which can further exploit the ground fiber segment to realize converged space/terrestrial QKD networks.

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.

Abstract To overcome the ethical and technical limitations of in vivo human disease models, the broader scientific community frequently employs model organism-derived cell lines to investigate disease mechanisms, pathways, and therapeutic strategies. Despite the widespread use of certain in vitro models, many still lack contemporary genomic analysis supporting their use as a proxy for the affected human cells and tissues. Consequently, it is imperative to determine how accurately and effectively any proposed biological surrogate may reflect the biological processes it is assumed to model. One such cellular surrogate of human disease is the established mouse neural precursor cell line, SN4741, which has been used to elucidate mechanisms of neurotoxicity in Parkinson disease for over 25 years. Here, we are using a combination of classic and contemporary genomic techniques – karyotyping, RT-qPCR, single cell RNA-seq, bulk RNA-seq, and ATAC-seq – to characterize the transcriptional landscape, chromatin landscape, and genomic architecture of this cell line, and evaluate its suitability as a proxy for midbrain dopaminergic neurons in the study of Parkinson disease. We find that SN4741 cells possess an unstable triploidy and consistently exhibits low expression of dopaminergic neuron markers across assays, even when the cell line is shifted to the non-permissive temperature that drives differentiation. The transcriptional signatures of SN4741 cells suggest that they are maintained in an undifferentiated state at the permissive temperature and differentiate into immature neurons at the non-permissive temperature; however, they may not be dopaminergic neuron precursors, as previously suggested. Additionally, the chromatin landscapes of SN4741 cells, in both the differentiated and undifferentiated states, are not concordant with the open chromatin profiles of ex vivo, mouse E15.5 forebrain- or midbrain-derived dopaminergic neurons. Overall, our data suggest that SN4741 cells may reflect early aspects of neuronal differentiation but are likely not a suitable proxy for dopaminergic neurons as previously thought. The implications of this study extend broadly, illuminating the need for robust biological and genomic rationale underpinning the use of in vitro models of molecular processes.

Summary: Background: Identifying novel epigenetic signatures associated with serum immunoglobulin E (IgE) may improve our understanding of molecular mechanisms underlying asthma and IgE-mediated diseases. Methods: We performed an epigenome-wide association study using whole blood from Framingham Heart Study (FHS; n = 3,471, 46% females) participants and validated results using the Childhood Asthma Management Program (CAMP; n = 674, 39% females) and the Genetic Epidemiology of Asthma in Costa Rica Study (CRA; n = 787, 41% females). Using the closest gene to each IgE-associated CpG, we highlighted biologically plausible pathways underlying IgE regulation and analyzed the transcription patterns linked to IgE-associated CpGs (expression quantitative trait methylation loci; eQTMs). Using prior UK Biobank summary data from genome-wide association studies of asthma and allergy, we performed Mendelian randomization (MR) for causal inference testing using the IgE-associated CpGs from FHS with methylation quantitative trait loci (mQTLs) as instrumental variables. Findings: We identified 490 statistically significant differentially methylated CpGs associated with IgE in FHS, of which 193 (39.3%) replicated in CAMP and CRA (FDR < 0.05). Gene ontology analysis revealed enrichment in pathways related to transcription factor binding, asthma, and other immunological processes. eQTM analysis identified 124 cis-eQTMs for 106 expressed genes (FDR < 0.05). MR in combination with drug-target analysis revealed CTSB and USP20 as putatively causal regulators of IgE levels (Bonferroni adjusted P

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains

BackgroundAsthma is a common respiratory disorder with a highly heterogeneous nature that remains poorly understood. The objective was to use whole genome sequencing (WGS) data to identify regions of common genetic variation contributing to lung function in individuals with a diagnosis of asthma.MethodsWGS data were generated for 1,053 individuals from trios and extended pedigrees participating in the family-based Genetic Epidemiology of Asthma in Costa Rica study. Asthma affection status was defined through a physician's diagnosis of asthma, and most participants with asthma also had airway hyperresponsiveness (AHR) to methacholine. Family-based association tests for single variants were performed to assess the associations with lung function phenotypes.ResultsA genome-wide significant association was identified between baseline FEV1/FVC ratio and a single-nucleotide polymorphism in the top hit cysteine-rich secretory protein LCCL domain-containing 2 (CRISPLD2) (rs12051168; P = 3.6 × 10-8 in the unadjusted model) that retained suggestive significance in the covariate-adjusted model (P = 5.6 × 10-6). Rs12051168 was also nominally associated with other related phenotypes: baseline FEV1 (P = 3.3 × 10-3), postbronchodilator (PB) FEV1 (7.3 × 10-3), and PB FEV1/FVC ratio (P = 2.7 × 10-3). The identified baseline FEV1/FVC ratio and rs12051168 association was meta-analyzed and replicated in three independent cohorts in which most participants with asthma also had confirmed AHR (combined weighted z-score P = .015) but not in cohorts without information about AHR.ConclusionsThese findings suggest that using specific asthma characteristics, such as AHR, can help identify more genetically homogeneous asthma subgroups with genotype-phenotype associations that may not be observed in all children with asthma. CRISPLD2 also may be important for baseline lung function in individuals with asthma who also may have AHR.

Abstract Multifactorial diseases are characterized by inter-individual variation in etiology, age of onset, and penetrance. These diseases tend to be relatively common and arise from the combined action of genetic and environmental factors; however, parsing the convoluted mechanisms underlying these gene-by-environment interactions presents a significant challenge to their study and management. For neurodegenerative disorders, resolving this challenge is imperative, given the enormous health and societal burdens they impose. The mechanisms by which genetic and environmental effects may act in concert to destabilize homeostasis and elevate risk has become a major research focus in the study of common disease. Emphasis is further being placed on determining the extent to which a unifying biological principle may account for the progressively diminishing capacity of a system to buffer disease phenotypes, as risk for disease increases. Data emerging from studies of common, neurodegenerative diseases are providing insights to pragmatically connect mechanisms of genetic and environmental risk that previously seemed disparate. In this review, we discuss evidence positing inflammation as a unifying biological principle of homeostatic destabilization affecting the risk, onset, and progression of neurodegenerative diseases. Specifically, we discuss how genetic variation associated with Alzheimer disease and Parkinson disease may contribute to pro-inflammatory responses, how such underlying predisposition may be exacerbated by environmental insults, and how this common theme is being leveraged in the ongoing search for effective therapeutic interventions.

Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.

Abstract Scarless genome editing of induced pluripotent stem cells (iPSCs) is crucial for the precise modeling of genetic disease. Here we present CRISPR Del/Rei, a two-step deletion-reinsertion strategy with high editing efficiency and simple PCR-based screening that generates isogenic clones in ~ 2 months. We apply our strategy to edit iPSCs at 3 loci with only rare off target editing.

Governments and health authorities emphasize the importance of early detection of breast cancer, usually through mammography, to improve prognosis, increase therapeutic options and achieve optimum outcomes. Despite technological advances and the advent of full-field digital mammography (FFDM), diagnosis of breast abnormalities on mammographic images remains a challenge due to qualitative variations in different tissue types and densities. Highly accurate computer-aided diagnosis (CADx) systems could assist in the differentiation between normal and abnormal tissue and the classification of abnormal tissue as benign or malignant. In this paper, classical, advanced fuzzy sets and fusion techniques for image enhancement were combined with three different thresholding methods (Global, Otsu and type-2 fuzzy sets threshold) and three different classifying techniques (K-means, FCM and ANFIS) for the classification of breast masses on FFDM. The aim of this paper is to identify the performance of the advanced fuzzy sets, fuzzy sets type-2 segmentation, decisions based on K-means and FCM, and the ANFIS classifier. Sixty-three combinations were evaluated on ninety-seven digital mammographic masses (sixty-five benign and thirty-two malignant). The performance of the sixty-three combinations was evaluated by estimating the accuracy, the F1 score, and the area under the curve (AUC). LH-XWW enhancement method with Otsu thresholding and FCM classifier outperformed all other combinations with an accuracy of 95.17%, F1 score of 89.42% and AUC of 0.91. This algorithm seems to offer a promising CADx system for breast cancer diagnosis on FFDM.

The use of composite materials has seen widespread adoption in modern aerospace industry. This has been facilitated due to their favourable mechanical characteristics, namely, low weight and high stiffness and strength. For broader implementation of those materials though, the out-of-autoclave production processes have to be optimized, to allow for higher reliability of the parts produced as well as cost reduction and improved production speed. This optimization can be achieved by monitoring and controlling resin filling and curing cycles. Photonic Integrated Circuits (PICs), and, in particular, Silicon Photonics, owing to their fast response, small size, ability to operate at higher temperatures, immunity to electromagnetic interference, and compatibility with CMOS fabrication techniques, can offer sensing solutions fulfilling the requirements for composite material production using carbon fibres. In this paper, we demonstrate a passive optical temperature sensor, based on a 220 nm height Silicon-on-Insulator platform, embedded in a composite tool used for producing RTM-6 composite parts of high quality (for use in the aerospace industry). The design methodology of the photonic circuit as well as the experimental results and comparison with the industry standard thermocouples during a thermal cycling of the tool are presented. The optical sensor exhibits high sensitivity (85 pm/°C), high linearity (R2 = 0.944), and is compatible with the RTM-6 production process, operating up to 180 °C.

An abnormal cardiac action potential underlies different types of cardiac arrhythmias. Here the authors show that microRNA-365 regulates the cardiac action potential by modulating key cardiac repolarizing channels.

Background. High-flow nasal cannula (HFNC) is an oxygen delivery method shown to reduce the risk of intubation and mortality in patients with type 1 respiratory failure. The ROX-index score can predict HFNC failure. This study aims to evaluate sequential ROX-index assessments as predictors of HFNC failure and mortality. Methods. Prospective observational single-center study including all adult patients with positive SARS-CoV-2 PCR placed under HFNC from 1st November 2020 to 31st May 2021, and patients with hemodynamic instability or unable to tolerate HFNC were excluded. The primary endpoint was successful HFNC de-escalation. Results. In univariate analysis, HFNC de-escalation was associated with younger age (59.2 ± 14 vs. 67.7 ± 10.5 and p

Background: Degeneration of the serotonin system has been observed in Alzheimer’s disease (AD) and in mild cognitive impairment (MCI). In transgenic amyloid mouse models, serotonin degeneration is detected prior to widespread cortical beta-amyloid (Aβ) deposition, also suggesting that serotonin degeneration may be observed in preclinical AD. Methods: The differences in the distribution of serotonin degeneration (reflected by the loss of the serotonin transporter, 5-HTT) relative to Aβ deposition was measured with positron emission tomography in a group of individuals with MCI and a group of healthy older adults. A multi-modal partial least squares (mmPLS) algorithm was applied to identify the spatial covariance pattern between 5-HTT availability and Aβ deposition. Results: Forty-five individuals with MCI and 35 healthy older adults were studied, 22 and 27 of whom were included in the analyses who were “amyloid positive” and “amyloid negative”, respectively. A pattern of lower cortical, subcortical and limbic 5-HTT availability and higher cortical Aβ deposition distinguished the MCI from the healthy older control participants. Greater expression of this pattern was correlated with greater deficits in memory and executive function in the MCI group, not in the control group. Conclusion: A spatial covariance pattern of lower 5-HTT availability and Aβ deposition was observed to a greater extent in an MCI group relative to a control group and was associated with cognitive impairment in the MCI group. The results support the application of mmPLS to understand the neurochemical changes associated with Aβ deposition in the course of preclinical AD.

Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88) presented a critique of our recently published paper in Cell Reports entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' (Lam et al., Cell Reports, Vol. 21, 2017, 2597-2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229-237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from 'inflation in the FDR [false discovery rate]', as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88), and are not 'more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence'.

Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P

ObjectiveTo identify genetic differences among siblings with a family history of idiopathic transverse myelitis (ITM).MethodsWe compared whole-exome sequencing (WES) on germline samples from the 2 affected sisters with ITM with 3 of their healthy siblings.ResultsThe 2 sisters with ITM both had acute onset of sensory loss in the legs, weakness, and bowel/bladder dysfunction. The first developed ITM at age 15 years with a clinical nadir of complete paralysis, which slowly recovered over a few years. MRI demonstrated a persistent T2 lesion in the lower thoracic cord. The second developed ITM at age 50 years with a nadir of sensory loss from T6 down and paraparesis in the legs, associated with an MRI lesion at T6. She also made a partial recovery with treatment. Both sisters are homozygous for a missense variant in VPS37A (c.700C>A, p.Leu234Ile) identified by WES. We performed targeted sequencing of VPS37A in an additional 86 samples from patients with ITM and 175 with other diseases to investigate the p.Leu234Ile variant. We identified another patient with ITM homozygous for the same rare variant. No patients with multiple sclerosis, neuromyelitis optica, other neurologic conditions, or any healthy controls in public databases were homozygous for this variant.ConclusionsA rare missense variant in VPS37A may predispose to development of ITM. Further studies are necessary to determine the frequency of this variant in the patient population and the mechanism through which it contributes to the risk of disease.

ObjectiveWe sought to identify rare variants influencing brain imaging phenotypes in the Framingham Heart Study by performing whole genome sequence association analyses within the Trans-Omics for Precision Medicine Program.MethodsWe performed association analyses of cerebral and hippocampal volumes and white matter hyperintensity (WMH) in up to 2,180 individuals by testing the association of rank-normalized residuals from mixed-effect linear regression models adjusted for sex, age, and total intracranial volume with individual variants while accounting for familial relatedness. We conducted gene-based tests for rare variants using (1) a sliding-window approach, (2) a selection of functional exonic variants, or (3) all variants.ResultsWe detected new loci in 1p21 for cerebral volume (minor allele frequency [MAF] 0.005, p = 10-8) and in 16q23 for hippocampal volume (MAF 0.05, p = 2.7 × 10-8). Previously identified associations in 12q24 for hippocampal volume (rs7294919, p = 4.4 × 10-4) and in 17q25 for WMH (rs7214628, p = 2.0 × 10-3) were confirmed. Gene-based tests detected associations (p ≤ 2.3 × 10-6) in new loci for cerebral (5q13, 8p12, 9q31, 13q12-q13, 15q24, 17q12, 19q13) and hippocampal volumes (2p12) and WMH (3q13, 4p15) including Alzheimer disease- (UNC5D) and Parkinson disease-associated genes (GBA). Pathway analyses evidenced enrichment of associated genes in immunity, inflammation, and Alzheimer disease and Parkinson disease pathways.ConclusionsWhole genome sequence-wide search reveals intriguing new loci associated with brain measures. Replication of novel loci is needed to confirm these findings.

Abstract Depression in late-life is associated with increased risk of cognitive decline and development of all-cause dementia. The neurobiology of late-life depression (LLD) may involve both neurochemical and neurodegenerative mechanisms that are common to depression and dementia. Transgenic amyloid mouse models show evidence of early degeneration of monoamine systems. Informed by these preclinical data, the hypotheses were tested that a spatial covariance pattern of higher beta-amyloid (Aβ) and lower serotonin transporter availability (5-HTT) in frontal, temporal, and parietal cortical regions would distinguish LLD patients from healthy controls and the expression of this pattern would be associated with greater depressive symptoms. Twenty un-medicated LLD patients who met DSM-V criteria for major depression and 20 healthy controls underwent PET imaging with radiotracers for Aβ ([11C]-PiB) and 5-HTT ([11C]-DASB). A voxel-based multi-modal partial least squares (mmPLS) algorithm was applied to the parametric PET images to determine the spatial covariance pattern between the two radiotracers. A spatial covariance pattern was identified, including higher Aβ in temporal, parietal and occipital cortices associated with lower 5-HTT in putamen, thalamus, amygdala, hippocampus and raphe nuclei (dorsal, medial and pontine), which distinguished LLD patients from controls. Greater expression of this pattern, reflected in summary 5-HTT/Aβ mmPLS subject scores, was associated with higher levels of depressive symptoms. The mmPLS method is a powerful approach to evaluate the synaptic changes associated with AD pathology. This spatial covariance pattern should be evaluated further to determine whether it represents a biological marker of antidepressant treatment response and/or cognitive decline in LLD patients.

The recent advances in creating pluripotent stem cells from somatic cells and differentiating them into a variety of cell types is allowing us to study them without the caveats associated with disease-related changes. We generated induced Pluripotent Stem Cells (iPSCs) from eight Alzheimer’s disease (AD) patients and six controls and used lentiviral delivery to differentiate them into excitatory glutamatergic neurons. We then performed RNA sequencing on these neurons and compared the Alzheimer’s and control transcriptomes. We found that 621 genes show differences in expression levels at adjusted p < 0.05 between the case and control derived neurons. These genes show significant overlap and directional concordance with genes reported from a single-cell transcriptome study of AD patients; they include five genes implicated in AD from genome-wide association studies and they appear to be part of a larger functional network as indicated by an excess of interactions between them observed in the protein–protein interaction database STRING. Exploratory analysis with Uniform Manifold Approximation and Projection (UMAP) suggests distinct clusters of patients, based on gene expression, who may be clinically different. Our research outcomes will enable the precise identification of distinct biological subtypes among individuals with Alzheimer’s disease, facilitating the implementation of tailored precision medicine strategies.

The first-, second-, and third-order molecular nonlinear optical properties, including two-photon absorption of a series of derivatives, involving two dithienylethene (DTE) groups connected by several molecular linkers (bis(ethylene-1,2-dithiolato)Ni- (NiBDT), naphthalene, quasilinear oligothiophene chains), are investigated by employing density functional theory (DFT). These properties can be efficiently controlled by DTE switches, in connection with light of appropriate frequency. NiBDT, as a linker, is associated with a greater contrast, in comparison to naphthalene, between the first and second hyperpolarizabilities of the “open–open” and the “closed–closed” isomers. This is explained by invoking the low-lying excited states of NiBDT. It is shown that the second hyperpolarizability can be used as an index, which follows the structural changes induced by photochromism. Assuming a Förster type transfer mechanism, the intramolecular excited-state energy transfer (EET) mechanism is studied. Two important parameters related to this are computed: the electronic coupling (VDA) between the donor and acceptor fragments as well as the overlap between the absorption and emission spectra of the donor and acceptor groups. NiBDT as a linker is associated with a low electronic coupling, VDA, value. We found that VDA is affected by molecular geometry. Our results predict that the linker strongly influences the communication between the open–closed DTE groups. The sensitivity of the molecular nonlinear optical properties could assist with identification of molecular isomers.

This corrects the article DOI: 10.1038/mp.2016.244.

Here, we present a large (n = 107,207) genome-wide association study (GWAS) of general cognitive ability ("g"), further enhanced by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with general cognitive ability. Results showed significant enrichment for genes causing Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis implicated the biological processes of neurogenesis and synaptic regulation, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker, and LY97241, a potassium channel inhibitor. Transcriptome-wide and epigenome-wide analysis revealed that the implicated loci were enriched for genes expressed across all brain regions (most strongly in the cerebellum). Enrichment was exclusive to genes expressed in neurons but not oligodendrocytes or astrocytes. Finally, we report genetic correlations between cognitive ability and disparate phenotypes including psychiatric disorders, several autoimmune disorders, longevity, and maternal age at first birth.