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Thompson, P.

Publications and source records attributed to Thompson, P..

At least 37 records · Page 2Linked to original sources

Circular RNA profiling identifies circ5078 as a BMPR2-derived regulator of endothelial translation

Germline loss-of-function BMPR2 mutations are the leading genetic cause of pulmonary arterial hypertension (PAH) and are strongly linked to aberrant endothelial proliferation and impaired translational stress responses. While these effects are generally attributed to a loss of the type-II bone morphogenetic protein receptor (BMPR-II), we used circular RNA profiling to identify circ5078 as a new functional RNA derived from exon 12 of the BMPR2 gene. circ5078 and linear BMPR2 mRNA exert opposing effects on endothelial proliferation and stress granule formation, driving impaired stress responses in PAH patient-derived endothelial cells that are deficient in linear BMPR2 transcripts, but not circ5078. Rebalancing circular to linear transcript abundance by circ5078 depletion rescued stress granule formation in patient-derived endothelial cells, independent of BMPR-II protein levels. Polysome analysis demonstrated a reduction in free ribosomal subunits with the depletion of either linear or circular BMPR2 transcripts, and an accumulation of 80S monosomes exclusively with linear BMPR2 mRNA loss. These effects did not impact global protein synthesis or stress-induced eIF2 phosphorylation, but did alter the translational efficiency of multiple genes, including a group of nuclear encoded, mitochondrial ribosome proteins that were translationally enhanced with circ5078 silencing. Endothelial circ5078 depletion increased the efficiency of oxidative metabolism while reducing mitochondrial spare capacity, providing a potential link between mitochondrial function, proliferation and translational stress responses. Together, these findings reveal interdependent roles for linear and circular BMPR2 transcripts as functional contributors to the endothelial phenotype of PAH.

molecular biology↗

Identifying signals of memory from observations of animal movements in Plato's cave

Incorporating memory (i.e., some notion of familiarity or experience with the landscape) into models of animal movement is a rising challenge in the field of movement ecology. The recent proliferation of new methods offers new opportunities to understand how memory influences movement. However, there are no clear guidelines for practitioners wishing to parameterize the effects of memory on moving animals. We review approaches for incorporating memory into Step-Selection Analyses (SSAs), a frequently used movement modeling framework. Memory-informed SSAs can be constructed by including spatial-temporal covariates (or maps) that define some aspect of familiarity (e.g., whether, how often, or how long ago the animal visited different spatial locations) derived from long-term telemetry data. We demonstrate how various familiarity covariates can be included in SSAs using a series of coded examples in which we fit models to wildlife tracking data from a wide range of taxa. We discuss how these different approaches can be used to address questions related to whether and how animals use information from past experiences to inform their future movements. We also highlight challenges and decisions that the user must make when applying these methods to their tracking data. By reviewing different approaches and providing code templates for their implementation, we hope to inspire practitioners to investigate further the importance of memory in animal movements using wildlife tracking data.

ecology↗

The Influence of Brain MRI Defacing Algorithms on Brain-Age Predictions via 3D Convolutional Neural Networks

In brain imaging research, it is becoming standard practice to remove the face from the individuals 3D structural MRI scan to ensure data privacy standards are met. Face removal - or defacing - is being advocated for large, multi-site studies where data is transferred across geographically diverse sites. Several methods have been developed to limit the loss of important brain data by accurately and precisely removing non-brain facial tissue. At the same time, deep learning methods such as convolutional neural networks (CNNs) are increasingly being used in medical imaging research for diagnostic classification and prognosis in neurological diseases. These neural networks train predictive models based on patterns in large numbers of images. Because of this, defacing scans could remove informative data. Here, we evaluated 4 popular defacing methods to identify the effects of defacing on brain age prediction - a common benchmarking task of predicting a subjects chronological age from their 3D T1-weighted brain MRI. We compared brain-age calculations using defaced MRIs to those that were directly brain extracted, and those with both brain and face. Significant differences were present when comparing average per-subject error rates between algorithms in both the defaced brain data and the extracted facial tissue. Results also indicated brain age accuracy depends on defacing and the choice of algorithm. In a secondary analysis, we also examined how well comparable CNNs could predict chronological age from the facial region only (the extracted portion of the defaced image), as well as visualize areas of importance in facial tissue for predictive tasks using CNNs. We obtained better performance in age prediction when using the extracted face portion alone than images of the brain, suggesting the need for caution when defacing methods are used in medical image analysis.

bioinformatics↗

The Genetic Heterogeneity of Multimodal Human Brain Age

The complex biological mechanisms underlying human brain aging remain incompletely understood, involving multiple body organs and chronic diseases. In this study, we used multimodal magnetic resonance imaging and artificial intelligence to examine the genetic architecture of the brain age gap (BAG) derived from gray matter volume (GM-BAG, N=31,557 European ancestry), white matter microstructure (WM-BAG, N=31,674), and functional connectivity (FC-BAG, N=32,017). We identified sixteen genomic loci that reached genome-wide significance (P-value<5x10-8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG showed the highest heritability enrichment for genetic variants in conserved regions, whereas WM-BAG exhibited the highest heritability enrichment in the 5 untranslated regions; oligodendrocytes and astrocytes, but not neurons, showed significant heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several exposure variables on brain aging, such as type 2 diabetes on GM-BAG (odds ratio=1.05 [1.01, 1.09], P-value=1.96x10-2) and AD on WM-BAG (odds ratio=1.04 [1.02, 1.05], P-value=7.18x10-5). Overall, our results provide valuable insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at the MEDICINE knowledge portal: https://labs.loni.usc.edu/medicine.

genetics↗

Oncomodulin Regulates Spontaneous Calcium Signaling and Maturation of Afferent Innervation in Cochlear Outer Hair Cells

Cochlear outer hair cells (OHCs) are responsible for the exquisite frequency selectivity and sensitivity of mammalian hearing. During development, the maturation of OHC afferent connectivity is refined by coordinated spontaneous Ca2+ activity in both sensory and non-sensory cells. Calcium signaling in neonatal OHCs can be modulated by Oncomodulin (OCM, {beta}-parvalbumin), an EF-hand calcium-binding protein. Here, we investigated whether OCM regulates OHC spontaneous Ca2+ activity and afferent connectivity during development. Using a genetically encoded Ca2+ sensor (GCaMP6s) expressed in OHCs in wild-type (Ocm+/+) and Ocm knockout (Ocm-/-) littermates, we found increased spontaneous Ca2+ activity and upregulation of purinergic receptors in OHCs from GCaMP6s Ocm-/- cochlea immediately following birth. The afferent synaptic maturation of OHCs was delayed in the absence of OCM, leading to an increased number of ribbon synapses and afferent fibers on GCaMP6s Ocm-/- OHCs before hearing onset. We propose that OCM regulates the spontaneous Ca2+ signaling in the developing cochlea and the maturation of OHC afferent innervation.

developmental biology↗

Genetic, clinical underpinnings of subtle early brain change along Alzheimer's dimensions

Alzheimers disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised clustering technique known as Surreal-GAN, through which we identified two dominant dimensions of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE {varepsilon}4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE {varepsilon}4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction - driven by genes different from APOE - which may collectively contribute to the early pathogenesis of AD.

bioengineering↗

Predicting Dementia Severity by Merging Anatomical and Diffusion MRI with Deep 3D Convolutional Neural Networks

Machine learning methods have been used for over a decade for staging and subtyping a variety of brain diseases, offering fast and objective methods to classify neurodegenerative diseases such as Alzheimers disease (AD). Deep learning models based on convolutional neural networks (CNNs) have also been used to infer dementia severity and predict future clinical decline. Most CNN-based deep learning models use T1-weighted brain MRI scans to identify predictive features for these tasks. In contrast, we examine the added value of diffusion-weighted MRI (dMRI) - a variant of MRI, sensitive to microstructural tissue properties - as an additional input in CNN-based models of dementia severity. dMRI is sensitive to microstructural brain abnormalities not evident on standard anatomical MRI. By training CNNs on combined anatomical and diffusion MRI, we hypothesize that we could boost performance when predicting widely-used clinical assessments of dementia severity, such as individuals scores on the ADAS11, ADAS13, and MMSE (mini-mental state exam) clinical scales. For benchmarking, we evaluate CNNs that use T1-weighted MRI and dMRI to estimate "brain age" - the task of predicting a persons chronological age from their neuroimaging data. To assess which dMRI-derived maps were most beneficial, we computed DWI-derived diffusion tensor imaging (DTI) maps of mean and radial diffusivity (MD/RD), axial diffusivity (AD) and fractional anisotropy (FA) for 1198 elderly subjects (age: 74.35 +/- 7.74 yrs.; 600 F/598 M, with a distribution of 636 CN/421 MCI/141 AD) from the Alzheimers Disease Neuroimaging Initiative (ADNI). We tested both 2D Slice CNN and 3D CNN neural network models for the above predictive tasks. Our results suggest that for at least some deep learning architectures, diffusion-weighted MRI may enhance performance for several AD-relevant deep learning tasks relative to using T1-weighted images alone.

neuroscience↗

Rare CNVs and phenome-wide profiling: a tale of brain-structural divergence and phenotypical convergence

Copy number variations (CNVs) are rare genomic deletions and duplications that can exert profound effects on brain and behavior. Previous reports of pleiotropy in CNVs imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, studies to date have primarily examined single CNV loci in small clinical cohorts. It remains unknown how distinct CNVs escalate the risk for the same developmental and psychiatric disorders. Here, we quantitatively dissect the impact on brain organization and behavioral differentiation across eight key CNVs. In 534 clinical CNV carriers from multiple sites, we explored CNV-specific brain morphology patterns. We extensively annotated these CNV-associated patterns with deep phenotyping assays through the UK Biobank resource. Although the eight CNVs cause disparate brain changes, they are tied to similar phenotypic profiles across [~]1000 lifestyle indicators. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders.

genetics↗

Somatosensory Cortical Signature of Facial Nociception and Vibrotactile Touch Induced Analgesia

Pain relief by vibrotactile touch is a common human experience. Previous neurophysiological investigations in animals focused on spinal mechanisms while human studies suggested the involvement of supraspinal mechanisms. Here we asked whether and how the primary somatosensory cortex (S1) is involved in touch induced analgesia. We discovered that in mice, vibrotactile reafferent signals from self-generated whisking significantly reduce facial nociception, which is abolished by specifically blocking touch transmission from thalamus to the barrel cortex (S1B). The presence of whisking altered nociceptive signal processing in S1B neurons. Intrinsic manifold analysis of S1B population activity revealed that whisking pushes the transition of neural state induced by noxious stimuli towards the state encoding non-nocifensive actions. Thus, S1B integrates facial tactile and noxious signals to enable touch mediated analgesia. TeaserVibrotactile signals modulate barrel cortex population dynamics during touch mediated facial analgesia

neuroscience↗

Kinetics of the inflammatory response during experimental Babesia rossi infection of beagle dogs

Babesia rossi causes severe morbidity and mortality in dogs in sub-Saharan Africa, and the complications associated with this disease are likely caused by an unfocused, excessive inflammatory response. During this experimental B. rossi study we investigated inflammatory marker and cytokine kinetics during infection and after treatment. We aimed to determine whether infectious dose and treatment would influence the progression of the inflammatory response and clinical disease. Five healthy male beagle dogs were infected with B. rossi, three with a high infectious dose (HD group) and two with a low infectious dose (LD group). Clinical examination, complete blood count (CBC) and C-reactive protein (CRP) were determined daily. Cytokines were quantified on stored plasma collected during the study, using a canine specific cytokine magnetic bead panel (Milliplex(C)). The experiment was terminated when predetermined endpoints were reached. Parasitemia occurred on day 1 and 3 in the HD group and LD group respectively. The rate of increase in parasitemia in the HD group was significantly faster than that seen in the LD group. Significant differences were found in heart rate, blood pressure, interferon gamma (INF{gamma}), keratinocyte chemoattractant (KC), INF{gamma}-induced protein 10 (IP10), granulocyte-macrophage colony-stimulating factor (GM-CSF), monocyte chemoattractant protein 1 (MCP1), tumor necrosis factor alpha (TNF), interleukin 2 (IL-2), IL-6, IL-7, IL-8, IL-10 IL-15, IL-18, CRP, neutrophils and monocytes between groups at multiple time points during the course of the infection. Our findings suggest that the initiation of inflammation occurs before the onset of clinical disease in B. rossi infection and infectious dose influences the onset of the inflammatory response. Treatment not only fails to curb the inflammatory response but may enhance it. Finally, we found that there is an imbalance in pro/anti-inflammatory cytokine concentrations during infection which may promote parasite replication.

immunology↗

Sterol scarcity primes p38 immune defenses through a TIR-1/SARM1 phase transition

Intracellular signaling regulators can be concentrated into membrane-free, higher-ordered protein assemblies to initiate protective responses during stress -- a process known as phase transition. Here, we show that a phase transition of the Caenorhabditis elegans Toll/interleukin-1 receptor domain protein (TIR-1), an NAD+ glycohydrolase homologous to mammalian sterile alpha and TIR motif-containing 1 (SARM1), underlies p38 PMK-1 immune pathway activation in C. elegans intestinal epithelial cells. Through visualization of fluorescently labeled TIR-1/SARM1 protein, we demonstrate for the first time that physiologic stresses, both pathogen and non-pathogen, induce multimerization of TIR-1/SARM1 into visible puncta within intestinal epithelial cells. In vitro enzyme kinetic analyses revealed that, like mammalian SARM1, the NAD+ glycohydrolase activity of C. elegans TIR-1 is dramatically potentiated by protein oligomerization and a phase transition. Accordingly, C. elegans with genetic mutations that specifically block either multimerization or the NAD+ glycohydrolase activity of TIR-1/SARM1 fail to induce p38 PMK phosphorylation, are unable to increase immune effector expression, and are dramatically susceptible to bacterial infection. Finally, we demonstrate that the TIR-1/SARM1 phase transition is modified by dietary cholesterol, revealing a new adaptive response that allows a metazoan host to anticipate pathogen threats during micronutrient deprivation, a time of relative susceptibility to infection. When cholesterol is limited, TIR-1/SARM1 oligomerizes into puncta in intestinal epithelial cells and engages its NAD+ glycohydrolase activity, which increases p38 PMK-1 phosphorylation, and primes immune effector induction in a manner that promotes pathogen clearance from the intestine during a subsequent infection. Thus, a phase transition of TIR-1/SARM1 as a prerequisite for its NAD+ glycohydrolase activity is strongly conserved across millions of years of evolution and is essential for diverse physiological processes in multiple cell types.

immunology↗

Brain Laterality Dynamics Support Human Cognition

Hemispheric lateralization constitutes a core architectural principle of human brain organization underlying cognition, often argued to represent a stable, trait-like feature. However, emerging evidence underlines the inherently dynamic nature of brain networks, in which time-resolved alterations in functional lateralization remain uncharted. Integrating dynamic network approaches with the concept of hemispheric laterality, we map the spatiotemporal architecture of whole-brain lateralization in a large sample of high-quality resting-state fMRI data (N=991, Human Connectome Project). We reveal distinct laterality dynamics across lower-order sensorimotor systems and higher-order associative networks. Specifically, we expose two aspects of the laterality dynamics: laterality fluctuations, defined as the standard deviation of laterality time series, and laterality reversal, referring to the number of zero-crossings in laterality time series. These two measures are associated with moderate and extreme changes in laterality over time, respectively. While laterality fluctuations depict positive association with language function and cognitive flexibility, laterality reversal shows a negative association with the same neurocognitive factors. These opposing interactions indicate a dynamic balance between intra- and inter-hemispheric communication, i.e., segregation and integration of information across hemispheres. Furthermore, in their time-resolved laterality index, the default-mode and language networks correlate negatively with visual/sensorimotor and attention networks, indicating flexible while parallel processing capabilities that are linked to better out-of-scanner cognitive performance. Finally, the laterality dynamics correlate with regional metabolism and structural connectivity and showed significant heritability. Our results provide insights into the adaptive nature of the lateralized brain and new perspectives for future studies of human cognition, genetics and brain disorders.

neuroscience↗

Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study

IntroductionCortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCN) constructed from CT and SA may represent developmental associations, or unique interactions between brain regions, possibly influenced by a common causal antecedent. The ENIGMA-PGC PTSD Working Group aggregated PTSD and control subjects data from 29 cohorts in five countries (n=3439). MethodsUsing Destrieux Atlas, we built SCNs and compared centrality measures between PTSD subjects and controls. Centrality is a graph theory measure derived using SCN. ResultsNotable nodes with higher CT-based centrality in PTSD compared to controls were left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. We found sex-based centrality differences in bilateral frontal lobe regions, left anterior cingulate, left superior occipital cortex and right ventromedial prefrontal cortex (vmPFC). Comorbid PTSD and MDD showed higher CT-based centrality in the right anterior cingulate gyrus, right parahippocampal gyrus and lower SA-based centrality in left insular gyrus. ConclusionUnlike previous studies with smaller sample sizes ([&le;]318), our study found differences in centrality measures using a sample size of 3439 subjects. This is the first cross-sectional study to examine SCN interactions with age, sex, and comorbid MDD. Although limited to group level inferences, centrality measures offer insights into a nodes relationship to the entire functional connectome unlike approaches like seed-based connectivity or independent component analysis. Nodes having higher centrality have greater structural or functional connections, lending them invaluable for translational treatments like neuromodulation.

neuroscience↗

A Liquid-to-Solid Phase Transition Enhances the Catalytic Activity of SARM1

Sterile alpha and toll/interleukin receptor (TIR) motif-containing protein 1 (SARM1) is a neuronally expressed NAD+ glycohydrolase whose activity is increased in response to various stressors. The consequent depletion of NAD+ triggers axonal degeneration (i.e., Wallerian degeneration), which is a characteristic feature of neurological diseases, including peripheral neuropathies and traumatic brain injury. Notably, SARM1 knockout mice show minimal degeneration in models of peripheral neuropathy and traumatic brain injury, making SARM1 a promising therapeutic target. However, the development of SARM1 inhibitors has been challenging as the purified enzyme is largely inactive. Herein, we report that SARM1 activity is increased [~]2000-fold by a liquid-to-solid phase transition. These findings provide critical insights into SARM1 biochemistry with important implications for the situation in vivo. Moreover, they will facilitate the discovery of novel SARM1-targeted therapeutics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=71 SRC="FIGDIR/small/272377v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@d9c222org.highwire.dtl.DTLVardef@588637org.highwire.dtl.DTLVardef@1d3a3d4org.highwire.dtl.DTLVardef@1a8e058_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

Site-Specific Incorporation of Citrulline into Proteins in Mammalian Cells

Citrullination is a post-translational modification (PTM) of arginine that is crucial for several physiological processes, including gene regulation and neutrophil extracellular trap formation. Despite recent advances, studies of protein citrullination remain challenging due to the difficulty of accessing proteins homogeneously citrullinated at a specific site. Herein, we report a novel technology that enables the site-specific incorporation of citrulline (Cit) into proteins in mammalian cells. This approach exploits an E. coli-derived engineered leucyl tRNA synthetase-tRNA pair that incorporates a photocaged-citrulline (SM60) into proteins in response to a nonsense codon. Subsequently, SM60 is readily converted to Cit with light in vitro and in living cells. To demonstrate the utility of the method, we biochemically characterized the effect of incorporating Cit at two known autocitrullination sites in Protein Arginine Deiminase 4 (PAD4, R372 and R374) and showed that the R372Cit and R374Cit mutants are 181- and 9-fold less active than the wild-type enzyme. This powerful technology possesses immense potential to decipher the biology of citrullination.

biochemistry↗

The role of CAPG in molecular communication between the embryo and the uterine endometrium: Is its function conserved in species with different implantation strategies?

During the pre-implantation period of pregnancy in eutherian mammals, changes to the uterine endometrium are required (both at the transcriptional and protein level) to facilitate the endometrium becoming receptive to an implanting embryo. We know that the developing conceptus (embryo and extraembryonic membranes) produces proteins during this developmental stage. We hypothesised that this common process in early pregnancy in eutheria may be facilitated by highly conserved conceptus-derived proteins such as macrophage capping protein CAPG. More specifically, we propose that CAPG may share functionality in modifying the transcriptome of the endometrial epithelial cells to facilitate receptivity to implantation in species with different implantation strategies, such as human and bovine. A recombinant bovine form of CAPG (91% sequence identity between bovine and human) was produced and bovine endometrial epithelial (bEECs) and stromal (bESCs) cells and human endometrial epithelial cells (hEECs) were cultured for 24 h with or without rbCAPG. RNA sequencing and quantitative real-time PCR analysis was used to assess the transcriptional response to rbCAPG (Control, vehicle, CAPG 10, 100, 1000 ng/ml: n=3 biological replicates per treatment per species). Treatment of bEECs with CAPG resulted in changes to 1052 transcripts (629 increased and 423 decreased) compared to vehicle controls, including those previously only identified as regulated by interferon-tau, the pregnancy recognition signal in cattle. Treatment of hEECs with bovine CAPG increased expression of transcripts previously known to interact with CAPG in different systems (CAPZB, CAPZA2, ADD1 and ADK) compared with vehicle controls (P<0.05). In conclusion, we have demonstrated that CAPG, a highly conserved protein in eutherian mammals elicits a transcriptional response in the endometrial epithelium in two species with different implantation strategies that may facilitate uterine receptivity.

physiology↗

Structural Brain Imaging Studies Offer Clues about the Effects of the Shared Genetic Etiology among Neuropsychiatric Disorders

BackgroundGenomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. MethodsFrom the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD) and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. ResultsThe SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.49). ConclusionsOur results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

neuroscience↗

Beyond SNP Heritability: Polygenicity and Discoverability of Phenotypes Estimated with a Univariate Gaussian Mixture Model

Of signal interest in the genetics of human traits is estimating their polygenicity (the proportion of causally associated single nucleotide polymorphisms (SNPs)) and the discoverability (or effect size variance) of the causal SNPs. Narrow-sense heritability is proportional to the product of these quantities. We present a basic model, using detailed linkage disequilibrium structure from an extensive reference panel, to estimate these quantities from genome-wide association studies (GWAS) summary statistics for SNPs with minor allele frequency >1%. We apply the model to diverse phenotypes and validate the implementation with simulations. We find model polygenicities ranging from [~=] 2 x 10-5 to [~=] 4 x 10-3, with discoverabilities similarly ranging over two orders of magnitude. A power analysis allows us to estimate the proportions of phenotypic variance explained additively by causal SNPs at current sample sizes, and map out sample sizes required to explain larger portions of additive SNP heritability. The model also allows for estimating residual inflation.

genetics↗