Publications by authors named "Fabio Macciardi"

107 Publications

Plasma Sphingomyelins in Late-Onset Alzheimer's Disease.

J Alzheimers Dis 2021 ;83(3):1161-1171

Department of Neurology, University of California, Irvine, Irvine, CA, USA.

Background: Altered plasma levels of sphingolipids, including sphingomyelins (SM), have been found in mouse models of Alzheimer's disease (AD) and in AD patient plasma samples.

Objective: This study assesses fourteen plasma SM species in a late-onset AD (LOAD) patient cohort (n = 138).

Methods: Specimens from control, preclinical, and symptomatic subjects were analyzed using targeted mass-spectrometry-based metabolomic methods.

Results: Total plasma SM levels were not significantly affected by age or cognitive status. However, one metabolite that has been elevated in manifest AD in several recent studies, SM OHC14:1, was reduced significantly in pre-clinical AD and MCI relative to normal controls.

Conclusion: We recommend additional comprehensive plasma lipidomics in experimental and clinical biospecimens related to LOAD that might advance the utility of plasma sphingomyelin levels in molecular phenotyping and interpretations of pathobiological mechanisms.
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http://dx.doi.org/10.3233/JAD-200871DOI Listing
January 2021

Sparse deep neural networks on imaging genetics for schizophrenia case-control classification.

Hum Brain Mapp 2021 Jun 16;42(8):2556-2568. Epub 2021 Mar 16.

Department of Computer Science, Georgia State University, Atlanta, Georgia, USA.

Deep learning methods hold strong promise for identifying biomarkers for clinical application. However, current approaches for psychiatric classification or prediction do not allow direct interpretation of original features. In the present study, we introduce a sparse deep neural network (DNN) approach to identify sparse and interpretable features for schizophrenia (SZ) case-control classification. An L -norm regularization is implemented on the input layer of the network for sparse feature selection, which can later be interpreted based on importance weights. We applied the proposed approach on a large multi-study cohort with gray matter volume (GMV) and single nucleotide polymorphism (SNP) data for SZ classification. A total of 634 individuals served as training samples, and the classification model was evaluated for generalizability on three independent datasets of different scanning protocols (N = 394, 255, and 160, respectively). We examined the classification power of pure GMV features, as well as combined GMV and SNP features. Empirical experiments demonstrated that sparse DNN slightly outperformed independent component analysis + support vector machine (ICA + SVM) framework, and more effectively fused GMV and SNP features for SZ discrimination, with an average error rate of 28.98% on external data. The importance weights suggested that the DNN model prioritized to select frontal and superior temporal gyrus for SZ classification with high sparsity, with parietal regions further included with lower sparsity, echoing previous literature. The results validate the application of the proposed approach to SZ classification, and promise extended utility on other data modalities and traits which ultimately may result in clinically useful tools.
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http://dx.doi.org/10.1002/hbm.25387DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8090768PMC
June 2021

The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area.

Cereb Cortex 2021 03;31(4):1873-1887

Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.

Structural brain changes along the lineage leading to modern Homo sapiens contributed to our distinctive cognitive and social abilities. However, the evolutionarily relevant molecular variants impacting key aspects of neuroanatomy are largely unknown. Here, we integrate evolutionary annotations of the genome at diverse timescales with common variant associations from large-scale neuroimaging genetic screens. We find that alleles with evidence of recent positive polygenic selection over the past 2000-3000 years are associated with increased surface area (SA) of the entire cortex, as well as specific regions, including those involved in spoken language and visual processing. Therefore, polygenic selective pressures impact the structure of specific cortical areas even over relatively recent timescales. Moreover, common sequence variation within human gained enhancers active in the prenatal cortex is associated with postnatal global SA. We show that such variation modulates the function of a regulatory element of the developmentally relevant transcription factor HEY2 in human neural progenitor cells and is associated with structural changes in the inferior frontal cortex. These results indicate that non-coding genomic regions active during prenatal cortical development are involved in the evolution of human brain structure and identify novel regulatory elements and genes impacting modern human brain structure.
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http://dx.doi.org/10.1093/cercor/bhaa327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7945014PMC
March 2021

Functional impairment of cortical AMPA receptors in schizophrenia.

Schizophr Res 2020 Jun 5. Epub 2020 Jun 5.

Department of Psychiatry & Human Behavior, University of California Irvine, CA 92697, USA. Electronic address:

Clinical and preclinical studies suggest that some of the behavioral alterations observed in schizophrenia (SZ) may be mechanistically linked to synaptic dysfunction of glutamatergic signaling. Recent genetic and proteomic studies suggest alterations of cortical glutamate receptors of the AMPA-type (AMPARs), which are the predominant ligand-gated ionic channels of fast transmission at excitatory synapses. The impact of gene and protein alterations on the electrophysiological activity of AMPARs is not known in SZ. In this proof of principle work, using human postmortem brain synaptic membranes isolated from the dorsolateral prefrontal cortex (DLPFC), we combined electrophysiological analysis from microtransplanted synaptic membranes (MSM) with transcriptomic (RNA-Seq) and label-free proteomics data in 10 control and 10 subjects diagnosed with SZ. We observed in SZ a reduction in the amplitude of AMPARs currents elicited by kainate, an agonist of AMPARs that blocks the desensitization of the receptor. This reduction was not associated with protein abundance but with a reduction in kainate's potency to activate AMPARs. Electrophysiologically-anchored dataset analysis (EDA) was used to identify synaptosomal proteins that linearly correlate with the amplitude of the AMPARs responses, gene ontology functional annotations were then used to determine protein-protein interactions. Protein modules associated with positive AMPARs current increases were downregulated in SZ, while protein modules that were upregulated in SZ were associated with decreased AMPARs currents. Our results indicate that transcriptomic and proteomic alterations, frequently observed in the DLPFC in SZ, converge at the synaptic level producing a functional electrophysiological impairment of AMPARs.
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http://dx.doi.org/10.1016/j.schres.2020.03.037DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718399PMC
June 2020

Metabolic correlates of prevalent mild cognitive impairment and Alzheimer's disease in adults with Down syndrome.

Alzheimers Dement (Amst) 2020 5;12(1):e12028. Epub 2020 Apr 5.

Taub Institute for Research in Alzheimer's Disease and the Aging Brain Columbia University New York New York USA.

Introduction: Disruption of metabolic function is a recognized feature of late onset Alzheimer's disease (LOAD). We sought to determine whether similar metabolic pathways are implicated in adults with Down syndrome (DS) who have increased risk for Alzheimer's disease (AD).

Methods: We examined peripheral blood from 292 participants with DS who completed baseline assessments in the Alzheimer's Biomarkers Consortium-Down Syndrome (ABC-DS) using untargeted mass spectrometry (MS). Our sample included 38 individuals who met consensus criteria for AD (DS-AD), 43 who met criteria for mild cognitive impairment (DS-MCI), and 211 who were cognitively unaffected and stable (CS).

Results: We measured relative abundance of 8,805 features using MS and 180 putative metabolites were differentially expressed (DE) among the groups at false discovery rate-corrected < 0.05. From the DE features, a nine-feature classifier model classified the CS and DS-AD groups with receiver operating characteristic area under the curve (ROC AUC) of 0.86 and a two-feature model classified the DS-MCI and DS-AD groups with ROC AUC of 0.88. Metabolite set enrichment analysis across the three groups suggested alterations in fatty acid and carbohydrate metabolism.

Discussion: Our results reveal metabolic alterations in DS-AD that are similar to those seen in LOAD. The pattern of results in this cross-sectional DS cohort suggests a dynamic time course of metabolic dysregulation which evolves with clinical progression from non-demented, to MCI, to AD. Metabolomic markers may be useful for staging progression of DS-AD.
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http://dx.doi.org/10.1002/dad2.12028DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7131985PMC
April 2020

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

Transl Psychiatry 2020 03 20;10(1):100. Epub 2020 Mar 20.

Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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http://dx.doi.org/10.1038/s41398-020-0705-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083923PMC
March 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry.

Mol Psychiatry 2020 10 7;25(10):2455-2467. Epub 2019 Oct 7.

Department of Public Health and Preventive Medicine, State University of New York, Upstate Medical University, Syracuse, NY, USA.

Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke's R = 0.032; liability R = 0.017; P < 10), Latino (Nagelkerke's R = 0.089; liability R = 0.021; P < 10), and European individuals (Nagelkerke's R = 0.089; liability R = 0.037; P < 10), further highlighting the advantages of incorporating data from diverse human populations.
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http://dx.doi.org/10.1038/s41380-019-0517-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515843PMC
October 2020

Dentate gyrus volume deficit in schizophrenia.

Psychol Med 2020 06 3;50(8):1267-1277. Epub 2019 Jun 3.

Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92617, USA.

Background: Schizophrenia is associated with robust hippocampal volume deficits but subregion volume deficits, their associations with cognition, and contributing genes remain to be determined.

Methods: Hippocampal formation (HF) subregion volumes were obtained using FreeSurfer 6.0 from individuals with schizophrenia (n = 176, mean age ± s.d. = 39.0 ± 11.5, 132 males) and healthy volunteers (n = 173, mean age ± s.d. = 37.6 ± 11.3, 123 males) with similar mean age, gender, handedness, and race distributions. Relationships between the HF subregion volume with the largest between group difference, neuropsychological performance, and single-nucleotide polymorphisms were assessed.

Results: This study found a significant group by region interaction on hippocampal subregion volumes. Compared to healthy volunteers, individuals with schizophrenia had significantly smaller dentate gyrus (DG) (Cohen's d = -0.57), Cornu Ammonis (CA) 4, molecular layer of the hippocampus, hippocampal tail, and CA 1 volumes, when statistically controlling for intracranial volume; DG (d = -0.43) and CA 4 volumes remained significantly smaller when statistically controlling for mean hippocampal volume. DG volume showed the largest between group difference and significant positive associations with visual memory and speed of processing in the overall sample. Genome-wide association analysis with DG volume as the quantitative phenotype identified rs56055643 (β = 10.8, p < 5 × 10-8, 95% CI 7.0-14.5) on chromosome 3 in high linkage disequilibrium with MOBP. Gene-based analyses identified associations between SLC25A38 and RPSA and DG volume.

Conclusions: This study suggests that DG dysfunction is fundamentally involved in schizophrenia pathophysiology, that it may contribute to cognitive abnormalities in schizophrenia, and that underlying biological mechanisms may involve contributions from MOBP, SLC25A38, and RPSA.
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http://dx.doi.org/10.1017/S0033291719001144DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068799PMC
June 2020

A method for building a genome-connectome bipartite graph model.

J Neurosci Methods 2019 05 19;320:64-71. Epub 2019 Mar 19.

The Mind Research Network, Albuquerque, NM, 87106, USA; Department of Psychiatry, Yale University, New Haven, CT, 06520, USA; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, 87016, USA. Electronic address:

It has been widely shown that genomic factors influence both risk for schizophrenia and variation in functional brain connectivity. Moreover, schizophrenia is characterized by disrupted brain connectivity. In this work, we proposed a genome-connectome bipartite graph model to perform imaging genomic analysis. Functional network connectivity (FNC) was estimated after decomposing resting state functional magnetic resonance imaging data from both healthy controls (HC) and patients with schizophrenia (SZ) into spatial brain components using group independent component analysis (G-ICA). Then 83 FNC connections showing a group difference (HC vs SZ) were selected as fMRI nodes, and eighty-one schizophrenia-related single nucleotide polymorphisms (SNPs) were selected as genetic nodes respectively in the bipartite graph. Edges connecting pairs of genetic and fMRI nodes were defined based on the SNP-FNC associations across subjects evaluated by a general linear model. Results show that some SNP nodes in the bipartite graph have a high degree implying they are influential in modulating brain connectivity and may be more strongly associated with the risk of schizophrenia than other SNPs. A bi-clustering analysis detected a cluster with 15 SNPs interacting with 38 FNC connections, most of which were within or between somato-motor and visual brain areas. This suggests that the activity of these brain regions may be related to common SNPs and provides insights into the pathology of schizophrenia. The findings suggest that the SNP-FNC bipartite graph approach is a novel model to investigate genetic influences on functional brain connectivity in mental illness.
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http://dx.doi.org/10.1016/j.jneumeth.2019.03.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6504548PMC
May 2019

Neandertal Introgression Sheds Light on Modern Human Endocranial Globularity.

Curr Biol 2019 01 13;29(1):120-127.e5. Epub 2018 Dec 13.

Language and Genetics Department, Max Planck Institute for Psycholinguistics, P.O. Box 310, 6500 AH, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, P.O. Box 9101, 6500 HB, Nijmegen, the Netherlands. Electronic address:

One of the features that distinguishes modern humans from our extinct relatives and ancestors is a globular shape of the braincase [1-4]. As the endocranium closely mirrors the outer shape of the brain, these differences might reflect altered neural architecture [4, 5]. However, in the absence of fossil brain tissue, the underlying neuroanatomical changes as well as their genetic bases remain elusive. To better understand the biological foundations of modern human endocranial shape, we turn to our closest extinct relatives: the Neandertals. Interbreeding between modern humans and Neandertals has resulted in introgressed fragments of Neandertal DNA in the genomes of present-day non-Africans [6, 7]. Based on shape analyses of fossil skull endocasts, we derive a measure of endocranial globularity from structural MRI scans of thousands of modern humans and study the effects of introgressed fragments of Neandertal DNA on this phenotype. We find that Neandertal alleles on chromosomes 1 and 18 are associated with reduced endocranial globularity. These alleles influence expression of two nearby genes, UBR4 and PHLPP1, which are involved in neurogenesis and myelination, respectively. Our findings show how integration of fossil skull data with archaic genomics and neuroimaging can suggest developmental mechanisms that may contribute to the unique modern human endocranial shape.
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http://dx.doi.org/10.1016/j.cub.2018.10.065DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6380688PMC
January 2019

Genetic and epigenetic analyses guided by high resolution whole-genome SNP array reveals a possible role of in Wilms tumour susceptibility.

Oncotarget 2018 Sep 25;9(75):34079-34089. Epub 2018 Sep 25.

Molecular Bases of Genetic Risk and Genetic Testing Unit, Department of Research, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.

Wilms tumour (WT), the most frequent malignant childhood renal tumour, shows a high degree of genetic and epigenetic heterogeneity. Loss of imprinting on chromosome 11p15 is found in a large fraction of cases and mutations in a few genes, including , , , and, more recently, and micro RNA processing genes (miRNAPGs), have been observed. However, these alterations are not sufficient to describe the entire spectrum of genetic defects underlying WT development. We inspected data obtained from a previously performed genome-wide single nucleotide polymorphism (SNP) array analysis on 96 WT samples. By selecting focal regions commonly involved in chromosomal anomalies, we identified genes with a possible role in WT development, based on the prior knowledge of their biological relevance, including , , , and , , and . The hotspot mutation c.131C>T was detected in seven cases (7.3%). Full sequencing of the remaining genes disclosed 16 rare missense variants and a splicing mutation. Most of these were present at the germline level. Promoter analysis of , and disclosed partial methylation affecting in a consistent fraction of cases (85%). Interestingly, of the four missense variants identified in , three were predicted to be deleterious by analyses, while an additional variant was observed to alter mRNA splicing, generating a functionally defective protein. Our study adds additional information on putative WT genes, and adds evidences involving in WT susceptibility.
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http://dx.doi.org/10.18632/oncotarget.26123DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6183341PMC
September 2018

Novel Bioinformatics Approach Identifies Transcriptional Profiles of Lineage-Specific Transposable Elements at Distinct Loci in the Human Dorsolateral Prefrontal Cortex.

Mol Biol Evol 2018 10;35(10):2435-2453

Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA.

Expression of transposable elements (TE) is transiently activated during human preimplantation embryogenesis in a developmental stage- and cell type-specific manner and TE-mediated epigenetic regulation is intrinsically wired in developmental genetic networks in human embryos and embryonic stem cells. However, there are no systematic studies devoted to a comprehensive analysis of the TE transcriptome in human adult organs and tissues, including human neural tissues. To investigate TE expression in the human Dorsolateral Prefrontal Cortex (DLPFC), we developed and validated a straightforward analytical approach to chart quantitative genome-wide expression profiles of all annotated TE loci based on unambiguous mapping of discrete TE-encoded transcripts using a de novo assembly strategy. To initially evaluate the potential regulatory impact of DLPFC-expressed TE, we adopted a comparative evolutionary genomics approach across humans, primates, and rodents to document conservation patterns, lineage-specificity, and colocalizations with transcription factor binding sites mapped within primate- and human-specific TE. We identified 654,665 transcripts expressed from 477,507 distinct loci of different TE classes and families, the majority of which appear to have originated from primate-specific sequences. We discovered 4,687 human-specific and transcriptionally active TEs in DLPFC, of which the prominent majority (80.2%) appears spliced. Our analyses revealed significant associations of DLPFC-expressed TE with primate- and human-specific transcription factor binding sites, suggesting potential cross-talks of concordant regulatory functions. We identified 1,689 TEs differentially expressed in the DLPFC of Schizophrenia patients, a majority of which is located within introns of 1,137 protein-coding genes. Our findings imply that identified DLPFC-expressed TEs may affect human brain structures and functions following different evolutionary trajectories. On one side, hundreds of thousands of TEs maintained a remarkably high conservation for ∼8 My of primates' evolution, suggesting that they are likely conveying evolutionary-constrained primate-specific regulatory functions. In parallel, thousands of transcriptionally active human-specific TE loci emerged more recently, suggesting that they could be relevant for human-specific behavioral or cognitive functions.
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http://dx.doi.org/10.1093/molbev/msy143DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6188555PMC
October 2018

Toward Reproducible Results from Targeted Metabolomic Studies: Perspectives for Data Pre-processing and a Basis for Analytic Pipeline Development.

Curr Top Med Chem 2018 ;18(11):883-895

Translational Laboratory and Biorepository, University of California, Irvine School of Medicine, Irvine, CA 92697, United States.

Contemporary metabolomics experiments generate a rich array of complex high-dimensional data. Consequently, there have been concurrent efforts to develop methodological standards and analytical workflows to streamline the generation of meaningful biochemical and clinical inferences from raw data generated using an analytical platform like mass spectrometry. While such considerations have been frequently addressed in untargeted metabolomics (i.e., the broad survey of all distinguishable metabolites within a sample of interest), this methodological scrutiny has seldom been applied to data generated using commercial, targeted metabolomics kits. We suggest that this may, in part, account for past and more recent incomplete replications of previously specified biomarker panels. Herein, we identify common impediments challenging the analysis of raw, targeted metabolomic abundance data from a commercial kit and review methods to remedy these issues. In doing so, we propose an analytical pipeline suitable for the pre-processing of data for downstream biomarker discovery. Operational and statistical considerations for integrating targeted data sets across experimental sites and analytical batches are discussed, as are best practices for developing predictive models relating pre-processed metabolomic data to associated phenotypic information.
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http://dx.doi.org/10.2174/1568026618666180711144323DOI Listing
September 2018

Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium.

Biol Psychiatry 2018 11 14;84(9):644-654. Epub 2018 May 14.

Division of Mental Health and Addiction, NORMENT, K.G. Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway.

Background: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group.

Methods: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide.

Results: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset.

Conclusions: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.
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http://dx.doi.org/10.1016/j.biopsych.2018.04.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6177304PMC
November 2018

Analysis of shared heritability in common disorders of the brain.

Science 2018 06;360(6395)

Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.
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http://dx.doi.org/10.1126/science.aap8757DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6097237PMC
June 2018

Polygenic risk score, genome-wide association, and gene set analyses of cognitive domain deficits in schizophrenia.

Schizophr Res 2018 11 12;201:393-399. Epub 2018 Jun 12.

Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617, United States. Electronic address:

This study assessed genetic contributions to six cognitive domains, identified by the MATRICS Cognitive Consensus Battery as relevant for schizophrenia, cognition-enhancing, clinical trials. Psychiatric Genomics Consortium Schizophrenia polygenic risk scores showed significant negative correlations with each cognitive domain. Genome-wide association analyses identified loci associated with attention/vigilance (rs830786 within HNF4G), verbal memory (rs67017972 near NDUFS4), and reasoning/problem solving (rs76872642 within HDAC9). Gene set analysis identified unique and shared genes across cognitive domains. These findings suggest involvement of common and unique mechanisms across cognitive domains and may contribute to the discovery of new therapeutic targets to treat cognitive deficits in schizophrenia.
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http://dx.doi.org/10.1016/j.schres.2018.05.041DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252137PMC
November 2018

Plasma metabolomic biomarkers accurately classify acute mild traumatic brain injury from controls.

PLoS One 2018 20;13(4):e0195318. Epub 2018 Apr 20.

Translational Laboratory and Biorepository, Department of Neurology, University of California Irvine, Irvine, CA United States of America.

Past and recent attempts at devising objective biomarkers for traumatic brain injury (TBI) in both blood and cerebrospinal fluid have focused on abundance measures of time-dependent proteins. Similar independent determinants would be most welcome in diagnosing the most common form of TBI, mild TBI (mTBI), which remains difficult to define and confirm based solely on clinical criteria. There are currently no consensus diagnostic measures that objectively define individuals as having sustained an acute mTBI. Plasma metabolomic analyses have recently evolved to offer an alternative to proteomic analyses, offering an orthogonal diagnostic measure to what is currently available. The purpose of this study was to determine whether a developed set of metabolomic biomarkers is able to objectively classify college athletes sustaining mTBI from non-injured teammates, within 6 hours of trauma and whether such a biomarker panel could be effectively applied to an independent cohort of TBI and control subjects. A 6-metabolite panel was developed from biomarkers that had their identities confirmed using tandem mass spectrometry (MS/MS) in our Athlete cohort. These biomarkers were defined at ≤6 hours following mTBI and objectively classified mTBI athletes from teammate controls, and provided similar classification of these groups at the 2, 3, and 7 days post-mTBI. The same 6-metabolite panel, when applied to a separate, independent cohort provided statistically similar results despite major differences between the two cohorts. Our confirmed plasma biomarker panel objectively classifies acute mTBI cases from controls within 6 hours of injury in our two independent cohorts. While encouraged by our initial results, we expect future studies to expand on these initial observations.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0195318PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5909890PMC
July 2018

Shared Genetic Risk of Schizophrenia and Gray Matter Reduction in 6p22.1.

Schizophr Bull 2019 01;45(1):222-232

The Mind Research Network, Albuquerque, NM.

Genetic factors are known to influence both risk for schizophrenia (SZ) and variation in brain structure. A pressing question is whether the genetic underpinnings of brain phenotype and the disorder overlap. Using multivariate analytic methods and focusing on 1,402 common single-nucleotide polymorphisms (SNPs) mapped from the Psychiatric Genomics Consortium (PGC) 108 regions, in 777 discovery samples, we identified 39 SNPs to be significantly associated with SZ-discriminating gray matter volume (GMV) reduction in inferior parietal and superior temporal regions. The findings were replicated in 609 independent samples. These 39 SNPs in chr6:28308034-28684183 (6p22.1), the most significant SZ-risk region reported by PGC, showed regulatory effects on both DNA methylation and gene expression of postmortem brain tissue and saliva. Furthermore, the regulated methylation site and gene showed significantly different levels of methylation and expression in the prefrontal cortex between cases and controls. In addition, for one regulated methylation site we observed a significant in vivo methylation-GMV association in saliva, suggesting a potential SNP-methylation-GMV pathway. Notably, the risk alleles inferred for GMV reduction from in vivo imaging are all consistent with the risk alleles for SZ inferred from postmortem data. Collectively, we provide evidence for shared genetic risk of SZ and regional GMV reduction in 6p22.1 and demonstrate potential molecular mechanisms that may drive the observed in vivo associations. This study motivates dissecting SZ-risk variants to better understand their associations with focal brain phenotypes and the complex pathophysiology of the illness.
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http://dx.doi.org/10.1093/schbul/sby010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6293216PMC
January 2019

Mitochondrial variability in the Mediterranean area: a complex stage for human migrations.

Ann Hum Biol 2018 Feb;45(1):5-19

a Centre of Molecular Anthropology for Ancient DNA Studies , University of Rome "Tor Vergata" , Rome , Italy.

Context: The Mediterranean area has always played a significant role in human dispersal due to the large number of migratory events contributing to shape the cultural features and the genetic pool of its populations.

Objective: This paper aims to review and diachronically describe the mitogenome variability in the Mediterranean population and the main demic diffusions that occurred in this area over time.

Methods: Frequency distributions of the leading mitochondrial haplogroups have been geographically and chronologically evaluated. The variability of U5b and K lineages has been focussed to broaden the knowledge of their genetic histories.

Results: The mitochondrial genetic makeup of Palaeolithic hunter-gatherers is poorly defined within the extant Mediterranean populations, since only a few traces of their genetic contribution are still detectable. The Neolithic lineages are more represented, suggesting that the Neolithic revolution had a marked effect on the peopling of the Mediterranean area. The largest effect, however, was provided by historical migrations.

Conclusion: Although the mitogenome variability has been widely used to try and clarify the evolution of the Mediterranean genetic makeup throughout almost 50 000 years, it is necessary to collect whole genome data on both extinct and extant populations from this area to fully reconstruct and interpret the impact of multiple migratory waves and their cultural and genetic consequences on the structure of the Mediterranean populations.
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http://dx.doi.org/10.1080/03014460.2017.1416172DOI Listing
February 2018

Systems healthcare: a holistic paradigm for tomorrow.

BMC Syst Biol 2017 Dec 19;11(1):142. Epub 2017 Dec 19.

Department of Neurology, School of Medicine, Irvine, USA.

Systems healthcare is a holistic approach to health premised on systems biology and medicine. The approach integrates data from molecules, cells, organs, the individual, families, communities, and the natural and man-made environment. Both extrinsic and intrinsic influences constantly challenge the biological networks associated with wellness. Such influences may dysregulate networks and allow pathobiology to evolve, resulting in early clinical presentation that requires astute assessment and timely intervention for successful mitigation. Herein, we describe the components of relevant biological systems and the nature of progression from at-risk to manifest disease. We illustrate the systems approach by examining two relevant clinical examples: Alzheimer's and cardiovascular diseases. The implications of systems healthcare management are examined through the lens of economics, ethics, policy and the law. Finally, we propose the need to develop new educational paradigms to enhance the training of the health professional in an era of systems medicine.
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http://dx.doi.org/10.1186/s12918-017-0521-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5738174PMC
December 2017

Epigenetic mechanisms and associated brain circuits in the regulation of positive emotions: A role for transposable elements.

J Comp Neurol 2016 10 24;524(15):2944-54. Epub 2016 Jul 24.

Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, 92617, California.

Epigenetic programming and reprogramming are at the heart of cellular differentiation and represent developmental and evolutionary mechanisms in both germline and somatic cell lines. Only about 2% of our genome is composed of protein-coding genes, while the remaining 98%, once considered "junk" DNA, codes for regulatory/epigenetic elements that control how genes are expressed in different tissues and across time from conception to death. While we already know that epigenetic mechanisms are at play in cancer development and in regulating metabolism (cellular and whole body), the role of epigenetics in the developing prenatal and postnatal brain, and in maintaining a proper brain activity throughout the various stages of life, in addition to having played a critical role in human evolution, is a relatively new domain of knowledge. Here we present the current state-of-the-art techniques and results of these studies within the domain of emotions, and then speculate on how genomic and epigenetic mechanisms can modify and potentially alter our emotional (limbic) brain and affect our social interactions. J. Comp. Neurol. 524:2944-2954, 2016. © 2016 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/cne.24046DOI Listing
October 2016

LINE1 insertions as a genomic risk factor for schizophrenia: Preliminary evidence from an affected family.

Am J Med Genet B Neuropsychiatr Genet 2016 06 16;171(4):534-45. Epub 2016 Mar 16.

Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California.

Recent studies show that human-specific LINE1s (L1HS) play a key role in the development of the central nervous system (CNS) and its disorders, and that their transpositions within the human genome are more common than previously thought. Many polymorphic L1HS, that is, present or absent across individuals, are not annotated in the current release of the genome and are customarily termed "non-reference L1s." We developed an analytical workflow to identify L1 polymorphic insertions with next-generation sequencing (NGS) using data from a family in which SZ segregates. Our workflow exploits two independent algorithms to detect non-reference L1 insertions, performs local de novo alignment of the regions harboring predicted L1 insertions and resolves the L1 subfamily designation from the de novo assembled sequence. We found 110 non-reference L1 polymorphic loci exhibiting Mendelian inheritance, the vast majority of which are already reported in dbRIP and/or euL1db, thus, confirming their status as non-reference L1 polymorphic insertions. Four previously undetected L1 polymorphic loci were confirmed by PCR amplification and direct sequencing of the insert. A large fraction of our non-reference L1s is located within the open reading frame of protein-coding genes that belong to pathways already implicated in the pathogenesis of schizophrenia. The finding of these polymorphic variants among SZ offsprings is intriguing and suggestive of putative pathogenic role. Our data show the utility of NGS to uncover L1 polymorphic insertions, a neglected type of genetic variants with the potential to influence the risk to develop schizophrenia like SNVs and CNVs. © 2016 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/ajmg.b.32437DOI Listing
June 2016

Chromosomal anomalies at 1q, 3, 16q, and mutations of SIX1 and DROSHA genes underlie Wilms tumor recurrences.

Oncotarget 2016 Feb;7(8):8908-15

Molecular Bases of Genetic Risk and Genetic Testing Unit, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.

Approximately half of children suffering from recurrent Wilms tumor (WT) develop resistance to salvage therapies. Hence the importance to disclose events driving tumor progression/recurrence. Future therapeutic trials, conducted in the setting of relapsing patients, will need to prioritize targets present in the recurrent lesions. Different studies identified primary tumor-specific signatures associated with poor prognosis. However, given the difficulty in recruiting specimens from recurrent WTs, little work has been done to compare the molecular profile of paired primary/recurrent diseases. We studied the genomic profile of a cohort of eight pairs of primary/recurrent WTs through whole-genome SNP arrays, and investigated known WT-associated genes, including SIX1, SIX2 and micro RNA processor genes, whose mutations have been recently proposed as associated with worse outcome. Through this approach, we sought to uncover anomalies characterizing tumor recurrence, either acquired de novo or already present in the primary disease, and to investigate whether they overlapped with known molecular prognostic signatures. Among the aberrations that we disclosed as potentially acquired de novo in recurrences, some had been already recognized in primary tumors as associated with a higher risk of relapse. These included allelic imbalances of chromosome 1q and of chromosome 3, and CN losses on chromosome 16q. In addition, we found that SIX1 and DROSHA mutations can be heterogeneous events (both spatially and temporally) within primary tumors, and that their co-occurrence might be positively selected in the progression to recurrent disease. Overall, these results provide new insights into genomic and genetic events underlying WT progression/recurrence.
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http://dx.doi.org/10.18632/oncotarget.6950DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4891013PMC
February 2016

Cross-disorder genome-wide analyses suggest a complex genetic relationship between Tourette's syndrome and OCD.

Am J Psychiatry 2015 Jan 31;172(1):82-93. Epub 2014 Oct 31.

From the Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetics Research, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston; the Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Mass.; the Department of Psychiatry, University of California, San Francisco; the Department of Neurology, Massachusetts General Hospital, Boston; the Division of Cognitive and Behavioral Neurology, Brigham and Women's Hospital, Boston; the Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston; Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago; the Department of Psychiatry, Academic Medical Center, University of Amsterdam, Amsterdam; the Department of Preventive Medicine, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles; the Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Md.; the Genomic and Bioinformatic Unit, Filarete Foundation, Milan, Italy; the Department of Health Sciences, Graduate School of Nephrology, University of Milan, Milan; the Toronto Western Research Institute, University Health Network, Toronto; Hospital for Sick Children, Toronto; Università Vita-Salute San Raffaele, Milan; the Herman Dana Division of Child and Adolescent Psychiatry, Hadassah-Hebrew University Medical Center, Jerusalem; Universidad de Antioquia, Universidad Pontificia Bolivariana, Medellín, Colombia; the Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore; the Department of Psychiatry, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City; the Child Study Center and the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; the Department of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil; North Shore-Long Island Jewish Medical Center and North Shore-Lo

Objective: Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The authors report a combined genome-wide association study (GWAS) of Tourette's syndrome and OCD.

Method: The authors conducted a GWAS in 2,723 cases (1,310 with OCD, 834 with Tourette's syndrome, 579 with OCD plus Tourette's syndrome/chronic tics), 5,667 ancestry-matched controls, and 290 OCD parent-child trios. GWAS summary statistics were examined for enrichment of functional variants associated with gene expression levels in brain regions. Polygenic score analyses were conducted to investigate the genetic architecture within and across the two disorders.

Results: Although no individual single-nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels (expression quantitative loci, or eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10(-4)), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, Tourette's syndrome had a smaller, nonsignificant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and co-occurring Tourette's syndrome/chronic tics were included in the analysis (p=0.01).

Conclusions: Previous work has shown that Tourette's syndrome and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of these two disorders. Furthermore, OCD with co-occurring Tourette's syndrome/chronic tics may have different underlying genetic susceptibility compared with OCD alone.
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http://dx.doi.org/10.1176/appi.ajp.2014.13101306DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4282594PMC
January 2015

Imaging genetics approaches to identify mechanisms in severe mental illness.

Biol Psychiatry 2014 Sep;76(6):436-7

Transdisciplinary Imaging Genetics Center, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California.

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http://dx.doi.org/10.1016/j.biopsych.2014.07.020DOI Listing
September 2014

Copy number variation in obsessive-compulsive disorder and tourette syndrome: a cross-disorder study.

J Am Acad Child Adolesc Psychiatry 2014 Aug 24;53(8):910-9. Epub 2014 Jun 24.

Yale University School of Medicine, New Haven, CT.

Objective: Obsessive-compulsive disorder (OCD) and Tourette syndrome (TS) are heritable neurodevelopmental disorders with a partially shared genetic etiology. This study represents the first genome-wide investigation of large (>500 kb), rare (<1%) copy number variants (CNVs) in OCD and the largest genome-wide CNV analysis in TS to date.

Method: The primary analyses used a cross-disorder design for 2,699 case patients (1,613 ascertained for OCD, 1,086 ascertained for TS) and 1,789 controls. Parental data facilitated a de novo analysis in 348 OCD trios.

Results: Although no global CNV burden was detected in the cross-disorder analysis or in secondary, disease-specific analyses, there was a 3.3-fold increased burden of large deletions previously associated with other neurodevelopmental disorders (p = .09). Half of these neurodevelopmental deletions were located in a single locus, 16p13.11 (5 case patient deletions: 0 control deletions, p = .08 in the current study, p = .025 compared to published controls). Three 16p13.11 deletions were confirmed de novo, providing further support for the etiological significance of this region. The overall OCD de novo rate was 1.4%, which is intermediate between published rates in controls (0.7%) and in individuals with autism or schizophrenia (2-4%).

Conclusion: Several converging lines of evidence implicate 16p13.11 deletions in OCD, with weaker evidence for a role in TS. The trend toward increased overall neurodevelopmental CNV burden in TS and OCD suggests that deletions previously associated with other neurodevelopmental disorders may also contribute to these phenotypes.
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http://dx.doi.org/10.1016/j.jaac.2014.04.022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4218748PMC
August 2014

Transposable elements and psychiatric disorders.

Am J Med Genet B Neuropsychiatr Genet 2014 Apr 28;165B(3):201-16. Epub 2014 Feb 28.

Department of Psychiatry, Columbia University, New York, New York.

Transposable Elements (TEs) or transposons are low-complexity elements (e.g., LINEs, SINEs, SVAs, and HERVs) that make up to two-thirds of the human genome. There is mounting evidence that TEs play an essential role in genomic architecture and regulation related to both normal function and disease states. Recently, the identification of active TEs in several different human brain regions suggests that TEs play a role in normal brain development and adult physiology and quite possibly in psychiatric disorders. TEs have been implicated in hemophilia, neurofibromatosis, and cancer. With the advent of next-generation whole-genome sequencing approaches, our understanding of the relationship between TEs and psychiatric disorders will greatly improve. We will review the biology of TEs and early evidence for TE involvement in psychiatric disorders.
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http://dx.doi.org/10.1002/ajmg.b.32225DOI Listing
April 2014
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