Transcriptome signatures from discordant sibling pairs reveal changes in peripheral blood immune cell composition in Autism Spectrum Disorder

Notwithstanding several research efforts in the past years, robust and replicable molecular signatures for autism spectrum disorders from peripheral blood remain elusive. The available literature on blood transcriptome in ASD suggests that through accurate experimental design it is possible to extract important information on the disease pathophysiology at the peripheral level. Here we exploit the availability of a resource for molecular biomarkers in ASD, the Italian Autism Network (ITAN) collection, for the investigation of transcriptomic signatures in ASD based on a discordant sibling pair design. Whole blood samples from 75 discordant sibling pairs selected from the ITAN network where submitted to RNASeq analysis and data analyzed by complementary approaches. Overall, differences in gene expression between affected and unaffected siblings were small. In order to assess the contribution of differences in the relative proportion of blood cells between discordant siblings, we have applied two different cell deconvolution algorithms, showing that the observed molecular signatures mainly reflect changes in peripheral blood immune cell composition, in particular NK cells. The results obtained by the cell deconvolution approach are supported by the analysis performed by WGCNA. Our report describes the largest differential gene expression profiling in peripheral blood of ASD subjects and controls conducted by RNASeq. The observed signatures are consistent with the hypothesis of immune alterations in autism and an increased risk of developing autism in subjects exposed to prenatal infections or stress. Our study also points to a potential role of NMUR1, HMGB3, and PTPRN2 in ASD

Deep Phenotyping of CD11c+ B Cells in Systemic Autoimmunity and Controls

Circulating CD11c+ B cells are a key phenomenon in certain types of autoimmunity but have also been described in the context of regular immune responses (i.e., infections, vaccination). Using mass cytometry to profile 46 different markers on individual immune cells, we systematically initially confirmed the presence of increased CD11c+ B cells in the blood of systemic lupus erythematosus (SLE) patients. Notably, significant differences in the expression of CD21, CD27, and CD38 became apparent between CD11c- and CD11c+ B cells. We observed direct correlation of the frequency of CD21-CD27- B cells and CD21-CD38- B cells with CD11c+ B cells, which were most pronounced in SLE compared to primary Sjögren's syndrome patients (pSS) and healthy donors (HD). Thus, CD11c+ B cells resided mainly within memory subsets and were enriched in CD27-IgD-, CD21-CD27-, and CD21-CD38- B cell phenotypes. CD11c+ B cells from all donor groups (SLE, pSS, and HD) showed enhanced CD69, Ki-67, CD45RO, CD45RA, and CD19 expression, whereas the membrane expression of CXCR5 and CD21 were diminished. Notably, SLE CD11c+ B cells showed enhanced expression of the checkpoint molecules CD86, PD1, PDL1, CD137, VISTA, and CTLA-4 compared to HD. The substantial increase of CD11c+ B cells with a CD21- phenotype co-expressing distinct activation and checkpoint markers, points to a quantitative increased alternate (extrafollicular) B cell activation route possibly related to abnormal immune regulation as seen under the striking inflammatory conditions of SLE which shows a characteristic PD-1/PD-L1 upregulation

The challenges of genome-wide interaction studies: Lessons to learn from the analysis of HDL blood levels

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP6SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value, 1 · 1028 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30, 011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP6SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS

The Challenges of Genome-Wide Interaction Studies : Lessons to Learn from the Analysis of HDL Blood Levels

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10-8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.Peer reviewe

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia

Schizophrenia has a heritability of 60–80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Massive Parallelisierung der kombinatorischen statistischen Genetik-Analysen mit Methoden des maschinellen Lernens auf graphics processing units (GPU)

Dank jüngster Fortschritte in der Genomsequenzierung und automatisierten Phänotypisierung wurde es möglich den Zusammenhang zwischen Genotyp und Phänotyp mit bislang unerreichter Präzision zu untersuchen. Wahrend die Zuordnung von Phänotypen auf einzelne Loci im Genom zum Standardverfahren geworden ist, bleibt die Epistasis-Suche, d.h. die Zuordnung von Phänotypen auf zwei oder mehr Loci eine rechnerische Herausforderung. Epistatische Interaktionen zwischen Loci tragen jedoch wesentlich zur phänotypischen Varianz bei. Mit Hilfe der Rechenleistung von Graphikkarten konnte die Suche nach solchen Interaktionen mittels linearer und logistischer Regressionen auf einem einzelnen Rechner ermöglicht werden. Der Einsatz von Graphics Processing Units (GPUs) wird zudem immer ökonomischer und bedienungsfreundlicher. Unsere Gruppe hat neue Programme entwickelt, um GPUs für das Epistasis Problem einzusetzen. Ein GPU-spezifischer kernel code schaltet die parallele Rechenleistung der GPUs frei und ermöglicht die statistische Berechnung aller möglichen Loci Paare. Die erreichbare Rechenleistung übertrifft Single-CPU-Core und Multiple-CPU-Core basierte Ansätze. Die erschöpfende Epistasis-Suche steht damit allen interessierten Wissenschaftlern zur Verfügung. Insbesondere erlaubt es uns die Umsetzung einer systematischen Epistasis-Erfassungs-Studie basierend auf eine grosse Vielzahl von bereits veröffentlichten GWAS Daten, einschliesslich dem Wellcome Trust Case Control Consortium (WTCCC). Zur Berechnung von statistischen Signifikanzen in biologischen Daten mit über Hundert Milliarden Interaktionen wird nicht mehr als ein einzelner Computer benötigt. Dadurch werden entsprechende Untersuchungen erschwinglich und es kann vermehrt mit neuen Erkenntnissen aus ihnen gerechnet werden.Recent advances in sequencing technology and automated phenotyping render it possible to study the relationship between genotype and phenotype at an unprecedented level of detail. While mapping phenotypes to single loci in the genome is a standard technique in Statistical Genetics, the problem of epistasis search, that is mapping phenotypes to pairs of loci, remains computationally infeasible in practice. This is problematic, as epistatic interactions between loci are expected to contribute significantly to phenotypic variance. By making use of the computational power of graphics cards, we enable epistasis detection via linear and logistic regression on a single desktop machine. As the use of graphics processing units (GPUs) is becoming synonymous with an economical and ease-of-access parallel computing option, it is spawning many innovative projects in several fields of study. Our group has successfully developed new tools with the aim of using the multiple cores available on GPUs to solve the epistasis problem. A dedicated kernel code running on GPUs helps to unlock the parallel computational power of these devices and compute the statistical scores of all possible second order interactions. The GPU-bound programs have shown to outperform not only standard single CPU-core based approaches but also tools designed for multiple CPU cores by up to two orders of magnitude. The tools will be of great assistance to researchers intent on performing exhaustive epistasis searches. In particular, our implementations enable to conduct a systematic epistasis detection study on the large host of previously published Genome-wide association studies (GWAS) data, including Wellcome Trust Case Control Consortium (WTCCC). The vision of researchers employing no more than a single desktop computer to evaluate the statistical significance of interactions of biological inputs in the order of hundred of billions has become a reality. This will in turn help drive down costs and increase innovation in this field of study

Fast phase components of the vestibulo ocular reflex: segment classification and transient system identification

This thesis investigates the dynamic characteristics of the Vestibulo-Ocular Reflex (VOR) in particular the rapid components of eye movements induced by head rotations in the horizontal plane. The VOR is a reflex eye movement that serves to provide a stabilized perception of the external environment in response to head movement. The reflex originates in the vestibular sensors in both inner ears, in particular the semicircular canals for the angular VOR. The afferent sensory signals eventually drive the appropriate eye movements by sending motoneural signals to the eye plant(s). The VOR response consists of alternating slow phase and fast phase modes of operation. During slow phases, the eye velocity acts in a compensatory direction to the head stimulus to maintain a constant perception of the outside world. During fast phases, there is a sudden short-duration spike in eye velocity in the same direction as the head velocity. The eye then acts in the anti-compensatory direction to minimize the error signal noted between a stored efferent eye position and the intended target extracted from the vestibular signal. This thesis reports on improved model fitting performance and physiological relevance in the analysis of VOR characteristics. In particular, it uses transient system identification in contrast to traditional end point envelopes for the detection of VOR fast phase dynamics. This required the implementation of an automated model complexity selection scheme, based on Null-Hypothesis and Akaike criteria to allow for any combination of coefficients in a non-linear representation with up to third order polynomials. Identification results are compared for cases using either all, rightwards-only or leftwards-only fast phase segments. The results support implications from physiology, in that the fast phase mechanism is predominantly unilateral with respect to motion sensors. Moreover, the estimated non-linear characteristics and dynamics of the fast phase mCe mémoire étudie les caractéristiques dynamiques des mouvements de l'œil en particulier les composants rapides du Réflexe Vestibulo-Oculaire (RVO) induits par les rotations de la tête sur le plan horizontal. Le RVO est un mouvement réflexe de l'œil qui sert à fournir une perception stabilisée de l'environnement externe en réponse au mouvement de la tête. Le réflexe commence aux canaux semi-circulaires, organes sensorielles de l'accélération angulaire situés dans les deux oreilles externes. Les signaux sensoriels afférents conduisent par la suite les mouvements appropriés d'oeil en envoyant des signaux motoneurals aux muscles oculaires. La réponse RVO se compose d'une alternation entre la phase lente et la phase rapide. Pendant les phases lentes, la vitesse des mouvements de l'œil agit dans une direction compensatoire au stimulus, principalement pour maintenir une perception constante du monde externe. Durant les phases rapides, il y a une transition soudaine de courte durée de la vitesse de l'œil dans la même direction que celle de la tête. L'œil agit alors dans la direction anti-compensatoire pour réduire au minimum le signal d'erreur entre une position efférente de l'œil enregistrée et le point prévu de la cible prévue extraite à partir du signal vestibulaire. Cette thèse présente un modèle ayant une performance améliorée et une meilleure acuité physiologique dans l'analyse des caractéristiques de RVO En particulier, elle emploie l'identification du système transitoire contrairement aux enveloppes traditionnelles de point final pour la détection de la dynamique de la phase rapide du RVO. Ceci a exigé l'exécution d'un arrangement modèle automatisé de choix de complexité, basée sur des critères de Nul-Hypothèse et d'Akaike pour tenir compte de n'importe quelle combinaison des coefficients dans une représentation non linéaire avec des polynômes de troisième ordre. Trois modèles de la phase rapide ont ét

Transcriptome signatures from discordant sibling pairs reveal changes in peripheral blood immune cell composition in Autism Spectrum Disorder

Notwithstanding several research efforts in the past years, robust and replicable molecular signatures for autism spectrum disorders from peripheral blood remain elusive. The available literature on blood transcriptome in ASD suggests that through accurate experimental design it is possible to extract important information on the disease pathophysiology at the peripheral level. Here we exploit the availability of a resource for molecular biomarkers in ASD, the Italian Autism Network (ITAN) collection, for the investigation of transcriptomic signatures in ASD based on a discordant sibling pair design. Whole blood samples from 75 discordant sibling pairs selected from the ITAN network where submitted to RNASeq analysis and data analyzed by complementary approaches. Overall, differences in gene expression between affected and unaffected siblings were small. In order to assess the contribution of differences in the relative proportion of blood cells between discordant siblings, we have applied two different cell deconvolution algorithms, showing that the observed molecular signatures mainly reflect changes in peripheral blood immune cell composition, in particular NK cells. The results obtained by the cell deconvolution approach are supported by the analysis performed by WGCNA. Our report describes the largest differential gene expression profiling in peripheral blood of ASD subjects and controls conducted by RNASeq. The observed signatures are consistent with the hypothesis of immune alterations in autism and an increased risk of developing autism in subjects exposed to prenatal infections or stress. Our study also points to a potential role of NMUR1, HMGB3, and PTPRN2 in ASD

An examination of single nucleotide polymorphism selection prioritization strategies for tests of gene-gene interaction

Background Given that genome-wide association studies (GWAS) of psychiatric disorders have identified only a small number of convincingly associated variants (single nucleotide polymorphism [SNP]), there is interest in seeking additional evidence for associated variants with tests of gene–gene interaction. Comprehensive pair-wise single SNP–SNP interaction analysis is computationally intensive, and the penalty for multiple testing is severe, given the number of interactions possible. Aiming to minimize these statistical and computational burdens, we have explored approaches to prioritize SNPs for interaction analyses. Methods Primary interaction analyses were performed with the Wellcome Trust Case-Control Consortium bipolar disorder GWAS (1868 cases, 2938 control subjects). Replication analyses were performed with the Genetic Association Information Network bipolar disorder dataset (1001 cases, 1033 control subjects). The SNPs were prioritized for interaction analysis that showed evidence for association that surpassed a number of nominally significant thresholds, are within genome-wide significant genes, or are within genes that are functionally related. Results For no set of prioritized SNPs did we obtain evidence to support the hypothesis that the selection strategy identified pairs of variants that were enriched for true (statistical) interactions. Conclusions The SNPs prioritized according to a number of criteria do not have a raised prior probability for significant interaction that is detectable in samples of this size. We argue that the use of significance levels reflecting only the number of tests performed, as is now widely accepted for single SNP analysis, does not offer an appropriate degree of protection against the potential for GWAS studies to generate an enormous number of false positive interactions