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Contains fulltext : 248865.pdf (Publisher’s version ) (Closed access) OBJECTIVE: Autism spectrum disorder (ASD) is accompanied by highly individualized neuroanatomical deviations that potentially map onto distinct genotypes and clinical phenotypes. This study aimed to link differences in brain anatomy to specific biological pathways to pave the way toward targeted therapeutic interventions. METHODS: The authors examined neurodevelopmental differences in cortical thickness and their genomic underpinnings in a large and clinically diverse sample of 360 individuals with ASD and 279 typically developing control subjects (ages 6-30 years) within the EU-AIMS Longitudinal European Autism Project (LEAP). The authors also examined neurodevelopmental differences and their potential pathophysiological mechanisms between clinical ASD subgroups that differed in the severity and pattern of sensory features. RESULTS: In addition to significant between-group differences in "core" ASD brain regions (i.e., fronto-temporal and cingulate regions), individuals with ASD manifested as neuroanatomical outliers within the neurotypical cortical thickness range in a wider neural system, which was enriched for genes known to be implicated in ASD on the genetic and/or transcriptomic level. Within these regions, the individuals' total (i.e., accumulated) degree of neuroanatomical atypicality was significantly correlated with higher polygenic scores for ASD and other psychiatric conditions, and it scaled with measures of symptom severity. Differences in cortical thickness deviations were also associated with distinct sensory subgroups, especially in brain regions expressing genes involved in excitatory rather than inhibitory neurotransmission. CONCLUSIONS: The study findings corroborate the link between macroscopic differences in brain anatomy and the molecular mechanisms underpinning heterogeneity in ASD, and provide future targets for stratification and subtyping.

Autism spectrum disorders (ASDs) are phenotypically as well as genetically heterogeneous developmental disorders with a strong heritability. Clinical and basic science research has described many replicated genetic risk factors. Many findings can well be translated into clinical human genetic practice. The current article summarizes results of genetic studies in ASD, provides a diagnostic algorithm for the clinical human genetic work-up reflecting the German health care system options and gives information with regard to the obligatory genetic counselling after a clinical genetic assessment.

Genetic risk factors and their influence on neural development in autism spectrum disorders

Die Ätiologie der Autismus-Spektrum-Störungen (ASS) ist in genetischen Risikofaktoren sowie der Interaktion von genetischen und biologisch wirksamen Umweltrisikofaktoren begründet. ASS werden aufgrund von Verhaltensmerkmalen, nämlich bleibend eingeschränkter sozialer Kommunikation, sowie durch stereotypes Verhalten, sensorische und Sonderinteressen diagnostiziert. Hinsichtlich des genetischen Hintergrundes besteht eine hohe genetische Heterogenität, d. h., die genetischen Ursachen sind vielfältig und individuell oft sehr unterschiedlich ausgeprägt. Allerdings konvergieren diese Ursachen in bestimmten biologischen Mechanismen und überlappenden biologischen Endstrecken, deren Veränderung sehr wahrscheinlich den autismusspezifischen Verhaltensmerkmalen zugrunde liegt. Die vorliegende, selektive Literaturübersicht summiert die genetischen Befunde und fokusiert sich insbesondere auf Mechanismen und Endstrecken, die aufgrund der neueren Forschung immer besser charakterisiert werden. Der Artikel schließt mit Hinweisen zur klinischen Relevanz der aktuellen Befunde sowie offenen Fragen der translationalen Forschung. Autism spectrum disorders are etiologically based on genetic and specific gene x biologically relevant environmental risk factors. They are diagnosed based on behavioral characteristics, such as impaired social communication and stereotyped, repetitive behavior and sensory as well as special interests. The genetic background is heterogeneous, i. e., it comprises diverse genetic risk factors across the disorder and high interindividual differences of specific genetic risk factors. Nevertheless, risk factors converge regarding underlying biological mechanisms and shared pathways, which likely cause the autism-specific behavioral characteristics. The current selective literature review summarizes differential genetic risk factors and focuses particularly on mechanisms and pathways currently being discussed by international research. In conclusion, clinically relevant aspects and open translational research questions are presented.

Discrimination of anxiety disorders by parent ratings: A study based on the Questionnaire for Anxiety and Obsessive-Compulsive Disorders (FBB-ANZ)

Im Rahmen der Abklärung des Verdachts einer Angststörung kommen in der klinischen Praxis regelmäßig Screeningfrage- bögen für Eltern zum Einsatz, die teilweise auch unterschiedliche Angststörungen erfassen. Im klinischen Kontext ist die valide Abgrenzung von Angststörungen zu anderen psychischen Störung sowie die differenzialdiagnostische Abklärung spezifischer Angststörungen relevant. Das Ziel der vorliegenden Studie ist die Untersuchung der Validität eines Screenings durch den Fremdbeurteilungsbogen für Angst- und Zwangsstörun- gen (FBB-ANZ) hinsichtlich unterschiedlicher Angststörungen. Überprüft wurde die Diskriminationsfähigkeit von (1) Angststörungen und ande- ren kinder- und jugendpsychiatrischen Störungen und (2) verschiedenen Angststörungen mittels ROC-Analysen (Receiver Operating Characte- ristics). Der FBB-ANZ wurde von 972 Eltern von 4;00–11;11-jährigen Kindern und 12;00–17;11-jährigen Jugendlichen mit Angststörungen oder depressiven Episoden oder externalisierenden Störungen ausgefüllt. Die Diskriminationsfähigkeit von Angststörungen und externalisierenden Störungen bei Kindern (AUC [Area Under the Curve] = .72) und Jugendlichen (AUC = .76) sowie von Angststörungen und depressiven Episoden im Kindesalter (AUC = .77) war moderat. Eine gute Unterscheidung verschiedener Angststörungen bei Angstpatient_innen war nur hinsichtlich der emotionalen Störung mit Trennungsangst bei Kindern (AUC = .84) und Jugendlichen (AUC = .87) gegeben. Die Ergebnisse deuten auf einen eingeschränkten diagnostischen Nutzen des Screeningurteils der Eltern zur Unterscheidung verschiedener Angststörungen im Kindes- und Jugendalter hin. Mögliche Erklärungsansätze für die vorliegenden Ergebnisse werden kritisch diskutiert. Parent ratings are often used for screening during the diagnostic evaluation of anxiety disorders. Clinically, it is important to correctly differentiate between anxiety and other psychiatric disorders and to distinguish specific anxiety disorders. The present study examined the validity of the screening results obtained by the Parent Questionnaire for Anxiety and Obsessive-Compulsive Disorders (FBB-ANZ). We exam- ined whether the FBB-ANZ discriminated (1) anxiety and other psychiatric disorders and (2) specific anxiety disorders in children and adoles- cents using ROC analyses. 972 parents of 4;00–11;11-year-old children and 12;00–17;11-year-old adolescents with anxiety disorders, depres- sive episodes, or externalizing disorders completed the FBB-ANZ. Discrimination of anxiety disorders and externalizing disorders in children (AUC = .72) and adolescents (AUC = .76) as well as depressive episodes in children (AUC = .77) was moderate. Good discrimination of different anxiety disorders was found only for separation anxiety in children (AUC = .84) and adolescents (AUC = .87). The results indicate the limited di- agnostic benefit of parent ratings for discriminating different anxiety disorders in children and adolescents. Potential explanations for the re- sults are critically discussed.

The genetic architecture underlying Autism spectrum disorder (ASD) has been suggested to differ between individuals with lower (IQ ≤ 70; LIQ) and higher intellectual abilities (IQ > 70; HIQ). Among the identified pathomechanisms, the glutamatergic signalling pathway is of specific interest in ASD. We investigated 187 common functional variants of this neurotransmitter system for association with ASD and with symptom severity in two independent samples, a German (German-ALL: N = 583 families) and the Autism Genome Project cohort (AGP-ALL: N = 2001 families), split into HIQ, and LIQ subgroups. We did not identify any association withstanding correction for multiple testing. However, we report a replicated nominal significant under-transmission (OR

Common variants contribute significantly to the genetics of autism spectrum disorder (ASD), although the identification of individual risk polymorphisms remains still elusive due to their small effect sizes and limited sample sizes available for association studies. During the last decade several genome-wide association studies (GWAS) have enabled the detection of a few plausible risk variants. The three main studies are family-based and pointed at SEMA5A (rs10513025), MACROD2 (rs4141463) and MSNP1 (rs4307059). In our study we attempted to replicate these GWAS hits using a case-control association study in five European populations of ASD patients and gender-matched controls, all Caucasians. Results showed no association of individual variants with ASD in any of the population groups considered or in the combined European sample. We performed a meta-analysis study across five European populations for rs10513025 (1,904 ASD cases and 2,674 controls), seven European populations for rs4141463 (2,855 ASD cases and 36,177 controls) and five European populations for rs4307059 (2,347 ASD cases and 2,764 controls). The results showed an odds ratio (OR) of 1.05 (95% CI = 0.84-1.32) for rs10513025, 1.0002 (95% CI = 0.93-1.08) for rs4141463 and 1.01 (95% CI = 0.92-1.1) for rs4307059, with no significant P-values (rs10513025, P = 0.73; rs4141463, P = 0.95; rs4307059, P = 0.9). No association was found when we considered either only high functioning autism (HFA), genders separately or only multiplex families. Ongoing GWAS projects with larger ASD cohorts will contribute to clarify the role of common variation in the disorder and will likely identify risk variants of modest effect not detected previously. Autism Res 2017, 10: 202-211. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

MotivationComplex neuropsychiatric conditions including autism spectrum disorders are among the most heritable neurodevelopmental disorders with distinct profiles of neuropsychological traits. A variety of genetic factors modulate these traits (phenotypes) underlying clinical diagnoses. To explore the associations between genetic factors and phenotypes, genome-wide association studies are broadly applied. Stringent quality checks and thorough downstream analyses for in-depth interpretation of the associations are an indispensable prerequisite. However, in the area of neuropsychology there is no framework existing, which besides performing association studies also affiliates genetic variants at the brain and gene network level within a single framework.ResultsWe present a novel bioinformatics approach in the field of neuropsychology that integrates current state-of-the-art tools, algorithms and brain transcriptome data to elaborate the association of phenotype and genotype data. The integration of transcriptome data gives an advantage over the existing pipelines by directly translating genetic associations to brain regions and developmental patterns. Based on our data integrative approach, we identify genetic variants associated with Intelligence Quotient (IQ) in an autism cohort and found their respective genes to be expressed in specific brain areas.ConclusionOur data integrative approach revealed that IQ is related to early down-regulated and late up-regulated gene modules implicated in frontal cortex and striatum, respectively. Besides identifying new gene associations with IQ we also provide a proof of concept, as several of the identified genes in our analysis are candidate genes related to intelligence in autism, intellectual disability, and Alzheimer’s disease. The framework provides a complete extensive analysis starting from a phenotypic trait data to its association at specific brain areas at vulnerable time points within a timespan of four days.Availability and ImplementationOur framework is implemented in R and Python. It is available as an in-house script, which can be provided on demand.Contactafsheen.yousaf@kgu.de

Supplementary methods, supplementary results, supplementary table S1, supplementary figures S1-S6. (DOCX 555 kb)

Background Common single nucleotide polymorphisms (SNPs) explain around 50% of genetic risk underlying Autism-Spectrum-Disorder (ASD). In a previous study we showed that common functional SNPs of genes implicated in Fragile X Syndrome (FXS) were associated with ASD (Waltes et al., 2014). The FXS associated protein FMRP is regulated by the glutamatergic system, a patho-mechanism discussed for ASD. Objective We tested if functional common SNPs of glutamatergic genes were associated with ASD or ASD specific symptoms in two large ASD family cohorts (Autism Genome Project/AGP set, N=2734 families; German data set N=578 families). Since the genetic architecture between individuals with High IQ (HIQ= IQ>70) and Low IQ (LIQ= IQ≤70) differs (Vieland et al., 2010), we also split the two cohorts into high and low functioning (HIQ, LIQ) individuals. Methods 207 functional SNPs of 124 glutamatergic genes with a minor allele frequency over 5% were tested using Plink v 1.9 (DFAM) in the cohort with HIQ, LIQ and the combined cohorts, respectively. Phenotype association was studied by logistic ordinal regression correcting for gender, IQ, clinical site and population stratification. Phenotype measures were taken from the Autism Diagnostic Interview-Revised (ADI-R) scores for Social Interaction (Domain A), Verbal Communication (B1-B4; verbal individuals only), Non-Verbal Communication (Domain B2; B3; all individuals) and Repetitive Behavior (Domain C). Variants significant in both cohorts with effect sizes in the same direction were considered as replicated. Similarly, genes with any nominal significant variant in both cohorts were considered as replicated hits. Results We identified nominal significant associations of variants rs7206796 and rs3790112 (GNAO1) as well as rs3742926 (AKAP6) in both the German and the AGP LIQ cohort. In addition, significant but not overlapping SNPs of AKAP2 were identified (LIQ only). rs731826 (AKT1S1) was associated with Non Verbal Communication in the HIQ cohorts. In addition, we report 24 variants that were nominally associated with ADI-R scores in both cohorts. Genes that were involved in all five phenotypes tested were strongly related to the mTOR Pathway (e.g. genes MTOR and TSC2) or the second messenger system (e.g. G-proteins GNAS, phospholipases PLCB, protein phosphatases PPP1CA). A subset of genes was specific to each phenotype or significant in one of the subgroups (HIQ and LIQ) only. For example AKAP13 or RPS6K are associated with Verbal Communication in Low Functioning Individuals. Discussion Replication and extending previous findings we found that variants of genes that are associated with glutamate signaling, and specifically the mTOR pathway are modulators of ASD symptoms. Genes such as TSC1 or RPS6K are known to mediate glutamatergic signaling through mTOR, whereas AKAP proteins are important interactors of glutamate receptors (Sanderson et al., 2011). Both, the mTOR pathways and AKAP proteins have previously been associated with ASD (Chen et al ., 2014; Poelmans et al., 2013). Further functional analyses of glutamatergic variants are thus recommended to elucidate ASD etiology.