cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14272/razitxfwtapvox-uhfffaoysa-n.1
title: C8H12N6O
title: InChI=1S/C8H12N6O/c15-8(5-7-10-13-14-11-7)12-9-6-3-1-2-4-6/h1-5H2,(H,12,15)(H,10,11,13,14)

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367]. The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]: InChI descriptor[cheminf_000113]: InChI=1S/C8H12N6O/c15-8(5-7-10-13-14-11-7)12-9-6-3-1-2-4-6/h1-5H2,(H,12,15)(H,10,11,13,14), and canonical SMILES descriptor[cheminf_000007]: O=C(Cc1nnn[nH]1)NN=C1CCCC1, and by the IUPAC name[cheminf_000107]: . The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]: O=C(Cc1nnn[nH]1)NN=C1CCCC1 The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-33425 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]: Melting point descriptor[CHEMINF_000256]: 180.0 (°C) Boiling point descriptor[CHEMINF_000257]: Refractive index descriptor[CHEMINF_000253]: The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]: CHMO:0000636 | Fourier transform infrared spectroscopy (FTIR) CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR) CHMO:0000595 | 13C nuclear magnetic resonance spectroscopy (13C NMR) CHMO:0000498 | high-resolution mass spectrometry (HRMS) The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: Used ontologies: CHEBI - Chemical Entities of Biological Interest CHEMINF - chemical information ontology (information entities about chemical entities) CHMO - Chemical Methods Ontology OBI - Ontology for Biomedical Investigations
DOI: 10.14272/razitxfwtapvox-uhfffaoysa-n/chmo0000498
title: high-resolution mass spectrometry (HRMS) ()
title: InChI=1S/C8H12N6O/c15-8(5-7-10-13-14-11-7)12-9-6-3-1-2-4-6/h1-5H2,(H,12,15)(H,10,11,13,14)

description: dataset for high-resolution mass spectrometry (HRMS) HRMS–ESI (C8H13N6O+) (m/z): calcd 209.1145, found 209.1222.
DOI: 10.14272/razitxfwtapvox-uhfffaoysa-n/chmo0000636
title: Fourier transform infrared spectroscopy (FTIR) ()
title: InChI=1S/C8H12N6O/c15-8(5-7-10-13-14-11-7)12-9-6-3-1-2-4-6/h1-5H2,(H,12,15)(H,10,11,13,14)

description: dataset for Fourier transform infrared spectroscopy (FTIR) IR (ATR, ṽ) = 3051 (w), 3045 (w), 2974 (w), 1662 (vs), 1549 (w), 1520 (m), 1450 (w), 1435 (w), 1414 (w), 1388 (m), 1348 (w), 1261 (w), 1240 (w), 1213 (w), 1200 (w), 1065 (m), 1041 (w), 955 (w), 930 (w), 872 (w), 733 (w), 717 (w), 710 (w), 692 (w), 660 (w), 619 (w), 499 (w), 472 (w), 467 (w) cm–1.
DOI: 10.15154/1149598
title: Derivation of Quality Measures from Time-Series Images by Neuroimaging Pipelines

description: Using the National Database for Autism Research cloud platform, MRI data were analyzed using neuroimaging pipelines that included packages available as part of the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) Computational Environment to derive standardized measures of MR image quality.  Time series QA was performed according to Friedman, et al. (http://www.ncbi.nlm.nih.gov/pubmed/16952468) providing values for Signal to Noise Ratio that can be compared to other subjects. Diffusion QA was performed according to Liu, et al. (http://www.ncbi.nlm.nih.gov/pubmed/24353379), which provides a number of pass/fail checks and advisory flags.
DOI: 10.15154/1149599
title: Derivation of Quality Measures from Structural Images by Neuroimaging Pipelines

description: Using the National Database for Autism Research cloud platform, MRI data were analyzed using neuroimaging pipelines that included packages available as part of the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) Computational Environment to derive standardized measures of MR image quality.  Structural QA was performed according to Haselgrove, et al (http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00052/abstract) to provide values for Signal to Noise Ratio that can be compared to other subjects.  Diffusion QA was performed according to Liu, et al (http://www.ncbi.nlm.nih.gov/pubmed/24353379), which provides a number of pass/fail checks and advisory flags.
DOI: 10.15154/1149697
title: The contribution of de novo coding mutations to autism spectrum disorder

description: Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.

PLEASE NOTE: Additional data on these subjects, unrelated to this publication exist in other NDAR Studies.  These data include realigned BAM files, unfiltered SNV/InDel variant calls (made by GATK and FreeBayes), and CNVs.  Please see this news item for more details: https://ndar.nih.gov/ndarpublicweb/aboutNDAR.html#news_item_201
DOI: 10.15154/1151812
title: Excess of rare inherited truncating mutations in autism

description: In order to quantify the effect of private, inherited mutations on autism risk, we generated a callset of both inherited and de novo single nucleotide variants (SNVs) and copy number variants (CNVs) across 2,377 Simons Simplex Collection families. The publically deposited dataset includes 1,786 parents-child-unaffected sibling "quads" allowing us to compare burden of inherited and de novo mutations between affected and unaffected siblings in simplex autism families. We find that private, inherited truncating SNV mutations in conserved genes are significantly enriched in probands (odds ratio = 1.14, p = 0.0002) and more likely to be transmitted to children with autism when compared to their unaffected siblings (p &lt; 0.0001). We find that this effect becomes more pronounced with increasing gene conservation (Residual Variation Intolerance Score, RVIS). Likewise, we observe a similar bias for inherited CNVs specifically for small (&lt;100 kbp), maternally inherited events (p = 9.6x10^-3) that are enriched in CHD8 target genes (OR = 3.6, p = 2.0x10^-3). We quantified autism spectrum disorder (ASD) risk for de novo and inherited CNVs and SNVs by using a conditional logistic regression model. Independent from de novo mutations, private truncating SNVs and rare, inherited CNVs contribute an increase in risk with an odds ratio 1.11 (p = 0.0002) and 1.23 (p = 0.01), respectively. Our results indicate a statistically independent role for inherited mutations in ASD risk and identify additional high-impact risk candidate genes (e.g., RIMS1, CUL7, LZTR1 and CC2D2A) where transmitted mutations may create a sensitized background for autism but are unlikely to be necessary and sufficient for the disorder.
DOI: 10.15154/1157584
title: Cryptic and complex chromosomal aberrations in early onset neuropsychiatric disorders

description: Structural variation (SV) is a significant component of the genetic etiology of both neurodevelopmental and psychiatric disorders; however, routine guidelines for clinical genetic screening have been established only in the former category. Genome-wide chromosomal microarray (CMA) can detect genomic imbalances such as copy-number variants (CNVs), but balanced chromosomal abnormalities (BCAs) still require karyotyping for clinical detection. Moreover, submicroscopic BCAs and subarray threshold CNVs are intractable, or cryptic, to both CMA and karyotyping. Here, we performed whole-genome sequencing using large-insert jumping libraries to delineate both cytogenetically visible and cryptic SVs in a single test among 30 clinically referred youth representing a range of severe neuropsychiatric conditions. We detected 96 SVs per person on average that passed filtering criteria above our highest-confidence resolution (6,305 bp) and an additional 111 SVs per genome below this resolution. These SVs rearranged 3.8 Mb of genomic sequence and resulted in 42 putative loss-of-function (LoF) or gain-of-function mutations per person.We estimate that 80% of the LoF variants were cryptic to clinical CMA. We found myriad complex and cryptic rearrangements, including a "paired" duplication (360 kb, 169 kb) that flanks a 5.25 Mb inversion that appears in 7 additional cases from clinical CNV data among 47,562 individuals. Following convergent genomic profiling of these independent clinical CNV data, we interpreted three SVs to be of potential clinical significance. These data indicate
that sequence-based delineation of the full SV mutational spectrum warrants exploration in youth referred for neuropsychiatric evaluation and clinical diagnostic SV screening more broadly.
DOI: 10.15154/1158938
title: Psychometric Analysis of the Social Communication Questionnaire Using an Item-Response Theory Framework: Implications for the Use of the Lifetime and Current Forms

description: NDAR Study for new article accepted for publication in Journal of Psychopathology and Behavioral Assessment.
DOI: 10.15154/1163508
title: Gastrointestinal Dysfunction in Autism: Parental Report, Clinical Evaluation, and Associated Factors

description: The objectives of this study were to characterize gastrointestinal dysfunction (GID) in autism spectrum disorder (ASD), to examine parental reports of GID relative to evaluations by pediatric gastroenterologists, and to explore factors associated with GID in ASD. One hundred twenty-one children were recruited into three groups: co-occurring ASD and GID, ASD without GID, and GID without ASD. A pediatric gastroenterologist evaluated both GID groups. Parents in all three groups completed questionnaires about their child`s behavior and GI symptoms, and a dietary journal. Functional constipation was the most common type of GID in children with ASD (85.0%). Parental report of any GID was highly concordant with a clinical diagnosis of any GID (92.1%). Presence of GID in children with ASD was not associated with distinct dietary habits or medication status. Odds of constipation were associated with younger age, increased social impairment, and lack of expressive language (adjusted odds ratio in nonverbal children: 11.98, 95% confidence interval 2.54-56.57). This study validates parental concerns for GID in children with ASD, as parents were sensitive to the existence, although not necessarily the nature, of GID. The strong association between constipation and language impairment highlights the need for vigilance by health-care providers to detect and treat GID in children with ASD. Medications and diet, commonly thought to contribute to GID in ASD, were not associated with GID status. These findings are consistent with a hypothesis that GID in ASD represents pleiotropic expression of genetic risk factors.
DOI: 10.15154/1163510
title: Whole-Exome Sequencing and Homozygosity Analysis Implicate Depolarization-Regulated Neuronal Genes in Autism

description: Although autism has a clear genetic component, the high genetic heterogeneity of the disorder has been a challenge for the identification of causative genes. We used homozygosity analysis to identify probands from nonconsanguineous families that showed evidence of distant shared ancestry, suggesting potentially recessive mutations. Whole-exome sequencing of 16 probands revealed validated homozygous, potentially pathogenic recessive mutations that segregated perfectly with disease in 4/16 families. The candidate genes (UBE3B, CLTCL1, NCKAP5L, ZNF18) encode proteins involved in proteolysis, GTPase-mediated signaling, cytoskeletal organization, and other pathways. Furthermore, neuronal depolarization regulated the transcription of these genes, suggesting potential activity-dependent roles in neurons. We present a multidimensional strategy for filtering whole-exome sequence data to find candidate recessive mutations in autism, which may have broader applicability to other complex, heterogeneous disorders
DOI: 10.15154/1163511
title: Using Whole-Exome Sequencing to Identify Inherited Causes of Autism

description: NOTE: DO NOT SHARE. Despite significant heritability of autism spectrum disorders (ASDs), their extreme genetic heterogeneity has proven challenging for gene discovery. Studies of primarily simplex families have implicated de novo copy number changes and point mutations, but are not optimally designed to identify inherited risk alleles. We apply whole-exome sequencing (WES) to ASD families enriched for inherited causes due to consanguinity and find familial ASD associated with biallelic mutations in disease genes (AMT, PEX7, SYNE1, VPS13B, PAH, and POMGNT1). At least some of these genes show biallelic mutations in nonconsanguineous families as well. These mutations are often only partially disabling or present atypically, with patients lacking diagnostic features of the Mendelian disorders with which these genes are classically associated. Our study shows the utility of WES for identifying specific genetic conditions not clinically suspected and the importance of partial loss of gene function in ASDs.
DOI: 10.15154/1163514
title: The Study of Health Outcomes in Children with Autism and their Families

description: The purpose of this study was to validate autism spectrum disorder cases identified through claims-based case identification algorithms against a clinical review of medical charts. Charts were reviewed for 432 children who fell into one of the three following groups: (a) more than or equal to two claims with an autism spectrum disorder diagnosis code (n = 182), (b) one claim with an autism spectrum disorder diagnosis code (n = 190), and (c) those who had no claims for autism
spectrum disorder but had claims for other developmental or neurological conditions (n = 60). The algorithm-based diagnoses were compared with documented autism spectrum disorders in the medical charts. The algorithm requiring more than or equal to two claims for autism spectrum disorder generated a positive predictive value of 87.4%, which suggests that such an algorithm is a valid means to identify true autism spectrum disorder cases in claims data.
DOI: 10.15154/1163515
title: Elucidating the Genetic Architecture of Autism by Deep Genomic Sequencing

description: ARRA Autism Sequencing Collaboration
DOI: 10.15154/1163516
title: A protein interaction network of alternatively-spliced isoforms from brain links genetic risk factors for autism

description: Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.
DOI: 10.15154/1163517
title: Autism spectrum disorder: interaction of air pollution with the MET receptor tyrosine kinase gene.

description: Background:

Independent studies report association of autism spectrum disorder with air pollution exposure and a functional promoter variant (rs1858830) in the MET receptor tyrosine kinase (MET) gene. Toxicologic data find altered brain Met expression in mice after prenatal exposure to a model air pollutant. Our objective was to investigate whether air pollution exposure and MET rs1858830 genotype interact to alter ASD risk.

Methods:

We studied 252 cases of autism spectrum disorder and 156 typically developing controls the Childhood Autism Risk from Genetics and the Environment Study. Air pollution exposure was assigned for local traffic-related sources and regional sources (particulate matter, nitrogen dioxide and ozone). MET genotype was determined by direct re-sequencing.

Results:

Subjects with both MET rs1858830 CC genotype and high air pollutant exposures were at increased risk of autism spectrum disorder compared with subjects who had both the CG/GG genotypes and lower pollutant exposures. A statistical test of multiplicative interaction identified a statistically significant effect between NO2 and MET CC genotype (p=0.03)

Conclusions:

MET rs1858830 CC genotype and air pollutant exposure may interact to increase autism spectrum disorder risk.
DOI: 10.15154/1163542
title: Transmission disequilibrium of small CNVs in simplex autism.

description: Cohorts:

411 ASD Quads from Simons Simplex Collection 

177 Quads from Sanders et al. (PubMed ID: 22495306)
166 Quads from I. Iossifov et al. (PubMed ID: 22542183)
71 Quads from O'Roak et al. (PubMed ID: 22495309)


Publication Abstract:

We searched for disruptive, genic rare copy-number variants (CNVs) among 411 families affected by sporadic autism spectrum disorder (ASD) from the Simons Simplex Collection by using available exome sequence data and CoNIFER (Copy Number Inference from Exome Reads). Compared to high-density SNP microarrays, our approach yielded ¿2× more smaller genic rare CNVs. We found that affected probands inherited more CNVs than did their siblings (453 versus 394, p = 0.004; odds ratio [OR] = 1.19) and that the probands' CNVs affected more genes (921 versus 726, p = 0.02; OR = 1.30). These smaller CNVs (median size 18 kb) were transmitted preferentially from the mother (136 maternal versus 100 paternal, p = 0.02), although this bias occurred irrespective of affected status. The excess burden of inherited CNVs among probands was driven primarily by sibling pairs with discordant social-behavior phenotypes (p &lt; 0.0002, measured by Social Responsiveness Scale [SRS] score), which contrasts with families where the phenotypes were more closely matched or less extreme (p &gt; 0.5). Finally, we found enrichment of brain-expressed genes unique to probands, especially in the SRS-discordant group (p = 0.0035). In a combined model, our inherited CNVs, de novo CNVs, and de novo single-nucleotide variants all independently contributed to the risk of autism (p &lt; 0.05). Taken together, these results suggest that small transmitted rare CNVs play a role in the etiology of simplex autism. Importantly, the small size of these variants aids in the identification of specific genes as additional risk factors associated with ASD.
DOI: 10.15154/1163543
title: Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations.

description: In addition to cohorts of Parents (N=418), Siblings (N=50), and Probands (N=209), the publication publication describes a subset of male (N=47) and female (N=26) autistic subjects, with significant impairment and intellectual disability, and with cognitive impairment, respectively.  These subsets have been defined based on hi/low IQ value in Supplementary Table 1 from the publication.


Publication Abstract:

It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes--so-called sporadic or simplex families--we sequenced all coding regions of the genome (the exome) for parent-child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 677 individual exomes from 209 families. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected l-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics.
DOI: 10.15154/1163544
title: Patterns and rates of exonic de novo mutations in autism spectrum disorders.

description: Notes:

Data submitted to NDAR did not include interview age.


Publication Abstract:

Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.