The twin boys were born at 35 weeks, had breathing problems at birth, and spent 10 days in the newborn intensive care unit. Neither child has any dysmorphic features nor congenital medical abnormalities, and brain imaging studies were negative. Likewise, neither child has a history of confirmed seizures; however, there are concerns for possible absence epilepsy. There is no history of abnormal neurological examination or macro-/microcephaly. Development of both siblings was delayed, but neither had appreciable regression. The more severely affected twin (designated as the affected proband, AP, and from whom the induced pluripotent stem cell (iPSC) model of severe ASD affectation was acquired) began to exhibit delays in development by 9 months of age. He was speaking single words at 14 months and was ultimately diagnosed with autism at 3.5 years old. Research confirmation of the diagnosis was obtained using the Autism Diagnostic Observation Schedule. Compared to his twin brother, he has had more perseverative interests on odd objects. Psychological testing at the age of nine revealed an IQ of 65 using the Leiter International Performance Scale. Now in late adolescence, he has the ability to engage in reciprocal and meaningful verbal exchanges, although his language is often echolalic and repetitive. He is socially motivated and develops superficial friendships with peers. Functionally, he is able to complete most self-care, dress himself, prepare food and feed himself, and count money. He participates in a vocational program at school and is able to complete rudimentary tasks assigned to him. His monozygotic twin was also diagnosed with ASD at 3.5 years old and is less severely affected, but still requires significant support. Selected clinical characteristics of the family members studied are summarized in Table 1. 
Standard trio ES was performed by the clinical diagnostic laboratory GeneDx for the unaffected mother (UM), the AP, and the unaffected father. As described by GeneDx, exons were captured and sequenced on an Illumina platform with at least 100 base pair read length, followed by alignment to human genome build GRCh37/hg19 and subsequent variant identification. GeneDx's custom-developed tool, Xome Analyzer, was used for variant analysis, as described. This process involves comparing the sequences of each individual to a number of resources, such as published reference sequences, other family members, and control individuals, including the 1000 Genomes database, NHLBI Exome Sequencing Project, ExAC, gnomAD, OMIM, PubMed, and Clinvar. Variant annotations include evolutionary conservation scores, results of in silico prediction tools, and references from the published literature. A phenotype-based approach is also used to generate candidate gene lists. This information was interpreted by GeneDx experts according to the American College of Medical Genetics and Genomics Guidelines. ES was performed by The Genome Technology Access Center (GTAC) at Washington University on the intermediate phenotype sister (IS), and variant-specific testing was performed by GeneDx on the trait-affected brother (TB) to confirm the presence of the identified GPD2 variant.
iPSC lines were generated by the Genome Engineering and iPSC Center (GEiC) at Washington University. Biomaterials for reprogramming were only available from the UM, IS, and AP. Briefly, renal epithelial cells were isolated and cultured from fresh urine samples and were reprogrammed using a CytoTune-iPS 2.0 Sendai Reprogramming kit (Thermo Fisher Scientific), following the manufacturer's instructions. At least three clonal iPSC lines were derived for each subject, and one or two of these clonal lines (clones 1 and 2) were used for all experimentation involving the UM, IS, and AP. The UC line was previously derived by the GEiC, and one clonal line was available for use in all experiments involving this cell line. All clones (clones 1 and 2) used in experiments were assessed for karyotypic abnormalities by the Washington University School of Medicine Cytogenetics and Molecular Pathology Laboratory, and were also characterized for pluripotency by immunocytochemistry (ICC) and RT-qPCR. Each statistically significant experimental finding reported here was made in experiments that used two different clonal lines per individual (except for the UC, where only one clonal line was available), with at least three independent biological replicate experiments performed per clonal line. Statistical comparisons were made by one-way ANOVA or unpaired t test. Documentation of the clone used for each replicate experiment, the replicates performed, and the statistics for each finding is detailed in Additional file 1: Table S1.
iPSC lines were grown under feeder-free conditions on Matrigel (Corning) in mTeSR1 (STEMCELL Technologies). cExN and cIN differentiation of iPSCs was performed using previously described protocols. Briefly, for cExN differentiation, iPSCs were dissociated to single cells with Accutase (Life Technologies) and 40,000 cells were seeded in V-bottom 96-well non-adherent plates (Corning). Plates were spun at 200xg for 5 min to generate embryoid bodies (EBs) and were incubated in 5% CO2 at 37  C in cExN differentiation medium with 10 muM Y-27632 (Tocris Biosciences). cExN differentiation medium components include Neurobasal-A (Life Technologies), 1X B-27 supplement (without Vitamin A) (Life Technologies), 10 muM SB-431542 (Tocris Biosciences), 100 nM LDN-193189 (Tocris Biosciences). On day four of differentiation, EBs were transferred from V-bottom plates to Poly-l-Ornithine- (20 mug/ml) and laminin- (10 mug/ml) coated plates. Media (without Y-27632) was replenished every other day, and on day 12, Neural Rosette Selection reagent (STEMCELL Technologies) was used to select neural progenitor cells (NPCs) from within neural rosettes, per the manufacturer's instructions. cExN NPCs were grown as a monolayer using cExN differentiation media for up to 15 passages. cIN differentiation media contained the same components as cExN differentiation media, while also including 1 muM Purmorphamine (Calbiochem) and 2 muM XAV-939 (Tocris Biosciences). EBs were generated as described for cExNs. At day four of differentiation, the EBs were transferred to non-adherent plates and were placed on an orbital shaker (80 rpm) in an incubator with 5% CO2 at 37  C. The media was replenished every other day and, at day ten, EBs were transferred to Matrigel- and laminin- (5 mug/ml) coated plates. Y-27632 was included in media until day eight of differentiation. On day 12 of differentiation, NPCs were dissociated with Accutase and maintained as a monolayer for up to 15 passages. For both cIN and cExN NPC growth analysis, an equal number of cells were seeded on Matrigel- and laminin- (5 mug/ml) coated plates and total cells were counted 4 days later when the cells reached 70-80% confluence.
For differentiation of cExN NPCs into neurons for maturation, 40,000 cells per well were seeded in V-bottom 96-well non-adherent plates. Plates were spun at 200xg for 5 min and incubated in 5% CO2 at 37  C in maturation medium with Y-27632. Maturation medium components include Neurobasal-A, 1X B-27 supplement (without Vitamin A), 200 muM cAMP (Sigma), 200 muM Ascorbic acid (Sigma), and 20 ng BDNF (PeproTech). After 2 days, EBs were transferred to Matrigel- and laminin- (5 mug/ml) coated plates and media was replenished every other day (without Y-27632). On day 12 of neuronal differentiation and maturation, cells were dissociated with Accutase and seeded in an eight-well chamber for ICC.
For neurosphere size measurement analysis, P values *P < 0.05, **P < 0.01, ***P < 0.001 were determined by one-way ANOVA.
DNA was isolated from cell lines using the PureLink Genomic DNA Kit (Invitrogen). Primers were designed to amplify a 248 base pair region of GPD2 flanking the identified point mutation (forward primer: AAGCAGCAGACTGCATTTCA, reverse primer: CACCATGGCACACACTTACC). Sanger sequencing was performed on this PCR amplified fragment using either the forward or reverse primer. CodonCode Aligner software was used to analyze sequencing results.
For ICC, cells were plated on eight-well chamber slides coated with Matrigel and laminin (5 mug/mL). After 1 day, cells were washed once with PBS without calcium and magnesium (PBS - Ca2+/Mg2+) and fixed in 4% paraformaldehyde for 20 min, followed by washing with PBS + Ca2+/Mg2+. Cells were blocked with blocking buffer (10% donkey serum, 1% BSA, and 0.1% TritonX-100 in PBS + Ca2+/Mg2+) for at least 1 h and incubated with primary antibodies overnight (Additional file 1: Table S1) in antibody dilution buffer (1% donkey serum, 1% BSA, and 0.1% TritonX-100 in PBS + Ca2+/Mg2+). After overnight incubation, cells were washed three times with wash buffer (0.1% Triton X-100 in PBS + Ca2+/Mg2+). Cells were incubated with corresponding secondary antibodies (Additional file 1: Table S1), along with DAPI (1 mg/mL; ThermoFisher Scientific), diluted in antibody dilution buffer for 1 h. Following secondary antibody incubation, cells were washed twice with wash buffer and once with PBS + Ca2+/Mg2+. Slides were mounted with Prolong Gold anti-fade agent (Life Technologies). Images were obtained using a spinning-disk confocal microscope (Quorum) with MetaMorph software and were processed using ImageJ. For immunoblotting, cell lysate was extracted and 30 mug of protein was used per lane. Antibodies used are listed in Additional file 1: Table S1.
For each experiment, approximately one million cells were pelleted, washed with PBS - Ca2+/Mg2+, resuspended in PBS - Ca2+/Mg2+ and fixed by adding 70% ice-cold ethanol dropwise while vortexing. Cells were stained with 10 mug/mL propidium iodide (Sigma) and 200 mug/mL RNase A (Fisher Scientific) in FACS buffer (PBS - Ca2+/Mg2+, 0.2% BSA, 1 mM EDTA). FACS was performed on single-cell suspensions and the cell cycle analysis function of FlowJo was used to analyze cell cycle composition for each sample, based on propidium iodide staining to detect DNA content in each cell. P values *P < 0.05, **P < 0.01, ***P < 0.001 were determined by one-way ANOVA.
Total RNA was collected from iPSC-derived day 12 cExN and cIN NPCs using the NucleoSpin RNA II kit (Takara) per the manufacturer's instructions. RNA was quantified using a NanoDrop ND-1000 spectrophotometer (Thermo Scientific), and the integrity of RNA was confirmed with an Agilent Bioanalyzer 2100 to ensure a RIN value above eight. RNA-sequencing (RNA-seq) library preparation and Illumina sequencing were performed by the GTAC at Washington University. Single-end 50 base pair reads were obtained using an Illumina HiSeq 3000 sequencer, obtaining an average of ~30 million uniquely aligned reads per sample. For RT-qPCR, 1 mug total RNA was reverse transcribed using iScript Reverse Transcription Supermix (Bio-Rad). Equal quantities of cDNA were used as a template for RT-qPCR, using the Applied Biosystems Fast Real-Time quantitative PCR system. RPL30 mRNA levels were used as endogenous controls for normalization. P values *P < 0.05, **P < 0.01, ***P < 0.001 were determined by an unpaired t test.
RNA-seq data analysis was performed as described in to curate differentially expressed gene (DEG) lists. In summary, RNA-seq reads were aligned to the human genome (assembly hg38) with STAR version 2.5.4b. Gene counts were derived from the number of uniquely aligned unambiguous reads by Subread:featureCount, version 1.6.3, with GENCODE gene annotation (V27). All gene-level transcript counts were then imported into the R/Bioconductor package DESeq2. Genes expressed below a CPM of 1.0 in more than half the samples were excluded from further analysis. DEG cutoffs were set at a log2-fold change of > 1.0 and a Benjamini and Hochberg FDR of < 0.05.
To uncover the biological significance of DEGs, network analysis was performed with the data interpretation tool Ingenuity Pathway Analysis (IPA) (Qiagen). IPA's Ingenuity Knowledge Base uses network-eligible DEGs to generate networks and to define connections between one and more networks. Based on the number of eligible DEGs, IPA defines network scores as inversely proportional to the probability of finding the network and defines significant networks (P <= 0.001). Within each network, red symbols indicate upregulated genes and green symbols indicate downregulated genes, where the color intensity represents the relative degree of differential expression.
For this correlation analysis, the read counts matrix for DEGs in either the cIN or cExN samples was log2-CPM transformed. A similarity matrix for these genes was created by calculating the Euclidian distance among the genes from the log2-CPM matrix in R. The WGCNA R package "adjacency.fromSimilarity" function with arguments power=12, type='signed' was used to create an adjacency matrix from the similarity matrix. Hierarchical clustering was performed using the hclust function in R on the distance matrix transformation of the adjacency matrix using the ward.D2 method. The dendrogram of this gene tree was split into k = 3 clusters using the cutree function in the stats package of R. The read counts matrix for all genes in either the cIN or cExN samples was CPM transformed. Genes expressed at < 1 CPM in over half of the samples were excluded. Average CPM among the four sample types was calculated for each gene, and genes with expression ratios of < 1.25 between the highest and lowest expressed sample type were excluded from further analysis. The filtered gene CPM matrix was log2 transformed, and the Pearson correlation matrix for the remaining genes was calculated using the cor function from the stats package in R. A gene was considered to be correlated to a DEG cluster if it had a Pearson correlation coefficient > 0.7 for over half the genes in the DEG cluster. Genes with expression correlated to a cluster of genes from the DEG clustering were merged with those genes and fed into the ToppFun GO analysis of ToppGene. For each correlated cluster, up to five terms with the most significant Benjamini and Hochberg FDR values were retained for each biological process, cellular component, and molecular function GO terms. The top three pathway and disease terms were also retained for each cluster. To assess the impact of different covariates on expression, the R/Bioconductor package variancePartition was utilized. The parameters assessed were cell type (cExN vs. cIN), subject (UC, UM, IS, AP), age (young vs. old), or sex (male vs. female).
The RNA-seq data generated during the current study are available in the Gene Expression Omnibus (GEO) repository as Series GSE129806.
Subjects were consented for biobanking and iPSC line generation by the Washington University Institutional Review Board of the Human Research Protection Office under human studies protocol #201409091 (Dr. John Constantino).
Consent to publish data was provided by all subjects.