Current clinical practices and challenges in molecular testing: a GOAL Consortium Hematopathology Working Group report.

While molecular testing of hematologic malignancies is now standard of care, there is variability in practice and testing capabilities between different academic laboratories, with common questions arising on how to best meet clinical expectations. A survey was sent to hematopathology subgroup members of the Genomics Organization for Academic Laboratories consortium to assess current and future practice and potentially establish a reference for peer institutions. Responses were received from 18 academic tertiary-care laboratories regarding next-generation sequencing (NGS) panel design, sequencing protocols and metrics, assay characteristics, laboratory operations, case reimbursement, and development plans. Differences in NGS panel size, use, and gene content were reported. Gene content for myeloid processes was reported to be generally excellent, while genes for lymphoid processes were less well covered. The turnaround time (TAT) for acute cases, including acute myeloid leukemia, was reported to range from 2 to 7 calendar days to 15 to 21 calendar days, with different approaches to achieving rapid TAT described. To help guide NGS panel design and standardize gene content, consensus gene lists based on current and future NGS panels in development were generated. Most survey respondents expected molecular testing at academic laboratories to continue to be viable in the future, with rapid TAT for acute cases likely to remain an important factor. Molecular testing reimbursement was reported to be a major concern. The results of this survey and subsequent discussions improve the shared understanding of differences in testing practices for hematologic malignancies between institutions and will help provide a more consistent level of patient care.

The genetic landscape of germline DDX41 variants predisposing to myeloid neoplasms.

Germline DDX41 variants are the most common mutations predisposing to acute myeloid leukemia (AML)/myelodysplastic syndrome (MDS) in adults, but the causal variant (CV) landscape and clinical spectrum of hematologic malignancies (HMs) remain unexplored. Here, we analyzed the genomic profiles of 176 patients with HM carrying 82 distinct presumably germline DDX41 variants among a group of 9821 unrelated patients. Using our proposed DDX41-specific variant classification, we identified features distinguishing 116 patients with HM with CV from 60 patients with HM with variant of uncertain significance (VUS): an older age (median 69 years), male predominance (74% in CV vs 60% in VUS, P = .03), frequent concurrent somatic DDX41 variants (79% in CV vs 5% in VUS, P < .0001), a lower somatic mutation burden (1.4 ± 0.1 in CV vs 2.9 ± 0.04 in VUS, P = .012), near exclusion of canonical recurrent genetic abnormalities including mutations in NPM1, CEBPA, and FLT3 in AML, and favorable overall survival (OS) in patients with AML/MDS. This superior OS was determined independent of blast count, abnormal karyotypes, and concurrent variants, including TP53 in patients with AML/MDS, regardless of patient's sex, age, or specific germline CV, suggesting that germline DDX41 variants define a distinct clinical entity. Furthermore, unrelated patients with myeloproliferative neoplasm and B-cell lymphoma were linked by DDX41 CV, thus expanding the known disease spectrum. This study outlines the CV landscape, expands the phenotypic spectrum in unrelated DDX41-mutated patients, and underscores the urgent need for gene-specific diagnostic and clinical management guidelines.

Comparison of commonly used solid tumor targeted gene sequencing panels for estimating tumor mutation burden shows analytical and prognostic concordance within the cancer genome atlas cohort.

BACKGROUND: Tumor mutation burden (TMB) is a biomarker frequently reported by clinical laboratories, which is derived by quantifying of the number of single nucleotide or indel variants (mutations) identified by next-generation sequencing of tumors. TMB values can inform prognosis or predict the response of a patient's tumor to immune checkpoint inhibitor therapy. Methods for the calculation of TMB are not standardized between laboratories, with significant variables being the gene content of the panels sequenced and the inclusion or exclusion of synonymous variants in the calculations. The impact of these methodological differences has not been investigated and the concordance of reported TMB values between laboratories is unknown. METHODS: Sequence variant lists from more than 9000 tumors of various types were downloaded from The Cancer Genome Atlas. Variant lists were filtered to include only appropriate variant types (ie, non-synonymous only or synonymous and non-synonymous variants) within the genes found in five commonly used targeted solid tumor gene panels as well as an in-house gene panel. Calculated TMB was paired with corresponding overall survival (OS) data of each patient. RESULTS: Regression analysis indicates high concordance of TMB as derived from the examined panels. TMB derived from panels was consistently and significantly lower than that derived from a whole exome. TMB, as derived from whole exome or the examined panels, showed a significant correlation with OS in the examined data. CONCLUSIONS: TMB derived from the examined gene panels was analytically equivalent between panels, but not between panels and whole-exome sequencing. Correlation between TMB and OS is significant if TMB method-specific cut-offs are used. These results suggest that TMB values, as derived from the gene panels examined, are analytically and prognostically equivalent.

Genetic variation in alcohol dehydrogenase is associated with neurocognition in men with HIV and history of alcohol use disorder: preliminary findings.

The co-occurrence of HIV and alcohol use disorder (AUD) amplifies risk for neural injury and neurocognitive deficits. However, the substantial neurocognitive heterogeneity across HIV+/AUD+ individuals suggests inter-individual differences in vulnerability to the neurotoxicity of comorbid HIV/AUD. Genetic variation in alcohol dehydrogenase (ADH), which metabolizes ethanol, may contribute to inter-individual neurocognitive variability. We evaluated associations between five ADH single-nucleotide polymorphisms (SNPs) and neurocognition in men stratified by HIV and lifetime AUD status. Neurobehavioral assessments were administered to 153 men. Three-way ANOVAs examined the interaction of HIV, AUD, and ADH SNPs on global and domain-specific demographically corrected T scores. Follow-up ANCOVAs adjusted for age, estimated verbal IQ, depression, and remote non-alcohol substance use disorders. HIV/AUD groups differed globally and for verbal fluency, working memory, executive function, and processing speed T scores specifically, with HIV+/AUD+ exhibiting the poorest performance. ADH4 (rs1126671) was associated with large effects on working memory (d = - 1.16, p = .001) and executive function (d = - 0.77, p = .028) selectively in HIV+/AUD+, which remained significant in ANCOVA models. ADH1A (rs3819197) moderated the deleterious effects of HIV+/AUD+ on processing speed such that HIV+/AUD+ related to slower information processing in A allele carriers but not GG homozygotes (ps < 0.03). Preliminary findings suggest genetic variation in the ADH pathway moderates the deleterious neurocognitive effects of comorbid HIV/AUD. Differential metabolism of heavy ethanol exposure may compromise neurocognition under conditions of neurobiological stress, such as in HIV infection. The functional effects on ethanol metabolism of ADH SNPs examined in this study remain poorly understood, warranting further examination of pharmacokinetic mechanisms mediating ADH gene-neurobehavior relationships in HIV.

Multi-Institutional Evaluation of Interrater Agreement of Variant Classification Based on the 2017 Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer.

This multi-institutional study was undertaken to evaluate interrater reliability of the 2017 Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists guidelines for interpretation and reporting of oncology sequence variants and to assess current practices and perceptions surrounding these guidelines. Fifty-one variants were distributed to 20 participants from 10 institutions for classification using the new guidelines. Agreement was assessed using chance-corrected agreement (Cohen κ). κ was 0.35. To evaluate if data sharing could help resolve disagreements, a summary of variant classifications and additional information about each variant were distributed to all participants. κ improved to 0.7 after the original classifications were revised. Participants were invited to take a web-based survey regarding their perceptions of the guidelines. Only 20% (n = 3) of the survey respondents had prior experience with the guidelines in clinical practice. The main perceived barriers to guideline implementation included the complexity of the guidelines, discordance between clinical actionability and pathobiologic relevance, lack of familiarity with the new classifications, and uncertainty when applying criteria to potential germline variants. This study demonstrates noteworthy discordances between pathologists for variant classification in solid tumors when using the 2017 Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists guidelines. These findings highlight potential areas for clarification/refinement before mainstream clinical adoption.

Adverse effect of catechol-O-methyltransferase (COMT) Val158Met met/met genotype in methamphetamine-related executive dysfunction.

INTRODUCTION: The Val allele of the Val158Met single-nucleotide polymorphism of the catechol-o-methyltransferase gene (COMT) confers greater catabolism of dopamine (DA) in the prefrontal cortex (PFC) than the Met allele. Met/Met homozygotes typically outperform Val-carriers on tests of executive function (EF), perhaps resulting from increased DA bioavailability. Methamphetamine (METH) causes large releases of DA, which is associated with neurotoxicity and executive dysfunction in chronic METH users. We hypothesized that, contrary to its effect in non-METH-using populations, slower DA clearance conferred by Met/Met will relate to worse EF in METH users. METHODS: 149 non-Hispanic White men, stratified by METH dependence (METH+/-) and COMT (Val/Val, Val/Met, Met/Met), completed three tests of EF: Wisconsin Card Sorting Test (WCST), Stroop Color-Word Test (Stroop), and Trail Making Test Part B (Trails B). Demographically-adjusted test scores were averaged to create an EF composite T-score. We examined the interaction of METH and COMT on the EF composite and individual test T-scores, controlling for premorbid functioning and alcohol use. RESULTS: METH group differences in EF were evident only among Met/Met carriers (beta = -9.36, p < .001) but not among Val carriers: Val/Met (beta = -1.38, p = .44) and Val/Val (beta = -4.34, p = .10). These effects were most salient on the WCST. CONCLUSIONS: In the pre-frontal hyperdopaminergic state triggered by methamphetamine, greater DA inactivation conferred by the Val allele may protect against METH-related executive dysfunction, suggesting genetically-driven differences in vulnerability to METH.

Library Preparation Using FFPE-Derived Tumor DNA for High-Throughput Hybridization-Based Targeted or Exome Sequencing.

The use of next generation sequencing (NGS) to profile tumor genomes for the presence of diagnostic, prognostic, or therapeutically targetable variants is revolutionizing the practice of oncology and is increasingly utilized in clinical laboratory settings. Beginning with the isolation of DNA of sufficient quality and quantity from a tumor specimen, the creation of a library of genomic fragments representing the portion of the genome of interest, ranging from a few genes to the entire exome, is the first step required in the sequencing process. Fixed tumor tissue in the form of a tissue block is the most commonly encountered specimen for analysis in a clinical setting. Special precautions must be employed to ensure that material isolated from these specimens is suitable for use. Once DNA is obtained, one of the most commonly used methods for library preparation involves fluid phase hybridization-based capture of the genomic regions to be interrogated. This multistep process involves fragmentation of the DNA to a uniform size distribution, ligating adapter molecules which are labeled with specific barcodes to enable downstream sequencing and sample identification, and the use of a multiplexed pool of biotinylated single stranded RNA or DNA hybridization probes to recognize and capture the targeted genomic regions. Fragments which are not specifically captured during the hybridization process are removed via a series of wash steps, and a final low cycle amplification is used to prepare the library of captured fragments for sequencing. In this chapter, we provide a step-by-step guide to the preparation of fixed tissue-derived DNA libraries for sequencing via the Illumina process and highlight some of the precautions necessary when working with these types of specimens.

Bioinformatics Basics for High-Throughput Hybridization-Based Targeted DNA Sequencing from FFPE-Derived Tumor Specimens: From Reads to Variants.

The use of next-generation sequencing and hybridization-based capture for target enrichment have enabled the interrogation of coding regions of several clinically significant cancer genes in tumor specimens using both targeted panels of a few to hundreds of genes, to whole-exome panels encompassing coding regions of all genes in the genome. Next-generation sequencing (NGS) technologies produce millions of relatively short segments of sequences or reads that require bioinformatics tools to map reads back to a reference genome using various read alignment tools, as well as to determine differences between single bases (single nucleotide variants or SNVs) or multiple bases (insertions and deletions or indels) between the aligned reads and the reference genome to call variants. In addition to single nucleotide changes or small insertions and deletions, high copy gains and losses can also be gleaned from NGS data to call gene amplifications and deletions. Throughout these processes, numerous quality control metrics can be assessed at each step to ensure that the resulting called variants are of high quality and are accurate. In this chapter we review common tools used to generate reads from Illumina-derived sequence data, align reads, and call variants from hybridization-based targeted NGS panel data generated from tumor FFPE-derived DNA specimens as well as basic quality metrics to assess for each assayed specimen.

Annotation of Variant Data from High-Throughput DNA Sequencing from Tumor Specimens: Filtering Strategies to Identify Driver Mutations.

The use of next-generation sequencing technologies has enabled the analysis of a wide spectrum of somatic mutations in tumors. This analysis can be carried out using various strategies including the use of small panels of focused, clinically actionable genes, large panels of cancer-related genes, whole exomes, and the entire genome. One of the main goals in these analyses is to identify key mutations in these tumors that drive the oncogenic process. Depending on the gene, mutations can have altering effects, such as loss of function mutations in tumor suppressor genes, to mutations that activate genes such as kinases involved with cell cycle progression or proliferation. Once the sequencing process is complete, and the alignment of the large collection of reads to the reference genome and variant calling has been carried out, one is left with a large collection of variants. The challenge then becomes assigning where the variant resides in the genome with respect to coding regions, splice site regions, regulatory regions, and what potential functional effect these variants may have on the resulting protein. Other helpful information includes determining if the variant has been identified before, and if so, the tumor type associated with the variant. In addition, if the tumor profiling experiment is not conducted with a matched specimen representing the inherited genome, various tools are helpful to determine if the variant is likely to be an inherited polymorphism or a somatic event. In this chapter, we review the various tools available for annotating variants to assist in filtering down and prioritizing the hundreds to thousands of variants down to the key variants likely to be driver mutations and relevant to the tumor being profiled.

Efficient region-based test strategy uncovers genetic risk factors for functional outcome in bipolar disorder.

Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 - 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 - rs2086256 - rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data.

Expression of LDL receptor-related proteins (LRPs) in common solid malignancies correlates with patient survival.

LDL receptor-related proteins (LRPs) are transmembrane receptors involved in endocytosis, cell-signaling, and trafficking of other cellular proteins. Considerable work has focused on LRPs in the fields of vascular biology and neurobiology. How these receptors affect cancer progression in humans remains largely unknown. Herein, we mined provisional databases in The Cancer Genome Atlas (TCGA) to compare expression of thirteen LRPs in ten common solid malignancies in patients. Our first goal was to determine the abundance of LRP mRNAs in each type of cancer. Our second goal was to determine whether expression of LRPs is associated with improved or worsened patient survival. In total, data from 4,629 patients were mined. In nine of ten cancers studied, the most abundantly expressed LRP was LRP1; however, a correlation between LRP1 mRNA expression and patient survival was observed only in bladder urothelial carcinoma. In this malignancy, high levels of LRP1 mRNA were associated with worsened patient survival. High levels of LDL receptor (LDLR) mRNA were associated with decreased patient survival in pancreatic adenocarcinoma. High levels of LRP10 mRNA were associated with decreased patient survival in hepatocellular carcinoma, lung adenocarcinoma, and pancreatic adenocarcinoma. LRP2 was the only LRP for which high levels of mRNA expression correlated with improved patient survival. This correlation was observed in renal clear cell carcinoma. Insights into LRP gene expression in human cancers and their effects on patient survival should guide future research.

Gray matter maturation and cognition in children with different APOE ε genotypes.

OBJECTIVE: The aims of the current study were to determine whether children with the 6 different APOE ε genotypes show differences in gray matter maturation, particularly for those with ε4 and ε2 alleles, which are associated with poorer outcomes in many neurologic disorders. METHODS: A total of 1,187 healthy children (aged 3-20 years, 52.1% boys, 47.9% girls) with acceptable data from the cross-sectional Pediatric Imaging Neurocognition and Genetics Study were evaluated for the effects of 6 APOE ε genotypes on macroscopic and microscopic cortical and subcortical gray matter structures (measured with 3-tesla MRI and FreeSurfer for automated morphometry) and on cognition (NIH Toolbox). RESULTS: Among APOE ε4 carriers, age-related changes in brain structures and cognition varied depending on genotype, with the smallest hippocampi in ε2ε4 children, the lowest hippocampal fractional anisotropy in younger ε4ε4 children, the largest medial orbitofrontal cortical areas in ε3ε4 children, and age-dependent thinning of the entorhinal cortex in ε4ε4 children. Younger ε4ε4 children had the lowest scores on executive function and working memory, while younger ε2ε4 children performed worse on attention tasks. Larger parietal gyri in the younger ε2ε4 children, and thinner temporal and cingulate isthmus cortices or smaller hippocampi in the younger ε4ε4 children, predicted poorer performance on attention or working memory. CONCLUSIONS: Our findings validated and extended prior smaller studies that showed altered brain development in APOE ε4-carrier children. The ε4ε4 and ε2ε4 genotypes may negatively influence brain development and brain aging at the extremes of age. Studying APOE ε polymorphisms in young children may provide the earliest indicators for individuals who might benefit from early interventions or preventive measures for future brain injuries and dementia.

The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository.

The main objective of the multi-site Pediatric Imaging, Neurocognition, and Genetics (PING) study was to create a large repository of standardized measurements of behavioral and imaging phenotypes accompanied by whole genome genotyping acquired from typically-developing children varying widely in age (3 to 20 years). This cross-sectional study produced sharable data from 1493 children, and these data have been described in several publications focusing on brain and cognitive development. Researchers may gain access to these data by applying for an account on the PING portal and filing a data use agreement. Here we describe the recruiting and screening of the children and give a brief overview of the assessments performed, the imaging methods applied, the genetic data produced, and the numbers of cases for whom different data types are available. We also cite sources of more detailed information about the methods and data. Finally we describe the procedures for accessing the data and for using the PING data exploration portal.

Dyslexia and language impairment associated genetic markers influence cortical thickness and white matter in typically developing children.

Dyslexia and language impairment (LI) are complex traits with substantial genetic components. We recently completed an association scan of the DYX2 locus, where we observed associations of markers in DCDC2, KIAA0319, ACOT13, and FAM65B with reading-, language-, and IQ-related traits. Additionally, the effects of reading-associated DYX3 markers were recently characterized using structural neuroimaging techniques. Here, we assessed the neuroimaging implications of associated DYX2 and DYX3 markers, using cortical volume, cortical thickness, and fractional anisotropy. To accomplish this, we examined eight DYX2 and three DYX3 markers in 332 subjects in the Pediatrics Imaging Neurocognition Genetics study. Imaging-genetic associations were examined by multiple linear regression, testing for influence of genotype on neuroimaging. Markers in DYX2 genes KIAA0319 and FAM65B were associated with cortical thickness in the left orbitofrontal region and global fractional anisotropy, respectively. KIAA0319 and ACOT13 were suggestively associated with overall fractional anisotropy and left pars opercularis cortical thickness, respectively. DYX3 markers showed suggestive associations with cortical thickness and volume measures in temporal regions. Notably, we did not replicate association of DYX3 markers with hippocampal measures. In summary, we performed a neuroimaging follow-up of reading-, language-, and IQ-associated DYX2 and DYX3 markers. DYX2 associations with cortical thickness may reflect variations in their role in neuronal migration. Furthermore, our findings complement gene expression and imaging studies implicating DYX3 markers in temporal regions. These studies offer insight into where and how DYX2 and DYX3 risk variants may influence neuroimaging traits. Future studies should further connect the pathways to risk variants associated with neuroimaging/neurocognitive outcomes.

Anxiety is related to indices of cortical maturation in typically developing children and adolescents.

Anxiety is a risk factor for many adverse neuropsychiatric and socioeconomic outcomes, and has been linked to functional and structural changes in the ventromedial prefrontal cortex (VMPFC). However, the nature of these differences, as well as how they develop in children and adolescents, remains poorly understood. More effective interventions to minimize the negative consequences of anxiety require better understanding of its neurobiology in children. Recent research suggests that structural imaging studies may benefit from clearly delineating between cortical surface area and thickness when examining these associations, as these distinct cortical phenotypes are influenced by different cellular mechanisms and genetic factors. The present study examined relationships between cortical surface area and thickness of the VMPFC and a self-report measure of anxiety (SCARED-R) in 287 youths aged 7-20 years from the Pediatric Imaging, Neurocognition, and Genetics (PING) study. Age and gender interactions were examined for significant associations in order to test for developmental differences. Cortical surface area and thickness were also examined simultaneously to determine whether they contribute independently to the prediction of anxiety. Anxiety was negatively associated with relative cortical surface area of the VMPFC as well as with global cortical thickness, but these associations diminished with age. The two cortical phenotypes contributed additively to the prediction of anxiety. These findings suggest that higher anxiety in children may be characterized by both delayed expansion of the VMPFC and an altered trajectory of global cortical thinning. Further longitudinal studies will be needed to confirm these findings.

Cell cycle networks link gene expression dysregulation, mutation, and brain maldevelopment in autistic toddlers.

Genetic mechanisms underlying abnormal early neural development in toddlers with Autism Spectrum Disorder (ASD) remain uncertain due to the impossibility of direct brain gene expression measurement during critical periods of early development. Recent findings from a multi-tissue study demonstrated high expression of many of the same gene networks between blood and brain tissues, in particular with cell cycle functions. We explored relationships between blood gene expression and total brain volume (TBV) in 142 ASD and control male toddlers. In control toddlers, TBV variation significantly correlated with cell cycle and protein folding gene networks, potentially impacting neuron number and synapse development. In ASD toddlers, their correlations with brain size were lost as a result of considerable changes in network organization, while cell adhesion gene networks significantly correlated with TBV variation. Cell cycle networks detected in blood are highly preserved in the human brain and are upregulated during prenatal states of development. Overall, alterations were more pronounced in bigger brains. We identified 23 candidate genes for brain maldevelopment linked to 32 genes frequently mutated in ASD. The integrated network includes genes that are dysregulated in leukocyte and/or postmortem brain tissue of ASD subjects and belong to signaling pathways regulating cell cycle G1/S and G2/M phase transition. Finally, analyses of the CHD8 subnetwork and altered transcript levels from an independent study of CHD8 suppression further confirmed the central role of genes regulating neurogenesis and cell adhesion processes in ASD brain maldevelopment.

Prediction of autism by translation and immune/inflammation coexpressed genes in toddlers from pediatric community practices.

IMPORTANCE: The identification of genomic signatures that aid early identification of individuals at risk for autism spectrum disorder (ASD) in the toddler period remains a major challenge because of the genetic and phenotypic heterogeneity of the disorder. Generally, ASD is not diagnosed before the fourth to fifth birthday. OBJECTIVE: To apply a functional genomic approach to identify a biologically relevant signature with promising performance in the diagnostic classification of infants and toddlers with ASD. DESIGN, SETTING, AND PARTICIPANTS: Proof-of-principle study of leukocyte RNA expression levels from 2 independent cohorts of children aged 1 to 4 years (142 discovery participants and 73 replication participants) using Illumina microarrays. Coexpression analysis of differentially expressed genes between Discovery ASD and control toddlers were used to define gene modules and eigengenes used in a diagnostic classification analysis. Independent validation of the classifier performance was tested on the replication cohort. Pathway enrichment and protein-protein interaction analyses were used to confirm biological relevance of the functional networks in the classifier. Participant recruitment occurred in general pediatric clinics and community settings. Male infants and toddlers (age range, 1-4 years) were enrolled in the study. Recruitment criteria followed the 1-Year Well-Baby Check-Up Approach. Diagnostic judgment followed DSM-IV-TR and Autism Diagnostic Observation Schedule criteria for autism. Participants with ASD were compared with control groups composed of typically developing toddlers as well as toddlers with global developmental or language delay. MAIN OUTCOMES AND MEASURES: Logistic regression and receiver operating characteristic curve analysis were used in a classification test to establish the accuracy, specificity, and sensitivity of the module-based classifier. RESULTS: Our signature of differentially coexpressed genes was enriched in translation and immune/inflammation functions and produced 83% accuracy. In an independent test with approximately half of the sample and a different microarray, the diagnostic classification of ASD vs control samples was 75% accurate. Consistent with its ASD specificity, our signature did not distinguish toddlers with global developmental or language delay from typically developing toddlers (62% accuracy). CONCLUSIONS AND RELEVANCE: This proof-of-principle study demonstrated that genomic biomarkers with very good sensitivity and specificity for boys with ASD in general pediatric settings can be identified. It also showed that a blood-based clinical test for at-risk male infants and toddlers could be refined and routinely implemented in pediatric diagnostic settings.