We introduce a novel method called Prophetic Granger Causality (PGC) for inferring gene regulatory networks (GRNs) from protein-level time series data. The method uses an L1-penalized regression ...adaptation of Granger Causality to model protein levels as a function of time, stimuli, and other perturbations. When combined with a data-independent network prior, the framework outperformed all other methods submitted to the HPN-DREAM 8 breast cancer network inference challenge. Our investigations reveal that PGC provides complementary information to other approaches, raising the performance of ensemble learners, while on its own achieves moderate performance. Thus, PGC serves as a valuable new tool in the bioinformatics toolkit for analyzing temporal datasets. We investigate the general and cell-specific interactions predicted by our method and find several novel interactions, demonstrating the utility of the approach in charting new tumor wiring.
The fields of developmental psychopathology, developmental neuroscience, and behavioral genetics are increasingly moving toward a data sharing model to improve reproducibility, robustness, and ...generalizability of findings. This approach is particularly critical for understanding attention-deficit/hyperactivity disorder (ADHD), which has unique public health importance given its early onset, high prevalence, individual variability, and causal association with co-occurring and later developing problems. A further priority concerns multi-disciplinary/multi-method datasets that can span different units of analysis. Here, we describe a public dataset using a case-control design for ADHD that includes: multi-method, multi-measure, multi-informant, multi-trait data, and multi-clinician evaluation and phenotyping. It spans > 12 years of annual follow-up with a lag longitudinal design allowing age-based analyses spanning age 7–19 + years with a full age range from 7 to 21. Measures span genetic and epigenetic (DNA methylation) array data; EEG, functional and structural MRI neuroimaging; and psychophysiological, psychosocial, clinical and functional outcomes data. The resource also benefits from an autism spectrum disorder add-on cohort and a cross sectional case-control ADHD cohort from a different geographical region for replication and generalizability. Datasets allowing for integration from genes to nervous system to behavior represent the “next generation” of researchable cohorts for ADHD and developmental psychopathology.
Background
attention‐deficit/hyperactivity disorder (ADHD) is associated with both polygenic liability and environmental exposures, both intrinsic to the family, such as family conflict, and ...extrinsic, such as air pollution. However, much less is known about the interplay between environmental and genetic risks relevant to ADHD—a better understanding of which could inform both mechanistic models and clinical prediction algorithms.
Methods
Two independent data sets, the population‐based Adolescent Brain Cognitive Development Study (ABCD) (N = 11,876) and the case‐control Oregon‐ADHD‐1000 (N = 1449), were used to examine additive (G + E) and interactive (GxE) effects of selected polygenic risk scores (PRS) and environmental factors in a cross‐sectional design. Genetic risk was measured using PRS for nine mental health disorders/traits. Exposures included family income, family conflict/negative sentiment, and geocoded measures of area deprivation, lead exposure risk, and air pollution exposure (nitrogen dioxide and fine particulate matter).
Results
ADHD PRS and family conflict jointly predicted concurrent ADHD symptoms in both cohorts. Additive‐effects models, including both genetic and environmental factors, explained significantly more variation in symptoms than any individual factor alone (joint R2 = .091 for total symptoms in ABCD; joint R2 = .173 in Oregon‐ADHD‐1000; all delta‐R2 p‐values <2e‐7). Significant effect size heterogeneity across ancestry groups was observed for genetic and environmental factors (e.g., Q = 9.01, p = .011 for major depressive disorder PRS; Q = 13.34, p = .001 for area deprivation). GxE interactions observed in the full ABCD cohort suggested stronger environmental effects when genetic risk is low, though they did not replicate.
Conclusions
Reproducible additive effects of PRS and family environment on ADHD symptoms were found, but GxE interaction effects were not replicated and appeared confounded by ancestry. Results highlight the potential value of combining exposures and PRS in clinical prediction algorithms. The observed differences in risks across ancestry groups warrant further study to avoid health care disparities.
Patient-specific aberrant expression patterns in conjunction with functional screening assays can guide elucidation of the cancer genome architecture and identification of therapeutic targets. Since ...most statistical methods for expression analysis are focused on differences between experimental groups, the performance of approaches for patient-specific expression analyses are currently less well characterized. A comparison of methods for the identification of genes that are dysregulated relative to a single sample in a given set of experimental samples, to our knowledge, has not been performed.
We systematically evaluated several methods including variations on the nearest neighbor based outlying degree method, as well as the Zscore and a robust variant for their suitability to detect patient-specific events. The methods were assessed using both simulations and expression data from a cohort of pediatric acute B lymphoblastic leukemia patients.
We first assessed power and false discovery rates using simulations and found that even under optimal conditions, high effect sizes (>4 unit differences) were necessary to have acceptable power for any method (>0.9) though high false discovery rates (>0.1) were pervasive across simulation conditions. Next we introduced a technical factor into the simulation and found that performance was reduced for all methods and that using weights with the outlying degree could provide performance gains depending on the number of samples and genes affected by the technical factor. In our use case that highlights the integration of functional assays and aberrant expression in a patient cohort (the identification of gene dysregulation events associated with the targets from a siRNA screen), we demonstrated that both the outlying degree and the Zscore can successfully identify genes dysregulated in one patient sample. However, only the outlying degree can identify genes dysregulated across several patient samples.
Our results show that outlying degree methods may be a useful alternative to the Zscore or Rscore in a personalized medicine context especially in small to medium sized (between 10 and 50 samples) expression datasets with moderate to high sample-to-sample variability. From these results we provide guidelines for detection of aberrant expression in a precision medicine context.
Summary
Upregulation of the Wilms' tumour 1 (WT1) gene is common in acute myeloid leukaemia (AML) and is associated with poor prognosis. WT1 generates 12 primary transcripts through different ...translation initiation sites and alternative splicing. The short WT1 transcripts express abundantly in primary leukaemia samples. We observed that overexpression of short WT1 transcripts lacking exon 5 with and without the KTS motif (sWT1+/− and sWT1−/−) led to reduced cell growth. However, only sWT1+/− overexpression resulted in decreased CD71 expression, G1 arrest, and cytarabine resistance. Primary AML patient cells with low CD71 expression exhibit resistance to cytarabine, suggesting that CD71 may serve as a potential biomarker for chemotherapy. RNAseq differential expressed gene analysis identified two transcription factors, HOXA3 and GATA2, that are specifically upregulated in sWT1+/− cells, whereas CDKN1A is upregulated in sWT1−/− cells. Overexpression of either HOXA3 or GATA2 reproduced the effects of sWT1+/−, including decreased cell growth, G1 arrest, reduced CD71 expression and cytarabine resistance. HOXA3 expression correlates with chemotherapy response and overall survival in NPM1 mutation‐negative leukaemia specimens. Overexpression of HOXA3 leads to drug resistance against a broad spectrum of chemotherapeutic agents. Our results suggest that WT1 regulates cell proliferation and drug sensitivity in an isoform‐specific manner.
Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical ...annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a dataset that has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort concordance and identify features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally affecting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers avenues for mechanistic exploration and drug development, and reveals tools for predicting outcome in AML.
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•Acute myeloid leukemia patient cohort with clinical, molecular, drug response data•Validation and discovery of diverse biological features of drug response•Broad mapping of tumor cell differentiation state affecting response to drugs•Modeling reveals a strong and targetable determinant of clinical outcome
Bottomly et al. present a functional genomic resource composed of molecular, clinical, and drug response data on acute myeloid leukemia patient specimens. Through integration of all of these data, they identify genetic and cell differentiation state features that predict drug response, and they utilize modeling to identify targetable determinants of clinical outcome.
Background
A central nosological problem concerns the etiological relationship of emotional dysregulation with ADHD. Molecular genetic risk scores provide a novel method for informing this question.
...Methods
Participants were 514 community‐recruited children of Northern European descent age 7‐11 defined as ADHD or non‐ADHD by detailed research evaluation. Parents‐rated ADHD on standardized ratings and child temperament on the Temperament in Middle Childhood Questionnaire (TMCQ) and reported on ADHD and comorbid disorders by semi‐structured clinical interview. Categorical and dimensional variables were created for ADHD, emotional dysregulation (implicating disruption of regulation of both anger‐irritability and of positive valence surgency‐sensation seeking), and irritability alone (anger dysregulation). Genome‐wide polygenic risk scores (PRS) were computed for ADHD and depression genetic liability. Structural equation models and computationally derived emotion profiles guided analysis.
Results
The ADHD PRS was associated in variable‐centered analyses with irritability (β = .179, 95% CI = 0.087–0.280; ΔR2 = .034, p < .0002), but also with surgency/sensation seeking (B = .146, 95%CI = 0.052–0.240, ΔR2=.022, p = .002). In person‐centered analysis, the ADHD PRS was elevated in the emotion dysregulation ADHD group versus other ADHD children (OR = 1.44, 95% CI = 1.03–2.20, Nagelkerke ΔR2 = .013, p = .033) but did not differentiate irritable from surgent ADHD profiles. All effects were independent of variation in ADHD severity across traits or groups. The depression PRS was related to oppositional defiant disorder but not to ADHD emotion dysregulation.
Conclusions
Irritability‐anger and surgency‐sensation seeking, as forms of negative and positively valenced dysregulated affect in ADHD populations, both relate principally to ADHD genetic risk and not mood‐related genetic risk.
Epigenetic variation in peripheral tissues is being widely studied as a molecular biomarker of complex disease and disease-related exposures. To date, few studies have examined differences in DNA ...methylation associated with attention-deficit hyperactivity disorder (ADHD). In this study, we profiled genetic and methylomic variation across the genome in saliva samples from children (age 7-12 years) with clinically established ADHD (N = 391) and nonpsychiatric controls (N = 213). We tested for differentially methylated positions (DMPs) associated with both ADHD diagnosis and ADHD polygenic risk score, by using linear regression models including smoking, medication effects, and other potential confounders in our statistical models. Our results support previously reported associations between ADHD and DNA methylation levels at sites annotated to VIPR2, and identify several novel disease-associated DMPs (p < 1e-5), although none of them were genome-wide significant. The two top-ranked, ADHD-associated DMPs (cg17478313 annotated to SLC7A8 and cg21609804 annotated to MARK2) are also significantly associated with nearby SNPs (p = 1.2e-46 and p = 2.07e-59), providing evidence that disease-associated DMPs are under genetic control. We also report a genome-wide significant association between ADHD polygenic risk and variable DNA methylation at a site annotated to the promoter of GART and SON (p = 6.71E-8). Finally, we show that ADHD-associated SNPs colocalize with SNPs associated with methylation levels in saliva. This is the first large-scale study of DNA methylation in children with ADHD. Our results represent novel epigenetic biomarkers for ADHD that may be useful for patient stratification, reinforce the importance of genetic effects on DNA methylation, and provide plausible molecular mechanisms for ADHD risk variants.
Understanding the role of endophenotypes is essential for process models of psychopathology. This study examined which candidate cognitive endophenotypes statistically mediate common variant genetic ...risk for attention-deficit/hyperactivity disorder (ADHD).
A case-control design using community-recruited volunteer children 7 to 11 years of age (n = 656, n = 435 ADHD), of whom 514 were of homogenous European ancestry for the primary models (n = 337 ADHD, 177 non-ADHD). Children were assessed with a multi-informant, best-estimate diagnostic procedure and laboratory measures of working memory, response inhibition, executive functioning, arousal/attention, temporal information processing, and processing speed. Latent variables were created for the candidate cognitive measures and for parent- and teacher-rated ADHD dimensions. Polygenic risk scores (PGS) were computed using a discovery sample of 20,183 individuals with ADHD and 35,191 controls from the Psychiatric Genetics Consortium. Cognitive measures that survived multiple testing correction for association with the PGS were evaluated for mediation with ADHD using structural equation models.
Results were essentially identical in the homogeneous European ancestry subgroup (n = 514) and in the full sample (N = 656). For the European population, the PGS was associated with ADHD diagnosis (Nagelkerke R
= 0.045; β = 0.233, SE = 0.053, p = .000011) and multi-indicator dimensional ADHD latent variables by parent report (β = 0.185, SE = 0.043) and teacher report (β = 0.165, SE = 0.042). The PGS effect was statistically mediated by working memory (indirect effect, β = 0.101, SE = 0.029, 95% CI = 0.05, 0.16, p = .00049, 43% of genetic effect accounted for) and arousal/alertness (indirect effect β = 0.115, 95% CI = 0.04, 0.20, SE = 0.041, p = .005, 49% of genetic effect accounted for).
This is the first clear demonstration from molecular genetic data that working memory and arousal regulation are promising cognitive endophenotypes for ADHD with regard to mediating genetic risk from common genetic variants.
To evaluate the prevalence and major comorbidities of ADHD using different operational definitions in a newly available national dataset and to test the utility of operational definitions against ...genetic and cognitive correlates.
The US Adolescent Brain Cognitive Development (ABCD) Study enrolled 11,878 children aged 9-10 years at baseline. ADHD prevalence, comorbidity, and association with polygenic risk score and laboratory-assessed executive functions were calculated at 4 thresholds of ADHD phenotype restrictiveness. Bias from missingness, sampling, and nesting were addressed statistically.
Prevalence of current ADHD for 9- to 10-year old children was 3.53% (95% CI 3.14%-3.92%) when Computerized Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS-COMP) score and parent and teacher ratings were required to converge. Of ADHD cases so defined, 70% had a comorbid psychiatric disorder. After control for overlapping comorbidity and ruling out for psychosis or low IQ, 30.9% (95% CI 25.7%-36.7%) had a comorbid disruptive behavior disorder, 27.4% (95% CI 22.3%-33.1%) had an anxiety or fear disorder, and 2.1% (95% CI 1.2%-3.8%) had a mood disorder. Children in the top decile of polygenic load incurred a 63% increased chance of having ADHD vs the bottom half of polygenic load (p < .01)-an effect detected only with a stringent phenotype definition. Dimensional latent variables for irritability, externalizing, and ADHD yielded convergent results for cognitive correlates.
This fresh estimate of national prevalence of ADHD in the United States suggests that the DSM-5 definition requiring multiple informants yields a prevalence of about 3.5%. Results may inform further ADHD studies in the ABCD sample.
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