In Search of Cognitive Promotive and Protective Factors for Word Reading.

This study examined whether strong cognitive skills (i.e. vocabulary, rapid naming, verbal working memory [VWM], and processing speed [PS]) contributed to resilience in single-word reading skills in children at risk for reading difficulties because of low phonological awareness scores (PA). Promotive factors were identified by main effects and protective factors through PA x cognition interactions. This study included 1,807 children ages 8-16. As predicted, all cognitive skills were significantly related to reading, consistent with promotive effects. A significant, but small effect PA x vocabulary interaction (R2 change=.002, p=.00038) was detected but its form was not consistent with a classic protective effect. Rather, the PA x vocabulary interaction was consistent with a "skill-enhancement" pattern, such that children with strong PA and vocabulary skills had better than expected reading. This study provides a framework for reading resilience research and directs attention to promotive mechanisms underlying reading success.

The Multiple Deficit Model: Progress, Problems, and Prospects.

The multiple deficit model (MDM) was proposed because the prevailing single-deficit model provided an inadequate account of atypical neuropsychological development. Across methods and levels of analysis, there has been support for the two fundamental tenets of the MDM, that multiple predictors contribute probabilistically to neurodevelopmental disorders and shared risk factors contribute to comorbidity. Diagnostically, the multiplicity of factors means that no single cognitive deficit or combination of deficits can be used to rule in or out most neurodevelopmental disorders. Challenges for the MDM are that the theory is difficult to falsify and that current cross-sectional studies cannot establish causality. Prospects for further development of the MDM include incorporating an explicit focus on promotive and protective factors and pursuing mechanistic connections between multiple factors across levels of analysis.

Understanding Comorbidity Between Specific Learning Disabilities.

Current definitions of specific learning disability (SLD) identify a heterogeneous population that includes individuals with weaknesses in reading, math, or writing, and these academic difficulties often co-occur in many of the same individuals. The Colorado Learning Disabilities Research Center (CLDRC) is an interdisciplinary, multisite research program that uses converging levels of analysis to understand the genetic and environmental etiology, neuropsychology, and developmental outcomes of SLDs in reading (RD), math (MD), and writing (WD), along with the comorbidity between these SLDs and other developmental disorders. The latest results from the CLDRC twin study suggest that shared genetic influences contribute to the significant covariance between all aspects of reading (word reading, reading fluency, and reading comprehension) and math (calculations, math fluency, and word problems), and distinct genetic or environmental influences also contribute to weaknesses in each specific academic domain. RD and MD are associated with a range of negative outcomes on both concurrent measures and measures of functional outcomes completed 5 years after the twins were first assessed. Over the next several years the CLDRC will continue to expand on this work by administering a comprehensive test battery that includes measures of all dimensions of academic achievement that are described in current definitions of SLD and incorporating these measures in new neuroimaging and molecular genetic studies.

Cross-Disorder Cognitive Impairments in Youth Referred for Neuropsychiatric Evaluation.

OBJECTIVES: Studies suggest that impairments in some of the same domains of cognition occur in different neuropsychiatric conditions, including those known to share genetic liability. Yet, direct, multi-disorder cognitive comparisons are limited, and it remains unclear whether overlapping deficits are due to comorbidity. We aimed to extend the literature by examining cognition across different neuropsychiatric conditions and addressing comorbidity. METHODS: Subjects were 486 youth consecutively referred for neuropsychiatric evaluation and enrolled in the Longitudinal Study of Genetic Influences on Cognition. First, we assessed general ability, reaction time variability (RTV), and aspects of executive functions (EFs) in youth with non-comorbid forms of attention-deficit/hyperactivity disorder (ADHD), mood disorders and autism spectrum disorder (ASD), as well as in youth with psychosis. Second, we determined the impact of comorbid ADHD on cognition in youth with ASD and mood disorders. RESULTS: For EFs (working memory, inhibition, and shifting/ flexibility), we observed weaknesses in all diagnostic groups when participants' own ability was the referent. Decrements were subtle in relation to published normative data. For RTV, weaknesses emerged in youth with ADHD and mood disorders, but trend-level results could not rule out decrements in other conditions. Comorbidity with ADHD did not impact the pattern of weaknesses for youth with ASD or mood disorders but increased the magnitude of the decrement in those with mood disorders. CONCLUSIONS: Youth with ADHD, mood disorders, ASD, and psychosis show EF weaknesses that are not due to comorbidity. Whether such cognitive difficulties reflect genetic liability shared among these conditions requires further study. (JINS, 2018, 24, 91-103).

Extending the 'cross-disorder' relevance of executive functions to dimensional neuropsychiatric traits in youth.

BACKGROUND: Evidence that different neuropsychiatric conditions share genetic liability has increased interest in phenotypes with 'cross-disorder' relevance, as they may contribute to revised models of psychopathology. Cognition is a promising construct for study; yet, evidence that the same cognitive functions are impaired across different forms of psychopathology comes primarily from separate studies of individual categorical diagnoses versus controls. Given growing support for dimensional models that cut across traditional diagnostic boundaries, we aimed to determine, within a single cohort, whether performance on measures of executive functions (EFs) predicted dimensions of different psychopathological conditions known to share genetic liability. METHODS: Data are from 393 participants, ages 8-17, consecutively enrolled in the Longitudinal Study of Genetic Influences on Cognition (LOGIC). This project is conducting deep phenotyping and genomic analyses in youth referred for neuropsychiatric evaluation. Using structural equation modeling, we examined whether EFs predicted variation in core dimensions of the autism spectrum disorder, bipolar illness, and schizophrenia (including social responsiveness, mania/emotion regulation, and positive symptoms of psychosis, respectively). RESULTS: We modeled three cognitive factors (working memory, shifting, and executive processing speed) that loaded on a second-order EF factor. The EF factor predicted variation in our three target traits, but not in a negative control (somatization). Moreover, this EF factor was primarily associated with the overlapping (rather than unique) variance across the three outcome measures, suggesting that it related to a general increase in psychopathology symptoms across those dimensions. CONCLUSIONS: Findings extend support for the relevance of cognition to neuropsychiatric conditions that share underlying genetic risk. They suggest that higher-order cognition, including EFs, relates to the dimensional spectrum of each of these disorders and not just the clinical diagnoses. Moreover, results have implications for bottom-up models linking genes, cognition, and a general psychopathology liability.

Genetic predictors of risk and resilience in psychiatric disorders: a cross-disorder genome-wide association study of functional impairment in major depressive disorder, bipolar disorder, and schizophrenia.

Functional impairment is one of the most enduring, intractable consequences of psychiatric disorders and is both familial and heritable. Previous studies have suggested that variation in functional impairment can be independent of symptom severity. Here we report the first genome-wide association study (GWAS) of functional impairment in the context of major mental illness. Participants of European-American descent (N = 2,246) were included from three large treatment studies of bipolar disorder (STEP-BD) (N = 765), major depressive disorder (STAR*D) (N = 1091), and schizophrenia (CATIE) (N = 390). At study entry, participants completed the SF-12, a widely used measure of health-related quality of life. We performed a GWAS and pathway analysis of the mental and physical components of health-related quality of life across diagnosis (∼1.6 million single nucleotide polymorphisms), adjusting for psychiatric symptom severity. Psychiatric symptom severity was a significant predictor of functional impairment, but it accounted for less than one-third of the variance across disorders. After controlling for diagnostic category and symptom severity, the strongest evidence of genetic association was between variants in ADAMTS16 and physical functioning (P = 5.87 × 10(-8) ). Pathway analysis did not indicate significant enrichment after correction for gene clustering and multiple testing. This study illustrates a phenotypic framework for examining genetic contributions to functional impairment across psychiatric disorders.

Shared grey matter correlates of reading and attention.

Disorders of reading (developmental dyslexia) and attention (ADHD) have a high rate of comorbidity (25-40%), yet little is known about the neural underpinnings of this phenomenon. The current study investigated the shared and unique neural correlates of reading and attention in 330 typically developing children ages 8-18 from the Philadelphia Neurodevelopmental Cohort. Multiple regression analyses were used to identify regions of the brain where grey matter (GM) volume was associated with reading or attention scores (p < 0.001, cluster FDR p < 0.05). Better attention scores correlated with increased GM in the precuneus and higher reading scores were associated with greater thalamic GM. An exploratory conjunction analysis (p < 0.05, k > 239) found that GM in the caudate and precuneus correlated with both reading and attention scores. These results are consistent with a recent meta-analysis which identified GM reductions in the caudate in both dyslexia and ADHD and reveal potential shared neural correlates of reading and attention.

Compounding Effects of Domain-General Cognitive Weaknesses and Word Reading Difficulties on Anxiety Symptoms in Youth.

This study examined whether domain-general cognitive weaknesses in processing speed (PS) or executive functioning (EF) moderate the relation between word reading scores and anxiety such that lower word reading scores in combination with lower cognitive scores are associated with higher anxiety symptoms. The sample consisted of 755 youth ages 8-16 who were recruited as part of the Colorado Learning Disabilities Research Center twins study. Lower scores on PS (R2 = .007, p = .014), EF (R2 = .009, p = .006), and word reading (R2 = .006-.008, p = .010-.032) were associated with higher anxiety scores. In addition, the word reading × cognitive interactions were significant such that lower scores on PS (R2 = .010, p = .005) or EF (R2 = .013, p = .010) combined with lower word reading were associated with higher-than-expected anxiety symptoms. Results suggest that weaknesses in PS, EF, and word reading are modestly associated with higher anxiety symptoms, and these anxiety symptoms may be compounded in youth with both PS or EF weaknesses and word reading difficulties. These findings can guide assessment approaches for identifying youth with word reading challenges who may be at increased risk for anxiety.

Processing Speed is Related to the General Psychopathology Factor in Youth.

The relationship between the p factor and cognition in youth has largely focused on general cognition (IQ) and executive functions (EF). Another cognitive construct, processing speed (PS), is dissociable from IQ and EF, but has received less research attention despite being related to many different mental health symptoms. The present sample included 795 youth, ages 11-16 from the Colorado Learning Disabilities Research Center (CLDRC) sample. Confirmatory factor analyses tested multiple p factor models, with the primary model being a second-order, multi-reporter p factor. We then tested the correlation between the p factor and a latent PS factor. There was a significant, negative correlation between the p factor and PS (r(87) = -0.42, p < .001), indicating that slower processing speed is associated with higher general mental health symptoms. This association is stronger than previously reported associations with IQ or EF. This finding was robust across models that used different raters (youth and caregiver) and modeling approaches (second-order vs. bifactor). Our findings indicate that PS is related to general psychopathology symptoms. This research points to processing speed as an important transdiagnostic construct that warrants further exploration across development.

Bringing a developmental perspective to anxiety genetics.

Despite substantial recent advancements in psychiatric genetic research, progress in identifying the genetic basis of anxiety disorders has been limited. We review the candidate gene and genome-wide literatures in anxiety, which have made limited progress to date. We discuss several reasons for this hindered progress, including small samples sizes, heterogeneity, complicated comorbidity profiles, and blurred lines between normative and pathological anxiety. To address many of these challenges, we suggest a developmental, multivariate framework that can inform and enhance anxiety phenotypes for genetic research. We review the psychiatric and genetic epidemiological evidence that supports such a framework, including the early onset and chronic course of anxiety disorders, shared genetic risk factors among disorders both within and across time, and developmentally dynamic genetic influences. We propose three strategies for developmentally sensitive phenotyping: examination of early temperamental risk factors, use of latent factors to model underlying anxiety liability, and use of developmental trajectories as phenotypes. Expanding the range of phenotypic approaches will be important for advancing studies of the genetic architecture of anxiety disorders.

Heritability and Clinical Characteristics of Neuropsychological Profiles in Youth With and Without Elevated ADHD Symptoms.

OBJECTIVE: In the last decade, there has been an increase in research that aims to parse heterogeneity in attention deficit hyperactivity disorder (ADHD). The current study tests heritability of latent class neuropsychological subtypes. METHOD: Latent class analysis was used to derive subtypes in a sample of school-age twins (N = 2,564) enriched for elevated ADHD symptoms. RESULTS: Five neuropsychological profiles replicated across twin 1 and twin 2 datasets. Latent class membership was heritable overall, but heritability varied by profile and was lower than heritability of ADHD status. Variability in neuropsychological performance across domains was the strongest predictor of elevated ADHD symptoms. Neuropsychological profiles showed distinct associations with age, psychiatric symptoms and reading ability. CONCLUSION: Neuropsychological profiles are associated with unique neurocognitive presentations, but are not strong candidate endophenotypes for ADHD diagnosis.

A multiple deficit model of reading disability and attention-deficit/hyperactivity disorder: searching for shared cognitive deficits.

BACKGROUND: This study tests a multiple cognitive deficit model of reading disability (RD), attention-deficit/hyperactivity disorder (ADHD), and their comorbidity. METHODS: A structural equation model (SEM) of multiple cognitive risk factors and symptom outcome variables was constructed. The model included phonological awareness as a unique predictor of RD and response inhibition as a unique predictor of ADHD. Processing speed, naming speed, and verbal working memory were modeled as potential shared cognitive deficits. RESULTS: Model fit indices from the SEM indicated satisfactory fit. Closer inspection of the path weights revealed that processing speed was the only cognitive variable with significant unique relationships to RD and ADHD dimensions, particularly inattention. Moreover, the significant correlation between reading and inattention was reduced to non-significance when processing speed was included in the model, suggesting that processing speed primarily accounted for the phenotypic correlation (or comorbidity) between reading and inattention. CONCLUSIONS: This study illustrates the power of a multiple deficit approach to complex developmental disorders and psychopathologies, particularly for exploring comorbidities. The theoretical role of processing speed in the developmental pathways of RD and ADHD and directions for future research are discussed.

How Specific Are Learning Disabilities?

Despite historical emphasis on "specific" learning disabilities (SLDs), academic skills are strongly correlated across the curriculum. Thus, one can ask how specific SLDs truly are. To answer this question, we used bifactor models to identify variance shared across academic domains (academic g), as well as variance unique to reading, mathematics, and writing. Participants were 686 children ages 8 to 16. Although the sample was overselected for learning disabilities, we intentionally included children across the full range of individual differences in this study in response to growing recognition that a dimensional, quantitative view of SLD is more accurate than a categorical view. Confirmatory factor analysis identified five academic domains (basic reading, reading comprehension, basic math, math problem-solving, and written expression); spelling clustered with basic reading and not writing. In the bifactor model, all measures loaded significantly on academic g. Basic reading and mathematics maintained variance distinct from academic g, consistent with the notion of SLDs in these domains. Writing did not maintain specific variance apart from academic g, and evidence for reading comprehension-specific variance was mixed. Academic g was strongly correlated with cognitive g (r = .72) but not identical to it. Implications for SLD diagnosis are discussed.

A Review of Online Dyslexia Learning Modules.

This paper presents a comprehensive review of publicly available online dyslexia learning modules with a particular focus on the extent to which modules address the prevalent myth that dyslexia is caused by "backwards reading." The authors conducted a systematic internet search to identify publicly available online dyslexia learning modules and coded the content across education, neurocognition, and policy disciplinary domains. We identified 18 topics across a small number (N = 14) of publicly available modules that focused on dyslexia, with only two modules directly addressing this dyslexia myth. While both identified this myth as false, neither provided information about the neurocognitive underpinnings of dyslexia to explain why this myth is false. This review will be useful for guiding further development of online dyslexia learning modules which are urgently needed due to persisting misinformation about this disorder. The coded content reviews of each module will also be beneficial for directing attention to existing resources for professional development on dyslexia.

Gene X environment interactions in reading disability and attention-deficit/hyperactivity disorder.

This article examines Gene x Environment (G x E) interactions in two comorbid developmental disorders--reading disability (RD) and attention-deficit/hyperactivity disorder (ADHD)--as a window on broader issues on G x E interactions in developmental psychology. The authors first briefly review types of G x E interactions, methods for detecting them, and challenges researchers confront in interpreting such interactions. They then review previous evidence for G x E interactions in RD and ADHD, the directions of which are opposite to each other: bioecological for RD and diathesis stress for ADHD. Given these results, the authors formulate and test predictions about G x E interactions that would be expected at the favorable end of each symptom dimension (e.g., above-average reading or attention). Consistent with their prediction, the authors found initial evidence for a resilience interaction for above-average reading: higher heritability in the presence of lower parental education. However, they did not find a G x E interaction at the favorable end of the ADHD symptom dimension. The authors conclude with implications for future research.

Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies.

BACKGROUND: Dyslexia and Attention-deficit/hyperactivity disorder (ADHD) are highly comorbid neurodevelopmental disorders (estimates of 25-40% bidirectional comorbidity). Previous work has identified strong genetic and cognitive overlap between the disorders, but neural overlap is relatively unexplored. This study is a systematic meta-analysis of existing voxel-based morphometry studies to determine whether there is any overlap in the gray matter correlates of both disorders. METHODS: We conducted anatomic likelihood estimate (ALE) meta-analyses of voxel-based morphometry studies in which individuals with dyslexia (15 studies; 417 cases, 416 controls) or ADHD (22 studies; 898 cases, 763 controls) were compared to typically developing controls. We generated ALE maps for dyslexia vs. controls and ADHD vs. controls using more conservative (p < .001, k = 50) and more lenient (p < .005, k = 50) thresholds. To determine the overlap of gray matter correlates of dyslexia and ADHD, we examined the statistical conjunction between the ALE maps for dyslexia vs. controls and ADHD vs. controls (false discovery rate [FDR] p < .05, k = 50, 5000 permutations). RESULTS: Results showed largely distinct gray matter differences associated with dyslexia and ADHD. There was no evidence of statistically significant gray matter overlap at our conservative threshold, and only one region of overlap in the right caudate at our more lenient threshold. Reduced gray matter in the right caudate may be relevant to shared cognitive correlates in executive functioning and/or procedural learning. The more general finding of largely distinct regional differences in gray matter between dyslexia and ADHD suggests that other neuroimaging modalities may be more sensitive to overlapping neural correlates, and that current neuroimaging recruitment approaches may be hindering progress toward uncovering neural systems associated with comorbidity. CONCLUSIONS: The current study is the first to meta-analyze overlap between gray matter differences in dyslexia and ADHD, which is a critical step toward constructing a multi-level understanding of this comorbidity that spans the genetic, neural, and cognitive levels of analysis.

Children with comorbid speech sound disorder and specific language impairment are at increased risk for attention-deficit/hyperactivity disorder.

This study focuses on the comorbidity between attention-deficit/hyperactivity disorder (ADHD) symptoms and speech sound disorder (SSD). SSD is a developmental disorder characterized by speech production errors that impact intelligibility. Previous research addressing this comorbidity has typically used heterogeneous groups of speech-language disordered children. This study employed more precise speech-language diagnostic criteria and examined ADHD symptomatology in 108 SSD children between the ages of 4 and 7 years old with specific language impairment (SLI) (n = 23, 14 males, 9 females) and without SLI (n = 85, 49 males, 36 females). We also examined whether a subcategory of SSD, persistent (n = 39, 25 males, 14 females) versus normalized SSD (n = 67, 38 males, 29 females), was associated with ADHD and/or interacted with SLI to predict ADHD symptomatology. Results indicated that participants in the SSD + SLI group had higher rates of inattentive ADHD symptoms than those in the SSD-only and control groups. In addition, an unexpected interaction emerged such that children with SLI and normalized-SSD had significantly higher ADHD inattentive ratings than the other subgroups. A proposed explanation for this interaction is discussed.

Breakthroughs in the search for dyslexia candidate genes.

Four genes have recently been proposed as candidates for dyslexia: dyslexia susceptibility 1 candidate 1 (DYX1C1), roundabout Drosophila homolog 1 (ROBO1), doublecortin domain-containing protein 2 (DCDC2) and KIAA0319. Each gene is implicated in global brain-development processes such as neural migration and axonal guidance, with the exception of DYX1C1, the function of which is still unknown. The most immediate clinical prospect of the discovery of these genes is the possibility of early identification of dyslexia via genetic screening. However, research efforts have yet to identify a functional mutation in any of these genes. When causal variants are identified, they will need to be considered within a multifactorial framework, which is likely to involve gene-gene and gene-environment interactions, to make accurate predictions of diagnostic status.

Neuropsychology and genetics of speech, language, and literacy disorders.

The authors review the neuropsychology, brain bases, and genetics of three related disorders of language development: reading disability, or developmental dyslexia (RD); language impairment (LI); and speech sound disorder (SSD). Over the past three decades, cognitive analysis has demonstrated that the reading difficulties of most children who have RD result from phonologic impairments (difficulties processing the sound structure of language). Although understanding of LI and SSD is somewhat less developed, both disorders are also associated with phonologic impairments, which may account for their comorbidity with RD. Research across levels of analysis is progressing rapidly to promote understanding not only of each disorder by itself but also of the relationships of the three disorders to each other.

Dispelling the Myth: Training in Education or Neuroscience Decreases but Does Not Eliminate Beliefs in Neuromyths.

Neuromyths are misconceptions about brain research and its application to education and learning. Previous research has shown that these myths may be quite pervasive among educators, but less is known about how these rates compare to the general public or to individuals who have more exposure to neuroscience. This study is the first to use a large sample from the United States to compare the prevalence and predictors of neuromyths among educators, the general public, and individuals with high neuroscience exposure. Neuromyth survey responses and demographics were gathered via an online survey hosted at TestMyBrain.org. We compared performance among the three groups of interest: educators (N = 598), high neuroscience exposure (N = 234), and the general public (N = 3,045) and analyzed predictors of individual differences in neuromyths performance. In an exploratory factor analysis, we found that a core group of 7 "classic" neuromyths factored together (items related to learning styles, dyslexia, the Mozart effect, the impact of sugar on attention, right-brain/left-brain learners, and using 10% of the brain). The general public endorsed the greatest number of neuromyths (M = 68%), with significantly fewer endorsed by educators (M = 56%), and still fewer endorsed by the high neuroscience exposure group (M = 46%). The two most commonly endorsed neuromyths across all groups were related to learning styles and dyslexia. More accurate performance on neuromyths was predicted by age (being younger), education (having a graduate degree), exposure to neuroscience courses, and exposure to peer-reviewed science. These findings suggest that training in education and neuroscience can help reduce but does not eliminate belief in neuromyths. We discuss the possible underlying roots of the most prevalent neuromyths and implications for classroom practice. These empirical results can be useful for developing comprehensive training modules for educators that target general misconceptions about the brain and learning.