Familial clustering of psychiatric disorders and low IQ

Background Although the ICD and DSM differentiate between different psychiatric disorders, these often share symptoms, risk factors, and treatments. This was a population-based, case–control, sibling study examining familial clustering of all psychiatric disorders and low IQ, using data from the Israel Draft-Board Registry on all Jewish adolescents assessed between 1998 and 2014. Methods We identified all cases with autism spectrum disorder (ASD, N = 2128), severe intellectual disability (ID, N = 9572), attention-deficit hyperactive disorder (ADHD) (N = 3272), psychotic (N = 7902), mood (N = 9704), anxiety (N = 10 606), personality (N = 24 816), or substance/alcohol abuse (N = 791) disorders, and low IQ (⩾2 SDs below the population mean, N = 31 186). Non-CNS control disorders were adolescents with Type-1 diabetes (N = 2427), hernia (N = 29 558) or hematological malignancies (N = 931). Each case was matched with 10 age-matched controls selected at random from the Draft-Board Registry, with replacement, and for each case and matched controls, we ascertained all full siblings. The main outcome measure was the relative recurrence risk (RRR) of the sibling of a case having the same (within-disorder RRR) or a different (across-disorder RRR) disorder. Results Within-disorder RRRs were increased for all diagnostic categories, ranging from 11.53 [95% confidence interval (CI): 9.23–14.40] for ASD to 2.93 (95% CI: 2.80–3.07) for personality disorders. The median across-disorder RRR between any pair of psychiatric disorders was 2.16 (95% CI: 1.45–2.43); the median RRR between low IQ and any psychiatric disorder was 1.37 (95% CI: 0.93–1.98). There was no consistent increase in across-disorder RRRs between the non-CNS disorders and psychiatric disorders and/or low IQ. Conclusion These large population-based study findings suggest shared etiologies among most psychiatric disorders, and low IQ.

Default Mode and Fronto-Parietal Network Associations with IQ Development Across Childhood in Autism

Background: Intellectual disability affects approximately one third of individuals with autism spectrum disorder (autism), yet a major unresolved question remains concerning the neurobiology that differentiates autistic individuals with and without intellectual disability. IQ is highly variable during childhood. We previously identified subgroups of autistic children with different trajectories of intellectual development from early childhood (2-3½ yeas) up to middle childhood (9-12 years): (a) Persistently-High: Individuals whose intelligence quotients (IQs) remained in the average or better range during this period, (b) Persistently-Low: Individuals whose IQs remained in the range of intellectual disability (IQ < 70) throughout development, and (c) Changers: Individuals whose IQs began in the range of intellectual disability but increased to the borderline or normal IQ range by middle childhood. In the present research, we sought to identify neurobiology that differentiates these trajectory-defined groups within our autism cohort in two brain networks with established links to intellectual functioning and its impairment in (1) the frontoparietal network (FPN), and (2) the default mode network (DMN). Methods: We conducted multivariate distance matrix regression (MDMR) and effect size analyses to examine the volumes of 22 brain regions (11 regions x 2 hemispheres) within the FPN and 24 (12 regions x 2 hemispheres) within the DMN in 48 Persistently-High (18 female), 108 Persistently-Low (32 female), and 109 Changers (39 female) using structural MRI that had been acquired at baseline, and IQ measurements from up to three time points spanning early to middle childhood (Mean Age Time 1: 3.2 years; Time 2: 5.4 years; Time 3: 11.3 years). FPN and DMN network regions of interest were defined on the basis of the large-scale networks defined in Smith et al., (2009).Results: Changers exhibited different DMN network structure from both Persistently-Low and Persistently-High trajectory groups at baseline, but the Persistently-High did not differ from the Persistently-Low group, suggesting that DMN structure may be an early predictor for change in IQ trajectory across childhood. In contrast, Persistently-High exhibited differences in the FPN from both Persistently-Low and Changers groups at baseline, suggesting a difference related more to concurrent IQ and the absence of intellectual disability. Conclusions: Within autism, DMN structure at baseline may differentiate individuals with persistently low IQ from those with more transitory low IQ that improves to the borderline range or better through early childhood, potentially indicating compensatory mechanisms which may be targeted by future interventions. The brain structure differences between these three IQ-based subgroups may be indicative of distinct neural underpinnings of autism phenotypic subtypes.

Assessing the feasibility of a classroom-based visual attention training program targeting academics for students with extremely low IQ

Background This feasibility study investigated the viability of implementing a cognitive-based training program (NeuroTracker) and assessing its potential effects on academic performance for adolescents with extremely low IQ. Methods Twenty-six adolescents aged between 11 and 16 years with a Wechsler-based IQs in the extremely low range (MIQ = 56.00, SDIQ = 13.89) completed 15 training sessions on either the NeuroTracker or an active control task; math and reading performance were assessed using clinically validated instruments before and after training. Recruitment and retention rates, adherence, and properties of the academic measures were assessed. Results All recruited participants completed 15 training sessions within a 6-week period. Eighty-three percent of participants meeting initial inclusion criteria completed all stages of the study from baseline to post-intervention assessments. Some limitations of the academic measures were identified. Conclusions Results suggest that implementing NeuroTracker as a classroom-based intervention and using clinically validated outcome measures is feasible with this population.

Dyslexia Primer for Social Work

Dyslexia is a lifelong epigenetic neurobiological difference (neurodiversity) in brain formation and processing. Though highly prevalent, most people, including social workers, know little about dyslexia. Whereas dyslexia predicts common cognitive strengths and weaknesses, it is most often associated only with weaknesses, due to misinformation or a simple lack of information. As a result, pervasive myths (e.g., laziness, low IQ) drive beliefs, attitudes, and policies that contribute to disproportionally poorer educational, financial, justice system, and mental health outcomes for individuals with dyslexia – a cycle of externally and internally applied stigmas with significant practical effects. This analysis applies a person-in-environment conceptual framework to explain this cycle, as a step toward disrupting it. The analysis uses translational research methods, drawing from current science, to provide positive framing to dispel common stigmatizing myths and to foster strengths-based social work practice and advocacy by and for individuals with dyslexia.

Gray-Matter Correlates of Reading Fluency Deficits: SES Matters, IQ Does Not

Brain correlates of reading ability have been intensely investigated. Most studies have focused on single-word reading and phonological processing, but the brain basis of reading fluency remains poorly explored to date. Here, in a voxel-based morphometry study with 8-year-old children, we compared fluent readers (n = 18; 7 boys) with dysfluent readers with normal IQ (n = 18; 6 boys) and with low IQ (n = 18; 10 boys). Relative to dysfluent readers, fluent readers had larger gray matter volume in the right superior temporal gyrus and the two subgroups of dysfluent readers did not differ from each other, as shown in frequentist and Bayesian analyses. Pairwise comparisons showed that dysfluent readers of normal and low IQ did not differ in core reading regions and that both subgroups had less gray matter volume than fluent readers in occipito-temporal, parieto-temporal and fusiform areas. We also examined gray matter volume in matched subgroups of dysfluent readers differing only in socioeconomic status (SES): lower-SES (n = 14; 7 boys) vs. higher-SES (n = 14; 7 boys). Higher-SES dysfluent readers had larger gray matter volume in the right angular gyrus than their lower-SES peers, and the volume of this cluster correlated positively with lexico-semantic fluency. Age, sex, IQ, and gray matter volume of the right angular cluster explained 68% of the variance in the reading fluency of higher-SES dysfluent readers. In sum, this study shows that gray matter correlates of dysfluent reading are independent of IQ and suggests that SES modulates areas sub-serving lexico-semantic processes in dysfluent readers — two findings that may be useful to inform language/reading remediation programs.

Compact and Low-Power Under-Voltage Lockout and Thermal-Shutdown Protection Circuits Using a Novel Low-IQ All-in-One Bandgap Comparator

This paper presents a novel and compact bandgap comparator (BGRCOMP) for under-voltage lockout (UVLO) and thermal shutdown (TSD) protection circuits. The proposed BGRCOMP is self-referenced and combines the advantages of both a high-accuracy bandgap reference and a comparator into one single circuit. A latch-controlled biasing technique is also presented, which reduces static power consumption of the proposed BGRCOMP. The proposed BGRCOMP is used for the design of compact and low power UVLO and TSD circuits. The post-layout simulation results using a 0.18 µm BCD-on-SOI technology prove the attractive performance of the UVLO and TSD with a static current (I_Q) of 7.76 µA and 5.4 µA from a 5 V supply, respectively. The deviations of UVLO thresholds are less than 3 mV in the temperature range of -40~85 °C.

Compact and Low-Power Under-Voltage Lockout and Thermal-Shutdown Protection Circuits Using a Novel Low-IQ All-in-One Bandgap Comparator

This paper presents a novel and compact bandgap comparator (BGRCOMP) for under-voltage lockout (UVLO) and thermal shutdown (TSD) protection circuits. The proposed BGRCOMP is self-referenced and combines the advantages of both a high-accuracy bandgap reference and a comparator into one single circuit. A latch-controlled biasing technique is also presented, which reduces static power consumption of the proposed BGRCOMP. The proposed BGRCOMP is used for the design of compact and low power UVLO and TSD circuits. The post-layout simulation results using a 0.18 µm BCD-on-SOI technology prove the attractive performance of the UVLO and TSD with a static current (I_Q) of 7.76 µA and 5.4 µA from a 5 V supply, respectively. The deviations of UVLO thresholds are less than 3 mV in the temperature range of -40~85 °C.