scholarly journals Sparse parallel independent component analysis and its application to identify linked genomic and gray matter alterations underlying working memory impairment in attention-deficit/hyperactivity disorder

2020 ◽  
Author(s):  
Kuaikuai Duan ◽  
Jiayu Chen ◽  
Vince D. Calhoun ◽  
Wenhao Jiang ◽  
Kelly Rootes-Murdy ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Working Memory ◽  
Independent Component Analysis ◽  
Psychiatric Disorders ◽  
Gray Matter ◽  
Attention Deficit ◽  
Component Analysis ◽  
Independent Component ◽  
Hyperactivity Disorder ◽  
Common Genetic Variants

AbstractMost psychiatric disorders are highly heritable and associated with altered brain structural and functional patterns. Data fusion analyses on brain imaging and genetics, one of which is parallel independent component analysis (pICA), enable the link of genomic factors to brain patterns. Due to the small to modest effect sizes of common genetic variants in psychiatric disorders, it is usually challenging to reliably separate disorder-related genetic factors from the rest of the genome with the typical size of clinical samples. To alleviate this problem, we propose sparse parallel independent component analysis (spICA) to leverage the sparsity of individual genomic sources. The sparsity is enforced by performing Hoyer projection on the estimated independent sources. Simulation results demonstrate that the proposed spICA yields improved detection of independent sources and imaging-genomic associations compared to pICA. We applied spICA to gray matter volume (GMV) and single nucleotide polymorphism (SNP) data of 341 unrelated adults, including 127 controls, 167 attention-deficit/hyperactivity disorder (ADHD) cases, and 47 unaffected siblings. We identified one SNP source significantly and positively associated with a GMV source in superior/middle frontal regions. This association was replicated with a smaller effect size in 317 adolescents from ADHD families, including 188 individuals with ADHD and 129 unaffected siblings. The association was found to be more significant in ADHD families than controls, and stronger in adults and older adolescents than younger ones. The identified GMV source in superior/middle frontal regions was not correlated with head motion parameters and its loadings (expression levels) were reduced in adolescent (but not adult) individuals with ADHD. This GMV source was associated with working memory deficits in both adult and adolescent individuals with ADHD. The identified SNP component highlights SNPs in genes encoding long non-coding RNAs and SNPs in genes MEF2C, CADM2, and CADPS2, which have known functions relevant for modulating neuronal substrates underlying high-level cognition in ADHD.

Risk of attention deficit/hyperactivity disorder (ADHD) and other psychiatric disorders in siblings of ADHD probands

2019 ◽  
Vol 48 (1) ◽  
pp. 44-49 ◽  
Author(s):  
Catalina Hidalgo-López ◽  
Alejandra María Gómez-Álzate ◽  
Jenny García-Valencia ◽  
Juan David Palacio-Ortiz
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Psychiatric Disorders ◽  
Attention Deficit ◽  
Hyperactivity Disorder

Good Holders, Bad Shufflers: An Examination of Working Memory Processes and Modalities in Children with and without Attention-Deficit/Hyperactivity Disorder

2015 ◽  
Vol 22 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Ashley N. Simone ◽  
Anne-Claude V. Bédard ◽  
David J. Marks ◽  
Jeffrey M. Halperin
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Working Memory ◽  
Attention Deficit ◽  
Digit Span ◽  
Specific Pattern ◽  
Significant Group ◽  
Children With Adhd ◽  
Hyperactivity Disorder ◽  
Group Condition ◽  
Visual Spatial

AbstractThe aim of this study was to examine working memory (WM) modalities (visual-spatial and auditory-verbal) and processes (maintenance and manipulation) in children with and without attention-deficit/hyperactivity disorder (ADHD). The sample consisted of 63 8-year-old children with ADHD and an age- and sex-matched non-ADHD comparison group (N=51). Auditory-verbal and visual-spatial WM were assessed using the Digit Span and Spatial Span subtests from the Wechsler Intelligence Scale for Children Integrated - Fourth Edition. WM maintenance and manipulation were assessed via forward and backward span indices, respectively. Data were analyzed using a 3-way Group (ADHD vs. non-ADHD)×Modality (Auditory-Verbal vs. Visual-Spatial)×Condition (Forward vs. Backward) Analysis of Variance (ANOVA). Secondary analyses examined differences between Combined and Predominantly Inattentive ADHD presentations. Significant Group×Condition (p=.02) and Group×Modality (p=.03) interactions indicated differentially poorer performance by those with ADHD on backward relative to forward and visual-spatial relative to auditory-verbal tasks, respectively. The 3-way interaction was not significant. Analyses targeting ADHD presentations yielded a significant Group×Condition interaction (p=.009) such that children with ADHD-Predominantly Inattentive Presentation performed differentially poorer on backward relative to forward tasks compared to the children with ADHD-Combined Presentation. Findings indicate a specific pattern of WM weaknesses (i.e., WM manipulation and visual-spatial tasks) for children with ADHD. Furthermore, differential patterns of WM performance were found for children with ADHD-Predominantly Inattentive versus Combined Presentations. (JINS, 2016, 22, 1–11)

Neural correlates of visuospatial working memory in attention-deficit/hyperactivity disorder and healthy controls

2015 ◽  
Vol 233 (2) ◽  
pp. 233-242 ◽  
Author(s):  
Hanneke van Ewijk ◽  
Wouter D. Weeda ◽  
Dirk J. Heslenfeld ◽  
Marjolein Luman ◽  
Catharina A. Hartman ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Working Memory ◽  
Attention Deficit ◽  
Neural Correlates ◽  
Healthy Controls ◽  
Visuospatial Working Memory ◽  
Hyperactivity Disorder

scholarly journals Brain structural and functional substrates of ADGRL3 (latrophilin 3) haplotype in attention-deficit/hyperactivity disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ana Moreno-Alcázar ◽  
Josep A. Ramos-Quiroga ◽  
Marta Ribases ◽  
Cristina Sánchez-Mora ◽  
Gloria Palomar ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Working Memory ◽  
Attention Deficit ◽  
Temporal Cortex ◽  
Functional Brain Imaging ◽  
Brain Anatomy ◽  
Risk Haplotype ◽  
Healthy Controls ◽  
Functional Brain ◽  
Hyperactivity Disorder

AbstractPrevious studies have shown that the gene encoding the adhesion G protein-coupled receptor L3 (ADGRL3; formerly latrophilin 3, LPHN3) is associated with Attention-Deficit/Hyperactivity Disorder (ADHD). Conversely, no studies have investigated the anatomical or functional brain substrates of ADGRL3 risk variants. We examined here whether individuals with different ADGRL3 haplotypes, including both patients with ADHD and healthy controls, showed differences in brain anatomy and function. We recruited and genotyped adult patients with combined type ADHD and healthy controls to achieve a sample balanced for age, sex, premorbid IQ, and three ADGRL3 haplotype groups (risk, protective, and others). The final sample (n = 128) underwent structural and functional brain imaging (voxel-based morphometry and n-back working memory fMRI). We analyzed the brain structural and functional effects of ADHD, haplotypes, and their interaction, covarying for age, sex, and medication. Individuals (patients or controls) with the protective haplotype showed strong, widespread hypo-activation in the frontal cortex extending to inferior temporal and fusiform gyri. Individuals (patients or controls) with the risk haplotype also showed hypo-activation, more focused in the right temporal cortex. Patients showed parietal hyper-activation. Disorder-haplotype interactions, as well as structural findings, were not statistically significant. To sum up, both protective and risk ADGRL3 haplotypes are associated with substantial brain hypo-activation during working memory tasks, stressing this gene’s relevance in cognitive brain function. Conversely, we did not find brain effects of the interactions between adult ADHD and ADGRL3 haplotypes.

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