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Hermosillo, R.

Publications and source records attributed to Hermosillo, R..

8 recordsLinked to original sources

Salience network expansion as a transdiagnostic neural marker for psychopathology risk in adolescence

Increased cortical surface area of the brain's salience network (SAL) has been observed in depression and appears to emerge during early adolescence. However, similar expansion has also been reported in bipolar disorder (BD), obsessive compulsive disorder (OCD), and other atypicalities of salience network function have been broadly implicated across multiple psychiatric conditions. Whether increased SAL surface area is specific to depression or related more generally with psychopathology remains unclear. Using data collected as part of the Adolescent Brain Cognitive Development (ABCD) Study (baseline: N = 7942; ages 9-10; Year 2: N = 5901; ages 11-12), we quantified individual SAL size and examined associations with dimensional symptoms from the Child Behavior Checklist. SAL surface area showed substantial inter-individual variability, with expansion occurring primarily through encroachment into the default mode (DMN), action-mode (AMN), and frontoparietal (FP) networks. Larger SAL size showed a modest positive association with depressive symptoms in the baseline sample, consistent with prior reports; however, this association did not replicate in the year 2 internal replication sample. Instead, associations with total problems were stronger and replicated across both timepoints, suggesting a subtle, dimensional relationship between SAL organization and general psychopathology burden. These findings suggest that individual differences in SAL organization may represent a broader transdiagnostic neural correlate of dimensional psychopathology rather than a disorder-specific neural signature.

neuroscience↗

Optical genome mapping identifies source-associated structural variant differences across early-passage human iPSCs

BackgroundInduced pluripotent stem cells (iPSCs) are an important model for studying human diseases in vitro. However, previous studies have shown that iPSC reprogramming and extended cell culture can introduce genomic structural variants (SVs). Technologies like karyotyping, CNV microarrays, and whole-genome sequencing have limitations in resolution, sensitivity, or the ability to detect large and complex structural variants compared to optical genome mapping (OGM). OGM is a genome-wide structural variant detection method that analyzes fluorescently labeled ultra-high-molecular-weight DNA molecules to identify copy-number and balanced rearrangements. At sufficient coverage, OGM can detect SVs at approximately [≥]2 kbp and identify mosaic events supported by molecule-level evidence, offering higher resolution than conventional karyotyping or SNP-array-based QC. Here, we compared iPSC clones derived from peripheral blood mononuclear cells (PBMCs) and fibroblasts (FBCs) to determine whether starting somatic cell source is associated with differences in structural variant burden and SV-type profiles after nuclear reprogramming into iPSCs. ResultsWe analyzed 73 low-passage iPSC clones generated from 25 parental lines using OGM. Compared with PBMC-iPSCs, FBC-iPSCs showed higher SV burden with the enrichment of duplications [≥]100 kbp, more frequent overlap with protein-coding genes, fragile sites, and recurrent chromosomal hotspot regions. In contrast, PBMC-iPSCs showed fewer SVs overall, and a higher proportion of clones without detectable clone-specific SVs. ConclusionsOGM provides a high-resolution approach for post-reprogramming genomic quality control by detecting clone-specific structural variants at approximately [≥]2 kbp, including events below the resolution of conventional cytogenetic and SNP-array-based assays. In these early passage iPSCs, SVs overlapped protein-coding genes, fragile sites, and recurrent culture-associated chromosomal regions, underscoring the need for clone-level genomic assessment before downstream applications. FBC-derived iPSCs showed a higher SV burden, including more frequent and larger duplications, whereas PBMC-derived iPSCs more often lacked detectable clone-specific SVs. These findings suggest that PBMC-iPSCs and FBC-iPSCs can differ in post-reprogramming SV profiles and support the use of OGM as a QC strategy during iPSC generation and selection.

genomics↗

Cortical Thickness and Curvature in Autism and ADHD: A Mega-Analysis

BackgroundExisting evidence suggests cortical morphometric alterations occur in people with autism and ADHD. However, these findings remain tentative due to small sample sizes, heterogeneous imaging pipelines, varied statistical approaches, and limited harmonization across acquisition sites. Few studies have applied standardized processing to large, clinically enriched datasets or addressed site-related batch effects. MethodsWe leveraged six large-scale brain imaging datasets (n = 9,647; male=5,835; female=3,812; ages 5-64 years), including 1,533 individuals with ADHD, 1,080 with autism spectrum disorder, and 7,034 matched controls. All imaging data were processed using the validated ABCD-HCP pipeline, with cortical parcellation into 360 regions based on the Human Connectome Project (HCP) atlas, and ComBat harmonization was applied to account for variability across 67 acquisition sites. Group-level differences in cortical thickness and sulcal curvature were examined with ANCOVAs, controlling for covariates and using Bonferroni correction for multiple comparisons. ResultsOur analyses revealed distinct neuroanatomical signatures for both autism and ADHD. Individuals with autism exhibited regionally thinner cortex and curvature alterations particularly in the Cingulo-Opercular network. In contrast, individuals with ADHD displayed regionally thicker cortex, particularly in the default mode and somatomotor networks, alongside curvature differences. Control participants showed intermediate patterns, suggesting that autism and ADHD may represent diverging extremes of cortical maturation. ConclusionsCortical thickness and curvature emerge as potential biomarkers that can advance understanding of neurodevelopmental conditions and disentangle heterogeneity across diagnostic groups. These findings highlight the value of harmonized, large-scale, standardized analyses for resolving inconsistencies in the literature.

neuroscience↗

Associations between amygdala connectivity and experienced discrimination in children

Discrimination is a chronic stressor linked to adverse health outcomes, particularly in racial and ethnic minorities. Understanding associations between early discrimination and the brain in childhood may help identify mechanisms through which discrimination impacts future health. Data from 4512 children (ages 9-11) and a subsample of Black, Indigenous, and People of Color (BIPOC; N = 1567) from the Adolescent Brain and Cognitive Development (ABCD) Study(R) was used to create linear mixed-effects models that evaluated associations between Perceived Discrimination (PD) and amygdala resting-state fMRI connectivity (AC) to the salience network (SN), default mode network (DMN), and thalamus. PD was measured using the youth self-reported PD Scale. Results indicated that greater PD significantly predicted greater AC to the right thalamus in our full sample. In secondary analyses, environmental and behavioral factors were evaluated as potential moderators for associations significant at least at a trend level in both our full sample and BIPOC subsample. In our BIPOC subsample, traumatic events experienced moderated the relationship between PD and AC to the anterior cingulate cortex (ACC; SN), such that greater traumatic experiences predicted stronger positive associations between PD and this connection. Results suggest PD impacts neural connections in early life, highlighting the need to consider the impact of discrimination on risk for psychopathology.

neuroscience↗

Commonality and Variability in Functional Networks In Young Children Under 5 Years Old

Functional brain networks support human cognition, yet how individualized network architecture emerges in early childhood remains poorly understood. Averaging across participants can obscure age-specific organization and person-to-person differences, particularly in slowly developing association cortices. We developed an age-appropriate functional reference that captured common structure across toddlers without averaging away individual variability, enabling estimation of each childs networks from resting-state fMRI. Across cohorts of 8-60-month-old children, we found individualized network organization--including finer-scale subdivisions and emerging language lateralization--well before age five. Network layouts showed longitudinal stability, with greater consistency in sensory than association regions. Within-network connectivity was stronger and explained age-related variance when networks were defined using individualized rather than group-consensus topography. Left-lateralization of language networks tracked age-normalized verbal ability, linking early functional architecture to emerging cognition. These findings show that behaviorally relevant brain networks arise far earlier than previously recognized, providing a foundation for studying typical development and early biomarkers.

neuroscience↗

Examining the heritability of functional brain networks in adolescence

Discovering mechanisms underlying mental illness requires disentangling genetic and environmental factors influencing mental health. Researchers have started investigating the brains role as a potential intermediate biomarker linking genes and environment to mental health; however, understanding how much genetics shapes adolescent brain function remains elusive. Using data from the ABCD study (5,247 unrelated, 330 dizygotic, 248 monozygotic twin subjects), we estimated the heritability of functional connectivity and topography using both SNP and twin data. SNP-based heritability was calculated using genetic correlation and the recently developed AdjHE-RE estimator. We found low SNP heritability for brain functional connectivity (median = 2e-10% Gordon, 5.8e-7% probabilistic) and topography (max = 2%). Twin estimates using ACE models replicated prior findings from the literature (median = 8.9e-6% Gordon, 6% probabilistic, 27% topography). This suggest that additive genetic effects are minimally associated with functional brain features in adolescents highlighting the importance of considering both genetic and environmental factors when studying the development of functional brain networks and their relevance to mental health.

genomics↗

Vertex-wise characterization of Non-Human Primate cortical development with prenatal insights.

Characterization of the interwoven complexities of early cortical thickness development has been an ongoing undertaking in neuroscience research. Longitudinal studies of Non-Human Primates (NHP) offer unique advantages to categorizing the diverse patterns of cortical growth trajectories. Here, we used latent growth models to characterize the trajectories of typical cortical thickness development in Japanese macaques at each cortical surface vertex (i.e. grayordinate). Cortical thickness from 4 to 36 months showed regional specific linear and non-linear trajectories and distinct maturation timing across the cortex. Intriguingly, we revealed a "accumulation/ablation phenomenon" of cortical maturation where the most profound development changes in cortical thickness occur in the accumulation or ablation zones surrounding the focal points (i.e., a center of a delineated regions where cortical thickness is thickest or thinnest) throughout the brain. We further examined maternal diet and inflammation in the context of these typical brain trajectories and known network architecture. A well-controlled NHP model of a maternal "Western-style" diet was used alongside measures of inflammatory cytokine interleukin-6 (IL-6) in the mothers during gestation. We observed that these accumulation and ablation zones of variable change might be most susceptible to environmental effects. The maternal factors, diet and inflammation during pregnancy were distinctively associated with different aspects of offspring cortical development reflected in regions related to distinctive functional networks. Our findings characterize the versatile intricacies of typical cortical thickness development and highlight how the maternal environment plays a role in offspring cortical development.

neuroscience↗

Adolescent Brain Cognitive Development (ABCD) Community MRI Collection and Utilities

The Adolescent Brain Cognitive Development Study (ABCD), a 10 year longitudinal neuroimaging study of the largest population based and demographically distributed cohort of 9-10 year olds (N=11,877), was designed to overcome reproducibility limitations of prior child mental health studies. Besides the fantastic wealth of research opportunities, the extremely large size of the ABCD data set also creates enormous data storage, processing, and analysis challenges for researchers. To ensure data privacy and safety, researchers are not currently able to share neuroimaging data derivatives through the central repository at the National Data Archive (NDA). However, sharing derived data amongst researchers laterally can powerfully accelerate scientific progress, to ensure the maximum public benefit is derived from the ABCD study. To simultaneously promote collaboration and data safety, we developed the ABCD-BIDS Community Collection (ABCC), which includes both curated processed data and software utilities for further analyses. The ABCC also enables researchers to upload their own custom-processed versions of ABCD data and derivatives for sharing with the research community. This NeuroResource is meant to serve as the companion guide for the ABCC. In section we describe the ABCC. Section II highlights ABCC utilities that help researchers access, share, and analyze ABCD data, while section III provides two exemplar reproducibility analyses using ABCC utilities. We hope that adoption of the ABCCs data-safe, open-science framework will boost access and reproducibility, thus facilitating progress in child and adolescent mental health research.

neuroscience↗