Biology subjects

Hadaya, L.

Publications and source records attributed to Hadaya, L..

4 recordsLinked to original sources

bioRxiv2024

Exploring functional connectivity in clinical and data-driven groups of preterm and term adults

BackgroundAdults born very preterm (i.e., at <33 weeks gestation) are more susceptible to long-lasting structural and functional brain alterations and cognitive and socio-emotional difficulties, compared to full-term controls. However, behavioural heterogeneity within very preterm and full-term individuals makes it challenging to find biomarkers of specific outcomes. To address these questions, we parsed brain-behaviour heterogeneity in participants subdivided according to their clinical birth status (very preterm vs full-term) and/or data-driven behavioural phenotype (regardless of birth status). MethodsThe Network Based Statistic approach was used to identify topological components of resting state functional connectivity differentiating between i) 116 very preterm and 83 full-term adults (43% and 57% female, respectively), and ii) data-driven behavioural subgroups identified using consensus clustering (n= 156, 46% female). Age, sex, socio-economic status, and in-scanner head motion were used as confounders in all analyses. Post-hoc two-way group interactions between clinical birth status and behavioural data-driven subgrouping classification labels explored whether functional connectivity differences between very preterm and full-term adults varied according to distinct behavioural outcomes. ResultsVery preterm compared to full-term adults had poorer scores in selective measures of cognitive and socio-emotional processing and displayed complex patterns of hyper- and hypo-connectivity in subsections of the default mode, visual, and ventral attention networks. Stratifying the study participants in terms of their behavioural profiles (irrespective of birth status), identified two data-driven subgroups: An "At-risk" subgroup, characterised by increased cognitive, mental health, and socio-emotional difficulties, displaying hypo-connectivity anchored in frontal opercular and insular regions, relative to a "Resilient" subgroup with more favourable outcomes. No significant interaction was noted between clinical birth status and behavioural data-driven subgrouping classification labels in terms of functional connectivity. ConclusionsFunctional connectivity differentiating between very preterm and full-term adults was dissimilar to functional connectivity differentiating between the data-driven behavioural subgroups. We speculate that functional connectivity alterations observed in very preterm relative to full-term adults may confer both risk and resilience to developing behavioural sequelae associated with very preterm birth, while the localised functional connectivity alterations seen in the "At-risk" subgroup relative to the "Resilient" subgroup may underlie less favourable behavioural outcomes in adulthood, irrespective of birth status.

developmental biology↗

bioRxiv2022

Exploring cognitive, behavioural and autism trait network topology in very preterm and term-born children

Compared to full-term (FT) born peers, children who were born very preterm (VPT; <32 weeks gestation) are likely to display more cognitive and behavioural difficulties, including inattention, anxiety and socio-communication problems. In the published literature, such difficulties tend to be studied independently, thus failing to account for how different aspects of child development interact. The current study aimed to investigate childrens cognitive and behavioural outcomes as interconnected, dynamically related facets of development that influence one another. Participants were 93 VPT and 55 FT children (median age 8.79 years). IQ was evaluated with the Wechsler Intelligence Scale for Children - 4th edition (WISC-IV), autism spectrum condition (ASC) traits with the Social Responsiveness Scale - 2nd edition (SRS-2), behavioural and emotional problems with the Strengths and Difficulties Questionnaire (SDQ), temperament with the Temperament in Middle Childhood Questionnaire (TMCQ) and executive function with the Behaviour Rating Inventory of Executive Functioning (BRIEF-2). Outcome measures were studied in VPT and FT children using Network Analysis, a method that graphically represents partial correlations between variables and yields information on each variables propensity to form a bridge between other variables. Results showed that VPT and FT children exhibited marked topological differences. Bridges (i.e., the variables most connected to others) in the VPT group network were: SDQ Conduct Problems scale and BRIEF-2 Organisation of Materials scale. In the FT group network, the most important bridges were: the BRIEF-2 Initiate, SDQ Emotional Problems and SDQ Prosocial Behaviours scales. These findings highlight the importance of targeting different aspects of development to support VPT and FT children in person-based interventions.

developmental biology↗

bioRxiv2022

Parsing brain-behavior heterogeneity in very preterm born children using integrated similarity networks

Very preterm birth (VPT; [≤] 32 weeks gestation) is associated with altered brain development and cognitive and behavioral difficulties across the lifespan. However, heterogeneity in outcomes among individuals born VPT makes it challenging to identify those most vulnerable to neurodevelopmental sequelae. Here, we aimed to stratify VPT children into distinct behavioral subgroups and explore between-subgroup differences in neonatal brain structure and function. 198 VPT children (98 females) previously enrolled in the Evaluation of Preterm Imaging study (EudraCT 2009-011602-42) underwent Magnetic Resonance Imaging at term-equivalent age and neuropsychological assessments at 4-7 years. Using an integrative clustering approach, we combined neonatal socio-demographic, clinical factors and childhood socio-emotional and executive function outcomes, to identify distinct subgroups of children based on their similarity profiles in a multidimensional space. We characterized resultant subgroups using domain-specific outcomes (temperament, psychopathology, IQ and cognitively stimulating home environment) and explored between-subgroup differences in neonatal brain volumes (voxel-wise Tensor-Based-Morphometry), functional connectivity (voxel-wise degree centrality) and structural connectivity (Tract-Based-Spatial-Statistics). Results showed two-and three-cluster data-driven solutions. The two-cluster solution comprised a resilient subgroup (lower psychopathology and higher IQ, executive function and socio-emotional outcomes) and an at-risk subgroup (poorer behavioral and cognitive outcomes). The three-cluster solution showed an additional third intermediate subgroup displaying behavioral and cognitive outcomes intermediate between the resilient and at-risk subgroups. The resilient subgroup had the most cognitively stimulating home environment and the at-risk subgroup showed the highest neonatal clinical risk, while the intermediate subgroup showed the lowest clinical but the highest socio-demographic risk. Compared to the intermediate subgroup, the resilient subgroup displayed larger neonatal insular and orbitofrontal volumes and stronger orbitofrontal functional connectivity, while the at-risk group showed widespread white matter microstructural alterations. These findings suggest that risk stratification following VPT birth is feasible and could be used translationally to guide personalized interventions aimed at promoting childrens resilience.

neuroscience↗

bioRxiv2022

Clinical, socio-demographic, and parental correlates of early autism traits

BackgroundAutism traits emerge between the ages of 1 and 2. It is not known if experiences which increase the likelihood of childhood autism are related to early trait emergence, or if other exposures are more important. Identifying factors linked to toddler autism traits in the general population may improve our understanding of the mechanisms underlying atypical neurodevelopment. MethodsClinical, socio-demographic, and parental information was collected at birth from 536 toddlers in London, UK (gestational age at birth, sex, maternal body mass index, age, parental education level, parental first language, parental history of neurodevelopmental disorders) and at 18 months (parent cohabiting status, two measures of social deprivation, three measures of maternal parenting style, and a measure of maternal postnatal depression). General neurodevelopment was assessed with the Bayley Scales of Infant and Toddler Development, 3rd Edition (BSID-III), and autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT). Multivariable models were used to identify associations between variables and Q-CHAT. A model including BSID-III was used to identify factors associated with Q-CHAT independent of general neurodevelopment. Models were also evaluated addressing variable collinearity with principal component analysis (PCA). ResultsA multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). After adding general neurodevelopment into the model 36% of Q-CHAT variance was explained, with three individually significant variables (two measures of parenting style and one measure of language development). After addressing variable collinearity with PCA, parenting style and social deprivation were positively correlated with Q-CHAT score via a single principal component, independently of general neurodevelopment. Neither sex nor family history of autism were associated with Q-CHAT score. LimitationsThe Q-CHAT is parent rated and is therefore a subjective opinion rather than a clinical assessment. We measured Q-CHAT at a single timepoint, and to date no participant has been followed up in later childhood, so we are focused purely on emerging traits rather than clinical autism diagnoses. ConclusionsAutism traits are common at age 18 months, and greater emergence is specifically related to exposure to early life adversity.

neuroscience↗