Circadian Rhythms Tied to Changes in Brain Morphology in a Densely Sampled Male.

Circadian, infradian, and seasonal changes in steroid hormone secretion have been tied to changes in brain volume in several mammalian species. However, the relationship between circadian changes in steroid hormone production and rhythmic changes in brain morphology in humans is largely unknown. Here, we examined the relationship between diurnal fluctuations in steroid hormones and multiscale brain morphology in a precision imaging study of a male who completed 40 MRI and serological assessments at 7 A.M. and 8 P.M. over the course of a month, targeting hormone concentrations at their peak and nadir. Diurnal fluctuations in steroid hormones were tied to pronounced changes in global and regional brain morphology. From morning to evening, total brain volume, gray matter volume, and cortical thickness decreased, coincident with decreases in steroid hormone concentrations (testosterone, estradiol, and cortisol). In parallel, cerebrospinal fluid and ventricle size increased from A.M. to P.M. Global changes were driven by decreases within the occipital and parietal cortices. These findings highlight natural rhythms in brain morphology that keep time with the diurnal ebb and flow of steroid hormones.

Diurnal Fluctuations in Steroid Hormones Tied to Variation in Intrinsic Functional Connectivity in a Densely Sampled Male.

Most of mammalian physiology is under the control of biological rhythms, including the endocrine system with time-varying hormone secretion. Precision neuroimaging studies provide unique insights into how the endocrine system dynamically regulates aspects of the human brain. Recently, we established estrogen's ability to drive widespread patterns of connectivity and enhance the global efficiency of large-scale brain networks in a woman sampled every 24 h across 30 consecutive days, capturing a complete menstrual cycle. Steroid hormone production also follows a pronounced sinusoidal pattern, with a peak in testosterone between 6 and 7 A.M. and nadir between 7 and 8 P.M. To capture the brain's response to diurnal changes in hormone production, we carried out a companion precision imaging study of a healthy adult man who completed MRI and venipuncture every 12-24 h across 30 consecutive days. Results confirmed robust diurnal fluctuations in testosterone, 17ß-estradiol-the primary form of estrogen-and cortisol. Standardized regression analyses revealed widespread associations between testosterone, estradiol, and cortisol concentrations and whole-brain patterns of coherence. In particular, functional connectivity in the Dorsal Attention Network was coupled with diurnally fluctuating hormones. Further, comparing dense-sampling datasets between a man and a naturally cycling woman revealed that fluctuations in sex hormones are tied to patterns of whole-brain coherence in both sexes and to a heightened degree in the male. Together, these findings enhance our understanding of steroid hormones as rapid neuromodulators and provide evidence that diurnal changes in steroid hormones are associated with patterns of whole-brain functional connectivity.

Plasma metabolomic signature of healthy lifestyle, structural brain reserve and risk of dementia.

Although the association between healthy lifestyle and dementia risk has been documented, the relationship between a metabolic signature indicative of healthy lifestyle and dementia risk and the mediating role of structural brain impairment remain unknown. We retrieved 136 628 dementia-free participants from UK Biobank. Elastic net regression was used to obtain a metabolic signature that represented lifestyle behaviours. Cox proportional hazard models were fitted to explore the associations of lifestyle-associated metabolic signature with incident dementia. Causal associations between identified metabolites and dementia were investigated using Mendelian randomization. Mediation analysis was also conducted to uncover the potential mechanisms involving 19 imaging-derived phenotypes (brain volume, grey matter volume, white matter volume and regional grey matter volumes). During a follow-up of 12.55 years, 1783 incident cases of all-cause dementia were identified, including 725 cases of Alzheimer's dementia and 418 cases of vascular dementia. We identified 83 metabolites that could represent healthy lifestyle behaviours using elastic net regression. The metabolic signature was associated with a lower dementia risk, and for each standard deviation increment in metabolic signature, the hazard ratio was 0.89 [95% confidence interval (CI): 0.85, 0.93] for all-cause dementia, 0.95 (95% CI: 0.88, 1.03) for Alzheimer's dementia and 0.84 (95% CI: 0.77, 0.91) for vascular dementia. Mendelian randomization revealed potential causal associations between the identified metabolites and risk of dementia. In addition, the specific structural brain reserve, including the hippocampus, grey matter in the hippocampus, parahippocampal gyrus and middle temporal gyrus, were detected to mediate the effects of metabolic signature on dementia risk (mediated proportion ranging from 6.21% to 11.98%). The metabolic signature associated with a healthy lifestyle is inversely associated with dementia risk, and greater structural brain reserve plays an important role in mediating this relationship. These findings have significant implications for understanding the intricate connections between lifestyle, metabolism and brain health.

Sex differences in the pleiotropy of hearing difficulty with imaging-derived phenotypes: a brain-wide investigation.

Hearing difficulty (HD) is one of the major health burdens in older adults. While aging-related changes in the peripheral auditory system play an important role, genetic variation associated with brain structure and function could also be involved in HD predisposition. We analyzed a large-scale HD genome-wide association study (GWAS; Ntotal = 501,825, 56% females) and GWAS data related to 3,935 brain imaging-derived phenotypes (IDPs) assessed in up to 33,224 individuals (52% females) using multiple magnetic resonance imaging modalities. To investigate HD pleiotropy with brain structure and function, we conducted genetic correlation, latent causal variable, Mendelian randomization, and multivariable generalized linear regression analyses. Additionally, we performed local genetic correlation and multi-trait colocalization analyses to identify genomic regions and loci implicated in the pleiotropic mechanisms shared between HD and brain IDPs. We observed a widespread genetic correlation of HD with 120 IDPs in females, 89 IDPs in males, and 171 IDPs in the sex-combined analysis. The latent causal variable analysis showed that some of these genetic correlations could be due to cause-effect relationships. For seven correlations, the causal effects were also confirmed by the Mendelian randomization approach: vessel volume→HD in the sex-combined analysis; hippocampus volume→HD, cerebellum grey matter volume→HD, primary visual cortex volume→HD, and HD→fluctuation amplitudes of node 46 in resting-state functional MRI dimensionality 100 in females; global mean thickness→HD and HD→mean orientation dispersion index in superior corona radiata in males. The local genetic correlation analysis identified 13 pleiotropic regions between HD and these seven IDPs. We also observed a colocalization signal for the rs13026575 variant between HD, primary visual cortex volume, and SPTBN1 transcriptomic regulation in females. Brain structure and function may have a role in the sex differences in HD predisposition via possible cause-effect relationships and shared regulatory mechanisms.

Reduced covariation between brain morphometry and local spontaneous activity in young children with ASD.

While disruptions in brain maturation in the first years of life in ASD are well documented, little is known about how the brain structure and function are related in young children with ASD compared to typically developing peers. We applied a multivariate pattern analysis to examine the covariation patterns between brain morphometry and local brain spontaneous activity in 38 toddlers and preschoolers with ASD and 31 typically developing children using T1-weighted structural MRI and resting-state fMRI data acquired during natural sleep. The results revealed significantly reduced brain structure-function correlations in ASD. The resultant brain structure and function composite indices were associated with age among typically developing children, but not among those with ASD, suggesting mistiming of typical brain maturational trajectories early in life in autism. Additionally, the brain function composite indices were associated with the overall developmental and adaptive behavior skills in the ASD group, highlighting the neurodevelopmental significance of early local brain activity in autism.

Associations of hearing loss and structural changes in specific cortical regions: a Mendelian randomization study.

INTRODUCTION: Previous studies have suggested a correlation between hearing loss (HL) and cortical alterations, but the specific brain regions that may be affected are unknown. METHODS: Genome-wide association study (GWAS) data for 3 subtypes of HL phenotypes, sensorineural hearing loss (SNHL), conductive hearing loss, and mixed hearing loss, were selected as exposures, and GWAS data for brain structure-related traits were selected as outcomes. The inverse variance weighted method was used as the main estimation method. RESULTS: Negative associations were identified between genetically predicted SNHL and brain morphometric indicators (cortical surface area, cortical thickness, or volume of subcortical structures) in specific brain regions, including the bankssts (ß = -0.006 mm, P = 0.016), entorhinal cortex (ß = -4.856 mm2, P = 0.029), and hippocampus (ß = -24.819 cm3, P = 0.045), as well as in brain regions functionally associated with visual perception, including the pericalcarine (ß = -10.009 cm3, P = 0.013). CONCLUSION: Adaptive changes and functional remodeling of brain structures occur in patients with genetically predicted HL. Brain regions functionally associated with auditory perception, visual perception, and memory function are the main brain regions vulnerable in HL.

Neuropsychological insights into exercise addiction: the role of brain structure and self-efficacy in middle-older individuals.

This study aimed to investigate the relationship between exercise addiction and brain structure in middle-older individuals, and to examine the role of self-efficacy in mediating physiological changes associated with exercise addiction. A total of 133 patients exhibiting symptoms of exercise addiction were recruited for this study (male = 43, age 52.86 ± 11.78 years). Structural magnetic resonance imaging and behavioral assessments were administered to assess the study population. Voxel-based morphological analysis was conducted using SPM12 software. Mediation analysis was employed to explore the potential neuropsychological mechanism of self-efficacy in relation to exercise addiction. The findings revealed a positive correlation between exercise addiction and gray matter volume in the right inferior temporal region and the right hippocampus. Conversely, there was a negative correlation with gray matter volume in the left Rolandic operculum. Self-efficacy was found to indirectly influence exercise addiction by affecting right inferior temporal region gray matter volume and acted as a mediating variable in the relationship between the gray matter volume of right inferior temporal region and exercise addiction. In summary, this study elucidates the link between exercise addiction and brain structure among middle-older individuals. It uncovers the intricate interplay among exercise addiction, brain structure, and psychological factors. These findings enhance our comprehension of exercise addiction and offer valuable insights for the development of interventions and treatments.

Alternation of psychological resilience may moderate mentalization toward mental health conditions from macro- and microstructure aspects.

OBJECTIVE: We aim to investigate the interplay between mentalization, brain microstructure, and psychological resilience as potential protective factors against mental illness. METHOD: Four hundred and twenty-six participants (mean age 40.12±16.95; 202 males, 224 females), without psychiatric or neurological history, completed assessments: Dissociative Process Scale (DPS), Peace of Mind (PoM), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Resilience Scale for Adults (RSA), and Magnetic Resonance Imaging (MRI) structures with selected regions of interest, and Diffusion Tensor Imaging (DTI) maps from various tracts in the right hemisphere and connection to the frontal areas, including anterior thalamic radiation (ATR), Cingulum (hippocampus) (CH), Corticospinal tract (CST), Superior longitudinal fasciculus (SLF), Inferior fronto-occipital fasciculus (IFOF), and Uncinate fasciculus (UF) were analyzed. RESULTS: Two clusters, representing hypomentalization (HypoM) and hypermentalization (HyperM), were identified based on DPS, CPSS, and RFQ responses. One-way ANOVA showed no significant age or gender differences between clusters. The HypoM group exhibited lower PoM scores, higher BDI and BAI scores, and lower RSA scores (ps< 0.05). Structural brain metric comparison showed significant differences in GMV in the right caudal middle frontal gyrus (rcMFG), right superior frontal gyrus (rsFG), and right frontal pole (rFP) between groups. In addition, the HyperM individuals with a higher risk of depression and a higher ratio of intrapersonal to interpersonal factors of resilience were found with reduced GMV on the rcMFG. Additionally, analyses of DTI metrics revealed significant differences between two groups in rATR and rSLF in terms of fractional anisotropy (FA) values; rATR, rCST, rUF, rSLF, rCH and rIFOF in terms of mean diffusivity (MD) values, and radial diffusivity (RD) (corrected p = 0.05). Moreover, the positive correlation between different domains of resilience and white matter (WM) integrity implied further enhancement of intrapersonal or interpersonal resilience factors that are different for people with different mentalization. CONCLUSIONS: The findings underscore the importance of considering both intrapersonal and interpersonal factors in understanding the interactions between psychological resilience and mental health conditions relevant to brain mechanisms.

Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure.

Individuals with congenital heart disease (CHD) have an increased risk of neurodevelopmental impairments. Given the hypothesized complexity linking genomics, atypical brain structure, cardiac diagnoses and their management, and neurodevelopmental outcomes, unsupervised methods may provide unique insight into neurodevelopmental variability in CHD. Using data from the Pediatric Cardiac Genomics Consortium Brain and Genes study, we identified data-driven subgroups of individuals with CHD from measures of brain structure. Using structural magnetic resonance imaging (MRI; N = 93; cortical thickness, cortical volume, and subcortical volume), we identified subgroups that differed primarily on cardiac anatomic lesion and language ability. In contrast, using diffusion MRI (N = 88; white matter connectivity strength), we identified subgroups that were characterized by differences in associations with rare genetic variants and visual-motor function. This work provides insight into the differential impacts of cardiac lesions and genomic variation on brain growth and architecture in patients with CHD, with potentially distinct effects on neurodevelopmental outcomes.

Computational limits to the legibility of the imaged human brain.

Our knowledge of the organisation of the human brain at the population-level is yet to translate into power to predict functional differences at the individual-level, limiting clinical applications and casting doubt on the generalisability of inferred mechanisms. It remains unknown whether the difficulty arises from the absence of individuating biological patterns within the brain, or from limited power to access them with the models and compute at our disposal. Here we comprehensively investigate the resolvability of such patterns with data and compute at unprecedented scale. Across 23 810 unique participants from UK Biobank, we systematically evaluate the predictability of 25 individual biological characteristics, from all available combinations of structural and functional neuroimaging data. Over 4526 GPU*hours of computation, we train, optimize, and evaluate out-of-sample 700 individual predictive models, including fully-connected feed-forward neural networks of demographic, psychological, serological, chronic disease, and functional connectivity characteristics, and both uni- and multi-modal 3D convolutional neural network models of macro- and micro-structural brain imaging. We find a marked discrepancy between the high predictability of sex (balanced accuracy 99.7%), age (mean absolute error 2.048 years, R2 0.859), and weight (mean absolute error 2.609Kg, R2 0.625), for which we set new state-of-the-art performance, and the surprisingly low predictability of other characteristics. Neither structural nor functional imaging predicted an individual's psychology better than the coincidence of common chronic disease (p < 0.05). Serology predicted chronic disease (p < 0.05) and was best predicted by it (p < 0.001), followed by structural neuroimaging (p < 0.05). Our findings suggest either more informative imaging or more powerful models will be needed to decipher individual level characteristics from the human brain. We make our models and code openly available.

Associations of liver dysfunction with incident dementia, cognition, and brain structure: A prospective cohort study of 431 699 adults.

The relationship between liver dysfunction and dementia has been researched extensively but remains poorly understood. In this study, we investigate the longitudinal and cross-sectional associations between liver function and liver diseases and risk of incident dementia, impaired cognition, and brain structure abnormalities using Cox proportion hazard model and linear regression model. 431 699 participants with a mean of 8.65 (standard deviation [SD] 2.61) years of follow-up were included from the UK Biobank; 5542 all-cause dementia (ACD), 2427 Alzheimer's disease (AD), and 1282 vascular dementia (VaD) cases were documented. We observed that per SD decreases in alanine transaminase (ALT; hazard ratio [HR], 0.917; PFDR <0.001) and per SD increases in aspartate aminotransferase (AST; HR, 1.048; PFDR = 0.010), AST to ALT ratio (HR, 1.195; PFDR <0.001), gamma-glutamyl transpeptidase (GGT; HR, 1.066; PFDR <0.001), alcoholic liver disease (ALD; HR, 2.872; PFDR <0.001), and fibrosis and cirrhosis of liver (HR, 2.285; PFDR = 0.002), being significantly associated with a higher risk of incident ACD. Restricted cubic spline models identified a strong U-shaped association between Alb and AST and incident ACD (Pnonlinear <0.05). Worse cognition was positively correlated with AST, AST to ALT ratio, direct bilirubin (DBil), and GGT; negatively correlated with ALT, Alb, and total bilirubin (TBil); and ALD and fibrosis and cirrhosis of liver (PFDR <0.05). Moreover, changes in ALT, GGT, AST to ALT ratio, and ALD were significantly associated with altered cortical and subcortical regions, including hippocampus, amygdala, thalamus, pallidum, and fusiform (PFDR <0.05). In sensitivity analysis, metabolic dysfunction-associated steatotic liver disease (MASLD) was associated with the risk of ACD and brain subcortical changes. Our findings provide substantial evidence that liver dysfunction may be an important factor for incident dementia. Early intervention in the unhealthy liver may help prevent cognitive impairment and dementia incidence.

Hormonal contraceptives and the brain: A systematic review on 60 years of neuroimaging, EEG, and biochemical studies in humans and animals.

Hormonal contraception has been widely prescribed for decades. Although safety and efficacy are well-established, much uncertainty remains regarding brain effects of hormonal contraception. We systematically review human and animal studies on the brain effects of hormonal contraception which employed neuroimaging techniques such as MRI, PET and EEG, as well as animal studies which reported on neurotransmitter and other brain biochemical effects. We screened 1001 articles and ultimately extracted data from 70, comprising 51 human and 19 animal studies. Of note, there were no animal studies which employed structural or functional MRI, MRS or PET. In summary, our review shows hormonal contraceptive associations with changes in the brain have been documented. Many questions remain and more studies are needed to describe the effects of hormonal contraception on the brain.

Sex, gender diversity, and brain structure in early adolescence.

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions.

With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age-related changes are consistent between datasets and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age-related changes of brain structure (regional cortical thickness and regional surface area; N = 1218) and function (resting-state functional connectivity strength; N = 1254) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental Network and the Healthy Brain Network. We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For regional measures of cortical surface area, the patterns of differences were associated with race/ethnicity, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age-related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling for age effects in analyses.

Menstrual cycle-driven hormone concentrations co-fluctuate with white and gray matter architecture changes across the whole brain.

Cyclic fluctuations in hypothalamic-pituitary-gonadal axis (HPG-axis) hormones exert powerful behavioral, structural, and functional effects through actions on the mammalian central nervous system. Yet, very little is known about how these fluctuations alter the structural nodes and information highways of the human brain. In a study of 30 naturally cycling women, we employed multidimensional diffusion and T1-weighted imaging during three estimated menstrual cycle phases (menses, ovulation, and mid-luteal) to investigate whether HPG-axis hormone concentrations co-fluctuate with alterations in white matter (WM) microstructure, cortical thickness (CT), and brain volume. Across the whole brain, 17ß-estradiol and luteinizing hormone (LH) concentrations were directly proportional to diffusion anisotropy (µFA; 17ß-estradiol: ß1 = 0.145, highest density interval (HDI) = [0.211, 0.4]; LH: ß1 = 0.111, HDI = [0.157, 0.364]), while follicle-stimulating hormone (FSH) was directly proportional to CT (ß1 = 0 .162, HDI = [0.115, 0.678]). Within several individual regions, FSH and progesterone demonstrated opposing relationships with mean diffusivity (Diso) and CT. These regions mainly reside within the temporal and occipital lobes, with functional implications for the limbic and visual systems. Finally, progesterone was associated with increased tissue (ß1 = 0.66, HDI = [0.607, 15.845]) and decreased cerebrospinal fluid (CSF; ß1 = -0.749, HDI = [-11.604, -0.903]) volumes, with total brain volume remaining unchanged. These results are the first to report simultaneous brain-wide changes in human WM microstructure and CT coinciding with menstrual cycle-driven hormone rhythms. Effects were observed in both classically known HPG-axis receptor-dense regions (medial temporal lobe, prefrontal cortex) and in other regions located across frontal, occipital, temporal, and parietal lobes. Our results suggest that HPG-axis hormone fluctuations may have significant structural impacts across the entire brain.

Brain structure ages-A new biomarker for multi-disease classification.

Age is an important variable to describe the expected brain's anatomy status across the normal aging trajectory. The deviation from that normative aging trajectory may provide some insights into neurological diseases. In neuroimaging, predicted brain age is widely used to analyze different diseases. However, using only the brain age gap information (i.e., the difference between the chronological age and the estimated age) can be not enough informative for disease classification problems. In this paper, we propose to extend the notion of global brain age by estimating brain structure ages using structural magnetic resonance imaging. To this end, an ensemble of deep learning models is first used to estimate a 3D aging map (i.e., voxel-wise age estimation). Then, a 3D segmentation mask is used to obtain the final brain structure ages. This biomarker can be used in several situations. First, it enables to accurately estimate the brain age for the purpose of anomaly detection at the population level. In this situation, our approach outperforms several state-of-the-art methods. Second, brain structure ages can be used to compute the deviation from the normal aging process of each brain structure. This feature can be used in a multi-disease classification task for an accurate differential diagnosis at the subject level. Finally, the brain structure age deviations of individuals can be visualized, providing some insights about brain abnormality and helping clinicians in real medical contexts.

Sex-specific associations of adolescent motherhood with cognitive function, behavioral problems, and autistic-like traits in offspring and the mediating roles of family conflict and altered brain structure.

BACKGROUND: Previous studies have linked adolescent motherhood to adverse neurodevelopmental outcomes in offspring, yet the sex-specific effect and underlying mechanisms remain unclear. METHODS: This study included 6952 children aged 9-11 from the Adolescent Brain Cognitive Development study. The exposed group consisted of children of mothers < 20 years at the time of birth, while the unexposed group was composed of children of mothers aged 20-35 at birth. We employed a generalized linear mixed model to investigate the associations of adolescent motherhood with cognitive, behavioral, and autistic-like traits in offspring. We applied an inverse-probability-weighted marginal structural model to examine the potential mediating factors including adverse perinatal outcomes, family conflict, and brain structure alterations. RESULTS: Our results revealed that children of adolescent mothers had significantly lower cognitive scores (ß, - 2.11, 95% CI, - 2.90 to - 1.31), increased externalizing problems in male offspring (mean ratio, 1.28, 95% CI, 1.08 to 1.52), and elevated internalizing problems (mean ratio, 1.14, 95% CI, 0.99 to 1.33) and autistic-like traits (mean ratio, 1.22, 95% CI, 1.01 to 1.47) in female. A stressful family environment mediated ~ 70% of the association with internalizing problems in females, ~ 30% with autistic-like traits in females, and ~ 20% with externalizing problems in males. Despite observable brain morphometric changes related to adolescent motherhood, these did not act as mediating factors in our analysis, after adjusting for family environment. No elevated rate of adverse perinatal outcomes was observed in the offspring of adolescent mothers in this study. CONCLUSIONS: Our results reveal distinct sex-specific neurodevelopmental outcomes impacts of being born to adolescent mothers, with a substantial mediating effect of family environment on behavioral outcomes. These findings highlight the importance of developing sex-tailored interventions and support the hypothesis that family environment significantly impacts the neurodevelopmental consequences of adolescent motherhood.

Sarcopenic obesity is part of obesity paradox in dementia development: evidence from a population-based cohort study.

BACKGROUND: Sarcopenic obesity, a clinical and functional condition characterized by the coexistence of obesity and sarcopenia, has not been investigated in relation to dementia risk and its onset. METHODS: We included 208,867 participants from UK biobank, who aged 60 to 69 years at baseline. Dementia diagnoses were identified using hospital records and death register data. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models to evaluate the associations of obesity, sarcopenia, and sarcopenic obesity with dementia risk, stratified by sex. Stratified analyses were performed across dementia-related polygenic risk score (PRS). Restricted mean survival time models were established to estimate the difference and 95%CIs of dementia onset across different status. Additionally, linear regression models were employed to estimate associations of different status with brain imaging parameters. The mediation effects of chronic diseases were also examined. RESULTS: Obese women with high PRS had a decreased risk (HR = 0.855 [0.761-0.961]), but obese men with low PRS had an increased risk (HR = 1.223 [1.045-1.431]). Additionally, sarcopenia was associated with elevated dementia risk (HRwomen = 1.323 [1.064-1.644]; HRmen = 2.144 [1.753-2.621]) in those with low PRS. Among those with high PRS, however, the association was only significant in early-life (HRwomen = 1.679 [1.355-2.081]; HRmen = 2.069 [1.656-2.585]). Of note, sarcopenic obesity was associated with higher dementia risk (HRwomen = 1.424 [1.227-1.653]; HRmen = 1.989 [1.702-2.323]), and results remained similar stratified by PRS. Considering dementia onset, obesity was associated with dementia by 1.114 years delayed in women, however, 0.170 years advanced in men. Sarcopenia (women: 0.080 years; men: 0.192 years) and sarcopenic obesity (women: 0.109 years; men: 0.511 years) respectively advanced dementia onset. Obesity, sarcopenia, and sarcopenic obesity were respectively related to alterations in different brain regions. Association between sarcopenic obesity and dementia was mediated by chronic diseases. CONCLUSIONS: Sarcopenic obesity and sarcopenia were respectively associated with increased dementia risk and advanced dementia onset to vary degree. The role of obesity in dementia may differ by sex and genetic background.

Association of in utero HIV exposure with child brain structure and language development: a South African birth cohort study.

BACKGROUND: There is a growing population of children with in utero HIV exposure who are at risk of poor neurodevelopmental outcomes despite avoiding HIV infection. However, the underlying neurobiological pathways are not understood and neuroimaging studies are lacking. We aimed to investigate the cortical brain structure of children who are HIV-exposed and uninfected (HEU) compared to HIV-unexposed (HU) children and to examine the relationship with neurodevelopment. METHODS: The Drakenstein Child Health birth cohort study enrolled pregnant women from a high HIV prevalence area in South Africa with longitudinal follow-up of mother-child pairs. High-resolution magnetic resonance imaging scans from 162 children (70 HEU; 92 HU) were acquired at 2-3 years of age. All HEU children were born to mothers taking antiretroviral therapy. Measures of brain structure (cortical thickness and surface area) in the prefrontal cortex regions were extracted from T1-weighted images and compared between groups using multivariate analysis of variance and linear regression. Child development, assessed using the Bayley Scales of Infant and Toddler Development-III, was correlated with cortical structure, and mediation analyses were performed. RESULTS: Analyses demonstrated an association between HIV exposure and cortical thickness across the prefrontal cortex (p = 0.035). Children who were HEU had thicker cortices in prefrontal regions, with significantly greater cortical thickness in the medial orbitofrontal cortex (mOFC) bilaterally compared to HU children (3.21 mm versus 3.14 mm, p = 0.009, adjusted effect size 0.44 [95% CI 0.12 to 0.75]). Estimates held across multiple sensitivity analyses. There were no group differences in cortical surface area. Language scores, which were lower in HEU versus HU children (81.82 versus 86.25, p = 0.011, effect size - 0.44 [95% CI - 0.78 to - 0.09]), negatively correlated with prefrontal cortical thickness in both groups. Cortical thickness in the mOFC mediated the relationship between HIV exposure and poor language outcomes (Sobel test p = 0.032). CONCLUSIONS: In this cohort study, exposure to HIV during pregnancy was associated with altered cortical structure in early life. Our findings indicate that differences in cortical thickness development in the prefrontal region in children who are HEU may be a pathway leading to language impairment. Longitudinal studies are needed to determine the lasting impact.

Associations between Parenting and Cognitive and Language Abilities at 2 Years of Age Depend on Prenatal Exposure to Disadvantage.

OBJECTIVE: To investigate whether parenting or neonatal brain volumes mediate associations between prenatal social disadvantage (PSD) and cognitive/language abilities and whether these mechanisms vary by level of disadvantage. STUDY DESIGN: Pregnant women were recruited prospectively from obstetric clinics in St Louis, Missouri. PSD encompassed access to social (eg, education) and material (eg, income to needs, health insurance, area deprivation, and nutrition) resources during pregnancy. Neonates underwent brain magnetic resonance imaging. Mother-child dyads (n = 202) returned at age 1 year for parenting observations and at age 2 years for cognition/language assessments (Bayley Scales of Infant and Toddler Development, Third Edition). Generalized additive and mediation models tested hypotheses. RESULTS: Greater PSD associated nonlinearly with poorer cognitive/language scores. Associations between parenting and cognition/language were moderated by disadvantage, such that supportive and nonsupportive parenting behaviors related only to cognition/language in children with lesser PSD. Parenting mediation effects differed by level of disadvantage: both supportive and nonsupportive parenting mediated PSD-cognition/language associations in children with lesser disadvantage, but not in children with greater disadvantage. PSD-associated reductions in neonatal subcortical grey matter (ß = 0.19; q = 0.03), white matter (ß = 0.23; q = 0.02), and total brain volume (ß = 0.18; q = 0.03) were associated with lower cognition, but did not mediate the associations between PSD and cognition. CONCLUSIONS: Parenting moderates and mediates associations between PSD and early cognition and language, but only in families with less social disadvantage. These findings, although correlational, suggest that there may be a critical threshold of disadvantage, below which mediating or moderating factors become less effective, highlighting the importance of reducing disadvantage as primary prevention.