Topological network properties of resting-state functional connectivity patterns are associated with metal mixture exposure in adolescents

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

The large number of different analytical choices used by researchers is partly responsible for the challenge of replication in neuroimaging studies. For an exhaustive robustness analysis, knowledge of the full space of analytical options is essential. We conducted a systematic literature review to identify the analytical decisions in functional neuroimaging data preprocessing and analysis in the emerging field of cognitive network neuroscience. We found 61 different steps, with 17 of them having debatable parameter choices. Scrubbing, global signal regression, and spatial smoothing are among the controversial steps. There is no standardized order in which different steps are applied, and the parameter settings within several steps vary widely across studies. By aggregating the pipelines across studies, we propose three taxonomic levels to categorize analytical choices: 1) inclusion or exclusion of specific steps, 2) parameter tuning within steps, and 3) distinct sequencing of steps. We have developed a decision support application with high educational value called METEOR to facilitate access to the data in order to design well-informed robustness (multiverse) analysis.

The impact of psychosocial adversity on brain and behaviour: an overview of existing knowledge and directions for future research

Environmental experiences play a critical role in shaping the structure and function of the brain. Its plasticity in response to different external stimuli has been the focus of research efforts for decades. In this review, we explore the effects of adversity on brain's structure and function and its implications for brain development, adaptation, and the emergence of mental health disorders. We are focusing on adverse events that emerge from the immediate surroundings of an individual, i.e., microenvironment. They include childhood maltreatment, peer victimisation, social isolation, affective loss, domestic conflict, and poverty. We also take into consideration exposure to environmental toxins. Converging evidence suggests that different types of adversity may share common underlying mechanisms while also exhibiting unique pathways. However, they are often studied in isolation, limiting our understanding of their combined effects and the interconnected nature of their impact. The integration of large, deep-phenotyping datasets and collaborative efforts can provide sufficient power to analyse high dimensional environmental profiles and advance the systematic mapping of neuronal mechanisms. This review provides a background for future research, highlighting the importance of understanding the cumulative impact of various adversities, through data-driven approaches and integrative multimodal analysis techniques.

Association of plasma metals with resting-state functional connectivity in ischemic stroke

BACKGROUND

Metal exposure has long been considered a significant risk factor for ischemic stroke. However, existing data on the effects of metal exposure on brain function in ischemic stroke are limited. Therefore, this study aimed to explore the correlation between exposure to various metals and changes in resting-state functional connectivity (rs-FC) in ischemic stroke patients.

METHODS

This study included 28 acute ischemic stroke patients with hemiplegia and 28 matched healthy controls (HCs). All participants underwent T1-weighted MRI and 3.0 T resting-state functional magnetic resonance imaging (fMRI). After MRI acquisition, the rs-FC between 137 cortical and subcortical regions was extracted and preprocessed. Plasma levels of 19 metals were measured using inductively coupled plasma mass spectrometry (ICP-MS). The Bayesian kernel machine regression (BKMR) model and the weighted quantile sum regression (WQS) model were used to assess the overall effect of metal mixture exposure. The severity of neurological deficits in each acute ischemic stroke patient was evaluated using the National Institutes of Health Stroke Scale (NIHSS). Additionally, the associations between exposure to various metals and modifications in brain functional connectivity were determined using Pearson or Spearman correlation analysis.

RESULTS

Bilateral brain connectivity was significantly decreased compared to controls and was associated with neurological impairment in ischemic stroke. In patients with ischemic stroke, the plasma concentrations of Cr (p < 0.001), Cu (p = 0.004), As (p = 0.010), Cs (p = 0.046), Rb (p = 0.041), and Sb (p = 0.001) were significantly higher than those in the HCs, whereas the plasma Tl concentrations (p = 0.022) were significantly lower. The results of the BKMR and WQS models showed that combined exposure to metal mixtures was linked to a higher risk of ischemic stroke. Cr was positively correlated with the rs-FC between the left Rolandic_Oper and the left Supp_Motor_Area (r = 0.414, p = 0.029), while negatively correlated with the rs-FC between the right Parietal_Inf and the left supramarginal (r = -0.398, p = 0.037). Cu was negatively correlated with the rs-FC between the left paracentral lobule and the left thalamus (r = -0.409, p = 0.031). Tl was positively correlated with the rs-FC between the right Parietal_Inf and the left supramarginal cortex (r = 0.590, p = 0.001). A negative correlation was observed between Cs and rs-FC between the right Cingulate_Mid and left Occipital_Sup (r = -0.429, p = 0.024). Sb was negatively correlated with the rs-FC between the left Parietal_Inf and the right SupraMarginal (r = -0.384, p = 0.044), the right Parietal_Inf and the left SupraMarginal (r = -0.583, p = 0.001), and the left SupraMarginal and the right SupraMarginal (r = -0.377, p = 0.048).

CONCLUSION

Plasma levels of Cr, Cu, Tl, Cs, and Sb were associated with altered rs-FC in brain regions related to motor control, sensory integration, executive function, language processing, and emotional regulation in ischemic stroke patients with basal ganglia infarction.

Associations of a toenail metal mixture with attention and memory in the Gulf long-term follow-up (GuLF) study

BACKGROUND

Research on metal-associated neurodegeneration has largely focused on single metals. Since metal exposures typically co-occur as combinations of both toxic and essential elements, a mixtures framework is important for identifying risk and protective factors. This study examined associations between toenail levels of an eight-metal mixture and attention and memory in men living in US Gulf states.

METHODS

We measured toenail concentrations of toxic (arsenic, chromium, lead, and mercury) and essential (copper, manganese, selenium, and zinc) metals in 413 non-smoking men (23-69 years, 46 % Black) from the Gulf Long-Term Follow-Up (GuLF) Study. Sustained attention and working memory were assessed at the time of toenail sample collection using the continuous performance test (CPT) and digit span test (DST), respectively. Associations between toenail metal concentrations and performance on neurobehavioral tests were characterized using co-pollutant adjusted general linear models and Bayesian Kernel Machine Regression.

RESULTS

Adjusting for other metals, one interquartile range (IQR) increase in toenail chromium was associated with a 0.19 (95 % CI: -0.31, -0.07) point reduction in CPT D Prime score (poorer ability to discriminate test signals from noise). One IQR increase in toenail manganese was associated with a 0.20 (95 % CI, -0.41, 0.01) point reduction on the DST Reverse Count (fewer numbers recalled). Attention deficits were greater among Black participants compared to White participants for the same increase in toenail chromium concentrations. No evidence of synergistic interaction between metals or adverse effect of the overall metal mixture was observed for either outcome.

CONCLUSIONS

Our findings support existing studies of manganese-related memory deficits and are some of the first to show chromium related attention deficits in adults. Longitudinal study of cognitive decline is needed to verify chromium findings. Research into social and chemical co-exposures is also needed to explain racial differences in metal-associated neurobehavioral deficits observed in this study.

The Role of Copper Overload in Modulating Neuropsychiatric Symptoms

Copper is a transition metal essential for growth and development and indispensable for eukaryotic life. This metal is essential to neuronal function: its deficiency, as well as its overload have been associated with multiple neurodegenerative disorders such as Alzheimer's disease and Wilson's disease and psychiatric conditions such as schizophrenia, bipolar disorder, and major depressive disorders. Copper plays a fundamental role in the development and function of the human Central Nervous System (CNS), being a cofactor of multiple enzymes that play a key role in physiology during development. In this context, we thought it would be timely to summarize data on alterations in the metabolism of copper at the CNS level that might influence the development of neuropsychiatric symptoms. We present a non-systematic review with the study selection based on the authors' judgement to offer the reader a perspective on the most significant elements of neuropsychiatric symptoms in Wilson's disease. We highlight that Wilson's disease is characterized by marked heterogeneity in clinical presentation among patients with the same mutation. This should motivate more research efforts to disentangle the role of environmental factors in modulating the expression of genetic predisposition to this disorder.

Sex-specific associations between co-exposure to multiple metals and externalizing symptoms in adolescence and young adulthood

Externalizing disorders, such as attention-deficit/hyperactivity disorder (ADHD), account for the majority of the child/adolescent referrals to mental health services and increase risk for later-life psychopathology. Although the expression of externalizing disorders is more common among males, few studies have addressed how sex modifies associations between metal exposure and adolescent externalizing symptoms. This study aimed to examine sex-specific associations between co-exposure to multiple metals and externalizing symptoms in adolescence and young adulthood. Among 150 adolescents and young adults (55% female, ages: 15-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study in Brescia, Italy, we measured five metals (manganese (Mn), lead (Pb), copper (Cu), chromium (Cr), nickel (Ni)) in four biological matrices (blood, urine, hair, and saliva). Externalizing symptoms were assessed using the Achenbach System of Empirically Based Assessment (ASEBA) Youth Self-Report (YSR) or Adult Self Report (ASR). Using generalized weighted quantile sum (WQS) regression, we investigated the moderating effect of sex (i.e., assigned at birth) on associations between the joint effect of exposure to the metal mixture and externalizing symptoms, adjusting for age and socioeconomic status. We observed that metal mixture exposure was differentially associated with aggressive behavior in males compared to females (β = -0.058, 95% CI [-0.126, -0.009]). In males, exposure was significantly associated with more externalizing problems, and aggressive and intrusive behaviors, driven by Pb, Cu and Cr. In females, exposure was not significantly associated with any externalizing symptoms. These findings suggest that the effect of metal exposure on externalizing symptoms differs in magnitude between the sexes, with males being more vulnerable to increased externalizing symptoms following metal exposure. Furthermore, our findings support the hypothesis that sex-specific vulnerabilities to mixed metal exposure during adolescence/young adulthood may play a role in sex disparities observed in mental health disorders, particularly those characterized by externalizing symptoms.

Neuro-environmental interactions: a time sensitive matter

Introduction

The assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions. Here, we investigated how temporally-distal environmental inputs, specifically metal exposures experienced up to several months prior to scanning, affect functional dynamics measured using rs functional magnetic resonance imaging (rs-fMRI).

Methods

We implemented an interpretable XGBoost-shapley additive explanation (SHAP) model that integrated information from multiple exposure biomarkers to predict rs dynamics in typically developing adolescents. In 124 participants (53% females, ages, 13-25 years) enrolled in the public health impact of metals exposure (PHIME) study, we measured concentrations of six metals (manganese, lead, chromium, copper, nickel, and zinc) in biological matrices (saliva, hair, fingernails, toenails, blood, and urine) and acquired rs-fMRI scans. Using graph theory metrics, we computed global efficiency (GE) in 111 brain areas (Harvard Oxford atlas). We used a predictive model based on ensemble gradient boosting to predict GE from metal biomarkers, adjusting for age and biological sex.

Results

Model performance was evaluated by comparing predicted versus measured GE. SHAP scores were used to evaluate feature importance. Measured versus predicted rs dynamics from our model utilizing chemical exposures as inputs were significantly correlated (p < 0.001, r = 0.36). Lead, chromium, and copper contributed most to the prediction of GE metrics.

Discussion

Our results indicate that a significant component of rs dynamics, comprising approximately 13% of observed variability in GE, is driven by recent metal exposures. These findings emphasize the need to estimate and control for the influence of past and current chemical exposures in the assessment and analysis of rs functional connectivity.

Associations between blood essential metal mixture and serum uric acid: a cross-sectional study

Introduction

Although several studies have explored the associations between single essential metals and serum uric acid (SUA), the study about the essential metal mixture and the interactions of metals for hyperuricemia remains unclear.

Methods

We performed a cross-sectional study to explore the association of the SUA levels with the blood essential metal mixture, including magnesium (Mg), calcium (Ca), iron (Fe), copper (Cu), zinc (Zn), manganese (Mn) in Chinese community-dwelling adults (n=1039). The multivariable linear regression, the weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were conducted to estimate the associations of blood essential metals with SUA levels and the BKMR model was also conducted to estimate the interactions of the essential metals on SUA.

Results

In the multivariable linear regression, the association of blood Mg, Mn, and Cu with SUA was statistically significant, both in considering multiple metals and a single metal. In WQS regression [β=13.59 (95%CI: 5.57, 21.60)] and BKMR models, a positive association was found between the mixture of essential metals in blood and SUA. Specifically, blood Mg and Cu showed a positive association with SUA, while blood Mn showed a negative association. Additionally, no interactions between individual metals on SUA were observed.

Discussion

In conclusion, further attention should be paid to the relationship between the mixture of essential metals in blood and SUA. However, more studies are needed to confirm these findings.

Neuro-Environmental Interactions: a time sensitive matter

The assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions. Here, we investigated how temporally-distal environmental inputs, specifically metal exposures experienced up to several months prior to scanning, affect functional dynamics measured using rs functional magnetic resonance imaging (rs-fMRI). We implemented an interpretable XGBoost-Shapley Additive Explanation (SHAP) model that integrated information from multiple exposure biomarkers to predict rs dynamics in typically developing adolescents. In 124 participants (53% females, ages: 13-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of six metals (manganese, lead, chromium, cupper, nickel and zinc) in biological matrices (saliva, hair, fingernails, toenails, blood and urine) and acquired rs-fMRI scans. Using graph theory metrics, we computed global efficiency (GE) in 111 brain areas (Harvard Oxford Atlas). We used a predictive model based on ensemble gradient boosting to predict GE from metal biomarkers, adjusting for age and biological sex. Model performance was evaluated by comparing predicted versus measured GE. SHAP scores were used to evaluate feature importance. Measured versus predicted rs dynamics from our model utilizing chemical exposures as inputs were significantly correlated ( p < 0.001, r = 0.36). Lead, chromium, and copper contributed most to the prediction of GE metrics. Our results indicate that a significant component of rs dynamics, comprising approximately 13% of observed variability in GE, is driven by recent metal exposures. These findings emphasize the need to estimate and control for the influence of past and current chemical exposures in the assessment and analysis of rs functional connectivity.