Interactions between the lipidome and genetic and environmental factors in autism

Maternal-infant probiotic transmission mitigates early-life stress-induced autism in mice

Autism, a disorder influenced by both genetic and environmental factors, presents significant challenges for prevention and treatment. While maternal-infant gut microbiota has been a focus in autism research, preventive strategies targeting maternal gut microbiota remain underexplored. This study demonstrates that prenatal probiotic intake can effectively prevent maternal separation-induced autistic-like behaviors in offspring without altering the embryonic neurodevelopment in mice. Using specific PCR primers and cross-fostering experiments, we traced the vertical transmission of probiotics, primarily via fecal/vaginal contamination. Early probiotic colonization conferred resilience against stress-induced gut pathogenic microbes and Th17-mediated peripheral inflammation while significantly inhibiting hypermyelination and neuroinflammation linked to systemic inflammation. Microbial metabolites like tyrosol and xanthurenic acid alleviated neuroinflammation and hypermyelination in vitro, though the causal relationship among neuroinflammation, hypermyelination, and autism in vivo requires further validation. These findings underscore the importance of the maternal-infant microbiota transmission window in autism prevention and highlight the clinical potential of prenatal probiotic interventions.

Bidirectional Mendelian randomization analysis of plasma lipidome and psychiatric disorders

BACKGROUND

Evidence from observational studies and clinical experiments suggests a close association between plasma lipidome and psychiatric disorders. However, the causal relationship between plasma lipidome and psychiatric disorders remains insufficiently determined. Plasma lipidome are relatively easy to measure and regulate clinically, and they play a crucial role in neuronal signal transduction, making them a focus of interest as potential therapeutic targets for psychiatric disorders.

METHODS

In this study, we utilized the latest Finnish population-based genome-wide association study (GWAS) data on 179 lipid species. We downloaded data on five psychiatric disorders from the IEU database, including schizophrenia, bipolar disorder, depression, autism from the PGC consortium, and anxiety disorder from the Neale lab. Using two-sample bidirectional Mendelian randomization (MR) analysis, we assessed the relationship between these 179 lipid species and the risk of the five psychiatric disorders. To validate the assumptions of Mendelian randomization, we conducted tests for horizontal pleiotropy and heterogeneity.

RESULTS

After applying FDR correction to assess the relationship between 179 lipid species traits and the risk of five psychiatric disorders, our analysis provided evidence of a causal relationship specifically between genetic susceptibility in the plasma lipidome and bipolar disorder. This relationship notably involves eight phosphatidylcholines (PCs) and two sterols, with PCs displaying a dual and complex role in the disorder. Reverse Mendelian randomization (MR) analysis did not reveal a significant causal impact of psychiatric disorders on the plasma lipidome.

LIMITATIONS

Despite using two-sample bidirectional Mendelian randomization analysis, the complex biological pathways and potential confounding factors may still affect the accuracy of the causal relationships. The impact of genetic variations on the lipidome and psychiatric disorders may involve multiple mechanisms, which cannot be fully elucidated in this study.

CONCLUSION

This study identified a causal relationship between genetic susceptibility in plasma lipidome and bipolar disorder, indicating that plasma lipidome may influence the risk of psychiatric disorders and providing direction for exploring them as potential intervention targets. The findings not only deepen our understanding of the etiology of psychiatric disorders but also provide a critical theoretical foundation for future clinical interventions and prevention strategies, potentially contributing to the development of novel therapeutic approaches.

Cerebrospinal fluid metabolomics in autistic regression reveals dysregulation of sphingolipids and decreased β-hydroxybutyrate

BACKGROUND

Autism is highly heritable, however actionable genetic findings are only found in a minority of patients. Many people with autism suffer loss of neurodevelopmental skills, known as autistic regression. The cause of regression is poorly understood, and the diagnostic and therapeutic pathways are lacking.

METHODS

We used untargeted metabolomics using a UPLC-Q-Exactive-HFx Mass Spectrometry to examine cerebrospinal fluid (CSF) from twenty-two patients with autistic regression compared to sixteen controls with neurodevelopmental disorders (but not autistic regression) and thirty-four controls with other neurological disease (headache, encephalitis, epilepsy). The twenty-two patients with autistic regression consisted of two groups: early (infantile) autistic regression <2 years of age (n = 8), and later regression of skills >4 years of age, often in the context of pre-existing developmental concerns (n = 14). Metabolites of interest were then quantified and validated using targeted assays.

FINDINGS

Untargeted case-control studies revealed good separation of patients from controls using multivariate analysis. β-hydroxybutyrate was significantly decreased in the CSF of patients with autistic regression, and the findings were validated using a targeted β-hydroxybutyrate assay. The sphingolipid, sphingosine-1-phosphate was significantly elevated in the discovery case-control studies, and sphingolipid metabolism pathways were also significantly dysregulated. We therefore developed a targeted metabolite assay of forty sphingolipids. After FDR correction, 21 of the 40 sphingolipids were significantly dysregulated (pFDR < 0.05) (Benjamini-Hochberg correction) in autistic regression compared to the neurodevelopmental controls, and 26 of the 40 sphingolipids were significantly dysregulated in autistic regression compared to other neurological controls, with elevated ceramides, hexosylceramides, sphingosines (including sphingosine-1-phosphate), and sulfatides. By contrast, sphingomyelin levels were generally decreased in autistic regression.

INTERPRETATION

Our data shows the potential utility of CSF metabolomics in the context of autistic regression, a clinical syndrome which has historically lacked pathophysiological biomarkers and disease modifying therapies.

FUNDING

Financial support for the study was granted by Dale NHMRC Investigator grant APP1193648, Petre Foundation, Cerebral Palsy Alliance, and Ainsworth and SCHF Neuroscience grant scheme.

Investigating the association of the plasma lipidomic profile with cognitive performance and genetic risk in the PsyCourse study

Although lipid biology may play a key role in the pathophysiology of mental health disorders such as schizophrenia (SCZ) and bipolar disorder (BD), the nature of this interplay and how it could shape phenotypic presentation, including cognitive performance is still incompletely understood. To address this question, we analyzed the association of plasma level of different lipid species with cognitive performance in the transdiagnostic PsyCourse Study. Plasma lipidomic profiles of 623 individuals (188 SCZ, 243 BD, 192 healthy controls) belonging to the PsyCourse Study were assessed using liquid chromatography and untargeted mass spectrometry. The association between 364 annotated lipid species from 16 lipid classes and six cognitive tests was evaluated. Likewise, the association of polygenic risk scores (PRS) for SCZ, BD, executive function (EF), and educational attainment (EA) with lipid plasma levels were also investigated. In the regression analysis, three lipid species belonging to phosphatidylethanolamine plasmalogen and one belonging to ceramide class showed significant negative association with Digit-Symbol test scores. Lipid class-based enrichment analysis in LipidR replicated the significance of the phosphatidylethanolamines class for the Digit-Symbol test, which evaluates the processing speed in cognitive tasks. Polygenic load for SCZ, BD, EF, or EA was not associated with lipid levels. Our findings suggest a link between lipids and cognitive performance independent of mental health disorders. Still, independent replication is warranted to better understand if phosphatidylethanolamines could represent an actionable pharmacologic target to tackle cognitive dysfunction, an important unmet clinical need that affects long-term functional outcomes in individuals with severe mental health disorders.

Inequities in cardiovascular risk and lifestyle factors among individuals with developmental disabilities: evidence from Korea's national health screening program

Significant gaps persist in the awareness and understanding of the health challenges faced by individuals with developmental disabilities. This study aims to examine health disparities among individuals with developmental disabilities in South Korea, focusing on cardiovascular risk factors, including obesity, hypertension, diabetes, and dyslipidemia, and lifestyle factors like physical activity, smoking, and drinking behaviors. We analyzed data from the National General Health Screening Program for 2019 and 2020, including a sample of 17,012 persons with disabilities and 5,623,993 persons without disabilities. We utilized propensity score matching (1:1) and multivariable logistic regression estimated outcomes. After matching, each group included 13,863 individuals with balanced baseline characteristics. Individuals with disability had higher risks of overall and abdominal obesity and lower risks of smoking and drinking. No significant differences were found in blood pressure and fasting blood sugar levels post-matching. In addition, individuals with disability showed lower risks of abnormal cholesterol, low-density lipoprotein cholesterol and triglyceride levels, but higher risks for abnormal high-density lipoprotein cholesterol levels and lower physical activity levels. These findings highlight the urgent need for targeted interventions to address obesity and promote physical activity, while also acknowledging the lower risks of smoking and drinking in individuals with developmental disabilities.

Absence of Causal Relationship Between Levels of Unsaturated Fatty Acids and ADHD: Evidence From Mendelian Randomization Study

OBJECTIVE

Previous research suggests a potential link between unsaturated fatty acids (UFAs) and ADHD, but the causal relationship remains uncertain. This study aims to investigate the causal association between ADHD and UFAs using Mendelian randomization (MR) analysis.

METHODS

Summary data from genome-wide association studies were used to estimate the concentration of circulating UFAs, including Monounsaturated Fatty Acids (MUFAs), Polyunsaturated Fatty Acids (PUFAs), Omega-3 PUFAs, Omega-6 PUFAs, Linoleic Acid (LA), and Docosahexaenoic Acid (DHA). Data from the Psychiatric Genomics Consortium, including both childhood and adult ADHD, were respectively used to examine the relationship between genetically predicted UFAs levels and ADHD. Various MR methods, including Inverse-variance weighted (IVW), MR Pleiotropy RESidual Sum and Outlier, MR-Egger, weighted median, and weighted mode, were employed to assess heterogeneity and pleiotropy.

RESULTS

The IVW revealed only nominal evidence suggesting a potential causal relationship between genetically predicted PUFAs (OR = 0.92, 95% CI [0.85, 0.99], p = .031), Omega-6 PUFAs (OR = 0.90, 95% CI [0.83, 0.98], p = .020), and LA levels (OR = 0.90, 95% CI [0.82, 0.98], p = .021) with childhood ADHD risk. However, after false discovery rate correction, the p-values for PUFAs, Omega-6 PUFAs, and LA levels all exceeded the threshold for significance. For adult ADHD, we did not find any significant associations between the six circulating UFA levels and adult ADHD.

CONCLUSION

Our findings do not support a causal relationship between UFAs levels and ADHD. This suggests that UFAs supplements may not be effective in improving ADHD symptoms and importantly, it appears that UFAs levels may not have a long-term effect on ADHD.

Association between 25(OH) vitamin D and multiple sclerosis: cohort, shared genetics, and Causality

BACKGROUND

Multiple Sclerosis (MS), an autoimmune disorder causing demyelination and neurological damage, has been linked to 25-hydroxyvitamin D (25OHD) levels, suggesting its role in immune response and MS onset. This study used GWAS datasets to investigate genetic associations between 25OHD and MS.

METHODS

We utilized a large-scale prospective cohort to evaluate serum 25OHD levels and MS risk. Linkage Disequilibrium Score Regression (LDSC) assessed genetic correlations between 25OHD levels and MS. Cross-trait genome-wide pleiotropy analysis revealed shared genetic loci. MAGMA analysis identified pleiotropic genes, enriched tissues, and gene sets. Stratified LDSC estimated tissue-specific and cell-specific heritability enrichment, and multi-trait co-localization analysis identified shared immune cell subsets. Bidirectional Mendelian Randomization (MR) assessed the causal association between 25OHD and MS risk.

RESULTS

The observational study found a nonlinear relationship between 25OHD levels and MS risk, with the lowest quartile showing significant risk elevation. Our findings revealed shared genetic structure between 25OHD levels and MS, suggesting a common biological pathway involving immune function and CNS integrity. We found 24 independent loci shared between 25OHD levels and MS risk, enriched in brain tissues and involved in pathways like LDL, HDL, and TG metabolism. Four loci (6p24.3, 6p22.2, 12q14.1, and 19p13.2) had strong co-localization evidence, with mapped genes as potential drug targets. Bidirectional MR analysis supported a causal effect of 25OHD levels on MS risk, suggesting 25OHD supplementation could modulate MS risk.

CONCLUSION

This study reveals the complex relationship between 25OHD levels and MS, indicating that higher levels are not always advantageous and recommending moderation in supplementation. We identified SMARCA4 as a potential therapeutic target and detailed key pathways influencing this interaction.

Relationship between residual cholesterol and cognitive performance: a study based on NHANES

Background and aims

Age-related cognitive impairment impacts a significant portion of the elderly population. Remnant cholesterol (RC) has attracted increased attention in relation to cardiovascular disease, diabetes, hypertension, and fatty liver disease. Nevertheless, its role in cognitive function is still enigmatic, prompting our exploration into the potential associations between them.

Methods

A total of 1,331 participants from the NHANES (2011-2014) database, all aged over 60, were included in this investigation. Cognitive function was assessed using four widely applied tests, including the Consortium to Establish a Registry for Alzheimer's Disease Word Learning (CERAD-WL), CERAD Delayed Recall (CERAD-DR), Animal Fluency Test (AFT), as well as Digit Symbol Substitution test (DSST). Z-score is calculated by scores from the above four tests. The association between RC, total cholesterol (TC) to RC and cognitive performance was assessed by logistic regression analyses. In addition, restricted cubic spline (RCS) regression was performed to assess non-linearity between RC and cognitive function. Subgroup analysis was performed to evaluate the robustness of the results in populations with relevant covariate variables.

Results

Those with Z-scores below the 25% quartile are defined as having cognitive impairment, totaling 498 individuals. Observationally, higher RC levels and a lower TC/RC were associated with an increased risk of cognitive impairment. After adjusting for confounding factors, the impact of RC levels on cognitive performance quartiles was consistent across various subgroups, except in individuals with trouble sleeping, no/unknown alcohol use, and no hypertension. Americans with high RC levels and trouble sleeping are more likely to develop cognitive impairment, with an odds ratio of 2.33 (95% CI: 1.18-4.59).

Conclusion

This study suggests that higher RC levels and lower levels of TC/RC are associated with an increased likelihood of cognitive impairment, suggesting that RC can serve as a novel and convenient indicator for predicting the risk of cognitive impairment in the US population.

Western diets and chronic diseases

'Westernization', which incorporates industrial, cultural and dietary trends, has paralleled the rise of noncommunicable diseases across the globe. Today, the Western-style diet emerges as a key stimulus for gut microbial vulnerability, chronic inflammation and chronic diseases, affecting mainly the cardiovascular system, systemic metabolism and the gut. Here we review the diet of modern times and evaluate the threat it poses for human health by summarizing recent epidemiological, translational and clinical studies. We discuss the links between diet and disease in the context of obesity and type 2 diabetes, cardiovascular diseases, gut and liver diseases and solid malignancies. We collectively interpret the evidence and its limitations and discuss future challenges and strategies to overcome these. We argue that healthcare professionals and societies must react today to the detrimental effects of the Western diet to bring about sustainable change and improved outcomes in the future.

A lipidomic based metabolic age score captures cardiometabolic risk independent of chronological age

BACKGROUND

Metabolic ageing biomarkers may capture the age-related shifts in metabolism, offering a precise representation of an individual's overall metabolic health.

METHODS

Utilising comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,833, including 6630 males, 8203 females), we employed different machine learning models, to predict age, and calculated metabolic age scores (mAge). Furthermore, we defined the difference between mAge and age, termed mAgeΔ, which allow us to identify individuals sharing similar age but differing in their metabolic health status.

FINDINGS

Upon stratification of the population into quintiles by mAgeΔ, we observed that participants in the top quintile group (Q5) were more likely to have cardiovascular disease (OR = 2.13, 95% CI = 1.62-2.83), had a 2.01-fold increased risk of 12-year incident cardiovascular events (HR = 2.01, 95% CI = 1.45-2.57), and a 1.56-fold increased risk of 17-year all-cause mortality (HR = 1.56, 95% CI = 1.34-1.79), relative to the individuals in the bottom quintile group (Q1). Survival analysis further revealed that men in the Q5 group faced the challenge of reaching a median survival rate due to cardiovascular events more than six years earlier and reaching a median survival rate due to all-cause mortality more than four years earlier than men in the Q1 group.

INTERPRETATION

Our findings demonstrate that the mAge score captures age-related metabolic changes, predicts health outcomes, and has the potential to identify individuals at increased risk of metabolic diseases.

FUNDING

The specific funding of this article is provided in the acknowledgements section.

Metabolomic changes in children with autism

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication and repetitive behaviors. Metabolomic profiling has emerged as a valuable tool for understanding the underlying metabolic dysregulations associated with ASD.

AIM

To comprehensively explore metabolomic changes in children with ASD, integrating findings from various research articles, reviews, systematic reviews, meta-analyses, case reports, editorials, and a book chapter.

METHODS

A systematic search was conducted in electronic databases, including PubMed, PubMed Central, Cochrane Library, Embase, Web of Science, CINAHL, Scopus, LISA, and NLM catalog up until January 2024. Inclusion criteria encompassed research articles (83), review articles (145), meta-analyses (6), systematic reviews (6), case reports (2), editorials (2), and a book chapter (1) related to metabolomic changes in children with ASD. Exclusion criteria were applied to ensure the relevance and quality of included studies.

RESULTS

The systematic review identified specific metabolites and metabolic pathways showing consistent differences in children with ASD compared to typically developing individuals. These metabolic biomarkers may serve as objective measures to support clinical assessments, improve diagnostic accuracy, and inform personalized treatment approaches. Metabolomic profiling also offers insights into the metabolic alterations associated with comorbid conditions commonly observed in individuals with ASD.

CONCLUSION

Integration of metabolomic changes in children with ASD holds promise for enhancing diagnostic accuracy, guiding personalized treatment approaches, monitoring treatment response, and improving outcomes. Further research is needed to validate findings, establish standardized protocols, and overcome technical challenges in metabolomic analysis. By advancing our understanding of metabolic dysregulations in ASD, clinicians can improve the lives of affected individuals and their families.

Blood Lipids, Lipoproteins, and Apolipoproteins With Risk of Coronary Heart Disease: A Prospective Study Among Racially Diverse Populations

BACKGROUND

Comprehensive blood lipoprotein profiles and their association with incident coronary heart disease (CHD) among racially and geographically diverse populations remain understudied.

METHODS AND RESULTS

We conducted nested case-control studies of CHD among 3438 individuals (1719 pairs), including 1084 White Americans (542 pairs), 1244 Black Americans (622 pairs), and 1110 Chinese adults (555 pairs). We examined 36 plasma lipids, lipoproteins, and apolipoproteins, measured by nuclear magnetic resonance spectroscopy, with incident CHD among all participants and subgroups by demographics, lifestyle, and metabolic health status using conditional or unconditional logistic regression adjusted for potential confounders. Conventionally measured blood lipids, that is, total cholesterol, triglycerides, low-density lipoprotein-cholesterol, and high-density lipoprotein-cholesterol, were each associated with incident CHD, with odds ratios (ORs) being 1.33, 1.32, 1.24, and 0.79 per 1-SD increase among all participants. Seventeen lipoprotein biomarkers showed numerically stronger associations than conventional lipids, with ORs per 1-SD among all participants ranging from 1.35 to 1.57 and a negative OR of 0.78 (all false discovery rate <0.05), including apolipoprotein B100 to apolipoprotein A1 ratio (OR, 1.57 [95% CI, 1.45-1.7]), low-density lipoprotein-triglycerides (OR, 1.55 [95% CI, 1.43-1.69]), and apolipoprotein B (OR, 1.49 [95% CI, 1.37-1.62]). All these associations were significant and consistent across racial groups and other subgroups defined by age, sex, smoking, obesity, and metabolic health status, including individuals with normal levels of conventionally measured lipids.

CONCLUSIONS

Our study highlighted several lipoprotein biomarkers, including apolipoprotein B/ apolipoprotein A1 ratio, apolipoprotein B, and low-density lipoprotein-triglycerides, strongly and consistently associated with incident CHD. Our results suggest that comprehensive lipoprotein measures may complement the standard lipid panel to inform CHD risk among diverse populations.

Additive interaction between birth asphyxia and febrile seizures on autism spectrum disorder: a population-based study

BACKGROUND

Autism Spectrum Disorder (ASD) is a pervasive neurodevelopmental disorder that can significantly impact an individual's ability to socially integrate and adapt. It's crucial to identify key factors associated with ASD. Recent studies link both birth asphyxia (BA) and febrile seizures (FS) separately to higher ASD prevalence. However, investigations into the interplay of BA and FS and its relationship with ASD are yet to be conducted. The present study mainly focuses on exploring the interactive effect between BA and FS in the context of ASD.

METHODS

Utilizing a multi-stage stratified cluster sampling, we initially recruited 84,934 Shanghai children aged 3-12 years old from June 2014 to June 2015, ultimately including 74,251 post-exclusion criteria. A logistic regression model was conducted to estimate the interaction effect after controlling for pertinent covariates. The attributable proportion (AP), the relative excess risk due to interaction (RERI), the synergy index (SI), and multiplicative-scale interaction were computed to determine the interaction effect.

RESULTS

Among a total of 74,251 children, 192 (0.26%) were diagnosed with ASD. The adjusted odds ratio for ASD in children with BA alone was 3.82 (95% confidence interval [CI] 2.42-6.02), for FS alone 3.06 (95%CI 1.48-6.31), and for comorbid BA and FS 21.18 (95%CI 9.10-49.30), versus children without BA or FS. The additive interaction between BA and FS showed statistical significance (P < 0.001), whereas the multiplicative interaction was statistically insignificant (P > 0.05).

LIMITATIONS

This study can only demonstrate the relationship between the interaction of BA and FS with ASD but cannot prove causation. Animal brain experimentation is necessary to unravel its neural mechanisms. A larger sample size, ongoing monitoring, and detailed FS classification are needed for confirming BA-FS interaction in ASD.

CONCLUSION

In this extensive cross-sectional study, both BA and FS were significantly linked to ASD. The coexistence of these factors was associated with an additive increase in ASD prevalence, surpassing the cumulative risk of each individual factor.

Investigating the shared genetic architecture between COVID-19 and obesity: a large-scale genome wide cross-trait analysis

Observational studies have reported high comorbidity between obesity and severe COVID-19. The aim of this study is to explore whether genetic factors are involved in the co-occurrence of the two traits. Based on the available genome-wide association studies (GWAS) summary statistics, we explored the genetic correlation and performed cross-trait meta-analysis (CPASSOC) and colocalization analysis (COLOC) to detect pleiotropic single nucleotide polymorphisms (SNPs). At the genetic level, we obtained genes detected by Functional mapping and annotation (FUMA) and the Multi-marker Analysis of GenoMic Annotation (MAGMA). Potential functional genes were further investigated by summary-data-based Mendelian randomization (SMR). Finally, the casualty was identiied using the latent causal variable model (LCV). A significant positive genetic correlation was revealed between obesity and COVID-19. We found 331 shared genetic SNPs by CPASSOC and 13 shared risk loci by COLOC. At the genetic level, We obtained 3546 pleiotropic genes, among which 107 genes were found to be significantly expressed by SMR. Lastly, we observed these genes were mainly enriched in immune pathways and signaling transduction. These indings could provide new insights into the etiology of comorbidity and have implications for future therapeutic trial.

Neuropsychiatric biomarker discovery: go big or go home

Technological advances have enabled high-throughput omics assays, such as parallelized screening of lipids across plasma samples. Pioneering a new paradigm for neuropsychiatric biomarker discovery, Yap et al. describe a large-scale systematic analysis of comprehensive phenotypic, genotypic, environmental, and lipidomic data to unravel the intricate interplay between these and autism-associated traits.

The microbiota-gut-brain axis and neurodevelopmental disorders

The gut microbiota has been found to interact with the brain through the microbiota-gut-brain axis, regulating various physiological processes. In recent years, the impacts of the gut microbiota on neurodevelopment through this axis have been increasingly appreciated. The gut microbiota is commonly considered to regulate neurodevelopment through three pathways, the immune pathway, the neuronal pathway, and the endocrine/systemic pathway, with overlaps and crosstalks in between. Accumulating studies have identified the role of the microbiota-gut-brain axis in neurodevelopmental disorders including autism spectrum disorder, attention deficit hyperactivity disorder, and Rett Syndrome. Numerous researchers have examined the physiological and pathophysiological mechanisms influenced by the gut microbiota in neurodevelopmental disorders (NDDs). This review aims to provide a comprehensive overview of advancements in research pertaining to the microbiota-gut-brain axis in NDDs. Furthermore, we analyzed both the current state of research progress and discuss future perspectives in this field.

Screening autism-associated environmental factors in differentiating human neural progenitors with fractional factorial design-based transcriptomics

Research continues to identify genetic variation, environmental exposures, and their mixtures underlying different diseases and conditions. There is a need for screening methods to understand the molecular outcomes of such factors. Here, we investigate a highly efficient and multiplexable, fractional factorial experimental design (FFED) to study six environmental factors (lead, valproic acid, bisphenol A, ethanol, fluoxetine hydrochloride and zinc deficiency) and four human induced pluripotent stem cell line derived differentiating human neural progenitors. We showcase the FFED coupled with RNA-sequencing to identify the effects of low-grade exposures to these environmental factors and analyse the results in the context of autism spectrum disorder (ASD). We performed this after 5-day exposures on differentiating human neural progenitors accompanied by a layered analytical approach and detected several convergent and divergent, gene and pathway level responses. We revealed significant upregulation of pathways related to synaptic function and lipid metabolism following lead and fluoxetine exposure, respectively. Moreover, fluoxetine exposure elevated several fatty acids when validated using mass spectrometry-based metabolomics. Our study demonstrates that the FFED can be used for multiplexed transcriptomic analyses to detect relevant pathway-level changes in human neural development caused by low-grade environmental risk factors. Future studies will require multiple cell lines with different genetic backgrounds for characterising the effects of environmental exposures in ASD.