Absence of association between maternal adverse events and long-term gut microbiome outcomes in the Australian autism biobank.

Introduction: Maternal immune activation (MIA) and prenatal maternal stress (MatS) are well-studied risk factors for psychiatric conditions such as autism and schizophrenia. Animal studies have proposed the gut microbiome as a mechanism underlying this association and have found that risk factor-related gut microbiome alterations persist in the adult offspring. In this cross-sectional study, we assessed whether maternal immune activation and prenatal maternal stress were associated with long-term gut microbiome alterations in children using shotgun metagenomics. Methods: This cross-sectional study included children diagnosed with autism (N = 92), siblings without a diagnosis (N = 42), and unrelated children (N = 40) without a diagnosis who were recruited into the Australian Autism Biobank and provided a faecal sample. MIA exposure was inferred from self-reported data and included asthma/allergies, complications during pregnancy triggering an immune response, auto-immune conditions, and acute inflammation. Maternal stress included any of up to 9 stressful life events during pregnancy, such as divorce, job loss, and money problems. Data were analysed for a total of 174 children, of whom 63 (36%) were born to mothers with MIA and 84 (48%) were born to mothers who experienced maternal stress during pregnancy (where 33 [19%] experienced both). Gut microbiome data was assessed using shotgun metagenomic sequencing of the children's faecal samples. Results: In our cohort, MIA, but not MatS, was associated with ASD. Variance component analysis revealed no associations between any of the gut microbiome datasets and neither MIA nor MatS. After adjusting for age, sex, diet and autism diagnosis, there was no significant difference between groups for bacterial richness, α-diversity or ß-diversity. We found no significant differences in species abundance in the main analyses. However, when stratifying the cohort by age, we found that Faecalibacterium prausnitzii E was significantly decreased in MIA children aged 11-17. Discussion: Consistent with previous findings, we found that children who were born to mothers with MIA were more likely to be diagnosed with autism. Unlike within animal studies, we found negligible microbiome differences associated with MIA and maternal stress. Given the current interest in the microbiome-gut-brain axis, researchers should exercise caution in translating microbiome findings from animal models to human contexts and the clinical setting.

Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics.

Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial cell loss contributes to Alzheimer's disease, with comparable effect size to APOE genotype among older people. Genome-wide association identified five genetic loci related to cell-type composition, involving plausible genes for the neurovascular unit (P2RX5 and TRPV3) and excitatory neurons (DPY30 and MEMO1). These results implicate specific cell-type shifts in the pathophysiology of neuropsychiatric disorders.

New horizons in undergraduate geriatric medicine education.

Current projections show that between 2000 and 2050, increasing proportions of older individuals will be cared for by a smaller number of healthcare workers, which will exacerbate the existing challenges faced by those who support this patient demographic. This review of a collection of Age and Ageing papers on the topic in the past 10 years explores (1) what best practice geriatrics education is and (2) how careers in geriatrics could be made more appealing to improve recruitment and retention. Based on these deeper understandings, we consider, as clinician educators, how to close the gap both pragmatically and theoretically. We point out paradigm shifting solutions that include innovations at the Undergraduate level, use of simulation, incorporation of learner and patient perspectives, upskilling professionals outside of Geriatrics and integration of practice across disciplines through Interprofessional Learning. We also identify an education research methodological gap. Specifically, there is an abundance of simple descriptive or justification studies but few clarification education studies; the latter are essential to develop fresh insights into how Undergraduate students can learn more effectively to meet the needs of the global ageing challenge. A case of improving understanding in delirium education is presented as an illustrative example of a new approach to exploring at greater depth education and outlines suggested directions for the future.

Interactions between the lipidome and genetic and environmental factors in autism.

Autism omics research has historically been reductionist and diagnosis centric, with little attention paid to common co-occurring conditions (for example, sleep and feeding disorders) and the complex interplay between molecular profiles and neurodevelopment, genetics, environmental factors and health. Here we explored the plasma lipidome (783 lipid species) in 765 children (485 diagnosed with autism spectrum disorder (ASD)) within the Australian Autism Biobank. We identified lipids associated with ASD diagnosis (n = 8), sleep disturbances (n = 20) and cognitive function (n = 8) and found that long-chain polyunsaturated fatty acids may causally contribute to sleep disturbances mediated by the FADS gene cluster. We explored the interplay of environmental factors with neurodevelopment and the lipidome, finding that sleep disturbances and unhealthy diet have a convergent lipidome profile (with potential mediation by the microbiome) that is also independently associated with poorer adaptive function. In contrast, ASD lipidome differences were accounted for by dietary differences and sleep disturbances. We identified a large chr19p13.2 copy number variant genetic deletion spanning the LDLR gene and two high-confidence ASD genes (ELAVL3 and SMARCA4) in one child with an ASD diagnosis and widespread low-density lipoprotein-related lipidome derangements. Lipidomics captures the complexity of neurodevelopment, as well as the biological effects of conditions that commonly affect quality of life among autistic people.

The shared genetic landscape of blood cell traits and risk of neurological and psychiatric disorders.

Phenotypic associations have been reported between blood cell traits (BCTs) and a range of neurological and psychiatric disorders (NPDs), but in most cases, it remains unclear whether these associations have a genetic basis and, if so, to what extent genetic correlations reflect causality. Here, we report genetic correlations and Mendelian randomization analyses between 11 NPDs and 29 BCTs, using genome-wide association study summary statistics. We found significant genetic correlations for four BCT-NPD pairs, all of which have prior evidence for a phenotypic correlation. We identified a previously unreported causal effect of increased platelet distribution width on susceptibility to Parkinson's disease. We identified multiple functional genes and regulatory elements for specific BCT-NPD pairs, some of which are targets of known drugs. These results enrich our understanding of the shared genetic landscape underlying BCTs and NPDs and provide a robust foundation for future work to improve prognosis and treatment of common NPDs.

Phenotypic and genetic factors associated with donation of DNA and consent to record linkage for prescription history in the Australian Genetics of Depression Study.

Samples can be prone to ascertainment and attrition biases. The Australian Genetics of Depression Study is a large publicly recruited cohort (n = 20,689) established to increase the understanding of depression and antidepressant treatment response. This study investigates differences between participants who donated a saliva sample or agreed to linkage of their records compared to those who did not. We observed that older, male participants with higher education were more likely to donate a saliva sample. Self-reported bipolar disorder, ADHD, panic disorder, PTSD, substance use disorder, and social anxiety disorder were associated with lower odds of donating a saliva sample, whereas anorexia was associated with higher odds of donation. Male and younger participants showed higher odds of agreeing to record linkage. Participants with higher neuroticism scores and those with a history of bipolar disorder were also more likely to agree to record linkage whereas participants with a diagnosis of anorexia were less likely to agree. Increased likelihood of consent was associated with increased genetic susceptibility to anorexia and reduced genetic risk for depression, and schizophrenia. Overall, our results show moderate differences among these subsamples. Most current epidemiological studies do not search for attrition biases at the genetic level. The possibility to do so is a strength of samples such as the AGDS. Our results suggest that analyses can be made more robust by identifying attrition biases both on the phenotypic and genetic level, and either contextualising them as a potential limitation or performing sensitivity analyses adjusting for them.

Broad transcriptomic dysregulation occurs across the cerebral cortex in ASD.

Neuropsychiatric disorders classically lack defining brain pathologies, but recent work has demonstrated dysregulation at the molecular level, characterized by transcriptomic and epigenetic alterations1-3. In autism spectrum disorder (ASD), this molecular pathology involves the upregulation of microglial, astrocyte and neural-immune genes, the downregulation of synaptic genes, and attenuation of gene-expression gradients in cortex1,2,4-6. However, whether these changes are limited to cortical association regions or are more widespread remains unknown. To address this issue, we performed RNA-sequencing analysis of 725 brain samples spanning 11 cortical areas from 112 post-mortem samples from individuals with ASD and neurotypical controls. We find widespread transcriptomic changes across the cortex in ASD, exhibiting an anterior-to-posterior gradient, with the greatest differences in primary visual cortex, coincident with an attenuation of the typical transcriptomic differences between cortical regions. Single-nucleus RNA-sequencing and methylation profiling demonstrate that this robust molecular signature reflects changes in cell-type-specific gene expression, particularly affecting excitatory neurons and glia. Both rare and common ASD-associated genetic variation converge within a downregulated co-expression module involving synaptic signalling, and common variation alone is enriched within a module of upregulated protein chaperone genes. These results highlight widespread molecular changes across the cerebral cortex in ASD, extending beyond association cortex to broadly involve primary sensory regions.

Autism-related dietary preferences mediate autism-gut microbiome associations.

There is increasing interest in the potential contribution of the gut microbiome to autism spectrum disorder (ASD). However, previous studies have been underpowered and have not been designed to address potential confounding factors in a comprehensive way. We performed a large autism stool metagenomics study (n = 247) based on participants from the Australian Autism Biobank and the Queensland Twin Adolescent Brain project. We found negligible direct associations between ASD diagnosis and the gut microbiome. Instead, our data support a model whereby ASD-related restricted interests are associated with less-diverse diet, and in turn reduced microbial taxonomic diversity and looser stool consistency. In contrast to ASD diagnosis, our dataset was well powered to detect microbiome associations with traits such as age, dietary intake, and stool consistency. Overall, microbiome differences in ASD may reflect dietary preferences that relate to diagnostic features, and we caution against claims that the microbiome has a driving role in ASD.

Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism. METHODS: Genome-wide single-nucleotide polymorphism genotypes were available for 2,477 individuals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed (n = 871) or suspected (n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European (n = 1,964 European individuals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain. RESULTS: The ASD (p = 6.1e-13), sibling (p = 4.9e-3) and unrelated (p = 3.0e-3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height-a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children (r = 0.24, p = 2.1e-3) and parents (r = 0.17, p = 8.0e-7; 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group (r = 0.13, p = 1.9e-3; 1.3% of variance). In the CNV analysis, we identified 13 individuals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants. LIMITATIONS: This dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered. CONCLUSIONS: We report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair).

Dissection of genetic variation and evidence for pleiotropy in male pattern baldness.

Male pattern baldness (MPB) is a sex-limited, age-related, complex trait. We study MPB genetics in 205,327 European males from the UK Biobank. Here we show that MPB is strongly heritable and polygenic, with pedigree-heritability of 0.62 (SE = 0.03) estimated from close relatives, and SNP-heritability of 0.39 (SE = 0.01) from conventionally-unrelated males. We detect 624 near-independent genome-wide loci, contributing SNP-heritability of 0.25 (SE = 0.01), of which 26 X-chromosome loci explain 11.6%. Autosomal genetic variance is enriched for common variants and regions of lower linkage disequilibrium. We identify plausible genetic correlations between MPB and multiple sex-limited markers of earlier puberty, increased bone mineral density (rg = 0.15) and pancreatic ß-cell function (rg = 0.12). Correlations with reproductive traits imply an effect on fitness, consistent with an estimated linear selection gradient of -0.018 per MPB standard deviation. Overall, we provide genetic insights into MPB: a phenotype of interest in its own right, with value as a model sex-limited, complex trait.

Author Correction: Misestimation of heritability and prediction accuracy of male-pattern baldness.

The original version of this Article contained an error in the spelling of the author Julia Sidorenko, which was incorrectly given as Julia Sirodenko. This has now been corrected in both the PDF and HTML versions of the Article. Further, the sixth sentence of the second paragraph of the Correspondence and the legend to Fig. 1 incorrectly omitted citation of work by Heilmann-Helmbach, S. et al. This has now been corrected in both the PDF and HTML versions of the Article.

Trans-eQTLs identified in whole blood have limited influence on complex disease biology.

Trans-eQTLs have been implicated in complex traits and common diseases, but many were initially identified on the basis of having an effect in cis, and there has been no assessment of the significance of the overlap in relation to chance expectations. Here, we investigated whether trans-expression quantitative trait loci (eQTL) associations identified in whole blood contribute to variance in complex traits by determining (1) whether genome-wide significant (GWS) single-nucleotide polymorphisms (SNPs) were enriched for trans-eQTL (including trans-only eQTL), and (2) whether the genomic regions surrounding associated trans-genes were enriched for statistical associations in the relevant GWAS. On average for a given phenotype, we identify 4.8% of GWS SNPs overlapping with trans-eQTL present in blood, and show that for the majority of these phenotypes, this observation does not exceed that expected by chance. Likewise, we observe no enrichment for genetic associations with the GWAS phenotype in the regions surrounding the linked trans-genes, with the exception of rheumatoid arthritis. Interestingly, the GWS SNPs for each phenotype were consistently more enriched for unique trans-eQTL SNPs than trans-eQTL SNP-probe pairs (p = 4 × 10-7), with schizophrenia the only exception. This relative enrichment for trans-eQTL SNPs over trans-eQTL SNP-probe pairs implies that trait-associated trans-eQTL SNPs in whole blood are less likely to be 'master regulators' than random trans-eQTL SNPs. Taken together, these results suggest little evidence for the role of blood-based trans-eQTL in complex traits and disease, although this may reflect the finite size of currently available data sets and our findings may not hold for trans-eQTLs in more trait-relevant tissues. All software is publically available at https://github.com/IMB-Computational-Genomics-Lab/eqtlOverlapper .

Signatures of negative selection in the genetic architecture of human complex traits.

We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.

Contact inhibition of locomotion and mechanical cross-talk between cell-cell and cell-substrate adhesion determine the pattern of junctional tension in epithelial cell aggregates.

We used a computational approach to analyze the biomechanics of epithelial cell aggregates-islands, stripes, or entire monolayers-that combines both vertex and contact-inhibition-of-locomotion models to include cell-cell and cell-substrate adhesion. Examination of the distribution of cell protrusions (adhesion to the substrate) in the model predicted high-order profiles of cell organization that agree with those previously seen experimentally. Cells acquired an asymmetric distribution of basal protrusions, traction forces, and apical aspect ratios that decreased when moving from the edge to the island center. Our in silico analysis also showed that tension on cell-cell junctions and apical stress is not homogeneous across the island. Instead, these parameters are higher at the island center and scale up with island size, which we confirmed experimentally using laser ablation assays and immunofluorescence. Without formally being a three-dimensional model, our approach has the minimal elements necessary to reproduce the distribution of cellular forces and mechanical cross-talk, as well as the distribution of principal stress in cells within epithelial cell aggregates. By making experimentally testable predictions, our approach can aid in mechanical analysis of epithelial tissues, especially when local changes in cell-cell and/or cell-substrate adhesion drive collective cell behavior.