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.

Parkinson's disease age at onset genome-wide association study: Defining heritability, genetic loci, and α-synuclein mechanisms.

BACKGROUND: Increasing evidence supports an extensive and complex genetic contribution to PD. Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age at onset are largely unknown. OBJECTIVES: To identify the genetic determinants of PD age at onset. METHODS: Using genetic data of 28,568 PD cases, we performed a genome-wide association study based on PD age at onset. RESULTS: We estimated that the heritability of PD age at onset attributed to common genetic variation was ∼0.11, lower than the overall heritability of risk for PD (∼0.27), likely, in part, because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni-corrected significant effect at other known PD risk loci, GBA, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. Notably, SNCA, TMEM175, SCARB2, BAG3, and GBA have all been shown to be implicated in α-synuclein aggregation pathways. Remarkably, other well-established PD risk loci, such as GCH1 and MAPT, did not show a significant effect on age at onset of PD. CONCLUSIONS: Overall, we have performed the largest age at onset of PD genome-wide association studies to date, and our results show that not all PD risk loci influence age at onset with significant differences between risk alleles for age at onset. This provides a compelling picture, both within the context of functional characterization of disease-linked genetic variability and in defining differences between risk alleles for age at onset, or frank risk for disease. © 2019 International Parkinson and Movement Disorder Society.

Life history trade-offs at a single locus maintain sexually selected genetic variation.

Sexual selection, through intra-male competition or female choice, is assumed to be a source of strong and sustained directional selection in the wild. In the presence of such strong directional selection, alleles enhancing a particular trait are predicted to become fixed within a population, leading to a decrease in the underlying genetic variation. However, there is often considerable genetic variation underlying sexually selected traits in wild populations, and consequently, this phenomenon has become a long-discussed issue in the field of evolutionary biology. In wild Soay sheep, large horns confer an advantage in strong intra-sexual competition, yet males show an inherited polymorphism for horn type and have substantial genetic variation in their horn size. Here we show that most genetic variation in this trait is maintained by a trade-off between natural and sexual selection at a single gene, relaxin-like receptor 2 (RXFP2). We found that an allele conferring larger horns, Ho(+), is associated with higher reproductive success, whereas a smaller horn allele, Ho(P), confers increased survival, resulting in a net effect of overdominance (that is, heterozygote advantage) for fitness at RXFP2. The nature of this trade-off is simple relative to commonly proposed explanations for the maintenance of sexually selected traits, such as genic capture ('good genes') and sexually antagonistic selection. Our results demonstrate that by identifying the genetic architecture of trait variation, we can determine the principal mechanisms maintaining genetic variation in traits under strong selection and explain apparently counter-evolutionary observations.

Gene networks associated with non-syndromic intellectual disability.

Non-syndromic intellectual disability (NS-ID) is a genetically heterogeneous disorder, with more than 200 candidate genes to date. Despite the increasing number of novel mutations detected, a relatively low number of recurrently mutated genes have been identified, highlighting the complex genetic architecture of the disorder. A systematic search of PubMed and Medline identified 245 genes harbouring non-synonymous variants, insertions or deletions, which were identified as candidate NS-ID genes from case reports or from linkage or pedigree analyses. From this list, 33 genes are common to syndromic intellectual disability (S-ID) and 58 genes are common to certain neurological and neuropsychiatric disorders that often include intellectual disability as a clinical feature. We examined the evolutionary constraint and brain expression of these gene sets, and we performed gene network and protein-protein interaction analyses using GeneGO MetaCoreTM and DAPPLE, respectively. The 245 NS-ID candidate genes were over-represented in axon guidance, synaptogenesis, cell adhesion and neurotransmission pathways, all of which are key neurodevelopmental processes for the establishment of mature neuronal circuitry in the brain. These 245 genes exhibit significantly elevated expression in human brain and are evolutionarily constrained, consistent with expectations for a brain disorder such as NS-ID that is associated with reduced fecundity. In addition, we report enrichment of dopaminergic and glutamatergic pathways for those candidate NS-ID genes that are common to S-ID and/or neurological and neuropsychiatric disorders that exhibit intellectual disability. Collectively, this study provides an overview and analysis of gene networks associated with NS-ID and suggests modulation of neurotransmission, particularly dopaminergic and glutamatergic systems as key contributors to synaptic dysfunction in NS-ID.

Study protocol for the Australian autism biobank: an international resource to advance autism discovery research.

BACKGROUND: The phenotypic and genetic heterogeneity of autism spectrum disorder (ASD) presents considerable challenges in understanding etiological pathways, selecting effective therapies, providing genetic counselling, and predicting clinical outcomes. With advances in genetic and biological research alongside rapid-pace technological innovations, there is an increasing imperative to access large, representative, and diverse cohorts to advance knowledge of ASD. To date, there has not been any single collective effort towards a similar resource in Australia, which has its own unique ethnic and cultural diversity. The Australian Autism Biobank was initiated by the Cooperative Research Centre for Living with Autism (Autism CRC) to establish a large-scale repository of biological samples and detailed clinical information about children diagnosed with ASD to facilitate future discovery research. METHODS: The primary group of participants were children with a confirmed diagnosis of ASD, aged between 2 and 17 years, recruited through four sites in Australia. No exclusion criteria regarding language level, cognitive ability, or comorbid conditions were applied to ensure a representative cohort was recruited. Both biological parents and siblings were invited to participate, along with children without a diagnosis of ASD, and children who had been queried for an ASD diagnosis but did not meet diagnostic criteria. All children completed cognitive assessments, with probands and parents completing additional assessments measuring ASD symptomatology. Parents completed questionnaires about their child's medical history and early development. Physical measurements and biological samples (blood, stool, urine, and hair) were collected from children, and physical measurements and blood samples were collected from parents. Samples were sent to a central processing site and placed into long-term storage. DISCUSSION: The establishment of this biobank is a valuable international resource incorporating detailed clinical and biological information that will help accelerate the pace of ASD discovery research. Recruitment into this study has also supported the feasibility of large-scale biological sample collection in children diagnosed with ASD with comprehensive phenotyping across a wide range of ages, intellectual abilities, and levels of adaptive functioning. This biological and clinical resource will be open to data access requests from national and international researchers to support future discovery research that will benefit the autistic community.

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.

Associations of the Gut Microbiome With Treatment Resistance in Schizophrenia.

Importance: There is growing interest in the role of gut microbiome composition in schizophrenia. However, lifestyle factors are often neglected, and few studies have investigated microbiome composition in treatment-resistant schizophrenia. Objective: To explore associations between the gut microbiome and schizophrenia diagnosis, treatment resistance, clozapine response, and treatment-related adverse effects while adjusting for demographic and lifestyle factors. Design, Setting, and Participants: In this case-control study of adults aged 20 to 63 years, stool samples and data on demographic characteristics, lifestyle, and medication use were collected and gut microbiome measures obtained using shotgun metagenomics. Participants with a schizophrenia diagnosis were referred through psychiatric inpatient units and outpatient clinics. Data were collected for 4 distinct groups: control individuals without a psychiatric diagnosis (past or present), individuals with treatment-responsive schizophrenia taking nonclozapine antipsychotic medications, clozapine-responsive individuals with treatment-resistant schizophrenia, and clozapine-nonresponsive individuals with treatment-resistant schizophrenia. Participants were recruited between November 2020 and November 2021. Control individuals were recruited in parallel through posters and online advertisements and matched for age, sex, and body mass index (BMI) to the individuals with schizophrenia. Participants were excluded if taking antibiotics in the past 2 months, if unable to communicate in English or otherwise follow study instructions, were pregnant or planning to become pregnant, or had any concomitant disease or condition making them unsuited to the study per investigator assessment. Data were analyzed from January 2022 to March 2023. Main Outcomes and Measures: Omics relationship matrices, α and ß diversity, and relative abundance of microbiome features. Results: Data were collected for 97 individuals (71 [74%] male; mean [SD] age, 40.4 [10.3] years; mean [SD] BMI, 32.8 [7.4], calculated as weight in kilograms divided by height in meters squared). Significant microbiome associations with schizophrenia were observed at multiple taxonomic and functional levels (eg, common species: b2, 30%; SE, 13%; adjusted P = .002) and treatment resistance (eg, common species: b2, 27%; SE, 16%; adjusted P = .03). In contrast, limited evidence was found for microbiome associations with clozapine response, constipation, or metabolic syndrome. Significantly decreased microbial richness was found in individuals with schizophrenia compared to control individuals (t95 = 4.25; P < .001; mean [SD] for control individuals, 151.8 [32.31]; mean [SD] for individuals with schizophrenia, 117.00 [36.2]; 95% CI, 18.6-51.0), which remained significant after a covariate and multiple comparison correction. However, limited evidence was found for differences in ß diversity (weighted UniFrac) for schizophrenia diagnosis (permutational multivariate analysis of variance [PERMANOVA]: R2, 0.03; P = .02), treatment resistance (R2, 0.02; P = .18), or clozapine response (R2, 0.04; P = .08). Multiple differentially abundant bacterial species (19) and metabolic pathways (162) were found in individuals with schizophrenia, which were primarily associated with treatment resistance and clozapine exposure. Conclusions and Relevance: The findings in this study are consistent with the idea that clozapine induces alterations to gut microbiome composition, although the possibility that preexisting microbiome differences contribute to treatment resistance cannot be ruled out. These findings suggest that prior reports of microbiome alterations in individuals with chronic schizophrenia may be due to medication or lifestyle factors and that future studies should incorporate these variables in their design and interpretation.

Introgression and the fate of domesticated genes in a wild mammal population.

When domesticated species are not reproductively isolated from their wild relatives, the opportunity arises for artificially selected variants to be re-introduced into the wild. However, the evolutionary consequences of introgression of domesticated genes back into the wild are poorly understood. By combining high-throughput genotyping with 25 years of long-term ecological field data, we describe the occurrence and consequences of admixture between a primitive sheep breed, the free-living Soay sheep of St Kilda, and more modern breeds. Utilizing data from a 50 K ovine SNP chip, together with forward simulations of demographic scenarios, we show that admixture occurred between Soay sheep and a more modern breed, consistent with historical accounts, approximately 150 years ago. Haplotype-sharing analyses with other breeds revealed that polymorphisms in coat colour and pattern in Soay sheep arose as a result of introgression of genetic variants favoured by artificial selection. Because the haplotypes carrying the causative mutations are known to be under natural selection in free-living Soay sheep, the admixture event created an opportunity to observe the outcome of a 'natural laboratory' experiment where ancestral and domesticated genes competed with each other. The haplotype carrying the domesticated light coat colour allele was favoured by natural selection, while the haplotype associated with the domesticated self coat pattern allele was associated with decreased survival. Therefore, we demonstrate that introgression of domesticated alleles into wild populations can provide a novel source of variation capable of generating rapid evolutionary changes.

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.

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.

Australian Parkinson's Genetics Study (APGS): pilot (n=1532).

PURPOSE: Parkinson's disease (PD) is a neurodegenerative disorder associated with progressive disability. While the precise aetiology is unknown, there is evidence of significant genetic and environmental influences on individual risk. The Australian Parkinson's Genetics Study seeks to study genetic and patient-reported data from a large cohort of individuals with PD in Australia to understand the sociodemographic, genetic and environmental basis of PD susceptibility, symptoms and progression. PARTICIPANTS: In the pilot phase reported here, 1819 participants were recruited through assisted mailouts facilitated by Services Australia based on having three or more prescriptions for anti-PD medications in their Pharmaceutical Benefits Scheme records. The average age at the time of the questionnaire was 64±6 years. We collected patient-reported information and sociodemographic variables via an online (93% of the cohort) or paper-based (7%) questionnaire. One thousand five hundred and thirty-two participants (84.2%) met all inclusion criteria, and 1499 provided a DNA sample via traditional post. FINDINGS TO DATE: 65% of participants were men, and 92% identified as being of European descent. A previous traumatic brain injury was reported by 16% of participants and was correlated with a younger age of symptom onset. At the time of the questionnaire, constipation (36% of participants), depression (34%), anxiety (17%), melanoma (16%) and diabetes (10%) were the most reported comorbid conditions. FUTURE PLANS: We plan to recruit sex-matched and age-matched unaffected controls, genotype all participants and collect non-motor symptoms and cognitive function data. Future work will explore the role of genetic and environmental factors in the aetiology of PD susceptibility, onset, symptoms, and progression, including as part of international PD research consortia.

Investigating the shared genetic architecture between multiple sclerosis and inflammatory bowel diseases.

An epidemiological association between multiple sclerosis (MS) and inflammatory bowel disease (IBD) is well established, but whether this reflects a shared genetic aetiology, and whether consistent genetic relationships exist between MS and the two predominant IBD subtypes, ulcerative colitis (UC) and Crohn's disease (CD), remains unclear. Here, we use large-scale genome-wide association study summary data to investigate the shared genetic architecture between MS and IBD overall and UC and CD independently. We find a significantly greater genetic correlation between MS and UC than between MS and CD, and identify three SNPs shared between MS and IBD (rs13428812), UC (rs116555563) and CD (rs13428812, rs9977672) in cross-trait meta-analyses. We find suggestive evidence for a causal effect of MS on UC and IBD using Mendelian randomization, but no or weak and inconsistent evidence for a causal effect of IBD or UC on MS. We observe largely consistent patterns of tissue-specific heritability enrichment for MS and IBDs in lung, spleen, whole blood and small intestine, and identify cell-type-specific enrichment for MS and IBDs in CD4+ T cells in lung and CD8+ cytotoxic T cells in lung and spleen. Our study sheds light on the biological basis of comorbidity between MS and IBD.

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).

Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders.

BACKGROUND: People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer's disease, amyotrophic lateral sclerosis, and Parkinson's disease. RESULTS: We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson's disease (and none with Alzheimer's disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights. CONCLUSIONS: We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.

Analysis of DNA methylation associates the cystine-glutamate antiporter SLC7A11 with risk of Parkinson's disease.

An improved understanding of etiological mechanisms in Parkinson's disease (PD) is urgently needed because the number of affected individuals is projected to increase rapidly as populations age. We present results from a blood-based methylome-wide association study of PD involving meta-analysis of 229 K CpG probes in 1,132 cases and 999 controls from two independent cohorts. We identify two previously unreported epigenome-wide significant associations with PD, including cg06690548 on chromosome 4. We demonstrate that cg06690548 hypermethylation in PD is associated with down-regulation of the SLC7A11 gene and show this is consistent with an environmental exposure, as opposed to medications or genetic factors with effects on DNA methylation or gene expression. These findings are notable because SLC7A11 codes for a cysteine-glutamate anti-porter regulating levels of the antioxidant glutathione, and it is a known target of the environmental neurotoxin ß-methylamino-L-alanine (BMAA). Our study identifies the SLC7A11 gene as a plausible biological target in PD.

Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis.

We conducted DNA methylation association analyses using Illumina 450K data from whole blood for an Australian amyotrophic lateral sclerosis (ALS) case-control cohort (782 cases and 613 controls). Analyses used mixed linear models as implemented in the OSCA software. We found a significantly higher proportion of neutrophils in cases compared to controls which replicated in an independent cohort from the Netherlands (1159 cases and 637 controls). The OSCA MOMENT linear mixed model has been shown in simulations to best account for confounders. When combined in a methylation profile score, the 25 most-associated probes identified by MOMENT significantly classified case-control status in the Netherlands sample (area under the curve, AUC = 0.65, CI95% = [0.62-0.68], p = 8.3 × 10-22). The maximum AUC achieved was 0.69 (CI95% = [0.66-0.71], p = 4.3 × 10-34) when cell-type proportion was included in the predictor.

The genetic relationship between female reproductive traits and six psychiatric disorders.

Female reproductive behaviours have important implications for evolutionary fitness and health of offspring. Here we used the second release of UK Biobank data (N = 220,685) to evaluate the association between five female reproductive traits and polygenic risk scores (PRS) projected from genome-wide association study summary statistics of six psychiatric disorders (N = 429,178). We found that the PRS of attention-deficit/hyperactivity disorder (ADHD) were strongly associated with age at first birth (AFB) (genetic correlation of -0.68 ± 0.03), age at first sexual intercourse (AFS) (-0.56 ± 0.03), number of live births (NLB) (0.36 ± 0.04) and age at menopause (-0.27 ± 0.04). There were also robustly significant associations between the PRS of eating disorder (ED) and AFB (0.35 ± 0.06), ED and AFS (0.19 ± 0.06), major depressive disorder (MDD) and AFB (-0.27 ± 0.07), MDD and AFS (-0.27 ± 0.03) and schizophrenia and AFS (-0.10 ± 0.03). These associations were mostly explained by pleiotropic effects and there was little evidence of causal relationships. Our findings can potentially help improve reproductive health in women, hence better child outcomes. Our findings also lend partial support to the evolutionary hypothesis that causal mutations underlying psychiatric disorders have positive effects on reproductive success.

Examining the Impact of Imputation Errors on Fine-Mapping Using DNA Methylation QTL as a Model Trait.

Genetic variants disrupting DNA methylation at CpG dinucleotides (CpG-SNP) provide a set of known causal variants to serve as models to test fine-mapping methodology. We use 1716 CpG-SNPs to test three fine-mapping approaches (Bayesian imputation-based association mapping, Bayesian sparse linear mixed model, and the J-test), assessing the impact of imputation errors and the choice of reference panel by using both whole-genome sequence (WGS), and genotype array data on the same individuals (n = 1166). The choice of imputation reference panel had a strong effect on imputation accuracy, with the 1000 Genomes Project Phase 3 (1000G) reference panel (n = 2504 from 26 populations) giving a mean nonreference discordance rate between imputed and sequenced genotypes of 3.2% compared to 1.6% when using the Haplotype Reference Consortium (HRC) reference panel (n = 32,470 Europeans). These imputation errors had an impact on whether the CpG-SNP was included in the 95% credible set, with a difference of ∼23% and ∼7% between the WGS and the 1000G and HRC imputed datasets, respectively. All of the fine-mapping methods failed to reach the expected 95% coverage of the CpG-SNP. This is attributed to secondary cis genetic effects that are unable to be statistically separated from the CpG-SNP, and through a masking mechanism where the effect of the methylation disrupting allele at the CpG-SNP is hidden by the effect of a nearby SNP that has strong linkage disequilibrium with the CpG-SNP. The reduced accuracy in fine-mapping a known causal variant in a low-level biological trait with imputed genetic data has implications for the study of higher-order complex traits and disease.