Leanne Wallace

Background: Endometriosis is a complex condition with substantial diagnostic delays and health burden. This study aimed to develop and evaluate a polygenic risk score (PRS) for endometriosis and compare its predictive utility with, and alongside, family history (FH). Methods: Genetic effect estimates were derived from a large genome-wide association study meta-analysis and applied to an independent Australian cohort (n≈3,400) with linked survey and health data. PRS was calculated using clumping/thresholding and Bayesian (SBayesRC) approaches. Predictive performance was assessed using logistic regression and area under the receiver operating characteristic curve (AUC). Findings: PRS was associated with endometriosis risk, with the best-performing model achieving modest discrimination (AUC≈0.61). Individuals in the highest PRS decile had increased risk compared with the lowest decile. FH was a stronger predictor, with 3–5-fold higher odds of disease among those with an affected relative. PRS and FH were weakly correlated and independently associated with endometriosis. Combining them improved prediction (AUC up to ~0.72). Interpretation: PRS and FH capture complementary aspects of endometriosis risk. While FH remains a robust and clinically accessible predictor, PRS provides additional genetic information that enhances risk stratification. Integrating these measures may support improved risk assessment and earlier diagnosis.

Objectives Sleep and circadian rhythm disturbances (SCRDs) are proposed to be pathophysiological mechanisms underlying some cases of depressive and bipolar (mood) disorders. An unresolved clinical question is whether sleep and circadian based therapies are effective antidepressants for young adults (18-30-years) with a mood disorder. Method & analysis MELODY (Melatonin for Depression in Youth) is an investigator-initiated, single-centre, randomised, placebo-controlled, phase 3 clinical trial. The trial is testing whether 12 weeks of adjunctive melatonin or digital cognitive behavioural therapy for insomnia (dCBT-I) are more effective than pill placebo at reducing depressive symptoms in 660 young people aged 18-30-years with a Structured Clinical Interview for DSM-5 (SCID-5) diagnosis of Major Depressive Disorder or Bipolar Disorder type II, moderate-to-severe depressive symptoms, and significant sleep or sleep-wake complaints. The week 12 primary outcome is depressive symptoms (Quick Inventory of Depressive Symptomatology, Adolescent version). Secondary outcomes include partial remission of the Major Depressive Episode (SCID-5) and change in other mental health symptoms, sleep, functioning, or quality of life. A subset of participants will undergo in-home assessment of sleep physiology (Sleep Profiler^TM) and in-lab assessment of circadian rhythms (dim-light melatonin onset) to examine biological changes. A 6-month follow-up will explore durability of treatment effects. Mediation analyses will test whether sleep or circadian rhythm changes play a causal role in antidepressant effects. Ethics & dissemination MELODY has been reviewed and approved by the Human Research Ethics Committee (HREC) of the Sydney Local Health District (HREC Approval Number: X23-0450, Protocol version: 1.4, 7/7/25). The findings of the MELODY trial will be disseminated into the scientific and clinical communities via refereed publications, talks, and other professional and media outlets. The Brain and Mind Centre’s Lived Experience Working Group (LEWG) will contribute to dissemination of MELODY’s findings via youth-friendly methods (e.g., social media videos, explainers). Trial registration number ACTRN12624000017527 Strengths and limitations of the study MELODY is the first trial to be well-powered (>80%) to detect the summary effect size reported in the only meta-analysis on the effect of melatonin on depressive symptoms in people with mood disorders (standardised mean difference=0.37); MELODY will therefore be the first definitive trial on the topic. As melatonin and digital cognitive behavioural therapy for insomnia (dCBT-I) are scalable treatments, the success of either arm compared to placebo is likely to lead to real-world clinical impacts. By recruiting a sample with a spectrum of sleep and sleep-wake complaints, post-hoc analyses may be able to identify profiles or subgroups that can guide stratified trials or guidelines for melatonin and dCBT-I in young people with mood disorders. While we expect participants in the dCBT-I arm will learn sustainable skills to improve their sleep, sleep-wake cycles, and circadian rhythms, the likelihood of durable gains from melatonin is unclear; this will be explored at 6-month follow-up. This study adopts a primarily biomedical and clinical approach to the understanding and treatment of mood disorders and therefore does not encompass all perspectives on mood disorders (e.g., social, cultural).

Background: Amyotrophic lateral sclerosis (ALS), the most predominant form of Motor Neuron Disease (MND), is a progressive and fatal neurodegenerative condition that spreads throughout the neuromotor system by afflicting upper and lower motor neurons. Lower motor neurons project from the central nervous system and innervate muscle fibres at motor endplates, which degrade over the course of the disease leading to muscle weakness. The direction of neurodegeration from or to the point of neuromuscular junctions and the role of muscle itself in pathogenesis has continued to be a topic of debate in ALS research. Methods: To assess the variation in gene expression between affected and nonaffected muscle tissue that might lead to this local degeneration of motor units, we generated RNA-seq skeletal muscle transcriptomes from 28 MND cases and 18 healthy controls and conducted differential expression analyses on gene-level counts, as well as an isoform switching analysis on isoform-level counts. Results: We identified 52 differentially-expressed genes (Benjamini-Hochberg-adjusted p < 0.05) within this comparison, including 38 protein coding, 9 long non-coding RNA, and 5 pseudogenes. Of protein-coding genes, 31 were upregulated in cases including with notable genes including the collagenic COL25A1 ( p = 3.1 × 10 ⁻¹⁰ ), SAA1 which is released in response to tissue injury ( p = 3.6 × 10 ⁻⁵ ) as well as others of the SAA family, and the actin-encoding ACTC1 ( p = 2.3 × 10 ⁻⁵ ). Additionally, we identified 17 genes which exhibited a functional isoform switch with likely functional consequences between cases and controls. Conclusions: Our analyses provide evidence of increased tissue generation in MND cases, which likely serve to compensate for the degeneration of motor units and skeletal muscle.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with an estimated heritability between 40 and 50%. DNA methylation patterns can serve as proxies of (past) exposures and disease progression, as well as providing a potential mechanism that mediates genetic or environmental risk. Here, we present a blood-based epigenome-wide association study meta-analysis in 9706 samples passing stringent quality control (6763 patients, 2943 controls). We identified a total of 45 differentially methylated positions (DMPs) annotated to 42 genes, which are enriched for pathways and traits related to metabolism, cholesterol biosynthesis, and immunity. We then tested 39 DNA methylation–based proxies of putative ALS risk factors and found that high-density lipoprotein cholesterol, body mass index, white blood cell proportions, and alcohol intake were independently associated with ALS. Integration of these results with our latest genome-wide association study showed that cholesterol biosynthesis was potentially causally related to ALS. Last, DNA methylation at several DMPs and blood cell proportion estimates derived from DNA methylation data were associated with survival rate in patients, suggesting that they might represent indicators of underlying disease processes potentially amenable to therapeutic interventions.

Amyotrophic Lateral Sclerosis (ALS) is recognised to be a complex neurodegenerative disease involving both genetic and non-genetic risk factors. The underlying causes and risk factors for the majority of cases remain unknown; however, ever-larger genetic data studies and methodologies promise an enhanced understanding. Recent analyses using published summary statistics from the largest ALS genome-wide association study (GWAS) (20,806 ALS cases and 59,804 healthy controls) identified that schizophrenia (SCZ), cognitive performance (CP) and educational attainment (EA) related traits were genetically correlated with ALS. To provide additional evidence for these correlations, we built single and multi-trait genetic predictors using GWAS summary statistics for ALS and these traits, (SCZ, CP, EA) in an independent Australian cohort (846 ALS cases and 665 healthy controls). We compared methods for generating the risk predictors and found that the combination of traits improved the prediction (Nagelkerke-R²) of the case–control logistic regression. The combination of ALS, SCZ, CP, and EA, using the SBayesR predictor method gave the highest prediction (Nagelkerke-R²) of 0.027 (P value = 4.6 × 10⁻⁸), with the odds-ratio for estimated disease risk between the highest and lowest deciles of individuals being 3.15 (95% CI 1.96–5.05). These results support the genetic correlation between ALS, SCZ, CP and EA providing a better understanding of the complexity of ALS.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with an estimated heritability of around 50%. DNA methylation patterns can serve as biomarkers of (past) exposures and disease progression, as well as providing a potential mechanism that mediates genetic or environmental risk. Here, we present a blood-based epigenome-wide association study (EWAS) meta-analysis in 10,462 samples (7,344 ALS patients and 3,118 controls), representing the largest case-control study of DNA methylation for any disease to date. We identified a total of 45 differentially methylated positions (DMPs) annotated to 42 genes, which are enriched for pathways and traits related to metabolism, cholesterol biosynthesis, and immunity. We show that DNA-methylation-based proxies for HDL-cholesterol, BMI, white blood cell (WBC) proportions and alcohol intake were independently associated with ALS. Integration of these results with our latest GWAS showed that cholesterol biosynthesis was causally related to ALS. Finally, we found that DNA methylation levels at several DMPs and blood cell proportion estimates derived from DNA methylation data, are associated with survival rate in patients, and could represent indicators of underlying disease processes.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a life-time risk of 1 in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry GWAS in ALS including 29,612 ALS patients and 122,656 controls which identified 15 risk loci in ALS. When combined with 8,953 whole-genome sequenced individuals (6,538 ALS patients, 2,415 controls) and the largest cortex-derived eQTL dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, repeat expansions or regulatory effects. ALS associated risk loci were shared with multiple traits within the neurodegenerative spectrum, but with distinct enrichment patterns across brain regions and cell-types. Across environmental and life-style risk factors obtained from literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. All ALS associated signals combined reveal a role for perturbations in vesicle mediated transport and autophagy, and provide evidence for cell-autonomous disease initiation in glutamatergic neurons.

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).

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, CI_95% = [0.62–0.68], p = 8.3 × 10⁻²²). The maximum AUC achieved was 0.69 (CI_95% = [0.66–0.71], p = 4.3 × 10⁻³⁴) when cell-type proportion was included in the predictor.