Depression, a leading cause of global disability, arises from a multifaceted combination of genetic and environmental components. This study explores the relationship between major depressive disorder (MDD) polygenic scores (PGS), characteristics and symptoms of depression, and community-shared socioeconomic factors derived from postal code data in a cohort of 12,646 individuals from the Australian Genetics of Depression Study (AGDS). Our findings reveal that people living in areas with relatively higher socioeconomic advantages and education/occupation scores are more likely to report experiencing fewer depressive symptoms during their worst depressive period, as well as fewer number of lifetime episodes. Additionally, participants who reported depression onset later in life tend to currently reside in wealthier areas. Interestingly, no significant interaction between genetic and socioeconomic factors was observed, suggesting their independent contribution to depression outcomes. This research underscores the importance of integrating socioeconomic factors into psychiatric evaluation and care, and points to the critical role of public policy in addressing mental health disparities driven by socioeconomic factors. Future research should aim to further elucidate the causal relationships within these associations and explore the potential for integrated genetic and socioeconomic approaches in mental health interventions.

The mobility of a weed species is a strong determinant of the optimal management strategy, including whether area-wide management will be beneficial. In this paper, we examine the mobility and dispersal distances of flaxleaf fleabane [Conyza bonariensis (L.) Cronquist; syn.: Erigeron bonariensis L.], widely regarded as a highly mobile weed. We sampled individual weeds from two regions and sampled the same sites in the following season to conduct parentage analysis and assess intergenerational dispersal distances. We find high values of FIS across populations consistent with mostly self-fertilization, but also relatively high genotypic diversity, suggesting that outcrossing does occur at low rates. We find evidence for long-distance dispersal (more than 350 km) and detect dispersal distances of up to 71 km and 36 km within each of the two regions using parentage analysis. We also find high spatial genetic structure within the Riverina region, with sites in 2021 genetically very similar to sites in 2020, indicating that local dispersal may be a more important driver of population genetics than long-distance dispersal, perhaps due to the high rates of seed production and self-fertilization. Glyphosate resistance was not spatially structured in C. bonariensis in these regions, highlighting the role of movement, and significant proportions of susceptible plants were found in both regions. The high levels of mobility, including over potentially long distances, indicate that the value of control and preventing weed seed set is likely to extend beyond the farm and offer “area-wide” benefit.

Although financial stressors are implicated as risk factors for suicidal behavior, these associations might be confounded by other factors. Furthermore, a move toward high-risk subgroup definition is necessary. The authors used Swedish national registry data to examine the associations between receipt of social welfare, unemployment benefits, or early retirement (N = 627,745−2,260,753) with suicidal behavior in Cox proportional hazards models. They applied co-relative models to improve causal inference, and examined interactions with aggregate genetic risk for suicidality. All three exposures were associated with elevated suicidal behavior risk. Initial hazard ratios for suicide attempt ranged from 1.37−3.86, were similar for suicide death, and declined after controlling for psychopathology and time elapsed after exposure. Age at registration differentially impacted risk of suicidal behavior. Aggregate genetic liability for suicidality was associated with risk, but its effect was not moderated by financial stress. Financial stressors are associated with suicidal behavior risk even after controlling for psychopathology. Associations are attributable in part to familial confounding, though a potentially causal pathway was observed in most cases. Suicidality risk varied as a function of sex and age at exposure; these findings could be used to identify subgroups at high risk who warrant targeted prevention.

Major depressive disorder (MDD) and coronary heart disease (CHD) can both cause significant morbidity and mortality. The association of MDD and CHD has long been identified, but the mechanisms still require further investigation. Seven mRNA microarray datasets containing samples from patients with MDD and CHD were downloaded from Gene Expression Omnibus. Combined matrixes of MDD and CAD were constructed for subsequent analysis. Differentially expressed genes (DEGs) were identified. Functional enrichment analyses based on shared DEGs were conducted to identify pivotal pathways. A protein-protein network was also applied to further investigate the functional interaction. Results showed that 24 overlapping genes were identified. Enrichment analysis indicated that the shared genes are mainly associated with immune function and ribosome biogenesis. The functional interactions of shared genes were also demonstrated by PPI network analysis. In addition, three hub genes including MMP9, S100A8, and RETN were identified. Our results indicate that MDD and CHD have a genetic association. Genes relevant to immune function, especially IL-17 signalling pathway may be involved in the pathogenesis of MDD and CHD.

Autism spectrum disorder is defined by the presence of sustained problems in areas of social cognition and social understanding alongside repetitive and/or restricted patterns of behaviour. Behavioural presentations and developmental trajectories in autism are highly heterogeneous. For most, characteristics variably continue across the lifespan, and, for many, they overlap with numerous overrepresented comorbid combinations spanning behavioural, psychiatric and somatic domains. The current autism diagnostic systems (DSM-5, ICD-11) reflect this heterogeneity, focusing on discerning different assistance needs and symptom severity combinations. An emerging view on the pluralisation of autism – ‘the autisms’ – based on different severity levels and different developmental trajectories is gaining popularity, bolstered by the introduction of the grouping ‘profound autism’ and observations of non-persistence of autism for some. We advance the case for expanding the definition of the plural autisms based also on the numerous different aetiological routes that can lead to autism. Various genetic conditions, susceptibility to infectious agents, non-infectious environmental exposures and immune-mediated occurrences have all been observed to culminate in a diagnosis of autism. As a triad, aetiology, presentation intensity and developmental trajectory offer new ways to classify the autisms, with potentially important implications for research and practice.

Do we owe anything to our genetic relatives qua genetic relatives? The philosophical literature has primarily addressed this question in the context of procreation. But genetic matching databases raise the question of whether we owe anything to previously unknown genetic relatives. This article argues that influential philosophical arguments regarding moral claims to know one’s genetic origins (sometimes referred to as a ‘right to know’) in the context of gamete donation have implications for a broader set of claims. First, these arguments imply more than a claim to know the identity of a genetic relative; the interests which they invoke can only be satisfied through a relationship. Second, the scope of the claims is broader than tends to be acknowledged: even if procreators have special obligations towards their offspring, these arguments imply that weighty moral claims can be made against other genetic relatives in many different contexts.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with significant social, communicative, and behavioral challenges, and its prevalence is increasing globally at an alarming rate. Children with ASD often have nutritional imbalances, and multiple micronutrient deficiencies. Among these, zinc (Zn2+) deficiency is prominent and has gained extensive scientific interest over the past few years. Zn2+ supports numerous proteins, including enzymes and transcription factors, and controls neurogenesis and cell differentiation. It modulates synaptic transmission and plasticity by binding to receptors, ion channels, and transporters. These interactions are crucial, as changes in these processes may contribute to cognitive and behavioral abnormalities in neurodevelopmental disorders, including ASD. Notably, mutations in genes linked to ASD result in Zn2+ dyshomeostasis, altering pivotal biological processes. In addition, Zn2+ promotes gut health by maintaining gut wall integrity, preventing inflammation and leaky gut, preventing translocation of gut bacteria and their metabolites into systemic circulation, and supporting cognitive processes via the gut–brain axis. Zn2+ deficiency during pregnancy alters gut microbiota composition, induces pro-inflammatory cytokine production, may affect neuronal functioning, and is associated with ASD etiology in offspring, as well as the exacerbation of autistic traits in genetically predisposed children. This review focuses on Zn2+ dyshomeostasis, discussing various Zn2+-dependent dysfunctions underlying distinct autistic phenotypes and describing recent progress in the neurobiology of individuals with ASD and animal models.

This paper reports the methods and preliminary findings of Germina, an ongoing cohort study to identify biomarkers and trajectories of executive functions and language development in the first 3 years of life. 557 mother-infant dyads (mean age of mothers 33.7 years, 65.2% white, 48.7% male infants) have undergone baseline and are currently collecting data for other timepoints. A linear regression was used to predict baseline Bayley-III using scores derived from data-driven sparse partial least squares utilizing a multiple holdout framework of 15 domains. Significant associations were found between socioeconomic/demographic characteristics (B = 0.29), epigenetics (B = 0.11), EEG theta (B = 0.14) and beta activity (B = 0.11), and microbiome functional pathways (B = 0.08) domains, and infant development measured by the Bayley-III at T1, suggesting potential interventions to prevent impairments.

Low birthweight is a risk factor for type 2 diabetes. We hypothesised that differential associations between birthweight and clinical characteristics in persons with and without type 2 diabetes may provide novel insights into the role of birthweight in type 2 diabetes and its progression. We analysed UK Biobank data from 9,442 persons with and 254,446 without type 2 diabetes. Associations between birthweight, clinical traits, and genetic predisposition were assessed using adjusted linear and logistic regression, comparing the lowest and highest 25% of birthweight to the middle 50%. Each kg increase in birthweight was associated with higher BMI, waist, and hip circumference, with stronger effects in persons with versus without type 2 diabetes (BMI: 0.74 [0.58, 0.90] vs. 0.21 [0.18, 0.24] kg/m2; waist: 2.15 [1.78, 2.52] vs. 1.04 [0.98, 1.09] cm; hip: 1.65 [1.33, 1.97] vs. 1.04 [1.04, 1.09] cm). Family history of diabetes was associated with higher birthweight regardless of diabetes status, albeit with a twofold higher effect estimate in type 2 diabetes. Low birthweight was further associated with prior myocardial infarction regardless of type 2 diabetes status (OR 1.33 [95% CI 1.11, 1.60] for type 2 diabetes; 1.23 [95% CI 1.13, 1.33] without), and hypertension (OR 1.25 [1.23, 1.28] and stroke 1.24 [1.14, 1.34]) only among persons without type 2 diabetes. Differential associations between birthweight and cardiometabolic traits in persons with and without type 2 diabetes illuminate potential causal inferences reflecting the roles of pre- and postnatal environmental versus genetic aetiologies and disease mechanisms.