The role of loneliness and social isolation in mediating the relationship between childhood maltreatment and schizophrenia: A genetically informed approach.

Observational studies have found loneliness and social isolation to mediate the relationship between childhood maltreatment and schizophrenia. Limitations with observational studies (e.g., confounding and reverse causation), however, have meant the robustness of these relationships has thus far not been explored. To address this gap, the current study utilized genomic structural equation modeling (genomic SEM) and Mendelian randomization (MR) to perform a genetic mediation analysis between childhood maltreatment, loneliness/isolation, and schizophrenia, using summary statistics from three genome-wide association studies (sample sizes 105,318-487,647). While we observed a putative effect of both childhood maltreatment (inverse variance weighted OR = 3.44 per standard deviation increase, 95% confidence interval [CI] [1.66-7.13], p < .001) and loneliness/isolation (OR = 2.98, 95% CI [1.37-6.46], p = .006) on schizophrenia, our hypothesis that loneliness/isolation would mediate the relationship between childhood maltreatment and schizophrenia was not supported (genomic SEM indirect effect = -0.05, SE = 0.05, p = .255; MR indirect effect = 0.10, SE = 0.11, p = .369). Furthermore, reverse mediation analysis indicated that the effect may be in the opposite direction (genomic SEM indirect effect = 0.11, SE = 0.02, p < .001; MR indirect effect = 0.01, SE = 0.00, p < .001), accounting for 20.3%-28.9% of the total effect. The current results suggest that intervening in loneliness/isolation in individuals with a history of childhood maltreatment is unlikely to reduce schizophrenia risk. On the contrary, targeting loneliness/isolation in individuals with a genetic predisposition toward schizophrenia may diminish childhood maltreatment risk. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The role of lifestyle factors in the association between early-life stress and adolescent psycho-physical health: Moderation analysis in two European birth cohorts.

OBJECTIVE: Early-life stress (ELS) is an established risk factor for a host of adult mental and physical health problems, including both depression and obesity. Recent studies additionally showed that ELS was associated with an increased risk of comorbidity between mental and physical health problems, already in adolescence. Healthy lifestyle factors, including physical activity, sleep and diet have also been robustly linked to both emotional and physical wellbeing. However, it is yet unclear whether these lifestyle factors may moderate the association between ELS and psycho-physical comorbidity. METHODS: We investigated whether (a) participation in physical activity, (b) sleep duration, and (c) adherence to a Mediterranean diet, moderated the relationship between cumulative ELS exposure over the first 10 years of life and psycho-physical comorbidity at the age of 13.5 years. Analyses were conducted in 2022-2023, using data from two large adolescent samples based in the UK (ALSPAC; n = 8428) and The Netherlands (Generation R; n = 4268). RESULTS: Exposure to ELS was significantly associated with a higher risk of developing comorbidity, however this association was not modified by any of the three lifestyle factors investigated. Only physical activity was significantly associated with a reduced risk of comorbidity in one cohort (ORALSPAC [95%CI] = 0.73 [0.59;0.89]). CONCLUSIONS: In conclusion, while we found some evidence that more frequent physical activity may be associated with a reduction in psycho-physical comorbidity, we did not find evidence in support of the hypothesised moderation effects. However, more research is warranted to examine how these associations may evolve over time.

Effects of Pre- and Postnatal Early-Life Stress on Internalizing, Adiposity, and Their Comorbidity.

OBJECTIVE: Depression and obesity are 2 highly prevalent and often comorbid conditions. Exposure to early-life stress (ELS) has been associated with both depression and obesity in adulthood, as well as their preclinical manifestations during development. However, it remains unclear whether (1) associations differ depending on the timing of stress exposure (prenatal vs postnatal), and whether (2) ELS is a shared risk factor underlying the comorbidity between the 2 conditions. METHOD: Leveraging data from 2 large population-based birth cohorts (ALSPAC: n = 8,428 [52% male participants]; Generation R: n = 4,268 [48% male participants]), we constructed comprehensive cumulative measures of prenatal (in utero) and postnatal (from birth to 10 years) ELS. At age 13.5 years, we assessed the following: internalizing symptoms (using maternal reports); fat mass percentage (using dual-energy X-ray absorptiometry); and their comorbidity, defined as the co-occurrence of high internalizing and high adiposity. RESULTS: Both prenatal (total effect [95% CI] = 0.20 [0.16; 0.22]) and postnatal stress (ß [95%CI] = 0.22 [0.17; 0.25]) were associated with higher internalizing symptoms, with evidence of a more prominent role of postnatal stress. A weaker association (driven primarily by prenatal stress) was observed between stress and adiposity (prenatal: 0.07 [0.05; 0.09]; postnatal: 0.04 [0.01; 0.07]). Both prenatal (odds ratio [95%CI] = 1.70 [1.47; 1.97]) and postnatal (1.87 [1.61; 2.17]) stress were associated with an increased risk of developing comorbidity. CONCLUSION: We found evidence of timing and shared causal effects of ELS on psycho-cardiometabolic health in adolescence; however, future research is warranted to clarify how these associations may unfold over time. DIVERSITY & INCLUSION STATEMENT: We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. We actively worked to promote sex and gender balance in our author group.

Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study.

Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting that brain structure is often 'older' than expected at a given chronological age. Whether advanced brain age is linked to genetic liability for schizophrenia remains unclear. In this pre-registered secondary data analysis, we utilised a recall-by-genotype approach applied to a population-based subsample from the Avon Longitudinal Study of Parents and Children to assess brain age differences between young adults aged 21-24 years with relatively high (n = 96) and low (n = 93) polygenic risk for schizophrenia (SCZ-PRS). A global index of brain age (or brain-predicted age) was estimated using a publicly available machine learning model previously trained on a combination of region-wise gray-matter measures, including cortical thickness, surface area and subcortical volumes derived from T1-weighted magnetic resonance imaging (MRI) scans. We found no difference in mean brain-PAD (the difference between brain-predicted age and chronological age) between the high- and low-SCZ-PRS groups, controlling for the effects of sex and age at time of scanning (b = -.21; 95% CI -2.00, 1.58; p = .82; Cohen's d = -.034; partial R2 = .00029). These findings do not support an association between SCZ-PRS and brain-PAD based on global age-related structural brain patterns, suggesting that brain age may not be a vulnerability marker of common genetic risk for SCZ. Future studies with larger samples and multimodal brain age measures could further investigate global or localised effects of SCZ-PRS.

A multivariate genome-wide association study of psycho-cardiometabolic multimorbidity.

Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74-2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways.

A systematic review of neuroimaging epigenetic research: calling for an increased focus on development.

Epigenetic mechanisms, such as DNA methylation (DNAm), have gained increasing attention as potential biomarkers and mechanisms underlying risk for neurodevelopmental, psychiatric and other brain-based disorders. Yet, surprisingly little is known about the extent to which DNAm is linked to individual differences in the brain itself, and how these associations may unfold across development - a time of life when many of these disorders emerge. Here, we systematically review evidence from the nascent field of Neuroimaging Epigenetics, combining structural or functional neuroimaging measures with DNAm, and the extent to which the developmental period (birth to adolescence) is represented in these studies. We identified 111 articles published between 2011-2021, out of which only a minority (21%) included samples under 18 years of age. Most studies were cross-sectional (85%), employed a candidate-gene approach (67%), and examined DNAm-brain associations in the context of health and behavioral outcomes (75%). Nearly half incorporated genetic data, and a fourth investigated environmental influences. Overall, studies support a link between peripheral DNAm and brain imaging measures, but there is little consistency in specific findings and it remains unclear whether DNAm markers present a cause, correlate or consequence of brain alterations. Overall, there is large heterogeneity in sample characteristics, peripheral tissue and brain outcome examined as well as the methods used. Sample sizes were generally low to moderate (median nall = 98, ndevelopmental = 80), and attempts at replication or meta-analysis were rare. Based on the strengths and weaknesses of existing studies, we propose three recommendations on how advance the field of Neuroimaging Epigenetics. We advocate for: (1) a greater focus on developmentally oriented research (i.e. pre-birth to adolescence); (2) the analysis of large, prospective, pediatric cohorts with repeated measures of DNAm and imaging to assess directionality; and (3) collaborative, interdisciplinary science to identify robust signals, triangulate findings and enhance translational potential.