A biologically-informed polygenic score identifies endophenotypes and clinical conditions associated with the insulin receptor function on specific brain regions

Examining the associations between microglia genetic capacity, early life exposures and white matter development at the level of the individual

There are inter-individual differences in susceptibility to the influence of early life experiences for which the underlying neurobiological mechanisms are poorly understood. Microglia play a role in environmental surveillance and may influence individual susceptibility to environmental factors. As an index of neurodevelopment, we estimated individual slopes of mean white matter fractional anisotropy (WM-FA) across three time-points (age 4.5, 6.0, and 7.5 years) for 351 participants. Individual variation in microglia reactivity was derived from an expression-based polygenic score(ePGS) comprised of Single Nucleotide Polymorphisms (SNPs) functionally related to the expression of microglia-enriched genes.A higher ePGS denotes an increased genetic capacity for the expression of microglia-related genes, and thus may confer a greater capacity to respond to the early environment and to influence brain development. We hypothesized that this ePGS would associate with the WM-FA index of neurodevelopment and moderate the influence of early environmental factors.Our findings show sex dependency, where a significant association between WM-FA and microglia ePGS was only obtained for females.We then examined associations with perinatal factors known to decrease (optimal birth outcomes and familial conditions) or increase (systemic inflammation) the risk for later mental health problems.In females, individuals with high microglia ePGS showed a negative association between systemic inflammation and WM-FA and a positive association between more advantageous environmental conditions and WM-FA. The microglia ePGS in females thus accounted for variations in the influence of the quality of the early environment on WM-FA.Finally, WM-FA slopes mediated the association of microglia ePGS with interpersonal problems and social hostility in females. Our findings suggest the genetic capacity for microglia function as a potential factor underlying differential susceptibility to early life exposuresthrough influences on neurodevelopment.

The brain insulin receptor gene network and associations with frailty index

OBJECTIVE

To investigate longitudinal associations between variations in the co-expression-based brain insulin receptor polygenic risk score and frailty, as well as change in frailty across follow-up.

METHODS

This longitudinal study included 1605 participants from the Helsinki Birth Cohort Study. Biologically informed expression-based polygenic risk scores for the insulin receptor gene network, which measure genetic variation in the function of the insulin receptor, were calculated for the hippocampal (hePRS-IR) and the mesocorticolimbic (mePRS-IR) regions. Frailty was assessed in at baseline in 2001-2004, 2011-2013 and 2017-2018 by applying a deficit accumulation-based frailty index. Analyses were carried out by applying linear mixed models and logistical regression models adjusted for adult socioeconomic status, birthweight, smoking and their interactions with age.

RESULTS

The FI levels of women were 1.19%-points (95% CI 0.12-2.26, P = 0.029) higher than in men. Both categorical and continuous hePRS-IR in women were associated with higher FI levels than in men at baseline (P < 0.05). In women with high hePRS-IR, the rate of change was steeper with increasing age compared to those with low or moderate hePRS-IR (P < 0.05). No associations were detected between mePRS-IR and frailty at baseline, nor between mePRS-IR and the increase in mean FI levels per year in either sex (P > 0.43).

CONCLUSIONS

Higher variation in the function of the insulin receptor gene network in the hippocampus is associated with increasing frailty in women. This could potentially offer novel targets for future drug development aimed at frailty and ageing.

Plant-based dietary patterns and genetic susceptibility to obesity in the CARTaGENE cohort

OBJECTIVE

The study's objective was to examine whether adherence to three plant-based dietary indices (PDIs) mediated or moderated genetic susceptibility to obesity.

METHODS

Baseline participants were 7037 adults (57% women, aged 55.6 ± 7.7 years) from the CARTaGENE cohort of Quebec adults. Two polygenic risk scores for BMI (PRS-BMI), 92 single-nucleotide polymorphisms and 2 million single-nucleotide polymorphisms, and three plant-based scores were calculated (overall, healthy, and unhealthy). Follow-up participants were 2258 adults with data on obesity outcomes, measured 6 years later. General linear models were used to examine the relationships between PRSs and PDI scores on obesity outcomes. Causal mediation analyses were conducted to assess mediation and interaction models.

RESULTS

The overall- and healthy-PDIs and PRSs were significantly associated with obesity outcomes. Adherence to PDIs did not mediate or moderate genetic susceptibility to obesity. Associations between PRSs and obesity outcomes were partly mediated by meat intake cross-sectionally and whole grains intake among males both cross-sectionally and longitudinally. Higher meat intake had a positive association with obesity outcomes, whereas higher whole grains intake had an inverse association.

CONCLUSIONS

These findings suggest that components of a plant-based diet and a shift away from animal products, specifically meat, might be beneficial for nutrition interventions, particularly among individuals with higher genetic risk of obesity.

How are overweight and obesity associated with reinforcement learning deficits? A systematic review

Reinforcement learning (RL) refers to the ability to learn stimulus-response or response-outcome associations relevant to the acquisition of behavioral repertoire and adaptation to the environment. Research data from correlational and case-control studies have shown that obesity is associated with impairments in RL. The aim of the present study was to systematically review how obesity and overweight are associated with RL performance. More specifically, the relationship between high body mass index (BMI) and task performance was explored through the analysis of specific RL processes associated with different physiological, computational, and behavioral manifestations. Our systematic analyses indicate that obesity might be associated with impairments in the use of aversive outcomes to change ongoing behavior, as revealed by results involving instrumental negative reinforcement and extinction/reversal learning, but further research needs to be conducted to confirm this association. Hypotheses regarding how obesity might be associated with altered RL were discussed.

Hofbauer cell function in the term placenta associates with adult cardiovascular and depressive outcomes

Pathological placental inflammation increases the risk for several adult disorders, but these mediators are also expressed under homeostatic conditions, where their contribution to adult health outcomes is unknown. Here we define an inflammation-related expression signature, primarily expressed in Hofbauer cells of the term placenta and use expression quantitative trait loci to create a polygenic score (PGS) predictive of its expression. Using this PGS in the UK Biobank we conduct a phenome-wide association study, followed by Mendelian randomization and identify protective, sex-dependent effects of the placental module on cardiovascular and depressive outcomes. Genes differentially regulated by intra-amniotic infection and preterm birth are over-represented within the module. We also identify aspirin as a putative modulator of this inflammation-related signature. Our data support a model where disruption of placental Hofbauer cell function, due to preterm birth or prenatal infection, contributes to the increased risk of depression and cardiovascular disease observed in these individuals.

Brain insulin signaling as a potential mediator of early life adversity effects on physical and mental health

In numerous brain structures, insulin signaling modulates the homeostatic processes, sensitivity to reward pathways, executive function, memory, and cognition. Through human studies and animal models, mounting evidence implicates central insulin signaling in the metabolic, physiological, and psychological consequences of early life adversity. In this review, we describe the consequences of early life adversity in the brain where insulin signaling is a key factor and how insulin may moderate the effects of adversity on psychiatric and cardio-metabolic health outcomes. Further understanding of how early life adversity and insulin signaling impact specific brain regions and mental and physical health outcomes will assist in prevention, diagnosis, and potential intervention following early life adversity.

Serotonin transporter (5-HTT) gene network moderates the impact of prenatal maternal adversity on orbitofrontal cortical thickness in middle childhood

In utero, the developing brain is highly susceptible to the environment. For example, adverse maternal experiences during the prenatal period are associated with outcomes such as altered neurodevelopment and emotion dysregulation. Yet, the underlying biological mechanisms remain unclear. Here, we investigate whether the function of a network of genes co-expressed with the serotonin transporter in the amygdala moderates the impact of prenatal maternal adversity on the structure of the orbitofrontal cortex (OFC) in middle childhood and/or the degree of temperamental inhibition exhibited in toddlerhood. T1-weighted structural MRI scans were acquired from children aged 6-12 years. A cumulative maternal adversity score was used to conceptualize prenatal adversity and a co-expression based polygenic risk score (ePRS) was generated. Behavioural inhibition at 18 months was assessed using the Early Childhood Behaviour Questionnaire (ECBQ). Our results indicate that in the presence of a low functioning serotonin transporter gene network in the amygdala, higher levels of prenatal adversity are associated with greater right OFC thickness at 6-12 years old. The interaction also predicts temperamental inhibition at 18 months. Ultimately, we identified important biological processes and structural modifications that may underlie the link between early adversity and future deviations in cognitive, behavioural, and emotional development.

A biologically informed polygenic score of neuronal plasticity moderates the association between cognitive aptitudes and cortical thickness in adolescents

Although many studies of the adolescent brain identified positive associations between cognitive abilities and cortical thickness, little is known about mechanisms underlying such brain-behavior relationships. With experience-induced plasticity playing an important role in shaping the cerebral cortex throughout life, it is likely that some of the inter-individual variations in cortical thickness could be explained by genetic variations in relevant molecular processes, as indexed by a polygenic score of neuronal plasticity (PGS-NP). Here, we studied associations between PGS-NP, cognitive abilities, and thickness of the cerebral cortex, estimated from magnetic resonance images, in the Saguenay Youth Study (SYS, 533 females, 496 males: age=15.0 ± 1.8 years of age; cross-sectional), and the IMAGEN Study (566 females, 556 males; between 14 and 19 years; longitudinal). Using Gene Ontology, we first identified 199 genes implicated in neuronal plasticity, which mapped to 155,600 single nucleotide polymorphisms (SNPs). Second, we estimated their effect sizes from an educational attainment meta-GWAS to build a PGS-NP. Third, we examined a possible moderating role of PGS-NP in the relationship between performance intelligence quotient (PIQ), and its subtests, and the thickness of 34 cortical regions. In SYS, we observed a significant interaction between PGS-NP and object assembly vis-à-vis thickness in male adolescents (p = 0.026). A median-split analysis showed that, in males with a 'high' PGS-NP, stronger associations between object assembly and thickness were found in regions with larger age-related changes in thickness (r = 0.55, p = 0.00075). Although the interaction between PIQ and PGS-NP was non-significant (p = 0.064), we performed a similar median-split analysis. Again, in the high PGS-NP males, positive associations between PIQ and thickness were observed in regions with larger age-related changes in thickness (r = 0.40, p = 0.018). In the IMAGEN cohort, we did not replicate the first set of results (interaction between PGS-NP and cognitive abilities via-a-vis cortical thickness) while we did observe the same relationship between the brain-behaviour relationship and (longitudinal) changes in cortical thickness (Matrix reasoning: r = 0.63, p = 6.5e-05). No statistically significant results were observed in female adolescents in either cohort. Overall, these cross-sectional and longitudinal results suggest that molecular mechanisms involved in neuronal plasticity may contribute to inter-individual variations of cortical thickness related to cognitive abilities during adolescence in a sex-specific manner.

Examining the biological mechanisms of human mental disorders resulting from gene-environment interdependence using novel functional genomic approaches

We explore how functional genomics approaches that integrate datasets from human and non-human model systems can improve our understanding of the effect of gene-environment interplay on the risk for mental disorders. We start by briefly defining the G-E paradigm and its challenges and then discuss the different levels of regulation of gene expression and the corresponding data existing in humans (genome wide genotyping, transcriptomics, DNA methylation, chromatin modifications, chromosome conformational changes, non-coding RNAs, proteomics and metabolomics), discussing novel approaches to the application of these data in the study of the origins of mental health. Finally, we discuss the multilevel integration of diverse types of data. Advance in the use of functional genomics in the context of a G-E perspective improves the detection of vulnerabilities, informing the development of preventive and therapeutic interventions.

Independent role of Alzheimer's disease genetics and C-reactive protein on cognitive ability in aging

Apolipoprotein E (APOE) ε4, the strongest genetic risk factor for late onset Alzheimer's disease (LOAD), has been associated with cognitive decline independent from AD pathology, but the role for other LOAD risk genes in normal cognitive aging is less studied. We examined the effect of APOE ε4 and several different polygenic risk scores (PRS) for LOAD on cognitive level and decline in aging, using longitudinal data from the UK Biobank. While PRS-LOAD including all variants (except APOE) predicted cognitive level, APOE ε4 and PRS-LOAD based on 17 non-APOE gene variants with strong association to AD (p < 5e-8) predicted age-related decline in verbal numeric reasoning. The effect on decline were partly driven by 4 variants involved in the immune system. Those variants also predicted serum levels of the inflammatory marker C-reactive protein (CRP), but CRP did not mediate the effect on decline. Those findings suggest genetic variations in immune functions play a role in aspects of cognitive aging that may be independent of LOAD pathology as well as systemic inflammation measured by CRP.

Hippocampus Insulin Receptors Regulate Episodic and Spatial Memory Through Excitatory/Inhibitory Balance

It is well known that the hippocampus is a vital brain region playing a key role in both episodic and spatial memory. Insulin receptors (InsRs) are densely distributed in the hippocampus and are important for its function. However, the effects of InsRs on the function of the specific hippocampal cell types remain elusive. In this study, hippocampal InsRs knockout mice had impaired episodic and spatial memory. GABAergic neurons and glutamatergic neurons in the hippocampus are involved in the balance between excitatory and inhibitory (E/I) states and participate in the processes of episodic and spatial memory. InsRs are located mainly at excitatory neurons in the hippocampus, whereas 8.5% of InsRs are glutamic acid decarboxylase 2 (GAD2)::Ai9-positive (GABAergic) neurons. Next, we constructed a transgenic mouse system in which InsR expression was deleted from GABAergic (glutamate decarboxylase 2::InsRfl/fl, GAD2Cre::InsRfl/fl) or glutamatergic neurons (vesicular glutamate transporter 2::InsRfl/fl,Vglut2Cre::InsRfl/fl). Our results showed that in comparison to the InsRfl/fl mice, both episodic and spatial memory were lower in GAD2Cre::InsRfl/fl and Vglut2Cre::InsRfl/fl. In addition, both GAD2Cre::InsRfl/fl and Vglut2Cre::InsRfl/fl were associated with more anxiety and lower glucose tolerance. These findings reveal that hippocampal InsRs might be crucial for episodic and spatial memory through E/I balance hippocampal regulation.

Leptin receptor co-expression gene network moderates the effect of early life adversity on eating behavior in children

Leptin influences eating behavior. Exposure to early adversity is associated with eating behaviour disorders and metabolic syndrome, but the role of the leptin receptor on this relationship is poorly explored. We investigated whether individual differences in brain region specific leptin receptor (LepR) gene networks could moderate the effects of early adversity on eating behavior and metabolism. We created an expression-based polygenic risk score (ePRS) reflecting variations in the function of LepR gene network in prefrontal cortex and hypothalamus to investigate the interactions between a cumulative index of postnatal adversity on eating behavior in two independent birth cohorts (MAVAN and GUSTO). To explore whether variations in the prefrontal cortex or hypothalamic genetic scores could be associated with metabolic measurements, we also assessed the relationship between LepR-ePRS and fasting blood glucose and leptin levels in a third independent cohort (ALSPAC). We identified significant interaction effects between postnatal adversity and prefrontal-based LepR-ePRS on the Child Eating Behavior Questionnaire scores. In MAVAN, we observed a significant interaction effect on food enjoyment at 48 months (β = 61.58, p = 0.015) and 72 months (β = 97.78, p = 0.001); food responsiveness at 48 months (β = 83.79, p = 0.009) satiety at 48 months (β = −43.63, p = 0.047). Similar results were observed in the GUSTO cohort, with a significant interaction effect on food enjoyment (β = 30.48, p = 0.006) food fussiness score (β = −24.07, p = 0.02) and satiety score at 60 months (β = −17.00, p = 0.037). No effects were found when focusing on the hypothalamus-based LepR-ePRS on eating behavior in MAVAN and GUSTO cohorts, and there was no effect of hypothalamus and prefrontal cortex based ePRSs on metabolic measures in ALSPAC. Our study indicated that exposure to postnatal adversity interacts with prefrontal cortex LepR-ePRS to moderate eating behavior, suggesting a neurobiological mechanism associated with the development of eating behavior problems in response to early adversity. The knowledge of these mechanisms may guide the understanding of eating patterns associated with risk for obesity in response to fluctuations in stress exposure early in life.

An expression-based polygenic risk score analysis of leptin receptor (LepR) genes suggests that LepR-specific genes co-expressed in the prefrontal cortex interact with exposure to postnatal adversity, potentially modulating eating behavior in children.

Using genetic designs to identify likely causal environmental contributions to psychopathology

The multifactorial nature of psychopathology, whereby both genetic and environmental factors contribute risk, has long been established. In this paper, we provide an update on genetically informative designs that are utilized to disentangle genetic and environmental contributions to psychopathology. We provide a brief reminder of quantitative behavioral genetic research designs that have been used to identify potentially causal environmental processes, accounting for genetic contributions. We also provide an overview of recent molecular genetic approaches that utilize genome-wide association study data which are increasingly being applied to questions relevant to psychopathology research. While genetically informative designs typically have been applied to investigate the origins of psychopathology, we highlight how these approaches can also be used to elucidate potential causal environmental processes that contribute to developmental course and outcomes. We highlight the need to use genetically sensitive designs that align with intervention and prevention science efforts, by considering strengths-based environments to investigate how positive environments can mitigate risk and promote children's strengths.

Novel functional genomics approaches bridging neuroscience and psychiatry

The possibility of establishing a metric of individual genetic risk for a particular disease or trait has sparked the interest of the clinical and research communities, with many groups developing and validating genomic profiling methodologies for their potential application in clinical care. Current approaches for calculating genetic risk to specific psychiatric conditions consist of aggregating genome-wide association studies-derived estimates into polygenic risk scores, which broadly represent the number of inherited risk alleles for an individual. While the traditional approach for polygenic risk score calculation aggregates estimates of gene-disease associations, novel alternative approaches have started to consider functional molecular phenotypes that are closer to genetic variation and are less penalized by the multiple testing required in genome-wide association studies. Moving the focus from genotype-disease to genotype-gene regulation frameworks, these novel approaches incorporate prior knowledge regarding biological processes involved in disease and aggregate estimates for the association of genotypes and phenotypes using multi-omics data modalities. In this review, we discuss and list different functional genomics tools that can be used and integrated to inform researchers and clinicians for a better understanding and diagnosis of psychopathology. We suggest that these novel approaches can help generate biologically driven hypotheses for polygenic signals that can ultimately serve the clinical community as potential biomarkers of psychiatric disease susceptibility.

Genetically Adjusted Propensity Score Matching: A Comparison to Discordant MZ Twin Models

Discordant monozygotic (MZ) twin methodologies are considered one of the foremost statistical approaches for estimating the influence of environmental factors on phenotypic variance. Limitations associated with the discordant MZ twin approach generates an inability to estimate particular relationships and adjust estimates for the confounding influence of gene-nonshared environment interactions. Recent advancements in molecular genetics, however, can provide the opportunity to address these limitations. The current study reviews an alternative technique, genetically adjusted propensity scores (GAPS) matching, that integrates observed genetic and environmental information to adjust for the confounding of these factors in nonkin individuals. Simulations and a real data example were used to compare the GAPS matching approach to the discordant MZ twin method. Although the results of the simulated comparisons demonstrated that the discordant MZ twin approach remains the more robust statistical technique to adjust for shared environmental and genetic factors, GAPS matching - under certain conditions - could represent a viable alternative when MZ twin samples are unavailable. Overall, the findings suggest that GAPS matching can potentially provide an alternative to the discordant MZ twin approach when limited variation exists between identical twin pairs. Moreover, the ability to adjust for gene-nonshared environment interactions represents a potential advancement associated with the GAPS approach. The limitations of the approach, as well as polygenic risk scores, are also discussed.

Corticolimbic DCC gene co-expression networks as predictors of impulsivity in children

Inhibitory control deficits are prevalent in multiple neuropsychiatric conditions. The communication- as well as the connectivity- between corticolimbic regions of the brain are fundamental for eliciting inhibitory control behaviors, but early markers of vulnerability to this behavioral trait are yet to be discovered. The gradual maturation of the prefrontal cortex (PFC), in particular of the mesocortical dopamine innervation, mirrors the protracted development of inhibitory control; both are present early in life, but reach full maturation by early adulthood. Evidence suggests the involvement of the Netrin-1/DCC signaling pathway and its associated gene networks in corticolimbic development. Here we investigated whether an expression-based polygenic score (ePRS) based on corticolimbic-specific DCC gene co-expression networks associates with impulsivity-related phenotypes in community samples of children. We found that lower ePRS scores associate with higher measurements of impulsive choice in 6-year-old children tested in the Information Sampling Task and with impulsive action in 6- and 10-year-old children tested in the Stop Signal Task. We also found the ePRS to be a better overall predictor of impulsivity when compared to a conventional PRS score comparable in size to the ePRS (4515 SNPs in our discovery cohort) and derived from the latest GWAS for ADHD. We propose that the corticolimbic DCC-ePRS can serve as a novel type of marker for impulsivity-related phenotypes in children. By adopting a systems biology approach based on gene co-expression networks and genotype-gene expression (rather than genotype-disease) associations, these results further validate our methodology to construct polygenic scores linked to the overall biological function of tissue-specific gene networks.

Early adversity and insulin: neuroendocrine programming beyond glucocorticoids

Exposure to direct or contextual adversities during early life programs the functioning of the brain and other biological systems, contributing to the development of physical as well as mental health issues in the long term. While the role of glucocorticoids in mediating the outcomes of early adversity has been explored for many years, less attention has been given to insulin. Beyond its metabolic effects in the periphery, central insulin action affects synaptic plasticity, brain neurotransmission, and executive functions. Knowledge about the interactions between the peripheral metabolism and brain function from a developmental perspective can contribute to prevention and diagnosis programs, as well as early interventions for vulnerable populations.

Cognitive Development and Brain Gray Matter Susceptibility to Prenatal Adversities: Moderation by the Prefrontal Cortex Brain-Derived Neurotrophic Factor Gene Co-expression Network

Background: Previous studies focused on the relationship between prenatal conditions and neurodevelopmental outcomes later in life, but few have explored the interplay between gene co-expression networks and prenatal adversity conditions on cognitive development trajectories and gray matter density. Methods: We analyzed the moderation effects of an expression polygenic score (ePRS) for the Brain-derived Neurotrophic Factor gene network (BDNF ePRS) on the association between prenatal adversity and child cognitive development. A score based on genes co-expressed with the prefrontal cortex (PFC) BDNF was created, using the effect size of the association between the individual single nucleotide polymorphisms (SNP) and the BDNF expression in the PFC. Cognitive development trajectories of 157 young children from the Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) cohort were assessed longitudinally in 4-time points (6, 12, 18, and 36 months) using the Bayley-II mental scales. Results: Linear mixed-effects modeling indicated that BDNF ePRS moderates the effects of prenatal adversity on cognitive growth. In children with high BDNF ePRS, higher prenatal adversity was associated with slower cognitive development in comparison with those exposed to lower prenatal adversity. Parallel-Independent Component Analysis (pICA) suggested that associations of expression-based SNPs and gray matter density significantly differed between low and high prenatal adversity groups. The brain IC included areas involved in visual association processes (Brodmann area 19 and 18), reallocation of attention, and integration of information across the supramodal cortex (Brodmann area 10). Conclusion: Cognitive development trajectories and brain gray matter seem to be influenced by the interplay of prenatal environmental conditions and the expression of an important BDNF gene network that guides the growth and plasticity of neurons and synapses.

Diminished insulin sensitivity is associated with altered brain activation to food cues and with risk for obesity - Implications for individuals born small for gestational age

While classically linked to memory, the hippocampus is also a feeding behavior modulator due to its multiple interconnected pathways with other brain regions and expression of receptors for metabolic hormones. Here we tested whether variations in insulin sensitivity would be correlated with differential brain activation following exposure to palatable food cues, as well as with variations in implicit food memory in a cohort of healthy adolescents, some of whom were born small for gestational age (SGA). Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) was positively correlated with activation in the cuneus, and negatively correlated with activation in the middle frontal lobe, superior frontal gyrus and precuneus when presented with palatable food images versus non-food images in healthy adolescents. Additionally, HOMA-IR and insulinemia were higher in participants with impaired food memory. SGA individuals had higher snack caloric density and greater chance for impaired food memory. There was also an interaction between the HOMA-IR and birth weight ratio influencing external eating behavior. We suggest that diminished insulin sensitivity correlates with activation in visual attention areas and inactivation in inhibitory control areas in healthy adolescents. Insulin resistance also associated with less consistency in implicit memory for a consumed meal, which may suggest lower ability to establish a dietary pattern, and can contribute to obesity. Differences in feeding behavior in SGA individuals were associated with insulin sensitivity and hippocampal alterations, suggesting that cognition and hormonal regulation are important components involved in their food intake modifications throughout life.

The relationship between health-related quality of life and melancholic depressive symptoms is modified by brain insulin receptor gene network

To investigate whether expression-based polygenic risk scores for the insulin receptor gene network (ePRS-IRs) modifiy the association between type of depressive symptoms and health-related quality of life (HRQoL). This cross-sectional study includes 1558 individuals from the Helsinki Birth Cohort Study. Between 2001 and 2004, the Short Form-36 questionnaire was employed to assess mental and physical components of HRQoL and Beck Depression Inventory (BDI) to assess depressive symptoms. Depressive symptoms were categorized into minimal (BDI < 10), non-melancholic and melancholic types of depression. The ePRS-IRs were calculated for the hippocampal (hePRS-IR) and the mesocorticolimbic (mePRS-IR) regions of the brain. General linear regression models adjusted for age, sex, population stratification, lifestyle factors and body mass index were applied to analyze the data. Both types of depressive symptoms were associated with lower HRQoL (p < 0.0001). HePRS-IR modified the association between the types of depression and mental HRQoL (p for interaction = 0.005). Melancholic type of depressive symptoms was associated with higher mental HRQoL compared to the non-melancholic symptoms among individuals with low hePRS-IR (adjusted mean 4.1, 95% CI 0.7–7.4, p = 0.018). However, no such difference was evident in moderate or high hePRS-IR groups as higher hePRS-IR was associated with lower mental HRQoL (B = − 3.4, 95% CI − 5.6 to − 1.2) in individuals with melancholic type of depressive symptoms. No direct associations were detected between the ePRS-IRs and type of depressive symptoms or HRQoL. Variations in the glucose-insulin metabolism can lower HRQoL in individuals with melancholic depressive symptoms.

Association of increased abdominal adiposity at birth with altered ventral caudate microstructure

BACKGROUND

Neonatal adiposity is associated with a higher risk of obesity and cardiometabolic risk factors in later life. It is however unknown if central food intake regulating networks in the ventral striatum are altered with in-utero abdominal growth, indexed by neonatal adiposity in our current study. We aim to examine the relationship between striatal microstructure and abdominal adipose tissue compartments (AATCs) in Asian neonates from the Growing Up in Singapore Toward healthy Outcomes mother-offspring cohort.

STUDY DESIGN

About 109 neonates were included in this study. Magnetic resonance imaging (MRI) was performed for the brain and abdominal regions between 5 to 17 days of life. Diffusion-weighted imaging of the brain was performed for the derivation of caudate and putamen fractional anisotropy (FA). Abdominal imaging was performed to quantify AATCs namely superficial subcutaneous adipose tissue (sSAT), deep subcutaneous adipose tissue (dSAT), and internal adipose tissue (IAT). Absolute and percentage adipose tissue of total abdominal volume (TAV) were calculated.

RESULTS

We showed that AATCs at birth were significantly associated with increased FA in bilateral ventral caudate heads which are part of the ventral striatum (sSAT: β_left = 0.56, p < 0.001; β_right = 0.65, p < 0.001, dSAT: β_left = 0.43, p < 0.001; β_right = 0.52, p < 0.001, IAT: β_left = 0.30, p = 0.005; β_right = 0.32, p = 0.002) in neonates with low birth weights adjusted for gestational age.

CONCLUSIONS

Our study provides preliminary evidence of a potential relationship between neonatal adiposity and in-utero programming of the ventral striatum, a brain structure that governs feeding behavior.

Advancing the use of genome-wide association studies for drug repurposing

Genome-wide association studies (GWAS) have revealed important biological insights into complex diseases, which are broadly expected to lead to the identification of new drug targets and opportunities for treatment. Drug development, however, remains hampered by the time taken and costs expended to achieve regulatory approval, leading many clinicians and researchers to consider alternative paths to more immediate clinical outcomes. In this Review, we explore approaches that leverage common variant genetics to identify opportunities for repurposing existing drugs, also known as drug repositioning. These approaches include the identification of compounds by linking individual loci to genes and pathways that can be pharmacologically modulated, transcriptome-wide association studies, gene-set association, causal inference by Mendelian randomization, and polygenic scoring.

Early Life Adversity and Polygenic Risk for High Fasting Insulin Are Associated With Childhood Impulsivity

While the co-morbidity between metabolic and psychiatric behaviors is well-established, the mechanisms are poorly understood, and exposure to early life adversity (ELA) is a common developmental risk factor. ELA is associated with altered insulin sensitivity and poor behavioral inhibition throughout life, which seems to contribute to the development of metabolic and psychiatric disturbances in the long term. We hypothesize that a genetic background associated with higher fasting insulin interacts with ELA to influence the development of executive functions (e.g., impulsivity in young children). We calculated the polygenic risk scores (PRSs) from the genome-wide association study (GWAS) of fasting insulin at different thresholds and identified the subset of single nucleotide polymorphisms (SNPs) that best predicted peripheral insulin levels in children from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort [N = 467; p_{t– initial} = 0.24 (10,296 SNPs), p_{t– refined} = 0.05 (57 SNPs)]. We then calculated the refined PRS (rPRS) for fasting insulin at this specific threshold in the children from the Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) cohort and investigated its interaction effect with adversity on an impulsivity task applied at 36 months. We found a significant effect of interaction between fasting insulin rPRS and adversity exposure predicting impulsivity measured by the Snack Delay Task at 36 months [β = −0.329, p = 0.024], such that higher PRS [β = −0.551, p = 0.009] was linked to more impulsivity in individuals exposed to more adversity. Enrichment analysis (MetaCore^TM) of the SNPs that compose the fasting insulin rPRS at this threshold was significant for certain nervous system development processes including dopamine D2 receptor signaling. Additional enrichment analysis (FUMA) of the genes mapped from the SNPs in the fasting insulin rPRS showed enrichment with the accelerated cognitive decline GWAS. Therefore, the genetic background associated with risk for adult higher fasting insulin moderates the impact of early adversity on childhood impulsivity.

GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

Applying deep learning in population genomics is challenging because of computational issues and lack of interpretable models. Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, interpretable and memory-efficient neural network architectures are constructed by embedding biologically knowledge from public databases, resulting in neural networks that contain only biologically plausible connections. We applied the framework to seventeen phenotypes and found well-replicated genes such as HERC2 and OCA2 for hair and eye color, and novel genes such as ZNF773 and PCNT for schizophrenia. Additionally, the framework identified ubiquitin mediated proteolysis, endocrine system and viral infectious diseases as most predictive biological pathways for schizophrenia. GenNet is a freely available, end-to-end deep learning framework that allows researchers to develop and use interpretable neural networks to obtain novel insights into the genetic architecture of complex traits and diseases.

van Hilten and colleagues present GenNet, a deep-learning framework for predicting phenotype from genetic data. This framework generates interpretable neural networks that provide insight into the genetic basis of complex traits and diseases.

Prefrontal cortex VAMP1 gene network moderates the effect of the early environment on cognitive flexibility in children

During development, genetic and environmental factors interact to modify specific phenotypes. Both in humans and in animal models, early adversities influence cognitive flexibility, an important brain function related to behavioral adaptation to variations in the environment. Abnormalities in cognitive functions are related to changes in synaptic connectivity in the prefrontal cortex (PFC), and altered levels of synaptic proteins. We investigated if individual variations in the expression of a network of genes co-expressed with the synaptic protein VAMP1 in the prefrontal cortex moderate the effect of early environmental quality on the performance of children in cognitive flexibility tasks. Genes overexpressed in early childhood and co-expressed with the VAMP1 gene in the PFC were selected for study. SNPs from these genes (post-clumping) were compiled in an expression-based polygenic score (PFC-ePRS-VAMP1). We evaluated cognitive performance of the 4 years-old children in two cohorts using similar cognitive flexibility tasks. In the first cohort (MAVAN) we utilized two CANTAB tasks: (a) the Intra-/Extra-dimensional Set Shift (IED) task, and (b) the Spatial Working Memory (SWM) task. In the second cohort, GUSTO, we used the Dimensional Change Card Sort (DCCS) task. The results show that in 4 years-old children, the PFC-ePRS-VAMP1 network moderates responsiveness to the effects of early adversities on the performance in attentional flexibility tests. The same result was observed for a spatial working memory task. Compared to attentional flexibility, reversal learning showed opposite effects of the environment, as moderated by the ePRS. A parallel ICA analysis was performed to identify relationships between whole-brain voxel based gray matter density and SNPs that comprise the PFC-ePRS-VAMP1. The early environment predicts differences in gray matter content in regions such as prefrontal and temporal cortices, significantly associated with a genetic component related to Wnt signaling pathways. Our data suggest that a network of genes co-expressed with VAMP1 in the PFC moderates the influence of early environment on cognitive function in children.

Associations Among Parental Caregiving Quality, Cannabinoid Receptor 1 Expression-Based Polygenic Scores, and Infant-Parent Attachment: Evidence for Differential Genetic Susceptibility?

Attachment is a biological evolutionary system contributing to infant survival. When primary caregivers/parents are sensitive and responsive to their infants’ needs, infants develop a sense of security. Secure infant attachment has been linked to healthy brain and organ-system development. Belsky and colleagues proposed the term differential susceptibility to describe context-dependent associations between genetic variations and behavioral outcomes as a function of parenting environments. Variations in the Cannabinoid Receptor Gene 1 (CNR1) are associated with memory, mood, and reward and connote differential susceptibility to more and less optimal parental caregiving quality in predicting children’s behavioral problems.

Improved genetic prediction of complex traits from individual-level data or summary statistics

Most existing tools for constructing genetic prediction models begin with the assumption that all genetic variants contribute equally towards the phenotype. However, this represents a suboptimal model for how heritability is distributed across the genome. Therefore, we develop prediction tools that allow the user to specify the heritability model. We compare individual-level data prediction tools using 14 UK Biobank phenotypes; our new tool LDAK-Bolt-Predict outperforms the existing tools Lasso, BLUP, Bolt-LMM and BayesR for all 14 phenotypes. We compare summary statistic prediction tools using 225 UK Biobank phenotypes; our new tool LDAK-BayesR-SS outperforms the existing tools lassosum, sBLUP, LDpred and SBayesR for 223 of the 225 phenotypes. When we improve the heritability model, the proportion of phenotypic variance explained increases by on average 14%, which is equivalent to increasing the sample size by a quarter.

Multi-omic and multi-species meta-analyses of nicotine consumption

Cross-species translational approaches to human genomic analyses are lacking. The present study uses an integrative framework to investigate how genes associated with nicotine use in model organisms contribute to the genetic architecture of human tobacco consumption. First, we created a model organism geneset by collecting results from five animal models of nicotine exposure (RNA expression changes in brain) and then tested the relevance of these genes and flanking genetic variation using genetic data from human cigarettes per day (UK BioBank N = 123,844; all European Ancestry). We tested three hypotheses: (1) DNA variation in, or around, the 'model organism geneset' will contribute to the heritability to human tobacco consumption, (2) that the model organism genes will be enriched for genes associated with human tobacco consumption, and (3) that a polygenic score based off our model organism geneset will predict tobacco consumption in the AddHealth sample (N = 1667; all European Ancestry). Our results suggested that: (1) model organism genes accounted for ~5-36% of the observed SNP-heritability in human tobacco consumption (enrichment: 1.60-31.45), (2) model organism genes, but not negative control genes, were enriched for the gene-based associations (MAGMA, H-MAGMA, SMultiXcan) for human cigarettes per day, and (3) polygenic scores based on our model organism geneset predicted cigarettes per day in an independent sample. Altogether, these findings highlight the advantages of using multiple species evidence to isolate genetic factors to better understand the etiological complexity of tobacco and other nicotine consumption.

Genes, Environments, and Time: The Biology of Adversity and Resilience

Exposures to adverse environments, both psychosocial and physicochemical, are prevalent and consequential across a broad range of childhood populations. Such adversity, especially early in life, conveys measurable risk to learning and behavior and to the foundations of both mental and physical health. Using an interactive gene-environment-time (GET) framework, we survey the independent and interactive roles of genetic variation, environmental context, and developmental timing in light of advances in the biology of adversity and resilience, as well as new discoveries in biomedical research. Drawing on this rich evidence base, we identify 4 core concepts that provide a powerful catalyst for fresh thinking about primary health care for young children: (1) all biological systems are inextricably integrated, continuously "reading" and adapting to the environment and "talking back" to the brain and each other through highly regulated channels of cross-system communication; (2) adverse environmental exposures induce alterations in developmental trajectories that can lead to persistent disruptions of organ function and structure; (3) children vary in their sensitivity to context, and this variation is influenced by interactions among genetic factors, family and community environments, and developmental timing; and (4) critical or sensitive periods provide unmatched windows of opportunity for both positive and negative influences on multiple biological systems. These rapidly moving frontiers of investigation provide a powerful framework for new, science-informed thinking about health promotion and disease prevention in the early childhood period.

Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration

Genome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatric conditions. Recent advances in psychiatric genetics have been made possible through large-scale collaborative efforts. These studies have begun to unearth many novel genetic variants associated with psychiatric disorders and behavioral traits in human populations. Significant challenges remain in characterizing the resulting disease-associated genetic variants and prioritizing functional follow-up to make them useful for mechanistic understanding and development of therapeutics. Model organism research has generated extensive genomic data that can provide insight into the neurobiological mechanisms of variant action, but a cohesive effort must be made to establish which aspects of the biological modulation of behavioral traits are evolutionarily conserved across species. Scalable computing, new data integration strategies, and advanced analysis methods outlined in this review provide a framework to efficiently harness model organism data in support of clinically relevant psychiatric phenotypes.

DCC gene network in the prefrontal cortex is associated with total brain volume in childhood

BACKGROUND

Genetic variation in the guidance cue DCC gene is linked to psychopathologies involving dysfunction in the prefrontal cortex. We created an expression-based polygenic risk score (ePRS) based on the DCC coexpression gene network in the prefrontal cortex, hypothesizing that it would be associated with individual differences in total brain volume.

METHODS

We filtered single nucleotide polymorphisms (SNPs) from genes coexpressed with DCC in the prefrontal cortex obtained from an adult postmortem donors database (BrainEAC) for genes enriched in children 1.5 to 11 years old (BrainSpan). The SNPs were weighted by their effect size in predicting gene expression in the prefrontal cortex, multiplied by their allele number based on an individual's genotype data, and then summarized into an ePRS. We evaluated associations between the DCC ePRS and total brain volume in children in 2 community-based cohorts: the Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) and University of California, Irvine (UCI) projects. For comparison, we calculated a conventional PRS based on a genome-wide association study of total brain volume.

RESULTS

Higher ePRS was associated with higher total brain volume in children 8 to 10 years old (β = 0.212, p = 0.043; n = 88). The conventional PRS at several different thresholds did not predict total brain volume in this cohort. A replication analysis in an independent cohort of newborns from the UCI study showed an association between the ePRS and newborn total brain volume (β = 0.101, p = 0.048; n = 80). The genes included in the ePRS demonstrated high levels of coexpression throughout the lifespan and are primarily involved in regulating cellular function.

LIMITATIONS

The relatively small sample size and age differences between the main and replication cohorts were limitations.

CONCLUSION

Our findings suggest that the DCC coexpression network in the prefrontal cortex is critically involved in whole brain development during the first decade of life. Genes comprising the ePRS are involved in gene translation control and cell adhesion, and their expression in the prefrontal cortex at different stages of life provides a snapshot of their dynamic recruitment.

From GWAS to Function: Using Functional Genomics to Identify the Mechanisms Underlying Complex Diseases

Genome-wide association studies (GWAS) have successfully mapped thousands of loci associated with complex traits. These associations could reveal the molecular mechanisms altered in common complex diseases and result in the identification of novel drug targets. However, GWAS have also left a number of outstanding questions. In particular, the majority of disease-associated loci lie in non-coding regions of the genome and, even though they are thought to play a role in gene expression regulation, it is unclear which genes they regulate and in which cell types or physiological contexts this regulation occurs. This has hindered the translation of GWAS findings into clinical interventions. In this review we summarize how these challenges have been addressed over the last decade, with a particular focus on the integration of GWAS results with functional genomics datasets. Firstly, we investigate how the tissues and cell types involved in diseases can be identified using methods that test for enrichment of GWAS variants in genomic annotations. Secondly, we explore how to find the genes regulated by GWAS loci using methods that test for colocalization of GWAS signals with molecular phenotypes such as quantitative trait loci (QTLs). Finally, we highlight potential future research avenues such as integrating GWAS results with single-cell sequencing read-outs, designing functionally informed polygenic risk scores (PRS), and validating disease associated genes using genetic engineering. These tools will be crucial to identify new drug targets for common complex diseases.

Mental health dished up-the use of iPSC models in neuropsychiatric research

Genetic and molecular mechanisms that play a causal role in mental illnesses are challenging to elucidate, particularly as there is a lack of relevant in vitro and in vivo models. However, the advent of induced pluripotent stem cell (iPSC) technology has provided researchers with a novel toolbox. We conducted a systematic review using the PRISMA statement. A PubMed and Web of Science online search was performed (studies published between 2006–2020) using the following search strategy: hiPSC OR iPSC OR iPS OR stem cells AND schizophrenia disorder OR personality disorder OR antisocial personality disorder OR psychopathy OR bipolar disorder OR major depressive disorder OR obsessive compulsive disorder OR anxiety disorder OR substance use disorder OR alcohol use disorder OR nicotine use disorder OR opioid use disorder OR eating disorder OR anorexia nervosa OR attention-deficit/hyperactivity disorder OR gaming disorder. Using the above search criteria, a total of 3515 studies were found. After screening, a final total of 56 studies were deemed eligible for inclusion in our study. Using iPSC technology, psychiatric disease can be studied in the context of a patient’s own unique genetic background. This has allowed great strides to be made into uncovering the etiology of psychiatric disease, as well as providing a unique paradigm for drug testing. However, there is a lack of data for certain psychiatric disorders and several limitations to present iPSC-based studies, leading us to discuss how this field may progress in the next years to increase its utility in the battle to understand psychiatric disease.

Amygdala 5-HTT Gene Network Moderates the Effects of Postnatal Adversity on Attention Problems: Anatomo-Functional Correlation and Epigenetic Changes

Variations in serotoninergic signaling have been related to behavioral outcomes. Alterations in the genome, such as DNA methylation and histone modifications, are affected by serotonin neurotransmission. The amygdala is an important brain region involved in emotional responses and impulsivity, which receives serotoninergic input. In addition, studies suggest that the serotonin transporter gene network may interact with the environment and influence the risk for psychiatric disorders. We propose to investigate whether/how interactions between the exposure to early life adversity and serotonin transporter gene network in the amygdala associate with behavioral disorders. We constructed a co-expression-based polygenic risk score (ePRS) reflecting variations in the function of the serotonin transporter gene network in the amygdala and investigated its interaction with postnatal adversity on attention problems in two independent cohorts from Canada and Singapore. We also described how interactions between ePRS-5-HTT and postnatal adversity exposure predict brain gray matter density and variation in DNA methylation across the genome. We observed that the expression-based polygenic risk score, reflecting the function of the amygdala 5-HTT gene network, interacts with postnatal adversity, to predict attention and hyperactivity problems across both cohorts. Also, both postnatal adversity score and amygdala ePRS-5-HTT score, as well as their interaction, were observed to be associated with variation in DNA methylation across the genome. Variations in gray matter density in brain regions linked to attentional processes were also correlated to our ePRS score. These results confirm that the amygdala 5-HTT gene network is strongly associated with ADHD-related behaviors, brain cortical density, and epigenetic changes in the context of adversity in young children.

Genetically predicted gene expression of prefrontal DRD4 gene and the differential susceptibility to childhood emotional eating in response to positive environment

Genetic differential susceptibility states that individuals may vary both by exhibiting poor responses when exposed to adverse environments, and disproportionally benefiting from positive settings. The dopamine D4 receptor gene (DRD4) may be particularly implicated in these effects, including disturbed eating behaviors that might lead to obesity. Here, we explore differential susceptibility to positive environments according to the predicted genetically regulated gene expression of prefrontal cortex DRD4 gene. Using MAVAN as the discovery cohort (Maternal Adversity, Vulnerability and Neurodevelopment) and GUSTO as the replication cohort (Growing Up in Singapore Towards Healthy Outcomes), we analyzed the interaction between a) a Positive postnatal environmental score, that accounts for positive outcomes in the postnatal period and b) the genetically regulated gene expression of prefrontal DRD4, computed using a machine learning prediction method (PrediXcan). The outcome measures were the pro-intake domains (Emotional over-eating, Food Responsiveness, Food Enjoyment and Desire to Drink) from the Child Eating Behavior Questionnaire at 48 months of age (MAVAN) and 60 months of age (GUSTO). The interaction between the positive environment and the predicted prefrontal DRD4 gene expression was significant for emotional over-eating in MAVAN (β = -0.403, p < 0.02), in which the high gene expression group had more or less emotional eating according to the exposure to lower or higher positive environment respectively, showing evidence of differential susceptibility criteria. In the replication cohort, a similar result was found with the pro-intake domain Desire to drink (β = -0.583, p < 0.05). These results provide further evidence for the genetic differential susceptibility, accounting for the benefit of positive environments.

Prefrontal Cortex Dopamine Transporter Gene Network Moderates the Effect of Perinatal Hypoxic-Ischemic Conditions on Cognitive Flexibility and Brain Gray Matter Density in Children

BACKGROUND

Genetic polymorphisms of the dopamine transporter gene (DAT1) and perinatal complications associated with poor oxygenation are risk factors for attentional problems in childhood and may show interactive effects.

METHODS

We created a novel expression-based polygenic risk score (ePRS) reflecting variations in the function of the DAT1 gene network (ePRS-DAT1) in the prefrontal cortex and explored the effects of its interaction with perinatal hypoxic-ischemic-associated conditions on cognitive flexibility and brain gray matter density in healthy children from two birth cohorts-MAVAN from Canada (n = 139 boys and girls) and GUSTO from Singapore (n = 312 boys and girls).

RESULTS

A history of exposure to several perinatal hypoxic-ischemic-associated conditions was associated with impaired cognitive flexibility only in the high-ePRS group, suggesting that variation in the prefrontal cortex expression of genes involved in dopamine reuptake is associated with differences in this behavior. Interestingly, this result was observed in both ethnically distinct birth cohorts. Additionally, parallel independent component analysis (MAVAN cohort, n = 40 children) demonstrated relationships between single nucleotide polymorphism-based ePRS and gray matter density in areas involved in executive (cortical regions) and integrative (bilateral thalamus and putamen) functions, and these relationships differ in children from high and low exposure to hypoxic-ischemic-associated conditions.

CONCLUSIONS

These findings reveal that the impact of conditions associated with hypoxia-ischemia on brain development and executive functions is moderated by genotypes associated with dopamine signaling in the prefrontal cortex. We discuss the potential impact of innovative genomic and environmental measures for the identification of children at high risk for impaired executive functions.

Polygenic risk scores in psychiatry: Will they be useful for clinicians?

Major psychiatric disorders are heritable but they are genetically complex. This means that, with certain exceptions, single gene markers will not be helpful for diagnosis. However, we are learning more about the large number of gene variants that, in combination, are associated with risk for disorders such as schizophrenia, bipolar disorder, and other psychiatric conditions. The presence of those risk variants may now be combined into a polygenic risk score (PRS). Such a score provides a quantitative index of the genomic burden of risk variants in an individual, which relates to the likelihood that a person has a particular disorder. Currently, such scores are quite useful in research, and they are telling us much about the relationships between different disorders and other indices of brain function. In the future, as the datasets supporting the development of such scores become larger and more diverse and as methodological developments improve predictive capacity, we expect that PRS will have substantial clinical utility in the assessment of risk for disease, subtypes of disease, and even treatment response. Here, we provide an overview of PRS in general terms (including a glossary suitable for informed non-geneticists) and discuss the use of PRS in psychiatry, including their limitations and cautions for interpretation, as well as their applications now and in the future.