Background Activation of brain insulin receptors modulates reward sensitivity, inhibitory control and memory. Variations in the functioning of this mechanism likely associate with individual differences in the risk for related mental disorders (attention deficit hyperactivity disorder or ADHD, addiction, dementia), in agreement with the high co-morbidity between insulin resistance and psychopathology. These neurobiological mechanisms can be explored using genetic studies. We propose a novel, biologically informed genetic score reflecting the mesocorticolimbic and hippocampal insulin receptor-related gene networks, and investigate if it predicts endophenotypes (impulsivity, cognitive ability) in community samples of children, and psychopathology (addiction, dementia) in adults. Methods Lists of genes co-expressed with the insulin receptor in the mesocorticolimbic system or hippocampus were created. SNPs from these genes (post-clumping) were compiled in a polygenic score using the association betas described in a conventional GWAS (ADHD in the mesocorticolimbic score and Alzheimer in the hippocampal score). Across multiple samples ( n = 4502), the biologically informed, mesocorticolimbic or hippocampal specific insulin receptor polygenic scores were calculated, and their ability to predict impulsivity, risk for addiction, cognitive performance and presence of Alzheimer's disease was investigated. Findings The biologically-informed ePRS-IR score showed better prediction of child impulsivity and cognitive performance, as well as risk for addiction and Alzheimer's disease in comparison to conventional polygenic scores for ADHD, addiction and dementia. Interpretation This novel, biologically-informed approach enables the use of genomic datasets to probe relevant biological processes involved in neural function and disorders. Fund Toxic Stress Research network of the JPB Foundation, Jacobs Foundation (Switzerland), Sackler Foundation.

Conventional polygenic scores derived from genome-wide association studies do not reflect gene networks that code for biological functions. We present an alternative approach creating a biologically-informed polygenic score based on the insulin receptor (IR) gene networks in the mesocorticolimbic system and hippocampus that regulate reward sensitivity/inhibitory control and memory, respectively. Across multiple samples (n = 4300) our biologically-informed IR-PRS score showed better prediction of child impulsivity and cognitive performance, as well as risk for early addiction onset and Alzheimer's disease in comparison to conventional polygenic scores for ADHD, addiction and dementia. This novel, biologicallyinformed approach enables the use of genomic datasets to probe relevant biological processes involved in neural function and disorders.One Sentence Summary: A polygenic score based on genes co-expressed with the insulin receptor predicts childhood behavior and adult disease. Main Text:The co-morbidity between metabolic and neuropsychiatric disorders is well-established, but poorly understood. The high co-occurrence of several psychiatric conditions (e.g. major depression, bipolar disorder, dementia) with insulin resistance suggests a common underlying mechanism (Anderson, Freedland et al. 2001). Insulin receptors (IR) are expressed throughout the brain, in areas including the ventral tegmental area, striatum, prefrontal cortex and hippocampus. Insulin is actively transported across the blood-brain barrier, and its action on mesocorticolimbic receptors modulates synaptic plasticity in dopaminergic neurons, affecting dopamine-related behaviors such as response to reward, impulsivity and decision-making (Kullmann, Heni et al. 2016). IR location on hippocampal glutamatergic synapses suggests a role of insulin in neurotransmission, synaptic plasticity and modulation of learning and memory, while its inhibition is described in Alzheimer's disease and related animal models (Bomfim, Forny-Germano et al. 2012).Genetic studies can be a pertinent tool to investigate the neurobiological mechanisms that explain the co-morbidity between metabolic and neuropsychiatric conditions. Genome-wide association studies (GWAS) provide the basis for cumulative variants that associate with health outcomes and reflect genetic predispositions to common disorders where individual variants carry small effects. The cumulative polygenetic risk of the individual can be used to estimate risk through polygenic risk scores (PRS), by multiplying the measured number of risk alleles at a locus by the effect size of the association between a particular genotype and the outcome from the relevant GWAS study, and summing across the genome (Wray and Goddard 2010). GWAS and PRS methodologies are focused on statistically significant candidate associations between scattered loci and a certain condition or trait, not accounting for the fact that genes operate in networks, and code for precise biological functions in specific tissues. Although recent studie...

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