Genomics of schizophrenia, bipolar disorder and major depressive disorder

Schizophrenia, bipolar disorder and major depressive disorder - which are the most common adult disorders requiring psychiatric care - contribute substantially to premature mortality and morbidity globally. Treatments for these disorders are suboptimal, there are no diagnostic pathologies or biomarkers and their pathophysiologies are poorly understood. Novel therapeutic and diagnostic approaches are thus badly needed. Given the high heritability of psychiatric disorders, psychiatry has potentially much to gain from the application of genomics to identify molecular risk mechanisms and to improve diagnosis. Recent large-scale, genome-wide association studies and sequencing studies, together with advances in functional genomics, have begun to illuminate the genetic architectures of schizophrenia, bipolar disorder and major depressive disorder and to identify potential biological mechanisms. Genomic findings also point to the aetiological relationships between different diagnoses and to the relationships between adult psychiatric disorders and childhood neurodevelopmental conditions.

Shedding Light on Antisocial Behavior Through Genetically Informed Research

Antisocial behavior (ASB) refers to a set of behaviors that violate social norms and disregard the well-being and rights of others. In this review, we synthesize evidence from studies using genetically informed designs to investigate the genetic and environmental contributions to individual differences in ASB. We review evidence from studies using family data (twin and adoption studies) and measured DNA (candidate gene and genome-wide association studies) that have informed our understanding of ASB. We describe how genetically informative designs are especially suited to investigate the nature of environmental risk and the forms of gene-environment interplay. We also highlight clinical and legal implications, including how insights from genetically informed research can help inform prevention and intervention, and we discuss some challenges and opportunities within this field of research.

Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.

Monozygotic twins discordant for depression: An extended network comparison of depressive symptoms, cognitive functions and daily activities

Monozygotic twins share the same genotype; however, they can be phenotypically discordant on various traits. Studying discordant monozygotic twins allows the investigation of differences in associations between symptoms and psychopathological risk factors, controlled for shared genetic liability. The network approach to psychopathology suggests that depressive symptoms, along with risk and protective factors (e.g., cognition, daily activities), form a complex system of mutually interacting components. We compared monozygotic twins discordant for lifetime depression on their respective extended networks of depressive symptoms, cognitive functions and daily activities (intellectual, physical, social), and evaluated if these networks differ in their associations between variables and in the role of each variable within the network. Regularized partial correlations investigated the networks' composition in 147 monozygotic twin pairs discordant for depression from the Danish Twin Registry. Affected twins had stronger overall associations within their network of depressive symptoms, cognitive functions and daily activities than their unaffected co-twins, while the importance of the network components' associations did not differ between the co-twins. In affected twins, decreased frequency in experiencing happiness had the strongest association with remaining variables (i.e., the most influence in activating other network elements). Also, variables from different groups were significantly associated (e.g., loneliness with delayed memory, pessimism with low social activities, verbal learning with intellectual activities). In unaffected twins, both mood symptoms and cognitive functions were important, but between-groups associations were quasi-absent. These results suggest that external events affecting the ability to feel happiness likely trigger the psychopathological process (depression network activation), independently from the genetic predisposition to depression.

A Wolf in Sheep's Clothing: Idealisations and the aims of polygenic scores

Research in pharmacogenomics and precision medicine has recently introduced the concept of Polygenic Scores (PGSs), namely, indexes that aggregate the effects that many genetic variants are predicted to have on individual disease risk. The popularity of PGSs is increasing rapidly, but surprisingly little attention has been paid to the idealisations they make about phenotypic development. Indeed, PGSs rely on quantitative genetics models and methods, which involve considerable theoretical assumptions that have been questioned on various grounds. This comes with epistemological and ethical concerns about the use of PGSs in clinical decision-making. In this paper, I investigate to what extent idealisations in genetics models can impact the data gathering and clinical interpretation of genomics findings, particularly the calculation and predictive accuracy of PGSs. Although idealisations are considered ineliminable components of scientific models, they may be legitimate or not depending on the epistemic aims of a model. I thus analyse how various idealisations have been introduced in classical models and progressively readapted throughout the history of genetic theorising. Notably, this process involved important changes in the epistemic purpose of such idealisations, which raises the question of whether they are legitimate in the context of contemporary genomics.

Genetic polymorphisms of bone marrow stromal cell antigen-1 (BST-1/CD157): implications for immune/inflammatory dysfunction in neuropsychiatric disorders

Bone marrow stromal cell antigen-1 (BST-1/CD157) is an immune/inflammatory regulator that functions as both nicotinamide adenine dinucleotide-metabolizing ectoenzyme and cell-surface signaling receptor. BST-1/CD157 is expressed not only in peripheral tissues, but in the central nervous system (CNS). Although its pathophysiological significance in the CNS is still unclear, clinical genetic studies over a decade have begun revealing relationships between BST-1/CD157 and neuropsychiatric diseases including Parkinson's disease, autism spectrum disorders, sleep disorders, depressive disorders and restless leg syndrome. This review summarizes the accumulating evidence for the involvement of BST-1/CD157 in these disorders.

Why mental disorders are brain disorders. And why they are not: ADHD and the challenges of heterogeneity and reification

Scientific attempts to identify biomarkers to reliably diagnose mental disorders have thus far been unsuccessful. This has inspired the Research Domain Criteria (RDoC) approach which decomposes mental disorders into behavioral, emotional, and cognitive domains. This perspective article argues that the search for biomarkers in psychiatry presupposes that the present mental health categories reflect certain (neuro-) biological features, that is, that these categories are reified as biological states or processes. I present two arguments to show that this assumption is very unlikely: First, the heterogeneity (both within and between subjects) of mental disorders is grossly underestimated, which is particularly salient for an example like Attention Deficit/Hyperactivity Disorder (ADHD). Second, even the search for the biological basis of psychologically more basic categories (cognitive and emotional processes) than the symptom descriptions commonly used in mental disorder classifications has thus far been inconclusive. While philosophers have discussed this as the problem of mind-body-reductionism for ages, Turkheimer presented a theoretical framework comparing weak and strong biologism which is more useful for empirical research. This perspective article concludes that mental disorders are brain disorders in the sense of weak, but not strong biologism. This has important implications for psychiatric research: The search for reliable biomarkers for mental disorder categories we know is unlikely to ever be successful. This implies that biology is not the suitable taxonomic basis for psychiatry, but also psychology at large.

MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders

Autism spectrum disorder (ASD) is a childhood neurodevelopmental disorder with a complex and heterogeneous genetic etiology. MicroRNA (miRNA), a class of small non-coding RNAs, could regulate ASD risk genes post-transcriptionally and affect broad molecular pathways related to ASD and associated disorders. Using whole-genome sequencing, we analyzed 272 samples in 73 families in the New Jersey Language and Autism Genetics Study (NJLAGS) cohort. Families with at least one ASD patient were recruited and were further assessed for language impairment, reading impairment, and other associated phenotypes. A total of 5104 miRNA variants and 1,181,148 3' untranslated region (3' UTR) variants were identified in the dataset. After applying several filtering criteria, including population allele frequency, brain expression, miRNA functional regions, and inheritance patterns, we identified high-confidence variants in five brain-expressed miRNAs (targeting 326 genes) and 3' UTR miRNA target regions of 152 genes. Some genes, such as SCP2 and UCGC, were identified in multiple families. Using Gene Ontology overrepresentation analysis and protein-protein interaction network analysis, we identified clusters of genes and pathways that are important for neurodevelopment. The miRNAs and miRNA target genes identified in this study are potentially involved in neurodevelopmental disorders and should be considered for further functional studies.