Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

Wendt, Frank R.; Pathak, Gita A; Tylee, Daniel S.; Goswami, Aranyak; Polimanti, Renato

doi:10.1177/2470547020924844

Cited by 41 publications

(31 citation statements)

References 205 publications

(281 reference statements)

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“…In the last few decades, genome-wide association scans (GWAS) have been used to identify the genetic basis of chronic diseases, which revealed the influence of several common genetic variants on their risk. These conditions include but are not limited to cardiovascular disease (CVD) [ 13 , 14 ], cancer [ 15 ], and metabolic [ 16 ], neurodegenerative [ 17 ], and neuropsychiatric disorders [ 18 ]. However, despite the high heritability observed for these chronic diseases, the genetic variants identified explained a small proportion of the disease variability.…”

Section: Development and Perspectives For Italian Public Health Gementioning

confidence: 99%

Precision Medicine and Public Health: New Challenges for Effective and Sustainable Health

Traversi¹,

Pulliero

Izzotti

et al. 2021

JPM

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The development of high-throughput omics technologies represents an unmissable opportunity for evidence-based prevention of adverse effects on human health. However, the applicability and access to multi-omics tests are limited. In Italy, this is due to the rapid increase of knowledge and the high levels of skill and economic investment initially necessary. The fields of human genetics and public health have highlighted the relevance of an implementation strategy at a national level in Italy, including integration in sanitary regulations and governance instruments. In this review, the emerging field of public health genomics is discussed, including the polygenic scores approach, epigenetic modulation, nutrigenomics, and microbiomes implications. Moreover, the Italian state of implementation is presented. The omics sciences have important implications for the prevention of both communicable and noncommunicable diseases, especially because they can be used to assess the health status during the whole course of life. An effective population health gain is possible if omics tools are implemented for each person after a preliminary assessment of effectiveness in the medium to long term.

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Section: Development and Perspectives For Italian Public Health Gementioning

confidence: 99%

Precision Medicine and Public Health: New Challenges for Effective and Sustainable Health

Traversi¹,

Pulliero

Izzotti

et al. 2021

JPM

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“…Increasingly large genome-wide association studies (GWAS) show that brain disorders and related traits are driven by polygenic factors. Polygenicity has long been assumed for complex behavioural traits, but it is only now that we have come to fully appreciate the extreme form this polygenicity takes 1 . The brain is the logical organ of convergence for genetic effects on behavioural phenotypes, and quantitative neuroimaging can putatively trace some of these effects in living humans non-invasively 2 .…”

Section: Introductionmentioning

confidence: 99%

Independent Genomic Sources of Brain Structure and Function

Soheili-Nezhad

Beckmann

Sprooten

2021

Preprint

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IntroductionThe last decade has seen a surge in well powered genome-wide association studies (GWASs) of complex behavioural traits, disorders, and more recently, of brain structural and functional neuroimaging features. However, the extreme polygenicity of these complex traits makes it difficult to translate the GWAS signal into mechanistic biological insights. We postulate that the covariance of SNP-effects across many brain features, as be captured by latent genomic components of SNP effect sizes. These may partly reflect the concerted multi-locus genomic effects through known molecular pathways and protein-protein interactions. Here, we test the feasibility of a new data-driven method to derive such latent components of genome-wide effects on more than thousand neuroimaging derived traits, and investigate their utility in interpreting the complex biological processes that shape the GWAS signal.MethodsWe downloaded the GWAS summary statistics of 3,143 brain imaging-derived phenotypes (IDPs) from the UK Biobank, provided by the Oxford Brain Imaging Genetics (BIG) Server (Elliott et al. 2018). Probabilistic independent component analysis (ICA) was used to extract two hundred independent genomic components from the matrix of SNP-effect sizes. We qualitatively describe the distribution of the latent component’s loadings in the neuroimaging and the genomic dimensions. Gene-wide statistics were calculated for each genomic component. We tested the genomic component’s enrichment for molecular pathways using MSigDB, and for single-cell RNA-sequencing of adult and foetal brain cells.Results200 components explained 80% of the variance in SNP-effects sizes. Each MRI modality and data processing method projected the imaging data into a clearly distinct cluster in the genomic component embedded space. Among the 200 genomic components, 157 were clearly driven by a single locus, while 39 were highly polygenic. Together, these 39 components were significantly enriched for 2,274 MSigDB gene sets (fully corrected for multiple testing across gene-sets and components). Several components were sensitive to molecular pathways, single cell expression profiles, and brain traits in patterns consistent with knowledge across these biological levels. To illustrate this, we highlight a component that implicated axonal regeneration pathways, which was specifically enriched for gene expression in oligodendrocyte precursors, microglia and astrocytes, and loaded highly on white matter neuroimaging traits. We highlight a second component that implicated synaptic function and neuron projection organization pathways that was specifically enriched for neuronal cell transcriptomes.ConclusionWe propose genomic ICA as a new method to identify latent genetic factors influencing brain structure and function by multimodal MRI. The derived latent genomic dimensions are highly sensitive to known molecular pathways and cell-specific gene expression profiles. Genomic ICA may help to disentangle the many different biological routes by which the genome defines the inter-individual variation of the brain. Future research is aimed at using this method to profile individual subjects’ genomic data along the new latent dimensions and evaluating the utility of these dimensions in stratifying heterogeneous patient populations.

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“…SCZ and BD are highly polygenic diseases, with many associated genetic variants with small effects, as demonstrated by several genome-wide association studies (GWAS) 14 – 17 . Moreover, several genetic-based studies have shown a limited contribution to support the diagnosis and/or the characterization of pathways underlying these major MDs, due to the well-recognized pleiotropic features and small size effect of each gene 18 , 19 . Therefore, none of genetic studies was adequate to reveal the mechanisms underlying the etiology and/or pathophysiology of SCZ and/or BD.…”

Section: Introductionmentioning

confidence: 99%

A system biology approach based on metabolic biomarkers and protein–protein interactions for identifying pathways underlying schizophrenia and bipolar disorder

Altaf-Ul-Amin

Hirose

Nani

et al. 2021

Sci Rep

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Mental disorders (MDs), including schizophrenia (SCZ) and bipolar disorder (BD), have attracted special attention from scientists due to their high prevalence and significantly debilitating clinical features. The diagnosis of MDs is still essentially based on clinical interviews, and intensive efforts to introduce biochemical based diagnostic methods have faced several difficulties for implementation in clinics, due to the complexity and still limited knowledge in MDs. In this context, aiming for improving the knowledge in etiology and pathophysiology, many authors have reported several alterations in metabolites in MDs and other brain diseases. After potentially fishing all metabolite biomarkers reported up to now for SCZ and BD, we investigated here the proteins related to these metabolites in order to construct a protein–protein interaction (PPI) network associated with these diseases. We determined the statistically significant clusters in this PPI network and, based on these clusters, we identified 28 significant pathways for SCZ and BDs that essentially compose three groups representing three major systems, namely stress response, energy and neuron systems. By characterizing new pathways with potential to innovate the diagnosis and treatment of psychiatric diseases, the present data may also contribute to the proposal of new intervention for the treatment of still unmet aspects in MDs.

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Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

Cited by 41 publications

References 205 publications

Precision Medicine and Public Health: New Challenges for Effective and Sustainable Health

Precision Medicine and Public Health: New Challenges for Effective and Sustainable Health

Independent Genomic Sources of Brain Structure and Function

A system biology approach based on metabolic biomarkers and protein–protein interactions for identifying pathways underlying schizophrenia and bipolar disorder

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