Biology subjects

Suvisaari, J.

Publications and source records attributed to Suvisaari, J..

6 recordsLinked to original sources

bioRxiv2020

Patient iPSC-astrocytes show transcriptional and functional dysregulation in schizophrenia

Human astrocytes are multifunctional brain cells and may contribute to the pathophysiology of schizophrenia (SCZ). We differentiated astrocytes from induced pluripotent stem cells of monozygotic twins discordant for SCZ, and found sex-specific gene expression and signaling pathway alterations related particularly to inflammation and synaptic functions. While Ingenuity Pathway Analysis identified SCZ disease and synaptic transmission pathway changes in SCZ astrocytes, the most consistent findings were related to collagen and cell adhesion associated pathways. Neuronal responses to glutamate and GABA differed between astrocytes from control persons, affected twins, and their unaffected co-twins, and were normalized by clozapine treatment. SCZ astrocyte cell transplantation to the mouse forebrain caused gene expression changes in demyelination, synaptic dysfunction and inflammation pathways of mouse brain cells and resulted in behavioral changes in cognitive and olfactory functions. Altogether, our results show that astrocytes contribute to both familial risk and clinical manifestation of SCZ in a sex-specific manner.

neuroscience↗

bioRxiv2020

Molecular signaling pathways underlying schizophrenia

The molecular pathophysiological mechanisms underlying schizophrenia have remained unknown, and no treatment exists for primary prevention. Studies using stem cell-derived neurons have investigated differentially expressed genes (DEGs) and GO and KEGG pathways between patients and controls, but not analyzed data-driven causal molecular pathways involved. We used Ingenuity Pathway Analysis (IPA) to analyze canonical and causal pathways in two different datasets, including patients from Finland and USA. The most significant findings in canonical pathway analysis were observed for glutamate receptor signaling, hepatic fibrosis, and glycoprotein 6 (GP6) pathways in the Finnish dataset, and GP6 and hepatic fibrosis pathways in the US dataset. In data-driven causal pathways, ADCYAP1, ADAMTS, and CACNA genes were involved in the majority of the top 10 pathways differentiating patients and controls in both Finnish and US datasets. In contrast, no dopamine-specific genes were consistently involved. Results from a Finnish nation-wide database showed that the risk of schizophrenia relapse was 41% lower among first-episode patients during the use of losartan, the master regulator of an ADCYAP1, ADAMTS, and CACNA -related pathway, compared to those time periods when the same individual did not use the drug. This association was not attributable to general adherence to drug treatments. The results from the two independent datasets suggest that the GP6 signaling pathway, and the ADCYAP1, ADAMTS, and CACNA -related purine, oxidative stress, and glutamatergic signaling pathways are primary pathophysiological alterations in schizophrenia among patients with European ancestry. While no reproducible dopaminergic alterations were observed, the results imply that agents such as losartan, and ADCYAP1/PACAP -deficit alleviators, such as metabotropic glutamate 2/3 agonist MGS0028 and 5-HT7 antagonists - which have shown beneficial effects in an experimental Adcyap1-/- mouse model for schizophrenia - could be potential treatments before the full manifestation of illness involving dopaminergic abnormalities.

neuroscience↗

bioRxiv2019

Advantages of genotype imputation with ethnically matched reference panel for rare variant association analyses

Genotype imputation has become a standard procedure prior genome-wide association studies (GWASs). For common and low-frequency variants, genotype imputation can be performed sufficiently accurately with publicly available and ethnically heterogeneous reference datasets like 1000 Genomes Project (1000G) and Haplotype Reference Consortium panels. However, the imputation of rare variants has been shown to be significantly more accurate when ethnically matched reference panel is used. Even more, greater genetic similarity between reference panel and target samples facilitates the detection of rare (or even population-specific) causal variants. Notwithstanding, the genome-wide downstream consequences and differences of using ethnically mixed and matched reference panels have not been yet comprehensively explored.\n\nWe determined and quantified these differences by performing several comparative evaluations of the discovery-driven analysis scenarios. A variant-wise GWAS was performed on seven complex diseases and body mass index by using genome-wide genotype data of [~]37,000 Estonians imputed with ethnically mixed 1000G and ethnically matched imputation reference panels. Although several previously reported common (minor allele frequency; MAF > 5%) variant associations were replicated in both resulting imputed datasets, no major differences were observed among the genome-wide significant findings or in the fine-mapping effort. In the analysis of rare (MAF < 1%) coding variants, 46 significantly associated genes were identified in the ethnically matched imputed data as compared to four genes in the 1000G panel based imputed data. All resulting genes were consequently studied in the UK Biobank data.\n\nThese associations provide a solid example of how rare variants can be efficiently analysed to discover novel, potentially functional genetic variants in relevant phenotypes. Furthermore, our work serves as proof of a cost-efficient study design, demonstrating that the usage of ethnically matched imputation reference panels can enable substantially improved imputation of rare variants, facilitating novel high-confidence findings in rare variant GWAS scans.\n\nAuthor summaryOver the last decade, genome-wide association studies (GWASs) have been widely used for detecting genetic biomarkers in a wide range of traits. Typically, GWASs are carried out using chip-based genotyping data, which are then combined with a more densely genotyped reference panel to infer untyped genetic variants in chip-typed individuals. The latter method is called genotype imputation and its accuracy depends on multiple factors. Publicly available and ethnically heterogeneous imputation reference panels (IRPs) such as 1000 Genomes Project (1000G) are sufficiently accurate for imputation of common and low-frequency variants, but custom ethnically matched IRPs outperform these in case of rare variants. In this work, we systematically compare downstream association analysis effects on eight complex traits in [~]37,000 Estonians imputed with ethnically mixed and ethnically matched IRPs. We do not observe major differences in the single variant analysis, where both imputed datasets replicate previously reported significant loci. But in the gene-based analysis of rare protein-coding variants we show that ethnically matched panel clearly outperforms 1000G panel based imputation, providing 10-fold increase in significant gene-trait associations. Our study demonstrates empirically that imputed data based on ethnically matched panel is very promising for rare variant analysis - it captures more population-specific variants and makes it possible to efficiently identify novel findings.

genomics↗

bioRxiv2018

Variants in regulatory elements of PDE4D associate with Major Mental Illness in the Finnish population

We have previously reported a replicable association between variants at the PDE4D gene and familial schizophrenia in a Finnish cohort. In order to identify the potential functional mutations alluded to by these previous findings, we sequenced the 1.5Mb of the PDE4D genomic locus in 20 families (consisting of 96 individuals, and 79 independent chromosomes), followed by two stages of genotyping across 6,668 individuals from multiple Finnish cohorts for major mental illnesses. We identified 4,570 SNPs across the PDE4D gene, with 380 associated to schizophrenia (p[≤]0.05). Importantly, two of these variants, rs35278 and rs165940, are located at transcription factor binding sites, and displayed replicable association in the two-stage enlargement of the familial schizophrenia cohort, (combined statistics for rs35278 p=0.0012; OR=1.18, 95% CI 1.06-1.32; and rs165940 p=0.0016; OR=1.27, 95% CI 1.13-1.41). Further analysis using additional cohorts and endophenotypes revealed that rs165940 principally associates within the psychosis (p=0.025, OR=1.18, 95% CI 1.07-1.30) and cognitive domains of major mental illnesses (g-score p=0.044, beta=-0.033). Specifically, the cognitive domains represented verbal learning and memory (p=0.0091, beta=-0.044) and verbal working memory (p=0.0062, beta=-0.036). Moreover, expression data from the GTEx database demonstrated that rs165940 significantly correlates with the mRNA expression levels of PDE4D in the cerebellum (p-value=0.04; m-value=0.9), demonstrating a potential functional consequence for this variant. Thus, rs165940 represents the most likely functional variant for major mental illness at the PDE4D locus in the Finnish population, increasing risk broadly to psychotic disorders.

genetics↗

bioRxiv2018

Contribution of rare and common variants to intellectual disability in a high-risk population sub-isolate of Northern Finland

The contribution of de novo and ultra-rare genetic variants in severe and moderate intellectual disability (ID) has been extensively studied whereas the genetic architecture of mild ID has been less well characterized. To elucidate the genetic background of milder ID we studied a regional cohort of 442 ID patients enriched for mild ID (>50%) from a population isolate of Finland. We analyzed rare variants using exome sequencing and CNV genotyping and common variants using common variant polygenic risk scores. As controls we used a Finnish collection of exome sequenced (n=11311) and GWAS chip genotyped (n=11699) individuals.\n\nWe show that rare damaging variants in genes known to be associated with cognitive defects are observed more often in severe (27%) than in mild ID (13%) patients (p-value: 7.0e-4). We further observed a significant enrichment of protein truncating variants in loss-of-function intolerant genes, as well as damaging missense variants in genes not yet associated with cognitive defects (OR: 2.1, p-value: 3e-8). For the first time to our knowledge, we show that a common variant polygenic load significantly contributes to all severity forms of ID. The heritability explained was the highest for educational attainment (EDU) in mild ID explaining 2.2% of the heritability on liability scale. For more severe ID it was lower at 0.6%. Finally, we identified a homozygote variant in the CRADD gene to be a cause of a specific syndrome with ID and pachygyria. The frequency of this variant is 50x higher in the Finnish population than in non-Finnish Europeans, demonstrating the benefits of utilizing population isolates in rare variant analysis of diseases under negative selection.

genetics↗

bioRxiv2016

The NDE1 Genomic Locus Affects Treatment of Psychiatric Illness through Gene Expression Changes Related to MicroRNA-484

Genetic studies of familial schizophrenia in Finland have observed significant associations with a group of biologically related genes, DISC1, NDE1, NDEL1, PDE4B and PDE4D, the \"DISC1 network\". Here, we utilize gene expression and psychoactive medication use data to study their biological consequences and potential treatment implications. Gene expression levels were determined in 64 individuals from 18 families, whilst prescription medication information has been collected over a ten-year period for 931 affected individuals. We demonstrate that the NDE1 SNP rs2242549 associates with significant changes in gene expression for 2,908 probes (2,542 genes), of which 794 probes (719 genes) were replicable. A significant number of the genes altered were predicted targets of microRNA-484 (p=3.0x10-8), located on a non-coding exon of NDE1. Variants within the NDE1 locus also displayed significant genotype by gender interaction to early cessation of psychoactive medications metabolized by CYP2C19. Furthermore, we demonstrate that miR-484 can affect the expression of CYP2C19 in a cell culture system. Thus, variation at the NDE1 locus may alter risk of mental illness, in part through modification of miR-484, and such modification alters treatment response to specific psychoactive medications, leading to the potential for use of this locus in targeting treatment.

genetics↗