Genetic background for the major psychiatric disorders in the general Finnish population
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ABSTRACT:
PROVIDER: EGAS00001000162 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Low coverage (4-6x) sequencing on samples from population cohorts (Finrisk, Health2000) will be done at Wellcome Trust Sanger Institute (WTSI) using Illumina HiSeq sequencing technology. We will produce 100bp paired end reads. Variants will be called using the 1000 Genomes Project pipeline. The samples have been selected from a national representative set of 8028 samples from persons of 30 years or older, which were screened for psychotic and bipolar disorders using the Composite International Diagnostic Interview, self-reported diagnoses, medical examination, and national registers.
| EGAD00001001250 | EGA
Project description:Low coverage (4-6x) sequencing on samples from population cohorts (Finrisk, Health2000) will be done at Wellcome Trust Sanger Institute (WTSI) using Illumina HiSeq sequencing technology. We will produce 100bp paired end reads. Variants will be called using the 1000 Genomes Project pipeline. The samples have been selected from a national representative set of approximately 30,300 samples and comprises 500 individuals of each gender in the extreme tail of high density lipoprotein (HDL) concentrations. Included individuals were between 25 and 65 years of age. Individuals with a diagnosis of diabetes or BMI>30 were excluded from the study.
| EGAS00001000229 | EGA
Project description:Whole Genome Sequencing in Psychotic Major Depression
| PRJNA476193 | ENA
Project description:Whole Genome Sequencing in Psychotic Major Depression
| PRJNA476194 | ENA
Project description:<p>We propose to undertake, at the McDonnell Genome Institute of Washington University, a collaborative exome sequencing project of ~10,000 samples from a large Finnish population cohort, FINRISK, a participating component of the Sequencing Initiative Suomi (SISu) consortium. Together these sequenced samples will provide a unique resource for identification of infrequent or rare variants with a large impact on cardiovascular and metabolic disorders as well as on a wide range of heritable, disease-related quantitative phenotypes. Our collaborative group has already shown, in exome sequencing studies of smaller Finnish samples, that numerous loss of function variants are dramatically more frequent in Finland compared to other European populations, and that such variants demonstrate strong associations to several disease-related traits. Finland is the largest population isolate in Europe and the enrichment of these variants reflects its rapid growth from a severe population bottleneck about 100 generations ago.</p> <p>Northern and Eastern parts of Finland experienced additional, more recent bottlenecks, and therefore the enrichment of particular high-impact variants in these regions is even more extreme (Stoll et al., 2013, PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/23912948" target="_blank">23912948</a>). We therefore propose to focus exome sequencing efforts on about 10,000 members of FINRISK who are specifically drawn from these sub-isolate regions. As a very wide range of phenotypes are available from this cohort (including cardiovascular and metabolic disease outcomes obtained from national registries) we hypothesize that the proposed exome sequencing will identify numerous new disease-related associations. Within the National Biobanks of Finland (<a href="http://www.nationalbiobanks.fi/" target="_blank">www.nationalbiobanks.fi</a>) we have DNA and tissue samples from over 200,000 individuals of whom 50,000 have GWAS data; these samples provide an exceptional resource for both imputation from the sequencing studies proposed here, as well as for replication of associations.</p>
| phs000756 | dbGaP
Project description:Mental disorders have been shown to be associated with a number of general medical conditions (also referred to as somatic or physical conditions). The investigators aim to undertake a comprehensive study of comorbidity among those with treated mental disorders, by using high-quality Danish registers to provide age- and sex-specific pairwise estimates between the ten groups of mental disorders and nine groups of general medical conditions.
The investigators will examine the association between all 90 possible pairs of prior mental disorders and later GMC categories using the Danish national registers. Depending on whether individuals are diagnosed with a specific mental disorder, the investigators will estimate the risk of receiving a later diagnosis within a specific GMC category, between the start of follow-up (January 1, 2000) or at the earliest age at which a person might develop the mental disorder, whichever comes later. Follow-up will be terminated at onset of the GMC, death, emigration from Denmark, or December 31, 2016, whichever came first. Additionally for dyslipidemia, follow-up will be ended if a diagnosis of ischemic heart disease was received. A "wash-out" period will be employed in the five years before follow-up started (1995-1999), to identify and exclude prevalent cases from the analysis. Individuals with the GMC of interest before the observation period will be considered prevalent cases and excluded from the analyses (i.e. prevalent cases were "washed-out"). When estimating the risk of a specific GMC, the investigators will consider all individuals to be exposed or unexposed to the each mental disorder depending on whether a diagnosis is received before the end of follow-up. Persons will be considered unexposed to a mental disorder until the date of the first diagnosis, and exposed thereafter.
| 2297710 | ecrin-mdr-crc
Project description:<p>The goal of this case-control study, "Whole Genome Sequencing in Psychotic Major Depression", is to identify genes that contribute to the psychotic major depression phenotype. The samples herein were used as controls and were obtained from the NIMH Repository Study #108, "Sustaining Remission of Psychotic Depression".</p>
| phs001625 | dbGaP
Project description:To identify risk factors for experiencing nightmares among the Finnish general adult population. The study aimed to both test whether previously reported correlates of frequent nightmares could be reproduced in a large population sample and to explore previously unreported associations.Two independent cross-sectional population surveys of the National FINRISK Study.Age- and sex-stratified random samples of the Finnish population in 2007 and 2012.A total of 13,922 participants (6,515 men and 7,407 women) aged 25-74 y.N/A.Nightmare frequency as well as several items related to socioeconomic status, sleep, mental well-being, life satisfaction, alcohol use, medication, and physical well-being were recorded with a questionnaire. In multinomial logistic regression analysis, a depression-related negative attitude toward the self (odds ratio [OR] 1.32 per 1-point increase), insomnia (OR 6.90), and exhaustion and fatigue (OR 6.86) were the strongest risk factors for experiencing frequent nightmares (P < 0.001 for all). Sex, age, a self-reported impaired ability to work, low life satisfaction, the use of antidepressants or hypnotics, and frequent heavy use of alcohol were also strongly associated with frequent nightmares (P < 0.001 for all).Symptoms of depression and insomnia were the strongest predictors of frequent nightmares in this dataset. Additionally, a wide variety of factors related to psychological and physical well-being were associated with nightmare frequency with modest effect sizes. Hence, nightmare frequency appears to have a strong connection with sleep and mood problems, but is also associated with a variety of measures of psychological and physical well-being.
| S-EPMC4355890 | biostudies-literature
Project description:Individuals with a later chronotype (evening types) tend to have unhealthier behaviors and increased morbidity and mortality as compared with those with an earlier chronotype (morning types). However, the role of genetics in explaining evening types' adverse health and health behavior is unclear. Our aim was to study genetic associations of chronotype among 8433 Finns from the cross-sectional National FINRISK 2007 and 2012 studies. First, we studied associations between chronotype and 20 key clock genes with a candidate-gene approach and then performed a full genome-wide association study (GWAS) of chronotype. We also developed a genetic risk score (GRS) for chronotype based on 313 single nucleotide polymorphisms (SNPs) that have previously been associated with chronotype. Chronotype was assessed with a shortened version of Horne and Östberg's Morningness-Eveningness Questionnaire (sMEQ), and for comparison, we also used the single self-evaluation question on chronotype from the questionnaire. Linear and logistic regression was used for statistical analysis assuming additive effects. The clock gene analysis revealed 1 independent association signal within NR1D2 (lead SNP rs4131403) that was associated with chronotype (p < 0.05; as based on both chronotype assessment methods). The GWAS analysis did not yield any genome-wide significant associations (p > 5 × 10-8). However, higher GRS was associated with evening chronotype (p < 0.001; as based on both chronotype assessment methods). In conclusion, our findings indicated novel genetic associations between chronotype and the NR1D2 clock gene, which has previously been associated with carbohydrate and lipid metabolism. Furthermore, the GRS was able to capture the genetic aspect of chronotype in our study population. These findings expand our knowledge of the genetic basis of chronotype.
| S-EPMC7534025 | biostudies-literature