Publications by authors named "Kajsa-Lotta Georgii Hellberg"

The NRXN1 locus is a hotspot for non-recurrent copy number variants and exon-disrupting NRXN1 deletions have been associated with increased risk of neurodevelopmental disorders in case-control studies. However, corresponding population-based estimates of prevalence and disease-associated risk are currently lacking. Also, most studies have not differentiated between deletions affecting exons of different NRXN1 splice variants nor considered intronic deletions.

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Article Synopsis
  • Large biobank samples allow researchers to combine detailed family histories and genetic data to investigate complex diseases.
  • The study introduces a new method called Pearson-Aitken Family Genetic Risk Scores (PA-FGRS) to estimate disease risk based on family medical histories.
  • Applying PA-FGRS to major depressive disorder (MDD) shows improved understanding of genetic factors and clinical variability, and enhances the effectiveness of genetic studies across different complex conditions.
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The impact of rare recurrent copy number variants (rCNVs) and polygenic background attributed to common variants, on the risk of psychiatric disorders is well-established in separate studies. However, it remains unclear how polygenic background modulates the effect of rCNVs. Using the population-representative iPSYCH2015 case-cohort sample (N=96,599), we investigated the association between absolute risk of psychiatric disorders and carriage of rCNVs and polygenic scores (PGS), as well as the interaction effect between the two on disease risk.

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Importance: Recurrent copy number variants (rCNVs) have been associated with increased risk of psychiatric disorders in case-control studies, but their population-level impact is unknown.

Objective: To provide unbiased population-based estimates of prevalence and risk associated with psychiatric disorders for rCNVs and to compare risks across outcomes, rCNV dosage type (deletions or duplications), and locus features.

Design, Setting, And Participants: This genetic association study is an analysis of data from the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) case-cohort sample of individuals born in Denmark in 1981-2008 and followed up until 2015, including (1) all individuals (n = 92 531) with a hospital discharge diagnosis of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder, major depressive disorder (MDD), or schizophrenia spectrum disorder (SSD) and (2) a subcohort (n = 50 625) randomly drawn from the source population.

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Large-scale genome-wide association studies (GWAS) strongly suggest that most traits and diseases have a polygenic component. This observation has motivated the development of disease-specific "polygenic scores (PGS)" that are weighted sums of the effects of disease-associated variants identified from GWAS that correlate with an individual's likelihood of expressing a specific phenotype. Although most GWAS have been pursued on disease traits, leading to the creation of refined "Polygenic Risk Scores" (PRS) that quantify risk to diseases, many GWAS have also been pursued on extreme human longevity, general fitness, health span, and other health-positive traits.

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Article Synopsis
  • Accurately diagnosing bipolar disorder (BD) can take around 7 years due to its overlap with unipolar major depressive disorder (MDD), especially since the first manic episode often follows a depressive one.
  • This study uses genome-wide association analyses (GWAS) and polygenic risk scores (PRS) from a large cohort to identify genetic factors that could help differentiate between BD and MDD early on.
  • The results show that while BD and MDD are genetically distinct and share a continuum of genetic risk, larger future studies are needed to enhance the accuracy of these genetic predictors for early diagnosis.
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Recurrent copy number variants (rCNVs) are associated with increased risk of neuropsychiatric disorders but their pathogenic population-level impact is unknown. We provide population-based estimates of rCNV-associated risk of neuropsychiatric disorders for 34 rCNVs in the iPSYCH2015 case-cohort sample (n=120,247). Most observed significant increases in rCNV-associated risk for ADHD, autism or schizophrenia were moderate (HR:1.

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