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Articles by Emil Uffelmann
Distinguishing different psychiatric disorders using DDx-PRS
Abstract Despite great progress on case–control polygenic prediction, an unmet need remains for a method that genetically distinguishes clinically related disorders (e.g., schizophrenia (SCZ) versus bipolar disorder (BIP) versus major depressive disorder (MDD) versus controls).
Genomic analyses reveal new insights into Alzheimer's disease
DR served as consultant for Boehringer-Ingelheim and Janssen, received honoraria from Boehringer-Ingelheim, Gerot Lannacher, Indorsia, Janssen and Pharmagenetix, received research/ travel support from Angelini, Boehringer-Ingelheim, Janssen and Schwabe, and served on advisory boards of AC Immune, Boehringer-Ingelheim, Indorsia, Roche and Rovi.
Local genetic sex differences in quantitative traits - Nature Communications
Abstract Many traits show small global sex differences in genetic correlations and heritability. However, how these differences are distributed across the genome remains unknown. Here, we use LAVA to test for local genetic sex differences in genetic correlations, heritabilities, and the magnitude of genetic effects across 157 quantitative traits in the UK Biobank. Nearly every trait shows evidence for sex-dimorphic effects in at least one locus.
Local Genetic Sex Differences in Quantitative Traits
Abstract Many traits show small global sex differences in genetic correlations and heritability. However, how these differences are distributed across the genome remains unknown. Here, we use LAVA to test for local genetic sex differences in genetic correlations, heritabilities, and the magnitude of genetic effects across 157 quantitative traits in the UK Biobank. Nearly every trait shows evidence for sex-dimorphic effects in at least one locus.
Local Genetic Sex Differences in Quantitative Traits
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Genome-wide association studies of polygenic risk score-derived phenotypes may lead to inflated false positive rates - Scientific Reports
Introduction arising from: C. Gouveia et al.; Scientific Reports https://doi.org/10.1038/s41598-022-12391-2 (2022). Gouveia and colleagues (2022)1 conducted a genome-wide association study (GWAS) of a polygenic risk score (PRS)-derived phenotype (N = 37,784), in which they identified 246 independent loci and 473 lead SNPs. This is an enormous increase compared to the most recent and largest GWAS of AD2 (N = 1,126,563), which identified 38 loci.
Genome-wide association studies of polygenic risk score-derived phenotypes may lead to inflated false positive rates
Contradictory Results doi: https://doi.org/10.1101/2022.09.10.507410 Abstract In a recent study, a polygenic risk score (PRS) for Alzheimer's disease was used to construct a new phenotype for a subsequent genome-wide association study (GWAS). Here we show that the applied method, in which the same genetic variants are used to construct the PRS-derived phenotype as well as to assess their effect in a GWAS of the same phenotype, leads to inflated false positive rates.
Uncovering the Genetic Architecture of Broad Antisocial Behavior through a Genome-Wide Association Study Meta-analysis.
New Results Jorim J Tielbeek, Emil Uffelmann, Benjamin S Williams, Lucia Colodro-Conde, Eloi Gagnon, Travis T Mallard, Brandt E Levitt, Philip R Jansen, Ada Johansson, View ORCID ProfileHannah M Sallis, Giorgio Pistis, Gretchen RB Saunders, Andrea G Allegrini, View ORCID ProfileKaili Rimfeld, Bettina Konte, Marieke Klein, View ORCID ProfileAnnette M Hartmann, Jessica E Salvatore, Ilja M Nolte, Ditte Demontis, Anni Malmberg, S.
Genome-wide association studies - Nature Reviews Methods Primers
Abstract Genome-wide association studies (GWAS) test hundreds of thousands of genetic variants across many genomes to find those statistically associated with a specific trait or disease. This methodology has generated a myriad of robust associations for a range of traits and diseases, and the number of associated variants is expected to grow steadily as GWAS sample sizes increase.
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