Tune H. Pers
- Genetic Associations and Epidemiology
- Adipose Tissue and Metabolism
- Regulation of Appetite and Obesity
- Nutrition, Genetics, and Disease
- Bioinformatics and Genomic Networks
- Genetics and Neurodevelopmental Disorders
- Single-cell and spatial transcriptomics
- Genetic Mapping and Diversity in Plants and Animals
- Epigenetics and DNA Methylation
- Adipokines, Inflammation, and Metabolic Diseases
- RNA modifications and cancer
- Diet and metabolism studies
- Migraine and Headache Studies
- Pancreatic function and diabetes
- Genetic and phenotypic traits in livestock
- Genomics and Rare Diseases
- Genetic factors in colorectal cancer
- Genomic variations and chromosomal abnormalities
- Neuroinflammation and Neurodegeneration Mechanisms
- Liver Disease Diagnosis and Treatment
- Health, Environment, Cognitive Aging
- interferon and immune responses
- Birth, Development, and Health
- Gene expression and cancer classification
- Biochemical Analysis and Sensing Techniques
Novo Nordisk Foundation
2016-2025
University of Copenhagen
2016-2025
Broad Institute
2013-2024
Foundation Center
2019-2024
Novo Nordisk (United States)
2023-2024
Novo Nordisk Foundation Center for Basic Metabolic Research
2019-2021
Statens Serum Institut
2015-2021
Boston University
2015-2021
Boston Children's Hospital
2013-2020
Technical University of Denmark
2009-2017
We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects established a reference map the architecture MS that includes 200 autosomal susceptibility variants outside major histocompatibility complex (MHC), one chromosome X variant, 32 within extended MHC. used an ensemble methods to prioritize 551 putative genes implicate innate adaptive pathways distributed across cellular components immune system. Using expression profiles from purified human microglia, we...
The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize most likely causal at associated loci, highlight enriched identify tissues/cell types where loci are highly expressed. DEPICT not limited with established prioritizes relevant sets many phenotypes.
To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects European ancestry after imputation using 1000 Genomes multiethnic reference panel. Promising signals were followed up in additional sets (of 14,545 or 7,397 38,994 71,604 subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near GLP2R, GIP, HLA-DQA1...
Abstract We conduct a genome-wide association study (GWAS) of educational attainment (EA) in sample ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A polygenic predictor, or index (PGI), explains 12–16% EA variance contributes to risk prediction for ten diseases. Direct effects (i.e., controlling parental PGIs) explain roughly half the PGI’s magnitude with other phenotypes. The correlation between mate-pair...
There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into best practices in the areas of sequence data generation, analysis, interpretation reporting. The CLARITY Challenge was designed spur convergence diagnosing genetic disease starting from case history data. DNA samples were obtained three families with heritable disorders genomic donated by platform vendors....
Identifying Important Identifiers Each of us has millions sequence variations in our genomes. Signatures purifying or negative selection should help identify which those is functionally important. Khurana et al. ( 1235587 ) used polymorphisms from 1092 humans across 14 populations to patterns selection, especially noncoding regulatory regions. Noncoding regions under very strong included binding sites some chromatin and general transcription factors (TFs) core motifs important TF families....