Krumsiek, Jan

An atlas of genetic influences on human blood metabolites

The Multiple Tissue Human Expression Resource (MuTHER) Consortium, Shin, S.-Y., Fauman, E. B., Petersen, A.-K., Krumsiek, J., Santos, R., Huang, J., Arnold, M., Erte, I., Forgetta, V., et al. (2014) · Nature Genetics

Genetic Associations and EpidemiologyMetabolomics and Mass Spectrometry Studies

Cited by 1,515

The dynamic range of the human metabolome revealed by challenges

Krug, S., Kastenmüller, G., Stückler, F., Rist, M. J., Skurk, T., Sailer, M., Raffler, J., Römisch‐Margl, W., Adamski, J., Prehn, C., et al. (2012) · The FASEB Journal

Metabolomics and Mass Spectrometry StudiesHealth, Environment, Cognitive Aging

Cited by 327

The gut microbiota promotes hepatic fatty acid desaturation and elongation in mice

Kindt, A., Liebisch, G., Clavel, T., Haller, D., Hörmannsperger, G., Yoon, H., Kolmeder, D., Sigruener, A., Krautbauer, S., Seeliger, C., et al. (2018) · Nature Communications

Gut microbiota and healthLipid metabolism and biosynthesis

Cited by 311

Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease

Baloni, P., Funk, C. C., Yan, J., Yurkovich, J. T., Kueider-Paisley, A., Nho, K., Heinken, A., Jia, W., Mahmoudiandehkordi, S., Louie, G., et al. (2020) · Cell Reports Medicine

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 211

A metabolome-wide association study of kidney function and disease in the general population

Sekula, P., Goek, O.-N., Quaye, L., Barrios, C., Levey, A. S., Römisch-Margl, W., Menni, C., Yet, I., Gieger, C., Inker, L. A., et al. (2016) · Journal of the American Society of Nephrology

Metabolomics and Mass Spectrometry StudiesChronic Kidney Disease and Diabetes

Cited by 203

Sex and APOE ε4 genotype modify the Alzheimer’s disease serum metabolome

Arnold, M., Nho, K., Kueider-Paisley, A., Massaro, T., Huynh, K., Brauner, B., MahmoudianDehkordi, S., Louie, G., Moseley, M. A., Thompson, J. W., et al. (2020) · Nature Communications

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Cited by 202

Mining the Unknown: A Systems Approach to Metabolite Identification Combining Genetic and Metabolic Information

Krumsiek, J., Suhre, K., Evans, A. M., Mitchell, M. W., Mohney, R. P., Milburn, M. V., Wägele, B., Römisch-Margl, W., Illig, T., Adamski, J., et al. (2012) · PLoS Genetics

Metabolomics and Mass Spectrometry StudiesBioinformatics and Genomic Networks

Cited by 197

Intermuscular adipose tissue directly modulates skeletal muscle insulin sensitivity in humans

Sachs, S., Zarini, S., Kahn, D. E., Harrison, K. A., Perreault, L., Phang, T., Newsom, S. A., Strauss, A., Kerege, A., Schoen, J. A., et al. (2019) · American Journal of Physiology-Endocrinology and Metabolism

Adipokines, Inflammation, and Metabolic DiseasesAdipose Tissue and Metabolism

Cited by 192

Integrative metabolomics‐genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease

Horgusluoglu, E., Neff, R., Song, W., Wang, M., Wang, Q., Arnold, M., Krumsiek, J., Galindo‐Prieto, B., Ming, C., Nho, K., et al. (2022) · Alzheimer's & Dementia

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 175

Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: a prospective study in children

Bonifacio, E., Beyerlein, A., Hippich, M., Winkler, C., Vehik, K., Weedon, M. N., Laimighofer, M., Hattersley, A. T., Krumsiek, J., Frohnert, B. I., et al. (2018) · PLOS Medicine

Diabetes and associated disordersGenetic Associations and Epidemiology

Cited by 148

A strategy for combining minor genetic susceptibility genes to improve prediction of disease in type 1 diabetes

Winkler, C., Krumsiek, J., Lempainen, J., Achenbach, P., Grallert, H., Giannopoulou, E., Bunk, M., Theis, F. J., Bonifacio, E., & Ziegler, A.-G. (2012) · Genes & Immunity

Diabetes and associated disordersGenetic Associations and Epidemiology

Cited by 68

Exploring the molecular basis of age-related disease comorbidities using a multi-omics graphical model

Zierer, J., Pallister, T., Tsai, P.-C., Krumsiek, J., Bell, J. T., Lauc, G., Spector, T. D., Menni, C., & Kastenmüller, G. (2016) · Scientific Reports

Bioinformatics and Genomic NetworksGenetics, Aging, and Longevity in Model Organisms

Cited by 63

Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Jo, T., Kim, J., Bice, P., Huynh, K., Wang, T., Arnold, M., Meikle, P. J., Giles, C., Kaddurah-Daouk, R., Saykin, A. J., et al. (2023) · eBioMedicine

Dementia and Cognitive Impairment ResearchMetabolomics and Mass Spectrometry Studies

Cited by 15