The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases
Open accessAbstract
The Metabolic Syndrome in Men (METSIM) study is a population-based study including 10,197 Finnish men examined in 2005-2010. The aim of the study is to investigate nongenetic and genetic factors associated with the risk of T2D and CVD, and with cardiovascular risk factors. The protocol includes a detailed phenotyping of the participants, an oral glucose tolerance test, fasting laboratory measurements including proton NMR measurements, mass spectometry metabolomics, adipose tissue biopsies from 1,400 participants, and a stool sample. In our ongoing follow-up study, we have, to date, reexamined 6,496 participants. Extensive genotyping and exome sequencing have been performed for essentially all METSIM participants, and >2,000 METSIM participants have been whole-genome sequenced. We have identified several nongenetic markers associated with the development of diabetes and cardiovascular events, and participated in several genetic association studies to identify gene variants associated with diabetes, hyperglycemia, and cardiovascular risk factors. The generation of a phenotype and genotype resource in the METSIM study allows us to proceed toward a "systems genetics" approach, which includes statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein, or metabolite levels, to provide a global view of the molecular architecture of complex traits.
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Analysis of protein-coding genetic variation in 60,706 humans
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Self-citationGenetic studies of body mass index yield new insights for obesity biology
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Self-citationIntegrative approaches for large-scale transcriptome-wide association studies
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Self-citationLarge-scale association analysis identifies new risk loci for coronary artery disease
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Self-citationNew genetic loci link adipose and insulin biology to body fat distribution
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Self-citationGenetics of gene expression and its effect on disease
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The genetic architecture of type 2 diabetes
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Self-citationPrediction of Type 2 Diabetes using Machine Learning Classification Methods
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Loss-of-function variants in ADCY3 increase risk of obesity and type 2 diabetes
Grarup, N., Moltke, I., Andersen, M. K., Dalby, M., Vitting-Seerup, K., Kern, T., Mahendran, Y., Jørsboe, E., Larsen, C. V. L., Dahl-Petersen, I. K., et al. (2018) · Nature Genetics · doi:10.1038/s41588-017-0022-7 · Cited by 216
Fgr kinase is required for proinflammatory macrophage activation during diet-induced obesity
Acín-Pérez, R., Iborra, S., Martí-Mateos, Y., Cook, E. C. L., Conde-Garrosa, R., Petcherski, A., Muñoz, M. D. M., Martínez de Mena, R., Krishnan, K. C., Jiménez, C., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-020-00273-8 · Cited by 83
Self-citationStatins and risk of type 2 diabetes: mechanism and clinical implications
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Metadata
- Authors
- Laakso, M., Kuusisto, J., Stančáková, A., Kuulasmaa, T., Pajukanta, P., Lusis, A. J., Collins, F. S., Mohlke, K. L., & Boehnke, M.
- Venue
- Journal of Lipid Research
- Publisher
- Elsevier BV
- Published
- 2017-03
- Volume
- 58
- Issue
- 3
- Pages
- 481-493
- ISSN
- 0022-2275 (ISSN-L)
- OpenAlex
- W2581490583
- Cited by
- 204
- References
- 20
- FWCI
- 11.13
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Laakso, M., Kuusisto, J., Stančáková, A., Kuulasmaa, T., Pajukanta, P., Lusis, A. J., Collins, F. S., Mohlke, K. L., & Boehnke, M. (2017). The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases. Journal of Lipid Research. https://doi.org/10.1194/jlr.o072629
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
