Mika Ala-Korpela

发表

A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic data

Aki Vehtari, Kimmo Kaski, Ville-Petteri Mäkinen, 2007, BMC Bioinformatics.

Proof of concept for quantitative urine NMR metabolomics pipeline for large-scale epidemiology and genetics

Minna Männikkö, Michael Hill, Michael V Holmes, 2019, International journal of epidemiology.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

Matti Pirinen, Juho Rousu, Anna Cichonska, 2015, bioRxiv.

EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics

Terho Lehtimäki, Mika Ala-Korpela, Mari Karsikas, 2020, International journal of epidemiology.

Efficient Estimation and Applications of Cross-Validated Genetic Predictions to Polygenic Risk Scores and Linear Mixed Models

Jian Yang, Arthur Ko, Päivi Pajukanta, 2020, J. Comput. Biol..

Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression

Matti Pirinen, Samuel Kaski, Jussi Gillberg, 2014, Bioinform..

Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons

Toomas Haller, Andres Metspalu, Markus Perola, 2014, PLoS medicine.

Three-Dimensional cryoEM Reconstruction of Native LDL Particles to 16Å Resolution at Physiological Body Temperature

Jukka Heikkonen, Kimmo Kaski, Peter Engelhardt, 2011, PloS one.

Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis

Niku Oksala, Markus Perola, Michael Inouye, 2012, PLoS genetics.

Identification of seven novel loci associated with amino acid levels using single-variant and gene-based tests in 8545 Finnish men from the METSIM study

Vilmundur Gudnason, Christian Fuchsberger, Tanya M. Teslovich, 2018, Human molecular genetics.

Upstream Transcription Factor 1 (USF1) allelic variants regulate lipoprotein metabolism in women and USF1 expression in atherosclerotic plaque

Niku Oksala, Thomas Illig, Terho Lehtimäki, 2014, Scientific Reports.

Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: towards metabolomics diagnostics.

Age K Smilde, Jildau Bouwman, John P M van Duynhoven, 2012, Omics : a journal of integrative biology.

Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts.

Tom R. Gaunt, Jari Kaikkonen, Debbie A Lawlor, 2015, Circulation.

A Differential Network Approach to Exploring Differences between Biological States: An Application to Prediabetes

Taru Tukiainen, Pasi Soininen, Mika Ala-Korpela, 2011, PloS one.

Design and Implementation of Intelligent Cross Media Services in a Modern Information Society

Yrjö Hiltunen, Kari Heikkinen, Mika Ala-Korpela, 2002 .

Metabolomic Profiling of Statin Use and Genetic Inhibition of HMG-CoA Reductase

Alun D. Hughes, Markus Perola, Nish Chaturvedi, 2016, Journal of the American College of Cardiology.

Hyperglycemia and a Common Variant of GCKR Are Associated With the Levels of Eight Amino Acids in 9,369 Finnish Men

Jussi Paananen, Johanna Kuusisto, Päivi Pajukanta, 2012, Diabetes.

High-throughput quantification of circulating metabolites improves prediction of subclinical atherosclerosis.

Reino Laatikainen, Jari Laurikka, Terho Lehtimäki, 2012, European heart journal.

Genome metabolome integrated network analysis to uncover connections between genetic variants and complex traits: an application to obesity

Timothy M. D. Ebbels, Pasi Soininen, Mika Ala-Korpela, 2014, Journal of The Royal Society Interface.

The inherent accuracy of 1H NMR spectroscopy to quantify plasma lipoproteins is subclass dependent.

Kimmo Kaski, Reino Laatikainen, Károly Héberger, 2007, Atherosclerosis.

Genetic Variants in Novel Pathways Influence Blood Pressure and Cardiovascular Disease Risk

Christian Gieger, Xiaofeng Zhu, Paolo Vineis, 2011, Nature.

Lipoprotein subclass profiling reveals pleiotropy in the genetic variants of lipid risk factors for coronary heart disease: a note on Mendelian randomization studies.

Terho Lehtimäki, Mika Kähönen, Pasi Soininen, 2013, Journal of the American College of Cardiology.

Genome-wide association study identifies multiple loci influencing human serum metabolite levels

Markus Perola, Kaisa Silander, Michael Inouye, 2012, Nature Genetics.

A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context

Noah Zaitlen, Hugues Aschard, Hanna Julienne, 2019, Nature Communications.

Metabolic diversity of progressive kidney disease in 325 patients with type 1 diabetes (the FinnDiane Study).

Kimmo Kaski, Tomi Peltola, Reino Laatikainen, 2012, Journal of proteome research.

Critical evaluation of 1H NMR metabonomics of serum as a methodology for disease risk assessment and diagnostics

Mika Ala-Korpela, M. Ala-Korpela, 2008, Clinical chemistry and laboratory medicine.

Metabonomic, transcriptomic, and genomic variation of a population cohort

Markus Perola, Kaisa Silander, Michael Inouye, 2010, Molecular systems biology.

Branched-Chain and Aromatic Amino Acids Are Predictors of Insulin Resistance in Young Adults

Terho Lehtimäki, Mika Kähönen, Pasi Soininen, 2013, Diabetes Care.

Sphingomyelinase Induces Aggregation and Fusion, but Phospholipase A2 Only Aggregation, of Low Density Lipoprotein (LDL) Particles

Arto Annila, Petri T. Kovanen, Mika Ala-Korpela, 1998, The Journal of Biological Chemistry.

Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma

Christian Gieger, Yusuke Nakamura, Philippe Froguel, 2011, Nature Genetics.

Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies

Debbie A Lawlor, Pasi Soininen, Mika Ala-Korpela, 2017, American journal of epidemiology.

Metabolic Signatures of Adiposity in Young Adults: Mendelian Randomization Analysis and Effects of Weight Change

Samuli Ripatti, Kirsi H. Pietiläinen, Veikko Salomaa, 2014, PLoS medicine.

Quantitative high-throughput metabolomics: a new era in epidemiology and genetics

Pasi Soininen, Mika Ala-Korpela, Antti J Kangas, 2012, Genome Medicine.

STRUCTURAL CHANGES OF LIPOPROTEIN LIPIDS BY 1H NMR

Markku J. Savolainen, Mika Ala-Korpela, M. Savolainen, 1995 .

Metabolic Signatures of Insulin Resistance in 7,098 Young Adults

Tuija Tammelin, Taru Tukiainen, Samuli Ripatti, 2012, Diabetes.

1H NMR spectroscopy of human blood plasma

Mika Ala-Korpela, M. Ala-Korpela, 1995 .

Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics.

Pasi Soininen, Mika Ala-Korpela, Antti J Kangas, 2015, Circulation. Cardiovascular genetics.

A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals

Andres Metspalu, Fotios Drenos, Markus Perola, 2019, Nature Communications.

A multi-metabolite analysis of serum by 1H NMR spectroscopy: early systemic signs of Alzheimer's disease.

Aki Vehtari, Kimmo Kaski, Olli Gröhn, 2008, Biochemical and biophysical research communications.

Detailed metabolic and genetic characterization reveals new associations for 30 known lipid loci.

Kimmo Kaski, Markus Perola, Taru Tukiainen, 2012, Human molecular genetics.

High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism.

Reino Laatikainen, Taru Tukiainen, Terho Lehtimäki, 2009, The Analyst.

Sex hormone-binding globulin associations with circulating lipids and metabolites and the risk for type 2 diabetes: observational and causal effect estimates.

Markus Perola, Veikko Salomaa, Terho Lehtimäki, 2015, International journal of epidemiology.

Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis

Tom M Palmer, Michael V Holmes, Brian A Ference, 2020, PLoS medicine.