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Terho Lehtimäki

Researcher at University of Tampere

Publications -  1375
Citations -  129159

Terho Lehtimäki is an academic researcher from University of Tampere. The author has contributed to research in topics: Population & Genome-wide association study. The author has an hindex of 142, co-authored 1304 publications receiving 106981 citations. Previous affiliations of Terho Lehtimäki include Boston University & National Institutes of Health.

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Indoleamine 2,3-dioxygenase activation and depressive symptoms: results from the Young Finns Study.

TL;DR: Data suggest that IDO activity may be a risk factor for future depression especially in women, and IDO-induced alterations in serotonergic function may offer one biologic explanation to the well-established associations between inflammation and depression.
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Variability gene effects of DNA polymorphisms at the apo B, apo A I/C III and apo E loci on serum lipids: the Cardiovascular Risk in Young Finns Study.

TL;DR: Many of the presently known DNA polymorphisms of the coronary heart disease candidate gene loci also influence intraindividual variability of serum lipid or lipoprotein levels, and can be used to further refine the ability to predict the risk of a cardiovascular event.
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SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function

Man Li, +163 more
TL;DR: A two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine among participants of European ancestry from the CKDGen Consortium identifies novel genes with potential roles in kidney formation.
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Model selection for metabolomics: predicting diagnosis of coronary artery disease using automated machine learning.

TL;DR: It is demonstrated that the phenotypic profile that distinguishes non-obstructive CAD patients from no CAD patients is associated with higher precision, suggesting a discrepancy in the underlying processes between these phenotypes.
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The Effect of Weight on Labor Market Outcomes: an Application of Genetic Instrumental Variables

TL;DR: In this article, the authors used genetic risk score, which reflects the predisposition to higher body mass index across many genetic loci, to estimate IV models of the effect of BMI on labor market outcomes.