Common sources of bias in gene-lifestyle interaction studies of cardiometabolic disease

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Common sources of bias in gene-lifestyle interaction studies of cardiometabolic disease. / Oskari Kilpeläinen, Tuomas.

In: Current Nutrition Reports, Vol. 2, 29.09.2013, p. 251-257.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Oskari Kilpeläinen, T 2013, 'Common sources of bias in gene-lifestyle interaction studies of cardiometabolic disease', Current Nutrition Reports, vol. 2, pp. 251-257.

APA

Oskari Kilpeläinen, T. (2013). Common sources of bias in gene-lifestyle interaction studies of cardiometabolic disease. Current Nutrition Reports, 2, 251-257.

Vancouver

Oskari Kilpeläinen T. Common sources of bias in gene-lifestyle interaction studies of cardiometabolic disease. Current Nutrition Reports. 2013 Sep 29;2:251-257.

Author

Oskari Kilpeläinen, Tuomas. / Common sources of bias in gene-lifestyle interaction studies of cardiometabolic disease. In: Current Nutrition Reports. 2013 ; Vol. 2. pp. 251-257.

Bibtex

@article{b97c32d73abe4c2f8ef72c97419496a7,
title = "Common sources of bias in gene-lifestyle interaction studies of cardiometabolic disease",
abstract = "The role of gene x lifestyle interactions in the development of cardiometabolic diseases is often highlighted, but very few robustly replicated examples of interactions exist in the literature. The slow pace of discoveries may largely be due to interaction effects being generally small in magnitude and/or more complex than initially thought. However, the progress may also be hindered by the poor accuracy in large-scale epidemiological studies to estimate the true interaction effect sizes. Often, this bias tends to underestimate the interaction effect, leading to inadequate statistical power to detect the interaction. In this review, I will discuss the most common sources of bias in the estimation of gene x lifestyle interactions, and will discuss how such factors could be addressed in the future to enhance our potential to identify and replicate interactions for cardiometabolic diseases.",
author = "{Oskari Kilpel{\"a}inen}, Tuomas",
year = "2013",
month = sep,
day = "29",
language = "English",
volume = "2",
pages = "251--257",
journal = "Current Nutrition Reports",
issn = "2161-3311",
publisher = "Springer Healthcare",

}

RIS

TY - JOUR

T1 - Common sources of bias in gene-lifestyle interaction studies of cardiometabolic disease

AU - Oskari Kilpeläinen, Tuomas

PY - 2013/9/29

Y1 - 2013/9/29

N2 - The role of gene x lifestyle interactions in the development of cardiometabolic diseases is often highlighted, but very few robustly replicated examples of interactions exist in the literature. The slow pace of discoveries may largely be due to interaction effects being generally small in magnitude and/or more complex than initially thought. However, the progress may also be hindered by the poor accuracy in large-scale epidemiological studies to estimate the true interaction effect sizes. Often, this bias tends to underestimate the interaction effect, leading to inadequate statistical power to detect the interaction. In this review, I will discuss the most common sources of bias in the estimation of gene x lifestyle interactions, and will discuss how such factors could be addressed in the future to enhance our potential to identify and replicate interactions for cardiometabolic diseases.

AB - The role of gene x lifestyle interactions in the development of cardiometabolic diseases is often highlighted, but very few robustly replicated examples of interactions exist in the literature. The slow pace of discoveries may largely be due to interaction effects being generally small in magnitude and/or more complex than initially thought. However, the progress may also be hindered by the poor accuracy in large-scale epidemiological studies to estimate the true interaction effect sizes. Often, this bias tends to underestimate the interaction effect, leading to inadequate statistical power to detect the interaction. In this review, I will discuss the most common sources of bias in the estimation of gene x lifestyle interactions, and will discuss how such factors could be addressed in the future to enhance our potential to identify and replicate interactions for cardiometabolic diseases.

M3 - Journal article

VL - 2

SP - 251

EP - 257

JO - Current Nutrition Reports

JF - Current Nutrition Reports

SN - 2161-3311

ER -

ID: 118452180