Smoking-Related Metabolic Changes Partly Drive Type 2 Diabetes Risk

— Those with the most metabolic changes, genetic risk had a threefold higher diabetes risk

by
Kristen Monaco, Senior Staff Writer, MedPage Today
October 6, 2023

HAMBURG, Germany — Smokers were more likely to have a specific metabolic signature that mediated their risk for developing type 2 diabetes, a researcher reported here.

In a study of nearly 94,000 people in the U.K. Biobank, smoking was tied with a 73% higher risk for developing type 2 diabetes compared with no smoking (HR 1.73, 95% CI 1.54-1.94), largely driven by smoking-related changes in metabolism, reported Yuxia Wei, a PhD student at the Karolinska Institutet in Sweden, at the European Association for the Study of Diabetes annual meeting.

Smokers with a high level of a particular metabolic signature had a 61% excess risk for diabetes development compared with those with a low level of this signature (HR 1.61, 95% CI 1.46-1.77).

“The high level of this metabolic signature could explain up to 38% of the excess risk of type 2 diabetes in smokers,” Wei noted. This explained 44% of the excess risk in men and 30% of the excess risk in women.

Smoking affects several physical aspects related to metabolism, Wei explained, and these metabolic changes can subsequently put the smoker at a higher susceptibility to diabetes.

Wei’s group highlighted 131 various metabolites that are affected by smoking confirmed via Mendelian randomization analyses. For example, smokers tended to have higher levels of triglycerides, very-low-density lipoprotein (VLDL) cholesterol concentrations and diameters, saturated and monounsaturated fatty acids, and glycoprotein acetyls — a marker of inflammation — and lower levels of docosahexaenoic acid (DHA), omega-6 and -3 fatty acids, and high-density lipoprotein (HDL) cholesterol.

Additionally, smokers with a high-level metabolic signature and a high genetic risk score for type 2 diabetes had a more than threefold higher risk for developing diabetes compared with those with a low-low risk pairing (HR 3.18, 95% CI 2.46-4.12). In addition, those with a high metabolic signature and high genetic risk score for insulin resistance had a more than twofold higher risk for diabetes (HR 2.18, 95% CI 1.74-2.75).

Having a high genetic risk score for type 2 diabetes appeared to impact the risk for diabetes development more than a high metabolic signature alone:

  • High genetic risk/low metabolic signature: HR 1.82 (95% CI 1.38-2.40)
  • Low genetic risk/high metabolic signature: HR 1.52 (95% CI 1.14-2.01)

Wei said that these associations were validated in another cohort by creating a metabolic signature using TwinGene study participants from Sweden, including 3,626 individuals. Here, there was a trend towards a higher risk for developing type 2 diabetes among smokers, though this didn’t reach statistical significance (HR 1.29, 95% CI 0.97-1.72). However, smokers who carried a high-level metabolic signature had a significantly higher risk for diabetes than those with a low-level signature (HR 1.34, 95% CI 1.04-1.74).

This high-level signature explained an excess risk of type 2 diabetes of 55% in smokers, she noted.

These findings only add to the argument that people should avoid smoking for diabetes prevention, Wei concluded.

The U.K. Biobank cohort included individuals ages 37 to 73 followed for a median of 13 years. Of the 93,722 individuals included, there were 1,869 new cases of diabetes identified. They were screened for 249 metabolites.

  • author['full_name']

    Kristen Monaco is a senior staff writer, focusing on endocrinology, psychiatry, and nephrology news. Based out of the New York City office, she’s worked at the company since 2015.

Disclosures

This study was supported by the Swedish Research Council, FORTE, the Novo Nordisk Foundation, and the China Scholarship Council.

Wei reported no disclosures.

Primary Source

European Association for the Study of Diabetes

Source Reference: Wei Y, et al “Metabolic profiling of smoking, associations with type 2 diabetes and interaction with genetic susceptibility” EASD 2023; Poster 322.

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