Higher plasma caffeine levels linked to reduced body fat and type 2 diabetes risk according to genetic study

23rd March 2023

Increased plasma caffeine levels may help reduce body mass index as well as fat mass and the risk of developing type 2 diabetes.

A higher plasma caffeine (PC) concentration may produce a lower body mass index (BMI) as well as reducing body fat and the risk of type 2 diabetes, according to the findings of a genetic study by Swedish and UK researchers.

Caffeinated beverages such as coffee, tea and soda drinks are widely consumed across the world. Given that caffeine has a known thermogenic effect and which might help lower body weight, there is the potential that caffeine-containing beverages may have a role in lowering the risk of disease related to adiposity.

In fact, there is already some data to suggest that caffeine-containing drinks such as coffee are inversely associated with risk of type 2 diabetes.

It is recognised the caffeine metabolism occurs mainly in the liver by the cytochrome P450 isoform 1A2 (CYP1A2) and how genetic variations near two genes, CYP1A2 and AHR (which regulates the expression of CYP1A2) are linked to PC concentrations. In fact, individuals with genetic variants linked to slower caffeine metabolism, although generally consuming less caffeine-related beverages, do have higher plasma caffeine levels.

Using Mendelian randomisation, researchers sought to investigate the effects of long-term exposure to higher plasma caffeine concentrations on adiposity, type 2 diabetes and major cardiovascular diseases. 

They used data from a genome-wide association meta-analysis of 9876 individuals of European ancestry from six population-based studies and which identified genome-wide significant associations of single nucleotide polymorphisms near CYP1A2 and AHR loci with plasma caffeine concentrations.

Plasma caffeine and adiposity-related outcomes

Researchers identified that genetically predicted higher PC concentrations in those carrying the two gene variants, were in fact, associated with a lower BMI, with one standard deviation (SD) increase in predicted PC equal to about 4.8 kg/m² in BMI (p < 0.001).

Similarly, for whole-body fat mass, one SD increase in PC equated to a reduction of about 9.5 kg (p < 0.001), although interestingly, there was no association with fat-free body mass (p= 0.17).

Again among genetically predicted higher PC concentrations, there were also significant and lower associations with the risk of developing type 2 diabetes, with the combined odds ratio of type 2 diabetes per SD increase in PC concentration being 0.81 (95% CI 0.74 – 0.89, p < 0.001).

The authors concluded that while their study found evidence of a causal association between a higher plasma caffeine concentration and lower levels of adiposity and a reduced risk of type 2 diabetes, they called for randomised trials to further examine the role of caffeine in reducing the risk of obesity and diabetes.

Citation
Larrson SC et al. Appraisal of the causal effect of plasma caffeine on adiposity, type 2 diabetes, and cardiovascular disease: two sample mendelian randomisation study. BMJ 2023.

Genetic risk score could improve triage of men with suspected prostate cancer

19th August 2022

A higher genetic risk score in symptomatic men is significantly associated with the development of prostate cancer over the next 2 years

Use of a genetic risk score (GRS) in men with symptoms suggestive of prostate cancer could enable the identification of those at risk and fast track them for further investigation according to the results of a study by UK researchers using a cohort from the UK Biobank database.

Prostate cancer was responsible for 1.4 million global cases in 2020 and is the 2nd most commonly occurring cancer in men. Screening for the cancer may help to save lives and a European study which followed-up on men for 13 years found that one prostate cancer death was averted per 781 men invited for screening although the authors concluded that ‘despite our findings, further quantification of harms and their reduction are still considered a prerequisite for the introduction of populated-based screening.’

Symptoms potentially suggestive of prostate cancer include lower urinary tract symptoms (LUTS) including nocturia, urinary frequency or poor stream but these are often present at the time of a prostate cancer diagnosis.

The use of prostate-specific antigen (PSA) in men with LUTS is another means of screening though a 2022 systematic review concluded that the available evidence suggests PSA is highly sensitive but poorly specific for prostate cancer detection in symptomatic patients. 

Prostate cancer is a highly heritable disease and there are 269 known genetic risk variants such that the use of a genetic risk score offers an approach for personalised risk prediction.

Moreover, it has been suggested that the use of a GRS provides additional information to improve upon current practices in prostate cancer screening by risk-stratifying patients before initial prostate-specific antigen testing.

However, to date, GRS is not routinely used and for the present study, researchers set out to assess whether a GRS was able to predict a new diagnosis of prostate cancer in men with LUTS over the next 2 years.

The team used information held in the UK Biobank and included men with LUTS but no recorded diagnosis of prostate cancer and a GRS was calculated for each participant based on the known genetic variants.

The association between the GRS and prostate cancer diagnosis within 2 years of symptom onset was calculated using logistic regression and GRS scores were split into quintiles for analysis.

Genetic risk score and prostate cancer

A total of 6777 men with prostate cancer symptoms were included and of whom, 247 men had a record of prostate cancer within 2 years. For the remaining 6530 men, 62 died during the 2-year follow-up period, leaving 6448 as control patients.

Among men with symptoms, the GRS was associated with the development of symptoms over the next 2-years (odds ratio, OR = 2.12, 95% CI 1.86 – 2.41). The risk of prostate cancer was also age dependent such that men in the highest GRS quintile had a 13% greater incidence than those in the lowest (2.3%).

When researchers added age to the GRS score, the predictive power of the model improved with an area under (AUC) the receiver operating characteristic curve of 0.77 (95% CI 0.74 – 0.80) which was higher than either the GRS (AUC = 0.70) or age (AUC = 0.68) alone.

The authors discussed how the results of the study could be used to enable identification of men at low risk of prostate cancer and therefore avoid further testing but also to fast track those with the highest risk.

A recognised limitation of the study was that genetic sequencing is not currently available in the UK so that the GRS approach cannot be implemented at present.

Citation
Green HD et al. Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis: a cohort study in the UK Biobank Br J Cancer 2022