Brain versus cardiometabolic health: a delicate balance in need of precision lifestyle medicine approaches

Depression is a major cause of morbidity and has major consequences on quality of life, impacting absenteeism, productivity at work, and health care costs [(1)]. In 2023, 24% of adult women and 11% of adult men were treated for depressive symptoms [(2)]. Because some antidepressants (AD) are known to have an impact on body weight [(3)], the balance between managing mental health versus limiting adiposity-related cardiometabolic risk remains an important dilemma in clinical practice.

Furthermore, we have substantial evidence from more than three decades of cardiometabolic imaging (computed tomography [CT] or magnetic resonance imaging [MRI]) studies demonstrating that, for the same body mass index (BMI), there are considerable individual differences in body composition and regional adipose tissue distribution [(4)]. For instance, it is now well established that visceral adipose tissue (VAT) is the body fat compartment most closely associated with insulin resistance and features of the metabolic syndrome that increase risk of type 2 diabetes and cardiovascular disease [(5)]. We also understand that excess VAT is a marker of the relative inability of subcutaneous adipose tissue to expand and act as a metabolic sink, leading to deposition of fat not only in the abdominal cavity but also in usually lean tissues such as the heart, liver, kidney, pancreas, and skeletal muscle, a phenomenon referred to as ectopic fat deposition.

Andersson et al. took the opportunity of having access to the now-famous UK Biobank imaging data (n = 40,174) to retrospectively examine whether AD (selective serotonin reuptake inhibitors and tricyclic antidepressants) users would display differences in body fat distribution and muscle composition compared with sex-, age-, and BMI-matched nonusers [(6)]. The authors report that selective serotonin reuptake inhibitor users had higher levels of VAT and less muscle volume combined with greater fat infiltration than control individuals. Sex differences were also found in BMI gained over time (women > men). Although an increased risk of cardiovascular disease (men) and type 2 diabetes was found among tricyclic antidepressant users, the specific contribution of changes in muscle composition to such increased risks could not be determined with certainty.

The paper by Andersson et al. addresses an important topic because some AD medications have been reported to induce weight gain, with differences observed among classes and specific molecules. The paper also nicely demonstrates that changes (or lack of changes) in body weight could sometimes be misleading in order to track clinically relevant variations in body composition with significant consequences on cardiometabolic health.

This paper presents a large amount of data from several relevant exploratory analyses providing additional evidence that monitoring body weight over time is not sufficient to monitor changes in cardiometabolic health, especially among patients treated with these drugs. However, some study limitations should be highlighted. Contrary to other subanalyses conducted in the UK Biobank cohort, the authors could not use accelerometry data to better evaluate the level of physical activity across the groups. Another limitation is the inability to examine potential changes in overall diet quality and caloric intake. Finally, because intermediate markers of cardiometabolic health were not available, the assumption made by the authors that the decreased muscle mass and increased fat infiltration associated with some of these drugs contributed to increasing cardiometabolic health is speculative. Although sarcopenia is clearly detrimental to people living with obesity, to what extent this phenomenon independently contributed to cardiometabolic risk in this cohort after control for visceral adiposity (and increased liver and heart fat) is a question that could not be properly addressed by the authors.

One thing is certain: in this day and age, because many pharmacological agents are not weight-neutral, we are clearly in need of better tools than BMI to assess adiposity phenotypes in clinical practice, particularly to evaluate the response to whichever treatment. Furthermore, because behaviors are known to modulate the risk associated with any given adiposity phenotype (drug-induced or not) [(4)], “lifestyle vital signs” such as overall diet quality, level of physical activity, quality of sleep, cardiorespiratory fitness, and anthropometric markers of abdominal adiposity should be obtained in all patients [(7, 8)]. This interesting analysis by Andersson et al. should pave the way to further precision lifestyle medicine studies conducted in this prevalent patient population in need of solutions to improve not only their cardiometabolic health but also their mental health and quality of life.

The authors declared no conflict of interest.