Physical and neurobiological depression-associated factors: A cross-sectional study

• Combining neurobiological markers with clinical characteristics may improve prediction of depression • a clinical diagnosis of depression based on the reported current symptomatology and history may become more valid when extended with neurobiological markers • Measures of gait, executive functioning and Heart Rate Variability add to the strength of a clinical diagnosis A diagnosis of depression is traditionally made based on clinical criteria, including current symptomatology and history. This process relies on subjective interpretation only. Identification of objective depression-associated factors using appropriate statistical methods can help formulate prevention and refine treatment programs and policies aimed at reducing depression burden. The purpose of this study was to test whether physical and neurobiological markers might be important depression-associated factors. Ninety adults (mean age (SD) 45.7 (10.8) years, 55 females) were categorized as depressed or non-depressed. All were assessed for executive functions, heart rate variability (HRV), gait, and prefrontal cortex oxygenation during walking (measured with functional near-infrared spectroscopy, fNIRS). Least Absolute Shrinkage and Selection Operator (LASSO) regression and planned contrasts were performed to determine independent associations with a diagnosis of depression and assess differences between groups. LASSO regression analysis resulted in variable selection from gait, executive functions, HRV, and fNIRS measures. The resulting multiparametric model displayed very high predictive power to distinguish non-depressed individuals from those with depression (area under the curve,AUC = 0.946). Planned contrasts revealed that depression significantly differs from non-depression regarding selected single measures of executive functioning (e.g., r = 0.16, p ˂ 0.009), HRV (e.g., r = 0.14, p = 0.05), gait (e.g., r = 0.19, p ˂ 0.001), and fNIRS (e.g., r = 0. 16, p = 0.04). The identified depression-associated factors can possibly be combinedly used to raise awareness of modifiable factors associated with depression. Our findings warrant further investigations into the causality of the associations to determine their possible utility as modifiable risk factors and to identify their relevance within novel treatments in individuals with depression.