Use of selective serotonin reuptake inhibitors is associated with very low plasma-free serotonin concentrations in humans

Plasma Serotonin and Cardiovascular Outcomes in Chronic Kidney Disease

Background Platelet-poor plasma serotonin levels are associated with adverse cardiovascular outcomes. Although plasma serotonin levels increase in chronic kidney disease, the cardiovascular implications remain unknown. Methods and Results In 1114 participants from the prospective CRIC (Chronic Renal Insufficiency Cohort) Study, we evaluated the association between plasma serotonin, categorized as undetectable, intermediate, and high (≥20 ng/mL) levels, and cross-sectional findings on echocardiography, including left ventricular hypertrophy, left ventricular ejection fraction, and pulmonary hypertension. We also analyzed whether serotonin was associated with time-to-event cardiovascular outcomes, including heart failure hospitalization and atherosclerotic cardiovascular disease (ASCVD) events, in addition to mortality. Because selective serotonin reuptake inhibitors decrease plasma serotonin levels, we specifically evaluated the influence of selective serotonin reuptake inhibitor use in the relationship between serotonin and outcomes. Plasma serotonin level inversely correlated with estimated glomerular filtration rate and directly correlated with blood pressure. High plasma serotonin was associated with left ventricular hypertrophy (adjusted odds ratio, 2.74 [95% CI, 1.11-7.41]). In contrast, undetectable plasma serotonin level was associated with the highest risk of heart failure (adjusted hazard ratio [HR], 2.26 [95% CI, 1.40-3.66]) and ASCVD events (adjusted HR, 1.96 [95% CI, 1.15-3.32]). Conclusions In a large chronic kidney disease cohort, plasma serotonin levels correlated with blood pressure, and elevated serotonin levels were associated with left ventricular hypertrophy. In contrast, undetectable plasma serotonin was associated with the highest risk of heart failure and ASCVD events.

Systematic review of studies using platelet serotonin content to assess bioeffect of serotonin reuptake inhibitors at the serotonin transporter

RATIONALE

Assessment of the bioeffect of serotonin reuptake inhibitors (SRIs, including both selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs)) at the serotonin transporter (SERT) in patients and healthy controls can have important theoretical and clinical implications.

OBJECTIVES

Bioeffect at SERT has been assessed by neuroimaging of brain SERT occupancy, through in vitro measurements of platelet serotonin (5-HT) uptake, and by measuring platelet 5-HT content pre- and post-initiation of SRI administration. Studies of platelet 5-HT content were reviewed in order to (1) determine the overall apparent bioeffect of SRIs; (2) compare bioeffect across types of SRIs; (3) compare the three approaches to assessing SRI bioeffect; and (4) determine how the findings might inform clinical practice.

METHODS

We performed a systematic review of the published studies that measured platelet 5-HT content to assess SRI bioeffect at the platelet SERT. Studies using neuroimaging and in vitro platelet 5-HT uptake to assess SRI bioeffect were reviewed for comparison purposes.

RESULTS

Clinical doses of SRIs typically resulted in 70-90% reductions in platelet 5-HT content. The observed bioeffect at the platelet SERT appeared similar among different SSRIs and SNRIs. The bioeffect estimations based on platelet 5-HT content were consistent with those obtained using neuroimaging to assess brain SERT occupancy and those based on the in vitro measurement of platelet 5-HT uptake.

CONCLUSIONS

In general, excellent agreement was seen in the apparent SRI bioeffect (70-90% inhibition) among the platelet 5-HT content studies and across the three bioeffect approaches. Theoretical and practical clinical implications are discussed.

Mammary homeostasis in the mother-offspring dyad

Homeostasis during lactation is a special case in which the unit for regulation is a dyad comprising the mother and her currently nursing offspring (the mother-offspring dyad). This arrangement is not a trivial. A litter of mice can have a mass greater than the mother and nutrient demands that far exceed her. Homeostasis for milk secretion, appetite, and calcium metabolism must come under integrated control, responding seamlessly to the needs of the mother and the offspring. Serotonin (5-HT) is a primary local regulator of mammary homeostasis. 5-HT synthesis in the mammary epithelium is high during lactation and increases during milk stasis. Two important functions are attributed to the 5-HT system. Firstly, when alveolar spaces are filled with milk 5-HT inhibits milk secretion and opens tight junctions. This feedback induces early phases of involution. Secondly, 5-HT induces synthesis and secretion of parathyroid hormone-related peptide (PTHrP).

Predicting Neuroimaging Biomarkers for Antidepressant Selection in Early Treatment of Depression

BACKGROUND

Due to the biological heterogeneity, 60%-70% of patients with major depressive disorder (MDD) do not respond to or achieve remission from first-line antidepressants. Predicting neuroimaging biomarkers for early antidepressant treatment could guide initial antidepressant therapy.

PURPOSE

To assess for neuroimaging biomarkers for antidepressant selection in early antidepressant treatment.

STUDY TYPE

Prospective.

SUBJECTS

A total of 85 MDD patients from the major site and 33 MDD patients from an out-of-sample test site.

FIELD STRENGTH/SEQUENCE

A 3.0 T, T1-weighted imaging using a magnetization-prepared rapid acquisition gradient-echo sequence and diffusion tensor imaging (DTI) using an echo-planar sequence.

ASSESSMENT

Baseline DTI data of patients who achieved early improvement after 2-weeks of antidepressant treatment (selective serotonin reuptake inhibitors [SSRI] or serotonin-norepinephrine reuptake inhibitors [SNRI]) were analyzed. An ensemble model was constructed using data from the major site and then applied to assess the early response of patients at the out-of-sample test site.

STATISTICAL TESTS

Support vector machine combined with leave-one-out cross-validation were applied to construct the whole model from individual base models from different brain regions. Discriminative biomarkers were evaluated by calculating the changes in sensitivity and specificity obtained when removing a single base model from the whole model, the base model being removed changing in each run.

RESULTS

Training performance over MDD patients at the major site achieved 75% accuracy while performance with accuracy of 70% was achieved in the out-of-sample test site. Assessing sensitivity and specificity changes following the removal of single base models from the prominent model highlighted the functions of two neural circuitries: SSRI-related emotion regulation circuitry, centered on the hippocampus (sensitivity changes: 10%) and amygdala (sensitivity changes: 11%); and SNRI-related emotion and reward circuitry, centered on the putamen (specificity changes: 8%) and orbital part of superior frontal gyrus (specificity changes: 12%).

DATA CONCLUSION

These findings support future research on clinical antidepressant selection for MDD.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.