For decades, researchers hunting for blood-based biomarkers of depression have measured proteins like brain-derived neurotrophic factor and inflammatory signaling molecules at a single, arbitrary point in time. A new study suggests that this practice may have been quietly scrambling the data. Published in Biology of Sex Differences, the research shows that in adult women with major depressive disorder, or MDD, key neurotrophic and inflammatory markers in the blood do not sit still across the menstrual cycle. They rise and fall in patterns that are strikingly absent in psychiatrically healthy women, and the divergence appears strongest in younger adults with the illness.
The study, led by Melanie Dratva and Tiffany Ho of the University of California, Los Angeles, together with colleagues at the University of California, San Francisco and other institutions, enrolled 60 regularly menstruating women aged 21 to 54. Thirty-five had a diagnosis of MDD and 25 were psychiatrically healthy controls. Rather than pinning each participant to a specific cycle phase, the researchers used a continuous measure called days since last period, or DSLP, recorded as the number of days elapsed since the start of each woman’s most recent menstrual period. This approach allowed them to model biomarker levels as a function of cycle timing across the entire cycle, rather than collapsing women into broad categories such as follicular or luteal phase.
The team focused on four molecules with well-established links to depression biology. The first was brain-derived neurotrophic factor, or BDNF, a protein that supports the survival, growth and plasticity of neurons and has been repeatedly implicated in the brain’s ability to adapt to stress. The other three were markers of peripheral inflammation: interleukin-6, or IL-6, a cytokine involved in acute immune signaling; tumor necrosis factor-alpha, or TNF-α, another pro-inflammatory cytokine; and C-reactive protein, or CRP, a liver-produced protein that rises in response to systemic inflammation. Elevated levels of several of these markers have been reported in subsets of patients with depression, feeding a broader theory that neuroimmune dysregulation contributes to the disorder.
When the researchers compared average biomarker levels between the two diagnostic groups, they found no significant differences. On its face, that null result might seem unremarkable, and it is precisely the kind of finding that has fueled skepticism about peripheral markers of depression. But the picture changed dramatically once cycle timing entered the statistical models. In women with MDD, higher DSLP, meaning a later point in the cycle, was associated with higher circulating BDNF, with a standardized effect of β = 0.23 and a p-value of 0.02. In healthy controls, no such relationship emerged. The BDNF signal was not uniform across the MDD group either. Age moderation analyses revealed that the association was statistically significant specifically among women with MDD under 36 years of age, suggesting that the cycle-linked dynamics of this neurotrophic protein are most pronounced in younger reproductive-aged adults with the disorder.
The inflammatory markers moved in the opposite direction. Within the MDD group, higher DSLP was associated with lower levels of TNF-α, with β = -0.03 and p = 0.03, and showed a similar trend for CRP, with β = -0.04 and p = 0.06, just short of conventional significance thresholds. Again, these relationships were absent in the control group, and the TNF-α association was significant specifically among women with MDD under 35 years of age. IL-6, the fourth marker examined, did not show a comparable cycle-linked pattern. Taken together, the results describe a diagnostic divergence in how the menstrual cycle sculpts the peripheral neuroimmune landscape: in depression, BDNF climbs as the cycle progresses while inflammatory markers drift downward, whereas in health, these molecules remain comparatively stable across the same interval.
Perhaps the most consequential finding is what did not appear. Neither cycle timing nor any of the biomarker levels were associated with clinician-rated depressive symptom severity. The cycle-sensitive biological dynamics, in other words, appear partially dissociable from a woman’s concurrent depressive state. This dissociation carries real technical weight for the field. It implies that the peripheral neuroimmune changes tied to the menstrual cycle in MDD are not simply a biological echo of how depressed a person feels at the moment of measurement. Instead, they may reflect deeper, state-independent differences in how cycle-related processes operate in the bodies of women with the disorder, differences that persist regardless of current symptom levels.
The age dependence of the effects adds another layer of complexity. The BDNF association was concentrated in women with MDD under 36, and the TNF-α association in those under 35. Reproductive biology changes across the late twenties and thirties, and the study’s age range of 21 to 54 spans substantial variation in ovarian function and cycle regularity. The concentration of effects in younger participants raises the possibility that the cycle-linked neuroimmune dynamics are most robust when ovarian cycling is at its most vigorous, or alternatively that age-related changes in inflammation and neurotrophic signaling progressively mask the cycle signal in older adults. Disentangling these possibilities will require larger samples and longitudinal designs that follow individual women across multiple cycles.
The methodological implications may be the study’s most viral takeaway. Many canonical biomarkers of MDD, including BDNF and CRP, are influenced by physiological changes across the menstrual cycle, yet a large share of published depression biomarker studies have either ignored cycle timing entirely or collapsed it into coarse phase categories. If BDNF rises and TNF-α falls across the cycle in women with depression but not in controls, then a study that samples women at different, unrecorded points in their cycles will inject systematic noise into group comparisons. Depending on the phase distribution of participants, this noise could produce spurious group differences, mask real ones, or explain why findings across the depression biomarker literature have been so stubbornly inconsistent. The authors argue that accounting for menstrual cycle timing when examining peripheral biomarkers of MDD is not an optional refinement but a necessary control.
The study also speaks to the broader question of why depression disproportionately affects women. Sex differences in depression rates are well documented, but the mechanisms underlying elevated risk in reproductive-aged females remain poorly understood. The new findings suggest that the menstrual cycle is not merely background physiology in this population. In women with MDD, the cycle appears to modulate neurotrophic and inflammatory pathways that are themselves implicated in depression pathophysiology, hinting that cycle-sensitive neuroimmune processes could be part of the biological substrate of the elevated risk. Whether these dynamics contribute causally to vulnerability or are a downstream correlate of the disorder remains an open question that the cross-sectional design cannot settle.
Several caveats frame the work. The sample of 60 women is modest, and the effect sizes, while statistically significant, are small in absolute terms. The participants were recruited between 2011 and 2020 at the University of California, San Francisco, before the COVID-19 pandemic, which limits potential confounding from infection-related immune changes but also means the findings await replication in contemporary cohorts. DSLP itself is an imperfect proxy for cycle phase, since cycle length varies between women and ovulation timing is not directly verified. Nonetheless, the core message stands: peripheral neurotrophic and inflammatory factors show menstrual cycle-related variation in women with MDD that is absent in healthy controls, most evident in younger adults, and independent of current symptom severity. For a field that has struggled to reconcile conflicting biomarker findings, the menstrual cycle may be the overlooked variable that has been hiding in plain sight all along.
Subject of Research: Neuroscience
Article Title: Menstrual cycle-related neurotrophic and inflammatory variation differs between adult females with and without Major Depressive Disorder
Article References: Dratva, M. A., Wu, G. W. Y., Rampersaud, R., Reus, V. I., Mellon, S. H., Lindqvist, D., Dhabhar, F. S., Irwin, M. R., Wolkowitz, O. M., & Ho, T. C. (2026). Menstrual cycle-related neurotrophic and inflammatory variation differs between adult females with and without Major Depressive Disorder. Biology of Sex Differences. https://doi.org/10.1186/s13293-026-01003-7
Image Credits: AI Generated
DOI: 10.1186/s13293-026-01003-7
Keywords: Menstrual, cycle-related, neurotrophic, inflammatory, variation, differs, between, adult, females, without, Major, Depressive
News Source: Cassandra Pierce. (October 16, 2026). Depression Rewrites How the Menstrual Cycle Moves Brain and Inflammatory Markers. Scienmag.
