Individual patterns may help predict changes in PMDD symptoms
For people with premenstrual dysphoric disorder (PMDD), individual symptoms do not necessarily follow the same pattern throughout the menstrual cycle. A new study by SciLifeLab Group Leader Erika Comasco (UU) and colleagues, published in Nature Communications, shows that the timing and sequence of symptoms can vary between individuals, and that changes in some symptoms may help predict what happens next.
PMDD is associated with recurring periods of severe psychological symptoms linked to hormonal changes during the menstrual cycle. In this study, the condition has been investigated in terms of which symptoms a person experiences, their severity and cyclicity. These findings suggest that *when* each of those symptoms appears, how they develop over time and how they relate to each other, may also be important.
PMDD symptoms follow different patterns
To investigate these patterns, people with PMDD completed daily symptom assessments across two consecutive menstrual cycles. Using so-called dense sampling and statistical models designed to capture dynamic processes, the researchers looked at when different symptoms emerged and subsided, as well as how changes in one symptom were associated with changes in others over time.
Clear differences emerged in when symptoms began, how severe they became, and how long they lasted. Different symptoms also followed different trajectories in many participants. This suggests that PMDD can involve different individual symptom patterns rather than following one course that looks the same for everyone.
Symptoms can change what happens next
There were also clear temporal interactions among the core psychological symptoms. Anxiety emerged as a central part of the symptom trajectory and was associated with changes in several other symptoms.
Depression showed the strongest associations with later changes in other core symptoms, with the clearest relationships occurring around three to four days later. Irritability, meanwhile, could come before an increase in depressive symptoms by up to five days, suggesting that PMDD symptoms are linked in a dynamic network rather than occurring independently.
“PMDD has traditionally been described mainly in terms of which symptoms are present. Our findings suggest that it may also be important to understand the sequence in which symptoms emerge and how they develop over time,” says Erika Comasco, researcher at Uppsala University, Dept. of Women´s and Children´s Health.
Rather than looking only at which symptoms are present, the findings point to the importance of understanding how symptoms unfold over time. Daily symptom data could potentially help researchers identify patterns that signal when symptoms are likely to get worse.
Toward more personalized treatment
The next step is to find out whether these individual symptom patterns can be used to better predict worsening symptoms, and whether that information can be useful in clinical treatment.
“In the longer term, this could contribute to more personalized and time-sensitive care, where PMDD is not only treated once symptoms have become severe, but where treatment also takes into account how and when symptoms typically develop in each individual,” Comasco says.
The researchers are now investigating whether these patterns predict symptom relief upon different pharmacological treatments but will need to test whether these patterns can reliably predict symptom changes before this approach can be translated into clinical care. Yet, the findings suggest that tracking symptoms over time may offer information that is missed when symptoms are considered individually.
