Accelerated cellular aging and cognitive dysfunction in perimenopausal women with bipolar disorder

Background

Bipolar disorder (BD) is increasingly conceptualized as a disorder of accelerated biological aging, characterized by telomere shortening, mitochondrial dysfunction, oxidative stress, and epigenetic dysregulation [1]. These biological processes are thought to contribute not only to increased medical comorbidity and reduced life expectancy, but also to persistent cognitive impairment, which represents a core dimension of BD and a major determinant of functional outcome [2]. Notably, cognitive deficits in executive function, attention, and memory often persist even during euthymic phases, suggesting underlying neurobiological mechanisms beyond mood symptoms.

The perimenopausal transition constitutes a critical neuroendocrine period marked by significant fluctuations in estrogen levels, which exert modulatory effects on neurotransmitter systems, mitochondrial function, inflammatory pathways, and neuroplasticity. Emerging evidence suggests that this transitional phase may represent a window of heightened vulnerability for mood destabilization and cognitive decline. However, despite growing interest in both accelerated aging and hormonal modulation in BD, the interaction between cellular aging processes and neurocognitive function in perimenopausal women remains poorly understood. To date, no study has comprehensively integrated multiple biological aging markers with cognitive outcomes within this specific population [3].

Objectives

This study aims to provide a comprehensive, multimodal investigation of accelerated biological aging and its cognitive correlates in perimenopausal women with BD. Specifically, we will examine relative telomere length, mitochondrial DNA (mtDNA) copy number, and the expression profiles of selected long non-coding RNAs (lncRNAs) implicated in aging and neuropsychiatric processes. We further aim to explore how these biomarkers relate to domain-specific cognitive performance and clinical characteristics.

Methods

We propose a cross-sectional, case–control study including 100 perimenopausal women diagnosed with BD according to DSM-5-TR criteria and 100 age-matched healthy controls. Perimenopausal status will be determined based on STRAW+10 criteria and supported by clinical and hormonal assessments. Participants will undergo detailed clinical evaluation, including illness duration, episode frequency, hospitalization history, and lithium treatment response.

Neurocognitive function will be assessed using a comprehensive battery targeting executive function, attention, processing speed, memory, and social cognition. Peripheral blood samples will be collected under standardized conditions to quantify telomere length (qPCR-based T/S ratio), mtDNA copy number, and lncRNA expression using RT-qPCR techniques. Multivariate regression and integrative modeling approaches will be applied to examine associations between biological aging markers, cognitive domains, and clinical variables, while controlling for relevant confounders such as age, lifestyle factors, and comorbidities.

Hypotheses: We hypothesize that perimenopausal women with BD will exhibit a distinct profile of accelerated cellular aging compared to healthy controls. Furthermore, we expect that alterations in telomere length, mtDNA copy number, and lncRNA expression will be significantly associated with impairments in cognitive performance. Additionally, we propose that lithium treatment response may be linked to more favorable biological aging profiles, suggesting a potential neuroprotective effect.

Conclusions

By integrating molecular biomarkers with neurocognitive assessment within a hormonally sensitive period, this study introduces a novel and mechanistically informed framework for understanding vulnerability in BD. The findings have the potential to identify biologically grounded markers of cognitive risk and resilience, and to inform the development of targeted, precision-based interventions addressing aging-related pathways in mood disorders.

References

Fries, G. R., Zamzow, M. J., Andrews, T., Pink, O., Scaini, G., & Quevedo, J. (2020). Accelerated aging in bipolar disorder: A comprehensive review of molecular findings and their clinical implications. Neuroscience & Biobehavioral Reviews, 112, 107–116. https://doi.org/10.1016/j.neubiorev.2020.01.035
Chan, J. K. N., Tong, C. C. H. Y., Wong, C. S. M., Chen, E. Y. H., & Chang, W. C. (2022). Life expectancy and years of potential life lost in bipolar disorder: Systematic review and meta-analysis. The British Journal of Psychiatry, 221(3), 567–576. https://doi.org/10.1192/bjp.2022.19
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2023). Hallmarks of aging: An expanding universe. Cell, 186(2), 243–278. https://doi.org/10.1016/j.cell.2022.11.001