Dataset Information

Collected plasma samples from 30 healthy postpartum women and 30 postpartum depression patients for proteomic analysis using Data-Independent Acquisition (DIA)

ABSTRACT: Collected plasma samples from 30 healthy postpartum women and 30 postpartum depression patients, performed protein profiling analysis using Data-Independent Acquisition (DIA). Identified differential proteins, conducted functional enrichment analysis, established a diagnostic model for postpartum depression, and evaluated the model's performance.

ORGANISM(S): Homo Sapiens

SUBMITTER: Pengfei Gao

PROVIDER: PXD050851 | iProX | Thu Mar 21 00:00:00 GMT 2024

REPOSITORIES: iProX

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Publications

A Plasma Proteomics-Based Model for Identifying the Risk of Postpartum Depression Using Machine Learning.

Wang Shusheng S Xu Ru R Li Gang G Liu Songping S Zhu Jie J Gao Pengfei P

Journal of proteome research 20250107 2

Postpartum depression (PPD) poses significant risks to maternal and infant health, yet proteomic analyses of PPD-risk women remain limited. This study analyzed plasma samples from 30 healthy postpartum women and 30 PPD-risk women using mass spectrometry, identifying 98 differentially expressed proteins (29 upregulated and 69 downregulated). Principal component analysis revealed distinct protein expression profiles between the groups. Functional enrichment and PPI analyses further explored the bi ...[more]

PMID: 39772732

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Project description:Bronx County, New York is the poorest urban county in the U.S.A., and residents are almost entirely Latino or African American. Cancer is the leading cause of premature death in the Bronx, with morality rates significantly higher than for New York City as a whole. Low-income/minority populations are more likely to be diagnosed with preventable and late-stage cancers than the general population, in part, due to lower screening rates. While research has addressed screening barriers in low-income/minority groups, depression, a common,potentially critical barrier, has received scant attention. Research suggests that depressed women are less likely to engage in cancer screening, especially mammography and Pap testing. The link between mental health and cancer screening is particularly important to address in the Bronx, which has the highest rates of self-reported serious psychological distress (a measure closely related to depression) in New York City. Depression affects almost 1 in 4 minority women, and while minorities often seek help for depression in primary care, primary care depression management often does not meet evidence-based standards. Drawing on the expertise and close collaboration of Bronx medical and social service providers and patient stakeholders, this study will determine whether a collaborative care intervention that addresses both depression and cancer screening needs simultaneously among women ages 50-64 is more effective at improving cancer screening and patient-reported outcomes for women with depression than an existing evidence-based cancer screening intervention alone. To achieve this, the investigators will compare the effectiveness of these two interventions using a randomized controlled trial (RCT). In partnership with six Bronx Federally Qualified Health Centers (FQHCs), the investigators will recruit approximately 800 women ages 50-64 who screen positive for depression and are non-adherent with recommended cervical, breast, and/or colorectal cancer screenings. The investigators specific aims are to: 1) compare the impact of the two interventions on patient-reported outcomes, including cancer screening knowledge and attitudes, self-efficacy, depression-related stigma, provider referrals, participation in mental health care, medication adherence, quality of life, satisfaction with care and treatment decisions, and depression; 2) compare the effectiveness of the two interventions in increasing breast, cervical, and colorectal cancer screening; 3) determine whether reducing depression increases the likelihood that low-income women 50-64 will receive cancer screening; 4) determine whether effectiveness of the two interventions in increasing cancer screening varies according to patient characteristics, such as duration of depression, presence of other chronic conditions, and obesity. This study is designed to increase the investigators understanding of how to enhance primary care systems’ ability to improve a range of outcomes related to cancer screening and depression among low-income minority women, and how to best support this population in making cancer-screening decisions.

Dataset Information

Collected plasma samples from 30 healthy postpartum women and 30 postpartum depression patients for proteomic analysis using Data-Independent Acquisition (DIA)

Publications

A Plasma Proteomics-Based Model for Identifying the Risk of Postpartum Depression Using Machine Learning.

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