| 1. |
- Möllerberg, Marie-Louise, et al.
(författare)
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Managing an altered social context-Patients experiences of staying away from home while undergoing proton beam therapy
- 2020
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Ingår i: Nursing Open. - : John Wiley & Sons. - 2054-1058. ; 7:4, s. 1157-1163
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To illuminate the experience of an altered social context for patients with primary brain tumours living away from home while undergoing proton beam therapy.Design: A descriptive, qualitative cross-sectional interview study.Methods: Nineteen patients were interviewed between December 2015-August 2016, either during (N = 7) or before and after (N = 12) their proton beam therapy. A hermeneutical analysis was performed.Results: Participants made adjustments to achieve control and well-being during the treatment period. The analysis also revealed two interrelated patterns that helped participants adjust: being part of the family from a distance and seeking affinity.Conclusion: It is important that patients receiving treatment far from home find a way to remain a part of their family and find affinity in the altered social context. Health professionals can prepare patients for the treatment period and can implement interventions to promote well-being for both patients and their relatives.
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| 2. |
- Axfors, Cathrine, et al.
(författare)
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Cohort profile : the Biology, Affect, Stress, Imaging and Cognition (BASIC) study on perinatal depression in a population-based Swedish cohort
- 2019
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Ingår i: BMJ Open. - : BMJ. - 2044-6055. ; 9:10
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: With the population-based, prospective Biology, Affect, Stress, Imaging and Cognition (BASIC) cohort, we aim to investigate the biopsychosocial aetiological processes involved in perinatal depression (PND) and to pinpoint its predictors in order to improve early detection.PARTICIPANTS: From September 2009 to November 2018, the BASIC study at Uppsala University Hospital, Sweden, has enrolled 5492 women, in 6478 pregnancies, of which 46.3% first-time pregnancies and with an average age of 31.5 years. After inclusion around gestational week 16-18, participants are followed-up with data collection points around gestational week 32, at childbirth, as well as three times postpartum: after 6 weeks, 6 months and 1 year. At the last follow-up, 70.8% still remain in the cohort.FINDINGS TO DATE: In addition to internet-based surveys with self-report instruments, participants contribute with biological samples, for example, blood samples (maternal and from umbilical cord), biopsies (umbilical cord and placenta) and microbiota samples. A nested case-control subsample also takes part in cognitive and emotional tests, heart rate variability tests and bioimpedance tests. Subprojects have identified various correlates of PND of psychological and obstetric origin in addition to factors of the hypothalamic-pituitary-adrenal axis and immune system.FUTURE PLANS: In parallel with the completion of data collection (final follow-up November 2019), BASIC study data are currently analysed in multiple subprojects. Since 2012, we are conducting an ongoing follow-up study on the participants and their children up to 6 years of age (U-BIRTH). Researchers interested in collaboration may contact Professor Alkistis Skalkidou (corresponding author) with their request to be considered by the BASIC study steering committee.
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| 3. |
- Bilal, Ayesha, et al.
(författare)
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Mom2B: a study of perinatal health via smartphone application and machine learning methods
- 2022
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Ingår i: European Psychiatry. - : Royal College of Psychiatrists. - 0924-9338 .- 1778-3585. ; 65:S1
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Tidskriftsartikel (refereegranskat)abstract
- IntroductionPeripartum depression (PPD) impacts around 12% of women globally and is a leading cause of maternal mortality. However, there are currently no accurate methods in use to identify women at high risk for depressive symptoms on an individual level. An initial study was done to assess the value of deep learning models to predict perinatal depression from women at six weeks postpartum. Clinical, demographic, and psychometric questionnaire data was obtained from the “Biology, Affect, Stress, Imaging and Cognition during Pregnancy and the Puerperium†(BASIC) cohort, collected from 2009-2018 in Uppsala, Sweden. An ensemble of artificial neural networks and decision trees-based classifiers with majority voting gave the best and balanced results, with nearly 75% accuracy. Predictive variables identified in this study were used to inform the development of the ongoing Swedish Mom2B study.ObjectivesThe aim of the Mom2be study is to use digital phenotyping data collected via the Mom2B mobile app to evaluate predictive models of the risk of perinatal depression.MethodsIn the Mom2B app, clinical, sociodemographic and psychometric information is collected through questionnaires, including the Edinburgh Postnatal Depression Scale (EPDS). Audio recordings are recurrently obtained upon prompts, and passive data from smartphone sensors and activity logs, reflecting social-media activity and mobility patterns. Subsequently, we will implement and evaluate advanced machine learning and deep learning models to predict the risk of PPD in the third pregnancy trimester, as well as during the early and late postpartum period, and identify variables with the strongest predictive value.ResultsAnalyses are ongoing.ConclusionsPending results.DisclosureNo significant relationships.
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| 4. |
- Bilal, Ayesha, et al.
(författare)
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Predicting perinatal health outcomes using smartphone-based digital phenotyping and machine learning in a prospective Swedish cohort (Mom2B) : study protocol
- 2022
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Ingår i: BMJ Open. - : BMJ Publishing Group Ltd. - 2044-6055. ; 12:4
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Perinatal complications, such as perinatal depression and preterm birth, are major causes of morbidity and mortality for the mother and the child. Prediction of high risk can allow for early delivery of existing interventions for prevention. This ongoing study aims to use digital phenotyping data from the Mom2B smartphone application to develop models to predict women at high risk for mental and somatic complications.Methods and analysis: All Swedish-speaking women over 18 years, who are either pregnant or within 3 months postpartum are eligible to participate by downloading the Mom2B smartphone app. We aim to recruit at least 5000 participants with completed outcome measures. Throughout the pregnancy and within the first year postpartum, both active and passive data are collected via the app in an effort to establish a participant's digital phenotype. Active data collection consists of surveys related to participant background information, mental and physical health, lifestyle, and social circumstances, as well as voice recordings. Participants' general smartphone activity, geographical movement patterns, social media activity and cognitive patterns can be estimated through passive data collection from smartphone sensors and activity logs. The outcomes will be measured using surveys, such as the Edinburgh Postnatal Depression Scale, and through linkage to national registers, from where information on registered clinical diagnoses and received care, including prescribed medication, can be obtained. Advanced machine learning and deep learning techniques will be applied to these multimodal data in order to develop accurate algorithms for the prediction of perinatal depression and preterm birth. In this way, earlier intervention may be possible.Ethics and dissemination: Ethical approval has been obtained from the Swedish Ethical Review Authority (dnr: 2019/01170, with amendments), and the project fully fulfils the General Data Protection Regulation (GDPR) requirements. All participants provide consent to participate and can withdraw their participation at any time. Results from this project will be disseminated in international peer-reviewed journals and presented in relevant conferences.
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| 5. |
- Bränn, Emma, 1988-
(författare)
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Biomarkers for Peripartum Depression : Focusing on aspects of the immune system and the metabolome
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Peripartum depression is a common, multifactorial, and potentially devastating disease among new mothers. A biological marker for peripartum depression would facilitate early detection, better understanding of the pathophysiology, and identification of targets for treatment. Evidence is growing for a potential role of the immune system in depression outside the peripartum period. Major adaptations of the immune system occur during pregnancy, justifying the search for immunological markers for peripartum depression. The immune system is very complex and dynamic during pregnancy, complicating the study of associations with depression. The metabolome is also affected by pregnancy and is linked to the immune system via, e.g., the microbiota. Hence, metabolomic profiling could increase the understanding of peripartum depression. This thesis aimed to explore inflammatory markers and metabolic profiles in the peripartum period, in order to discover possible biomarkers, and to increase the understanding of the pathophysiology of peripartum depression.All studies were conducted within the Biology, Affect, Stress, Imaging, and Cognition (BASIC) study. The Edinburgh Postnatal Depression Scale and the Mini International Neuropsychiatric Interview were used to assess depressive symptoms. Multiplex Proximity Extension assays were used to analyze inflammatory markers in pregnancy and postpartum. Luminex Bio-Plex Pro Human Cytokine Assays were used to analyze cytokine levels across the peripartum period, and gas chromatography-mass spectrometry metabolomics were used for metabolic profiling. No marker was discriminative enough to be used on its own as a biomarker for peripartum depression. However, several inflammatory markers (such as STAM-BP, TRANCE, HGF, IL-18, FGF-23, and CXCL1) were identified as possible candidates for more advanced diagnostic algorithms. The results further pointed towards the importance of adaptation of the immune system during pregnancy and postpartum, where levels of cytokines such as VEGF-A might have an important role in antenatal and postpartum depression. The results even highlight the importance of examination timing. Lastly, the metabolic profiling suggested different subgroups of women with postpartum depressive symptoms, supporting theories of peripartum depression being a heterogeneous disease in need of subgroup definition.
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| 6. |
- Bränn, Emma, et al.
(författare)
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Inflammatory markers in late pregnancy in association with postpartum depression-A nested case-control study.
- 2017
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Ingår i: Psychoneuroendocrinology. - : Elsevier BV. - 0306-4530 .- 1873-3360. ; 79, s. 146-159
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Tidskriftsartikel (refereegranskat)abstract
- Recent studies indicate that the immune system adaptation during pregnancy could play a significant role in the pathophysiology of perinatal depression. The aim of this study was to investigate if inflammation markers in a late pregnancy plasma sample can predict the presence of depressive symptoms at eight weeks postpartum. Blood samples from 291 pregnant women (median and IQR for days to delivery, 13 and 7-23days respectively) comprising 63 individuals with postpartum depressive symptoms, as assessed by the Edinburgh postnatal depression scale (EPDS≥12) and/or the Mini International Neuropsychiatric Interview (M.I.N.I.) and 228 controls were analyzed with an inflammation protein panel using multiplex proximity extension assay technology, comprising of 92 inflammation-associated markers. A summary inflammation variable was also calculated. Logistic regression, LASSO and Elastic net analyses were implemented. Forty markers were lower in late pregnancy among women with depressive symptoms postpartum. The difference remained statistically significant for STAM-BP (or otherwise AMSH), AXIN-1, ADA, ST1A1 and IL-10, after Bonferroni correction. The summary inflammation variable was ranked as the second best variable, following personal history of depression, in predicting depressive symptoms postpartum. The protein-level findings for STAM-BP and ST1A1 were validated in relation to methylation status of loci in the respective genes in a different population, using openly available data. This explorative approach revealed differences in late pregnancy levels of inflammation markers between women presenting with depressive symptoms postpartum and controls, previously not described in the literature. Despite the fact that the results do not support the use of a single inflammation marker in late pregnancy for assessing risk of postpartum depression, the use of STAM-BP or the novel notion of a summary inflammation variable developed in this work might be used in combination with other biological markers in the future.
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| 7. |
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| 8. |
- Bränn, Emma, et al.
(författare)
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Inflammatory markers in women with postpartum depressive symptoms
- 2020
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Ingår i: Journal of Neuroscience Research. - : Wiley. - 0360-4012 .- 1097-4547. ; 98:7, s. 1309-1321
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Tidskriftsartikel (refereegranskat)abstract
- Postpartum depression (PPD) is a devastating disorder affecting not only more than 10% of all women giving birth, but also the baby, the family, and the society. Compiling evidence suggests the involvement of the immune system in the pathophysiology of major depression; yet, the immune response in perinatal depression is not as well studied. The aim of this study was to investigate the alterations in peripheral levels of inflammatory biomarkers in 169 Swedish women with and without depressive symptoms according to the Edinburgh postnatal depression scale or the M.I.N.I neuropsychiatric interview at eight weeks postpartum. Among the 70 markers analyzed with multiplex proximity extension assay, five were significantly elevated in women with postpartum depressive symptoms in the adjusted LASSO logistic regression analysis: Tumor necrosis factor ligand superfamily member (TRANCE) (OR-per 1 SD increase = 1.20), Hepatocyte growth factor (HGF) (OR = 1.17) Interleukin (IL)-18 (OR = 1.06), Fibroblast growth factor 23 (FGF-23) (OR = 1.25), and C-X-C motif chemokine 1 (CXCL1) (OR 1.11). These results indicate that women with PPD have elevated levels of some inflammatory biomarkers. It is, therefore, plausible that PPD is associated with a compromised adaptability of the immune system.
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| 9. |
- Bränn, Emma, et al.
(författare)
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Longitudinal assessment of inflammatory markers in the peripartum period by depressive symptom trajectory groups
- 2022
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Ingår i: Brain, Behavior, & Immunity - Health. - : Elsevier. - 2666-3546. ; 22
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveMechanisms driving temporal fluctuations of inflammatory markers during pregnancy, and how these might differ between distinct perinatal depressive trajectories, are not well understood. The aim of this study was to investigate cytokines levels over the course of pregnancy in women with different trajectories of depressive symptoms peripartum, and relate the levels to levels of non-pregnant controls.MethodsBased on the Edinburgh Postnatal Depression Scale and/or selective serotonin reuptake inhibitors use, 131 women were categorized into: no (n = 65); antepartum (APD, n = 19), postpartum (PPD, n = 17) and persistent (n = 30) depressive symptoms. Plasma samples (n = 386) were analyzed for levels of interleukin (IL)-8, IL-18, Tumor necrosis factor-α, macrophage colony-stimulating factor (M-CSF), vascular endothelial growth factor A (VEGF-A) and fractalkine, at four different time-points (twice during pregnancy, during childbirth, and postpartum) using Bio-Plex Pro Human Cytokine Assays. Generalized linear mixed models were applied to analyze the associations between cytokine levels, time-point, perinatal depressive symptom trajectory group and their interaction.ResultsFor all markers but VEGF-A, pregnancy was associated with higher cytokine levels compared to the non-pregnant controls, with delivery being the most prominent time-point. For M-CSF, IL-18 and VEGF-A, levels were back to the non-pregnant status at postpartum week 8. An effect of perinatal depressive symptom trajectory groups on cytokine levels was found for VEGF-A. Women with PPD and women with APD had lower levels of VEGF-A throughout the study period compared to women with persistent depression, and women with PPD had lower levels compared to non-depressed women.ConclusionsLower levels of VEGF-A were noted among women in some trajectories of depressive symptoms peripartum. The peripartum period is a time of tremendous immune system adaptations. Standardization of time-points for cytokine measurements in studies of perinatal depression are important in order to draw valid conclusions on the role of the immune system in perinatal depression.
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| 10. |
- Bränn, Emma, 1988-, et al.
(författare)
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Metabolic Profiling Indicates Diversity in the Metabolic Physiologies Associated With Maternal Postpartum Depressive Symptoms
- 2021
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Ingår i: Frontiers in Psychiatry. - : Frontiers Media S.A.. - 1664-0640. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Postpartum depression (PPD) is a devastating disease requiring improvements in diagnosis and prevention. Blood metabolomics identifies biological markers discriminatory between women with and those without antenatal depressive symptoms. Whether this cutting-edge method can be applied to postpartum depressive symptoms merits further investigation. Methods: As a substudy within the Biology, Affect, Stress, Imagine and Cognition Study, 24 women with PPD symptom (PPDS) assessment at 6 weeks postpartum were included. Controls were selected as having a score of ≤ 6 and PPDS cases as ≥12 on the Edinburgh Postnatal Depression Scale. Blood plasma was collected at 10 weeks postpartum and analyzed with gas chromatography-mass spectrometry metabolomics. Results: Variations of metabolomic profiles within the PPDS samples were identified. One cluster showed altered kidney function, whereas the other, a metabolic syndrome profile, both previously associated with depression. Five metabolites (glycerol, threonine, 2-hydroxybutanoic acid, erythritol, and phenylalanine) showed higher abundance among women with PPDSs, indicating perturbations in the serine/threonine and glycerol lipid metabolism, suggesting oxidative stress conditions. Conclusions: Alterations in certain metabolites were associated with depressive pathophysiology postpartum, whereas diversity in PPDS physiologies was revealed. Hence, plasma metabolic profiling could be considered in diagnosis and pathophysiological investigation of PPD toward providing clues for treatment. Future studies require standardization of various subgroups with respect to symptom onset, lifestyle, and comorbidities.
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