Disentangling the Epidemiologic and Genetic Heterogeneity of Postpartum Depression to Predict Risk and Prognosis

解开产后抑郁症的流行病学和遗传异质性以预测风险和预后

基本信息

批准号：
10200624
负责人：
Anna Elizabeth Bauer
金额：
$ 15.63万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10200624
关键词：
Affect Anxiety Attention deficit hyperactivity disorder Award Bioinformatics Biological Bipolar Disorder Body mass index Child Childbirth Cohort Studies Complement Complex Complication Computing Methodologies Data Data Analytics Data Science Data Set Development Diagnosis Differential Diagnosis Disease Drops Early Diagnosis Environment Environmental Risk Factor Epidemiology Estrogens Etiology Event Family Family history of Feeling suicidal Foundations Funding Future Genes Genetic Genetic Heterogeneity Genetic Risk Genomics Goals Grant Heritability Heterogeneity International Intervention Investigation Lead Life Literature Major Depressive Disorder Measures Mental Depression Mental Health Mental disorders Mentors Mentorship Methodology Modeling Modernization Morbidity - disease rate Mothers Norway Outcome Perinatal Phenotype Positioning Attribute Postpartum Depression Postpartum Period Postpartum Women Pregnancy Progesterone Prognosis Psychometrics Quality Control Recording of previous events Reporting Research Research Personnel Resources Risk Risk Factors Sampling Scandinavia Severities Statistical Methods Symptoms Testing Training Translating Translational Research Variant Woman Work aged arm biopsychosocial career chronic depression cohort comorbidity early life adversity epidemiologic data experience genetic association genome wide association study improved individualized medicine insight learning strategy mortality multidimensional data novel perinatal health perinatal mental health perinatal period personalized intervention personalized medicine personalized therapeutic phenotypic data predictive modeling preventive intervention prognostic psychiatric genomics psychogenetics reproductive risk prediction model skills societal costs sociodemographic factors statistical learning statistics stressor trait

项目摘要

PROJECT SUMMARY Postpartum depression (PPD), a common complication of childbirth, has significant morbidity and mortality for mother and child, yet etiology is still poorly understood. PPD is a more heritable subtype of MDD, yet significant heterogeneity exists within the PPD phenotype, which may reflect differences in etiology. This study aims to disentangle the heterogeneity of PPD to understand etiology by leveraging existing data from two unique global resources, the Norwegian Mother and Child Cohort Study (MoBa) and the US arm of the Postpartum Depression: Action Towards Causes and Treatment Consortium. The study aims to 1) apply modern statistical learning methods in a master training set (N=63,528) and two independent testing sets (N=31,716 and N=4,978) to identify PPD subtypes, 2) identify genetic contributors to PPD subtypes and genetic overlap with other traits, and 3) examine the extent to which PPD subtypes predict longer-term mental health prognosis. This research will support my primary career goal to become an independently funded investigator with the expertise necessary to conduct integrated epidemiologic and genomic research to understand the complex etiology of PPD. My long-term research objective is to develop comprehensive risk prediction models that can ultimately be translated into effective preventive interventions and novel individualized treatments for PPD. I have expertise is in epidemiology and perinatal health, but I need additional mentored training to conduct large- scale, integrated gene-environment analyses to understand the biological basis of PPD. The specific objectives to meet my career goal are to 1) develop skills in data science to effectively analyze large, complex datasets, 2) establish an in-depth understanding of genomics and statistical genetics, and 3) understand the complex phenotypes of PPD and other related psychiatric conditions. The core mentorship team consists of Dr. Samantha Meltzer-Brody, lead mentor, an internationally recognized expert in perinatal mental health research, and Dr. Patrick Sullivan, co-lead mentor, a psychiatric geneticist who has built a collaborative network of depression research in Scandinavia. Dr. Yun Li, co-mentor, has extensive experience in developing statistical and computational methods for genomic and high-dimensional data. Dr. Ted Reichborn-Kjennerud, co-mentor, and Drs. Helga Ask and Alexandra Havdahl, collaborators, have extensive experience with assessment of psychiatric outcomes in the MoBa cohort. Dr. Cathryn Lewis, collaborator, is a leading expert in the development of genetic risk score methodology. Their combined mentorship will place me in an ideal position to succeed as an independent investigator. This work will inform further investigation of unique contributions of genes and environment to develop multifactorial predictive models for PPD, representing an important step towards personalized medicine in perinatal mental health. The vital skills I attain during this grant award will provide a foundation for future research evaluating interventions for prevention and personalized therapeutic treatments of PPD.

项目摘要产后抑郁症（PPD）是分娩的常见并发症，具有显着的发病率和死亡率母亲和孩子，但病因仍然鲜为人知。 PPD是MDD的更可遗传的亚型，但很重要 PPD表型内存在异质性，这可能反映了病因的差异。这项研究旨在通过利用来自两个唯一全局的现有数据来利用PPD的异质性来理解病因的异质性资源，挪威母亲和儿童队列研究（MOBA）和产后抑郁症的美国部门：对原因和治疗联盟的行动。该研究的目的是1）应用现代统计学习主训练集（n = 63,528）和两个独立的测试集（n = 31,716和n = 4,978）中的方法识别PPD亚型，2）确定对PPD亚型的遗传因素和与其他特征的遗传重叠，以及 3）检查PPD亚型预测长期心理健康预后的程度。这项研究将支持我的主要职业目标，成为成为独立资助的调查员进行综合流行病学和基因组研究所必需的专业知识以了解复杂 PPD的病因。我的长期研究目标是开发全面的风险预测模型最终将其转化为有效的预防性干预措施和PPD的新型个性化治疗方法。我拥有专业知识是流行病学和围产期健康，但我需要其他的指导培训来进行大型培训比例，集成基因环境分析，以了解PPD的生物学基础。具体目标为了满足我的职业目标是1）发展数据科学技能，以有效地分析大型，复杂的数据集，2）对基因组学和统计遗传学建立深入的理解，3）了解复杂 PPD和其他相关精神病疾病的表型。核心指导团队由萨曼莎博士组成 Meltzer-Brody，首席导师，围产期心理健康研究的国际认可的专家，博士精神病遗传学家帕特里克·沙利文（Patrick Sullivan），他建立了抑郁症的协作网络斯堪的纳维亚研究的研究。联合会员Yun Li博士在开发统计和基因组和高维数据的计算方法。 Ted Reichborn-Kjennerud博士博士。 Helga Ask和合作者Alexandra Havdahl在评估精神病学方面拥有丰富的经验 MOBA队列的结果。合作者Cathryn Lewis博士是遗传发展的领先专家风险评分方法。他们的合并指导将使我处于成功的理想位置独立研究者。这项工作将为基因和环境的独特贡献提供进一步的调查以发展 PPD的多因素预测模型，代表了迈向个性化医学的重要一步围产期心理健康。我在此赠款奖上获得的重要技能将为将来的研究提供基础评估PPD预防和个性化治疗治疗的干预措施。