A Latin American biobank for large-scale genetics research on severe mental illness
A Latin American biobank for large-scale genetics research on severe mental illness
批准号:
10363749
负责人:
NELSON B. FREIMER
金额:
$238.77万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-05-01 至 2026-02-28
关键词:
AffectAgeAllelesArchitectureAreaBehaviorBipolar DisorderCategoriesCollaborationsColombiaCommunitiesComputerized Medical RecordCopy Number PolymorphismDNADataData SetDatabasesDelusionsDiagnosisDiagnosticDiseaseEthnic OriginEthnic groupEtiologyEuropeanFrequenciesGenderGene FrequencyGenesGeneticGenetic ResearchGenetic studyGenotypeGeographic LocationsGoalsGrantHomeHospital RecordsHospitalsIndividualInterviewInvestigationLatin AmericaLatin AmericanLinkage DisequilibriumLiteratureMajor Depressive DisorderMapsMedicalMental HealthMeta-AnalysisMethodsMiningMinorMood DisordersParticipantPersonsPharmaceutical PreparationsPhenotypePopulationPopulation ControlPredictive ValuePrimary Health CarePsychiatric HospitalsPsychotic DisordersRecording of previous eventsReduce health disparitiesResearchResearch DesignResourcesSNP arraySNP genotypingSamplingSampling StudiesSchizophreniaStructureSuicide attemptSymptomsTestingTranscendUnited StatesVariantbasebiobankcare providerscohortdata repositorydemographicsdisease phenotypedisorder riskexome sequencinggenetic analysisgenome wide association studygenome-widegenomic locushealth disparityimprovedlongitudinal analysisloss of functionmembernovelphenomephenotypic datapolygenic risk scoreprimary care servicespsychiatric genomicspsychogeneticsrare variantrecruitscreeningsevere mental illnessside effecttraittreatment planning
中文摘要
项目总结/摘要
这一拟议项目将开发拉丁美洲生物库并向科学界提供
严重精神疾病(LAB-SMI)这种资源,一个数据库和生物库(包括DNA样本和两者)
表型和基因型数据),以及相同数量的
根据年龄、性别和地理位置与病例相匹配的对照将构成逆转
拉丁美洲人口在精神病遗传学研究中的代表性不足。所有参与者
将是“派萨”的成员,这是一个基因和文化上同质的人口,是主要的种族,
哥伦比亚(CO)地区的一个团体,该地区拥有约900万人口。案件将包括受影响的个人,
精神病或情绪障碍谁将被确定,不可知的诊断,通过电子医疗
在“派萨地区”五家大型精神病医院的电子病历中,对照组为无病史的个体
的SMI诊断谁将通过SURA的数据库,最大的供应商之一,
该地区的初级保健服务。通过从EMR中提取广泛的信息,使用方法
在一个Paisa地区医院的SMI现有调查中开发的,项目团队将记录生命周期
SMI诊断的名称以及是否存在SMI相关症状(如妄想)
行为(如自杀)。据推测,这些表型特征可能具有遗传相似性。
超越诊断范畴的因果关系。SNP基因分型和全外显子组测序研究
整个100 K LAB-SMI将很好地识别等位基因频谱中的新关联,
SMI诊断,症状和行为,并帮助确定因果变化负责以前
发现协会。此外,该项目将使用LAB-SMI数据库来探索
SMI表型。具体来说,它将调查不同疾病轨迹的遗传基础,并挖掘
与先前(通过本项目或其他项目)显示的基因座相关的全套表型数据有助于
SMI诊断、症状或行为。
英文摘要
PROJECT SUMMARY / ABSTRACT
This proposed project will develop and make available to the scientific community the Latin American Biobank
of Severe Mental Illness (LAB-SMI). This resource, a databank and biobank (including DNA samples and both
phenotypic and genotypic data) for 50,000 individuals affected with SMI together with an equal number of
controls matched to the cases by age, gender, and geographical location will constitute a major step in reversing
the underrepresentation of Latin American populations in psychiatric genetics research. All of the participants
will be members of the “Paisa”, a genetically and culturally homogenous population that is the predominant ethnic
group in a region of Colombia (CO) that is home to ~9M people. Cases will consist of individuals affected with
psychotic or mood disorders who will be ascertained, agnostic to diagnosis, through the electronic medical
records (EMR) of five large psychiatric hospitals in the “Paisa region”. Controls will be individuals without a history
of an SMI diagnosis who will be ascertained through the databases of SURA, one of the largest providers of
primary care services in this region. By extracting a wide range of information from the EMR, using methods
developed in an existing investigation of SMI in a single Paisa-region hospital, the project team will record lifetime
designations of an SMI diagnosis and the presence or absence of SMI-related symptoms (such as delusions)
and behaviors (such as suicide attempt). It is hypothesized that these phenotypic features may share genetic
causation that transcends diagnostic categories. SNP genotyping and whole exome sequencing studies of the
entire 100K LAB-SMI will be well powered to identify novel associations across the allele frequency spectrum for
SMI diagnoses, symptoms, and behaviors, and to help identify the causal variation responsible for previously
discovered associations. Additionally, the project will use the LAB-SMI databank to explore the architecture of
SMI phenotypes. Specifically, it will investigate the genetic basis of different disease trajectories, and mine the
full set of phenotype data for association with loci shown previously (through this project or others) to contribute
to SMI diagnoses, symptoms, or behaviors.
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