Bruce Wolffenbuttel Joost Keers LifeLines. ‘Broad spectre’ Biobank:  Genes, physical examinations, lifestyle, environment, psychological. 165,000 people.

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Presentation transcript:

Bruce Wolffenbuttel Joost Keers LifeLines

‘Broad spectre’ Biobank:  Genes, physical examinations, lifestyle, environment, psychological. 165,000 people 3 generations 30 years follow-up

Focus Ageing Metabolic disease & Diabetes Cardiovascular & Renal Asthma, COPD, Allergy ‘ Psychiatry’ (Depression & Cognitive) Musculoskeletal & Joint

1st generation 2nd generation 3rd generation jr Father Mother Partner’s father Partner’s mother ‘Index’ Partner Child 1 Child 2 45,000 30,000 55,00035,000 Total number of participants: 165,000

Datacollecting: 5-year cycle Baseline 1 year General & Thematic 2 year General & Thematic 3year General & Thematic 4 year General & Thematic

LifeLines gegevens verzameling LifeLines Datacenter LifeLines Lab & Archive, QA/QC GP Records GP Health Record Symptoms Diagnoses Referrals Medications Procedures Hospital Records ICD-10/ICD-9 (Diagnoses) OPCS4 (procedure) Primary Diagnosis Questionnaire e.g. Diet Circumstances Family History Employment Smoking, alcohol Lifestyle Medications Cognitive Function Health Measurements e.g. Height, Weight Respiratory Function Sight Blood Pressure Results Biochemistry Haematology Advanced testing Biomarkers Genomics Yearly

First step Asking all departments (UMCG) what they need/ want to be measured in lifeLines Categorizing wishes and needs  Outcome – predictor  Related to central focus?  Looking for overlap  Determine multiple interests

Second step Selection of baseline measures based on 1st step Comparing this selection to other biobanks using the Datashaper Adapting selection based on Datashaper

Third step Selection or composing measures to collect data (Questionnaires, procedures, lab, etc.). Using Datashaper/ catalogue Feedback to departments Monitoring during use (pilot study, interviews)

How we used Datashaper Making sure we measured the most important domains As a support to select a variable Making sure our ‘data-items’ can be converted into variables that can be shared. Extra focus on registrating data-collection procedures and cirumstances, using SOPs

When we did not follow datashaper With respect to some variables we used more detailled instruments to collect data, e.g. quality of life and well-being. ‘unique’ interests (cognitive functioning, personality).