Twin Registers: The Danish Twin Registry Axel Skytthe, Institute of Pubic Health, University of Southern Denmark.

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Presentation transcript:

Twin Registers: The Danish Twin Registry Axel Skytthe, Institute of Pubic Health, University of Southern Denmark

Twin Registers Collection of individuals from multiple births … Register:  Longitudinal dimension - maintenance  Continued follow-up  Big numbers … Purpose:  Provide basis for studies to disentangle the importance of genetic, familial and environmental factors on life events, health conditions and diseases

Types of Twin Registers  Local registers vs. national registers  Specific vs. general  Focus on a specific phenotype  Wide range of phenotypes  Population-based vs. Disease-based

Ascertainment  Identification methods  Self-reported  Advertisments  Hospital-based  Medical birth records  Population registers  Follow up / Tracing  Population registers  Death registers  Relatives  Probate court

Twin Registers - Examples Nordic twin registers n Sweden Established in late 1950’s Birth cohorts Approx. 97,000 twin pairs n Norway 3 separate twin cohorts compiled at different research institutions, and each compiled with specific research agendas Birth cohorts from and Approx. 67,000 twin pairs Not consistently followed up n Finland First cohort established 1975 from Central population register Approx. 65,000 twin pairs

Twin Registers - Examples European n Sct Thomas, UK Established 1990 Volunteers Focused on diseases occuring in women -> predominantly same-sexed female twin pairs n The Netherlands Twin Register Established 1986 Predominantly young twins registered at birth Includes other family members as well Approx. 30,000 win pairs n East Flandern Prospective Twin Survey Initiated in 1964 Registered at birth – collection of data related to twin maternities Approx 7,000 twin pairs n Italian Twin Register Initiated 1996 as a register of ”possible twins” – 600,000 pairs Enrolled approx. 4,500 twin pairs

Twin Registers - Examples Outside Europe n NAS-NRC Twin Registry of WWII Military Veteran Twins Established in 1960’s Only white male-male twin pairs – 16,000 twin pairs Born Both served in the armed forces n Minnesota Twin Registry (USA) Established in 1983 Birth record based … n Vietnam Era Twin Registry (USA) Established mid 1980’s Only male-male twin pairs – 7,369 twin pairs Both serving in the military during Identification based on miltary records

Danish Twin Registry (DTR) – Old Cohorts Local vicars searched births registers and reported twins

DTR – Old Cohorts Local vicars searched birth registers and reported twins Twins were traced through municipial population registers, death registers, probate courts, family members Period:

The Old Core of DTR

The Old Core...

Data processing...

DTR – Young Cohorts Identified and traced through the national Civil Registration System Selection criteria: Children of mothers giving birth to more than one child within 3 days Period:

DTR – Young Cohorts

DTR – Middle Cohorts Mainly identified and traced through the CRS, followed by questionnaire of twin status Selection criteria: Persons born the same day and same place, and given the same surname at birth Period:

DTR – Child Cohorts Identified through the Medical Birth Registry as all multiple births Traced through CRS Period:

DTR – Number of Twin Pairs - Gender Gender Twin pairs born CohortM/MM/FF/FUnknownTotal # # Total § # Twin pairs born outside Denmark are included in DTR (678 twin pairs) § In addition 775 triplets and 22 quadruplets are included in DTR

Assesment of Zygosity Questionnaire method Similarity questions: n 1. Do you and your twin look - like two ordinary siblings? - like two peas in a pod? - not very much alike? n 2. In school, is/was it difficult for your teachers and friends to tell you apart? n 3. Is/was it difficult for your family and friends to tell you apart? n 4. In childhood, did you and your twin have both the same eye color and the same hair color? Biological material n Serological markers n Genetic markers

Zygosity Assesment - Accuracy MZ accuracyDZ accuracyTotal accuracy Men (N= 342)92% (155/169)99% (172/173)96% (327/342) Women (N= 525)96% (229/239)96% (275/286)96% (504/525) Christiansen et al., Twin Res 2003;6:

Zygosity Assesment - Accuracy Birth cohortsMZ accuracyDZ accuracyTotal accuracy (N = 250)94% (94/100)93% (139/150)93% (233/250) (N = 143)97% (72/74)99% (68/69)98% (140/143) (N = 474)93% (218/234)100% (240/240)97% (458/474) All cohorts (N = 867)94% (384/408)97% (447/459)96% (831/867) Christiansen et al., Twin Res 2003;6:

DTR – Number of Twin Pairs - Zygosity Zygosity CohortMZDZ-SSDZ-OSUZTotal # # Total § # Twin pairs born outside Denmark are included in DTR (678 twin pairs) § In addition 775 triplets and 22 quadruplets are included in DTR

Basic Data Core data n Identification n Gender n Date of birth, place of birth n Name & address n Vital status (incl. date of death, emigration) n Protection status n Zygosity

DTR – Present Core Data Structure Person Id PNR Date of Birth Gender Name Address Vital status Date of Vital st. Access Pair Pair-Id Tw1-Id Tw2-Id Type Ascertainment Method Date of Ascert Zygosity Pair-Id Zygosity Method Date of assessment Parent-Child P-Id C-Id Type (biol/legal) Spouse Sp-Id Marital status Date of M.St.

Additional Data Test results (performance tests, physical, cognitive) Family (Spouse(s), Parents, Children) Biological material n Blood spots on filter paper n Full blood samples n Cheek swab n Hair Pictures

Surveys Questionnaire surveys n Large scale self-administered questionnaire surveys (1966, 1994, 2002, 2003) n Interview-based surveys (LSADT , MADT 1998) Disease-specific surveys n Asthma n Low back pain n Epilepsy n Arthritis Clinical studies n GEMINAKAR – 1 day test program (e.g. oral glucose test, fat tolerance test, fitness, EKG, BP, blood samples, etc)

Middle-aged Twins 2008 Biobank with samples from 13,000 twins Collection period Birth cohorts Full blood samples Short questionnaire n Life style n Health problems n Medicine n SES Physical and cognitive performance Height, weight

Data from National Registers DTR Medical Birth Register Hospital Discharge Register Cancer Register Death causes Population Register Requirement: Unique Personal Identification Number (PIN) used in all registers

Linkage to Databases and Registers Registration unit of database? n Hospital discharge register: Admissions Diagnoses Operational procedures Organisation of database? n Cross-sectional vs. longitudinal Truncation? n Which period is covered by database? Studybase? n Both twins should be at risk

Twins and Register-based Research Advantages n Data exist n Big numbers n No dropout n No bias n Population-based Caution n Zygosity needed n Not all phenotypes available n Administrative registers – not always suited for research