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Variations in the incidence of schizophrenia: where to next John McGrath

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Variations in the incidence of schizophrenia: where to next John McGrath

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    1. Variations in the incidence of schizophrenia: where to next? John McGrath

    2. Outline of talk

    3. Beliefs about schizophrenia There is little or no variation in the incidence of schizophrenia WHO 10 nation study eight sites (seven nations). “Narrow” 7 to 14 per 100,000 (Aarhus, Denmark to Nottingham, UK, respectively. “Broad” 16 to 42 per 100,000 (Honolulu, Hawaii to the urban Chandigarh, India, respectively). “The results provide strong support for the notion that schizophrenic illnesses occur with comparable frequency in different populations…”.

    4. Beliefs about schizophrenia Men and women are equally affected

    7. Methods Electronic data search Medline PsychoInfo Embase LILAC 1965-2001 inclusive (schizo* OR psycho*) AND incidence OR prevalence) Review article bibliography Writing to authors

    8. Results Electronic search = 834 potential papers Manual checking = 249 potential papers Letters from 52 authors, who provided an additional 41 references Of potentially relevant papers, 74% were identified from electronic sources 98 studies in Languages Other Than English (LOTE) – after translation 10 were included in the study.

    9. Results 1,458 rates. Rates based on 176,056 potentially overlapping incident cases Data from 33 countries Types of studies Core studies = 100 Migrant studies = 24 Cohort studies = 23 Other special groups = 14

    14. Urban rural differences

    15. Other gradients Increased paternal age Season of birth Latitude Urban birth/residence Prenatal famine Prenatal infection Obstetric complications Cannabis use

    16. The epidemiological landscape of schizophrenia is rich and informative

    17.

    18. A systematic review of mortality in schizophrenia

    19. Results 37 studies = 561 SMRs for different causes of death SMRs based on 22,296 discrete deaths From 25 countries

    20. All-cause SMRs

    21. The differential mortality gap is worsening 2-3 fold increased risk The gap is getting wider! 1970s = 1.8 fold risk 1980s = 2.9 fold risk 1990s = 3.2 fold risk

    22. Where to next? What type of epidemiology should we do now? How can we leverage variation? How can we differentiate risk indicators versus risk modifiers? Confounding and the imprecision of epidemiology

    23. Can we model incidence, mortality, recovery, and prevalence estimates?

    26. The profound heterogeneity of schizophrenia Clinical features Neurobiological correlates Course of illness ‘Heritable’ susceptibility factors Exposures that influence susceptibility

    28. Sources of variation The prevalence of candidate susceptibility genes vary between groups sorted by “distant geographical origin”

    29. Understanding how evolution builds robust systems Emergent properties of complex systems

    30. Building a brain over evolutionary time Important process are buffered by complex regulatory control Key features of brain development are often ‘frozen accidents’ Behavioural phenotypes are emergent properties of complex systems.

    31. What happens when recently evolved brain systems fail? The brain has a complex web of back-up systems When one system falters, other systems will try to take over If the reserve functions fail, then symptoms “break through” “System crash” versus “graceful degradation” Last in – first to break

    32.

    33. What needs to be done now? Use epidemiology and genetics to provide clues to pathways Establish tight linkages with neuroscience in order to explore candidates

    34. The ataxia of schizophrenia epidemiology Circular epidemiology – season of birth Will the interesting new clues be wasted? Migrant status Urban birth

    35. Why epidemiology needs neuroscience – and vice versa The curse of observation epidemiology In the absence of RCTs, how else can we interrogate clues from epidemiology?

    37. Why epidemiology needs neuroscience – and vice versa Links to clinical neuroscience Post-mortem studies Genetics Neuroimaging Animal models Biological plausibility Can help rank order candidates Experimental efficiencies

    38. Why neuroscience benefits from epidemiology Epidemiologically-derived clues can help Uncover previously unsuspected pathways Focus biological research on pathways related to human diseases Vitamin A, folate Different animals can provide different clues Rodents, flies, bees, zebra fish

    39. The vitamin D hypothesis Low prenatal vitamin D impacts adversely on brain development, leaving the affected offspring at increased risk of schizophrenia.

    40. Rat experiments

    41. Future directions Measuring 25 OH vitamin D3 in neonatal dried blood spots. Nested case-control study

    42. Animal models to examine potential mechanisms linking paternal age and schizophrenia

    43. Integrated research programs

    44. Linking epidemiology and neuroscience

    45. “One should not be afraid to try new things, such as moving from one field to another or working at the boundaries of different disciplines, for it is at the borders that some of the most interesting problems reside” Eric Kandel

    46. Variations in schizophrenia epidemiology are here to stay. We can’t afford to waste these clues Avoid circular epidemiology Link psychiatric epidemiology with neuroscience

    47. Acknowledgements

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