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Analysis of shared heritability
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SEMINAR
Analysis of shared heritabiLity IN COMMON DISORDERS OF THE BRAIN
María Jesús Grueso Alcántara
Neurogenetics
Supervisor: Eva Beins Life & Brain Universität Bonn
TABLE OF CONTENTS
4. Main conclusions
1. Introduction
5. References
2. Study design
3. Results
1. INTRODUCTION
Brain disorders, overlaps among them and goals of the study
How do hugs feel?
'A picture is worth a thousand words'
Define Mondays
...same as a good diagnosis.
more overlaps or differences at the genomic level?
Understanding the genetic underpinnings may inform about their biological mechanisms
Brain disorders
There are phenotypic and symptomatic overlaps, as well as shared individual common risk variants.
What about its CLASSIFICATION? It has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena.
PSYCHIATRIC DISORDERS
NEUROLOGICAL DISORDERS
Brain disorders included in the Brainstorm project
HERITABILITY
Relation with brain disorders
dEFINITION
Heritability is a statistic representing the percentage of phenotype variability that can be attributed to genetic variation.
Studies of twins and families have indicated that, in general, brain disorders (except those caused by trauma, infection or cancer) show substantial heritability.
Linkage disequilibrium score (ldsc) regression
Heritability methods
MAIN GOALS OF THE STUDY
Inform the search for the biological mechanisms of brain disorders
Shed light on the nature of diagnostic boundaries in brain disorders
2. Explore how statistical power, diagnostic misclassification and phenotypic heterogeneity affect genetic correlations
1. Quantify the overlap for genetic risk factors of 25 brain disorders using GWAS data
2. STUDY DESIGN
GWAS metaanalysis consortia for 25 disorders
brainstorm consortium
which meta-analysis were included?
GWAS meta-analyses of sufficient size for heritability analysis.
STUDY SAMPLE
- 265218 patients with 25 different brain disorders.
- 784643 control participants.
- 1191588 individuals with 17 different phenotypes.
3. RESULTS
Heritability estimates, error sources and correlations
3.1 heritability estimates and their error sources
Similar range of heritability estimates among the disorders and the behavioral-cognitive phenotypes.
3.1 heritability estimates and their error sources
- Common variant heritability estimates for the brain disorders were generally LOWER than previously reported estimates
SOME ATTENUATION IN HERITABILITY IS OBSERVED WHEN MOVING TO LARGER SAMPLE SIZES
- Correlation between heritability and age of disorder onset.
Early onset brain disorders tend to be more heritable
are Methodological differences contributing to the variations in the estimates?
what about rare variants?
3.2 correlations among brain disorders
Psychiatric disorders
Psychiatric disorders
Psychiatric disorders
Neurological disorders
Neurological disorders
Behavioural-cognitive and additional phenotypes
Neurological disorders
Neurological disorders
Psychiatric disorders
Behavioural-cognitive and additional phenotypes
3.2.1 widespread sharing across psychiatric disorders
1. Schizophrenia: significant genetic correlation with most of the psychiatric disorders. 2. Significant sharing among: - Anorexia nervosa, OCD and schizophrenia. - TS, OCD and MDD. 3. ASD and TS: potentially more distinct from the other psychiatric disorders. 4. PSTD: no significant correlation with any of the other psychiatric phenotypes.
3.2.2 Less sharing across neurological disorders
1. Parkinson’s disease, AD, generalized epilepsy, and MS: little to no correlation with other brain disorders. 2. Focal epilepsy: highest degree of genetic correlation among the neurological disorders , though none of the correlations were significant.
Suggesting greater diagnostic specifity and/or more distinct etiologies
3.2.3 LIMITED sharing across neurological AND PSYCHIATRIC disorders
1. The only significant cross-category correlations were with migraine.
Suggesting that migraine share some of its genetics with psychiatric disorders
3.2.4 SIGNIFICANT CORRELATIONS BETWEEN phenotypes AND brain DISORDERS
BEHAVIOURAL-COGNITIVE PHENOTYPES
1. Years of education and college attainment: positive correlation with psychiatric disorders, negative correlation with neurological phenotypes. 2. Neuroticism: correlated with almost every psychiatric disorder and migraine.
3.2.5 SIGNIFICANT CORRELATIONS BETWEEN PHENOTYPES AND brain DISORDERS
ADDITIONAL PHENOTYPES
1. BMI: positively correlated with ADHD and MDD, and negatively correlated with anorexia nervosa. 2. Myocardial infarction: correlation with MDD, ischemic stroke and early-onset stroke.
4. MAIN CONCLUSIONS
take-home messages
Psychiatric disorders share a considerable portion of their common variant genetic risk.Their current clinical boundaries do not reflect distinct underlying pathogenic processes. Neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine.Their current classification reflects relatively specific genetic etiologies.Neuroticism is significantly correlated with almost every psychiatric disorder and migraine.Years of education shows genetic sharing with different brain disorders, either positively or negatively.
outlook
1. Need to REFINE psychiatric nosology and diagnostics: genetically informed analyses may provide a basis, consistent with twin- and family-based results. 2. The existing clinical delineation between neurology and psychiatry is corroborated at the level of common variant risk for the studied disorders. Multiple different and largely independently regulated etiological pathways may give rise to similar clinical manifestations. 3. Both psychiatric and neurological disorders show robust correlations with cognitive and personality measures, indicating avenues for follow-up studies.
6. references
Anttila V, Bulik-Sullivan B, Finucane HK, Walters RK, Bras J, Duncan L, et al. Analysis of shared heritability in common disorders of the brain. Science (80- ). 2018;360(6395).
Hill WG. Heritability. Brenner’s Encycl Genet Second Ed. 2013 Feb 27;432–4. Bulik-Sullivan BK, Loh PR, Finucane HK, Ripke S, Yang J; Schizophrenia Working Group of the Psychiatric Genomics Consortium, Patterson N, Daly MJ, Price AL, Neale BM. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015 Mar;47(3):291-5. doi: 10.1038/ng.3211.
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