Neuroimaging Genetics

By correlating neuroimaging data with genetic data, imaging genetics tries to discover genes (=genotype) affecting brain function and connectivity (=phenotype), and to identify risks for neurological and psychiatric diseases [1].

The ENIGMA (=Enhancing Neuro Imaging Genetics through Meta-Analysis) project has gathered 21,000 brain scans and genomic profiles [2]. Two examples of the outcome of this project are:

  • Studies have identified genetic variants affecting the volume of the hippocampus [3], which could be used as predictors of cognitive decline and dementia [4];
  • Some genes, such as the Met Receptor Tyrosine Kinase (MET) gene, confer increased risk for autism. MET risk genotype predicted atypical fMRI activation and deactivation patterns to social stimuli (i.e., emotional faces), as well as reduced functional and (DTI-based) structural connectivity in temporo-parietal regions known to have high MET expression [5].

Imaging genetics has been used in clinical trials, e.g. in OCD patients [6]. On the other hand, genomics has been used to predict treatment response [7], giving rise to a new discipline called “personalized medicine”. Some genetic risk factors, such as ApoE, are well known in Alzheimer’s disease [8]. Although not considered as genetic diseases, there are genes that seem to be associated with multiple sclerosis [9] and neuropsychiatric disorders [10].

Neuroimaging Genetics: References

  1. [1] Jahanshad N, Hibar DP, Ryles A, et al. DISCOVERY OF GENES THAT AFFECT HUMAN BRAIN CONNECTIVITY: A GENOME-WIDE ANALYSIS OF THE CONNECTOME. Proc. IEEE Int. Symp. Biomed. Imaging Nano Macro IEEE Int. Symp. Biomed. Imaging. , 542–545 (2012).
  2. [2] Genetic Analysis of Brain Images from 21,000 people: The ENIGMA Project
  3. [3] Bis JC, DeCarli C, Smith AV, et al. Common variants at 12q14 and 12q24 are associated with hippocampal volume. Nat. Genet. 44(5), 545–551 (2012).
  4. [4] Jahanshad N, Rajagopalan P, Hua X, et al. Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity. Proc. Natl. Acad. Sci. U. S. A. 110(12), 4768–4773 (2013).
  5. [5] Rudie JD, Hernandez LM, Brown JA, et al. Autism-associated promoter variant in MET impacts functional and structural brain networks. Neuron. 75(5), 904–915 (2012).
  6. [6] Hoexter MQ, Shavitt RG, D’Alcante CC, et al. The drug-naïve OCD patients imaging genetics, cognitive and treatment response study: methods and sample description. Rev. Bras. Psiquiatr. São Paulo Braz. 1999. 31(4), 349–353 (2009).
  7. [7] Garman KS, Nevins JR, Potti A. Genomic strategies for personalized cancer therapy. Hum. Mol. Genet. 16(R2), R226–R232 (2007).
  8. [8] Ringman JM, Coppola G. New genes and new insights from old genes: update on Alzheimer disease. Contin. Minneap. Minn. 19(2 Dementia), 358–371 (2013).
  9. [9] Dyment DA, Ebers GC, Sadovnick AD. Genetics of multiple sclerosis. Lancet Neurol. 3(2), 104–110 (2004).
  10. [10] Ehninger D, Silva AJ. Genetics and neuropsychiatric disorders: Treatment during adulthood. Nat. Med. 15(8), 849–850 (2009).

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