4.6 Review

Mapping genetic influences on human brain structure

Journal

ANNALS OF MEDICINE
Volume 34, Issue 7-8, Pages 523-536

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/078538902321117733

Keywords

Alzheimer's disease; anatomy; brain; cognition; genetics; imaging; MRI; quantitative trait loci (QTL); schizophrenia; twin

Funding

  1. NATIONAL CENTER FOR RESEARCH RESOURCES [P41RR013642] Funding Source: NIH RePORTER
  2. NATIONAL INSTITUTE OF MENTAL HEALTH [P20MH052176, P01MH052176, P20MH065166] Funding Source: NIH RePORTER
  3. NATIONAL LIBRARY OF MEDICINE [R01LM005639] Funding Source: NIH RePORTER
  4. NCRR NIH HHS [P41 RR13642] Funding Source: Medline
  5. NIMH NIH HHS [MH52176, MH65166] Funding Source: Medline
  6. NLM NIH HHS [LM05639] Funding Source: Medline

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Recent advances in brain imaging and genetics have empowered the mapping of genetic and environmental influences on the human brain. These techniques shed light on the 'nature/nurture' debate, revealing how genes determine individual differences in intelligence quotient (IQ) or risk for disease. They visualize which aspects of brain structure and function are heritable, and to what degree, linking these features with behavioral or cognitive traits or disease phenotypes. In genetically transmitted disorders such as schizophrenia, patterns of brain structure can be associated with increased disease liability, and sites can be mapped where non-genetic triggers may initiate disease. We recently developed a large-scale computational brain atlas, including data components from the Finnish Twin registry, to store information on individual variations in brain structure and their heritability. Algorithms from random field theory, anatomical modeling, and population genetics were combined to detect a genetic continuum in which brain structure is heavily genetically determined in some areas but not others. These algorithmic advances motivate studies of disease in which the normative atlas acts as a quantitative reference for the heritability of structural differences and deficits in patient populations. The resulting genetic brain maps isolate biological markers for inherited traits and disease susceptibility, which may serve as targets for genetic linkage and association studies. Computational methods from brain imaging and genetics can be fruitfully merged, to shed light on the inheritance of personality differences and behavioral traits, and the genetic transmission of diseases that affect the human brain.

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