Imaging the genetics of executive function

Recent advances in neuroimaging technologies have allowed ever more detailed studies of the human brain. The combination of neuroimaging techniques with genetics may provide a more sensitive measure of the influence of genetic variants on cognitive function than behavioural measures alone. Here we present a review of functional magnetic resonance imaging (fMRI) studies of genetic links to executive functions, focusing on sustained attention, working memory and response inhibition. In addition to studies in the normal population, we also address findings from three clinical populations: schizophrenia, ADHD and autism spectrum disorders. While the findings in the populations studied do not always converge, they all point to the usefulness of neuroimaging techniques such as fMRI as potential endophenotypes for parsing the genetic aetiology of executive function. (C) 2007 Elsevier B.V. All rights reserved.

Understanding marine reserve function in a seascape genetics context: Nucella lapillus in Strangford Lough (Northern Ireland) as an example

A conservation priority in the marine environment is the establishment of ecologically coherent reserve networks. Since these networks will integrate existent reserves, an understanding of spatial genetic diversity and genetic connectivities between areas is necessary. Using Strangford Lough marine nature reserve (MNR) as a model, spatial genetic analyses were employed to evaluate the function of the lough. Samples of the marine gastropod Nucella lapillus (L.) from 7 locations in the reserve and adjacent areas were screened at 6 microsatellites. Genetic variation was temporally stable. Significant genetic structuring (F-ST = 0.133) was observed among samples. Genetic divergence and isolation by distance indicated reduced gene flow between the marine reserve and coastal samples relative to that between adjacent coastal samples. Partitioning of genetic variation between the reserve and coast was significant (AMOVA, 7.45%, p

The historical geography of ancient Sicily: implications for genetics.

Malone, C.A.T. and S.K.F. Stoddart, . (co-authored).

Contribution of 30 Biomarkers to 10-year cardiovascular risk estimation in 2 population cohorts: The MONICA, risk, genetics, archiving and monograph (MORGAM) biomarker project

Background— Cardiovascular risk estimation by novel biomarkers needs assessment in disease-free population cohorts, followed up for incident cardiovascular events, assaying the serum and plasma archived at baseline. We report results from 2 cohorts in such a continuing study.
Methods and Results— Thirty novel biomarkers from different pathophysiological pathways were evaluated in 7915 men and women of the FINRISK97 population cohort with 538 incident cardiovascular events at 10 years (fatal or nonfatal coronary or stroke events), from which a biomarker score was developed and then validated in the 2551 men of the Belfast Prospective Epidemiological Study of Myocardial Infarction (PRIME) cohort (260 events). No single biomarker consistently improved risk estimation in FINRISK97 men and FINRISK97 women and the Belfast PRIME Men cohort after allowing for confounding factors; however, the strongest associations (with hazard ratio per SD in FINRISK97 men) were found for N-terminal pro-brain natriuretic peptide (1.23), C-reactive protein (1.23), B-type natriuretic peptide (1.19), and sensitive troponin I (1.18). A biomarker score was developed from the FINRISK97 cohort with the use of regression coefficients and lasso methods, with selection of troponin I, C-reactive protein, and N-terminal pro-brain natriuretic peptide. Adding this score to a conventional risk factor model in the Belfast PRIME Men cohort validated it by improved c-statistics (P=0.004) and integrated discrimination (P<0.0001) and led to significant reclassification of individuals into risk categories (P=0.0008).
Conclusions— The addition of a biomarker score including N-terminal pro-brain natriuretic peptide, C-reactive protein, and sensitive troponin I to a conventional risk model improved 10-year risk estimation for cardiovascular events in 2 middle-aged European populations. Further validation is needed in other populations and age groups.