Evidence For Genetic Variance in White Matter Hyperintensity Volume in Normal Elderly Male Twins

Abstract

Background and Purpose-White matter hyperintensities (WMHs), as detected by MRI, are common among the elderly and are frequently interpreted as representing a subclinical form of ischemic brain damage. We used volumetric MR techniques to investigate the contribution of genes and the environment to measures of brain morphology in a sample of community dwelling elderly male twins. Methods-Brain MR (1.5 T) scans were obtained from 74 monozygotic (MZ) and 71 dizygotic (DZ), white, male, World War II veteran twins born in the United States and age 68 to 79 when scanned. MR quantification used a previously published semiautomated segmentation algorithm to segment brain images into total brain, cerebrospinal fluid (CSF), and WMH volumes. Twin pair covariances were computed for each measure, and structural equation genetic models were fitted to these data. Results-Total cranial, brain parenchyma, CSF, and WMH volumes were highly correlated in MZ pairs, and correlations in MZ pairs were significantly greater than those in DZ pairs. Structural equation modeling indicated heritabilities of 91%, 92%, and 73%, respectively, for total cranial, brain parenchyma, and WMH volumes. Correction for age and head size reduced the heritability of brain parenchyma to 62% (95% confidence interval, 56% to 68%) and the heritability of WMH volume to 71% (95% confidence interval, 66% to 76%). Proband concordance rates for large amounts of WMH were 61% in MZ pairs and 38% in DZ pairs, compared with a prevalence of 15% in the entire sample. Conclusions-This study is the first to quantify the relative contribution of genetic and individual environmental influences to measures of brain morphology in the elderly.

Heritability of regional and global brain structure at the onset of puberty: A magnetic resonance imaging study in 9‐year‐old twin pairs

“…Our approach of studying children within a very narrow age-range allowed an estimation of heritability which is unaffected by age 3 genotype interactions or age-dependent gene expression [Plomin et al, 1997]. Our data are in line with heritability estimates of global brain volumes in adults [Baaré et al, 2001;Carmelli et al, 1998;Geschwind et al. 2002;Pfefferbaum et al, 2000;Posthuma and Boomsma, 2000;Wright et al, 2002] and with a pediatric sample in which a considerable part of the children had already entered adolescence [Wallace et al, 2006].…”

The phenotypes of bipolar disorder: relevance for genetic investigations

“…Heritability of WMHs was 0.73 in community dwelling elderly male subjects and 0.55 in a large population-based sample of stroke-and dementia-free subjects. 223,224 A high prevalence of WMHs is also found in 22q11-deletion syndrome frequently associated with psychosis, 225 cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, which is caused by mutations in the NOTCH3 gene on chromosome 19 and frequently associated with depression, and other less common genetic conditions. [226][227][228][229] Nongenetic factors are associated with WMHs as well; [230][231][232][233][234][235][236][237][238] for example, Moore et al 239 reported a correlation between WMH and season of birth in a group of patients with BD.…”

Cortical mapping of genotype–phenotype relationships in schizophrenia

“…Prior work using traditional volumetric approaches has shown high heritabilities for major neuroanatomic features [Baare et al, 2001;Bartley et al, 1997;Biondi et al, 1998;Carmelli et al, 1998;Geschwind et al, 2002;Oppenheim et al, 1989;Pennington et al, 2000;Pfefferbaum et al, 2000Pfefferbaum et al, , 2001Posthuma et al, 2000;Scamvougeras et al, 2003;Sullivan et al, 2001;Thompson et al, 2001Thompson et al, , 2004Tramo et al, 1998;White et al, 2002;Wright et al, 2002]. Based on variance component analyses, additive genetic influences appear to account for 52-91% of the total variance in intracranial volume [Carmelli et al, 1998;Pfefferbaum et al, 2000;Posthuma et al, 2000], 62-94% for total brain volume [Bartley et al, 1997;Carmelli et al, 1998;Wright et al, 2002], 82-87% for gray and white matter volumes [Baare et al, 2001], 40-69% for hippocampal volume , and 79-94% for corpus callosum areas [Pfefferbaum et al, 2000;Scamvougeras et al, 2003].…”

“…Based on variance component analyses, additive genetic influences appear to account for 52-91% of the total variance in intracranial volume [Carmelli et al, 1998;Pfefferbaum et al, 2000;Posthuma et al, 2000], 62-94% for total brain volume [Bartley et al, 1997;Carmelli et al, 1998;Wright et al, 2002], 82-87% for gray and white matter volumes [Baare et al, 2001], 40-69% for hippocampal volume , and 79-94% for corpus callosum areas [Pfefferbaum et al, 2000;Scamvougeras et al, 2003]. However, because many aspects of cortical surface geometry differ between individuals, and even between pairs of genetically identical cotwins, quantification techniques that do not account for individual differences in these features may be misleading.…”

“…Given that nearly half of all genes are expressed in the brain [Sandberg et al, 2000], and brain structure volumes are highly heritable [Carmelli et al, 1998;Pfefferbaum et al, 2000;Posthuma et al, 2000], neuroanatomic phenotypes offer a compelling alternative to categorically defined disease syndromes. It is our hypothesis that many of these genes contribute to schizophrenia susceptibility through their impact on brain systems involved in motivational, attentional, and memory processes, and that most of these genes have been undetected by previous studies that have examined syndromal status as the phenotypic target.…”