Genetic Influences on Four Measures of Executive Functions and Their Covariation with General Cognitive Ability: The Older Australian Twins Study

Lee, Teresa; Mosing, Miriam A.; Henry, Julie D.; Trollor, Julian N.; Ames, David; Martin, Nicholas G.; Wright, Margaret J.; Sachdev, Perminder S.

doi:10.1007/s10519-012-9526-1

Cited by 63 publications

(54 citation statements)

References 41 publications

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“…65 Previous studies of the genetic overlap between trail making and other cognitive abilities have shown genetic overlap between trail making and general cognitive function using a twin design. 30,34 Our results add to this by using a molecular genetic design and showing shared genetic aetiology between trail making and verbal numerical reasoning in UK Biobank, as well as with general cognitive function, processing speed, and memory from the CHARGE consortium. The estimates of the genetic correlations within UK Biobank were similar for both GCTA-GREML and LDS regression, suggesting that these results are unlikely to constitute false positives.…”

Section: Discussionsupporting

confidence: 58%

“…The results are consistent with the hypothesis that trail making is genetically and phenotypically similar to general fluid cognitive function. 9,20,34 Univariate GCTA-GREML analyses suggested SNP-based heritability estimates for TMT A, TMT B and TMT B − A of 8%, 22% and 18%, respectively. These provide a first estimate of the contribution of common SNPs to the phenotype of trail making and suggest that common SNPs account for around half of the additive genetic variation for trail making, based on twin and family studies.…”

Section: Discussionmentioning

confidence: 99%

“…32,33 Trail making is thought to have genetic influences that are shared with other cognitive abilities, with a twin-based genetic correlation of 0.48 reported between trail making, measured as the ratio between trail making part A and trail making part B, and general cognitive function, and 0.52 with working memory. 34 In addition to a relatively poor understanding of the molecular genetic underpinnings of TMT, its cognitive and psychometric architecture merits further research. Specifically, it is unclear whether the cognitive abilities required for TMT B performance are distinct from other cognitive domains, because TMT A and B scores correlate with measures of general cognitive function and processing speed (correlation coefficient estimates range from 0.3 to~0.7 (refs 9,20)).…”

Section: Introductionmentioning

confidence: 99%

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Genetic contributions to Trail Making Test performance in UK Biobank

et al. 2017

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The Trail Making Test (TMT) is a widely used test of executive function and has been thought to be strongly associated with general cognitive function. We examined the genetic architecture of the TMT and its shared genetic aetiology with other tests of cognitive function in 23 821 participants from UK Biobank. The single-nucleotide polymorphism-based heritability estimates for trail-making measures were 7.9% (part A), 22.4% (part B) and 17.6% (part B − part A). Significant genetic correlations were identified between trail-making measures and verbal-numerical reasoning (r g 40.6), general cognitive function (r g 40.6), processing speed (r g 40.7) and memory (r g 40.3). Polygenic profile analysis indicated considerable shared genetic aetiology between trail making, general cognitive function, processing speed and memory (standardized β between 0.03 and 0.08). These results suggest that trail making is both phenotypically and genetically strongly associated with general cognitive function and processing speed.Molecular Psychiatry advance online publication, 19 September 2017; doi:10.1038/mp.2017.189 INTRODUCTIONThe Trail Making Test (TMT) is widely used in both research and clinical settings as a test of some aspects of executive function. [1][2][3] The TMT is usually given as two parts, from which three measures are derived. In TMT Part A (TMT A), participants are required to connect an array of numbers in ascending order, by drawing a continuous line (trail) between them as quickly and accurately as possible. TMT Part B (TMT B) requires participants to connect an array of both numbers and letters in alternating ascending order (1, A, 2, B, 3, C and so on) with the same emphasis on speed and accuracy (Supplementary Figure 1). Subtracting TMT A completion time from that of TMT B (TMT B − A) is thought to allow the relative contributions of visual search and psychomotor speed to be parsed from the more complex executive functions (such as cognitive flexibility) required to alternate between numbers and letters. [4][5][6][7][8] TMT performance has been ascribed to a number of cognitive processes, 'including attention, visual search and scanning, sequencing and shifting, psychomotor speed, abstraction, flexibility, ability to execute and modify a plan of action, and ability to maintain two trains of thought simultaneously '. 9 It is considered a useful tool in research and clinical practice due to the sensitivity of the task (particularly TMT B and B − A) to frontal lobe damage (in some, but not other studies 10 ) and dementia. [11][12][13] There are declines in both TMT A and B performance in ageing. 10,[14][15][16][17][18][19][20] There is also evidence for performance deficits on TMT B in mood disorders 21 and in patients with schizophrenia and their relatives 18,[22][23][24][25][26][27] Family-based and twin-based studies have provided evidence for a genetic contribution to individual differences in trail making, estimating the heritability for trail making part A between 0.23 and 0.38, and between 0.39 and 0.65...

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Section: Discussionsupporting

confidence: 58%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genetic contributions to Trail Making Test performance in UK Biobank

et al. 2017

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“…Moreover, these findings are in agreement with reported heritability estimates of diverse cognitive abilities in children and adolescents using the same genetic approach [Benyamin B et al, 2013; Trzaskowski M et al, 2013; Roninson EB et al, 2014], supporting the contribution of multiple common variants to neurocognitive functioning. Twin and family studies in clinical and non‐clinical samples have also revealed a considerable heritability for WM [Greenwood TA et al, 2007; Wilson RS et al, 2011; Goldberg X et al, 2013], as well as a significant genetic relationship between general cognitive ability and aspects of executive function, including WM [Aukes MF et al, 2009; Lee T et al, [Link]]. In addition, neuroimaging findings in young twins of the same age range as the participants in the current study, who performed the same WM N‐back task, demonstrated an increased heritability for WM‐related brain activation [Blokland GA et al, 2011].…”

Section: Discussionmentioning

confidence: 99%

Common genetic variation and schizophrenia polygenic risk influence neurocognitive performance in young adulthood

Hatzimanolis

Bhatnagar

Moes

et al. 2015

American J of Med Genetics Pt B

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Neurocognitive abilities constitute complex traits with considerable heritability. Impaired neurocognition is typically observed in schizophrenia (SZ), whereas convergent evidence has shown shared genetic determinants between neurocognition and SZ. Here, we report a genome‐wide association study (GWAS) on neuropsychological and oculomotor traits, linked to SZ, in a general population sample of healthy young males (n = 1079). Follow‐up genotyping was performed in an identically phenotyped internal sample (n = 738) and an independent cohort of young males with comparable neuropsychological measures (n = 825). Heritability estimates were determined based on genome‐wide single‐nucleotide polymorphisms (SNPs) and potential regulatory effects on gene expression were assessed in human brain. Correlations with general cognitive ability and SZ risk polygenic scores were tested utilizing meta‐analysis GWAS results by the Cognitive Genomics Consortium (COGENT) and the Psychiatric Genomics Consortium (PGC‐SZ). The GWAS results implicated biologically relevant genetic loci encoding protein targets involved in synaptic neurotransmission, although no robust individual replication was detected and thus additional validation is required. Secondary permutation‐based analysis revealed an excess of strongly associated loci among GWAS top‐ranked signals for verbal working memory (WM) and antisaccade intra‐subject reaction time variability (empirical P < 0.001), suggesting multiple true‐positive single‐SNP associations. Substantial heritability was observed for WM performance. Further, sustained attention/vigilance and WM were suggestively correlated with both COGENT and PGC‐SZ derived polygenic scores. Overall, these results imply that common genetic variation explains some of the variability in neurocognitive functioning among young adults, particularly WM, and provide supportive evidence that increased SZ genetic risk predicts neurocognitive fluctuations in the general population. © 2015 The Authors American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

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“…All the covariation between the four measures, and their covariation with GCA were attributable to one genetic factor. The genetic correlations between the measures were moderately high, suggesting that they have common biological underpinnings (Lee et al, 2012b).…”

Section: Genetic Infl Uences On Four Measures Of Executive Functionmentioning

confidence: 99%

The contribution of twins to the study of cognitive ageing and dementia: The Older Australian Twins Study

Sachdev

Lee

Wang

et al. 2013

International Review of Psychiatry

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The Older Australian Twins Study (OATS) is a major longitudinal study of twins, aged ≥ 65 years, to investigate genetic and environmental factors and their interactions in healthy brain ageing and neurocognitive disorders. The study collects psychiatric, neuropsychological, cardiovascular, metabolic, biochemical, neuroimaging, genomic and proteomic data, with two-yearly assessments, and is currently in its third wave. The initial cohort comprises 623 individuals (161 monozygotic and 124 dizygotic twin pairs; 1 MZ triplets; 27 single twins and 23 non-twin siblings), of whom 426 have had wave 2 assessment. A number of salient findings have emerged thus far which assist in the understanding of genetic contributions to cognitive functions such as processing speed, executive ability and episodic memory, and which support the brain reserve hypothesis. The heritability of brain structures, both cortical and subcortical, brain spectroscopic metabolites and markers of small vessel disease, such as lacunar infarction and white matter hyperintensities, have been examined and can inform future genetic investigations. Work on amyloid imaging and functional magnetic resonance imaging is proceeding and epigenetic studies are progressing. This internationally important study has the potential to inform research into cognitive ageing in the future, and offers an excellent resource for collaborative work.

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Genetic Influences on Four Measures of Executive Functions and Their Covariation with General Cognitive Ability: The Older Australian Twins Study

Cited by 63 publications

References 41 publications

Genetic contributions to Trail Making Test performance in UK Biobank

Genetic contributions to Trail Making Test performance in UK Biobank

Common genetic variation and schizophrenia polygenic risk influence neurocognitive performance in young adulthood

The contribution of twins to the study of cognitive ageing and dementia: The Older Australian Twins Study

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