Cohort Profile: The Lothian Birth Cohorts of 1921 and 1936

Deary, Ian J.; Gow, Alan J.; Pattie, Alison; Starr, John M.

doi:10.1093/ije/dyr197

Cited by 366 publications

(453 citation statements)

References 73 publications

(63 reference statements)

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“…Validation of age-associated CpGs was done in two independent longitudinal cohorts; the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) [18] and the Lothian Birth Cohort (LBC) [19]. The PIVUS cohort measured methylation data from 196 individuals at age 70 and 80, and the LBC cohort, including two sub-cohorts of 906 and 436 individuals at baseline, measured blood samples at three time points, with mean ages of 70 and 79 at baseline (Table S1).…”

Section: Resultsmentioning

confidence: 99%

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Epigenetic influences on aging: a longitudinal genome-wide methylation study in old Swedish twins

et al. 2018

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Age-related changes in DNA methylation were observed in cross-sectional studies, but longitudinal evidence is still limited. Here, we aimed to characterize longitudinal age-related methylation patterns using 1011 blood samples collected from 385 Swedish twins (age at entry: mean 69 and standard deviation 9.7, 73 monozygotic and 96 dizygotic pairs) up to five times (mean 2.6) over 20 years (mean 8.7). We identified 1316 age-associated methylation sites (P<1.3×10−7) using a longitudinal epigenome-wide association study design. We measured how estimated cellular compositions changed with age and how much they confounded the age effect. We validated the results in two independent longitudinal cohorts, where 118 CpGs were replicated in Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS, 390 samples) (P<3.9×10−5), 594 in Lothian Birth Cohort (LBC, 3018 samples) (P<5.1×10−5) and 63 in both. Functional annotation of age-associated CpGs showed enrichment in CCCTC-binding factor (CTCF) and other transcription factor binding sites. We further investigated genetic influences on methylation and found no interaction between age and genetic effects in the 1316 age-associated CpGs. Moreover, in the same CpGs, methylation differences within twin pairs increased with 6.4% over 10 years, where monozygotic twins had smaller intra-pair differences than dizygotic twins. In conclusion, we show that age-related methylation changes persist in a longitudinal perspective, and are fairly stable across cohorts. The changes are under genetic influence, although this effect is independent of age. Moreover, methylation variability increase over time, especially in age-associated CpGs, indicating the increase of environmental contributions on DNA methylation with age.

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Section: Resultsmentioning

confidence: 99%

“…The LBC study was composed of two different birth cohorts, LBC1936 and LBC1921 [19], with 3018 samples collected in max of three time points. In the three waves, LBC1936 included 906, 801 and 619 individuals with mean ages of 69.6, 72.5 and 76.3 years; LBC1921 included 436, 174, 82 individuals with mean ages of 79.1, 86.7 and 90.2 years.…”

Section: Methodsmentioning

confidence: 99%

Epigenetic influences on aging: a longitudinal genome-wide methylation study in old Swedish twins

et al. 2018

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“…This study reports analysis of data collected from members of the Lothian Birth Cohort 1936 (LBC1936; [Deary et al, 2012, 2007]), a longitudinal study of ageing in the Edinburgh and Lothians area of Scotland, UK. Written informed consent was obtained from all participants, and the overall study was approved by the Lothian Research Ethics Committee (LREC/2003/2/29) and the Multi‐Centre Research Ethics Committee for Scotland (MREC/01/0/56).…”

Section: Methodsmentioning

confidence: 99%

Brain volumetric changes and cognitive ageing during the eighth decade of life

Ritchie

Dickie

Cox

et al. 2015

Human Brain Mapping

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Later‐life changes in brain tissue volumes—decreases in the volume of healthy grey and white matter and increases in the volume of white matter hyperintensities (WMH)—are strong candidates to explain some of the variation in ageing‐related cognitive decline. We assessed fluid intelligence, memory, processing speed, and brain volumes (from structural MRI) at mean age 73 years, and at mean age 76 in a narrow‐age sample of older individuals (n = 657 with brain volumetric data at the initial wave, n = 465 at follow‐up). We used latent variable modeling to extract error‐free cognitive levels and slopes. Initial levels of cognitive ability were predictive of subsequent brain tissue volume changes. Initial brain volumes were not predictive of subsequent cognitive changes. Brain volume changes, especially increases in WMH, were associated with declines in each of the cognitive abilities. All statistically significant results were modest in size (absolute r‐values ranged from 0.114 to 0.334). These results build a comprehensive picture of macrostructural brain volume changes and declines in important cognitive faculties during the eighth decade of life. Hum Brain Mapp 36:4910–4925, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc

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“…Our Discovery cohort consisted of genome-wide association study (GWAS) data relating to 6,732 (after QC) cognitively healthy subjects participating in the "Generation Scotland: Scottish Family Health Study" (GS:SFHS) 24 . The Replication cohort consisted of independent GWAS data relating to 1,003 (after QC) cognitively healthy subjects participating in the Lothian Birth Cohort 1936 (LBC1936) 25 . Mean age at assessment was 55 years (standard deviation (SD)=11.35) in GS:SFHS and 69.6 years (SD=0.8) in LBC1936.…”

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confidence: 99%

Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease

et al. 2015

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2Genetic determinants of cognition are poorly characterized and their relationship to genes that confer risk for neurodevelopmental disease is unclear. Here, we used a systems-level analysis of genome-wide gene expression data to infer gene-regulatory networks conserved across species and brain regions. Two of these networks, M1 and M3, showed replicable enrichment for common genetic variants underlying healthy human cognitive abilities including memory. Using exome sequence data from 6,871 trios, we find that M3 genes are also enriched for mutations ascertained from patients with neurodevelopmental disease generally, and intellectual disability and epileptic encephalopathy in particular. M3 consists of 150 genes whose expression is tightly developmentally regulated, but which are collectively poorly annotated for known functional pathways. These results illustrate how systems-level analyses can reveal previously unappreciated relationships between neurodevelopmental disease genes in the developed human brain, and provide empirical support for a convergent generegulatory network influencing cognition and neurodevelopmental disease.Cognition refers to human mental abilities such as memory, attention, processing speed, reasoning and executive function. Performance on cognitive tasks varies between individuals and is highly heritable 1 and polygenic 2,3 . However, to date, progress in identifying molecular genetic contributions to healthy human cognitive abilities has been limited 4,5 .A distinction can be made between cognitive domains such as the ability to apply acquired knowledge and learned skills (so called crystallized abilities) and fluid cognitive abilities such as the capacity to establish new memories, reason in novel situations or perform cognitive tasks accurately and quickly 6 . Notably, within individuals, performance on different measures of cognitive ability tend to be positively correlated such that people who do well in one domain, such as memory, tend to do well in other domains 7 . Seemingly disparate domains of cognitive ability also show high levels of genetic correlation in twin studies, typically in excess of 0.6 8 , and analyses using genome-wide similarity between unrelated individuals 3 (genome-wide complex trait analysis, GCTA) has also demonstrated substantial genetic correlation between diverse cognitive and learning abilities 9,10 . These studies suggest genes that influence human cognition may exert pleiotropic effects across diverse cognitive domains, such that genes regulating one cognitive ability might influence other cognitive abilities.Since impairment of cognitive function is a core clinical feature of many neurodevelopmental diseases including schizophrenia 11 , autism 12 , epilepsy 13 and intellectual disability (by definition), we sought to investigate gene-regulatory networks for human cognition and to determine their relationship to neurodevelopmental disease. An overview of our experimental design is provided in Supplementary Fig. 1. RESULTS Gene co-expression network a...

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Cohort Profile: The Lothian Birth Cohorts of 1921 and 1936

Cited by 366 publications

References 73 publications

Epigenetic influences on aging: a longitudinal genome-wide methylation study in old Swedish twins

Epigenetic influences on aging: a longitudinal genome-wide methylation study in old Swedish twins

Brain volumetric changes and cognitive ageing during the eighth decade of life

Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease

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