Eilis Hannon

Dr. Eilis Hannon


Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 April 2018 in Nature Genetics
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NWNaomi R. Wray
Naomi R. Wray
SRStephan Ripke
Stephan Ripke
MMManuel Mattheisen
Manuel Mattheisen
MTMaciej Trzaskowski
Maciej Trzaskowski
EBEnda M. Byrne
Enda M. Byrne
EQEqtlgen
Eqtlgen
Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

22 January 2014 in Nature
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Journal Article
Closed access
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MFMenachem Fromer
Menachem Fromer
APAndrew J. Pocklington
Andrew J. Pocklington
DKDavid H. Kavanagh
David H. Kavanagh
HWHywel Williams
Hywel Williams
SDSarah Dwyer
Sarah Dwyer
MOMichael C. O’donovan
Michael C. O’donovan

14 January 2022 in eLife
Verified
Journal Article
Open access
DBDaniel W Belsky
Daniel W Belsky
ACAvshalom Caspi
Avshalom Caspi
DCDavid L Corcoran
David L Corcoran
KSKaren Sugden
Karen Sugden
RPRichie Poulton
Richie Poulton
TMTerrie E Moffitt
Terrie E Moffitt
Background: Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously, we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al., 2020). Here, we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome).Methods: We used data from the Dunedin Study 1972–1973 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named DunedinPACE, in five additional datasets.Results: DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge.Conclusions: DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience.Funding: This research was supported by US-National Institute on Aging grants AG032282, AG061378, AG066887, and UK Medical Research Council grant MR/P005918/1.

6 August 2019 in JAMA
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ILIlianna Lourida
Ilianna Lourida
EHEilis Hannon
Eilis Hannon
TLThomas J. Littlejohns
Thomas J. Littlejohns
KLKenneth M. Langa
Kenneth M. Langa
EHElina Hyppönen
Elina Hyppönen
DLDavid J. Llewellyn
David J. Llewellyn
Both genetic and lifestyle factors play a role in determining individual risk of Alzheimer disease and other dementia subtypes.1 Mutations in the amyloid precursor protein (APP; OMIM:104760), presenilin 1 (PSEN1; OMIM:104311), and presenilin 2 (PSEN2; OMIM:600759) genes can cause early-onset Alzheimer disease, although this accounts for a small percentage of cases.2 Most dementia cases occur sporadically in older adults in whom multiple genes influence risk. The ε4 allele of the apolipoprotein E gene (APOE; OMIM:107741) is known to increase the risk of Alzheimer disease.3,4 A meta-analysis of genome-wide association studies identified additional loci associated with the risk of late-onset Alzheimer disease in participants of European ancestry.3 Polygenic risk scores combining multiple risk alleles for Alzheimer disease are predictive of incident all-cause dementia and provide a quantitative measure of genetic dementia risk.5,6

5 May 2020 in eLife
Verified
Journal Article
Open access
DBDaniel W Belsky
Daniel W Belsky
ACAvshalom Caspi
Avshalom Caspi
LALouise Arseneault
Louise Arseneault
ABAndrea Baccarelli
Andrea Baccarelli
DCDavid L Corcoran
David L Corcoran
TMTerrie E Moffitt
Terrie E Moffitt
Biological aging is the gradual, progressive decline in system integrity that occurs with advancing chronological age, causing morbidity and disability. Measurements of the pace of aging are needed as surrogate endpoints in trials of therapies designed to prevent disease by slowing biological aging. We report a blood-DNA-methylation measure that is sensitive to variation in pace of biological aging among individuals born the same year. We first modeled change-over-time in 18 biomarkers tracking organ-system integrity across 12 years of follow-up in n = 954 members of the Dunedin Study born in 1972–1973. Rates of change in each biomarker over ages 26–38 years were composited to form a measure of aging-related decline, termed Pace-of-Aging. Elastic-net regression was used to develop a DNA-methylation predictor of Pace-of-Aging, called DunedinPoAm for Dunedin(P)ace(o)f(A)ging(m)ethylation. Validation analysis in cohort studies and the CALERIE trial provide proof-of-principle for DunedinPoAm as a single-time-point measure of a person’s pace of biological aging.

6 December 2021 in Nature Genetics
Verified
Journal Article
Open access
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WRWouter van Rheenen
Wouter van Rheenen
RSRick A. A. van der Spek
Rick A. A. van der Spek
MBMark K. Bakker
Mark K. Bakker
JVJoke J. F. A. van Vugt
Joke J. F. A. van Vugt
PHPaul J. Hop
Paul J. Hop
JVJan H. Veldink
Jan H. Veldink
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons.