Genetic architecture of epigenetic and neuronal ageing rates in human brain regions

Identifying genes regulating the pace of epigenetic ageing represents a new frontier in genome-wide association studies (GWASs). Here using 1,796 brain samples from 1,163 individuals, we carry out a GWAS of two DNA methylation-based biomarkers of brain age: the epigenetic ageing rate and estimated proportion of neurons. Locus 17q11.2 is significantly associated (P=4.5 × 10−9) with the ageing rate across five brain regions and harbours a cis-expression quantitative trait locus for EFCAB5 (P=3.4 × 10−20). Locus 1p36.12 is significantly associated (P=2.2 × 10−8) with epigenetic ageing of the prefrontal cortex, independent of the proportion of neurons. Our GWAS of the proportion of neurons identified two genome-wide significant loci (10q26 and 12p13.31) and resulted in a gene set that overlaps significantly with sets found by GWAS of age-related macular degeneration (P=1.4 × 10−12), ulcerative colitis (P<1.0 × 10−20), type 2 diabetes (P=2.8 × 10−13), hip/waist circumference in men (P=1.1 × 10−9), schizophrenia (P=1.6 × 10−9), cognitive decline (P=5.3 × 10−4) and Parkinson's disease (P=8.6 × 10−3).

[1]  Michael Q. Zhang,et al.  Integrative analysis of 111 reference human epigenomes , 2015, Nature.

[2]  Gustavo Turecki,et al.  Methylomic profiling of human brain tissue supports a neurodevelopmental origin for schizophrenia , 2014, Genome Biology.

[3]  Nick C Fox,et al.  Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease , 2013, Nature Genetics.

[4]  Gabriëlle H S Buitendijk,et al.  Seven New Loci Associated with Age-Related Macular Degeneration , 2013, Nature Genetics.

[5]  Petr Klemera,et al.  A new approach to the concept and computation of biological age , 2006, Mechanisms of Ageing and Development.

[6]  Manolis Kellis,et al.  Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci , 2014 .

[7]  S. Horvath DNA methylation age of human tissues and cell types , 2013, Genome Biology.

[8]  Suzanne Craft,et al.  Insulin resistance syndrome and Alzheimer's disease: Age- and obesity-related effects on memory, amyloid, and inflammation , 2005, Neurobiology of Aging.

[9]  Ayellet V. Segrè,et al.  Common Inherited Variation in Mitochondrial Genes Is Not Enriched for Associations with Type 2 Diabetes or Related Glycemic Traits , 2010, PLoS genetics.

[10]  H. Brenner,et al.  Epigenetic age acceleration predicts cancer, cardiovascular, and all-cause mortality in a German case cohort , 2016, Clinical Epigenetics.

[11]  Judy H. Cho,et al.  Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations , 2015, Nature Genetics.

[12]  Sonja W. Scholz,et al.  Genome-Wide Association Study reveals genetic risk underlying Parkinson’s disease , 2009, Nature Genetics.

[13]  L. Kiemeney,et al.  A Comparison of Multivariate Genome-Wide Association Methods , 2014, PloS one.

[14]  Steve Horvath,et al.  The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936 , 2015, International journal of epidemiology.

[15]  D. Bennett,et al.  Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer's disease , 2014, Nature Neuroscience.

[16]  Joel Eriksson,et al.  FTO genotype is associated with phenotypic variability of body mass index , 2012, Nature.

[17]  D. Reich,et al.  Principal components analysis corrects for stratification in genome-wide association studies , 2006, Nature Genetics.

[18]  Manolis Kellis,et al.  Large-scale epigenome imputation improves data quality and disease variant enrichment , 2015, Nature Biotechnology.

[19]  S. Horvath,et al.  Epigenetic age analysis of children who seem to evade aging , 2015, Aging.

[20]  M. MacDonald,et al.  Genetic modifiers of Huntington's disease , 2014, Movement disorders : official journal of the Movement Disorder Society.

[21]  Steve Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[22]  K. Langa,et al.  The Aging, Demographics, and Memory Study: Study Design and Methods , 2005, Neuroepidemiology.

[23]  ENCODEConsortium,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[24]  P. Visscher,et al.  Estimating missing heritability for disease from genome-wide association studies. , 2011, American journal of human genetics.

[25]  J. Vaupel,et al.  DNA methylation age is associated with mortality in a longitudinal Danish twin study , 2015, Aging cell.

[26]  Tanya M. Teslovich,et al.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes , 2012, Nature Genetics.

[27]  Jun S. Liu,et al.  The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans , 2015, Science.

[28]  Jennifer S. Woo,et al.  The cerebellum ages slowly according to the epigenetic clock , 2015, Aging.

[29]  S. Horvath,et al.  Increased epigenetic age and granulocyte counts in the blood of Parkinson's disease patients , 2015, Aging.

[30]  S. Horvath,et al.  Huntington's disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels , 2016, Aging.

[31]  A Hofman,et al.  Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949) , 2015, Molecular Psychiatry.

[32]  A. Singleton,et al.  Genetic variability in the regulation of gene expression in ten regions of the human brain , 2014, Nature Neuroscience.

[33]  Lewis H Kuller,et al.  Midlife and late-life obesity and the risk of dementia: cardiovascular health study. , 2009, Archives of neurology.

[34]  Steve Horvath,et al.  Accelerated epigenetic aging in Down syndrome , 2015, Aging cell.

[35]  N. Wray,et al.  A mega-analysis of genome-wide association studies for major depressive disorder , 2013, Molecular Psychiatry.

[36]  Claude Bouchard,et al.  A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance , 2012, Nature Genetics.

[37]  J. Schneider,et al.  Overview and findings from the religious orders study. , 2012, Current Alzheimer research.

[38]  Michael Boehnke,et al.  LocusZoom: regional visualization of genome-wide association scan results , 2010, Bioinform..

[39]  R. Goodman,et al.  Aging in the United States: opportunities and challenges for public health. , 2012, American journal of public health.

[40]  Naomi R. Wray,et al.  Statistical Power to Detect Genetic (Co)Variance of Complex Traits Using SNP Data in Unrelated Samples , 2014, PLoS genetics.

[41]  Jutta Gampe,et al.  Genome-wide association meta-analysis of human longevity identifies a novel locus conferring survival beyond 90 years of age , 2014, Human molecular genetics.

[42]  S. Horvath,et al.  HIV-1 Infection Accelerates Age According to the Epigenetic Clock , 2015, The Journal of infectious diseases.

[43]  M. Levine,et al.  Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer’s disease related cognitive functioning , 2015, Aging.

[44]  Luigi Ferrucci,et al.  Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain , 2010, PLoS genetics.

[45]  Ron Brookmeyer,et al.  Dementia incidence continues to increase with age in the oldest old: The 90+ study , 2010, Annals of neurology.

[46]  Yun Li,et al.  METAL: fast and efficient meta-analysis of genomewide association scans , 2010, Bioinform..

[47]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[48]  Mark R Cookson,et al.  Distinct DNA methylation changes highly correlated with chronological age in the human brain. , 2011, Human molecular genetics.

[49]  R. Dolmetsch,et al.  Molecular mechanisms of autism: a possible role for Ca2+ signaling , 2007, Current Opinion in Neurobiology.

[50]  P. Visscher,et al.  Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets , 2016, Nature Genetics.

[51]  S. Horvath,et al.  DNA methylation age of blood predicts all-cause mortality in later life , 2015, Genome Biology.

[52]  Tamara S. Roman,et al.  New genetic loci link adipose and insulin biology to body fat distribution , 2014, Nature.

[53]  Manolis Kellis,et al.  Alzheimery's disease pathology is associated with early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci , 2014, Nature Neuroscience.

[54]  “Monoallelic germline methylation and sequence variant in the promoter of the RB1 gene: a possible constitutive epimutation in hereditary retinoblastoma” , 2016, Clinical Epigenetics.

[55]  M. Levine,et al.  An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease , 2016, Genome Biology.

[56]  M. Levine,et al.  DNA methylation-based measures of biological age: meta-analysis predicting time to death , 2016, Aging.

[57]  Ross M. Fraser,et al.  A General Approach for Haplotype Phasing across the Full Spectrum of Relatedness , 2014, PLoS genetics.

[58]  M. Levine Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age? , 2013, The journals of gerontology. Series A, Biological sciences and medical sciences.

[59]  Jason J. Corneveaux,et al.  Genetic susceptibility for Alzheimer disease neuritic plaque pathology. , 2013, JAMA neurology.

[60]  J. Schneider,et al.  Overview and findings from the rush Memory and Aging Project. , 2012, Current Alzheimer research.

[61]  Anton P. Porsteinsson,et al.  Meta-Analysis of Alzheimer's Disease Risk with Obesity, Diabetes, and Related Disorders , 2010, Biological Psychiatry.

[62]  M. Dale,et al.  Review: Obesity and Alzheimer’s Disease: A Link Between Body Weight and Cognitive Function in Old Age , 2009, American journal of Alzheimer's disease and other dementias.

[63]  S. Resnick,et al.  Midlife adiposity predicts earlier onset of Alzheimer’s dementia, neuropathology and presymptomatic cerebral amyloid accumulation , 2015, Molecular Psychiatry.

[64]  Martin J. Aryee,et al.  A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression , 2013, Epigenetics.

[65]  Disorder Working Group Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4 , 2012, Nature Genetics.

[66]  Jane S. Paulsen,et al.  Identification of Genetic Factors that Modify Clinical Onset of Huntington’s Disease , 2015, Cell.

[67]  Steve Horvath,et al.  Obesity accelerates epigenetic aging of human liver , 2014, Proceedings of the National Academy of Sciences.

[68]  Lijun Cheng,et al.  Genetic control of individual differences in gene-specific methylation in human brain. , 2010, American journal of human genetics.

[69]  J. Schwartz,et al.  Endothelin-converting enzyme-1 is expressed in human cerebral cortex and protects against Alzheimer's disease , 2004, Molecular Psychiatry.

[70]  Chuong B. Do,et al.  Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson’s disease , 2014, Nature Genetics.

[71]  Jamie P. Halsall,et al.  Aging in the United States , 2012 .

[72]  C. Spencer,et al.  Biological Insights From 108 Schizophrenia-Associated Genetic Loci , 2014, Nature.

[73]  P. Visscher,et al.  GCTA: a tool for genome-wide complex trait analysis. , 2011, American journal of human genetics.

[74]  M. Levine,et al.  Menopause accelerates biological aging , 2016, Proceedings of the National Academy of Sciences.

[75]  M. Levine,et al.  Genetic variants near MLST8 and DHX57 affect the epigenetic age of the cerebellum , 2016, Nature Communications.

[76]  P. Donnelly,et al.  A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies , 2009, PLoS genetics.

[77]  Susanne Walitza,et al.  Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder. , 2010, Journal of the American Academy of Child and Adolescent Psychiatry.

[78]  J. Marchini,et al.  Fast and accurate genotype imputation in genome-wide association studies through pre-phasing , 2012, Nature Genetics.

[79]  N. Timpson,et al.  Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors , 2015, European Journal of Epidemiology.

[80]  G. Davey Smith,et al.  Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression , 2015, International journal of epidemiology.

[81]  S. Love,et al.  Endothelin-converting enzyme-1 activity, endothelin-1 production, and free radical-dependent vasoconstriction in Alzheimer's disease. , 2013, Journal of Alzheimer's disease : JAD.