570 research outputs found
Testing departure from additivity in Tukey's model using shrinkage: application to a longitudinal setting
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109558/1/sim6281-sup-0001-WebBased.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/109558/2/sim6281.pd
Opioid medication use and blood DNA methylation:epigenome-wide association meta-analysis
Aim: To identify differential methylation related to prescribed opioid use. Methods: This study examined whether blood DNA methylation, measured using Illumina arrays, differs by recent opioid medication use in four population-based cohorts. We meta-analyzed results (282 users; 10,560 nonusers) using inverse-variance weighting. Results: Differential methylation (false discovery rate \u3c0.05) was observed at six CpGs annotated to the following genes: KIAA0226, CPLX2, TDRP, RNF38, TTC23 and GPR179. Integrative epigenomic analyses linked implicated loci to regulatory elements in blood and/or brain. Additionally, 74 CpGs were differentially methylated in males or females. Methylation at significant CpGs correlated with gene expression in blood and/or brain. Conclusion: This study identified DNA methylation related to opioid medication use in general populations. The results could inform the development of blood methylation biomarkers of opioid use
Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-Analysis of Community-Based Cohorts
BACKGROUND AND OBJECTIVES: Previous studies suggest that lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer disease (AD) and AD-related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults.
METHODS: We included dementia-free participants from 9 diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within ±5 years (i.e., cross-sectional analyses) or 5-20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (≥60 years). Fixed-effects or sample size-weighted meta-analyses were performed to combine results. Finally, we performed mendelian randomization (MR) analyses to assess causality.
RESULTS: We included up to 19,152 participants (mean age 59 years, 57% women). Higher mtDNA CN was cross-sectionally associated with better general cognitive function (β = 0.04; 95% CI 0.02-0.06) independent of age, sex, batch effects, race/ethnicity, time between blood draw and cognitive evaluation, cohort-specific variables, and education. Additional adjustment for blood cell counts or cardiometabolic traits led to slightly attenuated results. We observed similar significant associations with cognition in prospective analyses, although of reduced magnitude. We found no significant associations between mtDNA CN and brain MRI measures in meta-analyses. MR analyses did not reveal a causal relation between mtDNA CN in blood and cognition.
DISCUSSION: Higher mtDNA CN in blood is associated with better current and future general cognitive function in large and diverse communities across the United States. Although MR analyses did not support a causal role, additional research is needed to assess causality. Circulating mtDNA CN could serve nevertheless as a biomarker of current and future cognitive function in the community
Whole Genome Sequence analysis of apparent Treatment Resistant Hypertension Status in Participants From the Trans-Omics For Precision Medicine Program
Recommended from our members
Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use.
Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures
GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy.
To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files.
This article is open access.The genetic contribution to longevity in humans has been estimated to range from 15% to 25%. Only two genes, APOE and FOXO3, have shown association with longevity in multiple independent studies.We conducted a meta-analysis of genome-wide association studies including 6,036 longevity cases, age ≥90 years, and 3,757 controls that died between ages 55 and 80 years. We additionally attempted to replicate earlier identified single nucleotide polymorphism (SNP) associations with longevity.In our meta-analysis, we found suggestive evidence for the association of SNPs near CADM2 (odds ratio [OR] = 0.81; p value = 9.66 × 10(-7)) and GRIK2 (odds ratio = 1.24; p value = 5.09 × 10(-8)) with longevity. When attempting to replicate findings earlier identified in genome-wide association studies, only the APOE locus consistently replicated. In an additional look-up of the candidate gene FOXO3, we found that an earlier identified variant shows a highly significant association with longevity when including published data with our meta-analysis (odds ratio = 1.17; p value = 1.85×10(-10)).We did not identify new genome-wide significant associations with longevity and did not replicate earlier findings except for APOE and FOXO3. Our inability to find new associations with survival to ages ≥90 years because longevity represents multiple complex traits with heterogeneous genetic underpinnings, or alternatively, that longevity may be regulated by rare variants that are not captured by standard genome-wide genotyping and imputation of common variants.Netherlands Organisation of Scientific Research NWO Investments
175.010.2005.011
911-03-012
Research Institute for Diseases in the Elderly
014-93-015
RIDE2
Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO)
050-060-810
Erasmus Medical Center
Erasmus University, Rotterdam
Netherlands Organization for the Health Research and Development (ZonMw)
Research Institute for Diseases in the Elderly (RIDE)
Ministry of Education, Culture and Science
Ministry for Health, Welfare and Sports
European Commission (DG XII)
Municipality of Rotterdam
National Institutes of Health
National Institute on Aging (NIA)
R01 AG005407
R01 AR35582
R01 AR35583
R01 AR35584
R01 AG005394
R01 AG027574
R01 AG027576
AG023629
R01AG29451
U01AG009740
RC2 AG036495
RC4 AG039029
P30AG10161
R01AG17917
R01AG15819
R01AG30146
U01-AG023755
U19-AG023122
NHLBI
HHSN 268201200036C
HHSN268200800007C
N01HC55222
N01HC85079
N01HC85080
N01HC85081
N01HC85082
N01HC85083
N01HC 85086
HL080295
HL087652
HL105756
National Institute of Neurological Disorders and Stroke (NINDS)
National Center for Advancing Translational Sciences, CTSI
UL1TR000124
National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC)
DK063491
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
National Center for Research Resources (NCRR)
NIH Roadmap for Medical Research
U01 AR45580
U01 AR45614
U01 AR45632
U01 AR45647
U01 AR45654
U01 AR45583
U01 AG18197
U01-AG027810
UL1 RR024140
NIAMS
R01-AR051124
RC2ARO58973
National Heart, Lung and Blood Institute's Framingham Heart Study
N01-HC-25195
Affymetrix, Inc
N02-HL-6-4278
Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine
Boston Medical Center
National Institute of Arthritis, Musculoskeletal and Skin Diseases
NIA
R01 AR/AG 41398
NIH
N01-AG-12100
NIA Intramural Research Program
Hjartavernd (the Icelandic Heart Association)
Althingi (the Icelandic Parliament)
Illinois Department of Public Health
Translational Genomics Research Institute
Italian Ministry of Health
ICS110.1/RF97.71
U.S. National Institute on Aging
263 MD 9164
263 MD 821336
Intramural Research Program of the NIH, National Institute on Aging
1R01AG028321
1R01HL09257
Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging
BACKGROUND: Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. RESULTS: Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. CONCLUSION: This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity
A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium
OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants
GWAS for executive function and processing speed suggests involvement of the CADM2 gene
To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32 070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.Molecular Psychiatry advance online publication, 14 April 2015; doi:10.1038/mp.2015.37
- …