Stratified randomization controls better for batch effects in 450K methylation analysis: a cautionary tale

Background: Batch effects in DNA methylation microarray experiments can lead to spurious results if not properly handled during the plating of samples. Methods: Two pilot studies examining the association of DNA methylation patterns across the genome with obesity in Samoan men were investigated for chip- and row-specific batch effects. For each study, the DNA of 46 obese men and 46 lean men were assayed using Illumina's Infinium HumanMethylation450 BeadChip. In the first study (Sample One), samples from obese and lean subjects were examined on separate chips. In the second study (Sample Two), the samples were balanced on the chips by lean/obese status, age group, and census region. We used methylumi, watermelon, and limma R packages, as well as ComBat, to analyze the data. Principal component analysis and linear regression were respectively employed to identify the top principal components and to test for their association with the batches and lean/obese status. To identify differentially methylated positions (DMPs) between obese and lean males at each locus, we used a moderated t-test.Results: Chip effects were effectively removed from Sample Two but not Sample One. In addition, dramatic differences were observed between the two sets of DMP results. After removing'' batch effects with ComBat, Sample One had 94,191 probes differentially methylated at a q-value threshold of 0.05 while Sample Two had zero differentially methylated probes. The disparate results from Sample One and Sample Two likely arise due to the confounding of lean/obese status with chip and row batch effects.Conclusion: Even the best possible statistical adjustments for batch effects may not completely remove them. Proper study design is vital for guarding against spurious findings due to such effects

Genetic variants associated with lung function: The long life family study

Background: Reduced forced expiratory volume in 1 second (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) are strong predictors of mortality and lung function is higher among individuals with exceptional longevity. However, genetic factors associated with lung function in individuals with exceptional longevity have not been identified. Method: We conducted a genome wide association study (GWAS) to identify novel genetic variants associated with lung function in the Long Life Family Study (LLFS) (n = 3,899). Replication was performed using data from the CHARGE/SpiroMeta consortia. The association between SNPs and FEV1 and FEV1/FVC was analyzed using a linear mixed effects model adjusted for age, age2, sex, height, field center, ancestry principal components and kinship structure to adjust for family relationships separately for ever smokers and never smokers. In the linkage analysis, we used the residuals of the FEV1 and FEV1/FVC, adjusted for age, sex, height, ancestry principal components (PCs), smoking status, pack-years, and field center. Results: We identified nine SNPs in strong linkage disequilibrium in the CYP2U1 gene to be associated with FEV1 and a novel SNP (rs889574) associated with FEV1/FVC, none of which were replicated in the CHARGE/SpiroMeta consortia. Using linkage analysis, we identified a novel linkage peak in chromosome 2 at 219 cM for FEV1/FVC (LOD: 3.29) and confirmed a previously reported linkage peak in chromosome 6 at 28 cM (LOD: 3.33) for FEV1. Conclusion: Future studies need to identify the rare genetic variants underlying the linkage peak in chromosome 6 for FEV1

Incentives as connectors : insights into a breastfeeding incentive intervention in a disadvantaged area of North-West England

PMID: 22458841 [PubMed - indexed for MEDLINE] PMCID: PMC3414740 Free PMC ArticlePeer reviewedPublisher PD

Assessment of gene-by-sex interaction effect on bone mineral density

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed expression quantitative trait loci (eQTL) analysis and bioinformatics network analysis. We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS) and femoral neck (FN) BMD in 25,353 individuals from 8 cohorts. In a second stage, we followed up the 12 top single-nucleotide polymorphisms (SNPs; p < 1 × 10(-5) ) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 and p = 3.0 × 10(-5) ; female effect = -0.007 and p = 3.3 × 10(-2) ), and 11 suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (p < 5 × 10(-8) ) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found to influence BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. © 2012 American Society for Bone and Mineral Research.Medtronic NIH R01 AG18728 R01HL088119 R01AR046838 U01 HL084756 R01 AR43351 P01-HL45522 R01-MH-078111 R01-MH-083824 Nutrition and Obesity Research Center of Maryland P30DK072488 NIAMS/NIH F32AR059469 Instituto de Salud Carlos III-FIS (Spanish Health Ministry) PI 06/0034 PI08/0183 Canadian Institutes of Health Research (CIHR) NHLBI HHSN268201200036C N01-HC-85239 N01-HC-85079 N01-HC-85086 N01-HC-35129 N01 HC15103 N01 HC-55222 N01-HC-75150 N01-HC-45133 HL080295 HL087652 HL105756 NIA AG-023629 AG-15928 AG-20098 AG-027058 N01AG62101 N01AG62103 N01AG62106 1R01AG032098-01A1 National Center of Advancing Translational Technologies CTSI UL1TR000124 National Institute of Diabetes and Digestive and Kidney Diseases DK063491 EUROSPAN (European Special Populations Research Network) European Commission FP6 STRP grant 018947 LSHG-CT-2006-01947 Netherlands Organisation for Scientific Research Erasmus MC Centre for Medical Systems Biology (CMSB) Netherlands Brain Foundation (HersenStichting Nederland) US National Institute for Arthritis, Musculoskeletal and Skin Diseases National Institute on Aging R01 AR/AG41398 R01 AR050066 R21 AR056405 National Heart, Lung, and Blood Institute's Framingham Heart Study N01-HC-25195 Affymetrix, Inc. N02-HL-6-4278 Canadian Institutes of Health Research from Institute of Aging 165446 Institute of Genetics 179433 Institute of Musculoskeletal health 221765 Intramural Research Program of the NIH, National Institute on Aging National Institutes of Health HHSN268200782096C Hong Kong Research Grant Council HKU 768610M Bone Health Fund of HKU Foundation KC Wong Education Foundation Small Project Funding 201007176237 Matching Grant CRCG Grant Osteoporosis and Endocrine Research Fund Genomics Strategic Research Theme of The University of Hong Kong Netherlands Organisation of Scientific Research NWO Investments 175.010.2005.011 911-03-012 Research Institute for Diseases in the Elderly 014-93-015 Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Aging (NCHA) 050-060-810 Erasmus Medical Center and 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 German Bundesministerium fur Forschung und Technology 01 AK 803 A-H 01 IG 07015

Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value OBFC1indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes

Genetic determinants of heel bone properties: genome-wide association meta-analysis and replication in the GEFOS/GENOMOS consortium

Quantitative ultrasound of the heel captures heel bone properties that independently predict fracture risk and, with bone mineral density (BMD) assessed by X-ray (DXA), may be convenient alternatives for evaluating osteoporosis and fracture risk. We performed a meta-analysis of genome-wide association (GWA) studies to assess the genetic determinants of heel broadband ultrasound attenuation (BUA; n = 14 260), velocity of sound (VOS; n = 15 514) and BMD (n = 4566) in 13 discovery cohorts. Independent replication involved seven cohorts with GWA data (in silico n = 11 452) and new genotyping in 15 cohorts (de novo n = 24 902). In combined random effects, meta-analysis of the discovery and replication cohorts, nine single nucleotide polymorphisms (SNPs) had genome-wide significant (P < 5 × 10(-8)) associations with heel bone properties. Alongside SNPs within or near previously identified osteoporosis susceptibility genes including ESR1 (6q25.1: rs4869739, rs3020331, rs2982552), SPTBN1 (2p16.2: rs11898505), RSPO3 (6q22.33: rs7741021), WNT16 (7q31.31: rs2908007), DKK1 (10q21.1: rs7902708) and GPATCH1 (19q13.11: rs10416265), we identified a new locus on chromosome 11q14.2 (rs597319 close to TMEM135, a gene recently linked to osteoblastogenesis and longevity) significantly associated with both BUA and VOS (P < 8.23 × 10(-14)). In meta-analyses involving 25 cohorts with up to 14 985 fracture cases, six of 10 SNPs associated with heel bone properties at P < 5 × 10(-6) also had the expected direction of association with any fracture (P < 0.05), including three SNPs with P < 0.005: 6q22.33 (rs7741021), 7q31.31 (rs2908007) and 10q21.1 (rs7902708). In conclusion, this GWA study reveals the effect of several genes common to central DXA-derived BMD and heel ultrasound/DXA measures and points to a new genetic locus with potential implications for better understanding of osteoporosis pathophysiology

Association of Forced Vital Capacity with the Developmental Gene <i>NCOR2</i>

Background Forced Vital Capacity (FVC) is an important predictor of all-cause mortality in the absence of chronic respiratory conditions. Epidemiological evidence highlights the role of early life factors on adult FVC, pointing to environmental exposures and genes affecting lung development as risk factors for low FVC later in life. Although highly heritable, a small number of genes have been found associated with FVC, and we aimed at identifying further genetic variants by focusing on lung development genes. Methods Per-allele effects of 24,728 SNPs in 403 genes involved in lung development were tested in 7,749 adults from three studies (NFBC1966, ECRHS, EGEA). The most significant SNP for the top 25 genes was followed-up in 46,103 adults (CHARGE and SpiroMeta consortia) and 5,062 chi

Genome-wide association analysis identifies six new loci associated with forced vital capacity

Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 additional individuals of European ancestry. We found six new regions associated at genome-wide significance (P < 5 × 10−8) with FVC in or near EFEMP1, BMP6, MIR129-2–HSD17B12, PRDM11, WWOX and KCNJ2. Two loci previously associated with spirometric measures (GSTCD and PTCH1) were related to FVC. Newly implicated regions were followed up in samples from African-American, Korean, Chinese and Hispanic individuals. We detected transcripts for all six newly implicated genes in human lung tissue. The new loci may inform mechanisms involved in lung development and the pathogenesis of restrictive lung disease

Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci.

Bone Mineral Density (BMD) is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR) method to identify single nucleotide polymorphisms (SNPs) associated with BMD by leveraging cardiovascular disease (CVD) associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD) at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity