Identifying flaws in the GWAS datasets of a published Mendelian randomization study: complementary re-evaluation and suggestion for analytical refinements.
Ontology highlight
ABSTRACT:
SUBMITTER: Xiang JC
PROVIDER: S-EPMC10964565 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
Publications
Identifying flaws in the GWAS datasets of a published Mendelian randomization study: complementary re-evaluation and suggestion for analytical refinements.
Xiang Jia-Cheng JC Xiong Yi-Fan YF Wang Shao-Gang SG Xia Qi-Dong QD
Journal of translational medicine 20240326 1
Similar Datasets
Project description:The existence of a placental microbiota is debated. The human placenta has historically been considered sterile and microbial colonization was associated with adverse pregnancy outcomes. Yet, recent DNA sequencing investigations reported a microbiota in typical human term placentas. However, this detected microbiota could represent background DNA or delivery-associated contamination. Using fifteen publicly available 16S rRNA gene datasets, existing data were uniformly re-analyzed with DADA2 to maximize comparability. While Amplicon Sequence Variants (ASVs) identified as Lactobacillus, a typical vaginal bacterium, were highly abundant and prevalent across studies, this prevalence disappeared after applying likely DNA contaminant removal to placentas from term cesarean deliveries. A six-study sub-analysis targeting the 16S rRNA gene V4 hypervariable region demonstrated that bacterial profiles of placental samples and technical controls share principal bacterial ASVs and that placental samples clustered primarily by study origin and mode of delivery. Contemporary DNA-based evidence does not support the existence of a placental microbiota.ImportanceEarly-gestational microbial influences on human development are unclear. By applying DNA sequencing technologies to placental tissue, bacterial DNA signals were observed, leading some to conclude that a live bacterial placental microbiome exists in typical term pregnancy. However, the low-biomass nature of the proposed microbiome and high sensitivity of current DNA sequencing technologies indicate that the signal may alternatively derive from environmental or delivery-associated bacterial DNA contamination. Here we address these alternatives with a re-analysis of 16S rRNA gene sequencing data from 15 publicly available placental datasets. After identical DADA2 pipeline processing of the raw data, subanalyses were performed to control for mode of delivery and environmental DNA contamination. Both environment and mode of delivery profoundly influenced the bacterial DNA signal from term-delivered placentas. Aside from these contamination-associated signals, consistency was lacking across studies. Thus, placentas delivered at term are unlikely to be the original source of observed bacterial DNA signals.
| S-EPMC10024458 | biostudies-literature
Project description: Not available
| S-BSST1843 | biostudies-other
Project description: Not available
| S-BSST1453 | biostudies-other
Project description:Genome-wide association studies are proven tools for finding disease genes, but it is often necessary to combine many cohorts into a meta-analysis to detect statistically significant genetic effects. Often the component studies are performed by different investigators on different populations, using different chips with minimal SNPs overlap. In some cases, raw data are not available for imputation so that only the genotyped single nucleotide polymorphisms (SNPs) results can be used in meta-analysis. Even when SNP sets are comparable, different cohorts may have peak association signals at different SNPs within the same gene due to population differences in linkage disequilibrium or environmental interactions. We hypothesize that the power to detect statistical signals in these situations will improve by using a method that simultaneously meta-analyzes and smooths the signal over nearby markers. In this study, we propose regionally smoothed meta-analysis methods and compare their performance on real and simulated data.
| S-EPMC4724289 | biostudies-literature
Project description:DNA repair pathways maintain genomic integrity and stability, and dysfunction of DNA repair leads to cancer. We hypothesize that functional genetic variants in DNA repair genes are associated with risk of lung cancer. We performed a large-scale meta-analysis of 123,371 single nucleotide polymorphisms (SNPs) in 169 DNA repair genes obtained from six previously published genome-wide association studies (GWASs) of 12160 lung cancer cases and 16838 controls. We calculated odds ratios (ORs) with 95% confidence intervals (CIs) using the logistic regression model and used the false discovery rate (FDR) method for correction of multiple testing. As a result, 14 SNPs had a significant odds ratio (OR) for lung cancer risk with P FDR < 0.05, of which rs3115672 in MSH5 (OR = 1.20, 95% CI = 1.14-1.27) and rs114596632 in GTF2H4 (OR = 1.19, 95% CI = 1.12-1.25) at 6q21.33 were the most statistically significant (P combined = 3.99×10(-11) and P combined = 5.40×10(-10), respectively). The MSH5 rs3115672, but not GTF2H4 rs114596632, was strongly correlated with MSH5 rs3131379 in that region (r (2) = 1.000 and r (2) = 0.539, respectively) as reported in a previous GWAS. Importantly, however, the GTF2H4 rs114596632 T, but not MSH5 rs3115672 T, allele was significantly associated with both decreased DNA repair capacity phenotype and decreased mRNA expression levels. These provided evidence that functional genetic variants of GTF2H4 confer susceptibility to lung cancer.
| S-EPMC5008248 | biostudies-literature
Project description:BackgroundFor the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called "missing" heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS.ResultsWe investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called 'SNP-set' tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer.ConclusionsHere we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.
| S-EPMC4776370 | biostudies-literature
Project description:A recent hypothesis-free pathway-level analysis of genome-wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta-analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis-driven approach, we selected 138 candidate genes from the NER pathway using the "Molecular Signatures Database (MsigDB)" and "PathCards". All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta-analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM-ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03-1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89-0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03-1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90-0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08-1.16, ptrend < 0.0001). The eQTL analysis revealed that BIVM-ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10-22 , respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression.
| S-EPMC6930956 | biostudies-literature
Project description: Not available
| S-BSST1455 | biostudies-other
Project description: Not available
| S-BSST1820 | biostudies-other
Project description:A new measuring system based on the already existing Multi-Color-PAM Fluorimeter (Schreiber et al. in Photosynth Res 113:127-144, 2012) was developed that in addition to standard PAM measurements enables pump-and-probe flash measurements and allows simultaneous measurements of the changes in chlorophyll fluorescence yield (F) during application of saturating flashes (ST). A high-power Chip-on-Board LED array provides ST flashes with close to rectangular profiles at wide ranges of widths (0.5 µs to 5 ms), intensities (1.3 mmol to 1.3 mol 440 nm quanta m-2 s-1) and highly flexible repetition times. Using a dedicated rising-edge profile correction, sub-µs time resolution is obtained for assessment of initial fluorescence and rise kinetics. At maximal to moderate flash intensities the flash-kinetics (changes of F during course of ST, STK) are strongly affected by 'High Intensity Quenching' (HIQ), consisting of Car-triplet quenching, TQ, and donor-side-dependent quenching, DQ. The contribution of TQ is estimated by application of a second ST after 20 µs dark-time. Upon application of flash trains (ST sequences with defined repetition times) typical period-4 oscillations in dark fluorescence yield (F0) and ST-induced fluorescence yield, FmST, are obtained which can be measured in vivo both with suspensions and from the surface of leaves. Examples of application with dilute suspensions of Chlorella and an intact dandelion leaf are presented. It is shown that weak far-red light (730-740 nm) advances the S-state distribution of the water-splitting system by one step, resulting in substantial lowering of FmST and also of the I1-level in the polyphasic rise of fluorescence yield induced by a multiple-turnover flash (MT). Based on comparative measurements of STK and the polyphasic rise kinetics with the same Chlorella sample, it is concluded that the generally observed lower values of maximal fluorescence yields using ST-protocols compared to MT-protocols are due to a higher extent of HIQ (mainly DQ) and the contribution of variable PSI fluorescence to FmST.
| S-EPMC11324780 | biostudies-literature