Effect Of Individual Single Nucleotide Polymorphisms Research Articles

Unraveling genetic causality between metformin and myocardial infarction on the basis of Mendelian randomization.

In recent years, several studies have explored the effect of metformin on myocardial infarction (MI), but whether metformin has an improvement effect in patients with MI is controversial. This study was aimed to investigate the causal relationship between metformin and MI using Mendelian randomization (MR) analysis. The genome-wide significant (P<5×10-8) single-nucleotide polymorphisms (SNPs) in patients with metformin and patients with MI were screened from the Open genome-wide association study (GWAS) project as instrumental variables (IVs). The study outcomes mainly included MI, old MI, acute MI, acute transmural MI of inferior wall, and acute transmural MI of anterior wall. The inverse variance weighted (IVW) method was applied to assess the main causal effect, and weighted median, simple mode, weighted mode methods, and MR-Egger regression were auxiliary applied for supplementary proof. The causal relationship between metformin and MI was assessed using odds ratios (OR) and 95% confidence intervals (95% CI). A leave-one-out method was used to explore the effect of individual SNPs on the results of IVW analyses, and a funnel plot was used to analyze the potential bias of the study results, thus ensuring the robustness of the results. In total, 16, 84, 39, 26, and 34 SNPs were selected as IVs to assess the genetic association between metformin and outcomes of MI, old MI, acute MI, acute transmural MI of inferior wall, and acute transmural MI of anterior wall, respectively. Treatment with metformin does not affect the risk of acute transmural MI of anterior wall at the genetic level (P>0.05; OR for inverse variance weighted was 1.010). In the cases of MI, old MI, acute MI, and acute transmural MI of inferior wall, metformin may even be a risk factor for patients (P<0.05; ORs for inverse variance weighted were 1.078, 1.026, 1.022 and 1.018 respectively). There was no horizontal pleiotropy or heterogeneity among IVs. The results were stable when removing the SNPs one by one. Metformin is not protective against the risk of myocardial infarction in patients and may even be a risk factor for MI, old MI, acute MI, and acute transmural MI of inferior wall.

No genetic causality between obesity and benign paroxysmal vertigo: A two-sample Mendelian randomization study.

We applied Mendelian randomization to explore the causal relationship between obesity and benign paroxysmal vertigo (BPV). We chose two types of obesity diseases. Obesity due to excessive calories and other or unspecified obesity from the FinnGen database. We used genomic significance (p < 5 × 10-8) to obtain independent single nucleotide polymorphisms (SNPs) as instrumental variables. Similarly, genome-wide association study data for the disease BPV were selected from the FinnGen database. R was then used to test the data for multiplicity and heterogeneity, as well as to detect the effect of individual SNPs on the results. Random effects inverse variance weighting was used as the main statistical analysis. First, by analyzing, we found an outlier in obesity due to excessive calories (rs12956821). Outliers were then removed, and the statistical results were analyzed without heterogeneity (p > 0.05) and horizontal pleiotropy (p > 0.05), as well as individual SNPs having no effect on the results. Meanwhile, random-effects IVW results showed obesity due to excessive calories (p = 0.481; OR = 0.941), and other or unspecified obesity (p = 0.640; OR = 0.964). The present study did not find a causal relationship between the above two obesity types and BPV at the genetic level.

Association between circulating unsaturated fatty acid and preeclampsia: a two-sample Mendelian randomization study

Objective In recent years, several studies have reported an association between unsaturated fatty acids (UFAs) and the risk of developing preeclampsia; however, its exact causal effect is unclear. This study assessed the causal association between circulating UFAs and preeclampsia. Methods A two-sample Mendelian randomization (MR) study using publicly available genome-wide association study (GWAS) summary data for circulating UFA s (N = 114,999) and preeclampsia (N = 118,291) was performed. Single nucleotide polymorphisms (SNPs) significantly associated with exposure was selected as instrumental variables (IVs). The inverse variance weighted (IVW) test was used as the primary method for estimating causality in MR analysis, while MR pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger regression methods were used to assess horizontal pleiotropy. Cochran’s Q test was used to evaluate heterogeneity among SNPs, and leave-one-out sensitivity analysis was used to determine the effect of individual SNPs on the results of the MR analysis. Bonferroni correction was used as a correction for multiple corrections. Results Two-sample MR analysis suggested that the ratio of monounsaturated fatty acids (MUFAs) to total fatty acids (OR 1.150, 95% CI 1.006–1.315, p = 0.041), the ratio of polyunsaturated fatty acids (PUFAs) to total fatty acids (OR 0.805, 95% CI 0.658–0.986, p = 0.036) and the ratio of PUFAs to MUFAs (OR 0.807, 95% CI 0.694–0.938, p = 0.005) were causally associated with preeclampsia. After Bonferroni correction, the causal association between the ratio of polyunsaturated to MUFAs and preeclampsia remained statistically different. Conclusions This MR analysis provides evidence for a genetic causal association between circulating UFAs and preeclampsia.

Identifying potential genetic epistasis implicated in Alzheimer’s disease via detection of SNP-SNP interaction on quantitative trait CSF Aβ42

Although genome-wide association studies have identified multiple Alzheimer's disease (AD)-associated loci by selecting the main effects of individual single-nucleotide polymorphisms (SNPs), the interpretation of genetic variance in AD is limited. Based on the linear regression method, we performed genome-wide SNP-SNP interaction on cerebrospinal fluid Aβ42 to identify potential genetic epistasis implicated in AD, with age, gender, and diagnosis as covariates. A GPU-based method was used to address the computational challenges posed by the analysis of epistasis. We found 368 SNP pairs to be statistically significant, and highly significant SNP-SNP interactions were identified between the marginal main effects of SNP pairs, which explained a relatively high variance at the Aβ42 level. Our results replicated 100 previously reported AD-related genes and 5 gene-gene interaction pairs of the protein-protein interaction network. Our bioinformatics analyses provided preliminary evidence that the 5-overlapping gene-gene interaction pairs play critical roles in inducing synaptic loss and dysfunction, thereby leading to memory decline and cognitive impairment in AD-affected brains.

Multi-Polymorphism Analysis Reveals Joint Effects in Males With Chronic Central Serous Chorioretinopathy.

Central serous chorioretinopathy (CSCR) is a leading cause of central vision impairment in the working-age population with male predilection. Knowledge about the genetic basis of CSCR and its male predilection remained limited. This study aimed to evaluate the association patterns of multiple gene variants in chronic CSCR (cCSCR) in Chinese patients. This case-control genetic association study included 531 patients with cCSCR and 2383 controls from two independent Chinese cohorts. Nine single-nucleotide polymorphisms (SNPs) of six genes, namely CFH, NR3C2, GATA5, VIPR2, TNFRSF10A, and ARMS2, were genotyped in all subjects. The main outcome measures were the association of individual single-nucleotide polymorphism (SNP) with cCSCR, the sex-stratification effects of individual SNP, and joint effects of different SNPs on cCSCR. Association results in the two cohorts were consistent with low heterogeneities. In the combined analysis, SNPs CFH rs800292 (odds ratio [OR] = 1.25, P = 0.0020), CFH rs1329428 (OR = 1.23, P = 0.0037), and TNFRSF10A rs13278062 (OR = 1.43, P = 0.0014) were significantly associated with cCSCR. In stratification analysis by sex, 3SNPs in CFH, rs3753394, rs800292, and rs1329428, were associated with cCSCR in male patients, but not in female patients. Joint analysis revealed that subjects homozygous for the risk alleles of CFH rs800292 and TNFRSF10A rs13278062 had over 4-fold of increased risk of cCSCR when compared with subjects homozygous for the non-risk alleles (OR = 4.06, P = 2.30 × 10-5). This study revealed main and joint effects of SNPs in CFH and TNFRSF10A on cCSCR, and suggested CFH as a potential genetic factor underlying the male predilection of cCSCR. Further replication in other study populations is needed.

Interactions of SNPs in Folate Metabolism Related Genes on Prostate Cancer Aggressiveness in European Americans and African Americans.

Studies showed that folate and related single nucleotide polymorphisms (SNPs) could predict prostate cancer (PCa) risk. However, little is known about the interactions of folate-related SNPs associated with PCa aggressiveness. The study's objective is to evaluate SNP-SNP interactions among the DHFR 19-bp polymorphism and 10 SNPs in folate metabolism and the one-carbon metabolism pathway associated with PCa aggressiveness. We evaluated 1294 PCa patients, including 690 European Americans (EAs) and 604 African Americans (AAs). Both individual SNP effects and pairwise SNP-SNP interactions were analyzed. None of the 11 individual polymorphisms were significant for EAs and AAs. Three SNP-SNP interaction pairs can predict PCa aggressiveness with a medium to large effect size. For the EA PCa patients, the interaction between rs1801133 (MTHFR) and rs2236225 (MTHFD1), and rs1801131 (MTHFR) and rs7587117 (SLC4A5) were significantly associated with aggressive PCa. For the AA PCa patients, the interaction of DHFR-19bp polymorphism and rs4652 (LGALS3) was significantly associated with aggressive PCa. These SNP-SNP interactions in the folate metabolism-related genes have a larger impact than SNP individual effects on tumor aggressiveness for EA and AA PCa patients. These findings can provide valuable information for potential biological mechanisms of PCa aggressiveness.

PS-P02-8: HOST GENOMIC INFLUENCE ON THE GUT MICROBIAL METABOLITE-BLOOD PRESSURE RELATIONSHIP

Objective: The human metabolic profile is affected by host genetic, microbiome, environmental/lifestyle, and dietary factors which may all influence human raised blood pressure (BP). We aim to delineate metabolite-BP relationships by evaluating the effect of single-nucleotide polymorphisms (SNPs) mapped to enzyme-coding genes involved in metabolic pathways on this association. We specifically focus on human commensal urinary gut microbial co-metabolites. Design and Method: Two cross-sectional datasets of over 4,000 individuals in total were used in a two-stage design. The first cohort uses two timed 24-hr urine samples for the discovery and replication of urinary metabolites associated with BP. The second cohort uses spot urine samples to validate the associations and subsequently investigates the influence of BP and other metabolic syndrome-related SNPs on these associations. Urine samples from both cohorts were measured with 600 MHz 1H Nuclear Magnetic Resonance spectroscopy. The SNPs were mapped to metabolites using a bioinformatic approach, which also incorporates the microbiome in establishing the metabolic distance between SNPs and metabolites through biochemical reactions and pathways. Results: 11 urinary metabolites, replicated within the first cohort and validated in the second cohort (adjusted P-values 1.68 × 10–15 to 1.08 × 10–4) were associated with systolic BP (SBP); 9 of these were also associated with diastolic BP (DBP) in both cohorts as well as 2 further metabolites with DBP only (adjusted P-values 9.18 × 10–13 to 1.23 × 10–4). The analysis of the host-genomic (SNPs linked to GLYAT, KYAT3 and SULT13A genes) effect on gut microbial co-metabolites phenylacetylglutamine, hippurate and 4-cresylsulfate and their association with BP revealed a significant contribution of SNPs on the metabolite-BP association (P-values 1.08 × 10–133 to 2.87 × 10–29). Other metabolite-BP associations, such as for amino acids tyrosine, glycine, lysine, and leucine, also demonstrated a significant effect of individual SNPs (P-values 1.54 × 10–303 to 2.04 × 10–8) on the relationship. These associations were validated with null models of random SNPs with the same minor allele frequency also mapping to enzyme-coding genes, as well as a null model demonstrating that these metabolites have more SNPs linked to them than other metabolites with similar network topologies in other metabolic pathways. Conclusions: We have shown that human commensal urinary gut microbial co-metabolites are reliably associated with BP differences in two cohorts, and we demonstrated a significant host-genetic component that contributes to these associations. These relationships indicate potential complex mechanisms involving host genetics, the gut microbiome, and metabolic changes associated with BP that may lead to new ways to prevent high BP.

Pleiotropy Structures Plant Height and Seed Weight Scaling in Barley despite Long History of Domestication and Breeding Selection.

Size scaling describes the relative growth rates of different body parts of an organism following a positive correlation. Domestication and crop breeding often target the scaling traits in the opposite directions. The genetic mechanism of the size scaling influencing the pattern of size scaling remains unexplored. Here, we revisited a diverse barley (Hordeum vulgare L.) panel with genome-wide single-nucleotide polymorphisms (SNPs) profile and the measurement of their plant height and seed weight to explore the possible genetic mechanisms that may lead to a correlation of the two traits and the influence of domestication and breeding selection on the size scaling. Plant height and seed weight are heritable and remain positively correlated in domesticated barley regardless of growth type and habit. Genomic structural equation modeling systematically evaluated the pleiotropic effect of individual SNP on the plant height and seed weight within a trait correlation network. We discovered seventeen novel SNPs (quantitative trait locus) conferring pleiotropic effect on plant height and seed weight, involving genes with function in diverse traits related to plant growth and development. Linkage disequilibrium decay analysis revealed that a considerable proportion of genetic markers associated with either plant height or seed weight are closely linked in the chromosome. We conclude that pleiotropy and genetic linkage likely form the genetic bases of plant height and seed weight scaling in barley. Our findings contribute to understanding the heritability and genetic basis of size scaling and open a new venue for seeking the underlying mechanism of allometric scaling in plants.

Optimal experimental designs for estimating genetic and non-genetic effects underlying infectious disease transmission

BackgroundThe spread of infectious diseases in populations is controlled by the susceptibility (propensity to acquire infection), infectivity (propensity to transmit infection), and recoverability (propensity to recover/die) of individuals. Estimating genetic risk factors for these three underlying host epidemiological traits can help reduce disease spread through genetic control strategies. Previous studies have identified important ‘disease resistance single nucleotide polymorphisms (SNPs)’, but how these affect the underlying traits is an unresolved question. Recent advances in computational statistics make it now possible to estimate the effects of SNPs on host traits from epidemic data (e.g. infection and/or recovery times of individuals or diagnostic test results). However, little is known about how to effectively design disease transmission experiments or field studies to maximise the precision with which these effects can be estimated.ResultsIn this paper, we develop and validate analytical expressions for the precision of the estimates of SNP effects on the three above host traits for a disease transmission experiment with one or more non-interacting contact groups. Maximising these expressions leads to three distinct ‘experimental’ designs, each specifying a different set of ideal SNP genotype compositions across groups: (a) appropriate for a single contact-group, (b) a multi-group design termed “pure”, and (c) a multi-group design termed “mixed”, where ‘pure’ and ‘mixed’ refer to groupings that consist of individuals with uniformly the same or different SNP genotypes, respectively. Precision estimates for susceptibility and recoverability were found to be less sensitive to the experimental design than estimates for infectivity. Whereas the analytical expressions suggest that the multi-group pure and mixed designs estimate SNP effects with similar precision, the mixed design is preferred because it uses information from naturally-occurring rather than artificial infections. The same design principles apply to estimates of the epidemiological impact of other categorical fixed effects, such as breed, line, family, sex, or vaccination status. Estimation of SNP effect precisions from a given experimental setup is implemented in an online software tool SIRE-PC.ConclusionsMethodology was developed to aid the design of disease transmission experiments for estimating the effect of individual SNPs and other categorical variables that underlie host susceptibility, infectivity and recoverability. Designs that maximize the precision of estimates were derived.

SNP-SNP interactions of oncogenic long non-coding RNAs HOTAIR and HOTTIP on gastric cancer susceptibility

Genetic variants within oncogenic long non-coding RNAs HOTAIR and HOTTIP may affect their gene expression levels, thereby modifying genetic susceptibility to gastric cancer (GC). In a hospital-based study in Ardabil—a very high-risk area in North-West Iran, 600 blood samples from 300 GC patients and 300 healthy controls were recruited for genotyping. Seven HOTAIR (i.e., rs17720428, rs7958904, rs1899663, and rs4759314) and HOTTIP (i.e., rs3807598, rs17501292, and rs1859168) ‘tag’ single nucleotide polymorphisms (SNPs) were genotyped by the Infinium HTS platform. The rs17720428, rs7958904, and rs1899663 tagSNPs significantly increased GC risk under dominant models by 1.5-, 1.57-, and 1.5-fold, respectively. The G-C-T-A haplotype of HOTAIR tagSNPs increased the risk of GC by 1.31-fold. No significant association was found between HOTTIP SNPs and the risk of GC. HOTAIR and HOTTIP variants were also not associated with any clinicopathologic characteristics. The SNP-SNP interaction of HOTAIR rs17720428/rs7958904 with HOTTIP rs1859168 was associated with an increased risk of GC (rs17720428 TG-rs1859168 CC, OR = 1.76; rs7958904 GC-rs1859168 CC, OR = 1.85; rs7958904 CC-rs1859168 CC, OR = 1.86). Interestingly, the SNP-SNP interaction of HOTAIR rs1899663 with HOTTIP rs1859168 strongly increased the risk of GC (rs1899663 GT-rs1859168 CC, OR = 4.3; rs1899663 TT-rs1859168 CC, OR = 9.37; rs1899663 TT-rs1859168 CA, OR = 6.59). We showed that the HOTAIR rs17720428, rs7958904, and rs1899663 tagSNPs and their interactions with the HOTTIP rs1859168 polymorphism significantly increased the risk of GC. Specifically, novel SNP-SNP interactions between HOTAIR and HOTTIP tagSNPs have a larger impact than individual SNP effects on GC risk, thereby providing us with valuable information to reveal potential biological mechanisms for developing GC.

The FTO Gene and Diseases: The Role of Genetic Polymorphism, Epigenetic Modifications, and Environmental Factors

The review provides information on the function of the FTO gene (known as the fat mass and obesity-associated gene) and the encoded enzyme, on the functional role of single nucleotide polymorphisms (SNPs) in coding and noncoding gene regions and the range of their competences, and on association of the FTO polymorphisms with diseases and traits. Factors that have modifying effect on the contribution of polymorphisms to the risk of disease development and trait variability are discussed. The FTO gene encodes alpha-ketoglutarate-dependent dioxygenase, which has a wide range of competences (including demethylation of RNA and single-stranded DNA), which are important for the functioning of the body. Nonsynonymous substitutions in the FTO gene lead to the development of orphan autosomal recessive disease (OMIM 612938). In the FTO noncoding regions, a wide range of variants has been detected, including those of regulatory importance (eQTL, sQTL, etc.). The competence of these variants extends to both FTO and neighboring genes (IRX3, IRX5, RPGRIP1L). Intronic polymorphisms of the FTO gene have been found to be associated with a wide range of multifactorial diseases and traits (obesity and related anthropometric traits, lipid metabolism markers, diabetes mellitus (type 2), coronary heart disease, metabolic syndrome, and other diseases). In the overwhelming majority of studies, the same allele variants are classified as risk ones; however, previously established associations of the FTO polymorphisms with diseases (traits) are demonstrated not in all populations. It is demonstrated that the effects of the FTO gene SNPs can be modified by exogenous and endogenous environmental factors, as well as lifestyle (including the type of diet, consumption of certain nutrients and medications, physical activity, etc.). Epigenetic factors (DNA methylation at CpG sites) are also important for regulating the level of FTO expression and the effects of individual SNPs. The accumulated data on the FTO structure and function, as well as the functional role of the encoded enzyme, make this gene attractive from the point of view of developing personalized approaches to healthcare.

Donor genetic backgrounds contribute to the functional heterogeneity of stem cells and clinical outcomes

Stable and sustainable stem cell sources for stem cell‐based therapies are scarce and a key bottleneck for clinical applications. The regenerative potential of stem cells is usually attributed to several allogeneic or even autologous donor‐related factors. Genetic background and epigenetic variations in different individuals may significantly affect the functional heterogeneity of stem cells. Particularly, single‐nucleotide polymorphisms (SNPs) have been implicated in diseases with monogenetic or multifactorial and complex genetic etiologies. However, the possible effects of individual SNPs on donor stem cells remain far from fully elucidated. In this Perspective, we will discuss the roles played by donor genetic traits in the functional heterogeneity of induced pluripotent stem cells, mesenchymal stem cells, and hematopoietic stem cells and their implications for regenerative medicine and therapy.

Assessment of a causal relationship between body mass index and atopic dermatitis

Assessment of a causal relationship between body mass index and atopic dermatitis

Genome-wide association analysis for maize stem Cell Wall-bound Hydroxycinnamates

BackgroundThe structural reinforcement of cell walls by hydroxycinnamates has a significant role in defense against pests and pathogens, but it also interferes with forage digestibility and biofuel production. Elucidation of maize genetic variations that contribute to variation for stem hydroxycinnamate content could simplify breeding for cell wall strengthening by using markers linked to the most favorable genetic variants in marker-assisted selection or genomic selection approaches​.ResultsA genome-wide association study was conducted using a subset of 282 inbred lines from a maize diversity panel to identify single nucleotide polymorphisms (SNPs) associated with stem cell wall hydroxycinnamate content. A total of 5, 8, and 2 SNPs were identified as significantly associated to p-coumarate, ferulate, and total diferulate concentrations, respectively in the maize pith. Attending to particular diferulate isomers, 3, 6, 1 and 2 SNPs were related to 8–O–4 diferulate, 5–5 diferulate, 8–5 diferulate and 8–5 linear diferulate contents, respectively. This study has the advantage of being done with direct biochemical determinations instead of using estimates based on Near-infrared spectroscopy (NIRS) predictions. In addition, novel genomic regions involved in hydroxycinnamate content were found, such as those in bins 1.06 (for FA), 4.01 (for PCA and FA), 5.04 (for FA), 8.05 (for PCA), and 10.03 and 3.06 (for DFAT and some dimers).ConclusionsThe effect of individual SNPs significantly associated with stem hydroxycinnamate content was low, explaining a low percentage of total phenotypic variability (7 to 10%). Nevertheless, we spotlighted new genomic regions associated with the accumulation of cell-wall-bound hydroxycinnamic acids in the maize stem, and genes involved in cell wall modulation in response to biotic and abiotic stresses have been proposed as candidate genes for those quantitative trait loci (QTL). In addition, we cannot rule out that uncharacterized genes linked to significant SNPs could be implicated in dimer formation and arobinoxylan feruloylation because genes involved in those processes have been poorly characterized. Overall, genomic selection considering markers distributed throughout the whole genome seems to be a more appropriate breeding strategy than marker-assisted selection focused in markers linked to QTL.

Genetic Variant Set-Based Tests Using the Generalized Berk–Jones Statistic With Application to a Genome-Wide Association Study of Breast Cancer

Studying the effects of groups of single nucleotide polymorphisms (SNPs), as in a gene, genetic pathway, or network, can provide novel insight into complex diseases such as breast cancer, uncovering new genetic associations and augmenting the information that can be gleaned from studying SNPs individually. Common challenges in set-based genetic association testing include weak effect sizes, correlation between SNPs in a SNP-set, and scarcity of signals, with individual SNP effects often ranging from extremely sparse to moderately sparse in number. Motivated by these challenges, we propose the Generalized Berk–Jones (GBJ) test for the association between a SNP-set and outcome. The GBJ extends the Berk–Jones statistic by accounting for correlation among SNPs, and it provides advantages over the Generalized Higher Criticism test when signals in a SNP-set are moderately sparse. We also provide an analytic p-value calculation for SNP-sets of any finite size, and we develop an omnibus statistic that is robust to the degree of signal sparsity. An additional advantage of our work is the ability to conduct inference using individual SNP summary statistics from a genome-wide association study (GWAS). We evaluate the finite sample performance of the GBJ through simulation and apply the method to identify breast cancer risk genes in a GWAS conducted by the Cancer Genetic Markers of Susceptibility Consortium. Our results suggest evidence of association between FGFR2 and breast cancer and also identify other potential susceptibility genes, complementing conventional SNP-level analysis. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Identity informative SNP associations in the UK Biobank

Single nucleotide polymorphisms (SNPs) are amenable to genotyping DNA from degraded, inhibited, and/or ancient substrates due to their relatively small amplicon size. Though they have clear advantages over traditional short tandem repeat (STR) typing for specific casework scenarios, the advances in massively parallel sequencing (MPS) have drastically increased the utility of this marker type. The biallelic nature of SNPs makes them individually less informative than STRs due to limited heterozygosity; however, in sufficiently large multiplexes, identity informative SNPs (iiSNPs) may produce combined random match probabilities comparable to STR typing. Multiple MPS library preparation kits now include iiSNPs and similar to STRs, these loci have been rigorously characterized during multiplex development. The relative accessibility of genome-wide association study (GWAS) summary statistics enables re-investigation of forensically relevant targets in high-quality datasets. Here, 4085 GWASs from the UK Biobank European datasets (UKB; 787 ≤ N ≤ 361,194) were mined for iiSNPs typed by the ForenSeq DNA Signature Prep Kit (Verogen). Seven iiSNPs had genome-wide association (p ≤ 5 × 10−8) with 17 phenotypes in UKB Europeans. Most notably, these relationships involve two outwardly visible characteristics: standing height (rs907100; β = 0.011, p = 1.35 × 10-10) and hair/balding patterns (rs2399332; β = −0.009, p = 3.83 × 10−8). The remaining associations involve red blood cell characteristics and measures of lung function. Though these traits are highly polygenic and the individual SNP effects described here have been refuted empirically, we describe the importance and ease of exploring high-quality, freely accessible data to continuously and robustly characterize new and existing forensically relevant loci.

FADS and PPARG2 Single Nucleotide Polymorphisms are Associated with Plasma Lipids in 9-Mo-Old Infants

Dietary intake of polyunsaturated fatty acids (PUFAs), e.g., linoleic acid and n-3 (ω-3) long-chain PUFAs, has been shown in adults to affect plasma cholesterol and triglycerides (TGs), respectively. Little is known about the effects of PUFAs on plasma lipids in early life. The aim of this study was to explore the associations between plasma concentrations of total, LDL, and HDL cholesterol and TGs in infants and 2 single nucleotide polymorphisms (SNPs) in the fatty acid desaturase genes (FADS) oppositely associated with docosahexaenoic acid (rs1535 and rs174448) and potential effect modification by a functional peroxisome proliferator-activated receptor-γ2 gene variant (PPARG2 Pro12Ala). In 9-mo-old infants (n=561) from 3 Danish cohorts, we analyzed associations between plasma lipids, erythrocyte PUFAs, and FADS SNPs, and interactions with PPARG2 Pro12Ala genotype, by multiple linear regression. We also examined potential effect modification by breastfeeding, as 46% of the infants were still being breastfed. Minor allele carriage of rs174448 was associated with lower total cholesterol (difference: -0.22 mmol/L; 95% CI: -0.37, -0.06 mmol/L; P=0.006) and LDL cholesterol (difference: -0.15 mmol/L; 95% CI: -0.29, -0.01 mmol/L; P=0.035), but no associations were observed with TGs or for rs1535. Minor allele carriage of both FADS SNPs was associated with 1 SD lower HDL cholesterol, but only in currently breastfed infants (rs174448×breastfeeding, P=0.080; rs1535×breastfeeding, P=0.030) and PPARG2 minor allele carriers (rs174448×PPARG2, P=0.001; rs1535×PPARG2, P=0.004). Erythrocyte arachidonic acid and eicosapentaenoic acid were inversely associated with LDL cholesterol [estimated effect (β): -0.3 mmol/L; 95% CI: -0.06, -0.00 mmol/L per percentage of fatty acids (FA%); P=0.035] and TGs (β: -0.23 mmol/L; 95% CI: -0.41, -0.05 mmol/L per FA%; P=0.015), respectively. The observed associations with FADS variants indicate that PUFAs are involved in plasma lipid regulation in 9-mo-old infants. Observed FADS SNP differences and interactions with breastfeeding and PPARG2 warrant additional studies to explore the effects of individual FADS SNPs on PUFA status and potential genetic modification of dietary PUFA effects.

H19 gene polymorphisms and neuroblastoma susceptibility in Chinese children: a six-center case-control study.

Neuroblastoma is the most common seen solid tumor in children less than one year old. Given that polymorphisms in the lncRNA H19 gene are observed in several types of human malignancies, there likely to be similar events that contribute to the pathogenesis of neuroblastoma. We hypothesize that single nucleotide polymorphisms (SNPs) in the H19 gene might predispose to neuroblastoma. Here, we genotyped three SNPs (rs2839698 G>A, rs3024270 C>G, rs217727 G>A) from H19 gene in a Chinese population (700 subjects with neuroblastoma and 1516 control subjects) enrolled from six hospitals and examined the effect of individual and combined SNPs on the risk of neuroblastoma. Odds ratios (ORs) and 95% confidence intervals (CIs) calculated from logistic regression were adopted to assess such association, adjusted for age and gender. Among them, 700 controls and 1514 cases were successfully genotyped. None of these three SNPs were found to be relevant to the risk of neuroblastoma, either in overall analysis or stratification analysis. Findings from this study excluded the participation of lncRNA H19 gene SNPs in the risk of neuroblastoma. More independent case-control studies are encouraged to better elucidate this relationship.

POWERFUL TEST BASED ON CONDITIONAL EFFECTS FOR GENOME-WIDE SCREENING.

This paper considers testing procedures for screening large genome-wide data, where we examine hundreds of thousands of genetic variants, e.g., single nucleotide polymorphisms (SNP), on a quantitative phenotype. We screen the whole genome by SNP sets and propose a new test that is based on conditional effects from multiple SNPs. The test statistic is developed for weak genetic effects and incorporates correlations among genetic variables, which may be very high due to linkage disequilibrium. The limiting null distribution of the test statistic and the power of the test are derived. Under appropriate conditions, the test is shown to be more powerful than the minimum p-value method, which is based on marginal SNP effects and is the most commonly used method in genome-wide screening. The proposed test is also compared with other existing methods, including the Higher Criticism (HC) test and the sequence kernel association test (SKAT), through simulations and analysis of a real genome data set. For typical genome-wide data, where effects of individual SNPs are weak and correlations among SNPs are high, the proposed test is more advantageous and clearly outperforms the other methods in the literature.

Differential effect of ABCB1 haplotypes on promoter activity.

Promoter single-nucleotide polymorphisms (SNPs) of the ABCB1 gene, encoding the placental efflux transporter P-glycoprotein, can affect its expression and alter xenobiotic transfer from the maternal to the fetal circulation. Because SNPs are arranged in specific combinations as defined haplotypes, the aims of this study were to: (i) determine the placental haplotype structure of the ABCB1 promoter and (ii) determine the differential effect of these haplotypes on placental ABCB1 promoter activity. DNA samples from 100 healthy placentas were PCR-amplified and sequenced to identify existing SNPs in the proximal ABCB1 promoter. The haplotype structure encompassing these SNPs was inferred by PHASE analysis. Luciferase reporter constructs representing these haplotypes were generated and transfected into human placental 3A cells and their effect on ABCB1 promoter activity was determined using a dual-luciferase assay. We identified 12 ABCB1 promoter SNPs. These SNPs were predicted by PHASE to segregate into 28 haplotypes with frequencies ranging between 0.019 and 0.88. We found 12 of these haplotypes in our population in addition to two haplotypes not predicted by PHASE. We also generated two haplotypes to determine individual SNP effects for a total of 16 studied. Compared with the ancestral haplotype, three haplotypes significantly up-regulated (107-266% increase; P<0.05), one significantly down-regulated (95.4% decrease; P<0.01), and 12 had no statistically significant effect on ABCB1 promoter activity. Our data show that the effect of SNPs on promoter activity depends on their presence in a specific haplotype. This indicates that haplotypes, rather than individual SNPs, could play a significant role in regulating placental P-glycoprotein expression and affect placental transfer and fetal exposure to xenobiotics.