Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies

Babies born clinically Small- or Large-for-Gestational-Age (SGA or LGA; sex- and gestational age-adjusted birth weight (BW) <10th or >90th percentile, respectively), are at higher risks of complications. SGA and LGA include babies who have experienced environment-related growth-restriction or overgrowth, respectively, and babies who are heritably small or large. However, the relative proportions within each group are unclear. We assessed the extent to which common genetic variants underlying variation in birth weight influence the probability of being SGA or LGA. We calculated independent fetal and maternal genetic scores (GS) for BW in 11,951 babies and 5,182 mothers. These scores capture the direct fetal and indirect maternal (via intrauterine environment) genetic contributions to BW, respectively. We also calculated maternal fasting glucose (FG) and systolic blood pressure (SBP) GS. We tested associations between each GS and probability of SGA or LGA. For the BW GS, we used simulations to assess evidence of deviation from an expected polygenic model. Higher BW GS were strongly associated with lower odds of SGA and higher odds of LGA (ORfetal = 0.75 (0.71,0.80) and 1.32 (1.26,1.39); ORmaternal = 0.81 (0.75,0.88) and 1.17 (1.09,1.25), respectively per 1 decile higher GS). We found evidence that the smallest 3% of babies had a higher BW GS, on average, than expected from their observed birth weight (assuming an additive polygenic model: Pfetal = 0.014, Pmaternal = 0.062). Higher maternal SBP GS was associated with higher odds of SGA P = 0.005. We conclude that common genetic variants contribute to risk of SGA and LGA, but that additional factors become more important for risk of SGA in the smallest 3% of babies.

A New Polygenic Model for Nonfamilial Colorectal Cancer Inheritance Based on the Genetic Architecture of the Azoxymethane-Induced Mouse Model

The azoxymethane model of colorectal cancer (CRC) was used to gain insights into the genetic heterogeneity of nonfamilial CRC. We observed significant differences in susceptibility parameters across 40 mouse inbred strains, with 6 new and 18 of 24 previously identified mouse CRC modifier alleles detected using genome-wide association analysis. Tumor incidence varied in F1 as well as intercrosses and backcrosses between resistant and susceptible strains. Analysis of inheritance patterns indicates that resistance to CRC development is inherited as a dominant characteristic genome-wide, and that susceptibility appears to occur in individuals lacking a large-effect, or sufficient numbers of small-effect, polygenic resistance alleles. Our results suggest a new polygenic model for inheritance of nonfamilial CRC, and that genetic studies in humans aimed at identifying individuals with elevated susceptibility should be pursued through the lens of absence of dominant resistance alleles rather than for the presence of susceptibility alleles.

Accuracy of Genomic-Polygenic and Polygenic Breeding Values for Age at First Calving and Milk Yield in Thai Multibreed Dairy Cattle

Single-nucleotide polymorphisms (SNPs) have been used in genomic prediction and shown to increase prediction accuracy and selection responses for economic traits in dairy cattle. The successful report in genomic prediction for improving age at first calving (AFC) and 305-d milk yield (MY) in multibreed dairy population is limited. Therefore, the objective of this research was to compare estimates of variance components, genetic parameters, and prediction accuracies for AFC and MY using a genomic-polygenic model (GPM) and a polygenic model (PM). The AFC and MY records of 9,106 first-lactating multibreed dairy cows, calved between 1991 and 2014, were collected from 1,012 Thai dairy farms. The SNP genotyped individuals were selected from cows that had completed pedigree and phenotypes information. The total genomic DNA samples of 2,661 dairy cattle were genotyped using various GeneSeek Genomic Profiler low-density bead chips (9K, 20K, and 80K). The 2-trait GPM and PM contained herd-year-season and heterosis as fixed effects, and animal additive genetic and residual as random effects. Variance components and genetic parameters were estimated using the procedure of average information-restricted maximum likelihood (AI-REML). Estimates of additive genetic variance components and heritabilities from GPM were higher than PM for AFC and MY. Correlations between AFC and MY were near zero for both models. Mean EBV accuracies were higher for GPM (32.95% for AFC and 38.24% for MY) than for PM (32.65% for AFC, and 32.99% for MY). Mean sire EBV accuracies were higher for GPM (31.35% for AFC and 36.25% for MY) than for PM (28.37% for AFC and 28.80% for MY). Thus, the GPM should be considered the model of choice to increase accuracy of genetic predictions for AFC and MY in the Thai multibreed dairy population.

3255 Association between dopaminergic genetic variants, COMTrs4680 and DRD2rs1076560, and alcohol consumption and reward behaviors in non-dependent drinkers

OBJECTIVES/SPECIFIC AIMS: The objective of this exploratory study is to evaluate the relationship between the individual genetic variants in COMTrs4680 and DRDrs1076560 and relevant alcohol use behaviors (i.e. alcohol consumption and reward processing behaviors) in non-dependent drinkers within experimentally controlled IV-ASA CAIS sessions. The overall goal of this study is to begin gathering data on the influence of individual genetic variants on alcohol consumption and other drinking-related behaviors. This will aid in the creation of a polygenic model of risk for AUD which will provide more insight into how the mesolimbic pathway is affected by alcohol use. METHODS/STUDY POPULATION: Study population: The sample included male and female non-dependent drinkers (N=149). Genotypes for functional polymorphisms in COMT (rs4680) and DRD2 (rs1076560) genes were determined for all subjects from blood samples obtained during screening. Alcohol consumption was assessed using the 90-day Timeline Followback Interviews (TLFB). Study population demographics: Self-reported gender (53.5% identified as male); Self-reported race (61.2% identified as white); Age ranged from 21-46 years old, with 22 years being the mode. Experiment: Free access (open-bar) intravenous alcohol self-administration (IV-ASA) using the computer-assisted alcohol infusion system (CAIS) paradigm; Subjects had the choice of pressing a button ad libitum for IV alcohol infusions during the session, neurobehavioral questionnaires were collected throughout the 2.5-hr alcohol infusion session. Primary outcome measures included: Total Rewards, Peak breath alcohol concentration (BrAC) achieved, and Total Ethanol consumed. Statistical Analyses: Conducted using SPSS IBM Statistics Versions 1.0.0-2482; non-dependent drinkers were organized into two groups based on their genotypes, minor allele carriers and major allele homozygotes. Outcome measures were compared between genotype groups using analysis of variance or non-parametric Mann-Whitney U-test as appropriate. RESULTS/ANTICIPATED RESULTS: -We expect the genetic makeup of the sample to be reflective of larger genome samples that are publically available (e.g. e!Ensembl) - Initial analysis for COMTrs4680 did not reveal significant effects on IV-ASA measures. Specifically, the majo DISCUSSION/SIGNIFICANCE OF IMPACT: Alcohol Use Disorder (AUD) affects millions of men and women globally. The heterogeneity within AUD individuals has made it difficult to identify biological and/or psychological factors that could be targeted for the development of treatments. By using the human laboratory model of free access IV-ASA, this study evaluated the relationship between dopaminergic genetic variants, COMTrs4680 and DRDrs1076560, and alcohol consumption in non-dependent drinkers within a controlled experimental environment. This study will begin to evaluate genetic and behavioral data that can be used to create a polygenic model of risk for AUD, which will provide more insight as to how the mesolimbic reward pathway is affected by alcohol use and contributes to risk for AUD.

Does thinner right entorhinal cortex underlie genetic liability to cannabis use?

BackgroundAlthough alterations in medial temporal lobe structures have been previously associated with use of cannabis, one of the most widely used illicit drugs, whether such alterations are a cause or effect of cannabis use has been unclear.MethodsIn this cross-sectional observational study involving 404 twins/siblings, we have compared cortical thickness and surface area between groups of gender-matched sibling-pairs (concordant cannabis unexposed, concordant exposed and discordant for cannabis exposure) using permutation tests after controlling for potential confounds. Bi-variate polygenic model was used to assess the genetic and environmental contributions underlying cortical morphological phenotypes and frequency of cannabis use.ResultsCortical thickness of the right entorhinal cortex was significantly lower in the concordant exposed siblings compared to both discordant unexposed and discordant exposed groups [false discovery rate (FDR)-corrected, q < 0.05]. The association between the right entorhinal cortex thickness and frequency of cannabis use is due to the contribution of significant shared additive genetic (ρg = −0.19 ± 0.08; p = 0.02) factors but not unique environment (ρe = 0.05 ± 0.09; p = 0.53). Significantly lower surface area of the right entorhinal cortex in discordant exposed group compared with the discordant unexposed group furnishes preliminary evidence in support of causal effect of cannabis use (FDR-corrected, q < 0.05). However, bi-variate polygenic model-based analysis did not show any significant effect.ConclusionsShared genetic liability may underlie the association between cannabis exposure and thinner right entorhinal cortex. Prospective longitudinal studies are necessary to definitively disentangle the cause–effect relationships of cannabis use.